bluuebunny/crossref_metadata_2025 huggingface dataset:
PressInPose: Integrating Pressure and Inertial Sensors for Full-Body Pose Estimation in Activities
Authors: Gao Yang , Zhang Wenbo , Ren Junbin , Zheng Ruihao , Jin Yingcheng , Wu Di , Shu Lin , Xu Xiangmin , Jin Zhanpeng
Published: November 2024

The accurate assessment of human body posture through wearable technology has significant implications for sports science, clinical diagnostics, rehabilitation, and VR interaction. Traditional methods often require complex setups or are limited by the environment's constraints. In response to these challenges, this paper presents an innovative approach to human posture estimation under complex motion scenarios through the development of an advanced shoe insole embedded with pressure sensors and an Inertial Measurement Unit (IMU). Coupled with a single wrist-mounted IMU, our system facilitates a comprehensive analysis of human biomechanics by integrating physical kinematics modeling based on pressure data with a multi-region human posture estimation network. To enhance the robustness of our system model, we employed large language models to generate virtual human motion sequences. These sequences were utilized to create synthetic IMU data for data augmentation purposes, addressing the challenge of limited real-world data availability and variability. Our approach uniquely combines physical modeling with data-driven techniques to improve the accuracy and reliability of posture estimation. Experimental results demonstrate that our integrated system significantly advances wearable technology for motion analysis. The Mean Per Joint Position Error (MPJPE) was reduced to 7.75 cm, highlighting the effectiveness of our multi-modal modeling and virtual data augmentation in refining posture estimation.
Playlogue: Dataset and Benchmarks for Analyzing Adult-Child Conversations During Play
Authors: Kalanadhabhatta Manasa , Rastikerdar Mohammad Mehdi , Rahman Tauhidur , Grabell Adam S. , Ganesan Deepak
Published: November 2024

There has been growing interest in developing ubiquitous technologies to analyze adult-child speech in naturalistic settings such as free play in order to support children's social and academic development, language acquisition, and parent-child interactions. However, these technologies often rely on off-the-shelf speech processing tools that have not been evaluated on child speech or child-directed adult speech, whose unique characteristics might result in significant performance gaps when using models trained on adult speech. This work introduces the Playlogue dataset containing over 33 hours of long-form, naturalistic, play-based adult-child conversations from three different corpora of preschool-aged children. Playlogue enables researchers to train and evaluate speaker diarization and automatic speech recognition models on child-centered speech. We demonstrate the lack of generalizability of existing state-of-the-art models when evaluated on Playlogue, and show how fine-tuning models on adult-child speech mitigates the performance gap to some extent but still leaves considerable room for improvement. We further annotate over 5 hours of the Playlogue dataset with 8668 validated adult and child speech act labels, which can be used to train and evaluate models to provide clinically relevant feedback on parent-child interactions. We investigate the performance of state-of-the-art language models at automatically predicting these speech act labels, achieving significant accuracy with simple chain-of-thought prompting or minimal fine-tuning. We use inhome pilot data to validate the generalizability of models trained on Playlogue, demonstrating its utility in improving speech and language technologies for child-centered conversations. The Playlogue dataset is available for download at https://huggingface.co/datasets/playlogue/playlogue-v1.
A Self-Enhancement Solution for Standard RFIDs: Software-based Cross-protocol Communication and Localization
Authors: Zhao Cui , Li Zhenjiang , Ding Han , Sun Xieyang , Xi Wei , Zhao Jizhong
Published: November 2024

Radio Frequency Identification (RFID) is widely recognized for its cost-effectiveness, energy efficiency, and ease of manufacturing, promising versatile applications such as material recognition, vibration detection, and localization. However, these inherent lightweight characteristics necessitate extensive computations or tailored devices for specific tasks. Consequently, there is a critical imperative to explore and augment the sensing and communication capabilities of standard RFIDs to better accommodate a broader spectrum of Internet of Things (IoT) services. In this paper, we introduce SENSO, a self-enhancement solution designed to facilitate diverse tasks without the need for hardware modifications or additional device support. Our approach introduces two key innovations to enable cross-protocol communication (RFID-LoRa) and localization. Firstly, we seamlessly integrate Chirp Spread Spectrum (CSS) modulation into RFID, enabling simultaneous communication with commercial tags and LoRa devices. Secondly, we realize the transmission of wider-band chirps to activate and localize the tag concurrently. By harnessing these techniques, we developed a prototype while addressing several challenges. Our evaluation demonstrates that when maintaining the fundamental RFID communication, SENSO can effectively deliver additional messages to LoRa devices across various indoor scenarios, e.g., through multiple floors, rooms, and corners, and extending over outdoor distances spanning kilometers. Furthermore, it achieves an average accuracy of approximately 5 to 10 centimeters in tag ranging and localization. The source codes of SENSO are available at https://github.com/Cui-Zhao/SENSO.
Animating the Crowd Mirage: A WiFi-Positioning-Based Crowd Mobility Digital Twin for Smart Campuses
Authors: Chen Chunhua , Yang Yuxin , Yuan Hao , Chen Longbiao , Wang Leye , Qu Bingqing , Yang Dingqi
Published: November 2024

