nils-herrmann/clean_scirepeval huggingface dataset:
Bit-interleaved low density spread (BI-LDS) transmission

Achieving higher aggregate data rates for many simultaneous users is considered as a fundamental challenge for the next generation of wireless systems. With low-density spreading (LDS), one could transmit information by overloading, i.e., using more spreading sequences than chips with reasonable implementation complexity. In this paper, we propose an improvement to the conventional LDS technique that consists in introducing a bit interleaver in the transmission scheme. Its role is to render the error bursts that appear at the output of the LDS detector into correctable patterns for the channel decoder. Numerical evaluations of the spectral efficiency show SNR improvements of more than 2dB when using convolutional codes in BI-LDS schemes. Slight improvements are also observed when turbo codes are employed.
SpPack: spatial point pattern analysis in Excel using Visual Basic for Applications (VBA)

Many different sciences have developed many different tests to describe and characterise spatial point data. For example, all the trees in a given area may be mapped such that their x, y co-ordinates and other variables, or ‘marks’, (e.g. species, size) might be recorded. Statistical techniques can be used to explore interactions between events at different length scales and interactions between different types of events in the same area. SpPack is a menu-driven add-in for Excel written in Visual Basic for Applications (VBA) that provides a range of statistical analyses for spatial point data. These include simple nearest-neighbour-derived tests and more sophisticated second-order statistics such as Ripley’s K-function and the neighbourhood density function (NDF). Some simple grid or quadrat-based statistics are also calculated. The application of the SpPack add-in is demonstrated for artificially generated event sets with known properties and for a multi-type ecological event set.
Seismic TETwalker mobile robot design and modeling

The Center of Remote Sensing of Ice Sheets (CReSIS) is studying the use of the TETwalker mobile robot developed by NASA/Goddard Space Flight Center for polar seismic data acquisition. This paper discusses the design process for deploying seismic sensors within the 4-TETwalker mobile robot architecture. The 4-TETwalkerpsilas center payload node was chosen as the deployment medium. An alternative method of deploying seismic sensors that rest on the surface is included. Detailed models were also developed to study robot mobility dynamics and the deployment process. Finally, potential power options of solar sheaths and harvesting vibration energy are proposed.
Contextual Dependencies in Unsupervised Word Segmentation

Developing better methods for segmenting continuous text into words is important for improving the processing of Asian languages, and may shed light on how humans learn to segment speech. We propose two new Bayesian word segmentation methods that assume unigram and bigram models of word dependencies respectively. The bigram model greatly outperforms the unigram model (and previous probabilistic models), demonstrating the importance of such dependencies for word segmentation. We also show that previous probabilistic models rely crucially on suboptimal search procedures.
On cross-validation and stacking: building seemingly predictive models on random data

A number of times when using cross-validation (CV) while trying to do classification/probability estimation we have observed surprisingly low AUC's on real data with very few positive examples. AUC is the area under the ROC and measures the ranking ability and corresponds to the probability that a positive example receives a higher model score than a negative example. Intuition seems to suggest that no reasonable methodology should ever result in a model with an AUC significantly below 0.5. The focus of this paper is not on the estimator properties of CV (bias/variance/significance), but rather on the properties of the 'holdout' predictions based on which the CV performance of a model is calculated. We show that CV creates predictions that have an 'inverse' ranking with AUC well below 0.25 using features that were initially entirely unpredictive and models that can only perform monotonic transformations. In the extreme, combining CV with bagging (repeated averaging of out-of-sample predictions) generates 'holdout' predictions with perfectly opposite rankings on random data. While this would raise immediate suspicion upon inspection, we would like to caution the data mining community against using CV for stacking or in currently popular ensemble methods. They can reverse the predictions by assigning negative weights and produce in the end a model that appears to have close to perfect predictability while in reality the data was random.
Optimizing Chemical Reactions with Deep Reinforcement Learning

