snu-aidas/HVMap-dataset huggingface dataset:
A Clinical Study of 35 Cases of Pincer Nails

BACKGROUND
Pincer nail is a nail deformity characterized by transverse overcurvature of the nail plate. Pincer nail can affect a patient's quality of life due to its chronic, recurrent course; however, there have been no clinical studies on the pincer nail condition in Korean patients.


OBJECTIVE
The purpose of this study was to characterize the clinical findings and treatment of pincer nail. In addition, possible etiological factors were considered, and treatment efficacy was evaluated.


METHODS
The medical records and clinical photographs of 35 patients (12 males, 23 females) who were diagnosed with pincer nail between August 1, 2005 and July 31, 2009 were studied.


RESULTS
Patient age ranged from 10 to 77 (52.09±17.26) years, and there was a predominance of female (23 out of 35 patients, F:M=2:1). The mean duration of the disorder was 7.45 years (range 0.25~40); 85% had pincer nail for at least 1 year. In addition, 40% had a history of previous treatment and recurrence. There were 82.8% patients with the common type of pincer nails. The most commonly involved nails were both great toenails. Among 35 patients, nail grinding was started in 30 patients, and 25 patients showed clinical improvement with nail grinding. The width index increased and the height index decreased after treatment. The mean follow up period was 8.42 months (range 1~27), and 7 patients showed recurrence after 8.8 months (range 2~20). Among 35 patients, 5 patients were treated with nail extraction with matricectomy, and the symptoms resolved immediately. The mean follow up period was 7.6 months (range 0~19), and recurrence was not observed. Onychomycosis was also present in 37.1% of patients, and itraconazole pulse therapy for 3 months was added.


CONCLUSION
The results of this study demonstrate the clinical features of pincer nail in Korean patients. The findings show that the common type of pincer nail was most common, and nail grinding as a conservative treatment greatly improved pincer nails despite a risk of recurrence. When onychomycosis was also present, oral antifungal therapy added to nail grinding resulted in a more rapid change in nail thickness and clinical improvement.
Health information systems: a survey of frameworks for developing countries.

OBJECTIVES
The objective of this paper is to perform a survey of excellent research on health information systems (HIS) analysis and design, and their underlying theoretical frameworks. It classifies these frameworks along major themes, and analyzes the different approaches to HIS development that are practical in resource-constrained environments.


METHOD
Literature review based on PubMed citations and conference proceedings, as well as Internet searches on information systems in general, and health information systems in particular.


RESULTS
The field of health information systems development has been studied extensively. Despite this, failed implementations are still common. Theoretical frameworks for HIS development are available that can guide implementers.


CONCLUSION
As awareness, acceptance, and demand for health information systems increase globally, the variety of approaches and strategies will also follow. For developing countries with scarce resources, a trial-and-error approach can be very costly. Lessons from the successes and failures of initial HIS implementations have been abstracted into theoretical frameworks. These frameworks organize complex HIS concepts into methodologies that standardize techniques in implementation. As globalization continues to impact healthcare in the developing world, demand for more responsive health systems will become urgent. More comprehensive frameworks and practical tools to guide HIS implementers will be imperative.
Segmentation using Eigenvectors: A Unifying View

