Miracle-dz/UniFAR-FTUs huggingface dataset:
Compressive Sensing Algorithms for Signal Processing Applications: A Survey

In digital signal processing (DSP), Nyquistrate sampling completely describes a signal by exploiting its bandlimitedness. Compressed Sensing (CS), also known as compressive sampling, is a DSP technique efficiently acquiring and reconstructing a signal completely from reduced number of measurements, by exploiting its compressibility. The measurements are not point samples but more general linear functions of the signal. CS can capture and represent sparse signals at a rate significantly lower than ordinarily used in the Shannon’s sampling theorem. It is interesting to notice that most signals in reality are sparse; especially when they are represented in some domain (such as the wavelet domain) where many coefficients are close to or equal to zero. A signal is called K-sparse, if it can be exactly represented by a basis, , and a set of coefficients , where only K coefficients are nonzero. A signal is called approximately K-sparse, if it can be represented up to a certain accuracy using K non-zero coefficients. As an example, a K-sparse signal is the class of signals that are the sum of K sinusoids chosen from the N harmonics of the observed time interval. Taking the DFT of any such signal would render only K non-zero values . An example of approximately sparse signals is when the coefficients , sorted by magnitude, decrease following a power law. In this case the sparse approximation constructed by choosing the K largest coefficients is guaranteed to have an approximation error that decreases with the same power law as the coefficients. The main limitation of CS-based systems is that they are employing iterative algorithms to recover the signal. The sealgorithms are slow and the hardware solution has become crucial for higher performance and speed. This technique enables fewer data samples than traditionally required when capturing a signal with relatively high bandwidth, but a low information rate. As a main feature of CS, efficient algorithms such as -minimization can be used for recovery. This paper gives a survey of both theoretical and numerical aspects of compressive sensing technique and its applications. The theory of CS has many potential applications in signal processing, wireless communication, cognitive radio and medical imaging.
Experimentally Validated Dynamic Model for a Hybrid Cascade System for Solar Heating and Cooling Applications

This paper presents the dynamic modelling of a hybrid cascade chiller for solar cooling in industrial applications driven by Fresnel solar thermal collectors. The chiller comprises an adsorption module, which is directly connected to the bottoming vapor compression chiller. This cascade configuration allows enhancing the overall electric COP, since the adsorption module is operated to dissipate the heat rejected by the vapor compression chiller, thus reducing the condensation temperature quite below the ambient temperature. The model was implemented in Dymola/Modelica, allowing describing heat and mass transfer phenomena inside each component. The complete model was then validated against experimental data obtained on a cascade chiller prototype at the CNR ITAE lab. Finally, a reference daily simulation was performed to evaluate the ability of the developed chiller in providing cooling energy to a typical industrial application.
Interstitial fluid pressure correlates with intravoxel incoherent motion imaging metrics in a mouse mammary carcinoma model

The effective delivery of a therapeutic drug to the core of a tumor is often impeded by physiological barriers, such as the interstitial fluid pressure (IFP). There are a number of therapies that can decrease IFP and induce tumor vascular normalization. However, a lack of a noninvasive means to measure IFP hinders the utilization of such a window of opportunity for the maximization of the treatment response. Thus, the purpose of this study was to investigate the feasibility of using intravoxel incoherent motion (IVIM) diffusion parameters as noninvasive imaging biomarkers for IFP. Mice bearing the 4T1 mammary carcinoma model were studied using diffusion‐weighted imaging (DWI), immediately followed by wick‐in‐needle IFP measurement. Voxelwise analysis was conducted with a conventional monoexponential diffusion model, as well as a biexponential model taking IVIM into account. There was no significant correlation of IFP with either the median apparent diffusion coefficient from the monoexponential model (r = 0.11, p = 0.78) or the median tissue diffusivity from the biexponential model (r = 0.30, p = 0.44). However, IFP was correlated with the median pseudo‐diffusivity (Dp) of apparent vascular voxels (r = 0.76, p = 0.02) and with the median product of the perfusion fraction and pseudo‐diffusivity (fpDp) of apparent vascular voxels (r = 0.77, p = 0.02). Although the effect of IVIM in tumors has been reported previously, to our knowledge, this study represents the first direct comparison of IVIM metrics with IFP, with the results supporting the feasibility of the use of IVIM DWI metrics as noninvasive biomarkers for tumor IFP. Copyright © 2011 John Wiley & Sons, Ltd.
Validation environment of UML2 IOD based on hierarchical coloured Petri nets

