Search Results (716)

This study examines the role of humanitarian diplomacy during the Tigray humanitarian crisis in Ethiopia, a humanitarian disaster marked by severe shortages in food, healthcare, and essential services that deeply affect civilians. A qualitative approach using both primary and secondary data grounds the study by exploring key actors in humanitarian diplomacy, their successes, and barriers to aid delivery. Humanitarian actors, such as UN agencies, international NGOs, donor countries, the EU, the US, and the African Union, have engaged with the Ethiopian government, the TPLF, and the Tigray Transitional Government to alleviate the crisis. Notable achievements in humanitarian diplomacy include negotiations, information gathering, communication, civilian needs assessment, resource mobilization, advocacy for international law, and distressed civilians. Humanitarian diplomacy has facilitated international aid operations, saving lives during critical periods, despite practical difficulties. Diplomatic efforts have faced significant interruptions due to access restrictions imposed by the Ethiopian government, security threats from ongoing fighting leading to attacks on aid convoys and casualties among aid workers, and bureaucratic obstacles imposed by the Ethiopian government. This study highlights the necessity for effective humanitarian diplomacy in accounting for complex political landscapes in conflict-affected regions, developing flexible strategies that enhance access to aid, and improving humanitarian interventions. Full article

The particle size distribution (PSD) is a crucial parameter used to characterize the material composition of debris-flow deposits which determines their hydraulic permeability, affecting the mobility of debris flows and, hence, the sustainable development of debris-flow fans. Three types of graded bedding structures—normal, reverse, and mixed graded bedding structures—are characterized by discontinuous gradation within a specific deposit thickness. A series of permeability tests were conducted to study the effects of bed sediment composition, particularly coarse grain sizes and fine particle contents, on the permeability and migration of fine particles in discontinuous debris-flow deposits. An increase in fine particles within the discontinuously graded bed sediment led to a power-law decrease in the average permeability coefficient. With fine particle contents of 10% and 15% in the bed sediments, the final permeability coefficient consistently exceeded the initial value. However, this trend reversed when the fine particle contents were increased to 20%, 25%, and 30%. Lower fine particle contents indicated enhanced permeability efficiency due to more interconnected voids within the coarse particle skeleton. Conversely, an increase in fine particle content reduced the permeability efficiency, as fine particles tended to aggregate at the lower section of the seepage channel. An increase in coarse particle size decreased the formation of flow channels at the coarse–fine particle interface, causing fine particles to move slowly along adjacent or clustered slow flow channels formed by fine particles, resulting in decreased permeability efficiency. Three formulae are proposed to calculate the permeability coefficients of discontinuously graded bed sediments, which may aid in understanding the initiation mechanism of channel deposits. Based on experimental studies and field investigations, it is proposed that achieving sustainable development of debris-flow fans requires a practical approach that integrates three key components: spatial land-use planning, in situ monitoring of debris flows and the environment, and land-use adjustment and management. This comprehensive and integrated approach is essential for effectively managing and mitigating the risks associated with debris flows, ensuring sustainable development in vulnerable areas. Full article

Seed reserve mobilization is a crucial physiological process during seed germination. Enhancing the reserve mobilization in sweet corn is vital for seed germination and seedling growth. In this study, a genome-wide association analysis (GWAS) was conducted to predict candidate genes for regulating the weight of mobilized reserved seeds (WMRS) and kernel weight (KW) in sweet corn. GWAS was performed using the BLINK model with the maize 56K SNP chip. The results indicated that there was a positive correlation between the WMRS and KW, with coefficients of variation of 68.18% and 44.63%. Association analysis identified thirteen SNPs associated with two traits, and linkage disequilibrium analysis revealed that eight of these SNPs were in strong linkage. A total of 298 candidate genes were identified within the confidence interval, of which 79 were annotated. About 20 candidate genes were identified through the comparison of homologous genes in Arabidopsis. These genes were enriched in regulating ribosome biogenesis, signal transduction, hormone synthesis, and RNA degradation processes. This study provides important insights into the genetic mechanisms governing germination traits in sweet corn, aiding further research into the localization and cloning of genes involved in the mobilization of reserve materials. Full article

