Miracle-dz/UniFAR-FTUs huggingface dataset:
Feature Selection Using Linear Support Vector Machines

Text categorization is the task of classifying natural language documents into a set of predefined categories. Documents are typically represented by sparse vectors under the vector space model, where each word in the vocabulary is mapped to one coordinate axis and its occurrence in the document gives rise to one nonzero component in the vector representing that document. When training classifiers on large collections of documents, both the time and memory requirements connected with these vectors may be prohibitive. This calls for the use of a feature selection method not only to reduce the number of features but also to increase the sparsity of vectors. We propose a feature selection method based on linear Support Vector Machines (SVMs). Linear SVM is used on a subset of training data to train a linear classifier which is characterized by the normal to the hyper-plane dividing positive and negative instances. Components of the normal with higher absolute values have a larger impact on data classification. Instead of pre-defining the number of highest scoring features to be included in a classifier we apply feature selection that aims at a pre-defined average sparsity level across documents and classifiers for a given training set. After the feature set is determined, the model is trained on the full training data set represented within the selected feature set. We compare this feature selection approach to more traditional feature selection methods such as Mutual Information and Odds Ratio in terms of the sparsity of vectors and classification performance achieved. We also examine how the size of the training data subset affects the quality of feature selection and ultimately the classification performance. Preliminary results indicate that, at the same level of vector sparsity, feature selection based on SVM normals performs better than Odds Ratio- or Mutual Information-based feature selection. In the reported experiments we use linear SVM as the classification model.
Ontology Partition Method for Semantic Query Routing

With a large quantity of data and services existing in virtual organization, query routing is an efficient approach to satisfy entities on community for their requirements of knowledge. The entities, which are organized according to the semantic relationship of each other, together with the query routing method under the guidance of semantics, endeavor to meet the querist with the most relevant answer. This paper proposes an extended query routing method that draws on the relationships between different concepts on Domain Ontology to mine the relationship between the knowledge querist holds and the knowledge querist wants. Through Related Segmentation of Ontology Algorithm, this paper tries to explore a cognitive chain to get the querist to fully understand how the knowledge in answer comes about, and to infer the answer querist wants to know.
Online Gaussian process for nonstationary speech separation

In a practical speech enhancement system, it is required to enhance speech signals from the mixed signals, which were corrupted due to the nonstationary source signals and mixing conditions. The source voices may be from different moving speakers. The speakers may abruptly appear or disappear and may be permuted continuously. To deal with these scenarios with a varying number of sources, we present a new method for nonstationary speech separation. An online Gaussian process independent component analysis (OLGP-ICA) is developed to characterize the real-time temporal structure in time-varying mixing system and to capture the evolved statistics of independent sources from online observed signals. A variational Bayes algorithm is established to estimate the evolved parameters for dynamic source separation. In the experiments, the proposed OLGP-ICA is compared with other ICA methods and is illustrated to be effective in recovering speech and music signals in a nonstationary speaking environment.
Resveratrol Inhibits Cardiac Hypertrophy via AMP-activated Protein Kinase and Akt*

Whereas studies involving animal models of cardiovascular disease demonstrated that resveratrol is able to inhibit hypertrophic growth, the mechanisms involved have not been elucidated. Because studies in cells other than cardiomyocytes revealed that AMP-activated protein kinase (AMPK) and Akt are affected by resveratrol, we hypothesized that resveratrol prevents cardiac myocyte hypertrophy via these two kinase systems. Herein, we demonstrate that resveratrol reduces phenylephrine-induced protein synthesis and cell growth in rat cardiac myocytes via alterations of intracellular pathways involved in controlling protein synthesis (p70S6 kinase and eukaryotic elongation factor-2). Additionally, we demonstrate that resveratrol negatively regulates the calcineurin-nuclear factor of activated T cells pathway thus modifying a critical component of the transcriptional mechanism involved in pathological cardiac hypertrophy. Our data also indicate that these effects of resveratrol are mediated via AMPK activation and Akt inhibition, and in the case of AMPK, is dependent on the presence of the AMPK kinase, LKB1. Taken together, our data suggest that resveratrol exerts anti-hypertrophic effects by activating AMPK via LKB1 and inhibiting Akt, thus suppressing protein synthesis and gene transcription.
STRATEGIC HUMAN RESOURCE MANAGEMENT

