Search Results (1,042)

In the context of a low-carbon economic transition and escalating uncertainties in financial markets, understanding the relationship between the long-term benefits of ESG (Environmental, Social, and Governance) investments and the stability of China’s financial markets emerges as a critical issue. This paper analyzes the risk contagion mechanisms within China’s financial system from the perspective of volatility spillovers associated with ESG investments. Initially, the study employs the Time-Varying Parameter Vector Autoregression (TVP-VAR) model to calculate the variance decomposition spillover index, contrasting the dynamics and risk transmission mechanisms of market volatility between portfolios composed of ESG and conventional stocks. Building upon the analysis of risk spillover relations among financial sub-markets, the study utilizes the generalized forecast error variance decomposition method to construct a complex network of financial system risk spillovers, investigating the risk contagion characteristics within both financial systems through network topology. Empirical findings indicate a significant reduction in the risk and net spillover effects of China’s financial system when ESG stock indices replace conventional stock indices, with a notable mutation in the volatility spillover network structure during extreme risk events and even more substantial changes during the COVID-19 pandemic. Furthermore, based on volatility spillover analysis, the study computes optimal weights and hedging strategies for portfolios incorporating the ESG volatility index and other market volatility indices. The conclusions of this research are instrumental for regulatory authorities in establishing early warning mechanisms and for investors in avoiding financial investment risks. Full article

The concept of quantum acceleration limit has been recently introduced for any unitary time evolution of quantum systems under arbitrary nonstationary Hamiltonians. While Alsing and Cafaro used the Robertson uncertainty relation in their derivation, employed the Robertson–Schrödinger uncertainty relation to find the upper bound on the temporal rate of change of the speed of quantum evolutions. In this paper, we provide a comparative analysis of these two alternative derivations for quantum systems specified by an arbitrary finite-dimensional projective Hilbert space. Furthermore, focusing on a geometric description of the quantum evolution of two-level quantum systems on a Bloch sphere under general time-dependent Hamiltonians, we find the most general conditions needed to attain the maximal upper bounds on the acceleration of the quantum evolution. In particular, these conditions are expressed explicitly in terms of two three-dimensional real vectors, the Bloch vector that corresponds to the evolving quantum state and the magnetic field vector that specifies the Hermitian Hamiltonian of the system. For pedagogical reasons, we illustrate our general findings for two-level quantum systems in explicit physical examples characterized by specific time-varying magnetic field configurations. Finally, we briefly comment on the extension of our considerations to higher-dimensional physical systems in both pure and mixed quantum states. Full article

Milk fat is an important indicator for evaluating milk quality and a symbol of the core competitiveness of the dairy industry. It can be improved through genetic and feed management factors. Interferon alpha-inducible protein 27 (IFI27) was found to be differentially expressed when comparing the transcriptome in high- and low-fat bovine mammary epithelial cells (bMECs) in our previous research. Therefore, this study aimed to investigate whether the IFI27 gene had a regulatory effect on lipid metabolism.We detected six SNPs in the IFI27 gene (UTR-(-127) C>A, UTR-(-105) T>A, UTR-(-87) G>A, I1-763 G>T, E2-77 G>A, E2-127 G>T) in a Chinese Holstein cow population. Association analysis of the polymorphism of IFI27 and milk quality traits showed that the AG and GG genotype of E2-77 G>A, and the GG and TT genotypes of E2-127 G>T were connected to milk fat (p < 0.05). Haplotype frequency analysis showed that H5H5 was associated with lower milk fat content (p < 0.05), while milk from H5H6 animals had a higher fat content (p < 0.05). Subsequently, IFI27 overexpression vectors (PBI-CMV3-IFI27) and interference vectors (Pb7sk-GFP-shRNA) were constructed. Overexpression of the IFI27 gene in bMECs caused a significant increase in triglycerides (TGs) content (p < 0.05) and decreases in cholesterol (CHOL) and nonestesterified fatty acid (NEFA) content (p < 0.05), while interference with IFI27 expression produced opposing changes (p < 0.05). In summary, IFI27 E2-77 G>A and IFI27 E2-127 G>T may be useful as molecular markers in dairy cattle to measure milk fat, and the IFI27 gene may play an important role in milk lipid metabolism. Full article

