Miracle-dz/UniFAR-FTUs huggingface dataset:
Complement mediates human immunodeficiency virus type 1 infection of a human T cell line in a CD4- and antibody-independent fashion

Incubation of the human T cell lymphotropic virus (HTLV)-IIIB and HTLV- RF strains of human immunodeficiency virus type 1 (HIV-1) with normal seronegative human serum under conditions that allow complement activation resulted in enhancement of infection of the MT2 human T cell line cultured in the presence of low amounts of virus. Infection of MT2 cells was assessed by measuring reverse transcriptase activity in supernatants at day 9 of culture. Complement activation by viral suspensions occurred through the alternative pathway. Opsonization of HTLV-RF viral particles with complement was sufficient to allow a productive infection to occur in cells exposed to suboptimal amounts of virus. Infection of MT2 cells with suboptimal amounts of serum- opsonized HIV-1 was suppressed by blocking the C3dg receptor (CR2, CD21) on MT2 cells with monoclonal anti-CR2 antibody and rabbit F(ab')2 anti-mouse immunoglobulin antibodies. Blocking of the gp120-binding site on CD4 under similar experimental conditions had no inhibitory effect on infection of MT2 cells with opsonized virus. Opsonization of HIV-1 with seronegative serum also resulted in a CR2-mediated enhancement of the infection of normal peripheral blood mononuclear cells and T lymphocytes. These results indicate that complement in the absence of antibody may enhance infection of C3 receptor-bearing T cells with HIV-1, and that the interaction of opsonized virus with the CR2 receptor may result by itself in the infection of target T cells in a CD4- and antibody-independent fashion.
Combination Exchange Mechanisms for Efficient Bandwidth Allocation

The size, scale and multiple ownership of communication network resources makes it important to consider an economic framework wherein we can investigate the efficiency of network operation taking agents' incentives into account. Such a framework has been considered in the design and analysis of pricing mechanisms to regulate congestion and share bandwidth over short time scales. We consider time scales of a few months over which owners of communication links lease bandwidth to network service providers. As is well-known, economic efficiency is related to how close an allocation is to a competitive equilibrium. We first show that achieving economic efficiency through a market mechanism depends on network topology. We then show that in finite networks a competitive equilibrium may not exist. But a competitive equilibrium does exist in an idealized continuum model, in which all agents are infinitesimal compared with the size of the network. This suggests that approximate competitive equilibria with good performance may be attainable in real networks. We finally introduce a market mechanism called the combinatorial seller's bid double auction whose outcome, in the continuum model, is a competitive equilibrium. 1. Introduction. Communication networks have increased in scale and hetero- geneity. There are multiple network owners and operators, each with their own hetero- geneous endowments and privately known cost and revenue models. So, an allocation of network resources efficient from an engineering perspective need not be realized in the market. Hence, it is useful to find economic mechanisms that result in efficient resource allocations among selfish agents. The efficiency of bandwidth allocation among competing users in a communica- tion network has been studied within an economic framework before. The previous research literature focuses attention on congestion that results when aggregate user demand exceeds capacity, and proposes usage-dependent pricing as a method for con- trolling congestion (23, 24). However, several difficulties must be faced in coming up with a good price-adjustment mechanism. First, congestion occurs over a very short time scale: Aggregate traffic is bursty and exceeds nominal capacity for periods of a few seconds (10). So the pricing mechanism must react very quickly to changes in aggregate demand. Second, the 'correct' congestion price depends on how much users are willing to pay for the service, which is not known. This has prompted invention of distributed price iteration algorithms that converge to the 'correct' price (16, 22). These algorithms are not practical but permit a re-interpretation of TCP-like proto-
Coupled mode characteristics for the twin coupled microdisks

The characteristics for the twin coupled microdisks are investigated by finite-difference time-domain (FDTD) technique. In the twin coupled microdisks, mode coupling between the same order whispering-gallery modes (WGMs) results in coupled WGMs with split mode wavelengths and different quality factor (Q-factor). The numerical results show that the coupling between the first and the second order WGMs exists, which can greatly decrease the quality factor of the coupled first order WGMs and deduce the anti- crossing of the mode wavelength. Furthermore, we can see the coupling phenomenon from the field distribution varies with the gap.
Compiler-Assisted Distributed Shared Memory Schemes Using Memory-Based Communication Facilities

