Miracle-dz/UniFAR-FTUs huggingface dataset:
The banking sector as the absorber of the COVID-19 crisis? economic consequences: perception of WSE investors

Research background: The paper focuses on the research of investors? decisions with regard to shares of all 12 banks listed on the Warsaw Stock Exchange during the first half of 2020. It examines the behavior of a subindex reflecting bank shares? prices against the main WIG index WIG and 14 sector subindices. The authors identify groups of banks with different investors? responses. They also classify banks into separate groups on the basis of changes in the fundamental indicators describing their economic and financial performance. The study concentrates mainly on the verification of the stability of this attribution, explaining reasons for its modifications over time. Purpose of the article: To identify the characteristics of bank clusters determining different capital market responses to their listed shares and to explain the reasons for volatility in investors? behavior within the analyzed period. Methods: The methodology of the research can be described in three areas. The first is the statistical analysis with the emphasis on the use of a quarter range to capture changes in the volatility of share prices. The second area is the clustering k-means method based on the interpolated ? from quarterly to daily ? measures of the bank? s financial condition. This mathematical approach is a novelty in finance and economics. The last, third, area is forecasting with the use of linear regression analysis, which is the key factor in determining the abnormal rates of return. The indicated areas are combined through a generally understood correlation analysis. Findings & value added: Large retail banks have been less affected compared to medium-sized ones with relatively rich corporate portfolios. The initial market reaction reflected concern about the resistance to the crisis of poorly capitalized banks with mean liquidity buffers. Upon the announcement of government support, investors? approach to the shares of banks of differentiated economic and financial performance conformed accordingly. These findings are valuable in the long term especially from the perspective of supervision authorities? policy during external shocks. The presented study suggests designing flexible and tailor-made regulatory approach aligned with the defined bank clusters. Its value added also consists in proposing a new method of analysis, combining interpolation and automatic clustering, which has proved to be adequate for the study of a bank? s financial condition based on daily frequency data. Furthermore, assuming the same length of the estimation window, a close relationship is shown between the results of clustering and the forecasts based on different measures of rates of return.
DMSO_A_313488 2883..2892

1Department of Endocrinology, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, People’s Republic of China; 2Department of General Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, 646000, People’s Republic of China; 3Southwest Medical University, Luzhou, Sichuan, 646000, People’s Republic of China Purpose: Bile acids, amphipathic cholesterol metabolites, have been reported to have cytoprotective and neuroprotective effects in humans and animal models. The relationship of physiological serum total bile acid (TBA) levels with diabetic peripheral neuropathy (DPN), however, has not been determined. The purpose of this study was to investigate the relationship between physiological serum TBA and DPN. Patients and Methods: In total, 856 patients with type 2 diabetes mellitus (T2DM) aged 20–89 years were enrolled in this cross-sectional study. Serum TBA was measured, and its relationship with DPN and other parameters was analyzed. Results: T2DM patients with DPN had significantly lower serum TBA compared with those without (P<0.01). Serum TBA was negatively associated with glycated hemoglobin A1C, plateletcrit, fibrinogen, urine albumin-to-creatinine ratio, vibration perception thresholds, and prevalence of DPN, peripheral arterial disease, and diabetic foot ulceration after adjustment for age, sex, and body mass index (P<0.01 or P<0.05). A graded association with prevalence of DPN and increase in serum TBA quartiles was observed (P for trend <0.01), and there was an 48.2% decreased risk of DPN in the highest quartile of serum TBA versus the lowest quartile (95% CI 0.299–0.617; P=0.000) after multivariate adjustment. Receiver-operating characteristic analysis revealed that the optimal cutoff point of serum TBA to indicate DPN was 2.85 μmol/L (sensitivity 77.6% and specificity 45.6%). Conclusion: These findings suggest that lower physiological serum TBA level may be associated with the prevalence of DPN in T2DM patients and may be a potential biomarker for DPN.
First genome size assessments in Carduncellus and its related genera Femeniasia and Phonus (Asteraceae, Cardueae), with data on 21 taxa

