Miracle-dz/UniFAR-FTUs huggingface dataset:
Dietary zinc intake and sources among Koreans: findings from the Korea National Health and Nutrition Examination Survey 2016–2019

BACKGROUND/OBJECTIVES Zinc is an essential trace mineral which is important for the growth and development of the human body and immunological and neurological functions. Inadequate zinc intake may cause zinc deficiency with its adverse consequences. In this study, we aimed to estimate the dietary zinc intake levels and sources among Koreans. SUBJECTS/METHODS For this secondary analysis, we obtained data from the Korea National Health and Nutrition Examination Survey (KNHANES) 2016–2019. Individuals aged ≥ 1 yr who had completed a 24-h recall were included. The dietary zinc intake of each individual was calculated by applying data from a newly developed zinc content database to the KNHANES raw data. We also compared the extracted data with the sex-, age-specific reference values suggested in the Korean Dietary Reference Intakes 2020. The prevalence of adequate zinc intake was then evaluated by the proportion of the individuals who met the estimated average requirement (EAR). RESULTS The mean zinc intake of Koreans aged ≥ 1 yr and adults aged ≥ 19 yrs were 10.2 and 10.4 mg/day, equivalent to 147.4% and 140.8% of the EAR, respectively. Approximately 2 in 3 Koreans met the EAR for zinc, but the zinc intake differed slightly among the different age and sex groups. In children aged 1–2 yrs, 2 out of 5 exceeded the upper level of intake, and nearly half of the younger adults (19–29 yrs) and the elders (≥ 75 yrs) did not meet the EAR. The major contributing food groups were grains (38.9%), meats (20.4%), and vegetables (11.1%). The top 5 food contributors to zinc intake were rice, beef, pork, egg, and baechu kimchi, which accounted for half of the dietary intake. CONCLUSION The mean zinc intake among Koreans was above the recommended level, but 1 in 3 Koreans had inadequate zinc intake and some children were at risk of excessive zinc intake. Our study included zinc intake from diet only, thus to better understand zinc status, further research to include intake from dietary supplements is needed.
The synchronic and diachronic status of English light verbs

This article elucidates the synchronic and diachronic status of English light verbs. In doing so, it contributes to the debate on the status of light verbs cross-linguistically. Synchronically, light verbs appear to straddle the boundary between lexical and functional categories. This has led to the view that light verbs are a diachronic stage on a grammaticalisation cline from full verb to auxiliary. Another view holds that light verbs are historically a dead-end. In this article I will present synchronic and diachronic data that show that the history of English light verbs does not display signs of grammaticalisation. I will argue that English light verbs are synchronic variants of full verbs.
Implementation of a Web-Based Communication System for Primary Care Providers and Cancer Specialists

Healthcare providers have reported challenges with coordinating care for patients with cancer. Digital technology tools have brought new possibilities for improving care coordination. A web- and text-based asynchronous system (eOncoNote) was implemented in Ottawa, Canada for cancer specialists and primary care providers (PCPs). This study aimed to examine PCPs’ experiences of implementing eOncoNote and how access to the system influenced communication between PCPs and cancer specialists. As part of a larger study, we collected and analyzed system usage data and administered an end-of-discussion survey to understand the perceived value of using eOncoNote. eOncoNote data were analyzed for 76 shared patients (33 patients receiving treatment and 43 patients in the survivorship phase). Thirty-nine percent of the PCPs responded to the cancer specialist’s initial eOncoNote message and nearly all of those sent only one message. Forty-five percent of the PCPs completed the survey. Most PCPs reported no additional benefits of using eOncoNote and emphasized the need for electronic medical record (EMR) integration. Over half of the PCPs indicated that eOncoNote could be a helpful service if they had questions about a patient. Future research should examine opportunities for EMR integration and whether additional interventions could support communication between PCPs and cancer specialists.
Face Mask Use and Social Distancing Attitude of Healthcare Students: A Multi-Disciplinary Study

