bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic Prediction of Overall Survival for Patients with Osteosarcoma: A Retrospective Analysis of the EURAMOS-1 Clinical Trial Data
Authors: Spreafico Marta , Hazewinkel Audinga-Dea , Gelderblom Hans , Fiocco Marta
Published: June 2024

Current prediction models for patients with ostosarcoma are restricted to predictions from a single, static point in time, such as diagnosis or surgery. These approaches discard information which becomes available during follow-up and may have an impact on patient’s prognosis. This study aims at developing a dynamic prediction model providing 5-year overall survival (OS) predictions from different time points during follow-up. The developed model considers relevant baseline prognostic factors, accounting for where appropriate time-varying effects and time-varying intermediate events such as local recurrence (LR) and new metastatic disease (NM). A landmarking approach is applied to 1965 patients with high-grade resectable osteosarcoma from the EURAMOS-1 trial (NCT00143030). Results show that LR and NM negatively affected 5-year OS (HRs: 2.634, 95% CI 1.845–3.761; 8.558, 95% CI 7.367–9.942, respectively). Baseline factors with strong prognostic value (HRs > 2) included poor histological response (≥10% viable tumor), axial tumor location, and the presence of lung metastases. The effect of poor versus good histological response changed over time, becoming non-significant from 3.25 years post-surgery onwards. This time-varying effect, as well as the strong impact of disease-related time-varying variables, show the importance of including updated information collected during follow-up in the model to provide more accurate survival predictions.
Space–Time Patterns of Nest Site and Nesting Area Selection by the Italian Population of European Rollers: A 3-Year Study of a Farmland Bird Species
Authors: Meschini Angelo , Brambilla Olivia , Cannarella Sebastian , Muscianese Eugenio , Mastronardi Danila , Norante Nicola , Pascucci Mina , Pucci Mario , Sottile Francesco , Tagliagambe Sandro , Gustin Marco , Ferrarini Alessandro
Published: June 2024

The European Roller Coracias garrulus has suffered greatly from breeding habitat loss due to the renovation of old farmhouses and rural buildings and changing agricultural practices that took place extensively across Europe in the last decades. As a consequence, this species experienced a significant decline, and local extinctions of breeding populations were recorded in several European countries. We investigated nest sites and nesting area selection by the Italian Roller population during the breeding period (May–August) between 2016 and 2018. We collected 711 points from field surveys and used four types of point pattern analysis to detect space-time patterns of nest site and nesting area selection. We found that: (a) the spatial distribution of selected (i.e., occupied) nest sites was significantly nonrandom (p < 0.01) for all years and months; (b) only 2.6% of the selected nest sites was located within parks or reserves; (c) there were significant (p < 0.01) latitudinal, longitudinal, and altitudinal shifts of selected nest sites between May and August; (d) the geographical barycentres of selected nest sites shifted northward by about 80 km per month from May (southernmost barycentre) to August (northernmost barycentre); (e) four main nesting areas (7886 km2 in total) occurred in central and southern Italy, whose utilization by the European Rollers differed between months but not between years; (f) the detected nesting areas corresponded mainly to non-irrigated arable lands (41.22% of their extent) and natural grasslands (12.80%). Our results are useful to support conservation strategies for the breeding sites of this farmland species, which is not a regular visitor to protected areas in Italy.
Leveraging Sports Analytics and Association Rule Mining to Uncover Recovery and Economic Impacts in NBA Basketball
Authors: Sarlis Vangelis , Papageorgiou George , Tjortjis Christos
Published: June 2024

This study examines the multifaceted field of injuries and their impacts on performance in the National Basketball Association (NBA), leveraging a blend of Data Science, Data Mining, and Sports Analytics. Our research is driven by three pivotal questions: Firstly, we explore how Association Rule Mining can elucidate the complex interplay between players’ salaries, physical attributes, and health conditions and their influence on team performance, including team losses and recovery times. Secondly, we investigate the relationship between players’ recovery times and their teams’ financial performance, probing interdependencies with players’ salaries and career trajectories. Lastly, we examine how insights gleaned from Data Mining and Sports Analytics on player recovery times and financial influence can inform strategic financial management and salary negotiations in basketball. Harnessing extensive datasets detailing player demographics, injuries, and contracts, we employ advanced analytic techniques to categorize injuries and transform contract data into a format conducive to deep analytical scrutiny. Our anomaly detection methodologies, an ensemble combination of DBSCAN, isolation forest, and Z-score algorithms, spotlight patterns and outliers in recovery times, unveiling the intricate dance between player health, performance, and financial outcomes. This nuanced understanding emphasizes the economic stakes of sports injuries. The findings of this study provide a rich, data-driven foundation for teams and stakeholders, advocating for more effective injury management and strategic planning. By addressing these research questions, our work not only contributes to the academic discourse in Sports Analytics but also offers practical frameworks for enhancing player welfare and team financial health, thereby shaping the future of strategic decisions in professional sports.
Central Retinal Artery Occlusion Associated with Takayasu Arteritis
Authors: Mumtaz Sehreen , Wilson Claire , Vibhute Prasanna , Eggenberger Eric R. , Berianu Florentina , Abril Andy
Published: June 2024

