Miracle-dz/UniFAR-FTUs huggingface dataset:
Antecedents influencing SNS addiction and exhaustion (fatigue syndrome): focusing on six countries

ABSTRACT This study empirically analyzed how ‘SNS-perceived playfulness, tendency of self-display, and information sharing’ affect ‘SNS addiction and exhaustion’ based on four major base theories, i.e. uses and gratifications, motivation, self-control, and motivational balancing theories. Furthermore, this study comparatively analyzed the influences of nationality on SNS addiction and exhaustion (fatigue syndrome) in six countries. The sample comprised a total of 1,198 people from six countries. Three statistics programmes (SmartPLS, GSCA Pro, and JASP) were used to approve the research hypotheses. (1) The SNS tendency of self-display and SNS information sharing had a positive effect on SNS addiction. (2) SNS perceived playfulness had a negative effect on SNS exhaustion, and SNS tendency of self-display had a positive effect. (3) SNS addiction had a positive effect on SNS exhaustion. (4) In the comparative country analysis, SNS tendency of self-display was the most influential factor on SNS addiction and exhaustion. SNS are highly convenient and practical, provide users with sensational entertainment, and enable exhibitionism (e.g. self-display, information sharing), thus potentially leading to SNS addiction, which in turn results in SNS exhaustion. Therefore, it identifies the appropriate antecedents, identifies country-specific differences, and proposes practical guidelines for users to prevent SNS addiction and exhaustion.
Diagnostic Accuracy of Elastography and Liver Disease: A Meta-Analysis

Background Ultrasound-based transient elastography (TE) is a non-invasive alternative to liver biopsy for the staging of hepatic fibrosis due to various chronic liver diseases. This meta-analysis aims to assess the diagnostic accuracy of TE for detecting liver cirrhosis (F4) and severe fibrosis (F3) in patients with chronic liver diseases, in comparison to the gold standard liver biopsy. Methods A systematic search was performed using PubMed search engine following Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines from inception to May 2021. The meta-analysis studies evaluating the diagnostic accuracy of TE for severe fibrosis and cirrhosis were identified. We conducted a meta-meta-analysis to generate pooled estimates of the sensitivity, specificity, and diagnostic odds ratios (ORs) for F3 and F4 fibrosis stage. Results We included five studies with a total of 124 sub-studies and 20,341 patients in our analysis. Three studies have reported the diagnostic accuracy of TE in detecting F3/severe fibrosis stage and found 81.9% pooled sensitivity (95% confidence interval (CI): 79.9-83.7%; P < 0.001) (I2 = 0%), 84.7% pooled specificity (95% CI: 81.3-87.6%) (I2 = 81%; P = 0.02). All five studies reported the diagnostic accuracy of TE in detecting F4/liver cirrhosis stage. We found 84.8% pooled sensitivity (95% CI: 81.4-87.7%) (I2 = 86.4%; P < 0.001), 87.5% pooled specificity (95% CI: 85.4-89.3%) (I2 = 90%; P < 0.001) and pooled diagnostic OR (41.8; 95% CI: 3.9 - 56.5) (I2 = 87%; P < 0.001). Conclusions Ultrasound-based TE has excellent diagnostic accuracy for identifying cirrhosis and liver fibrosis stages 3. Future studies should focus on estimating the diagnostic accuracy of other fibrosis stages in chronic liver disease patients. This will eventually decrease the risk associated with invasive liver biopsy.
A handy-assay procedure to measure simultaneously the polyphenol content and the antioxidant capacity in teas using the Folin Ciocalteu reagent

