nils-herrmann/clean_scirepeval huggingface dataset:
Learning Category Specific Mesh Reconstruction from Image Collections
Venue: ECCV
Year: 2018

We present a learning framework for recovering the 3D shape, camera, and texture of an object from a single image. The shape is represented as a deformable 3D mesh model of an object category where a shape is parameterized by a learned mean shape and per instance predicted deformation. Our approach allows leveraging an annotated image collection for training, where the deformable model and the 3D prediction mechanism are learned without relying on ground truth 3D or multi view supervision. Our representation enables us to go beyond existing 3D prediction approaches by incorporating texture inference as prediction of an image in a canonical appearance space. Additionally, we show that semantic keypoints can be easily associated with the predicted shapes. We present qualitative and quantitative results of our approach on the CUB dataset, and show that we can learn to predict the diverse shapes and textures across birds using only an annotated image collection. We also demonstrate the the applicability of our method for learning the 3D structure of other generic categories.
FCET2EC (From controlled experimental trial to 2 everyday communication) How effective is intensive integrative therapy for stroke induced chronic aphasia under routine clinical conditions? A study protocol for a randomized controlled trial
Venue: Trials
Year: 2013

BackgroundTherapy guidelines recommend speech and language therapy (SLT) as the "gold standard" for aphasia treatment. Treatment intensity (i.e. =5 hours of SLT per week) is a key predictor of SLT outcome. The scientific evidence to support the efficacy of SLT is unsatisfactory to date given the lack of randomized controlled trials (RCT) particularly with respect to chronic aphasia (lasting for >6 months after initial stroke) This randomized waiting list controlled multi centre trial examines whether intensive integrative language therapy provided in routine in and outpatient clinical settings is effective in improving everyday communication in chronic post stroke aphasia.DesignParticipants are men and women aged 18 to 70 years, at least 6 months post an ischemic or haemorrhagic stroke resulting in persisting language impairment (i.e. chronic aphasia) 220 patients will be screened for participation, with the goal of including at least 126 patients during the 26 month recruitment period. Basic language production and comprehension abilities need to be preserved (as assessed by the Aachen Aphasia Test).Therapy consists of language systematic and communicative pragmatic exercises for at least 2 hours/day and at least 10 hours/week, plus at least 1 hour self administered training per day, for at least three weeks. Contents of therapy are adapted to patients' individual impairment profiles.Prior to and immediately following the therapy/waiting period, patients' individual language abilities are assessed via primary and secondary outcome measures. The primary (blinded) outcome measure is the A scale (informational content, or 'understandability' of the message) of the Amsterdam Nijmegen Everyday Language Test (ANELT) a standardized measure of functional communication ability. Secondary (unblinded) outcome measures are language systematic and communicative pragmatic language screenings and questionnaires assessing life quality as viewed by the patient as well as a relative.The primary analysis tests for differences between the therapy group and an untreated (waiting list) control group with respect to pre versus post 3 week therapy (or waiting period, respectively) scores on the ANELT A scale. Statistical between group comparisons of primary and secondary outcome measures will be conducted in intention to treat analyses.Long term stability of treatment effects will be assessed six months post intensive SLT (primary and secondary endpoints).Trial registrationRegistered in ClinicalTrials.gov with the Identifier NCT01540383
Demystifying the Influential IS Legends of Positivism
Venue: J. Assoc. Inf. Syst.
Year: 2018

Positivism has been used to establish a standard that Information Systems (IS) research must meet to be scientific. According to such positivistic beliefs in IS, scientific research should: 1) be generalizable, 2) focus on stable independent variables, 3) have certain ontological assumptions, and 4) use statistical or quantitative methods rather than qualitative methods. We argue that logical positivist philosophers required none of these. On the contrary, logical positivist philosophers regarded philosophizing in general and ontological considerations in particular as nonsense. Moreover, the positivists' preferred empirical research method was not a survey, but rather a qualitative observation recorded by field notes. In addition, positivist philosophers required neither statistical nor nonstatistical generalizability. At least some positivist philosophers also acknowledged the study of singular cases as being scientific. Many research orientations (e.g. single setting research, examination of change, qualitative research) that are deemed "unscientific" by positivism in IS seem to be "scientific" (in principle) according to logical positivism. In turn, generally speaking, what has been justified as scientific by positivism in IS (e.g. requirements of statistical or nonstatistical generalizability, surveys, independent variables, ontological views) were either not required by logical positivists or were regarded as nonsensical by logical positivists. Furthermore, given that positivism is sometimes associated (or confused) with logical empiricism in IS, we also briefly discuss logical empiricism. Finally, realizing that certain influential, taken forgranted assumptions that underlie IS research are unwarranted could have ground breaking implications for future IS research.
Prevalence and Risk factors for Urinary Incontinence in postmenopausal women
Venue: Journal of Medical Science And clinical Research
Year: 2019

