Miracle-dz/UniFAR-FTUs huggingface dataset:
Associations of Serum Liver Function with Cerebral Blood Flow in Patients with Alzheimer’s Disease

Background: Increasing evidence suggests that both amyloid-β metabolism disorders in the liver and cerebral hypoperfusion play an important role in the pathogenesis of Alzheimer’s disease (AD). However, the relevance of liver function alterations to cerebral blood flow (CBF) of patients with AD remains unclear. Objective: We aimed to investigate the associations between liver function changes and CBF of patients with AD. Methods: We recruited 17 patients with sporadic AD. In addition to physical and neurological examinations, detection of AD biomarkers in cerebrospinal fluid by enzyme-linked immunosorbent assay and CBF assessment by arterial spin labeling sequence of magnetic resonance image scans as well as measure of liver function markers in serum by routine laboratory testing were conducted. Neuropsychological tests were evaluated, including Mini-Mental State Examination and Montreal Cognitive Assessment. Linear and rank correlations were performed to test the associations of liver function alterations with regional CBF of AD. Results: We found that liver function markers, especially total protein, the ratio of albumin to globin, globin, alkaline phosphatase, and aspartate aminotransferase were significantly associated with regional CBF of AD patients. Conclusions: These findings demonstrated significant associations between perfusion in certain brain regions of AD and alterations of liver function markers, particularly proteins and liver enzymes, which might provide implications to the pathogenesis and treatment of AD.
Molecular Mechanism of Taurocholate Transport by the Bile Salt Export Pump, an ABC Transporter Associated with Intrahepatic Cholestasis

The bile salt export pump (BSEP/ABCB11) transports bile salts from hepatocytes into bile canaliculi. Its malfunction is associated with severe liver disease. One reason for functional impairment of BSEP is systemic administration of drugs, which as a side effect inhibit the transporter. Therefore, drug candidates are routinely screened for potential interaction with this transporter. Hence, understanding the functional biology of BSEP is of key importance. In this study, we engineered the transporter to dissect interdomain communication paths. We introduced mutations in noncanonical and in conserved residues of either of the two nucleotide binding domains and determined the effect on BSEP basal and substrate-stimulated ATPase activity as well as on taurocholate transport. Replacement of the noncanonical methionine residue M584 (Walker B sequence of nucleotide binding site 1) by glutamate imparted hydrolysis competency to this site. Importantly, this mutation was able to sustain 15% of wild-type transport activity, when the catalytic glutamate of the canonical nucleotide binding site 2 was mutated to glutamine. Kinetic modeling of experimental results for the ensuing M584E/E1244Q mutant suggests that a transfer of hydrolytic capacity from the canonical to the noncanonical nucleotide binding site results in loss of active and adoption of facilitative characteristics. This facilitative transport is ATP-gated. To the best of our knowledge, this result is unprecedented in ATP-binding cassette proteins with one noncanonical nucleotide binding site. Our study promotes an understanding of the domain interplay in BSEP as a basis for exploration of drug interactions with this transporter.
Automatic Selection of Machine Learning Models for Compiler Heuristic Generation

Machine learning has shown its capabilities for an automatic gen- eration of heuristics used by optimizing compilers. The advantages of these heuristics are that they can be easily adopted to a new environment and in some cases outperform hand-crafted compiler optimizations. However, this approach shifts the effort from manual heuristic tuning to the model selection problem of machine learning - i.e., selecting learning algorithms and their respective parameters - which is a tedious task in its own right. In this paper, we tackle the model selection problem in a systematic way. As our experiments show, the right choice of a learning algorithm and its parame- ters can significantly affect the quality of the generated heuristics. We present a generic framework integrating machine learning into a compiler to enable an automatic search for the best learning algorithm. To find good settings for the learner parameters within the large search space, optimizations based on evolu- tionary algorithms are applied. In contrast to the majority of other approaches aiming at a reduction of the average-case execution time (ACET), our goal is the minimization of the worst-case execution time (WCET) which is a key pa- rameter for embedded systems acting as real-time systems. A careful case study on the heuristic generation for the well-known optimization loop invariant code motion shows the challenges and benefits of our methods.
Framing and stakes: A survey study of decisions under uncertainty

