Miracle-dz/UniFAR-FTUs huggingface dataset:
Thrombin and Antithrombotics

From injury through healing, thrombin has several important functions in blood clotting, subsequent clot lysis, and tissue repair. These include edema, inflammation, cell recruitment, cellular releases, transformations, mitogenesis, and angiogenesis. Thrombin also participates in disease states, such as venous thrombosis, coronary thrombosis, stroke, and pulmonary emboli, among others and is implicated in atherosclerosis, the growth and metastasis of certain cancers, Alzheimer's disease, and perhaps other conditions. Thrombin must be continually generated to sustain normal and pathogenic processes. This is because of a variety of consumptive mechanisms. Unlike other activated factors in thrombotic and fibrinolytic pathways, and because thrombin promotes its own generation (feedback and cellular activation), thrombin is a primary target for therapeutics. Besides recombinant hirudins, Argatroban (Novastan) and Bivalirudin (Hirulog) are promising thrombin-directed inhibitors for antithrombotic intervention.
Survey on usable and secure two-factor authentication

System resources are usually not retrieved through deception by users who are not legal. This is basically ensured by Authentication. Text password is one of the forms of user authentication that is very suitable due to its ease and convenience. However such passwords are prone to be stolen and negotiated under different threats and vulnerabilities. Users often select weak passwords and tend to use the same password across different websites. Users are required to remember more, longer and changing passwords. An adversary can launch several passwords stealing attacks and gain access to user's personal data. It is evident that a convenient and more secure form of user authentication is necessary. The authentication mechanism called Two-factor authentication is introduced to overcome this drawback. Two factors compared to one factor generally deliver a higher level of security assurance. Various schemes have been proposed which allow the users to freely choose their password like PassFile, and thus eliminate the problem of entering and remembering the reusable password. These schemes use a smart card and are secure against various possible attacks.
Fast Fourier Transform and its Applications to Integer Knapsack Problems

In this paper we suggest a new e.cient technique for solving integer knapsack problems. Our algorithms can be seen as application of Fast Fourier Transform to generating functions of integer polytopes.Using this approach, it is possible to count the number of boolean solutions of a single n-dimensional Diophantine equation {a, x} = b in O(//a//1 ln//a1//lnn) operations. Another application example is an integer knapsack optimization problem of volume b, which can be solved in O(//a//1 ln//a1//ln n + b lnsq.2n) operations of exact real arithmetics. These complexity estimates improve by a factor of n the complexity of the traditional Dynamic Programming technique.
A 1-Kb Bcl-2-PCR Fragment Detection in a Patient With Follicular Lymphoma and Development of a New Diagnostic PCR Method

The t(14;18) translocation is a useful marker to characterize follicular lymphoma and to monitor residual disease. The polymerase chain reaction (PCR) is a powerful technique to detect this translocation. Located on chromosome 18, within the Bcl-2 gene, breakpoints occur mainly in the 3´ untranslated region, in the third exon of Bcl-2 (MBR region). In this study, the authors amplified MBR breakpoints by PCR and found an unexpectedly large fragment of 1 Kb that corresponds to a recently described new breakpoint in the Bcl-2 gene. With a new primer set, a further previously considered t(14;18)-unrelated tumor was in fact positive for this new breakpoint.
Sensitivity of the EOQ Model to Parameter Estimates

The Economic Order Quantity (EOQ) model for independent demand is well known to be somewhat insensitive to the choice of order quantity. The cost goes up as the square root of the ratio of the actual order quantity to that of the optimal order quantity. The question arises as to how sensitive this cost is to parameter estimates. This paper extends the work by T. J. Lowe and L. B. Schwarz to show that under minimax and expected value criteria, the sensitivity of the cost to the parameters of the model grows as the fourth root of the uncertainty in the values of the parameters. Furthermore, for a wide class of distributions, including the beta (hence, uniform) and the gamma (hence, exponentials), a tight bound exists for the expected error.
A Novel Compact Dual-Band Antenna Array With High Isolations Realized Using the Neutralization Technique

