bluuebunny/crossref_metadata_2025 huggingface dataset:
The impact of mobile-assisted swimming applications on intrinsic motivation and fear reduction in aquatic environments among students in the swimming course
Authors: Alkasasbeh Walaa Jumah , Alawamleh Thekra , Aloran Hasan , Farash Tamara , Orhan Bekir Erhan
Published: December 2024

Introduction

This study investigates the impact of mobile-assisted swimming applications on intrinsic motivation and fear reduction in aquatic environments among students enrolled in a swimming course. While technological tools are increasingly integrated into physical education settings, their effects on motivation and psychological barriers such as fear of water remain underexplored.

Methods

A total of 69 male and female students enrolled in the “Swimming Education and Training” course participated in the study. The Intrinsic Motivation Scale (IMS) and the Water Fear Assessment Questionnaire (WFAQ) were used to measure intrinsic motivation and water-related fear, respectively, before and after using a mobile-assisted swimming application. Data were analyzed to assess changes in motivation and fear, and potential relationships with demographic variables (gender, academic year, parental swimming experience, and university GPA) were explored.

Results

The study found no statistically significant differences in intrinsic motivation levels before and after the use of the mobile-assisted swimming application. However, a statistically significant reduction in water fear was observed following the intervention. No significant relationships were found between demographic factors and either motivation or fear reduction.

Discussion

The results suggest that while the mobile-assisted swimming application did not significantly impact intrinsic motivation, it was effective in reducing fear of water among students. This highlights the potential of mobile applications in addressing psychological barriers in aquatic environments, supporting skill acquisition, and enhancing the overall learning experience in swimming courses. The absence of demographic influences suggests that the application's benefits may be broadly applicable across different student groups.
How does agricultural land scale affect recycling behavior of agricultural wastes: evidence from CLES
Authors: Liu Jing , Liu Jin , Zhang Huan , Zhou Tianshu
Published: December 2024

The recycling of agricultural waste is an important measure for achieving green agricultural production. Existing studies have discussed the relationship between agricultural land scale and agricultural production from different angles, but ignored the disposal of agricultural waste. This study used China Land Economic Survey (CLES) from 2020 to 2021 and applied the probit model and the instrumental variable method to conduct the empirical analysis. The results showed a significant negative relationship between farmers' agricultural land scale and the recycling of agricultural waste. Heterogeneity analysis showed that the effect of less-developed areas was higher than that of relatively developed areas, and younger samples were less affected than the elderly. The mechanism analysis further pointed out that social norms and economic incentives can effectively promote the recycling of agricultural waste for farmers, given the scale of agricultural land. This study expands the relevant studies on agricultural waste disposal behavior, clarifies the impact and relevant mechanisms, and provides insights for realizing sustainable agricultural development.
Integrating Explanations into CNNs by Adopting Spiking Attention Block for Skin Cancer Detection
Authors: Nasir Inzamam Mashood , Tehsin Sara , Damaševičius Robertas , Maskeliūnas Rytis
Published: December 2024

Lately, there has been a substantial rise in the number of identified individuals with skin cancer, making it the most widespread form of cancer worldwide. Until now, several machine learning methods that utilize skin scans have been directly employed for skin cancer classification, showing encouraging outcomes in terms of enhancing diagnostic precision. In this paper, multimodal Explainable Artificial Intelligence (XAI) is presented that offers explanations that (1) address a gap regarding interpretation by identifying specific dermoscopic features, thereby enabling (2) dermatologists to comprehend them during melanoma diagnosis and allowing for an (3) evaluation of the interaction between clinicians and XAI. The specific goal of this article is to create an XAI system that closely aligns with the perspective of dermatologists when it comes to diagnosing melanoma. By building upon previous research on explainability in dermatology, this work introduces a novel soft attention mechanism, called Convolutional Spiking Attention Module (CSAM), to deep neural architectures, which focuses on enhancing critical elements and reducing noise-inducing features. Two instances of the proposed CSAM were placed inside the proposed Spiking Attention Block (SAB). The InceptionResNetV2, DenseNet201, and Xception architectures with and without the proposed SAB mechanism were compared for skin lesion classification. Pretrained networks with SAB outperform state-of-the-art methods on the HAM10000 dataset. The proposed method used the ISIC-2019 dataset for the crossdataset validation process. The proposed model provides attention regarding cancer pixels without using an external explainer, which proves the importance and significance of the SAB module.
A Comparative Transcriptomic and Proteomic Analysis of the Pileus of Agaricus bisporus During Its Different Developmental Phases
Authors: Feng Weilin , Guo Zier , Jin Qunli , Shen Yingyue , Song Tingting , Wang Mei , Zhang Jun , Fan Lijun , Cai Weiming
Published: December 2024

