Miracle-dz/UniFAR-FTUs huggingface dataset:
Family functioning among adolescents with narcolepsy.

Background Narcolepsy is a sleep disorder with no cure with onset typically during adolescence. Caring for an adolescent with a lifelong medical condition can negatively impact family structure, cohesion, relationships, and overall functioning. The primary objective of this study was to evaluate family functioning in a cohort of adolescents with narcolepsy using the PedsQL Family Impact Module. The secondary objective was to compare family functioning in adolescents with narcolepsy to adolescents with chronic pain based on published data. Methods This was a cross-sectional study of adolescents (aged 10 to 18 years) with narcolepsy. The narcolepsy group was recruited from The Hospital for Sick Children in Toronto, Canada. Family functioning was assessed by the PedsQL family impact module total scores, which was completed by the patient's caregiver. The PedsQL family impact module yields a total scale which encompasses parent health-related quality of life, daily activities, family relationships, communication, and worry subscales. Lower scores suggest poorer family functioning. Secondary data analyses were used to compare participants' family functioning to a cohort of adolescents with chronic pain. Results Thirty adolescents with narcolepsy participated (mean age=13.8 ± 2.2 years, 76.7% male). Family functioning was impaired in this cohort of adolescents with narcolepsy and similar to adolescents with chronic pain (64.0 ± 19.8 versus 64.7 ± 19.5; P=0.849). Conclusion Family functioning is impaired in adolescents with narcolepsy. Clinical teams should assess family functioning at routine clinic visits by asking about concerns and challenges related to caring for an adolescent with narcolepsy and providing resources and support as needed.
Subsurface Stratification and Aquifer Characterization of Federal College of Education (Technical), Gusauusing Geoelectric Method

Abstract: The determination of subsurface stratification and aquifer characterization were carried out at Federal College of Education (Technical), Gusau using the Schlumberger electrical resistivity array with maximum current electrode separation of 200m. Twenty four Vertical electrical soundings (VES) were conducted along six profiles.WinGlink software has been used in interpreting the results. Two and three subsurface layers exist in the study area. The topmost geoelectric layer has resistivity mostly within the range of 1-522 . The lithology of the topsoil is mainly clay to sandy clay. The topsoil thickness ranges from 0.40 to 4.0 m while the overburden thickness of the surveyed area ranges from 0.40 to 18.0 m. The aquifer thickness of the study area ranges from 1.00 to 19.32m. The interpreted results suggest that the main aquifer in the area appears to be the weathered and fractured basements. Productive boreholes can be located around VES 3, 10, 16 and 17. The stratification of the survey revealed mainly clay, sandy clay, weathered and fractured sand which show the formation characterization obtained through interpretation of VES curves and this corroborate with the borehole log of the area.
Modelling wildlife species abundance using automated detections from drone surveillance

Reliable estimates of abundance are critical to the conservation of threatened species. Aerial surveying is a sampling method that has been used to estimate wildlife abundance over large or inaccessible areas. An increasing trend in aerial surveying methodology is to use remotely piloted aircraft systems (RPAS), also known as drones, in lieu of traditional manned aircraft systems such as planes and helicopters. Studies which used RPAS instead of manned aircraft have recently attempted to analyse imagery using automated detection methods. While there are a number of advantages to this approach, there are also potential issues in abundance estimation using this data since the errors associated with using these approaches are largely unaccounted for in established models of abundance estimation. In this paper we applied a model developed by Terletzky and Koons (2016) for fixed wing survey, to data derived from RPAS surveys that has been processed by an automated detection method for koalas. The data collected enabled ground-truthing of detections which allowed both the probability of detection and the probability of duplicate detection to be accounted for in abundance estimates, as well as a comparison between the estimates and the true number of koalas present on site. Overall, it was found that the Terletzky & Koons (2016) method resulted in artificial inflation of abundance estimates when using data collected from RPAS surveys with automated detection. This is likely to have resulted from false positive detections, which can have a considerable impact on the accuracy of automated wildlife counts. Incorporating more sources of error than the probability of detection and duplicate detection appears to be essential to improving abundance estimation for these novel survey methods. An exploration of additional covariates that could affect detection in RPAS-derived thermal imaging due the unique constraints of these technologies should be considered in future model development.
Reverse Control for Humanoid Robot Task Recognition

