Miracle-dz/UniFAR-FTUs huggingface dataset:
Inline quality rating of multi‐crystalline wafers based on photoluminescence images

The quality assessment of multi‐crystalline and high‐performance multi‐crystalline silicon wafers during incoming inspection of solar cell production requires a reproducible description of the relevant material defects and a classification scheme that is capable to rate as‐cut wafers from unknown manufacturers. Both needs are addressed in this work. We introduce an image processing framework that allows the various types of crystallization‐related defects visible in photoluminescence images to be detected quantitatively and thus enables a complete wafer description in terms of defects. The importance of different features within this defect characteristic is weighted by predicting the open‐circuit voltage of solar cells with aluminum back‐surface field as well as passivated emitter and rear cells with a stepwise extension of the model. The resulting robust classification scheme is successfully evaluated on a set of 7500 wafers, which represents the whole spectrum of material types and qualities that are currently available at the market. A comparison of defect signatures in high‐performance multi‐crystalline and standard multi‐crystalline silicon materials underlines the relevance of additional features. As a result of this paper, we show that a regularized version of multi‐linear regression models for quality prediction can optimize simpler linear models by adding selected features to the defect characteristic leading to mean absolute prediction errors of 2.2 mV for solar cells with aluminum back‐surface field and 2.9 mV for passivated emitter and rear cells solar cells in a true blind test. Copyright © 2015 John Wiley & Sons, Ltd.
Synthesis of Cyclic Carbonate From Carbon Dioxide and Epoxide Using Amino Acid Ionic Liquid Under 1 atm Pressure

Herein, we report an effective synthesis of cyclic carbonates by cycloaddition of carbon dioxide to epoxide using a modified amino acid ionic liquid as catalyst under 1 atm pressure. With triethylamine as co-catalyst, the catalytic activity of the l-proline based ionic liquid was greatly enhanced, and up to 97 % isolated yield of cyclic carbonate was achieved at 90°C under atmospheric pressure without organic solvent and metal component.
Antiinflammatory activity of leaf extracts of Kalanchoe crenata Andr

Objective: To evaluate the acute and chronic antiinflammatory properties of leaf extracts of Kalanchoe crenata in rats. Material and methods: The methylene chloride/methanol extract of K. crenata was extracted by using hexane, methylene chloride, ethyl acetate, and n-butanol. The antiinflammatory profile of these extracts was investigated on the basis of paw edema induced by carrageenan. The n-butanol fraction (most potent) was further assessed through acute inflammatory models induced by histamine, serotonin, and formalin. The chronic antiinflammatory and the ulcerogenic activities of the n-butanol fraction were also examined. Results: The oral administration of n-butanol fraction (600 mg/kg) caused a maximum inhibition of about 45% in paw edema induced by carrageenan. The n-butanol fraction also exhibited acute antiinflammatory activity on paw edema induced by histamine (47.51%), serotonin (54.71%), and formalin-(40.00%) . In the chronic inflammation model, this extract showed maximum inhibition of 61.26% on the ninth day of treatment. The ulcerogenic assessment showed that ulcer indices after oral treatment with n-butanol fraction were zero and 0.4±0.2, for the 300 and 600 mg/kg doses, respectively. Conclusion: On the basis of these findings, it may be inferred that K. crenata is an antiinflammatory and antiarthritic agent that blocks histamine and serotonin pathways. The results are in agreement with the traditional use of the plant in inflammatory conditions.
Application-based Evaluation of Automatic Terminology Extraction

The aim of this paper is to evaluate performance of several automatic term extraction methods which can be easily utilized by translators themselves. The experiments are conducted on German newspaper articles in the domain of politics on the topic of Brexit. However, they can be easily replicated on any other topic or language as long as it is supported by all three tools used. The paper first provides an extensive introduction into the field of automatic terminology extraction. Next, selected terminology extraction methods are assessed using precision with respect to the gold standard compiled on the same corpus. Moreover, the corpus has been completely annotated to allow for the calculation of recall. The effects of using five cut-off points are examined in order to find an optimal value which should be used in translation practice.
Opinion Mining and Sentiment Analysis on DEFT

