Miracle-dz/UniFAR-FTUs huggingface dataset:
Variable selection in high dimensional semi-varying coefficient models

With the development of computing and sampling technologies, high dimensionality has become an important characteristic of commonly used science data, such as some data from bioinformatics, information engineering, and the social sciences. The varying coefficient model is a flexible and powerful statistical model for exploring dynamic patterns in many scientific areas. It is a natural extension of classical parametric models with good interpretability, and is becoming increasingly popular in data analysis. The main objective of thesis is to apply the varying coefficient model to analyze high dimensional data, and to investigate the properties of regularization methods for high-dimensional varying coefficient models. We first discuss how to apply local polynomial smoothing and the smoothly clipped absolute deviation (SCAD) penalized methods to estimate varying coefficient models when the dimension of the model is diverging with the sample size. Based on the nonconcave penalized method and local polynomial smoothing, we suggest a regularization method to select significant variables from the model and estimate the corresponding coefficient functions simultaneously. Importantly, our proposed method can also identify constant coefficients at same time. We investigate the asymptotic properties of our proposed method and show that it has the so called “oracle property. ” We apply the nonparametric independence Screening (NIS) method to varying coefficient models with ultra-high-dimensional data. Based on the marginal varying coefficient model estimation, we establish the sure independent screening property under some regular conditions for our proposed sure screening method. Combined with our proposed regularization method, we can systematically deal with high-dimensional or ultra-high-dimensional data using varying coefficient models. The nonconcave penalized method is a very effective variable selection method. However, maximizing such a penalized likelihood function is computationally challenging, because the objective functions are nondifferentiable and nonconcave. The local linear approximation (LLA) and local quadratic approximation (LQA) are two popular algorithms for dealing with such optimal problems. In this thesis, we revisit these two algorithms. We investigate the convergence rate of LLA and show that the rate is linear. We also study the statistical properties of the one-step estimate based on LLA under a generalized statistical model with a diverging number of dimensions. We suggest a modified version of LQA to overcome its drawback under high dimensional models. Our proposed method avoids having to calculate the inverse of the Hessian matrix in the modified Newton Raphson algorithm based on LQA. Our proposed methods are investigated by numerical studies and in a real case study in Chapter 5.
Existence and Uniqueness of Solutions for(Systems of)Mixed Non-Monotone Binary Operator Equations

By using the cone theory and the Banach's contraction mapping principle,the existence and uniqueness theorems of solutions for a class of systems of mixed non-monotone binary operator equations as well as mixed non-monotone binary operator equations and unary operator equations in ordered Banach spaces under more general conditions without demanding the existence of upper and lower solutions and compactness and continuity conditions are established.The results in this paper generalize many known results.
Distribution of transmission eigenvalues and inverse spectral analysis with partial information on the refractive index

In this work, we consider the interior transmission eigenvalue problem for a spherically stratified medium, which can be formulated as y′′(r) + k2η(r)y(r) = 0 endowed with boundary conditions y(0)=0=y′(1)sinkk−y(1)cosk , where the refractive index η(r) is positive and real. We obtain the distribution of transmission eigenvalues under assumptions that a:=∫01η(r)dr=1 and one of these conditions that (i) η(1) ≠ 1, (ii) η(1) = 1,η′(1) ≠ 0, and (iii) η(1) = 1,η′(1) = 0,η″(1) ≠ 0, respectively. Moreover, in the case a = 1, we prove that if partial information on η(r) is known on subdomain, then only a part of eigenvalues can uniquely determine η(r) on the whole interval, and the relationship between the proportion of the missing eigenvalues and the subinterval of the known information on η(r) is revealed. Copyright © 2016 John Wiley & Sons, Ltd.
Non-commutative measure theory: Henkin and analytic functionals on C ∗ -algebras

