Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Monovalent Cations on Na+/Ca2+ Exchange and ATP‐Dependent Ca2+ Transport in Synaptic Plasma Membranes

Abstract: Two Ca2+ transport systems were investigated in plasma membrane vesicles isolated from sheep brain cortex synaptosomes by hypotonic lysis and partial purification. Synaptic plasma membrane vesicles loaded with Na+ (Na+i) accumulate Ca2+ in exchange for Na+, provided that a Na+ gradient (in→out) is present. Agents that dissipate the Na+ gradient (monensin) prevent the Na+/Ca2+ exchange completely. Ca2+ accumulated by Na+/Ca2+ exchange can be released by A 23187, indicating that Ca2+ is accumulated intravesicularly. In the absence of any Na+ gradient (K+i‐loaded vesicles), the membrane vesicles also accumulate Ca2+ owing to ATP hydrolysis. Monovalent cations stimulate Na+/Ca2+ exchange as well as the ATP‐dependent Ca2+ uptake activity. Taking the value for Na+/Ca2+ exchange in the presence of choline chloride (external cation) as reference, other monovalent cations in the external media have the following effects: K+ or NH4+ stimulates Na+/Ca2+ exchange; Li+ or Cs+ inhibits Na+/Ca2+ exchange. The ATP‐dependent Ca2+ transport system is stimulated by increasing K+ concentrations in the external medium (Km for K+ is 15 mM). Replacing K+ by Na+ in the external medium inhibits the ATP‐dependent Ca2+ uptake, and this effect is due more to the reduction of K+ than to the elevation of Na+. The results suggest that synaptic membrane vesicles isolated from sheep brain cortex synaptosomes possess mechanisms for Na+/Ca2+ exchange and ATP‐dependent Ca2+ uptake, whose activity may be regulated by monovalent cations, specifically K+, at physiological concentrations.
The MacWilliams identity for quantum convolutional codes

In this paper, we propose a definition of the dual code of a quantum convolutional code, with or without entanglement assistance. We then derive a MacWilliams identity for quantum convolutional codes. Along the way, we obtain a direct proof of the MacWilliams identity, first found by Gluesing-Luerssen and Schneider, in the setting of classical convolutional codes.
Unusual serum electrophoresis pattern in a woman with pancreatic carcinoma.

A 51-year-old woman presented with progressive severe icterus associated with advanced inoperable pancreatic carcinoma. Biopsy of the liver revealed metastasis of a moderately differentiated adenocarcinoma, possibly of pancreatic origin. Imaging studies did not show any primary tumor in the pancreas but did reveal a deep vein thrombosis of the left lower extremity and a pulmonary embolism. Bone scans revealed metastases. The patient began treatment with chemotherapy (gemcitabine), radiotherapy to alleviate pain, and placement of a percutaneous transhepatic stent in the right biliary system because of progressive icterus. Routine biochemical investigation of the patient’s serum revealed increased total bilirubin (275 μmol/L, reference value <22 μmol/L), which consisted mainly of direct bilirubin (215 μmol/L, reference value <4 μmol/L). The cytosolic liver enzymes alanine aminotransferase (115 U/L) and aspartate aminotransferase (143 U/L) were moderately increased. The serum protein concentration was 68 g/L (reference interval 60–85 g/L), but capillary electrophoresis of serum proteins (CAPILLARYS 2, Sebia) demonstrated a low albumin fraction together with a marked additional peak observed between the β and the γ region (Fig. 1⇓ ). Results of immunofixation with antibodies against G, M, and A heavy chains and κ and λ light chains were negative, indicating that this additional electrophoretic fraction did not indicate the presence of a paraprotein. Agarose gel electrophoresis confirmed the abnormal pattern, ruling out analytical interference caused by atypical ultraviolet absorbance. Figure 1. Capillary electrophoresis of the patient’s serum. The arrow points to a marked additional fraction present between the β and γ zone. Absorbance is expressed as ultraviolet absorption …
Modulation of Endothelial Glycocalyx Structure under Inflammatory Conditions