Takayasu arteritis is a chronic inflammatory vasculitis with granulomatous panarteritis particularly impacting large vessels including the aorta and its branches, especially the subclavian arteries, with clinical manifestation dependent on the involved artery. Sequelae of the active disease vary, including stenosis, occlusions, or aneurysmal dilatations of the large vessels. The prevalence of Takayasu arteritis is higher in the Asian population and in Japan, but quite low in the United States, varying from 0.9–8.4 per million people. Ocular manifestations are rare and lead to a delay in diagnosis and appropriate treatment. Ocular manifestations include Takayasu retinopathy, anterior ischemic optic neuropathy (AION), retinal artery occlusion (RAO) and retinal vein occlusion (RVO). We present two cases in which central retinal artery occlusion (CRAO) was associated with Takayasu arteritis. CRAO is an ophthalmic emergency with an incidence of 1.9 per 100,000 person years in the United States; only 5% of cases are arteritic, which can be observed with inflammatory vasculitides secondary to the formation of immune deposits.
Intraoral Ultrasonography for the Exploration of Periodontal Tissues: A Technological Leap for Oral Diagnosis
Authors: Renaud Matthieu , Gette Mickael , Delpierre Alexis , Calle Samuel , Levassort Franck , Denis Frédéric , Rochefort Gaël Y.
Published: June 2024

Introduction: Periodontal disease is an infectious syndrome presenting inflammatory aspects. Radiographic evaluation is an essential complement to clinical assessment but has limitations such as the impossibility of assessing tissue inflammation. It seems essential to consider new exploration methods in clinical practice. Ultrasound of periodontal tissues could make it possible to visualize periodontal structures and detect periodontal diseases (periodontal pocket measurement and the presence of intra-tissue inflammation). Clinical Innovation Report: An ultrasound probe has been specially developed to explore periodontal tissues. The objective of this clinical innovation report is to present this device and expose its potential. Discussion: Various immediate advantages favor using ultrasound: no pain, no bleeding, faster execution time, and an image recording that can be replayed without having to probe the patient again. Ultrasound measurements of pocket depth appear to be as reliable and reproducible as those obtained by manual probing, as do tissue thickness measurements and the detection of intra-tissue inflammation. Conclusions: Ultrasound seems to have a broad spectrum of indications. Given the major advances offered by ultrasound imaging as a complementary aid to diagnosis, additional studies are necessary to validate these elements and clarify the potential field of application of ultrasound imaging in dentistry.
Wheat Yield Prediction Using Machine Learning Method Based on UAV Remote Sensing Data
Authors: Yang Shurong , Li Lei , Fei Shuaipeng , Yang Mengjiao , Tao Zhiqiang , Meng Yaxiong , Xiao Yonggui
Published: June 2024

Accurate forecasting of crop yields holds paramount importance in guiding decision-making processes related to breeding efforts. Despite significant advancements in crop yield forecasting, existing methods often struggle with integrating diverse sensor data and achieving high prediction accuracy under varying environmental conditions. This study focused on the application of multi-sensor data fusion and machine learning algorithms based on unmanned aerial vehicles (UAVs) in wheat yield prediction. Five machine learning (ML) algorithms, namely random forest (RF), partial least squares (PLS), ridge regression (RR), k-nearest neighbor (KNN) and extreme gradient boosting decision tree (XGboost), were utilized for multi-sensor data fusion, together with three ensemble methods including the second-level ensemble methods (stacking and feature-weighted) and the third-level ensemble method (simple average), for wheat yield prediction. The 270 wheat hybrids were used as planting materials under full and limited irrigation treatments. A cost-effective multi-sensor UAV platform, equipped with red–green–blue (RGB), multispectral (MS), and thermal infrared (TIR) sensors, was utilized to gather remote sensing data. The results revealed that the XGboost algorithm exhibited outstanding performance in multi-sensor data fusion, with the RGB + MS + Texture + TIR combination demonstrating the highest fusion performance (R2 = 0.660, RMSE = 0.754). Compared with the single ML model, the employment of three ensemble methods significantly enhanced the accuracy of wheat yield prediction. Notably, the third-layer simple average ensemble method demonstrated superior performance (R2 = 0.733, RMSE = 0.668 t ha−1). It significantly outperformed both the second-layer ensemble methods of stacking (R2 = 0.668, RMSE = 0.673 t ha−1) and feature-weighted (R2 = 0.667, RMSE = 0.674 t ha−1), thereby exhibiting superior predictive capabilities. This finding highlighted the third-layer ensemble method’s ability to enhance predictive capabilities and refined the accuracy of wheat yield prediction through simple average ensemble learning, offering a novel perspective for crop yield prediction and breeding selection.
Research on Variable Parameter Color Image Encryption Based on Five-Dimensional Tri-Valued Memristor Chaotic System
Authors: Wang Pan , Ding Lina
Published: June 2024

