Miracle-dz/UniFAR-FTUs huggingface dataset:
New connections between positivity and Parameter-Optimal Iterative Learning Control

In this paper new connections between positivity and Parameter-Optimal Iterative Learning Control (ILC) are established. It is in fact shown that if a given plant satisfies a positivity condition, there exists both a simple feedforward and feedback ILC-algorithm that gives convergent learning, and the convergence is monotonic. Furthermore, under the positivity assumption the feedback algorithm results in geometric convergence, which is a very strong property of an ILC algorithm. The convergence properties of the feedback algorithm are derived for the first time in this publication. As another new result it is shown that an important subclass of discrete-time systems can be conditioned with a simple feedback loop so that they become positive. Hence, after the conditioning, also this subclass of systems can be approached with Parameter-Optimal ILC algorithms so that monotonic convergence (geometric convergence with the feedback algorithm) is achieved. The different theoretical findings are illustrated with simulation examples, which support the theory presented in this paper.
SISa model Emotions as infectious diseases in a large social network : the

References ml#ref-list-1 http://rspb.royalsocietypublishing. org/content/early/2010/07/03/rspb.2010. 1217.full. ht This article cites 42 articles, 10 of which can be accessed free P<P Published online 7 July 2010 in advance of the print journal. Subject collections (292 articles) health and disease and epidemiology (1325 articles) behaviour Articles on similar topics can be found in the following collections Email alerting service here right-hand corner of the article or click Receive free email alerts when new articles cite this article sign up in the box at the top
The Need-Adapted Approach in psychosis: the impact of psychosis on the treatment, the psychiatrists, and other professionals

Psychosis is a challenging phenomenon for professionals. In the Need-Adapted Approach (NAA), therapy meetings constitute a deliberate effort to meet the challenges by bringing all the main parties together within a common discussion. The aims of this study are to analyze and evaluate psychiatrists’ experiences of the treatment processes in psychosis. A qualitative multiple case study approach has been used. Between August 2007 and January 2009 co-research interviews (CR-Is) and stimulated-recall interviews (STR-Is) with ten psychiatrists from three different part of Finland were videoed and transcribed verbatim. The material was analyzed using qualitative content analysis. The difficult emotions of the professionals and the critical views expressed had a prominent role. It was almost impossible to proceed with the treatment until the memories of coercive acts had been addressed. There were fewer harmful effects in outpatient than in inpatient care. If the client-centered principles of NAA were not followed, the CR-Is functioned primarily as critical evaluations of the treatment processes. The STR-Is helped the psychiatrists to find words for difficult experiences. For the sake of both practice and research, the experiences of staff in the treatment of psychosis should be taken into account. For better prediction of failure, routine measures to obtain feedback could be included in NAA.
Group Fairness in Bandit Arm Selection

We propose a novel formulation of group fairness in the contextual multi-armed bandit (CMAB) setting. In the CMAB setting a sequential decision maker must at each time step choose an arm to pull from a finite set of arms after observing some context for each of the potential arm pulls. In our model arms are partitioned into two or more sensitive groups based on some protected feature (e.g., age, race, or socio-economic status). Despite the fact that there may be differences in expected payout between the groups, we may wish to ensure some form of fairness between picking arms from the various groups. In this work we explore two definitions of fairness: equal group probability, wherein the probability of pulling an arm from any of the protected groups is the same; and proportional parity, wherein the probability of choosing an arm from a particular group is proportional to the size of that group. We provide a novel algorithm that can accommodate these notions of fairness for an arbitrary number of groups, and provide bounds on the regret for our algorithm. We then validate our algorithm using synthetic data as well as two real-world datasets for intervention settings wherein we want to allocate resources fairly across protected groups.
New rules for methylene chloride.

