Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic Intermediate Gradient Method for Convex Problems with Inexact Stochastic Oracle

AbstractIn this paper we introduce new methods for convex optimization problems with inexactstochastic oracle. First method is an extension of the intermediate gradient method proposedby Devolder, Glineur and Nesterov for problems with inexact oracle. Our new method can beapplied to the problems with composite structure, stochastic inexact oracle and allows usingnon-Euclidean setup. We prove estimates for mean rate of convergence and probabilities oflarge deviations from this rate. Also we introduce two modi cations of this method for stronglyconvex problems. For the rst modi cation we prove mean rate of convergence estimates and forthe second we prove estimates for large deviations from the mean rate of convergence. All therates give the complexity estimates for proposed methods which up to multiplicative constantcoincide with lower complexity bound for the considered class of convex composite optimizationproblems with stochastic inexact oracle. 1 Introduction In this paper we introduce new rst-order methods for problems from rather wide class of convexcomposite optimization problems with stochastic inexact oracle. First order methods are widelydeveloped since the earliest stage of development of optimization theory, see e.g. [1, 2]. The book[3] started an activity in providing complexity bounds for proposed methods and for consideredclasses of problems (see also [4]). Later for convex problem with special structure ellipsoid methods(e.g. [5]) and interior-point methods [6] were proposed. These methods have very fast convergencerate but have rather costly iterations requiring for solving n-dimensional problem about n
Parametric Solution for Efficient Li-ion Battery Charging with Current and SOC Constraints

This paper utilizes Pontryagin’s Minimum Principle (PMP) and Quadratic Programming (QP) to find the optimal charging current profile for Li-ion batteries that minimizes energy losses. The optimization problem is formulated in terms of a second-order equivalent circuit model, and the closed-form solution is derived in the absence of constraints using PMP. The solution is parametric since it can adapt to different battery parameters without additional derivation. This result is then utilized to derive the necessary conditions of optimality and closed-form solution under the electrical current and State of Charge (SOC) constraints. Findings reveal that the SOC constraint is never active, and the optimal current input is a trajectory that combines the bang and hyperbolic functions. The optimal solution to the aforementioned problem is found using QP, which proves the PMP necessary conditions are also sufficient. The main contribution of this paper is the parametric solution of the constrained battery charging problem and the complete proof of its optimality. When compared to constant current charging, the optimal current reduces the charging energy loss by 10.8% and 9.5% in simulations without and with constraints respectively.
Teachers' Perceptions of Student's Weaknesses While Scoring Answer Sheets

This paper aims to explore the perceptions of examiners in examining bachelor's level answer sheets. This study was carried out by adopting the hermeneutic phenomenological method under a qualitative research design. The participant of the study were five teachers from the constituent campuses of Tribhuvan University.This study explored whether students mismatched the answer numbers, such as writing the incorrect answer or writing an irrelevant answer. Unpreparedness about curriculum content and writing inappropriate answers with verbal repertoire is a common problems. Most of the answer sheets were found to be lacking in managing the time while writing the answers. Furthermore, students were found poor at structuring answers and wrapping them with appropriate remarks. The study findings can contribute to the test construction, test administration, and refinement of a student's writing with relevant content and demand for the questions.
Geometrical dependence of optimal bounds in Taylor–Couette flow

This paper is concerned with the optimal upper bound on mean quantities (torque, dissipation and the Nusselt number) obtained in the framework of the background method for the Taylor–Couette flow with a stationary outer cylinder. Along the way, we perform the energy stability analysis of the laminar flow, and demonstrate that below radius ratio $0.0556$ , the marginally stable perturbations are not the axisymmetric Taylor vortices but rather a fully three-dimensional flow. The main result of the paper is an analytical expression of the optimal bound as a function of the radius ratio. To obtain this bound, we begin by deriving a suboptimal analytical bound using analysis techniques. We use a definition of the background flow with two boundary layers, whose relative thicknesses are optimized to obtain the bound. In the limit of high Reynolds number, the dependence of this suboptimal bound on the radius ratio (the geometrical scaling) turns out to be the same as that of numerically computed optimal bounds in three different cases: (1) the perturbed flow only satisfies the homogeneous boundary conditions but need not be incompressible; (2) the perturbed flow is three-dimensional and incompressible; (3) the perturbed flow is two-dimensional and incompressible. We compare the geometrical scaling with the observations from the turbulent Taylor–Couette flow, and find that the analytical result indeed agrees well with the available direct numerical simulations data. In this paper, we also dismiss the applicability of the background method to certain flow problems and therefore establish the limitation of this method.
The complete chloroplast genome of Miliusa glochidioides (Annonaceae) and phylogenetic analysis

