The foundry industry is responsible for the production of several potentially polluting and hazardous compounds. One of the major sources of pollution is the use of organic binders for the manufacturing of sand cores and sand moulds. To address this problem, in recent years, the use of low-emission products, known as inorganic binders, has been proposed. Their use in ferrous foundries, otherwise, is limited due to some problematic features that complicate their introduction in the manufacturing process, as often happens when a breakthrough innovation is introduced. In light of this, the aim of this work is to provide a Green Innovation Practice (GIP) to manage the introduction of green breakthrough innovations, as previously described, within an existing productive context. This practice was applied to better manage the experimental phase of the Green Casting Life Project, which aims to evaluate the possibility of using inorganic binders for the production of ferrous castings. After describing the state of the art of GIPs and their application in manufacturing contexts, the paper described the proposed GIP and its application to a real case consisting of testing inorganic binders in a ferrous foundry. Full article

Acid mine drainage (AMD) is an environmental issue linked with mining activities, causing the release of toxic water from mining areas. Polyethersulphone (PES) membranes are explored for AMD treatment, but their limited hydrophilicity hinders their performance. Chitosan enhances hydrophilicity, addressing this issue. However, the effectiveness depends on chitosan’s degree of deacetylation (DD), determined during the deacetylation process for chitosan production. This study optimized the chitin deacetylation temperature, alkaline (NaOH) concentration, and reaction time, yielding the highest chitosan degree of deacetylation (DD) for PES/chitosan membrane applications. Prior research has shown that high DD chitosan enhances membrane antifouling and hydrophilicity, increasing contaminant rejection and permeate flux. Evaluation of the best deacetylation conditions in terms of temperature (80, 100, 120 °C), NaOH concentration (20, 40, 60 wt.%), and time (2, 4, 6 h) was performed. The highest chitosan DD obtained was 87.11% at 80 °C, 40 wt. %NaOH at 4 h of chitin deacetylation. The PES/0.75 chitosan membrane (87.11%DD) showed an increase in surface hydrophilicity (63.62° contact angle) as compared to the pristine PES membrane (72.83° contact angle). This was an indicated improvement in membrane performance. Thus, presumably leading to high contaminant rejection and permeate flux in the AMD treatment context, postulate to literature. Full article

In this study, two by-products resulting from the processing of cherry (stems and pits) were used as natural coagulants to promote the valorization of these wastes and treat olive mill wastewater (OMW). The efficacy of the plant-based coagulants (PBCs) in the coagulation–flocculation–decantation process (CFD) was evaluated through the removal of turbidity, total suspended solids (TSS), total polyphenols (TPh), and dissolved organic carbon (DOC). The CFD process was demonstrated to be effective in turbidity and TSS reduction in OMW. Using cherry stems (CSs), these reductions were 65.2% of turbidity and 58.0% of TSS, while cherry pits (CPs) achieved higher reductions, 78.6% of turbidity and 68.2% of TSS. To improve the effectiveness of OMW treatment, mainly regarding the removal of TPh and DOC, the CFD process was complemented with the adsorption process (using bentonite clay). The adsorption capacity of bentonite was higher in acidic conditions (pH 3.0) and, with a dosage of 3.0 g L⁻¹, reached 17.3 mg of DOC and 13.8 mg of TPh per gram of bentonite. Several adsorption isothermal models were assessed, and the Langmuir (r² = 0.985), SIPS (r² = 0.992), and Jovanovic models (r² = 0.994) provided the best fittings. According to the optimal operational conditions defined throughout the present work, the combination of CFD and adsorption removals were as follows: (1) 98.0 and 91.3% of turbidity, (2) 80.8 and 81.2% of TSS, (3) 98.1 and 97.6% of TPh and (4) 57.9 and 62.2% of DOC, for CSs and CPs, correspondingly. Overall, the results suggest that cherry by-products can be used as low-cost natural coagulants and, when combined with another natural, abundant, and cheap material, such as bentonite clay, can be a sustainable alternative for treating OMW. Full article

