bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lightweight Salix Cheilophila Recognition Method Based on Improved YOLOv8n
Authors: Ma Haotian , Liu Zhigang , Pei Chenghui , Song Tianyou , Zhao Zhifei , Wang Shuhan 
Published: September 2024

Abstract

Stumping is an important measure for the care and management of salix cheilophila during its growth. Rapid and accurate detection of salix cheilophila in the stumping period in desert is the basis of intelligent stumping equipment. However, the complex model needs high computing power of hardware. It limits the deployment and application of salix cheilophila recognition in intelligent stumping equipment. Therefore, this study took salix cheilophila in the desert areas of Shierliancheng, Inner Mongolia Autonomous Region in the stumping period as the research object, and proposed an improved YOLOv8 rapid identification method, named YOLOV8-VCAD. First, the lightweight network VanillaNet was used to replace the backbone of YOLOv8 to lessen the computing load and complexity of the model. Coordinate attention mechanism was embedded to extract important features by setting in location information, which strengthened the regression and positioning abilities of the model. Second, introducing an adaptive feature fusion pyramid network significantly strengthens the model's ability to characterize and integrate the features, improving the accuracy and performance of target detection. Finally, the CIoU loss in YOLOv8 is replaced by DIoU loss to quicken the regression convergence of the model. The experimental results show the accuracy of this method is 95.4%, and the floating-point a second (Flops) and parameters are 7.4G and 5.46M, respectively. Compared to the traditional YOLOv8, the precision of the proposed algorithm is increased by 7.7%, the recall is increased by 1.0%, the computational complexity is reduced by 16.8%, and the parameters are reduced by 7.9%. The performance of YOLOV8-VCAD for the detection of salix cheilophila in the stumping period is obviously better than the traditional YOLOv8. The algorithm proposed in this paper can quickly and accurately detect the salix cheilophila in the stumping period. Besides, it can reduce the deployment cost and difficulty of the vision module of intelligent stumping equipment, and provide technical support for the automatic intelligence of salix cheilophila stumping equipment.
A second order non-uniform IMEX-Alikhanov-FEM for time-fractional PDEs and PIDEs with time-dependent coefficients
Authors: Tomar Aditi , Tripathi Lok Pati , Pani Amiya K. 
Published: September 2024

Abstract

The stability and error analysis of a non-uniform implicit-explicit Alikhanov finite element method (IMEX-Alikhanov-FEM) are investigated for a class of time-fractional linear partial differential/integro-differential equations. These equations involve a non-self-adjoint elliptic operator with variable coefficients in both space and time. A second-order error estimate in the L 2-norm is derived, up to a logarithmic factor, for the problem with initial data in H 1 0 (Ω) ∩ H 2 (Ω). Furthermore, in the case of a self-adjoint elliptic operator , a superconvergence result is obtained in the H 1-norm, leading to an error estimate in the L ∞-norm for two-dimensional problems. All the estimates are α-robust, i.e., constants do not blow up as α → 1 −. A set of numerical experiments is conducted to confirm our theoretical results.
AMS subject classifications. 65N35, 65N22
Comprehensive Machine Learning Approach for Heart Disease Diagnosis: Integrating HDTFS, Clustering and DNN
Authors: Romalt A. Ann , S.Kumar Mathusoothana 
Published: September 2024

Abstract

Heart disease ranks as a top cause of mortality globally, and the key to successful management lies in its timely diagnosis. Effective treatment depends on early detection. This research proposes a unique approach to detecting cardiac illness using machine learning (ML) methods, which have lately exhibited potential in this domain, combining deep neural networks (DNN) with probabilistic classification, often known as K-means clustering. The recommended strategy was evaluated using the UCI heart disease (HD) dataset. Prior to analysis, the data underwent pre-processing to manage missing values, encode categorical variables, scale them, and normalize them. An innovative technique called hybrid decision tree-based feature selection (HDTFS) is produced by merging decision trees with correlation feature selection. K-means partitioning was then used to categorize the data into groups depending on how similar they were to one another. A DNN was trained using the pre-processed data to predict the kind of heart illness. DNNs are trained using the adaptive moment optimizer (Adam optimizer), a well-known optimization method, to further refine the results. The research uncovered that the recommended strategy performed more precisely than other cutting-edge strategies. This suggests that combining HDTFS, K-means clustering, and DNN may improve the identification of heart illness and that the Adam optimizer can further improve the model's prediction capability.
A randomized, controlled study on the use of antifoaming and mucolytic agents in preparation for upper digestive endoscopy
Authors: Carvalho Amani Hamidah Carvalho , Couto Técio de Araújo , Carneiro Marcos de Vasconcellos , Trevizoli José Eduardo Trevizoli , de Faria Ricardo Jacaranda , de Meneses Juliana , Carvalho-Louro Daniela Mariano 
Published: September 2024

