nils-herrmann/clean_scirepeval huggingface dataset:
Corporate Board of Directors: Structure and Efficiency
Year: 2018

Cette these a pour objectif principal d'apporter une contribution a la litterature concernant la structure et l'efficacite du conseil d'administration (CA) Elle s'articule autour de quatre chapitres. Le premier chapitre est une revue de la litterature, tandis que les trois autres portent sur des questions de recherche distinctes. La premiere etude presentee dans le deuxieme chapitre de cette these a pour objectif d'etudier les determinants de la taille du CA, de l'independance de ses membres et de la dualite des fonctions de direction et de presidence du CA. Les principaux apports de cette etude peuvent etre resumes comme suit tout d'abord, nos resultats sont fondes sur l'analyse d'un des plus grands echantillons utilises dans ce domaine, avec a peu pres 16000 observations (entreprises annees) pour pres de 2300 entreprises americaines observees de 1997 a 2010. De plus, sur le plan methodologique, une batterie de tests statistiques a ete realisee afin de verifier la robustesse de nos resultats, notamment des tests tenant compte des biais d'heterogeneite et de simultaneite. Enfin, cette etude est probablement la premiere a demontrer que le passage de la loi SOX a limite la capacite des dirigeants a influencer la composition du CA. La deuxieme etude s'attache a analyser les deux principales fonctions du CA, qui sont le conseil au chef d'entreprise et le controle de ses activites. Ainsi, comprendre la capacite du CA a remplir ces fonctions est une question fondamentale que nous nous proposons d'approfondir. Cette etude vient enrichir la litterature emergente sur la fonction consultative du CA en fournissant de nouveaux elements de preuves sur l'importance de cette fonction dans la creation de valeur de l'entreprise. Ces resultats apportent egalement des eclairages sur le conflit potentiel existant entre les deux principales fonctions du CA. Enfin, cette etude s'inscrit dans le courant de pensee qui cherche a evaluer l'impact des caracteristiques des entreprises sur l'efficacite de leurs structures de gouvernance. Le principal objectif de la troisieme etude presentee dans le dernier chapitre de cette these est de determiner si la remuneration a base d'actions des administrateurs peut affecter les decisions futures en matiere d'acquisition, et le cas echeant, comment. Les resultats de cette etude apportent un nouvel eclairage concernant la remuneration des administrateurs. Cette etude met en exergue l'importance des pratiques de remuneration incitative sous forme d'actions et d'options pour les membres du CA. Par ailleurs, bien que de nombreuses etudes aient ete realisees afin d'analyser la relation existante entre les mesures incitatives a destination des administrateurs et la performance de l'entreprise, notre etude est l'une des premieres a explorer les mecanismes a travers lesquels ces mesures peuvent influencer la valeur de l'entreprise.
Issues for Deployment of Mobile Learning by Nurses in Australian Healthcare Settings
Venue: Nursing Informatics
Year: 2016

Undergraduate nursing curricula are being redesigned to include strategies for deployment of mobile learning as a legitimate nursing function. A recent online survey exploring the use of mobile learning by undergraduate student nurses revealed barriers, challenges, risks, and benefits to using mobile learning at the workplace. Inability to access mobile learning at both individual and organisational levels impacted on student learning and teaching opportunities. Students also indicated that educational preparation for ensuring appropriate use of mobile learning is necessary to guide learning and teaching in situ at point of care. This highlights the need for the development of policy to guide best practice that will enable this new pedagogy to be fully utilised for learning and teaching in healthcare settings. Until governance of mobile learning in educational and healthcare settings in Australia is addressed, harnessing the indubitable benefit of mobile learning and teaching will be unachievable.
Web Based Learning: Design, Implementation, and Evaluation
Year: 2006

