Miracle-dz/UniFAR-FTUs huggingface dataset:
Obstructive sleep apnea detection from ECG signal using neuro-fuzzy classifier

Obstructive sleep apnea syndrome (OSAS) is a common problem defined by frequent process of breathing due to the partial or complete obstruction of upper airway for short period during sleep. This leads to serious cardiovascular and other problems or even death if not properly detected. The existing method of detection considers temporal dependency within ECG segmented signal. Here HMM and corresponding state transmission probability, observed probability and initial state probability were used to detect the condition. However the system lacks proper feature selection criteria and also fails in detecting the sleep apnea. To overcome, a T-test method has been proposed to select the feature from RR interval and QRS complex. Also to reduce the miss classification a Neuro Fuzzy detection method has been introduced. A neuro fuzzy system is a fuzzy learning that uses learning algorithm derived from neural network theory. The required ECG signal is taken from Physionet database. The artificial intelligence based detection method reduce false positive rate in analysis of sleep apnea.
CHASE: Contract-based requirement engineering for cyber-physical system design

This paper presents CHASE, a framework for requirement capture, formalization, and validation for cyber-physical systems. CHASE combines a practical front-end formal specification language based on patterns with a rigorous verification back-end based on assume-guarantee contracts. The front-end language can express temporal properties of networks using a declarative style, and supports automatic translation from natural-language constructs to low-level mathematical languages. The verification back-end leverages the mathematical formalism of contracts to reason about system requirements and determine inconsistencies and dependencies between them. CHASE features a modular and extensible software infrastructure that can support different domain-specific languages, modeling formalisms, and analysis tools. We illustrate its effectiveness on industrial design examples, including control of aircraft power distribution networks and arbitration of a mixed-criticality automotive bus.
Bisphosphonates and fractures of the subtrochanteric or diaphyseal femur.

BACKGROUND A number of recent case reports and series have identified a subgroup of atypical fractures of the femoral shaft associated with bisphosphonate use. A population-based study did not support this association. Such a relationship has not been examined in randomized trials. METHODS We performed secondary analyses using the results of three large, randomized bisphosphonate trials: the Fracture Intervention Trial (FIT), the FIT Long-Term Extension (FLEX) trial, and the Health Outcomes and Reduced Incidence with Zoledronic Acid Once Yearly (HORIZON) Pivotal Fracture Trial (PFT). We reviewed fracture records and radiographs (when available) from all hip and femur fractures to identify those below the lesser trochanter and above the distal metaphyseal flare (subtrochanteric and diaphyseal femur fractures) and to assess atypical features. We calculated the relative hazards for subtrochanteric and diaphyseal fractures for each study. RESULTS We reviewed 284 records for hip or femur fractures among 14,195 women in these trials. A total of 12 fractures in 10 patients were classified as occurring in the subtrochanteric or diaphyseal femur, a combined rate of 2.3 per 10,000 patient-years. As compared with placebo, the relative hazard was 1.03 (95% confidence interval [CI], 0.06 to 16.46) for alendronate use in the FIT trial, 1.50 (95% CI, 0.25 to 9.00) for zoledronic acid use in the HORIZON-PFT trial, and 1.33 (95% CI, 0.12 to 14.67) for continued alendronate use in the FLEX trial. Although increases in risk were not significant, confidence intervals were wide. CONCLUSIONS The occurrence of fracture of the subtrochanteric or diaphyseal femur was very rare, even among women who had been treated with bisphosphonates for as long as 10 years. There was no significant increase in risk associated with bisphosphonate use, but the study was underpowered for definitive conclusions.
Live Sketch: Video-driven Dynamic Deformation of Static Drawings

Creating sketch animations using traditional tools requires special artistic skills, and is tedious even for trained professionals. To lower the barrier for creating sketch animations, we propose a new system, emphLive Sketch,</i> which allows novice users to interactively bring static drawings to life by applying deformation-based animation effects that are extracted from video examples. Dynamic deformation is first extracted as a sparse set of moving control points from videos and then transferred to a static drawing. Our system addresses a few major technical challenges, such as motion extraction from video, video-to-sketch alignment, and many-to-one motion-driven sketch animation. While each of the sub-problems could be difficult to solve fully automatically, we present reliable solutions by combining new computational algorithms with intuitive user interactions. Our pilot study shows that our system allows both users with or without animation skills to easily add dynamic deformation to static drawings.
Human Defensins in HIV Infection: Friends or Foes?

