bluuebunny/crossref_metadata_2025 huggingface dataset:
Navigating Post-COVID-19 Social–Spatial Inequity: Unravelling the Nexus between Community Conditions, Social Perception, and Spatial Differentiation
Authors: Zhao Minjun , Liu Ning , Chen Jinliu , Wang Danqing , Li Pengcheng , Yang Di , Zhou Pu
Published: April 2024

The 2023 SDGs report underscores the prolonged disruption of COVID-19 on community living spaces, infrastructure, education, and income equality, exacerbating social and spatial inequality. Against the backdrop of the dual impact of significant events and the emergence of digital technologies, a coherent research trajectory is essential for characterizing social–spatial equity and understanding its influential factors within the urban planning discipline. While prior research emphasized spatial dimensions and mitigated spatial differentiation to ensure urban equity, the complexity of these interconnections necessitates a more comprehensive approach. This study adopts a holistic perspective, focusing on the “social–spatial” dynamics, utilizing social perception (sentiment maps) and spatial differentiation (housing prices index) pre- and post-pandemic to elucidate the interconnected and interactive nature of uneven development at the urban scale. It employs a multi-dimensional methodological framework integrating morphology analysis of housing conditions, GIS analysis of urban amenities, sentiment semantic analysis of public opinion, and multiscale geographically weighted regression (MGWR) analysis of correlation influential factors. Using Suzhou, China, as a pilot study, this research demonstrates how these integrated methods complement each other, exploring how community conditions and resource distribution collectively bolster resilience, thereby maintaining social–spatial equity amidst pandemic disruptions. The findings reveal that uneven resource distribution exacerbates post-pandemic social stratification and spatial differentiation. The proximity of well-maintained ecological environments, such as parks or scenic landmarks, generally exhibits consistency and positive effects on “social–spatial” measurement. Simultaneously, various spatial elements influencing housing prices and social perception show geographic heterogeneity, particularly in areas farther from the central regions of Xiangcheng and Wujiang districts. This study uncovers a bilateral mechanism between social perception and spatial differentiation, aiming to delve into the interdependent relationship between social–spatial equity and built environmental factors. Furthermore, it aspires to provide meaningful references and recommendations for urban planning and regeneration policy formulation in the digital era to sustain social–spatial equity.
Evaluating the Efficacy of Resect-and-Discard and Resect-and-Retrieve Strategies for Diminutive Colonic Polyps
Authors: Groza Andrei Lucian , Miutescu Bogdan , Tefas Cristian , Popa Alexandru , Ratiu Iulia , Sirli Roxana , Popescu Alina , Motofelea Alexandru Catalin , Tantau Marcel
Published: April 2024

Background and Objectives: Diminutive polyps present a unique challenge in colorectal cancer (CRC) prevention strategies. This study aims to assess the characteristics and variables of diminutive polyps in a Romanian cohort, intending to develop a combined resect-and-retrieve or resect-and-discard strategy that reduces the need for an optical diagnosis. Materials and Methods: A prospective cohort study was conducted at two endoscopy centers in Romania from July to December 2021. Adult patients undergoing colonoscopies where polyps were identified and resected were included. Endoscopic procedures employed advanced diagnostic features, including blue-light imaging (BLI) and narrow-band imaging (NBI). Logistic regression analysis was utilized to determine factors impacting the probability of adenomatous polyps with high-grade dysplasia (HGD). Results: A total of 427 patients were included, with a mean age of 59.42 years (±11.19), predominantly male (60.2%). The most common indication for a colonoscopy was lower gastrointestinal symptoms (42.6%), followed by screening (28.8%). Adequate bowel preparation was achieved in 87.8% of cases. The logistic regression analysis revealed significant predictors of HGD in adenomatous polyps: age (OR = 1.05, 95% CI: 1.01–1.08, p = 0.01) and polyp size (>5 mm vs. ≤5 mm, OR = 4.4, 95% CI: 1.94–10.06, p < 0.001). Polyps classified as Paris IIa, Ip, and Isp were significantly more likely to harbor HGD compared to the reference group (Is), with odds ratios of 6.05, 3.68, and 2.7, respectively. Conclusions: The study elucidates significant associations between the presence of HGD in adenomatous polyps and factors such as age, polyp size, and Paris classification. These findings support the feasibility of a tailored approach in the resect-and-discard and resect-and-retrieve strategies for diminutive polyps, potentially optimizing CRC prevention and intervention practices. Further research is warranted to validate these strategies in broader clinical settings.
Aflatoxins in Wheat Grains: Detection and Detoxification through Chemical, Physical, and Biological Means
Authors: Ismail Ahmed Mahmoud , Raza Muhammad Hassan , Zahra Naseem , Ahmad Rafiq , Sajjad Yasar , Khan Sabaz Ali
Published: April 2024

