nils-herrmann/clean_scirepeval huggingface dataset:
Laser Based Online Sliding Window Approach for UAV Loop Closure Detection in Urban Environments

Online loop closure detection serves as an essential task for Unmanned Aerial Vehicles (UAVs) equipped with laser scanners. Due to the inherent errors in UAVs' pose estimation, a 3 D reconstruction algorithm is adopted to perform 3 D map building, which establishes probabilistic models of the system according to the assumption of errors. To meet the demand of online loop closure detection using sequential 2 D laser data, a robust ISW NDT (incremental sliding window based NDT) approach is proposed, which compares the appearance similarity between two scans by sliding a window with fixed size. Compared with the conventional 3 D NDT approach, the proposed loop closure detection algorithm is capable of providing superior performance in large scale outdoor environments, achieving higher recall rate at 100% precision and ensuring successful online implementation. Experimental results show the validity and robustness of the proposed method.
Methods for quantized compressed sensing
Venue: 2016 Information Theory and Applications Workshop (ITA)

In this paper, we compare and catalog the performance of various greedy quantized compressed sensing algorithms that reconstruct sparse signals from quantized compressed measurements. We also introduce two new greedy approaches for reconstruction: Quantized Compressed Sampling Matching Pursuit (QCoSaMP) and Adaptive Outlier Pursuit for Quantized Iterative Hard Thresholding (AOP QIHT) We compare the performance of greedy quantized compressed sensing algorithms for a given bit depth, sparsity, and noise level.
Does Corporate Capital Structure influence Corporate Financial Performance in Developing Economies? Evidence from East African Stock Markets

This paper examines the statistically significant influence which capital structure has had on corporate financial performance of listed non financial companies in East African stock markets. It used panel data of 272 observations including 34 East African non financial listed firms listed in East African stock markets such as Dar Es Salaam Stock Market (DSE) Nairobi Securities Exchange (NSE) and Uganda Securities Exchange (USE) for a period of 8 years {i.e. 2006 2013}.Using the Panel Corrected Standard Errors (PCSEs) and Fixed Effect (FE),the study formulated two (2) econometric models with return on assets (ROA) and return on equity (ROE) as dependent variables and measures of corporate financial performance respectively, three (3) independent variables such as short term debt ratio (STDR),long term debt ratio (LTDR) and total debt ratio (TDR) as a measure of capital structure, furthermore the study used size of the firm (SIZ) as a control variable in order to control the differences in firmi s operating environment. The result indicate that capital structure has a negative and statistically significant influence on East African listed firmi s financial performance at 5% significance level. These results show that in average profitable listed firms in East African prefers to use internal source of financing in their capital structure as compared to external source of financing {like Debts STDR,LTDR and TDR} and this results are supporting pecking order theory. Lastly the study recommends to corporate financial managers of East African non financial listed firms should reduce financing their operations and growth by debt (STDR,LTDR and TDR) on their capital structure in order to enhance their corporate financial performance, regulatory authorities in East African region such as East African member states securities regulatory authority (EASRA) to formulate policies that will improving of financial markets in the region in order to reduce the cost of debt, further research could examine the influence {if any} of capital structure on sector wise (as per industry like Manufacturing firms) for East African non financial listed firms, take into account more control variables which are likely to influence financial performance such as macroeconomic variables (like gross domestic product GDP) and consider other capital structure theories like ,market timing theory, agency theory which were not considered in our study.
Learning relationship between speech and image
Venue: 2016 Eighth International Conference on Knowledge and Systems Engineering (KSE)

Currently, studies on learning relationship between objects focus on the text domain. There are a few researchers who focus on relationship learning between objects in other domains. In these researches, they have tried to represent the qualitative description of structure of objects, and the symbolic relationship between them. This output provides symbolic meaning to the inter object relationships which are useful for subsequent common sense reasoning and decision making. In this paper, we propose an approach to learn the relationship between a speech signal and an image. In other words, this approach can classify objects based on speech input.
Transient Guarantees: Maximizing the Value of Idle Cloud Capacity
Venue: SC16: International Conference for High Performance Computing, Networking, Storage and Analysis

