Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemokines and chemokine receptors in CNS pathology.

Chemokines are small proinﬂammatory cytokineswhich stimulate migration of inﬂammatory cells invitro and in vivo. They can be divided according tostructure, function and gene localization into fourdifferent subfamilies. Chemokines have been as-cribed diverse additional functions, including reg-ulation of angiogenesis, control of cell proliferationand developmental tissue patterning.The suspicion that chemokines could be involvedin CNS pathology emerged from considering theirtarget-cell speciﬁcity, in light of the selectiverecruitment of leukocyte populations to the in-trathecal compartment in diverse disease processes.Initial studies of chemokine expression in the CNSwere performed in models including experimentalautoimmune encephalomyelitis (EAE), stroke andmeningitis. Early results from these investigationsprovided the exciting insight that parenchymal CNScells were among the most abundant sources ofchemokines, bothin vitro and in vivo. A landmarkobservation from Karpus et al (1995) was that EAEcould be abrogated by passive immunization withantibodies to a single chemokine, MIP-1a.Chemokine receptors have also found a place inthe unique pathologies of the nervous system.Evident relationships between chemokines thatfunction in speciﬁc processes and response byappropriate hematogenous receptor-bearing cellshave been demonstrated. Of more novelty (if lesswell understood) has been the ﬁnding that chemo-kine receptors such as CXCR4, CXCR2, CX3CR1 andthe Duffy antigen receptor for chemokines (DARC)are expressed by resident neuroepithelial cells.These varied observations point to a fascinating,diverse and complex array of biological roles forthese products in the CNS. Preliminary results inthis ﬁeld are reviewed in this manuscript andsummarized in the Tables.
Comparing Countermeasures against Interrupt-Related Covert Channels in an Information-Theoretic Framework

Interrupt-driven communication with hardware devices can be exploited for establishing covert channels. In this article, we propose an information-theoretic framework for analyzing the bandwidth of such interrupt-related channels while taking aspects of noise into account. As countermeasures, we present mechanisms that are already implemented in some operating systems, though for a different purpose. Based on our formal framework, the effectiveness of the mechanisms is evaluated. Despite the large body of work on covert channels, this is the first comprehensive account of interrupt-related covert channel analysis and mitigation.
The Effects of Soret and Dufour on Mixed Convection Boundary Layer Flow of a Porous Media along a Permeable Surface filled with a Nanofluid and Radiation

Article history: Received 11 October 2018 Received in revised form 16 December 2018 Accepted 20 December 2018 Available online 8 January 2019 An investigation of mixed convection flow in a boundary layer saturated by a nanofluid and lodged in a porous medium with the existence of Soret and Dufour numbers, suction and thermal radiation is numerically studied. By employed a similarity transformation technique, the governing set of ordinary differential equations has been conducted from a non-linear partial differential equations system, where we apply a Runge-Kutta-Fehlberg method in order to numerically solved the final equations for a group of variety metallic and nonmetallic nanoparticles in a water base fluid consisting of copper (Cu), aluminium oxide (Al2O3) and titanium dioxide (TiO2). Numerous values of presented parameters such as thermal radiation coefficient, suction parameters, as well as Dufour and Soret numbers are graphically presented and discussed on the dimensionless velocity, temperature and concentration distributions profiles.
Discriminative Sub-categorization

The objective of this work is to learn sub-categories. Rather than casting this as a problem of unsupervised clustering, we investigate a weakly supervised approach using both positive and negative samples of the category. We make the following contributions: (i) we introduce a new model for discriminative sub-categorization which determines cluster membership for positive samples whilst simultaneously learning a max-margin classifier to separate each cluster from the negative samples, (ii) we show that this model does not suffer from the degenerate cluster problem that afflicts several competing methods (e.g., Latent SVM and Max-Margin Clustering), (iii) we show that the method is able to discover interpretable sub-categories in various datasets. The model is evaluated experimentally over various datasets, and its performance advantages over k-means and Latent SVM are demonstrated. We also stress test the model and show its resilience in discovering sub-categories as the parameters are varied.
Large Kernel Matters — Improve Semantic Segmentation by Global Convolutional Network

One of recent trends [31, 32, 14] in network architecture design is stacking small filters (e.g., 1x1 or 3x3) in the entire network because the stacked small filters is more efficient than a large kernel, given the same computational complexity. However, in the field of semantic segmentation, where we need to perform dense per-pixel prediction, we find that the large kernel (and effective receptive field) plays an important role when we have to perform the classification and localization tasks simultaneously. Following our design principle, we propose a Global Convolutional Network to address both the classification and localization issues for the semantic segmentation. We also suggest a residual-based boundary refinement to further refine the object boundaries. Our approach achieves state-of-art performance on two public benchmarks and significantly outperforms previous results, 82.2% (vs 80.2%) on PASCAL VOC 2012 dataset and 76.9% (vs 71.8%) on Cityscapes dataset.
Saliency and Gist Features for Target Detection in Satellite Images

