Miracle-dz/UniFAR-FTUs huggingface dataset:
Central Nervous System Parasitosis and Neuroinflammation Ameliorated by Systemic IL-10 Administration in Trypanosoma brucei-Infected Mice

Invasion of the central nervous system (CNS) by African trypanosomes represents a critical step in the development of human African trypanosomiasis. In both clinical cases and experimental mouse infections it has been demonstrated that predisposition to CNS invasion is associated with a type 1 systemic inflammatory response. Using the Trypanosoma brucei brucei GVR35 experimental infection model, we demonstrate that systemic delivery of the counter-inflammatory cytokine IL-10 lowers plasma IFN-γ and TNF-α concentrations, CNS parasitosis and ameliorates neuro-inflammatory pathology and clinical symptoms of disease. The results provide evidence that CNS invasion may be susceptible to immunological attenuation.
Dependency Status and Demand for Social Insurance: Evidence from Experiments and Surveys*

Current thinking on the origins and size of the welfare state often ignores household relations in which people may depend on others for income or have dependents themselves. The influence of “dependency status” on individuals’ political preferences is unknown. We report results from a laboratory experiment designed to estimate the effect of dependency on preferences for policies that insure against labor market risk. Results indicate that (1) willingness to vote in favor of a social insurance policy is highly responsive to unemployment risk, (2) symmetric, mutual dependence is unrelated to support for insurance, but (3) asymmetric dependence (being dependent on someone else) increases support for social insurance. We connect our lab results to observational survey data and find similar relationships.
Ongoing burden of disease and mortality from HIV/CMV coinfection in Africa in the antiretroviral therapy era

Human Cytomegalovirus (CMV) is a well-recognized pathogen in the context of HIV infection, but since the roll out of ART, clinical and scientific interest in the problem of HIV/CMV coinfection has diminished. However, CMV remains a significant cofactor in HIV disease, with an influence on HIV acquisition, disease progression, morbidity, and mortality. Disease manifestations may be a result of direct interplay between the two viruses, or may arise as a secondary consequence of immune dysregulation and systemic inflammation. The problem is most relevant when the rates of coinfection are high, most notably in sub-Saharan Africa, and in children at risk of acquiring both infections early in life. Understanding the interplay between these viruses and developing strategies to diagnose, treat and prevent CMV should be a priority.
BACKGROUND IMAGE SUBTRACTION USING MULTIVIEW GEOMETRY FOR WIDE BASELINE IMAGE

Background subtraction has found its application for tracking and 3D reconstruction. The challenge remains in identifying a foreground object from a given set of 2D images. Such a framework needs to take into account shadows, occlusion, intensity variations and movements in the background. This project proposes one such background subtraction method which makes use of multi-view geometry. While such methods exist till date for stereo images, little research has been done for wide-baseline images. A novel approach to performing background subtraction across such wide-baseline images is proposed. For the purposes of background subtraction a dense pixel-to-pixel correspondence map is generated across three wide-baseline images. Using this correspondence data, a background subtraction method, which is invariant to shadows and intensity variation is proposed. The method is tested over wide-baseline example set with single and multiple-persons as foreground objects. A thorough evaluation of the results is done using epipolar geometry. Promising results are obtained even at 20 frames per second. The obtained results are compared with the results using the " Kernel Density Estimation " method and the conventional frame differencing to test its quality. Several extensions to the approach are proposed to further improve the quality of the foreground images including an extension to N-view images. Acknowledgements My sincere thanks to the entire team at Utrecht University working on this project, Nico van der Aa, Robby Tan, Xinghan Luo and Remco Veltkamp. I would like to thank Nico van der Aa for his invaluable suggestions and feedback on the project and continuous support throughout the phase of the project. Without his continued persistence and guidance I would not have managed to finish this project in the stipulated time-frame. Sincere thanks to Remco Veltkamp for providing an opportunity to work in such a challenging topic. Thanks to Robby Tan for his feedback on concepts of computer vision which were used throughout the progress of the project. Very special thanks to Xinghan for providing the calibration data and the input dataset.
FACTOR VIII COAGULANT ACTIVITY AND FACTOR VIII-LIKE ANTIGEN: INDEPENDENT MOLECULAR ENTITIES

