Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison of Stream-Oriented High-Availability Algorithms

Recently, significant efforts have focused on developing novel data-processing systems to support a new class of applications that commonly require sophisticated and timely processing of high-volume data streams. Early work in stream processing has primarily focused on streamoriented languages and resource-constrained, one-pass query-processing. High availability, an increasingly important goal for virtually all data processing systems, is yet to be addressed. In this paper, we first describe how the standard highavailability approaches used in data management systems can be applied to distributed stream processing. We then propose a novel stream-oriented approach that exploits the unique data-flow nature of streaming systems. Using analysis and a detailed simulation study, we characterize the performance of each approach and demonstrate that the stream-oriented algorithm significantly reduces runtime overhead at the expense of a small increase in recovery time.
Hepatocyte nuclear factor 4 contributes to an intestinal epithelial phenotype in vitro and plays a partial role in mouse intestinal epithelium differentiation

Babeu JP, Darsigny M, Lussier CR, Boudreau F. Hepatocyte nuclear factor 4 contributes to an intestinal epithelial phenotype in vitro and plays a partial role in mouse intestinal epithelium differentiation. Am J Physiol Gastrointest Liver Physiol 297: G124–G134, 2009. First published April 23, 2009; doi:10.1152/ajpgi.90690. 2008. —Hepatocyte nuclear factor 4 (HNF4 ) is a regulator of hepatocyte and pancreatic transcription. Hnf4 deletion in the mouse is embryonically lethal with severe defects in visceral endoderm formation. It has been concluded in the past that the role of Hnf4 in the developing colon was much less important than in the liver. However, the precise role of Hnf4 in the homeostasis of the small intestinal epithelium remains unclear. Our aim was to evaluate the potential of Hnf4 to support an intestinal epithelial phenotype. First, Hnf4 potential to dictate this phenotype was assessed in nonintestinal cell lines in vitro. Forced expression of Hnf4 in fibroblasts showed an induction of features normally restricted to epithelial cells. Combinatory expression of Hnf4 with specific transcriptional regulators of the intestine resulted in the induction of intestinal epithelial genes in this context. Second, the importance of Hnf4 in maintaining the homeostasis of the intestinal epithelium was investigated in mice. Mice conditionally deficient for intestinal Hnf4 developed normally throughout adulthood with an epithelium displaying normal morphological and functional structures with minor alterations. Subtle but statistical differences were observed at the proliferation and the cytodifferentiation levels. Hnf4 mutant mice displayed an increase in the number of goblet and enteroendocrine cells compared with controls. Given the fundamental role of this transcription factor in other tissues, these findings dispute the crucial role for this regulator in the maintenance of intestinal epithelial cell function at a period of time that follows cytodifferentiation but may suggest a functional role in instructing cells to become specific to the intestinal epithelium.
To CURe or not to CURe? Differential effects of the chaperone sorting factor Cur1 on yeast prions are mediated by the chaperone Sis1

Yeast self‐perpetuating protein aggregates (prions) provide a convenient model for studying various components of the cellular protein quality control system. Molecular chaperones and chaperone‐sorting factors, such as yeast Cur1 protein, play key role in proteostasis via tight control of partitioning and recycling of misfolded proteins. In this study, we show that, despite the previously described ability of Cur1 to antagonize the yeast prion [URE3], it enhances propagation and phenotypic manifestation of another prion, [PSI+]. We demonstrate that both curing of [URE3] and enhancement of [PSI+] in the presence of excess Cur1 are counteracted by the cochaperone Hsp40‐Sis1 in a dosage‐dependent manner, and show that the effect of Cur1 on prions parallels effects of the attachment of nuclear localization signal to Sis1, indicating that Cur1 acts on prions via its previously reported ability to relocalize Sis1 from the cytoplasm to nucleus. This shows that the direction in which Cur1 influences a prion depends on how this specific prion responds to relocalization of Sis1.
A Discordant Monozygotic-Twin Approach to Potential Risk Factors for Chronic Widespread Pain in Females

