nils-herrmann/clean_scirepeval huggingface dataset:
Identification of Bacteria by Gas Chromatography of Cellular Fatty Acids Technical Note # 101

For many years, analysis of short chain fatty acids (volatile fatty acids, VFAs) has been routinely used in identification of anaerobic bacteria. In numerous scientific papers, the fatty acids between 9 and 20 carbons in length have also been used to characterize genera and species of bacteria, especially nonfermentative Gram negative organisms. With the advent of fused silica capillary columns (which allows recovery of hydroxy acids and resolution of many isomers), it has become practical to use gas chromatography of whole cell fatty acid methyl esters to identify a wide range of organisms.
The enemy has passed through the gate Insider threats , the dark triad , and the challenges around security

The purpose of this paper is to highlight the potential role that the so-called “toxic triangle” (Padilla et al., 2007) can play in undermining the processes around effectiveness. It is the interaction between leaders, organisational members, and the environmental context in which those interactions occur that has the potential to generate dysfunctional behaviours and processes. The paper seeks to set out a set of issues that would seem to be worthy of further consideration within the Journal and which deal with the relationships between organisational effectiveness and the threats from insiders.  The paper adopts a systems approach to the threats from insiders and the manner in which it impacts on organisation effectiveness. The ultimate goal of the paper is to stimulate further debate and discussion around the issues.  The paper adds to the discussions around effectiveness by highlighting how senior managers can create the conditions in which failure can occur through the erosion of controls, poor decision making, and the creation of a culture that has the potential to generate failure. Within this setting, insiders can serve to trigger a series of failures by their actions and for which the controls in place are either ineffective or have been by-passed as a result of insider knowledge.  The issues raised in this paper need to be tested empirically as a means of providing a clear evidence base in support of their relationships with the generation of organisational ineffectiveness.  The paper aims to raise awareness and stimulate thinking by practising managers around the role that the “toxic triangle” of issues can play in creating the conditions by which organisations can incubate the potential for crisis.  The paper seeks to bring together a disparate body of published work within the context of “organisational effectiveness” and sets out a series of dark characteristics that organisations need to consider if they are to avoid failure. The paper argues the case that effectiveness can be a fragile construct and that the mechanisms that generate failure also need to be actively considered when discussing what effectiveness means in practice.
Delta vs. N-Gram Tracing: Evaluating the Robustness of Authorship Attribution Methods

Delta measures are a well-established and popular family of authorship attribution methods, especially for literary texts. N-gram tracing is a novel method for authorship attribution designed for very short texts, which has its roots in forensic linguistics. We evaluate the performance of both methods in a series of experiments on English, French and German literary texts, in order to investigate the relationship between authorship attribution accuracy and text length as well as the composition of the comparison corpus. Our results show that, at least in our setting, both methods require relatively long texts and are furthermore highly sensitive to the choice of authors and texts in the comparison corpus.
Pattern division multiple access (PDMA) for cellular future radio access

This paper presents a pattern division multiple access (PDMA) concept for cellular future radio access (FRA) towards the 2020s information society. Different from the current LTE radio access scheme (until Release 11), PDMA is a novel non-orthogonal multiple access technology based on the total optimization of multiple user communication system. It considers joint design from both transmitter and receiver. At the receiver, multiple users are detected by successive interference cancellation (SIC) detection method. Numerical results show that the PDMA system based on SIC improve the average sum rate of users over the orthogonal system with affordable complexity.
Ensemble based Distributed K-Modes Clustering

Clustering has been recognized as the unsupervised classification of data items into groups. Due to the explosion in the number of autonomous data sources, there is an emergent need for effective approaches in distributed clustering. The distributed clustering algorithm is used to cluster the distributed datasets without gathering all the data in a single site. The K-Means is a popular clustering method owing to its simplicity and speed in clustering large datasets. But it fails to handle directly the datasets with categorical attributes which are generally occurred in real life datasets. Huang proposed the K-Modes clustering algorithm by introducing a new dissimilarity measure to cluster categorical data. This algorithm replaces means of clusters with a frequency based method which updates modes in the clustering process to minimize the cost function. Most of the distributed clustering algorithms found in the literature seek to cluster numerical data. In this paper, a novel Ensemble based Distributed K-Modes clustering algorithm is proposed, which is well suited to handle categorical data sets as well as to perform distributed clustering process in an asynchronous manner. The performance of the proposed algorithm is compared with the existing distributed K-Means clustering algorithms, and K-Modes based Centralized Clustering algorithm. The experiments are carried out for various datasets of UCI machine learning data repository.
Bilaminar techniques for the treatment of recession-type defects. A comparative clinical study.

