Miracle-dz/UniFAR-FTUs huggingface dataset:
AdaBoost Based Multi-Instance Transfer Learning for Predicting Proteome-Wide Interactions between Salmonella and Human Proteins

Pathogen-host protein-protein interaction (PPI) plays an important role in revealing the underlying pathogenesis of viruses and bacteria. The need of rapidly mapping proteome-wide pathogen-host interactome opens avenues for and imposes burdens on computational modeling. For Salmonella typhimurium, only 62 interactions with human proteins are reported to date, and the computational modeling based on such a small training data is prone to yield model overfitting. In this work, we propose a multi-instance transfer learning method to reconstruct the proteome-wide Salmonella-human PPI networks, wherein the training data is augmented by homolog knowledge transfer in the form of independent homolog instances. We use AdaBoost instance reweighting to counteract the noise from homolog instances, and deliberately design three experimental settings to validate the assumption that the homolog instances are effective to address the problems of data scarcity and data unavailability. The experimental results show that the proposed method outperforms the existing models and some predictions are validated by the findings from recent literature. Lastly, we conduct gene ontology based clustering analysis of the predicted networks to provide insights into the pathogenesis of Salmonella.
Design and prototyping of framework for automated continuous malware collection and analysis

In this paper, design of a framework for malware collection and analysis is described. The framework enables researchers to collect malware samples for analysis continuously, to develop counter measures and to generate pattern signatures for detection. By using this framework security analysts and operators are able to minimize their workload. Five components of malware collection unit, malware database, dynamic analysis unit, static analysis unit, signature generation and response unit have been developed and with certain level of manual operation these units are functional and are able to reduce workload of analysts for counter malware activities. Functionality to manage resources for integrated units such as virtual machines, virtual networks etc is being developed. Development of automated generation of signature would be key for this solution. An approach which compare network traffic generated by machines with malicious executable running and innocent network traffic collected from network used in daily operation which is assumed not to include malicious traffic is proposed. Under the situation with increasing number of newly created malware development of automation and continuity of counter malware scheme has been significant issues. This proposed framework is considered possible solution for such problem in the area of computer and network security.
Factored POMDPs with Mixed Observability

POMDPs(Partially Observable Markov Decision Processes) provide a principled mathematical framework for planning and decision making under uncertainty. It is widely used to model many kinds of real-world problems. However, solving POMDPs with a large number states remains a big challenge. In this report, we propose a novel representation for POMDP problems with observed state variables using dynamic bayesian network. We discuss the challenges faced in this implementation. We design an efficient algorithm to solve the problem using the new representation. Two POMDP benchmark problems were modelled using the new representation. We also propose a 3-Dimensional Autonomous Underwater Navigation(AUV) model which exploits the advantages of having observed state variables. We implemented the algorithm and evaluated its performance against previously proposed algorithms with several well-known POMDP problems, and our new AUV model. Our results show that our representation is more space efficient. The algorithm also runs faster. The results of this project would be sent for submission to the 2009: Robotics: Science and Systems(RSS) conference. Subject Descriptors: G3 Probability and Statistics I2.8 Problem Solving, Control Methods and Search I2.9 Robotics Planning
IRIT at TREC Microblog 2012: adhoc Task

This paper describes the participation of the IRIT lab, university of Toulouse, France, to the Microblog Track of TREC 2012. Two dierent models are experimented by our team for the adhoc task: (i) a Bayesian network retrieval model for tweet search and (ii) a feature learning model for relevance classication. Experimental results show that Bayesian network retrieval model improves the performances comparing to the track median.
Control of Electrical Machines for Drives

Electric drive systems are one of the most important components of our life; billions of them are used in industry, traffic applications and private environment. In the recent past an accelerated development of controlled drive systems could be experienced. The scientific and technical background of today’s most important drive systems, the converter controlled DC-drives and the vector controlled induction motor, are described in detail.
Vaccines, Virucides and Drugs Against HIV/AIDS: Hopes and Optimisms for the Future

More than 25 million lives have been claimed by AIDS and 33.2 million people are estimated to have HIV, the majority of which are living in the underdeveloped countries. Failed tests on vaccines, virucides and complete virus eradication have caused scientists to refocus on the basic questions of what makes an effective HIV immune response. The "gloom" over disappointing research results on vaccine development and virucides "threatens to overshadow more positive" HIV/AIDS-related news, such as findings that male circumcision might reduce the likelihood of HIV transmission and that giving antiretroviral drugs to "high-risk" HIV-negative people (pre-exposure prophylaxis) could help protect them from infection. Something like pre-exposure prophylaxis has a good chance of becoming available before we have a 100% efficacious vaccine. The future in the field of HIV/AIDS will be much brighter if global research is appropriately coordinated and sufficient funds are available.
Numerical Method for Shock Front Hugoniot States

