bluuebunny/crossref_metadata_2025 huggingface dataset:
Porous Metal Backing for High-Temperature Ultrasonic Transducers
Authors: Feuillard Guy , Nguyen Dang Chi , Lethiecq Marc , Jean Mathieu , Navacchia Frédéric
Published: November 2024

Improving the performance of high-temperature ultrasonic transducers is a goal of major importance in many industrial applications. To this aim, we propose to use porous metals that support high temperatures as backings. Thus, the acoustic properties of stainless steel and porous stainless steel with porosity of 25% and 35% are determined at ambient temperature and up to 400 °C. Over the temperature range, the longitudinal wave velocity variation is comprised between 5% and 6% in the porous metals. We find that temperature does not significantly affect the attenuation in the material. The pulse-echo response and frequency response of a LiNbO3-based transducer with a porous backing are simulated using a one dimensional electroacoustic model. These simulations, compared to those of a reference transducer, show that the axial resolution with such a design allows these transducers to be used for imaging and/or Non-Destructive Testing and evaluation at high temperature.
Enhanced Operation Mode Design and Motion Control of a Dual-Redundancy Electro-Hydrostatic Actuator
Authors: Jin Huatao , Li Shuanglu , Yin Yaobao , Guo Rui , Fang Cheng , Zou Jiangkun
Published: November 2024

In dual-redundancy electro-hydrostatic actuators (EHAs), the dual pumps are mainly designed for safety, where the cylinder is controlled mainly by one pump while the other one is standby for redundancy. However, such a strategy is basically like a single-pump-controlled system, and the flow from the pump may be inaccurate when the cylinder moves slowly, which will affect the motion control performance. A new dual-redundancy EHA is designed, and a series of corresponding operation modes are developed, enabling differential operation of the dual pumps. With the proposed operation modes, the inevitable flow inaccuracy problem of the single pump can be addressed through the coordination control of the dual pumps. In order to achieve better motion tracking performance, a model-based backstepping controller is synthesized, where the nonlinearities and uncertainties of the EHA are handled by model compensation and robust feedback design. Comparative simulations with existing control methods for EHAs are conducted and better motion tracking precision is achieved, especially during low-speed motion.
Green Intellectual Capital and Corporate Environmental Performance: Does Environmental Management Accounting Matter?
Authors: Alnaim Musaab , Metwally Abdelmoneim Bahyeldin Mohamed
Published: November 2024

This study investigates the relationship between green intellectual capital and corporate environmental performance, with a specific focus on the moderating role of environmental management accounting. Data were collected from a sample of 298 employees working in the Egyptian industrial sector and analyzed using smart partial least squares (SmartPLS) software. The empirical results revealed a statistically positive and significant impact of all green intellectual capital components on corporate environmental performance, indicating that green intellectual capital is a critical determinant in enhancing environmental performance. Further, the analysis reveals that environmental management accounting functions as a significant moderator in the relationship between green intellectual capital and corporate environmental performance. The model explains 80.2% of the variance in corporate environmental performance, providing strong empirical support for this study’s hypotheses. These findings have important practical implications for companies working in the Egyptian context. They can help in guiding the development of corporate policies and strategies that improve environmental performance. This research also makes a significant contribution to the literature by being one of the first to study the moderating role of environmental management accounting practices in an emerging market like Egypt, as most early studies have concentrated on the direct relationship between green intellectual capital, environmental management accounting, and corporate environmental performance. This helps in better understanding of these concepts and how they interact.
A Novel Magnetic Integration High-Efficiency Converter with Low Ripple and High Dynamic Response for the Hybrid Power Supply Systems of All-Electric Aircraft
Authors: Chen Li , Gao Haifeng , Shen Fengjie , Zhang Yiyi , Qiu Liangjie , Wang Lei
Published: November 2024

With the continuous improvement of battery energy density and converter power density, as well as the miniaturization and lightweighting of related airborne electrical equipment, all-electric aircraft with hybrid power supply systems provide more trade-off space and possibilities for the design of future aircraft. It is indispensable to search for a more valuable topology and apply it to airborne power supply. This paper proposes an airborne high-gain unidirectional DC-DC converter suitable for between low-voltage unit and high-voltage bus, which consists of interleaved magnetic integrated switched coupled inductor units and improved switch capacitor units. This paper first analyzes the steady-state operating characteristics under different modes; the new topology has higher voltage gain and lower stress. Secondly, in response to the challenges of high efficiency and high power density, we propose a magnetic integration design method and comprehensive experimental scheme based on the EIE-type magnetic core structure. This successfully integrates multiple discrete inductors into a single magnetic core. Furthermore, based on the comprehensive consideration of steady-state, transient performance and power density, the general design criteria for a high-gain switched coupled inductor are summarized through the equivalent mathematical model of reverse flux coupling. Additionally, by adjusting the coupling coefficient, the converter can achieve zero-voltage switching under light load conditions, demonstrating versatility and scalability and better meeting the application requirements of electric aircraft. The proposed prototype can provide voltage gain in the range of 12–22 times the input voltage gain by varying the input voltage from a 12–24 V fuel cell. The comprehensive performance of the converter, including steady-state, transient, and efficiency, was tested under D < 0.5 and D > 0.5. The experimental results show that the proposed converter possesses advantages such as high gain and low stress, a high dynamic response and low ripple, and high efficiency and high power density, which can provide a more advantageous DC-DC converter solution for airborne hybrid power supply systems.
Online Task Switching and Scheduling Method for Attitude–Orbit–Shape-Distributed Control of Large Space Ring Structures
Authors: Han Shuo , Wang Miao , Xue Cong , Yao Weiran , Sun Guanghui
Published: November 2024

