Miracle-dz/UniFAR-FTUs huggingface dataset:
Pattern detection in unstructured data: An experience for a virtualized IT infrastructure

Data-agnostic management of today's virtualized and cloud IT infrastructures motivates statistical inference from unstructured or semi-structured data. We introduce a universal approach to the determination of statistically relevant patterns in unstructured data, and then showcase its application to log data of a Virtual Center (VMware's virtualization management software). The premise of this study is that the unstructured data can be converted into events, where an event is defined by time, source, and a series of attributes. Every event can have any number of attributes but all must have a time stamp and optionally a source of origination (be it a server, a location, a business process, etc.) The statistical relevance of the data can then be made clear via determining the joint and prior probabilities of events using a discrete probability computation. From this we construct a Directed Virtual Graph with nodes representing events and the branches representing the conditional probabilities between two events. Employing information-theoretic measures the graphs are reduced to a subset of relevant nodes and connections. Moreover, the information contained in the unstructured data set is extracted from these graphs by detecting particular patterns of interest.
Naked: The Dark Side of Shame and Moral Life

Naked is a worthwhile read for anyone interested in shame and its role in morality. The book is particularly timely given how common public shaming has become in online settings. Krista K. Thomas argues that, even though shame is a negative emotion with potentially damaging consequences, its dark side is outweighed by its moral benefits insofar as shame is constitutive of desirable moral commitments. According to the author, being liable to shame is constitutive of respecting other people’s points of view, acknowledging others’ moral standing, and accepting that our identities are not only set by what we think of ourselves, but also by factors outside of our control that include our personal histories and other people’s opinions of us.
Association between TLR7 copy number variations and hepatitis B virus infection outcome in Chinese

AIM To explore whether copy number variations (CNVs) of toll-like receptor 7 (TLR7) are associated with susceptibility to chronic hepatitis B virus (HBV) infection. METHODS This study included 623 patients (495 males and 128 females) with chronic hepatitis B virus infection (CHB) and 300 patients (135 females and 165 males) with acute hepatitis B virus infection (AHB) as controls. All CHB patients were further categorized according to disease progression after HBV infection (CHB, liver cirrhosis, or hepatocellular carcinoma). Copy numbers of the TLR7 gene were measured using the AccuCopy method. χ2 tests were used to evaluate the association between TLR7 CNVs and infection type. P values, odds ratios, and 95% confidence intervals (CIs) were used to estimate the effects of risk. RESULTS Among male patients, there were significant differences between the AHB group and CHB group in the distribution of TLR7 CNVs. Low copy number of TLR7 was significantly associated with chronic HBV infection (OR = 0.329, 95%CI: 0.229-0.473, P < 0.001). Difference in TLR7 copy number was also found between AHB and CHB female patients, with low copy number again associated with an increased risk of chronic HBV infection (OR = 0.292, 95%CI: 0.173-0.492, P < 0.001). However, there were no significant differences in TLR7 copy number among the three types of chronic HBV infection (CHB, liver cirrhosis, or hepatocellular carcinoma). In addition, there was no association between TLR7 copy number and titer of the HBV e antigen. CONCLUSION Low TLR7 copy number is a risk factor for chronic HBV infection but is not associated with later stages of disease progression.
Hemodynamics for Brain-Computer Interfaces

This article brings together the various elements that constitute the signal processing challenges presented by a hemodynamics-driven functional near-infrared spectroscopy (fNIRS) based brain-computer interface (BCI). We discuss the use of optically derived measures of cortical hemodynamics as control signals for next generation BCIs. To this end we present a suitable introduction to the underlying measurement principle, we describe appropriate instrumentation and highlight how and where performance improvements can be made to current and future embodiments of such devices. Key design elements of a simple fNIRS-BCI system are highlighted while in the process identifying signal processing problems requiring improved solutions and suggesting methods by which this might be accomplished.
A wireless electrocardiogram detection for personal health monitoring

