bluuebunny/crossref_metadata_2025 huggingface dataset:
Okra Micro-Cellulose Crystal (MCC) and Micro-Clay Composites for the Remediation of Copper, Nickel, and Dye (Basic Yellow II) from Wastewater
Authors: Mohana Anika Amir , Rahman Md. Aminur , Rahaman Md. Hafezur , Maniruzzaman Mohd. , Farhad S. M. , Islam Md Meftaul , Khan Md. Sirajul Islam , Parvez Md. Zahid
Published: July 2023

Water pollution by contaminants such as toxic metals and dyes is now a major concern due to their high toxicity and persistence in the environment. Advances in nanotechnology have enabled the use of micro/nanomaterials to treat and purify water in various industries. In this study, Bijoypur clay was modified with ethyldiamine and incorporated into an okra fiber (Abelmoschus esculentus) micro-cellulose crystal (MCC) to produce a composite that could absorb copper (Cu), nickel (Ni), and dyes like basic yellow (II) from industrial wastewater. Composites were prepared using different percentages of MCC and clay. Atomic absorption spectroscopy (AAS) was used to determine the concentrations of Cu and Ni whereas a UV–Visible spectrophotometer measured the absorbance of basic yellow (II). The synthesized composites were extensively characterized using a range of techniques including thermogravimetry (TG) and differential thermogravimetry (DTG), Fourier transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), and X-ray diffraction (XRD). Results show that both the MCC and clay could absorb Cu, Ni, and basic yellow (II) from the contaminated wastewater. The MCC and clay composite showed the maximum efficiency of metals removal, which was up to 95% (24 mg/g) for Cu at pH 6, 20 min contact time, 2 g/L adsorbent dose, and 100% (31 mg/g) for Ni at pH 8, 60 min contact time, and 2 g/L adsorbent dose, respectively, at the initial concentration of 50 mg/L. The maximum dye uptake capacity of 85% (19 mg/g) was observed by the MCC and clay composite under optimized conditions at the initial concentration of 50 mg/L, pH 8, 30 min contact time, and 1 g/L adsorbent dose compared to the pure clay, which had an efficiency up to 26% for Cu and 24% for dye removal. All of the results indicate that incorporating clay into MCC increases the absorption capacity of contaminants from wastewater, which could be more effective for environmental applications compared to untreated cellulose.
17q21.31 Microduplication Syndrome in a Patient with Autism Spectrum Disorder, Macrocephaly, and Intellectual Disability
Authors: Saia Federica , Prato Adriana , Florio Caterina Angela , Cutrone Vincenzo Paolo , Rizzo Renata
Published: July 2023

The chromosome 17q21.31 microduplication syndrome is a rare genetic syndrome presenting with craniofacial dysmorphisms, psychomotor delay, microcephaly, behavioral disorders, and poor social interaction. Only ten patients have been reported in the literature until today. All patients share some specific features, including psychomotor delay, behavioral disorders, and autism spectrum disorder (ASD). Here, a new case of this syndrome is reported in an 11-year-old Caucasian child who presented the classical clinical features of the 17q21.31 microduplication syndrome in association with new clinical characteristics previously unreported. The Array-Comparative Genomic Hybridization (aCGH) revealed a partial duplication of the long arm of chromosome 17. A literature review of previously studied patients with 17q21.31 microduplication syndrome is reported.
The Silicon Valley Bank Failure: Application of Benford’s Law to Spot Abnormalities and Risks
Authors: Dutta Anurag , Voumik Liton Chandra , Kumarasankaralingam Lakshmanan , Rahaman Abidur , Zimon Grzegorz
Published: July 2023

Data are produced every single instant in the modern era of technological breakthroughs we live in today and is correctly termed as the lifeblood of today’s world; whether it is Google or Meta, everyone depends on data to survive. But, with the immense surge in technological boom comes several backlashes that tend to pull it down; one similar instance is the data morphing or modification of the data unethically. In many jurisdictions, the phenomenon of data morphing is considered a severe offense, subject to lifelong imprisonment. There are several cases where data are altered to encrypt reliable details. Recently, in March 2023, Silicon Valley Bank collapsed following unrest prompted by increasing rates. Silicon Valley Bank ran out of money as entrepreneurial investors pulled investments to maintain their businesses afloat in a frigid backdrop for IPOs and individual financing. The bank’s collapse was the biggest since the financial meltdown of 2008 and the second-largest commercial catastrophe in American history. By confirming the “Silicon Valley Bank” stock price data, we will delve further into the actual condition of whether there has been any data morphing in the data put forward by the Silicon Valley Bank. To accomplish the very same, we applied a very well-known statistical paradigm, Benford’s Law and have cross-validated the results using comparable statistics, like Zipf’s Law, to corroborate the findings. Benford’s Law has several temporal proximities, known as conformal ranges, which provide a closer examination of the extent of data morphing that has occurred in the data presented by the various organizations. In this research for validating the stock price data, we have considered the opening, closing, and highest prices of stocks for a time frame of 36 years, between 1987 and 2023. Though it is worth mentioning that the data used for this research are coarse-grained, still since the validation is subjected to a larger time horizon of 36 years; Benford’s Law and the similar statistics used in this article can point out any irregularities, which can result in some insight into the situation and into whether there has been any data morphing in the Stock Price data presented by SVB or not. This research has clearly shown that the stock price variations of the SVB diverge much from the permissible ranges, which can give a conclusive direction on further investigations in this issue by the responsible authorities. In addition, readers of this article must note that the conclusion formed about the topic discussed in this article is objective and entirely based on statistical analysis and factual figures presented by the Silicon Valley Bank Group.
Blockchain and Machine Learning Inspired Secure Smart Home Communication Network
Authors: Menon Subhita , Anand Divya , Kavita  , Verma Sahil , Kaur Manider , Jhanjhi N. Z. , Ghoniem Rania M. , Ray Sayan Kumar
Published: July 2023

