Miracle-dz/UniFAR-FTUs huggingface dataset:
Indices of Cardiovascular Function Derived from Peripheral Pulse Wave Analysis Using Radial Applanation Tonometry in HIV Positive Patients from Mthatha District of South Africa

Background: HIV patients are suspected to have increased arterial stiffness which may contribute to a higher risk of coronary atherosclerosis. Invasive techniques are of limited value, hence in this study, the use on a noninvasive method was applied. The objective of the study was to see if there is increased arterial stiffness in HIV patients using applanation tonometry of the radial artery, consequently leading to cardiac dysfunction resulting in myocardial ischemia. Methods: 169 participants took part in the study between December 2012 and June 2013. There were 63 HIV positive participants, 52 HIV negative participants, and 54 HIV treatment naive participants. Augmentation index (AIx (75), Ejection duration index (ED%) and sub-endocardial variability ratio (SEVR) and other parameters of interest were measured using arterial wave reflection in these participants. Results: SEVR was highest in the HIV negative participants and lowest in HAART naive HIV participants (p<0.001). In both groups, the HIV positive participants had significant arterial stiffness compared to HIV negative participants (p=0.024). The HIV positive participants also had higher ejection duration index (ED %) with the highest values being observed in those that were not on treatment (p<0.001). Both SEVR and ED% had negative correlation with HR using Pearson's correlation and Stepwise Linear regression p<0.001. There was no significant correlation with age p=0.143. No significant differences in both the systolic and diastolic blood pressures between the three groups were observed, although heart rate was lower in the HIV negatives participants. Conclusion: HIV patients are prone to having systolic dysfunction which may lead to myocardial ischemia.
Comparison of Segmentation Methods for Cytometric Assay

In this paper we compare two segmentation techniques, a parameter-free variant of the watershed algorithm and a new robust method based on adaptive contours. To test them, we use a set of fluorescence in-situ hybridisation images of leucocyte nuclei: these images were obtained in realistic conditions of mass screening, and do not meet the prerequisites of usual segmentation methods. We present the two methods and describe them step by step. We then compare the results of the segmentation of the test images, showing over a hundred nuclei, and detail the incorrect segmentations. The contour-based method outperforms the watershed as regards correct segmentations and over-segmentations, but performs more under-segmentations. We analyse the origins of the incorrect segmentations from the two methods, and discuss possible improvements.
Regulation of cAMP‐specific phosphodiesterases type 4B and 4D (PDE4) splice variants by cAMP signaling in primary cortical neurons

This study examined the regulation of all known phosphodiesterase (PDE) type PDE4A, PDE4B and PDE4D splice variants in cortical neurons by cAMP signaling. Treatment with dibutyryl‐cAMP (db‐cAMP) caused the induction of two of the known splice variants, PDE4B2 and PDE4D1/PDE4D2. Although the splice variants PDE4A1, PDE4A5/PDE4A10, PDE4B3, PDE4B1, PDE4D3 and PDE4D4 were present in cortical neurons, their mRNA was not regulated at the transcriptional level by db‐cAMP. To assess the increase in PDE4B2 and PDE4D1/D2 mRNA expression, the promoters containing these genes were characterized. Transcription from both promoters was stimulated by db‐cAMP. Because chronic antidepressant treatment increases PDE4B, and not PDE4D, mRNA expression, we focused on the regulation of the PDE4B2 promoter by cAMP and CREB. Dominant negative mutants of CREB suppressed PDE4B2 promoter activity and a constitutively active form of CREB robustly stimulated it. These data demonstrate that in cortical neurons, a short PDE4B2 intronic promoter is regulated by CREB, confers cAMP responsitivity and directs PDE4B2 mRNA and protein expression.
Posterior Simulation in Countable Mixture Models for Large Datasets

