Miracle-dz/UniFAR-FTUs huggingface dataset:
A levelwise spectral co-clustering algorithm for collaborative filtering

Collaborative Filtering (CF) is a widely used approach in recommendation systems that predicts user preferences by learning from user-item ratings. To extract either user relationship or item dependencies, there exists several well known approaches; among them clustering is of great importance. Inspired by this understanding, this paper presents a novel levelwise paradigm whose first level clusters users and items separately using their pair wise similarity. Once the primary clusters of first level formed, the second level, does the simultaneously clustering user and item clusters by the means of Co-clustering. The main advantages of our approach include: First, it is able to alleviate the well known notion of sparsity problem intrinsically exists in CF. Second, the proposed method offers an elegant dimensionality reduction what in turn leads to better performance. Third experimental results on Movielens dataset have demonstrated that the proposed method can effectively reveal the subset aggregates of users and items which are closely related.
Taking Advantage of Within-Die Delay-Variation to Reduce Cache Leakage Power Using Additional Cache-Ways

Leakage power, especially in cache memories, is dominating total power consumption of processor-based embedded systems. By choosing a higher threshold voltage, SRAM leakage can be exponentially reduced in return for lower speed. Since SRAM cells in the same cache have different delays in nanometer technologies due to within-die process variation, not all of the cells violate the cache delay. However, since timing-violating cells are randomly distributed over the cache, row/column redundancies are inefficient. We propose to add extra cache-way(s) to replace slow cache-lines separately in each cache-set. In a commercial 90nm process, our technique can reduce leakage power by up to 54% which, depending on the share of leakage in total cache power, translates to 25.36% and 53.37% reduction of total energy respectively in L1 and L2 cache by adding two spare ways to a 4-way set-associative cache with no performance penalty.
Tree Plantation Systems Influence Nitrogen Retention and the Abundance of Nitrogen Functional Genes in the Solomon Islands

Tree mono-plantations are susceptible to soil nutrient impoverishment and mixed species plantations have been proposed as a way of maintaining soil fertility while enhancing biodiversity. In the Solomon Islands, mixed species plantations where teak (Tectona grandis) is inter-planted with a local tree species (Flueggea flexuosa) have been used as an alternative to teak mono-plantations and are expected to increase soil microbial diversity and modify microbial biogeochemical processes. In this study, we quantified the abundance of microbial functional genes involved in the nitrogen (N) cycle from soil samples collected in teak, flueggea, and mixed species plantations. Furthermore, we measured soil properties such as pH, total carbon (C) and total N, stable N isotope composition (δ15N), and inorganic N pools. Soil pH and δ15N were higher under teak than under flueggea, which indicates that intercropping teak with flueggea may decrease bacterial activities and potential N losses. Higher C:N ratios were found under mixed species plantations than those under teak, suggesting an enhancement of N immobilization that would help preventing fast N losses. However, inorganic N pools remained unaffected by plant cover. Inter-planting teak with flueggea in mixed species plantations generally increased the relative abundance of denitrification genes and promoted the enrichment of nosZ-harboring denitrifiers. However, it reduced the abundance of bacterial amoA (ammonia monooxygenase) genes compared to teak mono-plantations. The abundance of most denitrification genes correlated with soil total N and C:N ratio, while bacterial and archeal nitrification genes correlated positively with soil NH4+ concentrations. Altogether, these results show that the abundance of bacterial N-cycling functional guilds vary under teak and under mixed species plantations, and that inter-planting teak with flueggea may potentially alleviate N losses associated with nitrification and denitrification and favor N retention. Mixed plantations could also allow an increase in soil C and N stocks without losing the source of income that teak trees represent for local communities.
Formalizing a strong normalization proof for Moggi's computational metalanguage: a case study in Isabelle/HOL-nominal

Lindley and Stark have given an elegant proof of strong normalization for various lambda calculi whose type systems preclude a direct inductive definition of Girard-Tait style logical relations, such as the simply typed lambda calculus with sum types or Moggi's calculus with monadic computation types. The key construction in their proof is a notion of relational TT-lifting, which is expressed with the help of stacks of evaluation contexts. We describe a formalization of Lindley and Stark's strong normalization proof for Moggi's computational metalanguage in Isabelle/HOL, using the nominal package.
SECTra_w.1: an Online Collaborative System for Evaluating, Post-editing and Presenting MT Translation Corpora

