Miracle-dz/UniFAR-FTUs huggingface dataset:
GGA1 Acts as a Spatial Switch Altering Amyloid Precursor Protein Trafficking and Processing

The β-amyloid (Aβ) precursor protein (APP) is cleaved sequentially by β-site of APP-cleaving enzyme (BACE) and γ-secretase to release the Aβ peptides that accumulate in plaques in Alzheimer's disease (AD). GGA1, a member of the Golgi-localized γ-ear-containing ARF-binding (GGA) protein family, interacts with BACE and influences its subcellular distribution. We now report that overexpression of GGA1 in cells increased the APP C-terminal fragment resulting from β-cleavage but surprisingly reduced Aβ. GGA1 confined APP to the Golgi, in which fluorescence resonance energy transfer analyses suggest that the proteins come into close proximity. GGA1 blunted only APP but not notch intracellular domain release. These results suggest that GGA1 prevented APP β-cleavage products from becoming substrates for γ-secretase. Direct binding of GGA1 to BACE was not required for these effects, but the integrity of the GAT (GGA1 and TOM) domain of GGA1 was. GGA1 may act as a specific spatial switch influencing APP trafficking and processing, so that APP–GGA1 interactions may have pathophysiological relevance in AD.
An effectiveness measure for software clustering algorithms

Selecting an appropriate software clustering algorithm that can help the process of understanding a large software system is a challenging issue. The effectiveness of a particular algorithm may be influenced by a number of different factors, such as the types of decompositions produced, or the way clusters are named. In this paper, we introduce an effectiveness measure for software clustering algorithms based on Mojo distance, and describe an algorithm that calculates its value. We also present experiments that demonstrate its improved performance over previous measures, and show how it can be used to assess the effectiveness of software clustering algorithms.
Data-driven design and robust implementation of monitoring and fault detection system for AMT vehicles

Automated manual transmission (AMT) and its automatic shifting is of significance on the improvement of driveline performance and reliability. Due to numbers of electrical, mechanical and vehicle longitudinal dynamics, both establishing an analytical AMT model and designing its monitoring and fault detection (MFD) system become too complicated to implement for automotive engineers and servicemen. To solve the problem, in this paper, the data-driven design approach is introduced. The central idea behind the scheme is to construct a parity vector-based residual generator from test data and, based on on-line ones, to realize a robust adaptive residual generation against changes along with driving conditions. A simulation study using a driveline model constructed by the commercial software AMESim is given to illustrate the availability of the designed MFD system.
On Column Selection in Approximate Kernel Canonical Correlation Analysis

We study the problem of column selection in large-scale kernel canonical correlation analysis (KCCA) using the Nystr\"om approximation, where one approximates two positive semi-definite kernel matrices using "landmark" points from the training set. When building low-rank kernel approximations in KCCA, previous work mostly samples the landmarks uniformly at random from the training set. We propose novel strategies for sampling the landmarks non-uniformly based on a version of statistical leverage scores recently developed for kernel ridge regression. We study the approximation accuracy of the proposed non-uniform sampling strategy, develop an incremental algorithm that explores the path of approximation ranks and facilitates efficient model selection, and derive the kernel stability of out-of-sample mapping for our method. Experimental results on both synthetic and real-world datasets demonstrate the promise of our method.
Cannabis Use as Risk or Protection for Type 2 Diabetes: A Longitudinal Study of 18 000 Swedish Men and Women

Aims. Whether or not cannabis use may increase or decrease the risk of type 2 diabetes is not clear. We analyzed the association between cannabis and subsequent type 2 diabetes and if a potential positive or reverse association persisted after controlling for potential confounders. Methods. In this population-based cohort study, 17,967 Swedish men and women (aged 18–84 years), who answered an extensive questionnaire in 2002 (including questions on cannabis use), were followed up for new cases of type 2 diabetes (n = 608) by questionnaire (in 2010) and in health registers during 2003–2011. Odds ratios (ORs) with 95% CIs were estimated in a multiple logistic regression analysis. Potential confounders included age, sex, BMI, physical inactivity, smoking, alcohol use, and occupational position. Results. The crude association showed that cannabis users had a reduced risk of type 2 diabetes OR = 0.68 (95% CIs: 0.47–0.99). However, this inverse association attenuated to OR = 0.94 (95% CIs: 0.63–1.39) after adjusting for age. Conclusions. The present study suggests that there is no association between cannabis use and subsequent type 2 diabetes after controlling for age. To make more robust conclusions prospective studies, with longer periods of follow-up and more detailed information about cannabis use, are needed.
The Benefits of Exercise on Structural and Functional Plasticity in the Rodent Hippocampus of Different Disease Models