Understanding crowd mobility is critical for many applications. In this paper, we propose CrowdMirage, a WiFi positioning-based crowd mobility digital twin for smart campuses. Specifically, we first design an end-to-end human mobility trace extraction pipeline from the comprehensive but noisy WiFi connection logs on a university campus. We then design two predictive and simulative models for the crowd flow prediction and simulation tasks, respectively. Considering the particularity of on-campus mobility, we propose a cross-grained crowd flow prediction model to forecast crowd flow at both building and floor levels. For crowd flow simulation, we design a conditional generative model based on conditional diffusion to simulate the crowd flow under given mobility-related contexts that are systematically identified. We evaluate CrowdMirage on two-year WiFi connection logs collected at our university. The results show that CrowdMirage achieves superior performance in both crowd flow prediction and simulation tasks. Our case studies show that CrowdMirage cannot only accurately forecast cross-grained crowd flow across different cases, but also simulate interpretable crowd flow under previously unseen conditions.
LR-Auth: Towards Practical Implementation of Implicit User Authentication on Earbuds
Authors: Hu Changshuo , Ma Xiao , Huang Xinger , Shen Yiran , Ma Dong
Published: November 2024

The increasing use of earbuds in applications like immersive entertainment and health monitoring necessitates effective implicit user authentication systems to preserve the privacy of sensitive data and provide personalized experiences. Existing approaches, which leverage physiological cues (e.g., jawbone structure) and behavioral cues (e.g., gait), face challenges such as limited usability, high delay and energy overhead, and significant computational demands, rendering them impractical for resource-constrained earbuds. To address these issues, we present LR-Auth, a lightweight, user-friendly implicit authentication system designed for various earbud usage scenarios. LR-Auth utilizes the modulation of sound frequencies by the user's unique occluded ear canal, generating user-specific templates through linear correlations between two audio streams instead of complex machine-learning models. Our prototype, evaluated with 30 subjects under diverse conditions, demonstrates over 99% balanced accuracy with five 100 ms audio segments, even in noisy environments and during music playback. LR-Auth significantly reduces system overhead, achieving a 20 × to 404 × decrease in latency and a 24 × to 410 × decrease in energy consumption compared to existing methods. These results highlight LR-Auth's potential for accurate, robust, and efficient user authentication on resource-constrained earbuds.
Does Sentiment and Emotion affect Mental Health? A Multi-task Classification Framework for Comprehensive Understanding of Mental Health, Emotion, and Sentiment from Motivational Conversations
Authors: Pathak Agnibh , Bhattacharjee Soham , Saha Tulika , Saha Sriparna
Published: November 2024

In light of the escalating challenges posed by our modern lifestyle, cultivating a nuanced approach for addressing mental health issues becomes imperative. Navigating the complexities of daily life demands a thoughtful and comprehensive strategy to identify and address the diverse array of mental health issues that may manifest. The challenges in accurately identifying mental health expressions stems from their complex character of communication, which frequently shares linguistic patterns and similar expressive nuances as communicated by humans. However, we hypothesize that mental health conditions are closely associated with affective factors in particular feelings, moods and emotions. These states define how we think, feel and behave. Thus, in this paper, we aim to explore and analyse the association of the affective states such as sentiment and emotion with mental health in the view of identifying mental health conditions accurately once the feelings and emotions of humans are understood. In this regard, this paper investigates multi-task classification encompassing mental health disorder identification (MHDI), emotion recognition (ER) and sentiment analysis (SA) in non-clinical conversations where MHDI forms the primary task and ER-SA the auxiliary tasks boosting the identification of the primary one. To demonstrate our hypothesis, we propose Core Fusion Network (CFN), a variation of multi-tasking in light of the significance that sentiment and emotion plays in understanding mental health. This method adeptly considers private and shared features across tasks, significantly enhancing classification precision. For our study, we extend the recently released MotiVAte dataset containing dyadic conversations between support seekers and a Virtual Assistant imparting hope and motivation to enclose emotion and sentiment tags for each conversation in a semi-supervised manner. Our hypothesis is reinforced by an extensive ablation study with state of the art multi-task models and the proposed Core Fusion Network (CFN), which exhibits increased accuracy of 89.12% for MHDI, 64.24% for ER, and 79.04% for SA in the tri-task variant as opposed to its corresponding uni-task and bi-task variants. These outcomes underscore the potential of multi-task learning in streamlining mental health classification by integrating emotional and sentiment dimensions.
Concept Drift Adaptation in Text Stream Mining Settings: A Systematic Review
Authors: Garcia Cristiano Mesquita , Abilio Ramon , Koerich Alessandro Lameiras , Britto Alceu de Souza , Barddal Jean Paul
Published: November 2024