Microgrids and hybrid renewable energy systems play a crucial role in today’s energy transition. They enable local power generation and distribution, reducing dependence on large centralized infrastructures, can operate independently or connected to a grid, and can provide backup power, thus increasing system resilience. In addition, they combine multiple renewable energy sources, such as solar, wind, hydro, and biomass, to maximize the efficiency and reliability of the supply, and are also adaptable to location-specific conditions, taking advantage of locally available energy resources and reducing the need for energy imports. Moreover, they contribute to decarbonization goals by offering a cleaner and more sustainable alternative. In this article, a documentary review is presented on the interaction of Homer Pro software 3.16.2 (July 2023), used for the design of hybrid renewable energy systems (HRES), with other methods of optimization or sizing. Allusion is made to the type of architecture in the most prominent clean and fossil source configurations, the levelized cost, net annual cost, and maintenance and capital investment cost. A comparison is made among the works reported in the last five years regarding the use of this software tool, based on load demand, geographical area, renewable energy sources, fossil sources, and objective functions, applied to the educational, rural, and industrial sectors. It is shown that India is one of the countries that has reported the most number of HRES techno-economic environmental analysis works, and that the case studies have focused approximately 47% on rural areas, 20% on educational agencies, 14% on commerce and industry, and 29% on urban buildings. Full article

Focusing on the trend of continuously seeking high-precision tree species classification results in small areas from the perspectives of sensors and classification algorithms. This study aimed to explore the effects of data sources, classifiers, and seasons on classification accuracy in regions with significant environmental variation, examining patterns of tree species classification to enhance the transferability of classification. Considering two typical forest distribution regions in the north and south of China, this study utilized the revisitation cycle and open-source advantages of Sentinel-2 and Landsat-8. Leveraging the Google Earth Engine (GEE) platform, this study captured spectral features, vegetation indices, and texture features for single seasonal and seasonal combination images. With the assistance of Sentinel-1A and SRTM (Shuttle Radar Topography Mission) DEM (Digital Elevation Model), backscattering coefficient features and topographical features were extracted and input with features captured from Sentinel-2 and Landsat-8 into three types of classifiers: random forest (RF), support vector machine (SVM), and gradient tree boosting (GTB) for major tree species classification. In this research, we discovered that the best classification for single season in the northern study area was spring, whereas, for the southern study area, it was winter. Seasonal combination images effectively improved the classification accuracy of single seasonal images, with Sentinel-2 imagery displaying better classification performance compared to Landsat-8, and the optimal classifier differing between the north and the south. The inclusion of topographical or backscattering coefficient features in the four-season combination imagery contributed to improvements in classification accuracy, with topographical features significantly enhancing the classification performance in the topographically varied southern study area. The evaluation of feature importance indicated that elevation was the most critical feature for classification, while spectral features and vegetation indices were also significant. In the southern study area with large topographical discrepancies, subdividing into different terrain units led to improved tree species classification accuracy in medium-altitude, gentle slope areas. These findings provide insights into the regularity of enhancing tree species classification accuracy in environmentally diverse areas through the use of multi-source remote sensing data and multi-seasonal imagery. Consequently, the results offer a reference for the identification of tree species across large areas and the creation of spatial distribution maps. Full article

Friedreich’s Ataxia (FRDA) stands out as the most prevalent form of hereditary ataxias, marked by progressive movement ataxia, loss of vibratory sensitivity, and skeletal deformities, severely affecting daily functioning. To date, the only medication available for treating FRDA is Omaveloxolone (Skyclarys^®), recently approved by the FDA. Missense mutations within the human frataxin (FXN) gene, responsible for intracellular iron homeostasis regulation, are linked to FRDA development. These mutations induce FXN dysfunction, fostering mitochondrial iron accumulation and heightened oxidative stress, ultimately triggering neuronal cell death pathways. This study amalgamated 226 FXN genetic variants from the literature and database searches, with only 18 previously characterized. Predictive analyses revealed a notable prevalence of detrimental and destabilizing predictions for FXN mutations, predominantly impacting conserved residues crucial for protein function. Additionally, an accurate, comprehensive three-dimensional model of human FXN was constructed, serving as the basis for generating genetic variants I154F and W155R. These variants, selected for their severe clinical implications, underwent molecular dynamics (MD) simulations, unveiling flexibility and essential dynamic alterations in their N-terminal segments, encompassing FXN42, FXN56, and FXN78 domains pivotal for protein maturation. Thus, our findings indicate potential interaction profile disturbances in the FXN42, FXN56, and FXN78 domains induced by I154F and W155R mutations, aligning with the existing literature. Full article

