Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiac Remodeling in Fish: Strategies to Maintain Heart Function during Temperature Change

Rainbow trout remain active in waters that seasonally change between 4°C and 20°C. To explore how these fish are able to maintain cardiac function over this temperature range we characterized changes in cardiac morphology, contractile function, and the expression of contractile proteins in trout following acclimation to 4°C (cold), 12°C (control), and 17°C (warm). The relative ventricular mass (RVM) of the cold acclimated male fish was significantly greater than that of males in the control group. In addition, the compact myocardium of the cold acclimated male hearts was thinner compared to controls while the amount of spongy myocardium was found to have increased. Cold acclimation also caused an increase in connective tissue content, as well as muscle bundle area in the spongy myocardium of the male fish. Conversely, warm acclimation of male fish caused an increase in the thickness of the compact myocardium and a decrease in the amount of spongy myocardium. There was also a decrease in connective tissue content in both myocardial layers. In contrast, there was no change in the RVM or connective tissue content in the hearts of female trout with warm or cold acclimation. Cold acclimation also caused a 50% increase in the maximal rate of cardiac AM Mg2+-ATPase but did not influence the Ca2+ sensitivity of this enzyme. To identify a mechanism for this change we utilized two-dimensional difference gel electrophoresis to characterize changes in the cardiac contractile proteins. Cold acclimation caused subtle changes in the phosphorylation state of the slow skeletal isoform of troponin T found in the heart, as well as of myosin binding protein C. These results demonstrate that acclimation of trout to warm and cold temperatures has opposing effects on cardiac morphology and tissue composition and that this results in distinct warm and cold cardiac phenotypes.
Journal of Cardiovascular Magnetic Resonance Open Access Quantitative Characterization of Myocardial Infarction by Cardiovascular Magnetic Resonance Predicts Future Cardiovascular Events in Patients with Ischemic Cardiomyopathy

Background: Cardiovascular magnetic resonance (CMR) can provide quantitative data of the myocardial tissue utilizing high spatial and temporal resolution along with exquisite tissue contrast. Previous studies have correlated myocardial scar tissue with the occurrence of ventricular arrhythmia. This study was conducted to evaluate whether characterization of myocardial infarction by CMR can predict cardiovascular events in patients with ischemic cardiomyopathy (ICM).
A detailed power model for field-programmable gate arrays

Power has become a critical issue for field-programmable gate array (FPGA) vendors. Understanding the power dissipation within FPGAs is the first step in developing power-efficient architectures and computer-aided design (CAD) tools for FPGAs. This article describes a detailed and flexible power model which has been integrated in the widely used Versatile Place and Route (VPR) CAD tool. This power model estimates the dynamic, short-circuit, and leakage power consumed by FPGAs. It is the first flexible power model developed to evaluate architectural tradeoffs and the efficiency of power-aware CAD tools for a variety of FPGA architectures, and is freely available for noncommercial use. The model is flexible, in that it can estimate the power for a wide variety of FPGA architectures, and it is fast, in that it does not require extensive simulation, meaning it can be used to explore a large architectural space. We show how the model can be used to investigate the impact of various architectural parameters on the energy consumed by the FPGA, focusing on the segment length, switch block topology, lookuptable size, and cluster size.
Topic Representation of Researchers' Interests in a Large-Scale Academic Database and Its Application to Author Disambiguation

It is crucial to promote interdisciplinary research and recommend collaborators from different research fields via academic database analysis. This paper addresses a problem to characterize researchers’ interests with a set of diverse research topics found in a large-scale academic database. Specifically, we first use latent Dirichlet allocation to extract topics as distributions over words from a training dataset. Then, we convert the textual features of a researcher’s publications to topic vectors, and calculate the centroid of these vectors to summarize the researcher’s interest as a single vector. In experiments conducted on CiNii Articles, which is the largest academic database in Japan, we show that the extracted topics reflect the diversity of the research fields in the database. The experiment results also indicate the applicability of the proposed topic representation to the author disambiguation problem. key words: researcher analysis, academic database, topic model, author disambiguation
Efficient unsupervised temporal segmentation of human motion

This work introduces an efficient method for fully automatic temporal segmentation of human motion sequences and similar time series. The method relies on a neighborhood graph to partition a given data sequence into distinct activities and motion primitives according to self-similar structures given in that input sequence. In particular, the fast detection of repetitions within the discovered activity segments is a crucial problem of any motion processing pipeline directed at motion analysis and synthesis. The same similarity information in the neighborhood graph is further exploited to cluster these primitives into larger entities of semantic significance. The elements subject to this classification are then used as prior for estimating the same target values for entirely unknown streams of data. The technique makes no assumptions about the motion sequences at hand and no user interaction is required for the segmentation or clustering. Tests of our techniques are conducted on the CMU and HDM05 motion capture databases demonstrating the capability of our system handling motion segmentation, clustering, motion synthesis and transfer-of-label problems in practice - the latter being an optional step which relies on the preexistence of a small set of labeled data.
A Hybrid Driving Simulator with Dynamics-Driven Motion and Data-Driven Motion

