Miracle-dz/UniFAR-FTUs huggingface dataset:
ESTIMATION OF THE DEGREE OF SIMILARITY OF SENTENCES IN A NATURAL LANGUAGE BASED ON USING THE LINK GRAMMAR PARSER PROGRAM SYSTEM

Our main goal is to construct the algorithms that can estimate the document relevance on the basis of the text structure analysis. It is important that this estimate should be based on the context of the search query and not limited only by keywords, their similarity or frequency. The semantic-syntactical relations between words built by the program system Link Grammar Parser (developed in Carnegie Mellon University, USA) can be used to solve these problems. They allow us to develop the methods of comparison of the sentences in a natural language and introduce certain measures of the closeness (similarity) between the sentences. These measures take into account both lexical and syntactic relations between words. Experiments with different types of sentences and links took almost one year. It was observed that there is no need to use too many links. First, the use of some links leads us to the analysis of diagrams which correspond badly to intuition and principles of classical linguistics, and it is not clear what we can do with them further. Second, there is also a complexity aspect. If there are fewer links, the algorithm works faster. Therefore, a compromise is necessary. The minimum variant giving good results is when only eight connectors (links) are used. One of the problems we solve in the current time is the development of a parser like Link Grammar Parser for Turkic languages most frequent in the Internet, such as Kazakh, Uzbek (Cyrillic and Roman alphabets), and Turkish. The results of our research are planned to be used in different information retrieval systems.
Recommendation for a Routing Architecture

It is commonly recognized that the Internet routing and addressing architecture is facing challenges in scalability, multihoming, and inter-domain traffic engineering. This document presents, as a recommendation of future directions for the IETF, solutions that could aid the future scalability of the Internet. To this end, this document surveys many of the proposals that were brought forward for discussion in this activity, as well as some of the subsequent analysis and the architectural recommendation of the chairs. This document is a product of the Routing Research Group. This document is not an Internet Standards Track specification; it is published for informational purposes.
Therapeutic Options for Sleep‐Maintenance and Sleep‐Onset Insomnia

Insomnia, defined as difficulty falling asleep, staying asleep, and/or experiencing restorative sleep with associated impairment or significant distress, is a common condition resulting in significant clinical and economic consequences. Many options are available to treat insomnia, to assist with either falling asleep (sleep onset) or maintaining sleep. We searched MEDLINE for articles published between January 1996 and January 2006, evaluated abstracts from recent professional meetings, and contacted the manufacturer of the most recent addition to the pharmacologic armamentarium for insomnia treatment (ramelteon) to gather information. Nonpharmacologic options include stimulus control, sleep hygiene education, sleep restriction, paradoxical intention, relaxation therapy, biofeedback, and cognitive behavioral therapy. Prescription and over‐the‐counter drug therapies include benzodiazepine and nonbenzodiazepine sedative‐hypnotic agents; ramelteon, a melatonin receptor agonist; trazodone; and sedating antihistamines. Herbal and alternative preparations include melatonin and valerian. Before recommending any treatment, clinicians should consider patient‐specific criteria such as age, medical history, and other drug use, as well as the underlying cause of the sleep disturbance. All pharmacotherapy should be used with appropriate caution, at minimum effective doses, and for minimum duration of time.
Order Optimization of Evolutionary Hypernetworks Using Genetic Algorithm

Hyper networks consist of a large number of hyper edges that represent high-order features sampled from training sets. The order of hyper edges is an important parameter of a hyper network model and influences the performance of the hyper network classification system. Previous studies determine the parameter by the artificial exhaustive search method before evolutionary learning. Not only is the approach time-consuming, but also the traditional hyper network lacks generalization. In this study, a genetic algorithm is employed to optimize the order of hyper networks. The proposed method is tested on the acute leukemia and the colon cancer dataset. Experimental results show that the proposed approach can find the global optimal order automatically. Also, a comparative study on five classification algorithms shows that the improved hyper network model achieves a comparable classification performance.
Learning to tag

Social tagging provides valuable and crucial information for large-scale web image retrieval. It is ontology-free and easy to obtain; however, irrelevant tags frequently appear, and users typically will not tag all semantic objects in the image, which is also called semantic loss. To avoid noises and compensate for the semantic loss, tag recommendation is proposed in literature. However, current recommendation simply ranks the related tags based on the single modality of tag co-occurrence on the whole dataset, which ignores other modalities, such as visual correlation. This paper proposes a multi-modality recommendation based on both tag and visual correlation, and formulates the tag recommendation as a learning problem. Each modality is used to generate a ranking feature, and Rankboost algorithm is applied to learn an optimal combination of these ranking features from different modalities. Experiments on Flickr data demonstrate the effectiveness of this learning-based multi-modality recommendation strategy.
The Experiences of Security Industry Contractors Working in Iraq: An Interpretative Phenomenological Analysis

