Miracle-dz/UniFAR-FTUs huggingface dataset:
On server-side file access pattern matching

In this paper, we propose a pattern matching approach for server-side access pattern detection for the HPC I/O stack. More specifically, our proposal concerns file-level accesses, such as the ones made to I/O libraries, I/O nodes, and the parallel file system servers. The goal of this detection is to allow the system to adapt to the current workload. Compared to existing detection techniques, ours differ by working at run-time and on the server side, where detailed application information is not available since HPC I/O systems are stateless, and without relying on previous traces. We build a time series to represent accesses spatiality, and use a pattern matching algorithm, in addition to an heuristic, to compare it to known patterns. We detail our proposal and evaluate it with two case studies – situations where detecting the current access pattern is important to select the best scheduling algorithm or to tune a fixed algorithm parameter. We show our approach has good detection capabilities, with precision of up to 93% and recall of up to 99%, and discuss all design choices.
Sensor Based Cyber Attack Detections in Critical Infrastructures Using Deep Learning Algorithms

The technology that has evolved with innovations in the digital world has also caused an increase in many security problems. Day by day the methods and forms of the cyber-attacks began to become complicated, and therefore their detection became more difficult. In this work we have used the datasets which have been prepared in collaboration with Raymond Borges and Oak Ridge National Laboratories. These datasets include measurements of the Industrial Control Systems related to chewing attack behavior. These measurements include synchronized measurements and data records from Snort and relays with the simulated control panel. In this study, we developed two models using this datasets. The first is the model we call the DNN Model which was build using the latest Deep Learning algorithms. The second model was created by adding the AutoEncoder structure to the DNN Model. All of the variables used when developing our models were set parametrically. A number of variables such as activation method, number of hidden layers in the model, the number of nodes in the layers, number of iterations were analyzed to create the optimum model design. When we run our model with optimum settings, we obtained better results than related studies. The learning speed of the model has 100\% accuracy rate which is also entirely satisfactory. While the training period of the dataset containing about 4 thousand different operations lasts about 90 seconds, the developed model completes the learning process at the level of milliseconds to detect new attacks. This increases the applicability of the model in real world environment.
mTORC2 Regulates Lipogenic Gene Expression through PPARγ to Control Lipid Synthesis in Bovine Mammary Epithelial Cells

The mechanistic target of rapamycin complex 2 (mTORC2) primarily functions as an effector of insulin/PI3K signaling to regulate cell proliferation and is associated with cell metabolism. However, the function of mTORC2 in lipid metabolism is not well understood. In the present study, mTORC2 was inactivated by the ATP-competitive mTOR inhibitor AZD8055 or shRNA targeting RICTOR in primary bovine mammary epithelial cells (pBMECs). MTT assay was performed to examine the effect of AZD8055 on cell proliferation. ELISA assay and GC-MS analysis were used to determine the content of lipid. The mRNA and protein expression levels were investigated by RT/real-time PCR and western blot analysis, respectively. We found that cell proliferation, mTORC2 activation, and lipid secretion were inhibited by AZD8055. RICTOR was knocked down and mTORC2 activation was specifically attenuated by the shRNA. Compared to control cells, the expression of the transcription factor gene PPARG and the lipogenic genes LPIN1, DGAT1, ACACA, and FASN was downregulated in RICTOR silencing cells. As a result, the content of intracellular triacylglycerol (TAG), palmitic acid (PA), docosahexaenoic acid (DHA), and other 16 types of fatty acid was decreased in the treated cells; the accumulation of TAG, PA, and DHA in cell culture medium was also reduced. Overall, mTORC2 plays a critical role in regulating lipogenic gene expression, lipid synthesis, and secretion in pBMECs, and this process probably is through PPARγ. This finding provides a model by which lipogenesis is regulated in pBMECs.
Doing it differently: emancipatory autism studies within a neurodiverse academic space

