Miracle-dz/UniFAR-FTUs huggingface dataset:
Effective Use of Phrases in Language Modeling to Improve Information Retrieval

Traditional information retrieval models treat the query as a bag of words, assuming that the occurrence of each query term is independent of the positions and occurrences of others. Several of these traditional models have been extended to incorporate positional information, most often through the inclusion of phrases. This has shown improvements in effectiveness on large, modern test collections. The language modeling approach to information retrieval is attractive because it provides a well-studied theoretical framework that has been successful in other fields. Incorporating positional information into language models is intuitive and has shown significant improvements in several language-modeling applications. However, attempts to integrate positional information into the language-modeling approach to IR have not shown consistent significant improvements. This paper provides a broader exploration of this problem. We apply the backoff technique to incorporate a bigram phrase language model with the traditional unigram one and compare its performance to an interpolation of a conditional bigram model with the unigram model. While this novel application of backoff does not improve effectiveness, we find that our formula for interpolating a conditional bigram model with the unigram model yields significantly different results from prior work. Namely, it shows an 11% relative improvement in average precision on one query set, while yielding no improvement on the other two.
Cutting the Long Tail: Hybrid Language Models for Translation Style Adaptation

In this paper, we address statistical machine translation of public conference talks. Modeling the style of this genre can be very challenging given the shortage of available in-domain training data. We investigate the use of a hybrid LM, where infrequent words are mapped into classes. Hybrid LMs are used to complement word-based LMs with statistics about the language style of the talks. Extensive experiments comparing different settings of the hybrid LM are reported on publicly available benchmarks based on TED talks, from Arabic to English and from English to French. The proposed models show to better exploit in-domain data than conventional word-based LMs for the target language modeling component of a phrase-based statistical machine translation system.
Efficient Resettably Secure Two-Party Computation

In 2000, Canetti, Goldreich, Goldwasser and Micali (STOC’00) proposed the notion of resettable zero-knowledge, which considers the scenario where a malicious verifier can reset the prover and force it to reuse its random tape. They provided a construction that resists such attacks, and in the following, the notion of resettability was considered in various other scenarios. Starting with resettably-sound zero-knowledge, over general resettable computation with one resettable party, to protocols where all parties are resettable. Most of these results are only concerned with the feasibility of resettable computation, while efficiency is secondary. There is a considerable gap in the roundand communication-efficiency between actively secure protocols and resettably secure protocols. Following the work of Goyal and Sahai (EUROCRYPT’09), we study the roundand communication-efficiency of resettable two-party computation in the setting where one of the two parties is resettable, and close the gap between the two notions of security: • We construct a fully simulatable resettable CRS in the plain model that directly yields constant-round resettable zero-knowledge and constant-round resettable two-party computation protocols in the plain model. • We present a new resettability compiler that follows the approach of Ishai, Prabhakaran and Sahai (CRYPTO’08) and yields constant-rate resettable two-party computation.
Demo: Interactive Visual Privacy Control with Gestures

Built-in cameras of mobile and wearable devices enable a variety of applications such as augmented reality, continuous sensing, and life-logging systems, which bring joy and convenience to human lives. However, being recorded by unauthorized or unnoticed cameras have raised people's concerns about visual privacy. To address this problem, we propose a novel interactive method to control visual privacy. We allow individuals to interact with cameras using static tags and more flexible hand gestures for privacy control. By delivering privacy control messages via visual indicators, devices will automatically perform control operations according to privacy indicators detected and control rules.
Efficient Arithmetic-Residue-Based SEU-Tolerant FIR Filter Design

