Miracle-dz/UniFAR-FTUs huggingface dataset:
Information Epidemics in Complex Networks with Opportunistic Links and Dynamic Topology

Wireless networks, especially mobile ad hoc networks (MANET) and cognitive radio networks (CRN), are facing two new challenges beyond traditional random network model: opportunistic links with random nature due to fading and dynamic channel access, and dynamic network topology due to mobility and time varying. For a more general networking of Internet users as social complex networks, such challenges of further importance remain open. A generic and reliable model is therefore required to capture the information dissemination dynamics (IDD) of machine- to-machine communications or interactions in relation-based social networks. Inspired from epidemiology, we investigate the IDD in well-known complex networks by modified Susceptible-Infected (SI) model, which is surprisingly suitable for above multiple scenarios. Systematically categorizing such networks and examining conditions to adopt SI model for IDD in complex networks, the fundamental properties including mixing type, vertex connectivity and giant component size provide valid insights for quantitative analysis. We also investigate the IDD in networks with time-varying topology and show that all individuals receive the information in dynamic sense, even if the giant component size is not compatible with the number of individuals in static sense. Consequently, we successfully establish such analytical model for characterizing the IDD in complex networks consisting of opportunistic links and time-varying topology, feasible for various random wireless networks and social networks.
Development of the hypothalamus: conservation, modification and innovation

The hypothalamus, which regulates fundamental aspects of physiological homeostasis and behavior, is a brain region that exhibits highly conserved anatomy across vertebrate species. Its development involves conserved basic mechanisms of induction and patterning, combined with a more plastic process of neuronal fate specification, to produce brain circuits that mediate physiology and behavior according to the needs of each species. Here, we review the factors involved in the induction, patterning and neuronal differentiation of the hypothalamus, highlighting recent evidence that illustrates how changes in Wnt/β-catenin signaling during development may lead to species-specific form and function of this important brain structure. Summary: This Review discusses the factors involved in hypothalamic induction, patterning and differentiation, highlighting how changes in Wnt signaling may lead to species-specific hypothalamic form and function.
Survey on Social-Aware Data Dissemination Over Mobile Wireless Networks

Data dissemination finds a wide range of appealing applications in disaster alert, event notification, and content distribution. In particular, with the evolution of mobile networks and the popularity of online social networks, mobile social networks (MSNs) offer a promising paradigm to facilitate data dissemination. Traditional data dissemination approaches focus on how to leverage the resources in the physical networks, such as opportunistic contacts in delay tolerant networks and opportunistic networks, or the infrastructure in the cellular networks. In contrast, social-aware data dissemination approaches also exploit the valuable information from the social networks and take into consideration the complex requirements of human users. A systematic review of the existing approaches for data dissemination can provide insightful information and motivate more in-depth studies in this area. In this paper, we first review some traditional approaches as a basis for comparison. Then, we introduce some fundamental background on MSNs, device-to-device (D2D) communication, game theory, and matching theory, which have been used in existing studies on social-aware data dissemination. The technical and mathematical information is helpful for readers to follow our discussions in the main body of this paper, which surveys many social-aware approaches in the literature. We group our discussions based on the theoretical models for various problems in data dissemination. Also, we separate the problems, initial source selection and incentive design, from others to emphasize their importance. In the end, we highlight some interesting research directions for future study on data dissemination.
Vehicle Fault Tolerant Control Using a Robust Output Fuzzy Controller Design

Modern life depends increasingly on the availability at all times of services and products provided by technological systems. Many areas, such as communication systems, water supply, power grids, urban transport systems are now completely automated. For such systems, the consequences of faults in component systems can be catastrophic. Reliability of such systems can be increased by ensuring that the faults will not occur, however, this objective unrealistic and often unattainable. In this context, it is very useful to design fault tolerant control systems that are able to tolerate possible faults in such systems to improve reliability and availability. Together with the increasing complexity of engineered systems and rising demands regarding reliability and safety, it is important to develop powerful fault-tolerant control methods.
On the implementation of huge random objects