1 BPTH Intern MAEER'S Physiotherapy College, Talegaon Dabhade 2 Professor MAEER'S Physiotherapy College, Talegaon Dabhade 3 Principal, MAEER'S Physiotherapy College, Talegaon Dabhade Corresponding Author Prajakta Deshmukh BPTH Intern MAEER'S Physiotherapy College, Talegaon Dabhade Abstract Urinary incontinence is the involuntary loss of urine which is objectively demonstrable and is social and hygienic problem. The prevalence of urinary incontinence has been reported to increase at menopause and menopausal age.  To find out the prevalence of urinary incontinence and risk factors among postmenopausal women.  105 subjects were selected in the age group of 45 65 based on inclusion and exclusion criteria in and around Talegaon Dabhade. Questionnaire of female urinary incontinence diagnosis was asked by the therapist to the subjects.  The prevalence of urinary incontinence was found to be 55% among postmenopausal women. Mixed urinary incontinence was the commonest type.  The study shows the prevalence of urinary incontinence was 55% among postmenopausal women in Talegaon Dabhade. Parity 3 or more, Increasing age, Hysterectomy, Diabetes mellitus and high BMI were the risk factors associated with it.
Treatment of Wastewater from Car Washes Using a Biofilter
Year: 2017

This project investigates the treatment of wastewater from two car washes using a biofilter of peat and carbon containing ash. An evaluation of the efficiency and waste handling of the filter material was done from an environmental perspective. The biofilters were used during 2 and 4 years respectively. The treatment included an oil separator and a peat/ash biofilter. The main function of the oil separator was to reduce the amount of oil in the wastewater. The peat/ash biofilter was used as a second step of the system to treat mainly heavy metals. A comparison with the guiding values for wastewater from car washes in the municipality of Kristianstad showed that this type of filter works well. Wastewater from car washes may contain many different unhealthy and environmentally dangerous substances such as surfactants and aromatic compounds. More tests are needed to investigate if the treatment method reduces such parameters from the wastewater as well. After usage the filter is considered solid waste and is to be classified and handled according to that. Classification of the filter as waste requires knowledge about the content of environmentally harmful substances in products used in the car washes. As the content of non analyzed substances in the filters was unknown, combustion was regarded to be an environmentally good way of disposing the filter material as both energy and ashes are recycled.
Probabilistic Hyperproperties of Markov Decision Processes
Venue: ATVA
Year: 2020

Hyperproperties are properties that describe the correctness of a system as a relation between multiple executions. Hyperproperties generalize trace properties and include information flow security requirements, like noninterference, as well as requirements like symmetry, partial observation, robustness, and fault tolerance. We initiate the study of the specification and verification of hyperproperties of Markov decision processes (MDPs) We introduce the temporal logic PHL (Probabilistic Hyper Logic) which extends classic probabilistic logics with quantification over schedulers and traces. PHL can express a wide range of hyperproperties for probabilistic systems, including both classical applications, such as probabilistic noninterference, and novel applications in areas such as robotics and planning. While the model checking problem for PHL is in general undecidable, we provide methods both for proving and for refuting formulas from a fragment of the logic. The fragment includes many probabilistic hyperproperties of interest.
Antimicrobial resistance, respiratory tract infections and role of biofilms in lung infections in cystic fibrosis patients.
Venue: Advanced drug delivery reviews
Year: 2015

Lung infection is the main cause of morbidity and mortality in patients with cystic fibrosis and is mainly dominated by Pseudomonas aeruginosa. The biofilm mode of growth makes eradication of the infection impossible, and it causes a chronic inflammation in the airways. The general mechanisms of biofilm formation and antimicrobial tolerance and resistance are reviewed. Potential anti biofilm therapeutic targets such as weakening of biofilms by quorum sensing inhibitors or antibiotic killing guided by pharmacokinetics and pharmacodynamics of antibiotics are presented. The vicious circle of adaptive evolution of the persisting bacteria imposes important therapeutic challenges and requires development of new drug delivery systems able to reach the different niches occupied by the bacteria in the lung of cystic fibrosis patients.
An introduction to digital media research methods: how to research and the implications of new media data
Year: 2016

