bluuebunny/crossref_metadata_2025 huggingface dataset:
Digitally Assisted Mindfulness in Training Self-Regulation Skills for Sustainable Mental Health: A Systematic Review
Authors: Mitsea Eleni , Drigas Athanasios , Skianis Charalabos
Published: December 2023

The onset of the COVID-19 pandemic has led to an increased demand for mental health interventions, with a special focus on digitally assisted ones. Self-regulation describes a set of meta-skills that enable one to take control over his/her mental health and it is recognized as a vital indicator of well-being. Mindfulness training is a promising training strategy for promoting self-regulation, behavioral change, and mental well-being. A growing body of research outlines that smart technologies are ready to revolutionize the way mental health training programs take place. Artificial intelligence (AI); extended reality (XR) including virtual reality (VR), augmented reality (AR), and mixed reality (MR); as well as the advancements in brain computer interfaces (BCIs) are ready to transform these mental health training programs. Mindfulness-based interventions assisted by smart technologies for mental, emotional, and behavioral regulation seem to be a crucial yet under-investigated issue. The current systematic review paper aims to explore whether and how smart technologies can assist mindfulness training for the development of self-regulation skills among people at risk of mental health issues as well as populations with various clinical characteristics. The PRISMA 2020 methodology was utilized to respond to the objectives and research questions using a total of sixty-six experimental studies that met the inclusion criteria. The results showed that digitally assisted mindfulness interventions supported by smart technologies, including AI-based applications, chatbots, virtual coaches, immersive technologies, and brain-sensing headbands, can effectively assist trainees in developing a wide range of cognitive, emotional, and behavioral self-regulation skills, leading to a greater satisfaction of their psychological needs, and thus mental wellness. These results may provide positive feedback for developing smarter and more inclusive training environments, with a special focus on people with special training needs or disabilities.
The Impact of Mindful Learning on Subjective and Psychological Well-Being in Postgraduate Students
Authors: Wang Qing , Zhang Yuanyuan , Zhang Ying , Chen Tingwei
Published: December 2023

Mindful learning is widely known to improve learning outcomes, yet its association with students’ well-being remains unexplored. This study aimed to investigate the impact of mindful learning on subjective well-being (SWB) and psychological well-being (PWB) in postgraduate students, using survey questionnaires and a randomized experimental design. In Study 1, correlation and regression analyses based on 236 postgraduate students revealed significant positive associations among mindful learning, SWB, and PWB. In Study 2, 54 students were randomly assigned to three groups: the experimental (which received Mindful Learning Coaching), active-, and blank control groups. The results from repeated-measures ANOVA showed that coaching significantly improved students’ mindful learning. The participants’ SWB and PWB significantly decreased in both the active- and blank control groups, whilst their SWB and PWB tended to increase in the experimental group. In conclusion, mindful learning, SWB, and PWB are significantly correlated, while the enhancement of mindful learning may be a protective factor in students’ well-being.
The Numerical Simulation Study of Pumping Airflow Driven by Wind Pressure for Single- and Multi-Room Buildings
Authors: Qiu Xinpeng , Zhou Junli , Xiao Xue , Zhu Wenjun , Zhang Jiaji , Gui Shuqiang , Peng Yangdong
Published: December 2023

Pumping airflow occurs in single-sided natural ventilation buildings when the openings are located on the leeward side; the direction of airflow through the building then changes periodicity. In order to propose a calculation method of the ventilation rates for single-room buildings and analyze the pumping ventilation for multi-room buildings, the CFD method with an SST k-ω turbulence model was used to conduct numerical simulation in this study, which is verified by other experimental results. Firstly, the qualitative and quantitative characteristics of pumping ventilation were investigated for a single-room building with two openings. The results show that the steady-state method underestimates the ventilation flow rates, and the unsteady-state method captures the microstructures of the flow better. Secondly, the vortex-shedding and indoor airflow oscillation frequencies were analyzed based on transient simulation for a single-room building. It was found that both of them increase with air speed. Then, the factors affecting ventilation flow rates were analyzed. A calculation method for dimensionless ventilation rates is proposed. Finally, the pumping ventilation for a multi-room building was numerically simulated. The ventilation rate for a middle room is greater than that for a corner room, and the ventilation rate for any room in a multi-room building is greater than the single-room building given the same room size and the same incoming wind speed. The findings of this paper are helpful for the design and evaluation of natural ventilation.
Exploring the Dynamic Cultural Driving Factors Underlying the Regional Spatial Pattern of Chinese Traditional Villages
Authors: Nie Zhongyi , Chen Chen , Pan Wei , Dong Tian
Published: December 2023

