Miracle-dz/UniFAR-FTUs huggingface dataset:
Crowdsourcing Tasks within Linked Data Management

Many aspects of Linked Data management – including exposing legacy data and applications to semantic formats, designing vocabularies to describe RDF data, identifying links between entities, query processing, and data curation – are necessarily tackled through the combination of human effort with algorithmic techniques. In the literature on traditional data management the theoretical and technical groundwork to realize and manage such combinations is being established. In this paper we build upon and extend these ideas to propose a framework by which human and computational intelligence can co-exist by augmenting existing Linked Data and Linked Service technology with crowdsourcing functionality. Starting from a motivational scenario we introduce a set of generic tasks which may feasibly be approached using crowdsourcing platforms such as Amazon’s Mechanical Turk, explain how these tasks can be decomposed and translated into MTurk projects, and roadmap the extensions to SPARQL, D2RQ/R2R and Linked Data browsing that are required to achieve this vision.
Theory of Change: a theory-driven approach to the MRC framework for complex interventions

ToC has not yet been widely used in the evaluation of complex interventions to improve health, and has not been used in conjunction with the MRC framework to design and evaluate interventions in the context of randomised controlled trials (RCTs). However, it holds much promise for this. We are piloting the use of ToC to design, implement, and evaluate complex interventions for mental health in a number of different research projects Using Theory of Change and how it ‘fits’ with MRC (Methods) Title Verdana Bold 72pt
Quality Control for Wordnet Development

This paper deals with quality assurance procedures for general-purpose language resources. Special attention is paid to quality control in wordnet develop- ment. General issues of quality management are tackled; technical as well as method- ological aspects are discussed. As a case study, the application of the described proce- dures is demonstrated on the quality evaluation techniques in the context of the Balka- Net project.
Approximate Time Separation of Events in Practice

Finding bounds on the time separations between events is a fundamental problem in the analysis of concurrent systems. In [4], we proposed a polynomial-time approximate algorithm for computing bounds on the separations between all pairs of events in acyclic timing constraint graphs. This paper describes applications of our algorithm to two interesting problems: (i) a buffered producer-consumer system, and (ii) a multiprocessor system operating under different scheduling and buffering schemes. We describe how the temporal behavior of each system is modeled using min and max constraints in a timing constraint graph. The resulting graph is analyzed using the algorithm of [4] to answer several important questions about the system.
Learning a Hierarchical Representation of Words within a Neural Language Model

Neural probabilistic language models have been shown to signi(cid:12)cantly out-perform traditional statistical models based on n -grams (Bengio, Ducharme and Vincent, 2001). However, they are not as popular, in particular due to the high computational resources needed to both train and use them. In this project we explore the idea of learning a hierarchical representation of words in order to obtain an exponential speed-up when computing word probabilities. We show in experiments that the proposed neural architecture, in spite of a reasonable training and testing time, does not yield satisfactory results as far as prediction performance is concerned, since it performs signi(cid:12)cantly worse than a simple unigram model
Optimal Web Service Selection based on Multi-Objective Genetic Algorithm

Considering that there are three aspects of constrains in the service selection process, such as control structure within a composition plan, relationship between concrete services, and tradeoff among multiple QoS indexes, a QoS based optimal Web services selection method by multi-objective genetic algorithm is presented. First we design a chromosome coding method to represent a feasible service selection solution, and then develop genetic operators and strategies for maintaining diversity of population and avoiding getting trapped in local optima. Experimental results show that within a finite number of evolving generations this algorithm can generate a set of nondominated Pareto optimal sol.utions which satisfy to user's QoS requirements.
Rapidly Creating Structure-Aware Halftoning with Improved Error Diffusion

Showing the details of edge and texture structure clearly is an important aspect of modern halftoning technique. This paper proposes a simple and effective error diffusion halftoning algorithm, and with keeping structure-aware on show. The method is based on the well-known Ostromoukhov algorithm. According with local area gray distribution, we calculate the local visual information of texture feedback (ITF) around each pixel and then the ITF is used to adjust the fixed threshold. The results of experiment show that achieved halftone images have clarity and natural texture structure. It not only represents ideal blue noise spectrum, but also shows a better performance in evaluation index of peak signal to noise ratio (PSNR), universal image quality index (UIQI) and structural similarity index measure (SSIM).
Using Program Slicing to Analyze Aspect-Oriented Composition