The society produces textual data online in several ways, e.g., via reviews and social media posts. Therefore, numerous researchers have been working on discovering patterns in textual data that can indicate peoples’ opinions, interests, and so on. Most tasks regarding natural language processing are addressed using traditional machine learning methods and static datasets. This setting can lead to several problems, e.g., outdated datasets and models, which degrade in performance over time. This is particularly true regarding concept drift, in which the data distribution changes over time. Furthermore, text streaming scenarios also exhibit further challenges, such as the high speed at which data arrive over time. Models for stream scenarios must adhere to the aforementioned constraints while learning from the stream, thus storing texts for limited periods and consuming low memory. This study presents a systematic literature review regarding concept drift adaptation in text stream scenarios. Considering well-defined criteria, we selected 48 papers published between 2018 and August 2024 to unravel aspects such as text drift categories, detection types, model update mechanisms, stream mining tasks addressed, and text representation methods and their update mechanisms. Furthermore, we discussed drift visualization and simulation and listed real-world datasets used in the selected papers. Finally, we brought forward a discussion on existing works in the area, also highlighting open challenges and future research directions for the community.
Solutions, Challenges and Opportunities in Volumetric Video Streaming: An Architectural Perspective
Authors: Bentaleb Abdelhak , Lim May , Hammoudi Sarra , Harous Saad , Zimmermann Roger
Published: November 2024

Volumetric video streaming technologies are the future of immersive media services such as virtual, augmented, and mixed-reality experiences. The challenges surrounding such technologies are tremendous due to the high network bandwidth needed to produce high-quality and low-latency streams. Many techniques and solutions have been proposed across the streaming workflow to mitigate such challenges. To better understand and organize these developments, this survey adopts an architectural framework to showcase current and emerging techniques and solutions for volumetric video streaming while highlighting some of their characteristic challenges and opportunities.
Quality Improvement Report: The Sliding Sign Initiative—Facilitating Earlier Detection of Deep Endometriosis in an Academic US Department
Authors: Pang Emily H. T. , Lee Caroline E. , Lee Abigail , Khalifa Esraa A.
Published: November 2024

A quality improvement initiative focused on pelvic US involving the sliding sign (SS) maneuver to screen for endometriosis resulted in consistent sonographer performance of the SS maneuver, consistent radiologist reporting of the SS, and a number of new endometriosis diagnoses.
Cardiac MRI Pectoralis Muscle Thickness as a Measure of Sarcopenia: Prognostic Significance, Interreader Agreement, and Physiologic Correlation
Authors: Drucker Iarovich Moran , Matos João Francisco , Lowes William Holden , de Silva Nilushi , Moayedi Yasbanoo , Thavendiranathan Paaladinesh , Wald Rachel M. , McInnis Michael , Hong Rachel , Hanneman Kate
Published: November 2024

Pectoralis major muscle thickness on routine cardiac MR images, a reproducible measure of sarcopenia, independently predicted major adverse cardiovascular events in both male and female patients and correlated with physiologic cardiopulmonary exercise test parameters.
Review—Development of Graphene-based Photodiode Device: Synthesis, Deposition, and Characterization
Authors: Nasir Syafiqa , Johrin NorSakinah , Low Weiyee , Moh Pak Yan , Megat Hasnan Megat Muhammad Ikhsan bin , Ghosh Bablu Kumar , Chee Fuei Pien
Published: November 2024

Graphene, a two-dimensional material with exceptional electrical, optical, and mechanical properties, have positioned it as a promising material for photodiode applications. This review delves into the development of graphene materials, emphasizing synthesis, deposition techniques, and characterization. Deposition methods, including spin-coating and direct growth, are evaluated for their scalability and integration capabilities. The synthesis of graphene through methods such as chemical vapor deposition (CVD), exfoliation, and reduction of graphene oxide is discussed, with a focus on optimizing material quality for photodiode applications. Deposition techniques, including drop-casting, spray coating and spin coating method on substrates, are evaluated for their impact on device performance and scalability. Key characterization techniques are highlighted for assessing graphene's structural integrity, and optical properties, photodiode efficiency. The integration of graphene with other materials, such as semiconductors and dielectrics, is reported to enhance device sensitivity, responsivity, and operational stability. Finally, A hybrid heterojunction device with graphene material emphasizes the critical role of the hole transport layer is addressed in this review.
Using X-ray Microscopy to Probe Failure Mechanisms in Anode-free Cells: An Industry Perspective
Authors: Lowe Jeffrey S. , Janakiraman Umamaheswari , Less Greg , Kerns Robert , Muyanja Nancy S.
Published: November 2024

To meet the energy demands of future electric vehicle technologies, batteries with ever-increasing energy densities are desired. One promising technology is an anode-free lithium metal battery (AFLMB) cell, where lithium ions are deposited directly on the anode current collector, resulting in more energy dense cells relative to the current state-of-the-art lithium-ion battery cell. Nevertheless, anode-free cells are prone to early capacity degradation and cell failure. To better understand the degradation mechanisms in these devices, we present a methodology for assessing microstructural changes in battery cells that can be easily implemented within existing battery manufacturing facilities. We employed X-ray tomographic imaging and analyses on small format, AFLMB pouch cells. Anode thickness variations were characterized non-destructively by housing the pouch cells in fabricated pressurized jigs during both cycling and tomographic imaging. Additionally, we present a technique to measure cathode porosities and tortuosities at the end-of-life (EOL) with higher resolution X-ray imaging. The proposed methodology is able to accurately reproduce known microstructural behaviors in AFLMBs. At the anode, significant thickness changes are observed because of continuous electrolyte degradation and solid electrolyte interphase growth. At the cathode, large porosity changes are detected at the EOL, potentially owing to NCM (LiNixCoyMnzO2) particle cracking.
Improving student learning outcomes and perception through a blended learning strategy based on virtual microscopy for teaching a histology laboratory course
Authors: Zhang Yanmin , Li Chunyang , Zhou Chan
Published: November 2024

