Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal provisioning for elastic service oriented virtual network request in cloud computing

In the cloud computing paradigm users access applications/services hosted and run on virtual machines in interconnected datacenters. Applications from the same user may need to interact and change data or information, thus, we may abstract the applications/services request from same user as a virtual network (VN). To improve performance and resource efficiency, it is critical that the VN request be optimally provisioned given the current resource state of the datacenters. However, all of the existing research about optimal VN provisioning conducted for deterministic services. In this work, we formulate the problem of optimal provisioning for elastic service oriented VN request as a mixed integer programming (MIP) model with the objective of maximizing the total revenue of infrastructure provider (InP), and propose a genetic algorithm based heuristic (GAH) algorithm for addressing the optimal provisioning for virtual network request with un-splittable flow (OPVNUF) and optimal provisioning for virtual network request with splittable flow (OPVNSF) problems of elastic services. We demonstrate the effectiveness of our approach for improving the total revenue, by conducting extensive simulations on real substrate network.
Ethanol Mediates Cell Cycle Arrest and Apoptosis in SK-N-SH Neuroblastoma Cells

Background: The mechanisms of cell or organ damage by chronic alcohol consumption are still poorly understood. The present study aimed to investigate the role of the mitogen-activated protein kinases during ethanol-induced damage to SK-N-SH neuroblastoma cells. Methods: Cells were treated with ethanol and subsequently analyzed for cell morphology, viability, and DNA fragmentation. Immunoblot analysis was performed to assess various proteins levels associated with cell cycle arrest and apoptosis after ethanol exposure. Results: Ethanol induced time- and dose-dependent cell death in SK-N-SH cells and increased c-Jun N-terminal protein kinase (JNK) activity in a time- and concentration dependent manner. In contrast, p38 kinase activity increased transiently. After treatment with JNK or p38 kinase inhibitors, ethanol-induced cell death significantly reduced. Ethanol-induced cell death was accompanied by increased cytochrome c release and caspase 3 activity observed at 12 h. In contrast, the level of anti-apoptotic Bcl-2 protein did not change. Ethanol also increased the phosphorylation of p53 and p53 activation was followed by an increase in the p21 tumor suppressor protein accompanied by a gradual decrease in phospho-Rb protein. Conclusion: Our results suggest that ethanol mediates apoptosis of neuroblastoma cells by stimulating p53-related cell cycle arrest mediated through activation of the JNK-related pathway.
Big Data and Learning Analytics in Blended Learning Environments: Benefits and Concerns

The purpose of this article is to examine big data and learning analytics in blended learning environments. It will examine the nature of these concepts, provide basic definitions, and identify the benefits and concerns that apply to their development and implementation. This article draws on concepts associated with data-driven decision making, which evolved in the 1980s and 1990s, and takes a sober look at big data and analytics. It does not present them as panaceas for all of the issues and decisions faced by higher education administrators, but sees them as part of solutions, although not without significant investments of time and money to achieve worthwhile benefits.
A systematic mapping study on dynamic metrics and software quality

Several important aspects of software product quality can be evaluated using dynamic metrics that effectively capture and reflect the software's true runtime behavior. While the extent of research in this field is still relatively limited, particularly when compared to research on static metrics, the field is growing, given the inherent advantages of dynamic metrics. The aim of this work is to systematically investigate the body of research on dynamic software metrics to identify issues associated with their selection, design and implementation. Mapping studies are being increasingly used in software engineering to characterize an emerging body of research and to identify gaps in the field under investigation. In this study we identified and evaluated 60 works based on a set of defined selection criteria. These studies were further classified and analyzed to identify their relativity to future dynamic metrics research. The classification was based on three different facets: research focus, research type and contribution type. We found a strong body of research related to dynamic coupling and cohesion metrics, with most works also addressing the abstract notion of software complexity. Specific opportunities for future work relate to a much broader range of quality dimensions.
A combined model for {311} defect and dislocation loop evolution: Analytical formulation of kinetic precipitation model