Background: Schwann cells (SCs) and their plasticity contribute to the peripheral nervous system’s capacity for nerve regeneration after injury. The Egr2/Krox20 promoter antisense RNA (Egr2-AS) recruits chromatin remodeling complexes to inhibit Egr2 transcription following peripheral nerve injury. Methods: RNA-seq and ATAC-seq were performed on control cells, Lenti-GFP-transduced cells, and cells overexpressing Egr2-AS (Lenti-AS). Egr2 AS-RNA was cloned into the pLVX-DsRed-Express2-N1 lentiviral expression vector (Clontech, Mountain View, CA, USA), and the levels of AS-RNA expression were determined. Ezh2 and Wdr5 were immunoprecipitated from rat SCs and RT-qPCR was performed against AS-Egr2 RNA. ChIP followed by DNA purification columns was used to perform qPCR for relevant promoters. Hi-C, HiC-DC+, R, Bioconductor, and TOBIAS were used for significant and differential loop analysis, identifications of COREs and CORE-promotor loops, comparisons of TF activity at promoter sites, and identification of site-specific TF footprints. OnTAD was used to detect TADs, and Juicer was used to identify A/B compartments. Results: Here we show that a Neuregulin-ErbB2/3 signaling axis mediates binding of the Egr2-AS to YY1^Ser184 and regulates its expression. Egr2-AS modulates the chromatin accessibility of Schwann cells and interacts with two distinct histone modification complexes. It binds to EZH2 and WDR5 and enables targeting of H3K27me3 and H3K4me3 to promoters of Egr2 and C-JUN, respectively. Expression of the Egr2-AS results in reorganization of the global chromatin landscape and quantitative changes in the loop formation and contact frequency at domain boundaries exhibiting enrichment for AP-1 genes. In addition, the Egr2-AS induces changes in the hierarchical TADs and increases transcription factor binding scores on an inter-TAD loop between a super-enhancer regulatory hub and the promoter of mTOR. Conclusions: Our results show that Neuregulin-ErbB2/3-YY1 regulates the expression of Egr2-AS, which mediates remodeling of the chromatin landscape in Schwann cells. Full article

Global warming and climate change, primarily driven by human activities, with agriculture playing a significant role, have become central topics of scientific research. Livestock production, especially enteric fermentation, is a major source of greenhouse gas emissions, making it a focal point for both climate change adaptation and mitigation strategies. Both the European Union (EU) and Least Developed Countries (LDCs) are highly dependent on agriculture, particularly livestock, which plays a key role in their economic growth. In developing countries, livestock systems are evolving rapidly due to various factors, while in the EU, the livestock sector remains economically and socially significant, representing 36% of total agricultural activity. This study explores the environmental impact of enteric fermentation in livestock production, alongside the economic value it generates in both the EU and LDCs. The analysis utilizes a Bayesian Vector Autoregression (BVAR) methodology, which provides a more robust performance compared to traditional models like Vector Autoregression (VAR) and the Vector-error Correction Model (VECM). This research identifies significant relationships between the variables studied, with structural breaks quantified to reflect the impact of initiatives undertaken in both regions. Interestingly, the results challenge the environmental Kuznets curve, which hypothesizes an inverted U-shaped relationship between economic growth and environmental degradation, as proposed by Stern. This suggests that stronger economic incentives may be necessary to enhance policy effectiveness and promote eco-efficiency. The distinctive characteristics of livestock production in the EU and LDCs should be carefully considered when shaping agricultural policies, with a strong emphasis on farmer education as a critical factor for success. Additionally, corporate management practices must be tailored to address the unique needs, strengths, and challenges of livestock businesses in these two diverse regions. Full article

In this study, Clostridium butyricum TO-A culture supernatant (CBCS) or butyric acid was added to a culture medium of human cervical carcinoma HeLa S3 cells, and changes in DNA-repair-related gene promoter activities were investigated. The HeLa S3 cells were transfected with a luciferase (Luc) expression vector containing approximately 500 bp of the 5′-upstream region of several human DNA-repair-related genes and cultured with a medium containing the CBCS (10%) or butyric acid (2.5 mM). The cells were harvested after 19 to 42 h of incubation. A Luc assay revealed that the human ATM, PARG, PARP1, and RB1 gene promoter activities were significantly increased. A Western blot analysis showed that the amounts of the proteins encoded by these genes markedly increased. Furthermore, 8, 24, and 48 h after the addition of the CBCS (10%), total RNA was extracted and subjected to RNAseq analysis. The results showed that the expression of several inflammation- and DNA-replication/repair-related genes, including NFKB and the MCM gene groups, decreased markedly after 8 h. However, the expression of the histone genes increased after 24 h. Elucidation of the mechanism by which the CBCS and butyrate affect the expression of genes that encode DNA-repair-associated proteins may contribute to the prevention of carcinogenesis, the risk of which rises in accordance with aging. Full article

