Miracle-dz/UniFAR-FTUs huggingface dataset:
Lowering Body Weight in Obese Mice With Diastolic Heart Failure Improves Cardiac Insulin Sensitivity and Function: Implications for the Obesity Paradox

Recent studies suggest improved outcomes and survival in obese heart failure patients (i.e., the obesity paradox), although obesity and heart failure unfavorably alter cardiac function and metabolism. We investigated the effects of weight loss on cardiac function and metabolism in obese heart failure mice. Obesity and heart failure were induced by feeding mice a high-fat (HF) diet (60% kcal from fat) for 4 weeks, following which an abdominal aortic constriction (AAC) was produced. Four weeks post-AAC, mice were switched to a low-fat (LF) diet (12% kcal from fat; HF AAC LF) or maintained on an HF (HF AAC HF) for a further 10 weeks. After 18 weeks, HF AAC LF mice weighed less than HF AAC HF mice. Diastolic function was improved in HF AAC LF mice, while cardiac hypertrophy was decreased and accompanied by decreased SIRT1 expression, increased FOXO1 acetylation, and increased atrogin-1 expression compared with HF AAC HF mice. Insulin-stimulated glucose oxidation was increased in hearts from HF AAC LF mice, compared with HF AAC HF mice. Thus lowering body weight by switching to LF diet in obese mice with heart failure is associated with decreased cardiac hypertrophy and improvements in both cardiac insulin sensitivity and diastolic function, suggesting that weight loss does not negatively impact heart function in the setting of obesity.
Prolonged Bioluminescence Monitoring in Mouse Ex Vivo Bone Culture Revealed Persistent Circadian Rhythms in Articular Cartilages and Growth Plates

The bone is a metabolically active organ which undergoes repeated remodeling cycles of bone resorption and formation. In this study, we revealed a robust and extremely long-lasting circadian rhythm in ex vivo culture maintained for over six months from the femoral bone of a PERIOD2Luciferase mouse. Furthermore, we also identified robust circadian clocks in flat bones. High- or low-magnification real-time bioluminescence microscopic imaging revealed that the robust circadian rhythms emanated from the articular cartilage and the epiphyseal cartilage within the growth plate of juvenile animals. Stimulation by forskolin or dexamethasone treatment caused type 0 phase resetting, indicating canonical entraining properties of the bone clock. Together, our findings from long-term ex vivo culture revealed that “tissue-autonomous” circadian rhythm in the articular cartilage and the growth plate of femoral bone functions for several months even in an organ culture condition, and provided a useful in vitro assay system investigating the role of the biological clock in bone formation or development.
Generation of multivariate scenario trees to model stochasticity in power management

Modern electricity portfolio and risk management models represent multistage stochastic programs. The input of such programs consists in a finite set of scenarios having the form of a scenario tree. They model the probabilistic information on random data (electrical load, stream flows to hydro units, market prices of fuel and electricity). Since the corresponding deterministic equivalents of multistage stochastic programs are mostly large scale, one has to find significant tree-structured scenarios. Our approach to generate multivariate scenario trees is based on recursive deletion and bundling of scenarios out of some given (possibly large) scenario set originating from historical or simulated data. The procedure makes use of certain Monge-Kantorovich transportation distances for multivariate probability distributions. We report on computational results for generating load-inflow scenario trees based on realistic data of EDF Electricite de France.
Open questions in the study of population III star formation

Abstract The first stars were key drivers of early cosmic evolution. We review the main physical elements of the current consensus view, positing that the first stars were predominantly very massive. We continue with a discussion of important open questions that confront the standard model. Among them are uncertainties in the atomic and molecular physics of the hydrogen and helium gas, the multiplicity of stars that form in minihalos, and the possible existence of two separate modes of metal-free star formation.
AutoCSP: Automatically Retrofitting CSP to Web Applications

