bluuebunny/crossref_metadata_2025 huggingface dataset:
Daily Activity Rhythms of Animals in the Southwest Mountains, China: Influences of Interspecific Relationships and Seasons
Authors: Li Qiuxian , Zhang Qian , Jiang Qingsong , Zhou Huaqiang , Zhang Zejun , Zhou Hong , Wei Wei , Hong Mingsheng
Published: October 2024

Temporal and spatial factors regulate the interactions between apex predators, mesocarnivores, and herbivores. Prey adjust their activity patterns and spatial utilization based on predator activities; in turn, predators also adapt to the activities of their prey. To elucidate the factors influencing the daily activity rhythms of animals, 115 camera traps were established from September 2019 to June 2023 to assess the influences of interspecific relationships and seasons on the daily activity rhythms of animals in the southwest mountains of China. The species captured by the cameras included six Carnivora (such as Panthera pardus and Lynx lynx), six Artiodactyla (such as Moschus spp. and Rusa unicolor), one Primate (Macaca mulatta), and two Galliformes (Crossoptilon crossoptilon, Ithaginis cruentus). The results demonstrated that the 15 species exhibited different activity rhythms and peak activities to reduce intense resource competition. There were differences in the species’ activity rhythms in different seasons, with competition among different species being more intense in the cold season than in the warm season. In predation relationships, the overlap coefficient in the cold season exceeded that of the warm season, possibly due to the abundant resources in summer and food scarcity in winter. In competitive relationships, 15 pairs of species exhibited significantly higher overlap coefficients in the cold season compared to the warm season, possibly due to increased demands for energy during the cold period or seasonal changes in predatory behavior. By analyzing the daily and seasonal activity patterns of dominant species in the study area, temporal niche overlaps were established to compare the competition levels between species. These findings indicate that the activity rhythms of the animals in this area not only result from evolutionary adaptation but are also influenced by season, food resources, and interspecific relationships (predation and competition). Thus, efforts should be made to reduce human interference, protect food resources in the winter, and monitor animals’ interspecific relationships to protect animal diversity and maintain the stability of the ecosystem in this biodiversity hotspot in China.
Serum 25(OH)D Analysis in Captive Pachyderms (Loxodonta africana, Elephas maximus, Diceros bicornis, Rhinoceros unicornis, Tapirus indicus) in Europe
Authors: Bruins-van Sonsbeek Linda G. R. , Corbee Ronald J.
Published: October 2024

This study aimed to detect seasonal and species differences in serum 25-hydroxy vitamin D (25(OH)D) concentrations during summer and winter months in captive pachyderms in Europe. Both elephant species had low 25(OH)D while African elephants did not show a seasonal variation. Asian elephants had significantly higher 25(OH)D compared to their African counterparts but also did not show a seasonal difference. Both rhinoceros species investigated had higher 25(OH)D compared to both elephant species; the Indian rhinoceros had high circulating levels year-round, while the black rhinoceroses showed significantly lower 25(OH)D in winter. Malayan tapirs have very low 25(OH)D, comparable to horses. The higher 25(OH)D of elephants and rhinoceroses could indicate that elephants and rhinoceroses are capable of producing vitamin D. This might indicate that the Indian rhinoceroses are capable of producing enough endogenous vitamin D year-round at latitudes around 52° N, while both elephant species and the black rhinoceros are not. This study also showed that it is likely that both elephant species and rhinoceros species are capable of absorbing cholecalciferol from the digestive tract, according to the existing literature, while tapirs may not.
A Survey of Robot Intelligence with Large Language Models
Authors: Jeong Hyeongyo , Lee Haechan , Kim Changwon , Shin Sungtae
Published: October 2024

Since the emergence of ChatGPT, research on large language models (LLMs) has actively progressed across various fields. LLMs, pre-trained on vast text datasets, have exhibited exceptional abilities in understanding natural language and planning tasks. These abilities of LLMs are promising in robotics. In general, traditional supervised learning-based robot intelligence systems have a significant lack of adaptability to dynamically changing environments. However, LLMs help a robot intelligence system to improve its generalization ability in dynamic and complex real-world environments. Indeed, findings from ongoing robotics studies indicate that LLMs can significantly improve robots’ behavior planning and execution capabilities. Additionally, vision-language models (VLMs), trained on extensive visual and linguistic data for the vision question answering (VQA) problem, excel at integrating computer vision with natural language processing. VLMs can comprehend visual contexts and execute actions through natural language. They also provide descriptions of scenes in natural language. Several studies have explored the enhancement of robot intelligence using multimodal data, including object recognition and description by VLMs, along with the execution of language-driven commands integrated with visual information. This review paper thoroughly investigates how foundation models such as LLMs and VLMs have been employed to boost robot intelligence. For clarity, the research areas are categorized into five topics: reward design in reinforcement learning, low-level control, high-level planning, manipulation, and scene understanding. This review also summarizes studies that show how foundation models, such as the Eureka model for automating reward function design in reinforcement learning, RT-2 for integrating visual data, language, and robot actions in vision-language-action models, and AutoRT for generating feasible tasks and executing robot behavior policies via LLMs, have improved robot intelligence.
A Deep Learning Inversion Method for Airborne Time-Domain Electromagnetic Data Using Convolutional Neural Network
Authors: Yu Xiaodong , Zhang Peng , Yu Xi
Published: October 2024