Abstract

Background
The randomized, controlled, double-blind study aimed to compare solutions containing antifoaming agent alone vs. antifoaming agent combined with mucolytic agent for improving endoscopic visibility to determine the most appropriate and effective solution for use in practical clinic.
Methods
A total of 178 adult individuals undergoing routine upper gastrointestinal endoscopy were divided into three groups to receive pre-endoscopic solutions: group A - Simethicone 100mg (Simet) + N-acetylcysteine 600mg (NAC) + water; group B - Simethicone 100mg + water; and group C (Control) - 100mL water. Mucosal visibility was assessed at four sites in the upper gastrointestinal tract (lower oesophagus, body, antrum and gastric fundus), and the sum of the scores was considered the total mucosal visibility score. The visibility scores were compared between the solutions. The total duration of the procedure, the volume of water required to obtain adequate vision and the mean time of administration of pre-endoscopic solutions were compared between groups. The likelihood of obtaining better visibility scores for each segment was evaluated in relation to the type of solution and the administrations times.
Results
The mean total visibility score of solution B was better than that of solution C. The mean antral score was better for solutions A and B than for solution C and the mean fundus score was better for solution B than for solution C. There was no significant difference between solutions A and B. Despite not demonstrating clear benefits, the combination of NAC with simethicone was superior to that of the placebo in the antrum. The duration of the exam and the volume of water required to improve visibility were similar between the solutions. There was a greater chance of obtaining better visibility scores when using solution B for 10-20 minutes in all segments.
Conclusion
The use of simethicone alone as a pre-endoscopic solution improved the visibility of the gastric mucosa, notably of the antrum and fundus when administered 10-20 minutes before the exam. The addition of NAC to the antifoaming agent did not improve mucosal visibility.
Trial registration: Research Ethics Committee of the Institute for Strategic Health Management of the Federal District (CAAE 31061420.6.0000.8153).
Association between Neutrophil-Percentage-to-Albumin Ratio and Kidney Stones: A Cross-Sectional Study Using NHANES Data
Authors: Guo Shihan , Jiao Xu , Lu Yun 
Published: September 2024

Abstract

Introduction: Our goal was to explore the potential association between the neutrophil-percentage-to-albumin-ratio (NPAR) and kidney stones.
Methods: This study utilized data from the National Health and Nutrition Examination Survey (NHANES), collected between 2007 and 2018. We employed multiple logistic regression models and smooth curve fitting to investigate the relationship between NPAR and other inflammatory biomarkers, including the systemic immune inflammation index (SII), platelet/lymphocyte ratio (PLR), and neutrophil/lymphocyte ratio (NLR), in relation to kidney stones. Independent relationships between these factors were assessed. Subgroup analysis revealed associations based on different population types. The study also evaluated the predictive ability of various inflammation markers in assessing the likelihood of developing kidney stones.
Results: A total of 17,258 subjects were recruited, with a prevalence of kidney stones at 8.9%. Through multiple logistic regression models and smooth curve fitting, we found that NPAR was associated with other inflammatory biomarkers (SII, PLR, NLR) and the presence of kidney stones. A nonlinear relationship with a saturation effect was observed, characterized by an L-shaped curve. The inflection points identified were 17.66, 1.06, 78.26, and 3.36. A positive correlation was noted on the left side of the inflection point, while a negative correlation was observed on the right side. In subgroup analysis, male participants and those with universal high school education exhibited a significantly increased incidence of kidney stones (P < 0.05). In ROC analysis, NPAR demonstrated the best discriminatory power and accuracy in predicting kidney stones compared to other inflammatory markers.
Discussion: NPAR may serve as a superior biomarker of inflammation relative to other inflammatory biomarkers (SII, PLR, NLR). U.S. adults with elevated levels of NPAR, SII, PLR, and NLR should be cognizant of potential risks to kidney health.
Physical and Chemical Characterization of Experimental Newly Formulated Resin Infiltrated Lithium Disilicate Ceramic Network versus Resin Infiltrated Feldspathic Ceramic Network(An in-vitro study)
Authors: Hussein Alaa , Aboushlieb Moustafa , Habib Nour 
Published: September 2024

