Miracle-dz/UniFAR-FTUs huggingface dataset:
Effectiveness of Self – Instruction Strategy in Improving Word Recognition Skills for Students With Learning Disabilities

The purpose of this study was to identify the effectiveness of self – instruction strategy in improving word recognition skills for Students with Learning Disabilities (SLD) at Najran in the Kingdom of Saudi Arabia. The sample of the study consisted of (14) SLD; it was divided randomly into two equal groups: control and experimental. The students in the experimental group have studied the word recognition skills by self – instruction strategy; however, the students in the control group were received their teaching by the conventional method. The word recognition skills test was applied for two groups as pre-test and post-test. Results showed the effectiveness of self – instruction strategy in improving word recognition skills for SLD in favor of the students in the experimental group.
Design of PI Controller for Voltage Controller of Four-Phase Interleaved Boost Converter Using Particle Swarm Optimization

This article introduces voltage feedback controlling using the PI controller tuned gains by metaheuristic optimizations for a four-phase interleaved boost converter. The metaheuristic optimizations, particle swarm optimization (PSO), genetic algorithm (GA), and Tabu search (TS) are applied to find the optimal gains for the proposed control system. In experiment, the designed control system is implemented on the DSP board TMS320F28335 with MATLAB/Simulink. In this paper, there are two conditions of the control system in the test, without load and with load. The response result of the proposed control system tuned gains by PSO is no overshoot and approaches to the steady state better than GA and TS methods. Moreover, it is able to maintain the output voltage feedback at a constant level according to the control signal both without load and with load conditions. As a result, the four-phase interleaved boost converter is regulated by the PI controller tuned gains with PSO which could efficiently maintain the voltage of both levels.
A self-calibrating and learning control system for non-invasive continuous perioperative blood pressure measurement

State-of-the-art non-invasive blood pressure measurement devices according to Riva-Rocci only allow for non-continuous measurements every few minutes. This paper presents a non-invasive system that can measure the blood pressure continuously. The system contains a pressure control loop as well as an Iterative Learning Control loop. The pressure controller initially performs a calibration procedure to adapt itself to different pressure dynamics. Furthermore, time-scale transformation is applied for the Iterative Learning Control to enable the system to deal with varying heart rates. The mentioned system properties render it well suited for blood pressure monitoring during surgery.
Effects of non-invasive ventilation in subjects undergoing cardiac surgery on length of hospital stay and cardiac-pulmonary complications: a systematic review and meta-analysis

Background Cardiac surgery often leads to pulmonary complications. Non-invasive ventilation (NIV) is a mechanical ventilation modality that may help to prevent the pulmonary complications, and the role of the prophylactic use of NIV in patients after cardiac surgery remains controversial. Methods We searched PubMed, Embase, Web of Science and Cochrane Central for randomized controlled trials comparing the use of NIV (continues positive airway pressure or bi-level positive airway pressure) with standard treatment in post-cardiac surgery subjects without language restriction. Two investigators screened the eligible studies up to July, 2019. Meta-analysis using random effect model or fixed effect model was conducted for pulmonary complications, mortality, rate of reintubation and cardiac complications, and mean difference (MD) or standard mean difference for length of hospital stay and length of ICU stay. Results We included nine randomized controlled trails with 830 subjects. The use of NIV failed to reduce the risk of pulmonary complications, including atelectasis [risk rate (RR) 0.60; 95% confidence interval (CI): 0.28 to 1.28, P=0.19] and pneumonia (RR 0.27; 95% CI: 0.05 to 1.64, P=0.16). However, it has shortened the length of ICU stay (MD −1.00 h, 95% CI: −1.38 to −0.63, P<0.00001) and the length of hospital stay (MD −1.00 d, 95% CI: −1.12 to −0.87, P<0.00001). NIV also failed to reduce the rate of reintubation (RR 0.68; 95% CI: 0.21 to 2.26, P=0.53) or the risk of cardiac complications (RR 0.81; 95% CI: 0.59 to 1.13, P=0.22). Conclusions The prophylactic use of NIV immediately in post-cardiac subjects who underwent cardiac surgery might be able to shorten the length of hospital stay and the length of ICU stay, but it has no significant effect on pulmonary complications, rate of reintubation or cardiac complications.
Hierarchy of Trade and Experience as an Exporter∗

