bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermomechanical Material Characterization of Polyethylene Terephthalate Glycol with 30% Carbon Fiber for Large-Format Additive Manufacturing of Polymer Structures
Authors: Martin Katie A. , Riveros Guillermo A. , Thornell Travis L. , McClelland Zackery B. , Freeman Elton L. , Stinson James T.
Published: July 2024

Large-format additive manufacturing (LFAM) is used to print large-scale polymer structures. Understanding the thermal and mechanical properties of polymers suitable for large-scale extrusion is needed for design and production capabilities. An in-house-built LFAM printer was used to print polyethylene terephthalate glycol with 30% carbon fiber (PETG CF30%) samples for thermomechanical characterization. Thermogravimetric analysis (TGA) shows that the samples were 30% carbon fiber by weight. X-ray microscopy (XRM) and porosity studies find 25% voids/volume for undried material and 1.63% voids/volume for dry material. Differential scanning calorimetry (DSC) shows a glass transition temperature (Tg) of 66 °C, while dynamic mechanical analysis (DMA) found Tg as 82 °C. The rheology indicated that PETG CF30% is a good printing material at 220–250 °C. Bending experiments show an average of 48.5 MPa for flexure strength, while tensile experiments found an average tensile strength of 25.0 MPa at room temperature. Comparison with 3D-printed PLA and PETG from the literature demonstrated that LFAM-printed PETG CF30% had a comparative high Young’s modulus and had similar tensile strength. For design purposes, prints from LFAM should consider both material choice and print parameters, especially when considering large layer heights.
Dynamic UAV Deployment Scheme Based on Edge Computing for Forest Fire Scenarios
Authors: Zuo Weihao , Xian Yongju
Published: July 2024

This study investigates the dynamic deployment of unmanned aerial vehicles (UAVs) using edge computing in a forest fire scenario. We consider the dynamically changing characteristics of forest fires and the corresponding varying resource requirements. Based on this, this paper models a two-timescale UAV dynamic deployment scheme by considering the dynamic changes in the number and position of UAVs. In the slow timescale, we use a gate recurrent unit (GRU) to predict the number of future users and determine the number of UAVs based on the resource requirements. UAVs with low energy are replaced accordingly. In the fast timescale, a deep-reinforcement-learning-based UAV position deployment algorithm is designed to enable the low-latency processing of computational tasks by adjusting the UAV positions in real time to meet the ground devices’ computational demands. The simulation results demonstrate that the proposed scheme achieves better prediction accuracy. The number and position of UAVs can be adapted to resource demand changes and reduce task execution delays.
An MRS-YOLO Model for High-Precision Waste Detection and Classification
Authors: Ren Yuanming , Li Yizhe , Gao Xinya
Published: July 2024

With the advancement in living standards, there has been a significant surge in the quantity and diversity of household waste. To safeguard the environment and optimize resource utilization, there is an urgent demand for effective and cost-efficient intelligent waste classification methodologies. This study presents MRS-YOLO (Multi-Resolution Strategy-YOLO), a waste detection and classification model. The paper introduces the SlideLoss_IOU technique for detecting small objects, integrates RepViT of the Transformer mechanism, and devises a novel feature extraction strategy by amalgamating multi-dimensional and dynamic convolution mechanisms. These enhancements not only elevate the detection accuracy and speed but also bolster the robustness of the current YOLO model. Validation conducted on a dataset comprising 12,072 samples across 10 categories, including recyclable metal and paper, reveals a 3.6% enhancement in mAP50% accuracy compared to YOLOv8, coupled with a 15.09% reduction in volume. Furthermore, the model demonstrates improved accuracy in detecting small targets and exhibits comprehensive detection capabilities across diverse scenarios. For transparency and to facilitate further research, the source code and related datasets used in this study have been made publicly available at GitHub.
An SNR Enhancement Method for Φ-OTDR Vibration Signals Based on the PCA-VSS-NLMS Algorithm
Authors: Chen Xiaojuan , Yu Haoyu , Xu Jingyao , Gao Funan
Published: July 2024

To improve the signal-to-noise ratio (SNR) of vibration signals in a phase-sensitive optical time-domain reflectometer (Φ-OTDR) system, a principal component analysis variable step-size normalized least mean square (PCA-VSS-NLMS) denoising method was proposed in this study. First, the mathematical principle of the PCA-VSS-NLMS algorithm was constructed. This algorithm can adjust the input signal to achieve the best filter effect. Second, the effectiveness of the algorithm was verified via simulation, and the simulation results show that compared with the wavelet denoising (WD), Wiener filtering, variational mode decomposition (VMD), and variable step-size normalized least mean square (VSS-NLMS) algorithms, the PCA-VSS-NLMS algorithm can improve the SNR to 30.68 dB when the initial SNR is −1.23 dB. Finally, the PCA-VSS-NLMS algorithm was embedded into the built Φ-OTDR system, an 11.22 km fiber was measured, and PZT was added at 10.19–10.24 km to impose multiple sets of fixed-frequency disturbances. The experimental results show that the SNR of the vibration signal is 8.77 dB at 100 Hz and 0.07 s, and the SNR is improved to 26.17 dB after PCA-VSS-NLMS filtering; thus, the SNR is improved by 17.40 dB. This method can improve the SNR of the system’s position information without the need to change the existing hardware conditions, and it provides a new scheme for the detection and recognition of long-distance vibration signals.
A Robust Deep Feature Extraction Method for Human Activity Recognition Using a Wavelet Based Spectral Visualisation Technique
Authors: Ahmed Nadeem , Numan Md Obaydullah Al , Kabir Raihan , Islam Md Rashedul , Watanobe Yutaka
Published: July 2024