We describe a Continuous Hugoniot Method for the efficient simulation of shock wave fronts. This approach achieves significantly improved efficiency when the generation of a tightly spaced collection of individual steady-state shock front states is desired, and allows for the study of shocks as a function of a continuous shock strength parameter, $v_p$. This is, to our knowledge, the first attempt to map the Hugoniot continuously. We apply the method to shock waves in Lennard-Jonesium along the $ $ direction. We obtain very good agreement with prior simulations, as well as our own benchmark comparison runs.
PREDICTING OF MACHINING QUALITY IN ELECTRIC DISCHARGE MACHINING USING INTELLIGENT OPTIMIZATION TECHNIQUES

This paper presents the development and application of fuzzy logic, neural network and genetic algorithm in EDM (Electrical Discharge Machining) for prediction of machining quality. Machining quality is the main indicator of technological performances of a component for EDM. The experiments are carried out on manganese alloyed cold-work tool steel, processed with electrodes made of copper. Experiments were conducted by varying the discharge current and pulse duration and the corresponding values of surface roughness were measured. The values of machining quality predicted by these models are then compared. All models show good agreement with experimental results. The results indicate that the genetic programming technique gives slightly smaller deviation of the measured values of model than fuzzy logic and neural network.
Extreme Markup Languages 2004 ® Montréal , Québec August 2-6 , 2004 DTD + + 2 . 0 : Adding support for co-constraints

In this paper we present an evolution of the DTD++ schema language for XML documents. The original DTD++ language provided support for a large and significant subset of XML Schema while maintaining a syntax closely resembling DTDs: thus the expressive power of XML Schema and the readability of DTDs were both supported in a modular architecture that could rely on a number of validating engine for XML schema. DTD++ did not provide solution for another big disadvantage of XML Schema and all other grammar-based validation languages: the inability (or limited ability) to express requirements on the co-existence or co-absence of elements and attributes, and other kind of reciprocal constraints cumulatively called coconstraints. The new version of DTD++, uninspiredly called DTD++ 2.0 and presented in this paper, provides a solution for specifying and verifying co-constraints on XML documents: by relying on one additional construct (conditional type assignment) and one additional predefined type (#ERROR) it is possible to express a large number of co-constraints in DTD++. Additionally, we describe an implementation of a validation engine for DTD++ 2.0 that maintains the main advantage of the previous version, in that it is but a pre-processor to any of a number of XML Schema validating engine, each of which can be used interchangeably. DTD++ 2.0: Adding support for co-constraints Table of
Measuring the impact of cognates in parallel text alignment

This paper evaluates the impact of considering cognates for aligning parallel texts using our aligner. By considering that two words may be cognates if their similarity is higher than a certain threshold and if they are automatically selected as aligners, we tested different degrees of cognativeness, by varying threshold values. A new methodology to measure the quality of resulting alignments is presented. Two language pairs are addressed: Portuguese-Spanish, and Portuguese-English
Fast Converging Blind Signal Separation Algorithm using the Bussgang Cost Function and the Natural Gradient

This paper proposes a new LMS based and RLS-like algorithms for blind separation of audio signals. The algorithms are developed based on classical adaptive filtering interpretation and modification to the Bussgang cost function, which is one of the main cost functions used in the filed of blind deconvolution. The fast converging RLS algorithm combines both the classical adaptive filtering theory along with the natural gradient rule to implement a more accurate update. This fast converging RLS algorithm is extended for the convolutive blind source separation. The paper also presents simulation results to prove that the new RLS algorithm has a faster convergence speed than the existing natural gradient algorithm.
A Joint Identification Approach for Argumentative Writing Revisions

Prior work on revision identification typically uses a pipeline method: revision extraction is first conducted to identify the locations of revisions and revision classification is then conducted on the identified revisions. Such a setting propagates the errors of the revision extraction step to the revision classification step. This paper proposes an approach that identifies the revision location and the revision type jointly to solve the issue of error propagation. It utilizes a sequence representation of revisions and conducts sequence labeling for revision identification. A mutation-based approach is utilized to update identification sequences. Results demonstrate that our proposed approach yields better performance on both revision location extraction and revision type classification compared to a pipeline baseline.
On the Validity of the IT-CISQ Quality Model for Automatic Measurement of Maintainability