Trade models à la Melitz predict a hierarchy of trade. However, Eaton et al. (2011) shows that firms do not enter markets according to a hierarchy. The present article aims to reassess the empirical and theoretical tenets of this hierarchy of trade. First, we reveal that the fact that firms obey a hierarchy of trade strongly depends on their experience as exporters. Firms export to different markets when they are young exporters, while, conditional on survival and over time, they tend to export to the same ordered set of countries. In so doing, we reconcile Melitz’s prediction with Eaton et al. (2011): the conclusion of an absence of hierarchy made by Eaton et al. (2011) is valid in the short run, whereas firms come closer to Melitz’s prediction the longer they have been exporters. Thus, we argue that what we observe in the data is not a drawback but a snapshot of the convergence toward the Melitz’s prediction. Second, we develop a unified model that explains the evidence outlined above. We offer a new class of export choice models in which firms always export to different sets of markets in the short run, whereas the strategies of firms tend to stick more to a hierarchy over time. We demonstrate that this result is due to a baseline competition effect that is present in any model with monopolistic competition. In particular, we identify a new firms’ self-selection effect based on a trade-off between accessibility and competition. JEL Classification: F1
VISUAL 2017

—This work presents a new architecture for creating virtual assistants on personal computers, building upon prior work on deep learning neural networks, image processing, mixed-initiative systems, and recommender systems. Recent progress in virtual assistants enables them to converse with users and interpret what the user sees. These systems can understand the world in intuitive ways with neural networks, and make action recommendations to the user. The assistant architecture in this work is described at the component level. It interprets a computer screen image in order to produce action recommendations to assist the user. It can assist in automating various tasks such as genetics research, computer programming, engaging with social media, and legal research. The action recommendations are personalized to the user, and are produced without integration of the assistant into each individual application executing on the computer. Recommendations can be accepted with a single mouse click by the computer user.
Dissecting FDI ?

This paper investigates the importance of firm heterogeneity for our understanding of the aggregate volume of cross-country multinational sales. The volume of multinational sales is a function of both the number of multinational affiliates active in each market and the average sales of these affiliates. Using the firm level data of the Deutsche Bundesbank, we show that most of variation of the aggregate volume of multinational sales is due to variation in the number of firms participating in the market.
Horizontal or Backward? FDI Spillovers and Industry Aggregation

Preliminary draft As the empirical evidence on FDI spillovers is mixed, this study explores the importance of the level of industry aggregation, the ownership structure and two computational issues in the capture of spillover effects. A Romanian firm-level panel data set extracted from the Amadeus database is used and input-output tables are taken from the Romanian National Statistical Office (at the nace2-digit and the nace3-digit level). Estimation results suggest that vertical spillovers are primarily found if the level of sectoral aggregation declines, whereas horizontal spillovers are present at higher levels of aggregation. The distinction between majority and minority foreign-owned affiliates is crucial, as this affects FDI spillovers. Including or excluding inputs supplied within the same industry seems to affect results. Controlling for final uses and exports has a small influence on spillover effects. JEL Classification: F23
Optimized Cylindrical Diffuser Powers for Interstitial PDT Breast Cancer Treatment Planning: A Simulation Study

