Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping Mars with HRSC, ISIS, and SOCET SET

Introduction: This abstract describes the techniques developed at the U.S. Geological Survey, Flagstaff, for stereomapping with images from the Mars Express High Resolution Stereo Camera (HRSC) and includes a preliminary characterization of the resulting products that we are preparing for a detailed comparison with products made from the same images by other instrument team members using other software. Although we use commercial software to produce digital topographic models (DTMs), a significant amount of the processing is done by using the USGS software system ISIS, which thus provides useful capabilities to potential users of HRSC data. HRSC [1] is the first camera designed specifically for stereo imaging to be used in mapping a planet other than the Earth. Nine detectors view the planet through a single lens to obtain four-band color coverage and stereo images at 3 to 5 distinct angles in a single pass over the target. The short interval (tens of seconds) between acquisition of the successive images ensures that the surface, atmosphere, and lighting conditions will be unchanged, minimizing problems in comparing the stereo images. The resolution of the nadir channel is 12.5 m at periapsis, poorer at higher points in the elliptical orbit. The stereo channels are typically operated at 2x coarser resolution and the color channels at 4x or 8x. Since the commencement of operations in January 2004, approximately 51% of Mars has been imaged at nadir resolutions better than 50 m/pixel. This coverage is expected to increase significantly during the recently approved extended mission of Mars Express, giving the HRSC dataset enormous potential for regional and even global mapping. Systematic processing of the HRSC images is carried out at the German Aerospace Center (DLR) in Berlin, by using the VICAR software system [2]. This processing includes decompression of the images, radiometric calibration, orthorectification (i.e., projection into map coordinates allowing for topographic parallax) based on elevations from MOLA altimetry [3], and production of standardized stereo DTMs and orthorectification based on these. The resulting standard products are referred to as Levels 1, 2, 3, and 4 respectively (note that these correspond to Levels 0, 1, 2, and 2 as generally referred to in ISIS processing [4]; ISIS refers to map-projected products as Level 2 regardless of the DTM data used for rectification). These products are generated systematically, in near-real time for all orbits, though only the HRSC Level 2 products are currently being archived. The tradeoff of …
Diverse Grouping-Based Aggregation Protocol With Error Detection for Smart Grid Communications

Smart grid, as the next generation of power grid characterized by “two-way” communications, has been paid great attention to realizing green, reliable, and efficient electricity delivery for our future lives. In order to support the two-way communications in smart grid, a large number of smart meters (SMs) should be deployed to customers to report their near real-time data to control center for monitoring purpose. However, this kind of real-time report could disclose users' privacy, bringing down the users' willingness to participate in smart grid. In order to address the challenge, in this paper, by considering the lifetime of SMs as exponential distribution, we propose a diverse grouping-based aggregation protocol with error detection (DG-APED), which employs differential privacy technique into grouping-based private stream aggregation for secure smart grid communications. DG-APED can not only achieve privacy-preserving aggregation, but also perform error detection efficiently when some SMs are malfunctioning. Detailed security analysis shows that DG-APED can guarantee the security and privacy requirements of smart grid communications. In addition, extensive performance evaluation also verifies the effectiveness and efficiency of the proposed DG-APED.
Quantifying Human‐Mediated Carbon Cycle Feedbacks

Changes in land and ocean carbon storage in response to elevated atmospheric carbon dioxide concentrations and associated climate change, known as the concentration‐carbon and climate‐carbon feedbacks, are principal controls on the response of the climate system to anthropogenic greenhouse gas emissions. Such feedbacks have typically been quantified in the context of natural ecosystems, but land management activities are also responsive to future atmospheric carbon and climate changes. Here we show that inclusion of such human‐driven responses within an Earth system model shifts both the terrestrial concentration‐carbon and climate‐carbon feedbacks toward increased carbon storage. We introduce a conceptual framework for decomposing these changes into separate concentration‐land cover, climate‐land cover, and land cover‐carbon effects, providing a parsimonious means to diagnose sources of variation across numerical models capable of estimating such feedbacks.
Automatic Virus Particle Selection—The Entropy Approach

This paper describes a fully automatic approach to locate icosahedral virus particles in transmission electron microscopy images. The initial detection of the particles takes place through automatic segmentation of the entropy-proportion image; this image is computed in particular regions of interest defined by two concentric structuring elements contained in a small overlapping window running over all the image. Morphological features help to select the candidates, as the threshold is kept low enough to avoid false negatives. The candidate points are subject to a credibility test based on features extracted from eight radial intensity profiles in each point from a texture image. A candidate is accepted if these features meet the set of acceptance conditions describing the typical intensity profiles of these kinds of particles. The set of points accepted is subjected to a last validation in a three-parameter space using a discrimination plan that is a function of the input image to separate possible outliers.
Design of a Programmable Gain, Temperature Compensated Current-Input Current-Output CMOS Logarithmic Amplifier

