nils-herrmann/clean_scirepeval huggingface dataset:
Defining the clinical pathway in cochrane diagnostic test accuracy reviews
Venue: BMC Medical Research Methodology
Year: 2016

BackgroundThe value of a medical test depends on the context in which it might be used. Ideally, questions, results and conclusions of a diagnostic test accuracy (DTA) systematic review should be presented in light of this context. There is increasing acceptance of the value for knowing the impact a test can have on downstream consequences such as costs, implications for further testing and treatment options however there is currently no explicit guidance on how to address this. Authors of a Cochrane diagnostic review have recently been asked to include the clinical pathway in which a test maybe used. We aimed to evaluate how authors were developing their clinical pathways in the light of this.MethodsWe searched the Cochrane Database of Systematic Reviews for all published DTA reviews. We included only those reviews that included a clinical pathway. We developed a checklist, based on the guidance in the Cochrane Handbook for DTA review authors. To this, we added a number of additional descriptors. We checked if the included pathways fulfilled these descriptors as defined by our checklist.ResultsWe found 47 reviews, of which 33 (73 contained aspects pertaining to a clinical pathway. The 33 reviews addressed the clinical pathway differently, both in content and format. Of these, 21 provided a textual description and 12 include visual and textual descriptions. There was considerable variation in how comprehensively review authors adhered to our checklist. Eighteen reviews (51 linked the index test results to downstream clinical management actions and patient consequences, but only eight went on to differentially report on the consequences for false negative results and nine on the consequences for false positive results.ConclusionThere is substantial variation in the clinical pathway descriptions in Cochrane systematic reviews of test accuracy. Most reviews do not link misclassifications (i.e. false negatives and false positive) to downstream patient consequences. Review authors could benefit from more explicit guidance on how to create such pathways, which in turn can help guide them in their evidence selection and appraisal of the evidence in the context of downstream consequences of testing.
Quantifying 3D Shape Similarity Using Maps: Recent Trends, Applications and Perspectives
Venue: Eurographics
Year: 2014

Shape similarity is an acute issue in Computer Vision and Computer Graphics that involves many aspects of human perception of the real world, including judged and perceived similarity concepts, deterministic and probabilistic decisions and their formalization. 3D models carry multiple information with them (e.g. geometry, topology, texture, time evolution, appearance) which can be thought as the filter that drives the recognition process. Assessing and quantifying the similarity between 3D shapes is necessary to explore large dataset of shapes, and tune the analysis framework to the user's needs. Many efforts have been done in this sense, including several attempts to formalize suitable notions of similarity and distance among 3D objects and their shapes. In the last years, 3D shape analysis knew a rapidly growing interest in a number of challenging issues, ranging from deformable shape similarity to partial matching and view point selection. In this panorama, we focus on methods which quantify shape similarity (between two objects and sets of models) and compare these shapes in terms of their properties (i.e. global and local, geometric, differential and topological) conveyed by (sets of) maps. After presenting in detail the theoretical foundations underlying these methods, we review their usage in a number of 3D shape application domains, ranging from matching and retrieval to annotation and segmentation. Particular emphasis will be given to analyse the suitability of the different methods for specific classes of shapes (e.g. rigid or isometric shapes) as well as the flexibility of the various methods at the different stages of the shape comparison process. Finally, the most promising directions for future research developments are discussed.
ActiveClean: Interactive Data Cleaning For Statistical Modeling
Venue: Proc. VLDB Endow.
Year: 2016

Analysts often clean dirty data iteratively cleaning some data, executing the analysis, and then cleaning more data based on the results. We explore the iterative cleaning process in the context of statistical model training, which is an increasingly popular form of data analytics. We propose ActiveClean, which allows for progressive and iterative cleaning in statistical modeling problems while preserving convergence guarantees. ActiveClean supports an important class of models called convex loss models (e.g. linear regression and SVMs) and prioritizes cleaning those records likely to affect the results. We evaluate ActiveClean on five real world datasets UCI Adult, UCI EEG, MNIST, IMDB, and Dollars For Docs with both real and synthetic errors. The results show that our proposed optimizations can improve model accuracy by up to 2.5x for the same amount of data cleaned. Furthermore for a fixed cleaning budget and on all real dirty datasets, ActiveClean returns more accurate models than uniform sampling and Active Learning.
Generational diversity: impact on recruitment and retention of registered nurses.
Venue: The Journal of nursing administration
Year: 2006

