Miracle-dz/UniFAR-FTUs huggingface dataset:
Coated mesalazine (5-aminosalicylic acid) versus sulphasalazine in the treatment of active ulcerative colitis: a randomised trial.

OBJECTIVE--To assess the safety and efficacy of a preparation of mesalazine (5-aminosalicylic acid) coated with a pH dependent resin (Eudragit L) as compared with sulphasalazine in patients with active mild to moderate ulcerative colitis. DESIGN--Eight week randomised double blind parallel group study. SETTING--Forty six gastroenterology outpatient clinics in seven countries. PATIENTS--Two hundred and twenty patients aged 18-70 who met the following criteria: clinical activity index greater than or equal to 6 and endoscopic index greater than or equal to 4; no concomitant treatment for ulcerative colitis; no hypersensitivity to salicylates or sulphonamides. Of the 164 patients eligible for efficacy analysis, 87 received the coated preparation of mesalazine and 77 sulphasalazine. Most of the remaining patients (28 in each group) were ineligible for the efficacy analysis because of treatment with steroid enemas. All pretrial characteristics were comparable in the two treatment groups. INTERVENTIONS--Coated mesalazine (Mesasal) 1.5 g daily or sulphasalazine 3.0 g daily for eight weeks. Compliance monitored by pill counts. END POINT--Clinical and endoscopic remission. MEASUREMENTS AND MAIN RESULTS--Clinical activity measured by daily diary cards, assessment by investigators, and laboratory findings. Endoscopic evaluation at week 8. After four weeks 50 of 70 patients (71%) taking coated mesalazine and 38 of 58 (66%) taking sulphasalazine had achieved remission of their disease by eight weeks remission rates were 74% (37/50 patients) and 81% (35/43) in the two treatment groups respectively. Endoscopic remission at eight weeks was recorded in 20 of 41 patients (49%) taking coated mesalazine and 18 of 38 (47%) taking sulphasalazine. There was a higher incidence of adverse events among patients taking sulphasalazine (25/105; 24%) than among those taking coated mesalazine (16/115; 14%). CONCLUSION--Mesalazine coated with Eudragit L is a safe, logical alternative to sulphasalazine.
New ternary alloy systems for infrared detectors

The emergence of HgCdTe as the most important intrinsic semiconductor alloy system for IR detectors is well established. The future of this material continues to be uncertain because of difficulties associated with its growth and processing. This paper is to devoted technology and performance of IR detectors manufactured from alternative to HgCdTe, new ternary alloy systems, such as InAsSb, HgZnTe, HgMnTe; and III-V superlattices, such as AlGaAs/GaAs superlattice multiple quantum wells.
Intelligent information triage

In many applications, large volumes of time-sensitive textual information require triage: rapid, approximate prioritization for subsequent action. In this paper, we explore the use of prospective indications of the importance of a time-sensitive document, for the purpose of producing better document filtering or ranking. By prospective, we mean importance that could be assessed by actions that occur in the future. For example, a news story may be assessed (retrospectively) as being important, based on events that occurred after the story appeared, such as a stock price plummeting or the issuance of many follow-up stories. If a system could anticipate (prospectively) such occurrences, it could provide a timely indication of importance. Clearly, perfect prescience is impossible. However, sometimes there is sufficient correlation between the content of an information item and the events that occur subsequently. We describe a process for creating and evaluating approximate information-triage procedures that are based on prospective indications. Unlike many information-retrieval applications for which document labeling is a laborious, manual process, for many prospective criteria it is possible to build very large, labeled, training corpora automatically. Such corpora can be used to train text classification procedures that will predict the (prospective) importance of each document. This paper illustrates the process with two case studies, demonstrating the ability to predict whether a news story will be followed by many, very similar news stories, and also whether the stock price of one or more companies associated with a news story will move significantly following the appearance of that story. We conclude by discussing how the comprehensibility of the learned classifiers can be critical to success. }
Online Visual Tracking using Multiple Instance Learning with Instance Significance Estimation

