Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy Efficiency Comparison of MIMO-Based and Multihop Sensor Networks

Wireless sensor networks (WSNs) demand the implementation of energy-aware techniques and low-complexity protocols in all layers. Recently, a MIMO-based structure has been proposed to offer enhanced energy savings in WSNs. In this paper, we examine and compare MIMO-based WSN with a multihop transmission in terms of energy efficiency. The results depend on the network density, the channel conditions, and the distance to the destination node. We reach analytical expressions to calculate threshold values of these parameters, which determine the areas where the MIMO-based structure outperforms multihop transmission. Moreover, we present a detailed analysis of the dissipated power during a sensor node_s operation, to prove that as microelectronics develops, the MIMO-based architecture will outperform the equivalent multihop structure for most of the cases examined. Finally, we implement a simple cooperative node selection algorithm to achieve higher energy gains in the MIMO approach, and we examine how this algorithm affects the calculated thresholds.
Multiple Model Framework of Extended Kalman Filtering for Predicting Vehicle Location using Latest Global Positioning System

This paper looks into various practical methods of improving existing collision avoidance systems that loose accuracy in non-straight paths. Different frameworks of models are studied to identify their accuracy in predicting a vehicle’s future location in non-straight path. From a simple mathematical approach to more complex frameworks of multiple Kalman Filters are evaluated to obtain more accurate collision warnings in situations that current systems can not handle correctly. To make any improvements cost effective, only a Global Positioning System (GPS) receiver was used to obtain all spatial information related to the vehicle. This paper goes through the implementation of several Extended Kalman Filters (EKF) to achieve full coverage of the possible vehicle movements. It then goes on to create multiple model frameworks that combine the different EKF to provide even more accurate estimations of a vehicle’s trajectory. The two frameworks studied in this paper are the Multiple Models Adaptive Estimation System (MMAE) and the Interacting Multiple Models Estimation (IMME). Both the MMAE and the IMME have proven very reliable in the robotics field, so they should also work in the field of automobiles. The last improvement this paper investigates is the integration of the Geographic Information System (GIS) into this system. Road information is available in the GIS data, and spatial information is available through the GPS receiver, therefore, this paper investigates a way to verify that the predicted vehicle’s location is on actual roads. This innovative method reduces the error by more than half when used as part of the system.
The Mureş–Uzhgorod–Debrecen study: a comparison of hospital stroke services in Central‐Eastern Europe

Stroke mortality is extremely high in Central‐Eastern European countries. The high rate of risk factors and differences in health care services might be among the factors resulting in high stroke morbidity and mortality in this region. As only few prospectively collected information are available from this region, we decided to evaluate some characteristics of stroke services in neurological departments of a Romanian, a Ukrainian and a Hungarian city in the framework of the Mureş–Uzhgorod–Debrecen comparative epidemiological study. We registered demographic data, the absence or presence of the most important risk factors, and clinical signs on admission and at discharge. We recorded the application of various diagnostic methods, stroke treatment and recommendations for secondary prevention. Follow‐up is planned after 30 days and after 1 year. The paper summarizes the methodology of this prospective epidemiological study of stroke patients hospitalized in neurological departments in Târgu Mureş, Uzhgorod and Debrecen, three Central‐Eastern European cities in Romania, Ukraine and Hungary, respectively.
Course of the Masseteric Nerve in Masseter Muscle

The masseter muscle is often exploited by plastic and reconstructive surgeons in transposition operations to correct facial palsy. In benign masseteric hypertrophy, a neurectomy induces atrophy of the muscle and therefore a slender face. A clear understanding of the course of the masseteric nerve is essential in maneuvering the masseter muscle. Detailed dissection was performed on 48 head halves of Korean cadavers, and the inside of each masseter muscle was explored under the microscope with ×10 magnification. The masseteric nerve ran anteriorly and inferiorly between the deep and the middle layers. The nerve was observed at 33±5.6 mm from the inferior border of the muscle on the anterior third vertical line of the masseter muscle and at 47±5.5 mm in the posterior third. The closest distance between the main nerve and the gonion was 32±4.1 mm. Approximately two thirds (69.6%) of the masseteric nerve intersected the artery. The safe limit is within 47 mm from the inferior border of the muscle on the posterior third vertical line and within radial 32 mm from the gonion.
The Influence of Random Element Displacement on DOA Estimates Obtained with (Khatri–Rao-)Root-MUSIC