A new interaction diagram, called Interaction Overview Diagram or IOD, was introduced in the second generation of UML. It defines interactions through a variant of activity diagrams in a way that promotes overview of the control flow. But its semantics remains unclear thus requiring formalisation tasks. We propose in this paper a validation environment for UML IODs. So we first formalise their semantics by translation to the semantics domain of Hierarchical Coloured Petri Nets, or HCPNs for short. The derived HCPN models are afterwards analysed by means of the model-checker CPNtools. The analysis tackles the simulation, verification and validation aspects. It especially focuses on the validation of system properties written by the UML designer. The properties are expressed in OCL and then automatically translated into ASKCTL temporal logic. A case study of an ATM system illustrates the approach.
Feline Panleukopenia Virus Is Not Associated With Myocarditis or Endomyocardial Restrictive Cardiomyopathy in Cats

Canine parvovirus-2 (CPV-2) is nearly indistinguishable from feline panleukopenia virus (FPV) and is a well-known cause of viral myocarditis in young puppies; however, it is not known whether either FPV or CPV-2 naturally infects feline cardiomyocytes and causes myocarditis. Endomyocarditis (EMC) and left ventricular endomyocardial fibrosis (LVEF), clinically known as “endomyocardial restrictive cardiomyopathy,” are important feline heart diseases suspected to have an infectious etiology. A continuum is suggested with EMC representing the acute reaction to an unknown infectious agent and LVEF the chronic manifestation of repair. The purpose of this study was to determine (1) whether there is natural parvovirus infection of the feline myocardium and (2) whether parvoviral infection is associated with feline EMC and/or LVEF. In a retrospective study, polymerase chain reaction and sequencing for the parvovirus VP1/2 gene was performed on archived heart tissue from cats with endomyocardial disease and controls. Similar methods were used prospectively on myocardial tissues from shelter-source kittens. Although 8 of 36 (22%; 95% confidence interval [CI], 11%–40%) shelter kittens had parvoviral DNA in myocardial tissue, VP1/2 DNA was not detected in 33 adult cases or 34 controls (95% CI, 0% to ∼11%). These findings were confirmed by in situ hybridization: adult cats did not have detectable parvovirus DNA, although rare intranuclear signal was confirmed in 7 of 8 shelter-source kittens. In kittens, parvovirus was not significantly associated with myocarditis, and in situ hybridization signal did not colocalize with inflammation. Although infection of cardiomyocytes was demonstrated in kittens, these data do not support a role for parvovirus in EMC-LVEF.
Using Dark Fiber to Displace Diesel Generators

Cloud providers and other data center operators are using geo-distributed data centers. But these data centers largely continue to employ the same designs as were appropriate for single data centers. These designs are wasteful because they do not take full advantage of geo-distribution. Geo-redundancy can reduce other redundancy at multiple intermediate layers in individual data centers and decrease costs. We discuss options for changing infrastructure design to realize such savings. Our proposal opens up an exciting and novel area of investigation into the design of software that can effectively leverage such platforms.
Stretchable, Transparent, Ultrasensitive, and Patchable Strain Sensor for Human-Machine Interfaces Comprising a Nanohybrid of Carbon Nanotubes and Conductive Elastomers.

