Miracle-dz/UniFAR-FTUs huggingface dataset:
Levels of selected heavy metals in some brands of Cigarettes marketedin University of Port Harcourt, Rivers State.

Four commonly smoked brands cigarette from Abuja campus in the University of Port Harcourt were randomly sampled and analyzed for heavy metals using Atomic Adsorption Spectrometry (AAS). The brands include Benson and Hedges, Rothmans, Dorchester, and St. Moritz. The results of the analysis indicated that the concentration of Zn was found to be in range of 27.48-64.29mgkg-1, Cu had 11.27-13.28mgkg-1, and Cd was 0.53-0.59mgkg-1. Pb was found in the range of 5.22-7.99mgkg-1, Mn concentrations were in the range of 87.42-106.22mgkg-1, and the values for Fe were in the range of 167.49-230.47mgkg-1 while Cr and Ni levels were in the range of 16.82-25.99mgkg-1 and 2.65-4.67mgkg-1 respectively. Iron concentrations were highest in all the brands compared to the other metals; while the cadmium concentration was lowest in all the four brands cigarette analyzed. Generally the levels of content of the metals in all the brands except Zinc were high compared with the WHO threshold values. In addition to emphasizing the danger of cigarette smoking, the results highlighted the heavy metals toxicity potential of each brand of cigarette
How to observe, describe and evaluate innovation and change?

: Using the results of a research-assessment about an international project of innovative schools, this paper addresses some questions raised by the educational innovation, especially when relying on ICT to promote change. How to define the innovative process? Could ICT be a vector of innovative learning practices? How to ensure that the ability to change is considered as a key competence for all educational actors? How can we support and accompany innovation in learning? How to describe and evaluate pedagogical innovation?
REITs as Lessees

Operating leases of REITs primarily take the form of sale-leaseback transactions and are largely ignored as an alternative source of financing in the REIT financing literature. This study examines the determinants of operating lease intensity of REITs. Using a sample of 172 unique REITs that report non-missing operating lease information between 1990 and 2017, we document that, consistent with existing corporate leasing research, operating lease intensity tends to be higher for REITs that are smaller, have lower leverage, and have better investment opportunities. However, contrary to corporate leasing studies, tax liabilities are found to positively relate to operating lease intensity of REITs. We argue that this is caused by the potential tax benefits the lessee receives from sale-leaseback transactions. In addition, financial distress and contracting costs have no significant effect on the tendency to lease. Lastly, we document that REITs use leasing as a substitute to debt financing.
Frequency of Costovertebral and Costotransverse Osteoarthritis in the Schroeder Mounds Site

Schroeder Mounds (11HE177) is a late Late Woodland mortuary site (AD 900-1100) located on the bluffs of Henderson County, Illinois. There is little contextual information available about the site, therefore skeletal analysis is critical to understanding the health and behavior of the people buried there. The Schroeder Mounds osteological sample is exceptionally well preserved and is well-suited to a paleopathological assessment of costovertebral and costotransverse joint surfaces. Osteoarthritis (OA) was identified by reactive changes to the joint surfaces (pitting, osteophytic remodeling of joint margins) on adult individuals (N = 28) classified by sex and age group and scored by severity. Out of this sample, 96% (27/28) had costotransverse and/or costovertebral osteoarthritis. There were no sex differences in the prevalence of osteoarthritis and severity was not consistent with simple age-related degenerative changes. There was a pattern of extensive osteoarthritis on the 6th, 7th, 8th, and 11th and 12th ribs and the 1st, 11th, and 12th thoracic vertebrae. Based on clinical data, respiratory stress may have been a factor involved in the prevalence of osteoarthritis, but a previous assessment of the visceral surfaces of the ribs does not support a population experiencing such stress. An alternative cause, supported by previous examinations of vertebral degenerative changes and the presence of cases of os acrominale, Cervical osteoarthritis, and Baastrup's disease suggest load bearing activities (e.g., tump line) and labor-related postures may have contributed to this osteoarthritis. However, more comparative osteoarchaeological research and clinical research is needed to assess the causative or synergistic role(s) of bronchial infection and mechanical stress.
Household Savings and Monetary Policy under Individual and Aggregate Stochastic Volatility

