Miracle-dz/UniFAR-FTUs huggingface dataset:
Usefulness of quality click-through data for training

Modern Information Retrieval (IR) systems often employ document weighting models with many parameters that require to be appropriately set for effective retrieval performance. To obtain these parameter settings, quality training is usually required, where assessors have manually labelled the relevance of retrieved items for many queries. In this work, we examine the usefulness of high-quality click-through data for training an IR system, on searching the . gov vertical domain of the Web. We find that, compared to training using relevance judgements created using human assessors, the click-through trained settings are as good and occasionally better.
Contribution of free play towards physical activity guidelines for New Zealand primary school children aged 7–9 years

Objective The objectives of this study were to investigate children's physical activity patterns to gain comparisons between home and school and to determine whether the current physical activity guidelines of 60 min of moderate to vigorous physical activity (MVPA) daily were being met. Methods Participants were recruited from two New Zealand primary schools (60 children, mean age (SD) 8.3 (0.7) years). Physical activity was measured for seven consecutive days using Actigraph accelerometers. Total activity and average counts were determined for school playtime, after school and weekends. Differences between average counts for these intervals were compared using the t statistic. Time and percentage of time spent were categorised into the activity thresholds: sedentary (<100), light (101–299), moderate (3000–5200) and vigorous (>5200). Total activity for each day was also determined. Results No child met the recommended 60 min of MVPA daily during the investigation. Compared to school playtime, activity counts were lower by 36% (CI 25% to 45.5%, p<0.001, effect size (ES)=−1.29) after school, 50.1% (CI 37% to 60.5%, p<0.001, ES=−2.01) on Saturday and 57.4% (CI 46.3% to 66.3%, p<0.001, ES=−2.47) on Sunday. Mean results showed children spent 91–96% of their time engaged in light or sedentary activities. Even during school playtime, where the children were most active, only 8 of 80 min were spent engaged in MVPA. Conclusions This study found activity levels were considerably lower than the recommended guidelines, and children were more active during school playtime compared to after school and weekends.
Hybrid rectenna and monolithic integrated zero-bias microwave rectifier

In this study, we have developed a hybrid sensitive rectenna (rectifier + antenna) system at 2.45 GHz. To achieve this system, we have first optimized and validated a zero-bias microwave sensitive rectifier using commercial Schottky diodes. We have then optimized and achieved a 2times2 patch antenna array, which is associated to the microwave rectifier in order to validate the rectenna system, where an RF-dc conversion efficiency of 56% has been observed experimentally. In order to minimize the rectenna dimensions, we have conducted a study using the OMMIC ED02AH 0.20-mum GaAs pseudomorphic high electron-mobility transistor process to develop and achieve a monolithic rectifier at 2.45 GHz with RF-dc conversion efficiency of 65%
Hotplate-based monolithic CMOS microsystems for gas detection and material characterization for operating temperatures up to 500/spl deg/C

Two monolithic CMOS microsystems for gas detection and material characterization fabricated in industrial 0.8-/spl mu/m CMOS technology combined with post-CMOS micromachining are presented. The first microsystem comprises an array of three microhotplates, and three single-ended proportional temperature controllers (one controller per microhotplate), which regulate the microhotplate temperature up to 350/spl deg/C using a polysilicon resistor as a temperature sensor on the microhotplate. The second microsystem comprises one microhotplate, and a fully differential proportional temperature controller, which regulates the microhotplate temperature up to 500/spl deg/C using a platinum (Pt) resistor as a temperature sensor on the microhotplate. For gas sensing applications, the microhotplates were covered with tin dioxide (SnO/sub 2/), which changes its conductivity upon exposure to gaseous analytes. Gas tests evidenced a detection limit of 0.2 ppm for carbon monoxide (CO). For material characterization, the microhotplates were covered with ammonium nitrate (NH/sub 4/NO/sub 3/), which exhibits a melting point of 169.6/spl deg/C according to the CRC handbook of chemistry and physics. The measured melting point was 168/spl plusmn/2/spl deg/C. Temperature sensors, on- and off-membrane (near the circuitry), showed excellent thermal isolation between the heated membrane area and the circuitry area on the bulk chip (overall chip temperature rose by max 3/spl deg/C at 500/spl deg/C microhotplate temperature).
Advanced Machine Learning Practical 2 Solution : Manifold Learning + Clustering ( Spectral Clustering and Kernel K-Means ) Professor : Aude Billard Assistants :

