bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interventional procedure plans generated by telemedicine visits in spine patients are rarely changed after in-person evaluation
Authors: Crawford Alexander M , Lightsey Harry M , Xiong Grace X , Striano Brendan M , Greene Nattaly , Schoenfeld Andrew J , Simpson Andrew K 
Published: March 2021

Background and objectivesThe role of telemedicine in the evaluation and treatment of patients with spinal disorders is rapidly expanding, brought on largely by the COVID-19 pandemic. Within this context, the ability of pain specialists to accurately diagnose and plan appropriate interventional spine procedures based entirely on telemedicine visits, without an in-person evaluation, remains to be established. In this study, our primary objective was to assess the relevance of telemedicine to interventional spine procedure planning by determining whether procedure plans established solely from virtual visits changed following in-person evaluation.MethodsWe reviewed virtual and in-person clinical encounters from our academic health system’s 10 interventional spine specialists. We included patients who were seen exclusively via telemedicine encounters and indicated for an interventional procedure with documented procedural plans. Virtual plans were then compared with the actual procedures performed following in-person evaluation. Demographic data as well as the type and extent of physical examination performed by the interventional spine specialist were also recorded.ResultsOf the 87 new patients included, the mean age was 60 years (SE 1.4 years) and the preprocedural plan established by telemedicine, primarily videoconferencing, did not change for 76 individuals (87%; 95% CI 0.79 to 0.94) following in-person evaluation. Based on the size of our sample, interventional procedures indicated solely during telemedicine encounters may be accurate in 79%–94% of cases in the broader population.ConclusionsOur findings suggest that telemedicine evaluations are a generally accurate means of preprocedural assessment and development of interventional spine procedure plans. These findings clearly demonstrate the capabilities of telemedicine for evaluating spine patients and planning interventional spine procedures.
Predicting long-term outcomes in acute intracerebral haemorrhage using delayed prognostication scores
Authors: Lun Ronda , Yogendrakumar Vignan , Ramsay Tim , Shamy Michel , Fahed Robert , Selim Magdy H , Dowlatshahi Dar 
Published: March 2021

ObjectiveThe concept of the ‘self-fulfilling prophecy’ is well established in intracerebral haemorrhage (ICH). The ability to improve prognostication and prediction of long-term outcomes during the first days of hospitalisation is important in guiding conversations around goals of care. We previously demonstrated that incorporating delayed imaging into various prognostication scores for ICH improves the predictive accuracy of 90-day mortality. However, delayed prognostication scores have not been used to predict long-term functional outcomes beyond 90 days.Design, setting and participantsWe analysed data from the ICH Deferoxamine trial to see if delaying the use of prognostication scores to 96 hours after ICH onset will improve performance to predict outcomes at 180 days. 276 patients were included.Interventions and measurementsWe calculated the original ICH score (oICH), modified-ICH score (MICH), max-ICH score and the FUNC score on presentation (baseline), and on day 4 (delayed). Outcomes assessed were mortality and poor functional outcome in survivors (defined as modified Rankin Scale of 4–5) at 180 days. We generated receiver operating characteristic curves, and measured the area under the curve values (AUC) for mortality and functional outcome. We compared baseline and delayed AUCs with non-parametric methods.ResultsAt 180 days, 21 of 276 (7.6%) died. Out of the survivors, 54 of 255 had poor functional outcome (21.2%). The oICH, MICH and max-ICH performed significantly better at predicting 180-day mortality when calculated 4 days later compared with their baseline equivalents ((0.74 vs 0.83, p=0.005), (0.73 vs 0.80, p=0.036), (0.74 vs 0.83, p=0.008), respectively). The delayed calculation of these scores did not significantly improve our accuracy for predicting poor functional outcomes.ConclusionDelaying the calculation of prognostication scores in acute ICH until day 4 improved prediction of 6-month mortality but not functional outcomes.Trial registration numberClinicalTrials.gov Registry (NCT02175225).
Impact of surface charge on the motion of light-activated Janus micromotors
Authors: Huang Tao , Ibarlucea Bergoi , Caspari Anja , Synytska Alla , Cuniberti Gianaurelio , de Graaf Joost , Baraban Larysa 
Published: March 2021

