scholarly journals Extracting Outcomes from Appellate Decisions in US State Courts

2020 ◽  
Author(s):  
Alina Petrova ◽  
John Armour ◽  
Thomas Lukasiewicz
Keyword(s):  
Large Scale ◽  
English Language ◽  
Learning System ◽  
State Courts ◽  
Research Attention ◽  
Textual Description ◽  
Set Up ◽  
Access Project ◽  
Project Data ◽  
F Measure

Predicting the outcome of a legal process has recently gained considerable research attention. Numerous attempts have been made to predict the exact outcome, judgment, charge, and fines of a case given the textual description of its facts and metadata. However, most of the effort has been focused on Chinese and European law, for which there exist annotated datasets. In this paper, we introduce CASELAW4 — a new dataset of 350k common law judicial decisions from the U.S. Caselaw Access Project, of which 250k have been automatically annotated with binary outcome labels of AFFIRM or REVERSE by our hybrid learning system. To our knowledge, it is the first attempt to perform outcome extraction (a) on such a large volume of English-language judicial opinions, (b) on the Caselaw Access Project data, and (c) on US State Courts of Appeal cases, and it paves the way to large-scale outcome prediction and advanced legal analytics using U.S. Case Law. We set up baseline results for the outcome extraction task on the new dataset, achieving an F-measure of 82.32%.

scholarly journals Scope and costs of autorefraction and photoscreening for childhood amblyopia—a systematic narrative review in relation to the EUSCREEN project data

Eye ◽  
2020 ◽  
Author(s):  
Anna M. Horwood ◽  
◽  
Helen J. Griffiths ◽  
Jill Carlton ◽  
Paolo Mazzone ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Large Scale ◽  
English Language ◽  
Cost Effective ◽  
Original Data ◽  
Community Services ◽  
Narrative Review ◽  
Effective Option ◽  
Automated Screening ◽  
Project Data

Abstract Background Amblyopia screening can target reduced visual acuity (VA), its refractive risk factors, or both. VA testing is imprecise under 4 years of age, so automated risk-factor photoscreening appears an attractive option. This review considers photoscreening used in community services, focusing on costs, cost-effectiveness and scope of use, compared with EUSCREEN project Country Reports describing how photo- and automated screening is used internationally. Methods A systematic narrative review was carried out of all English language photoscreening literature to September 10th 2018, using publicly available search terms. Where costs were considered, a CASP economic evaluation checklist was used to assess data quality. Results Of 370 abstracts reviewed, 55 reported large-scale community photoscreening projects. Five addressed cost-effectiveness specifically, without original data. Photoscreening was a stand-alone, single, test event in 71% of projects. In contrast, 25 of 45 EUSCREEN Country Reports showed that if adopted, photoscreening often supplements other tests in established programmes and is rarely used as a stand-alone test. Reported costs varied widely and evidence of cost-effectiveness was sparse in the literature, or in international practice. Only eight (13%) papers compared the diagnostic accuracy or cost-effectiveness of photoscreening and VA testing, and when they did, cost-effectiveness of photoscreening compared unfavourably. Discussion Evidence that photoscreening reduces amblyopia or strabismus prevalence or improves overall outcomes is weak, as is evidence of cost-effectiveness, compared to later VA screening. Currently, the most cost-effective option seems to be a later, expert VA screening with the opportunity for a re-test before referral.

Platelet Anti-Aggregating Activity and Tolerance of Clopidogrel in Atherosclerotic Patients

1996 ◽  
Vol 76 (06) ◽  
pp. 0939-0943 ◽  
Author(s):  
B Boneu ◽  
G Destelle ◽  
Keyword(s):  
Platelet Aggregation ◽  
Large Scale ◽  
Bleeding Time ◽  
Antithrombotic Activity ◽  
Ambulatory Patients ◽  
Patients At Risk ◽  
Set Up ◽  
Ischemic Events ◽  
Large Scale Clinical Trial ◽  
Selection Of

