Miracle-dz/UniFAR-FTUs huggingface dataset:
On Using Mobile Robotic Relays for Adaptive Communication in Search and Rescue Missions

This work addresses the problem of deploying and controlling mobile relays in robotic networks. We consider a general data collection scenario in which a group of robots stream data towards one or more base stations. The robots form a wireless mobile ad hoc network relaying data towards the base stations in a multi-hop fashion. Additional robots are used as mobile relays with the aim of optimizing overall network performance in terms of data throughput. To dynamically control the positions of these relays, we use the combination of a mathematical programming model that includes a number of constraints and penalties to closely model the wireless environment, and heuristics to account for variations in wireless links stability. We demonstrate that the approach is computationally affordable for reasonably sized networks. The approach is evaluated in realistic simulation scenarios, studying the impact of the model parameters on the quality of the provided solutions. An experimental validation is also carried out in a real testbed, confirming the efficacy of the proposed approach for adapting relays' positions to the changes in the robot network.
Cholinergic Augmentation Modulates Visual Task Performance in Sleep-Deprived Young Adults

Using 24 h of total sleep deprivation to perturb normal cognitive function, we conducted a double-blind, placebo-controlled crossover study to evaluate the effect of the acetylcholinesterase inhibitor, donepezil, on behavioral performance and task-related brain activation in 28 healthy, young, adult volunteers. The behavioral tasks involved the parametric manipulation of visual short-term memory load and perceptual load in separate experiments indirectly evaluating attention. Sleep deprivation significantly reduced posterior cortical activation (intraparietal sulcus and extrastriate cortex) at all levels of visual memory as well as perceptual load. Donepezil modulated an individual's performance in both tasks in accordance to whether accuracy declined after sleep deprivation without treatment. Critically, there were significant correlations between donepezil-induced increases in neural activation in the posterior cortical areas and improvement in accuracy. Reduced visual short-term memory after sleep deprivation may thus originate from a decline in visual attention and/or visual processing. Cholinergic augmentation can alleviate these deficits in individuals vulnerable to the effects of sleep deprivation, but it may have neutral or negative effects on those resistant to sleep deprivation.
Detecting cuts in sensor networks

We propose a low overhead scheme for detecting a network partition or cut in a sensor network. Consider a network S of n sensors, modeled as points in a two-dimensional plane. An /spl epsiv/-cut, for any 0</spl epsiv/<1, is a linear separation of /spl epsiv/n nodes in S from a distinguished node, the base station. We show that the base station can detect whenever an /spl epsiv/-cut occurs by monitoring the status of just O(1//spl epsiv/) nodes in the network. Our scheme is deterministic and it is free of false positives: no reported cut has size smaller than 1/2/spl epsiv/n. Besides this combinatorial result, we also propose efficient algorithms for finding the O(1//spl epsiv/) nodes that should act as sentinels, and report on our simulation results, comparing the sentinel algorithm with two natural schemes based on sampling.
The Effect of Marital Status on Home Ownership among Low-Income Households

This research examines whether married low-income renters are more likely to become home owners than comparable single, low-income renters. To do so, it employs data from the Community Advantage Panel Study and discrete-time survival analysis with propensity-score matching. Results suggest that married couples buy homes at higher rates, and buy them more quickly, than do their unmarried counterparts. Estimates in models that use propensity-score matching are robust to the control of selection bias between the married and the unmarried groups. The findings suggest that efforts to encourage marriage among low-income couples may be associated with subsequent economic mobility through home ownership.
Redesigning Geriatric Healthcare

Abstract This study examines the consequences of adding a geriatric subacute unit to the traditional health care mix offered by a nonprofit hospital. Historically, geriatric health care offerings have been limited to either acute care units or long-term care facilities. The study's findings demonstrate that the addition of a subacute unit that is operated by an interdisciplinary team is a competitively rational move for two reasons. First, it provides a continuum of care that integrates services and departments, thereby reducing costs. Second, it provides a supportive environment for patients and their families. As a consequence patients have a higher probability of returning home than patients who are assigned to more traditional modes of care.
A semi-supervised approach to question classification

This paper presents a machine learning approach to question classification. We have defined a kernel function based on latent semantic information acquired from unlabeled data. This kernel allows including external semantic knowledge into the supervised learning process. We have combined this knowledge with a bag-of-words approach by means of composite kernels to obtain state-of-the-art results. As the semantic information is acquired from unlabeled text, our system can be easily adapted to different languages and domains.
Bisecting K-Means for Clustering Web Log data