AspectJ language was proposed to make cross-cutting concerns clearly identifiable with special linguistic constructs called aspects. In order to analyze the properties of an aspect one should consider the aspect itself and the part of the system it affects. This part is just a slice of the entire system and can be extracted by exploiting program slicing algorithms. However, the expressive power of AspectJ constructs forces slicers to take into account big portions of programs. We suggest that AspectJ should regulate more formally the interaction among code units, by defining some stricter boundaries around aspect influence, otherwise the separation turns out to be just syntactic sugar.
A segmentation method for sub-solid pulmonary nodules based on fuzzy c-means clustering

Accurately and reliably automated segmentation of pulmonary tumors could play an important role in lung cancer diagnosis and radiation oncology work. However, it remains a very difficult task in particular for segmenting pulmonary tumors associated with sub-solid nodules that are partially obscured in lung CT images. In this study, we proposed and tested an improved weighed kernel fuzzy c-means (IWKFCM) method that incorporates vessels structure information and classes' distribution as weights to segment sub-solid pulmonary nodules. For this purpose, a ROI of a nodule in center CT slice is manually defined. The IWKFCM algorithm is applied to identify and cluster the potential nodule pixels located in this manually-defined center slice and its adjacent slices. The sub-solid nodule is then segmented and defined through 3D connected component labeling and morphological post-processing. The segmentation method was tested using a public CT dataset (LIDC) including 36 nodules. The average overlap ratio between the automated and radiologists' segmentation of nodules is 76.18%. The false-positive ratio (FPR) and false-negative ratio (FNR) are smaller. Experimental results showed that the proposed method enabled to achieve more accurate result in segmenting sub-solid pulmonary nodules.
Neuronal dystonin isoform 2 is a mediator of endoplasmic reticulum structure and function

ETOC: The diverging contributions of the cytoskeletal linker proteins dystonin-a1 and dystonin-a2 to pathology in dystonia musculorum are largely unknown. Sensory neurodegeneration results primarily from the loss of the dystonin-a2 isoform, which is attributed a novel role in maintenance of organelle integrity.
Virtual Energy-Efficient Encryption and Keying (VEEEK) for Wireless Sensor Networks

—The sensor nodes are resource-limited wireless devices; therefore the designing of protocols for WSNs (Wireless Sensor Networks) which are cost-efficient and secure is a major challenging problem in today’s networking and mobile computing area. The communication cost is the most important factor in the sensor’s energy consumption; here we are introducing a virtual energy-efficient encryption scheme for WSNs which reduces the transmissions between nodes which are required for rekeying to avoid stale keys. The main goal is to save energy in WSNs besides this we have minimal transmission is also imperative in some military applications of WSNs in which the adversary could be monitoring the wireless spectrum. This energy-efficient encryption is a secure communication framework in which an algorithm is used to encode the sensed data. This algorithm is worked based on a permutation codes generated via RC5 Encryption mechanism. The key to RC5 algorithm encrypts blocks of plaintext of length 32 bits into blocks of cipher text of the same length. And the key length ranges from 0 to 2040 bits. Thus, the key will be changed for every packet and different keys are used for successive packets. In this paper, we used the above algorithm to send the messages secretly in military applications while the wireless spectrum is adversely monitoring by the enemies.
Effects of overweight on luminal diameter, flow velocity and intima-media thickness of carotid arteries.

PURPOSE To the best of our knowledge, there are only a few previous studies on the effects of overweight on extracranial carotid arteries. We aimed to investigate the effects of overweight on flow velocities, luminal diameters and intima media thicknesses (IMTs) of the common and internal carotid arteries (CCA, ICA). MATERIALS AND METHODS A prospective study on color duplex sonography of the extracranial arteries was performed in 71 adults, ages between 25-58 years old. The body mass index (BMI) was found to be normal in 24 (group 1) and high in 47 (group 2) subjects of the study group. Flow velocity (FV), luminal diameter and IMT of carotid arteries of all the participants were measured. RESULTS There were significant differences between group 1 and group 2 in the following parameters; luminal diameters of the right CCAs were significantly larger in group 2, peak-systolic FV of ICAs were significantly lower in group 2 than in group 1 and ICA end-diastolic FVs were significantly lower in group 2 than in group 1. CONCLUSION The present data shows that there is a correlation among carotid artery luminal diameter, FVs and overweight. In the overweight subjects, the increased luminal diameter and decreased FVs can point at the early stage of atherosclerosis. The influence of adiposity on atherosclerosis is very complex and varies with gender and age, therefore we need larger series and further investigation.
Antibody production using a ciliate generates unusual antibody glycoforms displaying enhanced cell-killing activity

