nils-herrmann/clean_scirepeval huggingface dataset:
Diagnostic Accuracy of Full Body Linear X Ray Scanning in Multiple Trauma Patients in Comparison to Computed Tomography.
Venue: RoFo Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin

The purpose of this study was to evaluate the diagnostic accuracy of full body linear X ray scanning (LS) in multiple trauma patients in comparison to 128 multislice computed tomography (MSCT) MATERIALS AND METHODS 106 multiple trauma patients (female: 33; male: 73) were retrospectively included in this study. All patients underwent LS of the whole body, including extremities, and MSCT covering the neck, thorax, abdomen, and pelvis. The diagnostic accuracy of LS for the detection of fractures of the truncal skeleton and pneumothoraces was evaluated in comparison to MSCT by two observers in consensus. Extremity fractures detected by LS were documented.  The overall sensitivity of LS was 49.2 the specificity was 93.3 the positive predictive value was 91 and the negative predictive value was 57.5 The overall sensitivity for vertebral fractures was 16.7 and the specificity was 100 The sensitivity was 48.7 and the specificity 98.2 for all other fractures. Pneumothoraces were detected in 12 patients by CT, but not by LS. 40 extremity fractures were detected by LS, of which 4 fractures were dislocated, and 2 were fully covered by MSCT.  The diagnostic accuracy of LS is limited in the evaluation of acute trauma of the truncal skeleton. LS allows fast whole body X ray imaging, and may be valuable for detecting extremity fractures in trauma patients in addition to MSCT.  The overall sensitivity of LS for truncal skeleton injuries in multiple trauma patients was 50 The diagnostic reference standard MSCT is the preferred and reliable imaging modality. LS may be valuable for quick detection of extremity fractures.
Sustainable synthesis of silver nanoparticles using macroalgae Spirogyra varians and analysis of their antibacterial activity

In this research, silver nanoparticles (SNPs) were synthesized through bio reduction of silver ions using the Spirogyra varians The procedure used is simple and sustainable making it suitable for economic production of SNPs. The structure and morphology of SNPs were characterized by UV visible spectroscopy, X ray diffraction (XRD) pattern, scanning electron microscopy (SEM) and Fourier Transform Infra Red (FTIR) These nanoparticles indicated an absorption peak at 430 nm in the UV visible spectrum. The crystallite average size was estimated about 17.6 nm and SEM image confirmed synthesis of relatively uniform nanoparticles. The antibacterial effect of SNPs was also tested on several micro organisms by measuring the inhibition zone, MIC and MBC. The results confirmed that SNPs can act as a powerful antibacterial agent against various pathogenic bacteria.
Evaluation of mobile learning in workplace iraining
Venue: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)

At present, the organizations use either wired or wireless devices to exploit the internet services for effectively training their employees to achieve higher progression and production in their businesses. However, buying desktop PCs or mobile devices like laptops or tablet computers etc. for every employee, may exceed the financial plans designed for an organization. This leads us to take advantage of employee owned personal mobile devices, which helps organizations to reduce hardware costs. Now, to evaluate the effectiveness of the owned personal mobile devices, this study evaluates the learning performances of employees, who learn and acquire workplace trainings, through their owned personnel mobile devices, at their workplaces. For the purpose of evaluation, an experiment was conducted on two groups of learners. Observed experiment results indicate that the learning among organizational employees via the mobile devices, significantly promotes learning value, effects and increases approval levels for mobile technology adoption in their learning process. The results are useful for researchers involved in improving the development process of mobile learning projects dedicated to the organizational workplace training needs.
The unassigned distance geometry problem
Venue: Discret. Appl. Math.

Studies of distance geometry problems (DGP) have focused on cases where the vertices at the ends of all or most of the given distances are known or assigned, which we call assigned distance geometry problems (aDGPs) In this contribution we consider the unassigned distance geometry problem (uDGP) where the vertices associated with a given distance are unknown, so the graph structure has to be discovered. uDGPs arises when attempting to find the atomic structure of molecules and nanoparticles using X ray or neutron diffraction data from non crystalline materials. Rigidity theory provides a useful foundation for both aDGPs and uDGPs, though it is restricted to generic realizations of graphs, and key results are summarized. Conditions for unique realization are discussed for aDGP and uDGP cases, build up algorithms for both cases are described and experimental results for uDGP are presented.
Grover's Algorithm applied to the Molecular Distance Geometry Problem

Grover's algorithm is a quantum algorithm for searching in unstructured databases. Due to the proper ties of quantum mechanics, it provides a quadratic speedup over its classical counterparts. We present a new applica tion of the algorithm to the Molecular Distance Geome try Problem. This problem is related to the determination of the tridimensional structure of a molecule based on the knowledge of some of the distances between pairs of atoms. This problem is NP hard unless all possible inter atomic distances are known. Index Terms Quantum Computation, Grover's algo rithm, Molecular Distance Geometry Problem.
Service Productivity: What Stops Service Firms from Measuring It?

