Miracle-dz/UniFAR-FTUs huggingface dataset:
Static power of mobile devices: Self-updating radio maps for wireless indoor localization

The proliferation of mobile computing has prompted WiFi-based indoor localization to be one of the most attractive and promising techniques for ubiquitous applications. A primary concern for these technologies to be fully practical is to combat harsh indoor environmental dynamics, especially for long-term deployment. Despite numerous research on WiFi fingerprint-based localization, the problem of radio map adaptation has not been sufficiently studied and remains open. In this work, we propose AcMu, an automatic and continuous radio map self-updating service for wireless indoor localization that exploits the static behaviors of mobile devices. By accurately pinpointing mobile devices with a novel trajectory matching algorithm, we employ them as mobile reference points to collect real-time RSS samples when they are static. With these fresh reference data, we adapt the complete radio map by learning an underlying relationship of RSS dependency between different locations, which is expected to be relatively constant over time. Extensive experiments for 20 days across 6 months demonstrate that AcMu effectively accommodates RSS variations over time and derives accurate prediction of fresh radio map with average errors of less than 5dB. Moreover, AcMu provides 2x improvement on localization accuracy by maintaining an up-to-date radio map.
Species Distribution 2.0: An Accurate Time- and Cost-Effective Method of Prospection Using Street View Imagery

Species occurrence data provide crucial information for biodiversity studies in the current context of global environmental changes. Such studies often rely on a limited number of occurrence data collected in the field and on pseudo-absences arbitrarily chosen within the study area, which reduces the value of these studies. To overcome this issue, we propose an alternative method of prospection using geo-located street view imagery (SVI). Following a standardised protocol of virtual prospection using both vertical (aerial photographs) and horizontal (SVI) perceptions, we have surveyed 1097 randomly selected cells across Spain (0.1x0.1 degree, i.e. 20% of Spain) for the presence of Arundo donax L. (Poaceae). In total we have detected A. donax in 345 cells, thus substantially expanding beyond the now two-centuries-old field-derived record, which described A. donax only 216 cells. Among the field occurrence cells, 81.1% were confirmed by SVI prospection to be consistent with species presence. In addition, we recorded, by SVI prospection, 752 absences, i.e. cells where A. donax was considered absent. We have also compared the outcomes of climatic niche modeling based on SVI data against those based on field data. Using generalized linear models fitted with bioclimatic predictors, we have found SVI data to provide far more compelling results in terms of niche modeling than does field data as classically used in SDM. This original, cost- and time-effective method provides the means to accurately locate highly visible taxa, reinforce absence data, and predict species distribution without long and expensive in situ prospection. At this time, the majority of available SVI data is restricted to human-disturbed environments that have road networks. However, SVI is becoming increasingly available in natural areas, which means the technique has considerable potential to become an important factor in future biodiversity studies.
The GENIA corpus: an annotated research abstract corpus in molecular biology domain

With the information overload in genome-related field, there is an increasing need for natural language processing technology to extract information from literature and various attempts of information extraction using NLP has been being made. We are developing the necessary resources including domain ontology and annotated corpus from research abstracts in MEDLINE database (GENIA corpus). We are building the ontology and the corpus simultaneously, using each other. In this paper we report on our new corpus, its ontological basis, annotation scheme, and statistics of annotated objects. We also describe the tools used for corpus annotation and management.
A Survey on Network Tomography With Network Coding

The overhead of internal network monitoring motivates techniques of network tomography. Network coding (NC) presents a new opportunity for network tomography as NC introduces topology-dependent correlation that can be further exploited in topology estimation. Compared with traditional methods, network tomography with NC has many advantages, such as the improvement of tomography accuracy and the reduction of complexity in choosing monitoring paths. In this paper, we first introduce the problem of tomography with NC and then propose the taxonomy criteria to classify various methods. We also present existing solutions and future trend. We expect that our comprehensive review on network tomography with NC can serve as a good reference for researchers and practitioners working in the area.
SYSTEMATICS, MORPHOLOGY AND PHYSIOLOGY Genetic Variability of Native Populations of Wasmannia Forel (Hymenoptera: Formicidae) and their Biogeographical Implications

