Miracle-dz/UniFAR-FTUs huggingface dataset:
CXCL17 binds efficaciously to glycosaminoglycans with the potential to modulate chemokine signaling

CXCL17 is a mucosally secreted protein, and the most recently identified human chemokine, an assignment based on protein fold prediction and chemotactic activity for leukocytes. However, these credentials have been the subject of much recent discussion and no experimental evidence has been presented regarding the definitive structure of CXCL17. In this study, we evaluated the structural and chemoattractant credentials of CXCL17 to better characterise this molecule, and gain deeper insights into its functional role as a glycosaminoglycan (GAG) binding protein. In the absence of structural information, in silico modelling techniques assessed the likelihood of CXCL17 adopting a chemokine-fold. Recombinant CXCL17 was synthesized in mammalian and prokaryotic systems. Modified Boyden chamber and real-time chemotaxis assays assessed the ability of CXCL17 to promote chemotaxis of murine splenocytes, human neutrophils and CXCR1-transfectants. The efficacy of CXCL17 binding to GAGs was quantified with solid-phase assays and bio-layer interferometry techniques. All modelling efforts failed to support classification of CXCL17 as a chemokine based on its predicted conformation. Recombinant CXCL17 was observed to dimerize as a function of concentration, a characteristic of several chemokines. Contrary to a previous report, CXCL17 was not chemotactic for murine splenocytes, although it was a low-potency chemoattractant for human neutrophils at micromolar concentrations, several orders of magnitude higher than those required for CXCL8. As anticipated due to its highly basic nature, CXCL17 bound to GAGs robustly, with key C-terminal motifs implicated in this process. While inactive via CXCR1, CXCL17 was found to inhibit CXCR1-mediated chemotaxis of transfectants to CXCL8 in a dose-dependent manner. In summary, despite finding little evidence for chemokine-like structure and function, CXCL17 readily bound GAGs, and could modulate chemotactic responses to another chemokine in vitro. We postulate that such modulation is a consequence of superior GAG-binding, and that C-terminal fragments of CXCL17 may serve as prototypic inhibitors of chemokine function.
On the Classification of Rank-1 Four-dimensional N=2 Superconformal Field Theories by Seiberg-Witten Geometry

We develop a systematic approach to the classification of four dimensional N = 2 superconformal field theories (SCFTs) with a one dimensional moduli space of Coulomb vacua with planar topology, equivalently, of four dimensional N = 2 SCFTs with rank one freely generated Coulomb branch (CB) chiral rings. The geometric structure of the Coulomb branch encodes ultraviolet conformal field theory data: the relevant mass deformations of the UV N = 2 SCFTs are mapped to the complex deformations of singular Coulomb branch geometries. Our results go beyond the standard lore of the A-D-E classification, and a richer pattern of flavor symmetries is revealed corresponding to different deformations. We have constructed explicit Seiberg-Witten (SW) curves and one-forms for each possible regular deformation of the CB geometry. Further physical consistency conditions are obtained by considering N = 2 RG flows, and certain SW geometries are ruled out by our conjecture about the absence of dangerously irrelevant operators in N = 2 field theories. Along the way, we have discovered a full list of new rank-1 N = 2 SCFTs, notably including the rank-1 N = 3 SCFTs constructed via the S-fold construction in Type IIB string theory. The structure of the Higgs branch and enhanced Coulomb branches of these N = 2 SCFTs is also examined in terms of N = 2 chiral ring relations and N = 2 S-dualities. The conformal and flavor central charges are computed by a refined version of Shapere and Tachikawa’s topological twisting argument. We also initiate a systematic study of rank-1 SCFTs with CB chiral rings satisfying non-trivial operator product expansion relations, and the SW geometry of the corresponding non-planar CBs. The main result of our study is that (rank-1) SCFTs with non-freely generated CB chiral rings when deformed by relevant deformations, always flow to theories with non-freely generated CB rings. This implies that if they exist, they must thus form a distinct subset under RG flows. We also find many interesting characteristic properties that these putative theories satisfy which may be helpful in proving or disproving their existence using other methods.
Exploiting Connections among Personality, Job Position, and Work Behavior: Evidence from Joint Bayesian Learning