Human Activity Recognition (HAR), alongside Ambient Assisted Living (AAL), are integral components of smart homes, sports, surveillance, and investigation activities. To recognize daily activities, researchers are focusing on lightweight, cost-effective, wearable sensor-based technologies as traditional vision-based technologies lack elderly privacy, a fundamental right of every human. However, it is challenging to extract potential features from 1D multi-sensor data. Thus, this research focuses on extracting distinguishable patterns and deep features from spectral images by time-frequency-domain analysis of 1D multi-sensor data. Wearable sensor data, particularly accelerator and gyroscope data, act as input signals of different daily activities, and provide potential information using time-frequency analysis. This potential time series information is mapped into spectral images through a process called use of ’scalograms’, derived from the continuous wavelet transform. The deep activity features are extracted from the activity image using deep learning models such as CNN, MobileNetV3, ResNet, and GoogleNet and subsequently classified using a conventional classifier. To validate the proposed model, SisFall and PAMAP2 benchmark datasets are used. Based on the experimental results, this proposed model shows the optimal performance for activity recognition obtaining an accuracy of 98.4% for SisFall and 98.1% for PAMAP2, using Morlet as the mother wavelet with ResNet-101 and a softmax classifier, and outperforms state-of-the-art algorithms.
Traffic Feature Selection and Distributed Denial of Service Attack Detection in Software-Defined Networks Based on Machine Learning
Authors: Han Daoqi , Li Honghui , Fu Xueliang , Zhou Shuncheng
Published: July 2024

As 5G technology becomes more widespread, the significant improvement in network speed and connection density has introduced more challenges to network security. In particular, distributed denial of service (DDoS) attacks have become more frequent and complex in software-defined network (SDN) environments. The complexity and diversity of 5G networks result in a great deal of unnecessary features, which may introduce noise into the detection process of an intrusion detection system (IDS) and reduce the generalization ability of the model. This paper aims to improve the performance of the IDS in 5G networks, especially in terms of detection speed and accuracy. It proposes an innovative feature selection (FS) method to filter out the most representative and distinguishing features from network traffic data to improve the robustness and detection efficiency of the IDS. To confirm the suggested method’s efficacy, this paper uses four common machine learning (ML) models to evaluate the InSDN, CICIDS2017, and CICIDS2018 datasets and conducts real-time DDoS attack detection on the simulation platform. According to experimental results, the suggested FS technique may match 5G network requirements for high speed and high reliability of the IDS while also drastically cutting down on detection time and preserving or improving DDoS detection accuracy.
MWIRGas-YOLO: Gas Leakage Detection Based on Mid-Wave Infrared Imaging
Authors: Xu Shiwei , Wang Xia , Sun Qiyang , Dong Kangjun
Published: July 2024

The integration of visual algorithms with infrared imaging technology has become an effective tool for industrial gas leak detection. However, existing research has mostly focused on simple scenarios where a gas plume is clearly visible, with limited studies on detecting gas in complex scenes where target contours are blurred and contrast is low. This paper uses a cooled mid-wave infrared (MWIR) system to provide high sensitivity and fast response imaging and proposes the MWIRGas-YOLO network for detecting gas leaks in mid-wave infrared imaging. This network effectively detects low-contrast gas leakage and segments the gas plume within the scene. In MWIRGas-YOLO, it utilizes the global attention mechanism (GAM) to fully focus on gas plume targets during feature fusion, adds a small target detection layer to enhance information on small-sized targets, and employs transfer learning of similar features from visible light smoke to provide the model with prior knowledge of infrared gas features. Using a cooled mid-wave infrared imager to collect gas leak images, the experimental results show that the proposed algorithm significantly improves the performance over the original model. The segment mean average precision reached 96.1% (mAP50) and 47.6% (mAP50:95), respectively, outperforming the other mainstream algorithms. This can provide an effective reference for research on infrared imaging for gas leak detection.
Circularly Polarized Vivaldi Antennas Integrated with Septum-like Polarizer
Authors: Kim Ilkyu , Lee Sun-Gyu , Nam Yong-Hyun , Lee Jeong-Hae
Published: July 2024

