bluuebunny/crossref_metadata_2025_split huggingface dataset:
Specific and Plastic: Chandelier Cell-to-Axon Initial Segment Connections in Shaping Functional Cortical Network
Authors: Qi Yanqing , Zhao Rui , Tian Jifeng , Lu Jiangteng , He Miao , Tai Yilin 
Published: July 2024

AbstractAxon initial segment (AIS) is the most excitable subcellular domain of a neuron for action potential initiation. AISs of cortical projection neurons (PNs) receive GABAergic synaptic inputs primarily from chandelier cells (ChCs), which are believed to regulate action potential generation and modulate neuronal excitability. As individual ChCs often innervate hundreds of PNs, they may alter the activity of PN ensembles and even impact the entire neural network. During postnatal development or in response to changes in network activity, the AISs and axo-axonic synapses undergo dynamic structural and functional changes that underlie the wiring, refinement, and adaptation of cortical microcircuits. Here we briefly introduce the history of ChCs and review recent research advances employing modern genetic and molecular tools. Special attention will be attributed to the plasticity of the AIS and the ChC-PN connections, which play a pivotal role in shaping the dynamic network under both physiological and pathological conditions.
Hindrances and Enablers of Healthy Eating Behavior Among College Students in an HBCU: A Qualitative Study
Authors: Antwi Janet , Olawuyi Yetunde , Opara Innocent , Ifafore Modupe 
Published: July 2024

AbstractResearch indicates widespread unhealthy eating habits among college students, posing long-term health risks. This study at a Historically Black College and University (HBCU) aimed to explore the perceived obstacles and facilitators to healthy eating among college students, using the social ecological model (SEM). Through focus group discussions and key informant interviews, the study identified several barriers to healthy eating, including challenges in accessing federal food assistance resources, gaps in nutrition knowledge, cost concerns, limited food variety on campus, difficulty accessing grocery stores, and a lack of cooking skills. To address these barriers, participants suggested various solutions, such as implementing cooking demonstrations, providing nutrition education, increasing food variety on campus, offering gardening opportunities, adjusting cafeteria hours for more flexibility, making fresh produce more available on campus, assisting students in accessing federal food assistance programs, and providing transportation to nearby grocery stores. The findings highlight the need for targeted interventions to promote healthier dietary behaviors among college students, particularly those attending HBCUs. By addressing the identified barriers and implementing the suggested solutions, initiatives can be developed to support students in making healthier food choices, ultimately reducing long-term health risks associated with unhealthy eating habits.
Recent Advances in Bio-Based Adhesives and Formaldehyde-Free Technologies for Wood-Based Panel Manufacturing
Authors: Calvez Ingrid , Garcia Rosilei , Koubaa Ahmed , Landry Véronic , Cloutier Alain 
Published: July 2024

Abstract
Purpose of Review
Conventional formaldehyde-based adhesives for wood-based composite panels are subject to significant concerns due to their formaldehyde emissions. Over the past decade, the wood adhesive industry has undergone a considerable transformation that is characterized by a major push in bio-adhesive development. Various bio-based materials have been explored to create alternatives to conventional formaldehyde-based adhesives. Moreover, growing interest in circularity has led to increasingly exploiting industrial coproducts and by-products to find innovative solutions.

Recent Findings
Industrial production generates many coproducts that can serve as renewable resources to produce eco-friendly materials. These coproducts offer alternative supply sources for material production without encroaching on food production. Many bio-based compounds or coproducts, such as saccharides, proteins, tannins, and lignocellulosic biomass, can also be used to develop bio-based adhesives. As part of ongoing efforts to reduce formaldehyde emissions, new hardeners and crosslinkers are being developed to replace formaldehyde and bio-scavengers. Other alternatives, such as binderless panels, are also emerging.