To construct a chaotic system with complex characteristics and to improve the security of image data, a five-dimensional tri-valued memristor chaotic system with high complexity is innovatively constructed. Firstly, a pressure-controlled tri-valued memristor on Liu’s pseudo-four-wing chaotic system is introduced. Through analytical methods, such as Lyapunov exponential map, bifurcation map and attractor phase diagram, it is demonstrated that the new system has rich dynamical behaviors with periodic limit rings varying with the coupling parameter of the system, variable airfoil phenomenon as well as transient chaotic phenomenon of chaos-periodic depending on the system parameter and chaos-quasi-periodic depending on the memristor parameter. The system is simulated with dynamic circuits based on Simulink. Secondly, the differently structured synchronous controls of chaotic systems are realized using a nonlinear feedback control method. Finally, based on the newly constructed five-dimensional chaotic system, a variable parameter color image encryption scheme is proposed to iteratively generate varying chaotic pseudo-random sequences by varying the system parameters, which will be used for repetition-free disambiguation, additive modulo left-shift diffusion and DNA encryption for the three components of RGB of the color image after chunking. The simulation results are analyzed by histogram, information entropy, adjacent pixel correlation, etc., and the images are tested using differential attack, noise attack and geometric attack, as well as analyzing the PSNR and SSIM of the decrypted image quality. The results show that the encryption method has a certain degree of security and can be applied to medical, military and financial fields with more complex environmental requirements.
Leveraging Indoor Localization Data: The Transactional Area Network (TAN)
Authors: Nikolakopoulos Anastasios , Psychas Alexandros , Litke Antonios , Varvarigou Theodora
Published: June 2024

The fields of indoor localization and positioning have seen extensive research in recent years. Their scientific soundness is of great importance, as information about an entity’s location in indoor environments can lead to innovative services and products. Various techniques and frameworks have been proposed, some of which are already in practical use. This article emphasizes the value of indoor localization data and proposes the adoption of a new virtual field known as the ‘Transactional Area Network’ (TAN). By presenting a custom yet simple real-time, peer-to-peer (and therefore decentralized) software implementation that provides positioning information to users via their smart devices, this article demonstrates the potential value of TAN. Finally, it explores how TAN can increase the adoption rate of indoor positioning applications, enhance interactions between people in nearby locations and therefore amplify data generation.
A Wideband Timing Mismatch Calibration Design for Time-Interleaved Analog-to-Digital Converters with Fast Convergence
Authors: Huang Guojing , Xu Dong , Gao Peng , Zhou Min , Liu Jiarui , Wang Zhiyu
Published: June 2024

This paper presents a design for timing mismatch calibration in a TIADC (Time-Interleaved Analog-to-Digital Converter) with wideband inputs. By exploiting the approximately linear relationship between the autocorrelation properties of sub-ADCs and timing mismatch, we achieve rapid convergence of error estimation. A low-cost detection method is proposed based on the convergent monotonicity of the Least Mean Square (LMS) algorithm, which can automatically correct the calibration direction when the input signal goes beyond the Nyquist zone. Physical test results indicate that the spurs caused by timing mismatch can be suppressed by 26–30 dB using the proposed method.
Efficient Adversarial Attack Based on Moment Estimation and Lookahead Gradient
Authors: Hong Dian , Chen Deng , Zhang Yanduo , Zhou Huabing , Xie Liang , Ju Jianping , Tang Jianyin
Published: June 2024

Adversarial example generation is a technique that involves perturbing inputs with imperceptible noise to induce misclassifications in neural networks, serving as a means to assess the robustness of such models. Among the adversarial attack algorithms, momentum iterative fast gradient sign Method (MI-FGSM) and its variants constitute a class of highly effective offensive strategies, achieving near-perfect attack success rates in white-box settings. However, these methods’ use of sign activation functions severely compromises gradient information, which leads to low success rates in black-box attacks and results in large adversarial perturbations. In this paper, we introduce a novel adversarial attack algorithm, NA-FGTM. Our method employs the Tanh activation function instead of the sign which can accurately preserve gradient information. In addition, it utilizes the Adam optimization algorithm as well as the Nesterov acceleration, which is able to stabilize gradient update directions and expedite gradient convergence. Above all, the transferability of adversarial examples can be enhanced. Through integration with data augmentation techniques such as DIM, TIM, and SIM, NA-FGTM can further improve the efficacy of black-box attacks. Extensive experiments on the ImageNet dataset demonstrate that our method outperforms the state-of-the-art approaches in terms of black-box attack success rate and generates adversarial examples with smaller perturbations.
Mitigation Strategy of Neutral-Point DC for Transformer Caused by Metro Stray Currents
Authors: Wang Aimin , Lin Sheng , Wu Guoxing , Li Xiaopeng
Published: June 2024