Finite impulse response (FIR) filters are commonly used in many signal processing systems. In some cases, such as space systems, FIR filters are exposed to radiation sources that cause errors. A number of techniques can be used to protect against those errors. One of them is the use of an arithmetic residue replica of the FIR filter. This replica has a lower cost than the original filter and therefore reduces the overhead compared with replicating the filter. However, some errors may not be detected by the arithmetic residue replica. In this brief, schemes that avoid undetected errors are presented. The proposed techniques are implemented and evaluated showing that they can detect all single errors affecting register bits. The results also show that their implementation requires only a small overhead in circuit complexity for the existing residue-based fault-tolerant FIR filters.
Measuring effective capacity of IEEE 802.15.4 beaconless mode

IEEE 802.15. 4 is an emerging wireless standard addressing the needs of low-rate wireless personal area networks with a focus on enabling various pervasive and ubiquitous applications that require interactions with our surrounding environments. In view of the application potential of IEEE 802.15. 4, knowing the fundamental network properties soon becomes essential in fasten the interactivity between these devices. Among all, knowing effective capacity of a path in wireless networks is of particular importance in routing and traffic management. In this paper, we implement SenProbe, a recently proposed path capacity estimation tool specially designed for the multi-hop ad hoc wireless environment. We present an implementation of SenProbe in sensor operating system (SOS), and evaluate the behavior/effectiveness of SenProbe in various testbed setups; including an interfered setting that cannot be simulated. Experiment results validate the workings of SenProbe and offer insights into how the capacity of a wireless path changes in real wireless environments. Our efforts provide a basis for realistic results that can be of assistance in activities such as capacity planning, protocol design, performance analysis, and etc
Fault location in distribution systems based on analysis of voltage sags

Due to the complexity of distribution systems, fault location in distribution systems is still a challenging problem. Lateral lines, loads and sparse data give errors to fault location methods. This paper proposed an improved fault location method by using some voltage sag data in distribution systems. The main idea is to indicate a fault point by using the relationship between voltage sag and feeder impedance. By considering a real distribution system, the performance of the proposed method is evaluated. Various fault resistances are tested. The results show that fault point can be indicated effectively.
The long-term efficacy of three psychotherapies for anorexia nervosa: a randomized, controlled trial.

OBJECTIVE To evaluate the long-term efficacy of three psychotherapies for anorexia nervosa. METHOD Participants were women with broadly defined anorexia nervosa who had participated in a RCT comparing specialized psychotherapies (cognitive behavior therapy, CBT, and interpersonal psychotherapy, IPT) with a control condition (specialist supportive clinical management, SSCM), and attended long-term follow-up assessment (mean 6.7 years ± 1.2). RESULTS Forty three of the original sample of 56 women participated in long-term follow-up assessment (77%). No significant differences were found on any pre-selected primary, secondary or tertiary outcome measures among the three psychotherapies at long-term follow-up assessment. Significantly different patterns of recovery were identified for the psychotherapies across time on the primary global outcome measure. Although SSCM was associated with a more rapid response than IPT, by follow-up all three treatments were indistinguishable. DISCUSSION Potential implications for the timing of interventions to improve treatment response in anorexia nervosa are critically examined.
Continual monitoring of code quality

CQMM (Code Quality Monitoring Method) is a means for systematically monitoring and improving code level quality of a system during development. It employs goal directed monitoring using quality models and static code analysis tools. In this paper, we present the CQMM method, learnings gathered through pilot studies, and changes needed for its large scale adoption within our organization. This exercise was an important step towards evolving an organization wide common minimum baseline for code-centric quality. Initial results indicate that the process helps in exposing important code-centric issues, besides sensitizing developers to coding practices. We also demonstrate the usefulness of the approach by tracking code level issues on select open source projects.
Chemopreventive effect of sinapic acid on 1,2-dimethylhydrazine-induced experimental rat colon carcinogenesis

Sinapic acid (SA) is a naturally occurring phenolic acid found in various herbal plants which is attributed with numerous pharmacological properties. This study was aimed to investigate the chemopreventive effect of SA on 1,2-dimethylhydrazine (DMH)-induced rat colon carcinogenesis. Rats were treated with DMH injections (20 mg kg−1 bodyweight (b.w.) subcutaneously once a week for the first 4 consecutive weeks and SA (20, 40 and 80 mg kg−1 b.w.) post orally for 16 weeks. At the end of the 16-week experimental period, all the rats were killed, and the tissues were evaluated biochemically. Our results reveal that DMH alone treatment decreased the levels/activities of lipid peroxidation by-products such as thiobarbituric acid reactive substances, conjugated dienes and antioxidants such as superoxide dismutase, catalase, glutathione reductase, glutathione peroxidase and reduced glutathione in the intestine and colonic tissues which were reversed on supplementation with SA. Moreover, the activities of drug-metabolizing enzymes of phase I (cytochrome P450 and P4502E1) were enhanced and those of phase II (glutathione-S-transferase, DT-diaphorase and uridine diphosphate glucuronosyl transferase) were diminished in the liver and colonic mucosa of DMH alone-treated rats and were reversed on supplementation with SA. All the above changes were supported by the histopathological observations of the rat liver and colon. These findings suggest that SA at the dose of 40 mg kg−1 b.w. was the most effective dose against DMH-induced colon carcinogenesis, and thus, SA could be used as a potential chemopreventive agent.
Traffic Accident Analysis Using Machine Learning Paradigms

Engineers and researchers in the automobile industry have tried to design and build safer automobiles, but traffic accidents are unavoidable. Patterns involved in dangerous crashes could be detected if we develop accurate prediction models capable of automatic classification of type of injury severity of various traffic accidents. These behavioral and roadway accident patterns can be useful to develop traffic safety control policies. We believe that to obtain the greatest possible accident reduction effects with limited budgetary resources, it is important that measures be based on scientific and objective surveys of the causes of accidents and severity of injuries. This paper summarizes the performance of four machine learning paradigms applied to modeling the severity of injury that occurred during traffic accidents. We considered neural networks trained using hybrid learning approaches, support vector machines, decision trees and a concurrent hybrid model involving decision trees and neural networks. Experiment results reveal that among the machine learning paradigms considered the hybrid decision tree-neural network approach outperformed the individual approaches. Povzetek: Stirje pristopi strojnega ucenja so uporabljeni za preiskovanje zakonitosti poskodb v prometnih nesrecah.
PRIDE: new developments and new datasets

The PRIDE (http://www.ebi.ac.uk/pride) database of protein and peptide identifications was previously described in the NAR Database Special Edition in 2006. Since this publication, the volume of public data in the PRIDE relational database has increased by more than an order of magnitude. Several significant public datasets have been added, including identifications and processed mass spectra generated by the HUPO Brain Proteome Project and the HUPO Liver Proteome Project. The PRIDE software development team has made several significant changes and additions to the user interface and tool set associated with PRIDE. The focus of these changes has been to facilitate the submission process and to improve the mechanisms by which PRIDE can be queried. The PRIDE team has developed a Microsoft Excel workbook that allows the required data to be collated in a series of relatively simple spreadsheets, with automatic generation of PRIDE XML at the end of the process. The ability to query PRIDE has been augmented by the addition of a BioMart interface allowing complex queries to be constructed. Collaboration with groups outside the EBI has been fruitful in extending PRIDE, including an approach to encode iTRAQ quantitative data in PRIDE XML.
Classifying and quantifying certain phenomena effect

The goal of this paper is to create a hybrid system that will investigate possible stock market changes immediately after financial news article appear and how this information influences the stock market behavior in order to improve the profitability of a short or medium time period investment. We proposed a multi-agent system that uses text mining, information extraction, pattern recognition, sentiment analysis and a trust model. The system classifies and quantifies certain phenomena (financial news influence) in order to compute the effect of some properties and its size on the stock market and also checks if we can use turbulence to detect disasters. It also searches a correlation between the effect of news articles and the trader's behavior on the market. In order to validate our model a prototype was developed.
BP1 is a negative modulator of definitive erythropoiesis

Beta protein 1 (BP1), a human homeotic transcription factor, is expressed during hematopoeisis in the erythroid lineage. To determine the in vivo role of BP1 in erythropoiesis, we have undertaken two complementary approaches using enforced BP1 expression in both transgenic mice and embryonic stem (ES) cells. Despite repeated attempts, only one adult transgenic BP1 founder mouse among 121 mice was obtained. This mouse presumably survived due to transgene mosaicism because the transgene could not be transmitted. This mouse expressed BP1 and displayed splenomegaly, extramedullary erythropoiesis and severe amyloidosis A in the kidney, a phenotype compatible with thalassemia. Consistently, the presence of BP1 transgene in fetuses was associated with paleness and lethality. In ES cells, BP1 expression in primary differentiation appeared to antagonize adult β-globin expression. In secondary differentiation, BP1 expression reduced significantly β-globin gene expression in both primitive and definitive erythroid cells, whereas it impaired only the definitive erythroid cell differentiation. These studies showed that BP1 can negatively modulate adult β-globin gene expression and definitive erythroid cell differentiation, and suggest that BP1 could play a role in thalassemia.
Salient local 3D features for 3D shape retrieval

In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT). We use it to identify the salient keypoints (invariant points) on a 3D voxelized model and calculate invariant 3D local feature descriptors at these keypoints. We then use the bag of words approach on the 3D local features to represent the 3D models for shape retrieval. The advantages of the method are that it can be applied to rigid as well as to articulated and deformable 3D models. Finally, this approach is applied for 3D Shape Retrieval on the McGill articulated shape benchmark and then the retrieval results are presented and compared to other methods.
Genome Wide Association Study (GWAS) between Attention Deficit Hyperactivity Disorder (ADHD) and Obsessive Compulsive Disorder (OCD)

Objective: The aim of this study was to identify any potential genetic overlap between attention deficit hyperactivity disorder (ADHD) and obsessive compulsive disorder (OCD). We hypothesized that since these disorders share a sub-phenotype, they may share common risk alleles. In this manuscript, we report the overlap found between these two disorders. Methods: A meta-analysis was conducted between ADHD and OCD, and polygenic risk scores (PRS) were calculated for both disorders. In addition, a protein-protein analysis was completed in order to examine the interactions between proteins; p-values for the protein-protein interaction analysis was calculated using permutation. Conclusion: None of the single nucleotide polymorphisms (SNPs) reached genome wide significance and there was little evidence of genetic overlap between ADHD and OCD.
The Ethnographer as Community Manager: Language Translation and User Negotiation

This article investigates the ethnographic methodological question of how the researcher observes objectively while being part of the problem they are observing. It uses a case study of ABC Pool to argue a cooperative approach that combines the role of the ethnographer with that of a community manager who assists in constructing a true representation of the researched environment. By using reflexivity as a research tool, the ethnographer engages in a process to self-check their personal presumptions and prejudices, and to strengthen the constructed representation of the researched environment. This article also suggests combining management and expertise research from the social sciences with ethnography, to understand and engage with the research field participants more intimately – which, ultimately, assists in gathering and analysing richer qualitative data.
Scheduling trees using FIFO queues: a control-memory tradeoff

We study a combinatorial problem that is motivated by ‘(client-server” schedulers for networks of workstations. Using a number of FIFO quet~es the scheduler is required to schedule ~-leaf binary (or any fixed degree) trees in such a way that each nonleaf node of the tree being scheduled is executed before its children. We establish a tradeoff between the number of queues used by the algorithm — which we view as measuring the control complexity of the algorithm — and the memory requirements of the algorithm, as embodied in the required capacity of the largestcapacity queue. Let ~k (N) denote the minimax per-queue capacity for a k-queue algorithm that schedules all N-leaf binary trees, and let Q~ (N) denote the analogous quantity for complete binary trees. We establish the following bounds. For all N, k < log N,
Improving Sensitivity of Resonant Sensor Systems Through Strong Mechanical Coupling

