bluuebunny/crossref_metadata_2025 huggingface dataset:
Ginger Bioactives: A Comprehensive Review of Health Benefits and Potential Food Applications
Authors: Shaukat Muhammad Nouman , Nazir Akmal , Fallico Biagio
Published: November 2023

Ginger is an herbaceous and flowering plant renowned for its rhizome, which is widely employed as both a spice and an herb. Since ancient times, ginger has been consumed in folk medicine and traditional cuisines for its favorable health effects. Different in vitro and in vivo studies have disclosed the advantageous physiological aspects of ginger, primarily due to its antioxidant, anti-inflammatory, antimicrobial, and anti-carcinogenic properties. These health-promoting features are linked to the variety of bioactive compounds that are present in ginger. Following the advancement in consumer awareness and the industrial demand for organic antioxidants and functional ingredients, the application of ginger and its derivatives has been broadly investigated in a wide range of food products. The prominent features transmitted by ginger into different food areas are antioxidant and nutraceutical values (bakery); flavor, acceptability, and techno-functional characteristics (dairy); hedonic and antimicrobial properties (beverages); oxidative stability, tenderization, and sensorial attributes (meat); and shelf life and sensorial properties (film, coating, and packaging). This review is focused on providing a comprehensive overview of the tendencies in the application of ginger and its derivatives in the food industry and concurrently briefly discusses the beneficial aspects and processing of ginger.
The Detection of Aggressive Driving Patterns in Two-Wheeled Vehicles Using Sensor-Based Approaches
Authors: Kim Dongbeom , Kim Hyemin , Jun Chulmin
Published: November 2023

The growing concerns over road safety and the increasing popularity of two-wheeled vehicles highlight the need to address aggressive driving behaviors in this context. Understanding and detecting such behaviors can significantly contribute to rider safety and accident prevention. The primary aim of this research is to develop an effective method for detecting aggressive driving patterns, specifically focusing on rapid turns and lane-change maneuvers using two-wheeled vehicles. To achieve this objective, we conducted a survey to establish criteria for aggressive driving. Subsequently, we collected data through a virtual simulator, implementing staged aggressive driving scenarios. The data underwent preprocessing, feature engineering, and deep learning model training for detection. The results of this study demonstrate the successful detection of aggressive driving patterns, including rapid turns and lane changes, using sensor data. The criterion for rapid turns is specified as a significant change in sensor values within 1 s. In the CNN-LSTM model for aggressive lane changes, the precision for normal driving is 0.97, and the overall accuracy for aggressive driving is 95%. Our approach, which relies on sensor technology rather than impractical camera systems, showcases the potential for enhancing rider safety in two-wheeled vehicles. In conclusion, this research provides valuable insights into the detection of aggressive driving patterns in two-wheeled vehicles. By leveraging sensor data and innovative methods, it offers promising implications for improving rider safety and accident prevention in the future.
Long-Term MERRA-2 Reanalysis Data Indicate Atmospheric Environmental Changes for Three Major Concentrating-Solar-Power-Plant Project Areas in Xinjiang, China
Authors: Dai Zengli , Wang Dongxiang , Wang Renbao , Song Xiupeng , Stachlewska Iwona S. , Han Zhaohui , Song Xiaoquan
Published: November 2023

The characteristics, distributions, and trends of the aerosol optical depth (AOD) and dust aerosol optical depth (DAOD) of three major concentrating solar power (CSP)-plant project areas (Hami, Turpan, and Ruoqiang) in Xinjiang, China were investigated and analyzed during 1980–2022 using the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) reanalysis products. The monthly variation, seasonal variation, inter-annual variation, distributions of AOD and DAOD, and proportions of dust in the aerosols in these three CSP-plant project areas were computed and analyzed. Overall, the annual mean AOD at 550 nm in the Turpan project area was the highest (0.20–0.36), while Ruoqiang had the lowest annual mean AOD at 550 nm (0.13–0.30), and the annual mean AOD at 550 nm in Hami was distributed between 0.17 and 0.33. After 2010, the change in the rate of the annual mean AOD showed an overall downward trend in Hami and Ruoqiang, indicating that the atmospheric environmental changes in both areas were more favorable for the operation of CSP plants. In the project areas of Hami, Turpan, and Ruoqiang, more than 90% of the AOD values were mainly in ranges 0.10–0.30, 0.10–0.35, and 0.05–0.30, respectively. As expected, the AOD values in spring and summer were significantly higher than those in autumn and winter in the three study areas. In spring, the dust contents (i.e., ratios of DAOD to AOD) were the highest, accounting for 64% (Hami), 67% (Turpan), and 69% (Ruoqiang) of the total aerosol contents. In all three areas, the proportions of dust in aerosols in spring have shown an increasing trend since 2000, suggesting that the negative impact of the dust on the power generation efficiency in these areas has gradually been increasing. Therefore, it is recommended that the CSP plants in Hami, Turpan, and Ruoqiang develop a strategy for cleaning heliostats, especially in spring, to reduce the impact of dust adhesion on the efficiency of the CSP plants.
Genomic Insights on the Carbon-Negative Workhorse: Systematical Comparative Genomic Analysis on 56 Synechococcus Strains
Authors: Qian Meiwen , Han Xiao , Liu Jiongqin , Xu Ping , Tao Fei
Published: November 2023

