bluuebunny/crossref_metadata_2025 huggingface dataset:
A generalized integrable lattice hierarchy related to the Ablowitz–Ladik lattice: Conservation law, Darboux transformation and exact solution
Authors: Fan Fangcheng , Xie Weikang
Published: September 2023

Under investigation in this paper is a more general discrete [Formula: see text] matrix spectral problem. Starting from this spectral problem, the positive and negative integrable lattice hierarchies are constructed based on the Tu scheme, then by considering linear combination of the positive and negative lattice hierarchies, we give a more general integrable lattice hierarchy, which can reduce to the well-known Ablowitz–Ladik lattice and the discrete modified Korteweg–de Vries (mKdV) equation. In particular, we obtain some local and nonlocal integrable lattice equations, including reverse-space discrete mKdV equation, reverse-space complex discrete mKdV equation, higher-order discrete mKdV equation, higher-order complex discrete mKdV equation, higher-order reverse-space discrete mKdV equation and higher-order reverse-space complex discrete mKdV equation. In additional, infinitely many conservation laws and Darboux transformation (DT) for the first non-trivial system in the hierarchy are established with the help of its Lax pair. The exact solutions of the system are generated by applying the obtained DT. The results in this paper might be helpful for understanding some physical phenomena.
When amenable groups have real rank zero C∗-algebras
Authors: Moutzouris Iason
Published: September 2023

We investigate when discrete, amenable groups have [Formula: see text]-algebras of real rank zero. While it is known that this happens when the group is locally finite, the converse is an open problem. We show that if [Formula: see text] has real rank zero, then all normal subgroups of [Formula: see text] that are elementary amenable and have finite Hirsch length must be locally finite.
Impacts of coiling technique on hemodynamic of the MCA aneurysms: Computational study
Authors: Ding Jieping , Valipour Peiman
Published: September 2023

In this research, a computational approach is applied to model the blood flow inside the MCA aneurysm when the coiling technique is used for the treatment of the patients. To this end, porous condition with different permeability factors is applied and their impacts on the hemodynamic factors of wall shear stress, pressure and oscillatory shear index. The main attention is to find how endovascular technique could efficiently decrease the risk of bleeding in MCA aneurysms. Blood hemodynamic is simulated via solving transient Navier–Stokes equations with Casson model for the non-Newtonian condition for the blood stream. Besides, the impacts of the blood hematocrit are also examined on the hemodynamic characteristics. Attained results show that the effects of coiling permeability are significant on the reduction of the blood stress on the aneurysm.
Mass splittings and decay properties of B, Bs and Bc mesons in a Dirac formalism
Authors: Panda B. K. , Panda S. , Panda A. K.
Published: September 2023

In this paper, we investigate the mass spectra and decay properties of [Formula: see text], [Formula: see text] and [Formula: see text] mesons using the relativistic potential model with confining potential [Formula: see text]. The calculated mass spectra of [Formula: see text], [Formula: see text] and [Formula: see text] accord to the findings of the experiments and other theoretical forecasts. Using the same parameters, we calculate possible radiative decay widths of [Formula: see text] and [Formula: see text], [Formula: see text] and weak leptonic decay constants of [Formula: see text], [Formula: see text] and [Formula: see text] mesons. Our results, in most cases, generally agree with experimental and other theoretical predictions. Finally, we also investigate mixing parameters [Formula: see text], [Formula: see text] and [Formula: see text] for [Formula: see text] [Formula: see text] mesons, where our calculated values reasonably agree with the experiment.
Generalized half-dyon in SU(2) Yang–Mills–Higgs theory
Authors: Wong Guo-Quan , Wong Khai-Ming , Zhu Dan
Published: September 2023

In this paper, we report on generalized half-dyon solutions in SU(2) Yang–Mills–Higgs theory, namely Type I and Type II solutions. These solutions are constructed by considering [Formula: see text]-winding number [Formula: see text], electric charge parameter [Formula: see text] and Higgs self-coupling constant [Formula: see text]. They represent system of magnetic charge [Formula: see text] ([Formula: see text]) and electric charge [Formula: see text] that lies along the negative (positive) [Formula: see text]-axis. Fundamental properties, such as total energy, electric charge, dipole moment, are explored and discussed.
A New Nonlinear Ion Drift Model of Memristor Element and its Versatile Analog Reconfigurable Realizations
Authors: Randrianantenaina Jean Luck , Baran Ahmet Yasin , Korkmaz Nimet , Kılıç Recai
Published: September 2023

While using polynomial functions to define window functions is an initial approach in studying the memristor element, it is susceptible to generating imaginary results. However, using window functions, including the trigonometric function, is a current field of research on the memristor element. This paper uses the trigonometric Blackman window function to present a new memristor element model and investigates its nonlinear ion drift model properties. The motivation of this study is the usage of the trigonometric Blackman window function, which presents a more detailed definition and leads to more accurate results in windowing operations. The Blackman window function can address the issues of border locking and terminal state. Numerical simulations have verified this proposed structure. Additionally, the analog realizations of the memristor element constructed with the Blackman window function have been achieved on a Field Programmable Analog Array, which offers fast prototyping, serving as an alternative approach for emulating memristors.
Dual Cross-Attention Multi-Stage Embedding Network for Low-Light Image Enhancement
Authors: Fan Junyu , Li Jinjiang , Hua Zhen
Published: September 2023