The glycocalyx of the endothelium is an intravascular compartment that creates a barrier between circulating blood and the vessel wall. The glycocalyx is suggested to play an important role in numerous physiological processes including the regulation of vascular permeability, the prevention of the margination of blood cells to the vessel wall, and the transmission of shear stress. Various theoretical models and experimental approaches provide data about changes to the structure and functions of the glycocalyx under various types of inflammatory conditions. These alterations are suggested to promote inflammatory processes in vessels and contribute to the pathogenesis of number of diseases. In this review we summarize current knowledge about the modulation of the glycocalyx under inflammatory conditions and the consequences for the course of inflammation in vessels. The structure and functions of endothelial glycocalyx are briefly discussed in the context of methodological approaches regarding the determination of endothelial glycocalyx and the uncertainty and challenges involved in glycocalyx structure determination. In addition, the modulation of glycocalyx structure under inflammatory conditions and the possible consequences for pathogenesis of selected diseases and medical conditions (in particular, diabetes, atherosclerosis, ischemia/reperfusion, and sepsis) are summarized. Finally, therapeutic strategies to ameliorate glycocalyx dysfunction suggested by various authors are discussed.
Generalized digital reassembly using geometric registration

We present a novel and generic user-guided approach for the digital reconstruction of cultural heritage finds from fragments, which operates directly on generic 3D objects. Central to our approach is a three-tier geometric registration approach that addresses the reassembly problem using i) the contact surface of the fractured objects, ii) feature curves on the intact surfaces and iii) partial object symmetries. In contrast to most existing methodologies, our approach is more generic and addresses even the most difficult cases, where contact surface is unusable, small or absent. We evaluate our method using digitized fragments from the Nidaros Cathedral.
Parallel face Detection and Recognition on GPU

Human face detection and recognition finds various application in domain like Surveillance, Law Enforcement, Interactive game application etc. These application requires fast image processing in real time however with the proposed work earlier does not gives that capability. In this paper we have proposed technique that process image for face detection and recognition in parallel on NVIDIA GeForce GTX 770 GPU which has compute Capability of 3.0. We have used Viola and Jones for face detection and PCA Eigenfaces algorithm for face recognition. The viola and jones shown result of processing the faces at 15 frame per second but our method shown approximately 109 frame per second in CUDA (Compute Unified Device Architecture) development framework. The algorithm are implemented to process data in parallel and made some practical optimization changes to work fast in C based programming model from NVIDIA . We have tested our proposed work on static images, video frame as well as on live camera frames captured device. We also tested that our system works robustly in extremely illumination condition. This work is done by PG students in Institute NVIDIAs Research Lab. Keywords— NVIDIA, PCA Eigenfaces, GeForce GTX 770, GPU, CUDA, face detection, face recognition.
Assessment of software measurement: an information quality study

This paper reports on the first phase of an empirical research project concerning methods to assess the quality of the information in software measurement products. Two measurement assessment instruments are developed and deployed in order to generate two sets of analyses and conclusions. These sets will be subjected to an evaluation of their information quality in phase two of the project. One assessment instrument was based on AIMQ, a generic model of information quality. The other instrument was developed by targeting specific practices relating to software project management and identifying requirements for information support. Both assessment instruments delivered data that could be used to identify opportunities to improve measurement The generic instrument is cheap to acquire and deploy, while the targeted instrument requires more effort to build. Conclusions about the relative merits of the methods, in terms of their suitability for improvement purposes, await the results from the second phase of the project.
A principal components analysis of the Autism Diagnostic Interview-Revised.