Personality has been considered as a driving factor for work engagement, which significantly affects people’s role performance at work. Although existing research has provided some intuitive understanding of the connection between personality traits and employees’ work behaviors, it still lacks effective quantitative tools for modeling personality traits, job position characteristics, and employee work behaviors simultaneously. To this end, in this article, we introduce a data-driven joint Bayesian learning approach, Joint-PJB, to discover explainable joint patterns from massive personality and job-position-related behavioral data. Specifically, Joint-PJB is designed with the knowledgeable guidance of the four-quadrant behavioral model, namely, DISC (Dominance, Influence, Steadiness, Conscientiousness). Based on the real-world data collected from a high-tech company, Joint-PJB aims to highlight personality-job-behavior joint patterns from personality traits, job responsibilities, and work behaviors. The model can measure the matching degree between employees and their work behaviors given their personality and job position characteristics. We find a significant negative correlation between this matching degree and employee turnover intention. Moreover, we also showcase how the identified patterns can be utilized to support real-world talent management decisions. Both case studies and quantitative experiments verify the effectiveness of Joint-PJB for understanding people’s personality traits in different job contexts and their impact on work behaviors.
Pseudo-Cushing Syndrome With an Atypically High Cortisol Burden and Clinical Improvement With Adrenal Enzyme Inhibitor

Abstract Distinguishing between Cushing syndrome (CS) and pseudo Cushing syndrome (PCS), also known as physiological hypercortisolism, can be difficult. PCS is caused by nonneoplastic overactivity of the hypothalamic-pituitary-adrenal axis and may be secondary to a range of conditions, including obesity, physical stress, malnutrition, and chronic alcoholism, and typically results in a lesser degree of hypercortisolism and fewer clinical features than CS. Management of PCS includes treatment of the underlying cause and reassessment of hypercortisolemia following improvement in the underlying etiology, as this may result in normalization of cortisol levels. The role of adrenal enzyme inhibitors in lowering cortisol levels in those with PCS is poorly understood. We report a case of a man presenting with weight loss who was found to have severe hypercortisolemia and elevated adrenocorticotropin (ACTH) complicated by infection, neuropsychiatric disturbance, and hypokalemia. Despite high cortisol levels, he was phenotypically not cushingoid, and the circadian rhythm of cortisol was preserved. Extensive investigations did not demonstrate a cause of symptoms or source of ACTH. Medical management with ketoconazole improved neuropsychiatric symptoms, and weight gain with nasogastric feeds resulted in the normalization of cortisol levels and resolution of symptoms following ketoconazole cessation.
Three-dimensional MHD Simulation of Solar Wind Using a New Boundary Treatment: Comparison with In Situ Data at Earth

Three-dimensional magnetohydrodynamics (MHD) numerical simulation is an important tool in the prediction of solar wind parameters. In this study, we improve our corona interplanetary total variation diminishing MHD model by using a new boundary applicable to all phases of solar cycles. This model uses synoptic magnetogram maps from the Global Oscillation Network Group as the input data. The empirical Wang–Sheeley–Arge relation is used to assign solar wind speed at the lower boundary, while temperature is specified accordingly based on its empirical relation with the solar wind speed. Magnetic field intensity and solar wind density at the boundary are obtained from observational data in the immediate past Carrington rotations, permitting the persistence of these two parameters in a short time period. The boundary conditions depend on only five tunable parameters when simulating the solar wind for different phases of the solar cycle. We apply this model to simulate the background solar wind from 2007 to 2017 and compare the modeled results with the observational data in the OMNI database. Visual inspection shows that our model can capture the time patterns of solar wind parameters well at most times. Statistical analysis shows that the simulated solar wind parameters are all in good agreement with the observations. This study demonstrates that the improved interplanetary total variation diminishing model can be used for predicting all solar wind parameters near the Earth.
A HEWMA-CUSUM control chart for the Weibull distribution

