Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Smart Content in Adaptive Learning Systems: Potential, Challenges, and Solutions

This paper proposes a novel adaptive learning system – Structured Adaptive Individualized Learning System (SAILS), which incorporates several educational theories to help engage, motivate, and cognitively stimulate students throughout an introductory computer science course. SAILS will provide remedial material as well as interventions, specifically geared towards the specific user, and periodically assess students to measure the knowledge gained. Incorporated in SAILS is a novel concept called, ‘Smart Content’. Based on the student’s profile and the student’s proven successful grasp or lack of understanding of the topic presented, the content gets “smarter” by updating particular stored features associated with the content. The student’s profile will be updated and captured as a point of reference for other similar students to determine the content features that should be updated. SAILS will provide content to similar students by analyzing the content features and past student’s profile. By comparing current profiles and content features, the system would adjust the content the student receives based on its ability to detect when a student has truly mastered a specific topic or when additional practice is required in areas where the student is weak.
Future Implications

can be found at: Journal of Aging and Health Additional services and information for http://jah.sagepub. com/cgi/alerts Email Alerts: http://jah.sagepub. com/subscriptions Subscriptions: http://www.sagepub. com/journalsReprints.nav Reprints: http://www.sagepub. com/journalsPermissions.nav Permissions: http://jah.sagepub. com/cgi/content/refs/19/3/359 SAGE Journals Online and HighWire Press platforms): (this article cites 30 articles hosted on the Citations
LOOT: NOVEL END-TO-END TRAINABLE CONVOLUTIONAL NEURAL NETWORK FOR PARTICLE TRACK RECONSTRUCTION

We introduce a radically new approach to the particle track reconstruction problem for tracking detectors of HEP experiments. We developed the end-to-end trainable YOLO-like convolutional neural network named Look Once On Tracks (LOOT) which can process the whole event representing it as an image, but instead of three RGB channels, we use, as channels in-depth, discretized contents of sequential detector coordinate stations. The LOOT neural net avoids all problems of the existing sequential tracking algorithms because it does computations in one shot. The first promising results of the algorithm's application to the data from the Monte-Carlo simulations are presented and discussed.
QUANTITATIVE FINANCE RESEARCH CENTRE

The aim of this paper is to document some empirical facts related to log-returns of diversified world stock indices when these are denominated in different currencies. Motivated by earlier results, we have obtained the estimated distribution of log-returns for a range of world stock indices over long observation periods. We expand previous studies by applying the maximum likelihood ratio test to the large class of generalized hyperbolic distributions, and investigate the log-returns of a variety of diversified world stock indices in different currency denominations. This identifies the Student-t distribution with about four degrees of freedom as the typical estimated log-return distribution of such indices. Owing to the observed high levels of significance, this result can be interpreted as a stylized empirical fact. 1991 Mathematics Subject Classification: primary 90A12; secondary 60G30, 62P20. JEL Classification: G10, G13
OTT_A_212088 6013..6022

Jingguo Li Zhengyi Yang Biguang Tuo 1Department of Gastroenterology, Affiliated Hospital, Zunyi Medical University, Zunyi, People’s Republic of China; 2Department of Gastroenterology, Bijie First People’s Hospital, Bijie, Guizhou Province, People’s Republic of China Abstract: Hepatocellular carcinoma (HCC) is one of the most commonly diagnosed cancers causing death worldwide. It is difficult to detect at an early stage and most patients with advanced HCC rarely achieve satisfying therapeutic results. Accordingly, researchers have been trying to find new biomarkers for diagnosis and new methods of treatment. OCT1, a member of solute carrier super family, is highly expressed in normal liver tissues, and predominantly transports endogenous and exogenous substances, such as metabolites, drugs and toxins to hepatocytes. Studies have demonstrated that the expression of OCT1 is related to the progression and survival of HCC patients. Furthermore, sorafenib, which is regarded as the only effective molecular targeting drug for advanced HCC, is affected by OCT1 variants. In the current review, we summarized the reports about OCT1 and HCC in order to present a comprehensive overview of the relationship between OCT1 and HCC.
Trend of dividends disappearing and reappearing in Pakistani listed firms

