bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of Short-Term Differences in Concentrate Feeding on the Recovery of In Vivo Embryos in Hanwoo Donor Cows through Superovulation Treatment
Authors: Ha Seungmin , Kim Namtae , Park Mi-Ryung , Lee Seyoung , Cho Sang-Rae , Song Huimang , Jin Daehyeok , Kim Ui-Hyung , Ko Yeoung-Gyu
Published: September 2024

Superovulation is a technique used to increase the number of oocytes released for fertilization. This study investigated the effects of short-term differences in concentrate feed intake on in vivo embryo production through superovulation in indigenous Korean (Hanwoo) cows. The cows were given fresh water and hay ad libitum and randomly divided into three groups (control (CON, n = 9): 2.0 kg/day (unchanged diet); low concentrate (LC, n = 10): 0 kg/day; and high concentrate (HC, n = 8): 4.0 kg/day) according to the amount of formula they were fed. This feeding treatment began seven days before the start of the hormonal treatment for superovulation. From the results, the LC group had the greatest weight change and the lowest body condition score at harvest, followed by the CON and HC groups (p < 0.05). The LC group had the highest number of harvesting embryos, followed by the HC and CON groups (p < 0.05). Estradiol, progesterone, glucose, total cholesterol, high-density lipoprotein, low-density lipoprotein, total protein, and blood urea nitrogen concentrations did not differ between the groups, except for a temporary increase in the HC group on day 0. These findings suggest that more embryos may be harvested when short-term changes in concentrate intake are made during superovulatory responses in Hanwoo cows.
Antimicrobial Resistance and Use on Chinese Dairy Farms: Awareness and Opinions Regarding Selective Treatments of Farm Managers
Authors: Xiong Yindi , Barkema Herman W. , Yang Jingyue , Kastelic John P. , Nobrega Diego B. , Li Xiaoping , Tong Xiaofang , Fan Zhenying , Gao Jian
Published: September 2024

Background: In China’s expanding dairy industry, a lack of oversight regarding antimicrobial use and increasing antimicrobial resistance are evident. Selective treatments of dairy cows for clinical mastitis or dry cow therapy are proposed to promote judicious antimicrobial use without adversely impacting cattle health. These approaches have been successfully implemented on farms in other countries. Methods: On 28 October 2023, a 2-day in-person seminar was held in Beijing, China, on selective antimicrobial treatments of dairy cows for clinical mastitis or dry cow therapy on large Chinese dairy farms. Concurrently, a qualitative study involving 15 technical managers from the 13 largest Chinese dairy groups used focus group discussions and questionnaires to explore perspectives on selective treatments of dairy cows for clinical mastitis or dry cow therapy. The main outcomes assessed were opinions and concerns regarding implementing selective antimicrobial treatments. Results: Although there was diversity of cognition on AMR and selective treatments, the technical managers were generally positive regarding adoption of selective treatments. However, they expressed a need for more evidence and tools, including anticipated economic impacts, effects of delaying treatment until diagnosis, accurate interpretation of milk recording data, safe use of internal teat sealants, and spread of pathogens. Participants stressed the need for awareness, staff training, farm management, and China-specific standards, suggesting large-scale trials to assess efficacy of selective treatments. Conclusion: The findings revealed key challenges and barriers currently impeding selective AMU practices. These insights could inform efforts to promote judicious AMU on farms through targeted treatment regimens, reducing mounting selective pressure driving resistance.
Dietary Supplementation with 25-Hydroxyvitamin D3 on Reproductive Performance and Placental Oxidative Stress in Primiparous Sows during Mid-to-Late Gestation
Authors: Li Jing , Bi Qingyue , Pi Yu , Jiang Xianren , Li Yanpin , Li Xilong
Published: September 2024

The placenta plays a crucial role in nutrient transport and waste exchange between the dam and fetus, sustaining fetal growth. While the positive effects of 25-hydroxyvitamin D3 (25-OH-D3) on animal performance have been reported, its impact on placental function remains largely unknown. Therefore, this study aimed to investigate the effects of supplementing 25-OH-D3 in the diet of primiparous sows on reproductive performance, antioxidant capacity, placental oxidative stress, nutrient transport, and inflammatory response during mid-to-late gestation. A total of 45 healthy Landrace × Yorkshire primiparous sows on day 60 of gestation were selected and randomly allocated to three treatment groups based on body weight and backfat thickness: the control group (corn-soybean meal basal diet), the VD3 group (basal diet + 2000 IU VD3), and the 25-OH-D3 group (basal diet + 50 μg/kg 25-OH-D3). The results demonstrated that supplementation with 25-OH-D3 in the diet enhanced sows’ average litter weight and birth weight during mid-to-late gestation. Additionally, plasma malondialdehyde (MDA) concentrations in sows significantly decreased in the VD3 and 25-OH-D3 groups (p < 0.05). Furthermore, lower gene expressions of placental HO-1, GPX2, IL-8, and IL-6 were found in the VD3 or 25-OH-D3 groups (p < 0.05 or p < 0.10), while higher gene expressions of GLUT1 and SNAT2 in the placenta of sows were observed in the VD3 and 25-OH-D3 groups, respectively (p < 0.05). These findings indicate that the supplementation of VD3 and 25-OH-D3 in the diet of sows can improve their plasma oxidative stress status, enhance placental antioxidant capacity and nutrient transport, and reduce placental inflammatory responses, with more pronounced improvements in sow performance observed in sows fed diets supplemented with 25-OH-D3.
Actinidia chinensis Planch Ameliorates Photoaging in UVB-Irradiated NIH-3T3 Cells and SKH-1 Hairless Mice by Controlling the Reactive Oxygen Species/AKT Pathway
Authors: Jung Jong-Min , Kim Seo-Young , Kwon Oh-Yun , Lee Seung-Ho
Published: September 2024

