bluuebunny/crossref_metadata_2025 huggingface dataset:
UltraSEQ, a Universal Bioinformatic Platform for Information-Based Clinical Metagenomics and Beyond
Authors: Gemler Bryan T. , Mukherjee Chiranjit , Howland Carrie , Fullerton Patrick A. , Spurbeck Rachel R. , Catlin Lindsay A. , Smith Anthony , Minard-Smith Angela T. , Bartling Craig
Published: April 2023

Traditional clinical microbiology-based diagnostic tests rely on targeted methods that can detect only one to a few preselected organisms or slow, culture-based methods. Although widely used today, these methods have several limitations, resulting in rates of cases of an unknown etiology of infection of >50% for several disease types.
Oral Probiotic Expressing Human Ethanol Dehydrogenase Attenuates Damage Caused by Acute Alcohol Consumption in Mice
Authors: Jiang Xiaoxiao , Yan Chunlong , Zhang Hanlin , Chen Li , Jiang Rui , Zheng Kexin , Jin Wanzhu , Ma Huijuan , Liu Xiaomeng , Dong Meng
Published: April 2023

Alcohol plays an important role in medical treatment, culture, and social interaction. However, excessive alcohol consumption or improper alcohol intake patterns can lead to serious damage to health.
“Capillary” Structures in Transversely Trapped Nonlinear Optical Beams
Authors: Ruban V. P.
Published: April 2023

A mathematical analogy between paraxial optics with two circular polarizations of light in a defocusing Kerr medium with positive dispersion, binary Bose–Einstein condensates of cold atoms in the phase separation regime, and hydrodynamics of two immiscible compressible liquids can help in theoretical search for unknown three-dimensional coherent optical structures. In this work, transversely trapped (by a smooth profile of the refractive index) light beams are considered and new numerical examples are presented, including a “floating drop,” a precessing longitudinal optical vortex with an inhomogeneous profile of filling with the second component, and the combination of a drop and a vortex filament. Filled vortices that are perpendicular to the beam axis and propagate at large distances have also been simulated.
Novel intervention to promote COVID-19 protective behaviours among Black and South Asian communities in the UK: protocol for a mixed-methods pilot evaluation
Authors: Forbes Lindsay , Armes Jo , Shafi Shuja , Mohamed Amran , Mustafa Reham , Dar Osman , Vandrevala Tushna , Amlôt Richard , Hayward Andrew , Asaria Miqdad , Pirani Tasneem , Weston Dale , Shah Sunayana , Zumla Alimuddin , Ala Aftab
Published: April 2023

Introduction

Culturally appropriate interventions to promote COVID-19 health protective measures among Black and South Asian communities in the UK are needed. We aim to carry out a preliminary evaluation of an intervention to reduce risk of COVID-19 comprising a short film and electronic leaflet.

Methods and analysis

This mixed methods study comprises (1) a focus group to understand how people from the relevant communities interpret and understand the intervention’s messages, (2) a before-and-after questionnaire study examining the extent to which the intervention changes intentions and confidence to carry out COVID-19 protective behaviours and (3) a further qualitative study exploring the views of Black and South Asian people of the intervention and the experiences of health professionals offering the intervention. Participants will be recruited through general practices. Data collection will be carried out in the community.

Ethics and dissemination

The study received Health Research Authority approval in June 2021 (Research Ethics Committee Reference 21/LO/0452). All participants provided informed consent. As well as publishing the findings in peer-reviewed journals, we will disseminate the findings through the UK Health Security Agency, NHS England and the Office for Health Improvement and Disparities and ensure culturally appropriate messaging for participants and other members of the target groups.
Associations between neighbourhood social cohesion and subjective well-being in two different informal settlement types in Delhi, India: a quantitative cross-sectional study
Authors: Humble Steve , Sharma Aditya , Rangaraju Baladevan , Dixon Pauline , Pennington Mark
Published: April 2023

Objectives

To evaluate the relationships between neighbourhood cohesion and subjective well-being (SWB) in two different informal settlement types.

Design

Cross-sectional analysis of a community-based survey.

Setting

Communities in two districts, Sanjay Colony, Okhla Phase II and Bhalswa in Delhi, India.

Participants

328 residents in Bhalswa and 311 from Sanjay Colony.

Measurements

Neighbourhood social cohesion scale measured on an 18-point scale and the SWB scale made up of four subjective measures—hedonic, eudaemonic, evaluative and freedom of choice. Sociodemographic characteristics and trust were used as covariates.

Results

In both neighbourhood types there was a statistically significant positive bivariate correlation between neighbourhood cohesion and SWB (Sanjay: r=0.145, p<0.05; Bhalswa: r=0.264, p<0.01). Trust and neighbourhood cohesion were strongly correlated (Sanjay: r=0.618, p<0.01; Bhalswa: r=0.533, p<0.01) and the longer the resident had lived in the community the greater the feeling of neighbourhood cohesion (Sanjay: r=0.157, p<0.01; Bhalswa: r=0.171, p<0.05). Only in the resettlement colony (Bhalswa) was SWB negatively correlated with length of residency (r=−0.117, p<0.05). Residents who chose their settlement type (Sanjay residents) were 22.5 percentage points (pp) more likely to have a feeling of belonging to their neighbourhood than residents that had been resettled (Bhalswa) (Cohen’s d effect size 0.45). Sanjay residents had a greater likelihood to feel more satisfied with life (4.8 pp, p<0.01) and having greater perceived freedom of choice (4.8 pp, p<0.01).

