Food-producing animals are exposed to mycotoxins through ingestion, inhalation, or dermal contact with contaminated materials. This exposure can lead to serious consequences for animal health, affects the cost and quality of livestock production, and can even impact human health through foods of animal origin. Therefore, controlling mycotoxin exposure in animals is of utmost importance. A systematic literature search was conducted in this study to retrieve the results of monitoring exposure to mycotoxins in food-producing animals over the last five years (2019–2023), considering both external exposure (analysis of feed) and internal exposure (analysis of biomarkers in biological matrices). The most commonly used analytical technique for both approaches is LC-MS/MS due to its capability for multidetection. Several mycotoxins, especially those that are regulated (ochratoxin A, zearalenone, deoxynivalenol, aflatoxins, fumonisins, T-2, and HT-2), along with some emerging mycotoxins (sterigmatocystin, nivalenol, beauvericin, enniantins among others), were studied in 13,818 feed samples worldwide and were typically detected at low levels, although they occasionally exceeded regulatory levels. The occurrence of multiple exposure is widespread. Regarding animal biomonitoring, the primary objective of the studies retrieved was to study mycotoxin metabolism after toxin administration. Some compounds have been suggested as biomarkers of exposure in the plasma, urine, and feces of animal species such as pigs and poultry. However, further research is required, including many other mycotoxins and animal species, such as cattle and sheep. Full article

C/S1 basic leucine zipper (bZIP) transcription factors are essential for plant survival under energy deficiency. However, studies on the responses of C/S1-bZIPs to low energy in woody plants have not yet been reported. In this study, members of C/S1-bZIP subfamilies in Populus tomentosa were systematically analyzed using bioinformatic approaches. Four C-bZIPs and 10 S1-bZIPs were identified, and their protein properties, phylogenetic relationships, gene structures, conserved motifs, and uORFs were systematically investigated. In yeast two-hybrid assays, direct physical interactions between C-bZIP and S1-bZIP members were observed, highlighting their potential functional synergy. Moreover, expression profile analyses revealed that low energy induced transcription levels of most C/S1-bZIP members, with bZIP55 and bZIP21 (a homolog of bZIP55) exhibiting particularly significant upregulation. When the expression of bZIP55 and bZIP21 was co-suppressed using artificial microRNA mediated gene silencing in transgenic poplars, root growth was promoted. Further analyses revealed that bZIP55/21 negatively regulated the root development of P. tomentosa in response to low energy. These findings provide insights into the molecular mechanisms by which C/S1-bZIPs regulate poplar growth and development in response to energy deprivation. Full article

Knowledge of causal relationships is fundamental for understanding the dynamic mechanisms of ecological systems. To detect such relationships from multivariate time series, Granger causality, an idea first developed in econometrics, has been formulated in terms of vector autoregressive (VAR) models. Granger causality for count time series, often seen in ecology, has rarely been explored, and this may be due to the difficulty in estimating autoregressive models on multivariate count time series. The present research investigates the appropriateness of VAR-based Granger causality for ecological count time series by conducting a simulation study using several systems of different numbers of variables and time series lengths. VAR-based Granger causality for count time series (DVAR) seems to be estimated efficiently even for two counts in long time series. For all the studied time series lengths, DVAR for more than eight counts matches the Granger causality effects obtained by VAR on the continuous-valued time series well. The positive results, also in two ecological time series, suggest the use of VAR-based Granger causality for assessing causal relationships in real-world count time series even with few distinct integer values or many zeros. Full article