Synechococcus, a type of ancient photosynthetic cyanobacteria, is crucial in modern carbon-negative synthetic biology due to its potential for producing bioenergy and high-value products. With its high biomass, fast growth rate, and established genetic manipulation tools, Synechococcus has become a research focus in recent years. Abundant germplasm resources have been accumulated from various habitats, including temperature and salinity conditions relevant to industrialization. In this study, a comprehensive analysis of complete genomes of the 56 Synechococcus strains currently available in public databases was performed, clarifying genetic relationships, the adaptability of Synechococcus to the environment, and its reflection at the genomic level. This was carried out via pan-genome analysis and a detailed comparison of the functional gene groups. The results revealed an open-genome pattern, with 275 core genes and variable genome sizes within these strains. The KEGG annotation and orthology composition comparisons unveiled that the cold and thermophile strains have 32 and 84 unique KO functional units in their shared core gene functional units, respectively. Each KO functional unit reflects unique gene families and pathways. In terms of salt tolerance and comparative genomics, there are 65 unique KO functional units in freshwater-adapted strains and 154 in strictly marine strains. By delving into these aspects, our understanding of the metabolic potential of Synechococcus was deepened, promoting the development and industrial application of cyanobacterial biotechnology.
Functional Load Capacity of Teeth with Reduced Periodontal Support: A Finite Element Analysis
Authors: Dederichs Marco , Joedecke Paul , Weber Christian-Toralf , Guentsch Arndt
Published: November 2023

The purpose of this study was to investigate the functional load capacity of the periodontal ligament (PDL) in a full arch maxilla and mandible model using a numerical simulation. The goal was to determine the functional load pattern in multi- and single-rooted teeth with full and reduced periodontal support. CBCT data were used to create 3D models of a maxilla and mandible. The DICOM dataset was used to create a CAD model. For a precise description of the surfaces of each structure (enamel, dentin, cementum, pulp, PDL, gingiva, bone), each tooth was segmented separately, and the biomechanical characteristics were considered. Finite Element Analysis (FEA) software computed the biomechanical behavior of the stepwise increased force of 700 N in the cranial and 350 N in the ventral direction of the muscle approach of the masseter muscle. The periodontal attachment (cementum–PDL–bone contact) was subsequently reduced in 1 mm increments, and the simulation was repeated. Quantitative (pressure, tension, and deformation) and qualitative (color-coded images) data were recorded and descriptively analyzed. The teeth with the highest load capacities were the upper and lower molars (0.4–0.6 MPa), followed by the premolars (0.4–0.5 MPa) and canines (0.3–0.4 MPa) when vertically loaded. Qualitative data showed that the areas with the highest stress in the PDL were single-rooted teeth in the cervical and apical area and molars in the cervical and apical area in addition to the furcation roof. In both single- and multi-rooted teeth, the gradual reduction in bone levels caused an increase in the load on the remaining PDL. Cervical and apical areas, as well as the furcation roof, are the zones with the highest functional stress. The greater the bone loss, the higher the mechanical load on the residual periodontal supporting structures.
C-C Motif Chemokine Ligand 2 Enhances Macrophage Chemotaxis, Osteogenesis, and Angiogenesis during the Inflammatory Phase of Bone Regeneration
Authors: Shinohara Issei , Tsubosaka Masanori , Toya Masakazu , Lee Max L. , Kushioka Junichi , Murayama Masatoshi , Gao Qi , Li Xueping , Zhang Ning , Chow Simon Kwoon-Ho , Matsumoto Tomoyuki , Kuroda Ryosuke , Goodman Stuart B.
Published: November 2023

Local cell therapy has recently gained attention for the treatment of joint diseases and fractures. Mesenchymal stem cells (MSCs) are not only involved in osteogenesis and angiogenesis, but they also have immunomodulatory functions, such as inducing macrophage migration during bone regeneration via macrophage crosstalk. C-C motif chemokine ligand 2 (CCL2), a known inflammatory mediator, is associated with the migration of macrophages during inflammation. This study examined the utility of CCL2 as a therapeutic target for local cell therapy. Using lentiviral vectors for rabbit MSCs, genetically modified CCL2 overexpressing MSCs were generated. Osteogenic differentiation assays were performed using MSCs with or without macrophages in co-culture, and cell migration assays were also performed. Additionally, co-cultures were performed with endothelial cells (ECs), and angiogenesis was evaluated using a tube formation assay. Overexpression of CCL2 did not affect bone formation under monoculture conditions but promoted chemotaxis and osteogenesis when co-cultured with macrophages. Furthermore, CCL2-overexpression promoted tube formation in co-culture with ECs. These results suggest that CCL2 induces macrophage chemotaxis and osteogenesis by promoting crosstalk between MSCs and macrophages; CCL2 also stimulates ECs to induce angiogenesis. These findings indicate that CCL2 may be a useful therapeutic target for local cell therapy in areas of bone loss.
Epidemiology of Neuroendocrine Neoplasms and Results of Their Treatment with [177Lu]Lu-DOTA-TATE or [177Lu]Lu-DOTA-TATE and [90Y]Y-DOTA-TATE—A Six-Year Experience in High-Reference Polish Neuroendocrine Neoplasm Center
Authors: Durma Adam Daniel , Saracyn Marek , Kołodziej Maciej , Jóźwik-Plebanek Katarzyna , Dmochowska Beata , Kapusta Waldemar , Żmudzki Wawrzyniec , Mróz Adrianna , Kos-Kudła Beata , Kamiński Grzegorz
Published: November 2023