Wheat (Triticum aestivum L.) is an essential food crop in terms of consumption as well as production. Aflatoxin exposure has a widespread public health impact in economically developing nations, so there is a need to establish preventive techniques for these high-risk populations. Pre-harvest and post-harvest practices are the two strategies used to control aflatoxin contamination, which include the use of genetically modified crops that show resistance against Aspergillus infection, the use of pesticides, changing the planting and harvesting time of crops, and physical, chemical, and biological methods. In this research, aflatoxin detection and quantification were performed in different wheat varieties to determine quantitative differences in comparison to the European Commission’s limit of 4 ppb aflatoxins in wheat. TLC for qualitative and the ELISA kit method for quantitative analysis of aflatoxins were used. Out of 56 samples, 35 were found contaminated with aflatoxins, while the remaining 21 samples did not show any presence of aflatoxins. Out of the 35 contaminated samples, 20 samples showed aflatoxin contamination within the permissible limit, while the remaining 15 samples showed aflatoxin concentration beyond the permissible level, ranging from 0.49 to 20.56 ppb. After quantification, the nine highly contaminated wheat samples were detoxified using physical, chemical, and biological methods. The efficiency of these methods was assessed, and they showed a significant reduction in aflatoxins of 53–72%, 79–88%, and 80–88%, respectively. In conclusion, the difference in aflatoxin concentration in different wheat varieties could be due to genetic variations. Furthermore, biological treatment could be the method of choice for detoxification of aflatoxins in wheat as it greatly reduced the aflatoxin concentration with no harmful effect on the quality of the grains.
The Anti-Cholinesterase Potential of Fifteen Different Species of Narcissus L. (Amaryllidaceae) Collected in Spain
Authors: Tallini Luciana R. , Manfredini Giulia , Rodríguez-Escobar María Lenny , Ríos Segundo , Martínez-Francés Vanessa , Feresin Gabriela E. , Borges Warley de Souza , Bastida Jaume , Viladomat Francesc , Torras-Claveria Laura
Published: April 2024

Narcissus L. is a renowned plant genus with a notable center of diversity and is primarily located in the Mediterranean region. These plants are widely recognized for their ornamental value, owing to the beauty of their flowers; nonetheless, they also hold pharmacological importance. In Europe, pharmaceutical companies usually use the bulbs of Narcissus pseudonarcissus cv. Carlton to extract galanthamine, which is one of the few medications approved by the FDA for the palliative treatment of mild-to-moderate symptoms of Alzheimer’s disease. The purpose of this study was to evaluate the potential of these plants in Alzheimer’s disease. The alkaloid extract from the leaves of different species of Narcissus was obtained by an acid-base extraction work-up -procedure. The biological potential of the samples was carried out by evaluating their ability to inhibit the enzymes acetyl- and butyrylcholinesterase (AChE and BuChE, respectively). The species N. jacetanus exhibited the best inhibition values against AChE, with IC50 values of 0.75 ± 0.03 µg·mL−1, while N. jonquilla was the most active against BuChE, with IC50 values of 11.72 ± 1.15 µg·mL−1.
A Real-Time Dual-Task Defect Segmentation Network for Grinding Wheels with Coordinate Attentioned-ASP and Masked Autoencoder
Authors: Li Yifan , Li Chuanbao , Zhang Ping , Wang Han
Published: April 2024

The current network for the dual-task grinding wheel defect semantic segmentation lacks high-precision lightweight designs, making it challenging to balance lightweighting and segmentation accuracy, thus severely limiting its practical application in grinding wheel production lines. Additionally, recent approaches for addressing the natural class imbalance in defect segmentation fail to leverage the inexhaustible unannotated raw data on the production line, posing huge data wastage. Targeting these two issues, firstly, by discovering the similarity between Coordinate Attention (CA) and ASPP, this study has introduced a novel lightweight CA-ASP module to the DeeplabV3+, which is 45.3% smaller in parameter size and 53.2% lower in FLOPs compared to the ASPP, while achieving better segmentation precision. Secondly, we have innovatively leveraged the Masked Autoencoder (MAE) to address imbalance. By developing a new Hybrid MAE and applying it to self-supervised pretraining on tremendous unannotated data, we have significantly uplifted the network’s semantic understanding on the minority classes, which leads to further rises in both the overall accuracy and accuracy of the minorities without additional computational growth. Lastly, transfer learning has been deployed to fully utilize the highly related dual tasks. Experimental results demonstrate that the proposed methods with a real-time latency of 9.512 ms obtain a superior segmentation accuracy on the mIoU score over the compared real-time state-of-the-art methods, excelling in managing the imbalance and ensuring stability on the complicated scenes across the dual tasks.
On the Integrity of Large-Scale Direct-Drive Wind Turbine Electrical Generator Structures: An Integrated Design Methodology for Optimisation, Considering Thermal Loads and Novel Techniques
Authors: Bichan Magnus , Jaen-Sola Pablo , Gonzalez-Delgado Daniel , Oterkus Erkan
Published: April 2024

