Miracle-dz/UniFAR-FTUs huggingface dataset:
Suppression of erythropoiesis by dietary nitrate

In mammals, hypoxia‐triggered erythropoietin release increases red blood cell mass to meet tissue oxygen demands. Using male Wistar rats, we unmask a previously unrecognized regulatory pathway of erythropoiesis involving suppressor control by the NO metabolite and ubiquitous dietary component nitrate. We find that circulating hemoglobin levels are modulated by nitrate at concentrations achievable by dietary intervention under normoxic and hypoxic conditions; a moderate dose of nitrate administered via the drinking water (7 mg NaNO3/kg body weight/d) lowered hemoglobin concentration and hematocrit after 6 d compared with nonsupplemented/NaCl‐supplemented controls. The underlying mechanism is suppression of hepatic erythropoietin expression associated with the downregulation of tissue hypoxia markers, suggesting increased pO2. At higher nitrate doses, however, a partial reversal of this effect occurred; this was accompanied by increased renal erythropoietin expression and stabilization of hypoxia‐inducible factors, likely brought about by the relative anemia. Thus, hepatic and renal hypoxia‐sensing pathways act in concert to modulate hemoglobin in response to nitrate, converging at an optimal minimal hemoglobin concentration appropriate to the environmental/physiologic situation. Suppression of hepatic erythropoietin expression by nitrate may thus act to decrease blood viscosity while matching oxygen supply to demand, whereas renal oxygen sensing could act as a brake, averting a potentially detrimental fall in hematocrit. —Ashmore, T. , Fernandez, B. O. , Evans, C. E. , Huang, Y. , Branco‐Price, C. , Griffin, J. L. , Johnson, R. S. , Feelisch, M. , Murray, A. J., Suppression of erythropoiesis by dietary nitrate. FASEB J. 29, 1102–1112 (2015). www.fasebj. org
A Diagnostic Model for Dementia in Clinical Practice—Case Methodology Assisting Dementia Diagnosis

Dementia diagnosis is important for many different reasons. Firstly, to separate dementia, or major neurocognitive disorder, from MCI (mild cognitive impairment), mild neurocognitive disorder. Secondly, to define the specific underlying brain disorder to aid treatment, prognosis and decisions regarding care needs and assistance. The diagnostic method of dementias is a puzzle of different data pieces to be fitted together in the best possible way to reach a clinical diagnosis. Using a modified case methodology concept, risk factors affecting cognitive reserve and symptoms constituting the basis of the brain damage hypothesis, can be visualized, balanced and reflected against test results as well as structural and biochemical markers. The model’s origin is the case method initially described in Harvard business school, here modified to serve dementia diagnostics.
An architecture for non-orthogonal multi-carrier faster-than-nyquist transmission

This paper considers a multicarrier faster-than-Nyquist (FTN) transceiver architecture when spectrally efficient frequency division multiplexing (SEFDM) is also utilized at the transmitter. The received symbols are corrupted by both the introduced inter-symbol interference (ISI) due to FTN and inter-carrier interference (ICI) due to SEFDM. The interferences have to be eliminated to recover the transmitted data at the receiver. We propose a receiver architecture using a specific matched filter architecture that yields uncorrelated noise samples at the receiver. We investigate the bit error rate (BER) performance of coded transmission when iterative (turbo) equalization is used. Finally, we also present EXIT curves and decoder trajectories for the simulated systems.
Scalable Semantics – The Silver Lining of Cloud Computing

Semantic inferencing and querying across large-scale RDF triple stores is notoriously slow. Our objective is to expedite this process by employing Google's MapReduce framework to implement scale-out distributed querying and reasoning. This approach requires RDF graphs to be decomposed into smaller units that are distributed across computational nodes. RDF Molecules appear to offer an ideal approach - providing an intermediate level of granularity between RDF graphs and triples. However, the original RDF molecule definition has inherent limitations that will adversely affect performance. In this paper, we propose a number of extensions to RDF molecules (hierarchy and ordering) to overcome these limitations. We then present some implementation details for our MapReduce-based RDF molecule store. Finally we evaluate the benefits of our approach in the context of the Bio-MANTA project - an application that requires integration and querying across large-scale protein-protein interaction datasets.
Self‐nucleation and recrystallization of isotactic polypropylene (α phase) investigated by differential scanning calorimetry

