bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chatter Stability Analysis and Prediction for Elliptical Ultrasonic Vibration-assisted Milling Process
Authors: Li Zhongqun , Yang Shangzhen , Liu Qiang , Liu Hong , Liu Yang 
Published: August 2023

Abstract

Elliptical ultrasonic vibration-assisted milling (EUVAM) introduces ultrasonic frequency vibration into conventional milling (CM) to achieve high-frequency intermittent milling. It has broad application prospects in processing of difficult-to-cut materials such as titanium alloys, superalloys, carbon fiber reinforced plastic (CFRP), and hard and brittle materials. This study focuses on the development of a dynamic model for EUVAM that considers regenerative effects and analyzes the interaction between the cutting edge and the workpiece in both radial and tangential directions, and the dynamic chip thickness is derived based on this model. To solve the model, a Runge-Kuta based fully discrete method (RKFDM) is employed. This numerical method accurately predicts the stability of the EUVAM process under specified cutting conditions. In addition, a bisection algorithm is utilized to construct the stability lobe diagram of EUVAM, enhancing the computational efficiency of the process. Stability tests are conducted to validate the proposed stability model and solution method for EUVAM. The results of these tests confirm the accuracy and reliability of the approach presented in this paper. This study provides valuable insights and a practical framework for implementing EUVAM in the processing of difficult-to-cut materials, offering improved machining performance in various industrial applications.
Joint CFO and DOA Estimation Using Hybrid ESPRIT and root-MUSIC Scheme for Interleaved OFDMA/SDMA Uplink
Authors: Shen Chih-Chang , Jhang Wei 
Published: August 2023

Abstract

This paper deals with joint carrier frequency offset (CFO) and direction of arrival (DOA) estimation for an interleaved orthogonal frequency division multiple access (OFDMA)/space division multiple access (SDMA) uplink systems that equipped with small-scale arrays. This hybrid scheme, based on the decomposition of the two-dimensional parameter finding into double one-dimensional parameter finding, uses the ESPRIT method to estimate the CFO and the root-MUSIC for the DOA estimation. Specially, for each user, after the CFO estimation from the ESPRIT method, its DOA can be obtained simultaneously via polynomial rooting. Some simulation results are presented to verify the efficiency of this hybrid scheme.
Association of Single Nucleotide Polymorphism in OCT1 and OCT3 Genes with the Efficacy of Metformin Response in North Indian Type 2 Diabetes Mellitus Patients.
Authors: Rizvi Saliha , Raza Syed Tasleem , Mahdi Farzana 
Published: August 2023

Abstract
Purpose
Interindividual variation in efficacy of metformin among type 2 diabetes mellitus (T2DM) patients have been associated with several genetic variants. Understanding the genetic pathways involved in pharmacodynamics of metformin can affect personalized treatment of T2DM. Our study aimed to find the implication of genetic polymorphism in organic cation transporters (OCT1 and OCT3) genes on drug efficacy of metformin therapy in T2DM patients from North India.
Methods
This study evaluated the role of OCT1 (rs628031) and OCT3 (rs2292334) polymorphism in metformin response on T2DM patients. Response to metformin was defined by HbA1c levels based on which patients (n = 177) were divided into two groups: responders (HbA1C < 7% ; n = 127) and non-responders (HbA1C ≥ 7%; n = 50). The responders were further subcategorized as T2DM patients on monotherapy (n = 55) and on combination therapy (n = 72). Genotyping was done using PCR-RFLP approach.
Results
No significant association was found between OCT1 (rs628031) polymorphism and metformin response in T2DM patients. On the other hand, significant association of OCT3 (rs rs2292334) polymorphism was observed with metformin response where AA genotype carriers showed higher efficacy of metformin both in mono [OR (CI) = 0.29(0.11–0.72) and p = 0.007] and combination therapy [OR (CI) = 0.41(0.16-1.0) and p = 0.047]. Also, A allele was more prevalent in responders [OR (CI) = 0.48(0.28–0.84) and p = 0.010] while G allele was found to be associated with inefficacy of metformin in T2DM patients [OR (CI) = 2.07(1.19–3.61) and p = 0.010].
Conclusion
Genotyping of OCT3 (rs2292334) might be useful in predicting the response to metformin in T2DM patients.
Remediation of Aged Hexachlorobenzene Contaminated Soil by Nanoscale Zero-Valent Iron
Authors: Wang Qi 
Published: August 2023

