LLukas22/scidocs huggingface dataset:
Differential regulation of microRNAs in response to osmotic, salt and cold stresses in wheat

MicroRNAs (miRNAs) are tiny non-coding regulatory molecules that modulate plant’s gene expression either by cleaving or repressing their mRNA targets. To unravel the plant actions in response to various environmental factors, identification of stress related miRNAs is essential. For understanding the regulatory behaviour of various abiotic stresses and miRNAs in wheat genotype C-306, we examined expression profile of selected conserved miRNAs viz. miR159, miR164, miR168, miR172, miR393, miR397, miR529 and miR1029 tangled in adapting osmotic, salt and cold stresses. The investigation revealed that two miRNAs (miR168, miR397) were down-regulated and miR172 was up-regulated under all the stress conditions. However, miR164 and miR1029 were up-regulated under cold and osmotic stresses in contrast to salt stress. miR529 responded to cold alone and does not change under osmotic and salt stress. miR393 showed up-regulation under osmotic and salt, and down-regulation under cold stress indicating auxin based differential cold response. Variation in expression level of studied miRNAs in presence of target genes delivers a likely elucidation of miRNAs based abiotic stress regulation. In addition, we reported new stress induced miRNAs Ta-miR855 using computational approach. Results revealed first documentation that miR855 is regulated by salinity stress in wheat. These findings indicate that diverse miRNAs were responsive to osmotic, salt and cold stress and could function in wheat response to abiotic stresses.
Predicting HIV disease progression in children using measures of neuropsychological and neurological functioning. Pediatric AIDS clinical trials 152 study team.

BACKGROUND
Neuropsychological testing and 2 measures of neurological status, cortical atrophy, and motor dysfunction were assessed for their usefulness in predicting human immunodeficiency virus (HIV) disease progression in infants, children, and adolescents who participated in Pediatric AIDS Clinical Trials Group Protocol 152 (PACTG 152).


METHODS
A cohort of 722 antiretroviral therapy-naive children with symptomatic HIV infection were assessed at study entry and at later intervals. Assessments included neurodevelopmental testing, neuroradiologic imaging, and neurological examination of motor function. CD4 cell count and plasma RNA viral load also were measured.


RESULTS
Children with the lowest neuropsychological functioning (IQ < 70) at baseline had the highest risk for later HIV disease progression (56%), compared with those with borderline/low (IQ = 70-89) functioning (26%), or with average or above (IQ > 90) functioning (18%). This was also true of week 48 neuropsychological functioning. Motor dysfunction (especially reduced muscle mass) at entry also predicted disease progression. Furthermore, motor dysfunction and week 48 neuropsychological functioning provided predictive information beyond that obtainable from surrogate markers of HIV disease status (eg, CD4 count, HIV RNA level). Children with cortical atrophy also were at higher risk for later disease progression, but when CD4 count and RNA viral load were known, cortical atrophy information provided no additional predictive information.


CONCLUSIONS
Measures of neuropsychological and motor function status provide unique information regarding pediatric HIV disease progression. As such, these findings have important implications for predicting long-term outcomes (eg, longevity) in pediatric patients.
Real-time eye tracking for password authentication

Personal identification numbers are widely used for user authentication and security. Password authentication using PINs requires users to physically input the PIN, which could be vulnerable to password cracking via shoulder surfing or thermal tracking. PIN authentication with hands-off gaze-based PIN entry techniques, on the other hand, leaves no physical footprints behind and therefore offer a more secure password entry option. Gaze-based authentication refers to finding the eye location across sequential image frames, and tracking eye center over time. This paper presents a real-time application for gaze-based PIN entry, and eye detection and tracking for PIN identification using a smart camera.
A novel implantable vagus nerve stimulation system (ADNS-300) for combined stimulation and recording of the vagus nerve: Pilot trial at Ghent University Hospital

PURPOSE
Vagus nerve stimulation (VNS) is an established treatment for refractory epilepsy. The ADNS-300 is a new system for VNS that includes a rechargeable stimulus generator and an electrode for combined stimulation and recording. In this feasibility study, three patients were implanted with ADNS-300 for therapeutic VNS. In addition, compound action potentials (CAPs) were recorded to evaluate activation of the vagus nerve in response to VNS.