Reliably detecting objects in broad-area overhead or satellite images has become an increasingly pressing need, as the capabilities for image acquisition are growing rapidly. The problem is particularly difficult in the presence of large intraclass variability, e.g., finding “boats” or “buildings,” where model-based approaches tend to fail because no good model or template can be defined for the highly variable targets. This paper explores an automatic approach to detect and classify targets in high-resolution broad-area satellite images, which relies on detecting statistical signatures of targets, in terms of a set of biologically-inspired low-level visual features. Broad-area images are cut into small image chips, analyzed in two complementary ways: “attention/saliency” analysis exploits local features and their interactions across space, while “gist” analysis focuses on global nonspatial features and their statistics. Both feature sets are used to classify each chip as containing target(s) or not, using a support vector machine. Four experiments were performed to find “boats” (Experiments 1 and 2), “buildings” (Experiment 3) and “airplanes” (Experiment 4). In experiment 1, 14 416 image chips were randomly divided into training (300 boat, 300 nonboat) and test sets (13 816), and classification was performed on the test set (ROC area: 0.977 ±0.003). In experiment 2, classification was performed on another test set of 11 385 chips from another broad-area image, keeping the same training set as in experiment 1 (ROC area: 0.952 ±0.006). In experiment 3, 600 training chips (300 for each type) were randomly selected from 108 885 chips, and classification was conducted (ROC area: 0.922 ±0.005). In experiment 4, 20 training chips (10 for each type) were randomly selected to classify the remaining 2581 chips (ROC area: 0.976 ±0.003). The proposed algorithm outperformed the state-of-the-art SIFT, HMAX, and hidden-scale salient structure methods, and previous gist-only features in all four experiments. This study shows that the proposed target search method can reliably and effectively detect highly variable target objects in large image datasets.
Individual Secrecy for Broadcast Channels With Receiver Side Information

This paper studies the problem of secure communication over the broadcast channel with receiver-side information under the lens of individual secrecy constraints, that is, the transmitter wants to send two independent messages to two receivers, which have, respectively, the desired message of the other receiver as side information, while keeping the eavesdropper ignorant of each message (i.e., the information leakage rate from each message to the eavesdropper is made vanishing). Building upon one-time pad, secrecy coding, and broadcasting schemes, achievable rate regions are investigated, and the capacity region for special cases of either a weak or strong eavesdropper (compared to both legitimate receivers) is characterized. Interestingly, the capacity region for the former corresponds to a line and the latter corresponds to a rectangle with missing corners; a phenomenon occurring due to the coupling between user’s rates. Moreover, the individual secrecy capacity region is also fully characterized for the case where the eavesdropper’s channel is deterministic. In addition to discrete memoryless setup, Gaussian scenarios are studied. For the Gaussian model, in addition to the strong and weak eavesdropper cases, the capacity region is characterized for the low and high SNR regimes when the eavesdropper’s channel is stronger than one receiver but weaker than the other. Remarkably, positive secure transmission rates are always guaranteed under the individual secrecy constraint, unlike the case of the joint secrecy constraint (i.e., the information leakage rate from both messages to the eavesdropper is made vanishing). Thus, this notion of secrecy serves as an appropriate candidate for trading off secrecy level and transmission rate, making secrecy more affordable but still acceptable to the end user.
Predictors of Interpersonal Trust in Virtual Distributed Teams

Abstract : Human trust in virtual distributed teams plays a critical role in performing missions/tasks given the limited resources. This study attempted to review the available literature with regards to the human interpersonal trust characteristics to identify important traits or factors when temporary mission oriented teams must be assembled. Based on the review of the theories, a theory of human trust, trust continuum/grid/cube, was developed and discussed in this study. Finally, an experimental framework to test the proposed theory was developed, however the experiment was not conducted due to the time limitation.
Comparison of mental imagination skill of male and female athletes of individual and team athletic fields.

