Miracle-dz/UniFAR-FTUs huggingface dataset:
Thrombin is a Na(+)-activated enzyme.

The amidase activity of human alpha-thrombin has been studied at steady state as a function of the concentration of several chloride salts, at a constant ionic strength I = 0.2 M. All kinetic steps of the catalytic mechanism of the enzyme have been solved by studies conducted as a function of relative viscosity of the solution. Among all monovalent cations, Na+ is the most effective in activating thrombin catalysis. This effect is observed with different amide substrates and also with gamma-thrombin, a proteolytic derivative of the native enzyme which has little clotting activity but retains amidase activity toward small synthetic substrates. The specific effects observed as a function of Na+ concentration are indicative of a binding interaction of this monovalent cation with the enzyme. The basis of this interaction has been explored by measurements of substrate hydrolysis collected in a three-dimensional matrix of substrate concentration, relative viscosity, and Na+ concentration, keeping the ionic strength constant with an inert cation such as choline or tetraethylammonium. The data have globally been analyzed in terms of a kinetic linkage scheme where Na+ plays the role of an allosteric effector. The properties of the enzyme change drastically upon binding of Na+, with substrate binding and dissociation, as well as deacylation, occurring on a time scale which is 1 order of magnitude faster. The apparent association constants for Na+ binding to the various intermediate forms of the enzyme have all been resolved from analysis of experimental data and are in the range of 50-100 M-1 at 25 degrees C. Studies conducted at different temperatures, in the range 15-35 degrees C, have revealed the enthalpic and entropic components of Na+ binding to the enzyme. The results obtained from steady-state measurements are supported by independent measurements of the intrinsic fluorescence of the enzyme as a function of Na+ concentration at a constant ionic strength I = 0.2 M, over the temperature range 15-35 degrees C. These measurements are indicative of a drastic conformational change of the enzyme upon Na+ binding to a single site. The energetics of Na+ binding derived from analysis of fluorescence measurements agree very well with those derived independently from steady-state determinations. It is proposed that thrombin exists in two conformations, slow and fast, and that the slow-->fast transition is triggered by binding of a monovalent cation. The high specificity in thrombin activation found in the case of Na+ is the result of its higher affinity compared to all other monovalent cations. (ABSTRACT TRUNCATED AT 400 WORDS)
Printed Chinese Character Recognition Based on Pixel Distribution Probability of Character Image

This paper analyzed the disadvantage of the character recognition method of Casey and Nagy. It adopted advantage of two methods and proposed a new method of character recognition. In this method, the pixel distribution probability of character image is the basal index. The minimal distance product and the maximal fuzzy correlation measure are the evaluation index. It not only overcame the shortcoming of above two methods but also improved the rate of character recognition. With the recognition experiment of 3500 printed Chinese characters, the result showed that this method is accurate and effective since the recognition rate of single character exceeded 99.97%.
A Viable Approach to the Optimization of Energy Systems

A progressive step-by-step approach is suggested to optimize energy conversion plants and systems when many conflicting aspects must be considered and a mathematical description of the problem is very hard and/or can only be performed by means of complex and time-consuming calculations. The procedure can easily be adapted to meet different objectives pursued by analysts, designers, operators, and policy makers. Some examples of the application of this approach to different systems, according to different objectives, are presented in this paper.
Implementing the Viola-Jones Face Detection Algorithm

The emergence of high resolution digital cameras for recording of still images and video streams has had a significant impact on how communication and entertainment have developed during the recent years. At the same time Moore’s law has made tremendous computing power readily available that only some 20 years ago was reserved for high profile research establishments and intelligence services. These two tendencies have respectively called for and fostered the advent of unprecedented computationally heavy image processing algorithms. Algorithms that in turn have allowed for new processing of existing image based material. Parallel to this technological development the measures deployed in the protection against attacks from the enemies of modernity calls for more surveillance of the public space. As a result of this regrettable circumstance more video cameras are installed in airports, on stations and even on open streets in major cities. Whether or not the purpose is entertainment or dead serious surveillance, tasks like detection and recognition of faces are solved using the same methods. Due to the varying and generally adverse conditions under which images are recorded there is a call for algorithms capable of working in an unconstrained environment. In 2004 an article by Paul Viola and Michael J. Jones titled “Robust Real-Time Face Detection” was publish in the International Journal of Computer Vision. The algorithm presented in this article has been so successful that today it is very close to being the de facto standard for solving face detection tasks. This success is mainly attributed to the relative simplicity, the fast execution and the remarkable performance of the algorithm. This report documents all relevant aspects of the implementation of the Viola-Jones face detection algorithm. The intended input for the face detection algorithm is any conceivable image containing faces and the output is a list of face positions.
Latent Semantic Matching: Application to Cross-language Text Categorization without Alignment Information