In the context of global urbanization, traditional villages have garnered increasing scholarly interest due to their role in preserving rich ethnic cultures and their potential contributions to cultural heritage. Existing literature has predominantly attributed the spatial heterogeneity of traditional villages to natural, environmental, and economic factors. However, cultural elements, which are equally crucial to the inheritance and continuation of traditional villages, are rather deficient in current research. By establishing a tripartite framework encompassing “natural environment—space economy—social culture” elements, this article first employs relevant geographic spatial analysis to examine the overall distribution patterns of Chinese traditional villages. Subsequently, it utilizes the Optimal Parameter-based GeoDetector model to assess the maximum impact of single factors and interactions among factors on the spatial heterogeneity of Chinese traditional villages. The paper then integrates spatial production theory to reveal the mechanisms underlying the interactions among these tripartite elements. The research findings indicate that cultural factors exert the most substantial influence on the spatial distribution of traditional Chinese villages, in contrast to previous research records that suggested natural elements had the greatest impact. Additionally, population and genealogy emerge as the two most critical factors, with their interaction having the most significant effect on the spatial pattern of Chinese traditional villages (q = 0.82663). Finally, we put forward regional-level recommendations for the preservation of traditional villages. Overall, our work can not only provide valuable insights for global research on traditional villages in developing countries based on traditional agriculture but also offer recommendations for the preservation of traditional villages in China.
Vulnerability Assessment of Prefabricated Component Suppliers in Prefabricated Buildings Based on the Controlled Interval and Memory Method Extended under the Probability Language Terminology Set
Authors: Wang Xinyu , Peng Hao , Wu Han , He Zhi
Published: December 2023

Accurately evaluating the vulnerability of prefabricated components in prefabricated buildings is the basis of scientific management of its supply chain. Thus, a novel vulnerability evaluation method for the suppliers of prefabricated components in the context of prefabricated buildings was proposed in this study. First, a vulnerability evaluation index system was identified and constructed by the pressure–state–response (PSR) model. With the clear logic and strong applicability of PSR, this system, including 18 indexes, was easy to understand and exhibited strong practicability. The weights were then determined via the multiplicative analytic hierarchy process with the expansion of a probabilistic language terminology set (PLTS). PLTS could describe decision information more comprehensively, so the evaluation result is more scientific. Subsequently, the probability of the vulnerability level was superimposed in a parallel bottom-to-top method via the controlled interval and memory (CIM) models, and these were extended by the PLTS. This set handled the uncertain information in the decision-making process more efficiently and accurately, and finally determined the vulnerability distribution. Ultimately, the probability of each vulnerability level was determined by combining the weight information. The reconstruction and resettlement housing construction project of urban shanty towns in the Taohua South Road Community in Xihu District, Nanchang City, was selected as a case study. The case study proves the effectiveness of this method, which has higher resolution and is more convenient for managers to make decisions.
Visible-Light-Driven BiOBr-TiO2-Attapulgite Photocatalyst with Excellent Photocatalytic Activity for Multiple Xanthates
Authors: Qi Yaozhong , Zhao Sikai , Jiang Xiaoyu , Kang Zhangke , Gao Shuling , Liu Wengang , Shen Yanbai
Published: December 2023

The novel ternary composites BiOBr-TiO2-attapulgite (BTA) were synthesized using a simple hydrothermal and water-bath method, exhibiting excellent photocatalytic performance to multiple xanthates. For the BTA photocatalyst, TiO2 and BiOBr were uniformly loaded onto the surface of acid-activated attapulgite. As a widely used collector in mining processes, sodium ethyl-xanthate (SEX) was selected as the target pollutant due to its high toxicity. The BTA ternary photocatalyst demonstrated significantly higher adsorption and photocatalytic degradation performance compared to TiO2 nanoparticles, BiOBr nanosheets, and BiOBr-TiO2 heterojunction. Structural characterization and experimental results indicated that the exceptional photocatalytic degradation efficiency of BTA was mainly attributed to the formation of a heterojunction between BiOBr and TiO2, as well as the presence of additional active adsorption sites provided by attapulgite. Free radical scavenging experiments and EPR results confirmed that the photogenerated holes were the predominant active species in photodegrading SEX throughout the entire experiment. The LC-MS results provided insight into potential degradation pathways of SEX. This research demonstrates that BTA, as a novel triple composite material, achieves rapid and complete degradation to 20 mg/L SEX within 20 min. This work presents a novel approach to synthesize mineral-based photocatalysts, which have broad prospects for application in flotation wastewater treatment.
Navigating Challenges and Advances in Pediatric Psoriasis and Atopic Dermatitis Treatment
Authors: Lovell Katie K. , Strowd Lindsay C. , Feldman Steven R.
Published: December 2023

The contents of this Special Issue provide a broad overview of the current landscape of psoriasis and atopic dermatitis (AD) treatment in pediatric populations, highlighting the challenges and recent advances [...]
Shear-Enhanced Compaction Analysis of the Vaca Muerta Formation
Authors: Hasbani José G. , Kias Evan M. C. , Suarez-Rivera Roberto , Calo Victor M.
Published: December 2023

The laboratory measurements conducted on Vaca Muerta formation samples demonstrate stress-dependent elastic behavior and compaction under representative in situ conditions. The experimental results reveal that the analyzed samples display elastoplastic deformation and shear-enhanced compaction as primary plasticity mechanisms. These experimental findings contradict the expected linear elastic response anticipated before brittle failure, as reported in several studies on the geomechanical characterization of the Vaca Muerta formation. Therefore, we present a comprehensive laboratory analysis of Vaca Muerta formation samples showing their nonlinear elastic behavior and irrecoverable shear-enhanced compaction. Additionally, we calibrate an elastoplastic constitutive model based on these experimental observations. The resulting model accurately reproduces the observed phenomena, playing a pivotal role in geoengineering applications within the energy industry.
The Role of Multimodality Imaging in Patients with Congenital Heart Disease and Infective Endocarditis
Authors: Moscatelli Sara , Leo Isabella , Bianco Francesco , Surkova Elena , Pezel Théo , Donald Natasha Alexandra , Triumbari Elizabeth Katherine Anna , Bassareo Pier Paolo , Pradhan Akshyaya , Cimini Andrea , Perrone Marco Alfonso
Published: December 2023

