bluuebunny/crossref_metadata_2025 huggingface dataset:
Franz Rosenzweig on Divine Love and on the Love of Enemies: Complications of Agape in the Secularized World
Authors: Berman Nadav S.
Published: July 2024

Love is a keystone in Franz Rosenzweig’s philosophy, which reaffirmed Judaism’s emphasis on vital, relational love. What “love” exactly means, however, is controversial. In the Christian context, love is often denoted by Agape—which implies (1) that “God is Love”, (2) that love is universal, impartial, and rather endorses the sinner; and (3) that humans should practice and emulate such love. The ultimate expression of Agape is the commandment to love one’s enemy, which is rooted in the Sermon on the Mount (Matthew 5:44). This essay considers Rosenzweig’s understanding of Agape, at the implicit level (since the coining by Anders Nygren of Christian love as “Agape” became widespread only after Rosenzweig’s death). This essay opens by contextualizing Rosenzweig within political theology, in particular vis-à-vis Schmitt. Secondly, it considers Rosenzweig’s approach to Agape in the sense of divine love, and in the sense of the love of enemy. Concerning divine love, Rosenzweig criticized theological Agapism (‘God is love’) which equates God with love, and hence makes love into a dogma or noun, rather than an action or verb, thus depriving divinity’s personal loving agency. Concerning the agapic love of enemy, Rosenzweig discredits its Christian version (for being imperialistic), and advocates its Jewish version of accepting divine judgement. His surprising advocacy of the love of enemies may result from Rosenzweig’s opposition to Gnosticism, which excludes the ‘good God’ from involvement in the physical world. The essay’s conclusion reflects on the role of Agape and its pragmatist versions in the post-secular world of the 21st century and conveys Rosenzweig’s pragmatist contribution in this regard, of recognizing the significance of worldliness and togetherness.
A Review of Environmental Impacts of Wheat Production in Different Agrotechnical Systems
Authors: Kheiralipour Kamran , Brandão Miguel , Holka Malgorzata , Choryński Adam
Published: July 2024

In light of the environmental challenges currently facing humanity, the issue of the environmental sustainability of crop production is becoming increasingly pressing. This is due to the fact that global population growth and the related demand for food are placing significant pressure on the environment. Wheat is a strategic crop globally due to its extensive cultivation area, high production and consumption levels, and vital nutritional properties. It is cultivated across diverse climatic conditions and within various agricultural production systems. It is of the utmost importance to pursue sustainable wheat production on a global scale, given the necessity to protect the environment and climate. The application of life cycle assessment (LCA) enables the identification of potential avenues for enhancing wheat production processes, thereby reducing the negative environmental impacts associated with these processes. This paper presents a synthesis of the existing literature on the environmental LCA of wheat grain production. It compares the impacts of different production systems, highlights critical stages in wheat cultivation, and provides recommendations for sustainable practices and directions for future research.
CGMNet: Semantic Change Detection via a Change-Aware Guided Multi-Task Network
Authors: Tan Li , Zuo Xiaolong , Cheng Xi
Published: July 2024

Change detection (CD) is the main task in the remote sensing field. Binary change detection (BCD), which only focuses on the region of change, cannot meet current needs. Semantic change detection (SCD) is pivotal for identifying regions of change in sequential remote sensing imagery, focusing on discerning “from-to” transitions in land cover. The emphasis on features within these regions of change is critical for SCD efficacy. Traditional methodologies, however, often overlook this aspect. In order to address this gap, we introduce a change-aware guided multi-task network (CGMNet). This innovative network integrates a change-aware mask branch, leveraging prior knowledge of regions of change to enhance land cover classification in dual temporal remote sensing images. This strategic focus allows for the more accurate identification of altered regions. Furthermore, to navigate the complexities of remote sensing environments, we develop a global and local attention mechanism (GLAM). This mechanism adeptly captures both overarching and fine-grained spatial details, facilitating more nuanced analysis. Our rigorous testing on two public datasets using state-of-the-art methods yielded impressive results. CGMNet achieved Overall Score metrics of 58.77% on the Landsat-SCD dataset and 37.06% on the SECOND dataset. These outcomes not only demonstrate the exceptional performance of the method but also signify its superiority over other comparative algorithms.
Do Elite Basketball Players Maintain Peak External Demands throughout the Entire Game?
Authors: Salazar Hugo , Ujakovic Filip , Plesa Jernej , Lorenzo Alberto , Alonso-Pérez-Chao Enrique
Published: July 2024

Consideration of workload intensity and peak demands across different periods of basketball games contributes to understanding the external physical requirements of elite basketball players. Therefore, the aim of this study was to investigate the average intensity and peak demands encountered by players throughout game quarters. PlayerLoad per minute and PlayerLoad at three different time samples (30 s, 1 min, and 3 min) were used as workload metrics. A total of 14 professional elite male basketball players were monitored during 30 official games to investigate this. A linear mixed model and Cohen’s d were employed to identify significant differences and quantify the effect sizes among game quarters. The results showed a significant, moderate effect in PlayerLoad per minute between Q1 vs. Q4, and a small effect between Q2 and Q3 vs. Q4. Furthermore, a small to moderate decline was observed in external peak values for PlayerLoad across game quarters. Specifically,, a significant decrease was found for the 3 min time window between Q1 and other quarters. The findings from the present study suggest that professional basketball players tend to experience fatigue or reduced physical output as the game progresses.
A Hybrid Handover Scheme for Vehicular VLC/RF Communication Networks
Authors: Jia Linqiong , Feng Shicheng , Zhang Yijin , Wang Jin-Yuan
Published: July 2024

