nils-herrmann/clean_scirepeval huggingface dataset:
Translation, Adaptation, and Assessment of the Communication Assessment Tool in Tigray, Northern Ethiopia.
Venue: Journal of graduate medical education
Year: 2019

Ethiopia has experienced tremendous growth in medical education beginning in the early 2000s. Research shows a need for emphasis on empathy and compassionate care in this setting. In the United States, the Communication Assessment Tool (CAT) is a widely used, validated survey measuring provider patient interactions.  The goal of this study was to translate, culturally adapt, and pilot the CAT to allow it to be used with trainees and patients in Ethiopia.  Bilingual experts translated the CAT into Tigrigna, the primary language of the Tigray region in northern Ethiopia, followed by focus group discussions, back translation, and review by the original author of the CAT. The translated tool was administered to the patients of resident physicians in 6 specialties at Ayder Referral Hospital between December 2016 and February 2017.  Our translation of the CAT into Tigrigna had semantic, idiomatic, and experiential equivalence. Of 1024 patients recruited, 1002 (98% completed interviews using the CAT. Mean score was 3.09; 3% of all scores were excellent and 54% were good. Cronbach's alpha score for the full survey was 0.942, demonstrating high reliability.  The translated CAT in Tigrigna can be used to assess communication skills in Ethiopian residents. Both mean score and percentage of excellent scores were considerably lower than scores in other countries, suggesting that there may be opportunities for improvement in residents' communication skills.
Fair value accounting and analyst forecast accuracy
Year: 2017

This study examines the effect of fair value accounting on the behavior of analysts using a large, generalizable sample of U.S. firms. By employing a measure of firms' fair value intensity, we provide evidence showing that firms with higher fair value intensity have more accurate analyst earnings forecasts, a significant main effect elusive to Magnan, Menini, and Parbonetti (2015) Furthermore, by using disclosures required by Statement of Financial Accounting Standards (SFAS) No. 157, we find significant positive associations between analyst forecast accuracy and Level 1 and Level 2 fair value measurements, but we do not find such association for Level 3 measurements. We document that these main effects are predominantly concentrated in non financial industry firms in contrast to financial industry firms. This suggests that qualitative features of fair value measurements, including their business purpose and on average accounting treatment (e.g. trading assets, available for sale, etc. could also have an impact on analyst forecasting accuracy beyond mere measurement issues. Our results contribute to the debate over fair value accounting by showing the impact of fair value accounting upon an important participant in the capital markets.
Effect of Tiaoshen Kaiqiao acupuncture in the treatment of ischemic post stroke depression: a randomized controlled trial.
Year: 2017

To observe the effect of Tiaoshen Kaiqiao acupuncture in the treatment of ischemic post stroke depression.  This research was a single blind, positive controlled trial done in a single entity. Totally 58 patients with ischemic post stroke depression were randomly divided into two groups. The acupuncture group was given Tiaoshen Kaiqiao acupuncture therapy and placebo starch tablets treatment, while the control group was treated with fluoxetine tablets and body acupuncture treatment. Evaluated the clinical efficacy of the two groups with Hamilton Depression Scale (HAMD) Anti Depression Drug Side Effects Rating Scale (SERS) Clinical Global Impression Scale (CGI) respectively before treatment, the fourth weekend of treatment, the eighth weekend of treatment, the twelfth weekend of treatment. The adverse reactions in two groups were observed and documented.  The HAMD scale scores of the two groups in different treatment period were significantly decreased compared with that before treatment (P 0.05) There was significant difference between the SERS scores of two groups (P  The effects of Tiaoshen Kaiqiao acupuncture and fluoxetine in the treatment of ischemic post stroke depression were similar, but the former had no obvious adverse reaction and side effects.
Ruptured anomalous hyperplastic anterior choroidal artery aneurysm: a case report.
Venue: British journal of neurosurgery
Year: 2019

