Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensor Telemetry Using Bluetooth Technology

A traditional method for transferring data in rotating mechanisms has been the slip ring, but these are not viable inside pistons due to size, the associated cabling, and the requirement of one slip ring per parameter. A mechatronic data acquisition system is developed whereby signal conditioning is performed by the sensor and the signal passed to a Bluetooth transmitter module for wireless telemetry to a Bluetooth receiver located in very close proximity, connected to an external host PC. The Data Acquisition (DAQ) Bluetooth module integrates a microcontroller that reads the conditioned thermocouple signal and performs any other DAQ functionality required. The microcontroller firmware includes a server that collates all DAQ data for transmission via Bluetooth to the host PC for display via a client interface. This Short Distance Telemetry (SDT) system is a substitute for slip rings and their associated cabling. A slip ring also transfers power, but this cannot be achieved with the SDT system, therefore an independent power supply is required. The power supply consists of a rotor incorporating NdFeB magnets and a wire wound stator. As the shaft rotates the rotor induces an AC voltage into the stator. A rectifying circuit converts the AC voltage into a regulated DC output voltage that drives the signal conditioning and embedded Bluetooth circuits. Index Term-Short Distance Telemetry, Bluetooth,
Differential Effects of a Toll-Like Receptor Antagonist on Mycobacterium tuberculosis-Induced Macrophage Responses1

We previously showed that viable Mycobacterium tuberculosis (Mtb) bacilli contain distinct ligands that activate cells via the mammalian Toll-like receptor (TLR) proteins TLR2 and TLR4. We now demonstrate that expression of a dominant negative TLR2 or TLR4 proteins in RAW 264.7 macrophages partially blocked Mtb-induced NF-κB activation. Coexpression of both dominant negative proteins blocked virtually all Mtb-induced NF-κB activation. The role of the TLR4 coreceptor MD-2 was also examined. Unlike LPS, Mtb-induced macrophage activation was not augmented by overexpression of ectopic MD-2. Moreover, cells expressing an LPS-unresponsive MD-2 mutant responded normally to Mtb. We also observed that the lipid A-like antagonist E5531 specifically inhibited TLR4-dependent Mtb-induced cellular responses. E5531 could substantially block LPS- and Mtb-induced TNF-α production in both RAW 264.7 cells and primary human alveolar macrophages (AMφ). E5531 inhibited Mtb-induced AMφ apoptosis in vitro, an effect that was a consequence of the inhibition of TNF-α production by E5531. In contrast, E5531 did not inhibit Mtb-induced NO production in RAW 264.7 cells and AMφ. Mtb-stimulated peritoneal macrophages from TLR2- and TLR4-deficient animals produced similar amounts of NO compared with control animals, demonstrating that these TLR proteins are not required for Mtb-induced NO production. Lastly, we demonstrated that a dominant negative MyD88 mutant could block Mtb-induced activation of the TNF-α promoter, but not the inducible NO synthase promoter, in murine macrophages. Together, these data suggest that Mtb-induced TNF-α production is largely dependent on TLR signaling. In contrast, Mtb-induced NO production may be either TLR independent or mediated by TLR proteins in a MyD88-independent manner.
Molecular Characterization of Two Fatty Acyl-CoA Reductase Genes From Phenacoccus solenopsis (Hemiptera: Pseudococcidae)

Fatty acyl-CoA reductases (FARs) are key enzymes involved in fatty alcohol synthesis. Here, we cloned and characterized full-length cDNAs of two FAR genes from the cotton mealybug, Phenacoccus solenopsis. The results showed PsFAR I and PsFAR II cDNAs were 1,584 bp and 1,515 bp in length respectively. Both PsFAR I and PsFAR II were predicted to be located in the endoplasmic reticulum by Euk-mPLoc 2.0 approach. Both of them had a Rossmann folding region and a FAR_C region. Two conservative motifs were discovered in Rossmann folding region by sequence alignment including a NADPH combining motif, TGXXGG, and an active site motif, YXXXK. A phylogenetic tree made using MEGA 6.06 indicated that PsFAR I and PsFAR II were placed in two different branches. Gene expression analysis performed at different developmental stages showed that the expression of PsFar I is significantly higher than that of PsFar II in first and second instar nymphs and in male adults. Spirotetramat treatment at 125 mg/liter significantly increased the expression of PsFar I in third instar nymphs, but there was no effect in the expression of PsFar II. Our results indicated these two FAR genes showed different expression patterns during insect development and after pesticide treatment, suggesting they play different roles in insect development and detoxification against pesticides.
Adaptive information filtering: detecting changes in text streams

