LLukas22/scidocs huggingface dataset:
How good is the Electricity benchmark for evaluating concept drift adaptation

In this correspondence, we will point out a problem with testing adaptive classifiers on autocorrelated data. In such a case random change alarms may boost the accuracy figures. Hence, we cannot be sure if the adaptation is working well.
Association between glycaemic control and serum lipid profile in type 2 diabetic patients: Glycated haemoglobin as a dual biomarker

Patients with type 2 diabetes have an increased prevalence of lipid abnormalities, contributing to their high risk of cardiovascular diseases (CVD). This study is an attempt to evaluate the diagnostic value of Glycated haemoglobin (HbA1c) in predicting diabetic dyslipidemia. Venous blood samples were collected from 294 type 2 diabetic patients. The whole blood and sera were analyzed for HbA1c, fasting blood glucose (FBG) and lipid profile panel test. Dyslipidemia was defined as per the National Cholesterol Education Programme (NCEP) Adult Treatment Panel (ATP) III guidelines. Diabetes was defined as per American diabetes association criteria. The statistical analysis was done by SPSS statistical package version 13.0.In our present study 92 (80.70%) females out of 114 and 150 (83.33 %) males out of 180 were found to be dyslipidemic. HbA1c demonstrated positive and significant correlations with total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), high density lipoprotein cholesterol (HDL-C) and LDL-C ratio, non-HDL-C and TC/HDL-C ratio. Patients with HbA1c value > 7.0% had significantly higher value of TC, Triacylglycerol (TAG), LDL-C, LDL-C/HDL-C ratio, non-HDL-C and TC/HDL-C ratio as compared to the patients with HbA1c ≤ 7.0%. However, there was no significant difference in value of HDL-C between two groups. HbA1c can be used as a potential biomarker for predicting dyslipidemia in type 2 diabetic patients in addition to glycemic control.
Overgrowth of gold nanorods by using a binary surfactant mixture.

Seed-mediated surfactant-assisted growth is widely used as the most effective method for gold nanorod (NR) synthesis. Using prepared nanorods as seeds for further overgrowth can increase the dimensional tunability of the final particles. However, overgrowth in usual cetyltrimethylammonium bromide (CTAB) surfactant solutions leads to poor control of the final particle shape and size. In this work, we report an improved strategy to demonstrate the controllable overgrowth of gold NRs in the binary surfactant mixture sodium oleate (NaOL) + CTAB. This approach overcomes the difficulty of growing NR suspensions with small amounts of impurities. By controlling the total amount of added NR seeds, it is possible to tune the average length, diameter, and plasmon resonances of overgrown particles in a wide range. Together with the original NaOL + CTAB method developed by Murray and co-workers ( Nano Lett. 2013 , 13 , 555 ), this overgrowth approach expands the dimensional and plasmonic tunability of the fabrication technology without any decrease in the monodispersity and purity of samples.
Factors Affecting Adoption of Improved Rice Varieties among Rural Farm Households in Central Nepal

The use of improved high yielding crop varieties is an important avenue for reducing hunger and food insecurity in developing countries. Using cross-sectional data obtained from a survey conducted during 2013 crop season, we performed a probit model (plot-level analysis) to determine the probability of adopting new improved rice varieties (NIRVs) by smallholder farmers particularly from two main agro-ecological regions (hills and tropical plain terai regions) of Central Nepal. The results revealed that education, extension services and seed access play significant roles in adoption decisions. Additionally, farm and field characteristic variables such as farm size, endowment of favorable land type (e.g. lowlands), and animal power (e.g. oxen) are the key factors influencing the probability of adopting NIRVs. The results showed that technology specific variables (e.g. yield potential and acceptability) are significant for explaining adoption behavior, implying that it is important to take farmers’ preferences to varietal characteristics into consideration in the design of a research and development program. Given the significant role played by extension and access related variables, increased emphasis on information dissemination, field demonstration, and farmers’ participatory research and training programs to popularize new rice varieties and enhance their adoption rate are required. This also suggests that policy intervention should be made on improving the educational status of farming households, and developing programs on varietal package of rice seed which offer farmers a variety of choices among the appropriate pools of germplasm. Such programs ultimately help farmers develop more profit-oriented behavior which are necessary to enhance adoption rate, production and food security in the long run.
Periodontal inflammation and bone loss in aged mice.