Neuroendocrine neoplasms (NENs) are a group of neoplasms arising from neuroendocrine cells. The worldwide incidence and prevalence of the NENs are estimated to be 6/100,000 and 35/100,000, respectively. Those numbers are increasing every decade, requiring higher and higher diagnosis and treatment costs. Radioligand therapy (RLT) using beta-emitting radioisotopes is an efficient and relatively safe method of treatment, typically used as a second-line treatment. RLT tolerability is higher than other available pharmacotherapies (chemotherapy or tyrosine kinase inhibitors). Recent studies show an increase in overall survival among patients treated with RLT. The present study aimed to learn the epidemiology of NENs in Poland and assess the effectiveness of RLT in a high-reference center. A prospective analysis of 167 patients treated with RLT in one of Poland’s highest-reference NEN centers was performed. The analysis covered 66 months of observation (1 December 2017–30 May 2023), during which 479 RLT single administrations of radioisotope were given. The standard procedure was to give four courses of [177Lu]Lu-DOTA-TATE alone, or tandem therapy—[177Lu]Lu-DOTA-TATE and [90Y]Y-DOTA-TATE. Grading analysis showed that most patients had non-functioning G2 NEN with a mean Ki-67 of 6.05% (SD ± 6.41). The most common primary tumor location was the pancreas. Over two-thirds of patients did undergo surgery due to primary tumors or distant metastases. The majority of patients were using lanreotide as a chronically injected somatostatin analog. Median progression-free survival (PFS) on somatostatin analogs was 21.0 (IQR = 29.0) months. Directly after the last course of RLT, disease stabilization was noted in 69.46% of patients, partial regression was noted in 20.36% of patients, complete regression was noted in 0.60% of patients, and progression was noted in 9.58% of patients. In long-term follow-up, the median observation time among patients who underwent four treatment cycles (n = 108) was 29.8 (IQR = 23.9) months. Stabilization of the disease was observed in 55.56% of the patients and progression was observed in 26.85% of the patients, while 17.59% of patients died. Median PFS was 29.3 (IQR 23.9), and the median OS was 34.0 months (IQR 16.0). The mean age of NEN diagnosis is the sixth decade of life. It takes almost three years from NEN diagnosis to the start of RLT. In long-term observation, RLT leads to disease stabilization in over half of the patients with progressive disease. No differences in PFS or OS depend on the radioisotope used for RLT. In Poland, organized coordination of NEN treatment in high-reference centers ensures the continuity of patient care.
Retroperitoneal Soft Tissue Sarcoma: Emerging Therapeutic Strategies
Authors: de Bree Eelco , Michelakis Dimosthenis , Heretis Ioannis , Kontopodis Nikolaos , Spanakis Konstantinos , Lagoudaki Eleni , Tolia Maria , Zografakis-Sfakianakis Michail , Ioannou Christos , Mavroudis Dimitrios
Published: November 2023

Retroperitoneal soft tissue sarcoma (RPS) is a rare and heterogenous disease for which surgery is the cornerstone of treatment. However, the local recurrence rate is much higher than in soft tissue sarcoma of the extremities since wide resection is usually unfeasible in RPS due to its large size, indistinct tumour borders, anatomical constraints and the thinness of the overlying peritoneum. Local recurrence is the leading cause of death for low-grade RPS, whereas high-grade tumours are prone to distant metastases. In recent decades, the role of emerging therapeutic strategies, such as more extended surgery and (neo)adjuvant treatments to improve oncological outcome in primary localised RPS, has been extensively investigated. In this review, the recent data on the evolving multidisciplinary management of primary localised RPS are comprehensively discussed. The heterogeneity of RPS, with their different histological subtypes and biological behaviour, renders a standard therapeutic ‘one-size-fits-all’ approach inappropriate, and treatment should be modified according to histological type and malignancy grade. There is sufficient evidence that frontline extended surgery with compartmental resection including all ipsilateral retroperitoneal fat and liberal en bloc resection of adjacent organs and structures, even if they are not macroscopically involved, increases local tumour control in low-grade sarcoma and liposarcoma, but not in leiomyosarcoma for which complete macroscopic resection seems sufficient. Additionally, preoperative radiotherapy is not indicated for all RPSs, but seems to be beneficial in well-differentiated liposarcoma and grade I/II dedifferentiated liposarcoma, and probably in solitary fibrous tumour. Whether neoadjuvant chemotherapy is of benefit in high-grade RPS remains unclear from retrospective data and is subject of the ongoing randomised STRASS 2 trial, from which the results are eagerly awaited. Personalised, histology-tailored multimodality treatment is promising and will likely further evolve as our understanding of the molecular and genetic characteristics within RPS improves.
Input Behavior of Farmer Production Factors in the Range of Asian Elephant Distribution: Survey Data from 1264 Households in Yunnan Province, China
Authors: Liu Beimeng , Du Yuchen , Zhao Mengyuan , Xie Yi
Published: November 2023

