This study was conducted to compare and analyze whether Pilates exercise and yoga exercise help improve the performance of female fencers and prevent injury, and the dynamic balance test (LQ-YBT) and functional movement screening (FMS) test score of the elite adult female fencers were compared and analyzed as evaluation indicators. Participants were randomly classified into Pilates (n = 10) and yoga groups (n = 10), members of which took part in 50 min of exercise (5 min of warm-up, 40 min of main exercise, and 5 min of cool-down) twice weekly for eight weeks. The results obtained from this study were analyzed via independent t-test and 2-way ANOVA. The results were as follows: LQ-YBT measures (reaching distance) increased significantly for both groups, as did FMS scores (deep squat, hurdle step, inline lunge, shoulder mobility, active straight-leg raise, trunk-stability push-up, and rotary stability). These results suggest that Pilates exercise and yoga exercise might be likely effective in improving the performance of adult female fencers and injury prevention by increasing their dynamic balance ability and functional movement. Full article

In this paper, the notion of a cohesive and self-sufficient grid is proposed. Based on a cohesive and self-sufficient virtual microgrid, an active distribution network is optimally planned, and an optimal configuration of demand-side resources, distributed generations, and energy storage systems are generated. To cope with stochastic uncertainty from forecast error in wind speed and load, flexibility reserves are needed. In this paper, the supply relation between flexibility and uncertainty is quantified and integrated in an innovative index which is defined as cohesion. The optimization objectives are a minimized operational cost and system net-ability cohesion as well as self-sufficiency, which is defined as the abilities both to supply local load and to deal with potential uncertainty. After testing the optimal configuration in the PG&E 69 bus system, it is found that with a more cohesive VM partition, the self-sufficiency of VMs is also increased. Also, a case study on uncertainty-caused system imbalance is carried out to show how flexibility resources are utilized in real-time operational balance. Full article

China’s Ecological Protection Red Lines (ERLs) policy has proven effective in constructing regional ecological security patterns and protecting ecological space. However, the existing methods for the identification of high conservation value areas (HCVAs) usually use physical models, whose parameters and processes are complex and only for a single service, affecting the ERL delineation. In this study, the data-driven machine learning (ML) models were innovatively applied to construct a framework for ERL identification. First, the One-Class Support Vector Machine (OC-SVM) was used to generate negative samples from natural reserves and ecological factors. Second, the supervised ML models were applied to predict the HCVAs by using samples. Third, by applying the same ecological factors, the traditional physical models were used to assess the ecological services of the study area for reference and comparison. Take Chengdu–Chongqing Urban Agglomeration (CY) as a case study, wherein data from 11 factors and 1822 nature reserve samples were prepared for feasibility verification of the proposed framework. The results showed that the area under the receiver operating characteristic curve (AUC) of all ML models was more than 97%, and random forest (RF) achieved the best performance at 99.57%. Furthermore, the land cover had great contributions to the HCVAs prediction, which is consistent with the land use pattern of CY. High-value areas are distributed in the surrounding mountains of CY, with lush vegetation. All of the above results indicated that the proposed framework can accurately identify HCVAs, and that it is more suitable and simpler than the traditional physical model. It can help improve the effectiveness of ERL delimitation and promote the implementation of ERL policies. Full article

A predigested product from arachidonic acid oil (ARA) and docosahexaenoic acid (DHA) oil in a 2:1 (w/w) ratio has been developed and evaluated in an in vitro digestion model. To produce this predigested lipid mixture, first, the two oils were enzymatically hydrolyzed up to 90% of free fatty acids (FFAs) were achieved. Then, these two fatty acid (FA) mixtures were mixed in a 2:1 ARA-to-DHA ratio (w/w) and enzymatically esterified with glycerol to produce a mixture of FFAs, mono-, di-, and triacylglycerides. Different glycerol ratios and temperatures were evaluated. The best results were attained at 10 °C and a glycerol-to-FA molar ratio of 3:1. The bio-accessibility of this predigested mixture was studied in an in vitro digestion model. A total of 90% of the digestion product was found in the micellar phase, which contained 30% monoacylglycerides, more than 50% FFAs, and a very small amount of triacylglycerols (3% w/w). All these data indicate an excellent bio-accessibility of this predigested mixture. Full article