Automatic grouping and segmentation of images remains a challenging problem in computer vision. Recently, a number of authors have demonstrated good performance on this task using methods that are based on eigenvectors of the a nity matrix. These approaches are extremely attractive in that they are based on simple eigendecomposition algorithms whose stability is well understood. Nevertheless, the use of eigendecompositions in the context of segmentation is far from well understood. In this paper we give a unied treatment of these algorithms, and show the close connections between them while highlighting their distinguishing features. We then prove results on eigenvectors of block matrices that allow us to analyze the performance of these algorithms in simple grouping settings. Finally, we use our analysis to motivate a variation on the existing methods that combines aspects from di erent eigenvector segmentation algorithms. We illustrate our analysis with results on real and synthetic images. Human perceiving a scene can often easily segment it into coherent segments or groups. There has been a tremendous amount of e ort devoted to achieving the same level of performance in computer vision. In many cases, this is done by associating with each pixel a feature vector (e.g. color, motion, texture, position) and using a clustering or grouping algorithm on these feature vectors. Perhaps the cleanest approach to segmenting points in feature space is based on mixture models in which one assumes the data were generated by multiple processes and estimates the parameters of the processes and the number of components in the mixture. The assignment of points to clusters can then be easily performed by calculating the posterior probability of a point belonging to a cluster. Despite the elegance of this approach, the estimation process leads to a notoriously di cult optimization. The frequently used EM algorithm [3] often converges to a local maximum that depends on the initial conditions.
Variation in the impact of social network characteristics on physical functioning in elderly persons: MacArthur Studies of Successful Aging.

OBJECTIVES
Social support and social networks have been shown to exert significant effects on health and functioning among elderly persons. Although theorists have speculated that the strength of these effects may differ as a function of sociodemographic characteristics and prior health status, few studies have directly tested the moderating effects of these variables.


METHODS
Longitudinal data from the MacArthur Study of Successful Aging were used to examine the effects of structural and functional social support on changes in physical functioning over a 7-year period, measured by the Nagi scale, in a sample of initially high-functioning men and women aged 70 to 79 years. Multiple regression analyses were used to test the main effects of social support and social network variables, as well as their interactions with gender, income, and baseline physical performance.


RESULTS
After controlling for potential confounding effects, respondents with more social ties showed less functional decline. The beneficial effects of social ties were stronger for respondents who were male or had lower levels of baseline physical performance.


DISCUSSION
The effects of social support and social networks may vary according to the individual's gender and baseline physical capabilities. Studies of functional decline among elderly persons should not ignore this population variation in the effects of social networks.
Mood and Emotions in Small Groups and Work Teams

Affective influences abound in groups. In this article we propose an organizing model for understanding these affective influences and their effects on group life. We begin with individuallevel affective characteristics that members bring to their groups: moods, emotions, sentiments, and emotional intelligence. These affective characteristics then combine to form a group’s affective composition. We discuss explicit and implicit processes through which this affective combination occurs by examining the research on emotional contagion, entrainment, modeling, and the manipulation of affect. We also explore how elements of the affective context, such as organizationwide emotion norms and the group’s particular emotional history, may serve to constrain or amplify group members’ emotions. The outcome, group emotion, results from the combination of the group’s affective composition and the affective context in which the group is behaving. Last, we focus on the important interaction between nonaffective factors and affective factors in group life and suggest a possible agenda for future research. q 2001 Academic Press
Sensory integration dysfunction affects efficacy of speech therapy on children with functional articulation disorders

BACKGROUND
Articulation disorders in young children are due to defects occurring at a certain stage in sensory and motor development. Some children with functional articulation disorders may also have sensory integration dysfunction (SID). We hypothesized that speech therapy would be less efficacious in children with SID than in those without SID. Hence, the purpose of this study was to compare the efficacy of speech therapy in two groups of children with functional articulation disorders: those without and those with SID.


METHOD
A total of 30 young children with functional articulation disorders were divided into two groups, the no-SID group (15 children) and the SID group (15 children). The number of pronunciation mistakes was evaluated before and after speech therapy.


RESULTS
There were no statistically significant differences in age, sex, sibling order, education of parents, and pretest number of mistakes in pronunciation between the two groups (P > 0.05). The mean and standard deviation in the pre- and post-test number of mistakes in pronunciation were 10.5 ± 3.2 and 3.3 ± 3.3 in the no-SID group, and 10.1 ± 2.9 and 6.9 ± 3.5 in the SID group, respectively. Results showed great changes after speech therapy treatment (F = 70.393; P < 0.001) and interaction between the pre/post speech therapy treatment and groups (F = 11.119; P = 0.002).