With mounting concerns about sustainability, significant attention has been directed toward research within the green industry domain. However, existing literature on initial public offerings (IPOs) has overlooked a crucial distinction: investors do not perceive all firms operating in green industries equally. Firms with green business models (GBMs) are more attractive to investors by providing positive signals of future growth potential and sustainability. To reveal this, the study investigates the relationship between GBMs and IPO success by Ordinary Least Squares (OLS) regression analysis. As the Asia-Pacific IPO market accounts for about 60% of IPO volume and value, with Korea actively participating in this global surge, the study used a sample of 150 firms that underwent IPOs between 2016 and 2019 on the Korea Securities Dealers Automated Quotations (KOSDAQ) market. We find evidence that firms with GBMs are more likely to achieve successful IPO outcomes, and GMC also plays a positive moderating role, enhancing the positive link between GBMs and IPO success. However, GMC alone had no significant effect. These findings imply that green signals positively contribute to a successful IPO and that each green signal can have different signaling effects, ultimately contributing to the field of sustainability through signaling theory. Full article

This contribution gives basic information about the mechanical behavior of the facial part of the human skull cranium, i.e., the splanchnocranium, associated with external loads and injuries caused mainly by brachial violence. The main areas suffering from such violence include the orbit, frontal, and zygomatic bones. In this paper, as a first approach, brachial violence was simulated via quasi-static compression laboratory tests, in which cadaveric skulls were subjected to a load in a testing machine, increasing till fractures occurred. The test skulls were also used for research into the dynamic behavior, in which experimental and numerical analyses were performed. A relatively high variability in forces inducing the fractures has been observed (143–1403 N). The results lay the basis for applications mainly in forensic science, surgery, and ophthalmology. Full article

The intestinal tract of humans harbors a dynamic and complex bacterial community known as the gut microbiota, which plays a crucial role in regulating functions such as metabolism and immunity in the human body. Numerous studies conducted in recent decades have also highlighted the significant potential of the gut microbiota in promoting human health. It is widely recognized that training and nutrition strategies are pivotal factors that allow athletes to achieve optimal performance. Consequently, there has been an increasing focus on whether training and dietary patterns influence sports performance through their impact on the gut microbiota. In this review, we aim to present the concept and primary functions of the gut microbiota, explore the relationship between exercise and the gut microbiota, and specifically examine the popular dietary patterns associated with athletes’ sports performance while considering their interaction with the gut microbiota. Finally, we discuss the potential mechanisms by which dietary patterns affect sports performance from a nutritional perspective, aiming to elucidate the intricate interplay among dietary patterns, the gut microbiota, and sports performance. We have found that the precise application of specific dietary patterns (ketogenic diet, plant-based diet, high-protein diet, Mediterranean diet, and high intake of carbohydrate) can improve vascular function and reduce the risk of illness in health promotion, etc., as well as promoting recovery and controlling weight with regard to improving sports performance, etc. In conclusion, although it can be inferred that certain aspects of an athlete’s ability may benefit from specific dietary patterns mediated by the gut microbiota to some extent, further high-quality clinical studies are warranted to substantiate these claims and elucidate the underlying mechanisms. Full article

