Miracle-dz/UniFAR-FTUs huggingface dataset:
High Efficiency of Antiviral CD4+ Killer T Cells

The destruction of infected cells by cytotxic T lymphocytes (CTL) is integral to the effective control of viral and bacterial diseases, and CTL function at large has long been regarded as a distinctive property of the CD8+T cell subset. In contrast, and despite their first description more than three decades ago, the precise contribution of cytotoxic CD4+T cells to the resolution of infectious diseases has remained a matter of debate. In particular, the CTL activity of pathogen-specific CD4+ “helper” T cells constitutes a single trait among a diverse array of other T cell functionalities, and overall appears considerably weaker than the cytolytic capacity of CD8+ effector T cells. Here, using an in vivo CTL assay, we report that cytotoxic CD4+T cells are readily generated against both viral and bacterial pathogens, and that the efficiency of MHC-II-restricted CD4+T cell killing adjusted for effector:target cell ratios, precise specificities and functional avidities is comparable in magnitude to that of CD8+T cells. In fact, the only difference between specific CD4+ and CD8+T cells pertains to the slightly delayed killing kinetics of the former demonstrating that potent CTL function is a cardinal property of both antiviral CD8+ and CD4+T cells.
Human vision model including age dependencies

We extend a model of the human visual system to predict the effects of age. The extensions are based on the existing models of disability glare, aging of the crystalline lens and reduced pupil size with age. The complete model, including an empirical neural component, can well explain the differences in contrast sensitivity between old and young observers.
Protein Kinase C-δ and Phosphatidylinositol 3-Kinase/Akt Activate Mammalian Target of Rapamycin to Modulate NF-κB Activation and Intercellular Adhesion Molecule-1 (ICAM-1) Expression in Endothelial Cells*

We have shown that the mammalian target of rapamycin (mTOR) down-regulates thrombin-induced ICAM-1 expression in endothelial cells by suppressing the activation of NF-κB. However, the mechanisms by which mTOR is activated to modulate these responses remain to be addressed. Here, we show that thrombin engages protein kinase C (PKC)-δ and phosphattidylinositol 3-kinase (PI3K)/Akt pathways to activate mTOR and thereby dampens NF-κB activation and intercellular adhesion molecule 1 (ICAM-1) expression. Stimulation of human vascular endothelial cells with thrombin induced the phosphorylation of mTOR and its downstream target p70 S6 kinase in a PKC-δ- and PI3K/Akt-dependent manner. Consistent with this, thrombin-induced phosphorylation of p70 S6 kinase was defective in embryonic fibroblasts from mice with targeted disruption of PKC-δ (Pkc-δ–/–), p85α and p85β subunits of the PI3K (p85α–/–β–/–), or Akt1 and Akt2 (Akt1–/–2–/–). Furthermore, we observed that expression of the constitutively active form of PKC-δ or Akt was sufficient to induce NF-κB activation and ICAM-1 expression, and that co-expression of mTOR suppressed these responses. In reciprocal experiments, inhibition/depletion of mTOR augmented NF-κB activation and ICAM-1 expression induced by PKC-δ or Akt. In control experiments, increasing or impairing mTOR signaling by the above approaches produced similar effects on NF-κB activation and ICAM-1 expression induced by thrombin. Thus, these data reveal an important role of PKC-δ and PI3K/Akt pathways in activating mTOR as an endogenous modulator to ensure a tight regulation of NF-κB signaling of ICAM-1 expression in endothelial cells.
Deep Rooting In-Situ Expansion of mtDNA Haplogroup R8 in South Asia

