Miracle-dz/UniFAR-FTUs huggingface dataset:
Twitter Sentiment Analysis using Machine Learning and Knowledge-based Approach

Sentiment analysis is mainly concerned with identifying and classifying opinions or emotions that are expressed within a text. These days, sharing opinions and expressing emotions through social networking websites has become very common. Therefore, a large amount of data is generated each day, on which mining can be effectively performed to retrieve quality information. Sentiment analysis on such data can prove to be instrumental in generating an aggregated opinion on certain products. Twitter sentiment analysis often becomes a difficult task due to the presence of slangs and misspellings. Also, we constantly encounter new words, which makes it more difficult to analyze and compute the sentiment as compared to the usual sentiment analysis. Twitter restricts the length of a tweet to 140 characters. Thus, extracting valuable information from short texts is yet another challenge. Knowledge-based approach and machine learning can contribute considerably towards the analysis of sentiments from tweets. In this paper, we analyze people’s sentiments in their tweets about certain companies. Computing a basic sentiment score and then classifying them as positive or negative would help to serve the company by providing them critical reviews about their products from people worldwide.
Toward A Universal Psychological Structure of Human Values

We constructed a theory of the universal types of values as criteria by viewing values as cognitive representations of three universal requirements: (a) biological needs, (b) interactional requirements for interpersonal coordination, and (c) societal demands for group welfare and survival. From these requirements, we have derived and presented conceptual and operational definitions for eight motivational domains of values: enjoyment, security, social power, achievement, sehxiirection, prosocial, restrictive conformity, and maturity. In addition, we have mapped values according to the interests they serve (individualistic vs. collectivist) and the type of goal to which they refer (terminal vs. instrumental). We postulated that the structural organization of value systems reflects the degree to which giving high priority simultaneously to different values is motivationajly and practically feasible or contradictory. To test our theory, we performed smallest space analyses on ratings given by subjects from Israel (N = 455) and Germany (N = 331) of the importance of 36 Rokeach values as guiding principles in their lives. Partitioning of the obtained multidimensional space into regions revealed that people do indeed discriminate among values according to our a priori specifications of goal types, interests served, and motivational domains in both societies. Moreover, the motivational domains of values are organized dynamically in relation to one another in both societies, as predicted by the patterns of compatible or contradictory motivation and practical consequences. We have noted additional values and domains possibly needed for a universal scheme as well as potential applications of this approach for comparing the meanings, structure, and importance of values across cultures, for analyzing relations between social structure and values, and for predicting and interpreting relations of values to attitudes and behavior.
Risk of cardiovascular events associated with current exposure to HIV antiretroviral therapies in a US veteran population.

BACKGROUND To characterize the association of antiretroviral drug combinations on risk of cardiovascular events. METHODS Certain antiretroviral medications for human immunodeficiency virus (HIV) have been implicated in increasing risk of cardiovascular disease. However, antiretroviral drugs are typically prescribed in combination. We characterized the association of current exposure to antiretroviral drug combinations on risk of cardiovascular events including myocardial infarction, stroke, percutaneous coronary intervention, and coronary artery bypass surgery. We used the Veterans Health Administration Clinical Case Registry to analyze data from 24 510 patients infected with HIV from January 1996 through December 2009. We assessed the association of current exposure to 15 antiretroviral drugs and 23 prespecified combinations of agents on the risk of cardiovascular event by using marginal structural models and Cox models extended to accommodate time-dependent variables. RESULTS Over 164 059 person-years of follow-up, 934 patients had a cardiovascular event. Current exposure to abacavir, efavirenz, lamivudine, and zidovudine was significantly associated with increased risk of cardiovascular event, with odds ratios ranging from 1.40 to 1.53. Five combinations were significantly associated with increased risk of cardiovascular event, all of which involved lamivudine. One of these-efavirenz, lamivudine, and zidovudine-was the second most commonly used combination and was associated with a risk of cardiovascular event that is 1.60 times that of patients not currently exposed to the combination (odds ratio = 1.60, 95% confidence interval, 1.25-2.04). CONCLUSIONS In the VA cohort, exposure to both individual drugs and drug combinations was associated with modestly increased risk of a cardiovascular event.
Analysis of Probabilistic Forwarding in Opportunistic Networks Using the Percolation Theory

