Miracle-dz/UniFAR-FTUs huggingface dataset:
Viral Load HIV-1 and HIV-2 but Only Indirectly to the Immune Activation in the Pathogenesis of CD4 T Cell Depletion Is Linked Directly to

The causal relationships among CD4 cell depletion, HIV replication, and immune activation are not well understood. HIV-2 infection, “nature’s experiment” with inherently attenuated HIV disease, provides additional insights into this issue. We report the ﬁnding that in HIV-2 and HIV-1 patients with a comparable degree of CD4 depletion the imbalance in the relative sizes of the naive and memory T cell populations and the up-regulation of CD4 and CD8 cell activation markers (HLA-DR, CD38, CD69, Fas molecules) are similar, even though the viral load in the plasma of HIV-2-infected patients is two orders of magnitude lower than in HIV-1 patients and HIV-2 patients are known to have slower rates of CD4 T cell decline and a better clinical prognosis. Moreover, we found a similar increase in the frequency of cycling CD4 T cells (Ki67 (cid:1) ), which was in strong correlation with the expression of activation markers. Finally, the level of T cell anergy, as assessed by the proliferative responses to CD3 stimulation and to a panel of microbial Ags, proved to be comparable in HIV-1 and HIV-2 patients with a similar degree of CD4 depletion despite large differences in viral load. Our data are consistent with a direct causal relationship between immune activation and CD4 cell depletion in HIV disease and an only indirect relation of these parameters to the virus replication rate. Invoking the concept of proximal immune activation and virus transmission, which links efﬁcient transmission of virus to local cell activation and proliferation in response to Ags and inﬂammation, we propose an integrative interpretation of the data and suggest that strongly elevated immune activation induces CD4 cell depletion and not vice versa, with potential implications for the choice of treatment strategies. The Journal of Immunology, 2002, 169: 3400–3406. study, the HIV-1- and HIV-2-infected patients were classiﬁed into three groups according to the degree of CD4 depletion: (cid:3) 500 CD4 (cid:1) T cells/ (cid:1) l, 200–500 CD4 (cid:1) T cells/ (cid:1) l, and (cid:2) 200 CD4 (cid:1) T cells/ (cid:1) l. There were no statistically signiﬁcant differences in the mean CD4 counts between the corresponding groups of HIV-1- and HIV-2-infected patients. The study was approved by the Ethical Board of the Faculty of Medicine of Lisbon.
Transformative Consumer Research: For Personal and Collective Well-Being

In this chapter, we will give a brief introduction to the current practice of nutrition labeling in the USA and the EU. We will then address the question of how nutrition labeling affects consumer behavior, reviewing extant research and proposing an agenda for future research. Our discussion will focus on the effects of nutrition labeling that occur via their impact on consumer behavior. Labeling may also have effects on the supply side: For example, as labeling makes certain nutritional properties of a product more visible, new product development and product reformulation may take place to create positive nutritional profiles. Such effects, while potentially very important from a public health perspective, will not be addressed in this chapter (see Moorman, 1998 and Moorman, Du & Mela, 2005 for investigation of such effects).
Secure image retrieval through feature protection

This paper addresses the problem of image retrieval from an encrypted database, where data confidentiality is preserved both in the storage and retrieval process. The paper focuses on image feature protection techniques which enable similarity comparison among protected features. By utilizing both signal processing and cryptographic techniques, three schemes are investigated and compared, including bit-plane randomization, random projection, and randomized unary encoding. Experimental results show that secure image retrieval can achieve comparable retrieval performance to conventional image retrieval techniques without revealing information about image content. This work enriches the area of secure information retrieval and can find applications in secure online services for images and videos.
VERY LOW BIT RATE TOPOLOGICAL CODING AND VERIFICATION VIA GRAPH SPECTRAL ANALYSIS