Wasmannia auropunctata (Roger) and Wasmannia rochai Forel are economically important ants in the Southeast and Southwest regions of Bahia State, Brazil. Randomly Amplifi ed Polymorphic DNA (RAPD) markers were used to distinguish and analyze the genetic variability of populations of both species from Ilheus, Jequie, BA and French Guyana. The genetic distances among W. auropunctata and W. rochai populations (55.8-71.4%) suggest genetic differentiation among them. Wasmannia auropunctata populations from sugarcane and banana plantations in Jequie were the most distant genetically (30.1-46.3%) and may represent populations restricted to isolated fragments. The high genetic distances among W. auropunctata populations from CEPLAC experimental areas, in Ilheus (26.8-34.6%) and the other populations from Ilheus (23.3-40.8%), suggest a multicolonial structure of W. auropunctata in southeast Bahia. The genetic proximity among the W. auropunctata populations from cocoa (14.1%) and coconut plantations (18.5%) in Ilheus with the populations from the French Guyanan forests suggest that there was recent and large expansion of populations derived from a single population, that are today distributed in habitats with similar environmental characteristics. The high polymorphism and the estimated heterozygosity values for the two species suggest that we studied native W. auropunctata and W. rochai populations.
The Phrasal Lexicon in Multilingual Text Generation Submission Type: General Session Topic Areas or Theme Id: Multilingual Natural Language Generation Word Count: 3150 under Consideration for Other Conferences (specify)? None

We introduce the ML-Peba system, a system which generates textual descriptions of animals in both English and Spanish from an abstract knowledge base. The system relies upon a phrasal lexicon for linguistic realization. The paper discusses the pros and cons of this approach for multilingual generation, suggesting that its use enables a more language-independent knowledge representation than most generation approaches.
Joint n-gram Chinese language modeling with an application to Chinese word segmentation

The state-of-the-art language models (LMs) are n-gram models, which, for Chinese, are word-based n-grams. To construct Chinese word-based n-gram LMs, we need to have a lexicon and a Chinese word segmentation (CWS) step. However, there is no standard definition of a word in Chinese, and it is always possible to construct new words by combining multiple characters, which causes out-of-vocabulary (OOV) problems. These make lexicon definition and CWS being difficult and ill-defined, which deteriorates the quality of the Chinese LMs. Recently, conditional random fields (CRFs) have been shown to have the ability to perform robust and accurate CWS, especially in recalling OOV words. However they are in essence not Chinese language models, but conditional models of the position-of-character (POC) tag-sequence given the character-sequence. In this paper, we propose a new Chinese language model - joint n-gram, which incorporates the POC tags so that we escape from using a lexicon. It is a truly generative model of Chinese sentences. The effectiveness of the new LM is shown in terms of perplexities and CWS performances.
Knowledge and the Recognition and Understanding of Software Documents

We survey the work on the automatic recognition and understanding of software documents. In particular, we are concerned with the creation of formal models of the knowledge and information contained in software documents, and the uses that can be made of these models. This includes formal descriptions of the structure and layout of software documents, as well as the deeper semantics of a document's contents. We found only a few papers dealing speciically with the recognition and understanding of software documents. However, there are sources of information from which we can infer the state-of-the-art and the open research issues. Three sources are the work on recognition of technical documents that include graphics, tables, and formulae; the work on document management that uses knowledge representation and reasoning ; and the work on modeling the software development process, especially the meta-models that describe the information required about entities and activities. Current technology for document processing can handle several subtasks necessary for understanding software documents. The recognition and understanding of text from constrained domains, and of diagrams and tables are adequately handled in the state-of-the-art. These tasks would be improved if more contextual knowledge about document layouts, and domain standards were used. For the processing of text constrained to a particular domain of discourse, domain knowledge in the form of lexicons and grammars is vital. Mathematical formula and equations are not handled well. Deep understanding of documents is diicult. It has been handled on a case by case basis for a few individual document types, such as ow charts and circuit diagrams. Flexibility and robustness is added to document processing systems through a model-driven approach, thus separating processing from the models of the domain knowledge, such as document layouts and standards, and from algorithmic knowledge, such as image processing algorithms. The choice and representation of domain knowledge to enable deep understanding is a very diicult problem.
A Parametric Testing Environment for Finding the Operational Envelopes of Simulated Guidance Algorithms