The analysis of the developmental stages of Agaricus bisporus, a major edible and medicinal mushroom, has always been an important focus in this research area. The process of the growth and development of edible mushrooms is complex and involves the regulation of multiple genes and metabolic pathways. Less data exist on the mechanism of their growth and development at the overall level. In this study, RNA sequencing analyses (RNA-Seq) and data-independent acquisition (DIA) proteomic analyses were carried out at the button phase (BP), harvesting phase (HP), and opening phase (OP) stages of Agaricus bisporus ‘Shuangbao 106’ to reveal the changes in gene expression during the different growth periods of its substrates. The authors screened and explored 3351 differentially expressed genes (DEGs) with a difference factor of ≥2.0, including 2080 up-regulated and 1271 down-regulated genes. After proteome sequencing, 1156 differentially expressed proteins (DEPs) were screened, including 524 up-regulated and 632 down-regulated genes. The expression in TPM of glycoside hydrolase, catalytic core, and chitinase II decreased during both the HP and OP compared with the BP. This may be because mushrooms require higher levels of glycoside hydrolase, catalytic core, and chitinase II activity during the BP to cope with external threats and the need for cell wall remodeling. Conversely, the growth of mushrooms slowed down and the need for cell wall remodeling decreased during the HP and OP, leading to a decrease in the expression of glycoside hydrolase, catalytic core, and chitinase II. This change is related to the need for environmental adaptation, immune defense, and cell wall remodeling, and may regulate the post-growth process of A. bisporus via the hydrolysis of cell wall chitin and glycoside hydrolase. It may also inhibit the growth of mushroom pilei.
Design of a Micro-Plant Factory Using a Validated CFD Model
Authors: Chen Xinxin , Hou Tengyuan , Liu Shulin , Guo Yongxiu , Hu Jianping , Xu Gaoming , Ma Guoxin , Liu Wei
Published: December 2024

The uniformity of the cultivation environment in a micro-plant factory plays a critical role in ensuring the consistent growth of seedlings, and an optimal airflow pattern is the key to maintaining environmental uniformity. This study applied computational fluid dynamics (CFD) modeling to compare the effects of six different ventilation modes on the microclimate within the cultivation space. In cases 1 and 2, the inlet was positioned at the top, while the outlets were located at both the bottom and the top of the side walls. For cases 3 to 6, a side-inlet and side-outlet ventilation system was employed across the three cultivation layers. Case 4 maintained consistent inlet and outlet airflow speeds, whereas cases 3, 5, and 6 featured airflow settings that either increased or decreased progressively from the top layer to the bottom. Notably, case 6 was characterized by a more compact arrangement of cultivation racks within the space, which were positioned closer to the outlet than in the other cases. In case 1, the air inlets were positioned at the top, while the outlets were located on both side walls at the lower layer of cultivation. In contrast, case 6 used a side-inlet and side-outlet ventilation strategy, in which the airflow speed of the inlets decreases progressively from the top to the bottom of the cultivation layers. Additionally, the cultivation racks in case 6 were arranged more compactly and positioned closer to the outlet of the cultivation space. The relative standard deviation (RSD) was used to evaluate the uniformity of the airflow velocity (m/s), temperature (K), and relative humidity (%) within the crop-growing area. The results indicated that, among all the scenarios, case 6 demonstrated the lowest RSD values for the airflow velocity, temperature, and relative humidity, with reductions of 18.34%, 0.12%, and 2.05%, respectively, compared to the control group (case 1). Based on the ventilation design of case 6, a micro-plant factory was developed featuring a bidirectional flow fan, air conditioning, and PWM fans for the coordinated control of air circulation within the seedling cultivation space, along with adjustable cultivation layer heights and shelf spacing. The accuracy of the CFD model for the micro-plant factory was validated with normalized root mean square error (NMSE) for cultivation layer heights of 250 mm, 300 mm, and 350 mm. The NMSE values comparing the simulated and measured results for the airflow velocity, temperature, and relative humidity were found to be 0.032, 0.0020, and 0.0022; 0.031, 0.0021, and 0.0018; and 0.046, 0.0021, and 0.0021, respectively. These findings indicate that the established CFD model can reliably predict the microenvironment within the micro-plant factory.
Adaptation and Grain Yield Stability Analysis of Winter Wheat Cultivars with and Without Fungicides Treatment from National Variety Trials in Sweden
Authors: Alemu Admas , Singh Pawan K. , Chawade Aakash
Published: December 2024

The multi-environment evaluation of wheat genotypes for grain yield is an integral part of germplasm enhancement since it plays a pivotal role in sustainable production. A total of 178 winter wheat cultivars were evaluated across 20 environments in Sweden from 2016 to 2020, with 52 to 59 cultivars tested per year as part of the Swedish National Trials (Sverigeförsöken). The genotypes were evaluated for grain yield performance with and without fungicide treatments. Additive main-effects and multiplicative interaction (AMMI) and genotype plus genotype-by-environment interaction (GGE) biplot methods were explored to estimate the genotype-by-environment interaction (GEI) for grain yield performance. ANOVA revealed a significant variation between treatments, genotypes in all years, and GEI in all years except 2018. The majority of the explained variance came from the environment, with a range of 61–88% across the five-year trial. The 20 sites were grouped into two to four mega-environments in the yearly studies. From the fungicide-treated trials, G 0512LT3, Informer, SG SU1563-15, LG Imposanto, and Pondus were identified as the most stable and high-yielding cultivars each year. From the fungicide-untreated trials, Informer, Ancher Greece, RGT Saki, and Pondus were the best-performing cultivars and could be good candidates for organic wheat cultivation.
The Formation of Rice Tillers and Factors Influencing It
Authors: Yuan Rong , Mao Yuxin , Zhang Dehai , Wang Shun , Zhang Huina , Wu Meng , Ye Miao , Zhang Zujian
Published: December 2024