The attitude, orbit, and shape control actuators of large space structures on orbits are functional overlapping and task coupled, resulting in actuator redundancy and high-energy consumption. This paper explores the integrated attitude–orbit–shape control problem of large space ring structures and proposes an online task switching and scheduling method for multiple actuators of space structures (OTSS-MASS). An adaptive allocation framework is proposed for the task switching of distributed actuators. The objectives of attitude–orbit–shape control are decomposed into attitude adjustment, orbit change, and shape maintenance tasks through a task decomposition algorithm. Task value estimation models are designed to guide a greedy task allocation of actuators. The adaptive allocation framework achieves online task reconfiguration for multiple distributed actuators, thereby enhancing the maneuverability of large space structures, improving actuator work efficiency, and reducing energy consumption in orbit. Simulation results demonstrate that OTSS-MASS outperforms the conventional actuator distribution methods. The overall effectiveness is improved by over 24% in terms of the comprehensive index, time index, trajectory index, and shape index.
Nitrogen Residual Effect of Winter Cover Crops on Maize in Uruguay: Conventional and Isotopic Evaluation
Authors: Mori Alvez Cristina , Perdomo Varela Carlos , del Pino Machado Amabelia
Published: November 2024

This study aimed to evaluate the nitrogen (N) residual effects of winter cover crops (CCs) on soil N availability and corn (Zea mays L.) performance over two growing seasons and at two sites in Uruguay. Both conventional and isotopic methods were used to assess the N residual effects of two legume monocultures, a legume–grass mixture, an oat monoculture, and a control without CCs. The experimental design was a randomized block with split plots, where CCs were applied to main plots and N rates (0 and 100 kg ha⁻1) to subplots. An isotopic trial with 15N was included to measure fertilizer N use efficiency (NUE). Results varied between sites: at Site 1, legume monocultures enhanced soil N availability and, along with N rate, significantly increased corn yield and N uptake. At Site 2, only the N rate affected these variables. Site 1 had a low crop 15N recovery, averaging 9.5% due to weeds and heavy rainfall, while Site 2 showed higher recovery, notably when corn succeeded lupine (35%) and mixture CCs (40%). The soil’s top layer and corn grain showed the highest 15N concentration. The study suggests that specific CC combinations tailored to site conditions may optimize corn yield and NUE.
Design, Development, Integration, and Field Evaluation of a Ridge-Planting Strawberry Harvesting Robot
Authors: Yu Yang , Xie Hehe , Zhang Kailiang , Wang Yujie , Li Yutong , Zhou Jianmei , Xu Lizhang
Published: November 2024

Due to the complex unstructured environmental factors in ridge-planting strawberry cultivation, automated harvesting remains a significant challenge. This paper presents an oriented-ridge double-arm cooperative harvesting robot designed for this cultivation. The robot is equipped with a novel non-destructive harvesting end-effector and two self-developed specialized manipulators, integrated with the strawberry picking point visual perception system based on the lightweight Mask R-CNN and a CAN bus-based machine control system. The greenhouse harvesting experiments show that the robot achieved an average harvesting success rate of 49.30% in natural environments after flower and fruit thinning, while only a 30.23% success rate was achieved in untrimmed natural environments. This indicates that the agronomic practice of flower and fruit thinning can significantly simplify the automated harvesting environment and improve harvesting performance. Automated harvesting efficiency test results show that the single-arm average harvesting speed is 7 s per fruit, while double-arm cooperative harvesting can achieve 4 s per fruit. Future expansion by increasing the number of robotic arms could significantly improve harvesting efficiency. However, the study conducted for this paper was poor for those strawberries whose body or stem was severely blocked, which should be further improved upon in follow-up studies.
Design and Testing of a Tractor Automatic Navigation System Based on Dynamic Path Search and a Fuzzy Stanley Model
Authors: Cui Bingbo , Cui Xinyu , Wei Xinhua , Zhu Yongyun , Ma Zhen , Zhao Yan , Liu Yufei
Published: November 2024

