Miracle-dz/UniFAR-FTUs huggingface dataset:
Brief Report: Increased Apoptosis in Advanced Atherosclerotic Lesions of Apoe−/− Mice Lacking Macrophage Bcl-2

Objective—Macrophage apoptosis plays important roles in atherosclerosis. Bcl-2 is a key cell survival molecule, but its role in macrophage apoptosis in atherosclerosis is not known. The goal herein was to determine the effect of macrophage-targeted deletion of Bcl-2 on macrophage apoptosis in atherosclerotic lesions of Apoe−/− mice. Methods and Results—Bcl2flox-LysMCre mice were created as a model of macrophage Bcl-2 deficiency. Macrophages from these mice were more susceptible to apoptosis than those from control Bcl2WT-LysMCre mice. The mice were bred onto the Apoe−/− background and fed a Western-type diet for 4 or 10 weeks. Apoptotic cells were equally very rare in the lesions of both groups of the 4-week-diet mice, and there was no difference in lesion area. However, Bcl2flox-LysMCre;Apoe−/− plaques from the 10-week-diet protocol had a 40% to 45% increase in apoptotic cells and, in female mice, a ≈25% increase in plaque necrosis (P<0.05) compared with Bcl2WT-LysMCre lesions. Conclusions—Macrophage Bcl-2 plays a protective role against macrophage apoptosis specifically in advanced atherosclerotic lesions of Apoe−/− mice.
A Novel Digital Ultrasound System for Experimental Research Activities

Commercial ultrasound (US) equipment, although widely employed in diagnostic applications, is not suitable for the development and test of new investigation methods. Their typical architecture, designed for clinical use, is often "closed" and does not fit the requirements of flexibility, data access, programmability, which are necessary for the implementation of original approaches. More flexibility is achieved in high-level platforms, but they are typically characterized by high cost and dimensions. In this paper, a novel US system, specifically designed for research purposes, is presented. Its architecture is based on hi-end programmable devices to obtain the maximum flexibility with minimum cost and size. A preliminary example of application involving simultaneous B-mode and an experimental Doppler technique is discussed.
Impedance Spectrum in Cortical Tissue: Implications for Propagation of LFP Signals on the Microscopic Level

Visual Abstract Brain research investigating electrical activity within neural tissue is producing an increasing amount of physiological data including local field potentials (LFPs) obtained via extracellular in vivo and in vitro recordings. In order to correctly interpret such electrophysiological data, it is vital to adequately understand the electrical properties of neural tissue itself. An ongoing controversy in the field of neuroscience is whether such frequency-dependent effects bias LFP recordings and affect the proper interpretation of the signal. On macroscopic scales and with large injected currents, previous studies have found various grades of frequency dependence of cortical tissue, ranging from negligible to strong, within the frequency band typically considered relevant for neuroscience (less than a few thousand hertz). Here, we performed a detailed investigation of the frequency dependence of the conductivity within cortical tissue at microscopic distances using small current amplitudes within the typical (neuro)physiological micrometer and sub-nanoampere range. We investigated the propagation of LFPs, induced by extracellular electrical current injections via patch-pipettes, in acute rat brain slice preparations containing the somatosensory cortex in vitro using multielectrode arrays. Based on our data, we determined the cortical tissue conductivity over a 100-fold increase in signal frequency (5–500 Hz). Our results imply at most very weak frequency-dependent effects within the frequency range of physiological LFPs. Using biophysical modeling, we estimated the impact of different putative impedance spectra. Our results indicate that frequency dependencies of the order measured here and in most other studies have negligible impact on the typical analysis and modeling of LFP signals from extracellular brain recordings.
Covariance Structure Models for Gene Expression Microarray Data