This article, based on the sustainable livelihood framework and survey data from 1264 households in Xishuangbanna Dai Autonomous Prefecture, Puer City, and Lincang City in Yunnan Province, China, analyzes the impact mechanism of livelihood capital on the production input behavior of farmers affected by Asian elephant damage and the moderating effect of Asian elephant damage on this process using ordinary least squares (OLS) models. The study finds the following: (1) Asian elephant damage has a significant negative effect on farmers’ production input, meaning that as the severity of Asian elephant damage increases, farmers reduce their input into agricultural production factors. (2) Livelihood capital has a significant positive effect on farmers’ production input, and both the increment and stock of livelihood capital promote an increase in farmers’ production input. (3) Asian elephant damage strengthens the influence of livelihood capital on farmers’ inputs of agricultural production factors. Based on these findings, four recommendations are proposed: emphasizing the cultivation and enhancement of farmers’ livelihood capital, improving strategies for managing and preventing wildlife damage, optimizing the economic compensation mechanism for human–wildlife conflicts, and adhering to sustainable development and resource allocation. These recommendations aim to enhance wildlife conservation and management policies, strengthen farmers’ risk-coping capabilities, and ensure the sustainability of agricultural production and livelihoods.
Evaluation of a Decision Support System Developed with Deep Learning Approach for Detecting Dental Caries with Cone-Beam Computed Tomography Imaging
Authors: Amasya Hakan , Alkhader Mustafa , Serindere Gözde , Futyma-Gąbka Karolina , Aktuna Belgin Ceren , Gusarev Maxim , Ezhov Matvey , Różyło-Kalinowska Ingrid , Önder Merve , Sanders Alex , Costa Andre Luiz Ferreira , Castro Lopes Sérgio Lúcio Pereira de , Orhan Kaan
Published: November 2023

This study aims to investigate the effect of using an artificial intelligence (AI) system (Diagnocat, Inc., San Francisco, CA, USA) for caries detection by comparing cone-beam computed tomography (CBCT) evaluation results with and without the software. 500 CBCT volumes are scored by three dentomaxillofacial radiologists for the presence of caries separately on a five-point confidence scale without and with the aid of the AI system. After visual evaluation, the deep convolutional neural network (CNN) model generated a radiological report and observers scored again using AI interface. The ground truth was determined by a hybrid approach. Intra- and inter-observer agreements are evaluated with sensitivity, specificity, accuracy, and kappa statistics. A total of 6008 surfaces are determined as ‘presence of caries’ and 13,928 surfaces are determined as ‘absence of caries’ for ground truth. The area under the ROC curve of observer 1, 2, and 3 are found to be 0.855/0.920, 0.863/0.917, and 0.747/0.903, respectively (unaided/aided). Fleiss Kappa coefficients are changed from 0.325 to 0.468, and the best accuracy (0.939) is achieved with the aided results. The radiographic evaluations performed with aid of the AI system are found to be more compatible and accurate than unaided evaluations in the detection of dental caries with CBCT images.
A Novel Tool for Distinguishing Type A Acute Aortic Syndrome from Heart Failure and Acute Coronary Syndrome
Authors: Seo Min Joon , Lee Jae Hoon , Kim Yang-Weon
Published: November 2023

Type A acute aortic syndrome (urgent AAS, UAAS) has a low incidence and high mortality rate; however, it is often missed or diagnosed late. Our aim was to create a new tool for distinguishing UAAS by using multiple modalities to select patients for CT aortography. This study included 75 patients with UAAS, 77 with acute coronary syndrome (ACS), and 81 with heart failure (HF) who received urgent treatment after propensity matching. Specific symptoms, past medical history, mediastinal width, region of interest (ROI) ratio in the lung base/apex, D-dimers, and troponin I were investigated to differentiate UAAS from ACS and HF. The most significant variables were selected to create a new scoring system. The UAAS score exhibited a performance AUC of 0.982. A simple UAAS score >1, excluding ROI ratios in lung base/apex, showed an AUC of 0.977, a sensitivity of 96%, and specificity of 92.41%. The results were validated using an external data set of 292 patients (simple UAAS score > 1: AUC of 0.966, sensitivity 93.33%, and specificity 95.36%). The simple UAAS score may be a valuable tool for suspecting UAAS and may reduce the likelihood of misdiagnosis or performing unnecessary CT aortography.
GMIW-Pose: Camera Pose Estimation via Global Matching and Iterative Weighted Eight-Point Algorithm
Authors: Chen Fan , Wu Yuting , Liao Tianjian , Zeng Huiquan , Ouyang Sujian , Guan Jiansheng
Published: November 2023

We propose a novel approach, GMIW-Pose, to estimate the relative camera poses between two views. This method leverages a Transformer-based global matching module to obtain robust 2D–2D dense correspondences, followed by iterative refinement of matching weights using ConvGRU. Ultimately, the camera’s relative pose is determined through the weighted eight-point algorithm. Compared with the previous best two-view pose estimation method, GMIW-Pose reduced the Absolute Trajectory Error (ATE) by 24% on the TartanAir dataset; it achieved the best or second-best performance in multiple scenarios of the TUM-RGBD and KITTI datasets without fine-tuning, among which ATE decreased by 22% on the TUM-RGBD dataset.
A Conceptual Framework for Developing Intelligent Services (a Platform) for Transport Enterprises: The Designation of Key Drivers for Action
Authors: Sartzetaki Maria , Karagkouni Aristi , Dimitriou Dimitrios
Published: November 2023