Most studies examining virtual microscopy (VM) have been conducted in North America, with fewer studies focusing on other regions, particularly Asian countries. Additionally, a previous meta-analysis highlighted the need for more rigorous research on student performance in light microscopy (LM). Our present study investigated the use of LM + VM blended learning in histology for Chinese undergraduate dental students. This approach resulted in significant improvements in student performance, satisfaction, and perception compared to traditional LM learning.
Effect of Polyethylene Glycol and Humic Acid Coating on NPK Release From Controlled‐Release Fertilizer
Authors: Suwardi  , Tjahyandari Suryaningtyas Dyah , Ghofar Abdul , Rosjidi Mochamad , Mustafa Anwar , Saputra Hens
Published: November 2024

Plants require essential macronutrients such as nitrogen (N), phosphorus (P), and potassium (K), but their availability in soil is often inefficient due to evaporation, leaching, and binding. Controlled‐release fertilizers (CRFs) provide a solution by regulating nutrient release over time. This study evaluates the effects of two coating materials, polyethylene glycol (PEG) and humic acid, on the release patterns of N, P, and K during an 18‐week incubation using Inceptisol from Bogor, Indonesia. Various CRF treatments were tested, including uncoated (A1, A2), PEG‐coated (B1, B2), and humic acid–coated (C1, C2) formulations. Results showed that CRF with PEG (B2) demonstrated slower N release, with ammonium levels decreasing from 32.22% in week 1 to 9.36% by week 18. Nitrate release increased steadily from 26.37% to 37.36% between weeks 3 and 18. In contrast, CRF with humic acid (C2) showed slower nitrate release, reaching 36.26% by the end of incubation. P release patterns were similar across treatments, while K release was lowest in the humic acid–coated treatment (C2) at 24.48%. These findings underline the potential of coating materials like PEG and humic acid to optimize nutrient release, enhancing agricultural efficiency.
A Novel Hybrid Algorithm for Solving Economic Load Dispatch in Power Systems
Authors: Fahim Khairul Eahsun , De Silva Liyanage C. , Andiappan Viknesh , Shezan Sk. A. , Yassin Hayati
Published: November 2024

Various algorithms have been created in the past to take economic load dispatch (ELD) into account. These algorithms, however, concentrate on multiple tuning parameters, necessitating hyperparameter adjustment. A unique parameterless hybrid is presented to explicitly evaluate ELD for test systems and real‐world power plant systems matching the operational limitations. In addition, earlier algorithms could only offer estimates of the final cost of fuel based on the hyperparameter choices. This may prevent the global minimum values from being met. To find comprehensive solutions to the ELD problem in power systems, this paper suggests a new method called the hybrid Jaya optimization algorithm, which uses the merits of the Jaya and teaching–learning‐based optimization (TLBO) algorithms. This enhancement is proposed to improve the population variety, the balance between local and global search, and the early convergence of the original Jaya optimization method. A metaheuristic optimization technique called TLBO simulates the teaching–learning process in a classroom to optimize problems. The TLBO algorithm uses an exploration phase in which possible solutions are generated at random to discover the best solution. The algorithm then uses the exploitation phase to refine the search space‐based parameter adjustments to enhance the quality of the best solution identified. On the other hand, the Jaya algorithm is a metaheuristic optimization algorithm motivated by the idea of social behavior in nature. Candidate solutions are improved repeatedly through cooperation and competition using a population‐based approach, and each solution adjusts its position based on the best and worst answers in the population. By combining the advantages of both algorithms, hybrid Jaya (Jaya–TLBO) outperforms each method alone and minimizes the cost of power generation, improving convergence solution quality. To test its efficacy, the hybrid Jaya–TLBO algorithm is tested on four different test cases, such as an Institute of Electrical and Electronics Engineers (IEEE) 6‐unit, 13‐unit, 20‐unit, 40‐unit ELD system and an Indonesian 10‐unit one. Simulation results show that the proposed algorithm is superior in cost minimization to other well‐known algorithms that have been used recently. As a result, power system planners can utilize this technique to find the most economical load dispatch.
Perceived Physical Activity Levels and Objective Measures: A Mixed‐Methods Study of Residents Aged 65 and Above in Assisted Living Homes in Australia
Authors: Alowaydhah Samaher , Weerasekara Ishanka , Walmsley Sarah , Keir Sally , Marquez Jodie
Published: November 2024

Background and Purpose: Communities face a mounting social, economic and health burden as the global population of older adults continues to grow. Regular physical activity is consistently reported as an effective means of maintaining health and independence in older adults, yet engagement in activity remains low. This study assesses the activity levels of adults aged over 65 years residing in Australian assisted living homes, and extended to examine their perception of their activity and explore possible factors that hinder or promote their engagement in physical activity.