In driving simulator technology, which reproduces the sense of motion in a virtual reality environment, various research activities are attempting to enhance realism. Recently studies have focused on a data-driven method of generating motion; this method records the motions of real objects and regenerates them in a simulation system. By providing a simulator with real motion data, this method can easily guarantee realism without complicated dynamics models and equation solvers. This paper proposes a hybrid method of generating controllable motion in a driving simulator through the application of a data-driven motion generation method and a dynamics-based motion generation method. The driving data acquired from a real vehicle are parsed into motion blocks with a dynamic model of the vehicle; the motion blocks are then stored in the database. In real-time simulation, a natural motion stream is generated by a process of searching for and synthesizing optimal motion blocks from the database and is synthesized with dynamics-based motion again. A more realistic sense of motion can be generated by parameterizing the current simulation state and user requirements.
A Criterion and an Algorithm for Grouping Data

Many algorithms for grouping data without supervision depend on some criterion. We state two basic requirements such criteria should meet and we discuss several criteria in terms of these requirements. An attempt to satisfy both requirements simultaneously with a simple criterion leads us to introduce a linear transformation of the data. Although our principal result is for a two category problem, we present discussion and an example for the many category problem as well.
Distribution and morphology of synapses on nonspiking local interneurones in the thoracic nervous system of the locust

The structure and distribution of synapses on nonspiking local interneurones in the metathoracic ganglion of the locust was revealed by electron microscopy following intracellular injection of horseradish peroxidase (HRP). Before staining, each interneurone was characterized physiologically as nonspiking and its output effects on motor neurones innervating muscles in a hindleg were investigated. Three nonspiking interneurones of different morphologies, each typical of a previously described population, were selected for detailed study. The first has a dorsal soma and ipsilateral neuropilar branches, the second a ventral soma and ipsilateral branches, and the third a ventral soma and contralateral branches. The somata have few trophospongial invaginations, and most of their volume is occupied by the nucleus. The initial parts of the primary neurites are either wrapped in glia or isolated in tracts from the neuropile and thus do not participte in synaptic interactions. Some of the larger secondary neurites are also wrapped in glia, but others both make and receive synaptic contacts. Output synapses have an array of some 500–1,600 round, agranular vesicles (diameter 47.0 ± 5.7 nm; mean ± S.D., n = 97) associated with a bar‐shaped presynaptic density up to 0.3 μm long. Two postsynaptic processes, whose diameter can vary greatly, are usually associated with each presynaptic density. Processes making input synapses onto nonspiking local interneurones typically contain round, agranular vesicles and often make several contacts within a few microns. Serial reconstructions from one of the interneurones revealed input and output synapses intermingled on the larger processes with outputs dominating by a factor of 3:1, whereas on some of the thinner processes only input synapses are present. In the other two interneurones, however, both input and output synapses are present on the fine branches. No feature of the structure or distribution of synapses observed here on the nonspiking local interneurones distinguishes them from spiking neurones in the same ganglia.
Face Finder: Filtering a Large Face Database using Scars, Marks and Tattoos

Facial marks (e.g. moles, freckles, and scars) are soft biometric traits that have limited utility in uniquely identifying individuals. However, facial marks can still play a crucial role both in ﬁltering a large face gallery, as well as in distinguishing between ambiguous face comparisons such as identical twins. This research demonstrates that facial marks can indeed be used to speed up face matching and assist in individualizing identical twins. The facial mark detection process consists of two main stages: (i) Landmark detection using Active Shape Model (ASM) to represent face images in a common coordinate system, and (ii) a scale space extrema detection method to detect facial marks. All the detected marks are classiﬁed into six different types based on their morphology and color, and are encoded into a ﬁxed length feature vector to facilitate efﬁ-cient matching and retrieval. Experimental results on face retrieval using a mug shot data set consisting of 1,000 probe images (one per subject) and 100,000 gallery images (one per subject) demonstrate a signiﬁcant improvement in retrieval time with only a slight loss of matching accuracy. We also demonstrate a symbolic query based retrieval capability using the facial mark based indexing scheme. The symbolic queries can be constructed based on the morphology, color, and location of a mark. This will facilitate the face retrieval process when only a verbal description of the face is available instead of a the face image as a query. Additional experiments on a twin data set of 404 images collected from 178 identical twins (89 twin pairs) further demonstrates improvements in differentiating identical twins using face marks.
Do weekends or evenings matter in a pediatric intensive care unit?*