IT-CISQ (Consortium for IT Software Quality) standard that was initiated and is driven by an OMG (Object Management Group) consortium claims to provide operational measures for a number of quality criteria of the ISO / IEC 25010 quality standard. In order to show the applicability of the IT-CISQ standard, we built a tool that provides automatic measures for the maintainability related measures of the IT-CISQ standard. We evaluated five Java open source projects with our IT-CISQ quality model and compared these results with the result of an expert-centered evaluation of the maintainability of these projects. The study shows that the IT-CISQ quality model for maintainability is well suited as a predictor for the quality criterion maintainability. Compared to our more comprehensive EMISQ (Expert Centered Method for Internal Software Quality) quality model (165 EMISQ measures vs. 18 IT-CISQ measures), the IT-CISQ quality model yields a similar order of projects. However, it is of course less suitable to give good guidance about improving aspects, as our more comprehensive EMISQ quality model includes considerably more maintainability related aspects of software. Furthermore, the tooling provided by us is innovative and could directly be used in practice by itself.
Regional Development Planning in Ethiopia: Past Experience, Current Initiatives and Future Prospects

This paper examines the evolution of regional development planning in Ethiopia and explores its future prospects. The main contention of the paper is that in the past, regional development, in line with the functional integration approach, was considered a national project. Four main problems have influenced regional policy areas, namely: a) the need for rapid growth and development, b) the need to industrialise, c) the need to develop water resources, and d) the need to develop resource frontiers and expansion of agricultural export. A concentration strategy and package programs; import substitution industrialisation; river basin development and commercial farms have been the regional policy responses to the above problems. These policies were not adequate to stimulate regional development and reduce the imbalances in the country. The current initiatives of regional policies are marked by decentralised planning systems, inter-regional allocation of resources; investment policies; regional capacity building; river basin planning and special area programs. The adequacy of each of these elements, however, indicates that there is room for improvement. In addition these policies are not implemented as part of an overall regional policy. The future orientation of regional policy should be based on the macro-economic development model of the country. Hence regional policy should derive from the policies of de. regulation, liberalisation, promotion of private investment, export-led growth and rural centred strategies. Similarly, the deepening of decentralisation should lead to more emphasis on local level development. Explicit concern with bringing regional equity should guide the resource allocation in future. It is recommended that the country should develop an explicit regional policy whose components should emphasise inter-regional co-operation; regional competitiveness; and regional resource mobilisation. Regional policies at regional levels should work towards achieving appropriate incentives/investment policy, participation of the people and generation of inter-sectoral plans. Eastern Africa Social Science Research Review (EASSRR) VOLUME XVI No. 1 January 2000, pp. 65-94
A probabilistic approach for fast covariance descriptor

In this paper, a low computational load based region covariance descriptor (RCD) approach has been proposed. The proposed method is based on using fewer feature vectors on construction of RCD. Number of feature vectors is reduced by utilizing the random pixel decimation pattern. By making use of the proposed method, fast covariance descriptor based object tracking has been carried out. As can be seen from the experimental results, the proposed method enables to perform fast RCD based object tracking without compromising relatively tracking quality.
From Tumor Immunosuppression to Eradication: Targeting Homing and Activity of Immune Effector Cells to Tumors

Unraveling the mechanisms used by the immune system to fight cancer development is one of the most ambitious undertakings in immunology. Detailed knowledge regarding the mechanisms of induction of tolerance and immunosuppression within the tumor microenvironment will contribute to the development of highly effective tumor eradication strategies. Research within the last few decades has shed more light on the matter. This paper aims to give an overview on the current knowledge of the main tolerance and immunosuppression mechanisms elicited within the tumor microenvironment, with the focus on development of effective immunotherapeutic strategies to improve homing and activity of immune effector cells to tumors.
Cache modelling in a performance evaluator for parallel database systems

Cache modelling is an important issue in developing an analytical performance evaluator to estimate the performance of applications running on parallel DBMSs. This paper describes a cache model developed for parallel cache management in the Oracle7 parallel server. Some preliminary results have also been obtained by using the cache model to predict the cache hit ratio for varying database sizes and varying numbers of participating processing elements.
Reciprocity And The Emergence Of Power Laws In Social Networks

Research in network science has shown that many naturally occurring and technologically constructed networks are scale free, that means a power law degree distribution emerges from a growth model in which each new node attaches to the existing network with a probability proportional to its number of links (= degree). Little is known about whether the same principles of local attachment and global properties apply to societies as well. Empirical evidence from six ethnographic case studies shows that complex social networks have significantly lower scaling exponents γ ~ 1 than have been assumed in the past. Apparently humans do not only look for the most prominent players to play with. Moreover cooperation in humans is characterized through reciprocity, the tendency to give to those from whom one has received in the past. Both variables — reciprocity and the scaling exponent — are negatively correlated (r = -0.767, sig = 0.075). If we include this effect in simulations of growing networks, degree distributions emerge that are much closer to those empirically observed. While the proportion of nodes with small degrees decreases drastically as we introduce reciprocity, the scaling exponent is more robust and changes only when a relatively large proportion of attachment decisions follow this rule. If social networks are less scale free than previously assumed this has far reaching implications for policy makers, public health programs and marketing alike.
Sketch based image deformation and editing with guaranteed feature correspondence

