Miracle-dz/UniFAR-FTUs huggingface dataset:
Biotechnologically Relevant Enzymes and Proteins

β-Glucosidase from the hyperthermophilic archaeon Thermococcus sp. is a salt-tolerant enzyme that is stabilized by its reaction product glucose Abstract β-Glucosidase (BG) is widely applied in the biofuel's industry, as part of a cellulase cocktail to catalyze the hydrolysis of the β-1,4 linkages that join two glucose molecules in a cellulose polymer. The hydrolysis step is generally recognized as the major limiting step in the development of efficient enzyme-based technologies for the conversion of lignocellulosic biomass to sugars and the production of biofuels due to the accumulation of the reaction product, glucose. Relieving this glucose inhibition of BG is therefore a major challenge. In this study, O08324, a putative BG gene encoded in the hyperthermophilic archaeon Thermococcus sp. , was cloned and overexpressed in Escherichia coli. O08324 showed maximum activity between pH 5–6.8 and at 78 °C and was thermostable with a half-life of 860 min at 78 °C in the presence of 1.5 M glucose. O08324 was not inhibited by glucose up to the highest assayable concentration of 4 M and also shows no decrease in activity in the presence of up to 4 M of sodium chloride or potassium chloride. O08324 supplementation of Trichoderma viride cellulase enhanced glucose production by more than 50 % compared to a commercially available BG, when Avicel (10 %, w/v) was used as a substrate at 37 °C. Multiple sequence alignments across previously reported glucose-tolerant BGs shows that many conserved residues previously implicated in glucose tolerance are not conserved in this BG suggesting a need for a relook at understanding the molecular basis of glucose tolerance.
Myocardial Systolic Function Increases During Positive Pressure Lung Inflation

Lung inflation with positive airway pressure may have rapid and dynamic effects on myocardial contractile function. We designed this study to assess the magnitude and time to onset of myocardial function changes during the initiation of single positive pressure lung inflation at clinically relevant inflation pressures. In 8 anesthetized 40-kg pigs, left ventricular pressures and volumes were measured directly (conductance volumetry). A 15 cm H2O airway pressure plateau with lung inflation (PPLI-15) was performed, and 2 single beats from that sequence, one from resting apnea at zero airway pressure and the second from the point when the lungs were first maximally inflated, were selected for analysis. Systolic function variables for zero airway pressure and PPLI-15 were analyzed. Systolic elastance, derived from bilinear time-varying elastance curves, increased approximately 15% during PPLI-15 from zero airway pressure. This agreed with other systolic function variables that identified an increase in left ventricular contractile function for the lung inflation beat. Serial measurements of myocardial function should be conducted with constant airway pressure and lung inflation conditions.
Implicit Brain-Computer Interaction Applied to a Novel Adaptive Musical Interface

We present a novel brain-computer interface (BCI) integrated with a musical instrument that adapts passively to users’ changing cognitive state during musical improvisation. Traditionally, musical BCIs have been divided into camps: those that use some mapping of brainwaves to create audio signals; and those that use explicit brain signals to control some aspect of the music. Neither of these systems take advantage of higher level semantically meaningful brain data or implicit brain data which could be used in adaptive systems. We present a new type of real-time BCI that assists users in musical improvisation by adapting to users’ measured cognitive workload. Our system advances the state of the art in this area in three ways: 1) We demonstrate that cognitive workload can be classified in real-time while users play the piano using functional near-infrared spectroscopy. 2) We build a real-time system using this brain signal that musically adapts to what users are playing. 3) We demonstrate that users prefer this novel musical instrument over other conditions and report that they feel more creative.
FRODOCK: a new approach for fast rotational protein-protein docking

MOTIVATION Prediction of protein-protein complexes from the coordinates of their unbound components usually starts by generating many potential predictions from a rigid-body 6D search followed by a second stage that aims to refine such predictions. Here, we present and evaluate a new method to effectively address the complexity and sampling requirements of the initial exhaustive search. In this approach we combine the projection of the interaction terms into 3D grid-based potentials with the efficiency of spherical harmonics approximations to accelerate the search. The binding energy upon complex formation is approximated as a correlation function composed of van der Waals, electrostatics and desolvation potential terms. The interaction-energy minima are identified by a novel, fast and exhaustive rotational docking search combined with a simple translational scanning. Results obtained on standard protein-protein benchmarks demonstrate its general applicability and robustness. The accuracy is comparable to that of existing state-of-the-art initial exhaustive rigid-body docking tools, but achieving superior efficiency. Moreover, a parallel version of the method performs the docking search in just a few minutes, opening new application opportunities in the current 'omics' world. AVAILABILITY http://sbg.cib. csic.es/Software/FRODOCK/
Posttranslational processing of the prohormone-cleaving Kex2 protease in the Saccharomyces cerevisiae secretory pathway