To permit the collection of quantitative data on start, turn and clean swimming performances in any swimming pool, the aims of the present study were to (1) validate a mobile in-field performance analysis system (PAS) against the Kistler starting block equipped with force plates and synchronized to a 2D camera system (KiSwim, Kistler, Winterthur, Switzerland), (2) assess the PAS’s interrater reliability and (3) provide percentiles as reference values for elite junior and adult swimmers. Members of the Swiss junior and adult national swimming teams including medalists at Olympic Games, World and European Championships volunteered for the present study (n = 47; age: 17 ± 4 [range: 13–29] years; World Aquatics Points: 747 ± 100 [range: 527–994]). All start and turn trials were video-recorded and analyzed using two methods: PAS and KiSwim. The PAS involves one fixed view camera recording overwater start footage and a sport action camera that is moved underwater along the side of the pool perpendicular to the swimming lane on a 1.55 m long monostand. From a total of 25 parameters determined with the PAS, 16 are also measurable with the KiSwim, of which 7 parameters showed satisfactory validity (r = 0.95–1.00, p < 0.001, %-difference < 1%). Interrater reliability was determined for all 25 parameters of the PAS and reliability was accepted for 21 of those start, turn and swimming parameters (ICC = 0.78–1.00). The percentiles for all valid and reliable parameters provide reference values for assessment of start, turn and swimming performance for junior and adult national team swimmers. The in-field PAS provides a mobile method to assess start, turn and clean swimming performance with high validity and reliability. The analysis template and manual included in the present article aid the practical application of the PAS in research and development projects as well as academic works. Full article

The exploration of porphyry deposits in Greenland has become increasingly important due to their significant economic potential. We utilized total magnetic intensity (TMI) and mobile magnetotelluric (MobileMT) airborne data to delineate potential porphyry mineralization zones. The TMI method was employed to map variations in the Earth’s magnetic field caused by subsurface geological features, including mineral deposits. By analyzing anomalies in TMI data, potential porphyry targets were identified based on characteristic magnetic signatures associated with mineralized zones. Complementing TMI data, MT airborne surveys provided valuable insights into the electrical conductivity structure of the subsurface. Porphyry deposits exhibited distinct conductivity signatures due to the presence of disseminated sulfide minerals, aiding in their identification and delineation. Integration of the TMI and MobileMT datasets allowed for a comprehensive assessment of porphyry exploration targets in Flammefjeld. The combined approach facilitates the identification of prospective areas with enhanced geological potential, optimizing resource allocation and exploration efforts. Overall, this study demonstrates the efficacy of integrating TMI and MobileMT airborne data for porphyry exploration in Greenland, offering valuable insights for mineral exploration and resource development in the region. Full article

The planning of greener, more accessible, and safer cities is the focus of several strategies that aim to improve the population’s quality of life. This concern for the environment and the population’s quality of life has led to the implementation of active mobility policies. The effectiveness of the mobility solutions that are sought heavily depends on the identification of the main factors that favor their use, as well as how adequate urban spaces are in minimizing existing difficulties. This study presents an automated geographic information system (GIS) decision support tool that allows the identification of the level of suitability of urban transportation networks for the use of active modes. The tool is based on the determination of a set of mobility indices: walkability, bikeability, e-bikeability, and active mobility (a combination of walking and cycling suitability). The indices are obtained through a spatial multi-criteria analysis that considers the geometric features of roads, population density, and the location and attractiveness of the city’s main trip-generation points. The treatment, representation, and study of the variables considered in the analysis are carried out with the aid of geoprocessing, using the spatial and network analysis tools available in the GIS. The Model Builder functionality available in ArcGIS^® was used to automate the various processes required to calculate walking, cycling, and e-biking travel times, as well as the mobility indices. The developed tool was tested and validated through its application to a case study involving the road network of the urban perimeter of the medium-sized city of Covilhã, Portugal. However, the tool is designed to be applied with minimal adaptation to different scenarios and levels of known input information, providing average or typical values when specific information is not available. As a result, a flexible and automated GIS-based tool was obtained to support urban space and mobility managers in the implementation of efficient measures compatible with each city’s scenario. Full article