Smart agriculture development mainly depends on the intelligence and reliability of autonomous agricultural machinery. Automatic navigation systems (ANSs) play a key role in intelligent agricultural machinery design, as they not only reduce farmers’ workloads but also improve their land utilization rates. In this paper, a tractor ANS based on dynamic path search and a fuzzy Stanley model (FSM) was designed, and its capability for whole-field path tracking was tested. First, the tracking performance of the steering control module was validated after the automatic reconstruction of the tractor platform. Then, a navigation decision system was established based on a unified reference waypoint search framework, where the path generation for whole-field coverage was presented. Finally, the gain coefficient of the Stanley model (SM) was adjusted adaptively according to the tracking error by utilizing the fuzzy logic controller. Subsequently, the developed tractor ANS was tested in the field. The experiment’s results indicate that the FSM outperformed the SM in straight path tracking and whole-field path tracking. When the tractor traveled at a speed of 1 m/s, the maximum lateral tracking error for the straight path was 10 cm, and the average lateral tracking error was 5.2 cm, showing improvements of 16.7% and 10.3% compared to the SM. Whole-field autonomous navigation showed that the maximum lateral tracking error was improved from 34 cm for the SM to 27 cm for the FSM, a reduction of approximately 20.6%, illustrating the superiority of the FSM in the application of whole-field path tracking. As the maximum tracking error of whole-field autonomous navigation appears in the turning stage, where tractors often stop working, the designed ANS satisfies the requirements of a self-driving system for unmanned tractors.
Functional Analysis of Two Carboxylesterase Genes Involved in Beta-Cypermethrin and Phoxim Resistance in Plutella xylostella (L.)
Authors: Li Ran , Liang Liang , Zhao Yujia , Zhang Junyi , Hao Zhiyuan , Zhao Haibo , Liang Pei
Published: November 2024

Enhanced expression of carboxylesterase (CarE) genes is an important mechanism of insecticide resistance in pests. However, their roles in multi-insecticide resistance have rarely been reported. Herein, two CarE genes (PxαE6 and PxαE9) were identified; their relative expression levels in three multi-insecticide-resistant populations of P. xylostella (HN, GD-2017 and GD-2019) were 2.69- to 15.32-fold higher than those in the sensitive population, and they were considerably overexpressed at the larval stage and in the midgut of the 4th instar. PxαE6 and PxαE9 knockdown increased the susceptibility of GD-2019 larvae to phoxim or/and beta-cypermethrin. The recombinant PxαE6 and PxαE9 expressed in Escherichia coli exhibited high hydrolysis activity towards α-NA. GC–MS and LC–MS/MS assays revealed that PxαE9 could metabolize beta-cypermethrin and phoxim with efficiency determinations of 51.6% and 21.1%, respectively, while PxαE6 could metabolize phoxim with an efficiency of 12.0%. Homology modelling, molecular docking and molecular-dynamics simulation analyses demonstrated that beta-cypermethrin or/and phoxim could fit well into the active pocket and stably bind to PxαE6 or PxαE9. These results show that PxαE6 and PxαE9 overexpression were involved in resistance to beta-cypermethrin or/and phoxim in multi-insecticide-resistant P. xylostella populations, a finding which sheds light on the molecular mechanisms of multi-insecticide resistance in insect pests.
Impact of No Tillage and Low Emission N Fertilization on Durum Wheat Sustainability, Profitability and Quality
Authors: De Santis Michele Andrea , Giuzio Luigia , Tozzi Damiana , Soccio Mario , Flagella Zina
Published: November 2024

Mitigation practices for cereal systems, including conservation agriculture and low emission fertilization, are required to face global challenges of food security and climate change. The combination of these climate-smart approaches was investigated for durum wheat in a dry region of the Mediterranean basin in two crop seasons. The experimental design consisted in two different genotypes, Marco Aurelio (high protein content) and Saragolla (higher adaptability), subjected to no tillage (NT) vs. conventional tillage (CT) and to two fertilization strategies (standard vs. low emission plus an unfertilized control). Different environmental and economic sustainability parameters as well as two different technological and nutritional quality traits were evaluated. Saragolla showed a better environmental adaptability and a higher nitrogen use efficiency, evaluated as partial nutrient balance (+27%), and was associated with a lower protein content (14.5% vs. 15.6%). NT was associated with an improvement in yield (+15%) and quality, i.e., micronutrients (Fe, Zn) and antioxidant capacity (+15%), in the drier crop year. Low emission fertilization did not reduce crop performance and its combination with NT showed a higher economic net return. The combination of the two mitigation practices improved not only environmental and economic sustainability but also the health quality of durum wheat under water limited conditions.
Genomic Prediction of Kernel Water Content in a Hybrid Population for Mechanized Harvesting in Maize in Northern China
Authors: Luo Ping , Yang Ruisi , Zhang Lin , Yang Jie , Wang Houwen , Yong Hongjun , Zhang Runze , Li Wenzhe , Wang Fei , Li Mingshun , Weng Jianfeng , Zhang Degui , Zhou Zhiqiang , Han Jienan , Gao Wenwei , Xu Xinlong , Yang Ke , Zhang Xuecai , Fu Junjie , Li Xinhai , Hao Zhuanfang , Ni Zhiyong
Published: November 2024