Using a survey study of 261 decisions under uncertainty, we explore the factors that explain risk taking behavior and those that predict the importance of a decision. We also examine the relationship between framing and status quo, the similarity between monetary and non-monetary decisions, as well as the similarities and differences among our three subject groups (Undergraduates, MBAs and Executives). We find that framing, domain, and probability of success have a strong influence on the probability of taking risks. Other factors, such as group, importance of a decision, and whether the consequences are monetary or not, do not seem to influence risk attitudes. Our analysis of importance of a decision highlights the frequency with which a decision is taken as a key variable. Our results suggest that the cumulative effects of unimportant and frequent decisions are greater than the cumulative effects of very important and infrequent decisions.
An improved signal-selective direction finding algorithm using second-order cyclic statistics

A new signal-selective direction finding algorithm which exploits the property of the cyclostationarity of incoming signals is proposed. After dimensionality reducing by projecting the observed array data onto the signal subspace, the array manifold matrix is identified by the simultaneous diagonalization structure of the matrix pencil consisting of the cyclic correlation matrix and the cyclic conjugate correlation matrix. Then the direction-of-arrivals (DOAs) are obtained from the phase-differences of the estimated array manifold matrix. Simulation results demonstrate that the proposed algorithm is superior to the cyclic-MUSIC and cyclic-ESPRIT in terms of the root mean squares errors (RMSEs) of the DOA estimates.
Regulation of Banana Phytoene Synthase (MaPSY) Expression, Characterization and Their Modulation under Various Abiotic Stress Conditions

Phytoene synthase (PSY) is a key regulatory enzyme of carotenoid biosynthesis pathway in plants. The present study examines the role of PSY in carotenogenesis and stress management in banana. Germplasm screening of 10 Indian cultivars showed that Nendran (3011.94 μg/100 g dry weight) and Rasthali (105.35 μg/100 g dry weight) contained the highest and lowest amounts of β-carotene, respectively in ripe fruit-pulp. Nendran ripe pulp also showed significantly higher antioxidant activity as compared to Rasthali. Meta-analysis of three banana PSY genes (MaPSY1, MaPSY2, and MaPSY3) was performed to identify their structural features, subcellular, and chromosomal localization in banana genome. The distinct expression patterns of MaPSY1, MaPSY2, and MaPSY3 genes were observed in various tissues, and fruit developmental stages of these two contrasting cultivars, suggesting differential regulation of the banana PSY genes. A positive correlation was observed between the expression of MaPSY1 and β-carotene accumulation in the ripe fruit-peel and pulp of Nendran. The presence of stress responsive cis-regulatory motifs in promoter region of MaPSY genes were correlated with the expression pattern during various stress (abscisic acid, methyl jasmonate, salicylic acid and dark) treatments. The positive modulation of MaPSY1 noticed under abiotic stresses suggested its role in plant physiological functions and defense response. The amino acid sequence analysis of the PSY proteins in contrasting cultivars revealed that all PSY comprises conserved domains related to enzyme activity. Bacterial complementation assay has validated the functional activity of six PSY proteins and among them PSY1 of Nendran (Nen-PSY1) gave the highest activity. These data provide new insights into the regulation of PSY expression in banana by developmental and stress related signals that can be explored in the banana improvement programs.
Minerva scene analysis benchmark