Summary
This review focuses on sources of bio-based material derived from by-products of various industries, which have many advantages and disadvantages when incorporated into adhesives. Modification methods to enhance their properties and performance in wood-based panels are also discussed. Additionally, alternatives for developing low-emission or formaldehyde-free adhesives are addressed, including hardeners, bio-scavengers, and binderless options. Finally, the environmental impact of bio-based adhesives compared to that of synthetic alternatives is detailed.
Negation of permutation mass function in random permutation sets theory for uncertain information modeling
Authors: Tang Yongchuan , Li Rongfei , Guan He , Zhou Deyun , Huang Yubo 
Published: July 2024

AbstractNegation provides a novel perspective for the representation of information. However, current research seldom addresses the issue of negation within the random permutation set theory. Based on the concept of belief reassignment, this paper proposes a method for obtaining the negation of permutation mass function in the of random set theory. The convergence of proposed negation is verified, the trends of uncertainty and dissimilarity after each negation operation are investigated. Furthermore, this paper introduces a negation-based uncertainty measure, and designs a multi-source information fusion approach based on the proposed measure. Numerical examples are used to verify the rationality of proposed method.
Tests for market failures and overcoming transaction costs barriers to market participation in Afghanistan
Authors: Ahmadzai Hayatullah 
Published: July 2024

AbstractSimilar to other fragile poor countries, the majority of the rural population in Afghanistan depend directly or indirectly on small-scale farming for their livelihoods, and poor infrastructure and other barriers restrict access to markets and services, making improving access to local input markets a significant challenge for policymakers aiming to increase productivity. This paper offers empirical evidence addressing two important issues for smallholder participation in input markets: are rural markets incomplete or failing and how do transaction costs affect participation in factor markets? Pooled cross-sectional data from three waves of nationally representative surveys between 2011 and 2016 with a sample of nearly 21,000 households are used. The analysis first tests and rejects the separability hypothesis that household production and consumption decisions are independent which can be interpreted as evidence of market failures. A control function approach with instrumental variables to address endogeneity is employed to estimate household input market participation decisions. Ownership of or access to information and communication technology and transport equipment are used as proxies for transaction costs. Results confirm that lower transaction costs increase input market participation and expenditure on inputs by farm households. Additionally, households with better access to roads and district or provincial market centres have higher market participation and expenditure on input. Reducing transaction costs plays an important role in input use, potentially increasing productivity and incomes.
Thermal Properties of 3D-Printed Molds for Light Metal Casting
Authors: Kleinhans Robert , Pintore Manuel , Erhard Patricia , Renz Ralph , Tesfu Johanna 
Published: July 2024

AbstractBinder Jetting technology is well established for the production of sand molds and cores for foundry use, owing to its flexibility and expansive design capabilities. A wide array of sand, aggregate, and binder combinations is commercially available. Utilizing these types of refractory materials in the casting process presents both technical and economic benefits and drawbacks. For intricate cast components, foundry technologists must assess the thermophysical properties of the mold material systems. With this knowledge, specialized high-performance material combinations may be employed in specific areas of the mold, while more economically viable systems are used for shaping the external mold support. This study primarily focuses on determining the heat capacity and thermal diffusivity and consequently the thermal conductivity using a specially developed analytical method. It investigates three different fundamental aggregates: silica, cerabeads®, and chromite. The result’s range provides an overview of relevant characteristics for the selected material systems. Given that the properties of sand affect heat flow during casting and solidification, these newly determined values can be utilized in future simulations. Consequently, these findings aid in maintaining and enhancing the quality of critically stressed cast parts.
Knowledge Leaks in Data-Driven Business Models? Exploring Different Types of Knowledge Risks and Protection Measures
Authors: Fruhwirth Michael , Pammer-Schindler Viktoria , Thalmann Stefan 
Published: July 2024