The number of effective rice tillers determines the number of effective panicles and then affects the final yield. Rice tillering ability shows great differences among cultivars and under different environmental conditions, but the underlying mechanisms are not clear. The present paper investigated the formation of rice tillers and examined its genetic regulation, the effects of plant hormones, several environmental factors affecting rice tillering, and nitrogen’s regulation of tillers. Finally, the utilization of the tillering ability of weedy and wild rice was investigated. We concluded that many genes are involved in manipulating rice tillering, including MOC1, MOC3, FON1, LAX1, LAX2, APC/CTE, D3, D10, D14, D17, D27, and D53, by altering associated hormone contents or coding signal substances. The plant hormones auxin (IAA), gibberellin (GA), and strigolactone (SL) inhibit rice tillering, while cytokinin (CTK) promotes rice tillering. Weak light (light intensity is lower than 200 μmol m−2 s−1) and low and high temperatures (below 15 °C and above 38 °C) inhibit rice tillering, while optimized water management, such as alternate wetting and moderate drying irrigation, can greatly promote rice tillering. In addition, increasing plant nitrogen concentration can effectively improve rice tillers by adjusting multiple nitrogen metabolism enzymes. Weedy rice and some wild rice showed obvious superiority in tillering ability with respect to cultivated rice, but the underlying mechanisms are not clear and should be further explored. This study can provide theoretical guidance for the breeding and cultivation of high-yield and high-efficiency rice cultivars.
Effects of Multi Walled Carbon Nanotubes and Nano-SiO2 on Key Enzymes for Seed Germination and Endogenous Hormone Level in Maize Seedling
Authors: Wang Mingquan , Sun Guangyan , Li Guoliang , Hu Guanghui , Fu Lixin , Hu Shaoxin , Yang Jianfei , Wang Zhiguo , Gu Wanrong
Published: December 2024

Nanotechnology can improve crop yield and quality by improving seed germination and growth conditions. We chose multi walled carbon nanotubes (MWCNTs) and nano silica (nano-SiO2) for exploring the effects of different concentrations of MWCNTs and nano-SiO2 on key enzymes for germination and endogenous hormone level in maize. The results indicate that MWCNTs and nano-SiO2 can promote seed germination characteristics, such as the germination potential, germination rate, germination index, storage material transport rate, radicle and germ biomass of maize seeds. Amounts of 800 mg·L−1 MWCNTs and 1500 mg·L−1 nano-SiO2 showed a positive effect on germination index, and nano-SiO2 was better than MWCNTs in promoting germination effects. Most importantly, MWCNTs and nano-SiO2 can improve the activities of amylase in maize grain, cytochrome oxidase (COX) and alternating oxidase (AOX) in seed embryo and key enzymes of glycolysis, so as to accelerate the hydrolysis of carbohydrates such as starch, provide energy and material basis for seed germination, improve seed vitality and promote seed germination. MWCNTs and nano-SiO2 can enhance the content of key hormones in promoting roots and leaves, including decreased content of abscisic acid (ABA) and increased contents of methyl jasmonate (MeJA), auxin (IAA), gibberellin (GA), and zeaxanthin (ZR), which result directly in achieving an available balance of MeJA/ABA, GA/ABA, ZR/ABA, and IAA/ABA ratios between different hormone contents, providing support for the growth development of maize kernels and seedlings.
ACO-TSSCD: An Optimized Deep Multimodal Temporal Semantic Segmentation Change Detection Approach for Monitoring Agricultural Land Conversion
Authors: Zhang Henggang , Luo Kaiyue , Samat Alim , Zhu Chenhui , Jiao Tianyu
Published: December 2024

With the acceleration of urbanization in agricultural areas and the continuous changes in land-use patterns, the transformation of agricultural land presents complexity and dynamism, which puts higher demands on precise monitoring. And most existing monitoring methods are constrained by limited spatial and temporal resolution, high computational demands, and challenges in distinguishing complex land cover types. These limitations hinder their ability to effectively detect rapid and subtle land use changes, particularly in areas experiencing rapid urban expansion, where their shortcomings become more pronounced. To address these challenges, this study presents a multimodal deep learning framework using a temporal semantic segmentation change detection (TSSCD) model optimized with ant colony optimization (ACO) to detect and analyze agricultural land conversion in Zhengzhou City, a major grain-producing area in China. This model utilizes Landsat 7/8 imagery and Sentinel-2 satellite imagery from 2003 to 2023 to capture the spatiotemporal transformation of cropland driven by urban expansion, infrastructure development, and population changes over the last two decades. The optimized TSSCD model achieves superior classification accuracy, with the kappa coefficient improving from 0.871 to 0.892, spatial F1 score from 0.903 to 0.935, and temporal F1 score from 0.848 to 0.879, indicating its effectiveness in identifying complex land-use changes. The significant spatiotemporal variation characteristics of agricultural land conversion in Zhengzhou City from 2003 to 2023 were revealed through the TSSCD model, with transformations initially concentrated near Zhengzhou’s urban core and expanding outward, particularly to the east and north. These results highlight the effectiveness of remote sensing and deep learning techniques in monitoring agricultural land conversion.
Genetic Characterization of Spring Wheat Cultivars from a High-Altitude Region in China Using a 100K Single-Nucleotide Polymorphism Panel
Authors: Yao Yanlin , Liu Na , Ma Wenyan , Liang Yunlong , Li Yun , Cao Dong , Liu Baolong
Published: December 2024