SummaryThe anti-aggregating activity of five rising doses of clopidogrel has been compared to that of ticlopidine in atherosclerotic patients. The aim of this study was to determine the dose of clopidogrel which should be tested in a large scale clinical trial of secondary prevention of ischemic events in patients suffering from vascular manifestations of atherosclerosis [CAPRIE (Clopidogrel vs Aspirin in Patients at Risk of Ischemic Events) trial]. A multicenter study involving 9 haematological laboratories and 29 clinical centers was set up. One hundred and fifty ambulatory patients were randomized into one of the seven following groups: clopidogrel at doses of 10, 25, 50,75 or 100 mg OD, ticlopidine 250 mg BID or placebo. ADP and collagen-induced platelet aggregation tests were performed before starting treatment and after 7 and 28 days. Bleeding time was performed on days 0 and 28. Patients were seen on days 0, 7 and 28 to check the clinical and biological tolerability of the treatment. Clopidogrel exerted a dose-related inhibition of ADP-induced platelet aggregation and bleeding time prolongation. In the presence of ADP (5 \lM) this inhibition ranged between 29% and 44% in comparison to pretreatment values. The bleeding times were prolonged by 1.5 to 1.7 times. These effects were non significantly different from those produced by ticlopidine. The clinical tolerability was good or fair in 97.5% of the patients. No haematological adverse events were recorded. These results allowed the selection of 75 mg once a day to evaluate and compare the antithrombotic activity of clopidogrel to that of aspirin in the CAPRIE trial.

MODELING THE SOUTH ATLANTIC OCEAN FROM MEDIUM TO HIGH RESOLUTION

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Mariela Gabioux ◽  
Vladimir Santos da Costa ◽  
Joao Marcos Azevedo Correia de Souza ◽  
Bruna Faria de Oliveira ◽  
Afonso De Moraes Paiva
Keyword(s):  
High Resolution ◽  
Atlantic Ocean ◽  
Large Scale ◽  
South Atlantic ◽  
Surface Relaxation ◽  
The South ◽  
Small Surface ◽  
Basic Model ◽  
Basic Set ◽  
Set Up

Results of the basic model configuration of the REMO project, a Brazilian approach towards operational oceanography, are discussed. This configuration consists basically of a high-resolution eddy-resolving, 1/12 degree model for the Metarea V, nested in a medium-resolution eddy-permitting, 1/4 degree model of the Atlantic Ocean. These simulations performed with HYCOM model, aim for: a) creating a basic set-up for implementation of assimilation techniques leading to ocean prediction; b) the development of hydrodynamics bases for environmental studies; c) providing boundary conditions for regional domains with increased resolution. The 1/4 degree simulation was able to simulate realistic equatorial and south Atlantic large scale circulation, both the wind-driven and the thermohaline components. The high resolution simulation was able to generate mesoscale and represent well the variability pattern within the Metarea V domain. The BC mean transport values were well represented in the southwestern region (between Vitória-Trinidade sea mount and 29S), in contrast to higher latitudes (higher than 30S) where it was slightly underestimated. Important issues for the simulation of the South Atlantic with high resolution are discussed, like the ideal place for boundaries, improvements in the bathymetric representation and the control of bias SST, by the introducing of a small surface relaxation. In order to make a preliminary assessment of the model behavior when submitted to data assimilation, the Cooper & Haines (1996) method was used to extrapolate SSH anomalies fields to deeper layers every 7 days, with encouraging results.

scholarly journals Development and validation of a deep learning system to screen vision-threatening conditions in high myopia using optical coherence tomography images

2020 ◽  
pp. bjophthalmol-2020-317825
Author(s):  
Yonghao Li ◽  
Weibo Feng ◽  
Xiujuan Zhao ◽  
Bingqian Liu ◽  
Yan Zhang ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Deep Learning ◽  
High Myopia ◽  
Large Scale ◽  
Learning System ◽  
Youden Index ◽  
Optical Coherence ◽  
Test Dataset ◽  
Independent Test ◽  
Independent Test Dataset

Background/aimsTo apply deep learning technology to develop an artificial intelligence (AI) system that can identify vision-threatening conditions in high myopia patients based on optical coherence tomography (OCT) macular images.MethodsIn this cross-sectional, prospective study, a total of 5505 qualified OCT macular images obtained from 1048 high myopia patients admitted to Zhongshan Ophthalmic Centre (ZOC) from 2012 to 2017 were selected for the development of the AI system. The independent test dataset included 412 images obtained from 91 high myopia patients recruited at ZOC from January 2019 to May 2019. We adopted the InceptionResnetV2 architecture to train four independent convolutional neural network (CNN) models to identify the following four vision-threatening conditions in high myopia: retinoschisis, macular hole, retinal detachment and pathological myopic choroidal neovascularisation. Focal Loss was used to address class imbalance, and optimal operating thresholds were determined according to the Youden Index.ResultsIn the independent test dataset, the areas under the receiver operating characteristic curves were high for all conditions (0.961 to 0.999). Our AI system achieved sensitivities equal to or even better than those of retina specialists as well as high specificities (greater than 90%). Moreover, our AI system provided a transparent and interpretable diagnosis with heatmaps.ConclusionsWe used OCT macular images for the development of CNN models to identify vision-threatening conditions in high myopia patients. Our models achieved reliable sensitivities and high specificities, comparable to those of retina specialists and may be applied for large-scale high myopia screening and patient follow-up.