The current paper presents low-power analog integrated circuits (ICs) for wireless electrocardiogram (ECG) detection in personal health monitoring. Considering the power-efficient communication in the body sensor network (BSN), the required low-power analog ICs are developed for a healthcare system through miniaturization and system integration. The proposed system comprises the design and implementation with three subsystems, namely, (1) the ECG acquisition node, (2) the protocol for standard IEEE 802.15. 4 ZigBee system, and (3) the radio frequency (RF) transmitter circuits. A preamplifier, a low-pass filter, and a successive-approximation analog-to-digital converter (SA-ADC) are integrated to detect an ECG signal. For high integration, the ZigBee protocol is adopted for wireless communication. To transmit the ECG signal through wireless communication, a quadrature voltage-controlled oscillator and a 2.4 GHz low-IF transmitter with a power amplifier and up-conversion mixer are also developed. In the receiver, a 2.4 GHz fully integrated CMOS radio-frequency front-end with a low-noise amplifier, and a quadrature mixer is proposed. The low-power wireless bio-signal acquisition SoC (WBSA-SoC) has been implemented in TSMC 0.18-μm standard CMOS process. The measurement results on the human body reveal that the ECG signals can be acquired effectively by the proposed SoC.
Designing Internet-Based Software

Next-generation software is going to be Internet-based. It will involve web services, peer-topeer data sharing, grid-based execution, and open-source components, and will have to meet the continuously changing demands of a broad set of users. In such an environment software is out of the control of the developer. The requirements for the software will be continuous changing to meet user expectations and demands. Many of the components of a software system will developed independently and will change without notice during design, development and even after deployment. The underlying infrastructure, based on the Internet and on independent grid-based computers, will be inherently unreliable and out of the developer’s control. One essential issue that faces software design and development is how to cope with this lack of control. We propose a component-based mechanism which separates component interfaces and implementations, includes semantics, in a broad sense, as part of the interface, checks these semantics dynamically against the implementation, and allows for dynamic selection (and reselection) of implementations. In this paper we show how different aspects of the semantics including functional, recovery, security, and economics can be encoded and checked, and argue how this approach can address many of the problems that Internet-based software will face.
1-Anilino-8-Naphthalene Sulfonate (ANS) Is Not a Desirable Probe for Determining the Molten Globule State of Chymopapain

The molten globule (MG) state of proteins is widely detected through binding with 1-anilino-8-naphthalene sulphonate (ANS), a fluorescent dye. This strategy is based upon the assumption that when in molten globule state, the exposed hydrophobic clusters of protein are readily bound by the nonpolar anilino-naphthalene moiety of ANS molecules which then produce brilliant fluorescence. In this work, we explored the acid-induced unfolding pathway of chymopapain, a cysteine proteases from Carica papaya, by monitoring the conformational changes over a pH range 1.0–7.4 by circular dichroism, intrinsic fluorescence, ANS binding, acrylamide quenching, isothermal titration calorimetry (ITC) and dynamic light scattering (DLS). The spectroscopic measurements showed that although maximum ANS fluorescence intensity was observed at pH 1.0, however protein exhibited ∼80% loss of secondary structure which does not comply with the characteristics of a typical MG-state. In contrast at pH 1.5, chymopapain retains substantial amount of secondary structure, disrupted side chain interactions, increased hydrodynamic radii and nearly 30-fold increase in ANS fluorescence with respect to the native state, indicating that MG-state exists at pH 1.5 and not at pH 1.0. ITC measurements revealed that ANS molecules bound to chymopapain via hydrophobic interaction were more at pH 1.5 than at pH 1.0. However, a large number of ANS molecules were also involved in electrostatic interaction with protein at pH 1.0 which, together with hydrophobically interacted molecules, may be responsible for maximum ANS fluorescence. We conclude that maximum ANS-fluorescence alone may not be the criteria for determining the MG of chymopapain. Hence a comprehensive structural analysis of the intermediate is essentially required.
Let’s Look at This Another Way: How Supervisors Can Help Subordinates Manage the Threat of Relationship Conflict