The Kex2 protease of the yeast Saccharomyces cerevisiae is a prototypical eukaryotic prohormone-processing enzyme that cleaves precursors of secreted peptides at pairs of basic residues. Here we have established the pathway of posttranslational modification of Kex2 protein using immunoprecipitation of the biosynthetically pulse-labeled protein from a variety of wild-type and mutant yeast strains as the principal methodology. Kex2 protein is initially synthesized as a prepro-enzyme that undergoes cotranslational signal peptide cleavage and addition of Asn-linked core oligosaccharide and Ser/Thr-linked mannose in the ER. The earliest detectable species, I1 (approximately 129 kD), undergoes rapid amino-terminal proteolytic removal of a approximately 9-kD pro-segment yielding species I2 (approximately 120 kD) before arrival at the Golgi complex. Transport to the Golgi complex is marked by extensive elaboration of Ser/Thr-linked chains and minor modification of Asn-linked oligosaccharide. During the latter phase of its lifetime, Kex2 protein undergoes a gradual increase in apparent molecular weight. This final modification serves as a marker for association of Kex2 protease with a late compartment of the yeast Golgi complex in which it is concentrated about 27-fold relative to other secretory proteins.
Clive W.J. Granger - Nobel Lecture

The two prize winners in Economics this year would describe themselves as “Econometricians,” so I thought that I should start by explaining that term. One can begin with the ancient subject of Mathematics which is largely concerned with the discovery of relationships between deterministic variables using a rigorous argument. (A deterministic variable is one whose value is known with certainty.) However, by the middle of the last millennium it became clear that some objects were not deterministic, they had to be described with the use of probabilities, so that Mathematics grew a substantial sub-field known as “Statistics. ” This later became involved with the analysis of data and a number of methods have been developed for data having what may be called “standard properties. ” However, in some areas of application, the data that they generated were found to be not standard, and so special sub-sub-fields needed to be developed. For example, Biology produced Biometrics, Psychology gave us Psychometrics, and Economics produced Econometrics. There are many types of economic data, but the type considered by Rob Engle and myself is know as time series. Consider the measurement of unemployment rates which is an important measure of the health of the economy. Figures are gathered by a government agency and each month a new number is announced. Next month there will be another value, and so forth. String these value together in a simple graph and you get a “time series. ” Rather than show a diagram, I would rather you use internal visualization (I think that you learn more that way). Suppose that you have a loosely strung string of pearls which you throw down, gently, onto a hard table top with the string of pearls roughly stretched out. You will have created a time series with time represented by the distance down the table, the size of the variable as the distance from the bottom edge of the table to a point, and the set of pearls giving the points in the series. As the placement of one pearl will impact where the next one lies, because they are linked together, this series will appear to be rather smooth, and will not have big fluctuations in value for one term to the next. Time series can vary in many ways, some are gathered very often, others less frequently. Values for many important financial variables are known not
AN EXEMPLAR-BASED NMF APPROACH FOR AUDIO EVENT DETECTION

We present a novel, exemplar-based method for audio event detection based on non-negative matrix factorisation (NMF). Building on recent work in noise robust automatic speech recognition, we model events as a linear combination of dictionary atoms, and mixtures as a linear combination of overlapping events. The exemplar-based dictionary is created by extracting all available training data, artiﬁcially augmented by linear time warping at multiple rates. The method is evaluated on the Ofﬁce Live and Ofﬁce Synthetic development datasets released by the AASP Challenge on Detection and Classiﬁcation of Acoustic Scenes and Events.
On Gauged Maximal Supergravity In Six Dimensions

The maximal SO(5) gauged D=7 supergravity is dimensionally reduced to six dimensions yielding a new SO(5) gauged D=6 model. It is shown that, unlike in D=7, the SO(5) gauge coupling constant can be taken to zero to yield the maximally extended supergravity in six dimensions. It is also shown that the limit of D=5 N=4 SU(2)xU(1) gauged supergravity in which the U(1) coupling constant is turned off can be obtained.
The effect of dust on Tremaine–Weinberg measurements

We investigate the effect of dust on the observed rotation rate of a stellar bar. The only direct way to measure this quantity relies on the Tremaine & Weinberg (TW) method which requires that the tracer satisfies the continuity equation. Thus, it has been applied largely to early-type barred galaxies. We show using numerical simulations of barred galaxies that dust attenuation factors typically found in these systems change the observed bar pattern speed by 20‐ 40 per cent. We also address the effect of star formation on the TW method and find that it does not change the results significantly. The results presented here suggest that applications of the TW method can be extended to include barred galaxies covering the full range of Hubble type.
Object oriented assessment of damage due to natural disaster using very high resolution images

