Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between serum interleukin-6 concentrations and chronic obstructive pulmonary disease: a systematic review and meta-analysis

Background. Interleukin-6 (IL-6) is an important pro-inflammatory cytokine and has been implicated to play a role in the systemic inflammation of patients with chronic obstructive pulmonary disease (COPD). We conducted this meta-analysis to assess the association between serum IL-6 concentrations and COPD. Methods. PubMed and Embase were searched for eligible studies. Data were extracted by two investigators (Wei J, Xiong XF) independently and analyzed using Review Manager 5.3 and STATA 12.0 software. Standard mean differences (SMDs) and 95% confidence intervals (CI) were calculated. Results. Thirty-three studies were included in this meta-analysis. The serum IL-6 concentrations were higher in patients with stable COPD than healthy controls (SMD = 0.65, 95% CI [0.51–0.79]). COPD patients without major comorbidities also showed higher IL-6 levels than healthy controls (SMD = 0.74, 95% CI [0.56–0.91]). COPD patients with an forced expiratory volume in one second (FEV1) of either <50% predicted or >50% predicted had increased IL-6 concentrations compared to healthy controls (SMD = 0.77, 95% CI [0.48–1.05], SMD = 1.01, 95% CI [0.43–1.59], respectively). The serum IL-6 concentrations between mild-moderate and severe-very severe COPD patient groups were not found to be significant (SMD = −0.1, 95% CI [−0.65–0.44]). Conclusions. This meta-analysis indicated that patients with stable COPD had higher serum IL-6 concentrations than healthy controls. No evidence showing positive or negative association between IL-6 concentrations and the severity of pulmonary function impairment was found. The correlation between IL-6 levels and pulmonary function was weak in different severities of stable COPD patients.
A Linear Algebraic Approach to Kalman Filtering

A new linear algebraic approach is used here to derive the celebrated Kalman filter. The filtering problem is first converted into an equivalent linear algebraic problem by relating the estimate of process state to the vector of measured output via a linear equation. Then we obtain the Kalman recursion equations by using a simple linear algebraic lemma. This derivation is conceptually simple, elegant, and thus very suitable for pedagogical purposes. Another advantage of our approach is that the noise correlated case is dealt with as easily as the noise uncorrelated case.
The dopamine transporter: immunochemical characterization and localization in brain

Antibodies specific for the dopamine transporter (DAT) was developed and characterized by immunoblot analysis, immunoprecipitation, and immunocytochemistry, and used for immunolocalization of transporter protein in rat brain at the light microscopic level. Antibodies targeting the N-terminus, the second extracellular loop, and the C- terminus were generated from fusion proteins containing amino acid sequences from these respective regions. Immunoblot analysis demonstrated that N-terminus and loop antibodies were specific for expressed cloned DAT, recognized transporter protein in rat and human striatal membranes, and were sensitive to preabsorption with excess homologous fusion protein. Immunoprecipitation studies demonstrated that anti-DAT antisera recognized solubilized, radiolabeled DAT protein in a concentration-dependent manner. DAT immunocytochemistry with these antibodies were also sensitive to preabsorption with fusion protein and to lesions of dopaminergic mesostriatal and mesocorticolimbic pathways. Regional distribution of DAT coincided with established dopaminergic innervation of several regions, including ventral mesencephalon, medial forebrain bundle, and dorsal and ventral striatum. However, certain mismatches between immunocytochemical distributions of DAT and tyrosine hydroxylase were apparent, indicating that dopaminergic systems are heterogeneous and may use independent mechanisms for the regulation of dopamine levels in brain. The generation of specific DAT antibodies will permit further characterization of the cellular and subcellular localization of DAT protein, and of dopaminergic circuits in neurological and psychiatric disorders.
Machine Learning Performance on Face Expression Recognition using Filtered Backprojection in DCT-PCA Domain.