The climate emergency is increasingly looming, and its consequences on nature and human systems are increasingly severe and pervasive, as reported by the world’s leading conferences and organizations on the subject. There appears to be an immediate need to adopt more sustainable behaviors in order to stem consequences that are becoming increasingly dramatic. In this regard, environmental psychology and other related disciplines have sought and still seek to understand how to translate the environmental concerns of individuals and communities into effective and efficient conservation and protection actions to contain the emergency and avoid further consequences. The contribution of psychological theories, particularly the transtheoretical model of change and the planned behavior model, appears very promising for assessing and promoting the potential for activation toward sustainability. The aim of this study was to develop a new conceptualization of the psychological construct of readiness to change (RtC) applied to sustainability issues and validated internally and externally through two separate studies (N1 = 228, N2 = 713). The sample for the two studies was recruited by distributing an anonymous online survey. For Study 1, we administered an online survey investigating basic sociodemographic characteristics and the preliminary set of 42 items of the readiness to change scale. For Study 2, the survey was composed of the following tools: a sociodemographic form, the readiness to change scale, a connectedness to nature scale, a climate change attitude survey, consumers’ perceived readiness toward green products, and a pro-environmental behaviors scale. Through exploratory factor analysis and confirmatory factor analysis, 29 items were selected from an initial set of 42. The 29 items were divided and organized into seven factors (namely: perceived importance of the problem/change, motivation, self-efficacy, effectiveness of the proposed solution, social support, action and involvement, and perceived readiness). Each factor showed adequate reliability (McDonald’s ω range: 0.74–0.87). Regarding external validity, the scale showed correlations—with typical to large effect sizes—with pro-environmental identity, green attitudes, sustainable intentions, and pro-environmental behaviors (PEBs) (i.e., conservation, environmental citizenship, food, transportation). Given the results obtained, we can say that the scale we constructed can infer the individual’s propensity to enact PEBs, and consequently it can give input to the implementation of interventions aimed at stimulating RtC and, therefore, sustainable behaviors. In conclusion, the scale appears valid and usable for assessing the activation potential of both individuals but also at the group and community levels—the latter factor being an important contribution to scientific research, since most of the instruments used to date fail to estimate this aspect. Full article

Intensity-modulated signals have the advantage of being directly detectable by the image sensor but have the drawback that the signal quality is easily deteriorated by crosstalk noise, in contrast to phase-modulated signals. In order to suppress the crosstalk noise, we propose a new signal arrangement for multilevel intensity-modulated signals. The concept of our method is to reduce the number of adjacent pixels that are a source of inter-pixel crosstalk noise and to minimize intensity modulation owing to interference with crosstalk noise. We have numerically and experimentally demonstrated that our method can reduce the error rate and improve the recording density compared to the conventional signal arrangement. Our proposed method offers a promising solution for achieving higher recording densities in intensity-modulated holographic data storage systems. Full article

Respiratory viruses cause airway inflammation, resulting in epithelial injury and repair. miRNAs, including miR-149-5p, regulate different pathological conditions. We aimed to determine how miR-149-5p functions in regulating pro-inflammatory IL-6 and p63, key regulators of airway epithelial wound repair, in response to viral proteins in bronchial (BEAS-2B) and alveolar (A549) epithelial cells. BEAS-2B or A549 cells were incubated with poly (I:C, 0.5 µg/mL) for 48 h or SARS-CoV-2 spike protein-1 or 2 subunit (S1 or S2, 1 μg/mL) for 24 h. miR-149-5p was suppressed in BEAS-2B challenged with poly (I:C), correlating with IL-6 and p63 upregulation. miR-149-5p was down-regulated in A549 stimulated with poly (I:C); IL-6 expression increased, but p63 protein levels were undetectable. miR-149-5p remained unchanged in cells exposed to S1 or S2, while S1 transfection increased IL-6 expression in BEAS-2B cells. Ectopic over-expression of miR-149-5p in BEAS-2B cells suppressed IL-6 and p63 mRNA levels and inhibited poly (I:C)-induced IL-6 and p63 mRNA expressions. miR-149-5p directly suppressed IL-6 mRNA in BEAS-2B cells. Hence, BEAS-2B cells respond differently to poly (I:C), S1 or S2 compared to A549 cells. Thus, miR-149-5p dysregulation may be involved in poly (I:C)-stimulated but not S1- or S2-stimulated increased IL-6 production and p63 expression in BEAS-2B cells. Full article

Surface-enhanced Raman spectroscopy (SERS) tagging using silica(SiO₂)@Ag nanoparticles (NPs) is easy to handle and is being studied in various fields, including SERS imaging and immunoassays. This is primarily due to its structural advantages, characterized by high SERS activity. However, the Ag NPs introduced onto the SiO₂ surface may undergo structural transformation owing to the Ostwald ripening phenomenon under various conditions. As a result, the consistency of the SERS signal decreases, reducing their usability as SERS substrates. Until recently, research has been actively conducted to improve the stability of single Ag NPs. However, research on SiO₂@Ag NPs used as a SERS-tagging material is still lacking. In this study, we utilized a Raman labeling compound (RLC) to prevent the structural deformation of SiO₂@Ag NPs under various conditions and proposed excellent SiO₂@Ag@RLC-Pre NPs as a SERS-tagging material. Using various RLCs, we confirmed that 4-mercaptobenzoic acid (4-MBA) is the RLC that maintains the highest stability for 2 months. These results were also observed for the SiO₂@Ag NPs, which were unstable under various pH and temperature conditions. We believe that SERS tags using SiO₂@Ag NPs and 4-MBA can be utilized in various applications on based SERS because of the high stability and consistency of the resulting SERS signal. Full article

