Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Motions of General 3- RPR Planar Parallel Robots

We study the kinematic geometry of general 3-RPR planar parallel robots with actuated base joints. These robots, while largely overlooked, have simple direct kinematics and large singularity-free workspace. Furthermore, their kinematic geometry is the same as that of a newly developed parallel robot with SCARA-type motions. Starting from the direct and inverse kinematic model, the expressions for the singularity loci of 3-RPR planar parallel robots are determined. Then, the global behavior at all singularities is geometrically described by studying the degeneracy of the direct kinematic model. Special cases of self-motions are then examined and the degree of freedom gained in such special configurations is kinematically interpreted. Finally, a practical example is discussed and experimental validations performed on an actual robot prototype are presented.
Production and partial characterization of serine and metallo peptidases secreted by Aspergillus fumigatus Fresenius in submerged and solid state fermentation

Enzyme production varies in different fermentation systems. Enzyme expression in different fermentation systems yields important information for improving our understanding of enzymatic production induction. Comparative studies between solid-state fermentation (SSF) using agro-industrial waste wheat bran and submerged fermentation (SmF) using synthetic media were carried out to determinate the best parameters for peptidase production by the fungus Aspergillus fumigatus Fresen. Variables tested include: the concentration of carbon and protein nitrogen sources, the size of the inoculum, the pH of the media, temperature, and the length of the fermentation process. The best peptidase production during SSF was obtained after 96 hours using wheat bran at 30 °C with an inoculum of 1 × 106 spores and yielded 1500 active units (U/mL). The best peptidase production using SmF was obtained after periods of 72 and 96 hours of fermentation in media containing 0.5% and 0.25% of casein, respectively, at a pH of 6.0 and at 30 °C and yielded 40 U/mL. We also found examples of catabolite repression of peptidase production under SmF conditions. Biochemical characterization of the peptidases produced by both fermentative processes showed optimum activity at pH 8.0 and 50 °C, and also showed that their proteolytic activity is modulated by surfactants. The enzymatic inhibition profile using phenylmethylsulfonyl fluoride (PMSF) in SmF and SSF indicated that both fermentative processes produced a serine peptidase. Additionally, the inhibitory effect of the ethylene-diaminetetraacetic acid (EDTA) chelating agent on the peptidase produced by SmF indicated that this fermentative process also produced a metallopeptidase.
Characterization of Three Different Unusual S-Layer Proteins from Viridibacillus arvi JG-B58 That Exhibits Two Super-Imposed S-Layer Proteins

Genomic analyses of Viridibacillus arvi JG-B58 that was previously isolated from heavy metal contaminated environment identified three different putative surface layer (S-layer) protein genes namely slp1, slp2, and slp3. All three genes are expressed during cultivation. At least two of the V. arvi JG-B58 S-layer proteins were visualized on the surface of living cells via atomic force microscopy (AFM). These S-layer proteins form a double layer with p4 symmetry. The S-layer proteins were isolated from the cells using two different methods. Purified S-layer proteins were recrystallized on SiO2 substrates in order to study the structure of the arrays and self-assembling properties. The primary structure of all examined S-layer proteins lack some features that are typical for Bacillus or Lysinibacillus S-layers. For example, they possess no SLH domains that are usually responsible for the anchoring of the proteins to the cell wall. Further, the pI values are relatively high ranging from 7.84 to 9.25 for the matured proteins. Such features are typical for S-layer proteins of Lactobacillus species although sequence comparisons indicate a close relationship to S-layer proteins of Lysinibacillus and Bacillus strains. In comparison to the numerous descriptions of S-layers, there are only a few studies reporting the concomitant existence of two different S-layer proteins on cell surfaces. Together with the genomic data, this is the first description of a novel type of S-layer proteins showing features of Lactobacillus as well as of Bacillus-type S-layer proteins and the first study of the cell envelope of Viridibacillus arvi.
UMTG: a toolset to automatically generate system test cases from use case specifications

We present UMTG, a toolset for automatically generating executable and traceable system test cases from use case specifications. UMTG employs Natural Language Processing (NLP), a restricted form of use case specifications, and constraint solving. Use cases are expected to follow a template with restriction rules that reduce imprecision and enable NLP. NLP is used to capture the control flow implicitly described in use case specifications. Finally, to generate test input, constraint solving is applied to OCL constraints referring to the domain model of the system. UMTG is integrated with two tools that are widely adopted in industry, IBM Doors and Rhapsody. UMTG has been successfully evaluated on an industrial case study.
Robust background subtraction on traffic videos