Due to the high detection efficiency of the airborne time-domain electromagnetic method, it can quickly collect electromagnetic response data for large area-wide regions, but it also brings great challenges to the inversion interpretation of the data because there are numerous survey data that need to be inverted. Conventional optimal inversion and fast imaging methods still take a long time to obtain conductivity and depth information, which affect the efficiency of real-time data interpretation. In this paper, we present a deep learning inversion method that can be used to solve the fast inversion problem of airborne time-domain electromagnetic data; the method uses a one-dimensional convolutional neural network. The network structure consists of two parts containing different numbers of convolutional and pooling layers. The training sample dataset was generated via two ways of constructing geoelectric models through forward modelling. To check the effectiveness of our deep learning inversion strategy, we tested it on synthetic data and two types of survey data. The experimental results show that this inversion method is effective and that it can be applied to airborne time-domain electromagnetic data collected using different observation systems. The proposed inversion method can obtain better inversion results for both simple and complex stratigraphic structures and requires significantly less computation time compared to conventional optimal inversion methods.
Multi-Layer QCA Reversible Full Adder-Subtractor Using Reversible Gates for Reliable Information Transfer and Minimal Power Dissipation on Universal Quantum Computer
Authors: Jeon Jun-Cheol
Published: October 2024

The effects of quantum mechanics dominate nanoscale devices, where Moore’s law no longer holds true. Additionally, with the recent rapid development of quantum computers, the development of reversible gates to overcome the problems of energy and information loss and the nano-level quantum-dot cellular automata (QCA) technology to efficiently implement them are in the spotlight. In this study, a full adder-subtractor, a core operation of the arithmetic and logic unit (ALU), the most important hardware device in computer operations, is implemented as a circuit capable of reversible operation using QCA-based reversible gates. The proposed circuit consists of one reversible QCA gate and two Feynman gates and is designed as a multi-layer structure for efficient use of area and minimization of delay. The proposed circuit is tested on QCADesigner 2.0.3 and QCADesigner-E 2.2 and shows the best performance and lowest energy dissipation. In particular, it shows tremendous improvement rates of 180% and 562% in two representative standard design cost indicators compared to the best existing studies, and also shows the highest circuit average output polarization.
An Operations Chain Model for Automatic Assessment of Operation Procedure for Equipment Operators
Authors: Wang Haiyan , Hu Binghua , Li Jingming
Published: October 2024

Automatic assessment of the operation ability of operators based on computers is an essential approach for improving the effectiveness of equipment operation training and enhancing equipment safety. Present methods primarily focus on the operation results but pay less attention to the operation procedure. One reason is that there is a lack of a model that has the ability to describe all probable paths to accomplish the same task. Therefore, an operations chain model is put forward for the first time to describe the standard operation procedure and relationships among operations based on the decomposition of operational tasks and the relationships among the various operations required to fulfill the task. A specific operation task corresponds to an operations chain, which will form one or multiple standard operation sequences that will allow trainees to complete the same task through different paths. The Needleman–Wunsch sequence alignment algorithm is introduced to match the trainees’ operation sequence with all standard sequences. The maximum alignment result is the score of the trainees’ operations. An example shows that the operations chain model can accurately describe the complex structure of the standard operating procedures. The Needleman–Wunsch sequence alignment algorithm can objectively evaluate the trainee’s operation capabilities. The combination of the operations chain model and sequence alignment algorithm can form a complete operation procedure assessment method that is friendlier to trainees and has more objective evaluation results. The method will help to improve the effectiveness of the competency assessment of equipment operators.
Performance Evaluation of African catfish (Clarias gariepinus) Fed Diets with Varying Dietary Inclusion Levels of Christmas Melon (Laganaria breviflorus) as a Partial Replacement for Wheat Offal
Authors: Adagha Oghenefejiro , Ekelemu Jerimoth Kesena , Nwachi Oster Francis , Irabor Arnold Ebuka
Published: October 2024