PART I INTRODUCTION TO WEB BASED LEARNING, COMMUNITIES, AND INSTRUCTIONAL DESIGN Chapter 1 Overview of Web Based Instruction, Web Based Learning Environments, and Web Based Learning Communities Chapter 2 Foundations of Web Based Instructional Design PART II THE WBID MODEL FOR CREATING A WEB BASED COMMUNITY OF LEARNERS Chapter 3 Analysis: Considering Goals, Context, and Learners Chapter 4 Analysis: Considering the Instructional Content for Web Based Instruction Chapter 5 Planning the Evaluation of Web Based Instruction Chapter 6  Pre Planning and Design Tasks Chapter 7  Plans into Development Action PART III IMPLEMENTATION AND EVALUATION OF WEB BASED INSTRUCTION Chapter 9  Establishing a Sense of Community Chapter 10 Conducting Summative  The Final Stage
Magnitude and risk factors of non communicable diseases among people living with HIV in Tanzania: a cross sectional study from Mbeya and Dar es Salaam regions
Venue: BMC Public Health
Year: 2014

BackgroundHIV and Non communicable diseases (NCDs) are major problem of public health importance in developing countries. This study was conducted to explore and establish information on the magnitude, distribution of NCDs risk factors among people living with HIV (PLWHIV) which is scarce in Tanzania.MethodA cross sectional study was conducted to PLWHIV from 12 care and treatment clinics in Dar es Salaam and Mbeya regions from October 2011 to February 2012. Data on demographic characteristics, NCD risk factors including behavioral, biochemical tests and physical measurements was collected from PLWHIV.ResultsOf 754 PLWHIV recruited, 671(89.0% consented to participate in the study and 354/671(52.8% were on antiretroviral therapy (ART) The following NCD risk factors: raised blood levels of low density lipoprotein (61.3% vs 38.7% p 0.001) total cholesterol (TC) (71.6% vs 28.4% p 0.001) and triglyceride (67.0% vs 33.0% p 0.001) as well as overweight/obesity (61.1% vs 38.9% p 0.010) abnormal waist circumference (61.7% vs 38.3% p 0.001) and being aged >40 years (63.3% vs 36.7% p 0.001) were more prevalent among PLWHIV on ART than ART naive. The prevalence of Diabetes mellitus among PLWHIV was 4.2% and was slightly high among those ART naive (4.7% vs 3.7% The prevalence of hypertension was 26.2% and was high among those on ART (30.0% vs 21.9% p 0.010) Being aged >40 years (AOR 2.52, 95% CI 1.37 4.63) abnormal waist circumference (AOR 2.37 95% CI 1.13 5.00) overweight/obesity (AOR 2.71, 95% CI 1.26 5.84) and male sex (AOR 1.17, 1.02 4.20) were the predictors of hypertension among patients on ART while raised TC (AOR 1.47 (1.01 2.21) and being aged >40 years (AOR 3.42, 95% CI 2.06 5.70) were predictors for hypertension among ART naive patients.ConclusionThis study has revealed that the magnitude of NCD risk factors is significantly higher among PLWHIV on ART than those not on ART. Initiating and strengthening of interventions for minimizing preventable NCD risks should be considered when initiating ART among PLWHIV. Regular monitoring of NCD risk factors is of paramount importance among ART patients.
Text Detection Using Maximally Stable External Regions and Stroke Width Variation
Year: 2019

There is a proverb "an image is worth, than ten thousand words" So it is very difficult to explain a single image. But what happens if a single image itself contains some information in the form of text. Though it is easy to extract text from the structured image, it is difficult to retrieve it from unstructured image. Thus in this paper, we are providing an efficient and concrete algorithm to solve this problem. This algorithm consists of detecting candidate text region using maximally stable external regions (MSER) Then it removes false region based on basic geometric properties. Now, again removing false region based on stroke width variation (SWV) and finally merging all text regions for detection of the result. At last, recognition of detected text with the help of optical character recognition (OCR) All these methods are combined to give high performance of the proposed algorithm.
Innate Immune Mechanisms with a Focus on Small Molecule Microbe Host Cross Talk
Venue: Journal of Innate Immunity
Year: 2019