The crystallization behavior after partial or complete melting of the α phase of iPP is examined by combined differential scanning calorimetry (DSC) and optical microscopy: calorimetric results are directly correlated with corresponding morphologies of microtome sections of DSC samples. On partial melting at various temperatures (hereafter referred to as Ts) located in a narrow range (4°C) below and near Tm, the number of nuclei increases (as in classical self-nucleation experiments), by several orders of magnitude; on subsequent cooling, the crystallization peak is shifted by up to 25°C. After partial melting in the lower part of the Ts range and recrystallization, the polymers display a prominent morphology “memory effect” whereby a phantom pattern of the initial spherulite morphology is maintained. After partial melting in the upper part of the Ts range the initial morphology is erased and self-nucleation affects only the total number of nuclei. The present experimental procedures make it possible to define, under “standard” conditions, the crystallization range of the polymer and in particular, the maximum crystallization temperature achievable when “ideally” nucleated. © John Wiley & Sons, Inc.
Energy and carbon efficient VM placement and migration technique for green cloud datacenters

One of the most popular emerging technologies in today's world is Cloud Computing and it is being used widely all over the world by many IT companies as it provides various benefits to the users like cost saving and ease of use. But with the growing demands of users for computing services, cloud providers are encouraged to deploy large data centers which consume very large amount of energy and contribute to high operational costs. Carbon dioxide emission rate is also increasing day by day due to huge amount of power consumption. Therefore, we require to develop techniques which will help to get more environment friendly computing i.e. Green Cloud Computing. Some of the techniques being used in cloud data centers for reducing the operational costs, power consumption and CO2 emission are resource allocation, virtualization and VM migrations. In this paper, we propose a new technique to reduce the carbon emission and energy consumption in the distributed cloud datacenters having different energy sources and carbon footprint rates. Our approach uses the carbon footprints of all the datacenters in distributed cloud architecture and the concept of virtual machine allocation and migration inside each datacenter for reducing the carbon emission and energy consumption in the federated cloud system.
Author ' s personal copy Optimal measurement combinations as controlled variables

This paper deals with the optimal selection of linear measurement combinations as controlled variables, c 1⁄4 Hy. The objective is to achieve ‘‘self-optimizing control”, which is when fixing the controlled variables c indirectly gives near-optimal steady-state operation with a small loss. The nullspace method of Alstad and Skogestad [V. Alstad, S. Skogestad, Null space method for selecting optimal measurement combinations as controlled variables, Ind. Eng. Chem. Res. 46 (3) (2007) 846–853] focuses on minimizing the loss caused by disturbances. We here provide an explicit expression for H for the case where the objective is to minimize the combined loss for disturbances and measurement errors. In addition, we extend the nullspace method to cases with extra measurements by using the extra degrees of freedom to minimize the loss caused by measurement errors. Finally, the results are interpreted more generally as deriving linear invariants for quadratic optimization problems. 2008 Elsevier Ltd. All rights reserved.
Mutation analysis in Norwegian families with hereditary hemorrhagic telangiectasia: founder mutations in ACVRL1

Hereditary hemorrhagic telangiectasia (HHT, Osler–Weber–Rendu disease) is an autosomal dominant inherited disease defined by the presence of epistaxis and mucocutaneous telangiectasias and arteriovenous malformations (AVMs) in internal organs. In most families (∼85%), HHT is caused by mutations in the ENG (HHT1) or the ACVRL1 (HHT2) genes. Here, we report the results of genetic testing of 113 Norwegian families with suspected or definite HHT. Variants in ENG and ACVRL1 were found in 105 families (42 ENG, 63 ACVRL1), including six novel variants of uncertain pathogenic significance. Mutation types were similar to previous reports with more missense variants in ACVRL1 and more nonsense, frameshift and splice‐site mutations in ENG. Thirty‐two variants were novel in this study. The preponderance of ACVRL1 mutations was due to founder mutations, specifically, c.830C>A (p.Thr277Lys), which was found in 24 families from the same geographical area of Norway. We discuss the importance of founder mutations and present a thorough evaluation of missense and splice‐site variants.
Design and Implementation of a Large Scale Tree-Based QR Decomposition Using a 3D Virtual Systolic Array and a Lightweight Runtime