Complete root coverage is the primary objective to be accomplished when treating gingival recessions in patients with aesthetic demands. Furthermore, in order to satisfy patient demands fully, root coverage should be accomplished by soft tissue, the thickness and colour of which should not be distinguishable from those of adjacent soft tissue. The aim of the present split-mouth study was to compare the treatment outcome of two surgical approaches of the bilaminar procedure in terms of (i) root coverage and (ii) aesthetic appearance of the surgically treated sites.



Fifteen young systemically and periodontally healthy subjects with two recession-type defects of similar depth affecting contralateral teeth in the aesthetic zone of the maxilla were enrolled in the study. All recessions fall into Miller class I or II. Randomization for test and control treatment was performed by coin toss immediately prior to surgery. All defects were treated with a bilaminar surgical technique: differences between test and control sites resided in the size, thickness and positioning of the connective tissue graft. The clinical re-evaluation was made 1 year after surgery.



The two bilaminar techniques resulted in a high percentage of root coverage (97.3% in the test and 94.7% in the control group) and complete root coverage (gingival margin at the cemento-enamel junction (CEJ)) (86.7% in the test and 80% in the control teeth), with no statistically significant difference between them. Conversely, better aesthetic outcome and post-operative course were indicated by the patients for test compared to control sites.



The proposed modification of the bilaminar technique improved the aesthetic outcome. The reduced size and minimal thickness of connective tissue graft, together with its positioning apical to the CEJ, facilitated graft coverage by means of the coronally advanced flap.
Time Series Modeling of River Flow Using Wavelet Neural Networks

A new hybrid model which combines wavelets and Artificial Neural Network (ANN) called wavelet neural network (WNN) model was proposed in the current study and applied for time series modeling of river flow. The time series of daily river flow of the Malaprabha River basin (Karnataka state, India) were analyzed by the WNN model. The observed time series are decomposed into sub-series using discrete wavelet transform and then appropriate sub-series is used as inputs to the neural network for forecasting hydrological variables. The hybrid model (WNN) was compared with the standard ANN and AR models. The WNN model was able to provide a good fit with the observed data, especially the peak values during the testing period. The benchmark results from WNN model applications showed that the hybrid model produced better results in estimating the hydrograph properties than the latter models (ANN and AR).
Polyp detection in Colonoscopy Videos Using Deeply-Learned Hierarchical Features

This paper summarizes the method of polyp detection in colonoscopy images and provides preliminary results to participate in ISBI 2015 Grand Challenge on Automatic Polyp Detection in Colonoscopy videos. The key aspect of the proposed method is to learn hierarchical features using convolutional neural network. The features are learned in different scales to provide scale-invariant features through the convolutional neural network, and then each pixel in the colonoscopy image is classified as polyp pixel or non-polyp pixel through fully connected network. The result is refined via smooth filtering and thresholding step. Experimental result shows that the proposed neural network can classify patches of polyp and non-polyp region with an accuracy of about 90%.
Treatment of paradoxical insomnia with atypical antipsychotic drugs. A comparison of olanzapine and risperidone.

To compare the efficacy of 2 atypical anti-psychotic drugs, olanzapine and risperidone, in the treatment of paradoxical insomnia.



In this cross-sectional study over a 2-year period (September 2008 to September 2010), 29 patients with paradoxical insomnia, diagnosed in Kermanshah, Iran by both psychiatric interview and actigraphy, were randomly assigned to 2 groups. For 8 weeks, the first group (n=14) was treated with 10 mg olanzapine daily, and the second group (n=15) was treated with 4 mg risperidone daily. All participants completed the Pittsburgh Sleep Quality Inventory (PSQI) at baseline and at the end of the study.



As expected, a baseline actigraphy analysis showed that total sleep time was not significantly different between the 2 treatment groups (p<0.3). In both groups, sleep quality was improved (p<0.001) with treatment. When comparing the 2 treatments directions, a significant difference emerged (9.21+/-2.35, 6.07+/-4.46) among the 2 treatment groups based on data from the PSQI. Patients who were treated with olanzapine showed greater improvement than patients who were treated by risperidone (p<0.04).



Atypical anti-psychotic drugs such as olanzapine and risperidone may be beneficial options for treatment of paradoxical insomnia. Larger clinical trials with longer periods of follow-up are needed for further investigation.
On the evaluation of generative models in music

The modeling of artificial, human-level creativity is becoming more and more achievable. In recent years, neural networks have been successfully applied to different tasks such as image and music generation, demonstrating their great potential in realizing computational creativity. The fuzzy definition of creativity combined with varying goals of the evaluated generative systems, however, makes subjective evaluation seem to be the only viable methodology of choice. We review the evaluation of generative music systems and discuss the inherent challenges of their evaluation. Although subjective evaluation should always be the ultimate choice for the evaluation of creative results, researchers unfamiliar with rigorous subjective experiment design and without the necessary resources for the execution of a large-scale experiment face challenges in terms of reliability, validity, and replicability of the results. In numerous studies, this leads to the report of insignificant and possibly irrelevant results and the lack of comparability with similar and previous generative systems. Therefore, we propose a set of simple musically informed objective metrics enabling an objective and reproducible way of evaluating and comparing the output of music generative systems. We demonstrate the usefulness of the proposed metrics with several experiments on real-world data.
Super-Resolution Using Convolutional Neural Networks Without Any Checkerboard Artifacts