Uncovering the genetic characteristics of important traits in wheat cultivars is essential for targeted wheat breeding. Here, a liquid 100K single-nucleotide polymorphism (SNP) chip panel, integrating markers of known function, was selected and used to analyze genetic characteristics for 115 spring wheat cultivars from a high-altitude region of China. A total of 102 reported functional markers closely related to important traits were identified, including 54 related to yield and grain quality and 33 associated with disease resistance and stress tolerance. Of the cultivars, 58.2% of cultivars contained excellent marker genes in the range of 20 to 29. Genetic structure analysis revealed that the cultivars were grouped into five subgroups. Genome-wide association studies identified 218 significant loci on 20 chromosomes, with the exception of chromosome 3D, associated with nine traits and which explained 14.15–29% of phenotypic variance, with 199 potential candidate genes being annotated for the nine traits studied. Notably, 21 previously unidentified candidate genes, with associated SNPs, were closely associated with seven traits, explaining 14.26–19.86% of the phenotypic variance. The current study revealed the genetic characteristics of spring wheat cultivars from a high-altitude region of China. This will provide a reference for spring wheat breeding for high-altitude regions and promote the fine-mapping of new genetic loci controlling important traits.
Comparison Study on the Trophic Niche of Red Pandas Using Stable Isotope Analysis
Authors: Zhang Yuyu , Lei Wanxin , Luo Wei , Dai Qinlong , Han Han , Nie Yonggang
Published: December 2024

The red panda (Ailurus), a rare and endangered mammal native to the Himalayan–Hengduan Mountains, has a specialized bamboo diet. Combining morphological and genomic evidence, red pandas have been classified as Ailurus fulgens and Ailurus styani. However, previous studies focused on ecological aspects such as foraging behaviors, habitat use and threats within specific distributions; hence, there is still a gap in quantitative comparative studies on the trophic niches of these two species. In this study, we calculated and compared the isotopic trophic niche widths of A. styani and A. fulgens by measuring carbon and nitrogen stable isotopes in hair keratin of 102 red pandas, then conducting a fecal analysis to explore the diet of a population. The results showed that (1) there was no significant difference in δ13C values between A. styani (−24.73 ± 1.26‰, N = 86) and A. fulgens (−24.43 ± 1.20‰, N = 16); however, A. styani had 1.4‰ higher average δ1⁵N value than that of A. fulgens, and the isotopic niche widths converted by Bayesian ellipse model were A. styani SEAC = 4.40‰2, A. fulgens SEAC = 4.70‰2, which might be caused by their lower and narrower altitude distribution. (2) Niche widths of three genetic populations in A. styani were XXL-LS (5.16‰2), EH-GLG (3.40‰2), QL (2.31‰2), and the comparison of the fecal composition suggested their diet diversity, which might imply a degree of competitive pressure with sympatric animals. (3) Sichuan red pandas occupied a lower trophic position compared to other herbivores but higher than giant pandas in the same ecosystem, and the niche width of red pandas was two times larger than that of sympatric giant pandas, which was related to the foraging strategies and microhabitat selection of the giant and red panda. This research provides basic stable isotopic data for red pandas, offers scientific support for the differentiated and refined conservation and management of the red panda and its habitat, and develops the application of stable isotope analysis in the ecological studies of endangered species.
Impact of Precision Feeding During Gestation on the Performance of Sows over Three Cycles
Authors: Cloutier Laetitia , Galiot Lucie , Sauvé Béatrice , Pierre Carole , Guay Frédéric , Dumas Gabrielle , Gagnon Patrick , Létourneau Montminy Marie-Pierre
Published: December 2024

This study evaluated the impact of precision feeding and bump feeding strategies during gestation on the reproductive performance of sows monitored over three cycles. Four treatments were compared: two constant-concentration feeding strategies (0.53% standardized ileal digestible lysine content; SID Lys) with the feed supply remaining constant (flat feeding; FF) or variable (bump feeding; BF) and two precision feeding strategies based on the InraPorc model considering performance by parity (precision feeding per parity; PFP) or the weight of each sow at breeding (precision feeding by individual; PFI). Sows were followed over three gestation and lactation cycles. In the first cycle (n = 502), the birth-to-weaning piglet mortality for PFP (8.7%) and PFI (10.3%) was lower than for BF (13.8%), with FF (11.3%) being intermediate (p = 0.001). No differences were observed in litter performance during the second cycle (n = 340). During the third cycle (n = 274), the stillborn rate was lower for PFP (6.2%) than for BF (9.1%) and FF (10.4%), with PFI (7.0%) being intermediate (p = 0.01). The BF strategy did not significantly improve sow or litter performance during lactation. Meanwhile, precision feeding could reduce nitrogen (10–13%) and total phosphorus intake (6–9%) with PFP and PFI strategies. Also, the results showed that it could even reduce piglet mortality during lactation.
Alterations in Ileal Microbiota and Fecal Metabolite Profiles of Chickens with Immunity to Eimeria mitis
Authors: Wang Zhongchuang , Shang Peiyao , Song Xingju , Wu Minghui , Zhang Tong , Zhao Qiping , Zhu Shunhai , Qiao Yu , Zhao Fanghe , Zhang Ruiting , Wang Jinwen , Yu Yu , Han Hongyu , Dong Hui
Published: December 2024