Metro stray currents flowing into neutral-point-grounded transformers can cause serious direct current (DC) bias. Affected by both metro train and urban power grid operations, transformer neutral-point DC caused by metro stray current is complex, dynamic, and time-varying, which changes the DC bias risk level of transformers. Thus, just installing blocking devices (BDs) at transformer neutral points with high instantaneous DC may make it difficult to comprehensively mitigate DC bias and lead to increased BD installation. To solve this, through optimizing BD installation placements, a mitigation method for transformer DC bias is proposed. In the proposed method, the DC bias risk level and BD installation number are included in the constraint and objective functions. To evaluate the risk level of transformer DC bias, four indicators are proposed considering the distribution characteristics of neutral DC. To optimize the BD installation placements, the effects of both the metro train dynamic operation and the operation topology of the urban power grid on neutral DCs are considered. The Monte Carlo method is used to sample the train operation conditions and a relation matrix among transformers is established. Applying the method to a certain power system, the result of BD installation placements shows that the transformers supplying the metro system must have BDs installed at their neutral points.
A Model for Detecting Abnormal Elevator Passenger Behavior Based on Video Classification
Authors: Lei Jingsheng , Sun Wanfa , Fang Yuhao , Ye Ning , Yang Shengying , Wu Jianfeng
Published: June 2024

In the task of human behavior detection, video classification based on deep learning has become a prevalent technique. The existing models are limited due to an inadequate understanding of behavior characteristics, which restricts their ability to achieve more accurate recognition results. To address this issue, this paper proposes a new model, which is an improvement upon the existing PPTSM model. Specifically, our model employs a multi-scale dilated attention mechanism, which enables the model to integrate multi-scale semantic information and capture characteristic information of abnormal human behavior more effectively. Additionally, to enhance the characteristic information of human behavior, we propose a gradient flow feature information fusion module that integrates high-level semantic features with low-level detail features, enabling the network to extract more comprehensive features. Experiments conducted on an elevator passenger dataset containing four abnormal behaviors (door picking, jumping, kicking, and door blocking) show that the top-1 Acc of our model is improved by 10% compared to the PPTSM model, reaching 95%. Moreover, experiments with four publicly available datasets(UCF24, UCF101, HMDB51, and the Something-Something-v1 dataset) demonstrate that our method achieves results superior to PPTSM by 6.8%, 6.1%, 21.2%, and 3.96%, respectively.
Multi-Objective Optimization towards Heat Dissipation Performance of the New Tesla Valve Channels with Partitions in a Liquid-Cooled Plate
Authors: Xu Liang , Lin Hongwei , Hu Naiyuan , Xi Lei , Li Yunlong , Gao Jianmin
Published: June 2024

The utilization of liquid-cooled plates has been increasingly prevalent within the thermal management of batteries for new energy vehicles. Using Tesla valves as internal flow channels of liquid-cooled plates can improve heat dissipation characteristics. However, conventional Tesla valve flow channels frequently experience challenges such as inconsistencies in heat dissipations and unacceptably high levels of pressure loss. In light of this, this paper proposes a new type of Tesla valve with partitions, which is used as internal channel for liquid-cooled plate. Its purpose is to solve the shortcomings of existing flow channels. Under the working conditions of Reynolds number equal to 1000, the neural network prediction-NSGA-II multi-objective optimization method is used to optimize the channel structural parameters. The objective is to identify the optimal structural configuration that exhibits the greatest Nusselt number while simultaneously exhibiting the lowest Fanning friction factor. The variables to consider are the half of partition thickness H, partition length L, and the fillet radius R. The study result revealed that the optimal parameter combination consisted of H = 0.25 mm, R = 1.253 mm, L = 0.768 mm, which demonstrated the best performance. The Fanning friction factor of the optimized flow channel is substantially reduced compared to the reference channel, reducing by approximately 16.4%. However, the Nusselt number is not noticeably increased, increasing by only 0.9%. This indicates that the optimized structure can notably reduce the fluid’s friction resistance and pressure loss and slightly enhance the heat dissipation characteristics.
Renewable Adoption, Energy Reliance, and CO2 Emissions: A Comparison of Developed and Developing Economies
Authors: Bi Zhaoming , Guo Renyu , Khan Rabnawaz
Published: June 2024

Emerging economies and ecosystems rely heavily on fossil fuels, and a country’s energy dependence is a strong indicator of its reliance on foreign suppliers. This study investigates the impact of energy dependence on energy intensity, CO2 emission intensity, and the exploitation of renewable resources in 35 developing and 20 developed nations. It also explores the correlation between renewable energy, GDP growth, and CO2 emissions. This study utilizes the Generalized Linear Model (GLM) and the Robust Least Squares (RLS) method to investigate the negative correlation between renewable energy and policymakers in established and emerging economies. It also employs distinctive linear panel estimation techniques spanning from 1970 to 2022. This study examines the impact of renewable energy on economic growth, energy consumption, and CO2 emissions across four continents. Developing countries see an increase in per capita CO2 emissions when their utilization of renewable energy exceeds their capacity. Even with the introduction of several proxies for renewable energy use using changed techniques, this discovery remains valid. Moreover, this is particularly crucial for industrialized nations with well-established institutions. Energy dependency has increased the energy and carbon intensity needed for expansion across all components, which is surprising. The regional study discovered a spillover impact in most regions, indicating that the consequences of energy reliance are similar in neighboring countries. Regional energy exchange unions play a vital role in reducing the adverse environmental and economic impacts of energy dependence, which is essential for the growth of the renewable energy sector and the decrease in greenhouse gas emissions. Undeveloped countries need to enhance their investment in research and development to advance technologically.
CFD Calculation of Natural Convection Heat Transmission in a Three-Dimensional Pool with Hemispherical Lower Head
Authors: Mao Zhangliang , Chen Yuqing , Wang Wei , Cai Qi , Yuan Xianbao , Zhou Jianjun , Du Xiaochao , Zhang Binhang , Zhang Yonghong , Xiao Renzheng
Published: June 2024

