bluuebunny/crossref_metadata_2025 huggingface dataset:
Scene Classification of Remote Sensing Image Based on Multi-Path Reconfigurable Neural Network
Authors: Hu Wenyi , Lan Chunjie , Chen Tian , Liu Shan , Yin Lirong , Wang Lei
Published: October 2024

Land image recognition and classification and land environment detection are important research fields in remote sensing applications. Because of the diversity and complexity of different tasks of land environment recognition and classification, it is difficult for researchers to use a single model to achieve the best performance in scene classification of multiple remote sensing land images. Therefore, to determine which model is the best for the current recognition classification tasks, it is often necessary to select and experiment with many different models. However, finding the optimal model is accompanied by an increase in trial-and-error costs and is a waste of researchers’ time, and it is often impossible to find the right model quickly. To address the issue of existing models being too large for easy selection, this paper proposes a multi-path reconfigurable network structure and takes the multi-path reconfigurable residual network (MR-ResNet) model as an example. The reconfigurable neural network model allows researchers to selectively choose the required modules and reassemble them to generate customized models by splitting the trained models and connecting them through modules with different properties. At the same time, by introducing the concept of a multi-path input network, the optimal path is selected by inputting different modules, which shortens the training time of the model and allows researchers to easily find the network model suitable for the current application scenario. A lot of training data, computational resources, and model parameter experience are saved. Three public datasets, NWPU-RESISC45, RSSCN7, and SIRI-WHU datasets, were used for the experiments. The experimental results demonstrate that the proposed model surpasses the classic residual network (ResNet) in terms of both parameters and performance.
Assessing the Impact of Geospatial Susceptibility on the Rural Agricultural Landscapes of Village Settlements in Southwestern Nigeria
Authors: Adesina John Adekunle , Liu Yuanyuan , Tang Xiaolan , Ren Yujie
Published: October 2024

A theoretical framework for agricultural landscape pattern transitions in rural areas is proposed to fill the gap of current research with an empirical study in the Alabata farm settlement in Ogun State, Southwest Nigeria. Adopting the use of ArcGIS 10.8 and Surfer 27.3 the surface area and volume of the ground surface degraded and exposed to harsh weather conditions due to both natural and man-made anthropogenic activities causing runoffs and continuous soil erosion were calculated, which have affected agricultural production and sent some of the farmers packing, abandoning their farmlands. The farm settlement within the total sampled frame area of 1.50 km2 covers a total distance of 5.11 km. The sample frame was divided into 36 frames with similar ecological microclimates, topographical features, terrain, and soil types that fell into either of the two identified soil types: 1 and 2. The study involved the completion of a questionnaire onsite using three major criteria and only 23 farmers responded positively to the few questions as farmers who were either living on the farm or working as hired laborers on-site at the time of the visit. The transition characteristics of agricultural landscape patterns as represented in abandoned, degraded farmlands and orchards are analyzed from a local perspective.
Quantifying and Zoning Ecological Compensation for Cultivated Land in Intensive Agricultural Areas: A Case Study in Henan Province, China
Authors: Li Ling , Li Xingming , Fan Hanghang , Lu Jie , Wang Xiuli , Zhai Tianlin
Published: October 2024

Cultivated land ecological compensation (CLEC) is an important way to solve regional development imbalance and cultivated land problems, and the scientific quantification of the ecological value of cultivated land is the key to CLEC. This study quantified the total amount and urgency of CLEC in China’s main grain-producing region using the cropland ecological footprint (EF) and ecosystem service value (ESV) methods. Furthermore, this study analyzed the comprehensive zoning of CLEC considering natural and economic development. The results showed that the spatial distribution of EFs and the ecological carrying capacity of cultivated land in Henan Province are similar, presenting the spatial characteristics of being high in the southeast and low in the northwest; the cultivated land in most of the counties and districts is in a state of ecological surplus, and the cultivated land resources are sufficient to support their own consumption needs. Henan Province as a whole is an ecologically compensated region, with a compensation amount of CNY 1.39 billion, and the total amount of compensation is in a positive value of 94.94%. The Southwest Yu and North Yu economic zone of Henan are the areas of high and low values of cultivated land compensation. The priority compensation region is the most extensive and widely distributed type in the five regions of Henan Province, accounting for 55% of the counties and districts. The degree of compensation is most urgent in the Huanghuai, Southwest Yu, and North Yu economic zones. This study’s findings provide new ideas for the development of differentiated ecological compensation policies, and provide references for the participation of multiple market participants and the diversification of compensation forms.
Synergistic Promotion of Particulate and Mineral-Associated Organic Carbon Within Soil Aggregates After 10 Years of Organic Fertilization in Wheat-Maize Systems
Authors: Li Jing , Wu Huijun , Song Xiaojun , Li Shengping , Wu Xueping , Han Ya , Liu Zhiping , Yang Na , Wang Ke , Yang Zhiguo , Zhang Jiancheng
Published: October 2024