 Abstract — Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte ( DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.
Polynomially Bounding the Number of Minimal Separators in Graphs: Reductions, Sufficient Conditions, and a Dichotomy Theorem

A graph class is said to be tame if graphs in the class have a polynomially bounded number of minimal separators. Tame graph classes have good algorithmic properties, which follow, for example, from an algorithmic metatheorem of Fomin, Todinca, and Villanger from 2015. We show that a hereditary graph class $\mathcal{G}$ is tame if and only if the subclass consisting of graphs in $\mathcal{G}$ without clique cutsets is tame. This result and Ramsey's theorem lead to several types of sufficient conditions for a graph class to be tame. In particular, we show that any hereditary class of graphs of bounded clique cover number that excludes some complete prism is tame, where a complete prism is the Cartesian product of a complete graph with a $K_2$. We apply these results, combined with constructions of graphs with exponentially many minimal separators, to develop a dichotomy theorem separating tame from non-tame graph classes within the family of graph classes defined by sets of forbidden induced subgraphs with at most four vertices.
Calculations of electorn inelastic mean free paths. II. Data for 27 elements over the 50–2000 eV range

We report calculations of electron inelastic mean free paths (IMFPs) for 50–2000 eV electrons in a group of 27 elements (C, Mg, Al, Si, Ti, V, Cr, Fe, Ni, Cu, Y, Zr, Nb, Mo, Ru, Rh, Pd, Ag, Ta, W, Re, Os, Ir, Pt, Au and Bi). This work extends our previous calculations (Surf. Interface Anal. 11, 57 (1988)) for the 200–2000 eV range. Substantial variations were found in the shapes of the IMFP versus energy curves from element to element over the 50–2000 eV range and we attribute these variations to the different inelastic scattering properties of each material. Our calculated IMFPs wee fitted to a modified form of the Bethe equation for inelastic electron scattering in matter; this equation has four parameters. These four parameters could be empirically related to several material parameters for our group of elements (atomic weight, bulk density and number of valence electron per atom). IMFPs and those initially calculated was 13%. The modified Bethe equation and our expressions for the four parameters can therefore be used to estimate IMFPs in other materials. The uncertainties in the algorithm used for our IMFP calculation are difficult to estimate but are believed to be largely systematic. Since the same algorithm has been used for calculating IMFPs, our predictive IMFP formula is considered to be particularly useful for predicting the IMFP dependence on energy in the 50–2000 eV range and the material dependence for a given energy.
Personalized Book Recommendation System using Machine Learning Algorithm

As the amounts of online books are exponentially increasing due to COVID-19 pandemic, finding relevant books from a vast e-book space becomes a tremendous challenge for online users Personal recommendation systems have been emerged to conduct effective search which mine related books based on user rating and interest Most of these existing systems are user-based ratings where content-based and collaborativebased learning methods are used These systems' irrationality is their rating technique, which counts the users who have already been unsubscribed from the services and no longer rate books This paper proposed an effective system for recommending books for online users that rated a book using the clustering method and then found a similarity of that book to suggest a new book The proposed system used the K-means Cosine Distance function to measure distance and Cosine Similarity function to find Similarity between the book clusters Sensitivity, Specificity, and F Score were calculated for ten different datasets The average Specificity was higher than sensitivity, which means that the classifier could re-move boring books from the reader's list Besides, a receiver operating characteristic curve was plotted to find a graphical view of the classifiers' accuracy Most of the datasets were close to the ideal diagonal classifier line and far from the worst classifier line The result concludes that recommendations, based on a particular book, are more accurately effective than a user-based recommendation system © 2021, International Journal of Advanced Computer Science and Applications All Rights Recerved
Influence of tungstate ion dopants in corrosion protection behavior of polyaniline coating on mild steel

Electropolymerization of polyaniline (PANI) and polyaniline‐tungstate (PANIW) coatings on mild steel were successfully performed using cyclic voltammetry technique. Processes were carried out in aqueous electrolyte solutions of 0.3 M oxalic acid + 0.1 M aniline and 0.3 M oxalic acid + 0.1 M aniline + 0.001 M sodium tungstate dehydrate. Corrosion protection of PANI and PANIW coatings was evaluated with the help of open circuit potential (Eocp) monitoring and electrochemical impedance spectroscopy (EIS) methods. All the results reveal the influence of additional doping agent (i.e., tungstate) in corrosion protection behavior of PANI coating.
X-Ray crystal structures , 1 H NMR investigation of ligand fluxional behavior and EPR studies