This multi-disciplinary, cross-sectional, and descriptive study investigated health care students’ face mask use knowledge, attitude, and practices (KAP) and social distancing attitudes. The study was carried out from October to December 2021 and surveyed 543 health care students selected via convenience sampling from the three Shaqra University campuses in Saudi Arabia. Standard multiple linear regressions were conducted on face mask use KAP and social distancing attitude to identify their significant associated factors. The students in this study had poor knowledge and a neutral attitude towards and modest use practices of face masks during the COVID-19 pandemic. Being female, being a nursing student, and having greater self-reported COVID-19-prevention knowledge were related to higher levels of face mask use knowledge. Having higher face mask use knowledge was linked to better attitude and practice. Knowledge of COVID-19 and its prevention and decreased COVID-19 risk perception were associated with better face mask use practices. The students had more positive than negative attitudes toward social distancing. Having known someone who was infected by the virus, lower risk perception, and better face mask use practices were associated with more positive social distancing attitudes. The findings imply the need to ensure that future health care practitioners are knowledgeable, have a positive attitude and good practices concerning face mask use, and have positive attitudes toward social distancing. The study implications are relevant for health care education in Saudi Arabia and elsewhere.
Stationary, nonstationary, and hybrid iterative method of moments solution schemes

The purpose of this paper is to report on the convergence rates of two iterative matrix solution methods individually and then to combine the two methods into a hybrid scheme to achieve additional convergence rate benefits. One iterative matrix solver investigated is the sparse iterative method (SIM) which is a stationary, Jacobi-like solver but uses a sparse and not a banded matrix, with matrix elements corresponding to strong interactions, rather than position in the matrix. In this paper, the SIM is modified to include an adaptive relaxation scheme to improve its convergence speed and numerical stability. Another iterative scheme investigated is the nonstationary biconjugate gradient stabilized (BiCGSTAB) method. It is shown that the BiCGSTAB is considerably improved when the method is preconditioned by the sparse matrix used in the SIM method. Finally, a hybrid scheme is proposed which combines both SIM-AR and BiCGSTAB-precon and it is shown that the hybrid gives best results on the problems considered. Examples giving convergence time versus accuracy are presented for two problems: a wire-grid plate, and a wire-grid partial helicopter.
Some generalized beta distributions of the second kind having desirable application features in hydrology and meteorology

Two distinct versions of the generalized beta distribution of the second kind are considered. These beta-type distributions compare favorably with the commonly used gamma and log normal distributions in their ability to fit selected sets of accumulated streamflow and precipitation amount data. The comparisons are based on empirical results associated with three different goodness of fit criteria. Since the cumulative distribution functions of these beta-type distributions are in closed form, they possess unique computational advantages over the gamma and log normal distributions.
A multi-subgroup predictive model based on clinical parameters and laboratory biomarkers to predict in-hospital outcomes of plasma exchange-centered artificial liver treatment in patients with hepatitis B virus-related acute-on-chronic liver failure

Background Postoperative risk stratification is challenging in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) who undergo artificial liver treatment. This study characterizes patients’ clinical parameters and laboratory biomarkers with different in-hospital outcomes. The purpose was to establish a multi-subgroup combined predictive model and analyze its predictive capability. Methods We enrolled HBV-ACLF patients who received plasma exchange (PE)-centered artificial liver support system (ALSS) therapy from May 6, 2017, to April 6, 2022. There were 110 patients who died (the death group) and 110 propensity score-matched patients who achieved satisfactory outcomes (the survivor group). We compared baseline, before ALSS, after ALSS, and change ratios of laboratory biomarkers. Outcome prediction models were established by generalized estimating equations (GEE). The discrimination was assessed using receiver operating characteristic analyses. Calibration plots compared the mean predicted probability and the mean observed outcome. Results We built a multi-subgroup predictive model (at admission; before ALSS; after ALSS; change ratio) to predict in-hospital outcomes of HBV-ACLF patients who received PE-centered ALSS. There were 110 patients with 363 ALSS sessions who survived and 110 who did not, and 363 ALSS sessions were analyzed. The univariate GEE models revealed that several parameters were independent risk factors. Clinical parameters and laboratory biomarkers were entered into the multivariate GEE model. The discriminative power of the multivariate GEE models was excellent, and calibration showed better agreement between the predicted and observed probabilities than the univariate models. Conclusions The multi-subgroup combined predictive model generated accurate prognostic information for patients undergoing HBV-ACLF patients who received PE-centered ALSS.
Mind the gap: Bridging evidence-based witness identification procedures to practice through police training