It is well-known that a number of excellent super-resolution (SR) methods using convolutional neural networks (CNNs) generate checkerboard artifacts. A condition to avoid the checkerboard artifacts is proposed in this paper. So far, checkerboard artifacts have been mainly studied for linear multirate systems, but the condition to avoid checkerboard artifacts can not be applied to CNNs due to the non-linearity of CNNs. We extend the avoiding condition for CNNs, and apply the proposed structure to some typical SR methods to confirm the effectiveness of the new scheme. Experiment results demonstrate that the proposed structure can perfectly avoid to generate checkerboard artifacts under two loss conditions: mean square error and perceptual loss, while keeping excellent properties that the SR methods have.
A cross-cultural investigation of situational information security awareness programs

The aim of this research is to make users aware of the importance surrounding the issue of security and security awareness while at the same time making educators as well as other individuals aware of the differing effects of cultural dimensions into the learning process.  An inter-cultural study was conducted to investigate if users from the USA and Taiwan exposed to the same situational awareness learning would have different performance in those security awareness outcomes.  The findings confirm that American users who received the situational learning outperformed those users who received the traditional face-to-face instruction. Taiwanese users did not perform significantly differently between these two treatments.  The study was only focused on two countries and therefore may limit its implications worldwide. But the study does show that global citizens also react differently to security awareness as would be expected due to differing cultures. Certainly, awareness of the risks and safeguards is the first line of defense that can be employed by any individual, but how individuals address these risks can be very dissimilar in different cultures. Therefore, the implications are apparent that the issue of security awareness should be studied from different cultural perspectives.  This paper offers original findings and value into the investigation of whether or not situational security awareness training is culturally-bounded Charlie C. Chen, B. Dawn Medlin, R.S. Shaw (2008) "A Cross-Cultural Investigation Of Situational Information Security Awareness Programs" Information Management & Computer Security vol. 16(4) pp. 360-376 Version Of Record Available At www.emeraldinsight.com A Cross-Cultural Investigation Of Situational Information Security
Q-FDBA: improving QoE fairness for video streaming

Multiplayer video streaming scenario can be seen everywhere today as the video traffic is becoming the “killer” traffic over the Internet. The Quality of Experience fairness is critical for not only the users but also the content providers and ISP. Consequently, a QoE fairness adaptive method of multiplayer video streaming is of great importance. Previous studies focus on client-side solutions without network global view or network-assisted solution with extra reaction to client. In this paper, a pure network-based architecture using SDN is designed for monitoring network global performance information. With the flexible programming and network mastery capacity of SDN, we propose an online Q-learning-based dynamic bandwidth allocation algorithm Q-FDBA with the goal of QoE fairness. The results show the Q-FDBA could adaptively react to high frequency of bottleneck bandwidth switches and achieve better QoE fairness within a certain time dimension.
Convolution neural network-based lane change intention prediction of surrounding vehicles for ACC

Adaptive cruise control is one of the most widely used vehicle driver assistance systems. However, uncertainty about drivers' lane change maneuvers in surrounding vehicles, such as unexpected cut-in, remains a challenge. We propose a novel adaptive cruise control framework combining convolution neural network (CNN)-based lane-change-intention inference and a predictive controller. We transform real-world driving data, collected on public roads with only standard production sensors, to a simplified bird's-eye view. This enables a CNN-based inference approach with low computational cost and robustness to noisy input. The predicted inference of traffic participants' lane change intention is utilized to improve safety and ride comfort with model predictive control. Simulation results based on driving scene reconstruction demonstrate the superior performance of inference using the proposed CNN-based approach, as well as enhanced safety and ride comfort.
Interoperability Challenges for ICT-enabled Governance: Towards a pan-European Conceptual Framework

In the European academic and institutional debate, interoperability is predominantly seen as a means to enable public administrations to collaborate within Members State and across borders. The article presents a conceptual framework for ICT-enabled governance and analyses the role of interoperability in this regard. The article makes a specific reference to the exploratory research project carried out by the Information Society Unit of the Institute for Prospective Technological Studies (IPTS) of the European Commission’s Joint Research Centre on emerging ICT-enabled governance models in EU cities (EXPGOV). The aim of this project is to study the interplay between ICTs and governance processes at city level and formulate an interdisciplinary framework to assess the various dynamics emerging from the application of ICT-enabled service innovations in European cities. In this regard, the conceptual framework proposed in this article results from an action research perspective and investigation of e-governance experiences carried out in Europe. It aims to elicit the main value drivers that should orient how interoperable systems are implemented, considering the reciprocal influences that occur between these systems and different governance models in their specific context.
Tourette's syndrome, trichotillomania, and obsessive–compulsive disorder: How closely are they related?

