Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward improving Agile Mantema: Measurement, control and evaluation of maintenance projects in SMEs

An increasing adoption of agile methodologies in small organizations dedicated to software development and maintenance is a reality. An agile methodology oriented to the context of maintenance and allows the adoption of a quality model is necessary. This methodology must consider the capabilities and characteristics of small software organizations and the recommendations of a quality model for defining its task or activities. The aim of this paper is to describe the improvements made to Agile Mantema methodology and its integration with tasks and activities of ISO/IEC 12207∶2008 standard. This tasks and activities are related to measurement and control of maintenance projects. The objective is to obtain the maturity level 2 of ISO/IEC 15504-ISO/IEC 12207∶2008 evaluation model in a future. This paper shows the experience in a small organization which implanted the proposed improvement in its maintenance area. Results demonstrate a good control in maintenance projects, agility, formality and simplicity in the methodological improvement proposed.
Guggulusome - A Novel Vesicular Carriers for Enhanced Transdermal Delivery

The present work describes guggul as a novel carrier for some anti-inflammatory drugs. Guggulusomes containing different concentration of guggul with aceclofenac were prepared by sonication method and characterized for vesicle shape, size, size-distribution, pH, viscosity, spread ability, homogeneity, and accelerated stability in-vitro drug permeation through mouse skin. The vesicles exhibited an entrapment efficiency of 93.2 Â± 12%, vesicle size of 0.769 Â± 3Î¼m and a zeta potential of - 6.21mV. In vitro drug release was analyzed using Franzâ€™s diffusion cells. The cumulative release of the guggulusomes gel (G2) was 75.8% in 18 hrs, which is greater than that all the gel formulation. The stability profile of prepared system assessed for 45 days. The vesicular suspension was kept in sealed vials (10ml) at 4 Â± 2ÂºC and at room temperature for 45 days no change was showned in entrapment efficiency. The optimized guggulusomes formulation showed transdermal flux 216. 1Î¼g/cmÂ²/hr. The result advocates the potential of guggulusomes formulation to treat diseases where facilitated penetration of the drug into muscle and synovial fluid is desirable. In the end of the tests guggulusomes gel G2 with carbopol 934K was the most stable. The paw edema and percentage inhibition of carrageenan-induced paw edema in rats treated with aceclofenac guggulusomes gels and commercial formulation of aceclofenac gel marketed gel. The formulation G2 were devoid of any irritation potential and no edema formation was observed in any case. Irritation score for aceclofenac guggulusomes gels was zero, which indicated its acceptability for topical administration. Keywords: Aceclofenac, Gel, Carbopol, Guggulu carrier.
Patch antenna sensor rosettes for surface strain measurement

Passive (battery-free) wireless patch antenna sensors have been developed in recent years for strain sensing, to provide convenient and low-cost instrumentation. Despite past efforts, current analytical and experimental studies have mainly focused on performance in single-axial measurement, which is simple and unrealistic from typically encountered arbitrary plane stress fields. This paper presents strain sensor rosettes made of folded patch antennas and slotted patch antennas for measuring an arbitrary surface strain (plane stress) field. The transverse strain effect of both sensors is discussed and has been validated through laboratory experiments. Multiphysics coupled simulation is conducted to describe accurately the mechanical and electromagnetic behaviours of antenna sensors. Resonance frequency shifts of the antenna sensors are used to derive the three strain components in an arbitrary plane stress scenario – that is, two normal and one shear strain components. Both numerical studies and experiment.
Modeling and forecasting return volatility: A new reduced form approach using nonparametric variation measures

This paper motivates a reduced form discrete-time series approach that models realized volatility by using its separated components, continuous variation and variation due to jumps. For this purpose, I combine Engle and Russell’s (1998) autoregressive conditional duration (ACD) model applied to the continuous and jump size variation with
Multi-contact Locomotion of Legged Robots in Complex Environments – The Loco3D project