Defensins are antimicrobial peptides (AMPs) and play an important role in both innate and adaptive immune response (Ganz, 2002; Yang et al., 2004). Defensins display broad antimicrobial activities against bacteria, fungi and viruses (Ganz, 2003; Lehrer, 2004; Zanetti, 2004),(Yang et al., 2004). Importantly, they also play a role in inflammation, tissue repair and angiogenesis (Kruse and Kristensen, 2008; Rehaume and Hancock, 2008). Increasing evidence indicates that the AMPs can act as a double-edged sword by providing protection against invading pathogens but at the same time causing potentially harmful inflammation or facilitating pathogen invasion. This review focuses on the role of human defensins in HIV infection. We will summarize the complex mechanisms by which defensins inhibit or enhance HIV infection in vitro, clinical evidence and studies in macaques with respect to the role of defensins in HIV transmission and pathogenesis.
Cataract frequency and subtypes involved in workers assessed for their solar radiation exposure: a systematic review

Cataract is currently the primary cause of blindness worldwide, and one of its main risk factors is solar ultraviolet radiation exposure. According to the localization of lens opacities, three main subtypes of cataract are recognized: nuclear, cortical and posterior subcapsular cataract. One of the main determinants of individual long‐term solar radiation exposure is outdoor work. We systematically reviewed scientific literature from the last 20 years to update the recent development of research on the risk of cataract in outdoor workers and on the specific subtypes involved, also investigating the methods applied to evaluate the occupational risk. A total of 15 studies were included in the review, of which 12 showed a positive association. The studies confirm the relationship of long‐term occupational solar radiation exposure with cortical cataract and give new support for nuclear cataract, although no substantial new data were available to support a relation with the posterior subcapsular subtype. In most of the studies, the exposure assessment was not adequate to support a representative evaluation of the ocular risk; however, outdoor work is clearly a relevant risk factor for cataract. Further research providing a better evaluation of the relation between solar radiation exposure levels and lens damage in workers is needed and aimed to establish adequate occupational exposure limits and better preventive measures, studying also their effectiveness.
A Signaling Mechanism from Gαq-Protein-Coupled Metabotropic Glutamate Receptors to Gene Expression: Role of the c-Jun N-Terminal Kinase Pathway

Gαq-protein-coupled group I metabotropic glutamate receptors (mGluRs) are densely expressed in brain neurons and are actively involved in various cellular activities. In this study, we investigated the role of group I mGluRs in regulating the c-Jun N-terminal kinase (JNK)/stress-activated protein kinase in cultured neurons. We found that selective activation of mGluR5 induced a rapid and transient phosphorylation of JNK. In a series of studies to determine the mechanisms, we found that the conventional mGluR5-associated signaling pathways (inositol-1,4,5-triphosphate-mediated Ca2+ release and activation of protein kinase C) were not involved in the mGluR5 regulation. Instead, ligand stimulation of mGluR5 caused a dynamic transactivation of the epidermal growth factor (EGF) receptor, which in turn triggered a downstream signaling pathway to upregulate JNK phosphorylation. Furthermore, the mGluR5-dependent JNK activation specifically activated c-Jun, but not activating transcription factor-2 or JunD, and increased activator protein-1 (AP-1)-mediated endogenous transcriptional activity. Together, we identified a novel mGluR5-to-nucleus communication through the EGF/JNK pathway, which functions to regulate AP-1-mediated transcription.
A long track on backbone nodes of content sharing networks

As a kind of sharing platform for files, information and resources, Content Sharing Networks (CSNs) are faced with a serious security situation of swarming malicious files, illegal information and spywares, especially the mainstream P2P (Peer-to-Peer) CSNs. Apart from the familiar importance for the rapid development and wide application of CSNs, backbone nodes should have been paid more attention for their significance to monitor and mitigate malicious sharing contents. In this paper, we proposed a comprehensive and effective determining method named MED to distinguish backbone nodes during the longest ever tracking and in-depth analysis of CSNs for nearly four years.
Talking to Ana: A Mobile Self-Anamnesis Application with Conversational User Interface

Normally, a physician is collecting a patient's medical history under time pressure during the initial patient interview. This leads to incomplete, erroneous data with negative effects on treatment and patient safety. The objective of this work is to introduce a concept for a self-anamnesis realized as a mobile application for patients. We implement the concept for the concrete example of self-anamnesis in music therapy. For this purpose, requirements are collected in discussions with music therapists. A conversational user interface is chosen to simulate the patient-therapist conversation. The self-anamnesis application is equipped with 63 questions that are asked subsequently to the user. We have chosen a rule-based approach for realizing the chat conversation and used the Artificial Intelligence Markup Language (AIML) for encapsulating the questions and responses of the chatbot. In contrast to digital questionnaires, the application of a conversational user interface in the context of collecting information regarding a patient's medical history, provides several benefits: the user can be encouraged to complete all queries and can ask clarifying questions in case something is unclear.
Decoupled Networks

