Miracle-dz/UniFAR-FTUs huggingface dataset:
MetaReg: A platform for modeling, analysis and visualization of biological systems using large-scale experimental data

) is a computational tool that models cellular networks and integrates experimental results with such models. MetaReg represents established knowledge about a biological system, available today mostly in informal form in the literature, as probabilistic network models with underlying combinatorial regulatory logic. MetaReg enables contrasting predictions with measurements, model improvements and studying what-if scenarios. By summarizing prior knowledge and providing visual and computational aids, it helps the expert explore and understand her system better.
The role of guanxi in buyer – supplier relationships in Chinese small-and medium-sized enterprises – a resource-based perspective

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The irace Package: Iterated Race for Automatic Algorithm Configuration

The program irace implements the iterated racing procedure, which is an extension of the Iterated F-race procedure (I/F-Race). Its main purpose is to automatically configure optimization algorithms by finding the most appropriate settings given a set of instances of an optimization problem. It builds upon the race package by Birattari and it is implemented in R. This revision documents irace version 0.9. The latest version of the irace software is available at http://iridia.ulb. ac.be/irace.
Deep Learning for NLP (without Magic)

Machine learning is everywhere in today's NLP, but by and large machine learning amounts to numerical optimization of weights for human designed representations and features. The goal of deep learning is to explore how computers can take advantage of data to develop features and representations appropriate for complex interpretation tasks. This tutorial aims to cover the basic motivation, ideas, models and learning algorithms in deep learning for natural language processing. Recently, these methods have been shown to perform very well on various NLP tasks such as language modeling, POS tagging, named entity recognition, sentiment analysis and paraphrase detection, among others. The most attractive quality of these techniques is that they can perform well without any external hand-designed resources or time-intensive feature engineering. Despite these advantages, many researchers in NLP are not familiar with these methods. Our focus is on insight and understanding, using graphical illustrations and simple, intuitive derivations. The goal of the tutorial is to make the inner workings of these techniques transparent, intuitive and their results interpretable, rather than black boxes labeled "magic here". The first part of the tutorial presents the basics of neural networks, neural word vectors, several simple models based on local windows and the math and algorithms of training via backpropagation. In this section applications include language modeling and POS tagging. In the second section we present recursive neural networks which can learn structured tree outputs as well as vector representations for phrases and sentences. We cover both equations as well as applications. We show how training can be achieved by a modified version of the backpropagation algorithm introduced before. These modifications allow the algorithm to work on tree structures. Applications include sentiment analysis and paraphrase detection. We also draw connections to recent work in semantic compositionality in vector spaces. The principle goal, again, is to make these methods appear intuitive and interpretable rather than mathematically confusing. By this point in the tutorial, the audience members should have a clear understanding of how to build a deep learning system for word-, sentence- and document-level tasks. The last part of the tutorial gives a general overview of the different applications of deep learning in NLP, including bag of words models. We will provide a discussion of NLP-oriented issues in modeling, interpretation, representational power, and optimization.
Water Quality Monitoring Project for Demonstration of Canal Remediation Methods Florida Keys

Several important results have been realized from Florida International University’s regional monitoring project. First is the documentation of elevated nutrient concentrations (nitrogen, phosphorous and silica) in waters close to shore along the Keys, and corresponding responses from the system, such as higher phytoplankton biomass (chlorophyll-a), turbidity and light attenuation, as well as lower oxygenation and lower salinities of the water column. These changes, associated to human impact, have become more obvious in a new series of stations located very close to shore, near canal mouths and sampled since November 2011. These waters are part of the so called Halo Zone, a belt following the shoreline which extends up to 500 meters offshore, and whose water quality characteristics are closely related to those in canals and affected by quick movement of infiltrated runoff and wastewaters (septic tanks), tides and high water tables pre-remediation
Security Framework for Wireless Sensor Networks

This paper presents an overview of the various issues and requirements of Wireless Sensor Network („WSN‟) deployments, and explores the unique network architecture of WSNs and the security issues involved. It is determined that in order to provide adequate security there is a need for the integration of security services into the existing routing protocols. To this end, an extension of the „LowEnergy Adaptive Clustering Hierarchy‟ („LEACH‟) network routing protocol called, the „Security Enabled Low-Energy Adaptive Clustering Hierarchy‟ („SE-LEACH‟) is proposed. This proposed protocol provides security services, such as data confidentiality, key management, data integrity and data freshness in the form of a flexible and extendable framework, thereby overcoming the security issues of existing WSN protocols.
Crossing Borders within the ABC Automation, Biomedical Engineering and Computer Science 55. IWK