The task of information filtering is to classify documents from a stream as either relevant or non-relevant according to a particular user interest with the objective to reduce information load. When using an information filter in an environment that is changing with time, methods for adapting the filter should be considered in order to retain classification accuracy. We favor a methodology that attempts to detect changes and adapts the information filter only if inevitable in order to minimize the amount of user feedback for providing new training data. Yet, detecting changes may require costly user feedback as well. This paper describes two methods for detecting changes without user feedback. The first method is based on evaluating an expected error rate, while the second one observes the fraction of classification decisions made with a confidence below a given threshold. Further, a heuristics for automatically determining this threshold is suggested and the performance of this approach is experimentally explored as a function of the threshold parameter. Some empirical results show that both methods work well in a simulated change scenario with real world data.
Binary Function Clustering Using Semantic Hashes

The ability to identify semantically-related functions, in large collections of binary executables, is important for malware detection. Intuitively, two pieces of code are similar if they have the same effect on a machine's state. Current state-of-the-art tools employ a variety of pair wise comparisons (e.g., template matching using SMT solvers, Value-Set analysis at critical program points, API call matching, etc.) However, these methods are unshakable for clustering large datasets, of size N, since they require O(N2) comparisons. In this paper, we present an alternative approach based upon "hashing". We propose a scheme that captures the semantics of functions as semantic hashes. Our approach treats a function as a set of features, each of which represent the input-output behavior of a basic block. Using a form of locality-sensitive hashing known as Min Hashing, functions with many common features can be quickly identified, and the complexity of clustering is reduced to O(N). Experiments on functions extracted from the CERT malware catalog indicate that we are able to cluster closely related code with a low false positive rate.
What Makes the Sun Tick? - The Origin of the Solar Cycle

In contrast to the situation with the geodynamo, no breakthrough has been made in the solar dynamo problem for decades. Since the appearance of mean-field electrodynamics in the 1960's, the only really significant advance was in the field of flux tube theory and flux emergence calculations. These new results, together with helioseismic evidence, have led to the realization that the toroidal magnetic flux giving rise to activity phenomena must be stored and presumably generated below the convection zone proper, in what I will call the DOT (Dynamo-Overshoot-Tachoclyne) layer. The only segment of the problem we can claim to basically understand is the transport of flux from this layer to the surface. On the other hand, as reliable models for the DOT layer do not exist we are clueless concerning the precise mechanisms responsible for toroidal/poloidal flux conversion and for characteristic migration patterns (extended butterfly diagram) and periodicities. Even the most basic result of mean-field theory, the interpretation of the butterfly diagram as an alpha-omega dynamo wave, has been questioned. This review therefore will necessarily ask more questions than give answers. Some of these key questions are - Structure of the DOT layer - alpha-quenching and distributed dynamo - High-latitude migration patterns and their interpretation - The ultimate fate of emerged flux
L’impact de l’IFRS 8 sur le coût des capitaux propres

L’article vise a mesurer l’impact de l’IFRS 8 sur le contenu informationnel des donnees sectorielles. Sur un echantillon francais, nous constatons qu’une evolution de la segmentation avec l’IFRS 8 s’accompagne d’un moindre cout des capitaux propres. Lorsque le nombre de segments presentes change, l’IFRS 8 semble apporter un complement d’information utile a l’investisseur. Ce resultat confirme les attentes et les conclusions de l’IASB.
Antiviral Susceptibility of Avian and Swine Influenza Virus of the N1 Neuraminidase Subtype