METHODS
Three patients were implanted with a cuff-electrode around the left vagus nerve, that was connected to a rechargeable pulse generator under the left clavicula. Two weeks after surgery, therapeutic VNS (0.25-1.25 mA, 500 μs, 30s on, 10 min off and 30Hz) was initiated and stimulus-induced CAPs were recorded.


RESULTS
The ADNS-300 system was successfully implanted in all three patients and patients were appropriately stimulated during six months of follow-up. A reduction in seizure frequency was demonstrated in two patients (43% and 40% in patients 1 and 3, respectively), while in patient 2 seizure frequency remained unchanged. CAPs could be recorded in patients 1 and 2, proving stimulation-induced activation of the vagus nerve.


CONCLUSION
This feasibility study demonstrates that the ADNS-300 system can be used for combined therapeutic stimulation (in 3/3 patients) and recording of CAPs in response to VNS (in 2/3 patients) up to three weeks after surgery. Implantation in a larger number of patients will lead to a better understanding of the electrophysiology of the vagus nerve, which in turn could result in more adequate and individualized VNS parameter choice.
Ethical and moral matters in teaching and teacher education

The author reviews a set of articles on ethical and moral matters in teaching and teacher education previously published by Teaching and Teacher Education. Comparisons are made and a summary of findings offered.
Unpaired Image Captioning by Language Pivoting

•We present an approach to this unpaired image captioning problem by language pivoting. •Our method can effectively capture the characteristics of an image captioner from the pivot language (Chinese) and align it to the target language (English) using another pivot-target (Chinese-English) parallel corpus. •Quantitative comparisons against several baseline approaches demonstrate the effectiveness of our method.
On the splitting method for vector quantization codebook generation

Timo Kaukoranta Olli Nevalainen University of Turku Turku Centre for Computer Science (TUCS) Department of Computer Science Lemminkäisenkatu 14 A FIN-20520 Turku, Finland Abstract. The well-known LBG algorithm uses binary splitting for generating an initial codebook, which is then iteratively improved by the generalized Lloyd algorithm (GLA). We study different variants of the splitting method and its application to codebook generation with and without the GLA. A new iterative splitting method is proposed, which is applicable to codebook generation without the GLA. Experiments show that the improved splitting method outperforms both the GLA and the other existing splitting-based algorithms. The best combination uses hyperplane partitioning of the clusters along the principal axis as proposed by Wu and Zhang, integrated with a local repartitioning phase at each step of the algorithm. © 1997 Society of Photo-Optical Instrumentation Engineers. [S0091-3286(97)02311-8]
Distance-Based Reconstruction of Tree Models for Oncogenesis

Comparative genomic hybridization (CGH) is a laboratory method to measure gains and losses in the copy number of chromosomal regions in tumor cells. It is hypothesized that certain DNA gains and losses are related to cancer progression and that the patterns of these changes are relevant to the clinical consequences of the cancer. It is therefore of interest to develop models which predict the occurrence of these events, as well as techniques for learning such models from CGH data. We continue our study of the mathematical foundations for inferring a model of tumor progression from a CGH data set that we started in Desper et al. (1999). In that paper, we proposed a class of probabilistic tree models and showed that an algorithm based on maximum-weight branching in a graph correctly infers the topology of the tree, under plausible assumptions. In this paper, we extend that work in the direction of the so-called distance-based trees, in which events are leaves of the tree, in the style of models common in phylogenetics. Then we show how to reconstruct the distance-based trees using tree-fitting algorithms developed by researchers in phylogenetics. The main advantages of the distance-based models are that 1) they represent information about co-occurrences of all pairs of events, instead of just some pairs, 2) they allow quantitative predictions about which events occur early in tumor progression, and 3) they bring into play the extensive methodology and software developed in the context of phylogenetics. We illustrate the distance-based tree method and how it complements the branching tree method, with a CGH data set for renal cancer.
Augmented Reality in Reality