In this paper, two orthogonally placed Vivaldi antennas with a septum-like polarizer to generate circular polarized (CP) waves are presented. Septum polarizers have garnered attention due to their simple structure and high quality of CP waves. While a typical septum polarizer has been applied to various types of waveguides, its applicability to the substrate integrated Vivaldi antenna is demonstrated here for the first time. A pulse train-shaped polarizer is used, which is placed on one of the two Vivaldi antennas. The contours of the polarizer are optimized using a genetic algorithm to provide an equal amplitude and 90° phase difference between the two orthogonal electric fields. In contrast to typical feed networks with a 90° phase shifter, any unwanted loss caused by an electronic circuit can be greatly mitigated. The antenna prototype was fabricated, and its radiation pattern and impedance matching were measured and compared to the simulated results.
Effect of Melatonin on Germination and Seedling Growth in Aging Seeds or under Drought Conditions
Authors: García-Cánovas Isabel , Giraldo-Acosta Manuela , Cano Antonio , Arnao Marino B. , Hernández-Ruiz Josefa
Published: July 2024

Seed germination (GS) and seedling growth are vital plant stages that can be affected by stresses such as drought and aging, which cause deterioration and reduce seed viability. With the aim of homogenizing and improving GS, priming treatments with biostimulants such as the antioxidant melatonin are commonly used in seeds. In this study, the effects of melatonin on germination and seedling growth in two different situations, i.e., aging seeds of rice, barley, and sorghum and under polyethylene glycol (PEG)-induced drought stress in sorghum, were studied. Aged seeds were primed for 7 days in different concentrations of melatonin, and drought stress seeds were primed for 24 h before PEG treatment for 7 days, and germination and initial growth parameters were monitored. Aging-seeds of rice and barley showed the maximum response in terms of germination percentage at 20 µM melatonin and 0.05 µM respectively; while aging-seeds of sorghum showed improvement in germination for practically all concentrations studied, even the highest tested at 50 µM. Regarding the effect of melatonin treatments on drought stress in sorghum seeds, all the studied parameters showed a significant attenuation of the adverse effects of drought stress, alleviating them, for all concentrations tested but especially at 200 µM melatonin. The results obtained confirm that priming seeds with melatonin under low germinability conditions relieves stress and improves both germination and seedling growth.
Breakage Patterns of High-Level Thick Weakly Cemented Overburden for Coal Safe and Sustainable Mining
Authors: Yuan Yafei , Guo Guangli , Huang Cheng , Chen Yu , Li Huaizhan , Zheng Hui , Hu Yonghua
Published: July 2024

The breakage of massive thick weakly cemented rock layer is likely to cause strong mine earthquakes, which threatens the safe and sustainable production of the mine. In order to reveal the breakage law of high-level giant-thickness weakly cemented overburden rock and prevent the occurrence of mine earthquakes, we took the 2201 and 2202 working faces of Yingpanhao Coal Mine as the research object, established the mechanical calculation model of breakage of the high-level giant-thickness weakly cemented overburden, and used the methods of medium-thickness plate and short-beam function to solve the breakage law of high-level giant-thickness weakly cemented overburden rock. The findings indicate that during initial mining operations of high-level giant-thickness weakly cemented overburden rock, the applied force remains well below its bearing capacity. This condition ensures the stability of the overburden, effectively suppressing energy release events and minimizing surface subsidence. However, as mining progresses and approaches its operational limits, the overburden experiences both tensile and shear failures. This results in substantial increases in surface subsidence and the occurrence of frequent high-energy events. Finally, the model is verified against the surface-measured data and microseismic data of Yingpanhao Coal Mine, which proves the reliability of the model. The research results have important practical significance for mine earthquake prevention and safe and sustainable mining in similar geological conditions.
Resilience Measurement and Enhancement Strategies for Meizhou Bay Port Enterprises
Authors: Chen Chenyang , He Wei
Published: July 2024

The measurement of resilience in port enterprises has seldom been studied and understood. To assist port enterprises in formulating scientifically sound resilience enhancement strategies, this paper aims to develop a resilience measurement framework. The entropy-weighted TOPSIS method is utilized to measure the resilience of Meizhou Bay Port, effectively extending the application of resilience theory in the port sector and providing a crucial reference for the resilience measurement of port enterprises. The results reveal that the resilience of Meizhou Bay Port decreased from 0.4049 in 2018 to 0.34013 in 2022, indicating a current low level of resilience that requires a series of measures to enhance. Analyzing different dimensions, absorptive capacity experienced the most significant decline at the onset of the pandemic and then stabilized; adaptive capacity decreased the most, falling below absorptive capacity by 2022; and recovery capacity remained the most stable, with the least decline. This reflects the vulnerability of absorptive and adaptive capacities under significant shocks, necessitating attention and improvement in daily port operations.
Transforming Healthcare Delivery with Advanced Air Mobility: A Rural Study with GIS-Based Optimization
Authors: Bridgelall Raj , Tolliver Denver
Published: July 2024