This study evaluates the effects of Christmas melon (Laganaria breviflorus)-based diets on the growth and hematology of African catfish (Clarias gariepinus) after a 6 (six)-month feeding trial. A total of 240 C. gariepinus juveniles with an average weight of 10.68 g were procured from the Fisheries and Aquaculture Department Hatchery Unit for the feeding trial. After acclimating for a week (7 days) using 2.00 mm Coppens feed (45% CP) twice per day, the fish samples were randomly distributed into 12 tarpaulin tanks of 4 ft × 4 ft × 4 ft with a 200 L water holding capacity (four (4) different treatments presented in triplicate). Twenty (20) fish per tank were fed twice daily with the compounded feed with varying dietary inclusion levels of Christmas melon (0% (control), 5%, 10% and 15%). The weights and lengths of the sampled fish were measured biweekly to determine the growth performance, while hematological parameters, such as the packed cell volume, erythrocytes, hemoglobin, and leucocytes were determined midway through and at end of the feeding trial. The data collected were analyzed using ANOVA, and the results revealed the optimum growth and nutrient utilization and hematological and serum biochemical parameters of C. gariepinus in T3. The length–weight relationship results revealed that the fish exhibited an isometric growth pattern with B-values above 3 across the treatments. In conclusion, the results obtained in this study revealed that Christmas melon (L. breviflorus) could replace wheat offal by up to 10% in the diet of C. gariepinus without negative effects on the obtained optimal growth performance, hematological parameters, or serum biochemistry.
Trauma Exposure Checklist: Preliminary Results Show Promising Psychometric Properties to Assess Subjective Perceptions of Exposure to Potentially Traumatic Events
Authors: Morgado Alice Murteira
Published: October 2024

Most individuals in the general population will be exposed to potentially traumatic situations at some point in their lifespan. There is a strong body of research focusing on the clinical implications of exposure to potentially traumatic situations, but less attention has been given to psychological adjustment following these events. Very few available instruments assess trauma exposure while considering subjective perceptions of both positive and negative features. In this study, 304 adults from the general population, mostly women of middle and high socioeconomic status (mean age = 43), filled in a questionnaire with sociodemographic questions and an adapted version of the Trauma Exposure Checklist, which was originally developed in the context of the COVID-19 pandemic. Results indicate that most participants have experienced a potentially traumatic event, most prevalently related to violence and/or criminality and to the severe illnesses and deaths of close relatives. Principal components and reliability analyses lent support to a three-factor structure that considers perceptions of internal and external losses and a positive factor that addresses resources and social support. This study is a first step towards advancing our knowledge on the impact of developmental and sociodemographic factors on subjective experiences of psychological crises and, consequently, psychological adjustment throughout the lifespan.
Investigating the Behavioral Intention of Smart Home Systems among Older People in Linyi City
Authors: Wang Yuan , Sani Norazmawati Md. , Shu Bo , Jiang Qianling , Lu Honglei
Published: October 2024

Background: With an aging population and the continuous advancement of smart technology, the Chinese government is exploring smart elderly care models to address the challenges posed by aging. Although smart home systems are viewed as a promising solution, their adoption rate among older people remains low. Objectives: This study aimed to investigate the factors influencing the behavioral intention to use smart home systems among older people in Linyi City, Shandong Province, China. Methods: A literature review revealed a lack of quantitative research on older people’s behavioral intention toward smart home systems based on the Innovation Diffusion Theory. This study developed an extended model based on the Innovation Diffusion Theory, Technology Acceptance Model, and external variables, incorporating eight variables: intergenerational technical support, perceived cost, self-reported health conditions, compatibility, observability, trialability, perceived usefulness, perceived ease of use, and behavioral intention. Results: Analysis of 387 valid questionnaires showed that compatibility and trialability significantly and positively affect perceived ease of use, while self-reported health conditions, perceived ease of use, and perceived usefulness have significant effects on behavioral intention. In addition, perceived cost had a negative influence on behavioral intention. Contributions/Significance: These findings highlight the importance of considering these factors in the design of smart home systems to improve user experience and provide valuable practical guidance to smart home system developers, R&D institutions, and policymakers.
Hyperparameter Tuning Technique to Improve the Accuracy of Bridge Damage Identification Model
Authors: Chung Su-Wan , Hong Sung-Sam , Kim Byung-Kon
Published: October 2024

In recent years, active research has been conducted using deep learning to evaluate damage to aging bridges. However, this method is inappropriate for practical use because its performance deteriorates owing to numerous classifications, and it does not use photos of actual sites. To this end, this study used image data from an actual bridge management system as training data and employed a combined learning model for each member among various instance segmentation models, including YOLO, Mask R-CNN, and BlendMask. Meanwhile, techniques such as hyperparameter tuning are widely used to improve the accuracy of deep learning, and this study aimed to improve the accuracy of the existing model through this. The hyperparameters optimized in this study are DEPTH, learning rate (LR), and iterations (ITER) of the neural network. This technique can improve the accuracy by tuning only the hyperparameters while using the existing model for bridge damage identification as it is. As a result of the experiment, when DEPTH, LR, and ITER were set to the optimal values, mAP was improved by approximately 2.9% compared to the existing model.
Study on Rheological Properties of Waste Cooking Oil and Organic Montmorillonite Composite Recycled Asphalt
Authors: Xie Cheng , Ye Qunshan , Fan Lingyi , Weng Anqi , Liu Haobin
Published: October 2024