The aging of the registered nurse indicates that as nurses retire, there will be insufficient replacement numbers. Many shortages linked to increased demand and the solution was simply to increase the supply. Education was made more accessible, salaries were increased, and within 3 to 5 years the problem was solved. Unfortunately, today's nursing shortage is more complex than earlier shortages. One of the biggest concerns related to the supply issue is the average age of practicing registered nurses is 44 years. Approximately 50% of nurses will leave the work force to retire in the next 10 years. In addition, 50% of school of nursing faculty will retire by 2010, compounding the problem of not only recruiting people to nursing, but having enough teachers. By the year 2020, the registered nurse work force will fall short of demand by 20% or nearly 500,000 nurses; this will come when the first wave of baby boomers celebrate their 65th birthday. The study also indicated that some of this shortage is related to a shift of careers from nursing school to medical school. The research indicated that an average nurse's salary tops out at $47,000; when young women see their growth potential, they opt for careers with higher income possibilities. Salaries are not the only factor decreasing the supply of nurses. As the nurse work force was downsized in the 1990s, many nurses left hospital nursing for positions that offer normal work hours with no weekend and holiday work. When people are faced with making career choices, nursing is often perceived as unstable, high risk, and demeaning. With these facts in mind and decreasing reimbursements, healthcare administrators are challenged to not only attract people to their facility, but also retain current staff. Simply increasing hourly wages or offering sign on bonuses do not seem to be providing incentive, This is leading to study of the value of nonmonetary benefits that recruit and retain staff. Although nursing salaries are only one of several factors that influence recruitment, it does have a direct impact on retention. So to retain staff, working conditions of a 24 hour, 7 days a week operation require some modifications reflective of identified needs of the work force. The present nursing work force has an interesting make up, involving 4 distinct generations, often with different needs. This generational diversity is an important issue in designing a work environment that attracts both the younger generation and, hopefully, retains the present generation of nurses as long as possible. Today's nursing work force is compromised of primarily 3 of the 4 generationsVthe Traditional Generation, the Baby Boomers, and Generation X. The Generation Y group is in the process of choosing their careers. Generalizations have been made about each generation and what has shaped them. In examining generational diversity, we see the following.
Context Sensitive Fencing: Securing Speculative Execution via Microcode Customization
Venue: ASPLOS
Year: 2019

This paper describes context sensitive fencing (CSF) a microcode level defense against multiple variants of Spectre. CSF leverages the ability to dynamically alter the decoding of the instruction stream, to seamlessly inject new micro ops, including fences, only when dynamic conditions indicate they are needed. This enables the processor to protect against the attack, but with minimal impact on the efficacy of key performance features such as speculative execution. This research also examines several alternative fence implementations, and introduces three new types of fences which allow most dynamic reorderings of loads and stores, but in a way that prevents speculative accesses from changing visible cache state. These optimizations reduce the performance overhead of the defense mechanism, compared to state of the art software based fencing mechanisms by a factor of six.
A Cross Platform Test Management System for the SUDAAN Statistical Software Package
Venue: 2009 Seventh ACIS International Conference on Software Engineering Research, Management and Applications
Year: 2009

Testing software can be particularly challenging for a small or mid size firm interested in commercially distributing their software to a wide variety of users. Testing is clearly an important part of any software development life cycle (SDLC) because it provides a method for the developers to verify and validate the software. However, testing can be expensive and time consuming, and creating a testing strategy that ensures a software product is 100% bug free is unrealistic and impossible. This paper discusses the methodologies used to address one component of software testing by a small group of developers (essentially equivalent to a small firm) responsible for programming and distributing the SUDAAN(r) Statistical Software product. In addition we discuss SUDAAN's bug management system. Specifically, this paper discusses issues related to testing and debugging software on multiple platforms and operating systems.
On the complexity of Nash equilibria of action graph games
Venue: SODA
Year: 2009