Efficient methods to perform motion recognition have been developed using statistical tools. Those methods rely on primitive learning in a suitable space, for example, the latent space of the joint angle and/or adequate task spaces. Learned primitives are often sequential: A motion is segmented according to the time axis. When working with a humanoid robot, a motion can be decomposed into parallel subtasks. For example, in a waiter scenario, the robot has to keep some plates horizontal with one of its arms while placing a plate on the table with its free hand. Recognition can thus not be limited to one task per consecutive segment of time. The method presented in this paper takes advantage of the knowledge of what tasks the robot is able to do and how the motion is generated from this set of known controllers, to perform a reverse engineering of an observed motion. This analysis is intended to recognize parallel tasks that have been used to generate a motion. The method relies on the task-function formalism and the projection operation into the null space of a task to decouple the controllers. The approach is successfully applied on a real robot to disambiguate motion in different scenarios where two motions look similar but have different purposes.
The genomic landscape of Legionella pneumophila

In 2016 Sydney was the epicentre of several outbreaks of legionellosis that spanned three geographical regions, the CBD, Kogarah and Burwood [1]. The CBD was affected twice, once during March 2016 (named the CBD March period) and then from 28 of April to the 11 of May 2016 (named the CBD May period). For the CBD March period, five towers were found to be Legionella pneumophila serogroup 1 (Lp1) positive and despite the cleaning of these towers, legionellosis returned in late April (CBD May period). The aplication of whole genome sequencing (WGS) on Lp1 isolates obtained in the CBD March period revealed that several patients were infected with the same strain of Lp1. Further, the L. pneumophila sequence based typing scheme (SBT) labelled the dominant Lp1 strain as ST211 [2]. When cases of Legionellosis were detected in the CBD May period that were also ST211, WGS was used on isolates from newly sampled towers and the environmental source of the Lp1 was found.
Dictionary learning for M/EEG multidimensional data

Signals obtained from magneto- or electroencephalography (M/EEG) are very noisy and inherently multi-dimensional, i.e. provide a vector of measurements at each single time instant. To cope with noise, researchers traditionally acquire measurements over multiple repetitions (trials) and average them to classify various patterns of activity. This is not optimal because of trial-to-trial variability (waveform variation, jitters). The jitter-adaptive dictionary learning method (JADL) has been developed to better handle for this variability (with a particular emphasis on jitters). JADL is a data-driven method that learns a dictionary (prototype pieces) from a set of signals, but is currently limited to a single channel, which restricts its capacity to work with very noisy data such as M/EEG. We propose an extension to the jitter-adaptive dictionary learning method, that is able to handle multidimensional measurements such as M/EEG.
The Impact of Self-Efficacy and Work Engagement on Healthcare Professionals’ Proactive Behavior

Job crafting (JC) is a form of proactive behavior and refers to the initiatives employees that could take to change their tasks or other job characteristics to achieve the best person-job fit. JC consists of six dimensions: seeking structural and social job resources, as well as challenges, hindering job demands, optimizing job demands, and delegating tasks. The aim of the present study was to explore the impact of self-efficacy and work engagement on healthcare professionals’ (HP) proactive behavior. A convenience sample of 295 HP working in Primary and Secondary healthcare structures of Northern Greece completed a questionnaire that included: 1) demographic/occupational characteristics, 2) the Job Crafting Scale, 3) the Generalized Self-Efficacy Scale (GSE) and 4) the Utrecht Work Engagement Scale (UWES). Increased age was found to be associated with decreased levels of seeking social job resources (p < 0.01). Education level was positively associated with increased levels of seeking structural job resources (p < 0.01), seeking challenges (p < 0.05), and optimizing job demands (p < 0.05), while job position was found to be negatively related to delegating tasks (p < 0.01). Self-efficacy was positively associated with increased levels of seeking structural resources (p < 0.001), challenges (p < 0.001), and increased levels of optimizing job demands (p < 0.001), while it was positively associated with decreased levels of delegating tasks (p < 0.05). In addition, increased work engagement was found to be associated with increased levels of seeking social job resources (p < 0.05), challenges (p < 0.01), and optimizing job demands (p < 0.01). Findings highlight the importance of self-efficacy, work engagement and individual characteristics in the realization of a resourceful work environment and HP’ adjustment in the organization. Thus, interventions that promote HP’ JC proactive behaviors should be encouraged.
WiHRR: CSI based English Alphabet Handwriting Recognition

Human Computer Interaction has been an important and vital subject of research since last few years and new and innovative techniques are being implemented in this field with each passing day. This research paper tries to improve existing samples of Channel frequency Response (CFR) that is obtained from Wi-Fi devices in the form of channel state information (CSI). In this research article, handwriting is used as an input but character recognition is not done on the paper but in the air.It discusses all the important procedures which are undertaken to accomplish this task which include fetching the input, pre-processing , feature extraction and classification of characters using machine learning algorithms.Current wireless devices can measure the interference caused by handwritten English alphabet in the range of signal coverage during the transmission of wireless signals in their own channels, and these measured interference s can be applied to handwritten recognition. Compared with traditional behavior recognition using cameras or wearable sensor devices, handwritten recognition using Wi-Fi wireless signals has more unexpected benefits: first, the wireless signals do not need LOS (line of sight) monitoring; second, no need to wear redundant sensor devices; and, at the same time, no need to wear redundant sensor devices. Wireless signals can be deployed in various scenarios without dead corners, such as home, office, public area and so on. Compared with the camera, the behavior recognition based on wireless signal is not affected by the weather.
A Survey on Different Techniques for Covert Communication Using Steganography