Methods: Thirty‐five older adults were recruited to this mixed‐methods study from four separate assisted living homes. Objective activity data from five consecutive days of accelerometer wear were collected in combination with data from standardised and demographic questionnaires, and semistructured interviews. Qualitative data from interview transcripts were thematically analysed using NVivo software to develop themes relating to physical activity levels of older adults. Quantitative data from accelerometers and questionnaires were descriptively analysed, and associations between variables were examined using STATA software.

Results and Discussion: Findings indicated that females were more active than males, and those who were younger and those with lower body mass index (BMI) displayed higher activity levels. Additionally, residents in assisted living facility (number 4) and those who did not need ambulatory assistance are more active. Conversely, those utilising support services and those with more comorbidities demonstrated lower activity levels. Marital status and cognitive function did not show any association with activity levels of older adults. During the interviews, many older adults acknowledged the importance of physical activity, and some believed they were active. However, objective results contradicted this perception.

Conclusion: This study provides valuable insight into the demographic and health factors contributing to higher levels of activity, and the perceptions of activity among older adults vulnerable to health conditions associated with inactivity.
Increasing the Efficiency of the Cadmium Telluride Solar Cell by Increasing the Number of Absorber Layers and Optimizing Its Efficiency
Authors: Saeedi Aylin , Karimi Mohammad , Mohammadpour Hakimeh
Published: November 2024

To reduce the recombination of carriers, the number of layers were increased from 5‐layer to 9‐layer solar cells while keeping other effective parameters intact. In this work, the efficiency of the cell is increased from 25.93% to 28%, which means a relative increase of 8.2%. The change in impurity density and the length of the layers are employed to achieve maximum efficiency. Increasing the number of layers of the proposed structure does not necessarily lead to an efficiency increment. In this paper, we design a new multijunction solar cell with 9‐layer structure that has higher efficiency as compared to the 5‐layer counterpart. The performance of cadmium sulfide‐cadmium telluride (CdS/CdTe) multijunction solar cells is numerically investigated. Because of the flexibility of the proposed model and feasible construction of the structure, the cell characteristics obtained by this program can be examined by experiment. This structure, accompanied by multilayers of n‐CdTe and p‐CdTe (n‐SnO2/n‐CdS/p‐CdTe/n‐CdTe/p‐CdTe/n‐CdTe/p‐CdTe/p+‐Cu2O) are investigated with different thicknesses, doping densities and number of layers.
SARS‐CoV‐2 Seroprevalence in Indoor House Cats From the Lisbon Area During the COVID‐19 Pandemic, 2019–2021
Authors: Moutinho Isa , Henriques Mafalda , Cardoso Sara , da Penha Coutinho Teresa , Penha-Gonçalves Carlos , Demengeot Jocelyne , Castanho Miguel , Tavares Luís , Gil Solange , Nunes Telmo , Aires-da-Silva Frederico
Published: November 2024

The susceptibility of various animal species to severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) infection has been studied extensively. Cats have garnered significant concern due to their high susceptibility and proximity to humans. This study aimed to evaluate the susceptibility and antibody response in house cats exposed to SARS‐CoV‐2 when human infection was spreading in the Lisbon area during the 2019–2021 period. A total of 733 serum samples were collected and characterized from cats admitted to the Veterinary Teaching Hospital of the Faculty of Veterinary Medicine at the University of Lisbon (HEV‐FMV‐ULisboa). All samples were tested by enzyme‐linked immunosorbent assay (ELISA) for immunoglobulin M (IgM) and immunoglobulin G (IgG) anti‐SARS‐CoV‐2 whole Spike and receptor‐binding domain (RBD) proteins from the Wuhan‐Hu‐1 isolate and 14.7% (108/733) tested positive, suggesting exposure to the human virus. Surrogate virus neutralization test (sVNT) against the Wuhan‐Hu‐1 isolate showed that 20.4% of ELISA positive samples (22/108) harbored neutralizing antibodies against the virus. The 22 most promising serum samples were retested using ELISA and sVNT against Alpha, Delta, and Omicron SARS‐CoV‐2 variants. Notably, these samples exhibited antibodies that were capable of recognizing and neutralizing these variants. Subsequent neutralization assays confirmed that the serum samples effectively inhibited the infection process of Wuhan‐Hu‐1 D614G, Delta, and Omicron SARS‐CoV‐2 pseudotyped viruses. Our findings indicate that cats were exposed to SARS‐CoV‐2 infection during the pandemic period and generated highly effective and broadly neutralizing antibodies against the virus. Although cats have not been demonstrated to significantly contribute to the spread of SARS‐CoV‐2, their high susceptibility to asymptomatic infection underscores the importance of investment in preventive surveillance measures. In summary, our study reinforces the notion that cats naturally infected with SARS‐CoV‐2 represent a valuable anthroponotic disease model in house settings and might be a potential source for the development of antibodies against SARS‐CoV‐2 in tackling future outbreaks with a One Heath perspective.
Mapping of the T-cell Landscape of Biliary Tract Cancer Unravels Anatomic Subtype-Specific Heterogeneity
Authors: Nie Jianhua , Zhang Shuyuan , Guo Ying , Liu Caiqi , Shi Jiaqi , Wu Haotian , Na Ruisi , Liang Yingjian , Yu Shan , Quan Fei , Liu Kun , Li Mingwei , Zhou Meng , Zhao Ying , Li Xuehan , Luo Shengnan , Zhang Qian , Wang Guangyu , Zhang Yanqiao , Yao Yuanfei , Xiao Yun , Tai Sheng , Zheng Tongsen
Published: November 2024

