Miracle-dz/UniFAR-FTUs huggingface dataset:
Virtual Learning during COVID-19: Exploring Challenges and Identifying Highly Vulnerable Groups Based on Location

Amid the outbreak of the COVID-19 pandemic in the year 2020, educational platforms have been forced to change and adapt from conventional physical learning to virtual learning. Nearly all higher learning institutions worldwide are forced to follow the new educational setting through virtual platforms. Sabah is one of the poorest states in Malaysia with the poorest infrastructure, with the technology and communication facilities in the state remaining inept. With the changes in virtual platforms in all higher education institutions in Malaysia, higher learning institutions in Sabah are expected to follow the lead, despite the state lagging in its development. This has certainly impacted the overall productivity and performance of students in Sabah. Therefore, this study aims to explore the challenges of the implementation of virtual learning among students in Sabah. More specifically, this study seeks to identify vulnerable groups among students based on their geographical location. To achieve the objective of this study, a survey has been conducted on a total of 1,371 students in both private and public higher learning institutions in Sabah. The sample selection for this study was determined using a purposive sampling technique. Based on Principal Component Analysis (PCA), it was found that there are five challenges in virtual learning faced by students in higher learning institutions in Sabah. These are the unconducive learning environment (var(X) = 20.12%), the deterioration of physical health (var(X) = 13.40%), the decline of mental health (var(X) = 12.10%), the limited educational facilities (var(X) = 10.14%) and social isolation (var(X) = 7.47%). The K-Means Clustering analysis found that there are six student clusters in Sabah (Cluster A, B, C, D, E & F), each of which faces different challenges in participating in virtual learning. Based on the assessment of location, almost half of the total number of districts in Sabah are dominated by students from Cluster A (9 districts) and Cluster B (4 districts). More worryingly, both Cluster A and Cluster B are classified as highly vulnerable groups in relation to the implementation of virtual learning. The results of this study can be used by the local authorities and policymakers in Malaysia to improve the implementation of virtual learning in Sabah so that the education system can be more effective and systematic. Additionally, the improvement and empowerment of the learning environment are crucial to ensuring education is accessible and inclusive for all societies, in line with the fourth of the Sustainable Development Goals (SDG-4).
Multivariate Statistics, Mineralogy, and Radiological Hazards Assessment Due to the Natural Radioactivity Content in Pyroclastic Products from Mt. Etna, Sicily, Southern Italy

In this article, an investigation of the natural radioactivity content of pyroclastic products from Mt. Etna, eastern Sicily, Southern Italy, was carried out. In particular, the assessment of the average activity concentration of the investigated radionuclides, related to the mineralogical phase composition of the analyzed samples, and the radiological health risk for the population, was performed. High Purity Germanium (HPGe) gamma-ray spectrometry was employed in order to quantify the average specific activity of 226Ra, 232Th, and 40K natural radioisotopes. The absorbed gamma dose rate (D), the radium equivalent activity (Raeq), the hazard indices (Hin and Hex), the annual effective dose equivalent outdoor (AEDEout), and the excess lifetime cancer risk (ELCR) were also estimated in order to assess any possible radiological hazard for the population. In our case, they were found to be lower than the maximum recommended values for the population members, thus reasonably excluding radiological hazard effects. Moreover, the identification of the source of the aforementioned naturally occurring radionuclides was attempted by X-ray Diffraction (XRD) and Micro-Raman Scattering (MRS), thereby recognizing the main radioisotope-bearing minerals present in the investigated pyroclastic products. Finally, Pearson correlation, Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA) were performed by processing observed radioactivity and radiological parameters in order to determine their correlation with the sampling locations.
A group structure on squares

We show that there is an abelian group structure on the orbit set of "squares" of unimodular rows of length n over a commutative ring of stable dimension d when d = 2 n - 3, n odd and also an abelian group structure on the orbit set of "fourth powers" of unimodular rows of length n over a commutative ring of stable dimension d when d = 2n - 3, n even.
Response of Bletilla striata to Drought: Effects on Biochemical and Physiological Parameter Also with Electric Measurements

