Miracle-dz/UniFAR-FTUs huggingface dataset:
Earth surface reflectance climatology from 3 years of OMI data

[1] Global maps of the Earth's surface Lambertian equivalent reflectance (LER) are constructed using 3 years of Ozone Monitoring Instrument (OMI) measurements obtained between October 2004 and October 2007 at 23 wavelengths between 328 and 500 nm. The maps are constructed on a 0.5° by 0.5° longitude-latitude grid for each calendar month using an algorithm based on temporal histograms of the observed LER values per geophysical location. The algorithm allows seasonal effects related to vegetation, snow, and ice but excludes statistical outliers. The maps show typical features like open ocean regions with high reflectivity indicative of low phytoplankton levels, coastal waters with high reflectance caused by silt, and oceanic regions with low reflectance correlated with chlorophyll. Open oceans in general have a higher reflectivity than does land up to 420 nm. The highest reflectivity values of oceans occur at 380 nm. Good agreement is found with a similar LER map based on data from the Total Ozone Mapping Spectrometer (TOMS) at 331, 340, 360, and 380 nm, which is 0.015 lower on average. The comparison with data from the Global Ozone Monitoring Experiment (GOME) at 335, 380, 440, and 494 nm is also satisfactory, being 0.005 lower on average. The LER derived from OMI data is approximately 0.02 higher than the black sky albedo as derived from the Moderate Resolution Imaging Spectroradiometer at 470 nm, which is partly related to viewing geometry effects of the bidirectional reflectance distribution function of the surface. The data set presented contains residual cloud features over tropical rain forest regions, has a higher spatial resolution than those created using TOMS and GOME data, and includes more wavelengths.
Novel control strategy of torque pulsations on a hybrid vehicle

Abstract In conventional internal combustion engines the periodic fuel combustion in cylinders and oscillating masses results in a pulsating engine torque. In hybrid power trains the electrical motor can be used to control such pulsations. In the paper, the authors propose a novel control strategy of torque pulsations on a hybrid vehicle. Using an active filter and an a.c. machine, which is mounted on the crankshaft to generate an inverse torque sequence, reduces the combustion engine pulsations. The control strategy is based on a multiobjective state feedback synthesis. A complete modelling of the hybrid propulsion of the vehicle is achieved. Simulation results highlight the interest of the control scheme.
Feedback and power optimization in the multiuser downlink under QoS constraints

We consider the Multiple-Input Single-Output (MISO) Broadcast Channel (BC) with linear filters and perfect Channel State Information (CSI) at reception that is fed back to the transmitter via a limited feedback channel. Our goal is to jointly achieve per-user rate requirements by using minimum total transmit power. We develop a Lloyd's algorithm to find both optimal quantizer and codebook by means of the duality between Multiple Access Channel (MAC) and BC w.r. t. the average Mean Square Error (MSE), and the properties of standard interference functions.
Track formation in clutter using a bi-band imaging sensor

In this paper we present an extension of the Markov-chain-based performance evaluation technique for a bi-band two-stage sliding window cascaded logic (2/2/spl times/min) for track formation in clutter. This work has been motivated by a ballistic target surveillance problem based on a bi-spectral satellite observation system. We show how to combine an AND and OR fusion decision logic within the classical performance evaluation approach and how this can result in better performance and serve as a useful tool in satellite tracking system design.
Robustness to connectivity loss for collaborative mapping

Having a team of robots to perform a task such as mapping is faster and more reliable than doing the same with a single robot, which can be crucial in scenarios such as search and rescue. We are developing a fully distributed framework for collaborative mapping with large robot swarms that is robust to abrupt departure of robots due to malfunctions or network problems. While several approaches to multi-robot mapping have been proposed, most of them either build a collection of local sub-maps, or rely on a central authority to merge maps built by individual robots. Our framework is unique in that it requires no central authority, yet allows robots to simultaneously contribute to a single global map, which is stored in a decentralized fashion. This greatly improves the scalability of our system with respect to number of robots. However, our approach requires systematic coordination among robots in order to make modifications to the map. Unannounced departure of the robots makes coordination challenging, and can potentially make the map inconsistent or result in loss of data. We borrow ideas from the domain of distributed computing to address those challenges. Further, we demonstrate the robustness of the proposed system by subjecting it to various conditions in which participating robots fail.
Measuring Pair-Wise Social Influence in Microblog

