snu-aidas/HVMap-dataset huggingface dataset:
Living in two homes-a Swedish national survey of wellbeing in 12 and 15 year olds with joint physical custody

BACKGROUND
The practice of joint physical custody, where children spend equal time in each parent's home after they separate, is increasing in many countries. It is particularly common in Sweden, where this custody arrangement applies to 30 per cent of children with separated parents. The aim of this study was to examine children's health-related quality of life after parental separation, by comparing children living with both parents in nuclear families to those living in joint physical custody and other forms of domestic arrangements.


METHODS
Data from a national Swedish classroom study of 164,580 children aged 12 and 15-years-old were analysed by two-level linear regression modelling. Z-scores were used to equalise scales for ten dimensions of wellbeing from the KIDSCREEN-52 and the KIDSCREEN-10 Index and analysed for children in joint physical custody in comparison with children living in nuclear families and mostly or only with one parent.


RESULTS
Living in a nuclear family was positively associated with almost all aspects of wellbeing in comparison to children with separated parents. Children in joint physical custody experienced more positive outcomes, in terms of subjective wellbeing, family life and peer relations, than children living mostly or only with one parent. For the 12-year-olds, beta coefficients for moods and emotions ranged from -0.20 to -0.33 and peer relations from -0.11 to -0.20 for children in joint physical custody and living mostly or only with one parent. The corresponding estimates for the 15-year-olds varied from -0.08 to -0.28 and from -0.03 to -0.13 on these subscales. The 15-year-olds in joint physical custody were more likely than the 12-year-olds to report similar wellbeing levels on most outcomes to the children in nuclear families.


CONCLUSIONS
Children who spent equal time living with both parents after a separation reported better wellbeing than children in predominantly single parent care. This was particularly true for the 15-year-olds, while the reported wellbeing of 12-years-olds was less satisfactory. There is a need for further studies that can account for the pre and post separation context of individual families and the wellbeing of younger age groups in joint physical custody.
VALUE , RARENESS , COMPETITIVE ADVANTAGE , AND PERFORMANCE : A CONCEPTUAL-LEVEL EMPIRICAL INVESTIGATION OF THE RESOURCE-BASED VIEW OF THE FIRM

The resource-based view of the firm (RBV) hypothesizes that the exploitation of valuable, rare resources and capabilities contributes to a firm’s competitive advantage, which in turn contributes to its performance. Despite this notion, few empirical studies test these hypotheses at the conceptual level. In response to this gap, this study empirically examines the relationships between value, rareness, competitive advantage, and performance. The results suggest that value and rareness are related to competitive advantage, that competitive advantage is related to performance, and that competitive advantage mediates the rareness-performance relationship. These findings have important academic and practitioner implications which are then discussed. Copyright  2008 John Wiley & Sons, Ltd.
Dragonfly wing nodus: A one-way hinge contributing to the asymmetric wing deformation.

Dragonfly wings are highly specialized locomotor systems, which are formed by a combination of several structural components. The wing components, also known as structural elements, are responsible for the various aspects of the wing functionality. Considering the complex interactions between the wing components, modelling of the wings as a whole is only possible with inevitable huge oversimplifications. In order to overcome this difficulty, we have recently proposed a new approach to model individual components of complex wings comparatively. Here, we use this approach to study nodus, a structural element of dragonfly wings which has been less studied to date. Using a combination of several imaging techniques including scanning electron microscopy (SEM), wide-field fluorescence microscopy (WFM), confocal laser scanning microscopy (CLSM) and micro-computed tomography (micro-CT) scanning, we aim to characterize the spatial morphology and material composition of fore- and hindwing nodi of the dragonfly Brachythemis contaminata. The microscopy results show the presence of resilin in the nodi, which is expected to help the deformability of the wings. The computational results based on three-dimensional (3D) structural data suggest that the specific geometry of the nodus restrains its displacements when subjected to pressure on the ventral side. This effect, resulting from an interlocking mechanism, is expected to contribute to the dorso-ventral asymmetry of wing deformation and to provide a higher resistance to aerodynamic forces during the downstroke. Our results provide an important step towards better understanding of the structure-property-function relationship in dragonfly wings.