A novel compact dual-band antenna array with high isolations is presented in this paper. It consists of four antenna elements with two feeding networks, and it operates at dual-band of 0.89-0.96 and 1.7-2.2 GHz with return loss more than 9 dB, respectively. Two feeding networks are made of a wideband balun and a Wilkinson power divider, respectively. The two-port symmetrical array is constructed using the neutralization technique (NT), leading to the array port isolation over 30 dB from 0.5 to 3.0 GHz. Such a compact dual-band antenna array is realized and its gains and normalized patterns for both ports P1 and P2 are measured, with good agreements obtained in comparison with the simulated ones.
Re-Investigation of Generalized Integrator Based Filters From a First-Order-System Perspective

The generalized integrator (GI)-based filters can be categorized into two types: one is related to quadrature signal generator (QSG), and the other is related to sequence filter (SF). The QSG is used for generating the in-quadrature sinusoidal signals and the SF works for extracting the symmetrical sequence components. The signals generated by QSG and SF are useful in many applications, such as grid synchronization and harmonic estimation. However, the principles of QSG and SF are usually explained by either differential equations or transfer functions, which are not appropriate for analyzing some extended structures and thus restrict their applications. To overcome the drawback, this paper uses the first-order-system concept to re-investigate the GI-based filters, with which their working principles can be intuitively understood and their structure correlations can be easily discovered. Moreover, the proposed analysis method also provides the convenience for developing improved structures. To illustrate it, two improved filters are presented to enhance the performance of the basic QSG and SF. Finally, experimental results verify the effectiveness of the proposed method.
Project snowflake: non-blocking safe manual memory management in .NET

Garbage collection greatly improves programmer productivity and ensures memory safety. Manual memory management on the other hand often delivers better performance but is typically unsafe and can lead to system crashes or security vulnerabilities. We propose integrating safe manual memory management with garbage collection in the . NET runtime to get the best of both worlds. In our design, programmers can choose between allocating objects in the garbage collected heap or the manual heap. All existing applications run unmodified, and without any performance degradation, using the garbage collected heap. Our programming model for manual memory management is flexible: although objects in the manual heap can have a single owning pointer, we allow deallocation at any program point and concurrent sharing of these objects amongst all the threads in the program. Experimental results from our . NET CoreCLR implementation on real-world applications show substantial performance gains especially in multithreaded scenarios: up to 3x savings in peak working sets and 2x improvements in runtime.
Monetary Policy According to HANK

We revisit the transmission mechanism of monetary policy for household consumption in a Heterogeneous Agent New Keynesian (HANK) model. The model yields empirically realistic distributions of household wealth and marginal propensities to consume because of two key features: multiple assets with different degrees of liquidity and an idiosyncratic income process with leptokurtic income changes. In this environment, the indirect effects of an unexpected cut in interest rates, which operate through a general equilibrium increase in labor demand, far outweigh direct effects such as intertemporal substitution. This finding is in stark contrast to small- and medium-scale Representative Agent New Keynesian (RANK) economies, where intertemporal substitution drives virtually all of the transmission from interest rates to consumption.
A Randomized Trial of Two Cover Gowns Comparing Contamination of Healthcare Personnel During Removal of Personal Protective Equipment

In a randomized trial, a gown designed to allow easy removal at the neck and with increased skin coverage and snugness of fit at the wrist significantly reduced contamination of personnel during personal protective equipment (PPE) removal. Our results suggest that simple modifications of PPE can reduce contamination of personnel. Infect Control Hosp Epidemiol 2018;39:97–100
Atomistic simulation on mechanical behaviors of Al/SiC nanocomposites

