Miracle-dz/UniFAR-FTUs huggingface dataset:
SUBCELLULAR DISTRIBUTION OF A HEAT‐STABLE PROTEIN INHIBITOR OF CYCLIC AMP‐DEPENDENT PROTEIN KINASE IN RAT BRAIN

Abstract— Cyclic AMP (cAMP)‐dependent protein kinase catalyzes the phosphorylation of polypeptidic serine and threonine residues according to the following chemical equation: ATP + protein → phospho‐protein + ADP. A heat stable, trypsin labile factor present in brain, skeletal muscle and other tissues inhibits enzymatic phosphorylation of some proteins and enhances that of others. Since brain is one of the richest sources of adenylate cyclase, cAMP, cAMP‐dependent protein kinase and the heat stable protein kinase inhibitor and because they may play a role in neurotransmission, an investigation of the subcellular distribution of the heat stable factor in rat brain was undertaken. Although present in the nuclear, mitochondrial and microsomal fractions, the highest activity of protein kinase inhibitor is in the soluble fraction: its activity parallels that of the cytoplasmic enzyme marker, lactate dehydro‐genase. The inhibitory activity is also found in the synaptosome or pinched‐off nerve ending fraction. Following osmotic lysis of this fraction, about 90% of the factor occurs in the soluble fraction. On the other hand, only 40% of the cAMP‐dependent protein kinase is solubilized and 60% remains membrane‐bound. Using this membrane‐bound protein kinase, phosphorylation of endogenous substrate is unaltered by inhibitor, but phosphorylation of added histone substrate is decreased.
Advanced Manufacturing Collaboration in a Cloud-based App Marketplace

Advanced Manufacturing Apps that perform complex modeling and simulation are now becoming available in Marketplaces. App stakeholders face two fundamental challenges in cloud engineering of the App Marketplaces: (i) orchestration of service chaining through an App Runtime, and (ii) finding a suitable cost model to evaluate App pricing strategies. In this paper, we address these challenges by proposing a new cloud architecture that aims at supporting an 'App Marketplace' that thrives on agile development, organic collaboration and scalable sales of next generation Manufacturing Apps requiring high-performance simulation and modeling. We describe how we are realizing the vision of this architecture through an App Runtime we have developed that leverages a Resource Brokering Service to create App chaining mechanisms. We also detail a new cost model that could be part of an Accounting Service in our proposed architecture to address the issues of cost accounting and pricing of the Apps faced by the App developers while using cloud infrastructures for hosting their Apps. Lastly, we describe experiments with a real-world implementation of our App Runtime and cost model in a WheelSim testbed that uses NSF GENI Cloud and Ohio Supercomputer Center resources. Our results show benefits to an App developer in terms of: satisfactory user experience, lower design time and lower cost/simulation.
Amplification of Coronary Arteriogenic Capacity of Multipotent Stromal Cells by Epidermal Growth Factor

Objective—We determined whether increasing adherence of multipotent stromal cells (MSCs) would amplify their effects on coronary collateral growth (CCG). Methods and Results—Adhesion was established in cultured coronary endothelials cells (CECs) or MSCs treated with epidermal growth factor (EGF). EGF increased MSCs adhesion to CECs, and increased intercellular adhesion molecule (ICAM-1) or vascular cell adhesion molecule (VCAM-1) expression. Increased adherence was blocked by EGF receptor antagonism or antibodies to the adhesion molecules. To determine whether adherent MSCs, treated with EGF, would augment CCG, repetitive episodes of myocardial ischemia (RI) were introduced and CCG was measured from the ratio of collateral-dependent (CZ) and normal zone (NZ) flows. CZ/NZ was increased by MSCs without treatment versus RI-control and was further increased by EGF-treated MSCs. EGF-treated MSCs significantly improved myocardial function versus RI or RI+MSCs demonstrating that the increase in collateral flow was functionally significant. Engraftment of MSCs into myocardium was also increased by EGF treatment. Conclusions—These results reveal the importance of EGF in MSCs adhesion to endothelium and suggest that MSCs may be effective therapies for the stimulation of coronary collateral growth when interventions are used to increase their adhesion and homing (in vitro EGF treatment) to the jeopardized myocardium.
Supporting novel home network management interfaces with openflow and NOX

