bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Characteristics and Mechanism of Inorganic Nitrogen Nutrients Preferential Assimilation by Phaeocystis globosa
Authors: Guo Honghong , Wang Wentao , Han Jishu , Zhu Jianan , Wang Zhongshi , He Liyan , Song Xiuxian , Yu Zhiming
Published: June 2024

Phaeocystis globosa is an important harmful algal species that is globally distributed. Previous studies have indicated that P. globosa preferentially uptake nitrate, but the underlying mechanism is still unclear. To further verify this preference and reveal the underlying mechanism, the assimilation rates of nitrate and ammonium by P. globosa at different concentrations was quantitatively studied by using a nitrogen stable isotope (15N) tracer technique, and the regulatory mechanism was determined from the physiological and biochemical responses. The findings revealed that the preferential assimilation of nitrate by P. globosa was influenced by the ambient ammonium concentration. When the ambient concentration of ammonium was less than approximately 3.5 μmol·L−1, the assimilation rates of nitrate form P. globosa were as high as 1.05 × 10−5 μmol·L−1·h−1·cell−1. Even though the nitrate assimilation in P. globosa was inhibited at ammonium concentrations greater than this threshold, nitrate assimilation could not be completely suppressed. The activity of NR and the expression of related genes in P. globosa were also affected by ammonium. In addition, 15N signals originally labeled nitrate accumulated in ammonium. This indicated that P. globosa was likely to reduce excess nitrate to ammonium and subsequently release it into the substrate, which might be an important energy dissipation mechanism for P. globosa. These results expand the classical understanding of the utilization of nitrogen nutrients by marine phytoplankton, and offer valuable resources for comprehending the mechanism of harmful algal blooms.
Fusion of Multi-Layer Attention Mechanisms and CNN-LSTM for Fault Prediction in Marine Diesel Engines
Authors: Sun Jiawen , Ren Hongxiang , Duan Yating , Yang Xiao , Wang Delong , Tang Haina
Published: June 2024

Timely and effective maintenance is imperative to minimize operational disruptions and ensure the reliability of marine vessels. However, given the low early warning rates and poor adaptability under complex conditions of previous data-driven fault prediction methods, this paper presents a hybrid deep learning model based on multi-layer attention mechanisms for predicting faults in a marine diesel engine. Specifically, this hybrid model first introduces a Convolutional Neural Network (CNN) and self-attention to extract local features from multi-feature input sequences. Then, we utilize Long Short-Term Memory (LSTM) and multi-head attention to capture global correlations across time steps. Finally, the hybrid deep learning model is integrated with the Exponential Weighted Moving Average (EWMA) to monitor the operational status and predict potential faults in the marine diesel engine. We conducted extensive evaluations using real datasets under three operating conditions. The experimental results indicate that the proposed method outperforms the current state-of-the-art methods. Moreover, ablation studies and visualizations highlight the importance of fusing multi-layer attention, and the results under various operating conditions and application scenarios demonstrate that this method possesses predictive accuracy and broad applicability. Hence, this approach can provide decision support for condition monitoring and predictive maintenance of marine mechanical systems.
Influence of Well Layout on Submarine Slope Stability during Natural Gas Hydrate Development
Authors: Zhou Guangxu , Yan Chuanliang , Li Zhenqi , He Yufa , Tian Zheng , Cheng Yuanfang
Published: June 2024

The exploitation of natural gas hydrates (NGHs) reduces the reservoir strength and increases the effective stress, which may trigger stratum settlement and submarine landslides. In particular, commercial-scale production requires the exploitation of NGHs through multiple wells at the same time, which increases the submarine landslide risk. Therefore, it is necessary to study the influences of well layouts on the stability of submarine slopes in the exploitation of NGHs. To this end, a thermo-fluid–solid multifield coupling model that considers the phase change of NGHs in the exploitation process was established. Considering the finite element strength reduction method, an evaluation model was built to analyze the slope stability in the multiwell exploitation of NGHs with the depressurization method. The results show that because NGH decomposition reduces the reservoir strength, the reservoir is compressed overall, and plastic yield zones first occur in the NGH decomposition zone and the slope toe. Finally, a coalesced plastic yield zone propagates throughout the slope. When exploiting NGHs, slope stability is enhanced with increasing well spacing in a multiwell pattern. The linear well layout along the slope dip direction is more conducive to maintaining slope stability than that perpendicular to the slope dip direction. The slope stability decreases with increasing well spacing density but increases with decreasing slope dip. The influence of well layout on submarine slope stability during natural gas hydrate development is studied, which provides a basis for well layouts during gas hydrate exploitation.
Ultrasonographic Synovitis Is Associated with the Development of Joint Destruction in Patients with Psoriatic Arthritis
Authors: Yamada Yutaro , Inui Kentaro , Mandai Koji , Mamoto Kenji , Koike Tatsuya , Tateishi Chiharu , Tsuruta Daisuke , Okano Tadashi
Published: June 2024