Background: In today's society organizations are characterized by economic changes, this by globalization, changing customer circumstances and increased competition. Organizations need to constantly improve their competitiveness by streamlining its operations. Today, employees are seen as the organizations most important asset, this because they provide organizations with important sources to become competitive. Strategic Human Resource Management (SHRM) is an approach that is about to build HR-strategies that make employees knowledge and skills to contribute the organizations to achieve the overall goals. Purpose: The aim of this study was to examine how the organization is using a strategic HR-work (SHRM) and if it is a successful strategy. Our study has contributed to a better understanding of the concept of SHRM and how it can be used and how SHRM can affect the organization. Method: The collection of our empirical material is based on a qualitative approach where we conducted in-depth interviews with HR-managers working in an organization that is active in the automotive industry. Conclusion: We have concluded that our survey shows that the organization uses the SHRM as working strategy. However, we can not draw any concrete conclusions in which way SHRM affect the organization, but there are clear indications that SHRM has a positive effect, contributing to increased productivity and efficiency. A further conclusion of our study is that it ́s very important that the organization have a leadership that promotes SHRM. AbbreviaHR Human Resource tions: HRM Human Resource Management SHRM Strategic Human Resource Management SQLCP Saftey, Quality, Leadtime, Cost and People AMO Ability, Motivation and Opportunity
Experiments with Web QA System and TREC 2004 Questions

We describe our first participation in TREC. We only competed in the Question Answering (QA) category and limited our runs to factoids. Our approach was to use our open domain QA system that finds the answer among Web pages indexed by a commercial search engine, then project the answer to the TREC test collection. Our Web QA takes advantage of the redundancy of the Web, obtains the candidate answers by pattern matching, then performs probabilistic triangulation of them to assign a final score. Our novel contributions are the following 1) the probabilistic triangulation algorithm, 2) a more powerful pattern language than used in prior research, and 3) use of semantic features of expected answers instead of relying on an elaborate hierarchy of question types. Although, we were able to run only first 91 out of 230 factoid questions before the submission deadline, we find our result encouraging, and if interpolated to the entire questions set, it would have placed us above the median performance on factoid questions.
Learning speaker-specific phrase breaks for text-to-speech systems

The objective of this paper is to investigate whether prosodic phrase breaks are specific to a speaker, and if so, propose a mechanism of learning speaker-specific phrase breaks from the speech database. Another equally important aspect dealt in this work is to demonstrate the usefulness of these speaker-specific phrase breaks for a text-to-speech system. Experiments are carried out on two different English voices as well as on a Telugu voice, and it is shown that speaker-specific phrase breaks improves duration as well as spectral quality of synthetic speech.
HIP/PAP is an adhesive protein expressed in hepatocarcinoma, normal Paneth, and pancreatic cells.

Human hepatocarcinoma-intestine-pancreas (HIP) cDNA, isolated from a hepatocellular carcinoma, encodes a C-type lectin. According to published cDNA sequences, HIP protein is identical to human pancreatitis-associated protein (PAP). In these sequences, a putative signal peptide and the carbohydrate recognition domain (CRD) can be recognized. In the present study, we established transgenic mice to drive the production of soluble recombinant HIP/PAP protein in the milk of lactating animals; using this model, we showed that HIP/PAP protein was secreted after suitable cleavage of the potential signal peptide. Moreover, we also produced HIP/PAP protein by Escherichia coli cultures performed to generate specific antibodies. These antibodies enabled the detection of HIP/PAP protein in normal intestine and pancreas (both in endocrine and exocrine cells), e.g., intestinal neuroendocrine and Paneth cells, pancreatic islets of Langerhans, and acinar cells. HIP/PAP protein was also identified in the cytoplasm of tumoral hepatocytes but not in nontumoral hepatocytes. Finally, HIP/PAP protein activity was tested and we showed that HIP/PAP induced the adhesion of rat hepatocytes and bound strongly to extracellular matrix proteins (laminin-1, fibronectin), less strongly to type I and IV collagen, and not at all to heparan sulfate proteoglycan. In conclusion, these results showed that HIP/PAP protein was matured on secretion. We also demonstrated that HIP/PAP protein was specifically expressed in hepatocarcinoma cells and interacted with rat hepatocytes and the extracellular matrix. Taken overall, these results suggest that HIP/PAP protein may be of potential importance to liver cell differentiation/proliferation.
Aggregating Forecasts Using a Learned Bayesian Network