The ever-increasing size and complexity of aerospace systems often drive developers to validate using modeling and Monte Carlo simulations confined around expected points of operation in a hyper-dimensional parameter space. This paper describes an alternative that explores large regions of the parameter space with explicit coverage guarantees, searching for n parameter relations that characterize a system’s performance envelope.
Characterization and modeling of oxide chemical-mechanical polishing using planarization length and pattern density concepts

Chemical-mechanical polishing (CMP) has emerged as the dominant dielectric planarization method due to its ability to reduce topography over longer lateral distances than earlier techniques. However, CMP still suffers from pattern dependencies that result in large variation in polished oxide thickness across typical chips, which can impact circuit performance and yield. A comprehensive semiphysical pattern dependent model of the CMP process, integrated with a parameter extraction and process characterization methodology, has been developed to enable accurate and efficient prediction of post-CMP oxide thickness across patterned chips. In the characterization phase, test wafers are polished to obtain model parameters for the desired CMP process. Standard test layouts have been defined which consist of regions with different feature density and pitch; a new contribution is the inclusion of "step density" structures which provide large abrupt post-CMP thickness variations to improve parameter extraction. The key extracted parameter which characterizes the particular CMP process is the planarization length.
Towards the Automotive HMI of the Future: Overview of the AIDE-Integrated Project Results

The Adaptive Integrated Driver-vehicle interfacE (AIDE) is an integrated project funded by the European Commission in the Sixth Framework Programme. The project, which involves 31 partners from the European automotive industry and academia, deals with behavioral and technical issues related to automotive human-machine interface (HMI) design, with a particular focus on integration and adaptation. The project involves tightly integrated empirical research, driver-behavior modeling, and methodological and technological development. This paper provides an overview of the AIDE Sub-Project 3 results dealing with the design, development, and integration of the AIDE system in three prototype vehicles, together with the evaluation results of the trials.
List decoding for noisy channels

Summary. Shannon's fundamental coding theorem for noisy channels states that such a channel has a capacity C, and that for any transmission rate R less than C it is possible for the receiver to use a received sequence of n symbols to select one of the 2 nR possible transmitted sequences, with an error probability Pe which can be made arbitrarily small by increasing n, keeping R and C fixed. Recently upper and lower bounds have been found for the best obtainable Pe as a function of C,R and n. This paper investigates this relationship for a modified decoding procedure, in which the receiver lists L messages, rather than one, after reception. In this case for given C and R, it is possible to choose L large enough so that the ratio of upper and lower bounds to the error probability is arbitrarily near to 1 for all large n. This implies that for large L, the average of all codes is almost as good as the best code, and in fact that almost all codes are almost as good as the best code
Power and Data Aware Best Fit Algorithm for Energy Saving in Cloud Computing

Cloud computing is a computing advancement that provides a large number of computing and storage resources to different people. Management of huge amount of data in cloud computing is done by VM consolidation. Nowadays, energy saving has become a key aspect in designing VM consolidation algorithms. Algorithms for selecting next VM have never given consideration to both power and data at the same time in past. This paper proposes power and data aware best fit algorithm (PDABFD) for selecting next VM with power and data constraints. Proposed algorithm work in the direction of maximum resource utilization by VMs. Proper utilization of resources leads to conservation of energy. As a result, energy consumption using PDABFD algorithm is less than previous algorithms. KEYWORDSCloud computing, CloudSim, Clouds, Simulator, PDABFD, Power Aware algorithm, Energy saving algorithm
Modern avenues for intergroup contact: Using E-contact and intergroup emotions to reduce stereotyping and social distancing against people with schizophrenia