A building damage assessment method applied to the case of the earthquake of Bam is proposed in this paper. It uses two very high resolution images and focuses on the footprints of the buildings. The need of an accurate registration of the buildings is demonstrated; a registration method that improved the damage assessment is proposed. It allows a classification performance of the buildings among four damage grades up to 78%. The impact of a lower accuracy of the buildings roofs segmentation is evaluated; we show that it mainly leads to a decrease of the capacity to identify the partial damage on buildings.
Supporting information retrieval on mobile devices

We present a search interface that has been designed for the use on mobile devices in order to provide improved navigation and visualization of result sets. Besides automatic context switching, the interfaces provide methods to store prior search results in a structured way and to annotate documents with respect to user interests and the query. These methods enable a user to retrieve documents with fewer interactions and less data traffic, which is especially important for mobile devices.
On the Feng-Rao Bound for the L-construction of Algebraic Geometry Codes

which is called the L-construction, was not explicitly mentioned by Goppa but known to researchers including Goppa and Manin [17, p.386]. CL(D,mQ) seems to be first explicitly defined in [8], [15]. Most research articles treat only CΩ(D,mQ). A reason for this trend may be due to the lack of efficient decoding algorithms for CL(D,mQ), while we know efficient decoding algorithms for CΩ(D,mQ) proposed by Feng and Rao [1] and Sakata et al. [12]. In this paper we show how to apply the Feng-Rao algorithm to CL(D,mQ). The reader may wonder if there is any advantage considering CL(D,mQ) over CΩ(D,mQ). We shall give examples in which the error-correcting capability of CL(D,mQ) is larger than CΩ(D,mQ) while their dimensions are the same, where F,D,Q are common to CL(D,mQ) and CΩ(D,mQ). Thus it is worth considering CL(D,mQ) as well for fixed F,D,Q.
Adaptive Image Compression Using Neural Networks

In this article applying neural networks in order to compress images adaptively based on their entropies has been studied. A three-layer perceptron network is used basically, to compress the blocks of Images. In order to improve such a network, we have used various networks with different compression ratios, for the image with different complexities and details. In order to measure the complexity of an image, entropy was used to estimate the amount of Information being present. The results of compression with such a network indicate that the compressed image has a very good visual quality and somehow they have improvement over commercial JPEG format in the same compression ratio.
Petri net controller synthesis for discrete event systems using weighted inhibitor arc

A Petri net (PN) with weighted inhibitor arc is exploited to solve the forbidden state problem of discrete event systems (DES). The forbidden state problem considered is described as the linear inequality constraint of the place marking. We first review the relevant work on the control of DES using inhibitor arcs. Then, the design of the PN controller is introduced with two steps. The first step of the design is to track the state of the system. Then, the weighted inhibitor arcs are exploited to disable the relative transitions in the case that the firing of these transitions will violate the constraints. A simple example of a discrete manufacturing system in the reported literature is used to show the detailed procedure of the controller synthesis and the advantages of the presented method.
Diagnostic test of screening generalized anxiety disorders in general hospital psychological department with GAD-7

Objective:Using a diagnostic test research,to explore the reliability and validity of the 7-tiem Generalized Anxiety Disorder Scale(GAD-7) on screening of generalized anxiety disorder(GAD) in general hospital,and to determine the cut points for GAD with different severities.Methods:Six hundred and forty-six help-seekers(n = 646) consulting the outpatient department of psychology in a general hospital were collected continuously.Among them,300 were normal person without any psychiatric diagnosis,346 were patients with mental disorders.All of subjects were asked to fulfill GAD-7,and were assessed by a psychiatrist with the Mini-International Neuropsychiatric Interview(M.LN.L) and Hamilton Anxiety Scale(HAMA). The M.L N.I. diagnosis was a gold standard to diagnose GAD,and HAMA was used to assess the illness severity.Result:Cronbach α coefficient of GAD-7 was 0.93. Factor analysis showed good structure validity of GAD-7.There were 107 patients who were diagnosed GAD according to M.I. N.L assessment For the all help-seekers(n = 646),the area under the receiver operator characteristic analysis(ROC) of GAD-7 was 0.86(95%CI:0.83-0.89) for GAD.With 6 as the critical value for anxiety disorder screening,the sensitivity was 0.91 and specificity was 0.71,respectively.By the result of HAMA as the standard to rank different levels of anxiety disorder,the cut points of GAD-7 for mild,moderate,and severe anxiety disorder was 4,9 and 12.Conclusion:It suggests that GAD-7 has satisfying reliability and validity,and is applicable for screening GAD and assessment of its severity of outpatients in general hospital.The recommended cut points of GAD-7 should be adjusted for outpatients in general hospital in China
Design of Multi Threshold (Multi Vth) Level Converters for Block Interfaces