The analysis of natural scenes is an important research area. Scene analysis research provides the foundation for the development of autonomous systems whose vision sensors provide important information about the surrounding environment. In this paper we introduce the Minerva scene analysis benchmark to the vision community and provide preliminary results on this data. The scene analysis benchmark contains 448 natural images in both colour and greyscale format. The images contain 8 natural objects including sky, brick, clouds, pebbles, road, trees, grass and leaves. The benchmark is intended to facilitate further research into scene analysis and to encourage the development of tools and techniques that work on natural object recognition. The results reported here have used four image segmentation techniques including fuzzy c-means clustering, histogram based thresholding, region growing, and split and merge. Following segmentation, texture features for object classification have been generated using five different texture analysis methods including autocorrelation, co-occurrence matrices, edge frequency, Law's, and run length. These results can be taken as a preliminary baseline on this benchmark.
Political ideology and American intergroup discrimination: A patriotism perspective

ABSTRACT In this research we demonstrate the powerful role of ingroup favoritism, rather than hostility, in American intergroup biases. Specifically, we take a novel perspective to understanding the relationship between political ideology and discrimination against ethnic-minority Americans by focusing on the role of patriotism. Across three studies, we show that political ideology is a strong predictor of resource allocation biases, and this effect is mediated by American patriotism and not by prejudice or nationalism. Conservatives report greater levels of patriotism than liberals, and patriotism is associated with donating more to American, as opposed to ethnic-minority American, organizations. We further show that the link between patriotism and partiality to the national group is mediated by stronger “American = White” associations. These findings have important implications for intergroup relations and diversity-related policy issues in the United States.
Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL

The goal of transfer learning is to use the knowledge acquired in a set of source tasks to improve performance in a related but previously unseen target task. In this paper, we present a multilayered architecture named CAse-Based Reinforcement Learner (CARL). It uses a novel combination of Case-Based Reasoning (CBR) and Reinforcement Learning (RL) to achieve transfer while playing against the Game AI across a variety of scenarios in MadRTSTM, a commercial Real Time Strategy game. Our experiments demonstrate that CARL not only performs well on individual tasks but also exhibits significant performance gains when allowed to transfer knowledge from previous tasks.
This Work Is Licensed under a Creative Commons Attribution 4.0 International License Free-living Gait Characteristics in Ageing and Parkinson's Disease: Impact of Environment and Ambulatory Bout Length

distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver Abstract Background: Gait is emerging as a powerful diagnostic and prognostic tool, and as a surrogate marker of disease progression for Parkinson's disease (PD). Accelerometer-based body worn monitors (BWMs) facilitate the measurement of gait in clinical environments. Moreover they have the potential to provide a more accurate reflection of gait in the home during habitual behaviours. Emerging research suggests that measurement of gait using BWMs is feasible but this has not been investigated in depth. The aims of this study were to explore (i) the impact of environment and (ii) ambulatory bout (AB) length on gait characteristics for discriminating between people with PD and age-matched controls.
Erasure codes in big data era

Data continues to explode exponentially in big data era, making the 3-replication scheme unaffordably expensive and space-consuming for a storage system. To this end, erasure code schemes prevail by offering the same or higher reliability at a relatively lower spatial cost. In this paper, an overview of up-to-date research work of erasure codes in big data era is presented. Additionally, we identify some problems of recent work and attempt to share our insights about possible future work of erasure codes.
Aboveground Carbon Storage and Net Primary Production in Human Impacted Forests Under Current and Future Climate Scenarios

