Miracle-dz/UniFAR-FTUs huggingface dataset:
High Throughput Variable Size Non-square Gabor Engine with Feature Pooling Based on GPU

Increasing application of Gabor feature space in various computer vision tasks and its high computational demand, encourages using parallel computing technologies. In this work we have designed a high throughput GPU based Gabor kernel that mimics the function of initial biological visual cortex layers namely ‘Simple’ and ‘Complex’ cells. The kernel is basically a Gabor filter bank with adjustable number of orientations and scales, supporting ‘Non-Square’ and ‘Variable Size’ filter masks on different channels. Consequently our GPU based Gabor kernel tends to be adjustably more accurate, more flexible for different applications, with optimum computational cost at lower resources. The second important task of our high throughput engine is ‘Gabor Feature Pooling’ with Max and Histogram methods, similar to biological visual ‘Complex cells’. This part of our ‘Gabor Engine’ makes it very practical for computer vision applications, since in addition to massive Gabor features, it also provides more abstract spatial invariant orientational information based on image Gabor features. We have optimised the Engine design to take maximum advantage of all GPU parallel resources and maximum bandwidths of all memories.
CAFASP2: The second critical assessment of fully automated structure prediction methods

The results of the second Critical Assessment of Fully Automated Structure Prediction (CAFASP2) are presented. The goals of CAFASP are to (i) assess the performance of fully automatic web servers for structure prediction, by using the same blind prediction targets as those used at CASP4, (ii) inform the community of users about the capabilities of the servers, (iii) allow human groups participating in CASP to use and analyze the results of the servers while preparing their nonautomated predictions for CASP, and (iv) compare the performance of the automated servers to that of the human‐expert groups of CASP. More than 30 servers from around the world participated in CAFASP2, covering all categories of structure prediction. The category with the largest participation was fold recognition, where 24 CAFASP servers filed predictions along with 103 other CASP human groups. The CAFASP evaluation indicated that it is difficult to establish an exact ranking of the servers because the number of prediction targets was relatively small and the differences among many servers were also small. However, roughly a group of five “best” fold recognition servers could be identified. The CASP evaluation identified the same group of top servers albeit with a slightly different relative order. Both evaluations ranked a semiautomated method named CAFASP‐CONSENSUS, that filed predictions using the CAFASP results of the servers, above any of the individual servers. Although the predictions of the CAFASP servers were available to human CASP predictors before the CASP submission deadline, the CASP assessment identified only 11 human groups that performed better than the best server. Furthermore, about one fourth of the top 30 performing groups corresponded to automated servers. At least half of the top 11 groups corresponded to human groups that also had a server in CAFASP or to human groups that used the CAFASP results to prepare their predictions. In particular, the CAFASP‐CONSENSUS group was ranked 7. This shows that the automated predictions of the servers can be very helpful to human predictors. We conclude that as servers continue to improve, they will become increasingly important in any prediction process, especially when dealing with genome‐scale prediction tasks. We expect that in the near future, the performance difference between humans and machines will continue to narrow and that fully automated structure prediction will become an effective companion and complement to experimental structural genomics. Proteins 2001;Suppl 5:171–183. © 2002 Wiley‐Liss, Inc.
Demographic and Welfare State Predictors of Out-of-Pocket Health Expenditures: A Path Analytic Model

ABSTRACT Out-of-pocket (OOP) payments are principal components of financing healthcare and have a significant effect on poverty in numerous developing countries. The present study seeks to ascertain the relation among demographic, welfare state, and OOP health expenditure indicators using a path analysis. National representative household budget data from the Turkish Statistical Institute for 2015 were used. To test the goodness of fit of the model, multiple fit indices were utilized. The model fit for redefined path analytic model data was good (X2/df = 70.20/9 = 7.8; RMSEA = 0.032; GFI = 1.00; AGFI = 0.99; CFI = 0.99). The results of the analysis revealed that demographic and welfare indicators are causally related to OOP health expenditures, and income was a mediating factor for this interrelationship. Designing of socially inclusive policies on the basis of the values of equity is essential to combat poverty due to OOP health expenditures in developing countries.
An Initial Agent Based Model for ! Innovation Ecosystems !

