Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk-Scoring Tool for respiratory syncytial virus prophylaxis in premature infants born at 33–35 completed weeks’ gestational age in Canada*

ABSTRACT Objective: To study the impact of the Risk-Scoring Tool (RST) as a strategy for targeting prophylaxis effectively in 33–35-week gestational age (GA) Canadian infants who range from low to high risk by evaluating the subsequent incidence of respiratory syncytial virus (RSV) infections resulting in emergency room (ER) visits and hospitalization. Design: Prospective, descriptive study. Setting: McMaster Children's Hospital and St Joseph's Healthcare in Hamilton, Ontario. Participants: Premature infants between 33 and 35 weeks’ completed gestation who were less than 6 months’ chronological age at the start of, or during, the local 2005–2008 RSV winter seasons. Methods: A validated, Canadian RST was used to calculate a total risk score based on seven risk factors. Only infants at moderate (RST score 49–64) and high risk (RST score 65–100) received palivizumab at monthly intervals from November to April and were followed during the respective RSV seasons. All parents received information on RSV prevention at hospital discharge. Parents of all recruited infants were contacted by telephone in May at the end of each season, and medical records were checked to determine ER visits for RSV-related respiratory tract infections and RSV hospitalization. Means, standard deviations, ranges, and percents were used to describe the variables for patients enrolled in the study. Results: Over 3 years, 430 infants were recruited. Of these, 346 (81%), 57 (13%), and 27 (6%) were in the low-, moderate- and high-risk categories, respectively, based on their risk scores. A total of 78 (18.1%) infants received full courses of palivizumab. Six out of 57 (10.5%) infants in the moderate-risk group did not receive prophylaxis, while all 27 high-risk group infants received palivizumab. Seven (1.6%) infants were RSV-positive and five (low-risk) infants were hospitalized. One high-risk, RSV-positive infant, was seen in the ER, and discharged home. There were no statistical differences in the number of infants with RSV-related ER visits and hospitalizations within the risk category groups (p = 0.43). The limitations of this study include the observational design and the relatively small sample size. Conclusions: The RST is a practical, easy-to-use instrument to guide judicious RSV prophylaxis for moderate–high-risk, 33–35-week GA infants. It is cost-effective, reducing hospitalization in infants who are most ‘at-risk’, while avoiding prophylaxis in a large segment (81.9%) of this GA cohort who are considered low risk for RSV infection.
Privacy preserving data publishing and data anonymization approaches: A review

The data engineering research community has fiercely felt the requisite for privacy of data of individuals. With technological advancement, every single of action of life is collected and stored thus creating databases with large amounts of details about individuals. It is both a benefit and a bane. A benefit because the novel and enhanced services helps in giving a bigger awareness about customer's preferences and greed thus allowing several possibilities for enhancing lives of people. However its bane too since this bigger knowledge related to confidential facets of lives of personal may cause damages if it is publicly available. Two generally-embraced ways to struggle privacy breach are Data encryption and Anonymization. The encryption of data is generally unsuitable when data is frequently shared after processing. The anonymization of big data and the management of these anonymized data sets are the major threats for conventional anonymization approaches. Till now several proposals are developed for privacy preserving data publishing, thus the major objective of this paper is the survey of the existing techniques, and the advantages and disadvantages of these approaches are analyzed.
Sustainability of current accounts: evidence from the quantile unit-root test

ABSTRACT Regarding the stationarity of current accounts, previous studies used panel unit-root tests to improve the power of augmented Dickey–Fuller (ADF) test. This paper applies a quantile autoregression (QAR) approach to improve ADF test in the presence of outliers, and found that first, the stationarity was present in a QAR framework, rather than ADF test. Second, current accounts exhibited symmetric (e.g. Taiwan) and asymmetric patterns, which showed that positive shocks in larger quantiles induce current accounts to adjust towards a long-term equilibrium for Korea, Thailand, the Philippines and Singapore. Japan exhibited an asymmetric pattern in response to negative shocks in smaller quantiles.
Tb-CNN: Joint tree-bank information for sentiment analysis using CNN

