Miracle-dz/UniFAR-FTUs huggingface dataset:
IRON CHELATING ACTIVITY, PHENOL AND FLAVONOID CONTENT OF SOME MEDICINAL PLANTS FROM IRAN

Thalassemia major is characterized by anemia, iron overload, further potentiation of reactive oxygen species (ROS) and damage to major organs, especially the cardiovascular system. Antioxidant and other supportive therapies protect red blood cells (RBC) against antioxidant damage. Chelation therapy reduces iron-related complications and thereby improves quality of life and overall survival. The poor oral bioavailability, short plasma half-life and severe side effects of available chelators are still not optimal. In this study, iron chelating activity of some medicinal plants was determined to find alternative sources with lower side effects in thalassemic patients. Extracts were prepared by soaking dry material of the selected plant in appropriate solvent. Phenol and flavonoid content of the extract were measured by folin ciocalteu and AlCl3 assays. Phenol content of the extracts varied between 9 -290 mg/g. The largest amount of phenolic compounds and highest chelating activity were found in Mellilotus arvensis. All extracts contained various amount of flavonoids from 10 to 60 mg/g. Extracts with high phytochemicals and chelating activity can be observed as a good source of new agents for thalassemic patients.
Evaluation of the energy-protein balance of feed rations for Montbéliarde cows on the basis of protein and urea content in their milk

The aim of the study was to evaluate the energy-protein balance of feed rations for Montbeliarde cows on the basis of protein and urea content in their milk. In 2016 the herd numbered 319 cows, with mean yield 9,374 kg of milk. The cows were housed in a free-stall barn on deep litter and fed Total Mixed Rations (TMR), the composition of which was balanced according to Deutsche Landwirtschafts Gesellschaft (DLG) norms. The data used in the study were obtained from milk performance evaluations. It was found that only 22.9% of milk samples indicated that the cows were appropriately supplied with protein and energy. Excess protein (>3.6%) was observed in 41.4% of cases of optimum urea content, which suggests an energy surplus in the feed rations. In 3.9% of samples optimal urea content was accompanied by an insufficient protein level ( 25 kg) the tendencies were reversed, i.e. a higher percentage of samples were indicative of excessive protein (21.5-34.1%) and fewer suggested a deficit (1.6-6.7%). In the case of optimal protein and urea levels in the milk (group 5), the daily yield of the cows was 37 kg of milk. It contained 3.7% fat, 3.43% protein, 4.87% lactose and 12.6% dry matter. The cows producing milk with protein and energy levels indicating a deficiency of energy and an excess of protein in the feed rations were much more productive (group 3). Daily yield of cows whose milk had an insufficient level of urea (groups 1, 4 and 7) was much lower than in the case of the cows whose milk had too much urea (groups 3, 6 and 9). The lowest daily yield (19.5 kg), accompanied by the highest content of protein (4.02%) and dry matter (13.5%) and one of the highest levels of fat (4.16%), was noted in the group in which the protein and urea levels in the milk suggested a protein deficiency and an excess of energy in the feed. It can be concluded from the analysis that the results of milk performance evaluations regarding protein and urea levels in the milk should be given greater consideration in composing TMR feeds for various feeding groups.
Gradient-based stochastic estimation of the density matrix

Fast estimation of the single-particle density matrix is key to many applications in quantum chemistry and condensed matter physics. The best numerical methods leverage the fact that the density matrix elements $f(H)_{ij}$ decay rapidly with distance $r_{ij}$ between orbitals. This decay is usually exponential. However, for the special case of metals at zero temperature, algebraic decay of the density matrix appears and poses a significant numerical challenge. We introduce a gradient-based probing method to estimate all local density matrix elements at a computational cost that scales linearly with system size. For zero-temperature metals the stochastic error scales like $S^{-(d+2)/2d}$, where $d$ is the dimension and $S$ is a prefactor to the computational cost. The convergence becomes exponential if the system is at finite temperature or is insulating.
Stabilization of Al 3Zr Allotropes in Dilute Aluminum Alloys Via the Addition of Ternary Elements

