LLukas22/scidocs huggingface dataset:
Integrated Terahertz Graphene Modulator with 100% Modulation Depth

1 OPTIMUS, School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798 Singapore. 2 School of Electronic and Electrical Engineering, University of Leeds, Leeds LS2 9JT, UK. 3 Singapore Institute of Manufacturing Technology, Singapore. CDPT, School of Physical and Mathematical Sciences, Nanyang Technological University, 50 Nanyang Avenue, 639798 Singapore.
High voltage direct current transmission - A Review, Part II - Converter technologies

This paper is the 2<sup>nd</sup> part of the survey titled “High Voltage Direct Current Transmission - A Review, Part I”. The main converter technologies and HVDC systems' components will be discussed in this complementary paper.
Is Customer Relationship Management a Success Factor in Electronic Commerce?

Customer Relationship Management (CRM) is a concept for increasing companies’ profitability by enabling them to identify and concentrate on their profitable customers. The term Electronic Commerce Customer Relationship Management (ECCRM) refers to the application of CRM in electronic commerce, i.e. when business relationships are maintained via the Internet or Worldwide Web. Previous studies on ECCRM implementations and their impact on businesses have often focused on the process level, technical aspects, or on marketing issues. However, viewed from a higher level, the effect on corporate success in electronic commerce is still unclear. The objective of our study is to examine this effect. Following a quantitative, indirect, and confirmatory methodology, we construct a covariance structure (or LISREL) model. We test our research hypotheses employing a data set comprising 469 cases of general companies, obtained from a representative survey of 1,308 companies in the German-speaking market. We also distinguish between Business-to-Business (B2B) and Business-to-Consumer (B2C) companies and control for the influence of company size and lag effects. We find that ECCRM is a critical success factor in electronic commerce, independent of companies’ time on the Web. It is especially critical for B2C and small companies.
Handsfree Omnidirectional VR Navigation using Head Tilt

Navigating mobile virtual reality (VR) is a challenge due to limited input options and/or a requirement for handsfree interaction. Walking-in-place (WIP) is considered to offer a higher presence than controller input but only allows unidirectional navigation in the direction of the user's gaze--which impedes navigation efficiency. Leaning input enables omnidirectional navigation but currently relies on bulky controllers, which aren't feasible in mobile VR contexts. This note evaluates the use of head-tilt - implemented using inertial sensing - to allow for handsfree omnidirectional VR navigation on mobile VR platforms. A user study with 24 subjects compared three input methods using an obstacle avoidance navigation task: (1) head-tilt alone (TILT) (2) a hybrid method (WIP-TILT) that uses head tilting for direction and WIP to control speed; and (3) traditional controller input. TILT was significantly faster than WIP-TILT and joystick input, while WIP-TILT and TILT offered the highest presence. There was no difference in cybersickness between input methods.
[Para-infectious seizures: A retrospective multicentre study].

INTRODUCTION
Para-infectious seizures are afebrile seizures that are associated with mild infections, and occur in children with no pre-existing neurological illness. They are still little known in our environment.


METHODS
A multicentre retrospective study was conducted that included patients with normal psychomotor development and had presented with one or more seizures in the context of a mild afebrile infection.


RESULTS
A total of 38 patients (47% male, 53% female) were included in the study over a period of three years (2012-2015). The mean age was 2.1 years. A previous history of febrile seizures was found in 7.9% of them. Mean number of seizures per patient was 2.2, with 57.9% of them being tonic-clonic seizures. The mean duration of seizures was 3.2minutes. An EEG was performed during admission in 73.7% of cases. Lumbar punctures were performed in 34.2% of cases. All were normal. Neuroimaging tests were carried out in 36.9% of cases. Brain MRI was the imaging test performed in most cases (21.1%), with no any pathological findings. The most frequent infection found was acute gastroenteritis (68%), followed by upper respiratory tract infection (32%). Almost two-thirds (63.2%) of patients did not require anticonvulsant medication. Rectal diazepam was the most frequently used drug in emergencies. Intravenous medication was required by 28.9% of patients due to repeated seizures. The most frequently used drug in the non-emergency setting was valproic acid. Anticonvulsant treatment was continued after discharge in 16% of patients. Para-infectious seizures was the diagnosis in 76.3% of cases when discharged.


