Miracle-dz/UniFAR-FTUs huggingface dataset:
CD47 Is Necessary for Inhibition of Nitric Oxide-stimulated Vascular Cell Responses by Thrombospondin-1*

CD36 is necessary for inhibition of some angiogenic responses by the matricellular glycoprotein thrombospondin-1 and is therefore assumed to be the receptor that mediates its anti-angiogenic activities. Although ligation of CD36 by antibodies, recombinant type 1 repeats of thrombospondin-1, or CD36-binding peptides was sufficient to inhibit nitric oxide (NO)-stimulated responses in both endothelial and vascular smooth muscle cells, picomolar concentrations of native thrombospondin-1 similarly inhibited NO signaling in vascular cells from wild-type and CD36-null mice. Ligation of the thrombospondin-1 receptor CD47 by recombinant C-terminal regions of thrombospondin-1, thrombospondin-1 peptides, or CD47 antibodies was also sufficient to inhibit NO-stimulated phenotypic responses and cGMP signaling in vascular cells. Thrombospondin-1 did not inhibit NO signaling in CD47-null vascular cells or NO-stimulated vascular outgrowth from CD47-null muscle explants in three-dimensional cultures. Furthermore, the CD36-binding domain of thrombospondin-1 and anti-angiogenic peptides derived from this domain failed to inhibit NO signaling in CD47-null cells. Therefore, ligation of either CD36 or CD47 is sufficient to inhibit NO-stimulated vascular cell responses and cGMP signaling, but only CD47 is necessary for this activity of thrombospondin-1 at physiological concentrations.
Design and implementation of a low-level language for interaction nets

Interaction nets are a graphical model of computation based on a restricted form of graph rewriting. A specific net can represent a program with a user-defined set of nodes and computation is modelled by a user-defined set of rewrite rules. This very simple model has had great success in modelling sharing in computation (specifically in the lambda calculus), and there is potential for generating a new theoretical foundation of parallel computation since all computation steps are local and thus can be implemented in parallel. This thesis is about the implementation of interaction nets. Specifically, for the first contributions we define a low-level language as an object language for the compilation of interaction nets. We study the efficiency and properties of different data structures, and focus on the management of the rewriting process which is usually hidden in the graph rewriting system. We provide experimental data comparing the different choices of data structures and select one for further development. For the compilation of nets and rules into this language, we show an optimisation such that allocated memory for agents is reused, and thus we obtain optimal efficiency for the rewriting process. The second part of this thesis describes extensions of interaction nets so that they can be used as a programming language. Interaction nets in their pure form are quite restrictive in expressive power. By extending the notions of agents and rules we can express computation more naturally, yet still preserve the good properties (such as strong confluence) of the rewriting system. We then implement a selection of algorithms using and extending the compilation techniques developed in the first part of the thesis. We also demonstrate experimental results on multi-core CPUs, using the Posix-thread library, thus realising some of the potential for parallel implementation mentioned above.
Sliding Mode Control for Trajectory Tracking of a Non-holonomic Mobile Robot using Adaptive Neural Networks

In this work a sliding mode control method for a non-holonomic mobile robot using an adaptive neural network is proposed. Due to this property and restricted mobility, the trajectory tracking of this system has been one of the research topics for the last ten years. The proposed control structure combines a feedback linearization model, based on a nominal kinematic model, and a practical design that combines an indirect neural adaptation technique with sliding mode control to compensate for the dynamics of the robot. A neural sliding mode controller is used to approximate the equivalent control in the neighbourhood of the sliding manifold, using an online adaptation scheme. A sliding control is appended to ensure that the neural sliding mode control can achieve a stable closed-loop system for the trajectory-tracking control of a mobile robot with unknown non-linear dynamics. Also, the proposed control technique can reduce the steady-state error using the online adaptive neural network with sliding mode control; the design is based on Lyapunov’s theory. Experimental results show that the proposed method is effective in controlling mobile robots with large dynamic uncertainties Normal 0 21 false false false ES-AR X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabla normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}
Molecular Typing of “Candidatus Bartonella ancashi,” a New Human Pathogen Causing Verruga Peruana