Productivity measurement poses a challenge for service organizations. Conventional management wisdom holds that this challenge is rooted in the difficulty of accurately quantifying service inputs and outputs. Few service firms have adequate service productivity measurement (SPM) systems in place and implementing such systems may involve organizational transformation. Combining field interviews and literature based insights, the authors develop a conceptual model of antecedents of SPM in service firms and test it using data from 276 service firms. Results indicate that one out of five antecedents affects the choice to use SPM, namely, the degree of service standardization. In addition, all five hypothesized antecedents and one additional antecedent (perceived appropriateness of the current SPM) predict the degree of SPM usage. In particular, the degree of SPM is positively influenced by the degree of service standardization, service customization, investments in service productivity gains, and the appropriateness of current service productivity measures. In turn, customer integration and the perceived difficulty of measuring service productivity negatively affect SPM. The fact that customer integration impedes actual measurement of service productivity is a surprising finding, given that customer integration is widely seen as a means to increase service productivity. The authors conclude with implications for service organizations and directions for research.
A cross country study of service productivity

This study empirically examines service productivity and complements prior studies by framing service productivity as consisting of a number of key constituents. Adopting a bottom up approach we present an integrative model proposing that resource commitment is the core from which employee readiness and customer readiness flow. These inform service productivity, which, in turn, informs job security. Our empirical examination reveals that service productivity has an impact on perceptions of job security, while resource commitment has the greatest impact on both employee readiness and customer readiness. In developing our integrative model we provide a framework that other researchers can apply, particularly where the service is highly intangible or in the public sector where service providers are being increasingly challenged to demonstrate value for money.
Characterizing Twitter Discussions About HPV Vaccines Using Topic Modeling and Community Detection
Venue: Journal of medical Internet research

In public health surveillance, measuring how information enters and spreads through online communities may help us understand geographical variation in decision making associated with poor health outcomes.  Our aim was to evaluate the use of community structure and topic modeling methods as a process for characterizing the clustering of opinions about human papillomavirus (HPV) vaccines on Twitter.  The study examined Twitter posts (tweets) collected between October 2013 and October 2015 about HPV vaccines. We tested Latent Dirichlet Allocation and Dirichlet Multinomial Mixture (DMM) models for inferring topics associated with tweets, and community agglomeration (Louvain) and the encoding of random walks (Infomap) methods to detect community structure of the users from their social connections. We examined the alignment between community structure and topics using several common clustering alignment measures and introduced a statistical measure of alignment based on the concentration of specific topics within a small number of communities. Visualizations of the topics and the alignment between topics and communities are presented to support the interpretation of the results in context of public health communication and identification of communities at risk of rejecting the safety and efficacy of HPV vaccines.  We analyzed 285,417 Twitter posts (tweets) about HPV vaccines from 101,519 users connected by 4,387,524 social connections. Examining the alignment between the community structure and the topics of tweets, the results indicated that the Louvain community detection algorithm together with DMM produced consistently higher alignment values and that alignments were generally higher when the number of topics was lower. After applying the Louvain method and DMM with 30 topics and grouping semantically similar topics in a hierarchy, we characterized 163,148 (57.16% tweets as evidence and advocacy, and 6244 (2.19% tweets describing personal experiences. Among the 4548 users who posted experiential tweets, 3449 users (75.84% were found in communities where the majority of tweets were about evidence and advocacy.  The use of community detection in concert with topic modeling appears to be a useful way to characterize Twitter communities for the purpose of opinion surveillance in public health applications. Our approach may help identify online communities at risk of being influenced by negative opinions about public health interventions such as HPV vaccines.
Cluster trees of improved trajectories for action recognition
Venue: Neurocomputing

Recently, as an efficient representation of realistic videos, improved trajectory features (ITF) combined with Fisher vector (FV) encoding achieved state of the art results on four challenging datasets concerning action recognition. However, directly integrating it with simple spatio temporal pyramid (STP) will result in performance degradation. Therefore, in this paper, a novel version of cluster trees model is proposed to improve recognition performance by taking into account spatio temporal relationships between local trajectory features. We modified and improved cluster trees model to reduce noisy clusters and alleviate intra class variation. A further advantage of the proposed method is significantly reducing memory storage and computation time by conduct dimensionality reduction on Fisher vectors. Finally, an adaptive kernel is proposed to efficiently compare the variable size tree representations of two videos for action recognition, which mitigates the risk introduced by noisy cluster tree nodes. Experimental results on four challenging action datasets (i.e. Olympic Sports, Hollywood2, HMDB51 and UCF50) demonstrate the effectiveness and robustness of the proposed approach which outperforms the current state of the art.
Human Action Recognition Using Improved Salient Dense Trajectories
Venue: Comput. Intell. Neurosci.