Infective endocarditis (IE) represents an important medical challenge, particularly in patients with congenital heart diseases (CHD). Its early and accurate diagnosis is crucial for effective management to improve patient outcomes. Multimodality imaging is emerging as a powerful tool in the diagnosis and management of IE in CHD patients, offering a comprehensive and integrated approach that enhances diagnostic accuracy and guides therapeutic strategies. This review illustrates the utilities of each single multimodality imaging, including transthoracic and transoesophageal echocardiography, cardiac computed tomography (CCT), cardiovascular magnetic resonance imaging (CMR), and nuclear imaging modalities, in the diagnosis of IE in CHD patients. These imaging techniques provide crucial information about valvular and intracardiac structures, vegetation size and location, abscess formation, and associated complications, helping clinicians make timely and informed decisions. However, each one does have limitations that influence its applicability.
Evaluation of a Point-of-Need Molecular Diagnostic Tool Coupled with Rapid DNA Extraction Methods for Visceral Leishmaniasis
Authors: Ghosh Prakash , Chowdhury Rajashree , Faisal Khaledul , Khan Md. Anik Ashfaq , Hossain Faria , Rahat Md. Abu , Chowdhury Md. Arko Ayon , Mithila Nishad Tasnim , Kamal Mostafa , Maruf Shomik , Nath Rupen , Kobialka Rea Maja , Ceruti Arianna , Cameron Mary , Duthie Malcolm S. , Wahed Ahmed Abd El , Mondal Dinesh
Published: December 2023

A rapid, cost-effective, and simple nucleic acid isolation technique coupled with a point-of-need DNA amplification assay is a desirable goal for programmatic use. For diagnosis of Visceral Leishmaniasis (VL), Recombinase Polymerase Amplification (RPA) rapid tests for the detection of Leishmania DNA are versatile and have operational advantages over qPCR. To facilitate the delivery of the RPA test at point-of-need for VL diagnosis, we compared two rapid DNA extraction methods, SwiftDx (SX) and an in-house Boil and Spin (BS) method, coupled with RPA amplification, versus more widely used methods for DNA extraction and amplification, namely Qiagen (Q) kits and qPCR, respectively. A total of 50 confirmed VL patients and 50 controls, matched for age and gender, were recruited from Mymensingh, Bangladesh, a region highly endemic for VL. Blood samples were collected from each participant and DNA was extracted using Q, SX and BS methods. Following DNA extraction, qPCR and RPA assays were performed to detect L. donovani in downstream analysis. No significant differences in sensitivity of the RPA assay were observed between DNA extraction methods, 94.00% (95% CI: 83.45–98.75%), 90% (95% CI: 78.19–96.67%), and 88% (95% CI: 75.69–95.47%) when using Q, SX, and BS, respectively. Similarly, using qPCR, no significant differences in sensitivity were obtained when using Q or SX for DNA extraction, 94.00% (95% CI: 83.45–98.75%) and 92.00% (80.77–97.78%), respectively. It is encouraging that RPA and qPCR showed excellent agreement (k: 0.919–0.980) when different extraction methods were used and that the DNA impurities using BS had no inhibitory effect on the RPA assay. Furthermore, significantly higher DNA yields were obtained using SX and BS versus Q; however, a significantly higher parasite load was detected using qPCR when DNA was extracted using Q versus SX. Considering the cost, execution time, feasibility, and performance of RPA assay, rapid extraction methods such as the Boil and Spin technique appear to have the potential for implementation in resource-limited endemic settings. Further clinical research is warranted prior to broader application.
Multivessel Coronary Artery Dissection in a Patient with Co-Occurrence of Aortic Dissection and Dilated Cardiomyopathy in the Postpartum Period
Authors: Kurihara Takahiro , Amiya Eisuke , Hatano Masaru , Ishida Junichi , Minatsuki Shun , Inoue Shunsuke , Nomura Seitaro , Morita Hiroyuki , Komuro Issei
Published: December 2023

The co-occurrence of dilated cardiomyopathy (DCM) and aortic dissection has been rarely reported. Here, we present the case of a patient with co-occurrence of DCM and aortic dissection, wherein multivessel coronary artery dissection eventually occurred, thereby leading to advanced heart failure. She suffered from co-occurrence of DCM and aortic dissection 6 years ago. After the heart failure had briefly stabilized, the myocardial infarction due to coronary artery dissection led to worsening mitral regurgitation and decreased right ventricular function, thereby worsening the status of her heart failure. In addition to cardiovascular abnormalities, the patient was also complicated by short stature (145 cm), mild scoliosis, nonfunctioning pituitary adenoma of 1 cm in size, and retinitis pigmentosa. Coronary artery dissection is a possible complication in patients with co-occurrence of DCM and aortopathy, which could dramatically affect the clinical course of advanced heart failure.
Graphene-Based Coatings for Surface Modification and Their Applications in Fixed Orthodontics: A Scoping Review
Authors: Garrocho-Rangel Arturo , Flores-Arriaga Juan Carlos , Zamora-Soberón Cristina , Martínez-Zumarán Alan , Ruiz-Rodríguez Socorro , Pozos-Guillén Amaury
Published: December 2023