In this paper, we study household consumption-saving and portfolio choices in a heterogeneousagent economy with sticky prices and time-varying total factor productivity and idiosyncratic stochastic volatility. Agents can save through liquid bonds and illiquid capital and shares. With rich heterogeneity at the household level, we are able to quantify the impact of uncertainty across the income and wealth distribution. Our results help us in identifying who wins and who loses when during periods of heightened individual and aggregate uncertainty. To study the importance of heterogeneity in understanding the transmission of economic shocks, we use a deep learning algorithm. Our method preserves non-linearities, which is essential for understanding the pricing decisions for illiquid assets. JEL Classification: N/A Keywords: Machine Learning, deep learning, neural network, HANK, Heterogeneous Agents Yuriy Gorodnichenko ygorodni@econ.berkeley. edu UC Berkeley and CEPR Lilia Maliar lmaliar@gc.cuny. edu The Graduate Center, CUNY, CEPR and CEPR Serguei Maliar smaliar@scu.edu Santa Clara University Christopher Naubert cnaubert@gradcenter.cuny. edu The Graduate Center, CUNY Acknowledgements The authors are grateful to Marc Maliar for his help with writing the TensorFlow code. Powered by TCPDF (www.tcpdf.org) Household Savings and Monetary Policy under Individual and Aggregate Stochastic Volatility Yuriy Gorodnichenkoy Lilia Maliarz Serguei Maliarx Christopher Naubert { December 25, 2020 Abstract We study a heterogeneous-agent model with sticky-prices in which total factor productivity and individual productivity are subject to stochastic volatility shocks. Agents save through liquid bonds and illiquid capital and shares. To construct equilibrium, we use a deep learning algorithm. Our method preserves non-linearities, which is essential for understanding portfolio choices. With rich heterogeneity at the household level, we are able to quantify the impact of uncertainty across the income and wealth distribution. We nd that persistent high levels of uncertainty increase wealth inequality, and that in response to a contractionary monetary policy shock, illiquid wealth inequality decreases and liquid wealth inequality increasesWe study a heterogeneous-agent model with sticky-prices in which total factor productivity and individual productivity are subject to stochastic volatility shocks. Agents save through liquid bonds and illiquid capital and shares. To construct equilibrium, we use a deep learning algorithm. Our method preserves non-linearities, which is essential for understanding portfolio choices. With rich heterogeneity at the household level, we are able to quantify the impact of uncertainty across the income and wealth distribution. We nd that persistent high levels of uncertainty increase wealth inequality, and that in response to a contractionary monetary policy shock, illiquid wealth inequality decreases and liquid wealth inequality increases
Efficient Integral Equation-Based Propagation Modelling for Radio Coverage Prediction

This study exhaustively explores integral equation based propagation modeling techniques for electromagnetic waves and tries to improve upon the existing models by providing a method that includes the backscattering electric field as well. All the methods discussed have the computational complexity of the order of the square of the number of integral intervals (groups in FExM) as opposed to the basic algorithm (Exact method) which has a computational complexity of the order of the cube of integral intervals. It is explained that how these modeling methods can be used in conjunction with a Radio Environment Map (REM) aided Cognitive Radio Network (CRN) to implement the 5G efficiently by enabling the Dynamic Spectrum Access (DSA), to get past the limitations of traditional static spectrum allocation. The predictions are made using all the models on the most commonly used and gently undulated ‘Hadsund’ terrain profile and on more rugged ‘German’ terrain profile. All the models work equally well on the ‘German’ terrain profile as they did on the ‘Hadsund’ terrain profile. The predictions made using these models are in sync with that of the state of the art Okumura-Hata model. This study als0 addresses the problem of localization of the non-cooperative transmitter using signal strength measurements based on the Reciprocity Theorem and produces the results accurate to around 147 meters, upon a random selection of the locations of three pair of transceivers. This localization method is a huge improvement over existing signal strength measurements based methods in terms of computational complexity, with highly accurate results. This study also provides a detailed roadmap for the future scope of improvement on the limitations of the study such that sufficient accuracy and execution times can be achieved.
Electrical and optical properties of hydrogen-related complexes and their interplay in ZnO

The commercial breakthrough of ZnO-based devices is hampered mainly by the unipolar n-type conductivity of this material. Hydrogen, which is known to form both electrically active and inactive complexes in ZnO, is considered as a main cause of this behavior. However, the existing literature is incomplete and partly contradictory. The object of the present thesis is a comprehensive investigation of the properties of two hydrogen-induced shallow donors HBC and HO, the hydrogen molecule H2, and a hydrogen-related defect, which gives rise to local vibrational modes (LVMs) at 3303 and 3320 cm−1 in ZnO and their interaction. The defects are characterized by Raman spectroscopy, infrared absorption spectroscopy, photoconductivtity (PC) and photoluminescence measurements. Based on the PC technique, a novel and highly sensitive spectroscopic approach is established, which is applicable for probing LVMs in strongly absorbing spectral regions. This technique enables the detection of the local modes of HO at 742 and 792 cm−1 in the neutral charge state. In consequence, earlier theoretical predictions regarding the microscopic structure of this shallow donor can be verified. In Raman measurements the electronic 1s → 2s transition of HO is identified at 273 cm−1. This quantity is found to blueshift with the HO defect concentration. A similar blueshift of the 1s → 2s(2p) donor transition of HBC is assigned to local lattice strain which was generated during high temperature processes. A Raman study of the H2 molecule covers its formation, stability, lattice position and interplay with the ZnO host. In particular, the role of H2 for the continuous generation of HO and HBC, and the related n-type behavior is elaborated. The analysis unambiguously confirms that the so-called “hidden hydrogen” species is indeed H2. Moreover, the observation of the ortho-paraconversion process and the coupling to the host phonons contribute to a general understanding of H2 in semiconductors. Experimental results of the LVMs of 3303 and 3320 cm−1 in conjunction with model calculations yield an underlying defect containing three hydrogen atoms. This complex Y–H3 exhibits two configurations, which differ only in the orientation of one chemical bond. The findings are consistent equally with a zinc vacancy decorated with three hydrogen atoms and an ammonia molecule, respectively. Earlier models proposed in the literature are discarded.
The Effects of Paracetamol on the Liver and Kidney Functions of a Rat Model Following Prolonged Alcohol Administration