Conclusions

Our findings contribute to the general knowledge about neighbourhood cohesion and SWB within different informal settlement types in a mega-city such as New Delhi, India. Interventions that promote sense of belonging, satisfaction with life and freedom of choice have the potential to significantly improve people’s well-being.
Protective effects of methylsulfonylmethane (MSM) on barrier function injury of porcine intestinal epithelial cells (IPEC-J2) induced by lipopolysaccharide (LPS)
Authors: Jiao Yang , Li Hengjiang , Ren Ting , Kim In Ho
Published: April 2023

Methylsulfonylmethane (MSM) is a natural organic sulfur component that has anti-inflammatory and antioxidant properties. In this study, injury of porcine intestinal epithelial cell (IPEC-J2) models were used to investigate the effect of MSM on lipopolysaccharide (LPS)-induced porcine intestinal epithelium barrier damage. The results of the cell cycle showed that the cells in the G2/M phase decreased significantly with the supplementation of 300 mmol/L MSM ( P < 0.05). The ELISA assay revealed that MSM could significantly inhibit the expression of tumor necrosis factor-alpha, interleukin-1, and interleukin-6 ( P < 0.01). Meanwhile, MSM could significantly increase the value of cell monolayer transepithelial electrical resistance while reducing the FITC-dextran flux permeability and lactate dehydrogenase activity in IPEC-J2 cells ( P < 0.01). Additionally, 300 mmol/L MSM significantly increased both mRNA and protein expression of occludin, claudin-1, and ZO-1 ( P < 0.05). Furthermore, MSM prevented the downregulation of epidermal growth factor receptor (EGFR) by LPS, indicating that MSM might enhance tight junction function through mechanisms of activation of EGFR-mediated protein synthesis in IPEC-J2 cells. Therefore, our findings suggested that MSM has protective effects on inflammation and epithelial barrier injury in LPS-induced IPEC-J2 cells, indicating that MSM might be used as a potential therapeutic agent in the pig industry.
Deep reinforcement learning for turbulent drag reduction in channel flows
Authors: Guastoni Luca , Rabault Jean , Schlatter Philipp , Azizpour Hossein , Vinuesa Ricardo
Published: April 2023

We introduce a reinforcement learning (RL) environment to design and benchmark control strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The environment provides a framework for computationally efficient, parallelized, high-fidelity fluid simulations, ready to interface with established RL agent programming interfaces. This allows for both testing existing deep reinforcement learning (DRL) algorithms against a challenging task, and advancing our knowledge of a complex, turbulent physical system that has been a major topic of research for over two centuries, and remains, even today, the subject of many unanswered questions. The control is applied in the form of blowing and suction at the wall, while the observable state is configurable, allowing to choose different variables such as velocity and pressure, in different locations of the domain. Given the complex nonlinear nature of turbulent flows, the control strategies proposed so far in the literature are physically grounded, but too simple. DRL, by contrast, enables leveraging the high-dimensional data that can be sampled from flow simulations to design advanced control strategies. In an effort to establish a benchmark for testing data-driven control strategies, we compare opposition control, a state-of-the-art turbulence-control strategy from the literature, and a commonly used DRL algorithm, deep deterministic policy gradient. Our results show that DRL leads to 43% and 30% drag reduction in a minimal and a larger channel (at a friction Reynolds number of 180), respectively, outperforming the classical opposition control by around 20 and 10 percentage points, respectively.
Mass spectroscopy and decay properties of Ξcb, Ξbb baryons
Authors: Kakadiya Amee , Menapara Chandni , Rai Ajay Kumar
Published: April 2023

Using the Hypercentral Constituent Quark Model (hCQM), the mass spectra of doubly heavy baryons [Formula: see text] and [Formula: see text] are determined. The model describes an interaction inside the baryonic system. Screened potential has been considered as confining potential with color-Coulomb potential to enumerate the masses of baryonic states. Regge trajectories have been plotted in [Formula: see text] plane. The properties like magnetic moment and radiative decay width have been determined using the obtained results.
Speculation-Free Function Table Construction in LLVM IR for Fine-Grained Control Flow Integrity
Authors: Zhao Sirong , Yu Xuejun , Luo Jianchun , Xie Guoqi
Published: April 2023

Securing the operating system kernel is the key to overall system security. Due to developer negligence and the inherent limitations of the code language, kernel data is exposed to various security risks, such as execution flow leakage and privilege hijacking. In binary security, most vulnerabilities are exploited by hijacking the control flow to make the program run according to the attacker’s idea of attack. Control flow integrity is a common defense scheme against control flow hijacking attacks. In this paper, we use speculation-free function tables in LLVM IR to achieve the integrity of fine-grained control flow. The technique enforces CFI policies by making logical judgments on jump instruction stubbing. All jump instructions share a common function table, and the information in the table is not repeatedly stored, reducing the additional memory consumption caused by the function table and achieving fine-grained CFI protection.
Applying Coding Behavior Features to Student Plagiarism Detection on Programming Assignments
Authors: Li Zheng , Zhang Yuting , Liu Yong , Wu Yonghao , Wu ShuMei
Published: April 2023