Coccidiosis, caused by different species of Eimeria parasites, is an economically important disease in poultry and livestock worldwide. This study aimed to investigate the changes in the ileal microbiota and fecal metabolites in chickens after repeated infections with low-dose E. mitis. The chickens developed solid immunity against a high dose of E. mitis infection after repeated infections with low-dose E. mitis. The composition of the ileal microbiota and the metabonomics of the Eimeria-immunized group and the control group were detected using 16S rRNA sequencing and liquid chromatography–mass spectrometry (LC-MS). The relative abundance of Neisseria, Erysipelotrichaceae, Incertae sedis, Coprobacter, Capnocytophaga, Bifidobacterium, and the Ruminococcus torques group declined in the Eimeria-immunized chickens, whereas Alloprevotella, Staphylococcus, Haemophilus, and Streptococcus increased. Furthermore, 286 differential metabolites (including N-undecylbenzenesulfonic acid, 1,25-dihydroxyvitamin D3, gluconic acid, isoleucylproline, proline, and 1-kestose) and 19 significantly altered metabolic pathways (including galactose metabolism, ABC transporters, starch and sucrose metabolism, the ErbB signaling pathway, and the MAPK signaling pathway) were identified between the Eimeria-immunized group and the control group. These discoveries will help us learn more about the composition and dynamics of the gut microbiota as well as the metabolic changes in chickens infected with Eimeria spp.
Appeasing Substance Administration at Feedlot Entry Impacted Temperament, Pen Behavior, Immunocompetence, and Meat Quality of Beef Heifers
Authors: Vieira Douglas Gomes , Vedovatto Marcelo , Ferreira Matheus Fellipe , Ranches Juliana , Cappellozza Bruno Ieda , de Sousa Osvaldo Alex , Canuto Nelson , de Nadai Bonin Gomes Marina , Fernandes Henrique Jorge
Published: December 2024

This experiment evaluated the effects of bovine appeasing substance (BAS) administration at feedlot entry on growth, temperament, inflammation, response to vaccination, behavior, carcass characteristics, and meat quality of beef heifers. Thirty heifers were weaned and assigned to (d 0): (1) BAS (n = 15; SecureCattle; IRSEA Group) or (2) Saline (n = 15). On d 0, heifers were also vaccinated against respiratory diseases and slaughtered on d 150. Administering BAS increased (p = 0.05) average daily gain from d 6 to 45, reduced (p ≤ 0.03) plasma ceruloplasmin and serum cortisol concentrations on d 15 and 45 and increased (p = 0.03) the response to vaccination. Additionally, BAS reduced (p < 0.01) the entry scores on d 6, 15, and 45 and reduced (p = 0.05) exit scores on d 2, 6, and 15. The BAS increased (p ≤ 0.04) walking, drinking, and eating time, and tended (p ≤ 0.10) to increase lying and ruminating time. Lastly, BAS tended (p ≤ 0.10) to increase the myofibrillar fragmentation index and reduce the thiobarbituric acid reactive substance concentration in meat. Thus, BAS administration increased growth, reduced stress, and inflammation, and improved immune responses, behavior, and meat quality of heifers.
Physical Measures of Welfare in Fin (Balaenoptera physalus) and Humpback Whales (Megaptera novangliae) Found in an Anthropized Environment: Validation of a First Animal-Based Indicator in Mysticetes
Authors: Boileau Anik , Blais Jonathan , Van Bressem Marie-Françoise , Hunt Kathleen E. , Ahloy-Dallaire Jamie
Published: December 2024

Anthropogenic activities impacting marine environments are internationally recognized as welfare issues for wild cetaceans. This study validates a first evidence-based physical indicator for the welfare assessment protocol of humpback (n = 50) and fin whales (n = 50) living in a highly anthropized environment. Visual assessments of body condition, skin health, prevalence of injuries and parasite/epibiont loads were performed using a species-specific multi-scale measuring tool. A total of 6403 images were analyzed (fin, n = 3152; humpback, n = 3251) and results were validated through reliability and positive discrimination statistical tests. Based on physical measures, welfare assessment results showed that 60% of humpback whales were considered in a good welfare state compared to only 46% of fin whales. Significant relationships were observed in both species, between environmental parameters like dissolved oxygen levels, and prevalence of cutaneous lesions like pale skin patch syndrome. Furthermore, animals with injuries due to anthropogenic activities were more likely to be in poorer body condition, suggesting chronic stress affecting welfare.
A High-Affinity Monoclonal Antibody Against the Pancreatic Ductal Adenocarcinoma Target, Anterior Gradient-2 (AGR2/PDIA17)
Authors: Robinson Reeder M. , Reyes Leticia , Christopher Benjamin N. , Duncan Ravyn M. , Burge Rachel A. , Siegel Julie , Nasarre Patrick , Wang Pingping , O’Bryan John P. , Hobbs G. Aaron , Klauber-DeMore Nancy , Dolloff Nathan G.
Published: December 2024

Background/Objectives: Anterior Gradient-2 (AGR2/PDIA17) is a member of the protein disulfide isomerase (PDI) family of oxidoreductases. AGR2 is up-regulated in several solid tumors, including pancreatic ductal adenocarcinoma (PDAC). Given the dire need for new therapeutic options for PDAC patients, we investigated the expression and function of AGR2 in PDAC and developed a novel series of affinity-matured AGR2-specific single-chain variable fragments (scFvs) and monoclonal antibodies. Results: We found that AGR2 was expressed in approximately 90% of PDAC but not normal pancreas biopsies, and the level of AGR2 expression correlated with increasing disease stage. AGR2 expression was inversely related to SMAD4 status in PDAC and colorectal cancer cell models and was secreted from cells into their media. In normal tissues, a high density of AGR2 was detected in the epithelium of cells in the digestive tract but was lacking in most other normal tissue systems. The addition of recombinant AGR2 to cell culture and genetic overexpression of AGR2 increased the adhesion, motility, and invasiveness of both human and mouse PDAC cells. Human phage display library screening led to the discovery of multiple AGR2-specific scFv clones that were affinity-matured to produce monoclonal antibody (MAb) clones with low picomolar binding affinity (S31R/A53F/Y). These high-affinity MAbs inhibited AGR2-mediated cell adhesion, migration, and binding to LYPD3, which is a putative cell surface binding partner of AGR2. Conclusions: Our study provides novel, high-affinity, fully human, anti-AGR2 MAbs that neutralize the pro-tumor effects of extracellular AGR2 in PDAC.
A Preliminary Lexicon for Juçara (Euterpe edulis Martius) Pulp: Possible Applications for Industry and Clinical Practice
Authors: Siqueira Ana Paula Silva , Siqueira Jéssika Martins , Lopes Mirella de Paiva , Carneiro Bárbara Silva , Pimentel Gustavo Duarte
Published: December 2024