Digital methods have previously been described as 'a term that seeks to capture a recent development in Internet related research, summarized as approaches to the web as data set' Using this as a starting point, this paper positions digital media methods as a methodological approach that incorporates internet based data, while also including other communicative and social media platforms such as Instagram, Vine, Twitter, giffy, Periscope, and Facebook amongst others. Digital media methods also extends to database research, data generated by sensors, drones and autonomous automobiles. Contemporary research engaging digital media methods is built upon the 'computational turn' where 'computational approaches is increasingly reflected across a number of disciplines, including the arts, humanities and social sciences, which use technologies to shift the critical ground of their concepts and theories' As media and communication scholars, our 'research is increasingly being mediated through digital technology. affecting both the epistemologies and ontologies that underlie a research program' This paper highlights three significant points of departure for digital media methods in the media and communication discipline: the increasing need for typologies and ontologies in social media research; the significance of mapping public issues; and the difficulties researchers face as text based communication shifts to visually oriented platforms.
What Cost and Usage Data Reveals About E Book Acquisitions: Ramifications for Collection Development
Year: 2015

To better determine how e book acquisitions might affect future collection development decisions, a team of librarians from the University of Florida (UF) launched a project to assess cost and usage of e books purchased using three different acquisitions methods: e books acquired in large publisher packages; single title e books selected through firm orders; and e books purchased through two patron driven acquisitions (PDA) plans. The cost usage data were then sorted into three broad areas of subject disciplines humanities and social sciences (HSS) science technology engineering mathematics (STEM) and medicine (MED) and the results were reviewed and summarized. The authors compared the cost usage data of e books acquired by the acquisitions methods across the three subject areas and describe how the findings are affecting current and future acquisitions, traditional collection management, and budgeting at UF.
Young Children's Curiosity About Physical Differences Associated with Race: Shared Reading to Encourage Conversation
Year: 2016

Many have called for re examination of the "colorblind" philosophy to which some early educators have, tacitly or explicitly, adhered (e.g. Boutte et al. 2011; Derman Sparks and Edwards 2010; Husband 2012) It has been argued that, while colorblind approaches may appear to be politically neutral, they actually exacerbate racial oppression. In this article, we advocate for a direct and active approach to raising conversations about race with younger preschool children. Based on the developmental nature of young children's concepts of self and of other, our focus is on initiating discussions about concrete and observable physical aspects of human diversity associated with race. Young children notice and are curious about differences in skin color, hair texture, and facial features. Because these differences are salient, are accessible, and are of interest to young children they can serve as an effective starting point. We suggest shared reading of high quality illustrated children's books, incorporating the principles of dialogic reading, as a potent springboard for discussions about race with very young children. Our purpose is to equip children, very early in their schooling, with a color filled appreciation for and comfort with physical diversity of appearance. On that foundation, children may better proceed on the course of developing anti racist attitudes.
Quantifying Risk and How It All Goes Wrong
Year: 2018

Over the course of a twenty year study into the shortcomings with risk quantification the author has identified several fundamental errors in both the data and algorithms employed in probabilistic models. These are shown to have detrimental impacts on the perception of risk and choice of mitigations. The author argues that all forms of risk prediction (as opposed to statistics) distort understanding and distract effort away from more holistic methods, such as well reasoned arguments, for demonstrating ALARP. The psychological aspects of risk assessment have profound influences on both quantitative and qualitative assessment, because there is too much flexibility and subjectivity allowed in QRA/PRA and Risk Assessment Matrices for them to add any real value. It is concluded that, whilst UK legislation does not require quantification, or the assessment of risk tolerability, there exists a 'perfect storm' of conditions that maintain the status quo and obstructs a necessary paradigm shift for how risk should be assessed. This stalemate can only be broken by a rigorous challenge to the statistical and mathematical processes, legal interpretation and guidance.
Ectoparasite sharing among native and invasive birds in a metropolitan area
Venue: Parasitology Research
Year: 2018

Parasite mediated competition has been reported to be one of the most harmful, although overlooked, impacts that alien species have on native ecosystems. Monk parakeets Myiopsitta monachus are successful invaders in Europe, where they have been introduced from South America. Colonial nests of these parrots may also host other species, e.g. the rock pigeon Columba livia forma domestica. In this work, we analysed the ectoparasite composition of monk parakeets in Barcelona (Spain) and we evaluated their potential role as parasite mediated competitors, by comparing their parasitic load with that of coexisting rock pigeons. Only two arthropod species were observed on monk parakeets, whereas four species were detected on pigeons. Parakeets were rarely infested by pigeon parasites (prevalence 0.66% whereas parakeet mites were recorded more often on pigeons (prevalence 10.00% The number of total parasites per bird increased with increasing densities of monk parakeets, both for pigeons and for parakeets. Therefore, overcrowding of birds due to the increasing population of monk parakeets in Barcelona may affect the health status of native pigeons, suggesting a potential role for parasite mediated competition by introduced parakeets. Furthermore, spill over of alien mites (Ornithonyssus bursa) by monk parakeets to rock pigeons should be monitoring as it may affect human health.
The Prognostic Significance of Diabetes and Microvascular Complications in Patients With Heart Failure With Preserved Ejection Fraction
Venue: Diabetes Care
Year: 2017