Despite their complex design, cycloidal gearboxes are characterized by high efficiency. Nevertheless, due to friction, some power is lost during gearbox operation. Basically, these losses occur in two structural nodes: the cycloid gearing and the output mechanism. Since the first of these nodes has been well discussed in the literature, the output mechanism will be discussed in this article. The design of the output mechanism has a significant impact on mechanical power losses. There are several mechanism design solutions. One of them is a mechanism with serially arranged rollers. Three solutions that are different in design but work identically will be discussed. Due to this affinity, a single, common mathematical model will be used to determine the value of losses. As will be shown, the value of losses is directly affected by the backlash, number, and diameter of the rollers used in the output mechanism and indirectly by the ratio and eccentricity of the cycloidal gearbox. Sample calculations were carried out using the developed model of mechanical power losses in the output mechanism. This made it possible to analyze the distribution of backlash created by manufacturing tolerances. It was also shown that the backlash has a significant effect on the number of rollers involved in torque transmission, as well as on the distribution of loads, contact pressures, and mechanical power losses. Full article

Foraging, the gathering of wild edibles for food and medicinal use, opens opportunities to connect with local environments and pursue sustainability and food sovereignty. We engage with insights from semi-structured qualitative interviews, participant observation, and site visits with individuals identifying as foragers and wildcrafters across Oklahoma to better understand foragers’ interactions with local wild food and foodscapes. We ask: Why do individuals in Oklahoma forage and/or wildcraft? How do foraging practices provide a pathway to support the creation of imagined foodways and foodscapes? We review the literature on foraging and foodways to situate foraging within alternative food systems and consider dimensions of sustainability and sovereignty within foodscapes. Foragers and wildcrafters reveal that their practices foster both tangible and non-tangible benefits, including deep connections with place and nature in the process of procuring wild edibles. While participants come to foraging in various ways, their strategies include engagement with sustainable practices and greater control and agency in food access. Building on the concept of ‘imagined foodways,’ we introduce ‘imagined foodscapes’ to illustrate foragers’ ability to create food practices and spaces based on their ideal methods of procuring and connecting with food. Full article

The 2017–2024 period has been prolific in the area of the algorithms for deep-based survival analysis. We have searched the answers to the following three questions. (1) Is there a new “gold standard” already in clinical data analysis? (2) Does the DL component lead to a notably improved performance? (3) Are there tangible benefits of deep-based survival that are not directly attainable with non-deep methods? We have analyzed and compared the selected influential algorithms devised for two types of input: clinicopathological (a small set of numeric, binary and categorical) and omics data (numeric and extremely high dimensional with a pronounced p >> n complication). Full article

Aerial photoelectric imaging payloads have become an important means of reconnaissance and surveillance in recent years. However, aerial images are easily affected by external conditions and have unclear edges, which greatly reduces the accuracy of imaging target recognition. This paper proposes the M-YOLOv5 model, which uses a shallow feature layer. The RFBs module is introduced to improve the receptive field and detection effect of small targets. In the neck network part, the BiFPN structure is used to reuse the underlying features to integrate more features, and a CBAM attention mechanism is added to improve detection accuracy. The experimental results show that the detection effect of this method on the DroneVehicle dataset is better than that of the original network, with the precision rate increased by 2.8%, the recall rate increased by 16%, and the average precision increased by 2.3%. Considering the real-time problem of target detection, based on the improved model, the Clight-YOLOv5 model is proposed, by lightweighting the network structure and using the depth-separable convolution optimization module. After lightweighting, the number of model parameters is decreased by 71.3%, which provides a new idea for lightweight target detection and proves the model’s effectiveness in aviation scenarios. Full article