This paper presents the design of a programmable gain, temperature compensated, current-mode CMOS logarithmic amplifier that can be used for biomedical signal processing. Unlike conventional logarithmic amplifiers that use a transimpedance technique to generate a voltage signal as a logarithmic function of the input current, the proposed approach directly produces a current output as a logarithmic function of the input current. Also, unlike a conventional transimpedance amplifier the gain of the proposed logarithmic amplifier can be programmed using floating-gate trimming circuits. The synthesis of the proposed circuit is based on the Hart's extended translinear principle which involves embedding a floating-voltage source and a linear resistive element within a translinear loop. Temperature compensation is then achieved using a translinear-based resistive cancelation technique. Measured results from prototypes fabricated in a 0.5 μm CMOS process show that the amplifier has an input dynamic range of 120 dB and a temperature sensitivity of 230 ppm/°C (27 °C- 57°C), while consuming less than 100 nW of power.
Parallel field ranking

Recently, ranking data with respect to the intrinsic geometric structure (manifold ranking) has received considerable attentions, with encouraging performance in many applications in pattern recognition, information retrieval and recommendation systems. Most of the existing manifold ranking methods focus on learning a ranking function that varies smoothly along the data manifold. However, beyond smoothness, a desirable ranking function should vary monotonically along the geodesics of the data manifold, such that the ranking order along the geodesics is preserved. In this paper, we aim to learn a ranking function that varies linearly and therefore monotonically along the geodesics of the data manifold. Recent theoretical work shows that the gradient field of a linear function on the manifold has to be a parallel vector field. Therefore, we propose a novel ranking algorithm on the data manifolds, called Parallel Field Ranking. Specifically, we try to learn a ranking function and a vector field simultaneously. We require the vector field to be close to the gradient field of the ranking function, and the vector field to be as parallel as possible. Moreover, we require the value of the ranking function at the query point to be the highest, and then decrease linearly along the manifold. Experimental results on both synthetic data and real data demonstrate the effectiveness of our proposed algorithm.
On expectation maximization based channel and noise estimation beyond the vector Taylor series expansion

In this work, we show how expectation maximization based simultaneous channel and noise estimation can be derived without a vector Taylor series expansion. The central idea is to approximate the distribution of all the random variables involved — that is noisy speech, clean speech, channel and noise — as one large, joint Gaussian distribution. Consequently, instantaneous estimates of the noise and channel distribution parameters can be obtained by conditioning the joint distribution on observed, noisy speech spectra. This approach allows for the combination of expectation maximization based channel and noise estimation with the unscented transform.
Environmental and physical controls on northern terrestrial methane emissions across permafrost zones

Methane (CH4) emissions from the northern high‐latitude region represent potentially significant biogeochemical feedbacks to the climate system. We compiled a database of growing‐season CH4 emissions from terrestrial ecosystems located across permafrost zones, including 303 sites described in 65 studies. Data on environmental and physical variables, including permafrost conditions, were used to assess controls on CH4 emissions. Water table position, soil temperature, and vegetation composition strongly influenced emissions and had interacting effects. Sites with a dense sedge cover had higher emissions than other sites at comparable water table positions, and this was an effect that was more pronounced at low soil temperatures. Sensitivity analysis suggested that CH4 emissions from ecosystems where the water table on average is at or above the soil surface (wet tundra, fen underlain by permafrost, and littoral ecosystems) are more sensitive to variability in soil temperature than drier ecosystems (palsa dry tundra, bog, and fen), whereas the latter ecosystems conversely are relatively more sensitive to changes of the water table position. Sites with near‐surface permafrost had lower CH4 fluxes than sites without permafrost at comparable water table positions, a difference that was explained by lower soil temperatures. Neither the active layer depth nor the organic soil layer depth was related to CH4 emissions. Permafrost thaw in lowland regions is often associated with increased soil moisture, higher soil temperatures, and increased sedge cover. In our database, lowland thermokarst sites generally had higher emissions than adjacent sites with intact permafrost, but emissions from thermokarst sites were not statistically higher than emissions from permafrost‐free sites with comparable environmental conditions. Overall, these results suggest that future changes to terrestrial high‐latitude CH4 emissions will be more proximately related to changes in moisture, soil temperature, and vegetation composition than to increased availability of organic matter following permafrost thaw.
Elasticity Evaluation of IaaS Cloud Based on Mixed Workloads

Elasticity mechanism is the important feature of infrastructure clouds, which can add or remove resources to adapt the workload change. The elasticity mechanism impacts the quality of service and service level agreement. However, the performance of elasticity is hard to quantity. There are no efficient benchmarks to evaluate the elasticity mechanism. Exiting methods haven't considerate the different evaluation metrics and mixed workloads. In this paper, we propose a new framework to evaluate the elasticity of IaaS cloud based on mixed workload. Firstly, we design different types and patterns workload for the infrastructure cloud. Then, we propose the aggregated metrics which are based on different aspects. Finally, we present the experiments of real-world demonstrating that our method is applicable on the commercial IaaS cloud and has efficient results of elasticity evaluation.
The impact of diabetes mellitus on mortality from all causes and coronary heart disease in women: 20 years of follow-up.