ABSTRACT Influenza viruses of the N1 neuraminidase (NA) subtype affecting both animals and humans caused the 2009 pandemic. Anti-influenza virus NA inhibitors are crucial early in a pandemic, when specific influenza vaccines are unavailable. Thus, it is urgent to confirm the antiviral susceptibility of the avian viruses, a potential source of a pandemic virus. We evaluated the NA inhibitor susceptibilities of viruses of the N1 subtype isolated from wild waterbirds, swine, and humans. Most avian viruses were highly or moderately susceptible to oseltamivir (50% inhibitory concentration [IC50], <5.1 to 50 nM). Of 91 avian isolates, 7 (7.7%) had reduced susceptibility (IC50, >50 nM) but were sensitive to the NA inhibitors zanamivir and peramivir. Oseltamivir susceptibility ranged more widely among the waterbird viruses (IC50, 0.5 to 154.43 nM) than among swine and human viruses (IC50, 0.33 to 2.56 nM). Swine viruses were sensitive to oseltamivir, compared to human seasonal H1N1 isolated before 2007 (mean IC50, 1.4 nM). Avian viruses from 2007 to 2008 were sensitive to oseltamivir, in contrast to the emergence of resistant H1N1 in humans. Susceptibility remained high to moderate over time among influenza viruses. Sequence analysis of the outliers did not detect molecular markers of drug-resistance (e.g., H275Y NA mutation [N1 numbering]) but revealed mutations outside the NA active site. In particular, V267I, N307D, and V321I residue changes were found, and structural analyses suggest that these mutations distort hydrophobic pockets and affect residues in the NA active site. We determined that natural oseltamivir resistance among swine and wild waterbirds is rare. Minor naturally occurring variants in NA can affect antiviral susceptibility.
Size-Constrained Tree Decompositions

Tree-Decompositions are the corner-stone of many dynamic programming algorithms for solving graph problems. Since the complexity of such algorithms generally depends exponentially on the width (size of the bags) of the decomposition, much work has been devoted to compute tree-decompositions with small width. However, practical algorithms computing tree-decompositions only exist for graphs with treewidth less than 4. In such graphs, the time-complexity of dynamic programming algorithms based on tree-decompositions is dominated by the size (number of bags) of the tree-decompositions. It is then interesting to minimize the size of the tree-decompositions. In this report, we consider the problem of computing a tree-decomposition of a graph with width at most k and minimum size. More precisely, we focus on the following problem: given a fixed k ≥ 1, what is the complexity of computing a tree-decomposition of width at most k with minimum size in the class of graphs with treewidth at most k? We prove that the problem is NP-complete for any fixed k ≥ 4 and polynomial for k ≤ 2; for k = 3, we show that it is polynomial in the class of trees and 2-connected outerplanar graphs.
Emission and Accumulation of Monoterpene and the Key Terpene Synthase (TPS) Associated with Monoterpene Biosynthesis in Osmanthus fragrans Lour

Osmanthus fragrans is an ornamental and economically important plant known for its magnificent aroma, and the most important aroma-active compounds in flowers are monoterpenes, mainly β-ocimene, linalool and linalool derivatives. To understand the molecular mechanism of monoterpene production, we analyzed the emission and accumulation patterns of these compounds and the transcript levels of the genes involved in their biosynthesis in two O. fragrans cultivars during flowering stages. The results showed that both emission and accumulation of monoterpenes varied with flower development and glycosylation had an important impact on floral linalool emission during this process. Gene expression demonstrated that the transcript levels of terpene synthase (TPS) genes probably played a key role in monoterpene production, compared to the genes in the MEP pathway. Phylogenetic analysis showed that OfTPS1 and OfTPS2 belonged to a TPS-g subfamily, and OfTPS3 and OfTPS4 clustered into a TPS-b subfamily. Their transient and stable expression in tobacco leaves suggested that OfTPS1 and OfTPS2 exclusively produced β-linalool, and trans-β-ocimene was the sole product from OfTPS3, while OfTPS4, a predictive sesquiterpene synthase, produced α-farnesene. These results indicate that OfTPS1, OfTPS2, and OfTPS3 could account for the major floral monoterpenes, linalool and trans-β-ocimene, produced in O. fragrans flowers.
Nonnegative Ricci curvature, small linear diameter growth and finite generation of fundamental groups