Visible light communication (VLC) is a promising complementary technology to its radio frequency (RF) counterpart to satisfy the high quality-of-service (QoS) requirements of intelligent vehicular communications by reusing LED street lights. In this paper, a hybrid handover scheme for vehicular VLC/RF communication networks is proposed to balance QoS and handover costs by considering the vertical handover and horizontal handover together judging from the mobile state of the vehicle. A Markov decision process (MDP) is formulated to describe this hybrid handover problem, with a cost function balancing the handover consumption, delay, and reliability. A value iteration algorithm was applied to solve the optimal handover policy. The simulation results demonstrated the performance of the proposed hybrid handover scheme in comparison to other benchmark schemes.
Efficient Aperture Fill Time Correction for Wideband Sparse Array Using Improved Variable Fractional Delay Filters
Authors: Gu Jie , Xu Min , Zhou Wenjing , Shen Mingwei
Published: July 2024

To solve the problem of aperture fill time (AFT) for wideband sparse arrays, variable fractional delay (VFD) FIR filters are applied to eliminate linear coupling between spatial and time domains. However, the large dimensions of the filter coefficient matrix result in high system complexity. To alleviate the computational burden of solving VFD filter coefficients, a novel multi–regultion minimax (MRMM) model utilizing the sparse representation technique has been presented. The error function is constrained by the introduction of L2–norm and L1–norm regularizations within the minimax criterion. The L2–norm effectively resolves the problems of overfitting and non–unique solutions that arise in the sparse optimization of traditional minimax (MM) models. Meanwhile, the use of multiple L1–norms enables the optimal design of the smallest sub–filter number and order of the VFD filter. To solve the established nonconvex model, an improved sequential–alternating direction method of multipliers (S–ADMM) algorithm for filter coefficients is proposed, which utilizes sequential alternation to iteratively update multiple soft–thresholding problems. The experimental results show that the optimized VFD filter reduces system complexity significantly and corrects AFT effectively in a wideband sparse array.
Tissue-Specific Accumulation Profiles of Phorbol Esters in Response to Abiotic and Biotic Stresses in Jatropha curcas
Authors: Zhang Wei , Wei Lei , Li Shijuan , Chen Fang , Xu Ying
Published: July 2024

Jatropha curcas L. (J. curcas), a shrub plant of the Euphorbiaceae family, has received enormous attention as a promising biofuel plant for the production of biodiesel and medical potential in ethnopharmacology. However, the tumor-promoter toxin phorbol esters present in J. curcas raise concerns for health and environmental risk as its large-scale cultivation limits the use of meal obtained after oil extraction for animal feed. Here, we determined the variation of phorbol ester profiles and contents in eight J. curcas tissues by high-performance liquid chromatography (HPLC) and found phorbol esters present in all parts of the plant except the seed shell. We showed tissue-specific patterns of accumulation of phorbol esters and associated terpenoids at the transcriptional level with high transcript levels in reproductive and young tissues. Genes involved in the same module of terpenoids biosynthesis were positively correlated. We further present diverse abiotic and biotic stresses that had different effects on the accumulation of transcripts in terpenoids shared and branched terpenoid pathways in plant seedlings. The fine-tuning of terpenoids biosynthesis may link with ecological functions in plants under extreme environments and defense against pathogens.
Personalization of the Car-Sharing Fleet Selected for Commuting to Work or for Educational Purposes—An Opportunity to Increase the Attractiveness of Systems in Smart Cities
Authors: Turoń Katarzyna
Published: July 2024

Car-sharing services, which provide short-term vehicle rentals in urban centers, are rapidly expanding globally but also face numerous challenges. A significant challenge is the effective management of fleet selection to meet user expectations. Addressing this challenge, as well as methodological and literature gaps, the objective of this article is to present an original methodology that supports the evaluation of the suitability of vehicle fleets used in car-sharing systems and to identify the vehicle features preferred by users necessary for specific types of travel. The proposed methodology, which incorporates elements of transportation system modeling and concurrent analysis, was tested using a real-world case study involving a car-sharing service operator. The research focused on the commuting needs of car-sharing users for work or educational purposes. The study was conducted for a German car-sharing operator in Berlin. The research was carried out from 1 January to 30 June 2022. The findings indicate that the best vehicles for the respondents are large cars representing classes D or E, equipped with a combustion engine with a power of 63 to 149 kW, at least parking sensors, navigation, hands-free, lane assistant, heated seats, and high safety standards as indicated by Euro NCAP ratings, offered at the lowest possible rental price. The results align with market trends in Germany, which focus on the sale of at least medium-sized vehicles. This suggests a limitation of small cars in car-sharing systems, which were ideologically supposed to be a key fleet in those kinds of services. The developed methodology supports both system operators in verifying whether their fleet meets user needs and urban policymakers in effectively managing policies towards car-sharing services, including fleet composition, pricing regulations, and vehicle equipment standards. This work represents a significant step towards enhancing the efficiency of car-sharing services in the context of smart cities, where personalization and optimizing transport are crucial for sustainable development.
Perceptions of El Niño-Southern Oscillation (ENSO) and La Niña Shape Fishers’ Adaptive Capacity and Resilience
Authors: Pollnac Richard , Beitl Christine M. , Vina Michael A. , Gaibor Nikita
Published: July 2024