In this study, we evaluated the antiphotoaging properties of Actinidia chinensis Planch (ACP) and the molecular mechanisms underlying its ability to prevent UVB-mediated photoaging. Administration of the ethanolic extract of ACP (EEACP) to the dorsal area of hairless mice effectively ameliorated UVB-mediated wrinkle formation, epidermal thickening, and loss of lipid droplets in the epidermis. Additionally, the UVB-induced loss of collagen content in the epidermis was significantly attenuated in mouse skin treated with EEACP. The expression of procollagen type 1 and metalloproteinase-1a, which are related to collagen content in the epidermis, was restored by EEACP treatment in UVB-irradiated mice and NIH-3T3 mouse skin fibroblast cells. Interestingly, EEACP effectively ameliorated UVB-induced reactive oxygen species overproduction. Furthermore, the activation/phosphorylation of AKT, rather than mitogen-activated protein kinases, has been identified as a major target of EEACP in preventing UVB-mediated photoaging. Additionally, N-(1 deoxy-1-fructosyl) valine and phenethylamine glucuronide were identified as analytical indicators of EEACP using high-performance liquid chromatography/mass spectrometry. These results suggest that EEACP can be developed as a functional natural agent capable of preventing photoaging by attenuating UVB-induced activation of the reactive oxygen species/AKT pathway.
Active Learning for Biomedical Article Classification with Bag of Words and FastText Embeddings
Authors: Cichosz Paweł
Published: September 2024

In several applications of text classification, training document labels are provided by human evaluators, and therefore, gathering sufficient data for model creation is time consuming and costly. The labeling time and effort may be reduced by active learning, in which classification models are created based on relatively small training sets, which are obtained by collecting class labels provided in response to labeling requests or queries. This is an iterative process with a sequence of models being fitted, and each of them is used to select query articles to be added to the training set for the next one. Such a learning scenario may pose different challenges for machine learning algorithms and text representation methods used for text classification than ordinary passive learning, since they have to deal with very small, often imbalanced data, and the computational expense of both model creation and prediction has to remain low. This work examines how classification algorithms and text representation methods that have been found particularly useful by prior work handle these challenges. The random forest and support vector machines algorithms are coupled with the bag of words and FastText word embedding representations and applied to datasets consisting of scientific article abstracts from systematic literature review studies in the biomedical domain. Several strategies are used to select articles for active learning queries, including uncertainty sampling, diversity sampling, and strategies favoring the minority class. Confidence-based and stability-based early stopping criteria are used to generate active learning termination signals. The results confirm that active learning is a useful approach to creating text classification models with limited access to labeled data, making it possible to save at least half of the human effort needed to assign relevant or irrelevant class labels to training articles. Two of the four examined combinations of classification algorithms and text representation methods were the most successful: the SVM algorithm with the FastText representation and the random forest algorithm with the bag of words representation. Uncertainty sampling turned out to be the most useful query selection strategy, and confidence-based stopping was found more universal and easier to configure than stability-based stopping.
Bootstrap and MRCD Estimators in Hotelling’s T2 Control Charts for Precise Intrusion Detection
Authors: Prasetya Ichwanul Kahfi , Ahsan Muhammad , Mashuri Muhammad , Lee Muhammad Hisyam
Published: September 2024

Intrusion detection systems (IDS) are crucial in safeguarding network security by identifying unauthorized access attempts through various techniques. Statistical Process Control (SPC), particularly Hotelling’s T2 control charts, is noted for monitoring network traffic against known attack patterns or anomaly detection. This research advances the domain by incorporating robust statistical estimators—namely, the Fast-MCD and MRCD (Minimum Regularized Covariance Determinant) estimators—into bootstrap-enhanced Hotelling’s T2 control charts. These enhanced charts aim to strengthen detection accuracy by offering improved resistance to outlier contamination, a prevalent challenge in intrusion detection. The methodology emphasizes the MRCD estimator’s robustness in overcoming the limitations of traditional T2 charts, especially in environments with a high incidence of outliers. Applying the proposed bootstrap-based robust T2 charts to the UNSW-NB15 dataset illustrates a marked enhancement in intrusion detection performance. Results indicate superior performance of the proposed method over conventional T2 and Fast-MCD-based T2 charts in detection accuracy, even in varied levels of outlier contamination. Despite increasing execution time, the precision and reliability in detecting intrusions present a justified trade-off. The findings underscore the significant potential of integrating robust statistical methods to enhance IDS effectiveness.
Health-Conscious Energy Management for Fuel Cell Hybrid Electric Vehicles Based on Adaptive Equivalent Consumption Minimization Strategy
Authors: Zhang Pei , Wang Yubing , Du Hongbo , Du Changqing
Published: September 2024