CHIANG, JYH-MIN, Ph.D., March 2007, Environmental and Plant Biology ABOVEGROUND CARBON STORAGE AND NET PRIMARY PRODUCTION IN HUMAN IMPACTED FORESTS UNDER CURRENT AND FUTURE CLIMATE SCENARIOS (247 pp.) Director of Dissertation: Kim J. Brown Forested ecosystems contain the largest terrestrial carbon pools and fluxes on earth. Thus, forest ecosystem disturbances can result in large perturbations in global carbon cycling and subsequently climate. The objective of my dissertation was to investigate the role of forest burning and thinning, changing climate, and changing species compositions on carbon cycling in a subset of forests in the eastern United States. I examined processes that influenced net primary production (NPP) of forested ecosystems at different scales: First, I examined the sensitivity of budburst phenology on simulations of NPP and, based on the Harvard Forest phenology database, I optimized a subroutine, which included a chilling factor, for the prediction of budburst dates. Budburst phenology was a sensitive variable in PnET model simulations but leaf-off date was not. The phenology subroutine, when applied to southern Ohio forests, exhibited geographic specificity, highlighting the importance of local phenological data. Second, I examined the effects of mechanical thinning, prescribed burning, and multiple environmental factors on specific leaf weight (SLW) and leaf nitrogen content (Nmass) of seven common tree species. Increases in both leaf traits were positively associated with increases in potential NPP. Thinning increased SLW at the lower canopy by 22% and resulted in an 8% increase of modeled NPP. The effects of burning were not significant. Variations of both leaf traits were primarily explained by species differences. Third, I assessed the impacts of thinning and burning on aboveground carbon stocks and NPP using both field measurements and PnET model simulations in southern Ohio. Only thinning affected NPP (> -30%); however, the thinning effect on NPP was transient (1-2 years) according to both field and model results. Lastly, at a larger spatio-temporal scale, I used the PnET-II model to simulate the NPP consequences of potential tree species redistribution and future climate in four selected focal areas (40,000 km each). The effects of potential species redistribution predicted in 2100 had moderate effects (-12% to 8%) on NPP compared to the impacts of future climatic change (-60% to 25%). As increasing temperatures negatively impact NPP, the reduction in forest carbon uptake capacity could accelerate changing climate. Approved: Kim J. Brown Assistant Professor of Environmental and Plant biology
A Design Framework for Highly Concurrent Systems

Building highly concurrent systems, such as large-scale Internet services, requires managing many information flows at once and maintaining peak throughput when demand exceeds resource availability. In addition, any platform supporting Internet services must provide high availability and be able to cope with burstiness of load. Many approaches to building concurrent systems have been proposed, which generally fall into the two categories of threaded and event-driven programming. We propose that threads and events are actually on the ends of a design spectrum, and that the best implementation strategy for these applications is somewhere in between. We present a general-purpose design framework for building highly concurrent systems, based on three design components -- tasks, queues, and thread pools -- which encapsulate the concurrency, performance, fault isolation, and software engineering benefits of both threads and events. We present a set of design patterns that can be applied to map an application onto an implementation using these components. In addition, we provide an analysis of several systems (including an Internet services platform and a highly available, distributed, persistent data store) constructed using our framework, demonstrating its benefit for building and reasoning about concurrent applications.
Change of stress patterns during 2004 MW 9.3 off‐Sumatra mega‐event: Insights from ridge–trench interaction for plate margin deformation

The Andaman–Sumatra subduction margin is identified as a complex tectonic transition zone between the Myanmar and Java regions. The Late Cenozoic evolution of various basins, faults, plate slivers, and the Andaman back‐arc rift‐transform system altered the boundary. The sharp changes in free air gravity anomaly, north‐eastward swing of the Andaman Sea spreading ridge, increased dip of the subducting plate and the decrease in seismicity towards the north of the study area possibly account for increased interaction of the Ninetyeast Ridge (NER) against the Andaman Trench. Stress fields of the subducting plate were modified from semi‐radial compression (SRC) during pre‐seismic deformation to pure extension (PE), semi‐radial extension (SRE), and strike‐slip extension (SSE) during post‐seismic deformation phase in the central segment. The co‐seismic second energy burst, subsidence in the overriding plate, and subsequent reactivation of the Barren and Narcondum volcanoes also corroborate the transformation of the stress fields in the overriding plate into predominant extension. The dominant SRC stress in the subducting Indo‐Australian lithosphere in the south changed to pure compression (PC) prior to the 2004 MW 9.3 mega‐event. While the changes in stress field from SRC to pure strike‐slip (PSS) in the north account for stress relaxation after the occurrence of the mega‐event and the co‐seismic ~1,300‐km rupturing, the occurrences of uplift and subsidence in the northern part of the study area were possibly caused by inherited stress field from the Eastern Himalaya. The continued overall compression in the subducting Indo‐Australian Plate in the south, under pre‐ and post‐seismic deformation phases, is presumably correlated with the focal mechanism stress parameters of the 2004 mega‐event, whereas the strike‐slip‐dominated movement in the overriding plate remained almost unchanged. The stress perturbations in the central segment are interpreted to be the result of interaction between the NER and Andaman–Sumatra Trench.
Predictive Adaptive Responses to Maternal High-Fat Diet Prevent Endothelial Dysfunction but Not Hypertension in Adult Rat Offspring