Chromium(III)-pyrazole complexes. X-Ray crystal structures, H NMR investigation of ligand fluxional behavior and EPR studies Jessica M. López Plá, Athanassios K. Boudalis, Joshua Telser, and Raphael G. Raptis* Department of Chemistry and Biochemistry, Florida International University, 11200 SW 8th Str. , Miami, FL, 33199-0001, USA. Propriétés Optiques & Magnétiques des Architectures Moléculaires (POMAM), Institut de Chimie UMR 7177 / Université de Strasbourg 4, rue Blaise Pascal / CS 90032, F-67081 STRASBOURG CEDEX. [c] Department of Biological, Physical and Health Sciences, Roosevelt University, 430 S. Michigan Avenue, Chicago, Illinois 60605, USA.
Detecting and categorizing Android malware with graph neural networks

Android is the most dominant operating system in the mobile ecosystem. As expected, this trend did not go unnoticed by miscreants, and quickly enough, it became their favorite platform for discovering new victims through malicious apps. These apps have become so sophisticated that they can bypass anti-malware measures implemented to protect the users. Therefore, it is safe to admit that traditional anti-malware techniques have become cumbersome, sparking the urge to come up with an efficient way to detect Android malware. In this paper, we present a novel Natural Language Processing (NLP) inspired Android malware detection and categorization technique based on Function Call Graph Embedding. We design a graph neural network (graph embedding) based approach to convert the whole graph structure of an Android app to a vector. We then utilize the graphs' vectors to detect and categorize the malware families. Our results reveal that graph embedding yields better results as we get 99.6% accuracy on average for the malware detection and 98.7% accuracy for the malware categorization.
A quantitative assessment of economic impact of trade wars and the ‘Make in India’ program

In a unique attempt, our paper aims to provide a quantitative economic assessment of the impact of “Make in India”, a flagship program for industrialization, launched by the Government of India in 2014, combining it with the global trade war of 2017-18. We analyze whether the expected favourable impact of the former was reversed due to its reactive policies compared its pro-active policies, and whether it worsened due to the trade war, whose effects continue to aggravate in a post-COVID recalibration of global supply chains. The question assumes significance as Make in India program's proactive measures to boost investment may have a favourable impact on the industries at large in terms of output and employment. In contrast, its protectionist measures involving tariff barriers may have an ambiguous effect on the same. We utilize an applied general equilibrium analysis, exploring the impact of Make in India and the global trade war in a combined way. Our results suggest that the combined effects of both policies, while being beneficial for the Indian economy, yields negative ramifications for exports, jobs, and investment growth. Specific sectors are also unable to increase domestic output despite being a part of Make in India, such as the Chemical, Rubber, and Plastics industries, and those that use it as raw materials.
Assessment of Acute Pancreatitis Using CT Severity Index and Modified CT Severity Index

Quick Response Code Abstract: To assess the severity of acute pancreatitis (AP) using computed tomography (CT) severity index (CTSI) and modified CT severity index (MCTSI), to correlate with clinical outcome measures, and to assess concordance with severity grading, as per the revised Atlanta classification (RAC). Material and Methods: This is a prospective and descriptive study conducted in the Department of Radiology at a Maheshwara Medical College. A total of 50 patients enrolled with the chief complaint of epigastric pain, nausea and vomiting and CECT abdomen were suggestive of acute pancreatitis were included in this study. Assessment of severity of acute pancreatitis was done in all cases by Balthazar CTSI scoring and Mortele Modified CTSI scoring. Results: In our study total 50 cases of acute pancreatitis cases were included in the study. Out of 50 cases, 36 (72 %) were male and 13 (26%) were females. We found that acute pancreatitis was found three times more common in males than in females. Cholelithiasis was found to be most common aetiological factor for acute pancreatitis in 48% cases followed by alcoholic pancreatitis was seen in 26% of cases. Least Aetiological factor such as Trauma and drug induced. Pleural effusion was the most common extra-pancreatic complication, 27 patients (54%). Left pleural effusion was more common than the right, and in none of the cases, isolated right sided pleural effusion was found. Ascites was the second most common complication seen in 9 patients (18%). Conclusion: In conclusion CECT was found to be an excellent imaging modality for diagnosis, establishing the extent of disease process and in grading its severity. The Modified CT Severity Index is a simpler scoring tool and more accurate than the Balthazar CT Severity Index. In this study, it had a stronger statistical correlation with the clinical outcome, be it the length of hospital stay, development of infection and occurrence of organ failure. It could also predict the need for interventional procedures.
Thyroglobulin may affect telomerase activity in thyroid follicular cells