Mixture models, or convex combinations of a countable number of probability distributions, offer an elegant framework for inference when the population of interest can be subdivided into latent clusters having random characteristics that are heterogeneous between, but homogeneous within, the clusters. Traditionally, the different kinds of mixture models have been motivated and analyzed from very different perspectives, and their common characteristics have not been fully appreciated. The inferential techniques developed for these models usually necessitate heavy computational burdens that make them difficult, if not impossible, to apply to the massive data sets increasingly encountered in real world studies. This paper introduces a flexible class of models called generalized Pólya urn (GPU) processes. Many common mixture models, including finite mixtures, hidden Markov models, and Dirichlet processes, are obtained as special cases of GPU processes. Other important special cases include finite-dimensional Dirichlet priors, infinite hidden Markov models, analysis of densities models, nested Chinese restaurant processes, hierarchical DP models, nonparametric density models, spatial Dirichlet processes, weighted mixtures of DP priors, and nested Dirichlet processes. An investigation of the theoretical properties of GPU processes offers new insight into asymptotics that form the basis of cost-effective Markov chain Monte Carlo (MCMC) strategies for large datasets. These MCMC techniques have the advantage of providing inferences from the posterior of interest, rather than an approximation, and are applicable to different mixture models. The versatility and impressive gains of the methodology are demonstrated by simulation studies and by a semiparametric Bayesian analysis of high-resolution comparative genomic hybridization data on lung cancer. The appendixes are available online as supplemental material.
Estimation of the Rate of Cloned Gene Integration via Retrotransposition

A theoretical method has been developed to estimate retrotransposition (integration) rates of the Saccharomyces cerevisiae Ty3 and Ty1 retrotransposons bearing heterologous and homologous genes (neor, HIS3) . The method is based on population growth modeling and Lea and Coulson's maximal likelihood method for mutation rate estimation (Lea and Coulson, 1949 ) . This method has allowed us to examine directly retrotransposition rates of GAL‐regulated marked Ty3 and Ty1 elements into the whole yeast genome, not just a particular DNA sequence, for the purpose of cloned gene integration. The integration rates of a Ty3‐neor system (ca. 1 × 10−3 cell−1 generation−1) and a Ty1‐neor system (ca. (2–3) × 10−3 cell−1 generation−1) were not significantly affected by temperature (18 and 30 °C) . However, the retrotransposition rate of the Ty3‐neor‐HIS3 system increased from ca. 2 × 10−5 to 2 × 10−4 cell−1 generation−1 when the temperature was decreased from 30 to 18 °C. The retrotransposition rate of Ty3‐neor was significantly higher than that of Ty3‐neor‐HIS3 and slightly lower than that of Ty1‐neor. This method can be used to estimate integration rates of other Ty3 and Ty1 elements and to evaluate the efficiency of Ty‐mediated cloned gene integration.
Challenging the great vascular wall: Can we envision a simple yet comprehensive therapy for stroke?

Stroke is a leading cause of death in adult life, closely behind ischemic heart disease, and causes a significant and abiding socioeconomic burden. However, current therapies are not able to ensure full neurologic and/or sequelae‐free recovery to all stroke survivors. We believe treatment efficacy and patient rehabilitation could be enhanced significantly by targeting blood‐brain barrier (BBB) deregulation and inflammation‐induced barrier loss that occurs after stroke. In this pathological context, bone marrow‐derived endothelial progenitor cells (EPC) enter the bloodstream towards the lesion site, but their insufficient numbers and impaired angiogenic ability compromise neurovascular regeneration. In this context, cell‐based therapies have become increasingly appealing since treating patients with large numbers of mesenchymal or hematopoietic stem/progenitor cells alone may boost repair. However, this approach could be met with several challenges in terms of logistics and cost; hence, the development of a drug delivery system suitable for intravenous administration and functionalized for selective uptake by circulating EPC could enhance their restorative potential without perceived complications. The ability to encapsulate proangiogenic and anti‐inflammatory agents, such as retinoic acid, and to safely and easily deliver them systemically may open new therapeutic perspectives for the treatment of cerebrovascular disorders. Copyright © 2017 John Wiley & Sons, Ltd.
A Review of EEG-Based Brain-Computer Interfaces as Access Pathways for Individuals with Severe Disabilities