Henkin functionals on non-commutative C ∗ -algebras have recently emerged as a piv-otal link between operator theory and complex function theory in several variables. Our aim in this paper is characterize these functionals through a notion of absolute continuity, inspired by a seminal theorem of Cole and Range. To do this, we recast the problem as a question in non-commutative measure theory. We develop a Glicksberg– König–Seever decomposition of the dual space of a C ∗ -algebra into an absolutely continuous part and a singular part, relative to a ﬁxed convex subset of states. Lever-aging this tool, we show that Henkin functionals are absolutely continuous with respect to the so-called analytic functionals if and only if a certain compatibility condition is satisﬁed by the ambient weak- ∗ topology. In contrast with the classical setting, the issue of stability under absolute continuity is not automatic in this non-commutative framework, and we illustrate its key role in sharpening our description of Henkin functionals. Our machinery yields new insight when specialized to the multiplier algebras of the Drury–Arveson space and of the Dirichlet space, and to Popescu’s noncommutative disc algebra. As another application, we make a contribution to the theory of non-commutative peak and interpolation sets.
Unravelling the controversy with small intestinal bacterial overgrowth

Purpose of review The aim of this review is to summarize the current and emergent approaches to characterize the small intestinal microbiota and discuss the treatment options for management of small intestinal bacterial overgrowth (SIBO). Recent findings This review captures the growing body of evidence for the role of SIBO, a type of small intestinal dysbiosis in the pathophysiology various gastrointestinal and extraintestinal disorders. We have highlighted the drawbacks of the available methods for characterizing the small intestinal microbiota and focus on the new culture-independent techniques to diagnose SIBO. Although recurrence is common, targeted modulation of the gut microbiome as a therapeutic option for management of SIBO is associated with improvement in symptoms and quality of life. Summary As a first step to precisely characterize the potential link between SIBO and various disorders, we need to address the methodological limitations of the available traditional tests for diagnosing SIBO. There is an urgency to develop culture independent techniques that can be routinely used in clinical setting, that will enable characterization of the gastrointestinal microbiome and explore the response to antimicrobial therapy including the links between long-lasting symptom resolution and the microbiome.
Predicting Complicated Mild Traumatic Brain Injury in Adolescent Trauma to Enhance Clinical Decisions in Imaging

BACKGROUND: The Pediatric Emergency Care Applied Research Network (PECARN) traumatic brain injury algorithm is used to identify children at low risk of clinically significant traumatic brain injuries to reduce computed tomography (CT) exposure. Adapting PECARN rules based on population-specific risk stratification has been suggested to improve diagnostic accuracy. OBJECTIVE: This study sought to identify center-specific patient variables, beyond PECARN rules, that may enhance the identification of patients requiring neuroimaging. METHODS: This single-center, retrospective cohort study was conducted from July 1, 2016, to July 1, 2020, in a Southwestern U.S. Level II pediatric trauma center. The inclusion criteria were adolescents (10–15 years), Glasgow Coma Scale (13–15), with a confirmed mechanical blow to the head. Patients without a head CT were excluded. Logistic regression was performed to identify additional complicated mild traumatic brain injury predictor variables beyond the PECARN. RESULTS: There were 136 patients studied; 21 (15%) presented with a complicated mild traumatic brain injury. Relative to motorcycle collision or all-terrain vehicle trauma (odds ratio [OR] 211.75, 95% confidence interval, CI [4.51, 9931.41], p < .001), an unspecified mechanism (OR 42.0, 95% CI [1.30, 1350.97], p = .03) and consult activation (OR 17.44, 95% CI [1.75, 173.31], p = .01) were significantly associated with complicated mild traumatic brain injury. CONCLUSIONS: We identified additional factors associated with complex mild traumatic brain injury, including motorcycle collision and all-terrain vehicle trauma, unspecified mechanism, and consult activation that are not in the PECARN imaging decision rule. Adding these variables may aid in determining the need for appropriate CT scanning.
Therapeutic Strategies for Spinocerebellar Ataxia Type 1