The integrity of a pressure vessel (PRV) is affected by the decay heat of the molten pool in the lower head, so it is very important to study the natural convection heat transmission in the lower head. Scholars from all over the world have carried out a lot of experimental studies and calculations to determine the convection mechanism and heat transmission characteristics of the molten pool. Most of them were based on the empirical formula of convective heat transmission on the wall of a hemispherical molten pool based on two-dimensional slice experiments and simulation calculations. In this study, FLUENT 2021R1 software was used to simulate the three-dimensional convective heat transmission process of the hemispherical molten pool, and the temperature, velocity and wall heat transmission coefficients of the flow field were analyzed. The results were in good agreement with experimental data from UCLA (University of California, Los Angeles). Through research on the heat transmission of the lower head, the results showed that in the region where the wall angle was θ between approximately 72 and 90 degrees, heat transmission coefficients had larger fluctuations, and a more reasonable empirical relation was proposed. Comparing between the simulation results of CFD and the two-dimensional empirical formula, it was found that the latter one was smaller under the same θ angle condition. Finally, the convection phenomena of different external temperatures were simulated, and the main factors affecting the flow field by temperature were analyzed.
Hydrogen Jet Flame Simulation and Thermal Radiation Damage Estimation for Leakage Accidents in a Hydrogen Refueling Station
Authors: Fu Xiang , Yan Xianglin , Chen Shiyu , Song Chunyan , Xiao Zhili , Luo Hao , Wan Jiaqi , Yang Tianqi , Xu Nianfeng , Xiao Jinsheng
Published: June 2024

With the rapid development of hydrogen energy worldwide, the number of hydrogen energy facilities, such as hydrogen refueling stations, has grown rapidly in recent years. However, hydrogen is prone to leakage accidents during use, which could lead to hazards such as fires and explosions. Therefore, research on the safety of hydrogen energy facilities is crucial. In this paper, a study of high-pressure hydrogen jet flame accidents is conducted for a proposed integrated hydrogen production and refueling station in China. The effects of leakage direction and leakage port diameter on the jet flame characteristics are analyzed, and a risk assessment of the flame accident is conducted. The results showed that the death range perpendicular to the flame direction increased from 2.23 m to 5.5 m when the diameter of the leakage port increased from 4 mm to 10 mm. When the diameter of the leakage port is larger than 8 mm, the equipment on the scene will be within the boundaries of the damage. The consequences of fire can be effectively mitigated by a reasonable firewall setup to ensure the overall safety of the integrated station.
Efficiency Improvement of Darrieus Wind Turbine Using Oscillating Gurney Flap
Authors: Zereg Alaeddine , Aksas Mounir , Bouzaher Mohamed Taher , Laghrouche Salah , Lebaal Nadhir
Published: June 2024

In this work, a new model of Darrieus wind turbines with an oscillating gurney flap (OGF) is proposed. A detailed 2D computational fluid dynamics (CFD) investigation is carried out using ANSYS-Fluent 22.0 to assess the turbine performance. The OGF can alter its position between the upper and lower blade surfaces during the turbine rotation. Equations related to the combined motion are implemented through a user-defined function (UDF). The proposed model is validated where a good coincidence is achieved. The overset dynamic mesh method is used. It was found that a judicious synchronization of OGF and turbine blades creates beneficial vortex interactions, which correct the pressure distribution and lead to an overall improvement in the lift force. The magnitude of the improvement is highly dependent on the OGF length and the phase motion φ. The average torque coefficient Cm for the controlled case increased by more than 19% in comparison with the nominal case.
Comparison of Libration- and Precession-Driven Flows: From Linear Responses to Broadband Dynamics
Authors: Wu Ke , Welfert Bruno D. , Lopez Juan M.
Published: June 2024