ABSTRACT Antibody glycosylation is a key parameter in the optimization of antibody therapeutics. Here, we describe the production of the anti-cancer monoclonal antibody rituximab in the unicellular ciliate, Tetrahymena thermophila. The resulting antibody demonstrated enhanced antibody-dependent cell-mediated cytotoxicity, which we attribute to unusual N-linked glycosylation. Detailed chromatographic and mass spectrometric analysis revealed afucosylated, oligomannose-type glycans, which, as a whole, displayed isomeric structures that deviate from the typical human counterparts, but whose branches were equivalent to fragments of metabolic intermediates observed in human glycoproteins. From the analysis of deposited crystal structures, we predict that the ciliate glycans adopt protein-carbohydrate interactions with the Fc domain that closely mimic those of native complex-type glycans. In addition, terminal glucose structures were identified that match biosynthetic precursors of human glycosylation. Our results suggest that ciliate-based expression systems offer a route to large-scale production of monoclonal antibodies exhibiting glycosylation that imparts enhanced cell killing activity.
Strategic planning and corporate performance . What is the relationship ?

The majority of management literature describes strategic planning (SP) as being effective in relation to improving corporate performance (CP), but is that assumption correct? Several studies have shown that the relationship is dubious if not non-existent. To clarify the relationship a comprehensive meta-analysis was conducted on 88 individual studies representing a total sample size of 32,472 observations. The findings of the meta-analysis suggest that strategic planning does in fact have a positive effect on corporate performance, although it is smaller than the strategic management literature existing to date has proclaimed it to be. Explanations of the unexpected result and directions for future research will be provided.
IGSA: Individual Gene Sets Analysis, including Enrichment and Clustering

Analysis of gene sets has been widely applied in various high-throughput biological studies. One weakness in the traditional methods is that they neglect the heterogeneity of genes expressions in samples which may lead to the omission of some specific and important gene sets. It is also difficult for them to reflect the severities of disease and provide expression profiles of gene sets for individuals. We developed an application software called IGSA that leverages a powerful analytical capacity in gene sets enrichment and samples clustering. IGSA calculates gene sets expression scores for each sample and takes an accumulating clustering strategy to let the samples gather into the set according to the progress of disease from mild to severe. We focus on gastric, pancreatic and ovarian cancer data sets for the performance of IGSA. We also compared the results of IGSA in KEGG pathways enrichment with David, GSEA, SPIA, ssGSEA and analyzed the results of IGSA clustering and different similarity measurement methods. Notably, IGSA is proved to be more sensitive and specific in finding significant pathways, and can indicate related changes in pathways with the severity of disease. In addition, IGSA provides with significant gene sets profile for each sample.
The Capacity Region of Two-way Collision Networks

The collision channel without feedback is a system with multiple source nodes and a single destination node, where coordination among the source nodes and feedback from the destination node are not available. Its capacity region was first derived by Massey and Mathys. We generalize their model by introducing multiple destination nodes and relay nodes. In this paper, we consider linear collision networks in which the nodes lie on a straight line. The two nodes at the ends want to exchange data through the relay nodes in the middle. An outer bound on achievable rates is derived. By using a simple network code, we can show that all points within the outer bound are indeed achievable, and thus obtain the capacity region.
Potent Tumor-Specific Immunity Induced by an In vivo Heat Shock Protein-Suicide Gene–Based Tumor Vaccine

Tumor cells harbor a repertoire of unique, mutated antigens and shared self-antigens but generally are incapable of provoking an effective immune response, likely because of inadequate antigen presentation by professional antigen-presenting cells. Heat shock proteins (HSPs) play important roles in eliciting innate and adaptive immunity by chaperoning peptides for antigen presentation and providing endogenous danger signaling. Although effective in inducing tumor-specific immunity in mice and in some clinical trials, tumor-derived HSPs have many limitations like vaccines, such as the technical difficulty of ex vivo preparation of adequate quantities of HSPs from the resected tumors of individual patients. Here we have developed an in vivo HSP-suicide gene tumor vaccine by generating a recombinant replication-defective adenovirus (Ad-HT) that coexpresses HSP70 and a herpes simplex virus thymidine kinase suicide gene. The combination of HSP70 overexpression in situ and tumor killing by thymidine kinase/ganciclovir treatment, but neither strategy alone, provoked potent systemic antitumor activities after intratumor injection of Ad-HT. Tumor-specific CD4+ and CD8+ T-cell responses were induced by Ad-HT intratumor injection. CD11c+ dendritic cells (DCs) isolated from mice treated with Ad-HT were able to prime tumor-specific CTLs. Collectively, these results indicate that the combination of tumor killing by activation of a suicide gene to release tumor antigens and in situ HSP70 overexpression to enhance DC antigen presentation overcomes host immune tolerance to tumor antigens, leading to the induction of potent antitumor immunity. Our findings may have broad relevance to the use of the in vivo HSP/suicide gene tumor vaccine in therapy for human solid tumors.
Two-View Motion Segmentation by Gaussian Blurring Mean Shift with Fitness Measure