In programming education, the result of plagiarism detection is a crucial criterion for assessing whether or not students can pass course exams. Recently, the prevalent methods for detecting student plagiarism have been proposed by analyzing source code. These methods extract features (such as token, abstract syntax tree and control flow graph) from the source code, examine the similarity of codes using various similarity detection methods, and then perform plagiarism detection based on a predefined plagiarism threshold. However, these previous methods for plagiarism detection have some problems. First, they are less effective in detecting code modification related to structure. Second, they require a considerable number of training data, which demand high computing time and space. Third, they cannot determine whether students plagiarize in time. We propose a novel plagiarism detection method by analyzing the behavioral features of students during the coding process. Specifically, we extract five behavioral features based on students’ programming habits. Then, we use a feature ranking-based suspiciousness algorithm to obtain the possibility of student plagiarism. Based on our proposed method, we develop the Online Integrated Programming Platform. To evaluate the accuracy of our method, we conduct a series of experiments. Final experimental results indicate that our method achieves promising results with Accuracy, Precision, Recall and [Formula: see text] values of 0.95, 0.90, 0.95 and 0.92, respectively. Finally, we also analyze the correlation between whether students plagiarized and their regular and final grades, which can further verify the effectiveness of our proposed method.
VDIBA-Based Current-Mode PID Controller Design
Authors: Oruçoğlu Umut Cem , Özer Emre , Kaçar Firat
Published: April 2023

This paper aims to bring a voltage differencing inverting buffered amplifier (VDIBA)-based current-mode (CM) proportional integral derivative (PID) controller circuit. This CM PID controller is designed with a single VDIBA, three resistors, and two grounded capacitors. The proposed circuit is easy to design, and the control parameters can be tuned without changing the design configuration. A sensitivity analysis of the control parameters to electronic components has been conducted. The Simulation Program with Integrated Circuit Emphasis (SPICE) simulation has been performed using Taiwan Semiconductor Manufacturing Company (TSMC) [Formula: see text]m complementary metal-oxide semiconductor (CMOS) technology parameters. An application circuit example is given to demonstrate the reliability of the proposed PID design. A comparison table of the PID controllers previously reported in the literature is also presented.
Electromagnetic vacuum stresses and energy fluxes induced by a cosmic string in de Sitter spacetime
Authors: Saharian A. A. , Manukyan V. F. , Kotanjyan V. Kh. , Grigoryan A. A.
Published: April 2023

For the electromagnetic field in [Formula: see text]-dimensional locally de Sitter (dS) spacetime, we analyze the effects of a generalized cosmic string type defect on the vacuum expectation value of the energy-momentum tensor. For the Bunch–Davies vacuum state, the topological contributions are explicitly extracted in both the diagonal and off-diagonal components. The latter describes the presence of radially directed energy flux in the vacuum state. It vanishes for [Formula: see text] because of the conformal invariance of the electromagnetic field and is directed towards the cosmic string for [Formula: see text]. The topological contributions in the vacuum stresses are anisotropic and, unlike the geometry of a cosmic string in the Minkowski spacetime, for [Formula: see text] the stresses along the directions parallel to the string core differ from the energy density. Depending on the planar angle deficit and the distance from the cosmic string, the corresponding expectation values can be either positive or negative. Near the cosmic string the effect of the gravitational field on the diagonal components of the topological part is weak and the leading terms in the respective expansions coincide with the expectation values for a cosmic string in the background of Minkowski spacetime. The spacetime curvature essentially modifies the behavior of the topological terms at proper distances from the cosmic string larger than the dS curvature radius. In that region, the topological contributions in the diagonal components of the energy–momentum tensor decay in inverse proportion to the fourth power of the proper distance and the energy flux density behaves as inverse-fifth power for all values of the spatial dimension [Formula: see text]. The exception is the energy density in the special case [Formula: see text]. For a cosmic string in the Minkowski bulk the energy flux is absent and the diagonal components are proportional to the [Formula: see text]th power of the inverse distance.
FRACTAL ANALYSIS FOR THERMAL CONDUCTIVITY OF DUAL POROUS MEDIA EMBEDDED WITH ASYMMETRIC TREE-LIKE BIFURCATION NETWORKS
Authors: ZHANG YIDAN , XIAO BOQI , TU BILIANG , ZHANG GUOYING , WANG YANBIN , LONG GONGBO
Published: April 2023