UNLABELLED Interactivity between humans and smart systems, including wearable, body-attachable, or implantable platforms, can be enhanced by realization of multifunctional human-machine interfaces, where a variety of sensors collect information about the surrounding environment, intentions, or physiological conditions of the human to which they are attached. Here, we describe a stretchable, transparent, ultrasensitive, and patchable strain sensor that is made of a novel sandwich-like stacked piezoresisitive nanohybrid film of single-wall carbon nanotubes (SWCNTs) and a conductive elastomeric composite of polyurethane (PU)-poly(3,4-ethylenedioxythiophene) polystyrenesulfonate ( PEDOT PSS). This sensor, which can detect small strains on human skin, was created using environmentally benign water-based solution processing. We attributed the tunability of strain sensitivity (i.e., gauge factor), stability, and optical transparency to enhanced formation of percolating networks between conductive SWCNTs and PEDOT phases at interfaces in the stacked PU-PEDOT:PSS/SWCNT/PU-PEDOT:PSS structure. The mechanical stability, high stretchability of up to 100%, optical transparency of 62%, and gauge factor of 62 suggested that when attached to the skin of the face, this sensor would be able to detect small strains induced by emotional expressions such as laughing and crying, as well as eye movement, and we confirmed this experimentally.
Endocrine factors related to changes in total peripheral vascular resistance after treatment of thyrotoxic and hypothyroid patients.

OBJECTIVE Total peripheral vascular resistance (TPR) decreases in thyrotoxicosis and increases in hypothyroidism. Several mechanisms may be involved, including adaptation to changes in heat production and direct non-genomic effects of tri-iodothyronine (T3) on vascular smooth muscle cells. The aim of this study was to see if changes in TPR are related to changes in plasma concentrations of the endothelial hormones adrenomedullin and endothelin-1 as well as other hormones affecting vasculature. DESIGN A prospective study. SUBJECTS Eleven hypothyroid patients (pretreatment: thyroid-stimulating hormone (TSH) 68 (38-201) mU/l, T3 0.7 (0.35-1.5) nmol/l, fT4 3.0 (2.0-5.9) pmol/l, median (range)) and 14 with hyperthyroidism (pretreatment: TSH 0.02 (<0.01-0.06) mU/l, T3 6.4 (2.3-13.0) nmol/l, fT4 56.1 (22.9-70.0) pmol/l) were studied before treatment and 3 months after reaching the euthyroid state. Blood collection was carried out simultaneously with the recording of finger arterial pressure (FINAP). Cardiac output and TPR were derived from stroke volume computations by modelling flow from the FINAP signal. RESULTS Thyroid-function tests of hypothyroid and thyrotoxic patients did not differ after restoration of the euthyroid state. TPR, expressed in arbitrary units (AU), decreased after correction of hypothyroidism (from 1.32+/-0.65 to 0.96+/-0.36 AU, P=0.04) and increased after correction of hyperthyroidism (from 0.75+/-0.18 to 1.10+/-0.35 AU, P=0.007). Adrenomedullin concentrations did not change during the transition from the hypothyroid state 3.2(0.9-11.0) pmol/l to the euthyroid state 4.9(0.9-8.6) pmol/l, but decreased after treatment of hyperthyroidism, from 5.2(0.9-11.0) pmol/l to 2.2(0.9-5.4) pmol/l. Plasma endothelin-1 was undetectable in all samples. Changes in TPR upon treatment correlated with log DeltafT4 (r=-0.65, P=0.001), log DeltaT3, (r=-0.57, P=0.006), Delta noradrenaline (r=0.54, P=0.02) and Delta ANP (atrial natriuretic peptide) (r=-0.59, P=0.004). Multiple linear regression analysis indicated that only T3 was an independent determinant of TPR. Changes in T3 accounted for 46% of the variability in the changes in TPR. CONCLUSIONS TPR is reduced in thyrotoxicosis and increased in hypothyroidism. Restoration of the euthyroid state normalizes TPR. Changes in TPR are not related to plasma adrenomedullin concentrations, but 46% could be explained by changes in T3. Altered ANP secretion and adrenergic tone may contribute to the T3-induced changes in TPR.
Distinct subcellular localization of alternative splicing variants of EFA6D, a guanine nucleotide exchange factor for Arf6, in the mouse brain