Genomic prediction enables rapid selection of maize varieties with low kernel water content (KWC), facilitating the development of mechanized maize harvesting and reducing costs. This study evaluated and characterized the KWC and grain yield (GY) of hybrid maize in northern China and used genomic prediction to identify superior hybrid combinations with low kernel water content at maturity (MKWC) and high GY adapted to northern China. A total of 285 hybrids obtained from single crosses of 34 inbred lines from Stiff Stalk and Non-Stiff Stalk heterotic groups were used for genomic prediction of KWC and GY. We tested 20 different statistical prediction models considering additive effects and evaluating the impact of dominance and epistasis on prediction accuracy. Employing 10-fold cross-validation, it showed that the average prediction accuracy ranged drastically from 0.386 to 0.874 across traits and models. Eight linear statistical methods displayed a very similar prediction accuracy for each trait. The average prediction accuracy of machine learning methods was lower than that of linear statistical methods for KWC-related traits, but the random forest model had a high prediction accuracy of 0.510 for GY. When genetic effects were incorporated into the prediction model, the prediction accuracy for each trait was improved. Overall, the model with dominant and epistatic effects (G:AD(AA)) performed best. For the same number of markers, predictions using trait-specific markers resulted in higher prediction accuracy than randomly selected markers. When the number of trait-specific SNPs was set to 100, the prediction accuracy of GY increased by 33.27%, from 0.406 to 0.541. Out of all the 561 potential hybrids, the TOP 30 hybrids selected by genomic prediction would lead to a 1.44% decrease in MKWC compared with Xianyu335, a hybrid with a fast kernel water dry-down, and these hybrids also had higher GY simultaneously. Our results confirm the value of genomic prediction for hybrid breeding low MKWC suitable for maize mechanized harvesting in northern China. In conclusion, this study highlights the potential of genomic prediction to optimize maize hybrid breeding, enhancing efficiency and providing insights into genotype-accuracy relationships. The findings offer new strategies for hybrid design and advancing mechanized harvesting in northern China.
RNA-Sequencing Analysis of the Viral Community in Yellow Catfish (Pelteobagrus fulvidraco) in the Upper Reaches of the Yangtze River
Authors: Liu Wenzhi , Tian Huiwu , Ma Jie , Xue Mingyang , Zhou Yong , Li Mengmeng , Jiang Jingwen , Fan Yuding , Liu Mingdian
Published: November 2024

Different viruses are abundant in aquatic ecosystems. There has been limited research on the viral communities in the upper reaches of the Yangtze River. Yellow catfish (Pelteobagrus fulvidraco), an important economic fish that is widely distributed in the upper reaches of the Yangtze River, was selected as the research object. Using RNA sequencing, we identified 11 viruses belonging to the Adintoviridae, Tombusviridae, Caudovirales, Microviridae, Picornavirales, and other bacteriophage families. The predominant viral families/order in Luzhou (LZ), Fuling (FL), and Wanzhou (WZ) were Caudovirales, Adinoviridae, and Microviridae, respectively. The virome from WZ had a unique community composition, with a high abundance of Picornavirales compared with LZ and FL. In LZ, the predominant double-stranded RNA virus family was Siphoviridae. Phylogenetic analyses showed that viruses presented high genetic diversity. Phylogenetically, Wenling pleuronectiformes picornavirus was close to the family Caliciviridae, which includes yellow catfish calicivirus (YcCV), responsible for the massive mortality of yellow catfish in 2020. This study provides insights into the viral community composition in yellow catfish in the upper reaches of the Yangtze River, revealing a diverse and unique river water virome and providing clues for future research on the origin of viral pathogens.
Sustainable Alternatives to the Reduction of Plastic Straws Used with Chilled Equine Semen
Authors: González Noelia , Peñalosa Aroa , de Blas Ignacio , Gil Lydia
Published: November 2024

Currently, plastic is used being without any limitations. The livestock sector is no stranger to its use. For example, artificial insemination involves the use of different plastic materials, including semen straws and insemination catheters, which increase the levels of waste in our environment. Finding a sustainable solution to avoid plastic materials is a challenge. The aim of this study was to examine different biodegradable materials as alternatives to conventional syringes used for refrigerated equine semen. The materials tested were bamboo, avocado, grass, paper, Kraft paper, wheat, and rice. Bamboo and avocado were selected to continue testing with the refrigerated semen with a lifespan extended by INRA 96®; the rest of the materials did not meet the requirements necessary for preservation. Motility and movement kinetics tests were performed at 24 and 96 h of refrigeration to evaluate semen quality; relative to the control, significantly better results were displayed in regard to the total and progressive motility avocado straws. The kinetic parameters were comparable to the control for both materials and within normal ranges. After performing a microbiological control process for both straws, it was confirmed that there was no bacterial growth in either straw. We can confirm that avocado straws can be used to preserve chilled equine semen, guaranteeing seminal quality while being respectful to the environment.
Effects of Dietary Supplementation of DL-Methionine or DL-Methionine Hydroxyl Analogue (MHA-Ca) on Growth Performance and Blood and Liver Redox Status in Growing Pigs
Authors: Oladejo Emmanuel , Hasan Md , Sotak Susan , Htoo John , Brett James , Feugang Jean , Liao Shengfa
Published: November 2024