"Life would not exist with macromolecules alone"  This thematic issue of the Journal of Innate Immunity takes up a slightly different angle and zooms in on the microbes describing their mutual interactions with the innate immune system via small molecules. Most of the articles focus or touch upon the bacterial multicellular lifestyle called biofilm. This is maybe not surprising as these microbial populations embedded in a self produced extracellular matrix adherent to each other and/or to a surface or interfaces  have developed intricate tolerance mechanisms against the actions of the immune system and most conventional antimicrobial therapies, which enables biofilm forming bacteria to associate with 80% of human infections [3, 4] However, fully competent eukaryotic organisms respond with sophisticated defense mechanisms against microbial biofilms [5] For example, antimicrobial peptides can specifically tackle biofilm bacteria at subinhibitory concentration [6, 7] These features of antimicrobial peptides are exploited for novel anti biofilm therapies as described by Dostert et al.  in this issue. The free radical NO is another innate immune component with a broad concentration dependent activity against microbes ranging from a signaling molecule like anti biofilm to a bactericidal activity [9, 10] Williams and Boon [11] describe the anti biofilm molecular mechanisms of action to be surprisingly convergent in different bacteria with NO being consistently sensed by two types of conserved sensors covalently or noncovalently connected downstream to a quorum sensing and/or second messenger cyclic di GMP signaling output [12] Both, extracellular quorum sensing and intracellular cyclic diGMP signaling can be intimately connected to biofilm regulation  Reactive nitrogen and oxygen species are effective bactericidal molecules, but pathogens like gastroenteritis causing Salmonella typhimurium have also developed effective detoxification and repair defense systems as described by Rhen [13] Perhaps not surprising, Lesouhaitier et al.  report that also nonprofessional innate immune components such as eukaryotic communication molecules interfere with bacterial biofilm formation, physiology, and virulence. However, the bacteria have evolved the ability to fight innate immune mechanisms. Although primarily recognized as a bacterial derived potent immune stimulatory molecule [15] secreted cyclic di GMP surprisingly has an anti innate immune activity preventing lipocalin 2 to sequester iron scavenging siderophores as discovered by Cui et al.  But microorganisms can not only overcome host siderophore scavenging strategies with their plethora of over 500 recognized siderophores, but counteract a diversity of innate immune mechanisms beyond their anti scavenging activities as described by Golonka et al.
How psychological resourcefulness increases salesperson's sales performance and the satisfaction of their customers: Exploring the mediating role of customer oriented behaviors
Year: 2017

This research examines the relationships among psychological resourcefulness, customer oriented behaviors, sales performance, and customer satisfaction. Drawing from positive organizational behavior and broaden and build theory, the authors propose that (1) psychological resourcefulness positively influences customer oriented behaviors and (2) customer oriented behaviors mediate the influence of psychological resourcefulness on sales performance and customer satisfaction. The authors test, and provide support for, these hypotheses using a unique data set consisting of objective sales performance data and survey data collected from 175 salesperson customer dyads from various industries within a business to business setting. The broader contribution of the article is that psychological resourcefulness may be central to salesperson performance and customer relationship effectiveness. Implications of the findings for theoreticians and practitioners are discussed.
Ragnar Nurkse and the international financial architecture*
Year: 2018

This lecture discusses the work by the Estonian economist Ragnar Nurkse (1907 1959) It focuses on the early Nurkse, who was concerned with exchange rates, capital flows and what today we call the international financial architecture. It asks how many of the conclusions of International Currency Experience [Nurkse, R. (1944) International Currency Experience. Geneva: League of Nations. survive.
A Three Stage Deep Learning Model for Accurate Retinal Vessel Segmentation
Venue: IEEE Journal of Biomedical and Health Informatics
Year: 2019

Automatic retinal vessel segmentation is a fundamental step in the diagnosis of eye related diseases, in which both thick vessels and thin vessels are important features for symptom detection. All existing deep learning models attempt to segment both types of vessels simultaneously by using a unified pixel wise loss that treats all vessel pixels with equal importance. Due to the highly imbalanced ratio between thick vessels and thin vessels (namely the majority of vessel pixels belong to thick vessels) the pixel wise loss would be dominantly guided by thick vessels and relatively little influence comes from thin vessels, often leading to low segmentation accuracy for thin vessels. To address the imbalance problem, in this paper, we explore to segment thick vessels and thin vessels separately by proposing a three stage deep learning model. The vessel segmentation task is divided into three stages, namely thick vessel segmentation, thin vessel segmentation, and vessel fusion. As better discriminative features could be learned for separate segmentation of thick vessels and thin vessels, this process minimizes the negative influence caused by their highly imbalanced ratio. The final vessel fusion stage refines the results by further identifying nonvessel pixels and improving the overall vessel thickness consistency. The experiments on public datasets DRIVE, STARE, and CHASE_DB1 clearly demonstrate that the proposed three stage deep learning model outperforms the current state of the art vessel segmentation methods.
Rational Emotional Behavior Therapy (REBT) to Reduce Anxiety Bullying Victims in Adolescents
Year: 2020