In light of much recent interest in finding a model of multi player multi action games that allows for efficient computation of Nash equilibria yet remains as expressive as possible, we investigate the computational complexity of Nash equilibria in the recently proposed model of action graph games (AGGs) AGGs, introduced by Bhat and Leyton Brown, are succinct representations of games that encapsulate both local dependencies as in graphical games, and partial indifference to other agents' identities as in anonymous games, which occur in many natural settings such as financial markets. This is achieved by specifying a graph on the set of actions, so that the payoff of an agent for selecting a strategy depends only on the number of agents playing each of the neighboring strategies in the action graph. We present a simple Fully Polynomial Time Approximation Scheme for computing mixed Nash equilibria of AGGs with constant degree, constant treewidth and a constant number of agent types (but an arbitrary number of strategies) and extend this algorithm to a broader set of instances. However, the main results of this paper are negative, showing that when either of the latter conditions are relaxed the problem becomes intractable. In particular, we show that even if the action graph is a tree but the number of agent types is unconstrained, it is NP complete to decide the existence of a pure strategy Nash equilibrium and PPAD complete to compute a mixed Nash equilibrium (even an approximate one) Similarly for AGGs with a constant number of agent types but unconstrained treewidth. These hardness results suggest that, in some sense, our FPTAS is as strong a positive result as one can expect. In the broader context of trying to pin down the boundary where the equilibria of multi player games can be computed efficiently, these results complement recent hardness results for graphical games and algorithmic results for anonymous games.
Financial Knowledge and Short Term and Long Term Financial Behaviors of Millennials in the United States
Year: 2019

This study investigates the role of financial knowledge in various short term and long term financial behaviors among Millennials in the United States. Results from the 2015 National Financial Capability Study (NFCS) indicate that Millennials have lower levels of objective financial knowledge and similar levels of perceived financial knowledge as compared to all households. Consistent multivariate results find financial knowledge to be positively associated with performing positive short term and long term financial behaviors. Results are found to be robust across different measurements of financial knowledge and behavior, and the issue of the potential for reverse causality is specifically addressed. This study provides a comprehensive financial profile of Millennials with important insight for policymakers as well as financial practitioners.
Understanding primary school students' use of self regulated writing strategies through think aloud protocols
Year: 2018

This study seeks to extend our current understanding about the relationship between writing competence, grade level and use of self regulated writing strategies. Especially, research regarding primary school students' use of self regulated writing strategies in an ESL/EFL context is still lacking. Thirty two Singapore primary school students wrote a picture composition while thinking aloud. Through analysis of the participants' think aloud protocols related their use of metacognitive and cognitive writing strategies, the findings show that the students used 24 self regulated writing strategies among the 87 writing strategies found in the sample more than once. The high competence students outperformed their low competence counterparts in using both metacognitive and cognitive strategies. However, inconsistent findings were found between the middle graders and upper graders. The study underscores the importance of understanding young learners' use of self regulated writing strategies through think aloud protocols. The findings provide practical implications for teachers to conduct differentiated writing instruction in an ESL/EFL context.
Makerspaces in University Colleges: a workshop about maker technologies and design thinking in higher education
Venue: FabLearn
Year: 2018

VIA University College in Denmark is currently placing greater priority on Makerspaces, with special focus on material design in all its education programs (e.g. teacher trainings, social service workers, social education etc. The special feature of the Makerspaces initiative is the dual perspective on learning. Educating teacher students entails having the dual perspective of learning to master technologies and design processes, while also mastering the ability to create learning designs for childrens' innovative design processes in maker settings. In this workshop, we (1) lay out our teaching approach, (2) provide examples of course activities, (3) provide a hands on example of our teaching methods, and (4) invite participants to discuss a dual perspective on learning in maker settings in teacher education. This workshop will provide a case example of how the teachers at VIA University College incorporate digital fabrication and design processes in the courses for student teachers and students in Social Education.
Migration Experiences of Foreign Educated Nurses
Venue: Journal of transcultural nursing official journal of the Transcultural Nursing Society
Year: 2016

Global nurse migration has a recognized impact on host and source countries, but the lived experience of foreign educated nurses is an important aspect of the success of this migration. A systematic review of the literature was conducted to understand the lived migration and acculturation experiences of foreign educated nurses.  A systematic review of the literature, based on Preferred Reporting Items for Systematic Reviews and Meta Analyses (PRISMA) guidelines, was conducted. Primary research articles or secondary analyses were selected based on keyword and citation based searches (n 44) Findings: Nurses' experiences included migration and licensing barriers, difficulty with communication, racism and discrimination, skill underutilization, acculturation, and the role of the family.  Barriers encountered in host countries may impede acculturation and successful nursing practice, resulting in circular migration and poor patient safety outcomes.  Social support systems and cultural orientation programs can mitigate the impacts of social isolation and racism. Addressing common barriers can help minimize deskilling and allow safe and effective transitions to host countries.
Suffering in silence: How COVID 19 school closures inhibit the reporting of child maltreatment
Venue: Journal of Public Economics
Year: 2020