An accurate and robust transformed face descriptor that exploits the capabilities of filtered backprojection applied on Discrete Cosine Transform (DCT) and kernel Principal Component Analysis (PCA) methods is proposed. The method is invariant to rotation, variations in facial expression and illumination. Filtered backprojection constructs transform parameters from a set of projections through an image enhancing feature patterns that provide an initialization for subsequent DCT computations. DCT discards high-frequency coefficients that form least significant data to retain a subset of lower frequency coefficients visually significant in the image. The resulting coefficient features are mapped to lower dimensional space using PCA which extracts principal components that form the basis for the neural network classifier. Experiments were carried on JAFEE database and computed results compared with PCA and DCT approach. The results demonstrate significant improvements in results compared to other approaches.
A Systematic Approach to Testing Automotive Control Software

Usually, the testing of today's ECU software follows a gut feeling approach, leading to test gaps and test redundancies. This paper presents a new, more systematic way of testing automotive control software. The central element of the approach is the Classification-Tree Method for Embedded Systems (CTM/ES). Using an interface description, which can be based on the specification and / or an executable model of the software, test scenarios can be derived systematically and described in a graphical way so as to provide the user with visual information about test coverage. The CTM/ES can be integrated into an overall test strategy for automotive control software developed in a model-based way. The approach opens up a new way of assuring quality for embedded control software which is especially designed for automotive software developers.
A cache based scheme of data management in mobile devices

An increased uses of mobile devices such as smart phones, PDAs and tablet computers with limited energy and intermittent wireless network are growing rapidly. Data management in these devices raises new challenges that must be addressed. These challenges have traditionally been the responsibility of the OS. In this paper, we propose a novel cache based scheme to the problem of energy saving, bandwidth saving and asynchronous data access while raise the efficiency of application running on the device. We achieve this by using a combination of local cache and two queues in memory. We also exploit object view to provide application-specific service and convenient data access.
Neural mechanisms of temperature compensation in an insect auditory system

The human brain largely remains functional regardless of whether one is searching for the shortest path to a warming shelter in a snowstorm or running a marathon on a summer’s day. This robustness of brain functionality can be attributed to the maintenance of a constant body temperature, which requires a large investment of energy. Due to homeothermy, the temperature dependence of all chemical reactions, including those inside the body, loses relevance as a constraint for humans. For poikilotherms, in contrast, a rise in ambient temperature translates to an increase in body temperature, which speeds up all chemical processes. Yet, many poikilotherms exhibit robustness of vital behaviors across a broad range of temperatures, which suggests the existence of mechanisms that compensate for temperature dependencies at the microscopic level. The present thesis proposes mechanisms for such temperature compensation, using the auditory system of the grasshopper as a model system. For various grasshopper species, the auditory system facilitates localization and recognition of conspecifics under conditions of low visibility. In particular, communication and recognition remain functional across a temperature range of up to 15◦C. Here, we show on the one hand how single nerve cells with temperaturedependent ion channels can generate a temperature-compensated stimulus representation. Importantly, we reveal that the underlying cell-intrinsic compensation mechanism need not impair neuronal energy efficiency. On the other hand, we show that sound processing in higher-order neurons does not exhibit the degree of compensation that is found at the input level. Using a combination of mathematical modeling and simulations we show how temperature compensation of song recognition can be achieved at the network level, with temperature-dependent neural filters. In principle the proposed mechanisms are applicable to all poikilothermic species. Die Benennung der Poikilothermen mit ”Spielball der Umgebung” ist sprachlich und sachlich in die physiologische Literatur übergegangen. Wir möchten nun im Folgenden klarzulegen versuchen, wie gegenüber den physikalischen Kräften der Umgebung der Körper des Kaltblüters keineswegs lediglich das Verhalten eines leblosen physikalischen Objects zeigt, und wie auch bei ihm schon Vorrichtungen bestehen, die den Organismus von den Launen der Umgebung zu emancipiren suchen. —Ludolf von Krehl & Franz Soetbeer, 1899
Universal Neural Network Control of MIMO Uncertain Nonlinear Systems

