Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed under Creative Commons Cc-by 4.0 Epidemiological Research on Parent–child Conflict in the United States: Subgroup Variations by Place of Birth and Ethnicity, 2002–2013

Background. Chronically escalated parent–child conflict has been observed to elicit maladaptive behavior and reduced psychological well-being in children and youth. In this epidemiological study, we sought to estimate the occurrence of escalated parent– child conflict for United States (US) adolescent subgroups defined by (a) ethnic self-identification, and (b) nativity (US-born versus foreign-born). Methods. US study populations of 12-to-17-year-olds were sampled, recruited, and assessed for the National Surveys on Drug Use and Health (NSDUH), 2002–2013 (n = 111,129). Analysis-weighted contingency table analyses contrasted US-born versus foreign-born who self-identified as: (a) Hispanic, (b) non-Hispanic African-American, (c) non-Hispanic Asian, and (c) non-Hispanic White. Broad and sometimes overlapping CI indicate that larger sample sizes are needed for complete evaluation of an apparent excess occurrence of frequent parent-child conflict among US-born versus foreign-born. Nonetheless, in the larger subgroups, the US-born show a clear excess occurrence of frequent parent-child conflict. For example, US-born Mexican children have 1.7 times higher odds of experiencing frequent parent-child conflict than foreign-born Mexican children (OR = 1.7, 95% CI [1.5, 2.0], p-value < 0.001). Discussion. The main discovery from this multi-ethnic sample investigation is a rank-ordering of parent-child conflict prevalence estimates from high (non-Hispanic White) to low (non-Hispanic African-American). The pattern also suggests a possibly gen-eralizable excess associated with US-born subgroups. The epidemiological estimates presented here merit attention in future cross-cultural research focused on parent-child conflict.
Assisted Colorization of Grayscale Images

We propose a colorization tool which utilizes both minimal user input and traditional convolutional neural networks to color gray-scale images. Deep learning can only go so far in solving colorization. Our major contribution is to show how we can condense color information into a low dimensional color palette and be able to infer this color palette from minimal user input. This allows an interactive system in which a user can provide insightful color hints to gray-scale images in order to generate better colored image results.
Pose-Based 3 D Human Motion Analysis Using Extreme Learning Machine

In 3D human motion pose-based analysis, the main problem is how to classify multi-class label activities based on primitive action (pose) inputs efficiently for both accuracy and processing time. Because, pose is not unique and the same pose can be anywhere on different activity classes. In this paper, we evaluate the effectiveness of Extreme Learning Machine (ELM) in 3D human motion analysis based on pose cluster. ELM has reputation as eager classifier with fast training and testing time but the classification result originally has still low testing accuracy even by increasing the hidden nodes number and adding more training data. To achieve better accuracy, we pursue a feature selection method to reduce the dimension of pose cluster training data in time sequence. We propose to use frequency of pose occurrence. This method is similar like bag of words which is a sparse vector of occurrence counts of poses in histogram as features for training data (bag of poses). By using bag of poses as the optimum feature selection, the ELM performance can be improved without adding network complexity (Hidden nodes number and training data).
Polarity Analysis for Food and Disease Relationships

The explosive growth of published articles in biomedical science field has led more research to focus on biomedical relationship extraction. However, there is relatively little investigation conducted on polarity analysis of these relationships, such as food (or nutrition) and disease relationships. In this paper, we investigate how to automatically identify the polarity of relationships between food and disease in biomedical text. In particular, we first analyze the characteristics and challenges of relation polarity analysis, and then propose an integrated approach, which utilizes background knowledge in terms of relation word and polarity class association, and refines this association by using any available domain specific training data. In addition, we propose several novel learning features and a computational approach to construct background knowledge base. Empirical results on real world datasets show that the proposed method is effective.
Implementation of Adaptive Viterbi Decoder on FPGA for Wireless Communication

2 ABSTRACT: A new trend in wireless communication systems has dictated the need for dynamical adaptation of communication systems in order to suit environmental requirements. Wireless networks usually employ sophisticated Forward Error Correction (FEC) techniques such as Viterbi Algorithm to combat with the channel distortion effects such as multipath fading and intersymbol interference. Viterbi algorithm is employed in wireless communication to decode the Convolution codes; these are the class of FEC codes. Such decoders are complex & dissipates large amount of power. Thus this paper presents the design of an Adaptive Viterbi Decoder (AVD) that uses survivor path with parameters in an attempt to reduce the power and cost and at the same time increase in speed. Most of the researches aimed to reduce power consumption or work with high frequency for using the decoder in the modern applications such as 3 GPP, DVB, and wireless technology. Field Programmable Gate Array technology (FPGA) is considered as highly configurable option for implementing many sophisticated signal processing tasks. The proposed viterbi decoder design is simulated on Modelsim.SE6. 3f and implemented using VHDL code.
A three-topology based, wide input range switched-capacitor DC-DC converter with low-ripple and enhanced load line regulations