ABSTRACT The Weibull distribution is one of the most popular distributions for lifetime modeling. However, there has not been much research on control charts for a Weibull distribution. Shewhart control is known to be inefficient to detect a small shift in the process, while exponentially weighted moving average (EWMA) and cumulative sum control chart (CUSUM) charts have the ability to detect small changes in the process. To enhance the performance of a control chart for a Weibull distribution, we introduce a new control chart based on hybrid EWMA and CUSUM statistic, called the HEWMA-CUSUM chart. The performance of the proposed chart is compared with the existing chart in terms of the average run length (ARL). The proposed chart is found to be more sensitive than the existing chart in ARL. A simulation study is provided for illustration purposes. A real data is also applied to the proposed chart for practical use.
Pan-cancer analysis reveals embryonic and hematopoietic stem cell signatures to distinguish different cancer subtypes

Purpose Stem cells-like properties in cancer cells may confer cancer development and therapy resistance. With the advancement of multi-omics technology, the multi-omics-based exploration of cancer stemness has attracted certain interests. However, subtyping of cancer based on the combination of different types of stem cell signatures remains scarce. Methods In this study, 10,323 cancer specimens from 33 TCGA cancer types were clustered based on the enrichment scores of six stemness gene sets, representing two types of stem cell backgrounds: embryonic stem cells (ESCs) and hematopoietic stem cells (HSCs). Results We identified four subtypes of pan-cancer, termed StC1, StC2, StC3 and StC4, which displayed distinct molecular and clinical features, including stemness, genome integrity, intratumor heterogeneity, methylation levels, tumor microenvironment, tumor progression, chemotherapy and immunotherapy responses, and survival prognosis. This subtyping method for pan-cancer is reproducible at the protein level. Conclusion Our findings indicate that the ESC signature is an adverse prognostic factor, while the HSC signature and ratio of HSC/ESC signatures are positive prognostic factors in cancer. The ESC and HSC signatures-based subtyping of cancer may provide insights into cancer biology and clinical implications of cancer.
Organic Matter in the Asteroid Ryugu: What We Know So Far

Simple Summary Organic matter is an integral part of all living things on our planet, but abiotic (not relating to life) organic matter can be found throughout the Solar System within meteorites, asteroids, comets and even on the surfaces of other planets such as Mars. Therefore, one of the most profound questions for humanity concerns how life originated on Earth. In order to answer this, we must first understand how organic matter is formed and altered throughout our solar system and the universe in general. To better understand the origin and evolution of organic matter, the Japan Aerospace Exploration Agency (JAXA) sent the Hayabusa2 spacecraft to collect and return material from the near-earth asteroid Ryugu. Here, a review concerning the organic material within the returned Ryugu samples will be presented. The review will inform the reader about the Hayabusa2 mission, the nature of the organic matter analyzed and the various interpretations concerning the analytical findings. The review puts the findings and individual interpretations in the context of the current theories surrounding the formation and evolution of Ryugu and highlights the issues that remain to be solved. Abstract The Hayabusa2 mission was tasked with returning samples from the C-complex asteroid Ryugu (1999 JU3), in order to shed light on the formation, evolution and composition of such asteroids. One of the main science objectives was to understand whether such bodies could have supplied the organic matter required for the origin of life on Earth. Here, a review of the studies concerning the organic matter within the Ryugu samples is presented. This review will inform the reader about the Hayabusa2 mission, the nature of the organic matter analyzed and the various interpretations concerning the analytical findings including those concerning the origin and evolution of organic matter from Ryugu. Finally, the review puts the findings and individual interpretations in the context of the current theories surrounding the formation and evolution of Ryugu. Overall, the summary provided here will help to inform those operating in a wide range of interdisciplinary fields, including planetary science, astrobiology, the origin of life and astronomy, about the most recent developments concerning the organic matter in the Ryugu return samples and their relevance to understanding our solar system and beyond. The review also outlines the issues that still remain to be solved and highlights potential areas for future work.
Propolis Controlled Delivery Systems for Oral Therapeutics in Dental Medicine: A Systematic Review