scholarly journals Vibration characteristics of triple-gear-rotor system in compressed air energy storage under variable torque load

2021 ◽  
Vol 104 (1) ◽  
pp. 003685042098705
Author(s):  
Xinran Wang ◽  
Yangli Zhu ◽  
Wen Li ◽  
Dongxu Hu ◽  
Xuehui Zhang ◽  
...  
Keyword(s):  
Large Scale ◽  
Three Dimensional ◽  
Element Model ◽  
Rotor System ◽  
Dynamic Responses ◽  
System Response ◽  
Rotating Speed ◽  
Torque Load ◽  
Set Up ◽  
Two Stages

This paper focuses on the effects of the off-design operation of CAES on the dynamic characteristics of the triple-gear-rotor system. A finite element model of the system is set up with unbalanced excitations, torque load excitations, and backlash which lead to variations of tooth contact status. An experiment is carried out to verify the accuracy of the mathematical model. The results show that when the system is subjected to large-scale torque load lifting at a high rotating speed, it has two stages of relatively strong periodicity when the torque load is light, and of chaotic when the torque load is heavy, with the transition between the two states being relatively quick and violent. The analysis of the three-dimensional acceleration spectrum and the meshing force shows that the variation in the meshing state and the fluctuation of the meshing force is the basic reasons for the variation in the system response with the torque load. In addition, the three rotors in the triple-gear-rotor system studied show a strong similarity in the meshing states and meshing force fluctuations, which result in the similarity in the dynamic responses of the three rotors.

scholarly journals Precision Agriculture for Resource Use Efficiency in Smallholder Farming Systems in Sub-Saharan Africa: A Systematic Review

2021 ◽  
Vol 13 (3) ◽  
pp. 1158
Author(s):  
Cecilia M. Onyango ◽  
Justine M. Nyaga ◽  
Johanna Wetterlind ◽  
Mats Söderström ◽  
Kristin Piikki
Keyword(s):  
Resource Use ◽  
Precision Agriculture ◽  
Large Scale ◽  
English Language ◽  
Management Practices ◽  
Smallholder Farmers ◽  
Management Strategies ◽  
Sub Saharan Africa ◽  
Smallholder Farming ◽  
Sub Saharan

Opportunities exist for adoption of precision agriculture technologies in all parts of the world. The form of precision agriculture may vary from region to region depending on technologies available, knowledge levels and mindsets. The current review examined research articles in the English language on precision agriculture practices for increased productivity among smallholder farmers in Sub-Saharan Africa. A total of 7715 articles were retrieved and after screening 128 were reviewed. The results indicate that a number of precision agriculture technologies have been tested under SSA conditions and show promising results. The most promising precision agriculture technologies identified were the use of soil and plant sensors for nutrient and water management, as well as use of satellite imagery, GIS and crop-soil simulation models for site-specific management. These technologies have been shown to be crucial in attainment of appropriate management strategies in terms of efficiency and effectiveness of resource use in SSA. These technologies are important in supporting sustainable agricultural development. Most of these technologies are, however, at the experimental stage, with only South Africa having applied them mainly in large-scale commercial farms. It is concluded that increased precision in input and management practices among SSA smallholder farmers can significantly improve productivity even without extra use of inputs.

scholarly journals Environmental Engineering Techniques to Restore Degraded Posidonia oceanica Meadows

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 661
Author(s):  
Luigi Piazzi ◽  
Stefano Acunto ◽  
Francesca Frau ◽  
Fabrizio Atzori ◽  
Maria Francesca Cinti ◽  
...  
Keyword(s):  
Large Scale ◽  
Natural Habitat ◽  
Cost Benefit ◽  
Cost Effective ◽  
Posidonia Oceanica ◽  
Environmental Engineering ◽  
Bottom Surface ◽  
Sessile Invertebrates ◽  
Set Up ◽  
Short Time