Microglia are key players in the brain’s innate immune response, contributing to homeostatic and reparative functions but also to inflammatory and underlying mechanisms of neurodegeneration. Targeting microglia and modulating their function may have therapeutic potential for mitigating neuroinflammation and neurodegeneration. The anti-inflammatory properties of essential oils suggest that some of their components may be useful in regulating microglial function and microglial-associated neuroinflammation. This study, starting from the ethnopharmacological premises of the therapeutic benefits of aromatic plants, assessed the evidence for the essential oil modulation of microglia, investigating their potential pharmacological mechanisms. Current knowledge of the phytoconstituents, safety of essential oil components, and anti-inflammatory and potential neuroprotective effects were reviewed. This review encompasses essential oils of Thymus spp., Artemisia spp., Ziziphora clinopodioides, Valeriana jatamansi, Acorus spp., and others as well as some of their components including 1,8-cineole, β-caryophyllene, β-patchoulene, carvacrol, β-ionone, eugenol, geraniol, menthol, linalool, thymol, α-asarone, and α-thujone. Essential oils that target PPAR/PI3K-Akt/MAPK signalling pathways could supplement other approaches to modulate microglial-associated inflammation to treat neurodegenerative diseases, particularly in cases where reactive microglia play a part in the pathophysiological mechanisms underlying neurodegeneration. Full article

Flexible job shop scheduling problem (FJSP), widely prevalent in many intelligent manufacturing industries, is one of the most classic problems of production scheduling and combinatorial optimization. In actual manufacturing enterprises, the setup of machines and the handling of jobs have an important impact on the scheduling plan. Furthermore, there is a trend for a cluster of machines with similar functionalities to form a work center. Considering the above constraints, a new order-driven multi-equipment work center FJSP model with setup and handling including multiple objectives encompassing the minimization of the makespan, the number of machine shutdowns, and the number of handling batches is established. An improved shuffled frog leading algorithm is designed to solve it through the optimization of the initial solution population, the improvement of evolutionary operations, and the incorporation of Pareto sorting. The algorithm also combines the speed calculation method in the gravity search algorithm to enhance the stability of the solution search. Some standard FJSP data benchmarks have been selected to evaluate the effectiveness of the algorithm, and the experimental results confirm the satisfactory performance of the proposed algorithm. Finally, a problem example is designed to demonstrate the algorithm’s capability to generate an excellent scheduling plan. Full article

Large-caliber and long-barrel weapons are important experimental devices for exploring the impact resistance and reliability of warheads. The force of impact of the muzzle jet has a significant influence on the overload resistance of the warhead and surrounding devices. The mechanism of motion of the body inside the tube cannot be ignored owing to the high kinetic energy at the muzzle. In this study, we designed the relevant experiment and a simulation model to analyze the structural characteristics and mechanism of evolution of the shock wave and the vortex structure in a muzzle jet. The aim was to examine the evolution of the shock wave with initial jet-induced interference. And we established three other simulation models to compare the similarities and differences between the results of the models. The results showed that, in the original complex model, the initial jet restricted the free expansion of the muzzle jet, and this led to many shock–shock collisions that retarded the development of the shock waves. Multiple reflected shock waves were thus formed under a high local pressure that distorted the shock structure, while the structure of the shock wave in the simplified models was clear and simple. The parameters of motion of the body changed by a little when the initial jet-induced interference was ignored. The difference in values of the strongest impact force measured at monitoring points far from the muzzle was small, with an error of about 2%, such that the simplified model without the initial jet could be used in place of the original complex model. The other simplified models yielded significant differences. Our results provide an important theoretical basis for further research on the muzzle jet and its applications in engineering. Full article

Optimizing process parameters to minimize defects remains an important challenge in injection molding (IM). Machine learning (ML) techniques offer promise in this regard, but their application often requires extensive datasets. Transfer learning (TL) emerges as a solution to this problem, leveraging knowledge from related tasks to enhance model training and performance. This study explores TL’s viability in predicting weld line visibility in injection-molded components using artificial neural networks (ANNs). TL techniques are employed to transfer knowledge between datasets related to different components. Furthermore, both source datasets obtained from simulations and experimental tests are used during the study. In order to use process simulations to obtain data regarding the presence of surface defects, it was necessary to correlate an output variable of the simulations with the experimental observations. The results demonstrate TL’s efficacy in reducing the data required for training predictive models, with simulations proving to be a cost-effective alternative to experimental data. TL from simulations achieves comparable predictive metric values to those of the non-pre-trained network, but with an 83% reduction in the required data for the target dataset. Overall, transfer learning shows promise in streamlining injection molding optimization and reducing manufacturing costs. Full article