Covariance structure models are applied to gene expression data using a factor model, a path model, and their combination. The factor model is based on a few factors that capture most of the expression information. A common factor of a group of genes may represent a common protein factor for the transcript of the co-expressed genes, and hence, it has a biological interpretation. With simultaneous regressions among variables, a path analysis model is used to specify a structure based on biological pathways. Path models are applied to a simple cell cycle and the tricarboxylic acid cycle from yeast gene expression data. Finally, combining factor and path models, a covariance structure model produces a more complicated pathway structure of the yeast cell cycle involving genes and their underlying factors. All the models are estimated by maximum likelihood using the EQS software package.
Macular Pigment Optical Density Measured by Heterochromatic Modulation Photometry

Purpose To psychophysically determine macular pigment optical density (MPOD) employing the heterochromatic modulation photometry (HMP) paradigm by estimating 460 nm absorption at central and peripheral retinal locations. Methods For the HMP measurements, two lights (B: 460 nm and R: 660 nm) were presented in a test field and were modulated in counterphase at medium or high frequencies. The contrasts of the two lights were varied in tandem to determine flicker detection thresholds. Detection thresholds were measured for different R:B modulation ratios. The modulation ratio with minimal sensitivity (maximal threshold) is the point of equiluminance. Measurements were performed in 25 normal subjects (11 male, 14 female; age: 30±11 years, mean ± sd) using an eight channel LED stimulator with Maxwellian view optics. The results were compared with those from two published techniques – one based on heterochromatic flicker photometry (Macular Densitometer) and the other on fundus reflectometry (MPR). Results We were able to estimate MPOD with HMP using a modified theoretical model that was fitted to the HMP data. The resultant MPODHMP values correlated significantly with the MPODMPR values and with the MPODHFP values obtained at 0.25° and 0.5° retinal eccentricity. Conclusions HMP is a flicker-based method with measurements taken at a constant mean chromaticity and luminance. The data can be well fit by a model that allows all data points to contribute to the photometric equality estimate. Therefore, we think that HMP may be a useful method for MPOD measurements, in basic and clinical vision experiments.
Equivalent circuit modeling of on-chip inductors using feature-based optimization

We propose a method for extraction of equivalent circuit model for on-chip spiral inductor. The method is based on optimization of circuit elements based on feature points extracted from frequency dependent response. The accuracy of the method is validated by extracting a set of models from electromagnetic simulations of on-chip rectangular spiral inductors. An excellent agreement is achieved between the model and simulation data.
Precarity’s Prospect: Contingent Control and Union Renewal in the Retail Sector

Precarity and deunionization have grown up (or down) together. Yet the focus of union renewal scholars on the forms and constituencies of organizing has neglected a holistic appraisal of their connection and the role of work itself. This article uses a focused examination of frontline retail to understand the links between deteriorating job quality, new modes of control and their effects on worker consciousness. Based on qualitative interviews with 75 workers at Macy’s and Target stores, I identify a paradigm of contingent control embodied in precarious employment, routinized tasks, “soft” management and a largely “secondary” workforce. This regime diminishes job identity and opposition but heightens workers’ solidarity, pointing toward a model of community-based industrial unionism that could serve as an organizational vehicle to reverse the growth of precarity.
A Review of Acupoint Specificity Research in China: Status Quo and Prospects

The theory of acupoint specificity is the basis for elucidating the actions of acupoints as employed in clinical practice. Acupoint specificity has become a focus of attention in international research efforts by scholars in the areas of acupuncture and moxibustion. In 2006, the Chinese Ministry of Science approved and initiated the National Basic Research Program (973 Program), one area of which was entitled Basic Research on Acupoint Specificity Based on Clinical Efficacy. Using such approaches as data mining, evidence-based medicine, clinical epidemiology, neuroimaging, molecular biology, neurophysiology, and metabolomics, fruitful research has been conducted in the form of literature research, clinical assessments, and biological studies. Acupoint specificity has been proved to exist, and it features meridian-propagated, relative, persistent, and conditional effects. Preliminarily investigations have been made into the biological basis for acupoint specificity.
semanticSBML a Tool for Creating , Checking , Annotating and Merging of SBML Documents