Abstract The chloroplast (cp) genome of Miliusa glochidioides has been fully sequenced. The cp genome of this species has a typical quadripartite structure comprised of four parts: a large single copy (LSC; 88,782 bp) region, a small single copy (SSC; 18,949 bp) region, and two inverted repeat (IR; 26,029 bp each) regions. The full length of the cp genome is 159,789 bp; its GC content is 36.7%, and it encodes a total of 129 genes including 84 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Among the protein-coding genes, nine (rps16, rpl2, rpl16, atpF, rpoC1, petB, petD, ndhA, and ndhB) contain one intron, and three (rps12, clpP, and ycf3) have two introns. A maximum-likelihood (ML) phylogenetic tree shows that M. glochidioides is a sister to Chieniodendron hainanense.
Association of Dilated Perivascular Spaces With Lipid Indices in Ischemic Stroke Patients

Background Dilated perivascular spaces (dPVS) in the basal ganglia are associated with aging, vascular risk factors, and other magnetic resonance imaging (MRI) markers of cerebral small vessel disease (cSVD). While high blood lipids are a well-demonstrated risk factor for large artery atherosclerosis, their role in cSVD remains largely elusive. Methods We evaluated lipid profiles, cardiovascular risk factors, and brain MRI findings in patients with ischemic stroke or transient ischemic attack. We analyzed the extent of dPVS, cerebral microbleed (CMB), and cerebral white matter hyperintensities (WMHs) as MRI indices of cSVD and investigated associations of dPVS with lipid parameters and other cSVD indices. Results Our study enrolled 173 patients with ischemic stroke or transient ischemic attack. The mean age was 68.38±14.31 (range 35-99) years, and 57.8% (n=100) of patients were male. dPVSwere detected in 97% (n=168) of the patients. Among the whole population, half of the patients (n=87) had moderate to severe dPVS. According to the univariate analysis, age, hypertension, previous antiaggregant and/or anticoagulant use, and the high-density lipoprotein to low-density lipoprotein (HDL/LDL) ratio but not other lipid profiles, cerebral microbleed load, and cerebral white matter hyperintensities severity were found to be positively associated with dPVS number in the basal ganglia. After multivariate logistic regression analysis, only age and WMH severity remained statistically significant. Conclusions dPVS are closely associated with other cSVD subtypes and aging. The studied lipid indices were not independently associated with moderate to severe dPVS in basal ganglia in ischemic stroke patients. The association of each lipid and HDL/LDL ratio needs to be further studied with a larger number of participants.
AN EFFICIENT COMPROMISED IMPUTATION METHOD FOR ESTIMATING POPULATION MEAN

This paper suggests a modified new ratio-product-exponential imputation procedure to deal with missing data in order to estimate a finite population mean in a simple random sample without replacement. The bias and mean squared error of our proposed estimator are obtained to the first degree of approximation. We derive conditions for the parameters under which the proposed estimator has smaller mean squared error than the sample mean, ratio, and product estimators. We carry out an empirical study which shows that the proposed estimator outperforms the traditional estimators using real data.
Strategies for Increasing Asian American, Native Hawaiian, and Pacific Islander Representation in Survey Research