Chronic widespread pain (CWP) is a common disorder affecting up to 15% of the general population. The objective of the present study was to explore the role of previously reported psychosocial and interpersonal risk factors on variation in CWP by investigating CWP discordant monozygotic (MZ) twins. This approach allows separation of cause and effect relationships, albeit imperfectly, as well the control for critical confounding variables such as common environment or genetics. In a total sample of N = 3,266 female twins aged 18–89 years, MZ (113 full pairs) and DZ twins (180 full pairs) discordant for CWP were selected. Items from the London fibromyalgia symptom screening questionnaire were used to discriminate cases from controls. To assess potential risk factors, including body mass index, anxiety sensitivity (AS), emotional intelligence, personality, obsessive-compulsive behavior, and coping, validated questionnaires were used. A set of univariate and multivariate logistic regression analyses were conducted. Of the variables showing significant links with CWP in the univariate individual-level analyses, including age, AS, and emotional intelligence, only emotional intelligence turned out to an independent predictor to the pathogenesis of CWP in both the individual level and discordant MZ analyses. These data indicate that in women having identical genetic risk, emotional intelligence seems to play a key role, although of small effect, in the development and/or maintenance of CWP. It further seems that many of the previously reported risk factors for CWP suffer from genetic confounding.
Calculation of Magnetic Flux Leakage and Loss of 220kV Transformer Based on MAGNET Field-Circuit Coupling

Magnetic flux leakage and loss of a transformer reduce the energy conversion efficiency of the transformer, also cause abnormal temperature distribution of the transformer. Studying magnetic flux leakage and loss of a transformer through measurement is a challenging task due to the difficulty of measuring magnetic flux leakage and loss. The finite element calculation makes up for the difficulty of measuring magnetic flux leakage and loss, which is very important for analyzing the magnetic flux leakage loss of a transformer. Based on the actual parameters, a refined three-dimensional(3D) modeling of 220kV three-phase three-winding on load tap-changer oil immersed power transformer in operation is established. The field circuit coupling finite element models of tank and turret are carried out by using professional electromagnetic simulation software MAGNET. Through setting impedance boundary conditions to improve the calculation speed, the distribution of magnetic flux leakage and loss of the transformer under high and medium voltage rated operating conditions is obtained by simulation. The results show that using MAGNET field-circuit coupling analysis can be used to quickly and efficiently calculate and analyze transformer magnetic flux leakage and loss.
Elevated CO2 affects embryonic development and larval phototaxis in a temperate marine fish

As an effect of anthropogenic CO2 emissions, the chemistry of the world's oceans is changing. Understanding how this will affect marine organisms and ecosystems are critical in predicting the impacts of this ongoing ocean acidification. Work on coral reef fishes has revealed dramatic effects of elevated oceanic CO2 on sensory responses and behavior. Such effects may be widespread but have almost exclusively been tested on tropical reef fishes. Here we test the effects elevated CO2 has on the reproduction and early life history stages of a temperate coastal goby with paternal care by allowing goby pairs to reproduce naturally in an aquarium with either elevated (ca 1400 μatm) CO2 or control seawater (ca 370 μatm CO2). Elevated CO2 did not affect the occurrence of spawning nor clutch size, but increased embryonic abnormalities and egg loss. Moreover, we found that elevated CO2 significantly affected the phototactic response of newly hatched larvae. Phototaxis is a vision-related fundamental behavior of many marine fishes, but has never before been tested in the context of ocean acidification. Our findings suggest that ocean acidification affects embryonic development and sensory responses in temperate fishes, with potentially important implications for fish recruitment.
3 D Indoor Mapping for Micro-UAVs Using Hybrid Range Finders and Multi-Volume Occupancy Grids