In heterogeneous landscapes with temporary water deficit characteristics in southwestern China, understanding the electrophysiological and morphological characteristics of Bletilla striata under different water conditions can help to better evaluate its suitability for planting plants in specific locations and guide planting and production. Using B. striata seedlings as experimental materials, the maximum field capacity (FC) was 75–80% (CK: control group), 50–60% FC (LS: light drought stress), 40–45% FC (MS: moderate drought stress), and 30–35% FC (SS: severe drought stress). In terms of physiological response, the activities of peroxidase (POD) and catalase (CAT) decreased under drought conditions, but the activity was well under the LS treatment, and the contents of proline (Pro) and malondialdehyde (MDA) increased. In terms of morphological responses, under drought conditions, root lengths of the rhizomes (except the LS treatment) were significantly reduced, the leaf lengths were reduced, and the biomass was significantly reduced. The stomatal size reached the maximum under the LS treatment, and the stomatal density gradually decreased with the increase in drought degree. In terms of electrophysiological responses, drought significantly decreased the net photosynthetic rate (PN) of B. striata, stomatal conductance (gs), and transpiration rate (Tr), but effectively increased the water use efficiency (WUE). The effective thickness of leaves of B. striata increased under drought conditions, and drought promoted the formation of leaf morphological diversity. Our results showed that drought stress changed the physiological and morphological characteristics of B. striata, and under light drought conditions had higher physiological activity, good morphological characteristics, higher cellular metabolic energy and ecological adaptability. Appropriate drought can promote the improvement of the quality of B. striata, and it can be widely planted in mildly arid areas.
Prognostic Nutritional Index as a Predictor of Diabetic Nephropathy Progression

Abstract Malnutrition and immunologic derangement were not uncommon in patients with chronic kidney disease (CKD). However, the long-term effects of prognostic nutritional index (PNI), an immunonutrition indictor, on renal outcomes in patients with diabetic nephropathy (DN) and type 2 diabetes mellitus (T2DM) are unknown. In this retrospective cohort study, 475 patients with T2DM and biopsy-confirmed DN from West China Hospital between January 2010 and September 2019 were evaluated. PNI was evaluated as serum albumin (g/L) + 5 × lymphocyte count (109/L). The study endpoint was defined as progression to end-stage renal disease (ESRD). The Cox regression analysis was performed to investigate the risk factors of renal failure in DN patients. A total of 321 eligible individuals were finally included in this study. The patients with higher PNI had a higher eGFR and lower proteinuria at baseline. Correlation analysis indicated PNI was positively related eGFR (r = 0.325, p < 0.001), and negatively correlated with proteinuria (r = −0.68, p < 0.001), glomerular lesion (r = −0.412, p < 0.001) and interstitial fibrosis and tubular atrophy (r = −0.282, p < 0.001). During a median follow-up of 30 months (16–50 months), the outcome event occurred in 164(51.09%) of all the patients. After multivariable adjustment, each SD (per-SD) increment of PNI at baseline was associated with a lower incidence of ESRD (hazard ratio, 0.705, 95% CI, 0.523–0.952, p = 0.023), while the hypoalbuminemia and anemia were not. For the prediction of ESRD, the area under curves (AUC) evaluated with time-dependent receiver operating characteristics were 0.79 at 1 year, 0.78 at 2 years, and 0.74 at 3 years, respectively, and the addition of PNI could significantly improve the predictive ability of the model incorporating traditional risk factors. In summary, PNI correlated with eGFR and glomerular injury and was an independent predictor for DN progression in patients with T2DM. Thus, it may facilitate the risk stratification of DN patients and contribute to targeted management.
The ALHAMBRA Survey: Bayesian photometric redshifts with 23 bands for 3 deg2