Background: Psoriatic arthritis (PsA) is characterized by enthesitis. As persistent inflammation around joints results in bone and cartilage destruction and physical impairment, a detailed assessment of inflammation is essential. We previously reported the difference between clinical assessment (tenderness) and ultrasound (US) assessment (inflammation) of entheses. Herein, we investigated whether clinical or US assessment of joints and entheses can predict the progression of joint destruction in Japanese patients with PsA. Methods: Thirty joints and 14 entheses in 47 patients were assessed using US and clinical examination. The US greyscale (GS) and power Doppler (PD) scores at the ultrasonographic synovitis, the US active enthesitis count, and the clinical tender joint/entheses count were assessed. Additionally, the yearly radiographic progression of the Sharp–van der Heijde scoring method for PsA was assessed. Their correlations were investigated. Results: About half of the patients with PsA experienced joint destruction during a follow-up period of 20.4 months. Progression of joint destruction in patients with PsA only correlated with joint GS and PD scores, reflecting the severity of ultrasonographic synovitis, not with the tender joint/entheses count. Conclusions: US examinations are essential for preventing joint destruction and physical impairment in patients with PsA.
AI-Based Pedestrian Detection and Avoidance at Night Using Multiple Sensors
Authors: Kulhandjian Hovannes , Barron Jeremiah , Tamiyasu Megan , Thompson Mateo , Kulhandjian Michel
Published: June 2024

In this paper, we present a pedestrian detection and avoidance scheme utilizing multi-sensor data collection and machine learning for intelligent transportation systems (ITSs). The system integrates a video camera, an infrared (IR) camera, and a micro-Doppler radar for data acquisition and training. A deep convolutional neural network (DCNN) is employed to process RGB and IR images. The RGB dataset comprises 1200 images (600 with pedestrians and 600 without), while the IR dataset includes 1000 images (500 with pedestrians and 500 without), 85% of which were captured at night. Two distinct DCNNs were trained using these datasets, achieving a validation accuracy of 99.6% with the RGB camera and 97.3% with the IR camera. The radar sensor determines the pedestrian’s range and direction of travel. Experimental evaluations conducted in a vehicle demonstrated that the multi-sensor detection scheme effectively triggers a warning signal to a vibrating motor on the steering wheel and displays a warning message on the passenger’s touchscreen computer when a pedestrian is detected in potential danger. This system operates efficiently both during the day and at night.
Mapping Dryland Ecosystems Using Google Earth Engine and Random Forest: A Case Study of an Ecologically Critical Area in Northern China
Authors: Li Shuai , Guo Pu , Sun Fei , Zhu Jinlei , Cao Xiaoming , Dong Xue , Lu Qi
Published: June 2024

Drylands are characterized by unique ecosystem types, sparse vegetation, fragile environments, and vital ecosystem services. The accurate mapping of dryland ecosystems is essential for their protection and restoration, but previous approaches primarily relied on modifying land use data derived from remote sensing, lacking the direct utilization of latest remote sensing technologies and methods to map ecosystems, especially failing to effectively identify key ecosystems with sparse vegetation. This study attempts to integrate Google Earth Engine (GEE), random forest (RF) algorithm, multi-source remote sensing data (spectral, radar, terrain, texture), feature optimization, and image segmentation to develop a fine-scale mapping method for an ecologically critical area in northern China. The results showed the following: (1) Incorporating multi-source remote sensing data significantly improved the overall classification accuracy of dryland ecosystems, with radar features contributing the most, followed by terrain and texture features. (2) Optimizing the features set can enhance the classification accuracy, with overall accuracy reaching 91.34% and kappa coefficient 0.90. (3) User’s accuracies exceeded 90% for forest, cropland, and water, and were slightly lower for steppe and shrub-steppe but were still above 85%, demonstrating the efficacy of the GEE and RF algorithm to map sparse vegetation and other dryland ecosystems. Accurate dryland ecosystems mapping requires accounting for regional heterogeneity and optimizing sample data and feature selection based on field surveys to precisely depict ecosystem patterns in complex regions. This study precisely mapped dryland ecosystems in a typical dryland region, and provides baseline data for ecological protection and restoration policies in this region, as well as a methodological reference for ecosystem mapping in similar regions.
Influences of Vegetation Rehabilitation on Soil Infiltrability and Root Morphological Characteristics in Coastal Saline Soil
Authors: Chu Linlin , Yuan Si , Chen Dan , Kang Yaohu , Shaghaleh Hiba , El-Tayeb Mohamed A. , Sheteiwy Mohamed S. , Hamoud Yousef Alhaj
Published: June 2024

Soil’s hydraulic properties are an essential characteristic that influences the hydrologic cycle by influencing infiltration and runoff and the transport of soil water and salt in the process of vegetation rehabilitation in coastal saline soils. To date, few studies have specifically addressed the soil’s hydraulic properties and root–soil interactions of coastal saline soil under revegetation. This study aimed to identify the unique hydraulic characteristics of soil, the pore size distribution parameter, Gardner α, and the different contributions of soil’s physical properties and vegetation’s root morphological characteristics with regard to soil infiltration. For this purpose, disc infiltration experiments at different pressure heads were performed on three vegetation types, Salix matsudana (SM), Hibiscus syriacus (HC), and Sabina vulgaris (SV), after two years of vegetation rehabilitation. The results demonstrated that the initial and steady infiltration rate, Gardner α, and soil porosity fraction exhibit significant differences among the three plant species. A correlation analysis indicated that the soil water content, surface area, density, and dry weight of roots had inverse relationships with soil infiltration at heads of pressure of 0 cm and 9 cm. The regulation of soil infiltration was influenced by the root dry weight and root average diameter, which played crucial roles in determining the roots’ morphological properties and the formation of pathways and soil pores.
Unveiling the Trajectories and Trends in Women-Inclusive City Related Studies: Insights from a Bibliometric Exploration
Authors: Hermaputi Roosmayri Lovina , Hua Chen
Published: June 2024