Electroencephalography (EEG) is a non-invasive method for measuring brain activity and is a strong candidate for brain-computer interface (BCI) development. While BCIs can be used as a means of communication for individuals with severe disabilities, the majority of existing studies have reported BCI evaluations by able-bodied individuals. Considering the many differences in body functions and usage scenarios between individuals with disabilities and able-bodied individuals, involvement of the target population in BCI evaluation is necessary. In this review, 39 studies reporting EEG-oriented BCI assessment by individuals with disabilities were identified in the past decade. With respect to participant populations, a need for assessing BCI performance for the pediatric population with severe disabilities was identified as an important future direction. Acquiring a reliable communication pathway during early stages of development is crucial in avoiding learned helplessness in pediatric-onset disabilities. With respect to evaluation, augmenting traditional measures of system performance with those relating to contextual factors was recommended for realizing user-centered designs appropriate for integration in real-life. Considering indicators of user state and developing more effective training paradigms are recommended for future studies of BCI involving individuals with disabilities.
Two-Tier VoI Prioritization System on Requirement-Based Data Streaming toward IoT

Toward the world of Internet of Things, people utilize knowledge from sensor streams in various kinds of smart applications. The number of sensing devices is rapidly increasing along with the amount of sensing data. Consequently, a bottleneck problem at the local gateway has attracted high concern. An example scenario is smart elderly houses in rural areas where each house installs thousands of sensors and all connect to resource-limited and unstable 2G/3G networks. The bottleneck state can incur unacceptable latency and loss of significant data due to the limited waiting-queue. Orthogonally to the existing solutions, we propose a two-tier prioritization system to enhance information quality, indicated by VoI, at the local gateway. The proposed system has been designed to support several requirements with several conflicting criteria over shared sensing streams. Our approach adopts Multicriteria Decision Analysis technique to merge requirements and to assess the VoI. We introduce the framework that can reduce the computational cost by precalculation. Through a case study of building management systems, we have shown that our merge algorithm can provide 0.995 cosine-similarity for representing all user requirements and the evaluation approach can obtain satisfaction values around 3 times higher than the naive strategies for the top-list data.
Comment on “ApoE-Directed Therapeutics Rapidly Clear β-Amyloid and Reverse Deficits in AD Mouse Models”

Cramer et al. (Reports, 23 March 2012, p. 1503; published online 9 February 2012) demonstrates short-term bexarotene treatment clearing preexisting β-amyloid deposits from the brains of APP/PS1ΔE9 mice with low amyloid burden, providing a rationale for repurposing this anticancer agent as an Alzheimer’s disease (AD) therapeutic. Using a nearly identical treatment regimen, we were unable to detect any evidence of drug efficacy despite demonstration of target engagement.
Increased Rates of Fatty Acid Uptake and Plasmalemmal Fatty Acid Transporters in Obese Zucker Rats*

Giant vesicles were used to study the rates of uptake of long-chain fatty acids by heart, skeletal muscle, and adipose tissue of obese and lean Zucker rats. With obesity there was an increase in vesicular fatty acid uptake of 1.8-fold in heart, muscle and adipose tissue. In some tissues only fatty acid translocase (FAT) mRNA (heart, +37%; adipose, +80%) and fatty acid-binding protein (FABPpm) mRNA (heart, +148%; adipose, +196%) were increased. At the protein level FABPpm expression was not changed in any tissues except muscle (+14%), and FAT/CD36 protein content was altered slightly in adipose tissue (+26%). In marked contrast, the plasma membrane FAT/CD36 protein was increased in heart (+60%), muscle (+80%), and adipose tissue (+50%). The plasma membrane FABPpm was altered only in heart (+50%) and adipose tissues (+70%). Thus, in obesity, alterations in fatty acid transport in metabolically important tissues are not associated with changes in fatty acid transporter mRNAs or altered fatty acid transport protein expression but with their increased abundance at the plasma membrane. We speculate that in obesity fatty acid transporters are relocated from an intracellular pool to the plasma membrane in heart, muscle, and adipose tissues.
An antisense oligodeoxynucleotide targeted to chromaffin cell scinderin gene decreased scinderin levels and inhibited depolarization‐induced cortical F‐actin disassembly and exocytosis