Introduction: Pain perception, far from being a pathological mechanism, is a crucial protective stimulus to prevent additional injuries. Any disturbance in this complex system poses significant risks to individuals, affecting their quality of life and even their survival. Objective: This review aims to explore congenital insensitivity to pain, an extremely rare genetic disorder with an autosomal recessive pattern that results in the inability to perceive pain. We will focus on the well-known subtype, congenital insensitivity to pain with anhidrosis (CIPA). Our research seeks to update existing knowledge through a comprehensive literature review. Methodology: The review employs a systematic literature review, analyzing various sources and scientific documents, primarily emphasizing CIPA. The review follows the PROSPERO protocol, registered under CRD42023394489. The literature search was performed on the Scopus, PubMed, and Cinahl databases. Results: Our review reveals secondary complications associated with CIPA, such as recurrent bone fractures, temperature insensitivity, self-mutilation, and, occasionally, intellectual disabilities. The limited available information underscores the need for expanding our knowledge. Conclusions: In summary, CIPA, particularly, presents a significant medical challenge with adverse impacts on quality of life. Early diagnosis, education for families and healthcare professionals, and appropriate nursing care are essential for effective management. This review highlights the necessity of further research and awareness to enhance support for those affected. Full article

Methane (CH₄), a non-polar molecule characterized by a tetrahedral structure, stands as the simplest organic compound. Predominantly constituting conventional natural gas, shale gas, and combustible ice, it plays a pivotal role as a carbon-based resource and a key raw material in the petrochemical industry. In natural formations, CH₄ and H₂O coexist in a synergistic system. This interplay necessitates a thorough examination of the phase equilibrium in the CH₄-H₂O system and CH_4’s solubility under extreme conditions of temperature and pressure, which is crucial for understanding the genesis and development of gas reservoirs. This study synthesizes a comprehensive solubility database by aggregating extensive solubility data of CH₄ in both pure and saline water. Utilizing this database, the study updates and refines the key parameters of Henry’s law. The updated Henry’s law has a prediction error of 22.86% at less than 40 MPa, which is an improvement in prediction accuracy compared to before the update. However, the modified Henry’s law suffers from poor calculation accuracy under certain pressure conditions. To further improve the accuracy of solubility prediction, this work also trains a BP (Back Propagation) neural network model based on the database. In addition, MSE (Mean-Square Error) is used as the model evaluation index, and pressure, temperature, compression coefficient, salinity, and fugacity are preferred as input variables, which finally reduces the mean relative error of the model to 16.32%, and the calculation results are more accurate than the modified Henry’s law. In conclusion, this study provides a novel and more accurate method for predicting CH₄ solubility by comparing modified Henry’s law to neural network modeling. Full article

Frequency-modulated (FM) signals, prevalent across various applied disciplines, exhibit time-dependent frequencies and a multicomponent nature necessitating the utilization of time-frequency methods. Accurately determining the number of components in such signals is crucial for various applications reliant on this metric. However, this poses a challenge, particularly amidst interfering components of varying amplitudes in noisy environments. While the localized Rényi entropy (LRE) method is effective for component counting, its accuracy significantly diminishes when analyzing signals with intersecting components, components that deviate from the time axis, and components with different amplitudes. This paper addresses these limitations and proposes a convolutional neural network-based (CNN) approach for determining the local number of components using a time–frequency distribution of a signal as input. A comprehensive training set comprising single and multicomponent linear and quadratic FM components with diverse time and frequency supports has been constructed, emphasizing special cases of noisy signals with intersecting components and differing amplitudes. The results demonstrate that the estimated component numbers outperform those obtained using the LRE method for considered noisy multicomponent synthetic signals. Furthermore, we validate the efficacy of the proposed CNN approach on real-world gravitational and electroencephalogram signals, underscoring its robustness and applicability across different signal types and conditions. Full article