ABSTRACT A recently described clinical isolate, “Candidatus Bartonella ancashi,” was obtained from a blood sample of a patient presenting with verruga peruana in the Ancash region of Peru. This sample and a second isolate obtained 60 days later from the same patient were molecularly typed using multilocus sequence typing (MLST) and multispacer sequence typing (MST). The isolates were 100% indistinguishable from each other but phylogenetically distant from Bartonella bacilliformis and considerably divergent from other known Bartonella species, confirming their novelty.
Human adenovirus replication in immunocompetent Syrian hamsters can be attenuated with chlorpromazine or cidofovir

Adenoviruses can cause severe toxicity in children and in immunocompromised adults, and therefore a means to abrogate replication would be useful. With regard to cancer treatment, replication competent oncolytic adenoviruses have been safe in humans, although their efficacy has been variable. Therefore, more effective agents are now entering clinical testing and, consequently, replication‐associated side effects remain a concern. Preclinical analysis of replication related toxicity has been hampered by a lack of permissive models. Therefore, it has been difficult to study modulation of human adenovirus replication in immune competent animals.
Jibbigo: Speech-to-speech translation on mobile devices

Jibbigo is a speech-to-speech translation application for iPhone, iPod touch, and iPad devices. Jibbigo allows the user to simply speak a sentence, and it speaks the sentence aloud in the other language, much like a personal human interpreter would. The speech-to-speech translation is bi-directional for a two way dialog between participants.
Moment Condition Tests for Heavy-Tailed Time Series

We develop an asymptotically chi-squared statistic for testing moment conditions E[mt(θ0)]=0, where mt(θ0) may be weakly dependent, scalar components of mt(θ0) may have an infinite variance, and E[mt(θ)] need not exist for any θ under the alternative. Score tests are a natural application, and in general a variety of tests can be heavy-tail robustified by our method, including white noise, GARCH affects, omitted variables, distribution, functional form, causation, volatility spillover and over-identification. The test statistic is derived from a tail-trimmed sample version of the moments evaluated at a consistent plug-in θˆT for θ0. Depending on the test in question and heaviness of tails, θˆT may be any consistent estimator including sub-T1/2-convergent and/or asymptotically non-Gaussian ones, since θˆT can be assured not to affect the test statistic asymptotically. We adapt bootstrap, p-value occupation time, and covariance determinant methods for selecting the trimming fractile in any sample, and apply our statistic to tests of white noise, omitted variables and volatility spillover. We find it obtains sharp empirical size and strong power, while conventional tests exhibit size distortions.
Object recognition and pose estimation for modular manipulation system: Overview and initial results

Object detection and pose estimation is a fundamental functionality among robotic perception for manipulation. Applying robots to diverse tasks requires a robust perception skill. In this manuscript, we introduce an overview of our object recognition and pose estimation process and its our initial results. Our approach follows the previous approaches using local feature extraction and match. As a training stage, synthetic dataset is generated with its 2D-3D information. Local features is extracted and its 2D-3D information are stored in the dataset. As a test stage, the background area is removed and blobs which might include object candidates are extracted. Then, the local features are extracted and matched with the features stored in the database and the correspondences are found. Based on the correspondences, object instance and pose information is estimated by solving Perspective-n-Point problem. To validate our approach, we trained the system with synthetic images and tested it with real images for object recognition and detection and with synthetic images for object pose estimation.
Estimating Investment Functions Based on Cointegration: The Case of China