The low-light image enhancement task aims to improve the visibility of information in the dark to obtain more data and utilize it, while also improving the visual quality of the image. In this paper, we propose a dual cross-attention multi-stage embedding network (DCMENet) for fast and accurate enhancement of low-light images into high-quality images with high visibility. The problem that enhanced images tend to have more noise in them, which affects the image quality, is improved by introducing an attention mechanism in the encoder–decoder structure. In addition, the encoder–decoder can focus most of its attention on the dark areas of the image and better attend to the detailed features in the image that are obscured by the dark areas. In particular, the poor performance of the Transformer when the dataset size is small is solved by fusing the CNN-Attention and Transformer in the encoder. Considering the purpose of the low-light image enhancement task, we raise the importance of recovering image detail information to the same level as reconstructing the lighting. For features such as texture details in images, cascade extraction using spatial attention and pixel attention can reduce the model complexity while the performance is also improved. Finally, the global features obtained by the encoder–decoder are fused into the shallow feature extraction structure to reconstruct the illumination while guiding the network for the focused extraction of information in the dark. The proposed DCMENet achieves the best results in both objective quality assessment and subjective evaluation, while for the computer vision tasks working in low-light environments as well, the enhanced images using the DCMENet proposed in this paper show the best performance.
Black holes, equilibrium and cosmology
Authors: Simovic Fil
Published: September 2023

We trace the origins and development of black hole thermodynamics across the past half-century, emphasizing the framework’s relation to classical thermodynamics, and the vital role played by the notions of equilibrium, stationarity and symmetry. We discuss different interpretations of the first law of black hole mechanics, and assess the validity of its mechanical, process-based interpretation for evaporating black holes. We bring these ideas to the cosmological realm, and highlight the various difficulties that arise when formulating thermodynamics for black holes in asymptotically de Sitter backgrounds. We discuss a number of proposed solutions and the open questions that arise therein.
α-FRACTAL FUNCTION WITH VARIABLE PARAMETERS: AN EXPLICIT REPRESENTATION
Authors: PRIYANKA T. M. C. , SERPA C. , GOWRISANKAR A.
Published: September 2023

In this paper, new results on the [Formula: see text]-fractal function with variable parameters are presented. The Weyl–Marchaud variable order fractional derivative of an [Formula: see text]-fractal function with variable parameters is examined by imposing certain conditions on the scaling factors. Following the investigation of fractional derivative, the definite integral of the [Formula: see text]-fractal function with variable parameters is evaluated for various intervals in the prescribed domain. Finally, an explicit structure for the [Formula: see text]-fractal function is provided using the base [Formula: see text] representation of numbers.
WITHDRAWAL SUCCESS ESTIMATION
Authors: BROWN HAYDEN
Published: September 2023

Given an asset having a geometric Lévy alpha-stable wealth process, a log-Lévy alpha-stable lower bound is constructed for the terminal wealth of a regular investing schedule. Using a transformation, the lower bound is applied to a schedule of withdrawals occurring after an initial investment. As a result, an upper bound is described on the probability to complete a given schedule of withdrawals. For withdrawals of a constant amount at equidistant times, necessary conditions are given on the initial investment and parameters of the wealth process such that k withdrawals can be made with 95% confidence. When withdrawing from an annually rebalanced portfolio maintaining 100p% in the S&P Composite Index and 100([Formula: see text])% in inflation protected bonds, the initial investment must be at least k times the amount of each withdrawal for [Formula: see text] and [Formula: see text].
A Physics-Data Hybrid Framework to Develop Bridge Digital Twin Model in Structural Health Monitoring
Authors: Qin Li-Feng , Ren Wei-Xin , Guo Chuan-Rui
Published: September 2023

Digital twin aims to create a virtual model for a physical structure by combining measurement data in structural health monitoring. The most important feature is to achieve the physical structure-monitoring data synchronization. For this purpose, a physics-data hybrid framework to develop the bridge digital twin model in structural health monitoring is proposed in the paper. The physical base is firstly formed by the finite element model of the digital representation for the physical bridge that can fully incorporate both structural geometry and structural state. The data base is then built by all measurement data of the monitored bridge. By defining the context that is common to both physical base and data base, the mirror relationship between physical base and data base for the specified context is formulated. To achieve the best matching of the mirror relationship by minimizing process, the digital twin model in terms of the specified context can be developed. In such a way, the proposed framework integrates physical knowledge and data intelligence into one model. A demonstration of a simulated simply supported beam is provided to show how the digital twin model is developed by using proposed physics-data hybrid framework. It is found that the generated digital twin model is consistent with the current structural state of the beam. The presented physics-data hybrid framework helps in clearer understanding of the realization of digital twin model in structural health monitoring, providing a new perspective for smart bridge solutions.
Modeling and Experimental Investigation of an Active Angular Vibration Absorber
Authors: Chen Zhuo , Wang Guangyuan , Li Jindong , Liu Feihu , Wu Yongsheng , Wang Dong
Published: September 2023