Bullying is an act of hurting others physically and mentally and is done repeatedly. The case of bullying is one of the issues that are still a particular concern at Muhammadiyah Boarding School Al Mujahidin Gunungkidul. This study aims to reduce the anxiety of victims of bullying by using a rational emotive behavior therapy (REBT) counseling approach. The subjects of this study were students of class VII Muhammadiyah Boarding School Al Mujahidin Gunungkidul, who were victims of bullying in classes and schools with a total of 28 students. This research was conducted from August 1 to September 30, 2017. The type and design of the study used collaborative action research. Data analysis was carried out quantitatively using a questionnaire for victims of bullying anxiety. Qualitative analysis is performed on data obtained from interviews, observations, and follow up. The counseling program with the rational emotive behavior therapy (REBT) approach has proven to be effective and has an effect on reducing anxiety in bullying victims, which is characterized by a decrease in anxiety scores. In addition, the subject feels that he is not alone or not isolated; self confidence increases have a role towards others and can observe and follow instructions given by the researcher.
Uncertainty quantification metrics for whole product life cycle cost estimates in aerospace innovation
Year: 2015

The lack of defensible methods for quantifying cost estimate uncertainty over the whole product life cycle of aerospace innovations such as propulsion systems or airframes poses a significant challenge to the creation of accurate and defensible cost estimates. Based on the axiomatic definition of uncertainty as the actual prediction error of the cost estimate, this paper provides a comprehensive overview of metrics used for the uncertainty quantification of cost estimates based on a literature review, an evaluation of publicly funded projects such as part of the CORDIS or Horizon 2020 programs, and an analysis of established approaches used by organizations such NASA, the U.S. Department of Defence, the ESA, and various commercial companies. The metrics are categorized based on their foundational character (foundations) their use in practice (state of practice) their availability for practice (state of art) and those suggested for future exploration (state of future) Insights gained were that a variety of uncertainty quantification metrics exist whose suitability depends on the volatility of available relevant information, as defined by technical and cost readiness level, and the number of whole product life cycle phases the estimate is intended to be valid for. Information volatility and number of whole product life cycle phases can hereby be considered as defining multi dimensional probability fields admitting various uncertainty quantification metric families with identifiable thresholds for transitioning between them. The key research gaps identified were the lacking guidance grounded in theory for the selection of uncertainty quantification metrics and lacking practical alternatives to metrics based on the Central Limit Theorem. An innovative uncertainty quantification framework consisting of; a set theory based typology, a data library, a classification system, and a corresponding input output model are put forward to address this research gap as the basis for future work in this field.
The vehicle routing problem latest advances and new challenges
Year: 2008

Overviews and Surveys. Routing a Heterogeneous Fleet of Vehicles. A Decade of Capacitated Arc Routing. Inventory Routing. The Period Vehicle Routing Problem and its Extensions. The Split Delivery Vehicle  A Survey. Challenges and Advances  A Categorized Bibliography. Parallel Solution Methods for Vehicle Routing Problems. Recent Developments in Dynamic Vehicle Routing Systems. New Directions in Modeling and Algorithms. Online Vehicle Routing Problems: A Survey. Modeling and Solving the Capacitated Vehicle Routing Problem on Trees. Using a Genetic Algorithm to Solve the Generalized Orienteering Problem. An Integer Linear Programming Local Search for Capacitated Vehicle Routing Problems. Robust Branch Cut and Price Algorithms for Vehicle Routing Problems. Recent Models and Algorithms for One to One Pickup and Delivery Problems. One to Many to One Single Vehicle Pickup and Delivery Problems. Challenges and Opportunities in Attended Home Delivery. Chvatal Gomory Rank 1 Cuts Used in a Dantzig Wolfe Decomposition of the Vehicle Routing Problem with Time Windows. Vehicle Routing Problems with Inter Tour Resource Constraints. From Single Objective to Multi Objective Vehicle Routing Problems: Motivations, Case Studies, and Methods.  Vehicle Routing for Small Package Delivery and Pickup Services. Advances in Meter Reading: Heuristic Solution of the Close Enough Traveling Salesman Problem over a Street Network. Multiperiod Planning and Routing on a Rolling Horizon for Field Force Optimization Logistics. Health Care Logistics, Emergency Preparedness, and Disaster Relief: New Challenges for Routing Problems with a Focus on the Austrian Situation. Vehicle Routing Problems and Container Terminal Operations An Update of Research.
Learn on Source, Refine on Target: A Model Transfer Learning Framework with Random Forests
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence
Year: 2017

