Miracle-dz/UniFAR-FTUs huggingface dataset:
Serum Procalcitonine Levels as an Early Diagnostic Indicator of Sepsis

Introduction: Prompt and accurate diagnosis of sepsis is of high importance for clinicians. Procalcitonine (PCT) and C-reactive protein (CRP) have been proposed as markers for this purpose. Our aim was to evaluate the levels of PCT and CRP in early sepsis and its correlation with severity of sepsis. Methods: Levels of PCT and CRP were taken from 60 patients with sepsis criteria and 39 patients with SIRS symptoms from the University Hospital Center “Mother Teresa” in Tirana, Albania during 2010-2012. Sensitivity, specificity and predictive values for PCT and CRP were calculated. Results: PCT and CRP levels increased in parallel with the severity of the clinical conditions of the patients. The mean PCT level in patients with sepsis was 11.28 ng/ml versus 0.272 ng/ml in patients with SIRS symptoms, with a sensitivity of 97.4% and a specificity of 96.6% for PCT >0.5ng/ml. The mean CRP level in septic patients was 146.58 mg/l vs. 34.4 mg/l in patients with SIRS, with a sensitivity of 98.6% for sepsis and a specificity of 75 % for CRP >11mg/l. Conclusion: PCT and CRP values are useful markers to determine early diagnosis and severity of an infection. In the present study, PCT was found to be a more accurate diagnostic parameter for differentiating SIRS from sepsis and may be helpful in the follow-up of critically ill patients.
Data Allocation and Dynamic Load Balancing for Distributed Video Storage Server

In this paper, a novel initial videos allocation scheme and a dynamic load balancing strategy are proposed for a distributed video storage server in order to increase the availability and reduce operation cost. The initial allocation scheme determines the allocation of video replicas on the servers to achieve static load balance and to obtain a configuration for efficient dynamic load adjustment. From the simulation results, the proposed load shifting algorithm can reduce up to 50% request fail rate if compared with the same initialization algorithm without load shifting. The proposed initial allocation with load shifting also reduces 25% to 60% request fail rate from the least load first initial allocation scheme with load shifting, 5% to 10% request fail rate and 5% to 25% the number of shifting steps from the DASD dancing method. Moreover, a prototype is implemented on Windows NT to examine the correctness and practicability of the proposed schemes.
Run-time dynamic linking for reprogramming wireless sensor networks

From experience with wireless sensor networks it has become apparent that dynamic reprogramming of the sensor nodes is a useful feature. The resource constraints in terms of energy, memory, and processing power make sensor network reprogramming a challenging task. Many different mechanisms for reprogramming sensor nodes have been developed ranging from full image replacement to virtual machines.We have implemented an in-situ run-time dynamic linker and loader that use the standard ELF object file format. We show that run-time dynamic linking is an effective method for reprogramming even resource constrained wireless sensor nodes. To evaluate our dynamic linking mechanism we have implemented an application-specific virtual machine and a Java virtual machine and compare the energy cost of the different linking and execution models. We measure the energy consumption and execution time overhead on real hardware to quantify the energy costs for dynamic linkin.Our results suggest that while in general the overhead of a virtual machine is high, a combination of native code and virtual machine code provide good energy efficiency. Dynamic run-time linking can be used to update the native code, even in heterogeneous networks.
The Decoding Toolbox (TDT): a versatile software package for multivariate analyses of functional imaging data

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce The Decoding Toolbox (TDT) which represents a user-friendly, powerful and flexible package for multivariate analysis of functional brain imaging data. TDT is written in Matlab and equipped with an interface to the widely used brain data analysis package SPM. The toolbox allows running fast whole-brain analyses, region-of-interest analyses and searchlight analyses, using machine learning classifiers, pattern correlation analysis, or representational similarity analysis. It offers automatic creation and visualization of diverse cross-validation schemes, feature scaling, nested parameter selection, a variety of feature selection methods, multiclass capabilities, and pattern reconstruction from classifier weights. While basic users can implement a generic analysis in one line of code, advanced users can extend the toolbox to their needs or exploit the structure to combine it with external high-performance classification toolboxes. The toolbox comes with an example data set which can be used to try out the various analysis methods. Taken together, TDT offers a promising option for researchers who want to employ multivariate analyses of brain activity patterns.
Relay Node Position Optimization in Complex Environment

Environment has an essential effect on the selection of relay node positions. Real application environment of Wireless Sensor Networks usually is complex and heterogeneous where wireless channel has different characteristics at different locations. In network deployment, the environment also constrains relay node locations. There are areas unfeasible for node deployment. This paper studies the relay node placement problem in such complex environment. Our target of relay node position optimization is to minimize the relay node number and improve network performance by optimizing route paths of sensor nodes. Heuristic operations for genetic algorithms are proposed to optimize relay node positions. Simulation results show that the relay nodes number of the proposed algorithm is less than that of 2-approximation Steiner tree algorithm and the route paths of selected relay nodes have almost the best cost among route paths of all feasible relay nodes.
mmdump: a tool for monitoring internet multimedia traffic