Cícera Pimenta Marcelino cicera.pimenta@gmail.com Faculdade de Medicina do ABC, Santo André, São Paulo, Brasil. Lucas Belini Oliveira lucasbelini@outlook.com Faculdade de Medicina do ABC, Santo André, São Paulo, Brasil. Waila Evelyn Lima Santana waila.evelyn@gmail.com https://orcid.org/0000-0002-4175-9297 Faculdade de Medicina do ABC, Santo André, São Paulo, Brasil. Horacio Dorigan Moya horacio.moya@fmabc.br http://orcid.org/0000-0003-0888-291X Faculdade de Medicina do ABC, Santo André, São Paulo, Brasil. Folin Ciocalteu reagent (FCR) is commonly used for the quantification of total polyphenol content (TPC) in plants and theirs derived materials. Tea is one of the most consumed beverages in the world and widely used in developing countries in folk medicine. Tea contains several compounds (especially polyphenols) which are believed to have antioxidant capacity. In the present study, a handy-assay procedure to measure simultaneously the TPC and the antioxidant capacity in teas using the FCR was developed. A spectrophotometric procedure using the FCR was undertaken to evaluate simultaneously the TPC and the antioxidant capacity, expressed in Trolox equivalents antioxidant capacity (TEAC), of 32 samples of 7 different types of teas. For comparison purposes, the antioxidant activity of the same samples was determined using the CUPRAC (cupric reducing antioxidant capacity) reagent. Finally, the antioxidant capacity in a cup of tea (200 mL) obtained with the FCR and expressed in ascorbic acid equivalents (AAEC) was performed. The TEAC values obtained with FCR presented a good positive correlation with the CUPRAC method (r = 0.853), suggesting that both reagents can be used to quantify the antioxidant capacity. The TEAC and CUPRAC values also showed good agreement with the TPC (r = 0.969 and r = 0.809, respectively) indicating that the antioxidant capacity should be due to the presence of polyphenols. The results obtained and the calculation strategy used may be an easier way to present the antioxidant capacity values to the final consumer who is most commonly unfamiliar with this important concept.
Comprehensive Analysis of Set-Up Gain of 6-Dimensional Cone-Beam CT Correction Method in Radiotherapy for Head and Neck and Brain Tumors

This study quantitatively analyzed the gain of the six-dimensional (6D) cone-beam CT (CBCT) correction method compared with the conventional set-up method in 60 patients who underwent radiation treatment of head and neck and brain tumors. The correction gain of CBCT was calculated for the translational and rotational motion components separately and in combination to evaluate the individual and overall effects of these motion components. Using a statistical simulation mimicking the actual set-up correction process, the effective gain of periodic CBCT correction during the entire treatment fraction was analyzed by target size and CBCT correction period under two different correction scenarios: translation alone and full 6D corrections. From the analyses performed in this study, the gain of CBCT correction was quantitatively determined for each situation, and the appropriate CBCT correction strategy was suggested based on treatment purpose and target size.
The Expansion Proper Motions of the Planetary Nebula NGC 6302 from HST imaging

Planetary nebulae expand on time scales of 10^3-10^4 yr. For nearby objects, their expansion can be detected within years to decades. The pattern of expansion probes the internal velocity field and provides clues to the nebula ejection mechanism. In the case of non-symmetric nebulae, and bipolar nebulae in particular, it can also provide information on the development of the morphology. We have measured the expansion proper motions in NGC 6302 from two epochs of HST imaging, separated by 9.43 years. This is used to determine the expansion age and the structure of the velocity field. We use HST images in the [N II] 6583{\AA} filter from HST WF/PC2 and WFC3. The proper motions were obtained for a set of 200 individual tiles within 90" of the central star. The velocity field shows a characteristic linear increase of velocity with radial distance (a so-called Hubble flow). It agrees well with a previous determination by Meaburn et al. (2008), made in a lobe further from the star, which was based on a much longer time span. The pattern of proper motion vectors is mostly radial and the origin is close to the position of the central star directly detected by Szyszka et al. (2009). The results show that the lobes of NGC 6302 were ejected during a brief event 2250 \pm 35yr ago. In the inner regions there is evidence for a subsequent acceleration of the gas by an additional 9.2 km/s, possibly related to the onset of ionization. The dense and massive molecular torus was ejected over 5000yr, ending about 2900yr ago. The lobes were ejected after a short interlude (the 'jet lag') of \sim 600 yr during a brief event. The torus and lobes orig- inate from separate mass-loss events with different physical processes. The delay between the cessation of equatorial mass loss and the ejection of the lobes provides an important constraint for explaining the final mass-loss stages of the progenitor stellar system.
Feature selection in high‐dimensional microarray cancer datasets using an improved equilibrium optimization approach