Juçara is an important element for biodiversity in the Atlantic Forest, not only providing a rich source of nutritional and bioactive compounds, but also holding promising potential for sustainability. However, despite its virtues, there remains a dearth of studies fully exploring its potential. In our pioneering study, conducted using a panel of eight trained specialists, we delved into a sensory analysis of dehydrated juçara pulp, employing both descriptive analysis and the temporal dominance of sensations (TDS) technique. The findings revealed striking differences between juçara and açaí, not only in terms of flavor and aroma, but also in their potential to drive more mindful eating habits. By promoting the consumption of juçara, we are supporting the sustainability of the Atlantic Forest, where it is cultivated in an environmentally responsible manner. Thus, we are contributing to the preservation of this unique ecosystem and the well-being of local communities.
FGRL: Federated Growing Reinforcement Learning for Resilient Mapless Navigation in Unfamiliar Environments
Authors: Tian Shunyu , Wei Changyun , Li Yajun , Ji Ze
Published: December 2024

In this paper, we propose a federated growing reinforcement learning (FGRL) approach for solving the mapless navigation problem of unmanned ground vehicles (UGVs) facing cluttered unfamiliar obstacles. Deep reinforcement learning (DRL) has the potential to provide adaptive behaviors for autonomous agents through interactive learning, but standard episodic DRL algorithms often struggle with out-of-distribution observations. For navigation tasks, UGVs often encounter unfamiliar situations where novel obstacles differ from prior experience. To address this problem, the proposed FGRL approach enables multiple agents to obtain their individual navigation models in diverse scenarios, and achieves online knowledge aggregation to obtain an adaptive and resilient model that copes with unfamiliar uncertain obstacles. Specifically, during the learning process of navigation tasks, we introduce the growth rate of each agent’s local model based on the performance of consecutive learning rounds. Then, we weight the local model of each agent based on the growth rate to achieve knowledge aggregation in a shared model. We also consider a growth threshold to eliminate the interference of low-quality local models. We carry out extensive simulations to validate the proposed solution, and the results show that our approach can learn resilient behaviors of collision avoidance for UGVs to cope with never encountered and cluttered unfamiliar obstacles.
Spatial–Temporal Reconstruction of Trajectories in Free Space Using Automatic Target Position Detection Data
Authors: Chen Yang , Chen Xin , Bai Bin , Zheng Linjiang
Published: December 2024

The monitoring technology for targets such as aircraft and vehicles has rapidly developed in recent years and is widely used in national airspace security supervision, urban traffic supervision, and the tracking of special targets. However, the sparse trajectories of targets, primarily caused by the insufficient density of monitoring points, significantly reduce their usability. Therefore, it is important to reconstruct the target trajectories. Existing methods for the reconstruction of target trajectories often rely on topological data and convert trajectory reconstruction into a trajectory matching problem. Such methods heavily rely on topological data and cannot reconstruct trajectories in free space. To address this issue, we proposed a trajectory reconstruction method, named Prob-Attn, which does not rely on topological data and can accurately reconstruct target trajectories in free space. This method can be divided into two steps: first, a spatial trajectory construction module is proposed to determine the spatial trajectories of targets. Then, based on the reconstructed spatial trajectory of the target, this paper proposes a time series prediction model based on historical trajectories and an attention mechanism, which considers the impact of the target’s activity cycle and the surrounding status to predict the time series inside the trajectory. Finally, the proposed method is evaluated on real automatic vehicle detection datasets collected in Chongqing, China. The experimental results show that, compared with traditional methods, the proposed method can reconstruct the spatiotemporal trajectory of the target more accurately. The reconstructed trajectory data can be used for critical applications such as the intent and behavior analysis of key targets in national airspace and ground areas, providing valuable insights into security and safety.
A Stochastic Approach to the Analysis of Pollutant Emissions and Fuel Consumption of Motor Vehicles Driven in Real Traffic
Authors: Andrych-Zalewska Monika , Chłopek Zdzisław , Lasocki Jakub , Merkisz Jerzy , Pielecha Jacek
Published: December 2024