Web applications often handle sensitive user data, which makes them attractive targets for attacks such as cross-site scripting (XSS). Content security policy (CSP) is a content-restriction mechanism, now supported by all major browsers, that offers thorough protection against XSS. Unfortunately, simply enabling CSP for a web application would affect the application's behavior and likely disrupt its functionality. To address this issue, we propose AutoCSP, an automated technique for retrofitting CSP to web applications. AutoCSP (1) leverages dynamic taint analysis to identify which content should be allowed to load on the dynamically-generated HTML pages of a web application and (2) automatically modifies the server-side code to generate such pages with the right permissions. Our evaluation, performed on a set of real-world web applications, shows that AutoCSP can retrofit CSP effectively and efficiently.
Reverse Analysis and Vulnerability Detection for Network System Software

In information era advocating ubiquitous computing, computing resources are susceptible to attack without guaranteeing security of network system. It is necessary and desirable for network system to employ powerful safeguard to protect itself against diversified vulnerabilities. In this paper, we present reverse analysis and vulnerability detection for network system software (RAVDNSS), a novel approach which uses reverse analysis and vulnerability detection technologies to deal with security problems on critical network system. Adaptive reverse analysis we propose is used to dig out potential vulnerabilities, which might be abused by unauthorized and unlawful communities. A new vulnerability detection model is designed to provide safety precautions through detecting vulnerabilities and monitoring program behaviors. Our investigation aims to improve the ability to guard network system against malicious attacks. The proposed schemes demonstrate that our approach can effectively perform security detection and management of network system software.
CRISPR / Cas-mediated gene editing of retinal cells in vivo .

PURPOSE: CRISPR/Cas has recently been adapted to enable efficient editing of the mammalian genome, opening novel avenues for therapeutic intervention of inherited diseases. In seeking to disrupt Yellow Fluorescent Protein (YFP) in a Thy1-YFP transgenic mouse, we assessed the feasibility of utilising the adeno-associated virus 2 (AAV2) to deliver CRISPR/Cas for genome modification of retinal cells in vivo. METHODS: sgRNA plasmids were designed to target YFP and after in vitro validation, selected guides were cloned into a dual AAV system. One AAV2 construct was used to deliver SpCas9 and the other delivered sgRNA against YFP or LacZ (control) in the presence of mCherry. Five weeks after intravitreal injection, retinal function was determined using electroretinography and CRISPR/Casmediated gene modifications were quantified in retinal flat mounts. RESULTS: AAV2-mediated in vivo delivery of SpCas9 with sgRNA targeting YFP, significantly reduced the number of YFP fluorescent cells of the inner retina of our transgenic mouse model. Overall, we found an 84.0% (95% CI: 81.8-86.9) reduction of YFP-positive cells in YFP-sgRNA infected retinal cells compared to eyes treated with LacZ-sgRNA. Electroretinography profiling found no significant alteration in retinal function following AAV2-mediated delivery of CRISPR/Cas components compared to contralateral untreated eyes. CONCLUSIONS: Thy1-YFP transgenic mice were used as a rapid quantifiable means to assess the efficacy of CRISPR/Cas-based retinal gene modification in vivo. We demonstrate that genomic modification of cells in the adult retina can be readily achieved by viral mediated delivery of
Design space exploration for 3D-stacked DRAMs

3D integration based on TSV (through silicon via) technology enables stacking of multiple memory layers and has the advantage of higher bandwidth at lower energy consumption for the memory interface. As in mobile applications energy efficiency is key, 3D integration is especially here a strategic technology. In this paper we focus on the design space exploration of 3D-stacked DRAMs with respect to performance, energy and area efficiency for densities from 256Mbit to 4Gbit per 3D-DRAM channel. We investigate four different technology nodes from 75nm down to 45nm and show the optimal design point for the currently most common commodity DRAM density of 1Gbit. Multiple channels can be combined for main memory sizes of up to 32GB. We present a functional SystemC model for the 3D-stacked DRAM which is coupled with a SDR/DDR 3D-DRAM channel controller. Parameters for this model were derived from detailed circuit level simulations. The exploration demonstrates that an optimized 1Gbit 3D-DRAM stack is 15× more energy efficient compared to a commodity Low-Power DDR SDRAM part without IO drivers and pads. To the best of our knowledge this is the first design space exploration for 3D-stacked DRAM considering different technologies and real world physical commodity DRAM data.
The Truth about Burnout: How Organizations Cause Personal Stress and What to Do about It