In this paper, three novel level converters based on a multi threshold voltage CMOS technology are presented. Unlike the conventional level conversion techniques based on feedback, the proposed level converters eliminate the static dc current using multi-Vth devices. The new level converters are compared with two previously published feedback-based level converters for different supply voltages. The effectiveness of the proposed circuits for reducing power consumption, propagation delay, and area is evaluated at scaled supply voltages down to the subthreshold regime.
Quality Assessment Tool for Quantitative Studies Dictionary

The purpose of this dictionary is to describe items in the tool thereby assisting raters to score study quality. Due to under-reporting or lack of clarity in the primary study, raters will need to make judgements about the extent that bias may be present. When making judgements about each component, raters should form their opinion based upon information contained in the study rather than making inferences about what the authors intended.
Depletion of Plasmodium berghei Plasmoredoxin Reveals a Non-Essential Role for Life Cycle Progression of the Malaria Parasite

Proliferation of the pathogenic Plasmodium asexual blood stages in host erythrocytes requires an exquisite capacity to protect the malaria parasite against oxidative stress. This function is achieved by a complex antioxidant defence system composed of redox-active proteins and low MW antioxidants. Here, we disrupted the P. berghei plasmoredoxin gene that encodes a parasite-specific 22 kDa member of the thioredoxin superfamily. The successful generation of plasmoredoxin knockout mutants in the rodent model malaria parasite and phenotypic analysis during life cycle progression revealed a non-vital role in vivo. Our findings suggest that plasmoredoxin fulfils a specialized and dispensable role for Plasmodium and highlights the need for target validation to inform drug development strategies.
Effective shrinkage of large multi-class linear svm models for text categorization

When linear support vector machines (SVMs) are applied to multi-class text categorization in industry, the size of the linear SVM model is very large, usually greater than several gigabytes. As a result, the model cannot directly fit into the computer memory and the classification process is slow. In this paper, a novel method based on vector norm is proposed to shrink the model size significantly without sacrificing the classification accuracy. Also, we propose a cache-efficient implementation of multi-class linear SVMs in the classification phase. Our experimental results have shown that on Yahoo-Korea dataset the proposed method can shrink the model size from 5.2 gigabytes to 260 megabytes and the efficient implementation of linear SVM has obtained a speedup factor of 44.
Bayesian evidence synthesis to estimate HIV prevalence in men who have sex with men in Poland at the end of 2009

SUMMARY HIV spread in men who have sex with men (MSM) is an increasing problem in Poland. Despite the existence of a surveillance system, there is no direct evidence to allow estimation of HIV prevalence and the proportion undiagnosed in MSM. We extracted data on HIV and the MSM population in Poland, including case-based surveillance data, diagnostic testing prevalence data and behavioural data relating to self-reported prior diagnosis, stratified by age (⩽35, >35 years) and region (Mazowieckie including the capital city of Warsaw; other regions). They were integrated into one model based on a Bayesian evidence synthesis approach. The posterior distributions for HIV prevalence and the undiagnosed fraction were estimated by Markov Chain Monte Carlo methods. To improve the model fit we repeated the analysis, introducing bias parameters to account for potential lack of representativeness in data. By placing additional constraints on bias parameters we obtained precisely identified estimates. This family of models indicates a high undiagnosed fraction [68·3%, 95% credibility interval (CrI) 53·9–76·1] and overall low prevalence (2·3%, 95% CrI 1·4–4·1) of HIV in MSM. Additional data are necessary in order to produce more robust epidemiological estimates. More effort is urgently needed to ensure timely diagnosis of HIV in Poland.
User profiling for content personalisation in information retrieval

One of the key issues with the overabundance of online information sources is that of finding what is relevant. The key to success for any type of information provider must be the personalisation of content in information retrieval, and this can be achieved through the maintenance of user profiles and the matching of these profiles to content metadata. This paper is concerned with user profiling and its role in content personalisation of information retrieval, and in particular presents a profile model which incorporates user preference information and action history information (representing the user’s previous searches). The benefits and costs of such a model are examined and it is argued that the benefits (including personalisation accuracy, computational costs extensibility and flexibility) far outweigh the costs. The matching of profiles to metadata is also discussed as it fulfils an important role in the personalisation process. Although, the user profile model presented is focused on E-Learning, the general platform could be applied to other areas.
Mathematical Modelling of the Pattern of Occurrence of Words in Different Corpora of the Hindi Language∗

Abstract The incidence of different components of language in natural language texts are not arbitrarily organized but tend to obey particular laws which enable us to explain characteristic features of human language. The present paper is an attempt to analyse and model the pattern of occurrence of words in the Hindi language. Various kinds of corpora have been selected from different sources for the study, and the occurrence of words in these corpora has been observed for a variety of properties such as: frequencies, vocabulary measures, and pattern of initials of words relative to the subsequent matra.