SECTra_w is a web-oriented system mainly dedicated to the evaluation of MT systems. After importing a source corpus, and possibly reference translations, one can call various MT systems, store their results, and have a collection of human judges perform subjective evaluation online (fluidity, adequacy). It is also possible to perform objective, task-oriented evaluation by letting humans post-edit the MT results, using a web translation editor, and measuring an edit distance and/or the post-editing time. The post-edited results can be added to the set of reference translations, or constitute it if there were no references. SECTra_w makes it possible to show not only tables of figures as results of an evaluation campaign, but also the real data (source, MT outputs, references, post-edited outputs), and to make the post-edition effort sensible by transforming the trace of the edit distance computation in an intuitive presentation, much like a revision presentation in Word. The system is written in java under Xwiki and uses the Ajax technique. It can handle large, multilingual and multimedia corpora: EuroParl, BTEC, ERIM (bilingual interpreted dialogues with audio and text), Unesco-B@bel, and a test corpus by France Telecom have been loaded together and used in tests.
QoE-Aware Computing Resource Allocation for CDN-as-a-Service Provision

We focus on the provision of Content-Delivery-Network-as-a- Service (CDNaaS) functionality for video distribution and, in particular, on how to appropriately decide on the amount of computing resources to allocate to a CDNaaS instance to satisfy Quality of Experience (QoE) and resource capacity constraints. Our work is put in the context of a telco cloud environment, which is open for content providers to request the dynamic deployment of a virtual CDN infrastructure on top of it, to cover a target user demand with a desired service quality at the regions where the telecom operator has presence. We perform extensive testbed experiments to quantify the dependence of user experience on the load of a virtualized video service, and apply our measurement results to drive a QoE-aware virtual CPU resource allocation algorithm. Using simulation, we show our algorithm to optimally address the quality-cost tradeoff, demonstrating the benefits of QoE-awareness.
Determinants of Exclusive Breastfeeding and Introduction of Complementary foods in Rural Egyptian Communities

Background: Determinants of breastfeeding (BF) exclusivity at a rural Egyptian setting are largely unknown. This cross-sectional study aimed to assess BF indicators, specifically exclusivity and the timely complementary feeding while assessing potential determinants that affect exclusivity of BF among a sample of mothers inhabiting Egyptian rural communities. Methods: A community based cross-sectional study was carried out over a period of four months with inclusion of 1000 eligible women having infants aged less than two years through a multi-stage random sampling method. Personal interview, using structured questionnaire, to collect information on socio-demographic characteristics, antenatal care services, women’s lactation practices, complementary feeding practices and knowledge about BF. Results: All the included mothers had breastfed their infants, and 32.4% of them initiated BF within the first hour of life and 29.9% exclusively breastfed their infants for 6 months after birth. Complementary feeding was introduced for children aged 6-9 months in 63.6% of them. Bivariate analysis showed that factors favoring exclusive BF were age of the mother (<25 years), with secondary or higher education, number of children, with no history of complicated pregnancy or lactation problems, received health education about BF and having knowledge about BF. Logistic regression model showed that most influential significant predictor for exclusive BF was receiving of health education about BF and adequate knowledge of BF. Conclusions: Although all rural Egyptian mothers included, initiated BF, the rate of its exclusivity was low. Comprehensive education about BF during pregnancy is strongly needed to promote BF among them.
Randomized Sketching for Large-Scale Sparse Ridge Regression Problems

We present a fast randomized ridge regression solver for sparse overdetermined matrices in distributed-memory platforms. Our solver is based on the Blendenpik algorithm, but employs sparse random projection schemes to construct a sketch of the input matrix. These sparse random projection sketching schemes, and in particular the use of the Randomized Sparsity-Preserving Transform, enable our algorithm to scale the distributed memory vanilla implementation of Blendenpik and provide up to × 13 speedup over a state-of-the-art parallel Cholesky-like sparse-direct solver.
Cache-oblivious wavefront: improving parallelism of recursive dynamic programming algorithms without losing cache-efficiency

State-of-the-art cache-oblivious parallel algorithms for dynamic programming (DP) problems usually guarantee asymptotically optimal cache performance without any tuning of cache parameters, but they often fail to exploit the theoretically best parallelism at the same time. While these algorithms achieve cache-optimality through the use of a recursive divide-and-conquer (DAC) strategy, scheduling tasks at the granularity of task dependency introduces artificial dependencies in addition to those arising from the defining recurrence equations. We removed the artificial dependency by scheduling tasks ready for execution as soon as all its real dependency constraints are satisfied, while preserving the cache-optimality by inheriting the DAC strategy. We applied our approach to a set of widely known dynamic programming problems, such as Floyd-Warshall's All-Pairs Shortest Paths, Stencil, and LCS. Theoretical analyses show that our techniques improve the span of 2-way DAC-based Floyd Warshall's algorithm on an $n$ node graph from $Thn^2n$ to $Thn$, stencil computations on a $d$-dimensional hypercubic grid of width $w$ for $h$ time steps from $Th(d^2 h) w^ (d+2) - 1$ to $Thh$, and LCS on two sequences of length $n$ each from $Thn^_2 3$ to $Thn$. In each case, the total work and cache complexity remain asymptotically optimal. Experimental measurements exhibit a $3$ - $5$ times improvement in absolute running time, $10$ - $20$ times improvement in burdened span by Cilkview, and approximately the same L1/L2 cache misses by PAPI.
Speckle Denoising Based on Bivariate Shrinkage Functions and Dual-tree Complex Wavelet Transform