Background: Dogs have the second largest number of genetic diseases, after humans. Among the diseases present in dogs, progressive retinal atrophy has been reported in more than a hundred breeds. In some of them, the mutation has been identified and genetic tests have allowed the identification of carriers, thus enabling a drastic reduction in the incidence of the disease. The Finnish lapphund is a dog breed presenting late-onset progressive retinal atrophy for which the disease locus remains unknown. Results: In this study we mapped the progressive retinal atrophy locus in the Finnish lapphund using a DNA pooling approach, assuming that all affected dogs within the breed share the same identical-by descent-mutation as the cause of the disease (genetic homogeneity). Autosomal recessive inheritance was also assumed, after ruling out, from pedigree analysis, dominant and Xlinked inheritance. DNA from 12 Finnish lapphund cases was mixed in one pool, and DNA from 12 first-degree relatives of these cases was mixed to serve as the control pool. The 2 pools were tested with 133 microsatellite markers, 3 of which showed a shift towards homozygosity in the cases. Individual genotyping with these 3 markers confirmed homozygosity for the GALK1 microsatellite only (chromosome 9). Further individual genotyping with additional samples (4 cases and 59 controls) confirmed the association between this marker and the disease locus (p < 0.001). Closely related to this breed are the Swedish lapphund and the Lapponian herder for which a small number of retinal atrophy cases have been reported. Swedish lapphund cases, but not Lapponian herder cases, had the same GALK1 microsatellite genotype as Finnish lapphund cases. Conclusion: The locus for progressive rod-cone degeneration is known to be close to the GALK1 locus, on the telomeric region of chromosome 9, where the retinal atrophy locus of the Finnish lapphund has been mapped. This suggests that the disease in this breed, as well as in the Swedish lapphund, may correspond to progressive rod-cone degeneration. This would increase the number of known dog breeds having this particular form of progressive retinal atrophy. Background There are more than 350 dog breeds, each maintained as a breeding population separate from other breeds, which are collectively afflicted by more than 450 reported genetic diseases, the incidence of which varies from breed to breed [1,2]. Many of the breeds have been founded Published: 10 July 2007 BMC Veterinary Research 2007, 3:14 doi:10.1186/1746-6148-3-14 Received: 20 June 2006 Accepted: 10 July 2007 This article is available from: http://www.biomedcentral. com/1746-6148/3/14 © 2007 Aguirre-Hernández et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Network-Aware Optimization of Distributed Learning for Fog Computing

Fog computing promises to enable machine learning tasks to scale to large amounts of data by distributing processing across connected devices. Two key challenges to achieving this are (i) heterogeneity in devices’ compute resources and (ii) topology constraints on which devices can communicate. We are the first to address these challenges by developing a network-aware distributed learning optimization methodology where devices process data for a task locally and send their learnt parameters to a server for aggregation at certain time intervals. Unlike traditional federated learning frameworks, our method enables devices to offload their data processing tasks, with these decisions determined through a convex data transfer optimization problem that trades off costs associated with devices processing, offloading, and discarding data points. We analytically characterize the optimal data transfer solution for different fog network topologies, showing for example that the value of a device offloading is approximately linear in the range of computing costs in the network. Our subsequent experiments on both synthetic and real-world datasets we collect confirm that our algorithms are able to improve network resource utilization substantially without sacrificing the accuracy of the learned model.
Stress lavorativo e burnout negli infermieri: analisi del fenomeno in terapia intensiva

Introduction: work-related stress is an important issue among intensive care staff and is the basis for the development of the burnout syndrome. The characteristics of work environment and work organizational procedures are very important factors for the onset of burnout. Objective: to measure burnout levels of nursing staff by assessing how the organization of work in intensive care units with the depart-mental management model influences stress levels. Methods: administration of the Maslach Burnout Inventory questionnaire to nurses of the Intensive Care Department that work with adult patients. Results: 38 (82%) nurses participated in the study. 47.4% showed high levels of emotional exhaustion, in particular 44.7% of the interviewees reported the “perception of being exhausted at the end of the work day” while 36.8% underlined the “feeling of working too hard”. ICU nurses with less professional experience (less than 10 years) have higher levels of emotional exhaustion than their senior colleagues and a lower level of personal accomplishment. Conclusions: 35% of nurses have a medium-high burnout level and this should lead to a global reflection on the departmental admin - istration model and a call for action to improve the staff quality life inside the hospital.
Effect of Seed Coat Colour on the Seed Quality of Water Melon (Citrullus Lanatus)

Water melon is one of most cultivated vegetable fruit crop in the world. In Kenya the demand for this fruit for both local and export markets outstrips the supply. For Kenya to meet the high demand for water melon, quality seed is paramount since it guarantees high germination rate and vigor and on sequential high crop yields. However, it has been observed that water melon seeds have different seed coat colours even in the same growing season. The aim of this study was to establish to what extent seed colour affects seed viability (measured by % germination) and vigor (measured by absorption of water and electrical conductivity) of water melon (sugar baby variety). The study was conducted at University of Eldoret seed science laboratory. Seeds were obtained from the Kenya Genebank whose colour was determined using Munsell colour chart for plant tissues. Water absorption, electrical conductivity and germination percentage of seeds were determined using recommended methodologies. Complete random design was used and data collected was subjected to ANOVA and Duncan Multiple Range Test (DMRT) test at 5% level of significance using the GENSTAT version 14.2. The correlation between water absorption, germination and electrical conductivity was determined by Pearson Product moment correlation coefficient and regression analysis. It was found that water absorption, germination percentage and electrical conductivity significantly differed between the dark brown, light brown, brown and yellow seeds. Seed quality was highest for dark brown, followed by brown, light brown and finally yellow seeds. There was negative correlation between water absorbed and germination but positive correlation between water absorbed and electrical conductivity. It was concluded that seed companies should consider seed colour as one of the parameter during grading of water melon seeds. This would improve the quality of seed sold to farmers and consequently water melon yields in Kenya.
Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations

Despite the great progress made by deep neural networks in the semantic segmentation task, traditional neural network-based methods typically suffer from a shortage of large amounts of pixel-level annotations. Recent progress in few-shot semantic segmentation tackles the issue by utilizing only a few pixel-level annotated examples. However, these few-shot approaches cannot easily be applied to utilize image-level weak annotations, which can easily be obtained and considerably improve performance in the semantic segmentation task. In this paper, we advance the few-shot segmentation paradigm towards a scenario where image-level annotations are available to help the training process of a few pixel-level annotations. Specifically, we propose a new framework to learn the class prototype representation in the metric space by integrating image-level annotations. Furthermore, a soft masked average pooling strategy is designed to handle distractions in image-level annotations. Extensive empirical results on PASCAL-5i show that our method can achieve 5.1% and 8.2% increases of mIoU score for one-shot settings with pixel-level and scribble annotations, respectively.
Life After Life: The Investigation of a Phenomenon--Survival of Bodily Death

In Life After Life Raymond Moody investigates more than one hundred case studies of people who experienced "clinical death" and were subsequently revived. First published in 1975, this classic exploration of life after death started a revolution in popular attitudes about the afterlife and established Dr. Moody as the world's leading authority in the field of near-death experiences. Life after Life forever changed the way we understand both death -- and life -- selling millions of copies to a world hungry for a greater understanding of this mysterious phenomenon.The extraordinary stories presented here provide evidence that there is life after physical death, as Moody recounts the testimonies of those who have been to the "other side" and back -- all bearing striking similarities of an overwelming positive nature. These moving and inspiring accounts give us a glimpse of the peace and unconditional love that await us all.
PANDA: A Gigapixel-level Human-centric Video Dataset Supplementary Material

Currently, PANDA consists of 21 real-world large-scale scenes, as shown in Fig. 1, and the annotation details are illustrated in Tab. 1. We are continuously collecting more videos to enrich our dataset. Note that all the data was collected in public areas where photography is officially approved, and it will be published under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License [2].
Optimising the periodic distribution of gas cylinders with customers priority

This paper deals with a real-life application related to the distribution of gas cylinders to customers over a one-week horizon. Every customer should be served a pre-specified number of times during the week horizon. Customers are also characterised by a priority factor that expresses the importance of that customer to the company. Three heuristic methods have been develop based on a two-stage decomposition approach. The first stage assigns the customers to the service days and then, the second stage solves several VRPs, one for each working day. Several real-life experiments have been conducted to show that the heuristic that considers explicitly the customers priority performs well with respect to the other heuristics and also to the actual solution adopted by the company.
A Metaheuristic Approach to Optimize European Call Function with Boundary Conditions

Abstract The purpose of this paper is to investigate the pricing European call option valuation problems under the exercise price, maturity, risk-free interest rate, and the volatility function. An advance methodology, Chebyshev simulated annealing neural network (ChSANN), is enforced for the Black-Scholes (B-S) model with boundary conditions. Our scheme is stable and easy to implement on B-S equation, for arbitrary volatility and arbitrary interest rate values. Also, the comparative results demonstrate that the attained approximate solutions are converging towards the exact solution. The graphical results show that the increasing flow of the European call option as the exponential increase takes place in assets. The presented algorithm can be further applied to other financial models with certain boundary conditions. The algorithm of the method shows that the approach can also be easily employed on time-fractional B-S equation.
Molecular epidemiology of Staphyloccocus aureus colonization in the Old Order of Amish of Lancaster county, Pennsylvania, USA

SUMMARY Transmission of Staphylococcus aureus colonization in community-based populations is not well understood. We sought to describe the molecular epidemiology of S. aureus colonization in the Old Order Amish. The study was a prospective, observational study of healthy adults and their same-sex siblings who were cultured from the anterior nares twice. S. aureus isolates were characterized using spa typing. Overall, 40% (159/398) of the study population was colonized with S. aureus. There were 84 spa types with the most abundant spa types being t012 (13%) and t021 (7%). There was no clustering of spa types within sibling groups; however, there was clustering within households. There were 111 S. aureus-colonized participant pairs living within the same household. Of these, 47% had concordant spa types. The diversity of spa types across a relatively isolated, genetically homogenous population with a similar lifestyle is striking. Taken together this suggests that S. aureus transmission is a local phenomenon limited to very close contact.
Cosmic Microwave Background Anisotropies from the Rees-Sciama Effect in Omega 0 <=1 Universes

