Miracle-dz/UniFAR-FTUs huggingface dataset:
Production and Purification of an Optimized Osteopontin Peptide for Use in Vascular Calcification Treatment Studies

We have previously shown that native, full length murine osteopontin (OPN), an anti-calcific protein, was able to prevent vascular calcification (VC) in a uremic mouse model. An optimized murine bioactive and bioengineered N-terminal OPN peptide (mnOPN), is being investigated as a preventative and as a treatment to reverse VC. The goal of the present study was to produce 5 mg of purified, recombinant mnOPN by subcloning mnOPN cDNA into a pQE-30 vector, transforming SURE 2 E. coli, and purifying by nickel-nitrilotriacetic acid (NiNTA) column method. Identity was confirmed by SDS-PAGE and western blots using anti-OPN and anti-His primary antibodies. The initial purification process yielded a non-optimal product. This process was further refined and a time-course was conducted. A three hour growing period after IPTG induction was determined to be optimal. In future studies, the purified recombinant bacterial mnOPN will be used in preclinical mouse studies of VC.
Did you offend me? Classification of Offensive Tweets in Hinglish Language

The use of code-switched languages (e.g., Hinglish, which is derived by the blending of Hindi with the English language) is getting much popular on Twitter due to their ease of communication in native languages. However, spelling variations and absence of grammar rules introduce ambiguity and make it difficult to understand the text automatically. This paper presents the Multi-Input Multi-Channel Transfer Learning based model (MIMCT) to detect offensive (hate speech or abusive) Hinglish tweets from the proposed Hinglish Offensive Tweet (HOT) dataset using transfer learning coupled with multiple feature inputs. Specifically, it takes multiple primary word embedding along with secondary extracted features as inputs to train a multi-channel CNN-LSTM architecture that has been pre-trained on English tweets through transfer learning. The proposed MIMCT model outperforms the baseline supervised classification models, transfer learning based CNN and LSTM models to establish itself as the state of the art in the unexplored domain of Hinglish offensive text classification.
Review of Inflatable Booms for Deployable Space Structures: Packing and Rigidization

Inflatable structures offer the potential of compactly stowing lightweight structures, which assume a fully deployed state in space. An important category of space inflatables are cylindrical booms, which may form the structural members of trusses or the support structure for solar sails. Two critical and interdependent aspects of designing inflatable cylindrical booms for space applications are i) packaging methods that enable compact stowage and ensure reliable deployment, and ii) rigidization techniques that provide long-term structural ridigity after deployment. The vast literature in these two fields is summarized to establish the state of the art.
Effectiveness of an Educational Program on Nurses’ Knowledge Concerning Medication Error at Teaching Hospital in AL-Nasiriyah City

Background: Medication errors are the main factors endangering the patient safety. Patient safety is a significant challenge facing health care system today. The aim of this study was to assess the effectiveness of educational program on nurses' knowledge concerning medication error to reduce medication errors. Methods: A quasi-experimental in the bigger teaching hospital in ALNasiriyah city during period between 12 February2017 to 25th April 2017 have been build up the program by the researcher in order study shamble, a non-probability "purposive sample" of (180) nurse were working in AL-Nasiriyah city hospitals ,It is collected from medical ,surgical , emergency department and intensive care unit (90) nurses to control study 90 to study group. divided in to two groups (90) study group and (90) control group. Data were collected by utilizing the following Structure Questionnaire to assess nurses’ knowledge concerning medication errors contain the demographic data , general basic information about medication and Ten drug right it is composed from 39 questions. Then Reliability of the Instrument and Validity of the Study Instrument by the experts
Joint quantum-state and measurement tomography with incomplete measurements

Estimation of quantum states and measurements is crucial for the implementation of quantum information protocols. The standard method for each is quantum tomography. However, quantum tomography suffers from systematic errors caused by imperfect knowledge of the system. We present a procedure to simultaneously characterize quantum states and measurements that mitigates systematic errors by use of a single high-fidelity state preparation and a limited set of high-fidelity unitary operations. Such states and operations are typical of many state-of-the-art systems. For this situation we design a set of experiments and an optimization algorithm that alternates between maximizing the likelihood with respect to the states and measurements to produce estimates of each. In some cases, the procedure does not enable unique estimation of the states. For these cases, we show how one may identify a set of density matrices compatible with the measurements and use a semi-definite program to place bounds on the state's expectation values. We demonstrate the procedure on data from a simulated experiment with two trapped ions.
Optical Design and Engineering IV