AbstractData-driven business models imply the inter-organisational exchange of data or similar value objects. Data science methods enable organisations to discover patterns and eventually knowledge from data. Further, by training machine learning models, knowledge is materialised in those models. Thus, organisations might risk the exposure of competitive knowledge by sharing data-related value objects, such as data, models or predictions. Although knowledge risks have been studied in traditional business models, little research has been conducted in the direction of data-driven business models. In this explorative qualitative study, we conducted 28 expert interviews in three rounds (two exploratory and one evaluatory) and identified five types of risks along the three basic types of value objects: data, models and predictions. These risks depend on the context, i.e., when competitive knowledge could be discovered from shared value objects. We found that those risks can be mitigated by technology, contractual regulations, trusted relationships, and adjusting the business model design. In this study, we show that the risk of knowledge leakage is a relevant risk factor in data-driven business models. Overall, knowledge risks should be considered already during business model design, and their management requires an interdisciplinary approach via a balanced assessment. The level of knowledge protection from a technology perspective highly depends on computer science innovations and thus is a moving target. As an outlook, we suggest that knowledge risk will become even more relevant with the extensive usage of machine learning and artificial intelligence in data-driven business models.
Two deep learning methods in comparison to characterize droplet sizes in emulsification flow processes
Authors: Burke Inga , Dhayaparan Thajeevan , Youssef Ahmed S. , Schmidt Katharina , Kockmann Norbert 
Published: July 2024

AbstractFor reliable supervision in multiphase processes, the droplet size represents a critical quality attribute and needs to be monitored. A promising approach is the use of smart image flow sensors since optical measurement is the most commonly used technique for droplet size distribution determination. For this, two different AI-based object detection methods, Mask RCNN and YOLOv4, are compared regarding their accuracy and their applicability to an emulsification flow process. Iterative optimization steps, including data diversification and adaption of training parameters, enable the models to achieve robust detection performance across varying image qualities and compositions. YOLOv4 shows better detection performances and more accurate results which leads to a wider application window than Mask RCNN in determining droplet sizes in emulsification processes. The final droplet detection model YOLOv4 with Hough Circle (HC) for feature extraction determines reliable droplet sizes across diverse datasets of liquid-liquid flow systems (disperse phase content 1–15 vol.-%, droplet size range 5–150 μm). Evaluating the adjustment of Confidence Scores (CS) ensures statistical representation of even smaller droplets. The droplet detection performance of the final YOLOv4 model is compared with a manual image processing method to validate the model in general as well as its accuracy and reliability. Since YOLOv4 in combination with Hough Circle (HC) shows an accurate and robust detection and size determination, it is applicable for online monitoring and characterization of various liquid-liquid flow processes.
Graphical abstract
Internet of robotic things with a local LoRa network for teleoperation of an agricultural mobile robot using a digital shadow
Authors: Shamshiri Redmond R. , Navas Eduardo , Dworak Volker , Schütte Tjark , Weltzien Cornelia , Cheein Fernando A. Auat 
Published: July 2024

AbstractIn unstructured agricultural fields where autonomous navigation is challenging and demands additional safety, the operator’s experience and knowledge are essential for supervising operations and making decisions beyond the robot’s autonomous capabilities. Local networks with long-range wireless communication combined with digital twin concepts are promising solutions that can be used for robot teleoperation. The purpose of this study was to demonstrate the feasibility of supervising a mobile robot inside berry orchards using a digital shadow from a long-range distance (between 300 and 3000 m), with the primary objective of assisting the robot in navigating in complex situations such as row-end turning. This involved creating a virtual representation of the robot that mirrors its state and actions, allowing the remote operator to monitor and guide the robot effectively. The system comprised a GPS-based navigation controller with collision avoidance sensors, two sets of LoRa transmitters and repeaters, a simulation environment with a digital shadow of the robot, and a graphical user interface for the remote operator. Information about the digital shadow’s state, including location, orientation, and distances to obstacles, was received as a message by the LoRa gateway and was used to update the path for the actual robot that interfaced with the Robot Operating System (ROS). The main research hypothesis aimed to test the quality of the LoRa communication link between the robot and the operator, as well as the robustness of the robot’s control system, with an emphasis on the architecture, communication link, and situation awareness creation. Preliminary results showed that depending on the environment, the average packet loss was 12% at distances of approximately 2300 m. Our results highlight some of the core technical challenges that need to be addressed for an effective teleoperation system, including latency, stability, and the limited range of wireless communication. Future works involves evaluating the performance and reliability of the proposed method under different field conditions and scenarios, as well as considering the use of the 5G network for a significant improvement in data transmission speed, navigation efficiency, and visual feedback. Upon successful implementation, this study has the potential to enhance the efficiency and safety of robot navigation, providing a practical solution for remote supervision in challenging environments.
Pharmacological and phytochemical review of Acmella oleracea: a comprehensive analysis of its therapeutic potential
Authors: Aktar Mst. Asma , Bhuia Md. Shimul , Molla Shamim , Chowdhury Raihan , Sarkar Chandan , Al Shahariar Md. , Roy Pias , Reiner Željko , Sharifi-Rad Javad , Calina Daniela , Shakil Md. Abdul Kader , Islam Muhammad Torequl 
Published: July 2024

