Miracle-dz/UniFAR-FTUs huggingface dataset:
The Prevalence of Emotional and Behaviour Disorders and Patterns of Service Utilisation in Children and Adolescents

This study compared the prevalence of emotional and behavioural disorders in children attending schools of different socio-economic class. In addition, the study compared the rate of service utilization by children with and without disorders. Using cutoff scores recommended for use with Australian children, the prevalence of disorders in schools of different socio-economic class ranged from 2.3±2.2 to 13.9±5.3 per 100 children, with the highest prevalence being found in the lower socio-economic class schools. Although few children with disorders had been seen in a mental health clinic, advice had been sought from other services with regard to 66% of these children. This high rate of service utilization by children with disorders highlights the key role that general practitioners, school guidance officers and hospital services could play in facilitating the early identification and management of children with emotional and behavioural disorders.
Renal Function in Gout: Long-Term Treatment Effects of Febuxostat

Background:The association between hyperuricemia, gout, and impaired renal function has long been recognized. Recent data provide evidence for the causal relationship between elevated serum urate (sUA) and renal changes, leading to declines in glomerular filtration rates. In healthy adults, glomerular filtration rate wanes with age. Urate-lowering therapy (ULT) with allopurinol has been shown to stabilize or reverse this. Objective:Here we examine the long-term effects of ULT with febuxostat on estimated glomerular filtration rate (eGFR). Methods:This is a post hoc analysis of the Febuxostat Open-label Clinical trial of Urate-lowering efficacy and Safety study, during which 116 hyperuricemic gout subjects received daily doses of febuxostat (40, 80, or 120 mg) for up to 5 years. sUA concentrations and eGFR were assessed regularly. Results were stratified by mean change in sUA from baseline. Mathematical modeling was used to predict the effect of sUA reduction on eGFR. Results:Maintenance or improvement in eGFR was inversely correlated with the quantitative reduction in sUA from baseline. For every 1 mg/dL decrease in sUA, the model projected an expected improvement in eGFR of 1 mL/min from the untreated value. Conclusion:Individuals with the greatest reductions in sUA may experience reduced rates of renal deterioration or even stabilization of renal function. Further studies examining the impact of long-term ULT on renal function in hyperuricemic gout patients are needed to both confirm our results and verify if improvements in renal function are feasible in such patients.
Experimentally increased insectivorous bird density results in a reduction of caterpillar density and leaf damage to Pyrenean oak

The indirect effect of insectivorous breeding-bird density on Pyrenean oak (Quercus pyrenaica) through consumption of leaf-damaging caterpillars in a temperate deciduous forest was examined. Caterpillar abundance, caterpillar body mass and the resultant leaf damage were compared between a plot with nest-boxes and a plot without nest-boxes within the same forest. First, the installation of nest-boxes led to an increase in the breeding population of insectivorous birds. Second, the present study reports experimental evidence, under natural conditions, that a high breeding-bird density depresses the numbers of free-living defoliating caterpillars. Third, caterpillars reached significantly lower body masses in the nest-box plot than in the control plot. Finally, caterpillar damage to oak leaves was significantly less in the nest-box plot compared with the control plot. Therefore, the installation of nest-boxes is an effective means of decreasing insect damage to oak leaves. These results suggest that breeding-bird predation (the third trophic level) can be important in the regulation of interactions between oak and caterpillars (the first and second trophic levels, respectively).
PHYSIOLOGICALLY BASED PHARMACOKINETIC MODEL FOR PRALMORELIN HYDROCHLORIDE IN RATS

Pralmorelin hydrochloride (pralmorelin), consisting of six amino acid residues, is a growth hormone-releasing peptide. The aim of this study is to analyze the pharmacokinetics of pralmorelin after intravenous bolus administration to rats, and to develop a physiologically based pharmacokinetic (PB-PK) model to describe and predict the concentrations of pralmorelin in blood and tissues. Pralmorelin (3 mg/kg) was administered intravenously to 24 Sprague-Dawley rats. Groups of three rats were sacrificed by decapitation at each designated time point (up to 4 h), and plasma and tissues (brain, lung, heart, liver, kidney, small intestine, muscle, adipose, and skin) were collected. Bile was also pooled until decapitation. The concentration of pralmorelin in samples was determined by liquid chromatography-tandem mass spectrometry. Plasma concentrations of pralmorelin declined rapidly in a biexponential manner. Biliary excretion of pralmorelin was so rapid that 80% of the dose was recovered unchanged in the bile within 1 h after administration. The distribution parameters in each tissue were obtained by using a hybrid model and an integration plot. They revealed that the distribution of pralmorelin into liver was blood flow-limited, and its distribution was permeability-limited in all other tissues. The PB-PK model developed in this study well described the time courses of pralmorelin concentration in the blood and tissues of rats.
A DNase Encoded by Integrated Element CJIE1 Inhibits Natural Transformation of Campylobacter jejuni