BACKGROUND AND OBJECTIVE
Young mice do not develop measurable periodontal bone loss, unless heavily infected with human periodontal pathogens. However, mice with a genetically altered immune system are unable to control their own oral flora and develop periodontitis early in life. Based on the potential of the indigenous oral microbiota to cause periodontitis, we hypothesized that normal mice may ultimately develop inflammatory periodontal bone loss, i.e. as a function of age. If confirmed, this could serve as an aging model of chronic periodontitis.


MATERIAL AND METHODS
Periodontal bone levels were measured as the distance from the cementoenamel junction to the alveolar bone crest in young mice (8-10 wk of age), old mice (>or= 18 mo of age) and mice of intermediate ages. Differential expression of inflammatory mediators in the gingivae of young and old mice was determined by quantitative real-time PCR.


RESULTS
In comparison with young mice, old mice displayed significantly (p < 0.05) increased periodontal bone loss, accompanied by elevated expression of proinflammatory cytokines (interleukin-1 beta, tumor necrosis factor alpha and interleukin-17A) and innate immune receptors involved in the induction or amplification of inflammation (Toll-like receptor 2, CD14, CD11b, CD18, complement C5a receptor and triggering receptor expressed on myeloid cells 3).


CONCLUSION
Mice develop naturally induced periodontal bone loss as a function of age. This aging model of periodontitis represents a genuinely chronic model to study mechanisms of periodontal tissue destruction.
Control of a visual keyboard using an electrocorticographic brain-computer interface.

OBJECTIVE
Brain-computer interfaces (BCIs) are devices that enable severely disabled people to communicate and interact with their environments using their brain waves. Most studies investigating BCI in humans have used scalp EEG as the source of electrical signals and focused on motor control of prostheses or computer cursors on a screen. The authors hypothesize that the use of brain signals obtained directly from the cortical surface will more effectively control a communication/spelling task compared to scalp EEG.


METHODS
A total of 6 patients with medically intractable epilepsy were tested for the ability to control a visual keyboard using electrocorticographic (ECOG) signals. ECOG data collected during a P300 visual task paradigm were preprocessed and used to train a linear classifier to subsequently predict the intended target letters.


RESULTS
The classifier was able to predict the intended target character at or near 100% accuracy using fewer than 15 stimulation sequences in 5 of the 6 people tested. ECOG data from electrodes outside the language cortex contributed to the classifier and enabled participants to write words on a visual keyboard.


CONCLUSIONS
This is a novel finding because previous invasive BCI research in humans used signals exclusively from the motor cortex to control a computer cursor or prosthetic device. These results demonstrate that ECOG signals from electrodes both overlying and outside the language cortex can reliably control a visual keyboard to generate language output without voice or limb movements.
Prevalence of cigarette smoking and associated risk factors among adolescents in Hamadan City, west of Iran in 2010.

BACKGROUND
Most people start smoking during teenage years. There is an increasing trend in the prevalence of cigarette smoking among children and adolescents in recent years. The aim of the present study was to investigate the prevalence of cigarette smoking and associated risk factors among high-school students.


METHODS
This cross-sectional study was conducted in January 2010 in Hamadan City, west of Iran. A random sample of 1161 high-school students was enrolled voluntarily. The data collection tool was a self-administered questionnaire including demographic characteristics as well as questions about knowledge and attitude toward cigarette smoking. Stata version 11 (StataCorp, College Station, TX, USA) was employed for data analysis.


RESULTS
The prevalence of cigarette smoking was 10.2% (95% CI: 8.4%, 11.9%; SD = 0.30) with an increasing trend toward older ages. Of the 118 smokers, 70% were boys, 93% were 15-20 years old, 80% had experienced smoking before age of 15 yr, 80.3% used less than five cigarettes per day, and 39% started smoking out of curiosity. Students' mean scores of knowledge and attitude toward smoking were 53% and 74%, respectively. Odds ratio estimate of becoming a smoker was 4.44 for those who lived with people other than their parents, 5.68 for those who had siblings who smoke, 10.74 for those who had friends who smoke, 12.56 for those who were frequently offered cigarettes by their friends.