The active angular absorber for angular vibration control is proposed. Characteristics of the angular absorber are analyzed and an experiment is performed. The active angular absorber consists of a base and two identical voice coil actuators. The actuators have central symmetry and the coils are series connected to get the same current so that they output inertia forces with the same amplitude in opposite directions. There is a certain distance between the axes of the two actuators to produce a moment from the inertia forces, which can be employed to actively control the angular vibration. First, the mechanics of the angular absorber are presented. Then, the dynamic model of an angular vibration system with the absorber is demonstrated and the control law is proposed. Parameters of the absorber are discussed, showing that the absorber has the advantages of reliable structure and flexibility for installation. Next, numerical simulation is performed and the results show that the control method is effective and the simplification of the dynamic model is reasonable. Finally, a prototype of the absorber is produced and the angular vibration control experiment is conducted. Test results show that angular vibration with the amplitude of 1” level and at a frequency of 6 Hz can be attenuated by 93% to the level of the noise, while vibration at 0.1” level and 46 Hz can be attenuated by 80.7% to 0.01”. The control process is rapid and convergence is stable.
Electro-Mechanical Buckling of Shallow Segments of Functionally Graded Porous Toroidal Shell Covered by Piezoelectric Actuators
Authors: Jin Renyun , Qiu Haifeng , Weng Liguo , Yu Bin , Chen Jie , Zhang Yanghui
Published: September 2023

The current work deals with the mechanical buckling behavior of saturated porous toroidal shell segments sandwiched by piezoelectric actuator layers. Material properties of the porous shells with nonuniform distributed porosities are assumed to vary as a specific function of the thickness and porosity parameters. The nonlinear equations of the sandwich toroidal shell having either positive or negative Gaussian curvature are obtained on the basis of Biot’s poroelasticity theory. The energy method as the minimum potential energy principle is applied to derive the governing equations of the sandwich shells. The buckling equations of the piezo-porous sandwich shells under various types of mechanical loading are established by employing the adjacent equilibrium criterion. The governing equations as a set of the coupled partial differential equations are solved using an analytical method including the Airy stress function. Closed-form solutions are derived for shallow segments of the sandwich toroidal shell with positive/negative Gaussian curvature under lateral pressure, axial compression, and hydrostatic pressure loadings. Novel numerical results are presented in this work to show the effects of important factors such as the piezoelectric layer thickness, applied voltage, shell geometrical ratio, and variation of the porosity coefficient on the buckling behavior of these structures.
Dynamic Response Characteristics of Heliostat Impacted by Continuous Hails
Authors: Ji Baifeng , Xu Fan , Xiong Qian , Xu Shuaijun , Chen Changkun , Sun Jing
Published: September 2023

The Tibet Plateau is an area with abundant solar energy resources. However, it is also a location where severe thunderstorm disasters, for instance hail, frequently occur. In this paper, the dynamic response of the heliostat under impact by continuous hails was investigated. The effects of time interval of hail impact, hail diameter, impact position, as well as random multi-hail impact and random multi-hail distribution density were studied on the dynamic failure assessment of heliostat under continuous hail impacts. Results indicate that the continuous impact of hail on the same position of the heliostat causes a superposition effect on the heliostat. In case where larger-diameter hail initially impacts the heliostat, followed by smaller-diameter hail impact, the maximum principal stress in heliostat reaches its peak after the first hail impact and then steadily declines. When the heliostat is hit first by small-diameter hail followed by larger-diameter hail, it causes more damage to the heliostat compared to the case when the impact sequence is switched. The distance between continuous hail impacts reduces the increase of the maximum principal stress of the heliostat while increases the displacement value at the impact point of the heliostat. When the hail density increases by twice, the maximum principal stress increases significantly. The larger the hail distribution density, the smaller the stress concentration area, and then it gradually expands to both ends over time.
Automated Deep Learning Model with Optimization Mechanism for Segmenting Leukemia from Blood Smear Images
Authors: Rai Anjani Kumar , Ganeshan P. , Almoallim Hesham S. , Alharbi Sulaiman Ali , Raghavan S. S.
Published: September 2023

The advancement of digital microscopic scanning has made the study of image processing as well as categorization an exciting field of diagnostic studies. The literature describes a number of methods for detecting acute lymphocytic leukemia (ALL) using blood smear pictures. The goal of this research is to create an efficient approach for segmenting and detecting leukemia. This research has created a leukemia diagnosis module predicated on deep learning (DL) using blood smear pictures. Pre-processing, segmentation, extraction of features, and classification are performed here by the identification scheme. The presented hybrid model of African Buffalo and African Vulture Optimization (AB-AVO) performs the segmentation process, in which cytoplasm and nucleus regions are segmented. The Local Directional Pattern (LDP) and color histogram characteristics have been then retrieved from the segmented pictures and given into the presented Recurrent Neural Network (RNN) for categorization. The ALL-IDB1 and ALL-IDB2 databases’ blood smear pictures are taken into account for the investigation and assessed using metrics including F1-score, sensitivity, dice coefficient, precision, specificity, recall, and accuracy. The presented AB-AVO-RNN approach exhibits 100% accuracy, according to simulation data. Modern methodologies are used to compare the effectiveness of the suggested AB-AVO-RNN methodology. The investigation demonstrates that the suggested classifier performs comparably better and can identify leukemia from blood smear pictures.
PREDICTING CARDIAC HEALTH USING SUB-COMPONENT OF A PHONOCARDIOGRAM
Authors: ARORA SHRUTI , JAIN SUSHMA , CHANA INDERVEER
Published: September 2023