First genome size assessments in CardunCellus and its related genera Femeniasia and Phonus (asteraceae, cardueae), with data on 21 taxa. — Genome size of 18 species of the genus Carduncellus, two species of the related genus Phonus and the monotypic genus Femeniasia (F. balearica) has been assessed by flow cytometry for the first time. Ploidy levels were assigned using genome size data together with previously reported chromosome counts. A phylogenetic framework was built to visualize how cytogenetic traits distributed across taxa. The results confirmed three ploidy levels (2x, 4x and 6x), with a predominance of diploids. The 2C values ranged from 3.24 pg in Carduncellus calvus to 11.16 pg in C. eriocephalus, whereas monoploid genome size (1Cx) ranged from 1.29 pg in C. duvauxii (4x) to 2.30 pg in Phonus rhiphaeus (2x). The mean 1Cx for tetraploids was lower than for diploids. For each ploidy level, genome size values of Carduncellus, Femeniasia and Phonus were found to be higher than those of Carthamus. This result is consistent with a trend frequently observed in plants, of higher genome sizes in long life cycle taxa compared to short-lived relatives.
Incorporating Multiple Observations into Logistic Regression Models of Incident Disease

We apply the delete-a-group jackknife variance estimator to a multi-wave longitudinal population-based study, the Chicago Health and Aging Project. This study examines risk factors for chronic health problems of older adults, particularly Alzheimer’s disease. Every three years, all surviving members of the study population are interviewed and a “disease-free” cohort is identified, from which a Poisson (stratified Bernoulli) sample is drawn for detailed clinical evaluation of incident disease at the next cycle. We show how multiple observations from the same individual can be incorporated into an analytic model and how the deletea-group jackknife can be used for variance estimation.
ADHERENCE TO MANAGEMENT IN PATIENTS WITH END STAGE RENAL DISEASE

Objective: To document overall adherence to haemodialysis, medications, fluid restriction and dietary prescription in patients with end-stage renal disease and to study factors that could predict poor adherence. Study Design: Cross-sectional analytical study. Place and Duration of Study: Department of Nephrology, Pak Emirates Military Hospital, Rawalpindi, from Jul to Sep 2018. Methodology: Adult patients on haemodialysis for at least three months were selected using consecutive sampling technique. Patients with acute kidney injury, patients on haemodialysis for less than 3 months, those on infrequent haemodialysis and unwilling patients were excluded. Demographic data was recorded. Adherence to management was assessed by administering End Stage Renal Disease Adherence Questionnaire in direct faceto-face interviews. Results: There were a total of 101 patients having a mean age of 51.05 ± 13.80 years. Median haemodialysis vintage was 9 months (interquartile range 3-24 months). Mean adherence scores were 970.54 ± 149.43. Mean perception scores were 7.22 ± 1.37. Only 49 (48.51%) patients had good adherence, whereas 52 (51.49%) had poor adherence to management. Increasing age was associated with poor adherence (β=-0.038; Odds Ratio=0.963, 95% CI 0.9281.000, p=0.048). No other demographic parameter could predict poor adherence. Conclusion: Non-adherence to different aspects of management plan was a significant problem, more so in younger patients.
Pattern of congenital heart diseases among children attending a pediatric cardiology OPD of a tertiary level hospital in West Bengal, India: a retrospective study

CHDs are a rapidly emerging global health problem. CHDs are defined as structural abnormalities of the heart and/or great vessels that are present at birth. These are one of the most frequently diagnosed congenital disorders with a global prevalence of approximately 0.8-1.2%. In India, the reported prevalence of CHDs has been found to be ranged between 0.04-0.9% in various studies. Although the reported prevalence of CHDs in our country seems to have increased dramatically in recent years, the prevalence is assumed to be a gross underestimation of the actual burden as many of the cases remain undiagnosed at birth and thereafter for a long duration. ABSTRACT
Influence of Rice Straw Extract and Amino Acids on the Growth, Yield and Chemical Parameters of some Crops