Optimal feature selection of a high‐dimensional micro‐array datasets has gained a significant importance in medical applications for early detection and prevention of disease. Traditional Optimal feature selection percolates through a population‐based meta‐heuristic optimization technique, a Machine Learning classifier and traditional wrapper method for transforming the original feature set into a better feature set. These techniques require a number of iterations for the convergence of random solutions to the global optimum with high‐dimensionality issues such as over‐fitting, memory constraints, computational costs, and low accuracy. In this article, an efficient equilibrium optimization technique is proposed for an optimized feature selection that increases the diversity of the population in the search space through Random Opposition based learning and classify the best features using a 10‐fold cross‐validation‐based wrapper method. The proposed method is tested with six standard micro‐array datasets and compared with the conventional algorithms such as Marine Predators Algorithm, Harris Hawks Optimization, Whale Optimization Algorithm, and conventional Equilibrium Optimization. From the statistical results using the standard metrics, it is interpreted that the proposed method converges to the global minimum in a few iterations through optimized feature selection, fitness value and higher classification accuracy. This proves its efficacy in exploring and finding a better solution as compared to the counterpart algorithms. In addition to complexity analysis, these results indicate a global optimum solution, an effective representation of least amount of data‐high dimensionality reduction and an avoidance of over‐fitting problems. The source code is available at https://github.com/balasv/ROBL‐EOA/blob/main/ROBL_EOA. ipynb
Evaluation of Gait Smoothness in Patients with Stroke Undergoing Rehabilitation: Comparison between Two Metrics

The use of quantitative methods to analyze the loss in gait smoothness, an increase in movement intermittency which is a distinguishing hallmark of motor deficits in stroke patients, has gained considerable attention in recent years. In the literature, the spectral arc length (SPARC), as well as metrics based on the measurement of the jerk, such as the log dimensionless jerk (LDLJ), are currently employed to assess smoothness. However, the optimal measure for evaluating the smoothness of walking in stroke patients remains unknown. Here, we investigated the smoothness of the body’s center of mass (BCoM) trajectory during gait, using an optoelectronic system, in twenty-two subacute and eight chronic patients before and after a two-month rehabilitation program. The two measures were evaluated for their discriminant validity (ability to differentiate the smoothness of the BCoM trajectory calculated on the cycle of the affected and unaffected limb, and between subacute and chronic patients), validity (correlation with clinical scales), and responsiveness to the intervention. According to our findings, the LDLJ outperformed the SPARC in terms of the examined qualities. Based on data gathered using an optoelectronic system, we recommend using the LDLJ rather than the SPARC to investigate the gait smoothness of stroke patients.
Enlargement of the Nerve Fibers of Silenced Lumbosacral Motoneurons in Cats

Whether neuromuscular activity influences the size of motor nerves is controversial. All neuromuscular activity in cat hindlimbs was eliminated by spinal cord isolation (SCI), namely, spinal cord transection above and below the medial gastrocnemius (MG) and soleus (SOL) motoneuron pools and L5-S3 dorsal root transection. MG, SOL and sural (SUR) nerves were removed for size measurements, eight months after SCI surgery and from age-matched control cats. Nerve fiber number, the linear relationship between axon size and myelin thickness, and the bimodal distributions of nerve fiber area and diameter were maintained in all three nerves after SCI. The distributions of myelinated sensory fibers were unchanged in SUR nerves in contrast to the myelinated motor fibers in the MG and SOL nerves that were significantly larger. These findings provide evidence that all lumbar motoneurons survive SCI and that their nerve fibers enlarge. Thus, motor nerve fiber size in addition to the properties of the motoneurons and their muscle fibers is dynamic, responding to neuromuscular activity.
Analysis of Sub-threshold Short Gamma-Ray Bursts in Fermi GBM Data