A 48 year old man hospitalized for subarachnoid hemorrhage harbored a ruptured aneurysm arising from an anomalous hyperplastic anterior choroidal artery. Endovascular treatment was performed and the aneurysm was successfully embolized with neck remnant. The anterior choroidal artery is a very important artery supplying critical brain structures in the treatment of intracranial vascular disease. Anomalous hyperplastic anterior choroidal artery is rare, so the embryological perspective is important for its recognition in surgical procedures.
A DTN Routing and Buffer Management Strategy for Message Delivery Delay Optimization
Venue: 2015 8th IFIP Wireless and Mobile Networking Conference (WMNC)
Year: 2015

Delay Tolerant Networks (DTNs) are sparse mobile ad hoc networks in which there is typically no complete path between the source and destination. To increase the reliability of message delivery, multi copy routing is often used at the expense of high buffer and bandwidth overhead. While much work has been done in the design of forwarding algorithms, little work has focused on studying forwarding under the presence of resource constraints such as short contact durations and small buffers. In this paper, we investigate a multi copy routing strategy and a buffer management policy that minimize the average message delivery delay in DTN networks with resource constraints. We focus on three key issues: (1) to which next hop relay node should messages be replicated, (2) in which order should messages be replicated when contact duration and forwarding bandwidth are limited, and (3) which messages should be dropped first when the buffer is full. We propose to forward a message to a neighboring node with the least expected minimum delay among all possible routes to the message's destination. For the second and third issue, we develop a utility function using global network information to compute per packet average delay utility. Messages are then scheduled and dropped according to their utility values. Extensive simulation results based on the real world San Francisco cab trace show that our proposed scheme can deliver messages in up to 30% less time than existing schemes, while still achieving a high delivery ratio.
Bitumen and Bitumen Modification: A Review on Latest Advances
Venue: Applied Sciences
Year: 2019

This synthesis explores the state of the knowledge and state of the practice regarding the latest updates on polymer modified bitumens (PmBs) The information in this study was gathered from a thorough review of the latest papers in the literatures related to modified bituminous materials, technologies, and advances. For this purpose, the paper is presented in two principle sections. In the first part, the bitumen itself is investigated in terms of chemical structure and microstructural systems. In the second part, the paper focuses on bitumen modification from different aspects for assessing the effectiveness of the introduced additives and polymers for enhancing the engineering properties of bitumen in both paving and industrial applications. In conclusion, the knowledge obtained in this study has revealed the importance of the chemical composition of base bitumen for its modification. It can be declared that while some polymers/additives can improve one or some aspects of neat bitumen properties, they can lead to compatibility problems in storage and production. In this respect, several studies showed the effectiveness of waxes for improving the compatibility of polymers with bitumen in addition to some benefits regarding warm mix asphalt (WMA) production.
Touch Editing: A Flexible One Time Interaction Approach for Translation
Venue: AACL
Year: 2020

We propose a touch based editing method for translation, which is more flexible than traditional keyboard mouse based translation postediting. This approach relies on touch actions that users perform to indicate translation errors. We present a dual encoder model to handle the actions and generate refined translations. To mimic the user feedback, we adopt the TER algorithm comparing between draft translations and references to automatically extract the simulated actions for training data construction. Experiments on translation datasets with simulated editing actions show that our method significantly improves original translation of Transformer (up to 25.31 BLEU) and outperforms existing interactive translation methods (up to 16.64 BLEU) We also conduct experiments on post editing dataset to further prove the robustness and effectiveness of our method.
Treatments for Poststroke Motor Deficits and Mood Disorders: A Systematic Review for the 2019 U.S. Department of Veterans Affairs and U.S. Department of Defense Guidelines for Stroke Rehabilitation
Venue: Annals of Internal Medicine
Year: 2019