It has been proven that the software testing phase is one of the most critical and important phases in the software development life cycle. In general, the software testing phase takes around 40-70% of the effort, time, and cost. This area is well researched over a long period of time. Unfortunately, while many researchers have found methods of reducing time and cost during the testing process, there are still a number of important related issues that need to be researched. This paper introduces a new high level test case generation process with a requirement prioritization method to resolve the following research problems: unable to identify suitable test cases with limited resources, lack of an ability to identify critical domain requirements in the test case generation process and ignore a number of generated test cases. Also, this paper proposes a practical test case generation technique derived from use case diagram.
Crossing Borders within the ABC Automation, Biomedical Engineering and Computer Science 55. IWK

In this paper, we describe a simulation framework to simulate a vehicle telematics system, using the example of a satellite-based toll collection system. The system consists of a large number of independent mobile agents which exchange messages with a single computing center, via a mobile communications network. The aim of the simulation study is the analysis of the frequency and the amount of communication, depending on system parameters and update strategies. The paper focuses on simulating communication caused by toll-collecting processes. As well as presenting the simulation framework and essential model components, it discusses several simulation results.
Crossing Borders within the ABC Automation, Biomedical Engineering and Computer Science 55. IWK

Even though one usually calculates capacitor losses with a complex Epsilon it still offends the principle of a constant speed of light. Maxwell's term c² = 1/(cid:2)·μ would even entail a physically unexplicable complex speed! By such an offence against basic principles every physicist is asked to search and to repair the mistake in the textbooks. In the present treatise vortex losses get in the place of a postulated and fictive imaginary part of the material constant (cid:2) when the function of a microwave oven, welding of PVC foils or capacitor losses are to be explained. The responsible potential vortices can be derived without postulate from approved physical laws and their existence can even be proved experimentally.
Real-time sail and heading optimization for a surface sailing vessel by extremum seeking control

In this paper we develop a simplified mathematical model representing the main elements of the behaviour of sailing vessels as a basis for simulation and controller design. For adaptive real-time optimization of the sail and heading angle we then apply extremum seeking control (which is a gradient based control law that drives the output of a linear or nonlinear system to its extremum) as an approach to maximize the longitudinal velocity. The basic idea behind extremum seeking and “how it works” is presented, as well as a simulation study on noise, convergence and stability issues.
Marker-less Facial Motion Capture based on the Parts Recognition.

A motion capture method is used to capture facial motion to create 3D animations and for recognizing facial expressions. Since the facial motion consists of non-rigid deformations of a skin, it is difficult to track a transition of a point on the face over time. Therefore, a number of methods based on markers have been proposed to solve this problem. However, since it is difficult to place the markers on a face or on an actual texture of the face, it is difficult to apply the marker-based capture methods. To overcome this problem, we propose a marker-less motion capture method for facial motions. Since the thickness of a skin varies in each facial part, the features of the motion of the each parts also vary. These features make the non-rigid tracking problem more difficult. To prevent the problem, we recognize five types of facial parts (nose, mouth, eye, cheek and obstacle) from 3D points of a face by using Random Forest algorithm. After the recognition of the facial parts, we track the motion of the each part by using a non-rigid registration algorithm based on the Gaussian Mixture Model. Since the motions of the each part are independently detected, we integrate the motions of the each part as 3D shape deformations for tracking the motions of the points on the whole face. We adopt a Free-Form Deformation technique which is based on the Radial Basis Function for the integration. This deformation method deforms 3D shapes seamlessly with pairs of key points: several numbers of points of a source face and the corresponding points of a target shape which are detected by the non-rigid registration algorithm. Finally, we represent the motion of the face as the deformation from the face of the initial frame to the others. In our results, we show that the proposed method enables us to detect the motion of the face more accurately.
End-to-end Deep Learning of Optimization Heuristics

Accurate automatic optimization heuristics are necessary for dealing with the complexity and diversity of modern hardware and software. Machine learning is a proven technique for learning such heuristics, but its success is bound by the quality of the features used. These features must be hand crafted by developers through a combination of expert domain knowledge and trial and error. This makes the quality of the final model directly dependent on the skill and available time of the system architect. Our work introduces a better way for building heuristics. We develop a deep neural network that learns heuristics over raw code, entirely without using code features. The neural network simultaneously constructs appropriate representations of the code and learns how best to optimize, removing the need for manual feature creation. Further, we show that our neural nets can transfer learning from one optimization problem to another, improving the accuracy of new models, without the help of human experts. We compare the effectiveness of our automatically generated heuristics against ones with features hand-picked by experts. We examine two challenging tasks: predicting optimal mapping for heterogeneous parallelism and GPU thread coarsening factors. In 89% of the cases, the quality of our fully automatic heuristics matches or surpasses that of state-of-theart predictive models using hand-crafted features, providing on average 14% and 12% more performance with no human effort expended on designing features.
TECHNISCHE BERICHTE TECHNICAL REPORTS