Heat transport in tree-like bifurcation networks has been widely studied in various fields. In this work, we investigate heat conduction in the dual porous media embedded with asymmetric tree-like bifurcation networks. In addition, considering the effects of nonuniform tube shape, we assume that the bifurcated tube shows sinusoidal fluctuations. Based on the fractal distribution of pore size and bifurcation structure, we established a dimensionless effective thermal conductivity (ETC) model of the dual porous media. The dimensionless ETC ([Formula: see text] obtained is related to the porosity ([Formula: see text], the fluid–solid thermal conductivity ratio ([Formula: see text], the pore area fractal dimension [Formula: see text] and the structural parameters of the bifurcation network (bifurcation level [Formula: see text], length ratio [Formula: see text], radius ratio [Formula: see text], fluctuation amplitude factor [Formula: see text], bifurcation angle [Formula: see text]. To verify the validity of this model, a comparison of the present dimensionless ETC model with available experimental data was carried out and the results were in good agreement. We have discussed the effects of each parameter on the dimensionless thermal conductivity in detail and constructed parametric planes to evaluate the structural parameters more directly. The model has positive implications for revealing the heat transport mechanism in asymmetric tree-like bifurcation dual porous media.
A NEW FRACTAL MODIFIED BENJAMIN–BONA–MAHONY EQUATION: ITS GENERALIZED VARIATIONAL PRINCIPLE AND ABUNDANT EXACT SOLUTIONS
Authors: WANG KANG-JIA , SI JING , WANG GUO DONG , SHI FENG
Published: April 2023

In this paper, we derive a new fractal modified Benjamin–Bona–Mahony equation (MBBME) that can model the long wave in the fractal dispersive media of the optical illusion field based on He’s fractal derivative. First, we apply the semi-inverse method (SIM) to develop its fractal generalized variational principle with the aid of the fractal two-scale transforms. The obtained fractal generalized variational principle reveals the conservation laws via the energy form in the fractal space. Second, Wang’s Bäcklund transformation-based method, which combines the Bäcklund transformation and the symbolic computation with the ansatz function schemes, is used to study the abundant exact solutions. Some new solutions in the form of the rational function-type, double-exp function-type, Sin-Cos function-type and the Sinh-Cosh function-type are successfully constructed. The impact of the fractal orders on the behaviors of the different solutions is elaborated in detail via the 3D plots, 2D contours and 2D curves, where we can find that: (1) When the fractal order [Formula: see text], the direction of wave propagation tends to be more vertical to the [Formula: see text]-axis, on the other hand, it tends to be more parallel to the [Formula: see text]-axis when [Formula: see text]; (2) The fractal order cannot impact the peak amplitude of the waveform; (3) For the periodic waveform, the fractal orders can affect its period, that is, the period becomes smaller when the fractal order [Formula: see text]. The obtained results show that the proposed methods are effective and powerful, and can construct the abundant exact solutions, which are expected to give some new enlightenment to study the variational theory and traveling wave solutions of the fractal partial differential equations.
APPROXIMATION ORDERS OF A REAL NUMBER IN A FAMILY OF BETA-DYNAMICAL SYSTEMS
Authors: WANG XIAOQIONG , LI RAO
Published: April 2023

In this paper, we study the approximation orders of a real number [Formula: see text] by the partial sums of its [Formula: see text]-expansions as [Formula: see text] varies in the parameter space [Formula: see text]. More precisely, letting [Formula: see text] be the partial sum of the first [Formula: see text] items of the [Formula: see text]-expansion of [Formula: see text], we prove that for any real number [Formula: see text], the approximation order of [Formula: see text] by [Formula: see text] is [Formula: see text] for Lebesgue almost all [Formula: see text]. Moreover, we obtain the size of the set of [Formula: see text] for which [Formula: see text] can be approximated with a more general order [Formula: see text], where [Formula: see text] is a positive function. We also determine the Hausdorff dimension of the set [Formula: see text] where [Formula: see text] is the number of the longest consecutive zeros just after the [Formula: see text]th digit in the [Formula: see text]-expansion of [Formula: see text].
INVESTIGATION OF FINANCIAL BUBBLE MATHEMATICAL MODEL UNDER FRACTAL-FRACTIONAL CAPUTO DERIVATIVE
Authors: LI BO , ZHANG TONGXIN , ZHANG CHAO
Published: April 2023

In this study, we proposed a novel approach for modeling the dynamics of a three-agent financial bubble using the fractal-fractional (FF) derivative of the Caputo sense. This new concept was developed to deal with the complex geometry of any dynamical system, and it utilizes both the fractional derivative for the order and the fractal term for the order of the independent variables. The model was investigated using the conformable order derivative of the Caputo operator, with a focus on the fractal dimension and fractional order. The existence and uniqueness of the solution were tested using a FF global derivative, and the approximate root of the system was calculated using the numerically iterative technique of the Newton polynomial. To verify the accuracy of the approximate root scheme, we applied the power singular law with two fractional parameters in the developed numerical technique. The curve representation of the system was also verified by applying the data for the fractals and different conformable orders. Additionally, we tested the sensitivities of the fractional parameters and dynamical system parameters by varying the parameter values. This allowed us to gain a better understanding of how changes in these parameters affect the system’s behavior and stability. As a result, this study presents an innovative and effective approach for modeling the dynamics of financial bubbles using the FF derivative of the Caputo sense. The results of this research contribute to the ongoing efforts to develop more accurate and comprehensive models of complex systems in economics and finance.
THE THICKNESS AND QUASISYMMETRICAL EQUIVALENCE OF THE SETS DEFINED BY DIGIT RESTRICTIONS
Authors: DAI YUXIA , QIN HAOTIAN , WANG SHANGYU , WEI CHUN
Published: April 2023