We propose novel <italic>model transfer learning</italic> methods that refine a decision forest model <inline formula><tex math notation="LaTeX"$M$/tex math><alternatives> <inline graphic xlink:href="segev ieq1 2618118.gif"/alternatives>/inline formula> learned within a "source" domain using a training set sampled from a "target" domain, assumed to be a variation of the source. We present two random forest transfer algorithms. The first algorithm searches greedily for locally optimal modifications of each tree structure by trying to locally expand or reduce the tree around individual nodes. The second algorithm does not modify structure, but only the parameter (thresholds) associated with decision nodes. We also propose to combine both methods by considering an ensemble that contains the union of the two forests. The proposed methods exhibit impressive experimental results over a range of problems.
Bluff: Interactively Deciphering Adversarial Attacks on Deep Neural Networks
Venue: 2020 IEEE Visualization Conference (VIS)
Year: 2020

Deep neural networks (DNNs) are now commonly used in many domains. However, they are vulnerable to adversarial attacks: carefully crafted perturbations on data inputs that can fool a model into making incorrect predictions. Despite significant research on developing DNN attack and defense techniques, people still lack an understanding of how such attacks penetrate a model's internals. We present Bluff, an interactive system for visualizing, characterizing, and deciphering adversarial attacks on vision based neural networks. Bluff allows people to flexibly visualize and compare the activation pathways for benign and attacked images, revealing mechanisms that adversarial attacks employ to inflict harm on a model. Bluff is open sourced and runs in modern web browsers.
Immunization with the Yersiniabactin Receptor, FyuA, Protects against Pyelonephritis in a Murine Model of Urinary Tract Infection
Venue: Infection and Immunity
Year: 2013

Urinary tract infections (UTI) are common and represent a substantial economic and public health burden. Roughly 80% of these infections are caused by a heterogeneous group of uropathogenic Escherichia coli (UPEC) strains. Antibiotics are standard therapy for UTI, but a rise in antibiotic resistance has complicated treatment, making the development of a UTI vaccine more urgent. Iron receptors are a promising new class of vaccine targets for UTI, as UPEC require iron to colonize the iron limited host urinary tract and genes encoding iron acquisition systems are highly expressed during infection. Previously, three of six UPEC siderophore and heme receptors were identified as vaccine candidates by intranasal immunization in a murine model of ascending UTI. To complete the assessment of iron receptors as vaccine candidates, an additional six UPEC iron receptors were evaluated. Of the six vaccine candidates tested in this study (FyuA, FitA, IroN, the gene product of the CFT073 locus c0294, and two truncated derivatives of ChuA) only FyuA provided significant protection (P 0.0018) against UPEC colonization. Intranasal immunization induced a robust and long lived humoral immune response. In addition, the levels of FyuA specific serum IgG correlated with bacterial loads in the kidneys [Spearman's rank correlation coefficient r(14) 0.72, P 0.0018] providing a surrogate of protection. FyuA is the fourth UPEC iron receptor to be identified from our screens, in addition to IutA, Hma, and IreA, which were previously demonstrated to elicit protection against UPEC challenge. Together, these iron receptor antigens will facilitate the development of a broadly protective, multivalent UTI vaccine to effectively target diverse strains of UPEC.