STATEMENT OF SIGNIFICANCE
In this study, we investigate the wing nodus, a specialized wing component in dragonflies. Using a combination of modern imaging techniques, we demonstrate the presence of resilin in the nodus, which is expected to facilitate the wing deformability in flight. The specific geometry of the nodus, however, seems to restrain its displacements when subjected to pressure on the ventral side. This effect, resulting from an interlocking mechanism, is suggested to contribute to dorso-ventral asymmetry of wing deformations and to provide a higher resistance to aerodynamic forces during the downstroke. Our results provide an important step towards better understanding of the structure-property-function relationship in dragonfly wings and might help to design more efficient wings for biomimetic micro-air vehicles.
End-to-End Sound Source Separation Conditioned On Instrument Labels

Can we perform an end-to-end sound source separation (SSS) with a variable number of sources using a deep learning model? This paper presents an extension of the WaveU-Net [1] model which allows end-to-end monaural source separation with a non-fixed number of sources. Furthermore, we propose multiplicative conditioning with instrument labels at the bottleneck of the Wave-U-Net and show its effect on the separation results. This approach can be further extended to other types of conditioning such as audio-visual SSS and score-informed SSS.
The efficiency frontier approach to economic evaluation of health-care interventions.

BACKGROUND
IQWiG commissioned an international panel of experts to develop methods for the assessment of the relation of benefits to costs in the German statutory health-care system.


PROPOSED METHODS
The panel recommended that IQWiG inform German decision makers of the net costs and value of additional benefits of an intervention in the context of relevant other interventions in that indication. To facilitate guidance regarding maximum reimbursement, this information is presented in an efficiency plot with costs on the horizontal axis and value of benefits on the vertical. The efficiency frontier links the interventions that are not dominated and provides guidance. A technology that places on the frontier or to the left is reasonably efficient, while one falling to the right requires further justification for reimbursement at that price. This information does not automatically give the maximum reimbursement, as other considerations may be relevant. Given that the estimates are for a specific indication, they do not address priority setting across the health-care system.


CONCLUSION
This approach informs decision makers about efficiency of interventions, conforms to the mandate and is consistent with basic economic principles. Empirical testing of its feasibility and usefulness is required.
Activities on Facebook Reveal the Depressive State of Users

BACKGROUND
As online social media have become prominent, much effort has been spent on identifying users with depressive symptoms in order to aim at early diagnosis, treatment, and even prevention by using various online social media. In this paper, we focused on Facebook to discern any correlations between the platform's features and users' depressive symptoms. This work may be helpful in trying to reach and detect large numbers of depressed individuals more easily.


OBJECTIVE
Our goal was to develop a Web application and identify depressive symptom-related features from users of Facebook, a popular social networking platform.


METHODS
55 Facebook users (male=40, female=15, mean age 24.43, SD 3.90) were recruited through advertisement fliers distributed to students in a large university in Korea. Using EmotionDiary, the Facebook application we developed, we evaluated depressive symptoms using the Center for Epidemiological Studies-Depression (CES-D) scale. We also provided tips and facts about depression to participants and measured their responses using EmotionDiary. To identify the Facebook features related to depression, correlation analyses were performed between CES-D and participants' responses to tips and facts or Facebook social features. Last, we interviewed depressed participants (CES-D≥25) to assess their depressive symptoms by a psychiatrist.


RESULTS
Facebook activities had predictive power in distinguishing depressed and nondepressed individuals. Participants' response to tips and facts, which can be explained by the number of app tips viewed and app points, had a positive correlation (P=.04 for both cases), whereas the number of friends and location tags had a negative correlation with the CES-D scale (P=.08 and P=.045 respectively). Furthermore, in finding group differences in Facebook social activities, app tips viewed and app points resulted in significant differences (P=.01 and P=.03 respectively) between probably depressed and nondepressed individuals.


CONCLUSIONS
Our results using EmotionDiary demonstrated that the more depressed one is, the more one will read tips and facts about depression. We also confirmed depressed individuals had significantly fewer interactions with others (eg, decreased number of friends and location tagging). Our app, EmotionDiary, can successfully evaluate depressive symptoms as well as provide useful tips and facts to users. These results open the door for examining Facebook activities to identify depressed individuals. We aim to conduct the experiment in multiple cultures as well.
Terminological ontology learning and population using latent Dirichlet allocation

The success of Semantic Web will heavily rely on the availability of formal ontologies to structure machine understanding data. However, there is still a lack of general methodologies for ontology automatic learning and population, i.e. the generation of domain ontologies from various kinds of resources by applying natural language processing and machine learning techniques In this paper, the authors present an ontology learning and population system that combines both statistical and semantic methodologies. Several experiments have been carried out, demonstrating the effectiveness of the proposed system. Keywords-Ontologies, Ontology Learning, Ontology Population, Latent Dirichlet Allocation
Me , myself , and lie : The role of self-awareness in deception