Many products and services, which we are using today, are powered by software. The software has a big impact on our everyday life and became in the last three decades one of the most important drivers of the global economy. The result of this development is that our presentday society extremely relies on software. This dependency will grow in the future, because of that we need to find and understand the challenges and trends, which will influence software in future, so that research and the economy can focus on them. A way to do so is to answer the question: What is the difference in software in 2025? We will make a contribution to the answer for this question through discussing the influence of heterogeneous processor units on the software and their deployment environments in 2025 in the first part of the paper. In the discussion we will present some reasons for our conclusion of the first part. The conclusion is that we expect that the software of 2025 will be executed on mobile devices from a heterogeneous processor unit and on stationary devices from a central or graphic processing unit. This very likely development rise the need for more and better dynamic adaptation technologies so that software can efficiently use the different processor unit kinds. In the second part of the paper we discuss reasons beside the efficiently use of processor units for the importance of the self adaptation approach, the autonomic computing approach and the role approach for the software in 2025. But important as autonomic computing may be we expect that autonomic computing as envisioned by IBM [10] will not completely exist in 2025, because of the standardization process, the difficult development of a query language, legal issues and security issues. More information to these are presented in the paper. To conclude both discussions we will give some recommendations.
Modularity for teams of I / O automata ✩

Input/Output automata (or I/O automata) were or inally introduced by Tuttle and Lynch [10,13] as model for distributed computations in asynchrono networks and as a means of constructing correct proofs of distributed algorithms. Basically, an I/O a tomaton is a transition system with action names beling its transitions. A distinction is made betwe internal actions and external (i.e., input and output) tions used for communication with the environme which may consist of other I/O automata. They c be composed using a synchronous product cons tion yielding a new I/O automaton. Many variants I/O automata were considered and the model is n widely used for describing reactive, distributed s tems [6–8,10–13].
Intergeneric symmetric and asymmetric somatic hybridization in

G. Spangenberg*, Z.Y. Wang, G. Legris, P. Montavon, T. Takamizo1 , R. Perez-Vicente2, M.P. Valles3 , 1. Nagel & I. Potrykus Institutefor Plant Sciences, Swiss Federal Institute of Technology, CH-8092 Zurich, Switzerland; I present address: National Grassland Research Institute, Senbonmatsu 768, Nishinasunomachi, Tochigi, Japan 329-27; 2 present address: Dpto. Fisiologfa Vegetal, Facultad de Ciencias, Universidad de Cordoba, 14004 Cordoba, Spain; 3 present address: Dpto. Genetica y Produccion Vegetal, Estacion Experimental de Aula Dei, C.S. l.c. , 50080 Zaragoza, Spain (* author for correspondence)
Water stress and social vulnerability in the southern United States, 2010-2040

Water scarcities are striking in semiarid, subregions of the Southern United States such as Oklahoma and western Texas (Glennon 2009, Sabo et al. 2010). In Texas, water stress has been a constant concern since the 1950s when the state experienced severe drought conditions (Moore 2005). The nearly 2000-mile Rio Grande River, which forms part of the Texas–Mexico border, is the sole source of groundwater for residents and businesses at the far western part of the state. The river also provides water for Ciudad Juarez in Mexico. Because of its strategic location, the Rio Grande is a site of water contestation between United States and Mexican concerns (Szydlowski 2007). To the east, a 3-year, state-level dispute over water rights involved North and South Carolina, as each state struggled to assert rights to the waters of the 225-mile Catawba River, which flows through the two states. The Catawba is a source of domestic water for more than one million residents and provides electricity to nearly double that number of consumers. The dispute was settled amicably in 2010, but these examples illustrate that the oftentimes, taken-for-granted assumptions of freshwater access in industrialized nations are being challenged by decreasing supplies, resulting from both existing and projected climatic changes. This chapter focuses on the social vulnerability of human communities to water stress in the U.S. South, commencing in 2010 and extending through 2040. One of the primary purposes for including it in this chapter is to highlight the interactions between climate change (in this case, through impacts on water availability) and humans, both in the context of social vulnerability and response drivers. To do so, we examine the intersection of social vulnerability and stresses on Q1 4
The Construct of State-Level Suspicion