A systolic array provides an alternative computing paradigm to the von Neuman architecture. Though its hardware implementation has failed as a paradigm to design integrated circuits in the past, we are now discovering that the systolic array as a software virtualization layer can lead to an extremely scalable execution paradigm. To demonstrate this scalability, in this paper, we design and implement a 3D virtual systolic array to compute a tile QR decomposition of a tall-and-skinny dense matrix. Our implementation is based on a state-of-the-art algorithm that factorizes a panel based on a tree-reduction. Using a runtime developed as a part of the Parallel Ultra Light Systolic Array Runtime (PULSAR) project, we demonstrate on a Cray-XT5 machine how our virtual systolic array can be mapped to a large-scale machine and obtain excellent parallel performance. This is an important contribution since such a QR decomposition is used, for example, to compute a least squares solution of an overdetermined system, which arises in many scientific and engineering problems.
Quantifying the Effect of Applying the NCEP ATP III Criteria in a Managed Care Population Treated With Statin Therapy

OBJECTIVES: Revised treatment goals suggested by the third report of the National Cholesterol Education Program (NCEP) Adult Treatment Panel (ATP III) represent a challenge to both physicians and the health care industry. We sought to quantify the impact of these changes in a large managed care population being treated with statin therapy. METHODS: Using data collected from a retrospective chart review of 1,962 managed care enrollees who received statin drug therapy between February 2001 and August 2001, we quantified the low-density lipoprotein cholesterol (LDL-C) goals and goal attainment of this population according to both the NCEP ATP II and ATP III criteria and further identified independent predictors of ATP III goal attainment using multivariable logistic regression modeling. RESULTS: Overall, 21.1% (n = 414) of statin patients moved to a more stringent LDL-C goal when ATP III criteria were applied over ATP II. Substituting ATP III criteria for ATP II criteria resulted in a 6.8% decrease in the percentage of participants who had their most recent LDL-C value below the suggested goal, from 59.8% under ATP II to 53.0% under ATP III. Persons with existing coronary heart disease, diabetes, obesity, and stroke or transient ischemic attack were all less likely to meet the suggested NCEP ATP III LDL-C goal. CONCLUSIONS: Taking into account the revised risk stratification of the ATP III guidelines and the lack of LDL-C goal attainment in patients currently taking statins, there will be an increase in the number of statin patients who require dose or agent adjustment, combination therapy, or compliance counseling to achieve their lower LDL-C goal.
Classification of Lung Regions using Morphometrics for Chest CT Scans

Medical diagnosis is extremely important but complicated task that should be performed accurately and efficiently. Disease diagnosis is one of the applications where data mining tools are proving successful results. Chronic obstructive pulmonary disease (also known as COPD) is a condition that makes breathing difficult. Chronic Obstructive Pulmonary Disease (COPD) is the fourth leading cause of death worldwide and the only chronic disease with increasing mortality rates. COPD is the name for a group of lung diseases including chronic bronchitis, emphysema and chronic obstructive airways disease. The primary cause of COPD is smoking. Progression of the disease is irreversible but can be stabilized or prevented by quitting. If COPD is detected earlier, the formation of lung cancer is prevented. In CT scan may provide additional information and also it provides more detailed images of parts of the body that cannot easily be seen on a standard chest radiograph. First the input image is pre-processed then the lung region is segmented from that image, segmented the cavity region in that lung region, extracted some features for training the classifier and used the Extreme Learning Machine (ELM) classifier to identify the COPD affected lung. The preprocessing is done by using the median Filtering to avoid the noise in the input image and to increase the image quality. After the lung and cavity segmentation, some parameters are chosen to train the classifier to identify whether an x-ray image is a normal or affected. The ELM Classifier is then trained using the parameters chosen from the sample chest CT scan images to identify the normal lung and tuberculosis affected lung.
Routing protocols for mobile social networks achieving trade-off among energy consumption, delivery ratio and delay