This paper presents a novel switched-capacitor (SC) DC-DC converter that incorporates three conversion topologies. At 100 kHz, the design is proposed to cater to wide input range, of 2.5 V to 4.5 V. Excellent accuracy and output regulation capabilities are obtained with output ripple voltage and error of <; 6 mV and <; 1.3%, respectively, when operated with a fixed output voltage of 1 V. A proportional-integral (PI) compensator is constructed for close-loop feedback compensation where it successfully enhanced both the load and line regulations. Finally, the peak efficiency of 70.76% is obtained at full load.
Real-time On-Demand Crowd-powered Entity Extraction

Output-agreement mechanisms such as ESP Game have been widely used in human computation to obtain reliable human-generated labels. In this paper, we argue that a "time-limited" output-agreement mechanism can be used to create a fast and robust crowd-powered component in interactive systems, particularly dialogue systems, to extract key information from user utterances on the fly. Our experiments on Amazon Mechanical Turk using the Airline Travel Information System (ATIS) dataset showed that the proposed approach achieves high-quality results with an average response time shorter than 9 seconds.
Cerebral blood flow MRI in mice using the cardiac‐spin‐labeling technique

Continuous arterial spin labeling MRI with a separate neck labeling coil provides a highly sensitive method to image cerebral blood flow (CBF). In mice, however, this has not been possible because the proximity of the neck coil to the brain uses the neck coil to significantly saturate the brain signal. To overcome this limitation the cardiac spin labeling (CSL) technique is introduced in which the labeling coil is placed at the heart position. To demonstrate its utility, CSL CBF was applied to image quantitative basal CBF and hypercapnia‐induced CBF changes. This approach provides a practical means to image CBF with high sensitivity in small animals, compares favorably to existing mouse CBF imaging techniques, and could broaden CBF applications in mice where many brain disease and transgenic models are widely available. Magn Reson Med 60:744–748, 2008. © 2008 Wiley‐Liss, Inc.
Language-Based Security for Software-Defined Networks

In many settings, including campuses, enterprises, militaries, and datacenters, networks must be shared between entities that send and receive traffic over common hardware. We analyze the fundamental problem of how to program shared networks in a secure and reliable manner. Our solution is based on a new programming model that supports the concept of a network slice. Slices isolate the traffic of one program from another, and also isolate traffic within a single program from other traffic generated by the same program. Consequently, slices bring a critical form of modularity to network programs that has long been absent. We develop a semantics for slices, illustrate the kinds of modular reasoning principles they enable, provide formal definitions of end-to-end security properties they guarantee, and prove the correctness of a slice compiler for an idealized core calculus. We describe our implementation and a translation validation framework based on the Z3 prover.
A dynamic subgrid-scale model based on differential filters for LES of particle-laden turbulent flows By

where it is assumed that the flow around the particles is dominated by molecular transport. In this formulation, xp,i and up,i are the particle position and particle velocity, ρp and a are the particle density and radius, and μ is the dynamic viscosity of the carrier phase. In Eq. (1.2), ui refers to the full-scale velocity of the carrier phase at the particle position, which in direct numerical simulations (DNS) is obtained by integrating the Navier Stokes equations. In contrast, in large-eddy simulations (LES) the only velocity available is the filtered one, denoted here by ui. In particular, when the mass of particles per unit mass of carrier phase is small, the filtered velocity is obtained by integrating
Private Equity Returns : Persistence and Capital Flows

This paper investigates individual fund returns in the private equity industry using a unique data set collected by Venture Economics. We find a large degree of heterogeneity among fund returns. Those returns persist strongly across funds by private equity firms. The returns also improve with firm experience. Better performing funds are more likely to raise follow-on funds and raise larger funds than more poorly performing firms. This relationship is concave so that top performing funds grow more slowly than the market average. Finally, we find that funds that are raised in boom times (and firms that are started in boom times) are less likely to raise a follow-on fund, suggesting that these funds perform worse. Several of these results differ substantially from those for mutual funds. ∗Very Preliminary draft. Please do not quote without authors’ permission. University of Chicago Graduate School of Business, NBER; MIT Sloan School of Management, NBER and CEPR. Addresses: 1101 E. 58th Street, Chicago, IL 60637; 50 Memorial Drive, E52-447, Cambridge, MA 02142. E-mail: steve.kaplan@gsb.uchicago. edu; aschoar@mit.edu. We thank Ken Morse and Jesse Reyes for making this project possible. We thank seminar participants at the University of Alberta and NYU. All data for this project were obtained from the VentureExpert database collected by Venture Economics.
Artefacts Removal to Detect Visual Evoked Potentials in Brain Computer Interface Systems