The global economies have been trying various methods of investments in innovation to raise productivity, create jobs and improve life standards. For the same purpose, the United States has long been supporting the foundation of basic research and innovation for technological advances, which generate wealth over time. The productivity gains through technological advancements, labor specialization and innovation have been articulated by evolutionary economists since the middle of the twentieth century [1, 2]. However, it is still open to research how certain innovation ecosystems such as Silicon Valley are extremely productive and grow continuously while other similar systems languish. Therefore it is critical for the national economic well-being to study, understand and more efficiently create the innovation ecosystems. The economic entities in an innovation ecosystem are intertwined such that the success of an innovation depends not only on the innovating entities, but also on the suppliers and consumers of those entities. All of the members of an ecosystem coevolve and the innovations of an entity result in the innovations of others [3]. Over time, the technology space of the ecosystem changes in response to the innovations. In order to reflect these characteristics, we aim to model the innovation ecosystems as non-linear, complex adaptive networks in which economic agents are connected by social networks and compete, cooperate and adapt to each other's needs forming unplanned consequences in the network. The goal of creating such a model is to improve the understanding of innovation ecosystem dynamics using agent-based computational economics to inform policy makers and test policy hypotheses. In this paper, we first explore the state of the art agent-based innovation ecosystem models and work on the compartmentalization of these models. In particular, we classify the models in terms of their simulation methods, objectives and approaches in the adoption of stochastic processes [4, 5]. Then we present our bottom-up approach to create our model and conduct simplistic experiments, whose purpose is to illustrate the initial ideas behind the model framework, rather than to accurately describe the whole innovation ecosystem. As we focus on a system in which the agents interact and compete, we study the basic minimal ecosystem dynamics of our model by comparing its behavior to systems with trophic functions [6, 7]. Overall, this study 1) demonstrates the critical points in innovation ecosystem models including current theoretical and methodological contributions; and 2) identifies the position of our approach in …
A limiting velocity for quarkonium propagation in a strongly coupled plasma via AdS/CFT

We study the dispersion relations of mesons in a particular hot strongly coupled supersymmetric gauge theory plasma. We find that at large momentum k the dispersion relations become ω ≃ v0k+a+b/k+. , where the limiting velocity v0 is the same for mesons with any quantum numbers and depends only on the ratio of the temperature to the quark mass T/mq. We compute a and b in terms of the meson quantum numbers and T/mq. The limiting meson velocity v0 becomes much smaller than the speed of light at temperatures below but close to Tdiss, the temperature above which no meson bound states at rest in the plasma are found. From our result for v0(T/mq), we find that the temperature above which no meson bound states with velocity v exist is Tdiss(v) ≃ (1 − v 2 ) 1/4 Tdiss, up to few percent corrections. We thus confirm by direct calculation of meson dispersion relations a result inferred indirectly in previous work via analysis of the screening length between a static quark and antiquark in a moving plasma. Although we do not do our calculations in QCD, we argue that the qualitative features of the dispersion relation we compute, including in particular the relation between dissociation temperature and meson velocity, may apply to bottomonium and charmonium mesons propagating in the strongly coupled plasma of QCD. We discuss how our results can contribute to understanding quarkonium physics in heavy ion collisions.
Caspofungin Treatment of Aspergillus fumigatus Results in ChsG-Dependent Upregulation of Chitin Synthesis and the Formation of Chitin-Rich Microcolonies