Sentiment analysis still is a problem in text data analysis. In this paper, the proposed model which fuses the convolution neural network with the tree bank information has been introduced. This model not only takes into consideration of the syntax information, but also the structure information which is better than other single factor model. By a sequence of experiments, we can prove the goodness of this model in sentiment analysis.
A simulation approach for reduced outpatient waiting time

Extended waiting time for treatment in National hospitals is very common in Sri Lanka. This situation has created several problems to patients, doctors and even to other health workers. The quality of service leaves a lot to be desired and is costly to the economy. This study analyses different queues which create bottlenecks in the Out Patient Department at national eye hospital in Sri Lanka and critically evaluate several appointment scheduling rules with the help of a simulation model to come up with a solution which minimises the total patient waiting time. Our results shows that total patient waiting time can be reduced more than 60% using proper appointment scheduling system with process improvement.
1-cm3 event-driven wireless sensor nodes

This paper describes a 1-cm3 event-driven wireless sensor node (WSN) consisting of a solar battery with a capacitor, vibration sensor, wireless circuit, and antenna. The WSN transmits data using energy in the millimeter-size capacitor charged by the solar battery. The concept of the wireless transmission scheme is to not only reduce 1-bit energy while transmitting data continuously but also to reduce all energy of “one-time data transmission” from circuit start-up to the end of data transmission. We have already fabricated and evaluated a wireless chip that uses ring oscillators as clocks and transmits OOK pulse trains. In this paper, we show that these architectures are suitable for reducing energy of “one-time data transmission” and for WSN operation by limited energy because they can reduce the start-up time and activated time in 1-bit symbol of RF circuits. The fabricated sensor node can transmit 36-bit data 3 m by charged energy of 8 μJ in the capacitor when the sensor detects the event. This enables us to achieve 1-cm3 WSN and paves the way to the future millimeter-size battery less WSNs.
Pitfalls of Policy Implementation: The Case of the South African Feed-In Tariff

The carbon intensity of the South African economy is among the highest in the world: the amount of CO2 emitted per million international dollars generated reaches almost twice the world average. The first steps have been taken by the South African government to tackle the challenge of decarbonization, such as the introduction of a renewable energy feed-in tariff (REFIT) in 2009. However, REFIT is a showcase for potential pitfalls in the implementation of renewable energy support policies: a stalemate lasting two years after the introduction of REFIT ended with the abandonment of the scheme in favor of a competitive bidding process in 2011. This paper seeks to analyze the underlying reasons for this and to offer recommendations for similar situations in the future.The paper identifies three main barriers to the implementation of REFIT: 1) social priorities other than the deployment of renewable energy technologies, 2) a lack of coordination and capacity at the policymaking level, and 3) strong lobby groups with interests in fossil fuel technologies. These barriers not only exist in South Africa, but in most other developing countries. Therefore, many of the recommendations for South Africa can be transferred to other country contexts, such as: informing the public about climate change and stressing the positive side-effects of renewable energy technologies, thereby building public support, making use of international mechanisms to build political momentum, forming clean-energy coalitions with powerful groups in society, communicating support rules as early and clearly as possible, and keeping later adjustments to the rules predictable to maintain investment certainty, establishing inter-ministerial groups with oversight authority to enhance political coordination, supporting established energy suppliers in their discovery of renewable energy tariffs (RETs) as a new business field, strengthening the position and capacity of renewable energy newcomers.
Mechanism of inhibition of taurolithocholate‐induced retrieval of plasma membrane MRP2 by cyclic AMP and tauroursodeoxycholate