Purpose It is well known that interstitial photodynamic therapy (iPDT) of large tumors requires effective planning to ensure efficient delivery of therapeutic dose to the target tumors. This should be achieved in parallel with minimal damage to the nearby intact tissues. To that end, clinical iPDT can be attained using cylindrical diffusing optical fibers (CDFs) as light sources. In this work, we optimize output CDF powers in order to deliver a prescribed light dose to a spherical volume such as a tumor node. Methods Four CDFs are placed vertically inside the tumor node. The fluence rate is calculated using the diffusion equation. Therapeutic target dose is (20-50) J·cm−2. The optical properties (μa = 0.085 cm−1, μs′ = 16 cm−1) of a breast tumor and the treatment time of 150 sec are used to calculate the fluence rate. Results For four CDFs, the therapeutic target dose (20-50) J·cm−2 is delivered to more than 90%. This is the ratio of the total points that receive the target dose in proportion to the total points in the volume of the node of 3 cm in diameter, whereas, in larger nodes, the ratio is decreased to approximately 67%. Five CDFs are required to improve this ratio by more than 10%. Conclusion Optimizing delivered powers enables the distribution of the therapeutic dose uniformly in the medium. In addition, this simulation study represents an essential part of a development dosimetry system for measuring and controlling the optical dose in the breast tumors.
DEVELOPMENT OF AN AUTONOMOUS AVOIDANCE ALGORITHM FOR UAVS IN GENERAL AIRSPACE

OVERVIEW An autonomous avoidance system for the use in UAVs in controlled and uncontrolled airspace has to be able to ensure that a UAV is able to fulfil the 'Sense-and-Avoid' requirement with an equivalent level of safety to inhabited aircraft in which the pilot is able to monitor the direct surroundings of the aircraft and has direct control over the aircraft systems. The focus of this paper is on the avoidance functionality of the system. For this functionality a decision making architecture is introduced which is able to determine whether an intervention is required and then define an avoidance strategy and generate an avoidance manoeuvre. A modular approach ensures that only those parts of the system which are critical to the safety of the aircraft need to be certified as such. Depending on the scenario the 'Sense-and-Avoid' requirement is fulfilled using a hybrid approach of a reactive and/or deliberate avoidance manoeuvre generation algorithm. The deliberate part ensures sufficient separation between aircraft such that a potential conflict is avoided in the first place. The reactive function acts as a safety net to avoid an imminent collision hazard. Due to the different requirements for each function two types of algorithms are used. The separation function is based on a deliberate short-term path search. The safety net uses a direct command reactive algorithm. Both algorithms are able to handle constraints with respect to airspace, aircraft performance and multiple intruding aircraft.
LEARNING TO SCHEDULE WEB PAGE UPDATES USING GENETIC PROGRAMMING

One of the main challenges endured when designing a scheduling policy regarding freshness is to estimate the likelihood of a previously crawled web page being modified on the web, so that the scheduler can use this estimation to determine the order in which those pages should be visited. A good estimation of which pages have more chance of being modified allows the system to reduce the overall cost of monitoring its crawled web pages for keeping updated versions. In this work we present a novel approach that uses machine learning to generate score functions that produce accurate rankings of pages regarding their probability of being modified on the Web when compared to their previously crawled versions. We propose a flexible framework that uses Genetic Programming to evolve score functions to estimate the likelihood that a web page has been modified. We present a thorough experimental evaluation of the benefits of using the framework over five state-of-the-art baselines. Considering the Change Ratio metric, the values produced by our best evolved function show an improvement from 0.52 to 0.71 on average over the baselines.
An Overview of Prescription in the Nursing