Abstract
Currently, there are limited studies on the elimination of chlorinated organic compounds in aged soil. In this study, we utilized Nanoscale zero-valent iron (nZVI) to explore the removal of various chlorinated organic compounds presented in aged hexachlorobenzene (HCB)-contaminated soil. We also investigated the effects of initial pH values, as well as temperature, on the removal of HCB and other coexisting chlorobenzene congeners. Our results revealed that the highest removal efficiency for four chlorinated organic compounds was achieved under acidic conditions and elevated reaction temperatures. The maximum removal efficiency was higher than 80% for HCB and reached 90%, 60%, and 30% for pentachlorobenzene (PeCB), 1,2,4,5-tetrachlorobenzene (1,2,4,5-TeCB), and 1,2,4-trichlorobenzene (1,2,4-TCB), respectively. The removal of HCB by nZVI followed pseudo-first-order kinetics, which was different to other chemicals selected in this study. The reaction rate constant varied from 0.27 (initial pH value of 3) to 0.021 (initial pH value of 11). Furthermore, the reaction temperature was another affecting factor of the rate constant, which increased from 0.036 (15°C) to 0.192 (45°C). Notably, the presence of H+ did not significantly influence the rate-determining step of the chemical dehalogenation process for HCB and coexisting chlorobenzene congeners throughout the entire reaction. The removal of HCB and PeCB using nZVI in aged HCB-contaminated soil was characterized as an endothermic and diffusion-controlled process, with activation energies of 38.02 kJ/mol and 17.34 kJ/mol, respectively.
Analysis of pulse wave propagation characteristics in abdominal aortic sclerosis disease
Authors: Miao Fuxing , Sun Xuehang , Li Bensen , Lu Yicheng , Chen Xiabo 
Published: August 2023

Abstract
In this paper, a bidirectional fluid‒solid coupling finite element analysis model of the abdominal aorta was established with the use of vascular elastic modulus as the main indicator of atherosclerosis, in consideration of blood dynamic viscosity and compressibility, and pulse-wave propagation time-course calculations were carried out by the application of full-coupling analysis of the arbitrary Lagrangian‒Eulerian algorithm in COMSOL Multiphysics. The effect of atherosclerosis degree on the propagation characteristics of pulse waves in the bifurcated abdominal aorta was quantitatively analyzed. An increase in the modulus of elasticity of the arterial wall resulted in a considerable decrease in the peak pressure pulse wave, an increase in the pressure wave velocity, and a decrease in the axial wave velocity. Arterial bifurcation caused a substantial attenuation of the peak pressure pulse wave and an increase in wave velocity during the cardiac cycle. The modulus of elasticity and bifurcation properties of the arterial wall directly affected the peak value and wave velocity in the propagation of the pressure pulse wave. In addition, the stress concentration effect was evident at the bifurcation site, which was prone to the occurrence of lesions, such as arterial lumen stenosis, and the formation of arterial plaques. In conclusion, in atherosclerotic disease, the time course of pulse-wave propagation changes due to alterations in the geometry and material properties of the vessel wall. The preliminary results of this research will be crucial in guiding the evolution of the pressure pulse wave and the initial diagnosis of atherosclerotic disease through its waveform.
Comparative Survival Analysis Between Pathological N3B Nodal Disease and Other Node Positive Patients of Oral Squamous Cell Carcinoma and Their Management in Current Practice - Single Centre Experience.
Authors: ARORA VIKAS , YADAV VISHAL , Mandal Ghanashyam , Dewan Krati , Chakraborty Arnab , Sharma Prerit , Pasricha Sunil , Dewan Ajay Kumar 
Published: August 2023