In this survey of academic contributions driving augmented reality’s commercial potential and of the industry trends advancing software and hardware developments and emerging applications, the author offers advice on how startups hoping to leverage these advances can compete against senior tech tycoons.
Effect of classroom-based physical activity interventions on academic and physical activity outcomes: a systematic review and meta-analysis

BACKGROUND
Physical activity is associated with many physical and mental health benefits, however many children do not meet the national physical activity guidelines. While schools provide an ideal setting to promote children's physical activity, adding physical activity to the school day can be difficult given time constraints often imposed by competing key learning areas. Classroom-based physical activity may provide an opportunity to increase school-based physical activity while concurrently improving academic-related outcomes. The primary aim of this systematic review and meta-analysis was to evaluate the impact of classroom-based physical activity interventions on academic-related outcomes. A secondary aim was to evaluate the impact of these lessons on physical activity levels over the study duration.


METHODS
A systematic search of electronic databases (PubMed, ERIC, SPORTDiscus, PsycINFO) was performed in January 2016 and updated in January 2017. Studies that investigated the association between classroom-based physical activity interventions and academic-related outcomes in primary (elementary) school-aged children were included. Meta-analyses were conducted in Review Manager, with effect sizes calculated separately for each outcome assessed.


RESULTS
Thirty-nine articles met the inclusion criteria for the review, and 16 provided sufficient data and appropriate design for inclusion in the meta-analyses. Studies investigated a range of academic-related outcomes including classroom behaviour (e.g. on-task behaviour), cognitive functions (e.g. executive function), and academic achievement (e.g. standardised test scores). Results of the meta-analyses showed classroom-based physical activity had a positive effect on improving on-task and reducing off-task classroom behaviour (standardised mean difference = 0.60 (95% CI: 0.20,1.00)), and led to improvements in academic achievement when a progress monitoring tool was used (standardised mean difference = 1.03 (95% CI: 0.22,1.84)). However, no effect was found for cognitive functions (standardised mean difference = 0.33 (95% CI: -0.11,0.77)) or physical activity (standardised mean difference = 0.40 (95% CI: -1.15,0.95)).


CONCLUSIONS
Results suggest classroom-based physical activity may have a positive impact on academic-related outcomes. However, it is not possible to draw definitive conclusions due to the level of heterogeneity in intervention components and academic-related outcomes assessed. Future studies should consider the intervention period when selecting academic-related outcome measures, and use an objective measure of physical activity to determine intervention fidelity and effects on overall physical activity levels.
How well are hypertension, hyperlipidemia, diabetes, and smoking managed after a stroke or transient ischemic attack?

BACKGROUND AND PURPOSE
Stroke prevention clinics (SPCs) are not usually involved with the active management of hypertension, hyperlipidemia, diabetes, and smoking. The effect of consultations generated at SPCs on the adequacy of the management of these risk factors for stroke has not been well described, and few studies have long-term follow-up.


METHODS
We performed a prospective study of 119 consecutive patients referred to an SPC for secondary prevention. One year after their baseline visit, patients were re-evaluated for the adequacy of the management of the above risk factors, and the proportion of improvement was assessed.


RESULTS
One-hundred twelve patients returned for their 1-year follow-up visit. Sixty-six were male, and the average age was 65 years. Hypertension was present in 83 patients, hyperlipidemia in 92, diabetes in 26, and smoking in 38, and 80 had multiple risk factors. At baseline, 66% of patients with hypertension, 17% of patients with hyperlipidemia, and 23% of diabetics had adequate management of their respective risk factors. During 1 year of follow-up, hypertension management improved 20% (P<0.001) and lipid management improved 32% (P<0.001). There was no significant improvement in diabetes management or smoking cessation.