In real road traffic, combustion engines of motor vehicles operate in dynamic conditions. Under such conditions, significant time variability in the values describing engine operations is observed, especially in terms of rotational speed and torque. Therefore, it is possible to model such conditions as probabilistic and to treat the properties of combustion engines in these conditions as stochastic processes. This paper presents a stochastic approach to the analysis of pollutant emission and fuel consumption test results of a motor vehicle driven in real traffic conditions. The empirical data were obtained from tests conducted on a car with a spark-ignition engine equipped with mobile on-board measuring equipment. The scope of the investigations covered the domains of time, frequency and process values. In the time domain, statistical characteristics of the processes were analyzed to explore potential correlations between them. In the frequency domain, the power spectral density of the processes was determined. In the process values domain, the emphasis was placed on examining the probability density of processes. A large diversification of the determined characteristics was found, in particular for vehicle velocity, engine operating states and the processes of pollutant emissions and fuel consumption. For practical reasons, the results of the correlation studies were particularly valuable, as they enabled assessment of the effects of taking action to reduce emissions of various pollutants.
Efficiency of Biofortification with Zn and Se in Soybean: Yield and Overall Mineral Content in Plant
Authors: Lončarić Zdenko , Varga Ivana , Nemet Franjo , Perić Katarina , Jović Jurica , Zebec Vladimir , Ivezić Vladimir , Iljkić Dario , Galić Lucija , Sudarić Aleksandra
Published: December 2024

Since plant’s edible parts are one of the most important sources of nutrition, agronomic biofortification plays a huge role in overcoming mineral deficiency worldwide. The field-based research trial was set up in 2 years (2020 and 2021) with seven different treatments of foliar Zn and Se biofortification: 1. control (without Se or Zn solutions); 2. Se_1 treatment: 10 g/ha Se; 3. Se_2 treatment: 20 g/ha Se; 4. Se_3 treatment: 30 g/ha Se; 5. Zn_1 treatment: 3 kg/ha Zn; 6. Zn_2 treatment: 6 kg/ha Zn; 7. Se_3 Zn_2 treatment: 30 g/ha Se + 6 kg ha Zn. There were six soybean varieties of the 00 to I maturity group (Ika, Korana, Lucija, Sonja, Sunce, and Toma) included in the study, which originated from the Agricultural Institute Osijek, Croatia. After sampling the plants at the harvest, the macro- and micronutrient status in the grain, pods, leaves, and stems were determined, as well as nutrient removal by the plant. In general, biofortification treatment has a very significant influence (p < 0.001) on both Zn and Se accumulation in soybean grain and the removal of the elements within all above-ground organs. The highest increments of Zn in the soybean grain were determined at the Zn_2 treatment, which was 43% higher than the control treatment. The Toma variety accumulates the highest Zn in the grain (61.47 mg/kg), and the Lucija variety accumulates the highest Se (1070.71 µg/kg). The Se content in the soybean grain was the highest at the Se_3 treatment, where it was 53 times higher compared to the control. The linear regression showed that for each kg Zn and g Se applied, the grain status increased by 3.18 mg/kg and 338.71 µg/kg, respectively. The highest Zn nutrient use efficiency (NUE) of foliar biofortification for grain (2.6%) and vegetative mass (4.4%) was with 3 kg/ha (Zn_1). Generally, for all the Se treatments, it was found that the seed and vegetative mass yields of 4.0 t/ha have average Se NUE, around 38%, and vegetative mass of around 6%.
Pulpal Responses to Leukocyte- and Platelet-Rich Plasma Treatment in Mouse Models for Immediate and Intentionally Delayed Tooth Replantation
Authors: Quispe-Salcedo Angela , Suzuki-Barrera Kiyoko , Zapata-Sifuentes Mauricio , Watanabe Taisuke , Kawase Tomoyuki , Ohshima Hayato
Published: December 2024

This study aimed to evaluate the effect of leukocyte and platelet-rich plasma (L-PRP) on the pulpal healing process following immediate and intentionally delayed tooth replantation in mice. After the maxillary first molars of 3-week-old mice were extracted, the teeth were immersed for 1 min [immediate reimplantation (IR)] or 30 min [intentionally delayed reimplantation (IDR)] in phosphate-buffered saline (PBS) solution. The alveolar socket was filled with or without 1.5 μL of L-PRP [experimental or control groups (EG or CG)] followed by tooth replantation. Samples were collected from day 1 to week 4 after the operation, processed for histology, and evaluated by immunohistochemistry for Nestin and Ki-67 expression. Quantitative analysis revealed positive Nestin staining during pulpal healing in the EG at week 1 following IR and week 2 following IDR. Hard tissue deposition was significantly increased in the EG after IR at week 2. Cell proliferation was higher in the EG compared with that in the CG at week 1 and significantly decreased in the coronal pulp of the EG after the IDR at week 2. Our data suggest that treatment with L-PRP may have a positive effect on pulpal healing, even in teeth replanted after an extended extra-oral period.
Radon Exhalation Rate, Radioactivity Content, and Mineralogy Assessment of Significant Historical and Artistic Interest Construction Materials
Authors: Caridi Francesco , Chiriu Daniele , Pelo Stefania Da , Faggio Giuliana , Guida Michele , Messina Giacomo , Ponte Maurizio , Ruffolo Silvestro Antonio , Majolino Domenico , Venuti Valentina
Published: December 2024

