Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Stigmatizing Attitude towards Depression and its Treatment among Medical and Paramedical Students: An Exploratory Study

Background: The prevalence of psychiatric disorders in medical schools has been continuously increasing, escalating the use of antidepressants. Despite this, a huge treatment gap persists, especially in traditional societies like India, where stigma towards mental illnesses is highly prevalent. Prejudice persists not only in the general population but also among medical students. Research on stigmatizing attitudes among medical students towards depression and its treatment is crucial to ensure timely interventions and promote mental wellbeing. Hence this paper aims to assess stigmatizing attitude towards depression and its treatment among medical and paramedical students in a tertiary care teaching hospital. Material and Methods: Google form was created and data collection was conducted through online platforms that included 474 students. All participants were assessed for depression, anxiety and stress symptoms, antidepressants awareness, and stigmatizing attitude towards depression and antidepressants by using a 21 item Depression Anxiety Stress Scale (DASS) and 28-item self-administered Depression and antidepressants knowledge and awareness scale (DAKAS) respectively. Results: In study population the mean age was of medical students was 22.07 (SD-3.17) years and paramedical students was 25.88 (SD-5.03) respectively. 80.4 % of participants were medical students and 19.8 % of participants were paramedical students. 12.2% of the medical students and 10.2% of paramedical students reported depression. 44.4% of the student’s strongly agreed that happiness achieved through anti-depressants is fake happiness, while 51.9% strongly agreed that antidepressants are addictive. Conclusion: The findings suggest that awareness and proper knowledge about mental health are lacking among medical profession students and proper measures like medical education must be arranged to promote awareness.
TSP in a Simple Polygon

We study the Traveling Salesman Problem inside a simple polygon. In this problem, which we call tsp in a simple polygon , we wish to compute a shortest tour that visits a given set S of n sites inside a simple polygon P with m edges while staying inside the polygon. This natural problem has, to the best of our knowledge, not been studied so far from a theoretical perspective. It can be solved exactly in poly( n, m ) + 2 O ( √ n log n ) time, using an algorithm by Marx, Pilipczuk, and Pilipczuk (FOCS 2018) for subset tsp as a subroutine. We present a much simpler algorithm that solves tsp in a simple polygon directly and that has the same running time.
Categorical Data Deduplication

Data Preparation involved in Machine Learning Pipelines reduces ML user productivity and hinders progress. One of the data pre-processing steps is the identification and removal of duplicates in categorical data. Encoding Categorical duplicates as different entities poses risk to ML model accuracy. In this work, we look at statistical features of categorical data, build a dataset with duplicate and non-duplicate word pairs, and build a binary classifier to distinguish between duplicate and non-duplicate word pairs. We perform feature engineering using text comparison metrics and model selection over classic ML models such as Logistic Regression, Trees, and SVMs; and embedding-based Neural network models. Our best performing model trained on a held-out cross-validation - a Random Forest binary classifier achieves an F1 score of 0.95
Online Metric Allocation and Time-Varying Regularization

We introduce a general online allocation problem that connects several of the most fundamental problems in online optimization. Let 𝑀 be an 𝑛 -point metric space. Consider a resource that can be allocated in arbitrary fractions to the points of 𝑀 . At each time 𝑡 , a convex monotone cost function 𝑐 𝑡 : [ 0 , 1 ] → R + appears at some point 𝑟 𝑡 ∈ 𝑀 . In response, an algorithm may change the allocation of the resource, paying movement cost as determined by the metric and service cost 𝑐 𝑡 ( 𝑥 𝑟 𝑡 ) , where 𝑥 𝑟 𝑡 is the fraction of the resource at 𝑟 𝑡 at the end of time 𝑡 . For example, when the cost functions are 𝑐 𝑡 ( 𝑥 ) = 𝛼𝑥 , this is equivalent to randomized MTS, and when the cost functions are 𝑐 𝑡 ( 𝑥 ) = ∞· 𝟙 𝑥< 1 / 𝑘 , this is equivalent to fractional 𝑘 -server. Because of an inherent scale-freeness property of the problem, existing techniques for MTS and 𝑘 -server fail to achieve similar guarantees for metric allocation. To handle this, we consider a generalization of the online multiplicative update method where we decouple the rate at which a variable is updated from its value, resulting in interesting new dynamics. We use this to give an 𝑂 ( log 𝑛 ) -competitive algorithm for weighted star metrics. We then show how this corresponds to an extension of the online mirror descent framework to a setting where the regularizer is time-varying. Using this perspective, we further refine the guarantees of our algorithm. We also consider the case of non-convex cost functions. Using a simple ℓ 22 -regularizer, we give tight bounds of Θ ( 𝑛 ) on tree metrics, which imply deterministic and randomized competitive ratios of 𝑂 ( 𝑛 2 ) and 𝑂 ( 𝑛 log 𝑛 ) respectively on arbitrary metrics.
Requirement for STAT3 and its target, TFCP2L1, in self-renewal of naïve pluripotent stem cells in vivo and in vitro