To prevent rejecting requests, cloud platforms typically provision for their peak demand. Thus, a platform's idle capacity can be significant, as demand varies widely over multiple time scales, e.g. daily and seasonally. To reduce waste, platforms have begun to offer this idle capacity in the form of transient servers, which they may unilaterally revoke, for much lower prices ~50 90% less than on demand servers, which they cannot revoke. However, transient servers' revocation characteristics their volatility and predictability influence their performance, since they affect the overhead of fault tolerance mechanisms applications use to handle revocations. Unfortunately, current cloud platforms offer no guarantees on revocation characteristics, which makes it difficult for users to optimally configure (and correctly value) transient servers. To address the problem, we propose the abstraction of a transient guarantee, which offers probabilistic assurances on revocation characteristics. Transient guarantees have numerous benefits: they increase the performance of transient servers, enable users to optimally use and correctly value them, and permit platforms to control their freedom to revoke them. We present policies for partitioning a variable amount of idle capacity into classes with different transient guarantees to maximize performance and value. We then implement and evaluate these policies on job traces from a production Google cluster. We show that our approach can increase the aggregate revenue from idle server capacity by up to ~6.5x compared to existing approaches.
SkyEyes: adaptive video streaming from UAVs
Venue: HotWireless@MobiCom

UAVs (unmanned aerial vehicles) equipped with high end cameras have become increasingly popular among consumers. UAVs have been traditionally considered for applications such as disaster response and surveillance, while emerging applications include live event broadcasts, precision agriculture, and augmented reality games. Consumer UAVs today use fixed bitrate video streaming where users configure the resolution (4K or 1080p) However, applications with real time streaming that deploy UAVs in the wild will require adaptive video streaming to tackle uncertain wireless link capacities and meet their video quality requirements. This paper is a first step toward the design of adaptive video streaming algorithms that can provide significant gains for UAV streaming. Our system SkyEyes leverages two novel aspects to aid UAV streaming: content based compression and video rate adaptation based on location sensors and client buffer status. Our system prototype, while far from complete, exhibits promise we believe that adaptive video streaming is indeed crucial for real time UAV applications
Novel hydrazone derivatives containing pyridine amide moiety: Design, synthesis, and insecticidal activity.
Venue: Bioorganic medicinal chemistry letters

A series of novel hydrazone derivatives containing pyridine amide moiety were designed, synthesized, and evaluated for their insecticidal activity. Bioassays indicated that some of the target compounds exhibited good insecticidal activities against Nilaparvata lugens (N. lugens) Plutella xylostella (P. xylostella) Mythimna separata (M. separata) Helicoverpa armigera (H. armigera) Pyrausta nubilalis (P. nubilalis) and Culex pipiens pallens (C. pipiens pallens) In particular, compound 5j revealed excellent insecticidal activity against C. pipiens pallens, with the 50% lethal concentration (LC50) and the 95% lethal concentration (LC95) values of 2.44 and 5.76 mg/L, respectively, which were similar to those of chlorpyrifos (3.26 and 6.98 mg/L, respectively) tebufenozide (1.22 and 2.49 mg/L, respectively) and RH 5849 (2.61 and 6.37 mg/L, respectively) These results indicated that hydrazone derivatives containing pyridine amide moiety could be developed as novel and promising insecticides.
SEPARABLY CLOSED VALUED FIELDS: QUANTIFIER ELIMINATION
Venue: The Journal of Symbolic Logic