Accurate modeling of extended defect kinetics is of primary importance for prediction of transient enhanced diffusion (TED) following ion implantation of silicon. Our previously developed moment-based model [Gencer and Dunham, J. Appl. Phys. 81, 631 (1997)] accurately accounts for formation and evolution of {311} defects and can be used to predict TED under subamorphizing conditions. Using experimental knowledge about the distribution of the {311} defect population, and making approximations on the sums that are encountered in the model, we are able to simplify this model. We demonstrate that these simplifications don’t affect the predictive capabilities of the model for {311} defect kinetics and TED. Furthermore, we are able to extend the model, under the same simplifying assumptions, to account for dislocation loop formation from {311} defect unfaulting and dislocation loop evolution, giving a unified model for interstitial aggregation in silicon. The resulting analytical model does not impose any compu.
Horizontally Acquired Genes Are Often Shared between Closely Related Bacterial Species

Horizontal gene transfer (HGT) serves as an important source of innovation for bacterial species. We used a pangenome-based approach to identify genes that were horizontally acquired by four closely related bacterial species, belonging to the Enterobacteriaceae family. This enabled us to examine the extent to which such closely related species tend to share horizontally acquired genes. We find that a high percent of horizontally acquired genes are shared among these closely related species. Furthermore, we demonstrate that the extent of sharing of horizontally acquired genes among these four closely related species is predictive of the extent to which these genes will be found in additional bacterial species. Finally, we show that acquired genes shared by more species tend to be better optimized for expression within the genomes of their new hosts. Combined, our results demonstrate the existence of a large pool of frequently horizontally acquired genes that have distinct characteristics from horizontally acquired genes that are less frequently shared between species.
Asymptotic Signal Detection Rates with 1-Bit Array Measurements

This work considers detecting the presence of a band-limited random radio source using an antenna array featuring a low-complexity digitization process with single-bit output resolution. In contrast to high-resolution analog-to-digital conversion, such a direct transformation of the analog radio measurements to a binary representation can be implemented hardware and energy-efficient. However, the probabilistic model of the binary receive data becomes challenging. Therefore, we first consider the Neyman-Pearson test within generic exponential families and derive the associated analytic detection rate expressions. Then we use a specific replacement model for the binary likelihood and study the achievable detection performance with 1-bit radio array measurements. As an application, we explore the capability of a low-complexity GPS spectrum monitoring system with different numbers of antennas and different observation intervals. Results show that with a moderate amount of binary sensors it is possible to reliably perform the monitoring task.
Simulation of Thermopile IR-Sensors for Automotive Safety Applications

The growing demand for active safety systems implies also the requirement for new and suitable evaluation and test processes for such systems. However, the evaluation of these systems is in most cases a non trivial, time consuming and expensive task. Especially, for active pedestrian protection systems, which are based on infrared detection of humans. In this paper we present a simulation of Thermopile sensors to evaluate the performance of an infrared based pedestrian detection system. By means of the simulation tool, any test scenario can be generated and the simulation provides the sensor data to the generated scenario. The simulated sensor output depends on the objects placed in the virtual environment and the background radiation. Considering the physical sensor dimensions and Planck's radiation law, an approximate image of the reality can be achieved. Thereby, it is possible to simulate pedestrian crash tests, which saves extensive time of testing and enables a fast optimization and adaption of the system
The Pho4 transcription factor mediates the response to arsenate and arsenite in Candida albicans