With the rapid expansion of offshore wind capacity worldwide, minimising operation and maintenance requirements is pivotal. Regarded as a low-maintenance alternative to conventional drivetrain systems, direct-drive generators are increasingly commonplace for wind turbines in hard-to-service areas. To facilitate higher torque requirements consequent to low-speed operation, these machines are bulky, greatly increasing nacelle size and mass over their counterparts. This paper therefore details the structural optimisation of the International Energy Agency 15 MW Reference Wind Turbine rotor through iterative Parameter and Topology Optimisation and the inclusion of additional structural members, with consideration to its mechanical, modal, and thermal performances. With temperature found to have a significant impact on the structural integrity of multi-megawatt direct-drive machines, a Computational Fluid Dynamics analysis was carried out to map the temperature of the structure during operation and inform a consequent Finite Element Method analysis. This process, novel to this paper, found that topologically optimised structures outperform parametrically optimised structures thermally and that integrated heatsinks can be employed to further reduce deformation. Lastly, generative design techniques were used to further optimise the structure, reducing its mass, deformation, and maximum stress and expanding its operating envelope. This study reaches several key conclusions, demonstrating that significant mass reductions are achievable through the removal of cylinder wall geometry areas as well as through the implementation of structural supports and iterative parametric and topology optimisation techniques. Through the flexibility it grants, generative design was found to be a powerful tool, delivering further improvements to an already efficient, yet complex design. Heatsinks were found to lower generator structural temperatures, which may yield lower active cooling requirements whilst providing structural support. Lastly, the link between the increased mass and the increased financial and environmental impact of the rotor was confirmed.
Study on Performance Improvement through Reducing Axial Force of Ferrite Double-Layer Spoke-Type Permanent Magnet Synchronous Motor with Core Skew
Authors: Nam Dong-Woo , Lee Kangbeen , Song Si-Woo , Kim Won-Ho , Lee Jae-Jun
Published: April 2024

Recently, due to the price fluctuation and supply instability of rare earth mineral resources, there has been a lot of development of electric motors using non-rare-earth permanent magnets. As a result, motors using Dy-free permanent magnets and ferrite permanent magnets are being researched, and, in particular, ferrite permanent magnets often utilize spoke-type structures, which are magnetic flux concentrators, to compensate for their low coercivity and residual flux density. However, in general, spoke-type PMSMs do not use much reluctance torque, so double-layer spoke-type PMSMs have been studied for their more efficient design. Unlike general spoke-type PMSMs, double-layer spoke-type PMSMs can utilize high reluctance torque by increasing the difference between d-axis and q-axis reluctance. However, as the difference in magnetic resistance increases, vibration and noise are generated, which adversely affects the mechanical part and shortens the life of the motor. Although this problem seemed to be solved by applying core skew in the previous study, it was confirmed that the axial force caused by the axial leakage flux occurred in the maximum torque per ampere (MTPA) control section and the torque ripple was increased. Therefore, in this paper, a model that can apply symmetrical core skew and reduce axial force is proposed. First, the causes of the axial force generated in previous studies were analyzed. Based on the analysis of these causes, a new symmetrical core skew structure was proposed, and its justification was verified through FEA.
Re-Entrant Green Scheduling Problem of Bearing Production Shops Considering Job Reworking
Authors: Wang Yansen , Shi Jianwei , Wang Wenjie , Li Cheng
Published: April 2024

To solve various reworking and repair problems caused by unqualified bearing product quality inspections, this paper introduces a green re-entrant scheduling optimization method for bearing production shops considering job reworking. By taking into account quality inspection constraints, this paper establishes an integrated scheduling mathematical model based on the entire processing–transportation–assembly process of bearing production shops with the goals for minimizing the makespan, total carbon emissions, and waste emissions. To solve these problems, the concepts of the set of the longest common machine routes (SLCMR) and the set of the shortest recombination machine combinations (SSRMC) were used to propose the re-entrant scheduling optimization method, based on system reconfiguration, to enhance the system stability and production scheduling efficiency. Then, a multi-objective hybrid optimization algorithm, based on a neighborhood local search (MOOA-LS), is proposed to improve the search scope and optimization ability by constructing a multi-level neighborhood search structure. Finally, this paper takes a bearing production shop as an example to carry out the case study and designs a series of experimental analyses and comparative tests. The final results show that in the bearing production process, the proposed model and algorithm can effectively realize green and energy-saving re-entrant manufacturing scheduling.
Fractional-Order Sliding Mode Observer for Actuator Fault Estimation in a Quadrotor UAV
Authors: Borja-Jaimes Vicente , Coronel-Escamilla Antonio , Escobar-Jiménez Ricardo Fabricio , Adam-Medina Manuel , Guerrero-Ramírez Gerardo Vicente , Sánchez-Coronado Eduardo Mael , García-Morales Jarniel
Published: April 2024

In this paper, we present the design of a fractional-order sliding mode observer (FO-SMO) for actuator fault estimation in a quadrotor unmanned aerial vehicle (QUAV) system. Actuator faults can significantly compromise the stability and performance of QUAV systems; therefore, early detection and compensation are crucial. Sliding mode observers (SMOs) have recently demonstrated their accuracy in estimating faults in QUAV systems under matched uncertainties. However, existing SMOs encounter difficulties associated with chattering and sensitivity to initial conditions and noise. These challenges significantly impact the precision of fault estimation and may even render fault estimation impossible depending on the magnitude of the fault. To address these challenges, we propose a new fractional-order SMO structure based on the Caputo derivative definition. To demonstrate the effectiveness of the proposed FO-SMO in overcoming the limitations associated with classical SMOs, we assess the robustness of the FO-SMO under three distinct scenarios. First, we examined its performance in estimating actuator faults under varying initial conditions. Second, we evaluated its ability to handle significant chattering phenomena during fault estimation. Finally, we analyzed its performance in fault estimation under noisy conditions. For comparison purposes, we assess the performance of both observers using the Normalized Root-Mean-Square Error (NRMSE) criterion. The results demonstrate that our approach enables more accurate actuator fault estimation, particularly in scenarios involving chattering phenomena and noise. In contrast, the performance of classical (non-fractional) SMO suffers significantly under these conditions. We concluded that our FO-SMO is more robust to initial conditions, chattering phenomena, and noise than the classical SMO.
Tampered Random Variable Analysis in Step-Stress Testing: Modeling, Inference, and Applications
Authors: Ahmad Hanan Haj , Ramadan Dina A. , Almetwally Ehab M.
Published: April 2024

