bluuebunny/crossref_metadata_2025_split huggingface dataset:
Cryptography-based location privacy protection in the Internet of Vehicles
Authors: Routis George , Katsouris George , Roussaki Ioanna 
Published: May 2024

AbstractThe evolution of the Internet of Things paradigm in recent years demonstrate a significant impact on the transportation sector, leading to the emergence of a new research field, known as the Internet of Vehicles (IoV). In the IoV, vehicles can exchange information with each other and with the roadside units making use of Vehicular Ad Hoc Networks (VANETs). As this technology reaches near-to-market maturity levels, several issues arise related to the protection of users’ privacy, while the interest of adversaries for such private user data in IoV environments gets stronger. This paper aims to present a review of the state-of-the-art techniques tackling the protection of location privacy in IoV environments, as well as experimental evaluation findings regarding the usage of various cryptographic algorithms for the protection of information exchange in these networks. In the conducted evaluations, the AES algorithm has been used as the main standard, which has been coupled with several other encryption/decryption algorithms, such as RSA, ECC and NTRU. The metrics used for the evaluation include measurements over the key generation process, the certificate generation, the encryption/decryption times, the signature generation/verification times, etc. Moreover, the size of messages in the negotiation, the pseudonym exchange and the new pseudonym enabling phases has been recorded, while the energy consumption in the exchange pseudonyms phase has also been measured. All previous experiments have been carried out mainly on NS-3 and SUMO open-source software aiming to have an estimation of how the aforementioned algorithms behave under constrained resources such as CPU usage and power.
Geochemistry and mineralogy of modern floodplain Nile sediments of Sohag area, Egypt: an environmental perspective
Authors: Ali Mohammed H. , Aal Ahmed Abd El , Radwan Ahmed E. , Saber El Sayed A. 
Published: May 2024

AbstractUnderstanding the characteristics of modern floodplain sediment (MFS) is important for geomorphological, paleoclimatic, sedimentation, and environmental investigations. We collected samples from present floodplain Nile sediments in Egypt’s Sohag area and used mineralogical and geochemical (i.e., major and trace elements) proxies to investigate the characteristics and establish their provenances, climatic conditions during deposition, and weathering influence. The study revealed that the Nile floodplain sediments are composed mainly of silt (26–77%), clay fraction (7–44%), and sand content (3–63%), and their texture is classified as clayey silt. These sediments are classified geochemically as greywacke to shale. The mineralogical studies revealed two main assemblages of heavy minerals: the first assemblage represented by magnetite, goethite, zircon, epidote, and garnet and reflects the basement complex in the Eastern Desert and its surrounding rocks; and the second assemblage of goethite, pyroxene, hornblend, and mica of fooldplain deposits derived from the Ethiopian highlands. The geochemical studies indicate that the Nile sediments are immature and formed due to the moderate degree and nonsteady chemical weathering of the parent rocks. The geochemical studies show different mixed sources of sediments, where fine sediments are mostly mafic igneous with a partial contribution from siliscic sedimentary rocks, while the coarser ones are derived mainly from siliscic sedimentary and acidic igneous rocks. The sediments of the presented modern fooldplain reflected two different tectonic setting source areas (collision and continental rift tectonic setting for high silica and low silica samples, respectively) that were shared in supplying the sediments to the present basin. The study revealed that the investigated area may become desertified as a result of climate change and human activities such as salinity, fertiliser use, sand encroachment, and pollution.
Celastrol inhibits mouse B16-F10 melanoma cell survival by regulating the PI3K/AKT/mTOR signaling pathway and repressing HIF-1α expression
Authors: Zhao Ping , He Xing-Bo , Chen Xin-Yue , Li Zhang-Long , Xing Wen-Jia , Liu Wei , Ren Cong , Han Xu-Dong , Guo Bin 
Published: May 2024

Abstract
Objective
Melanoma, with its high degree of malignancy, stands as one of the most dangerous skin cancers and remains the primary cause of death from skin cancer. With studies demonstrating the potential of traditional Chinese medicine to intervene and treat melanoma, we turned our attention to celastrol. Celastrol is a triterpene compound extracted from the traditional Chinese medicine derived from Tripterygium wilfordii. Previous studies have shown that celastrol exerts inhibitory effects on various malignant tumors, including melanoma. Hence, our goal was to clarify the impact of celastrol on cell viability, apoptosis, and cell cycle progression by elucidating its effects on the PI3K/AKT/mTOR pathway.