Objective: To explore the occupational experiences of private security contractors working in a war zone and how it impacts on their mental health. Methods: Semistructured interviews were conducted with seven contractors employed by a large UK-based private security company. Interpretative phenomenological analysis was used to analyze the interview transcripts. Participants also completed the 12-item General Health Questionnaire and the Posttraumatic Stress Disorder Checklist. Results: Four overarching themes emerged: the appeal of the job; vulnerability; keep going; and seeking help for stress in the workplace. No clinically significant levels of distress were reported. Conclusions: Contractors are frequently exposed to stressors known to increase risk of psychiatric difficulty in military personnel. A number of potential protective factors were identified. Only a minority of participants were open to seeking help for mental health difficulties.
Renewable energy-fed switched reluctance motor for PV pump applications

A photovoltaic (PV)-sourced switched reluctance motor (SRM) system based on maximum power point tracking (MPPT) control is proposed in this paper. The power flow between PV array, storage battery and SRM can be achieved by using only one power converter. There are four operational modes of the new energy SRM system as the PV-only motor drive mode, the battery-only motor drive mode, the battery charging mode and the hybrid motor drive mode. By controlling the duty cycle of the switching devices, the constant voltage tracking (CVT) of the PV array in the hybrid mode can be realized, which enables the maximum power point tracking of the PV array and the output power control of the SRM. The proposed topology and control strategy are validated by the simulation and experimental results, which shows great potentials for many industrial pump applications.
Mechanism of Suppression of Protein Aggregation by α-Crystallin

This review summarizes experimental data illuminating the mechanism of suppression of heat-induced protein aggregation by α-crystallin, one of the small heat shock proteins. The dynamic light scattering data show that the initial stage of thermal aggregation of proteins is the formation of the initial aggregates involving hundreds of molecules of the denatured protein. Further sticking of the starting aggregates proceeds in a regime of diffusion-limited cluster-cluster aggregation. The protective effect of α-crystallin is due to transition of the aggregation process to the regime of reaction-limited cluster-cluster aggregation, wherein the sticking probability for the colliding particles becomes lower than unity.
Image Interpretation Using Appraisal Analysis

In geophysical inversion, a significant effort is invested to obtain images of the Earth from finite data. The first step is to obtain an image i.e. solve the inverse problem. This step alone provides significant challenges that are not addressed in this paper. The next step is to interpret the image in terms of specific questions. For example, what can we say about the average value of a physical property within a certain region of the model? What scale information can we resolve from the data? These questions are problem dependent and may require that inversion be carried out several times to arrive at a satisfactory answer. Therefore the solution to an inverse problem is only a step towards answering these questions. Appraisal analysis of the solution takes the next step by providing a set of tools to judge and select from the possibly infinite suite of images that adequately fit our observations. We discuss the use of point spread functions and averaging kernels in the interpretation of images. We use a controlled source electromagnetic example to demonstrate the methodology.
Fourier–Mukai transforms for coherent systems on elliptic curves

We determine all the Fourier–Mukai transforms for coherent systems consisting of a vector bundle over an elliptic curve and a subspace of its global sections, showing that these transforms are indexed by positive integers. We prove that the natural stability condition for coherent systems, which depends on a parameter, is preserved by these transforms for small and large values of the parameter. By means of the Fourier–Mukai transforms we prove that certain moduli spaces of coherent systems corresponding to small and large values of the parameter are isomorphic. Using these results we draw some conclusions about the possible birational type of the moduli spaces. We prove that for a given degree d of the vector bundle and a given dimension of the subspace of its global sections there are at most d different possible birational types for the moduli spaces.
Changes in soil physical and hydrological properties due to Bromus tectorum (cheatgrass) invasion

Changes In Soil Physical and Hydrological Properties Due to Bromus Tectorum (cheatgrass) Invasion by Joshua J. Boxell Dr. Patrick Drohan, Examination Committee Chair Pine Lake Institute for Environmental and Sustainability Studies Hartwick College, Oneonta, New York Introduction of Bromus tectorum (cheatgrass) into western rangelands has had a profound effect on the diversity and health of native ecosystems. Introduced in the late 19th century, B. tectorum has rapidly out-competed native species and colonized large areas of the Great Basin region (Mack, 1981). The objective of this research is to assess changes in soil physical and hydrologie properties on former tridentata sites now invaded by B. tectorum and to quantify the scope of the alterations through time. Study site selection was based upon a range o f A. tridentata stand replacing fire histories spanning approximately 20 years and subsequent colonization of each fire site by B. tectorum. Fire sites sam pled w ere invaded by B. tectorum fo llow in g a single fire event; the earliest plot was burned in 1985 with subsequent sites having fires in 1987, 1998, and 2002. Sites characterized by^L tridentata, and not burned, were sampled as controls. To assess soil physical and hydrological properties measures o f aggregate stability; hydrophobicity;
Evidence That Synaptically Released β-Amyloid Accumulates as Extracellular Deposits in the Hippocampus of Transgenic Mice

