Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolution of the Human Sex Hormone-binding Globulin Dimer Interface and Evidence for Two Steroid-binding Sites per Homodimer*

Human sex hormone-binding globulin (SHBG) transports sex steroids in the blood. It functions as a homodimer, but there is little information about the topography of its dimerization domain, and its steroid binding stoichiometry is controversial. The prevailing assumption is that each homodimeric SHBG molecule contains a single steroid-binding site at the dimer interface. However, crystallographic analysis of the amino-terminal laminin G-like domain of human SHBG has shown that the dimerization and steroid-binding sites are distinct and that both monomers within a homodimeric complex are capable of binding steroid. To validate our crystallographic model of the SHBG homodimer, we have used site-directed mutagenesis to create SHBG variants in which single amino acid substitutions (V89E and L122E) were introduced to produce steric clashes at critical positions within the proposed dimerization domain. The resulting dimerization-deficient SHBG variants contain a steroid-binding site with an affinity and specificity indistinguishable from wild-type SHBG. Moreover, when equalized in terms of their monomeric subunit content, dimerization-deficient and wild-type SHBGs have essentially identical steroid binding capacities. These data indicate that both subunits of the SHBG homodimer bind steroid and that measurements of the molar concentration of SHBG homodimer in serum samples have been overestimated by 2-fold.
Channel Capacity of IM/DD Optical Communication Systems and of ACO-OFDM

In this paper we investigate the channel capacity of intensity modulated direct detection (IM/DD) wireless optical communication systems for an AWGN channel with a limit on the average transmitted optical power. It has recently been shown that asymmetrically clipped optical orthogonal frequency division multiplexing (ACO-OFDM) is more efficient in terms of optical power than conventional optical modulation techniques such as pulse position modulation (PPM). When ACO-OFDM is used, the transmitted signal has a clipped Gaussian probability distribution. We calculate the channel capacity for systems using transmitted signals with exponential and clipped Gaussian distributions, and for an ACO-OFDM system. For practical signal to noise ratios, ACO-OFDM has a slightly lower capacity than the other distributions, due to the correlation between samples caused by the ACO-OFDM modulation process. ACO-OFDM has many practical advantages including its tolerance to multipath distortion. This paper shows that it also makes efficient use of the available power and bandwidth.
The Role of Boundary Objects in the Fuzzy Front End of IT Development

Different domains develop their own world views making collaboration between subject matter experts difficult. Despite the difficulties, IT project personnel routinely manage to establish common understanding. Documented software development methodologies say little about how that common understanding emerges or what might aid better understanding. This research sought to determine how people of diverse world views communicated their ideas and how they established that they had been understood. Of particular interest was the relevance and operation of boundary objects. The investigation quickly revealed that innovative problems required more abstract boundary objects over which different stakeholders could exchange meaningful understanding but that assuring understanding had been accomplished was invariably reflected explanation. The findings have implications for software development methodologies, pointing out a need for more awareness of a range of boundary objects when understanding must be achieved between diverse stakeholders such as business owners and IT specialists.
Frequency Domain System Identification for a Small , Low-Cost , Fixed-Wing UAV

This paper describes a practical and systematic procedure for modeling and identifying the flight dynamics of small, low-cost, fixed-wing uninhabited aerial vehicles (UAVs). The procedure is applied to the Ultra Stick 25e flight test vehicle of the University of Minnesota UAV flight control research group. The procedure hinges on a general model structure for fixed-wing UAV flight dynamics derived using first principles analysis. Wind tunnel tests and simplifying assumptions are applied to populate the model structure with an approximation of the Ultra Stick 25e flight dynamics. This baseline model is used to design informative flight experiments for the subsequent frequency domain system identification. The final identified model is validated against separately acquired time domain flight data.
IDReAM: intrusion detection and response executed with agent mobility architecture and implementation

This paper deals with a new approach to build a completely distributed and decentralized Intrusion Detection and Response System (IDRS) in computer networks. This approach is called Intrusion Detection and Response executed with Agent Mobility or IDReAM for short. Conceptually, IDReAM combines Mobile Agents (MAs) with self-organizing paradigms inspired by natural life systems. The Intrusion Detection System (IDS) borrows mechanisms from the immune system that protect the human body against external aggressions. The Intrusion Response System (IRS) borrows mechanisms from the stigmergic paradigm of a colony of ants. The two natural systems exhibit a social life by the organization of their entities (immune cells and ants) which is not possible without the functionality of mobility. Thus, in a natural way, MAs are good candidates to provide this property of mobility. After having presented IDReAM's conceptual model in a previous paper, the present paper concretely describes IDReAM's architecture and the corresponding implementation based on the conceptual model. The implementation is carried out with J-Seal2, a pure Java MA platform. This paper also provides IDReAM's assessment in term of resource consumption and intrusion detection and intrusion response efficiency.
Sliding mode control for uncertain T-S fuzzy systems with input saturation and known external disturbance