OBJECTIVE To develop factors based on the Autism Diagnostic Interview-Revised (ADI-R) that index separate components of the autism phenotype that are genetically relevant and validated against standard measures of the constructs. METHOD ADIs and ADI-Rs of 292 individuals with autism were subjected to a principal components analysis using VARCLUS. The resulting variable clusters were validated against standard measures. RESULTS Six clusters of variables emerged: spoken language, social intent, compulsions, developmental milestones, savant skills and sensory aversions. Five of the factors were significantly correlated with the validating measures and had good internal consistency, face validity, and discriminant and construct validity. Most intraclass correlations between siblings were adequate for use in genetic studies. CONCLUSION The ADI-R contains correlated clusters of variables that are valid, genetically relevant, and that can be used in a variety of studies.
Deformations of Gabor frames

The quantum mechanical Harmonic oscillator Hamiltonian H=(t2−∂2t)/2 generates a one‐parameter unitary group W(θ)=eiθH in L2(R) which rotates the time–frequency plane. In particular, W(π/2) is the Fourier transform. When W(θ) is applied to any frame of Gabor wavelets, the result is another such frame with identical frame bounds. Thus each Gabor frame gives rise to a one‐parameter family of frames, which we call a deformation of the original. For example, beginning with the usual tight frame F of Gabor wavelets generated by a compactly supported window g(t) and parameterized by a regular lattice in the time–frequency plane, one obtains a family {Fθ: 0≤θ<2π} of frames generated by the noncompactly supported windows gθ=W(θ)g, parameterized by rotated versions of the original lattice. This gives a method for constructing tight frames of Gabor wavelets for which neither the window nor its Fourier transform have compact support. When θ=π/2, Fθ is the well‐known Gabor frame generated by a window with compactly su.
New Islands of Tractability of Cost-Optimal Planning

We study the complexity of cost-optimal classical planning over propositional state variables and unary-effect actions. We discover novel problem fragments for which such optimization is tractable, and identify certain conditions that differentiate between tractable and intractable problems. These results are based on exploiting both structural and syntactic characteristics of planning problems. Specifically, following Brafman and Domshlak (2003), we relate the complexity of planning and the topology of the causal graph. The main results correspond to tractability of cost-optimal planning for propositional problems with polytree causal graphs that either have O(1)-bounded in-degree, or are induced by actions having at most one prevail condition each. Almost all our tractability results are based on a constructive proof technique that connects between certain tools from planning and tractable constraint optimization, and we believe this technique is of interest on its own due to a clear evidence for its robustness.
An Overview of Online Learning in Reproducing Kernel Hilbert Spaces

Learning System is a method to approximate an underlying function from a finite observation data. Since batch learning has a disadvantage in dealing with large data set, online learning is proposed to prevent the computational expensive. Iterative method called Stochastic Gradient Descent (SGD) is applied to solve for the underlying function on reproducing kernel Hilbert spaces (RKHSs). RKHS is widely used in many applications such as kernel method, radial basis function neural networks, Volterra filers and estimation of bandlimited functions. This approach has advantages that there is no local minima problem and convergence is also guaranteed because of using convex optimisation.This paper aims to provide background and theory of learning in RKHS which online kernel method is our main interest. The experiments show the results of learning from 3 test sets and some important parameters are also discussed.
Vehicle localization using mono-camera and geo-referenced traffic signs

Vision based localization is a cost effective method for indoor and outdoor application. However, it has drift problem if none global optimization is used. We proposed a geo-referenced traffic sign based localization method, which integrated the constraints of 3D traffic signs with local bundle adjustment to reduce the drift. Comparing to global bundle adjustment, Local Bundle Adjustment(LBA) has low computational cost but suffers the drift problem for large scale localization because of the random error accumulation. We reduced the drift by means of the constraints from geo-referenced traffic signs for bundle adjustment process. The original LBA model was extended for the constraints and the traffic signs were detected in images and matched with 3D landmark database automatically. From the experiments of simulated and real images, our approach can reduce the drift and have better locating results than none-constraint LBA based localization method.
The Role of Complement in Danger Sensing and Transmission