Pre-treated waste cooking oil (WCO) and organic montmorillonite (OMMT) were employed for the recycling of aged asphalt, which resulted in the improvement of the design of WCO asphalt rejuvenators and the enhancement of high-temperature performance of WCO-recycled asphalt. The effect of the rejuvenator and the properties of recycled asphalt were evaluated by viscosity, dynamic shear rheometer (DSR), bending beam rheometer (BBR) and scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and gel permeation chromatography (GPC) tests. The results indicated that aged asphalt could be obviously softened and restored to the level of original asphalt by adding 6% WCO. However, the high-temperature properties of recycled asphalt would be declined by adding too large a dose of WCO rejuvenator. The high-temperature performance of recycled asphalt was significantly improved by the WCO-OMMT complex rejuvenator, and the viscosity and rutting factor of recycled asphalt were increased. Light components of aged asphalt could be supplemented by WCO of the complex rejuvenator. The volatilization of small molecules could be slowed down by the peel structure formed by OMMT and small molecules of the asphalt, which resulted in the proportion of small molecular substances (SMS) being increased by 4% and improvement of the colloidal structure of aged asphalt. The high-temperature and low-temperature performance of recycled asphalt can be improved concurrently by the combination of 6% WCO and 1% OMMT, and this was evidenced by the fact that the high-temperature and low-temperature PG were all upgraded by one level.
Carbon Footprint Assessment: Case Studies for Hemp-Based Eco-Concrete Masonry Blocks
Authors: Isopescu Dorina Nicolina , Adam Laurentiu , Nistorac Andreea , Bodoga Alexandra
Published: October 2024

In recent times, climate change has become more evident than ever, and measures to slow down its negative effects are imperative for the future of the world. The scientific and economic communities of countries around the world, under the force of international climate agreements, are identifying solutions to reduce greenhouse gas (GHG) emissions by establishing appropriate measures and developing new strategies. In the context of these objectives, the effort to identify eco-sustainable practices for the construction industry is growing significantly. Recently, much research has focused on solutions for producing green building materials, as well as applying circular economy principles to achieve a balance between anthropogenic emissions and absorptions by greenhouse gas absorbers. The relevant indicators of the level of achievement of these major objectives can be identified, already from the construction design phase, with the help of Life Cycle Assessment (LCA) analysis. This paper presents a series of environmental impact analyses for an eco-friendly solution of precast concrete masonry blocks. Ecological concrete is manufactured with aggregates from biological waste resulting from hemp crops. Impact assessments were performed with the SimaPro 9.5 software application. Research has shown that in the production chain, which includes the materials resulting from the recycling and reuse of hemp concrete blocks, the contribution to the effort to achieve neutrality in terms of global warming is significant. The Cradle-to-Cradle scenario revealed that the recycling of hemp concrete masonry blocks at the end of their use, for a functional unit of 0.5 m3, has a GHG emission of 33.5228 [kg CO2-eq] and CO2 uptakes can reach the negative value of −53.8397 [kg CO2-eq]. Thus, the balance of GHG emissions is negative, with values of approximately −20.3169 [kg CO2-eq]. The LCA analyses also reflect a decreased damage to human health, natural resources, and biodiversity when hemp concrete is used for masonry blocks.
Adapting International Business Models for EU Projects: Macro- and Micro-Foundations of the Uppsala Model in Multinational Collaborations
Authors: Cordeiro Cheryl Marie , Sindhøj Erik
Published: October 2024

This study examines the adaptation of the Uppsala Model to enhance the management of European Union (EU)-funded projects, particularly focusing on the macro- and micro-foundational elements of the model. The Uppsala Model, originally developed for firm-level internationalization, provides a valuable framework for addressing the complex challenges of EU project implementation, which include bureaucratic hurdles, diverse stakeholder management, and the intricacies of European integration. This paper highlights the persistent issues faced by project managers despite improved application processes and skilled beneficiaries. By applying the Uppsala Model, which emphasizes incremental knowledge development and resource commitment, this study aims to bridge the gap between fund acquisition and project delivery. The integration of both macro- (broad external factors) and micro- (individual and organizational behaviors) perspectives of the Uppsala Model offers a comprehensive approach to managing international, multi-stakeholder EU initiatives. This approach is exemplified through the SuMaNu project, which addresses nutrient recycling and sustainable manure management in the Baltic Sea Region. The findings suggest that the Uppsala Model’s principles can be effectively applied to enhance the execution of complex EU projects by fostering better stakeholder relationships, incremental learning, and adaptive strategies. This study underscores the relevance of experiential learning and network perspectives in achieving successful project outcomes in the EU context.
Application Study of Acoustic Reflectivity Based on Phased Array Ultrasonics in Evaluating Lubricating Oil Film Thickness
Authors: Shang Fei , Chen Huilin , Sun Bo , Wang Shaofeng , Han Yongquan , Liu Wenjing , Miao Fengchun , Liu Zhendong
Published: October 2024