Internet multimedia traffic is increasing as applications like streaming media and packet telephony grow in popularity. It is important to monitor the volume and characteristics of this traffic, particularly because its behavior in the face of network congestion differs from that of the currently dominant TCP traffic. To monitor traffic on a high-speed link for extended periods, it is not practical to blindly capture all packets that traverse the link. We present mmdump, a tool that parses messages from RTSP, H.323 and similar multimedia session control protocols to set up and tear down packet filters as needed to gather traces of multimedia sessions. Unlike tcpdump, dynamic packet filters are necessary because these protocols dynamically negotiate TCP and UDP port numbers to carry the media content. Our tool captures only packets of interest for optional storage and further analysis, thus greatly reducing resource requirements. This paper presents the design and implementation of mmdump and demonstrates its utility in monitoring live RTSP and H.323 traffic on a commercial IP network. The preliminary results obtained from these measurements are presented.
Effects of Ecklonia cava as fucoidan-rich algae on growth performance, nutrient digestibility, intestinal morphology and caecal microflora in weanling pigs

Objective In the present study, role of increasing levels of Ecklonia cava (seaweed) supplementation in diets was investigated on growth performance, coefficient of total tract apparent digestibility (CTTAD) of nutrients, serum immunoglobulins, cecal microflora and intestinal morphology of weanling pigs. Methods A total of 200 weaned pigs (Landrace×Yorkshire×Duroc; initial body weight 7.08±0.15 kg) were randomly allotted to 4 treatments on the basis of body weight. There were 5 replicate pens in each treatment including 10 pigs of each. Treatments were divided by dietary Ecklonia cava supplementation levels (0%, 0.05%, 0.1%, or 0.15%) in growing-finishing diets. There were 2 diet formulation phases throughout the experiment. The pigs were offered the diets ad libitum for the entire period of experiment in meal form. Results The pigs fed with increasing dietary concentrations of Ecklonia cava had linear increase (p<0.05) in the overall average daily gain, however, there were no significant differences in gain to feed ratio, CTTAD of dry matter and crude protein at both phase I and phase II. Digestibility of gross energy was linearly improved (p<0.05) in phase II. At day 28, pigs fed Ecklonia cava had greater (linear, p<0.05) Lactobacillus spp. , fewer Escherichia coli (E. coli) spp. (linear, p<0.05) and a tendency to have fewer cecal Clostridium spp. (p = 0.077). The total anaerobic bacteria were not affected with supplementation of Ecklonia cava in diets. Polynomial contrasts analysis revealed that villus height of the ileum exhibited a linear increase (p<0.05) in response with the increase in the level of dietary Ecklonia cava. However, villus height of duodenum and jejunum, crypt depth, villus height to crypt depth ratio of different segments of the intestine were not affected. Conclusion The results suggest that Ecklonia cava had beneficial effects on the growth performance, cecal microflora, and intestinal morphology of weanling pigs.
QUANTUM-INSPIRED OPTIMIZATION APPROACH FOR ENGINEERING DESIGN

Optimization problems are widely encountered in various fields of mechanical engineering. Sometimes such problems can be very complex due to the actual and practical nature of the objective function or the model constraints. During the history of science of computational intelligence, many evolutionary algorithms and swarm intelligence approaches were proposed having more or less success in solving various mechanical engineering optimization problems. In this context, the Particle Swarm Optimization (PSO) is a bio-inspired optimization mechanism based on the metaphor of social behavior of birds flocking and fish schooling in search for food. In PSO each member is seen as a particle, and each particle is a potential solution to the problem under analysis. In this context, each particle which moves through the space of the problem has a randomized velocity associated to it. Inspired by the classical PSO method and quantum mechanics theories, this work presents a new Quantum-behaved PSO (QPSO) approach using Gaussian probability distribution function. The simulation results demonstrate good performance of the QPSO approaches in solving a benchmark problem of tension/compression spring design.
Presupposition Projection in Online Processing