Opportunistic networks are mobile networks that rely on the store-carry-and-forward paradigm, using contacts between nodes to opportunistically transfer data. For this reason, traditional routing mechanisms are no longer suitable. To increase the success of successful message delivery, different probability-based techniques were previously studies by various authors. Here we address the question of how much of the forwarding probability of an ON has to be increased, in order for the network to achieve a given desired hit rate. We propose an approach based on percolation theory, which explains the influence of forwarding probability in a network's performance, and we try to prove that such a phenomenon is indeed present in ONs. We demonstrate, through extensive experiments, that the transition phase can be indeed observed in ONs when the forwarding probability is varied from 0 to 0.1. After the transition phase, little benefit is obtained in terms of reachability (exponential relationship) when the forwarding probability is increased. In contrast, the delivery cost increases much faster than the reachability after the transition phase. Consequently, increasing the forwarding probability only impacts on metrics like the delivery cost and latency since high reachability can be assumed in opportunistic networks.
Microfluidics on foil: State of the art and new developments

The concept of microfluidics on foil opens up new opportunities for combining the advantages of having a flexible substrate with reel-to-reel processing, which has the potential to be the basis for extremely cheap micro products. To reach this goal, foil substrates must be combined with micro-manufacturing technologies that are well adapted to these substrates. Some technologies are already available, some are the subject of current research, and some still have to be conceived. In the current paper, technologies such as reel-to-reel embossing, reel-to-reel laminating, and laser ablation/cutting as well as laser welding will be discussed. The discussions include a brief review of the state of the art as well as a report on latest research results stemming from research by the present authors. Furthermore, this paper shows the vision of what can be achieved if foil-based technologies, such as polymer (opto-)electronics and microfluidics are combined. A polymer electronics-based alcohol sensor is presented as an example system.
Resource Description Framework (RDF)

The Resource Description Framework (RDF) is the standard knowledge representation language for the Semantic Web, an evolution of the World Wide Web that aims to provide a well-founded infrastructure for publishing, sharing and querying structured data. This article provides an introduction to RDF and its related vocabulary definition language RDF Schema, and explains its relationship with the OWL Web Ontology Language. Finally, it provides an overview of the historical development of RDF and related languages for Web metadata.
Study on Autogenous Deformation of Concrete Incorporating MgO as Expansive Agent

In order to establish a mathematic model of the autogenous deformation of concrete incorporating MgO as expansive agent, we study the characteristics of it. Based on the results of testing researches and testing data, we get a mathematic model, which can clearly reveal the characteristics of autogenous deformation of concrete incorporating MgO as expansive agent. Autogenous deformation of concrete incorporating MgO as expansive agent is steady, the expansion is not infinite and there is no retrogress. Age mainly influences the basic equation of autogenous deformation. The content of MgO (or fly ash) and temperature will magnify (or reduce) the deformation.
Low-Power 56Gb/s NRZ Microring Modulator Driver in 28nm FDSOI CMOS

High speed optical interconnects require low-power compact electro-optical transmit modules comprising driver circuits and optical modulators. This letter presents a low power 56 Gb/s non-return-to-zero CMOS inverter-based driver in 28 nm fully depleted silicon-on-insulator CMOS driving a 46 GHz silicon photonic microring modulator. The driver delivers 1 Vpp to the microring modulator from a 75 mVpp input while only consuming 40 mW (710 fJ/bit at 56 Gb/s). The realized transmitter shows 4 dB extinction ratio when running of a 1 V supply voltage. Transmission experiments up to 2 km of single mode fiber show a bit-error-ratio less than $1\cdot 10^{-9}$ at 56 Gb/s.
Low-temperature epitaxial Si absorber layers grown by electron-cyclotron resonance chemical vapor deposition

We studied the homo-epitaxial growth of Si layers on crystalline Si(100) substrates in the temperature range from 420/spl deg/C to 510/spl deg/C using electron-cyclotron resonance chemical vapour deposition (ECRCVD). Above 480/spl deg/C the films grew epitaxially. Films deposited with a growth rate of 15 nm/min at 510/spl deg/C are of excellent crystallographic quality up to layer thicknesses as large as 2.23 /spl mu/m. With increasing thickness local highly defective regions were formed in the epitaxial films. They are cone-shaped and consist of thin polycrystalline needles only. An abrupt breakdown of epitaxial growth as usually reported in literature was not observed. The non-intentionally doped films are n-type independently on the substrate temperature. The film/substrate interfaces were analyzed by I-V measurements.
Structure and optical properties of ultrathin p-phenylene oligomer films on dielectrics

A systematic investigation has been performed in order to determine the unit cells of ultrathin p-nP films grown under surface science conditions on dielectrics. We have employed low energy electron diffraction (LEED) as well as polarization dependent linear absorption spectroscopy on films deposited onto alkali halide (NaCl, KCl, NaF, LiF, KBr) and mica(0001) single crystals at various substrate temperatures. Surface unit cells of the films are determined as a function of chain length n(n=3-6) and deposition parameters. Linear optical spectroscopy reveals a strong dichroism and allows us to distinguish between laying and standing molecules on the substrate. In contrast to the alkali halides, we observe on mica at elevated surface temperatures the growth of single crystalline needles, the orientation of which is controlled by the presence of surface dipoles on the cleaved mica surface.
Biochemical and Structural Analysis of Substrate Specificity of a Phenylalanine Ammonia-Lyase1

