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19 pages, 2845 KiB  
Article
Enhanced Tribological Performance of Melamine Long-Chain Alcohol Esters in High-Temperature Boundary Lubrication
by Jingchun Zhang, Wenjing Hu and Jiusheng Li
Lubricants 2025, 13(3), 114; https://doi.org/10.3390/lubricants13030114 (registering DOI) - 6 Mar 2025
Abstract
The requirement to improve energy efficiency is constantly driving the development of high-performance and eco-friendly friction modifiers (FMs). Herein, two innovative sulfur- and phosphorus-free melamine long-chain alcohol esters (Dodec-EG-CC and Dodec-CC) are reported as novel organic friction modifiers (OFMs). Over a wide temperature [...] Read more.
The requirement to improve energy efficiency is constantly driving the development of high-performance and eco-friendly friction modifiers (FMs). Herein, two innovative sulfur- and phosphorus-free melamine long-chain alcohol esters (Dodec-EG-CC and Dodec-CC) are reported as novel organic friction modifiers (OFMs). Over a wide temperature range of 100 °C to 200 °C, the synthesized melamine long-chain alcohol esters, which have exceptional thermal stability, dramatically lessen wear and friction of PAO4 base oil. Dodec-EG-CC particularly reduces friction by up to 50% and wear rate by approximately 92% within this temperature range. Detailed studies of the tribological properties at elevated temperatures demonstrate that the synergistic effect of the melamine structural unit coupled with ester groups significantly enhances adsorption properties of additives on metal surfaces, improving adsorption strength and lubricating film stability. The adsorption of additives on the metal surfaces is further confirmed by surface analysis and adsorption energy calculation, which serve as a key parameter for characterizing the binding strength between molecules and surfaces. These findings demonstrate the potential of the designed triazine-based derivatives, especially Dodec-EG-CC, as OFMs in effectively reducing friction losses in motor vehicle engines. This highlights their significant potential for industrial applications in improving energy efficiency and extending engine lifespan. These in-depth studies not only provide valuable insights for the molecular structure design of OFMs, but also advances the development of sustainable lubrication technologies. Full article
(This article belongs to the Special Issue Novel Lubricant Additives in 2025)
14 pages, 1416 KiB  
Article
Measurement of Wheel Skidding on Racing Wheelchairs
by Nolwenn Poquerusse, Arnaud Hays, Aurélie Cortial, Opale Vigié, Ilona Alberca, Mathieu Deves, Lorian Honnorat, Safiya Noury, Bruno Watier and Arnaud Faupin
Methods Protoc. 2025, 8(2), 28; https://doi.org/10.3390/mps8020028 - 6 Mar 2025
Abstract
In the context of wheelchair racing, research primarily focuses on studying wheelchair ergonomics and determining kinematic, kinetic, and rolling resistance variables. One factor identified as influencing athletes’ performance is wheel skidding on the ground, a parameter complementary to rolling resistance. The objective of [...] Read more.
In the context of wheelchair racing, research primarily focuses on studying wheelchair ergonomics and determining kinematic, kinetic, and rolling resistance variables. One factor identified as influencing athletes’ performance is wheel skidding on the ground, a parameter complementary to rolling resistance. The objective of this study, therefore, is to identify, within a laboratory setting, the parameters that influence the risk of skidding in racing wheelchairs by measuring skidding torque. The ultimate goal is to enhance athletes’ performance by optimizing the interaction between the athlete and their wheelchair, and the wheelchair and the environment. In this perspective, four parameters were examined: the type of tubular, the camber angle, the tire pressure, and the load applied to the wheel using a skidometer. This tool characterizes a tire’s grip on a surface by measuring torques. The aim is to develop a system for classifying tire grip on dry athletics track at ambient temperature. The findings revealed that only the effects of load and tubular type had a significant impact on the torque values obtained. The tire that minimized the risk of skidding, among all tested combinations, is the Vittoria Pista Speed 23–28″. Furthermore, as the mass applied to the wheel increases, so do the resulting torques. This implies that a heavier athlete would require a greater force to be applied to the hand rim for the tire to skid. However, it was also demonstrated that the risk of skidding in a racing wheelchair is unlikely, as the torques obtained were over a range of 90 to 190 Nm. These values far exceed those typically exerted by para-athletes, which are a maximum of 60 Nm. The long-term goal would be to adjust the mode of torque application on the wheel using the skidometer for a more realistic field approach. Full article
(This article belongs to the Section Public Health Research)
23 pages, 2578 KiB  
Article
The Significance of the Sorption Isotherm on the Simulated Performance of Grain Driers
by Graham R. Thorpe
Appl. Sci. 2025, 15(5), 2871; https://doi.org/10.3390/app15052871 - 6 Mar 2025
Abstract
Sorption isotherms enable postharvest technologists to estimate the degree and rate of drying of agricultural produce. They are also useful in the design and operation of desiccant systems that are used to condition air. However, the published data on sorption isotherms contain several [...] Read more.
Sorption isotherms enable postharvest technologists to estimate the degree and rate of drying of agricultural produce. They are also useful in the design and operation of desiccant systems that are used to condition air. However, the published data on sorption isotherms contain several inconsistencies. For example, under the conditions considered in this work, it is shown that the widely cited Chung–Pfost isotherm predicts moisture contents of canola that are less than zero as the relative humidity tends to zero. Furthermore, it is shown that a long-established form of empirical expression appears to grossly overestimate the differential heat of wetting, hence the integral heat of wetting of canola. In this work, algebraic expressions are derived that enable the relationship between the forms of isotherm equations on the speed of drying to be calculated. Prima facie, it is anticipated the heat of adsorption will augment the speed of temperature waves through beds of drying canola. However, it is found that this may not be the case. Anomalies in published isotherms for agricultural produce reinforce the need for accurate psychometric data to be measured over a wide range of temperatures and relative humidities. Full article
(This article belongs to the Section Agricultural Science and Technology)
Show Figures

Figure 1

Figure 1
<p>Velocities of the drying, AP, and temperature, PB, fronts through a bed of canola. State A represents the system in equilibrium with the incoming air, and B is the system at its initial state prior to the initiation of drying. The drying fronts are separated by the plateau state, P.</p>
Full article ">Figure 2
<p>The states of the air and grain in the system portrayed on a psychrometric chart. As indicated in <a href="#applsci-15-02871-f001" class="html-fig">Figure 1</a>, states A and B are, respectively, those of the air at the entrance to the drier and at the initial conditions. The plateau state is denoted by P. The dotted lines between AP and PB indicate the discontinuities across the drying and heating fronts, respectively. The grain moistures are depicted in the range of 0.02 to 0.11.</p>
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<p>Air that enters an element of length <math display="inline"><semantics> <mrow> <mo>∆</mo> <mi>x</mi> </mrow> </semantics></math>, has a mean intergranular velocity <math display="inline"><semantics> <mrow> <mi>v</mi> </mrow> </semantics></math>, density <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>ρ</mi> </mrow> <mrow> <mi>a</mi> </mrow> </msub> </mrow> </semantics></math>, and humidity <math display="inline"><semantics> <mrow> <mi>w</mi> </mrow> </semantics></math>. It leaves with a velocity <math display="inline"><semantics> <mrow> <mi>v</mi> <mo>+</mo> <mo>∆</mo> <mi>v</mi> </mrow> </semantics></math>, density <math display="inline"><semantics> <mrow> <mo> </mo> <msub> <mrow> <mi>ρ</mi> </mrow> <mrow> <mi>a</mi> </mrow> </msub> <mo>+</mo> <mo>∆</mo> <msub> <mrow> <mi>ρ</mi> </mrow> <mrow> <mi>a</mi> </mrow> </msub> </mrow> </semantics></math>, and humidity <math display="inline"><semantics> <mrow> <mi>w</mi> <mo>+</mo> <mo>∆</mo> <mi>w</mi> </mrow> </semantics></math>. Initially, the moisture content of canola is in equilibrium with the air in the latter state, i.e., <math display="inline"><semantics> <mrow> <mi>W</mi> <mo>+</mo> <mo>∆</mo> <mi>W</mi> </mrow> </semantics></math>. After a time <math display="inline"><semantics> <mrow> <mo>∆</mo> <mi>t</mi> </mrow> </semantics></math>, all of the canola is in equilibrium with the incoming air, and it assumes a moisture content <math display="inline"><semantics> <mrow> <mi>W</mi> </mrow> </semantics></math>. The void fraction of the porous medium, canola, is <math display="inline"><semantics> <mrow> <mi>ε</mi> </mrow> </semantics></math>.</p>