With the increasing growth rate of smart home devices and their interconnectivity via the Internet of Things (IoT), security threats to the communication network have become a concern. This paper proposes a learning engine for a smart home communication network that utilizes blockchain-based secure communication and a cloud-based data evaluation layer to segregate and rank data on the basis of three broad categories of Transactions (T), namely Smart T, Mod T, and Avoid T. The learning engine utilizes a neural network for the training and classification of the categories that helps the blockchain layer with improvisation in the decision-making process. The contributions of this paper include the application of a secure blockchain layer for user authentication and the generation of a ledger for the communication network; the utilization of the cloud-based data evaluation layer; the enhancement of an SI-based algorithm for training; and the utilization of a neural engine for the precise training and classification of categories. The proposed algorithm outperformed the Fused Real-Time Sequential Deep Extreme Learning Machine (RTS-DELM) system, the data fusion technique, and artificial intelligence Internet of Things technology in providing electronic information engineering and analyzing optimization schemes in terms of the computation complexity, false authentication rate, and qualitative parameters with a lower average computation complexity; in addition, it ensures a secure, efficient smart home communication network to enhance the lifestyle of human beings.
ECKN: An Integrated Approach for Position Estimation, Packet Routing, and Sleep Scheduling in Wireless Sensor Networks
Authors: Bertanha Mauricio , Pazzi Richard W. , El-Khatib Khalil
Published: July 2023

Network lifetime and localization are critical design factors for a number of wireless sensor network (WSN) applications. These networks may be randomly deployed and left unattended for prolonged periods of time. This means that node localization is performed after network deployment, and there is a need to develop mechanisms to extend the network lifetime since sensor nodes are usually constrained battery-powered devices, and replacing them can be costly or sometimes impossible, e.g., in hostile environments. To this end, this work proposes the energy-aware connected k-neighborhood (ECKN): a joint position estimation, packet routing, and sleep scheduling mechanism. To the best of our knowledge, there is a lack of such integrated solutions to WSNs. The proposed localization algorithm performs trilateration using the positions of a mobile sink and already-localized neighbor nodes in order to estimate the positions of sensor nodes. A routing protocol is also introduced, and it is based on the well-known greedy geographic forwarding (GGF). Similarly to GGF, the proposed protocol takes into consideration the positions of neighbors to decide the best forwarding node. However, it also considers node residual energy in order to guarantee the forwarding node will deliver the packet. A sleep scheduler is also introduced in order to extend the network lifetime. It is based on the connected k-neighborhood (CKN), which aids in the decision of which nodes switch to sleep mode while keeping the network connected. An extensive set of performance evaluation experiments was conducted and results show that ECKN not only extends the network lifetime and localizes nodes, but it does so while sustaining the acceptable packet delivery ratio and reducing network overhead.
Multi-Focus Image Fusion via Distance-Weighted Regional Energy and Structure Tensor in NSCT Domain
Authors: Lv Ming , Li Liangliang , Jin Qingxin , Jia Zhenhong , Chen Liangfu , Ma Hongbing
Published: July 2023

In this paper, a multi-focus image fusion algorithm via the distance-weighted regional energy and structure tensor in non-subsampled contourlet transform domain is introduced. The distance-weighted regional energy-based fusion rule was used to deal with low-frequency components, and the structure tensor-based fusion rule was used to process high-frequency components; fused sub-bands were integrated with the inverse non-subsampled contourlet transform, and a fused multi-focus image was generated. We conducted a series of simulations and experiments on the multi-focus image public dataset Lytro; the experimental results of 20 sets of data show that our algorithm has significant advantages compared to advanced algorithms and that it can produce clearer and more informative multi-focus fusion images.
Vision-Based Methods for Food and Fluid Intake Monitoring: A Literature Review
Authors: Chen Xin , Kamavuako Ernest N.
Published: July 2023