The interference of artefacts with evoked scalp electroencephalogram (EEG) responses is a problem in event related brain computer interface (BCI) system that reduces signal quality and interpretability of user's intentions. Many strategies have been proposed to reduce the effects of non-neural artefacts, while the activity of neural sources that do not reflect the considered stimulation has been neglected. However discerning such activities from those to be retained is important, but subtle and difficult as most of their features are the same. We propose an automated method based on a combination of a genetic algorithm (GA) and a support vector machine (SVM) to select only the sources of interest. Temporal, spectral, wavelet, autoregressive and spatial properties of independent components (ICs) of EEG are inspected. The method selects the most distinguishing subset of features among this comprehensive fused set of information and identifies the components to be preserved. EEG data were recorded from 12 healthy subjects in a visual evoked potential (VEP) based BCI paradigm and the corresponding ICs were classified by experts to train and test the algorithm. They were contaminated with different sources of artefacts, including electromyogram (EMG), electrode connection problems, blinks and electrocardiogram (ECG), together with neural contributions not related to VEPs. The accuracy of ICs classification was about 88.5% and the energetic residual error in recovering the clean signals was 3%. These performances indicate that this automated method can effectively identify and remove main artefacts derived from either neural or non-neural sources while preserving VEPs. This could have important potential applications, contributing to speed and remove subjectivity of the cleaning procedure by experts. Moreover, it could be included in a real time BCI as a pre-processing step before the identification of the user’s intention.
Leader Development or Leader Distress? Examining the Interactive Effects of Leadership Self-Efficacy and Situational Strength on Perceptions of Stress, Performance, and Physiological Responses

Academic) Stress is a concept that can be studied using a variety of theoretical approaches, with a focus on the individual’s perceptions, the external stressor, or the physiological reactions of stress responding. However these approaches are often used independently, when they can be used complementarily to understand the nuanced relationship between the individual and the situation when appraising stressors as challenges or threats. The current study examined the relationship between individual differences in perceptions, situational strength (both as a categorical and a continuous predictor), and physiological reactions in a leadership task. Situational strength and leadership self-efficacy were found to interact, such that those high is LSE reported more appraisals of challenge as situational strength increased.
Performance of amplify-and-forward multihop transmission over relay clusters with different routing strategies

We consider a multihop relay network in which two terminals are communicating with each other via a number of cluster of relays. Performance of such networks depends on the routing protocols employed. In this paper, we find the expressions for the Average Symbol Error Probability ASEP performance of Amplify-and-Forward AF multihop transmission for the simplest routing protocol in which the relay transmits using the channel having the best Signal to Noise Ratio SNR. The ASEP performance of a better protocol proposed in Gui et al. 2009 known as the adhoc protocol is also analyzed. The derived expressions for the performance are a convenient tool to analyze the performance of AF multihop transmission over relay clusters. Monte-Carlo simulations verify the correctness of the proposed formulation and are in agreement with analytical results. Furthermore, we propose new generalized protocols termed as last-n-hop selection protocol, the dual path protocol, the forward-backward last-n-hop selection protocol and the forward-backward dual path protocol, to get improved ASEP performances. The ASEP performance of these proposed schemes is analysed by computer simulations. It is shown that close to optimal performance can be achieved by using the last-n-hop selection protocol and its forward-backward variant. The complexity of the protocols is also studied.
Informing Determiner and Preposition Error Correction with Hierarchical Word Clustering

We extend our n-gram-based data-driven prediction approach from the Helping Our Own (HOO) 2011 Shared Task (Boyd and Meurers, 2011) to identify determiner and preposition errors in non-native English essays from the Cambridge Learner Corpus FCE Dataset (Yannakoudakis et al., 2011) as part of the HOO 2012 Shared Task. Our system focuses on three error categories: missing determiner, incorrect determiner, and incorrect preposition. Approximately two-thirds of the errors annotated in HOO 2012 training and test data fall into these three categories. To improve our approach, we developed a missing determiner detector and incorporated word clustering (Brown et al., 1992) into the n-gram prediction approach.
An unconventional path to greater social-communication skills and independence for an adolescent on the autism spectrum

Background In 2015, a father took his 14-year-old son who is on the autism spectrum on a six-month journey aimed to develop his son’s social-communication and independent living skills. The duo travelled across 10 countries, meeting people and practising these skills. This study examined their goals, motivations for, and outcomes of the journey. Method We used intrinsic case study methodology with mixed methods, including interviews with parents and professionals; analyses of filmed interactions between the son, his father and strangers during the journey; and descriptive analysis of parent-reported changes in their son’s participation at home, school and in the community using the Participation and Environment Measure – Children and Youth. Results Qualitative analysis of the interviews with parents and professionals revealed a set of insightful goals and motivations, focusing on creating an optimal environment for the son’s development. Parents reported increases in their son’s social-communication and independent living skills, but also unexpected changes in his perspective and self-belief. The former findings were consistent with those arising from video analysis, whereby social-pragmatic skills critical to good conversations (staying on topic, body position, eye contact) all increased over the course of the journey, while abrupt topic changes and conversational prompts reduced. Participation and inclusion across home, school and community settings all increased over the same period. Conclusion While this study makes no claims regarding causation, the findings indicate that the journey was associated with positive changes for the son and his parents, leading to greater expectations for, and progress towards, independence following the journey. Implications of the findings for supporting young people on the autism spectrum in regular community settings are discussed.
Determining health-care facility catchment areas in Uganda using data on malaria-related visits.