In this paper, we discuss the thickness and quasisymmetric equivalence of a class of fractal sets based on the binary expansion of numbers. We give the sufficient and necessary conditions for the thickness of this kind of sets to be positive, and the necessary and sufficient condition for their quasisymmetric equivalence with the standard Cantor ternary set. This paper also studies the relationship between the thickness and the uniform completeness about the product sets of two sets defined by digit restrictions.
Logical metatheorems for accretive and (generalized) monotone set-valued operators
Authors: Pischke Nicholas
Published: April 2023

Accretive and monotone operator theory are central branches of nonlinear functional analysis and constitute the abstract study of certain set-valued mappings between function spaces. This paper deals with the computational properties of these accretive and (generalized) monotone set-valued operators. In particular, we develop (and extend) for this field the theoretical framework of proof mining, a program in mathematical logic that seeks to extract computational information from prima facie “non-computational” proofs from the mainstream literature. To this end, we establish logical metatheorems that guarantee and quantify the computational content of theorems pertaining to accretive and (generalized) monotone set-valued operators. On the one hand, our results unify a number of recent case studies, while they also provide characterizations of central analytical notions in terms of proof theoretic ones on the other, which provides a crucial perspective on needed quantitative assumptions in future applications of proof mining to these branches.
DETECTION OF PRETERM BIRTH FROM THE NONCONTRACTION SEGMENTS OF UTERINE EMG USING HJORTH PARAMETERS AND SUPPORT VECTOR MACHINE
Authors: SELVARAJU VINOTHINI , KARTHICK P. A. , SWAMINATHAN RAMAKRISHNAN
Published: April 2023

Uterine electromyography (uEMG) measures the electrical activity of the uterus noninvasively and is a promising technique for detecting preterm birth. Nevertheless, uterine contractions are irregular during pregnancy and may not present during standard 30-min recording. Hence, this study analyzes the noncontraction of uEMG signals for predicting premature birth. Three channels of 53 and 47 noncontraction segments under the term and preterm conditions, respectively, are obtained from the publicly available database. The signals are preprocessed, and the contractions and noncontraction segments are extracted manually based on the annotations. The Hjorth features, namely activity, mobility, and complexity, are extracted from the signals. Classification algorithms, namely support vector machine, random forest, and adaptive boosting classifier, are designed to distinguish between term and preterm conditions. The results show that mobility decreases, and complexity increases in preterm conditions. The support vector machine based on the proposed features of a single channel yields a maximum accuracy of 84.3% and F1-score of 82.8% in differentiating term and preterm conditions. In order to improve the performance further, we adapted a decision fusion approach that combines predictions from multiple channels. The improved model enhances the accuracy and F1-score by about 3%. Therefore, it appears that the proposed approach using noncontraction segments could be used as a biomarker for the reliable prediction of premature birth.
DEVELOPMENT OF MR-BASED PROCEDURES FOR THE IMPLEMENTATION OF PATIENT-SPECIFIC DIELECTRIC MODELS FOR CLINICAL USE
Authors: LIPORACE FLAVIA , CAVAGNARO MARTA
Published: April 2023

Nowadays, many medical techniques are based on the application of electromagnetic fields (EMF) on human body. For the optimization of these techniques, it is necessary to understand the mechanisms of interaction between the biological system under exposure and the applied EMF. Since this interaction is described by the dielectric properties of the biological system, an accurate dielectric characterization of human body is necessary. Biological tissues are complex and heterogeneous, and their dielectric properties can vary significantly from the ex-vivo to the in vivo condition. For this reason, there is the need to measure these properties for a specific subject. Unfortunately, traditional techniques used to measure dielectric properties of tissues are not able to reach this aim and an alternative method must be devised. In this work, a model is proposed for the reconstruction of dielectric properties of biological tissues from MR acquisitions. This model is wideband, specific, applicable in vivo and useful for those medical techniques that need a precise dielectric characterization of the patients.
A COMPARATIVE ANALYSIS OF EDA DECOMPOSITION METHODS FOR IMPROVED EMOTION RECOGNITION
Authors: KUMAR P. SRIRAM , GOVARTHAN PRAVEEN KUMAR , GANAPATHY NAGARAJAN , RONICKOM JAC FREDO AGASTINOSE
Published: April 2023

This study analyzed five decomposition algorithms for separating electrodermal activity (EDA) into tonic and phasic components to identify different emotions using machine learning algorithms. We used EDA signals from the Continuously Annotated Signals of Emotion dataset for this analysis. First, we decomposed the EDA signals into tonic and phasic components using five decomposition methods: continuous deconvolution analysis, discrete deconvolution analysis, convex optimization-based EDA, nonnegative sparse deconvolution (SparsEDA), and BayesianEDA. We extracted time, frequency, and time-frequency domain features from each decomposition method’s tonic and phasic components. Finally, various machine learning algorithms such as logistic regression (LR), support vector machine, random forest, extreme gradient boosting, and multilayer perceptron were applied to evaluate the performance of the decomposition methods. Our results show that the considered decomposition methods successfully split the EDA signal into tonic and phasic components. The SparsEDA decomposition method outperforms the other decomposition methods considered in the study. In addition, LR with features extracted from the tonic component of the SparsEDA achieved highest average classification accuracy of 95.83%. This study can be used to identify the optimal decomposition methods suitable for emotion recognition applications.
ELECTRODERMAL ACTIVITY-BASED ANALYSIS OF EMOTION RECOGNITION USING TEMPORAL-MORPHOLOGICAL FEATURES AND MACHINE LEARNING ALGORITHMS
Authors: SRIRAM KUMAR P. , GOVARTHAN PRAVEEN KUMAR , GANAPATHY NAGARAJAN , RONICKOM JAC FREDO AGASTINOSE
Published: April 2023