Multiple Instance Learning (MIL) recently provides an appealing way to alleviate the drifting problem in visual tracking. Following the tracking-by-detection framework, an online MILBoost approach is developed that sequentially chooses weak classifiers by maximizing the bag likelihood. In this paper, we extend this idea towards incorporating the instance significance estimation into the online MILBoost framework. First, instead of treating all instances equally, with each instance we associate a significance-coefficient that represents its contribution to the bag likelihood. The coefficients are estimated by a simple Bayesian formula that jointly considers the predictions from several standard MILBoost classifiers. Next, we follow the online boosting framework, and propose a new criterion for the selection of weak classifiers. Experiments with challenging public datasets show that the proposed method outperforms both existing MIL based and boosting based trackers.
kvm : the Linux Virtual Machine Monitor

Virtualization is a hot topic in operating systems these days. It is useful in many scenarios: server consolidation, virtual test environments, and for Linux enthusiasts who still can not decide which distribution is best. Recently, hardware vendors of commodity x86 processors have added virtualization extensions to the instruction set that can be utilized to write relatively simple virtual machine monitors. The Kernel-based Virtual Machine, or kvm, is a new Linux subsystem which leverages these virtualization extensions to add a virtual machine monitor (or hypervisor) capability to Linux. Using kvm, one can create and run multiple virtual machines. These virtual machines appear as normal Linux processes and integrate seamlessly with the rest of the system.
Analyzing the Impact of IS Support on Recruitment Processes: An E-Recruitment Phase Model

The skills and abilities of a company’s employees are a prerequisite for the enterprise to be innovative. In case the know-how needed to accomplish certain tasks is not available internally or cannot be developed within reasonable time, the company needs to address to the external labor market, e.g. by recruiting experts possessing the skill sets required. However, for rare candidate profiles there exists intense competition on the labor market. Thus, the ability to act within short periods of time when interacting with candidates becomes crucial. In the past, multiple elements of IS support provided many different benefits to improve the recruitment process. However, little research to date exists on what forms of IS support are adapted for what application scenarios within the recruitment arena. Therefore, this paper analyzes how the recruitment process can be optimized and what different levels of E-Recruitment adoption can be identified. We present results from quantitative and qualitative research showing that E-Recruitment functionality can be found in most companies nowadays ranging from isolated solutions for singular activities to integrated end-to-end solutions. Based on these findings we derive managerial guidelines for the management of projects in the E-Recruitment field.
Estimation of Time-Varying, Intrinsic and Reflex Dynamic Joint Stiffness during Movement. Application to the Ankle Joint

Dynamic joint stiffness determines the relation between joint position and torque, and plays a vital role in the control of posture and movement. Dynamic joint stiffness can be quantified during quasi-stationary conditions using disturbance experiments, where small position perturbations are applied to the joint and the torque response is recorded. Dynamic joint stiffness is composed of intrinsic and reflex mechanisms that act and change together, so that nonlinear, mathematical models and specialized system identification techniques are necessary to estimate their relative contributions to overall joint stiffness. Quasi-stationary experiments have demonstrated that dynamic joint stiffness is heavily modulated by joint position and voluntary torque. Consequently, during movement, when joint position and torque change rapidly, dynamic joint stiffness will be Time-Varying (TV). This paper introduces a new method to quantify the TV intrinsic and reflex components of dynamic joint stiffness during movement. The algorithm combines ensemble and deterministic approaches for estimation of TV systems; and uses a TV, parallel-cascade, nonlinear system identification technique to separate overall dynamic joint stiffness into intrinsic and reflex components from position and torque records. Simulation studies of a stiffness model, whose parameters varied with time as is expected during walking, demonstrated that the new algorithm accurately tracked the changes in dynamic joint stiffness using as little as 40 gait cycles. The method was also used to estimate the intrinsic and reflex dynamic ankle stiffness from an experiment with a healthy subject during which ankle movements were imposed while the subject maintained a constant muscle contraction. The method identified TV stiffness model parameters that predicted the measured torque very well, accounting for more than 95% of its variance. Moreover, both intrinsic and reflex dynamic stiffness were heavily modulated through the movement in a manner that could not be predicted from quasi-stationary experiments. The new method provides the tool needed to explore the role of dynamic stiffness in the control of movement.
Identification of multiple subclasses of plasma low density lipoproteins in normal humans.