Methods
CCK-8 and wound healing assays were used to determine the effect of celastrol on the viability and migration of B16-F10 cells. Changes in cell apoptosis, cell cycle, reactive oxygen species (ROS), and mitochondrial membrane potential were detected by flow cytometry. PI3K/AKT/mTOR pathway proteins and HIF-α mRNA expression in B16-F10 cells were detected by western blotting and qPCR. Moreover, the addition of a PI3K activator demonstrated that celastrol could inhibit the function of B16-F10 cells via the PI3K/AKT/mTOR pathway.

Results
Celastrol inhibited the viability and migration of B16-F10 cells. Through the inhibition of the PI3K/AKT/mTOR pathway down-regulates the expression of HIF-α mRNA, thereby causing an increase of ROS in cells and a decrease in the mitochondrial membrane potential to promote cell apoptosis and cell cycle arrest. The inhibitory effect of celastrol on B16-F10 cells was further demonstrated by co-culturing with a PI3K activator.

Conclusion
Celastrol inhibits the function of B16-F10 cells by inhibiting the PI3K/AKT/mTOR cellular pathway and regulating the expression of downstream HIF-α mRNA.
Meaning of ACR-TIRADS recommendation in favor of follow-up rather than FNAC in thyroid nodules
Authors: Leoncini Andrea , Curti Marco , Ruinelli Lorenzo , Trimboli Pierpaolo 
Published: May 2024

AbstractThyroid Imaging Reporting and Data Systems (TIRADSs) have been largely diffused for their high accuracy in risk stratification of thyroid nodules (TNs) and their selection for fine-needle aspiration cytology (FNAC). The most popular TIRADSs are ACR-, EU-, and K-TIRADS, with some discrepancies each other. One major difference is that ACR-TIRADS includes a recommendation in favor of follow-up in TNs having a major diameter insufficient to indicate FNAC. The present study aimed to explore prevalence and significance of this recommendation. EU- and K-TIRADS were used as comparator. A retrospective series of thyroidectomies was searched according to a pre-defined protocol. The study period was 2019–2023. Preoperative ultrasound images were reviewed by radiologists blinded of clinical data. Matching of TIRADS and histology was performed later. Histology was the gold standard. The study series included 39 TNs classified as category 3, 4, or 5 and assessed for follow-up according to ACR-TIRADS. The overall cancer frequency was 25.6%, being 13% in category 3, 20% in category 4, and 83.3% in category 5. The category assessment according to ACR-, EU-, and K-TIRADS was not significantly different. EU-TIRADS indicated FNAC in 10 TNs of which two cancers and eight benign lesions. K-TIRADS recommended FNAC in 32 TNs of which seven cancers and 25 benign lesions. TNs assessed for follow-up according to ACR-TIRADS are cancer in one-fourth of cases. EU- and, especially, K-TIRADS allow us to select for FNAC cancers, with the burden of non-negligible frequency of unnecessary FNACs.
Removal of reactive black 5 in water using adsorption and electrochemical oxidation technology: kinetics, isotherms and mechanisms
Authors: Ganthavee V. , Trzcinski A. P. 
Published: May 2024

AbstractIn this work, a novel graphite intercalation compound (GIC) particle electrode was used to investigate the adsorption of Reactive Black 5 (RB5) and the electrochemical regeneration in a three-dimensional (3D) electrochemical reactor to recover its adsorptive capacity. Various adsorption kinetics and isotherm models were used to characterise the adsorption behaviour of GIC. Several adsorption kinetics were modelled using linearised and non-linearised rate laws to evaluate the viability of the sorption process. Studies on the selective removal of RB5 dyes from binary mixture in solution were evaluated. RSM optimisation studies were integrated with ANOVA analysis to provide insight into the significance of selectivity reversal from the salting effect of textile dye solution on GIC adsorbent. A unique range of adsorption kinetics and isotherms were used to evaluate the adsorption process. Non-linear models best simulated the kinetic data in the order: Elovich > Bangham > Pseudo-second-order > Pseudo-first-order. The Redlich–Peterson isotherm was calculated to have a dye loading capacity of 0.7316 mg/g by non-linear regression analysis. An error function analysis with ERRSQ/SSE of 0.1390 confirmed the accuracy of dye loading capacity predicted by Redlich–Peterson isotherm using non-linear regression analysis. The results showed that Redlich–Peterson and SIPS isotherm models yielded better fitness to experimental data than the Langmuir type. The best dye removal efficiency achieved was ~ 93% using a current density of 45.14 mA/cm2, whereas the highest TOC removal efficiency achieved was 67%.
Anesthesia for Drug Induced Sleep Endoscopy (DISE)
Authors: Schwartz Daniel , Schall Cory , Harders Maureen , Tollinche Luis , Tanios Marianne , Alter Jonathan , Weidenbecher Mark 
Published: May 2024