Abstract In the current research climate, in which many autistic and autism communities are increasingly calling for a move towards collaborative forms of research, we consider how a loosely formed epistemological community may serve to challenge ‘business as usual’ in the academy. Mindful of the need to move beyond theory, we use this experience to concretely consider how knowledge about autism and neurotypicality can be meaningfully (co)-produced, and made available both to the research community and also to autistic and autism communities. Here, we use our own co-production of this article to explore how autistic experience may trouble normative meanings of academic knowledge production. We also consider the limits and possibilities of a neurodiverse research collaboration to reflect on ways in which a loose epistemological space may serve to contribute to knowledge about both autism and neurotypicality, adding to debate around collaborative research.
Muscle activation mapping of skeletal hand motion : an evolutionary approach

Creating controlled dynamic character animation consists of mathe- matical modelling of muscles and solving the activation dynamics that form the key to coordination. But biomechanical simulation and control is com- putationally expensive involving complex di erential equations and is not suitable for real-time platforms like games. Performing such computations at every time-step reduces frame rate. Modern games use generic soft- ware packages called physics engines to perform a wide variety of in-game physical e ects. The physics engines are optimized for gaming platforms. Therefore, a physics engine compatible model of anatomical muscles and an alternative control architecture is essential to create biomechanical charac- ters in games. This thesis presents a system that generates muscle activations from captured motion by borrowing principles from biomechanics and neural con- trol. A generic physics engine compliant muscle model primitive is also de- veloped. The muscle model primitive forms the motion actuator and is an integral part of the physical model used in the simulation. This thesis investigates a stochastic solution to create a controller that mimics the neural control system employed in the human body. The control system uses evolutionary neural networks that evolve its weights using genetic algorithms. Examples and guidance often act as templates in muscle training during all stages of human life. Similarly, the neural con- troller attempts to learn muscle coordination through input motion samples. The thesis also explores the objective functions developed that aids in the genetic evolution of the neural network. Character interaction with the game world is still a pre-animated behaviour in most current games. Physically-based procedural hand ani- mation is a step towards autonomous interaction of game characters with the game world. The neural controller and the muscle primitive developed are used to animate a dynamic model of a human hand within a real-time physics engine environment.
The Importance of Mesozooplankton Diel Vertical Migration for Sustaining a Mesopelagic Food Web

We used extensive ecological and biogeochemical measurements obtained from quasi-Lagrangian experiments during two California Current Ecosystem Long-Term Ecosystem Research cruises to analyze carbon fluxes between the epipelagic and mesopelagic zones using a linear inverse ecosystem model (LIEM). Measurement constraints on the model include 14C primary productivity, dilution-based microzooplankton grazing rates, gut pigment-based mesozooplankton grazing rates (on multiple zooplankton size classes), 234Th:238U disequilibrium and sediment trap measured carbon export, and metabolic requirements of micronekton, zooplankton, and bacteria. A likelihood approach (Markov Chain Monte Carlo) was used to estimate the resulting flow uncertainties from a sample of potential flux networks. Results highlight the importance of mesozooplankton active transport (i.e., diel vertical migration) for supplying the carbon demand of mesopelagic organisms and sequestering carbon dioxide from the atmosphere. In nine water parcels ranging from a coastal bloom to offshore oligotrophic conditions, mesozooplankton active transport accounted for 18% - 84% (median: 42%) of the total carbon supply to the mesopelagic, with gravitational settling of POC (12% - 55%; median: 37%) and subduction (2% - 32%; median: 14%) providing the majority of the remainder. Vertically migrating zooplankton contributed to downward carbon flux through respiration and excretion at depth and via consumption loses to predatory zooplankton and mesopelagic fish (e.g. myctophids and gonostomatids). Sensitivity analyses showed that the results of the LIEM were robust to changes in nekton metabolic demands, rates of bacterial production, and mesozooplankton gross growth efficiency. This analysis suggests that prior estimates of zooplankton active transport based on conservative estimates of standard (rather than active) metabolism should be revisited. Contribution to the Field Understanding the flows of carbon within the ocean is important for predicting how global climate will shift; yet even after decades of research, the magnitude with which the ocean sequesters carbon is highly uncertain. One reason behind this uncertainty is that a variety of mechanisms control the balance between carbon input and carbon output within the ocean. The topic of this work is to inspect the role of biological organisms in physically transferring organic carbon from the surface to the deep ocean. As opposed to other mechanisms—such as sinking particles, the biological transfer of carbon is difficult to measure directly and is often quite variable, leading to large uncertainties. Here we use an extensive set of in situ observations off the coast of southern California to model the flow of carbon through the ecosystem. The model determined that in our study area nearly half of the total transfer of carbon from the surface ocean to deep was carried out by zooplankton that swim up to the surface each night to feed. This finding has direct implications for global carbon budgets, which often underestimate this transfer of carbon.
The effect of titanium dioxide nanoparticles on mice midbrain substantia nigra