We previously demonstrated gradual loss of epiblast during diapause in embryos lacking components of the LIF/IL6 receptor. Here we explore requirement for the downstream signalling transducer and activator of transcription, STAT3 and its target, TFCP2L1, in maintenance of naïve pluripotency. Unlike conventional markers, such as NANOG, which remains high in epiblast until implantation, both STAT3 and TFCP2L1 proteins decline during blastocyst expansion, but intensify in the embryonic region after induction of diapause, as observed visually and confirmed using our novel image analysis tool, consistent with our previous transcriptional expression data. Embryos lacking STAT3 or TFCP2L1, underwent catastrophic loss of most of the inner cell mass during the first few days of diapause, implicating involvement of signals in addition to LIF/IL6 for sustaining naïve pluripotency in vivo. By blocking MEK/ERK signalling from the morula stage we could derive embryonic stem cells with high efficiency from STAT3 null embryos, but not those lacking TFCP2L1, suggesting a hitherto unknown additional role for this essential STAT3 target in transition from embryo to embryonic stem cells in vitro. Summary Statement Inducing diapause in mouse embryos demonstrates that STAT3 and TFCP2L1 are essential for self-renewal of the epiblast, but only TFCP2L1 is required for derivation of embryonic stem cells.
Systematic analysis of transcriptional and epigenetic effects of genetic variation in Kupffer cells enables discrimination of cell intrinsic and environment-dependent mechanisms

Noncoding genetic variation is a major driver of phenotypic diversity but determining the underlying mechanisms and the cell types in which it acts remain challenging problems. Here, we investigate the impact of natural genetic variation provided by phenotypically diverse inbred strains of mice on gene expression and epigenetic landscapes of Kupffer cells. Analysis of gene expression in Kupffer cells and other liver cell types derived from C57BL/6J, BALB/cJ and A/J mice provided evidence for strain-specific differences in environmental factors influencing Kupffer cell phenotypes, including preferential Leptin signaling in BALB/cJ Kupffer cells. Systematic analysis of transcriptomic and epigenetic data from F1 hybrids of these mice, and transcriptomic data from strain-specific Kupffer cells engrafted into a common host enabled quantitative assessment of cis versus trans effects of genetic variation on gene expression and an estimate of cell autonomous versus non cell autonomous effects. Under homeostatic conditions, trans effects of genetic variation were dominant, with the majority of trans regulation being non cell autonomous. In contrast, strain specific responses to acutely administered LPS were primarily associated with genetic variation acting in cis to modify response elements for lineage determining and signal dependent transcription factors. Collectively, these findings reveal cell intrinsic and environmental effects of natural genetic variation on gene expression, demonstrate the use of enhancers as detectors of trans effects of genetic variation, and provide a new resource for understanding the impact of genetic variation on gene expression in Kupffer cells.
Yeast NDI1 expression prevents the unfolded protein response and reconfigures metabolism to restore neuronal function in mitochondrial complex I deficiency