Chromaffin cell secretion requires cortical F‐actin disassembly and it has been suggested that scinderin, a Ca2+‐dependent F‐actin severing protein, controls cortical actin dynamics. An antisense oligodeoxynucleotide targeting the scinderin gene was used to decrease the expression of the protein and access its role in secretion. Treatment with 2 µm scinderin antisense oligodeoxynucleotide for 4 days produced a significant decrease in scinderin expression and its mRNA levels. The expression of gelsolin, another F‐actin severing protein, was not affected. Scinderin decrease was accompanied by concomitant and parallel decreases in depolarization‐evoked cortical F‐actin disassembly and exocytosis. Similar treatment with a mismatched oligodeoxynucleotide produced no effects. Scinderin antisense oligodeoxynucleotide treatment was also a very effective inhibitor of exocytosis in digitonin‐permeabilized cells stimulated with increasing concentrations of Ca2+. This ruled out scinderin antisense interference with stimulation‐induced depolarization or Ca2+ channel activation. Scinderin antisense treatment decreased the maximum (Bmax) secretory response to Ca2+ without modifying the affinity (Km) of the cation for the exocytotic machinery. Moreover, the antisense treatment did not affect norepinephrine uptake or the expression of dopamine β‐hydroxylase, suggesting that the number and function of chromaffin vesicles was not modified. In addition, scinderin antisense treatment did not alter the expression of proteins involved in vesicle–plasma membrane fusion, such as synaptophysin, synaptotagmin or syntaxin, indicating a lack of effects on the fusion machinery components. These observations strongly suggest that scinderin is a key player in the events involved in the secretory process.
Time dependent variance-based sensitivity analysis of development aggregation generated by heterogeneous land use agents

Agent-based models have been recognized as computational laboratories furnishing spatial scientists with a plausible exploratory apparatus for learning about land use dynamics through an explicit representation of human behavior. At the same time research suggests that the utility of agent-based modeling has been hampered by a limited understanding of the decision processes involving a wide array of stakeholders with different perceptions and preferences. Therefore, it is critically important to offer new tools for a more comprehensive inspection of uncertainties related to the interrelationships between individual choices and land development patterns. In this paper, we propose a new approach to evaluating agent behavioral uncertainty using time dependent variance-based global sensitivity analysis. The method produces time series of first order sensitivity indices that allocate the variance of development patterning to two heterogeneous behavioral features: risk perceptions, quantified through attitude utility functions, and land preferences, in the form of weights assigned to different decision criteria. We experiment with three ABM scenarios that emphasize the various decision components. The scenarios utilize a fixed number of parameters with changing distributions reflecting the behavioral characteristic under consideration. Outcome maps for each time step are summarized using the aggregation index, which is further employed in sensitivity computation. The resulting sensitivity indices are plotted against time to track the impact of input conditions on land use compactness. The comparisons of the plots reveal varying sensitivity trajectories that depend on the modified decision rule.
Textured voxels based method for display speed up

We present a novel method for the simplification of three-dimensional objects in order to optimise display. This is an incremental method with a specific feature: the processed scenes are simultaneously shown with two degrees of detail - precise and coarse. This allows for the creation of different types of simplification and adapts the geometrical and photometrical representation of the objects and scenes to precision and speed requirements. Voxels and textures are used in this method and it works with all kinds of object modelling. This method is based on the idea that in order to effectively reduce the volume of information to be processed while providing accurate rendering and fast display, we have to concentrate on the less visible pans of objects.
Pittsburgh Compound-B and Alzheimer’s Disease Biomarkers in CSF, Plasma and Urine: An Exploratory Study