This systematic review synthesizes the existing evidence in the literature regarding the association of propolis with controlled delivery systems (DDSs) and its potential therapeutic action in dental medicine. Two independent reviewers performed a literature search up to 1 June 2023 in five databases: PubMed/Medline, Web of Science, Cochrane Library, Scopus, and Embase, to identify the eligible studies. Clinical, in situ, and in vitro studies that investigated the incorporation of propolis as the main agent in DDSs for dental medicine were included in this study. Review articles, clinical cases, theses, dissertations, conference abstracts, and studies that had no application in dentistry were excluded. A total of 2019 records were initially identified. After carefully examining 21 full-text articles, 12 in vitro studies, 4 clinical, 1 animal model, and 3 in vivo and in vitro studies were included (n = 21). Relevant data were extracted from the included studies and analyzed qualitatively. The use of propolis has been reported in cariology, endodontics, periodontics, stomatology, and dental implants. Propolis has shown non-cytotoxic, osteoinductive, antimicrobial, and anti-inflammatory properties. Moreover, propolis can be released from DDS for prolonged periods, presenting biocompatibility, safety, and potential advantage for applications in dental medicine.
Determinants of Intention to Use Fintechs Services by Accounting Students: A Mixed Methods Approach

Fintechs are startups that operate in the financial sector and have gradually been receiving space in the market. However, it is still not clear which elements lead individuals, especially those involved in the business field, to adopt and use these services. Thus, this study aims to analyze which elements encourage the behavioral intention to use Fintech services from the perspective of students in the business field. The theoretical basis and hypothesis development were based on the Unified Theory of Acceptance and Use of Technology (UTAUT), which contemplates the facilitating conditions, performance expectancy, effort expectancy, social influence, and the behavioral intention to use said services. The study also included the variable “security” as an antecedent. Age and gender were controlled for this study. A survey resulted in a sample of 107 students, and the data was analyzed with a mixed-method approach: partial least squares - structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). With PLS-SEM, the findings demonstrate the positive effect of performance expectancy, effort expectancy and security on the behavioral intention to use fintech services. The fsQCA showed that different causal configurations can lead students to a high adoption of services provided by these startups. This study brings up new evidence that contributes to the UTAUT theory by intertwining this discussion with the security variable perceived during technology usage. Furthermore, it expands the entire discussion to the context of accepting a contemporary technology. Regarding the students, practical evidence is gathered regarding the determinants of their intention to use financial services.
Generating Natural Language Dialogues Using Large Language Models with Adapters

Communication through natural language dialogue has enabled humans to satisfy social needs, share knowledge, collaboratively solve problems, and negotiate compromises. Unfortunately, language barriers can hinder such communication. Thus, language education grounded in dialogue is essential for those with urgent needs, e.g., refugees or immigrants, and those who desire longer-term careers in an environment with an unfamiliar language. In many cases, there is a need to learn a domain-specific subset of a language for people to communicate in a new language environment. This work presents a method of creating dialogue for language education through surrounding dialogue generation. Surrounding dialogue generation, as defined, is a complex natural language generation problem. We propose a novel deep learning architecture with adapters; it generates domain-specific conversational dialogues using an open-source pre-trained language model used in several state-of-the-art architectures, namely GPT-2. Its successors, GPT-3 and GPT-4, have shown even more remarkable results. But they are, for a third party, impossible to add adapters to. Our architecture extends a dialogue by generating preceding and following utterances. Several experiments are done to validate the benefits of the architecture as a creative tool for educators. The experiments show promising results and provide a basis for future research.
An interferometric interpretation of Marchenko redatuming including free-surface multiples