Abstract
Control over micromotors’ motion is of high relevance for lab-on-a-chip and biomedical engineering, wherein such particles encounter complex microenvironments. Here, we introduce an efficient way to influence Janus micromotors’ direction of motion and speed by modifying their surface properties and those of their immediate surroundings. We fabricated light-responsive Janus micromotors with positive and negative surface charge, both driven by ionic self-diffusiophoresis. These were used to observe direction-of-motion reversal in proximity to glass substrates for which we varied the surface charge. Quantitative analysis allowed us to extract the dependence of the particle velocity on the surface charge density of the substrate. This constitutes the first quantitative demonstration of the substrate’s surface charge on the motility of the light-activated diffusiophoretic motors in water. We provide qualitative understanding of these observations in terms of osmotic flow along the substrate generated through the ions released by the propulsion mechanism. Our results constitute a crucial step in moving toward practical application of self-phoretic artificial micromotors.

Graphic abstract
Compacted CPU/GPU Data Compression via Modified Virtual Address Translation
Authors: Seiler Larry , Lin Daqi , Yuksel Cem 
Published: March 2021

We propose a method to reduce the footprint of compressed data by using modified virtual address translation to permit random access to the data. This extends our prior work on using page translation to perform automatic decompression and deswizzling upon accesses to fixed rate lossy or lossless compressed data.
Our compaction method allows a virtual address space the size of the uncompressed data to be used to efficiently access variable-size blocks of compressed data. Compression and decompression take place between the first and second level caches, which allows fast access to uncompressed data in the first level cache and provides data compaction at all other levels of the memory hierarchy. This improves performance and reduces power relative to compressed but uncompacted data.
An important property of our method is that compression, decompression, and reallocation are automatically managed by the new hardware without operating system intervention and without storing compression data in the page tables. As a result, although some changes are required in the page manager, it does not need to know the specific compression algorithm and can use a single memory allocation unit size.
We tested our method with two sample CPU algorithms. When performing depth buffer occlusion tests, our method reduces the memory footprint by 3.1x. When rendering into textures, our method reduces the footprint by 1.69x before rendering and 1.63x after. In both cases, the power and cycle time are better than for uncompacted compressed data, and significantly better than for accessing uncompressed data.
Open source column: Deep learning in the browser
Authors: Kletz Sabrina , Bertini Marco , Lux Mathias 
Published: March 2021

Having already discussed MatConvNet and Keras, let us continue with an open source framework for deep learning, which takes a new and interesting approach. TensorFlow.js is not only providing deep learning for JavaScript developers, but it's also making applications of deep learning available in the WebGL enabled web browsers, or more specifically, Chrome, Chromium-based browsers, Safari and Firefox. Recently node.js support has been added, so TensorFlow.js can be used to directly control TensorFlow without the browser.
TensorFlow.js is easy to install. As soon as a browser is installed one is ready to go. Browser based, cross platform applications, e.g. running with Electron, can also make use of TensorFlow.js without an additional install. The performance, however, depends on the browser the client is running, and memory and GPU on the client device. More specifically, one cannot expect to analyze 4K videos on a mobile phone in real time.
While it's easy to install, and it's easy to develop based on TensorFlow.js, there are drawbacks: (i) developers have less control over where the machine learning actually takes place (e.g. on CPU or GPU), that it is running in the same sandbox as all web pages in the browser do, and (ii) that in the current release it still has rough edges and is not considered stable enough to use in production.
Neural models for information retrieval without labeled data
Authors: Zamani Hamed 
Published: March 2021

Recent developments of machine learning models, and in particular deep neural networks, have yielded significant improvements on several computer vision, natural language processing, and speech recognition tasks. Progress with information retrieval (IR) tasks has been slower, however, due to the lack of large-scale training data as well as neural network models specifically designed for effective information retrieval [9]. In this dissertation, we address these two issues by introducing task-specific neural network architectures for a set of IR tasks and proposing novel unsupervised or
weakly supervised
solutions for training the models. The proposed learning solutions do not require labeled training data. Instead, in our weak supervision approach, neural models are trained on a large set of noisy and biased training data obtained from external resources, existing models, or heuristics.