Under the Defense Advanced Research Project Agency's (DARPA) Integrated Crisis Early Warning System (ICEWS), Innovative Decisions, Inc. (IDI) constructed a Bayesian network to combine forecasts produced by a set of social science models. We used Bayesian network structure learning with political science variables to produce meaningful priors. We employed a naive Bayes structure to aggregate the forecasts. In both cases, IDI improved classification by intelligently discretizing continuous variables. The resulting network not only met performance criteria set by DARPA, but also out-performed each of the social science models across all types of forecasted events. We describe the construction of the aggregator as well as a set of experiments performed to explore the nature of the Bayesian EOI Aggregator's performance.
A 220-MS/s 9-Bit 2X Time-Interleaved SAR ADC With a 133-fF Input Capacitance and a FOM of 37 fJ/conv in 65-nm CMOS

This brief presents a 9-bit 2X time-interleaved successive approximation (SAR) analog-to-digital converter (ADC) for high-speed applications. The proposed ADC fabricated in TSMC's 65-nm general-purpose process occupies an area of 0.0338 mm2 and consists of two time-interleaved channels, each operating at 110 MS/s. The sampling capacitor is separated from the capacitive DAC array by performing the input and DAC reference subtraction in the current domain rather than as done traditionally in the charge domain. This allows for an extremely small input capacitance of 133 fF. The measured ADC SFDR is 57 dB and the measured ENOB is 7.55 bits at Nyquist rate while using 1.55-mW power from a 1-V supply.
Chaos glial network connected to Multi-Layer Perceptron for Solving Two-Spiral Problem

Some methods using artificial neural network were proposed for solving to the Two-Spiral Problem (TSP). TSP is a problem which classifies two spirals drawn on the plane, and it is famous as the high nonlinear problem. In this paper, we propose a chaos glial network which connected to Multi-Layer Perceptron (MLP). The chaos glial network is inspired by astrocyte which is glial cell in the brain. By computer simulations for solving TSP, we confirmed that the proposed chaos glial network connected to MLP gains better performance than the conventional MLP.
3D Tracking via Body Radio Reflections

This paper introduces WiTrack, a system that tracks the 3D motion of a user from the radio signals reflected off her body. It works even if the person is occluded from the WiTrack device or in a different room. WiTrack does not require the user to carry any wireless device, yet its accuracy exceeds current RF localization systems, which require the user to hold a transceiver. Empirical measurements with a WiTrack prototype show that, on average, it localizes the center of a human body to within a median of 10 to 13 cm in the x and y dimensions, and 21 cm in the z dimension. It also provides coarse tracking of body parts, identifying the direction of a pointing hand with a median of 11.2°. WiTrack bridges a gap between RF-based localization systems which locate a user through walls and occlusions, and human-computer interaction systems like Kinect, which can track a user without instrumenting her body, but require the user to stay within the direct line of sight of the device.
The Alarmin Cytokine, High Mobility Group Box 1, Is Produced by Viable Cardiomyocytes and Mediates the Lipopolysaccharide-Induced Myocardial Dysfunction via a TLR4/Phosphatidylinositol 3-Kinase γ Pathway