In the Chinese context, a persistent tension exists between system-generated investment ambitions and both the supply and the distributive barriers to these ambitions. This holds for both pre- and postreform periods and across significant policy changes. As a result, the long-run investment function is characterized by equilibrium comovement among real fixed investment level, grain output per capita as representative of necessary consumer goods, and effective energy supply per capita as representative of basic producer goods. A large part of the cyclical pattern of investment growth can be explained by the adjustment to the comovement path and by the relevant changes in energy supply and agricultural output.J. Comp. Econom. ,March 1998, 26(1), pp. 175–191. International Institute for Applied Systems Analysis, Laxenburg, Austria, and Institute of Social Studies, the Hague, the Netherlands.
Merging Claims Databases with a Tumor Registry to Evaluate Variations in Cancer Mortality: Results from a Pilot Study of 698 Colorectal Cancer Patients Treated at One Hospital in the 1990s

Background: Prognostic models are essential for evaluating variations in cancer mortality statistics. While cancer stage is the most widely accepted and commonly used predictor of survival for cancer, electronic claims databases contain large amounts of information on cancer patients. Previous studies have used Medicare databases and tumor registry information from the Surveillance Epidemiology and End Results data sets to evaluate variations in outcomes for older cancer patients. We evaluated if similar analytic efforts could be carried out with readily available data sets for colorectal cancer patients of all ages who received care at a single hospital during the 1990s. Methods: Hospital tumor registry and discharge claims data for patients at one mid-western hospital with surgically treated stage I–III colorectal cancer from 1990–1998 were used to model survival. Kaplan–Meier logrank tests and Cox proportional hazards models tested the statistical significance of demographic, operative, and clinicopathological factors as predictors of survival. Survival probabilities also were compared to U.S. population life table data to determine if survival deficits were larger for younger cancer patients. Results: Of the 698 colorectal cancer patients, overall five-year survival probability was 65%, with a median follow-up of 44.7 months. Factors associated with higher relative risks of death included sociodemographic characteristics [female gender (1.5, 95% CI: 1.1–1.9), ages 70–79 years (1.7, 95% CI: 1.2–2.3), and ≥ 80 years (3.3, 95% CI: 2.4–4.7) as compared to younger patients], clinical characteristics [moderate (1.5, 95% CI: 1.1–2.1) or severe (2.1, 95%: 1.4–3.2) comorbid illness, as compared to mild or no comorbid illnesses and emergency admission (2.1, 95% CI: 1.5–2.9)], pathological characteristics [positive surgical margins (3.5, 95% CI: 2.3–5.3); and higher cancer stage (stage II RR = 1.5, 95% CI = 1.1–2.2; stage III RR = 2.2, 95% CI = 1.5–3.2), as compared to stage I]. A comparison to the age- and gender-matched survival probabilities of the general population demonstrated similar deficits in survival for older patients (≥ 70 years) and younger patients (< 70 years). Conclusions: While cancer stage is a reliable predictor of survival, other sociodemographic and clinical data elements can improve the evaluation of expected survival rates for patients with surgically resectable colorectal cancers. To facilitate comparative interpretations of mortality data, consideration should be given to merging hospital discharge claims data sets with tumor registry information in a manner analogous to that which has been done for older cancer patients who are covered by the Medicare program.
Partnering to Promote Equality in Cancer Care

The existence of major health disparities in the U.S. population is widely accepted. Despite the presence of many national initiatives to end cancer health disparities, there are still differentials at almost every step in the process of prevention to detection through treatment and survival (Centers for Disease Control and Prevention, Office of Minority Health, 2007). Underserved populations distinguished by race, ethnicity, sex, age, socioeconomic status, geographic location, occupation, and education bear a far greater cancer burden than the general population. These barriers are particularly prominent among low-income populations, a large proportion of whom are also racial-ethnic minorities. These disparities in staging, quality of care, and survival represent a complex interaction among social determinants of health, behavioral risk factors, and system access barriers to timely and high-quality medical care. Healthy People 2010 (U.S. Department of Health and Human Services, 2000) and the National Cancer Institute 2015 Challenge Goals (National Cancer Institute, 2002) of eliminating disparities in cancer mortality emphasize accelerating the dissemination and implementation of interventions to address cancer health disparities.
Optimization of burner's range of tunnel furnace by simulation