The formation of Al 3 Zr particles within dilute aluminum alloys can contribute effectively to controlling microstructure evolution and enhancing material properties. However, the possible transformation of Al 3 Zr from its initial metastable crystal structure L1 2 into its stable, tetragonal structure D0 23 is associated with faster coherency loss and the coarsening of Al 3 Zr particles. In this regard, our study aims at identifying ternary elements that can disrupt this mechanism. For this purpose, nine ternary Al-Zr-X alloys (Er, Sc, Hf, Y, Nb, Mn, Cu, Zn and Si) plus a base alloy (Al-Zr) were produced. Isochronal aging was performed at 475 °C and 550 °C, and an investigation of the particle landscape was carried out by STEM and HR-TEM. In parallel, we conducted ab initio calculations to investigate fundamental properties of ternary AlZrX-particles such as substitution likeliness, heat of formation and transformation mechanisms. The elements investigated show various behaviors. Fewer than half of the elements (Er, Sc, Hf and Si) are found to be incorporated into Zr-rich particles to any large extent; Er and Sc exhibit the well-known core-shell structure. Y and Zn do not interfere at all with the precipitation process. Nb, Mn and Cu form particles on their own, with Zr particles often attached to them. Concerning crystal structures, all element additions except for Y and Si widen the stability regime of L1 2.
Strategy, Intellectual Capital, and Operating Performance

This study explores the relationship between intellectual capital (IC) and future operating performance under the prism of different strategic orientations (i.e., prospectors versus defender) and explanations (i.e., investing versus signaling). Our data sample consists of 11,085 firm-year observations of US listed firms for the period 2000–2019. We employed organizational capital and R&D capital as measures of a firm’s IC intensity. It seems that strategy affects the likelihood of a firm to be classified as a low or high IC intensive. Organizational capital improves future operating performance across firms with the same or with different strategic orientations. R&D capital affects primarily prospectors’ future operating performance. Depending on the measure of IC intensity or operating performance, the positive relationship between IC and future operating performance can be explained because either the IC expenditures operate as investments that improve future performance or expectations for improved future operating performance trigger increased IC expenditures.
OMQV – Objectivized Market Quality Value a Market-Based Methodology To Assess the Quality of Office Buildings

Urban managers intervene to organize and plan territorial real estate. However, in reality the quality of existing real estate remains partly unknown. It is deduced from financial estimates made by certain experts, but the literature shows such metrics to be incomplete and biased. This article draws on the theory of perceived quality to propose an objectivized, general and granular, metric of quality, integrating both the strategic aspects of quality attributes and the operational aspects of quality cues. The relative importance of each dimension was determined by surveys among stakeholders (705 professionals). The quality score thus allows a true strategic assessment of a real estate inventory. Applied to 107 buildings in the Paris region, this metric proved reliable and consistent in time and space. It was also well-aligned with financial valuations. By identifying the real components of value, it is of greater relevance to stakeholders and allows more efficient resource allocation.
Determinants of Unmanned Store Usage Intention Based on Situational Theory and the Technology Readiness Index

With the recent rapid development of information and communication technologies, numerous unmanned stores have opened worldwide. These stores have obvious advantages, such as faster checkout processes and fewer employees, cutting wage costs. The unmanned store industry was expected to boom, but some unmanned stores have failed. This industry and academia must examine the factors that attract consumers to unmanned stores. We propose an integrated model using situational factors and the technology readiness (TR) index to examine the types of customers who may be attracted to unmanned stores and their reactions to various environmental settings (situations). To verify our model, 274 valid questionnaires were distributed to BingoBox customers. The results revealed that people with a positive TR index appreciate the benefits of ease of interaction, perceived task completion, and the speed of shopping. Negative TR had a negative impact on perceived task completion.
Too Close for Comfort? Understanding Peer Effects in Large Franchised Networks