High mobility group box 1 (HMGB1) is an alarmin actively secreted by immune cells and passively released by necrotic nonimmune cells. HMGB1 has been implicated in both cardiac contractile dysfunction and the lethality associated with sepsis/endotoxemia. The aim of the current study was to assess whether viable cardiomyocytes could produce HMGB1 and whether HMGB1 can affect myocardial contractility. LPS was used as a model of sepsis/endotoxemia in mice and isolated cardiac myocytes. LPS increased myocardial expression of HMGB1 in vivo (immunohistochemistry) and production and secretion of HMGB1 by viable cardiac myocytes in vitro (Western). LPS increased the phosphorylation status of PI3Kγ in cardiac myocytes, an effect not observed in TLR4−/− myocytes. Genetic (PI3Kγ−/−) or pharmacologic (AS605240) blockade of PI3Kγ ameliorated the LPS-induced 1) cardiomyocyte production and secretion of HMGB1 in vitro and 2) HMGB1 expression in the myocardium in vivo. The LPS-induced depression of myocardial contractility was prevented by the HMGB1 antagonist, A-box. Genetic (PI3Kγ−/−) or pharmacologic (AS605240) blockade of PI3Kγ ameliorated the LPS-induced decrease in myocardial contractility. No evidence of inflammatory infiltrate was noted in any of the in vivo studies. The findings of the current study indicate that 1) LPS can induce HMGB1 secretion by viable cardiac myocytes through a TLR4/PI3Kγ signaling pathway, and 2) HMGB1 plays a role in the LPS-induced myocardial contractile dysfunction. The results of the current study also have broader implications (i.e., that viable parenchymal cells, such as cardiac myocytes, participate in the alarmin response).
Timing and Outcomes of Vitreoretinal Surgery after Traumatic Retinal Detachment

Traumatic retinal detachments are a significant cause of morbidity. There are currently no evidence-based guidelines on the appropriate time to perform vitreoretinal surgery to repair a traumatic retinal detachment. Early intervention, within seven days of the inciting trauma, may decrease proliferative vitreoretinopathy and postoperative endophthalmitis. Later intervention may yield a reduced risk of inflammation and hemorrhage, particularly in cases of concomitant open globe injuries. This article reviews the literature on the management of retinal detachments associated with ocular trauma from the years 2006 to 2016. Particular focus was placed on the timing of surgery, concomitant open globe injury, anatomical success rates, visual acuity, and complication rates. In this review, anatomical success was not significantly related to timing of intervention when compared between early and delayed intervention in eyes with and without concomitant open globe injuries. Visual acuities postoperatively varied widely despite timing of intervention due to the large variation in mechanism and extent of ocular injuries. Proliferative vitreoretinopathy was a common complication. Preliminary data indicate that endophthalmitis rates may be lower when early vitreoretinal surgery is performed. There is insufficient data to conclude whether early or delayed surgery leads to improved outcomes, highlighting the need for further research in this domain.
Development of Cell Phone Application for Blood Glucose Self-Monitoring Based on ISO/IEEE 11073 and HL7 CCD

Objectives The objectives of this research were to develop and evaluate a cell phone application based on the standard protocol for personal health devices and the standard information model for personal health records to support effective blood glucose management and standardized service for patients with diabetes. Methods An application was developed for Android 4.0. 3. In addition, an IEEE 11073 Manager, Medical Device Encoding Rule, and Bluetooth Health Device Profile Connector were developed for standardized health communication with a glucometer, and a Continuity of Care Document (CCD) Composer and CCD Parser were developed for CCD document exchange. The developed application was evaluated by five healthcare professionals and 87 users through a questionnaire comprising the following variables: usage intention, effort expectancy, social influence, facilitating condition, perceived risk, and voluntariness. Results As a result of the evaluation of usability, it was confirmed that the developed application is useful for blood glucose self-monitoring by diabetic patients. In particular, the healthcare professionals stated their own views that the application is useful to observe the trends in blood glucose change through the automatic function which records a blood glucose level measured using Bluetooth function, and the function which checks accumulated records of blood glucose levels. Also, a result of the evaluation of usage intention was 3.52 ± 0.42 out of 5 points. Conclusions The application developed by our research team was confirmed by the verification of healthcare professionals that accurate feedback can be provided to healthcare professionals during the management of diabetic patients or education for glucose management.
Toward Secure Edge Networks: Taming Device-to-Device (D2D) Communication in IoT