Spinocerebellar ataxia type 1 (SCA1) is an autosomal dominant neurodegenerative disorder that affects one or two individuals per 100,000. The disease is caused by an extended CAG repeat in exon 8 of the ATXN1 gene and is characterized mostly by a profound loss of cerebellar Purkinje cells, leading to disturbances in coordination, balance, and gait. At present, no curative treatment is available for SCA1. However, increasing knowledge on the cellular and molecular mechanisms of SCA1 has led the way towards several therapeutic strategies that can potentially slow disease progression. SCA1 therapeutics can be classified as genetic, pharmacological, and cell replacement therapies. These different therapeutic strategies target either the (mutant) ATXN1 RNA or the ataxin-1 protein, pathways that play an important role in downstream SCA1 disease mechanisms or which help restore cells that are lost due to SCA1 pathology. In this review, we will provide a summary of the different therapeutic strategies that are currently being investigated for SCA1.
Structural and electronic properties of glassy GeSe 2 surfaces

We report first-principles structural models of surfaces of glassy GeSe2 (g-GeSe2). The structural properties of bulk and surface g-GeSe2 are compared with recent experimental data. The first diffraction peaks in the partial structure factors are accurately reproduced in both the surface and bulk models. We also examine the transition of the local bonding environment from the bulk to the surface. The surface reconstruction involves creation of several edge-sharing tetrahedra and electronic states are easily delocalized through rings formed in the reconstruction.
The influence of pet ownership on self-compassion among nurses: a cross-sectional study

Background The modern lifestyle trend of pet ownership is undoubtedly beneficial for both physical and mental health. Research has shown a connection between pet ownership and staff self-compassion. However, there has not been any evidence linking pet ownership to self-compassion in the nurse population. Aims To investigate the current status of pet ownership among nurses and explore the influence of pet ownership on self-compassion among nurses. Methods An online survey was conducted in July 2022 with 1,308 nurses in China. Data were collected using a general information questionnaire and a self-compassion scale. To compare categorical variables, the independent t test, one-way ANOVA, and multiple linear regression analysis were utilized. SPSS software was used for the statistical analysis. Results We found that 16.9% of nurses owned at least one pet, and dogs and cats were the primary pets. The t test for independent samples showed that pet owners and non-pet owners scored differently on self-compassion (t = 3.286, p = 0.001), self-kindness (t = 3.378, p = 0.001), common humanity (t = 2.419, p = 0.016), and mindfulness (t = 2.246, p = 0.025). One-way ANOVA revealed that the highest degree was an influencing factor of self-compassion (χ2 = 1.386, p = 0.019). Multiple linear regression showed that average monthly income, pet ownership, and highest degree were the factors that influenced self-compassion most significantly (F = 8.335, p < 0.001). Conclusion The results revealed that nurses actually own pets as part of their modern lifestyle, which provides them with social support and potentially enhances their self-compassion. More efforts should be focused on the impact of pet ownership on nurses’ physical and mental health, and pet-based interventions should also be developed.
An Explainable and Actionable Mistrust Scoring Framework for Model Monitoring

Continuous monitoring of trained ML models to determine when their predictions should and should not be trusted is essential for their safe deployment. Such a framework ought to be high-performing, explainable, post-hoc and actionable. We propose TRUST-LAPSE, a"mistrust"scoring framework for continuous model monitoring. We assess the trustworthiness of each input sample's model prediction using a sequence of latent-space embeddings. Specifically, (a) our latent-space mistrust score estimates mistrust using distance metrics (Mahalanobis distance) and similarity metrics (cosine similarity) in the latent-space and (b) our sequential mistrust score determines deviations in correlations over the sequence of past input representations in a non-parametric, sliding-window based algorithm for actionable continuous monitoring. We evaluate TRUST-LAPSE via two downstream tasks: (1) distributionally shifted input detection, and (2) data drift detection. We evaluate across diverse domains - audio and vision using public datasets and further benchmark our approach on challenging, real-world electroencephalograms (EEG) datasets for seizure detection. Our latent-space mistrust scores achieve state-of-the-art results with AUROCs of 84.1 (vision), 73.9 (audio), and 77.1 (clinical EEGs), outperforming baselines by over 10 points. We expose critical failures in popular baselines that remain insensitive to input semantic content, rendering them unfit for real-world model monitoring. We show that our sequential mistrust scores achieve high drift detection rates; over 90% of the streams show<20% error for all domains. Through extensive qualitative and quantitative evaluations, we show that our mistrust scores are more robust and provide explainability for easy adoption into practice.
In Support of a DP-Analysis of Nominal Phrases in Croatian