Objective(s): Widely used Titanium dioxide nanoparticles (TiO2) enter into the body and cause various organ damages. Therefore, we aimed to study the effect of TiO2 on the substantia nigra of midbrain. Materials and Methods: 40 male BALB/c mice were randomly divided into five groups: three groups received TiO2 at doses of 10, 25, and 50 mg/kg, the fourth group received normal saline for 45 days by gavage, and control group (without intervention). Then, Motor tests including pole and hanging tests were done to investigate motor disorders. The animal brain was removed for histological purposes. Accordingly, immunohistochemistry was performed to detect tyrosine hydroxylase positive cells, and then toluidine blue staining was done to identify dark neurons in the substantia nigra. Eventually, the total number of these neurons were counted using stereological methods in different groups. Results: The results showed that the time recorded for mice to turn completely downward on the pole in the TiO2-50 group increased and also the time recorded for animals to hang on the wire in the hanging test significantly decreased (P<0.05) in comparison with other groups. Also, the average number of tyrosine hydroxylase positive neurons in TiO2-25 and TiO2-50 groups significantly decreased as compared to the TiO2-10 and control groups (P<0.05). The total number of dark neurons in the TiO2-25 and TiO2-50 groups was substantially higher than the TiO2-10, control and normal saline groups (P<0.05). Conclusion: Our findings indicated that TiO2, depending on dose, can cause the destruction of dopaminergic neurons and consequently increase the risk of Parkinson’s disease.
Review Blockinarticle

The visual system is the most studied part of the cortex, providing a basis for understanding not only visual processing per se but also the fundamental operations of the brain in general. Significant progress has been made in understanding neural structures sensitive to different visual attributes such as form, surface brightness, color and motion. Here, the basic neural structures and processing pathways for these visual features are reviewed. Dysfunctions in these processing pathways lead to deficits in the perception of different aspects of a visual object. In recent years, there is a growing interest in applying accumulated knowledge in vision science to investigate altered neural structures and abnormal perceptual processing observed in neurological disorders. Key issues and clinical studies are also discussed within the context of visual feature processing.
Application of Neural Networks for Routing Problems

The thesis deals with the Traveling Salesman Problem in a polygonal domain using Self Organizing Maps. The task is transformed to the Traveling Salesman Problem in the Euclidean space of a higher dimension by the technique of the multidimensional scaling. Then it is solved using Self Organizing Maps procedures. Another method is based on the new nonEuclidean form of Self Organizing Maps, which was derived theoretically and implemented subsequently. Both methods were numerically compared concerning the speed of computation and the quality of solutions with various settings of parameters.
Bioequivalence of paclitaxel protein-bound particles in patients with breast cancer: determining total and unbound paclitaxel in plasma by rapid equilibrium dialysis and liquid chromatography–tandem mass spectrometry

