Miracle-dz/UniFAR-FTUs huggingface dataset:
On the classification of sleep states by means of statistical and spectral features from single channel Electroencephalogram

Traditional sleep scoring based on visual inspection of Electroencephalogram (EEG) signals is onerous for sleep scorers because of the gargantuan volume of data that have to be analyzed per examination. Computer-aided sleep staging can alleviate the onus of the sleep scorers. Again, most of the existing works on automatic sleep staging are multichannel based. Multichannel based sleep scoring is not pragmatic for the implementation of a wearable and portable sleep quality evaluation device. Due to all these factors, automatic sleep scoring based on single channel EEG is garnering increasing attention of sleep researchers. In this work, we propound a single channel based solution to sleep scoring. First, we decompose the EEG signals into segments. We then compute various statistical and spectral features from the signal segments. After performing statistical analyses, we perform classification using artificial neural network. Results of various experiments perspicuously manifest that the proposed scheme is superior to state-of-the-art ones in accuracy.
On the Multiuser Diversity of Relay-Aided Downlink Systems Using Reduced Feedback

We introduce an efficient multiuser scheduling method using amplify-and-forward relaying in relay-aided downlink systems, consisting of one base station (BS), one relay station, and multiple mobile stations (MSs). In our scheme, the BS opportunistically selects both the transmission mode, that is, either one- or two-hop transmission, and the desired user (i.e., the desired MS). Closed-form expressions for the average achievable rates are derived for the two transmission modes with multiuser scheduling, and its asymptotic solutions are also analyzed in the limit of large number of MSs. Based on the analysis, we propose a feedback-efficient two-step multiuser scheduling algorithm: the transmission mode selection followed by the user selection that only needs a partial feedback for instantaneous signal-to-noise ratios (SNRs) to the BS. We also analyze the average SNR condition such that the multiuser diversity gain is fully exploited for two-hop transmission. The proposed two-step scheduling algorithm exhibits the quite comparable achievable rates to those of the optimal one using full feedback information, while its required feedback information is reduced by half of the optimal one.
Glucocorticoids Induce Protein S-Dependent Phagocytosis of Apoptotic Neutrophils by Human Macrophages1

During resolution of an inflammatory response, recruited neutrophil granulocytes undergo apoptosis and are removed by tissue phagocytes before induction of secondary necrosis without provoking proinflammatory cytokine production and release. Promotion of physiological neutrophil clearance mechanisms may represent a viable therapeutic strategy for the treatment of inflammatory or autoimmune diseases in which removal of apoptotic cells is impaired. The mechanism underlying enhancement of macrophage capacity for phagocytosis of apoptotic cells by the powerful anti-inflammatory drugs of the glucocorticoid family has remained elusive. In this study, we report that human monocyte-derived macrophages cultured in the presence of dexamethasone exhibit augmented capacity for phagocytosis of membrane-intact, early apoptotic cells only in the presence of a serum factor. Our results eliminate a role for a number of potential opsonins, including complement, pentraxin-3, and fibronectin. Using ion-exchange and gel filtration chromatography, we identified a high molecular mass serum fraction containing C4-binding protein and protein S responsible for the augmentation of phagocytosis of apoptotic neutrophils. Because the apoptotic neutrophils used in this study specifically bind protein S, we suggest that glucocorticoid treatment of macrophages induces a switch to a protein S-dependent apoptotic cell recognition mechanism. Consistent with this suggestion, pretreatment of macrophages with Abs to Mer tyrosine kinase, a member of the Tyro3/Axl/Mer family of receptor tyrosine kinases, prevented glucocorticoid augmentation of phagocytosis. Induction of a protein S/Mer tyrosine kinase-dependent apoptotic cell clearance pathway may contribute to the potent anti-inflammatory effects of glucocorticoids, representing a potential target for promoting resolution of inflammatory responses.
Adaptive per-GOP Bandwidth allocation for H.264 Video Transmission over Differentiated Services Networks

While transmitting over differentiated services networks, in case of severe congestion also the most privileged classes may experience losses. In those cases, and especially in case of video transmission, protecting a higher fraction of traffic can have the effect of decreasing the quality, due to the overload of high-priority classes. We propose a method to compute, at source side, the allocation of video traffic over the available classes to ensure the lowest decoder-side distortion and provide traffic friendliness. To show this algorithm performance, the simple case of Poisson traffic with a bottleneck shared-buffer router is shown. The same approach can be extended to other traffic characteristics and router architectures
Proto-patterns for growing a community of practice