The Asian American, Native Hawaiian, and Pacific Islander (AANHPI) population in the United States is growing rapidly and is geographically dispersed and culturally diverse. Yet, national estimates produced for this population are often limited to a subset, typically those who are English proficient. Meaningful representation of AANHPI communities in survey research requires strategies that account for their diverse linguistic and cultural characteristics. However, translation alone will not suffice to increase representation. More culturally responsive approaches are needed as well. In a joint project, AARP and NORC at the University of Chicago reviewed the literature and conducted semistructured interviews with experts in AANHPI representation in research to examine barriers to AANHPI survey participation and strategies for overcoming these barriers. This article presents findings and recommendations from this research. We discuss three key challenges to AANHPI representation in surveys: Lack of familiarity with surveys and their importance, lack of trust in those conducting surveys, and issues of language and translation. We then present strategies for increasing AANHPI survey participation: Involving trusted leaders of the AANHPI community, at the local or national level as appropriate for the study; focusing on messaging about the survey that is culturally appropriate and tailored to the population; and providing culturally appropriate translations.
Self-compassion and negative outgroup attitudes: The mediating role of compassion for others

ABSTRACT Self-compassion, rooted in common humanity, self-kindness, and mindfulness, is an adaptive self-concept that assuages defensiveness to self-image threats. We hypothesized that self-compassion would buffer the need to express negative intergroup attitudes and that this relation would be explained by compassion for others. In a preregistered study, participants (N = 163) with stronger self-compassion rooted in common humanity, but not self-kindness or mindfulness, expressed less negative attitudes toward outgroups than those with lower self-compassion rooted in common humanity. Moreover, this relation persisted even after controlling for self-esteem, a construct related to but distinct from self-compassion. Finally, compassion for others mediated the relation between self-compassion and intergroup attitudes. These findings support the positive and unique role of individual-level self-compassion in intergroup relations.
Formulation and Characterization of Carbamazepine Chitosan Nanoparticle

Background: Carbamazepine is an antiepileptic drug used to treat trigeminal neuralgia and pain associated with neurological disorders. The drug belongs to class II of the Biopharmaceutical Classification System (BCS), which has low solubility. Hence, dissolution is a rate-limiting step. Objective: This study aimed to determine the best formula for carbamazepine nanoparticles based on physical characteristics and determine the effect of chitosan and Na-TPP concentration variation on nanoparticle characterization. Methods: The carbamazepine chitosan nanoparticles were prepared using ionic gelation method with a concentration of 0.1% w/v carbamazepine and the ratio of chitosan and Na-TPP concentrations of 0.2%:0.1% (F1), 0.2%:0.2% (F2), and 0.3%:0.1% w/v (F3). The parameters evaluated included particle size, polydispersity index, zeta potential, particle morphology, and entrapment efficiency. Statistical analysis was conducted on the evaluation data using One Way ANOVA. Results: The results showed that the effect of increasing the concentration of chitosan reduced particle size (p<0.05), increased zeta potential (p<0.05), and had no effect on the value of entrapment efficiency (p>0.05). Furthermore, F3 had a particle size of 169.8±13.71 nm with a polydispersity index of 0.378±0.02, the zeta potential of +28.80±2.44 mV, entrapment efficiency of 84.3±7.50%, and spheric particle morphology which was measured using Transmission Electron Microscope (TEM). Conclusion: Therefore, F3 with the ratio of chitosan and Na-TPP concentrations of 0.3%:0.1% was the formula that provided the best characteristics of chitosan carbamazepine nanoparticles.
Predicting early‐age stress evolution in restrained concrete by thermo‐chemo‐mechanical model and active ensemble learning

Early‐age stress (EAS) is an important index for evaluating the early‐age cracking risk of concrete. This paper encompasses a thermo‐chemo‐mechanical (TCM) model and active ensemble learning (AEL) for predicting the EAS evolution. The TCM model provides the data for the AEL model. First, based on Fourier's law, Arrhenius’ equation, and rate‐type creep law, a TCM model is built to simulate the heat transfer, cement hydration, and viscoelasticity, which together determine the EAS evolution. Then, a material model composed of an eXtreme Gradient Boosting model and adjusted Model Code 2010 is built to allow for parametric study and database construction. Finally, an AEL framework is built, which incorporates principal component analysis (PCA), Gaussian process, and light gradient boosting machine (LGBM). This study resulted in the following findings: (1) The dimensionality of the 672‐by‐1 EAS vector can be effectively reduced by PCA, and the first principal component (PC) is a global index representing the magnitude of the EAS; (2) the mechanical field of the TCM model is validated by testing data. Correlation analysis on the first PC quantifies the influence of various input parameters of the TCM model, which is in accordance with common understandings of the EAS evolution process. (3) The AEL and one‐shot ensemble learning (OSEL) both achieve high prediction performance in the testing set, whose R2 reaches 0.961 and 0.948, respectively. Thanks to the uncertainty‐based query procedure, comparing with OSEL, AEL shows advantages in prediction performance over the whole training history. (4) AEL can significantly reduce the number of samples required for training, which can be a major improvement in efficiency considering the computational cost of the TCM model.
The impacts of using modules on students’ entrepreneurial attitudes and intentions

