Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Norepinephrine on Coronary Circulation and Left Ventricular Dynamics in the Conscious Dog

The effects of norepinephrine (0.1 and 1.0 μg/kg, iv) on coronary blood flow and resistance, left ventricular pressure and diameter, dP/dt, (dP/dt)/P, and the velocity (VISO) of myocardial fiber shortening were studied in conscious dogs. When the heart rate was held constant, norepinephrine caused an initial reduction in coronary vascular resistance which was associated with increases in mean arterial blood pressure, systolic left ventricular pressure, end-diastolic diameter, dP/dt, (dP/dt)/P, and VISO. After this brief coronary vasodilator response, a sustained increase occurred in mean coronary vascular resistance (+0.55 ± 0.07 mm Hg/ml min−1), and increases persisted in mean arterial blood pressure (+67 ± 7 mm Hg), left ventricular systolic pressure (+74 ± 6 mm Hg), left ventricular end-diastolic pressure (+4 ± 1 mm Hg), left ventricular internal diameter (+1.3 ± 0.3 mm), peak dP/dt (+1660 mm Hg/sec), (dP/dt)/P (+15 ± 2 sec−1), and VISO (+11 ± 2 mm/sec); coronary sinus Po2 decreased. Beta-receptor blockade prevented the inotropic effects of norepinephrine, attenuated the early coronary vasodilator effects, and increased the late vasoconstrictor effects. Alpha-receptor blockade abolished the late coronary vasoconstrictor effects of norepinephrine; only dilatation occurred. In contrast to the effects of norepinephrine in conscious dogs without autonomic blockade , norepinephrine (1.0 μg/kg, iv) failed to produce late coronary vasoconstriction in anesthetized, open-chest dogs; only dilatation occurred. Thus, in the normal, conscious dog, norepinephrine exerts an important coronary vasoconstrictor effect which is sufficiently intense to counteract completely the simultaneous tendency toward metabolic vasodilatation.
Detection of diabetic retinopathy lesions in color retinalimages

Advances in medical device technology have resulted in a ple thora of devices that sense, record, transform and process digital data. Images are a key form of d iagnostic data, and many devices have been designed and deployed that capture high-resolution in -vivo images in different parts of the spectrum. Computers have enabled complex forms of reconstructi on of cross-sectional/ 3D structure (and temporal data) non-invasively, by combining views from mul tiple projections. Images thus present valuable diagnostic information that may be used to make wel l-informed decisions. Computer aided diagnosis is a contemporary exploration to a pply computers to process digital data with the aim of assisting medical practitioners in interpre ting diagnostic information. This thesis takes up a specific disease: diabetic retinopathy, which has visua l ch racteristics manifesting in different stages. Image analysis and pattern recognition have been us d to design systems with the objective of detecting and quantifying the extent. The quantitative inf ormation can be used by the practitioner to stage the disease and plan treatment, track drug efficacy, or make decisions on course of treatment or prognosis. The generic task of image understanding is known to be comput ationally ill-posed. However adding domain constraints and restricting the size of the problem m ake it possible to attempt solutions that are useful. Two basic tasks in image understanding : detection a nd segmentation, are used. A system is designed to detect a type of vascular lesion called microane urysm, which appear in the retinal vasculature at the advent of diabetic retinopathy. As the disease pr ogresses it manifests visually as exudative lesions, which are to be segmented, and a system has been deve loped for the same. The developed systems are tested with image datasets that ar e in the public domain, as well as a real dataset (from a local speciality hospital) collected d uring the course of the research, to compare performance indicators against the prior art and elicit bet ter understanding of the factors and challenges involved in creating a system that is ready for clinical use.
Towards Automated Assistance for Mined Roles Analysis in Role Mining Applications