In 1968, Milnor conjectured that a complete noncompact manifold with nonnegative Ricci curvature has a finitely generated fundamental group. The author applies the Excess Theorem of Abresch and Gromoll (1990), to prove two theorems. The first states that if such a manifold has small linear diameter growth then its fundamental group is finitely generated. The second states that if such a manifold has an infinitely generated fundamental group then it has a tangent cone at infinity which is not polar. A corollary of either theorem is the fact that if such a manifold has linear volume growth, then its fundamental group is finitely generated.
University and Community Resources for Sexual Assault Survivors: Familiarity With and Use of Services Among College Students

ABSTRACT Scholars have highlighted the prevalence of sexual assault on college campuses. Universities are generally equipped to address victimization through a range of resources, including counseling and psychological services. These resources are instrumental for posttrauma recovery, but students must be aware of and willing to use available services. This study used a sample of 505 survey responses collected at a mid-sized, public, Southern university regarding community and campus resource knowledge, familiarity, and service use. The majority of participants were unaware of resources. Females reported increased community resource familiarity compared to males. Multivariate models revealed distress disclosure, sexual victimization history, and race were significant predictors of service use but criminal justice major and law enforcement career plans were not significant. Implications are discussed.
On the Absorption of High Energy Gamma-Rays by Intergalactic Infrared Radiation

W e present a new calculation of the intergalactic (cid:13) -ray pair-production absorption coe(cid:14)cientasa function ofboth energy and redshiftup to the redshiftof3C279,z = 0.54. In reexam ining this problem ,we m ake use ofnew observationaldata on the intergalactic infrared radiation (cid:12)eld (IIR F), together with recent theoretical m odels of the galactic spectralenergy distributions ofthe IIR F from stars and dust reradiation and estim ates ofthe IIR F from galaxy counts and CO BE results. W e present our results for two fairly wellde(cid:12)ned IIR F spectralenergy distributions,one ofwhich is within 1 (cid:27) ofour previous estim ate ofthe IIR F at (cid:24) 20 (cid:22) m . W e then apply ourresultsto the (cid:13) -ray spectrum ofM rk 421,and obtain good agreem ent with the observationaldata,including the recent results ofthe H EG R A group.
Carrier Signal Selection for Sensorless Control of PM Synchronous Machines at Zero and Very Low Speeds

This paper compares pulsating and rotating vector carrier signal injection for self-sensing (or sensorless) control of PM synchronous machines. The main focus of the study is evaluation of estimation errors due to the physical non-ideal attributes of both the machine and the inverter. Initial position and magnet polarity estimation are analyzed as well. Transient response and signal processing for both techniques is discussed for completeness. The theoretical analysis is supported by experimental and simulation evidence obtained using interior PM synchronous machines.
Adapting Recommendations Organization to User Preferences

Given the overwhelming information appearing in the current web environment, recommendations have been increasingly applied to assist users in handling with the information overload and locating items that interest them. As a different way to generate and display recommendations, the organization interface has been found being more effective in building users' trust. In this paper, we propose a novel approach to generating the organization of recommendations, with the goal of making it dynamically adaptive to different conditions of user preferences (i.e. "incomplete preferences" and/or "preference conflicts"), so as to optimally support users' preference construction process and accurate decisions.
A Novel Approach on Mining Frequent Item Sets on Large Uncertain Databases