The Homework project has examined redesign of existing home network infrastructures to better support the needs and requirements of actual home users. Integrating results from several ethnographic studies, we have designed and built a home networking platform providing detailed per-flow measurement and management capabilities supporting several novel management interfaces. This demo specifically shows these new visualization and control interfaces (1), and describes the broader benefits of taking an integrated view of the networking infrastructure, realised through our router's augmented measurement and control APIs (2). Aspects of this work have been published: the Homework Database in Internet Management (IM) 2011 [3] and implications of the ethnographic results are to appear at the SIGCOMM W-MUST workshop 2011 [2]. Separate, more detailed expositions of the interface elements and system performance and implications are currently under submission at other venues. A partial code release is already available and we anticipate fuller public beta release by Q4 2011.
Use of Professional Accountants' Advisory Services and its Impact on SME Performance in an Emerging Economy: A Resource-based View

This paper aims to identify the factors that affect the decisions of managers of manufacturing sector SMEs in Iran to utilise external accountants’ advisory services and to examine the effect of these advisory services on SME performance using the Resource-Based View (RBV) of the firm as the theoretical lens in the Iranian SME manufacturing sector. A questionnaire survey of 658 Iranian manufacturing SMEs is used. The results of linear
Physiotherapy for vegetative and minimally conscious state patients: family perceptions and experiences

Abstract Purpose: To examine family perceptions of physiotherapy provided to relatives in vegetative or minimally conscious states. Method: Secondary thematic analysis of 65 in-depth narrative interviews with family members of people in vegetative or minimally conscious states. Results: Families place great significance on physiotherapy in relation to six dimensions: “Caring for the person”, “Maximising comfort”, “Helping maintain health/life”, “Facilitating progress”, “Identifying or stimulating consciousness” and “Indicating potential for meaningful recovery”. They can have high expectations of what physiotherapy may deliver but also, at times, express concerns about physiotherapy’s potential to cause pain or distress, or even constitute a form of torture if they believe there is no hope for “meaningful” recovery. Conclusion: Physiotherapists can make an important contribution to supporting this patient group and their families but it is vital to recognise that family understandings of physiotherapy may differ significantly from those of physiotherapists. Both the delivery and the withdrawal of physiotherapy is highly symbolic and can convey (inadvertent) messages to people about their relative’s current and future state. A genuine two-way dialogue between practitioners and families about the aims of physiotherapeutic interventions, potential outcomes and patients’ best interests is critical to providing a good service and establishing positive relationships and appropriate treatment. Implications for Rehabilitation Families of people in PVS or MCS consider physiotherapy as a vital part of good care. Clear communication is critical if therapeutic input is withdrawn or reduced. The purpose of physiotherapy interventions can be misinterpreted by family members. Physiotherapists need to clarify what physiotherapy can, and cannot, achieve. Families can find some interventions distressing to witness – explaining to families what interventions involve, what they can expect to see (and hear) may be helpful. Physiotherapists and families can attribute different meanings to physiotherapy. Physiotherapists need to identify how families view interventions and modify their explanations accordingly to enhance information sharing.
The Association of Metacognitive Beliefs With Emotional Distress After Diagnosis of Cancer