A central aspect of language comprehension is that hearers integrate incoming linguistic content both with the rest of the current sentence and the larger discourse context. Presuppositions crucially interact with both intraand inter-sentential context in intricate ways, which makes their study especially useful in this regard. We present a series of experiments investigating the time-course of interpreting presuppositions in online comprehension and the impact that so-called presupposition projection in cases where presuppositions appear in embedded environments has on this. We find immediate delays in eye tracking reading times when the presupposition of German wieder (‘again’) is not supported by the context, but only for unembedded occurrences of wieder. Further evidence from a rating experiment and a stops-making-sense study supports our interpretation of this result to the effect that global presuppositions of embedded presupposition triggers are not immediately available in processing. A second reading time experiment explores the effects of embedding further by providing presuppositional support in different locations in contexts with a more complex structure involving conditionals. We find longer reading times when the support is more distant, measured in terms of the number of projection steps posited by Discourse Representation Theory (DRT). Altogether, the results suggest that presupposition projection is a cognitively effortful process, and are thus consistent with theoretical accounts that reflect this in terms of the complexity of the representations involved in the different types of contexts, while other accounts that are more neutral in this regard need to be supplemented by additional assumptions or alternative explanations for the observed effects. On the more general level of discourse processing models, these results suggest that there is even more structure relevant to cognitive processes at a level between the surface representation and the purely semantic level (e.g., the commonly assumed level of a text-base) than previously assumed.
Metal-Free Fully Solution-Processable Flexible Electrolyte-Gated Carbon Nanotube Field Effect Transistor

Carbon nanotube-based field effect transistors (CNTFETs) are an interesting alternative to organic FETs in the growing field of printed electronics. Solution processed CNTFETs can be fabricated at low temperatures, are compatible with roll to roll processes and with flexible substrates. Usually metal electrodes for CNTFETs are deposited using standard techniques (e.g., evaporation or sputtering) which require expensive equipment and a high thermal budget. The elimination of such deposition step would allow a fully solution-based process for the CNTFETs fabrication. In this paper, we demonstrate an all carbon nanotube (CNT) transistor which is entirely solution processable without sacrificing the device performance. Performed detailed contact resistance analysis shows that CNT electrodes make better contacts to semiconducting CNTs channel than gold electrodes. The device performance is shown for an electrolyte-gated CNTFET fabricated on a flexible substrate. Such transistors are used as low cost biosensors for vivo implants by exploiting better interaction of flexible substrates to cells.
Sex-specific association of epidermal growth factor gene polymorphisms with acute respiratory distress syndrome

Epidermal growth factor (EGF) is involved in alveolar epithelial repair, lung fluid clearance and inflammation, and is regulated by sex hormones. An unmatched, nested case–control study was conducted to evaluate the associations of EGF variants with acute respiratory distress syndrome (ARDS) and the role of sex on the associations between EGF variants and ARDS. Patients with ARDS risk factors upon intensive care unit admission were enrolled. Cases were 416 Caucasians who developed ARDS and controls were 1,052 Caucasians who did not develop ARDS. Cases were followed for clinical outcomes and 60-day mortality. One functional single nucleotide polymorphism (SNP), rs4444903, and six haplotype-tagging SNPs spanning the entire EGF gene were genotyped. No individual SNP or haplotype was associated with ARDS risk or outcomes in all subjects. Sex-stratified analyses showed opposite effects of EGF variants on ARDS in males versus in females. SNPs rs4444903, rs2298991, rs7692976 and rs4698803, and haplotypes GGCGTC and ATCAAG were associated with ARDS risk in males. No associations were observed in females. Interaction analysis showed that rs4444903, rs2298991, rs7692976 and rs6533485 significantly interacted with sex for ARDS risk. The present study suggests that associations of epidermal growth factor gene variants with acute respiratory distress syndrome risk are modified by sex. The current findings should be replicated in other populations.
Defects Appearing in the Surfacing Layers of Abrasion Resistant

The surfacing technologies are used for constitution of protection layer against wear and is destined for obtaining coating with high hardness. Among many weldings methods currently used to obtain the hard surface layer one of the most effective way of hardfacing is using flux cored arc welding. This additional material gives more possibilities to make expected hard surface layer. Chemical composition, property and economic factors obtained in flux cored wire are much richer in comparison to these obtained with other additional materials. This is the reason why flux cored wires give possibilities of application this kind of material for improving surface in different sectors of industry. In the present paper the imperfection in the layers was used for hardfacing process in different situations to show the possible application in the surface layer. The work presents studies of imperfection of the welds, contains the picture of microstructures, macrostructures and shows the results of checking by visual and penetrant testing methods.
Integrated motion planning for indoor mobile robots using motor schema and adaptive fuzzy behavioral modulation

This paper presents a novel approach for integrating global and local path planning of indoor mobile robots using motor schema based behavior coordination with fuzzy logic based adaptive behavioral modulation. First, Voronoi diagram approach is exploited to determine the global safe-path. Then A* search algorithm is employed to identify the Voronoi vertices (junctions or nodes) along the optimal path between the starting point of the robot and target position. Locally located junctions then act as subgoals for local motion planning. Motor schema based behavior fusion generates the safe direction of motion. Subgoals and points on the safe path exhibit attractive forces whereas obstacles cause repulsive forces. A supervisory fuzzy module is developed to incorporate adaptive behavioral capabilities which exploit the weighted decision-making based on contextual behavior composition. It dynamically produces the force coefficients for context dependent modulation of the virtual forces to generate local-minima free trajectory without oscillation. Adapted vector field histogram is deployed in order to modify the safe path in the presence of unknown obstacles. Simulation of indoor navigation examples validates the performance of the algorithm.
Different apolipoprotein E, apolipoprotein A1 and prostaglandin-H2 D-isomerase levels in cerebrospinal fluid of schizophrenia patients and healthy controls