Objective: To assess what independent influence, if any, weekend or evening admission to a pediatric intensive care unit (PICU) staffed 24 hrs/day, 7 days/wk by in-house, board-certified pediatric intensivists might have on mortality. Design and Patients: A retrospective study of 5,968 consecutive admissions to the PICU from August 1996 to December 2003 for patients aged 0 days to 21 yrs. Setting: A single, 14-bed, multidisciplinary PICU at an academic medical center. Measurements: Standardized mortality ratios of observed-to-predicted mortality were derived with their corresponding p values. Multivariate logistic regression was used to test the independent effect of weekend admission, weekend discharge/death, and evening PICU admission on mortality for the entire sample and, separately, for only emergency admissions, controlling for other significant predictor variables or interaction terms. Results: Overall, crude mortality was significantly higher on the weekend (weekday, 2.2%; weekend, 5.0% [p = .0000]) and in the evening (day, 2.1%; evening, 3.8% [p = .0004]). Assessing the entire sample using multivariate logistic regression, neither weekend admission (p = .146), weekend discharge/death (p = .348), nor evening PICU admission (p = .711) showed a significant relationship with mortality controlling for other significant factors. Limiting the scope to the emergency admissions subset, neither weekend admission (p = .135), weekend discharge/death (p = .278), nor evening PICU admission (p = .867) were significant predictors of mortality. Weekend and evening admissions differed in important ways from weekday and daytime admissions, making simple comparisons of crude mortality rates inappropriate. Weekend and evening admissions were more likely to be emergency, nonoperative patients; have a lower Pediatric Risk of Mortality III score but have a higher overall predicted mortality risk; and differ in the distributions of patients by primary diagnosis. Conclusions: Using multivariate logistic regression to control for important clinical differences, neither weekend admission, weekend discharge/death, nor evening admission had a significant independent effect on mortality risk in the entire sample or for the emergency patient subset. Our findings are consistent with previous work demonstrating the benefit of intensive care units staffed 24 hrs/day, 7-days/wk by in-house, board-certified intensivists.
A20 Inhibits Cytokine-Induced Apoptosis and Nuclear Factor κB–Dependent Gene Activation in Islets

Insulin-dependent diabetes mellitus (IDDM) is an autoimmune disease resulting from apoptotic destruction of β cells in the islets of Langerhans. Low expression of antioxidants and a predilection to produce nitric oxide (NO) have been shown to underscore β cell apoptosis. With this perspective in mind, we questioned whether β cells could mount an induced protective response to inflammation. Here we show that human and rat islets can be induced to rapidly express the antiapoptotic gene A20 after interleukin (IL)-1β activation. Overexpression of A20 by means of adenovirus-mediated gene transfer protects islets from IL-1β and interferon γ–induced apoptosis. The cytoprotective effect of A20 against apoptosis correlates with and is dependent on the abrogation of cytokine-induced NO production. The inhibitory effect of A20 on cytokine-stimulated NO production is due to transcriptional blockade of inducible NO synthase (iNOS) induction; A20 inhibits the activation of the transcription factor nuclear factor κB at a level upstream of IκBα degradation. These data demonstrate a dual antiapoptotic and antiinflammatory function for A20 in β cells. This qualifies A20 as part of the physiological cytoprotective response of islets. We propose that A20 may have therapeutic potential as a gene therapy candidate to achieve successful islet transplantation and the cure of IDDM.
Approximate Counting and Quantum Computation

Motivated by the result that an ‘approximate’ evaluation of the Jones polynomial of a braid at a 5th root of unity can be used to simulate the quantum part of any algorithm in the quantum complexity class BQP, and results relating BQP to the counting class GapP, we introduce a form of additive approximation which can be used to simulate a function in BQP. We show that all functions in the classes #P and GapP have such an approximation scheme under certain natural normalizations. However, we are unable to determine whether the particular functions we are motivated by, such as the above evaluation of the Jones polynomial, can be approximated in this way. We close with some open problems motivated by this work.
Planktivorous feeding in calm and turbulent environments, with emphasis on copepods