Human action recognition in videos is a topic of active research in computer vision. Dense trajectory (DT) features were shown to be efficient for representing videos in state of the art approaches. In this paper, we present a more effective approach of video representation using improved salient dense trajectories: first, detecting the motion salient region and extracting the dense trajectories by tracking interest points in each spatial scale separately and then refining the dense trajectories via the analysis of the motion saliency. Then, we compute several descriptors (i.e. trajectory displacement, HOG, HOF, and MBH) in the spatiotemporal volume aligned with the trajectories. Finally, in order to represent the videos better, we optimize the framework of bag of words according to the motion salient intensity distribution and the idea of sparse coefficient reconstruction. Our architecture is trained and evaluated on the four standard video actions datasets of KTH, UCF sports, HMDB51, and UCF50, and the experimental results show that our approach performs competitively comparing with the state of the art results.
The IEC 60255 121:2014 standard and its impact on performance specification, testing and evaluation of distance protection relays
Venue: 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)

Different test methodologies have been used in the past by various relay manufacturers to specify and assess the distance protection relay performance. This lead to difficulties in selecting relays for the correct application and also in comparing relays from different manufacturers. The IEC 60255 121 standard "Functional requirements for distance protection" published in March 2014, specifies the minimum requirements for functional and performance evaluation of distance protection relays, describes the tests to be performed and how to publish the test results. This paper clarifies the most important aspects of this new standard, detailing how it will positively impact the power system protection community.
3D point cloud based indoor mobile robot in 6 DoF pose localization using Fast Scene Recognition and Alignment approach
Venue: 2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)

This paper describes an algorithm for localization of a robot which can efficiently estimate robot in 6 degrees of freedom (DoF) pose which consist of position and orientation with large scale point cloud data without giving the initial pose. We introduce the Fast Scene Recognition and Alignment algorithm to reduce the computation time needed for the point cloud alignment by matching robot's scene only with the retrieved Sub Map in database. Our developed algorithm is to extract Sub Maps descriptor by cascading several features, and learn a Distance Metric to increase the precision of place recognition due to the environmental changes. We then align the robot's scene with Sub Map to estimate robot pose. Our technique has been implemented and tested extensively in different buildings. The experimental results show that our Fast Scene Recognition and Alignment system can localize mobile robot in a variety of large scale 3D point cloud dataset efficiently.
Unleashing the Power of Emotional Competency Development Program on Leaders' Self Motivation

This study attempts to investigate the effects of the emotional competency development program on leaders' self motivation. Eighty leaders at a non profit agency in Malaysia were involved in an experimental/control group research design where the experimental group was given a nine week emotional competency development program. Pre and post test were conducted to assess participants' self motivation using the Motivation Sources Inventory. The findings indicate that the emotional competency development program does have an effect on increasing leaders' self motivation. However, positive effects were only seen on intrinsic process, self concept internal and goal internalization. Whereas, the instrumental and self concept external does not produce any significant changes after the training. As a conclusion, this study has provided some empirical proof on the effectiveness of the EI training program on developing leaders' emotional intelligence and intrinsic motivation, which might contribute to the theoretical and methodological aspect of leadership development.
A Narrative Review of Diabetes Intervention Studies to Explore Diabetes Care Opportunities for Pharmacists
Venue: Journal of diabetes research

We conducted a review of current diabetes intervention studies in type 2 diabetes and identified opportunities for pharmacists to deliver quality diabetes care.  A search on randomised controlled trials (RCT) on diabetes management by healthcare professionals including pharmacists published between 2010 and 2015 was conducted.  Diabetes management includes multifactorial intervention which includes seven factors as outlined in diabetes guidelines, namely, glycaemic, cholesterol and blood pressure control, medication, lifestyle, education, and cardiovascular risk factors. Most studies do not provide evidence that the intervention methods used included all seven factors with exception of three RCT which indicated HbA1c (glycated hemoglobin) reduction range of 0.5% to 1.8% The varied HbA1C reduction suggests a lack of standardised and consistent approach to diabetes care. Furthermore, the duration of most studies was from one month to two years; therefore long term outcomes could not be established.  Although pharmacists' contribution towards improving clinical outcomes of diabetes patients was well documented, the methods used to deliver structured, consistent evidence based care were not clearly stipulated. Therefore, approaches to achieving long term continuity of care are uncertain. An intervention strategy that encompass all seven evidence based factors will be useful.
A Family Based, Culturally Tailored Diabetes Intervention for Hispanics and Their Family Members
Venue: The Diabetes educator