Factor VIII coagulant activity (VIIIC) and the von Willebrand's disease antigen (Factor VIII-like antigen, vW-Ag) are biologically linked, and it has been suggested that they reside on the same molecule. However, insolubilized human isoantibody to VIIIC and rabbit antiserum containing antibodies to VIIIC and vW-Ag differentially bind and remove these entities from plasma, thus physically segregating one from the other. These findings indicate that Factor VIII coagulant activity resides on a molecule distinct from that expressing the von Willebrand's antigen.
An Experimental Study on Neighbourhood Component Analysis

In this experimentation project, we introduce the Neighbourhood Component Analysis (NCA), a classification method combining k-nearest neighbour (KNN) and learned distance metric, originally proposed by Goldberger et al. in 2004. With an implementation in the R environment, we perform experiments on several datasets. Results of our experiments suggest that with the learned distance metric, KNN classification can be improved, especially for skewed and noisy data. For certain type of data, NCA also outperforms traditional dimension reduction methods. However, the comparisons to other classifiers, i.e. linear and quadratic discriminant analysis, do not show significant strength in this method.
HCV Infection among Saudi Population: High Prevalence of Genotype 4 and Increased Viral Clearance Rate

HCV is a major etiological agent of liver disease with a high rate of chronic evolution. The virus possesses 6 genotypes with many subtypes. The rate of spontaneous clearance among HCV infected individuals denotes a genetic determinant factor. The current study was designed in order to estimate the rate of HCV infection and ratio of virus clearance among a group of infected patients in Saudi Arabia from 2008 to 2011. It was additionally designed to determine the genotypes of the HCV in persistently infected patients. HCV seroprevalence was conducted on a total of 15,323 individuals. Seropositive individuals were tested by Cobas AmpliPrep/Cobas TaqMan HCV assay to determine the ratio of persistently infected patients to those who showed spontaneous viral clearance. HCV genotyping on random samples from persistently infected patients were conducted based on the differences in the 5′untranslated region (5′UTR). Anti-HCV antibodies were detected in 7.3% of the totally examined sera. A high percentage of the HCV infected individuals experienced virus clearance (48.4%). HCV genotyping revealed the presence of genotypes 1 and 4, the latter represented 97.6% of the tested strains. Evidences of the widespread of the HCV genotype 4 and a high rate of HCV virus clearance were found in Saudi Arabia.
The Academic Corporation: A History of College and University Governing Boards

Series Editor's Preface Foreword Preface Prologue Chapter 1 - Medieval Origins 1. Precedents from Roman Law 2. The University at Paris 3. The Medieval Corporation 4. Formation of the Universities in England Chapter 2 - English Antecedents 1. Primacy of the State 2. Royal Jurisdiction 3. The Colleges 4. English Law of Corporations 5. Transition to American Colonies American Adaptations 1. Influence of the English Corporations 2. Reformation Influences 3. European Precedents 4. Conclusion Governance of the Colonial Colleges 1. Harvard 2. William and Mary 3. Yale 4. Other Colonial Colleges Corporate Autonomy: The Dartmouth College Case 1. Antecedents to the Case 2. The Corporate Context for the Decision 3. Legal Decisions Prior to the Dartmouth Case 4. The Case 5. Implications of the Decision Foundation of an American System 1. Modification of the Dartmouth Decision 2. Expansion of Public Higher Education 3. Expansion of Public Higher Education 4. State Foundations as Public Corporations Governing Board Authority in Practice 1. The Control of Educational Programs 2. Faculty Relations 3. The Oversight of Students 4. Requirements for Educational Achievement 5. Financial Management Conclusion: From Past to Future 1. The Past 2. Developments Since the 1950s 3. A Look to the Future Bibliography Appendix 1: Cases for Chapters Seven and Eight Appendix 2: Founding Documents Index
LRRK2 protein levels are determined by kinase function and are crucial for kidney and lung homeostasis in mice