Taurolithocholate (TLC) produces cholestasis by inhibiting biliary solute secretion in part by retrieving MRP2 from the plasma membrane (PM). Tauroursodeoxycholate (TUDC) and cAMP reverse TLC‐induced cholestasis by inhibiting TLC‐induced retrieval of MRP2. However, cellular mechanisms for this reversal are incompletely understood. Recently, we reported that TLC decreases PM‐MRP2 by activating PKCε followed by phosphorylation of myristoylated alanine‐rich C kinase substrate (MARCKS). Thus, cAMP and TUDC may reverse TLC‐induced cholestasis by inhibiting the TLC/PKCε/MARCKS phosphorylation pathway. We tested this hypothesis by determining whether TUDC and/or cAMP inhibit TLC‐induced activation of PKCε and phosphorylation of MARCKS. Studies were conducted in HuH‐NTCP cell line and rat hepatocytes. Activation of PKCε was determined from the translocation of PKCε to PM using a biotinylation method. Phosphorylation of MARCKS was determined by immunoblotting with a phospho‐MARCKS antibody. TLC, but not cAMP and TUDC, activated PKCε and increased MARCKS phosphorylation in HuH‐NTCP as well in rat hepatocytes. Treatment with TUDC or cAMP inhibited TLC‐induced activation of PKCε and increases in MARCKS phosphorylation in both cell types. Based on these results, we conclude that the reversal of TLC‐induced cholestasis by cAMP and TUDC involves, at least in part, inhibition of TLC‐mediated activation of the PKCε/MARCKS phosphorylation pathway.
Off-line Telugu handwritten characters recognition using optical character recognition

The Aim of the proposed paper is to recognize offline Hand written Telugu characters using Optical character recognition, OCR is one of the most popular and challenging topic of pattern recognition This paper proposes an OCR system for Telugu documents which comprises of three stages, namely pre-processing, feature extraction, and classification. In the preprocessing stage, we have employed median filtering on the input characters and applied normalization and skeletonization method over characters for extraction of boundary edge pixel points. In the feature extraction stage, initially the each character is divided into 3×3 grids and the corresponding centroid for all the nine zones are evaluated. With this we can identify the characters of different styles. There after, we have drawn the horizontal and vertical symmetric projection angel to the nearest pixel of the character which is dubbed as Binary External Symmetry Axis Constellation for unconstrained handwritten character. From which we have calculated the horizontal and vertical Euclidean distance for the same nearest pixel from centroid of each zone. Then we have calculated the mean Euclidean distance as well as the mean angular values of the zones. This is considered as the key feature values of our proposed system. Lastly, both support vector machine (SVM) and Quadratic discriminate Classifier (QDA) has been separately used as the classifier.
Decompositions, Network Flows, and a Precedence Constrained Single-Machine Scheduling Problem

We present an in-depth theoretical, algorithmic, and computational study of a linear programming (LP) relaxation to the precedence constrained single-machine scheduling problem 1|prec|S jw jC jto minimize a weighted sum of job completion times. On the theoretical side, we study the structure of tight parallel inequalities in theLP relaxation and show thatevery permutation schedule that is consistent with Sidney's decomposition has total cost no more than twice the optimum. On the algorithmic side, we provide a parametric extension to Sidney's decomposition and show that a finest decomposition can be obtained by essentially solving a parametric minimum-cut problem. Finally, we report results obtained by an algorithm based on these developments on randomly generated instances with up to 2,000 jobs.
Toward Optimal Closure of the Earth's Top-of-Atmosphere Radiation Budget

Abstract Despite recent improvements in satellite instrument calibration and the algorithms used to determine reflected solar (SW) and emitted thermal (LW) top-of-atmosphere (TOA) radiative fluxes, a sizeable imbalance persists in the average global net radiation at the TOA from satellite observations. This imbalance is problematic in applications that use earth radiation budget (ERB) data for climate model evaluation, estimate the earth’s annual global mean energy budget, and in studies that infer meridional heat transports. This study provides a detailed error analysis of TOA fluxes based on the latest generation of Clouds and the Earth’s Radiant Energy System (CERES) gridded monthly mean data products [the monthly TOA/surface averages geostationary (SRBAVG-GEO)] and uses an objective constrainment algorithm to adjust SW and LW TOA fluxes within their range of uncertainty to remove the inconsistency between average global net TOA flux and heat storage in the earth–atmosphere system. The 5-yr global mean.
Diagnostic impact of contemporary biomarker assays for rheumatoid arthritis