The problem of sliding mode control for uncertain time-delay systems with input saturation and known external disturbance is considered. Combining T-S fuzzy model and sliding mode control method, we first establish the T-S model for the system, then an integral switching function is chosen, and a special sliding mode controller is designed such that the state trajectories can be driven onto the specified sliding surface in a finite period of time. Using linear matrix inequality and Lyapunov stability theory, we give a sufficient condition to guarantee the asymptotic stability of the sliding motion. An example is provided to illustrate the effectiveness of the proposed method.
Evaluation of the Psychometric Properties of SOGS-RA in the Polish Version

Objective: The objective was to adapt the American pathological gambling screening tool /SOGS-RA The South Oaks Gambling Screen - Revised for Adolescent/ by K. Winters, R. Stinchfield and J. Fulkerson (1993) and to evaluate its psychometric properties. Method: The adapted tool was used in research on a randomly selected sample of 2,617 adolescents aged 13-20 years in the 2012/2013 school year. Results: On the SOGS-RA scale, 2.6% of the trial participants achieved a score indicating past year problem gambling before the survey, 4.1% were classified as problem gamblers, whereas 17.3% of adolescents engaged in social gambling that did not pose a problem gambling risk at the time. The SOGS-RA demonstrated satisfactory internal consistency (Cronbach's alpha = 0.78). Conclusions: The Polish adaptation of the SOGS-RA scale is reliable and accurate, which is why it is worth recommending it for use in further research on Polish adolescents.
Clustering web pages with expanded tags

Social annotations e.g. tags are good descriptors of web page semantics, which have large potential for web document clustering. However, most web pages have few tags. The sparsity seriously affects the clustering performance. To overcome the problem, we incorporate user-related tag context, a specially constructed tag set, to improve the topic representation and estimation for documents. Experimental results demonstrate the nice effect of tag context on addressing the sparsity problem. Compared to clustering based on non-expanded tags, our approach achieves a statistically significant increase of 26.5% to 47.4% on F1 score.
On Accelerated Gradient Approximation for Least Square Regression with L1-Regularization

In this paper, we consider an online least square regression problem where the objective function is composed of a quadratic loss function and an L1 regularization on model parameter. For each training sample, we propose to approximate the L1 regularization by a convex function. This results in an overall convex approximation to the original objective function. We apply an efficient accelerated stochastic approximation algorithm to solve the approximation. The developed algorithm does not need to store previous samples which reduces the space complexity. We further prove that the developed algorithm is guaranteed to converge to the global optimum with a convergence rate O (ln n/√n) where n is the number of training samples. The proof is based on a weaker assumption than those applied in similar research work.
Genome-Wide Identification and Analysis of Expression Profiles of Maize Mitogen-Activated Protein Kinase Kinase Kinase

Mitogen-activated protein kinase (MAPK) cascades are highly conserved signal transduction model in animals, yeast and plants. Plant MAPK cascades have been implicated in development and stress responses. Although MAPKKKs have been investigated in several plant species including Arabidopsis and rice, no systematic analysis has been conducted in maize. In this study, we performed a bioinformatics analysis of the entire maize genome and identified 74 MAPKKK genes. Phylogenetic analyses of MAPKKKs from maize, rice and Arabidopsis have classified them into three subgroups, which included Raf, ZIK and MEKK. Evolutionary relationships within subfamilies were also supported by exon-intron organizations and the conserved protein motifs. Further expression analysis of the MAPKKKs in microarray databases revealed that MAPKKKs were involved in important signaling pathways in maize different organs and developmental stages. Our genomics analysis of maize MAPKKK genes provides important information for evolutionary and functional characterization of this family in maize.
SeRQL: A Second Generation RDF Query Language

RDF Query Language proposals are more numerous than fish in the sea1, it seems. However, the most prominent proposals out there are query languages that were conceived as first generation tryouts of RDF querying, with little or no RDF-specific implementation and use experience to guide design, and based on an ever-changing set of syntactical and semantic specifications. In this position paper, we introduce a set of general requirements for an RDF query language. This set is compiled from discussions between RDF implementors, our own experience and user feedback that we received on our work in Sesame [4], as well as general principles of query language design. We go on to show how we have compiled these requirements into drafting the SeRQL query language. SeRQL is explicitly not meant as ’yet another’ query language: its aim is to reconcile ideas from existing proposals (most prominently RQL, RDQL and N3) into a proposal that satisfies a list of key requirements.
Classification and Categorization in Computer Assisted Reading and Analysis of Texts

