bluuebunny/crossref_metadata_2025_split huggingface dataset:
Testing the “Zero‐Sum Game” Hypothesis: An Examination of School Health Policies and Practices and Inequalities in Educational Outcomes
Authors: Long Sara J. , Littlecott Hannah , Hawkins Jemma , Eccles Gemma , Fletcher Adam , Hewitt Gillian , Murphy Simon , Moore Graham F. 
Published: March 2020

ABSTRACTBACKGROUNDHealth and education are intrinsically linked, while both are significantly patterned by socioeconomic status throughout the life course. Nevertheless, the impact of promoting health via schools on education is seen by some as a “zero‐sum game”; ie, focusing resources on health improvement activity distracts schools from their core business of educating pupils, potentially compromising educational attainment. There is emerging evidence that school health improvement interventions may beneficially influence both health and attainment. However, few studies have examined the relationship between school health improvement activity and socioeconomic inequalities in educational attainment.METHODSWales‐wide, school‐level survey data on school health policies and practices was linked with routinely collected data on academic attainment. Primary outcomes included attendance and academic attainment at age 14 (Key Stage 3) and 16 (Key Stage 4). Linear regression models were constructed separately for high and low Free School Meal (FSM) schools, adjusting for confounders. Interaction terms were fitted to test whether there was an interaction between FSM, health improvement activity, and outcomes.RESULTSThere were positive associations between almost all school health variables and KS3 attainment among high, but not low FSM schools. Similarly, for attendance, there were positive associations of several health variables among high but not low FSM schools. There were no associations for KS4 attainment.CONCLUSIONSOur findings did not support the “zero‐sum game” hypothesis; in fact, among more deprived schools there was a tendency for better attendance and attainment at age 14 in schools with more embedded health improvement action.
Effects of electroacupuncture on the intestinal motility and local inflammation are modulated by acupoint selection and stimulation frequency in postoperative ileus mice
Authors: Yang Na‐Na , Ye Yang , Tian Zhong‐Xue , Ma Si‐Ming , Zheng Yang , Huang Jin , Yang Jing‐Wen , Shao Jia‐Kai , Liu Cun‐Zhi 
Published: March 2020

AbstractBackgroundElectroacupuncture (EA) is widely used in various gastrointestinal diseases around the world, including POI. Here, we investigated different therapeutic effects of EA using lower limb and abdomen acupoints.MethodsIntestinal manipulation was performed in 88 mice, and eight mice underwent a sham operation. Forty mice were randomly divided into model group and four EA groups receiving stimulation at ST36 (2, 10, 30, 100 Hz). The most effective frequency was then used in the following experiments. Forty‐eight mice were randomly divided into six groups receiving EA treatment at ST37, ST39, ST25, CV4, CV12, and a non‐acupuncture point. Gastrointestinal motility and plasma TNF‐α, IL‐6 were evaluated in all mice. The local immune response and α‐smooth muscle actin (α‐SMA) expression were assessed by immunofluorescence, ELISA, and HE staining.ResultsST36 stimulated with 10 or 30 Hz EA significantly increased the gastrointestinal motility and attenuated peripheral inflammation; however, ST36 stimulated with 2 or 100 Hz did not induce any effect. The therapeutic effects on motility and inflammation of 10 Hz EA in the ST36 group were similar in the ST36, ST37, ST39, or CV4 groups, but when applied to ST25, CV12 or non‐acupoint had no significant differences. EA at ST36, ST37, ST39, or CV4 significantly inhibited local MPO activity, immune cells infiltration, and increased α‐SMA.ConclusionsEA at lower limb and abdomen acupoints with the same stimulation parameters had different therapeutic effects on postoperative dysmotility and inflammation. Furthermore, EA protected SMC to improve gastrointestinal transit by reducing local inflammation in the intestinal musculature in POI.
Attentional modulation of unconscious inhibitory visuomotor processes: An EEG study
Authors: Wang Yongchun , Di Meilin , Zhao Jingjing , Hu Saisai , Yao Zhao , Wang Yonghui 
Published: March 2020