The question of whether Tourette's syndrome (TS) and trichotillomania (TTM) are best conceptualized as obsessive-compulsive spectrum disorders was raised by family studies demonstrating a close relationship between TS and obsessive-compulsive disorder (OCD), and by psychopharmacological research indicating that both TTM and OCD respond more robustly to clomipramine than to desipramine. A range of studies have subsequently allowed comparison of the phenomenology, psychobiology, and management of TS and TTM, with that of OCD. Here we briefly review this literature. The data indicate that there is significant psychobiological overlap between TS and OCD, supporting the idea that TS can be conceptualized as an OCD spectrum disorder. TTM and OCD have only partial overlap in their phenomenology and psychobiology, but there are a number of reasons for why it may be useful to classify TTM and other habit disorders as part of the obsessive-compulsive spectrum of disorders.
Computing Tensor Eigenvalues via Homotopy Methods

We introduce the concept of mode-k generalized eigenvalues and eigenvectors of a tensor and prove some properties of such eigenpairs. In particular, we derive an upper bound for the number of equivalence classes of generalized tensor eigenpairs using mixed volume. Based on this bound and the structures of tensor eigenvalue problems, we propose two homotopy continuation type algorithms to solve tensor eigenproblems. With proper implementation, these methods can find all equivalence classes of isolated generalized eigenpairs and some generalized eigenpairs contained in the positive dimensional components (if there are any). We also introduce an algorithm that combines a heuristic approach and a Newton homotopy method to extract real generalized eigenpairs from the found complex generalized eigenpairs. A MATLAB software package TenEig has been developed to implement these methods. Numerical results are presented to illustrate the effectiveness and efficiency of TenEig for computing complex or real generalized eigenpairs.
Syntactic Skeleton-Based Translation

In this paper we propose an approach to modeling syntactically-motivated skeletal structure of source sentence for machine translation. This model allows for application of high-level syntactic transfer rules and low-level non-syntactic rules. It thus involves fully syntactic, non-syntactic, and partially syntactic derivations via a single grammar and decoding paradigm. On large-scale Chinese-English and EnglishChinese translation tasks, we obtain an average improvement of +0.9 BLEU across the newswire and web genres.
Management of deformational plagiocephaly: repositioning versus orthotic therapy.

We compare positioning with orthotic therapy in 298 consecutive infants referred for correction of head asymmetry.



We evaluated 176 infants treated with repositioning, 159 treated with helmets, and 37 treated with initial repositioning followed by helmet therapy when treatment failed. We compared reductions in diagonal difference (RDD) between repositioning and cranial orthotic therapy. Helmets were routinely used for infants older than 6 months with DD >1 cm.



For infants treated with repositioning at a mean age of 4.8 months, the mean RDD was 0.55 cm (from an initial mean DD of 1.05 cm). For infants treated with cranial orthotics at a mean age of 6.6 months, the mean RDD was 0.71 cm (from an initial mean DD of 1.13 cm).



Infants treated with orthotics were older and required a longer length of treatment (4.2 vs 3.5 months). Infants treated with orthosis had a mean final DD closer to the DD in unaffected infants (0.3 +/- 0.1 cm), orthotic therapy was more effective than repositioning (61% decrease versus 52% decrease in DD), and early orthosis was significantly more effective than later orthosis (65% decrease versus 51% decrease in DD).
Mathematical analysis of the pharmacokinetic-pharmacodynamic (PKPD) behaviour of monoclonal antibodies: predicting in vivo potency.

We consider the relationship between the target affinity of a monoclonal antibody and its in vivo potency. The dynamics of the system is described mathematically by a target-mediated drug disposition model. As a measure of potency, we consider the minimum level of the free receptor following a single bolus injection of the ligand into the plasma compartment. From the differential equations, we derive two expressions for this minimum level in terms of the parameters of the problem, one of which is valid over the full range of values of the equilibrium dissociation constant K(D) and the other which is valid only for a large drug dose or for a small value of K(D). Both of these formulae show that the potency achieved by increasing the association constant k(on) can be very different from the potency achieved by decreasing the dissociation constant k(off). In particular, there is a saturation effect when decreasing k(off) where the increase in potency that can be achieved is limited, whereas there is no such effect when increasing k(on). Thus, for certain monoclonal antibodies, an increase in potency may be better achieved by increasing k(on) than by decreasing k(off).