Fire engineering endeavours to mitigate injury or the loss of life in the event of a fire. This is achieved primarily through fire prevention, containment, and extinguishment measures. Should prevention fail, the structural integrity of buildings, coupled with effective evacuation strategies, becomes paramount. While glass fibre-reinforced polymer (GFRP) materials have demonstrated efficacy in reinforcing concrete elements, their performance under fire conditions, notably in comparison to steel, necessitates a deeper understanding for structural applications. This study experimentally and numerically investigates the fire performance of GFRP-reinforced concrete (RC) columns subjected to only fire load without additional external loads. The research aims to ascertain the fire resistance based on the thickness of the concrete coating and the ultimate tensile strength of GFRP rebars after 90 min of fire exposure. Four GFRP-RC columns were subjected to a standardized fire curve on all sides in the experimental program. In the analytical program, a theoretical model was developed using the heat transfer module of the COMSOL software. The results of both analyses were very close, indicating the reliability of the procedure used. Based on the findings, recommendations regarding the fire resistance of GFRP-RC columns were formulated for structural applications. Results from this research provide the civil engineering community with data that will help them continue using FRP materials as internal reinforcement for concrete. Full article

Supporting refugee and migrant health has become a critical focus of healthcare policy. Developing and designing health literacy interventions that meet the needs of refugees and migrants is core to achieving this objective. This literature review sought to identify antecedents and consequences of health literacy among refugees and migrants during the first two years of the COVID-19 pandemic. We systematically searched nine electronic databases and numerous grey literature sources to identify studies published between December 2019 and March 2022. The antecedents (societal and environmental determinants, situational determinants, and personal determinants) and consequences of health literacy among refugees and migrants were mapped to a validated integrated health literacy model. Social and environmental determinants (n = 35) were the most reported antecedent influencing health literacy among refugees and migrants during the first two years of COVID-19. Language (n = 26) and culture (n = 16) were these determinants’ most frequently reported aspects. Situational determinants (n = 24) and personal determinants (n = 26) were less frequently identified factors influencing health literacy among refugees and migrants. Literacy (n = 11) and socioeconomic status (n = 8) were the most frequently reported aspects of personal determinants. Media use (n = 9) and family and peer influence (n = 7) were the most cited situational determinants reported. Refugees and migrants with higher levels of health literacy were more likely to use healthcare services, resulting in better health outcomes. The findings of this review reveal personal and situational factors that impacted health literacy among refugees and migrants during COVID-19 that require attention. However, the inadequate adaptation of health literacy interventions for linguistic and cultural diversity was a greater problem. Attention to this well-known aspect of public health preparedness and tailoring health literacy interventions to the needs of refugees and migrants during pandemics and other public health emergencies are paramount. Full article

In this article, a comparison of ionization techniques is provided and discussed. Conventional liquid chromatography with an electrospray ionization source shows higher robustness and repeatability in comparison with liquid chromatography coupled with a coordination ion spray (CIS-MS) source using silver nitrate as the dopant. However, the higher sensitivity and possibility to collect more data in untargeted applications mean CIS-MS is emerging as an instrument used in specific applications. During this research, the limit of detection (LOD) for GHRP-2 and GHRP-6 was established at 0.2 ng/mL, and the lower limit of quantification (LLOQ) was 0.5 ng/mL for CIS-MS. For conventional ESI-MS combined with solid-phase extraction on weak cation exchange columns, the limit of detection was found to be 1 ng/mL, and the lower limit of quantification was 2 ng/mL. Full article

Time series forecasting has been a challenging area in the field of Artificial Intelligence. Various approaches such as linear neural networks, recurrent linear neural networks, Convolutional Neural Networks, and recently transformers have been attempted for the time series forecasting domain. Although transformer-based architectures have been outstanding in the Natural Language Processing domain, especially in autoregressive language modeling, the initial attempts to use transformers in the time series arena have met mixed success. A recent important work indicating simple linear networks outperform transformer-based designs. We investigate this paradox in detail comparing the linear neural network- and transformer-based designs, providing insights into why a certain approach may be better for a particular type of problem. We also improve upon the recently proposed simple linear neural network-based architecture by using dual pipelines with batch normalization and reversible instance normalization. Our enhanced architecture outperforms all existing architectures for time series forecasting on a majority of the popular benchmarks. Full article