Tunnel furnace belongs between thermal devices with big energy consumption. Therefore constructers and users are interested about some possibilities to decrease energy consumption in this group of thermal devices. One way for this aim appears the analysis building or rebuilding tunnel furnace by evaluation by simulation cases. In paper will be described mathematical model of tunnel furnace as basic tool for the creating simulation model. Mathematical model is given by based equations describing thermal processes by heat conducting, convection and radiation in tunnel furnace. Then will be presented an optimization of burner's range by simulations with aim to minimize the energy consumption to manufacture subjects.
Co-evolution of Two GTPases Enables Efficient Protein Targeting in an RNA-less Chloroplast Signal Recognition Particle Pathway*

The signal recognition particle (SRP) is an essential ribonucleoprotein particle that mediates the co-translational targeting of newly synthesized proteins to cellular membranes. The SRP RNA is a universally conserved component of SRP that mediates key interactions between two GTPases in SRP and its receptor, thus enabling rapid delivery of cargo to the target membrane. Notably, this essential RNA is bypassed in the chloroplast (cp) SRP of green plants. Previously, we showed that the cpSRP and cpSRP receptor GTPases (cpSRP54 and cpFtsY, respectively) interact efficiently by themselves without the SRP RNA. Here, we explore the molecular mechanism by which this is accomplished. Fluorescence analyses showed that, in the absence of SRP RNA, the M-domain of cpSRP54 both accelerates and stabilizes complex assembly between cpSRP54 and cpFtsY. Cross-linking coupled with mass spectrometry and mutational analyses identified a new interaction between complementarily charged residues on the cpFtsY G-domain and the vicinity of the cpSRP54 M-domain. These residues are specifically conserved in plastids, and their evolution coincides with the loss of SRP RNA in green plants. These results provide an example of how proteins replace the functions of RNA during evolution.
Multichannel speech signal enhancement method based on ICA for objective auscultation of traditional Chinese medicine

Auscultation is one of the Four Diagnosis Methods in traditional Chinese medicine (TCM). Objective auscultation based on applications of computer and digital signal processing techniques became a new trend in modern days. However, speech is inevitably corrupted by ambient noise which leads to rapid deterioration on the accuracy of diagnosis on the part of objective auscultation system. This paper attempts to apply ICA method in a noise reduction process. The basic principles of ICA and noise reduction are illuminated briefly. Experiments are conducted to evaluate the effect of different kinds of ICA algorithm. Finally, the paper concludes with a discussion on the feasibility and practicality of this method.
Statistical mechanics of phase space partitioning in large-scale spiking neuron circuits

Synaptic interactions structure the phase space of the dynamics of neural circuits and constrain neural computation. Understanding how requires methods that handle those discrete interactions, yet few exist. Recently, it was discovered that even random networks exhibit dynamics that partitions the phase space into numerous attractor basins. Here we utilize this phenomenon to develop theory for the geometry of phase space partitioning in spiking neural circuits. We find basin boundaries structuring the phase space are pre-images of spike-time collision events. Formulating a statistical theory of spike-time collision events, we derive expressions for the rate of divergence of neighboring basins and for their size distribution. This theory reveals that the typical basin diameter grows with inhibitory coupling strength and shrinks with the rate of spike events. Our study provides an analytical and generalizable approach for dissecting how connectivity, coupling strength, single neuron dynamics and population activity shape the phase space geometry of spiking circuits.
generic assay for whole-genome amplification and deep sequencing f enterovirus A 71 e