We initiate a general study of pseudo-random implementations of huge random objects, and apply it to a few areas in which random objects occur naturally. For example, a random object being considered may be a random connected graph, a random bounded-degree graph, or a random error-correcting code with good distance. A pseudo-random implementation of such type T objects must generate objects of type T that can not be distinguished from random ones, rather than objects that can not be distinguished from type T objects (although they are not type T at all). We will model a type T object as a function and access objects by queries into these functions. We investigate supporting both standard queries that only evaluates the primary function at locations of the user's choice (e.g., edge queries in a graph), and complex queries that may ask for the result of a computation on the primary function, where this computation is infeasible to perform with a polynomial number of standard queries (e.g., providing the next vertex along a Hamiltonian path in the graph).
Risk assessment of readmissions following an initial COPD-related hospitalization

Background Acute exacerbation of chronic obstructive pulmonary disease (COPD) is a leading cause of hospitalizations and readmissions in the US. Reducing the frequency of hospital readmission is a high priority of US health care organizations and government agencies. This study evaluated the risk factors associated with readmissions among commercially insured adults aged 40–65 years in the US who were hospitalized for COPD. Methods This retrospective cohort study used anonymized claims data from the Truven Health MarketScan® Commercial Claims and Encounters database. The patients included were aged 40–65 years, had an index hospitalization with a primary diagnosis of COPD between July 1, 2008 and June 30, 2010 (continuously enrolled 12 months before and after), and were alive at hospital discharge. Patients with cystic fibrosis or tuberculosis or who were transferred to another inpatient facility after hospital discharge were excluded. All readmissions regardless of diagnosis, and separately a subset of all readmissions that had COPD as a primary or secondary diagnosis (COPD-related), were examined. Univariate descriptive statistics and multivariable regression methods were used. Results Of the 18,568 patients with index COPD hospitalizations, 6,095 (32.83%) met the eligibility criteria. Of those, 503 (8.25%) were readmitted within the first 30 days post-index hospitalization and 2,527 (41.46%) within the first year (COPD-related 340 [5.58%] and 1,681 [27.58%], respectively). The median time to the first readmission post initial discharge was 4.0 months, with a mean of 5.0 ± 3.4 months. Multivariable regression analyses showed that comorbid conditions and health care utilization in the pre-index period were significant predictors for readmission both 30 and 90 days following index hospitalization. Conclusion A relatively high readmission rate was observed for patients aged 40–65 years. The results suggest that attention to patient comorbidities and pre-index/index health care service utilization may help identify hospitalized COPD patients at higher risk for readmission.
An exploration of German and British physiotherapists' views on the effects of hippotherapy and their measurement

Hippotherapy (Greek hippos = horse) is a specialised physiotherapy treatment that makes use of the horses' unique three-dimensional movement impulses at a walk to facilitate movement responses in patients sitting on the horse's back (Strauß, ). Despite a substantial body of anecdotal and clinical evidence for its benefits, research evidence for hippotherapy is sparse. This questionnaire survey was the first study in a series of investigations exploring the views of physiotherapists and people with cerebral palsy who use hippotherapy. These investigations, in turn, form the basis from which the authors will recommend outcome measures for individuals with cerebral palsy in a hippotherapy environment. This study aimed to: (a) establish the pattern of hippotherapy practice in Germany and the U.K.; (b) examine the perceived main effects of hippotherapy on people with cerebral palsy in Germany and the U.K.; and (c) investigate how these effects are being measured in both countries. The results highlighted considerable differences in how hippotherapy is practised in the U.K. compared with in Germany. In spite of this, the study revealed agreement among respondents on the overall perceived effects of hippotherapy on individuals with cerebral palsy, namely, the regulation of muscle tone, improvement of postural control and psychological benefits. The results also indicate scant use of outcome measures to evaluate these effects. The impact of these findings is discussed in the light of published research, and suggestions for further research are made.
Within-class covariance normalization for SVM-based speaker recognition