ABSTRACT The species Campylobacter jejuni is considered naturally competent for DNA uptake and displays strong genetic diversity. Nevertheless, nonnaturally transformable strains and several relatively stable clonal lineages exist. In the present study, the molecular mechanism responsible for the nonnatural transformability of a subset of C. jejuni strains was investigated. Comparative genome hybridization indicated that C. jejuni Mu-like prophage integrated element 1 (CJIE1) was more abundant in nonnaturally transformable C. jejuni strains than in naturally transformable strains. Analysis of CJIE1 indicated the presence of dns (CJE0256), which is annotated as a gene encoding an extracellular DNase. DNase assays using a defined dns mutant and a dns-negative strain expressing Dns from a plasmid indicated that Dns is an endogenous DNase. The DNA-hydrolyzing activity directly correlated with the natural transformability of the knockout mutant and the dns-negative strain expressing Dns from a plasmid. Analysis of a broader set of strains indicated that the majority of nonnaturally transformable strains expressed DNase activity, while all naturally competent strains lacked this activity. The inhibition of natural transformation in C. jejuni via endogenous DNase activity may contribute to the formation of stable lineages in the C. jejuni population.
Renal Dysfunction, Stroke Risk Scores (CHADS2, CHA2DS2-VASc, and R2CHADS2), and the Risk of Thromboembolic Events After Catheter Ablation of Atrial Fibrillation: The Leipzig Heart Center AF Ablation Registry

Background— There are limited data on the predictive value of stroke risk scores for thromboembolic events (TEs) after catheter ablation of atrial fibrillation (AF). Our objectives were to report the incidence of TEs after AF ablation in a large contemporary AF ablation cohort and to investigate the impact of renal dysfunction and the value of stroke risk stratification scores (CHADS2, CHA2DS2-VASc, and R2CHADS2) for predicting TE after AF ablation. Methods and Results— Using the Leipzig Heart Center AF Ablation Registry, we documented TEs in patients undergoing radiofrequency AF catheter ablation. TE was defined as stroke, transient ischemic attack, or systemic embolism. Study population (N=2069; 66% men; 60±10 years; 62% paroxysmal AF; mean CHADS2, 1.2±0.9; CHA2DS2-VASc, 2.1±1.4; and R2CHADS2, 1.3±1.1) were followed up for a median 18 (Q1–Q3, 12–29) months (ie, 3078 patient-years). Overall, 31 TEs occurred, with 16 events within 30 days of ablation and 15 TEs (0.72%) during the follow-up period. On multivariate analysis, CHADS2 (P<0.001), R2CHADS2 (P<0.001), and CHA2DS2-VASc (P=0.003) scores were independent predictors of TEs during follow-up, and AF recurrence conferred a nonsignificant trend for increased TE risk (P=0.071–0.094). The CHA2DS2-VASc score further differentiated TE risk in patients with CHADS2 and R2CHADS2 0 to 1 (0.13% if CHA2DS2-VASc was 0–1 and 0.71% if CHA2DS2-VASc was >2) and had the best predictive value in patients with AF recurrences (c-index 0.894, P=0.022 versus CHADS2, P=0.031 versus R2CHADS2). Conclusions— CHADS2, CHA2DS2-VASc, and R2CHADS2 scores were associated with TE risk. The CHA2DS2-VASc score differentiated TE risk in the low-risk strata based on CHADS2 and R2CHADS2 scores and may be superior in the subgroup with AF recurrences.
A Comparison of Classification Methods for Telediagnosis of Parkinson's Disease

Parkinson’s disease (PD) is a progressive and chronic nervous system disease that impairs the ability of speech, gait, and complex muscle-and-nerve actions. Early diagnosis of PD is quite important for alleviating the symptoms. Cost effective and convenient telemedicine technology helps to distinguish the patients with PD from healthy people using variations of dysphonia, gait or motor skills. In this study, a novel telemedicine technology was developed to detect PD remotely using dysphonia features. Feature transformation and several machine learning (ML) methods with 2-, 5- and 10-fold cross-validations were implemented on the vocal features. It was observed that the combination of principal component analysis (PCA) as a feature transformation (FT) and k-nearest neighbor (k-NN) as a classifier with 10-fold cross-validation has the best accuracy as 99.1%. All ML processes were applied to the prerecorded PD dataset using a newly created program named ParkDet 2.0. Additionally, the blind test interface was created on the ParkDet so that users could detect new patients with PD in future. Clinicians or medical technicians, without any knowledge of ML, will be able to use the blind test interface to detect PD at a clinic or remote location utilizing internet as a telemedicine application.
Traffic duplication through segmentable disjoint paths