Many researchers have studied the factors that impact on students’ entrepreneurial intention; however, findings are conflicting. The present study attempts, through an extensive review of the literature, to provide a holistic view and deeper knowledge of the most significant factors that influence university students’ decisions to be self-employed or to start a business. A systematic review as well as a bibliometric analysis of the literature was implemented, using a three-step literature mapping protocol to search, select, evaluate, and validate the literature by examining and analyzing numerous papers from the scientific community. The process ended up with 677 papers, from which the forty-three most cited were used as our research sample. Findings revealed that there are four primary categories of factors: the contextual factors, such as the economic, social, and political environment, the motivational factors, such as individuals’ personal needs, personality traits, and characteristics, and the factors related with the personal background of individuals such as family, education, and peers. We also examined the countries with the maximum number of papers on university students’ entrepreneurial intentions. These findings can be useful for policy makers and educators and will serve as a basis for future research, while they also contribute to the literature by highlighting the factors that most affect the entrepreneurial intention of university students. Full article

This study’s goals are divided into two categories. The first is to design and build an excavator equipped with parallel electrical linear actuators. The second is to generate and test a PSO-based and a PFM-based path for this excavator in order to save energy by reducing energy consumption, improve the digging accuracy by minimizing the deviation between the desired and dug surfaces of the ground, and prevent colliding with subsurface objects. For this purpose, computer vision was employed to improve monitoring and verification. Five types of experiments were carried out in this investigation. The first two and the other three examined the impact of energy conservation in PSO- and PFM-based path generation, respectively. Finally, the results from these experiments were compared to identify and show the effect of optimal path generation. Full article

SARS-CoV-2 vaccination-induced protection against infection is likely to be affected by functional antibody features. To understand the kinetics of antibody responses in healthy individuals after primary series and third vaccine doses, sera from the recipients of the two licensed SARS-CoV-2 mRNA vaccines were assessed for circulating anti-SARS-CoV-2 spike IgG levels and avidity for up to 6 months post-primary series and 9 months after the third dose. Following primary series vaccination, anti-SARS-CoV-2 spike IgG levels declined from months 1 to 6, while avidity increased through month 6, irrespective of the vaccine received. The third dose of either vaccine increased anti-SARS-CoV-2 spike IgG levels and avidity and appeared to enhance antibody level persistence—generating a slower rate of decline in the 3 months following the third dose compared to the decline seen after the primary series alone. The third dose of both vaccines induced significant avidity increases 1 month after vaccination compared to the avidity response 6 months post-primary series vaccination (p ≤ 0.001). A significant difference in avidity responses between the two vaccines was observed 6 months post-third dose, where the BNT162b2 recipients had higher antibody avidity levels compared to the mRNA-1273 recipients (p = 0.020). Full article

Background/Objectives: Lipid metabolism plays an important role in maternal health and fetal development. There is a gap in the knowledge of how lipid metabolism changes during pregnancy for Black women who are at a higher risk of adverse outcomes. We hypothesized that the comprehensive lipidome profiles would show variation across pregnancy indicative of requirements during gestation and fetal development. Methods: Black women were recruited at prenatal clinics. Plasma samples were collected at 8–18 weeks (T₁), 22–29 weeks (T₂), and 30–36 weeks (T₃) of pregnancy. Samples from 64 women who had term births (≥37 weeks gestation) were subjected to “shotgun” Orbitrap mass spectrometry. Mixed-effects models were used to quantify systematic changes and dimensionality reduction models were used to visualize patterns and identify reliable lipid signatures. Results: Total lipids and major lipid classes showed significant increases with the progression of pregnancy. Phospholipids and glycerolipids exhibited a gradual increase from T₁ to T₂ to T₃, while sphingolipids and total sterol lipids displayed a more pronounced increase from T₂ to T₃. Acylcarnitines, hydroxy acylcarnitines, and Lyso phospholipid levels significantly decreased from T₁ to T₃. A deviation was that non-esterified fatty acids decreased from T₁ to T₂ and increased again from T₂ to T₃, suggestive of a potential role for these lipids during the later stages of pregnancy. The fatty acids showing this trend included key fatty acids—non-esterified Linoleic acid, Arachidonic acid, Alpha-linolenic acid, Eicosapentaenoic acid, Docosapentaenoic acid, and Docosahexaenoic acid. Conclusions: Mapping lipid patterns and identifying lipid signatures would help develop intervention strategies to reduce perinatal health disparities among pregnant Black women. Full article