The energy management strategy plays an essential role in improving the fuel economy and extending the energy source lifetime for fuel cell hybrid electric vehicles (FCHEVs). However, the traditional energy management strategy ignores the lifetime of the energy sources for good fuel economy. In this work, an adaptive equivalent consumption minimization strategy considering performance degradation (DA-ECMS) is proposed by incorporating fuel cell and battery performance degradation models and establishing an optimal covariate predictor based on a long short-term memory (LSTM) neural network. The comparative simulations show that, compared with the adaptive equivalent consumption minimization strategy (A-ECMS), the DA-ECMS reduces the fuel cell stack voltage degradation by 17.1%, 23.2%, and 16.6% for the Worldwide Harmonized Light Vehicle Test Procedure (WLTP), the China Light-Duty Vehicle Test Cycle (CLTC), and the New European Driving Cycle (NEDC), respectively, and the corresponding battery capacity degradation is reduced by 5.1%, 11.1%, and 11.2%. The average relative error between the hardware-in-the-loop (HIL) test and simulation results of the DA-ECMS is 5%. In conclusion, the proposed DA-ECMS can effectively extend the lifetime of the fuel cell and battery compared to the A-ECMS.
Knowledge Graph and Personalized Answer Sequences for Programming Knowledge Tracing
Authors: Pan Jianguo , Dong Zhengyang , Yan Lijun , Cai Xia
Published: September 2024

Knowledge tracing is a significant research area in educational data mining, aiming to predict future performance based on students’ historical learning data. In the field of programming, several challenges are faced in knowledge tracing, including inaccurate exercise representation and limited student information. These issues can lead to biased models and inaccurate predictions of students’ knowledge states. To effectively address these issues, we propose a novel programming knowledge tracing model named GPPKT (Knowledge Graph and Personalized Answer Sequences for Programming Knowledge Tracing), which enhances performance by using knowledge graphs and personalized answer sequences. Specifically, we establish the associations between well-defined knowledge concepts and exercises, incorporating student learning abilities and latent representations generated from personalized answer sequences using Variational Autoencoders (VAE) in the model. This deep knowledge tracing model employs Long Short-Term Memory (LSTM) networks and attention mechanisms to integrate the embedding vectors, such as exercises and student information. Extensive experiments are conducted on two real-world programming datasets. The results indicate that GPPKT outperforms state-of-the-art methods, achieving an AUC of 0.8840 and an accuracy of 0.8472 on the Luogu dataset, and an AUC of 0.7770 and an accuracy of 0.8799 on the Codeforces dataset. This demonstrates the superiority of the proposed model, with an average improvement of 9.03% in AUC and 2.02% in accuracy across both datasets.
Examining Performance between Different Cognitive-Motor Dual-Task Tests in Community-Dwelling Older Adults
Authors: Georgantas Anastasios , Stefani Panagiota , Lyros Epameinondas , Chytas Dimitrios , Christakou Anna
Published: September 2024

Performing dual-task (DT) activities is essential for independent living among elderly people. No study has investigated motor performance in various cognitive-motor DT activities, utilizing the Timed Up and Go (TUG) test. This study aimed to compare motor performance between four cognitive-motor DT tests in community-dwelling older adults. The sample consisted of 60 older women. The cognitive tasks performed with the TUG test were (a) mental calculation, (b) memory recall, (c) verbal fluency, and (d) reaction to a stimulus. Lower limb muscle strength was assessed with the 30-Second Chair Stand Test, balance with the Four Square Step Test, and balance confidence with the Activities-specific Balance Confidence Scale. Completion times and DT costs were calculated. Mental calculation (r = 0.63, p < 0.01) and verbal fluency (r = 0.65, p < 0.01) tasks were similarly correlated with the TUG test, and significantly impacted motor performance compared to other DT tests. The reaction to a stimulus test showed a high relationship with the TUG test (r = 0.89, p < 0.01) and had the least impact on motor performance. These findings suggest that the cognitive task type can significantly influence motor performance during DT activities. Adding a cognitive load to the TUG test may improve its ability to identify older adults at risk for falls, aiding in the development of targeted interventions. Further research is required to validate these findings.
Mitochondrial Dysfunction in Aristolochic Acid I-Induced Kidney Diseases: What We Know and What We Do Not Know
Authors: Lukinich-Gruia Alexandra T. , Calma Crenguta L. , Szekely Flavia A. E. , Cristea Iustina-Mirabela , Pricop Maria-Alexandra , Simina Alina-Georgiana , Ordodi Valentin L. , Pavlović Nikola M. , Tatu Calin A. , Paunescu Virgil
Published: September 2024