Inner product-based convolution has been a central component of convolutional neural networks (CNNs) and the key to learning visual representations. Inspired by the observation that CNN-learned features are naturally decoupled with the norm of features corresponding to the intra-class variation and the angle corresponding to the semantic difference, we propose a generic decoupled learning framework which models the intra-class variation and semantic difference independently. Specifically, we first reparametrize the inner product to a decoupled form and then generalize it to the decoupled convolution operator which serves as the building block of our decoupled networks. We present several effective instances of the decoupled convolution operator. Each decoupled operator is well motivated and has an intuitive geometric interpretation. Based on these decoupled operators, we further propose to directly learn the operator from data. Extensive experiments show that such decoupled reparameterization renders significant performance gain with easier convergence and stronger robustness.
Diagnostic proteomics: back to basics?

The recent emergence of methods for rapidly profiling large numbers of protein markers by use of mass spectrometry (MS) has raised hopes for the rapid identification of novel cancer biomarkers (1). In particular, MS-based assays using surface-enhanced laser desorption/ionization (SELDI) have been used to compare serum proteomic patterns from healthy and diseased individuals in hopes of finding diagnostic signatures that can be adapted for use in the clinical laboratory. Early investigations in ovarian cancer patients suggested that panels of anonymous markers might substantially advance our current diagnostic capabilities (2)(3), although subsequent criticism has been directed at the primary data from these studies (4)(5) as well as at the SELDI time-of-flight (TOF) profiling approach itself (6)(7) [for summaries of this ongoing controversy, see Refs. (8)(9)]. Specific questions have been raised regarding the reproducibility of SELDI-TOF spectra, possible changes in protocols or inadequate calibration, and the ability of SELDI to detect low-abundance tumor markers. Additionally, observations that spectra can vary based on analytical factors such as the time of processing have been noted during large profiling experiments (10). Several of these issues have recently been addressed through the combined efforts of investigators in the National Cancer Institute–sponsored Early Detection Research Network (EDRN). This group has undertaken a systematic assessment of the interlaboratory reproducibility of SELDI-TOF measurements along with their potential applicability to prostate cancer diagnosis. Their initial results demonstrated that relevant portions of SELDI-TOF profiles can be measured reproducibly and used to distinguish a reference set of prostate cancer cases from controls (11). This study was an encouraging step toward defining the analytical reproducibility of serum proteome profiling, although it highlighted the need for rigorous calibration of instruments …
The Role of Energy in Economic Growth: The Case of Croatia

The purpose of this research is to examine the causal relationship between energy and economic growth in Croatia using data for the period from 1993 to 2006. We use a bivariate model of real GDP and five energy variables: energy consumption in industry and households, oil consumption, primary energy production and net energy imports. Since we found cointegration for all of the tested relationships, we use an Error Correction Model (ECM) which also allows us to distinguish between long and short term relationship among the variables. The empirical results provide clear support of causality that runs from real GDP growth to all energy variables. Our results differ from most of the studies analysing developing countries and are similar to those investigating developed, post-industrial economies with strong tertiary sector. Our research results reflect relatively low energy intensity in Croatia as a consequence of transition depression during the 1990s and the process of deindustrialization.
The transprecision computing paradigm: Concept, design, and applications

Guaranteed numerical precision of each elementary step in a complex computation has been the mainstay of traditional computing systems for many years. This era, fueled by Moore's law and the constant exponential improvement in computing efficiency, is at its twilight: from tiny nodes of the Internet-of-Things, to large HPC computing centers, sub-picoJoule/operation energy efficiency is essential for practical realizations. To overcome the power wall, a shift from traditional computing paradigms is now mandatory. In this paper we present the driving motivations, roadmap, and expected impact of the European project OPRECOMP. OPRECOMP aims to (i) develop the first complete transprecision computing framework, (ii) apply it to a wide range of hardware platforms, from the sub-milliWatt up to the MegaWatt range, and (iii) demonstrate impact in a wide range of computational domains, spanning IoT, Big Data Analytics, Deep Learning, and HPC simulations. By combining together into a seamless design transprecision advances in devices, circuits, software tools, and algorithms, we expect to achieve major energy efficiency improvements, even when there is no freedom to relax end-to-end application quality of results. Indeed, OPRECOMP aims at demolishing the ultra-conservative “precise” computing abstraction, replacing it with a more flexible and efficient one, namely transprecision computing.
Mechanisms Underlying the Risk to Develop Drug Addiction, Insights From Studies in Drosophila melanogaster