CONCLUSIONS
Knowledge of para-infectious seizures, their clinical diagnosis and benign course is crucial, as this would avoid further testing and unnecessary treatments.
Ultra-fast NoC emulation on a single FPGA

Network-on-Chip (NoC) has become the de facto on-chip communication architecture for many-core systems. This paper proposes novel methods for emulating large-scale NoC designs on a single FPGA. Since FPGAs offer a highly parallel platform, FPGA-based emulation can be much faster than the software-based approach. However, emulating NoC designs with up to thousands of nodes is a challenging task due to the FPGA capacity constraints. We first describe how to accurately model synthetic workloads on FPGA by separating the time of the emulated network and the times of the traffic generation units. We next present a novel use of time-multiplexing in emulating the entire network using several physical nodes. Finally, we show the basic steps to apply the proposed methods to emulate different NoC architectures. The proposed methods enable ultrafast emulations of large-scale NoC designs with up to thousands of nodes using only on-chip resources of a single FPGA. In particular, more than 5,000× simulation speedup over BookSim, a widely used software-based NoC simulator, is achieved.
Author’s Reply to Srinivas: “Pharmacokinetics and Pharmacokinetic/Pharmacodynamic Modeling of Filgotinib (GLPG0634), a Selective JAK1 Inhibitor, in Support of Phase IIB Dose Selection”

Background and Objectives Filgotinib (GLPG0634) is a selective inhibitor of Janus kinase 1 (JAK1) currently in development for the treatment of rheumatoid arthritis and Crohn’s disease. While less selective JAK inhibitors have shown long-term efficacy in treating inflammatory conditions, this was accompanied by dose-limiting side effects. Here, we describe the pharmacokinetics of filgotinib and its active metabolite in healthy volunteers and the use of pharmacokinetic–pharmacodynamic modeling and simulation to support dose selection for phase IIB in patients with rheumatoid arthritis. Methods Two trials were conducted in healthy male volunteers. In the first trial, filgotinib was administered as single doses from 10 mg up to multiple daily doses of 200 mg. In the second trial, daily doses of 300 and 450 mg for 10 days were evaluated. Non-compartmental analysis was used to determine individual pharmacokinetic parameters for filgotinib and its metabolite. The overall pharmacodynamic activity for the two moieties was assessed in whole blood using interleukin-6-induced phosphorylation of signal-transducer and activator of transcription 1 as a biomarker for JAK1 activity. These data were used to conduct non-linear mixed-effects modeling to investigate a pharmacokinetic/pharmacodynamic relationship. Results Modeling and simulation on the basis of early clinical data suggest that the pharmacokinetics of filgotinib are dose proportional up to 200 mg, in agreement with observed data, and support that both filgotinib and its metabolite contribute to its pharmacodynamic effects. Simulation of biomarker response supports that the maximum pharmacodynamic effect is reached at a daily dose of 200 mg filgotinib. Conclusion Based on these results, a daily dose range up to 200 mg has been selected for phase IIB dose-finding studies in patients with rheumatoid arthritis.
Caregiving, Metabolic Syndrome Indicators, and 1-year Decline in Walking Speed: Results of Caregiver-SOF

BACKGROUND
Chronic stress may lead to health decline through metabolic syndrome. Thus, persons in stressful caregiving situations who also have more indicators of metabolic syndrome may experience more decline than other caregivers or noncaregivers.


METHODS
The sample included 921 women (338 caregivers and 583 noncaregivers) from the Caregiver-Study of Osteoporotic Fractures study. Participants had home-based baseline and 1-year follow-up interviews between 1999 and 2003. At baseline, caregivers were categorized as long term ((3)4 years) versus short term (<4 years), and caring for someone with Alzheimer's disease/dementia or not. A metabolic risk composite score was the sum of four indicators: body mass index (3)30, and diagnosis or using medications for hypertension, diabetes, or high cholesterol. Walking speed (m/second) was measured at both interviews.