Bearings play a key role in rolling mills, and the uniformity of their lubricant film directly affects the degree of wear of bearings and the safety of equipment. Due to long-term stress, the lubricant film inside the bearing is not uniformly distributed, resulting in uneven wear between the journal and the shaft tile, which increases the potential safety hazards in production. Traditional disassembly inspection methods are complex and time-consuming. Ultrasonic nondestructive testing technology, which has the advantages of nondestructive and adaptable, has become an effective means of assessing the thickness of the oil film in bearings. In this study, an experimental platform for calibrating the lubricant film thickness in bearings was constructed for the first time, and the acoustic characteristics of different thicknesses of the oil film were measured using ultrasonic detection equipment to verify the accuracy of the simulation process. The experimental results show that after discrete Fourier transform processing, the main features of the frequency channels of the reflected acoustic signals of different thicknesses of the oil film are consistent with the finite element simulation results, and the errors of the oil film thicknesses calculated from the reflection coefficients are within 10% of the set thicknesses, and the measurement ranges cover from 5 μm to 250 μm. Therefore, the above method can realize the accurate measurement of the thicknesses of the oil film in bearings.
A Case of Primary Ewing Sarcoma of the Kidney: Robotic-Assisted Nephron-Sparing Surgery, a Feasible Alternative in Treatment of Localized Disease
Authors: Ahmed Amr , Zubelic Aleksa , Radovanovic Milan , Stojanoski Gjoko , Aksünger Metin
Published: October 2024

Extra-skeletal Ewing sarcoma (EWS) occurs in about 12% of EWS patients; at the same time, primary involvement of the kidneys remains extremely rare. Since it was first described in 1975, only a small case series have been reported worldwide. About 95% of surgically treated patients with EWS of the kidney described in the literature underwent nephrectomy, and the remaining patients only had a tumor biopsy. Nephron-sparing surgery (NSS) has not been sufficiently investigated as an alternative in the local surgical treatment of localized disease, mostly as a result of technically unfeasible provisions of negative surgical margins. In this report, we present a unique case of primary EWS of the kidney with an asymptomatic course without radiographic signs that suggest a highly aggressive disease, successfully locally treated with robotic-assisted NSS. This report showcases that robotic-assisted NSS could be a feasible alternative in treatment of localized disease yielding equally good oncological results while, at the same time, creating better prerequisites for necessary adjuvant chemotherapy.
Optimization of Division and Reconfiguration Locations of the Medium-Voltage Power Grid Based on Forecasting the Level of Load and Generation from Renewable Energy Sources
Authors: Sidor Karol , Miller Piotr , Małkowski Robert , Izdebski Michał
Published: October 2024

The article addresses challenges in optimizing the operation of medium voltage networks, emphasizing optimizing network division points and selecting the best network configuration for minimizing power and energy losses. It critically reviews recent research on the issue of network configuration optimization. The optimization of the medium voltage power grid reconfiguration process was carried out using known optimization tools. The novelty lies in the inclusion of a probabilistic approach in the decision-making process in forecasting loads and generation from renewable energy sources (RES). Optimization studies utilizing heuristic optimization methods were completed, and an algorithm was developed for forecasting load and power generated from RES based on historical data and current weather data obtained from weather API. The solution proposed in the article allows multiple applications, including optimizing network division points’ locations (which decreases financial costs of modernizing network infrastructure) as well as improving the reconfiguration process, resulting in lower power losses while maintaining voltage requirements.
Assessing the Sustainability Reporting Transparency and Engagement of European Energy Companies
Authors: Zrnic Ana , Pekanov Dubravka , Borozan Djula
Published: October 2024

Energy companies are facing increasing pressure from institutional and industry stakeholders to prioritize their responsibility to the environment and society, including providing accurate, reliable, and comprehensive reports on their sustainability practices. Three metrics were developed in this study: the average sustainability reporting score and two sustainability performance reporting indices based on two different performance measurement methodologies. These were designed to assess the effect of mandatory non-financial disclosure on sustainability reporting and the level of transparency and engagement of energy companies. The study also examined the relationship between the level of sustainability reporting and sustainability performance in the period of 2016–2019 by correlating these metrics. The analysis sheds light on the effectiveness of non-financial disclosure regulations in promoting sustainability practices in the energy industry. The results revealed no difference in metric scores prior to, or even following, the adoption of Directive 2014/95/EU. Energy companies performed better in terms of sustainability when more indicators were reported. Their primary focus was on the economic aspect of sustainability, particularly corruption. They gave less importance to the environmental aspect, mainly reporting on emissions. The social aspect received the least attention, although indicators for employee education and training were mentioned most frequently. The analysis showed that the metrics are statistically significantly correlated and complement each other, highlighting the need to consider a variety of metrics when assessing sustainability performance in the energy industry.
A Technological Update on Heat Pumps for Industrial Applications
Authors: Bobbo Sergio , Lombardo Giulia , Menegazzo Davide , Vallese Laura , Fedele Laura
Published: October 2024