Self–non-self discrimination has long been considered the main function of the immune system. Increasing evidence supports the view of the immune system as a network of complex danger sensors and transmitters in which self–non-self discrimination is only one facet. To meet the challenge of danger sensing, the immune system carries a large stock of germline-encoded, highly conserved molecules that can recognize microbial as well as modified host structures. Among those are the Toll-like receptors (TLR), which comprise a dozen membrane-bound pattern-recognition receptors that directly link danger recognition to danger transmission through activation of several distinct cellular signaling pathways. Here, I discuss the function and biology of a complex, evolutionary ancient system, the complement system, which has long been considered critical to host defense. In contrast to TLRs, the complement system senses danger by a panel of soluble molecules that can directly bind to specific complement receptors and/or initiate a complex cascade of proteolytic events that lead to the generation of soluble complement fragments able to bind to another, distinct set of specific complement receptors. As I will outline in this review, complement-mediated danger sensing and the complex transition of this information into distinct cellular activation profiles is critical for tissue homeostasis under steady-state conditions and in response to infection and cell injury. Furthermore, I will discuss recent findings that support a concept of intense cross-talk between the complement system and TLRs, which defines the quality and the magnitude of immune responses in vivo. Key Words
Crosstalk at the Dynamic Node of Domino CMOS Circuits

The need for faster circuits in smaller area with lower power dissipation has made it a common practice to use the domino CMOS in high performance integrated circuits. However this improved performance comes at the cost of lower noise immunity. Also current trends in integrated circuit technology have increased chances of crosstalk due to capacitive coupling. Though several works have investigated the problem of crosstalk at the inputs of domino circuits, crosstalk at the dynamic node of the domino circuits has been ignored. A model for crosstalk at the dynamic node is developed and verified in this paper. Application of this model can ensure immunity of domino circuits from crosstalk failures.
A Non-parametric Approach to Approximate Dynamic Programming

Approximate Dynamic Programming (ADP) is a machine learning method aiming at learning an optimal control policy for a dynamic and stochastic system from a logged set of observed interactions between the system and one or several non-optimal controlers. It defines a class of particular Reinforcement Learning (RL) algorithms which is a general paradigm for learning such a control policy from interactions. ADP addresses the problem of systems exhibiting a state space which is too large to be enumerated in the memory of a computer. Because of this, approximation schemes are used to generalize estimates over continuous state spaces. Nevertheless, RL still suffers from a lack of scalability to multidimensional continuous state spaces. In this paper, we propose the use of the Locally Weighted Projection Regression (LWPR) method to handle this scalability problem. We prove the efficacy of our approach on two standard benchmarks modified to exhibit larger state spaces.
Data Replication Placement Strategy Based On Bidding Mode for Cloud Storage Cluster

The data availability in large-scale cloud storage has been increasing by means of data replica. To provide cost-effective availability, minimize the response time of applications and make load balancing for cloud storage, a new replica placement policy with bidding thought is proposed. The policy combines the own characteristics of replica and factors of bidding mode(e.g. bidding time, bidding standard, bidding price etc.) and starts replica bidding activity when the file data availability cannot meet the given requirement. Replica placement is based on capacity and accessing probability of data nodes. The experimental results show that our policy has a better performance in both load balance and response time comparing to the static replica policy and CDRM scheme.
Crowd-sourcing satellite image analysis

This paper discusses several ways in which a community of volunteers can be put together to generate good quality geographical information by the use of remote sensing image analysis tools. Three different scenarios are proposed and a system architecture, based on existing open source solutions, is suggested and discussed. The main objective of this paper is to motivate contributions to build such a system.
Little-Higgs corrections to precision data after CERN LEP2