Objective: Emotional distress after a diagnosis of cancer is normal and, for most people, will diminish over time. However, a significant minority of patients with cancer experience persistent or recurrent symptoms of emotional distress for which they need help. A model developed in mental health, the self-regulatory executive function model (S-REF), specifies that maladaptive metacognitive beliefs and processes, including persistent worry, are key to understanding why such emotional problems persist. This cross-sectional study explored, for the first, time whether metacognitive beliefs were associated with emotional distress in a cancer population, and whether this relationship was mediated by worry, as predicted by the S-REF model. Method: Two hundred twenty-nine participants within 3 months of diagnosis of, and before treatment for, primary breast or prostate cancer completed self-report questionnaires measuring anxiety, depression, posttraumatic stress disorder (PTSD) symptoms, metacognitive beliefs, worry, and illness perceptions. Results: Regression analysis showed that metacognitive beliefs were associated with symptoms of anxiety, depression, and PTSD, and explained additional variance in these outcomes after controlling for age, gender, and illness perceptions. Structural equation modeling was consistent with cross-sectional hypotheses derived from the theory that metacognitive beliefs cause and maintain distress both directly and indirectly by driving worry. Conclusions: The findings provide promising first evidence that the S-REF model may be usefully applied in cancer. Further study is required to establish the predictive and clinical utility of these findings.
Vulnerability of Protoxylem and Metaxylem Vessels to Embolisms and Radial Refilling in a Vascular Bundle of Maize Leaves

Regulation of water flow in an interconnected xylem vessel network enables plants to survive despite challenging environment changes that can cause xylem embolism. In this study, vulnerability to embolisms of xylem vessels and their water-refilling patterns in vascular bundles of maize leaves were experimentally investigated by employing synchrotron X-ray micro-imaging technique. A vascular bundle in maize consisted of a protoxylem vessel with helical thickenings between two metaxylem vessels with single perforation plates and nonuniformly distributed pits. When embolism was artificially induced in excised maize leaves by exposing them to air, protoxylem vessels became less vulnerable to dehydration compared to metaxylem vessels. After supplying water into the embolized vascular bundles, when water-refilling process stopped at the perforation plates in metaxylem vessels, discontinuous radial water influx occurred surprisingly in the adjacent protoxylem vessels. Alternating water refilling pattern in protoxylem and metaxylem vessels exhibited probable correlation between the incidence location and time of water refilling and the structural properties of xylem vessels. These results imply that the maintenance of water transport and modulation of water refilling are affected by hydrodynamic roles of perforation plates and radial connectivity in a xylem vascular bundle network.
Near-linear constructions of exact unitary 2-designs

A unitary 2-design can be viewed as a quantum analogue of a 2-universal hash function: it is indistinguishable from a truly random unitary by any procedure that queries it twice. We show that exact unitary 2-designs on n qubits can be implemented by quantum circuits consisting of Oe(n) elementary gates in logarithmic depth. This is essentially a quadratic improvement in size (and in width times depth) over all previous implementations that are exact or approximate (for sufficiently strong approximations).
Layered Constructions for Low-Delay Streaming Codes

We study error correction codes for multimedia streaming applications where a stream of source packets must be transmitted in real-time, with in-order decoding, and strict delay constraints. In our setup, the encoder observes a stream of source packets in a sequential fashion, and <inline-formula> <tex-math notation="LaTeX">$M$ </tex-math></inline-formula> channel packets must be transmitted between the arrival of successive source packets. Each channel packet can depend on all the source packets observed up to and including that time, but not on any future source packets. The decoder must reconstruct the source stream with a delay of <inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula> packets. We consider a class of packet erasure channels with burst and isolated erasures, where the erasure patterns are locally constrained. Our proposed model provides a tractable approximation to statistical models, such as the Gilbert–Elliott channel, for capacity analysis. When <inline-formula> <tex-math notation="LaTeX">$M=1$ </tex-math></inline-formula>, i.e., when the source-packet arrival and channel-packet transmission rates are equal, we establish upper and lower bounds on the capacity, that are within one unit of the decoding delay <inline-formula> <tex-math notation="LaTeX">$T$ </tex-math></inline-formula>. We also establish necessary and sufficient conditions on the column distance and column span of a convolutional code to be feasible, and in turn establish a fundamental tradeoff between these. Our proposed codes—maximum distance and span codes—achieve a near-optimal tradeoff between the column distance and column span, and involve a layered construction. When <inline-formula> <tex-math notation="LaTeX">$M>1$ </tex-math></inline-formula>, we establish the capacity for the burst-erasure channel and an achievable rate in the general case. Extensive numerical simulations over Gilbert–Elliott and Fritchman channel models suggest that our codes also achieve significant gains in the residual loss probability over statistical channel models.
Pyvolve: A Flexible Python Module for Simulating Sequences along Phylogenies