Despite the ongoing discrimination that hinders women’s full participation in urban life, the International Agenda 2030 and its Sustainable Development Goals (SDGs) emphasize the eradication of violence against women and underscore the need for regulatory measures, local governance, and equitable practices for sustainable urban development focusing on women’s needs. The women-inclusive cities related (WICR) studies, which have been gaining academic attention since the late 1990s, remain broadly explored yet lack a holistic trajectory and trend study and a precise women-inclusive city concept framework. This study applies bibliometric analysis with R-package Bibliometrix version 3.3.2 and a systematic review of 1144 articles, mapping global trends and providing a framework for women-inclusive city concepts. The findings show that WICR research increased significantly from 1998 to 2022, indicating continuous interest. Gender, women, and politics are the top three most frequent keywords. Emerging research directions are expected to focus on politics, violence, and urban governance. The findings also indicate a clear tendency for researchers from the same geographical backgrounds or regions to co-author papers, suggesting further international collaboration. Although no explicit definitions were found in the articles used, the prevailing literature consistently suggests that a “woman-inclusive city” ensures full rights, equal consideration of needs, and the active participation of women in all aspects of urban life.
Ion Channels and Neurological Disease
Authors: Musio Carlo
Published: June 2024

Ion channels are key elements in the control of membrane physiology and neurotransmission because ionic fluxes assure neuronal signal propagation across and between neurons through synaptic transmission [...]
Emergent Penile Venous Stripping for Treating Adolescent Impotence
Authors: Chang Ko-Shih , Chang Yi-Kai , Chung Cho-Hsing , Hsu Geng-Long , Chueh Jeff SC
Published: June 2024

Introduction: Traditional anatomy-based penile venous surgery is deemed inadequate. Based on revolutionary insights into penile vasculature, penile venous stripping (PVS) shows promise in treating adolescent erectile dysfunction (AED). We aimed to report on this novel approach. Methods: We conducted a retrospective analysis of 223 individuals under 30 diagnosed with veno-occlusive dysfunction (VOD) between 2009 and 2023. Among them, 83 were diagnosed with AED and divided into the PVS (n = 37) and no-surgery (NS, n = 46) groups. All participants had been dissatisfied with conventional therapeutic options. Dual pharmaco-cavernosography was the primary diagnostic modality. PVS involved stripping the deep dorsal vein and two cavernosal veins after securing each emissary’s vein with a 6-0 nylon suture. Erection restoration was accessed using the abridged five-item version of the International Index of Erectile Function (IIEF-5) score system and the erection hardness scale (EHS). Statistical analysis was performed using IBM SPSS 21.0. Results: There were significant differences (both p < 0.001) between the preoperative and postoperative IIEF-5 scores in the PVS and NS groups (9.8 ± 3.0 vs. 20.4 ± 2.2; 9.9 ± 2.5 vs. 9.5 ± 2.1), as well as in the EHS scores (1.7 ± 0.7 vs. 3.5 ± 0.6 and 1.8 ± 0.5 vs. 1.3 ± 0.4). The satisfaction rate was 87.9% (29/33) in the PVS group and 16.7% (17/41) in the NS group. Conclusions: AED can be effectively treated using physiological methods, although larger patient cohorts are needed for validation.
Influence of Natural Gas Composition and Operating Conditions on the Steady-State Performance of Dry Gas Seals for Pipeline Compressors
Authors: Wu Fan , Jiang Jinbo , Peng Xudong , Teng Liming , Meng Xiangkai , Li Jiyun
Published: June 2024

A dry gas seal (DGS) is one of the key basic components of natural gas transmission pipeline compressors, and the sealing performance of a DGS dealing with complex multi-component pipeline natural gas is different from that dealing with conventional nitrogen medium. In this paper, a spiral groove DGS of the compressor in natural gas transmission pipeline systems is taken as the research object. The thermal hydrodynamic lubrication model of the DGS is established considering turbulence effect and choking effect. Based on the finite difference method, the temperature and pressure distributions and the steady-state performance of the DGS are obtained by simulating. The influence of unitary impurity compositions such as light hydrocarbon, heavy hydrocarbon, non-hydrocarbon, and their contents on the steady-state performance of the DGS is analyzed. The steady-state performance of the DGS dealing with multi-impurity natural gas such as in the West-East gas transmission is investigated under different operating conditions. The results show that turbulence had a significant effect on the DGS, while choking had a weak effect. Increasing the content of light hydrocarbon such as C2H6 and heavy hydrocarbon such as C5H10 resulted in an increase in the gas film stiffness, leakage rate, and the temperature difference between the inlet and outlet, while non-hydrocarbon, such as N2, reduced the temperature difference between the inlet and outlet. The greatest impact on seal performance was produced by the heavy hydrocarbon, followed by the light hydrocarbon, and the least was produced by the non-hydrocarbon.
5,10,15,20-Tetrakis-(4-(3-carbamoyl-pyridyl)-methylphenyl)porphyrin Bromide
Authors: Satta Giuseppe , Gaspa Silvia , Pisano Luisa , De Luca Lidia , Carraro Massimo
Published: June 2024