Background subtraction involves processing of a video sequence from a static camera to detect the foreground objects in all frames. This paper introduces a robust background subtraction technique, the Adaptive Local Threshold (ALT) algorithm, which it is based on the Approximate Median Filter (AMF). It has been applied to accurately extract the moving vehicles on complex weather traffic videos (i.e. fog and snow scenes). Experimental results have shown that the proposed algorithm produces similar qualitative detection results (based on the Jaccard coefficient) than AMF for the tested videos. Additionally, our method has the advantage of not needing any threshold parameter to detect the foreground targets.
COMPONENT ORIENTED SOFTWARE DESIGN BY UTILIZING QUALITY FUNCTION DEPLOYMENT

One of the problems in software development is the gap between customer requirements and the final product. Especially, if component-oriented programming is taken into consideration, the cost, complexity, and development time should mostly depend on customer requirements. Quality function deployment provides a systematic method for tying design decisions directly to customer wants and needs. This study proposes a two-phased model for optimizing the cost and development time of the software in component-oriented design approach. The component-based software quality function deployment (CBSQFD) model identifies the most appropriate components that need to be used as the building blocks of a software project. For making the decision of which components to use, a 0-1 programming model is proposed. An application of proposed models is presented on a project and process management software (PPMS), which is being developed for an advertising agency. IPEK DEVECI KOCAKOC and ENGIN DEVECI 2
Conjunctival TGF-B Level in Primary Augmented Trabeculectomy

Purpose : To compare the levels of conjunctival transforming growth factor beta (TGF-β) between glaucoma and control patients and to determine conjunctival TGF-β levels before and 3 months after augmented primary trabeculectomy. Methods : Patients with primary open angle glaucoma (POAG) or primary angle closure glaucoma (PACG) admitted for mitomycin (MMC) augmented primary trabeculectomy due to failure in achieving target pressure after maximum medical therapy were selected. Age-matched non-glaucoma patients were controls. Impression cytology of the conjunctiva was obtained twice from glaucoma patients (1 week before augmented primary trabeculectomy and 3 months after surgery) and once from controls. Conjunctival cells were tagged with an anti-TGF-β antibody and analyzed by flow cytometry. Results : Eighteen patients (11 POAG and 7 PACG patients) and 18 age-matched control patients were included. Conjunctival TGF-β levels were significantly different between glaucoma (35.21% ± 14.12%) and control patients (14.96% ± 6.34%) (p = 0.001). There was a significant reduction in conjunctival TGF-β levels after augmented trabeculectomy (23.0% ± 13.8%) (p < 0.001). A significantly greater reduction in conjunctival TGF-β levels (61.6% ± 17.9%) was associated with complete success of trabeculectomy at 3 months (83.3%) after surgical intervention (p = 0.029). Conclusion : The reduction of TGF-β on the conjunctival post primary augmented trabeculectomy may suggest TGF-β as potential predicting marker of short term trabeculectomy success. However, the result may be affected by site of impression, topical pressure lowering drugs and small sample size.
Malicious web page detection based on feature classification

Malicious code detection is a major concern in computer science community in this decade. With the rapid growth of web applications, web sites have been become the attacker's main target. Innocent users' machines become compromised by just visiting a malicious page. This paper presents a malicious web page detection based on static feature classification. We classified features into three groups: explicit features, replicated features, and miscellaneous features. We employed Greasemonkey to develop the detection script. It provides the alert when an innocent user is visiting a malicious page. The accuracy of our detection system is 97.9% with 1.42 % of false positive and 2.76% of false negative. The average detection time is 2.49 seconds per page.
Web2.0 paves new ways for collaborative and exploratory analysis of Chemical Compounds in Spectrometry Data

Summary In nowadays life science projects, sharing data and data interpretation is becoming increasingly important. This considerably calls for novel information technology approaches, which enable the integration of expert knowledge from different disciplines in combination with advanced data analysis facilities in a collaborative manner. Since the recent development of web technologies offers scientific communities new ways for cooperation and communication, we propose a fully web-based software approach for the collaborative analysis of bioimage data and demonstrate the applicability of Web2.0 techniques to ion mobility spectrometry image data. Our approach allows collaborating experts to easily share, explore and discuss complex image data without any installation of software packages. Scientists only need a username and a password to get access to our system and can directly start exploring and analyzing their data.
Importance Driven Rendering – Using Importance Information in the Rendering Process

This paper describes the concept of using importance information in the rendering process. Doing so, we can adapt the rendering time and image quality to the requirements of a user. For that, we discuss two problems: assignment of importance and rendering of importance. We present results of first tests done with an example implementation and show how much rendering time can be saved.
THE INTEGRATION OF TRADITIONAL TECHNICAL GRAPHICS WITH SCIENTIFIC DATA VISUALIZATION