Density gradient ultracentrifugation of low density lipoproteins (LDL) from 12 normal subjects showed multiple, distinct isopycnic bands. Densitometric scanning of the gradient tubes revealed that each band could be assigned to one of four density intervals and that the boundaries of these intervals were consistent among all the subjects. Analytic ultracentrifuge flotation (S(f)(0)) rates were assigned to the four density intervals, and there was a strong correlation between peak S(f)(0) rate and peak isopycnic banding position (R(f)) of the LDL in the 12 subjects. The S(f)(0) value corresponding to the boundary between the two most buoyant LDL density subgroups was 7.5. This value is close to that previously demonstrated to define two LDL subdivisions (S(f)(0) 0-7 and S(f)(0) 7-12) that were discriminated by differing concentrations in men and women, and differing statistical relationships with levels of HDL and VLDL in a normal population. Further delineation of distinct subspecies of LDL was afforded by electrophoresis in 2-16% gradient polyacrylamide gels. Densitometric scans of protein-stained gels revealed multiple peaks, and particle diameters were assigned to these peaks using calibration markers. Particles of diameter >/= 280 A included both IDL and Lp(a), the latter defined by pre-beta mobility on agarose electrophoresis and density > 1.050 g/ml. LDL particles with diameters 220-272 A could be grouped into seven size intervals defined by modes in the distribution of gradient gel electrophoretic peaks in LDL from a group of 68 healthy men and women. Particle diameters of the major peaks in each of seven density subfractions decreased with increasing density of the fractions. However, particles within each of the size groups were distributed across a range of densities. Use of a lipid-staining procedure allowed identification of electrophoretic bands in whole plasma which corresponded to those seen in isolated LDL, eliminating the possibility that ultracentrifugation was responsible for formation of the subspecies detected by the gradient gel procedure. The application of density gradient ultracentrifugation and gradient gel electrophoresis provides a means of characterizing LDL from normal humans in terms of multiple distinct subpopulations which may also prove to have differing metabolic and pathologic properties. -Krauss, R. M. , and D. J. Burke. Identification of multiple subclasses of plasma low density lipoproteins in normal humans.
SYSTEMIC SIDE EFFECTS OF TRANSTYMPANIC STEROIDS

OBJECTIVE Review largest series of patients treated with transtympanic steroids, including outcomes, steroid dosing and adverse outcomes. Review first reported cases of systemic side effects from transtympanic steroids. METHODS A retrospective case series of 166 patients who underwent placement of transtympanic Silverstein tube with microwick for steroid administration was reviewed. RESULTS 5/166 patients developed systemic side effects, 9/166 patients developed local side effects. 48/166 (29%) of patients had a persistent perforation after therapy. The percent of patients with improvement as a function of symptoms: hearing loss 42%, tinnitus 56%, vertigo 68%, aural fullness 25% and dysequilibrium 66%. CONCLUSIONS While our study revealed a significant risk of persistent tympanic membrane perforation, the incidence of systemic and local side effects from transtympanic steroid administration is low.
Combination of turbo coding and cryptography in NONGEO satellite communication systems

Turbo code has the capability of error correction near Shannonpsilas limit. This code is concatenated of 2 recursive convolutional codes with pseudo random interleaving. In this paper secure turbo code performance in Rayleigh, Rician fading and NONGEO satellite channels are simulated and analyzed. Simulation results show that this code has appropriate performance in wireless channel in presence of light shadowing, and good performance in heavy shadowing. This scheme has the advantages of high-speed encryption and decryption with high security, smaller encoder and decoder size and greater efficiency.
Adherence to and Invasion of Vero Cells by Recombinant Escherichia coli Expressing the Outer Membrane Protein rOmpB of Rickettsia japonica