: The data handled in emerging applications like location-based services, sensor monitoring systems and data integration, are often inexact in nature. In this paper, we study the important problem of extracting frequent item sets from a large uncertain database, interpreted under the Possible World Semantics (PWS). This issue is technically challenging, since an uncertain database contains an exponential number of possible worlds. By observing that the mining process can be modeled as a Poisson binomial distribution, we develop an approximate algorithm, which can efficiently and accurately discover frequent item sets in a large uncertain database. The important issue of maintaining the mining result for a database that is evolving was discussed. Specifically, we propose incremental mining algorithm, which enable Probabilistic Frequent Item Set (PFI) results to be refreshed. This reduces the need of re-executing the whole mining algorithm on the new database, which is often more expensive and unnecessary. All our approaches support both tuple and attribute uncertainty, which are two common uncertain database models. We also perform extensive evaluation on real and synthetic data sets to validate our approaches.
Benchmarking of Quantile-based Indoor Fingerprinting Algorithm

A growing demand for the information about location of numerous devices in indoor and urban environments raises the need for indoor localization. Indoor localization is needed for various applications and services, and it is considered as one of the key enablers of the Future Internet concepts. One of the most promising approaches in indoor localization is fingerprinting using information from the WiFi infrastructure. We propose a new fingerprinting-based indoor localization algorithm that makes use of the RSSI values from WiFi beacon packets for estimating the location. Namely, for generating fingerprints our algorithm uses the quantiles of RSSI values from beacon packets transmitted from various WiFi access points in the premises. Furthermore, the proposed algorithm uses Pompeiu-Hausdorff distance for calculating the difference between training fingerprints and ones generated by user to be localized. In the evaluation of the performance of indoor localization algorithms usual claims are the geometrical and room level accuracy of the algorithm. Unfortunately, due to the poorly defined scenarios and localization methodologies, those results are mostly unrepeatable and incomparable with other benchmarks. We aim on experimentally comparing the performance of our fingerprinting algorithm with three well known alternatives. For objective comparison of different algorithms we use guidelines and directions given in a newly developed EVARILOS Benchmarking Handbook (EBH). Following the classification in this handbook we evaluate the localization accuracy of different algorithms in three scenarios, namely small and big office and big open space scenarios. Using the systematic approach for evaluation of indoor localization solutions proposed in EBH we demonstrate that our algorithm achieves similar or better performance results in comparison to other algorithms in terms of geometrical and room level accuracy in the office scenarios, while our solution significantly prevail in the open-space scenario.
Rank-Based Analysis for the Time-course Microarray Data

Microarray technology allows the monitoring of expression levels for thousands of genes simultaneously. In time-course microarray experiments in which gene expression is monitored over time, we are interested in clustering genes that show similar temporal profiles and identifying genes that show a pre-specified profile. Unfortunately, many traditional clustering methods used for analyzing the microarray data do not effectively detect temporal profiles for the timecourse microarray data. We propose a rank based analysis for the time-course microarray data. Our clustering method consists of two steps. The first step discretizes the expression data into groups and then transform them into the rank data. The second step performs the rank-based clustering analysis. Our testing procedure uses the bootstrap samples to select the genes that show similar patterns for the candidate profiles. Simulation study is performed to evaluate the performance of the proposed rank based method and compare it with other clustering methods. The rank based method is shown to be more powerful than other methods. The proposed method is illustrated with a breast cancer data introduced by Lobenhofer et al. (2002)[6].
Design and Optimization of Agent-Based Emergency Supply Chains

Networks provide the physical and information structure of systems for transporting all food, water, people, information and goods within our modern life. Emergency Management (EM) organizations need to have highly functioning logistics networks as key towards supporting and aiding affected populations in disasters or conflicts. Optimization has made immense strides towards improving logistics costs and services. However, most optimization has been designed to operate in a centralized environment, while many systems actually operate in a decentralized way, with individuals making decisions that impact the entire system, especially in emergency management. EM operations can be linked with mobile computing, but new methods are needed to operate across the decentralized network. We introduce research that explicitly integrates the decentralized decision-makers into the optimization of the entire supply chain by incorporating their behavior with mathematical models so as to improve the overall system outcomes. Specific research areas we study include: