Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy logic torque ripple reduction by turn-off angle compensation for switched reluctance motors

A fuzzy-logic-based turn-off angle compensator for torque ripple reduction in a switched reluctance motor is proposed. The turn-off angle, as a complex function of motor speed and current, is automatically changed for a wide motor speed range to reduce torque ripple. Experimental results are presented that show ripple reduction when the turn-off angle compensator is used.
Synthesis for mixed CMOS/PTL logic (poster paper)

High noise immunity and level-restoring capabilities of static CMOS gates, combined with small area and low power of PTL cells, make a mixed CMOS/PTL design style an ideal alternative to the all-CMOS technology. However, the synthesis of mixed CMOS/PTL circuits imposes a great challenge to the existing synthesis methodology. Neither traditional techniques based on algebraic factorization nor methods based on direct BDD mapping [1] [2] [3] are applicable to this new circuit style. We have recently proposed a new BDD-based logic optimization method for static CMOS [4]. It is based on iterative BDD decomposition using various dominators which correspond to decomposable BDD structures leading to AND, OR, XOR and MUX decompositions. Synthesis results show that the method is very efficient for both AND/ORand XOR-intensive functions. Since PTL structures can be easily identified on a BDD, our method can be readily extended to perform logic decomposition leading to mixed CMOS/PTL logic implementation. In contrast to other PTL synthesis techniques, based on direct BDD mapping, our method is not limited to decomposition onto PTLs only; its logic decomposition and optimization is driven by the capabilities of both the static CMOS and PTL logic. Our BDD decomposition method can also account for various parameters associated with circuit performance, thus avoiding drawbacks of direct BDD mapping-based synthesis, such as large fanouts and long transistor chains. The bulk of our BDD decomposition theory has been published in [4]. Table I summarizes the different types of BDD decompositions available; it can be seen that all types of atomic decompositions and their corresponding BDD structures can be easily identified.
Implicit feature detection for sentiment analysis

Implicit feature detection is a promising research direction that has not seen much research yet. Based on previous work, where co-occurrences between notional words and explicit features are used to find implicit features, this research critically reviews its underlying assumptions and proposes a revised algorithm, that directly uses the co-occurrences between implicit features and notional words. The revision is shown to perform better than the original method, but both methods are shown to fail in a more realistic scenario.
Enhancement of Santa Ana Winds due to wildfire smoke

The Santa Ana winds are strong warm and dry down-slope airflows blowing from the Great Basin to the Pacific coast in late fall and winter (Sommers, 1978; Raphael, 2003; Conil and Hall, 2006). They are one of the dominant features of climate in southern California during this period. Santa Ana winds are driven by the air pressure gradient between the two regions located in the southern edge of an anti-cyclonic system over the western U.S. Both large mountains (Klemp and Lilly, 1975; Smith, 1985; Durran, 1990) and local topography features such as gaps (Gabersˇek and Durran, 2004) play important roles in their formation and variability. A summary of past studies and a recent analysis of the local and synoptic mechanisms for Santa Ana winds were provided by Hughes and Hall (2010).
Young ’ s modulus of electroplated Ni thin film for MEMS applications

The Young’s modulus of an electroplated nickel (Ni) thin film suitable for microelectromechanical applications has been investigated as a function of process variables: the plating temperature and current density. It was found that the Young’s modulus is approximately 205 GPa at plating temperatures less than 60 jC, close to that of bulk Ni, but drastically drops to approximately 100 GPa at 80 jC. The inclusion of ammonium and sulphate ions by hydrolysis is believed to be responsible for the sharp drop. The Young’s modulus of 205 GPa is for a Ni film plated at J=2 mA/cm and it decreases to 85 GPa as the plating current density is increased to 30 mA/cm. The results imply that at low current density, the plating speed is slow and there is sufficient time for the as-plated Ni atoms to rearrange to form a dense coating. At high currents, the plating speed is high, and the limited mass transport of Ni ions leads to a less dense coating. D 2004 Elsevier B.V. All rights reserved.
Analyzing Brain Dynamics of Affective Engagement