Mutations in leucine-rich repeat kinase 2 (LRRK2) cause late-onset Parkinson's disease (PD), but the underlying pathophysiological mechanisms and the normal function of this large multidomain protein remain speculative. To address the role of this protein in vivo, we generated three different LRRK2 mutant mouse lines. Mice completely lacking the LRRK2 protein (knock-out, KO) showed an early-onset (age 6 weeks) marked increase in number and size of secondary lysosomes in kidney proximal tubule cells and lamellar bodies in lung type II cells. Mice expressing a LRRK2 kinase-dead (KD) mutant from the endogenous locus displayed similar early-onset pathophysiological changes in kidney but not lung. KD mutants had dramatically reduced full-length LRRK2 protein levels in the kidney and this genetic effect was mimicked pharmacologically in wild-type mice treated with a LRRK2-selective kinase inhibitor. Knock-in (KI) mice expressing the G2019S PD-associated mutation that increases LRRK2 kinase activity showed none of the LRRK2 protein level and histopathological changes observed in KD and KO mice. The autophagy marker LC3 remained unchanged but kidney mTOR and TCS2 protein levels decreased in KD and increased in KO and KI mice. Unexpectedly, KO and KI mice suffered from diastolic hypertension opposed to normal blood pressure in KD mice. Our findings demonstrate a role for LRRK2 in kidney and lung physiology and further show that LRRK2 kinase function affects LRRK2 protein steady-state levels thereby altering putative scaffold/GTPase activity. These novel aspects of peripheral LRRK2 biology critically impact ongoing attempts to develop LRRK2 selective kinase inhibitors as therapeutics for PD.
Konwergencja gospodarek państw Europy Środkowo-Wschodniej względem strefy euro - test wspólnego trendu i wspólnego cyklu

Aby odpowiedzieć na pytanie o optymalność wspólnego obszaru walutowego krajów Europy Środkowo-Wschodniej oraz krajów strefy euro, w artykule wykorzystano metakryterium optymalności w odniesieniu zarówno do krótkookresowego, jak i długookresowego komponentu aktywności gospodarczej, a więc łączny test wspólnego trendu i wspólnego cyklu, zaproponowany przez Engle’a i Kozickiego (1993) oraz Vahida i Engle’a (1993). Dotychczasowe badania w tym zakresie koncentrowały się na synchronizacji cykli koniunkturalnych gospodarek, a więc analizowały spełnienie metakryterium w ujęciu retrospektywnym, na podstawie szoków koniunkturalnych w przeszłości. Poszerzenie analizy o zbieżność trendów pozwala na uwzględnienie wymiaru prospektywnego, jako że zjawiska natury długookresowej mają przełożenie na strukturalne cechy gospodarek i tym samym na prawdopodobieństwo wystąpienia szoków asymetrycznych w przyszłości. Otrzymane rezultaty sugerują, że zarówno w krótkim, jak i w długim okresie strefa euro wyznacza ścieżkę równowagi, do której dostosowuje się aktywność gospodarcza krajów Europy Środkowo-Wschodniej, jednak tempo i siła dostosowań są różne.
On Grothendieck's construction of Teichmüller space

In his 1944 paper Ver\"anderliche Riemannsche Fl\"achen , Teichm\"uller defined a structure of complex manifold on the set of isomorphism classes of marked closed Riemann surfaces of genus g. The complex manifold he obtained is the space called today Teichm\"uller space. In the same paper, Teichm\"uller introduced the so-called universal Teichm\"uller curve -- a space over Teichm\"uller space where the fiber above each point is a Riemann surface representing that point. In fact, Teichm\"uller proved the existence of the Teichm\"uller curve as a space of Riemann surfaces parametrized by an analytic space, with an existence and uniqueness theorem establishing this analytic structure. This result was later reformulated and proved by Grothendieck in a series of ten lectures he gave at Cartan's seminar in 1960-1961. In his approach , Grothendieck replaced Teichm\"uller's explicit parameters by a general construction of fiber bundles whose base is an arbitrary analytic space. This work on Teichm\"uller space led him to recast the bases of analytic geometry using the language of categories and functors. In Grothendieck's words, the Teichm\"uller curve becomes a space representing a functor from the category of analytic spaces into the category of sets. In this survey, we comment on Grothendieck's series of lectures. The survey is primarily addressed to low-dimensional topologists and geometers. In presenting Grothendieck's results, we tried to explain or rephrase in more simple terms some notions that are usually expressed in the language of algebraic geometry. However, it is not possible to short-circuit the language of categories and functors. The survey is also addressed to those algebraic geometers who wish to know how the notion of moduli space evolved in connection with Teichm\"uller theory. Explaining the origins of mathematical ideas contributes in dispensing justice to their authors and it usually renders the theory that is surveyed more attractive. The final version of this paper will appear as a chapter in Volume VI of the Handbook of Teichm\"uller theory. This volume is dedicated to the memory of Alexander Grothendieck.
Approximating weighted shortest paths on polyhedral surfaces