Aristolochic acids, compounds derived from Aristolochiaceae plant species, are associated with significant renal nephrotoxicity and carcinogenicity. Aristolochic acid I (AAI), the most predominant and potent of these compounds, is a primary etiological agent in acute and chronic kidney diseases such as Aristolochic Acid Nephropathy (AAN) and Balkan Endemic Nephropathy (BEN). Due to the kidneys’ critical role in xenobiotic excretion, they are the primary organs affected by AAI toxicity. Recent in vitro and in vivo studies have highlighted mitochondrial dysfunction as a crucial factor in the pathogenesis of these kidney diseases. This review provides an update on the recent advances in understanding the causes of acquired mitochondrial dysfunction within the context of AAN and BEN. Key findings include the identification of mitochondrial DNA depletion, loss of mitochondrial membrane potential, and decreased ATP production as significant contributors to kidney damage. Additionally, oxidative stress markers and inflammatory mediators have been implicated in disease progression. Potential therapeutic approaches, such as the use of antioxidants like vitamin C and catalpol, have shown promise in mitigating AAI-induced cytotoxicity. Furthermore, future predictive approaches like pharmacogenomics could pave the way for novel mitochondria-targeted treatments. A comprehensive characterization of mitochondrial function, its underlying molecular mechanisms, and specific biomarkers could offer valuable insights and potential therapeutic options, significantly impacting the current management of AAN and BEN.
Uniaxial Compression Test and Numerical Study on the Mechanical Mechanism of Crack Exhibition and Propagation in Layered Rocks
Authors: Zhang Zhengnan , Liu Xiangxin , Gong Bin , Liang Zhengzhao , Liu Xianxian , You Xun
Published: September 2024

Layered rocks are widely distributed in mining and underground engineering. The evolution processes, such as crack initiation, development and penetration, inevitably occur due to stress changes. This study carried out an experiment and numerical simulation to explore the correspondence between crack distribution and bedding dip, and to reveal the mechanical mechanism of layered rock fracturing. The results show that the layered rock specimens with different bedding dips obtained different stress combinations under the same uniaxial compression conditions. There are a total of five types of stress combinations, including pure compression type, compression shear type, pure shear type, tension shear type, and pure tension type. The Mohr circle is effective in characterizing the relationship between the stress combinations and failure modes. The failure mode of layered rocks in the range of 0° to 150° is presented the variation features of “tensile failure → compression-shear failure → shear failure → tensile shear failure → tensile failure”. Furthermore, the combined distributions of dominant and secondary cracks are summarized into the penetrating mode, the exfoliation mode, the feather crack mode, and the associated mode in high-dip of layered marbles. This paper provides research ideas for stability monitoring and crack tracking of layered rock mass engineering.
Analysis of Plasma Electrolytic Oxidation Process Parameters for Optimizing Adhesion in Aluminum–Composite Hybrid Structures
Authors: Lucas Rafael Resende , Silva Emanuelle Roza Rodrigues , Marques Luís Felipe Barbosa , da Silva Francisco José Gomes , Abrahão Ana Beatriz Ramos Moreira , Vieira Miguel de Omena Lucas , Hein Luís Rogério de Oliveira , Botelho Edson Cocchieri , Mota Rogério Pinto , Sales-Contini Rita de Cássia Mendonça
Published: September 2024

The Plasma Electrolytic Oxidation (PEO) process was investigated to enhance the adhesion of AA2024-O aluminum alloy with a polyetherimide (PEI) matrix composite, using oxy-fuel welding (OFW). A Central Composite Design (CCD) statistical model was used to optimize three independent parameters in PEO: immersion time (s), duty cycle (%), and electrolyte concentration (Na2B4O7·10H2O), aiming to achieve a maximum value of shear strength of the hybrid joint (in MPa). The hybrid joint without PEO treatment presented a resistance of 2.2 MPa while the best condition presented a resistance of 9.5 MPa, resulting in a value 4× higher than the untreated material, due to the characteristics of the coating, which presented a more hydrophilic surface, allowing better mechanical interlocking with the polymer matrix and resulting in mixed-mode failure (adhesive, cohesive, and light fiber). In addition to improving adhesion, the PEO treatment provided better corrosion resistance to the alloy, forming an inert aluminum oxide (Al2O3) coating, with an improvement of approximately 99.84% compared to the untreated alloy. The statistical design covers about 77.15% of the total variability of the PEO + welding process, with independent factors influencing around 48.4% of the variability.
Non-Destructive Cyclic Analysis of Sealing Ability of Well Cement for Seasonal Underground Hydrogen Storage
Authors: Hussain Athar , Emadi Hossein , Thiyagarajan Sugan Raj , Fernandez Diana Maury , Ispas Ion , Watson Marshall
Published: September 2024

Underground hydrogen storage (UHS) is one potential solution that could provide a steady source of clean energy to the globe. Given their infrastructure, depleted hydrocarbon reservoirs may be a suitable storage option. However, ensuring wellbore integrity is a significant challenge when storing hydrogen in such reservoirs. In this study, 3.81 × 7.62 cm cement samples were cured for 12 and 18 months and were cyclically exposed to hydrogen for three 28-day cycles at 10.34 MPa and 50 °C. The pressure increment was achieved at the rate of 2.06 MPa/hr. The cement’s porosity, permeability, and ultrasonic velocity were tested before and after each cycle. To investigate the changes in the surface structure and elemental composition, scanning electron microscopy (SEM) was conducted. The results illustrate increased porosity and permeability, but the ultrasonic velocity changes were insignificant. The SEM images do not exhibit any change in the microstructure. However, energy dispersive spectroscopy (EDS) mapping exhibited mineral dissolution. This study demonstrates how cyclic exposure to hydrogen will affect the integrity and the sealing ability of aged cement, which will be an essential factor to consider while repurposing existing oil and gas wells to hydrogen injectors or producers for UHS applications in depleted hydrocarbon reservoirs.
The Impact of Coordination Training on Psychomotor Abilities in Adolescent Handball Players: A Randomized Controlled Trial
Authors: Spieszny Michał , Kamys Zygmunt , Kasicki Krzysztof , Wąsacz Wojciech , Ambroży Tadeusz , Jaszczur-Nowicki Jarosław , Rydzik Łukasz
Published: September 2024