Planning, adapting and executing multi-contact locomotion movements on legged robots in complex environments remains an open problem. In this proposal, we introduce a complete pipeline to address this issue in the context of humanoid robots inside industrial environments. This pipeline relies on a multi-stage approach in order to simplify the process flow and to exploit at best state-of-the-art techniques both in terms of contact planning, whole-body control and perception. The main challenges lie in the choice of the different modules composing this pipeline as well as their mutual interactions: e.g. at which frequency rates each module has to work in order to allow safe and robust locomotion? or which information must transit between the modules? We named this project Loco3D standing for Locomotion in 3D, in contrast to the classic locomotion on quasi-flat terrains, where the motion of the center of mass of the robot is mostly limited to a 2D plane.
Dietary Intake of c 9 , t 11-Conjugated Linoleic Acid Correlates with Its Concentration in Plasma Lipid Fractions of Men but Not Women 1 , 2

The c9,t11–18:2 isomer of conjugated linoleic acid (c9,t11-CLA) represents the main dietary CLA formwith putative health benefits. Whereas CLA intake influences the tissue CLA concentration, little is known about the association between dietary CLA and the CLA content of plasma lipid fractions. This study was designed to document fasting and nonfasting plasma c9,t11-CLA concentrations in a population of free-living adults (n = 94) and relate these concentrations to c9,t11CLA intake. We also determined the c9,t11-CLA content of the primary plasma lipid fractions in a subset (n = 50) of our participants, related these to c9,t11-CLA intake, and determined whether c9,t11-CLA intake or plasma c9,t11-CLA was correlated with plasma cholesterol. Mean fasting plasma c9,t11-CLA concentrations were 0.466 0.01 and 0.546 0.01% (wt:wt) of total fatty acids for men and women, respectively (P < 0.05); nonfasting concentrations were 0.28 6 0.01 and 0.386 0.01% of total fatty acids, respectively (P < 0.001). All major esterified plasma lipid fractions contained c9,t11-CLA; TG had the highest percentages. In men, c9,t11-CLA intake correlated (r = 0.47; P < 0.05) with TG c9,t11-CLA content, suggesting that TG c9,t11-CLA may serve as a biomarker for c9,t11-CLA intake. In females, there were no correlations between c9,t11-CLA intake and the c9,t11-CLA content of any esterified plasma lipid fraction. In neither sex was there a relation between dietary c9,t11-CLA or plasma c9,t11-CLA concentration and circulating lipoprotein cholesterol concentration. The influence of sex on circulating c9,t11-CLA content and further validation of biomarkers of c9,t11CLA intake warrant further investigation. J. Nutr. 142: 1645–1651, 2012.
Statistical Analysis for Multisite Trials Using Instrumental Variables With Random Coefficients

Abstract Multisite trials can clarify the average impact of a new program and the heterogeneity of impacts across sites. Unfortunately, in many applications, compliance with treatment assignment is imperfect. For these applications, we propose an instrumental variable (IV) model with person-specific and site-specific random coefficients. Site-specific IV coefficients can be interpreted as site-average effects of program participation or as site-average effects of participation for the compliers. The validity of these interpretations depends on the analyst's assumptions. Within the framework of a two-level hierarchical linear model, we propose three ways to estimate the mean and variance of these site-specific effects: (a) estimate the impact of program participation and its standard error in each site, then combine these site-specific statistics to estimate the mean and variance of the true site effects; (b) estimate the mean and variance of the effect of treatment assignment on the outcome and the mean and variance of the effect of treatment assignment on program participation; then combine these results to obtain estimates of the mean and variance of the effect of program participation; and (c) use Site by Treatment interactions as multiple instruments. If we assume the IV coefficients to be homogenous across sites, the three approaches are equivalent to variants of familiar two-stage least squares estimates with site fixed effects. Estimates based on our model are valid under a weaker assumption: that site-average levels of compliance are independent of site-average effects of program participation. To illustrate our approach, we evaluate a district-wide policy intended to increase math instructional time in math for low-achieving students. Finally, we discuss how Method (c) can be extended to incorporate multiple mediators.
Visual Image Retrieval and Localization

This paper suggests a content-based image retrieval scheme, applicable to large web collections. A fast and robust system is proposed, based on the popular bag-of-words model. SURF features are extracted from images and a visual vocabulary is created, through which images are efficiently represented. Furthermore, geometric constraints on the image features are taken into account, facilitating accurate retrieval. The performance of the proposed methods is evaluated on two common datasets, while an advanced web-based image retrieval application is presented, that yields a geographic position estimation about the query image, exploiting geotagged datasets.
Adaptive level set for fluid surface tracking

We introduce an adaptive hybrid level set surface tracking for fluid simulation in this paper. To improve the accuracy of the convectional level set method, we propose a method that combines the higher accuracy interpolation and octree grid to improve the accuracy while still maintain good efficiency. Adaptive gradient-augmented level set is adopted for higher accuracy interpolation and two strategies are proposed to guide the building of the octree structure. We demonstrate our method with several level set tests, and couple it to several existing fluid simulators. The results show that our method facilitates significant improvements in accuracy and efficiency, and is effective for free surface fluid simulation in capturing fluid details.
Supplementary Material Supplementary Methods Encoding the Data and Handling Missing Entries the Singular Value Decomposition and Principal Components Analy- Sis

In order to provide more efficient navigation and access to supplementary material, all the proposed panels of AIMs, as well as additional details of our analysis and numerous PCA plots are available online at the following address (please respect capitalization): The proportion of missing entries in the Bovine HapMap dataset after our quality control step was approximately 2.45%. It is worth emphasizing that we do not need to fill in missing entries in any manner, since our computations ignore missing entries. We transformed the raw data to numeric values, without any loss of information, in order to apply our linear algebraic methods. More specifically, given a dataset of m samples, and assuming that for each subject n biallelic SNPs have been assayed, we can view the original data as a table consisting of m rows and n columns. Each entry in the table is a pair of bases (in alphabetical order). We transformed this table to an m × n integer matrix A. Each entry of A is set to −1,0, or +1 (or is empty). Let B 1 and B 2 be the two possible alleles that appear in the j-th SNP (in alphabetical order). If the genotypic information for the j-th SNP of the i-th sample is B 1 B 1 , then the (i, j)-th entry of A is set to +1; else if it is B 1 B 2 , then the (i, j)-th entry of A is set to 0; else if it is B 2 B 2 , then the (i, j)-th entry of A is set to-1 [4, 3]. We briefly describe the Singular Value Decomposition (SVD) of matrices and the related Principal Components Analysis (PCA). Given m subjects and n SNPs (m ≤ n), let the m × n matrix A denote the subject-SNP matrix encoded as described above. After mean-centering the columns (SNP genotypes) of A, the SVD of the matrix returns m pairwise orthonormal vectors u i , n pairwise orthonormal vectors v i , and m non-negative singular values σ i such that σ 1 ≥ σ 2 ≥. ≥ σ m ≥ 0. The matrix A may be written as a sum of outer products as A = m ∑ i=1 σ i u i v i T. (1) Each triplet (σ i , u i , v i) may be used to form a principal component …
Solution structure of hypothetical protein, HP0495 (Y495_HELPY) from Helicobacter pylori

Introduction. Helicobacter pylori is a spiral shaped and gram-negative bacteria which lives in stomach and cause the diverse gastric diseases such as peptic ulcers, chronic gastritis, mucosa-associated lymphoid tissue lymphoma, and gastric cancer. Complete genome sequences of H. pylori, strain 26695 and strain J99, have been determined. In the chromosome of strain 26695, 1590 open reading frames (ORFs) were identified. Among them, 499 ORFs are annotated as ‘‘hypothetical proteins’’ whose function and three-dimensional structures have never been identified. As part of our structural genomics effort on H. pylori, we have determined the solution structure of HP0495 (Y495_HELPY; Swiss-Prot ID). The HP0495 (Y495_ HELPY) gene of Helicobacter pylori encodes an 86-residue hypothetical protein from Helicobacter pylori strain 26695 with a molecular weight of 10,192.7 Da and a calculated isoelectric point of 8.71. The result of sequence homology search showed that HP0495 (Y495_HELPY) has a restricted sequence homology with unknown proteins from several bacteria, except the protein from strain J99 of H. pylori (86% identity). Several proteins were identified with below 40% sequence identity with HP0495 (Y495_HELPY) (Fig. 1).
Applying Hierarchical Clustering to Discover the Typical Process Route