Deception has been studied extensively but still little is known about individual differences in deception ability. We investigated the relationship between self-awareness and deception ability. We enlisted novice actors to portray varying levels of deception. Forty-two undergraduates viewed the videotaped portrayals and rated the actors believability. Actors with high private self-awareness were more effective deceivers, suggesting that high self-monitors are more effective at deceiving. Self-awareness may lead to knowledge of another s mental state (i.e., Theory of Mind), which may improve an individual s deception ability. 2005 Elsevier Ltd. All rights reserved.
Experimental study of desalination using direct contact membrane distillation : a new approach to flux enhancement

New membrane distillation configurations and a new membrane module were investigated to improve water desalination. The performances of three hydrophobic microporous membranes were evaluated under vacuum enhanced direct contact membrane distillation (DCMD) with a turbulent flow regime and with a feed water temperature of only 40 ◦C. The new configurations provide reduced temperature polarization effects due to better mixing and increased mass transport of water due to higher permeability through the membrane and due to a total pressure gradient across the membrane. Comparison with previously reported results in the literature reveals that mass transport of water vapors is substantially improved with the new approach. The performance of the new configuration was investigated with both NaCl and synthetic sea salt feed solutions. Salt rejection was greater than 99.9% in almost all cases. Salt concentrations in the feed stream had only a minor effect on water flux. The economic aspects of the enhanced DCMD process are briefly discussed and comparisons are made with the reverse osmosis (RO) process for desalination. © 2003 Elsevier B.V. All rights reserved.
Pixelwise View Selection for Unstructured Multi-View Stereo

This work presents a Multi-View Stereo system for robust and efficient dense modeling from unstructured image collections. Our core contributions are the joint estimation of depth and normal information, pixelwise view selection using photometric and geometric priors, and a multi-view geometric consistency term for the simultaneous refinement and image-based depth and normal fusion. Experiments on benchmarks and large-scale Internet photo collections demonstrate stateof-the-art performance in terms of accuracy, completeness, and efficiency. Fig. 1. Reconstructions for Louvre, Todai-ji, Paris Opera, and Astronomical Clock.
Thumbs up? Sentiment Classification using Machine Learning Techniques

We consider the problem of classifying documents not by topic, but by overall sentiment, e.g., determining whether a review is positive or negative. Using movie reviews as data, we find that standard machine learning techniques definitively outperform human-produced baselines. However, the three machine learning methods we employed (Naive Bayes, maximum entropy classification, and support vector machines) do not perform as well on sentiment classification as on traditional topic-based categorization. We conclude by examining factors that make the sentiment classification problem more challenging. Publication info: Proceedings of EMNLP 2002, pp. 79–86.
Parents with doubts about vaccines: which vaccines and reasons why.

OBJECTIVES
The goals were (1) to obtain national estimates of the proportions of parents with indicators of vaccine doubt, (2) to identify factors associated with those parents, compared with parents reporting no vaccine doubt indicators, (3) to identify the specific vaccines that prompted doubt and the reasons why, and (4) to describe the main reasons parents changed their minds about delaying or refusing a vaccine for their child.


METHODS
Data were from the National Immunization Survey (2003-2004). Groups included parents who ever got a vaccination for their child although they were not sure it was the best thing to do ("unsure"), delayed a vaccination for their child ("delayed"), or decided not to have their child get a vaccination ("refused").


RESULTS
A total of 3924 interviews were completed. Response rates were 57.9% in 2003 and 65.0% in 2004. Twenty-eight percent of parents responded yes to ever experiencing >or=1 of the outcome measures listed above. In separate analyses for each outcome measure, vaccine safety concern was a predictor for unsure, refused, and delayed parents. The largest proportions of unsure and refused parents chose varicella vaccine as the vaccine prompting their concern, whereas delayed parents most often reported "not a specific vaccine" as the vaccine prompting their concern. Most parents who delayed vaccines for their child did so for reasons related to their child's illness, unlike the unsure and refused parents. The largest proportion of parents who changed their minds about delaying or not getting a vaccination for their child listed "information or assurances from health care provider" as the main reason.