Abstract: Recombinant Escherichia coli expressing the outer membrane protein rOmpB of rickettsiae on the surface were generated. The DNA corresponding to the open reading frame of the ompB gene of a spotted fever group rickettsia, Rickettsia japonica, was amplified by polymerase chain reaction. The amplified fragment was inserted between the Sal I and the Xho I sites of the expression vector pET‐22b(+). E. coli BL21(DE3) was transformed by the constructed plasmid. The recombinant bacteria expressed a recombinant protein with a molecular size of 165 kilodaltons on the surface. The size was consistent with that of the precursor of rOmpB. The protein was reactive with monoclonal antibodies to heat‐labile epitopes of the rOmpB. This result suggested a rather native conformation of the recombinant protein. Immunofluorescence of the recombinant bacteria demonstrated the surface expression of the protein. The recombinant bacteria acquired properties to enter Vero cells. The morphological change was observed by means of transmission electron microscopy and scanning electron microscopy. Adherence triggered the generation of abundant microvilli and membrane ruffling for the cells to engulf the bacteria The manner of entry of the recombinant bacteria was similar to that of rickettsiae. Thus it is suggested that the rOmpB plays an important role in the adherence to and invasion of host cells by rickettsiae. Moreover, since even the recombinant rOmpB precursor protein expressed on the surface of the bacteria promotes adherence and invasion, the conformation of the functional domain may be similar to that of the processed mature rOmpB.
Modeling Business Process of Web Services with an Extended STRIPS Operations to Detection Feature Interaction Problems Runtime

Service-Oriented Computing is benefit of interoperation among services. Current service-oriented computing research is much more concerning the low level interoperation among services, such as service discovery, service composition etc. However, the high level research issue-the feature interaction problem is also challenging the interoperation of service-oriented computing. Traditional feature interaction methods are focused on the service design phrase with formal methods or software engineering analysis. Autonomy and distribution of service deploying style have made the needs of runtime detecting and resolving feature interaction in SOC research community. This paper investigates the detection of feature interactions in web services at runtime and proposes ESTRIPs, an extended STRIPS operation conflict-free of services in business process detection method, which reasons from OWL-S and SWRL combined with runtime SOAP messages. First, we give the model of the feature interaction problem in business process during its execution and then the ESTRIPS method given in detail. The implementation of a prototype is illustrated. Using a real world scenario shows the plausibility of our method of detecting feature interactions of business process.
Performing Stance Detection on Twitter Data using Computational Linguistics Techniques

As humans, we can often detect from a persons utterances if he or she is in favor of or against a given target entity (topic, product, another person, etc). But from the perspective of a computer, we need means to automatically deduce the stance of the tweeter, given just the tweet text. In this paper, we present our results of performing stance detection on twitter data using a supervised approach. We begin by extracting bag-of-words to perform classification using TIMBL, then try and optimize the features to improve stance detection accuracy, followed by extending the dataset with two sets of lexicons - arguing, and MPQA subjectivity; next we explore the MALT parser and construct features using its dependency triples, finally we perform analysis using Scikit-learn Random Forest implementation.
Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons

The autoencoder algorithm is a simple but powerful unsupervised method for training neural networks. Autoencoder networks can learn sparse distributed codes similar to those seen in cortical sensory areas such as visual area V1, but they can also be stacked to learn increasingly abstract representations. Several computational neuroscience models of sensory areas, including Olshausen & Field’s Sparse Coding algorithm, can be seen as autoencoder variants, and autoencoders have seen extensive use in the machine learning community. Despite their power and versatility, autoencoders have been difficult to implement in a biologically realistic fashion. The challenges include their need to calculate differences between two neuronal activities and their requirement for learning rules which lead to identical changes at feedforward and feedback connections. Here, we study a biologically realistic network of integrate-and-fire neurons with anatomical connectivity and synaptic plasticity that closely matches that observed in cortical sensory areas. Our choice of synaptic plasticity rules is inspired by recent experimental and theoretical results suggesting that learning at feedback connections may have a different form from learning at feedforward connections, and our results depend critically on this novel choice of plasticity rules. Specifically, we propose that plasticity rules at feedforward versus feedback connections are temporally opposed versions of spike-timing dependent plasticity (STDP), leading to a symmetric combined rule we call Mirrored STDP (mSTDP). We show that with mSTDP, our network follows a learning rule that approximately minimizes an autoencoder loss function. When trained with whitened natural image patches, the learned synaptic weights resemble the receptive fields seen in V1. Our results use realistic synaptic plasticity rules to show that the powerful autoencoder learning algorithm could be within the reach of real biological networks.
High Stored Iron Levels Are Associated With Excess Risk of Myocardial Infarction in Eastern Finnish Men