There has been a steady rise in the number of deaths throughout the world due to heart diseases. This can be mitigated, to a large extent, if cardiovascular disorders can be detected timely and efficiently. Electrocardiograms (ECGs) and phonocardiograms (PCGs) are the two most popular diagnostic tools used for detecting cardiac problems. Another simple and efficient method for quickly identifying cardiovascular illness is Auscultation. In this work, the cardiac sound signal has been transformed into its equivalent spectrogram representation for detecting cardiac problems. The novelty of the proposed approach is the deployment of customized transfer learning (TL) models on sub-component of a spectrogram called Harmonic Spectrogram, instead of taking full spectrogram. Experiments have been conducted using PhysioNet 2016, which is considered a benchmark dataset. TL models, viz. MobileNet, DenseNet121, InceptionResnetV2, VGG16, and InceptionV3 have been put to use for categorizing cardiac sound waves as normal or pathological. The results exhibit that the MobileNet has achieved greater accuracy (93.45%), recall (92.46%), Precision (97.82%), F1 Score (95.06%) than many of the peers.
A class of stochastic nonlocal evolution equations with nonlocal initial conditions
Authors: Liu Yarong , Wang Yejuan , Kloeden Peter E.
Published: September 2023

In this paper, we consider the existence and uniqueness of mild solutions for stochastic nonlocal evolution equations with Lévy diffusion operator and nonlocal initial conditions. Based on the continuity of the Lévy semigroup and the technique of the measure of noncompactness, we establish the local existence of mild solutions in [Formula: see text] under some weaker growth conditions. Moreover, we obtain the existence of mild solutions on any finite interval by using the general growth conditions on the nonlinear. Finally, the global existence and uniqueness of mild solutions follow from the additional Lipschitz conditions on nonlinear terms.
iAMY-RECMFF: Identifying amyloidgenic peptides by using residue pairwise energy content matrix and features fusion algorithm
Authors: Yu Zizheng , Yin Zhijian , Zou Hongliang
Published: September 2023

Various diseases, including Huntington’s disease, Alzheimer’s disease, and Parkinson’s disease, have been reported to be linked to amyloid. Therefore, it is crucial to distinguish amyloid from non-amyloid proteins or peptides. While experimental approaches are typically preferred, they are costly and time-consuming. In this study, we have developed a machine learning framework called iAMY-RECMFF to discriminate amyloidgenic from non-amyloidgenic peptides. In our model, we first encoded the peptide sequences using the residue pairwise energy content matrix. We then utilized Pearson’s correlation coefficient and distance correlation to extract useful information from this matrix. Additionally, we employed an improved similarity network fusion algorithm to integrate features from different perspectives. The Fisher approach was adopted to select the optimal feature subset. Finally, the selected features were inputted into a support vector machine for identifying amyloidgenic peptides. Experimental results demonstrate that our proposed method significantly improves the identification of amyloidgenic peptides compared to existing predictors. This suggests that our method may serve as a powerful tool in identifying amyloidgenic peptides. To facilitate academic use, the dataset and codes used in the current study are accessible at https://figshare.com/articles/online_resource/iAMY-RECMFF/22816916 .
Relativistic tolman stellar spheres in f(R,ϕ) theory of gravity
Authors: Malik Adnan , Shahzad M. Umair , Naz Tayyaba , Zulqarnain Rana Muhammad , Sultana Abeera
Published: September 2023

In this study, we investigate the literature on anisotropic stellar spheres in [Formula: see text] gravity utilizing Tolman–Kuchowicz (TK) spacetime. Due to the existence of anisotropic matter distribution, we derive the equations of motion for spherically symmetric spacetime by taking into account physically accurate formulations of the metric potentials. For this purpose, we develop the matching conditions by comparing them with the exterior solution to determine the TK constants. We have also discussed the graphical analysis of energy density, pressure components, equation of state components, equilibrium condition, and stability analysis. Moreover, other properties of a compact star, like the mass–radius function, compactness, and redshift function, have also been investigated. It is also noticed that energy conditions are satisfied, which justifies that our considered stars are viable. The validity of our proposed model has been proven by studying the development of various physical characteristics, and it is determined that our system is physically stable and free of any singularities.
Properties of Bipolar Fuzzy Automata
Authors: Kumar Bikky , Singh Anupam K. , Ram Anil Kumar
Published: September 2023

This work focuses on establishing the relationship between bipolar fuzzy automata, reverse bipolar fuzzy automata, and double bipolar fuzzy automata. It also introduces the concepts of bipolar fuzzy subsystems, reverse bipolar fuzzy subsystems, and double bipolar fuzzy subsystems, and explores various properties associated with these subsystems. Furthermore, the paper aims to introduce the categorical aspects of bipolar fuzzy automata and reverse bipolar fuzzy automata, along with their functorial relationship.
Investigating the Traits of Soft Semigraph-Associated Degrees
Authors: George Bobin , Jose Jinta , Thumbakara Rajesh K.
Published: September 2023