Web technologies can support the online exchange of practical knowledge. While the infrastructure for online communities is well understood, the facilitators' activities for supporting the emergence of a community of practice remain an open challenge. This article presents a first step towards a pattern language for growing communities of practice. Based on experiences in large distributed communities, we present good practices for organizations and facilitators who want to encourage active exchange on practical knowledge within the organization and beyond.
Addressing “Nature-Deficit Disorder”: A Mixed Methods Pilot Study of Young Adults Attending a Wilderness Camp

Background and Objectives. Rapid urbanization raises concern about chronic human health issues along with less frequent interaction with the natural world. “Nature-deficit disorder,” a nonclinical term, describes this potential impact on the well-being of youth. We conducted a mixed methods pilot study of young adults attending a four-week wilderness camp to investigate whether nature-based camp experiences would increase connection to nature and promote multiple dimensions of well-being. Methods. Participants completed precamp (n = 46) and postcamp (n = 36) online questionnaires including nature-related and holistic well-being measures. Differences were investigated using paired t-tests. Interviews (n = 16) explored camp experiences and social relations. Results. All nature-related measures—exposure, knowledge, skills, willingness to lead, perceived safety, sense of place, and nature connection—significantly increased. Well-being outcomes also significantly improved, including perceived stress, relaxation, positive and negative emotions, sense of wholeness, and transcendence. Physical activity and psychological measures showed no change. Interviews described how the wilderness environment facilitated social connections. Conclusion. Findings illustrate the change in nature relations and well-being that wilderness camp experiences can provide. Results can guide future research agendas and suggest that nature immersion experiences could address the risk of “nature-deficit disorder,” improve health, and prepare future environmental leaders.
ICA’s suitability assisted by Voice Activity Detection

This research presents an innovative system for adaptive speech denoising using Independent Component Analysis (ICA) and Voice Activity Detection (VAD). Designed for instantaneous mixtures (two sources and two microphones), the proposed system identifies the noise contained in each noisy mixture. For that type of noise applies the most suitable ICA method among three methods (FastICA, Kernel ICA and JADE) and, after source separation, identifies the estimated speech signal. The signal mixtures are non-linear and the proposed system extracts information that can be used for further pre and/or post-processing. The experimental data shows that adaptive ICA allows better performance than applying a fixed ICA method for all hypothetic cases (an average ofldB SNR improvement). The process is completely automatic from the source recording to its output and such system has a wide range of applications.
3D Face Recognition Using Radon Transform and Factorial Discriminant Analysis (FDA)

Automatic recognition of human faces is considered to be a challenging task despite significant progress in both computer vision and pattern recognition. A facial recognition system is a computer application of automatically identifying or verifying a person from a digital image or a video frame from a video source. Typical variations such as in-depth pose changes or illumination variations increase the dissimilarity of two face images of the same person more than the dissimilarity of different persons' face images. In this paper, we have proposed a novel method for three dimensional (3D) face recognition using Radon transform and Factorial Discriminant Analysis. In this method, the Factorial Discriminant Analysis (FDA) based feature computation takes into account of face image variations to a larger extent and has the advantage of dimensionality reduction. The experimental results have yielded 99.66% recognition performance with reduced computational cost, which compares well with other state-of-the-art methods in the literature.
An iterative learning controller with initial state learning

In iterative learning control (ILC), a common assumption is that the initial states in each repetitive operation should be inside a given ball centred at the desired initial states which may be unknown. This assumption is critical to the stability analysis, and the size of the ball will directly affect the final output trajectory tracking errors. In this paper, this assumption is removed by using an initial state learning scheme together with the traditional D-type ILC updating law. Both linear and nonlinear time-varying uncertain systems are investigated. Uniform bounds for the final tracking errors are obtained and these bounds are only dependent on the system uncertainties and disturbances, yet independent of the initial errors. Furthermore, the desired initial states can be identified through learning iterations.
Imports and Productivity

What is the effect of imports on productivity? To answer this question, we estimate a structural model of producers using product-level import data for a panel of Hungarian manufacturing firms from 1992 to 2001. In our model with heterogenous firms, producers choose to import or purchase domestically varieties of intermediate inputs. Imports affect firm productivity through expanding variety as well as improved input quality. The model leads to a production function where the total factor productivity of a firm depends on the share of inputs imported. To estimate this import-augmented production function, we extend the Olley and Pakes (1996) procedure for a setting with an additional state variable, the number of input varieties imported. Our results suggest that the role of imports is both statistically and economically significant. Imports are responsible for 30% of the growth in aggregate total factor productivity in Hungary during the 1990s. About 50% of this effect is through imports advancing firm level productivity, while the remaining 50% comes from the reallocation of capital and labor to importers.
Numerical modelling of the blowing phase in the production of glass containers