Molecular dynamics (MD) simulations were carried out to study the mechanical properties of co-continuous Al/SiC nanocomposites under tensile loading. Three cases of different models were implemented to investigate the influence of volume fraction (Vf) of SiC, thickness of SiC skeletons and shape of Al nanowire on the mechanical properties of the nanocomposites. It is found that the ultimate strength and Young's modulus of nanocomposites increase nonlinearly with the Vf of SiC, whereas the limit strains decrease with the increasing Vf of SiC. The Young's modulus obtained by MD simulations are in good agreement with the prediction by micromechanics methods and experimental results. In addition, the thickness of SiC skeletons and the shape of Al nanowire have a significant impact on the mechanical behaviors of co-continuous Al-SiC nanocomposites. This study on the mechanical properties of co-continuous Al-SiC nanocomposites will be helpful to further understanding the mechanical behaviors of the metal/ceramics co-continuous composites.
Modeling of passively Q-switched Er/sup 3+//Yb/sup 3+/-codoped clad-pumped fiber lasers

We present the modeling of passively Q-switched Er/sup 3+//Yb/sup 3+/-codoped double-clad fiber lasers (EYDFL). Both two-level and three-level saturable absorbers (SAs) are used. The model is based on detailed rate equations of SAs, Er/sup 3+/, and Yb/sup 3+/ populations in the fiber, and light propagation equations including spontaneous emissions due to both Er/sup 3+/ and Yb/sup 3+/. Laser output characteristics including pulse energy, width, peak power, repetition frequency (PRF), and average power are computed as functions pump power, fiber length, single-mode/multi-mode fibers, Er/sup 3+//Yb/sup 3+/ concentrations, out-coupling reflectivity, focus area on the SA, and SA doping and length. Several transition metal-doped crystal SAs and semiconductor SA mirrors (SESAM) are considered and compared.
A Machine Learning-Based Approach to Detect Web Service Design Defects

Design defects are symptoms of poor design and implementation solutions adopted by developers during the development of their software systems. While the research community devoted a lot of effort to studying and devising approaches for detecting the traditional design defects in object-oriented (OO) applications, little knowledge and support is available for an emerging category of Web service interface design defects. Indeed, it has been shown that service designers and developers tend to pay little attention to their service interfaces design. Such design defects can be subjectively interpreted and hence detected in different ways. In this paper, we propose a novel approach, named WS3D, using machine learning techniques that combines Support Vector Machine (SVM) and Simulated Annealing (SA) to learn from real world examples of service design defects. WS3D has been empirically evaluated on a benchmark of Web services from 14 different application domains. We compared WS3D with the state-of-theart approaches which rely on traditional declarative techniques to detect service design defects by combining metrics and threshold values. Results show that WS3D outperforms the the compared approaches in terms of accuracy with a precision and recall scores of 91% and 94%, respectively.
Verification and Validation for Java Classes using Design by Contract. The Modular External Approach

—Since the conception of JML, many tools, applications and implementations have been done. In this context, the users or developers who want to use JML seem surounded by many of these tools, applications and so on. Looking for a common infrastructure and an independent language to provide a bridge between these tools and JML, we developed an approach to embedded contracts in XML for Java: XJML. This approach offer us the ability to separate preconditions, posconditions and class invariants using JML and XML, so we made a front-end which can process Runtime Assertion Checking, Extended Static Checking and Full Static Program Veriﬁ-cation. Besides, the capabilities for this front-end can be extended and easily implemented thanks to XML. We believe that XJML is an easy way to start the building of a Graphic User Interface delivering in this way a friendly and IDE independency to developers community wich want to work with JML.
Identification of Web Communities Using Distributed Learning Automata and Association Rules Mining

A collection of web pages which are about a common topic and are created by individuals or any kind of associations that have a common interest on that specific topic is called a web community. Since at present, the size of the web is about 3 billion pages and it is still growing very fast, identification of web communities has become an increasingly hard task. In this paper, we used distributed learning Automata and mining association rules to identify we communities. Our proposed method is the same [1] that uses distributed learning automata and mining association rules to calculate hub and authority scores of web pages, which causes most cases unrelated to the topic, as members of the community web pages not considered. Our proposed method, are compared with the approaches of [1] and [2], and the results show that the our proposed is efficient.
Incremental organ segmentation with machine learning techniques : application to radiotherapy