Early rehabilitation after stroke is essential to help reduce disability.  To summarize evidence on the benefits and harms of nonpharmacologic and pharmacologic treatments for motor deficits and mood disorders in adults who have had stroke. Data Sources English language searches of multiple electronic databases from April 2009 through July 2018; targeted searches to December 2018 for studies of selective serotonin reuptake inhibitors (SSRIs) or serotonin norepinephrine reuptake inhibitors. Study Selection 19 systematic reviews and 37 randomized controlled trials addressing therapies for motor deficits or mood disorders in adults with stroke.  One investigator abstracted the data, and quality and GRADE assessment were checked by a second investigator.  Most interventions (for example, SSRIs, mental practice, mirror therapy) did not improve motor function. High quality evidence did not support use of fluoxetine to improve motor function. Moderate quality evidence supported use of cardiorespiratory training to improve maximum walking speed and repetitive task training or transcranial direct current stimulation to improve activities of daily living (ADLs) Low quality evidence supported use of robotic arm training to improve ADLs. Low quality evidence indicated that antidepressants may reduce depression, whereas the frequency and severity of antidepressant related adverse effects was unclear. Low quality evidence suggested that cognitive behavioral therapy and exercise, including mind body exercise, may reduce symptoms of depression and anxiety. Limitation Studies were of poor quality, interventions and comparators were heterogeneous, and evidence on harms was scarce.  Cardiorespiratory training, repetitive task training, and transcranial direct current stimulation may improve ADLs in adults with stroke. Cognitive behavioral therapy, exercise, and SSRIs may reduce symptoms of poststroke depression, but use of SSRIs to prevent depression or improve motor function was not supported.
Capcane de diagnostic in patologia pulmonara malformativa la copil
Year: 2020

Bronchogenic cyst in children is a lung malformative pathology that can often be confused with the initial presentation of infectious or tumor processes. The symptoms may be minimal when bronchogenic cysts are found accidentally, or mimicking complicated bacterial lung infections. Imaging (lung CT or MRI) describes the lesion, and the surgical resection is postponed until the cyst becomes symptomatic or, frequently, overinfected. The authors present two recent cases of children diagnosed with bronchogenic cyst at the age of small infant, and at 5 years old, with their peculiarities of presentation and evolution.
Increasing Support and Job Satisfaction for Program Administrators at the Postgraduate Medical Education Program at the University of Ottawa: The Program Administrator's Perspective
Year: 2016

Realizing Program Administrators (PAs) are crucial to the success of the postgraduate medical education (PGME) program, the PGME office at the University of Ottawa conducted a needs analysis to (a) identify training opportunities PAs felt would support them in being effective at meeting role expectations including supporting Program Directors (PDs) and (b) gather information from PAs to guide the PGME office in taking positive action toward increasing satisfaction with services and resources.  A mixed methods approach involved collecting and analyzing data from online surveys and follow up qualitative interviews. Data analysis was conducted using the constructs of the W(e)Learn framework (content, media (delivery) service, structure and outcomes) Results PAs identified the following professional development topics they said would benefit them: Human Resources; Communication and Conflict Management Courses; Career Development; Evaluation; Policy; Multigenerational Workforces; and Best Technological Practices of Relevance to PAs The PAs also identified several recommendations for how the PGME office could facilitate them effectively carrying out their roles and responsibilities.  An effective form of support is offering convenient, relevant professional development to help employees meet role expectations. A well designed professional development program should begin with a needs analysis to determine stakeholder needs with regard to relevant content, preferred delivery methods, service issues and course structure, in order to ensure desired learner outcomes.
WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale
Venue: AAAI
Year: 2020