The chief goal of the Blood Profiling Atlas in Cancer (BloodPAC) consortium is to promote collaborative efforts that support the development and implementation of liquid biopsy tests. Here, we report the results of a pilot study conducted by three BloodPAC members that aimed to demonstrate a multisite liquid biopsy testing framework using longitudinal blood specimens from 38 patients with metastatic breast cancer. Three laboratories receiving identical samples from two clinical sites each applied a different targeted sequencing platform to analyze mutations in cell-free DNA (cfDNA). The resulting mutational profiles reflected common breast cancer alterations, including clinically actionable mutations for 40% of hormone- receptor-positive patients. In 12 genes with shared target regions across sequencing panels, perfect inter-assay concordance was also observed for mutations detected above the lowest common assay limit of detection. Whole-genome copy number profiling of cfDNA and circulating tumor cells (CTCs) further revealed marked heterogeneity in copy number alterations and cfDNA tumor fractions across patients. Additionally, comparison of tumor fraction and CTC abundance demonstrated the complementary nature of cfDNA and CTC analyses. Overall, the framework described in this study may serve as a resource for future trials aiming to identify multimodal liquid biopsy biomarkers to guide clinical care. Full article

With the aging of China’s population, the problem of pension security has become more and more prominent, and whether delayed retirement can effectively alleviate the pension fund gap and ensure the sustainability of the pension fund has become the focus of social concern. This study predicts the income and expenditure of urban workers’ basic pension insurance fund from 2021 to 2050 by constructing an actuarial model of pension insurance fund income and expenditure, and simulates the effect of delayed retirement policy. The prediction results show that under the existing system, the basic pension insurance fund for urban workers will have a shortfall for the first time in 2027, and the shortfall will expand year by year. Compared with the non-implementation of delayed retirement policy, the simulation of the implementation of a delayed retirement program delayed the emergence of the fund gap until 2029, and the forecast period of the pension fund gap significantly narrowed, indicating that delayed retirement policy has a certain positive impact on alleviating the pressure of pension payments, but delayed retirement cannot completely eliminate the pension fund gap. In view of this, this paper suggests that a progressive and flexible delayed retirement policy should be introduced as soon as possible to better adapt to the needs of different groups. At the same time, differentiated policies should be formulated for different groups of people and a pension incentive mechanism for delayed retirement should be set up to improve public acceptance of delayed retirement policy. In addition, delayed retirement policy should be combined with other measures, such as lowering the corporate contribution rate and enhancing the value-added capacity of the pension fund, so as to ensure the sustainability of the pension fund. Full article

Ensuring the tightness of buildings using self-adhesive tapes is one of the cost-effective, efficient, and reliable solutions. There is a lack of research, standards, and methodologies for construction adhesive tape, especially for assessing the functional properties of the tape after ageing. The aim of this work is to evaluate the tightness of different building surfaces and adhesive tape systems by conducting artificial ageing. It was found that adhesive tapes with an acrylic adhesive base ensured a fully sealed system. In all cases, tapes applied to surfaces such as plywood, gypsum plasterboard, cement-bonded particle board, plastered cement-bonded particle board, and plastic board provided sufficient sealing. The air permeability of the tapes on the OSB was two to seven times higher than that of the defined sealed system with other surfaces. In most cases, air permeability increased on OSB, gypsum plasterboard, and plastered cement-bonded particle board after ageing. The least problematic surface is the plastic board. In all tested cases, adequate sealing was observed after ageing, with only three of all tested tapes not providing sufficient bonding strength. Full article