Much research has raised concerns about how a warming planet will interact with natural cyclical climatic variations, and the implications for the resilience and vulnerability of coastal communities. As the anticipated effects of climate change will continue to intensify, it is necessary to understand the response and adaptive capacity of individuals and communities. Coastal communities in Ecuador have evolved in an environment of such cyclical climatic variations referred to as El Niño-Southern Oscillation (ENSO) and La Niña. These climatic events are frequently characterized by extreme variations in precipitation, violent storms, and coastal flooding during El Niño and lowered sea water temperatures and drought during La Niña. This paper draws on survey data and long-term ethnographic research in Ecuadorian coastal communities to explore how fishers understand the impacts of ENSO and implications for their livelihood decisions and resilience to climate variability. The results suggest that fishers along the coast of Ecuador understand and respond differentially to the impacts of ENSO depending on social, cultural, environmental, and geographical factors. These differential levels of response suggest that livelihood diversification may uphold social resilience, which has implications for how coastal communities may adapt to the increasingly harsh weather conditions predicted by many climate models. Our findings further suggest that the impacts of El Niño are more salient than the impacts of La Niña; these findings have significant implications for fisheries management and science communication.
Taxifolin Adsorption on Nitrogenated Graphenes: Theoretical Insights
Authors: Petrushenko Igor
Published: July 2024

Solid-state drug delivery systems for the drug substances transport are of great importance nowadays. In the present work, the non-covalent interactions between taxifolin (Tax) and graphene as well as nitrogenated (N-doped) graphenes were systematically studied by using a wide set of theoretical techniques. Symmetry-adapted perturbation theory (SAPT0) calculations confirmed more favorable adsorption of Tax on N-doped graphenes compared to pristine graphene. It was established that dispersion interactions play the main role in the attractive interactions (>60%), whereas electrostatic and induction forces contribute only moderately to the attraction (~25% and 7–8%, respectively). Independent gradient model (IGM) analysis visually demonstrated the existence of dispersion interactions and hydrogen bonding in the studied Tax complexes. Ab initio molecular dynamics calculations indicated stability of these complexes at different temperatures. Our results show that N-doped graphenes with the enhanced interaction energy (Eint) toward Tax are promising candidates for the technical realization of the targeted drug delivery systems.
Bridging Cultural Perspectives: Developing a Sustainable Framework for the Comparative Aesthetic Evaluation of Eastern and Western Art
Authors: Wang Yuan , Jiang Ye , Ning Xizhen , Gao Linna
Published: July 2024

Sustainability in art is crucial for fostering intercultural understanding and preserving cultural heritage, which is essential to promoting the Sustainable Development Goals (SDGs). In previous research on Western and Chinese art, studies typically focused on individual artists and summarized their aesthetic values, often suffering from a lack of comparative analysis, a unidimensional sensory perspective, and a deficiency in comprehensive aesthetic evaluation standards. Consequently, this study selected representative watercolor works from five master artists in Western and Chinese art history as an example, constructing a comprehensive aesthetic evaluation system focusing on composition, color, themes, and techniques. Beginning with the influence of aesthetic and non-aesthetic perspectives by natural experimental method, the research employs correlation analysis and structural equation modeling to analyze the functional relationships between evaluative factors, perspective forces, and the overall aesthetic appeal of the paintings. Furthermore, the study reveals the distinctions between Eastern and Western paintings through multi-group analysis. Key findings include the following: Evaluation factors have varying effects on the influence of aesthetic and non-aesthetic perspectives. All factors, except conceptual expression (X12), brushwork expressiveness (X14), and watercolor language (X16), positively impact the overall aesthetic appeal. In mediation effects, X16 positively mediates between the influence of aesthetic perspectives and the overall aesthetic appeal. Factors such as warm–cool relationship (X8), X12, emotional atmosphere (X11), X14, and X16 positively or negatively affect the relationship between non-aesthetic perspectives and the overall aesthetic appeal. Multi-group analysis reveals significant differences in the evaluation factors and mediation effects that influence the overall aesthetic appeal. This study demonstrates the relationship between evaluation factors from different perspectives and aesthetics, providing valuable insights into evaluating Eastern and Western art. This evaluation system is applicable to academic research and practice in cultural heritage preservation and evaluation and art education, facilitating a deeper understanding of artistic values and promoting cross-cultural exchanges.
Knowledge-Guided Parallel Hybrid Local Search Algorithm for Solving Time-Dependent Agile Satellite Scheduling Problems
Authors: Shan Yuyuan , Wang Xueping , Cheng Shi , Zhang Mingming , Xing Lining
Published: July 2024