Mutations in mitochondrial complex I cause mitochondrial complex I deficiency, a group of severe neurological diseases that can result in death in infancy. The mechanisms underlying complex I deficiency pathogenesis remain poorly understood, and as a result there are currently no available treatments. To better understand the causes of neuronal dysfunction in complex I deficiency, we modelled complex I deficiency in Drosophila by knocking down the mitochondrial complex I subunit ND-75 (NDUFS1) specifically in neurons. Neuronal complex I deficiency causes locomotor defects, seizures and reduced lifespan. At the cellular level, complex I deficiency leads to mitochondrial morphology defects, reduced endoplasmic reticulum-mitochondria contacts and activation of the endoplasmic reticulum unfolded protein response (UPR) in neurons. Remarkably, we find that expression of the yeast non-proton translocating NADH dehydrogenase NDI1 in neurons, which couples NADH oxidation to transfer of electrons into the respiratory chain, reinstates endoplasmic reticulum-mitochondria contacts, prevents UPR activation and rescues the behavioural and lifespan phenotypes caused by complex I deficiency. Metabolomic analysis shows that NDI1 expression also reconfigures neuronal metabolism and implicates increased GABA levels as a contributor to the neurological manifestations of complex I deficiency. Together, these data indicate that NDI1 abrogates UPR signalling and reprogrammes metabolism to alleviate neuronal dysfunction caused by neuronal complex I deficiency.
Population dynamics of immunological synapse formation induced by bispecific T cell engagers predict clinical pharmacodynamics and treatment resistance

Effector T cells form immunological synapses (IS) with recognized target cells to elicit cytolytic effects. Facilitating IS formation is the principal pharmacological action of most T cell-based cancer immunotherapies. However, the dynamics of IS formation at the cell population level, the primary driver of the pharmacodynamics of many cancer immunotherapies, remains poorly defined. With classic immunotherapy CD3/CD19 bispecific T cell engager (BiTE) as a model system, we integrate experimental and theoretical approaches to investigate the population dynamics of IS formation and their relevance to clinical pharmacodynamics and treatment resistance. Our models produce experimentally consistent predictions when defining IS formation as a series of spatiotemporally coordinated events driven by molecular and cellular interactions. The models predict tumor-killing pharmacodynamics in patients and reveal trajectories of tumor evolution across anatomical sites under BiTE immunotherapy. Our model highlight the bone marrow may serve as a sanctuary site permitting tumor evolution and antigen escape. The models also suggest the optimal dosing regimens as a function of tumor growth and patient T cell abundance that confer adequate tumor control with minimal disease evolution. This work has implications for developing more effective T cell-based cancer immunotherapies.
Birefringence-managed normal-dispersion fiber laser delivering energy-tunable chirp-free 2

22 Chirp-free solitons have been mainly achieved with anomalous-dispersion fiber lasers by the balance of dispersive and nonlinear effects, and the single-pulse energy is constrained within a relatively small range. Here, we report a class of chirp-free pulse in normal- 25 dispersion erbium-doped fiber lasers, termed birefringence-managed soliton, in which the 26 birefringence-related phase-matching effect dominates the soliton evolution. Controllable 27 harmonic mode-locking from 5-order to 85-order is obtained at the same pump level of ~10 28 mW with soliton energy fully tunable beyond ten times, which indicates a new birefringence-related soliton energy law, fundamentally differs from the conventional 30 soliton energy theorem. The unique transformation behavior between birefringence- managed solitons and dissipative solitons is directly visualized via the single-shot spectroscopy. The results demonstrate a novel approach of engineering fiber birefringence to create energy-tunable chirp-free solitons in normal-dispersion regime, and open new research directions in fields of optical solitons, ultrafast lasers and their applications.
Lexicon based Fine-tuning of Multilingual Language Models for Sentiment Analysis of Low-resource Languages

Massively multilingual language models 001 (MMLM) such as mBERT and XLM-R have 002 shown good cross-lingual transferability. 003 However, they are not specifically trained 004 to capture cross-lingual signals with respect 005 to sentiment words. In this paper, we use a 006 sentiment lexicon of a high-resource language 007 in order to generate an intermediate fine-tuning 008 task for the MMLM, when fine-tuning it 009 for a low-resource sentiment classification 010 task. We show that such a fine-tuning task 011 improves the mapping between similar 012 sentiment words in different languages and 013 improves the sentiment classification task of 014 the low-resource language. 015
Observation of the universal jump across the Berezinskii-Kosterlitz-Thouless transition in two-dimensional Bose gases