Biochar (Bc) and liquid vermicompost extracts (LVEs) are increasingly being used as biofertilizers in agriculture to promote soil-microbe-crop interactions. However, although both these products can potentially act synergistically due to their complementary characteristics, their co-application in different soils has not yet been investigated. Therefore, firstly, an LVE-activated biochar (B_LVE) was experimentally formulated and the persistence of LVE bacteria over a 60-day storage period was determined. The total number of LVE bacteria increased by 10-fold after 7 days and was stable throughout the entire biochar storage period. In addition, changes in the composition of the bacterial community were observed after 30 days of storage, indicating that taxa less represented in pure LVE may be advantaged upon biochar colonization. Secondly, a microcosm experiment was performed to evaluate whether the biological fertility and enzyme activities of two soils, differing in organic matter content, could be enhanced by the addition of LVE-activated biochar. In this experiment, three different doses of Bc, LVE, and B_LVE against the carbon-related biological fertility index (i.e., biological fertility index, BFI) and three enzyme activities over a 21-day incubation period were tested. The B_LVE treatment yielded the best results (i.e., BFI +32%, enzyme activities +38%). This indicates that Bc and LVEs can act synergistically to promote soil fertility, quality, and microbial activity. By integrating LVE-activated biochar into their soil management practices, farmers could achieve higher crop yields and healthier products. Full article

Due to the prevalent challenges of inadequate accuracy, unstandardized parameters, and suboptimal efficiency with regard to icing prediction, this study introduces an innovative online method for icing prediction based on Robust STL–BTSF and IBWO–LSSVR. Firstly, this study adopts the Robust Seasonal Decomposition of Time Series and Bilinear Temporal–Spectral Fusion (Robust STL–BTSF) approach, which is demonstrably effective for short-term and limited sample data preprocessing. Subsequently, injecting a multi-faceted enhancement approach to the Beluga Whale Optimization algorithm (BWO), which integrates a nonlinear balancing factor, a population optimization strategy, a whale fall mechanism, and an ascendant elite learning scheme. Then, using the Improved BWO (IBWO) above to optimize the key hyperparameters of Least Squares Support Vector Regression (LSSVR), a superior offline predictive part is constructed based on this approach. In addition, an Incremental Online Learning algorithm (IOL) is imported. Integrating the two parts, the advanced online icing prediction model for transmission lines is built. Finally, simulations based on actual icing data unequivocally demonstrate that the proposed method markedly enhances both the accuracy and speed of predictions, thereby presenting a sophisticated solution for the icing prediction on the transmission lines. Full article

Random polypropylene is considered an alternative material to regular polypropylene for applications where improved impact and creep resistance, as well as stiffness, are required. Random polypropylene nanocomposites reinforced with dimethyldichlorosilane-treated silica particles were prepared using meltmixing. The effect of varying the nanoparticles’ content on the structural, mechanical, damping and thermal behavior of the nanocomposites was investigated. The results indicated the improved deformation potential, fracture toughness, and energy storage capacity of the matrix with increasing the filler content. It was observed that the use of high filler fractions limited the reinforcing efficiency of the SiO₂ nanoparticles due to the formation of large agglomerates. The nanoparticles’ segregation was initially advised by modeling Young’s modulus but was also confirmed by electron imaging. Examination of the thermal properties of the nanocomposites indicated the limited effect of the nanoparticles on the melting behavior along with the thermal stability of the matrix. These results confirmed the usage of silica nanoparticles as a way of further improving the mechanical and thermomechanical properties of random polypropylene. Full article

Biogas is a renewable energy source generated through the anaerobic digestion (AD) of organic feedstocks. This study aims to quantify the biogas production potential (BPP) of fruit wastes via semi-continuous lab-scale mesophilic AD over a total of 100 days. The feed was composed of 80% banana peelings and 20% pineapple residues, mimicking the waste composition of a Costa Rican fruit processing facility used as a test case. The average loading rate of volatile suspended solids (VSS) corresponded to 3.6 kg VSS·m⁻³·d⁻¹. Biogas yield and composition were monitored, along with the concentration of ammonium, volatile fatty acids, and pH. Discounting the start-up phase, the BPP averaged to 526 L_N (kg VSS)⁻¹ with a methane concentration of around 54%, suggesting suitability of the substrate for AD. We calculated that if upscaled to the Costa Rican test case facility, these values translate into a gross average heat and electricity production via AD of around 5100 MWh_el·a⁻¹ and 5100 MWh_th·a⁻¹, respectively. Deducting self-consumption of the AD treatment, this is equivalent to 73% of the facility’s electricity demand, and could save about 450,000 L of heavy oil per year for heat generation. To circumvent nitrogen shortage, the addition of a co-substrate such as dry manure seems advisable. Full article