The System Biology Markup Language (SBML) is a common language for expressing biochemical sets of reactions that are accompanied by mathematical statements such as kinetic infomation. The program semanticSBML provides the systems biology community with the ability to integrate (merge) and annotate models with MIRIAM annotations. User interfaces are provided on multiple levels: application programming interface (API), console interface (CI), graphical user interface (GUI). This work aims to enable a full support of SBML level 2 version 3 for the merging of models (including mathematical statements) and the manipulation of MIRIAM annotations (including annotation qualifiers). It is based on the previous work of the Computational Systems Biology Group (Max Planck Institute for Molecular Genetics) SBMLmerge. In its first development phase it extended SBMLmerge with a cross platform GUI and CI for all existing algorithms as well as a simplified API. In its second phase the underlying library (libSBML) was updated. The MIRIAM annotation manipulation as well as the merging algorithm was rewritten. The concept of annotation qualifiers was integrated. For the annotation and merging of models independent abstractions of systems biology models were developed. The merge abstraction is used for a better detection and resolution of conflicts in matching biological objects. Experiments were conducted to show the functional efficiency of the new algorithms as well as to show its possible uses.
Common-patterns based mapping for robot navigation

Mobile Robot Navigation problem has been extensively studied for decades, but a general solution which suits to various environments remains a challenging topic. One of the popular methods is to build the map and then navigate based on such map. Although most of the map-building approaches, either metric or topological, can efficiently create the map in an unknown environment, they rely on coordinates so that the error in self-pose estimation is unavoidable. In this paper, we alternatively propose a new map-building approach which is especially suitable to mobile robot navigation and does not rely on coordinates. Two key ingredients of the proposed method are (i) the self-organized common-pattern and (ii) the reasoning technique. First the common-patterns are generated in an unsupervised manner by the Self-Organizing and Incremental Neural Networks (SOINN). These patterns are used to incrementally represent the map of environments. The map generated in this manner is called Common-Patterns Based Map (CPM). The CPM is incrementally generated while the robot wandering in the environment. The reasoning technique is proposed to optimize the CPM. The evaluation of the proposed method is done by the experiment of 3D-physical robot simulators (Webots). All environments are the maze. The results show that the CPM is suitable to the navigation with an impressive rate of memory consumption. The loop can be closed successfully. The navigating performance is superior to that of reinforcement learning as it always requires only two episodes.
Impacts of hemlock decline and ecological considerations for hemlock stand restoration following hemlock woolly adelgid outbreaks

We present a synthesis of current knowledge and information of hemlock woolly adelgid (HWA, Adelges tsugae Annand) impact on hemlock forests and a conceptual framework of restoring damaged hemlock stands by HWA infestation. Native to Asia, HWA has been thriving in the eastern United States since the early 1950s and has become a serious pathological agent of both eastern hemlock (Tsuga canadensis (L.) Carriere) and Carolina hemlock (Tsuga caroliniana Engelm.) even since. By 2007, it was established in portions of 16 States from Maine to Georgia, where infestations covered about half of the range of hemlock and continuously spreading. The impacts of HWA induced hemlock mortality and decline on key ecosystem resource and processes are still not fully understood. Successful and effective restoration of the declined hemlock population is challenging and involves a complex process that commonly spans many years. Development of a management and restoration strategy that will establish priorities, standards, and practices could facilitate objective decisions and allocation of limited resources. In addition to encourage natural regeneration of hemlock in the damaged forest stands and both chemical and biological control, three strategies seem to stand out as possibilities: growing off-site stocks of hemlock seedlings for replant, creating hybrid hemlocks that are resistant to HWA, and replanting with the already resistant western hemlock or Chinese hemlock. Other ecological considerations in the context of restoring hemlock forests following HWA are also discussed. _____________________________________________________________________________________________________________
Resting Heart Rate and Risk of Cardiovascular Diseases and All-Cause Death: The Kailuan Study