In this brief, a continuous tracking control law is proposed for a class of high-order multi-input-multi-output uncertain nonlinear dynamic systems with external disturbance and unknown varying control direction matrix. The proposed controller consists of high-gain feedback, Nussbaum gain matrix selector, online approximator (OLA) model and a robust term. The OLA model is represented by a two-layer neural network. The continuousness of the control signal is guaranteed to relax the requirement for the actuator bandwidth and avoid the incurred chattering effect. Asymptotic tracking performance is achieved theoretically by standard Lyapunov analysis. The control feasibility is also verified in simulation environment.
Density Estimations for Approximate Query Processing on SIMD Architectures

Approximate query processing (AQP) is an interesting alternative for exact query processing. It is a tool for dealing with the huge data volumes where response time is more important than perfect accuracy (this is typically the case during initial phase of data exploration). There are many techniques for AQP, one of them is based on probability density functions (PDF). PDFs are typically calculated using nonparametric data-driven methods. One of the most popular nonparametric method is the kernel density estimator (KDE). However, a very serious drawback of using KDEs is the large number of calculations required to compute them. The shape of final density function is very sensitive to an entity called bandwidth or smoothing parameter. Calculating it's optimal value is not a trivial task and in general is very time consuming. In this paper we investigate the possibility of utilizing two SIMD architectures: SSE CPU extensions and NVIDIA's CUDA architecture to accelerate finding of the bandwidth. Our experiments show orders of magnitude improvements over a simple sequential implementation of classical algorithms used for that task.
APPLICATION OF AUTONOMIC COMPUTING PRINCIPLES IN VIRTUALIZED ENVIRONMENT

The infrastructure of IT-sector is heterogeneous and complex. It is difficult for a system administrator to manage these complex systems. This led to complex, unmanageable and insecure systems. A new approach to solve this problem is the IT infrastructure automation. Autonomic computing is the solution to manage complex infrastructure which provides "must have" solutions for the problems above. The increased resource utilization in IT made the enterprises to use the costly physical servers. These physical servers were under-utilized. Virtualization is a technology with efficient and better utilization of resources. Virtualization and autonomic computing are of major importance for the IT-sector and could be successfully combined to reach the ideals of the autonomic computing. This paper addresses the design issues in automating live migration of virtual machines in virtualized environment using autonomic computing.
Linear trend of resting-state fMRI time series

Although linear trend removing has often been implemented as a routine preprocessing step in resting-state functional magnetic resonance imaging (RS-fMRI) data analysis, the spatial distribution of the magnitude of linear trend is still unclear. Further, it is interesting whether there will be any difference of the linear trend magnitude between different resting-states. For the first aim, we analyzed 5 RS-fMRI datasets from 5 different scanners (namely Beijing-Simens-3T, Cambridge-Siemens3T, CCBD-GE750-3T, Milwaukee-GE-3T, and Oulu-GE-1.5T). One-sample t-tests on the regression coefficient (i.e., the magnitude of linear trend) were performed for each datasets. For the second aim, we used 2 datasets in each of which different states were compared, one containing eyes-open resting-state (EO-RS) vs. eyes-closed resting-state (EC-RS) and the other containing two steady-state tasks, i.e., real-time finger force feedback (RT-FFF) and sham finger force feedback (S-FFF) tasks. Paired t-tests were performed between EO-RS and EC-RS, and between RT-FFF and S-FFF. One-sample t-tests showed that the spatial pattern of linear trend of RS-fMRI time series were quite different between different manufactures. The 3T SIEMENS scanners showed positive linear trend in almost all part of the brain, while GE scanners showed primarily negative linear trend in most part of the brain. Paired ttests showed some differences between paired conditions; differences between EO-RS and EC-RS were mainly in cuneus and eyeballs, and differences between RT-FFF and S-FFF were found in the thalamus, anterior cingulate gyrus, and right sensorimotor cortex. The current study indicated that, while the manufacturer-dependent linear ch in aX iv :2 01 71 1. 00 27 7v 1 trend of RS-fMRI time series were mostly scanner-related noise, the linear trend may also be physiological noise (eyeballs) or even physiologically meaningful, especially during steady-state tasks.
AN EFFICIENT COMPRESSION ALGORITHM FOR HYPERSPECTRAL IMAGES BASED ON A MODIFIED CODING FRAMEWORK OF H . 264 / AVC