To execute shared-memory-based parallel programs efficiently, we introduce two compiler-assisted software cache schemes which are well-suited to automatic optimizations of remote communications. One scheme is a full user-level software cache (User-level Distributed Shared Memory: UDSM) and another is a page-based cache (Asymmetric Distributed Shared Memory: ADSM) which exploits TLB/MMU only in the cases of read-access-misses. Under these schemes we can apply several optimizing techniques, which exploit capabilities of the middle-grained or coarsegrained remote-memory-accesses, to reduce the number and the amount of communications. We also introduce a highspeed user-level communication and synchronization scheme “Memory-Based Communication Facilities (MBCF)” for providing the capabilities in a general-purpose system with offthe-shelf communication-hardware. In this paper, we explain outline of our approach, the UDSM and the ADSM, the MBCF, and optimizing techniques for remote communications. Finally we show experimental results on effects of our proposed approach using our prototype optimizing compiler “Remote Communication Optimizer (RCOP)” and the MBCF on Fast
CAUSES AND CONSEQUENCES OF FIRMS ’ SELF-REPORTED ANTICORRUPTION EFFORTS

We use Transparency International’s ratings of self-reported anticorruption efforts for 480 corporations to examine factors underlying firms’ efforts and their consequences. We find that firms with high anticorruption efforts are domiciled in countries with low corruption ratings and strong anticorruption enforcement, operate in high corruption risk industries, have recently faced a corruption enforcement action, employ a Big Four audit firm, and have a higher percentage of independent directors. Controlling for these effects, we find that firms with abnormally low anticorruption efforts have relatively higher subsequent media allegations of corruption. They also report higher future sales growth and show a negative relation between profitability change and sales growth in high corruption geographic segments compared to firms with high anticorruption efforts. The net effect on valuation from sales growth and profitability is close to zero. We conclude that, on average, firms’ self-reported anticorruption efforts reflect real efforts to combat corruption and are not merely cheap talk. * Paul Healy is a Professor of Business Administration at Harvard Business School, and George Serafeim is an Assistant Professor of Business Administration in Harvard Business School. We are grateful to Transparency International, in particular Robin Hodess and Deborah Hardoon, for providing the data for this study. We also wish to thank Barbara Esty, Kathleen Ryan and James Zeitler for research assistance with the media and governance data. Many thanks go to anticorruption experts at PwC and Siemens for helpful conversations around the importance of transparency in anticorruption efforts. Finally we are grateful for comments received by our editors SP Kothari and Rebecca Henderson, Robert Eccles, Eddie Riedl, Joe Weber (discussant), Gwen Yu, and participants at the HBS International Seminar, Boston University, Cornell University, and the HBS Corporate Accountability Reporting Conference. The project was supported by financial assistance from the Department of Faculty Research and Development of the Harvard Business School. Contact emails: Paul Healy phealy@hbs.edu, George Serafeim gserafeim@hbs.edu.
Web Usage Mining for a Better Web-Based Learning Environment

Web-based technology is often the technology of choice for distance education given the ease of use of the tools to browse the resources on the Web, the relative affordability of accessing the ubiquitous Web, and the simplicity of deploying and maintaining resources on the WorldWide Web. Many sophisticated web-based learning environments have been developed and are in use around the world. The same technology is being used for electronic commerce and has become extremely popular. However, while there are clever tools developed to understand online customer’s behaviours in order to increase sales and profit, there is very little done to automatically discover access patterns to understand learners’ behaviour on webbased distance learning. Educators, using on-line learning environments and tools, have very little support to evaluate learners’ activities and discriminate between different learners’ on-line behaviours. In this paper, we discuss some data mining and machine learning techniques that could be used to enhance web-based learning environments for the educator to better evaluate the leaning process, as well as for the learners to help them in their learning endeavour.
Preference learning for affective modeling

There is an increasing trend towards personalization of services and interaction. The use of computational models for learning to predict user emotional preferences is of significant importance towards system personalization. Preference learning is a machine learning research area that aids in the process of exploiting a set of specific features of an individual in an attempt to predict her preferences. This paper outlines the use of preference learning for modeling emotional preferences and shows the methodology's promise for constructing accurate computational models of affect.
q-Gaussian activation function Circular Extreme learning machine for classification problems

Circular Extreme learning machine (C-ELM) is the one extended Extreme Learning Machine (ELM). It has the same structure as ELM and Circular Back Propagation (CBP) to make it can mapping both linear and circular decision boundaries. The activation function is the one main point to define the decided boundaries. Many activation functions have been proposed. This paper proposes q-Gaussian activation function based on Tsallis statistics that is the one choice to make flexibility decision boundaries with different Gaussian shapes in the Circular Extreme Learning Machine. It calls q-Gaussian activation function Circular Extreme Learning Machine (QC-ELM) that added and varied parameter q (the entropic index) to improve C-ELM's performance. From experimental results of QC-ELM compared with many other methods tested on UCI datasets shows that the QC-ELM has better results in accuracy than many the compared classical methods.
Hybrid Collaborative and Content-based Music Recommendation Using Probabilistic Model with Latent User Preferences