In this paper, an investigation focused on assessing the radon exhalation, the natural radioactivity level, and the mineralogy of natural stones of particular historical–artistic interest employed as building materials was carried out. The Closed Chamber Method (CCM) with the Durridge Rad7 apparatus for short-lived radon progeny alpha spectrometry and High Purity Germanium (HPGe) gamma spectrometry were used to determine the radon exhalation rate and specific activities of 226Ra, 232Th, and 40K, respectively. Furthermore, several indices were evaluated to determine the radiological risk due to radiation exposure from the investigated natural stones, i.e., the absorbed gamma dose rate (D), the activity concentration index (ACI), and the alpha index (Iα). Finally, X-ray diffraction (XRD) and Micro-Raman Scattering (MRS) investigations were performed to correlate the chemical composition and mineralogical characteristics of natural stones with the radon exhalation rate and the natural radioactivity content. It is worth noting that the findings from this study can be used to guide future research into the background levels of radioactivity in stones used as construction materials.
Recent Developments in Materials Science for the Conservation and Restoration of Historic Artifacts
Authors: Doni Mihaela , Fierascu Irina , Fierascu Radu Claudiu
Published: December 2024

The preservation of cultural heritage artifacts presents complex challenges that require innovative solutions to prevent deterioration and extend the lifespan of priceless historical objects. Advances in materials science are revolutionizing the field of cultural heritage conservation and restoration, offering new techniques and materials that enhance the protection, stability, and aesthetic integrity of artifacts. This review explores cutting-edge technologies and materials developed for the conservation and restoration of heritage artifacts, including nanomaterials, smart materials, and bio-inspired polymers. Case studies highlight successful applications of these technologies on various artifacts, from ancient manuscripts to architectural heritage. This review also addresses the challenges associated with integrating modern materials into conservation practices, including compatibility, reversibility, and long-term effects. By synthesizing current research and technological advancements, this review aims to provide a comprehensive understanding of how advanced materials are transforming the conservation and restoration of cultural heritage, ensuring the preservation of human history for future generations.
Flue Gas Desulfurization in a Fixed-Bed Reactor: Mild-Condition Uptake Through Different Adsorbent Materials
Authors: Mancinelli Maura , Spagnoli Elena , Di Benedetto Francesco , Cristino Vito , Valt Matteo , Montegrossi Giordano , Barion Luca , Vanzetti Lia , Gaiardo Andrea , Vola Gabriele , Massa Mattia , Martucci Annalisa , Gherardi Sandro , Ardit Matteo
Published: December 2024

In quest of a substantial reduction in potentially toxic gas emissions into the air from industrial plants, dry flue gas desulfurization (FGD) systems offer several advantages, such as reduced operational costs, adaptability, ease of use, and the elimination of liquid waste. This study describes the development of a laboratory-scale pilot system for conducting SO2 abatement experiments using a fixed-bed reactor. To validate the experimental setup, the reactor was equipped with a control system for measuring and monitoring relative humidity, temperature, and total flux composition. The study utilized two standards, slaked lime and 13X zeolite, under identical experimental conditions to ensure comparability. This research will significantly advance the understanding of adsorbent materials for capturing low SO2 concentrations by measuring adsorption kinetics and equilibrium data. The findings highlight the impact of distinct morphological, chemical, and crystallographic properties on the efficiency of dry FGD systems.
SCENet: Small Kernel Convolution with Effective Receptive Field Network for Brain Tumor Segmentation
Authors: Guo Bin , Cao Ning , Zhang Ruihao , Yang Peng
Published: December 2024

Brain tumors are serious conditions, which can cause great trauma to patients, endangering their health and even leading to disability or death. Therefore, accurate preoperative diagnosis is particularly important. Accurate brain tumor segmentation based on deep learning plays an important role in the preoperative treatment planning process and has achieved good performance. However, one of the challenges involved is an insufficient ability to extract features with a large receptive field in encoder layers and guide the selection of deep semantic information in decoder layers. We propose small kernel convolution with an effective receptive field network (SCENet) based on UNet, which involves a small kernel convolution with effective receptive field shuffle module (SCER) and a channel spatial attention module (CSAM). The SCER module utilizes the inherent properties of stacking convolution to obtain effectively receptive fields and improve the features with a large receptive field extraction ability. CSAM of decoder layers can preserve more detailed features to capture clearer contours of the segmented image by calculating the weights of channels and spaces. An ASPP module is introduced to the bottleneck layer to enlarge the receptive field and can capture multi-scale detailed features. Furthermore, a large number of experiments were performed to evaluate the performance of our model on the BraTS2021 dataset. The SCENet achieved dice coefficient scores of 91.67%, 87.70%, and 83.35% for whole tumor (WT), tumor core (TC), and enhancing tumor (ET), respectively. The results show that the proposed model achieves the state-of-the-art performance compared with more than twelve benchmarks.
Adaptive Noise-Powered Diffusion Model for Efficient and Accurate Object Detection
Authors: Zou Xingyu , Han Kaixu , Zhang Xinle , Wang Wenhao , Wu Ning
Published: December 2024

Recent advancements in object detection, particularly with DiffusionDet, have demonstrated impressive performance. However, its reliance on numerous random noise-based object candidates limits its efficiency. To overcome this limitation, we propose DifAda, a novel object detection model that incorporates adaptive noise into the diffusion framework. DifAda employs an adaptive noise mechanism that blends random noise with latent codes, enhancing object candidate utilization and improving object localization. Our model features a simplified decoder structure by employing a single decoder layer and utilizes an adaptive interaction mechanism to further refine feature representations, leading to improved performance with fewer parameters. In addition, DifAda supports flexible speed–accuracy trade-offs through adjustable sampling and iteration steps, requiring no retraining. Experimental results across multiple benchmarks, including COCO and RUOD, demonstrate that DifAda achieves competitive performance with significantly fewer object candidates and parameters. Our findings suggest that DifAda represents a step forward in efficient and scalable object detection.