Background: Surface coating technology can assist fixed appliances by reducing friction, improving antibacterial characteristics, and increasing corrosion resistance. The application of functional coatings composed of graphene onto the surfaces of orthodontic brackets and archwires has been shown to enhance their mechanical qualities. The objective of the current study was to carry out a scoping analysis of published recent evidence on the utilization of graphene as a covering material in metallic orthodontic accessories, such as brackets and archwires; Methods: A scoping review was undertaken following the PRISMA-ScR guidelines. PubMed, Embase, the Cochrane Library, Dentistry and Oral Science Source, and Google Scholar were searched between 2003 and 2023; Results: In total, 38 potential references were detected, from which 10 were selected for this review. These articles addressed the benefits of the application of graphene-oxide functional coatings onto the surface of archwires and brackets during fixed orthodontic treatment. Orthodontic graphene-oxide-based coatings provide improved surface characteristics (e.g., reduced friction and anticorrosive effects), antibacterial capabilities, and biocompatibility. These characteristics can increase the effectiveness of orthodontic therapy, improve patient comfort, and lower the likelihood of problems; Conclusion: Orthodontists should be aware of and comprehend the prerequisites for using graphene-oxide-coated archwires and brackets to fulfill needs throughout their clinical practice.
An Attention-Based Odometry Framework for Multisensory Unmanned Ground Vehicles (UGVs)
Authors: Xiao Zhiyao , Zhang Guobao
Published: December 2023

Recently, deep learning methods and multisensory fusion have been applied to address odometry challenges in unmanned ground vehicles (UGVs). In this paper, we propose an end-to-end visual-lidar-inertial odometry framework to enhance the accuracy of pose estimation. Grayscale images, 3D point clouds, and inertial data are used as inputs to overcome the limitations of a single sensor. Convolutional neural network (CNN) and recurrent neural network (RNN) are employed as encoders for different sensor modalities. In contrast to previous multisensory odometry methods, our framework introduces a novel attention-based fusion module that remaps feature vectors to adapt to various scenes. Evaluations on the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago (KITTI) odometry benchmark demonstrate the effectiveness of our framework.
Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks
Authors: Li Hanpeng , Mao Kai , Ye Xuchao , Zhang Taotao , Zhu Qiuming , Wang Manxi , Ge Yurao , Li Hangang , Ali Farman
Published: December 2023

Unmanned aerial vehicles (UAVs) have found expanding utilization in smart agriculture. Path loss (PL) is of significant importance in the link budget of UAV-aided air-to-ground (A2G) communications. This paper proposes a machine-learning-based PL model for A2G communication in agricultural scenarios. On this basis, a double-weight neurons-based artificial neural network (DWN-ANN) is proposed, which can strike a fine equilibrium between the amount of measurement data and the accuracy of predictions by using ray tracing (RT) simulation data for pre-training and measurement data for optimization training. Moreover, an RT pre-correction module is introduced into the DWN-ANN to optimize the impact of varying farmland materials on the accuracy of RT simulation, thereby improving the accuracy of RT simulation data. Finally, channel measurement campaigns are carried out over a farmland area at 3.6 GHz, and the measurement data are used for the training and validation of the proposed DWN-ANN. The prediction results of the proposed PL model demonstrate a fine concordance with the measurement data and are better than the traditional empirical models.
Accounting Lecture Quality Factors during Online Learning: Student Perceptions
Authors: Abdullahu Safet , Vokshi Nexhmie Berisha
Published: December 2023

This research aimed to identify and understand the key factors influencing the effectiveness of online learning, with a specific focus on accounting courses. To achieve this goal, the study relied on the assessments and perceptions of students in the accounting department engaged in online learning. This study provided a model example to uncover the key factors and connections between the quality of online learning and its advantages in accounting education. The research was organized into three main phases: initially presenting the research concept, defining the goals and the essential components of the study. Subsequently, the research continued with a review of the literature, integrating scientific contributions from around the world and linking them to the research hypotheses. The research revealed three key factors in the quality of online learning: Factor 1, Access and communication between students and professors in online learning, emphasizing the importance of interaction and accessibility in this context; Factor 2, The security of platforms and the content of electronic learning, identifying the significance of technology safety and content security; and Factor 3, The ease of use and flexibility of access in online learning, improving student autonomy and global access to content. Hypothesis 1 confirmed that the factors of online learning quality were influenced by the context and the structure of online learning, including specific requirements. Hypothesis 2 asserted that the advantages of online learning were linked to the acceptability of electronic assistance, self-efficiency, and students’ intention to use electronic learning. Hypothesis 3 confirmed that quality factors had a strong correlation with the advantages of online learning in the field of accounting. This research, through student feedback and perspectives, contributed to a deeper understanding of online learning and the importance of quality factors in promoting it in the accounting field. In summary, this research highlights the crucial link between quality attributes and the benefits of online learning in accounting education. It is recommended that educators and institutions prioritize these attributes to enhance the effectiveness of online education, offering valuable insights for the development of more efficient and advantageous online learning environments.
Do Mental Health Symptoms during the Pandemic Predict University Non-Completion in a Sample of UK Students? A Prospective Study
Authors: Chandler Laura , McEnery Katharine A. M. , Toro Carla , Singh Swaran P. , Meyer Caroline , Tang Nicole K. Y.
Published: December 2023