The use of role engineering has grown in importance with the expansion of highly abstracted access control frameworks in organizations. In particular, the use of role mining techniques for the discovery of roles from previously deployed authorizations has facilitated the configuration of such frameworks. However, the literature lacks from a clear basis for appraising and leveraging the learning outcomes of the role mining process. In this paper, we provide such a formal basis. We compare sets of roles by projecting roles from one set into the other set. This approach allows to measure how comparable the two configurations of roles are, and to interpret each role. We formally define the problem of comparing sets of roles, and prove that the problem is NP-complete. Then, we propose an algorithm to map the inherent relation among the sets based on algebraic expressions. We demonstrate the correctness and completeness of our solution, and investigate some further issues that may benefit from our approach, such as detection of unhandled perturbations or source misconfiguration.
Exploiting Radiation-Induced Signaling to Increase the Susceptibility of Resistant Cancer Cells to Targeted Drugs: AKT and mTOR Inhibitors as an Example

Implementing targeted drug therapy in radio-oncologic treatment regimens has greatly improved the outcome of cancer patients. However, the efficacy of molecular targeted drugs such as inhibitory antibodies or small molecule inhibitors essentially depends on target expression and activity, which both can change during the course of treatment. Radiotherapy has previously been shown to activate prosurvival pathways, which can help tumor cells to adapt and thereby survive treatment. Therefore, we aimed to identify changes in signaling induced by radiation and evaluate the potential of targeting these changes with small molecules to increase the therapeutic efficacy on cancer cell survival. Analysis of “The Cancer Genome Atlas” database disclosed a significant overexpression of AKT1, AKT2, and MTOR genes in human prostate cancer samples compared with normal prostate gland tissue. Multifractionated radiation of three-dimensional–cultured prostate cancer cell lines with a dose of 2 Gy/day as a clinically relevant schedule resulted in an increased protein phosphorylation and enhanced protein–protein interaction between AKT and mTOR, whereas gene expression of AKT, MTOR, and related kinases was not altered by radiation. Similar results were found in a xenograft model of prostate cancer. Pharmacologic inhibition of mTOR/AKT signaling after activation by multifractionated radiation was more effective than treatment prior to radiotherapy. Taken together, our findings provide a proof-of-concept that targeting signaling molecules after activation by radiotherapy may be a novel and promising treatment strategy for cancers treated with multifractionated radiation regimens such as prostate cancer to increase the sensitivity of tumor cells to molecular targeted drugs. Mol Cancer Ther; 17(2); 355–67. ©2017 AACR. See all articles in this MCT Focus section, “Developmental Therapeutics in Radiation Oncology. ”
Priority Random Linear Codes in Distributed Storage Systems

Node churn and failures exist as fundamental characteristics in both peer-to-peer (P2P) and sensor networks. Peers in P2P networks are highly dynamic, whereas sensors are not dependable. As such, maintaining the persistence of periodically measured data in a scalable fashion has become a critical challenge in such systems, without the use of centralized servers. To better cope with node dynamics and failures, we propose priority random linear codes (RLCs), as well as their affiliated predistribution protocols, to maintain measurement data in different priorities, such that critical data have a higher opportunity to survive node failures than data of less importance. A salient feature of priority RLCs is the ability to partially recover more important subsets of the original data with higher priorities, when it is not feasible to recover all of them due to node dynamics. We present extensive analytical and experimental results to show the effectiveness of priority RLCs.
Calretinin, &bgr;-Tubulin Immunohistochemistry, and Submucosal Nerve Trunks Morphology in Hirschsprung Disease: Possible Applications in Clinical Practice