How different fertilization practices modify soil organic carbon (SOC) sequestration is still unclear. Our study aimed to evaluate the changes in SOC stocks and their physical fractions after 10 years of organic and inorganic fertilization. Five treatments were established under a wheat-maize system in Northern China: control (CK), chemical fertilizer (F), straw plus chemical fertilizer (SF), manure plus chemical fertilizer (MF), and straw and manure plus chemical fertilizer (SMF). The results showed that the SOC sequestration rate at 0–20 cm depth decreased in the following order: SMF (1.36 Mg C/ha/yr) > MF (1.13 Mg C/ha/yr) > SF (0.72 C/ha/yr) > F (0.15 Mg C/ha/yr) > CK (−0.25 Mg C/ha/yr). The values indicated that straw returning and manure application were important measures to achieve the “4 per 1000” target, and the application of manure was a more effective strategy. The high input of chemical fertilizer only maintained the initial SOC level and was not a powerful C-farming practice. A minimum input of 4.93 Mg C/ha/yr was required to keep the initial SOC storage. The SOC associated with small macroaggregate (0.25–2 mm) was the most sensitive indicator for the changes of bulk SOC. In addition, the accumulation of SOC under SMF, MF, and SF treatments mainly occurred in the occluded particulate organic C (oPOC) in small macroaggregates, indicating that the physical protection of macroaggregates played a predominant role in SOC sequestration. The SMF, MF, and SF treatments also displayed higher mineral organic C (mSOC) in soil aggregates than the CK and F treatments. A transformation of oPOC towards the mSOC fraction indicated that exogenous C further shifted into stable C pools under the physical protection of soil aggregates. In conclusion, these findings confirmed the important role of straw returning and manure application in SOC accumulation and stabilization, highlighting that a combination strategy of straw + manure + chemical fertilizer had the best effect.
Inverse Shifting-PCR Modified by Capillary Electrophoresis for Detecting F8 int22h and int1h Inversions in Severe Hemophilia A Patients and Probable Carriers
Authors: Martínez-Contreras Rosa Michel , García-López Silvia Sofía , Luna-Záizar Hilda , Jaloma-Cruz Ana Rebeca
Published: October 2024

Globally, intron 22 inversions (Inv22s) of the factor VIII gene (F8) are the most frequent pathogenic variants and account for 45–50% of severe hemophilia A (SHA) cases, while intron 1 inversion (Inv1) explains 1–5% of SHA cases. The detection of both inversions by an inverse shifting-polymerase chain reaction (IS-PCR) is the first choice worldwide for the diagnosis of patients and carriers of SHA. To improve its sensitivity and reproducibility in the visualization of PCR products, we approached the IS-PCR with fluorescent capillary electrophoresis instead of agarose electrophoresis. Based on the original protocol, we modified two primers by 5’-end labeling with FAM™ fluorescent dye for the detection of the PCR products by capillary electrophoresis. Additionally, the “fast enzymes” BclI and T4-Ligase were incorporated for work saving in the genomic digestion and ligation reactions, respectively. Once we accomplished the standardization and verified the reproducibility of the modified IS-PCR method, we applied it for the diagnosis of a cohort of SHA patients and carriers. The modified IS-PCR by fluorescent capillary electrophoresis for PCR product detection is more sensitive than agarose electrophoresis. The method was also improved by using the new rapid enzymes to save time in the whole process.
Impact of Plant Growth-Promoting Microorganism (PGPM) Consortium on Biochemical Properties and Yields of Tomato Under Drought Stress
Authors: Krishna Ram , Ansari Waquar Akhter , Altaf Mohammad , Jaiswal Durgesh Kumar , Pandey Sudhakar , Singh Achuit Kumar , Kumar Sudhir , Verma Jay Prakash
Published: October 2024

Drought is the most important abiotic stress that restricts the genetically predetermined yield potential of the crops. In the present study, four tomato varieties: Kashi Vishesh, Kashi Aman, Kashi Abhiman, and Kashi Amrit, were used to study the effect of PGPMs (plant growth-promoting microorganisms). PGPM strains, Bacillus megaterium BHUPSB14, Pseudomonas fluorescens BHUPSB06, Pseudomonas aeruginosa BHUPSB01, Pseudomonas putida BHUPSB0, Paenibacillus polymixa BHUPSB17, and Trichoderma horzianum, were used as the consortium. The control group was irrigated up to 80% of field capacity, while 7-, 14-, and 21-day water-deficit-exposed (DWD) plants’ pot soil moisture was maintained to 40, 25, and 15% of the field capacity, both with and without the PGPM inoculation condition. The physiological parameters, such as electrolyte leakage, relative water content, photosynthetic efficiency, and chlorophyll color index, were significantly improved by PGPM application under progressive drought stress, compared to the control. PGPM application enhanced the proline accumulation and reduced the formation of hydrogen peroxide and lipid peroxidation under drought stress. The plant growth attributes were significantly increased by PGPM application. The Kashi Amrit variety showed the highest fruit yield among the four varieties under all the treatments. The PGPM consortium application also improved the soil physico-biological properties and nutrient availability in the soil. The PGPM consortium used in this study can potentially mitigate drought stress on tomato in drought-prone regions and act as a biofertilizer. The present study will open a new avenue of drought stress management in tomato.
Will Mobile-Bearing Total Knee Arthroplasty Be Lost to History? A Comparative Study of Long-Term Follow-Up
Authors: Kim Sangrim , Yang Joseph , Moon Seokhwan , Choi Sungwook
Published: October 2024