The application of continuous glass fiber-reinforced polypropylene thermoplastic composites (GF/PP) is limited due to the inadequate flame retardancy of the polypropylene (PP) matrix. Apart from altering the composition of the flame retardants, the distribution modes of flame retardants also impact material performance. In this study, an alternative approach involving non-uniform distribution is proposed, namely, dispersed distribution, in which non-flame-retardant-content layers (NFRLs) and/or low-flame-retardant-content layers (LFRLs) are dispersed among high-flame-retardant-content layers (HFRLs). The mechanical, flame retardant and dielectric properties of GF/PP with intumescent flame retardant (IFR/GF/PP) are investigated comparatively under uniform, gradient, and dispersed distributions of the flame retardants. The results demonstrate that non-uniform distribution exhibits superior flame retardant performance compared to uniform distribution. Dispersed distribution enables IFR/GF/PP to attain enhanced mechanical properties and reduced dielectric constants while maintaining excellent flame-retardant properties. Full article

The efficient and timely identification of oil spill areas is crucial for ocean environmental protection. Synthetic aperture radar (SAR) is widely used in oil spill detection due to its all-weather monitoring capability. Meanwhile, existing deep learning-based oil spill detection methods mainly rely on the classical U-Net framework and have achieved impressive results. However, SAR images exhibit high noise, blurry boundaries, and irregular shapes of target areas, as well as speckles and shadows, which lead to the loss of performance in existing algorithms. In this paper, we propose a novel network architecture to achieve more precise segmentation of oil spill areas by reintroducing rich semantic contextual information before obtaining the final segmentation mask. Specifically, the proposed architecture can re-fuse feature maps from different levels at the decoder end. We design a multi-convolutional layer (MCL) module to extract basic feature information from SAR images, and a feature extraction module (FEM) module further extracts and fuses feature maps generated by the U-Net decoder at different levels. Through these operations, the network can learn rich global and local contextual information, enable sufficient interaction of feature information at different stages, enhance the model’s contextual awareness, and improve its ability to recognize complex textures and blurry boundaries, thereby enhancing the segmentation accuracy of SAR images. Compared to many U-Net based segmentation networks, our method shows promising results and achieves state-of-the-art performance on multiple evaluation metrics. Full article

Infrared (IR) imaging-based detection systems are of vital significance in the domains of early warning and security, necessitating a high level of precision and efficiency in infrared small moving target detection. IR targets often appear dim and small relative to the background and are easily buried by noise and difficult to detect. A novel high-speed spatial–temporal saliency model (HS-STSM) based on a guided filter (GF) is proposed, which innovatively introduces GF into IR target detection to extract the local anisotropy saliency in the spatial domain, and substantially suppresses the background region as well as the bright clutter false alarms present in the background. Moreover, the proposed model extracts the motion saliency of the target in the temporal domain through vectorization of IR image sequences. Additionally, the proposed model significantly improves the detection efficiency through a vectorized filtering process and effectively suppresses edge components in the background by integrating a prior weight. Experiments conducted on five real infrared image sequences demonstrate the superior performance of the model compared to existing algorithms in terms of the detection rate, noise suppression, real-time processing, and robustness to the background. Full article

Targeting the issues of slow speed and inadequate precision of optimal solution calculation for multi-user detection in complex noise environments, this paper proposes a multi-user detection algorithm based on a Hybrid Cheetah Optimizer (HCO). The algorithm first optimizes the control parameters and individual update mechanism of the Cheetah Optimizer (CO) algorithm using a nonlinear strategy to improve the uniformity and discretization of the individual search range, and then dynamically introduces a differential evolutionary algorithm into the improved selection mechanism of the CO algorithm, which is utilized to fine-tune the solution space and maintain the local diversity during the fast search process. Simulation results demonstrate that this detection algorithm not only realizes fast convergence with a very low bit error rate (BER) at eight iterations but also has obvious advantages in terms of noise immunity, resistance to far and near effects, communication capacity, etc., which greatly improves the speed and accuracy of optimal position solving for multi-user detection and can achieve the purpose of accurate solving in complex environments. Full article