Telomerase (TA) activity is known to be present in malignant tumor cells, but not in most somatic differentiated cells. TA shows relatively high activity in thyroid cancer cells, but reports vary. This fact prompted us to elucidate whether cell component inhibitors of TA in the thyroid follicles can modulate its activity. The activity of TA extracted from Hela cells was inhibited by mixing with the supernatant fraction of human thyroid tissue extract. To examine the effect of iodine, thyroid hormones (ℓ-T3 and ℓ-T4) and human thyroglobulin (hTg) contained in the thyroid follicles, ℓ-T3, ℓ-T4 and hTg were added to the TRAP assay system in vitro, using TA from Hela cells. Iodine, ℓ-T3 and ℓ-T4 did not affect TA activity, but hTg inhibited the TA activity in a dose-dependent manner (IC50 of hTg: ca 0.45 μM: inhibiting concentration of hTg was from 0.15 μM to 3.0 μM). The hTg inhibition was not evident in the RT-PCR system, suggesting no effect of hTg on Taq DNA polymerase activity. The hTg inhibition of TA activity was attenuated by dNTP but not significantly by TS primer. These data suggest that hTg contained in thyroid follicular cells of various thyroid diseases may affect the TA activity measured in biopsied thyroid specimens, and that the reduction of the TA activity by hTg may induce slow progression and growth, and low grade malignancy of thyroid cancer, particularly differentiated carcinoma.
ACUTE & PERIOPERATIVE PAIN SECTION Blood Dehydroepiandrosterone and Dehydroepiandrosterone Sulfate as Pathophysiological Correlates of Chronic Pain: Analyses Using a National Sample of Midlife Adults in the United States

Objective. Identifying biomarkers is a priority in translational chronic pain research. Dehydroepiandrosterone (DHEA) and its sulfated form, DHEA-S, are adrenocortical steroids in the blood with neuroprotective properties that also produce sex hormones. They may capture key sex-specific neuroendocrine mechanisms of chronic pain. Design. Crosssectional study. Methods. Using data from 1,216 community-dwelling adults aged 34–84 from the Midlife in the United States (MIDUS) cohort, we examined blood DHEA and DHEA-S levels in association with chronic pain in men and women, adjusting for demographics, chronic diseases, medications including opioids, and psychosocial factors. If an association was found, we further explored dose-response relationships by the number of pain locations and the degree of pain interference. Results. In women, chronic pain was associated with 0.072 lower (95% confidence interval [CI], –0.127 to –0.017) log10 DHEA-S mg/dL, with pain in one to two locations associated with 0.068 lower (95% CI, –0.131 to –0.006) and in three or more locations 0.071 lower (95% CI, –0.148 to 0.007) log10 DHEA-S (P for trend 1⁄4 0.074). Furthermore for women, low-interference pain was associated with 0.062 lower (95% CI, –0.125 to –0.000), whereas high-interference pain was associated with 0.138 lower (95% CI, –0.233 to –0.043) log10 DHEA-S (P for trend 1⁄4 0.004). Chronic pain was not associated with DHEA or DHEA-S levels in men or DHEA levels in women. Conclusions. Chronic pain and its functional interference correspond to lower blood DHEA-S levels in women.
Effect of ionic liquid on the crystallization kinetics behaviour of polymer poly(ethylene oxide)