A neuropathological hallmark of Alzheimer's disease is the deposition of amyloid-β (Aβ) peptides in senile plaques in the hippocampus and cerebral cortex. Aβ is derived from larger integral membrane proteins termed amyloid precursor proteins (APP). We demonstrated previously that APP, synthesized by neurons in the entorhinal cortex, is transported via the perforant pathway to presynaptic terminals in the dentate gyrus. We reported that, although full-length APP and membrane-tethered, C-terminal APP derivatives (APP-CTFs) accumulate at terminal fields, the production of Aβ peptides at these sites was indeterminate. To test the hypothesis that APP-CTFs, generated from axonally transported APP, are further metabolized to Aβ peptides that are subsequently released and deposited proximal to nerve terminals, we created unilateral knife lesions of the perforant pathway of transgenic mice that exhibit hippocampal amyloid deposits. We observed pronounced reductions in amyloid burden in the ipsilateral dentate gyrus, findings that lead us to conclude that axonally transported APP gives rise to Aβ peptides that are released from presynaptic sites in the dentate gyrus and deposited in extracellular plaques. Moreover, our findings are consistent with the view that Aβ deposits are dynamic structures and that the perforant path lesion alters the equilibrium between Aβ production–deposition toward clearance as a consequence of blocked axonal transport of APP from the entorhinal cortex to terminal fields in the hippocampus.
Base-specific spin-labeling of RNA for structure determination

To facilitate the measurement of intramolecular distances in solvated RNA systems, a combination of spin-labeling, electron paramagnetic resonance (EPR), and molecular dynamics (MD) simulation is presented. The fairly rigid spin label 2,2,5,5-tetramethyl-pyrrolin-1-yloxyl-3-acetylene (TPA) was base and site specifically introduced into RNA through a Sonogashira palladium catalyzed cross-coupling on column. For this purpose 5-iodo-uridine, 5-iodo-cytidine and 2-iodo-adenosine phosphoramidites were synthesized and incorporated into RNA-sequences. Application of the recently developed ACE® chemistry presented the main advantage to limit the reduction of the nitroxide to an amine during the oligonucleotide automated synthesis and thus to increase substantially the reliability of the synthesis and the yield of labeled oligonucleotides. 4-Pulse Electron Double Resonance (PELDOR) was then successfully used to measure the intramolecular spin–spin distances in six doubly labeled RNA-duplexes. Comparison of these results with our previous work on DNA showed that A- and B-Form can be differentiated. Using an all-atom force field with explicit solvent, MD simulations gave results in good agreement with the measured distances and indicated that the RNA A-Form was conserved despite a local destabilization effect of the nitroxide label. The applicability of the method to more complex biological systems is discussed.
Social, Structured and Semantic Search

Social content such as blogs, tweets, news etc. is a rich source of interconnected information. We identify a set of requirements for the meaningful exploitation of such rich content, and present a new data model, called S3, which is the first to satisfy them. S3 captures social relationships between users, and between users and content, but also the structure present in rich social content, as well as its semantics. We provide the first top-k keyword search algorithm taking into account the social, structured, and semantic dimensions and formally establish its termination and correctness. Experiments on real social networks demonstrate the efficiency and qualitative advantage of our algorithm through the joint exploitation of the social, structured, and semantic dimensions of S3.
A novel approach to part-of-speech tagging based on latent analogy

Part-of-speech tagging is a necessary pre-processing step for many natural language tasks. Recent statistical approaches, such as conditional random fields, rely on well chosen feature functions to ensure that important characteristics of the empirical training distribution are reflected in the trained model. In practice, however, it is not always clear how to best select these feature functions in order to obtain a suitably robust model. This paper proposes an alternative strategy based on the principle of latent analogy. For each sentence under consideration, we construct a neighborhood of globally relevant training sentences through an appropriate data-driven mapping of the input surface form. Tagging then proceeds via locally optimal sequence alignment and maximum likelihood position scoring. Empirical evidence shows that this solution is competitive with state-of-the-art Markovian techniques.
Capture pursuit games on unbounded domains

We introduce simple tools from geometric convexity to analyze capturetype (or “Lion and Man”) pursuit problems in unbounded domains. The main result is a necessary and sufficient condition for eventual capture in equal-speed discrete-time multi-pursuer capture games on convex Euclidean domains of arbitrary dimension and shape. This condition is presented in terms of recession sets in unit tangent spheres. The chief difficulties lie in utilizing the boundary of the domain as a constraint on the evader’s escape route. We also show that these convex-geometric techniques provide sufficient criteria for pursuit problems in non-convex domains with a convex decomposition.
HIPERLAN/2 for vehicle-to-vehicle communication