Web usage mining is the area of web mining which deals with extraction of useful knowledge from web log information produced by web servers. One of the most important tasks of Web Usage Mining (WUM) is web user clustering which forms groups of users exhibiting similar interests or similar browsing patterns. This paper presents results of clustering techniques for Web log data using K-means and Bisecting K-means algorithm. Clusters are formed with respect to similar IP address and packet combinations. The clustering framework is further used as an approach for intrusion detection from the log files. The system is trained first by labeling the classes and then tested to check for any intrusions. Recommendation output is generated which help in classifying the whether the input IP’s are “safe” or “infected”. Comparison of both algorithms is done and performance is evaluated with respect to time and accuracy. From the experimental results, it is found that Bisecting K-means overcomes the major drawbacks of basic K-means algorithm.
Padé approximants in linear repetitive learning controls for robotic manipulators

We present the use of [m, m]-Padé approximants in the implementation of repetitive learning controls for the asymptotic link position tracking in robotic manipulators with uncertain dynamics and periodic position reference signals (with known period). The resulting linear learning controllers are described by transfer functions exhibiting all their poles with negative real part. Analyses from both theoretical and experimental points of view are carried out.
Properties of a Cyclodextrin-specific, Unusual Porin from Klebsiella oxytoca *

The function of CymA, 1 of the 10 gene products involved in cyclodextrin uptake and metabolism by Klebsiella oxytoca, was characterized. CymA is essential for growth on cyclodextrins, but it can also complement the deficiency of alamB (maltoporin) mutant of Escherichia colifor growth on linear maltodextrins, indicating that both cyclic and linear oligosaccharides are accepted as substrates. CymA was overproduced in E. coli and purified to apparent homogeneity. CymA is a component of the outer membrane, is processed from a signal peptide-containing precursor, and possesses a high content of antiparallel β-sheet. Incorporation of CymA into lipid bilayers and conductance measurements revealed that it forms ion-permeable channels, which exhibit a substantial current noise. CymA-induced membrane conductance decreased considerably upon addition of α-cyclodextrin. Titration experiments allowed the calculation of a half-saturation constant,KS , of 28 μm for its binding to CymA. CymA assembled in vitro to two-dimensionally crystalline tubular membranes, which, on electron microscopy, are characterized by a p1-related two-sided plane group. The crystallographic unit cell contains four monomeric CymA molecules showing a central pore. The lattice parameters are a = 16.1 nm, b = 3.8 nm, γ = 93°. CymA does not form trimeric complexes in lipid membranes and shows no tendency to trimerize in solution. CymA thus is an atypical porin with novel properties specialized to transfer cyclodextrins across the outer membrane.
Assessment of Quality of Ti Alloys Melted in Induction Furnace with Ceramic Crucible

In this work, the possibility of melting titanium alloys in vacuum induction furnaces in metal and ceramic crucibles and in ceramic crucibles with coatings deposited by the plasma-spray method or by hand using a brush was evaluated. The effect of the crucible material and the coating material on the chemical composition, microstructure and alloy properties was studied. The main criterion for evaluating the suitability of individual crucibles was the content of oxygen in the molten alloys and of impurities remaining as a result of the reaction of the liquid alloy with the crucible and coating material.
New Method for Automatic and Precise Edge Extraction from Slimi Images

Slimi is a kind of schemes made of arcs that was ripped in Islamic Era. All of the Slimi curves have inside vectors and outside vectors. Theses vectors are essence of Slimi and are the sign of infinity and eternity. Slimi is a design including of beautiful rounds and these rounds will be completed with appropriate subsets. Slimi is one of the seven Iranian traditional paintings. In extraction of schemes boundaries from Slimi images, we were faced to edge extraction. The problem was quality of images that were taken by typical cameras and images had inseparable amount of noises. Noise affectedthe boundaries between regions and so edge detection methods did not work very well. In this article, we developed a region-based segmentation method for region boundary extraction. We used Level Set Method to extract every kind of schemes region and to eliminate of noises. After using proposed method on test images, a comparison between this method and usual methods for edge extraction was done in this research. Results showed that the proposed method had a higher completeness and precision in comparison to edge detection methods like Canny Method.
Exploring the adoption of online discussion forums for knowledge sharing and social relations among virtual communities

This paper investigates the adoption and use of online discussion forums by Sudanese virtual communities located in different places in the world. For this purpose, an extended Technology Acceptance Model (TAM) is proposed to analyze the users' adoption of online discussion forums for sharing knowledge and social relations. A survey questionnaire is administered to the users of Sudanese-Online.com: one popular online Sudanese discussion forum. Results from preliminary analysis show that social influence and online social skills influence users' acceptance of online discussion forums for social relations and knowledge sharing.
On the performance of vehicular communications with a measurement-based radio propagation model