Soft set theory, introduced by D. Molodtsov, is a mathematical approach that tackles uncertain data. Semigraph is a generalization of the concept of a graph. By incorporating soft sets into semigraphs, a new concept called soft semigraphs has emerged. The study of soft semigraphs has gained significance in graph theory due to their valuable applications in parametrization. This paper explores the properties of various vertex degrees in soft semigraphs, including degrees, end degrees, edge degrees, adjacent degrees, and consecutive adjacent degrees.
A Fuzzy Approach to Sustainability I: A Time-Series Analysis of the Sustainable Development Goals
Authors: Doig Margaret I. , Malik D. S.
Published: September 2023

We use a [Formula: see text]-measure derived from fuzzy logic to evaluate progress toward the 2030 Agenda for Sustainable Development adopted by the United Nations Member States. In this first of a two-part series, we evaluate the 17 individual Sustainable Development Goals by applying the [Formula: see text]-measure to a set of indicators. We examine the distribution and characteristics of the scores for each Goal and note trends over time, highlight outlier countries, and evaluate progress in each Goal area. In the second part, we will consider worldwide progress toward the Goals as a whole.
Influence on the Energy Conservation and Green Environment R152A Refrigeration with Various Nanorefrigerants
Authors: Vandaarkuzhali S. , Balu P. , Jayabalakrishnan D. , Maniyarasan M.
Published: September 2023

Global Warming Potential (GWP) has proven to be just as critical in determining a possible coolant in recent years as Ozone Depletion Potential (ODP). By lowering the refrigerant charge and enhancing the coolant containment systems, R152A emissions are now aggressively reduced. The option to use the R152A device must be discussed due to concerns about its global warming potential. Disperse the specified quantities of nanoparticles in the compressor oil using a magnetic stirrer for two hours, and then ultrasonic dissolve for four hours to prepare the necessary volume fractions. The experiments showed a performance improvement using CuOs with 0.5% volume fractions with a base refrigerant such as R152A. Experimental results from three different nanoparticles, such as CuO, ZnO and Al2O3, indicate strong miscibility of the nano-CuO lubricant and an increase in lubricity oil to two nanoparticles.
Finite direct projective modules
Authors: Gupta Sonal , Gupta Ashok Ji
Published: September 2023

In this paper, we introduce the notion of finite direct projective modules, which is a generalization of direct projective modules; counter-example is given. We study the properties of finite direct projective modules with respect of their summands. We characterized von Neumann regular rings in terms of the endomorphism ring of finite direct projective modules. Also, we find connections among Rickart modules, [Formula: see text] modules, direct projective modules, finite direct projective modules and endoregular modules.
Graphs on groups in terms of the order of elements: A review
Authors: Madhumitha S. , Naduvath Sudev
Published: September 2023

Two mathematical fields that concentrate on creating and analyzing structures are algebra and graph theory. There are numerous studies linking algebraic structures like groups, rings, fields and vector spaces with graph theory. Several algebraic graphs have been defined based on the properties of the order of the group and its elements. In this paper, we systematically review the literature on such graphs to understand the research dynamics in the field.
Automated and Efficient Test-Generation for Grid-Based Multiagent Systems: Comparing Random Input Filtering versus Constraint Solving
Authors: Entekhabi Sina , Mostowski Wojciech , Mousavi Mohammad Reza
Published: September 2023

Automatic generation of random test inputs is an approach that can alleviate the challenges of manual test case design. However, random test cases may be ineffective in fault detection and increase testing cost, especially in systems where test execution is resource- and time-consuming. To remedy this, the domain knowledge of test engineers can be exploited to select potentially effective test cases. To this end, test selection constraints suggested by domain experts can be utilized either for filtering randomly generated test inputs or for direct generation of inputs using constraint solvers. In this article, we propose a domain specific language (DSL) for formalizing locality-based test selection constraints of autonomous agents and discuss the impact of test selection filters, specified in our DSL, on randomly generated test cases. We study and compare the performance of filtering and constraint solving approaches in generating selective test cases for different test scenario parameters and discuss the role of these parameters in test generation performance. Through our study, we provide criteria for suitability of the random data filtering approach versus the constraint solving one under the varying size and complexity of our testing problem. We formulate the corresponding research questions and answer them by designing and conducting experiments using QuickCheck for random test data generation with filtering and Z3 for constraint solving. Our observations and statistical analysis indicate that applying filters can significantly improve test efficiency of randomly generated test cases. Furthermore, we observe that test scenario parameters affect the performance of the filtering and constraint solving approaches differently. In particular, our results indicate that the two approaches have complementary strengths: random generation and filtering works best for large agent numbers and long paths, while its performance degrades in the larger grid sizes and more strict constraints. On the contrary, constraint solving has a robust performance for large grid sizes and strict constraints, while its performance degrades with more agents and long paths.
Negative Stances Detection from Multilingual Data Streams in Low-Resource Languages on Social Media Using BERT and CNN-Based Transfer Learning Model
Authors: Kumar Sanjay
Published: September 2023

