Miracle-dz/UniFAR-FTUs huggingface dataset:
Phase noise testing of single chip TV tuners

Phase noise testing for TV tuners is time consuming and expensive because of the great number of TV channels. This paper presents a hierarchical simulation method for a complex single chip TV tuner. Based on the simulation results, an effective and economic test method is proposed to save the test application time. This method determines the most effective channels and frequencies to test so the number of phase noise measurements is reduced. Experimental results on commercial chips show that our proposed method reduces the test time by a factor often without test escapes.
Cut-in maneuver recognition and behavior generation using Bayesian networks and fuzzy logic

In this paper a method for recognizing the cutin maneuver using a Bayesian network is proposed, followed by an evaluation of the degree of danger of the situation. An adequate behavior of the ego-vehicle is generated using a fuzzy logic controller. The task of this controller is to provide appropriate actions such as to help prevent a possible collision caused by a dangerous cut-in maneuver, by issuing an emergency brake, as well as to assure a high degree of comfort to the vehicle passengers, i.e. to avoid triggering false emergency brakes. The fuzzy controller provides qualitative and quantitative values, for a HMI and possible actuators, respectively. The qualitative values provide the appropriate response of the ego-vehicle for avoiding an imminent collision, in the form of passive warnings. The quantitative values are the adequate brake values, which should be used by actuators, in order to avoid a collision avoidance maneuver. The solution is based on the environment information provided by a stereovision perception system. The experiments show the solution is able to reason and make decision using the uncertain sensorial data, providing an overall good performance.
Branch Prediction by Checking Loop Terminal Conditions

Branch prediction accuracy is a crucial parameter in determining the amount of parallelism that can be exploited. Current advanced branch prediction techniques are able to attain correct predictions in most cases. Conventionally, the profiling information is used to predict the behavior of a branch. However, they are unsuccessful in predicting specific conditions like branch loop terminations, arrays e.t. c. This hinders them from achieving full accuracy. Neural Networks have an inherent capability to analyze inputs to form meaningful relationships among them. This property of neural networks makes them useful to identify program elements that constitute a branch. In this paper, we investigate further and propose an algorithm to predict correctly specific loop conditions using neural networks which can increase the efficiency beyond the rates reported by existing schemes.
A new binary similiraty metric for two LSB steganalysis

In this paper, a novel steganalytic method is proposed for 2LSB (Two Least Significant Bits) steganography. This method is original from two perspectives: it is based on the application of Zipf's law as an analysis tool for images, and it proposes a new binary similarity metric (BSMC) between the seventh and eighth bit planes. Because the hidden message leaves statistical artifacts on the cover image, the embedding process often decreases the correlation existing in bit planes of an image to some extent. Therefore, Zipf's law is used to compute the binary similarity metric between curves of Zipf of the cover and stego images, which is based on the distribution of patterns of the 7th and 8th bit planes. This method can not only detect the presence of secret messages embedded using 2LSB embedding, but it can also be easily generalized to multi least significant bit embedding (MLSB).
STAGGER: Improving Channel Utilization for Convergecast in Wireless Sensor Networks

Channel utilization for wireless sensor networks is far from efficient, especially for convergecast in which multiple nodes are sending packets to a receiver. In this paper, we analyze the channel utilization when multiple nodes contend for the channel in convergecast and show that channel utilization can be improved by accumulating packets on each node. However, the number of accumulated packets should be carefully determined. Otherwise, the system performance may not be improved or even be degraded, e.g., incurring additional packet delay. Based on the analysis result, we present STAGGER to achieve channel utilization improvement while guarantee the worst case performance. We implement STAGGER in TinyOS 2.1 and evaluate its performance on TelosB nodes. STAGGER only uses local information to determine the number of accumulated packets without incurring additional overhead. It adopts CSMA at the low level and preserves its nice properties, e.g., fairness. The experimental results show that the design can significantly improve the per-hop throughput and reduce packet loss ratio under high traffic rate.
$L^p$-bounds on spectral clusters associated to polygonal domains

We look at the $L^p$ bounds on eigenfunctions for polygonal domains (or more generally Euclidean surfaces with conic singularities) by analysis of the wave operator on the flat Euclidean cone $C(\mathbb{S}^1_\rho) := \mathbb{R}_+ \times \left(\mathbb{R} \big/ 2\pi\rho \mathbb{Z}\right)$ of radius $\rho > 0$ equipped with the metric $h(r,\theta) = d r^2 + r^2 \, d\theta^2$. Using explicit oscillatory integrals and relying on the fundamental solution to the wave equation in geometric regions related to flat wave propagation and diffraction by the cone point, we can prove spectral cluster estimates equivalent to those in works on smooth Riemannian manifolds.
MASE1 and MASE2: Two Novel Integral Membrane Sensory Domains