We investigate the imprint of nonlinear matter condensations on the Cosmic Microwave Background (CMB) in $\Omega_{0}<1$ cold dark matter (CDM) model universes. We consider simulation domains ranging from $120h^{-1}$ Mpc to $360h^{-1}$ Mpc in size. We concentrate on the secondary temperature anisotropies induced by time varying gravitational potentials occurring after decoupling. Specifically, we investigate the importance of the Rees-Sciama effect due to: (1) intrinsic changes in the gravitational potential of forming, nonlinear structures, (2) proper motion of nonlinear structures, and (3) late time decay of gravitational potential perturbations in open universes. CMB temperature anisotropies are obtained by numerically evolving matter inhomogeneities and CMB photons from an early, linear epoch ($z=100$) to the present, nonlinear epoch $(z=0)$. We test the dependence and relative importance of these secondary temperature anisotropies as a function of the scale of the underlying matter (voids, superclusters) and as a function of $\Omega_{0}$. The results of the $\Omega_{0}<1$ models are compared to a similarly executed $\Omega_{0}=1.0$ simulation. We find that in low density models all three sources of anisotropy could be relevant and reach levels of $\Delta T/T \sim 10^{-6}$. In particular, we find that for $\Omega_{0}<1$ at large scales, secondary temperature anisotropies are dominated by the decaying potential.
User Behavior , Social Networking , and Playing Style in Online and Face to Face Bridge Communities

Online social games are Internet-based games that use the social networks formed by players to extend in-game functionality. For example, gamers participating in the BBO Fans community combine online bridge play with social networking. Despite an increase in online social gaming’s popularity–currently, there exist over one million online bridge players–, and of decades of research on social networks, the activity characteristics and the community structure of online social gaming remain relatively unknown. In this work we investigate and contrast these aspects for two bridge communities, BBO Fans (online) and Locomotiva (face to face). We propose the use of playing relationships instead of traditional social relationships such as friends and friends-of-friends. Using long-term, large-scale data we have collected from both the online and face to face bridge communities, we analyze user behavior, social network structure, and playing style in bridge communities. We find many similar characteristics in the two studied communities. Surprisingly, we also find more variation in the activity levels and fewer stable partnerships for the face to face bridge community. Wp 1 http://www.pds. ewi.tudelft. nl/∼iosup/ M. Balint et al. Wp Analysis of Online and Face to Face Bridge CommunitiesWp PDS
Passive sensing data predicts stress in university students: A supervised machine learning method for digital phenotyping

University students are particularly susceptible to developing high levels of stress, which occur when environmental demands outweigh an individual's ability to cope. The growing advent of mental health smartphone apps has led to a surge in use by university students seeking ways to help them cope with stress. Use of these apps has afforded researchers the unique ability to collect extensive amounts of passive sensing data including GPS and step detection. Despite this, little is known about the relationship between passive sensing data and stress. Further, there are no established methodologies or tools to predict stress from passive sensing data in this group. In this study, we establish a clear machine learning-based methodological pipeline for processing passive sensing data and extracting features that may be relevant in the context of mental health. We then use this methodology to determine the relationship between passive sensing data and stress in university students. In doing so, we offer the first proof-of-principle data for the utility of our methodological pipeline and highlight that passive sensing data can indeed digitally phenotype stress in university students.
AN EFFICIENT ALGORITHM FOR THINNING OF IMAGES

Thinning is an important step in image processing where we minimize (reduces) the width of the image i.e. the no. of pixels that helps in reducing the memory usage. This paper proposes a new algorithm for thinning of images and helps minimizing its size. The newly proposed algorithm preserves the connectivity of the image pattern and provides a reduced image after processing the given image. The algorithm is composed of three passes to get thinned image that is connected, reduced and gives clear view of whole image.
Estimating realistic speech levels for virtual acoustic environments

Speech intelligibility is commonly assessed in rather unrealistic acoustic environments at negative signal-to-noise ratios (SNRs). As a consequence, the results seem unlikely to reflect the subjects’ experience in the real world. To improve the ecological validity of speech tests, different sound reproduction techniques have been used by researchers to recreate field-recorded acoustic environments in the laboratory. Whereas the real-world sound pressure levels of these environments are usually known, this is not necessarily the case for the level of the target speech (and therefore the SNR). In this study, a two-talker conversation task is used to derive realistic target speech levels for given virtual acoustic environments. The talkers communicate with each other while listening to binaural recordings of the environments using highly open headphones. During the conversation their speech is recorded using close-talk microphones. Conversations between ten pairs of young normal-hearing talkers were recorded.