This paper examines the relationship between a technology shock and employment, considering price, wage rigidities, and heterogeneous agents. To explore this relationship, we utilized a Dynamic Stochastic General Equilibrium (DSGE) model, incorporating households with varying savings rates. For empirical validation, we conducted a Structural Vector Autoregression (SVAR) analysis using data from two economies with distinct savings patterns—the United States and China. This approach allowed us to assess the impact of technology shocks on employment dynamics across different savings environments. Under these conditions, we observe that the effect of technology on aggregate employment is initially positive. Still, it gradually decreases in the mid-term, eventually switching to a negative impact before slowly recovering to equilibrium. The reason for this phenomenon depends on (i) the magnitude of fluctuations in price and wage, precisely, which variable’s fluctuations have a greater magnitude, and (ii) which effect, between income effect and substitute effect, is preferred by restricted and unrestricted households. Due to (i), real wages change, and because of (ii), households make different labor supply decisions, leading to fluctuations in employment in response to technology shocks. Full article

Change detection in biomedical signals is crucial for understanding physiological processes and diagnosing medical conditions. This study evaluates various change detection methods, focusing on synthetic signals that mimic real-world scenarios. We examine the following three methods: classical statistical techniques (thresholding based on mean and standard deviation), Support Vector Machine (SVM) classification, and time–frequency analysis using Continuous Wavelet Transform (CWT). Each method’s performance is assessed using synthetic signals, including nonlinear signals and those with simulated anomalies. We calculated the F1-score to quantify performance, providing a balanced measure of precision and recall. Results showed that SVM classification outperformed both classical techniques and CWT analysis, achieving a higher F1-score in detecting changes. While all methods struggled with synthetic nonlinear signals, classical techniques and SVM successfully detected changes in signals with simulated anomalies, whereas CWT had difficulty with both types of signals. These findings underscore the importance of selecting appropriate change detection methods based on signal characteristics. Future research should explore advanced machine learning and signal processing techniques to improve detection accuracy in biomedical applications. Full article

For several years, the determination of a differential cell count of a raw milk sample has been proposed as a more accurate tool for monitoring the udder health of dairy cows compared with using the absolute somatic cell count. However, the required sample preparation and staining process can be labor- and cost-intensive. Therefore, the aim of our study was to demonstrate the feasibility of analyzing unlabeled blood and milk leukocytes from dairy cows by means of digital holographic microscopy (DHM). For this, we trained three different machine learning methods, i.e., k-Nearest Neighbor, Random Forests, and Support Vector Machine, on sorted leukocyte populations (granulocytes, lymphocytes, and monocytes/macrophages) isolated from blood and milk samples of three dairy cows by using fluorescence-activated cell sorting. Afterward, those classifiers were applied to differentiate unlabeled blood and milk samples analyzed by DHM. A total of 70 blood and 70 milk samples were used. Those samples were collected from five clinically healthy cows at 14-time points within a study period of 26 days. The outcome was compared with the results of the same samples analyzed by flow cytometry and (in the case of blood samples) also to routine analysis in an external laboratory. Moreover, a standard vaccination was used as an immune stimulus during the study to check for changes in cell morphology or cell counts. When applied to isolated leukocytes, Random Forests performed best, with a specificity of 0.93 for blood and 0.84 for milk cells and a sensitivity of 0.90 and 0.81, respectively. Although the results of the three analytical methods differed, it could be demonstrated that a DHM analysis is applicable for blood and milk leukocyte samples with high reliability. Compared with the flow cytometric results, Random Forests showed an MAE of 0.11 (SD = 0.04), an RMSE of 0.13 (SD = 0.14), and an MRE of 1.00 (SD = 1.11) for all blood leukocyte counts and an MAE of 0.20 (SD = 0.11), an RMSE of 0.21 (SD = 0.11) and an MRE of 1.95 (SD = 2.17) for all milk cell populations. Further studies with larger sample sizes and varying immune cell compositions are required to establish method-specific reference ranges. Full article