The covid-19 pandemic made classroom-based learning change into online-based digital learning. It leads to the students’ need for useful learning resources to study independently. The current research aimed to evaluate the impacts of module-assisted learning on students’ entrepreneurial attitudes and intentions. It was designed with a one-group quasi-experimental pre-and post-test, and the whole learning process was online. It was hypothesized that there will be a remarkable improvement in students’ entrepreneurial attitudes and intentions after they learn with the module. Data were collected by distributing questionnaires to students of two selected universities. To test the deviation between the two population means, t-test formula was used. The results demonstrated that 1) the use of modules can significantly improve students’ entrepreneurial attitudes and 2) it cannot significantly increase their entrepreneurial intentions. Online learning of entrepreneurship with modules can increase entrepreneurial attitudes, but to increase entrepreneurial intentions, it is vital to explore learning strategies through maximum use of information technology. Keywords: COVID-19 pandemic, entrepreneurial attitude, entrepreneurial intention, entrepreneurship education, entrepreneurship module.
Is There a Relevant Clinical Impact in Differentiating Idiopathic versus Unexplained Male Infertility?

Purpose Overall, male factor infertility (MFI) accounts for up to 50% of etiologies of couple’s infertility, with almost 30% of MFI cases being idiopathic in nature. Idiopathic MFI does not support a tailored treatment work-up in clinical practice. To investigate rates of and characteristics of men presenting for idiopathic versus unexplained primary infertility as compared with same-ethnicity, age-comparable fertile men. Materials and Methods Demographic, clinical and laboratory data from 3,098 primary infertile men consecutively evaluated were analyzed and compared with those of 103 fertile controls. Idiopathic male infertility (IMI) was defined for abnormality at semen analysis with no previous history of diseases affecting fertility and normal findings on physical examination and genetic and laboratory testing. Unexplained male infertility (UMI) was defined as infertility of unknown origin with completely normal findings at semen analysis. Descriptive statistics and logistic regression models tested the association between clinical variables and idiopathic infertility status. Results Overall, 570 (18.5%) and 154 (5.0%) patients depicted criteria suggestive for either IMI or UMI, respectively. Groups were similar in terms of age, BMI, CCI, recreational habits, hormonal milieu, and sperm DNA fragmentation indexes. Conversely, testicular volume was lower in IMI (p<0.001). Vitamin D3 levels were lower in IMI vs. UMI vs. fertile controls (p=0.01). At multivariable logistic regression analysis only vitamin D3 deficiency (OR, 9.67; p=0.03) was associated with IMI. Characteristics suggestive for IMI versus UMI were observed in almost 20% and 5% of men, respectively. Overall, clinical differences between groups were slightly significant and certainly not supportive of a tailored management work-up. Conclusions Current findings further support the urgent need of a more detailed and comprehensive assessment of infertile men to better tailoring their management work-up in the everyday clinical setting.
Stochastic Claims Reserving Methods in Insurance