Development of EEG-based brain computer interface (BCI) methods has largely focused on creating a communication channel for subjects with intact cognition but profound loss of motor control from stroke or neurodegenerative disease, allowing such subjects to communicate by spelling out words on a personal computer. However, another important human communication channel may also be limited or unavailable in handicapped subjects -direct non-linguistic emotional communication as by gesture, vocal prosody, and facial expression. We report and examine a first demonstration of an ‘emotion BCI’ in which, as one element of a live musical performance, an able-bodied subject successfully engaged the electronic delivery of an ordered sequence of five music two-tone ground intervals by imaginatively reexperiencing the human feeling he had spontaneously associated with the sound of each interval during training sessions. The EEG data included activities of both brain and non-brain sources (scalp muscles, eye movements). Common Spatial Pattern classification gave 84% correct pseudo-online performance and 5-of-5 correct classification in live performance. Re-analysis of the training session data including only brain EEG sources found by multiple-mixture Amica ICA decomposition achieved five-class classification accuracy of 5970%, confirming that different imagined emotion states may be associated with distinguishable brain source EEG dynamics. smakeig@ucsd.edu
A wear-leveling-aware dynamic stack for PCM memory in embedded systems

Phase Change Memory (PCM) is a promising DRAM replacement in embedded systems due to its attractive characteristics such as extremely low leakage power, high storage density and good scalability. However, PCM's low endurance constrains its practical applications. In this paper, we propose a wear leveling aware dynamic stack to extend PCM's lifetime when it is adopted in embedded systems as main memory. Through a dynamic stack, the memory space is circularly allocated to stack frames, and thus an even usage of PCM memory is achieved. The experimental results show that the proposed method can significantly reduce the write variation on PCM cells and enhance the lifetime of PCM memory.
A Role for 14-3-3 in Insulin-stimulated GLUT4 Translocation through Its Interaction with the RabGAP AS160*

Translocation of the insulin-regulated glucose transporter GLUT4 to the cell surface is dependent on the phosphatidylinositol 3-kinase/Akt pathway. The RabGAP (Rab GTPase-activating protein) AS160 (Akt substrate of 160 kDa) is a direct substrate of Akt and plays an essential role in the regulation of GLUT4 trafficking. We have used liquid chromatography tandem mass spectrometry to identify several 14-3-3 isoforms as AS160-interacting proteins. 14-3-3 proteins interact with AS160 in an insulin- and Akt-dependent manner via an Akt phosphorylation site, Thr-642. This correlates with the dominant negative effect of both the AS160T642A and the AS1604P mutants on insulin-stimulated GLUT4 translocation. Introduction of a constitutive 14-3-3 binding site into AS1604P restored 14-3-3 binding without disrupting AS160-IRAP (insulin-responsive amino peptidase) interaction and reversed the inhibitory effect of AS1604P on GLUT4 translocation. These data show that the insulin-dependent association of 14-3-3 with AS160 plays an important role in GLUT4 trafficking in adipocytes.
Spatial Variation in Sound Frequency Components Across an Urban Area Derived from Mobile Surveys

Continuous exposure to noise can lead to premature hearing loss, reduced cognitive performance, insomnia, stress, hypertension, cardiovascular diseases and stroke. Road noise affects the health of >125 million people in the European Union and Member States are required to map major noise hotspots. These strategic noise maps are usually derived from traffic counts and propagation models because large- scale measurement of the acoustic environment using conventional methods is infeasible. In this study, the authors surveyed the entire city of Southampton, UK using a mobile survey technique, capturing spatial variations in street-level sound characteristics across multiple frequencies from all sound sources. Over 52,000 calibrated and georeferenced sound clips covering 11 Hz to 22.7 kHz are analysed here to investigate variations in sound frequency composition across urban space and then applied to two issues: the definition of naturalness in the acoustic environment; and perceptions of social inequity in sound exposure. Clusters of acoustic characteristics were identified and mapped using spectral clustering and principal components analysis based on octave bands, ecoacoustic indices and dBA. We found independent patterns in low, mid and high frequencies, and the ecoacoustic indices that related to land use. Ecoacoustic indices partially mapped onto greenspace, identifying naturalness, but not uniquely, probably because urban anthropogenic sounds occur at higher frequencies than in the natural areas where such indices were developed. There was some evidence of inequity in sound exposure according to social deprivation and ethnicity, and results differed according to frequency bands. The consequences of these findings and the benefits of city-wide sound surveys for urban planning are discussed.
FIRE SPOT IDENTIFICATION BASED ON HOTSPOT SEQUENTIAL PATTERN AND BURNED AREA CLASSIFICATION