Background The phylogeny of the indigenous Indian-specific mitochondrial DNA (mtDNA) haplogroups have been determined and refined in previous reports. Similar to mtDNA superhaplogroups M and N, a profusion of reports are also available for superhaplogroup R. However, there is a dearth of information on South Asian subhaplogroups in particular, including R8. Therefore, we ought to access the genealogy and pre-historic expansion of haplogroup R8 which is considered one of the autochthonous lineages of South Asia. Methodology/Principal Findings Upon screening the mtDNA of 5,836 individuals belonging to 104 distinct ethnic populations of the Indian subcontinent, we found 54 individuals with the HVS-I motif that defines the R8 haplogroup. Complete mtDNA sequencing of these 54 individuals revealed two deep-rooted subclades: R8a and R8b. Furthermore, these subclades split into several fine subclades. An isofrequency contour map detected the highest frequency of R8 in the state of Orissa. Spearman's rank correlation analysis suggests significant correlation of R8 occurrence with geography. Conclusions/Significance The coalescent age of newly-characterized subclades of R8, R8a (15.4±7.2 Kya) and R8b (25.7±10.2 Kya) indicates that the initial maternal colonization of this haplogroup occurred during the middle and upper Paleolithic period, roughly around 40 to 45 Kya. These results signify that the southern part of Orissa currently inhabited by Munda speakers is likely the origin of these autochthonous maternal deep-rooted haplogroups. Our high-resolution study on the genesis of R8 haplogroup provides ample evidence of its deep-rooted ancestry among the Orissa (Austro-Asiatic) tribes.
Flatness of heavy chain systems

This paper gives an overview of the results of Petit and Rouchon (2001). Furthermore it contains some previously unpublished material concerning the homogeneous chain carrying a load. In the above paper the flatness of heavy chain systems, i.e. trolleys carrying a fixed length heavy chain that may carry a load, is addressed in the partial derivatives equations framework. We parameterize the system trajectories by the trajectories of its free end and solve the motion planning problem, namely steering from one state to another state. When considered as a finite set of small pendulums these systems were shown to be flat in Murray (1996). Our study is an extension to the infinite dimensional case. Under small angle approximations, these heavy chain systems are described by a 1D partial differential wave equation. Dealing with this infinite dimensional description, we show how to get the explicit parameterization of the chain trajectory using (distributed and punctual) advances and delays of its free end.
Preoperative 123I-iomazenil SPECT imaging predicts cerebral hyperperfusion following endarterectomy for unilateral cervical internal carotid artery stenosis.

PURPOSE Cerebral hyperperfusion following carotid endarterectomy (CEA) occurs in patients with preoperative impairments in cerebral hemodynamics. The aim of the present study was to determine whether late images/early images on preoperative brain (123)I-iomazenil (IMZ) single-photon emission computed tomography (SPECT), which correlate with oxygen extraction fraction images on positron emission tomography, could identify patients at risk for cerebral hyperperfusion following endarterectomy for unilateral cervical internal carotid artery (ICA) stenosis. METHODS In 80 patients, preoperative brain SPECT scans were initiated immediately after (early images) and 180 min after (late images) administration of (123)I-IMZ. A region of interest (ROI) was automatically placed in the middle cerebral artery territory in both the cerebral hemispheres using a three-dimensional stereotaxic ROI template. Transcranial regional cerebral oxygen saturation (rSO(2)) was monitored using near-infrared spectroscope throughout carotid endarterectomy, and a patient was defined as having cerebral hyperperfusion when a ratio of rSO(2) at the end of the surgery to rSO(2) before ICA clamping was ≥ 1.1. RESULTS Cerebral hyperperfusion was observed on intraoperative rSO(2) monitoring in eight patients (10%). Preoperative increase in affected side-to-contralateral side asymmetry on late/early (123)I-IMZ value was the only significant independent predictor of cerebral hyperperfusion (95% confidence interval [CI], 1.606 to 8.710; P = 0.0010). The preoperative late/early (123)I-IMZ asymmetry corresponded to an 88% sensitivity and 89% specificity, with 47% positive- and 98% negative-predictive values for the development of cerebral hyperperfusion. CONCLUSIONS Preoperative late/early (123)I-IMZ images can identify patients at risk for cerebral hyperperfusion following endarterectomy for unilateral cervical ICA stenosis.
Learning Color Names from Real-World Images