Background Resting heart rate (RHR) predicts both cardiovascular and noncardiovascular death in different populations. However, the results of the association between RHR and cardiovascular diseases (CVDs) are inconsistent, especially for each subtype of CVDs. Objective The aim of this study was to prospectively explore the relationship between RHR and CVDs including myocardial infarction (MI), ischemic stroke, and hemorrhagic stroke and all-cause death in a general population. Methods The Kailuan study is a prospective longitudinal cohort study on cardiovascular risk factors and cardiovascular or cerebrovascular events. Hazard ratio (HR) with 95% confidence intervals (CI) were calculated using Cox regression modeling. Results We analyzed 92,562 participants (18–98 years old) in the Kailuan Study. CVDs were developed in 1,903 people during follow-ups. In multivariate analysis with adjustment for major traditional cardiovascular risk factors, HRs of the highest quintile group compared with the lowest quintile group of RHR for all-cause CVDs, MI, any stroke, ischemic stroke, hemorrhagic stroke, and all-cause death were 1.03 (95% CI, 0.98–1.07), 1.10 (95% CI, 1.01–1.20), 1.01 (95% CI, 0.97–1.06), 1.02 (95% CI, 0.96–1.07), 1.01 (95% CI, 0.92–1.11) and 1.18, (95% CI, 1.13–1.23), respectively. Conclusions The elevated RHR was independently associated with the increased risk for MI and all-cause death, but not for all-cause CVDs, any stroke, ischemic stroke, nor hemorrhagic stroke. This indicates that the elevated RHR might be a risk marker for MI and all-cause death in general populations.
Fusion of Log-Gabor wavelet and orthogonal locality sensitive discriminant analysis for face recognition

Local Sensitive Discriminant Analysis (LSDA) algorithm aims at finding a projection by maximizing the margin between data points from different classes in each local area. However, a major disadvantage of LSDA is that LSDA is non-orthogonal and this makes it difficult to estimate the intrinsic dimensionality and reconstruct the face data. Non-orthogonality distorts the local geometrical structure of the data submanifold. In this paper, an Orthogonal LSDA algorithm is proposed to preserve the local geometrical structure by computing the mutually orthogonal basis functions iteratively. First, the Log-Gabor wavelet is used to extract their corresponding Log-Gabor magnitude features (LGMF) by convolving the normalized face image with multi-scale and multi-orientation Log-Gabor filters. Then, OLSDA operates on LGMFs to extract the discriminative submanifolds. Furthermore, the nearest distance classifier is adopted for classification. Experiments based on the ORL and Yale face databases show the impressive performance of the proposed method.
The Influence of Game Addiction and Internet Addiction among University Students on Depression Stress and Anxiety Mediated by Self-regulation and Social Support

The present study investigated the direct and indirect influences of Internet and online game addiction on the levels of depression, anxiety, and stress mediated by self-regulation and social support among students of a private university in Thailand. The study’s sample consisted of 380 students of whom (218 females and 162 males) from a private university. Results from the path analysis indicated that the respondents’ level of game addiction and internet addiction had both direct and indirect influences on their levels of depression, anxiety, and stress. The findings were discussed in relation to the significance of self-regulation among university students and the level of social support provided by the University. ผลกระทบของการตดเกมและการตดอนเตอรเนตทมตอภาวะซมเศรา ความวตกกงวล และความเครยดของนกศกษาทมระดบการควบคมตวเองและการสนบสนนทางสงคมทแตกตาง งานวจยครงนเปนศกษาผลกระทบทงโดยตรงและโดยออมของการตดเกมสและตดอนเตอรเนตตอภาวะซมเศรา ความวตกกงวล และความเครยด โดยมปจจยเกยวกบการควบคมตวเองและการสนบสนนของสงคมมาเปนตวกลาง โดยศกษาจากนกศกษามหาวทยาลยเอกชนแหงหนง จำนวน 380 คน ซงเปนชาย 162 คนและหญง 218 คน ผลการวเคราะหขอมลพบวาระดบของการตดเกม และการตดอนเตอรเนตมผลกระทบทงทางตรงและทางออมอยางมนยสำคญตอระดบความซมเศรา ความวตกกงวล และความเครยด ผลการวจยยงแสดงใหเหนวา การควบคมตวเองและการสนบสนนจากสงคมเปนปจจยทสงผลอยางมนยสำคญตอผลกระทบของการตดเกมสและการตดอนเตอรเนตตอปจจยทางจตวทยาขางตน
Learning to Generate Networks