Escherichia coli proteins YegE and YaiC contain N-terminal integral membrane regions, followed by the putative diguanylate cyclase (GGDEF, DUF1) domains. The membrane domains of these proteins, named MASE1 (membrane-associated sensor) and MASE2, respectively, were found in other bacterial signaling proteins, such as histidine kinases (MASE1) and an adenylate cyclase (MASE2). Although the nature of the signals sensed by MASE1 and MASE2 is still unknown, MASE1-containing receptors appear to play important roles in bacteria, including iron and/or oxygen sensing by hemerythrine-containing proteins in the sulfate-reducing bacterium Desulfovibrio vulgaris.
IL-17A and TNF-α Increase the Expression of the Antiapoptotic Adhesion Molecule Amigo-2 in Arthritis Synoviocytes

Rheumatoid arthritis (RA) is a chronic inflammatory disorder, characterized by a persistent immune cell infiltrate in the synovium accompanied by high levels of inflammatory mediators and synovial hyperplasia. Despite significant therapeutic advances, RA remains an important unmet medical need. To discover potential new genes controlling inflammation and apoptosis in synoviocytes, genes induced by the two pro-inflammatory cytokines, tumor necrosis factor α (TNF-α) and interleukin 17A (IL-17A), were systematically searched. We identified Amphoterin-induced gene and ORF 2 (Amigo-2), a novel antiapoptotic adhesion molecule, as synergistically upregulated by the IL-17A/TNF combination specifically in RA synoviocytes. In addition, when RA synoviocytes were cocultured with immune cells, Amigo2 expression was significantly increased in both fibroblasts and immune cells. This induction persisted in RA synoviocytes even after the removal of the immune cells. Amigo2 induction was ERK-dependent and on the contrary, inhibited by JNK. Furthermore, Amigo2 expression levels correlated with apoptosis of the cells when exposed to the proapoptotic agent cadmium (Cd). Interestingly, exposure of the cells to HMGB1 in inflammatory conditions increased synergistically Amigo2 expression and significantly reduced Cd-mediated cellular toxicity. Our findings support a model whereby cell–cell contact with immune cells and exposure to the combination of both inflammatory cytokines and HMGB1 in the joints of RA patients increases Amigo2 expression in synoviocytes in an ERK-dependent manner which, in turn, enhances cellular adhesion and promotes cell survival and cellular proliferation.
Torque improvement in IPMSM for Electric vehicle application

The high power density, efficiency, and wide constant power operating region of an Interior Permanent Magnet Synchronous Motor (IPMSM) makes it the best choice for driving an Electric vehicle. But IPMSM has a pulsating torque which is inherent in its design. Fractional slot concentrated windings are used to reduce the cogging torque. But to have maximum use of the flux produced by the permanent magnets, a very small air gap is used. This introduces further ripples in torque. An IPMSM suitable for Electric vehicle application is designed in RMxprt. The effect of slot opening width on cogging torque is investigated in Maxwell 2D. The machine is coupled in Simplorer software to drive an Electric vehicle model. A rotor shaping technique with Inverse Cosine Shape (ICS) around each pole is used to modify the air gap flux density into sinusoidal shape and to reduce the cogging torque and torque ripple. Inverse cosine with third harmonic injected shape is used in rotor to enhance the average torque of ICS IPMSM. Electromagnetic performance, cogging torque, average torque, and torque ripple for conventional, ICS and ICS with third harmonic injected machines is investigated. The machine is further optimized using Genetic Algorithm.
Neurotrophic factors in the testis

Neurotrophic factors, interacting with neurons to affect their growth, are a subset of the polypeptide growth factors. There is increasing evidence for a broader physiological role of these factors which includes effects on a variety of nonneuronal tissues. Among the cell systems, where neurotrophic factors have been hypothesized to exert local nonneurotrophic activities, the testis is of particular interest. This organ represents a complex biological unit which requires the concerted action of very diverse cell types interacting with each other in order to ensure correct spermatogenesis. As signaling molecules that may be involved in these intercellular communication events, various neurotrophic factors have attained considerable scientific attention. This article intends to summarize the presently available data on the distribution and possible local activities of neurotrophic factors and their receptors in testicular cells and provides further information on local expression sites of some of these factors in the human testis. Biomedical Reviews 1999; 10: 25-30.
Deep feature representations for high-resolution remote sensing scene classification