Mobile-bearing (MB) total knee arthroplasty (TKA) implants were introduced as an alternative to fixed-bearing (FB) implants because of their theoretical advantages related to femorotibial rotational mismatch. The purpose of this study is to compare the clinical and radiologic outcomes of MB and FB TKA after approximately 13 years of follow-up. We compared the results of 88 patients with a mean age of 66 years who had received a rotating platform MB implant or a FB implant. The mean follow-up was 13.6 years. The patients were assessed clinically (VAS, ROM, KSS, WOMAC scores) and radiographically before and 13 years after operation. There were no statistically significant differences between the FB and MB groups in terms of clinical outcomes and radiological outcomes (p > 0.05 for all). Although the incidence of complications was higher in the MB group, the findings were not statistically significant compared to the FB group (p > 0.05 for all). Although there were no significant differences in the clinical and radiologic outcomes between the FB and MB groups, the possible higher risk of osteolysis or aseptic loosening in the MB group could be an important clinical implication when selecting the TKA implant.
Nanofluid Minimum Quantity Lubrication (NMQL): Overview of Nanoparticle Toxicity and Safer-Design Guidelines
Authors: Abellán-Nebot José V. , Andreu-Sánchez Oscar , Fito-López Carlos , Mondragón Rosa
Published: October 2024

Minimum Quantity Lubrication (MQL) has received much attention from the research community as a potential lubricating system to reduce environmental hazards and health issues that can be commonly found in flood cooling/lubricating systems based on metalworking fluids. The addition of nanoparticles in MQL systems (NMQL) has led to improved machining performance, increasing the cooling capability and reducing friction and tool wear, and some researchers have proved the applicability of this type of system for difficult-to-cut materials. However, the mist generated by MQL systems due to both the MQL system itself and the machining operation may pose an additional hazard to operators which is being overlooked by the research community. These hazards become more severe when using nanoparticles, but unfortunately very few works have paid attention to nanoparticle toxicity as applied in MQL systems, and this issue should be clearly understood before encouraging its implementation in industry. Furthermore, current legislation does not help since regulation of permissible exposure limits when dealing with nanoparticles is still ongoing in most cases. In this work, the toxicity of nanoparticles applied in MQL systems is analyzed, and recent research on studies of nanoparticle toxicity both in vitro and in vivo is presented. A relative comparison of toxicity is provided for those nanoparticles that have been reported in the literature as potential additives for MQL. The review is focused on analyzing the main factors of toxicity of nanoparticles which are identified as size, shape, surface properties, agglomeration and solubility. This review presents guidelines for safer nanolubricant formulations, guiding practitioners towards proper NMQL implementations in industry. Furthermore, current occupational exposure limits and recommendations are provided for all the nanoparticles potentially used in MQL systems, which is of interest in terms of work safety.
Multi-Objective Optimization of an Inertial Wave Energy Converter for Multi-Directional Wave Scatter
Authors: Carapellese Fabio , De Clerck Viola , Sirigu Sergej Antonello , Giorgi Giuseppe , Bonfanti Mauro , Faedo Nicolás , Giorcelli Ermanno
Published: October 2024

To advance wave energy devices towards commercialization, it is essential to optimize their design to enhance system performance. Additionally, a thorough economic evaluation is crucial for making these technologies competitive with other renewable energy sources. This study focuses on the techno-economic optimization of an innovative inertial system, the so-called SWINGO system, which is based on gyropendulum technology. SWINGO stands out due to its high energy efficiency in multi-directional installation sites, where wave directions vary significantly throughout the year. The study introduces the application of a multi-objective Evolutionary Algorithm (EA), specifically the Non-dominated Sorting Genetic Algorithm II (NSGA-II), to optimize the techno-economic performance of the SWINGO system. This approach aims to identify optimal design parameters that maximize energy extraction while considering economic viability. By deriving a Pareto frontier, a set of optimal devices is selected for further analysis. The performance of the SWINGO system is also compared to an alternative (mono-directional) inertial wave energy converter, the Inertial Sea Wave Energy Converter (ISWEC), to highlight the differences in techno-economic outcomes. Both systems are evaluated at two different installation sites: Pantelleria island and the North Sea in Denmark, with a focus on the directional wave scatter at each location.
Analysis of Influential Parameters in the Dynamic Loading and Stability of the Swing Drive in Hydraulic Excavators
Authors: Jovanović Vesna , Janošević Dragoslav , Marinković Dragan , Petrović Nikola , Djokić Radomir
Published: October 2024

The proper design and configuration of the swing drive mechanism of a hydraulic excavator are crucial to improve energy consumption and efficiency and ensure operational stability. This paper analyzes the influence of the relationship between the parameters of a hydraulic motor and a reducer, which form the integrated transmission of a swing drive, the dynamic characteristics of a hydraulic excavator on loading, and the dynamic stability of the drive. The analysis deals with an excavator model that has the same parameters of the kinematic chain members, the same parameters of the upper structure drive mechanisms, and two variants of the swing drive that, with different integrated transmission parameters, provide the upper structure with the identical number of revolutions and equal rotating moment. One swing drive variant possesses an integrated transmission with a hydraulic motor with a low specific flow and a reducer with a high transmission ratio, while the other drive variant has the opposite parameters. Understanding this relationship is essential for optimizing the design of excavators to achieve better performance and dynamic stability under varying operational conditions. As an example, this paper provides the analysis results regarding the influence of the relationship between the parameters of the integrated transmission hydraulic motor and reducer on the loading and dynamic stability of the swing drive in a tracked hydraulic excavator of 100,000 kg in mass and 4.4 m3 in loading bucket volume, as obtained from the developed dynamic mathematical models of the excavator using the MSC ADAMS program. The results indicate that the dynamic loads on the swing drive’s axial bearing are higher in the variant with a low-specific-flow motor and high transmission ratio reducer during the acceleration and deceleration phases. However, this configuration demonstrated better dynamic stability, with lower oscillation amplitudes and shorter damping times compared to the variant with a high-flow motor and low transmission ratio. Those findings provide valuable criteria for the optimal synthesis of swing drive mechanisms in large hydraulic excavators using multi-criteria optimization methods.
A Method for Generating Toolpaths in the Manufacturing of Orthosis Molds with a Five-Axis Computer Numerical Control Machine
Authors: Obrovac Karlo , Raos Pero , Staroveški Tomislav , Brezak Danko
Published: October 2024

This paper proposes a new algorithm for the automatic generation of toolpaths for machining complex geometric positions, such as molds used in orthosis production. The production of individualized orthoses often requires the use of multi-axis machining systems, such as five-axis machines or industrial robots. Typically, complex and expensive CAD/CAM systems are used to generate toolpaths for these machines, requiring the definition of a machining strategy for each surface. While this approach can achieve a reliable and high-quality machining process, it is very time-consuming and makes it challenging to meet the criteria for rapid production of orthopedic aids. Given that their production is a custom-made process using individual shapes as inputs, the toolpath generation process becomes even more demanding. To address these challenges, this paper proposes an algorithm suitable for the automatic generation of toolpaths for such complex positions. The proposed algorithm has been tested and has proven to be robust and applicable.
Analysis of Magnetization Dynamics in NiFe Thin Films with Growth-Induced Magnetic Anisotropies
Authors: Merryweather Leah , Hindmarch Aidan T.
Published: October 2024

We have used angled magnetron sputter deposition with and without sample rotation to control the magnetic anisotropy in 20 nm NiFe films. Ferromagnetic resonance spectroscopy, with data analysis using a Bayesian approach, is used to extract material parameters relating to the magnetic anisotropy. When the sample is rotated during growth, only shape anisotropy is present, but when the sample is held fixed, a strong uniaxial anisotropy emerges with in-plane easy axis along the azimuthal direction of the incident atom flux. When the film is deposited in two steps, with an in-plane rotation of 90 degrees between steps, the two orthogonal induced in-plane easy-axes effectively cancel. The analysis approach enables precise and accurate determination of material parameters from ferromagnetic resonance measurements; this demonstrates the ability to precisely control both the direction and strength of uniaxial magnetic anisotropy, which is important in magnetic thin-film device applications.
Dual Stream Encoder–Decoder Architecture with Feature Fusion Model for Underwater Object Detection
Authors: Nissar Mehvish , Mishra Amit Kumar , Subudhi Badri Narayan
Published: October 2024

Underwater surveillance is an imminent and fascinating exploratory domain, particularly in monitoring aquatic ecosystems. This field offers valuable insights into underwater behavior and activities, which have broad applications across various domains. Specifically, underwater surveillance involves detecting and tracking moving objects within aquatic environments. However, the complex properties of water make object detection a challenging task. Background subtraction is a commonly employed technique for detecting local changes in video scenes by segmenting images into the background and foreground to isolate the object of interest. Within this context, we propose an innovative dual-stream encoder–decoder framework based on the VGG-16 and ResNet-50 models for detecting moving objects in underwater frames. The network includes a feature fusion module that effectively extracts multiple-level features. Using a limited set of images and performing training in an end-to-end manner, the proposed framework yields accurate results without post-processing. The efficacy of the proposed technique is confirmed through visual and quantitative comparisons with eight cutting-edge methods using two standard databases. The first one employed in our experiments is the Underwater Change Detection Dataset, which includes five challenges, each challenge comprising approximately 1000 frames. The categories in this dataset were recorded under various underwater conditions. The second dataset used for practical analysis is the Fish4Knowledge dataset, where we considered five challenges. Each category, recorded in different aquatic settings, contains a varying number of frames, typically exceeding 1000 per category. Our proposed method surpasses all methods used for comparison by attaining an average F-measure of 0.98 on the Underwater Change Detection Dataset and 0.89 on the Fish4Knowledge dataset.
An Observer-Based View of Euclidean Geometry
Authors: Bahreyni Newshaw , Cafaro Carlo , Rossetti Leonardo
Published: October 2024

An influence network of events is a view of the universe based on events that may be related to one another via influence. The network of events forms a partially ordered set which, when quantified consistently via a technique called chain projection, results in the emergence of spacetime and the Minkowski metric as well as the Lorentz transformation through changing an observer from one frame to another. Interestingly, using this approach, the motion of a free electron as well as the Dirac equation can be described. Indeed, the same approach can be employed to show how a discrete version of some of the features of Euclidean geometry including directions, dimensions, subspaces, Pythagorean theorem, and geometric shapes can emerge. In this paper, after reviewing the essentials of the influence network formalism, we build on some of our previous works to further develop aspects of Euclidean geometry. Specifically, we present the emergence of geometric shapes, a discrete version of the parallel postulate, the dot product, and the outer (wedge product) in 2+1 dimensions. Finally, we show that the scalar quantification of two concatenated orthogonal intervals exhibits features that are similar to those of the well-known concept of a geometric product in geometric Clifford algebras.
Topological Interactions Between Homotopy and Dehn Twist Varieties
Authors: Bagchi Susmit
Published: October 2024