The objective of this study was to explore the main factors of dividend policy determinants. For this purpose, a sample of 150 listed firms in PSX taken into account for the period of 2008-2018. A secondary data taken from SBP publication, Stock exchange collected for this study and variables used size, debt ratio, profitability, size, investment, Firm’s Maturity, Market Capitalization, Return on Equity (ROE), Growth in Sales and leverage was utilized using Panel regression techniques. Data of dividend shows most of the period dividend amount and dividend firms increased during the period of research 2008-18. The trend also shows that dividend pattern increase as base year data to end period study during both democratic governments. Study findings also show that three different aspects of the dividend payment propensity during 2008-2018. Results show that payment of dividend is declined mostly in the small and newly firms because they have less income generated from profit, younger firms, and firms as compared with highly investment pattern of firm, high debts, higher risk in their business and high tax rates on dividend. The Study also finds a significant and positive association with propensity to pay dividend of catering theory and support the catering theory.
Steel defect detection with high-frequency camera images FA 19-20 CS 229 Project

We focus on the problem of steel defect detection, where we are given images of a steel sheet taken by high-frequency cameras and aim to mark pixel wise defected area. We explored three deep learning methods: Xception, U-Net and Mask R-CNN to solve for the task and compared their performance and achieved highest Dice coefficient of 0.492 with U-Net.
Method and Device for Researching and Diagnostics of Respiratory Diseases

Researching of dynamics process of breathing is presented. There are three branches of the researching. It’s solid 3D model, virtual 3D model, and sensor device. Method and device for diagnostics of the respiratory diseases are designed according to the results of the modeling. The innovation of this device is that sensors are placed directly into nasal cavity without using tubes and masks. The method of diagnostic is based on the idea of studying the breathing as a dynamic process. Key-Words: study of breathing, respiratory diseases, virtual model, solid model, sensor device, nonlinear dynamics, NARMAX
Comparison of Re-sampling Methods in the Spectral Analysis of RR-interval Series Data

The heart rate variability (HRV), refers to the beat-to-beat alterations in heart rate, is analyzed using RR-interval (RRI) series derived from the ECG signal as an interval between successive QRS complexes. For deciphering the true HRV spectrum using FFT, the RRI series should be resampled. But re-sampling often induces a noticeable distortion in the HRV power spectral estimates. Thus, the re-sampling operation should be accurate enough in reproducing the finest variation in the given signal. This paper compared three most widely used interpolation techniques: linear, cubicspline, and Berger’s, as re-sampling methods, in an attempt to propose an optimal method of interpolation for HRV analysis. The linear and cubicspline methods based PSD estimates, for artificially generated non-uniformly sampled RRI series, introduce linear phase shifting, and thus lower the HRV frequencies. On the contrary, Berger’s method efficiently reproduced the inherent frequencies in the underlying signal except some amplitude distortion. Further, similar trends in PSD estimates were obtained for real RRI series as well. Thus, it was concluded that at the expense of some increase in computational complexity, the spectral distortion has been significantly reduced using the Berger’s interpolation based re-sampling method as compared to the linear and cubicspline methods.
A closer look at the performance of neural language models on reflexive anaphor licensing

An emerging line of work uses psycholinguistic methods to evaluate the syntactic generalizations acquired by neural language models (NLMs). While this approach has shown NLMs to be capable of learning a wide range of linguistic knowledge, confounds in the de-sign of previous experiments may have obscured the potential of NLMs to learn certain grammatical phenomena. Here we re-evaluate the performance of a range of NLMs on reﬂex-ive anaphor licensing. Under our paradigm, the models consistently show stronger evidence of learning than reported in previous work. Our approach demonstrates the value of well-controlled psycholinguistic methods in gaining a ﬁne-grained understanding of NLM learning potential. 1
Negative Mood Is Associated with Diet and Dietary Antioxidants in University Students During the Menstrual Cycle: A Cross-Sectional Study from Guangzhou, China