The Winograd Schema Challenge (WSC) (Levesque, Davis, and Morgenstern 2011) a benchmark for commonsense reasoning, is a set of 273 expert crafted pronoun resolution problems originally designed to be unsolvable for statistical models that rely on selectional preferences or word associations. However, recent advances in neural language models have already reached around 90% accuracy on variants of WSC. This raises an important question whether these models have truly acquired robust commonsense capabilities or whether they rely on spurious biases in the datasets that lead to an overestimation of the true capabilities of machine commonsense.To investigate this question, we introduce WinoGrande, a large scale dataset of 44k problems, inspired by the original WSC design, but adjusted to improve both the scale and the hardness of the dataset. The key steps of the dataset construction consist of (1) a carefully designed crowdsourcing procedure, followed by (2) systematic bias reduction using a novel AfLite algorithm that generalizes human detectable word associations to machine detectable embedding associations. The best state of the art methods on WinoGrande achieve 59.4 79.1% which are ~15 35% (absolute) below human performance of 94.0% depending on the amount of the training data allowed (2% 100% respectively).Furthermore, we establish new state of the art results on five related benchmarks WSC 90.1% DPR 93.1% COPA( 90.6% KnowRef 85.6% and Winogender 97.1% These results have dual implications: on one hand, they demonstrate the effectiveness of WinoGrande when used as a resource for transfer learning. On the other hand, they raise a concern that we are likely to be overestimating the true capabilities of machine commonsense across all these benchmarks. We emphasize the importance of algorithmic bias reduction in existing and future benchmarks to mitigate such overestimation.
A novel digital intervention for actively reducing severity of paediatric ADHD (STARS ADHD) a randomised controlled trial.
Venue: The Lancet. Digital health
Year: 2020

Attention deficit hyperactivity disorder (ADHD) is a common paediatric neurodevelopmental disorder with substantial effect on families and society. Alternatives to traditional care, including novel digital therapeutics, have shown promise to remediate cognitive deficits associated with this disorder and may address barriers to standard therapies, such as pharmacological interventions and behavioural therapy. AKL T01 is an investigational digital therapeutic designed to target attention and cognitive control delivered through a video game like interface via at home play for 25 min per day, 5 days per week for 4 weeks. This study aimed to assess whether AKL T01 improved attentional performance in paediatric patients with ADHD.  The Software Treatment for Actively Reducing Severity of ADHD (STARS ADHD) was a randomised, double blind, parallel group, controlled trial of paediatric patients (aged 8 12 years, without disorder related medications) with confirmed ADHD and Test of Variables of Attention (TOVA) Attention Performance Index (API) scores of 1*8 and below done by 20 research institutions in the USA. Patients were randomly assigned 1:1 to AKL T01 or a digital control intervention. The primary outcome was mean change in TOVA API from pre intervention to post intervention. Safety, tolerability, and compliance were also assessed. Analyses were done in the intention to treat population.  Between July 15, 2016, and Nov 30, 2017, 857 patients were evaluated and 348 were randomly assigned to receive AKL T01 or control. Among patients who received AKL T01 (n=180 [52% mean [SD] age, 9*7 3] years) or control (n=168 [48% mean [SD] age, 9*6 3] years) the non parametric estimate of the population median change from baseline TOVA API was 0*88 (95% CI 0*24 1*49; p=0*0060) The mean (SD) change from baseline on the TOVA API was 0*93 (3*15) in the AKL T01 group and 0*03 (3*16) in the control group. There were no serious adverse events or discontinuations. Treatment related adverse events were mild and included frustration (5 [3% of 180) and headache (3 [2% of 180) Patient compliance was a mean of 83 (83% of 100 expected sessions played (SD, 29*2 sessions) INTERPRETATION Although future research is needed for this digital intervention, this study provides evidence that AKL T01 might be used to improve objectively measured inattention in paediatric patients with ADHD, while presenting minimal adverse events.
Leadership of socio political vanguards: A review and future directions
Year: 2020