Oxidative stress impairs pigs’ health and production performance. This study examined the effects of level and source of methionine (Met) supplementation against the diquat-induced oxidative stress in pigs. Forty growing barrows were randomly assigned to four groups. Groups 1 and 2 received a basal diet that was adequate in energy and nutrients (Diet 1), Group 3 received a DL-Met-supplemented diet, and Group 4 received an MHA-Ca-supplemented diet. After 3 weeks of feeding (Phase 1), pigs were injected with 10 mL saline (Group 1) or 10 mg/kg-BW diquat in 10 mL saline (Groups 2, 3, and 4), and then continually fed for one week (Phase 2). During or at the end of Phase 1, there were no differences in nearly all of the growth performance and redox parameters among the four groups. During or at the end of Phase 2, however, the ADFI and ADG were lower (p < 0.01) in Group 2 than in Group 1 while the serum malondialdehyde content was higher (p < 0.05) in Group 2 than in Group 1. The serum glutathione peroxidase (GPX) activity and liver superoxide dismutase (SOD) activity were lower (p < 0.05) in Group 2 than in Group 1. The serum GPX activity, the serum total antioxidant capacity, and the liver GPX activity were higher (p < 0.05) in Group 3 than in Group 2. There were nearly no differences in these redox parameters between Groups 3 and 4. In conclusion, MHA-Ca and DL-Met, when used at an equivalent bioefficacy level, had similar effects on the pigs’ growth performance and antioxidative status. Therefore, increased Met supplementation can improve pigs’ antioxidative status.
A Nationwide Evaluation of Antibiotic Consumption in Kazakhstan from 2019 to 2023
Authors: Semenova Yuliya , Yergaliyeva Ademi , Aimurziyeva Ainur , Manatova Almira , Kuntuganova Anargul , Makalkina Larissa , Aldiyarova Nurgul , Semenov Daniil , Lim Lisa
Published: November 2024

Background/Objectives: There has been a lack of a holistic approach to evaluating antibiotic consumption in Kazakhstan over the past few years using an internationally recognized methodology. Therefore, this study aimed to provide a nationwide evaluation of antibiotic consumption in Kazakhstan during the period 2019–2023. Methods: Defined daily doses per 1000 inhabitants per day (DIDs) were calculated for systemic antibiotics (J01 code of the Anatomical Therapeutic Chemical Classification System (ATC)) following the methodology established by the Global Antimicrobial Resistance and Use Surveillance System (GLASS-AMC). The average annual percent change (AAPC) was computed for each chemical agent, pharmacological group, and J01 in general to evaluate past trends in antibiotic consumption. Results: The consumption of J01 antibiotics ranged between 10.869 DIDs (2022) and 14.470 DIDs (2020). There was an increase in antibiotic consumption during 2020 and 2021, but the overall trend was declining, with an AAPC of −2.45%. Azithromycin was the most consumed systemic antibiotic, followed by ceftriaxone and ciprofloxacin. The consumption of “Watch” group antibiotics prevailed in Kazakhstan during the study period, with the number of people consuming the top five “Watch” group antibiotics rising from 72,578 in 2019 to 94,617 in 2023. Conclusions: The findings of this study are crucial for the reorganization of the national antimicrobial stewardship program.
Genomic Analysis of Carbapenem-Resistant Acinetobacter baumannii Isolated from Bloodstream Infections in South Korea
Authors: Jeon Wook Jong , Kim Yoo Jung , Seo Ju Hui , Yoo Jung Sik , Moon Dong Chan
Published: November 2024

Background/Objectives: Bloodstream infection by carbapenem-resistant Acinetobacter baumannii (CRAB) is a serious clinical problem worldwide. To study its clonal relationship and genetic features, we report the draft genome sequence of CRAB strains isolated from human blood in South Korea. Methods: Among A. baumannii strains isolated from patients at nine general hospitals in 2020, 12 CRAB strains of different genotypes were selected. Genomic DNA was sequenced using a combination of Illumina MiSeq and Oxford Nanopore MinION platforms. Antimicrobial susceptibility testing was performed using the disk diffusion method. Antimicrobial resistance and virulence genes were investigated in silico using the Center for Genomic Epidemiology server and the Virulence Factors Database. Results: The multilocus sequence types of isolates included ST191, ST195, ST357, ST369, ST451, ST469, ST491, ST784, ST862, ST1933, ST2929, and a novel type, ST3326. The predominant sequence type, ST191, demonstrated close genetic relationships with several isolates, including ST469, ST369, ST195, ST784, ST491, and ST3326, with ST3326 classified as a subgroup of ST191. We found 18 antimicrobial resistance genes and one quaternary ammonium compound resistance gene. All examined strains harbored blaOXA-23, which is associated with carbapenem resistance. While variations in antibiotic and disinfectant resistance genes were observed, all isolates exhibited similar virulence factors, with the exception of the biofilm and capsule production genes. Conclusions: This nationwide report of the draft genome sequence of patient-derived strains provides valuable insights into the genomic features associated with clonal relationships and antimicrobial resistance of CRAB in bloodstream infections.
Unveiling the Dynamics of Antimicrobial Resistance: A Year-Long Surveillance (2023) at the Largest Infectious Disease Profile Hospital in Western Romania
Authors: Laitin Sorina Maria Denisa , Baditoiu Luminita Mirela , Laza Ruxandra , Stefan Irina-Maria , Besliu Razvan Sebastian , Susa Septimiu Radu , Oancea Cristian , Stoicescu Emil Robert , Manolescu Diana , Fira-Mladinescu Corneluta
Published: November 2024