The industrial manufacturing of glass containers consists of several phases, one of which is the blowing phase. This paper describes the development of a numerical simulation tool for this phase. The hot liquid glass is modelled as a viscous fluid and its flow is governed by the Stokes equations. We use the boundary element method to solve the Stokes equations and obtain the velocity profile at the glass surface. The movement of the surface obeys an ordinary differential equation. We use the Euler forward method to perform a time integration step and update the shape of the glass surface. All calculations are performed in three dimensions. This allows us to simulate the blowing of glass containers that are not rotationally symmetric. The contact between glass and mould is modelled using a partial-slip condition. A number of simulations on model glass containers illustrates the results. Please note that this article has three supplemental video files: Video 1 Video 2 Video 3
Computer-Mediated Mobile Messaging as Collaboration Support for Nurses

Collaboration in hospitals is coordinated mainly by communication, which currently happens by face-to-face meetings, phone calls, pagers, notes and the electronic patient record. These habits raise problems e.g., delayed notifications and unnecessary interruptions. Dealing with these problems could save time and improve the care. Therefore we designed and prototyped a mobile messaging solution based on two specific scenarios coming from observations at a cardiology department of a Norwegian hospital. The main focus was on supporting the work of nurses. One prototype supported patient management while another one dealt with messages related to medication planning. The evaluation of the prototypes suggested that messaging-based collaboration support is worth to explore and also gave ideas for improvement.
ViotSOC: Controlling Access to Dynamically Virtualized IoT Services using Service Object Capability

Virtualization of Internet of Things(IoT) is a concept of dynamically building customized high-level IoT services which rely on the real time data streams from low-level physical IoT sensors. Security in IoT virtualization is challenging, because with the growing number of available (building block) services, the number of personalizable virtual services grows exponentially. This paper proposes Service Object Capability(SOC) ticket system, a decentralized access control mechanism between servers and clients to efficiently authenticate and authorize each other without using public key cryptography. SOC supports decentralized partial delegation of capabilities specified in each server/client ticket. Unlike PKI certificates, SOC's authentication time and handshake packet overhead stays constant regardless of each capability's delegation hop distance from the root delegator. The paper compares SOC's security benefifits with Kerberos and the experimental results show SOC's authentication incurs significantly less time packet overhead compared against those from other mechanisms based on RSA-PKI and ECC-PKI algorithms. SOC is as secure as, and more efficient and suitable for IoT environments, than existing PKIs and Kerberos.
Clustering Ad Hoc Networks: Schemes and Classifications

Many clustering schemes have been proposed for different ad hoc networks and play an important role in self organizing them. A systematic classification of these clustering schemes enables one to better understand and make improvements. This paper surveys clustering schemes and classifies them into ad hoc sensor network clustering schemes and mobile ad hoc network clustering schemes. In sensor networks, the energy stored in the network nodes is limited and usually infeasible to recharge; the clustering schemes for these networks therefore aim at maximizing the energy efficiency. In mobile ad hoc networks, the movement of the network nodes may quickly change the topology resulting in the increase of the overhead message in topology maintenance; the clustering schemes for mobile ad hoc networks therefore aim at handling topology maintenance, managing node movement or reducing overhead
Novel recursive approach for OFDM channel estimation under highly mobile conditions

This paper proposes a novel recursive approach for orthogonal frequency division multiplexing (OFDM) channel estimation over highly mobile channels without any priori channel statistics. The key idea is to decompose each objective channel into the known component and the rest for estimation. The known component is the output of the prior iteration except that the first one is attained in linear time-varying (LTV) model. In each iteration, the rest channel component, obtained by subtracting the known channel component from the original channel, is estimated in generalized complex exponential basis expansion model (GCEBEM). Since the rest component varies much milder than the original channel, both modeling error and inter-carrier interference (ICI) are significantly reduced in GCEBEM-based estimation. Monte Carlo simulations demonstrate the superiority of the proposed approach with a few iterations over the conventional methods under highly mobile conditions.
Designing and experimenting bio-inspired chromatic behaviours in surveillance robot