The physics in two-dimensional (2D) systems is very different from what we observe in three-dimensional (3D) systems. Thermal fluctuations in 2D systems are enhanced, and they prevent the conventional Bose-Einstein condensation (BEC) at non-zero temperatures by destroying the long-range order. However, a phase transition to a superfluid phase is still expected to occur in a 2D system along with an emergence of a quasi-long-range order, explained by the Berezinskii-Kosterlitz-Thouless (BKT) mechanism. Within the BKT mechanism, a universal jump of the superfluid density in a 2D Bosonic system was theoretically predicted by Nelson and Kosterlitz, and was first observed in 2D \textsuperscript{4}He films by Bishop and Reppy. Recent experiments in trapped ultracold 2D Bose gas systems have shown signatures of the BKT transition, and its superfluidity. However, the universal jump in the superfluid density was not observed in these systems. Here we report the first observation of the universal jump in the superfluid density using an optically trapped ultracold 2D Bose gas. The measured superfluid phase space density at the BKT transition agrees well with the predicted value within our measurement uncertainty. Additionally, we measure the phase fluctuations in our density profiles to show that the BKT transition occurs first, followed by the BEC transition.
Chapter 2 General Degree Distributions 2 . 1 Configuration model

sec:config The first appearance of the configuration model came in the construction of random regular graphs. See Bollobas (1980, 1985). Suppose that we want a graph with n vertices, each of which has degree r. If nr is even (otherwise the structure is impossible) one partitions {1, . n} × {1, . r} into rn/2 pairs (which can be done in (rn − 1)! = (rn)! /2(rn/2)! ways) to define the edges of the graph. As we will see in Section 2.3 it is often advantageous to allow loops and multiple edges and work with r-regular multigraphs G∗(n, r) which are constructed by using the procedure described below with di = r for 1 ≤ i ≤ r. If we condition on the graph being simple then we get a random choice from the set of random regular graphs G(n, r). A more important motivation for the study of thee graphs comes from the fact thati In an Erdös-Rényi random graph, vertices have degrees that have asymptotically a Poisson distribution. However, in social and communication networks, the distribution of degrees is much different from the Poisson and in many cases has a power law form, i.e., the fraction of vertices of degree k, pk ∼ Ck−β as k → ∞.
Prospective Teachers’ Financial Knowledge and Teaching Self-Efficacy

This study explored the financial knowledge and self-efficacy of prospective teachers toward teaching basic concepts in personal finance. The financial knowledge level of 99 prospective teachers was found to be that of the average U.S. consumer. Older prospective teachers (≥ 26 years) were significantly more knowledgeable about savings than younger ones (≤ 25 years). Also, prospective teachers who had never married were less knowledgeable about savings than those who were married, divorced or widowed ( x = 67.50, x = 80.77, respectively; f = 6.63, p ≤ .05). Prospective teachers were least knowledgeable about credit, yet felt most efficacious towards teaching credit; similarly, they felt least capable of teaching about mortgages, yet their knowledge scores for mortgages were among the highest.
One-dimensional collision carts computer model and its design ideas for productive experiential learning

We develop an Easy Java Simulation (EJS) model for students to experience the physics of idealized one-dimensional collision carts. The physics model is described and simulated by both continuous dynamics and discrete transition during collision. In designing the simulations, we discuss briefly three pedagogical considerations namely (1) a consistent simulation world view with a pen and paper representation, (2) a data table, scientific graphs and symbolic mathematical representations for ease of data collection and multiple representational visualizations and (3) a game for simple concept testing that can further support learning. We also suggest using a physical world setup augmented by simulation by highlighting three advantages of real collision carts equipment such as a tacit 3D experience, random errors in measurement and the conceptual significance of conservation of momentum applied to just before and after collision. General feedback from the students has been relatively positive, and we hope teachers will find the simulation useful in their own classes.
Technology Package for the Goal Question Metric Paradigm