With the influential rise of the Alt Right throughout the West in recent years, there has been a renewed interest in the leadership of these forms of fringe political groups. While some work on the leadership of these types of groups was done in the 1960s, 70s, and 80s, less work has been done since then. Given the important role of these groups in today's political environment, a review and theoretical integration of this past leadership work, along with suggestions for future research directions, is overdue. This paper begins by reviewing what literature exists regarding the leadership of socio political vanguards, as well as what additional literature exists that may also be relevant to better understanding the phenomenon of vanguard leadership. Vanguard leadership is then placed within the historical context and goals of past vanguard groups. This analysis then leads to further defining some of the components of vanguard leadership along with a review of typically associated leadership traits, skills and behaviours. While few theories directly address the way in which vanguard leadership operates, this paper reviews related leadership theories that might offer meaningful contributions to our understanding of socio political vanguard leadership. Some theories, such as those related to social movements (particularly burgeoning) minor but influential mainstream political groups, and advocacy/activist collectives are particularly relevant here and are reviewed along with more general leadership theories that might also hold applicability, such as those related to leader and follower (and public) information processing and sensemaking under crises. The paper then concludes with some suggestions for future research directions.
A look inside the black box: Using graph theoretical descriptors to interpret a Continuous Filter Convolutional Neural Network (CF CNN) trained on the global and local minimum energy structures of neutral water clusters.
Venue: The Journal of chemical physics
Year: 2020

We describe a method for the post hoc interpretation of a neural network (NN) trained on the global and local minima of neutral water clusters. We use the structures recently reported in a newly published database containing over 5 x 106 unique water cluster networks (H2O)N of size N 3 30. The structural properties were first characterized using chemical descriptors derived from graph theory, identifying important trends in topology, connectivity, and polygon structure of the networks associated with the various minima. The code to generate the molecular graphs and compute the descriptors is available at https:/github.com/exalearn/molecular graph descriptors, and the graphs are available alongside the original database at https:/sites.uw.edu/wdbase/ A Continuous Filter Convolutional Neural Network (CF CNN) was trained on a subset of 500 000 networks to predict the potential energy, yielding a mean absolute error of 0.002 0.002 kcal/mol per water molecule. Clusters of sizes not included in the training set exhibited errors of the same magnitude, indicating that the CF CNN protocol accurately predicts energies of networks for both smaller and larger sizes than those used during training. The graph theoretical descriptors were further employed to interpret the predictive power of the CF CNN. Topological measures, such as the Wiener index, the average shortest path length, and the similarity index, suggested that all networks from the test set were within the range of values as the ones from the training set. The graph analysis suggests that larger errors appear when the mean degree and the number of polygons in the cluster lie further from the mean of the training set. This indicates that the structural space, and not just the chemical space, is an important factor to consider when designing training sets, as predictive errors can result when the structural composition is sufficiently different from the bulk of those in the training set. To this end, the developed descriptors are quite effective in explaining the results of the CF CNN (a.k.a. the "black box" model.
Mental distress during the COVID 19 pandemic: Its association with public perceptions toward government's pandemic responses and lifestyle changes
Venue: Current psychology
Year: 2021

In order to propose better mental health interventions under the pandemic threat, the present study aimed to investigate whether depression and anxiety are associated to Chinese adults' perceptions of government's pandemic responses and the personal lifestyle changes imposed by those responses during the COVID 19 pandemic. We used a telephone survey with random sampling and obtained a probability community sample of 616 adults (39.1% men; Mage 41.7, SDage 16.3) in Macao, China in April 2020. The prevalence of 8.8% probable depression and 12.0% probable anxiety was observed in this sample. Positive perceptions toward government's pandemic responses were found to be negatively associated with probable depression and probable anxiety (ORu .36 and .41, p .05) Three lifestyle changing stressors (i.e. increased family conflict, friendship deterioration, and weight gain) were commonly reported (29.9, 27.5, and 43.0% respectively) and displayed positive associations with probable depression (ORu 1.67 to 1.87, p .05) and probable anxiety (ORu 1.54 to 2.10, p .05) Our findings suggest protective effects of perceived trust and satisfaction regarding government's pandemic responses against mental distress and the potential mental health threats from three pandemic specific lifestyle changing stressors. These findings can inform clinicians and policymakers to better prepare for the mental health impacts of the current and future pandemics.