I. reapplication of the morphosyntactic locus and the semantic argument tests shows that the noun is not the ultimate morphosyntactic locus of the NP => determiners (quantifiers, numerals) also carry phi-features and display head-like properties II. morphological and syntactic differences between determiners and adjectives show that they do not belong to the same class III. split readings in premodified coordinated NPs (wide scope readings) suggest that adjectives (and determiners) cannot be NP-internal IV. demonstrative determiners (as potential “article substitutes” in Croatian) are not always optional within NP (as assumed in 2) => being D-elements of non-adjectival nature they occupy their own functional projections above NP (see Appendix)
Analysis And Application Of Optimal Homotopy Asymptotic Method And The Use Of Daftardar Jaffery Polynomials

In this thesis, we use the standard optimal homotopy asymptotic method for the analytical solution of higher order ordinary differential equations with two or multi point boundary conditions, a nonlinear family of partial differential equations with an initial condition and Integro differential equations.The results obtained are compared with the results obtained by the application of Adomain decomposition method, homotopy perturbation method, variational iteration method, differential transform method and homotopy analysis method etc.The optimal homotopy asymptotic method uses a flexible auxiliary function, which controls the convergence of the solution and allows adjustment in the convergence region where it is needed. Moreover, the procedure of this method is simple, clearly well-defined and the built-in recursive relations are explicitly worked out for easy use. Numerical results obtained by the optimal homotopy asymptotic method reveal high accuracy and excellent agreement with the exact solutions.Apart from the application of optimal homotopy asymtotic method, we develop a new scheme by using Daftardar-Jafari polynomials in the homotopy of optimal homotopy asymptotic method to solve nonlinear problems more effectively.This scheme is almost as simple as the optimal homotopy asymtotic method but its results are more accurate than the usual optimal homotopy asymptotic method.To show the effectiveness of this scheme, we solve different bench mark problems from literature and compare the results with those obtained by the standard optimal homotopy asymptotic method.To determine the convergence control parameters of the auxiliary function, two well known methods are followed The Least squares and the Galerkin methods. We also explore and use a variety of the forms of auxiliary functions that results more accuracy and shows flexibility and reliability of the methods.For symbolic computation, we use Mathematica 7.The work presented in chapters 2, 3 and 4 of this thesis has been published in different reputed international journals and the work presented in chapters 3, 5, 6 and 7 is submitted for possible publication.The details of published/submitted work are included in the list of publications.
The Increasing Role of Seasonal Rainfall in Western U.S. Summer Streamflow

Summer streamflow variations strongly affect water supply reliability and ecological functioning of western U.S. (WUS) streams. Traditional snow‐based forecasts of summer streamflow are becoming less accurate with warming‐induced reductions in winter snow accumulation. This reflects a rising importance of competing runoff‐generating processes in controlling summer streamflow variations, primarily an increasing role of rainfall in contrast to snowmelt. Here, based on a snowmelt‐rainfall tracking algorithm applied to two hydrological models, we show that cool‐season rainfall provides an important volumetric contribution to summer streamflow for many WUS streams in the current climate, and this contribution will increase under climate warming, especially in years with warm snow droughts and abnormally dry summers. We also show that seasonal rainfall (warm‐/cool‐seasons) dominates the variability of summer streamflow across ∼70% area of WUS. We show that an increasing warm‐season rainfall contribution to summer streamflow (largely replacing snowmelt) results in reduced summer streamflow predictability.
Teacher's Speech Acts in Indonesian Language Learning at Islamic Boarding School

