Miracle-dz/UniFAR-FTUs huggingface dataset:
UVBLUE: A New High-Resolution Theoretical Library of Ultraviolet Stellar Spectra

We present an extended ultraviolet-blue (850-4700 Å) library of theoretical stellar spectral energy distributions computed at high resolution, λ/Δλ = 50,000. The UVBLUE grid, as we named the library, is based on LTE calculations carried out with ATLAS9 and SYNTHE codes developed by R. L. Kurucz and consists of nearly 1800 entries that cover a large volume of the parameter space. It spans a range in Teff from 3000 to 50,000 K, the surface gravity ranges from log g = 0.0 to 5.0 with Δ log g = 0.5 dex, while seven chemical compositions are considered: [M/H] = -2.0, - 1.5, - 1.0, - 0.5, + 0.0, + 0.3, and +0.5 dex. For its coverage across the Hertzsprung-Russell diagram, this library is the most comprehensive one ever computed at high resolution in the short-wavelength spectral range, and useful application can be foreseen for both the study of single stars and in population synthesis models of galaxies and other stellar systems. We briefly discuss some relevant issues for a safe application of the theoretical output to ultraviolet observations, and a comparison of our LTE models with the non-LTE (NLTE) ones from the TLUSTY code is also carried out. NLTE spectra are found, on average, to be slightly "redder" compared to the LTE ones for the same value of Teff, while a larger difference could be detected for weak lines, which are nearly wiped out by the enhanced core emission component in case of NLTE atmospheres. These effects seem to be magnified at low metallicity (typically [M/H]≲ -1). A match with a working sample of 111 stars from the IUE atlas, with available atmosphere parameters from the literature, shows that UVBLUE models provide an accurate description of the main mid- and low-resolution spectral features for stars along the whole sequence from the B to ~G5 type. The comparison sensibly degrades for later spectral types, with supergiant stars that are in general more poorly reproduced than dwarfs. As a possible explanation of this overall trend, we partly invoke the uncertainty in the input atmosphere parameters to compute the theoretical spectra. In addition, one should also consider the important contamination of the IUE stellar sample, where the presence of binary and variable stars certainly works in the sense of artificially worsening the match between theory and observations.
ENRICHED MODEL CATEGORIES AND PRESHEAF CATEGORIES

We collect in one place a variety of known and folklore results in enriched model category theory and add a few new twists. The central theme is a general procedure for constructing a Quillen adjunction, often a Quillen equivalence, between a given V -model category and a category of enriched presheaves in V , where V is any good enriching category. For example, we rederive the result of Schwede and Shipley that reasonable stable model cate- gories are Quillen equivalent to presheaf categories of spectra (alias categories of module spectra) under more general hypotheses. The technical improve- ments and modifications of general model categorical results given here are applied to equivariant contexts in the sequels (14, 15). They are bound to have applications in various other contexts.
Automatic ADL classification using 3-axial accelerometers and RFID sensor

This paper presents a new method for recognizing the activities of daily living (ADL) based on the state-dependent motion analysis using three accelerometers and a glove type RFID reader. Two accelerometers are used for the classification of five body states based on the decision tree. Classification of the instrumental activities is performed based on the hand interaction with an object ID using an accelerometer and a RFID reader. Hand movements when using objects are classified into five classes in advance and final decision combines the body state and the instrumental activities. Experiment shows that the suggested hierarchical motion analysis provides accuracy rate of over 90% for all 20 ADLs.
Keyword based categorisation of diary entries to support personal Internet content pre-caching on mobile devices

This paper presents a study into the effectiveness of our algorithm for automatic categorisation of real users' diary entries, as a first step towards personal Internet content pre-caching on mobile devices. The study reports an experiment comparing trial subjects allocations of 99 diary entries to those predicted by a keyword-based algorithm. While leaving considerable grounds for improvement, results are positive and show pave the way for supporting mobile services based on categorising users' diary entries.
A New Approach to Hindi Text Steganography by Shifting Matra

Steganography is the means of storing information inside another message in such a way that hides informations existence. A number of steganography algorithms have been introduced using text, image, audio, video files as the cover media. Among these, text documents have been widely used for a very long time. This paper presents a new approach for steganography in Hindi texts. Considering the structure of Hindi alphabet/words, in this approach, by shifting the specific matra towards left or right, we hide the secret message in the text. This approach can be categorized under feature coding methods. The approach shows good result on the sample collected from different Hindi newspaper.
Functions of Genes and Enzymes Involved in Phenalinolactone Biosynthesis