Online social media allows users to connect with a large number of people across the globe and facilitate the exchange of information efficiently. These platforms cater to many of our day-to-day needs. However, at the same time, social media have been increasingly used to transmit negative stances such as derogatory language, hate speech, and cyberbullying. The task of identifying the negative stances from social media posts or comments or tweets is termed
negative stance detection
. One of the major challenges associated with negative stance detection is that most of the content published on social media is often in a multilingual format. This work aims to identify negative stances from multilingual data streams in low-resource languages on social media using a hybrid transfer learning and deep convolutional neural network approach. The proposed work starts by preprocessing the multilingual datasets by removing irrelevant information such as special characters and hyperlinks. The processed dataset is then passed through a pretrained BERT (bidirectional encoder representations from Transformers) model to generate embeddings by fine-tuning the model as per the dataset under consideration. The generated word embeddings are then passed to a deep convolutional neural network for extracting the latent features from the texts and removing the unessential information. This helps our model to achieve robustness and effectiveness for efficient learning on the given dataset and make appropriate predictions on zero-shot data. The article utilizes several optimization strategies for examining the impact of fine-tuning different BERT layers on the model’s performance. Intensive experiments on a variety of languages — namely, English, French, Italian, Danish, Arabic, Spanish, Indonesian, German, and Portuguese — are performed. The experimental results demonstrate the effectiveness and efficiency of the proposed framework.
Prevalence and Associated Factors of Adolescent Obesity among Rural School Adolescents in Nepal: A Cross-Sectional Study
Authors: Sitaula Deekshanta , Dhakal Aarati , Lageju Nimesh , Silwal Amisha , Basnet Samjhana Kshetri , Shrestha Niki , Anup Bikram B. C. , Phoju Niraj
Published: September 2023

Background. Overweight and obesity are major risk factors for chronic diseases and are the leading cause of mortality worldwide. Obesity during adolescence is strongly associated with adulthood obesity leading to increased morbidities and mortality. As a developing country undergoing rapid urbanization, Nepal is in a transitional phase where undernutrition coexists with obesity; however, there is a dearth of literature on the status of adolescent obesity in the rural section of Nepal. The aim of this study was to determine the prevalence of adolescent obesity in a rural district of Nepal and find out its associated factors. Methods. An institution-based cross-sectional study was conducted among the adolescent students studying in classes 8, 9, and 10 in four secondary schools of Gosaikunda rural municipality of Rasuwa district, Nepal. Total enumerative sampling was used, and Global School-based Health Survey (GSHS) standard questionnaires were used in collecting the information. Height and weight measurements were taken, and the body mass index was classified according to Asia-Pacific criteria. The collected data were analyzed using “SPSS” version 22. Logistic regression analysis was used to evaluate the associated factors, and a

p

value of ≤0.05 was considered statistically significant. Results. Out of 267 adolescents, 14.6% were obese and 14.6% were overweight. Of the female participants, 39.6% were either obese or overweight, while 12.6% of the male adolescents were overweight/obese. Among the total participants, 16.5% were underweight, including 14.0% females and 20.4% males. Female adolescents were about five times (AOR: 5.2, 95% CI (2.5–10.9),

p

 < 0.01) more likely of being overweight/obese than male adolescents. Conclusions. More than one-quarter of the adolescents were found to be obese/overweight, and the prevalence was significantly more among female adolescents. It emphasizes the necessity of school-based programs promoting a healthy lifestyle among students to maintain healthy weight status.
Production of Highly Uniform Midbrain Organoids from Human Pluripotent Stem Cells
Authors: Yao Xuerui , Kang Ji Hyun , Kim Kee-Pyo , Shin Hyogeun , Jin Zhe-Long , Guo Hao , Xu Yong-Nan , Li Ying-Hua , Hali Sai , Kwon Jeongwoo , La Hyeonwoo , Park Chanhyeok , Kim Yong-June , Wang Lin , Hong Kwonho , Cao Qilong , Cho Il-Joo , Kim Nam-Hyung , Han Dong Wook
Published: September 2023

Brain organoids have been considered as an advanced platform for in vitro disease modeling and drug screening, but numerous roadblocks exist, such as lack of large-scale production technology and lengthy protocols with multiple manipulation steps, impeding the industrial translation of brain organoid technology. Here, we describe the high-speed and large-scale production of midbrain organoids using a high-throughput screening-compatible platform within 30 days. Micro midbrain organoids (µMOs) exhibit a highly uniform morphology and gene expression pattern with minimal variability. Notably, µMOs show dramatically accelerated maturation, resulting in the generation of functional µMOs within only 30 days of differentiation. Furthermore, individual µMOs display highly consistent responsiveness to neurotoxin, suggesting their usefulness as an in vitro high-throughput drug toxicity screening platform. Collectively, our data indicate that µMO technology could represent an advanced and robust platform for in vitro disease modeling and drug screening for human neuronal diseases.
hsa_circ_0129047 Upregulates LYVE1 to Inhibit Hepatocellular Carcinoma Progression by Sponging miR-492
Authors: Feng Zhenzhen , Wu Jiyuan
Published: September 2023