Abstract
Background
Regional nodal metastasis with extra nodal extension (ENE) in patients of oral cavity squamous cell carcinoma (OCSCC) has a low survival in spite of aggressive multimodality therapeutic approach. Till now there is no level I data for decision making, and optimal treatment for N3b nodal disease. We aim at providing our institutional experience on survival analysis of N3b nodal disease in OCSCC, including its pattern on loco regional & distant recurrence.
Methods
Retrospective analysis of all diagnosed nodal positive 199 patients (from January 2019 to December 2020 ) of OCSCC was done. These patients underwent surgery followed by adjuvant therapy & were followed up for atleast 2 years.
Results
199 patients underwent surgery. 89 (44.7%) patients had pN3b disease & 110 patients (55.3%) had non-N3b disease (N1 to N3a). 2-year overall survival for pN3b & non N3b was 58.2% & 97.1% (P = 0.0023). Most common sites of distant metastasis were lung, bone, liver. 33 (37.1%) patients from N3b cohort and 20 (18.2%) patients from non N3b cohort had recurrence within 2 years. Interestingly, patients in N3b cohort, commonly had loco regional recurrence (primary site > neck node > satellite nodules).
Conclusions
OCSCC with N3b nodes is an aggressive subtype with poor prognosis in spite of R0 resection and adjuvant therapy. Maintenance with Metronomic / Immunotherapy at least for initial 2 years should be considered. There is a pressing need to identify N3b status on pre-operative radiology & consider neoadjuvant immunotherapy +/- CT.
Single-cell RNA sequencing reveals the cellular and molecular heterogeneity of treatment-naïve primary osteosarcoma in dogs
Authors: Ammons Dylan , Hopkins Leone , Cronise Kathryn , Kurihara Jade , Regan Daniel , Dow Steven 
Published: August 2023

Abstract

Osteosarcoma (OS) is a heterogeneous, aggressive malignancy of the bone that disproportionally affects children and adolescents. Therapeutic interventions for OS are limited, which is in part due to the complex tumor microenvironment (TME) that has proven to be refractory to immunotherapies. Thus, there is a need to better define the complexity of the OS TME. To address this need, we used single-cell RNA sequencing (scRNA-seq) to describe the cellular and molecular composition of the TME in 6 treatment-naïve dogs with spontaneously occurring primary OS. Through analysis of 35,310 cells, we identified 30 distinct immune cell types, 9 unique tumor populations, 1 cluster of fibroblasts, and 1 cluster of endothelial cells. Independent reclustering of major cell types revealed the presence of follicular helper T cells, mature regulatory dendritic cells (mregDCs), and 8 transcriptomically distinct macrophage/monocyte populations. Cell-cell interaction inference analysis predicted that mregDCs and tumor-associated macrophages (TAMs) play key roles in modulating T cell mediate immunity. Furthermore, we used publicly available human OS scRNA-seq data to complete a cross-species cell type gene signature homology analysis. The analysis revealed a high degree of cell type gene signature homology between species, suggesting the cellular composition of OS is largely conserved between humans and dogs. Our findings provide key new insights into the biology of canine OS and highlight the conserved features of OS across species. Generally, the data presented here acts as a cellular and molecular roadmap of canine OS which can be applied to advance the translational immuno-oncology research field.
Determination of space-time-dependent source terms in the integer-fractional MIM solute transport model based on dynamical system
Authors: Yu Chengyuan , Liu Wenyi , Li Gongsheng 
Published: August 2023

Abstract
We consider a numerical inversion problem of determining two space-time-dependent source terms in the integer-fractional MIM solute transport model by using the Dirichlet-Neumann boundary data. The unique existence of a solution to the forward problem is obtained by the inverse Laplace transform, and a dynamical system connecting the known data with the unknown sources is established by the variational method and boundary homogenization. The dynamical system is discretized to a linear system at given time in the homogenized polynomial space, and the source functions can be reconstructed by the alternative iteration and Tikhonov regularization. Two examples are presented to illustrate the validness of the inversion algorithm.
MSC(2010) 35R11; 35R30; 65N21
M2AST:MLP-Mixer-based Adaptive Spatial-Temporal Graph Learning for Human Motion Prediction
Authors: Tang Junyi , Liu Yuanwei , Su Yong , An Simin 
Published: August 2023