During this week’s practical we will cover two more manifold learning algorithms, namely (i) Laplacian Eigenmaps and (ii) Isomaps, and compare their projections to kernel PCA. We will then perform Spectral Clustering, which involves applying K-means on the projections of these non-linear embeddings. Finally, we will evaluate the kernel K-Means algorithm, which clusters and extracts the non-linear embedding simultaneously.
Answering XML queries by means of data summaries

XML is a rather verbose representation of semistructured data, which may require huge amounts of storage space. We propose a summarized representation of XML data, based on the concept of instance pattern, which can both provide succinct information and be directly queried. The physical representation of instance patterns exploits itemsets or association rules to summarize the content of XML datasets. Instance patterns may be used for (possibly partially) answering queries, either when fast and approximate answers are required, or when the actual dataset is not available, for example, it is currently unreachable. Experiments on large XML documents show that instance patterns allow a significant reduction in storage space, while preserving almost entirely the completeness of the query result. Furthermore, they provide fast query answers and show good scalability on the size of the dataset, thus overcoming the document size limitation of most current XQuery engines.
Reranking for Biomedical Named-Entity Recognition

This paper investigates improvement of automatic biomedical named-entity recognition by applying a reranking method to the COLING 2004 JNLPBA shared task of bioentity recognition. Our system has a common reranking architecture that consists of a pipeline of two statistical classifiers which are based on log-linear models. The architecture enables the reranker to take advantage of features which are globally dependent on the label sequences, and features from the labels of other sentences than the target sentence. The experimental results show that our system achieves the labeling accuracies that are comparable to the best performance reported for the same task, thanks to the 1.55 points of F-score improvement by the reranker.
A Hybrid Congestion Control for TCP over High Speed Networks

Transmission Control Protocol (TCP) is a widely used end-to-end transport protocol in the Internet. However, the congestion control of standard TCP (Reno) functions poorly in high speed networks because of its slow response with large congestion windows. Therefore, standard TCP may become the performance bottleneck as the bandwidth of Internet continues to grow. in this paper, we propose a new variant of hybrid TCP, Concave Convex TCP (CCTCP), to overcome this issue. CCTCP revises Reno's congestion avoidance phase by appending delay-based features. through ns-2 based simulations we find that, as compared to other hybrid TCPs, CCTCP can achieve a high performance with minor dependence on bottleneck buffer sizes under a variety of network bandwidths, especially in high speed networks.
Multi-robot routing under limited communication range

Teams of mobile robots have been recently proposed as effective means of completing complex missions involving multiple tasks spatially distributed over a large area. A central problem in such domains is multi-robot routing, namely the problem of coordinating a team of robots in terms of the locations they should visit and the routes they should follow in order to accomplish their common mission. A typical assumption made in prior work on multi-robot routing is that robots are able to communicate uninterruptedly at all times independently of their locations. In this paper, we investigate the multi-robot routing problem under communication constraints, reflecting on the fact that real mobile robots have a limited range of communication and the requirement that connectivity must remain intact (even through relaying) during the entire mission. We propose four algorithms for this problem, all based on the same reactive framework, ranging from greedy to deliberative approaches. All algorithms are tested in various scenarios implemented using the Player-Stage robot simulation environment. Our results demonstrate that effective multi-robot routing can be achieved even under limited communication range with moderate loss compared to the case of infinite communication range.
Mineral and geochemical composition of the Onega Ice Lake sediments