To combat the spread of COVID 19, many primary and secondary schools in the United States canceled classes and moved instruction online. This study examines an unexplored consequence of COVID 19 school closures: the broken link between child maltreatment victims and the number one source of reported maltreatment allegations school personnel. Using current, county level data from Florida, we estimate a counterfactual distribution of child maltreatment allegations for March and April 2020, the first two months in which Florida schools closed. While one would expect the financial, mental, and physical stress due to COVID 19 to result in additional child maltreatment cases, we find that the actual number of reported allegations was approximately 15,000 lower (27% than expected for these two months. We leverage a detailed dataset of school district staffing and spending to show that the observed decline in allegations was largely driven by school closures. Finally, we discuss policy implications of our findings for the debate surrounding school reopenings and suggest a number of responses that may mitigate this hidden cost of school closures.
An Analysis of BERT in Document Ranking
Venue: SIGIR
Year: 2020

Although BERT has shown its effectiveness in a number of IR related tasks, especially document ranking, the understanding of its internal mechanism remains insufficient. To increase the explainability of the ranking process performed by BERT, we investigate a state of the art BERT based ranking model with focus on its attention mechanism and interaction behavior. Firstly, we look into the evolving of the attention distribution. It shows that in each step, BERT dumps redundant attention weights on tokens with high document frequency (such as periods) This may lead to a potential threat to the model robustness and should be considered in future studies. Secondly, we study how BERT models interactions between query and document and find that BERT aggregates document information to query token representations through their interactions, but extracts query independent representations for document tokens. It indicates that it is possible to transform BERT into a more efficient representation focused model. These findings help us better understand the ranking process by BERT and may inspire future improvement.
Tiny YOLO object detection supplemented with geometrical data
Venue: 2020 IEEE 91st Vehicular Technology Conference (VTC2020 Spring)
Year: 2020

We propose a method of improving detection precision (mAP) with the help of the prior knowledge about the scene geometry: we assume the scene to be a plane with objects placed on it. We focus our attention on autonomous robots, so given the robot's dimensions and the inclination angles of the camera, it is possible to predict the spatial scale for each pixel of the input frame. With slightly modified YOLOv3 tiny we demonstrate that the detection supplemented by the scale channel, further referred as S, outperforms standard RGB based detection with small computational overhead.
Estimating the Associations between SNAP and Food Insecurity, Obesity, and Food Purchases with Imperfect Administrative Measures of Participation
Venue: Southern Economic Journal
Year: 2019

Administrative data are considered the "gold standard" when measuring program participation, but little evidence exists on the potential problems with administrative records or their implications for econometric estimates. We explore issues with administrative data using the FoodAPS, a unique dataset that contains two different administrative measures of Supplemental Nutrition Assistance Program (SNAP) participation as well as a survey based measure. We first document substantial ambiguity in the two administrative participation variables and show that they disagree with each other almost as often as they disagree with self reported participation. Estimated participation and misreporting rates can be meaningfully sensitive to choices made to resolve this ambiguity and disagreement. We then document similar sensitivity in regression estimates of the associations between SNAP and food insecurity, obesity, and the Healthy Eating Index. These results serve as a cautionary tale about uncritically relying on linked administrative records when conducting program evaluation research.
Bovista himalaica sp. nov. (gasteroid fungi; Basidiomycetes) from Pakistan
Venue: Mycological Progress
Year: 2012

The gasteroid fungus Bovista himalaica sp. nov. (Agaricaceae; Basidiomycota) is described and illustrated from Himalayan moist temperate forests of Pakistan. Analysis of the ITS region of the nuclear ribosomal RNA gene suggests B. himalaica is phylogenetically distinct and confirms its position within Bovista section Globaria. Descriptions with SEM images of spores, comparison with closely related taxa, and a key to the Bovista species with ovoid oblong basidiospores are provided.
Importance of Local Data and Resource Allocation for Effective Successful Public Health Interventions to Reduce COVID 19 Transmission: Commentary on COVID 19 Medical Vulnerability Indicators: A Predictive Local Data Model for Equity in Public Health Decision Making
Venue: International journal of environmental research and public health
Year: 2021

The article, COVID 19 Medical Vulnerability Indicators: Predictive Local Data Model for Equity in Public Health Decision Making (2021) is an important contribution to identifying and prioritizing the needs of Los Angeles' public healthcare in responding to the COVID 19 pandemic crisis