We introduce Pyvolve, a flexible Python module for simulating genetic data along a phylogeny using continuous-time Markov models of sequence evolution. Easily incorporated into Python bioinformatics pipelines, Pyvolve can simulate sequences according to most standard models of nucleotide, amino-acid, and codon sequence evolution. All model parameters are fully customizable. Users can additionally specify custom evolutionary models, with custom rate matrices and/or states to evolve. This flexibility makes Pyvolve a convenient framework not only for simulating sequences under a wide variety of conditions, but also for developing and testing new evolutionary models. Pyvolve is an open-source project under a FreeBSD license, and it is available for download, along with a detailed user-manual and example scripts, from http://github.com/sjspielman/pyvolve.
Identification of Virulence Determinants in Influenza Viruses

To date there is no rapid method to screen for highly pathogenic avian influenza strains that may be indicators of future pandemics. We report here the first development of an oligonucleotide-based spectroscopic assay to rapidly and sensitively detect a N66S mutation in the gene coding for the PB1-F2 protein associated with increased virulence in highly pathogenic pandemic influenza viruses. 5′-Thiolated ssDNA oligonucleotides were employed as probes to capture RNA isolated from six influenza viruses, three having N66S mutations, two without the N66S mutation, and one deletion mutant not encoding the PB1-F2 protein. Hybridization was detected without amplification or labeling using the intrinsic surfaced-enhanced Raman spectrum of the DNA-RNA complex. Multivariate analysis identified target RNA binding from noncomplementary sequences with 100% sensitivity, 100% selectivity, and 100% correct classification in the test data set. These results establish that optical-based diagnostic methods are able to directly identify diagnostic indicators of virulence linked to highly pathogenic pandemic influenza viruses without amplification or labeling.
A Small-Gain Approach to Robust Event-Triggered Control of Nonlinear Systems

This paper presents a new approach to event-triggered control for nonlinear uncertain systems by using the notion of input-to-state stability (ISS) and the nonlinear small-gain theorem. The contribution of this paper is threefold. First, it is proved that infinitely fast sampling can be avoided if the system is input-to-state stabilizable with the sampling error as the external input and the corresponding ISS gain is locally Lipschitz. No assumption on the existence of known ISS-Lyapunov functions is made in the discussions. Moreover, the forward completeness problem with event-triggered control is studied systematically by using ISS small-gain arguments. Second, the proposed approach gives rise to a new self-triggered sampling strategy for a class of nonlinear systems subject to external disturbances. If an upper bound of the external disturbance is known, then the closed-loop system can be designed to be robust to the external disturbance, and moreover, the system state globally asymptotically converges to the origin if the external disturbance decays to zero. Third, a new design method is developed for event-triggered control of nonlinear uncertain systems in the strict-feedback form. It is particularly shown that the ISS gain with the sampling error as the input can be designed to satisfy the proposed condition for event-triggered control and self-triggered control.
FacPad: Bayesian sparse factor modeling for the inference of pathways responsive to drug treatment

MOTIVATION It is well recognized that the effects of drugs are far beyond targeting individual proteins, but rather influencing the complex interactions among many relevant biological pathways. Genome-wide expression profiling before and after drug treatment has become a powerful approach for capturing a global snapshot of cellular response to drugs, as well as to understand drugs' mechanism of action. Therefore, it is of great interest to analyze this type of transcriptomic profiling data for the identification of pathways responsive to different drugs. However, few computational tools exist for this task. RESULTS We have developed FacPad, a Bayesian sparse factor model, for the inference of pathways responsive to drug treatments. This model represents biological pathways as latent factors and aims to describe the variation among drug-induced gene expression alternations in terms of a much smaller number of latent factors. We applied this model to the Connectivity Map data set (build 02) and demonstrated that FacPad is able to identify many drug-pathway associations, some of which have been validated in the literature. Although this method was originally designed for the analysis of drug-induced transcriptional alternation data, it can be naturally applied to many other settings beyond polypharmacology. AVAILABILITY AND IMPLEMENTATION The R package 'FacPad' is publically available at: http://cran.open-source-solution.org/web/packages/FacPad/.
Nesting habitat selection and distribution of an avian top predator in the Canadian Arctic