CONCLUSIONS
Parents who exhibit doubts about immunizations are not all the same. This research suggests encouraging children's health care providers to solicit questions about vaccines, to establish a trusting relationship, and to provide appropriate educational materials to parents.
Feature Extraction and Classification for Automatic Speaker Recognition System – A Review

Automatic speaker recognition (ASR) has found immense applications in the industries like banking, security, forensics etc. for its advantages such as easy implementation, more secure, more user friendly. To have a good recognition rate is a pre-requisite for any ASR system which can be achieved by making an optimal choice among the available techniques for ASR. In this paper, different techniques for the system have been discussed such as MFCC, LPCC, LPC, Wavelet decomposition for feature extraction and VQ, GMM, SVM, DTW, HMM for feature classification. All these techniques are also compared with each other to find out best suitable candidate among them. On the basis of the comparison done, MFCC has upper edge over other techniques for feature extraction as it is more consistent with human hearing. GMM comes out to be the best among classification models due to its good classification accuracy and less memory usage. Keywords— Automatic Speaker Recognition, Mel Frequency Cepstral Coefficients (MFCC), Linear Predictive Cepstral Coefficients, Gaussian Mixture Model ( GMM), Vector Quantization ( VQ), Dynamic Time Warping (DTW), Hidden Markov Model ( HMM), Wavelet decomposition
Using association rules to guide a search for best fitting transfer models of student learning

We say a transfer model is a mapping between the questions in an intelligent tutoring system and the knowledge components (i.e., skills, strategies, declarative knowledge, etc) needed to answer a question correctly. [JKT00] showed how you could take advantage of 1) the Power Law Of Learning, 2) an existing transfer model, and 3) set of tutorial log files, to learn a function (using logistic regression) that will predict when a student will get a question correct. In the main conference proceeding [CHK2004] give an example of using this technique for transfer model selection. Koedinger and Junker [KJ99] also conceptualized a search space where each state is a new transfer model. The operators in this search space split, add or merge knowledge components based upon factors that are tagged to questions. Koedinger and Junker called this method learning factors analysis emphasizing that this method can be used to study learning. Unfortunately, the search space is huge and searching for good fitting transfer models is exponential. The main goal of this paper is show a technique that will make searching for transfer models more efficient. Our procedure implements a search method using association rules as a means of guiding the search. The association rules are mined from a dataset derived from student-tutor interaction logs. The association rules found in the mining process determine what operations to perform on the current transfer model. We report on the speed up achieved. Being able to find good transfer models quicker will help intelligent tutor system builders as well as cognitive science researchers better assess what makes certain problems hard and other problems easy for students.
Technology adoption: A conjoint analysis of consumers' preference on future online banking services

The importance of service delivery technology and online service adoption and usage in the banking industry has received an increased discussion in the literature in recent years. Owing to the fact that Strong online banking services are important drivers for bank performance and customer service delivery; several studies have been carried out on online banking service adoption or acceptance where services are already deployed and on the factors that influence customers' adoption and use or intention to use those services. However, despite the increasing discussion in the literatures, no attempt has been made to look at consumers' preference in terms of future online banking service adoption. This study used conjoint analysis and stated preference methods with discrete choice model to analyze the technology adoption pattern regarding consumers' preference for potential future online banking services in the Nigerian banking industry. The result revealed that to increase efficiency and strengthen competitiveness, banks need to promote smart and practical branded services especially self-services at the same time promote a universal adoption of e-banking system services that add entertainment or extra convenience to customers such as ease of usage including digital wallet, real-time interaction (video banking), ATMs integrated with smart phones, website customization, biometric services, and digital currency. These services can contribute to an increasing adoption of online services. & 2015 Elsevier Ltd. All rights reserved.
Discoverer: Automatic Protocol Reverse Engineering from Network Traces

Application-level protocol specifications are useful for many security applications, including intrusion prevention and detection that performs deep packet inspection and traffic normalization, and penetration testing that generates network inputs to an application to uncover potential vulnerabilities. However, current practice in deriving protocol specifications is mostly manual. In this paper, we present Discoverer, a tool for automatically reverse engineering the protocol message formats of an application from its network trace. A key property of Discoverer is that it operates in a protocol-independent fashion by inferring protocol idioms commonly seen in message formats of many application-level protocols. We evaluated the efficacy of Discoverer over one text protocol (HTTP) and two binary protocols (RPC and CIFS/SMB) by comparing our inferred formats with true formats obtained from Ethereal [5]. For all three protocols, more than 90% of our inferred formats correspond to exactly one true format; one true format is reflected in five inferred formats on average; our inferred formats cover over 95% of messages, which belong to 30-40% of true formats observed in the trace.