1. The Current Crisis. 2. How You Experience Burnout. 3. What Causes Burnout? 4. Why Do Anything About Burnout? 5. Crisis Intervention to Stop Burnout. 6. Preventing Burnout and Building Engagement. 7. Promoting Human Values. Afterword: Moving Toward a Better Future. Appendix: Assessing the Work Environment.
A public key compression method for Fully Homomorphic Encryption using Genetic Algorithms

The Fully Homomorphic Encryption (FHE) is an encryption technique for processing encrypted data without the need of decrypting them. This method is suitable for use in untrusted environments, such as cloud computing platforms. Various methods have been proposed to implement this technique. But the greatest problem of these methods is that for its operation, there is the need to generate public keys with large sizes, whose immediate consequence is to cause such encryption schemes not reach the desired runtime performance. This article aims to optimize public keys compression techniques using Genetic Algorithms (GA) for parameter calibration of Coron test variants primitives in order to speed up the execution time of each of these primitives.
Strings with Maximally Many Distinct Subsequences and Substrings

A natural problem in extremal combinatorics is to maximize the number of distinct subsequences for any length-$n$ string over a finite alphabet $\Sigma$; this value grows exponentially, but slower than $2^n$. We use the probabilistic method to determine the maximizing string, which is a cyclically repeating string. The number of distinct subsequences is exactly enumerated by a generating function, from which we also derive asymptotic estimates. For the alphabet $\Sigma=\{1,2\}$, $\,(1,2,1,2,\dots)$ has the maximum number of distinct subsequences, namely ${\rm Fib}(n+3)-1 \sim \left((1+\sqrt5)/2\right)^{n+3} \! / \sqrt{5}$. We also consider the same problem with sub strings in lieu of sub sequences . Here, we show that an appropriately truncated de Bruijn word attains the maximum. For both problems, we compare the performance of random strings with that of the optimal ones.
Why Is HTTP Adaptive Streaming So Hard?

HTTP adaptive streaming is increasingly popular in video delivery. This is mainly because HTTP allows easy deployment while it simplifies content delivery, and chunk-based delivery enables dynamic adaptation of video quality to varying network bandwidth. However, we find that the very nature of chunk delivery on HTTP causes some fundamental problems in efficient bandwidth utilization. In this work, we investigate why it is so hard to adapt to varying bandwidth with HTTP adaptive streaming. First, we find that the choice of chunk duration greatly affects the bandwidth adaptation logic. Second, we observe that the disparity between the advertised quality of a chunk and real encoding rate confuses the client-side adaptation logic. Third, the dependence on TCP/HTTP leads to suboptimal bandwidth utilization while it makes it challenging to adapt to rapidly-changing bandwidth. We show the evidence of the problems in our controlled experiments with popular HTTP adaptive streaming schemes, and lay out the future requirements for robust bandwidth adaptation in video streaming.
Fast Algorithms for Numerical, Conservative, and Entropy Approximations of the Fokker-Planck-Landau Equation

We present fast numerical algorithms to solve the nonlinear Fokker? Planck? Landau equation in 3D velocity space. The discretization of the collision operator preserves the properties required by the physical nature of the Fokker? Planck? Landau equation, such as the conservation of mass, momentum, and energy, the decay of the entropy, and the fact that the steady states are Maxwellians. At the end of this paper, we give numerical results illustrating the efficiency of these fast algorithms in terms of accuracy and CPU time.
Irregular Signal Constellations, Mappings and Precoder

This paper investigates adaptive bit-interleaved coded modulation (BICM) with different iterative decoding schemes for bandwidth efficient transmission. We assume knowledge of the average channel quality at the transmitter. For a fixed modulation scheme, the bandwidth efficiency can be adapted to the channel quality by changing the channel code rate and the iterative decoding procedure can be optimized by using irregular codes. In this paper, we will fix the channel code and focus on the modulation in the BICM system. We propose irregular modulation schemes, where different signal constellations, mappings and precoder may be used within one code block. With these schemes, the bandwidth efficiency can be adapted to the channel quality in an accurate way and the iterative decoding procedure can be optimized for a fixed channel code. Thus, new additional possibilities to design a highly adaptive system are given.
Applicability of DryadLINQ to Scientific Applications