Water scarcity is a critical abiotic stress factor for plants in arid and semi-arid regions, impacting crop development and production yield and quality. Monitoring water stress at finer scales (e.g., farm and plant), requires multispectral imagery with thermal capabilities at centimeter resolution. This study investigates drought stress in pistachio trees in a farm located in Yazd province, Iran, by using Unmanned Aerial Vehicle (UAV) images to quantify evapotranspiration and assess drought stress in individual trees. Images were captured on 10 July 2022, using a Matrix 300 UAV with a MicaSense Altum multispectral sensor. By employing the Surface Energy Balance Algorithm for Land (SEBAL), actual field evapotranspiration was accurately calculated (10 cm spatial resolution). Maps of the optimum crop coefficient (K_c) were developed from the Normalized Difference Vegetation Index (NDVI) based on standard evapotranspiration using the Food and Agriculture Organization (FAO) 56 methodology. The comparison between actual and standard evapotranspiration allowed us to identify drought-stressed trees. Results showed an average and maximum daily evaporation of 4.3 and 8.0 mm/day, respectively, in pistachio trees. The real crop coefficient (K_c) for pistachio was 0.66, contrasting with the FAO 56 standard of 1.17 due to the stress factor (K_s). A significant correlation was found between K_c and NDVI (R² = 0.67, p < 0.01). The regression model produced a crop coefficient map, valuable to support precise irrigation management and drought prevention, considering the heterogeneity at the farm scale. Full article

Calmodulin (Calm), a crucial Ca²⁺ sensor, plays an important role in calcium-dependent signal transduction cascades. However, the expression and the relevance of Calm in stress and immune response have not been characterized in Megalobrama amblycephala. In this study, we identified the full-length cDNA of Calm (termed MaCalm) in blunt snout bream M. amblycephala, and analyzed MaCalm expression patterns in response to cadmium and Aeromonas hydrophila challenges. MaCalm was 1603 bp long, including a 5′-terminal untranslated region (UTR) of 97 bp, a 3′-terminal UTR of 1056 bp and an open reading frame (ORF) of 450 bp encoding a polypeptide of 149 amino acids with a calculated molecular weight (MW) of 16.84 kDa and an isoelectric point (pI) of 4.09. Usually, MaCalm contains four conservative EF hand motifs. The phylogenetic tree analysis indicated that the nucleotide sequence of MaCalm specifically clustered with Ctenopharyngodon idella with high identity (98.33%). Tissue distribution analysis demonstrated that the ubiquitous expression of MaCalm mRNA was found in all tested tissues, with the highest expression in the brain and the lowest expression in muscle. MaCalm showed significant upregulation at 14 d and 28 d post exposure to varying concentrations of cadmium in the liver; HSP70 transcripts in the liver significantly upregulated at 14 d post exposure to different concentrations of cadmium. Moreover, in response to the A. hydrophila challenge in vivo, MaCalm transcripts in the liver first increased and then decreased, but MaCalm transcripts in the kidney declined gradually with prolonged infection. After the A. hydrophila challenge, the expression level of HSP70 was significantly downregulated at 24 h in the liver and its expression level was notably downregulated at 12 h and at 24 h in the kidney. Collectively, our results suggest that MaCalm possesses vital roles in stress and immune response in M. amblycephala. Full article

Climate change poses significant challenges to agricultural productivity, making the efficient management of water resources essential for sustainable crop production. The assessment of plant water status is crucial for understanding plant physiological responses to water stress and optimizing water management practices in agriculture. Proximal and remote sensing techniques have emerged as powerful tools for the non-destructive, efficient, and spatially extensive monitoring of plant water status. This review aims to examine the recent advancements in proximal and remote sensing methodologies utilized for assessing the water status, consumption, and irrigation needs of fruit tree crops. Several proximal sensing tools have proved useful in the continuous estimation of tree water status but have strong limitations in terms of spatial variability. On the contrary, remote sensing technologies, although less precise in terms of water status estimates, can easily cover from medium to large areas with drone or satellite images. The integration of proximal and remote sensing would definitely improve plant water status assessment, resulting in higher accuracy by integrating temporal and spatial scales. This paper consists of three parts: the first part covers current plant-based proximal sensing tools, the second part covers remote sensing techniques, and the third part includes an update on the on the combined use of the two methodologies. Full article