Autonomous micro-UAV navigation requires techniques that allow for the accurate mapping of unstructured 3D environments such as stairwells, tunnels, and caves. As a step towards that goal, this paper presents a system to build three-dimensional maps of rectilinear environments, where the horizontal cross-section of the world is invariant at different heights. The assumption that the environment is structured makes our approach suitable for mapping of indoor spaces. One of the largest challenges in 3D mapping is correctly estimating the full 6-DOF pose of the vehicle. We present an approach that estimates the pose by fusing the information of an altimeter, an IMU, and a horizontally-mounted laser range-finder. A key step in the estimation is an orthogonal projection of the laser scan data, allowing for accurate scan matching in 2D. We also propose a novel map data structure called a Multi-Volume Occupancy Grid. MVOGs explicitly store information about both obstacles and free space. This allows us to correct previous potentially erroneous sensor readings by incrementally fusing in new sensor information. In turn, this enables extracting more reliable probabilistic information about the occupancy of 3D space. Observations are grouped together into continuous vertical volumes, which makes this new data structure considerably more space-efficient than point cloud or voxel-grid representations.
Exploring Unsupervised Features in Conditional Random Fields for Spanish Named Entity Recognition

Unsupervised features such as word representations mostly given by word embeddings have been shown significantly improve semi supervised Named Entity Recognition (NER) for English language. In this work we investigate whether unsupervised features can boost (semi) supervised NER in Spanish. To do so, we use word representations and collocations as additional features in a linear chain Conditional Random Field (CRF) classifier. Experimental results (82.44% F-score on the CoNLL-2002 corpus and 65.72% F-score on Ancora Corpus) show that our approach is comparable to some state-of-art Deep Learning approaches for Spanish, in particular when using cross-lingual Word Representations.
An Intelligent Monitoring Method of Construction Progress of Power Transmission and Transformation Projects Based on Mask-RCNN

The timely and high-quality completion of PTT (power transmission and transformation, PTT) project construction has a decisive impact on the power supply quality and efficiency of the power system. So in the construction of PTT projects, we must do a good job in the management and control of construction efficiency and construction progress. The traditional mode of construction progress monitoring of PTT projects is mainly adopts the manual monitoring mode, which is time-consuming and labor-intensive. In order to realize the intelligent monitoring of construction progress of PTT projects, this study proposes an intelligent monitoring method of construction progress of PTT projects based on Mask-RCNN. This method first uses the marker recognition model based on Mask-RCNN to recognize the markers of key nodes in PTT projects, and then judges the construction progress according to the calculation rules for construction progress of PTT projects. We selected 21 kinds of PTT project markers to carry out experiments, and the results showed that the average accuracy of the marker recognition model based on Mask-RCNN can reach 92.16%, which effectively proved the effectiveness of the model. In addition, this article used the proposed method to analyze the construction progress of the Shiyan Hanshui 500kV PTT project, and the results showed that our method could effectively monitor the construction progress of the PTT project. It proved that our method had great application market and potential.
Intracerebroventricular Leptin Infusion Improves Glucose Homeostasis in Lean Type 2 Diabetic MKR Mice via Hepatic Vagal and Non-Vagal Mechanisms

MKR mice, lacking insulin-like growth factor 1 receptor (IGF-1R) signaling in skeletal muscle, are lean yet hyperlipidemic, hyperinsulinemic, and hyperglycemic, with severe insulin resistance and elevated hepatic and skeletal muscle levels of triglycerides. We have previously shown that chronic peripheral administration of the adipokine leptin improves hepatic insulin sensitivity in these mice independently of its effects on food intake. As central leptin signaling has been implicated in the control of peripheral glucose homeostasis, here we examined the ability of central intracerebroventricular leptin administration to affect energy balance and peripheral glucose homeostasis in non-obese diabetic male MKR mice. Central leptin significantly reduced food intake, body weight gain and adiposity, as well as serum glucose, insulin, leptin, free fatty acid and triglyceride levels relative to ACSF treated controls. These reductions were accompanied by increased fat oxidation as measured by indirect calorimetry, as well as increased oxygen consumption. Central leptin also improved glucose tolerance and hepatic insulin sensitivity determined using the euglycemic-hyperinsulinemic clamps relative to pair fed vehicle treated controls, as well as increasing the rate of glucose disappearance. Hepatic vagotomy only partially reversed the ability of central leptin to improve glucose tolerance. These results demonstrate that central leptin dramatically improves insulin sensitivity independently of its effects on food intake, in a lean mouse model of type 2 diabetes. The findings also suggest that: 1) both hepatic vagal and non-vagal pathways contribute to this improvement, and 2) central leptin alters glucose disposal in skeletal muscle in this model.
Fair Wages in a New Keynesian Model of the Business Cycle