It is proved in this article that the theory of separably closed nontrivially valued fields of characteristic p 0 and imperfection degree e 0 (e has quantifier elimination in the language \cal L}_{p,\rm{div} \times ,0,1\ \cup \lambda _{n,j}(x;{y_1} \ldots {y_n} _{0 \le n \omega ,0 \le j {p^n} \cup in particular, when e is finite, the corresponding theory has quantifier elimination in the language \cal L} \times ,0,1\ \cup {b_1} \ldots {b_e} \cup \lambda _{e,j}(x;{b_1} \ldots {b_e} _
The role of IgG hypersensitivity and changes in gut microbiota in the pathogenesis and therapy of depressive disorders
Venue: European Psychiatry

Depression is a complex, heterogeneous psychiatric disorder with multifactorial aetiology. Substantial evidence indicates that depressive episodes are associated not only with changes in neurotransmission in the central nervous system (CNS) but also may lead to structural changes in the brain through neuroendocrine, inflammatory, and immunological mechanisms. Among the factors deserving special attention connected with developing systematic inflammation are altered intestinal permeability, IgG food intolerance, and changes in gut microbiota. We present a possible scenario of the development of depression, linking elevated zonulin production, loosening of the tight junction barrier, an increase in permeability of the gut wall, and the passage of macromolecules, normally staying the gut, into the bloodstream, with the immuno inflammatory cascade and induction of IgG dependent food sensitivity. Alterations in bidirectional signaling between the gastrointestinal tract and the brain, so called "microbiota gut brain axis" may be normalized by dietary immunomodulating factors, including prebiotics and probiotics. In the case of increased IgG concentrations, the implementation of an elimination rotation diet may prove to be an effective method of reducing inflammation and, in this way, alleviating depressive symptoms. Given complexity and variety of mood disorders, it is necessary to develop improved integration models. Preliminary study results raise hope that the new methods mentioned above, i.e. psychobiotics, prebiotics, an elimination rotation diet, may be an important addition to the psychiatrist's armamentarium as therapeutic agents improving the efficacy of the treatment for affective disorders  Disclosure of interest The authors have not supplied their declaration of competing interest.
NIST Cryptographic Standards and Guidelines Development Process

This document describes the principles, processes and procedures that drive cryptographic standards and guidelines development efforts at the National Institute of Standards and Technology (NIST) This document reflects public comments received on two earlier versions, and will serve as the basis to guide NIST's future cryptographic standards and guidelines development efforts. It will be reviewed and updated every five years, or more frequently if a need arises, to help ensure that NIST fulfills its role and responsibilities for producing robust, effective cryptographic standards and guidelines.
Constraints on the composition and particle size of chloride salt bearing deposits on Mars

Chloride salt bearing deposits on Mars were discovered using the Mars Odyssey Thermal Emission Imaging System (THEMIS) and have been characterized by both mid infrared (MIR) and visible to near infrared (VNIR) remote sensing instruments. The chloride salt bearing deposits exhibit a blue slope at MIR wavelengths and a featureless red slope at VNIR wavelengths. These deposits also lack strong 3 um bands in VNIR spectra, indicating that they are desiccated compared to the surrounding regolith. The lack of VNIR spectral features suggests that an anhydrous chloride salt, the most likely of which is halite, is responsible for the observed spectral slope. In this work, we use laboratory spectra and a hybrid T matrix/Hapke light scattering model to constrain the particle sizes and salt abundances of the Martian chloride salt bearing deposits. Our work shows that the two broad spectral classes of these deposits observed by THEMIS can be explained by a difference in the particle size of the admixed silicate regolith. In all cases, chloride salt abundances of 10 25% are required to match the THEMIS data. The chloride salt abundances determined in this work suggest deposition in a lacustrine/playa setting or in association with late stage groundwater upwelling.
Durability of reactive powder concrete under chloride salt freeze thaw cycling