AbstractAcmella oleraceaL. (Asteraceae), commonly known as the toothache plant, is a tropical herb with significant therapeutic potential. Traditionally, it has been used for its analgesic and sialagogue properties, and it is known for its distinctive yellow flower crest. This review addresses current gaps in the understanding of its pharmacological properties and aims to provide a comprehensive analysis of its therapeutic potential. A thorough literature review was conducted using databases such as Google Scholar, ScienceDirect, and PubMed/MedLine. The findings indicate that A. oleraceacontains a variety of phytochemicals, including spilanthol, which exhibit diverse pharmacological activities such as antioxidant, anti-inflammatory, immunomodulatory, antinociceptive, pronociceptive, antibacterial, antifungal, antidiabetic, diuretic, and vasorelaxant effects. The results highlight the significant medicinal potential ofA. oleraceawhile also identifying areas for further research, particularly regarding its toxicological impacts on humans and animals. This review aims to guide future studies on the health benefits and safety of this plant.
Field test of a bioaugmentation agent for the bioremediation of chlorinated ethene contaminated sites
Authors: Krett Gergely , Romsics Csaba , Jurecska Laura , Bódai Viktória , Erdélyi Balázs , Márialigeti Károly , Nagymáté Zsuzsanna 
Published: July 2024

AbstractChlorinated ethenes are toxic compounds that were widely used in the past, and their improper handling and storage caused notable pollutions worldwide. In situ bioremediation by reductive dechlorination of bacteria is a cost-effective and ecologically friendly way to eliminate these pollutions. During the present study, the efficiency of a previously developed bioaugmentation agent combined with biostimulation was tested under field conditions in contaminated soil. Furthermore, the preservation of dechlorinating ability was also investigated in a long-term experiment. Initially, aerobic conditions were present in the groundwater with possible presence of anaerobic micro-niches providing habitat for Brocadia related anammox bacteria. “Candidatus Omnitrophus” was also identified as a dominant member of community then. Significant changes were detected after the biostimulation, anaerobic conditions established and most of the dominant OTUs were related to fermentative taxa (e.g. Clostridium, Trichococcusand Macillibacteroides). Dominant presence of vinyl-chloride coupled with the lack of vinyl-chloride reductase gene was observed. The most notable change after the bioaugmentation was the significant decrease in the pollutant quantities and the parallel increase in the vcrA gene copy numbers. Similar to post-biostimulation state, fermentative bacteria dominated the community. Bacterial community composition transformed considerably with time after the treatment, dominance of fermentative—mainly Firmicutes related—taxa decreased and chemolithotrophic bacteria became abundant, but the dechlorinating potential of the community remained and could be induced by the reappearance of the pollutants even after 4 years.
Comment on ‘Research contribution of bibliometric studies related to sustainable development goals and sustainability’ [Discover Sustainability, 2023, 5, 1, 7, 10.1007/s43621-024-00182-w]
Authors: Elango Bakthavachalam 
Published: July 2024

