mdpi-ai/citelens huggingface dataset:
Cyberinfrastructure for machine learning applications in agriculture: experiences, analysis, and vision
Field: AI

Introduction: Advancements in machine learning (ML) algorithms that make predictions from data without being explicitly programmed and the increased computational speeds of graphics processing units (GPUs) over the last decade have led to remarkable progress in the capabilities of ML. In many fields, including agriculture, this progress has outpaced the availability of sufficiently diverse and high-quality datasets, which now serve as a limiting factor. While many agricultural use cases appear feasible with current compute resources and ML algorithms, the lack of reusable hardware and software components, referred to as cyberinfrastructure (CI), for collecting, transmitting, cleaning, labeling, and training datasets is a major hindrance toward developing solutions to address agricultural use cases. This study focuses on addressing these challenges by exploring the collection, processing, and training of ML models using a multimodal dataset and providing a vision for agriculture-focused CI to accelerate innovation in the field.Methods: Data were collected during the 2023 growing season from three agricultural research locations across Ohio. The dataset includes 1 terabyte (TB) of multimodal data, comprising Unmanned Aerial System (UAS) imagery (RGB and multispectral), as well as soil and weather sensor data. The two primary crops studied were corn and soybean, which are the state's most widely cultivated crops. The data collected and processed from this study were used to train ML models to make predictions of crop growth stage, soil moisture, and final yield.Results: The exercise of processing this dataset resulted in four CI components that can be used to provide higher accuracy predictions in the agricultural domain. These components included (1) a UAS imagery pipeline that reduced processing time and improved image quality over standard methods, (2) a tabular data pipeline that aggregated data from multiple sources and temporal resolutions and aligned it with a common temporal resolution, (3) an approach to adapting the model architecture for a vision transformer (ViT) that incorporates agricultural domain expertise, and (4) a data visualization prototype that was used to identify outliers and improve trust in the data.Discussion: Further work will be aimed at maturing the CI components and implementing them on high performance computing (HPC). There are open questions as to how CI components like these can best be leveraged to serve the needs of the agricultural community to accelerate the development of ML applications in agriculture.
The impact of artistic sports on academic self-efficacy
Field: PSYCHOLOGY

Introduction: Artistic sports have a more positive impact on adolescents on the basis of basic sports. This study delves into the beneficial effects of Artistic sports compared to basic sports in enhancing academic self-efficacy in college students, and investigates the mediating roles of mindfulness, social anxiety, and academic procrastination in this process.Methods: A questionnaire survey was conducted among students in some universities in Gansu Province, collecting a total of 1,976 online questionnaires, including 263 males and 1,713 females, with 1,543 participants in Artistic sports courses and 433 participants in basic sports. Data processing was carried out using SPSS 26.0 software and its plugin PROCESS.Results: The analysis results indicate significant differences in mindfulness, social anxiety, academic procrastination, and academic self-efficacy among different types of sports training (ps < 0.05); significant correlations were found among all variables (ps < 0.001). Sports training types can directly predict academic self-efficacy (β = 0.069, t = 3.155, p < 0.01), further confirming that sports training types can directly predict academic self-efficacy. Moreover, mindfulness, social anxiety, and academic procrastination play a chain mediating role between Artistic sports and academic self-efficacy.Discussion: These findings highlight the potential value of Artistic sports in enhancing academic self-efficacy and provide practical guidance for education policymakers, school administrators, teachers, parents, and students to promote adolescent academic and psychological health development. It is recommended to enhance the promotion and training of Artistic sports.
Gaussian process latent variable models-ANN based method for automatic features selection and dimensionality reduction for control of EMG-driven systems
Field: AI

Electromyography (EMG) signals have gained significant attention due to their potential applications in prosthetics, rehabilitation, and human-computer interfaces. However, the dimensionality of EMG signal features poses challenges in achieving accurate classification and reducing computational complexity. To overcome such issues, this paper proposes a novel approach that integrates feature reduction techniques with an artificial neural network (ANN) classifier to enhance the accuracy of high-dimensional EMG classification. This approach aims to improve the classification accuracy of EMG signals while substantially reducing computational costs, offering valuable implications for all EMG-related processes on such data. The proposed methodology involves extracting time and frequency domain features from twelve channels of EMG signals, followed by dimensionality reduction using techniques such as PCA, LDA, PPCA, Lasso and GPLVM, and classification using an ANN. Our investigation revealed that LDA is not appropriate for this dataset. The dimensionality reduction models did not have any significant effect on the accuracy, but the computational cost decreased significantly. In individual comparisons, GPLVM had the shortest computational time (29 s), which was significantly less than that of all the other models (p < 0.05), with PCA following at approximately 35 s and Relief at approximately 57 s, while PPCA took approximately 69 s, and Lasso exhibited higher computational costs than all the models but lower computational costs than did the original set. Using the best-performing features, all possible sets of 2, 3, 4 and 5 features were tested, and the 5-feature set exhibited the best performance. This research demonstrates the effectiveness of dimensionality reduction and feature selection in improving the accuracy of movement recognition in myoelectric control.
Application of human-in-the-loop hybrid augmented intelligence approach in security inspection system
Field: AI