In the digital era, effective business management relies on dynamic risk analysis and real-time data integration, particularly amid the evolving landscape shaped by technological advancements and external factors such as climate change and global health crises. This study delves into the specific demands for digital services within the transportation sector, focusing on the crucial task of identifying an optimal data-driven management system (platform) to bolster transportation decision-making processes. The paper revolves around the formulation of a comprehensive conceptual framework for the development of intelligent services and platforms tailored explicitly to transport enterprises. Methodologically, a thorough analysis of critical infrastructure-related challenges was conducted, emphasizing the integration of a service-oriented approach to enhance overall functionality. Central to the paper’s approach is the careful navigation of conflicting user requirements, resource constraints, and the imperative of maintaining adaptability in service implementation. Additionally, a robust data flow analysis framework is presented, encompassing data collection, model building, and model extrapolation, which enables the generation of reliable outputs essential for informed decision-making. Notably, the study underscores the pivotal role played by the EN.I.R.I.S.S.T. research infrastructure in delivering essential services to the transportation domain, offering accessible data, user-friendly interfaces, and data analysis tools. The findings highlight the enthusiastic reception of the diverse services among potential users, indicating a strong willingness to engage and benefit from the proposed solutions. By emphasizing the integration of intelligent services, the paper seeks to present a systematic approach aimed at enhancing the efficiency, productivity, and competitive edge of transport enterprises through the strategic deployment of advanced technological solutions and proactive planning. This paper ultimately contributes cutting-edge research insights, empowering transportation managers, planners, and decision-makers with valuable resources for informed business intelligence and corporate strategy.
Design and Implementation of Omnidirectional Mobile Robot for Materials Handling among Multiple Workstations in Manufacturing Factories
Authors: Li Hongfu , Liu Jiang , Lyu Changhuai , Liu Daoxin , Liu Yinsen
Published: November 2023

This paper introduces the mechanical design and control system of a mobile robot for logistics transportation in manufacturing workshops. The robot is divided into a moving part and a grasping part. The moving part adopts the mecanum wheel four-wheel-drive chassis, which has omnidirectional moving ability. The mechanical system is based on four mechanical wheels, and a modular suspension mechanism is designed. The grasping part is composed of a depth camera, a cooperative manipulator, and an electric claw. Finally, the two are coordinated and controlled by computer. The controller hardware of the mobile platform is designed, and the functional modules of the mobile platform are designed based on the RT thread embedded system. For the navigation part of the mobile robot, a fuzzy PID deviation correction algorithm is designed and simulated. Using the Hough circular transform algorithm, the visual grasping of the manipulator is realized. Finally, the control mode of the computer-controlled manipulator and the manipulator-controlling mobile platform is adopted to realize the feeding function of the mobile robot, and the experimental verification is carried out.
Guaranteeing Zero Secrecy Outage in Relaying Systems under Eavesdropper’s Arbitrary Location and Unlimited Number of Antennas
Authors: Ta Hien Q. , Nguyen Nga B. T. , Ho-Van Khuong , Oh Hoon
Published: November 2023

This paper proposes a three-phase transmission scheme to ensure zero secrecy outage in decode-and-forward relay systems by using the strategies of artificial noise (AN) injection and channel state information (CSI) leakage avoidance. The zero-outage secrecy spectral efficiency (ZOSSE) and energy efficiency (ZOSEE) of the scheme are then analyzed. Finally, the paper demonstrates that the scheme can always achieve zero secrecy outage even when the eavesdropper has an unlimited number of antennas or is in an arbitrary location, which shows its practical applicability. The paper also shows that the ZOSSE increases with the transmit power and that both the ZOSSE and the ZOSEE are maximized when the relay is halfway between the transmitter and the receiver. This suggests that the placement of the helper node is important in securing the communication of two distant nodes.
DanceTrend: An Integration Framework of Video-Based Body Action Recognition and Color Space Features for Dance Popularity Prediction
Authors: Ding Shiying , Hou Xingyu , Liu Yujia , Zhu Wenxuan , Fang Dong , Fan Yusi , Li Kewei , Huang Lan , Zhou Fengfeng
Published: November 2023