The synthesis of a new tetracationic porphyrin derivative is described. Contrary to the best known derivatives in the literature, which are derived from 5,10,15,20-tetrakis-4-pyridylporphyrin (TPyP), in this procedure we start from 5,10,15,20-tetrakis-(4-carboxymethoxyphenyl)porphyrin (TPPCOOMe), obtained by the condensation reaction between pyrrole and 4-formylbenzoate. The reaction is carried out in refluxed xylene, avoiding the use of halogenated solvents. The final product, 5,10,15,20-tetrakis-(4-(3-carbamoyl-pyridyl)-methylphenyl)porphyrin bromide (P15p), exhibits four cationic portions that make it soluble in water and suitable for G4 stabilization. The choice to synthesize a derivative of TPPCOOMe is based on the idea of having a possible stabilizer that, unlike those obtained from TPyP, shows the cationic moieties farther from the porphyrin core and thus closer to the phosphate groups present on the G4 loops.
CO2 Capture with Polyethylenimine Supported on 3D-Printed Porous SiO2 Structures
Authors: Wick-Joliat René , Weisshar Florian B. , Gorbar Michal , Meier Daniel M. , Penner Dirk
Published: June 2024

Amines supported on porous solid materials have a high CO2 adsorption capacity and low regeneration temperature. However, the high amine load on such substrates and the substrate itself may lead to substantial pressure drop across the reactor. Herein, we compare the CO2 adsorption capacity and pressure drop of fumed silica powder to 3D-printed monolithic fumed silica structures, both functionalized by polyethylenimine (PEI), and find a drastically reduced pressure drop for 3D-printed substrates (0.01 bar vs. 0.76 bar) in the sorption bed with equal CO2 adsorption capacity. Furthermore, the effect of 3D-printing nozzle diameter and PEI loading on the adsorption capacity are investigated and the highest capacities (2.0 mmol/g at 25 °C with 5000 ppm CO2) are achieved with 0.4 mm nozzle size and 34 wt% PEI loading. These high capacities are achieved since the 3D printing and subsequent sintering (700 °C) of monolithic samples does not compromise the surface area of the fumed silica. Finally, the comparison between 3D-printed monoliths and extruded granulate of varying diameter reveals that the ordered channel system of 3D-printed structures is superior to randomly oriented granulate in terms of CO2 adsorption capacity.
Skin Comfort Sensation with Mechanical Stimulus from Electronic Skin
Authors: Ji Dongcan , Zhu Yunfan , Li Min , Fan Xuanqing , Zhang Taihua , Li Yuhang
Published: June 2024

The field of electronic skin has received considerable attention due to its extensive potential applications in areas including tactile sensing and health monitoring. With the development of electronic skin devices, electronic skin can be attached to the surface of human skin for long-term health monitoring, which makes comfort an essential factor that cannot be ignored in the design of electronic skin. Therefore, this paper proposes an assessment method for evaluating the comfort of electronic skin based on neurodynamic analysis. The holistic analysis framework encompasses the mechanical model of the skin, the modified Hodgkin–Huxley model for the transduction of stimuli, and the gate control theory for the modulation and perception of pain sensation. The complete process, from mechanical stimulus to the generation of pain perception, is demonstrated. Furthermore, the influence of different factors on pain perception is investigated. Sensation and comfort diagrams are provided to assess the mechanical comfort of electronic skin. The comfort assessment method proposed in this paper provides a theoretical basis when assessing the comfort of electronic skin.
The Influence of the Grinding Media Diameter on Grinding Efficiency in a Vibratory Ball Mill
Authors: Tomach Paweł
Published: June 2024

The grinding process plays a crucial role in industry, allowing for the reduction of particle sizes of raw materials and substances to the required fineness—either as a finished product or for further technological processes. The high demand for micro- and nanopowders or suspensions is associated with the high energy consumption of the milling process. Therefore, optimizing the milling process, including correctly selecting grinding media, is essential to reduce energy consumption. This article presents experimental studies of the grinding process of a model material (quartz sand) in a laboratory vibratory mill. Five sets of grinding media with different diameters were used in the research, and grinding was conducted for various durations. The studies showed that the vibratory grinding process is efficient for each set of grinding media and grinding durations. The research has shown that conducting studies on the proper selection of mills is beneficial, especially regarding very fine grinding of various materials. The study confirmed that properly selecting grinding media sets can significantly accelerate the grinding process. For the selected technological variant, it was demonstrated that using 15 mm grinding media, compared to 12 mm, resulted in a 22.5% reduction in grinding time to achieve a specified particle size class of 0–10 μm.
Mechanical Behavior of 3D-Printed Thickness Gradient Honeycomb Structures
Authors: Yang Dongxia , Guo Lihua , Fan Changsheng
Published: June 2024