The corrosion of reinforcements that results from chloride iron erosion and freeze thaw damage is the key cause of concrete material failure. Indoor accelerated freeze thaw cycling tests on reactive powder concrete are carried out in this study, and the mass loss rate (MLR) relative dynamic elastic modulus (RDEM) and compressive strength are measured in order to evaluate its durability. In addition, the microstructure and composition of the reactive powder concrete during the chloride salt freeze thaw cycles were analyzed using scanning electron microscopy, energy dispersive spectroscopy, and mercury intrusion porosimetry. The results show that the reactive powder concrete was durable under chloride freeze thaw cycling. Furthermore, the values of MLR and RDEM indicated that the actual method is not suitable for reactive powder concrete and should be modified, and that ettringite type erosion products are generated during the freeze thaw cycles. The conclusions in this study are valid for specific reactive powder concrete mix.
Calculation of chloride ion concentration in expressed pore solution of cement based materials exposed to a chloride salt solution

To investigate the relationship between the chloride ion concentration of the expressed pore solution C e and the exposure solution C es of cement based materials exposed to a chloride salt solution, a calculation of the C e based on an electrical double layer (EDL) model was proposed. The C e values were calculated using the proposed equations, applying the measured parameters: relative potential dps 0 dielectric constant e porosity P bulk density D volume percentage p i of pores with diameter d i The calculations explain why C e does not always equal to C es The results indicate that the expression method does not test the concentration of free chloride ions in the bulk solution C Cl b or the average concentration of the transportable chloride ions C ttr.a in the pores. However, the ratio C r of C e to C Cl b and the relationship between C e and C ttr.a can be calculated to more accurately measure chloride ion migration in cement based materials.
The Micellization and Clouding Phenomena of a Nonionic Surfactant, Poly(ethylene glycol) t octylphenyl ether (Triton X 100) Effect of (Chloride Salt) Electrolytes

Herein, we report the micellization and the clouding of a nonionic surfactant, poly(ethylene glycol) t octylphenyl ether (Triton X 100) in aqueous solutions in the absence and presence of (chloride salt) electrolytes. In the absence and presence of electrolytes, the critical micelle concentration (CMC) of Triton X 100 was measured by surface tension measurements. Upon increasing the temperature as well as the concentration of electrolytes, the CMCs decreased. The surface properties and the thermodynamic parameters of the micellar systems were evaluated. From these evaluated thermodynamic parameters, it was found that in the presence of an electrolyte, the stability of the micellar system is high. The cloud points (CPs) of Triton X 100 were also measured in the absence and presence of metallic ions of electrolytes. Upon the addition of metallic ions of chloride salts (electrolytes) the decrease in CP values was observed and the order was found to be: K+ Na+ Li+ NH+4.
Cellulose aerogels prepared from an aqueous zinc chloride salt hydrate melt.
Venue: Carbohydrate polymers

Monolithic cellulose aerogels are prepared using a salt hydrate melt based on cheap zinc chloride tetrahydrate (ZnCl2*4H2O) that can be washed out of the wet gel body by using common solvents such as water, ethanol, isopropanol or acetone. Cellulose aerogels with concentrations of 1 5 wt. cellulose were produced. These aerogels are characterized with respect to shrinkage, density and surface area as well as mechanical properties and micro structure via SEM. Cellulose aerogels regenerated in acetone show a specific surface area of around 340 m(2)g( 1) being 60% higher than those regenerated in water. The onset of irreversible plastic deformation under compressive load is around 0.8 MPa for acetone regenerated aerogels and thus a factor of two larger compared to ethanol regenerated ones. The Young's modulus depends almost linearly on the cellulose concentration which is observed for all regenerative fluids with the exception of water. The results achieved are presented in light of the polarity and ability of solvation of ZnCl2*4H2O in the regenerative fluids used.
Learning to Hash for Indexing Big Data A Survey
Venue: Proceedings of the IEEE