There is increasing concern about environmental contamination risks associated with the extensive use of mineral fertilizer in crops production. The aim of this study is to evaluate rice straw extract as natural fertilizer and suitable alternative to nitrogen mineral fertilizer. Two successive field experiments were carried out at Giza, Agricultural Research Station, during two seasons of summer and winter /2015/2016 to study the effect of rice straw extract as soil addition and soaking seed with or without amino acids on yield of maize and wheat crops. Maize and wheat seeds were soaked in aqueous solution of rice straw extract without or with amino acids for 6, 12, 24 hours. The results indicated that there are significant differences between average of grain and biological yield of maize (15.59 and 23.56 t/ha), protein yield (1934.37 kg/ha) and N, P uptake (322.97, 129.4 kg/ha) by application of rice straw extract and seed soaking for 12 hours in rice straw extract mixed with amino acids as natural fertilizer compared to nitrogen fertilizer. Contrary, maize is better adapted and produce more yield than wheat, the data regarding grain and straw yield of wheat (8.97 and 22.1 t/ha) and protein yield (1256.91 kg/ha) and N uptake (228.45 kg/ha) was observed by application of rice straw extract and seed soaking for 6 hours with rice straw extract only compared to nitrogen fertilizer. It can be concluded that rice straw extract as natural fertilizer with or without amino acids could be suitable alternative to nitrogen mineral fertilizers.
Uncorrected Proof ) Title : A Predictive Model for Emotion Recognition Based on Individual Characteristics and Autonomic Changes Running title : A Predictive Model for Emotion Recognition

Introduction: The importance of individual differences in the problem of emotion recognition has been repeatedly stated in the studies. The major concentration of this study was the prediction of heart rate variability (HRV) changes due to affective stimuli from the subject characteristics. These features were age (A), gender (G), linguality (L), and sleep (S) information. In addition, the most potent combination of individual variables (like gender and age (GA) or age, linguality, and sleep (ALS)) in the estimation of emotional HRV was explored. Methods: To this end, HRV indices of 47 college students exposed to images with four emotional categories, including happy, sad, afraid, and relaxed were analyzed. Then, a novel predictive model was introduced based on the regression equation. Results: The results showed distinctive emotional situations provoke the importance of different individual variable combinations. Generally, the most satisfactory variable arrangement in the prediction of HRV changes due to affective provocations was LS, GL, GA, ALS, and GALS. However, considering each subject separately, these combinations were changed. Conclusion: In conclusion, the suggested simple model is effective in offering new insight into the emotion studies regarding subject characteristics and autonomic parameters.
Sequential changepoint detection in classification data under label shift

Classifier predictions often rely on the assumption that new observations come from the same distribution as training data. When the underlying distribution changes, so does the optimal classification rule, and performance may degrade. We consider the problem of detecting such a change in distribution in sequentially-observed, unlabeled classification data. We focus on label shift changes to the distribution, where the class priors shift but the class conditional distributions remain unchanged. We reduce this problem to the problem of detecting a change in the one-dimensional classifier scores, leading to simple nonparametric sequential changepoint detection procedures. Our procedures leverage classifier training data to estimate the detection statistic, and converge to their parametric counterparts in the size of the training data. In simulations, we show that our method outperforms other detection procedures in this label shift setting.
Loan Loss Signaling Among Banks Competing with FinTech Firms: Evidence from Peer-to-Peer Lending

Financial technology (FinTech) companies are increasingly important to the financial system. We investigate the effect of peer-to-peer (P2P) lending on traditional banks by examining whether and how P2P lending activity in a state affects loan loss provisions among that state’s commercial banks. When borrowers take out loans from both a bank and a P2P lending platform, they become more leveraged. Banks may signal their anticipation of bad loans due to overleveraged borrowers by increasing their expected future loan losses. Using a large sample of US single-state banks from 2010 to 2018, we find that banks in states with a higher P2P lending volume report higher loan loss provisions. This positive relation is stronger for banks with greater exposure to the consumer loan market and for those with consumer borrowers who are more leveraged. Our findings show that bank managers use loan loss provisions to signal expected credit losses in response to P2P lending. We also find that P2P lending is associated with higher future loan charge-offs, which validates the signaling channel. Overall, our study offers new insight into the interaction between FinTech firms and traditional financial institutions.
Reasoning Visual Dialog with Sparse Graph Learning and Knowledge Transfer