This paper presents a hybrid music recommendation method that solves problems of two prominent conventional methods: collaborative filtering and content-based recommendation. The former cannot recommend musical pieces that have no ratings because recommendations are based on actual user ratings. In addition, artist variety in recommended pieces tends to be poor. The latter, which recommends musical pieces that are similar to users’ favorites in terms of music content, has not been fully investigated. This induces unreliability in modeling of user preferences; the content similarity does not completely reflect the preferences. Our method integrates both rating and content data by using a Bayesian network called an aspect model. Unobservable user preferences are directly represented by introducing latent variables, which are statistically estimated. To verify our method, we conducted experiments by using actual audio signals of Japanese songs and the corresponding rating data collected from Amazon. The results showed that our method outperforms the two conventional methods in terms of recommendation accuracy and artist variety and can reasonably recommend pieces even if they have no ratings.
In the Developing Rat Hippocampus, Endogenous Activation of Presynaptic Kainate Receptors Reduces GABA Release from Mossy Fiber Terminals

Presynaptic kainate receptors regulate synaptic transmission in several brain areas but are not known to have this action at immature mossy fiber (MF) terminals, which during the first week of postnatal life release GABA, which exerts into targeted cells a depolarizing and excitatory action. Here, we report that, during the first week of postnatal life, endogenous activation of GluK1 receptors by glutamate present in the extracellular space severely depresses MF-mediated GABAergic currents [GABAA-mediated postsynaptic currents (GPSCs)]. Activation of GluK1 receptors was prevented by treating the slices with enzymatic glutamate scavengers that enhanced the clearance of glutamate from the extracellular space. The depressant effect of GluK1 on MF-GPSCs was mediated by a metabotropic process sensitive to pertussis toxin. In the presence of U73122 (1-[6-[[(17b)-3-methoxyestra-1,3,5(10)-trien-17-yl]amino]hexyl]-1H-pyrrole-2,5-dione), a selective inhibitor of phospholipase C, along the transduction pathway downstream to G-protein, GluK1 activation increased the probability of GABA release, thus unveiling the ionotropic action of this receptor. In line with this type of action, we found that GluK1 enhanced MF excitability by directly depolarizing MF terminals via calcium-permeable cation channels. Furthermore, GluK1 dynamically regulated the direction of spike time-dependent plasticity occurring by pairing MF stimulation with postsynaptic spiking and switched spike time-dependent potentiation into depression. The GluK1-induced depression of MF-GPSCs would prevent excessive activation of the CA3 associative network by the excitatory action of GABA and the emergence of seizures in the immature brain.
An introduction to the methods available for ion channel reconstitution

Reconstitution describes the disassembly of a complex structure; the isolation of one or more of the components of that system and the reassembly of these components into an intelligible, measurable system. When applied to membrane proteins, such as ion-channels, it describes the solubilisation of the membrane, the isolation of the channel protein from the other membrane constituents and the reintroduction of that protein into some form of artificial membrane system which facilitates the measurement of channel function. However, in practice, the term is often applied less rigorously in the study of ion channel function and can be used to describe the incorporation of intact membrane vesicles, including the protein of interest, into artificial membrane systems that allow the properties of the channel to be investigated. In this chapter I will describe methods that are currently in use for incorporation of both native and purified channel proteins into artificial membranes. The diversity of the subject means that the technical aspects of the various approaches cannot be covered in detail; rather, this chapter is designed to act as an introduction to ion channel reconstitution. Detailed descriptions of experimental protocols can be obtained from the literature cited throughout the chapter. Ion-channel function can be monitored in a number of ways; by monitoring isotope flux in isolated tissues or membrane vesicles, or by using electrophysiological techniques, such as whole cell voltage-clamp or patch-clamp. What then are the advantages of monitoring channel function following incorporation into some form of artificial membrane?
DUKF-based GTM UAV fault detection and diagnosis with nonlinear and LPV models

Fault tolerant control system (FTCS) is to maintain system stability in the presence of fault occurred in the actuators, sensors or other system components. When a fault/failure occurs either in an actuator, sensor or plant, the fault detection and diagnosis (FDD) as the central part of a FTCS will detect and diagnose the source and the magnitude of the fault. The reconfiguration scheme in the FTCS will design the reconfigurable controller based on the FDD information to balance and adapt the system for being able to tolerate to the faults and failures. This paper presents an applicable procedure of integrated fault detection and diagnosis for the NASA Generic Transport Model (GTM) unmanned aerial vehicle (UAV) aircraft model. The implementation of a FDD scheme in handling partial control effector fault cases with the nonlinear GTM and the linear parameter varying (LPV) representation of the nonlinear GTM have been carried out based on a dual unscented Kalman filter (DUKF) and a Baysian rule for detection and isolation decision making. Simulation results show satisfactory results for detecting and diagnosing the control effectors failures.
Comparative Study on Cursor Position Controlled by Pen Pressure and Pen Tilt