AbstractThe present study examined the role of attention in unconscious inhibitory visuomotor processes in three experiments that employed a mixed paradigm including a spatial cueing task and masked prime task. Spatial attention to the prime was manipulated. Specifically, the valid‐cue condition (in which the prime obtained more attentional resources) and invalid‐cue condition (in which the prime obtained fewer attentional resources) were included. The behavioral results showed that the negative compatibility effect (a behavioral indicator of inhibitory visuomotor processing) in the valid‐cue condition was larger than that in the invalid‐cue condition. Most importantly, lateralized readiness potential results indicated that the prime‐related activation was stronger in the valid‐cue condition than in the invalid‐cue condition and that the followed inhibition in the compatible trials was also stronger in the valid‐cue condition than in the invalid‐cue condition. In line with the proposed attentional modulation model, unconscious visuomotor inhibitory processing is modulated by attentional resources.
Outcome according to subspecies following lung transplantation in cystic fibrosis pediatric patients infected with Mycobacterium abscessus
Authors: Kavaliunaite Ema , Harris Kathryn A. , Aurora Paul , Dixon Garth , Shingadia Delane , Muthialu Nagarajan , Spencer Helen 
Published: March 2020

AbstractBackgroundMycobacterium abscessus infection has been associated with variable outcomes following lung transplantation. M abscessus comprises three subspecies (M abscessus subsp abscessus, M abscessus subsp massiliense, and M abscessus subsp bolletii). We investigated whether lung transplantation outcome in cystic fibrosis (CF) patients in a single center was related to the M abscessus subspecies and genetic cluster.MethodsCF patients with chronic M abscessus infection transplanted at Great Ormond Street Hospital between 2004 and 2017 were retrospectively examined. All M abscessus isolates were identified to subspecies level by polymerase chain reaction and sequencing. Genetic cluster was determined by variable number tandem repeat profiling and whole‐genome sequencing (WGS), and sequence type inferred from WGS.ResultsThirteen patients with chronic M abscessus infection underwent heart/lung or lung transplantation. Subspecies identification showed n = 1 with M abscessus bolletii, n = 5 with M abscessus massiliense, and n = 7 with M abscessus abscessus infection. Eight (62%) patients (one with M abscessus massiliense and seven with M abscessus abscessus) died post–lung transplant. The patient with M abscessus bolletii and three patients with M abscessus massiliense did well post‐transplant. One patient with M abscessus massiliense is receiving ongoing treatment.ConclusionsDramatically worse outcomes are observed in patients infected with M abscessus subspecies abscessus, the majority of whom were infected with ST‐1 and ST‐26 strains. Patients infected with other M abcsessus strains can have acceptable outcomes.
The gravity model and trade in intermediate inputs
Authors: Greaney Theresa M. , Kiyota Kozo 
Published: March 2020

AbstractIs the gravity model as applicable to trade in intermediate inputs as it is to trade in final goods? One of the contributions of this paper is that we explicitly account for the dual nature of products that can be used as either intermediate inputs or final goods. We find that the structural gravity model performs extremely well for describing bilateral trade in final goods and in intermediate inputs. Moreover, this continues to hold even when we focus on a subset of countries in which intermediate inputs trade accounts for a growing share of trade, namely "Factory Asia." However, the gravity model may perform poorly due to model misspecification (i.e., exclusion of intranational trade) and/or sample selection, even after the model considers the dual nature of products. We demonstrate that the poor performance of the gravity model is not attributable to the large trade flow of intermediate inputs, which supports the continued use of the model as these trade flows continue to grow in importance worldwide.
MEF2c-Dependent Downregulation of Myocilin Mediates Cancer-Induced Muscle Wasting and Associates with Cachexia in Patients with Cancer
Authors: Judge Sarah M. , Deyhle Michael R. , Neyroud Daria , Nosacka Rachel L. , D'Lugos Andrew C. , Cameron Miles E. , Vohra Ravneet S. , Smuder Ashley J. , Roberts Brandon M. , Callaway Chandler S. , Underwood Patrick W. , Chrzanowski Stephen M. , Batra Abhinandan , Murphy Meghan E. , Heaven Jonathan D. , Walter Glenn A. , Trevino Jose G. , Judge Andrew R. 
Published: March 2020