Detecting and planning for ecosystem changes from climate and land-use alteration is limited by uncertainty about the current distribution of many species. This is exacerbated in remote areas like the Arctic, where the impacts of climate change are the strongest and where industrial exploration and development are expanding. Using remotely-sensed environmental information and known nest sites, we estimated the breeding distribution and habitat selection of the peregrine falcon (Falco peregrinus) throughout most of Nunavut, a massive northern Canadian territory (>1.8 M km2) encompassing ∼15% of the world’s tundra biome. Our results show that peregrine falcons selected features of prior known importance such as rugged topography, but also sites with higher than average summer temperatures, more productive land classes, lower mean elevations, and lower mean summer precipitation. Our model identifies several areas of high relative probability of peregrine occurrence, some of which were unrecognized to date. Some of these areas may be targets for future industrial developments and are located in an area where some of the fastest climate changes are expected. Our model will allow managers to identify the areas that could be the most critical for monitoring in the context of future development and climate change.
Modeling synchronous wakeup patterns in wireless sensor networks: server vacation model analysis

Power-saving in wireless sensor networks is very crucial since most of the wireless sensors are battery-operated. Turning the sensor nodes into a low-power sleep state periodically is an important technique to conserve energy and prolong network lifetime. However, putting the sensor nodes into the sleep state will result in increased message latency. In this paper, we aim at developing a framework for modeling the synchronous wakeup patterns of networked sensors so as to provide a basis for studying such design tradeoff. The proposed framework employed the vacation model from queuing theory to model the synchronous wakeup patterns as an M/G/1 queue with server vacations. Based on the model, the optimal operation scenario for the synchronous wakeup operation is first deduced. We then make use of the model to study the synchronous wakeup patterns with exhaustive and gated services disciplines in particular. Analytical results for these two wakeup patterns are derived and summarized in this paper
New geophysical complex-field approach to modelling dynamics of heat-mass-transfer and ventilation in atmosphere of the industrial region

New generalized approach, including an improved theory of atmospheric circulation in combination with the hydrodynamic model (with correct account of turbulence in atmosphere of the urban area) and the Arakawa-Schubert method of calculation of cloud convection and theory of complex geophysical field is applied to the simulation of heat and air transfer in atmosphere of industrial region. The modelling ventilation data (mesocirculation) parameters over territory of Odessa, as well as the area of the Fukushima power plant after 2011 accident are presented.
A Highly Sensitive Rapid Diagnostic Test for Chagas Disease That Utilizes a Recombinant Trypanosoma cruzi Antigen

Improved diagnostic tests for Chagas disease are urgently needed. A new lateral flow rapid test for Chagas disease is under development at PATH, in collaboration with Laboratorio Lemos of Argentina, which utilizes a recombinant antigen for detection of antibodies to Trypanosoma cruzi. To evaluate the performance of this test, 375 earlier characterized serum specimens from a region where Chagas is endemic were tested using a reference test (the Ortho T. cruzi ELISA, Johnson & Johnson), a commercially available rapid test (Chagas STAT-PAK, Chembio), and the PATH-Lemos rapid test. Compared to the composite reference tests, the PATH-Lemos rapid test demonstrated an optimal sensitivity of 99.5% and specificity of 96.8%, while the Chagas STAT-PAK demonstrated a sensitivity of 95.3% and specificity of 99.5%. These results indicate that the PATH-Lemos rapid test shows promise as an improved and reliable tool for screening and diagnosis of Chagas disease.