We build a New Keynesian model of the business cycle with sticky prices and real wage rigidities motivated by efficiency wages of the gift exchange variety. Compared to a standard sticky price model, our Fair Wage model provides an explanation for structural unemployment and generates more plausible labor market dynamicsâânotably accounting for the low correlation between wages and employment. The fair wage induced real wage rigidity also significantly reduces the elasticity of marginal cost with respect to output. The smoother dynamics of real marginal cost increase both amplification and persistence of output responses to monetary shocks, thus remedying the well-known lack of internal propagation of standard sticky price models. We take these improvements as a strong endorsement of the addition of real wage rigidities to nominal price rigidities and conclude that the fair wage extension of this paper constitutes a promising platform for an enriched New Keynesian synthesis. (Copyright: Elsevier)
Enhancing Service Quality in Healthcare Systems Through Deep Learning

In recent years, there has been a growing need for effective system health management in various industries, including aerospace, manufacturing, and healthcare. The use of deep learning for the analysis and diagnosis of biomedical and healthcare problems has received unprecedented attention in the last decade. This technique has so far produced several achievements that have made it difficult to discover meaningful features by other methods and human experts as a promising approach to deal with these challenges. DL is a type of machine learning algorithm with multiple layers of similar functions stacked in the network and has the capability to create meaning from medical big data. These algorithms can learn to identify patterns indicative of diseases, helping physicians make more accurate diagnoses and potentially reducing errors. deep learning models can extract and classify relevant information from Electronic Health Records.
Brazilian Thalassemia Association protocol for iron chelation therapy in patients under regular transfusion

In the absence of an iron chelating agent, patients with beta-thalassemia on regular transfusions present complications of transfusion-related iron overload. Without iron chelation therapy, heart disease is the major cause of death; however, hepatic and endocrine complications also occur. Currently there are three iron chelating agents available for continuous use in patients with thalassemia on regular transfusions (desferrioxamine, deferiprone, and deferasirox) providing good results in reducing cardiac, hepatic and endocrine toxicity. These practice guidelines, prepared by the Scientific Committee of Associação Brasileira de Thalassemia (ABRASTA), presents a review of the literature regarding iron overload assessment (by imaging and laboratory exams) and the role of T2* magnetic resonance imaging (MRI) to control iron overload and iron chelation therapy, with evidence-based recommendations for each clinical situation. Based on this review, the authors propose an iron chelation protocol for patients with thalassemia under regular transfusions.
On computing quadratic controls for acyclic networks of heterogeneous systems

In this paper we consider the problem of computing finite-horizon quadratic optimal controls for a network of interconnected heterogeneous linear systems. We assume that the network is isomorphic to an acyclic directed graph and propose a solution to the problem via dynamic programming. This yields a finite sequence of smaller problems to be solved. Each smaller problem is associated with a node (or collection of such) in the network graph. It involves only local information and information from neighbours. As such, the solution algorithm lends itself to a distributed implementation. We numerically compare the performance of the proposed solution with computing the finite-horizon optimal controls by solving the global problem without exploiting structure.
NoCGEN:a template based reuse methodology for Networks On Chip architecture

In this paper, we describe NoCGEN, a Network On Chip (NoC) generator, which is used to create a simulatable and synthesizable NoC description. NoCGEN uses a set of modularised router components that can be used to form different routers with a varying number of ports, routing algorithms, data widths and buffer depths. A graph description representing the interconnection between these routers is used to generate a top-level VHDL description. A wormhole output-queued 2-D mesh router was created to verify the capability of NoCGEN. Various parameterized designs were synthesized to provide estimated gate counts of 129 K to 695 K for a number of topologies varying from a 2/spl times/2 mesh to a 4/spl times/4 mesh, with constant data bus size width of 32. The NoC was simulated with random traffic using a mixed SystemC/VHDL environment to ensure correctness of operation and to obtain performance and average latency. The results show an accepted load of 53% to 55.6% with an increase in buffer depth from 8 to 32 flits for the 4/spl times/4 mesh router.
Reduced Androgen Receptor Expression Accelerates the Onset of ERBB2 Induced Breast Tumors in Female Mice