This paper extends the within-class covariance normalization (WCCN) technique described in [1, 2] for training generalized linear kernels. We describe a practical procedure for applying WCCN to an SVM-based speaker recognition system where the input feature vectors reside in a high-dimensional space. Our approach involves using principal component analysis (PCA) to split the original feature space into two subspaces: a low-dimensional “PCA space” and a high-dimensional “PCA-complement space. ” After performing WCCN in the PCA space, we concatenate the resulting feature vectors with a weighted version of their PCAcomplements. When applied to a state-of-the-art MLLR-SVM speaker recognition system, this approach achieves improvements of up to 22% in EER and 28% in minimum decision cost function (DCF) over our previous baseline. We also achieve substantial improvements over an MLLR-SVM system that performs WCCN in the PCA space but discards the PCA-complement.
A Software Reliability GEP Model Based on Usage Profile

In this paper, software reliability measurement is studied from the perspective of usage profile. Reliability parameters on each usage profile are expressed with unascertained rational numbers. Since failure process of each usage profile can be affected by multiple factors such as software attributes and users imports etc., GEP (gene expression programming) is introduced into software reliability modeling, to study comprehensive force among the factors. Finally, a software reliability GEP model based on usage profile is constructed. With the new model, users can confirm software reliability according to its usage, thus enabling software reliability to a more objective assessment. The new model is experimented to measure reliability of SYS in Musa data, and proved with a satisfactory performance. DOI: http://dx.doi. org/10.11591/telkomnika.v10i7. 1572 Full Text: PDF
Beyond the MOOC platform: gaining insights about learners from the social web

Massive Open Online Courses (MOOCs) have enabled millions of learners across the globe to increase their levels of expertise in a wide variety of subjects. Research efforts surrounding MOOCs are typically focused on improving the learning experience, as the current retention rates (less than 7% of registered learners complete a MOOC) show a large gap between vision and reality in MOOC learning. Current data-driven approaches to MOOC adaptations rely on data traces learners generate within a MOOC platform such as edX or Coursera. As a MOOC typically lasts between five and eight weeks and with many MOOC learners being rather passive consumers of the learning material, this exclusive use of MOOC platform data traces limits the insights that can be gained from them. The Social Web potentially offers a rich source of data to supplement the MOOC platform data traces, as many learners are also likely to be active on one or more Social Web platforms. In this work, we present a first exploratory analysis of the Social Web platforms MOOC learners are active on --- we consider more than 320,000 learners that registered for 18 MOOCs on the edX platform and explore their user profiles and activities on StackExchange, GitHub, Twitter and LinkedIn.
Coma Prognosis in Children: Part I: Definitional and Methodological Challenges

Summary Prediction of outcome from coma is a frequent and important task of neurologists. It is difficult enough in adult patients and even more difficult in children. Part I of this review considers some of the methodological problems and caveats besetting clinical research in this field: the very definition of coma, definition of the study population and outcome variables, study design, the fallacy of self-fulfilling prophecy, early death rate from nonneurologic causes resulting in low statistical power, and invalid attempts to compensate for that by combining outcome categories, lumping together age groups, short and inhomogeneous follow-up, and failure to provide confidence intervals. Part II reviews the clinical pediatric coma-prognosis literature, first according to etiology and then according to electrodiagnostic tests.
Peptide Inhibition of Topoisomerase IB from Plasmodium falciparum