An experiment was conducted in this study to investigate the human ability to control pen pressure and pen tilt input to couple to cursor position. Comparison between pressure input and tilt input has been made in the experiment. Experimental results show that decreasing pressure input resulted in very bad performance and was not a good input technique, and that the tilt input technique performed relatively better than the increasing pressure input technique, even though the tilt technique had a slightly higher error rate. These results will be useful for further user interface design.
A component supervisor for RT-Middleware using supervision trees

The 4C's of software, computation, communication, configuration and coordination, indicate that the deployment and configuration of software components is an important part of using a component-based software system. This applies as much to robotics as anywhere else, where how to easily deploy the complex web of software components that make up a complete robot system is a well-known problem. We have developed an experimental tool for the deployment and configuration of components using RT-Middleware. It is based on the supervision tree concept. Components are organised into a hierarchy of sub-systems and managed in these groups. The use of a supervision tree ensures that dependencies between components are managed when errors occur, and that errors will propagate up the tree to a supervisor that is capable of handling them.
Image compression using wavelet based compressed sensing and vector quantization

Sparse signal representations and compressed sensing have found use in a large number of applications including image compression. Compressed sensing exploits the sparsity of naturally occurring images to reduce the volume of the data by using less number of measurements. Inspired by this, we propose a new framework for image compression that combines compressed sensing theory with wavelet and vector quantization. Wavelet transform is used to sparsify the input image while measurement vectors generated from the sparse vectors are transmitted using vector quantization. Simulation experiments are carried out to analyze the effects of various parameters on the image reconstruction quality. Results obtained have been found to be quite promising.
Risk Factors of Hyperammonemia in Patients With Epilepsy Under Valproic Acid Therapy

Abstract Hyperammonemia has been reported to be associated with patients who receive valproic acid (VPA) therapy. This study aimed to determine the risk factors for hyperammonemia in patients with epilepsy treated with VPA. One hundred and fifty-eight adult patients with epilepsy aged older than 17 years who received VPA therapy were enrolled into this study. Blood samples were taken during the interictal state and analyzed for the blood level of ammonia. Statistical analysis was conducted between different groups of patients. The results showed that the frequency of hyperammonemia associated with VPA therapy was 27.8% (ammonia level >93 µg/dL), and 5.1% of the patients had severe hyperammonemia (ammonia level >150 µg/dL). The blood ammonia level was significantly correlated with the dosage of VPA and the plasma concentration of VPA. An increase of 1 mg in the dosage of VPA increased the risk of hyperammonemia by 0.1%. In addition, combination treatment with liver enzyme inducing antiepileptic drugs (AEDs) and antipsychotic drugs increased the risk of hyperammonemia. In conclusion, the use of VPA in adult patients with epilepsy was associated with a dose-dependent increase in blood concentrations of ammonia. Combination treatment with liver enzyme-inducing AEDs and antipsychotic drugs increased the risk of VPA-induced hyperammonemia. Most of the patients with VPA-induced hyperammonemia were asymptomatic; however, if patients taking VPA present with symptoms such as nausea, fatigue, somnolence, ataxia, and consciousness disturbance, the blood ammonia level should be measured.
Harmonic analysis of cosmic microwave background data – II. From ring‐sets to the sky

Despite the fact that the physics of the cosmic microwave background anisotropies is most naturally expressed in Fourier space, pixelized maps are almost always used in the analysis and simulation of microwave data. A complementary approach is investigated here, in which maps are used only in the visualization of the data, and the temperature anisotropies and polarization are only ever expressed in terms of their spherical multipoles. This approach has a number of advantages: there is no information loss (assuming a band-limited observation); deconvolution of asymmetric beam profiles and the temporal response of the instrument are naturally included; correlated noise can easily be taken into account, removing the need for additional ‘destriping’; polarization is also analysed in the same framework; and reliable estimates of the spherical multipoles of the sky and their errors are obtained directly for subsequent component separation and power spectrum estimation. The formalism required to analyse experiments which survey the full sky by scanning on circles is derived here, with particular emphasis on the Planck mission. A number of analytical results are obtained in the limit of simple scanning strategies. Although there are non-trivial computational obstacles to be overcome before the techniques described here can be implemented at high resolution, if these can be overcome the method should allow for a more robust return from the next generation of full-sky microwave background experiments.
A continuous-time approach to the oblique Procrustes problem

In the paper proposed we will make use of the gradient flow approach to consider a generalization of the well-known oblique Procrustes rotation problem, involving oblique simple structure rotation of both the core and component matrices resulting from three-mode factor analysis. The standard oblique Procrustes rotations to specified factor-structure and factor-pattern follw as special cases. The approach adopted leads to globally convergent algorithm and includes solving of initial value problem for certain matrix ordinary differential equation. Necessary conditions are established for the solution of the problem. The same approach is extended easily to the weighted oblique Procrustes rotation. Finally, some simulated numerical results are given and commented.