Pesantren, or Islamic boarding school, is one of the places where speech acts occur between teachers and students. The linguistic phenomena in the Islamic boarding school environment are very diverse. This study aimed to describe teachers' speech acts in learning the Indonesian language in class VIII at Islamic Boarding School Salsabila Samarinda, focusing on exploring locutionary, illocutionary, and perlocutionary acts. This study used a qualitative descriptive research method to describe the phenomenon. The data source was the teacher's speech in Indonesian language learning. The data collection techniques used in this research were observation, recording, and transcription. In this study, the data obtained were the results of recordings that were transcribed to obtain written notes from the subject. The data analysis techniques used were collecting, analyzing, and interpreting data. The results showed that the speech acts found in Indonesian language learning are locutionary acts in the form of news and question, illocutionary acts in the form of directive utterances, and perlocutionary acts of convivial and motivational functions. The locutionary acts spoken by the teacher in the Indonesian language learning process were 52 utterances, illocutionary acts were 30 utterances, perlocutionary acts were 25. The teacher’s speech acts in the boarding school environment have particular characteristics like using Islamic terms, Arabic language, and containing religious motivation in the utterances. The results of this research might have implications to contribute to insights about locutionary, illocutionary, and perlocutionary acts in the boarding school environment.
A Scoping Review Investigating the “Gene-Dosage Theory” of Mitochondrial DNA in the Healthy Skeletal Muscle

This review provides an overview of the evidence regarding mtDNA and valid biomarkers for assessing mitochondrial adaptions. Mitochondria are small organelles that exist in almost all cells throughout the human body. As the only organelle, mitochondria contain their own DNA, mitochondrial DNA (mtDNA). mtDNA-encoded polypeptides are subunits of the enzyme complexes in the electron transport chain (ETC) that are responsible for production of ATP to the cells. mtDNA is frequently used as a biomarker for mitochondrial content, since changes in mitochondrial volume are thought to induce similar changes in mtDNA. However, some exercise studies have challenged this “gene-dosage theory”, and have indicated that changes in mitochondrial content can adapt without changes in mtDNA. Thus, the aim of this scoping review was to summarize the studies that used mtDNA as a biomarker for mitochondrial adaptions and address the question as to whether changes in mitochondrial content, induce changes in mtDNA in response to aerobic exercise in the healthy skeletal muscle. The literature was searched in PubMed and Embase. Eligibility criteria included: interventional study design, aerobic exercise, mtDNA measurements reported pre- and postintervention for the healthy skeletal muscle and English language. Overall, 1585 studies were identified. Nine studies were included for analysis. Eight out of the nine studies showed proof of increased oxidative capacity, six found improvements in mitochondrial volume, content and/or improved mitochondrial enzyme activity and seven studies did not find evidence of change in mtDNA copy number. In conclusion, the findings imply that mitochondrial adaptions, as a response to aerobic exercise, can occur without a change in mtDNA copy number.
Exploring the determinants of NEET youth in Jambi Province: A socioeconomic perspective

This study aims to analyze: 1) the socioeconomic characteristics and NEET (Not in employment, education, or training) status of young individuals in Jambi Province; 2) the determinants influencing the NEET status of young people in Jambi Province. The data utilized in this study is derived from a survey conducted in four sample villages within Jambi Province, consisting of 200 young participants. Descriptive statistical tools, single-frequency and cross-frequency tables, and binary logit regression are employed for analysis. The findings of the study reveal that: 1) NEET youth, when compared to non-NEET youth, tend to be older, have a higher proportion of females, possess higher education levels, are more likely to be married, are predominantly non-migrants, and have fewer siblings or step-siblings; 2) The parents of NEET youth, in comparison to non-NEET youth, generally have higher incomes and predominantly belong to non-Malay ethnicities in Jambi. 3) Factors significantly impacting the categorization of youth as NEET include gender, education, marital status, and parental income.