Background: Handball requires significant psychomotor skills, especially in young athletes, to enhance performance. Coordination training is crucial but under-researched in this context. The objective of this study was to evaluate the impact of an experimental coordination training program on the psychomotor abilities of young handball players. Methods: A randomized controlled trial was conducted with 27 young handball players. Participants were divided into an experimental group (n = 15) receiving additional coordination training and a control group (n = 12) following standard training. Psychomotor skills were assessed before, during, and after the intervention by PNTR (Computer Tests of Coordination Abilities) tests. Statistical analysis included the Mann–Whitney U test for between-group differences and the Wilcoxon test for within-group comparisons, with significance set at p < 0.05. Results: The experimental group showed significant improvements in psychomotor performance, including reaction time and visual–motor coordination, compared to the control group. Specifically, there were statistically significant improvements in simple reaction time, visual–motor coordination, spatial orientation, attention distribution, and perception orientation. Conclusions: Coordination training effectively enhances the psychomotor abilities of young handball players, suggesting that its integration into regular training sessions can optimize performance.
Comparison of Dynamic Decoupling Point and Dynamic Buffer Level for Flexible Flow Shops in a Hybrid MTS–MTO Production Model
Authors: Renna Paolo
Published: September 2024

The competition and the volatility of today’s production context require that enterprises are able to rapidly adapt to changes, reducing total costs in production. The main relationship between producer and consumer can be conducted through Make-To-Order (MTO) or Make-To-Stock (MTS) systems. This study proposes a hybrid MTS and MTO production system with a dynamic decoupling point. The proposed model concerns the monitoring of earliness and tardiness of customer orders to move the decoupling point towards MTS or MTO. Simulation models are proposed to test the proposed model following periodic or continuous review. The numerical results highlight that the best dynamic approach is the periodic review, which is more effective when the customer demand rate is higher.
Trajectory Tracking via Interconnection and Damping Assignment Passivity-Based Control for a Permanent Magnet Synchronous Motor
Authors: Martinez-Padron Daniel Sting , de la Rosa-Mendoza San Jose , Alvarez-Salas Ricardo , Espinosa-Perez Gerardo , Gonzalez-Garcia Mario Arturo
Published: September 2024

This paper presents a controller design to track speed, position, and torque trajectories for a permanent magnet synchronous motor (PMSM). This scheme is based on the interconnection and damping assignment passivity-based control (IDA-PBC) technique recently proposed to solve the tracking control problem for mechanical underactuated systems. The proposed approach regulates the dynamics of the tracking system error at the origin, assuming the realizable trajectories preserve the motor’s port-controlled Hamiltonian structure. The importance of the contribution is two-fold: First, from the theoretical perspective, the trajectory tracking control problem is solved with proved stability properties, a topic that has not been deeply studied with the IDA-PBC methodology design. Second, from the practical point of view, the proposed control scheme exhibits a simple structure for practical implementation and strong robustness properties with respect to parametric uncertainties. The contribution is evaluated under both numerical and experimental environments considering a speed profile that demands the achievement of high dynamic performances.
Nematocidal Properties of Wild Strains of Pleurotus ostreatus Progeny Derived from Buller Phenomenon Crosses
Authors: Nelke Robert , Nabrdalik Małgorzata , Żurek Marcin , Kudrys Paweł , Hendel Patrycja , Nowakowski Mirosław , Moliszewska Ewa B.
Published: September 2024

Plant pathogenic nematodes play an important role in crop production and are difficult to control. One of them is Heterodera schachtii—a cyst nematode, pathogenic to sugar beet. Nature suggests a natural way to resolve this problem by using nematode-trapping fungi, one of which is Pleurotus ostreatus. It is one of the most widespread mushrooms in the world. It is a valuable and widely cultivated edible mushroom with nematocidal properties. The mycelium of this mushroom produces toxin droplets that paralyze nematodes, after which the nematodes become infected with the hyphae filament, resulting in their death. This feature can be put to practical use as a natural nematocidal agent. In this paper, we have described studies on the variability of the nematocidal properties in the progeny of three wild strains of P. ostreatus (Po1, Po2, Po4), obtained by crossing dikaryons with monokaryons (Buller phenomenon). The toxicity of mycelium was tested against the model organism Caenorhabditis elegans and against sugar beet pest—H. schachtii. The results of the study allowed the selection of the progeny heterokaryotic mycelia with the best parameters useful for in vitro control of both nematodes. They differed in the activity against C. elegans and H. schachtii, and in the toxic knobs production. The results indicated that the progeny of the Po1 strain presented a good ability to produce hyphal knobs in the presence of C. elegans, and progenies of the Po4 strain presented good quality of growth in preferred temperatures (10–25 °C). Three strains Po1 5dix27, Po2 20dix21, and Po4 2dix1, as well as a maternal strain Po4 controlled H. schachtii by entwining cysts better than other strains. These strains were moderately effective against C. elegans. Strains Po2 15dix17, Po4 1dix18, and Po4 1dix30 may be considered good controlling isolates against both tested organisms. The results of the research also clearly suggest that the killing properties of P. ostreatus mycelia should not be assessed only by their ability to produce toxic hyphal knobs. Their nematocidal properties also depend on other mechanisms developed by mycelia, which is observed as the lethality of nematodes. The results of this research will lead to a natural way to protect plants against nematodes. The research also proved the nematocidal properties of the wild strains to reduce the H. schachtii population in the soil.
Student Behavior Recognition in Classroom Based on Deep Learning
Authors: Jia Qingzheng , He Jialiang
Published: September 2024