Abstract

Human motion prediction is a challenging task in human-centric computer vision that involves forecasting future poses based on historical sequences. Despite recent progress in modeling spatial-temporal relationships of motion sequences using complex structured graphs, few approaches have been able to provide an adaptive and compact representation for varying graph structures of human motion. Inspired by the advantages of MLP-Mixer, a lightweight architecture developed for learning complex interactions in multi-dimensional data, we explore its potential as a backbone for motion prediction. Human motion prediction is a challenging task in human-centric computer vision, involving forecasting future poses based on historical sequences. Despite recent progress in modeling spatial-temporal relationships of motion sequences using complex structured graphs, few approaches have provided an adaptive and lightweight representation for varying graph structures of human motion. Taking inspiration from the advantages of MLP-Mixer, a lightweight architecture designed for learning complex interactions in multi-dimensional data, we explore its potential as a backbone for motion prediction. To this end, we propose a novel MLP-Mixer-based adaptive spatial-temporal pattern learning framework (M\(^2\)AST). Our framework includes an adaptive spatial mixer to model the spatial relationships between joints, an adaptive temporal mixer to learn temporal smoothness, and a local dynamic mixer to capture fine-grained cross-dependencies between joints of adjacent poses. The final method achieves a compact representation of human motion dynamics by adaptively considering spatial-temporal dependencies from coarse to fine. Unlike the trivial spatial-temporal MLP-Mixer, our proposed approach can more effectively capture both local and global spatial-temporal relationships simultaneously. We extensively evaluated our proposed framework on three commonly used benchmarks (Human3.6M, AMASS, 3DPW MoCap), demonstrating comparable or better performance than existing state-of-the-art methods in both short and long-term predictions, despite having significantly fewer parameters. Overall, our proposed framework provides a novel and efficient solution for human motion prediction with adaptive graph learning.
The Relationship Between Temperatures, Electricity Consumption, and Business Cycles in Mexico
Authors: German-Soto Vicente , Favela Ruth A. Bordallo 
Published: August 2023

Abstract

This research uses the X-13 ARIMA methodology to investigate the co-movement, persistence, and volatility of business cycles, electricity consumption, and temperatures in Mexico during the period 2003.I–2019.IV. Theoretically, electricity consumption sustains a direct but non-linear relationship with economic development and temperatures because it is affected by seasonal factors. The greater the volume of economic activity, the greater the demand for electrical energy. Furthermore, extreme weather increases demand for electricity. During extreme weather seasons, electricity consumption is accentuated due to the greater fluctuation in the electricity supply. Our study finds that electricity consumption is procyclical––with regard to the business cycle––but maximum and minimum temperatures are countercyclical. Meanwhile, the link between minimum temperature and business cycle shows the greatest volatility, indicating that extreme cold represents a more significant risk factor than extreme heat. Furthermore, the duration of fluctuations is not significant, a result explained by the seasonality of the temperature. These findings enable the conclusion that temperatures have substantial effects on economic development and electricity supply. This leads to some policy recommendations that might address future electricity demand.
Application of nitrogen-doped reduced graphene oxide-persimmon tannin nanocomposites for electrochemical detection of Cd (II) in water resources
Authors: Zhang Shuai 
Published: August 2023

Abstract
A ultrasensitive electrochemical biosensor was successfully constructed for the detection of Cd (II) based on nitrogen-doped reduced graphene oxide-persimmon tannin (PT-N-RGO) and gold nanoparticles (Au NPs) modified screen printing electrode (SPE). The structure and morphology of the prepared PT-N-RGO nanocomposite were characterized by ultraviolet-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), and scanning electron microscopy (TEM). And each step in the sensor preparation was characterized by cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Au NPs as a material of modified electrode not only increased the effective surface area of the electrode, but also promoted the electron transfer during the redox reaction. The high specific surface area of PT-N-RGO composites further increased the electron transfer rate, thus improving the conductivity of the electrode and providing more binding sites for the subsequent capture of Cd (II). Under the optimized experimental conditions, the sensor exhibited good linearity in the range of 3.0~30 µg/L Cd (II) with a minimum detection limit of 0.46 µg/L. The sensor showed good selectivity, stability and reproducibility for the determination of Cd (II). The sensor was applied to the analysis of real water samples and the results were verified by inductively coupled plasma mass spectrometry (ICP-MS), and satisfactory results were obtained, providing a new idea for the effective determination of trace heavy metals in the environment.
Flight Traits of Dengue-Infected Aedes Aegypti Mosquitoes
Authors: Javed Nouman , López-Denman Adam J. , Paradkar Prasad N. , Bhatti Asim 
Published: August 2023