Jean Guy Meunier, Université du Québec à Montréal Dominic Forest, Université du Québec à Montréal Ismail Biskri, Université du Québec à Trois-Rivières published Lefebvre, C. Cohen, H. (2005) Handbook on Categorization, Elsivier 2006
A Novel Role of the PrpR as a Transcription Factor Involved in the Regulation of Methylcitrate Pathway in Mycobacterium tuberculosis

Mycobacterium tuberculosis, the pathogen that causes tuberculosis, presumably utilizes fatty acids as a major carbon source during infection within the host. Metabolism of even-chain-length fatty acids yields acetyl-CoA, whereas metabolism of odd-chain-length fatty acids additionally yields propionyl-CoA. Utilization of these compounds by tubercle bacilli requires functional glyoxylate and methylcitrate cycles, respectively. Enzymes involved in both pathways are essential for M. tuberculosis viability and persistence during growth on fatty acids. However, little is known about regulatory factors responsible for adjusting the expression of genes encoding these enzymes to particular growth conditions. Here, we characterized the novel role of PrpR as a transcription factor that is directly involved in regulating genes encoding the key enzymes of methylcitrate (methylcitrate dehydratase [PrpD] and methylcitrate synthase [PrpC]) and glyoxylate (isocitrate lyase [Icl1]) cycles. Using cell-free systems and intact cells, we demonstrated an interaction of PrpR protein with prpDC and icl1 promoter regions and identified a consensus sequence recognized by PrpR. Moreover, we showed that an M. tuberculosis prpR-deletion strain exhibits impaired growth in vitro on propionate as the sole carbon source. Real-time quantitative reverse transcription-polymerase chain reaction confirmed that PrpR acts as a transcriptional activator of prpDC and icl1 genes when propionate is the main carbon source. Similar results were also obtained for a non-pathogenic Mycobacterium smegmatis strain. Additionally, we found that ramB, a prpR paralog that controls the glyoxylate cycle, is negatively regulated by PrpR. Our data demonstrate that PrpR is essential for the utilization of odd-chain-length fatty acids by tubercle bacilli. Since PrpR also acts as a ramB repressor, our findings suggest that it plays a key role in regulating expression of enzymes involved in both glyoxylate and methylcitrate pathways.
Numerical simulation of a one-dimensional shock tube problem at supercritical fluid conditions

The numerical computation of supercritical fluid flows is extremely challenging because of the complexity of the physical processes and the disparity of the space and time scales involved. Supercritical fluids exhibit large density fluctuations especially very close to the critical region. In this region, the perfect gas law is no longer valid and has to be replaced by a specific equation of state (EoS) as, for instance, the Altunin and Gadetskii EoS. In the present work, the problem of choosing a suitable numerical scheme for dense gas flow computations in a shock tube is addressed. In particular, the extension of the classical Roe’s scheme to real gas flows is used and its performance is evaluated by comparing with the analytical profile of the dimensionless density obtained by Sod in the shock tube problem. The application of this numerical implementation near the critical region of the fluid gives significant differences compared to gas dynamics and shows a relevant behaviour of the compressibility variation and localises an important gradient of temperature in the shock tube.
The evolution of the social programmer

Social media has revolutionized how humans create and curate knowledge artifacts [1]. It has increased individual engagement, broadened community participation and led to the formation of new social networks. This paradigm shift is particularly evident in software engineering in three distinct ways: firstly, in how software stakeholders co-develop and form communities of practice; secondly, in the complex and distributed software ecosystems that are enabled through insourcing, outsourcing, open sourcing and crowdsourcing of components and related artifacts; and thirdly, by the emergence of socially-enabled software repositories and collaborative development environments [2].
Model Checking the Leader Election Protocol with Fujaba

We have developed a new library for Fujaba that provides explicit concepts for hierarchical graphs. These graphs come with a generic deep clone operation, a sophisticated hash function, and an isomorphism check for pairs of graphs. Given a set of rewrite operations, above graph functionalities enable us to compute reachability graphs, i.e. from an start graph we compute the set of all graphs that might be created by repeated application of the graph rules. In this case study, we use these new features to do model checking for the leader election protocol.
Comparative Analysis of Artificial Intelligence Techniques for Goods Classification

In this paper, different methods of inventory classification are compared. ABC classical methodology discriminates the articles to be classified according to two variables: unitary cost and yearly demand. This paper proposes different methodologies that broaden the analysis over more attributes: Genetic Algorithms, Neural Networks, Tabu Search and several techniques included the WEKA program developed by the University of Waikato. To check the reliability of the models, the results are compared to the heuristic classification that an expert made in a set of 189 pharmaceutical products considering five input attributes. In addition, an Inventory Generator Program has been used to create five inventories that have been classified by the different algorithms, so that the results obtained by the algorithms could be compared.
Perturbation Solutions of the Quintic Duffing Equation with Strong Nonlinearities

The quintic Duffing equation with strong nonlinearities is considered. Perturbation solutions are constructed using two different techniques: The classical multiple scales method (MS) and the newly developed multiple scales Lindstedt Poincare method (MSLP). The validity criteria for admissible solutions are derived. Both approximate solutions are contrasted with the numerical solutions. It is found that MSLP provides compatible solution with the numerical solution for strong nonlinearities whereas MS solution fail to produce physically acceptable solution for large perturbation parameters.
Factors Influencing the Acceptance of Collaboration Technology within the Context of Virtual Teamwork Training.