The development of Microblog services has created an unprecedented opportunity for people to share information. To better understand the information propagation behaviors in such social networks, an important task is to measure the influence among users. A number of previous works measure users' influence through analyzing the network characteristics or by retweet rate. However, high in degree not necessarily means influential and retweet rate fluctuates over time. In this paper, we propose a user interaction model in microblog by considering the following three key factors: user's active level, user's willingness to retweet, and the influence between a pair of users. One advantage of this model is that the model fitting only requires a sub graph and hence may be performed in a piece-wise fashion. Furthermore, we can find the users with potential influence in the network. We fit the model with a Sina Microblog dataset. We show that this model is able to predict influence at high accuracy. Moreover, this model can be used to predicting retweet rate and finding influential users.
Ways to Evade Spai Filters and Machine Learning as a Potential Solution

The growth of unsolicited email or junk mail has become a major threat to information security today. Most of the commercial Websites providing email facility today provide some form of programmable automatic filtration of junk mails, typically in the form of a set of rules to dispose of mails based on keywords detected in headers or message body. There are some other methods for the purpose as well, but an adaptive email filtering system based on Bayesian technique that can learn from its user's mail preferences appears to be a better solution. It not only considers the keywords that identify spam, but also words that denote innocent or legitimate mail which makes the filter more efficient . However direct marketers discover new ways to evade even the Bayesian filters, so as to reach the potential customers. The way most commonly adopted by the spammers to mislead the Bayesian filters is injection of out of context text in the email. This paper aims at presenting a critical analysis of the various ways adopted by spammers to dodge the spam filters. Further we explore the Bayesian noise reduction (BNR) technique which attempts to solve this problem by identifying and eliminating the 'out of context' data (so injected by spammers or otherwise) to provide a cleaner classification
Farming and Fighting: An Empirical Analysis of the Ecological-Evolutionary Theory of the Incidence of Warfare

Explanations of the causes of war fall roughly into two schools: those arguing for the primacy of environment and technology, and those arguing for the primacy of sociopolitical factors. We re-examine two hypotheses from the former school, viz, societies are more likely to engage in war when they have: 1) more productive subsistence technology; and 2) higher population density. Using data from the Standard Cross-Cultural Sample, and up-to-date multivariate modeling methods, we find only qualified support for the first hypothesis and find the reverse relationship for the second: higher population densities lead to less war, not more. We show that omitted variable bias can explain the failure of previous studies to discover this relationship. Finally, we show that the two schools seem to be equally correct, in that each explains about the same proportion of the variation in frequency of external war.
Soft information in earnings announcements: news or noise?

This paper examines whether the “soft” information contained in the text of management’s quarterly earnings press releases is incrementally informative over the company’s reported “hard” earnings news. We use Diction, a textual-analysis program, to extract various dimensions of managerial net optimism from more than 20,000 corporate earnings announcements over the period 1998 to 2006 and document that unanticipated net optimism in managers’ language affects announcement period abnormal returns and predicts post-earnings announcement drift. We find that it takes longer for the market to understand the implications of soft information than those of hard information. We also find that the market response varies by firm size, turnover, media and analyst coverage, and the extent to which the standard accounting model captures the underlying economics of the firm. We also show that the second moment of soft information, the level of certainty in the text, is an important determinant of contemporaneous idiosyncratic volatility, and it predicts future idiosyncratic volatility.
Mirror Based Framework for Human Body Measurement