A security inspection system exemplifies human-machine collaboration, and enhancing its safety and reliability through advanced technology remains a key research priority. While deep learning has incrementally improved the autonomous capabilities of security inspection equipment for automatic contraband detection, a gap persists between current technological capabilities and practical implementation. Recognizing that humans excel at learning, reasoning, and collaborating, while artificial intelligence offers normative, repeatable, and logical processing, we propose a human-in-the-loop hybrid augmented intelligence approach. This approach addresses the practical needs of security inspection systems by introducing a hybrid decision-making method that leverages two distinct strategies: “Reject-priority” and “Clear-priority.” These strategies play complementary roles in bolstering the decision-making process’s overall performance. Comparative experiments on a dataset from a specific security inspection site confirmed the hybrid method’s effectiveness, drawing several conclusions. This “Hybrid decision-making” method not only enhances risk perception, thereby widening the safety margin of the security inspection system, but also reduces the need for human labor, leading to increased efficiency and reduced labor costs. Additionally, it is less time-consuming, further improving the system’s overall efficiency. By integrating human and machine intelligence, this method significantly boosts decision-making effectiveness. Tailored to their unique characteristics, the method based on “Reject-priority” strategy is particularly well-suited for security inspection scenarios that demand stringent safety protocols, while the “Clear-priority” method is ideal for scenarios with high-volume traffic flow, where efficiency is paramount. As the volume of collected data grows, this approach will enable seamless adaptation of the method to evolving application needs.
The role of cGAS-STING pathway in the development of radiation-induced lung injury
Field: ONCOLOGY

Background and purpose Radiation-induced lung injury (RILI) limits the efficacy of thoracic radiotherapy. However, the underlying mechanism of RILI remains unclear. cGAS-STING pathway is reported to be involved in the recognization of cytosolic dsDNA and various inflammatory diseases. This study aimed to investigate the role of cGAS-STING pathway in the development of RILI. Materials and methods A pre-clinical mouse model of RILI was established by whole thorax irradiation and confirmed using H&E and Masson’s trichrome staining. STING agonist (DMXAA) and antagonist(C-176) were administrated to modulate cGAS-STING pathway in vivo. Western blot and ELISA were used to determine the expression levels of different proteins. Results Quantitation analysis showed dsDNA accumulation in lung tissue and western blot showed the up-regulation of cGAS and STING protein level post-irradiation, indicating pathway activation. Histological evaluation showed that C-176 administration ameliorated radiation-induced pulmonary inflammation and fibrosis, while DMXAA exhibited contrary effects. In further in vitro study, the release of dsDNA induced by radiation led to the activation of cGAS-STING pathway in RAW 264.7 cells, resulting in the polarization into M1 phenotype and pro-inflammatory production. Conclusion In summary, our data demonstrated a link between cGAS-STING pathway and the development of RILI, indicating its potential application in clinic.
Enhancing Africa’s agriculture and food systems through responsible and gender inclusive AI innovation: insights from AI4AFS network
Field: AI

The integration of artificial intelligence (AI) technologies into agriculture holds urgent and transformative potential for enhancing food security across Sub-Saharan Africa (SSA), a region acutely impacted by climate change and resource constraints. This paper examines experiences from the Artificial Intelligence for Agriculture and Food Systems (AI4AFS) Innovation Research Network, which provided funding to innovative projects in eight SSA countries. Through a set of case studies, we explore AI-driven solutions for pest and disease detection across crops such as cashew, maize, tomato, and cassava, including a real-time health monitoring tool for Nsukka Yellow pepper. Using participatory design, and key informant interview, robust monitoring and evaluation, and incorporating ethical frameworks, the research prioritizes gender equality, social inclusion, and environmental sustainability in AI development and deployment. Our results demonstrate that responsible AI practices can significantly enhance agricultural productivity while maintaining low carbon footprints. This research offers a unique, localized perspective on AI’s role in addressing SSA’s agricultural challenges, with implications for global food security as demand rises and environmental resources shrink. Key recommendations include establishing robust policy frameworks, strengthening capacity-building efforts, and securing sustainable funding mechanisms to support long-term AI adoption. This work provides the global community, policymakers, and stakeholders with critical insights on establishing ethical, responsible, and inclusive AI practices that can be adapted to similar agricultural contexts worldwide, contributing to sustainable food systems on an international scale.
Spatial and social relevance perceptions by pre-service teachers of learning about oil palm management as a local or nonlocal socioscientific issue
Field: EDUCATION