Unsupervised object matching (UOM) is a promising approach to cross-language natural language processing such as bilingual lexicon acquisition, parallel corpus construction, and cross-language text categorization, because it does not require labor-intensive linguistic resources. However, UOM only finds one-to-one correspondences from data sets with the same number of instances in source and target domains, and this prevents us from applying UOM to real-world cross-language natural language processing tasks. To alleviate these limitations, we proposes latent semantic matching, which embeds objects in both source and target language domains into a shared latent topic space. We demonstrate the effectiveness of our method on cross-language text categorization. The results show that our method outperforms conventional unsupervised object matching methods.
Trade and Investment Relationship in SAARC Countries: A Gravity Model Analysis

The recent surge in the volume of world trade and FDI has attracted a debate amongst the researchers and policy makers on the issue of the relationship between these two. I.e. whether FDI enhances trade or contracts trade? Our current study tries to find out the answer of this question in case of SAARC group of countries. This study applies gravity model for the analysis. The study covered the time period from 2000 to 2012. The study finds both complementary and supplementary relationship exists between these two variables in the SAARC region.
Arrhythmia Classification with Support Vector Machines and Genetic Algorithm 2009

This research is on presenting a new approach for cardiac arrhythmia disease classification. The proposed method combines both Support Vector Machine (SVM) and Genetic Algorithm approaches. First, twenty two features from electrocardiogram signal are extracted. These features are obtained semiautomatically from time-voltage of R, S, T, P, Q features of an Electro Cardiagram signals. Genetic algorithm is used to improve the generalization performance of the SVM classifier. In order to do this, the design of the SVM classifier is optimized by searching for the best value of the parameters that tune its discriminate function, and looking for the best subset of features that optimizes the classification fitness function. Experimental results demonstrate that the approach adopted better classifies ECG signals. Four types of arrhythmias were distinguished with 93% accuracy.
Experimental realization of epsilon-near-zero metamaterial slabs with metal-dielectric multilayers

Epsilon-near-zero (ENZ) metamaterial slabs at visible frequencies based on metal-dielectric multilayers are experimentally realized. Transmission, reflection, and absorption spectra are measured and used to determine the complex refractive indices and the effective permittivities of the ENZ slabs, which agree with the results obtained from both the numerical simulations and the optical nonlocalities analysis. Furthermore, light propagation in ENZ slabs and directional emission from ENZ prisms are also analyzed. The accurate determination of the ENZ wavelength for metal-dielectric multilayer metamaterial slabs is important for realizing many unique applications, such as phase front manipulation and enhancement of photonic density of states.
Real-time anomalies detection and analysis of network structure, with application to the Autonomous System network

The structural analysis is the very basic tool for understanding the properties of a network. In this paper we present a (customizable) tool, able to compute in real-time the most important connectivity properties of a network, modeled as an undirected graph: connected and biconnected components, articulation points and bridges. The algorithm underlying the tool has been theoretically analyzed in the (semi-)streaming model, and has been tested with graphs up to hundreds of millions nodes and billions edges. The tool, therefore, can be employed to monitor traffic flows in medium and large networks, at real-time, and detect possible anomalies. As an application, we provide results about the structural properties of ten years of samples of the Autonomous System network, obtained from the Univ. of Oregon Route Views project [1], that (once again) shows the ubiquitous presence of power-law distribution.
Polyion Complex Vesicles with Solvated Phosphobetaine Shells Formed from Oppositely Charged Diblock Copolymers

Diblock copolymers consisting of a hydrophilic poly(2-(methacryloyloxy)ethyl phosphorylcholine) (PMPC) block and either a cationic or anionic block were prepared from (3-(methacrylamido)propyl)trimethylammonium chloride (MAPTAC) or sodium 2-(acrylamido)-2-methylpropanesulfonate (AMPS). Polymers were synthesized via reversible addition-fragmentation chain transfer (RAFT) radical polymerization using a PMPC macro-chain transfer agent. The degree of polymerization for PMPC, cationic PMAPTAC, and anionic PAMPS blocks was 20, 190, and 196, respectively. Combining two solutions of oppositely charged diblock copolymers, PMPC-b-PMAPTAC and PMPC-b-PAMPS, led to the spontaneous formation of polyion complex vesicles (PICsomes). The PICsomes were characterized using 1H NMR, static abd dynamic light scattering, transmittance electron microscopy (TEM), and atomic force microscopy. Maximum hydrodynamic radius (Rh) for the PICsome was observed at a neutral charge balance of the cationic and anionic diblock copolymers. The Rh value and aggregation number (Nagg) of PICsomes in 0.1 M NaCl was 78.0 nm and 7770, respectively. A spherical hollow vesicle structure was observed in TEM images. The hydrodynamic size of the PICsomes increased with concentration of the diblock copolymer solutions before mixing. Thus, the size of the PICsomes can be controlled by selecting an appropriate preparation method.
An Experiment on Tabled Evaluation for Hidden Predicates ?