Libration and precession are different body forces that are ubiquitous in many rapidly rotating systems, particularly in geophysical and astrophysical flows. Libration is a modulation of the background rotation magnitude, whereas precession is a modulation of the background rotation direction. Assessing the consequences of these body forces in large-scale flows is challenging. The Ekman number, the ratio of the rotation time scale to the viscous time scale quantifying the rotation speed, is extremely small, leading to extremely thin and intense shear layers in the flows even when the amplitudes of the body forces are very small. We consider the consequences of libration and precession numerically in a geometrically simple container, a cube, which lends itself to very efficient, accurate, and robust numerical treatment, with the axis of rotation passing through opposite vertices, so that all walls of the cube are at oblique angles to the rotation axis. This results in the geometric focusing of inertial wavebeams reflecting off the walls, whereby the energy density of the wavebeams increases along with the magnitude of their wavevector. The nature of this focusing depends on the forcing frequency but not on the body force. In the inviscid setting, wavebeams form infinitesimally thin vortex sheets, and their energy density becomes unbounded upon focusing. We present linear inviscid ray tracing to set the scene for the focusing of wavebeams and then consider viscous problems at an Ekman number that is typical of current state-of-the-art laboratory experiments. We begin by considering the linear responses, which are comprised of focusing viscous shear layers, of which their details are mostly captured via ray tracing, and particular solutions accounting for the body forces. These have complicated spatio-temporal structures, which differ for libration and precession. Increasing the forcing amplitude from zero introduces nonlinear interactions, enhances the focusing effects via vortex tilting and stretching when the shear layers reflect at the walls, and also introduces temporal superharmonics and a mean flow. When the magnitude of the mean flow is within a few percent of the magnitude of the instantaneous flow, instabilities breaking the spatio-temporal symmetries set in. These are localized in the oscillatory boundary layers where the reflections are concentrated and introduce broadband dynamics in the boundary layers, with additional inertial wavebeams emitted into the interior. The details again depend on the specifics of the body forces.
Carbon Nanotube-Doped 3D-Printed Silicone Electrode for Manufacturing Multilayer Porous Plasticized Polyvinyl Chloride Gel Artificial Muscles
Authors: Luo Bin , Lu Hanjing , Zhong Yiding , Zhu Kejun , Wang Yanjie
Published: June 2024

Plasticized polyvinyl chloride (PVC) gel has large deformation under an applied external electrical field and high driving stability in air and is a candidate artificial muscle material for manufacturing a flexible actuator. A porous PVC gel actuator consists of a mesh positive pole, a planar negative pole, and a PVC gel core layer. The current casting method is only suitable for manufacturing simple 2D structures, and it is difficult to produce multilayer porous structures. This study investigated the feasibility of a 3D-printed carbon nanotube-doped silicone electrode for manufacturing multilayer porous PVC gel artificial muscle. Carbon nanotube-doped silicone (CNT-PDMS) composite inks were developed for printing electrode layers of PVC gel artificial muscles. The parameters for the printing plane and mesh electrodes were explored theoretically and experimentally. We produced a CNT-PDMS electrode and PVC gel via integrated printing to manufacture multilayer porous PVC artificial muscle and verified its good performance.
Neutrophils in the Focus: Impact on Neuroimmune Dynamics and the Gut–Brain Axis
Authors: Krsek Antea , Baticic Lara
Published: June 2024

The growing field of gut–brain axis research offers significant potential to revolutionize medical practices and improve human well-being. Neutrophils have emerged as key players in gut–brain inflammation, contributing to the relocation of inflammatory cells from the gut to the brain and exacerbating neuroinflammation in conditions, such as inflammatory bowel disease and neurodegenerative diseases. The intricate network of molecular and functional connections that interlinks the brain with the gastrointestinal system is characterized by complex signaling pathways. Understanding the complex interplay among the microbiota, gut, and brain offers unparalleled opportunities to develop novel therapeutic interventions for neurological disorders and improve overall health outcomes. The aim of this review was to comprehensively summarize current knowledge and future perspectives regarding the multifaceted role of neutrophils and their impact on the neuroimmune dynamics in the context of the gut–brain axis.
Preliminary Report of Nationwide COVID-19 Vaccine Compensation in Taiwan
Authors: Lu Yi-An , Huang Fu-Yuan , Chi Hsin , Lin Chien-Yu , Chiu Nan-Chang
Published: June 2024

The potential adverse effects of coronavirus disease 2019 (COVID-19) vaccinations raise public concerns. Data from Taiwan’s Vaccine Injury Compensation Program (VICP) can provide valuable insights. This study analyzed the preliminary application data for COVID-19 vaccine compensation in Taiwan’s VICP, focusing on applicants receiving vaccines between March 2021 and June 2022. Among the 2941 adverse events, 113 cases (3.8%) were deemed causally associated with vaccination, 313 (10.6%) were indeterminate, and 2515 (85.5%) had no causal association. Nearly half (47.6%) of the applicants were over 60 years old, and 76.6% had a history of pre-existing chronic diseases. Among the 426 vaccine-associated or indeterminate cases, the most common causes were hematological diseases and thrombosis. There were 920 mortality cases reported, and 97.4% were unassociated with vaccination. Only five deaths were judged to be associated with the COVID-19 vaccination, all involving the adenovirus vector vaccine and thrombosis with thrombocytopenia syndrome. In conclusion, most compensation applications were not causally linked to vaccination. Compared to other countries, the number of applications in Taiwan’s VICP is relatively high. These findings may indicate a need to adjust the application requirements for compensation in Taiwan’s program.
The Biomechanics of Musculoskeletal Tissues during Activities of Daily Living: Dynamic Assessment Using Quantitative Transmission-Mode Ultrasound Techniques
Authors: Wearing Scott C. , Hooper Sue L. , Langton Christian M. , Keiner Michael , Horstmann Thomas , Crevier-Denoix Nathalie , Pourcelot Philippe
Published: June 2024