Shortest path problems are among the fundamental prob lems studied in computational geometry. In this video, we consider the problem of computing a shortest cost path between two points s and t on a (possibly nonconvex) polyhedral surface P. The surface is composed of triangular regions (faces) in which each region has an associated positive weight. The cost of travel through each region is the distance traveled times its weight.
Algorithm for Riemannian manifold learning

We present a novel method for manifold learning, which identifies the low-dimensional manifold-like structure presented in a set of data points in a possibly high-dimensional space with homomorphism contained. The main idea is derived from the concept of covariant components in curvilinear coordinate systems. In a linearly transparent way, we translate this idea to a cloud of data points in order to calculate the coordinates of the points directly. Our implementation currently uses Dijkstra's algorithm for shortest paths in graphs and some basic theorems from Riemannian differential geometry. We expect this approach to open up new possibilities for manifold learning using only geometry constraints, which means the coordinate system is “learned” from experimental high-dimensional data rather than defined analytically using e.g. models based on PCA, MDS, and Eigenmaps.
Survey of Morris and E-FAST algorithms based on power-generation operation and assistant decision model

Global uncertainty and sensitivity analysis(UA-SA) can be applied to quantify the influence of uncertain model inputs on the response variability of a power system model. Uncertainty and sensitivity analysis algorithms are becoming an efficient tool for the understanding, application and development of mathematical and computer models. In this paper, Morris and Extended Fourier Amplitude Sensitivity Test (E-FAST) is used to test the Power-generation Operation and Assistant Decision Model (POADM). Rankings of POADM parameters (from the most to the least relevant) were generated. And then we further analyse the effect of the uncertainty of parameters and interaction between the parameters. Sensitivity algorithms was devoted to predict the risk of facing a loss of total profits as thermoelectric conversion efficiency decreases and assess the relative importance of input parameters on the output. As evidenced by the performance indices, Morris and E-FAST algorithms have demonstrated to be powerful techniques for quantifying uncertainty in complex model. Those two algorithms are reliable and robust in global uncertainty and sensitivity analysis.
Improve performance of tcp new reno over mobile ad-hoc network using abra

In a mobile ad hoc network, temporary link failures and route changes occur frequently. With the assumption that all packet losses are due to congestion, TCP performs poorly in such an environment. There are many versions of TCP which modified time to time as per need. In this paper modifications introduced on TCP New Reno over mobile ad-hoc networks using calculation of New Retransmission Time out (RTO), to improve performance in term of congestion control. To calculate New RTO, adaptive backoff response approach (ABRA) in TCP New Reno was applied which suggest ABRA New Reno. It utilizes an ABRA by which congestion window and slow start threshold values were decreased whenever an acknowledgement is received and new backoff value calculate from smoothed round trip time. Evaluation based on comparative study of ABRA New Reno with other TCP Variants like New Reno and Reno was done using realistic parameters like TCP Packet Received, Packet Drop, Packets Retransmitted, Throughput, and Packet Delivery Ratio calculated by varying attributes of Node Speed, Number of Nodes and Pause Time. Implementation and simulations were performed in QualNet 4.0 simulator.
COINSTAC: A Privacy Enabled Model and Prototype for Leveraging and Processing Decentralized Brain Imaging Data