Within a computer vision context color naming is the action of assigning linguistic color labels to image pixels. In general, research on color naming applies the following paradigm: a collection of color chips is labelled with color names within a well-defined experimental setup by multiple test subjects. The collected data set is subsequently used to label RGB values in real-world images with a color name. Apart from the fact that this collection process is time consuming, it is unclear to what extent color naming within a controlled setup is representative for color naming in real-world images. Therefore we propose to learn color names from real-world images. Furthermore, we avoid test subjects by using Google Image to collect a data set. Due to limitations of Google Image this data set contains a substantial quantity of wrongly labelled data. The color names are learned using a PLSA model adapted to this task. Experimental results show that color names learned from real-world images significantly outperform color names learned from labelled color chips on retrieval and classification.
ZVT Interleaved Boost Converters with Built-In Voltage Doubler and Current Auto-Balance Characteristic

An interleaved boost converter with coupled inductors and switched capacitors is proposed in this paper. The switched capacitors are used to realize the inherent voltage-double function that increases the voltage gain and reduces the voltage stress of the switch greatly. Therefore, the low-conduction resistance and low-voltage-rated switches can be applied to improve the efficiency of this topology. Moreover, the load current can automatically be equally shared by each phase as a consequence of the switched capacitors adopted in the output stage. Active clamp circuits are applied for the interleaved two phases to recycle the leakage energy and absorb the voltage spikes caused by the leakage inductance. Both the main and the clamping switches are zero-voltage transition (ZVT) switches during the whole switching transition that reduce the switching losses. The current falling rates of the clamping diodes and output diodes are controlled by the leakage inductance so that the diode reverse-recovery problem is alleviated. The experimental results are shown to verify the effectiveness of the theoretical analysis based on a 48- to- 380-V DC/DC prototype.
Select ahead: efficient object selection technique using the tendency of recent cursor movements

Virtual hand is one of the most intuitive metaphors for object selection in the virtual environment because of its natural mapping between the user action input and the cursor. However, it has a limitation of lengthy cursor manipulation for object selection task which is directly related to the level of workload of the user in performing object selection. In this paper, we propose 'Select Ahead' as a new object selection technique that improves efficiency by reducing the physical workload. Select Ahead guides the user to select the distant object along the estimated tendency of the recent cursor movements. We evaluate the relative performance of Select Ahead through the experiments in the 3D virtual environment with various object densities. The results show that Select Ahead significantly reduces the length of the cursor movements compared to those of the 3D point cursor and the 3D bubble cursor regardless of the object density. In the aspect of the total duration time for selection, Select Ahead outperforms the 3D point cursor and has no significant difference compared to that of the 3D bubble cursor.
A feature-based robust digital image watermarking scheme

The effectiveness of a digital watermarking algorithm is indicated by the robustness of embedded watermarks against various attacks. Improving the robustness of a watermark so as to withstand attacks has been one of the main research objectives in digital image watermarking. The two issues of existing feature-based schemes that have to be addressed are: one is avoiding repeated selection of robust regions for watermarking to resist similar attacks, and the other is the difficulty of selecting the most robust and smallest feature region set to be watermarked. In order to achieve robustness, an overall architecture for a feature-based robust digital image watermarking scheme is designed. A simulated attacking procedure is performed using predefined attacks to evaluate the robustness of every candidate feature region selected. Comparing with some well-known feature-based methods, the proposed method exhibits better performance in robust digital watermarking.
Microstructure and mechanical properties of cast (Al–Si)/SiCp composites produced by liquid and semisolid double stirring process