Arsenate (As (V)) is the dominant form of the toxic metalloid arsenic (As). Microorganisms have consequently developed mechanisms to detoxify and tolerate this kind of compounds. In the present work, we have explored the arsenate sensing and signaling mechanisms in the pathogenic fungus Candida albicans. Although mutants impaired in the Hog1 or Mkc1-mediated pathways did not show significant sensitivity to this compound, both Hog1 and Mkc1 became phosphorylated upon addition of sodium arsenate to growing cells. Hog1 phosphorylation upon arsenate challenge was shown to be Ssk1-dependent. A screening designed for the identification of transcription factors involved in the arsenate response identified Pho4, a transcription factor of the myc-family, as pho4 mutants were susceptible to As (V). The expression of PHO4 was shortly induced in the presence of sodium arsenate in a Hog1-independent manner. Pho4 level affects Hog1 phosphorylation upon As (V) challenge, suggesting an indirect relationship between Pho4 activity and signaling in C. albicans. Pho4 also mediates the response to arsenite as revealed by the fact that pho4 defective mutants are sensitive to arsenite and Pho4 becomes phosphorylated upon sodium arsenite addition. Arsenite also triggers Hog1 phosphorylation by a process that is, in this case, independent of the Ssk1 kinase. These results indicate that the HOG pathway mediates the response to arsenate and arsenite in C. albicans and that the Pho4 transcription factor can differentiate among As (III), As (V) and Pi, triggering presumably specific responses.
Management of Fulminating Ulcerative Colitis in Childhood with Chimeric Anti-CD25 Antibody

Fulminating acute ulcerative colitis (UC) is a potentially life threatening medical emergency. Up to 30% of individuals respond poorly to corticosteroids alone and second line medical or surgical therapies are indicated. We describe the successful use of chimeric anti-CD25 therapy in 4 such children poorly responsive to combined therapy with intravenous steroids and calcineurin inhibitors with a pretreatment predictive risk of colectomy of 85-100%. Clinical disease activity scores normalized within 72 hours of anti-CD25 administration and colonic histology provided evidence of mucosal healing within 10-14 days. None required emergency colectomy. Anti-CD25 is efficacious in fulminating UC and randomized placebo controlled trials appear indicated.
A gradient based method for fully constrained least-squares unmixing of hyperspectral images

Linear unmixing of hyperspectral images is a popular approach to determine and quantify materials in sensed images. The linear unmixing problem is challenging because the abundances of materials to estimate have to satisfy non-negativity and full-additivity constraints. In this paper, we investigate an iterative algorithm that integrates these two requirements into the coefficient update process. The constraints are satisfied at each iteration without using any extra operations such as projections. Moreover, the mean transient behavior of the weights is analyzed analytically, which has never been seen for other algorithms in hyperspectral image unmixing. Simulation results illustrate the effectiveness of the proposed algorithm and the accuracy of the model.
Search for a retrovirus in long‐term cultured cerebrospinal fluid cells and peripheral blood mononuclear cells from patients with multiple sclerosis

Long‐term peripheral blood mononuclear cell (MNC) cultures stimulated with interleukin 2 (IL‐2) or IL‐2 + phytohemagglutinin were established from 33 multiple sclerosis (MS) patients, 9 with other neurological diseases (OND), and 24 normal controls (C). Cultures were analysed for growth characteristics, reverse transcriptase (RT) in the culture medium, 2′‐5′ oligoadenylate synthetase in the cells, and cell morphology. None of these paramenters differed in the MS group compared with the OND and C groups. Furthermore, 11 cerebrospinal fluid cell cultures were established without feeder ceils. Morphology studies of the cells and RT assays of the supernatants from these cultures were normal. Induction studies by dexamethasone and 2‐bromo‐5′‐deoxuridine in 2 of these cultures did not reveal any signs of a virus. The significance of these results for the retrovirus hypothesis is discussed.
A Local, Periactive Zone Endocytic Machinery at Photoreceptor Synapses in Close Vicinity to Synaptic Ribbons