Abstract In this review, the benefits of physical exercise on structural and functional plasticity in the hippocampus are discussed. The evidence is clear that voluntary exercise in rats and mice can lead to increases in hippocampal neurogenesis and enhanced synaptic plasticity which ultimately result in improved performance in hippocampal-dependent tasks. Furthermore, in models of neurological disorders, including fetal alcohol spectrum disorders, traumatic brain injury, stroke, and neurodegenerative disorders including Alzheimer’s, Parkinson’s and Huntington’s disease exercise can also elicit beneficial effects on hippocampal function. Ultimately this review highlights the multiple benefits of exercise on hippocampal function in both the healthy and the diseased brain.
Neuronal Clearance of Amyloid-β by Endocytic Receptor LRP1

Alzheimer's disease (AD) is the most prevalent form of dementia in the elderly population. Accumulation, aggregation, and deposition of amyloid-β (Aβ) peptides generated through proteolytic cleavage of amyloid precursor protein (APP) are likely initiating events in the pathogenesis of AD. While Aβ production is accelerated in familial AD, increasing evidence indicates that impaired clearance of Aβ is responsible for late-onset AD. Because Aβ is mainly generated in neurons, these cells are predicted to have the highest risk of encountering Aβ among all cell types in the brain. However, it is still unclear whether they are also involved in Aβ clearance. Here we show that receptor-mediated endocytosis in neurons by the low-density lipoprotein receptor-related protein 1 (LRP1) plays a critical role in brain Aβ clearance. LRP1 is known to be an endocytic receptor for multiple ligands including Aβ. Conditional knock-out of Lrp1 in mouse forebrain neurons leads to increased brain Aβ levels and exacerbated amyloid plaque deposition selectively in the cortex of amyloid model APP/PS1 mice without affecting Aβ production. In vivo microdialysis studies demonstrated that Aβ clearance in brain interstitial fluid is impaired in neuronal Lrp1 knock-out mice. Because the neuronal LRP1-deletion did not affect the mRNA levels of major Aβ degrading enzymes, neprilysin and insulin-degrading enzyme, the disturbed Aβ clearance is likely due to the suppression of LRP1-mediated neuronal Aβ uptake and degradation. Together, our results demonstrate that LRP1 plays an important role in receptor-mediated clearance of Aβ and indicate that neurons not only produce but also clear Aβ.
Case study of applying SPLE to development of network switch products

Software product line engineering has spread as a technique for promoting the efficient development of embedded products with many product line-ups. During the development of network switch products at Hitachi Metals, Ltd., the number of development man-months increased as the number of product line-ups increased. Therefore, we shifted our development paradigm to product line development for efficient product development. We classified software assets as implementation assets, test assets, and design assets, and from these three assets, we extracted common objects and integrated them as reusable elements. By doing so, we promoted the efficient development of software assets and reduced the contradictions between the contents of the software assets. As a result, we reduced the amount of the source code by 53.1%. In this paper, we discuss the details of our technique and the effect of applying it. In addition, we discuss how you can apply our technique in the development of other products.
Modeling of axial flux permanent-magnet machines

In modeling axial field machines, three-dimensional (3-D) finite-element method (FEM) models are required in accurate computations. However, 3-D FEM analysis is generally too time consuming in industrial use. In order to evaluate the performance of the axial flux machine rapidly, an analytical design program that uses quasi-3-D computation is developed. In this paper the main features of the developed program are illustrated. Results given by the program are verified with two-dimensional and 3-D finite element computations and measurements. According to the results, it is possible to evaluate the performance of the surface-mounted axial flux PM machine with reasonable accuracy via an analytical model using quasi-3-D computation.
Creation of X-Ray Holes with Cool Rims in Cooling Flows

The density irregularities and holes visible in many Chandra X-ray images of cluster and galactic cooling flows can be produced by symmetrically heated gas near the central galactic black hole. As the heated gas rises away from the galactic center, a relatively small number of large plumes and bubbles are formed in qualitative agreement with the observed features. The expanding centrally heated gas drives a shock into the surrounding gas, displacing it radially. Both computational and analytic results show that the ambient gas near the bubble is cooled by expansion, accounting for the cool rims commonly observed around X-ray holes in cooling flows.
Generalized Sampling and Variance in Counterfactual Regret Minimization

In large extensive form games with imperfect information, Counterfactual Regret Minimization (CFR) is a popular, iterative algorithm for computing approximate Nash equilibria. While the base algorithm performs a full tree traversal on each iteration, Monte Carlo CFR (MCCFR) reduces the per iteration time cost by traversing just a sampled portion of the tree. On the other hand, MCCFR's sampled values introduce variance, and the effects of this variance were previously unknown. In this paper, we generalize MCCFR by considering any generic estimator of the sought values. We show that any choice of an estimator can be used to probabilistically minimize regret, provided the estimator is bounded and unbiased. In addition, we relate the variance of the estimator to the convergence rate of an algorithm that calculates regret directly from the estimator. We demonstrate the application of our analysis by defining a new bounded, unbiased estimator with empirically lower variance than MCCFR estimates. Finally, we use this estimator in a new sampling algorithm to compute approximate equilibria in Goofspiel, Bluff, and Texas hold'em poker. Under each of our selected sampling schemes, our new algorithm converges faster than MCCFR.
Simulation of In Vitro Dissolution Behavior Using DDDPlus™