Background/Objectives: Antimicrobial resistance (AMR) is a critical global health threat, leading to increased morbidity, mortality, and healthcare costs. This study aimed to identify the most common bacterial pathogens and their resistance profiles from 2179 positive clinical cultures from inpatients at “Victor Babes” Hospital of Infectious Disease and Pneumoftiziology Timisoara in 2023. Methods: Samples were collected from sputum, bronchial aspiration, hemoculture, urine, wound secretions, catheter samples, and other clinical specimens. Results: Key pathogens identified included Klebsiella pneumoniae, Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, and Acinetobacter baumannii, with notable resistance patterns, observed K. pneumoniae exhibited high resistance rates, notably 41.41% in Quarter 1, while E. coli showed 35.93% resistance in the same period. S. aureus, particularly MRSA, remained a persistent challenge, with 169 cases recorded over the year. A. baumannii and P. aeruginosa displayed alarming levels of multi-drug resistance, especially in Quarter 3 (88.24% and 22.02%, respectively). Although there was a general decline in resistance rates by Quarter 4, critical pathogens such as S. aureus and K. pneumoniae continued to exhibit significant resistance (81.25% and 21.74%, respectively). Conclusions: The study’s findings align with the broader antimicrobial resistance trends observed in Romania, where high resistance rates in K. pneumoniae, E. coli, S. aureus (MRSA), Acinetobacter, and Pseudomonas species have been widely reported, reflecting the country’s ongoing struggle with multi-drug-resistant infections. Despite some reductions in resistance rates across quarters, the persistent presence of these resistant strains underscores the critical need for strengthened antimicrobial stewardship, infection control measures, and continuous surveillance to combat the growing threat of AMR in Romania and similar healthcare settings.
Therapeutic Monitoring of Vancomycin Implemented by Eremomycin ELISA
Authors: Galvidis Inna A. , Surovoy Yury A. , Sharipov Vitaly R. , Sobolev Pavel D. , Burkin Maksim A.
Published: November 2024

Background/Objectives: Due to a narrow therapeutic window, side-effects, toxicities, and individual pharmacokinetics (PK) variability, WHO classifies vancomycin (VCM) as a “watch antibiotic” whose use should be monitored to improve clinical effectiveness. Availability and ease of use have made the immunoassay technique the basic tool for the therapeutic drug monitoring (TDM) of VCM concentrations. Methods: The present study describes the development of a TDM tool for VCM based on anti-eremomycin (ERM) antibody enzyme-linked immunosorbent assay (ELISA). Results: The optimized assay format based on coating a BSA-VCM conjugate allowed for the equal recognition of both VCM and ERM (100 and 104%) and was not influenced by concomitant antibiotics. Among the sample pretreatments studied, acetonitrile deproteinization was preferred to effectively remove the most likely matrix interferences and to provide 75–96% VCM recovery in the range of 3–30 mg/L, ensuring reliable determination of the key PK parameter, Ctrough. Higher peak concentrations were measured in more diluted samples. Several inflammatory indices, biochemical markers, and key proteins significantly different from normal in critically ill patients were investigated as assay interferers and were found not to interfere with VCM analysis. Serum samples (n = 108) from patients (n = 4) with extensive burn injuries treated with combined antibiotic therapy were analyzed for VCM using the developed assay and confirmed by LC-MS/MS, demonstrating good agreement. Conclusions: The approach used shows that the same analytical instrument is suitable for measuring structurally related analytes and is fully adequate for their therapeutic monitoring. Suboptimal exposure based on Ctrough values obtained with standard dosing regimens supports the use of TDM in these patients.
Research Updates and Advances on Flavonoids Derived from Dandelion and Their Antioxidant Activities
Authors: Zhuang Xiaocui , Shi Wei , Shen Tao , Cheng Xiaoyang , Wan Qilin , Fan Minxia , Hu Dongbao
Published: November 2024

As a common medicinal and edible plant, dandelion plays a crucial and significant role in the fields of traditional Chinese medicines, functional foods, healthcare products, daily chemicals, and feed additives, which are closely related to its rich chemical constituents and remarkable biological activities. Modern studies have demonstrated that dandelion contains all kinds of bioactive constituents, including flavonoids, amino acids, fatty acids, organic acids, phenolic acids, coumarins, lignans, polysaccharides, phytosterols, terpenes, glycoproteins, oligosaccharides, alkaloids, etc. Meanwhile, dandelion has been proven to possess antioxidant, antibacterial, anti-inflammatory, antitumor, antivirus, hypoglycemic, and hypolipidemic properties, as well as the ability to regulate hormone levels and protect some visceral organs. Among them, flavonoids derived from dandelion and their antioxidant activities have received considerable attention. This study reviews dandelion flavonoids and their in vitro and in vivo antioxidant activities by consulting and organizing relevant domestic and international works of literature to provide a scientific and theoretical basis for further research, development, and utilization of dandelion.
ZigBeeNet: Decrypted Zigbee IoT Network Traffic Dataset in Smart Home Environment
Authors: Keleşoğlu Nur , Sobczak Łukasz
Published: November 2024

The number of smart homes is increasing steadily. One of the first technologies that comes to mind when talking about smart homes is Zigbee, which stands out for its low cost, low latency, low power consumption, and mesh networking capabilities. One of the key features of Zigbee is the encryption of payloads within its frames for security purposes. However, being able to decrypt this payload is crucial for fully understanding its operation and for purposes such as testing the network’s security. Therefore, in this paper, we present the decrypted Zigbee IoT Network Traffic dataset, ZigBeeNet. We captured packets using Wireshark in real time from a smart home with 15 Zigbee devices over 20 days and saved them in pcap files. Additionally, we used a key extraction method to obtain the network key, decrypt the payload data, and analyze the characteristic features of network traffic, which we present in this paper. ZigBeeNet will be useful in wider areas than existing datasets with its ability to support network security research, pattern analysis, network performance analysis, and Zigbee traffic generator. We believe that this open-source dataset will contribute significantly to a wide range of industrial and academic research applications.
Influence of Modal Decomposition Algorithms on Nonlinear Time Series Machine Learning Prediction Models in Engineering: A Case Study of Subway Tunnel Settlement
Authors: Shen Qingmeng , Wu Yuming , Wan Limin , Chen Qian , Li Yue , Liao Zichao , Wang Wenbo , Li Feng , Li Tao , Shu Jiajun
Published: November 2024