AbstractThis investigation discusses a comment on a recently published research study (Raman, Discov Sustain 5:7, 2024) related to Sustainable Development Goals (SDGs) and Sustainability, focusing on bibliometric analysis. The observation highlighted a computational error in the calculation of Compound Annual Growth Rate (CAGR) as presented in the original publication. A revised formula was provided, along with corrected computations, revealing a notable disparity in growth forecasts. It emphasizes the need to use appropriate formulas for growth assessments and suggests that researchers should focus on identifying and rectifying inaccuracies.
Associations of Plasma Lipidomic Profiles with Uric Acid and Hyperuricemia Risk in Middle-Aged and Elderly Chinese
Authors: Kang Wanhui , Xu Xinming , Yang Xiaowei , Wu Qingqing , Li Shuning , Gao Keran , Zeng Rong , Sun Liang , Lin Xu 
Published: July 2024

AbstractLittle is known about the links of disturbed lipid metabolism with hyperuricemia (HUA). We aimed to investigate the associations of lipidomic profiles with uric acid (UA)/HUA and their modifying factors in middle-aged and elderly Chinese. A total of 350 lipids were quantified in 2247 community-based Chinese aged 50–70 years by high-coverage targeted lipidomics. HUA was defined by plasma UA > 420 μmol/L in men or > 360 μmol/L in women. The prevalence of HUA in this population was 10.4%. After multivariable adjustment including BMI and lifestyle, 123 lipids were significantly associated with UA, predominantly glycerolipids (GLs) and glycerophospholipids (GPs). Specifically, diacylglycerol [DAG (16:0/22:5), DAG (16:0/22:6), DAG (18:1/20:5), DAG (18:1/22:6)], phosphatidylcholine [PC (16:0/20:5)), and triacylglycerol (TAG (53:0)] were the most significant lipid signatures positively associated with HUA risk, while lysophosphatidylcholine (LPC (20:2)) was inversely associated with HUA risk (p < 0.05). Network analysis also showed a positive association between TAGs/PCs/DAGs contained module and HUA risk (p < 0.01). Notably, HUA-related lipids were associated with de novo lipogenesis fatty acids, especially 16:1n-7 (Spearman correlation coefficients = 0.32–0.41, p < 0.001). Reduced rank regression showed that increased aquatic products intake was correlated to elevated HUA risk and HUA-associated lipids; while high dairy consumption was correlated with low level of HUA-associated lipids (|factor loadings| ≥ 0.2). Moreover, mediation analyses suggested that the lipid-HUA associations were partially mediated by retinol-binding protein 4 (RBP4, mediation proportion 5–14%), an adipokine linked with dyslipidemia and insulin resistance. In conclusion, disturbed specific metabolisms of GLs and GPs were associated with high prevalent HUA, partially mediated by RBP4 and/or influenced by certain dietary factors.
Students’ acceptance of e-learning: extending the technology acceptance model with self-regulated learning and affinity for technology
Authors: Barz Nathalie , Benick Manuela , Dörrenbächer-Ulrich Laura , Perels Franziska 
Published: July 2024

AbstractThe present study examines university students’ acceptance of e-learning according to the Technology Acceptance Model (TAM). We also investigate the influence of external factors, including self-efficacy with digital media, self-regulated learning, prior experience, and affinity for technology, to extend the model with valid individual factors. Structural equation modeling with maximum-likelihood estimation served to evaluate the proposed research model, which included online questionnaire data from N = 225 undergraduates studying various subjects in 53 universities. The results indicate that the TAM is replicable regarding e-learning for German-speaking university students. Additionally, we found self-regulated learning and affinity for technology to be significantly positively related to the two main components of the TAM, perceived ease of use and perceived usefulness, implying their importance in technology acceptance. However, self-efficacy with digital media and prior experience showed no significant impact on university students’ technology acceptance. We also found a significant positive relationship between attitudes toward e-learning and behavioral intention, showing that university students with positive attitudes are more willing to use it in the future. Therefore, higher education should consider students’ individual prerequisites for e-learning and support students during the use of e-learning environments, to promote the development of positive experiences and attitudes toward e-learning.