The major phenylalanine ammonia-lyases from Sorghum bicolor were characterized through crystal structures, molecular docking, site-directed mutagenesis, and kinetic and thermodynamic analyses. Phenylalanine ammonia-lyase (PAL) is the first enzyme of the general phenylpropanoid pathway catalyzing the nonoxidative elimination of ammonia from l-phenylalanine to give trans-cinnamate. In monocots, PAL also displays tyrosine ammonia lyase (TAL) activity, leading to the formation of p-coumaric acid. The catalytic mechanism and substrate specificity of a major PAL from sorghum (Sorghum bicolor; SbPAL1), a strategic plant for bioenergy production, were deduced from crystal structures, molecular docking, site-directed mutagenesis, and kinetic and thermodynamic analyses. This first crystal structure of a monocotyledonous PAL displayed a unique conformation in its flexible inner loop of the 4-methylidene-imidazole-5-one (MIO) domain compared with that of dicotyledonous plants. The side chain of histidine-123 in the MIO domain dictated the distance between the catalytic MIO prosthetic group created from 189Ala-Ser-Gly191 residues and the bound l-phenylalanine and l-tyrosine, conferring the deamination reaction through either the Friedel-Crafts or E2 reaction mechanism. Several recombinant mutant SbPAL1 enzymes were generated via structure-guided mutagenesis, one of which, H123F-SbPAL1, has 6.2 times greater PAL activity without significant TAL activity. Additional PAL isozymes of sorghum were characterized and categorized into three groups. Taken together, this approach identified critical residues and explained substrate preferences among PAL isozymes in sorghum and other monocots, which can serve as the basis for the engineering of plants with enhanced biomass conversion properties, disease resistance, or nutritional quality.
Interferon-free combination therapies for the treatment of hepatitis C: current insights

The hepatitis C virus (HCV) treatment landscape has rapidly changed over the past 5 years. The development of direct-acting antiviral (DAA) agents that specifically target various steps in the HCV lifecycle has revolutionized therapeutic options for patients with HCV, with the development of highly effective and well-tolerated oral interferon-free regimens. There are many DAAs that are currently in development or have recently been approved, which target different nonstructural HCV proteins and host targets that are essential for HCV replication. This review will focus on the different classes of DAAs and the various combinations that are in advanced development for the treatment of chronic HCV infection and will focus on the different regimens in specific patient populations.
Automatic Surface Characterization for Micro-Structured Surfaces Fabricated by Fast Tool Servo Diamond Turning

Fast tool servo diamond turning is a promising machining method for precision and complex micro-structured surfaces with spatial wavelength above tens of microns. It is crucial to measure and characterize the micro-structured surfaces to sub-micrometer form accuracy. The general purpose measurement instruments are not able to evaluate the true form accuracy between the measured surface and designed surface. Therefore, in this paper an automatic surface characterization method is proposed to evaluate the form accuracy for micro-structured surfaces. The fabricated surfaces can be measured by any high-resolution measurement instruments. After the surface measurement, an iterative closest point (ICP) algorithm is modified to align the measured surfaces to the designed surfaces with the form error evenly distributed over the whole surface. After alignment, the designed surface height corresponding to each measured point is calculated to form the areal error map. 3D surface parameters are chosen and calculated from the error map to characterize the surface form error. Experimental results demonstrate the effectiveness of the proposed surface characterization method.
Dexterity measures for design and control of manipulators

The authors investigate dexterity measures of a manipulator based on its Jacobian matrix. The goal is to derive dexterity measures which can be used for both design and control of a manipulator. Generally, a dexterity measure must be independent of the scale of a manipulator for design, and must be expressed analytically so that it can be used for real-time control. Every dexterity measure must bear a physical meaning. The measure of manipulability has an analytical expression, but it depends on the scale of a manipulator. On the other hand, the condition number is independent of the scale, but cannot be expressed analytically. These two main problems (scale dependency and analytical expression) of previous dexterity measures derived from the Jacobian matrix are solved and applied in design and control of manipulators. In addition, a dexterity measure called the measure of isotropy is introduced. <<ETX>>
Forecasting Unusual Infection of Patient used by Irregular Weighted Point Set