This study proposes a low-cost, automatic, wide-area real-time water pipeline monitoring model based on Narrowband Internet of Things (NB-IoT) technology, aiming to solve the challenges faced in the context of global water pipeline management. This model focuses on real-time monitoring of pipeline operations to reduce water waste and improve management efficiency, directly contributing to the achievement of the sustainable development goals (SDGs). Water resource management faces several significant global challenges, including water scarcity, inefficient resource utilization, and infrastructure degradation. Traditional water pipeline monitoring systems are often manual, time-consuming, and unable to detect leaks or failures in real time, leading to significant water loss and financial costs. In response to these issues, NB-IoT technology offers a promising solution with its advantages of low power consumption, long-range communication, and cost-effectiveness. The development of an NB-IoT-based smart water pipeline monitoring system is therefore essential for enhancing the efficiency and sustainability of water resource management. Through enabling real-time monitoring and data collection, this system can address critical issues in global water management, reducing waste and supporting the sustainable development goals (SDGs). This model utilizes Low-Power Wide-Area Network (LPWAN) technology, combined with an LTE mobile network and ARM Cortex-M4 microcontroller, to achieve long-distance multi-sensor data collection and monitoring. The research results show that NB-IoT technology can effectively improve water resource management efficiency, reduce water waste, and is of great significance for the digital transformation of infrastructure and the development of smart cities. This technical solution not only supports “Goal 6: Clean Drinking Water and Sanitation” in the United Nations’ sustainable development goals (SDGs) but also promotes the realization of low-cost teaching aids related to engineering education-related information and communication technologies (ICTs). This study demonstrates the key role of ICTs in promoting sustainable development and provides a concrete practical example for smart water resource management. Full article

People with hearing impairments often face increased risks related to traffic accidents due to their reduced ability to perceive surrounding sounds. Given the cost and usage limitations of traditional hearing aids and cochlear implants, this study aims to develop a sound alert assistance system (SAAS) to enhance situational awareness and improve travel safety for people with hearing impairments. We proposed the VAS-Compass Net (Vehicle Alert Sound–Compass Net), which integrates three lightweight convolutional neural networks: EfficientNet-lite0, MobileNetV3-Small, and GhostNet. Through employing a fuzzy ranking ensemble technique, our proposed model can identify different categories of vehicle alert sounds and directions of sound sources on an edge computing device. The experimental dataset consisted of images derived from the sounds of approaching police cars, ambulances, fire trucks, and car horns from various directions. The audio signals were converted into spectrogram images and Mel-frequency cepstral coefficient images, and they were fused into a complete image using image stitching techniques. We successfully deployed our proposed model on a Raspberry Pi 5 microcomputer, paired with a customized smartwatch to realize an SAAS. Our experimental results demonstrated that VAS-Compass Net achieved an accuracy of 84.38% based on server-based computing and an accuracy of 83.01% based on edge computing. Our proposed SAAS has the potential to significantly enhance the situational awareness, alertness, and safety of people with hearing impairments on the road. Full article

In recent years, assistive technology usage among the visually impaired has risen significantly worldwide. While traditional aids like guide dogs and white canes have limitations, recent innovations like RFID-based indoor navigation systems and alternative sensory solutions show promise. Nevertheless, there is a need for a user-friendly, comprehensive system to address spatial orientation challenges for the visually impaired. This research addresses the significance of developing a deep learning-based walking assistance device for visually impaired individuals to enhance their safety during mobility. The proposed system utilizes real-time ultrasonic sensors attached to a cane to detect obstacles, thus reducing collision risks. It further offers real-time recognition and analysis of diverse obstacles, providing immediate feedback to the user. A camera distinguishes obstacle types and conveys relevant information through voice assistance. The system’s efficacy was confirmed with a 90–98% object recognition rate in tests involving various obstacles. This research holds importance in providing safe mobility, promoting independence, leveraging modern technology, and fostering social inclusion for visually impaired individuals. Full article