With the widespread application of information technology in education, the real-time detection of student behavior in the classroom has become a key issue in improving teaching quality. This paper proposes a Student Behavior Detection (SBD) model that combines YOLOv5, the Contextual Attention (CA) mechanism and OpenPose, aiming to achieve efficient and accurate behavior recognition in complex classroom environments. By integrating YOLOv5 with the CA attention mechanism to enhance feature extraction capabilities, the model’s recognition performance in complex backgrounds, such as those with occlusion, is significantly improved. In addition, the feature map generated by the improved YOLOv5 is used to replace VGG-19 in OpenPose, which effectively improves the accuracy of student posture recognition. The experimental results demonstrate that the proposed model achieves a maximum mAP of 82.1% in complex classroom environments, surpassing Faster R-CNN by 5.2 percentage points and YOLOv5 by 4.6 percentage points. Additionally, the F1 score and R value of this model exhibit clear advantages over the other two traditional methods. This model offers an effective solution for intelligent classroom behavior analysis and the optimization of educational management.
Deterioration Model for Corroded Circular Columns
Authors: Liu Haibing , Lin Junqi , Liu Jinlong
Published: September 2024

A hysteretic model is essential for the study of the seismic performance of structures. Due to the ability to capture the component strength and stiffness deterioration, the modified Ibarra–Medina–Krawinkler (ModIMK) hysteretic model has been widely used recently. Previous studies on the ModIMK model have mainly focused on reinforced-concrete (RC) square columns, and very few have focused on circular columns. In contrast, studies on the ModIMK model specifically for corroded circular RC columns have not yet been conducted. For this reason, a database of 35 corroded and uncorroded comparison columns was gathered, and the hysteretic model parameters of each column were calibrated. The ratios of the model parameters of the corroded and uncorroded comparison components are defined as the corrosion-induced deterioration coefficients (CIDCs). After the CIDCs were calculated for all the corroded columns, the empirical equations for the CIDCs were established using regression methods. Through determining the ModIMK model parameters of the corroded columns when they were uncorroded, combined with these equations, the ModIMK model parameters of the corroded circular columns were calculated and their hysteretic models defined. Finally, the accuracy of the ModIMK model’s prediction method was demonstrated using the hysteretic response analyses of four components in the database and the application of two components outside the database. The prediction method lays the foundation for applying the ModIMK model to structures containing corroded circular RC columns.
Assessing Ambisonics Sound Source Localization by Means of Virtual Reality and Gamification Tools
Authors: Medina Esaú , Viveros-Muñoz Rhoddy , Otondo Felipe
Published: September 2024

Sound localization is a key area of interest in auditory research, especially in complex acoustic environments. This study evaluates the impact of incorporating higher-order Ambisonics (HOA) with virtual reality (VR) and gamification tools on sound source localization. The research addresses the current limitations in VR audio systems, particularly the lack of native support for HOA in game engines like Unreal Engine (UE). A novel framework was developed, combining UE for VR graphics rendering and Max for HOA audio processing. Participants performed sound source localization tasks in two VR environments using a head-mounted display (HMD). The assessment included both horizontal and vertical plane localization. Gamification elements were introduced to improve engagement and task comprehension. Results showed significant improvements in horizontal localization accuracy, although challenges remained in back localization. The findings underscore the potential of VR and gamification to enhance auditory tests, reducing test duration and participant fatigue. This research contributes to the development of immersive and interactive audio experiences, highlighting the broader applications of VR beyond entertainment.
A Parcel Transportation and Delivery Mechanism for an Indoor Omnidirectional Robot
Authors: Rubies Elena , Bitriá Ricard , Palacín Jordi
Published: September 2024

Parcel transportation is a task that is expected to be highly automated with the development of application-specific mobile robots. This paper presents the design and implementation of a parcel transportation and delivery mechanism aimed at converting a general-purpose indoor omnidirectional robot into an indoor delivery robot. The design of this new mechanism has considered the best placement in the robot and the limitation of not exceeding the original robot diameter. The mechanism consists of a basket with a lid that allows for the manual loading and automatic unloading of parcels. Despite the space limitations imposed by the general-purpose robot design, the designed mechanism can transport up to 90% of the packages received in an educational building. The mechanism was empirically validated by conducting 125 static manual loading experiments, 150 static unloading experiments, and 50 complete parcel delivery experiments. Results show that the delivery robot can efficiently deliver 78% of the total packages received in the building: envelopes, very small parcels, and small parcels. In the case of medium parcels, the delivery was unsuccessful in 30% of cases, in which the parcel did not properly slide out of the basket.
The Impact of Sea Buckthorn (Hippophae rhamnoides L.) and Cornelian Cherry (Cornus mas L.) Plant Extracts on the Physiology of Gastrointestinal Tract Cell In Vitro Model in the Context of Metabolic Diseases
Authors: Grabacka Maja , Lakatošová Jana , Waś Gabriela , Wydra Anna , Jakubiec Karolina , Fialková Veronika , Speváková Ivana , Pierzchalska Małgorzata
Published: September 2024