Background and objective: Paclitaxel protein-bound particles for injectable suspension (nab-paclitaxel) showed many advantages in safety, effectiveness, and convenience. Different from conventional formulations, the bioequivalence evaluation of nab-paclitaxel formulations requires to determine the total amount of paclitaxel in plasma and the unbound paclitaxel to reflect their in vivo disposition. This study aimed to develop an analytical method to quantify the total and unbound paclitaxel in plasma and evaluate the bioequivalence of two formulations of nab-paclitaxel in patients with breast cancer. Materials and methods: An open-label, randomized, two-period crossover study was completed among 24 Chinese patients with breast cancer. The patients were randomized to receive either the test formulation on cycle 1 day 1 and after 21 days in cycle 2 day 1 by the reference formulation (Abraxane®), or vice versa. Rapid equilibrium dialysis was adopted to separate the unbound paclitaxel in human plasma. Total and unbound paclitaxel concentrations were measured by the validated liquid chromatography–tandem mass spectrometry methods over the range of 5.00–15,000 and 0.200–200 ng/mL, respectively. The bioequivalence of the test formulation to the reference formulation was assessed using the Food and Drug Administration and European Medicines Agency guidelines. Results: All the 90% confidence intervals (CIs) of the geometric mean ratios fell within the predetermined acceptance range. The 90% CIs for the area under the concentration–time curve (AUC) from 0 h to 72 h (AUC0–t), AUC from time zero to infinity (AUC0–∞), and peak plasma concentrations (Cmax) for total paclitaxel were 92.03%–98.05%, 91.98%–99.37%, and 91.37%–99.36%, respectively. The 90% CIs of AUC0–t, AUC0–∞, and Cmax for unbound paclitaxel were 86.77%–97.88%, 86.81%–97.88%, and 87.70%–98.86%, respectively. Conclusion: Bioequivalence between the two nab-paclitaxel formulations was confirmed for total and unbound paclitaxel at the studied dose regimen.
The Modifying Effect of General and Regional Anesthesia on the Endocrine-metabolic Response to Surgery

The modifying effect of anesthetic procedures on the endocrine-metabolic response to surgery is reviewed. Administration of intravenous or volatile agents in normal “low” doses has no major effect on endocrine-metabolic parameters in themselves or on the surgically induced metabolic changes. In contrast, “high-dose” opiate anesthesia or administration of volatile agents at high minimum alveolar concentration (MAC) values suppress the intraoperative endocrine-metabolic response to surgery but without a persistent effect on postoperative responses or on nitrogen balance. Regional anesthesia prevents a predominant part of the endocrine-metabolic response to surgery, and postoperative nitrogen balance is improved. This inhibitory effect of neurogenic blockade (combined afferent blockade of stimuli from the surgical area and blockade of efferent pathways to the adrenal medulla) on the surgically induced endocrine-metabolic changes is most consistent during lower abdominal surgery and operations on the lower extremities. During upper abdominal surgery, regional anesthesia has a lesser modifying influence on the stress response, probably because of insufficient afferent blockade. Epidural administration of opiates has no influence on the intraoperative stress response, but partially inhibits the normal postoperative increase in plasma cortisol and glucose. Posttraumatic application of regional anesthesia prevents further amplification of the stress response. Future studies should consider the influence of regional anesthesia on the stress response during major abdominal surgery, the relative importance of sensory analgesia versus blockade of sympathetic afferent and efferent pathways. Existing data should lead to randomized clinical studies on the effect of regional anesthesia on postoperative morbidity, based upon the hypothesis that inhibition of the surgically induced endocrine-metabolic response will reduce postoperative morbidity.
Simultaneous screening of antibiotic residues in honey by biochip multi-array technology

The existence of antibiotic residues in food causes serious health problems in humans. This study aims to determine antibiotic residues in honey intended for consumption. Evidence Investigator™ Biochip Array technology enables simultaneous quantitative detection of multiple analytes on a single sample. The Anti Microbial Array IV test kit is used in simultaneously detecting the quantity of 12 different groups of antimicrobials in honey samples. A competitive chemiluminescent immunoassay was employed for the detection of antimicrobials. The light signal produced from each test region on the biochip was detected using digital imaging technology. In this study, a total of 45 honey samples including 5 brands of honey and 40 local honey were analyzed. The honey samples were simultaneously screened for 12 different types of antibiotic residues by using the Evidence Investigator™ Anti Microbial Array IV test kit. In the honey samples examined, residues of erythromycin, streptomycin, amikacin, lincosamides, tylosin B and neomycin were detected. 91% of samples involved erythromycin residues whereas 15% of the local samples included streptomycin residues above the recommended concentration.
ISLAMIC BANKING AND ECONOMIC GROWTH: APPLYING THE CONVENTIONAL HYPOTHESIS