Desertification poses a significant threat to dry and semi-arid regions worldwide, including Northeast Iran. This study investigates the impact of future climate and land-use changes on desertification in this region. Six remote sensing indices were selected to model desertification using four machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and Generalized Linear Models (GLM). To enhance the model’s reliability, an ensemble model was employed. Future climate and land-use scenarios were projected using the CNRM-CM6 model and Markov chain analysis, respectively. Results indicate that the RF and SVM models performed best in mapping current desertification patterns. The ensemble model highlights a 2% increase in decertified areas by 2040, primarily in the northwestern regions. The study underscores the importance of land-use change and climate change in driving desertification and emphasizes the need for sustainable land management practices and climate change adaptation strategies to mitigate future impacts. Full article

When the winch traction system of a carrier-based aircraft works under complex sea conditions, the rope and the tire forces are greatly changed compared with under simple sea conditions, and it poses a potential threat to the safety and stability of the aircraft’s traction system. The accurate calculation of the rope and tire forces of a carrier-based aircraft’s winch traction under complex sea conditions is an arduous problem. A novel method of dynamic analysis of the aircraft-winch-ship whole system under complex sea conditions is proposed. A multiple-frequency excitation is adopted to describe the complex sea conditions and the influences of pitching amplitude, and the rolling frequency on the traction dynamics of a carrier-based aircraft along the setting trajectory under complex sea conditions are studied. The advantages and disadvantages of a winch traction system with trajectory control and without trajectory control in complex sea conditions are analyzed. For realizing the trajectory control of the aircraft, the vector difference between the center of mass for the carrier-based aircraft and the position on the predetermined Bessel curve is calculated, so as to obtain the azimuth vector in the aircraft coordinate system. This research is innovative in the modeling of the whole system and the trajectory control of a carrier-based aircraft’s winch traction system under the complicated sea condition of the multi-frequency excitation. ADAMS (Automatic Dynamic Analysis of Mechanical System) is used to verify the correctness of the theoretical calculation for the winch traction. The results show that the complex sea environment has a certain influence on the winch traction safety of the aircraft; in the range of 10–15 s for the traction, the rope force amplitude of complex sea conditions under the multi-frequency excitation is 29.5% larger than that of the single-frequency amplitude, while the vertical force amplitude of the tire is 201.1% larger than that of the single-frequency amplitude. This research has important guiding significance for the selection of rope and tire models for a carrier-borne aircraft’s winch traction in complex sea conditions. Full article

Despite the seriousness of the disease carried by ticks, little is known about the Bourbon virus. Only three US states have recorded human cases of Bourbon virus (BRBV) infection; in all cases, a tick bite was connected with the onset of the illness. The Bourbon virus (BRBV) belongs to the Orthomyxoviridae family and Thogotovirus genus, originating in the states of the US, i.e., Kansas, Oklahoma and Missouri. The growing rates of BRBV infections in various parts of the US highlight the necessity for a thorough analysis of the virus’s transmission mechanisms, vector types and reservoir hosts. Currently, there are no vaccines or efficient antiviral therapies to stop these infections. It is imperative to produce a vaccination that is both affordable and thermodynamically stable to reduce the likelihood of future pandemics. Various computational techniques and reverse vaccinology methodologies were employed to identify specific B- and T-cell epitopes. After thorough examination, the linker proteins connected the B- and T-cell epitopes, resulting in this painstakingly constructed vaccine candidate. Furthermore, 3D modeling directed the vaccine construct toward molecular docking to determine its binding affinity and interaction with TLR-4. Human beta-defensin was used as an adjuvant and linked to the N-terminus to boost immunogenicity. Furthermore, the C-IMMSIM simulation resulted in high immunogenic activities, with activation of high interferon, interleukins and immunoglobulin. The results of the in silico cloning process for E. coli indicated that the vaccine construct will try its utmost to express itself in the host, with a codon adaptation CAI value of 0.94. A net binding free energy of −677.7 kcal/mol obtained during docking showed that the vaccine has a high binding affinity for immunological receptors. Further validation was achieved via molecular dynamic simulations, inferring the confirmational changes during certain time intervals, but the vaccine remained intact to the binding site for a 100 ns interval. The thermostability determined using an RMSF score predicted certain changes in the mechanistic insights of the loop region with carbon alpha deviations, but no major changes were observed during the simulations. Thus, the results obtained highlight a major concern for researchers to further validate the vaccine’s efficacy using in vitro and in vivo approaches. Full article