An analysis of the mineral-geochemical composition and structure of the Holocene–Pleistocene bottom sediments was performed on Lake Polevskoye, a small lake in the northern Lake Onega area in Russian Karelia, which is considered representative to describe the Late Weichselian Onega Ice Lake sediments. The analysis was accomplished using modern analytical methods, including scanning electron microscopy and ICP-MS, which allowed us to interpret their genesis in a new light. It is assumed that the distribution of rare earth elements (REE) in the bottom sediments of the recent Lake Onega and in the sediments of Onega Ice Lake will improve our understanding of the history of sedimentogenesis. It is apparent in the distribution of REE, their composition and data on the geochemical and mineral composition of the Holocene bottom sediments of Lake Onega and Lake Polevskoye (varved clays) that in their composition of terrigenous matter the material introduced from the north-western part of the catchment area is mainly composed of Archaean and Early Proterozoic crystalline complexes. However, the values of several indicator ratios of elements in the lower part of the of varved clays with shungite interlayers indicate the presence of mixing of clastic material from two sources of different geochemical origin: the north-western part of the catchment area (source of shungite rocks) and the south-eastern part of the catchment area (Phanerozoic sedimentary rocks of the Russian Platform).
WINK: a Web-based system for collaborative project management in virtual enterprises

The increasing of globalization and flexibility required to the companies has generated, in the last decade, new issues, related to the managing of large scale projects within geographically distributed networks and to the cooperation of enterprises. ICT support systems are required to allow enterprises to share information, guarantee data-consistency and establish synchronized and collaborative processes. In this paper, we present a collaborative project management system that integrates data coming from aerospace industries with two main goals: avoiding inconsistencies generated by updates at the sources' level and minimizing data replications. The proposed system is composed of a collaborative project management component supported by a Web interface, a multiagent data integration component, which supports information sharing and querying, and SOAP enabled Web-services which ensure the whole interoperability of the software components. The system was developed by the University of Modena and Reggio Emilia, Gruppo Formula S.p.A. and Alenia Spazio S.p.A. within the EU WINK Project (Web-linked Integration of Network based Knowledge - IST-2000-28221).
Passive snubber energy recovery for a GTO thyristor inverter bridge leg

This paper presents a turn-on and turn-off passive energy recovery snubber circuit suitable for high-voltage high-power gate-turn-off thyristor inverter bridge configurations. The circuit recovers not only inductive turn-on and capacitive turn-off snubber energies, but also energies associated with freewheel diode reverse recovery. Energy is transferred back to the DC supply via a high-frequency transformer, that is fully reset. A method for reducing the transformer secondary diode voltage stress is presented. The performance of the circuit is supported by PSpice simulation, mathematical analysis, and practical results.
Organization of Partner Knowledge: Relationship Outcomes and Longitudinal Change

This study examined the association between organization of knowledge about a romantic partner (partner structure) and relationship status (ongoing or ended) 1 year later. Ironically, partner structures that were associated with more positive feelings about one’s partner at Time 1 were associated with greater rates of breakup by Time 2. These results are interpreted in terms of the vulnerability of compartmentalized partner structures to shifts in the salience of negative beliefs and the hypothesized difficulty of maintaining integrative structures for an extended period of time. Change in partner structure during 1 year’s time was consistent with the predictions of the dynamic model that evaluative integration should increase when negative beliefs become salient. Such change (which may represent a transient shift) was associated with couples’ longevity when relationship conflict was low, supporting the view that integration reflects a struggle with negative attributes that may or may not be successful.
MicroRNAome and Expression Profile of Developing Tooth Germ in Miniature Pigs

MicroRNAs (miRNAs) play important roles in the regulation of rodent tooth development, but little is known about their role in tooth development in large mammals. We identified 637 unique miRNA sequences in a large-scale screen for miRNA expression profiles in the developing lower deciduous molars of miniature pigs (Sus scrofa) using Illumina Solexa deep sequencing. These candidate miRNAs and another 105 known Sus scrofa miRNAs were included in the custom-designed microarray and used to analyze the miRNA expression profile in the bud, cap, early bell, and late bell stages of tooth development. Microarray analysis revealed 166 transcripts that were differentially expressed in the four stages. Bioinformatic analysis identified 18 key miRNAs, including let-7f, miR-128, miR-200b, and miR-200c, that might play key roles in tooth development. Taken together, our results not only identified the specific microRNAome and expression profile in developing lower deciduous molars of the miniature pig, but they also provided useful information for investigating the molecular mechanism of tooth development in the miniature pig.
Effectiveness of systematic monitoring of rheumatoid arthritis disease activity in daily practice: a multicentre, cluster randomised controlled trial