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<p>The Chung–Pfost (C-P), Henderson (HEN-GAZ), Hunter, Halsey, and Oswin isotherms are fitted to the experimental data presented by Gazor [<a href="#B8-applsci-15-02871" class="html-bibr">8</a>], whilst the remaining Henderson isotherm (HEN-SOK) is fitted to data presented by Sokhansanj et al. [<a href="#B18-applsci-15-02871" class="html-bibr">18</a>]. The Hunter and Oswin isotherms are almost coincident in the range of relative humidities depicted in the figure. Note that relative humidity is expressed on a fractional basis, hence <span class="html-italic">r</span> = 0.1 is equivalent to <span class="html-italic">rh</span> = 10% on a percentage basis.</p>
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<p>The isotherms predicted by the equations proposed by Henderson, using Sokansanj et al.’s [<a href="#B18-applsci-15-02871" class="html-bibr">18</a>] parameters, Hunter, Halsey, and Oswin. Note that the Henderson and Chung–Pfost equations based on Gazor’s [<a href="#B8-applsci-15-02871" class="html-bibr">8</a>] data are omitted because they are almost indistinguishable from the Henderson isotherm fitted to Sokhansanj et al.’s [<a href="#B18-applsci-15-02871" class="html-bibr">18</a>] data.</p>
Full article ">Figure 6
<p>The contrast between values of <math display="inline"><semantics> <mrow> <mrow> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>s</mi> </mrow> </msub> </mrow> <mo>/</mo> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>v</mi> </mrow> </msub> </mrow> </mrow> </mrow> </semantics></math> predicted by the equation employed by Cenkowski [<a href="#B14-applsci-15-02871" class="html-bibr">14</a>], Equation (29), and the Henderson isotherm based on Sokhansanj et al.’s (1986) [<a href="#B18-applsci-15-02871" class="html-bibr">18</a>] data.</p>
Full article ">Figure 7
<p>Values of <math display="inline"><semantics> <mrow> <mrow> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>s</mi> </mrow> </msub> </mrow> <mo>/</mo> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>v</mi> </mrow> </msub> </mrow> </mrow> </mrow> </semantics></math> calculated using the Clausius–Clapeyron equation using Henderson isotherm using Sokhansanj et al.’s [<a href="#B18-applsci-15-02871" class="html-bibr">18</a>] (HEN-SOK) and Gazor’s [<a href="#B8-applsci-15-02871" class="html-bibr">8</a>] (HEN-GAZ) data; Hunter’s and Halsey’s isotherms predict that <math display="inline"><semantics> <mrow> <mrow> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>s</mi> </mrow> </msub> </mrow> <mo>/</mo> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>v</mi> </mrow> </msub> <mo>→</mo> <mo>∞</mo> </mrow> </mrow> </mrow> </semantics></math> as <math display="inline"><semantics> <mrow> <mi>W</mi> <mo>→</mo> <mn>0</mn> </mrow> </semantics></math>.</p>
Full article ">Figure 8
<p>The integral <math display="inline"><semantics> <mrow> <mi>I</mi> </mrow> </semantics></math>, defined as <math display="inline"><semantics> <mrow> <mi>I</mi> <mo>=</mo> <mrow> <mrow> <msub> <mrow> <mi>H</mi> </mrow> <mrow> <mi>W</mi> </mrow> </msub> </mrow> <mo>/</mo> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>v</mi> </mrow> </msub> </mrow> </mrow> </mrow> </semantics></math>, as a function of grain moisture content, <math display="inline"><semantics> <mrow> <mi>W</mi> </mrow> </semantics></math>. It is observed that the empirically based method, Equation (31), produces lower values than Equation (34), which arises when the Clausius–Clapeyron equation is applied with the Henderson isotherm which embodies the empirical constants proposed by Sokhansanj et al. [<a href="#B18-applsci-15-02871" class="html-bibr">18</a>].</p>
Full article ">Figure 9
<p>The integral <math display="inline"><semantics> <mrow> <mi>I</mi> </mrow> </semantics></math> as a function of grain moisture content when the temperature is 30 °C. The values are consistent with integrating <math display="inline"><semantics> <mrow> <mn>1</mn> <mo>−</mo> <mrow> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>s</mi> </mrow> </msub> </mrow> <mo>/</mo> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>v</mi> </mrow> </msub> </mrow> </mrow> </mrow> </semantics></math>, as may be gleaned by observing the results given in <a href="#applsci-15-02871-f007" class="html-fig">Figure 7</a>. Halsey’s equation does not yield a finite solution.</p>
Full article ">Figure 10
<p>The passage of temperature, moisture content, and humidity fronts through a bed of canola ventilated with an air flow rate, <math display="inline"><semantics> <mrow> <mi>G</mi> </mrow> </semantics></math>, of 1 kg/(s.m<sup>2</sup>). Henderson’s isotherm is invoked using the parameters given by Sokhansanj et al. [<a href="#B18-applsci-15-02871" class="html-bibr">18</a>]. When the empirical expression, Equation (29) HEN-EQN (29), is used to predict <math display="inline"><semantics> <mrow> <mrow> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>s</mi> </mrow> </msub> </mrow> <mo>/</mo> <mrow> <msub> <mrow> <mi>h</mi> </mrow> <mrow> <mi>v</mi> </mrow> </msub> </mrow> </mrow> </mrow> </semantics></math>, the velocity of the drying wave is lower than when the Clausius–Clapeyron equation, Equation (12) HEN-C-C, is employed.</p>
Full article ">Figure 11
<p>The flows of enthalpy through an element of length <math display="inline"><semantics> <mrow> <mo>∆</mo> <mi>x</mi> </mrow> </semantics></math>. Initially, the grains are in equilibrium with the air leaving the element, but after a time <math display="inline"><semantics> <mrow> <mo>∆</mo> <mi>t</mi> </mrow> </semantics></math>, the initial sensible and latent heat contents of the solids are in equilibrium with the entering air. The above system enables us to observe how the sorption isotherms determine the velocities of the drying and heating waves.</p>
Full article ">Figure 12
<p>Air in state A enters a bed of canola initially in state B. When Equation (12) is used to calculate the plateau state, P, Equation (29) results in lower values of the temperature and humidity of the air than when the Clausius–Clapeyron Equation (12) is invoked. Grain moisture contents of 0.02, 0.05, 0.08, and 0.11 are shown on the psychrometric chart.</p>
Full article ">
22 pages, 1744 KiB  
Article
Hybrid Long-Range–5G Multi-Sensor Platform for Predictive Maintenance for Ventilation Systems
by Praveen Mohanram and Robert H. Schmitt
Electronics 2025, 14(5), 1055; https://doi.org/10.3390/electronics14051055 - 6 Mar 2025
Abstract
In this paper, we present a multi-sensor platform for predictive maintenance featuring hybrid long-range (LoRa) and 5G connectivity. This hybrid approach combines LoRa’s low-power transmission for energy efficiency with 5G’s real-time data capabilities. The hardware platform integrates multiple sensors to monitor machine health [...] Read more.
In this paper, we present a multi-sensor platform for predictive maintenance featuring hybrid long-range (LoRa) and 5G connectivity. This hybrid approach combines LoRa’s low-power transmission for energy efficiency with 5G’s real-time data capabilities. The hardware platform integrates multiple sensors to monitor machine health parameters, with data analyzed on the device using pre-trained AI models to assess the machine’s condition. Inferences are transmitted via LoRa to the operator for maintenance scheduling, while a cloud application tracks and stores sensor data. Periodic sensor data bursts are sent via 5G to update the AI model, which is then delivered back to the platform through over-the-air (OTA) updates. We provide a comprehensive overview of the hardware architecture, along with an in-depth analysis of the data generated by the sensors, and its processing methodology. However, the data analysis and the software for ventilation control and its predictive capabilities are not the focus of this paper and are not presented. Full article
(This article belongs to the Special Issue 5G Mobile Telecommunication Systems and Recent Advances)
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Figure 1

Figure 1
<p>Hybrid LoRa and 5G predictive maintenance system of a ventilation unit.</p>
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<p>Predictive maintenance system.</p>
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<p>Hardware of the realized hybrid multi-sensor platform.</p>
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<p>Software architecture of the hybrid LoRa and 5G multi-sensor platform.</p>
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<p>Power measurement hardware as used for the validation.</p>
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<p>Data flow timing diagram.</p>
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<p>Portenta H7 power consumption.</p>
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13 pages, 530 KiB  
Review
Optimizing Conservative Management of Groin Pain in Athletes: Insights from a Narrative Review
by Roberto Tedeschi, Federica Giorgi, Daniela Platano, Lisa Berti and Danilo Donati
Life 2025, 15(3), 411; https://doi.org/10.3390/life15030411 - 6 Mar 2025
Abstract
Background: Groin pain is a complex and multifactorial condition commonly observed in athletes, often impairing performance and quality of life. While conservative treatments are the first-line approach, the variability in intervention protocols and inconsistent evidence necessitate a comprehensive synthesis of current knowledge. Methods: [...] Read more.