Abstract

Purpose of Review
Drug-induced sleep endoscopy is a technique in which fiberoptic examination of the upper airway is performed under deep sedation and used to elucidate potential therapies. The most often utilized agents are propofol, midazolam, and dexmedetomidine.

Recent Findings
We propose a protocol for Drug-induced sleep endoscopy using propofol and review its beneficial characteristics compared to midazolam and dexmedetomidine. Propofol has an ideal pharmacokinetic profile and provides adequate sedation that closely enough mimics the upper airway tone and respiratory pattern of natural sleep.

Summary
Drug-induced sleep endoscopy is performed to determine anatomically where sleep-disordered breathing takes place. There are several different anesthetic agents that can be utilized for this procedure, each with their own unique set of characteristics. Nevertheless, we believe that propofol is the agent that best simulates natural sleep to elucidate the site of obstruction.
Identification of Lightning Strike Damage Severity Using Pulse Thermography Through Integration of Thermal Data
Authors: Harrell T. M. , Dulieu-Barton J. M. , Thomsen O. T. 
Published: May 2024

Abstract
Carbon fibre reinforced polymers (CFRP) structures, e.g., wind turbine blades, are suspectable to direct lightning strikes due to their semiconductive nature and ability to conduct current. It is critical to identify and evaluate lightning damage as it can cause premature failure of the primary load carrying components. Direct strike lightning damage has been traditionally identified and assessed by ultrasonic (UT) inspection, which is time consuming, usually requires contact, and does not directly provide a measure of damage severity. An appealing alternative to UT is pulsed thermography (PT), which takes minutes to conduct rather than hours and does not require a couplant. The aim of this work is to explore the application of pulse thermography to identify and evaluate the damage state of CFRP panels damaged by simulated lightning strike. A new analysis technique is presented that provides a damage severity metric which allows damage to be categorized, separated, and quantified.
A Learning-based Control Framework for Fast and Accurate Manipulation of a Flexible Object
Authors: Wang Junyi , Xiong Xiaofeng , Tolu Silvia , Gorb Stanislav N. 
Published: May 2024

AbstractThis paper presents a learning-based control framework for fast (< 1.5 s) and accurate manipulation of a flexible object, i.e., whip targeting. The framework consists of a motion planner learned or optimized by an algorithm, Online Impedance Adaptation Control (OIAC), a sim2real mechanism, and a visual feedback component. The experimental results show that a soft actor-critic algorithm outperforms three Deep Reinforcement Learning (DRL), a nonlinear optimization, and a genetic algorithm in learning generalization of motion planning. It can greatly reduce average learning trials (to < 20$$\%$$
%
of others) and maximize average rewards (to > 3 times of others). Besides, motion tracking errors are greatly reduced to 13.29$$\%$$
%
and 22.36$$\%$$
%
of constant impedance control by the OIAC of the proposed framework. In addition, the trajectory similarity between simulated and physical whips is 89.09$$\%$$
%
. The presented framework provides a new method integrating data-driven and physics-based algorithms for controlling fast and accurate arm manipulation of a flexible object.
A deep learning based approach for image retrieval extraction in mobile edge computing
Authors: Alasadi Jamal , Bati Ghassan F. , Al Hilli Ahmed 
Published: May 2024