The efficient and timely delivery of pharmaceuticals is critical, particularly in regions with dispersed populations and challenging logistics. Inclement weather often disrupts ground transport, complicating the consistent supply of essential medications. Advanced air mobility (AAM), particularly through the use of drones, presents a promising solution to these logistical challenges by enabling smaller, more frequent deliveries to low density populated places and bypassing traditional transport constraints. This study evaluates the potential benefits of AAM for pharmaceutical transport in North Dakota (ND). The authors developed a comprehensive GIS and optimization framework to identify optimal locations for logistical centers and routes for drone and truck transport. The study introduces a person-years-saved (PYS) metric to rank the potential for AAM deployments to foster healthcare improvements in underserved communities. Moreover, the study found that drone trips were significantly more cost-effective and efficient than truck trips, with trucks being 2.3 times more expensive and having a 2.8 times higher underutilization rate. The study concludes with recommendations for regulatory support and future research to validate and expand the application of AAM in pharmaceutical logistics, contributing to improved healthcare delivery and operational efficiency in often overlooked rural populations. These insights provide a foundation for the practical implementation of AAM technologies, emphasizing their potential to revolutionize pharmaceutical logistics in challenging environments.
Promoting the Sustainable Development of Enterprises: Unraveling the Dual Impact of Informal Communication on Employee Affect and Problem-Solving Capabilities
Authors: Zhu Endong , Li Weifeng , Zhao Chen , Wang Junli
Published: July 2024

In the contemporary business environment, fostering sustainable development within enterprises necessitates a nuanced understanding of the multifaceted impacts of workplace dynamics, particularly informal communication. This study delves into how informal communication, a pervasive yet underexplored aspect, influences employee emotional well-being and problem-solving capabilities—critical components for sustainable organizational growth. Leveraging theories of interaction rituals and conservation of resources, we employed a three-wave survey and structural equation modeling to dissect the complex relationships between informal communication, work-related rumination, and their subsequent effects on employee performance outcomes. Our findings illuminate that informal communication serves a dual role: it enhances interpersonal harmony, thereby reducing affective rumination, but it also detracts from work-related flow, adversely affecting problem-solving pondering. Furthermore, the ability to focus attention emerged as a significant moderating factor, amplifying or mitigating the effects of informal communication on work-related outcomes. The study contributes to the extant literature by highlighting the nuanced, double-edged-sword nature of informal communication within the context of promoting employee well-being. It underscores the necessity for managers to strategically balance fostering a supportive communication climate against maintaining optimal productivity. Our research proposes actionable strategies for leveraging informal communication as a tool for enhancing work-place well-being and sustaining future organizational growth, offering a new perspective on managing informal interactions to bolster both individual and organizational resilience.
Cross-Country Comparison of Risk Factors in Public–Private Partnerships in Infrastructure Development: Evidence from Colombia, Kazakhstan, and Ghana
Authors: Samoilov Andrey , Osei-Kyei Robert , Kussaiyn Meruyert , Mamyrbayev Almas , Mukashev Yerzhan
Published: July 2024

Governments enter into public–private partnership (PPP) agreements to attract private financing and bring innovation to the development of their sustainable public infrastructure; however, PPP projects are marked by their complexity and are driven by uncertain economic and institutional environments. The purpose of this study is to conduct a cross-country comparison of PPP risks in three developing countries (Colombia, Kazakhstan, and Ghana) and provide insights into their best practices. The research surveyed diverse risk factors involving 261 local respondents with pertinent experience in PPPs. The study conducted Cronbach’s alpha and Kendall’s coefficient of concordance tests to check the validity of responses, an ANOVA test to examine the differences in the risk perceptions, and risk ranking to reveal the country-specific as well as top-rank risks in the countries. The results of the quantitative analysis revealed risk aversion among developing countries with PPP programs at different maturity stages. Less mature programs, with lower overall investment, exhibited greater overall risk aversion (for Kazakhstan) and greater concerns about transparency and corruption (for Ghana). Highly populated countries with more mature PPP programs that rely significantly on transportation projects demonstrated higher risk aversion regarding the social and political legitimacy of PPPs and land acquisition (for Colombia).
Exploring the Multisensory Attractiveness of Cosmetic Packaging: A Study of Visual and Tactile Design Elements and Attractiveness Factors
Authors: Wang I-Chen , Jiang Yi-Ru , Wang Yu-Wei , Li Chun-Ying
Published: July 2024

The prevalence of e-commerce has led to a significant increase in online shopping among consumers, resulting in a surge in returns due to discrepancies between received products and consumer expectations. To resolve this issue, many retailers resort to disposing of returned items, contributing to wastage and environmental pollution, thereby obstructing the path to environmental sustainability. Understanding consumer expectations during the design phase holds promise for addressing this challenge. While most designers still primarily consider the visual aspect, they often overlook the emotional experiences and overall evaluations emphasized by consumers through tactile sensations during product usage. Therefore, this study employs the Miryoku Engineering approach to explore the visual and tactile attractiveness aspects and elements of cosmetic box designs for young women aged 20–30 in Taiwan. Through Evaluation Grid Method interviews, 4 attractiveness styles, 7 original attractiveness evaluations, and 35 specific conditions were identified. The results show that tactile sensations can compensate for the limitations of visual evaluations when assessing products. Participants with extensive makeup experience tended to evaluate cosmetic boxes based on both visual and tactile sensations, whereas those with moderate makeup experience focused on visual sensations and functionality. The selection of materials that prioritize sustainability and reusability in the design of cosmetic packaging can enhance brand image. In addition, this study elaborates on the visual and tactile aspects of cosmetic box designs that attract young women aged 20–30 in Taiwan. The aim is to provide future designers with insights from this study to meet young consumers’ expectations regarding the tactile and usage experience of cosmetics, thereby addressing the issue of high return rates, achieving the vision of sustainable development, and fulfilling the United Nations Sustainable Development Goal 12.5.
Synergistic Impact of Internet of Things and Big-Data-Driven Supply Chain on Sustainable Firm Performance
Authors: Zhang Qingyu , Ullah Aman , Ashraf Sana , Abdullah Muhammad
Published: July 2024