CONCLUSIONS
Speech therapy can improve the articulation performance of children who have functional articulation disorders whether or not they have SID, but it results in significantly greater improvement in children without SID. SID may affect the treatment efficiency of speech therapy in young children with articulation disorders.
A fast and efficient python library for interfacing with the Biological Magnetic Resonance Data Bank

The Biological Magnetic Resonance Data Bank (BMRB) is a public repository of Nuclear Magnetic Resonance (NMR) spectroscopic data of biological macromolecules. It is an important resource for many researchers using NMR to study structural, biophysical, and biochemical properties of biological macromolecules. It is primarily maintained and accessed in a flat file ASCII format known as NMR-STAR. While the format is human readable, the size of most BMRB entries makes computer readability and explicit representation a practical requirement for almost any rigorous systematic analysis. To aid in the use of this public resource, we have developed a package called nmrstarlib in the popular open-source programming language Python. The nmrstarlib’s implementation is very efficient, both in design and execution. The library has facilities for reading and writing both NMR-STAR version 2.1 and 3.1 formatted files, parsing them into usable Python dictionary- and list-based data structures, making access and manipulation of the experimental data very natural within Python programs (i.e. “saveframe” and “loop” records represented as individual Python dictionary data structures). Another major advantage of this design is that data stored in original NMR-STAR can be easily converted into its equivalent JavaScript Object Notation (JSON) format, a lightweight data interchange format, facilitating data access and manipulation using Python and any other programming language that implements a JSON parser/generator (i.e., all popular programming languages). We have also developed tools to visualize assigned chemical shift values and to convert between NMR-STAR and JSONized NMR-STAR formatted files. Full API Reference Documentation, User Guide and Tutorial with code examples are also available. We have tested this new library on all current BMRB entries: 100% of all entries are parsed without any errors for both NMR-STAR version 2.1 and version 3.1 formatted files. We also compared our software to three currently available Python libraries for parsing NMR-STAR formatted files: PyStarLib, NMRPyStar, and PyNMRSTAR. The nmrstarlib package is a simple, fast, and efficient library for accessing data from the BMRB. The library provides an intuitive dictionary-based interface with which Python programs can read, edit, and write NMR-STAR formatted files and their equivalent JSONized NMR-STAR files. The nmrstarlib package can be used as a library for accessing and manipulating data stored in NMR-STAR files and as a command-line tool to convert from NMR-STAR file format into its equivalent JSON file format and vice versa, and to visualize chemical shift values. Furthermore, the nmrstarlib implementation provides a guide for effectively JSONizing other older scientific formats, improving the FAIRness of data in these formats.
Autonomous Driving in Urban Environments: Boss and the Urban Challenge

Chris Urmson, Joshua Anhalt, Drew Bagnell, Christopher Baker, Robert Bittner, M. N. Clark, John Dolan, Dave Duggins, Tugrul Galatali, Chris Geyer, Michele Gittleman, Sam Harbaugh, Martial Hebert, Thomas M. Howard, Sascha Kolski, Alonzo Kelly, Maxim Likhachev, Matt McNaughton, Nick Miller, Kevin Peterson, Brian Pilnick, Raj Rajkumar, Paul Rybski, Bryan Salesky, Young-Woo Seo, Sanjiv Singh, Jarrod Snider, Anthony Stentz, William “Red” Whittaker, Ziv Wolkowicki, and Jason Ziglar Carnegie Mellon University Pittsburgh, Pennsylvania 15213 e-mail: curmson@ri.cmu.edu
Commonsense Reasoning in and Over Natural Language