Abstract

Skeletal muscle wasting is a devastating consequence of cancer that contributes to increased complications and poor survival, but is not well understood at the molecular level. Herein, we investigated the role of Myocilin (Myoc), a skeletal muscle hypertrophy-promoting protein that we showed is downregulated in multiple mouse models of cancer cachexia. Loss of Myoc alone was sufficient to induce phenotypes identified in mouse models of cancer cachexia, including muscle fiber atrophy, sarcolemmal fragility, and impaired muscle regeneration. By 18 months of age, mice deficient in Myoc showed significant skeletal muscle remodeling, characterized by increased fat and collagen deposition compared with wild-type mice, thus also supporting Myoc as a regulator of muscle quality. In cancer cachexia models, maintaining skeletal muscle expression of Myoc significantly attenuated muscle loss, while mice lacking Myoc showed enhanced muscle wasting. Furthermore, we identified the myocyte enhancer factor 2 C (MEF2C) transcription factor as a key upstream activator of Myoc whose gain of function significantly deterred cancer-induced muscle wasting and dysfunction in a preclinical model of pancreatic ductal adenocarcinoma (PDAC). Finally, compared with noncancer control patients, MYOC was significantly reduced in skeletal muscle of patients with PDAC defined as cachectic and correlated with MEF2c. These data therefore identify disruptions in MEF2c-dependent transcription of Myoc as a novel mechanism of cancer-associated muscle wasting that is similarly disrupted in muscle of patients with cachectic cancer.

Significance:
This work identifies a novel transcriptional mechanism that mediates skeletal muscle wasting in murine models of cancer cachexia that is disrupted in skeletal muscle of patients with cancer exhibiting cachexia.
Field Application of Digital Technologies for Health Assessment in the 10,000 Families Study
Authors: Thyagarajan Bharat , Nelson Heather H. , Poynter Jenny N. , Prizment Anna E. , Roesler Michelle A. , Cassidy Erin , Putnam Sara , Amos Laura , Hickle Andrea , Reilly Cavan , Spector Logan G. , Lazovich DeAnn 
Published: March 2020

Abstract

Background:
We field tested new-to-market portable, digital applications to assess hearing, pulmonary, and cognitive function to determine the feasibility of implementing these applications across a range of age groups in the pilot phase of the 10,000 Families Study (10KFS), a new Minnesota family–based prospective cohort study.

Methods:
We followed manufacturer recommended protocols for audiometry (SHOEBOX Inc), spirometry (NuvoAir), and the digital clock drawing test (dCDT; Digital Cognition Technologies Inc).

Results:
These digital devices were low cost and readily implemented in a 2.5-hour health fair visit with minimal training (2–3 hours) of study staff. To date, we have performed these measurements on 197 eligible 10KFS participants during an in-person clinic visit. A total of 37 children (age 4–17 years), 107 adults (18–64 years), and 53 seniors (≥65 years) were eligible to undergo hearing and pulmonary assessments. Children were less likely to successfully complete the hearing test (76%) compared with adults (86%) and seniors (89%). However, successful completion of the pulmonary assessment was high across all groups: 100% of children and seniors and 98% of adults. The dCDT was performed among those over the age of 40, and completion rates were 92% for those aged 41–64 and 94% for those ≥65 years.

Conclusions:
Our field testing indicates these digital applications are easy and cost-effective to implement in epidemiologic studies.

Impact:
Digital applications provide exciting opportunities to collect data in population studies. Issues related to data privacy, data access, and reproducibility of measurements need to be addressed before deploying digital applications in epidemiologic studies.
See all articles in this CEBP Focus section, “Modernizing Population Science.”
Statistical analysis of night radiance RH using VIIRS day/night band satellite time series data
Authors: Devkota Jyoti U. 
Published: March 2020

<p class="SAP-AffiliationLastline">Amount of night lights in an area is a proxy indicator of electricity consumption. This is interlinked to indicators of economic growth such as socio-economic activities, urban population size, physical capital, incidence of poverty. These night lights are generated by renewable and non renewable energy source. In this paper the behavior of night radiance RH data was minutely analyzed over a period of 28 hour; Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) satellite earth observation data were used. These 28 hours and 8936 observations time series data is from 2 September 2018 to 4 September 2018. The behavior of night radiance RH data over 122 time intervals was analyzed using box plots. It was seen that the arithmetic mean of RH data is more sensitive than the arithmetic mean of first order difference of RH data. The first order difference of night radiance RH was regressed on night radiance over 110 intervals of time. The box plot of slope and intercept of this linear regression showed the behavior of these regression parameters over 110 intervals of time. It is seen that the data are more scattered with respect to slope than with respect to intercept. </p>
Suggestive GAN for supporting Dysgraphic drawing skills
Authors: Pallavi Smita 
Published: March 2020