As satellite capabilities have evolved and new observation requirements have emerged, satellites have become essential tools in disaster relief, emergency monitoring, and other fields. However, the efficiency of satellite scheduling still needs to be enhanced. Learning and optimization are symmetrical processes of solving problems. Learning problem knowledge could provide efficient optimization strategies for solving problems. A knowledge-guided parallel hybrid local search algorithm (KG-PHLS) is proposed in this paper to solve time-dependent agile Earth observation satellite (AEOS) scheduling problems more efficiently. Firstly, the algorithm uses heuristic algorithms to generate initial solutions. Secondly, a knowledge-based parallel hybrid local search algorithm is employed to solve the problem in parallel. Meanwhile, data mining techniques are used to extract knowledge to guide the construction of new solutions. Finally, the proposed algorithm has demonstrated superior efficiency and computation time through simulations across multiple scenarios. Notably, compared to benchmark algorithms, the algorithm improves overall efficiency by approximately 7.4% and 8.9% in large-scale data scenarios while requiring only about 60.66% and 31.89% of the computation time of classic algorithms. Moreover, the proposed algorithm exhibits scalability to larger problem sizes.
A Factory of Fractional Derivatives
Authors: Ortigueira Manuel D.
Published: July 2024

This paper aims to demonstrate that, beyond the small world of Riemann–Liouville and Caputo derivatives, there is a vast and rich world with many derivatives suitable for specific problems and various theoretical frameworks to develop, corresponding to different paths taken. The notions of time and scale sequences are introduced, and general associated basic derivatives, namely, right/stretching and left/shrinking, are defined. A general framework for fractional derivative definitions is reviewed and applied to obtain both known and new fractional-order derivatives. Several fractional derivatives are considered, mainly Liouville, Hadamard, Euler, bilinear, tempered, q-derivative, and Hahn.
Quantum Gravity Corrections to the Inflationary Spectrum in a Bohmian Approach
Authors: Maniccia Giulia , Montani Giovanni
Published: July 2024

A precise interpretation of the universe wave function is forbidden in the spirit of the Copenhagen School since a precise notion of measure operation cannot be satisfactorily defined. Here, we propose a Bohmian interpretation of the isotropic universe quantum dynamics, in which the Hamilton–Jacobi equation is restated by including quantum corrections, which lead to a classical trajectory containing effects of order ℏ2. This solution is then used to determine the spectrum of gauge-invariant quantum fluctuations living on the obtained background model. The analysis is performed adopting the wave function approach to describe the fluctuation dynamics, which gives a time-dependent harmonic oscillator for each Fourier mode and whose frequency is affected by the ℏ2 corrections. The properties of the emerging spectrum are discussed, outlining the modification induced with respect to the scale-invariant result, and the hierarchy of the spectral index running is discussed.
Design of a Photonic Crystal Exclusive-OR Gate Using Recurrent Neural Networks
Authors: Karami Pouya , Yahya Salah I. , Chaudhary Muhammad Akmal , Assaad Maher , Roshani Saeed , Hazzazi Fawwaz , Parandin Fariborz , Roshani Sobhan
Published: July 2024

In this paper, a novel approach to design a photonic crystal exclusive-OR (XOR) gate with high performance using recurrent neural network (RNN) is proposed, integrating the principles of symmetry and asymmetry inherent in photonic structures. The proposed model realizes the nonlinearities and dispersion properties in photonic systems, optimizing the waveguide paths and interference patterns to improve the performance of the logic gate. Simulation results demonstrate that the presented RNN design not only achieves high fidelity in the logical operation but also significantly enhances the functionality of the all-optical gate. This integration of machine learning with photonic crystal technology opens a new era for developing compact, energy-efficient photonic circuits for high-speed optical computing. Finally, the performance of the designed all-optical gate is compared with other related methods, which shows that the proposed gate outperforms other works. The results show that the obtained output power of the proposed all-optical XOR gate is 0, 0.813, 0.82, and 1 × 10−7 in the logical states.
Portfolio Optimization with Multi-Trend Objective and Accelerated Quasi-Newton Method
Authors: Lin Caiming , He Xinyi
Published: July 2024

We propose a portfolio optimization method with a multi-trend objective and an accelerated quasi-Newton method (MTO-AQNM). It leverages a BFGS-based quasi-Newton algorithm and incorporates an ℓ1 regularization term and the self-funding constraint. The MTO is designed to identify multiple trend reversals. Different trend reversals are asymmetric, and we hoped to extract rich and effective information from them. The AQNM adopts the BFGS method with the Wolfe conditions, which reduces computational complexity and improves convergence speed. We wanted to evaluate the performance of our algorithm through financial markets that were asymmetric in all respects. To this end, we conducted comprehensive experimental approaches on six benchmark data sets of real-world financial markets that were asymmetric in time, frequency, and asset type. Our method demonstrated superior performance over other state-of-the-art competitors across several mainstream evaluation metrics.
Study on Fault Diagnosis of Single-Group Springs of Mining Vibrating Screen
Authors: Cai Xiaoxiao , Chu Changyong , Wang Zhenyu , Lu Hao
Published: July 2024