BACKGROUND Few data are available on the long-term impact of type 2 diabetes mellitus on total mortality and fatal coronary heart disease (CHD) in women. METHODS We examined prospectively the impact of type 2 diabetes and history of prior CHD on mortality from all causes and CHD among 121 046 women aged 30 to 55 years with type 2 diabetes in the Nurses' Health Study who were followed up for 20 years from 1976 to 1996. RESULTS During 20 years of follow-up, we documented 8464 deaths from all causes, including 1239 fatal CHD events. Compared with women with no diabetes or CHD at baseline, age-adjusted relative risks (RRs) of overall mortality were 3.39 (95% confidence interval [CI], 3.08-3.73) for women with a history of diabetes and no CHD at baseline, 3.00 (95% CI, 2.50-3.60) for women with a history of CHD and no diabetes at baseline, and 6.84 (95% CI, 4.71-9.95) for women with both conditions at baseline. The corresponding age-adjusted RRs of fatal CHD across these 4 groups were 1.0, 8.70, 10.6, and 25.8, respectively. Multivariate adjustment for body mass index and other coronary risk factors only modestly attenuated the RRs. Compared with nondiabetic persons, the multivariate RRs of fatal CHD across categories of diabetes duration (< or =5, 6-10, 11-15, 16-25, >25 years) were 2.75, 3.63, 5.51, 6.38, and 11.9 (P< .001 for trend), respectively. The combination of prior CHD and a long duration of clinical diabetes (ie, >15 years) was associated with a 30-fold (95% CI, 20.7-43.5) increased risk of fatal CHD. CONCLUSIONS Our data indicate that among women, history of diabetes is associated with dramatically increased risks of death from all causes and fatal CHD. The combination of diabetes and prior CHD identifies particularly high-risk women.
Probing the structure of membrane proteins with electron spin echo envelope modulation spectroscopy

A new approach has been developed to probe the structural properties of membrane peptides and proteins using the pulsed electron paramagnetic resonance technique of electron spin echo envelope modulation (ESEEM) spectroscopy and the α‐helical M2δ subunit of the acetylcholine receptor incorporated into phospholipid bicelles. To demonstrate the practicality of this method, a cysteine‐mutated nitroxide spin label (SL) is positioned 1, 2, 3, and 4 residues away from a fully deuterated Val side chain (denoted i + 1 to i + 4). The characteristic periodicity of the α‐helical structure gives rise to a unique pattern in the ESEEM spectra. In the i + 1 and i + 2 samples, the 2H nuclei are too far away to be detected. However, with the 3.6 residue per turn pattern of an α‐helix, the i + 3 and i + 4 samples reveal a strong signal from the 2H nuclei of the Val side chain. Modeling studies verify these data suggesting that the closest 2H‐labeled Val to SL distance would in fact be expected in the i + 3 and i + 4 samples. This technique is very advantageous, because it provides pertinent qualitative structural information on an inherently difficult system like membrane proteins in a short period of time (minutes) with small amounts of protein (μg).
AN INVESTIGATION INTO THE CHARACTERISTICS AND KINETICS OF OIL SHALE OXY-FUEL COMBUSTION BY THERMOGRAVIMETRIC ANALYSIS

The characteristics of Huadian oil shale combustion in O2/CO2 atmospheres were compared to those in O2/N2 atmospheres by using nonisothermal methods. The combustion kinetics parameters were calculated using the Kissinger-Akahira-Sunose (KAS) and Friedman methods. Specifically, the effect of oxygen concentration (10, 20, 30, 50, 65 and 80% O2) and heating rate (2, 5, 10 and 20 °C min ) on the combustion reactivity and kinetics of Huadian oil shale in CO2-based and N2-based atmospheres were investigated to identify the optimal gases mixture and oxygen concentration. Comparison of the combustion performances of oil shale in CO2/O2 and N2/O2 environments indicated that the organic matter combusted earlier in CO2-based atmospheres than in N2-based atmospheres when the oxygen concentration was 10% and 20%. Meanwhile, the average activation energies of organic matter combustion in CO2-based atmospheres was higher than those in N2-based atmospheres at an oxygen concentration of 10% and 20%. With an appropriate amount of O2 and CO2, the combustion performance of oil shale in 30% O2/70% CO2 was superior to that in 30% O2/70% N2, and the combustion activation energy in the 30% O2/70% CO2 atmosphere was also lower. The similar combustion processes and activation energies of oxy-fuel and conventional combustion with oxygen concentrations above 50% indicate that oxygen plays a leading role in organic matter combustion under high oxic conditions. The results reveal that the 30% O2/70% CO2 atmosphere is optimal for oil shale combustion.
Chat with illustration: a chat system with visual aids