With the advancement of the rural revitalization strategy, counties have emerged as vital platforms for supporting rural revitalization, underscoring the increasing importance of sustainable development in their economies. It is imperative to evaluate the sustainable development potential of county economies and implement precise measures accordingly. This paper selects relevant economic development indicators from 2016 to 2020 for 76 counties in Gansu Province, constructs an evaluation system for assessing their sustainable development potential, and employs methods such as the Theil index, spatial autocorrelation, principal component analysis, and cluster grouping classification. The evaluation considers three aspects: the county economic development gap, the development potential score, and cluster analysis. The findings reveal that the economic development of Gansu Province’s counties exhibits spatial characteristics of multi-point flowering and scattered distribution, with relatively weak communication and development between surrounding counties. Over the five-year period, significant disparities in economic development among Gansu Province’s counties are evident. Liangzhou District ranks highest in county economic development, while other counties with robust economic development are primarily concentrated in the Lanzhou–Baiyin metropolitan area, the Tianshui metropolitan area, the west entrance of the Hexi Corridor economic belt, and the Qingyang–Pingliang group area. These counties exhibit a spatial pattern of agglomeration towards the central and eastern regions. Moreover, some counties in the southeastern region of Longdong demonstrate promising economic development potential, forming an initial scale of contiguous development. This indicates favorable prospects for sustainable development in the region’s county economy. Full article

In this paper, a novel input impedance analysis methodology based on Babinet’s principle to broaden bandwidth is proposed, and a broadband multiple-input and multiple-output (MIMO) antenna system is designed, fabricated, and measured for fifth-generation (5G) and Wireless Fidelity (Wi-Fi) 6E/7 mobile applications. By analyzing the input impedance of open-slot antennas and planar monopole antennas using numerical calculations, the characteristics of the input impedance can be obtained. We find that combining the two antenna types in parallel can significantly enhance the bandwidth. Then, the four-dimensional image calculated by MATLAB based on the parallel impedance formula is processed to validate the methodology. Thus, a broad antenna element based on the impedance property analysis methodology is achieved, which operates ranging from 2.6 GHz to 7.46 GHz. Moreover, the equivalent circuit of the antenna element is established to further verify the validity of the methodology. Finally, a broadband MIMO antenna system consisting of eight antenna elements is designed, fabricated, and measured, and the isolation performance is better than 12 dB. Acceptable total efficiency higher than 45% is also obtained with envelope correlation coefficients (ECCs) lower than 0.05. The proposed impedance property analysis methodology innovatively proposes a new way to increase bandwidth, which can be widely applied in various antenna designs. Also, reasonable results show that the proposed MIMO antenna system is a good candidate for 5G and Wi-Fi 6E/7 mobile applications. Full article

Neurodegenerative diseases represent a cluster of conditions characterized by the progressive degeneration of the structure and function of the nervous system. Despite significant advancements in understanding these diseases, therapeutic options remain limited. The medicinal mushroom Ganoderma lucidum has been recognized for its comprehensive array of bioactive compounds with anti-inflammatory and antioxidative effects, which possess potential neuroprotective properties. This literature review collates and examines the existing research on the bioactivity of active compounds and extracts from Ganoderma lucidum in modulating the pathological hallmarks of neurodegenerative diseases. The structural information and preparation processes of specific components, such as individual ganoderic acids and unique fractions of polysaccharides, are presented in detail to facilitate structure–activity relationship research and scale up the investigation of in vivo pharmacology. The mechanisms of these components against neurodegenerative diseases are discussed on multiple levels and elaborately categorized in different patterns. It is clearly presented from the patterns that most polysaccharides of Ganoderma lucidum possess neurotrophic effects, while ganoderic acids preferentially target specific pathogenic proteins as well as regulating autophagy. Further clinical trials are necessary to assess the translational potential of these components in the development of novel multi-target drugs for neurodegenerative diseases. Full article