The settlement values of subway tunnels during the construction period exhibit significant nonlinear and spatial–temporal variation characteristics. To overcome the problems of historical data interference and spatiotemporal characteristics in tunnel settlement prediction models, this paper proposes a tunnel settlement prediction method based on data decomposition, reconstruction, and optimization. First, the original data are optimized via the SSA, which has global optimization capability, high noise immunity, and high adaptivity. The original signal is subsequently decomposed into multiple subsignal sequences via a variational modal decomposition (VMD) algorithm combined with a rolling decomposition technique. Finally, the decomposed signals are fed into the machine learning model to construct a high-precision settlement prediction model based on rolling decomposition. The prediction accuracy of different models was analyzed via the measured settlement data during the construction period of the Beijing subway as an example. The results show that the prediction model with the integrated decomposition algorithm reduces the RMSE and MAE by 33% and 37%, respectively, which significantly improves the prediction accuracy and generalization ability of the neural network to meet the demand of practical engineering prediction and simultaneously enhances the risk warning ability of the model.
Optimization of Vacuum Impregnation with Aqueous Extract from Hibiscus sabdariffa Calyces in Apple Slices by Response Surface Methodology: Effect on Soluble Phenols, Flavonoids, Antioxidant Activity, and Physicochemical Parameters
Authors: Anaya-Esparza Luis Miguel , Rodríguez-Lafitte Ernesto , Villagrán Zuamí , Aurora-Vigo Edward F. , Ruvalcaba-Gómez José Martín , Símpalo-López Walter Bernardo , Martínez-Esquivias Fernando , Sarango-Córdova Cristhian Henry
Published: November 2024

Vacuum impregnation (VI) of natural extracts is often used as a pretreatment for fruit dehydration. Apple slices were subjected to VI [XVP: vacuum pressure (−0.4 to −0.2 mbar), XIT: impregnation time (2–10 min), and XRT: restoration time (1–3 min)] of Hibiscus sabdariffa (HS) calyces aqueous extract and optimized using response surface methodology (RSM). Total soluble phenols (TSP) and flavonoids, antioxidant capacity, and physicochemical parameters were evaluated before and after vacuum impregnation. Also, optimized VI apple slices were heat air-dried and characterized for all the mentioned parameters. Under the experimental conditions, all vacuum-impregnated apple slices increased in TSP content, with impregnation time, restoration time, and the interaction between impregnation time and vacuum pressure being the key factors. According to RSM, the optimal VI conditions for TSP (R2 = 0.99) were XVP −0.4 bar, XIT: 6.73 min, and XRT 3 min. VI also improved flavonoid and antioxidant activities (DPPH and ABTS) of apple slices and promoted changes in total soluble solids, pH, titratable acidity, water activity, moisture, and color (luminosity, a*, and b*) parameters. Additionally, vacuum-impregnated apple slices (under optimized conditions) were further dehydrated, resulting in an increase in soluble phenols, flavonoids, and antioxidant activity. VI with HS extract is an effective alternative for developing dehydrated apple slices with an increase in antioxidant compounds.
Interplay Between Wear and Thermal Expansion in 6082 Aluminum: A Simulation and Experimental Study
Authors: Tian Yang , Kalifa Mohamed , Khan Muhammad , Yang Yifan
Published: November 2024

This study investigates how wear and thermal expansion interact in 6082 aluminum, utilizing a pin-on-disc tribometer and finite element analysis under diverse mechanical conditions. The findings show that thermal expansion reduces contact area by forming a protrusion at the contact interface. This interaction between wear and thermal expansion causes dynamic shifts in the contact region and pressure distribution, affecting the disc center and altering wear progression and temperature patterns. High thermal expansion shifts maximum wear from the contact center to outer regions, especially at higher speeds and loads. Without thermal expansion, wear-only conditions overestimate friction dissipation, resulting in a higher peak temperature. These results highlight the critical role of thermal expansion in shaping wear patterns and contact behavior in sliding applications. This research offers insights for optimizing tribological performance in 6082 aluminum, with potential applications in other materials.
Effect of the Concentration of Bioethanol Mixed with Gasoline on the Energy and Environmental Performance of a Hybrid Vehicle in the Worldwide Harmonized Light Vehicles Test Cycle (WLTC)
Authors: Rimkus Alfredas , Mejeras Gabrielius , Dittrich Aleš , Pukalskas Saugirdas , Barta Dalibor
Published: November 2024