The measurement of musculoskeletal tissue properties and loading patterns during physical activity is important for understanding the adaptation mechanisms of tissues such as bone, tendon, and muscle tissues, particularly with injury and repair. Although the properties and loading of these connective tissues have been quantified using direct measurement techniques, these methods are highly invasive and often prevent or interfere with normal activity patterns. Indirect biomechanical methods, such as estimates based on electromyography, ultrasound, and inverse dynamics, are used more widely but are known to yield different parameter values than direct measurements. Through a series of literature searches of electronic databases, including Pubmed, Embase, Web of Science, and IEEE Explore, this paper reviews current methods used for the in vivo measurement of human musculoskeletal tissue and describes the operating principals, application, and emerging research findings gained from the use of quantitative transmission-mode ultrasound measurement techniques to non-invasively characterize human bone, tendon, and muscle properties at rest and during activities of daily living. In contrast to standard ultrasound imaging approaches, these techniques assess the interaction between ultrasound compression waves and connective tissues to provide quantifiable parameters associated with the structure, instantaneous elastic modulus, and density of tissues. By taking advantage of the physical relationship between the axial velocity of ultrasound compression waves and the instantaneous modulus of the propagation material, these techniques can also be used to estimate the in vivo loading environment of relatively superficial soft connective tissues during sports and activities of daily living. This paper highlights key findings from clinical studies in which quantitative transmission-mode ultrasound has been used to measure the properties and loading of bone, tendon, and muscle tissue during common physical activities in healthy and pathological populations.
Molecular Cloning and Expression Analysis of Geranyllinalool Synthase Gene (SgGES) from Salvia guaranitica Plants
Authors: Abdelhameed Ahmed Ali , Eissa Mohamed A. , El-kholy Ragab I. , Darwish Doaa Bahaa Eldin , Abeed Amany H. A. , Soudy Fathia A. , Alyamani Amal Ahmed , Abdelmigid Hala M. , Morsi Maissa M. , Zhao Jian , Ali Mohammed , Zayed Muhammad
Published: June 2024

Salvia guaranitica is considered one of the most significant medicinal and aromatic herbs in terms of nutritional and medical benefits due to its wealth of important active components. Among these compounds, terpenoids are the most prominent and abundant, particularly monoterpenes (C10), sesquiterpenes (C15), and diterpenes (C20). They are biologically advantageous to plants and perform a multitude of functions. The current study aimed to clone the S. guaranitica gene that encodes for geranyllinalool synthases (SgGES, EC: 4.2.3.144), with consideration for these features. The open reading frame of the 867-amino-acid protein encoded by SgGES consists of 2.721 base pairs. In addition, the SgGES protein has five domains that belong to the terpene synthase family, which are related to the terpene and terpenoid synthase domains. We manipulated and overexpressed the SgGES gene in Nicotiana tabacum to explore its function. When compared to the GUS control, the transgenic N. tabacum plants displayed an increase in leaf production and diameter when compared with the wild-type plants. Finally, analysis of transgenic plants using gas chromatography/mass spectrometry (GC-MS) showed that SgGES is responsible for producing various terpene species, especially diterpenes.
Scaling up a Positive Safety Culture among Construction Small and Medium-Sized Enterprises in Ghana
Authors: Adzivor Eric , Emuze Fidelis , Ahiabu Moses , Kusedzi Moses
Published: June 2024

The Ghanaian construction industry faces challenges in managing safety, especially for small and medium-sized enterprises (SMEs) that need more resources. This research addressed the critical need for a positive safety culture framework specifically designed for SMEs in Ghana. The study adopts the Delphi research approach, which involves a series of questionnaire ‘rounds’ to gather and refine information and develop a collaborative safety culture framework with SME stakeholders. The study employed a mixed-methods strategy, harnessing quantitative and qualitative data to meet the research goals. The critical components of the developed framework included safety commitment, adaptability, information, awareness, culture, and performance. The research offered evidence-based recommendations for effective positive safety practices across Ghana’s SMEs by analysing the relationship between these interventions and safety outcomes. Applying the framework should reduce workplace accidents and foster a positive safety culture that aligns with international best practices.
A Novel Flexible Geographically Weighted Neural Network for High-Precision PM2.5 Mapping across the Contiguous United States
Authors: Wang Dongchao , Cao Jianfei , Zhang Baolei , Zhang Ye , Xie Lei
Published: June 2024

Air quality degradation has triggered a large-scale public health crisis globally. Existing machine learning techniques have been used to attempt the remote sensing estimates of PM2.5. However, many machine learning models ignore the spatial non-stationarity of predictive variables. To address this issue, this study introduces a Flexible Geographically Weighted Neural Network (FGWNN) to estimate PM2.5 based on multi-source remote sensing data. FGWNN incorporates the Flexible Geographical Neuron (FGN) and Geographical Activation Function (GWAF) within the framework of Artificial Neural Network (ANN) to capture the intricate spatial non-stationary relationships among predictive variables. A robust air quality remote sensing estimation model was constructed using remote sensing data of Aerosol Optical Depth (AOD), Normalized Difference Vegetation Index (NDVI), Temperature (TMP), Specific Humidity (SPFH), Wind Speed (WIND), and Terrain Elevation (HGT) as inputs, and Ground-Based PM2.5 as the observation. The results indicated that FGWNN successfully generates PM2.5 remote sensing data with a 2.5 km spatial resolution for the contiguous United States (CONUS) in 2022. It exhibits higher regression accuracy compared to traditional ANN and Geographically Weighted Regression (GWR) models. FGWNN holds the potential for applications in high-precision and high-resolution remote sensing scenarios.
Inflammatory Changes after Medical Suppression of Suspected Endometriosis for Implantation Failure: Preliminary Results
Authors: Lessey Bruce A. , Dong Allan , Deaton Jeffrey L. , Angress Daniel , Savaris Ricardo F. , Walker Stephen J.
Published: June 2024