So far, the routing protocols designed for mobile social networks (MSNs) have mainly focused on the delivery ratio and delay, but rarely considered the energy consumption for message delivery. This paper addresses the routing protocols for MSNs, which are capable of achieving the trade-off among energy consumption, delivery ratio and delay, and hence is referred to as the EC/DR/D trade-off. We first provide an approach for implementing the EC/DR/D trade-off. Then, we extend three existing routing protocols, namely, the social contact probability assisted routing (SCPR), Bubble and the Prophet protocols, correspondingly to three routing protocols that are able to achieve EC/DR/D trade-off. These routing protocols are referred to as the ESCPR, EBubble and the EProphet protocols, respectively. Finally, we study the performance of these routing protocols based on a community-assisted mobility model. Our studies show that the extended routing protocols can allow us to attain the required EC/DR/D trade-off according to practical requirements.
Dimerization with Cannabinoid Receptors Allosterically Modulates Delta Opioid Receptor Activity during Neuropathic Pain

The diversity of receptor signaling is increased by receptor heteromerization leading to dynamic regulation of receptor function. While a number of studies have demonstrated that family A G-protein-coupled receptors are capable of forming heteromers in vitro, the role of these heteromers in normal physiology and disease has been poorly explored. In this study, direct interactions between CB1 cannabinoid and delta opioid receptors in the brain were examined. Additionally, regulation of heteromer levels and signaling in a rodent model of neuropathic pain was explored. First we examined changes in the expression, function and interaction of these receptors in the cerebral cortex of rats with a peripheral nerve lesion that resulted in neuropathic pain. We found that, following the peripheral nerve lesion, the expression of both cannabinoid type 1 receptor (CB1R) and the delta opioid receptor (DOR) are increased in select brain regions. Concomitantly, an increase in CB1R activity and decrease in DOR activity was observed. We hypothesize that this decrease in DOR activity could be due to heteromeric interactions between these two receptors. Using a CB1R-DOR heteromer-specific antibody, we found increased levels of CB1R-DOR heteromer protein in the cortex of neuropathic animals. We subsequently examined the functionality of these heteromers by testing whether low, non-signaling doses of CB1R ligands influenced DOR signaling in the cortex. We found that, in cortical membranes from animals that experienced neuropathic pain, non-signaling doses of CB1R ligands significantly enhanced DOR activity. Moreover, this activity is selectively blocked by a heteromer-specific antibody. Together, these results demonstrate an important role for CB1R-DOR heteromers in altered cortical function of DOR during neuropathic pain. Moreover, they suggest the possibility that a novel heteromer-directed therapeutic strategy for enhancing DOR activity, could potentially be employed to reduce anxiety associated with chronic pain.
Hybrid Process for Fabricating 3D Hierarchical Scaffolds Combining Rapid Prototyping and Electrospinning

An ideal scaffold should have good mechanical properties and provide a biologically functional implant site. A rapid prototyping system has been introduced as a good method of fabricating 3D scaffolds that mimic the structure in the human body. However, the scaffolds have strands that are too smooth and a pore size that is too large relative to the seeded cells and present unfavorable conditions for initial cell attachment. To overcome these problems, we propose a hybrid technology combining a 3D rapid prototyping system and an electrospinning process to produce a hierarchical 3D biomedical scaffold. The resulting structure consists of alternating layers of 3D-structured/microsized polymer strands and nanofiber webs. The results of cell culturing of chondrocytes indicate that this technique is a feasible new method for fabricating high quality 3D polymeric scaffolds.
Enhanced optical communication and broadband sub-shot-noise interferometry with a stable free-running periodically poled KTiOPO 4 squeezer