Mental health symptoms are highly prevalent in university students and have been further exacerbated following the COVID-19 pandemic. The aim of this study was to examine the prospective prediction of five mental health symptoms (anxiety, depression, insomnia, suicidality, substance misuse risk) on university non-completion. Baseline data were collected between July and September 2020 following the first UK lockdown and prior to the 2020/2021 academic year. Univariate binary logistic regression analyses were performed using data from 147 participants who were due to graduate at the end of the 2020/2021 academic year. Only substance misuse risk was found to predict university non-completion, with students with a higher risk of substance misuse more likely to not complete their university course. There appears to be an association between substance misuse risk and university non-completion; however, this was attenuated once study characteristic covariates (study level, changes in study hours and study engagement) were included, indicating possible associations between these variables. Future research should further consider the role of substance use in this population and the relationship with study characteristics, engagement and university completion.
The Head Coach as a Coach Developer: A Coach Education Case Study inside a World Champion Futsal Team
Authors: Ramos Ana Gracinda , Valério Carla , Mesquita Isabel
Published: December 2023

As teacher education, coach education is also a continuous and unfinished path by nature. This study explored how the head-coach (HC) of a world champion futsal team worked as a coach developer of their assistant-coaches (AC). Specifically, the main pedagogical strategies used, how they were applied, and impacted on the perceived professional development of their staff members were investigated. An interpretative case-study was adopted since it enables an in-depth investigation of the complexity and uniqueness of this particular technical staff in educational context. Participants included four experienced coaches, one HC and three ACs. Data was gathered through semi-structured interview method and analyzed by thematic analysis. Findings highlighted an intentional structuration of sequence and timings of the pedagogical tasks and activities assigned by the HC to ACs. Evidence emphasized the (i) vision of mistakes as learning opportunities, (ii) fostering commitment of ACs to enhance team performance, and (iii) space to plan and lead in practical contexts as the main strategies adopted by the HC, who also considered reflective skills as a paramount competency and pedagogical strategy in coach education. From ACs’ perspective, these strategies largely impacted their personal and professional growth. Findings could guide the re-design of future coach education programs.
A High-Efficiency Single-Stage Isolated Sepic-Flyback AC–DC Led Driver
Authors: Gürçam Kenan , Almalı Mehmet Nuri
Published: December 2023

Regulating LED current and voltage is critical to maintaining a constant luminous flux in AC- or DC-powered LED lighting circuits. Today, users require constant current drivers that can provide a wide range of output voltages to drive different numbers of series-connected LED arrays. This work proposes an LED driver by combining an isolated SEPIC converter operating in the continuous conduction mode (CCM) and a modified Vienna rectifier. The proposed LED driver offers a single-switch control structure by adding a Vienna rectifier to the integrated SEPIC-FLYBACK converter. This driver structure provides many advantages over traditional bridge rectifier structures. The prototype circuit was tested in an 18 W continuous current mode (CCM) to verify its feasibility. As a result of the values obtained from both simulation and prototype circuit models, it has been shown to provide many of the following advantages: 95% high efficiency, high reliability, 4% low total harmonic distortion, 97% high power factor, and 70 V low switching voltage. This work meets class C 3-2 and IEC 61000 standards.
Tracing the Influence of Large Language Models across the Most Impactful Scientific Works
Authors: Petroșanu Dana-Mihaela , Pîrjan Alexandru , Tăbușcă Alexandru
Published: December 2023

In recent years, large language models (LLMs) have come into view as one of the most transformative developments in the technical domain, influencing diverse sectors ranging from natural language processing (NLP) to creative arts. Their rise signifies an unprecedented convergence of computational prowess, sophisticated algorithms, and expansive datasets, pushing the boundaries of what was once thought to be achievable. Such a profound impact mandates a thorough exploration of the LLMs’ evolutionary trajectory. Consequently, this article conducts a literature review of the most impactful scientific works, using the reliable Web of Science (WoS) indexing database as a data source in order to attain a thorough and quality-assured analysis. This review identifies relevant patterns, provides research insights, traces technological growth, and anticipates potential future directions. Beyond mapping the known, this study aims to highlight uncharted areas within the LLM landscape, thereby catalyzing future research endeavors. The ultimate goal is to enhance collective understanding, encourage collaboration, and guide subsequent innovations in harnessing the potential of LLMs for societal and technological advancement.
How Chinese Media Addresses Esports Issues: A Text Mining Comparative Analysis of Online News and Viewers’ Comments on the Hangzhou Asian Games
Authors: Cui Linjie , Kim Eun Joung , Kim JungYoon
Published: December 2023