Intergroup contact is the leading strategy for reducing the stigma associated with mental illness. For the first time, the current study examines the effectiveness of a contemporary intergroup contact strategy, called electronic or E-contact, to reduce stigma against people diagnosed with schizophrenia. It also examines the mediating role of three target-relevant intergroup emotions, namely fear, anger, and pity. In total, 133 participants engaged in E-contact with a person diagnosed with schizophrenia (intergroup E-contact), E-contact with a person without a mental illness (intragroup E-contact), or no contact. Compared to the intragroup E-contact and no-contact conditions, intergroup E-contact reduced fear, anger, and stereotyping toward people with schizophrenia. Additionally, fear and anger, but not pity, were found to be significant affective mediators of the E-contact effect. The findings demonstrate the value of computer-mediated intergroup contact for stigma reduction, and emphasize the importance of intergroup emotions in this domain.
Oral prescription opioid-seeking behavior in male and female mice

A significant portion of prescription opioid users self-administer orally rather than intravenously. Animal models of opioid addiction have demonstrated that intravenous cues are sufficient to cause drug-seeking. However, intravenous models may not model oral users, and the preference to self-administer orally appears to be partially influenced by the user’s sex. Our objectives were to determine whether oral opioid-associated cues are sufficient for relapse and whether sex differences exist in relapse susceptibility. Mice orally self-administered escalating doses of oxycodone under postprandial (prefed) or non-postprandial (no prefeeding) conditions. Both sexes demonstrated robust cue-induced reinstatement. In separate mice we found that oral oxycodone cues were sufficient to reinstate extinguished oral oxycodone-seeking behavior in the absence of postprandial or prior water self-administration training. During self-administration, we found that female mice earned significantly more mg/kg oxycodone than male mice. Follow-up studies indicated sex differences in psychomotor stimulation and plasma oxycodone/oxymorphone following oral oxycodone administration. In addition, gonadal steroid studies were performed in which we found divergent responses where ovariectomy enhanced and orchiectomy suppressed oral self-administration. While the suppressive effects of orchiectomy were identified across doses and postprandial conditions, the enhancing effects of ovariectomy were selective to non-postprandial conditions. These studies establish that 1) oral drug cues are sufficient to cause reinstatement that is independent of prandial conditions and water-seeking behavior, 2) earned oral oxycodone is larger in female mice compared with male mice potentially through differences in psychomotor stimulation and drug metabolism, and 3) gonadectomy produces divergent effects on oral oxycodone self-administration between sexes.
THE TURBULENT HEATING RATE IN STRONG MAGNETOHYDRODYNAMIC TURBULENCE WITH NONZERO CROSS HELICITY

Different results for the cascade power ϵ in strong, incompressible magnetohydrodynamic turbulence with nonzero cross helicity appear in the literature. In this paper, we discuss the conditions under which these different results are valid. Our conclusions can be expressed in terms of the density ρ, the rms amplitudes z+ and z− of Alfvénic fluctuations propagating parallel and antiparallel to the background magnetic field B0, and the correlation length (outer scale) measured perpendicular to B0, denoted L⊥. We argue that if z+ ≫ z− and if the z− fluctuations are sustained by the reflection of z+ fluctuations in a strong background magnetic field, then ϵ ∼ ρ(z+)2z−/L⊥ as in previous studies by Hossain, Matthaeus, Dmitruk, Lithwick, Goldreich, Sridhar, and others. On the other hand, if the minority wave type (z−) is sustained by some form of forcing that is uncorrelated with or only weakly correlated with the z+ fluctuations, then ϵ can be much less than ρ(z+)2z−/L⊥, as in previous studies by Dobrowolny, Lazarian, Chandran, and others. The mechanism for generating the minority wave type strongly affects the cascade power because it controls the coherence time for interactions between oppositely directed wave packets at the outer scale.
Software-defined networking: Reconfigurable network systems in LAN topology