The objective of the IST project MIND (Mobile IP based network developments) is to facilitate IP-based broadband services for mobile users in various operating environments. Activities within MIND concentrate on the development, optimisation and harmonisation of the appropriate layers involved. The physical (PHY) layer was chosen to base on the high performance radio local area network type 2 standard (HIPERLAN/2). The work presented here demonstrates the applicability of HIPERLAN/2 to scenarios with increased mobility. Initially, HIPERLAN/2 was designed for rather static environments providing hot spot data rates of up to 54 Mbps. Mitigation techniques to overcome the drawbacks of a fast fading environment are thus studied within IST-MIND. The extracted transceiver structures allow the deployment of HIPERLAN/2 in almost any environments currently envisaged. Particularly, the system deployment of HIPERLAN/2 to a vehicle-to-vehicle communication scenario is studied and preliminary system level performance results presented.
A Quantitative Model of Capabilities in Multi-Agent Systems

Reasoning about capabilities in multi-agent systems is crucial for many applications. There are two aspects of reasoning about the capabilities of an agent to achieve its goals. One is the symbolic, logical reasoning, which is based on whether the agent can determine a plan that can be used to achieve a goal (i.e. “know-how”). Another is quantitative reasoning about levels of skill and whether a set of tasks can be achieved within a specified time and with quality constraints. Capabilities in this sense are determined by the limits of internal processing capacity. Both artificial agents and human agents can be subject to processing capacity limits, whether due to CPU speed, or cognitive limits on attention, memory, etc. This could depend not only on the unique skill levels of each individual and their cognitive abilities, but also on their ability to handle those task demands in parallel, given intrinsic limits on internal cognitive resource capacities. In past work, researchers have focused primarily on the logical aspect of capability reasoning; less work has been done on modeling the quantitative aspects of reasoning about capabilities in agents. In this paper, we introduce a general mathematical model to define the capabilities of agents to achieve a set of tasks. Our definitions of capabilities are based on whether a feasible schedule exists to complete the tasks within the constraints, either in static environments or dynamic environments, for which we present two corresponding preliminary scheduling algorithms. We illustrate this model with two experiments to evaluate the algorithms. We conclude by discussing the potential applications of this model, and future work.
POTRA: a framework for building power models for next generation multicore architectures

Ramon Bertran Barcelona Supercomputing Center C. Jordi Girona 1-3 08034 Barcelona, Spain ramon.bertran@bsc.es Marc Gonzalez Universitat Politecnica de Catalunya C. Jordi Girona 1-3 08034 Barcelona, Spain marc@ac.upc. edu Xavier Martorell Barcelona Supercomputing Center C. Jordi Girona 1-3 08034 Barcelona, Spain xavier.martorell@bsc.es Nacho Navarro Barcelona Supercomputing Center C. Jordi Girona 1-3 08034 Barcelona, Spain nacho.navarro@bsc.es Eduard Ayguade Barcelona Supercomputing Center C. Jordi Girona 1-3 08034 Barcelona, Spain eduard.ayguade@bsc.es
Comments on "Pruning Error Minimization in Least Squares Support Vector Machines"

In this letter, we comment on "Pruning Error Minimization in Least Squares Support Vector Machines" by B. J. de Kruif and T. J. A. de Vries. The original paper proposes a way of pruning training examples for least squares support vector machines (LS SVM) using no regularization (-gamma = infinity). This causes a problem as the derivation involves inverting a matrix that is often singular. We discuss a modification of this algorithm that prunes with regularization (gamma finite and nonzero) and is also computationally more efficient.
Application of a usage profile in software quality models

Faults discovered by customers are an important aspect of software quality. The working hypothesis of this paper is that variables derived from an execution profile can be useful in software quality models. An execution profile of a software system consists of the probability of execution of each module during operations. Execution represents opportunities for customers to discover faults. However, an execution profile over an entire customer-base can be difficult to measure directly. Deployment records of past releases can be a valuable source of data for calculating an approximation to the probability of execution. We analyze a metric derived from deployment records which is a practical surrogate for an execution profile in the context of a software quality model. We define usage as the proportion of systems in the field which have a module deployed. We present a case study of a very large legacy telecommunications system. We developed models using a standard statistical technique to predict whether software modules will have any faults discovered by customers on systems in the field. Static software product metrics and usage were independent variables. The significance levels of variables in logistic regression models were analyzed, and models with and without usage as an independent variable were compared. The case study was empirical evidence that usage can be a significant contributor to a software quality model.