Motion segmentation for dynamic scene is fundamental in computer vision. The key issue is to estimate number and parameters of transformations simultaneously. However, transformations cannot be measured by general Euclidean distance because of them not lying in vector space. In this paper, we convert transformations into fitness vectors which can be easily measured by cosine similarity. Then we apply Gaussian Blurring Mean Shift (GBMS) algorithm as a non-parameter clustering for further motion segmentation. Our approach doesn’t need any preknowledge of the number of motions and converges within a few iterations. Experimental results have shown that the method has a good performance for motion segmentation. Keywords-GBMS; motion segmentation; fitness; non-parameter clustering
A Visual Analytics Approach to Study Anatomic Covariation

Gaining insight into anatomic co variation helps the understanding of organismic shape variability in general and is of particular interest for delimiting morphological modules. Generation of hypotheses on structural co variation is undoubtedly a highly creative process, and as such, requires an exploratory approach. In this work we propose a new local anatomic covariance tensor which enables interactive visualizations to explore co variation at different levels of detail, stimulating rapid formation and (qualitative) evaluation of hypotheses. The effectiveness of the presented approach is demonstrated on a μCT dataset of mouse mandibles for which results from the literature are successfully reproduced, while providing a more detailed representation of co variation compared to state-of-the-art methods.
Global increases in both common and rare copy number load associated with autism

Children with autism have an elevated frequency of large, rare copy number variants (CNVs). However, the global load of deletions or duplications, per se, and their size, location and relationship to clinical manifestations of autism have not been documented. We examined CNV data from 516 individuals with autism or typical development from the population-based Childhood Autism Risks from Genetics and Environment (CHARGE) study. We interrogated 120 regions flanked by segmental duplications (genomic hotspots) for events >50 kbp and the entire genomic backbone for variants >300 kbp using a custom targeted DNA microarray. This analysis was complemented by a separate study of five highly dynamic hotspots associated with autism or developmental delay syndromes, using a finely tiled array platform (>1 kbp) in 142 children matched for gender and ethnicity. In both studies, a significant increase in the number of base pairs of duplication, but not deletion, was associated with autism. Significantly elevated levels of CNV load remained after the removal of rare and likely pathogenic events. Further, the entire CNV load detected with the finely tiled array was contributed by common variants. The impact of this variation was assessed by examining the correlation of clinical outcomes with CNV load. The level of personal and social skills, measured by Vineland Adaptive Behavior Scales, negatively correlated (Spearman's r = −0.13, P = 0.034) with the duplication CNV load for the affected children; the strongest association was found for communication (P = 0.048) and socialization (P = 0.022) scores. We propose that CNV load, predominantly increased genomic base pairs of duplication, predisposes to autism.
Spliced Leader Trapping Reveals Widespread Alternative Splicing Patterns in the Highly Dynamic Transcriptome of Trypanosoma brucei

Trans-splicing of leader sequences onto the 5′ends of mRNAs is a widespread phenomenon in protozoa, nematodes and some chordates. Using parallel sequencing we have developed a method to simultaneously map 5′splice sites and analyze the corresponding gene expression profile, that we term spliced leader trapping (SLT). The method can be applied to any organism with a sequenced genome and trans-splicing of a conserved leader sequence. We analyzed the expression profiles and splicing patterns of bloodstream and insect forms of the parasite Trypanosoma brucei. We detected the 5′ splice sites of 85% of the annotated protein-coding genes and, contrary to previous reports, found up to 40% of transcripts to be differentially expressed. Furthermore, we discovered more than 2500 alternative splicing events, many of which appear to be stage-regulated. Based on our findings we hypothesize that alternatively spliced transcripts present a new means of regulating gene expression and could potentially contribute to protein diversity in the parasite. The entire dataset can be accessed online at TriTrypDB or through: http://splicer.unibe. ch/.
A Secure Framework for Communications in Heterogeneous Networks

Heterogeneous Networks represent an open architecture in which two different domains need to cooperate in order to provide ubiquitous connectivity. The first is network operators domain, where multiple network operators share the core network to provide network accessibility over a wide variety of wireless technologies such as WiFi and mobile network technologies. The other is the Application-Service Providers domain, which launches various services ranging from the normal video streaming to the most confidential E-Commerce services. This highlights the fact that any efficient security solution for heterogeneous networks has to consider the security in these different domains. Therefore, this paper introduces security framework that comprises two Authentication and Key Agreement protocols to secure transactions at the network and service levels. The proposed protocols have been formally verified using formal methods approach based on Casper/FDR tool.