The Fermi Gamma-ray Burst Monitor (GBM) is currently the most prolific detector of gamma-ray bursts (GRBs). Recently the detection rate of short GRBs (SGRBs) has been dramatically increased through the use of ground-based searches that analyze GBM continuous time-tagged event (CTTE) data. Here, we examine the efficiency of a method developed to search CTTE data for sub-threshold transient events in temporal coincidence with LIGO/Virgo compact binary coalescence triggers. This targeted search operates by coherently combining data from all 14 GBM detectors by taking into account the complex spatial and energy dependent response of each detector. We use the method to examine a sample of SGRBs that were independently detected by the Burst Alert Telescope on board the Neil Gehrels Swift Observatory, but which were too intrinsically weak or viewed with unfavorable instrument geometry to initiate an onboard trigger of GBM. We find that the search can successfully recover a majority of the BAT detected sample in the CTTE data. We show that the targeted search of CTTE data will be crucial in increasing the GBM sensitivity, and hence the gamma-ray horizon, to weak events such as GRB 170817A. We also examine the properties of the GBM signal possibly associated with the LIGO detection of GW150914 and show that it is consistent with the observed properties of other sub-threshold SGRBs in our sample. We find that the targeted search is capable of recovering true astrophysical signals as weak as the signal associated with GW150914 in the untriggered data.
Generative Transfer Optimization for Aerodynamic Design

Transfer optimization, one type of optimization methods, which leverages knowledge of the completed tasks to accelerate the design progress of a new task, has been in widespread use in machine learning community. However, when applying transfer optimization to accelerate the progress of aerodynamic shape optimization (ASO), two challenges are encountered in sequence, that is, (1) how to build a shared design space among the related aerodynamic design tasks, and (2) how to exchange information between tasks most efficiently. To address the first challenge, a datadriven generative model is used to learn airfoil representations from the existing database, with the aim of synthesizing various airfoil shapes in a shared design space. To address the second challenge, both singleand multifidelity Gaussian processes (GPs) are employed to carry out optimization. On one hand, the multifidelity GP is used to leverage knowledge from the completed tasks. On the other hand, mutual learning is established between singleand multifidelity GP models by exchanging information between them in each optimization cycle. With the above, a generative transfer optimization (GTO) framework is proposed to shorten the design cycle of aerodynamic design. Through airfoil optimizations at different working conditions, the effectiveness of the proposed GTO framework is demonstrated.
Modular embeddings of Teichmüller curves

Fuchsian groups with a modular embedding have the richest arithmetic properties among non-arithmetic Fuchsian groups. But they are very rare, all known examples being related either to triangle groups or to Teichmüller curves. In Part I of this paper we study the arithmetic properties of the modular embedding and develop from scratch a theory of twisted modular forms for Fuchsian groups with a modular embedding, proving dimension formulas, coefficient growth estimates and differential equations. In Part II we provide a modular proof for an Apéry-like integrality statement for solutions of Picard–Fuchs equations. We illustrate the theory on a worked example, giving explicit Fourier expansions of twisted modular forms and the equation of a Teichmüller curve in a Hilbert modular surface. In Part III we show that genus two Teichmüller curves are cut out in Hilbert modular surfaces by a product of theta derivatives. We rederive most of the known properties of those Teichmüller curves from this viewpoint, without using the theory of flat surfaces. As a consequence we give the modular embeddings for all genus two Teichmüller curves and prove that the Fourier developments of their twisted modular forms are algebraic up to one transcendental scaling constant. Moreover, we prove that Bainbridge’s compactification of Hilbert modular surfaces is toroidal. The strategy to compactify can be expressed using continued fractions and resembles Hirzebruch’s in form, but every detail is different.
Upregulation of Succinate Dehydrogenase (SDHA) Contributes to Enhanced Bioenergetics of Ovarian Cancer Cells and Higher Sensitivity to Anti-Metabolic Agent Shikonin