Proximity between stores in franchise networks that share the same brand is a highly contentious issue. A high-performance store may have different impacts on its proximal peer stores from a negative impact, such as potential cannibalization, to a positive impact, such as improved brand reputation or knowledge spillover. Most of the previous studies exploring the peer effects between stores in branded franchise networks emphasize only either the positive effect or the negative effect. In this paper, we consider both and seek to understand the net peer effect between each store pair in a large franchise network and how it changes with distance. We adapt an approach from spatial econometrics utilizing a weight matrix and extend it to allow for identification of both positive and negative peer effects between stores within a large-scale network. By applying our method to a large dataset from a major national fast food restaurant chain in the US, we show that the peer effects are negative between stores within 3 miles of each other, positive between stores within 3-7 miles of each other, both of which are economically significant. However, the peer effects generally diminish beyond 7 miles. These results inform individual franchisees of when they may be threatened or benefit from their proximal peer stores that share the same brand and for lawmakers to design policies to protect individual franchisees from encroachment. These results also reconcile the seemingly conflicting view of the issue in the literature and in practice. We then conduct a network analysis based on our estimated peer effects. Our network analysis results provide guidance for the franchisor on which areas they should avoid for further expansion and which stores they should prioritize to mitigate the tension between the franchisor and the franchisees.
The Effect of Recent Technological Change on US Immigration Policy

Did recent technological change, in the form of automation, affect immigration policy in the United States? I argue that as automation shifted employment from routine to manual occupations at the bottom end of the skill distribution, it increased competition between natives and immigrants, consequently leading to increased support for restricting low-skill immigration. I formalise this hypothesis theoretically in a partial equilibrium model with constant elasticity of substitution in which technology leads to employment polarization, and policy makers can vote on immigration legislation. I empirically evaluate these predictions by analysing voting on low-skill immigration bills in the House of Representatives during the period 1973-2014. First, I find evidence that policy makers who represent congressional districts with a higher share of manual employment are more likely to support restricting low-skill immigration. Second, I provide empirical evidence that representatives of districts which experienced more manual-biased technological change are more likely to support restricting low-skill immigration. Finally, I provide evidence that this did not affect trade policy, which is in line with automation having increased employment in occupations exposed to low-skill immigration, but not those exposed to international trade.
The Impact of Assurance Quality and Level on Cybersecurity Risk Management Program on Non-Professional Egyptian Investors’ Decisions: An Experimental Study

The objective of this study is to examine and analyze the impact of assurance quality (measured by the size of the audit firm performing this assurance; Big4 auditor vs. non-Big4) and assurance level (reasonable vs. limited assurance) on cybersecurity risk management program on non-professional investors’ willingness to invest and their stock valuation. To fulfil the research objective, a 2X2 between-subjects experiment was designed to test the research hypotheses. Based on a sample of 64 MBA and postgraduate students in the Faculty of Commerce, Alexandria University and ESLSCA University, the researcher found evidence that high assurance quality (Big4 auditor) and reasonable assurance level conveyed in the assurance report on cybersecurity risk management program have a significant and positive effect on investors’ willingness to invest and their stock valuation. However, the researcher didn’t find significant difference in investors’ willingness to invest or their stock valuation in case a limited assurance report is offered by a Big4 audit firm in comparison with the case of a reasonable assurance report offered by a non-Big4 audit firm. This study adds an experimental evidence to the literature on non-audit services and cybersecurity and will help in reducing the accounting research gap related to cybersecurity risk management program, which is consistent with the Egyptian government’s efforts and attention paid to cybersecurity and its related risks.
The Macroeconomic Effects of Universal Basic Income Programs