Abstract
Understanding the flight behaviour of dengue-infected mosquitoes can play a vital role in various contexts, including modelling disease risks and developing effective interventions against dengue. Studies on the locomotor activity of dengue-infected mosquitoes have often faced challenges in terms of methodology. Some studies used small tubes, which impacted the natural movement of the mosquitoes, while others that used cages did not capture the three-dimensional flights, despite mosquitoes naturally flying in three dimensions. Here we performed a comprehensive analysis of the three-dimensional flight behaviour of dengue-infected Aedes aegypti mosquitoes using Mask RCNN (Region-based Convolutional Neural Network). This analysis considered varying parameters such as flight duration, number of flights, Euclidean distance, flight speed, and the volume (space) covered during flights. Results revealed that dengue infection significantly increases the flight duration and volume (space) covered during flights whilst decreasing the total number of flights compared to uninfected mosquitoes. The study did not observe any evident impact on the Euclidean distance and speed of Aedes aegypti. These results highlight the intricate relationship between dengue infection and the flight behaviour of Aedes aegypti, providing valuable insights into the virus transmission dynamics.
Self-adaptive metaheuristic optimization technique for multi-objective reservoir operation
Authors: Kumar Vijendra , Sharma Kul Vaibhav , Yadav S. M , Deshmukh Arpan 
Published: August 2023

Abstract

Multi-objective reservoir operation presents a number of critical challenges that must be overcome for efficient management of water resources. The inherent contradiction between several goals, such as satisfying irrigation demand and maximizing hydropower generation, is one of the major issues. Trade-offs and compromises must be carefully considered to balance these objectives. To solve this problem, a study was carried out to optimize the operation of multi-objective reservoirs with two primary goals: minimizing irrigation deficits and maximizing hydropower generation. This study employs the self-adaptive multipopulation multi-objective Jaya algorithm (SAMP-MOJA), an improved version of the Jaya algorithm, to construct an optimal Pareto Front utilizing an a priori approach. The performance of SAMP-MOJA is compared to that of other algorithms such as multi-objective particle swarm optimization, multi-objective invasive weed optimization, and multi-objective Jaya algorithm. The results of this study demonstrate that the hydropower generated by the developed model surpasses 80% of the actual generation. The study's findings will aid in designing the most effective Pareto front possible.
Geospatial mitigation of the effect of undulating terrain on efficient water distribution network: a case study of Enugu Urban, South-Eastern Nigeria
Authors: Ugwuoti Amos Iloabuchi , Ojinnaka Oliver Chinagorom , Ibem Eziyi Ofia , Uzodinma Victus Ndubisi 
Published: August 2023

Abstract
Undulating terrain has continued to aggravate pipe-borne water supply challenges in the Enugu Urban area. The rapid increase in urbanization has worsened the situation. This, therefore, calls for the deployment of systems that can support the effective planning of surface and underground facilities for the development of an efficient water distribution network in this region. Remote Sensing, Geographic Information Systems (GIS), Hydrographic Survey, and Geophysical Survey, collectively referred to as geospatial technologies, have been combined in different ways by developed nations to resolve challenges facing surface and underground facilities. This study, therefore, demonstrates the application of this technology in designing an efficient water distribution network for urban areas with undulating terrain. The spot heights dataset extracted from Light Detection and Ranging (LiDAR) satellite imagery offered the bases for the re-structure of the existing water distribution network map to accommodate the undulation of the topography. This was integrated into a GIS tool to synergize the topography with the radial and dead-end standard water distribution patterns. The result was a sub-division of the Enugu Urban Area into 12 zones with reservoirs at the most elevated points to facilitate water reticulation by gravity. The efficacy of this distribution network map was confirmed suitable with EPANET software.