ABSTRACT Treatment of Aspergillus fumigatus with echinocandins such as caspofungin inhibits the synthesis of cell wall β-1,3-glucan, which triggers a compensatory stimulation of chitin synthesis. Activation of chitin synthesis can occur in response to sub-MICs of caspofungin and to CaCl2 and calcofluor white (CFW), agonists of the protein kinase C (PKC), and Ca2+-calcineurin signaling pathways. A. fumigatus mutants with the chs gene (encoding chitin synthase) deleted (ΔAfchs) were tested for their response to these agonists to determine the chitin synthase enzymes that were required for the compensatory upregulation of chitin synthesis. Only the ΔAfchsG mutant was hypersensitive to caspofungin, and all other ΔAfchs mutants tested remained capable of increasing their chitin content in response to treatment with CaCl2 and CFW and caspofungin. The resulting increase in cell wall chitin content correlated with reduced susceptibility to caspofungin in the wild type and all ΔAfchs mutants tested, with the exception of the ΔAfchsG mutant, which remained sensitive to caspofungin. In vitro exposure to the chitin synthase inhibitor, nikkomycin Z, along with caspofungin demonstrated synergistic efficacy that was again AfChsG dependent. Dynamic imaging using microfluidic perfusion chambers demonstrated that treatment with sub-MIC caspofungin resulted initially in hyphal tip lysis. However, thickened hyphae emerged that formed aberrant microcolonies in the continued presence of caspofungin. In addition, intrahyphal hyphae were formed in response to echinocandin treatment. These in vitro data demonstrate that A. fumigatus has the potential to survive echinocandin treatment in vivo by AfChsG-dependent upregulation of chitin synthesis. Chitin-rich cells may, therefore, persist in human tissues and act as the focus for breakthrough infections.
The Importance of Physical Activity in the Protection of the Mental Health of Students of Faculty of Sport Sciences

The purpose of the present research is determining the psychological symptoms observed among the students of the Faculty of Sports Sciences and to define the effects of physical activity on the mental health of the students. The sample of the research consists of 222 volunteer students (n=75 female and n=147 male) who study at Adnan Menderes University Faculty of Sports Sciences in 2017-2018 Academic Year. International Physical Activity Questionnaire (IPAQ) was used to define the physical activity levels of students and Symptom Distress Check List (SCL-90-R) was used to define the psychological symptoms of the students. SPSS 22.0 package program was used for the statistical analysis of the data collected for the present research. According to the findings of the statistical analyses, the most frequent psychological symptoms observed among students respectively were obsessive-compulsive symptoms (70.3%, n=156), paranoid thoughts (63.1%, n=140), interpersonal sensitivity (51.8%, n=115) and anger hostility (51.4%, n=114). It was also found that there was a significant negative correlation between the physical activity levels of the students and general symptom averages and the psychological symptoms such as obsessive-compulsive symptoms, depression, anxiety, anger hostility at 0.01 level (p>0.05). According to the findings of the present research, symptoms, such as obsessive-compulsive symptoms, paranoid thoughts, interpersonal sensitivity and anger hostility are observed, and general symptom average was high among students of Faculty of Sports Sciences and psychological symptoms such as obsessive-compulsive symptoms, depression, anxiety, anger hostility, phobic reaction decreased as the physical activity level of the students increased. Psychological symptoms other than psychotics were mostly among female students. Participation in meditation, yoga, music therapy, exercise and physical activity programs as well as applied lessons in the curriculum can contribute to the prevention of mental problems among students with these symptoms.
Signals on Pencils of Lines

This paper proposes the "epipolar pencil transformation" (EPT). This is a tool for comparing the signals in different images, with no use of feature detection, yet taking advantage of the constraints given by epipolar geometry. The idea is to develop a descriptor for each point, summarizing the signals on the pencil of lines intersecting at that point. To compute the EPT, first find compact descriptors for each line, then combine these appropriately for each pencil. Given the EPT for two images, computing the epipolar geometry reduces to a closest pairs problem- select one pencil from each set such that the L1 distance (in descriptor space) is minimized. By this reduction to a high dimensional closest pairs problem, recent advances in computational geometry can be used to efficiently identify the best global solution. This technique is robust, as each potential solution is evaluated by comparing the signals for all the lines passing through the two hypothesized epipoles. At the same time, as the closest pairs algorithm performs a global search, the solution is not distracted by local minima. The EPT is used here both for the problem of two-view rigid motion, and many-view place recognition.
Permanent Cardiac Sarcomere Changes in a Rabbit Model of Intrauterine Growth Restriction