In this work a vectorized and parallel version of the Finite-Difference Time-Domain method (FDTD) is applied to Volume Holographic Gratings (VHG) and Thin-Film Filters (TFF). In particular, in this work gratings with a grating period vector forming an arbitrary angle with the perpendicular to the plane of incidence are analyzed. Angular and wavelength selectivity are obtained by means of the normalized diffraction efficiency. These parameters are positively compared with experimental values and also with analytical closed expressions, thus validating our method. Furthermore, analysis of the performance of the parallel method is shown obtaining a severe improvement with respect to the classical version of the FDTD method. This improvement of the algorithm provides a feasible and accurate scheme for simulating a wide range of optical devices.
Effect of Cooking Temperature and Time Period on Phytochemical Content and in vitro Antioxidant and Anti-Inflammatory Activity of the Leaf Extracts of Typhonium trilobatum ( A Less Focussed Edible Herbal Plant )

The effect of cooking temperature(100-180oc) and contact time (10-30min) on the leaf extract of Typhonium trilobatum (Kharkol) was explored for phytochemical profile and in vitro antioxidant activity. The overall objective of this study was to assess the changes in phenolic content and antioxidant and anti-inflammatory activity of T. trilobatum during heating. Methodology: At each time/temperature combination, total phenolic content, total flavanoid content, total tannin content, DDPH, Hydroxyl (OH), ABTS radical scavenging assay, total antioxidant capacity assay, FRAP assay, Lipid peroxidation inhibition assay, Albumin denaturation assay were analysed. Results: Large diversity in phytochemicals content and antioxidant activity were found with temperature and time variation in comparison to crude extract (unheated). Heating increases total phenolic and antioxidant as well as anti-inflammatory capacity of the sample by liberating the phenolic compounds from their esterified or glycosylated bound form On heating at high temperature, which is relevant to domestic frying 150180 oc for 30 min, the leaves showed highest polyphenol (194.86±25.07 mg GAE/DE), flavonoids (61.28±2.99 GAE/DE) and tannin (46.77±1.30 GAE/DE) content. Conclusion: In major cases significant increase in (in vitro) antioxidant capacity is observed on heating at 150oc for 10 min. So domestic cooking at this temperature seemed to be optimum for maximum utilization of its antioxidant or disease preventing capacity.
Gr upSM Newly Diagnosed Patients with Type 2 Diabetes Mellitus Reveal Different Lipid Pattern

Patients with type 2 diabetes mellitus are having the typical form of atherogenic dyslipidemia. This dyslipidaemia type is typically present with the increase of triglyceride levels, de-crease of HDL-cholesterol and small increase of LDL-cholesterol levels (predominantly with small dense LDL-particles). The prognostic importance of this type of atherogenic dyslipidae-mia is of the increase of the risk of atherothrombosis.
Factors Behind International Relocation and Changes in Production Geography in the European Automobile Components Industry

This article analyses business strategies in the automobile sector to determine the key factors behind production relocation processes in automobile components suppliers. These factors help explain changes in production geography in the sector not only in terms of location advantages but also from a perspective of corporate strategies and decision-making mechanisms within firms. The results obtained from an empirical study in Spain during the period 2001-2008 show how the components sector has used relocation to meet the requirements for efficiency imposed by automobile manufacturers. The search for lower labour costs, production concentration and specialisation in order to obtain economies of scale and improved productivity are found to be the main factors determining relocation in the sector. These processes are facilitated by the operational flexibility of the multinational firms that dominate the sector which allows them to transfer resources internationally. Lean supply, technological requirements for production processes and the integration of production plants in the institutional environment are the main barriers to such processes of mobility, and may also determine the geographical destination of migrated production.
An Unlikely cause of Atrial Fibrillation-induced Cardiomyopathy: Phentermine, a diet pill

We present a case of an unusual cause of atrial fibrillation-induced cardiomyopathy, which is a diet pill, known as phentermine. This medication used for weight loss and can function as a stimulant is intended for short-term use but when taken for an extensive period of time can become a significant risk factor for developing arrhythmias such as atrial fibrillation.
State Abstraction Synthesis for Discrete Models of Continuous Domains