Applying high level parallel runtimes to data/compute intensive applications is becoming increasingly common. The simplicity of the MapReduce programming model and the availability of open source MapReduce runtimes such as Hadoop, are attracting more users to the MapReduce programming model. Recently, Microsoft has released DryadLINQ for academic use, allowing users to experience a new programming model and a runtime that is capable of performing large scale data/compute intensive analyses. The goal of our study is to explore the applicability of DryadLINQ to real scientific applications and compare its performance with other relevant parallel runtimes such as Hadoop. To achieve this goal we have developed a series of scientific applications using DryadLINQ, namely, CAP3 DNA sequence assembly program [1], Pairwise ALU sequence alignment, High Energy Physics(HEP)data analysis, and K-means Clustering [2]. Each of these applications has unique requirements for parallel runtimes. For example, the HEP data analysis application requires ROOT [3] data analysis framework to be available in all the compute nodes and in Pairwise ALU sequence alignment the framework must handle computing of distance matrix with hundreds of millions of points. We have implemented all these applications using DryadLINQ and Hadoop, and used them to compare the performance of these two runtimes. Twister and MPI are used in applications where the contrast in performance needs to be highlighted. In the sections that follow, we first present an overview of the different parallel runtimes we use in this analysis followed by a detailed discussion of the data analysis applications we developed. Here we discuss the mappings of parallel algorithms to the DryadLINQ programming model and present performance comparisons with Hadoop implementations of the same applications. In section 4 we analyze DryadLINQ's programming model comparing it with other relevant technologies such as Hadoop and Twister. We also include a set of usability requirements for DryadLINQ. We present our conclusions in section 5. This section presents a brief introduction to a set of parallel runtimes we use our evaluations. 2.1 Microsoft DryadLINQ Dryad [4] is a distributed execution engine for coarse grain data parallel applications. Dryad considers computation tasks as directed acyclic graphs (DAG) where the vertices represent computation tasks and while the edges acting as communication channels over which the data flow from one vertex to another. In the HPC version of Dryad the data is stored in (or partitioned to) Windows shared directories in local compute nodes and a meta-data file …
Incremental nested partition method

In this paper, we introduce an incremental nested partition algorithm for finding the inner structuralization of dynamic datasets. Here we use three partition criteria that allow to obtain a hierarchy of clusterings. The algorithm is based on some mathematical properties, which are introduced in the paper. The experimental results over the AFP and TDT2 news collections show the usefulness of our method to reveal different levels of the information hidden in the datasets.
Improving the Effectiveness of Local Context Analysis Based on Semantic Similarity

Local context analysis is a main way to enhance the effectiveness of query expansion in the information retrieval field. A typical query may go through a pre- refinement process to improve its retrieval power. Most of the existing local context analysis methods are attempting to solve invalid selection of additive terms, which will result in retrieval performance degradation, in the process of query expansion. In this paper, we introduce a complementary method. The new local context analysis technique is improved by incorporating semantic similarity metric into query expansion model. Finally in our experimental results, using the three groups of data sets on text retrieval conference, we show a significant enhancement of precision over current existing method in the field.
An Online Method for Minimizing Network Monitoring Overhead