Background: Groin pain is a complex and multifactorial condition commonly observed in athletes, often impairing performance and quality of life. While conservative treatments are the first-line approach, the variability in intervention protocols and inconsistent evidence necessitate a comprehensive synthesis of current knowledge. Methods: This narrative review analyzed the available literature on conservative management of groin pain in athletes. A systematic search was conducted across the MEDLINE, Cochrane CENTRAL, Scopus, PEDro, and Web of Science databases. Studies focusing on pain reduction, functional recovery, return-to-sport outcomes, and prevention strategies were included. Findings were synthesized to evaluate the efficacy of conservative interventions and identify gaps in the evidence. Results: Conservative treatments, particularly active rehabilitation and multimodal therapy, demonstrated significant efficacy in reducing pain (50–80%) and improving function, as measured by tools such as the HAGOS score. Return-to-sport rates ranged from 70% to 90%, depending on intervention type and adherence. Screening tools, including the adductor squeeze test, were effective in predicting and preventing groin injuries. However, variability in methodologies, small sample sizes, and a lack of long-term follow-up limited the generalizability of the findings. Conclusions: Conservative management remains a cornerstone for treating groin pain in athletes, offering effective outcomes for pain reduction, functional recovery, and injury prevention. However, standardized protocols and high-quality research are needed to enhance clinical guidance and optimize patient outcomes. Full article
(This article belongs to the Section Physiology and Pathology)
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Figure 1
<p>Preferred reporting items for systematic reviews and meta-analyses 2020 (PRISMA) flow diagram.</p>
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10 pages, 868 KiB  
Article
Outcomes and Predictive Factors of I-125 Plaque Therapy for Refractory Retinoblastoma
by Yacoub A. Yousef, Farah Halawa, Mona Mohammad, Lama Al-Fahoum, Rama Soudi, Mustafa Mehyar, Reem AlJabari, Hadeel Halalsheh, Ibrahim AlNawaiseh and Imad Jaradat
J. Clin. Med. 2025, 14(5), 1778; https://doi.org/10.3390/jcm14051778 - 6 Mar 2025
Abstract
Objective: This study aimed to evaluate the outcomes and predictive factors of I-125 radioactive plaque therapy for recurrent and refractory retinoblastoma (Rb) cases that failed primary systemic chemotherapy and focal therapies. Methods: A retrospective study of 20 eyes with intraocular Rb [...] Read more.
Objective: This study aimed to evaluate the outcomes and predictive factors of I-125 radioactive plaque therapy for recurrent and refractory retinoblastoma (Rb) cases that failed primary systemic chemotherapy and focal therapies. Methods: A retrospective study of 20 eyes with intraocular Rb treated with I-125 radioactive plaque therapy (Apex dose 45 Gy) from 2013 to 2023 was conducted. Data on tumor characteristics, treatments, and outcomes were collected over a follow-up period of at least one year. Results: There were 11 (55%) males and 8 (40%) patients who had bilateral disease. All 20 treated eyes (100%) showed initial tumor regression, while long-term tumor control and eye salvage were achieved in 14 eyes (70%). Six eyes (30%) experienced uncontrollable tumor recurrence after a mean of 6 months (range: 3–12 months) after plaque therapy. Recurrence included main tumor activity in six eyes and additional resistant vitreous seeds in two of them. Poor predictive factors for eye salvage included Group D at diagnosis (p = 0.044), active vitreous seeds at the time of plaque therapy ((p = 0.045), tumor thickness >5.0 mm (p = 0.045), and tumor base dimension >12 mm (p = 0.023). Post-plaque complications included cataracts in seven eyes (35%), tumor hemorrhage in six eyes (30%), retinal detachment in four eyes (20%), radiation retinopathy in three eyes (15%), and neovascular glaucoma in one eye (5%). Five (83%) of those with tumor hemorrhage had plaque surgery performed within less than 6 months of the last cycle of systemic chemotherapy. At a mean follow-up of 36 months (range: 12–96 months), five eyes (25%) were enucleated, and high-risk pathological features were identified in three eyes, including post-laminar optic nerve infiltration (one eye) and massive choroidal invasion (two eyes). All patients were alive and free of metastasis except one patient (5%) whose parents refused enucleation and came back with extra-scleral extension and bone marrow metastasis and eventually passed away. Conclusions: I-125 radioactive plaque therapy is a valuable salvage treatment for recurrent and refractory retinoblastoma, achieving tumor control and eye salvage in 70% of cases with an acceptable safety profile. However, the observed recurrence rate (30%) at an apex dose of 45 Gy suggests a need for dose optimization and individualized treatment strategies. Identifying high-risk features, such as Group D disease, active vitreous seeds, and larger tumors, is crucial for patient selection and outcome prediction. Future research should explore alternative dosing strategies, combination therapies, and improved predictive models to enhance long-term tumor control while minimizing complications. Full article
(This article belongs to the Section Ophthalmology)
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Figure 1

Figure 1
<p>Clinical course of a 2-year-old girl with left unilateral retinoblastoma (Group D). (<b>A</b>) Initial presentation showing the tumor before treatment. (<b>B</b>) Complete tumor regression following six cycles of CVE chemotherapy and focal consolidation therapy using Transpupillary Thermotherapy (TTT). (<b>C</b>) Significant tumor recurrence observed three months after the last chemotherapy cycle. (<b>D</b>) Complete tumor regression two months after I-125 radioactive plaque therapy. (<b>E</b>) Sustained tumor regression for an additional two months. (<b>F</b>) Tumor-associated hemorrhage detected six months post-plaque therapy, which resolved gradually without intervention over six months. At two years post-plaque therapy, no tumor activity was detected.</p>
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<p>A 2-year-old single-eye patient was referred after 6 cycles of chemotherapy (VCR/Carbo/VP-16) and 2 cycles of Topotecan/VCR. (<b>A</b>) Active tumor treated with massive TTT and cryotherapy. (<b>B</b>,<b>C</b>) Partial response but residual active tumor unresponsive to cryotherapy. (<b>D</b>) Fundus photo 3 months after I-125 plaque therapy shows excellent tumor response. (<b>E</b>) Recurrent vitreous seeds 3 months after plaque therapy, which was treated successfully with intravitreal melphalan. (<b>F</b>) After 3 years of follow-up, no tumor activity. Dense cataract treated with IOL implantation; vision 20/30.</p>
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20 pages, 5280 KiB  
Article
Commodity Risk and Forecastability of International Stock Returns: The Role of Oil Returns Skewness
by Afees A. Salisu and Rangan Gupta
Risks 2025, 13(3), 49; https://doi.org/10.3390/risks13030049 - 6 Mar 2025
Abstract
This study examines the out-of-sample predictability of expected skewness of oil price returns, which serves as a metric for global future risks, as we show statistically through the association with crises of different nature, for stock returns of 10 (8 advanced plus two [...] Read more.
This study examines the out-of-sample predictability of expected skewness of oil price returns, which serves as a metric for global future risks, as we show statistically through the association with crises of different nature, for stock returns of 10 (8 advanced plus two emerging) countries using long-range monthly data of over a century for each country. Using a distributed lag predictive econometric model, which controls for endogeneity, persistence, and conditional heteroscedasticity, we provide evidence of the strong statistical significance of the predictive impact of the third moment of oil price returns for equity returns for all the countries across various forecast horizons and the length of out-of-sample periods. These findings also hold for the shorter sample periods of 3 other emerging markets: Brazil, China, and Russia. Our findings have important implications for academics, investors, and policymakers. Full article
(This article belongs to the Special Issue Traditional and Emerging Risks in the World and Financial Markets)
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Figure A1

Figure A1
<p>Data Plots. (<b>a</b>): Oil return (skewness)—stock return nexus in the G7 plus Switzerland. (<b>b</b>): Oil return (skewness)—stock return nexus in BRICS—Brazil, Russia, India, China, and South Africa.</p>
Full article ">Figure A1 Cont.
<p>Data Plots. (<b>a</b>): Oil return (skewness)—stock return nexus in the G7 plus Switzerland. (<b>b</b>): Oil return (skewness)—stock return nexus in BRICS—Brazil, Russia, India, China, and South Africa.</p>
Full article ">Figure A1 Cont.
<p>Data Plots. (<b>a</b>): Oil return (skewness)—stock return nexus in the G7 plus Switzerland. (<b>b</b>): Oil return (skewness)—stock return nexus in BRICS—Brazil, Russia, India, China, and South Africa.</p>
Full article ">Figure A1 Cont.