We present an interferometric interpretation of the iterative Marchenko scheme including both free-surface multiples and internal multiples. Cross-correlations are used to illustrate the combination of causal and acausal events that are essential for the process of multiple removal. The first 4 steps in the scheme are discussed in detail, where the effect of different contributions on the result is displayed and the formation of individual events is illustrated. We highlight the events that are necessary to understand the process that removes both internal multiples and free-surface multiples from the data. We demonstrate that additional contributions are needed to correct for the presence of free-surface multiples.
Correlation between Perceptions of School Support and The Mastery Of Information Technology to Teachers' Self-Efficacy

Curriculum 2013 requires teachers to master information technology in order to teach in a better way. In fact, many elementary school teachers have not been able to use computers. Lack of school support and information technology skills may be associated with low self-efficacy. The purpose of this study is to determine whether teachers’ self-efficacy can be predicted by school support and mastery of information technology. Subjects of this research were 225 teachers from 19 elementary schools in Daerah Istimewa Yogyakarta province, which have become the pilot project of Curriculum 2013. Instruments used in this study were Self Efficacy Scale, School Support Scale, and Information Technology Test. The data were analyzed using multiple linear regression analysis. The result of this study found that school support and mastery of information mastery simultaneously positively correlated to teachers’ self-efficacy with a correlation value of 139,616 significance level p<0,01. The effective contribution of school support and mastery of information mastery together positively correlated to teachers’ self-efficacy is 55,7%.
A COMPARISON OF MULTIPLE‐CHOICE AND CONSTRUCTED FIGURAL RESPONSE ITEMS

In contrast to multiple-choice test questions, figural response items call for constructed responses and rely upon figural material, such as illustrations and graphs, as the response medium. Figural response questions in various science domains were created and administered to a sample of 4th-, 8th-, and 12th-grade students. Item and test statistics from parallel sets of figural response and multiple-choice questions were compared. Figural response items were generally more difficult, especially for questions that were difficult (p<.5) in their constructed-response forms. Figural response questions were also slightly more discriminating and reliable than their multiple-choice counterparts, but had higher omit rates. The paper addresses the relevance of guessing to figural response items and the diagnostic value of the item type. Plans for future research on figural response items are discussed.
What is R2 all about

Which substantive meaning we can draw from the R2 statistic? The coefficient of determination is defined as the sum of squares due to the regression divided by the sum of total squares. Usually, R2 is interpreted as representing the percentage of variation in the dependent variable explained by variation in the independent variables. This definition is found by both econometrics and statistics handbooks and is widely accepted among quantitative scholars. However, this view is challenged by one of the most distinguished political science methodologists. Gary King argues that the R2 is highly misused as a measure of the influence of X on Y. This paper analyzes the R2 statistic using a non-technical approach. Our purpose is to provide an intuitive understanding of the coefficient of determination and its major shortcomings
I want it all and I want it now: Irrational beliefs and dark tetrad traits in men

The Dark Tetrad (DT) - an umbrella term for four socially aversive traits (Machiavellianism, narcissism, psychopathy, and sadism) gained a lot of research interest. However, little is known about how these traits are related to cognitive constructs such as hostile interpretation bias (HIB) and low frustration tolerance (LFT). In an attempt to explain what could contribute to understanding the development of DT, the present study aimed to combine two different theoretical perspectives: a theory underlying CBT and a trait-based model of personality. The study used a community sample of men (N = 612) to test whether LFT (a) predicts HIB and the expression of DT traits and (b) has an indirect, mediated by HIB, effect on DT traits. Results showed a significant direct effect of LFT on all four DT traits. Also, the indirect effect was significant in all four tested models. It might be that, by seeking schema confirmation, individuals gradually develop a stable pattern of behavioral, emotional, motivational reactions, labeled as (DT) traits. HIB seems to be an integral part of the assimilation process, by mediating the relationship between LFT and all four DT traits.