Network monitoring is an essential component of network operation and, as the network size increases, it usually generates a significant overhead in large scale networks such as sensor and data center networks. In this paper, we show that measurement correlation often exhibited in real networks can be successfully exploited to reduce the network monitoring overhead. In particular, we propose an online adaptive measurement technique with which a subset of nodes are dynamically chosen as monitors while the measurements of the remaining nodes are estimated using the computed correlations. We propose an estimation framework based on jointly Gaussian distributed random variables, and formulate an optimization problem to select the monitors which minimize the estimation error under a total cost constraint. We show that the problem is NP-Hard and propose three efficient heuristics. In order to apply our framework to real-world networks, in which measurement distribution and correlation may significantly change over time, we also develop a learning based approach that automatically switches between learning and estimation phases using a change detection algorithm. Simulations carried out on two real traces from sensor networks and data centers show that our algorithms outperforms previous solutions based on compressed sensing and it is able to reduce the monitoring overhead by 50% while incurring a low estimation error. The results further demonstrate that applying the change detection algorithm reduces the estimation error up to two orders of magnitude.
Duality, Entropy and ADM Mass in Supergravity

We consider the Bekenstein-Hawking entropy-area formula in four dimensional extended ungauged supergravity and its electric-magnetic duality property. Symmetries of both 'large' and 'small' extremal black holes are considered, as well as the ADM mass formula for N=4 and N=8 supergravity, preserving different fraction of supersymmetry. The interplay between BPS conditions and duality properties is an important aspect of this investigation.
Mind Wandering: Mechanism, Function, and Intervention

Mind wandering is an important part of the stream of consciousness, which allows the stream of consciousness to continue when the individual does not process external stimuli or does tasks. The neural mechanism of mind wandering is the current research hotspot. This study involves the brain’s default network and two theories of different positions, one is the theory of executive control, and the other is the theory of executive control failure. The study discusses adaptive functioning of mind wandering, especially in terms of creative problem solving. Finally, there is a discussion of how to reduce the negative effects of mind wandering—mindfulness training.
Motor Neuron Regeneration in Adult Zebrafish

The mammalian spinal cord does not regenerate motor neurons that are lost as a result of injury or disease. Here we demonstrate that adult zebrafish, which show functional spinal cord regeneration, are capable of motor neuron regeneration. After a spinal lesion, the ventricular zone shows a widespread increase in proliferation, including slowly proliferating olig2-positive (olig2+) ependymo-radial glial progenitor cells. Lineage tracing in olig2:green fluorescent protein transgenic fish indicates that these cells switch from a gliogenic phenotype to motor neuron production. Numbers of undifferentiated small HB9+ and islet-1+ motor neurons, which are double labeled with the proliferation marker 5-bromo-2-deoxyuridine (BrdU), are transiently strongly increased in the lesioned spinal cord. Large differentiated motor neurons, which are lost after a lesion, reappear at 6–8 weeks after lesion, and we detected ChAT+/BrdU+ motor neurons that were covered by contacts immunopositive for the synaptic marker SV2. These observations suggest that, after a lesion, plasticity of olig2+ progenitor cells may allow them to generate motor neurons, some of which exhibit markers for terminal differentiation and integration into the existing adult spinal circuitry.
Comparing CT perfusion with oxygen partial pressure in a rabbit VX2 soft-tissue tumor model

The aim of this study was to evaluate the oxygen partial pressure of the rabbit model of the VX2 tumor using a 64-slice perfusion CT and to compare the results with that obtained using the oxygen microelectrode method. Perfusion CT was performed for 45 successfully constructed rabbit models of a VX2 brain tumor. The perfusion values of the brain tumor region of interest, the blood volume (BV), the time to peak (TTP) and the peak enhancement intensity (PEI) were measured. The results were compared with the partial pressure of oxygen (PO2) of that region of interest obtained using the oxygen microelectrode method. The perfusion values of the brain tumor region of interest in 45 successfully constructed rabbit models of a VX2 brain tumor ranged from 1.3–127.0 (average, 21.1 ± 26.7 ml/min/ml); BV ranged from 1.2–53.5 ml/100g (average, 22.2 ± 13.7 ml/100g); PEI ranged from 8.7–124.6 HU (average, 43.5 ± 28.7 HU); and TTP ranged from 8.2–62.3 s (average, 38.8 ± 14.8 s). The PO2 in the corresponding region ranged from 0.14–47 mmHg (average, 16 ± 14.8 mmHg). The perfusion CT positively correlated with the tumor PO2, which can be used for evaluating the tumor hypoxia in clinical practice.