CONCLUSIONS
Although our understanding of the benefit of addressing hypertension, hyperlipidemia, diabetes, and smoking for secondary prevention of stroke is evolving, we found marked room for improvement in the management of these four risk factors. SPCs may need to be more actively involved in the management of these modifiable risk factors, if we are to significantly impact the risk of recurrent stroke.
Averaging Inhomogeneous Cosmologies -- a Dialogue

The averaging problem for inhomogeneous cosmologies is discussed in the form of a disputation between two cosmologists, one of them (RED) advocating the standard model, the other (GREEN) advancing some arguments against it. Technical explanations of these arguments as well as the conclusions of this debate are given by BLUE.
Stochastic Modeling of Composite Web Services for Closed-Form Analysis of Their Performance and Reliability Bottlenecks

Web services providers often commit service-level agreements (SLAs) with their customers for guaranteeing the quality of the services. These SLAs are related not just to functional attributes of the services but to performance and reliability attributes as well. When combining several services into a composite service, it is non-trivial to determine, prior to service deployment, performance and reliability values of the composite service appropriately. Moreover, once the service is deployed, it is often the case that during operation it fails to meet its SLA and needs to detect what has gone wrong (i.e., performance/reliabilty bottlenecks). To resolve these, we develop a continuous-time Markov chain (CTMC) formulation of composite services with failures. By explicitly including failure states into the CTMC representation of a service, we can compute accurately both its performance and reliability using the single CTMC. We can also detect its performance and reliability bottlenecks by applying the formal sensitivity analysis technique. We demonstrate our approach by choosing a representative example of composite Web services and providing a set of closed-form formulas for its bottleneck detection.
Endurance and neuromuscular changes in world-class level kayakers during a periodized training cycle

This study was undertaken to analyze changes in selected cardiovascular and neuromuscular variables in a group of elite kayakers across a 12-week periodized cycle of combined strength and endurance training. Eleven world-class level paddlers underwent a battery of tests and were assessed four times during the training cycle (T0, T1, T2, and T3). On each occasion subjects completed an incremental test to exhaustion on the kayak-ergometer to determine maximal oxygen uptake (VO2max), second ventilatory threshold (VT2), peak blood lactate, paddling speed at VO2max (PSmax) and at VT2 (PSVT2), stroke rate at VO2max and at VT2, heart rate at VO2max and at VT2. One-repetition maximum (1RM) and mean velocity with 45% 1RM load (V 45%) were assessed in the bench press (BP) and prone bench pull (PBP) exercises. Anthropometric measurements (skinfold thicknesses and muscle girths) were also obtained. Training volume and exercise intensity were quantified for each of three training phases (P1, P2, and P3). Significant improvements in VO2max (9.5%), VO2 at VT2 (9.4%), PSmax (6.2%), PSVT2 (4.4%), 1RM in BP (4.2%) and PBP (5.3%), V 45% in BP (14.4%) and PBP (10.0%) were observed from T0 to T3. A 12-week periodized strength and endurance program with special emphasis on prioritizing the sequential development of specific physical fitness components in each training phase (i.e. muscle hypertrophy and VT2 in P1, and maximal strength and aerobic power in P2) seems effective for improving both cardiovascular and neuromuscular markers of highly trained top-level athletes.
Determinants of darunavir cerebrospinal fluid concentrations: impact of once-daily dosing and pharmacogenetics.

OBJECTIVES
To compare cerebrospinal fluid (CSF) darunavir and ritonavir concentrations in patients receiving darunavir/ritonavir 800/100 mg once daily or 600/100 mg twice daily. To determine the influence of single-nucleotide polymorphisms in the genes encoding for blood-brain barrier transporters (ABCB1 3435 C>T, ABCB1 1236 C>T, ABCB1 2677 G>T, SLCO1A2 38 A>G, SLCO1A2 516 A>C, ABCC2 -24 G>A) on darunavir and ritonavir penetration into CSF.


DESIGN
Comparative pharmacokinetics study in patients.


METHODS
Plasma and CSF darunavir and ritonavir concentrations (2-26 h after drug intake) were determined by a validated HPLC coupled with mass spectrometry method in adults on darunavir-based combination antiretroviral therapy undergoing a lumbar puncture.