Visual dialog is a task of answering a sequence of questions grounded in an image using the previous dialog history as context. In this paper, we study how to address two fundamental challenges for this task: (1) reasoning over underlying semantic structures among dialog rounds and (2) identifying several appropriate answers to the given question. To address these challenges, we propose a Sparse Graph Learning (SGL) method to formulate visual dialog as a graph structure learning task. SGL infers inherently sparse dialog structures by incorporating binary and score edges and leveraging a new structural loss function. Next, we introduce a Knowledge Transfer (KT) method that extracts the answer predictions from the teacher model and uses them as pseudo labels. We propose KT to remedy the shortcomings of single ground-truth labels, which severely limit the ability of a model to obtain multiple reasonable answers. As a result, our proposed model significantly improves reasoning capability compared to baseline methods and outperforms the state-of-the-art approaches on the VisDial v1.0 dataset. The source code is available at https://github.com/gicheonkang/SGLKT-VisDial.
First-principles calculations of defects in metal halide perovskites: A performance comparison of density functionals

Metal halide perovskite semiconductors have outstanding optoelectronic properties. Although these perovskites are defect-tolerant electronically, defects hamper their long-term stability and cause degradation. Density functional theory (DFT) calculations are an important tool to unravel the microscopic structures of defects, but results suffer from the different approximations used in the DFT functionals. In the case of metal halide perovskites, qualitatively different results have been reported with different functionals, either predicting vacancy or interstitial point defects to be most dominant. Here, we conduct a comprehensive comparison of a wide range of functionals for calculating the equilibrium defect formation energies and concentrations of point defects in the archetype metal halide perovskite, MAPbI$_3$. We find that it is essential to include long-range Van der Waals interactions in the functional, and that it is vital to self-consistently optimize structure and volume of all compounds involved in the defect formation. For calculating equilibrium formation energies of point defects in MAPbI$_3$ and similar metal halide perovskites, we argue that the exact values of the chemical potentials of the species involved, or of the intrinsic Fermi level, are not important. In contrast to the simple Schottky or Frenkel pictures, we find that the dominant defects are MA and I interstitials, and Pb vacancies.
Heat flow regularity, Bismut–Elworthy–Li’s derivative formula, and pathwise couplings on Riemannian manifolds with Kato bounded Ricci curvature

We prove that if the Ricci tensor Ric of a geodesically complete Riemannian manifold M , endowed with the Riemannian distance ρ and the Riemannian measure m , is bounded from below by a continuous function k : M → R whose negative part k − satisﬁes, for every t > 0 , the exponential integrability condition then the lifetime ζ x of Brownian motion X x on M starting in any x ∈ M is a.s. inﬁnite. This assumption on k holds if k − belongs to the Kato class of M . We also derive a Bismut–Elworthy–Li derivative formula for ∇ P t f for every f ∈ L ∞ ( M ) and t > 0 along the heat ﬂow ( P t ) t ≥ 0 with generator ∆ / 2 , yielding its L ∞ - Lip -regularization as a corollary. Moreover, given the stochastic completeness of M , but without any assumption on k except continuity, we prove the equivalence of lower boundedness of Ric by k to the existence, given any x, y ∈ M , of a coupling ( X x , X y ) of Brownian motions on M starting in ( x, y ) such that a.s. , holds for every s, t ≥ 0 with s ≤ t , involving the “average” k ( u, v ) := inf γ (cid:82) 1 0 k ( γ r ) d r of k along geodesics from u to v . Our results generalize to weighted Riemannian manifolds, where the Ricci curvature is replaced by the corresponding Bakry–Émery Ricci tensor.
A note on the modular representation on the $\mathbb Z/2$-homology groups of the fourth power of real projective space and its application