Reinforcement Learning (RL) is a paradigm for enabling autonomous learning wherein rewards are used to influence an agent’s action choices in various states. As the number of states and actions available to an agent increases, so it becomes increasingly difficult for the agent to quickly learn the optimal action for any given state. One approach to mitigating the detrimental effects of large state spaces is to represent collections of states together as encompassing “abstract states". State abstraction itself leads to a host of new challenges for an agent. One such challenge is that of automatically identifying new abstractions that balance generality and specificity; the agent must identify both the similarities and the differences between states that are relevant to its goals, while ignoring unnecessary details that would otherwise hinder the agent’s progress. We call this problem of identifying useful abstract states the Abstraction Synthesis Problem (ASP). State abstractions can provide a significant benefit to modelbased agents by simplifying their models. T-UCT, a hierarchical model-learning algorithm for discrete, factored domains, is one such method that leverages state abstractions to quickly learn and control an agent’s environment. Such abstractions play a pivotal role in the success of T-UCT; however, T-UCT’s solution to ASP requires a fully discrete state space. In this work we develop and compare enhancements to T-UCT that relax its assumption of discreteness. We focus on solving ASP in domains with multidimensional, continuous state factors, using only the T-UCT agent’s limited experience histories and minimal knowledge of the domain’s structure. Finally, we present a new abstraction synthesis algorithm, RCAST, and compare this algorithm to existing approaches in the literature. We provide the algorithmic details of RCAST and its subroutines, and we show that RCAST outperforms earlier approaches to ASP by enabling T-UCT to accumulate significantly greater total reward with minimal expert configuration and processing time.
Student Food Data Analysis System

In today's society where science and technology is rapidly developing, the level of information is increasing year by year, and the canteen needs to change the status quo to provide students with quality food service. Combine the dietary data that can be collected in the canteen with big data to reduce waste and improve the quality of students' diet. Based on the current situation of the need for student canteens, this paper describes the concept of smart canteen construction, and introduces the i-plates big data analysis system—the system of collecting information based on single-chip RFID technology, python data analysis and computer-side information display; Based on the dietary data, the students' nutrition and health information is generated through data analysis and delivered to students and parents through the webpage, thus promoting the common development of both students and canteens.
2 A Methodology for Assessing International Efficiency

This chapter is structured in three parts. The first part outlines the methodological steps, involving both theoretical and empirical work, for assessing whether an observed allocation of resources across countries is efficient. The second part applies the methodology to the long-run allocation of capital and consumption in a large cross section of countries. We find that countries that grow faster in the long run also tend to save more both domestically and internationally. These facts suggest that either the long-run allocation of resources across countries is inefficient, or that there is a systematic relation between fast growth and preference for delayed consumption. The third part applies the methodology to the allocation of resources across developed countries at the business cycle frequency. Here we discuss how evidence on international quantity comovement, exchange rates, asset prices, and international portfolio holdings can be used to assess efficiency. Overall, quantities and portfolios appear consistent with efficiency, while evidence from prices is difficult to interpret using standard models. The welfare costs associated with an inefficient allocation of resources over the business cycle can be significant if shocks to relative country permanent income are large. In those cases partial financial liberalization can lower welfare.
Chapters ILR Collection 2006 Groups , Teams , and the Division of Labor — Interdisciplinary Perspectives on the Organization of Work

The purpose of this chapter is to survey and critique this varied landscape of research on groups at work, drawing out common themes and selective weaknesses with the goal of suggesting a more synthetic and informed future agenda. Our discussion is not encyclopedic, but rather focused on three quite different research traditions: those based in psychology, in industrial relations, and in critical sociology. We outline the intellectual landscape of each case and highlight areas of agreement and disagreement. We argue that this project of cross-disciplinary theory building encounters substantial challenges, but is rich in potential. These traditions differ in their theoretical assumptions, research questions and methods, and outcomes of interest. Nonetheless, we suggest that building a more multi-disciplinary research agenda is worthwhile and conclude with suggestions for further work in this direction.
Line-by-line Femtosecond FBG Inscription for Innovative Fiber Lasers

We report the fabrication of fiber Bragg gratings (FBGs) in passive as well as doped fibers utilizing the femtosecond laser line-by-line technique. Narrow-linewidth linear gratings as well as broadband chirped gratings were inscribed into silica- and fluoride-glass optical fibers. Polarization-dependent characteristics of non-tilted and of 45°-tilted gratings are analyzed and the possibility of direct inscription into coated (i.e. non-stripped) fibers is demonstrated.
Downscaling Daily Temperature with Evolutionary Artificial Neural Networks