: With digitization, data hiding has become more important than ever. Steganography forms an undisputable tool to attain privacy during data sharing. Steganography is the art and science of hiding data within seemingly innocuous data so as to not draw suspicion. This paper provides a survey on steganography, its advantage over cryptography, the types of digital media over which steganography can be applied and the progress of steganographic methods and recent trends in steganography. Images, video, text, audio are the digital media which serve as cover-media through which secret data may be transmitted often by exchanging stego-key.
Optimal Placement of Retry-Based Fault Recovery Annotations in HPC Applications ∗

As larger HPC systems are built, fault recovery becomes a fundamental capability. Traditional fault recovery approaches, such as checkpointing, may not be suﬃcient for future exascale systems. Retry-based recovery techniques have been proposed as an alternative. These techniques simply re-execute a code region when a fault occurs and require code annotations. However, no previous work has investigated the optimal placement of these annotations in a program. Via fault injection, we evaluate how to place optimally retry annotations in a hydrodynamics mini application. We found that, contrary to our expectations, a simple scheme of protecting the main function works well for low fault rates: slowdown is up to 1.25 for a 3 faults/hour rate. We also found that the optimal recovery method is rolling a few iterations back in the application’s main loop.
Porter's Five Forces Model Competition as a Framework for Determining the Competitive Strategy of State University

This study aims to evaluate organizational performance in order to improve competitiveness. This research is a case study at Universitas Negeri Medan, Indonesia. Data collection was carried out by analyzing performance in services, organizations and human resources, finance, and infrastructure. Data was collected from the management level of universities, faculties, and bureaus. Data were analyzed using SWOT analysis, which integrated the Porter's Five Forces Model Competition. The results showed that the margin on the strength component was 1.165, weakness was 0.069, the opportunity was 0.220, and the threat component was 0.195. It was concluded that the position of Unimed’s competitiveness was in a position ready to grow and develop and support an aggressive strategy. The strategies used as alternatives to improve Unimed's competitiveness are improving the quality of human resources, improving the quality of study programs, increasing research and innovation, increase the relevance of graduates, and increase vocational education.
Meanings of Flora and Fauna Related Ecolexicon in the Karonese Proverbs

This article aims at finding out the meanings of flora and fauna related ecolexicon used in the Karonese proverbs. This is a descriptive qualitative study using ecolexicon used in the Karonese proverbs as the data. The data were collected using interviews involving seven informants who were native Karonese living in Kabanjahe with the predetermined criteria. The interviews were followed by the elicitation technique. The data were analyzed using an interactive model of data analysis. The results of data analysis show that ecolexical items related to flora and fauna were found in the Karonese proverbs. The choice of such ecolexicon completely depends on the availability of the plants and animals in the local environment. In conclusion, the Karonese proverbs utilizing flora and fauna related lexicon used in Kabanjahe have the following functions: (i) as the advice, (ii) as the warning, and (iii) as the reflection of the Karonese traditional culture.
Computational Drug Simulation: A Step to the Possible Cure of COVID-19

World Health Organization declared COVID-19 as a pandemic on 11th March,2020. Without any exact cure or vaccine, this disease has certainly taken a toll of humanity. Computer-aided Drug Design (CADD) is the modern era simulator for aiding in finding cure before starting actual clinical trials in patients. We have not indulged into making a new drug but analysing the existing drugs as approved by FDA to find the possible cure options. Based on the above data from our study, we find that anti-inflammatory drugs like prednisone and anti-psychotic drugs can be used for targeting the spike glycoprotein of the SARS-CoV2 virus.
Supplementary information: The role of topological defects in the two-stage melting and elastic behaviour of active Brownian particles