The growing popularity of Internet-of-Things (IoT) has created the need for network-based traffic anomaly detection systems that could identify misbehaving devices. In this work, we propose a lightweight technique, IoT-guard, for identifying malicious traffic flows. IoT-guard uses semi-supervised learning to distinguish between malicious and benign device behaviours using the network traffic generated by devices. In order to achieve this, we extracted 39 features from network logs and discard any features containing redundant information. After feature selection, fuzzy C-Mean (FCM) algorithm was trained to obtain clusters discriminating benign traffic from malicious traffic. We studied the feature scores in these clusters and use this information to predict the type of new traffic flows. IoT-guard was evaluated using a real-world testbed with more than 30 devices. The results show that IoTguard achieves high accuracy (98%), in differentiating various types of malicious and benign traffic, with low false positive rates. Furthermore, it has low resource footprint and can operate on OpenWRT enabled access points and COTS computing boards.
The MOTIV-HEART Study: A Prospective, Randomized, Single-Blind Pilot Study of Brief Strategic Therapy and Motivational Interviewing among Cardiac Rehabilitation Patients

Background: Psychological distress, biomedical parameters, and unhealthy lifestyles contribute to a poorer prognosis for cardiac disease. Public health's challenge is to motivate patients to utilize self-care. Objective: This prospective, randomized, single-blind pilot study aimed at testing the incremental efficacy of Brief Strategic Therapy (BST) combined with Motivational Interviewing (MI) in improving selected biomedical and psychological outcomes over and beyond those of the stand-alone BST in a residential Cardiac Rehabilitation (CR) program. Method: Fourty-two inpatients (17 females), enrolled in a 1-month CR program, were randomly allocated into two conditions: (a) Three sessions of BST and (b) Three sessions of BST plus MI. Data were collected at baseline, discharge, and after 3 months through phone interviews. Results: At discharge, no significant between-group difference was found in any outcome variable. Changes from pre- to post-treatment within each condition showed significant improvements only in the BST group, where the level of external regulation diminished, and both the participants' self-regulation (Relative Autonomous Motivation Index, RAI) and willingness to change improved. At the 3-month follow-up, within-group analyses on responders (BST = 9; BST + MI = 11) showed a statistically significant improvement in the level of systolic blood pressure in both groups. Discussion: Findings showed no evidence of the incremental efficacy of combining BST and MI over and beyond BST alone on either selected biomedical or psychological outcomes among CR patients. Conclusions: Ends and limitations from the present pilot study should be considered and addressed in future investigations.
A matching circuit tuned, multi-band (WLAN and WiMAX), Class — a power amplifier using 0.25μm-SiGe HBT technology

In this work, a MOS based output matching network is designed and fabricated using IHP (innovations for high performance), 0.25 mum-SiGe HBT process and measured which can give 4 different impedance values. Also, a multi-band, Class-A, power amplifier (PA) has been designed with same technology and the desired output impedances for matching network are taken from the load-pull simulation results of this PA. The behavior of the amplifier has been optimized for 2.4 GHz (WLAN), 3.6 GHz (UWB-WiMAX) and 5.4 GHz (WLAN) frequency bands for high output power. Multi-band characteristic of the amplifier was obtained by using MOS based switching network. Two MOS switches are used for changing the behavior of the matching network and 4 possible states are achieved. Post-Layout simulation results of the PA circuit provided the following performance parameters: output power of 28-dBm, gain value of 26-dB and efficiency value of %19 for the 2.4 GHz WLAN band, output power of 28-dBm, gain value of 22-dB and efficiency value of %20 for the 3.6 GHz UWB-WiMAX band, and output power of 27-dBm, gain value of 23-dB and efficiency value of %17 for the 5.4 GHz WLAN band.