The explosive growth in Big Data has attracted much attention in designing efficient indexing and search methods recently. In many critical applications such as large scale search and pattern matching, finding the nearest neighbors to a query is a fundamental research problem. However, the straightforward solution using exhaustive comparison is infeasible due to the prohibitive computational complexity and memory requirement. In response, approximate nearest neighbor (ANN) search based on hashing techniques has become popular due to its promising performance in both efficiency and accuracy. Prior randomized hashing methods, e.g. locality sensitive hashing (LSH) explore data independent hash functions with random projections or permutations. Although having elegant theoretic guarantees on the search quality in certain metric spaces, performance of randomized hashing has been shown insufficient in many real world applications. As a remedy, new approaches incorporating data driven learning methods in development of advanced hash functions have emerged. Such learning to hash methods exploit information such as data distributions or class labels when optimizing the hash codes or functions. Importantly, the learned hash codes are able to preserve the proximity of neighboring data in the original feature spaces in the hash code spaces. The goal of this paper is to provide readers with systematic understanding of insights, pros, and cons of the emerging techniques. We provide a comprehensive survey of the learning to hash framework and representative techniques of various types, including unsupervised, semisupervised, and supervised. In addition, we also summarize recent hashing approaches utilizing the deep learning models. Finally, we discuss the future direction and trends of research in this area.
The National Early Warning Score (NEWS) for outcome prediction in emergency department patients with community acquired pneumonia: results from a 6 year prospective cohort study
Venue: BMJ Open

To investigate the accuracy of the National Early Warning Score (NEWS) to predict mortality and adverse clinical outcomes for patients with community acquired pneumonia (CAP) compared to standard risk scores such as the pneumonia severity index (PSI) and CURB 65.  Secondary analysis of patients included in a previous randomised controlled trial with a median follow up of 6.1 years.  Patients with CAP included on admission to the emergency departments (ED) of 6 tertiary care hospitals in Switzerland.  A total of 925 patients with confirmed CAP were included. NEWS, PSI and CURB 65 scores were calculated on admission to the ED based on admission data.  Our primary outcome was all cause mortality within 6 years of follow up. Secondary outcomes were adverse clinical outcome defined as intensive care unit (ICU) admission, empyema and unplanned hospital readmission all occurring within 30 days after admission. We used regression models to study associations of baseline risk scores and outcomes with the area under the receiver operating curve (AUC) as a measure of discrimination.  6 year overall mortality was 45.1% (n=417) with a stepwise increase with higher NEWS categories. For 30 day and 6 year mortality prediction, NEWS showed only low discrimination (AUC 0.65 and 0.60) inferior compared to PSI and CURB 65. For prediction of ICU admission, NEWS showed moderate discrimination (AUC 0.73) and improved the prognostic accuracy of a regression model, including PSI (AUC from 0.66 to 0.74, p=0.001) and CURB 65 (AUC from 0.64 to 0.73, p=0.015) NEWS was also superior to PSI and CURB 65 for prediction of empyema, but did not well predict rehospitalisation.  NEWS provides additional prognostic information with regard to risk of ICU admission and complications and thereby improves traditional clinical risk scores in the management of patients with CAP in the ED setting.
Bacterial Secretion Systems: An Overview.
Venue: Microbiology spectrum

Bacterial pathogens utilize a multitude of methods to invade mammalian hosts, damage tissue sites, and thwart the immune system from responding. One essential component of these strategies for many bacterial pathogens is the secretion of proteins across phospholipid membranes. Secreted proteins can play many roles in promoting bacterial virulence, from enhancing attachment to eukaryotic cells, to scavenging resources in an environmental niche, to directly intoxicating target cells and disrupting their functions. Many pathogens use dedicated protein secretion systems to secrete virulence factors from the cytosol of the bacteria into host cells or the host environment. In general, bacterial protein secretion apparatuses can be divided into classes, based on their structures, functions, and specificity. Some systems are conserved in all classes of bacteria and secrete a broad array of substrates, while others are only found in a small number of bacterial species and/or are specific to only one or a few proteins. In this chapter, we review the canonical features of several common bacterial protein secretion systems, as well as their roles in promoting the virulence of bacterial pathogens. Additionally, we address recent findings that indicate that the innate immune system of the host can detect and respond to the presence of protein secretion systems during mammalian infection.