Photoreceptor ribbon synapses are continuously active synapses with large active zones that contain synaptic ribbons. Synaptic ribbons are anchored to the active zones and are associated with large numbers of synaptic vesicles. The base of the ribbon that is located close to l-type voltage-gated Ca2+ channels is a hotspot of exocytosis. The continuous exocytosis at the ribbon synapse needs to be balanced by compensatory endocytosis. Recent analyses indicated that vesicle recycling at the synaptic ribbon is also an important determinant of synaptic signaling at the photoreceptor synapse. To get insights into mechanisms of vesicle recycling at the photoreceptor ribbon synapse, we performed super-resolution structured illumination microscopy and immunogold electron microscopy to localize major components of the endocytotic membrane retrieval machinery in the photoreceptor synapse of the mouse retina. We found dynamin, syndapin, amphiphysin, and calcineurin, a regulator of activity-dependent endocytosis, to be highly enriched around the active zone and the synaptic ribbon. We present evidence for two clathrin heavy chain variants in the photoreceptor terminal; one is enriched around the synaptic ribbon, whereas the other is localized in the entry region of the terminal. The focal enrichment of endocytic proteins around the synaptic ribbon is consistent with a focal uptake of endocytic markers at that site. This endocytic activity functionally depends on dynamin. These data propose that the presynaptic periactive zone surrounding the synaptic ribbon complex is a hotspot of endocytosis in photoreceptor ribbon synapses.
Genetic analyses using a mouse cell cycle mutant identifies magoh as a novel gene involved in Cdk regulation

Many of the genes that control cyclin‐dependent kinase (Cdks) activity have been identified by genetic research using yeast mutants. Suppression analysis and synthetic enhancement analysis are two broad approaches to the identification of genetic interaction networks in yeasts. Here we show, by genetic analyses using a mammalian cell cycle mutant, that mouse magoh is involved in Cdk regulation. Magoh, a homolog of the Drosophila mago nashi gene product, is a component of the splicing‐dependent exon–exon junction complex (EJC). We show that, in addition to ccnb1 and cks2, magoh is also a dosage suppressor of the mouse temperature‐sensitive cdc2 mutant, and synthetic enhancement of the cdc2 ts phenotype by RNA interference (RNAi) of magoh is observed in a manner similar to RNAi of cks2. Moreover, the depletion of magoh by RNAi causes cold‐sensitive defects in the cell cycle transition, and exogenous cks2 expression partially suppresses the defect. Consistent with the genetic evidence, magoh RNAi caused defects in the expression of Cdc2 or Cks proteins, and introns of cks genes strongly affected protein expression levels. Thus, these data suggest that mouse Magoh is related to cell cycle regulation.
Universal growth law for knot energy of Faddeev type in general dimensions

The presence of a fractional-exponent growth law relating knot energy and knot topology is known to be an essential characteristic for the existence of ‘ideal’ knots. In this paper, we show that the energy infimum EN stratified at the Hopf charge N of the knot energy of the Faddeev type induced from the Hopf fibration (n≥1) in general dimensions obeys the sharp fractional-exponent growth law , where the exponent p is universally rendered as , which is independent of the detailed fine structure of the knot energy but determined completely by the dimensions of the domain and range spaces of the field configuration maps.
Assessing the Value of a Quality Assurance Certificate for Software: An Exploratory Investigation

An analysis of the opinions of decision makers who select software for business use indicated that a software quality assurance certificate would add value to and confidence in a software product. Marketing research techniques were used to obtain and analyze data from business users of software. Their problems, anxieties, influences on software choice, the value of a certificate in the choice process, and the importance of auditing the various aspects of the software development process were assessed. The findings indicate that such a certificate would benefit users and demonstrate how marketing research techniques can be applied to assess market acceptability. This study used three market segments and proposed two services to cater to their needs.
Complexion as a soft biometric in human-robot interaction