Objective: The impetus towards early treatment for patients with rheumatoid arthritis (RA) requires more reliable disease markers than the non‐specific immunoglobulin M (IgM) rheumatoid factor (RF). To determine the accuracy of newer biomarkers for RA testing for antibody against cyclic citrullinated peptides (anti‐CCP Ab), IgA‐ and IgG‐RF and cartilage oligomeric matrix protein (COMP) levels, measured by enzyme‐linked immunosorbent assay (ELISA), were compared with IgM‐RF isotyping. Methods: Serum samples were investigated in patients with an established diagnosis of RA (n = 54), ankylosing spondylitis (AS) (n = 36), and non‐inflammatory conditions (n = 18) (cohort A), and in 234 consecutive outpatients in a blinded fashion (cohort B). Non‐parametric analysis of areas under the curve (AUC) of receiver operator characteristics were performed. Results: The presence of anti‐CCP Ab had the highest accuracy (96%) in distinguishing RA patients in cohort A and cohort B (accuracy 83%), and in both cohorts combined (accuracy 87%). This was related to the high specificity of anti‐CCP Ab for RA (95–96%), even though IgM‐RF was the most sensitive test (87–96%). Sensitivity (15–48%) and specificity (66–69%) of COMP as a marker for RA was low. Combining results of anti‐CCP Ab and IgM‐RF or any of the other assays did not increase the diagnostic accuracy for RA. Conclusion: The presence of anti‐CCP Ab is the most accurate biomarker for RA in both selected and unselected cohorts, while the COMP assay is not very useful in RA diagnosis. Combining assays for anti‐CCP Ab and IgM‐RF or IgA‐RF does not enhance RA diagnosis.
Welfare Effects of Diversification on Farm Households in Cambodia

This paper analyzes the effects of diversifying into off-farm activities on farm household welfare in terms of household food consumption in rural Cambodia. An endogenous switching model is applied to data from the 2009 Cambodia Socio-Economic Survey to assess whether farm households make food consumption gains from participation in salary-paid employment and self-employment. This model accounts for selection bias arising from unobserved factors that potentially determine both off-farm participation and food consumption. It also controls for structural differences between participants and nonparticipants in off-farm activities that most previous studies do not account for. The results reveal that by participating in salary-paid employment, farm households make positive gains in food consumption per capita, then supporting the hypothesis that engagement in salary-paid employment has positive effects on farm households' welfare. However, per capita food consumption gains from participation in self-employment are negative, suggesting that the salary-paid employment has more important role in promoting household welfare in rural communities than does the self-employment.
Commentary: ‘Bankruptcy Laws and Entrepreneur Friendliness’ and ‘How Do Bankruptcy Laws Affect Entrepreneurship Development Around the World?’

Two recent papers examine the impact of corporate bankruptcy laws on new business start ups in 29 countries over 1990-2008 (Peng et al., 2010; Lee et al., 2010). In this commentary, I briefly point out two significant issues which future researchers might want to consider along this line of research. First, several countries in the data examined had changed their personal and corporate bankruptcy laws over the years studied. It is statistically inappropriate and inaccurate to treat bankruptcy laws as time invariant, as in Peng et al. (2010) and Lee et al. (2010), particularly in view of the dramatic changes in bankruptcy law over time in so many countries. Second, Peng et al. (2010) and Lee et al. (2010) have a misplaced focus on corporate bankruptcy law while ignoring personal bankruptcy law. This focus is at odds with theory and prior work on topic which relates entrepreneurship to personal bankruptcy law.
Education and Risk for Late Life Depression: A Meta-Analysis of Published Literature

Objective: Less education is commonly viewed as an important risk factor for late life depression. However, this has still not been confirmed. The goal of this study was to determine the relationship between education and risk for depression among the old. Method: MEDLINE, EMBASE, and The Cochrane Library database were used to identify potential studies. The studies were divided into cross-sectional and longitudinal subsets. The qualitative meta-analysis of cross-sectional studies and that of longitudinal studies were preformed, respectively. For prevalence and incidence rates of depression, odds risk (OR) and relative risk (RR) were calculated, respectively. Results: Twenty-four cross-sectional and 12 prospective longitudinal studies were included in this review. In this meta-analysis, in the more and less education groups, there were 22,964 and 28,024 subjects and 3032 and 6462 cases of depression, respectively. The qualitative meta-analysis showed that, compared with old people with more education, those with less education had higher risk for depression (odds risk (OR): 1.58, 95% confidence intervals (95% CI): 1.38–1.82; Relative risk (RR): 1.49, 95% CI: 1.16–1.91). Conclusions: Despite the methodological limitations of this meta-analysis, less education is associated with increase risk of late life depression.
A multi-party correlation measure based on cumulant