In order to discover the typical process route (TPR) in the Computer Aided Process Planning (CAPP) database, Hierarchical Clustering algorithm is adopted. A mathematics model based on the data matrix was built to describe the process route (PR). On the base of the operation code, the distance between operations, between the PRs, between clusters were measured to evaluate the PR similarity. Then, the PR clusters were eventually merged by the hierarchical clustering algorithm. Three methods are listed to confirm the clustering granularity that determines the clustering result. This TPR discovery method is successfully applied to discover the axle sleeves’ TPR.
Harnessing Vehicle-to-Vehicle Communications for 3G Downloads on the Move

This paper studies the problem of 3G downloads in vehicles on the move. Although the 3G brings larger coverage and instant access to data transfer, it may also incur high cost. We observe that many applications of vehicular 3G users can actually tolerate certain data access latency. In addition, vehicle-to-vehicle communications have been practical and can be exploited for intervehicle data delivery. Based on these observations, we propose to augment vehicular 3G users by data sharing through vehicle-to-vehicle communications. We formulate an optimization problem. The objective is to minimize the cost of 3G data communications, meanwhile maximizing the success probability of downloading all 3G user data. The two-hop transmission process and the bandwidth limitation in vehicular network are both modeled in the optimization problem. To lower the cost of 3G and meet the delivery ratio and delay constraints of data, one single-stage algorithm and one multistage algorithm are proposed for selection of seed vehicles (that download the data via 3G channel). We have evaluated our algorithm with simulations with real vehicular traces and the results show that our algorithms reduce the 3G cost and achieve good performance of data downloads.
Indexing Fingerprint Databases Based on Multiple Features

In a fingerprint identification system, a person is identified only by his fingerprint. To accomplish this, a database is searched by matching all entries to the given fingerprint. However, the maximum size of the database is limited, since each match takes some amount of time and has a small probability of error. A solution to this problem is to reduce the number of fingerprints that have to be matched. This is achieved by extracting features from the fingerprints and first matching the fingerprints that have the smallest feature distance to the query fingerprint. Using this indexing method, modern systems are able to search databases up to a few hundred fingerprints. In this paper, three possible fingerprint indexing features are discussed: the registered directional field estimate, FingerCode and minutiae triplets. It is shown that indexing schemes that are based on these features, are able to search a database more effectively than a simple linear scan. Next, a new indexing scheme is constructed that is based on advanced methods of combining these features. It is shown that this scheme results in a considerably better performance than the schemes that are based on the individual features or on more naive methods of combining the features, thus allowing much larger fingerprint databases to be searched.
Simba: spatial in-memory big data analysis

We present the Simba (Spatial In-Memory Big data Analytics) system, which offers scalable and efficient in-memory spatial query processing and analytics for big spatial data. Simba natively extends the Spark SQL engine to support rich spatial queries and analytics through both SQL and DataFrame API. It enables the construction of indexes over RDDs inside the engine in order to work with big spatial data and complex spatial operations. Simba also comes with an effective query optimizer, which leverages its indexes and novel spatial-aware optimizations, to achieve both low latency and high throughput in big spatial data analysis. This demonstration proposal describes key ideas in the design of Simba, and presents a demonstration plan.
Improvement of Xylose Fermentation Ability under Heat and Acid Co-Stress in Saccharomyces cerevisiae Using Genome Shuffling Technique