The crucial shift towards sustainable and circular practices is evident in the dynamic and environmentally focused landscape of the fast fashion industry. This study explores how internet of things (IOT) and big-data-driven supply chain (BDSC) technologies mitigate the environmental footprint of fast fashion manufacturing. A survey was conducted on individuals (n = 342) employed in the fast fashion manufacturing sector in Guangzhou, China. Deriving from the resource-based view (RBV) theory, IOT shows a significantly positive influence on firm performance through the mediation of green supply chain management (GSCM) and circular economy (CE) practices. Moreover, moderation of BDSC further strengthens the influence of IOT, GSCM and CE practices. Our empirical analysis investigates the synergistic impact of IOT and BDSC technologies to enhance the overall performance of CE supply chains. The research provides novel insights to improve the environmental sustainability of fast fashion sector.
Assessment of the Level of Digitalization of Polish Enterprises in the Context of the Fourth Industrial Revolution
Authors: Kowal Dominik , Radzik Małgorzata , Domaracká Lucia
Published: July 2024

Due to the dynamic development of the Fourth Industrial Revolution, also known as Industry 4.0, the impact of the coronavirus pandemic on the operation of enterprises, and the increasing demands of customers, more and more companies have taken and continue to take action to increase the level of digitalization. The implementation of innovative solutions contributes to the sustainability development of enterprises in various areas (economic, environmental, and social), streamlining processes and increasing effectiveness, efficiency, and quality of work. Such activities also contribute to the effective use of new opportunities by companies and strengthen their competitiveness and market position. The use of digital technologies increases the capacity of companies to innovate and grow, which brings significant benefits in terms of efficiency and competitiveness. The authors attempted to analyze and assess the level of digital transformation in enterprises in Poland. This study aimed to review the current state of digitization of companies, which made it possible to diagnose the level of digital maturity of Polish enterprises and to identify areas that will determine the activities of companies to quickly increase their competitiveness or improve internal processes. Qualitative and comparable methods were used in the analysis. The results show that the degree of digitization of Polish enterprises is increasing, and, in particular, was influenced by the COVID-19 pandemic. Nearly half of the companies analyzed declared that they are increasing their budget for digitalization. The presented study has cognitive value regarding the assessment of the level of digitization of Polish enterprises. Both managers and decision-makers can benefit from the results of the study because decision-making regarding the development of SMEs is crucial to the effectiveness of the industrial strategy.
Integrative Taxonomy of Metarhabditis Associated with Parasitic Otitis in Dairy Cattle
Authors: Caracciolo Makoto Enoki , de Andrade-Silva Beatriz Elise , Borba Victor Hugo , Castello-Branco Ander , Santos Hudson Andrade dos , Iñiguez Alena Mayo , Lopes-Torres Eduardo José
Published: July 2024

Parasitic otitis is an inflammatory process that can affect the external to internal cattle ear, causing discomfort in animals, impairing performance, and even leading to animal death. The infection was initially associated with nematodes of the Rhabditis genus in tropical and subtropical regions. Currently, the nematode species described as associated with bovine otitis are Metarhabditis costai, Metarhabditis freitasi, and, more recently, M. blumi. It is worth highlighting that there is still a lack of robust information regarding the morphological details, ultrastructural aspects, and molecular biology data of these species. The Metarhabditis genus is composed of seven species and two more have recently been added. The objective of this study is to update the morphological data using advanced microscopy techniques to emphasize and clarify the main morphological differences between three species of Metarhabditis currently associated with parasitic otitis. Samples of inflammatory exudate were collected from four adult female Gir cattle (Bos taurus indicus) on a farm in Itabira, Minas Gerais state, Brazil. Specimens were analyzed using light microscopy and scanning electron microscopy. Two species, M. costai and M. freitasi, were morphologically identified, consistent with previous reports. Scanning electron microscopy revealed new structural characteristics of the nematode species involved in parasitic otitis compared with M. blumi obtained from the CGC Center. Significant differences were observed in the male posterior region, bursa, and tail. Molecular analysis was conducted to differentiate these three species, and it was observed that the species first associated with otitis formed distinct clusters compared to M. blumi. However, it is important to note that further studies are needed to genetically characterize species of the Metarhabditis genus.
The Impact of the Reduction in Environmental Pollution during COVID-19 Lockdown on Healthy Individuals
Authors: Romero-Mesones Christian , de Homdedeu Miquel , Soler-Segovia David , Gómez-Ollés Carlos , Espejo-Castellanos David , Ojanguren Inigo , Saez-Gimenez Berta , Cruz María-Jesús , Munoz Xavier
Published: July 2024