Seagrass planting techniques have shown to be an effective tool for restoring degraded meadows and ecosystem function. In the Mediterranean Sea, most restoration efforts have been addressed to the endemic seagrass Posidonia oceanica, but cost-benefit analyses have shown unpromising results. This study aimed at evaluating the effectiveness of environmental engineering techniques generally employed in terrestrial systems to restore the P. oceanica meadows: two different restoration efforts were considered, either exploring non-degradable mats or, for the first time, degradable mats. Both of them provided encouraging results, as the loss of transplanting plots was null or very low and the survival of cuttings stabilized to about 50%. Data collected are to be considered positive as the survived cuttings are enough to allow the future spread of the patches. The utilized techniques provided a cost-effective restoration tool likely affordable for large-scale projects, as the methods allowed to set up a wide bottom surface to restore in a relatively short time without any particular expensive device. Moreover, the mats, comparing with other anchoring methods, enhanced the colonization of other organisms such as macroalgae and sessile invertebrates, contributing to generate a natural habitat.

scholarly journals Collateral impact of COVID-19: why should children continue to suffer?

2021 ◽  
Author(s):  
Prasad Nagakumar ◽  
Ceri-Louise Chadwick ◽  
Andrew Bush ◽  
Atul Gupta
Keyword(s):  
Young People ◽  
Large Scale ◽  
Hospital Admissions ◽  
Severe Disease ◽  
Children And Young People ◽  
Collateral Effects ◽  
Rsv Infection ◽  
Syncytial Virus ◽  
Set Up ◽  
The Uk

AbstractThe COVID-19 pandemic caused by SARS-COV-2 virus fortunately resulted in few children suffering from severe disease. However, the collateral effects on the COVID-19 pandemic appear to have had significant detrimental effects on children affected and young people. There are also some positive impacts in the form of reduced prevalence of viral bronchiolitis. The new strain of SARS-COV-2 identified recently in the UK appears to have increased transmissibility to children. However, there are no large vaccine trials set up in children to evaluate safety and efficacy. In this short communication, we review the collateral effects of COVID-19 pandemic in children and young people. We highlight the need for urgent strategies to mitigate the risks to children due to the COVID-19 pandemic. What is Known:• Children and young people account for <2% of all COVID-19 hospital admissions• The collateral impact of COVID-19 pandemic on children and young people is devastating• Significant reduction in influenza and respiratory syncytial virus (RSV) infection in the southern hemisphere What is New:• The public health measures to reduce COVID-19 infection may have also resulted in near elimination of influenza and RSV infections across the globe• A COVID-19 vaccine has been licensed for adults. However, large scale vaccine studies are yet to be initiated although there is emerging evidence of the new SARS-COV-2 strain spreading more rapidly though young people.• Children and young people continue to bear the collateral effects of COVID-19 pandemic

A Hindi Image Caption Generation Framework Using Deep Learning

2021 ◽  
Vol 20 (2) ◽  
pp. 1-19
Author(s):  
Santosh Kumar Mishra ◽  
Rijul Dhir ◽  
Sriparna Saha ◽  
Pushpak Bhattacharyya
Keyword(s):  
Computer Vision ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
English Language ◽  
Image Captioning ◽  
Textual Description ◽  
Proposed Model ◽  
Hindi Language ◽  
The Given

Image captioning is the process of generating a textual description of an image that aims to describe the salient parts of the given image. It is an important problem, as it involves computer vision and natural language processing, where computer vision is used for understanding images, and natural language processing is used for language modeling. A lot of works have been done for image captioning for the English language. In this article, we have developed a model for image captioning in the Hindi language. Hindi is the official language of India, and it is the fourth most spoken language in the world, spoken in India and South Asia. To the best of our knowledge, this is the first attempt to generate image captions in the Hindi language. A dataset is manually created by translating well known MSCOCO dataset from English to Hindi. Finally, different types of attention-based architectures are developed for image captioning in the Hindi language. These attention mechanisms are new for the Hindi language, as those have never been used for the Hindi language. The obtained results of the proposed model are compared with several baselines in terms of BLEU scores, and the results show that our model performs better than others. Manual evaluation of the obtained captions in terms of adequacy and fluency also reveals the effectiveness of our proposed approach. Availability of resources : The codes of the article are available at https://github.com/santosh1821cs03/Image_Captioning_Hindi_Language ; The dataset will be made available: http://www.iitp.ac.in/∼ai-nlp-ml/resources.html .

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