As the esports industry experiences unprecedented growth, efforts to legitimize it as a recognized sport have intensified. This paper explores the transformative changes in China’s esports landscape with focus on the aftermath of its official recognition at the 2023 Asian Games in Hangzhou. For this, this study employs a data-driven comparative approach to analyze both online news data and viewer comments on a video platform broadcasting the esports tournament during the Hangzhou Asian Games. For text data, it utilized text mining techniques of the Latent Dirichlet Allocation algorithm (LDA), and for conversion from image to text, it used through the Contrastive Language–Image Pretraining (CLIP) model. The findings reveal that the text and image data in online news emphasize the industry’s positive anticipation of esports becoming a medal sport, but the public who watched esports events showed mixed expectations, doubts, or even negative sentiments about the reevaluation of esports. As evidenced in the paper, the public’s divided stance towards esports might hinder the establishment of a solid consensus in developing the necessary infrastructure or policymaking. Thus, the transition for games to be recognized as an Olympic sport after their inclusion in the Asian Games demands a prolonged period and a comprehensive blend of economic, social, cultural, and educational policies.
Robust and Refined Salient Object Detection Based on Diffusion Model
Authors: Ye Hanchen , Zhang Yuyue , Zhao Xiaoli
Published: December 2023

Salient object detection (SOD) networks are vulnerable to adversarial attacks. As adversarial training is computationally expensive for SOD, existing defense methods instead adopt a noise-against-noise strategy that disrupts adversarial perturbation and restores the image either in input or feature space. However, their limited learning capacity and the need for network modifications limit their applicability. In recent years, the popular diffusion model coincides with the existing defense idea and exhibits excellent purification performance, but there still remains an accuracy gap between the saliency results generated from the purified images and the benign images. In this paper, we propose a Robust and Refined (RoRe) SOD defense framework based on the diffusion model to simultaneously achieve adversarial robustness as well as improved accuracy for benign and purified images. Our proposed RoRe defense consists of three modules: purification, adversarial detection, and refinement. The purification module leverages the powerful generation capability of the diffusion model to purify perturbed input images to achieve robustness. The adversarial detection module utilizes the guidance classifier in the diffusion model for multi-step voting classification. By combining this classifier with a similarity condition, precise adversarial detection can be achieved, providing the possibility of regaining the original accuracy for benign images. The refinement module uses a simple and effective UNet to enhance the accuracy of purified images. The experiments demonstrate that RoRe achieves superior robustness over state-of-the-art methods while maintaining high accuracy for benign images. Moreover, RoRe shows good results against backward pass differentiable approximation (BPDA) attacks.
LEO-Assisted Aerial Deployment in Post-Disaster Scenarios Using a Combinatorial Bandit and Genetic Algorithmic Approach
Authors: Mohamed Ehab Mahmoud , Hashima Sherief , Hatano Kohei , Khallaf Haithem S.
Published: December 2023

This paper proposes integrating low earth orbit satellites (LEO-Sats) and multiple aerials to provide rescue services in post-disaster areas. Aerials are distributed to provide wireless connectivity to survivors and rescue workers, while LEO-Sat exhibits backhaul linkages to aerials to connect them with the closest surviving ground base station (GBS). In this context, the aerials’ deployment should maximize the total system rate while guaranteeing fairness among the served post-disaster regions within aerials’ limited battery budget and LEO-Sat’s limited bandwidth resources. Therefore, a combinatorial bandit model with arms fairness and budget constraints (CB-FBC) is proposed to address the aerials’ deployment while maintaining fairness in covering post-disaster regions within the aerials’ limited battery resources. Additionally, the aerials’ transmit communication powers and LEO-Sat’s bandwidth resources are optimized according to traffic requests of LEO-aerial linkages using a genetic algorithm (GA). By means of numerical analysis, the proposed GA shows superior performance over other naïve benchmarks.
Application of High-Speed Gallium Nitride Devices in Mass Spectrometry Sweeping Mode
Authors: Han Le , Li Yongping
Published: December 2023

Quadrupole mass spectrometers are widely used, and voltage scanning is their traditional working mode. By fixing the scanning voltage frequency and changing the value of the RF voltage, ions with different mass numbers can reach the detector in sequence, achieving ion selection. When analyzing high-mass molecules, several kilovolts of scanning voltage are required, which is not conducive to the miniaturization and safety of the instrument. By selecting the frequency of the scanning RF power supply and fixing the value of the RF power supply voltage, ion selection can be achieved by changing the frequency of the RF power supply, enabling miniaturized mass spectrometry analysis of high-mass molecules. In this paper, a high-speed gallium nitride driver circuit for frequency scanning mass spectrometry analysis is designed. The NCP51820 high-speed gate driver and INN650D140A gallium nitride MOS tube are selected to form a full-bridge driver, realizing a quadrupole rectangular wave RF power supply. The system has a maximum withstand voltage of 650 V and a frequency range of 400 K–4 MHz, allowing for scanning measurements of mass numbers ranging from 3 to 606 amu.
A Constructal-Theory-Based Methodology to Determine the Configuration of Empty Channels Used in the Resin Impregnation of a Square Porous Plate
Authors: Magalhães Glauciléia Maria Cardoso , Souza Jeferson Avila , dos Santos Elizaldo Domingues
Published: December 2023