In this study, we evaluated the performance of tonic and phasic components of Electrodermal activity (EDA) using machine learning algorithms for accurately recognizing emotions. The EDA signals considered for this study were obtained from Continuously Annotated Signals of Emotion (CASE) dataset. Initially, we pre-processed and decomposed the EDA into tonic and phasic components using cvxEDA method. Further, we extracted the temporal and morphological features from both tonic and phasic. Finally, we tested the performance of various combinations of features using machine learning algorithms such as logistic regression, support vector machine (SVM), and random forest. Our results revealed that the tonic contributes significant information for emotional state classification. Further, the temporal features of the phasic were able to discriminate most of the emotions [Formula: see text]. In particular, the scary emotion was well discriminated against other emotions. Results of classification revealed that SVM performed best in classifying emotional states. The results of our process pipeline, which incorporated tonic, temporal features, and SVM, showed impressive classification performance with average accuracy, sensitivity, specificity, precision, and f1-score of 78.96%, 57.92%, 85.97%, 62.32%, and 56.48%, respectively. Our findings indicate that our proposed models could potentially be used to detect the positive and negative emotions in healthcare settings.
Strategies to Selecting Most Profitable Products by Price Settings
Authors: Tai Liang Kuang , Chen Arbee L. P.
Published: April 2023

For a company, it is important to know which products to launch to the market that may get the maximal profit. To achieve this goal, companies not only need to consider these products’ features, but also need to analyze how customers make their purchase decisions. For most customers, the price of a product is the most important purchase factor. If the price of a product can be adjusted, the purchase decision of a customer may change. With different price settings, we can speculate on the expected number of customers and the profit of the products. Motivated by this, we want to find the most profitable products among the candidates for the company. A distance-based adoption model can be used to evaluate the expected customers for products at different prices. The computational cost is high in two parts. One is the computational cost of obtaining the most profitable information on each set of candidate products. Another part is that many candidate product combinations need to be calculated. To tackle the computation problem, we propose two strategies. One is to avoid considering all possible price settings. The other is to avoid processing all possible subsets of the candidate products. Experimental results reveal the efficiency of our strategies.
An Improved Cell-Based Smoothed Discrete Shear Gap Method (CS-DSG3) for Static and Dynamic Analyses of Reissner–Mindlin Plates
Authors: Ma Houbiao , Zeng Yaoxiang , Zhang Yahui
Published: April 2023

The efficiency and accuracy of the cell-based smoothed discrete shear gap (CS-DSG3) are improved in simplifying the application process of the cell-based strain smoothing technique and redefining the stabilized parameter of Stenberg’s stabilization method, respectively. In the original CS-DSG3, both the smoothed bending strain and the smoothed shear strain are derived by the cell-based strain smoothing technique. This study proves that the smoothed bending strain matrix in the original CS-DSG3 is equal to the unsmoothed bending strain matrix. Theoretically, abandoning the bending strain smoothing operation can improve the efficiency while maintaining the accuracy of the original CS-DSG3. The introduction of Stenberg’s stabilization method can boost the accuracy of shear strain in the original CS-DSG3, whereas the relationships of the stabilized parameter in Stenberg’s stabilization method with the mesh density, the thickness–span ratio, and the boundary condition are still unclear. In this study, the range of the optimal stabilized parameter for different analyses and boundary conditions is determined through the static and dynamic analysis of the plate. The new stabilized parameter is applied to static analyses, free vibration analyses, and frequency response analyses for verification and comparison, which demonstrates that it can significantly improve the accuracy of the CS-DSG3.
The Role of Social Infrastructure in ICT Adoption Program: A Perspective from the Indonesian Regional Innovation System
Authors: Maninggar Nimas , Kusharsanto Zulfika Satria , Maulidya Dea , Fitriana Nur
Published: April 2023

Information and communication technology (ICT) adoption is nowadays regarded as an important program due to the fourth industrial revolution across the globe. In this study, we aimed to fill the literature gap by scrutinizing the role of social infrastructure in ICT adoption programs, which is still not much discussed. A perspective of regional innovation systems (RIS) was used because RIS key components resemble the concept of social infrastructure. We measured the implementation of the ICT adoption program in 19 cities in Indonesia by clustering them into two groups (strong and emerging innovators). To determine which social infrastructure indicators are most important in explaining the grouping, especially the strong one as the best practice, we additionally measured the F-test and t-test. The clustering results showed that cities in strong innovator clusters have homogeneously high performance in terms of the number of collaborations, local communities, and products that meet international standards. We suggest that such three indicators be taken into consideration in policymaking at the regional and national levels to improve the performance of the ICT adoption program.
Pseudo-symmetric almost cosymplectic 3-manifolds
Authors: Inoguchi Jun-ichi , Lee Ji-Eun
Published: April 2023