We investigate the problem of learning to generate complex networks from data. Specifically, we consider whether deep belief networks, dependency networks, and members of the exponential random graph family can learn to generate networks whose complex behavior is consistent with a set of input examples. We find that the deep model is able to capture the complex behavior of small networks, but that no model is able capture this behavior for networks with more than a handful of nodes.
Scalable nonconvex inexact proximal splitting

We study a class of large-scale, nonsmooth, and nonconvex optimization problems. In particular, we focus on nonconvex problems with composite objectives. This class includes the extensively studied class of convex composite objective problems as a subclass. To solve composite nonconvex problems we introduce a powerful new framework based on asymptotically nonvanishing errors, avoiding the common stronger assumption of vanishing errors. Within our new framework we derive both batch and incremental proximal splitting algorithms. To our knowledge, our work is first to develop and analyze incremental nonconvex proximal-splitting algorithms, even if we were to disregard the ability to handle nonvanishing errors. We illustrate one instance of our general framework by showing an application to large-scale nonsmooth matrix factorization.
ENHANCING SNAKES FOR VESSEL DETECTION IN ANGIOGRAPHY IMAGES

This paper proposes enhancements to the deformable models. Focusing on the problem of vessel segmentation, two general methods for improving the performance of the snakes are explained. The snake framework has a critical step when using the energy minimising scheme applied to the segmentation problem in computer vision: the potential map is based on the output of a low level feature detection over the original image, and therefore, the whole method, being theoretically sound and correct, is highly dependent on the quality of the image feature detector used to build the potential field. To avoid these problems we propose a statistical vessel learning for an optimal feature detection. The knowledge can be either embedded into the minimizing scheme or used within the traditional framework.
The critical elements of the patch management process

Introduction "After the flames from the slammer's attack were doused and the technology industry caught up on its lost sleep, we started asking questions. Why did this happen? Could we have prevented it? What can we do to keep such a thing from happening again? " These are some of the questions that the security industry asks after every major security incident. Today most security incidents are caused by flaws in software, called vulnerabilities. It is estimated that there are as many as 20 flaws per thousand lines of software code. Computer Emergency Response Team/Coordination Center (CERT/CC) statistics reveal that the number of vulnerabilities reported has increased dramatically over the years, from only 171 in 1995 to 8064 in 2006. Along with vulnerabilities, the sophistication of attack tools has also advanced over time. Using the interconnected nature of the Internet and automated attack tools, attackers exploit software vulnerabilities at an alarming rate to cause serious damage to organizations. Although the ultimate solution to fix software vulnerabilities is application of patches, until a few years ago the term "patch management" was not in the general vocabulary of even the most advanced information technology staff. Today, "patch management" is not only in the common vernacular of most IT staff, but it is also one of the most essential responsibilities of IT departments. Security threats stemming from the exploitation of vulnerabilities pose serious risks to corporations, including unauthorized access to systems, corruption or modification of data, and unavailability of system resources to authorized users. Systematically applying patches to vulnerable systems through effective patch management can effectively reduce the number of security lapses. It is estimated that 95% of security breaches could be prevented by keeping systems up-to-date with necessary patches. Though recognized as important for security, many organizations do not have a clear understanding of the elements of patch management and how these elements impact the success of the patch management process.