Ceramic proton conductors have the potential to lower the operating temperature of solid oxide cells (SOCs) to the intermediate temperature range of 400–600 °C. This is attributed to their superior ionic conductivity compared to oxide ion conductors under these conditions. However, prominent proton-conducting materials, such as yttrium-doped barium cerates and zirconates with specified compositions like BaCe_1−xY_xO_3−δ (BCY), BaZr_1−xY_xO_3−δ (BZY), and Ba(Ce,Zr)_1−yY_yO_3−δ (BCZY), face significant challenges in achieving dense electrolyte membranes. It is suggested that the incorporation of transition and alkali metal oxides as sintering additives can induce liquid phase sintering (LPS), offering an efficient method to facilitate the densification of these proton-conducting ceramics. However, current research underscores that incorporating these sintering additives may lead to adverse secondary effects on the ionic transport properties of these materials since the concentration and mobility of protonic defects in a perovskite are highly sensitive to symmetry change. Such a drop in ionic conductivity, specifically proton transference, can adversely affect the overall performance of cells. The extent of variation in the proton conductivity of the perovskite BCZY depends on the type and concentration of the sintering aid, the nature of the sintering aid precursors used, the incorporation technique, and the sintering profile. This review provides a synopsis of various potential sintering techniques, explores the influence of diverse sintering additives, and evaluates their effects on the densification, ionic transport, and electrochemical properties of BCZY. We also report the performance of most of these combinations in an actual test environment (fuel cell or electrolysis mode) and comparison with BCZY. Full article

Smartphones are intricately connected to the modern society. The two widely used mobile phone operating systems, iOS and Android, profoundly affect the lives of millions of people. Android presently holds a market share of close to 71% among these two. As a result, if personal information is not securely protected, it is at tremendous risk. On the other hand, mobile malware has seen a year-on-year increase of more than 42% globally in 2022 mid-year. Any group of human professionals would have a very tough time detecting and removing all of this malware. For this reason, deep learning in particular has been used recently to overcome this problem. Deep learning models, however, were primarily created for picture analysis. Despite the fact that these models have shown promising findings in the field of vision, it has been challenging to fully comprehend what the characteristics recovered by deep learning models are in the area of malware. Furthermore, the actual potential of deep learning for malware analysis has not yet been fully realized due to the translation invariance trait of well-known models based on CNN. In this paper, we present ViTDroid, a novel model based on vision transformers for the deep learning-based analysis of opcode sequences of Android malware samples from large real-world datasets. We have been able to achieve a false positive rate of 0.0019 as compared to the previous best of 0.0021. However, this incremental improvement is not the major contribution of our work. Our model aims to make explainable predictions, i.e., it not only performs the classification of malware with high accuracy, but it also provides insights into the reasons for this classification. The model is able to pinpoint the malicious behavior-causing instructions in the malware samples. This means that our model can actually aid in the field of malware analysis itself by providing insights to human experts, thus leading to further improvements in this field. Full article

Africa still struggles to end hunger, partly because not all Africans have access to nutritious food. Although studies have established the connection between digital technologies and food security, the reality in Africa is that, despite the laudable feat in the use of digital technologies, the accessibility and utilization of food still face challenges. Digital agriculture, or technology, is a data-driven innovation that predicts agricultural outcomes and guides food producers throughout the different phases of operations on the farm. The literature documents the efficacy of digital agriculture in food production and availability well, but it has hardly examined how it enhances food accessibility and utilization. And even though studies that have examined food accessibility and utilization have merely assessed income as a tool that guarantees food accessibility and utilization, not much attention has been paid to how digital resources can aid in the access to and utilization of food. Drawing on information asymmetry theory and the systematic qualitative method, this article investigates how digital agriculture, through the internet and mobile phones, enhances efforts towards the accessibility and utilization of food as prerequisites for the attainment of SDG 2 in Africa. The findings provide an understanding of the potential of digital technologies in promoting the accessibility and utilization of food. It advocates strategies through which stakeholders in the agricultural sector can utilize technology in ways that aid Africa’s strategic efforts to attain food security and zero hunger. Full article