Dissolution testing is a performance test for many dosage forms including tablets and capsules. The objective of this study was to evaluate if computer simulations can predict the in vitro dissolution of two model drugs for which different dissolution data were available. Published montelukast sodium and glyburide dissolution data was used for the simulations. Different pharmacopeial and biorelevant buffers, volumes, and rotations speeds were evaluated. Additionally, a pH change protocol was evaluated using these buffers. DDDPlus™ 3, Beta version (Simulation Plus, Inc.), was used to simulate the in vitro dissolution data. The simulated data were compared with the in vitro data. A regression coefficient between predicted and observed data was used to assess the simulations. The statistical analysis of Montelukast sodium showed that there was a significant correlation between the in vitro release data and the predicted data for all cases except for one buffer. For glyburide, there was also a significant correlation between the experimental data and the predicted data using single pH conditions. Using the dynamic pH protocol, a correlation was significant for one biorelevant media. The simulations showed that both in vitro drug releases were sensitive to solubility effects which confirmed their BCS class II category. Computer simulations of the in vitro release using DDDPlus™ have the potential to estimate the in vivo dissolution at an early stage in the drug development process. This might be used to choose the most appropriate dissolution condition to establish IVIVC and to develop biorelevant in vitro performance tests to capture critical product attributes for quality control procedures in quality by design environments.
A High Assurance Window System Prototype

This paper describes the architecture of a prototype multilevel secure windowing system based on the X Window System. The prototype, known as TX, is designed to meet the class B3 architectural requirements of the Trusted Computer System Evaluation Criteria (TCSEC). The architecture and prototype described here demonstrate that high assurance windowing technology is feasible.The TX architecture is based on the encapsulation of untrusted functionality, such as that contained in an ordinary X server, using a relatively small amount of trusted applications code. The untrusted functionality is then polyinstantiated or replicated once for each active sensitivity level. This leads to a combination of high assurance and complex functionality while reducing the evaluation effort to a tractable level. The architecture of TX is described, and its information flow and visible labeling security policies are discussed. The trade-offs that were made to maintain assurance while achieving other software engineering goals are considered. TX is compared with several other trusted windowing systems.
Organising as a strategy to reach precarious and marginalised workers. A review of debates on the role of the political dimension and the dilemmas of representation and solidarity

Organising as a trade union strategy has caught the imagination of the labour movement over the past 20 years or so. The vast possibilities of new forms of organising go hand in hand with concern about its highly constrained and sometimes hierarchical use. This article looks at key aspects of the debate, focusing on the question of how new forms of organising reach out to more vulnerable and precarious workers. Similar to other colleagues in the field, we conclude that there are political and organisational gaps in organising strategies and that new forms of organising can in some instances be bureaucratic and apolitical. Furthermore, it is important to extend our understanding of the role of trade unions in relation to the state, organised working class constituencies, and social rights, especially as, with regard to vulnerable workers and their organisations, questions of regulation are highly sensitive and challenging.
Cross-Linking as an Adjuvant Treatment for Tectonic Corneal Lamellar Graft Preparation

Purpose: To describe a new surgical approach for the tectonic reconstruction of the anterior ocular segment and the management of scleral and conjuctival melting. Methods: Case series of patients demonstrating anterior segment anomalies, such as scleral and conjunctival melting. The anterior stromal part of a pre-cut corneal graft for Descemet’s stripping automated endothelial keratoplasty (DSAEK) was cross-linked with riboflavin and ultraviolet A irradiation and was used to cover scleral (scleral melting in a patient with necrotizing scleritis, one case) and conjuctival (dehiscence of the conjunctiva in patients with anti-glaucomatous valve exposure, two cases) areas. The endothelial part of all corneal grafts was used for DSAEK in patients with need of corneal endothelial transplantation. Results: Repair of scleral and conjuctival melting was successful in all cases. No intra- or post- operative complications occured. Visual acuity of all patients remained stable during the follow up period. One year postoperatively the corneal graft remained in place and no signs of inflammation were evident, while all grafts were epithelialized. Conclusions: The use of cross-linked corneal graft for the tectonic reconstruction of the anterior ocular segment represents an adequate surgical approach for the management of scleral and conjuctival melting; while, at the same time it offers the advantage of using one corneal graft for two recipients.
Pollution Externality, Endogenous Labor Supply and Environmental Policy Choice