Objective: To test the efficacy of standardised monitoring using the disease activity index DAS28 versus usual care on disease modifying antirheumatic drug (DMARD) prescription and disease activity in rheumatoid arthritis. Methods: A 24 week cluster randomised trial. Rheumatology outpatient centres were randomised to systematic monitoring of disease activity using the DAS28 (12 centres, 205 patients) or usual care (12 centres, 179 patients). The aim for the DAS group was to reach a DAS28 score of ⩽3.2 by changes in DMARD treatment, at the discretion of the rheumatologist and the patient. Results: At baseline, disease activity was the same in both groups, with an overall mean (SD) DAS28 of 4.5 (1.2); 13% of the patients had a DAS28 of ⩽3.2. At 24 weeks, 31% of patients in the DAS group had a DAS28 ⩽3.2, while in the usual care centres this was 16% (p = 0.028). DMARDs were changed on average in 18% of visits in the DAS centres; in the 12 usual care centres they were changed on 8% of the visits (p = 0.013). The doses of methotrexate, sulfasalazine, and corticosteroids appeared to be higher in the DAS centres than in the usual care centres, but the differences were not significant. Conclusions: In daily practice, systematic monitoring of disease activity in rheumatoid arthritis may lead to more changes in DMARD treatment, resulting in a larger number of patients with low disease activity.
EFFECTS OF LOCAL PHASE ERRORS IN MULTI-LOOK SAR IMAGES

The synthetic aperture radar (SAR) is a widely used instrument for high-resolution imaging from aircraft or satellite platforms. In the paper, the problem of the defocusing of multi- look SAR images by uncompensated phase errors presented in the received data is analyzed. It is shown that the phase errors on a multi-look processing interval can be efiectively described in terms of local quadratic and local linear phase errors. Approximate analytical expressions are derived to describe the azimuth resolution degradation. Criteria for acceptable phase errors are given. The obtained results are verifled by numerical simulations. The approach is illustrated by two typical motion errors: slow de∞ections of a SAR platform trajectory from a reference ∞ight line and periodic trajectory deviations.
Identification of Hexon-Specific CD4 and CD8 T-Cell Epitopes for Vaccine and Immunotherapy

ABSTRACT Adenoviral infections in the immunocompromised host are associated with significant morbidity and mortality. Although the adoptive transfer of adenovirus-specific T cells may prevent and treat such infections, the T-cell immune response to the multiplicity of adenovirus serotypes and subspecies that infect humans has not been well characterized, impeding the development of such approaches. We have, therefore, analyzed the specificities of T-cell responses to the viral capsid hexon antigen, since this structure is highly conserved in human pathogens. We screened 25 human cytotoxic T-cell lines with adenovirus specificity to extensively characterize their responses to adenoviral hexon and to identify a panel of novel CD4+ and CD8+ T-cell epitopes. Using a peptide library spanning the entire sequence of the hexon protein, we confirmed the responsiveness of these cytotoxic T-cell lines to seven peptides described previously and also identified 33 new CD4- or CD8-restricted hexon epitopes. Importantly, the majority of these epitopes were shared among different adenovirus subspecies, suggesting that T cells with such specificities could recognize and be protective against multiple serotypes, simplifying the task of effective adoptive transfer or vaccine-based immunotherapy for treating infection by this virus.
Cyclosporine bioequivalence study: quantification using fluorescence polarization immunoassay (FPIA) and radioimmunoassay (RIA).