Postpubescent females may have negative mood or premenstrual syndrome during the menstrual cycle; with the emotional and physical symptoms interfering with their quality of life. Little is known about the relationship of dietary behaviors and dietary antioxidant intake with negative mood or premenstrual syndrome in university students in China; so we explored the relationship between negative mood and dietary behavior in female university students during the three menstrual cycle phases. Random sampling was used to enroll 88 individuals from a university in Guangzhou; China in the study. Data were collected using self-administered questionnaires. Descriptive statistics and multiple logistic regression analyses were performed. During the menstrual phase, tea, black coffee and carbonated beverage intake was higher in the group with a high negative affect scale score than in the low score group (p < 0.05). Likewise; during the premenstrual phase, fresh fruit (banana and red Chinese dates) intake was higher in the group with a high negative affect scale score than in the low-score group (p < 0.05). The logistic regression analysis results showed that negative mood was positively associated with tea, coffee, and carbonated beverage intake during the menstrual phase (β = 0.21, p = 0.0453, odds ratio = 1.23), and negative mood was positively associated with banana and red Chinese dates intake during the premenstrual phase (β = 0.59, p = 0.0172, odds ratio = 1.81). Our results suggest that negative mood may be associated with diet and specific food in university postpubescent females.
First-Principles Calculation of Transition Metal Hyperfine Coupling Constants with the Strongly Constrained and Appropriately Normed (SCAN) Density Functional and its Hybrid Variants

Density functional theory (DFT) is used extensively for the first-principles calculation of hyperfine coupling constants in both main-group and transition metal systems. As with many other properties, the performance of DFT for hyperfine coupling constants is of variable quality, particularly for transition metal complexes, because it strongly depends on the nature of the chemical system and the type of approximation to the exchange-correlation functional. Recently, a meta-generalized-gradient approximation (mGGA) functional was proposed that obeys all known exact constraints for such a method, known as the Strongly Constrained and Appropriately Normed (SCAN) functional. In view of its theoretically superior formulation a benchmark set of complexes is used to assess the performance of SCAN for the challenging case of transition metal hyperfine coupling constants. In addition, two global hybrid versions of the functional, SCANh and SCAN0, are described and tested. The values computed with the new functionals are compared with experiment and with those of other DFT approximations. Although the original SCAN and the SCAN-based hybrids may offer improved hyperfine coupling constants for specific systems, no uniform improvement is observed. On the contrary, there are specific cases where the new functionals fail badly due to a flawed description of the underlying electronic structure. Therefore, despite these methodological advances, systematically accurate and system-independent prediction of transition metal hyperfine coupling constants with DFT remains an unmet challenge.
Trail Making Test: normative data for the Lebanese adult population

Abstract Objective Trail Making Test (TMT) is a widespread neuropsychological test used to detect cognitive impairment in diverse neuropsychological conditions. Several studies have shown that TMT performance is influenced by different demographic factors. Thus, the present study aims to explore the effect of gender, age, and education on TMT basic and derived scores and to provide normative data for the Lebanese adult population. Method A total of 225 healthy Lebanese adults (aged between 18 and 64) were recruited. The two parts of the TMT were administered to the participants. Regression based strategy was applied to generate normative data. Results The results showed statistically significant effect of age and level of education on the TMT-A, TMT-B as well as the difference score TMT B –A. However, the ratio score was affected only by the age. Gender did not have any effect on TMT performance. An interactive calculator was created to calculate estimated Z-scores based on corresponding predictions of linear regression model. The calculator provides also percentile ranks. Conclusions The present study provides the first normative data for the TMT among the Lebanese population. Neuropsychologists in Lebanon will benefit from this outcome in order to improve the accurate detection of visual scanning/processing speed and executive function deficits in clinical settings for the adult population.
Clinical relevance of the left brachiocephalic vein anatomy for vascular access in dialysis patients