Liquid composite molding techniques are largely used to produce pieces such as truck cabins or wind turbine blades. The liquid resin infusion processes use a network of injection channels to improve the resin flow through a porous-reinforced medium. The present numerical study predicts the positioning of empty channels by applying constructal theory to an idealized problem. The channels’ position and size were not predefined but instead constructed (made to grow) from an elemental channel. Two strategies were tested for channel growth: each new elemental channel was placed next to the region with the lowest or highest resistance to resin flow. The geometric configuration of the channels was constructed using a control function instead of using pre-defined shapes. The conservation of mass and momentum and an additional transport equation for the resin volume fraction were solved using the finite volume method. The volume of the fluid model was used for the treatment of the multiphase flow (air + resin). The growth of an empty channel with the lowest resistance strategy led to a decrease in the injection time and waste of resin. The size (resolution) of the elemental channel also affected the performance indicators and geometric configuration of the injection channels.
Functional Fruit Trees from the Atlantic and Amazon Forests: Selection of Potential Chestnut Trees Rich in Antioxidants, Nutrients, and Fatty Acids
Authors: Palacio de Araujo Caroline , Medeiros Simões Ingridh , Lins Monteiro Rosa Thuanny , de Mello Tamyris , Bravim Canal Guilherme , Ferreira Adésio , Bestete de Oliveira João Paulo , Romais Schmildt Edilson , Lopes José Carlos , da Silva de Souza Tércio , Otoni Wagner Campos , Pinheiro Patrícia Fontes , Moreira Novaes Fábio Junior , Gonçalves Fabricio Gomes , Santos Alexandre Rosa dos , Sobreira Alexandre Rodrigo
Published: December 2023

The Amazon rainforest and the biodiversity hotspot of the Atlantic Forest are home to fruit trees that produce functional foods, which are still underutilized. The present study aimed to select potential functional nut donor trees from two Brazilian chestnuts, by evaluating the nutritional and antioxidant composition of the nuts and the fatty acid profile of the oil. The nutritional characteristics, antioxidants, oil fatty acid profile, and X-ray densitometry of the nuts were evaluated, as well as the characterization of leaf and soil nutrients for each parent tree. The nut oil was evaluated through Brix (%), mass (g), yield (%), and the fatty acid profile. For L. pisonis, the most nutritious nuts were produced by L. pisonis tree 4 (N > P > K > Mg > Ca > Zn > Fe) and L. pisonis tree 6 (P > Ca > Mg > Mn > Zn > Cu > Fe), and for the species L. lanceolata, L. lanceolata tree 6 (N > P > Ca > Mg > Zn > Fe > Cu) and L. lanceolata tree 2 (P > K > Mg > Zn > Cu). In L. pisonis, the highest production of anthocyanins, DPPH, total phenolics, and flavonoids was obtained from the nuts of L. pisonis tree 4 as well as for L. lanceolata, from L. lanceolata tree 1, except for flavonoids. The Brix of the oil from the nuts of both species showed no difference between the trees and the fatty acid profile with a similar amount between saturated (48–65%) and unsaturated (34–57%) fatty acids. Both species have nuts rich in nutrients and antioxidant compounds and can be considered unconventional functional foods. The data collected in the present study confirm that the nuts of these species can replace other foods as a source of selenium.
Analysis and Evaluation of Muscle Quality in Different Parts of the Bighead Carp (Aristichthys nobilis)
Authors: Peng Jiaqi , Lu Xiaorong , Fan Ruiqi , Ren Yuanyuan , Sun Huiwu , Yu Yali , Cheng Bo
Published: December 2023

In this study, the bighead carp (Aristichthys nobilis) was the object of research to compare and analyze the contents of conventional nutrients, amino acids, fatty acids, inosinic acid, and earthy-smelling compounds (geosmin and 2-methylisoborneol) in muscles of its dorsal, belly, tail, opercula, eye socket, and mandible in order to evaluate their quality. The findings could inform recommendations for the consumption and processing of different muscle parts of the bighead carp. The results showed that the water content in the abdominal muscle was significantly lower than that in other parts, and the crude fat content was significantly higher than that in other parts (p < 0.05, the same below). Seventeen kinds of amino acids were detected in the muscles of the six parts of the fish, and the dorsal muscles had the highest umami amino acids, essential amino acids and total amino acids, which were 6.45 g/100 g, 6.82 g/100 g and 17.26 g/100 g, respectively. The total amount of essential amino acids in the muscle was higher than that in the FAO/WHO standard model. According to the AAS standard, the first limiting amino acid in the muscle of the six parts was valine (Val). There were 26 kinds of fatty acids in the abdomen, under the gill cover and in the eye socket muscles, and the content of polyunsaturated fatty acids in the mandibular muscles was the highest (45.41%). The content of inosine in the dorsal muscle was significantly higher than that in other parts. Geosmin was the main substance in the muscle. There was no correlation between the distribution of earthy-smelling compounds and fat content, but the content of earthy-smelling compounds in the muscle of the belly and eye socket was the highest. Therefore, the muscle quality of different parts of the bighead carp has its own characteristics, and targeted development and utilization can make more efficient use of bighead carp resources.
Effect of Diacylglycerol Crystallization on W/O/W Emulsion Stability, Controlled Release Properties and In Vitro Digestibility
Authors: Qiu Chaoying , Liu Yingwei , Chen Canfeng , Lee Yee Ying , Wang Yong
Published: December 2023