An intrinsically stable type I optical parametric oscillator was built with a periodically poled KTiOPO4 crystal to generate a stable, bright, cw, broadband phase-squeezed beam. A 3.2 dB sensitivity enhancement of optical interferometry was demonstrated on weak electro-optic modulation signals within a 20 MHz squeezing bandwidth. This also realized a channel capacity increase beyond that of coherent optical communication.
Analysis of the cbbXYZ operon in Rhodobacter sphaeroides

Three genes, cbbX, cbbY, and cbbZ were found downstream from the form I ribulose 1,5-bisphosphate carboxylase/oxygenase (RubisCO) genes of Rhodobacter sphaeroides. As in chemoautotrophic bacteria, cbbZ was shown to encode phosphoglycolate phosphatase (PGP), whereas the identities of cbbX and cbbY are not known. To determine the physiological function of the cbbXYZ gene products, we constructed R. sphaeroides strains in which the genes were inactivated and characterized the resultant mutant strains according to growth phenotype and levels of RubisCO and PGP. Only a mutation in cbbX resulted in a discernible phenotype, namely, impaired photoautotrophic growth. No PGP activity was observed in any of the mutants, suggesting that the three genes are transcriptionally linked. Studies with a spontaneous chemoautotrophic competent derivative of the CBBX mutant suggested that the cbbXYZ gene products are not essential for chemoautotrophic growth. PGP activity determined in the wild-type strain grown under a variety of growth conditions, and in various strains containing mutations in Calvin-Benson-Bassham cycle structural and regulatory genes, indicated that transcription of the cbb(I) operon influenced expression of the downstream cbbXYZ operon.
Event-based state estimation with variance-based triggering

An event-based state estimation scenario is considered where a sensor sporadically transmits observations of a scalar linear process to a remote estimator. The remote estimator is a time-varying Kalman filter. The triggering decision is based on the estimation variance: the sensor runs a copy of the remote estimator and transmits a measurement if the associated measurement prediction variance exceeds a tolerable threshold. The resulting variance iteration is a new type of Riccati equation with switching that corresponds to the availability or unavailability of a measurement and depends on the variance at the previous step. We study asymptotic properties of the variance iteration and, in particular, asymptotic convergence to a periodic solution.
A slow hopping MAC protocol for coordinator-based cognitive radio network

Many opportunistic spectrum access MAC protocols for cognitive radio networks have been proposed to allow coexistence of both primary and secondary users in licensed bands. However, most of the proposed approaches are based on common control channel that may become a bottleneck for data transfer, as well as be prone to jammer or primary user activity. We propose a coordinator-based cognitive radio network and an opportunistic spectrum access MAC protocol using slow hopping, SH-MAC, to achieve robustness to primary user or jammer activity as well as aggregate throughput improvement. The coordinator considers primary user activity identification, spectrum sensing, channel hopping scheduling, and network time synchronization. The proposed MAC protocol includes mechanisms such as network joining, two-level CS-MACA operation, on-time channel switching, returning to common hop to run in the slow hopping and coordinator-based network environment. Furthermore, the proposal is devised for secondary users to operate with only one transceiver that has non-negligible switching overhead. We validate our protocol using simulation. Simulation results show SH-MAC efficiently increases network capacity regardless of PU activity over the licensed channels.
Application-specific memory management for embedded systems using software-controlled caches

We propose a way to improve the performance of embedded processors running data-intensive applications by allowing software to allocate on-chip memory on an application-specific basis. On-chip memory in the form of cache can be made to act like scratch-pad memory via a novel hardware mechanism, which we call column caching. Column caching enables dynamic cache partitioning in software, by mapping data regions to a specified sets of cache “columns” or “ways. ” When a region of memory is exclusively mapped to an equivalent sized partition of cache, column caching provides the same functionality and predictability as a dedicated scratchpad memory for time-critical parts of a real-time application. The ratio between scratchpad size and cache size can be easily and quickly varied for each application, or each task within an application. Thus, software has much finer software control of on-chip memory, providing the ability to dynamically tradeoff performance for on-chip memory.