The lockdown imposed to combat the COVID-19 pandemic produced a historic fall in air pollution in cities like Barcelona. This exceptional situation offered a unique context in which to examine the effects of air pollutants on human health. The present study aims to determine and compare the oxidative stress biomarkers Th1/Th2 and inflammatory-related cytokines in healthy individuals first during lockdown and then six months after the easing of the restrictions on mobility. A prospective study of a representative sample of 58 healthy, non-smoking adults was carried out. During lockdown and six months post-easing of restrictions, blood samples were drawn to measure the percentage of eosinophils, levels of Th1/Th2 and inflammatory-related cytokines assessed by a multiplex assay (BioRad Laboratories S.A., Marnes-la-Coquette, France), and levels of 8-isoprostane, glutathione peroxidase activity, and myeloperoxidase (Cayman Chemical Co., Ann Arbor, MI, USA), to assess their value as biomarkers of oxidative stress. Six months after easing mobility restrictions, increases in the levels of 8-isoprostane (p < 0.0001), IL-1β (p = 0.0013), IL-1ra (p = 0.0110), IL-4 (p < 0.0001), IL-13 (p < 0.0001), G-CSF (p = 0.0007), and CCL3 (p < 0.0001) were recorded, along with reductions in glutathione peroxidase (p < 0.0001), IFN-γ (p = 0.0145), TNFα (p < 0.0001), IP-10 (p < 0.0001), IL-2 (p < 0.0001), IL-7 (p < 0.0001), basic FGF (p < 0.0001), CCL4 (p < 0.0001), and CCL5 (p < 0.0001). No significant differences were observed in the rest of the biomarkers analyzed. The reduction in environmental pollution during the COVID-19 lockdown significantly lowered the levels of oxidative stress, systemic inflammation, and Th2-related cytokines in healthy people.
Safety and Immunogenicity of Morbillivirus canis Vaccines for Domestic and Wild Animals: A Scoping Review
Authors: Rendon-Marin Santiago , Higuita-Gutiérrez Luis Felipe , Ruiz-Saenz Julian
Published: July 2024

Morbillivirus canis (canine distemper virus (CDV)) is recognized as a multihost pathogen responsible for a transmissible disease affecting both domestic and wild animals. A considerable portion of wildlife populations remain unvaccinated due to a lack of safety and immunogenicity data on existing vaccines for the prevention of CDV infection in these species. This review aimed to assess the current state of CDV vaccination research for both domestic and wild animals and to explore novel vaccine candidates through in vivo studies. It also sought to synthesize the scattered information from the extensive scientific literature on CDV vaccine research, identify key researchers in the field, and highlight areas where research on CDV vaccination is lacking. A scoping review was conducted across four databases following the PRISMA-ScR protocol, with information analyzed using absolute and relative frequencies and 95% confidence intervals (CIs) for study number proportions. Among the 2321 articles retrieved, 68 met the inclusion criteria and focused on CDV vaccines in various animal species, such as dogs, ferrets, minks, and mice. Most of the scientific community involved in this research was in the USA, Canada, France, and Denmark. Various vaccine types, including MLV CDV, recombinant virus, DNA plasmids, inactivated CDV, and MLV measles virus (MeV), were identified, along with diverse immunization routes and schedules employed in experimental and commercial vaccines. Safety and efficacy data were summarized. Notably, 37 studies reported postimmunization CDV challenge, primarily in dogs, revealing the survival rates of vaccinated animals. In summary, CDV vaccines generally demonstrate an acceptable safety profile in dogs and show promise as a means of controlling CDV. However, significant gaps in vaccine research persist, particularly concerning wildlife reservoirs, indicating the need for further investigation.
Perceptual Biases in the Interpretation of Non-Rigid Shape Transformations from Motion
Authors: Choi Ryne , Feldman Jacob , Singh Manish
Published: July 2024