Food and fluid intake monitoring are essential for reducing the risk of dehydration, malnutrition, and obesity. The existing research has been preponderantly focused on dietary monitoring, while fluid intake monitoring, on the other hand, is often neglected. Food and fluid intake monitoring can be based on wearable sensors, environmental sensors, smart containers, and the collaborative use of multiple sensors. Vision-based intake monitoring methods have been widely exploited with the development of visual devices and computer vision algorithms. Vision-based methods provide non-intrusive solutions for monitoring. They have shown promising performance in food/beverage recognition and segmentation, human intake action detection and classification, and food volume/fluid amount estimation. However, occlusion, privacy, computational efficiency, and practicality pose significant challenges. This paper reviews the existing work (253 articles) on vision-based intake (food and fluid) monitoring methods to assess the size and scope of the available literature and identify the current challenges and research gaps. This paper uses tables and graphs to depict the patterns of device selection, viewing angle, tasks, algorithms, experimental settings, and performance of the existing monitoring systems.
A Review of the Motion Planning and Control Methods for Automated Vehicles
Authors: Song Xiaohua , Gao Huihui , Ding Tian , Gu Yunfeng , Liu Jing , Tian Kun
Published: July 2023

The motion planning and control method of automated vehicles, as the key technology of automated vehicles, directly affects the safety, comfort, and other technical indicators of vehicles. The planning module is responsible for generating a vehicle driving path. The control module is responsible for driving the vehicle. In this study, we review the main methods and achievements in motion planning and motion control for automated vehicles. The advantages and disadvantages of various planning and control methods are comparatively analyzed. Finally, some predictions and summaries based on the existing research results and trends are proposed. Through this analysis, it is believed that various types of algorithms will be further integrated in the future to complement each other’s strengths and weaknesses. The next area of research will be to establish more accurate vehicle models to describe vehicle motion, improve the generalization-solving ability of algorithms, and enhance the planning and control of integrated ‘human-vehicle-road’ traffic systems.
A Model for Urban Environment Instance Segmentation with Data Fusion
Authors: Du Kaiyue , Meng Jin , Meng Xin , Wang Shifeng , Yang Jinhua
Published: July 2023

Fine-grained urban environment instance segmentation is a fundamental and important task in the field of environment perception for autonomous vehicles. To address this goal, a model was designed with LiDAR pointcloud data and camera image data as the subject of study, and the reliability of the model was enhanced using dual fusion at the data level and feature level. By introducing the Markov Random Field algorithm, the Support Vector Machine classification results were optimized according to the spatial contextual linkage while providing the model with the prerequisite of the differentiation of similar but foreign objects, and the object classification and instance segmentation of 3D urban environments were completed by combining the Mean Shift. The dual fusion approach in this paper is a method for the deeper fusion of data from different sources, and the model, designed more accurately, describes the categories of items in the environment with a classification accuracy of 99.3%, and segments the different individuals into groups of the same kind of objects without instance labels. Moreover, our model does not have high computational resource and time cost requirements, and is a lightweight, efficient, and accurate instance segmentation model.
Railway Axle Early Fatigue Crack Detection through Condition Monitoring Techniques
Authors: Gomez María Jesús , Castejon Cristina , Corral Eduardo , Cocconcelli Marco
Published: July 2023

The detection of cracks in rotating machinery is an unresolved issue today. In this work, a methodology for condition monitoring of railway axles is presented, based on crack detection by means of the automatic selection of patterns from the vibration signal measurement. The time waveforms were processed using the Wavelet Packet Transform, and appropriate alarm values for diagnosis were calculated automatically using non-supervised learning techniques based on Change Point Analysis algorithms. The validation was performed using vibration signals obtained during fatigue tests of two identical railway axle specimens, one of which cracked during the test while the other did not. During the test in which the axle cracked, the results show trend changes in the energy of the vibration signal associated with theoretical defect frequencies, which were particularly evident in the direction of vibration that was parallel to the track. These results are contrasted with those obtained during the test in which the fatigue limit was not exceeded, and the test therefore ended with the axle intact, verifying that the effects that were related to the crack did not appear in this case. With the results obtained, an adjusted alarm value for a condition monitoring process was established.
Towards Onsite Age Estimation of Semen Stains Using Fluorescence Spectroscopy
Authors: Achetib Nihad , Leemberg Caren C. , Geurts Mathijs M. P. , Bloemen Paul R. , van den Elzen Richard M. , Aalders Maurice C. G. , van Dam Annemieke
Published: July 2023

The age estimation of biological traces is one of the holy grails in forensic investigations. We developed a method for the age estimation of semen stains using fluorescence spectroscopy in conjunction with a stoichiometric ageing model. The model describes the degradation and generation rate of proteins and fluorescent oxidation products (FOX) over time. The previously used fluorimeter is a large benchtop device and requires system optimization for forensic applications. In situ applications have the advantage that measurements can be performed directly at the crime scene, without additional sampling or storage steps. Therefore, a portable fiber-based fluorimeter was developed, consisting of two optimized light-emitting diodes (LEDs) and two spectrometers to allow the fluorescence protein and FOX measurements. The handheld fiber can be used without touching the traces, avoiding the destruction or contamination of the trace. In this study, we have measured the ageing kinetics of semen stains over time using both our portable fluorimeter and a laboratory benchtop fluorimeter and compared their accuracies for the age estimation of semen stains. Successful age estimation was possible up to 11 days, with a mean absolute error of 1.0 days and 0.9 days for the portable and the benchtop fluorimeters, respectively. These results demonstrate the potential of using the portable fluorimeter for in situ applications.
Calibration Assessment of Low-Cost Carbon Dioxide Sensors Using the Extremely Randomized Trees Algorithm
Authors: Araújo Tiago , Silva Lígia , Aguiar Ana , Moreira Adriano
Published: July 2023