Phenalinolactones are novel terpene glycoside antibiotics produced by Streptomyces sp. Tü6071. Inactivation of three oxygenase genes (plaO2, plaO3 and plaO5), two dehydrogenase genes (plaU, plaZ) and one putative acetyltransferase gene (plaV) led to the production of novel phenalinolactone derivatives (PL HS6, PL HS7, PL HS2 and PL X1). Furthermore, the exact biosynthetic functions of two enzymes were determined, and their in vitro activities were demonstrated. PlaO1, an FeII/α‐ketoglutarate‐dependent dioxygenase, is responsible for the key step in γ‐butyrolactone formation, whereas PlaO5, a cytochrome P450‐dependent monooxygenase, catalyses the 1‐C‐hydroxylation of phenalinolactone D. In addition, stable isotope feeding experiments with biosynthetic precursors shed light on the origin of the carbons in the γ‐butyrolactone moiety.
Opinion summarization for short texts based on BM25 and syntactic parsing

Online short texts of hot topics submitted to social media by users can provide valuable personal opinions, which are useful for service providers and individuals. However, it is difficult for readers to grasp the main opinions of massive short texts. In this paper, to cope with the summarization challenge of short texts, we proposed a novel approach, which makes full use of BM25 to weight each short text and syntactic parsing to generate important information of each opinion cluster. The approach also utilizes the feature pruning to reduce the dimensions of the vectors. We conduct our experiments on real datasets and evaluate the results by standard metrics and manual evaluation. The experimental results show that our proposed approach improves the accuracy when compared to the state-of-the-art method.
A Neural Dynamic Architecture for Reaching and Grasping Integrates Perception and Movement Generation and Enables On-Line Updating

Reaching for objects and grasping them is a fundamental skill for any autonomous robot that interacts with its environment. Although this skill seems trivial to adults, who effortlessly pick up even objects they have never seen before, it is hard for other animals, for human infants, and for most autonomous robots. Any time during movement preparation and execution, human reaching movement are updated if the visual scene changes (with a delay of about 100 ms). The capability for online updating highlights how tightly perception, movement planning, and movement generation are integrated in humans. Here, we report on an effort to reproduce this tight integration in a neural dynamic process model of reaching and grasping that covers the complete path from visual perception to movement generation within a unified modeling framework, Dynamic Field Theory. All requisite processes are realized as time-continuous dynamical systems that model the evolution in time of neural population activation. Population level neural processes bring about the attentional selection of objects, the estimation of object shape and pose, and the mapping of pose parameters to suitable movement parameters. Once a target object has been selected, its pose parameters couple into the neural dynamics of movement generation so that changes of pose are propagated through the architecture to update the performed movement online. Implementing the neural architecture on an anthropomorphic robot arm equipped with a Kinect sensor, we evaluate the model by grasping wooden objects. Their size, shape, and pose are estimated from a neural model of scene perception that is based on feature fields. The sequential organization of a reach and grasp act emerges from a sequence of dynamic instabilities within a neural dynamics of behavioral organization, that effectively switches the neural controllers from one phase of the action to the next. Trajectory formation itself is driven by a dynamical systems version of the potential field approach. We highlight the emergent capacity for online updating by showing that a shift or rotation of the object during the reaching phase leads to the online adaptation of the movement plan and successful completion of the grasp.
Together but apart: how spatial, temporal and cultural distances affect FLOSS developers' project retention

Companies rely more and more on virtual teams which consist of globally dispersed members. Unfortunately, members' separation can raise considerable interpersonal challenges. In order to prevent conflicts from deescalating and ensure effective teamwork, companies pay careful attention to the management of members' spatial, temporal and cultural distances. While initiatives developing Free Libre Open Source Software (FLOSS) similarly combine a worldwide distributed workforce, relatively little is known about how members' separation affects their collaboration. However, without such an understanding no adequate advice can be derived for managers of FLOSS initiatives on how to foster members' collaboration and retention. Building on lessons learned from the organizational domain this research hypothesizes that spatial, temporal and cultural distances are key factors for FLOSS developers' team integration and project retention. To evaluate our research hypotheses, we study FLOSS developers' contribution and conversation behavior and extract objective figures on their spatial, temporal and cultural distances to each other.
Safe cooperative CPS: A V2I traffic management scenario in the SafeCOP project

