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Materials scientists increasingly employ machine or statistical learning (SL) techniques to accelerate materials discovery and design. Such pursuits benefit from pooling training data across, and thus being able to generalize predictions over, k -nary compounds of diverse chemistries and structures. This work presents a SL framework that addresses challenges in materials science applications, where datasets are diverse but of modest size, and extreme values are often of interest. Our advances include the application of power or Hölder means to construct descriptors that generalize over chemistry and crystal structure, and the incorporation of multivariate local regression within a gradient boosting framework. The approach is demonstrated by developing SL models to predict bulk and shear moduli ( K and G , respectively) for polycrystalline inorganic compounds, using 1,940 compounds from a growing database of calculated elastic moduli for metals, semiconductors and insulators. The usefulness of the models is illustrated by screening for superhard materials.

In recent decades the overall smoking prevalence in the US has fallen steadily. This study examines whether the same trend is seen in the Medicaid population. National Health Interview Survey (NHIS) data from 17 consecutive annual surveys from 1997 to 2013 (combined N = 514,043) were used to compare smoking trends for 4 insurance groups: Medicaid, the Uninsured, Private Insurance, and Other Coverage. Rates of chronic disease and psychological distress were also compared. Adjusted smoking prevalence showed no detectable decline in the Medicaid population (from 33.8% in 1997 to 31.8% in 2013, trend test P = 0.13), while prevalence in the other insurance groups showed significant declines (38.6%-34.7% for the Uninsured, 21.3%-15.8% for Private Insurance, and 22.6%-16.8% for Other Coverage; all P's<0.005). Among individuals who have ever smoked, Medicaid recipients were less likely to have quit (38.8%) than those in Private Insurance (62.3%) or Other Coverage (69.8%; both P's<0.001). Smokers in Medicaid were more likely than those in Private Insurance and the Uninsured to have chronic disease (55.0% vs 37.3% and 32.4%, respectively; both P's<0.01). Smokers in Medicaid were also more likely to experience severe psychological distress (16.2% for Medicaid vs 3.2% for Private Insurance and 7.6% for the Uninsured; both P's<0.001). The high and relatively unchanging smoking prevalence in the Medicaid population, low quit ratio, and high rates of chronic disease and severe psychological distress highlight the need to focus on this population. A targeted and sustained campaign to help Medicaid recipients quit smoking is urgently needed.

E-cigarettes have generated controversy in the tobacco control field similar to that of Swedish snus, which came to the U.S. market six years earlier. Some argue that e-cigarettes have great potential to help smokers quit regular cigarettes while others contend they should be banned for lack of safety and efficacy data. This study examined population data from the U.S. A U.S. population survey with a national probability sample (N=10,041) was conducted (February 24 to March 8, 2012, before any major paid advertisement of e-cigarettes appeared on television). Survey respondents were asked if they had heard about e-cigarettes, where they had heard about them, whether they had used e-cigarettes or snus, how often they used them, and why they used them. Responses were weighted to represent the entire U.S. population. A high proportion, 75.4%, reported having heard about e-cigarettes. Television ranked as the number one source of information, followed by \"in-person conversation\" and \"Internet.\" About 8.1% had tried e-cigarettes, and 1.4% were current users. These rates were twice those of snus (4.3% and 0.8%, respectively). Among current smokers, 32.2% had tried e-cigarettes, and 6.3% were current users. Over 80% of current e-cigarette users were non-daily users. Women were significantly more likely to have tried e-cigarettes than men. Those who had tried e-cigarettes were more likely than those who tried snus to report their products being safer than regular cigarettes (49.9% vs. 10.8%). Almost half (49.5%) of current smokers were susceptible to using e-cigarettes in the future. That e-cigarettes have surpassed snus in adoption rate, even before any promotion by major tobacco companies, suggests that the former have tapped into smokers' intuitive preference for potentially harm-reducing products, probably due to the product design. E-cigarette use is likely to increase in the next few years.

Background. Human immunodeficiency virus (HIV)-associated neurocognitive disorders (HAND) can show variable clinical trajectories. Previous longitudinal studies of HAND typically have been brief, did not use adequate normative standards, or were conducted in the context of a clinical trial, thereby limiting our understanding of incident neurocognitive (NC) decline and recovery. Methods. We investigated the incidence and predictors of NC change over 16–72 (mean, 35) months in 436 HIV-infected participants in the CNS HIV Anti-Retroviral Therapy Effects Research Cohort. Comprehensive laboratory, neuromedical, and NC assessments were obtained every 6 months. Published, regression-based norms for NC change were used to generate overall change status (decline vs stable vs improved) at each study visit. Survival analysis was used to examine the predictors of time to NC change. Results. Ninety-nine participants (22.7%) declined, 265 (60.8%) remained stable, and 72 (16.5%) improved. In multivariable analyses, predictors of NC improvements or declines included time-dependent treatment status and indicators of disease severity (current hematocrit, albumin, total protein, aspartate aminotransferase), and baseline demographics and estimated premorbid intelligence quotient, non-HIV-related comorbidities, current depressive symptoms, and lifetime psychiatric diagnoses (overall model P < .0001). Conclusions. NC change is common in HIV infection and appears to be driven by a complex set of risk factors involving HIV disease, its treatment, and comorbid conditions.