The field of neuroimaging has embraced the need for sharing and collaboration. Data sharing mandates from public funding agencies and major journal publishers have spurred the development of data repositories and neuroinformatics consortia. However, efficient and effective data sharing still faces several hurdles. For example, open data sharing is on the rise but is not suitable for sensitive data that are not easily shared, such as genetics. Current approaches can be cumbersome (such as negotiating multiple data sharing agreements). There are also significant data transfer, organization and computational challenges. Centralized repositories only partially address the issues. We propose a dynamic, decentralized platform for large scale analyses called the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC). The COINSTAC solution can include data missing from central repositories, allows pooling of both open and “closed” repositories by developing privacy-preserving versions of widely-used algorithms, and incorporates the tools within an easy-to-use platform enabling distributed computation. We present an initial prototype system which we demonstrate on two multi-site data sets, without aggregating the data. In addition, by iterating across sites, the COINSTAC model enables meta-analytic solutions to converge to “pooled-data” solutions (i.e., as if the entire data were in hand). More advanced approaches such as feature generation, matrix factorization models, and preprocessing can be incorporated into such a model. In sum, COINSTAC enables access to the many currently unavailable data sets, a user friendly privacy enabled interface for decentralized analysis, and a powerful solution that complements existing data sharing solutions.
Kernel Ridge Regression via Partitioning

In this paper, we investigate a divide and conquer approach to Kernel Ridge Regression (KRR). Given n samples, the division step involves separating the points based on some underlying disjoint partition of the input space (possibly via clustering), and then computing a KRR estimate for each partition. The conquering step is simple: for each partition, we only consider its own local estimate for prediction. We establish conditions under which we can give generalization bounds for this estimator, as well as achieve optimal minimax rates. We also show that the approximation error component of the generalization error is lesser than when a single KRR estimate is fit on the data: thus providing both statistical and computational advantages over a single KRR estimate over the entire data (or an averaging over random partitions as in other recent work, [30]). Lastly, we provide experimental validation for our proposed estimator and our assumptions.
Direct numerical simulation of turbulence modulation by particles in isotropic turbulence

The modulation of isotropic turbulence by particles has been investigated using direct numerical simulation (DNS). The particular focus of the present work is on the class of dilute flows in which particle volume fractions and inter-particle collisions are negligible. Gravitational settling is also neglected and particle motion is assumed to be governed by drag with particle relaxation times ranging from the Kolmogorov scale to the Eulerian time scale of the turbulence and particle mass loadings up to 1. The velocity field was made statistically stationary by forcing the low wavenumbers of the flow. The calculations were performed using 963 collocation points and the Taylor-scale Reynolds number for the stationary flow was 62. The effect of particles on the turbulence was included in the Navier–Stokes equations using the point-force approximation in which 963 particles were used in the calculations. DNS results show that particles increasingly dissipate fluid kinetic energy with increased loading, with the reduction in kinetic energy being relatively independent of the particle relaxation time. Viscous dissipation in the fluid decreases with increased loading and is larger for particles with smaller relaxation times. Fluid energy spectra show that there is a non-uniform distortion of the turbulence with a relative increase in small-scale energy. The non-uniform distortion significantly affects the transport of the dissipation rate, with the production and destruction of dissipation exhibiting completely different behaviours. The spectrum of the fluid–particle energy exchange rate shows that the fluid drags particles at low wavenumbers while the converse is true at high wavenumbers for small particles. A spectral analysis shows that the increase of the high-wavenumber portion of the fluid energy spectrum can be attributed to transfer of the fluid–particle covariance by the fluid turbulence. This in turn explains the relative increase of small-scale energy caused by small particles observed in the present simulations as well as those of Squires & Eaton (1990) and Elghobashi & Truesdell (1993).
Multipitch estimation of quasi-harmonic sounds in colored noise

This paper proposes a new multipitch estimator based on a likelihood maximization principle. For each tone, a sinusoidal model is assumed with a colored, Moving-Average, background noise and an autoregressive spectral envelope for the overtones. A monopitch estimator is derived following a Weighted Maximum Likelihood principle and leads to find the fundamental frequency (F0 ) which jointly maximally flattens the noise spectrum and the sinusoidal spectrum. The multipitch estimator is obtained by extending the method for jointly estimating multiple F0 's. An application to piano tones is presented, which takes into account the inharmonicity of the overtone series for this instrument.