Although a wide range of direction of arrival (DOA) estimation algorithms has been described for a diverse range of array configurations, no specific stochastic analysis framework has been established to assess the probability density function of the error on DOA estimates due to random errors in the array geometry. Therefore, we propose a stochastic collocation method that relies on a generalized polynomial chaos expansion to connect the statistical distribution of random position errors to the resulting distribution of the DOA estimates. We apply this technique to the conventional root-MUSIC and the Khatri-Rao-root-MUSIC methods. According to Monte-Carlo simulations, this novel approach yields a speedup by a factor of more than 100 in terms of CPU-time for a one-dimensional case and by a factor of 56 for a two-dimensional case.
Second harmonic generation imaging of the deep shade plant Selaginella erythropus using multifunctional two‐photon laser scanning microscopy

Background: Multifunctional two‐photon laser scanning microscopy provides attractive advantages over conventional two‐photon laser scanning microscopy. For the first time, simultaneous measurement of the second harmonic generation (SHG) signals in the forward and backward directions and two photon excitation fluorescence were achieved from the deep shade plant Selaginella erythropus.
Electric dyadic Green's functions in the source region

A straightforward approach that does not involve delta-function techniques is used to rigorously derive a generalized electric dyadic Green's function which defines uniquely the electric field inside as well as outside the source region. The electric dyadic Green's function, unlike the magnetic Green's function and the impulse functions of linear circuit theory, requires the specification of two dyadics: the conventional dyadic G-eoutside its singularity and a source dyadic L-which is determined solely from the geometry of the "principal volume" chosen to exclude the singularity of G-e. The source dyadic L-is characterized mathematically, interpreted physically as a generalized depolarizing dyadic, and evaluated for a number of principal volumes (self-cells) which are commonly used in numerical integration or solution schemes. Discrepancies at the source point among electric dyadic Green's functions derived by a number of authors are shown to be explainable and reconcilable merely through the proper choice of the principal volume. Moreover, the ordinary delta-function method, which by itself is shown to be inadequate to extract uniquely the proper electric dyadic Green's function in the source region, can be supplemented by a simple procedure to yield unambiguously the correct Green's function representation and associated fields.
An optimal sound detection for robots in an unknown environment

Robot technology has been rapidly developed more & more robots such as humanoid robots work with humans. The objective of this project is to develop a system for an autonomous mobile robot for searching and tracking sound source based target using sound sensors. Finding objects or events by following a sound source direction is an intuitive response for human and animal when they cannot see the target. Lego nxt sound sensor can detect the frequency of sound but is unable to detect the direction from where the sound is originating. PSO algorithm has been implemented for the optimization of the exact sound source. PSO (particle swarm optimization) is a stochastic population based computational method that optimizes the problem in each iteration, trying to improve the particle solutions and to get better quality of the particles each time. Objective function has been applied to detect the frequency and then the source continuously updates its position on the basis of frequency being detected. So that maximum frequency sound can be detected in minimum possible time and in exact location. Simulation work has been carried out by implementing the PSO algorithm in MATLAB to see how exactly the sound sources are detecting the frequency and at what particular frequency the source is exactly detecting the sound. Results have been computed by changing the number of iterations to see the exact location where the sound source is finding the frequency. Thus the main objective of this paper is to compute that the source is detecting the optimized maximum frequency sound by updating its gbest values continuously in every iteration and finally reaching the best possible value.
Hierarchical IP flow clustering