The establishment of a good correspondence mapping is a key issue in planar animations such as image morphing and deformation. In this paper, we present a novel mapping framework for animation of complex shapes. We firstly let the user extract the outlines of the interested object and target interested area from the input images and specify some optional feature lines, and then we generate a sparse delaunay triangulation mesh taking the outlines and the feature lines of the source shape as constraints. Then we copy the topology from the source shape to the target shape to construct a valid triangulation in the target shape. After that, each triangle of this triangular mesh is further segmented into a dense mesh patch. Each mesh patch is parameterized onto a unit circle domain. With such parameterization, we can easily construct a correspondence mapping between the source patches and the corresponding target patches. Our framework can work well for various applications such as shape deformation and morphing. Pleasing results generated by our framework show that the framework works well.
PPAR and Local Renin-Angiotensin Systems in Cardiovascular and Metabolic Diseases Associated with Obesity: A Unifying Hypothesis

Recent research has revealed roles for the PPAR family of transcription factors in the modulation of the RAAS. In particular, PPARα and PPARγ have been shown to control the transcription of renin in several tissues and influence the activity of local renin-angiotensin-systems coupling vascular and metabolic functions and contributing to their modulation. In this conceptual framework, PPAR and local RAS participate in the pathophysiology of blood pressure elevation, as well as in organ and tissue damage, and disturbances of glucose and lipid metabolism associated with cardiovascular diseases and obesity. The understanding of these mechanisms here discussed and their adequate pharmacological manipulation enlarge the potential to intervene pathological processes that connect the obesity with associate diseases and could alert about the adverse effects of some PPAR agonists on involved organs.
THE IMPACT OF EXCHANGE RATES AND OIL PRICES ON WHOLESALE ELECTRICITY SPOT PRICES IN EUROPEAN COUNTRIES : AN EMPIRICAL STUDY

This study is the first to investigate the relationship between daily electricity spot price returns and crude oil spot price returns (in US dollars) and the exchange rate return across a sample of six European countries-namely The EU countries investigated were selected on the basis of their national currency (EUR/USD or GBP/USD) and their dependency on oil for electricity production, with France, Spain and Germany using more nuclear, hydro and alternative sources than UK, the Netherlands and Italy. Furthermore, Spain was also chosen in order to provide terms of comparison with the results reported in Muñoz and Dickey (2009) [1]. The main contribution of our study is to show that there is in fact a transmission of volatility between both the exchange rate and the oil price towards the price of wholesale electricity and that, for some countries, the level of the electricity price is also affected by changes in exchange rate and oil price returns. Methods In order to model the effect of the exchange rate and oil price on each of the country's spot price of wholesale electricity we make use of a Generalised Autoregressive Conditionally Heteroscedastic (GARCH) approach. The conditional mean is modelled as a simple GARCH process-AR(1)-GARCH(1,1)-while the conditional variance is modelled as a non-linear GARCH with orders AR(1)-NGARCH(1,1). We explicitly look at two time frames, 2005-07 and 2008-11 (i.e. before and after the start of the subprime crisis). Results In the time period 2005-2007, the effect of exchange rate returns volatility on electricity price volatility was significant only for Italy, The Netherlands and Spain, but became significant for all the examined countries within the time frame 2008-2011. Given that the fuels used to produce electricity are traded in USD, it follows that the movements in the USD have affected the volatility of electricity prices. It has recently been shown [2] that peak oil prices, such as during oil supply restriction, more seriously hit some economic sectors compared to others. A 14% reduction of British electricity production and distribution was observed both in absolute and relative terms by increased oil prices with a loss of GBP 35.38 billion [2]. Exchange rate movements affected the Italian electricity price level in both periods indicating that the appreciation of the US dollar against the Euro is reflected through a rise of electricity prices in the country. In general, the more the oil import the larger should be the impact …
Readability Annotation: Replacing the Expert by the Crowd

This paper investigates two strategies for collecting readability assessments, an Expert Readers application intended to collect fine-grained readability assessments from language experts and a Sort by Readability application designed to be intuitive and open for everyone having internet access. We show that the data sets resulting from both annotation strategies are very similar. We conclude that crowdsourcing is a viable alternative to the opinions of language experts for readability prediction.