Xylose-assimilating yeasts with tolerance to both fermentation inhibitors (such as weak organic acids) and high temperature are required for cost-effective simultaneous saccharification and cofermentation (SSCF) of lignocellulosic materials. Here, we demonstrate the construction of a novel xylose-utilizing Saccharomyces cerevisiae strain with improved fermentation ability under heat and acid co-stress using the drug resistance marker-aided genome shuffling technique. The mutagenized genome pools derived from xylose-utilizing diploid yeasts with thermotolerance or acid tolerance were shuffled by sporulation and mating. The shuffled strains were then subjected to screening under co-stress conditions of heat and acids, and the hybrid strain Hyb-8 was isolated. The hybrid strain displayed enhanced xylose fermentation ability in comparison to both parental strains under co-stress conditions of heat and acids. Hyb-8 consumed 33.1 ± 0.6 g/L xylose and produced 11.1 ± 0.4 g/L ethanol after 72 h of fermentation at 38°C with 20 mM acetic acid and 15 mM formic acid. We also performed transcriptomic analysis of the hybrid strain and its parental strains to screen for key genes for multiple stress tolerances. We found that 13 genes, including 5 associated with cellular transition metal ion homeostasis, were significantly upregulated in Hyb-8 compared to levels in both parental strains under co-stress conditions. The hybrid strain Hyb-8 has strong potential for cost-effective SSCF of lignocellulosic materials. Moreover, the transcriptome data gathered in this study will be useful for understanding the mechanisms of multiple tolerance to high temperature and acids in yeast and facilitate the development of robust yeast strains for SSCF.
Modelling environmental limits to light use efficiency for a canopy of two broad-leaved tree species with contrasting leaf habit

We used outputs from a model of canopy carbon uptake (Dungan et al. (2004) Functional Ecology 18: 34-42) and measurements of irradiance (PAR, 400-700 nm) intercepted by the canopy to investigate the effect of daily changes in environmental conditions on daily light use efficiency, e, for a canopy comprising two broadleaved New Zealand tree species with contrasting leaf habit. Irradiance absorbed by the canopy was 93% of the incident irradiance, and seasonal changes in the proportion of this absorbed by leaves of each species was estimated with a detailed model of leaf area phenology. Over the year, e for semi-deciduous wineberry (Aristotelia serrata) was 0.43 g C MJ -1 PAR, with maximum and minimum values of 0.80 g C MJ -1 PAR and 0.07 g C MJ -1 PAR in summer and winter respectively. In contrast annual e was 0.60 g C MJ -1 PAR for winter deciduous fuchsia, with a maximum value of 0.92 g C MJ -1 PAR in spring. The most important environmental regulator of e for both species was τ, atmospheric transmissivity. Maximum values for e were estimated on days when τ ≈0.2, on cloudy days in mid-summer. Limits to photosynthesis from restricted root-zone water availability were also important, showing that drought limitations can restrict e even at a field site with annual rainfall of 4800 mm. Environmental limits to photosynthesis and e have been investigated for only a few canopy tree species. Uncertainty in models of the national carbon budget required for reporting purposes would be reduced by considering the environmental regulation of e for a wider range of tree species.
The family of mapreduce and large-scale data processing systems

In the last two decades, the continuous increase of computational power has produced an overwhelming flow of data which has called for a paradigm shift in the computing architecture and large-scale data processing mechanisms. MapReduce is a simple and powerful programming model that enables easy development of scalable parallel applications to process vast amounts of data on large clusters of commodity machines. It isolates the application from the details of running a distributed program such as issues on data distribution, scheduling, and fault tolerance. However, the original implementation of the MapReduce framework had some limitations that have been tackled by many research efforts in several followup works after its introduction. This article provides a comprehensive survey for a family of approaches and mechanisms of large-scale data processing mechanisms that have been implemented based on the original idea of the MapReduce framework and are currently gaining a lot of momentum in both research and industrial communities. We also cover a set of introduced systems that have been implemented to provide declarative programming interfaces on top of the MapReduce framework. In addition, we review several large-scale data processing systems that resemble some of the ideas of the MapReduce framework for different purposes and application scenarios. Finally, we discuss some of the future research directions for implementing the next generation of MapReduce-like solutions.