Abstract Objectives. To identify proteins differentially expressed in schizophrenia patients, we collected 50 µl cerebrospinal fluid from 17 first-episode schizophrenia patients and 10 healthy controls. Methods. Their proteins were separated by two-dimensional gel electrophoresis without using any depletion method and identified by mass spectrometry. Results. Approximately 550 spots were detected, six of which had significantly different intensities in schizophrenia compared to control specimens. We were able to validate in individual samples the upregulation of apolipoprotein E, apolipoprotein A1 and prostaglandin-H2 D-isomerase by Western blot analyses and detect the downregulation of transthyretin, TGF-β receptor type-1 and coiled-coil domain-containing protein 3 precursor. Conclusions. These findings may help to elucidate the disease mechanisms and confirm the hypothesis of disturbed cholesterol and phospholipid metabolism in schizophrenia, and thus reveal the final role players. Moreover, a grouped protein expression analysis of apolipoprotein E, apolipoprotein A-I, and prostaglandin-H2 D-isomerase in cerebrospinal fluid from patients might be a potential diagnostic tool for schizophrenia.
Simultaneous fMRI and EEG during the Multi-Source Interference Task

Background fMRI and EEG are two non-invasive functional imaging techniques within cognitive neuroscience that have complementary advantages to obtain both temporal and spatial information. The multi-source interference task (MSIT) has been shown to generate robust activations of the dorsal anterior cingulate cortex (dACC) on both a single-subject level and in group averages, in fMRI studies. We have now simultaneously acquired fMRI and EEG during a cognitive interference task. Materials and Methods Healthy volunteers were tested in an MRI scanner with simultaneous EEG and fMRI recordings during the MSIT. Results The interference condition significantly increased the reaction time in the task. The fMRI analyses revealed activation of dACC as expected, in all subjects at the individual level and in group analyses. The posterior cingulate cortex was de-activated. Simultaneous EEG showed the expected anterior distribution of the interference effect, as it was restricted to frontal sites within a time frame of 80–120 ms post response. Conclusion The MSIT task is a reliable task for interference evaluation. fMRI shows robust activation of dACC and by adding EEG, an interference effect can be noticed within a temporal interval of 80–120 ms after the response, as a CRN (correct response negativity). This means that EEG could add a more detailed temporal aspect to the fMRI data from an interference task, and that despite the hostile environment within an MRI scanner, EEG data could be used.
Building and evaluating P2P systems using the Kompics component framework

We present a framework for building and evaluating P2P systems in simulation, local execution, and distributed deployment. Such uniform system evaluations increase confidence in the obtained results. We briefly introduce the Kompics component model and its P2P framework. We describe the component architecture of a Kompics P2P system and show how to define experiment scenarios for large dynamic systems. The same experiments are conducted in reproducible simulation, in real-time execution on a single machine, and distributed over a local cluster or a wide area network. This demonstration shows the component oriented design and the evaluation of two P2P systems implemented in Kompics: Chord and Cyclon. We simulate the systems and then we execute them in real time. During real-time execution we monitor the dynamic behavior of the systems and interact with them through their web-based interfaces. We demonstrate how component-oriented design enables seamless switching between alternative protocols.
Complexity curve: a graphical measure of data complexity and classifier performance

We describe a method for assessing data set complexity based on the estimation of the underlining probability distribution and Hellinger distance. In contrast to some popular complexity measures, it is not focused on the shape of a decision boundary in a classification task but on the amount of available data with respect to the attribute structure. Complexity is expressed in terms of graphical plot, which we call complexity curve. It demonstrates the relative increase of available information with the growth of sample size. We perform theoretical and experimental examination of properties of the introduced complexity measure and show its relation to the variance component of classification error. We then compare it with popular data complexity measures on 81 diverse data sets and show that it can contribute to explaining performance of specific classifiers on these sets. We also apply our methodology to a panel of simple benchmark data sets, demonstrating how it can be used in practice to gain insights into data characteristics. Moreover, we show that the complexity curve is an effective tool for reducing the size of the training set (data pruning), allowing to significantly speed up the learning process without compromising classification accuracy. The associated code is available to download at: https://github.com/zubekj/complexity_curve (open source Python implementation). Subjects Algorithms and Analysis of Algorithms, Artificial Intelligence, Data Mining and Machine Learning