Objectives: The aim of this study was to investigate calretinin and &bgr;-tubulin immunohistochemical expression together with submucosal nerve trunks morphology in differently innervated segments of Hirschsprung disease (HD) and total colonic aganglionosis (TCA). Methods: A total of 25 cases (22 HD, 3 TCA) and 18 controls were processed for calretinin and &bgr;-tubulin immunohistochemistry. Sections representative of distal aganglionic, transition, and proximal ganglionic segments were evaluated by a visual grading score; &bgr;-tubulin was evaluated also by image analysis. Submucosal nerve trunks hypertrophy and hyperplasia were measured by citomorphology. The length of proximal segment was correlated to postoperative bowel function. Results: Controls showed intense calretinin and &bgr;-tubulin staining. In HD and TCA, calretinin staining was related to the presence of ganglion cells: negative in distal, faint in transition, intense in proximal segment. &bgr;-Tubulin staining was weak in all of the segments of HD and negative in TCA. Hypertrophic and hyperplastic nerve trunks characterized aganglionic segment, and progressively decreasing nerve size was observed in transition and ganglionic segments. Transient postoperative constipation, soiling, or enterocolitis was present in 59% of patients with HD without clear relation to proximal segment length or presence of hypertrophic nerve trunks. Conclusions: Calretinin is a reliable marker of the presence of ganglion cells, and, together with nerve hypertrophy, it helps to identify the transition zone. Length and nerve size of proximal segment in resected specimen did not affect the postsurgical intestinal function. Reduced &bgr;-tubulin expression along the entire colonic tract, included proximal ganglionic segments, may represent a potential impairing factor for the enteric neural transmission.
The Expression, Purification, and Characterization of a Ras Oncogene (Bras2) in Silkworm (Bombyx mori)

The Ras oncogene of silkworm pupae (Bras2) may belong to the Ras superfamily. It shares 77% of its amino acid identity with teratocarcinoma oncogene 21 (TC21) related ras viral oncogene homolog-2 (R-Ras2) and possesses an identical core effector region. The mRNA of Bombyx mori Bras2 has 1412 bp. The open reading frame contains 603 bp, which encodes 200 amino acid residues. This recombinant BmBras2 protein was subsequently used as an antigen to raise a rabbit polyclonal antibody. Western blotting and real-time PCR analyses showed that BmBras2 was expressed during four developmental stages. The BmBras2 expression level was the highest in the pupae and was low in other life cycle stages. BmBras2 was expressed in all eight tested tissues, and it was highly expressed in the head, intestine, and epidermis. Subcellular localization studies indicated that BmBras2 was predominantly localized in the nuclei of Bm5 cells, although cytoplasmic staining was also observed to a lesser extent. A cell proliferation assay showed that rBmBras2 could stimulate the proliferation of hepatoma cells. The higher BmBras2 expression levels in the pupal stage, tissue expression patterns, and a cell proliferation assay indicated that BmBras2 promotes cell division and proliferation, most likely by influencing cell signal transduction.
Computational modeling and engineering in pediatric and congenital heart disease

Purpose of review Recent methodological advances in computational simulations are enabling increasingly realistic simulations of hemodynamics and physiology, driving increased clinical utility. We review recent developments in the use of computational simulations in pediatric and congenital heart disease, describe the clinical impact in modeling in single-ventricle patients, and provide an overview of emerging areas. Recent findings Multiscale modeling combining patient-specific hemodynamics with reduced order (i.e., mathematically and computationally simplified) circulatory models has become the de-facto standard for modeling local hemodynamics and ‘global’ circulatory physiology. We review recent advances that have enabled faster solutions, discuss new methods (e.g., fluid structure interaction and uncertainty quantification), which lend realism both computationally and clinically to results, highlight novel computationally derived surgical methods for single-ventricle patients, and discuss areas in which modeling has begun to exert its influence including Kawasaki disease, fetal circulation, tetralogy of Fallot (and pulmonary tree), and circulatory support. Summary Computational modeling is emerging as a crucial tool for clinical decision-making and evaluation of novel surgical methods and interventions in pediatric cardiology and beyond. Continued development of modeling methods, with an eye towards clinical needs, will enable clinical adoption in a wide range of pediatric and congenital heart diseases.
Evaluating branch prediction using two-level perceptron table

Nowadays, the commercial processors are designed on superscalar architectures. These processors use branch prediction techniques to forecast the code path that will be followed after each branch instruction, but before its execution. Branch prediction avoids pipeline stalls, anticipating the execution of instructions and providing high instruction level parallelism. This work evaluates a recent approach for intelligent branch prediction that is based on neural networks. Multiple perceptrons were organized in a two-level prediction table indexed by the branch address in the first level and by the branch history pattern in the second level. Many situations were examined changing the number of lines and the associativity of the prediction table. This approach showed ability to predict branches, reaching more than 98% in some cases.
Robust MMSE Transceiver Design for Nonregenerative Multicasting MIMO Relay Systems