As the monitoring of carbon dioxide is an important proxy to estimate the air quality of indoor and outdoor environments, it is essential to obtain trustful data from CO2 sensors. However, the use of widely available low-cost sensors may imply lower data quality, especially regarding accuracy. This paper proposes a new approach for enhancing the accuracy of low-cost CO2 sensors using an extremely randomized trees algorithm. It also reports the results obtained from experimental data collected from sensors that were exposed to both indoor and outdoor environments. The indoor experimental set was composed of two metal oxide semiconductors (MOS) and two non-dispersive infrared (NDIR) sensors next to a reference sensor for carbon dioxide and independent sensors for air temperature and relative humidity. The outdoor experimental exposure analysis was performed using a third-party dataset which fit into our goals: the work consisted of fourteen stations using low-cost NDIR sensors geographically spread around reference stations. One calibration model was trained for each sensor unit separately, and, in the indoor experiment, it managed to reduce the mean absolute error (MAE) of NDIR sensors by up to 90%, reach very good linearity with MOS sensors in the indoor experiment (r2 value of 0.994), and reduce the MAE by up to 98% in the outdoor dataset. We have found in the outdoor dataset analysis that the exposure time of the sensor itself may be considered by the algorithm to achieve better accuracy. We also observed that even a relatively small amount of data may provide enough information to perform a useful calibration if they contain enough data variety. We conclude that the proper use of machine learning algorithms on sensor readings can be very effective to obtain higher data quality from low-cost gas sensors either indoors or outdoors, regardless of the sensor technology.
Three-Dimensional Image Transmission of Integral Imaging through Wireless MIMO Channel
Authors: Lim Seung-Chan , Cho Myungjin
Published: July 2023

For the reconstruction of high-resolution 3D digital content in integral imaging, an efficient wireless 3D image transmission system is required to convey a large number of elemental images without a communication bottleneck. To support a high transmission rate, we herein propose a novel wireless three-dimensional (3D) image transmission and reception strategy based on the multiple-input multiple-output (MIMO) technique. By exploiting the spatial multiplexing capability, multiple elemental images are transmitted simultaneously through the wireless MIMO channel, and recovered with a linear receiver such as matched filter, zero forcing, or minimum mean squared error combiners. Using the recovered elemental images, a 3D image can be reconstructed using volumetric computational reconstruction (VCR) with non-uniform shifting pixels. Although the received elemental images are corrupted by the wireless channel and inter-stream interference, the averaging effect of the VCR can improve the visual quality of the reconstructed 3D images. The numerical results validate that the proposed system can achieve excellent 3D reconstruction performance in terms of the visual quality and peak sidelobe ratio though a large number of elemental images are transmitted simultaneously over the wireless MIMO channel.
Female Academics in Higher Education: Conducting Qualitative Research against All Odds
Authors: Zapata-Sepúlveda Pamela , Araneda-Guirriman Carmen , Suárez-Ortega Magdalena , Ramírez-Pereira Mirliana , Espinoza-Lobos Michelle
Published: July 2023

This piece brings together the experiences of four Chilean researchers and one Spanish researcher with different professional backgrounds (psychology, sociology, nursing, and education), who conduct qualitative inquiry from other approaches, moments, and gender-sensitive topics of interest in the border regions of Arica and Parinacota, and Tarapacá, both in northern Chile; the capital Santiago; and in Andalucía, southern Spain. In this paper, the authors problematize their research experiences by focusing on their condition as academics conducting qualitative research in the context of neoliberal higher education and with a pandemic affecting all spheres of life. Finally, they explore what their experiences have been like in leading government-funded research projects and representing the voices of underrepresented people in different spheres of life in the field of education and health. Voices are shared to identify challenges and assess implications for qualitative research in these difficult times in the academy.
Research Status, Hotspots, and Trend Analysis of the Rural Living Environment Upgrade in China from 1992 to 2022: A Bibliometric and Narrative Review Analysis
Authors: Wang Changxu , Guo Jinyong , Liu Changlin , Peng Yuanyuan , Tang Yonghong
Published: July 2023