In the mining vibrating screen’s working process, the support spring often fails due to alternating loads and a poor working environment. The six-degrees-of-freedom simplified rigid body dynamic model is established to obtain the vibration response of the mining vibrating screen with a faulty single-group spring and is verified using the ABAQUS (2020) simulation in this paper. Unlike previous studies focusing on multiple-group spring failures or using lower-degree-of-freedom models, this study addresses the common single-group spring failure with the comprehensive model capturing complex spatial motion. This study also reveals that the vibration angle can be used to diagnose the failure location, while the vibration displacement can be used to evaluate the health state of single-group springs. Based on these rules, the novel method for locating a faulty spring group and new evaluation formulas for their health states are validated by the simulations. The results indicate that the failure location is accurately diagnosed, and the errors of the health state evaluation are minimal. The evaluated values are 66.12% and 85.56% when the health states of the spring groups at the feed side and the out-feed side are 65% and 85%, respectively. Therefore, this diagnostic model provides significant theoretical assistance for diagnosing single-group spring failure in the mining vibrating screen, enhancing maintenance strategies and operational reliability.
Order Bounded and 2-Complex Symmetric Weighted Superposition Operators on Fock Spaces
Authors: Jiang Zhi-Jie
Published: July 2024

One aim of the paper is to characterize some complex symmetric and 2-complex symmetric bounded weighted superposition operators on Fock spaces respect to the conjugations J and Jr,s,t defined by Jf(z)=f(z¯)¯ and Jr,s,tf(z)=teszf(rz+s¯)¯. Another aim is to characterize the order bounded weighted superposition operators from one Fock space into another Fock space.
Tongue Disease Prediction Based on Machine Learning Algorithms
Authors: Hassoon Ali Raad , Al-Naji Ali , Khalid Ghaidaa A. , Chahl Javaan
Published: July 2024

The diagnosis of tongue disease is based on the observation of various tongue characteristics, including color, shape, texture, and moisture, which indicate the patient’s health status. Tongue color is one such characteristic that plays a vital function in identifying diseases and the levels of progression of the ailment. With the development of computer vision systems, especially in the field of artificial intelligence, there has been important progress in acquiring, processing, and classifying tongue images. This study proposes a new imaging system to analyze and extract tongue color features at different color saturations and under different light conditions from five color space models (RGB, YcbCr, HSV, LAB, and YIQ). The proposed imaging system trained 5260 images classified with seven classes (red, yellow, green, blue, gray, white, and pink) using six machine learning algorithms, namely, the naïve Bayes (NB), support vector machine (SVM), k-nearest neighbors (KNN), decision trees (DTs), random forest (RF), and Extreme Gradient Boost (XGBoost) methods, to predict tongue color under any lighting conditions. The obtained results from the machine learning algorithms illustrated that XGBoost had the highest accuracy at 98.71%, while the NB algorithm had the lowest accuracy, with 91.43%. Based on these obtained results, the XGBoost algorithm was chosen as the classifier of the proposed imaging system and linked with a graphical user interface to predict tongue color and its related diseases in real time. Thus, this proposed imaging system opens the door for expanded tongue diagnosis within future point-of-care health systems.
Evaluating Factors Shaping Real-Time Internet-of-Things-Based License Plate Recognition Using Single-Board Computer Technology
Authors: Netinant Paniti , Phonsawang Siwakron , Rukhiran Meennapa
Published: July 2024

Reliable and cost-efficient license plate recognition (LPR) systems enhance security, traffic management, and automated toll collection in real-world applications. This study addresses optimal unique configurations for enhancing LPR system accuracy and reliability by evaluating the impact of camera angle, object velocity, and distance on the efficacy of real-time LPR systems. The Internet of Things (IoT) LPR framework is proposed and utilized on single-board computer (SBC) technology, such as the Raspberry Pi 4 platform, with a high-resolution webcam using advanced OpenCV and OCR–Tesseract algorithms applied. The research endeavors to simulate common deployment scenarios of the real-time LPR system and perform thorough testing by leveraging SBC computational capabilities and the webcam’s imaging capabilities. The testing process is not just comprehensive, but also meticulous, ensuring the system’s reliability in various operational settings. We performed extensive experiments with a hundred repetitions at diverse angles, velocities, and distances. An assessment of the data’s precision, recall, and F1 score indicates the accuracy with which Thai license plates are identified. The results show that camera angles close to 180° significantly reduce perspective distortion, thus enhancing precision. Lower vehicle speeds (<10 km/h) and shorter distances (<10 m) also improve recognition accuracy by reducing motion blur and improving image clarity. Images captured from shorter distances (approximately less than 10 m) are more accurate for high-resolution character recognition. This study substantially contributes to SBC technology utilizing IoT-based real-time LPR systems for practical, accurate, and cost-effective implementations.
Comparison of the Size Measurement of Gallbladder Polyps by Three Different Radiologists in Abdominal Ultrasonography
Authors: Lee Kyu-Chong , Kim Jin-Kyem , Kim Dong-Kyu
Published: July 2024