Background—Population-based studies suggest that fetal adaptive responses to maternal dietary imbalance confer survival benefit when the postnatal diet remains suboptimal but increase susceptibility to cardiovascular disease when postnatal nutrition is improved. We have investigated “predictive adaptive” responses in a rodent model in which adult offspring of fat-fed dams develop characteristics of the metabolic syndrome. Methods and Results—Sprague-Dawley rats were fed a fat-rich diet or normal chow throughout pregnancy and weaning. Vascular endothelial function and blood pressure were determined in 180-day-old offspring of fat-fed dams raised on standard chow (FC) or on the fat-rich diet (FF) and in offspring of chow-fed dams raised on chow (CON). Small mesenteric artery endothelium-dependent dilation to acetylcholine was impaired in male and female FC (by ANOVA, P<0.001 versus CON) but similar to CON in FF (P=NS). Blood glucose was lower in FF versus FC. Heart rate was reduced in male FC versus CON (P<0.05) but not in FF. Plasma triglyceride concentrations were reduced in male FF compared with CON (P<0.05). Blood pressure was raised in female FC (systolic, 132.5±3.0 mm Hg versus CON, 119.0±3.8 mm Hg, P<0.05; diastolic, 91.2±1.7 mm Hg versus CON, 81.1±1.4 mm Hg, P<0.05) and in female FF (systolic, 132.5±4.2 mm Hg versus CON, P<0.05; diastolic, 91.0±1.9 mm Hg versus CON, P<0.05). Blood pressure was similar to CON in male FC and FF. Conclusions—Predictive adaptive responses prevent endothelial dysfunction and reduced heart rate in offspring of fat-fed dams if offspring are raised on the same diet but do not prevent development of raised blood pressure.
Since the analysis focuses on the high-SNR regime , the following asymptotic relation notation [ 15 ]

The recently established diversity-multiplexing frontier characterizes the highSNR tradeoff between the best possible robustness and throughput gains obtainable by employing multiple antennas for digital communication in fading environments. We focus on the case of two transmit and at least two receive antennas, and show that a sufficient condition for a family of codebooks indexed by rate to achieve the full diversity-multiplexing frontier is that the worst-case codeword difference determinant either does not decay to zero with rate or decays subexponentially. We further provide a constructive proof that the full frontier is achievable by codes of length two by developing families of rotation-based space-time block codes with rate-independent nonzero worst-case determinants. These determinants are optimized over reasonably rich code subspaces. By contrast, Gaussian codes of this length were known not to achieve the frontier, and earlier rotation-based codes were known only to achieve the extremal points of the frontier. Simulation results also verify that the new codes have sufficient coding gain to achieve error rates close enough to the infinite length code outage bound, and thus they provide superior performance to Alamouti’s orthogonal space-time block code at spectral efficiencies beyond about 4 b/s/Hz.
An Efficient Compiler for Weighted Rewrite Rules

Context-dependent rewrite rules are used in many areas of natural language and speech processing. Work in computational phonology has demonstrated that, given certain conditions, such rewrite rules can be represented as finite-state transducers (FSTs). We describe a new algorithm for compiling rewrite rules into FSTs. We show the algorithm to be simpler and more efficient than existing algorithms. Further, many of our applications demand the ability to compile weighted rules into weighted FSTs, transducers generalized by providing transitions with weights. We have extended the algorithm to allow for this.