The aim of this study was to evaluate the impact of ethanol extracts from sea buckthorn and Cornelian cherry fruits and leaves on physiology of gastrointestinal tract cells. We used three cell lines relevant to the types of cells, which are exposed to bioactive compounds after oral administration, namely intestinal absorptive cells (Caco-2/HT-29 MTX model), hepatocytes (HepG2 cells) and immunocompetent cells (RAW 264.7 and P388D1 monocytes). The contents of antioxidant and bioactive polyphenols, such as cinnamic, caffeic and p-coumaric acids, rutin, myricetin, resveratrol, quercetin, apigenin and kaempferol, were assessed in the extracts using HPLC chromatography. The application of the extracts to Caco-2/HT-29-MTX cultures increased enterocyte differentiation markers (alkaline phosphatase and villin1 level) and goblet cell markers (mucins) over a fortnight. The extracts reduced lipid droplet size in hepatocytes challenged with hyperglycaemic glucose concentration, insulin and palmitate. Sea buckthorn leaf, fruit and Cornelian cherry leaf extracts blocked oxidative burst in the PMA-stimulated monocytes, while the sea buckthorn leaf and Cornelian cherry fruit extracts downregulated lipopolysaccharide-induced NO and IL-1β, respectively. The results indicate that the tested extracts modulate the behaviour of cells in the gastrointestinal tract in a beneficial way, especially regarding lipid accumulation and innate immunity actions.
GSFedSec: Group Signature-Based Secure Aggregation for Privacy Preservation in Federated Learning
Authors: Kanchan Sneha , Jang Jae Won , Yoon Jun Yong , Choi Bong Jun
Published: September 2024

Privacy must be preserved when working with client data in machine learning. Federated learning (FL) provides a way to preserve user data privacy by aggregating locally trained models without sharing the user data. Still, the privacy of user identity is not preserved. Secure aggregation is a popular technique in FL for aggregating gradients without disclosing individual data. However, it is costly and inaccurate. Therefore, we propose a novel, scalable, cost-effective group signature-based secure aggregation algorithm in FL, called GSFedSec, where secure aggregation helps conceal the user’s update while the group signature helps conceal their identity. Our algorithm preserves the data and their source. Our simulation results show that the proposed algorithm does not suffer from a loss of accuracy, handles increases in network size competently, offers computational and communication efficiency, and is secure against various security attacks. We have compared the results of efficiency and security against existing algorithms in FL. Also, the security of the algorithm is verified using Burrows–Abadi–Needham (BAN) logic and simulated via the Automated Validation of Internet Security Protocols and Applications (AVISPA) protocol.
Advanced Control Strategies for Securing UAV Systems: A Cyber-Physical Approach
Authors: Ale Isaac Mohammad Sadeq , Flores Peña Pablo , Gîfu Daniela , Ragab Ahmed Refaat
Published: September 2024

This paper explores the application of sliding mode control (SMC) as a robust security enhancement strategy for unmanned aerial vehicle (UAV) systems. The study proposes integrating advanced SMC techniques with security protocols to develop a dual-purpose system that improves UAV control and fortifies against adversarial actions. The strategy includes dynamic reconfiguration capabilities within the SMC framework, allowing adaptive responses to threats by adjusting control laws and operational parameters. This is complemented by anomaly detection algorithms that monitor deviations in control signals and system states, providing early warnings of potential cyber-intrusions or physical tampering. Additionally, fault-tolerant SMC mechanisms are designed to maintain control and system stability even when parts of the UAV are compromised. The methodology involves simulation and real-world testing to validate the effectiveness of the SMC-based security enhancements. Simulations assess how the UAV handles attack scenarios, such as GPS spoofing and control signal jamming, with SMC adapting in real-time to mitigate these threats. Field tests further confirm the system’s capability to operate under varied conditions, proving the feasibility of SMC for enhancing UAV security. This integration of sliding mode control into UAV security protocols leverages control theory for security purposes, offering a significant advancement in the robust, adaptive control of UAVs in hostile environments.
Quantifying Future Annual Fluxes of Polychlorinated Dibenzo-P-Dioxin and Dibenzofuran Emissions from Sugarcane Burning in Indonesia via Grey Model
Authors: Siami Lailatus , Wang Yu-Chun , Wang Lin-Chi
Published: September 2024