We propose a genuine multi-party correlation measure for a multi-party quantum system as the trace norm of the cumulant of the state. The legitimacy of our multi-party correlation measure is explicitly demonstrated by proving it satisfies the five basic conditions required for a correlation measure. As an application we construct an efficient algorithm for the calculation of our measures for all stabilizer states.
NHE3 Regulatory Factor 1 (NHERF1) Modulates Intestinal Sodium-dependent Phosphate Transporter (NaPi-2b) Expression in Apical Microvilli*

Background: The type 2b sodium-dependent phosphate co-transporter (NaPi-2b) is the main mediator of intestinal active Pi absorption. Results: NaPi-2b interacts with the PDZ domain of NHE3 regulatory factor 1 (NHERF1). Conclusion: NHERF1 is an important regulator of NaPi-2b apical membrane targeting in response to a low Pi diet. Significance: Understanding of NaPi-2b adaptive mechanisms can help to design new therapies against hypo- and hyperphosphatemic disorders. Pi uptake in the small intestine occurs predominantly through the NaPi-2b (SLC34a2) co-transporter. NaPi-2b is regulated by changes in dietary Pi but the mechanisms underlying this regulation are largely undetermined. Sequence analyses show NaPi-2b has a PDZ binding motif at its C terminus. Immunofluorescence imaging shows NaPi-2b and two PDZ domain containing proteins, NHERF1 and PDZK1, are expressed in the apical microvillar domain of rat small intestine enterocytes. Co-immunoprecipitation studies in rat enterocytes show that NHERF1 associates with NaPi-2b but not PDZK1. In HEK co-expression studies, GFP-NaPi-2b co-precipitates with FLAG-NHERF1. This interaction is markedly diminished when the C-terminal four amino acids are truncated from NaPi-2b. FLIM-FRET analyses using tagged proteins in CACO-2BBE cells show a distinct phasor shift between NaPi-2b and NHERF1 but not between NaPi-2b and the PDZK1 pair. This shift demonstrates that NaPi-2b and NHERF1 reside within 10 nm of each other. NHERF1−/− mice, but not PDZK1−/− mice, had a diminished adaptation of NaPi-2b expression in response to a low Pi diet. Together these studies demonstrate that NHERF1 associates with NaPi-2b in enterocytes and regulates NaPi-2b adaptation.
A Novel Automatic Extraction Approach of Pollutants for Mobile Camera

Rapid and automatic extraction of pollutants is of great importance for mobile camera in real-world scenarios. In the moving process of robot, the camera is treated as dynamic background, and the pollutants on the camera are treated as static target. So as to realize the detection of static target in dynamic scene, this paper presents an automatic extraction algorithm for pollutants based on frame difference accumulation. Firstly, this algorithm can determine whether pollutants exist or not by the overall trend of gray histogram of the cumulative frame difference images. And then if existing pollutants, Otsu algorithm was adopted to adaptively calculate threshold to convert the gray image into binary image. In this paper, analysis of the important parameters of the algorithm - cumulative frame number and frame difference threshold was implemented. Moreover, feasibility of the algorithm was verified by experiments on the automatic extraction of pollutants for gun-type camera.
Feature-oriented development of applications for a domain

Software reuse is generally considered by both practitioners and researchers as one of the most effective ways of increasing productivity and improving quality of software. To achieve successful software reuse, commonalities of related systems must be discovered and represented in a form that can be exploited in developing similar systems. FORM (Feature-Oriented Reuse Method) (K.C. Kang et al., 1998), extended from the FODA (Feature-Oriented Domain Analysis) method (K.C. Kang et al., 1990), is a systematic method that focuses on capturing commonalities and differences of applications in a domain in terms of "features" and using the analysis results to develop domain architectures and components. Once a domain is described and explained in terms of common and different "units" of computation, they are used to construct different "feasible" configurations of reusable architectures. Features are distinctively identifiable functional implemented, tested, delivered, and maintained. Therefore, they are the first class objects in the development of domain oriented software.