In order to obtain a lightweight, high-strength, and customizable cellular structure to meet the needs of modern production and life, the mechanical properties of four thickness gradient honeycomb structures were studied. In this paper, four types of honeycomb structure specimens with the same porosity and different Poisson’s ratios were designed and manufactured by using SLA 3D-printing technology, including the honeycomb, square honeycomb, quasi-square honeycomb, and re-entrant honeycomb structures. Based on the plane compression mechanical properties and failure mode analysis of these specimens, the thickness gradient is applied to the honeycomb structure, and four structural forms of the thickness gradient honeycomb structure are formed. The experimental results show that the thickness gradient honeycomb structure exhibits better mechanical properties than the honeycomb structure with a uniform cellular wall thickness. In the studied thickness gradient honeycomb structure, the mechanical properties of the whole structure can be significantly improved by increasing the thickness of cell walls at the upper and lower ends of the structure. The wall thickness, arrangement order, shape, and Poisson’s ratio of the cell all have a significant impact on the mechanical properties of the specimens. These results provide an effective basis for the design and application of cellular structures in the future.
Modulation of the Structural, Magnetic, and Dielectric Properties of YMnO3 by Cu Doping
Authors: Wan Feng , Hua Xuexia , Guo Qiufen
Published: June 2024

The lower valence compensation of YMn1-xCuxO3 (x = 0.00, 0.05, and 0.10) is prepared by the solid-state reaction, and the effects of divalent cation Cu-doping on the construction and magnetic and dielectric attributes of multiferroic YMnO3 are systemically researched. Powder X-ray diffraction shows YMn1-xCuxO3 has a single-phase hexagonal construction with a P63cm space group as the parent YMnO3, and lattice parameters decrease systematically as Cu concentration increases. Using the scanning electric microscope, structure morphologies analysis shows that the mean grain size varies between 1.90 and 2.20 μm as Cu content increases. YMn1-xCuxO3 magnetization increases as Cu doping concentration increases, and the antiferromagnetic transition temperature declines from 71 K for x = 0.00 to 58 K for x = 0.10. The valence distributions of Mn ions conduce to the modified magnetic attributes. Due to Cu substitution, the dielectric loss and dielectric constant decline as frequency increases from 400 to 700 K, showing representative relaxation behaviors. Indeed, that is a thermally activated process. In addition, the peak of the dielectric loss complies with the Arrhenius law. The relaxation correlates to the dipole effect regarding carrier hopping between Mn3+ and Mn4+, and also correlates to oxygen vacancies generated by Mn2+.
On a Mixed Transient–Asymptotic Result for the Sequential Interval Reliability for Semi-Markov Chains
Authors: D’Amico Guglielmo , Gkelsinis Thomas
Published: June 2024

In this paper, we are concerned with the study of sequential interval reliability, a measure recently introduced in the literature. This measure represents the probability of the system working during a sequence of nonoverlapping time intervals. In the cited work, the authors proposed a recurrent-type formula for computing this indicator in the transient case and investigated the asymptotic behavior as all the time intervals go to infinity. The purpose of the present work is to further explore the asymptotic behavior when only some of the time intervals are allowed to go to infinity while the remaining ones are not. In this way, we provide a unique indicator that is able to describe the process evolution in the transient and asymptotic cases as well. It is important to mention that this is not a straightforward result since, in order to achieve it, we need to develop several mathematical ingredients that generalize the classical renewal and Markov renewal frameworks. A numerical example illustrates our theoretical results.
Location-Routing Optimization for Two-Echelon Cold Chain Logistics of Front Warehouses Based on a Hybrid Ant Colony Algorithm
Authors: Zhang Xuya , Wang Yue , Zhang Dongqing
Published: June 2024

Diverse demands have promoted the rapid development of the cold chain logistics industry. In the paper, a novel approach for calculating the comprehensive carbon emission cost was proposed and the front warehouse mode was analyzed under the background of energy conservation and emission reduction. To solve the two-echelon low-carbon location-routing problem (2E-LCLRP), a mathematical model considering operating cost, total transportation cost, fixed cost, refrigeration cost, cargo damage cost, and comprehensive carbon emission cost was proposed to determine the minimum total cost. A hybrid ant colony optimization (HACO) algorithm based on an elbow rule and an improved ant colony optimization (IACO) algorithm was proposed to solve the 2E-LCLRP. According to the elbow rule, the optimal number of front warehouses was determined and an IACO algorithm was then designed to optimize vehicle routes. An adaptive hybrid selection strategy and an optimized pheromone update mechanism were integrated into the HACO algorithm to accelerate convergence and obtain global optimal solutions. The proposed model and algorithm were verified through the case study of the 2E-LCLRP in Nanjing, China. The HACO algorithm outperformed the original ant colony optimization (ACO) algorithm in terms of convergence rate and solution quality. This study provides significant insights for enhancing heuristic algorithms as well as valuable research methods. Furthermore, the results can help cold chain logistics companies in balancing economic costs and environmental benefits and address cold chain distribution of agricultural products.
Wearable Sensors for Athletic Performance: A Comparison of Discrete and Continuous Feature-Extraction Methods for Prediction Models
Authors: White Mark , De Lazzari Beatrice , Bezodis Neil , Camomilla Valentina
Published: June 2024