What are the consequences of a nationwide reform of a transfer system based on means-testing toward one of unconditional transfers? I answer this question with a quantitative model to assess the general equilibrium, inequality, and welfare effects of substituting the current US income security system with a universal basic income (UBI) policy. To do so, I develop an overlapping generations model with idiosyncratic income risk that incorporates intensive and extensive margins of the labor supply, on-the-job learning, and child-bearing costs. The tax-transfer system closely mimics the US design. I calibrate the model to the US economy and conduct counterfactual analyses that implement reforms toward a UBI. I find that an expenditure-neutral reform has moderate impacts on agents’ labor supply response but induces aggregate capital and output to grow due to larger precautionary savings. A UBI of $1,000 monthly requires a substantial increase in the tax rate of consumption used to clear the government budget and leads to an overall decrease in the macroeconomic aggregates, stemming from a drop in the labor supply. In both cases, the economy has more equally distributed disposable income and consumption. The UBI economy constitutes a welfare loss at the transition if it is expenditure-neutral and results in a gain in the second scenario.
Why Do So Many MPs Lose their Seats in PNG?

Multiple regressions are used to assess the relative significance of a number of political and social variables that might be associated with the likelihood of sitting MPs retaining or losing their seats in the 85 partially rural open electorates of Papua New Guinea (PNG). The tests reveal that the most significant of the variables for which we have reasonably accurate measures is the amount of ministerial power accrued by sitting members, either over the previous term of parliament or at the time when they stand for re-election. MPs who have spent more of the past parliamentary term in more powerful ministerial roles are less likely to lose their seats in the next election. Also significant, though less so, is a second political variable. This is the level of political competition in each electorate, as measured by the average number of candidates challenging the incumbents. Incumbents are more likely to lose their seats in electorates where more candidates have typically stood for election. Relationships between the rate of MP turnover and the social variables selected for inclusion in this analysis appear to be quite weak or entirely non-existent, but the evidence does indicate that the rate of turnover has little if anything to do with the level of ‘development’ in each electorate, and is certainly no higher in electorates with higher levels of linguistic diversity than it is in electorates with greater linguistic uniformity.
Recourse as Shadow Equity: Evidence from Commercial Real Estate Loans

We study the role that recourse plays in the commercial real estate loan contracts of the largest U.S. banks. We find that recourse is valued by lenders and is treated as a substitute for conventional equity. At origination, recourse loans have rate spreads that are at least 20 basis points lower and loan-to-value ratios that are around 3 percentage points higher than non-recourse loans. Dynamically, recourse affects loan modification negotiations by providing additional bargaining power to the lender. Recourse loans were half as likely to receive accommodation during the COVID-19 pandemic, and the modifications that did occur entailed a relatively smaller reduction in payments.
A Comparative Assessment of Cost Income Ratio of Scheduled Urban Cooperative Banks in India: Benchmarking the Operational Efficiency

In a highly competitive environment, operational efficiency is an important factor for the survival of any organisation and banks are no exception. A comparative assessment of Cost Income Ratio (CIR) shows that the behaviour of CIR and its relationships with other vital financial parameters of scheduled Urban Co-operative Banks (UCBs) in India is different from that of the commercial banks. Unlike commercial banks, gross non-performing assets (GNPA) and the proportion of assets other than investments and advances to the total assets show a significant positive correlation with the CIR in case of scheduled UCBs, and hence, these impact their operating efficiency. In contrast to commercial banks, scheduled UCBs have higher wage CIR than non-wage CIR. While their wage CIR is negatively correlated with asset size, non-wage CIR is found positively correlated with asset size. Scheduled UCBs in the asset class of ₹ 5000 crores to ₹ 10000 crores (100 crores = 1 billion) show better cost-efficiency. Optimization of asset size emerges as an important aspect of economies of scale and cost-efficiency for these banks. We find that a suitable benchmark for CIR of scheduled UCBs lies in the range of 0.45 to 0.55, which requires an average improvement of about 25% from its present level.
Bayesian VARs and prior calibration in times of COVID-19

