Miracle-dz/UniFAR-FTUs huggingface dataset:
Situation Awareness : Issues and Challenges

To explain what I mean by " situation awareness " I often use the example of watching the games like Ameri-can football or baseball. Since I have never learned the rules and the strategies of these games, when watching them on TV, although I can clearly see where each player is and where the ball is, I still have no idea of what is going on. Clearly, in this case I cannot claim that I am aware of the situation. The term " situation awareness " has been often interpreted in a somewhat simplistic way as merely the knowledge of all the objects in a specific area, and possibly their kinematic states. It is clear, however, that the meaning of this term implies more than that. For instance, in [1], awareness is explained as " AWARE implies vigilance in observing or alertness in drawing inferences from what one experiences. " In other words, a subject is aware if the subject not only observes (experiences) the objects but also is capable of drawing conclusions from these observations. The next question is about the meaning of being aware of a specific situation. The word " situation " is defined in [1] as: " 1 a : the way in which something is placed in relation to its surroundings. " So the essence of situation awareness is the knowledge of all the objects that are relevant to the subject and the knowledge of the relations that the subject is in with respect to these objects. In other words, awareness means knowing not only objects but also relations. The notions of " awareness " and " situation " are not totally independent in the sense that they both have one common aspect, the aspect of " relation ". In mathematics , a relation is a subset of the Cartesian product of a number of sets. For instance, the Cartesian product A × B of two sets A and B is the set of all ordered pairs < a, b >, i.e., A × B = {< a, b >, a ∈ A, b ∈ B}. A relation R is then a subset of the Cartesian product, R ⊂ A × B. In logic, relations are treated as interpretations of predicates. While a predicate is a syntactic concept, a relation is a semantic counterpart of the predicate. Awareness requires the capability of drawing conclusions , …
WebLogger: A Data Collection Tool for Web-use Studies

Considering the amount of interest in studying Webbrowsing behavior, there is a relative lack of tools for data collection in this area. Those tools that do exist have significant limitations on the data they are able to collect or on their suitability for efficient analysis. We present WebLogger, a tool which instruments Microsoft 's Internet Explorer Web browser. We have found that WebLogger alleviates some of the problems associated with other approaches to browser-based data collection methods.
Eigenviruses for metamorphic virus recognition

Metamorphic virus recognition is the most challenging task for antivirus software, because such viruses are the hardest to detect as they change their appearance and structure on each new infection. In this study, the authors present an effective system for metamorphic virus recognition based on statistical machine learning techniques. The authors approach has successfully scored high detection rate for tested metamorphic virus classes and very low false-positive errors. The system is also able to learn new patterns of viruses for future recognition. The authors conclude the results of their simulation with results analysis and future enhancements in the system to detect other virus classes.
A Model for the Emergence of a Twisted Magnetic Flux Tube

Observations have shown that active region flux tubes often emerge in a twisted state and that the active region formed has magnetic helicity of the same sense as the flux tube that forms it. Separate theoretical models have been developed for coronal magnetic fields with helicity and for flux tubes with twist. Here we present a dynamical model that connects a twisted subphotospheric flux tube to a force-free coronal field. With this model it is possible to explore the emergence of a flux tube into the corona and its effect on both the coronal field and the subphotospheric flux tube. In particular, the model shows that only a fraction of the current carried by the twisted flux tube will pass into the corona. As a consequence of this "mismatch," a torsional Alfvén wave is launched downward along the flux tube at the instant of emergence. As the flux tube continues to emerge, the helicity of the coronal field increases owing to rotation of the footpoints. Our model predicts that the level of rotation will depend upon the rapidity of flux emergence. After this transient period the helicity of the active region will reflect the twist in its parent tube.
The high-eccentricity asymmetric expansion of the disturbing function for non-planar resonant problems

In this paper we present an extension to the nonplanar case of the asymmetric expansion of the averaged resonant disturbing function of Ferraz-Mello & Sato (1989, A&A 225, 541-547). Comparions with the exact averaged disturbing function are also presented. The expansion gives a good approximation of the exact function in a wide region around the center of expansion.
Document classification using semantic networks with an adaptive similarity measure

We consider supervised document classification where a semantic network is used to augment document features with their hypernyms. A novel document representation is introduced in which the contribution of the hypernyms to document similarity is determined by semantic network edge weights. We argue that the optimal edge weights are not a static property of the semantic network, but should rather be adapted to the given classification task. To determine the optimal weights, we introduce an efficient gradient descent method driven by the misclassifications of the k-nearest neighbor (kNN) classifier. The method iteratively adjusts the weights, increasing or decreasing the similarity of documents depending on their classes. We thoroughly evaluate the method using ten randomly chosen datasets and seven training set sizes on the problem of classifying PubMed documents indexed with the MeSH biomedical ontology. Using the kNN classifier, the method is shown to statistically significantly outperform the commonly used bag-of-words representation as well as the more advanced hypernym density representation (Scott & Matwin 98).
Effect of pomiferin administration on kidney ischaemia-reperfusion injury in rats