Wearable sensors have become increasingly popular for assessing athletic performance, but the optimal methods for processing and analyzing the data remain unclear. This study investigates the efficacy of discrete and continuous feature-extraction methods, separately and in combination, for modeling countermovement jump performance using wearable sensor data. We demonstrate that continuous features, particularly those derived from Functional Principal Component Analysis, outperform discrete features in terms of model performance, robustness to variations in data distribution and volume, and consistency across different datasets. Our findings underscore the importance of methodological choices, such as signal type, alignment methods, and model selection, in developing accurate and generalizable predictive models. We also highlight the potential pitfalls of relying solely on domain knowledge for feature selection and the benefits of data-driven approaches. Furthermore, we discuss the implications of our findings for the broader field of sports biomechanics and provide practical recommendations for researchers and practitioners aiming to leverage wearable sensor data for athletic performance assessment. Our results contribute to the development of more reliable and widely applicable predictive models, facilitating the use of wearable technology for optimizing training and enhancing athletic outcomes across various sports disciplines.
A Parallel Multi-Party Privacy-Preserving Record Linkage Method Based on a Consortium Blockchain
Authors: Han Shumin , Wang Zikang , Shen Dengrong , Wang Chuang
Published: June 2024

Privacy-preserving record linkage (PPRL) is the process of linking records from various data sources, ensuring that matching records for the same entity are shared among parties while not disclosing other sensitive data. However, most existing PPRL approaches currently rely on third parties for linking, posing risks of malicious tampering and privacy breaches, making it difficult to ensure the security of the linkage. Therefore, we propose a parallel multi-party PPRL method based on consortium blockchain technology which can effectively address the issue of semi-trusted third-party validation, auditing all parties involved in the PPRL process for potential malicious tampering or attacks. To improve the efficiency and security of consensus within a consortium blockchain, we propose a practical Byzantine fault tolerance consensus algorithm based on matching efficiency. Additionally, we have incorporated homomorphic encryption into Bloom filter encoding to enhance its security. To optimize computational efficiency, we have adopted the MapReduce model for parallel encryption and utilized a binary storage tree as the data structure for similarity computation. The experimental results show that our method can effectively ensure data security while also exhibiting relatively high linkage quality and scalability.
Dynamic Convolution Neural Networks with Both Global and Local Attention for Image Classification
Authors: Zheng Chusan , Li Yafeng , Li Jian , Li Ning , Fan Pan , Sun Jieqi , Liu Penghui
Published: June 2024

Convolution is a crucial component of convolution neural networks (CNNs). However, the standard static convolution has two primary defects: data independence and the weak ability to integrate global and local features. This paper proposes a novel and efficient dynamic convolution method with global and local attention to address these issues. A building block called the Global and Local Attention Unit (GLAU) is designed, in which a weighted fusion of global channel attention kernels and local spatial attention kernels generates the proposed dynamic convolution kernels. The GLAU is data-dependent and has better adaptability and the ability to integrate global and local features into each layer. We refer to such modified CNNs with GLAUs as “GLAUNets”. Extensive evaluation experiments for image classification compared to classical CNNs and the state-of-the-art dynamic convolution neural networks were conducted on the popular benchmark datasets. In terms of classification accuracy, the number of parameters, and computational complexity, the experimental results demonstrate the outstanding performance of GLAUNets.
Existence, Regularity, and Uniqueness of Solutions to Some Noncoercive Nonlinear Elliptic Equations in Unbounded Domains
Authors: Di Gironimo Patrizia
Published: June 2024

In this paper, we study a noncoercive nonlinear elliptic operator with a drift term in an unbounded domain. The singular first-order term grows like |E(x)||∇u|, where E(x) is a vector field belonging to a suitable Morrey-type space. Our operator arises as a stationary equation of diffusion–advection problems. We prove existence, regularity, and uniqueness theorems for a Dirichlet problem. To obtain our main results, we use the weak maximum principle and the same a priori estimates.
Constant Angle Ruled Surfaces with a Pointwise 1-Type Gauss Map
Authors: Baltić Vladimir , Eren Kemal , Savić Ana , Ersoy Soley
Published: June 2024

In this study, constant angle ruled surfaces with a pointwise 1-type Gauss map, which is very useful in the classification of surfaces, are investigated in terms of the Frenet elements of the base curves of the ruled surfaces in Euclidean 3-space. In order to form a basis for our work, firstly, basic concepts related to the Gauss map of an oriented surface are given. Later, a classification is satisfied by determining the necessary conditions to be the first kind, the second kind, and the harmonic of the pointwise 1-type of the Gauss map for these surfaces. Finally, some examples of these surfaces are provided, and their graphical illustrations are displayed.
A Legendre Spectral-Element Method to Incorporate Topography for 2.5D Direct-Current-Resistivity Forward Modeling
Authors: Xie Wei , Zhu Wendi , Tong Xiaozhong , Ma Huiying
Published: June 2024