Mining association rule is a key issue in data mining. In any case, the standard models ignore the distinction among the exchanges, and the weighted association rule mining does not transform on databases with just binary attributes. Paper propose a novel continuous examples and execute a tree (FPtree) structure, which is an increased prefix-tree structure for securing compacted, discriminating data about examples, and make a fit FP-tree- based mining system, FP enhanced capacity algorithm is used, for mining the complete game plan of examples by illustration incessant development. Here in this paper handles the motivation behind making remarkable and weighted itemsets, i.e. rare weighted item set mining issue. The two novel brightness measures are proposed for figuring the infrequent weighted itemset mining issue. Also, the algorithm are handled which perform IWI which is more insignificant IWI mining. Moreover we utilized the rare itemset for choice based structure. The general issue of the start of reliable definite rules is troublesome for the grounds that hypothetically no inciting technique with no other person can promise the rightness of influenced theories. In this way this framework expects the disorder with the uncommon signs. Usage study demonstrates that proposed algorithm upgrades the structure which is successful and versatile for mining both long and short diagnostics rules. Structure upgrades aftereffects of foreseeing rare diseases of patient.
Endoscopic Submucosal Dissection for Treatment of Patients Aged 75 Years and over with Esophageal Cancer

Background. Although many reports concerning the use of endoscopic submucosal dissection (ESD) for esophageal cancer have been published, the feasibility of ESD in elderly patients has not been reported. Therefore, we evaluated the efficacy and safety of ESD for treating early esophageal cancer in elderly patients. Methods. A total of 62 cases (52 men, 10 women; mean age ± standard deviation, 66.5 ± 10.5 years) for which the first resection (first treatment) of esophageal cancer was performed by ESD were identified from 77 consecutive esophageal epithelial cancers in 67 patients treated at our institution from January 2005 to March 2011. Patient characteristics, clinical findings, and outcomes were retrospectively assessed for patients separated into older (aged 75 years and older) and younger (aged under 75 years) groups. Results. No significant differences in specimen size, procedure time, median length of the hospital stay (8 versus 9 days; P = 0.252) or procedure-associated complications (8% versus 27%; P = 0.264) were observed between the older (n = 13) and younger (n = 49) groups. Lesions were completely resected in 12 patients and 44 patients, in the younger and older groups, respectively, and the curative resection rate was 77% and 59%, respectively. There were no deaths attributable to procedure-associated complications. Conclusions. ESD is an effective treatment for early esophageal cancer and is well tolerated by elderly patients.
PRIORS FOR ADVERSARIAL AU-TOENCODERS

Recent studies show that the choice of the prior has a profound effect on the expressiveness of deep latent factor models. In this paper, we propose to learn the prior from data for adversarial autoencoders (AAEs). We introduce the notion of code generators to transform manually selected simple priors into ones that can better characterize the data distribution.
Relaxed Biquadratic Optimization for Joint Filter-Signal Design in Signal-Dependent STAP

We investigate an alternative solution method to the joint signal-beamformer optimization problem considered in a recent publication devoted to this topic. First, we directly demonstrate that the problem, which minimizes the received noise, interference, and clutter power under a minimum variance distortionless response constraint, is generally nonconvex and we provide insight into the nature of the nonconvexity. Second, we employ the theory of biquadratic optimization and semidefinite relaxations to produce a relaxed version of the problem, which we show to be convex. The optimality conditions of this relaxed problem are examined and a variety of potential solutions are found, both analytically and numerically. These solutions are then compared to existing alternating minimization schemes.
A Robust Document Image Binarization Technique for Degraded Document Images

Segmentation of text from badly degraded document images is a very challenging task due to the high inter/intra-variation between the document background and the foreground text of different document images. In this paper, we propose a novel document image binarization technique that addresses these issues by using adaptive image contrast. The adaptive image contrast is a combination of the local image contrast and the local image gradient that is tolerant to text and background variation caused by different types of document degradations. In the proposed technique, an adaptive contrast map is ﬁrst constructed for an input degraded document image. The contrast map is then binarized and combined with Canny’s edge map to identify the text stroke edge pixels. The document text is further segmented by a local threshold that is estimated based on the intensities of detected text stroke edge pixels within a local window. The proposed method is simple, robust and involves minimum parameter tuning. It has been tested on three public datasets that were used in the recent Document Image Binarization Contest (DIBCO) 2009 & 2011 and Handwritten Document Image Binarization Contest (H-DIBCO) 2010 and achieves accuracies of 93 . 5% , 87 . 8% and 92 . 03% , respectively, that are signiﬁcantly higher than or close to that of the best-performing methods reported in the three contests. Experiments on the Bickley diary dataset that consists of several challenging bad quality document images also show the superior performance of our proposed method, compared with other techniques.