Increasing the use of renewable biofuels in internal-combustion-engine (ICE) vehicles is a key strategy for reducing greenhouse gas emissions and conserving fossil fuels. Hybrid vehicles used in urban environments significantly reduce fuel consumption compared to conventional internal-combustion-engine cars. In hybrid vehicles integrating electric propulsion with biofuels offers even more significant potential to lower fuel consumption. One would like to think they should also be less polluted in all cases, but some results show that the opposite is true. This study’s aim was to evaluate a hybrid vehicle’s energy and environmental performance using different gasoline–bioethanol blends. A Worldwide Harmonized Light Vehicles Test Cycle (WLTC) study was conducted on a Toyota Prius II hybrid vehicle to assess changes in energy and environmental performance. During the WLTC test, data were collected from the chassis dynamometer, exhaust gas analyser, fuel consumption meter, and engine control unit (ECU). The collected data were synchronised, and calculations were performed to determine the ICE cycle work, brake specific fuel consumption (BSFC), brake thermal efficiency (BTE), pollutant emissions (CO, HC, and NOx), CO2 mass emissions per cycle, and brake specific pollutant emissions per kilometre. The study shows that the performance of the hybrid vehicle’s ICE is strongly influenced by the utilisation of electrical energy stored in the battery, especially at low and medium speeds. As the bioethanol concentration increases, the engine’s ECU advances the ignition timing based on the knock sensor signal. A comprehensive evaluation using the WLTC indicates that increasing the bioethanol concentration up to 70% improves the energy efficiency of the hybrid vehicle’s internal combustion engine and reduces pollutant and CO2 emissions.
Securing the Future of Web-Enabled IoT: A Critical Analysis of Web of Things Security
Authors: Albarrak Khalied M.
Published: November 2024

The Web of Things (WoT) represents a significant advancement on the Internet of Things (IoT), where web technologies are integrated to enhance device interoperability and accessibility. While this integration offers numerous benefits, it also introduces new and complex security challenges. This paper presents a critical analysis of WoT security, examining the ecosystem’s vulnerabilities and associated threats. Our contributions include an in-depth analysis of existing threat enumeration methodologies, highlighting misconceptions and inefficiencies that may weaken security measures. We further conduct a comprehensive survey of critical threats within the WoT environment, detailing potential attack vectors and misuses linked to these threats. To address these security gaps, we propose a set of defenses tailored to each identified threat, providing a holistic view of the WoT’s security landscape. We also develop abstract architectural models of the WoT using UML, serving as foundational tools for understanding the interactions and risks within WoT systems. Finally, we model a specific attack scenario, demonstrating how attacks unfold in real-world WoT environments and the importance of defense strategies. These findings aim to guide the development of secure WoT systems, ensuring robust defenses against evolving security threats.
The Effect of Accelerated Storage Temperature Conditions on the Shelf Life of Pasteurized Orange Juice Based on Microbiological, Physicochemical, and Color Attributes
Authors: Frangopoulos Theofilos , Koliouskas Antonios , Petridis Dimitrios
Published: November 2024

The accelerated life testing (ASLT) method was used to evaluate the effect of increasing the storage temperature from 10 to 40 °C on the aerobic plate count (APC), the pH, and the colorimetric parameters (L*, a*, b*) of pasteurized orange juice during 40 days of storage. For APC growth, a polynomial model was found to fit better, and at the lower temperatures of 10 and 15 °C, the shelf life was longer, as expected. More specifically, 15 and 10 days were needed, respectively, until the rise in the APC population to 1000 cfu/mL. However, for the temperature range of 30–40 °C, only approximately 3 days were needed to reach 1000 cfu/mL APC. Regarding pH, according to an exponential 3P model, a stable trend was apparent at all temperatures until 30 days of storage, followed by a more abrupt decreasing trend at 25 °C. The lightness (L*), redness (a*), and yellowness (b*) of the juice showed a decreasing trend with the temperature increase, and this trend was more profound at higher temperature levels. The multiple regression analysis between the predictors L*, a*, b*, pH, storage temperature, and the APC response showed an increase in APC growth when the colorimetric parameters decreased and the temperature increased.
Creating and Validating a Ground Truth Dataset of Unified Modeling Language Diagrams Using Deep Learning Techniques
Authors: Torcal Javier , Moreno Valentín , Llorens Juan , Granados Ana
Published: November 2024

UML (Unified Modeling Language) diagrams are graphical representations used in software engineering which play a vital role in the design and development of software systems and various engineering processes. Large, good-quality datasets containing UML diagrams are essential for different areas in the industry, research, and teaching purposes; however, few exist in the literature and it is common to find duplicate elements in the existing datasets. This might affect the evaluation of the models obtained when using these datasets. This paper addresses the challenge of creating a ground truth dataset of UML diagrams, including semi-automated inspection to remove duplicates and ensuring the correct labeling of all UML diagrams contained in the dataset. In particular, a dataset of six UML diagram classes was assembled, comprising a total of 2626 images (426 activity diagrams, 636 class diagrams, 352 component diagrams, 357 deployment diagrams, 435 sequence diagrams, and 420 use case diagrams). Importantly, unlike other existing datasets, ours contains no duplicate elements and all diagrams are correctly labeled. Our curated dataset is a valuable and unique resource for the research community, serving as a foundation for training and evaluating diverse artificial intelligence models. In this paper, we demonstrate this by training and testing several deep learning models using our dataset, achieving highly satisfactory results compared to those presented in other works in the literature. Additionally, our experimental results highlight the potential of visual transformers for UML diagram classification, setting our approach apart from others that predominantly used convolutional neural networks for similar tasks.