We write $BV_h$ for the classifying space of the elementary Abelian 2-group $V_h$ of rank $h,$ which is homotopy equivalent to the cartesian product of $h$ copies of $\mathbb RP^{\infty}. $ Its cohomology with $\mathbb Z/2$-coefficients can be identified with the graded unstable algebra $P^{\otimes h} = \mathbb Z/2[t_1, \ldots, t_h]= \bigoplus_{n\geq 0}P^{\otimes h}_n$ over the Steenrod ring $\mathcal A$, where grading is by the degree of the homogeneous terms $P^{\otimes h}_n$ of degree $n$ in $h$ generators with the degree of each $t_i$ being one. Let $GL_h$ be the usual general linear group of rank $h$ over $\mathbb Z/2. $ The algebra $P^{\otimes h}$ admits a left action of $\mathcal A$ as well as a right action of $GL_h. $ A central problem of homotopy theory is to determine the structure of the space of $GL_h$-coinvariants, $\mathbb Z/2\otimes_{GL_h}{\rm Ann}_{\overline{\mathcal A}}H_n(BV_h; \mathbb Z/2) ,$ where ${\rm Ann}_{\overline{\mathcal A}}H_n(BV_h; \mathbb Z/2) ={\rm Ann}_{\overline{\mathcal A}}[P^{\otimes h}_n]^{*}$ denotes the space of primitive homology classes, considered as a representation of $GL_h$ for all $n. $ Solving this problem is very difficult and still open for $h\geq 4. $ In this Note, our intent is of studying the dimension of $\mathbb Z/2\otimes_{GL_h}{\rm Ann}_{\overline{\mathcal A}}[P^{\otimes h}_n]^{*}$ for the case $h = 4$ and the "generic" degrees $n$ of the form $k(2^{s} - 1) + r.2^{s},$ where $k,\, r,\, s$ are positive integers. Applying the results, we investigate the behaviour of the Singer cohomological "transfer" of rank $4$, which is a homomorphism from a certain subquotient of the divided power algebra $\Gamma(a_1^{(1)}, \ldots, a_4^{(1)})$ to mod-2 cohomology groups ${\rm Ext}_{\mathcal A}^{4, 4+n}(\mathbb Z/2, \mathbb Z/2)$ of the algebra $\mathcal A. $ Singer's algebraic transfer is one of the relatively efficient tools in determining the cohomology of the Steenrod algebra.
Asset Prices with Wealth Dispersion

With overlapping generations and heterogeneous risk aversion there is no unique relation between aggregate risk aversion and the real rate of interest, and this type of endogenous “noise” cannot arise in an economy where agents live forever. Our framework accommodates many agent types and the noise emerges precisely because all (but one) consumption shares drive the economy. Adding wealth dispersion to aggregate risk aversion sufficiently summarizes the rich dynamics of the model. Consistent with the model, we construct “level” and “slope” factors that do not require knowledge about agents’ risk aversion to predict excess returns.
PolicySpace2: Modeling Markets and Endogenous Public Policies

Policymakers decide on alternative policies facing restricted budgets and uncertain, ever-changing future. Designing public policies is further difficult due to the need to decide on priorities and handle effects across policies. Housing policies, specifically, involve heterogeneous characteristics of properties themselves and the intricacy of housing markets and the spatial context of cities. We propose PolicySpace2 (PS2) as an adapted and extended version of the open source PolicySpace agent-based model. PS2 is a computer simulation that relies on empirically detailed spatial data to model real estate, along with labor, credit, and goods and services markets. Interaction among workers, firms, a bank, households and municipalities follow the literature benchmarks to integrate economic, spatial and transport scholarship. PS2 is applied to a comparison among three competing public policies aimed at reducing inequality and alleviating poverty: (a) house acquisition by the government and distribution to lower income households, (b) rental vouchers, and (c) monetary aid. Within the model context, the monetary aid, that is, smaller amounts of help for a larger number of households, makes the economy perform better in terms of production, consumption, reduction of inequality, and maintenance of financial duties. PS2 as such is also a framework that may be further adapted to a number of related research questions.
Job Displacement and Job Mobility: The Role of Joblessness

Who is harmed by and who benefits from worker reallocation? We investigate the earnings consequences of changing jobs and find a wide dispersion in outcomes. This dispersion is driven not by whether the worker was displaced, but by the duration of joblessness between job spells. Job movers who experience joblessness suffer a persistent reduction in earnings and tend to move to lower-paying firms, suggesting that job ladder models offer a useful lens through which to understand the negative consequences of job separations.