<span lang="EN-US">The squat competence of dysgraphia affected students in drawing graphics on paper may deter the normal pace of learning skills of children. Convolutional neural network may tend to extract and stabilize the action-motion disorder by reconstructing features and inferences on natural drawings. The work in this context is to devise a scalable Generative Adversarial Network system that allows training and compilation of image generation using real time generated images and Google QuickDraw dataset to use quick and accurate modalities to provide feedback to empower the guiding software as an apt substitute for human tutor. The training loss accuracy of both discriminator and generator networks is also compared for the SGAN optimizer.</span>
Artificial Bee Colony algorithm used for load balancing in cloud computing: Review
Authors: Ullah ARIF 
Published: March 2020

<p>Cloud computing is emerging technology in IT land. But it still faces challenges like load balancing. It is a technique which dynamic distributed workload among various nodes equally in a situation where some nodes are under load and some are overload. Main achievements of load balancing are resource consumption and reduce energy. Swarm intelligence provides an important role in the field of those problems which cannot easily solve and they need classical and mathematical technique. An artificial bee colony is a foraging behavior inspires algorithm it established by karaboga in 2005. It has fast convergence, strong, robustness, and high flexibility. The different researcher used ABC algorithm for improvement in load balancing. This survey paper is a comprehensive study about load balancing in cloud computing using the ABC algorithm. It also defines some basic concept about swarm intelligent and its property<strong>.</strong></p>
Privileged Authenticity in Reconstruction of Digital Encrypted Shares
Authors: Dey Joydeep , Bhowmik Anirban , Sarkar Arindam , Karforma Sunil 
Published: March 2020

Efficient message reconstruction mechanism depends on the entire partial shares received in random manner. This paper proposed a technique to ensure the authenticated accumulation of shares based on the privileged share.Threshold number of received shares inclusive of the privileged share, were being accumulated together to validate the original message. Although attaining threshold number of shares or more excluding the privileged share, it would not be possible to reconstruct the original message. Encryptional procedure has been put into the desired partial shares to confuse the evaesdroppers. Decisive parameter termed as hash tag has been extracted from the cumulative shares and bitwise checking procedure has been carried out. In first appearance of first mismatch, rests of the checking bits were ignored, as test case put under failure transaction. Different statistical tests namely floating frequency, entropy value have proved the robustness of the proposed technique. Thus, extensive experiments were conducted to evaluate the security and efficiency with better productivity.<strong> </strong>
Performance Analysis of Supervised Learning Models for Product Title Classification
Authors: Noor Mathivanan Norsyela Muhammad , Md.Ghani Nor Azura , Mohd Janor Roziah 
Published: March 2020

<p>Online business development through e-commerce platforms is a phenomenon which change the world of promoting and selling products in this 21<sup>st</sup> century. Product title classification is an important task in assisting retailers and sellers to list a product in a suitable category. Product title classification is apart of text classification problem but the properties of product title are different from general document. This study aims to evaluate the performance of five different supervised learning models on data sets consist of e-commerce product titles with a very short description and they are incomplete sentences. The supervised learning models involve in the study are Naïve Bayes, K-Nearest Neighbor (KNN), Decision Tree, Support Vector Machine (SVM) and Random Forest. The results show KNN model is the best model with the highest accuracy and fastest computation time to classify the data used in the study. Hence, KNN model is a good approach in classifying e-commerce products.</p>
A Multiple Mitosis Genetic Algorithm
Authors: Kamil K. , Chong K.H , Hashim H. , Shaaya S.A. 
Published: March 2020