Background: With the rise of user-generated content (UGC) platforms, we are witnessing an unprecedented surge in data. Among various content types, dance videos have emerged as a potent medium for artistic and emotional expression in the Web 2.0 era. Such videos have increasingly become a significant means for users to captivate audiences and amplify their online influence. Given this, predicting the popularity of dance videos on UGC platforms has drawn significant attention. Methods: This study postulates that body movement features play a pivotal role in determining the future popularity of dance videos. To test this hypothesis, we design a robust prediction framework DanceTrend to integrate the body movement features with color space information for dance popularity prediction. We utilize the jazz dance videos from the comprehensive AIST++ street dance dataset and segment each dance routine video into individual movements. AlphaPose was chosen as the human posture detection algorithm to help us obtain human motion features from the videos. Then, the ST-GCN (Spatial Temporal Graph Convolutional Network) is harnessed to train the movement classification models. These pre-trained ST-GCN models are applied to extract body movement features from our curated Bilibili dance video dataset. Alongside these body movement features, we integrate color space attributes and user metadata for the final dance popularity prediction task. Results: The experimental results endorse our initial hypothesis that the body movement features significantly influence the future popularity of dance videos. A comprehensive evaluation of various feature fusion strategies and diverse classifiers discern that a pre–post fusion hybrid strategy coupled with the XGBoost classifier yields the most optimal outcomes for our dataset.
A Decoding Method Using Riemannian Local Linear Feature Construction for a Lower-Limb Motor Imagery Brain–Computer Interface System
Authors: Hou Yao , Tang Rongnian , Xie Xiaofeng
Published: November 2023

Recently, motor imagery brain–computer interfaces (BCIs) have been developed for use in motor function assistance and rehabilitation engineering. In particular, lower-limb motor imagery BCI systems are receiving increasing attention in the field of motor rehabilitation, because these systems could accurately and rapidly identify a patient’s lower-limb movement intention, which could improve the practicability of the motor rehabilitation. In this study, a novel lower-limb BCI system combining visual stimulation, auditory stimulation, functional electrical stimulation, and proprioceptive stimulation was designed to assist patients in lower-limb rehabilitation training. In addition, the Riemannian local linear feature construction (RLLFC) algorithm is proposed to improve the performance of decoding by using unsupervised basis learning and representation weight calculation in the motor imagery BCI system. Three in-house experiment were performed to demonstrate the effectiveness of the proposed system in comparison with other state-of-the-art methods. The experimental results indicate that the proposed system can learn low-dimensional features and correctly characterize the relationship between the testing trial and its k-nearest neighbors.
Assessing the Fire-Modified Meteorology of the Grassland and Forest Intersection Zone in Mongolia Using the WRF-Fire Model
Authors: Wang Yongli , Shi Lamei , Shi Zitong , Yao Qichao , Wang Zhou , Zhong Linhao
Published: November 2023

Climate change is already significantly affecting the frequency of wildfires in most regions of the world, and the risk of wildfires is expected to amplify further with global warming. Accordingly, there is growing concern about the mechanisms and impacts of extreme fires. In this study, a coupling of the Weather Research and Forecasting model and the Rothermel Fire model (WRF-Fire) is employed to reproduce the spread of fire within the national boundary of inner Mongolia from 21 to 27 May 2009. Simulations were run with or without feedback from fire-to-atmosphere models, and the study focused on how the energy flux of simulated fires changes the local meteorological environment. The coupled simulation could reproduce the burned area well, and the wind speed was the dominant factor in the fire spread, with a maximum value no more than 6.4 m/s, when the terrain height changes little and the proportion of grassland is low. After the feedback, the propagation speed of the fire accelerated, accompanying the release of latent and sensible heat, and local circulation formed near the front of the fire, leading to a convergence and divergence zone in the downwind area. It is worth noting that during a period of more than 140 h of simulation, the area of the fire field increased by 17% from ignition time. Therefore, considering the fire–atmosphere interaction is necessary for accurately predicting fire behavior.
Fire Hazard Analysis on Different Fire Source Locations in Multi-Segment Converging Tunnel with Structural Beams
Authors: Wei Lixin , Tang Honghui , Zhao Jiaming , Chen Shiyi , Xie Yiqiang , Feng Shilin , Xu Zhisheng , Yu Zihan
Published: November 2023

To investigate the fire risk in a complex tunnel with varying cross-sections, sloped structures, and dense upper cover beams, this study considered four fire source positions: the immersed tube section, confluence section, highway auxiliary road section, and four-lane sections of the main line. It also considered four beam spacings: 1 m, 1.8 m, 3.6 m, and 7.2 m. The Fire Dynamics Simulation Software FDS was utilized to create a comprehensive tunnel model. The analysis focused on temperature and visibility changes at a 2 m height under a 20 MW fire condition for different fire source positions. These changes were then compared with critical danger values to assess the safety of evacuating personnel within the tunnel. Subsequently, this study proposed corresponding emergency rescue strategies. The findings indicated that when the beam grid spacing exceeded 3.6 m, the upper dense beam gap showed a robust smoke storage capacity, leading to a reduced distance of high-temperature smoke spread. However, this increased smoke storage disrupted the stability of the smoke layer, resulting in a heightened smoke thickness. The location of the ventilation vent at the entrance of the immersed tunnel section caused a non-uniform ventilation flow under the girder, deflecting the smoke front towards the unventilated side and decreasing visibility in the road auxiliary area. In comparison to scenarios without a beam lattice, the presence of a beam lattice in the tunnel amplified fire hazards. When the beam lattice spacing was 3.6 m or greater, the extent of the hazardous environment, which is unfavorable for personnel evacuation, expanded. With the exception of the scenario where the fire source was located in the highway auxiliary roadway, all other conditions surpassed 150 m, which is roughly one-third of the tunnel length. Consequently, more targeted strategies are necessary for effective evacuation and rescue efforts.
Food Security and Land Use under Sustainable Development Goals: Insights from Food Supply to Demand Side and Limited Arable Land in China
Authors: Lan Yang , Xu Bingjie , Huan Yizhong , Guo Jinhua , Liu Xiaojie , Han Jingwen , Li Keran
Published: November 2023