RESULTS
Walking speed declined for the total sample (adjusted mean = -0.005 m/second, +/-0.16) over an average of 1.04 years (+/-0.16). Overall, caregiving was not associated with decline. Increasing metabolic risk score was associated with greater decline for the total sample and long-term and dementia caregivers, but not other caregivers or noncaregivers. Metabolic risk score modified the adjusted associations between years of caregiving and dementia caregiving with walking speed decline (p values for interaction terms were 0.039 and 0.057, respectively). The biggest declines were in long-term caregivers and dementia caregivers who also had 3-4 metabolic indicators (-0.10 m/second and -0.155 m/second, respectively).


CONCLUSIONS
Walking speed declined the most among older women who had both stressful caregiving situations and more metabolic syndrome indicators, suggesting these caregiver subgroups may have increased risk of health decline.
When Switches Became Programs: Programming Languages and Telecommunications, 1965-1980

Beginning in the mid-1960s, electromechanical telecommunications switches were increasingly replaced by computer-controlled switches. Production and development of this equipment relied on the construction of its software. This software was shaped by practices, ideas, and ideals appropriated from the computer industry and computer science as much as by concerns and constraints of the telecommunications industry itself.
Human contour extraction from RGBD camera for action recognition

Spatio-temporal cuboid pyramid (STCP) for action recognition using depth motion sequences [1] is influenced by depth camera error which leads the depth motion sequence (DMS) existing many kinds of noise, especially on the surface. It means that the dimension of DMS is awfully high and the feature for action recognition becomes less apparent. In this paper, we present an effective method to reduce noise, which is to segment foreground. We firstly segment and extract human contour in the color image using convolutional network model. Then, human contour is re-segmented utilizing depth information. Thirdly we project each frame of the segmented depth sequence onto three views. We finally extract features from cuboids and recognize human actions. The proposed approach is evaluated on three public benchmark datasets, i.e., UTKinect-Action Dataset, MSRActionPairs Dataset and 3D Online Action Dataset. Experimental results show that our method achieves state-of-the-art performance.
Temporal distortion for animated transitions

Animated transitions are popular in many visual applications but they can be difficult to follow, especially when many objects move at the same time. One informal design guideline for creating effective animated transitions has long been the use of slow-in/slow-out pacing, but no empirical data exist to support this practice. We remedy this by studying object tracking performance under different conditions of temporal distortion, i.e., constant speed transitions, slow-in/slow-out, fast-in/fast-out, and an adaptive technique that slows down the visually complex parts of the animation. Slow-in/slow-out outperformed other techniques, but we saw technique differences depending on the type of visual transition.
Target recognition by components for mobile robot navigation

This paper presents a vision-based technique for detecting targets of the environment which have to be reached by an autonomous mobile robot during its navigational tasks. The targets the robot has to reach are the doors of the authors’ office building. The detection of the door has been performed by detecting its most significant components in the image and it is based on data classification. Two neural classifiers have been trained for recognizing single components of the door. Then a combining algorithm, based on heuristic considerations, checks that they are in the proper geometric configuration of the structure of the door. The novelty of this work is to use together colour and shape information for identifying features and for detecting the components of the target. The approach, based on learning by components, is able to cleverly solve the problems of scale changes, perspective variations and partial occlusions. The obtained detecting system has been tested on a large test set of real images showing a high reliability and robustness: doors of different rooms, under different illumination conditions and by different viewpoints have been successfully recognized. Results in terms of door detection rate and false positive rate are presented throughout the paper.
Formation of nanostructured YSZ/Ni anode with pore channels by plasma spraying

Abstract YSZ/Ni is the conventionally most used material for making the anode of a solid oxide fuel cell. Agglomerated nanostructured YSZ/NiO powders and plasma spray are applied to produce nanostructured YSZ/NiO coatings on porous support substrates. After reduction in an ambient atmosphere of 7% hydrogen and 93% argon at about 800 °C for 4 hours, a novel SOFC anode with nanostructured characteristics such as nano YSZ particles, nano Ni particles, nano pores and nano pore channels is produced. This new YSZ/Ni anode provides larger triple phase boundaries for hydrogen oxidation reactions. X-ray diffraction patterns of these YSZ/NiO coatings after 1 h of heat treatment at temperatures from 700 to 1100 °C are obtained and Scherrer analysis is conducted to study the effect of temperature on grain size. The results obtained from SEM, TEM, XRD and EDX measurements and analyses are presented in this investigation.
Evolution Strategies for Deep Neural Network Models Design

Deep neural networks have become the state-ofart methods in many fields of machine learning recently. Still, there is no easy way how to choose a network architecture which can significantly influence the network performance. This work is a step towards an automatic architecture design. We propose an algorithm for an optimization of a network architecture based on evolution strategies. The al gorithm is inspired by and designed directly for the Keras library [3] which is one of the most common implementations of deep neural networks. The proposed algorithm is tested on MNIST data set and the prediction of air pollution based on sensor measurements, and it is compared to several fixed architectures and support vector regression.
Implementation of Text clustering using Genetic Algorithm

Text clustering is an important area of interest in the field of Text summarization, sentiment analysis etc. There have been a lot of algorithms experimented during the past years, which have a wide range of performances. One of the most popular method used is k-means, where an initial assumption is made about k, which is the number of clusters to be generated. Now a new method is introduced where the number of clusters is found using a modified spectral bisection and then the output is given to a genetic algorithm where the final solution is obtained. Keywords— Cluster, Spectral Bisection, Genetic Algorithm, kmeans.
Drawing ecological inferences from coincident patterns of population- and community-level biodiversity.

Biodiversity is comprised of genetic and phenotypic variation among individual organisms, which might belong to the same species or to different species. Spatial patterns of biodiversity are of central interest in ecology and evolution for several reasons: to identify general patterns in nature (e.g. species-area relationships, latitudinal gradients), to inform conservation priorities (e.g. identifying hotspots, prioritizing management efforts) and to draw inferences about processes, historical or otherwise (e.g. adaptation, the centre of origin of particular clades). There are long traditions in ecology and evolutionary biology of examining spatial patterns of biodiversity among species (i.e. in multispecies communities) and within species, respectively, and there has been a recent surge of interest in studying these two types of pattern simultaneously. The idea is that examining both levels of diversity can materially advance the above-stated goals and perhaps lead to entirely novel lines of inquiry. Here, we review two broad categories of approach to merging studies of inter- and intraspecific variation: (i) the study of phenotypic trait variation along environmental gradients and (ii) the study of relationships between patterns of molecular genetic variation within species and patterns of distribution and diversity across species. For the latter, we report a new meta-analysis in which we find that correlations between species diversity and genetic diversity are generally positive and significantly stronger in studies with discrete sampling units (e.g. islands, lakes, forest fragments) than in studies with nondiscrete sampling units (e.g. equal-area study plots). For each topic, we summarize the current state of knowledge and key future directions.
EyePACS: an adaptable telemedicine system for diabetic retinopathy screening.

BACKGROUND
Annual retinal screening of patients with diabetes is the standard clinical practice to prevent visual impairment and blindness from diabetic retinopathy. Telemedicine-based diabetic retinopathy screening (DRS) in primary care settings can effectively detect sight-threatening retinopathy and significantly increase compliance with annual retinal exams. EyePACS is a license-free Web-based DRS system designed to simplify the process of image capture, transmission, and review. The system provides a flexible platform for collaboration among clinicians about diabetic retinopathy.


METHODS
Primary clinic personnel (i.e., nursing, technical, or administrative staff) are trained and certified by the EyePACS program to acquire retinal images from standard digital retinal cameras. Relevant clinical data and eight high-resolution images per patient (two external and six retinal images) are encrypted and transmitted to a secure Internet server, using a standard computer and Web browser. Images are then interpreted by certified EyePACS reviewers or local eye care providers who are certified through the EyePACS Retinopathy Grading System. Reports indicating retinopathy level and referral recommendations are transmitted back to primary care providers through the EyePACS Web site or through interfaces between EyePACS and Health Level 7-compliant electronic medical records or chronic disease registries.


RESULTS
The pilot phase of the EyePACS DRS program in California (2005-2006) recorded 3562 encounters. Since 2006, EyePACS has been expanded to over 120 primary care sites throughout California and elsewhere recording over 34,000 DRSs. The overall rate of referral is 8.21% for sight-threatening retinopathy and 7.83% for other conditions (e.g., cataract and glaucoma).


CONCLUSION
The use of license-free Web-based software, standard interfaces, and flexible protocols has allowed primary care providers to adopt retinopathy screening with minimal effort and resources.
Sipuleucel-T immunotherapy for castration-resistant prostate cancer.

BACKGROUND
Sipuleucel-T, an autologous active cellular immunotherapy, has shown evidence of efficacy in reducing the risk of death among men with metastatic castration-resistant prostate cancer.


METHODS
In this double-blind, placebo-controlled, multicenter phase 3 trial, we randomly assigned 512 patients in a 2:1 ratio to receive either sipuleucel-T (341 patients) or placebo (171 patients) administered intravenously every 2 weeks, for a total of three infusions. The primary end point was overall survival, analyzed by means of a stratified Cox regression model adjusted for baseline levels of serum prostate-specific antigen (PSA) and lactate dehydrogenase.


RESULTS
In the sipuleucel-T group, there was a relative reduction of 22% in the risk of death as compared with the placebo group (hazard ratio, 0.78; 95% confidence interval [CI], 0.61 to 0.98; P=0.03). This reduction represented a 4.1-month improvement in median survival (25.8 months in the sipuleucel-T group vs. 21.7 months in the placebo group). The 36-month survival probability was 31.7% in the sipuleucel-T group versus 23.0% in the placebo group. The treatment effect was also observed with the use of an unadjusted Cox model and a log-rank test (hazard ratio, 0.77; 95% CI, 0.61 to 0.97; P=0.02) and after adjustment for use of docetaxel after the study therapy (hazard ratio, 0.78; 95% CI, 0.62 to 0.98; P=0.03). The time to objective disease progression was similar in the two study groups. Immune responses to the immunizing antigen were observed in patients who received sipuleucel-T. Adverse events that were more frequently reported in the sipuleucel-T group than in the placebo group included chills, fever, and headache.


CONCLUSIONS
The use of sipuleucel-T prolonged overall survival among men with metastatic castration-resistant prostate cancer. No effect on the time to disease progression was observed. (Funded by Dendreon; ClinicalTrials.gov number, NCT00065442.)
Relationship between oral health and its impact on the quality life of Alzheimer's disease patients: a supportive care trial.

UNLABELLED
Dental infections have recently been related with a possible risk factor for Neurodegenerative pathologies like Alzheimer's disease (AD). Even if there are no specific studies investigating orofacial pain in this patient group, dental health is known to be a potential cause of pain and to influence quality of life and disease progression. The aim of this study was to investigate how the AD patients' oral health status may influence their quality of life. 158 patients affected by AD were evaluated using Decayed Missed Filled Teeth (DMFT), Oral Health Impact Profile-14 (OHIP-14) and Clinical Investigation consisting in the detection of cavities and measurement of the probing depth in each patient; other parameters like gingival bleeding, biofilm index and tooth mobility degree test have been recorded. The ratio between diagnosis of periodontal disease and impact on quality of life was significant in individuals with periodontitis (p < 0.001) and missed filled teeth. Gingival bleeding, and probing depth > 4 mm were associated with intensely negative impact on quality of life (p = 0.013, p < 0.001, and p = 0.012 respectively). Moreover, the absence of more than 2 molar teeth increases the chewing inability decreasing the patient quality of life.


CONCLUSION
It was observed a correlation between the age and the high index of pathologies analyzed, due to the progressive nature of the disease. Concepts of health and disease determined by clinical diagnostic criteria may influence the assessment of the impact of periodontal disease on Alzheimer's quality of life.