Aim: aim of current research was comparison of intrinsic and extrinsic imagination skills of male and female athletes of individual and team athletic fields of Golestan Province. Method: method of this study was semi empirical field study which was conducted by questionnaire. Statistical universe of this study was all male and female athletes of Golestan province. 170 of total including 105 male and 65 female were chosen randomly. In this study for considering intrinsic imagination skill VMIQ questionnaire and for extrinsic imagination VVIQ questionnaire was used. Results and findings: results of t test indicated that: 1- there is significant difference between intrinsic imagination skill of male and female athletes of team athletic fields and males are better in intrinsic imagination. (p<0/05) 20 there is significant between extrinsic imagination skill of male and female athletes of individual athletic fields and males have higher extrinsic imagination skill. (p<0/05) 3- extrinsic imagination of male and female athletes of team fields was significantly higher than individual fields. (p<0/05) 4- intrinsic imagination skill of individual field was significantly higher than team fields. (p<0/05). Discussion and conclusion: These findings are discussed according to higher imagination skills of males compared to females and also nature of different athletic fields.
Colonization of diatoms and bacteria on artificial substrates in the northeastern coastal Adriatic Sea

Abstract Every surface that is immersed in seawater becomes rapidly covered with an unavoidable biofilm. Such biofilm formation, also known as fouling, is a complex multistage process and not yet thoroughly investigated. In this study, the succession of diatoms and bacteria was investigated during a one month exposure on an artificial substrate of plexiglass (polymer of methyl methacrylate) mounted above the seafloor at a depth of 5 m. For biofilm analyses, the fouling was investigated using selective agar plates, epifluorescence, light and electronic microscopy, as well as high performance liquid chromatography (HPLC) pigment analysis. During biofilm development, the abundance of all biofilm components increased and reached maximum values after a one month exposure. In the bacterial community, heterotrophic marine bacteria were dominant and reached 1.96 ± 0.79 × 104 colony forming units (CFU) cm-2. Despite the fact that faecal coliforms and intestinal enterococci were detected in the water column, faecal coliforms were not detected in the biofilm and intestinal enterococci appeared after one month of exposure but in the negligible number of 60 ± 10 CFU cm-2. The phototrophic component of the biofilm was dominated by diatoms and reached a concentration of 6.10 × 105 cells cm-2, which was supported by pigment analysis with fucoxanthin as dominant pigment in a concentration up to 110 ng cm-2. The diatom community was dominated by Cylindrotheca closterium and other pennate benthic diatoms. A detailed taxonomic analysis by electronic microscopy revealed 30 different taxa of diatoms. The study confirmed that a plexiglass surface in a marine environment is susceptible to biofouling within 30 days of contact. Furthermore, the co lonization process sequence firstly involved bacteria and cyanobacteria, and secondly diatoms, which together formed a primary biofilm in the sea.
Post-traumatic acute thoracic aortic injury (TAI)-a single center experience.

Background We assess the effectiveness and our experience in emergency thoracic endovascular aortic repair (TEVAR) in patients with post-traumatic acute thoracic aortic injury (TAI) and associated multiorgan trauma. TAI is a life-threatening condition. It usually results from a sudden deceleration caused by vehicle accident, a fall or some other misfortune. Techniques of endovascular aortic repair have become promising methods to treat emergent TAI. Methods Since 2007, 114 patients with thoracic aorta pathologies have been treated by TEVAR. Our study involved 15 (incl. 14 men) of them (13%) who underwent stent graft implantation for post-traumatic either aortic rupture or pseudoaneurysm. The procedural access was limited to small skin incision in one groin and percutaneous puncture of the contralateral femoral artery. We evaluated technical success, early and long-term mortality, complication rate of procedure and throughout clinical and instrumental follow-up. Results Technical success rate was 100%. All patients survived the endovascular interventions. No additional procedures or conversions to open surgery were necessary. After the operation, none of the patients had symptoms of stroke or spinal cord ischemia (SCI). No serious stent-graft-related adverse events such as endoleak, infection or migration were noted during follow-up period that ranged from 6 to 108 months. Conclusions In our department, techniques of TEVAR with stentgraft implantation have become methods of choice in treatment of traumatic TAIs since they have enabled to minimize operational risk, particularly in unstable multitrauma patients in severe clinical status. TEVAR for TAI performed in emergency settings provide favorable long-term results.
The effect of practice on the visual detection of near-threshold lines.

Two observers practised to detect small target lines of varying luminance presented either within a context of collinear inducing stimuli, or without the context in separate blocks. A two-alternative spatial-forced-choice procedure using the method of constant stimuli was employed. For blocks of 500 trials, reflecting individual performance on five successive days of training, the percentage of correct responses, and the response times were analyzed. After several thousands of trials, i.e. several weeks of practice, both observers managed to detect targets presented at their strongest luminance within the context condition. Without the context, these targets remained undetected. Response times (RT) vary nonsystematically during training. Once detection is observed at the highest target luminance, the accuracy of the individual responses (percentage of correct responses) systematically increases, and processing speed (RT) systematically decreases with increasing target intensity. These results show that, within the appropriate perceptual context, practice can lead to a better detectability of visual stimuli presented at luminance levels near detection threshold. This improvement is reflected by an optimization of the visual integration of the different luminance levels of the target (sensory coding), and processing speed (response routine) during training.
General Exact Level Crossing Rate and Average Fade Duration for Dual-Diversity Combining of Nonidentical Correlated Weibull Signals