ABSTFUCT Turbulence may enhance contact rates between planktonic predators and their prey We formulate slmple and general models of prey encounter rates, taklng into account the behaviours and motility patterns of both prey and predator as well as turbulent fluld motlon Uslng these models we determine the levels of turbulence (as clmipation rate) at which ambient fluid motlon is lmportant in enhancing prey encounter rates for vanous types of predators (e g ambush and cruise predators, suspension feeders) Generally, turbulence has the largest effect on prey encounters for predators with low motility and long reactlon distances Also, turbulence is most important for meso-sized (mm to cm) predators and insignificant for smaller and larger predators The effect of turbulence on copepods is specifically examined For copepods that establish feeding currents, turbulence is of minor importance, for ambush feeding copepods, such as Acartldae and many cyclopoids, turbulence has a dominant influence on prey encounter rates The effect on cruising predators is intermediate Application of the models to situations examined experimentally demonstrates a hlgh predictive performance Finally we explore and model the potentially negatlve effects of turbulence on copepod feedlng currents, prey perception and capture success At typical and even high turbulent lntenslties none of these IS slgnificantly affected
Spontaneous Reaction Silencing in Metabolic Optimization

Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances. Yet, the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood. Here we predict computationally and analytically that any organism evolving to maximize growth rate, ATP production, or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical nonoptimal states. The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all. We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity. Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways, shedding new light on microbial evolution, robustness, and versatility for the execution of specific biochemical tasks. In particular, the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function.
New buffer interlayer for improving device performances of organic small molecule solar cells

We investigate the effects of polytetrafluoroethylene (PTFE) on organic photovoltaic (OPV) devices with structure of ITO/PTFE/ poly(3,4-ethylenedioxythiophene):poly(styrene-sulfonate) (PEDOT:PSS)/copper phthalocyanine(CuPc)/C60/ bathocuproine(BCP)/Al by inserting thermally evaporated PTFE films between indium-tin-oxide (ITO) and PEDOT:PSS layers. Significant improvement in terms of open-circuit voltage, short-circuit current, and thereby in its commensurate power conversion efficiency is achieved compared to devices with PEDOT:PSS layers. The OPVs performance enhancement is attributed to the formation of an artificial dipole layer resulting from the rich, negatively charged fluorine that facilitates the hole extraction process.
The Neuroscience of Storing and Molding Tool Action Concepts: How “Plastic” is Grounded Cognition?

Choosing how to use tools to accomplish a task is a natural and seemingly trivial aspect of our lives, yet engages complex neural mechanisms. Recently, work in healthy populations has led to the idea that tool knowledge is grounded to allow for appropriate recall based on some level of personal history. This grounding has presumed neural loci for tool use, centered on parieto-temporo-frontal areas to fuse perception and action representations into one dynamic system. A challenge for this idea is related to one of its great benefits. For such a system to exist, it must be very plastic, to allow for the introduction of novel tools or concepts of tool use and modification of existing ones. Thus, learning new tool usage (familiar tools in new situations and new tools in familiar situations) must involve mapping into this grounded network while maintaining existing rules for tool usage. This plasticity may present a challenging breadth of encoding that needs to be optimally stored and accessed. The aim of this work is to explore the challenges of plasticity related to changing or incorporating representations of tool action within the theory of grounded cognition and propose a modular model of tool–object goal related accomplishment. While considering the neuroscience evidence for this approach, we will focus on the requisite plasticity for this system. Further, we will highlight challenges for flexibility and organization of already grounded tool actions and provide thoughts on future research to better evaluate mechanisms of encoding in the theory of grounded cognition.
An optimized design of distributed active transformer

A novel structure distributed active transformer (DAT), which significantly reduces the coupling from the DAT to the feed line is demonstrated. A grounded guard line is implemented to isolate the feed line from the magnetic field of the DAT. The measured result of the DAT on a GaAs substrate shows a 10.5-dB reduction in the coupling. To reduce DAT loss, an air-bridge connected double primary DAT structure is implemented. The DAT at 2 GHz shows a 0.7-dB loss reduction in comparison to the conventional DAT. The improved DAT performance is related to the reduced metal resistance and closer coupling between the primary and secondary loops without any increase in the DAT area.
A New Resonant Modular Multilevel Step-Down DC–DC Converter with Inherent-Balancing

Modular multilevel converters (MMCs) have become increasingly interesting in dc-dc applications, as there is a growing demand for dc-dc converters in high-voltage applications. Power electronics transformers can be used for high step-down ratio dc-dc power conversion, with high power rating and efficiency achieved. However, this arrangement requires a large number of high isolation voltage transformers and a complicated balancing control scheme. To provide a simple solution with inherent voltage balancing, this paper presents a new resonant MMC topology for dc-dc conversion. The proposed converter achieves high-voltage step-down ratio depending on the number of submodules. The converter also exhibits simplicity and scalability with no necessary requirement of high-voltage isolation transformers. By using phase-shift control, a much higher converter operating frequency is achieved compared to the switching frequency. Resonant conversion is achieved between the series inductor and submodule capacitors. The operation principle and theoretical analysis are presented in this paper, which have been verified by experimental results based on a bench-scale prototype.