The ALHAMBRA (Advance Large Homogeneous Area Medium Band Re dshift Astronomical) survey has observed 8 different regions of the sky, incl uding sections of the COSMOS, DEEP2, ELAIS, GOODS-N, SDSS and Groth fields using a new photometric system with 20 contiguous �300 ˚ A filters covering the optical range, combining them with deep JHKs imaging. The observations, carried out with the Calar Alto 3.5m telescope using the wide field (0.25 deg 2 FOV) optical camera LAICA and the NIR instrument Omega-2000, correspond to �700hrs of on-target science images. The photometric system was specifically designed to maximize the effective depth of the survey in terms of accurate spectral-type and photometric redshift estimation along with the capability of identi fication of relatively faint emission lines. Here we present multicolor photometry and photometric redshifts for �438,000 galaxies, detected in synthetic F814W images, complete down to a magnitude I�24.5AB, carefully taking into account realistic noise estimates, and correct ing by PSF and aperture effects with the ColorPro software. The photometric zeropoints have been calibrated using stellar transformation equations and refined internally, using a new tech nique based on the highly robust photometric redshifts measured for emission line galaxies. We calculate photometric redshifts with the BPZ2.0 code, which includes new empirically calibrated galaxy templates and priors. —
Prognostic Factors in Patients Treated with Pembrolizumab as a Second-Line Treatment for Advanced Biliary Tract Cancer

Simple Summary The five-year survival rate for advanced biliary tract cancer (BTC) is still less than 10%. Moreover, there is no established second-line chemotherapy after the failure of the first-line chemotherapy. Pembrolizumab is known to be an effective treatment in advanced BTC, but the prognostic factors of pembrolizumab are unknown. The purpose of this study is to provide guidelines for selecting treatment alternatives for BTC patients with refractory to gemcitabine-based chemotherapy, by exploring the prognostic factors of pembrolizumab in BTC. Abstract Some BTC types respond to pembrolizumab, but there are no known prognostic factors to predict its treatment benefits. In this study, we attempted to identify the prognostic factors associated with pembrolizumab as a second-line treatment for gemcitabine-refractory BTC. This retrospective and single tertiary-center study involved all the consecutive patients (n = 80) with refractory advanced BTC, who were diagnosed as programmed cell death ligand 1-positive and treated with pembrolizumab between August 2017 and February 2021. The overall survival (OS) was analyzed using Cox regression analysis. The median OS was 6.0 months [95% confidence interval (CI): 3.87–8.20]; median progression-free survival was 1.9 months (95% CI: 1.82–1.98); and the response rate was 15.9%. In the multivariate Cox regression analysis, the TB [adjusted hazard ratio (HR) = 2.286; 95% CI: 1.177–4.440; p = 0.015), albumin levels (adjusted HR = 0.392; 95% CI: 0.211–0.725; p = 0.003), ALP levels (adjusted HR = 1.938; 95% CI: 1.105–3.400; p = 0.021), and LMR (adjusted HR = 0.325; 95% CI: 0.173–0.609; p < 0.001) were identified as significant variables associated with the OS. High albumin levels and LMR and low ALP levels and TB were significantly associated with better OS in patients treated with pembrolizumab.
Subsampling in testing autocovariance for periodically correlated time series

Abstract. The main purpose of this article was to describe the asymptotic properties of subsampling procedure applied to nonstationary, periodically correlated time series. We present the conditions under which the subsampling version for the estimator of Fourier coefficient of autocovariance function is consistent. Our result provides new tools in statistical inference methods for nonstationary, periodically correlated time series. For example, it enables to construct consistent subsampling test which successfully distinguishes the period of the series.
The Association of Race with the Decision Whether or Not to Grant Parole