Biliary tract cancer (BTC), encompassing diseases such as intrahepatic (ICC), extrahepatic cholangiocarcinoma (ECC), and gallbladder cancer, is not only increasing but also poses a significant and urgent health threat due to its high malignancy. Genomic differences point to the possibility that these subtypes represent distinct diseases. Elucidation of the specific distribution of T-cell subsets, critical to cancer immunity, across these diseases could provide better insights into the unique biology of BTC subtypes and help identify potential precision medicine strategies. To address this, we conducted single-cell RNA sequencing and T-cell receptor sequencing on CD3+ T cells from 36 samples from 16 patients with BTC across all subtypes and analyzed 355 pathologic slides to examine the spatial distribution of T cells and tertiary lymphoid structures. Compared with ICC and gallbladder cancer, ECC possessed a unique immune profile characterized by T-cell exhaustion, elevated CXCL13 expression in CD4+ T helper–like and CD8+CXCL13+ exhausted T cells, more mature tertiary lymphoid structures, and fewer desert immunophenotypes. Conversely, ICC displayed an inflamed immunophenotype with an enrichment of IFN-related pathways and high expression of LGALS1 in activated regulatory T cells, associated with immunosuppression. Inhibition of LGALS1 reduced tumor growth and regulatory T-cell prevalence in ICC mouse models. Overall, this study unveils T-cell diversity across BTC subtypes at the single-cell and spatial level that could open paths for tailored immunotherapies.

Significance: Single-cell and spatial analyses detailed the T-cell characteristics specific to anatomic subtypes of biliary tract cancer, identifying unique immunologic features that could potentially be harnessed to improve patient outcomes.
supplementary figure1 from TAK1 Promotes an Immunosuppressive Tumor Microenvironment through Cancer-Associated Fibroblast Phenotypic Conversion in Pancreatic Ductal Adenocarcinoma
Authors: Sheng Nan , Shindo Koji , Ohuchida Kenoki , Shinkawa Tomohiko , Zhang Bo , Feng Haimin , Yamamoto Takeo , Moriyama Taiki , Ikenaga Naoki , Nakata Kohei , Oda Yoshinao , Nakamura Masafumi
Published: November 2024

supplementary figure1 from TAK1 Promotes an Immunosuppressive Tumor Microenvironment through Cancer-Associated Fibroblast Phenotypic Conversion in Pancreatic Ductal Adenocarcinoma
Renal and Vascular Functional Decline in Aged Low Birth Weight Murine Adults
Authors: Rabadi May M. , Verde Marella R. , Camilliere Mia , Vecchio Nicholas , Kandhi Sharath , Sekulic Miroslav , Wolin Michael S. , Ratliff Brian B.
Published: November 2024

Introduction: Maternal undernutrition (MUN)-induced low birth weight (LBW) neonates are susceptible to the development of high blood pressure and kidney disease later in life, although the underlying pathological causes remain unclear. The study here investigated the role of renal oxidative stress, impairment of vascular function, and altered sensitivity to angiotensin II (Ang II) as factors that contribute to these pathologies in aged LBW mice. Methods: LBW offspring were generated using a combined protein and caloric restricted MUN mouse model. The resulting LBW offspring were examined 1 year after birth for mean arterial blood pressure (MABP) (carotid artery catheterization), renal blood flow (RBF) (laser Doppler flowmetry), glomerular filtration rate (GFR) (sinistrin clearance), vasoreactivity (myograph), renal vascular density (CD31 staining), and reactive oxygen species (ROS) (ROS probes). Immunoblotting examined Ang II type 1 receptor (AT1R), soluble guanylate cyclase (sGC), and antioxidant systems. Pharmacological agents delivered to animals included the sGC stimulator δ-aminolevulinic acid (ALA), the AT1R inhibitor losartan, the antioxidant ethyl pyruvate (EP), and the toll-like receptor 4 inhibitor TAK242. Results: After 1 year, MABP was increased, while RBF, GFR, vascular reactivity, renal vascular density, and sGC were all reduced in the LBW aged adult. All four pharmacological agents improved MABP, RBF, GFR, vascular density, and vascular reactivity. Renal ROS was increased in the LBW adult but was reduced by ALA, EP, and TAK242 treatment. AT1R was upregulated in the LBW adult, while sGC was decreased, an effect reversed by ALA treatment. Endogenous antioxidant systems, including SOD1, catalase, and glutathione were downregulated in the LBW adult. Conclusion: MUN-induced LBW mice experience increased Ang II sensitivity and oxidative stress. The increased Ang II sensitivity and ROS generation influences vascular density and reactivity, which drive an increase in MABP, and a concomitantly decrease in RBF and glomerular filtration. Pharmacological intervention that inhibits AT1R, enhances levels of sGC, reduces ROS, or inhibits toll-like receptor 4 improves vascular and renal function in the LBW adult.
Exosomal LncRNA and CircRNA Regulate Peripheral Blood Mononuclear Cell Function through a Competitive Endogenous RNA Mechanism in Allergic Rhinitis
Authors: Mao Guangyao , Zhu Qian , Zeng Yiyun , Cong LiQiang , Ye Jun , Kong Xuhui
Published: November 2024