The purpose of this study was to test efficacy of a family based, culturally tailored intervention for Hispanics with type 2 diabetes and their family members.  Hispanic patients with type 2 diabetes and their family members recruited from community clinics and ethnic churches were assigned to groups (N 186) The intervention group received an 8 week culturally tailored diabetes educational program delivered in Spanish while the attention control group received 8 weekly sessions on general health information and 2 sessions on diabetes after completion of the study. Data were collected at baseline, after intervention, and at 1 and 6 month follow ups for both patients and families. Comparisons of change over time were performed using growth curve analyses after propensity score adjustment.  Intervention patients improved in diabetes knowledge and diabetes self efficacy over time (but did not sustain at 6 month follow up) A1C was lower at 1 month follow up. Family members had improvements in diabetes knowledge and physical health related quality of life.  Including families in the interventions may improve glycemic control, diabetes knowledge, self efficacy, and physical health related quality of life. However, strategies for sustaining improvements are needed.
Informatic analysis for hidden pulse attack exploiting spectral characteristics of optics in plug and play quantum key distribution system
Venue: Quantum Inf. Process.

Quantum channel loopholes due to imperfect implementations of practical devices expose quantum key distribution (QKD) systems to potential eavesdropping attacks. Even though QKD systems are implemented with optical devices that are highly selective on spectral characteristics, information theory based analysis about a pertinent attack strategy built with a reasonable framework exploiting it has never been clarified. This paper proposes a new type of trojan horse attack called hidden pulse attack that can be applied in a plug and play QKD system, using general and optimal attack strategies that can extract quantum information from phase disturbed quantum states of eavesdropper's hidden pulses. It exploits spectral characteristics of a photodiode used in a plug and play QKD system in order to probe modulation states of photon qubits. We analyze the security performance of the decoy state BB84 QKD system under the optimal hidden pulse attack model that shows enormous performance degradation in terms of both secret key rate and transmission distance.
Muraymycin nucleoside peptide antibiotics: uridine derived natural products as lead structures for the development of novel antibacterial agents
Venue: Beilstein journal of organic chemistry

Muraymycins are a promising class of antimicrobial natural products. These uridine derived nucleoside peptide antibiotics inhibit the bacterial membrane protein translocase I (MraY) a key enzyme in the intracellular part of peptidoglycan biosynthesis. This review describes the structures of naturally occurring muraymycins, their mode of action, synthetic access to muraymycins and their analogues, some structure activity relationship (SAR) studies and first insights into muraymycin biosynthesis. It therefore provides an overview on the current state of research, as well as an outlook on possible future developments in this field.
Real time human body tracking based on data fusion from multiple RGB D sensors
Venue: Multimedia Tools and Applications

In this work we present a human pose estimation method based on the skeleton fusion and tracking using multiple RGB D sensors. The proposed method considers the skeletons provided by each RGB D device and constructs an improved skeleton, taking into account the quality measures provided by the sensors at two different levels: the whole skeleton and each joint individually. Then, each joint is tracked by a Kalman filter, resulting in a smooth tracking performance. We have also developed a new dataset consisting of six subjects performing seven different gestures, recorded with four Kinect devices simultaneously. Experimental results performed on this dataset show that the system obtains better smoothness results than the most representative methods found in the literature. The proposed system operates at a processing rate of 25 frames per second (including the whole algorithm loop, i.e. data acquisition and processing) without the explicit use of the multithreading capabilities of the system.
An Agent Based Simulation of Residential Location Choice of Tenants in Tehran, Iran
Venue: Trans. GIS

Residential location choice modeling is one of the substantial components of land use and transportation models. While numerous aggregated mathematical and statistical approaches have been developed to model the residence choice behavior of households, disaggregated approaches such as the agent based modeling have shown interesting capabilities. In this article, a novel agent based approach is developed to simulate the residential location choice of tenants in Tehran, the capital of Iran. Tenants are considered as agents who select their desired residential alternatives according to their characteristics and preferences for various criteria such as the rent, accessibility to different services and facilities, environmental pollution, and distance from their workplace and former residence. The choice set of agents is limited to their desired residential alternatives by applying a constrained NSGA II algorithm. Then, agents compete with each other to select their final residence among their alternatives. Results of the proposed approach are validated by comparing simulated and actual residences of a sample of tenants. Results show that the proposed approach is able to accurately simulate the residence of 59.3% of tenants at the traffic analysis zone level.