N-doped porous carbon produced via chemical activation of polypyrrole functionalized graphene sheets shows selective adsorption of CO(2) (4.3 mmol g(-1)) over N(2) (0.27 mmol g(-1)) at 298 K. The potential for large scale production and facile regeneration makes this material useful for industrial applications.

PurposeTo investigate the influences of smartphone use on ocular symptoms, status of the tear film, and oxidative stress indices in the tears and at the ocular surface.MethodsEighty healthy volunteers were enrolled in the study. Subjective symptoms and asthenopia were evaluated using the ocular surface disease index (OSDI), visual analogue scale (VAS), and computer vision syndrome (CVS) score before and after smartphone or computer display (control) use. The status of the tear film was evaluated using fluorescein film break-up time (FBUT), non-invasive keratograph break up time (NIKBUT), Schirmer score, keratoepitheliopathy (KEP), and tear meniscus height (TMH). Oxidative stress markers in the tear film including hexanoyl lysine (HEL), 4-hydroxy-2-nonenal (4-HNE), malondialdehyde (MDA), and 8-oxo-2’-deoxyguanosine (8-OHdG) in the tear film were measured using ELISA. Reactive oxygen species (ROS) at the ocular surface were measured through 2’,7’-dichloro-dihydrofluorescein diacetate. All measurements were conducted at baseline, and after use for 1 and 4 h.ResultsAll parameters showed no significant group-wise differences at baseline. Scores of OSDI, VAS, fatigue, burning sensation, and dryness showed significant increases after 1 and 4 h of smartphone use compared with those at baseline (all P < 0.05). The smartphone group showed higher OSDI, fatigue, burning, and dryness scores than the control group at 4 h. Smartphone use showed significantly decreased FBUT and NIBUT at 4 h than those at baseline (P < 0.01). In the smartphone group, the concentration of HEL significantly increased at 4 h compared with that at baseline and 1 h (P < 0.01). Both groups showed increased ROS with higher value in the smartphone group versus the control group at 4 h (P < 0.01).ConclusionsSmartphone use could not only aggravate subjective symptom indices such as the OSDI, VAS, and CVS but also induce tear film instability and oxidative stress indices in the tears and at the ocular surface.

Motivation: Automatic knowledge discovery and efficient information access such as named entity recognition and relation extraction between entities have recently become critical issues in the biomedical literature. However, the inherent difficulty of the relation extraction task, mainly caused by the diversity of natural language, is further compounded in the biomedical domain because biomedical sentences are commonly long and complex. In addition, relation extraction often involves modeling long range dependencies, discontiguous word patterns and semantic relations for which the pattern-based methodology is not directly applicable. Results: In this article, we shift the focus of biomedical relation extraction from the problem of pattern extraction to the problem of kernel construction. We suggest four kernels: predicate, walk, dependency and hybrid kernels to adequately encapsulate information required for a relation prediction based on the sentential structures involved in two entities. For this purpose, we view the dependency structure of a sentence as a graph, which allows the system to deal with an essential one from the complex syntactic structure by finding the shortest path between entities. The kernels we suggest are augmented gradually from the flat features descriptions to the structural descriptions of the shortest paths. As a result, we obtain a very promising result, a 77.5 F-score with the walk kernel on the Language Learning in Logic (LLL) 05 genic interaction shared task. Availability: The used algorithms are free for use for academic research and are available from our Web site http://mllab.sogang. ac.kr/$shkim/LLL05.tar.gz.

Named entity (NE) recognition has become one of the most fundamental tasks in biomedical knowledge acquisition. In this paper, we present a two-phase named entity recognizer based on SVMs, which consists of a boundary identification phase and a semantic classification phase of named entities. When adapting SVMs to named entity recognition, the multi-class problem and the unbalanced class distribution problem become very serious in terms of training cost and performance. We try to solve these problems by separating the NE recognition task into two subtasks, where we use appropriate SVM classifiers and relevant features for each subtask. In addition, by employing a hierarchical classification method based on ontology, we effectively solve the multi-class problem concerning semantic classification. The experimental results on the GENIA corpus show that the proposed method is effective not only in reducing computational cost but also in improving performance. The F-score (beta=1) for the boundary identification is 74.8 and the F-score for the semantic classification is 66.7.

In both adults and children, metabolic syndrome (MetS) has been attributed to risk factors for type 2 diabetes and cardiovascular disease such as insulin resistance, abdominal obesity, hypertension, and dyslipidemia. This descriptive study aimed to compare the prevalence of MetS and diagnostic components according to the National Cholesterol Education Program, Adult Treatment Panel III (NCEP-ATP III) and International Diabetes Federation (IDF) in 2330 Korean adolescents (10–18 years), using data from the 2010–2012 Korea National Health and Nutrition Examination Survey-V. The NCEP-ATP III and IDF were used to diagnose MetS and yielded prevalence rates of 5.7% and 2.1%, respectively, with no sex-related differences. The most frequent MetS diagnostic components according to the NCEP-ATP III and IDF criteria were high triglyceride levels (21.2%) and low high-density lipoprotein cholesterol levels (13.6%), respectively; approximately 50.1% and 33.1% of adolescents had at least one MetS diagnostic component according to the respective criteria. Both overweight/obese male and female adolescents exhibited significantly increased prevalence rates of MetS and related diagnostic components, compared to normal-weight adolescents. In conclusion, the prevalence rates of MetS and diagnostic components differ according to the NCEP-ATP III and IDF criteria. Henceforth, efforts are needed to establish diagnostic criteria for Korean adolescents.