In this paper, we study the semi-symmetry and pseudo-symmetry of almost cosymplectic [Formula: see text]-manifolds. First, we prove that an [Formula: see text]-almost cosymplectic [Formula: see text]-manifold [Formula: see text] is semi-symmetric if and only if it is cosymplectic. Here by an [Formula: see text]-almost cosymplectic [Formula: see text]-manifold, we mean an almost cosymplectic [Formula: see text]-manifold whose characteristic vector field [Formula: see text] is a harmonic unit vector field. If an almost cosymplectic [Formula: see text]-manifold [Formula: see text] whose fundamental endomorphism field [Formula: see text] is parallel in the direction of the characteristic vector field [Formula: see text] ([Formula: see text]), then it is [Formula: see text]-almost cosymplectic. In particular, an almost cosymplectic [Formula: see text]-manifold [Formula: see text] satisfying [Formula: see text] is semi-symmetric if and only if it is cosymplectic. Next, we prove that pseudo-symmetric [Formula: see text]-almost cosymplectic [Formula: see text]-manifolds are certain generalized almost cosymplectic [Formula: see text]-spaces.
The pro-p-Iwahori invariants of the universal quotient representation for GL2(F)
Authors: Jana Arindam
Published: April 2023

Let [Formula: see text] be a finite extension of [Formula: see text]. Every supersingular mod [Formula: see text] representation of [Formula: see text] is a quotient of a certain universal module, say [Formula: see text] The space of pro-[Formula: see text]-Iwahori invariants of [Formula: see text] is instrumental in classifying the supersingular mod [Formula: see text] representations of [Formula: see text]. For [Formula: see text] the space of pro-[Formula: see text]-Iwahori invariants of [Formula: see text] has been determined by Schein and Hendel using the spherical Hecke algebra. An alternative way to study mod [Formula: see text] representations of [Formula: see text] is introduced by Anandavardhanan and Borisagar using the Iwahori–Hecke algebra. In this paper, we give a canonical isomorphism between the universal modules for [Formula: see text] obtained from the spherical approach and the Iwahori–Hecke approach. We also compute an explicit basis of the pro-[Formula: see text]-Iwahori invariant space of [Formula: see text] for [Formula: see text] using the Iwahori–Hecke approach. This method allows us to extend Hendel’s computation slightly in the range of [Formula: see text]-adic digits from [Formula: see text] to [Formula: see text]
Iterated integrals, multiple zeta values and Selberg integrals
Authors: Li Jiangtao
Published: April 2023

Classical multiple zeta values can be viewed as iterated integrals of the differentials [Formula: see text] from [Formula: see text] to [Formula: see text]. In this paper, we reprove Brown’s theorem: For [Formula: see text], the iterated integral of the form [Formula: see text] is a [Formula: see text]-linear combination of multiple zeta values of weight [Formula: see text] if convergent.

What is more, we show that if [Formula: see text] are in a [Formula: see text]-algebra generated by multiple polylogarithms and their dual, and if [Formula: see text], are in a [Formula: see text]-algebra generated by logarithm, then the iterated integral [Formula: see text] is a [Formula: see text]-linear combination of multiple zeta values.

As an application of our main results, we show that the coefficients of the Taylor expansions of the Selberg integrals [Formula: see text] (with respect to [Formula: see text]) at the integral points in some product of right half complex plane are [Formula: see text]-linear combinations of multiple zeta values for any [Formula: see text] This statement generalizes Terasoma’s original result.
The average of the exponential sums related to cusp forms
Authors: Hou Fei
Published: April 2023

In this paper, we investigate the average [Formula: see text] where [Formula: see text] for any [Formula: see text] and [Formula: see text], with [Formula: see text] running over primitive holomorphic cusp forms of weight [Formula: see text] and prime level P. As a result, we prove pointwise uniform bounds with respect to [Formula: see text], [Formula: see text] for the frequency of the P-values, and present that there exist strong oscillations in the exponential sum [Formula: see text], so long as the level of f varies. Concerning the applications of the main result, we consider the quadratic Waring problem associated to the coefficients of cusp forms exhibiting considerable cancellations.
Evaluation of iterated log-sine integrals in terms of multiple polylogarithms
Authors: Umezawa Ryota
Published: April 2023

It is known that multiple zeta values can be written in terms of certain iterated log-sine integrals. Conversely, we evaluate iterated log-sine integrals in terms of multiple zeta values and multiple polylogarithms in this paper. We also suggest some conjectures on multiple zeta values, multiple Clausen values, multiple Glaisher values and iterated log-sine integrals.
Cerebrovascular segmentation from mesoscopic optical images using Swin Transformer
Authors: Li Yuxin , Zhang Qianlong , Zhou Hang , Li Junhuai , Li Xiangning , Li Anan
Published: April 2023