The rural living environment is the foundation of rural ecology and rural residents’ life, and the quality of the rural living environment is directly related to the green and low-carbon development of rural areas and the physical and mental health of rural residents. This article aims to grasp the current situation and of rural living environment improvement research and its various research hotspots, explore research frontiers and trends, and provide crucial theoretical guidance for rural living environment improvement research by searching and analyzing China’ national knowledge infrastructure database (CNKI). The article adopts CiteSpace6.2 bibliometric software and the narrative review method to analyze 1349 papers on rural living environment upgrading in CNKI from 1992 to 2022. Among them, the narrative review collects and analyzes the relevant information on rural living environment improvement to provide the background and content for the relevant arguments. It is found that (1) the rural living environment governance policies can be divided into four stages, namely, the initial stage, policy exploration, policy enhancement, and policy deepening, with the policy system continuously maturing and the governance content becoming clearer; (2) research hot topics can be summarized as research on the connotation and governance model of the rural living environment, research on development status, research on effective evaluation and influential factors, and research on treatment model and technology involving interdisciplinary integration development; (3) the rural living environment upgrade research history can be divided into three periods: before 2004, which was the start-up stage, thus the number of publications was relatively small, and core topics included the transformation of rural toilets and rural domestic sewage treatment; 2004–2017, which is the expansion stage, thus the total amount of literature is increasing yearly, and the research topics are gradually enriched; after 2018, which is the the mature development stage, further clarifying the key tasks of rural living environment upgrades; (4) in the future, it is necessary to keep the focus on research in the four key areas, deepen the research on governance connotation, influential factors, and effect evaluation, explore the typical models of rural living environment construction in China, and provide research guidelines and practical decisions for rural living environment governance.
A Review of Global PM2.5 Exposure Research Trends from 1992 to 2022
Authors: Jia Nan , Li Yinshuai , Chen Ruishan , Yang Hongbo
Published: July 2023

Exposure to air pollutants of fine particulate matter (PM2.5) is a major threat to human health. Research on PM2.5 exposure has been on the rise in recent years, but there has been a lack of systematic literature analysis in this field. To address this research gap, we conducted a bibliometric analysis of the existing publications on PM2.5 exposure over the past three decades and analyzed the current state and historical trends of research using the open-access tool, KNIME. Our results show that the number of publications on PM2.5 exposure has been increasing at an accelerating rate over the last 30 years. The authors of the publications are primarily from developed nations, such as countries in North America, Europe, East Asia, and Oceania. Published research is mainly from the fields of Environmental Sciences and Ecology, Environmental Sciences, and Public, Environmental and Occupational Health. The main research hotspots are exposure, air pollution, and PM2.5. Research is trending toward the intersection and integration of multiple subjects. Our results highlight the rapid growth of PM2.5-related research and provide insights into the structure, impact, and trends of this interdisciplinary field.
Assessment of Ecological Benefits of Urban Green Spaces in Nanjing City, China, Based on the Entropy Method and the Coupling Harmonious Degree Model
Authors: Ji Yaou , Sheng Qianqian , Zhu Zunling
Published: July 2023

Urban green spaces (UGSs) are an important spatial carrier for carbon sequestration in the national land space. The urban ecosystem is a highly harmonious composite ecosystem of nature, society, and the economy. Therefore, this study constructed an evaluation system of the UGS ecological benefit based on two subsystems–the natural environment and the social economy–in order to quantitatively evaluate the construction level of the UGS ecological benefit in Nanjing City and to reveal its temporal evolution characteristics. The entropy method was applied to assess the ecological benefits of UGSs in Nanjing City, China, from 2011 to 2020. The coupling harmonious degree model was utilized to analyze the dynamic coordination relations among subsystems. The Robust regression analysis was used to verify the evaluation results. The results showed that: (i) Between 2011 and 2020, UGS ecological benefits in Nanjing City exhibited a substantial and consistent upward trend. (ii) Between 2011 and 2020, the coupling harmonious degree among the subsystems of UGS ecological benefits in Nanjing City showed an overall rising trend of fluctuation. With the enhancing of the coupling harmonious degree among the subsystems of UGSs, the ecological benefit of UGSs will be significantly improved. (iii) The comprehensive evaluation score of the social and economic subsystem of UGS in Nanjing City was higher than that of the natural environment subsystem; this highlights the significant constraints posed by the natural environment on the construction of UGSs in Nanjing City. The research conclusion provides a decision basis for realizing the collaborative optimization of the natural environment and the social economy in Nanjing City and further promotes the sustainable development of the UGS ecological environment.
A Study on the Impacts of One-Strut Failure Scenarios for Deep Excavation in Loose to Medium-Dense Sand
Authors: Hsiung Bin-Chen Benson , Phan Khac-Hai , Hsiao Darn-Horng
Published: July 2023

This study aims to identify the impacts of one-strut failure (OSF) during deep excavation in loose to medium-dense sand with respect to strut loads and wall deflections. The finite element software PLAXIS was used to carry out both 2D and 3D analyses. In addition, as two-dimensional (2D) analysis is commonly applied in engineering practice due to limited budget and time, the reasonable transferring of results obtained using 3D analyses to 2D analyses for OSF influences was explored. It was found that a failed strut located at the lowest level at the center of the excavation is the most critical case since it causes the most significant impacts on strut load transferring and additional wall deflection. In order to adequately demonstrate such impacts using 2D analyses, it is suggested that a reduction factor of axial stiffness of 2.5 should be adopted instead of removing an entire level of struts, as currently being used in 2D analyses of OSF.
Selected Motivations of Student Sports Volunteers in Terms of Professional Activity and Previous Volunteering Experience
Authors: Rozmiarek Mateusz , Grajek Mateusz , Malchrowicz-Mośko Ewa , Krupa-Kotara Karolina , Burgos Jose , Aguirre-Betolaza Aitor Martínez , Castañeda-Babarro Arkaitz
Published: July 2023