It is now widely confirmed by scientific evidence that greenhouse gas emissions must be reduced to counteract the effects of global warming. The production of heat for industrial purposes is responsible for 36.8% of world energy-related emissions due to the widespread use of fossil fuels. Heat pumps are a key technology in the transition towards more sustainable industrial processes. In this paper, a systematic review of the literature produced in the last 5 years in international journals regarding the integration of heat pumps in industrial processes is presented. Firstly, papers presenting innovative configurations for high temperature heat pumps (HTHP), i.e., heat pumps delivering temperatures in the range between 100 °C and 200 °C, suitable for many industrial processes but still under development, are reviewed. Then, papers reporting innovative solutions for the integration of heat pumps in specific industrial processes and sectors (e.g., distillation, drying, desalination, etc.) are analyzed. Finally, the literature about alternative low-GWP refrigerants for industrial heat pumps, both pure compounds and mixtures, is described. It is concluded that many progresses have been realized in the last 5 years (2020–2024) regarding the identification of innovative heat pumps for industrial applications, but further research is certainly required.
Research on the Performance and Control Strategy of Electro-Hydraulic Servo System for Selective Hole Digging Tree Planter
Authors: Zhu Binhai , Liu Jiuqing , Yu Hang , Yu Li , Wang Zhenli , Zhou Huan , Yang Chunmei
Published: October 2024

Compared to agricultural environments, afforestation sites are more complex, often presenting issues such as undulating and uneven terrain. These conditions lead to instability in hole digging depth and plant spacing during continuous movement, and the hole shape may not meet expectations. Additionally, the hydraulic system exhibits slow response speed and long steady-state time, affecting the quality of sapling planting. To address these issues, this paper designs an intelligent planting control system for intermittent hole digging under continuous dynamic movement, based on a large tree planter. The focus is on studying the dynamic accuracy of the hole digging cylinder to resolve the instability of plant spacing and planting depth in actual planting processes. Firstly, a motion trajectory model of the intermittent hole digging mechanism is established to obtain the relationship between the displacement trajectory of the rotating cutter and the displacements of the floating cylinder and the hole digging cylinder. Secondly, a mathematical model of the electro-hydraulic servo system is established to control the dynamic accuracy of the hole digging operation. Finally, a Simulink simulation model of the system is established to analyze the performance indicators of the hydraulic system during operation using step and sinusoidal excitation signals. The test results show that the displacement of the hydraulic piston rod can ensure a linear extension trend within the range of 0 to 0.4 m, and the extension distance of the hole digging cylinder in the planting system is 0 to 0.35 m, ensuring linear change within this stroke. When the system’s extension command is 1 V, the actual output is 0.6 m, with a relative error of less than 10% compared to the simulation value, indicating that the control strategy can effectively improve the dynamic performance of the system. When the hydraulic system is in a steady-state extension state at 50 to 58.6 s, the relative error with the simulation value is 7.3%, meeting the “double ten indicators” requirement. The research results clearly verify the superior performance of the proposed intelligent control system, and the proposed control strategy has great potential in practical applications, promising to improve afforestation quality by stabilizing planting spacing and planting depth.
Feeding Behavior and Bait Selection Characteristics for the Portunidae Crabs Portunus sanguinolentus and Charybdis natator
Authors: Lee Wei-Yu , Wu Yan-Lun , Naimullah Muhamad , Liang Ting-Yu , Lan Kuo-Wei
Published: October 2024

Understanding the feeding behavior of Portunidae crabs with different baits can improve bait selection and is crucial for improving the effectiveness of crab fishing gear. This study, conducted in indoor experimental tanks, used trajectory tracking software and two types of natural baits (mackerel (Scomber australasicus) and squid (Uroteuthis chinensis)) to understand the behavior of Portunus sanguinolentus and Charybdis natator. Spatial distribution results showed that P. sanguinolentus was frequently present in the starting area (S1) and bait area (S3) in the control and treatment groups. However, C. natator was frequently present and concentrated in the S1 area compared to the middle areas S2 and S3, and only in the mackerel treatments were they observed to move to the S3 areas. The spatial distribution results indicate that P. sanguinolentus shows a stronger willingness to explore its surroundings, while C. natator is generally in a stationary, wait-and-see state. The swimming speeds of P. sanguinolentus and C. natator showed different trends. P. sanguinolentus showed continuous movement with no fixed speed when no bait was present in the control groups. However, when treated with mackerel and squid, the average swimming speed of P. sanguinolentus was faster (>5 cm/s) in the first 10 min and showed a more stable movement speed when searching for the baits. C. natator showed a stationary or low movement speed when no bait was present in the control groups. However, when C. natator perceived the presence of the baits in the treatment groups, their movement speed increased in the first 10 min. In addition, there was no significant difference between male and female crabs of P. sanguinolentus and C. natator in movement speed in the control and treatment groups. Compared to C. natator, P. sanguinolentus might be more sensitive to natural baits, as shown by its movement from S1 to S3. The results indicate that the species of Portunidae crabs show different bait selections. Natural baits (mackerel and squid) are recommended for catching P. sanguinolentus in crab fisheries.
Subacute Toxicity and Pharmacokinetic Evaluation of the Synthetic Cannabinoid 4F-MDMB-BUTINACA in Rats: A Forensic and Toxicological Perspective
Authors: Abdelgadir Elkhatim Hassan , Al-Qudsi Jihad , Abu-Nukhaa Elham S. , Alsidrani Dimah A.
Published: October 2024