OBJECTIVE The aim of study was to compare the bioavailability of 2 cyclosporine capsule formulations (100 mg; Sigmasporin Microoral from Novaquímica Divisão Nature's Plus Farmacêutica Ltd., Brazil, as test formulation and Sandimmune Neoral from Novartis Biociências S.A., Brazil, as reference formulation) in 24 healthy male volunteers. METHODS The study was open, randomized, with a 2-period crossover, a 1-week washout interval between doses. Blood samples were obtained over a 12-hour interval after each oral administration of cyclosporine (2 capsules of 100 mg of each formulation). Cyclosporine blood concentrations were quantified using a fluorescence polarization immunoassay (FPIA) method provided by Abbott Axsym System and Cyclo-Trac SP. Whole-blood radioimmuoassay (RIA) kit was provided by DiaSorin. These assays provided concentration-time curves for cyclosporine in blood concentration from which the following pharmacokinetic parameters were obtained: AUC(last), AUC(inf), Cmax. RESULTS Geometric mean and 90% confidence intervals (CI) of Microoral/Neoral as percent ratios were 94.5% (90.8-98.4%) for AUC(last), 93.8% (89.7-98.1%) for AUC(inf), and 98.1% (94.5-101.8%) for Cmax when cyclosporine was determined using FPIA and 96.1% (91.9 to 100.6%) for AUC(last), 95.2% (90.2-100.5%) for AUC(inf), and 99.4% (96.4-102.4%) for Cmax using RIA. CONCLUSION Since the 90% CI for Cmax, AUC(last) and AUC(inf) ratio were within the 80-125% interval proposed by US-FDA, it is concluded that Sigmasporin Microoral 100 mg capsule formulation is bioequivalent to Sandimmune Neoral 100 mg capsule formulation with regard to both rate and the extent of absorption.
Adversarial Multi-task Learning for Text Classification

Neural network models have shown their promising opportunities for multi-task learning, which focus on learning the shared layers to extract the common and task-invariant features. However, in most existing approaches, the extracted shared features are prone to be contaminated by task-specific features or the noise brought by other tasks. In this paper, we propose an adversarial multi-task learning framework, alleviating the shared and private latent feature spaces from interfering with each other. We conduct extensive experiments on 16 different text classification tasks, which demonstrates the benefits of our approach. Besides, we show that the shared knowledge learned by our proposed model can be regarded as off-the-shelf knowledge and easily transferred to new tasks. The datasets of all 16 tasks are publicly available at http://nlp.fudan. edu.cn/data/.
Interpreting Natural Language Instructions Using Language, Vision, and Behavior

We define the problem of automatic instruction interpretation as follows. Given a natural language instruction, can we automatically predict what an instruction follower, such as a robot, should do in the environment to follow that instruction? Previous approaches to automatic instruction interpretation have required either extensive domain-dependent rule writing or extensive manually annotated corpora. This article presents a novel approach that leverages a large amount of unannotated, easy-to-collect data from humans interacting in a game-like environment. Our approach uses an automatic annotation phase based on artificial intelligence planning, for which two different annotation strategies are compared: one based on behavioral information and the other based on visibility information. The resulting annotations are used as training data for different automatic classifiers. This algorithm is based on the intuition that the problem of interpreting a situated instruction can be cast as a classification problem of choosing among the actions that are possible in the situation. Classification is done by combining language, vision, and behavior information. Our empirical analysis shows that machine learning classifiers achieve 77% accuracy on this task on available English corpora and 74% on similar German corpora. Finally, the inclusion of human feedback in the interpretation process is shown to boost performance to 92% for the English corpus and 90% for the German corpus.
Particle and salinity sensing for the marine environment via deep learning using a Raspberry Pi

The identification of mixtures of particles in a solution via analysis of scattered light can be a complex task, due to the multiple scattering effects between different sizes and types of particles. Deep learning offers the capability for solving complex problems without the need for a physical understanding of the underlying system, and hence offers an elegant solution. Here, we demonstrate the application of convolutional neural networks for the identification of the concentration of microparticles (silicon dioxide and melamine resin) and the solution salinity, directly from the scattered light. The measurements were carried out in real-time using a Raspberry Pi, light source, camera, and neural network computation, hence demonstrating a portable and low-cost environmental marine sensor.