Accurately identifying individual wildlife is critical to effective species management and conservation efforts. However, it becomes particularly challenging when distinctive features, such as spot shape and size, serve as primary discriminators, as in the case of Sika deer. To address this challenge, we employed four different Convolutional Neural Network (CNN) base models (EfficientNetB7, VGG19, ResNet152, Inception_v3) within a Siamese Network Architecture that used triplet loss functions for the identification and re-identification of Sika deer. Subsequently, we then determined the best-performing model based on its ability to capture discriminative features. From this model, we extracted embeddings representing the learned features. We then applied a Support Vector Machine (SVM) to these embeddings to classify individual Sika deer. We analyzed 5169 image datasets consisting of images of seven individual Sika deers captured with three camera traps deployed on farmland in Hokkaido, Japan, for over 60 days. During our analysis, ResNet152 performed exceptionally well, achieving a training accuracy of 0.97, and a validation accuracy of 0.96, with mAP scores for the training and validation datasets of 0.97 and 0.96, respectively. We extracted 128 dimensional embeddings of ResNet152 and performed Principal Component Analysis (PCA) for dimensionality reduction. PCA1 and PCA2, which together accounted for over 80% of the variance collectively, were selected for subsequent SVM analysis. Utilizing the Radial Basis Function (RBF) kernel, which yielded a cross-validation score of 0.96, proved to be most suitable for our research. Hyperparameter optimization using the GridSearchCV library resulted in a gamma value of 10 and C value of 0.001. The OneVsRest SVM classifier achieved an impressive overall accuracy of 0.97 and 0.96, respectively, for the training and validation datasets. This study presents a precise model for identifying individual Sika deer using images and video frames, which can be replicated for other species with unique patterns, thereby assisting conservationists and researchers in effectively monitoring and protecting the species. Full article

Over time, inclusive education has evolved in the search for more appropriate designations for its target audience, aiming to promote inclusive language and combat prejudiced and discriminatory behavior. More current paradigms, such as the Universal Design for Learning and the Multilevel Approach, propose completely abandoning the use of designations for students (1). This qualitative study uses a documentary analysis to examine how the statutes of 26 Portuguese public higher education institutions (HEIs) designate students who need academic support and to understand the educational concepts associated with these designations (2). The results revealed that Portuguese HEIs still adopt various student designations, often based on a medical model of classification and diagnosis. Furthermore, these designations do not fully encompass academic diversity, nor do they consider the diverse needs that students may present throughout their academic journey, which consequently limits access for all to inclusive practices in higher education (3). Considering these findings, there is an urgent need to abandon student designations in Portuguese HEIs and promote inclusive practices that cater to everyone, ensuring that students remain in and succeed in higher education, regardless of medical validation (4). Full article

Class III peroxidases (CIII PRXs) are plant-specific enzymes with high activity that play key roles in the catalysis of oxidation-reduction reactions. In plants, CIII PRXs can reduce hydrogen peroxide to catalyze oxidation–reduction reactions, thereby affecting plant growth, development, and stress responses. To date, no systematic analysis of the CIII PRX gene family in litchi (Litchi chinensis Sonn.) has been documented, although the genome has been reported. In this study, a total of 77 CIII PRX (designated LcPRX) gene family members were predicted in the litchi genome to provide a reference for candidate genes in the responses to abiotic stresses during litchi growth and development. All of these LcPRX genes had different numbers of highly conserved PRX domains and were unevenly distributed across fifteen chromosomes. They were further clustered into eight clades using a phylogenetic tree, and almost every clade had its own unique gene structure and motif distribution. Collinearity analysis confirmed that there were eleven pairs of duplicate genes among the LcPRX members, and segmental duplication (SD) was the main driving force behind the LcPRX gene expansion. Tissue-specific expression profiles indicated that the expression levels of all the LcPRX family members in different tissues of the litchi tree were significantly divergent. After different abiotic stress treatments, quantitative real-time PCR (qRT-PCR) analysis revealed that the LcPRX genes responded to various stresses and displayed differential expression patterns. Physicochemical properties, transmembrane domains, subcellular localization, secondary structures, and cis-acting elements were also analyzed. These findings provide insights into the characteristics of the LcPRX gene family and give valuable information for further elucidating its molecular function and then enhancing abiotic stress tolerance in litchi through molecular breeding. Full article