Research has led to evidence-based eyewitness identification procedures, but empirical research on how to train police officers in such techniques is limited. We tested the effectiveness of the FAIR (Find a suspect, Avoiding bias, Instructing the witness, Record the procedure) eyewitness identification training program with 88 Brazilian police officers. The hypothesis that FAIR training would improve identification procedures was supported by pre- and post-training assessment of performance on a lineup construction task. Training increased the likelihood that police officers would construct lineups with known-innocent fillers and provide recommended pre-lineup instructions to witnesses (e.g., stating that the witness is not required to make an identification). Training also decreased non-recommended lineup practices, such as revealing the identity of the main suspect after a witness response. Feedback from the participants supports the conclusion that FAIR training improved knowledge of how to build lineups, instruct witnesses, and avoid undesirable and potentially biasing practices. Nevertheless, participants anticipated that incorporating the reform procedures into practice would provoke resistance from superiors and colleagues, which highlights the need for FAIR training to be supported by infrastructure, resources and policy that enable police officers to use evidence-based procedures in eyewitness identification.
Zonotopic Under-Approximations of Input Reachable Sets for Controllable Linear Systems

Recent years have seen a surging interest in developing under-approximations of reachable sets due to their potential applications in control synthesis and verification. In this letter, we propose a method that yields under-approximations of finite-time input reachable sets for continuous-time controllable linear time-invariant systems with zonotopic input sets, utilizing approximations of the matrix exponential and its integral. The proposed method generates zonotopic under-approximations that converge in the sense of the Hausdorff distance. In addition, we introduce a variant of the proposed method that is better suited for applications with large time horizons. To illustrate its performance, we implement our proposed method in two numerical examples.
THE GAGLIARDO-NIRENBERG INEQUALITIES AND MANIFOLDS WITH NON-NEGATIVE WEIGHTED RICCI CURVATURE

In this paper, we show that n -dimensional (n (cid:2) 2 ) complete and non-compact smooth metric measure spaces with non-negative weighted Ricci curvature in which some Gagliardo–Nirenberg-type inequality holds are not far from the model metric measure n -space (i.e., the Euclidean metric n -space). Moreover, this fact, together with two generalized volume comparison theorems given in [P. Freitas et al. Calc. Var. Partial Differential Equations 51 (2014), 701–724], surprisingly leads to an interesting rigidity theorem for the given metric measure spaces.
Monitoring Drought Stress in Common Bean Using Chlorophyll Fluorescence and Multispectral Imaging

Drought is a significant constraint in bean production. In this study, we used high-throughput phenotyping methods (chlorophyll fluorescence imaging, multispectral imaging, 3D multispectral scanning) to monitor the development of drought-induced morphological and physiological symptoms at an early stage of development of the common bean. This study aimed to select the plant phenotypic traits which were most sensitive to drought. Plants were grown in an irrigated control (C) and under three drought treatments: D70, D50, and D30 (irrigated with 70, 50, and 30 mL distilled water, respectively). Measurements were performed on five consecutive days, starting on the first day after the onset of treatments (1 DAT–5 DAT), with an additional measurement taken on the eighth day (8 DAT) after the onset of treatments. Earliest detected changes were found at 3 DAT when compared to the control. D30 caused a decrease in leaf area index (of 40%), total leaf area (28%), reflectance in specific green (13%), saturation (9%), and green leaf index (9%), and an increase in the anthocyanin index (23%) and reflectance in blue (7%). The selected phenotypic traits could be used to monitor drought stress and to screen for tolerant genotypes in breeding programs.
Pulsational Evidence for Mass Loss in NGC 1866 Cepheids