The elastic constant tensor of an inorganic compound provides a complete description of the response of the material to external stresses in the elastic limit. It thus provides fundamental insight into the nature of the bonding in the material, and it is known to correlate with many mechanical properties. Despite the importance of the elastic constant tensor, it has been measured for a very small fraction of all known inorganic compounds, a situation that limits the ability of materials scientists to develop new materials with targeted mechanical responses. To address this deficiency, we present here the largest database of calculated elastic properties for inorganic compounds to date. The database currently contains full elastic information for 1,181 inorganic compounds, and this number is growing steadily. The methods used to develop the database are described, as are results of tests that establish the accuracy of the data. In addition, we document the database format and describe the different ways it can be accessed and analyzed in efforts related to materials discovery and design. Design Type(s) observation design Measurement Type(s) elastic constant tensor Technology Type(s) stress-strain methodology Factor Type(s) Machine-accessible metadata file describing the reported data (ISA-Tab format)

e-Cigarette or vaping use-associated lung injury (EVALI), first reported in July 2019, caused over 2807 hospitalizations and 68 deaths by February 2020, when the outbreak subsided and the Centers for Disease Control and Prevention (CDC) stopped updating the case number. Media coverage of EVALI was extensive but not always accurate concerning the cause, which turned out to be vitamin E acetate, a compound added to certain illicit cannabis vape products. Studies have documented a significant increase in the perceived risk of vaping among the US adult population. However, research on how the EVALI outbreak influenced adolescents' knowledge of the illness and their perception of the risk of vaping products is limited, especially those that used probability sampling of the adolescent population. This study examined knowledge of EVALI among adolescents and explored the impact of media messages on their perceptions of the condition. Archived news reports on EVALI from an online tobacco media analysis engine, Tobacco Watcher (July 2019-March 2020), and data from the California Student Tobacco Survey, a large statewide school-based survey of 8th, 10th, and 12th graders (September 2019-March 2020; N=157,499), were analyzed. Students' awareness of EVALI and perceptions of its cause were examined in relation to their sources of information about EVALI, and their perceived risk of vaping was analyzed by their awareness of EVALI. Of 19,661 news reports on Tobacco Watcher that discussed EVALI, 55.9% mentioned cannabis. Among the 157,499 middle and high school students participating in the statewide survey in California, 75% had heard about EVALI. The awareness level was similarly high for 8th, 10th, and 12th graders (75.7%, 74.6%, and 74.8%, respectively). Their primary source of knowledge about EVALI was media (63.1%), followed by parents (16.6%), teachers (8.1%), friends (7.7%), and peers (4.6%). Most students, 55%, believed nicotine was the cause of EVALI, while only 11% thought it was related to cannabis in vapes. Students who had heard about EVALI were more likely to rate vaping every day as extremely harmful than those who had not heard about it (67.8% vs 50.9%; P<.001). Most adolescents were aware of EVALI and cited media as the main source of their knowledge. The effects of extensive news coverage of EVALI have reached students as young as 8th graders. Most of those who were aware of EVALI, however, incorrectly believed that nicotine in vapes was the cause of EVALI. The actual cause-vitamin E acetate found in certain cannabis vapes-appeared to have been overlooked or not effectively communicated, especially in early media reports. Media coverage of EVALI presents a case study of the critical but complicated role of modern media in communicating health information.

Spasticity is a common and poorly controlled symptom of multiple sclerosis. Our objective was to determine the short-term effect of smoked cannabis on this symptom. We conducted a placebo-controlled, crossover trial involving adult patients with multiple sclerosis and spasticity. We recruited participants from a regional clinic or by referral from specialists. We randomly assigned participants to either the intervention (smoked cannabis, once daily for three days) or control (identical placebo cigarettes, once daily for three days). Each participant was assessed daily before and after treatment. After a washout interval of 11days, participants crossed over to the opposite group. Our primary outcome was change in spasticity as measured by patient score on the modified Ashworth scale. Our secondary outcomes included patients' perception of pain (as measured using a visual analogue scale), a timed walk and changes in cognitive function (as measured by patient performance on the Paced Auditory Serial Addition Test), in addition to ratings of fatigue. Thirty-seven participants were randomized at the start of the study, 30 of whom completed the trial. Treatment with smoked cannabis resulted in a reduction in patient scores on the modified Ashworth scale by an average of 2.74 points more than placebo (p < 0.0001). In addition, treatment reduced pain scores on a visual analogue scale by an average of 5.28 points more than placebo (p = 0.008). Scores for the timed walk did not differ significantly between treatment and placebo (p = 0.2). Scores on the Paced Auditory Serial Addition Test decreased by 8.67 points more with treatment than with placebo (p = 0.003). No serious adverse events occurred during the trial. Smoked cannabis was superior to placebo in symptom and pain reduction in participants with treatment-resistant spasticity. Future studies should examine whether different doses can result in similar beneficial effects with less cognitive impact.