<p>Data Plots. (<b>a</b>): Oil return (skewness)—stock return nexus in the G7 plus Switzerland. (<b>b</b>): Oil return (skewness)—stock return nexus in BRICS—Brazil, Russia, India, China, and South Africa.</p>
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<p>Data Plots. (<b>a</b>): Oil return (skewness)—stock return nexus in the G7 plus Switzerland. (<b>b</b>): Oil return (skewness)—stock return nexus in BRICS—Brazil, Russia, India, China, and South Africa.</p>
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<p>Cumulative sum of squares comparison between the benchmark model and our predictive model.</p>
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<p>Cumulative sum of squares comparison between the benchmark model and our predictive model.</p>
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<p>Cumulative sum of squares comparison between the benchmark model and our predictive model.</p>
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23 pages, 2476 KiB  
Article
A Stochastic Process-Based Approach for Power System Modeling and Simulation: A Case Study on China’s Long-Term Coal-Fired Power Phaseout
by Rui Yang, Wensheng Wang, Chuangye Chang and Zhuoqi Wang
Sustainability 2025, 17(5), 2303; https://doi.org/10.3390/su17052303 - 6 Mar 2025
Abstract
Power systems hold huge potential for emission reduction, which has made the modeling and pathway simulations of their decarbonizing development a subject of widespread interest. However, current studies have not yet provided a useful modeling method that can deliver analytical probabilistic information about [...] Read more.
Power systems hold huge potential for emission reduction, which has made the modeling and pathway simulations of their decarbonizing development a subject of widespread interest. However, current studies have not yet provided a useful modeling method that can deliver analytical probabilistic information about future system behaviors by considering various uncertainty factors. Therefore, this paper proposes a stochastic process-based approach that can provide analytical solutions for the uncertainty ranges, as well as their changing momentum, accumulation, and probabilistic distributions. Quantitative probabilities of certain incidents in power systems can be deduced accordingly, without massive Monte Carlo simulations. A case study on China’s long-term coal-fired power phaseout was conducted to demonstrate the practical use of the proposed approach. By modeling the coal-fired power system at the unit level based on stochastic processes, phaseout pathways are probabilistically simulated with consideration of national power security. Simulations span from 2025 to 2060, presenting results and accumulated uncertainties for annual power amounts, full-process emissions, and carbon efficiencies. Through this modeling and simulation, the probabilities of China’s coal-fired power system achieving carbon peaking by 2030 and carbon neutrality by 2060 are 91.15% and 42.13%, respectively. It is expected that there will remain 442 GW of capacity with 0.18 Gt of carbon emissions in 2060. Full article
(This article belongs to the Section Energy Sustainability)
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Figure 1
<p>The sectional sigmoid function divides units into 3 groups, namely, shutting down, reducing working, and continuing to work. The parameters adopted are <math display="inline"><semantics> <mrow> <mi>τ</mi> <mo>=</mo> <mn>5</mn> </mrow> </semantics></math> and <math display="inline"><semantics> <msub> <mi>u</mi> <mi>l</mi> </msub> </semantics></math>, equal to 50% of the total unit amount.</p>
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<p>The empirical rule for a random variable following <math display="inline"><semantics> <mrow> <mi mathvariant="script">N</mi> <mo>(</mo> <mn>0</mn> <mo>,</mo> <mi>σ</mi> <mo>)</mo> </mrow> </semantics></math>. In actual modeling, the statistical value is regarded as the distribution expectation.</p>
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<p>The annual normalized probability density function of the simulation results of the national power demand, i.e., <math display="inline"><semantics> <mrow> <msub> <mi>D</mi> <mi>T</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>The annual normalized probability density function of the simulation results of the new energy power amount, i.e., <math display="inline"><semantics> <mrow> <msubsup> <mo>∑</mo> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mn>7</mn> </msubsup> <msub> <mi>D</mi> <mrow> <mi>N</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>The annual normalized probability density function of the demand for coal-fired power, i.e., <math display="inline"><semantics> <mrow> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>t</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>. Demand reaching 0 means that coal-fired power is unnecessary (may completely quit) since new energies can meet the national power demand.</p>
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<p>Phaseout path simulation results when the demand scenario is as planned, as <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">F</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>=</mo> <mi mathvariant="double-struck">E</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> </mrow> </semantics></math>, (<b>a</b>) annual unit-level emission, (<b>b</b>) annual full-process emission, (<b>c</b>) annual power amount, (<b>d</b>) emission-power factor, indicating the cleanliness level of coal-fired power.</p>
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<p>Phaseout path simulation results when the demand scenario is over-planned, with <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">F</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>=</mo> <mi mathvariant="double-struck">E</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>+</mo> <mi mathvariant="double-struck">D</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> </mrow> </semantics></math>, (<b>a</b>) annual unit-level emission, (<b>b</b>) annual full-process emission, (<b>c</b>) annual power amount, (<b>d</b>) emission-power factor.</p>
Full article ">Figure 7 Cont.
<p>Phaseout path simulation results when the demand scenario is over-planned, with <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">F</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>=</mo> <mi mathvariant="double-struck">E</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>+</mo> <mi mathvariant="double-struck">D</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> </mrow> </semantics></math>, (<b>a</b>) annual unit-level emission, (<b>b</b>) annual full-process emission, (<b>c</b>) annual power amount, (<b>d</b>) emission-power factor.</p>
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<p>Phaseout path simulation results when the demand scenario is ‘below planned’, with <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">F</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>=</mo> <mi mathvariant="double-struck">E</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>−</mo> <mi mathvariant="double-struck">D</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> </mrow> </semantics></math>, (<b>a</b>) annual unit-level emission, (<b>b</b>) annual full-process emission, (<b>c</b>) annual power amount, (<b>d</b>) emission-power factor.</p>
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<p>The annual unit-level emission results of simulated phaseout paths when the demand is in stochastic process forms, such as <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">F</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>=</mo> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>.</p>
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<p>The full-process emission results of simulated phaseout paths when the demand is in stochastic process forms, as <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">F</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>=</mo> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, (<b>a</b>) annual amount, (<b>b</b>) accumulative amount since 2025.</p>
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<p>The full-process emission results of simulated phaseout paths when the demand is in stochastic process forms, as <math display="inline"><semantics> <mrow> <mi mathvariant="double-struck">F</mi> <mfenced separators="" open="(" close=")"> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mfenced> <mo>=</mo> <msub> <mi>D</mi> <mi>C</mi> </msub> <mrow> <mo>(</mo> <mi>T</mi> <mo>)</mo> </mrow> </mrow> </semantics></math>, (<b>a</b>) annual amount, (<b>b</b>) accumulative amount since 2025.</p>
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<p>The annual probabilities of the coal-fired system completely shutting down, <math display="inline"><semantics> <msub> <mi>P</mi> <mrow> <mi>q</mi> <mi>u</mi> <mi>i</mi> <mi>t</mi> </mrow> </msub> </semantics></math>, and coal-fired emission neutrality, <math display="inline"><semantics> <msub> <mi>P</mi> <mrow> <mi>n</mi> <mi>u</mi> <mi>l</mi> <mi>l</mi> </mrow> </msub> </semantics></math>.</p>
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<p>The long-term power structure in China, as projected by simulated expectations shown in <a href="#sustainability-17-02303-f004" class="html-fig">Figure 4</a> (<b>a</b>) annual amounts and (<b>b</b>) annual percentages.</p>
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25 pages, 11638 KiB  
Article
Geochemical Study of Trace Elements and In Situ S–Pb Isotopes of the Sachakou Pb–Zn Deposit in the Aksai Chin Region, Xinjiang
by Xiaojian Zhao, Nuo Li, Tingbin Fan, Jing Sun, Qinglin Sui, Huishan Zhang, Zhouping Guo, Jianatiguli Wusiman, Kai Weng and Yanjing Chen
Minerals 2025, 15(3), 271; https://doi.org/10.3390/min15030271 - 6 Mar 2025
Viewed by 91
Abstract
The sulfide Pb–Zn deposits in the Aksai Chin region of Xinjiang have long been subject to debate regarding their genetic classification due to the unclear origin of the ore-forming components. This study focuses on the Sachakou Pb–Zn deposit, the most representative deposit in [...] Read more.