<p>Genetic algorithm is a well-known metaheuristic method to solve optimization problem mimic the natural process of cell reproduction. Having great advantages on solving optimization problem makes this method popular among researchers to improve the performance of simple Genetic Algorithm and apply it in many areas. However, Genetic Algorithm has its own weakness of less diversity which cause premature convergence where the potential answer trapped in its local optimum. This paper proposed a method Multiple Mitosis Genetic Algorithm to improve the performance of simple Genetic Algorithm to promote high diversity of high-quality individuals by having 3 different steps which are set multiplying factor before the crossover process, conduct multiple mitosis crossover and introduce mini loop in each generation. Results shows that the percentage of great quality individuals improve until 90 percent of total population to find the global optimum.</p>
Review of anomalous sound event detection approaches
Authors: Affendi Amirul Sadikin Md , Yusoff Marina 
Published: March 2020

<p>This paper presents a review of anomalous sound event detection(SED) approaches. SED is becoming more applicable for real-world appliactaions such as security, fire determination or olther emergency alarms. Despite many research outcome previously, further research is required to reduce false positives and improve accurracy. SED approaches are comprehensively organized by methods covering system pipeline components of acoustic descriptors, classification engine, and decision finalization method. The review compares multiple approaches that is applied on a specific dataset. Security relies on anomalous events in order to prevent it one must find these anomalous events. Audio surveillance has become more efficient as that artificial intelligence has stepped up the game. Autonomous SED could be used for early detection and prevention. It is found that the state of the art method viable used in SED using features of log-mel energies in convolutional recurrent neural network(CRNN) with long short term memory(LSTM) with a verification step of thresholding has obtained 93.1% F1 score and 0.1307 ER. It is found that feature extraction of log mel energies are highly reliable method showing promising results on multiple experiments.</p>
Intelligent swarm-based optimization technique for oscillatory stability assessment in power system
Authors: Kamari N. A. M. , Musirin I. , Ibrahim A. A. , Halim S. A. 
Published: March 2020

<p>This paper discussed the prediction of oscillatory stability condition of the power system using a particle swarm optimization(PSO) technique. Indicators namely synchronizing(<em>K<sub>s</sub></em>)and damping(<em>K<sub>d</sub></em>) torque coefficients is appointed to justify the angle stability condition in a multi-machine system. PSO is proposed and implemented to accelerate the determination of angle stability. The proposed algorithm has been confirmed to be more accurate with lower computation time compared with evolutionary programming(EP) technique. This result also supported with other indicators such as eigenvalues determination, damping ratio and least squares method. As a result, proposed technique is achievable to determine the oscillatory stability problems.</p>
The Dating of the Acta Carpi
Authors: Kozlowski Jan M. 
Published: March 2020

Abstract
In the scholarly discussion on the dating of the Acta Carpi, two main proposals were hitherto formed: either II or III c. CE. The article argues that the earlier dating is probable. The Acta Carpi show many parallels with the Martyrium Polycarpi which can be best explained by a direct relationship between the two texts. Since the Acta Carpi betray more archaic features than the Martyrium Polycarpi, which in light of recent studies should be dated to the end of the second century, it is inferred that the Acta Carpi were written in the II c. CE, most probably in the years 166–168.
Augustine’s Use of Principium in De trinitate 1-7
Authors: Reese Ephrem 
Published: March 2020

Abstract
In his trinitarian theology, Augustine’s use of the term principium undergoes a change which has implications for his political theology. In De trinitate 1-7, the application of this concept to the Father first reflects an earlier usage, which follows a Neoplatonic idea of the divine ἀρχή of the One. However, reflection on scripture and religious polemic force a development, and he gradually abandons the term. While he does not abandon the theological idea of the Father’s special principium, the relations among the divine persons demand a consideration of the principium of the Son in common with the Father, an idea familiar to the debates on filioque. This Augustinian development is like what Erik Peterson identifies in the Cappadocians: a trinitarian theological development which threatens the monarchical political theology that would otherwise appeal to Christian Neoplatonist thinking.
Word and Table: The Origins of a Liturgical Sequence
Authors: Cosgrove Charles H. 
Published: March 2020

Abstract
This article shows that the word-table liturgical sequence set forth in Justin Martyr’s First Apology and attested by at least two other ancient descriptions of Christian community meals is not a departure from Greco-Roman banquet custom but has parallels in the wider culture. The evidence is examined in detail, and a possible rationale for a word-table sequence in a banquet setting is proposed.