Most existing research on the perception of 3D shape from motion has focused on rigidly moving objects. However, many natural objects deform non-rigidly, leading to image motion with no rigid interpretation. We investigated potential biases underlying the perception of non-rigid shape interpretations from motion. We presented observers with stimuli that were consistent with two qualitatively different interpretations. Observers were shown a two-part 3D object with the smaller part changing in length dynamically as the whole object rotated back and forth. In two experiments, we studied the misperception (i.e., perceptual reinterpretation) of the non-rigid length change to a part. In Experiment 1, observers misperceived this length change as a part orientation change (i.e., the smaller part was seen as articulating with respect to the larger part). In Experiment 2, the stimuli were similar, except the silhouette of the part was visible in the image. Here, the non-rigid length change was reinterpreted as a rigidly attached part with an “illusory” non-orthogonal horizontal angle relative to the larger part. We developed a model that incorporated this perceptual reinterpretation and could predict observer data. We propose that the visual system may be biased towards part-wise rigid interpretations of non-rigid motion, likely due to the ecological significance of movements of humans and other animals, which are generally constrained to move approximately part-wise rigidly. That is, not all non-rigid deformations are created equal: the visual systems’ prior expectations may bias the system to interpret motion in terms of biologically plausible shape transformations.
TESTING AND DISTRIBUTION OF A NEW GENETIC ANOMALY IN HOLSTIN CATTLE HMW (OMIA ID 002819-9913)
Authors: КОВАЛЮК Н.В. , ВОЛЧЕНКО А.Е. , ШИРЯЕВА Е.В. , ЯКУШЕВА Л.И. , САЦУК В.Ф. , ШАХНАЗАРОВА Ю.Ю. , КИРМАН М.А.
Published: July 2024

В 2022 году впервые появилась информация о новой аномалии голштинского скота. Телята, гомозиготные носители аномалии, не могут встать на ноги после рождения, 52% таких носителей гибнут в возрасте до 18 мес. Так называемый синдром мышечной слабости (HMW) встречается в популяции голштинского скота у 17% животных. Рецессивный гаплотип, приводящий к повышенной смертности молодняка, локализован на хромосоме 16, в гене CACNA1S. Нами разработана и успешно апробирована, с использованием образца, полученного от известного носителя, тест-система на основе аллель-специфической ПЦР для выявления синдрома мышечной слабости. Проанализированы данные племенного учета коров и телок из 3 племенных хозяйств Краснодарского края (n=7616). Носителями синдрома мышечной слабости являются свыше 5,5% животных. Проведенное генотипирование выборки коров (n=25) быкопроизводящей группы по локусу CACNA1S выявило 28% носителей. Аномалия HMW голштинского скота имеет опасный уровень распространения в субпопуляции Краснодарского края и, на наш взгляд, требует ограничения использования быков-носителей HMW.

In 2022, information about a new anomaly in Holstein cattle first appeared. Calves who are homozygous carriers of the anomaly cannot stand on their feet after birth; 52% of calves with such carriers die before the age of 18 months. The so-called muscle weakness syndrome (HMW) occurs in 17% of the Holstein cattle population. The recessive haplotype, leading to increased mortality of calves, is localized on chromosome 16, in the CACNA1S gene. A test system based on allele-specific PCR was developed and successfully tested, using a sample obtained from a known carrier, to detect “muscle weakness” syndrome. Data from breeding records of cows and heifers from three breeding farms in the Krasnodar region (n=7616) were analyzed. Over 5.5% of animals are probably carriers of muscle weakness syndrome. Genotyping of a sample (n=25) of the bull-producing group of animals at the CACNA1S locus revealed 28% of carriers. The anomaly of HMW Holstein cattle has a dangerous level of distribution in the subpopulation of the Krasnodar Territory and, in our opinion, requires limiting the use of bulls carrying HMW.
Design Principles for Moisture-Tolerant Sulfide-Based Solid Electrolytes and Associated Effect on the Electrochemical Performance of All-Solid-State Battery
Authors: Kwon Ohmin , Kim Se Young , Hwang Jinyeon , Han Jonghyun , Yu Seungho , Yim Taeeun , Oh Si Hyoung
Published: July 2024

The grave concern on the safety of Li-ion batteries adopted in commercial electrical vehicles pushes an urgent demand for developing safer all-solid-state batteries (ASSBs), where ion-conducting solid electrolytes play pivotal roles. Much higher conductivity and more ductile nature of sulfide-based electrolytes offers great advantages over conventional oxide materials in terms of manufacturing process difficulty and the battery performance. However, instability of sulfide materials towards atmospheric moisture results in the substantial degradation in the ionic conductivity and the release of hazardous gas. After over a decade of intensive research, various customized strategies based on the specific design rules were developed for each electrolyte to tackle this crucial issue. However, in most cases a moisture tolerance was endowed only after compromising its vital ionic conductivity to some extent. Nevertheless, the actual applications of sulfide electrolytes to ASSBs often lead to improved battery performance by virtue of the interfacial stabilization between oxide-based cathode materials and sulfide-based solid electrolytes. Therefore, it is essential to fully comprehend the critical factors of each atmospheric stabilization technology that potentially affects the eventual battery performance. Herein, we go over the current status of state-of-the-art moisture-stabilizing technologies for each sulfide-based solid electrolyte, summarizing the major effect of each technology on the various aspect of the electrochemical performance upon application. We believe that this review will contribute to achieving effective moisture-stabilization of sulfide-based solid electrolytes, catalyzing the successful commercialization of sulfide-based ASSBs.
The Role of Perceived Value and E-Service Quality of E-Commerce Users to Build Electronic Word Of Mouth (E-WOM)
Authors: Pratama Cikal Virgiawan , Sya'roni Deden Abdul Wahab
Published: July 2024