Objectives: Despite the potential health risks, Paracetamol is commonly misused for management of hangover among regular users of alcohol. Studies on the combined use of the two drugs are limited and controversial. The aim of this study was to evaluate the effects of the interaction of the two drugs on the biological parameters of a rat model. Methods: Animals were divided into twelve groups. The negative and positive controls received distilled water and alcohol, respectively. Alcohol was administered at 2.5, 3.5 and 4.5 g/kg orally for 4 weeks. Paracetamol was given at doses of 40 and 400 mg/kg. Half of the other groups received combined doses of the two drugs. Hematological and blood chemistry were determined using auto-analyzers while histostructure was scored under light microscopy. Results: Alcohol induced a dose and time dependent gain on body weight, but when used in combination with paracetamol the effect was mixed. When used independently and combined, the drugs did not affect (p>0.05) the hematological profiles. For blood chemistry, the drugs caused a dose dependent elevation of liver enzymes, bilirubin, urea, reduced albumin levels and various degrees of liver and renal pathology. Conclusion: In moderate doses, Paracetamol is safe but high doses and chronic use of alcohol causes hepatotoxicity. Individually, alcohol and Paracetamol have a low risk of renal damage but when used together the risk is increased. Thus, regular use of Paracetamol in management of alcohol induced hangover is discouraged as this increases the risk of liver and kidney diseases.
Unilateral Action under an Emissions Cap

Cap-and-trade programs where multiple jurisdictions agree on a common cap such as the European Union's Emission Trading Scheme (EU ETS) face the challenge of how to accommodate di erent levels of ambition with respect to carbon mitigation, and respective preferences about technology pathways. Jurisdictions that value marginal bene ts of mitigation above the average level have an incentive to take additional unilateral action, which has two important consequences: First, if the cap is binding, more mitigation in one jurisdiction would lead to less mitigation in other jurisdictions (waterbed e ect). Second, unilateral action will reduce the price of allowances, leading to even higher motivation by environmental advocates for additional action, i.e. it creates a negative feedback on allowance prices. This could over time lead to a situation where inactive jurisdictions are more and more freed from their obligation to contribute to the public good provision. Both e ects could endanger the integrity of cap and trade as a mechanism for cooperation, undermining stakeholder con dence and potentially putting its durability at stake. The EU ETS may be nearing such a state. In this paper, we investigate a price oor for allowances implemented as an minimum auction (reserve) price as a remedy to the waterbed e ects. Using a numerical electricity market model (LIMES-EU) we investigate how such a price oor, implemented by a coalition or all EU-countries, compares to a reference case where the price is strictly determined by the demand for allowances and the emissions cap. We examine the impacts of a price oor on allowance prices, emission quantities, as well as auction revenues and consumer and producer surplus in each member state. We consider related distributional outcomes, such as potential gains for inactive member states that would potentially oppose a respective reform at the EU level. Findings show that a minimum price starting at 25 ¿/t in 2020 and rising at 5% per year would substantially alleviate the waterbed e ect from the coal phase out policies envisioned in several EU member states, in particular in Germany. It implies withholding 3.9 Gt of allowances until 2050 in addition to the amount of allowances invalidated from the Market Stability Reserve (MSR) in 2023 as a result of the recent EU ETS reform. Implementing such a price oor creates both winners and losers, but overall e ects are relatively small in magnitude and auction revenues increase for all member states. This indicates the availability of a number of options for creating a political coalition adopting such a scheme. (*) Corresponding author: michael.pahle@pik-potsdam.de (a) Potsdam Institute for Climate Impact Research, Telegraphenberg A 56, 14473 Potsdam, Germany. (b) Resources for the Future, 1616 P St. NW, Suite 600, Washington, DC 20036, USA. (c) Mercator Research Institute on Global Commons and Climate Change, Torgauer Str. 12-15, 10829 Berlin, Germany. (d) Hertie School of Governance, Friedrichstraÿe 180, 10117 Berlin, Germany. (e) Technische Universität Berlin, Straÿe des 17. Juni 145, 10623 Berlin, Germany.
Performance of three molecular tests for SARS-CoV-2 on a university campus estimated jointly with Bayesian latent class modeling