The open burning of sugarcane residue is commonly used as a low-cost and fast method during pre-harvest and post-harvest periods. However, this practice releases various pollutants, including dioxins. This study aims to predict polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs or dioxins) emissions using the grey model (GM (1,1)) and to map the annual flux spatial distribution at the provincial level from 2023 to 2028. An annual emission inventory at the provincial level was developed using the activity rate of dry crop residue from national agencies and literature, following the guidelines set by the United Nations Environment Programme (UNEP). Emission distributions from 2016 to 2022 were then mapped. The average PCDD/F emission values show significant variation among the provinces, averaging 309 pg TEQ/year. Spatially, regions with intensive sugarcane production, such as Lampung and East Java consistently show high emissions, often exceeding 400 pg/m2. Emissions calculated using the UNEP emission factor tend to be higher compared to other factors, due to its generic nature and lack of regional specificity. Emission predictions using GM (1,1) indicate that North Sumatra is expected to experience a steady increase in PCDD/Fs emissions, whereas South Sumatra and Lampung are projected are projected to see a slight decline. This forecast assumes no changes in regional intervention strategies. Most regions in Java Island show a gradual increase in emissions, except for East Java, which is predicted to have a slight decline from 416 pg/year in 2023 to 397 pg/year in 2028. Additionally, regions such as Gorontalo and parts of East Java are projected to remain ‘hotspots’ with consistently high emissions, highlighting the need for targeted interventions. To address emission hotspots, this study emphasizes the need for cleaner agricultural practices, enhanced enforcement of environmental regulations, and the integration of advanced monitoring technologies to mitigate the environmental and health impacts of PCDD/F emissions in Indonesia. Future studies should consider developing monthly emissions profiles to better account for local agricultural practices and seasonal conditions. The emission data generated in this study, which include both spatial and temporal distributions, are valuable for air quality modeling studies and can help assess the impact of current and future emissions on ambient air quality.
Spatial–Temporal Variations and Driving Factors of the Albedo of the Qilian Mountains from 2001 to 2022
Authors: Xue Huazhu , Zhang Haojie , Yuan Zhanliang , Ma Qianqian , Wang Hao , Li Zhi
Published: September 2024

Surface albedo plays a pivotal role in the Earth’s energy balance and climate. This study conducted an analysis of the spatial distribution patterns and temporal evolution of albedo, normalized difference vegetation index (NDVI), normalized difference snow index snow cover (NSC), and land surface temperature (LST) within the Qilian Mountains (QLMs) from 2001 to 2022. This study evaluated the spatiotemporal correlations of albedo with NSC, NDVI, and LST at various temporal scales. Additionally, the study quantified the driving forces and relative contributions of topographic and natural factors to the albedo variation of the QLMs using geographic detectors. The findings revealed the following insights: (1) Approximately 22.8% of the QLMs exhibited significant changes in albedo. The annual average albedo and NSC exhibited a minor decline with rates of −0.00037 and −0.05083 (Sen’s slope), respectively. Conversely, LST displayed a marginal increase at a rate of 0.00564, while NDVI experienced a notable increase at a rate of 0.00178. (2) The seasonal fluctuations of NSC, LST, and vegetation collectively influenced the overall albedo changes in the Qilian Mountains. Notably, the highly similar trends and significant correlations between albedo and NSC, whether in intra-annual monthly variations, multi-year monthly anomalies, or regional multi-year mean trends, indicate that the changes in snow albedo reflected by NSC played a major role. Additionally, the area proportion and corresponding average elevation of PSI (permanent snow and ice regions) slightly increased, potentially suggesting a slow upward shift of the high mountain snowline in the QLMs. (3) NDVI, land cover type (LCT), and the Digital Elevation Model (DEM, which means elevation) played key roles in shaping the spatial pattern of albedo. Additionally, the spatial distribution of albedo was most significantly influenced by the interaction between slope and NDVI.
Climate Warming Has Contributed to the Rise of Timberlines on the Eastern Tibetan Plateau but Slowed in Recent Years
Authors: Peng Xuefeng , Feng Yu , Zang Han , Zhao Dan , Zhang Shiqi , Cai Ziang , Wang Juan , Peng Peihao
Published: September 2024

The alpine timberline is a component of terrestrial ecosystems and is highly susceptible to climate change. Since 2000, the Tibetan Plateau’s high-altitude zone has been experiencing a persistent warming, clarifying that the response of the alpine timberline to climate warming is important for mitigating the negative impacts of global warming. However, it is difficult for traditional field surveys to clarify changes in the alpine timberline over a wide range of historical periods. Therefore, alpine timberline sites were extracted from 2000–2021, based on remote sensing data sources (LANDSAT, MODIS), to quantify the timberline vegetation growth in the Gexigou National Nature Reserve and to explore the impacts of climate change on timberline vegetation growth. The results show that the mean temperature increased significantly from 2000 to 2021 (R2 = 0.35, p = 0.0036) at a rate of +0.03 °C/year. The alpine timberline continued to shift upwards, but at a slower rate, by +22.87 m, +23.23 m, and +2.73 m in 2000–2007, 2007–2014, and 2014–2021, respectively. The sample plots of the timberline showing an upward shift experienced a decreasing trend. The timberline NDVI increased significantly from 2000 to 2021 (R2 = 0.2678, p = 0.0136) with an improvement in its vegetation. The timberline NDVI is positively correlated with the annual mean temperature (p < 0.05), February mean temperature (p < 0.05), June minimum temperature (p < 0.05), February maximum temperature (p < 0.01), June maximum temperature (p < 0.01), and June mean temperature (p < 0.01). It was also found to be negatively correlated with annual precipitation (p < 0.01). The study showcases the practicality of using remote sensing techniques to investigate the alpine timberline shifts and timberline vegetation. The findings are valuable in developing approaches to the sustainable management of timberline ecosystems.