The sulfide Pb–Zn deposits in the Aksai Chin region of Xinjiang have long been subject to debate regarding their genetic classification due to the unclear origin of the ore-forming components. This study focuses on the Sachakou Pb–Zn deposit, the most representative deposit in the region, and integrates field investigations, petrographic observations, in situ LA-ICP-MS trace element analysis, and in situ S–Pb isotope analysis. The deposit is hosted within the siliceous rock and silicified limestone of the Lower Jurassic Bagongbulansha Formation, with ore bodies controlled by structural and stratigraphic factors. Three mineralization stages have been identified in the Sachakou deposit: a red–brown sphalerite mineralization stage (S1), a light-brown sphalerite stage (S2), and a galena mineralization stage (S3). The trace elements in sphalerite indicate that the mineralization process is unrelated to magmatic activity. The mineralization temperature, determined using a GGIMFis geothermometer, ranges from 294 °C to 121 °C. The δ34SV-CDT values of sulfides range from −4.93‰ to 1.24‰, suggesting that the Jurassic gypsum layer served as the sulfur source. The lead isotope ratios of 206Pb/204Pb range from 18.308 to 18.395, of 207Pb/204Pb—from 15.669 to 15.731, and of 208Pb/204Pb—from 38.595 to 38.776, indicating that the ore-forming metals were predominantly sourced from the upper crust. Based on geological and geochemical characteristics, the Sachakou Pb–Zn deposit is classified as a sedimentary-hosted epizonogenic hydrothermal deposit. Full article
(This article belongs to the Special Issue Genesis and Evolution of Pb-Zn-Ag Polymetallic Deposits: 2nd Edition)
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Figure 1
<p>Geographical location map (<b>a</b>), tectonic sketch map (<b>b</b>) (modified after Gao et al. [<a href="#B29-minerals-15-00271" class="html-bibr">29</a>]), and geological and mineral resources map (<b>c</b>) (modified after Zhao et al. [<a href="#B16-minerals-15-00271" class="html-bibr">16</a>]) of the Aksai Chin region.</p>
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<p>Simplified geological map of the Sachakou Pb–Zn mining area (modified after Wang et al. [<a href="#B38-minerals-15-00271" class="html-bibr">38</a>]).</p>
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<p>The profile of exploration line 317 in the Sachakou Pb–Zn Mining Area (modified after Wang et al. [<a href="#B38-minerals-15-00271" class="html-bibr">38</a>]).</p>
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<p>Photographs of the Sachakou mining area and typical ore samples. (<b>a</b>) Overview of Pb–Zn ore belt III. (<b>b</b>) Contact boundary between silicified limestone and the silicified and limonitized fracture zone. (<b>c</b>) Banded Pb–Zn ore. (<b>d</b>) Brecciated quartz (S0) cemented by the Pb–Zn ore (S1). (<b>e</b>) Partially oxidized vein-type Pb–Zn ore (S1). (<b>f</b>) Fully oxidized vein-type Pb–Zn ore. (<b>g</b>) Vein-type stibnite ore (S2). (<b>h</b>) Pb–Zn ore (S2) cementing breccias of the Pb–Zn ore (S1) and siliceous rock fragments. (<b>i</b>) Sphalerite vein (S2) crosscutting a sphalerite vein (S1) and the siliceous rock. (<b>j</b>) Contact relationship between the Pb–Zn ore (S2) and the Pb–Zn ore (S3). (<b>k</b>) Vein-type Pb–Zn ore (S2). (<b>l</b>) Brecciated galena ore (S3). Cer—cerussite; Gn—galena; Gyp—gypsum; Lm—limonite; Qz—quartz; Sbn—stibnite; Smt—smithsonite; Sp—sphalerite.</p>
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<p>Photomicrographs and BSE images of ore minerals from the Sachakou Pb–Zn deposit. (<b>a</b>) Rhythmic banded Sp1 coexisting with Qz1. (<b>b</b>) Qz1 coexisting with Gn1 and Sp1. (<b>c</b>) Qz1 coexisting with Py1, Sp1, and Gn1, with smithsonite replacing Sp1 along fractures. (<b>d</b>) Qz1 and Sp1 crosscut by later-stage Qz2 and Sp2. (<b>e</b>) Gn2 filling fractures within Sp2 in the siliceous rock. (<b>f</b>) Sbn1 coexisting with Sp2, with euhedral Py2 developing along the boundary between Sbn1 and the siliceous rock. (<b>g</b>) Anglesite and cerussite replacing the edges of Gn3. (<b>h</b>) Cerussite replacing Gn3 (BSE); (<b>i</b>) Siderite coexisting with Sp3 and Gn3, with cerussite developing along the fractures within siderite and Gn3 (BSE). Ang—anglesite; Cer—cerussite; Gn—galena; Py—pyrite; Qz—quartz; Sd—siderite; Sbn—stibnite; Smt—smithsonite; Sp—sphalerite.</p>
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<p>Mineralization stage division of the Sachakou Pb–Zn deposit.</p>
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<p>Comparison of the sphalerite trace element concentrations using LA-ICP-MS in the Sachakou Pb–Zn deposit.</p>
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<p>Representative time-resolved depth profiles of the sphalerite from the Sachakou Pb–Zn deposit. (<b>a</b>) Flat signals indicating elements mainly hosted in the sphalerite lattice. (<b>b</b>) Abnormal peak signals suggesting the presence of micro-scale mineral inclusions.</p>
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<p>Scatter plot of trace elements in the sphalerite from the Sachakou Pb–Zn deposit. (<b>a</b>) Fe vs. Mn. (<b>b</b>) Fe vs. Co. (<b>c</b>) Fe vs. Ge. (<b>d</b>) Fe vs. Cd. (<b>e</b>) In vs. Sn. (<b>f</b>) Ni vs. Mn. (<b>g</b>) As vs. Ag.</p>
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<p>Histogram of sphalerite mineralization temperatures in the Sachakou Pb–Zn deposit, determined using a GGIMFis geothermometer.</p>
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<p>Sulfur isotope histogram (<b>a</b>) and scatter plot (<b>b</b>) of the sulfides from the Sachakou Pb–Zn deposit and the surrounding area (Jurassic gypsum layer data from the research by Gao et al. [<a href="#B29-minerals-15-00271" class="html-bibr">29</a>], Jia et al. [<a href="#B19-minerals-15-00271" class="html-bibr">19</a>], Li et al. [<a href="#B58-minerals-15-00271" class="html-bibr">58</a>]; Tang et al. [<a href="#B28-minerals-15-00271" class="html-bibr">28</a>]).</p>
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<p>Pb isotope correlation diagrams of the galena from the Sachakou Pb–Zn Deposit. The <sup>207</sup>Pb/<sup>204</sup>Pb versus <sup>206</sup>Pb/<sup>204</sup>Pb evolution diagram (base map from Zartman and Doe [<a href="#B69-minerals-15-00271" class="html-bibr">69</a>]) is shown in (<b>a</b>), with a close-up view provided in (<b>b</b>); the <sup>208</sup>Pb/<sup>204</sup>Pb versus <sup>206</sup>Pb/<sup>204</sup>Pb evolution diagram (base map from Zartman and Doe [<a href="#B69-minerals-15-00271" class="html-bibr">69</a>]) is shown in (<b>c</b>), with a close-up view provided in (<b>d</b>); (<b>e</b>) ∆β versus ∆γ tectonic environment classification diagram (base map from Zhu [<a href="#B67-minerals-15-00271" class="html-bibr">67</a>]). The stratigraphic Pb isotope data in (<b>a</b>–<b>e</b>) are cited from Jia et al. [<a href="#B19-minerals-15-00271" class="html-bibr">19</a>] and Zhou [<a href="#B66-minerals-15-00271" class="html-bibr">66</a>]. 1—mantle-derived lead; 2—upper crustal lead; 3—subduction zone lead with a mixture of upper crustal and mantle-derived lead (3a—magmatism; 3b—sedimentation); 4—chemically precipitated lead; 5—seafloor hydrothermal lead; 6—medium- to high-grade metamorphic lead; 7—high-grade lower crustal lead; 8—orogenic belt lead; 9—ancient shale upper crustal lead; 10—retrograde metamorphic lead.</p>
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20 pages, 10269 KiB  
Article
Viscoelasticity of PPA/SBS/SBR Composite Modified Asphalt and Asphalt Mixtures Under Pressure Aging Conditions
by Zongjie Yu, Xinpeng Ling, Ze Fan, Yueming Zhou and Zhu Ma
Polymers 2025, 17(5), 698; https://doi.org/10.3390/polym17050698 - 6 Mar 2025
Viewed by 28
Abstract
The viscoelastic behavior of asphalt mixtures is a crucial consideration in the analysis of pavement mechanical responses and structural design. This study aims to elucidate the molecular structure and component evolution trends of polyphosphoric acid (PPA)/styrene butadiene styrene block copolymer (SBS)/styrene butadiene rubber [...] Read more.