Learning powerful feature representations is of great importance in order to improve the accuracy of high-resolution remote sensing imagery (HRRSI) scene classification. Generally, traditional methods mainly focus on low-level features. Though these feature representations can achieve satisfactory performance to some extent, the performance improvement is small. More importantly, these low-level feature representations are hand-crafted features, and it is difficult to design such a holistic feature representation. Recently, convolutional neural networks (CNN) has achieved remarkable performance on several natural benchmarks. In this paper, we investigate the extraction of the deep feature representations based on the pre-trained CNN architectures for scene classification tasks. More specially, we first evaluate the pre-trained CNN architectures on a public scene dataset and then fine-tune the CNN that performs best on the dataset using the target HRRSI dataset to learn dataset-specific features. Extensive experiments on two publicly available scene datasets indicate that the deep feature representations can achieve state-of-the-art performance.
Watershed Segmentation of Remotely Sensed Images Based on a Supervised Fuzzy Pixel Classification

Remotely sensed images are more and more precise (spatial resolution under 1 meter). For these images, objects of interest contains several pixels. Generally a segmentation method is used to cluster pixels that belong to the same objects before classification. The quality of such a segmentation method is crucial to achieve good clasification results. In this paper, a new segmentation method is proposed which aims to improve the classical watershed segmentation method based on multispectral gradient. The proposed method uses some labeled samples with classes of interest to induce a new dissimilarity between pixels which defines a new representation space to be used.
Wireless Measurement of Elastic and Plastic Deformation by a Metamaterial-Based Sensor

We report remote strain and displacement measurement during elastic and plastic deformation using a metamaterial-based wireless and passive sensor. The sensor is made of a comb-like nested split ring resonator (NSRR) probe operating in the near-field of an antenna, which functions as both the transmitter and the receiver. The NSRR probe is fixed on a standard steel reinforcing bar (rebar), and its frequency response is monitored telemetrically by a network analyzer connected to the antenna across the whole stress-strain curve. This wireless measurement includes both the elastic and plastic region deformation together for the first time, where wired technologies, like strain gauges, typically fail to capture. The experiments are further repeated in the presence of a concrete block between the antenna and the probe, and it is shown that the sensing system is capable of functioning through the concrete. The comparison of the wireless sensor measurement with those undertaken using strain gauges and extensometers reveals that the sensor is able to measure both the average strain and the relative displacement on the rebar as a result of the applied force in a considerably accurate way. The performance of the sensor is tested for different types of misalignments that can possibly occur due to the acting force. These results indicate that the metamaterial-based sensor holds great promise for its accurate, robust and wireless measurement of the elastic and plastic deformation of a rebar, providing beneficial information for remote structural health monitoring and post-earthquake damage assessment.
SINGING PORTUGUESE NASAL VOWELS: PRACTICAL STRATEGIES FOR MANAGING NASALITY IN BRAZILIAN ART SONGS

SINGING PORTUGUESE NASAL VOWELS: PRACTICAL STRATEGIES FOR MANAGING NASALITY IN BRAZILIAN ART SONGS The articulation of Portuguese nasalized vowels poses some articulatory problems accompanied by negative acoustic effects for the performance of Brazilian art songs. The main objective was to find strategies that permit the singer conciliate an idiomatic pronunciation of these vowels with a well-balanced resonance, a desirable quality in classical singing. In order to devise these strategies, the author examined sources dealing with nasalized vowels from varied perspectives: acoustic properties of vowel nasalization, phonetic and phonological aspects of Brazilian Portuguese (BP), historical views on nasality in singing, and recent vocal pedagogy research. In addition to the overall loss of sonority, the main effect of nasalization is felt mainly in the first formant (F1) region of oral vowels, due to the introduction of nasal formants and antiformants, and to shifts in the tongue posture. Several sources report the existence of a nasality contour in BP, by which a nasalized vowel starts with an oral phase and transitions gradually to a nasal phase. The author concludes that the basic approach to sing nasalized vowels in BP is (1) to find the tongue posture corresponding to the oral vowel congener (the “core vowel”), and (2) to adjust the nasality contour in such a way that the oral portion remains prominent in order to keep the resonance balance consistent during the emission of the vowel. Once the core vowel is determined, standard vowel modification choices can be made according to voice type and the musical context in which the vowel is being sung. Some challenging excerpts from Brazilian art songs are examined, with suggestions for the application of the discussed strategies.
Corin, atrial natriuretic peptide and hypertension.