The conflict between economic growth and the arable land demand poses a significant challenge to maintaining food security and achieving the Sustainable Development Goals. Meanwhile, substantial regional disparities in food consumption contribute to variations in land demand, further exacerbating constraints on food security. However, few studies have delved into regional differences in land demand related to food consumption. To bridge these gaps, this study estimated the arable land demand and associated pressures, considering food consumption patterns and the land footprint across 31 provincial districts in China. The findings reveal that grains remain the primary crop consumed by Chinese residents. Notably, the food consumption pattern exhibits substantial disparities among provincial districts, particularly concerning livestock products. Given China's vast population and escalating consumption of livestock, the country demonstrates heightened land demands. While China does not face a national-level food security threat, regional disparities are evident, with eight provincial districts facing potential food security risks. This study explored the challenges and pathways in maintaining food security and the visions to achieve it, emphasizing the importance of sustaining a balanced food consumption pattern, reducing food waste, improving environmentally friendly agriculture practices, formulating effective and continuous laws and regulations, and exploring potential land resource development to alleviate the pressure on arable land and ensure food security.
Transcriptomic Landscape of Circulating Extracellular Vesicles in Heart Transplant Ischemia–Reperfusion
Authors: Joo SeoJeong , Dhaygude Kishor , Westerberg Sofie , Krebs Rainer , Puhka Maija , Holmström Emil , Syrjälä Simo , Nykänen Antti I. , Lemström Karl
Published: November 2023

Ischemia–reperfusion injury (IRI) is an inevitable event during heart transplantation, which is known to exacerbate damage to the allograft. However, the precise mechanisms underlying IRI remain incompletely understood. Here, we profiled the whole transcriptome of plasma extracellular vesicles (EVs) by RNA sequencing from 41 heart transplant recipients immediately before and at 12 h after transplant reperfusion. We found that the expression of 1317 protein-coding genes in plasma EVs was changed at 12 h after reperfusion. Upregulated genes of plasma EVs were related to metabolism and immune activation, while downregulated genes were related to cell survival and extracellular matrix organization. In addition, we performed correlation analyses between EV transcriptome and intensity of graft IRI (i.e., cardiomyocyte injury), as well as EV transcriptome and primary graft dysfunction, as well as any biopsy-proven acute rejection after heart transplantation. We ultimately revealed that at 12 h after reperfusion, 4 plasma EV genes (ITPKA, DDIT4L, CD19, and CYP4A11) correlated with both cardiomyocyte injury and primary graft dysfunction, suggesting that EVs are sensitive indicators of reperfusion injury reflecting lipid metabolism-induced stress and imbalance in calcium homeostasis. In conclusion, we show that profiling plasma EV gene expression may enlighten the mechanisms of heart transplant IRI.
A Machine Learning Approach Unveils the Relationships between Sickness Behavior and Interoception after Vaccination: Suggestions for Psychometric Indices of Higher Vulnerability
Authors: Alfì Gaspare , Orrù Graziella , Menicucci Danilo , Miccoli Mario , Casigliani Virginia , Totaro Michele , Baggiani Angelo , Gemignani Angelo
Published: November 2023

Objective: Prior research has suggested a possible connection between vaccination and manifestations of Sickness Behavior; however, a need remains to first delve deeper into this association and second examine how Interoceptive Awareness and emotional factors may modulate individuals’ perceptions of their health status post vaccination. Method: An online retrospective cross-sectional survey of 647 individuals who received a COVID-19 vaccination was conducted. Together with vaccination side effects, socio-demographic characteristics, health status, level of concern about vaccination, and Interoceptive Awareness were collected at the baseline level. Mood, sleep, and Sickness Behavior were assessed at baseline and after vaccination. Data were analyzed using inferential statistics and machine learning techniques. Results: After vaccination, there was a significant increase in Sickness Behavior levels (mean (±SD) SicknessQ T0 = 1.57 (±2.72), mean (±SD) SicknessQ T1 = 5.54 (±5.51); p-value = 0.001; ES = 0.77). A Machine Learning analysis revealed specific patterns of individual dispositions (sex and age), baseline emotional characteristics (levels of depression, anxiety, stress, and concern about adverse reactions), as well as some components of Interoceptive Awareness (Noticing, Body Listening, and Attention Regulation), as predictors of high levels of Sickness Behavior, both in terms of overall scores (JRIP: 72.65% accuracy, AUC = 0.692, d = 0.709; F1 = 0.726) and individual items (JRIP: 75.77% accuracy, AUC = 0.694; d = 0.717; F1 = 0.754). Conclusions: Our results provide new insight into post-immune reactions by highlighting the contribution of Interoceptive Awareness in modulating the severity of Sickness Behavior. This sheds light on the role of awareness of bodily sensations in modulating perceptions of health status, helping to identify the characteristics that make individuals more prone to feeling sick.
Healthcare Cybersecurity Ethical Concerns during the COVID-19 Global Pandemic: A Rapid Review
Authors: Lieneck Cristian , McLauchlan Matthew , Phillips Sean
Published: November 2023