This study examined the prognostic significance of diabetes and microvascular complications in patients with heart failure with preserved ejection fraction (HFpEF) RESEARCH DESIGN AND METHODS This analysis included 3,385 patients (mean age 69 9.6 years; 49% male; 89% white) with HFpEF from the Treatment of Preserved Cardiac Function Heart Failure With an Aldosterone Antagonist Trial (TOPCAT) Diabetes and microvascular complications were ascertained by self reported history and medical record review. Microvascular complications included neuropathy, nephropathy, and retinopathy. Outcomes included hospitalization, hospitalization for heart failure, death, and cardiovascular death. Cox regression was used to examine the risk of each outcome associated with diabetes and microvascular complications.  Of the 1,109 subjects (32% with diabetes, 352 (32% had at least one microvascular complication. Patients with diabetes and microvascular complications had an increased risk for hospitalization (no diabetes: referent; diabetes no microvascular complication: hazard ratio [HR] 1.18, 95% CI 1.01, 1.37; diabetes microvascular complications: HR 1.54, 95% CI 1.25, 1.89; P trend <0.001) hospitalization for heart failure (no diabetes: referent; diabetes no microvascular complication: HR 1.51, 95% CI 1.14, 1.99; diabetes microvascular complications: HR 1.97, 95% CI 1.38, 2.80; P trend <0.001) death (no diabetes: referent; diabetes no microvascular complication: HR 1.35, 95% CI 1.04, 1.75; diabetes microvascular complications: HR 1.73, 95% CI 1.22, 2.45; P trend 0.0017) and cardiovascular death (no diabetes: referent; diabetes no microvascular complication: HR 1.34, 95% CI 0.96, 1.86; diabetes microvascular complications: HR 1.70, 95% CI 1.09, 2.65; P trend 0.018) When the analysis was limited to participants who reported prior hospitalization for heart failure (n 2,449) a higher risk of rehospitalization for heart failure was observed across diabetes categories (no diabetes: referent; diabetes no microvascular complication: HR 1.40, 95% CI 1.01, 1.96; diabetes microvascular complications: HR 1.78, 95% CI 1.18, 2.70; P trend 0.0036) CONCLUSIONS Diabetes is associated with adverse cardiovascular outcomes in HFpEF, and the inherent risk of adverse outcomes in HFpEF patients with diabetes varies by the presence of microvascular complications.
Population Pharmacokinetics of Danofloxacin After Single Intramuscular Dose Administration in California Brown Pelicans (Pelecanus occidentalis californicus)
Venue: Journal of Avian Medicine and Surgery
Year: 2019

The pharmacokinetics of danofloxacin was investigated in rehabilitated California brown pelicans (Pelecanus occidentalis californicus) after a single intramuscular injection at a dose of 15 mg/kg body weight. The concentration of the drug in plasma was assayed by high pressure liquid chromatography. A sparse sampling design was used to reduce the number of samples (1 4 venipunctures) obtained from 24 brown pelicans. A population pharmacokinetic analysis with nonlinear mixed effects modeling was used to accommodate the sparse sampling strategy. The nonlinear mixed effects modeling approach measured both fixed effects (typical values for the population) and random effects (between subject variability) for this population. A 1 compartment model best represented the concentration versus time data after injection. After injection, the elimination half life, peak concentration, area under the curve, and volume of distribution were 2.76 hours, 2.5 ug/mL, 13.75 ug/h/mL, and 4.35 L/kg, respectively. Rate of absorption was highly variable among the birds. The intramuscular injection of danofloxacin in pelicans at this dose produced plasma concentrations that meet therapeutic targets for bacteria with a minimum inhibitory concentration of =0.25 ug/mL. This dose can be used for future studies to evaluate the efficacy of danofloxacin for treating susceptible bacteria.
Deep sparse representations for land use scene classification in remote sensing images
Venue: 2016 IEEE 13th International Conference on Signal Processing (ICSP)
Year: 2016

Land use scene classification which provides highlevel interpretation for remote sensing images is a challenging task, and the performance of this task mainly lies in the representative ability of extracted scene level features. Motivated by the good generalization ability of deep convolutional neural network (CNN) we design a novel method, called deep sparse representation (DSR) building scene level features via directly transferring CNN models pre trained on general purpose image dataset for land use scene classification. We first extract deep CNN features in a feedforward way, and then compute sparse codes for the deep features through optimizing a sparse coding formulation; we finally max pool the obtained sparse codes to form the image representations. Extensive experiments on a public land use scene benchmark demonstrate that the image features generated by the proposed DSR, even with a simple linear classifier, can result in remarkable classification accuracies, which now become the new state of the art performance on the benchmark.