Traditional instant messaging service mainly transfers textual message, while the visual message is ignored to a great extent. In this paper, we propose a novel instant messaging scheme with visual aids named Chat with Illustration (CWI), which presents users visual messages associated with chat content automatically. When users start their chat, the system first identifies meaningful keywords from dialogue content and analyzes context relations. Then CWI explores keyword-based image search in a image database with cluster-based index. Finally, according to context relations, CWI assembles these images properly and presents an optimal visual message for each dialogue sentence. With the combination of textual and visual message, users could enjoy a more interesting and vivid communication experience. Especially for different native language speakers, CWI can help them cross language barrier to some degree. The in-depth user studies demonstrate the effectiveness of our approach.
MediaEval 2015: JKU-Tinnitus Approach to Emotion in Music Task

This paper describes the JKU-Tinnitus submission to the “Emotion in Music” task [1] of the 2015 MediaEval Benchmark. Given a set of manually annotated music and a set of features for each music file, machine learning algorithms are applied to estimate the development of emotional arousal and valence over the course of a piece of music. Our pipeline roughly contains feature extraction from the music files, a regression model and a Gauss filter as the final smoothing stage.
A comparison of secondary organic aerosol (SOA) yields and composition from ozonolysis of monoterpenes at varying concentrations of NO 2

tion gas-phase chemistry suggests that differences in observed aerosol yields for different NO2 concentrations are consistent with NO3 formation and subsequent competition between O3 and NO3 to oxidize each monoterpene. α-pinene was the only monoterpene studied that showed a systematic decrease in both aerosol number concentration and mass concentration with increasing [NO2]. β-pinene and ∆ -carene produced 10
Getting the most out of RNA-seq data analysis

Background. A common research goal in transcriptome projects is to find genes that are differentially expressed in different phenotype classes. Biologists might wish to validate such gene candidates experimentally, or use them for downstream systems biology analysis. Producing a coherent differential gene expression analysis from RNA-seq count data requires an understanding of how numerous sources of variation such as the replicate size, the hypothesized biological effect size, and the specific method for making differential expression calls interact. We believe an explicit demonstration of such interactions in real RNA-seq data sets is of practical interest to biologists. Results. Using two large public RNA-seq data sets—one representing strong, and another mild, biological effect size—we simulated different replicate size scenarios, and tested the performance of several commonly-used methods for calling differentially expressed genes in each of them. We found that, when biological effect size was mild, RNA-seq experiments should focus on experimental validation of differentially expressed gene candidates. Importantly, at least triplicates must be used, and the differentially expressed genes should be called using methods with high positive predictive value (PPV), such as NOISeq or GFOLD. In contrast, when biological effect size was strong, differentially expressed genes mined from unreplicated experiments using NOISeq, ASC and GFOLD had between 30 to 50% mean PPV, an increase of more than 30-fold compared to the cases of mild biological effect size. Among methods with good PPV performance, having triplicates or more substantially improved mean PPV to over 90% for GFOLD, 60% for DESeq2, 50% for NOISeq, and 30% for edgeR. At a replicate size of six, we found DESeq2 and edgeR to be reasonable methods for calling differentially expressed genes at systems level analysis, as their PPV and sensitivity trade-off were superior to the other methods’. Conclusion. When biological effect size is weak, systems level investigation is not possible using RNAseq data, and no meaningful result can be obtained in unreplicated experiments. Nonetheless, NOISeq or GFOLD may yield limited numbers of gene candidates with good validation potential, when triplicates or more are available. When biological effect size is strong, NOISeq and GFOLD are effective tools for detecting differentially expressed genes in unreplicated RNA-seq experiments for qPCR validation. When triplicates or more are available, GFOLD is a sharp tool for identifying high confidence differentially expressed genes for targeted qPCR validation; for downstream systems level analysis, combined results from DESeq2 and edgeR are useful.
Inter-FSP Funds Transfer Protocol Technical Report

The present work introduces the first decentralized secure funds transfer protocol, allowing funds transfer from payer to payee without a direct relationship, using the help of a mutuallytrusted peer, or a chain of trusted-peers connecting between payer and payee. The protocol guarantees that a participant only loses money if a trusted peer happens to be corrupt. Furthermore, the loss is limited to the amount of credit given to that peer. The protocol supports expiration times for payment orders, and takes into consideration actual network queuing delays. To achieve our goals, we used models and techniques from the Quality of Service area, to handle delays and avoid the expiration of payment orders. We provide rigorous proofs to the security of the protocol.