The analysis of flow traces can help to understand a network's usage patterns. We present a hierarchical clustering algorithm for network flow data that can summarize terabytes of IP traffic into a parsimonious tree model. The method automatically finds an appropriate scale of aggregation so that each cluster represents a local maximum of the traffic density from a block of source addresses to a block of destination addresses. We apply this clustering method on NetFlow data from an enterprise network, find the largest traffic clusters, and analyze their stationarity across time. The existence of heavy-volume clusters that persist over long time scales can help network operators to perform usage-based accounting, capacity provisioning and traffic engineering. Also, changes in the layout of hierarchical clusters can facilitate the detection of anomalies and significant changes in the network workload.
Sparse-induced similarity measure: mono-modal image registration via sparse-induced similarity measure

Similarity measure is an important key in image registration. Most traditional intensity-based similarity measures (e.g. sum-of-squared-differences, correlation coefficient, mutual information and correlation ratio) assume a stationary image and pixel-by-pixel independence. These similarity measures ignore the correlation among pixel intensities; hence, a perfect image registration cannot be achieved especially in the presence of spatially varying intensity distortions and outlier objects that appear in one image but not in the other. It is supposed here that non-stationary intensity distortion (such as bias field) has a sparse representation in the transformation domain. Based on this assumption, a novel similarity measure is proposed here based on sparse representation in a mono-modal setting. The zero norm (l 0 ) in the transform domain is introduced as a new similarity measure in the presence of non-stationary intensity distortion. The present study defines a sparsity similarity measure that indicates the complexity of the residual image between two registered images in the transform domain such as discrete cosine transform or wavelet. It is attempted here to analytically and statistically illustrate that the proposed similarity measure has important properties such as metric properties in vector space, from correntropy perspective. This measure produces accurate registration results on both artificial and real-world problems which are examined in the present study.
The Social Amplification of Risk: The logical structure of the social amplification of risk framework (SARF): Meta theoretical foundations and policy implications

The social amplification of risk framework (SARF) is the most comprehensive tool available for the study of risk. Theories and frameworks are useful and effective only insofar as they conform to certain fundamental features of logic: clearly defined terms, coherence, internal consistency, sound organization explicated with parsimony, accompanied by a specification of scope conditions, and the generation of testable hypotheses. The first goal of this chapter is to evaluate critically key foundational concepts of the SARF and to strengthen its foundation with a set of metatheoretical principles that have been coherently structured. The second goal is to use these same metatheoretical principles to establish symmetry between SARF and risk policy. Such symmetry should enhance communication between experts and laypersons in the development of risk policy and, therefore, remove some of the obstacles to effective, democratic risk policy. Genesis of the social amplification of risk framework The SARF developed in the late 1980s in response to the emergence of multiple perspectives in the rapidly growing risk literature. The multiple perspectives that emerged led, according to Kasperson (1992) one of the leading architects of the SARF, to key disjunctures which came to dominate the field: disjunctures between technical and social analyses of risk; disjunctures within the social sciences themselves (e.g. between the rational actor perspective (RAP) of economics and engineering and the psychometric paradigm; see also Jaeger et al. 2001); disjunctures between the older natural hazards social science and the newer technological hazard social sciences; and disjunctures over scientific and other claims to knowledge.
The spatial experiences of dwarfs within public spaces

ABSTRACTDwarfism is commonly defined as anyone 4ft 10″ (147.32 cm) or below and whose short stature involves a medical condition [Adelson, M. B. 2005. The Lives of Dwarfs, xv. NJ: Rutgers University Press]. Whilst it recognized that the built environment is unsuitable for dwarfs [see Kruse, R. 2002. “Social Spaces of Little People: The Experiences of the Jamisons. ” Social and Cultural Geography 3 (2): 175–191, Kruse, R. 2010. “Placing Little People: Dwarfism and Geographies of Everyday Life. ” In Towards Enabling Geographies, edited by V. Chouinard, E. Hall, and R. Wilton, 183–198. Surrey: Ashgate; Shakespeare, T. , M. Wright, and S. Thompson. 2007. A Small Matter of Equality: Living with Restricted Growth. Newcastle: Newcastle University], this paper critically examines how spaces and facilities designed with other users in mind, including disabled people and children, can have unintended consequences for dwarfs. The data used in this paper are taken from semi-structured interviews and photo elicitation ex.
Human Ng2+ adipose stem cells loaded in vivo on a new crosslinked hyaluronic acid‐lys scaffold fabricate a skeletal muscle tissue