Effect of pomiferin administration on kidney ischaemia-reperfusion injury in rats The aim of the study was to analyse protective effects of different doses of pomiferin in therapy of reperfusion injury. Rats were randomly divided into five groups (n=10). One group was intact. Three medicated groups and one placebo group were subjected to ischaemia and reperfusion of the left kidney. Pomiferin was administrated by single gastric gavage in 2 ml of 0.5% Avicel solution in doses of 5, 10 and 20 mg/kg. The placebo group was given only Avicel solution. On day 15, all the animals were exsanguinated and the reperfused kidneys were recovered. Selected biochemical markers were assessed in blood: antioxidative enzymes, total antioxidative capacity, malondialdehyde, creatinine, urea and uric acid. Creatinine, urea and total proteins were analysed in urine and 24-hour diuresis was recorded. The kidney tissue samples were used for histopathological examination. The results confirmed the expected protective effects of pomiferin. Pomiferin supported defensive reactions of the body against free radicals (increased levels of superoxide dismutase, total antioxidative capacity), decreased lipid peroxidation (decreased malondialdehyde) and contributed to the recovery of kidney functions (creatinine and urea in blood). The best biochemical and histopathological results were achieved after pomiferin administration in the dose of 5 mg/kg.
Online dense local 3D world reconstruction from stereo image sequences

This paper describes an online 3D reconstruction system from stereo image sequences to obtain a dense local world model for robot navigation. The proposed method consists of three components: 1) stereo depth map calculation, 2) correspondence calculation in time sequential images by tracking raw image features, 3) 6DOF camera motion estimation by RANSAC and integrate depth map into 3D reconstructed model. We examined and evaluated our method in a motion capture environment for comparison. Finally experimental results of a humanoid robot H7 are denoted.
Autonomic Mechanisms for Service Scaling in Wide-Area Shared Computing Environments 1

In this paper we present mechanisms and models for building autonomically scalable and resilient services in wide-area shared computing environments. Wide-area shared computing platforms as exemplified by PlanetLab provide a cooperatively shared pool of computing resources. Building services in such environments poses unique challenges due to the fluctuations in available resource capacities and node availability. Autonomic mechanisms for building scalable and resilient services in such environments need to appropriately scale the service capacity under fluctuating available resource capacities, node crashes, and fluctuations in client load. Towards addressing these issues, we have developed models and mechanisms for estimating the service capacity under varying available resource capacities through online micro-benchmarking. The mechanisms for autonomic scaling of service capacity perform dynamic replication and regeneration of service replicas based on the estimated service capacity and observed load. This requires selection of appropriate nodes for the placement of new replicas. Furthermore due to the fluctuations in resource capacities, the load distribution for such services need to adapt to the varying service capacities of the individual service replicas. For this purpose we develop mechanisms for adaptive load distribution. We present here the evaluation of these mechanisms through experiments conducted over the PlanetLab environment.
Use of Micronutrients Attenuates Cannabis and Nicotine Abuse as Evidenced From a Reversal Design: A Case Study

Abstract Prior research shows that micronutrients, particularly amino acids, can assist individuals with substance dependence to quit various drugs of abuse, including cannabis, alcohol, and cocaine. As part of a wider investigation of the impact of micronutrients (mostly vitamins and minerals) on psychiatric symptoms, such as Attention-Deficit/Hyperactivity Disorder (ADHD), depression, and anxiety, we observed that many participants reduced or eliminated use of alcohol, cigarettes, and cannabis. One case using a single-case reversal (off-on-off-on-off) design is presented and shows not only on-off control of psychiatric symptoms as micronutrients are consumed or withdrawn, but also simultaneous on-off use of cannabis and cigarettes, despite not directly targeting this substance use as part of the treatment protocol. This case adds to a growing body of research supporting the use of micronutrients in the treatment of psychiatric symptoms and suggests it may extend to substance dependence. Micronutrients, by assisting with mood regulation and reductions in anxiety, may assist with successful cessation of drug use. Alternatively, they may directly impact on the brain reward circuitry believed to be involved in the expression of addictions, thereby providing the appropriate precursors and cofactors necessary for adequate neurotransmitter synthesis. This case should continue to stimulate researchers to consider the role of nutrients, in particular vitamins and minerals, in drug treatment programs and encourage more rigorous trials.
Face recognition under varying illumination based on adaptive homomorphic eight local directional patterns