As water temperatures rise in streams due to global temperature variations, dams, and increased water usage, native fish species face uncertain futures. Our study defines the thermal limits of flannelmouth sucker larvae. By raising sucker eggs at three acclimation temperatures (11 °C, 16 °C, and 22 °C), we defined ideal conditions for larval survival and the temperature tolerance range using critical thermal maximum (CTMax) and minimum (CTMin) trials. Larvae survived best at 16 °C. Within our three acclimation temperatures, our data suggest that larvae can survive static temperatures between 6.9 °C and 26.4 °C. Beyond an upper temperature of 34.8 °C and a lower temperature of 6.3 °C, these fish may fail to adapt. While flannelmouth suckers withstand high temperatures, even small temperature decreases prove detrimental. By defining the temperature limits of the flannelmouth sucker, we can make informed management decisions to preserve the populations of this desert fish. Full article

Hansenula polymorpha is a non-conventional and thermo-tolerant yeast that is well-known for its use in the industrial production of recombinant proteins. However, research to evaluate this yeast’s potential for the high-temperature fermentation of sugar to produce alcohols for biofuel applications is limited. The present work investigated a wild-type H. polymorpha strain (DSM 70277) for the production of ethanol at a temperature of 40 °C under limited oxygen presence by using a batch fermentation reactor. Fermentation experiments were performed using three types of sugar (glucose, fructose, xylose) as substrates with two initial inoculum concentrations (1.1 g·L⁻¹ and 5.0 g·L⁻¹). The maximum specific growth rates of H. polymorpha yeast were 0.121–0.159 h⁻¹ for fructose, 0.140–0.175 h⁻¹ for glucose, and 0.003–0.009 h⁻¹ for xylose. The biomass volumetric productivity was 0.270–0.473 g·L⁻¹h⁻¹ (fructose), 0.185–0.483 g·L⁻¹h⁻¹ (glucose), and 0.001–0.069 g·L⁻¹h⁻¹ (xylose). The overall yield of ethanol from glucose (0.470 g·g⁻¹) was higher than that from fructose (0.434 g·g⁻¹) and xylose (0.071 g·g⁻¹). The H. polymorpha yeast exhibited different behavior and efficacy regarding the use of glucose, fructose, and xylose as substrates for producing ethanol. The present knowledge could be applied to improve the fermentation process for valorization of waste biomass to produce bioethanol. Full article

Hydrolyzed royal jelly peptide (RJP) has garnered attention for its health-promoting functions. However, the potential applications of RJP in skincare have not been fully explored. In this study, we prepared RJP through the enzymatic hydrolysis of royal jelly protein with trypsin and investigated its antioxidant and anti-inflammatory properties on primary human dermal fibroblasts (HDFs). Our results demonstrate that RJP effectively inhibits oxidative damage induced by H₂O₂ and lipid peroxidation triggered by AAPH and t-BuOOH in HDFs. This effect may be attributed to the ability of RJP to enhance the level of glutathione and the activities of catalase and glutathione peroxidase 4, as well as its excellent iron chelating capacity. Furthermore, RJP modulates the NLRP3 inflammasome-mediated inflammatory response in HDFs, suppressing the mRNA expressions of NLRP3 and IL-1β in the primer stage induced by LPS and the release of mature IL-1β induced by ATP, monosodium urate, or nigericin in the activation stage. RJP also represses the expressions of COX2 and iNOS induced by LPS. Finally, we reveal that RJP exhibits superior antioxidant and anti-inflammatory properties over unhydrolyzed royal jelly protein. These findings suggest that RJP exerts protective effects on skin cells through antioxidative and anti-inflammatory mechanisms, indicating its promise for potential therapeutic avenues for managing oxidative stress and inflammation-related skin disorders. Full article