Accurate tests for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been critical in efforts to control its spread. The accuracy of molecular tests for SARS-CoV-2 has been assessed numerous times, usually in reference to a gold standard diagnosis. One major disadvantage of that approach is the possibility of error due to inaccuracy of the gold standard, which is especially problematic for evaluating testing in a real-world surveillance context. We used an alternative approach known as Bayesian latent class modeling (BLCM), which circumvents the need to designate a gold standard by simultaneously estimating the accuracy of multiple tests. We applied this technique to a collection of 1,716 tests of three types applied to 853 individuals on a university campus during a one-week period in October 2020. We found that reverse transcriptase polymerase chain reaction (RT-PCR) testing of saliva samples performed at a campus facility had higher sensitivity (median: 0.923; 95% credible interval: 0.732-0.996) than RT-PCR testing of nasal samples performed at a commercial facility (median: 0.859; 95% CrI: 0.547-0.994). The reverse was true for specificity, although the specificity of saliva testing was still very high (median: 0.993; 95% CrI: 0.983-0.999). An antigen test was less sensitive and specific than both of the RT-PCR tests. These results suggest that RT-PCR testing of saliva samples at a campus facility can be an effective basis for surveillance screening to prevent SARS-CoV-2 transmission in a university setting.
COVID 19 accelerator of changes in the readiness of university teachers to use distant learning technologies

The article describes the experience of the Belgorod State University (BelSU) in organizing the educational process during the forced transition to full distant learning due to COVID-19. The authors present the results of the study of changes in the readiness of the university faculty to use distant learning technol-ogies. Many years of experience in the use of digital educational technologies, the availability of a well-developed distant learning system, and a high degree of provision of the educational process with electronic educational resources al-lowed BelSU to restructure the educational process in a short time. The results of the study show that the forced transition to distant learning had a beneficial effect on the readiness of teachers to use distant learning technologies, changed their attitude to new approaches in the organization of the educational process. © 2021 CEUR-WS. All rights reserved.
Development of Surface Roughness Model in Turning Process of 3X13 Steel Using TiAIN Coated Carbide Insert

Surface roughness that is one of the most important parameters is used to evaluate the quality of a machining process. Improving the accuracy of the surface roughness model will contribute to ensure an accurate assessment of the machining quality. This study aims to improve the accuracy of the surface roughness model in a machnining process. In this study, Johnson and Box-Cox transformations were successfully applied to improve the accuracy of surface roughness model when turning 3X13 steel using TiAlN insert. Four input parameters that were used in experimental process were cutting velocity, feed rate, depth of cut, and insert-nose radius. The experimental matrix was designed using Central Composite Design (CCD) with 29 experiments. By analyzing the experimental data, the influence of input parameters on surface roughness was investigated. A quadratic model was built to explain the relationship of surface roughness and the input parameters. Box-Cox and Johnson transformations were applied to develop two new models of surface roughness. The accuracy of three surface roughness models showed that the surface roughness model using Johnson transformation had the highest accuracy. The second one model of surface roughness is the model using Box-Cox transformation. And surface roughness model without transformation had the smallest accuracy. Using the Johnson transformation, the determination coefficient of surface roughness model increased from 80.43 % to 84.09 %, and mean absolute error reduced from 19.94 % to 16.64 %. Johnson and Box-Cox transformations could be applied to improve the acuaracy of the surface roughness prediction in turning process of 3X13 steel and can be extended with other materials and other machining processes
Facile synthesis of a highly SERS active nanosilver sol using microwaves and its application in the detection of E. coli using Victoria blue B as a molecular probe

A rapid and green microwave procedure was developed to synthesize highly surface-enhanced Raman scattering (SERS) active silver nanoparticles (AgNPs), using diethanolamine as a reducing agent, that had a surface plasmon resonance (SPR) absorption peak at 444 nm and a resonance Rayleigh scattering (RRS) peak at 450 nm, and a new SERS enhancement mechanism was proposed for the AgNPs–NaCl–AgNO3 system. Bacteria, which were stained using Victoria blue B (VBB), possess the characteristics of a SERS molecular probe in the AgNP sol substrate, with a strong SERS peak at 1611 cm−1 and a peak intensity linear to E. coli concentration in the range of 5 × 106 to 3 × 109 colony forming units per mL (cfu mL−1). This new, simple, rapid and sensitive SERS quantitative analysis method was used for detecting E. coli in real samples.