We first introduce relevance-based embedding models [3] that learn distributed representations for words and queries. We show that the learned representations can be effectively employed for a set of IR tasks, including query expansion, pseudo-relevance feedback, and query classification [1, 2].
We further propose a standalone learning to rank model based on deep neural networks [5, 8]. Our model learns a sparse representation for queries and documents. This enables us to perform efficient retrieval by constructing an inverted index in the learned semantic space. Our model outperforms state-of-the-art retrieval models, while performing as efficiently as term matching retrieval models.
We additionally propose a neural network framework for predicting the performance of a retrieval model for a given query [7]. Inspired by existing query performance prediction models, our framework integrates several information sources, such as retrieval score distribution and term distribution in the top retrieved documents. This leads to state-of-the-art results for the performance prediction task on various standard collections.
We finally bridge the gap between retrieval and recommendation models, as the two key components in most information systems. Search and recommendation often share the same goal: helping people get the information they need at the right time. Therefore, joint modeling and optimization of search engines and recommender systems could potentially benefit both systems [4]. In more detail, we introduce a retrieval model that is trained using user-item interaction (e.g., recommendation data), with no need to query-document relevance information for training [6].
Our solutions and findings in this dissertation smooth the path towards learning efficient and effective models for various information retrieval and related tasks, especially when large-scale training data is not available.
Report on CLEF 2019
Authors: Braschler Martin , Cappellato Linda , Crestani Fabio , Ferro Nicola , Bürki Gundula Heinatz , Losada David E. , Müller Henning , Rauber Andreas , Savoy Jacques 
Published: March 2021

This is a report on the tenth edition of the
Conference and Labs of the Evaluation Forum
(CLEF 2019), held from September 9--12, 2019, in Lugano, Switzerland.

CLEF was a four day event combining a Conference and an Evaluation Forum. The Conference featured keynotes by Bruce Croft, Yair Neuman, and Miguel Martínez, and presentation of peer reviewed research papers covering a wide range of topics in addition to many posters. The Evaluation Forum consisted to nine Labs: CENTRE, CheckThat, eHealth, eRisk, ImageCLEF, LifeCLEF, PAN, PIR-CLEF, and ProtestNews, addressing a wide range of tasks, media, languages, and ways to go beyond standard test collections.
CLEF 2019 marked the 20th anniversary of CLEF, which was celebrated with a dedicated session and a book on the lessons learnt in twenty years of evaluation activities and the future perspectives for CLEF.
CLEF 2019 also introduced the Industry Days to further extend the reach and impact of CLEF.
Mildly Elevated Pulmonary Arterial Pressure Is Associated With a High Risk of Progression to Pulmonary Hypertension and Increased Mortality: A Systematic Review and Meta‐Analysis
Authors: Xue Lin , Yang Yicheng , Sun Bo , Liu Bingyang , Zeng Qixian , Xiong Changming 
Published: March 2021

Background
Pulmonary hypertension (PH) is defined as a mean pulmonary arterial pressure (PAP) ≥25 mm Hg measured by right heart catheterization. However, the upper limit of a normal mean PAP is 20 mm Hg. There is a gap between the upper limit of normal and the threshold for diagnosing PH. Therefore, we aimed to investigate whether individuals with a mildly elevated PAP, defined as 20 mm Hg < mean PAP <25 mm Hg, are at an increased risk of progression to PH or mortality than those with a normal PAP.