Control of diseases inflicted by protozoan parasites such as Leishmania, Trypanosoma, and Plasmodium, which pose a serious threat to human health worldwide, depends on a rather small number of antiparasite drugs, of which many are toxic and/or inefficient. Moreover, the increasing occurrence of drug-resistant parasites emphasizes the need for new and effective antiprotozoan drugs. In the current study, we describe a synthetic peptide, WRWYCRCK, with inhibitory effect on the essential enzyme topoisomerase I from the malaria-causing parasite Plasmodium falciparum. The peptide inhibits specifically the transition from noncovalent to covalent DNA binding of P. falciparum topoisomerase I, while it does not affect the ligation step of catalysis. A mechanistic explanation for this inhibition is provided by molecular docking analyses. Taken together the presented results suggest that synthetic peptides may represent a new class of potential antiprotozoan drugs.
Hs3d, A Dataset Of Homo Sapiens Splice Regions, And Its Extraction Procedure From A Major Public Database

The aim of this work is to describe a cleaning procedure of GenBank data, producing material to train and to assess the prediction accuracy of computational approaches for gene characterization. A procedure (GenBank2HS3D) has been defined, producing a dataset (HS3D — Homo Sapiens Splice Sites Dataset) of Homo Sapiens Splice regions extracted from GenBank (Rel.123 at this time). It selects, from the complete GenBank Primate Division, entries of Human Nuclear DNA according with several assessed criteria; then it extracts exons and introns from these entries (actually 4523 + 3802). Donor and acceptor sites are then extracted as windows of 140 nucleotides around each splice site (3799 + 3799). After discarding windows not including canonical GT–AG junctions (65 + 74), including insufficient data (not enough material for a 140 nucleotide window) (686 + 589), including not AGCT bases (29 + 30), and redundant (218 + 226), the remaining windows (2796 + 2880) are reported in the dataset. Finally, windows of false splice sites are selected by searching canonical GT–AG pairs in not splicing positions (271 937 + 332 296). The false sites in a range +/- 60 from a true splice site are marked as proximal. HS3D, release 1.2 at this time, is available at the Web server of the University of Sannio: .
Real-Time, Multi-Perspective Perception for Unmanned Ground Vehicles

The most challenging technical problems facing successful autonomous UGV operation in off-road environments are reliable sensing and perception. In this paper, we describe our progress over the last year toward solving these problems in Phase II of DARPA’s PerceptOR program. We have developed a perception system that combines laser, camera, and proprioceptive sensing elements on both ground and air platforms to detect and avoid obstacles in natural terrain environments. The perception system has been rigorously tested in a variety of environments and has improved over time as problems have been identified and systematically solved. The paper describes the perception system and the autonomous vehicles, presents results from some experiments, and summarizes the current capabilities and limitations.
Which Thousand Words are Worth a Picture? Experiments on Video Retrieval using a Thousand Concepts

In contrast to traditional video retrieval that represents visual content with low-level features (e.g. color and texture), emerging concept-based video retrieval allows users to search video archives by specifying a limited number of high-level concepts (e.g. outdoors and car). Recent studies have demonstrated the feasibility of concept-based retrieval, but a fundamental question remains: what kinds of concepts should we index? We analyze a large video archive annotated with more than a thousand high-level concepts, and develop guidelines for choosing concepts of high utility to video retrieval
Rhodococcus aerolatus sp. nov., isolated from subarctic rainwater.

A Gram-stain-positive, rod-shaped and non-motile strain, designated PAMC 27367(T), was isolated from rainwater collected on the Bering Sea. Analysis of the 16S rRNA gene sequence of the strain showed an affiliation with the genus Rhodococcus. Phylogenetic analyses revealed that strain PAMC 27367(T) formed a robust clade with the type strains of Rhodococcus rhodnii, Rhodococcus aetherivorans and Rhodococcus ruber with 16S rRNA gene sequence similarities of 96.3 %, 95.8 % and 95.5 %, respectively. Cells of the strain grew optimally at 25 °C and at pH 6.5-7.0 in the presence of 0-2 % (w/v) sea salts. The major polar lipids were diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, phosphatidylinositol, phosphatidylinositol mannoside and three unknown phospholipids. The major cellular fatty acids (>10 %) were iso-C16 : 0, C17 : 1ω8c and 10-methyl C17 : 0. Cell wall analysis showed that strain PAMC 27367(T) contained meso-diaminopimelic acid. The genomic DNA G+C content was 77.1 mol%. Based on the phylogenetic, chemotaxonomic and phenotypic data presented here, we propose a novel species with the name Rhodococcus aerolatus sp. nov., with PAMC 27367(T) ( = KCTC 29240(T) = JCM 19485(T)) as the type strain.
Oxidants, antioxidants and mitochondrial function in non-proliferative diabetic retinopathy