With explosive growth of visual content repository in the Internet, a visual descriptor scheme that can support queryby-capture over the wireless link becomes attractive in a number of applications. In this work, we developed a local graph spectral embedding based model for representing high dimensional visual descriptors like SURF, SIFT, and achieves good scalability in query accuracy and bit rate required for transmitting the descriptors. Besides, we tried a simple quantization scheme for SURF to further reduce bit rate. Proposed 32 bit representation performs well on the datasets.
The Components of Happiness: Implications for Retirement Counselling

The suggestion is made that retirement be considered the most important criterion dimension of adjustment to retirement. Consequently, the primary function of the retirement counsellor is to promote the happiness of the client. The intention of the present investigationwas to assess the relative contributions to the happiness of elderly people ofthree components of the happiness construct: namely, affect, disposition and the affect x disposition interaction. From this evaluation it was hoped to provide general guidelines forretirement counselling practices. Using scale measures of happiness and its components, three populations of elderly Newfoundland residents and a multiple regression analysisprocedure, the relative contributions of the components to happiness were found to rank: affect > interaction > disposition. Implications for counselling practices arc discussed.
Poled composites with Nd-Mn-doped PZTfibers under bipolar electrical load

Using the sol-gel process, Nd-Mn-doped PZT fibers were produced. The PZT was doped with 2 mol% neodymium and 1.1 mol% manganese. For characterization, the fibers were embedded in a polymer. The resulting 1-3 composites were poled with constant electric field. Strain and polarization were measured by applying a bipolar sinusoidal voltage of high amplitude. Instead of the expected shifted butterfly-shaped strain hysteresis, an asymmetric strain-field relation was observed. It is characterized by a rather linear region in direction of the poling field and an inflated region without strain switching for reversed polarity. Within the temperature range from room temperature to 80degC, the strain switching seems to be suppressed. Measurements of the piezoelectric coefficient at superimposed electric field prove the blocking of strain switching. Cyclation experiments with sesquipolar load show a pronounced linearity of the strain loops that declines after more than 2 times 104 cycles.
Surface/bulk micromachined single-crystalline-silicon micro-gyroscope

A single-crystalline-silicon micro-gyroscope is fabricated in a single wafer using the recently developed surface/bulk micromachining (SBM) process. The SBM technology combined with deep silicon reactive ion etching allows fabricating accurately defined single-crystalline-silicon high-aspect-ratio structures with large sacrificial gaps, in a single wafer. The structural thickness of the fabricated micro-gyroscope is 40 /spl mu/m, and the sacrificial gap is 50 /spl mu/m. For electrostatic actuation and capacitive sensing of the developed gyroscope, a new isolation method which uses sandwiched oxide, polysilicon, and metal films, is developed in this paper. This triple-layer isolation method utilizes the excellent step coverage of low-pressure chemical vapor deposition polysilicon films, and thus, this new isolation method is well suited for high-aspect-ratio structures. The thickness of the additional films allows controlling and fine tuning the stiffness properties of underetched beams, as well as the capacitance between electrodes. The noise-equivalent angular-rate resolution of the SBM-fabricated gyroscope is 0.01/spl deg//s, and the bandwidth is 16.2 Hz. The output is linear to within 8% for a /spl plusmn/20/spl deg//s range. Work is currently underway to improve these performance specifications.
The Impact of Immigration on the Labour Market Outcomes of New Zealanders

This paper uses data from the 1996, 2001 and 2006 New Zealand Census to examine how the supply of immigrants in particular skill-groups affects the employment and wages of the New Zealand-born and of earlier migrants. We first estimate simple CES production functions that allow for substitutability between workers from different skill-groups, but assume that, within skill-groups, migrants are perfect substitutes for non-migrants. We next estimate hierarchical CES production functions that allow for substitutability between immigrant and non-immigrant workers within skillgroups, but constrain the patterns of wage impacts on different factors in response to changing factor shares, and that natives and migrants are not substitutable across skill-groups. Then, we extend the previous literature by estimating a Generalised Leontief production function that allows for a less restrictive relationship between changes in factors shares and changes in wages within a particular level of the production function and for substitution and complementarity between immigrant and nonimmigrant workers both between and across skill-groups. Regardless of the model being estimated, we find little evidence that immigrants negatively affect either the wages or employment opportunities of the average New Zealand-born worker. However, we find some evidence that increases in the number of high-skilled recent migrants have small negative impacts on the wages of high-skilled New Zealand-born workers, which are offset by small positive impacts on the wages of medium-skilled New Zealanders.
Atlas Generation for Subcortical and Ventricular Structures With Its Applications in Shape Analysis

Atlas-driven morphometric analysis has received great attention for studying anatomical shape variation across clinical populations in neuroimaging research as it provides a local coordinate representation for understanding the family of anatomic observations. We present a procedure for generating atlas of subcortical and ventricular structures, including amygdala, hippocampus, caudate, putamen, globus pallidus, thalamus, and lateral ventricles, using the large deformation diffeomorphic metric atlas generation algorithm. The atlas was built based on manually labeled volumes of 41 subjects randomly selected from the database of Open Access Series of Imaging Studies (OASIS, 10 young adults, 10 middle-age adults, 10 healthy elders, and 11 patients with dementia). We show that the estimated atlas is representative of the population in terms of its metric distance to each individual subject in the population. In the application of detecting shape variations, using the estimated atlas may potentially increase statistical power in identifying group shape difference when comparing with using a single subject atlas. In shape-based classification, the metric distances between subjects and each of within-class estimated atlases construct a shape feature space, which allows for performing a variety of classification algorithms to distinguish anatomies.
DOA Estimation Based on Compressive Sensing Method in Micro Underwater Location Platform

Based on a space sparse representation of underwater target, and combining compressed sensing sparse reconstruction principle, we present a new high-accuracy DOA estimation method. The proposed method can be used in narrowband and wideband scenarios. We demonstrate the effectiveness of the proposed method on simulated data by plots of spatial spectra, computation time and root mean square error. We observe that our approach has number of advantages over other DOA estimation methods including decreasing the calculated quantity, and the use of feasibil ity and superiority in the micro underwater location platform, as well as not requiring high demand of array.
Relevance vector machines with empirical likelihood-ratio kernels for PLDA speaker verification

Previous works have shown the benefits of empirical likelihood ratio (LR) kernels for i-vector/PLDA speaker verification. The method not only utilizes the multiple enrollment utterances of target speakers effectively, but also opens up opportunity for adopting sparse kernel machines for PLDA-based speaker verification systems. This paper proposes taking the advantages of the empirical LR kernels by incorporating them into relevance vector machines (RVMs). Results on NIST 2012 SRE demonstrate that the performance of RVM regression equipped with empirical LR kernels is slightly better than that of the support vector machines after performing utterance partitioning.
RGEM: A Responsive GPGPU Execution Model for Runtime Engines

General-purpose computing on graphics processing units, also known as GPGPU, is a burgeoning technique to enhance the computation of parallel programs. Applying this technique to real-time applications, however, requires additional support for timeliness of execution. In particular, the non-preemptive nature of GPGPU, associated with copying data to/from the device memory and launching code onto the device, needs to be managed in a timely manner. In this paper, we present a responsive GPGPU execution model (RGEM), which is a user-space runtime solution to protect the response times of high-priority GPGPU tasks from competing workload. RGEM splits a memory-copy transaction into multiple chunks so that preemption points appear at chunk boundaries. It also ensures that only the highest-priority GPGPU task launches code onto the device at any given time, to avoid performance interference caused by concurrent launches. A prototype implementation of an RGEM-based CUDA runtime engine is provided to evaluate the real-world impact of RGEM. Our experiments demonstrate that the response times of high-priority GPGPU tasks can be protected under RGEM, whereas their response times increase in an unbounded fashion without RGEM support, as the data sizes of competing workload increase.
CAPS: A Tool for Architecting Situational-Aware Cyber-Physical Systems

Situational Aware (SiA) Cyber-physical systems(CPS) harmoniously integrate computational and physicalcomponents to being aware of what is happening in the surroundings, and using this information to decide and act. In thistool demo, we present our architecture-driven modeling toolnamed CAPS. This tool enables architects, system engineers, and cyber-physical space designers to describe the softwarearchitecture, hardware configuration, and physical space viewsfor a situational aware CPS, respectively.
A meta-learning system based on genetic algorithms

The design of an efficient machine learning process through self-adaptation is a great challenge. The goal of meta-learning is to build a self-adaptive learning system that is constantly adapting to its specific (and dynamic) environment. To that end, the meta-learning mechanism must improve its bias dynamically by updating the current learning strategy in accordance with its available experiences or meta-knowledge. We suggest using genetic algorithms as the basis of an adaptive system. In this work, we propose a meta-learning system based on a combination of the a priori and a posteriori concepts. A priori refers to input information and knowledge available at the beginning in order to built and evolve one or more sets of parameters by exploiting the context of the system’s information. The self-learning component is based on genetic algorithms and neural Darwinism. A posteriori refers to the implicit knowledge discovered by estimation of the future states of parameters and is also applied to the finding of optimal parameters values. The in-progress research presented here suggests a framework for the discovery of knowledge that can support human experts in their intelligence information assessment tasks. The conclusion presents avenues for further research in genetic algorithms and their capability to learn to learn.
International Union of Pharmacology. XXVII. Classification of Cannabinoid Receptors

Two types of cannabinoid receptor have been discovered so far, CB1 (2.1: CBD:1:CB1:), cloned in 1990, and CB2(2.1:CBD:2:CB2:), cloned in 1993. Distinction between these receptors is based on differences in their predicted amino acid sequence, signaling mechanisms, tissue distribution, and sensitivity to certain potent agonists and antagonists that show marked selectivity for one or the other receptor type. Cannabinoid receptors CB1 and CB2 exhibit 48% amino acid sequence identity. Both receptor types are coupled through G proteins to adenylyl cyclase and mitogen-activated protein kinase. CB1 receptors are also coupled through G proteins to several types of calcium and potassium channels. These receptors exist primarily on central and peripheral neurons, one of their functions being to inhibit neurotransmitter release. Indeed, endogenous CB1 agonists probably serve as retrograde synaptic messengers. CB2 receptors are present mainly on immune cells. Such cells also express CB1receptors, albeit to a lesser extent, with both receptor types exerting a broad spectrum of immune effects that includes modulation of cytokine release. Of several endogenous agonists for cannabinoid receptors identified thus far, the most notable are arachidonoylethanolamide, 2-arachidonoylglycerol, and 2-arachidonylglyceryl ether. It is unclear whether these eicosanoid molecules are the only, or primary, endogenous agonists. Hence, we consider it premature to rename cannabinoid receptors after an endogenous agonist as is recommended by the International Union of Pharmacology Committee on Receptor Nomenclature and Drug Classification. Although pharmacological evidence for the existence of additional types of cannabinoid receptor is emerging, other kinds of supporting evidence are still lacking.
Evaluation of multicast routing algorithms for distributed real-time applications

Multicast (MC) routing algorithms capable of satisfying the QoS requirements of real-time applications will be essential for future high-speed networks. We compare the performance of all of the important MC routing algorithms when applied to networks with asymmetric link loads. Each algorithm is judged based on the quality of the MC tree it generates and its efficiency in managing the network resources. Simulation results over random networks show that unconstrained algorithms are not capable of fulfilling the QoS requirements of real-time applications in large networks. One algorithm, reverse path multicasting, is not suitable for asymmetric networks irrespective of the requirements of the application. All constrained Steiner tree (CST) heuristics reported to date are also studied. Simulations show that all three heuristics behave similarly and that they can manage the network efficiently and construct low cost MC trees that satisfy the QoS requirements of real-time traffic. The execution times of the CST heuristics are larger than those of the unconstrained algorithms.
A location-aware embedding technique for accurate landmark recognition