where r = |rij | is the distance between the centers of particle i and j, σ is the particle diameter pertaining to the length scale in WCA potential, and ε is the strength of the particle interactions. We set the system temperature kBT/ε = 1, following Ref. [1], and the damping coefficient γσ /ε = 1 fixing the translational diffusion coefficient to correspond to the free diffusion of particles given by the Stokes-Einstein relation Dt = γ −1kBT . This sets our time scale as τ = γσ/kBT . The rotational diffusion coefficient is set to Drτ = 3 and we use a time step size dt = 10−5τ for numerically integrating the equations of motion. We define a non-dimensional Péclet number Pe = v0τ/σ as the ratio of the persistence length of motion to the particle diameter and perform simulations using the HOOMD-Blue [2, 3] package in the range 0 ≤ Pe ≤ 150. We used N = 72× 10 particles in an approximately square 2D periodic simulation box with dimensions Lx, Ly ≈ 250σ for identifying the fluid-hexatic-solid transitions and N = 2.8× 10 for calculating the elastic moduli. We used a regular hexagonally packed arrangement of particles at the overall system density as our initial configuration and we collect snapshots for 200τ − 500τ at an interval of τ for analysis after allowing the system to achieve a stationary state for about 200τ . As mentioned in the main text, the state diagram shown in Fig. 1 was obtained by measuring the equation of state (pressure-density curves), the density histograms, the decay of the orientational and positional correlation functions to locate the boundaries as precisely as possible. Specifically, to locate the coexistence, we identified negative slope regions in the pressure-density curves as well as double-peaked structure of the density histograms similar to the analysis presented in Ref. [4] and Ref. [5]. We describe below the orientational and positional order parameters used for identifying the hexatic and solid phases.
Manipulating Users' Trust on Amazon Echo: Compromising Smart Home from Outside

Nowadays, voice control becomes a popular application that allows people to communicate with their devices more conveniently. Amazon Echo, designed around Alexa, is capable of controlling devices, e.g., smart lights, etc. Moreover, with the help of IFTTT (if-this-then-that) service, Amazon Echo’s skill set gets improved significantly. However, people who are enjoying these conveniences may not take security into account. Hence, it becomes important to carefully scrutinize the Echo’s voice control attack surface and the corresponding impacts. In this paper, we proposed MUTAE (Manipulating Users’ Trust on Amazon Echo) attack to remotely compromise Echo’s voice control interface. We also conducted security analysis and performed taxonomy based on different consequences considering the level of trust that users have placed on Echo. Finally, we also proposed mitigation techniques that protect Echo from MUTAE attack. Received on 29 March 2020; accepted on 02 April 2020; published on 07 April 2020
Aldosterone deficiency prevents high-fat-feeding-induced hyperglycaemia and adipocyte dysfunction in mice

© Springer-Verlag Berlin Heidelberg 2013 Correspondence to: J. M. Luther, James.Luther@Vanderbilt.edu. Duality of interest All other authors report that there is no duality of interest associated with this manuscript. Contribution statement All authors contributed to experimental design, researched data, wrote the manuscript, contributed to discussion, and approved the final version. JML is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. NIH Public Access Author Manuscript Diabetologia. Author manuscript; available in PMC 2014 April 01. Published in final edited form as: Diabetologia. 2013 April ; 56(4): 901–910. doi:10.1007/s00125-012-2814-8. N IH PA Athor M anscript N IH PA Athor M anscript N IH PA Athor M anscript Aims/hypothesis—Obesity is associated with aldosterone excess, hypertension and the metabolic syndrome, but the relative contribution of aldosterone to obesity-related complications is debated. We previously demonstrated that aldosterone impairs insulin secretion, and that genetic aldosterone deficiency increases glucose-stimulated insulin secretion in vivo. We hypothesised that elimination of endogenous aldosterone would prevent obesity-induced insulin resistance and hyperglycaemia. Methods—Wild-type and aldosterone synthase-deficient (As−/−) mice were fed a high-fat (HF) or normal chow diet for 12 weeks. We assessed insulin sensitivity and insulin secretion using clamp methodology and circulating plasma adipokines, and examined adipose tissue via histology. Results—HF diet induced weight gain similarly in the two groups, but As−/− mice were protected from blood glucose elevation. HF diet impaired insulin sensitivity similarly in As−/− and wild-type mice, assessed by hyperinsulinaemic–euglycaemic clamps. Fasting and glucosestimulated insulin were higher in HF-fed As−/− mice than in wild-type controls. Although there was no difference in insulin sensitivity during HF feeding in As−/− mice compared with wild-type controls, fat mass, adipocyte size and adiponectin increased, while adipose macrophage infiltration decreased. HF feeding significantly increased hepatic steatosis and triacylglycerol content in wildtype mice, which was attenuated in aldosterone-deficient mice. Conclusions/interpretation—These studies demonstrate that obesity induces insulin resistance independently of aldosterone and adipose tissue inflammation, and suggest a novel role for aldosterone in promoting obesity-induced beta cell dysfunction, hepatic steatosis and adipose tissue inflammation.