Abstract This paper investigates the ability of several generalized Bayesian vector autoregressions to cope with the extreme COVID-19 observations and discusses their impact on prior calibration for inference and forecasting purposes. It shows that the preferred model interprets the pandemic episode as a rare event rather than a persistent increase in macroeconomic volatility. For forecasting, the choice among outlier-robust error structures is less important, however, when a large cross-section of information is used. Besides the error structure, this paper shows that the standard Minnesota prior calibration is an important source of changing macroeconomic transmission channels during the pandemic, altering the predictability of real and nominal variables. To alleviate this sensitivity, an outlier-robust prior calibration is proposed.
Equations of state and phase boundary for stishovite and CaCl2-type SiO2

Abstract Silica is thought to be present in the Earth’s lower mantle in subducting plates, in addition to being a prototypical solid whose physical properties are of broad interest. It is known to undergo a phase transition from stishovite to the CaCl2-type structure at ~50–80 GPa, but the exact location and slope of the phase boundary in pressure-temperature space is unresolved. There have been many previous studies on the equation of state of stishovite, but they span a limited range of pressures and temperatures, and there has been no thermal equation of state of CaCl2-type SiO2 measured under static conditions. We have investigated the phase diagram and equations of state of silica at 21–89 GPa and up to ~3300 K using synchrotron X-ray diffraction in a laser-heated diamond-anvil cell. The phase boundary between stishovite and CaCl2-type SiO2 can be approximately described as T = 64.6(49)·P – 2830(350), with temperature T in Kelvin and pressure P in GPa. The stishovite data imply K0′$\begin{array}{} K_0^{'} \end{array} $ = 5.24(9) and a quasi-anharmonic T2 dependence of −6.0(4) × 10−6 GPa·cm3/mol/K2 for a fixed q = 1, γ0 = 1.71, and K0 = 302 GPa, while for the CaCl2-type phase K0 = 341(4) GPa, K0′$\begin{array}{} K_0^{'} \end{array} $ = 3.20(16), and γ0 = 2.14(4) with other parameters equal to their values for stishovite. The behaviors of the a and c axes of stishovite with pressure and temperature were also fit, indicating a much more compressible c axis with a lower thermal expansion as compared to the a axis. The phase transition between stishovite and CaCl2-type silica should occur at pressures of 68–78 GPa in the Earth, depending on the temperature in subducting slabs. Silica is denser than surrounding mantle material up to pressures of 58–68 GPa, with uncertainty due to temperature effects; at higher pressures than this, SiO2 becomes gravitationally buoyant in the lower mantle.
Stochastic scrabble: large deviations for sequences with scores

A derivation of a law of large numbers for the highest-scoring matching subsequence is given. Let Xk, Yk be i.i. d. q=(q(i)) i∊S letters from a finite alphabet S and v=(v(i)) i∊S be a sequence of non-negative real numbers assigned to the letters of S. Using a scoring system similar to that of the game Scrabble, the score of a word w=i 1 · ·· im is defined to be V(w)=v(i 1) + · ·· + v(im ). Let Vn denote the value of the highest-scoring matching contiguous subsequence between X 1 X 2 · ·· Xn and Y 1 Y 2 · ·· Yn. In this paper, we show that Vn/K log(n) → 1 a.s. where K ≡ K(q , v). The method employed here involves ‘stuttering’ the letters to construct a Markov chain and applying previous results for the length of the longest matching subsequence. An explicit form for β ∊Pr(S), where β (i) denotes the proportion of letter i found in the highest-scoring word, is given. A similar treatment for Markov chains is also included. Implicit in these results is a large-deviation result for the additive functional, H ≡ Σ n < τ v(Xn ), for a Markov chain stopped at the hitting time τ of some state. We give this large deviation result explicitly, for Markov chains in discrete time and in continuous time.