In this paper, an efficient compression algorithm for hyperspectral images is proposed, which is based on a modified coding framework of H.264/AVC. In virtue of the flexible and diverse prediction modes of H264/AVC, the most suitable ones are assigned for the macroblocks ( 16 16× pixel regions of a band) of the hyperspectral images other than for the whole band images. Only the 4 4× mode is employed for the intra-band prediction in view of the fact that correlation coefficients of pixels separated by not more than four pixels in the spatial domain are greater than 0.65 at most cases. After the optimal reference band is determined by the fast reference band selecting algorithm, the inter-band prediction mode is determined then. Thus, a modified coding scheme is proposed to speed up the implemental process with the fast reference band selection algorithm, the integer DCT and the quantification which just needs multiplication and bit-shifts operations. Several AVIRIS images are used to evaluate the proposed algorithm. Compared with the stateof-the-art 3D-based compression algorithms, the proposed algorithm achieves the best compression performance at different rates.
GIS VERSIONING MANAGEMENT – THE APPROACH OF THE SURVEY OF ISRAEL

In the last two decades, there has been considerable progress in mapping and spatial data collection and today many developed countries are completely mapped. The three main challenges for National Mapping Agencies in these countries are: • How to effectively update and revise these databases with new information about our rapidly changing environment • How to integrate these geospatial data in the national databases utilizing standard relationships for data interchange • How to manage the history of changes and to manage past versions of datasets The following report describes the new approach of the Survey of Israel (SOI) for spatial data consolidation and for map revision. This approach is based on a unique spatial identifier given for every spatial feature in the database. The properties and maintenance of this identifier will be discussed along with various options that were investigated. Using this unique identifier SOI developed an algorithm to create Add, Delete and Update tables. These tables present an efficient method to store and distribute revisions and updates of the national spatial database to various organizations. The approach also allows for efficient documentation of past changes and the maintenance of historical spatial data thus creating a spatial-temporal framework for databases that includes a timestamp versioning options. The significance of this approach to the Israeli National Spatial Data Infrastructure will be assessed using examples and a case study.
Three-Dimensional Chaotic Advection by Mixed Layer Baroclinic Instabilities

AbstractThree-dimensional (3D) finite-time Lyapunov exponents (FTLEs) are computed from numerical simulations of a freely evolving mixed layer (ML) front in a zonal channel undergoing baroclinic instability. The 3D FTLEs show a complex structure, with features that are less defined than the two-dimensional (2D) FTLEs, suggesting that stirring is not confined to the edges of vortices and along filaments and posing significant consequences on mixing. The magnitude of the FTLEs is observed to be strongly determined by the vertical shear. A scaling law relating the local FTLEs and the nonlocal density contrast used to initialize the ML front is derived assuming thermal wind balance. The scaling law only converges to the values found from the simulations within the pycnocline, while it displays differences within the ML, where the instabilities show a large ageostrophic component. The probability distribution functions of 2D and 3D FTLEs are found to be non-Gaussian at all depths. In the ML, the FTLEs wavenumb.
Chapter 3. Educating teachers for cultural diversity and social justice