Background: 4-MDMB-BUTINACA, a next-generation synthetic cannabinoid, presents significant public health and forensic challenges due to its evolving nature and potential toxicity. Methods: This study evaluates the subacute toxic effects and pharmacokinetics of 4−Fluoro MDMB−BUTINACA (4F-MDMB-BUTINACA) in adult male albino rats, administered orally for seven days at doses of 1 mg/kg, 5 mg/kg, and 15 mg/kg. The hematological, biochemical, and histopathological parameters were assessed and compared to controls. Results: The pharmacokinetics were determined using GC–MS/MS with a positive chemical ionization and granisetron as an internal standard. A histological analysis revealed inflammatory cell aggregation, congestion, hemorrhage, edema, and fibrosis in various tissues, with renal examinations showing tubule degradation, glomerular atrophy, Bowman’s space expansion, edema, and hemorrhage. The liver exhibited cellular infiltration, while cardiac muscle fibers showed myocardial fiber degradation and inflammatory cell aggregation. Biochemical assays indicated significant alterations (p < 0.05) in the serum levels of AST, ALT, ALP, GGT, total protein, albumin, triglycerides, urea, MCHC, MCV, RDW, platelets, neutrophils, eosinophils, and basophils compared to the controls. Conclusions: The validated bioanalytical method revealed rapid absorption of 4F-MDMB-BUTINACA, with a plasma half-life of 2.371 h, a volume of distribution of 2272.85 L, and a plasma clearance rate of 664.241 L/h. In conclusion, 4F-MDMB-BUTINACA is a highly toxic synthetic cannabinoid, particularly affecting the liver, kidneys, and heart.
The Potential of Using Generative AI/NLP to Identify and Analyse Critical Incidents in a Critical Incident Reporting System (CIRS): A Feasibility Case–Control Study
Authors: Hölzing Carlos Ramon , Rumpf Sebastian , Huber Stephan , Papenfuß Nathalie , Meybohm Patrick , Happel Oliver
Published: October 2024

Background: To enhance patient safety in healthcare, it is crucial to address the underreporting of issues in Critical Incident Reporting Systems (CIRSs). This study aims to evaluate the effectiveness of generative Artificial Intelligence and Natural Language Processing (AI/NLP) in reviewing CIRS cases by comparing its performance with human reviewers and categorising these cases into relevant topics. Methods: A case–control feasibility study was conducted using CIRS cases from the German CIRS-Anaesthesiology subsystem. Each case was reviewed by a human expert and by an AI/NLP model (ChatGPT-3.5). Two CIRS experts blindly assessed these reviews, rating them on linguistic quality, recognisable expertise, logical derivability, and overall quality using six-point Likert scales. Results: On average, the CIRS experts correctly classified 80% of human CIRS reviews as created by a human and misclassified 45.8% of AI reviews as written by a human. Ratings on a scale of 1 (very good) to 6 (failed) revealed a comparable performance between human- and AI-generated reviews across the dimensions of linguistic expression (p = 0.39), recognisable expertise (p = 0.89), logical derivability (p = 0.84), and overall quality (p = 0.87). The AI model was able to categorise the cases into relevant topics independently. Conclusions: This feasibility study demonstrates the potential of generative AI/NLP in analysing and categorising cases from the CIRS. This could have implications for improving incident reporting in healthcare. Therefore, additional research is required to verify and expand upon these discoveries.
The Incidence of Clinical Injuries among Undergraduate Dental Students: A Prevention Protocol
Authors: Antoniadou Maria , Chanioti Maria , Pantelaki Asteropi , Parasyris Antonios , Piperi Evangelia , Rahiotis Christos
Published: October 2024

Dental students are frequently exposed to percutaneous injuries (PCIs) due to the nature of their clinical work, which involves sharp instruments and close patient contact. The COVID-19 pandemic further emphasized the need for stringent biosafety measures and the use of personal protective equipment (PPE). Despite these precautions, injuries remain prevalent, highlighting the need for comprehensive education and training in biosafety and infection control. This study investigates the incidence and causes of injuries among undergraduate dental students during clinical sessions. This study was conducted at the Department of Dentistry, National and Kapodistrian University of Athens, focusing on injuries reported from 2021 to 2024. Data were collected through self-reported clinical records. The primary variables assessed included the type of injury, the instrument involved, the clinical procedure performed, and the immediate actions taken post-injury. Serological testing was conducted on students and patients to assess the risk of the transmission of bloodborne pathogens. The findings reveal a high prevalence of injuries, with needles being the most common cause (51.4%), followed by other tools such as dental probes (25.7%) and burs (8.6%). The most frequent injury type is piercing (74.2%), primarily affecting the fingers (88.6%). Periodontal treatments, restorative procedures, and endodontic treatments are the main activities leading to injuries, with 17.1% of injuries being caused by each. No statistically significant results are recorded. Despite regular medical records for most patients treated by injured students, serological testing shows significant positivity rates for HCV and HBV. Notably, most injured students demonstrate their commitment to safety by adhering to recommended post-exposure protocols, including wound cleaning, disinfecting, and serological testing. Furthermore, the impact of COVID-19 heightened the importance of personal protective equipment (PPE) and reinforced occupational health standards. Our study highlights the critical need for enhanced biosafety awareness and training among undergraduate dental students to reduce injury risks.
Hydrogel-Mediated Local Delivery of Induced Nephron Progenitor Cell-Sourced Molecules as a Cell-Free Approach for Acute Kidney Injury
Authors: Park Kyoungmin , Gao Wei-Wei , Zheng Jie , Oh Kyung Taek , Kim In-Yong , You Seungkwon
Published: October 2024