Objective: The objective was to review and integrate available research about the construct of state-level suspicion as it appears in social science literatures and apply the resulting findings to information technology (IT) contexts. Background: Although the human factors literature is replete with articles about trust (and distrust) in automation, there is little on the related, but distinct, construct of “suspicion” (in either automated or IT contexts). The construct of suspicion—its precise definition, theoretical correlates, and role in such applications—deserves further study. Method: Literatures that consider suspicion are reviewed and integrated. Literatures include communication, psychology, human factors, management, marketing, information technology, and brain/neurology. We first develop a generic model of state-level suspicion. Research propositions are then derived within IT contexts. Results: Fundamental components of suspicion include (a) uncertainty, (b) increased cognitive processing (e.g., generation of alternative explanations for perceived discrepancies), and (c) perceptions of (mal)intent. State suspicion is defined as the simultaneous occurrence of these three components. Our analysis also suggests that trust inhibits suspicion, whereas distrust can be a catalyst of state-level suspicion. Based on a three-stage model of state-level suspicion, associated research propositions and questions are developed. These propositions and questions are intended to help guide future work on the measurement of suspicion (self-report and neurological), as well as the role of the construct of suspicion in models of decision making and detection of deception. Conclusion: The study of suspicion, including its correlates, antecedents, and consequences, is important. We hope that the social sciences will benefit from our integrated definition and model of state suspicion. The research propositions regarding suspicion in IT contexts should motivate substantial research in human factors and related fields.
Oil Contamination in Mississippi Salt Marsh Habitats and the Impacts to Spartina alterniflora Photosynthesis

Introduction . 134 Methods . 138 Study Sites . 138 Sampling of Sediments, Plants, and Animals for Oil Contamination . 140 Comparison of Marsh Oil with Macondo Oil . 141 Plant Stress Responses . 141 Pulsed Amplitude Modulation Chlorophyll Fluorescence . 142 LI-COR Chlorophyll Fluorescence and Gas Exchange . 143 Statistical Analyses . 143 Results . 144 Spatial Contamination . 144 Time-Series Contamination . 144 Photosynthesis Responses to Oil Contamination . 150 Pulsed Amplitude Modulation Chlorophyll Fluorescence at Marsh Point . 150 LI-COR Fluorescence and Gas Exchange at Marsh Point . 151 One-Year Assessment . 155 Discussion . 155 Contamination . 155 Location-Specific Oil Impacts . 159 Acute and Chronic Photosynthesis Responses . 161 Conclusions . 164 Acknowledgments . 164 References . 164
MOBLOGGING TYPE AND ITS RELATION WITH USABILITY AND DEVELOPMENT OF KNOWLEDGE MANAGEMENT SKILLS FOR BLIND STUDENTS

Mobile technology is not only for interactive use but also for gaining prominence in Education. The application of mobile technologies to learning has the potential to facilitate the active participation of learners in the creation and the delivery of content. Mobile technologies can also provide a powerful connection between a variety of formal and informal learning contexts and can help to build a community of learners. However these versatile tools present challenges to Educators and Learners (Anna et al., 2009).
On Complete Completion using Types and Weights

Developing modern software applications typically involves composing functionality from existing libraries. This task is difficult because libraries may expose many methods to the developer. To help developers in such scenarios, we present a technique that synthesizes and suggests valid expressions of a given type at a given program point. As the basis of our technique we use type reconstruction for lambda calculus terms in long normal form. We introduce a succinct representation for type judgements that merges types into equivalence classes to reduce the search space, then reconstructs any desired number of solutions on demand. Furthermore, we introduce a method to rank solutions based on weights derived from a corpus of code. We implemented the algorithm and deployed it as a plugin for the Eclipse IDE for Scala. We show that the techniques we incorporated greatly increase the effectiveness of the approach. Our evaluation benchmarks are derived from real code and are made available for future benchmarking of code synthesis driven by types.
A lternative splicing detection workflow needs a careful combination of sample prep and bioinformatics analysis

Carrara M, Lum J, Cordero F, Beccuti M, Poidinger M, Donatelli S, Calogero RA, Zolezzi F Department of Molecular Biotechnology and Health Sciences, University of Torino, Via Nizza 52, 10126 Torino, Italy Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), Singapore Department of Computer Science, University of Torino, C.so Svizzera 185, 10149 Torino, Italy Department of Biological Sciences, National University of Singapore