Most hemodialysis patients start renal replacement therapy with a central venous catheter (CVC). The left internal jugular vein (LIJV) is the second‐choice vein for CVC positioning, after the right IJV. However, to reach the right atrium, the CVC must pass through the left brachiocephalic vein (LBV), which also drains blood from the left arm through the subclavian vein. The purpose of this study is to describe how the anatomy of the central venous system and in particular that of the LBV affects vascular access in hemodialysis patients.
Chemical analysis of Hg0-containing Hindu religious objects

Parad items used in Hindu practices and Ayurvedic medicines contain elemental mercury (Hg0) and have traditionally been used in prayer and to treat a variety of diseases including diabetes, heart conditions, and sexual dysfunction. These items are often referred to as amalgams of silver, and take the form of shivlings, statues of gods, necklaces, and other jewelry. Fourteen parad items were purchased from online vendors in India and the United States and analyzed. All items produced copious amounts of Hg0 vapor, with Hg0 concentrations exceeding 1,000,000 ng/m3 as measured using a Mercury Instruments Mercury Tracker 3000 IP atomic absorption spectrometer. Measured concentrations were highly variable, so a simple qualitative experiment employing a UV-C light source and a thin-layer chromatography plate impregnated with a fluorescent dye that glows green when irradiated at 254 nm allowed for the indirect visualization of the Hg0 being evolved. In addition, all items were screened using a hand-held X-ray fluorescence analyzer to estimate the concentration of Hg, Sn, Pb, As, and Cd on the surface of the item. Select samples were then digested in aqua regia and analyzed for Hg content using a direct mercury analyzer. All samples were found to exceed 20% by mass Hg. The digestates were analyzed using inductively-coupled plasma–optical emission spectrometry and were determined to be between 10–55% by mass Pb and contain up to 0.3% by mass As. While Article 4 of the Minamata Convention on Mercury specifically requires parties to stop importing, exporting, and manufacturing Hg-added products, products used in traditional and religious practices are excluded.
Development and Predictors of Sarcopenic Dysphagia during Hospitalization of Older Adults

The study aimed to investigate the impact of sarcopenia and sarcopenia-related conditions on the development of swallowing disorders during hospitalization. Older adult inpatients (n = 8768) without swallowing disorders in the premorbid period were studied. Sarcopenia-related conditions were evaluated in terms of nutritional status, physical status, and ambulatory conditions as well as hand-grip strength and muscle mass assessed by calf circumference. Development of swallowing disorders was defined based on food texture at discharge from the hospital. The patients’ mean age was 76.1 ± 6.9 years. A total of 374 (4.3%) patients developed swallowing disorders during hospitalization. They were older, with poorer nutritional status, and had more decline of physical performance than those without swallowing disorders. Performance Status score (odds ratio (OR) = 1.28 (1.12–1.46) p < 0.001), ambulatory dependency (OR = 1.72 (1.09–2.71), p = 0.020), malnutrition score (OR = 0.92 (0.87–0.97), p = 0.002), insufficient nutritional intake (OR = 2.33 (1.60–3.40), p < 0.001), and length of stay (OR = 1.01 (1.00–1.01), p = 0.001) were independent contributing factors for swallowing disorder development in the multivariate analysis. The presence of possible sarcopenia was also a contributor to swallowing disorder development. In conclusion, swallowing disorders could develop in patients with possible sarcopenia and sarcopenia-related conditions during hospitalization. Clinicians should be aware of this risk and provide appropriate interventions to prevent sarcopenic dysphagia.
Pulmonary infections in patients with myelodysplastic syndromes receiving frontline azacytidine treatment