Introduction: Pre-service teachers (PST)' perceived relevance of learning about environmental socioscientific issues (SSI) can be an indicator for their motivation to act as change agents. Until now, science education (research) has often addressed the relevance for learning about SSI insufficiently differentiated regarding spatial and social dimensions. However, theoretical frameworks suggest that such differentiation enhances meaningful teaching and learning. This study investigated how local, national, and global subdimensions of spatial relevance as well as individual, societal, and professional subdimensions of social relevance influence PST' relevance perceptions of learning about SSI. Additionally, we examined how relevance perceptions vary depending on whether the SSI is local or nonlocal to PST. We specifically investigated Indonesian PST' relevance perceptions of learning about oil palm management (OPM), a local SSI for PST of one university and a nonlocal SSI for PST of two other universities.Methods: The PST participated in a 5-week socioscientific inquiry-based educational unit on OPM in curricular courses (N = 111). We followed a mixed-method approach, employing measurements of utility value. Utility value is a specific construct of perceived relevance, which refers to the usefulness of learning about objects for a person's life, profession, and society. Quantitatively, we conducted pretest-posttest-follow-up surveys on PST' perceived utility value for learning about OPM over time. Qualitatively, we analyzed responses to a utility value reflection task that was integrated into the unit.Results: Overall, the unit increased PST' utility value over time. Local PST perceived lower utility value for learning about OPM than nonlocal PST. In the task responses, local PST referred more to the local subdimension, whereas nonlocal PST referred more to the national subdimension. Nonlocal PST' societal and professional utility value increased stronger over time compared to local PST.Discussion: We discuss potential reasons for local PST' lower relevance perceptions, e.g., personal experiences and skepticism through local embeddedness. Our findings on relevance perceptions among local and nonlocal PST underscore the importance of spatial- and social-sensitive SSI education. We point out practical implications for promoting relevance perceptions considering local and nonlocal PST. Moreover, we suggest research directions for more differentiated relevance research in science education.
Acceptance of sexual attraction and its link to psychological distress and sexual offending among pedohebephilic clients: results from a preliminary analysis
Field: PSYCHOLOGY

Introduction: Pedohebephilic disorder is characterized by intense sexual urges or fantasies involving children, which can lead to distress or sexual behavior with children. While theoretical and qualitative accounts suggest that accepting one’s pedohebephilic sexual interests may help mitigate both distress and problematic behaviors, the only published quantitative study to date has linked acceptance with behavior but did not analyze its effect on distress.Methods: We examined the relationship between acceptance of sexual interests and child sexual abuse (CSA), the use of child sexual exploitation material (CSEM), and psychological distress in 238 pedohebephilic and teleiophilic men outside the judicial system (i.e., in the “Dunkelfeld”).Results: Compared to teleiophilic individuals, pedohebephilic individuals showed lower acceptance of their sexual interests. No significant differences were found between groups regarding past sexual offending. In a subsample of 197 pedohebephilic individuals (n = 197), correlations with recent sexual behavior were minimal. In another subsample of pedohebephilic men (n = 84) with data on psychological distress, increased acceptance was associated with decreased psychological distress, although this association weakened among those reporting recent offenses.Discussion: Acceptance of one’s sexual interests is associated with reduced distress in pedohebephilic disorder among non-offending individuals. However, its role among offending individuals remains unclear. Efforts to improve measuring the acceptance of one’s sexual interests and further explore its role in pedohebephilic disorder are warranted.
Clinical analysis of different intestinal reconstruction methods after primary cytoreductive surgery combined with rectal resection for advanced ovarian cancer
Field: ONCOLOGY

Objective: To compare different intestinal reconstruction methods after intestinal resection for advanced ovarian malignancy.Methods: Retrospective data of patients with advanced ovarian malignancy were collected and then assigned into three groups: primary intestinal anastomosis, protective enterostomy and colostomy. General clinical characteristics, intraoperative findings and postoperative outcomes were compared between the three groups.Results: A total of 530 cases were included for final analysis. The colostomy group had a lower serum albumin level, larger volume of ascites, higher likelihood of multiple intestinal resections and lower likelihood of rectal resection, lower peritoneal cancer index, more intraoperative blood loss, transfusions and infusions, lower likelihood of optimal cytoreductive surgery and shorter interval time to chemotherapy than the other two groups (p < 0.05). The primary intestinal anastomosis group exhibited a larger blood transfusion volume, higher incidence rates of anastomotic leak and electrolyte disturbance, and longer times to first flatus, first feeding and drain removal than the other two groups (p < 0.05).Conclusions: Colostomy can be adopted for advanced ovarian cancer patients with a large ascites volume, hypoproteinemia, large intraoperative blood and fluid loss volumes, multiple intestinal resections, anastomoses located below the peritoneal reflection, high PCI and suboptimal cytoreductive surgery. For patients with good intraoperative and postoperative outcomes, one anastomosis, an anastomosis located above the peritoneal reflection, low PCI or optimal cytoreductive surgery, intestinal anastomosis can be carried out to restore the normal physiological function of the intestine. For patients with a large volume of ascites (≥500 mL), multiple anastomoses or an anastomosis located below the peritoneal reflection, intestinal anastomosis combined with protective enterostomy has an advantage over intestinal anastomosis alone.
Bibliometric analysis of liposarcomas treatment from 2004 to 2023
Field: ONCOLOGY