Background Intrauterine growth restriction (IUGR) induces fetal cardiac remodelling and dysfunction, which persists postnatally and may explain the link between low birth weight and increased cardiovascular mortality in adulthood. However, the cellular and molecular bases for these changes are still not well understood. We tested the hypothesis that IUGR is associated with structural and functional gene expression changes in the fetal sarcomere cytoarchitecture, which remain present in adulthood. Methods and Results IUGR was induced in New Zealand pregnant rabbits by selective ligation of the utero-placental vessels. Fetal echocardiography demonstrated more globular hearts and signs of cardiac dysfunction in IUGR. Second harmonic generation microscopy (SHGM) showed shorter sarcomere length and shorter A-band and thick-thin filament interaction lengths, that were already present in utero and persisted at 70 postnatal days (adulthood). Sarcomeric M-band (GO: 0031430) functional term was over-represented in IUGR fetal hearts. Conclusion The results suggest that IUGR induces cardiac dysfunction and permanent changes on the sarcomere.
Video retrieval based on video motion tracks of moving objects

Motion track is an important feature to show the spatio-temporal relationship of a video object in a video. In this paper, we propose a novel motion track representation based on MPEG-7 motion descriptor. A new descriptor is proposed to represent the motion track in the X-Y plane and the trend of velocity changes. Moreover, a new similarity measure for comparing two motion tracks based on the motion trajectory and velocity differences is proposed. The trajectory is compared by the properties of the polynomials, and the velocity is compared by the different trends. Furthermore, the motion track segmentation method is proposed to handle a complicated motion behavior and the relevance feedback is used to improve the query results. Experiment results show that this approach has a higher precision than existing approaches.
Bug fix-time prediction model using naïve Bayes classifier

Predicting bug fix-time is an important issue in order to assess the software quality or to estimate the time and effort needed during the bug triaging. Previous work has proposed several bug fix-time prediction models that had taken into consideration various bug report attributes (e.g. severity, number of developers, dependencies) in order to know which bug to fix first and how long it will take to fix it. Our aim is to distinguish the very fast and the very slow bugs in order to prioritize which bugs to start with and which to exclude at the mean time respectively. We used the data of four systems taken from three large open source projects Mozilla, Eclipse, Gnome. We used naïve Bayes classifier to compute our prediction model.
Inter-cell Interference and Frequency Reuse in Heterogeneous Networks

In heterogeneous networks, small cell base stations are deployed overlaid on the existing macro cells to offload network traffic, optimize coverage and improve the overall network capacity. Due to the disparity in cell sizes, the existing intra-tier inter-cell interference management (among macro cells) mechanisms will not be effective for the inter-tier inter-cell interference management (between macro and small cells). As a result, the full potential of frequency reuse gained by deploying small cells will be diminished. We propose a mechanism to analyze the inter-tier interference in terms of frequency reusability.
Is there a tradeoff between programmability and performance?

While the computational power of Field Programmable Gate Arrays (FPGA) makes them attractive as code accelerators, the lack of high-level language programming tools is a major obstacle to their wider use. Graphics Processing Units (GPUs), on the other hand, have benefitted from advanced and widely used high-level programming tools. This paper evaluates the performance, throughput and energy of both FPGAs and GPUs on image processing codes using high-level language programming tools for both.
Investigation of the Growth Ability of Probiotic (Lactobacillus and Bifidobacterium) in Infant’s Milk under Different Environmental Conditions