Background: There is little information regarding the size measurement differences in gallbladder (GB) polyps performed by different radiologists on abdominal ultrasonography (US). Aim: To reveal the differences in GB polyp size measurements performed by different radiologists on abdominal US. Methods: From June to September 2022, the maximum diameter of 228 GB polyps was measured twice on abdominal US by one of three radiologists (a third-year radiology resident [reader A], a radiologist with 7 years of experience in abdominal US [reader B], and an abdominal radiologist with 8 years of experience in abdominal US [reader C]). Intra-reader agreements for polyp size measurements were assessed by intraclass correlation coefficient (ICC). A Bland–Altman plot was used to visualize the differences between the first and second size measurements in each reader. Results: Reader A, reader B, and reader C evaluated 65, 77, and 86 polyps, respectively. The mean size of measured 228 GB polyps was 5.0 ± 1.9 mm. Except for the case where reader A showed moderate intra-reader agreement (0.726) for polyps with size ≤ 5 mm, all readers showed an overall high intra-reader reliability (reader A, ICC = 0.859; reader B, ICC = 0.947, reader C, ICC = 0.948), indicative of good and excellent intra-reader agreements. The 95% limit of agreement of reader A, B, and C was 1.9 mm of the mean in all three readers. Conclusions: GB polyp size measurement on abdominal US showed good or excellent intra-reader agreements. However, size changes of approximately less than 1.9 mm should be interpreted carefully because these may be within the measurement error.
Spirobenzofuran Mitigates Ochratoxin A-Mediated Intestinal Adverse Effects in Pigs through Regulation of Beta Defensin 1
Authors: Yoon Jung Woong , Kim Myoung Ok , Shin Sangsu , Kwon Woo-Sung , Kim Soo Hyun , Kwon Yun-Ju , Lee Sang In
Published: July 2024

Antimicrobial peptides (AMPs) function to extensively suppress various problematic factors and are considered a new alternative for improving livestock health and enhancing immunomodulation. In this study, we explored whether AMP regulation has positive influences on Ochratoxin A (OTA) exposure using a porcine intestinal epithelial cell line (IPEC-J2 cells). We constructed a beta-defensin 1 (DEFB1) expression vector and used it to transfection IPEC-J2 cells to construct AMP overexpression cell lines. The results showed that OTA induced cytotoxicity, decreased cell migration, and increased inflammatory markers mRNA in IPEC-J2 cells. In DEFB1 overexpressing cell lines, OTA-induced reduced cell migration and increased inflammatory markers mRNA were alleviated. Additionally, a natural product capable of inducing DEFB1 expression, which was selected through high-throughput screening, showed significant alleviation of cytotoxicity, cell migration, and inflammatory markers compared to OTA-treated IPEC-J2 cells. Our finding provides novel insights and clues for the porcine industry, which is affected by OTA exposure.
Investigation of the Use of Environmental Samples for the Detection of EHV-1 in the Stalls of Subclinical Shedders
Authors: Pusterla Nicola , Lawton Kaila , Barnum Samantha
Published: July 2024

In populations of healthy show horses, the subclinical transmission and circulation of respiratory pathogens can lead to disease outbreaks. Due to recent outbreaks of equine herpesvirus-1 myeloencephalopathy (EHM) in the USA and Europe, many show organizers have instituted various biosecurity protocols such as individual horse testing, monitoring for early clinical disease and increasing hygiene and cleanliness protocols. The aim of this study was to determine the accuracy of detecting EHV-1 in the various environmental samples collected from the stalls of subclinical shedders. Four healthy adult horses were vaccinated intranasally with a modified-live EHV-1 vaccine in order to mimic subclinical shedding. Three additional horses served as non-vaccinated controls. All the horses were stabled in the same barn in individual stalls. Each vaccinated horse had nose-to-nose contact with at least one other horse. Prior to the vaccine administration, and daily thereafter for 10 days, various samples were collected, including a 6” rayon-tipped nasal swab, an environmental sponge, a cloth strip placed above the automatic waterer and an air sample. The various samples were processed for nucleic acid purification and analyzed for the presence of EHV-1 via quantitative PCR (qPCR). EHV-1 in nasal secretions was only detected in the vaccinated horses for 1–2 days post-vaccine administration. The environmental sponges tested EHV-1 qPCR-positive for 2–5 days (median 3.5 days) in the vaccinated horses and 1 day for a single control horse. EHV-1 was detected by qPCR in stall strips from three out of four vaccinated horses and from two out of three controls for only one day. EHV-1 qPCR-positive air samples were only detected in three out of four vaccinated horses for one single day. For the vaccinated horses, a total of 25% of the nasal swabs, 35% of the environmental stall sponges, 7.5% of the strips and 7.5% of the air samples tested qPCR positive for EHV-1 during the 10 study days. When monitoring the subclinical EHV-1 shedders, the collection and testing of the environmental sponges were able to detect EHV-1 in the environment with greater frequency as compared to nasal swabs, stationary strips and air samples.
IgA Anti-β2-Glycoprotein I Antibodies as Markers of Thrombosis and Severity in COVID-19 Patients
Authors: Mellor-Pita Susana , Tutor-Ureta Pablo , Velasco Paula , Plaza Aresio , Diego Itziar , Vázquez-Comendador José , Vionnet Ana Paula , Durán-del Campo Pedro , Moreno-Torres Víctor , Vargas Juan Antonio , Castejon Raquel
Published: July 2024