Deep reinforcement learning was employed to optimize chemical reactions. Our model iteratively records the results of a chemical reaction and chooses new experimental conditions to improve the reaction outcome. This model outperformed a state-of-the-art blackbox optimization algorithm by using 71% fewer steps on both simulations and real reactions. Furthermore, we introduced an efficient exploration strategy by drawing the reaction conditions from certain probability distributions, which resulted in an improvement on regret from 0.062 to 0.039 compared with a deterministic policy. Combining the efficient exploration policy with accelerated microdroplet reactions, optimal reaction conditions were determined in 30 min for the four reactions considered, and a better understanding of the factors that control microdroplet reactions was reached. Moreover, our model showed a better performance after training on reactions with similar or even dissimilar underlying mechanisms, which demonstrates its learning ability.
A model of events based on a foundational ontology

Die Arbeitsberichte aus dem Fachbereich Informatik dienen der Darstellung vorläufiger Ergebnisse, die in der Regel noch für spätere Veröffentlichungen überarbeitet werden. Die Autoren sind deshalb für kritische Hinweise dankbar. Alle Rechte vorbehalten, insbesondere die der Übersetzung, des Nachdruckes, des Vortrags, der Entnahme von Abbildungen und Tabellen – auch bei nur auszugsweiser Verwertung. The " Arbeitsberichte aus dem Fachbereich Informatik " comprise preliminary results which will usually be revised for subsequent publication. Critical comments are appreciated by the authors. All rights reserved. No part of this report may be reproduced by any means or translated. The lack of a formal event model hinders interoperability in distributed event-based systems. Consequently, we present in this paper a formal model of events, called F. The model bases on an upper-level ontology and provides comprehensive support for all aspects of events such as time and space, objects and persons involved, as well as the structural aspects, namely mere-ological, causal, and correlational relationships. The event model provides a flexible means for event composition, modeling of event causality and correlation , and allows for representing different interpretations of the same event. The foundational event model F is developed in a pattern-oriented approach, modularized in different ontologies, and can be easily extended by domain specific ontologies.
An RNA-Seq based gene expression atlas of the common bean

Common bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species. Combining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change ≥ 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/ . Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form. These data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the nitrogen source on assimilation and distribution throughout the plant.
In vitro and in vivo plasmalogen replacement evaluations in rhizomelic chrondrodysplasia punctata and Pelizaeus-Merzbacher disease using PPI-1011, an ether lipid plasmalogen precursor

Childhood peroxisomal disorders and leukodystrophies are devastating diseases characterized by dysfunctional lipid metabolism. Plasmalogens (ether glycerophosphoethanolamine lipids) are decreased in these genetic disorders. The biosynthesis of plasmalogens is initiated in peroxisomes but completed in the endoplasmic reticulum. We therefore undertook a study to evaluate the ability of a 3-substituted, 1-alkyl, 2-acyl glyceryl ether lipid (PPI-1011) to replace plasmalogens in rhizomelic chrondrodysplasia punctata type 1 (RCDP1) and rhizomelic chrondrodysplasia punctata type 2 (RCDP2) lymphocytes which possess peroxisomal mutations culminating in deficient plasmalogen synthesis. We also examined plasmalogen synthesis in Pelizaeus-Merzbacher disease (PMD) lymphocytes which possess a proteolipid protein-1 (PLP1) missense mutation that results in abnormal PLP1 folding and it's accumulation in the endoplasmic reticulum (ER), the cellular site of the last steps in plasmalogen synthesis. In vivo incorporation of plasmalogen precursor into tissue plasmalogens was also evaluated in the Pex7 mouse model of plasmalogen deficiency. In both RCDP1 and RCDP2 lymphocytes, PPI-1011 repleted the target ethanolamine plasmalogen (PlsEtn16:0/22:6) in a concentration dependent manner. In addition, deacylation/reacylation reactions resulted in repletion of PlsEtn 16:0/20:4 in both RCDP1 and RCDP2 lymphocytes, repletion of PlsEtn 16:0/18:1 and PlsEtn 16:0/18:2 in RCDP2 lymphocytes, and partial repletion of PlsEtn 16:0/18:1 and PlsEtn 16:0/18:2 in RCDP1 lymphocytes. In the Pex7 mouse, oral dosing of labeled PPI-1011 demonstrated repletion of tissue levels of the target plasmalogen PlsEtn 16:0/22:6 with phospholipid remodeling also resulting in significant repletion of PlsEtn 16:0/20:4 and PlsEtn 16:0/18:1. Metabolic conversion of PPI-1011 to the target plasmalogen was most active in the liver. Our data demonstrate that PPI-1011 is activated (removal of 3-substitution) and converted to PlsEtn in vitro in both RCDP1 and RCDP2 lymphocytes and in vivo in the Pex7 mouse model of RCPD1 effectively bypassing the peroxisomal dysfunction present in these disorders. While PPI-1011 was shown to replete PlsEtns 16:0/x, ether lipid precursors of PlsEtn 18:0/x and PlsEtn 18:1/x may also be needed to achieve optimal clinical benefits of plasmalogen replacement in these complex patient populations. In contrast, only limited plasmalogen replacement was observed in PMD lymphocytes suggesting that the effects of protein misfolding and accumulation in the ER negatively affect processing of plasmalogen precursors in this cellular compartment.
Introducing temporal order of dominant visual word sub-sequences for human action recognition