Involvement in sports volunteering is not only a way to improve mental health by increasing a sense of appreciation or respect, but it also allows participants to take on an individual challenge, meet new people, or gain specific knowledge. The aim of this study was to analyze selected motivations of students from the University of Physical Education in Krakow to get involved in sports volunteering during the 2023 European Games organized in their city and verifying them in terms of gender, age, previous volunteering experience, and pursuing a career. A total of 535 students took part in the survey, of whom 52.71% (282) were female, and 47.29% (253) were male. Selected motivation statements were indicated by respondents through a 5-point Likert scale. The results of the completed study confirmed that pursuing a professional career alongside studies and previous experience in sports volunteering had an impact on undertaking sports volunteering (F = 11.754; r = 0.674; p = 0.003 and F = 10.241; r = 0.611; p = 0.002). The obtained research results may be important for sports psychologists and organizers of sports events in the context of recruiting volunteers or improving the process of managing sports volunteering.
Investigation of Following Vehicles’ Driving Patterns Using Spectral Analysis Techniques
Authors: Chae Chandle , Kim Youngho
Published: July 2023

Despite the potential benefits of autonomous vehicles (AVs) of reducing human driver errors and enhancing traffic safety, a comprehensive evaluation of recent AV collision data reveals a concerning trend of rear-end collisions caused by following vehicles. This study aimed to address this issue by developing a methodology that identifies the relationship between driving patterns and the risk of collision between leading and following vehicles using spectral analysis. Specifically, we propose a process for computing three indices: reaction time, stimulus compliance index, and collision-risk aversion index. These indices consistently produced reliable results under various traffic conditions. Our findings align with existing research on the driving patterns of following vehicles. Given the consistency and robustness of these indices, they can be effectively utilized in advanced driver assistance systems or incorporated into AVs to assess the likelihood of collision risk posed by following vehicles and develop safer driving strategies accordingly.
Heavy Metal Transport in Different Drip-Irrigated Soil Types with Potato Crop
Authors: Selim Tarek , Elkefafy Samah M. , Berndtsson Ronny , Elkiki Mohamed , El-kharbotly Ahmed A.
Published: July 2023

Heavy metal (HM)-polluted soil is a serious concern, especially as brackish water is widely used for irrigation purposes in water-scarce countries. In this study, the HYDRUS-2D model was used to simulate HM (copper (Cu), lead (Pb), and zinc (Zn)) transport through agricultural land cultivated with potato crops under surface drip irrigation to explore the potential groundwater contamination risk. Three soil types, namely, silty clay loam, sandy loam, and sandy soil, and two irrigation schemes, irrigation every two days (scheme A) and irrigation every four days (scheme B), were considered during the simulations. Firstly, the ability of HYDRUS-2D to simulate water flow was validated using data obtained from a full growing season of the potato crop in a lysimeter irrigated by surface drip irrigation using El-Salam Canal water, Egypt (i.e., water contaminated by HMs). Secondly, the model was calibrated for solute transport parameters. After that, the investigated simulation scenarios were executed. The results showed that HYDRUS-2D effectively simulated water flow. Moreover, a good agreement between the simulations and experimental results of HM concentrations under the calibrated solute parameters was obtained with R2 values of 0.99, 0.91, and 0.71 for Cu, Pb, and Zn concentrations, respectively. HM distribution is considerably influenced by the HMs’ adsorption isotherm. The results of the investigated scenarios reveal that soil texture has a greater impact on HM concentrations in the simulation domain and on the contamination risk of the groundwater than the irrigation scheme. Under both irrigation schemes, lower HM concentrations were observed in sand, while higher values were observed in silty clay loam. Subsequently, the potential shallow groundwater contamination risk is greater when cultivating potatoes in sand, as higher HM concentrations were found in drainage water compared to the two other investigated soils, regardless of the irrigation scheme. The cumulative Cu, Pb, and Zn concentrations in drainage water corresponding to scheme A for silty clay loam and sandy loam were 1.65, 1.67, and 1.67 and 1.15, 1.14, and 1.15 times higher, respectively, than scheme B. To safeguard the sustainability of groundwater and agricultural lands irrigated with water contaminated by HMs, it is recommended to adopt an irrigation frequency of once every four days in soils with silty clay loam and sandy loam textures.
Pig Farmers’ Preferences for the Adoption of Good Animal Husbandry Practices in Vietnam: A Choice Experiment
Authors: Quy Mai D. , Ha Dang T.
Published: July 2023