Diabetic retinopathy (DR) is a preventable cause of visual disability. The aims of the present study were to investigate levels and behavior oxidative stress markers and mitochondrial function in non‐proliferative DR (NPDR) and to establish the correlation between the severity of NPDR and markers of oxidative stress and mitochondrial function.
Experience based Learning and Control of Robotic Grasping

Johan Tegin and Jan Wikander Mechatronics Laboratory Machine Design KTH, Stockholm, Sweden Email: johant, jan@md.kth. se Staffan Ekvall and Danica Kragic Computational Vision and Active Perception Laboratory KTH, Stockholm, Sweden Email: ekvall, danik@nada.kth. se Boyko Iliev Biologically Inspired Systems Laboratory Applied Autonomous Sensor Systems Örebro University, Örebro, Sweden Email: boyko.iliev@tech.oru. se
Cooperative Transmission Strategy over Users' Mobility for Downlink Distributed Antenna Systems

Previously, a scheme in [1] was proposed for the outdated channel state information (CSI) problem, for data transmission in time division duplex (TDD) systems. In user movement environment, the actual channel of data transmission at downlink time slot is different from the estimated channel due to channel variation. In this paper, the effect of different user mobility on TDD downlink multiuser distributed antenna system is investigated. An efficient autocorrelation based feedback interval technique is proposed and updates CSI at less the cost of the downlink time slots. In the proposed technique, the frequency of CSI feedback for different users is proportional to their speed. Cooperative clusters are formed to maximize sum rate where channel gain based antenna selection and user clustering based on signal-to- interference plus noise ratio (SINR) threshold is applied to reduce computational complexity. Numerical results show that sum rate superiority of the proposed scheme over the user mobility.
RICE: rapid interconnect circuit evaluator

This paper describes RICE, an RLC interconnect evaluation tool based upon the moment-matching technique of Asymptotic Waveform Evaluation (AWE). The RLC circuit moments are calculated by a path-tracing algorithm which enables the analysis of large interconnect models several thousand times faster than a circuit simulation while requiring 5 to 10 times less memory. RICE also includes a new approach for determining the circuit dominant time-constants which avoids the inherent instability problems associated with moment matching methods in general.
Activity Detection in Scientific Visualization

For large-scale simulations, the data sets are so massive that it is sometimes not feasible to view the data with basic visualization methods, let alone explore all time steps in detail. Automated tools are necessary for knowledge discovery, i.e., to help sift through the data and isolate specific time steps that can then be further explored. Scientists study patterns and interactions and want to know when and where interesting things happen. Activity detection, the detection of specific interactions of objects which span a limited duration of time, has been an active research area in the computer vision community. In this paper, we introduce activity detection to scientific simulations and show how it can be utilized in scientific visualization. We show how activity detection allows a scientist to model an activity and can then validate their hypothesis on the underlying processes. Three case studies are presented.
Explanation-Based Acquisition of Planning Operators

Classical planning algorithms require that their operators be simple in order for planning to be tractable. However, the complexities of real world domains suggest that, in order to be accurate, planning operators must be complex. We demonstrate how, by taking advantage of background knowledge and the distribution of planning problems encountered, it is possible to automatically construct planning operators that are both reliable and succinct. The acquired operator is an encapsulated control loop that is specialized to best fit observed world behavior. Succinctness is achieved by publishing to the planner only those conditions required to succeed over the estimated distribution of problems. We demonstrate the acquisition of a context-appropriate "take-off" operator that can successfully control a complex flight simulator.