Bivariate shrinkage functions (bsf) statistically denoted as joint probability density functions (pdf) and noise pdf, can be united by MAP to denoise image. Because the intensity of speckle in synthetic aperture radar (SAR) image is hypothesized to be distributed according to Rayleigh distribution, SAR image denoising modal based on bsf and dual-tree complex wavelet transform (DT-CWT) is constructed and reduced. Local variance estimation and wiener filter are used to estimate noise variance and noisy wavelet coefficients variance respectively, and they are used to choose an appreciated threshold to denoise SAR image. Experiment results demonstrate that PSNR and ENL values of denoised images are extremely larger than the speckle denoising algorithms based on discrete wavelet transform (DWT) and edge features have been perfectly preserved.
Service Robots Dealing with Indirect Speech Acts

Successful interaction between a service robot and its human users depends on the robot's ability to understand not only direct commands, but also more indirect ways for a human to express what she would like the robot to do. Such indirect ways are pervasive in human-human interaction; enabling the robot to understand them can make human-robot interaction more human-friendly. This paper presents a model for a robot that pursues its serving duties by trying to interpret indirect ways of expressing requests to execute certain actions. In case of uncertainty about the proper interpretation the robot can ask for clarification and adapt its interpretation for future interactions
The role of the interactome in the maintenance of deleterious variability in human populations

Recent genomic projects have revealed the existence of an unexpectedly large amount of deleterious variability in the human genome. Several hypotheses have been proposed to explain such an apparently high mutational load. However, the mechanisms by which deleterious mutations in some genes cause a pathological effect but are apparently innocuous in other genes remain largely unknown. This study searched for deleterious variants in the 1,000 genomes populations, as well as in a newly sequenced population of 252 healthy Spanish individuals. In addition, variants causative of monogenic diseases and somatic variants from 41 chronic lymphocytic leukaemia patients were analysed. The deleterious variants found were analysed in the context of the interactome to understand the role of network topology in the maintenance of the observed mutational load. Our results suggest that one of the mechanisms whereby the effect of these deleterious variants on the phenotype is suppressed could be related to the configuration of the protein interaction network. Most of the deleterious variants observed in healthy individuals are concentrated in peripheral regions of the interactome, in combinations that preserve their connectivity, and have a marginal effect on interactome integrity. On the contrary, likely pathogenic cancer somatic deleterious variants tend to occur in internal regions of the interactome, often with associated structural consequences. Finally, variants causative of monogenic diseases seem to occupy an intermediate position. Our observations suggest that the real pathological potential of a variant might be more a systems property rather than an intrinsic property of individual proteins.
Uptake of HLA Alloantigens via CD89 and CD206 Does Not Enhance Antigen Presentation by Indirect Allorecognition

In organ transplantation, alloantigens are taken up by antigen presenting cells and presented via the indirect pathway to T-cells which in turn can induce allograft rejection. Monitoring of these T-cells is of major importance; however no reliable assay is available to routinely monitor indirect allorecognition. Recently we showed that HLA monomers can be successfully used to monitor indirect allorecognition. Targeting antigens to endocytic receptors on antigen presenting cells may further enhance the presentation of antigens via HLA class II and improve the efficiency of this assay. In the current study we explored targeting of HLA monomers to either CD89 expressing monocytes or mannose receptor expressing dendritic cells. Monomer-antibody complexes were generated using biotin-labeled monomers and avidin labeling of the antibodies. We demonstrate that targeting the complexes to these receptors resulted in a dose-dependent HLA class II mediated presentation to a T-cell clone. The immune-complexes were efficiently taken up and presented to T-cells. However, the level of T-cell reactivity was similar to that when only exogenous antigen was added. We conclude that HLA-A2 monomers targeted for presentation through CD89 on monocytes or mannose receptor on dendritic cells lead to proper antigen presentation but do not enhance indirect allorecognition via HLA-DR.
Effect of V/III ratios on surface morphology in a GaSb thin film grown on GaAs substrate by MOCVD