Abstract

Background
polymer infiltrated ceramic network is hybrid dental ceramic that mimic the properties of tooth structures, unfortunately commercially available PICN still present limitations such as low strength thus, the current study was assigned to prepare resin infiltrated lithium disilicate ceramic network (PILN) and compare with commercially available PICN regarding microstructure and biaxial flexural strength.
Methodology:
a fine powder of lithium disilicate was produced by grounding IPSe.max CAD/CAM blocks, a porous lithium disilicate ceramic networks containing 25% (PILN-25) and 20% (PILN-20) porosity were produced by firing at 820OC and 830OC respectively. Resin was infiltrated and polymerized to form a dense PILN. A total of 69 specimens were prepared and assigned into three groups (n = 23) according to the type of ceramic used in fabrication of the ceramic network. The comparable group was Enamic, while the intervention groups were (PILN-25) and (PILN-20). For two intervention groups, porosity and density were measured before and after resin infiltration using helium pycnometer (n = 3 at each stage). SEM for microstructure analysis (n = 9) and One specimen was examined under FESEM for better visualization of the crystalline phases. Another three specimens (n = 3) in each group were assigned for XRD testing and lastly ten specimens for each group (n = 10) were subjected to biaxial flexural strength test. The statistical significance level was set at p ≤ 0.005.
Results
There was statistically significant difference in biaxial flexural strength, PILN-20 recorded the highest significant strength followed by PILN-25 and Enamic. PILN-25 showed higher porosity% than PILN-20 and the porosity decreased after resin infiltration. PILN-20 showed higher density than PILN-25 and density increased after resin infiltration. XRD revealed the presence of lithium disilicate crystals in both PILN-25 and PILN-20. SEM revealed highly interlocked ceramic and polymeric networks. FESEM revealed the presence of spherical lithium disilicate crystals.
Conclusion
PILN is a new type of hybrid ceramic material with enhanced mechanical properties.
Clinical implication:
PILN can be used as a promising CAD/CAM block to make high strength high esthetics dental restorations.
Mixed FEM implementation of three-point bending of the beam with an edge crack within strain gradient elasticity theory
Authors: Chirkov Aleksandr Yu. , Nazarenko Lidiia , Altenbach Holm 
Published: September 2024

Abstract

This paper considers the problem of symmetrical three-point bending of a prismatic beam with an edge crack. The solution is obtained by the mixed finite element method within the simplified Toupin-Mindlin strain gradient elasticity theory. A mixed variational formulation of the boundary value problem for displacements-deformations-stresses and their gradients is applied, simplifying the choice of approximating functions. Griffith's concept of energy balance is adopted to calculate the energy release rate with a virtual increase in crack length. The increment of the potential energy of an elastic body is determined accounting for the strain gradient contribution. Numerical calculations were performed using a quasi-uniform triangular mesh of the cross-type. The mesh refinement was applied in the vicinity of the crack tip, at the concentrated support, and at the point of application of the transverse force, and uniform mesh partitioning was utilized in the rest of the beam. The fine-mesh analysis was carried out on the successively condensed meshes in the stress concentration domain for different values of the length scale parameter. The crack opening displacements and the distribution of strains and stresses for various values of the length scale parameter are presented. An increase in this parameter increases the stiffness of the crack, which leads to a decrease in the crack opening displacements and a smooth closure of its faces at the crack tip. In addition, accounting for the scale parameter reduces the calculated values of strains and stresses near the crack tip. Based on the energy balance criterion, local fracture parameters such as the release rate of elastic energy and the stress intensity factor are determined for different values of the mesh step. The numerical calculations indicate the convergence of the obtained approximations. The main feature of solutions, which includes the strain gradient contribution, is the decrease in the values of the calculated parameters associated with the fracture energy compared to the classical elasticity theory.
Coexistence structural characteristics and phenotypic variation process of root and soil in a heterogeneous environment after plantation construction
Authors: Meng Chen , Zhu Zhihao , Wang Li , Qu Jianjun , Wang Lei , Song Naiping , Wang Xing , Yin Zhengcong 
Published: September 2024