Radiotherapy is a cancer treatment modality that can be considered as a ballistic problem where the tumour must be irradiated while sparing the surrounding healthy organs. Before the beginning of the treatment, the radiation oncologist draws the contours of the organs at risk, tumour and nodal areas on an image of the patient. The accuracy of these contours is crucial to deliver an optimal treatment. In practice, manual drawing is a quite lengthy and repetitive operation, which is moreover subject to certain variability. This thesis aims at providing new tools to facilitate the delineation of organs at risk. For this purpose, an automatic method of organ segmentation is proposed. By automating the most repetitive part of organ drawing, the radiation oncologist can concentrate on the more essential steps of treatment planning. We propose a method that relies on machine learning where the parameters of the method are learnt from already delineated images. The images are first over-segmented in order to determine homogeneous areas and to avoid processing each pixel independently. To determine the organ each area belongs to, we propose to work in an incremental way. The organs are identified one after the other thanks to classification techniques. Organs, which are already identified, contribute to identifying the next ones. We show that this incremental method is effective and allows improving the organ classification accuracy. However a adequate sequence of identification is necessary in order to get optimal results. Two techniques are presented in this work to determine such a sequence of organ classification. These techniques lead to high performances of identification. We also show that a human operator can easily and quickly correct errors made by the incremental approach. Finally, our method being generic, it can be adapted to all regions of the human body.
On Improving the BLER for ML Receivers in Block Faded Channels through Random Phase Rotation

In this work, we apply the idea of random phase rotation of the modulated symbols to a system with interfering transmitters and a Maximum-likelihood (ML) receiver. Expressions for Bit Error Rate (BER) for a given channel realization and the average Block Error Rate (BLER) for an error correcting code are derived for the Hard-Decision based ML receiver (HDML). The derived expressions are verified through simulation results and it is observed that at high signal to noise ratio (SNR), when the channel is quasi-static (block fading), random phase rotation provides a gain in BLER when compared to the case without random phase rotation. Also it is observed that the BLER for a system with random phase rotation approaches the BLER for the case of no co-channel interference. The gain due to random phase rotation is also verified for an LTE framework with Soft-Decision based ML receiver (SD-ML).
PRP‐17 and the pre‐mRNA splicing pathway are preferentially required for the proliferation versus meiotic development decision and germline sex determination in Caenorhabditis elegans

In C. elegans, the decision between germline stem cell proliferation and entry into meiosis is controlled by GLP‐1 Notch signaling, which promotes proliferation through repression of the redundant GLD‐1 and GLD‐2 pathways that direct meiotic entry. We identify prp‐17 as another gene functioning downstream of GLP‐1 signaling that promotes meiotic entry, largely by acting on the GLD‐1 pathway, and that also functions in female germline sex determination. PRP‐17 is orthologous to the yeast and human pre‐mRNA splicing factor PRP17/CDC40 and can rescue the temperature‐sensitive lethality of yeast PRP17. This link to splicing led to an RNAi screen of predicted C. elegans splicing factors in sensitized genetic backgrounds. We found that many genes throughout the splicing cascade function in the proliferation/meiotic entry decision and germline sex determination indicating that splicing per se, rather than a novel function of a subset of splicing factors, is necessary for these processes. Developmental Dynamics 239:1555–1572, 2010. © 2010 Wiley‐Liss, Inc.
Obesity and High Blood Pressure: A Clinical Phenotype for the Insulin Resistance Syndrome in African Americans