Modification in the crystallization kinetics behaviour of the polymer poly(ethylene oxide) due to the incorporation of an ionic liquid (1-butyl-3-methylimidazolium hexafluorophosphate; BMIMPF6) has been studied. The PEO + x wt% BMIMPF6 polymer films were prepared by a solution casting technique. Crystallization kinetic parameters, such as relative crystallinity (Xt), crystallization half time (t1/2), crystallization rate constant (K), crystallization rate (G) and Avrami exponents (n), have been determined by both isothermal and non-isothermal techniques using DSC. The experimental results based on both non-isothermal and isothermal methods show that the melt crystallization of PEO slows down significantly with the incorporation of BMIMPF6 in the membranes. The growth of crystallized spherulites has also been monitored by polarizing optical microscope (POM), which confirms that the growth rate of crystallized spherulites slows down on the addition of BMIMPF6 in the polymeric membranes.
Decomposition and Nutrient Release from Litter Fall in the Semi‐arid Tropics of Sudan

In Sudan, tree plantations remain the first choice and are widely used in protecting arable lands from sand movement. Decomposition and nutrient changes from leaves of some agroforestry trees (Eucalyptus microtheca, Ficus spp., and Leucaena leucocephala) and litter fall from guava (Psidium guajava) and mango (Magnifera indica) were monitored (in a 12‐week litter‐bag experiment). Rate of dry‐matter weight loss from guava (0.098 wk−1) was significantly (P < 0.01) faster than from mango residues (0.04 wk−1). Corresponding values for Leucaena, Eucalyptus, and Ficus were 0.0533, 0.0524, and 0.0438 wk−1, respectively. In general, micronutrients tend to accummulate during a decomposition period. Potassium (K) was the only element found to be consistently lost by leaching very rapidly from all litters. Nitrogen (N) was released at a significantly (P < 0.03) higher rate from Leucaena (0.0558 wk−1) compared to Ficus (0.0399 wk−1) and Eucalyptus (0.0301 wk−1). Mobility of nutrients from the litters was in the order of K > phosphorus (P) = N > calcium (Ca) > magnesium (Mg). It is concluded that ficus and mango leaves are suitable for improving quality of arid soils through buildup of soil organic matter and supplying easily released organic sulfur (S) (environmentally sound management practice) whereas litter from guava is suitable for temporary nutrient correction. Mixing of guava and mango residues may slow fast decomposition of the former.
Securitization of the Coronavirus Crisis in Jordan: Successes and Limitations | The Washington Institute

Jordan has chosen to sharply prioritize public health (https://www.washingtoninstitute.org/fikraforum/view/Jordan-response-COVID19-pandemic-Middle-East) of people's lives at the expense of the economy, despite Jordan’s difficult economic conditions reflected by its high unemployment rates, huge debts, low economic growth, and economic stagnation. Due to an early shutdown and one of the strongest reactions in the region, the number of cases and deaths in Jordan is still small, with (562) cases registered and 9 deaths as of May 11. The state has gone on to address the economic consequences of this decision and take care of the Jordanian people, especially those who are economically disadvantaged, such as day laborers and self-employed workers.
Reactive ion etching for microelectrical mechanical system fabrication

The suitability of reactive ion etching for the fabrication of microelectro mechanical systems (MEMS) has been evaluated by characterizing the change of lateral dimensions versus depth in etching deep structures in silicon. Fluorine, chlorine, and bromine containing gases have provided the basis for this investigation. A conventional planar RIE (reactive ion etching) reactor has been used, in some cases with magnetic field enhancement or an inductive coupled plasma source and low substrate temperature. For RIE based on Cl2 or Cl2/HBr plasma a slightly ‘‘positive’’ (top wider than bottom) slope is achieved when etching structures with a depth of several 10 μm, whereas a ‘‘negative’’ slope is obtained when etching with an SF6 /CCl2F2‐based plasma. A pattern transfer with vertical walls is obtained for RIE based on SF6 (with O2 added) when maintaining the substrate at low temperature (≊−70 °C). Further optimization of plasma chemistries and RIE procedures should result in runouts on the order of 0.1/100 μm d.