Patients with COVID-19 may develop a hypercoagulable state due to tissue and endothelial injury, produced by an unbalanced immune response. Therefore, an increased number of thromboembolic events has been reported in these patients. The aim of this study is to investigate the presence of antiphospholipid antibodies (aPL) in COVID-19 patients, their role in the development of thrombosis and their relationship with the severity of the disease. In this retrospective study, serum samples from 159 COVID-19 patients and 80 healthy donors were analysed for the presence of aPL. A total of 29 patients (18.2%) and 14 healthy donors (17.5%) were positive for aPL. Nineteen COVID-19 patients (12%) but no healthy donor presented a positive percentage of the IgA isotype aPL. IgA anti-β2-glycoprotein I antibodies (anti-β2GPI) were the most frequent type (6.3%) in patients but was not detected in any healthy donor. The positivity of this antibody was found to be significantly elevated in patients with thromboembolic events (25% vs. 5%, p = 0.029); in fact, patients with positive IgA anti-β2GPI had an incidence of thrombosis over six times higher than those who had normal antibody concentrations [OR (CI 95%) of 6.67 (1.5–30.2), p = 0.014]. Additionally, patients with moderate-severe disease presented a higher aPL positivity than patients with mild disease according to the Brescia (p = 0.029) and CURB-65 (p = 0.011) severity scales. A multivariate analysis showed that positivity for IgA anti-β2GPI is significantly associated with disease severity measured by CURB-65 [OR (CI 95%) 17.8 (1.7–187), p = 0.0016]. In conclusion, COVID-19 patients have a significantly higher positive percentage of the IgA isotype aPL than healthy donors. IgA anti-β2GPI antibodies were the most frequently detected aPL in COVID-19 patients and were associated with thrombosis and severe COVID-19 and are thus proposed as a possible marker to identify high-risk patients.
Molecular Characterization of a Novel Rubodvirus Infecting Raspberries
Authors: Lenz Ondřej , Koloniuk Igor , Sarkisová Tatiana , Čmejla Radek , Valentová Lucie , Rejlová Martina , Sedlák Jiří , Blystad Dag-Ragnar , Sapkota Bijaya , Hamborg Zhibo , Tan Jiunn Luh , Zemek Rostislav , Jaroslava Přibylová , Fránová Jana
Published: July 2024

A novel negative-sense single-stranded RNA virus showing genetic similarity to viruses of the genus Rubodvirus has been found in raspberry plants in the Czech Republic and has tentatively been named raspberry rubodvirus 1 (RaRV1). Phylogenetic analysis confirmed its clustering within the group, albeit distantly related to other members. A screening of 679 plant and 168 arthropod samples from the Czech Republic and Norway revealed RaRV1 in 10 raspberry shrubs, one batch of Aphis idaei, and one individual of Orius minutus. Furthermore, a distinct isolate of this virus was found, sharing 95% amino acid identity in both the full nucleoprotein and partial sequence of the RNA-dependent RNA polymerase gene sequences, meeting the species demarcation criteria. This discovery marks the first reported instance of a rubodvirus infecting raspberry plants. Although transmission experiments under experimental conditions were unsuccessful, positive detection of the virus in some insects suggests their potential role as vectors for the virus.
Long-Lasting Enhanced Cytokine Responses Following SARS-CoV-2 BNT162b2 mRNA Vaccination
Authors: Cabău Georgiana , Badii Medeea , Mirea Andreea M. , Gaal Orsolya I. , van Emst Liesbeth , Popp Radu A. , Crișan Tania O. , Joosten Leo A. B.
Published: July 2024

The mRNA vaccine against COVID-19 protects against severe disease by the induction of robust humoral and cellular responses. Recent studies have shown the capacity of some vaccines to induce enduring non-specific innate immune responses by the induction of trained immunity, augmenting protection against unrelated pathogens. This study aimed to assess whether the mRNA vaccine BNT162b2 can induce lasting non-specific immune responses in myeloid cells following a three-dose vaccination scheme. In a sample size consisting of 20 healthy individuals from Romania, we assessed inflammatory proteins using the Olink® Target 96 Inflammation panel, as well as ex vivo cytokine responses following stimulations with unrelated PRR ligands. We assessed the vaccine-induced non-specific systemic inflammation and functional adaptations of myeloid cells. Our results revealed the induction of a stimulus- and cytokine-dependent innate immune memory phenotype that became apparent after the booster dose and was maintained eight months later in the absence of systemic inflammation.
Primary Healthcare Providers’ Views on Periodic COVID-19 Booster Vaccination for Themselves and Their Patients: A 2023 Nationwide Survey in Belgium
Authors: Digregorio Marina , Van Ngoc Pauline , Domen Julie , Bognar Zsofia , Duysburgh Els , Hendrickx Greet , Van Damme Pierre , Coenen Samuel , Scholtes Beatrice
Published: July 2024