Methods and Results
We reviewed studies evaluating the risk of progression to PH and/or mortality in individuals with a mildly elevated PAP versus those with a normal PAP. The mean PAP value of each participant was confirmed by right heart catheterization. We reviewed 1213 studies and 8 fulfilled our inclusion criteria. Our results indicated that individuals with a mildly elevated PAP were 1.81 to 2.45 times more likely to progress to PH than individuals with a normal PAP. There was a statistically significant difference in mortality between the mildly elevated PAP and normal PAP groups (hazard ratio, 2.48; 95% CI, 1.69–3.64). We also pooled survival probabilities in each arm to obtain a summary survival curve for each group, and the pooled survival rates in the mildly elevated PAP group were numerically lower than those in the normal PAP group.

Conclusions
Our study revealed that individuals with a mildly elevated PAP were at an increased risk of progression to PH and mortality than those with a normal PAP.
Atrial Fibrillation Is Associated With Mortality in Intermediate Surgical Risk Patients With Severe Aortic Stenosis: Analyses From the PARTNER 2A and PARTNER S3i Trials
Authors: Brener Michael I. , George Isaac , Kosmidou Ioanna , Nazif Tamim , Zhang Zixuan , Dizon Jose M. , Garan Hasan , Malaisrie S. Chris , Makkar Raj , Mack Michael , Szeto Wilson Y. , Fearon William F. , Thourani Vinod H. , Leon Martin B. , Kodali Susheel , Biviano Angelo B. 
Published: March 2021

Background
The impact of atrial fibrillation (AF) in intermediate surgical risk patients with severe aortic stenosis who undergo either transcatheter or surgical aortic valve replacement (AVR) is not well established.

Methods and Results

Data were assessed in 2663 patients from the PARTNER (Placement of Aortic Transcatheter Valve) 2A or S3i trials. Analyses grouped patients into 3 categories according to their baseline and discharge rhythms (ie, sinus rhythm [SR]/SR, SR/AF, or AF/AF). Among patients with transcatheter AVR (n=1867), 79.2% had SR/SR, 17.6% had AF/AF, and 3.2% had SR/AF. Among patients with surgical AVR (n=796), 71.7% had SR/SR, 14.1% had AF/AF, and 14.2% had SR/AF. Patients with transcatheter AVR in AF at discharge had increased 2‐year mortality (SR/AF versus SR/SR; hazard ratio [HR], 2.73; 95% CI, 1.68–4.44;
P
<0.0001; AF/AF versus SR/SR; HR, 1.56; 95% CI, 1.16–2.09;
P
=0.003); patients with SR/AF also experienced increased 2‐year mortality relative to patients with AF/AF (HR, 1.77; 95% CI, 1.04–3.00;
P
=0.03). For patients with surgicalAVR, the presence of AF at discharge was also associated with increased 2‐year mortality (SR/AF versus SR/SR; HR, 1.93; 95% CI, 1.25–2.96;
P
=0.002; and AF/AF versus SR/SR; HR, 1.67; 95% CI, 1.06–2.63;
P
=0.027). Rehospitalization and persistent advanced heart failure symptoms were also more common among patients with transcatheter AVR and surgical AVR discharged in AF, and major bleeding was more common in the transcatheter AVR cohort.

Conclusions
The presence of AF at discharge in patients with intermediate surgical risk aortic stenosis was associated with worse outcomes—especially in patients with baseline SR—including increased all‐cause mortality at 2‐year follow‐up.

Registration

URL:
https://www.clinicaltrials.gov
; Unique identifiers: NCT01314313 and NCT03222128.
Characteristics of Populations Excluded From Clinical Trials Supporting Intensive Blood Pressure Control Guidelines
Authors: Anderson Timothy S. , Odden Michelle C. , Penko Joanne , Kazi Dhruv S. , Bellows Brandon K. , Bibbins‐Domingo Kirsten 
Published: March 2021

Background
Only one third of patients recommended intensified treatment by the 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline for high blood pressure would have been eligible for the clinical trials on which recommendations were largely based. We sought to identify characteristics of adults who would have been trial‐ineligible in order to inform clinical practice and research priorities.