An effective and accurate solver for the direct-current-resistivity forward-modeling problem has become a cutting-edge research topic. However, computational limitations arise due to the substantial amount of data involved, hindering the widespread use of three-dimensional forward modeling, which is otherwise considered the most effective approach for identifying geo-electrical anomalies. An efficient compromise, or potentially an alternative, is found in two-and-a-half-dimensional (2.5D) modeling, which employs a three-dimensional current source within a two-dimensional subsurface medium. Consequently, a Legendre spectral-element algorithm is developed specifically for 2.5D direct-current-resistivity forward modeling, taking into account the presence of topography. This numerical algorithm can combine the complex geometric flexibility of the finite-element method with the high precision of the spectral method. To solve the wavenumber-domain electrical potential variational problem, which is converted into the two-dimensional Helmholtz equation with mixed boundary conditions, the Gauss–Lobatto–Legendre (GLL) quadrature is employed in all discrete quadrilateral spectral elements, ensuring identical Legendre polynomial interpolation and quadrature points. The Legendre spectral-element method is applied to solve a two-dimensional Helmholtz equation and a resistivity half-space model. Numerical experiments demonstrate that the proposed approach yields highly accurate numerical results, even with a coarse mesh. Additionally, the Legendre spectral-element algorithm is employed to simulate the apparent resistivity distortions caused by surface topographical variations in the direct-current resistivity Wenner-alpha array. These numerical results affirm the substantial impact of topographical variations on the apparent resistivity data obtained in the field. Consequently, when interpreting field data, it is crucial to consider topographic effects to the extent they can be simulated. Moreover, our numerical method can be extended and implemented for a more accurate computation of three-dimensional direct-current-resistivity forward modeling.
Diagnosis and Medical Treatment of Acute and Chronic Idiopathic Pouchitis in Inflammatory Bowel Disease
Authors: Meianu Corina , Stroie Tudor , Istratescu Doina , Preda Carmen Monica , Diculescu Mihai Mircea
Published: June 2024

Despite the decreased rates in inflammatory bowel disease (IBD) colectomies due to high advances in therapeutic options, a significant number of patients still require proctocolectomy with ileal pouch-anal anastomosis (IPPA) for ulcerative colitis (UC). Pouchitis is the most common complication in these patients, where up to 60% develop one episode of pouchitis in the first two years after UC surgery with IPAA with severe negative impact on their quality of life. Acute cases usually respond well to antibiotics, but 15% of patients will still develop a refractory disease that requires the initiation of advanced immunosuppressive therapies. For chronic idiopathic pouchitis, current recommendations suggest using the same therapeutic options as for IBD in terms of biologics and small molecules. However, the available data are limited regarding the effectiveness of different biologics or small molecules for the management of this condition, and all evidences arise from case series and small studies. Vedolizumab is the only biologic agent that has received approval for the treatment of adult patients with moderately to severely active chronic refractory pouchitis. Despite the fact that IBD treatment is rapidly evolving with the development of novel molecules, the presence of pouchitis represents an exclusion criterion in these trials. Recommendations for the approach of these conditions range from low to very low certainty of evidence, resulting from small randomized controlled trials and case series studies. The current review focuses on the therapeutic management of idiopathic pouchitis.
Validation of a Pseudovirus Neutralization Assay for Severe Acute Respiratory Syndrome Coronavirus 2: A High-Throughput Method for the Evaluation of Vaccine Immunogenicity
Authors: Cai Zhaohui , Kalkeri Raj , Wang Mi , Haner Benjamin , Dent Dominic , Osman Bahar , Skonieczny Paul , Ross Jeremy , Feng Sheau-Line , Cai Rongman , Zhu Mingzhu , Cloney-Clark Shane , Plested Joyce S.
Published: June 2024

The evaluation of coronavirus disease 2019 (COVID-19) vaccine immunogenicity remains essential as the severe acute respiratory syncytial virus 2 (SARS-CoV-2) pandemic continues to evolve and as additional variants emerge. Neutralizing antibodies are a known correlate of protection for SARS-CoV-2 vaccines. A pseudovirus neutralization (PNT) assay was developed and validated at Novavax Clinical Immunology Laboratories to allow for the detection of neutralizing antibodies in vaccine clinical trial sera. The PNT assay was precise, accurate, linear, and specific in measuring SARS-CoV-2 neutralization titers in human serum for ancestral strain and the Omicron subvariants BA.5 and XBB.1.5, with an overall geometric coefficient of variation of ≤43.4%, a percent relative bias within the expected range of −60% to 150%, and a linearity value of R2 > 0.98 for all three strains. This pseudovirus assay will be useful for the analysis of vaccine clinical trial samples to assess vaccine immunogenicity. Future work will focus on modifying the assay for emerging variants, including XBB.1.16, EG.5.1, BA.2.86, and any other variants that emerge in the ongoing pandemic.
Biological Traits and Comprehensive Genomic Analysis of Novel Enterococcus faecalis Bacteriophage EFP6
Authors: Ahmad Sajjad , Leng Qingwen , Hou Gongmingzhu , Liang Yan , Li Yanfang , Qu Yonggang
Published: June 2024

Enterococcus faecalis is a prevalent opportunistic pathogen associated with chicken embryonic and neonatal chick mortality, posing a significant challenge in poultry farming. In the current study, E. faecalis strain EF6, isolated from a recent hatchery outbreak, served as the host bacterium for the isolation of a novel phage EFP6, capable of lysing E. faecalis. Transmission electron microscopy revealed a hexagonal head and a short tail, classifying EFP6 as a member of the Autographiviridae family. EFP6 showed sensitivity to ultraviolet radiation and resistance to chloroform. The lytic cycle duration of EFP6 was determined to be 50 min, highlighting its efficacy in host eradication. With an optimal multiplicity of infection of 0.001, EFP6 exhibited a narrow lysis spectrum and strong specificity towards host strains. Additionally, EFP6 demonstrated optimal growth conditions at 40 °C and pH 8.0. Whole genome sequencing unveiled a genome length of 18,147 bp, characterized by a GC concentration of 33.21% and comprising 25 open reading frames. Comparative genomic assessment underscored its collinearity with related phages, notably devoid of lysogenic genes, thus ensuring genetic stability. This in-depth characterization forms the basis for understanding the biological attributes of EFP6 and its potential utilization in phage therapy, offering promising prospects for mitigating E. faecalis-associated poultry infections.
Research on an Accurate Simulation Modeling and Charge Motion Quantitative Evaluation Method for Ball Mill in Confined Space
Authors: Yin Zixin , Jin Zujin , Li Tongqing
Published: June 2024