The purpose of this study was to identify the factors that influence electronic collaboration technology acceptance and predicted usage for virtual team collaboration projects in higher education courses. The research combined the unified theory of acceptance and usage of technology (UTAUT) with a virtual team-training model. All 108 participants completed a survey following their participation in virtual team training. Ten hypotheses were tested using a structural equation modeling technique, partial least squares. Five of the hypotheses were supported and five were not supported. The results indicated that three of the four UTAUT constructs were significant in predicting if the participants would use the collaboration technology in the future. Additionally, the findings revealed that the participants had a positive perception of the virtual teamwork training.
Microfluidic Impedance Flow Cytometry Enabling High-Throughput Single-Cell Electrical Property Characterization

This article reviews recent developments in microfluidic impedance flow cytometry for high-throughput electrical property characterization of single cells. Four major perspectives of microfluidic impedance flow cytometry for single-cell characterization are included in this review: (1) early developments of microfluidic impedance flow cytometry for single-cell electrical property characterization; (2) microfluidic impedance flow cytometry with enhanced sensitivity; (3) microfluidic impedance and optical flow cytometry for single-cell analysis and (4) integrated point of care system based on microfluidic impedance flow cytometry. We examine the advantages and limitations of each technique and discuss future research opportunities from the perspectives of both technical innovation and clinical applications.
Small-signal analysis and control design of asymmetrical half-bridge DC-DC converters

This paper presents the small-signal modeling, dynamic analysis, and control design of the asymmetrical half-bridge dc-dc converter that employs a clamp capacitor and a magnetizing inductor to accommodate pulsewidth-modulated operation with asymmetrical duty ratios. The circuit averaging technique is applied to extract the small-signal dynamics of the power stage, and a graphical loop-gain method is used to design the feedback compensation and analyze the closed-loop performance of the converter. The distinctive power-stage dynamics of the converter are addressed and design guidelines for voltage feedback compensation are established. The results of the control design and closed-loop analysis are substantiated by experiments using an experimental converter.
Feature Based Video Extraction Using Tree Pruning

— Not long ago, advances in technology have made enormous amount of multimedia content available. The amount of video content is expanding, due to which the systems that better access the video is needed. Effectiveness of the retrieval system depends on the search method used within the system. The use of unsuitable search method may reduce the performance of the retrieval system. During last few years, multimedia storage is increased and price of storing digital data is also inexpensive. So there is huge volume of videos accessible in the multimedia database. It is very tough task to retrieve the relevant videos from the available huge volume of database, if user needs to access them. Hence a powerful video retrieval system is needed to retrieve the related videos from the available large database. To implement a powerful video retrieval system, visual perception should be taken into consideration. In this paper, we proposed an algorithm for video retrieval based on grouping of the video. This algorithm extracts or removes the key frames based on motion detection, Area of interest with the objects are perceived using bounding box method and are commented over the video and compared with the alike objects from the knowledge base constructed for various classes of videos to recognize the objects. This method also adopts tree based classifier to find out the class of the query video and to retrieve the same group videos from the large video database.
Automatic Measuring of English Language Proficiency using MT Evaluation Technology

Assisting in foreign language learning is one of the major areas in which natural language processing technology can contribute. This paper proposes a computerized method of measuring communicative skill in English as a foreign language. The proposed method consists of two parts. The first part involves a test sentence selection part to achieve precise measurement with a small test set. The second part is the actual measurement, which has three steps. Step one asks proficiency-known human subjects to translate Japanese sentences into English. Step two gauges the match between the translations of the subjects and correct translations based on the n-gram overlap or the edit distance between translations. Step three learns the relationship between proficiency and match. By regression it finds a straight-line fitting for the scatter plot representing the proficiency and matches of the subjects. Then, it estimates proficiency of proficiency-unknown users by using the line and the match. Based on this approach, we conducted experiments on estimating the Test of English for International Communication (TOEIC) score. We collected two sets of data consisting of English sentences translated from Japanese. The first set consists of 330 sentences, each translated to English by 29 subjects with varied English proficiency. The second set consists of 510 sentences translated in a similar manner by a separate group of 18 subjects. We found that the estimated scores correlated with the actual scores.