Despite decades of scholarly and practitioner attention on conflict management, few studies have addressed the important role that supervisors play in managing relationship conflict (RC). The current research addresses this gap by investigating the use of supervisory interpersonal emotion management in helping subordinates manage perceptions of RC. Examining RC through a threat framework, we propose that when individuals perceive RC in their workgroup, they are less likely to identify with their group and more likely to withdraw from the group in ways that affect critical team processes, both of which have performance implications. Furthermore, we propose that supervisors can mitigate the consequences of perceiving RC by encouraging subordinates to reappraise past negative events that contribute to such perceptions. Using a field sample of 917 employees, we tested and found support for these predictions. This research primarily has implications for conflict theory, RC management theory, and RC management practices.
Performance Evaluation of V-BLAST MIMO System Using Rayleigh & Rician Channels

Wireless communication system employs the application of multiple antennas at both transmitter and receiver to improve data rates through multiplexing techniques. In this paper, we studied the BER performance of Vertical Bell Labs Layered Space Time Architecture (V-BLAST) spatial Multiplexing Technique with various equalisation techniques like Maximum Likelihood (ML), Minimum Mean Square Error (MMSE), Zero Forcing (ZF), Zero Forcing Successive Interference Cancellation (ZF-SIC)by M-PSK modulation techniques in Rayleigh flat fading and Rician channel. We will compare different detection techniques for different modulation techniques and concluded that ML-VBLAST using BPSK under Rayleigh flat fading channel gives best results. The ML equaliser outperforms the ZF, ZF-SIC and MMSE equaliser, however its complexity increases exponentially as the modulation order increases. Also, MIMO systems with large constellations are less efficient compared to small constellation The performance of 1024PSK under Rician channel is the worst
LTM C — An Improved Long-Term Memory for Cognitive Architectures

As Newell (1990) has argued, every cognitive architecture should include a knowledge base modeling human long-term memory (LTM). A critical analysis of current architectures, however, reveals that none of these seems to implement such an LTM component in a completely satisfactory manner. Based on the problems with existing approaches identified by this analysis, a new LTM component has been developed and fully implemented. This new LTM is able to model a wide range of memory effects and to resolve the problems identified with existing approaches.
Hybrid Systems Diagnosability by Abstracting Faulty Continuous Dynamics

On-line model based reconfiguration is generally used to improve the ability of a system to tolerate faults. Recovery after fault occurrence relies on allowing the system to proceed with its mission from a new known nominal state. In this paper, we consider on-line reconfiguration from a novel point of view, having in mind to use reconfiguration actions to disambiguate the tracked estimated system state, i.e. to produce a more precise diagnosis. The choice of the best suited reconfiguration action(s) must hence be guided by the diagnosability properties of the system. However, diagnosability conditions known for continuous systems (CS) on one hand and for discrete event systems (DES) on the other hand cannot be applied directly because of the hybrid nature of the systems that we consider. Our work proposes a framework for analyzing the ability of a hybrid system that stands on recent results establishing the formal equivalence of diagnosability definitions for DES and CS. The approach relies on merging the fault signatures exhibited at the continuous level into the Mode Automaton that represents the discrete dynamics of the system, so that DES diagnosability analysis can be performed on the resulting Behavior Automaton and the corresponding diagnoser. When the state of the system is ambiguous, an analysis of the diagnoser allows us to point at reconfiguration actions that safely move the system into a mode reducing ambiguity.
Distributed key revocation scheme based on shared binary tree

Concerning the identity-based binary tree key revocation scheme, the storage and use of binary tree can not be guaranteed in open cloud environment. This paper proposes a distributed key revocation scheme based on shared binary tree. The scheme splits the binary key tree into branches and distributes them to multiple nodes to save. Then multiple nodes work together to rebuild the key. At the same time, this paper optimizes the lookup algorithm during rebuilding. It solves the issues on distributed storage, safe use and fast reconstruction of the binary tree in the open environment. Experiments and analysis show that the scheme has higher efficiency and makes identity-based key revocation scheme run safely in the open environment.
The reactor antineutrino anomaly