This study explores a new dimension of accelerated life testing by analyzing competing risk data through Tampered Random Variable (TRV) modeling, a method that has not been extensively studied. This method is applied to simple step-stress life testing (SSLT), and it considers multiple causes of failure. The lifetime of test units under changeable stress levels is modeled using Power Rayleigh distribution with distinct scale parameters and a constant shape parameter. The research introduces unique tampering coefficients for different failure causes in step-stress data modeling through TRV. Using SSLT data, we calculate maximum likelihood estimates for the parameters of our model along with the tampering coefficients and establish three types of confidence intervals under the Type-II censoring scheme. Additionally, we delve into Bayesian inference for these parameters, supported by suitable prior distributions. Our method’s validity is demonstrated through extensive simulations and real data application in the medical and electrical engineering fields. We also propose an optimal stress change time criterion and conduct a thorough sensitivity analysis.
Lie Modules of Banach Space Nest Algebras
Authors: Capitão Pedro , Oliveira Lina
Published: April 2024

In the present work, we extend to Lie modules of Banach space nest algebras a well-known characterisation of Lie ideals of (Hilbert space) nest algebras. Let A be a Banach space nest algebra and L be a weakly closed Lie A-module. We show that there exist a weakly closed A-bimodule K, a weakly closed subalgebra DK of A, and a largest weakly closed A-bimodule J contained in L,such that J⊆L⊆K+DK, with [K,A]⊆L. The first inclusion holds in general, whilst the second is shown to be valid in a class of nest algebras.
A Nonlinear ODE Model for a Consumeristic Society
Authors: Badiale Marino , Cravero Isabella
Published: April 2024

In this paper, we introduce an ODE system to model the interaction between natural resources and human exploitation in a rich consumeristic society. In this model, the rate of change in population depends on wealth per capita, and the rate of consumption has a quadratic growth with respect to population and wealth. We distinguish between renewable and non-renewable resources, and we introduce a replenishment term for non-renewable resources. We first obtain some information on the asymptotic behavior of wealth and population, then we compute all system equilibria and study their stability when the resource exploitation parameter is low. Some numerical simulations confirm the theoretical results and suggest directions for future research.
A Novel Computational Instrument Based on a Universal Mixture Density Network with a Gaussian Mixture Model as a Backbone for Predicting COVID-19 Variants’ Distributions
Authors: Al-Hadeethi Yas , El Ramley Intesar F. , Mohammed Hiba , Bedaiwi Nada M. , Barasheed Abeer Z.
Published: April 2024

Various published COVID-19 models have been used in epidemiological studies and healthcare planning to model and predict the spread of the disease and appropriately realign health measures and priorities given the resource limitations in the field of healthcare. However, a significant issue arises when these models need help identifying the distribution of the constituent variants of COVID-19 infections. The emergence of such a challenge means that, given limited healthcare resources, health planning would be ineffective and cost lives. This work presents a universal neural network (NN) computational instrument for predicting the mainstream symptomatic infection rate of COVID-19 and models of the distribution of its associated variants. The NN is based on a mixture density network (MDN) with a Gaussian mixture model (GMM) object as a backbone. Twelve use cases were used to demonstrate the validity and reliability of the proposed MDN. The use cases included COVID-19 data for Canada and Saudi Arabia, two date ranges (300 and 500 days), two input data modes, and three activation functions, each with different implementations of the batch size and epoch value. This array of scenarios provided an opportunity to investigate the impacts of epistemic uncertainty (EU) and aleatoric uncertainty (AU) on the prediction model’s fitting. The model accuracy readings were in the high nineties based on a tolerance margin of 0.0125. The primary outcome of this work indicates that this easy-to-use universal MDN helps provide reliable predictions of COVID-19 variant distributions and the corresponding synthesized profile of the mainstream infection rate.
Urban Origin–Destination Travel Time Estimation Using K-Nearest-Neighbor-Based Methods
Authors: Lagos Felipe , Moreno Sebastián , Yushimito Wilfredo F. , Brstilo Tomás
Published: April 2024

Improving the estimation of origin–destination (O-D) travel times poses a formidable challenge due to the intricate nature of transportation dynamics. Current deep learning models often require an overwhelming amount of data, both in terms of data points and variables, thereby limiting their applicability. Furthermore, there is a scarcity of models capable of predicting travel times with basic trip information such as origin, destination, and starting time. This paper introduces novel models rooted in the k-nearest neighbor (KNN) algorithm to tackle O-D travel time estimation with limited data. These models represent innovative adaptations of weighted KNN techniques, integrating the haversine distance of neighboring trips and incorporating correction factors to mitigate prediction biases, thereby enhancing the accuracy of travel time estimations for a given trip. Moreover, our models incorporate an adaptive heuristic to partition the time of day, identifying time blocks characterized by similar travel-time observations. These time blocks facilitate a more nuanced understanding of traffic patterns, enabling more precise predictions. To validate the effectiveness of our proposed models, extensive testing was conducted utilizing a comprehensive taxi trip dataset sourced from Santiago, Chile. The results demonstrate substantial improvements over existing state-of-the-art models (e.g., MAPE between 35 to 37% compared to 49 to 60% in other methods), underscoring the efficacy of our approach. Additionally, our models unveil previously unrecognized patterns in city traffic across various time blocks, shedding light on the underlying dynamics of urban mobility.
Performance Analysis of RIS-Assisted SatComs Based on a ZFBF and Co-Phasing Scheme
Authors: Jung Minchae , Kim Taehyoung , Son Hyukmin
Published: April 2024