In this digital era, especially after the pandemic, many business people choose to focus on marketing and promoting through various kinds of online media which makes consumers have high flexibility to choose the product they want.. The electronic perceived value in question is to build good values and benefits attached to the product being sold. Another factor that can build Electronic Word Of Mouth is E-Service Quality, with better quality of online service, consumers will not hesitate to promote products on marketplace platform. This study aims to determine the role of Perceived Value on Electronic Word Of Mouth by making 50 Marketplace customers as research samples with is purpossive sampling technique. Instrument for this research using perceived value, e – service quality and electronic word of mouth questionnaire form and also conducted interviews with some respondents after the author first made observations regarding the variables studied. The results of this study indicate that perceived value and e-service quality have a significant effect on electronic word of mouth based on statistical calculations using linear regression analysis, correlation coefficient and partial hypothesis testing. This is due to several factors including product quality management, speed of response from sellers and overall customer satisfaction that builds positive word of  mouth
Application of Government Accounting Standards in Government Financial Reporting
Authors: Anggadini S D , Agustin N , Agustin R S P , Zahrany D N , Bramasto A , Damayanti S
Published: July 2024

This study aims to determine the influence of the application of government accounting standards and the role of internal audits on the quality of financial reports of municipal governments in Indonesia. The research approach used in this research is descriptive analysis with a verification approach. The sample selection is a saturated sample including 127 offices in Regional Apparatus Organizations in Indonesia. The data analysis technique used in this study is multiple linear analysis using SPSS 26.0 software. Based on the research, it can be seen that the application of government accounting standards affects the quality of local government financial reports. The role of Internal Audit influences the quality of local government financial reports in Indonesia. This research is expected to be used by intellectuals and interested parties, both the government and other parties who need information related to research. Therefore, an improved role of internal audit will lead to an increase in the quality of local government financial reports, where a strong internal audit role can have a positive impact on improving the quality of financial reports. It is recommended that stakeholders take a closer look at the reliability of the system and improvements in the management of internal audit to facilitate the process and implementation of internal audit.
Impacts of Growing Number of Taxable Entrepreneurs on the Revenue of Value Added Tax
Authors: Febriansyah A , Aprilia R T , Gunawan S
Published: July 2024

This study aims to determine how much impact of the Number of Taxable Entrepreneurs on Value Added Tax (VAT) Revenue at the Madya Bandung Tax Service Office. The research method used is descriptive and verification methods with a quantitative approach. The sampling technique used is the Non-Probability Sampling technique with the determination of sampling using Saturated Sampling.The data analysis method used in this study is multiple linear regression analysis using SPSS v25 software.The results of this study indicate that partially the Number of Taxable Entrepreneurs has an positive impact on the of Value Added Tax Revenue at the Bandung Madya Tax Service Office. which means that the increasing number of taxable entrepreneurs will have an impact on increasing value added tax revenues at the Bandung Madya Tax Service Office
Dvandva and Appositional Compounds in the Food Menu on the Starbucks Cafe Website
Authors: Trializa R , Yuwita M R
Published: July 2024

The objective of this research is to analyze the differences between two types of compounds contained in food names. The discussion includes the basic constituent used to form new words. The data in this study is taken from foods name on the Starbucks Cafe menu, while the object is about the dvandva compound and appositional compounds. This research uses the qualitative method, which is a descriptive method, and the data found is reported in words. The study uses Bauer’s (2001) theory as a reference to explain dvandva (copulative) and appositional compounds. There are 9 data that the writer found on the Starbucks Cafe website. The result shows that there are 4 data of the dvandva compound, and 5 data of the appositional compound. Dvandva and appositional are frequently difficult to distinguish, therefore, the impact of this research is to help distinguish between the two types of compounds and to show the word formation process for the names of a product.
How Clause Relationships in Narrative Relieve Children from the Covid-19 Crisis
Authors: Nurin Fadhila Fasya  , Retno Purwani Sari
Published: July 2024

This study aims to discover how a clause-complex system supports information delivery in a children’s narrative story. It emphasizes interdependence and semantic-logico relations. This study debates how clause relationships can help children, whose lives are being impacted by covid-19 pandemic, maintaining their mental health and their language and communication skills while reading. Using the descriptive qualitative method, data from a closed reading were extracted and classified into complex-clause taxis based on Halliday and Matthiessen’s theory. The semantic-logico was described, showing how the narrative plot was systematically structured to create an imaginative world. The results show that Anderson’s The Little Match Girl creates its fictional world using 25 complex clauses in interdependence relationships. There are 15 parataxis and 10 hypotaxis. The parataxis clauses depict three types of logico-semantic relations: 12 enhancements, 1 elaboration, and 2 extensions, whereas the hypotaxis clauses describe two types: 8 enhancements and 2 extensions. The findings indicates that these clause-complex relationships drive the narrative flow of events in the fictional world; the narrative clauses play as persuasive tools that bring children to imagination. The implication of this study is that imaginations from the fictional world help children cope with the covid-19 crisis while also maintaining their mental health and their language and communication skills.