This paper attempts to bridge the languages of traditional technical graphics and scientific data visualization. A theoretical structure for guiding the generation and description of scientific visualizations is proposed. Examples are given as to how this structure can be used to generate visualizations of OsystemsO that might be explored by a scientist, engineer, or technician. Finally, how this theoretical structure relates to traditional technical graphics is shown, as is how this language can be used to support the creation of graphics throughout the engineering design cycle.
Spatial resolution improvement by merging MERIS-ETM images for coastal water monitoring

The Medium Resolution Imaging Spectrometer (MERIS) launched in March 2002 and has been providing images since June 2002. Before its launch, we had implemented a method to improve its resolution by merging its images with Landsat Enhanced Thematic Mapper images in order to preserve the best characteristics of the two images (spatial, spectral, temporal). We now present the results of this method for real MERIS images (level 1b and 2) in a coastal area. The robustness of the method is studied as well as the influence of the delay between the acquisitions of the two images.
Volatilty of Monthly Receipts of DGDA from January 1982 to December 2005

For a few years the revenue services of the DGDA have increased in a spectacular way in Democratic Republic of Congo. Thus, the objective of this paper is to empirically examine the evolution of these monthly receipts of 1982 to 2005. The Heteroskedastic Conditional Autoregressive model (ARCH) initiated by Engle (1982) was chosen to take into account the conditional variance of the error depending on time. The econometric literature informs us that if we generalize the model ARCH(p), while adding of the explanatory variables who represent variances of the shifted errors of q period, we obtain the Generalized Autoregressive Conditional Heteroskedastic GARCH(p,q) model. The empirical results of our study show that the receipts DGDA are represented by a model GARCH(1,1). This means that the heteroskedastic conditional variance of the errors of the monthly revenue services of the DGDA from January 1982 to December 2005 depends on its lag value and on the lag values of the error squared.
Accurate camera calibration using the collinearity constraint

In this paper, we apply the collinearity constraint for accurate camera calibration and correction. The novel method consists of two steps: the first is to estimate the relative parameters of interest with closed form solutions. The second employs the well known Levernburg-Marquardt (LM) algorithm for the global optimization of all the parameters of interest: 4 intrinsic, 7 extrinsic and 4 distortion parameters. The LM algorithm is initialised either as the parameters estimated in the first step or as zero. The optimization is achieved through minimising the sum of the squared back projected errors. The distorted points are finally corrected using again the LM algorithm initialized by the distorted image points themselves, minimizing the squared difference between the distorted corrected point and the given distorted image point. A comparative study based on both synthetic data and real images show that the proposed algorithm produces promising camera calibration and correction results.
A Distributed Clustering Algorithm Based on Cluster Stability for Mobile Ad Hoc Networks

In this paper, a new distributed clustering algorithm for mobile ad hoc networks, named as DCCS (Distributed Clustering Algorithm Based on delta- Cluster Stability) is proposed. The cluster stability of node, which is defined in this paper, is applied to clustering for mobile ad hoc networks. This algorithm is implemented on the ns2 environment, and compared with classical Lowest-ID clustering algorithm and Highest Degrees clustering algorithm. The results of simulation on ns2 simulator show that the proposed algorithm can improve efficiently clustering performances in terms of the number of clusterhead, and the number of reaffiliations per unit time.
The prevalence of atopic dermatitis in Puerto Rican school children.

BACKGROUND Atopic dermatitis is a common inflammatory disease of the skin that usually begins in childhood and its diagnosis depends on clinical criteria. Recent reports have indicated that the worldwide prevalence of atopic dermatitis is increasing. The objective of this study was to determine the prevalence of atopic dermatitis in schoolchildren between the ages of six and seven in two school districts in Puerto Rico. METHODS The Laughter questionnaire, developed to determine the prevalence of atopic dermatitis in schoolchildren was translated and validated in Spanish. A population-based prevalence survey was conducted among second grade students in the districts of Guaynabo and Humacao, Puerto Rico. The prevalence of atopic dermatitis was determined by sex, school type (private or public), and geographical location (urban or rural) using the questionnaire. RESULTS Ninety-two percent (92 %) of the eligible schools participated in the study. A total of 2,393 questionnaires were distributed with a response rate of 53 %. The prevalence of atopic dermatitis among the population surveyed was 24.8%. The prevalence of atopic dermatitis by sex or geographic location was not significantly different (p>0.05). An excess of atopic dermatitis was observed in private schools (31.0%) when compared to public schools (19.9%). The effect remained after controlling potential confounders (POR Mantel-Haenszel = 1.37; 95%CI: 1.07 - 1.42). CONCLUSION This study presents evidence of a significant public health problem in Puerto Rico. The prevalence of atopic dermatitis in Puerto Rico is high and possibly a large percentage (70%) of the patients is not been diagnosed.
Investment, growth and employment: VECM for Uruguay