Complexion plays a remarkably important role in recognition. Experiments with human subjects have shown that complexion provides as much distinctiveness as other well-known features such as the shape of the face. From the perspective an autonomous robot, changes in lighting (e.g., intensity, orientation) and camera parameters (e.g., white balance) can make capturing complexion challenging. In this paper, we evaluate complexion as a soft biometric using color (histograms) and texture (local binary patterns). We train a linear SVM to distinguish between the individual and impostors. We demonstrate the performance of this approach on a database of over 200 individuals collected to study biometrics in human-robot interaction. In our experiment, we identify 9 individuals that interact with the robot on a regular basis, rejecting all others as unknown.
Using the nonparametric curve generator algorithm in H/W acceleration solutions

The paper presents the implementation and an analysis of the Jordan's nonparametric curve generator algorithm in H/W acceleration solutions like sine/cosine generation. It is shown that the x and y coordinate sequences generated by the algorithm as the curve representation are really approximated nonuniform sampled cosine/sine functions sequences of values with useful properties. The nonuniformity of the samples along the curve inherent to the algorithm is analyzed and acknowledged as a drawback in its use for signal generation purposes. An extension of the four points neighbor algorithm that keeps the x and y sequences separate is shown to have promising efficiency in sine/cosine digital signal generation applications. Possible solutions for the correction of the non uniformity problem for practical implementations are presented. A VHDL description of the algorithm was derived, simulated and synthesized in a FPGA with final target H/W acceleration applications. FPGA synthesis efficiency results are compared with classical methods if sine/cosine generation like the CORDIC algorithm.
Modernizing the treatment of venous thoracic outlet syndrome

This study aims to quantify the management and outcomes of patients treated for venous thoracic outlet syndrome (vTOS) over a seven-year period. A retrospective case-note review of all patients undergoing first rib resection at a regional vascular unit between January 1, 2002 and December 31, 2009 was performed. Treatment pathways and outcomes recorded as freedom from symptoms and venous patency were analyzed. Thirty-five patients were identified with vTOS. Ninety-one percent of patients had patent veins at discharge from clinical follow-up and were symptom-free at a median of 44 months. Patients treated within seven days of symptoms (94.7 versus 85.7, P = 0.060), with catheter-directed thrombolysis (94 versus 87.5% P = 0.702) and excision of first rib in less than 30 days (100 versus 85.7%, P = 0.002), had improved symptom-free rates. In conclusion, early referral, immediate catheter-directed thrombolysis, perioperative balloon venoplasty and early thoracic outlet decompression may provide a suitable model for improving outcomes in vTOS.
A novel microarray approach reveals new tissue-specific signatures of known and predicted mammalian microRNAs

Microarrays to examine the global expression levels of microRNAs (miRNAs) in a systematic in-parallel manner have become important tools to help unravel the functions of miRNAs and to understand their roles in RNA-based regulation and their implications in human diseases. We have established a novel miRNA-specific microarray platform that enables the simultaneous expression analysis of both known and predicted miRNAs obtained from human or mouse origin. Chemically modified 2′-O-(2-methoxyethyl)-(MOE) oligoribonucleotide probes were arrayed onto Evanescent Resonance (ER) microchips by robotic spotting. Supplementing the complementary probes against miRNAs with carefully designed mismatch controls allowed for accurate sequence-specific determination of miRNA expression profiles obtained from a panel of mouse tissues. This revealed new expression signatures of known miRNAs as well as of novel miRNAs previously predicted using bioinformatic methods. Systematic confirmation of the array data with northern blotting and, in particular, real-time PCR suggests that the described microarray platform is a powerful tool to analyze miRNA expression patterns with rapid throughput and high fidelity.
Copula Gaussian graphical model for discrete data

Copula Gaussian graphical models are capable of describing dependencies between a large number of heterogeneous variables. In this paper, low-complexity algorithms are proposed for learning copula Gaussian graphical models from discrete data. The proposed approach is Monte-Carlo expectation maximization: in the E-step, an efficient Gibbs sampler is applied, and in the M-step, the sparse graphical model is inferred by solving a penalized maximize likelihood problem. The regularization parameter is determined through the BINCO method proposed by Li et al. Numerical results for both synthetic and real data demonstrate the effectiveness of the proposed approach.