Preface. Acknowledgement. 1 Introduction and Notation. 1.1 Claims Process. 1.2 Structural Framework to the Claims-Reserving Problem. 1.3 Outstanding Loss Liabilities, Classical Notation. 1.4 General Remarks. 2 Basic Methods. 2.1 Chain-Ladder Method (Distribution-Free). 2.2 Bornhuetter-Ferguson Method. 2.3 Number of IBNyR Claims, Poisson Model. 2.4 Poisson Derivation of the CL Algorithm. 3 Chain-Ladder Models. 3.1 Mean Square Error of Prediction. 3.2 Chain-Ladder Method. 3.3 Bounds in the Unconditional Approach. 3.4 Analysis of Error Terms in the CL Method. 4 Bayesian Models. 4.1 Benktander-Hovinen Method and Cape-Cod Model. 4.2 Credible Claims Reserving Methods. 4.3 Exact Bayesian Models. 4.4 Markov Chain Monte Carlo Methods. 4.5 Buhlmann-Straub Credibility Model. 4.6 Multidimensional Credibility Models. 4.7 Kalman Filter. 5 Distributional Models. 5.1 Log-Normal Model for Cumulative Claims. 5.2 Incremental Claims. 6 Generalized Linear Models. 6.1 Maximum Likelihood Estimators. 6.2 Generalized Linear Models Framework. 6.3 Exponential Dispersion Family. 6.4 Parameter Estimation in the EDF. 6.5 Other GLM Models. 6.6 Bornhuetter-Ferguson Method, Revisited. 7 Bootstrap Methods. 7.1 Introduction. 7.2 Log-Normal Model for Cumulative Sizes. 7.3 Generalized Linear Models. 7.4 Chain-Ladder Method. 7.5 Mathematical Thoughts about Bootstrapping Methods. 7.6 Synchronous Bootstrapping of Seemingly Unrelated Regressions. 8 Multivariate Reserving Methods. 8.1 General Multivariate Framework. 8.2 Multivariate Chain-Ladder Method. 8.3 Multivariate Additive Loss Reserving Method. 8.4 Combined Multivariate CL and ALR Method. 9 Selected Topics I: Chain-Ladder Methods. 9.1 Munich Chain-Ladder. 9.2 CL Reserving: A Bayesian Inference Model. 10 Selected Topics II: Individual Claims Development Processes. 10.1 Modelling Claims Development Processes for Individual Claims. 10.2 Separating IBNeR and IBNyR Claims. 11 Statistical Diagnostics. 11.1 Testing Age-to-Age Factors. 11.2 Non-Parametric Smoothing. Appendix A: Distributions. A.1 Discrete Distributions. A.2 Continuous Distributions. Bibliography. Index.
Structured Online Learning for Low-Level Control of Quadrotors

Although effective low-level control configurations of quadrotors are already known, the tuning of such controllers requires extensive expert knowledge which can impede their design and deployment. Considering the growing demand for quadrotors in different environments, the importance of an automated approach to designing the controller cannot be neglected. For this purpose, recently, a successful implementation of a model-based reinforcement learning technique was demonstrated by training a neural network using only flight data. In this paper, as an alternative to the neural network approach, we employ a structured model parameterized by a set of bases to identify the governing dynamics of quadrotors. The model accompanied by a value function defined in the product space of the bases leads to an analytical update rule for the controller that can be effectively solved by ODE solvers. The runtime results confirm that the controller together with a recursive least squares identifier can be used as a lightweight framework for learning to stabilize an unknown quadrotor at a given position. In the simulation results, a nonlinear model of the quadrotor is exploited that replaces the real unknown quadrotor. The flight data and 3D graphical simulation are generated to verify the presented learning approach.
Mixed Dimensional Compactness with Dimension Collapsing from Sn-1 Bundle Measures

We provide a measure based topology for certain unions of C2 rectifiable submanifolds of mixed dimensions in Rn. In this topology lower dimensional sets remain in the limit as measures when higher dimensional sets collapse down to them. For example a decreasing sequence of spheres may have a limit consisting of just a point. The n-1 dimensional space of outward pointing vectors can be used for such a measure. It represents all C2 rectifiable sets of codimension at least one of Rn as rectifiable sets in RnXSn-1 with n-1 dimensional Hausdorff measure. When viewed as (n-1)-rectifiable varifolds or currents in RnXSn-1 they come equipped with compactness theorems. The projection of their limits to Rn recovers the rectifiable sets of mixed dimensions giving the limits for the desired topology on subsets of Rn. Both varifold and current compactness are required as there are sequences, such as honeycombs, that converge as varifolds but not as currents. Conversely sequences such as lifts of polyhedral approximations converge as currents but not as varifolds.