Introduction: The role which nurses are playing in medication management is seriously changing over time. Nurses are authorized to prescribe medications in an ever-increasing number of countries. The main objective of the present review study is to introduce nurse prescribing as well as different types of prescriptions and their corresponding advantages, disadvantages, and barriers in the leading countries of nursing. Methods: The present study was performed by searching over the articles in information databases such as “PubMed”, “Google Scholar”, “Embase” , “Proquest”, “Ovid”, “Web of Science” and “Science Direct” using the English keywords such as “independent prescribing”, “supplementary nurse prescribing” and “prescribing”. As a result, 250 relevant papers were collected, out of which 38 ones were used in the present study. Results: The results of searching the sources and articles related to nurse prescribing were presented as the definition of nurse prescribing as well as different types of prescribing and their advantages and obstacles in the leading countries in nurse medication prescribing. Conclusions: Although there are many advantages for nurse prescribing such as cost-effectiveness of this method, the official prescribing by nurses is not authorized in many Asian countries such as Iran. Considering the positive role of nurse prescribing in the nursing professional improvement and the patient's satisfaction, it is also hoped to be applied in all countries.
Research on Image-Based Automatic Wafer Surface Defect Detection Algorithm

—Defects on the wafer surface usually reflect the abnormal problems in the semiconductor manufacturing process. By detecting and identifying the wafer surface defect mode, it can diagnose fault source in time and adjust online. In this paper, an online detection and adaptive recognition model for wafer surface defect mode is presented. Firstly, the model is used to extract the feature of the wafer surface defect mode. The Hidden Markov Model (HMM) is constructed for each wafer mode based on the feature set, and an on-line detection and recognition method based on HMM dynamic integration is proposed. The proposed model is successfully applied to the wafer defect detection and recognition in WM-811K database. The experimental results fully demonstrate the validity and practicability of the model. 
Functional Dissection of the RCC1 Protein ; the N-terminal Region of RCC1 Protein is a Nuclear Location Signal Rather Than a DNA-binding Domain.

The RCCl protein is involved in coupling of mitosis with S phase. It has seven homologous repeated domain of about 60 amino acids A DNA binding domain is in the N -terminal region outside this repeat. We found that the RCCl protein which has a deletion in this DNA-binding domain can complement the tsBN2 mutation. At 39.5°C, where the endogenous RCCl protein disappeared in the ts+ transformants of tsBN2 cells which were transfected with the deleted RCCl eDNA. The majority of the deleted RCCl protein was in the post-nuclear supernatant. However, a significant amount still remained in the nuclear fraction. The deleted RCCl remaining at the nuclei was eluted at the same concentration of NaCl and DNase I as the wild-type RCCl protein of BHK21 cells. Furthermore, the deleted RCCl protein was co-migrated with the nucleosome-fraction by sucrose-density gradient analysis. Expression of the N -terminal region fused with lacZ in COS cell revealed that the fused protein was located in the nucleoplasm. These findings suggest that the N-terminal region of the RCCl protein functions as a nuclear location signal rather than the DNA -binding domain and the RCC 1 protein may associate with the chromatin with an aid of other unknown protein(s).
Influence of aerosol copper on HO2 uptake: a novel parameterized equation

Abstract. Heterogeneous uptake of hydroperoxyl radicals (HO2) onto aerosols has been proposed to be a significant sink of HOx, hence impacting the atmospheric oxidation capacity. Accurate calculation of the HO2 uptake coefficient γHO2 is key to quantifying the potential impact of this atmospheric process. Laboratory studies show that γHO2 can vary by orders of magnitude due to changes in aerosol properties, especially aerosol soluble copper (Cu) concentration and aerosol liquid water content (ALWC). In this study we present a state-of-the-art model called MARK to simulate both gas- and aerosol-phase chemistry for the uptake of HO2 onto Cu-doped aerosols. Moreover, a novel parameterization of HO2 uptake was developed that considers changes in relative humidity (RH) and condensed-phase Cu ion concentrations and which is based on a model optimization using previously published and new laboratory data included in this work. This new parameterization will be applicable to wet aerosols, and it will complement current IUPAC recommendations. The new parameterization is as follows (the explanations for symbols are in the Appendix): 1γHO2=1αHO2+3×υHO24×106×RdHcorrRT×(5.87+3.2×ln⁡(ALWC/[PM]+0.067))×[PM]-0.2×Cu2+eff0.65+υHO2l4RTHorgDorgε. All parameters used in the paper are summarized in Table A1. Using this new equation, field data from a field campaign were used to evaluate the impact of the HO2 uptake onto aerosols on the ROx (= OH + HO2 + RO2) budget. Highly variable values for HO2 uptake were obtained for the North China Plain (median value < 0.1).
Systematic literature review of the relationship between adolescents' screen time, sleep and mental health