EFA6D (guanine nucleotide exchange factor for ADP‐ribosylation factor 6 [Arf6]D) is also known as EFA6R, Psd3, and HCA67. It is the fourth member of the EFA6 family with guanine nucleotide exchange activity for Arf6, a small guanosine triphosphatase (GTPase) that regulates endosomal trafficking and actin cytoskeleton remodeling. We propose a classification and nomenclature of 10 EFA6D variants deposited in the GenBank database as EFA6D1a, 1b, 1c, 1d, 1s, 2a, 2b, 2c, 2d, and 2s based on the combination of N‐terminal and C‐terminal insertions. Polymerase chain reaction analysis showed the expression of all EFA6D variants except for variants a and d in the adult mouse brain. Immunoblotting analysis with novel variant‐specific antibodies showed the endogenous expression of EFA6D1b, EFA6D1c, and EFA6D1s at the protein level, with the highest expression being EFA6D1s, in the brain. Immunoblotting analysis of forebrain subcellular fractions showed the distinct subcellular distribution of EFA6D1b/c and EFA6D1s. The immunohistochemical analysis revealed distinct but overlapping immunoreactive patterns between EFA6D1b/c and EFA6D1s in the mouse brain. In immunoelectron microscopic analyses of the hippocampal CA3 region, EFA6D1b/c was present predominantly in the mossy fiber axons of dentate granule cells, whereas EFA6D1s was present abundantly in the cell bodies, dendritic shafts, and spines of hippocampal pyramidal cells. These results provide the first anatomical evidence suggesting the functional diversity of EFA6D variants, particularly EFA6D1b/c and EFA6D1s, in neurons. J. Comp. Neurol. 524:2531–2552, 2016. © 2016 Wiley Periodicals, Inc.
Synthesis of a 2''-Deoxy-β-GalCer

Structural studies of ternary complexes of CD1d/glycosyl ceramides/iNKT cells and CD1d/sulfatide/sulfatide reactive Type II NKT cells have shown how the polar moieties on the glycolipids interact with both the antigen presenting protein (CD1d) and the T cell receptors. However, these structures alone do not reveal the relative importance of these interactions. This study focuses on the synthesis of the previously unknown 2''-deoxy-β-galactosyl ceramide 2. This glycolipid is also evaluated for its ability to stimulate iNKT cells and sulfatide-reactive Type II NKT cells.
An Interdisciplinary Approach to Teachers’ Voice Disorders and Psychosocial Working Conditions

Objectives: The goals of this epidemiological paper are focused on studying teachers’ vocal complaints, their voice pattern, and the impact of voice disorders on psychosocial working conditions. Patients: A representative stratified random sample of 282 teachers from kindergartens and elementary schools was studied. Two types of self-report questionnaires were applied: an inquiry about teachers’ occupational voice profile, and the adapted Spanish version of the Copenhagen Psychosocial Questionnaire (ISTAS-21). Pearson’s χ2 test was performed to search for statistical associations. Results: 62.7% of subjects were experiencing occupational voice disorders; these teachers showed significantly worse psychosocial conditions than their healthy voice colleagues. Conclusions: Occupational voice disorders affect more than 60% of teachers and have an impact on their psychosocial working conditions. Interdisciplinary work is essential to shed light on these multifactor mechanisms and effects.
Multi-feature Error Detection in Spoken Dialogue Systems

The present paper evaluates the role selected features and feature combinations play for error detection in spoken dialogue systems. We investigate the relevance of various, readily available features extracted from a corpus of dialogues with a train timetable information system, using RIPPER, a rule-inducing machine learning algorithm. The learning task consists of the identification of communication problems arising in either the previous turn or the current turn of the dialogue. Previous experiments with our corpus have shown that combining dialogue history and word-graph features is beneficial for detecting errors (in particular in the previous turn). Other researchers have reported that combining prosodic and ASR characteristics is helpful (primarily in the current turn). In this paper, we investigate the usefulness of large-scale combinations of these features for the above two tasks. We show that we are unable to reproduce the benefits of prosodic features for learning problematic situations, even though the overall prosodic trends in our corpus are similar to those earlier reported on. Moreover, the best results are obtained using just minimal combinations of two sources of information.
Preface Organising Committee