The viscoelastic behavior of asphalt mixtures is a crucial consideration in the analysis of pavement mechanical responses and structural design. This study aims to elucidate the molecular structure and component evolution trends of polyphosphoric acid (PPA)/styrene butadiene styrene block copolymer (SBS)/styrene butadiene rubber copolymer (SBR) composite modified asphalt (CMA) under rolling thin film oven test (RTFOT) and pressure aging (PAV) conditions, as well as to analyze the viscoelastic evolution of CMA mixtures. First, accelerated aging was conducted in the laboratory through RTFOT, along with PAV tests for 20 h and 40 h. Next, the microscopic characteristics of the binder at different aging stages were explored using Fourier-transform infrared spectroscopy (FTIR) and gel permeation chromatography (GPC) tests. Additionally, fundamental rheological properties and temperature sweep tests were performed to reveal the viscoelastic evolution characteristics of CMA. Ultimately, the viscoelastic properties of CMA mixtures under dynamic loading at different aging stages were clarified. The results indicate that the incorporation of SBS and SBR increased the levels of carbonyl and sulfoxide factors while decreasing the level of long-chain factors, which slowed down the rate of change of large molecule content and reduced the rate of change of LMS by more than 6%, with the rate of change of overall molecular weight distribution narrowing to below 50%. The simultaneous incorporation of SBS and SBR into CMA mixtures enhanced the dynamic modulus in the 25 Hz and −10 °C range by 24.3% (AC-13), 15.4% (AC-16), and reduced the φ by 55.8% (AC-13), 40% (AC-16). This research provides a reference for the application of CMA mixtures in the repair of pavement pothole damage. Full article
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<p>Main performance indexes of BA and CMA before and after RTFOT.</p>
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<p>The designed gradation curves: (<b>a</b>) AC-13; (<b>b</b>) AC-16.</p>
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<p>Dynamic modulus test.</p>
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<p>Rheological properties before and after RTFOT aging of BA and CMA. (<b>a</b>) <math display="inline"><semantics> <mrow> <mi mathvariant="sans-serif">δ</mi> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <msup> <mrow> <mi mathvariant="normal">G</mi> </mrow> <mrow> <mo>∗</mo> </mrow> </msup> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msup> <mrow> <mi mathvariant="normal">G</mi> </mrow> <mrow> <mo>∗</mo> </mrow> </msup> <mo>/</mo> <mi mathvariant="normal">s</mi> <mi mathvariant="normal">i</mi> <mi mathvariant="normal">n</mi> <mi mathvariant="sans-serif">δ</mi> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> </mrow> <mrow> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">I</mi> </mrow> </msub> </mrow> </semantics></math> and <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">P</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">I</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>FTIR spectra of BA and CMA with different aging conditions. (<b>a</b>) FTIR spectra of BA and CMA with different aging conditions; (<b>b</b>) BA and CMA; (<b>c</b>) RTFOT; (<b>d</b>) PAV20; (<b>e</b>) PAV40.</p>
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<p>Changes in functional group indicators: (<b>a</b>) variation of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>c</mi> <mo>=</mo> <mi>o</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) variation of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>s</mi> <mo>=</mo> <mi>o</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Changes in functional group indicators: (<b>a</b>) variation of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>L</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) variation of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>B</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Changes in functional group indicators: (<b>a</b>) variation of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>L</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) variation of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>I</mi> </mrow> <mrow> <mi>B</mi> <mi>C</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Changes in functional group indicators: (<b>a</b>) variation of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">I</mi> </mrow> <mrow> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">r</mi> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) variation of <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">I</mi> </mrow> <mrow> <mi mathvariant="normal">a</mi> <mi mathvariant="normal">l</mi> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Changes in functional group indicators at different aging stages.</p>
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<p>GPC results of BA and CMA: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>M</mi> </mrow> <mrow> <mi>w</mi> </mrow> </msub> </mrow> </semantics></math> distribution of BA; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>M</mi> </mrow> <mrow> <mi>w</mi> </mrow> </msub> </mrow> </semantics></math> of BA of different aging conditions; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>M</mi> </mrow> <mrow> <mi>w</mi> </mrow> </msub> </mrow> </semantics></math> distribution of CMA; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi>M</mi> </mrow> <mrow> <mi>w</mi> </mrow> </msub> </mrow> </semantics></math> of CMA of different aging conditions.</p>
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<p>Changes in molecular weight of BA and CMA before and after aging: (<b>a</b>) division of LMS, MMS, and SMS; (<b>b</b>) molecular weight distribution results.</p>
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<p>Marshall test results.</p>
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<p>Results of the analysis of road performance indicators.</p>
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<p><math display="inline"><semantics> <mrow> <msup> <mrow> <mi mathvariant="normal">E</mi> </mrow> <mrow> <mo>∗</mo> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>13</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>16</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>13</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>16</mn> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p><math display="inline"><semantics> <mrow> <mi>φ</mi> </mrow> </semantics></math>: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>13</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>16</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>13</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>16</mn> </mrow> </msub> </mrow> </semantics></math>.</p>
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<p>Master curve of <math display="inline"><semantics> <mrow> <msup> <mrow> <mi mathvariant="normal">E</mi> </mrow> <mrow> <mo>∗</mo> </mrow> </msup> </mrow> </semantics></math>: (<b>a</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>13</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>b</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">B</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>16</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>c</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>13</mn> </mrow> </msub> </mrow> </semantics></math>; (<b>d</b>) <math display="inline"><semantics> <mrow> <msub> <mrow> <mi mathvariant="normal">C</mi> <mi mathvariant="normal">M</mi> <mi mathvariant="normal">A</mi> </mrow> <mrow> <mi mathvariant="normal">A</mi> <mi mathvariant="normal">C</mi> <mo>−</mo> <mn>16</mn> </mrow> </msub> </mrow> </semantics></math>.</p>
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15 pages, 664 KiB  
Review
Optimizing Conservative Treatment for Femoroacetabular Impingement Syndrome: A Scoping Review of Rehabilitation Strategies
by Federica Giorgi, Daniela Platano, Lisa Berti, Danilo Donati and Roberto Tedeschi
Appl. Sci. 2025, 15(5), 2821; https://doi.org/10.3390/app15052821 - 5 Mar 2025
Viewed by 201
Abstract
Background: Femoroacetabular Impingement Syndrome (FAIS) is a musculoskeletal disorder characterized by hip pain, reduced range of motion (ROM), and functional impairment, particularly in young and physically active individuals. While surgery is generally not performed in individuals under 18 due to skeletal immaturity, [...] Read more.
Background: Femoroacetabular Impingement Syndrome (FAIS) is a musculoskeletal disorder characterized by hip pain, reduced range of motion (ROM), and functional impairment, particularly in young and physically active individuals. While surgery is generally not performed in individuals under 18 due to skeletal immaturity, it remains a standard treatment option for adults presenting with persistent symptoms and functional limitations. However, the overall effectiveness of physiotherapy-based interventions remains unclear. This review aimed to evaluate the effectiveness of conservative rehabilitation strategies for FAIS, assessing their impact on pain management, functional improvement, and quality-of-life outcomes, rather than directly comparing them to surgical interventions. Methods: This scoping review was conducted following the Joanna Briggs Institute (JBI) framework and PRISMA-ScR guidelines. A systematic literature search was performed in PubMed, Cochrane CENTRAL, Scopus, PEDro, and Web of Science. Studies were included if they examined conservative rehabilitation for FAIS, assessing outcomes such as pain reduction, functional improvement, range of motion (ROM), muscle strength, and quality of life. Data were extracted and synthesized narratively. Results: Both conservative rehabilitation and surgical intervention resulted in significant improvements in pain, function, and quality of life. Exercise-based physiotherapy, particularly programs incorporating core stability, progressive strengthening, and neuromuscular training, demonstrated positive outcomes. Surgery provided faster pain relief, ROM improvements, and earlier functional gains, particularly in activities requiring hip flexion. Given the variability in outcome measures, including pain, function, and quality of life, the interpretation of results must consider differences in treatment protocols across studies. Conclusions: Conservative rehabilitation should be considered a first-line treatment for Femoroacetabular Impingement Syndrome (FAIS), as it provides significant improvements in pain relief, function, and quality of life while mitigating the risks associated with surgery. Exercise-based physiotherapy, particularly programs incorporating core stabilization, progressive strengthening, and neuromuscular training, has demonstrated positive clinical outcomes. Although surgery may offer faster symptom relief and greater short-term functional gains, long-term differences between surgical and conservative management appear minimal in selected patient populations. Structured physiotherapy interventions should be prioritized before surgical consideration, except in cases where symptoms persist despite adequate rehabilitation. Future research should aim to establish standardized rehabilitation protocols, define optimal intervention parameters, and identify patient subgroups most likely to benefit from conservative management. Additionally, longitudinal studies with larger sample sizes are needed to clarify the long-term effects of non-surgical treatments on joint health and functional outcomes. Full article
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<p>Preferred reporting items for systematic reviews and meta-analyses 2020 (PRISMA) flow-diagram.</p>
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24 pages, 586 KiB  
Article
Performance Performance Evaluation of a Mesh-Topology LoRa Network
by Thomas Gerhardus Durand and Marthinus Johannes Booysen
Sensors 2025, 25(5), 1602; https://doi.org/10.3390/s25051602 - 5 Mar 2025
Viewed by 51
Abstract
Research into, and the usage of, Low-Power Wide-Area Networks (LPWANs) has increased significantly to support the ever-expanding requirements set by IoT applications. Specifically, the usage of Long-Range Wide-Area Networks (LoRaWANs) has increased, due to the LPWAN’s robust physical layer, Long-Range (LoRa), modulation scheme, [...] Read more.