Background Liposarcomas are mesenchymal malignant tumors characterized by varying degrees of adipocytic differentiation that comprises approximately 20% of soft tissue sarcomas. Despite advancements in this field, there remains a need for a comprehensive understanding of the mechanisms, diagnosis, and treatment of liposarcomas. Currently, there is a lack of bibliometric surveys on the development trajectory of liposarcomas treatment, research hotspots, and author and team collaboration. Methods In this study, we obtained publications from the Web of Science database from 2004 to 2023, with a specific focus on the treatment of liposarcomas. By utilizing bibliometric methods, the data were processed to facilitate visual analysis of various aspects, including authors, countries, institutions, cocitations, keywords, references, and gene characteristics. Results The number of publications on liposarcomas treatment has increased over the past two decades, from 39 in 2004 to 232 in 2023, with the United States of America contributing the most publications. Among the institutions, the Memorial Sloan Kettering Cancer Center had the highest volume of 87 publications. Notably, Alessandro Gronchi published 63 articles on the treatment of liposarcomas in the last 20 years. Cancers is the journal with the highest number of 57 publications. High-frequency keywords in these publications included “soft tissue sarcoma”, “liposarcoma”, “retroperitoneal sarcoma”, “surgery”, “dedifferentiated liposarcoma”, “trabectedin” and “radiotherapy”. Recent trends, identified through strong citation bursts from 2020 to 2023, include next-generation sequencing, radiotherapy, and patient-derived cell lines. High-frequency genes in the liposarcomas treatment field include TP53, MDM2, CDK4, DDIT3, and CD274. Conclusions The treatment of liposarcomas has garnered increasing attention worldwide in the last 20 years. The treatment approach has shifted from surgical resection to multidisciplinary therapy. The molecular and biological characteristics of different tumor subtypes have attracted more research attention, providing an important reference for the choice of treatment. The findings of this study contribute to providing a comprehensive understanding of liposarcomas treatment among researchers. Moreover, they offer valuable perspectives that can guide future research.
Psychometric properties of the Chinese version of the body image life disengagement questionnaire in a sample of adolescents
Field: PSYCHOLOGY

The negative consequences of body image concerns manifest in ways such as negative emotional experiences, eating disorders, and problems with social life. The Body Image Life Disengagement Questionnaire (BILD-Q) is an instrument for assessing the impact of body image concerns specifically on adolescents’ life disengagement. The objective of this study is to create a Chinese version of the BILD-Q and assess its validity and reliability with Chinese adolescents. A total of 593 adolescents were recruited, of whom 316 (Sample 1) completed only the BILD-Q and 277 (Sample 2) completed the BILD-Q, Eating Attitudes Test (EAT), and Body Appreciation Scale-2 (BAS-2). Data from Sample 1 were used for the item analysis, exploratory factor analysis (EFA), and test-retest reliability, while data from Sample 2 were used for the BILD-Q’s confirmatory factor analysis (CFA) and associations of BILD-Q with EAT and BAS-2. Both samples were used together for calculating descriptive statistics, measurement invariance, and internal consistency. EFA and CFA were used to verify the single-factor structure of the BILD-Q. Measurement invariance across genders was verified by multi-group CFA. The reliability of the instrument was verified using Cronbach’s alpha and the intraclass correlation coefficient (ICC). Finally, the convergent validity of the instrument was verified by correlating the BILD-Q scores with the EAT and BAS-2 scores. The results support a single-factor structure for the Chinese version of the BILD-Q, with good reliability (Cronbach’s alpha = 0.888, ICC value = 0.759). Gender invariance was established: no significant differences were found in BILD-Q scores between the male and female groups. Life disengagement was positively correlated with eating disorder psychopathology and negatively correlated with body appreciation, supporting the convergent validity of the BILD-Q. The Chinese version of the BILD-Q has strong psychometric properties when used with Chinese adolescents and can be used to assess the impact of body image concerns on their life disengagement.