This study proposes an illumination-invariant face-recognition method called adaptive homomorphic eight local directional pattern (AH-ELDP). AH-ELDP first uses adaptive homomorphic filtering to reduce the influence of illumination from an input face image. It then applies an interpolative enhancement function to stretch the filtered image. Finally, it produces eight directional edge images using Kirsch compass masks and uses all the directional information to create an illumination-insensitive representation. The author's extensive experiments show that the AH-ELDP technique achieves the best face recognition accuracy of 99.45% for CMU-PIE face images, 96.67% for Yale B face images and 84.42% for Extended Yale B face images using one image per subject for training when compared to seven representative state-of-the-art techniques.
Dynamic Programming-based QBF Solving

Solving Quantiﬁed Boolean Formulas (QBFs) is a challenging problem due to its high complexity. Many successful methods have been proposed, including extensions of DPLL/CDCL procedures and expansion-based approaches. In this paper, we present a novel method that is inspired by concepts from the ﬁeld of parameterized complexity. More speciﬁcally, we develop a dynamic programming algorithm that traverses a tree decomposition of the QBF instance. We implemented our method using Binary Decision Diagrams as key ingredient to compactly represent the partial solutions computed during dynamic programming. Experiments indicate that our prototype shows promising results for instances with few quantiﬁer alternations and where the treewidth of the propositional formula does not exceed 50. In fact, treewidth can be understood as a measurement of structure within the formula, and to the best of our knowledge has not been used explicitly in QBF solvers yet.
Renormalization group and Fermi liquid theory

We give a Hamiltonian-based interpretation of microscopic Fermi liquid theory within a renormalization group framework. The Fermi liquid fixed-point Hamiltonian with its leading-order corrections is identified and we show that the mean field calculations for this model correspond to the Landau phenomenological approach. This is illustrated first of all for the Kondo and Anderson models of magnetic impurities which display Fermi liquid behaviour at low temperatures. We then show how these results can be deduced by a reorganization of perturbation theory, in close parallel to that for the renormalized Φ 4 field theory. The Fermi liquid results follow from the two lowest order diagrams of the renormalized perturbation expansion. The calculations for the impurity models are simpler than for the general case because the self-energy depends on frequency only. We show, however, that a similar renormalized expansion can be derived also for the case of a translationally invariant system. The parameters specifying the Fermi liquid fixed-point Hamiltonian are related to the renormalized vertices appearing in the perturbation theory. The collective zero sound modes appear in the quasiparticle-quasihole ladder sum of the renormalized perturbation expansion. The renormalized perturbation expansion can in principle be used beyond the Fermi liquid regime to higher temperatures. This approach should be particularly useful for heavy fermions and other strongly correlated electron systems, where the renormalization of the single-particle excitations are particularly large. We briefly look at the breakdown of Fermi liquid theory from a renormalized perturbation theory point of view. We show how a modified version of the approach can be used in some situations, such as the spinless Luttinger model, where Fermi liquid theory is not applicable. Other examples of systems where the Fermi liquid theory breaks down are also briefly discussed
Toxic Effect of Destruxin A on Abnormal Wing Disc-Like (SLAWD) in Spodoptera litura Fabricius (Lepidoptera: Noctuidae)

Background Destruxin A (DA) is a microbial insecticide with potent bioactivity against Spodoptera litura larvae. A previous proteomic analysis of S. litura (SL-1) cells exposed to DA showed the abnormal expression of wing disc-like protein of S. litura (SLAWD). To further understand the effect of DA on SLAWD expression, a functional study was carried out. Principal Findings The SLAWD gene (SLAWD) was cloned and an open reading frame of 537 bp encoding a polypeptide of 178 amino acids was detected. Real-time fluorescence quantitative PCR (qRT-PCR) suggested that SLAWD is expressed in all developmental stages of S. litura, but expression was highest during the pupal and adult stages. RNAi knockdown of SLAWD expression in 6th-stage larvae was achieved by the microinjection of a specific double-stranded RNA (dsRNA). The results showed a significant decrease in SLAWD mRNA expression levels between the prepupal and adult stages. Interestingly, SLAWD expression was similarly down-regulated by treating 6th-stage larvae with DA. Growth- and development-related statistics confirmed the observed abnormalities in S. litura development after either RNAi or DA treatment. Conclusions SLAWD appears to have a biosynthetic function in the pupal and adult stages of S. litura. The toxic effect of DA on S. litura development is due the negative effect of DA on SLAWD gene expression.
Extraction of incremental information using query evaluator