Abstract A stirring process containing two steps, i.e. liquid and then semisolid stirring, was used to produce SiC particle reinforced aluminium matrix composites. The major advantages of this process are that full wetting of SiC particles by molten aluminium can be readily achieved at relatively low stirring rates, and undesirable Al4 C3 is not formed at the Al/SiC interface due to lower processing temperatures. Cast Al–Si matrix composites reinforced with 15 and 20 vol.-%SiC particles were produced in the present work. The mechanical properties of the composites were evaluated under the conditions of investment mould casting and heat treatment. For the composites obtained without employing semisolid stirring, the aggregation of SiC particles observed in the microstructure of composites resulted in quite poor mechanical properties. Observations and analyses indicated that some Al/SiC interfaces were very clean, and a reaction product of spinel MgAl2O4 was also found at some Al/SiC interfaces. Silicon dioxide (SiO2 ) was found to exist on the surface of as purchased and 250°C dried SiC powders. This SiO2 is involved in the spinel reaction at the interface between the SiC particles and the matrix in the present Al/SiC composites.
A Two-Tier User Simulation Model for Reinforcement Learning of Adaptive Referring Expression Generation Policies

We present a new two-tier user simulation model for learning adaptive referring expression generation (REG) policies for spoken dialogue systems using reinforcement learning. Current user simulation models that are used for dialogue policy learning do not simulate users with different levels of domain expertise and are not responsive to referring expressions used by the system. The two-tier model displays these features, that are crucial to learning an adaptive REG policy. We also show that the two-tier model simulates real user behaviour more closely than other baseline models, using the dialogue similarity measure based on Kullback-Leibler divergence.
Commissioning and quality assurance of Dynamic WaveArc irradiation

A novel three‐dimensional unicursal irradiation technique “Dynamic WaveArc” (DWA), which employs simultaneous and continuous gantry and O‐ring rotation during dose delivery, has been implemented in Vero4DRT. The purposes of this study were to develop a commissioning and quality assurance procedure for DWA irradiation, and to assess the accuracy of the mechanical motion and dosimetric control of Vero4DRT. To determine the mechanical accuracy and the dose accuracy with DWA irradiation, 21 verification test patterns with various gantry and ring rotational directions and speeds were generated. These patterns were irradiated while recording the irradiation log data. The differences in gantry position, ring position, and accumulated MU (EG,ER, and EMU, respectively) between the planned and actual values in the log at each time point were evaluated. Furthermore, the doses delivered were measured using an ionization chamber and spherical phantom. The constancy of radiation output during DWA irradiation was examined by comparison with static beam irradiation. The mean absolute error (MAE) of EG and ER were within 0.1° and the maximum error was within 0.2°. The MAE of EMU was within 0.7 MU, and maximum error was 2.7 MU. Errors of accumulated MU were observed only around control points, changing gantry, and ring velocity. The gantry rotational range, in which EMU was greater than or equal to 2.0 MU, was not greater than 3.2%. It was confirmed that the extent of the large differences in accumulated MU was negligibly small during the entire irradiation range. The variation of relative output value for DWA irradiation was within 0.2%, and this was equivalent to conventional arc irradiation with a rotating gantry. In conclusion, a verification procedure for DWA irradiation was designed and implemented. The results demonstrated that Vero4DRT has adequate mechanical accuracy and beam output constancy during gantry and ring rotation. PACS number: 87
EXTENSIONS OF PAC LEARNING FOR PARTIALLY OBSERVABLE MARKOV DECISION PROCESSES

We extend Valiant’s probably approximately correct (PAC) model of learning to Markov decision processes (MDPs). The work is related to the simulation-based estimation of value functions for discounted reward MDPs. We obtain uniform sample complexity results for MDP simulation. We also obtain uniform sample complexity results for the case when the states are partially observable and policies are non-stationary and have memory. The results can be extended to Markov games with a finite number of players.
Parametric limits

We develop a categorical model of polymorphic lambda calculi using the notion of parametric limits, which extend the notion of limits in categories to reflexive graphs of categories. We show that a number of parametric models of polymorphism can be captured in this way. We also axiomatize the structure of reflexive graphs needed for modelling parametric polymorphism based on ideas of fibrations, and show that it leads to proofs of representation results such as the initial algebra and final coalgebra properties one expects in polymorphic lambda calculi.
A reliable and distributed time synchronization for Cognitive Radio Networks