We present a novel video representation for human action recognition by considering temporal sequences of visual words. Based on state-of-the-art dense trajectories, we introduce temporal bundles of dominant, that is most frequent, visual words. These are employed to construct a complementary action representation of ordered dominant visual word sequences, that additionally incorporates fine grained temporal information. We exploit the introduced temporal information by applying local sub-sequence alignment that quantifies the similarity between sequences. This facilitates the fusion of our representation with the bag-of-visual-words (BoVW) representation. Our approach incorporates sequential temporal structure and results in a low-dimensional representation compared to the BoVW, while still yielding a descent result when combined with it. Experiments on the KTH, Hollywood2 and the challenging HMDB51 datasets show that the proposed framework is complementary to the BoVW representation, which discards temporal order.
Brick-Up Metaheuristic Algorithms

Metaheuristic algorithms have been a very important topic in computer science since the start of evolutionary computing the Genetic Algorithms 1950s. By now these metaheuristic algorithms have become a very large family with successful applications in industry. A challenge which is always pondered on, is finding the suitable metaheuristic algorithm for a certain problem. The choice sometimes may have to be made after trying through many experiments or by the experiences of human experts. As each of the algorithms have their own strengths in solving different kinds of problems, in this paper we propose a framework of metaheuristic brick-up system. The flexibility of brick-up (like Lego) offers users to pick a collection of fundamental functions of metaheuristic algorithms that were known to perform well in the past. In order to verify this brickup concept, in this paper we propose to use the Monte Carlo method with upper confidence bounds applied to a decision tree in selecting appropriate functional pieces. This paper validates the basic concept and discusses the further works.
Equivalence of graphical lasso and thresholding for sparse graphs

This paper is concerned with the problem of finding a sparse graph capturing the conditional dependence between the entries of a Gaussian random vector, where the only available information is a sample correlation matrix. A popular approach is to solve a graphical lasso problem with a sparsity-promoting regularization term. This paper derives a simple condition under which the computationally-expensive graphical lasso behaves the same as the simple heuristic method of thresholding. This condition depends only on the solution of graphical lasso and makes no direct use of the sample correlation matrix or the regularization coefficient. It is also proved that this condition is always satisfied if the solution of graphical lasso is replaced by its first-order Taylor approximation. The condition is tested on several random problems and it is shown that graphical lasso and the thresholding method (based on the correlation matrix) lead to a similar result (if not equivalent), provided the regularization term is high enough to seek a sparse graph.
Self-managing cloud-native applications: Design, implementation, and experience