The epitaxial growth of GaSb thin film with different V/III ratios on high-lattice-mismatched GaAs (001) substrates by metal organic chemical vapor deposition (MOCVD) was investigated. Under optimal V/III ratio of 2.5, we found that there are many periodic 90° interfacial misfit dislocation (IMF) arrays existing at the GaAs/GaSb interface. The surface roughness is about 3.6nm, 2.2nm, 3.8nm, respectively while different V/III ratios (1.25, 2.5, 5) were adopted. These results demonstrated that the hill-and valley structure on the surface of GaSb/GaAs heterostructure can be effectively improved, and formed smooth surface morphology.
Hippocampal plasticity and corticosterone : from dendrites to behavior

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HSV color space based segmentation of region of interest in satellite images

In this paper, a new method for the extraction of the necessary object or region from the satellite image is proposed. This color based method is based on HSV color space and histogram threshold. Usually the multispectral images received from satellite are in RGB color space. But human eye is more sensitive to intensity than color information (hue or saturation). In the proposed approach, the satellite image in RGB color space is transformed into HSV color space and then the transformed satellite image is split into three different components (channels or images) based on intensity and color. This HSV color space is designed to approximate the human vision. In the next step, the histogram for all three components (hue, saturation and value) is computed and plotted. Then the threshold value is separately applied to all three components. Finally the morphological operations like masking, filtering, smoothening is performed for the extraction of the desired region. The effectiveness of the proposed approach has been demonstrated by number of experiments. Experimental result demonstrates that the proposed method is more efficient in the extraction and segmentation of a desired object or region in the satellite images.
Sparse Channel Estimation and Equalization for OFDM-Based Underwater Cooperative Systems With Amplify-and-Forward Relaying

This paper is concerned with a challenging problem of channel estimation and equalization for amplify-and-forward cooperative relay based orthogonal frequency division multiplexing (OFDM) systems in sparse underwater acoustic (UWA) channels. The sparseness of the channel impulse response and prior information for the non-Gaussian channel gains, modeled by an exact continuous Gaussian mixture (CGM), are exploited to improve the performance of the channel estimation algorithm. The resulting novel algorithm initially estimates the overall sparse complex-valued channel taps from the source to the destination as well as their locations using the matching pursuit (MP) approach. The effective time-domain non-Gaussian noise is approximated well as a Gaussian noise in the frequency-domain, where the estimation takes place. An efficient and low complexity algorithm is developed based on a combination of the MP and the maximum a posteriori probability (MAP) based space-alternating generalized expectation-maximization technique, to improve the estimates of the channel taps and their locations in an iterative manner. Computer simulations show that the UWA channel is estimated very effectively and the proposed algorithm exhibits excellent symbol error rate and channel estimation performance.
The Role of Information Retrieval in Answering Complex Questions

This paper explores the role of information retrieval in answering "relationship" questions, a new class complex information needs formally introduced in TREC 2005. Since information retrieval is often an integral component of many question answering strategies, it is important to understand the impact of different term-based techniques. Within a framework of sentence retrieval, we examine three factors that contribute to question answering performance: the use of different retrieval engines, relevance (both at the document and sentence level), and redundancy. Results point out the limitations of purely term-based methods to this challenging task. Nevertheless, IR-based techniques provide a strong baseline on top of which more sophisticated language processing techniques can be deployed.
When Prefetching Works, When It Doesn’t, and Why

In emerging and future high-end processor systems, tolerating increasing cache miss latency and properly managing memory bandwidth will be critical to achieving high performance. Prefetching, in both hardware and software, is among our most important available techniques for doing so; yet, we claim that prefetching is perhaps also the least well-understood. Thus, the goal of this study is to develop a novel, foundational understanding of both the benefits and limitations of hardware and software prefetching. Our study includes: source code-level analysis, to help in understanding the practical strengths and weaknesses of compiler- and software-based prefetching; a study of the synergistic and antagonistic effects between software and hardware prefetching; and an evaluation of hardware prefetching training policies in the presence of software prefetching requests. We use both simulation and measurement on real systems. We find, for instance, that although there are many opportunities for compilers to prefetch much more aggressively than they currently do, there is also a tangible risk of interference with training existing hardware prefetching mechanisms. Taken together, our observations suggest new research directions for cooperative hardware/software prefetching.
Visualizing Blogsphere Using Content Based Clusters

Lots of people now have their own blogs or they publish comments, news in a public blog, even some companies publish their own blogs in order to introduce the services and products. However, there are many potential relationships inside the blogsphere. In this paper, we propose a novel method to cluster and visualize blogs to give a clear view of the blogsphere, and also provide an easy way to explore it. Using this method, people could easily find the interested blogs and can maintain the mental map when searching certain blog pages. Compare to other graph display for blogs, our approach can identify different groups based on topics, such as star, movie and music, also we give an interface to navigate the blogs. The method could also be applied to other areas, for instance social network, paper co-citation.