Indonesia has the world's largest tropical peatlands of about 14.9 million hectares that have important life support roles. However, fire frequently occurs in peatlands. According to experts and field forest fire fighters, fire hotspots that appear in a sequence of two to three days at the same location has a high potential of becoming a forest fire. This study aimed to determine the sequential patterns of hotspot occurrences, classify satellite image data and identify the fire spots. Fire spot identification was done using hotspot sequence patterns that were overlaid with burned area classification results. Sequential pattern mining using the Prefix Span algorithm was applied to identify sequences of hotspot occurrence. Maximum Likelihood method was applied to classify Landsat 7 satellite images toward identifying burned areas in Pulang Pisau and Palangkaraya in Central Kalimantan and Pontianak in West Kalimantan. Sequence patterns were overlaid with image classification results. The study results show that in Pulang Pisau, 26.19% of sequence patterns are located in burned areas and 72.62% sequence patterns were found in the buffer of burned area within a radius of one kilometer. As for Palangkaraya, there were 62.50% sequence patterns located in burned areas and 87.50% sequence patterns in the buffer of burned area with the radius of one kilometer. In total, there were 72.62% and 87.50% fire hotspots recorded in Pisau and Palangkaraya, respectively which are strong indicators of peatland fires.
Cohort Effects and Returns to Seniority in France

We examine empirically returns to seniority in France and estimate cohort effects in both firm specific compensation policies and returns to job seniority. We demonstrate the biases in several estimators of returns to seniority and show that allowing firm specific compensation policies and returns to seniority to vary by entry cohort uncovers patterns of variance within firm and within cohort in estimated intercepts and slopes that can be explained by no single theory. (This abstract was borrowed from another version of this item.)
Review on : Iterative Decoding schemes of LDPC codes

Low-density parity-check (LDPC) code, a very promising near-optimal error correction code (ECC), is being widely considered in next generation industry standards. In this paper, two simple iterative low complexity algorithms for decoding LDPC codes have been explained. These algorithms are implemented using real additions only and also not dependent on power spectral density. Comparison of these algorithms with standard BP algorithm are explained. How these algorithms are useful for standards DVBS2, T2 and WiMAX are explained. In VLSI implementation these algorithms using shiftLDPC codes these algorithms reduces hardware
Endoscopic ultrasound-guided hepaticogastrostomy versus percutaneous transhepatic drainage for malignant biliary obstruction after failed endoscopic retrograde cholangiopancreatography: a retrospective expertise-based study from two centers

Background: Percutaneous transhepatic biliary drainage (PTBD) is widely performed as a salvage procedure in patients with unresectable malignant obstruction of the common bile duct (CBD) after failed endoscopic retrograde cholangiopancreatography (ERCP) or in case of surgically altered anatomy. Endoscopic ultrasound-guided hepaticogastrostomy (EU-HGS) is a more recently introduced alternative to relieve malignant obstructive jaundice. The aim of this prospective observational study was to compare the outcome, efficacy and adverse events of EU-HGS and PTBD. Methods: From April 2012 to August 2015, consecutive patients with malignant CBD obstruction who underwent EU-HGS or PTBD in two tertiary-care referral centers were included. The primary endpoint was the clinical success rate. Secondary endpoints were technical success, overall survival, procedure-related adverse events, incidence of adverse events, and reintervention rate. Results: A total of 51 patients (EU-HGS, n = 31; PTBD, n = 20) were included. Median survival was 71 days (range 25–75th percentile; 30–95) for the EU-HGS group and 78 days (range 25–75th percentile; 42–108) for the PTBD group (p = 0.99). Technical success was achieved in all patients in both groups. Clinical success was achieved in 25 (86%) of 31 patients in the EU-HGS group and in 15 (83%) of 20 patients in the PTBD group (p = 0.88). There was no difference in adverse events rates between the two groups (EU-HGS: 16%; PTBD: 10%) (p = 0.69). Four deaths within 1 month (two hemorrhagic and two septic) were considered procedure related (two in the EU-HGS group and two in the PTBD group). Overall reintervention rate was significantly lower after EU-HGS (n = 2) than after PTBD (n = 21) (p = 0.0001). Length of hospital stay was shorter after EU-HGS (8 days versus 15 days; p = 0.002). Conclusions: EU-HGS can be an effective and safe mini invasive-procedure alternative to PTBD, with similar success and adverse-event rates, but with lower rates of reintervention and length of hospitalization.
Predicting multi-core performance: a case study using Solaris containers