The current state of the research in landmark recognition highlights the good accuracy which can be achieved by embedding techniques, such as Fisher vector and VLAD. All these techniques do not exploit spatial information, i.e. consider all the features and the corresponding descriptors without embedding their location in the image. This paper presents a new variant of the well-known VLAD (Vector of Locally Aggregated Descriptors) embedding technique which accounts, at a certain degree, for the location of features. The driving motivation comes from the observation that, usually, the most interesting part of an image (e.g., the landmark to be recognized) is almost at the center of the image, while the features at the borders are irrelevant features which do no depend on the landmark. The proposed variant, called locVLAD (location-aware VLAD), computes the mean of the two global descriptors: the VLAD executed on the entire original image, and the one computed on a cropped image which removes a certain percentage of the image borders. This simple variant shows an accuracy greater than the existing state-of-the-art approach. Experiments are conducted on two public datasets (ZuBuD and Holidays) which are used both for training and testing. Morever a more balanced version of ZuBuD is proposed.
Paclitaxel-Fe3O4 nanoparticles inhibit growth of CD138− CD34− tumor stem-like cells in multiple myeloma-bearing mice

Background There is growing evidence that CD138− CD34− cells may actually be tumor stem cells responsible for initiation and relapse of multiple myeloma. However, effective drugs targeted at CD138− CD34− tumor stem cells are yet to be developed. The purpose of this study was to investigate the inhibitory effect of paclitaxel-loaded Fe3O4 nanoparticles (PTX-NPs) on CD138− CD34− tumor stem cells in multiple myeloma-bearing mice. Methods CD138− CD34− cells were isolated from a human U266 multiple myeloma cell line using an immune magnetic bead sorting method and then subcutaneously injected into mice with nonobese diabetic/severe combined immunodeficiency to develop a multiple myeloma-bearing mouse model. The mice were treated with Fe3O4 nanoparticles 2 mg/kg, paclitaxel 4.8 mg/kg, and PTX-NPs 0.64 mg/kg for 2 weeks. Tumor growth, pathological changes, serum and urinary interleukin-6 levels, and molecular expression of caspase-3, caspase-8, and caspase-9 were evaluated. Results CD138− CD34− cells were found to have tumor stem cell characteristics. All the mice developed tumors in 40 days after injection of 1 × 106 CD138− CD34− tumor stem cells. Tumor growth in mice treated with PTX-NPs was significantly inhibited compared with the controls (P < 0.005), and the groups that received nanoparticles alone (P < 0.005) or paclitaxel alone (P < 0.05). In addition, the PTX-NPs markedly inhibited interleukin-6 secretion, increased caspase-8, caspase-9, and caspase-3 expression, and induced apoptosis of tumor cells in the treated mice. Conclusion PTX-NPs proved to be a potent anticancer treatment strategy that may contribute to targeted therapy for multiple myeloma tumor stem cells in future clinical trials.
MVP: Minimum-Violations Partitioning for Reducing Capture Power in At-Speed Delay-Fault Testing

Scan shift power can be reduced by activating only a subset of scan cells in each shift cycle. In contrast to shift power reduction, the use of only a subset of scan cells to capture responses in a cycle may cause capture violations, thereby leading to fault coverage loss. In order to restore the original fault coverage, new test patterns must be generated, leading to higher test-data volume. In this paper, we propose minimum-violations partitioning, a scan-cell clustering method that can support multiple capture cycles in delay testing without increasing test-data volume. This method is based on an integer linear programming model and it can cluster the scan flip-flops into balanced parts with minimum capture violations. Based on this approach, hierarchical partitioning is proposed to make the partitioning method routing-aware. Experimental results on ISCAS'89 and IWLS'05 benchmark circuits demonstrate the effectiveness of our method.