Investment is a key to analyze an economy’s growth, as its increase the economy productive capacity, either expanding the capital stock as incorporating new technology that makes the production process more efficient. In Uruguay, investment has substantially increased in recent years, both overall and sectoral. This would have occurred as a result of strong growth in the period, as well as government policies on investment promotion. Growth and investment evolution, together with employment, has undergone a long history in economic theory. In that sense, there are empirical studies that support the theory that investment precedes growth, while there are others that provide evidence to the hypothesis that growth determines investment. Through a model with vector error correction (VECM) we found a long-term relationship between GDP without primary activity, investment and urban workers of Uruguay. In this model we observe a positive relationship between GDP and the other two variables, where GDP precedes both urban workers and investment.
Saving memory movements through vector processing in the DRAM

Despite the ability of modern processors to execute a variety of algorithms efficiently through instructions based on registers with ever-increasing widths, some applications present poor performance due to the limited interconnection bandwidth between main memory and processing units. Near-data processing has started to gain acceptance as an accelerator device due to the technology constraints and high costs associated with data transfer. However, previous approaches to near-data computing do not provide general-purpose processing, or require large amounts of logic and do not fully use the potential of the DRAM devices. These issues limited its wide adoption. In this paper, we present the Memory Vector Extensions (MVX), which implement vector instructions directly inside the DRAM devices, therefore avoiding data movement between memory and processing units, while requiring a lower amount of logic than previous approaches. MVX is able to obtain up to 211× increase in performance for application kernels with a high spatial locality and a low temporal locality. Comparing to an embedded processor with 8 cores and 2 memory channels that supports AVX-512 instructions, MVX performs 24× faster on average for three well known algorithms.
Low-energy limit of Yang–Mills with massless adjoint quarks: chiral Lagrangian and Skyrmions

If the fundamental quarks of QCD are replaced by massless adjoint quarks, the pattern of the chiral symmetry breaking drastically changes compared to the standard one. It becomes SU(Nf) → SO(Nf). While for Nf = 2, the chiral Lagrangian describing the ‘pion’ dynamics is well known, this is not the case at Nf > 2. We outline a general strategy for deriving chiral Lagrangians for the coset spaces and study in detail the case of Nf = k = 3. We obtain two- and four-derivatives terms in the chiral Lagrangian on the coset space = SU(3)/SO(3), as well as the Wess–Zumino–Novikov–Witten term, in terms of an explicit parameterization of the quotient manifold. Then we discuss stable topological solitons supported by this Lagrangian. Aspects of relevant topological considerations scattered in the literature are reviewed. The same analysis applies to SO(N) gauge theories with Nf Weyl flavours in the vector representation.
Business Cycle Dynamics in the Euro Area

The role of global, euro area and country-specific shocks in business cycle dynamics of the euro area are assessed with the aid of SVAR models. It is found that euro area shocks became a relatively more important factor behind cyclical fluctuations of the euro area countries recently. Another robust finding of the paper is that business cycle heterogeneity is driven mainly by countryspecific shocks in the euro area and not by heterogeneous responses to common shocks. The Great Moderation is found to be related to changes corresponding to global and country-specific shocks in the euro area, euro area shocks do not play a significant role in this phenomenon. Heterogeneity also underwent a moderation which can be traced back to changes corresponding to country-specific shocks of the member countries. JEL classification: C32, E32
Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations

Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biology. However, these methods have been less frequently used with empirical population genetics data. In this study, we developed a new combined approach of data analysis using microsatellite marker data from our previous studies of olive populations using machine learning algorithms. Herein, 267 olive accessions of various origins including 21 reference cultivars, 132 local ecotypes, and 37 wild olive specimens from the Iranian plateau, together with 77 of the most represented Mediterranean varieties were investigated using a finely selected panel of 11 microsatellite markers. We organized data in two ‘4-targeted’ and ‘16-targeted’ experiments. A strategy of assaying different machine based analyses (i.e. data cleaning, feature selection, and machine learning classification) was devised to identify the most informative loci and the most diagnostic alleles to represent the population and the geography of each olive accession. These analyses revealed microsatellite markers with the highest differentiating capacity and proved efficiency for our method of clustering olive accessions to reflect upon their regions of origin. A distinguished highlight of this study was the discovery of the best combination of markers for better differentiating of populations via machine learning models, which can be exploited to distinguish among other biological populations.