Acute kidney injury (AKI) constitutes a severe condition characterized by a sudden decrease in kidney function. Utilizing lineage-restricted stem/progenitor cells, directly reprogrammed from somatic cells, is a promising therapeutic option in personalized medicine for serious and incurable diseases such as AKI. The present study describes the therapeutic potential of induced nephron progenitor cell-sourced molecules (iNPC-SMs) as a cell-free strategy against cisplatin (CP)-induced nephrotoxicity, employing hyaluronic acid (HA) hydrogel-mediated local delivery to minimize systemic leakage and degradation. iNPC-SMs exhibited anti-apoptotic effects on HK-2 cells by inhibiting CP-induced ROS generation. Additionally, the localized biodistribution facilitated by hydrogel-mediated iNPC-SM delivery contributed to enhanced renal function, anti-inflammatory response, and renal regeneration in AKI mice. This study could serve as a ‘proof of concept’ for injectable hydrogel-mediated iNPC-SM delivery in AKI and as a model for further exploration of the development of cell-free regenerative medicine strategies.
Blood–Brain Barrier Disruption in Neuroimmunological Disease
Authors: Shimizu Fumitaka , Nakamori Masayuki
Published: October 2024

The blood–brain barrier (BBB) acts as a structural and functional barrier for brain homeostasis. This review highlights the pathological contribution of BBB dysfunction to neuroimmunological diseases, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), autoimmune encephalitis (AE), and paraneoplastic neurological syndrome (PNS). The transmigration of massive lymphocytes across the BBB caused by the activation of cell adhesion molecules is involved in the early phase of MS, and dysfunction of the cortical BBB is associated with the atrophy of gray matter in the late phase of MS. At the onset of NMOSD, increased permeability of the BBB causes the entry of circulating AQP4 autoantibodies into the central nervous system (CNS). Recent reports have shown the importance of glucose-regulated protein (GRP) autoantibodies as BBB-reactive autoantibodies in NMOSD, which induce antibody-mediated BBB dysfunction. BBB breakdown has also been observed in MOGAD, NPSLE, and AE with anti-NMDAR antibodies. Our recent report demonstrated the presence of GRP78 autoantibodies in patients with MOGAD and the molecular mechanism responsible for GRP78 autoantibody-mediated BBB impairment. Disruption of the BBB may explain the symptoms in the brain and cerebellum in the development of PNS, as it induces the entry of pathogenic autoantibodies or lymphocytes into the CNS through autoimmunity against tumors in the periphery. GRP78 autoantibodies were detected in paraneoplastic cerebellar degeneration and Lambert–Eaton myasthenic syndrome, and they were associated with cerebellar ataxia with anti-P/Q type voltage-gated calcium channel antibodies. This review reports that therapies affecting the BBB that are currently available for disease-modifying therapies for neuroimmunological diseases have the potential to prevent BBB damage.
Breeding Maize Hybrids with Improved Drought Tolerance Using Genetic Transformation
Authors: Li Zhaoxia , Zhang Juren , Song Xiyun
Published: October 2024

Drought is considered the main agricultural menace, limiting the successful realization of land potential, and thereby reducing crop productivity worldwide. Therefore, breeding maize hybrids with improved drought tolerance via genetic manipulation is necessary. Herein, the multiple bud clumps of elite inbred maize lines, DH4866, Qi319, Y478 and DH9938, widely used in China, were transformed with the Escherichia coli betA gene encoding choline dehydrogenase (EC 1.1.99.1), a key enzyme in the biosynthesis of glycine betaine from choline, using Agrobacterium to generate betA transgenic lines. After 3–4 consecutive generations of self-pollination in these transgenic plants, progenies with a uniform appearance, excellent drought tolerance, and useful agricultural traits were obtained. We evaluated the drought tolerance of T4 progenies derived from these transgenic plants in the field under reduced irrigation. We found that a few lines exhibited much higher drought tolerance than the non-transformed control plants. Transgenic plants accumulated higher levels of glycine betaine and were relatively more tolerant to drought stress than the controls at both the germination and early seedling stages. The grain yield of the transgenic plants was significantly higher than that of the control plants after drought treatment. Drought-tolerant inbred lines were mated and crossed to create hybrids, and the drought tolerance of these transgenic hybrids was found to be enhanced under field conditions compared with those of the non-transgenic (control) plants and two other commercial hybrids in China. High yield and drought tolerance were achieved concurrently. These transgenic inbred lines and hybrids were useful in marginal and submarginal lands in semiarid and arid regions. The betA transgene can improve the viability of crops grown in soils with sufficient or insufficient water.