In this paper, we investigate the transceiver design for nonregenerative multicasting multiple-input multiple-output (MIMO) relay systems, where one transmitter broadcasts common message to multiple receivers with the aid of a relay node. The transmitter, relay, and receivers are all equipped with multiple antennas. We assume that the true (unknown) channel matrices have Gaussian distribution, with the estimated channels as the mean value, and the channel estimation errors follow the well-known Kronecker model. We first develop an iterative robust algorithm to jointly design the transmitter, relay, and receiver matrices to minimize the maximal mean-squared error (MSE) of the signal waveform estimation among all receivers. Then, we derive the optimal structure of the relay precoding matrix and show that the MSE at each receiver can be decomposed into the sum of the MSEs of the first-hop and second-hop channels. Based on this MSE decomposition, we develop a simplified transceiver design algorithm with a low computational complexity. Numerical simulations demonstrate the improved robustness of the proposed transceiver design algorithms against the mismatch between the true and estimated channels. Interestingly, compared with the iterative algorithm, the simplified transceiver design has only negligible performance loss with significantly reduced computational complexity.
Serine Protease Inhibitor Serp-1 Strongly Impairs Atherosclerotic Lesion Formation and Induces a Stable Plaque Phenotype in ApoE−/− Mice

Abstract— The myxoma virus protein Serp-1 is a member of the serine protease inhibitor superfamily. Serp-1 potently inhibits human serum proteases including plasmin, urokinase-type plasminogen activator (uPA), and tissue-type plasminogen activator (tPA). Serp-1 also displays a high antiinflammatory activity, rendering it a promising candidate for antiatherosclerotic therapy. In this study, we have thus examined the effect of Serp-1 on de novo atherosclerotic plaque formation and on advanced lesions. Perivascular collars were placed around carotid arteries of ApoE−/− mice to induce atherosclerotic plaques and Serp-1 treatment started at week 1 and week 5 after collar placement. Effects of Serp-1 on de novo atherogenesis were characterized by a significantly lower plaque size than that of control mice (18±5×103 versus 57±12×103 &mgr;m2, respectively; P =0.007). Immunostaining showed a 50% (P =0.004) decrease in the MOMA-2–stained lesion area of Serp-1–treated mice. Treatment of advanced lesions with Serp-1 resulted in a decrease in plaque size and lumen stenosis (P =0.028). &agr;-Actin staining of these lesions was significantly increased compared with the control (P =0.017). In both studies, a higher cellularity of the plaque and increased collagen content was observed in Serp-1–treated mice. In vitro studies showed that Serp-1 induces proliferation and migration of vascular smooth muscle cells. In conclusion, Serp-1 inhibits carotid artery plaque growth and progression in ApoE−/− mice. Equally relevant, it enhances cellularity of the plaque core potentially leading to improved plaque stability. The above results indicate that Serp-1 constitutes a promising lead in antiatherosclerotic therapy.
Nanosecond pulse generation with a gallium nitride saturable absorber

A mode-locked nanosecond Erbium-doped fiber laser (EDFL) was demonstrated using gallium nitrate (GaN) in the form of a polished crystal as a saturable absorber (SA). The GaN film exhibited a modulation depth of 2% with a saturable optical intensity of 0.46 MW/cm2. The laser directly produced nanosecond pulses with stable mode-locking operation at a pump threshold of 149.51 mW. The generated output pulses operated at a 1562 nm central wavelength with a pulse duration and a repetition rate of 485 ns and 967 kHz, respectively. The average output power was 3.068 mW at a pump power of 182.34 mW, corresponding to 3.1 nJ single pulse energy. These results indicate that GaN material has a promising application in ultrafast light generation.
Speed Determination of a Moving Object of a Video Using Background Extraction and Normalized Cuts Segmentation