Androgen receptor (AR) is commonly expressed in both the epithelium of normal mammary glands and in breast cancers. AR expression in breast cancers is independent of estrogen receptor alpha (ERα) status and is frequently associated with overexpression of the ERBB2 oncogene. AR signaling effects on breast cancer progression may depend on ERα and ERBB2 status. Up to 30% of human breast cancers are driven by overactive ERBB2 signaling and it is not clear whether AR expression affects any steps of tumor progression in this cohort of patients. To test this, we generated mammary specific Ar depleted mice (MARKO) by combining the floxed allele of Ar with the MMTV-cre transgene on an MMTV-NeuNT background and compared them to littermate MMTV-NeuNT, Arfl/+ control females. Heterozygous MARKO females displayed reduced levels of AR in mammary glands with mosaic AR expression in ductal epithelium. The loss of AR dramatically accelerated the onset of MMTV-NeuNT tumors in female MARKO mice. In this report we show that accelerated MMTV-NeuNT-dependent tumorigenesis is due specifically to the loss of AR, as hormonal levels, estrogen and progesterone receptors expression, and MMTV-NeuNT expression were similar between MARKO and control groups. MMTV-NeuNT induced tumors in both cohorts displayed distinct loss of AR in addition to ERα, PR, and the pioneer factor FOXA1. Erbb3 mRNA levels were significantly elevated in tumors in comparison to normal mammary glands. Thus the loss of AR in mouse mammary epithelium accelerates malignant transformation rather than the rate of tumorigenesis.
Cultivar, Season Extension, Fertilizer Trials of Swiss Chard and Pedagogy of Assessing Cultivars Using Technology

Diversity of species is a cornerstone of horticulture, and the constant stream of new plant cultivars broadens the palette of options available to the industry. Fifteen Swiss chard (Beta vulgaris var. cicla) cultivars were evaluated during the fall/winter of 2014-2015 season (season 1) and 27 cultivars during the fall/winter of 2015-2016 season (season 2) to determine the best performing cultivars for production and landscape use for east Texas and the southeast by assessing survivability and yield. There was an increase in production of 3.0 ± 0.5 g per plant per harvest under the low tunnel. The cultivar ‘Verde de Taglio’ had the best overall performance during season 1 both in covered and uncovered environments. In season 2, ‘Verde a Costa Blanca’ yielded the most uncovered. ‘Verde de Taglio’ yielded the most covered for this season. It is recommended to use the low tunnels to extend production. A trial was also conducted to determine optimum, pre-plant organic fertilizer amendment for container production of Swiss chard. Ten pre-plant organic fertilizers were compared against a control (Osmocote). There were no significant differences in dry weight, plant height, or plant width among the treatments suggesting all fertilizers were sufficient to produce Swiss chard ‘Prima Rosa’. In the 2016 spring and fall semesters, students in the Crop Science course (AGN 110) at SFASU were given an assignment where they were instructed to
Distributed Model Predictive Control of a Wind Farm for Optimal Active Power ControlPart I: Clustering-Based Wind Turbine Model Linearization

This paper presents a dynamic discrete-time piece-wise affine (PWA) model of a wind turbine for the optimal active power control of a wind farm. The control objectives include both the power reference tracking from the system operator and the wind turbine mechanical load minimization. Instead of partial linearization of the wind turbine model at selected operating points, the nonlinearities of the wind turbine model are represented by a piece-wise static function based on the wind turbine system inputs and state variables. The nonlinearity identification is based on the clustering-based algorithm, which combines the clustering, linear identification, and pattern recognition techniques. The developed model, consisting of 47 affine dynamics, is verified by the comparison with a widely used nonlinear wind turbine model. It can be used as a predictive model for the model predictive control (MPC) or other advanced optimal control applications of a wind farm.