Enterovirus A71 (EV-A71) has emerged as the most important cause of large outbreaks of severe and sometimes fatal hand, foot and mouth disease (HFMD) across the Asia-Pacific region. EV-A71 outbreaks have been associated with (sub)genogroup switches, sometimes accompanied by recombination events. Understanding EV-A71 population dynamics is therefore essential for understanding this emerging infection, and may provide pivotal information for vaccine development. Despite the public health burden of EV-A71, relatively few EV-A71 complete-genome sequences are available for analysis and from limited geographical localities. The availability of an efficient procedure for whole-genome sequencing would stimulate effort to generate more viral sequence data. Herein, we report for the first time the development of a next-generation sequencing based protocol for whole-genome sequencing of EV-A71 directly from clinical specimens. We were able to sequence viruses of subgenogroup C4 and B5, while RNA from culture materials of diverse EV-A71 subgenogroups belonging to both genogroup B and C was successfully amplified. The nature of intra-host genetic diversity was explored in 22 clinical samples, revealing 107 positions carrying minor variants (ranging from 0 to 15 variants per sample). Our analysis of EVA71 strains sampled in 2013 showed that they all belonged to subgenogroup B5, representing the first report of this subgenogroup in Vietnam. In conclusion, we have successfully developed a high-throughput next-generation sequencing-based assay for whole-genome sequencing of EV-A71 from clinical samples. © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license
Mining news streams using cross-stream sequential patterns

We present a new method for mining streams of news stories using cross-stream sequential patterns. We cluster stories reporting the same event across the streams within a given time window. For every discovered cluster of stories we create an itemset-sequence consisting of stream identifiers of the stories in the cluster, where the sequence is ordered according to the timestamps of the stories. For every such itemset-sequence we record exact timestamps and content similarities between the respective stories, thus building a collection of itemset-sequences that we use for two tasks: (I) to discover cross-stream dependencies in terms of frequent sequential publishing patterns and content similarity and (II) to rank the streams of news stories with respect to timeliness of reporting important events and content authority. We tested the applicability of the presented method on a collection of streams of news stories which was gathered from major world news agencies.
In vitro ruminal degradability of cereal grain starch

An in vitro method was used to determine ruminal degradability of starch (IVRDS) in a set of cereal grains. The set included 9 feed samples, including 2 samples of ground wheat, 2 samples of wheat treated with sodium hydroxide, ground barley, barley treated with sodium hydroxide, 2 samples of ground oats and ground maize. Ruminal degradability of starch was assayed by the feed fermentation for 2, 4, 6, 16 and 24 hours. A significant difference in starch degradability was found between treated and untreated ground samples a�er 2-hour fermentation (13.73 ± 3.12 vs. 32.77 ± 8.17; P < 0.001), 4-hour fermentation (33.44 ± 7.31 vs. 60.30 ± 16.71; P < 0.001) and 6-hour fermentation (42.63 ± 7.13 vs. 74.20 ± 6.38; P < 0.001). On the basis of the rate of ruminal degradability of starch the order of cereal grains was as follows (from the highest to the lowest value): ground oats, ground wheat, ground barley, ground maize, wheat and barley treated with sodium hydroxide.
Computation of the fractional anisotropy and mean diffusivity maps without tensor decoding and diagonalization: Theoretical analysis and validation

Diffusion tensor MRI (DT‐MRI) is a promising modality for in vivo mapping of the organization of deep tissues. The most commonly used DT‐MRI invariant maps are the mean diffusivity, μ(D), relative anisotropy (RA), and fractional anisotropy (FA). Because of the computational burden, anisotropy maps are generally computed offline. The availability of a simple procedure to compute RA, FA, and μ(D) online would make DT‐MRI more useful in clinical applications that require immediate feedback. In this study, analytical expressions that relate the commonly used tensor anisotropy measures obtained from the decoded and diagonalized DT with those obtained from the first and second moments of the measured diffusion‐weighted (DW) data are derived. Specifically, it is shown that for the principal icosahedron encoding scheme, RA is related to the mean and standard deviation (SD) of the DW measurements that can be computed online. Since FA is commonly used as an anisotropy measure, an analytical expression relating RA and FA was derived from the tensor invariants. These results were validated using both Monte Carlo simulations and high‐resolution, normal whole‐brain DT‐MRI measurements acquired with different b‐factors, encoding schemes, and signal‐to‐noise ratio (SNR) levels. The bias introduced by the rotationally variant encoding schemes into the diffusion measures is also investigated. Magn Reson Med 50:589–598, 2003. © 2003 Wiley‐Liss, Inc.