In the present investigation five species of probiotic bacteria, which belong to Lactobacillus (L. reautari, L. rhamnosus, L. acidophilus), Bifidobacterium (L. casei, L. helveticus, B. bifidum) were evaluated for their growth in dried infant’s milk. Three kinds of milk which is used for healthy infants and two other kinds which are widely spread and commonly used for unhealthy breastfeeding infants (vomiting and diarrhea). The study has clearly indicated that all the probiotics employed in this investigation have grown in all milk types to which the nutrient MRS medium was added as well as for the tested milk types without any additives. Findings showed that the optimal time period for adequate growth of probiotic ranges from 12 to 24 hours. Furthermore, it was found that during incubation period of the tested probiotics the pH was in the range of 7.20 to 7.87 for all the milk types tested. It was generally observed that changes in pH were meager during the first 8 hours after incubation and then pH started to decrease reaching a value of d” 4 with the increase in growth until the end of incubation period (i-e, 72 hours). The current results also showed that the optimal temperature for adequate growth of probiotics investigated is 37 oC whereas the least temperature is 5 oC. Variation in pH had a limiting effect on bacterial growth. Results showed that the best probiotic growth was detected at pH 6 and the least growth was at pH 11. Furthermore, the maximum growth levels at 55% relative humidity, except L. helveticus bacteria for which the highest growth rate was recorded at 75% RH and growth of the tested probiotics was decreased at RH of 35% and 100%.
Annexin A1 released from apoptotic cells acts through formyl peptide receptors to dampen inflammatory monocyte activation via JAK/STAT/SOCS signalling

The immunosuppressive effects of apoptotic cells involve inhibition of pro‐inflammatory cytokine release and establishment of an anti‐inflammatory cytokine profile, thus limiting the degree of inflammation and promoting resolution. We report here that this is in part mediated by the release of the anti‐inflammatory mediator annexin A1 from apoptotic cells and the functional activation of annexin A1 receptors of the formyl peptide receptor (FPR) family on target cells. Supernatants from apoptotic neutrophils or the annexin A1 peptidomimetic Ac2‐26 significantly reduced IL‐6 signalling and the release of TNF‐α from endotoxin‐challenged monocytes. Ac2‐26 activated STAT3 in a JAK‐dependent manner, resulting in upregulated SOCS3 levels, and depletion of SOCS3 reversed the Ac2‐26‐mediated inhibition of IL‐6 signalling. This identifies annexin A1 as part of the anti‐inflammatory pattern of apoptotic cells and links the activation of FPRs to established signalling pathways triggering anti‐inflammatory responses.
CONSISTENT ORDER ESTIMATION AND THE LOCAL GEOMETRY OF MIXTURES

Consider an i.i. d. sequence of random variables whose distr ibution f lies in one of a nested family of models (Mq)q∈N,Mq ⊂ Mq+1. The smallest index q such thatMq⋆ containsf is called the model order. We establish strong consistency of the penalized likelihood order estim ator in a general setting with penalties of order η(q) log log n, whereη(q) is a dimensional quantity. Moreover, such penalties are shown to be minimal. In contrast to previous work, an a priori upper bound on the model order is no t assumed. The local dimensionη(q) of the modelMq is defined in terms of the bracketing entropy of a class of weighted densities, whose c mputation is a nonstandard problem which is of independent interest. We pe rform the requisite computations for the case of one-dimensional locati n mixtures, thus demonstrating the consistency of the penalized likelihood mixture order estimator. The proof requires a delicate analysis of the local geometry of the mixture familyMq in a neighborhood of , for q > q. The extension to more general mixture models remains an open problem.
A NEW CONCURRENCY CONTROL ALGORITHM IN TEMPORAL DATABASE

The large number of applications manages time varying data. Existing database technology seldom supports temporal database, TDB, according to time aspects. These intrinsic temporal database applications rely on such database which stores and retrieves time referenced data. Moreover, applications need to be managed on common data items access simultaneously and to be precluded from inconsistency as soon as possible which is the main task of concurrency controller or CC in short. The method used by CC in typical DB differs from its attitude with TDB. The variety algorithms were proposed regarding to TDB properties by reduction of granule size and decreasing the rate of conflicts to satisfy good performance, but none of them has achieved robust results. There are two categories of CC such as pessimistic and optimistic. In this paper new approach, with considering the TDB aspects, based on optimistic method has been suggested. It reclines the size of granule as data item appropriately and recognizes the conflicts swiftly. Consequently, we compare our proposed algorithm with pervasive 2PL-pessimistic approach. The outcome shows that new proposed algorithm has high degree of trade off with satisfying near conflict time detection and high rate of parallelism metrics.