Running applications in the cloud efficiently requires much more than deploying software in virtual machines. Cloud applications have to be continuously managed: (1) to adjust their resources to the incoming load and (2) to face transient failures replicating and restarting components to provide resiliency on unreliable infrastructure. Continuous managementmonitors application and infrastructural metrics to provide automated and responsive reactions to failures (healthmanagement) and changing environmental conditions (auto-scaling) minimizing human intervention. In the current practice, management functionalities are provided as infrastructural or third party services. In both cases they are external to the application deployment. We claim that this approach has intrinsic limits, namely that separating management functionalities from the application prevents them from naturally scaling with the application and requires additional management code and human intervention. Moreover, using infrastructure provider services for management functionalities results in vendor lock-in effectively preventing cloud applications to adapt and run on the most effective cloud for the job. In this paper we discuss the main characteristics of cloud native applications, propose a novel architecture that enables scalable and resilient self-managing applications in the cloud, and relate on our experience in porting a legacy application to the cloud applying cloud-native principles.
Business Trends and Tendencies in Organization Design and Work Design Practice : Identifying Cause-and-Effect Relationships

Current global business environment has a strong impact on theory and practice of organizations, as well as on working behavior of their employees. Increased complexity and competitiveness is changing settled ways of organizing and working. The ultimate search for the holy grail of achieving organizational effectiveness through better design solutions is gaining momentum. There are many possible areas and means for improvement. Great opportunities emerge from better understanding of contemporary organization and work environment. To seize them, the link between organization design and work design tendencies will be emphasized. Through an in-depth theoretical research on current business trends and their impact on the changing nature of work in organizations, potentially very strong patterns between these two different environmental categories and levels of analysis will be identified. Our extensive analysis of current trends and tendencies in organization design and work design field will provide useful insights for business practitioners and researchers.
Application of Sinc-Galerkin method to singularly perturbed parabolic convection-diffusion problems

We develop a numerical algorithm for solving singularly perturbed one-dimensional parabolic convection-diffusion problems. The method comprises a standard finite difference to discretize in temporal direction and Sinc-Galerkin method in spatial direction. The convergence analysis and stability of proposed method are discussed in details, it is justifying that the approximate solution converges to the exact solution at an exponential rate. we know that the conventional methods for these problems suffer due to decreasing of perturbation parameter, but the Sinc method handel such difficulty as singularity. This scheme applied on some test examples, the numerical results illustrate the efficiency of the method and confirm the theoretical behavior of the rates of convergence.
Automatic Testing of Program Security Vulnerabilities

Vulnerabilities in applications and their widespread exploitation through successful attacks are common these days. Testing applications for preventing vulnerabilities is an important step to address this issue. In recent years, a number of security testing approaches have been proposed. However, there is no comparative study of these work that might help security practitioners select an appropriate approach for their needs. Moreover, there is no comparison with respect to automation capabilities of these approaches. In this work, we identify seven criteria to analyze program security testing work. These are vulnerability coverage, source of test cases, test generation method, level of testing, granularity of test cases, testing automation, and target applications. We compare and contrast prominent security testing approaches available in the literature based on these criteria. In particular, we focus on work that address four most common but dangerous vulnerabilities namely buffer overflow, SQL injection, format string bug, and cross site scripting. Moreover, we investigate automation features available in these work across a security testing process. We believe that our findings will provide practical information for security practitioners in choosing the most appropriate tools.
Distribution of microfilaments and microtubules inHomarus pleopod tegumental glands (Crustacea, Decapoda)

The distribution of microfilaments and microtubules was examined in pleopod tegumental glands of male and female lobsters (Homarus americanus). Glands were labeled with rhodamine-phalloidin or antibodies to tubulin, the antitubulin antibodies being demonstrated with secondary antibodies conjugated to fluorescein. The labeled glands were then examined using either a Zeiss epifluorescence microscope or a Bio-Rad confocal scanning microscope. Some glands were examined using transmission electron microscopy. Glands from males and females showed the same distribution of microfilaments and microtubules, which appeared most abundantly in the common locus and around the main duct of each rosette. F-actin was specifically found in the central lobe of the central cell, around the ductules of the common locus, surrounding the finger-like projection of secretory cells, and encircling the main duct draining the rosette. Microtubules were most abundant in the finger-like projections of the secretory cells, in the cytoplasm of the central cell and canal cell, and around the main duct of the canal cell. Contraction of the microfilaments may facilitate movement of secretory product from the rosette, while the microtubules may provide structural support for the attenuated finger-like projections and the main duct. Electron micrographs suggest there is some interaction between these two elements of the cytoskeleton.
Graph mining meets the Semantic Web

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluate the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.