Most Answer Set Programming grounders allow filtering the information shown in each answer set by selecting which predicates must be shown or become hidden instead. Full grounding of hidden predicates (usually introduced for auxiliary computations) is in many cases not necessary. In the paper, we consider the possibility of avoiding grounding of hidden (stratified) predicates by using tabled evaluation: a top-down strategy combined with an extension table that records the previously solved goals.
Auditioning the distinctiveness account: Expanding the production effect to the auditory modality reveals the superiority of writing over vocalising

The production effect (PE) documents the advantage in memory performance for words that are read aloud during study, rather than words that are read silently. Until now, the PE was examined in the visual modality, as the participants read the study words. In the present study, we extended the PE phenomenon and used the auditory modality at study. This novel methodology provides a critical test of the distinctiveness account. Accordingly, the participants heard the study words and learned them by vocal production (saying aloud) or by writing, followed by a free recall test. The use of the auditory modality yielded a memory advantage for words that were written during study over words that were vocally produced. We explain this result in light of the encoding distinctiveness account, suggesting that the PE is determined by the number of different encoding processes involved in learning, emphasising the essential role of active production.
Third Workshop on Programmability Issues for Multi-Core Computers (MULTIPROG-3)

In this paper we present a complete Java STM framework, called Deuce, intended as a platform for developing scalable concurrent applications and as a research tool for designing new STM algorithms. It was not clear if one could build an e cient Java STM without compiler support. Deuce provides several bene ts over existing Java STM frameworks: it avoids any changes or additions to the JVM, it does not require language extensions or intrusive APIs, and it does not impose any memory footprint or GC overhead. To support legacy libraries, Deuce dynamically instruments classes at load time and uses an original eld-based locking strategy to improve concurrency. Deuce also provides a simple internal API allowing di erent STMs algorithms to be plugged in. We show empirical results that highlight the scalability of our framework running benchmarks with hundreds of concurrent threads. This paper shows for the rst time that one can actually design a Java STM with reasonable performance without compiler support.
Building an Enterprise Ontology of Business Process Crowdsourcing: A Design Science Approach

Crowdsourcing is an emerging strategy for enterprises to harvest information, labour, expertise and innovation from a wide, anonymous crowd. To fully adopt this strategy, enterprise systems should not only extend existing frameworks with new services and users, but also efficiently integrate crowdsourced activities with, usually more stable, organisational processes. However, an ontological structure for this integration is still missing. Although a few lightweight ontologies have been proposed in the crowdsourcing domain, they seem to focus on clarifying concepts rather than providing a structure for modelling, designing, and developing an enterprise system. The current study fills the gap by building an enterprise ontology of business process crowdsourcing. Our results identified the main business processes, data entities, data attributes, and their hierarchy relationships, which were structured into a lightweight ontology. We then added decision-making relationships and business rules that turn a lightweight into a heavyweight ontology. The built ontology is evaluated by triangulation when comparing with two ontology versions generated by automated tools. The current study is significant as it is the first effort to build an enterprise ontology of crowdsourcing, which provides a blueprint for integrating business process crowdsourcing into enterprise systems.
A low power high speed Class-B buffer amplifier for flat panel display application

A low power, high speed, but with a large input dynamic range and output swing class-B output buffer circuit which is suitable for the flat-panel display application is proposed. The buffer draws little current during static but has a large driving capability during transients. It has been demonstrated with the TSMC 0.6 /spl mu/m CMOS technology.
Localising and Sustaining Poverty Reduction: Experiences from Ghana’ Management of Environmental Quality

Purpose – The aim of this paper is to examine poverty and poverty reduction at the local level using the Hohoe Municipality and Sefwi‐Wiaso District, both in Ghana, as a case.Design/methodology/approach – The paper adopts a survey method, collecting data from 180 farmers on the various aspects of the topic to form the basis of the study. Questionnaires and focus group discussions were used as the data collection instruments.Findings – The study found that, although many poverty reduction initiatives have been undertaken in Ghana, their impact on the poor farming communities has been very minimal. The failure of these poverty reduction policies could be attributed to the non‐involvement of local people in the process of policy formation. It also revealed that the number of poor people and the degree of poverty might be higher than the details captured by official statistics and publications.Research limitations/implications – The paper is biased towards farmers. It did not consider other sectors of the Gha.
Self-learning fuzzy sliding-mode control for antilock braking systems