Research into, and the usage of, Low-Power Wide-Area Networks (LPWANs) has increased significantly to support the ever-expanding requirements set by IoT applications. Specifically, the usage of Long-Range Wide-Area Networks (LoRaWANs) has increased, due to the LPWAN’s robust physical layer, Long-Range (LoRa), modulation scheme, which enables scalable, low-power consumption, long-range communication to IoT devices. The LoRaWAN Medium Access Control (MAC) protocol is currently limited to only support single-hop communication. This limits the coverage of a single gateway and increases the power consumption of devices which are located at the edge of a gateway’s coverage range. There is currently no standardised and commercialised multi-hop LoRa-based network, and the field is experiencing ongoing research. In this work, we propose a complementary network to LoRaWAN, which integrates mesh networking. An ns-3 simulation model has been developed, and the proposed LoRaMesh network is simulated for a varying number of scenarios. This research focuses on the design decisions needed to design a LoRa-based mesh network which maintains the low-power consumption advantages that LoRaWAN offers while ensuring that data packets are routed successfully to the gateway. The results highlighted a significant increase in the packet delivery ratio in nodes located far from a centralised gateway in a dense network. Nodes located further than 5.8 km from a gateway’s packet delivery ratio were increased from an average of 40.2% to 73.78%. The findings in this article validate the concept of a mesh-type LPWAN network based on the LoRa physical layer and highlight the potential for future optimisation. Full article
(This article belongs to the Special Issue LoRa Communication Technology for IoT Applications)
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<p>LoRaWAN topology.</p>
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<p>Real-Time Clock (RTC) synchronisation and up-link messages overview.</p>
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<p>Beacon frame dissemination proposed methods performance. (<b>a</b>) Time diverse beacon frame dissemination performance. (<b>b</b>) Beacon frame dissemination without time diversity performance.</p>
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<p>Simulation of two different layout networks.</p>
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<p>Parent node selection.</p>
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<p>LoRaMesh parent node selection’s impact on power consumption. (<b>a</b>) Closest parent node selected (with bottleneck prevention). (<b>b</b>) Furthest parent node selected (with bottleneck prevention). (<b>c</b>) Random parent node selection (with bottleneck prevention).</p>
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<p>PDR of a multi-hop network with different numbers of nodes placed within a 3.927 km, 5 km, and 7.071 km radius of the GW, normalised to node density.</p>
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<p>Energy consumption of a multi-hop network vs. distance from the GW.</p>
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<p>Power consumption of a LoRaWAN with ADR vs. distance from the GW.</p>
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<p>Average power consumption comparison of a single-hop network vs. multi-hop network.</p>
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<p>Packet delivery ratio of LoRaWAN vs. distance from the GW.</p>
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<p>Packet delivery ratio of LoRaMesh vs. distance from the GW.</p>
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21 pages, 7094 KiB  
Article
Accelerated Glacier Thinning and Area Loss in the Wind River Range, Wyoming (1968–2019): Climate and Topographic Drivers
by Yanan Li, Raihan Jamil and Jeffrey VanLooy
Remote Sens. 2025, 17(5), 916; https://doi.org/10.3390/rs17050916 - 5 Mar 2025
Viewed by 135
Abstract
Glacier meltwater influences streamflow and various activities in the western US. The Wind River Range (WRR) in Wyoming, which contains the largest glacial mass in the Rocky Mountains of the conterminous US, has been retreating since the Little Ice Age. This study examines [...] Read more.
Glacier meltwater influences streamflow and various activities in the western US. The Wind River Range (WRR) in Wyoming, which contains the largest glacial mass in the Rocky Mountains of the conterminous US, has been retreating since the Little Ice Age. This study examines long-term changes in WRR glaciers (>0.2 km2) over 1968–2019 and investigates their relationship with climatic and topographic factors. Using USGS topographic maps, satellite imagery, DEM datasets, and GPS surveys, we analyzed glacier area and surface elevation changes. Our results show a 19.2 ± 0.9% glacier area reduction from 1972 to 2019, with a 10.6 ± 0.3% decline from 2000–2019. Glacier thinning was most pronounced between 2000 and 2019 at −0.58 ± 0.11 m y−1, with lower-elevation glaciers thinning faster. Small, south-facing glaciers retreated more rapidly, while slope effects were mixed. Increasing spring temperatures and a shift toward more spring precipitation falling as rain has likely exacerbated glacier loss since 2000. Such accelerated melting has significant implications for water availability and ecosystem health if warming continues, affecting agricultural, industrial, and recreational water use. Understanding these trends is key for future water resource management and ecosystem sustainability in the region. Full article
(This article belongs to the Section Environmental Remote Sensing)
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<p>Location of the Wind River Range in western Wyoming and selected glaciers/snow patches (blue) with area &gt;0.2 km<sup>2</sup> in this study. For the Continental Glacier, GPS measurements were taken at 25 points (red dots) during a 2019 field campaign, and a high-resolution DEM was created based on aerial imagery collected during a flight in summer 2019.</p>
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<p>The histogram and statistics of off-glacier solid ground elevation differences (<span class="html-italic">dh</span>) between 2000 and 2019 DEMs.</p>
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<p>(<b>a</b>) The relationship between <span class="html-italic">aspect</span> and <span class="html-italic">dh/tan(slope)</span> and (<b>b</b>) the relationship between <span class="html-italic">dh</span> and elevations of off-glacier ground between 2000 and 2019 DEMs.</p>
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<p>Histograms of major topographic/geometric characteristic of glaciers in 1972 (light gray), 1991 (medium gray), and 2000 (dark gray). (<b>a</b>) area; (<b>b</b>) median elevation; (<b>c</b>) mean slope; (<b>d</b>) aspect; (<b>e</b>) shape index; and (<b>f</b>) hypsometric integral (HI). “Count” refers to the number of glaciers.</p>
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<p>Elevation change rate (<span class="html-italic">dh/dt</span>) of studied WRR glaciers at three time periods: 1968–1991, 1991–2000, and 2000–2019. The inset histograms show the distribution and the mean of <span class="html-italic">dh/dt</span> of each period.</p>
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<p>Elevation change rate (<span class="html-italic">dh/dt</span>) of two example glaciers: (<b>a</b>) Gannett Glacier and (<b>b</b>) Dinwoody Glacier at three time periods: 1968–1991, 1991–2000, and 2000–2019.</p>
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<p>The correlation matrix of the rate of elevation change (<span class="html-italic">dh/dt</span>) and nine topographic and geometric variables (<span class="html-italic">ln(A)</span>, minimum elevation, maximum elevation, median elevation, slope, <span class="html-italic">Sin(Aspect)</span>, <span class="html-italic">Cos(Aspect)</span>, shape, and HI), for 1968–1991, 1991–2000, and 2000–2019. Red colors indicate positive correlation coefficient; blue colors indicate negative correlation coefficient. Asterisks after values indicate the significance level: * at 0.1 level (<span class="html-italic">p</span> &lt; 0.1); ** at 0.05 level (<span class="html-italic">p</span> &lt; 0.05); *** at 0.01 level (<span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Annual mean temperature and total precipitation anomaly time series (red: positive temperature anomalies; light blue: negative temperature anomalies; dark blue: positive precipitation anomalies; olive: negative precipitation anomalies) from 1950 to 2019 for the WRR mountainous area (&gt;2800 m a.s.l.). The solid black line is the 10-year moving average line. The vertical dashed line marks the year of the change point detected using Student test (μ statistic) and Bartlett test (σ statistic).</p>
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<p>Annual and seasonal Mann–Kendall trends in mean temperature during 1950 to 2019; stippled area reached significance level of 0.05.</p>
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<p>Annual and seasonal Mann–Kendall trends in total precipitation during 1950 to 2019; stippled area reached significance level of 0.05.</p>
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<p>Heat map of the monthly mean temperature (<b>left</b>) and total precipitation (<b>right</b>) aggregated by decade over the 1950 to 2019 period based on the PRISM climate data over the WRR mountain area (same geographic scope with <a href="#remotesensing-17-00916-f009" class="html-fig">Figure 9</a>).</p>
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23 pages, 1882 KiB  
Article
Attention Mechanism-Based Cognition-Level Scene Understanding
by Xuejiao Tang and Wenbin Zhang
Information 2025, 16(3), 203; https://doi.org/10.3390/info16030203 - 5 Mar 2025
Viewed by 176
Abstract
Given a question–image input, a visual commonsense reasoning (VCR) model predicts an answer with a corresponding rationale, which requires inference abilities based on real-world knowledge. The VCR task, which calls for exploiting multi-source information as well as learning different levels of understanding and [...] Read more.