AbstractDeep learning has been widely explored in 5G applications, including computer vision, the Internet of Things (IoT), and intermedia classification. However, applying the deep learning approach in limited-resource mobile devices is one of the most challenging issues. At the same time, users’ experience in terms of Quality of Service (QoS) (e.g., service latency, outcome accuracy, and achievable data rate) performs poorly while interacting with machine learning applications. Mobile edge computing (MEC) has been introduced as a cooperative approach to bring computation resources in proximity to end-user devices to overcome these limitations. This article aims to design a novel image reiterative extraction algorithm based on convolution neural network (CNN) learning and computational task offloading to support machine learning-based mobile applications in resource-limited and uncertain environments. Accordingly, we leverage the framework of image retrieval extraction and introduce three approaches. First, privacy preservation is strict and aims to protect personal data. Second, network traffic reduction. Third, minimizing feature matching time. Our simulation results associated with real-time experiments on a small-scale MEC server have shown the effectiveness of the proposed deep learning-based approach over existing schemes. The source code is available here: https://github.com/jamalalasadi/CNN_Image_retrieval.
LLM potentiality and awareness: a position paper from the perspective of trustworthy and responsible AI modeling
Authors: Sarker Iqbal H. 
Published: May 2024

AbstractLarge language models (LLMs) are an exciting breakthrough in the rapidly growing field of artificial intelligence (AI), offering unparalleled potential in a variety of application domains such as finance, business, healthcare, cybersecurity, and so on. However, concerns regarding their trustworthiness and ethical implications have become increasingly prominent as these models are considered black-box and continue to progress. This position paper explores the potentiality of LLM from diverse perspectives as well as the associated risk factors with awareness. Towards this, we highlight not only the technical challenges but also the ethical implications and societal impacts associated with LLM deployment emphasizing fairness, transparency, explainability, trust and accountability. We conclude this paper by summarizing potential research scopes with direction. Overall, the purpose of this position paper is to contribute to the ongoing discussion of LLM potentiality and awareness from the perspective of trustworthiness and responsibility in AI.
A Hybrid CNN-TransXNet Approach for Advanced Glomerular Segmentation in Renal Histology Imaging
Authors: Liu Yangtao 
Published: May 2024

AbstractIn the specialized field of renal histology, precise segmentation of glomeruli in microscopic images is crucial for accurate clinical diagnosis and pathological analysis. Facing the challenge of discerning complex visual features, such as shape, texture, and size within these images, we introduce a novel segmentation model that innovatively combines convolutional neural networks (CNNs) with the advanced TransXNet block, specifically tailored for glomerular segmentation. This innovative model is designed to capture the intricate details and broader contextual features within the images, ensuring a comprehensive and precise segmentation process. The model's architecture unfolds in two primary phases: the down-sampling phase, which utilizes CNNs structures within the TransXNet block for meticulous extraction of detailed features, and the up-sampling phase, which employs CNNs deconvolution techniques to restore spatial resolution and enhance macroscopic feature representation. A critical innovation in our model is the implementation of residual connections between these two phases, which facilitate the seamless integration of features and minimize loss of precision during image reconstruction. Experimental results demonstrate a significant improvement in our model’s performance compared to existing medical image segmentation methods. We report enhancements in mean Pixel Accuracy (mPA) and mean Intersection over Union (mIoU), with increases of approximately 3–5% and 3–8%, respectively. Additionally, the segmented outputs exhibit higher subjective visual quality with fewer noise artifacts. These findings suggest that our model offers promising applications in the segmentation of medical microscopic images, marking a significant contribution to the domain.
Exploration of the Changes in Facial Microbiota of Maskne Patients and Healthy Controls Before and After Wearing Masks Using 16 S rRNA Analysis
Authors: Deng Kexin , Tong Xiaofei , Chen Shuyue , Wu Guojun , Shi Ke , Chen Hao , Tan Yurong , Liao Junlin , Zhou Jianda , Zhao Junxiang 
Published: May 2024