An emerging technology of SDN plays a vital role in network reconfiguration. In an existing system, real word experiment on dynamic changing network topology lacks the ability to change the network configuration. The article works for dynamic reconfiguration in networking through high-level programmability via such C++ or python via SDN controller. In this paper, SDN enable an innovation performance for improving the network reconfigurability through three resources such as controller (Raspberry pi), switch and host nodes. The protocol of Openflow acts as an interface between controller and switch. As a result, the dynamic network reconfigurability solves the problem of manual configuration and reconfiguration to the network operator where the system deploys on campus network.
Ablation of Mineralocorticoid Receptors in Myocytes But Not in Fibroblasts Preserves Cardiac Function

Antagonists of the mineralocorticoid receptor improve morbidity and mortality in patients with severe heart failure. However, the cell types involved in these beneficial effects are only partially known. The aim of this work was to evaluate whether genetic deletion of mineralocorticoid receptors in mouse cardiomyocytes or fibroblasts in vivo is cardioprotective after chronic left ventricular pressure overload. After transverse aortic constriction, mice deficient in myocyte mineralocorticoid receptors but not those deficient in fibroblast mineralocorticoid receptors were protected from left ventricular dilatation and dysfunction. After pressure overload, left ventricular ejection fraction was significantly higher in mice lacking myocyte mineralocorticoid receptors (70.2±4.4%) as compared with control mice (54.3±2.5%; P<0.01). Myocyte mineralocorticoid receptor-deficient mice showed mild cardiac hypertrophy at baseline, contributing to reduced left ventricular wall tension at baseline and after pressure overload. Cardiac levels of phospho-extracellular signal–regulated kinase 1/2 were higher in myocyte mineralocorticoid receptor-deficient mice than in control mice after pressure overload. Neither fibroblast nor myocyte mineralocorticoid receptor ablation altered the development of cardiac hypertrophy or fibrosis after pressure overload. Both mineralocorticoid receptor mutant mouse strains developed similar degrees of myocyte apoptosis, proinflammatory gene expression, and macrophage infiltration after pressure overload. Thus, mineralocorticoid receptors in cardiac myocytes but not in fibroblasts protect from cardiac dilatation and failure after chronic pressure overload.
Navigating Random Forests and related advances in algorithmic modeling

: This article addresses current methodological research on non-parametric Random Forests. It provides a brief intellectual history of Random Forests that covers CART, boosting and bagging methods. It then introduces the primary methods by which researchers can visualize results, the relationships between covariates and responses, and the out-of-bag test set error. In addition, the article considers current research on universal consistency and importance tests in Random Forests. Finally, several uses for Random Forests are discussed, and available software is identiﬁed.
Polish Coreference Corpus in Numbers

This paper attempts a preliminary interpretation of the occurrence of different types of linguistic constructs in the manually-annotated Polish Coreference Corpus by providing analyses of various statistical properties related to mentions, clusters and near-identity links. Among others, frequency of mentions, zero subjects and singleton clusters is presented, as well as the average mention and cluster size. We also show that some coreference clustering constraints, such as gender or number agreement, are frequently not valid in case of Polish. The need for lemmatization for automatic coreference resolution is supported by an empirical study. Correlation between cluster and mention count within a text is investigated, with short characteristics of outlier cases. We also examine this correlation in each of the 14 text domains present in the corpus and show that none of them has abnormal frequency of outlier texts regarding the cluster/mention ratio. Finally, we report on our negative experiences concerning the annotation of the near-identity relation. In the conclusion we put forward some guidelines for the future research in the area.