In recent high-throughput satellite communication (SatCom) systems, the use of reconfigurable intelligent surfaces (RISs) has emerged as a promising solution to improve spectral efficiency and extend coverage in areas with limited terrestrial network access. However, the RIS may amplify the inter-beam interference (IBI) caused by multibeam transmission at the satellite, and multiple RISs can also cause inter-RIS interference (IRI) to terrestrial users. In this paper, the performance of the RIS-assisted SatCom system is asymptotically analyzed for both full and partial channel state information (CSI) scenarios. In particular, zero-forcing beamforming is considered as the active beamforming for data transmission, while the co-phasing scheme is considered as the passive beamforming for RIS reflection. Based on the asymptotic analyses, deterministic active and passive beamforming techniques using partial CSI are proposed that can gradually eliminate both IBI and IRI, ultimately achieving ideal performance. Simulation results validate the accuracy of asymptotic analyses and demonstrate the superiority of deterministic active and passive beamforming techniques using partial CSI. The simulation results also confirm that the proposed beamforming can achieve approximately 92.8% of the ideal performance, even though it only requires partial CSI.
Fixed-Order Chemical Trees with Given Segments and Their Maximum Multiplicative Sum Zagreb Index
Authors: Ali Akbar , Noureen Sadia , Moeed Abdul , Iqbal Naveed , Hassan Taher S.
Published: April 2024

Topological indices are often used to predict the physicochemical properties of molecules. The multiplicative sum Zagreb index is one of the multiplicative versions of the Zagreb indices, which belong to the class of most-examined topological indices. For a graph G with edge set E={e1,e2,⋯,em}, its multiplicative sum Zagreb index is defined as the product of the numbers D(e1),D(e2),⋯,D(em), where D(ei) is the sum of the degrees of the end vertices of ei. A chemical tree is a tree of maximum degree at most 4. In this research work, graphs possessing the maximum multiplicative sum Zagreb index are determined from the class of chemical trees with a given order and fixed number of segments. The values of the multiplicative sum Zagreb index of the obtained extremal trees are also obtained.
On a Family of Hamilton–Poisson Jerk Systems
Authors: Lăzureanu Cristian , Cho Jinyoung
Published: April 2024

In this paper, we construct a family of Hamilton–Poisson jerk systems. We show that such a system has infinitely many Hamilton–Poisson realizations. In addition, we discuss the stability and we prove the existence of periodic orbits around nonlinearly stable equilibrium points. Particularly, we deduce conditions for the existence of homoclinic and heteroclinic orbits. We apply the obtained results to a family of anharmonic oscillators.
The Efficiency of Hazard Rate Preservation Method for Generating Discrete Rayleigh–Lindley Distribution
Authors: Ahmad Hanan Haj
Published: April 2024

In this study, we introduce two novel discrete counterparts for the Rayleigh–Lindley mixture, constructed through the application of survival and hazard rate preservation techniques. These two-parameter discrete models demonstrate exceptional adaptability across various data types, including skewed, symmetric, and monotonic datasets. Statistical analyses were conducted using maximum likelihood estimation and Bayesian approaches to assess these models. The Bayesian analysis, in particular, was implemented with the squared error and LINEX loss functions, incorporating a modified Lwin Prior distribution for parameter estimation. Through simulation studies and numerical methods, we evaluated the estimators’ performance and compared the effectiveness of the two discrete adaptations of the Rayleigh–Lindley distribution. The simulations reveal that Bayesian methods are especially effective in this setting due to their flexibility and adaptability. They provide more precise and dependable estimates for the discrete Rayleigh–Lindley model, especially when using the hazard rate preservation method. This method is a compelling alternative to the traditional survival discretization approach, showcasing its significant potential in enhancing model accuracy and applicability. Furthermore, two real data sets are analyzed to assess the performance of each analog.
Numerical Analysis for Sturm–Liouville Problems with Nonlocal Generalized Boundary Conditions
Authors: Liu Chein-Shan , Chang Chih-Wen , Kuo Chung-Lun
Published: April 2024

For the generalized Sturm–Liouville problem (GSLP), a new formulation is undertaken to reduce the number of unknowns from two to one in the target equation for the determination of eigenvalue. The eigenparameter-dependent shape functions are derived for using in a variable transformation, such that the GSLP becomes an initial value problem for a new variable. For the uniqueness of eigenfunction an extra condition is imposed, which renders the right-end value of the new variable available; a derived implicit nonlinear equation is solved by an iterative method without using the differential; we can achieve highly precise eigenvalues. For the nonlocal Sturm–Liouville problem (NSLP), we consider two types of integral boundary conditions on the right end. For the first type of NSLP we can prove sufficient conditions for the positiveness of the eigenvalue. Negative eigenvalues and multiple solutions may exist for the second type of NSLP. We propose a boundary shape function method, a two-dimensional fixed-quasi-Newton method and a combination of them to solve the NSLP with fast convergence and high accuracy. From the aspect of numerical analysis the initial value problem of ordinary differential equations and scalar nonlinear equations are more easily treated than the original GSLP and NSLP, which is the main novelty of the paper to provide the mathematically equivalent and simpler mediums to determine the eigenvalues and eigenfunctions.
Link Prediction and Graph Structure Estimation for Community Detection
Authors: Chen Dongming , Nie Mingshuo , Xie Fei , Wang Dongqi , Chen Huilin
Published: April 2024