Data obtained via Public Records Act requests from the California Board of Parole Hearings were analyzed to determine whether the race of parole applicants was associated with parole outcomes, i.e., whether race was a factor in the decision to grant or deny parole. Chi squared analysis of the data revealed that over a two-year period extending from July 1, 2018, through June 30, 2020 (N = 6,635), candidates for parole who were identified by the Board as Black received fewer parole grants and more parole denials than would be expected if race was a neutral factor. The findings were highly significant and robust overall. There were similar findings when the data was disaggregated to look at only those parole hearings presided over by male commissioners or only those hearings presided over by female commissioners or only those hearings presided over by White commissioners. It was also noted that female commissioners granted parole to every race of parole applicants at a higher rate than their male counterparts.
Hermite Fitted Block Integrator for Solving Second-Order Anisotropic Elliptic Type PDEs

A Hermite fitted block integrator (HFBI) for numerically solving second-order anisotropic elliptic partial differential equations (PDEs) was developed, analyzed, and implemented in this study. The method was derived through collocation and interpolation techniques using the Hermite polynomial as the basis function. The Hermite polynomial was interpolated at the first two successive points, while the collocation occurred at all the suitably chosen points. The major scheme and its complementary scheme were united together to form the HFBI. The analysis of the HFBI showed that it had a convergence order of eight with small error constants, was zero-stable, absolutely-stable, and satisfied the condition for convergence. In order to confirm the usefulness, accuracy, and efficiency of the HFBI, the method of lines approach was applied to discretize the second-order anisotropic elliptic partial differential equation PDE into a system of second-order ODEs and consequently used the derived HFBI to obtain the approximate solutions for the PDEs. The computed solution generated by using the HFBI was compared to the exact solutions of the problems and other existing methods in the literature. The proposed method compared favorably with other existing methods, which were validated through test problems whose solutions are presented in tabular form, and the comparisons are illustrated in the curves.
Gallic Acid Ameliorates the Inflammatory State of Periodontal Ligament Stem Cells and Promotes Pro-Osteodifferentiation Capabilities of Inflammatory Stem Cell-Derived Exosomes

The slow proliferation rate and poor osteodifferentiation ability of inflammatory periodontal membrane stem cells extracted from periodontitis tissues (i-PDLSCs) account for poor efficiency in treating inflammatory bone loss. Exosomes reportedly have inducible and relatively stable components, allowing them to promote inflammatory bone repair, but obtaining i-PDLSCs exosomes with the ability to promote osteodifferentiation is challenging. In the present study, i-PDLSCs were extracted from periodontal membrane tissues of patients with severe periodontitis, and in vitro induction with gallic acid (GA) significantly promoted the proliferative activity of i-PDLSCs at a concentration of 10 mM, with TC0 of 11.057 mM and TC50 of 67.56 mM for i-PDLSCs. After mRNA sequencing, we found that GA could alleviate oxidative stress in i-PDLSCs and increase its mitochondrial membrane potential and glucose aerobic metabolism level, thus promoting the osteodifferentiation of i-PDLSCs. After exosomes of i-PDLSCs after GA induction (i-EXO-GA) were isolated by differential centrifugation, we found that 200 ug/mL of i-EXO-GA could remarkably promote the osteodifferentiation of i-PDLSCs. Overall, our results suggest that GA induction can enhance the proliferation and osteodifferentiation in primary cultures of i-PDLSCs in vitro, mediated by alleviating oxidative stress and glycometabolism levels in cells, which further influences the osteodifferentiation-promoting ability of i-EXO-GA. Overall, we provide a viable cell and exosome induction culture method for treating inflammatory alveolar defects associated with periodontitis.
Industry Diversification and Optimal Industry Combination of Portfolios

The importance of asset diversification has been tested and proven many times in the past few decades. Investors can allocate their money into different asset classifications, such as stocks, golds, and funds. Undoubtedly, returns and risks vary across different types of assets. A huge number of risk lovers are keen to invest in stocks and equity funds due to their fascinating revenues. However, the equity market covers a wide variety of industries. How could one reasonably allocate assets to obtain a fair gain with low risks? We aimed at figure out the optimal combination of 20 industries that construct minimum variance, maximum Sharpe ratio, and maximum drawdown portfolios separately among 64 industries in China. Basically, we gathered industries index data in 2014 and 2015 and utilized Excel functions to do our experiment. Eventually, 7 industries showed up in both years’ minimum variance portfolios. If certain industries appeared in minimum variance portfolios over and over again, these industries usually had relatively low risks and could offer suggestions for investors. Some implications could also be found from maximum Sharpe ratio and maximum drawdown experiments.
Peroxisome Proliferator-Activated Receptor α Has a Protective Effect on Fatty Liver Caused by Excessive Sucrose Intake