Recently, new reactor antineutrino spectra have been provided for 235U, 239Pu, 241Pu, and 238U, increasing the mean flux by about 3 percent. To a good approximation, this reevaluation applies to all reactor neutrino experiments. The synthesis of published experiments at reactor-detector distances below 100 m leads to a ratio of observed event rate to predicted rate of 0.976 ± 0.024. With our new flux evaluation, this ratio shifts to 0.943 ± 0.023, leading to a deviation from unity at 98.6% C.L. which we call the reactor antineutrino anomaly. The compatibility of our results with the existence of a fourth non-standard neutrino state driving neutrino oscillations at short distances is discussed. The combined analysis of reactor data, gallium solar neutrino calibration experiments, and MiniBooNE-ν data disfavors the no-oscillation hypothesis at 99.8% C.L. The oscillation parameters are such that |Δm2new| > 1.5 eV2 (95%) and sin2(2θnew) = 0.14 ± 0.08 (95%).
Web personalization integrating content semantics and navigational patterns

The amounts of information residing on web sites make users' navigation a hard task. To address this problem, web sites provide recommendations to the end users, based on similar users' navigational patterns mined from past visits. In this paper we introduce a recommendation method, which integrates usage data recorded in web logs, and the conceptual relationships between web documents. In the proposed framework, the usage-oriented URI representation of web pages and users' behavior is augmented with content-based semantics expressed using domain-ontology terms. Since the number of multilingual web sites is constantly increasing, we also propose an automatic method for uniformly characterizing a web site's documents using a common vocabulary. Both methods are integrated in the semantic web personalization system SEWeP.
DETONATION CLASSIFICATION FROM ACOUSTIC SIGNATURE WITH THE RESTRICTED BOLTZMANN MACHINE

We compare the recently proposed Discriminative Restricted Boltzmann Machine (DRBM) to the classical Support Vector Machine (SVM) on a challenging classification task consisting in identifying weapon classes from audio signals. The three weapon classes considered in this work (mortar, rocket, and rocket‐propelled grenade), are difficult to reliably classify with standard techniques because they tend to have similar acoustic signatures. In addition, specificities of the data available in this study make it challenging to rigorously compare classifiers, and we address methodological issues arising from this situation. Experiments show good classification accuracy that could make these techniques suitable for fielding on autonomous devices. DRBMs appear to yield better accuracy than SVMs, and are less sensitive to the choice of signal preprocessing and model hyperparameters. This last property is especially appealing in such a task where the lack of data makes model validation difficult.
Measures in Collection Ranking EvaluationZhihong

As a technique to hunt information on the Internet, collection location has received more attention. Several approaches have been proposed to solve this problem. All these approaches adopt the same procedure: ranking the collections and returning the top-ranks. But these approaches deene diierent measures to evaluate collection ranking and the measures have signiicant weaknesses. In this paper, we survey the measures used in current research and propose a new pair of measures that are based on the concepts of precision and recall. The new measures overcome the problems found in the current measures.
Bioinformatics Applications Note Sequence Analysis Soap3: Ultra-fast Gpu-based Parallel Alignment Tool for Short Reads

SOAP3 is the first short read alignment tool that leverages the multi-processors in a graphic processing unit (GPU) to achieve a drastic improvement in speed. We adapted the compressed full-text index (BWT) used by SOAP2 in view of the advantages and disadvantages of GPU. When tested with millions of Illumina Hiseq 2000 length-100 bp reads, SOAP3 takes < 30 s to align a million read pairs onto the human reference genome and is at least 7.5 and 20 times faster than BWA and Bowtie, respectively. For aligning reads with up to four mismatches, SOAP3 aligns slightly more reads than BWA and Bowtie; this is because SOAP3, unlike BWA and Bowtie, is not heuristic-based and always reports all answers.
Effectiveness of state-of-the-art features for microblog search