RESULTS
HIV-infected patients on once-daily darunavir/ritonavir had significantly lower CSF darunavir trough concentrations and CSF-to-plasma ratios than patients on darunavir/ritonavir twice-daily (10.7 versus 38.2 ng/ml and 0.32 versus 0.90%; P < 0.05). No significant effect of single-nucleotide polymorphisms in the genes encoding for blood-brain barrier transporters was noted apart from slightly higher CSF darunavir penetration in patients carrying OATP1A2 uncommon variants.


CONCLUSIONS
This is the first study to compare darunavir CSF concentrations in patients taking the once-daily or the twice-daily dosage: our data show that darunavir and ritonavir dosing significantly affects not only CSF concentrations but also the extent of drug penetration into the CSF. Furthermore a minority of patients in the once-daily arm presented very low CSF concentration of potential concern for HIV control in the central nervous system. The relative importance of pharmacogenetics in influencing CSF darunavir pharmacokinetics deserves further clinical investigation.
Multisensor data fusion for robust pose estimation of a six-legged walking robot

For autonomous navigation tasks it is important that the robot always has a good estimate of its current pose with respect to its starting position and - in terms of orientation - with respect to the gravity vector. For this, the robot should make use of all available information and be robust against the failure of single sensors. In this paper a multisensor data fusion algorithm for the six-legged walking robot DLR Crawler is presented. The algorithm is based on an indirect feedback information filter that fuses measurements from an inertial measurement unit (IMU) with relative 3D leg odometry measurements and relative 3D visual odometry measurements from a stereo camera. Errors of the visual odometry are computed and considered in the filtering process in order to achieve accurate pose estimates which are robust against visual odometry failure. The algorithm was successfully tested and results are presented.
Determination of electron orbital magnetic moments in carbon nanotubes

The remarkable transport properties of carbon nanotubes (CNTs) are determined by their unusual electronic structure. The electronic states of a carbon nanotube form one-dimensional electron and hole sub-bands, which, in general, are separated by an energy gap. States near the energy gap are predicted to have an orbital magnetic moment, µorb, that is much larger than the Bohr magneton (the magnetic moment of an electron due to its spin). This large moment is due to the motion of electrons around the circumference of the nanotube, and is thought to play a role in the magnetic susceptibility of CNTs and the magnetoresistance observed in large multiwalled CNTs. But the coupling between magnetic field and the electronic states of individual nanotubes remains to be quantified experimentally. Here we report electrical measurements of relatively small diameter (2–5 nm) individual CNTs in the presence of an axial magnetic field. We observe field-induced energy shifts of electronic states and the associated changes in sub-band structure, which enable us to confirm quantitatively the predicted values for µorb.
Data Mining Algorithms and Techniques in Mental Health: A Systematic Review

Data Mining in medicine is an emerging field of great importance to provide a prognosis and deeper understanding of disease classification, specifically in Mental Health areas. The main objective of this paper is to present a review of the existing research works in the literature, referring to the techniques and algorithms of Data Mining in Mental Health, specifically in the most prevalent diseases such as: Dementia, Alzheimer, Schizophrenia and Depression. Academic databases that were used to perform the searches are Google Scholar, IEEE Xplore, PubMed, Science Direct, Scopus and Web of Science, taking into account as date of publication the last 10 years, from 2008 to the present. Several search criteria were established such as ‘techniques’ AND ‘Data Mining’ AND ‘Mental Health’, ‘algorithms’ AND ‘Data Mining’ AND ‘dementia’ AND ‘schizophrenia’ AND ‘depression’, etc. selecting the papers of greatest interest. A total of 211 articles were found related to techniques and algorithms of Data Mining applied to the main Mental Health diseases. 72 articles have been identified as relevant works of which 32% are Alzheimer’s, 22% dementia, 24% depression, 14% schizophrenia and 8% bipolar disorders. Many of the papers show the prediction of risk factors in these diseases. From the review of the research articles analyzed, it can be said that use of Data Mining techniques applied to diseases such as dementia, schizophrenia, depression, etc. can be of great help to the clinical decision, diagnosis prediction and improve the patient’s quality of life.