We reconsider little-Higgs corrections to precision data. In five models with global symmetries SU(5), SU(6), SO(9) corrections are (although not explicitly) of 'universal' type. We get simple expressions for the S-circumflex,T-circumflex,W,Y parameters, which summarize all effects. In all models W,Y{>=}0 and in almost all models S-circumflex>(W+Y)/2. Results differ from previous analyses, which are sometimes incomplete, sometimes incorrect, and because we add LEP2 ee{yields}ff cross sections to the data set. Depending on the model, the constraint on f ranges between 2 and 20 TeV. We next study the simplest little-Higgs model (and propose a related model) which is not universal and affects precision data due to the presence of an extra Z{sup '} vector. By restricting the data set to the most accurate leptonic data we show how corrections to precision data generated by a generic Z{sup '} can be encoded in four effective S-circumflex,T-circumflex,W,Y parameters, giving their expressions.
An efficient memory operations optimization technique for vector loops on Itanium 2 processors

To keep up with a large degree of instruction level parallelism (ILP), the Itanium 2 cache systems use a complex organization scheme: load/store queues, banking and interleaving. In this paper, we study the impact of these cache systems on memory instructions scheduling. We demonstrate that, if no care is taken at compile time, the non‐precise memory disambiguation mechanism and the banking structure cause severe performance loss, even for very simple regular codes. We also show that grouping the memory operations in a pseudo‐vectorized way enables the compiler to generate more effective code for the Itanium 2 processor. The impact of this code optimization technique on register pressure is analyzed for various vectorization schemes. Copyright © 2006 John Wiley & Sons, Ltd.
CTLA-4 Blockade Synergizes Therapeutically with PARP Inhibition in BRCA1-Deficient Ovarian Cancer

PARP inhibitors improve progression-free survival in BRCA1-deficient ovarian cancer. In a mouse model, checkpoint blockade with anti–CTLA-4, but not anti–PD-1, synergized with PARP inhibition to establish protective immune memory and achieve long-term survival. Immune checkpoint blockade has shown significant therapeutic efficacy in melanoma and other solid tumors, but results in ovarian cancer have been limited. With evidence that tumor immunogenicity modulates the response to checkpoint blockade, and data indicating that BRCA-deficient ovarian cancers express higher levels of immune response genes, we hypothesized that BRCA− ovarian tumors would be vulnerable to checkpoint blockade. To test this hypothesis, we used an immunocompetent BRCA1-deficient murine ovarian cancer model to compare treatment with CTLA-4 or PD-1/PD-L1 antibodies alone or combined with targeted cytotoxic therapy using a PARP inhibitor. Correlative studies were performed in vitro using human BRCA1− cells. We found that CTLA-4 antibody, but not PD-1/PD-L1 blockade, synergized therapeutically with the PARP inhibitor, resulting in immune-mediated tumor clearance and long-term survival in a majority of animals (P < 0.0001). The survival benefit of this combination was T-cell mediated and dependent on increases in local IFNγ production in the peritoneal tumor environment. Evidence of protective immune memory was observed more than 60 days after completion of therapy. Similar increases in the cytotoxic effect of PARP inhibition in the presence of elevated levels of IFNγ in human BRCA1− cancer cells support the translational potential of this treatment protocol. These results demonstrate that CTLA-4 blockade combined with PARP inhibition induces protective antitumor immunity and significant survival benefit in the BRCA1− tumor model, and support clinical testing of this regimen to improve outcomes for women with hereditary ovarian cancer. Cancer Immunol Res; 3(11); 1257–68. ©2015 AACR.
A review and update of the hydrology of Lake Victoria in East Africa

Water balance models have been used to examine trends in the level of Lake Victoria over this century. A monthly model developed in a previous study for the period 1925 to 1978 has been improved and the simulation period extended to 1990. Also, an annual model has been used to extend the water balance back to the start of the century. The simulations confirm the results from previous studies which showed that the observed variations in lake level can be explained primarily in terms of natural variations in rainfall over the lake and surrounding basin. An idealized interpretation of these variations is presented which illustrates the long response time of this large lake and which is used to speculate on the likely future behaviour of the lake.