ConceptNet is a very large semantic network of commonsense knowledge suitable for making various kinds of practical inferences over text. ConceptNet captures a wide range of commonsense concepts and relations like those in Cyc, while its simple semantic network structure lends it an ease-of-use comparable to WordNet. To meet the dual challenge of having to encode complex higher-order concepts, and maintaining ease-of-use, we introduce a novel use of semi-structured natural language fragments as the knowledge representation of commonsense concepts. In this paper, we present a methodology for reasoning flexibly about these semi-structured natural language fragments. We also examine the tradeoffs associated with representing commonsense knowledge in formal logic versus in natural language. We conclude that the flexibility of natural language makes it a highly suitable representation for achieving practical inferences over text, such as context finding, inference chaining, and conceptual analogy. 1 What is ConceptNet? ConceptNet (www.conceptnet.org) is the largest freely available, machine-useable commonsense resource. Structured as a network of semi-structured natural language fragments, ConceptNet presently consists of over 250,000 elements of commonsense knowledge. We were inspired dually by the range of commonsense concepts and relations in Cyc (Lenat, 1995), and by the ease-of-use of WordNet (Fellbaum, 1998), and hoped to combine the best of both worlds. As a result, we adopted the semantic network representation of WordNet, but extended the representation in several key ways. First, we extended WordNet’s lexical notion of nodes to a conceptual notion of nodes, but we kept the nodes in natural language, because one of the primary strengths of WordNet in the textual domain is that its knowledge representation is itself textual. ConceptNet’s nodes are thus natural language fragments which are semi-structured according to an ontology of allowable syntactic patterns, and accommodate both first-order concepts given as noun phrases (e.g. “potato chips”), and second-order concepts given as verb phrases (e.g. “buy potato chips”). Second, we extended WordNet’s small ontology of semantic relations, which are primarily taxonomic in nature, to include a richer set of relations appropriate to concept-level nodes. At present there are 19 semantic relations used in ConceptNet, representing categories of, inter alia, temporal, spatial, causal, and functional knowledge. By combining higher order nodes with this relational ontology, it is possible to represent richer kinds of knowledge in ConceptNet beyond what can be represented in WordNet (Fig 1.). For example, we can represent a layman’s common sense observation that “you may be hurt if you get into an accident” in ConceptNet as EffectOf(“get into accident”, “be hurt”). Note that because the knowledge representation is semi-structured natural language, there are often various ways to represent the same knowledge. This is a source of ambiguity, but as we will argue in this paper, maintaining some ambiguity lends us greater flexibility for reasoning.
Improved image-based classification of Alzheimer ’ s disease using multimodality brain imaging data

Purpose Amyloid-PET is an accurate marker of Alzheimer's disease. However, this technique is invasive and not widely available. Here we investigated whether other neuroimaging techniques can yield similar diagnostic accuracy as PET imaging. This proof of concept study presents two approaches of analyzing multi-modality combinations of metabolic, functional and anatomical brain imaging data using kernel-based pattern recognition techniques. Methods Input images were taken from a systematically collected database of previous studies. Data included [ 18 F]FDG-PET, rs-fMRI and structural MR data of 15 controls and 25 AD patients. [ 11 C]PIB was used as reference test for classification of AD using imaging data. From rs-fMRI data, both eigenvector centrality (EC) images and default mode network (DMN) regression maps were calculated. Structural MR data was used to create gray matter (GM) maps. Intermediate results were combined and analyzed with two types of existing pattern classification software; 1) using spatial concatenation of voxel data and, 2) a regional multi-kernel approach.
Exploring motivations for contributing to open source initiatives: The roles of contribution context and personal values

We explore contextual and dispositional correlates of the motivation to contribute to open source initiatives. We examine how the context of the open source project, and the personal values of contributors, are related to the types of motivations for contributing. A web-based survey was administered to 300 contributors in two prominent open source contexts: software and content. As hypothesized, software contributors placed a greater emphasis on reputation-gaining and self-development motivations, compared with content contributors, who placed a greater emphasis on altruistic motives. Furthermore, the hypothesized relationships were found between contributors’ personal values and their motivations for contributing. 2007 Elsevier Ltd. All rights reserved.
On the cognitive process of human problem solving