This document offers a concise introduction to the Goal Question Metric Paradigm (GQM Paradigm), and surveys research on applying and extending the GQM Paradigm. We describe the GQM Paradigm in terms of its basic principles, techniques for structuring GQM-related documents, and methods for performing tasks of planning and implementing a measurement program based on GQM. We also survey prototype software tools that support applying the GQM Paradigm in various ways. An annotated bibliography lists sources that document experience gained while using the GQM Paradigm and offer in-depth information about the GQM Paradigm.
Respect the ORIGIN!: a best-case evaluation of connection coalescing in the wild

Connection coalescing, enabled by HTTP/2, permits a client to use an existing connection to request additional resources at the connected hostname. The potential for requests to be coalesced is hindered by the practice of domain sharding introduced by HTTP/1.1, because subresources are scattered across subdomains in an effort to improve performance with additional connections. When this happens, HTTP/2 clients invoke additional DNS queries and new connections to retrieve content that is available at the same server. ORIGIN Frame is an HTTP/2 extension that can be used by servers to inform clients about other domains that are reachable on the same connection. Despite being proposed by content delivery network (CDN) operators and standardized by the IETF in 2018, the extension has no known server implementation and is supported by only one browser. In this paper, we collect and characterize a large dataset. We use that dataset to model connection coalescing and identify a least-effort set of certificate changes that maximize opportunities for clients to coalesce. We then implemented and deployed ORIGIN Frame support at a large CDN. To evaluate and validate our modeling at scale, 5000 certificates were reissued. Passive measurements were conducted on production traffic over two weeks, during which we also actively measured on the 5000 domains.
Electronic communication during nonwork time and withdrawal behavior: An analysis of employee cognition-emotion-behavior framework from Chinese cultural context

Although a large number of literatures have explored the relationship between electronic communication during nonwork time and individual perception and behavior under the Western culture background, we still have some limitations on this topic under the cultural background of collectivism, dedication and “Guanxi” in China. Different from Western organizations, Chinese employees tend to put work first and are more inclusive of handling work tasks during nonwork time. This type of communication during nonwork time can significantly affect employees’ cognition, emotion and behavior. From the perspective of Job Demands-Resources theory, this study constructs a double-edged (U-shaped) model between electronic communication during nonwork time and employee withdrawal behavior. Sample data were collected from 516 employees with clear working time boundaries in China. The results indicate that electronic communication during nonwork time has a U-shaped effect on employee withdrawal behavior and an inverted U-shaped effect on employee’s cognition, namely job engagement. Job engagement plays a mediating role between them. Moreover, regulatory emotional self-efficacy has a moderating effect on the relationship between electronic communication during nonwork time and job engagement. These findings not only provide theoretical and practical implications for managers and employees on how to reduce withdrawal behaviors, but also advance our understanding of electronic communication during nonwork time in Chinese cultural context.
Social cognitive career theory: The experiences of Korean college student-athletes on dropping out of male team sports and creating pathways to empowerment

The South Korean elite sport system is facing a wide range of problems that account for the high dropout rate among college student-athletes. However, research on dropout rates of student-athletes is so far been limited, which amplifies the actual voices of this group, their dropout experiences, and their challenges, while they were in the career transition process. Therefore, this study used a critical phenomenological approach as a primary methodological lens to gather information on 15 formal Korean male college student-athletes on dropping out of team sports, exploring their life challenges during their career transitions out of the sport. The result showed two main thematic categories with sub-themes, which include (1) factors affecting burning out and terminating athletic careers: (a) injury and failure of rehabilitation and (b) bullying and abandonment; and (2) factors hindering post-retirement career advancement: (a) prejudice and exclusion and (b) absence of mentors and counselors. This study used Social Cognitive Career Theory to explore the participants' progression through specific interventions that engage and empower. Overall, the current study calls upon researchers, counselors, and administrators to continue exploring advocacy efforts with this population to alter policy and practice.