A ball mill is a type of complex grinding device. Having knowledge of its charge-load behavior is key to determining the operating conditions that provide the optimum mill throughput. An elaborate description of the charge movement inside the ball mill is essential. This study focuses on a laboratory-scale ball mill and utilizes a discrete element simulation model to investigate the impact of mill speed and ball filling on charge-load behavior. Initially, the EDEM 2.7 (Engineering Discrete Element Method) software contact parameters were calibrated through heap-angle experiments. Subsequently, four charge-motion characteristic parameters were defined and analyzed based on Powell’s theory to understand the variations in charge-load behavior. This research proposes a theoretical calculation model for predicting power in a ball mill, highlighting the significance of the CoC (Center of Circulation) and CoM (Center of Mass) in reflecting changes in charge-load behavior. The theoretical model for mill-power prediction is effective and aligns well with the EDEM simulation and experimental results, providing valuable insights for optimizing large-scale ball mill structures and controlling charge motion during production.
Advances in Hydrometallurgical Gold Recovery through Cementation, Adsorption, Ion Exchange and Solvent Extraction
Authors: Kim Jihye , Kim Rina , Han Kenneth N.
Published: June 2024

Hydrometallurgical gold recovery processes play a pivotal role in the gold mining industry, contributing to more than 90% of global gold production. Among the array of techniques available, the Merrill–Crowe process, adsorption, ion exchange, and solvent extraction are central in extracting gold from leach solutions. While the Merrill–Crowe process and gold complex adsorption onto activated carbon represent historical cornerstones, their inherent limitations have prompted the emergence of more recent innovations in ion exchange and solvent extraction, offering enhanced selectivity, control, and sustainability. The evolution of modern organic chemistry has significantly influenced the progress of ion exchange technology, mainly through the introduction of advanced polymer matrix synthetic resins. At the same time, novel solvents tailored to gold complex interactions have revitalized ion exchange and solvent extraction. Introducing ionic liquids and deep eutectic solvents has also added a new dimension to efforts to improve gold extraction metallurgy. This paper reviews these cutting-edge developments and their potential to revolutionize the hydrometallurgical gold recovery process, addressing the pressing need for improved efficiency and environmental responsibility.
Synergistic Theoretical and Experimental Insights into NH4+-Enhanced Vanadium Oxide Cathodes for Aqueous Zinc-Ion Batteries
Authors: Lin He , Xu Jing , Zhang Yu
Published: June 2024

This study explores the enhancement of aqueous zinc-ion batteries (AZIBs) using ammonium-enhanced vanadium oxide cathodes. Density Functional Theory (DFT) calculations reveal that NH4+ incorporation into V6O16 lattices significantly facilitates Zn2+ ion diffusion by reducing electrostatic interactions, acting as a structural lubricant. Subsequent experimental validation using (NH4)2V6O16 cathodes synthesized via a hydrothermal method corroborates the DFT findings, demonstrating remarkable electrochemical stability with a capacity retention of 90% after 2000 cycles at 5 A g−1. These results underscore the potential of NH4+ in improving the performance and longevity of AZIBs, providing a pathway for sustainable energy storage solutions.
Targeting NAD Metabolism: Rational Design, Synthesis and In Vitro Evaluation of NAMPT/PARP1 Dual-Target Inhibitors as Anti-Breast Cancer Agents
Authors: Li Yingpeng , Kong Xianxiu , Chu Xinhong , Fu Hui , Feng Xinchi , Zhao Chengcheng , Deng Yanru , Ge Jun
Published: June 2024

The malignancy of breast cancer poses a global challenge, with existing treatments often falling short of desired efficacy. Extensive research has underscored the effectiveness of targeting the metabolism of nicotinamide adenine dinucleotide (NAD), a pivotal molecule crucial for cancer cell survival and growth, as a promising anticancer strategy. Within mammalian cells, sustaining optimal NAD concentrations relies on two key enzymes, namely nicotinamide phosphoribosyltransferase (NAMPT) and poly(ADP-ribose) polymer 1 (PARP1). Recent studies have accentuated the potential benefits of combining NAMPT inhibitors and PARP1 inhibitors to enhance therapeutic outcomes, particularly in breast cancer. In this study, we designed and synthesized eleven novel NAMPT/PARP1 dual-target inhibitors. Among them, compound DDY02 exhibited acceptable inhibitory activities against both NAMPT and PARP1, with IC50 values of 0.01 and 0.05 µM, respectively. Moreover, in vitro evaluations revealed that treatment with DDY02 resulted in proliferation inhibition, NAD depletion, DNA damage, apoptosis, and migration inhibition in MDA-MB-468 cells. These results posit DDY02, by targeting NAD metabolism through inhibiting both NAMPT and PARP1, as a promising lead compound for the development of breast cancer therapy.