By developing an endogenous growth model on the base of Lucas (1988) embodying the endogenous labor supply and pollution externality, this paper aims to examine the interaction between negative pollution externalities, endogenous leisure- labor choice, human capital investment and sustainable development. Within this framework, we first study the optimum in the planned economy and derive the conditions under which the sustainable growth path is both feasible and optimal. Furthermore, we show that an increase in the productivity of human capital sector, in the abatement expenditure elasticity of pollution damage reduction and in environment consciousness will stimulate the long-run growth rate. But a rise in leisure consciousness and in the output elasticity of pollution damage incremental will lower the long-run growth rate. Finally, it is also revealed in our model that a government could intervene and bring the market economy onto a sustainable and optimal growth path through conducting public abatement policies or levying Pigouvian taxes.
Semi-supervised feature extraction with local temporal regularization for EEG classification

Extreme energy ratio (EER) is a recently proposed feature extractor to learn spatial filters for electroencephalogram (EEG) signal classification. It is theoretically equivalent and computationally superior to the common spatial patterns (CSP) method which is a widely used technique in brain-computer interfaces (BCIs). However, EER may seriously overfit on small training sets due to the presence of large noise. Moreover, it is a totally supervised method that cannot take advantage of unlabeled data. To overcome these limitations, we propose a regularization constraint utilizing local temporal information of unlabeled trails. It can encourage the temporal smoothness of source signals discovered, and thus alleviate their tendency to overfit. By combining this regularization trick with the EER method, we present a semi-supervised feature extractor termed semi-supervised extreme energy ratio (SEER). After solving two eigenvalue decomposition problems, SEER recovers latent source signals that not only have discriminative energy features but also preserve the local temporal structure of test trails. Compared to the features found by EER, the energy features of these source signals have a stronger generalization ability, as shown by the experimental results. As a nonlinear extension of SEER, we further present the kernel SEER and provide the derivation of its solutions.
Test Suite Prioritization by Switching Cost

Test suite generation and prioritization are two main research fields to improve testing efficiency. Combinatorial testing has been proven as an effective method to generate test suite for highly configurable software systems, while test suites are often prioritized by interaction coverage to detect faults as early as possible. However, for some cases, there exists reasonable cost of reconfiguring parameter settings when switching test cases in different orders. Surprisingly, only few studies paid attention to it. In this paper, by proposing greedy algorithms and graph-based algorithms, we aim to prioritize a given test suite to minimize its total switching cost. We also compare two different prioritization strategies by a series of experiments, and discuss the advantages of our prioritization strategy and the selection of prioritization techniques. The results show that prioritization by switching cost can improve testing efficiency and our prioritization strategy can produce a small test suite with a reasonably low switching cost. This prioritization can be used widely and help locate fault causing interactions. The results also suggest that when testing highly configurable software systems and no knowledge of fault detection can be used, prioritization by switching cost is a good choice to detect faults earlier.
XSS Attack Detection in JSP and PHP : A Meta-Analysis Review

When data is uploaded from any means of data communication, data may be leaked or attacked. Cross-site scripting (XSS) attacks are the most vulnerable types of attack found now days. It empowers aggressors to infuse customer side script into Web pages saw by different clients. By the help of this type of injection you can control the page by inserting, updating and modifying the data. SQL Injection attacks are easily possible in PHP, JSP and ASP interfaces. It is so because of the older function interface. In case of Java/J2EE and ASP. Net interface it is not so easy because of the programmable interfaces. The main hassles due to the attacks are: Confidentiality, Authentication, Authorization and Integration. If the website is data driven, SQL Injection attacks are easy to employ. So due to the above characteristics controlling the attacks parameters are essential. Our paper main aim is to prevent and detect different types of attack. So for this means analysis and study has been presented.
Characterizations of Decomposable Dependency

Decomposable models are dependency models having the characteristic of being repres-entable by means of both undirected and directed graphical models, as well as a number of important and useful properties. Decomposable models can be characterized as the kind of dependency models that are isomorphic to chordal graphs. The aim of this paper is to nd characterizations of decomposable models in terms of independence relationships. This is achieved by adding a single property to the well-known set of axioms characterizing dependency models isomorphic to undirected graphs.
Detection of C5N− and Vibrationally Excited C6H in IRC +10216

We report the detection in the envelope of the C-rich star IRC +10216 of four series of lines with harmonically related frequencies: B1389, B1390, B1394, and B1401. The four series must arise from linear molecules with mass and size close to those of C6H and C5N. Three of the series have half-integer rotational quantum numbers; we assign them to the 2Δ and 2Σ− vibronic states of C6H in its lowest (ν11) bending mode. The fourth series, B1389, has integer J with no evidence of fine or hyperfine structure; it has a rotational constant of 1388.860(2) MHz and a centrifugal distortion constant of 33(1) Hz; it is almost certainly the C5N− anion.