Multi-core technology is an emerging hardware trend that provides significant capabilities for computationally expensive applications. However, it also demands a paradigm shift in the software industry, Software developers need to think about the best distribution of software components across the available CPUs, and trade-off the computational efficiency against the cost of re-structuring the standard sequential execution of software. The relationship between the measured performance and the corresponding parameters such as the number of threads and CPUs remains an interesting open problem, especially since it is a challenge to conduct controlled experiments. This paper reports a case study on the use of Solaris containers to control the assignment of threads to the available CPUs in a set of applications. We model the performance as a function of the number of threads, the number of CPUs and the type of program. We use two different modeling strategies: linear regression and Neural Networks, which are applied to the well-established Java Grande benchmark. We observe that there is a nonlinear relationship between these parameters and the associated performance. In addition, neural network models are observed to be consistently better at estimating the performance over a range of parameter values. The results reported in this paper can therefore be used to suitably re-structure software programs to fully utilize the available resources.
First Insight into the Kinome of Human Regulatory T Cells

Regulatory T cells (Tregs) are essential for controlling peripheral tolerance by the active suppression of various immune cells including conventional T effector cells (Teffs). Downstream of the T cell receptor (TCR), more than 500 protein kinases encoded by the human genome have to be considered in signaling cascades regulating the activation of Tregs and Teffs, respectively. Following TCR engagement, Tregs posses a number of unique attributes, such as constitutive expression of Foxp3, hyporesponsiveness and poor cytokine production. Furthermore, recent studies showed that altered regulation of protein kinases is important for Treg function. These data indicate that signaling pathways in Tregs are distinctly organized and alterations at the level of protein kinases contribute to the unique Treg phenotype. However, kinase-based signaling networks in Tregs are poorly understood and necessitate further systematic characterization. In this study, we analyzed the differential expression of kinases in Tregs and Teffs by using a kinase-selective proteome strategy. In total, we revealed quantitative information on 185 kinases expressed in the human CD4+ T cell subsets. The majority of kinases was equally abundant in both T cell subsets, but 11 kinases were differentially expressed in Tregs. Most strikingly, Tregs showed an altered expression of cell cycle kinases including CDK6. Quantitative proteomics generates first comparative insight into the kinase complements of the CD4+ Teff and Treg subset. Treg-specific expression pattern of 11 protein kinases substantiate the current opinion that TCR-mediated signaling cascades are altered in Tregs and further suggests that Tregs exhibit significant specificities in cell-cycle control and progression.
On the Power of Manifold Samples in Exploring Configuration Spaces and the Dimensionality of Narrow Passages