Mesenchymal stem cell (MSC) therapy holds promise for treating diseases and tissue repair. Regeneration of skeletal muscle tissue that is lost during pathological muscle degeneration or after injuries is sustained by the production of new myofibers. Human Adipose stem cells (ASCs) have been reported to regenerate muscle fibers and reconstitute the pericytic cell pool after myogenic differentiation in vitro. Our aim was to evaluate the differentiation potential of constructs made from a new cross‐linked hyaluronic acid (XHA) scaffold on which different sorted subpopulations of ASCs were loaded. Thirty days after engraftment in mice, we found that NG2+ ASCs underwent a complete myogenic differentiation, fabricating a human skeletal muscle tissue, while NG2− ASCs merely formed a human adipose tissue. Myogenic differentiation was confirmed by the expression of MyoD, MF20, laminin, and lamin A/C by immunofluorescence and/or RT‐PCR. In contrast, adipose differentiation was confirmed by the expression of adiponectin, Glut‐4, and PPAR‐γ. Both tissues formed expressed Class I HLA, confirming their human origin and excluding any contamination by murine cells. In conclusion, our study provides novel evidence that NG2+ ASCs loaded on XHA scaffolds are able to fabricate a human skeletal muscle tissue in vivo without the need of a myogenic pre‐differentiation step in vitro. We emphasize the translational significance of our findings for human skeletal muscle regeneration. J. Cell. Physiol. 228: 1762–1773, 2013. © 2013 Wiley Periodicals, Inc.
Yeast Population Dynamics in Spontaneous and Inoculated Alcoholic Fermentations of Zametovka Must

Summary Inoculated fermentations, which are more rapid and more reliable than spontaneous fermentations, and assure predictable wine quality, are nowadays prevalent in Slovenia’s large-scale wine production. However, spontaneous fermentation strengthens local characteristics of wine and offers opportunities for technological innovation. In the 1999 vintage, spontaneous and inoculated fermentations of Zametovka (Vitis vinifera) grape must were studied. Zametovka is the main red variety in production of traditional Slovene red blend wine, Cvicek. The diversity of yeast species and strains in both of the investigated fermentations was determined by molecular and traditional identification methods. The outset of alcoholic fermentation, yeast growth kinetics, and yeast population dynamics presents the main differences between the examined fermentations. Yeast population diversity was higher in the spontaneous process. Dominant yeast isolates from spontaneous fermentation were identified as Candida stellata, Hanseniaspora uvarum and Saccharomyces cerevisiae; whereas Saccharomyces bayanus, Pichia kluyveri, Pichia membranifaciens and Torulaspora delbrueckii were found less frequently. Dominant species in the inoculated fermentation was Saccharomyces cerevisiae; other species found in smaller numbers were Candida stellata, Hanseniaspora uvarum and Debaryomyces hansenii var. hansenii. Using PFGE, we were able to distinguish among 15 different Saccharomyces cerevisiae strains and three different Saccharomyces bayanus strains isolated from spontaneous fermentation, whereas, in the case of inoculated fermentation, only two Saccharomyces cerevisiae strains were found. Their chromosomal patterns coincide with the chromosomal patterns of the starter culture strains.
(Mis)Communication wars : terrorism, counterterrorism and the media

This chapter is part of a book dedicated to the memory of Professor Philip Taylor. It critically reviews existing assessments about the role of media and communication technologies in the current phenomenon of international terrorism. It demonstrates that most approaches are based on either flawed assumptions or outdated theories. It makes the point that an explicit engagement with communication theory and media studies supports not only a greater understanding of the phenomenon in an age of interconnectedness, but could also inform more effective counterterrorism practice.
MULTI-CRITERIA OPTIMAL DESIGN OF RESIDENTIAL VENTILATION SYSTEMS