The ability to adapt to environmental changes is an essential feature of biological systems, achieved in animals by a coordinated crosstalk between neuronal and hormonal programs that allow rapid and integrated organismal responses. Reward systems play a key role in mediating this adaptation by reinforcing behaviors that enhance immediate survival, such as eating or drinking, or those that ensure long-term survival, such as sexual behavior or caring for offspring. Drugs of abuse co-opt neuronal and molecular pathways that mediate natural rewards, which under certain circumstances can lead to addiction. Many factors can contribute to the transition from drug use to drug addiction, highlighting the need to discover mechanisms underlying the progression from initial drug use to drug addiction. Since similar responses to natural and drug rewards are present in very different animals, it is likely that the central systems that process reward stimuli originated early in evolution, and that common ancient biological principles and genes are involved in these processes. Thus, the neurobiology of natural and drug rewards can be studied using simpler model organisms that have their systems stripped of some of the immense complexity that exists in mammalian brains. In this paper we review studies in Drosophila melanogaster that model different aspects of natural and drug rewards, with an emphasis on how motivational states shape the value of the rewarding experience, as an entry point to understanding the mechanisms that contribute to the vulnerability of drug addiction.
MRI-guided focused ultrasound: methodology and applications

Focused ultrasound is very well suited for inducing noninvasive local hyperthermia. Since magnetic resonance imaging (MRI) may be employed to obtain real-time temperature maps noninvasively the combination of these two technologies offers great advantages specifically aimed toward oncological studies. Real-time identification of the target region and accurate control of the temperature evolution during the treatment has now become possible. Thermal ablation of pathological tissue, local drug delivery using thermosensitive micro-carriers and controlled transgene expression using thermosensitive promoters have recently been demonstrated with this unique technology. Based on these experiments combined focused ultrasound and MRI thermometry holds promise for future oncological diagnostics and treatment. In this paper, we review some of the recent methodological developments as well as experimental and first clinical studies using this approach
More Than a Show: Using Personalized Immersive Theater to Educate and Engage the Public in Technology Ethics

Devising strategies to engage the public in discussions around the design and development of technology is critical to building a future that works for everyone. This paper presents a novel case study, an immersive theater experience, "Quantified Self," that combines aspects of design fiction and user enactments to construct a public engagement opportunity about technology ethics. Our audience supplied their social data (Facebook, Twitter.) and received a personalized experience where they interacted with a narrative and technology exhibits. We used a design model targeting goals of engagement, education, and discussion. Here we overview the design and production of Quantified Self and report on the results (240 participants over 6 performances) and findings from audience surveys (n=179/240) and cast/crew interviews (n=15/22). We found our approach attracted a wide audience interested in different elements of the show. Affordances and challenges of our model are discussed in detail.
Autistic traits and neuropsychological performance in 6- to-10-year-old children: a population-based study

ABSTRACT Clinical studies of children with autism spectrum disorder (ASD) provide evidence for poorer neuropsychological performance within specific domains compared to age, gender, and sometimes IQ-matched controls. Since recent evidence suggests that autistic symptoms form a spectrum that extends into the general population, it was our goal to evaluate the nature of the relationship between autistic traits and neuropsychological performance across the continuum in the general population. We examined neuropsychological performance across five different domains in 1019 6-to-10-year-old children participating in a population-based study of child development. Autistic traits were assessed when the children were 6 years of age using the Social Responsiveness Scale and ASD diagnoses were obtained via medical records. Neuropsychological functioning was measured using the NEPSY-II-NL and included the domains of attention and executive function, memory and learning, sensorimotor functioning, language, and visuospatial functioning. We found that children with higher autistic traits showed significantly lower neuropsychological performance in all domains investigated and that this association remained even after excluding children with the highest autistic traits or confirmed ASD. When comparing 41 children with confirmed ASD diagnosis to typically developing controls, children with ASD showed significantly lower neuropsychological performance across all domains. Taken together, our results suggest that children with both ASD and subclinical autistic traits have lower neuropsychological performance. Thus, this may provide an understanding of why some children without an ASD diagnosis may require some additional assistance within academic settings.
Conflicting genomic signals affect phylogenetic inference in four species of North American pines

Eleven nuclear genes and multiple phylogenetic techniques were used to study relationships among four of North American pines from subsection Australes (genus Pinus). Support for phylogenies reconstructed based on all data was generally weak and inconsistent among methods. Subsequent analysis revealed that certain topologies were supported by genes with common putative functionalities. Therefore, each set of genes was analysed independently. Recovered alternative topologies were highly supported and the results were consistent among methods. Multiple evolutionary hypotheses could potentially explain the observed patterns, although incomplete lineage sorting seems to be the simplest one.