Nowadays, mobile–mobile interaction is becoming a fundamental methodology for human–human networking services since mobile devices are the most common interfacing equipment for recent smart services such as food delivery, e-commerce, ride-hailing, etc. Unlike legacy ways of human interaction, on-site and in-person mutual recognition between a service provider and a client in mobile–mobile interaction is not trivial. This is because of not only the avoidance of face-to-face communication due to safety and health concerns but also the difficulty of matching up the online user using mobiles with the real person in the physical world. So, a novel mutual recognition scheme for mobile–mobile interaction is highly necessary. This paper comes up with a novel cyber-physical secure communication scheme relying on the digital twin paradigm. The proposed scheme designs the digital twin networking architecture on which real-world users form digital twins as their own online abstraction, and the digital twins authenticate each other for a smart service interaction. Thus, inter-twin communication (ITC) could support secure mutual recognition in mobile–mobile interaction. Such cyber-physical authentication (CPA) with the ITC is built on the dynamic BLE beaconing scheme with accurate proximity detection and dynamic identifier (ID) allocation. To achieve high accuracy in proximity detection, the proposed scheme is conducted using a wide variety of data pre-processing algorithms, machine learning technologies, and ensemble techniques. A location-dependent ID exploited in the CPA is dynamically generated by the physical user for their own digital twin per each mobile service. Full article

Background and Objectives: Seliciclib (SEL) is the first selective, orally bioavailable potential drug containing cyclin-dependent kinase inhibitors. Preclinical studies showed antitumor activity in a broad range of human tumor xenografts, neurodegenerative diseases, renal dysfunctions, viral infections, and chronic inflammatory disorders. To support the pharmacokinetics and aid in therapeutic monitoring of SEL following its administration for therapy, an efficient analytical tool capable of quantifying the concentrations of SEL in blood plasma is needed. In the literature, there is no existing method for quantifying SEL in plasma samples. This study introduces the first HPLC method with a photodiode array (PDA) detector for the quantitation of SEL in plasma. Materials and Methods: The chromatographic resolution of SEL and linifanib as an internal standard (IS) was achieved on Zorbax Eclipse Plus C18 HPLC column (150 mm length × 4.6 mm internal diameter, 5 µm particle size), with a mobile phase composed of acetonitrile–ammonium acetate, pH 5 (50:50, v/v) at a flow rate of 1.0 mL min⁻¹. Both SEL and IS were detected by PDA at 230 nm. The method was validated according to the ICH guidelines for bioanalytical method validation. Results: The method exhibited linearity in concentrations ranging from 50 to 1000 ng mL⁻¹, with a limit of quantitation of 66.1 ng mL⁻¹. All remaining validation parameters satisfied the ICH validation criteria. The environmental sustainability of the method was verified using three extensive tools. The proposed HPLC-PDA method was effectively utilized to study the pharmacokinetics of SEL in rats after a single oral administration of 25 mg/kg. Conclusions: The proposed method stands as a valuable tool for studying SELs for pharmacokinetics in humans. It aids in achieving the targeted therapeutic advantages and safety of treatment with SEL by optimizing the SEL dosage and dosing schedule. Full article

(1) Background: Public transport has a vital role to play in creating sustainable, accessible societies. Accessible and inclusive, door-to-door public transport systems with low barriers to use benefit everyone, increasing the mobility of citizens and improving independence. As the industry strives towards multi-modal and Mobility as a Service (MaaS) concepts, there is a need to delve deep into the needs and perceptions of transport user’s door-to-door journeys to find ways to improve. Accordingly, in order to increase the sustainability of MaaS, improving accessibility and understanding service user perceptions are of utmost importance. However, there is a scarcity of research within national transport services to determine unmet user needs to increase the accessibility and autonomy of door-to-door journeys. This research aims to investigate if it is possible to improve the door-to-door journey experience for public transport travellers, increasing the accessibility and the perception of autonomy via technology, and by doing so, providing a more sustainable alternative to road transport. It focuses on understanding service users of Ireland’s National Rail service, Irish Rail, to create key improvements in interactive systems. (2) Methods: The study applies a user-centred mixed-methods methodology using surveys (N = 316) and co-design workshops (four workshops N = 15). The research collected deep insights into the mindsets and needs of service users, showing the potential to improve this door-to-the-door customer journey. Key improvements for interactive systems were outlined. Experience maps were designed, leading to a Conceptual Design for a travel assistant to aid the service user throughout the door-to-door journey. (3) Results: Travellers’ autonomy and the sense of freedom they experience can be improved, mainly if their needs across the complete door-to-door customer journey are supported. Highlighted areas for action include information, accessibility, personal security, ticketing, comfort, facilities, and anxiety. (4) Conclusions: This research reiterates the need for national transport and MaaS providers to prioritise service users’ perspectives when developing sustainable services. Co-designing is recommended as a means of achieving this. Full article