This paper is concerned with the determination of the traveling speed of a moving object of a video clip based on subsequent object detection techniques. After preprocessing of the original image sequence, which is sampled from the video camera, the target moving object is detected with the improved algorithm in which the moving object region can be extracted completely through several Segmentation. Among the multiple moving objects of the video, the target object has been detected based on particular criteria of region that it occupies. Then the results of these processing can be traveling speed of the target moving object from changes of its coordinate position from the video frames. Among the different video file format, Audio Video Interleaved (AVI) format has been used to examine our experiments.
Fusing discriminative and generative methods for speaker recognition: experiments on switchboard and NFI/TNO field data

Discriminatively trained support vector machines have recently been introduced as a novel approach to speaker recognition. Support vector machines (SVMs) have a distinctly different modeling strategy in the speaker recognition problem. The standard Gaussian mixture model (GMM) approach focuses on modeling the probability density of the speaker and the background (a generative approach). In contrast, the SVM models the boundary between the classes. Another interesting aspect of the SVM is that it does not directly produce probabilistic scores. This poses a challenge for combining results with a GMM. We therefore propose strategies for fusing the two approaches. We show that the SVM and GMM are complementary technologies. Recent evaluations by NIST (telephone data) and NFI/TNO (forensic data) give a unique opportunity to test the robustness and viability of fusing GMM and SVM methods. We show that fusion produces a system which can have relative error rates 23% lower than individual systems.
Fivebranes wrapped on associative three-cycles

We construct supergravity solutions corresponding to fivebranes wrapping associative three-cycles of constant curvature in manifolds of ${G}_{2}$-holonomy. The solutions preserve 2 supercharges and are first constructed in $D=7$ gauged supergravity and then lifted to $D=10,11. $ We show that the low-energy theory of M-fivebranes wrapped on a compact hyperbolic three-space is dual to a superconformal field theory in $D=3$ by exhibiting a flow to an ${\mathrm{AdS}}_{4}$ region. For IIB-fivebranes wrapped on a three-sphere we speculate on a connection with spontaneous supersymmetry breaking of pure $\mathcal{N}=1$ super Yang-Mills theory in $D=3. $
Worldmapper: The World as You've Never Seen it Before

This paper describes the Worldmapper project, which makes use of novel visualization techniques to represent a broad variety of social and economic data about the countries of the world. The goal of the project is to use the map projections known as cartograms to depict comparisons and relations between different territories, and its execution raises many interesting design challenges that were not all apparent at the outset. We discuss the approaches taken towards these challenges, some of which may have considerably broad application. We conclude by commenting on the positive initial response to the Worldmapper images published on the Web, which we believe is due, at least in part, to the particular effectiveness of the cartogram as a tool for communicating quantitative geographic data
Acquirement of DNA copy number variations in non-small cell lung cancer metastasis to the brain

Brain metastasis is a major complication of non-small cell lung cancer (NSCLC) and leads to most of the mortality of this disease. However, the biological mechanisms and molecular features in brain metastasis of NSCLC are poorly understood. In the present study, we compared whole-genome copy number variations (CNVs) between a primary lung adenocarcinoma and secondary metastatic brain lesion from the same patient using array comparative genomic hybridization (aCGH). The number of CNV regions was markedly higher in the secondary metastatic tumor than the primary tumor in the lung. In detail, the common CNVs in both tumors included gains of 7p22, 7p12-p11, 7q11, 7q22, 21q22, and 19q13; gains of 1p33-p34, 1q22, 5p13 and 14q11 whereas losses of 3p, 4q31, 5q, 11p15, Xp21-p22 and Xq21 were identified only in the secondary lesion. Gene Ontology enrichment analysis revealed that the genes with amplified copy numbers in both tumors were related to such processes as DNA replication and mismatch repair. Genes only amplified in the metastatic tumor were enriched in processes that include leukocyte migration and organ development, and genes with a lower copy number in the secondary tumor included the processes of proteolysis regulation, negative regulation of cell proliferation and cell adhesion. These findings provided new insight into the genomic mechanism of the spread of lung adenocarcinoma to the brain, and the candidate genes identified serve as novel indicators or putative targets in NSCLC brain metastasis.