The objective of this systematic review was to summarise the published experimental and longitudinal evidence on adolescent mobile device screen time or use, and the association with sleep and mental health and wellbeing. Five research questions guided this review, which included evidence from quantitative and qualitative studies conducted in Western countries classified as high-income by the World Bank.
Problem Solving: A Contextualized Approach to Teaching Mathematics

The process of creating the Problem Solving Methodology has been shown to be long and full of deviations. For some time, there has been talk about its applicability, however, in those cases where it was performed, the results regarding mathematical learning were not satisfactory. In its complexity, when analyzing the main reasons that cancel the use of this methodology, it opens a gap in its study, because, as a consequence of its implementation, a considerable level of failure is observed in the cases applied. The present study proposes a discussion of the Problem-Solving Methodology about its historical context, its teacher training, its application in the school context, attitudes that do not generate results, highlighting those that exceed positive expectations, thus allowing a systematic analysis of the problem by understanding what is shaping the school curriculum in the process of teaching math learning.
Estimating Biological Function Distribution of Yeast Using Gene Expression Data

—Microarray technologies that monitor the level of expression of a large number of genes have emerged. And given the technology in deoxyribonucleic acid (DNA) - microarray data for a set of cells characterized by a phenotype an important problem is to identify “patterns” of gene expression that can be used to predict cell phenotype. The potential number of such patterns is exponential in the number of genes. Detection of genes biological function in silico which has not yet been discovered through other means aside from wet laboratories is of practical significance. In this research, biological function distribution of budding yeast cell Saccharomyces cerevisiae , using 170 classified gene expression data of yeast is used for visualization and analysis, and evaluated with the reference time distribution using FACS and budding index analysis. We define the criteria using edit distances, a good scientific visualization with 83.78% prediction on time series distribution on the first peak and 86.49% on the second peak. 
Software Development Effort Estimation Using a Fuzzy Logic-Based System within the Context of the Scaled Agile Framework

: In the context of Scaled Agile Framework (SAFe), software development effort estimation represents a critical task. Proper estimation of the development effort enables the development team to plan the development tasks and predict the amount of time and cost required to deliver software products. Additionally, it allows the development team to determine if the staffing level is sufficient (i.e., team’s capacity) during the Program Iteration (PI) planning. Background : SAFe is a framework for scaling Agile across an enterprise. At the development team level, it provides guidance to define, build, test, and deploy software solutions in a short iteration timebox. Agile teams are responsible for delivering software results that meet customer needs and expectations. Part of that responsibility is to estimate the effort of the work they must perform. Agile teams decompose the required work into stories, which are short descriptions of small pieces (functionalities) of software-desired functionality. The effort to develop and deliver a story is estimated using story points, which is a numeric value that represents a combination of work complexity, amount of work, and uncertainty/risk to implement. The concept of story points is simple, yet often difficult to apply. The main difficulty resides in that a story point represents an abstract subjective value. Many software developers find it challenging to correlate story points to the degree of complexity, size, and uncertainty of work effort. Objective : In this paper, we will provide an overview of the software development process within the context of SAFe, specifically, how Agile teams typically estimate work effortby using story points. Then we will propose a novel approach to estimating work effort. This novel method makes essential use of a fuzzy logic-based system— an artificial intelligence technique that emulates the human reasoning process during the estimation of work effort phase by Agile software development teams. Conclusion : Software effort estimation model incorporating fuzzy logic can help software development teams to overcome the issue of estimating multiple attributes conjointly.