In real-world scenarios, obtaining the relationships between nodes is often challenging, resulting in incomplete network topology. This limitation significantly reduces the applicability of community detection methods, particularly neighborhood aggregation-based approaches, on structurally incomplete networks. Therefore, in this situation, it is crucial to obtain meaningful community information from the limited network structure. To address this challenge, the LPGSE algorithm was designed and implemented, which includes four parts: link prediction, structure observation, network estimation, and community partitioning. LPGSE demonstrated its performance in community detection in structurally incomplete networks with 10% missing edges on multiple datasets. Compared with traditional community detection algorithms, LPGSE achieved improvements in NMI and ARI metrics of 1.5781% to 29.0780% and 0.4332% to 31.9820%, respectively. Compared with similar community detection algorithms for structurally incomplete networks, LPGSE also outperformed other algorithms on all datasets. In addition, different edge-missing ratio settings were also attempted, and the performance of different algorithms in these situations was compared and analyzed. The results showed that the algorithm can still maintain high accuracy and stability in community detection across different edge-missing ratios.
Applying a Mathematical Model for Calculating the Ideal Nutrition for Sheep
Authors: Pavlova Kristina , Trichkova-Kashamova Elisaveta , Dimitrov Stanislav
Published: April 2024

The principal economic sector devoted to the breeding, raising, and production of farm animals is known as the livestock industry. There are precise standards for making high-quality feed in animal husbandry. Precision livestock feeding is a crucial component, with the potential to significantly impact the profitability of livestock; it permits the provision of diets to animals that are precisely tailored to their specific daily nutritional needs. Through simulation modeling, a single model can be created for automated systems to determine daily rations for farm animals. For the purposes of this document, precision livestock feeding refers to the practice of tailoring feed to individual animals or groups of animals, taking into account their changing nutritional needs over time and individual differences in terms of nutritional requirements. The practice aims to optimize animal health and performance while reducing feed waste. This paper presents a formal model for determining the quantities of components needed to achieve a minimum cost mixture that satisfies compositional and quantitative criteria. The present research calculates the amount of hay and silage required to feed an animal per day at the most economical cost by applying an optimization approach that involves defining and solving an optimization problem. The problem is solved using a well-known software package, which is necessary for the practical application of the resulting model. Real data from livestock production in Bulgaria are used to numerically test the model.
Histologically Validated Myocardial Fibrosis in Relation to Left Ventricular Geometry and Its Function in Aortic Stenosis
Authors: Aitaliyev Serik , Rumbinaitė Egle , Jurenas Martynas , Čeponienė Indrė , Keturakis Vytenis , Nekrošius Rokas , Orazymbetov Yerlan , Benetis Rimantas , Pangonytė Dalia
Published: April 2024

Background and Objectives: The combination of aortic valve stenosis (AS) and ischemic heart disease (IHD) is quite common and is associated with myocardial fibrosis (MF). The purpose of this study was to evaluate the association between the histologically verified left ventricular (LV) MF and its geometry and function in isolated AS and AS within IHD groups. Materials and Methods: In a single-center, prospective trial, 116 patients underwent aortic valve replacement (AVR) with/without concomitant surgery. The study population was divided into groups of isolated AS with/without IHD. Echocardiography was used, and LV measurements and aortic valve parameters were obtained from all patients. Myocardial tissue was procured from all study patients undergoing elective surgery. Results: There were no statistical differences between isolated AS and AS+IHD groups in LV parameters or systolic and diastolic functions during the study periods. The collagen volume fraction was significantly different between the isolated AS and AS+IHD groups and was 7.3 ± 5.6 and 8.3 ± 6.4, respectively. Correlations between MF and left ventricular end-diastolic diameter (LVEDD) (r = 0.59, p = < 0.001), left ventricular mass (LVM) (r = 0.42, p = 0.011), left ventricular ejection fraction (LVEF) (r = −0.67, p < 0.001) and an efficient orifice area (EOA) (r = 0.371, p = 0.028) were detected in isolated AS during the preoperative period; the same was observed for LVEDD (r = 0.45, p = 0.002), LVM (r = 0.36, p = 0.026), LVEF (r = −0.35, p = 0.026) and aortic annulus (r = 0.43, p = 0.018) in the early postoperative period; and LVEDD (r = 0.35, p ≤ 0.05), LVM (r = 0.43, p = 0.007) and EOA (r = 0.496, p = 0.003) in the follow-up period. In the group of AS and IHD, correlations were found only with LV posterior wall thickness (r = 0.322, p = 0.022) in the follow-up period. Conclusions: Histological MF in AS was correlated with LVM and LVEDD in all study periods. No correlations between MF and LV parameters were found in aortic stenosis in the ischemic heart disease group across all study periods.
Biodegradable Microspheres for Transarterial Chemoembolization in Malignant Liver Disease
Authors: Moschovaki-Zeiger Ornella , Arkoudis Nikolaos-Achilleas , Giannakis Athanasios , Grigoriadis Stavros , Anagnostopoulos Fotis , Spiliopoulos Stavros
Published: April 2024