The high prevalence of insulin resistance syndrome in African Americans predisposes this population to higher morbidity and mortality from cardiovascular disease. To test the hypothesis that the combination of obesity and high blood pressure (BP) represents the physical phenotype of insulin resistance syndrome, 337 African‐American men and women aged 32±4 years were examined and classified into four groups (nonobese‐normal BP, nonobese‐high BP, obese‐normal BP, obese‐high BP), according to presence or absence of obesity and high BP. Mean values of glucose, insulin, lipids, urinary albumin excretion, and clamp‐derived insulin sensitivity were determined for each group. Prevalence of prediabetes (24.4%), diabetes (19.2%), and insulin resistance syndrome (87.2%) were highest in the obese‐high BP group (p<0.001). Mean triglycerides, urinary albumin excretion, fasting glucose, fasting insulin, and insulin resistance were highest in the obese‐high BP group (p<0.001). Subjects with both obesity and high BP showed greater expression of lipid and glucose abnormalities, higher urinary albumin excretion, and greater prevalence of prediabetes, undetected type 2 diabetes, and insulin resistance syndrome.
Factors associated with differences in quit rates between "specialist" and "community" stop-smoking practitioners in the english stop-smoking services.

INTRODUCTION Behavioral support improves smokers' chances of quitting, but quit rates are typically lower for smokers supported by "community practitioners" for whom smoking cessation is a small part of their job than for those supported by "specialist practitioners" for whom it is the main role. This article examined the factors that might contribute to this. METHOD A total of 573 specialist practitioners and 466 community practitioners completed a 42-item online survey that covered demographic and employment information, current practices, levels of training, and 4-week CO-verified quit rates. Responses were compared for community and specialist practitioners. Mediation analysis was undertaken to assess how far "structural" and "modifiable" variables account for the difference in quit rates. RESULTS Specialist practitioners reported higher 4-week CO-verified quit rates than community practitioners (63.6% versus 50.4%, p < .001). Practitioners also differed significantly in employment variables, evidence-based practices, and levels of training. Six "modifiable" variables (proportion of clients using an "abrupt" quit model, duration of first session, always advising on medications, number of days training received, number of sessions observed when starting work, and number of sessions having been observed in practice and received feedback) mediated the association between practitioners' role and quit rates over and above the "structural" variables, explaining 14.3%-35.7% of the variance in the total effect. CONCLUSIONS "Specialist" practitioners in the English stop-smoking services report higher success rates than "community" practitioners and this is at least in part attributable to more extensive training and supervision and greater adherence to evidence-based practice including advising on medication usage and promoting abrupt rather than gradual quitting.
IL-1beta-induced nitric oxide release from insulin-secreting beta-cells: further evidence for the involvement of GTP-binding proteins.

Recently, we have demonstrated regulatory roles for G-proteins (e.g., H-Ras) in IL-1beta induced NO release from HIT-T15 cells. Herein, we report a similar regulatory mechanism for IL-1beta induced NO release from RIN5F and INS-1 cells. Our data indicate that functional inactivation of Ras, either by Clostridial toxins or by specific inhibitors of Ras function, results in a significant inhibition in IL-1beta induced NO release, suggesting that activation of specific G-proteins is essential for IL-1beta induced NO release. In the present study, we report possible loci where IL-1beta treatment might result in functional activation of these G-proteins. For example, IL-1beta treatment resulted in significant reduction in (high-and low-affinity) GTPase activities in lysates derived from normal rat islets; such a scenario might lead to retention of candidate G-proteins in GTP-bound, active conformation. Further, IL-1beta treatment increased the G-protein carboxyl methyl transferase activity as well as carboxyl methylation of endogenous beta-cell proteins; such a modification has been shown to increase the membrane association and interaction of these G-proteins with their respective effector proteins. Also, we report immunologic localization of H-Ras regulatory proteins including its nucleotide exchange factor (GRF-1) and its effector protein (eg., Raf-1) in isolated beta-cells. Together, our data indicate localization, and regulation by IL-1beta, of specific enzymes that are critical to activation of G-proteins. Based on these preliminary findings, we propose a model for the involvement of G-proteins in IL-1beta induced NO release and subsequent demise of the pancreatic beta-cell.