AbstractWhether in the field of medical care, or in people’s daily life and health protection, the importance of masks has been paid more and more attention. Acne, the most common complication after wearing masks, which is also called maskne, has been successfully introduced into the common language as a common topic of dermatologist consultations. This study aims to study the changes of microflora in maskne patients and healthy controls before and after wearing masks. In the summer of 2023, we collected a total of 50 samples from 15 maskne patients and 10 healthy controls before and after wearing surgical masks for a long time. 16 S ribosomal DNA sequencing and identification technology with V3-V4 variable region were adopted to explore the microbiome changes caused by mask wearing, analyze the changes in microbial diversity, and make interaction network. LDA effect size analysis was used to identify which bacteria showed significant changes in their relative abundance from phylum to genus. After wearing a mask, the microbiome of the maskne patients changed significantly more than that of the healthy controls, with both α diversity and β diversity lower than those of maskne patients before wearing masks and those of healthy controls after wearing masks. Co-occurrence network analysis showed that compared with other groups, the network of maskne patients after wearing masks for a long time had the lowest connectivity and complexity, but the highest clustering property, while the opposite was true for healthy controls. Many microbes that are potentially beneficial to the skin decreased significantly after wearing a mask. There was almost no difference in healthy controls before and after wearing a mask.
Accelerometer-Measured Physical Activity, Fitness and Indicators of Cardiometabolic Risk among Rural Adolescents: A Cross-Sectional Study at 15-Year Follow-up of the MINIMat Cohort
Authors: Islam Mohammad Redwanul , Nyström Christine Delisle , Kippler Maria , Kajantie Eero , Löf Marie , Rahman Syed Moshfiqur , Ekström Eva-Charlotte 
Published: May 2024

Abstract
Background
Little is known about the relationship of physical activity (PA) and fitness with cardiometabolic risk among rural adolescents in low- and middle-income countries. Thus, we examined the associations of PA and fitness with selected cardiometabolic indicators along with potential gender-based differences in a birth cohort of rural adolescents from southeast Bangladesh.

Methods
We utilized data from the 15-year follow-up of Maternal and Infant Nutrition Interventions in Matlab (MINIMat) cohort (n = 2253). Wrist-worn ActiGraph wGT3x-BT accelerometers were used to estimate sedentary time (ST) and PA. Fitness was assessed using: handgrip strength, standing long jump, and Chester Step Test. Anthropometric parameters, systolic blood pressure (SBP), and fasting lipid, insulin and glucose levels were measured. We calculated insulin resistance using the Homeostasis Model Assessment equation (HOMA-IR). Linear regression and isotemporal substitution models were fitted.

Results
The adolescents spent 64 min/day (inter-quartile range: 50–81) in moderate-to-vigorous physical activity (MVPA). A 10-minute-per-day higher vigorous PA (VPA) was associated with: 4.9% (95% confidence interval (CI): 2.9–6.8%) lower waist circumference (WC), 3.2 mmHg (95% CI: 1.5–4.8) lower SBP, 10.4% (95% CI: 2.9–17.3%) lower TG, and 24.4% (95% CI: 11.3–34.9%) lower HOMA-IR. MVPA showed similar associations of notably smaller magnitude. Except for WC, the associations were more pronounced among the boys. Substituting ST with VPA of equal duration was associated with lower WC, SBP, triglyceride and HOMA-IR. Grip strength was favorably associated with all indicators, displaying considerably large effect sizes.

Conclusion
Our findings indicated beneficial roles of PA– particularly VPA– and muscular fitness in shaping cardiometabolic profile in mid-adolescence. VPA and grip strength may represent potential targets for preventive strategies tailored to adolescents in resource-limited settings.
Paediatric surgery in Uganda: current challenges and opportunities
Authors: Alberti Piero , Kisa Phyllis 
Published: May 2024

AbstractOver half of the Ugandan population is under 18-years-old. Surgical care is provided by district general hospitals, whose activity is coordinated by fourteen regional referral hospitals. Mulago National Referral Hospital in Kampala is the main tertiary centre for paediatric surgery. The paediatric surgical need is vast and unmet, with around 15% of Ugandan children having an untreated surgical condition. Most paediatric surgical procedures are performed for neonatal emergencies and trauma, with widespread task-sharing of anaesthesia services. Facilities face shortages of staff, drugs, theatre equipment, and basic amenities. Surgical treatment is delayed by the combination of delays in seeking care due to factors such as financial constraints, gender inequality and reliance on community healers, delays in reaching care due to long distances, and delays in receiving care due to overcrowding of wards and the sharing of resources with other specialties. Nonetheless, initiatives by the Ugandan paediatric surgical community over the last decade have led to major improvements. These include an increase in capacity thanks to the opening of dedicated paediatric theatres at Mulago and in regional hospitals, the start of a paediatric surgical fellowship at Mulago by the College of Surgeons of East, Central and Southern Africa (COSECSA) and development of surgical camps and courses on management of paediatric surgical emergencies to improve delivery of paediatric surgical care in rural areas.