Ultra-low latency is a key component of safety-critical operations such as robot-assisted remote surgery or financial applications where every single millisecond counts. In this paper, we show how network operators can build upon the recently proposed Segment Routing architecture to provide a traffic duplication service to better serve the users of such demanding applications. We propose the first implementation of Segment Routing in the Linux kernel and leverage it to provide a traffic duplication service that sends packets over disjoint paths. Our experiments show that with such a service existing TCP stacks can preserve latency in the presence of packet losses. We also propose and evaluate an efficient algorithm that computes disjoint paths that can be realised by using segments. Our evaluation with real and synthetic network topologies shows that our proposed algorithms perform well in large networks.
The Impact of Intra-State Conflict on Economic Welfare and Consumption Smoothing: Empirical Evidence for the Displaced Population in Colombia

Intra-state conflicts and forced displacement impose a heavy burden upon the civil population, and produce severe welfare losses. Using a household level data administered to 2.322 Colombian displaced households, we estimate welfare losses for displaced households, as well as the determinants of labor income and aggregate consumption in reception sites. We also asses whether households are able to smooth consumption, and analyze the strategies they are compelled to adopt. Our results indicate that forced displacement entails a significant asset loss, limits the ability of household to generate income, disrupts risk-sharing mechanisms, and obliges households to rely on costly strategies in order to smooth consumption. Thus, the short and long-term consequences of forced displacement are large, and the need to design and implement specific policies for victims of internal conflict is evident. These policies, in particular, should provide mechanisms to prevent substantial welfare losses and to create conditions for sustainable income generation processes.
Maternal Arsenic Exposure and DNA Damage Biomarkers, and the Associations with Birth Outcomes in a General Population from Taiwan

Inorganic arsenic (iAs) is an established transplacental agent known to affect fetal development in animal studies. However, iAs has not been adequately studied in the general population with respect to iAs exposure during pregnancy and its impact on the health status of newborns. The aims of this study were to 1) elucidate the association between arsenic exposure and oxidative/methylated DNA damage in pregnant women, and 2) determine the association with birth outcomes. A birth cohort study of 299 pregnant mother-newborn pairs was recruited during 2001–2002 in Taiwan. We collected maternal urine samples during the 3rd trimester for measuring iAs and its metabolites. We used high-performance liquid chromatography/inductively coupled plasma mass spectrometry (HPLC-ICP-MS) for quantifications of the arsenic species. Liquid chromatography/tandem mass spectrometer (LC-MS/MS) was used to measure the 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG) and N7-methylguanosine (N7-MeG) DNA damage biomarkers. Birth outcomes were collected to assess the associations with maternal arsenic exposure and the DNA damage biomarkers. Multiple regression analyses showed that maternal urinary iAs had positive associations with the methylated N7-MeG (beta = 0.35, p<0.001) and oxidative 8-oxodG (beta = 0.24, p<0.001) DNA damage biomarkers, and a decreased one-minute (1-min) Apgar score (beta = -0.23, p = 0.041). Maternal N7-MeG was also associated with a decreased 1-min Apgar score (beta = −0.25, p = 0.042). Mutual adjustment for iAs and N7-MeG showed an independent and significant prediction for a decreased 1-min Apgar score of iAs (beta = −0.28, p = 0.036). Maternal iAs exposure was associated with both maternal DNA damage and adverse newborn health. Maternal N7-MeG levels might be a novel biomarker for monitoring fetal health related to iAs.
Identifying Node Role in Social Network Based on Multiple Indicators

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role.
A self-evaluated assessment suitable for seriously ill hospice patients

Current quality of life (QOL) assessments, whilst being suitable for patients undergoing active treatment, are often too cumbersome for patients who are in the terminal phase of their illness, and may themselves produce distress. In an attempt to measure QOL in these patients a simple assessment was piloted (PEPS - patient evaluated problem score) in which patients were asked to identify and grade major problems as they perceived them and also to grade problems previously identified by the medical and nursing staff. A global QOL score and a self-administered WHO score completed the assessment. Of 70 patients admitted to the unit over a seven-month period, 44 completed questionnaires, 38 in full. Subsequently, uptake has been far greater (due to establishment of the method as part of routine care) with 73% of all patients admitted to our unit completing PEPS. Overall, a mean of 5.6 problems per patient were identified, of which 14% were psychosocial. Of those patients who completed questionnaires, 58% identified problems not picked up by the nursing and medical staff; 52% of these were psychosocial problems. Of 28 patients who died having previously completed questionnaires 22 had done so in the previous three weeks including eight in the previous seven days. PEPS has proved very useful in the management of patients, enabling the identification of previously unrecognized or underrated problems, particularly of a psychosocial nature, and also as a means of evaluating progress. It is readily acceptable to patients, even those close to death.
Computing With Contextual Numbers