The choice of channel propagation model used for the simulation-based study of Vehicular Ad hoc NETworks (VANETs) plays a key role in the accuracy of conclusions drawn about the performance of applications proposed for these networks. Relying on simplistic channel models, as frequently practised in previous works, leads either to pessimistic or optimistic conclusions. In the view of this, in this paper, we use a realistic measurement-based channel model, implement it in OMNet++ simulator, construct a traffic scenario representing the basic building block of urban traffic networks, and investigate the performance of VANETs in terms of packet reception ratio (PRR). We further compare the performance of VANET under this measurement-based model with two more simplistic channel models used by the practitioners of the existing network simulation tools. Our results show that, for the most part of the simulated scenario, the PRR performance is significantly worse in the measurement-based channel model compared to the PRRs achieved with the simplistic models. However, there is an exception that, in close distances from an intersection and when the sender-receiver pairs are situated on different roads, the measurement-based model leads to better PRR performance.
Automatic, action driven classification of problem solving strategies by statistical and analytical methods : a comparative study

We have recorded the behaviour of several users solving the same tasks with an interactive database program and were able to identify several distinct strategies. Since the number of users exceeds the number of strategies, multiple users will have a strategy in common. Our aim was to find groups of users sharing the same strategy. Following each of the three methods (correlation, intersection, and exclusion) we define a metric among task solving sequences. For multiple users, we represent these measures by a matrix system, in order to find groups of users with common behaviour. Direct interpretation or multi dimensional scaling of such matrices indicates distinct user groups. The common denominator for each group can be interpreted as a strategy. A few distinctive solution strategies were found to exist.
Nasal Septal Cross-Over Flap Technique: A Choanal Atresia Micro-Endoscopic Surgical Repair

Choanal atresia is a congenital malformation of the posterior portion of the nasal cavity, which is usually unilateral. The incidence is estimated to be 1 in 5,000 to 8,000 live births. Several surgical approaches have been described to correct choanal atresia since Emmert's initial trocar perforation in 1853, including transnasal, transpalatal, transseptal, sublabial transseptal, transantral, and external rhinoplasty. Although the micro-endoscopic transnasal access is a more conservative technique, it allows greater surgical precision, and is currently recommended by many authors; choanal atresia repair is still considered a challenge, with risks of intraoperative and postoperative complications and re-stenosis. This paper reports the results of a series of 33 patients operated via the transnasal micro-endoscopic surgical approach, and describes a new endoscopic technique that the authors call “nasal septal cross-over flap technique. ”
Raman nanometrology of graphene on arbitrary substrates and at variable temperature

The unique properties of graphene have recently attracted major attention leading to proposals in electronic, optoelectronic, and detector applications. Micro-Raman spectroscopy has been utilized as a convenient tool for identifying graphene layers. Most Raman studies were limited to layers on silicon substrates with an oxide layer thickness of 300 nm, rendering graphene visible under an optical microscope. The development of graphene technology requires its integration with different materials and strict control of the number of layers and defects. Thus it is important to extend the nanometrology capabilities of Raman spectroscopy to arbitrary substrates and temperatures. Here we report that the deconvolution of the 2D band allows one to count graphene layers even when placed on "inconvenient" substrates such as glass or sapphire. We also show that even small excitation laser power typically used for Raman spectroscopy may lead to strong heating in graphene. The determined temperature coefficients for graphene allowed us to evaluate the temperature rise and decouple the temperature effects from those due to variations in the graphene edges or substrates.
Dependence of flashover voltage on the chemical composition of multi-component insulator surface contaminants

The withstand strength of contaminated insulators under practical field conditions depends on the type and distribution of contaminants as well as their conductivity. In this paper, the authors have investigated the dependence of flashover voltage on the chemical composition of multicomponent contaminants and have proposed a unique method to relate the flashover voltage to the types of salts present. Although the distribution of contaminants on the surface plays a significant role in the flashover, it was found that no one portion of the insulator tends to predominate in importance and the uniform contamination distribution yields the minimum flashover voltage.
Comparison of generality based algorithm variants for automatic taxonomy generation

We compare a family of algorithms for the automatic generation of taxonomies by adapting the Heymann-algorithm in various ways. The core algorithm determines the generality of terms and iteratively inserts them in a growing taxonomy. Variants of the algorithm are created by altering the way and the frequency, generality of terms is calculated. We analyse the performance and the complexity of the variants combined with a systematic threshold evaluation on a set of seven manually created benchmark sets. As a result, betweenness centrality calculated on unweighted similarity graphs often performs best but requires threshold fine-tuning and is computationally more expensive than closeness centrality. Finally, we show how an entropy-based filter can lead to more precise taxonomies.
Computational Methods to Interpret and Integrate Metabolomic Data