Introduction: Peripheral blood mononuclear cells (PBMCs) dysfunction is involved in the pathogenesis and progression of allergic rhinitis (AR). This study aims to investigate the competing endogenous RNA (ceRNA) networks in PBMCs influenced by differentially expressed long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) found in plasma exosomes induced by AR. Methods: All subjects were from the Affiliated Taizhou People’s Hospital of Nanjing Medical University. Differential expression of messenger RNA (mRNAs) in PBMCs and lncRNAs/circRNAs in plasma exosomes was analyzed using high-throughput sequencing. Differentially expressed lncRNAs and circRNAs that target mRNAs were identified using bioinformatics methods. The predicted target mRNAs were intersected with the differentially expressed mRNAs in PBMCs to construct ceRNA networks. The subcellular localizations of lncRNAs and circRNAs within the ceRNA networks were determined using RNA fluorescence in situ hybridization or bioinformatics methods. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of differentially expressed mRNAs in PBMCs were conducted using the clusterProfiler R package. Quantitative reverse transcription polymerase chain reaction was used to validate the expression levels of each molecule within the constructed ceRNA networks in clinical samples, along with receiver operating characteristic (ROC) curve analysis to assess diagnostic value. Further validation was performed using in vitro cultured PBMCs and dual-luciferase reporter assays. Results: Five differentially expressed circRNAs and 31 differentially expressed lncRNAs were identified in exosomes. In PBMCs, 130 differentially expressed mRNAs were identified. Six ceRNA networks were constructed, affecting PBMCs chemorepellent activity, JAK-STAT signaling pathway, and other functions or pathways. The expression level of ENST00000650850 in plasma exosomes was significantly lower in AR patients, suggesting its potential diagnostic value. The expression level of ENST00000650850 in plasma exosomes was positively correlated with the expression levels of ENST00000650850 and IL6 mRNA in PBMCs. PBMCs from healthy individuals were stimulated with plasma exosomes isolated from AR patients, leading to a reduction in IL6R mRNA expression levels in the PBMCs. Conclusion: Differentially expressed lncRNA (ENST00000650850) in plasma-derived exosomes of AR patients may regulate IL6R mRNA expression in PBMCs via miR-6747-3p, thereby influencing PBMC function and contributing to the pathogenesis and progression of AR.
Identification of the satisfaction of university students through sentiment analysis: a systematic review
Authors: Chamorro-Atalaya Omar Freddy , Aldana-Trejo Florcita , Alvarado-Bravo Nestor , Nieves-Barreto Constantino , Aguilar-Loyaga Santiago , Gamarra-Bustillos Carlos , Torres-Quiroz Almintor , Riveros-Cuéllar Alípio , Pérez-Samanamud Manuel , Pérez-Guevara Luciano
Published: November 2024

In these times it is necessary to use tools based on artificial intelligence (AI) that contribute to improving the quality of university education for the benefit of students. This article aims to define the state of the question on the application of sentiment analysis in the identification of student satisfaction, based on the systematic review of scientific publications. The research is of an exploratory level and of a mixed approach. The data collection method was based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) declaration, managing to focus the review based on 27 publications, downloaded from Scopus, ERIC, and Google Scholar. From the systematic review, the following conclusions were reached: the fields of application to a greater extent are found in the academic field and university well-being. Likewise, regarding the contributions achieved, these focused to a greater extent on aspects of the teaching activity, valuing their performance and contributing to their feedback for the redesign of didactic strategies. Finally, in terms of limitations, they focused mainly on the low student participation regarding the use of sentiment analysis to identify student satisfaction; this is due to the lack of regulations or regulations for it is application in the university environment.
The level of career indecision of senior high school students based on gender
Authors: Saputra Edy Cahya , Purwanta Edi , Astuti Budi
Published: November 2024

The purpose of this study was to determine the level of adolescent career indecision based on gender differences between male and female adolescents. This study used a quantitative descriptive method. The sampling technique employed a random sampling technique. The sample of this research was 361 students of class XII (12th grade) from 24 senior high schools in Kulon Progo Regency, Indonesia. The number of respondents based on gender consisted of 295 female and 66 male students. Data collection technique had been carried out using the career decision making difficulties questionnaire (CDDQ) in the 2022/2023 academic year through quantitative descriptive techniques and independent sample t-test. The independent sample t-test obtained the results of the Sig. less than 0.05 (0.031<0.05). Meanwhile, the results of descriptive analysis show that the level of career indecision of students who fall into the salient category is 26.44% of female students and 16.67% of male students. Thus, it can be concluded that there were respondents, both female and male students, who were included in the level of career indecision in the salient category or serious category that required assistance by a counselor to overcome its problem.
Factors affecting environmental ethics behavior of undergraduate students
Authors: Likhit Junkaew , Prayoon Wongchantra , Suparat Ongon , Kannika Sookngam , Praimee Uraiwan
Published: November 2024