In the paper a camera-mirror based 3D measurement system is introduced aimed for reconstruction of human body parts. During the measurement the patient cannot maintain static state even for a short period which may negatively affect the accuracy of the reconstruction. Nevertheless by such applications the duration of measurement plays significant role, as well. In order to handle these issues synchronized camera group has been used together with two mirrors to capture the targeted object with a single shot entirely. As the results reflect the proposed approach might be suitable for many application where targets being in small motion must be measured at once.
Japan's political trust deficit

Abstract This introductory article to the special issue on ‘Trust and Mistrust in Contemporary Japan’ lays out key trust concepts used in social science research. It then turns towards the Japanese case, summarizing important research on the notion of trust and Japanese politics and society, according to which trust levels are comparatively low. The subsequent part provides an overview on the case studies that scrutinize issues related to political trust in particular. As the contributions invariably point to low levels of political trust, we finally reflect on problems in Japan's politics in relation to the notion of trust.
FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing

Allele-specific copy number analysis (ASCN) from next generation sequencing (NGS) data can greatly extend the utility of NGS beyond the identification of mutations to precisely annotate the genome for the detection of homozygous/heterozygous deletions, copy-neutral loss-of-heterozygosity (LOH), allele-specific gains/amplifications. In addition, as targeted gene panels are increasingly used in clinical sequencing studies for the detection of ‘actionable’ mutations and copy number alterations to guide treatment decisions, accurate, tumor purity-, ploidy- and clonal heterogeneity-adjusted integer copy number calls are greatly needed to more reliably interpret NGS-based cancer gene copy number data in the context of clinical sequencing. We developed FACETS, an ASCN tool and open-source software with a broad application to whole genome, whole-exome, as well as targeted panel sequencing platforms. It is a fully integrated stand-alone pipeline that includes sequencing BAM file post-processing, joint segmentation of total- and allele-specific read counts, and integer copy number calls corrected for tumor purity, ploidy and clonal heterogeneity, with comprehensive output and integrated visualization. We demonstrate the application of FACETS using The Cancer Genome Atlas (TCGA) whole-exome sequencing of lung adenocarcinoma samples. We also demonstrate its application to a clinical sequencing platform based on a targeted gene panel.
A superposition decision procedure for the guarded fragment with equality

We give a new decision procedure for the guarded fragment with equality. The procedure is based on resolution with superposition. We argue that this method will be more useful in practice than methods based on the enumeration of certain finite structures. It is surprising to see that one does not need any sophisticated simplification and redundancy elimination method to make superposition terminate on the class of clauses that is obtained from the clausification of guarded formulas. Yet the decision procedure obtained is optimal with regard to time complexity. We also show that the method can be extended to the loosely guarded fragment with equality.
Inhibition of translation by IFIT family members is determined by their ability to interact selectively with the 5′-terminal regions of cap0-, cap1- and 5′ppp- mRNAs

Ribosomal recruitment of cellular mRNAs depends on binding of eIF4F to the mRNA’s 5′-terminal ‘cap’. The minimal ‘cap0’ consists of N7-methylguanosine linked to the first nucleotide via a 5′-5′ triphosphate (ppp) bridge. Cap0 is further modified by 2′-O-methylation of the next two riboses, yielding ‘cap1’ (m7GpppNmN) and ‘cap2’ (m7GpppNmNm). However, some viral RNAs lack 2′-O-methylation, whereas others contain only ppp- at their 5′-end. Interferon-induced proteins with tetratricopeptide repeats (IFITs) are highly expressed effectors of innate immunity that inhibit viral replication by incompletely understood mechanisms. Here, we investigated the ability of IFIT family members to interact with cap1-, cap0- and 5′ppp- mRNAs and inhibit their translation. IFIT1 and IFIT1B showed very high affinity to cap-proximal regions of cap0-mRNAs (K1/2,app ∼9 to 23 nM). The 2′-O-methylation abrogated IFIT1/mRNA interaction, whereas IFIT1B retained the ability to bind cap1-mRNA, albeit with reduced affinity (K1/2,app ∼450 nM). The 5′-terminal regions of 5′ppp-mRNAs were recognized by IFIT5 (K1/2,app ∼400 nM). The activity of individual IFITs in inhibiting initiation on a specific mRNA was determined by their ability to interact with its 5′-terminal region: IFIT1 and IFIT1B efficiently outcompeted eIF4F and abrogated initiation on cap0-mRNAs, whereas inhibition on cap1- and 5′ppp- mRNAs by IFIT1B and IFIT5 was weaker and required higher protein concentrations.
Scientific use of TerraSAR-X