CONCLUSION
The current study revealed the effect of several social variables on adolescents' smoking status. The results of our study thus provide information on possible areas of intervention, which should be the focus of special attention by policymakers when planning tobacco control preventive programs among adolescents and young adults.
CARS 2016—Computer Assisted Radiology and Surgery Proceedings of the 30th International Congress and Exhibition Heidelberg, Germany, June 21–25, 2016

CARS 2016—Computer Assisted Radiology and Surgery Proceedings of the 30th International Congress and Exhibition Heidelberg, Germany, June 21–25, 2016
A randomized algorithm for the decomposition of matrices ✩

Article history: Received 9 April 2008 Revised 23 August 2009 Accepted 13 February 2010 Available online 19 February 2010 Communicated by Charles K. Chui
Sequential Optimization for Efficient High-Quality Object Proposal Generation

We are motivated by the need for a generic object proposal generation algorithm which achieves good balance between object detection recall, proposal localization quality and computational efficiency. We propose a novel object proposal algorithm, BING++, which inherits the virtue of good computational efficiency of BING [1] but significantly improves its proposal localization quality. At high level we formulate the problem of object proposal generation from a novel probabilistic perspective, based on which our BING++ manages to improve the localization quality by employing edges and segments to estimate object boundaries and update the proposals sequentially. We propose learning the parameters efficiently by searching for approximate solutions in a quantized parameter space for complexity reduction. We demonstrate the generalization of BING++ with the same fixed parameters across different object classes and datasets. Empirically our BING++ can run at half speed of BING on CPU, but significantly improve the localization quality by 18.5 and 16.7 percent on both VOC2007 and Microhsoft COCO datasets, respectively. Compared with other state-of-the-art approaches, BING++ can achieve comparable performance, but run significantly faster.
Empirical extensions of the lasso penalty to reduce the false discovery rate in high-dimensional Cox regression models.

Correct selection of prognostic biomarkers among multiple candidates is becoming increasingly challenging as the dimensionality of biological data becomes higher. Therefore, minimizing the false discovery rate (FDR) is of primary importance, while a low false negative rate (FNR) is a complementary measure. The lasso is a popular selection method in Cox regression, but its results depend heavily on the penalty parameter λ. Usually, λ is chosen using maximum cross-validated log-likelihood (max-cvl). However, this method has often a very high FDR. We review methods for a more conservative choice of λ. We propose an empirical extension of the cvl by adding a penalization term, which trades off between the goodness-of-fit and the parsimony of the model, leading to the selection of fewer biomarkers and, as we show, to the reduction of the FDR without large increase in FNR. We conducted a simulation study considering null and moderately sparse alternative scenarios and compared our approach with the standard lasso and 10 other competitors: Akaike information criterion (AIC), corrected AIC, Bayesian information criterion (BIC), extended BIC, Hannan and Quinn information criterion (HQIC), risk information criterion (RIC), one-standard-error rule, adaptive lasso, stability selection, and percentile lasso. Our extension achieved the best compromise across all the scenarios between a reduction of the FDR and a limited raise of the FNR, followed by the AIC, the RIC, and the adaptive lasso, which performed well in some settings. We illustrate the methods using gene expression data of 523 breast cancer patients. In conclusion, we propose to apply our extension to the lasso whenever a stringent FDR with a limited FNR is targeted. Copyright © 2016 John Wiley & Sons, Ltd.
Question Answering with Character-Level LSTM Encoders and Model-Based Data Augmentation