Abstract

Aims
Little information is available on the physical interactions between the root system and soil structure in a heterogeneous environment. In this study, we aim to showed how to construct the coexistence structure of the root and soil in a heterogeneous field environment.
Methods
Computerized tomography (CT) scanning can be used to construct the structure of coexistence and various topological structure parameters of roots, pores, and aggregates in a controllable manner.
Results
A denser root-soil system network structure (such as the length, volume, surface area and diameter of root-macropore system, and the sphericity and girth of aggregates) formed in the surface soil as the plantation age increased. In particular, there was connectedness to find a stronger thick root, but there was a decrease in the number of clusters of fine roots. In a heterogeneous environment, the influence of macropore and aggregate on the root variable shows a weak positive relationship, in the inverse relationship, the root variable has a significant positive impact on the maropore and aggregate. In addition, the degree of aggregate has a significant positive effect on the porosity.
Conclusions
The introduction of shrubs led to the increase of coarse roots but the decrease of fine roots in desert steppe, indicating that the introduction of shrubs was not conducive to herb recovery.The root system has a direct positive influence on the soil pores, and also has an indirect positive influence on the soil pores by promoting the development of aggregates.
Identification of substituted acetanilide compounds as small molecule CBX2 inhibitors via in silico screening
Authors: Takase Shohei , Kumar Ashutosh , Maemoto Yuki , Yokoyama Sho , Arata Mayumi , Maruo Hiroki , Dohi Sayaka , Yun Young Sook , Inoue Hideshi , Hamamoto Makiko , Yoshida Minoru , Zhang Kam Y J , Ito Akihiro 
Published: September 2024

Abstract

The chromodomain protein CBX2 binds directly to histone H3 trimethylation at lysine 27 (H3K27me3) and is a component of polycomb repressive complex 1 (PRC1). CBX2 plays a pivotal role in transcriptional repression by acting as a reader protein that recognizes H3K27me3. In this study, we performed in silico screening based on the crystal structure of CBX2 to identify small molecule compounds that target the chromodomain of CBX2. The ability of the selected compounds to inhibit the interaction between CBX2 and histone H3 in cells was validated. After three rounds of in silico screening, CG3-46 was ultimately identified as the most potent CBX2 inhibitor in this study. CG3-46 inhibited the growth of the triple-negative breast cancer cell line MDA-MB-231 in a concentration range comparable to that used to inhibit the interaction between CBX2 and H3K27me3. Our results indicate that CG3-46 represents the first nonpeptide small molecule inhibitor of CBX2, which not only serves as a valuable chemical tool for elucidating the role of CBX2 in cellular epigenetic regulation but also as a starting compound for the development of CBX2-targeted therapeutics for triple-negative breast cancer.
Stock Market Prediction Based Multi-Attribute Decision Making Model Using Picture Fuzzy ˆZ-Information
Authors: Ashraf Shahzaib , Khalid Amna , Batool Bushra , Tlija Mehdi , Jana Chiranjibe , Pamucar Dragan 
Published: September 2024