Melatonin is ubiquitously present in all animals and plants, where it exerts a variety of physiological activities thanks to its antioxidant properties and its key role as the first messenger of extracellular signaling functions. Most of the clinical studies on melatonin refer to its widespread oral use as a dietary supplement to improve sleep. A far smaller number of articles describe the clinical applications of topical melatonin to treat or prevent skin disorders by exploiting its antioxidant and anti-inflammatory activities. This review focuses on the clinical studies in which melatonin was applied on the skin as a photoprotective, anti-aging, or hair growth-promoting agent. The methodologies and results of such studies are discussed to provide an overall picture of the state of the art in this intriguing field of research. The clinical studies in which melatonin was applied on the skin before exposure to radiation (UV, sunlight, and high-energy beams) were all characterized by an appropriate design (randomized, double-blind, and placebo-controlled) and strongly support its clinical efficacy in preventing or reducing skin damage such as dermatitis, erythema, and sunburn. Most of the studies examined in this review do not provide a clear demonstration of the efficacy of topical melatonin as a skin anti-aging or as a hair growth-promoting agent owing to limitations in their design and/or to the use of melatonin combined with extra active ingredients, except for one trial that suggests a possible beneficial role of melatonin in treating some forms of alopecia in women. Further research efforts are required to reach definitive conclusions concerning the actual benefits of topical melatonin to counteract skin aging and hair loss. Full article

The aim of this paper is to prove a theorem for holomorphic twisted quiver bundles over a special non-compact Gauduchon manifold, connecting the existence of $(\sigma ,\tau )$-Hermite–Yang–Mills metric in differential geometry and the analytic $(\sigma ,\tau )$-stability in algebraic geometry. The proof of the theorem relies on the flow method and the Uhlenbeck–Yau’s continuity method. Full article

The rising Greenhouse Gas (GHG) emissions stemming from the extensive use of automobiles across the globe represent a critical environmental challenge, contributing significantly to phenomena such as global warming and the deterioration of air quality. To address these challenges, there is a critical need for research and development in electric vehicles (EVs) and their associated charging infrastructure, including off-board and on-board chargers (OBCs). This paper aims to bridge the gaps in existing review literature by offering a comprehensive review of both integrated and non-integrated OBCs for EVs, based on the authors’ knowledge at the time of writing. The paper begins by outlining trends in the EV market, including voltage levels, power ratings, and relevant standards. It then provides a detailed analysis of two-level and multi-level power converter topologies, covering AC-DC power factor correction (PFC) and isolated DC-DC topologies. Subsequently, it discusses single-stage and two-stage non-integrated OBC solutions. Additionally, various categories of integrated OBCs (iOBCs) are explored, accompanied by relevant examples. The paper also includes comparison tables containing technical specifications and key characteristics for reference and analysis. Full article

Although the effect of campus landscape space on stress relief among college students has been confirmed, few existing studies have considered the impact on stress recovery from the perspective of factor combination, and the key visual elements and the most effective combination of visual elements to relieve stress are still unclear. This study attempts to conduct a natural experiment within Chinese campuses, measuring physiological indicators of stress such as heart rate (HR), frequency domain index of heart rate variability (LF/HF), skin conductance level (SCL), skin temperature (SKT), and respiratory rate (RESP) using physiological instruments. It explored the effects of visual elements and their combinations in campus landscape spaces on short-term stress relief among college students through semantic segmentation, multifactorial analysis of variance, and post hoc multiple comparison methods. Research results demonstrate that the presence of water elements in the field of vision can effectively improve the stress relief effects of landscape spaces. Reasonable combinations of natural landscape elements and artificial landscape elements in the design can also effectively promote stress relief among students. Building facade area and sky area, water area and sky area, and plant species and pavement area are three combinations of factors with the strongest interactive effects. “Natural water scenery” and “exquisite artificial” are two campus landscape design patterns most conducive to short-term stress relief. Full article