This paper presents a character-level encoder-decoder modeling method for question answering (QA) from large-scale knowledge bases (KB). This method improves the existing approach [9] from three aspects. First, long short-term memory (LSTM) structures are adopted to replace the convolutional neural networks (CNN) for encoding the candidate entities and predicates. Second, a new strategy of generating negative samples for model training is adopted. Third, a data augmentation strategy is applied to increase the size of the training set by generating factoid questions using another trained encoder-decoder model. Experimental results on the SimpleQuestions dataset and the Freebase5M KB demonstrates the effectiveness of the proposed method, which improves the state-of-the-art accuracy from 70.3% to 78.8% when augmenting the training set with 70,000 generated triple-question pairs.
Near-Optimal Velocity Control for Mobile Charging in Wireless Rechargeable Sensor Networks

Limited energy in each node is the major design constraint in wireless sensor networks (WSNs). To overcome this limit, wireless rechargeable sensor networks (WRSNs) have been proposed and studied extensively over the last few years. In a typical WRSN, batteries in sensor nodes can be replenished by a mobile charger that periodically travels along a certain trajectory in the sensing area. To maximize the charged energy in sensor nodes, one fundamental question is how to control the traveling velocity of the charger. In this paper, we first identify the optimal velocity control as a key design objective of mobile wireless charging in WRSNs. We then formulate the optimal charger velocity control problem on arbitrarily-shaped irregular trajectories in a 2D space. The problem is proved to be NP-hard, and hence a heuristic solution with a provable upper bound is developed using novel spatial and temporal discretization. We also derive the optimal velocity control for moving the charger along a linear (1D) trajectory commonly seen in many WSN applications. Extensive simulations show that the network lifetime can be extended by 2.5× with the proposed velocity control mechanisms.
Bringing Empathy into the Discussions about Corporate Social Responsibility and Value Based Ethical Leadership

Our aim is to understand and interpret leader and employee’s perception about ethical leadership. We engaged in qualitative research method based on interpretive paradigm based on our social constructed ontological perspective.Empirical findings were collected through eleven semi-structured interviews in two organizations operating in publications and microbiology-laboratories supply market.
Contract-Theoretic Approaches to Wages and Displacement

This paper develops a theoretical framework for analyzing contracting imperfections in long-term employment relationships. We focus chiefly on limited enforceability and limited worker liquidity. Inefficient severance of employment relationships, payment of efficiency wages, the relative responses of wages and employment to business cycle shocks, and the propagation of these shocks are linked to the nature of contracting imperfections.
Maternal Prepregnancy Body Mass Index and Gestational Weight Gain on Pregnancy Outcomes

OBJECTIVE
The aim of the present study was to evaluate the single and joint associations of maternal prepregnancy body mass index (BMI) and gestational weight gain (GWG) with pregnancy outcomes in Tianjin, China.


METHODS
Between June 2009 and May 2011, health care records of 33,973 pregnant women were collected and their children were measured for birth weight and birth length. The independent and joint associations of prepregnancy BMI and GWG based on the Institute of Medicine (IOM) guidelines with the risks of pregnancy and neonatal outcomes were examined by using Logistic Regression.


RESULTS
After adjustment for all confounding factors, maternal prepregnancy BMI was positively associated with risks of gestational diabetes mellitus (GDM), pregnancy-induced hypertension, caesarean delivery, preterm delivery, large-for-gestational age infant (LGA), and macrosomia, and inversely associated with risks of small-for-gestational age infant (SGA) and low birth weight. Maternal excessive GWG was associated with increased risks of pregnancy-induced hypertension, caesarean delivery, LGA, and macrosomia, and decreased risks of preterm delivery, SGA, and low birth weight. Maternal inadequate GWG was associated with increased risks of preterm delivery and SGA, and decreased risks of LGA and macrosomia, compared with maternal adequate GWG. Women with both prepregnancy obesity and excessive GWG had 2.2-5.9 folds higher risks of GDM, pregnancy-induced hypertension, caesarean delivery, LGA, and macrosomia compared with women with normal prepregnancy BMI and adequate GWG.