One of the fundamental human cognitive processes is problem solving. As a higher-layer cognitive process, problem solving interacts with many other cognitive processes such as abstraction, searching, learning, decision making, inference, analysis, and synthesis on the basis of internal knowledge representation by the object–attribute-relation (OAR) model. Problem solving is a cognitive process of the brain that searches a solution for a given problem or finds a path to reach a given goal. When a problem object is identified, problem solving can be perceived as a search process in the memory space for finding a relationship between a set of solution goals and a set of alternative paths. This paper presents both a cognitive model and a mathematical model of the problem solving process. The cognitive structures of the brain and the mechanisms of internal knowledge representation behind the cognitive process of problem solving are explained. The cognitive process is formally described using real-time process algebra (RTPA) and concept algebra. This work is a part of the cognitive computing project that designed to reveal and simulate the fundamental mechanisms and processes of the brain according to Wang’s layered reference model of the brain (LRMB), which is expected to lead to the development of future generation methodologies for cognitive computing and novel cognitive computers that are capable of think, learn, and perceive. 2008 Published by Elsevier B.V.
The effect of experimental presentation of thin media images on body satisfaction: a meta-analytic review.

OBJECTIVE
The effect of experimental manipulations of the thin beauty ideal, as portrayed in the mass media, on female body image was evaluated using meta-analysis.


METHOD
Data from 25 studies (43 effect sizes) were used to examine the main effect of mass media images of the slender ideal, as well as the moderating effects of pre-existing body image problems, the age of the participants, the number of stimulus presentations, and the type of research design.


RESULTS
Body image was significantly more negative after viewing thin media images than after viewing images of either average size models, plus size models, or inanimate objects. This effect was stronger for between-subjects designs, participants less than 19 years of age, and for participants who are vulnerable to activation of a thinness schema.


CONCLUSION
Results support the sociocultural perspective that mass media promulgate a slender ideal that elicits body dissatisfaction. Implications for prevention and research on social comparison processes are considered.
Current review of prepubertal vaginal bleeding.

PURPOSE OF REVIEW
Prepubertal vaginal bleeding raises many concerns and evaluation and diagnosis may prove difficult for many providers. We aim to provide a comprehensive review and recent updates for those practitioners who care for these patients.


RECENT FINDINGS
Prompt management in the case of prepubertal vaginal bleeding is indicated, especially to rule out malignancy or abuse. If a child is reluctant to undergo examination, or if the extent of injury or source of bleeding cannot be determined, examination under anesthesia and vaginoscopy is recommended. Use of vaginoscopy allows for clear visualization of the vagina and cervix without distorting hymenal anatomy, as well as diagnosis and removal of a foreign body and evaluation of mucosal damage caused. In the case of sexual abuse, providers specifically trained in pediatrics need to be present, and safety of the patient should always be ensured.


SUMMARY
Careful history taking and targeted examination may lead to diagnosis in the case of prepubertal vaginal bleeding. However, in more difficult cases, practitioners should not hesitate to examine a patient in the operating room using general anesthesia to elicit the cause. Although sexual abuse and malignancy are always on the differential, most causes of bleeding are benign and easily treated.
Doing good or doing well ? Image motivation and monetary incentives in behaving prosocially

Doing Good or Doing Well? Image Motivation and Monetary Incentives in Behaving Prosocially This paper experimentally examines image motivation – the desire to be liked and wellregarded by others – as a driver in prosocial behavior (doing good), and asks whether extrinsic monetary incentives (doing well) have a detrimental effect on prosocial behavior due to crowding out of image motivation. By definition, image depends on one’s behavior being visible to other people. Using this unique property we show that image is indeed an important part of the motivation to behave prosocially. Moreover, we show that extrinsic incentives interact with image motivation and are therefore less effective in public than in private. Together, these results imply that image motivation is crowded out by monetary incentives; which in turn means that monetary incentives are more likely to be counterproductive for public prosocial activities than for private ones. JEL Classification: D64, C90, H41