OBJECTIVE To illustrate the use of a new method for defining the catchment areas of health-care facilities based on their utilization. METHODS The catchment areas of six health-care facilities in Uganda were determined using the cumulative case ratio: the ratio of the observed to expected utilization of a facility for a particular condition by patients from small administrative areas. The cumulative case ratio for malaria-related visits to these facilities was determined using data from the Uganda Malaria Surveillance Project. Catchment areas were also derived using various straight line and road network distances from the facility. Subsequently, the 1-year cumulative malaria case rate was calculated for each catchment area, as determined using the three methods. FINDINGS The 1-year cumulative malaria case rate varied considerably with the method used to define the catchment areas. With the cumulative case ratio approach, the catchment area could include noncontiguous areas. With the distance approaches, the denominator increased substantially with distance, whereas the numerator increased only slightly. The largest cumulative case rate per 1000 population was for the Kamwezi facility: 234.9 (95% confidence interval, CI: 226.2-243.8) for a straight-line distance of 5 km, 193.1 (95% CI: 186.8-199.6) for the cumulative case ratio approach and 156.1 (95% CI: 150.9-161.4) for a road network distance of 5 km. CONCLUSION Use of the cumulative case ratio for malaria-related visits to determine health-care facility catchment areas was feasible. Moreover, this approach took into account patients' actual addresses, whereas using distance from the facility did not.
An atypical orthologue of 6-pyruvoyltetrahydropterin synthase can provide the missing link in the folate biosynthesis pathway of malaria parasites

Folate metabolism in malaria parasites is a long‐standing, clinical target for chemotherapy and prophylaxis. However, despite determination of the complete genome sequence of the lethal species Plasmodium falciparum, the pathway of de novo folate biosynthesis remains incomplete, as no candidate gene for dihydroneopterin aldolase (DHNA) could be identified. This enzyme catalyses the third step in the well‐characterized pathway of plants, bacteria, and those eukaryotic microorganisms capable of synthesizing their own folate. Utilizing bioinformatics searches based on both primary and higher protein structures, together with biochemical assays, we demonstrate that P. falciparum cell extracts lack detectable DHNA activity, but that the parasite possesses an unusual orthologue of 6‐pyruvoyltetrahydropterin synthase (PTPS), which simultaneously gives rise to two products in comparable amounts, the predominant of which is 6‐hydroxymethyl‐7,8‐dihydropterin, the substrate for the fourth step in folate biosynthesis (catalysed by 6‐hydroxymethyl‐7,8‐dihydropterin pyrophosphokinase; PPPK). This can provide a bypass for the missing DHNA activity and thus a means of completing the biosynthetic pathway from GTP to dihydrofolate. Supported by site‐directed mutagenesis experiments, we ascribe the novel catalytic activity of the malarial PTPS to a Cys to Glu change at its active site relative to all previously characterized PTPS molecules, including that of the human host.
Nystatin as a probe for investigating the electrical properties of a tight epithelium

We show how the antibiotic nystatin may be used in conjunction with microelectrodes to resolve transepithelial conductance Gt into its components: Ga, apical membrane conductance; Gbl, basolateral membrane conductance; and Gj, junctional conductance. Mucosal addition of nystatin to rabbit urinary bladder in Na+-containing solutions caused Gt to increase severalfold to ca. 460 micrometerho/muF, and caused the transepithelial voltage Vt to approach +50 mV regardless of its initial value. From measurements of Gt and the voltage-divider ratio as a function of time after addition or removal of nystatin, values for Ga, Gbl, and Gj of untreated bladder could be obtained. Nystatin proved to have no direct effect on Gbl or Gj but to increase Ga by about two orders of magnitude, so that the basolateral membrane then provided almost all of the electrical resistance in the transcellular pathway. The nystatin channel in the apical membrane was more permeable to cations than to anions. The dose-response curve for nystatin had a slope of 4.6. Use of nystatin permitted assessment of whether microelectrode impalement introduced a significant shunt conductance into the untreated apical membrane, with the conclusion that such a shunt was negligible in the present experiments. Nystatin caused a hyperpolarization of the basolateral membrane potential in Na+- containing solutions. This may indicate that the Na+ pump in this membrane is electrogenic.