sure are increased, ANP is secreted from the heart. It binds to its receptor in the kidney and blood vessels, and promotes salt excretion, lowers blood volume and relaxes the vessel. This endocrine mechanism links the heart and kidney in maintaining a fine balance of electrolytes and body fluid. The physiological importance of the ANP pathway has been shown in many animal studies. In mice, for example,ANPdeficiencycauseshypertension[9],whereasANP overexpression results in hypotension [10]. The hypertension in ANP null mice is sensitive to high dietary salts, indicating that ANP is critical in regulating the response to salt in vivo. The heart also makes another peptide, brain or B-type natriuretic peptide (BNP), which has similar natriuretic and diuretic activity to that of ANP. BNP null mice, however, had normal blood pressure but developed cardiac fibrosis [11], suggesting that the physiological function of BNP may differ from that of ANP. In humans, several single nucleotide polymorphisms (SNPs) have been found in the ANP gene. One of them (-C664G) is located in the promoter region. Genetic studies showed that the -664G allele was associated with low plasma ANP levels, high blood pressure and left ventricular hypertrophy in patients [12,13]. Most recently, a frameshift mutation in the ANP gene was reported in a family of European ancestry [14]. This mutation abolished the stop codon, creating a mutant molecule with 12 extra amino acids at the C-terminus of ANP. The members of this family with the mutant gene developed atrial fibrillation. Some of them also had hypertension that required medical intervention. In an animal model, the mutant ANP was shown to shorten monophasic action potential in cardiomyocytes, which may explain the phenotype of atrial fibrillation in the patients.
The Spectral Energy Distribution of Quiescent Black Hole X-Ray Binaries: New Constraints from Spitzer

Among the various issues that remain open in the field of accretion onto black hole X-ray binaries (BHBs) is the question of how gas accretes at very low Eddington ratios, in the so-called quiescent regime. While there is general agreement that X-rays are produced by a population of high-energy electrons near the BH, there is controversy concerning the modeling of the contributions of inflowing versus outflowing particles and their relative energy budget. Recent Spitzer observations of three quiescent BHBs have shown evidence for excess emission with respect to the Rayleigh-Jeans tail of the companion star between 8-24 μm. We suggest that synchrotron emission from a partially self-absorbed outflow might be responsible for the observed mid-IR excess, in place of, or in addition to, thermal emission from circumbinary material. If so, then the jet synchrotron luminosity, integrated from radio to near-IR frequencies, exceeds the measured 2-10 keV luminosity by a factor of a few in these systems. In turn, the mechanical power stored in the jet exceeds the bolometric X-ray luminosity by at least 4 orders of magnitude. We compile the broadband spectral energy distribution (SED) of A0620-00, the lowest Eddington-ratio stellar mass BH with a known radio counterpart, by means of simultaneous radio, optical, and X-ray observations, and the archival Spitzer data. We are able to fit the SED of A0620-00 with a maximally jet-dominated model, in which the radio through the soft X-rays are dominated by synchrotron emission, while the hard X-rays are dominated by inverse Compton at the jet base. The fitted parameters land in a range of values reminiscent of the Galactic center supermassive black hole Sgr A*. Most notably, the inferred ratio of the jet acceleration rate to local cooling rates is 2 orders of magnitude weaker than higher luminosity, hard-state sources.
Low complexity user and spatial detection by using AD8313 evaluation board

In this paper, a relatively low cost, simple user and spatial detection with AD8313 evaluation board is described. 16-element linear array antennas are designed in order to operate at frequency of 457 MHz for the rural communication network. A testing-bed with simple arrangement is setup in order to validate the proposed method. The array antennas are used as radar and enclosed a wide scanning angle of 120 degree via a mechanical motor. And, the AD8313 evaluation board is use to convert the radio frequency signal to a direct current output. The outputs of the board are measured with an oscilloscope.
Noncommutative geometry based on commutator expansions

We develop an approach to noncommutative algebraic geometry ``in the perturbative regime" around ordinary commutative geometry. Let R be a noncommutative algebra and A=R/[R,R] its commutativization. We describe what should be the formal neighborhood of M=Spec(A) in the (nonexistent) space Spec(R). This is a ringed space (M,O) where O is a certain sheaf of noncommutative rings on M. Such ringed spaces can be glued together to form more global objects called NC-schemes. We are especially interested in NC-manifolds, NC-schemes for which the completion of O at every point of M is isomorphic to the algebra of noncommutative power series (completion of the free associative algebra). An explicit description of the simplest NC-manifold, the affine space, is given by using the Feynman-Maslov calculus of ordered operators. We show that many familiar algebraic varieties can be naturally enlarged to NC-manifolds. Among these are all the classical flag varieties and all the smooth moduli spaces of vector bundles.