Global climate change and other anthropogenic stressors have heightened the need to rapidly characterize ecological changes in marine benthic communities across large scales. Digital photography enables rapid collection of survey images to meet this need, but the subsequent image annotation is typically a time consuming, manual task. We investigated the feasibility of using automated point-annotation to expedite cover estimation of the 17 dominant benthic categories from survey-images captured at four Pacific coral reefs. Inter- and intra- annotator variability among six human experts was quantified and compared to semi- and fully- automated annotation methods, which are made available at coralnet.ucsd.edu. Our results indicate high expert agreement for identification of coral genera, but lower agreement for algal functional groups, in particular between turf algae and crustose coralline algae. This indicates the need for unequivocal definitions of algal groups, careful training of multiple annotators, and enhanced imaging technology. Semi-automated annotation, where 50% of the annotation decisions were performed automatically, yielded cover estimate errors comparable to those of the human experts. Furthermore, fully-automated annotation yielded rapid, unbiased cover estimates but with increased variance. These results show that automated annotation can increase spatial coverage and decrease time and financial outlay for image-based reef surveys.

Recent studies show two-dimensional (2D)-magnetic resonance elastography (MRE) is accurate in diagnosing advanced fibrosis (stages 3 and 4) in nonalcoholic fatty liver disease (NAFLD) patients. Three-dimensional (3D)-MRE is a more advanced version of the technology that can image shear-wave fields in 3D of the entire liver. The aim of this study was to prospectively compare the diagnostic accuracy of 3D-MRE and 2D-MRE for diagnosing advanced fibrosis in patients with biopsy-proven NAFLD. This cross-sectional analysis of a prospective study included 100 consecutive patients (56% women) with biopsy-proven NAFLD who also underwent MRE. Area under the receiver operating characteristic (AUROC) analysis was performed to assess the accuracy of 2D- and 3D-MRE in diagnosing advanced fibrosis. The mean (±s.d.) of age and body mass index were 50.2 (±13.6) years and 32.1 (±5.0) kg/m(2), respectively. The AUROC for diagnosing advanced fibrosis was 0.981 for 3D-MRE at 40 Hz, 0.927 for 3D-MRE at 60 Hz (standard shear-wave frequency), and 0.921 for 2D-MRE at 60 Hz (standard shear-wave frequency). At a threshold of 2.43 kPa, 3D-MRE at 40 Hz had sensitivity 1.0, specificity 0.94, positive predictive value 0.72, and negative predictive value 1.0 for diagnosing advanced fibrosis. 3D-MRE at 40 Hz had significantly higher AUROC (P<0.05) than 2D-MRE at 60 Hz for diagnosing advanced fibrosis. Utilizing a prospective study design, we demonstrate that 3D MRE at 40 Hz has the highest diagnostic accuracy in diagnosing NAFLD advanced fibrosis. Both 2D- and 3D-MRE at 60 Hz, the standard shear-wave frequency, are also highly accurate in diagnosing NAFLD advanced fibrosis.

Objectives. We examined smoking cessation rate by education and determined how much of the difference can be attributed to the rate of quit attempts and how much to the success of these attempts. Methods. We analyzed data from the National Health Interview Survey (NHIS, 1991–2010) and the Tobacco Use Supplement to the Current Population Survey (TUS-CPS, 1992–2011). Smokers (≥ 25 years) were divided into lower- and higher-education groups (≤ 12 years and > 12 years). Results. A significant difference in cessation rate between the lower- and the higher-education groups persisted over the last 2 decades. On average, the annual cessation rate for the former was about two thirds that of the latter (3.5% vs 5.2%; P < .001, for both NHIS and TUS-CPS). About half the difference in cessation rate can be attributed to the difference in quit attempt rate and half to the difference in success rate. Conclusions. Smokers in the lower-education group have consistently lagged behind their higher-education counterparts in quitting. In addition to the usual concern about improving their success in quitting, tobacco control programs need to find ways to increase quit attempts in this group.