Transarterial chemoembolization (TACE) has revolutionized the treatment landscape for malignant liver disease, offering localized therapy with reduced systemic toxicity. This manuscript delves into the use of degradable microspheres (DMS) in TACE, exploring its potential advantages and clinical applications. DMS-TACE emerges as a promising strategy, offering temporary vessel occlusion and optimized drug delivery. The manuscript reviews the existing literature on DMS-TACE, emphasizing its tolerability, toxicity, and efficacy. Notably, DMS-TACE demonstrates versatility in patient selection, being suitable for both intermediate and advanced stages. The unique properties of DMS provide advantages over traditional embolic agents. The manuscript discusses the DMS-TACE procedure, adverse events, and tumor response rates in HCC, ICC, and metastases.
The Effect of Preprocedural Low-Dose Ketamine for Pain and Anxiety in Patients during Thoracic Epidural Catheterization
Authors: Küçük Onur , Sarı Esra , Zengin Musa , Ülger Gülay , Öztürk Yalçın Fatma , Baldemir Ramazan , Tunç Mehtap , Alagöz Ali
Published: April 2024

Background and Objectives: Thoracic epidural catheterization (TEC) can be both uncomfortable and fearful for patients when performed awake with the thought that the procedure may be painful. The aim of this study was to assess the effect of low-dose intravenous ketamine administration on pain and anxiety during the TEC procedure. Materials and Methods: Sixty patients were randomly divided into two groups to receive intravenous (IV) placebo (Group P) and IV low-dose (0.15 mg/kg) ketamine (LDK) (Group K) 3 min before the procedure in a double-blind manner. A visual analog scale (VAS) was used to measure anxiety (VAS-A) and pain (VAS-P) scores. Vital parameters were monitored before premedication (T1), 20 min after premedication (T2), during skin anesthesia (T3), during TEC (T4), and 5 min after TEC (T5). VAS-A values were recorded at T1, T3, T4, and T5 periods, and VAS-P levels were noted at T3, T4, and T5 periods. Results: During TEC (T4), both VAS-P and VAS-A were significantly lower in Group K (p < 0.001). The mean VAS-A value was 10.6 mm lower, and the mean VAS-P value was 9 mm lower in Group K than in Group P at the T4 time point. Additionally, the mean VAS-P value was 7.7 mm lower in Group K compared to Group P at the T3 time point (p < 0.001). Both groups showed a statistically significant difference in VAS-A measurements when compared at their respective time points (p < 0.001). However, only Group P demonstrated a statistically significant difference in VAS-P measurements (p < 0.001). VAS-P values remained stable in Group K. The number of patients who did not recall the procedure was significantly higher in Group K (p < 0.001). Furthermore, the number of patients who would consent to the same procedure in the future was significantly higher in Group K (p = 0.007). Conclusions: A preprocedural LDK (0.15 mg/kg) can effectively prevent anxiety and pain experienced by patients during the TEC procedure. Administration of LDK may provide a more comfortable procedure process without causing ketamine-induced side effects (hemodynamic, respiratory, and psychological).
TiAl Alloy Fabricated Using Election Beam Selective Melting: Process, Microstructure, and Tensile Performance
Authors: Zhang Yu , Li Yan , Song Meihui , Li Yanchun , Gong Shulin , Zhang Bin
Published: April 2024

TiAl alloy is one of the most attractive candidates for a new generation of high-temperature structural materials and has broad application prospects in the aerospace field. As a typical intermetallic material, TiAl is inevitably difficult to process using conventional methods. Election beam selective melting (EBSM) is an effective method of addictive manufacturing to prepare TiAl alloy with a complex structure. However, the microstructure of TiAl alloy formed using EBSM often contains defects such as pores, which seriously reduces the mechanical properties of the material. In this work, the effects of EBSM and post-processing procedures on the microstructure and mechanical properties of Ti-48Al-2Cr-2Nb alloy were studied. The results show that the microstructure of Ti-48Al-2Cr-2Nb alloy formed using the EBSM process was dense and composed of equiaxed γ-phase and double-phase regions. A large number of dislocations that formed due to thermal stress were clearly observed inside the Ti-48Al-2Cr-2Nb alloy. When the EBSM process parameters were 13.5 mA, 4.0 m/s, and 40.50 J/mm3, as the current intensity increased, the Al content decreased, the content of α2 phase increased, and the microstructure of the material was coarse. The results of the tensile test fracture morphology indicate that the Ti-48Al-2Cr-2Nb alloy exhibited brittle fracture during tensile deformation, lacking the typical yield deformation of metal materials. As the energy density of the EBSM process increased, the mechanical properties of the Ti-48Al-2Cr-2Nb alloy first increased and then decreased. The samples prepared with an energy density of 34.50~40.50 J/mm3 had excellent mechanical properties, of which the maximum tensile strength and maximum elongation reached 643 MPa and 2.09%, respectively. The phase composition of the Ti-48Al-2Cr-2Nb alloy after hot isostatic pressing (HIP) treatment remained unchanged from the EBSM samples, but there was a slight difference in content. There was an increase in the amount of γ phase and a decrease in B2 phase, accompanied by the generation of a massive γ phase after HIP treatment. Moreover, the number of dislocations inside the material increased. The Ti-48Al-2Cr-2Nb alloy after HIP treatment exhibited obvious plastic deformation characteristics, with a tensile strength of 679 MPa and elongation of 2.5%. A heat treatment of 900 °C/5 h was performed on the Ti-48Al-2Cr-2Nb alloy after HIP. The dislocation density of the Ti-48Al-2Cr-2Nb alloy decreased, and the B2 phase transformed from massive to lamellar.
Transcriptomic and Lipidomic Analysis Reveals Complex Regulation Mechanisms Underlying Rice Roots’ Response to Salt Stress
Authors: Xue Yingbin , Zhou Chenyu , Feng Naijie , Zheng Dianfeng , Shen Xuefeng , Rao Gangshun , Huang Yongxiang , Cai Wangxiao , Liu Ying , Zhang Rui
Published: April 2024