Background and objectives: Healthcare organizations have endured significant challenges and relied upon telehealth and related technological advances during the COVID-19 pandemic to allow for the sustainment of care. The purpose of this study was to systematically identify healthcare cybersecurity ethical concerns experienced during the pandemic to assist with the sustainability of the delivery of care going forward. Methods: This study was guided by Preferred Reporting Items for Systematic Reviews and Meta-Analysis protocols for systematic reviews and focused on cybersecurity in healthcare organizations that published articles during the COVID-19 pandemic (March 2020 through October 2022). The articles were accessed using the EBSCOhost and Pub-Med (which queries MEDLINE) platforms, through which the Academic Search Complete, MEDLINE Complete, and Complementary Index databases were accessed. Follow-on supplementary topic modeling allowed for the additional application of ethical principles to the review findings. Results: Among the 22 articles that met the inclusion criteria, three ethical concerns were identified by the rapid review: smart and medical technology concerns (73% of occurrences), at-risk population cybersecurity (55% of occurrences), and legal challenges in data protection (73% of occurrences). The research team also conducted a latent Dirichlet allocation (LDA) analysis, identifying three topics from the review corpus: robotic and biomedical/clinical care outcomes, diagnostic applications, and public health data usage. These were then mapped to primary ethical healthcare principles. Conclusions: The sustainment of healthcare technology interoperability and related telehealth initiatives involves the ongoing assessment of cybersecurity threats and adequate knowledge of related ethical stakeholder concerns to promote ongoing care delivery.
Analysis of Water Volume Required to Reach Steady Flow in the Constant Head Well Permeameter Method
Authors: Amoozegar Aziz , Heitman Joshua L.
Published: November 2023

The most common method for in situ measurement of saturated hydraulic conductivity (Ksat) of the vadose zone is the constant head well permeameter method. Our general objective is to provide an empirical method for determining volume of water required for measuring Ksat using this procedure. For one-dimensional infiltration, steady state reaches as time (t) → ∞. For three-dimensional water flow from a cylindrical hole under a constant depth of water, however, steady state reaches rather quickly when a saturated bulb forms around the hole. To reach a quasi-steady state for measuring Ksat, we assume an adequate volume of water is needed to form the saturated bulb around the hole and increase the water content outside of the saturated bulb within a bulb-shaped volume of soil, hereafter, referred to as wetted soil volume. We determined the dimensions of the saturated bulb using the Glover model that is used for calculating Ksat. We then used the values to determine the volume of the saturated and wetted bulbs around the hole. The volume of water needed to reach a quasi-steady state depends on the difference between the soil saturated and antecedent water content (Δθ). Based on our analysis, between 2 and 5 L of water is needed to measure Ksat when Δθ varies between 0.1 and 0.4 m3 m−3, respectively.
The Role of Positivity on Depressive Symptoms in Women Seeking Help for Intimate Partner Violence
Authors: Crapolicchio Eleonora , Cinquegrana Vincenza , Regalia Camillo
Published: November 2023

Intimate partner violence (IPV) is a complex and pervasive global phenomenon. Despite extensive research on physical and sexual violence, there has been a relative lack of investigation into the detrimental and distinctive consequences of psychological violence against women. This is surprising given the profound impact it has on the psychological well-being of victims, notably in the form of depression, which is commonly observed as an outcome in cases of psychological IPV victimization. The present study analyzes the impact of psychological IPV on depressive symptoms, considering the moderating influence of personal positivity, defined as positive self-perceptions, optimistic life perspectives, and a hopeful view of the future in a sample of 171 Italian women seeking assistance from anti-violence centers in different localities of Italy. The findings show that in line with the hypothesis, the association between psychological violence and depressive symptoms is moderated by the levels of perceived positivity, even when controlling for instances of physical violence. These results and implications for interventions are discussed within the framework of existing literature on positive psychology and psychological well-being in the context of IPV.
Reactive Oxygen Species Mediate Transcriptional Responses to Dopamine and Cocaine in Human Cerebral Organoids
Authors: Rudibaugh Thomas T. , Stuppy Samantha R. , Keung Albert J.
Published: November 2023

Dopamine signaling in the adult ventral forebrain regulates behavior, stress response, and memory formation and in neurodevelopment regulates neural differentiation and cell migration. Excessive dopamine levels, including those due to cocaine use in utero and in adults, could lead to long-term adverse consequences. The mechanisms underlying both homeostatic and pathological changes remain unclear, in part due to the diverse cellular responses elicited by dopamine and the reliance on animal models that exhibit species-specific differences in dopamine signaling. In this study, we use the human-derived ventral forebrain organoid model of Xiang–Tanaka and characterize their response to cocaine or dopamine. We explore dosing regimens of dopamine or cocaine to simulate acute or chronic exposure. We then use calcium imaging, cAMP imaging, and bulk RNA-sequencing to measure responses to cocaine or dopamine exposure. We observe an upregulation of inflammatory pathways in addition to indicators of oxidative stress following exposure. Using inhibitors of reactive oxygen species (ROS), we then show ROS to be necessary for multiple transcriptional responses of cocaine exposure. These results highlight novel response pathways and validate the potential of cerebral organoids as in vitro human models for studying complex biological processes in the brain.