TerraSAR-X is a new German radar satellite to be launched in April 2006. The expected lifetime is 5 years. It carries a high frequency X-band SAR sensor that can be operated in different modes and polarization. The Spotlight-, Stripmap- and ScanSAR-modes provide high resolution SAR images for detailed analysis as well as wide swath data whenever a larger coverage is required. Imaging is possible in single, dual and quad-polarization. TerraSAR-X is an operational SAR-system for scientific and commercial applications that equally shares the satellite tasking time. DLR is responsible for the scientific use while the Astrium GmbH has the exclusive commercial exploitation rights. The status "scientific use" needs to be gained via a selection process. An announcement of opportunity (AO) is to be released one year before the launch. TerraSAR-X data can be provided for the costs of fulfilling the user request
Load Balanced Broadcasting in Ad Hoc Wireless Networks Using Directional Antennas

Using directional antennas to conserve bandwidth and energy consumption in ad hoc wireless networks has attracted much attention of the research community in recent years. However, limited research has focused on applying directional antennas to broadcasting and the load balance in broadcasting. Taking the load balance into consideration, we devise a link reduction (LLR) based on broadcasting protocol for ad hoc wireless networks using directional antennas. LLR outperforms most existing omnidirectional and directional broadcasting schemes in the sense that its normalized transmission cost and redundancy are significantly reduced while the longevity of a network is greatly increased. LLR is a localized protocol based on 2-hop neighbor information and it achieves full delivery in ad hoc networks. Simulation is conducted in ideal networks where packet collision, channel contention, or node mobility is avoided.
Near-Infrared Fluorescence Optical Imaging and Tomography

The advent of recent advances in near-infrared laser diodes and fast electro-optic detection has spawned a new research field of diagnostic spectroscopy and imaging based on targeting and reporting exogenous fluorescent agents. This review seeks to concisely address the physics, instrumentation, advancements in tomography, and near-infrared fluorescent contrast agent development that promises selective and specific molecular targeting of diseased tissues. As an example of one area of the field, recent work focusing on pharmacokinetic analysis of fluorophores targeting the epidermal growth factor receptor (EGFR) is presented in a human breast cancer xenograft mouse model to demonstrate specificity of molecularly targeted contrast agents. Finally, a critical evaluation of the limitations and the opportunities for future translation of fluorescence-enhanced optical imaging of deep tissues is presented.
SCHMITT AND RANDALL : EFFECTS OF TEMPERATURE AND CLOUDS ON THE CO 2 FORCING