As the need for food safety rises, consumers are becoming more interested in certified safe pork products, such as those with safety certification or traceability. Implementing GAHP guidelines for pig farming is one potential approach to achieving food safety in Vietnam. Nevertheless, since GAHP requires a relatively substantial initial investment, its adoption is mostly determined by the economic feasibility of pig farming. A choice experiment was used in this study to investigate farmers’ preferences for adopting GAHP in pig farming in Vietnam. The findings show that pig farmers are strongly inclined to adopt GAHP if specific conditions are met. The presence of guaranteed output contracts, increased yields, and price premiums are important variables influencing their decision to implement GAHP. The findings could be used by policymakers to develop and implement supportive regulations to encourage GAHP adoption, while buyers, processors, and retailers can capitalize on pig farmers’ preferences by establishing and publicizing market channels for GAHP-certified products. Furthermore, these findings could be used to assist pig farmers in making informed choices about their farming practices, allowing them to analyze the possibility of getting output contracts, implementing productivity-boosting initiatives, and exploring market potential for GAHP-certified pigs.
The Prosumer: A Systematic Review of the New Paradigm in Energy and Sustainable Development
Authors: Parra-Domínguez Javier , Sánchez Esteban , Ordóñez Ángel
Published: July 2023

The deployment of distributed and affordable renewable energy has led to the development of the prosumer concept in the field of energy. To better understand its relevance and to analyse the main trends and research developments, a systematic literature review was performed. This work gathered 1673 articles related to this topic that were analysed following the PRISMA methodology with the help of VOSviewer 1.6.18 bibliometric software. These papers are classified into four clusters: smart grids, microgrids, peer to peer networks, and prosumers. The first two clusters show a certain degree of maturity, while the latter maintain a growing interest. The analysis of the articles provides a broad view of the prosumer’s role in energy and its potential, which is not limited to simple energy exchanges. Furthermore, this systematic review highlights the challenges, not only technical but also in terms of electricity market design and social aspects. The latter require further research, as society is undergoing a paradigm shift in the way in which energy is produced and used. How this shift occurred will determine whether it can lead to true prosumer empowerment and a fairer energy transition.
Optical Developments in Concentrator Photovoltaic Systems—A Review
Authors: Iqbal Waseem , Ullah Irfan , Shin Seoyong
Published: July 2023

Energy needs have increased with global advancements and industrial revolutions. Electrical energy utilization shares a huge amount of energy with residential and industrial loads. Traditional energy resources are expensive and polluting, producing greenhouse gasses, which is a major environmental concern. Solar energy utilization is a cost-effective, sustainable, and green solution to meet the ongoing energy demand. Concentrator photovoltaic (CPV) systems are developed for energy conversion by providing high efficiency using multi-junction solar cells. This paper provides an overview of the recent optical developments in CPV systems and emerging technologies that are likely to shape the future of CPV systems. The objective of this article is to provide an overview of the issues that need to be resolved to improve the geometrical concentration, acceptance angle, uniformity, and optical efficiency of CPV systems. A comprehensive comparison is also presented on different types of solar concentrators. In addition, future research directions are presented to facilitate the continued growth and success of CPV systems. Furthermore, this review article gives an up-to-date and widespread overview of CPV technology, assesses its potential for various applications, and distinguishes the challenges and opportunities for future research and development.
Intrapreneurial Capabilities: Multidimensional Construction and Measurement Index Validation
Authors: Yuan Fang , Wang Shuxiang , Sun Jianjun
Published: July 2023

In the era of knowledge innovation, this study addresses the new requirements for constructing enterprise intrapreneurial capabilities by examining existing theoretical research, using grounded theory to analyze sample data, and developing a measurement system for intrapreneurial capabilities. The results indicate that intrapreneurial capabilities are a concept model consisting of five categories: innovation, risk-taking, proactivity, resource management, and network construction. Utilizing structural equation verification, the study establishes an optimal second-order, five-factor measurement model for intrapreneurial capabilities, ultimately providing valuable insights for path selection and management in enterprise re-entrepreneurship.
Multiple Network Effects: “Individual-Organization Social Interaction” Model on China’s Sustainable Voluntary Service Supply Mechanism
Authors: Liu Huangjuan , Zhu Yiqiang , Li Yalan
Published: July 2023

Despite strong policy support for volunteerism, Chinese social service organizations require assistance in volunteer management, particularly concerning retaining volunteers and sustaining the supply of volunteer services. By interviewing volunteers from a successful volunteer organization and analyzing the collected data using the constructive grounded theories and methods, this study found that, contrary to the conclusions of previous studies, (1) sustainable volunteerism involves volunteers’ ability, motivation, and resources; (2) the ideal framework for the sustainability of volunteer service provision is based on a triangular support model of “individual-organization social interaction”; and (3) social interaction manifests itself in three network effects (emotional, family, and social). In particular, our analysis found that interpersonal relationships, intergenerational relationships, and parent–child education are essential to sustaining the supply of volunteer services.
Special Issue: Asymmetry and Symmetry in Organic Chemistry
Authors: Rachwalski Michał
Published: July 2023