Available observational data for the 20 known Cepheids in the LMC cluster NGC 1866 have been compared with Hubble Space Telescope observations, discovering in the cluster central region five additional variables, one of which appears to be a Cepheid candidate. We also reach the conclusion that only the photometric data for the seven variables in the cluster periphery appear accurate enough to allow a meaningful comparison with the results of pulsational theories. Out of these seven well-observed Cepheids, we find that the six probable cluster members are located in the color-magnitude diagram at the hot tip of the blue nose experienced by He-burning giants. Since evolutionary theory predicts for these giants an original mass on the order of 4 M⊙, we extend down to ∼3 M⊙ the theoretical pulsational scenario already presented for M ≥ 5.0 M⊙. On this basis we discuss the four member Cepheids with VI magnitudes accurate enough to produce robust constraints on the pulsating structures. Among these variables, one finds evidence for a spread of masses by about 7%, with the structures following a tight mass-luminosity relation. Moreover, we show that periods and colors of the Cepheids give a robust indication of pulsator masses smaller than predicted by stellar evolution theory without mass loss, independently of the occurrence of core overshooting.
The Empirical Study of the Impact of Firm- and Country-level Factors on Debt Financing Decisions of ICT Firms

The capital structure has been extensively analysed in the empirical literature. Despite of the great contribution of the technological industry to the global economy, little research has been conducted regarding corporate finance of ICT firms. Moreover, the previous literature barely considers the effect of macroeconomic variables on financial decisions, focusing much more on internal determinants, such as cash flow, firm’s size or growth opportunities. The objective of this work is to reduce this gap by disentangling the reasons behind the financial decisions of technological firms. The sample included 1,510 public ICT firms from 23 countries over the period 2004 – 2019 (17,342 observations). The variables used in this study are obtained from S&P Capital IQ, World Development Indicators, Main Science and Technology Indicators from OECD, and FMI dataset. The two-step system generalized method of moments (GMM) was used as methodology. Consistent with the extant literature, more profitable and liquid ICT firms and those with an increased non-debt tax shields are less leveraged. However, the companies which present higher risk, measured as volatility of EBIT, increase their use of debt financing. Contrary to the findings of many other studies, the analysis of a firm’s size and tangible assets shows non-conclusive results. Regarding macroeconomic determinants, only economic growth and foreign direct investment inflows were found to generate a positive effect on financial decisions of ICT firms. The findings of this work can be used to design and develop policies, measures, and facilitate mechanisms for optimal management of the financing decisions of ICT firms.
Novel Plant-Protein (Quinoa) Derived Bioactive Peptides with Potential Anti-Hypercholesterolemic Activities: Identification, Characterization and Molecular Docking of Bioactive Peptides

Hypercholesterolemia remains a serious global public health concern. Previously, synthetic anti-hypercholesterolemic drugs were used for ameliorating this condition; however, long-term usage presented several side-effects. In this regard, natural products as an adjunct therapy has emerged in recent times. This study aimed to produce novel bioactive peptides with anti-hypercholesterolemic activity (cholesterol esterase (CEase) and pancreatic lipase (PL)) from quinoa protein hydrolysates (QPHs) using three enzymatic hydrolysis methods (chymotrypsin, protease and bromelain) at 2-h hydrolysis intervals (2, 4, and 6 h). Chymotrypsin-generated hydrolysates showed higher CEase (IC50: 0.51 mg/mL at 2 h) and PL (IC50: 0.78 mg/mL at 6 h) inhibitory potential in comparison to other derived hydrolysates and intact quinoa proteins. Peptide profiling by LC-MS QTOF and in silico interaction with target enzymes showed that only four derived bioactive peptides from QPHs could bind in the active site of CEase, whereas twelve peptides could bind in the active site of PL. Peptides QHPHGLGALCAAPPST, HVQGHPALPGVPAHW, and ASNLDNPSPEGTVM were identified to be potential CEase inhibitors, and FSAGGLP, QHPHGLGALCAAPPST, KIVLDSDDPLFGGF, MFVPVPH, and HVQGHPALPGVPAHW were identified as potential PL inhibitors on the basis of the maximum number of reactive residues in these bioactive peptides. In conclusion, QPHs can be considered as an alternative therapy for the treatment of hypercholesterolemia.
Prospective Teachers' Perspectives on Function Representations