We extend our study of Motion Planning via Manifold Samples (MMS), a general algorithmic framework that combines geometric methods for the exact and complete analysis of low-dimensional configuration spaces with sampling-based approaches that are appropriate for higher dimensions. The framework explores the configuration space by taking samples that are low-dimensional manifolds of the configuration space capturing its connectivity much better than isolated point samples. The scheme is particularly suitable for applications in manufacturing, such as assembly planning, where typically motion planning needs to be carried out in very tight quarters. The contributions of this paper are as follows: (i) We present a recursive application of MMS in a six-dimensional configuration space, enabling the coordination of two polygonal robots translating and rotating amidst polygonal obstacles. In the adduced experiments for the more demanding test cases MMS clearly outperforms Probabilistic Roadmaps (PRM), with over 40-fold speedup in a six-dimensional coordination-tight setting. (ii) A probabilistic completeness proof for the case of MMS with samples that are affine subspaces. (iii) A closer examination of the test cases reveals that MMS has, in comparison to standard sampling-based algorithms, a significant advantage in scenarios containing high-dimensional narrow passages. This provokes a novel characterization of narrow passages, which attempts to capture their dimensionality, an attribute that had been (to a large extent) unattended in previous definitions.
Scalable and Efficient Data Streaming Algorithms for Detecting Common Content in Internet Traffic

Recent research on data streaming algorithms has provided powerful tools to efficiently monitor various characteristics of traffic passing through a single network link or node. However, it is often desirable to perform data streaming analysis on the traffic aggregated over hundreds or even thousands of links/nodes, which will provide network operators with a holistic view of the network operation. Shipping raw traffic data to a centralized location (i.e., “raw aggregation”) for streaming analysis is clearly not a feasible approach for a large network. In this paper, we propose a set of novel distributed data streaming algorithms that allow scalable and efficient monitoring of aggregated traffic without the need for raw aggregation. Our algorithms target the specific network monitoring problem of finding common content in the Internet traffic traversing several nodes/links, which has applications in network-wide intrusion detection, early warning for fast propagating worms, and detection of hot objects and spam traffic. We evaluate our algorithms through extensive simulations and experiments on traffic traces collected from a tier-1 ISP. The experimental results demonstrate that our algorithms can effectively detect common content in the traffic traversing across a large network.
High NPHP 1 and NPHP 6 Mutation Rate in Patients with Joubert Syndrome and Nephronophthisis : Potential Epistatic Effect of NPHP 6 and AHI 1 Mutations in Patients with NPHP 1 Mutations

Joubert Syndrome and Nephronophthisis: Potential Epistatic Effect of NPHP6 and AHI1 Mutations in Patients with NPHP1 Mutations Kálmán Tory,* Tiphanie Lacoste,* Lydie Burglen, Vincent Morinière,* Nathalie Boddaert, Marie-Alice Macher, Brigitte Llanas, Hubert Nivet,** Albert Bensman, Patrick Niaudet, Corinne Antignac,* Rémi Salomon,* and Sophie Saunier* *INSERM, U574, Université Paris Descartes, Departments of Genetics and Pediatric Neurology and Pediatric Nephrology, Hôpital Trousseau, AP-HP, Departments of Pediatric Radiology, Pediatric Nephrology, and Genetics, Hôpital Necker-Enfants Malades, AP-HP, and Department of Pediatric Nephrology, Hôpital Robert Debré, AP-HP, Paris, Department of Pediatrics, Hôpital Pellegrin, Bordeaux, and **Department of Pediatric Nephrology, Hôpital Gatien de Clocheville, Tours, France
Multi-Wavelength Based Optical Density Sensor for Autonomous Monitoring of Microalgae

A multi-wavelength based optical density sensor unit was designed, developed, and evaluated to monitor microalgae growth in real time. The system consisted of five main components including: (1) laser diode modules as light sources; (2) photodiodes as detectors; (3) driver circuit; (4) flow cell; and (5) sensor housing temperature controller. The sensor unit was designed to be integrated into any microalgae culture system for both real time and non-real time optical density measurements and algae growth monitoring applications. It was shown that the sensor unit was capable of monitoring the dynamics and physiological changes of the microalgae culture in real-time. Algae biomass concentration was accurately estimated with optical density measurements at 650, 685 and 780 nm wavelengths used by the sensor unit. The sensor unit was able to monitor cell concentration as high as 1.05 g·L−1 (1.51 × 108 cells·mL−1) during the culture growth without any sample preparation for the measurements. Since high cell concentrations do not need to be diluted using the sensor unit, the system has the potential to be used in industrial microalgae cultivation systems for real time monitoring and control applications that can lead to improved resource use efficiency.