In organic chemistry, the concepts of asymmetry and symmetry play crucial roles in understanding the properties and reactivity of molecules [...]
Long-Term Effectiveness and Sustainability of Integrating Peer-Assisted Ultrasound Courses into Medical School—A Prospective Study
Authors: Weimer Johannes Matthias , Widmer Nina , Strelow Kai-Uwe , Hopf Paula , Buggenhagen Holger , Dirks Klaus , Künzel Julian , Börner Norbert , Weimer Andreas Michael , Lorenz Liv Annebritt , Rink Maximilian , Bellhäuser Henrik , Schiestl Lina Judit , Kloeckner Roman , Müller Lukas , Weinmann-Menke Julia
Published: July 2023

Introduction: Ultrasound diagnostics is an important examination method in everyday clinical practice, but student education is often inadequate for acquiring sufficient basic skills. Individual universities have therefore started integrating (extra)curricular training concepts into medical education. This study aimed to evaluate sustainable skills development through participation in peer-assisted ultrasound courses. Methods: From 2017, students in the clinical part of medical school could opt for extracurricular peer-assisted ultrasound courses. Depending on the format (10-week course/2-day compact course) these comprised 20 teaching units focusing on abdominal and emergency ultrasonography. Students attending compulsory workshops at the start of their practical year were enrolled in this study, allowing for a comparison between the study group (attended ultrasound course) and the control group (did not attend ultrasound course). Competency from two out of four practical exams (subjects: “aorta”, “gallbladder”, “kidney” and “lung”) was measured, and a theory test on the same subject areas (“pathology recognition”) was administered. Additional questions concerned biographical data, subjective competency assessment (7-point Likert scale), and “attitude to ultrasound training in the curriculum”. Results: Analysis included 302 participants in total. Ultrasound courses had been attended on average 2.5 years earlier (10-week course) and 12 months earlier (2-day compact course), respectively. The study group (n = 141) achieved significantly better results than the control group (n = 161) in the long-term follow-up. This applies both to practical exams (p < 0.01) and theory tests (p < 0.01). After course attendance, participants reported a significantly higher subjective assessment of theoretical (p < 0.01) and practical (p < 0.01) ultrasound skills. Conclusions: Peer-assisted ultrasound courses can sustainably increase both theoretical and practical competency of medical students. This highlights the potential and need for standardised implementation of ultrasound courses in the medical education curriculum.
Emerging Plant Intoxications in Domestic Animals: A European Perspective
Authors: Nagy Andras-Laszlo , Ardelean Sabrina , Chapuis Ronan J. J. , Bouillon Juliette , Pivariu Dalma , Dreanca Alexandra Iulia , Caloni Francesca
Published: July 2023

Exposure to phytotoxins that are present in imported ornamental or native plants is an important cause of animal disease. Factors such as animal behaviors (especially indoor pets), climate change, and an increase in the global market for household and ornamental plants led to the appearance of new, previously unreported plant poisonings in Europe. This has resulted in an increase in the incidence of rarely reported intoxications. This review presents some of the emerging and well-established plant species that are responsible for poisoning episodes in companion animals and livestock in Europe. The main plant species are described, and the mechanism of action of the primary active agents and their clinical effects are presented. Data reflecting the real incidence of emerging poisoning cases from plant toxins are scarce to nonexistent in most European countries due to a lack of a centralized reporting/poison control system. The diversity of plant species and phytotoxins, as well as the emerging nature of certain plant poisonings, warrant a continuous update of knowledge by veterinarians and animal owners. The taxonomy and active agents present in these plants should be communicated to ensure awareness of the risks these toxins pose for domestic animals.
Knobs, Adhesion, and Severe Falciparum Malaria
Authors: Wiser Mark F.
Published: July 2023

Plasmodium falciparum can cause a severe disease with high mortality. A major factor contributing to the increased virulence of P. falciparum, as compared to other human malarial parasites, is the sequestration of infected erythrocytes in the capillary beds of organs and tissues. This sequestration is due to the cytoadherence of infected erythrocytes to endothelial cells. Cytoadherence is primarily mediated by a parasite protein expressed on the surface of the infected erythrocyte called P. falciparum erythrocyte membrane protein-1 (PfEMP1). PfEMP1 is embedded in electron-dense protuberances on the surface of the infected erythrocytes called knobs. These knobs are assembled on the erythrocyte membrane via exported parasite proteins, and the knobs function as focal points for the cytoadherence of infected erythrocytes to endothelial cells. PfEMP1 is a member of the var gene family, and there are approximately 60 antigenically distinct PfEMP1 alleles per parasite genome. Var gene expression exhibits allelic exclusion, with only a single allele being expressed by an individual parasite. This results in sequential waves of antigenically distinct infected erythrocytes and this antigenic variation allows the parasite to establish long-term chronic infections. A wide range of endothelial cell receptors can bind to the various PfEMP1 alleles, and thus, antigenic variation also results in a change in the cytoadherence phenotype. The cytoadherence phenotype may result in infected erythrocytes sequestering in different tissues and this difference in sequestration may explain the wide range of possible clinical manifestations associated with severe falciparum malaria.