Abstract

In the ever-evolving finance field, accurate market forecasts are necessary for traders and investors. Utilizing machine learning and data analysis, our focus is on developing an advanced model to predict stock prices with accuracy by analyzing historical trends. This research paper tackles pressing issues in Stock Market Prediction through the utilization of the multi-criteria group decision-making (MGCDM) approach. The approach offers a systematic means to assess and contrast various criteria and choices, enhancing decision-making accuracy. To further enhance this methodology, we integrate Zadeh’sˆZZadeh’sˆ Zadeh’sˆZ-numbers with constraints and reliability measures to address existing gaps in understanding their full capabilities. Our exploration focuses on utilizingˆZutilizingˆ utilizingˆZ-numbers, characterized by unpredictability and fuzziness, by merging them with picture fuzzy sets (PFSs) to capitalize on their potential benefits. To improve the capacity to handle completely unclear decisions and efficiently capture the fuzzy character, versatility, and application of decision-making data, we created picture fuzzyˆZfuzzyˆ fuzzyˆZ-numbers for pairwise comparisons of decision-makers possibilities. We created weighted averaging, ordered weighted averaging, hybrid averaging, weighted geometric, ordered weighted geometric , and hybrid geometric operators as well as operating rules and aggregation operators for picture fuzzy ˆ Z-number using algebraic T − N and T − CN .We utilize the average and geometric aggregation operators, comparing them with CoCo to Indicate the efficiency and functionality of our proposed technique. Through our investigation, particularly in decision-making contexts like Stock Market assessment, we underscore the significance of these operators and methodologies, particularly concerning Stock Market Prediction. We explore the relationship between uncertainty and randomness, enhancing our comprehension ofˆZofˆ ofˆZ-numbers and their capacity to handle uncertain data. Our research establishes a robust basis for better decision-making and uncertainty management across various fields by focusing on accuracy and precision.
Assessment of Local Pharmaceutical Manufacturing Sector in a Low-income Country: A Descriptive Study
Authors: Marew Tesfa , Belete Anteneh , Richmond Frances J. , Gebre-Mariam Tsige 
Published: September 2024

Abstract

Background
In high-income countries and emerging economies, pharmaceutical manufacturing is a driver for socioeconomic development. In sub-Saharan Africa, local pharmaceutical production is still fledgling largely because of historical economic and technological asymmetry. In Ethiopia alike, this environment has changed little despite six decades long operations and several support initiatives; access to essential medicines remained a persistent challenge. This study attempted to explore the views and experiences of professionals working in Ethiopian pharmaceutical industry regarding the context, performance, challenges and potential opportunities towards local production.
Methods
A validated structured survey questionnaire was disseminated to professionals working in local pharmaceutical companies. Multiple regression analysis was conducted to study the effects of different factors on the performance of the local manufacturing sector.
Results
About half of the professionals rated the current production technology as advanced while 68% described it as semi-automated. Close to one-third reported that the companies are operating at acceptable level of performance, and about 50% reported low-capacity utilization in their companies. Most professionals viewed export market activities as poor and many identified weak research and development activities. Unplanned operations downtimes, limited physical infrastructure, inadequate access to foreign currency, shortage and high staff turnover of qualified experts, lack of commitment from top management, absence of merit-based support system and limitations in compliance with regulatory and quality requirements were reported as major challenges. Multiple linear regression analysis demonstrated that capacity utilization (α = 0.008), research and development capacity (α = 0.014) and export market activities (α = 0.027) have significant impact on the sector performance.
Conclusion
Despite commendable efforts by the industry and government, limitations in financing, infrastructure, qualified workforce, and quality system implementation are affecting capacity utilization and performance. Absence of reliable staff attraction and retention system, lack of effective leadership and non-favourable working environment were identified as missing elements.
An Exact Solution for Equatorially Trapped Waves on the Modified Equatorial β-Plane
Authors: Liu Nan , Liu Hui , Yu Jing , Song Jian 
Published: September 2024

Abstract

We give a study of the exact solution of the nonlinear governing equations for geophysical water waves in the modified equatorial β-plane approximation in the vicinity of the equator. In the standard geophysical equatorial region, a correction is made to the modified equatorial β-plane model equations, a gravity correction term is added to the approximation of the equatorial tangent plane, and an exact solution to the corrected equations is derived. We can find analysis and consideration of nonlinear ocean wave propagation using a Lagrangian framework. In this sense, the exact solution obtained for the corrected equatorial captured wave is more convincing.