The antilock braking system (ABS) is designed to optimize braking effectiveness and maintain steerability; however, the ABS performance will be degraded in the case of severe road conditions. In this study, a self-learning fuzzy sliding-mode control (SLFSMC) design method is proposed for ABS. The SLFSMC ABS will modulate the brake torque for optimum braking. The SLFSMC system is comprised of a fuzzy controller and a robust controller. The fuzzy controller is designed to mimic an ideal controller and the robust controller is designed to compensate for the approximation error between the ideal controller and the fuzzy controller. The tuning algorithms of the controller are derived in the Lyapunov sense; thus, the stability of the system can be guaranteed. Also, the derivation of the proposed SLFSMC ABS does not need to use a vehicle-braking model. Simulations are performed to demonstrate the effectiveness of the proposed SLFSMC ABS in adapting to changes for various road conditions.
Evolutionary design of digital circuits using improved multi expression programming (IMEP)

Evolutionary Electronics is a research area which involves application of Evolutionary computation in the domain of electronics. It is seen as a quite promising alternative to overcome some drawbacks of conventional design. In this paper we propose a methodology based on an Improved Multi Expression Programming (IMEP) to automate the design of combinational logic circuits in which we aim to reach the functionality and to minimize the total number of used gates. MEP is a genetic Programming variant that uses linear chromosomes for solution encoding. A unique MEP feature is its ability of encoding multiples solutions of a problem in a single chromosome. These solutions are handled in the same time complexity as other techniques that encode a single solution in a chromosome. This paper presents the main idea of an improved version of the MEP method, and shows positive preliminary experimental results.
Extracting Document Semantics for Semantic Header

Accurate indexing and cataloguing of electronic information on the Internet is the foundation for precise retrieval. Most existing search systems, however, tend to generate misses and false hits due to the fact that they attempt to match the specified search terms in the target information resources without considering context. It is clear that using traditional keyword-based methods for representing semantics of information items has become a major obstacle to high precision. The notion of semantic header proposed previously captures the semantics of information resources that takes into account the logical structure of an information item. The contents of semantic header may be used by modern search systems to help locate an appropriate information item with minimum effort. In this paper, we present a system, called automatic semantic header generator (ASHG), for generating five key components of the semantic header. Finally, we evaluate the system with two sets of documents, and analyze the corresponding results
Using Hierarchical Recurrent Neuro-Fuzzy Systems for Decision Making

Over the last years, a number of methods have been proposed to automatically learn and optimize fuzzy rule bases from data. The obtained rule bases are usually robust and allow an interpretation even for data sets that contains imprecise or uncertain information. However, most of the proposed methods are still restricted to learn and/or optimize single layer feed-forward rule bases. The main disadvantages of this architecture are that the complexity of the rule base increases exponentially with the number of input and output variables and that the system is not able to store and reuse information of the past. Thus temporal dependencies have to be encoded in every data pattern. In this article we briefly discuss the advantages and disadvantages of hierarchical recurrent fuzzy systems that tackle these problems. Furthermore, we present a neuro-fuzzy model that has been designed to learn and optimize hierarchical recurrent fuzzy rule bases from data.
Long-term optical stimulation of channelrhodopsin-expressing neurons to study network plasticity

Neuronal plasticity produces changes in excitability, synaptic transmission, and network architecture in response to external stimuli. Network adaptation to environmental conditions takes place in time scales ranging from few seconds to days, and modulates the entire network dynamics. To study the network response to defined long-term experimental protocols, we setup a system that combines optical and electrophysiological tools embedded in a cell incubator. Primary hippocampal neurons transduced with lentiviruses expressing channelrhodopsin-2/H134R were subjected to various photostimulation protocols in a time window in the order of days. To monitor the effects of light-induced gating of network activity, stimulated transduced neurons were simultaneously recorded using multi-electrode arrays (MEAs). The developed experimental model allows discerning short-term, long-lasting, and adaptive plasticity responses of the same neuronal network to distinct stimulation frequencies applied over different temporal windows.
Overexpression of wildtype EGFR is tumorigenic and denotes a therapeutic target in non-small cell lung cancer

Current guidelines for lung cancer treatment with EGFR tyrosine kinase inhibitors (TKI) include only patients with mutated EGFR, although some patients with wildtype EGFR (wt-EGFR) have exhibited positive responses to this therapy as well. Biomarkers predicting the benefit from EGFR-TKIs treatment remain to be determined for patients with wild-type EGFR. Here, we report that wt-EGFR overexpression transformed cells in vitro and induced tumorigenesis in vivo in transgenic mouse models. Wt-EGFR driven lung cancer was hypersensitive to TKI treatment in mouse model. Lung cancer patients with high-expression of wt-EGFR showed longer Overall Survival in comparison to low-expression patients after TKI treatment. Our data therefore suggest that treatment with EGFR inhibitors should be extended to include not only patients with mutated EGFR but also a subset of patients with overexpression of wt-EGFR.