Sterol regulatory element binding protein (SREBP)-1c is a transcription factor that regulates lipid synthesis from glucose in the liver. It is activated by sucrose, which activates the fatty acid synthesis pathway. On the other hand, peroxisome proliferator-activated receptor (PPAR) α regulates the transcription of several genes encoding enzymes involved in fatty acid β-oxidation in the liver. To evaluate the beneficial effects of PPARα on fatty liver caused by excessive sucrose intake, we investigated the molecular mechanisms related to the development of fatty liver in PPARα-deficient mice that were fed a high-sucrose diet (Suc). The SREBP-1c target gene expression was increased by sucrose intake, leading to the development of fatty liver. Furthermore, PPARα−/− mice developed severe fatty liver. Male and female PPARα−/− mice fed Suc showed 3.7- and 3.1-fold higher liver fat content than Suc-fed male and female wild-type mice, respectively. Thus, PPARα may work to prevent the development of fatty liver caused by excessive sucrose intake. Liver TG accumulation differed between male and female PPARα−/− mice. A possible explanation is that male mice show the increased expression of Pparγ, which usually contributes to triglyceride synthesis in the liver, to compensate for Pparα deficiency. In contrast, female wild-type mice inherently have low Pparα levels. Thus, Pparα deficiency has less pronounced effects in female mice. A diet that activates PPARα may be effective for preventing the development of fatty liver due to excessive sucrose intake.
Three set inequalities in integer programming

Integer programming is a useful tool for modeling and optimizing real world problems. Unfortunately, the time required to solve integer programs is exponential, so real world problems often cannot be solved. The knapsack problem is a form of integer programming that has only one constraint and can be used to strengthen cutting planes for general integer programs. These facts make finding new classes of facet-defining inequalities for the knapsack problem an extremely important area of research. This thesis introduces three set inequalities (TSI) and an algorithm for finding them. Theoretical results show that these inequalities will be of dimension at least 2, and can be facet defining for the knapsack problem under certain conditions. Another interesting aspect of these inequalities is that TSIs are some of the first facet-defining inequalities for knapsack problems that are not based on covers. Furthermore, the algorithm can be extended to generate multiple inequalities by implementing an enumerative branching tree. A small computational study is provided to demonstrate the effectiveness of three set inequalities. The study compares running times of solving integer programs with and without three set inequalities, and is inconclusive.
IoT-enabled delivery time guarantee in logistics outsourcing and efficiency improvement

Industrial Internet of Things (IoT) technologies have been widely implemented in today’s logistics operations to reduce the handling time and improve service efficiency. This enables a firm to promise a delivery time (PDT) when selling products, which improves customer satisfaction and enhances the firm’s brand image. However, the costly PDT logistics service should be seriously evaluated when the market competition is intensified to aggravate the firm’s cost concern. In a competitive decentralized framework, this paper investigates the value of IoT-enabled PDT quotation in a brand’s logistics outsourcing decisions. We develop three-stage optimization models and show that the brand’s production quantity and equilibrium profit exhibit non-monotonic relationships to the competition intensity degree. Given a moderate competition intensity degree, the brand developing IoT and quoting PDT suffers from imbalanced payoffs between PDT cost-saving and sales volume expansion. This distorts the PDT cost and hence, investing in the IoT-enabled logistics system might not be beneficial. This paper contributes to the existing literature by examining the impact of heterogeneous logistics service incorporating the PDT quotation on traditional quantity competition within a dual-channel supply chain.