This paper derives general exact expressions for the level crossing rate (LCR) and the average fade duration (AFD) of dual-branch selection, equal-gain, and maximal-ratio combiners operating over non-identical correlated Weibull fading channels. Sample numerical results are discussed by specializing the general expressions to a space-diversity system using horizontally spaced antennas at a mobile station. It is verified that as the antenna spacing becomes larger, the LCR decreases, becoming oscillatory and convergent. In addition, when the direction of the mobile is perpendicular to the axis of the antenna, the AFD is loosely dependent on the antenna spacing. Some simulation results are presented to verify the correctness of the analytical formulation.
A liquid crystal infiltrated single polarization spiral photonic crystal fiber with large negative flat dispersion

A dispersion compensating fiber having average dispersion profile of -259 ps/nm-km with dispersion variation of about 4.58 ps/nm-km has been obtained over the wavelength range 1.35 μm to 1.675 μm using an equiangular spiral photonic crystal fiber (ES-PCF). The proposed fiber also exhibits single polarization behavior with one of its fundamental modes (x or y polarized) completely suppressed. To obtain these properties, liquid crystal (LC) is infiltrated in the defected core of ES-PCF. These unique features of the proposed fiber can be used in wavelength-division-multiplexing (WDM) optical fiber transmission system for residual chromatic dispersion compensation and also for maintaining single polarization.
Analysis of Gaze on Word Search Puzzles

Eye tracking experiments have been performed in attempts to capture eye movement patterns in a variety of different settings. Eyes tend to be drawn to certain objects and can be influenced by stimuli to focus more in a certain area as opposed to others. This study investigated if distractions similar to what the eye is searching for can create an increase in the amount of time taken to find the target. In order to test that, we used eye-tracker technology to record eye movements of a group of 13 participants (9 males and 4 females) when presented with stimulus that is distraction-free and with distractions present. Our experiment examined the speed at which a participant could find a target word in a word search puzzle based on if that word was the only valid word or there were additional valid words. We hypothesized that additional words would decrease participants search times. Based on the data collected, we were able to use key statistics such as amount of fixations and duration of fixation to determine that participants are able to more quickly find a target word in a word search puzzle if other valid words are present. Thus, disproving our hypothesis.
New Social Movements and the New Class in the Netherlands

The class base of the so-called new social movements is analyzed using data from the Dutch national election survey of 1986. This analysis is linked to the theory on the "new class," reconceptualized as those in the new middle class who try to defend their relative autonomy against the encroachment of the "technocrats. " The analysis shows that, although the Dutch new social movements are supported by broad segments of the population, their inner circles are predominantly constituted by segments of the reconceptualized new class: the young specialists in social and cultural services, and some of the yound administrative specialists in public service. In addition, the analysis documents the liberalizing effect of education for the younger cohorts and suggests a profound change of values in the postwar period.
Nikki Usher, Making News at The New York Times

Print reporters long for the luxury of researching a story uninterrupted by the necessity of writing constant updates to their Web articles. Web editors obsessively reorganize the structure of the homepage even though many users never visit it. The audience is still a mystery in the age of Web analytics: Journalists know what readers click through, but they do not know what their readers expect from them. Nikki Usher’s Making News at The New York Times reveals in meticulous detail the contradictions inherent in contemporary newsrooms. Instead of conducting a representative survey of hundreds of journalists, the author opted for the thick depiction and analytical insights offered by ethnography, focusing on one of the most influential media companies in the world. The fact that the Times has greater resources for innovative development than most other newsrooms means that its struggles with digital publishing are to be taken as a serious wake-up call for the whole industry.
Do Better Paid Politicians Perform Better? Disentangling Incentives from Selection

The wage paid to politicians affects both the choice of citizens to run for an elective office and the performance of those who are appointed. First, if skilled individuals shy away from politics because of higher opportunities in the private sector, an increase in politicians' pay may change their mind. Second, if the reelection prospects of incumbents depend on their in-office deeds, a higher wage may foster performance. We use data on all Italian municipal governments from 1993 to 2001 and test these hypotheses in a quasi-experimental framework. In Italy, the wage of the mayor depends on population size and sharply rises at different thresholds. We apply a regression discontinuity design to the only threshold that uniquely identifies a wage increase – 5,000 inhabitants – to control for unobservable town characteristics. Exploiting the existence of a two-term limit, we further disentangle the composition from the incentive component of the effect of the wage on performance. Our results show that a higher wage attracts more educated candidates, and that better paid politicians size down the government machinery by improving internal efficiency. Importantly, most of this performance effect is driven by the selection of competent politicians, rather than by the incentive to be reelected.