In text processing, most information carrying strings, or terms, are multi-word. Given this, the challenge in corpus-based term extraction is three-fold: (1) assigning the correct constituent structure of the multi-word term, (2) determining the meaning of constituents, and (3) interpreting the relationship between the constituents. Thus, we worked applied the head-modifier principle to Chinese term extraction as Chinese makes extensive use of compounding, and is right headed. In this paper, we explore the first of the three challenges by addressing what is known in the literature as bracketing ambiguities: a multi-word term containing more than two constituents can be assigned more than one constituent structure. We tested two techniques already used for English bracketing ambiguities to resolve Chinese ambiguities, the adjacency model and the dependency model. The (largely) positive results show that linguistic universal principles mean reusability of language specific resources for other languages.
Modelling and Simulation of Laser Welded Joints of Reinforced PP and PC Plastics

Welding of composites decreases their material strength. Proper evaluation of FEM simulations is necessary for correct design and safety factor determination. Neat and reinforced PP and PC specimens were measured on a testing machine to obtain their material properties. Experimental tensile curves were used as inputs in FEM simulations. 15 combinations of specimen were welded on laser work machine and afterwards the welded joint strength was measured on the testing machine. The results of shear tests and FEM simulations are compared in this paper. Also the influence of fiber presence in composites on welded joint strength is discussed. At the end suggestions for safe machinery design of laser welded reinforced composites are given.
A fuzzy operator based bat algorithm for cloud service composition

Cloud manufacturing service composition is an important issue in the cloud manufacturing mode. Because the number of services is large scale, the problem is NP hard. The conventional algorithm cannot get the satisfactory solution in the limited time. Therefore, the heuristic algorithms are always used to solve the problem. Although they can give a feasible solution in a limited time, the precision of the solution is still to be improved. A Fuzzy operator based Bat algorithm FBAT is presented to deal with the cloud service composition problem. In FBAT, the fuzzy encoding and decoding operations are put forward to replace the original real number coding and decoding operations in the bat algorithm. In addition, a virtual bat is introduced to utilise the historical useful information to guide the flying direction of bats, which helps improve the convergence speed of the algorithm. Experiments show that the proposed algorithm is promising in terms of precision, compared with the particle swarm optimisation and differential evolution algorithms.
IEEE 802.11: Wireless LANs from a to n

From its inception in 1980, the IEEE 802 committee has led the way in developing LAN (local area network) standards. The committee's work on wireless LANs (WLANs) began in 1987 within the TEEE 802.4 working group. Developing an ISM (industrial, scientific, and medical)-based WLAN using the equivalent of a token-passing bus media access control (MAC) protocol was the committee's initial goal. After some work, the committee decided that a token-bus-controlled radio medium would cause inefficient use of the radio frequency spectrum. In 1990, the committee formed a new working group, IEEE 802.11, specifically devoted to WLANs, with a charter to develop a MAC protocol and physical-medium specification. Since then, demand for WLANs, at different frequencies and data rates, has exploded. Keeping pace with this demand, the IEEE 802.11 working group has issued an ever-expanding list of standards.
Word Confidence Estimation for SMT N-best List Re-ranking

This paper proposes to use Word Confidence Estimation (WCE) information to improve MT outputs via N-best list reranking. From the confidence label assigned for each word in the MT hypothesis, we add six scores to the baseline loglinear model in order to re-rank the N-best list. Firstly, the correlation between the WCE-based sentence-level scores and the conventional evaluation scores (BLEU, TER, TERp-A) is investigated. Then, the N-best list re-ranking is evaluated over different WCE system performance levels: from our real and efficient WCE system (ranked 1st during last WMT 2013 Quality Estimation Task) to an oracle WCE (which simulates an interactive scenario where a user simply validates words of a MT hypothesis and the new output will be automatically re-generated). The results suggest that our real WCE system slightly (but significantly) improves the baseline while the oracle one extremely boosts it; and better WCE leads to better MT quality.
An analytical approach to evaluate service coverage in slow frequency-hopping mobile radio systems

The performance of a time-division multiple-access mobile radio system adopting slow frequency hopping is analyzed by following an original procedure that allows the evaluation of thermal noise and fast fading (e.g., Rayleigh) effects on block-coded transmission with nonideal interleaving. Starting from this approach, service coverage can be analytically evaluated when the "slow" disturbances affecting the transmission are fixed. The method proposed is able to take several impairments and parameters into account, such as shadowing and discontinuous transmission. The experimental results confirmed the validity of the theoretical approach.