Methods and Results
We examined the proportion of adults diagnosed with hypertension who met trial inclusion and exclusion criteria, stratified by age, diabetes mellitus status, and guideline recommendations in a cross‐sectional study of the National Health and Nutrition Examination Survey, 2013–2016. Of the 107.7 million adults (95% CI, 99.3–116.0 million) classified as having hypertension by the ACC/AHA guideline, 23.1% (95% CI, 20.8%–25.5%) were below the target blood pressure of 130/80 mm Hg, 22.2% (95% CI, 20.1%–24.4%) would be recommended nonpharmacologic treatment, and 54.6% (95% CI, 52.5%–56.7%) would be recommended additional pharmacotherapy. Only 20.6% (95% CI, 18.8%–22.4%) of adults with hypertension would be trial‐eligible. The majority of adults <50 years were excluded because of low cardiovascular risk and lack of access to primary care. The majority of adults aged ≥70 years were excluded because of multimorbidity and limited life expectancy. Reasons for trial exclusion were similar for patients with and without diabetes mellitus.

Conclusions
Intensive blood pressure treatment trials were not representative of many younger adults with low cardiovascular risk and older adults with multimorbidity who are now recommended more intensive blood pressure goals.
Criminalizing Migration
Authors: Hernández César Cuauhtémoc García 
Published: March 2021

Abstract
Beginning in the 1980s, the United States embarked on a decades-long restructuring of federal laws criminalizing migration and increasing the consequences for migrants engaging in criminal activity. Today, the results are clear: a law enforcement apparatus and immigration prison system propelled by a vast infrastructure of laws and policies. The presidency of Donald Trump augmented this trend and brought it to public attention. But lost in President Trump's unique flair is an ideological commitment shared by multiple presidential administrations and legislators from both major political parties to use the criminal justice system and imprisonment to sift migrants. Examining these ideological attachments reveals Trump-era policies to be the outer edge of decades-long trends rather than extreme and momentary deviations from the norm.
The Legal Status Divide among the Children of Immigrants
Authors: Gonzales Roberto G. , Ruszczyk Stephen P. 
Published: March 2021

Abstract
Over the past thirty-five years, federal immigration policy has brightened the boundaries of the category of undocumented status. For undocumented young people who move into adulthood, the predominance of immigration status to their everyday experiences and social position has been amplified. This process of trying to continue schooling, find work, and participate in public life has become synonymous with a process of learning to be “illegal.” This essay argues that despite known variations in undocumented youths by race, place, and educational history, undocumented status has become what Everett Hughes called a “master status.” The uniform set of immigration status-based exclusions overwhelms the impact of other statuses to create a socially significant divide. The rise, fall, and survival of the Deferred Action for Childhood Arrivals program, a policy offering qualified youths a temporary semilegal status, have underlined how closely access and rights hew to the contours of contemporary immigration policy.
A new method for assessing the performance of general circulation models based on their ability to simulate the response to observed forcing
Authors: Altamirano del Carmen M.A. , Estrada F. , Gay-García C. 
Published: March 2021

AbstractThe reliability of General Circulation Models (GCMs) is commonly associated with their ability to reproduce relevant aspects of observed climate and thus, the evaluation of GCMs performance has become a standard practice for climate change studies. As such, there is an ever-growing literature that focuses on developing and evaluating metrics to assess GCMs performance. In this paper it is shown that some commonly applied metrics provide little information for discriminating GCMs based on their performance, once uncertainty is included. A new methodology is proposed that differs from common approaches in that it focuses on evaluating GCMs ability to reproduce the observed response of surface temperature to changes in external radiative forcing (RF), while controlling for observed and simulated variability. It uses formal statistical tests to evaluate two aspects of the warming trend that are central for climate change studies: 1) if the response to RF produced by a particular GCM is compatible with observations and 2) if the magnitudes of the observed and simulated rates of warming are statistically similar. We illustrate the proposed methodology by evaluating the ability of 21 GCMs to reproduce the observed warming trend at the global scale and eight sub-continental land domains. Results show that most of the GCMs provide an adequate representation of the observed warming trend for the global scale and for domains located in the southern hemisphere. However, GCMs tend to overestimate the warming rate for domains in the northern hemisphere, particularly since the mid-1990s.