Given a question–image input, a visual commonsense reasoning (VCR) model predicts an answer with a corresponding rationale, which requires inference abilities based on real-world knowledge. The VCR task, which calls for exploiting multi-source information as well as learning different levels of understanding and extensive commonsense knowledge, is a cognition-level scene understanding challenge. The VCR task has aroused researchers’ interests due to its wide range of applications, including visual question answering, automated vehicle systems, and clinical decision support. Previous approaches to solving the VCR task have generally relied on pre-training or exploiting memory with long-term dependency relationship-encoded models. However, these approaches suffer from a lack of generalizability and a loss of information in long sequences. In this work, we propose a parallel attention-based cognitive VCR network, termed PAVCR, which fuses visual–textual information efficiently and encodes semantic information in parallel to enable the model to capture rich information for cognition-level inference. Extensive experiments show that the proposed model yields significant improvements over existing methods on the benchmark VCR dataset. Moreover, the proposed model provides an intuitive interpretation of visual commonsense reasoning. Full article
(This article belongs to the Special Issue Machine Learning and Data Mining: Innovations in Big Data Analytics)
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<p>Proposed framework.</p>
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<p>An example of VCR running.</p>
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<p>Multimodal Feature Fusion Layer.</p>
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<p>Co-attention.</p>
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<p>Overview of the types of inference required by questions in VCR.</p>
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<p>Case study example 1. The model predicts the correct answer and rationale.</p>
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<p>Qualitative example 1. The model predicts the correct answer and rationale.</p>
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<p>Qualitative example 2. The model predicts the correct answer and rationale.</p>
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<p>Qualitative example 3. The model predicts the correct answer and rationale.</p>
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16 pages, 48938 KiB  
Article
Three-Dimensional Magnetic Inversion with Mixed Lp Norm Regularization for Constraining the Crustal Architecture of Mesozoic Volcanic Arc in the Northern South China Sea
by Zhongwei Chen and Lianghui Guo
Appl. Sci. 2025, 15(5), 2791; https://doi.org/10.3390/app15052791 - 5 Mar 2025
Viewed by 137
Abstract
The high-magnetic anomaly belt in the northern slope of the South China Sea has long been associated with a Mesozoic volcanic arc. However, its crustal architecture remains unclear, limiting the understanding of its geological implications. We assembled high-resolution reduced-to-the-pole aeromagnetic anomaly data around [...] Read more.
The high-magnetic anomaly belt in the northern slope of the South China Sea has long been associated with a Mesozoic volcanic arc. However, its crustal architecture remains unclear, limiting the understanding of its geological implications. We assembled high-resolution reduced-to-the-pole aeromagnetic anomaly data around the northern South China Sea and then applied the 3-D magnetic inversion method based on mixed Lp norm regularization, with the constraint of multiple deep seismic reflection profiling data, to obtain high-resolution 3-D crustal susceptibility model. Our model confirms that the high-magnetic anomaly belt is caused by deep-seated magnetic bodies, which, supported by borehole and seismic data, are identified as a Mesozoic volcanic arc. We found that the Mesozoic volcanic arc described by high susceptibility bodies extends northeastward from the Dongsha Rise to Taiwan Island and primarily distributes within the depth range of 20~28 km. Our findings provide important constraints for understanding the pre-Cenozoic tectonic evolution of the northern South China Sea. Full article
(This article belongs to the Section Earth Sciences)
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<p>Tectonic map of the SCS and adjacent regions. ①: [<a href="#B15-applsci-15-02791" class="html-bibr">15</a>]; ②: [<a href="#B16-applsci-15-02791" class="html-bibr">16</a>]; ③ and ⑤: [<a href="#B9-applsci-15-02791" class="html-bibr">9</a>]; ④: [<a href="#B17-applsci-15-02791" class="html-bibr">17</a>]; ⑥: [<a href="#B18-applsci-15-02791" class="html-bibr">18</a>]; ⑦ and ⑧: [<a href="#B10-applsci-15-02791" class="html-bibr">10</a>]; ⑨: [<a href="#B19-applsci-15-02791" class="html-bibr">19</a>]; ⑩: [<a href="#B11-applsci-15-02791" class="html-bibr">11</a>]; ⑪, ⑫, and ⑬: [<a href="#B4-applsci-15-02791" class="html-bibr">4</a>]; ⑭: [<a href="#B20-applsci-15-02791" class="html-bibr">20</a>]; ⑮: [<a href="#B7-applsci-15-02791" class="html-bibr">7</a>]. PHR: Penghu Rise; TXNB: Taixinan Basin; DSR: Dongsha Rise; CSD: Chaoshan Depression; YTA: Yitong Ansha. The Speculated volcanic arc (yellow line) follows [<a href="#B8-applsci-15-02791" class="html-bibr">8</a>]. Black rectangular box represents the extent of the study area (<a href="#applsci-15-02791-f002" class="html-fig">Figure 2</a>).</p>
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<p>The RTP aeromagnetic anomaly map around the northern SCS (digitized from [<a href="#B25-applsci-15-02791" class="html-bibr">25</a>]). ZHU I D: Zhu I depression; PHR: Penghu Rise; TXNB: Taixinan Basin; DSR: Dongsha Rise; CSD: Chaoshan Depression; YTA: Yitong Ansha. Black lines represent the 0 m isobath. White lines outline the depressions.</p>
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<p>Magnetic anomalies caused by the synthetic model. The white dashed boxes outline the true cubes, while the black dashed line locates the profile A shown in <a href="#applsci-15-02791-f004" class="html-fig">Figure 4</a> and <a href="#applsci-15-02791-f005" class="html-fig">Figure 5</a>.</p>
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<p>Magnetic inversion results using L<sub>1</sub> and L<sub>2</sub> norm regularization for the synthetic model. (<b>a</b>,<b>b</b>) show the results at depth slice of Z = 350 m and along profile A using the L<sub>1</sub> norm regularization algorithm; (<b>c</b>,<b>d</b>) are those using the L<sub>2</sub> norm regularization algorithm. The black boxes outline the true model, and the black dashed lines in (<b>a</b>–<b>d</b>) locate the profiles shown in <a href="#applsci-15-02791-f006" class="html-fig">Figure 6</a>.</p>
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<p>Magnetic inversion results using mixed L<sub>p</sub> norm regularization for the synthetic model. (<b>a</b>,<b>b</b>) show the results at depth slice of Z = 350 m and along profile A using the L<sub>02</sub> norm regularization algorithm; (<b>c</b>,<b>d</b>) are those using the L<sub>12</sub> norm regularization algorithm. The black boxes outline the true model, and the black dashed lines in (<b>a</b>–<b>d</b>) locate the profiles shown in <a href="#applsci-15-02791-f006" class="html-fig">Figure 6</a>.</p>
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<p>Profiles of inversion results using different norms. (<b>a</b>) Inversion results along profile of X = 1000 m at depth slice of Z = 350 m; (<b>b</b>) Inversion results at the position of X = 1000 m along profile A. The black dashed lines represent the true susceptibility values of the cube.</p>
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<p>Three-dimensional prospective map of our crustal susceptibility model in the northern SCS. Only susceptibility greater than 0.02 (SI) is displayed in green, with red representing 0.03 (SI). Black lines represent 0 m isobath.</p>
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<p>(<b>a</b>) Calculated magnetic anomalies of the inversion model and (<b>b</b>) residuals between calculated and real magnetic anomalies. Black lines represent the 0 m isobath. White lines represent the depressions.</p>
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<p>The susceptibility model superimposed the multiple deep seismic reflection profile [<a href="#B10-applsci-15-02791" class="html-bibr">10</a>].</p>
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<p>Comparison of the susceptibility model (<b>below</b>) with the OBS2006-3 P-wave velocity model (<b>above</b>) [<a href="#B7-applsci-15-02791" class="html-bibr">7</a>]. The red circle in the above map highlights the high-velocity uplift.</p>
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<p>Magnetic inversion results along profiles A~D. ZHU I D: Zhu I depression; PHR: Penghu Rise; TXNB: Taixinan Basin; DSR: Dongsha Rise; CSD: Chaoshan Depression. White lines represent the 0 m isobath.</p>
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<p>The contour map of magnetic anomaly modulus around the northern SCS.</p>
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