SafeCOP (Safe Cooperating Cyber-Physical Systems using Wireless Communication) is an European project that targets cyber-physical systems-of-systems whose safe cooperation relies on wireless communication. In particular, SafeCOP will provide an approach to the safety assurance of such systems in the healthcare, maritime, vehicle-to-vehicle and vehicle-to-infrastructure sectors. The vehicle-to-infrastructure (V2I) cooperation for the traffic management scenario is a key use cases of SafeCOP, where the cooperation between different cyber-physical systems can also include a significant interaction with remote servers. In this paper, we outline the V2I traffic management scenario and assess the research goals that arise from it, with special focus on the IoT characteristics.
Distributed Beacon Frequency Control Algorithm for VANETs (DBFC)

Two types of safety messages, beacons and event-driven emergency warning messages, are playing a key role in many safety-related applications of Intelligent Transportation System (ITS), which are designed for improving road safety and traffic efficiency. Every vehicle on the road periodically sends safety beacons to notify the neighbors on the road its position, speed, direction and acceleration. When there is an emergency situation, the event-driven warning messages are emitted. As the same Control Channel is used by these two types of messages, in dense network when congestion happens, it is necessary to reduce the beacon load to improve the channel condition by adjusting the transmit parameters. As a solution to the problem of overloading the channel, this paper proposes and evaluates an adaptive congestion control scheme which adjusts the beacon transmission frequency according to the current network condition, while considering the appropriate accuracy of status information updating. To appraise the algorithm, several simulations are performed. Simulation results demonstrate the promising results for the adaptive scheme.
Efficient space-time modeling for informative sensing

Real world phenomena often exhibit complex dynamics across space and time. Understanding such dynamics requires deploying sensors that provide relevant information about the observed phenomena. It is imperative to develop an efficient and accurate model, representing the complex spacetime dynamics, that can both inform sensor placement for efficient monitoring as well as help in appropriate knowledge discovery from the collected sensor data. This paper extends a generic non-stationary non-separable space-time Gaussian Process (GP) model, that models complex correlation properties using variable hyper parameters across input space. We provide approaches to effectively observe the hyper parameter space and thus significantly reduce the training cost for the proposed model. We also formalize relationship between degree of non-stationarity of the phenomenon and learning cost of the proposed model. Extensive empirical validation of the proposed model is performed using two real world sensing datasets, exhibiting diverse dynamics across space and time, to demonstrate the real world applicability of the proposed approach.
Pac Learning Constraint Dependency Grammar Constraints

Constraint Dependency Grammar (CDG) 11, 13] is a constraint-based grammatical formalism that has proven eeective for processing English 5] and improving the accuracy of spoken language understanding systems 4]. However, prospective users of CDG face a steep learning curve when trying to master this powerful formalism. Therefore, a recent trend in CDG research has been to try to ease the burden of grammar writers by developing methods for automatically learning CDG grammars from annotated sentences 22, 23]. In this paper, we prove that CDG grammar constraints are PAC learnable.
International Conference on Research and Innovation in Information Systems – 2013 ( ICRIIS ’ 13 ) Web Information Gathering Processes for Gold and Silver Price Information

This paper presents a research on product-specific web information gathering concept that intends to improve web searching through conventional search engines. Search engines are useful for searching general information; however, the results are not always accurate because they return the results based on key-words occurrences, but not accurateness. Further, users must filter and organize the information accordingly to make the information meaningful. Users must also visit multiple websites independently to check whether the information is relevant. These processes are tedious and very time consuming especially for users who search for specific products information. Hence, we propose a web information gathering model that aims to provide a standard for developing product-specific web searching tools. It was applied in a mobile application called Gold-Trader. The mobile application provides gold and silver prices information to individual or personal traders. It can help individual or personal traders to monitor and compare gold and silver prices from multiple websites without the needs to visit them individually. Keywords—gold trading, gold price, decision making, information gathering, mobile application
Objects that agree on task frequency in the IoT: A lifetime-oriented consensus based approach