BackgroundIron can induce lipid peroxidation in vitro and in vivo in humans and has promoted ischemic myocardial injury in experimental animals. We tested the hypothesis that high serum ferritin concentration and high dietary iron intake are associated with an excess risk of acute myocardial infarction. Methods and ResultsRandomly selected men (n=1,931), aged 42, 48, 54, or 60 years, who had no symptomatic coronary heart disease at entry, were examined in the Kuopio Ischaemic Heart Disease Risk Factor Study (KIHD) in Eastern Finland between 1984 and 1989. Fifty-one of these men experienced an acute myocardial infarction during an average follow-up of 3 years. On the basis of a Cox proportional hazards model adjusting for age, examination year, cigarette pack-years, ischemic ECG in exercise test, maximal oxygen uptake, systolic blood pressure, blood glucose, serum copper, blood leukocyte count, and serum high density lipoprotein cholesterol, apolipoprotein B, and triglyceride concentrations, men with serum ferritin ≥200 μg/l had a 2.2-fold (95% CI, 1.2-4.0; p<0.01) risk factor-adjusted risk of acute myocardial infarction compared with men with a lower serum ferritin. An elevated serum ferritin was a strong risk factor for acute myocardial infarction in all multivariate models. This association was stronger in men with serum low density lipoprotein cholesterol concentration of 5.0 mmol/l (193 mg/dl) or more than in others. Also, dietary iron intake had a significant association with the disease risk in a Cox model with the same covariates. ConclusionsOur data suggest that a high stored iron level, as assessed by elevated serum ferritin concentration, is a risk factor for coronary heart disease.
Identification and functional differentiation of two type I fatty acid synthases in Brevibacterium ammoniagenes

The fatty acid synthase (FAS) from Brevibacterium ammoniagenes is a homohexameric multienzyme complex that catalyzes the synthesis of both saturated and unsaturated fatty acids. By immunological screening of a B. ammoniagenes expression library, an fas DNA fragment was isolated and subsequently used to clone the entire gene together with its flanking sequences. Within 10,525 bp of sequenced DNA, the 9,189-bp FAS coding region was identified, corresponding to a protein of 3,063 amino acids with a molecular mass of 324,910 Da. This gene (fasA) encodes, at its 5' end, the same amino acid sequence as is observed with purified B. ammoniagenes FAS. A second reading frame encoding another B. ammoniagenes FAS variant (FasB) had been identified previously. Both sequences are colinear and exhibit 61 and 47% identity at the DNA and protein levels, respectively. By using specific antibodies raised against a unique peptide sequence of FasB, this enzyme was shown to represent only 5 to 10% of the cellular FAS protein. Insertional inactivation of the FasB coding sequence causes no defective phenotype, while fasA disruptants require oleic acid for growth. Correspondingly, oleate-dependent B. ammoniagenes cells obtained by ethyl methanesulfonate mutagenesis were complemented by transformation with fasA DNA but not with fasB DNA. The data indicate that B. ammoniagenes contains two related though differently expressed type I FASs. FasA represents the bulk of cellular FAS protein and catalyzes the synthesis of both saturated and unsaturated fatty acids, while the minor variant, FasB, cannot catalyze the synthesis of oleic acid.