Cognitive Radio Networks (CRNs) have been envisioned as a solution for frequency spectrum-scarcity and spectrum misuse issues. Since the requirement for cooperation and dynamism increases with the new spectrum access approach, time synchronization is mandatory for ensuring the proper operation of CRNs. In this paper, we propose DCR-Sync, a novel time synchronization protocol for CRNs. Differently from existing proposals, DCR-Sync is fully distributed and resilient towards failure of root nodes, i.e., the nodes which play the role of master on the synchronization process. We present DCR-Sync in two versions. The first version is static in nature, and the second version can adapt dynamically to network changes. Through extensive simulations, we show that both versions outperform the performance of existing synchronization protocols. Precisely, both versions of DCR-Sync are simulated using NS2 simulator and are compared to the TPSN protocol. Simulation results show the improvements obtained by DCR-Sync in terms of network overhead and convergence time.
Kernel Carpentry for Online Regression Using Randomly Varying Coefficient Model

We present a Bayesian formulation of locally weighted learning (LWL) using the novel concept of a randomly varying coefficient model. Based on this, we propose a mechanism for multivariate non-linear regression using spatially localised linear models that learns completely independent of each other, uses only local information and adapts the local model complexity in a data driven fashion. We derive online updates for the model parameters based on variational Bayesian EM. The evaluation of the proposed algorithm against other state-of-the-art methods reveal the excellent, robust generalization performance beside surprisingly efficient time and space complexity properties. This paper, for the first time, brings together the computational efficiency and the adaptability of 'non-competitive' locally weighted learning schemes and the modelling guarantees of the Bayesian formulation.
Neurological, Functional, and Cognitive Stroke Outcomes in Mexican Americans

Background and Purpose— Our objective was to compare neurological, functional, and cognitive stroke outcomes in Mexican Americans (MAs) and non-Hispanic whites using data from a population-based study. Methods— Ischemic strokes (2008–2012) were identified from the Brain Attack Surveillance in Corpus Christi (BASIC) Project. Data were collected from patient or proxy interviews (conducted at baseline and 90 days poststroke) and medical records. Ethnic differences in neurological (National Institutes of Health Stroke Scale: range, 0–44; higher scores worse), functional (activities of daily living/instrumental activities of daily living score: range, 1–4; higher scores worse), and cognitive (Modified Mini-Mental State Examination: range, 0–100; lower scores worse) outcomes were assessed with Tobit or linear regression adjusted for demographics and clinical factors. Results— A total of 513, 510, and 415 subjects had complete data for neurological, functional, and cognitive outcomes and covariates, respectively. Median age was 66 (interquartile range, 57–78); 64% were MAs. In MAs, median National Institutes of Health Stroke Scale, activities of daily living/instrumental activities of daily living, and Modified Mini-Mental State Examination score were 3 (interquartile range, 1–6), 2.5 (interquartile range, 1.6–3.5), and 88 (interquartile range, 76–94), respectively. MAs scored 48% worse (95% CI, 23%–78%) on National Institutes of Health Stroke Scale, 0.36 points worse (95% CI, 0.16–0.57) on activities of daily living/instrumental activities of daily living score, and 3.39 points worse (95% CI, 0.35–6.43) on Modified Mini-Mental State Examination than non-Hispanic whites after multivariable adjustment. Conclusions— MAs scored worse than non-Hispanic whites on all outcomes after adjustment for confounding factors; differences were only partially explained by ethnic differences in survival. These findings in combination with the increased stroke risk in MAs suggest that the public health burden of stroke in this growing population is substantial.
Accelerating Stochastic Composition Optimization

Consider the stochastic composition optimization problem where the objective is a composition of two expected-value functions. We propose a new stochastic first-order method, namely the accelerated stochastic compositional proximal gradient (ASC-PG) method, which updates based on queries to the sampling oracle using two different timescales. The ASC-PG is the first proximal gradient method for the stochastic composition problem that can deal with nonsmooth regularization penalty. We show that the ASC-PG exhibits faster convergence than the best known algorithms, and that it achieves the optimal sample-error complexity in several important special cases. We further demonstrate the application of ASC-PG to reinforcement learning and conduct numerical experiments.