The majority of plant viruses rely on insect vectors for inter-plant transmission. Amid virus transmission, vector-borne viruses such as begomoviruses may significantly modulate host plants in various ways and, in turn, plant palatability to insect vectors. While many case studies on monopartite begomoviruses are available, bipartite begomoviruses are understudied. More importantly, detailed elucidation of the molecular mechanisms involved is limited. Here, we report the mechanisms by which an emerging bipartite begomovirus, the Sri Lankan cassava mosaic virus (SLCMV), modulates plant defenses against whitefly. SLCMV infection of tobacco (Nicotiana tabacum) plants significantly downregulated defenses against whitefly, as whitefly survival and fecundity increased significantly on virus-infected plants when compared to the controls. We then profiled SLCMV-induced transcriptomic changes in plants and identified a repertoire of differentially expressed genes (DEGs). GO enrichment analysis of DEGs demonstrated that the term defense response was significantly enriched. Functional analysis of DEGs associated with defense response revealed that four downregulated DEGs, including putative late blight resistance protein homolog R1B-17 (R1B-17), polygalacturonase inhibitor-like (PGI), serine/threonine protein kinase CDL1-like (CDL1), and Systemin B, directly contributed to plant defenses against whitefly. Taken together, our findings elucidate the role of novel plant factors involved in the modulation of plant defenses against whitefly by a bipartite begomovirus and shed new light on insect vector–virus–host plant tripartite interactions. Full article

Flood susceptibility prediction is complex due to the multifaceted interactions among hydrological, meteorological, and urbanisation factors, further exacerbated by climate change. This study addresses these complexities by investigating flood susceptibility in rapidly urbanising regions prone to extreme weather events, focusing on Gdańsk, Poland. Three popular ML techniques, Support Vector Machine (SVM), Random Forest (RF), and Artificial Neural Networks (ANN), were evaluated for handling complex, nonlinear data using a dataset of 265 urban flood episodes. An ensemble filter feature selection (EFFS) approach was introduced to overcome the single-method feature selection limitations, optimising the selection of factors contributing to flood susceptibility. Additionally, the study incorporates explainable artificial intelligence (XAI), namely, the Shapley Additive exPlanations (SHAP) model, to enhance the transparency and interpretability of the modelling results. The models’ performance was evaluated using various statistical measures on a testing dataset. The ANN model demonstrated a superior performance, outperforming the RF and the SVM. SHAP analysis identified rainwater collectors, land surface temperature (LST), digital elevation model (DEM), soil, river buffers, and normalized difference vegetation index (NDVI) as contributors to flood susceptibility, making them more understandable and actionable for stakeholders. The findings highlight the need for tailored flood management strategies, offering a novel approach to urban flood forecasting that emphasises predictive power and model explainability. Full article

Standardized suicide mortality rates per 100,000 (SMRs) in Japan consistently decreased from 2009 to 2019 but increased from 2020. The causes of these temporal SMR fluctuations remain to be clarified. Therefore, this study was conducted to identify the causalities underlying the recently transformed fluctuations of suicide mortality in Japan. Monthly suicide numbers disaggregated by sex and social standing, and political uncertainty indices, such as economic policy uncertainty (EPU) and government management instability (AENROP), were obtained from Japanese government databases. Interrupted time-series analysis was performed to analyze temporal fluctuations of SMRs disaggregated by sex/social standing associated with the three General Principles of Suicide Prevention Policy (GPSPP) periods and the COVID-19 pandemic. Panel data and vector autoregressive analyses were conducted to investigate causalities from political uncertainties to SMRs. During the first and second GPSPPs (2009–2017), all SMRs disaggregated by sex and social standing decreased, whereas those of unemployed females did not change. During the third GPSPP (2017–2022), decreasing trends in all SMRs were attenuated compared to previous periods. All female SMRs, except unemployed females, showed sharp increases synchronized with the pandemic outbreak. No male SMRs showed sharply increasing at the pandemic outbreak. SMRs of unemployed males/females drastically increased in the later periods of the pandemic, while SMRs of employed and multiple-person/single-person household males did not increase during the pandemic. SMR of unemployed males was positively related to AENROP but not EPU. Other male SMRs were positively related to EPU/AENROP. On the contrary, not all female SMRs were related to EPU/AENROP. Increasing AENROP generally contributed to increasing male SMRs throughout the observation period; however, susceptibility to AENROP and/or political information might have unexpectedly contributed to suppressing the sharply increasing male SMRs induced by large-scale social shocks (the COVID-19 pandemic outbreak) in Japan. Full article