This is a report of a study in which we aim to characterise the quality of subject-matter and pedagogical content knowledge constructed by a group of four student teachers in the domain of functions. A key feature of the results is that these teachers tended to emphasise the visual representations in their understanding of functions without sufficient attention to their symbolic equivalency. As expected, their pedagogical content knowledge was not well developed. We discuss the implications for subject-matter growth from the framework of modelling and schema development. The study of functions constitutes an important requirement at many levels of schooling. Early developments in the understanding of functions involve students’ ability at modelling one-to-one correspondences between members of a given set of objects. Such a relationship can also be given an algebraic interpretation as students advance to higher levels of understandings. Students with deeper understanding of functions can also be expected to articulate the many- or one-to-one correspondences that underlie the algebraic expression of a function. Thus functions can be represented in a wide variety of different ways, such as in algebraic symbol form, set diagrams, ordered pairs, graphs and tables of values. The multidimensional nature of functions presents particular challenge to the teachers in designing appropriate learning situations. Translating between these various forms of function representations is something which an experienced teacher might take for granted, but to do so one needs to have an overview of the way the definition of function relates to each representation, and how sub-concepts, such as independent and dependent variables, one-to-one, roots, discrete, continuous, etc. are manifest in each representation (Hong, Thomas & Kwon, 2000).
The optimization of a tanker autopilot control system using genetic algorithms

A genetic algorithm (GA) optimization application is presented in this paper. It involves the performance optimization of a navigation system for a nonlinear tanker model. This navigation system is fully autonomous and regulates the heading of the vessel with reference to a desired course made up of waypoints. The system consists of two components. The first is a line of sight (LOS) autopilot, which determines the desired heading of the tanker from positional information. The second is a heading control system that is derived from sliding mode (SM) control theory. In this investigation the GA is used to optimize the parameters for the SM controller so that the performance of the complete system satisfies specific design criteria. The resulting optimized navigation system is evaluated for different operating conditions for the tanker, e.g., different course, different forward velocities.
Turbulence inside a vortex

Following Bradshaw’s analogy between rotating and stratified flows, the turbulence within a vortex is analyzed using a new model for stratified entrainment. At the vortex radius where the tangential velocity is a maximum, the model predicts that the flow is so strongly “stratified” that even the smallest turbulent eddies are incapable of transporting fluid there. The growth of the vortex is thus limited by molecular viscosity, even though the vortex Reynolds number is large. The model prediction is compared to experiments in the literature of wingtip vortices. The result is consistent with the remarkable observations of laminar-like growth of this turbulent flow.
High Accurate Fourth-Order Finite Difference Solutions of the Three Dimensional Poisson's Equation in Cylindrical Coordinate

In this work, by extending the method of Hockney into three dimensions, the Poisson’s equation in cylindrical coordinates system with the Dirichlet’s boundary conditions in a portion of a cylinder for is solved directly. The Poisson equation is approximated by fourth-order finite differences and the resulting large algebraic system of linear equations is treated systematically in order to get a block tri-diagonal system. The accuracy of this method is tested for some Poisson’s equations with known analytical solutions and the numerical results obtained show that the method produces accurate results.