CO 2 forcing is defined as the initial change in heating rate, with no feedbacks included, that is the direct response to an increase in the CO2 concentration in the atmosphere. We have conducted a study of the effects of surface temperature and clouds on the CO2 forcing, based on use of the Colorado State University general circulation model. We report results from a pair of perpetual July simulations in which the sea surface temperatures differ by 4 K. The precipitable water is about 1.5 times larger in the warm run. The increased water vapor concentration amplifies the radiative effects of CO2, leading to greater CO2 forcing in the warm run. In the colder run the globally averaged reduction in upward longwave radiation due to a doubling of CO2 is 4.3 W m -2 at the level of maximum forcing, or the "CO2 tropopause. " Above and below this level the CO2 forcing decreases, resulting in a net tropospheric warming of 3.3 x 10 -2 K day -1, and a net stratospheric cooling. In the warm run the CO2 forcing at the CO2 tropopause is 4.6 W m -2, and is associated with a tropospheric warming of 4. x 10 -2 K day -1. The clear-sky CO2 forcing 2 at the CO2 tropopause is 5.0 W min the cold run, and 5.2 W m -2 in the warm run. By blocking infrared radiation that would otherwise be blocked by CO2, the clouds reduce the CO2 forcing of the surface-troposphere system by 0.66 W m -2 in the cold run, and by 0.59 W m -2 in the warm run. Our results for the CO2 forcing are model-dependent, of course. Every GCM-based study of CO2-induced climate change produces a CO 2 forcing, however, and the warming scenarios generated depend very directly on this forcing. A thorough investigation of the CO2 forcings produced by GCMs is thus a rather basic prerequisite for understanding the climate change predictions produced by the models.
GPU based graph bundling using geographic reference information

A common source of challenges in geographic visualisation systems is the growing amount of available data. Datasets containing different information need to be merged and analysed under a common context. For some purposes these datasets can interact intelligently and append additional information to a scientific visualisation. In this research proposal, we show how we are planning to optimize the process of bundling graphs to traffic networks and present a general method to solve this challenge.
High-speed potato grading and quality inspection based on a color vision system

A high-speed machine vision system for the quality inspection and grading of potatoes has been developed. The vision system grades potatoes on size, shape and external defects such as greening, mechanical damages, rhizoctonia, silver scab, common scab, cracks and growth cracks. A 3-CCD line-scan camera inspects the potatoes in flight as they pass under the camera. The use of mirrors to obtain a 360-degree view of the potato and the lack of product holders guarantee a full view of the potato. To achieve the required capacity of 12 tons/hour, 11 SHARC Digital Signal Processors perform the image processing and classification tasks. The total capacity of the system is about 50 potatoes/sec. The color segmentation procedure uses Linear Discriminant Analysis (LDA) in combination with a Mahalanobis distance classifier to classify the pixels. The procedure for the detection of misshapen potatoes uses a Fourier based shape classification technique. Features such as area, eccentricity and central moments are used to discriminate between similar colored defects. Experiments with red and yellow skin-colored potatoes have shown that the system is robust and consistent in its classification.
Power Transformer Fault Diagnosis based on Dissolved Gas Analysis with Logistic Regression

Logistic regression (LR) approach for power transformer fault diagnosis, based on dissolved gas analysis (DGA) is presented in this paper. DGA methods proposed by actual standard IEC 60599, often identify wrong fault or cannot even recognize fault type. To overcome these problems, in recent years, several artificial intelligence (AI) approaches are proposed. In this paper LR is applied for the first time in multi-layer and multi class configuration models for transformer fault diagnosis. It is shown that the proposed approach gives a very good classification performance. Streszczenie. Przedstawiono metode diagnostyki transformatora bazująca na analizie rozpuszczonego gazu metodą logistycznej regresji. Metoda ta umozliwia nie tylko wykrywanie uszkodzen ale takze ich klasyfikacje. (Diagnostyki transformatora bazująca na analizie rozpuszczonego gazu metodą logistycznej regresji)
On Internet Availability : Where Does Path Choice Matter ?

Today’s Internet availability is low, despite the efforts of organizations to improve failure resilience through multi-homing. In this paper, we analyze where and how much exposure to topology is needed to best improve availability without sacrificing scalability. Through this analysis, we find that exposing choice of the first and last AS hops between multi-homed AS pairs can almost always provide a maximum number of AS disjoint paths through the network, whereas the paths exposed under multi-homing tend to share the same inbound route to multi-homed destinations. We qualify our topological analysis with an active measurement study showing that exposing choice of the first and last AS hops can provide availability approaching the optimal availability possible, suggesting that high availability can be obtained without sacrificing scalability.