We investigate in this paper information retrieval in microblogs exploiting different state-of-the-art features. Microbloggers, besides posting microblogs, search for fresh and relevant information related to their interests, by submitting a query to a microblog search engine. The majority of approaches that collect information from microblogs exploit features such as the recency of the microblog, the authority of his/her author. to improve the quality of their results. In this paper, we evaluated some of the state-of-the-art features to determine those that discriminate relevant from irrelevant microblogs given an information need. Then, we used the selected features to learn models to determine their effectiveness in a microblog search task. We conducted a series of experiments using the dataset and topics of the TREC Microblog 2011 and 2012 tracks. Results show that content, hypertextuality, and recency are the best predictors of relevance. We also found that Naive Bayes was the most effective learning approach for this type of classification.
An energy saving base station employing spatial modulation

In this paper, we evaluate the energy efficiency of a multi-antenna Base Station (BS) employing Spatial Modulation (SM). Taking advantage of the single Radio Frequency (RF) chain configuration of SM, we show that SM offers a significant total power reduction compared to other multi-RF chain Multiple-Input Multiple-Output (MIMO) architectures. For the same RF transmit power, we demonstrate that the total power saving of SM scales linearly with the number of RF chains required by other MIMO schemes. Furthermore, we clarify that for the same ergodic capacity, SM has a significant advantage in energy efficiency compared to the studied multi-RF chain MIMO configurations. In addition, for a number of transmit antennas larger than two, we establish that SM results in higher ergodic capacity than Space-Time Block-Coding (STBC), combined with significant power saving. For a BS with 8 transmit antenna, the achieved power saving of SM can reach up to almost 90%. Finally, based on simulation results, we demonstrate that the energy efficiency (bits/J) of the studied MIMO schemes exhibits a maximum as function of ergodic capacity, and it is further shown that this maximum is several times higher in SM compared to the studied state-of-the-art MIMO schemes.
Endo-MitoEGFP Mice: A Novel Transgenic Mouse with Fluorescently Marked Mitochondria in Microvascular Endothelial Cells

Blood vessel-specific fluorescent transgenic mice are excellent tools to study the development of the vasculature and angiogenic processes. There is growing interest in the biological processes relevant to endothelial cells but limited tools exist to selectively evaluate subcellular functions of this cell type in vivo. Here, we report a novel transgenic animal model that expresses mitochondrially targeted enhanced green fluorescent protein (EGFP) via the Hb9 promoter, a homeobox transcription factor with limited known involvement in the vasculature. Random integration of the transgene, containing the entire mouse Hb9 promoter, was found to be expressed in a variety of vascularised tissues. Further inspection revealed that Mito-EGFP localizes to the endothelial cells (ECs) of a subset of microvascular blood vessels, especially in the central nervous system (CNS), heart, spleen, thymus, lymph nodes and skin. We demonstrate the utility of this novel transgenic mouse, named Endo-MitoEGFP, in the detection, imaging, and isolation of microvascular ECs and evaluation of EC mitochondrial function isolated from adult animals. These transgenic mice will be useful to studies of ECs in development, physiology, and pathology.
The Change in Knee Angle during the Gait by Applying Elastic Tape to the Skin

[Purpose] The aim of this study was to verify how the application of elastic tape to the anterior surface of the thigh changes the knee angle pattern during gait. [Subjects] The subjects were 10 people who showed an abnormal knee angle change pattern during usual walking. They did not show the so-called double knee action. [Methods] Subjects were asked to walk as usual, and then to walk with elastic tape attached to the anterior surface of the thigh. The knee angle was measured during gait with an electronic goniometer. We graphed the temporal changes of the knee angle and compared them with the normal gait pattern. [Results] The knee angle gait pattern of six of the 10 subjects improved after application of the tape and became like a normal gait pattern. The changes in the knee angle resulted from a stimulus via the skin, rather than voluntary muscular adjustment, suggesting that the changes may have originated due to differences in reflexive tensile strength. [Conclusion] In normal speed gait, it is suggested that the knee angle was altered such that it exhibited a normal pattern by applying elastic tape to the anterior surface of the thigh. We suspect that application of the elastic tape may change the muscle tonus.