The topological Dehn twists have several applications in mathematical sciences as well as in physical sciences. The interplay between homotopy theory and Dehn twists exposes a rich set of properties. This paper generalizes the Dehn twists by proposing the notion of pre-twisted space, orientations of twists and the formation of pointed based space under a homeomorphic continuous function. It is shown that the Dehn twisted homotopy under non-retraction admits a left lifting property (LLP) through the local homeomorphism. The LLP extends the principles of Hurewicz fibration by avoiding pullback. Moreover, this paper illustrates that the Dehn twisted homotopy up to a base point in a based space can be formed by considering retraction. As a result, two disjoint continuous functions become point-wise continuous at the base point under retracted homotopy twists. Interestingly, the oriented Dehn twists of a pre-twisted space under homotopy retraction mutually commute in a contractible space.
Adaptive Bi-Level Variable Selection for Quantile Regression Models with a Diverging Number of Covariates
Authors: Ding Xianwen , Yang Zhihuang
Published: October 2024

The paper develops an innovatively adaptive bi-level variable selection methodology for quantile regression models with a diverging number of covariates. Traditional variable selection techniques in quantile regression, such as the lasso and group lasso techniques, offer solutions predominantly for either individual variable selection or group-level selection, but not for both simultaneously. To address this limitation, we introduce an adaptive group bridge approach for quantile regression, to simultaneously select variables at both the group and within-group variable levels. The proposed method offers several notable advantages. Firstly, it adeptly handles the heterogeneous and/or skewed data inherent to quantile regression. Secondly, it is capable of handling quantile regression models where the number of parameters grows with the sample size. Thirdly, via employing an ingeniously designed penalty function, our method surpasses traditional group bridge estimation techniques in identifying important within-group variables with high precision. Fourthly, it exhibits the oracle group selection property, implying that the relevant variables at both the group and within-group levels can be identified with a probability converging to one. Several numerical studies corroborated our theoretical results.
A Lightweight GCT-EEGNet for EEG-Based Individual Recognition Under Diverse Brain Conditions
Authors: Alshehri Laila , Hussain Muhammad
Published: October 2024

A robust biometric system is essential to mitigate various security threats. Electroencephalography (EEG) brain signals present a promising alternative to other biometric traits due to their sensitivity, non-duplicability, resistance to theft, and individual-specific dynamics. However, existing EEG-based biometric systems employ deep neural networks, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which face challenges such as high parameter complexity, limiting their practical application. Additionally, their ability to generalize across a large number of subjects remains unclear. Moreover, they have been validated on datasets collected in controlled environments, which do not accurately reflect real-world scenarios involving diverse brain conditions. To overcome these challenges, we propose a lightweight neural network model, GCT–EEGNet, which is based on the design ideas of a CNN model and incorporates an attention mechanism to pay attention to the appropriate frequency bands for extracting discriminative features relevant to the identity of a subject despite diverse brain conditions. First, a raw EEG signal is decomposed into frequency bands and then passed to GCT–EEGNet for feature extraction, which utilizes a gated channel transformation (GCT) layer to selectively emphasize informative features from the relevant frequency bands. The extracted features were used for subject recognition through a cosine similarity metric that measured the similarity between feature vectors of different EEG trials to identify individuals. The proposed method was evaluated on a large dataset comprising 263 subjects. The experimental results demonstrated that the method achieved a correct recognition rate (CRR) of 99.23% and an equal error rate (EER) of 0.0014, corroborating its robustness against different brain conditions. The proposed model maintains low parameter complexity while keeping the expressiveness of representations, even with unseen subjects.
Leveraging Universal Adversarial Perturbation and Frequency Band Filters Against Face Recognition
Authors: Zhou Limengnan , He Bufan , Jin Xi , Sun Guangling
Published: October 2024

Universal adversarial perturbation (UAP) exhibits universality as it is independent of specific images. Although previous investigations have shown that the classification of natural images is susceptible to universal adversarial attacks, the impact of UAP on face recognition has not been fully investigated. Thus, in this paper we assess the vulnerability of face recognition for UAP. We propose FaUAP-FBF, which exploits the frequency domain by learning high, middle, and low band filters as an additional dimension of refining facial UAP. The facial UAP and filters are alternately and repeatedly learned from a training set. Furthermore, we convert non-target attacks to target attacks by customizing a target example, which is an out-of-distribution sample for a training set. Accordingly, non-target and target attacks form a uniform target attack. Finally, the variance of cosine similarity is incorporated into the adversarial loss, thereby enhancing the attacking capability. Extensive experiments on LFW and CASIA-WebFace datasets show that FaUAP-FBF has a higher fooling rate and better objective stealthiness metrics across the evaluated network structures compared to existing universal adversarial attacks, which confirms the effectiveness of the proposed FaUAP-FBF. Our results also imply that UAP poses a real threat for face recognition systems and should be taken seriously when face recognition systems are being designed.
Some Symmetry and Duality Theorems on Multiple Zeta(-Star) Values
Authors: Chen Kwang-Wu , Eie Minking , Ong Yao Lin
Published: October 2024

In this paper, we provide a symmetric formula and a duality formula relating multiple zeta values and zeta-star values. We find that the summation ∑a+b=r−1(−1)aζ★(a+2,{2}p−1)ζ★({1}b+1,{2}q) equals ζ★({2}p,{1}r,{2}q)+(−1)r+1ζ★({2}q,r+2,{2}p−1). With the help of this equation and Zagier’s ζ★({2}p,3,{2}q) formula, we can easily determine ζ★({2}p,1,{2}q) and several interesting expressions.
Approximation by Symmetrized and Perturbed Hyperbolic Tangent Activated Convolution-Type Operators
Authors: Anastassiou George A.
Published: October 2024

In this article, for the first time, the univariate symmetrized and perturbed hyperbolic tangent activated convolution-type operators of three kinds are introduced. Their approximation properties are presented, i.e., the quantitative convergence to the unit operator via the modulus of continuity. It follows the global smoothness preservation of these operators. The related iterated approximation as well as the simultaneous approximation and their combinations, are also extensively presented. Including differentiability and fractional differentiability into our research produced higher rates of approximation. Simultaneous global smoothness preservation is also examined.
Saccharomyces boulardii Mitigates Fructose-Induced Non-Alcoholic Fatty Liver in Rats
Authors: Ulusan Mehmet , Erdogan Mumin Alper , Simsek Ozkan , Gunes Vehbi , Erbas Oytun
Published: October 2024

Background and Objectives: Non-alcoholic fatty liver disease (NAFLD) is a growing global health concern closely linked to metabolic disorders, including obesity, insulin resistance, and dyslipidemia. Emerging evidence suggests that the gut–liver axis plays a critical role in the pathogenesis of NAFLD, with recent research highlighting the influence of gut microbiota, including fungal species such as Saccharomyces boulardii (S. boulardii). This study aimed to evaluate the effects of S. boulardii on lipid metabolism and oxidative stress in a rat model of fructose-induced NAFLD. Materials and Methods: Thirty Wistar rats were divided into three groups: a control group, a fatty liver group induced by 35% fructose supplementation, and a treatment group receiving S. boulardii (100 mg/kg/day) after fructose induction. Results: Biochemical analyses revealed that the treatment group exhibited significantly lower plasma levels of malondialdehyde (MDA), alanine aminotransferase (ALT), total triglycerides, and cholesterol compared to the untreated fatty liver group (p < 0.05). Furthermore, liver tissue analysis showed a marked reduction in lipid accumulation and fatty infiltration in the treatment group, with no visible lipid vacuoles in hepatocytes. The expression of aquaporin-8 (AQP8) and sirtuin-1 (SIRT1), key markers associated with hepatocyte function and lipid metabolism, was significantly higher in the S. boulardii group compared to the fatty liver group (p < 0.001). Conclusions: These findings indicate that S. boulardii supplementation mitigates the metabolic and oxidative stress-related alterations associated with fructose-induced NAFLD. In conclusion, our study suggests that S. boulardii exerts protective effects on the liver by reducing lipid accumulation and oxidative stress, highlighting its potential as a therapeutic intervention for NAFLD.
Evolution of Graded Surface Microstructure and Property of Ti6Al4V Threads Processed by Surface Rolling
Authors: Wang Wenchao , Bai Lufei , Shi Dapeng , Jin Hong , Yang Yao , Su Kun , Mei Qingsong
Published: October 2024

The surface rolling process is important for the forming property of titanium alloy bolts. This study systematically investigated the evolution of the surface microstructure and property of Ti6Al4V threads induced by surface rolling processes with different feeding times. Gradient surface microstructure and property, as characterized by the depth-dependent variations of refined and deformed grains and hardness, were revealed. A comparative analysis of the microstructure and property of the topmost and subsurface layers in different characteristic areas (root, flank, and crest) of the thread was specifically carried out. The surface microstructure and properties are highly heterogeneous in different areas of the rolled thread. Meanwhile, a gradient microstructure and hardness along the depth from the surface was revealed in the surface layer. Our results showed that the highly heterogeneous surface microstructure and property can be attributed to the close correlation between the different stress/strain levels at different depths from the surface and the different deformation mechanisms in the characteristic surface areas of the thread. The present study has indicated that the distinctive microstructure and property in the different characteristic areas of the rolled thread should be featured by those of surface layers at different depths.
Influence of β-Stabilizing Nb on Phase Stability and Phase Transformation in Ti-Zr Shape Memory Alloys: From the Viewpoint of the First-Principles Calculation
Authors: Feng Xinxin , Chen Xuepei , Yi Xiaoyang , Li Weijian , Liu Chenguang , Meng Xianglong , Gao Zhiyong , Cao Xinjian , Wang Haizhen
Published: October 2024

In the present study, the effect of the Nb element on the lattice parameters, phase stability and martensitic transformation behaviors of Ti-Zr-based shape memory alloys was extensively investigated using the first-principles calculation. The lattice parameters of both the β parent phase and α′ martensite phase gradually decreased with Nb content increasing. For the α″ martensite phase, the lattice constant (a) gradually increased with the increase in Nb content, whereas the lattice constants (b and c) continuously decreased due to the addition of Nb. Based on the formation energy and density of state, β→α′ martensitic transformation occurred, as the Nb content was not more than 12.5 at.%. However, the Ti-Zr-Nb shape memory alloys with a Nb content higher than 12.5 at.% possessed the β→α″ martensitic transformation. However, both the largest transformation strain and sensitivity of critical stress to temperature (dσ/dT) can be optimized by controlling 12.5 at.% Nb in the Ti-Zr-Nb shape memory alloy, which was favorable to obtaining the largest elastocaloric effect.
Predictive Modeling and Optimization of Hot Forging Parameters for AISI 1045 Ball Joints Using Taguchi Methodology and Finite Element Analysis
Authors: Jantepa Naiyanut , Siripath Nattarawee , Suranuntchai Surasak
Published: October 2024

This study focused on optimizing the hot forging process for AISI 1045 medium carbon steel ball joints, which is crucial for enhancing both their mechanical properties and production efficiency. Traditional hot forging processes often face challenges due to variations in flow stress and microstructural outcomes, which can result in a suboptimal product performance. To address these challenges, this research employed the Taguchi method in conjunction with a finite element (FE) simulation to identify the optimal forging parameters. The Arrhenius constitutive model, based on the Zener–Hollomon parameter, was applied to predict the flow stress with a high level of accuracy, achieving a coefficient of determination (R2) of 0.968 and an average absolute relative error (AARE) of 7.079%. An analysis of variance (ANOVA), a statistical innovation that partitions the total variation into components linked to key process factors, was utilized to determine the significance of these parameters. The ANOVA revealed that the billet temperature played a significant role in influencing the preforming force, finishing force, and mean stress, with a maximum impact of 62.30%, 59.50%, and 94.20% on the variation in the response variable, respectively. Additionally, the friction factor significantly affected the preforming and finishing forces, contributing 36.19% and 38.28%. The validation of the model through both simulations and practical experiments is a testament to the reliability of this research, demonstrating the accuracy of the model with minimal discrepancies in the forging forces and exhibiting errors of just 2.88% and 3.40%. Furthermore, microstructure modeling successfully predicted the key outcomes, such as the grain size and pearlite volume fraction, validating the effectiveness of the simulation in forecasting microstructural characteristics.
Exploring the Impact of Catechins on Bone Metabolism: A Comprehensive Review of Current Research and Future Directions
Authors: German Iris Jasmin Santos , Barbalho Sandra Maria , Andreo Jesus Carlos , Zutin Tereza Lais Menegucci , Laurindo Lucas Fornari , Rodrigues Victória Dogani , Araújo Adriano Cressoni , Guiguer Elen Landgraf , Direito Rosa , Pomini Karina Torres , Shinohara André Luis
Published: October 2024

Background/Objectives: Degenerative musculoskeletal diseases represent a global health problem due to the progressive deterioration of affected individuals. As a bioactive compound, catechins have shown osteoprotective properties by stimulating osteoblastic cells and inhibiting bone resorption. Thus, this review aimed to address the mechanism of action of catechins on bone tissue. Methods: The search was applied to PubMed without limitations in date, language, or article type. Fifteen articles matched the topic and objective of this review. Results: EGCG (epigallocatechin gallate) and epicatechin demonstrated action on the osteogenic markers RANKL, TRAP, and NF-κβ and expression of BMPs and ALP, thus improving the bone microarchitecture. Studies on animals showed the action of EGCG in increasing calcium and osteoprotegerin levels, in addition to regulating the transcription factor NF-ATc1 associated with osteoclastogenesis. However, it did not show any effect on osteocalcin and RANK. Regarding human studies, EGCG reduced the risk of fracture in a dose-dependent manner. In periodontal tissue, EGCG reduced IL-6, TNF, and RANKL in vitro and in vivo. Human studies showed a reduction in periodontal pockets, gingival index, and clinical attachment level. The action of EGCG on membranes and hydrogels showed biocompatible and osteoinductive properties on the microenvironment of bone tissue by stimulating the expression of osteogenic growth factors and increasing osteocalcin and alkaline phosphate levels, thus promoting new bone formation. Conclusions: EGCG stimulates cytokines related to osteogenes, increasing bone mineral density, reducing osteoclastogenesis factors, and showing great potential as a therapeutic strategy for reducing the risk of bone fractures.
The Underlying Effect of Urate Levels on Female Infertility
Authors: Naveed Muhammad , Hill Jennifer W.
Published: October 2024

Female infertility is a complex and multifaceted condition that affects millions of women globally [...]
Low Serum Fibroblast Growth Factor 21 Level and Its Altered Regulation by Thyroid Hormones in Patients with Hashimoto’s Thyroiditis on Levothyroxine Substitution
Authors: Berta Eszter , Halmi Sándor , Molnár István , Hutkai Dávid , Csiha Sára , Bhattoa Harjit Pal , Lőrincz Hajnalka , Somodi Sándor , Katkó Mónika , Harangi Mariann , Paragh György , Nagy Endre V. , Bodor Miklós
Published: October 2024

Background/Objectives: Fibroblast growth factor 21 (FGF21) is a hormonal regulator of lipid and glucose metabolism exerting protection against atherosclerosis by multiple actions on the blood vessels, liver, and adipose tissues. We aimed to investigate serum FGF21 level and its relation to thyroid hormones and metabolic parameters among patients with Hashimoto’s thyroiditis (HT). Methods: Eighty patients with HT on levothyroxine treatment and eighty-two age- and BMI-matched adults without thyroid disease serving as controls were enrolled. Serum FGF21 concentrations were determined with an enzyme-linked immunosorbent assay. Results: Median serum FGF21 level was significantly lower in HT patients compared with controls (74.2 (33.4–148.3) pg/mL vs. 131.9 (44.8–236.3) pg/mL; p = 0.03). We found a positive correlation between FGF21 and age, triglyceride, total cholesterol, and low-density lipoprotein cholesterol in both groups, while thyroid stimulating hormone and C-reactive protein showed a positive correlation, and thyroxine had an inverse correlation with FGF21 only in control subjects. According to multiple regression analyses, thyroid status is the main predictor of FGF21 in healthy controls, while it is not a significant predictor of FGF21 among HT patients on levothyroxine supplementation therapy. Conclusions: Our results indicate that the physiological role of thyroid function in the regulation of FGF21 synthesis is impaired in HT patients, which may contribute to the metabolic alterations characteristic of HT patients.
Metabolomics Approach to Identify Biomarkers of Acute and Subacute Mastitis in Milk Samples: A Pilot Case–Control Study
Authors: Quifer-Rada Paola , Aguilar-Camprubí Laia , Samino Sara , Amigó Nuria , Soler Oria , Padró-Arocas Alba
Published: October 2024

Background and aims: Mastitis is one of the main complications during breastfeeding and contributes to the cessation of breastfeeding. However, the etiopathogenesis and diagnosis of mastitis are complex and not yet well defined. We aimed to identify metabolic and lipidic changes in human milk during acute and subacute mastitis in order to detect potential biomarkers of mastitis. Methods: We conducted a pilot case–control study including 14 breastfeeding women with acute mastitis, 32 with subacute mastitis symptoms, and 19 without any mastitis symptoms (control). Milk samples were collected and analyzed by proton nuclear magnetic resonance (H-NMR) for metabolomics analysis. To assess the association between the significant metabolites and lipids and the development of acute and subacute mastitis, multi-adjusted logistic regression models were developed. Results: The NMR-based metabolomics approach was able to identify and quantify a total of 40 metabolites in breast milk samples. After adjusting for confounding variables, acute mastitis was significantly associated with acetate (OR 3.9 IC 1.4–10.8), total cholesterol (OR 14 CI 3.2–62), esterified cholesterol (OR 3.3 CI 1.9–5.8), and sphingomyelin (OR 2.6 CI 1.2–5.8). The other metabolites presented weak association (OR < 2.5). Subacute mastitis was significantly associated with glutamine, lysophosphatidylcholine, phosphatidylcholine, plasmalogen, and total polyunsaturated fatty acids, but only cholesterol showed a strong association (OR > 2.5) with an OR of 2.6 (IC 1.1–6.6). Conclusions: Metabolic alteration in breast milk occurs during a process of both acute and subacute mastitis. Acetate, esterified cholesterol, lysophostidylcholine, and polyunsaturated fatty acids increased in both acute and subacute mastitis. However, according to the multi-adjusted regression logistic models, the candidate biomarkers for acute and subacute mastitis are cholesterol, lysophosphatidylcoholine, phosphatidylcholine, plasmalogen, and polyunsaturated fatty acids.
Metabolomics Reveal Key Metabolic Pathway Responses to Anxiety State Regulated by Serotonin in Portunus trituberculatus
Authors: Zhai Wei , Fu Yuanyuan , Liu Lei , Huang Xinlian , Wang Sixiang
Published: October 2024

Background: Anxiety refers to the pathological persistence and intensification of emotional responses to danger, affecting health from psychological and physical aspects. Serotonin is an important neurotransmitter involved in the onset of anxiety. Methods and Results: To explore the biological changes in the formation of anxiety in crustaceans under the regulation of serotonin, we applied the open field-like test method for assessing anxiety states of larval Portunus trituberculatus, a highly aggressive crustacean species with a more simple neural structure compared with rodents and mammals. Compared with the control group, serotonin treatment resulted in a significant decrease in the time spent by the larvae in the central zone, suggesting anxiety-like behavior. Clonazepam treatment reversed this result and provided further evidence that the behavior of larval P. trituberculatus displayed anxiety. Moreover, a non-targeted metabolomic analysis found a significant alteration in the metabolites involved in tryptophan metabolism pathways associated with anxiety, including L-kynurenine, N-acetyl serotonin, and serotonin. These metabolites are involved in the serotonin pathway, the kynurenine pathway, and other pathways that affect anxiety through tryptophan metabolism. There were no significant differences in tryptophan metabolism levels between the control and clonazepam treatment groups. Conclusions: Our results demonstrate the possible existence of anxiety-like behavior in the larvae of P. trituberculatus from two perspectives. Being a species with a simpler neural structure than that of mammals, the larvae of P. trituberculatus offer a convenient model for studying the mechanisms of anxiety in crustaceans.