The research aimed to investigate the variables affecting undergraduate students’ environmental ethical conduct as well as the variables influencing the environmental ethical behavior of undergraduate students of various genders and academic years. In the topic of environmental education, year 1-4 pupils made up the research sample. A total of 231 people from Mahasarakham University’s Faculty of Environment and Resource Studies freely provided information. A survey was used as the research method to assess the variables influencing undergraduate students’ ethical conduct in the environment. Frequency, percentage, mean, standard deviation, and one-way ANOVA testing of hypotheses are the statistics used for the study. The factors affecting the undergraduate students’ overall environmental ethical behavior were found to be at the highest level, equal to 4.04. After examining each item, it was found that serving the public and keeping promises was equal to 4.86, followed by upholding universal ideals (¯x=4.22), a factor that involves avoiding punishment. fear of criminal and disciplinary penalty (¯x=4.11), conformity factor (¯x=4.02), reward-seeking factor (¯x=3.97), social responsibility compliance factor (¯x=3.74), and personal qualities (¯x=3.41) were the factors that had the smallest effect on the student’s environmental ethical behavior, in that order. At the 05 levels, several factors influenced learners of different genders’ environmental ethical behavior, and various factors affected the environmental.
State-of-the-art in teachers’ online pedagogical competencies in higher education from 2011 to 2022
Authors: Pham Thi-Thanh-Hai , Pham Hung-Hiep , Luong Dinh-Hai
Published: November 2024

University teachers play an important role in teaching and learning activities in the online environment. However, the emerging remote education due to the COVID-19 pandemic has revealed the shortcomings of online teaching competencies of teachers. The bibliometric study investigated the knowledge base of online teacher pedagogical competencies in higher education by analyzing 131 Web of Science-indexed documents from 2011 to 2022. The findings revealed the sudden decline of the number announced in the two years 2021 and 2022. Spain, Russia, the United States, and Canada are emerging countries in the network of international collaboration. The research community is based on small research groups and has emerged in recent years. Sources focus on subjects such as education, e-learning, computer science, developmental and educational psychology, among which education sciences is the most prominent one in the last years. With nine identified themes, these of interest are online teacher roles, remote emergency teaching, online professional development, and online teaching in COVID-19. Emerging keywords highlighted potential topics in the foreseeable future such as competency frameworks, global education, and teaching professionalism.
Higher order thinking skills research trends: a bibliometric analysis in selected journals (2014 to 2023)
Authors: Lismaya Lilis , Hartono Hartono , Subali Bambang , Sumarni Woro , Ridlo Saiful , Nuswowati Murbangun
Published: November 2024

This article aims to analyze the trend of higher order thinking skills (HOTS) research in selected journals, namely Journal of Research in Science Teaching (JRST), International Journal of Science Education (IJSE) and Review of Educational Research (RER) through bibliometrics on the Scopus database from 2014 to 2023. The articles consist of a total of 947, then divided into 333 articles analyzed, with details of JRST 113 articles, IJSE 130 articles and RER 90 articles. The method used in this research is article analysis using bibliometric stages, followed by keyword search, initial search results, correction of search results, initial data compilation and data analysis. The results showed that the publication of scientific articles in selected journals on HOTS varied from year to year. The results of this study are expected to help other researchers who are interested in reviewing and researching research trends related to HOTS in selected journals and to recommend further research directions.
Factors influencing students’ intention to enroll at private higher education institution
Authors: Somantri Ace , Zaid Zaid , Pratondo Katon , Asmara Abdullah Qiqi
Published: November 2024

Intense competition exists amid the rapid growth of universities worldwide and in Indonesia. Often, private higher education is the victim of defeat from competition. Because competitive pressures such as these will undoubtedly lead to reduced revenues, universities are encouraged to increase their student numbers to increase revenues. According to the theory of planned behavior, the intention to carry out certain actions is an essential prerequisite for the strategy’s success. This research examines the factors influencing students to enroll in private, Muhammadiyah contexts, higher education institutions. By involving 572 respondents and using partial least squares structural equation modeling (PLS-SEM) analysis, this research shows that among the factors that influence students’ intention in enrolling in Muhammadiyah Higher Education Institutions are higher education institution image and student characteristics, where both have a positive and significant influence with values (β=0.409; p-value=0.000) and (β=0.461; p-value=0.001).
Instructional leadership as a catalyst for organizational commitment: insights from a systematic literature review
Authors: Othman Cammellia , Busari Abdul Halim
Published: November 2024

This research intends to provide insight on the relationship between instructional leadership and organizational commitment, with a specific emphasis on the timeframe spanning from 2009 to 2023. Using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach, this study conducted a systematic search of academic databases, including Web of Science (WoS), Scopus, and ERIC. The search produced a large selection of papers, reviews, and articles about organizational commitment and instructional leadership. The analysis demonstrated the critical role that the impact of instructional leadership on organizational commitment played by using an advanced search strategy involving keywords, such as “instructional leadership,” “educational leadership,” “school leadership,” “organizational commitment,” “employee commitment,” and “workplace commitment.” The review identified three main themes from the final dataset, which included 33 items. These themes were: i) instructional leadership and teachers; ii) organizational commitment and school leadership styles; and iii) leadership in diverse educational contexts. The key themes were then validated by experts. The analysis reveals school leaders’ potential contributions to organizational commitment, which has consequences for educational leadership and management.