Revolutionary improvements in high-throughput DNA sequencing technologies have made it possible to measure gene, mRNA, proteins and metabolites, as well as their interaction at global level. In the past decades, significant efforts in improving analytical technologies pertaining to measuring mRNA, proteins and metabolites have been made. These efforts have led to the generation of several new ‘omics’ research fields: transcriptomics, proteomics, metabolomics, interactomics and so on (Singh & Nagaraj, 2006; Fiehn 2007; Lin & Qian, 2007; Kandpal et al., 2009; Ishii & Tomita, 2009). Among them, metabolomics is an approach to obtain a comprehensive evaluation of metabolites in cells. Compared with transcriptomics and proteomics approaches, metabolomics can achieve large-scale quantitative and qualitative measurements of cellular metabolites, which can thus generate a high-resolution biochemical and functional information of an organism.
ASOBEK at SemEval-2016 Task 1: Sentence Representation with Character N-gram Embeddings for Semantic Textual Similarity

A growing body of research has recently been conducted on semantic textual similarity using a variety of neural network models. While re- cent research focuses on word-based represen- tation for phrases, sentences and even paragraphs, this study considers an alternative approach based on character n-grams. We generate embeddings for character n-grams using a continuous-bag-of-n-grams neural network model. Three different sentence rep- resentations based on n-gram embeddings are considered. Results are reported for experi- ments with bigram, trigram and 4-gram em- beddings on the STS Core dataset for SemEval-2016 Task 1.
Using query logs and click data to create improved document descriptions

Logfiles of search engines are a promising resource for data mining, since they provide raw data associated to users and web documents. In this paper we focus on the latter aspect and explore how the information in logfiles could be used to improve document descriptions. A pilot experiment demonstrated that document descriptors extracted from the queries that are associated with documents by clicks provide useful semantic information about documents in addition to document descriptors extracted from the full text of the web pages.
Integration of linked data sources for gazetteer expansion

The determination of the geographic scope of documents is important for many applications in geographic information retrieval (GIR). Many techniques require the use of gazetteers as a source of reference data. However, creating and maintaining gazetteers is still a complex and demanding task. We propose using linked data sources to put together gazetteer data that can be both broad (e.g. planetary) and deep (e.g., down to urban detail). Linked data sources also allow enriching the resulting gazetteer with a set of geographic and semantic relationships involving place names and other geographic and non-geographic terms, thus expanding the possibilities for solving typical GIR problems such as disambiguation and filtering. This work shows the results of efforts to combine two linked data sources of gazetteer data, namely GeoNames and DBPedia, to populate an integrated and semantically-enriched gazetteer. We used evidence contained in attributes, such as Wikipedia URLs, Linked Data predicates that indicate that places in both sources are the same, and some additional criteria. The resulting gazetteer contains 8,729,833 places, of which 426;317 are found in both data sources. This relatively small overlap is analyzed, indicating that GeoNames and DBPedia are complementary, covering typically different classes of places, thus leading to the idea that further expansion can be achieved by integrating gazetteer data from additional Linked Data sources.
Quantum Circuit Complexity

We propose a complexity model of quantum circuits analogous to the standard (acyclic) Boolean circuit model. It is shown that any function computable in polynomial time by a quantum Turing machine has a polynomial-size quantum circuit. This result also enables us to construct a universal quantum computer which can simulate, with a polynomial factor slowdown, a broader class of quantum machines than that considered by E. Bernstein and U. Vazirani (1993), thus answering an open question raised by them. We also develop a theory of quantum communication complexity, and use it as a tool to prove that the majority function does not have a linear-size quantum formula. >
The low level of understanding of depression among patients treated with antidepressants: a survey of 424 outpatients in Japan

Background We used self-administered questionnaires to investigate the level of understanding of depression among outpatients who were administered antidepressants. Methods A total of 424 outpatients were enrolled in this study. We used an original self-administered questionnaire that consisted of eight categories: (A) depressive symptoms, (B) the course of depression, (C) the cause of depression, (D) the treatment plan, (E) the duration of taking antidepressants, (F) how to discontinue antidepressants, (G) the side effects of the antidepressants, and (H) psychotherapy. Each category consisted of the following two questions: “Have you received an explanation from the doctor in charge? ” and “How much do you understand about it? ” The level of understanding was rated on a scale of 0–10 (11 anchor points). The Quick Inventory of Depressive Symptomatology Japanese version, Global Assessment of Functioning, and Clinical Global Impression – Severity scale were administered, and clinical characteristics were investigated. Results The percentages of participants who received explanations were as follows: 61.8% for (A), 49.2% for (B), 50.8% for (C), 57.2% for (D), 46.3% for (E), 28.5% for (F), 50.6% for (G), and 36.1% for (H). The level of understanding in participants who received explanations from their physicians was significantly higher compared with patients who did not receive explanations for all evaluated categories. Patient age, age at disease onset, and Global Assessment of Functioning scores were significantly associated with more items compared with the other variables. Conclusion Psychoeducation is not sufficiently performed. According to the study results, it is possible for patients to receive better psychoeducation and improve their clinical outcomes.