Growth in Islamic banking has gained lot of interest and attention during last fewyears. The debate currently shifts from theoretical to empirical framework. Thegrowth in empirical work has given rise to a new concept, which can be called as“Islamic banking development” (IBD). It will be interesting to test nexus betweenIBD and growth, since literature suggests a positive result for conventionalfinance and growth. Our study uses a panel of 24 countries for a period of 11years using annual data (2004-2014) to test conventional hypothesis of supplyleading or demand following between IBD and growth. In addition, we alsoinvestigate direction of causality in a panel setting between the two. Apart fromthe topic, this paper differs from existing limited literature, on the basis of datasetused and the estimation procedure to assess the nexus. Our results suggest thatIBD affect growth positively. Comprehensive tests suggest the presence of a longrun relationship between IBD and growth. Moreover, the direction of causalityseems to follow supply leading hypothesis: IBD affects economic growth, and thatevidence on a reverse causality was not found. This is true, even when we controlfor CFD.
Molecular flux control encodes distinct cytoskeletal responses by specifying SRC signaling pathway usage

Multi-domain signaling proteins sample numerous stimuli to coordinate distinct cellular responses. Understanding the mechanisms of their pleiotropic signaling activity requires to directly manipulate their activity of decision leading to distinct cellular responses. We developed an optogenetic probe, optoSRC, to control spatio-temporally the SRC kinase, a representative example of versatile signaling node, and challenge its ability to generate different cellular responses. Genesis of different local molecular fluxes of the same optoSRC to adhesion sites, was sufficient to trigger distinct and specific acto-adhesive responses. Collectively, this study reveals how hijacking the pleiotropy of SRC signaling by modulating in space and time subcellular molecular fluxes of active SRC kinases.
Sistemas de hipermedia adaptativa en un entorno educativo: generalidades y tendencias II

Resumen En este trabajo se expone la evolucion que han tenido los sistemas educacionales virtuales y en particular los sistemas de hipermedia adaptativa en un entorno educativo (SHAE). Se realiza un acercamiento a sus caracteristicas esenciales, y a las ventajas y desventajas de otros sistemas; para ello, se ha seguido un orden logico-historico. Por otro lado, se ha profundizado en aspectos tales como la arquitectura general del sistema, los criterios de clasificacion de los SHAE desde diferentes perspectivas, la aplicabilidad de sus modelos, los metodos de adaptacion, el objeto de la adaptacion, los prerrequisitos de utilizacion, la integracion de la informacion, la integracion alumno- adaptacion, la creacion de hiperdocumentos, la historia de la navegacion, la informacion contextual, el modelo del alumno (MA), la construccion del MA, los ejemplos de MA en diferentes propuestas y el ciclo de vida de un SHAE. Este articulo puede ser de ayuda para los docentes y desarrolladores de cursos virtuales, pues muestra una fundamentacion teorica de los elementos mas importantes que caracterizan un SHAE. palabras clave: hipermedia adaptativa, sistemas e-learning. Abstract The present paper deals with the evolution of virtual educational systems, especially those of fitting hypermedia in an educational environment (SHAE). Its main features are also shown, as well as other systems´ advantages and disadvantages. A logical historical order has been used to this end. In addition, the paper goes deeper into other aspects, such as system´s general architecture, SHAE classification criteria from different perspectives, relevancy of its models, accommodation methods, accommodation object, usage requisites, integration of information, student-accommodation integration, creation of hyper documents, navigation history, context information, student´s model (MA), creation of MA, examples of MA in different SHAE´s proposals and life cycle. This article can be of help for teachers and creators of virtual courses, for it shows a theorical base of the most important elements that characterize a SHAE. keywords: fitting hypermedia, e-learning systems.