Numerous work has been done in biologically inspired robotics emulating models, systems and elements of nature for the purpose of solving traditional robotics problems. Chromatic behaviours are abundant in nature across a variety of living species to achieve camouflage, signaling, and temperature regulation. The ability of these creatures to successfully blend in with their environment by changing their colour is the fundamental inspiration for our research work. In this paper, we present a dwarf chameleon inspired chromatic behaviour in the context of an autonomous surveillance robot, Pachondhi. In our experiments, we successfully validated the ability of the robot to autonomously change its colour in relation to the terrain that it is traversing for both maximizing detectability to conspecifics as well as minimizing exposure to predators.
Resveratrol Inhibition of Cellular Respiration: New Paradigm for an Old Mechanism

Resveratrol (3,4′,5-trihydroxy-trans-stilbene, RSV) has emerged as an important molecule in the biomedical area. This is due to its antioxidant and health benefits exerted in mammals. Nonetheless, early studies have also demonstrated its toxic properties toward plant-pathogenic fungi of this phytochemical. Both effects appear to be opposed and caused by different molecular mechanisms. However, the inhibition of cellular respiration is a hypothesis that might explain both toxic and beneficial properties of resveratrol, since this phytochemical: (1) decreases the production of energy of plant-pathogenic organisms, which prevents their proliferation; (2) increases adenosine monophosphate/adenosine diphosphate (AMP/ADP) ratio that can lead to AMP protein kinase (AMPK) activation, which is related to its health effects, and (3) increases the reactive oxygen species generation by the inhibition of electron transport. This pro-oxidant effect induces expression of antioxidant enzymes as a mechanism to counteract oxidative stress. In this review, evidence is discussed that supports the hypothesis that cellular respiration is the main target of resveratrol.
Empirical Bayes interpretations of random point events

Given a sequence of apparently random point events, such as neuronal spikes, one may interpret them as being derived either irregularly in time from a constant rate or regularly from a fluctuating rate. To determine which interpretation is more plausible in any given case, we employ the empirical Bayes method. For a sequence of point events derived from a rate-fluctuating gamma process, the marginal likelihood function can possess two local maxima and the system exhibits a first-order phase transition representing the switch of the most plausible interpretation from one to the other.
Performance Analysis of Loosely Coupled Applications in Heterogeneous Distributed Computing Systems

Loosely coupled applications composed of a potentially very large number (from tens of thousands to even billions) of tasks are commonly used in High-Throughput Computing (HTC) and Many-Task Computing (MTC) paradigms. To efficiently execute large-scale computations which can exceed the capability in a single type of computing resources within expected time, we should be able to effectively integrate resources from Heterogeneous Distributed Computing (HDC) systems such as Clusters, Grids, and Clouds. In this paper, we quantitatively analyze the performance of three different real scientific applications consisting of many tasks on top of HDC systems based on a Partnership of Distributed Computing Clusters, Grids, and Clouds to show practical issues that normal scientific users can face during the course of leveraging these systems. Our experimental results show that the performance of a loosely coupled application can be significantly affected by the characteristics of a HDC system, along with hardware specification of a node, and their impacts on the performance can vary widely depending on the resource usage pattern of each application. Throughout our extensive performance study with representative HDC systems and real scientific applications, we aim to give an insight to the research community on design and implementation of a next generation middleware system that can intelligently support large-scale loosely coupled applications by considering both of resource and application perspectives.
Recognizing facial expressions using active textures with wrinkles

This paper explores the use of facial wrinkle textures for recognizing the facial expressions. Based on the observation of the wrinkles appearance and change along with performed expressions, we propose to extract the partial texture information in both the facial organ areas (e.g., eyes and mouth) and the facial wrinkle areas, and use the texture dissimilarity between the neutral expression and the active expression to extract the active texture for the expression representation. We present a novel method using multiple levels of detail to measure the active texture dissimilarity. The rate of change between levels is used as the rule for discriminating 6 types of universal expressions. The experiments on video sequences demonstrate the simplicity and efficiency of the proposed method for recognizing expressions with an 82.8% correct recognition rate.
Seismic source classification in Israel by signal imaging and rule-based coincidence evaluation

We tested the applicability of the sonogram detector and a rule-based evaluation for seismic source classification and identification in Israel. Source identification is based on the transformation of full seismograms to images and the correlation between a new image and known images from different seismic sources. These methods were initially developed to monitor the induced seismicity of northwest Germany by the BUG small array. Two new elements were introduced in this study: (a) the adaptation of the array technique to the identification of seismic sources using a local network and (b) the recognition of source regions with natural seismicity. The tested data include 41 local earthquakes and explosions in the time period September 1997 to December 1997. Automated processing yielded 95% success in correctly identifying the individual sources with no misclassification. One event was not classified. Path and distance effects did not influence the classification capability. The method could be useful for seismic verification under the Comprehensive Test Ban Treaty.