The spatial resolution of climate data generated by general circulation models (GCMs) is usually too coarse to present regional or local features and dynamics. State of the art research with Artificial Neural Networks (ANNs) for the downscaling of GCMs mainly uses back-propagation algorithm as a training approach. This paper applies another training approach of ANNs, Evolutionary Algorithm. The combined algorithm names neuroevolutionary (NE) algorithm. We investigate and evaluate the use of the NE algorithms in statistical downscaling by generating temperature estimates at interior points given information from a lattice of surrounding locations. The results of our experiments indicate that NE algorithms can be efficient alternative downscaling methods for daily temperatures.
Minimum Wages and the Distribution of Family Incomes

There is robust evidence that higher minimum wages increase family incomes at the bottom of the distribution. The long-run (3 or more years) minimum wage elasticity of the non-elderly poverty rate with respect to the minimum wage ranges between −0.220 and −0.459 across alternative specifications. The long-run minimum wage elasticities for the tenth and fifteenth unconditional quantiles of family income range between 0.152 and 0.430 depending on specification. A reduction in public assistance partly offsets these income gains, which are on average 66 percent as large when using an expanded income definition including tax credits and noncash transfers. (JEL D31, I32, I38, J31, J38)
Distribution of carbonic anhydrase IX, MN/CA IX, in normal and neoplastic gastrointestinal and hepatobiliary tissues : its potential value as a new biomarker and comparison of its expression with that of isoenzymes I, II, IV, V, and VI

The carbonic anhydrase (CA) gene family contains eleven active members, the basic physiological functions of which are linked to the interconversion of carbon dioxide and bicarbonate (CO2 + H2O <=> H+ + HCO3<=> H2CO3). They participate in a variety of physiological processes that involve pH regulation, CO2 and HCO3 transport and water and electrolyte balance, and some new functions have also been suggested recently. A novel tumour-associated antigen, MN, containing a CA-domain and named MN/CA IX, has been found to promote cell proliferation when transfected into NIH3T3 cells and has also been shown to be a potential biomarker for neoplasia in the uterine cervix. The present study examines the expression of MN/CA IX in the normal alimentary tract by immunohistochemistry and compares it with the expression of cytoplasmic CA I, CA II, apical plasma membrane associated CA IV and secretory CA VI. The distribution of mitochondrial CA V is examined by immunohistochemistry and Western blotting. The value of MN/CA IX as a potential biomarker of gastrointestinal tumours is assessed in a series of colorectal and hepatobiliary neoplasms. A positive immunoreaction for MN/CA IX was detected in the basolateral plasma membrane of the gastric, intestinal and biliary epithelium, but was confined to the proliferating cryptal enterocytes in the human gut, suggesting a role in cellular proliferation. In colorectal tumours, MN/ CA IX immunoreaction was also located in the proliferative zone, indicating that it could be a useful marker of cellular proliferation. In the case of hepatobiliary tumours a positive signal was mainly associated with tumours of biliary epithelial parentage. These results demonstrate that MN/CA IX has a unique expression pattern in the alimentary tract relative to other CAs. Its localization and enzymatic properties suggest that it may have a dual function in the gastrointestinal epithelium. Through its CA activity it could participate in the regulation of carbon dioxide/bicarbonate homeostasis, while its localization to the basolateral surfaces of proliferating cryptal enterocytes suggests that it may serve as a ligand or receptor for one or more other proteins that regulate intercellular communication and/or cell proliferation. MN/ CA IX may also serve as a new biomarker of gastrointestinal tumours.
A Spatial View of Ensemble Spread in Convection Permitting Ensembles

With movement toward kilometer-scale ensembles, new techniques are needed for their characterization. A new methodology is presented for detailed spatial ensemble characterization using the fractions skill score (FSS). To evaluate spatial forecast differences, the average and standard deviation are taken of the FSS calculated over all ensemble member‐member pairs at different scales and lead times. These methods were found to give important information about the ensemble behavior allowing the identification of useful spatial scales,spinuptimesforthemodel,andupscalegrowthoferrorsandforecastdifferences.Theensemblespread was found to be highly dependent on the spatial scales considered and the threshold applied to the field. High thresholds picked out localized and intense values that gave large temporal variability in ensemble spread: local processes and undersampling dominate for these thresholds. For lower thresholds the ensemble spread increases with time as differences between the ensemble members upscale. Two convective cases were investigated based on the Met Office United Model run at 2.2-km resolution. Different ensemble types were considered: ensembles produced using the Met Office Global and Regional Ensemble Prediction System (MOGREPS) and an ensemble produced using different model physics configurations. Comparison of the MOGREPS and multiphysics ensembles demonstrated the utility of spatial ensemble evaluation techniques for assessing the impact of different perturbation strategies and the need for assessing spread at different, believable, spatial scales.