Some key features of the end-systems impact on the way communications happen within the IoT: available objects' resources are limited, different objects may provide the same information (e.g. sense the same physical measure), the number of nodes in the IoT is quickly overcoming the number of Internet hosts with greater reliability issues. This entails for a new paradigm of communication with respect to those characterizing the traditional Internet. Before providing the required information about the physical world, objects coordinate with the other objects in groups and provide a unified service to the external world (the application that requires the service), with the intent to distribute the load of the requested services according to specific community defined rules, which could be: lifetime extension, QoS (Quality of Service) maximization, reward maximization, or others. In this paper other than describing the characteristics of this new communication paradigm and challenges it is called to address, we also propose a first solution for its implementation that relies on a distributed optimization protocol based on the consensus algorithm. Results of simulations and real experiments are also presented that show the viability in implementing the new communication model in a distributed way.
Truncated maximal ratio combining for iterative multiuser decoding

In this paper, the concept of information combining is investigated for iterative multiuser decoding. This is done by applying recursive maximal ratio combining (MRC) over iterations to interference cancellation based multiuser detectors. Here, we show that combining over all iterations may not be appropriate as correlations build up. Numerical results show that applying MRC only over the first few iterations can improve the bit error rate performance with only a modest increase in complexity, as compared to no combining
Use of Genome-Wide Association Studies for Cancer Research and Drug Repositioning

Although genome-wide association studies have identified many risk loci associated with colorectal cancer, the molecular basis of these associations are still unclear. We aimed to infer biological insights and highlight candidate genes of interest within GWAS risk loci. We used an in silico pipeline based on functional annotation, quantitative trait loci mapping of cis-acting gene, PubMed text-mining, protein-protein interaction studies, genetic overlaps with cancer somatic mutations and knockout mouse phenotypes, and functional enrichment analysis to prioritize the candidate genes at the colorectal cancer risk loci. Based on these analyses, we observed that these genes were the targets of approved therapies for colorectal cancer, and suggested that drugs approved for other indications may be repurposed for the treatment of colorectal cancer. This study highlights the use of publicly available data as a cost effective solution to derive biological insights, and provides an empirical evidence that the molecular basis of colorectal cancer can provide important leads for the discovery of new drugs.
Determinants of Private Investment Behaviour

This study analyses the determinants of private investment in Ghana using a time series analysis and complementing it with a cross-sectional one. From many perspectives, the cross-sectional analysis supports the time series analysis. While some of the individual effects of the components of macroeconomic instability are found to be negligible, the overall measure of macroeconomic instability has been a major hindrance to private investment. The results suggest that policies that address only some components of macroeconomic instability may not be enough to revive private investment. The growth of real credit to the private sector has a positive and statistically significant effect on private investment. The question of finance must therefore be addressed in order to ensure continuing participation of the private sector in investment. Private investment and public investment are found to be complementary and thus there is the need for the government to continue to develop the infrastructural base of the economy to boost the private sector. The econometric results suggest that the military takeovers may have created a climate hostile to private investment. The primary objective of the study is to analyse the determinants of private investment in Ghana between 1970 and 1992. For this purpose, we use both time series and cross-sectional analysis. The cross-sectional analysis will be used to determine whether the factors identified in the time series analysis are still constraints to private investment. Specifically, the study seeks to Estimate a time series model with private investment as the dependent variable to determine significant explanatory variables; Identify the factors that are perceived to influence the investment decisions of private manufacturers by surveying manufacturing firms; and To analyse the consistency of the time series analysis with the cross-sectional analysis.
Application of BIRCH to text clustering

This work represents a clustering technique, based on the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm and LSA-methods for clustering large, high dimensional datasets. We present a document model and a clustering tool for processing texts in Russian and English languages and compare our results with other clustering techniques. Experimental results for clustering the datasets of 10’000, 100’000 and 850’000 documents are provided.
Formal methods for V&V of partial specifications: an experience report

This paper describes our work exploring the suitability of formal specification methods for independent verification and validation (IV&V) of software specifications for large, safety critical systems. An IV&V contractor often has to perform rapid analysis on incomplete specifications, with no control over how those specifications are represented. Lightweight formal methods show significant promise in this context, as they offer a way of uncovering major errors, without the burden of full proofs of correctness. We describe an experiment in the application of the method SCR to testing for consistency properties of a partial model of the requirements for fault detection isolation and recovery on the space station. We conclude that the insights gained from formalizing a specification is valuable, and it is the process of formalization, rather than the end product that is important. It was only necessary to build enough of the formal model to test the properties in which we were interested. Maintenance of fidelity between multiple representations of the same requirements (as they evolve) is still a problem, and deserves further study.