Compelling evidence indicates the regulatory role of circular RNAs in cancers, including hepatocellular carcinoma (HCC). Our study aimed to elucidate the regulatory function of circ_0129047 in HCC progression. A reverse transcription-quantitative polymeric chain reaction was conducted to detect the expression of circ_0129047, lymphatic vessel endothelial hyaluronan receptor-1 (LYVE1), and miR-492 in HCC tissues and cells. The characteristics of circ_0129047 were determined by evaluating the nuclear and cytoplasmic fractions and by RNase R digestion assays. The cell counting kit-8 assay, scratch wound, and transwell invasion assays were used to examine the effects of circ_0129047 overexpression, miR-492 mimic, and LYVE1 overexpression on the proliferation, migration, and invasion abilities of HCC cells in vitro. A mouse xenograft model was also established. The relationship between miR-492 and circ_0129047 or LYVE1 was clarified using luciferase reporter and Argonaute-2 RNA immunoprecipitation assays. We found that circ_0129047 and LYVE1 were poorly expressed in HCC tissues and cells, whereas miR-492 was upregulated. Overexpression of circ_0129047 inhibits HCC cell proliferation, migration, and invasion and delays in vivo tumor growth. Furthermore, circ_0129047 sponged miR-492, and 3′UTR LYVE1 was a direct target of miR-492. Additionally, LYVE1 overexpression reduced the oncogenic activity of the miR-492 mimic, whereas the miR-492 mimic abolished the antimigratory, antiproliferative, and anti-invasive effects of circ_0129047 overexpression in HCC cells. These data suggest that circ_0129047 exerts a tumor-suppressive role in HCC by sponging miR-492 away from LYVE1 and that the circ_0129047/miR-492/LYVE1 axis may be a promising target for HCC treatment.
Evaluation of the Effect of Mental Health Education on Improving Adolescents’ Social Adaptability
Authors: Li Yuping
Published: September 2023

Adolescence is the preparatory stage for young people to enter the society. Although teenagers are good at catering to the development trend of society, they are limited by age, growth environment, and other factors, and their cognition of society is too simple, resulting in poor social adaptability. This paper adopts control method and questionnaire survey to study the effect of mental health education on improving social adaptability of teenagers. A total of 712 adolescents from two schools in Beijing were selected for the study (

M
=
15.76

,

SD
=
2.338

). In addition, the age, gender, family environment, and growth environment of the youth were taken as the independent variables. The results showed that the social adaptability of adolescents and its subdimensions were significantly affected by age, family environment, and growth environment (

p
<
0.05

), while gender had little effect on the overall social adaptability of adolescents (

p
>
0.05

). After receiving mental health education, adolescents’ social adaptability has significantly improved, with statistical differences in self-adjustment ability, interpersonal adaptability, behavioral adaptability, and environmental adaptability as well as in all dimensions (

p
<
0.01

), indicating that mental health education has obvious and comprehensive improvement effect on adolescents’ social adaptability. The social adaptability of adolescents is also affected by their own characteristics and growth background, which will further affect the effect of mental health education on the improvement of the social adaptability of adolescents. Based on these findings, this study provides significant insights for parents and teachers to improve the social adaptability of adolescents from the angle of mental health. Meanwhile, parents and teachers should specially pay attention to the influence of personality and growth background of adolescents which also play a decisive role on the effect of mental health education. This study provides practical and useful recommendations for improving adolescent social adaptability and adds to the theory for corresponding future research.
Brentuximab Vedotin–Driven Microtubule Disruption Results in Endoplasmic Reticulum Stress Leading to Immunogenic Cell Death and Antitumor Immunity
Authors: Heiser Ryan A. , Cao Anthony T. , Zeng Weiping , Ulrich Michelle , Younan Patrick , Anderson Martha E. , Trueblood Esther S. , Jonas Mechthild , Thurman Robert , Law Che-Leung , Gardai Shyra J.
Published: September 2023

Brentuximab vedotin, a CD30-directed antibody–drug conjugate (ADC), is approved for clinical use in multiple CD30-expressing lymphomas. The cytotoxic payload component of brentuximab vedotin is monomethyl auristatin E (MMAE), a highly potent microtubule-disrupting agent. Preclinical results provided here demonstrate that treatment of cancer cells with brentuximab vedotin or free MMAE leads to a catastrophic disruption of the microtubule network eliciting a robust endoplasmic reticulum (ER) stress response that culminates in the induction of the classic hallmarks of immunogenic cell death (ICD). In accordance with the induction of ICD, brentuximab vedotin–killed lymphoma cells drove innate immune cell activation in vitro and in vivo. In the “gold-standard” test of ICD, vaccination of mice with brentuximab vedotin or free MMAE-killed tumor cells protected animals from tumor rechallenge; in addition, T cells transferred from previously vaccinated animals slowed tumor growth in immunodeficient mice. Immunity acquired from killed tumor cell vaccination was further amplified by the addition of PD-1 blockade. In a humanized model of CD30+ B-cell tumors, treatment with brentuximab vedotin drove the expansion and recruitment of autologous Epstein-Barr virus–reactive CD8+ T cells potentiating the activity of anti–PD-1 therapy. Together, these data support the ability of brentuximab vedotin and MMAE to drive ICD in tumor cells resulting in the activation of antigen-presenting cells and augmented T-cell immunity. These data provide a strong rationale for the clinical combination of brentuximab vedotin and other MMAE-based ADCs with checkpoint inhibitors.
Associations of Sleep Patterns With Dynamic Trajectory of Cardiovascular Multimorbidity and Mortality: A Multistate Analysis of a Large Cohort
Authors: Zhang Jingyi , Chen Lan , Zhang Shiyu , Cai Miao , Zou Hongtao , Vaughn Michael G. , Tabet Maya , Qian Zhengmin (Min) , Lin Hualiang
Published: September 2023