In what contexts are teachers taught how to address racism and other forms of oppression in schools and society? How do we develop culturally relevant pedagogy for all students, in the interests of equity and social justice? And when teachers do receive such training, what might it look like and how do we evaluate it? It has been suggested that debate about multicultural education tends to take place against a background of social stability and shared debate of the kind that characterizes the wealthy countries of the ‘North’ (Morrow, 1996: 99). Yet it should be at the forefront of discussions in all societies seeking to teach for social justice, global perspectives and equity. Discussions of issues and strategies in multicultural teacher education seem, in the literature, to be addressing mainly the context of the white-dominant countries. Many compelling teacher education experiments in developing intercultural knowledge and skills are described, but the literature also suggests that an engagement with these issues is the exception rather than the rule. Most teacher education courses carry out only minimally their rhetorical goals of
Visual disruption using the thermal lensing effect in the human eye: pilot study

Abstract. At select wavelengths, near infrared (IR) light is absorbed in the preretinal media of the eye. This produces small transient increases in temperature that temporarily alter the local index of refraction. If the IR exposure is sufficiently high, a momentary reduction in the focusing power of the eye can be induced through an effect known as thermal lensing. Fundamental optical interaction and safety aspects of this phenomenon have been demonstrated previously in animal and artificial eye models. However, whether the effect will induce an observable visual change in human subjects has not been explored. Here, results of a pilot study are shown where eight human subjects were exposed to an IR laser at levels that were below the safe exposure limit. The exposures did induce a transient visual distortion if sufficiently high levels were used. While the description of the visual change varied between subjects, this experiment was able to determine a general guideline for power needed to induce significant effects in human subjects.
The open cluster Berkeley 53

We present a photometric study of the neglected open cluster Berkeley 53. We derived its fundamental parameters, such as the age, the interstellar reddening, and the distance from the Sun, based on BV photometry combined with near-infrared JHKS data. The structure and the mass function of the cluster were also studied and the total number of members and the total mass were estimated. The cluster was found to be a rich and massive stellar system, located in the Perseus Arm of the Milky Way, 3.1 ± 0.1 kpc from the Sun. Its age exceeds 1 Gy but it seems tobe very young in the context of its dynamical evolution. The analysis of the two-color diagrams and color-magnitude diagrams indicates that the cluster is significantly reddened. However, both methods resulted in different values of E (B – V), i.e. 1.21 ± 0.04 and 1.52 ± 0.01, respectively. This discrepancy suggests the presence of an abnormal interstellar extinction law toward the cluster (© 2009 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Root Isolation for Bitstream Polynomials with Adaptive Approximation Demand

We describe a new approach to isolate the roots (either real or complex) of a square-free polynomial F with real coefficients. It is assumed that each coefficient of F can be approximated to any specified error bound and we refer to such coefficients as bitstream coefficients. The presented method is exact, complete and deterministic. Compared to previous approaches [11, 20] we improve in two aspects. Firstly, our approach can be combined with any existing subdivision method for isolating the roots of a rational polynomial. Secondly, the approximation demand on the coefficients and the bit complexity of our approach is considerably smaller. In particular, we can replace the worst-case quantity σF by the averagecase quantity ∏i=1 n √ σi, where σi denotes the minimal distance of the i−th root ξi of F to any other root of F , σF := mini σi, and n = degF . For polynomials with integer coefficients our method matches the best bounds known for existing practical algorithms that perform exact operations on the input coefficients.
Internet Science Risk , Risk Perception , and Cyberwar

The rapid speed of computerization in all aspects of life renders us more and more dependent on elements of electronic infrastructure. At the same time, it opens up and widens a space of possible attacks on this backbone of our society. Direct impacts like power outages, water outages or even structural damage on critical systems are not the only consequences of possible attacks. Public reactions to this first level of events can ripple and cause a chain of instances that can even dominate and surpass the original problems. The comparably quick renewal cycle of technology provides an excellent opportunity to rapidly adapt to new technical aspects of security as well as discoveries in psychological and cultural research regarding the public perception of risk. This paper will utilize the Stuxnet cyber incident and its consequences to point out possible measures that could be incorporated in the design of future systems.