Information Extraction is an activity of examine text for information relevant to some interest. Information extraction needs depth analysis than simple key word searches. The information extraction system recognizes and extracts knowledge from a massive literature and extracted knowledge is accumulated in a knowledge base. Many conventional automatic information extraction approaches using Natural Language Processing and Text Mining technologies have been proposed to extract meaningful information automatically in biomedical realm. These conventional approaches have considerable pitfall that whenever a different extraction goal become visible or any component in system is upgraded, extraction has to be reapplied from beginning to the whole text collection although only a minor part of the text collection might be influenced. In this paper we have applied Stanford dependency grammar to furnish easy description of the grammatical relationships in a sentence. This work relates incremental information extraction approach in which extraction needs are exhibited in the form of database queries. This work aims that in the occasion of installation of a upgraded component, reduction in the processing time takes place as compared to a conventional approach.
Character Set Encoding Detection using a Support Vector Machine

I propose a method to automatically detect the character set encoding for an HTML text document using a Support Vector Machine. Using only the stream of bytes within the document, this algorithm learns the patterns of byte n-gram frequencies to classify the document. The algorithm will currently detect the following popular character set encodings: US-ASCII, UTF-8, UTF-16, ISO-88591, ISO-8859-2, ISO-8859-5, Big5, GB2312, GB18030, Shift-JIS, EUC-JP, EUCKR, KOI8-R.
Appendix I Quantitative Evaluation of Local Features

The main goal of our evaluation method of local features is to provide a clear and concise measure of the distinctiveness and the sensitivity of any local feature extractor. A straightforward way to quantitatively assess those properties is through the receiver operating characteristic (ROC) curve. In the literature, the only method that has the same goal is presented in [4], where the authors follow up on our own work [2]. In [4], they also use ROC curves to evaluate local descriptors, but the difference resides in that they use real image deformations as opposed to the artificial ones presented here. The use of real image deformations to quantitatively assess local image features is an important contribution since it provides a more accurate performance evaluation. However, we believe that there is not a significant discrepancy between the results shown in [3] and in [4]. Our quantitative evaluation utilizes a database of images [1], where is used to compute the sensitivity (or robustness) of local features, and the remaining 247 images are used to evaluate the expressiveness (or dis-tinctiveness) of local features. From the set we build the following set of " random " features with , which contains roughly features. On the other hand, each image is used to assess the robustness of the local feature extractor to the image deformations described in Appendix II. The set of features extracted from image is then given by with defined in Section III, while the set of features from its deformed version (using deformation) is represented by the set , with. Note that a fixed scale is used to extract the features from the deformed image , while the original image is processed at the set of scales. This is necessary to allow the evaluation method to measure the performance of the local feature in terms of scale changes. Given the eight types of image deformations described in Appendix II, the comparison is based on the ROC curves (see Fig. 1), where the true positive rate vs. false positive rate is computed for the local feature extractor. In order to define these rates, let be an interest point in an undeformed test image , and the transformation matrix and translation vector , from image locations in to , determined from deformation .
Temperature Effects on Biomass and Regeneration of Vegetation in a Geothermal Area

Understanding the effects of increasing temperature is central in explaining the effects of climate change on vegetation. Here, we investigate how warming affects vegetation regeneration and root biomass and if there is an interactive effect of warming with other environmental variables. We also examine if geothermal warming effects on vegetation regeneration and root biomass can be used in climate change experiments. Monitoring plots were arranged in a grid across the study area to cover a range of soil temperatures. The plots were cleared of vegetation and root-free ingrowth cores were installed to assess above and below-ground regeneration rates. Temperature sensors were buried in the plots for continued soil temperature monitoring. Soil moisture, pH, and soil chemistry of the plots were also recorded. Data were analyzed using least absolute shrinkage and selection operator and linear regression to identify the environmental variable with the greatest influence on vegetation regeneration and root biomass. There was lower root biomass and slower vegetation regeneration in high temperature plots. Soil temperature was positively correlated with soil moisture and negatively correlated with soil pH. Iron and sulfate were present in the soil in the highest quantities compared to other measured soil chemicals and had a strong positive relationship with soil temperature. Our findings suggest that soil temperature had a major impact on root biomass and vegetation regeneration. In geothermal fields, vegetation establishment and growth can be restricted by low soil moisture, low soil pH, and an imbalance in soil chemistry. The correlation between soil moisture, pH, chemistry, and plant regeneration was chiefly driven by soil temperature. Soil temperature was negatively correlated to the distance from the geothermal features. Apart from characterizing plant regeneration on geothermal soils, this study further demonstrates a novel approach to global warming experiments, which could be particularly useful in low heat flow geothermal systems that more realistically mimic soil warming.