Pulmonary infections (PIs) are a major complication of patients with myelodysplastic syndromes (MDS). We retrospectively evaluated 234 MDS patients treated with azacytidine (AZA). The total number of AZA cycles was 2886 (median 8 cycles per patient). There were 111 episodes of PI (3.8% of AZA cycles) in 81 patients (34.6%). PIs were considered of fungal origin in 27 cases (24.3%), associated to bacteremia in 11 cases (9.9%), to influenza infection in two cases (1.8%) and of unknown origin in the remaining 71 cases (64.0%). Forty‐five PI episodes were documented in cycles 1 to 4 of AZA (5.1% of 875 cycles) and the remaining 66 episodes beyond the fourth cycle (3.2% of 2011 cycles) (P = .017). Overall, a fungal PI was documented in 13/875 (1.5%) cycles 1 to 4 and in 13/2011 (0.6%) cycles beyond the fourth cycle (P = .001). A baseline chronic pulmonary disease was significantly associated to a higher risk of severe PIs. In the survival analysis, cases of PI in patients who progressed to acute leukemia (PAL) were excluded, in view of the predominant influence of PAL on the outcome of the patients. A PI unrelated to PAL documented during the first 4 AZA cycles was an independent factor predicting lower survival (OR, 2.13; 95% CI, 1.37‐3.33; P = .001). In conclusion, PIs are common in MDS patients receiving AZA, in particular during the first cycles of treatment and are associated with an unfavorable outcome. The results of our study raise the issue of the need of a tailored infection prevention strategy.
Fluorimetric Detection of Single Pathogenic Bacterium in Milk and Sewage Water Using pH-Sensitive Fluorescent Carbon Dots and MALDI-TOF MS

The current study is focused on the application of water-soluble, fluorescent, and pH-sensitive carbon dots (CDs) as a nanoprobe for sensitive detection of pathogenic bacteria in milk and sewage water. The CDs were facilely synthesized through the controlled carbonization of sucrose using sulfuric acid and characterized through XRD, FTIR, TEM, UV-Vis Spectroscopy, and fluorescent analysis. The as-synthesized CDs were highly water-soluble, stable, and pH-sensitive fluorescent nanomaterials. The pH-related fluorescence study showed that the ratio of fluorescence intensity (Log[IF410/IF350]) changed linearly in the pH range between 4.9 and 6.9 in the Britton-Robison buffer. By determining the pH variation of the growth medium caused by the released acidic metabolites, the CDs-based ratiometric nanoprobe and MALDI-TOF mass spectrometry (MS) were used for the detection and identification of Escherichia coli O157:H7, respectively. The practical applicability of the pH-sensitive fluorescent CDs-based ratiometric nanoprobe was evaluated to detect Escherichia coli O157:H7 in real samples, i.e., milk and sewage water using agar count plate method with a limit of detection (LOD) up to 1 colony-forming unit per mL (CFU/mL).
Indicators to distinguish symptom accentuators from symptom producers in individuals with a diagnosed adjustment disorder: A pilot study on inconsistency subtypes using SIMS and MMPI-2-RF

In the context of legal damage evaluations, evaluees may exaggerate or simulate symptoms in an attempt to obtain greater economic compensation. To date, practitioners and researchers have focused on detecting malingering behavior as an exclusively unitary construct. However, we argue that there are two types of inconsistent behavior that speak to possible malingering—accentuating (i.e., exaggerating symptoms that are actually experienced) and simulating (i.e., fabricating symptoms entirely)—each with its own unique attributes; thus, it is necessary to distinguish between them. The aim of the present study was to identify objective indicators to differentiate symptom accentuators from symptom producers and consistent participants. We analyzed the Structured Inventory of Malingered Symptomatology scales and the Minnesota Multiphasic Personality Inventory-2 Restructured Form validity scales of 132 individuals with a diagnosed adjustment disorder with mixed anxiety and depressed mood who had undergone assessment for psychiatric/psychological damage. The results indicated that the SIMS Total Score, Neurologic Impairment and Low Intelligence scales and the MMPI-2-RF Infrequent Responses (F-r) and Response Bias (RBS) scales successfully discriminated among symptom accentuators, symptom producers, and consistent participants. Machine learning analysis was used to identify the most efficient parameter for classifying these three groups, recognizing the SIMS Total Score as the best indicator.