This paper addresses the optimal design of residential ventilation systems in an apartment floor plan in Korea. The term “optimal design” refers to the selection of a ventilation method (mechanical, hybrid), type of heat recovery (total, sensible only), outdoor airflow rate, and the optimal sizing and location of supply diffusers/exhaust registers. Decision-making criteria include initial and operation costs, indoor air quality, energy use, and comfort. To solve this multi-criteria optimal design problem, we introduce multi-objective optimization using a genetic algorithm and Pareto optimality. The Genetic Algorithm (GA) was chosen to solve the constrained discontinuous optimization problem. The software CONTAMW 2.4 developed by NIST (National Institute of Science and Technology) was used to simulate ventilation phenomena. The problem was then solved by integrating GA, Pareto optimality, and CONTAMW simulation runs. The paper presents an example of an optimal design problem for a specific apartment plan.
How low energy is bluetooth low energy? Comparative measurements with ZigBee/802.15.4

Ultra low power communication mechanisms are essential for future Internet of Things deployments. Bluetooth Low Energy (BLE) is one promising candidate for such deployments. We study the energy consumption of BLE by measuring real devices with a power monitor and derive models of the basic energy consumption behavior observed from the measurement results. We investigate also the overhead of Ipv6-based communication over BLE, which is relevant for future IoT scenarios. We contrast our results by performing similar measurements with ZigBee/802.15. 4 devices. Our results show that when compared to ZigBee, BLE is indeed very energy efficient in terms of number of bytes transferred per Joule spent. In addition, IPv6 communication energy overhead remains reasonable. We also point out a few specific limitations with current stack implementations and explain that removing those limitations could improve energy utility significantly.
Does implicit memory extend to legal and illegal nonwords?

In 4 experiments, implicit and explicit memory for words and nonwords were compared. In Experiments 1-2 memory for words and legal nonwords (e.g., kers) was assessed with an identification (implicit) and a recognition (explicit) memory task: Robust priming was obtained for both words and nonwords, and the priming effects dissociated from explicit memory following a levels-of-processing manipulation (Experiment 1) and following a study-test modality shift (Experiment 2). In Experiment 3, priming for legal and illegal nonwords (e.g., xyks) was observed on an identification task, and the effects dissociated from explicit memory following a levels-of-processing manipulation. Finally, in Experiment 4, significant inhibitory priming for legal nonwords was observed when a lexical-decision task was used. Results suggest that implicit memory can extend to legal and illegal nonwords. Implications for theories of implicit memory are discussed.
On the control of the algebraic connectivity and clustering of a mobile robotic network

In this paper two related problems are studied: the control of the algebraic connectivity and clustering of a network of single-integrator agents. A steepest-descent algorithm is presented for the first problem, so that a smooth approximation of the algebraic connectivity of the underlying undirected communication graph converges to an assigned value. For the second problem, a new gradient-based control strategy is proposed to automatically partition the mobile robotic network into two predefined groups: our spectral-clustering method leverages a continuous-time power-iteration algorithm on the normalized Laplacian matrix which provides an estimate of its Fiedler vector at each time instant. The results of numerical simulations are provided to illustrate our theoretical findings.
THE RANGE OF TRADED OPTION PRICES

Suppose we are given a set of prices of European call options over a finite range of strike prices and exercise times, written on a financial asset with deterministic dividends which is traded in a frictionless market with no interest rate volatility. We ask: when is there an arbitrage opportunity? We give conditions for the prices to be consistent with an arbitrage‐free model (in which case the model can be realized on a finite probability space). We also give conditions for there to exist an arbitrage opportunity which can be locked in at time zero. There is also a third boundary case in which prices are recognizably misspecified, but the ability to take advantage of an arbitrage opportunity depends upon knowledge of the null sets of the model.