This paper reports on the first use of strongly coupled microresonators to improve the sensitivity of resonant sensing systems. To date, the research on coupled resonant sensors has concentrated on weakly coupled systems, which rely on the measurement of signal amplitudes. Strongly coupled resonant sensor systems, on the other hand, provide a frequency-shift output that results in improved accuracy, precision, and dynamic range. A system model is developed to investigate the effect of perturbations on the eigenvalues of resonator arrays. The model is used to study the system sensitivity to perturbations as the coupling strength between the resonators is increased and demonstrates a multi-fold increase in sensitivity for strong coupling. The developed theory is employed to design strongly coupled resonant sensor systems. Proof-of-concept devices were fabricated in a custom microfabrication process that allowed for inclusion of piezoresistors on structural layers. Experimental results were used to validate the theoretical model and demonstrated an improvement of more than 20% in sensitivity with moderate coupling ratios. This paper lays the foundation for the design of strongly coupled resonant sensor systems for single or multiple measurands.
A Novel Intergenic ETnII-β Insertion Mutation Causes Multiple Malformations in Polypodia Mice

Mouse early transposon insertions are responsible for ∼10% of spontaneous mutant phenotypes. We previously reported the phenotypes and genetic mapping of Polypodia, (Ppd), a spontaneous, X-linked dominant mutation with profound effects on body plan morphogenesis. Our new data shows that mutant mice are not born in expected Mendelian ratios secondary to loss after E9.5. In addition, we refined the Ppd genetic interval and discovered a novel ETnII-β early transposon insertion between the genes for Dusp9 and Pnck. The ETn inserted 1.6 kb downstream and antisense to Dusp9 and does not disrupt polyadenylation or splicing of either gene. Knock-in mice engineered to carry the ETn display Ppd characteristic ectopic caudal limb phenotypes, showing that the ETn insertion is the Ppd molecular lesion. Early transposons are actively expressed in the early blastocyst. To explore the consequences of the ETn on the genomic landscape at an early stage of development, we compared interval gene expression between wild-type and mutant ES cells. Mutant ES cell expression analysis revealed marked upregulation of Dusp9 mRNA and protein expression. Evaluation of the 5′ LTR CpG methylation state in adult mice revealed no correlation with the occurrence or severity of Ppd phenotypes at birth. Thus, the broad range of phenotypes observed in this mutant is secondary to a novel intergenic ETn insertion whose effects include dysregulation of nearby interval gene expression at early stages of development.
Massive Parallelism on the Hybrid Text

The design of a high-performance, cost-eeective, machine for retrieving textual data is discussed in this paper. High performance and cost eeectiveness are achieved by a combination of low-cost hard disks, software ltering techniques, and a large amount of main memory. The discussion focuses on the signature processor, which is based on the partitioned signature le technique, and the mass storage system, which is based on a disk array. A performance evaluation on the individual system components, namely, the signature processor and the mass storage system, as well as the entire system is presented.
Clinical use of brain volumetry

Magnetic resonance imaging (MRI)‐based brain volumetry is increasingly being used in the clinical setting to assess brain volume changes from structural MR images in a range of neurologic conditions. Measures of brain volumes have been shown to be valid biomarkers of the clinical state and progression by offering high reliability and robust inferences on the underlying disease‐related mechanisms. This review critically examines the different scenarios of the application of MRI‐based brain volumetry in neurology: 1) supporting disease diagnosis, 2) understanding mechanisms and tracking clinical progression of disease, and 3) monitoring treatment effect. These aspects will be discussed in a wide range of neurologic conditions, with particular emphasis on Alzheimer's disease and multiple sclerosis. J. Magn. Reson. Imaging 2013;37:1–14. ©2012 Wiley Periodicals, Inc.