Background

The purpose of this study was to explore the association of sleep patterns with the development of first cardiovascular diseases (FCVD), progression to cardiovascular multimorbidity (CVM), and subsequently to mortality.

Methods and Results

This prospective study included 381 179 participants without coronary heart disease, stroke, atrial fibrillation, or heart failure at baseline, and they were followed up until March 31, 2021. We generated sleep patterns by summing the scores for 5 sleep behaviors, whereby <7 or >8 hours/d of sleep, evening chronotype, frequent insomnia, snoring, and daytime dozing were defined as high‐risk groups. We used a multistate model to estimate the impacts of sleep patterns on the dynamic progression of cardiovascular diseases. Over a median follow‐up of 12.1 years, 41 910 participants developed FCVD, 7302 further developed CVM, and 20 707 died. We found that adverse sleep patterns were significantly associated with the transition from health to FCVD, from FCVD to CVM, and from health to death, with hazard ratio associated with 1‐factor increase in sleep scores being 1.08 (95% CI, 1.07–1.09), 1.04 (95% CI, 1.02–1.06), and 1.04 (95% CI, 1.02–1.05), respectively. When further dividing FCVD into coronary heart disease, stroke, atrial fibrillation, and heart failure, adverse sleep patterns showed a significant and persistent effect on the transition from health to each cardiovascular disease, and from heart failure or atrial fibrillation to CVM.

Conclusions

Our study provides evidence that adverse sleep patterns might increase the risk for the progression from health to cardiovascular diseases and further to CVM. Our findings suggest that improving sleep behaviors might be helpful for the primary and secondary prevention of cardiovascular diseases.
Assessment of the Effects of Sodium Nitroprusside Administered Via Intracranial Subdural Catheters on the Cerebral Blood Flow and Lactate Using Dynamic Susceptibility Contrast Magnetic Resonance Imaging and Proton Magnetic Resonance Spectroscopy in a Pig Cardiac Arrest Model
Authors: Lee Hyoung Youn , Jung Yong Hun , Mamadjonov Najmiddin , Jeung Kyung Woon , Lee Byung Kook , Kim Tae‐Hoon , Kim Hyung Joong , Gumucio Jorge Antonio , Salcido David D.
Published: September 2023

Background

Cerebral blood flow (CBF) is impaired in the early phase after return of spontaneous circulation. Sodium nitroprusside (SNP) administration via intracranial subdural catheters improves cerebral cortical microcirculation. We determined whether the SNP treatment improves CBF in the subcortical tissue and evaluated the effects of this treatment on cerebral lactate.

Methods and Results

Sixty minutes after return of spontaneous circulation following 14 minutes of untreated cardiac arrest, 14 minipigs randomly received 4 mg SNP or saline via intracranial subdural catheters. CBF was measured in regions of interest within the cerebrum and thalamus using dynamic susceptibility contrast‐magnetic resonance imaging. After return of spontaneous circulation, CBF was expressed as a percentage of the baseline value. In the saline group, the %CBF in the regions of interest within the cerebrum remained at approximately 50% until 3.5 hours after return of spontaneous circulation, whereas %CBF in the thalamic regions of interest recovered to approximately 73% at this time point. The percentages of the baseline values in the cortical gray matter and subcortical white matter were higher in the SNP group (group effect
P
=0.026 and 0.025, respectively) but not in the thalamus. The cerebral lactate/creatine ratio measured using magnetic resonance spectroscopy increased over time in the saline group but not in the SNP group (group–time interaction
P
=0.035). The thalamic lactate/creatine ratio was similar in the 2 groups.

Conclusions

SNP administered via intracranial subdural catheters improved CBF not only in the cortical gray matter but also in the subcortical white matter. The CBF improvement by SNP was accompanied by a decrease in cerebral lactate.
The Cyrenaics on the Premeditation of Future Evils
Authors: Chouinard Isabelle
Published: September 2023

In Book 3 of the Tusculans, Cicero reports that the Cyrenaics practised the premeditation of future evils. This article focuses on the philosophical consistency of this exercise with other Cyrenaic testimonies. It argues for the authenticity of Cicero’s report and provides a critical survey of previous attempts to reconstruct the theory underlying Cyrenaic premeditation, which addresses crucial questions about the management of future pleasures and pains, and the duration of affections. New evidence from Diogenes Laertius 2.94 is then used to support an alternative interpretation of the Cyrenaic praemeditatio malorum.