New COVID-19 strains and waning vaccine effectiveness prompted initiatives for booster vaccination. In Belgium, healthcare providers (HCPs) received a second booster in July 2022, with eligible individuals receiving a third in autumn. Primary HCPs (PHCPs) play a crucial role in healthcare organization and patient communication. This study, conducted in February–March 2023, surveyed 1900 Belgian PHCPs to assess their views on periodic COVID-19 boosters for themselves and their patients. The survey included questions on sociodemographic information, willingness to receive periodic COVID-19 boosters, reasons for acceptance or refusal, confidence in vaccine safety and efficacy, and views on booster recommendations. Overall, 86% of participants were willing to receive periodic COVID-19 boosters, motivated by self-protection, patient well-being, and the uninterrupted delivery of healthcare services. Factors influencing booster refusal included not being a general practitioner (GP) or GP trainee, working in Wallonia or Brussels, and lacking vaccine confidence. Although 243 participants would not take boosters periodically, only 74 would not recommend it. Regarding administration, 59% supported pharmacist involvement in COVID-19 vaccination. Further qualitative analysis of 290 PHCPs’ responses revealed varying recommendations, including specific roles like nurses, organizational structures, and collaborative approaches. This study highlights the need to address vaccine confidence, regional disparities, and PHCP roles in booster implementation.
The Reduced-Order Modeling Approach for a Double-Damper Concept: A Comparison with a Single Damper for Comfort Analysis
Authors: Hamedi Behzad , Shrikanthan Sudarshan , Taheri Saied
Published: July 2024

This paper explores the modeling and simulation of an innovative double-damper suspension system, evaluating its effectiveness through different test scenarios. The double damper integrates two individual dampers into a unified assembly. The modeling process involves representing the damper as two distinct dampers and a body block, accounting for the additional degree of freedom introduced by combining the two dampers. Simulink/MATLAB is employed for modeling the pressure, discharge, and force equations of the damper. A simplified quarter-car model is designed to conduct simulations for different road profiles, evaluating the efficacy of this double-damper model. The reduced-order modeling approach, suitable for complex systems like dampers, is utilized. Dedicated mathematical models are utilized to examine both single- and double-damper configurations, with the resulting non-linear equations solved using Newton’s iterative method. The equations derived for the single damper provide the basis for modeling the double-damper system. In this model, two separate dampers, each possessing similar properties, are simulated and considered to be rigidly linked at their connection point. Consequently, it is assumed that a portion of the force and velocity experienced by the lower damper is transmitted to the upper damper, and vice versa. Simulation results demonstrate that the innovative double-damper design outperforms a single passive damper in attenuating the oscillations of both the sprung and unsprung masses. Moreover, this innovative concept offers increased adaptability to balance between ride comfort and road holding, a feature previously limited to passive suspension systems.
Robot Motion Planning Based on an Adaptive Slime Mold Algorithm and Motion Constraints
Authors: Chen Rong , Song Huashan , Zheng Ling , Wang Bo
Published: July 2024

The rapid advancement of artificial intelligence technology has significantly enhanced the intelligence of mobile robots, facilitating their widespread utilization in unmanned driving, smart home systems, and various other domains. As the scope, scale, and complexity of robot deployment continue to expand, there arises a heightened demand for enhanced computational power and real-time performance, with path planning emerging as a prominent research focus. In this study, we present an adaptive Lévy flight–rotation slime mold algorithm (LRSMA) for global robot motion planning, which incorporates LRSMA with the cubic Hermite interpolation. Unlike traditional methods, the algorithm eliminates the need for a priori knowledge of appropriate interpolation points. Instead, it autonomously detects the convergence status of LRSMA, dynamically increasing interpolation points to enhance the curvature of the motion curve when it surpasses the predefined threshold. Subsequently, it compares path lengths resulting from two different objective functions to determine the optimal number of interpolation points and the best path. Compared to LRSMA, this algorithm reduced the minimum path length and average processing time by (2.52%, 3.56%) and (38.89%, 62.46%), respectively, along with minimum processing times. Our findings demonstrate that this method effectively generates collision-free, smooth, and curvature-constrained motion curves with the least processing time.
Place-Based Collaborative Action as a Means of Delivering Goods and Services in Rural Areas of Developed Economies
Authors: Slee Bill , Hopkins Jonathan
Published: July 2024

This paper challenges the simplified binary division of suppliers of goods and services into market or state categories and identifies the continued relevance of household, community, and third-sector provision in rural areas. We explain the emergence, survival, and development of place-based and collaborative action using a three-fold typology, reflecting differences in the motivations and rationales for providing goods and services in these ways. In a place-based context, some communities have acted collectively using collaborative agency. Many observers of rural community development have suggested that place-based communitarian action may be unable to break free from class-based controls, but this is contested by some compelling examples. Where supported by effective public policy, place-based communitarianism can offer an alternative mode of provision for a wide range of services. Using Scotland as an example, this paper explores the dynamics of interactions between community and policy actors in land acquisition and management, renewable energy, and social care.