CONCLUSIONS
Maternal prepregnancy obesity and excessive GWG were associated with greater risks of pregnancy-induced hypertension, caesarean delivery, and greater infant size at birth. Health care providers should inform women to start the pregnancy with a BMI in the normal weight category and limit their GWG to the range specified for their prepregnancy BMI.
Microwave irradiation of soil for routine measurement of microbial biomass carbon

 Microwave irradiation was evaluated as a non-toxic alternate to chloroform fumigation for routine measurement of soil microbial biomass C. Microwave energy was applied to moist soil to disrupt microbial cells. The flush of C released was then measured after extraction or incubation. Microwave irradiation at 800 J g–1 soil was optimal because this level resulted in an almost instantaneous rise in soil temperature (≥80  °C), an abrupt reduction in microbial activity, maximal release of biomass C, and minimal solubilization of humic substances. Both incubation-CO2 titration and extraction-colorimetry methods were used on separate 20-g subsamples to compare the labile C in the microwave-treated and untreated soil samples. The incubation-titration method was also used to measure C in chloroform-fumigated soil samples. Averaged across soils, the chloroform fumigation yielded 123.3±5.1 mg CO2-C kg–1. Microwave irradiation yielded 93.6±3.9 mg CO2-C kg–1 soil determined by incubation and 52.4±2.4 mg C kg–1 soil determined by extraction, accounting for 76% and 42% of the net flush of C measured by the chloroform fumigation. Microwave-stimulated net flushes of C were correlated closely (r 2=0.974 for incubation or 0.908 for extraction) with microbial biomass C measured by the chloroform fumigation. Little correlation was found with the total soil organic C (r 2=0.241 for incubation or for 0.166 extraction). Mean efficiency factors for incubation (K MI) or extraction (K ME) were used to calculate microbial biomass C from net flushes of C between microwaved and unmicrowaved soils. Values of K MI and K ME were not affected by soil pH, bulk density or clay contents. Extraction of microwaved soil by 0.5M K2SO4 proved to be a simple, fast, precise, reliable, and safe method to measure soil microbial biomass C.
Conceptual Design Tools for Civil Engineering

This paper gives a brief overview of the tools we have developed to support conceptual design in civil engineering. Based on the UPGRADE framework, two applications, one for the knowledge engineer and another for architects allow to store domain specific knowledge and to use this knowledge during conceptual design. Consistency analyses check the design against the defined knowledge and inform the architect if rules are violated.
Diet and Nutritional Status of Tribal Population in ITDA Project Areas of Khammam District, Andhra Pradesh

Tribal populations are socio-economically disadvantaged compared to other population groups. They have different health problems owing to the variability in their geographical, socio-economic development and cultural characteristics. At the request of the project officer, a cross sectional survey was carried out to assess the diet and nutritional status of tribal population in ITDA, Bhadrachalam in Khammam district of Andhra Pradesh. A total of eight hundred households in twenty villages from five Mandals, were covered for survey. The study revealed that a majority of the households were living in kutcha houses. The major occupation of the head of the HH in a majority of the HHs was either agricultural labour or other labour. About 72% of the men and 88% of their women counterparts were illiterate. In general at household level, the average consumption of all the foods except cereals and millets were below the recommended level. The average intake of all the nutrients was lower than the RDA as well as the figures reported in NNMB tribal survey. The extent of deficit was highest with respect to vitamin A (83%), followed by riboflavin (64%), iron (59%), and total fat (47%). Protein calorie adequacy status revealed that about half of the HHs (52%) were consuming adequate amounts of both protein and energy, while about 21% were consuming inadequate amounts of both the nutrients. The prevalence of undernutrition (<Median –2SD of weight for age) among 1-5 years children were lower (65.4%) than that reported for the Tribes in the State of Andhra Pradesh (68.8%). Among the adolescents (12-17 years), about 45% of boys and 21% of girls were undernourished. The prevalence of Chronic Energy Deficiency (CED) among adults was about 51%. Breastfeeding practices revealed that majority of the mothers initiated breast-feeding with in 24hrs of delivery. About 76% of the children started receiving the complementary feeding from the age of 4-6 months. About 93% of children (12-24 months) were fully immunized and 90% received at least one dose of massive dose vitamin A during previous one year. However the study indicates the need to control the micro nutrient deficiencies through dietary diversification by promoting home gardening. Since the prevalence of morbidity was higher in this population, effort should be made to improve the environmental sanitation and personal hygiene.