Simple Summary In recent years, targeting tumor specific metabolism has gained an interest as a promising therapeutic strategy. We discovered that the overexpression of mitochondrial enzyme succinate dehydrogenase (SDHA) is highly prevalent in ovarian carcinoma patients and contributes to elevated mitochondrial metabolism in ovarian tumor models. The SDHA overexpressing tumor cells are highly metabolically active, relying on both glycolysis and oxidative phosphorylation in mitochondria to meet their energy requirements. Further, we found that those cells are particularly vulnerable to deprivation of essential nutrients such as glucose and glutamine, which led to a substantial reduction of ATP yield. Lastly, we identified an anti-metabolic compound shikonin, which demonstrated a potent anti-tumor efficacy against SDHA overexpressing ovarian cancer cells. Overall, we strive to advance scientific knowledge by uncovering the previously unappreciated role of SDHA in reprogramming of ovarian cancer metabolism, which holds untapped opportunities for therapeutic intervention. Abstract We discovered that the overexpression of mitochondrial enzyme succinate dehydrogenase (SDHA) is particularly prevalent in ovarian carcinoma and promotes highly metabolically active phenotype. Succinate dehydrogenase deficiency has been previously studied in some rare disorders. However, the role of SDHA upregulation and its impact on ovarian cancer metabolism has never been investigated, emphasizing the need for further research. We investigated the functional consequences of SDHA overexpression in ovarian cancer. Using proteomics approaches and biological assays, we interrogated protein content of metabolic pathways, cell proliferation, anchorage-independent growth, mitochondrial respiration, glycolytic function, and ATP production rates in those cells. Lastly, we performed a drug screening to identify agents specifically targeting the SDHA overexpressing tumor cells. We showed that SDHA overexpressing cells are characterized by enhanced energy metabolism, relying on both glycolysis and oxidative phosphorylation to meet their energy needs. In addition, SDHA-high phenotype was associated with cell vulnerability to glucose and glutamine deprivation, which led to a substantial reduction of ATP yield. We also identified an anti-metabolic compound shikonin with a potent efficacy against SDHA overexpressing ovarian cancer cells. Our data underline the unappreciated role of SDHA in reprogramming of ovarian cancer metabolism, which represents a new opportunity for therapeutic intervention.
Connection 100—An Auto-Ethnography of My (Mystical) Connection Experiences

This paper provides an autoethnographic accounting and analysis of my own mystical experiences, called connection experiences in this paper. This account, which is structured around a description of my early experiences, attempts to weave together psychological, sociological, historical, and methodological themes into a coherent contribution that advances our understanding of connection experience. The paper includes an explication of the four stages of the research project that developed as a consequence of these experiences as well as an examination of the processes, tools (i.e., MediWiki), and emotional, psychological, professional, and scholarly challenges of collecting and analyzing the autoethnographic data of mystical experiences. The denouement of the paper is the presentation of a conceptual schema aimed at overcoming nomenclature confusion and providing a basis for description, analysis, and discussion of connection and connection experiences. The utility of the schema is demonstrated when it is used to provide a clear overview of my own connection experiences, and the connection experiences of others. In order to facilitate critical discussion of the conceptual framework, a glossary of terms developed and presented in this paper is provided at the end.
Horus: An Effective and Reliable Framework for Code-Reuse Exploits Detection in Data Stream

Recent years have witnessed a rapid growth of code-reuse attacks in advance persistent threats and cyberspace crimes. Carefully crafted code-reuse exploits circumvent modern protection mechanisms and hijack the execution flow of a program to perform expected functionalities by chaining together existing codes. The sophistication and intricacy of code-reuse exploits hinder the scrutinization and dissection of them. Although the previous literature has introduced some feasible approaches, effectiveness and reliability in practical applications remain severe challenges. To address this issue, we propose Horus, a data-driven framework for effective and reliable detection on code-reuse exploits. In order to raise the effectiveness against underlying noises, we comprehensively leverage the strengths of time-series and frequency-domain analysis, and propose a learning-based detector that synthesizes the contemporary twofold features. Then we employ a lightweight interpreter to speculatively and tentatively translate the suspicious bytes to open the black box and enhance the reliability and interpretability. Additionally, a functionality-preserving data augmentation is adopted to increase the diversity of limited training data and raise the generality for real-world deployment. Comparative experiments and ablation studies are conducted on a dataset composed of real-world instances to verify and prove the prevalence of Horus. The experimental results illustrate that Horus outperforms existing methods on the identification of code-reuse exploits from data stream with an acceptable overhead. Horus does not rely on any dynamic executions and can be easily integrated into existing defense systems. Moreover, Horus is able to provide tentative interpretations about attack semantics irrespective of target program, which further improve system’s effectiveness and reliability.