Self Organizing Map (SOM) has been applied into several classical modeling tasks including clustering, classification, function approximation and visualization of high dimensional spaces. The final products of a trained SOM are a set of ordered (low dimensional) indices and their associated high dimensional weight vectors. While in the above-mentioned applications, the final high dimensional weight vectors play the primary role in the computational steps, from a certain perspective, one can interpret SOM as a nonparametric encoder, in which the final low dimensional indices of the trained SOM are pointer to the high dimensional space. We showed how using a one-dimensional SOM, which is not common in usual applications of SOM, one can develop a nonparametric mapping from a high dimensional space to a continuous one-dimensional numerical field. These numerical values, called contextual numbers, are ordered in a way that in a given context, similar numbers refer to similar high dimensional states. Further, as these numbers can be treated similarly to usual continuous numbers, they can be replaced with their corresponding high dimensional states within any data driven modeling problem. As a potential application, we showed how using contextual numbers could be used for the problem of high dimensional spatiotemporal dynamics.
An Unscented Kalman Filter Approach to the Estimation of Nonlinear Dynamical Systems Models

In the past several decades, methodologies used to estimate nonlinear relationships among latent variables have been developed almost exclusively to fit cross-sectional models. We present a relatively new estimation approach, the unscented Kalman filter (UKF), and illustrate its potential as a tool for fitting nonlinear dynamic models in two ways: (1) as a building block for approximating the log–likelihood of nonlinear state–space models and (2) to fit time-varying dynamic models wherein parameters are represented and estimated online as other latent variables. Furthermore, the substantive utility of the UKF is demonstrated using simulated examples of (1) the classical predator-prey model with time series and multiple–subject data, (2) the chaotic Lorenz system and (3) an empirical example of dyadic interaction.
Sonic interventions: understanding and extending the domestic soundscape

This paper presents a new study of the role, importance and meaning of sound in the home. Drawing on interview data and sound recordings gathered from seven households, this study offers fresh insight into the ways in which the domestic soundscape is managed and understood. The data revealed that household members engaged in a wide variety of sound management practices to monitor and control the real-time flow of sonic information throughout the home. They also showed that families were sometimes surprised and delighted by the ability to record fragments of the soundscape for later use. These findings suggest a number of roles for technology in enhancing the domestic soundscape and its associated behaviors, which we present here in the form of example sonic interventions created in a design workshop at the end of the project.
Consensus protocols for distributed tracking in wireless camera networks

Consensus-based target tracking in camera networks faces three major problems: non-linearity in the measurement model, temporary lack of measurements (naivety) due to the limited field of view (FOV) and redundancy in the iterative exchange of information. In this paper we propose two consensus-based distributed algorithms for non-linear systems using the Extended Information Filter as underlying filter to handle the non-linearity in the camera measurement model. The first algorithm is an Extended Information Consensus Filter (EICF) that overcomes the effect of naivety and non-linearity without requiring knowledge of other nodes in the network. The second algorithm is an Extended Information Weighted Consensus Filter (EIWCF) that overcomes all the three major problems (naivety, redundancy and non-linearity) but requires knowledge of the number of cameras (Nc) in the network. The basic principle of these algorithms is weighting node estimates based on their covariance information. When Nc is not available, EICF can be used at the cost of not handling the redundancy problem. Simulations with highly maneuvering targets show that the two proposed distributed non-linear consensus filters outperform the related state of the art by achieving higher accuracy and faster convergence to the centralised estimates computed by simultaneously considering the information from all the nodes.
Health and Christianity: Controlling for Omitted Variable Bias by Using the Data of Twins and Siblings

To account for potential bias from heterogeneity in hereditary factors or family background, I use the within-twin and within-siblings differences to estimate the effects of Christian faith on three health outcome variables by applying fixed effect model to the data of twins and siblings from the first wave of the National Survey of Midlife in the United States (1995). Both this model and other statistical tests and model without controlling for omitted variable bias confirm significant positive health effects of religiosity of Christianity. The results also support the three explanatory mechanisms of religion on health proposed by Son and Wilson (2011): 1) behaviors and lifestyles, 2) social networks and 3) social support and psychological resources. However, the data also suggests that either other channels through which religiosity affects health may exist or the mechanism of psychological resources goes far beyond of “good moods” and contains much more plentiful and profound connotations that is relevant to health.