Unexplained euploid embryo transfer failure (UEETF) is a frustrating and unanswered conundrum accounting for 30 to 50% of failures in in vitro fertilization using preimplantation genetic testing for aneuploidy (PGT-A). Endometriosis is thought by many to account for most of such losses and menstrual suppression or surgery prior to the next transfer has been reported to be beneficial. In this study, we performed endometrial biopsy in a subset of women with UEETF, testing for the oncogene BCL6 and the histone deacetylase SIRT1. We compared 205 PGT-A cycles outcomes and provide those results following treatment with GnRH agonist versus controls (no treatment). Based on these and previous promising results, we next performed a pilot randomized controlled trial comparing the orally active GnRH antagonist, elagolix, to oral contraceptive pill (OCP) suppression for 2 months before the next euploid embryo transfer, and monitored inflammation and miRNA expression in blood, before and after treatment. These studies support a role for endometriosis in UEETF and suggest that medical suppression of suspected disease with GnRH antagonist prior to the next transfer could improve success rates and address underlying inflammatory and epigenetic changes associated with UEETF.
Effect of HVEM/CD160 Variations on the Clear Cell Renal Carcinoma Risk and Overall Survival
Authors: Andrzejczak Anna , Małkiewicz Bartosz , Tupikowski Krzysztof , Ptaszkowski Kuba , Szydełko Tomasz , Karabon Lidia
Published: June 2024

Renal cell carcinoma (RCC) accounts for approximately 90–95% of all kidney cancers in adults, with clear cell RCC (ccRCC) being the most frequently identified subtype. RCC is known for its responsiveness to immunotherapy, making it an area of significant research interest. Immune checkpoint (IC) molecules, which regulate immune surveillance, are established therapeutic targets in RCC. The aim of this study was to analyze the influence of HVEM and CD160 gene polymorphisms on ccRCC susceptibility and patient overall survival (OS) over a ten-year period of observation. We genotyped three HVEM single nucleotide polymorphisms (SNPs): rs1886730, rs2234167, and rs8725, as well as two CD160 SNPs: rs744877 and rs2231375, in 238 ccRCC patients and 521 controls. Our findings indicated that heterozygosity within rs2231375 and/or rs2234167 increases ccRCC risk. Furthermore, in women, heterozygosity within HVEM SNPs rs8725 and rs1886730 is also associated with an increased ccRCC risk. The presence of a minor allele for rs1886730, rs2234167, rs8725, and rs2231375 was also correlated with certain clinical features of ccRCC. Moreover, rs1886730 was found to be associated with OS. In conclusion, our study highlights an association between HVEM and CD160 polymorphisms and the risk of developing ccRCC as well as OS.
LPA-Induced Thromboxane A2-Mediated Vasoconstriction Is Limited to Poly-Unsaturated Molecular Species in Mouse Aortas
Authors: Vén Krisztina , Besztercei Balázs , Janovicz Anna , Karsai Noémi , Chun Jerold , Tigyi Gábor , Benyó Zoltán , Ruisanchez Éva
Published: June 2024

We have previously reported that, in aortic rings, 18:1 lysophosphatidic acid (LPA) can induce both vasodilation and vasoconstriction depending on the integrity of the endothelium. The predominant molecular species generated in blood serum are poly-unsaturated LPA species, yet the vascular effects of these species are largely unexplored. We aimed to compare the vasoactive effects of seven naturally occurring LPA species in order to elucidate their potential pathophysiological role in vasculopathies. Vascular tone was measured using myography, and thromboxane A2 (TXA2) release was detected by ELISA in C57Bl/6 mouse aortas. The Ca2+-responses to LPA-stimulated primary isolated endothelial cells were measured by Fluo-4 AM imaging. Our results indicate that saturated molecular species of LPA elicit no significant effect on the vascular tone of the aorta. In contrast, all 18 unsaturated carbon-containing (C18) LPAs (18:1, 18:2, 18:3) were effective, with 18:1 LPA being the most potent. However, following inhibition of cyclooxygenase (COX), these LPAs induced similar vasorelaxation, primarily indicating that the vasoconstrictor potency differed among these species. Indeed, C18 LPA evoked a similar Ca2+-signal in endothelial cells, whereas in endothelium-denuded aortas, the constrictor activity increased with the level of unsaturation, correlating with TXA2 release in intact aortas. COX inhibition abolished TXA2 release, and the C18 LPA induced vasoconstriction. In conclusion, polyunsaturated LPA have markedly increased TXA2-releasing and vasoconstrictor capacity, implying potential pathophysiological consequences in vasculopathies.