Vascular segmentation is a crucial task in biomedical image processing, which is significant for analyzing and modeling vascular networks under physiological and pathological states. With advances in fluorescent labeling and mesoscopic optical techniques, it has become possible to map the whole-mouse-brain vascular networks at capillary resolution. However, segmenting vessels from mesoscopic optical images is a challenging task. The problems, such as vascular signal discontinuities, vessel lumens, and background fluorescence signals in mesoscopic optical images, belong to global semantic information during vascular segmentation. Traditional vascular segmentation methods based on convolutional neural networks (CNNs) have been limited by their insufficient receptive fields, making it challenging to capture global semantic information of vessels and resulting in inaccurate segmentation results. Here, we propose SegVesseler, a vascular segmentation method based on Swin Transformer. SegVesseler adopts 3D Swin Transformer blocks to extract global contextual information in 3D images. This approach is able to maintain the connectivity and topology of blood vessels during segmentation. We evaluated the performance of our method on mouse cerebrovascular datasets generated from three different labeling and imaging modalities. The experimental results demonstrate that the segmentation effect of our method is significantly better than traditional CNNs and achieves state-of-the-art performance.
Software Engineering Challenges for Quantum Computing
Authors: Felderer Michael , Taibi Davide , Palomba Fabio , Epping Michael , Lochau Malte , Weder Benjamin
Published: April 2023

The First Working Seminar on Quantum Software Engineering (WSQSE 2022) took place on December 15 and 16, 2022 in Innsbruck, Austria. An audience of 33 quantum computing and software engineering researchers and practitioners joined the two-day event. The workshop enabled us to foresee short-term and longterms perspectives of Quantum Software Engineering, as well as a set of requirements, issues, and challenges for architecting, programming, and testing Quantum Software Engineering applications. In this report, we provide the summary of the workshop, by reporting on the structure of the event and the main results coming from the sessions and working groups.
Single-Cell RNA Sequencing for Studying Human Cancers
Authors: Aran Dvir
Published: April 2023

Since the first publication a decade ago describing the use of single-cell RNA sequencing (scRNA-seq) in the context of cancer, over 200 datasets and thousands of scRNA-seq studies have been published in cancer biology. scRNA-seq technologies have been applied across dozens of cancer types and a diverse array of study designs to improve our understanding of tumor biology, the tumor microenvironment, and therapeutic responses, and scRNA-seq is on the verge of being used to improve decision-making in the clinic. Computational methodologies and analytical pipelines are key in facilitating scRNA-seq research. Numerous computational methods utilizing the most advanced tools in data science have been developed to extract meaningful insights. Here, we review the advancements in cancer biology gained by scRNA-seq and discuss the computational challenges of the technology that are specific to cancer research.
Engineering Innovations, Challenges, and Opportunities for Lignocellulosic Biorefineries: Leveraging Biobased Polymer Production
Authors: Shapiro Alison J. , O'Dea Robert M. , Li Sonia C. , Ajah Jamael C. , Bass Garrett F. , Epps, Thomas H.
Published: April 2023

Alternative polymer feedstocks are highly desirable to address environmental, social, and security concerns associated with petrochemical-based materials. Lignocellulosic biomass (LCB) has emerged as one critical feedstock in this regard because it is an abundant and ubiquitous renewable resource. LCB can be deconstructed to generate valuable fuels, chemicals, and small molecules/oligomers that are amenable to modification and polymerization. However, the diversity of LCB complicates the evaluation of biorefinery concepts in areas including process scale-up, production outputs, plant economics, and life-cycle management. We discuss aspects of current LCB biorefinery research with a focus on the major process stages, including feedstock selection, fractionation/deconstruction, and characterization, along with product purification, functionalization, and polymerization to manufacture valuable macromolecular materials. We highlight opportunities to valorize underutilized and complex feedstocks, leverage advanced characterization techniques to predict and manage biorefinery outputs, and increase the fraction of biomass converted into valuable products.
Eye Morphogenesis in Vertebrates
Authors: Casey Macaulie A. , Lusk Sarah , Kwan Kristen M.
Published: April 2023

Proper eye structure is essential for visual function: Multiple essential eye tissues must take shape and assemble into a precise three-dimensional configuration. Accordingly, alterations to eye structure can lead to pathological conditions of visual impairment. Changes in eye shape can also be adaptive over evolutionary time. Eye structure is first established during development with the formation of the optic cup, which contains the neural retina, retinal pigment epithelium, and lens. This crucial yet deceptively simple hemispherical structure lays the foundation for all later elaborations of the eye. Building on descriptions of the embryonic eye that started with hand drawings and micrographs, the field is beginning to identify mechanisms driving dynamic changes in three-dimensional cell and tissue shape. A combination of molecular genetics, imaging, and pharmacological approaches is defining connections among transcription factors, signaling pathways, and the intracellular machinery governing the emergence of this crucial structure.
Notch signaling inactivation by small molecule γ-secretase inhibitors restores the multiciliated cell population in the airway epithelium
Authors: Vladar Eszter K. , Kunimoto Koshi , Rojas-Hernandez Laura S. , Spano Jacquelyn M. , Sellers Zachary M. , Joo Nam Soo , Cooney Riley A. , Axelrod Jeffrey D. , Milla Carlos E.
Published: April 2023

Our findings show that low-dose, short-term topical or systemic γ-secretase inhibitor treatment may lead to restoration of multiciliated cells without toxicity and potentially improve epithelial function in a wide range of chronic lung diseases.