Background: The positron emission tomography (PET) radiotracer Pittsburgh Compound-B (PIB) is an in vivo ligand for measuring β-amyloid (Aβ) load. Associations between PET PIB and cerebrospinal fluid (CSF) Aβ1–42 and apolipoprotein E Ε4 (APOE Ε4) have been observed in several studies, but the relations between PIB uptake and other biomarkers of Alzheimer’s disease (AD) are less investigated. Method: PET PIB, PET 18Fluoro-2-deoxy-D-glucose and different AD biomarkers were measured twice in CSF, plasma and urine 12 months apart in 10 patients with a clinical diagnosis of mild to moderate AD. Results: PIB retention was constant over 1 year, inversely related to low CSF Aβ1–42 (p = 0.01) and correlated positively to the numbers of the APOE Ε4 allele (0, 1 or 2) (p = 0.02). There was a relation between mean PIB retention and CSF ApoE protein (r = –0.59, p = 0.07), and plasma cystatin C (r = –0.56, p = 0.09). Conclusion: PIB retention is strongly related to CSF Aβ1–42, and to the numbers of the APOE Ε4 allele.
Identification of the Multiple ,B-Thalassemia Mutations by Denaturing Gradient Gel Electrophoresis

We used denaturing gradient gel electrophoresis to detect the fl-thalassemia mutations in the Chinese population. By amplifying the 0Bglobin gene in four separate fragments and electro-phoresing the amplified DNA in two gels, we were able to distinguish all the 12 known mutations on the basis of the mobility of the homoduplexes and heteroduplexes. We con-clude that denaturing gradient gel electrophoresis offers a nonradioactive means of detecting multiple mutations in genetic disorders. (J. Clin. Invest. 1990. 85:550-553.)
New identity-based key-encapsulation mechanism and its applications in cloud computing

Identity-based encryption IBE is an important primitive of identity-based cryptography. As such, it is a type of public-key encryption in which the public key of a user is some unique information about the identity of the user e.g., a user's e-mail address. As a special form of IBE, identity-based key encapsulation mechanism IB-KEM can be used to create a random session key for encrypting messages. Any IB-KEM can be updated to a full IBE scheme by adding a symmetric encryption scheme with appropriate security properties. Currently, IB-KEM is a fundamental primitive of cryptography, and can be used to protect information system security, network security, cloud security, etc. In this paper, we construct a new IB-KEM in a generic levelled multilinear map setting and prove its security under multilinear decisional Diffie-Hellman assumption in the selective-ID model. Then, we make our IB-KEM translated to the GGH framework, which is proposed by Garg et al. 2013a. This framework defines an approximate version of a multilinear group family from ideal lattices. Finally, as an application of our new scheme, we introduce how to achieve secure transmission in the hierarchical architecture for cloud computing HACC.
Cuttlefish : A Library For Building Elastic Distributed Neural Networks

This paper will discuss the implementation of Cuttlefish, a library for building configurable, fault tolerant, elastic, distributed neural networks. Cuttlefish is built on top of the Distributed TensorFlow library. It uses Docker containers to represent units or neurons in the a neural network. More specifically each container (neuron) will run as a service that can communicate with other neurons in the network. Our neural network will be a n layered network, implemented and configured to run on Amazon Web Service’s Elastic Container Service (ECS).
Towards Conversational Speech Recognition for Scheduling Agents on Wearable Computers

Mobile speech interfaces that are socially acceptable and technically feasible are difficult to design. This paper presents a first step in exploring conversational interfaces that use socially applicable speech to cue an appointment scheduling agent on a wearable computing platform. We present a user study of current appointment scheduling mechanisms which reveals a relationship between the time required to access a device and the probability that the user will choose an alternative method of recording the appointment. In addition, the study demonstrates that many subjects postpone entering appointments into their calendar until after the end of the conversation. These results inform the design of two prototype systems: the Calendar Navigator Agent (CNA) and Dialog Tabs. The CNA monitors the user’s speech and displays calendar information on a head-up display as the conversation progresses. We show that such an interface has the potential to speed the appointment scheduling process significantly. Dialog Tabs attempts to minimize user distraction by buffering and indexing appointment conversations for later processing.