Water-in-oil-in-water (W/O/W) emulsions with high-melting diacylglycerol (DAG) crystals incorporated in the oil droplets were fabricated and the compositions were optimized to achieve the best physical stability. The stability against osmotic pressure, encapsulation efficiency and in vitro release profiles of both water- and oil-soluble bioactives were investigated. The presence of interfacial crystallized DAG shells increased the emulsion stability by reducing the swelling and shrinkage of emulsions against osmotic pressure and heating treatment. DAG crystals located at the inner water/oil (W1/O) interface and the gelation of the inner phase by gelatin helped reduce the oil droplet size and slow down the salt release rate. The DAG and gelatin-contained double emulsion showed improved encapsulation efficiency of bioactives, especially for the epigallocatechin gallate (EGCG) during storage. The double emulsions with DAG had a lower digestion rate but higher bioaccessibility of EGCG and curcumin after in vitro digestion. DAG-stabilized double emulsions with a gelled inner phase thus can be applied as controlled delivery systems for bioactives by forming robust interfacial crystalline shells.
Effects of Peanuts and Pistachios on Gut Microbiota and Metabolic Syndrome: A Review
Authors: Campos Stéphani Borges , Oliveira Filho Josemar Gonçalves de , Salgaço Mateus Kawata , Jesus Marisa Helena De , Egea Mariana Buranelo
Published: December 2023

There is growing evidence that the gut microbiota is associated with various aspects of human health, including immune system regulation, vitamin synthesis, short-chain fatty acid production, etc. Peanuts and pistachios are foods rich in protein, unsaturated fatty acids, vitamins, polyphenols, and other dietary components that have been shown to benefit the gut microbiota. Therefore, this review aims to describe the effects of consuming peanuts and pistachios on the gut microbiota and the potential role of these microbiota in human health. This review suggests that the consumption of peanuts or pistachios can demonstrate the potential to exert a beneficial effect on the gut microbiota by promoting the growth of beneficial gut bacteria that produce, for example, short-chain fatty acids that are beneficial for human health. In the case of peanuts, in particular, the possible modulation of the microbiota is associated with an improvement in the risk factors of metabolic syndrome and the inflammatory process triggered by a high-fat diet.
Improved Results on Delay-Dependent and Order-Dependent Criteria of Fractional-Order Neural Networks with Time Delay Based on Sampled-Data Control
Authors: Dai Junzhou , Xiong Lianglin , Zhang Haiyang , Rui Weiguo
Published: December 2023

This paper studies the asymptotic stability of fractional-order neural networks (FONNs) with time delay utilizing a sampled-data controller. Firstly, a novel class of Lyapunov–Krasovskii functions (LKFs) is established, in which time delay and fractional-order information are fully taken into account. Secondly, by combining with the fractional-order Leibniz–Newton formula, LKFs, and other analysis techniques, some less conservative stability criteria that depend on time delay and fractional-order information are given in terms of linear matrix inequalities (LMIs). In the meantime, the sampled-data controller gain is developed under a larger sampling interval. Last, the proposed criteria are shown to be valid and less conservative than the existing ones using three numerical examples.
Does Lower-Limb Tendon Structure Influence Walking Gait?
Authors: Núñez-Trull Alejandro , Álvarez-Medina Javier , Jaén-Carrillo Diego , Rubio-Peirotén Alberto , Abat Ferrán , Roche-Seruendo Luis E. , Gómez-Trullén Eva M.
Published: December 2023

Background: Within the exploration of human gait, key focal points include the examination of functional rockers and the influential role of tendon behavior in the intricate stretch–shortening cycle. To date, the possible relationship between these two fundamental factors in the analysis of human gait has not been studied. Therefore, this study aimed to analyze the relationship between the morphology of the patellar and Achilles tendons and plantar fascia with respect to the duration of the rockers. Methods: Thirty-nine healthy men (age: 28.42 ± 6.97 years; height: 173 ± 7.17 cm; weight: 67.75 ± 9.43 kg) were included. Data of the rockers were recorded using a baropodometric platform while participants walked over a 10 m walkway at a comfortable velocity. Before the trials, the thickness and cross-sectional area were recorded for the patellar tendon, Achilles tendon and plantar fascia using ultrasound examination. The relationship between the morphology of the soft tissue and the duration of the rockers was determined using a pairwise mean comparison (t-test). Results: A significant difference was found for rocker 1 duration, where a longer duration was found in the group of subjects with thicker patellar tendons. Regarding the Achilles tendon and plantar fascia, no significant differences were observed in terms of tendon morphology. However, subjects with thicker Achilles tendons showed a longer duration of rocker 1. Conclusions: The findings underscore a compelling association, revealing that an increased thickness of the patellar tendon significantly contributes to the extension of rocker 1 duration during walking in healthy adults.