Rice (Oryza sativa L.), a crucial food crop that sustains over half the world’s population, is often hindered by salt stress during various growth stages, ultimately causing a decrease in yield. However, the specific mechanism of rice roots’ response to salt stress remains largely unknown. In this study, transcriptomics and lipidomics were used to analyze the changes in the lipid metabolism and gene expression profiles of rice roots in response to salt stress. The results showed that salt stress significantly inhibited rice roots’ growth and increased the roots’ MDA content. Furthermore, 1286 differentially expressed genes including 526 upregulated and 760 downregulated, were identified as responding to salt stress in rice roots. The lipidomic analysis revealed that the composition and unsaturation of membrane lipids were significantly altered. In total, 249 lipid molecules were differentially accumulated in rice roots as a response to salt stress. And most of the major phospholipids, such as phosphatidic acid (PA), phosphatidylcholine (PC), and phosphatidylserine (PS), as well as major sphingolipids including ceramide (Cer), phytoceramide (CerP), monohexose ceramide (Hex1Cer), and sphingosine (SPH), were significantly increased, while the triglyceride (TG) molecules decreased. These results suggested that rice roots mitigate salt stress by altering the fluidity and integrity of cell membranes. This study enhances our comprehension of salt stress, offering valuable insights into changes in the lipids and adaptive lipid remodeling in rice’s response to salt stress.
A Five-Hole Pressure Probe Based on Integrated MEMS Fiber-Optic Fabry-Perot Sensors
Authors: Song Yumiao , Ma Shuanghui , Zhao Jichun , Liu Jia , Wang Jingyi , Cui Yongjun
Published: April 2024

The five-hole pressure probe based on Micro-Electro-Mechanical Systems (MEMS) technology is designed to meet the needs of engine inlet pressure measurement. The probe, including a pressure-sensitive detection unit and a five-hole probe encapsulation structure, combines the advantages of a five-hole probe with fiber optic sensing. The pressure-sensitive detection unit utilizes silicon-glass anodic bonding to achieve the integrated and batch-producible manufacturing of five pressure-sensitive Fabry–Perot (FP) cavities. The probe structure and parameters of the sensitive unit were optimized based on fluid and mechanical simulations. The non-scanning correlation demodulation technology was applied to extract specific cavity lengths from multiple interference surfaces. The sealing platform was established to analyze the sealing performance of the five-hole probe and the pressure-sensitive detection unit. The testing platform was established to test the pressure response characteristics of the probe. Experimental results indicate that the probe has good sealing performance between different air passages, making it suitable for detecting pressure from multiple directions. The pressure responses are linear within the range of 0–250 kPa, with the average pressure sensitivity of the five sensors ranging from 11.061 to 11.546 nm/kPa. The maximum non-linear error is ≤1.083%.
Unveiling Antibacterial Potential and Physiological Characteristics of Thermophilic Bacteria Isolated from a Hot Spring in Iran
Authors: Rafiee Zeinab , Jalili Tabaii Maryam , Moradi Maryam , Harirchi Sharareh
Published: April 2024

The increasing worldwide demand for antimicrobial agents has significantly contributed to the alarming rise of antimicrobial resistance, posing a grave threat to human life. Consequently, there is a pressing need to explore uncharted environments, seeking out novel antimicrobial compounds that display exceptionally efficient capabilities. Hot springs harbor microorganisms possessing remarkable properties, rendering them an invaluable resource for uncovering groundbreaking antimicrobial compounds. In this study, thermophilic bacteria were isolated from Mahallat Hot Spring, Iran. Out of the 30 isolates examined, 3 strains exhibited the most significant antibacterial activities against Escherichia coli and Staphylococcus aureus. Furthermore, the supernatants of the isolated strains exhibited remarkable antibacterial activity, displaying notable resistance to temperatures as high as 75 °C for 30 min. It was determined that the two strains showed high similarity to the Bacillus genus, while strain Kh3 was classified as Saccharomonospora azurea. All three strains exhibited tolerance to NaCl. Bacillus strains demonstrated optimal growth at pH 5 and 40 °C, whereas S. azurea exhibited optimal growth at pH 9 and 45 °C. Accordingly, hot springs present promising natural reservoirs for the isolation of resilient strains possessing antibacterial properties, which can be utilized in disease treatment or within the food industry.