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Delay discounting is a component of reward processing that affects decision-making in various health behavior domains. This study examined the discounting of gains and losses for monetary and pain outcomes among adults with and without chronic pain. Pain severity and pain catastrophizing (PC) were examined as additional moderators. This study assessed the discounting rates of 138 adults with chronic pain and 147 adults without chronic pain using online convenience sampling. Delay discounting was measured using an adjusting amount procedure, which titrates discounting rates based on participants' responses to identify points of indifference. Adults with and without chronic pain discounted losses more than gains and discounted pain outcomes more than monetary outcomes. There were no differences between groups based on chronic pain status or average self-reported pain severity. Post hoc analyses show that, on average, adults with chronic pain and high pain catastrophizing discounted monetary losses less than adults without chronic pain and low pain catastrophizing. This finding suggests that a tendency to defer immediate losses in favor of even larger delayed losses is dependent on high pain catastrophizing in the context of chronic pain. If pain catastrophizing is a more robust predictor of discounting rates than other pain metrics, then catastrophizing may be the construct that predicts risky decision-making. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

PURPOSE: Despite the growing calls for early and ubiquitous completion of advance directives (ADs), studies exploring links between AD completion and their impact on outcomes of patients with cancer have mixed conclusions. We used the ASCO Quality Oncology Practice Initiative (QOPI) registry to compare end-of-life (EOL) quality measures and the effect of QOPI certification among patients with and without early AD completion, defined as completion within the first three oncology visits after cancer diagnosis. METHODS: Deidentified patient-level data were analyzed from the QOPI database from 2015 through 2017. Associations were assessed using Chi-square tests between early AD completion and patient enrollment in hospice < 7 days before death, chemotherapy receipt in the last 14 days of life, or with emergency room visits or intensive care unit admissions in the last 30 days of life. RESULTS: Data from 31,558 patients eligible for the AD question were analyzed. Patients treated at QOPI-certified practices had higher rates of early AD completion than patients at non-certified practices. Early AD completion was not associated with differences in hospice enrollment for < 7 days before death, chemotherapy receipt in the last 14 days of life, or emergency room visits or intensive care unit encounters in the last 30 days of life. CONCLUSION: The study found that QOPI certification is associated with higher rates of early AD completion. However, early AD completion was not associated with recognized EOL quality measures. Future research should focus on the timing, frequency, and content of AD conversations to demonstrate the impact on care at the EOL.

OBJECTIVE In the management of diabetic ketoacidosis (DKA), the standard of care is to administer insulin glargine after ketoacidosis has resolved and the patient is transitioning from intravenous (IV) insulin to subcutaneous insulin; however, there is evidence to suggest that earlier administration of insulin glargine may accelerate resolution of ketoacidosis. The objective of this research is to determine the efficacy of early subcutaneous insulin glargine on time to resolution of ketoacidosis in children with moderate to severe DKA. METHODS This retrospective chart review evaluated children age 2 to 21 years old admitted for moderate to severe DKA who received insulin glargine within 6 hours of hospital admission (early insulin glargine) compared with those who received insulin glargine greater than 6 hours from admission (late insulin glargine). The primary outcome was duration of time the patient received IV insulin. RESULTS A total of 190 patients were included. The median time on IV insulin was lower in patients who received early insulin glargine compared with those who received late insulin glargine (17.0 [IQR, 14–22.8] vs 22.9 hours [IQR, 4.3–29.3]; p = 0.0006). Resolution of DKA was faster in patients who received early insulin glargine compared with those who received late insulin glargine (median, 13.0 [IQR, 9.8–16.8] vs 18.2 hours [IQR, 12.5–27.6]; p = 0.005). Length of pediatric intensive care unit (PICU) and hospital stay and incidences of hypoglycemia and hypokalemia were similar between the 2 groups. CONCLUSIONS Children with moderate to severe DKA who received early insulin glargine had a significantly lower time on IV insulin, as well as significantly faster time to resolution of DKA when compared with those who received late insulin glargine. There were no significant differences observed in hospital stay and rates of hypoglycemia and hypokalemia.

Background: Delay discounting (DD), the decrease in reward valuation as a function of delay to receipt, is a key process undergirding alcohol use. Narrative interventions, including episodic future thinking (EFT), have decreased delay discounting and demand for alcohol. Rate dependence, the relationship between a baseline rate and change in that rate after an intervention, has been evidenced as a marker of ef- ficacious substance use treatment, but whether narrative interventions have rate dependent effects needs to be better understood. We investigated the effects of narrative interventions on delay discounting and hypothetical demand for alcohol in this longitudinal, online study. Methods: Individuals (n = 696) reporting high-or low risk alcohol use were recruited for a longitudinal 3 week survey via Amazon Mechanical Turk. Delay discounting and alcohol demand breakpoint were assessed at baseline. Individuals returned at weeks 2 and 3 and were randomized into the EFT or scarcity narrative interventions and again completed the delay discounting tasks and alcohol breakpoint task. Oldham's correlation was used to explore the rate-dependent effects of narrative interventions. Study attrition as a function of delay discounting was assessed. Results: Episodic future thinking significantly decreased, while scarcity significantly increased delay discounting relative to baseline. No effects of EFT or scarcity on the alcohol demand breakpoint were observed. Significant rate-dependent effects were observed for both narrative intervention types. Higher delay discounting rates were associated with a greater likelihood of attrition from the study. Conclusion: The evidence of a rate-dependent effect of EFT on delay discounting rates offers a more nuanced, mechanistic understanding of this novel therapeutic intervention and can allow more precise treatment targeting by demonstrating who is likely to receive the most benefit from it. NIAAA [R01 AA027381]; Fralin Biomedical Research Institute at VTC Published version This work was supported by NIAAA R01 AA027381 and the Fralin Biomedical Research Institute at VTC. The funders had no role other than financial support.

We present a mathematical modeling framework for roster construction of a Major League Soccer (MLS) expansion team. The model seeks to construct the best squad feasible under league salary rules, while balancing present value, potential value, and future cap flexibility. Player acquisition decisions, as well as allocation of salary, targeted allocation money (TAM), general allocation money (GAM), and designated player slots, are determined simultaneously by a mixed-integer programming model. We demonstrate the model’s functionality in constructing a hypothetical expansion roster and propose a number of extensions.

When creating mathematical models for forecasting and decision making, there is a tendency to include more complexity than necessary, in the belief that higher-fidelity models are more accurate than simpler ones. In this paper, we analyze the performance of models that submitted COVID-19 forecasts to the U.S. Centers for Disease Control and Prevention and evaluate them against a simple two-equation model that is specified using simple linear regression. We find that our simple model was comparable in accuracy to highly publicized models and had among the best-calibrated forecasts. This result may be surprising given the complexity of many COVID-19 models and their support by large forecasting teams. However, our result is consistent with the body of research that suggests that simple models perform very well in a variety of settings. History: This paper has been accepted for the Decision Analysis Special Issue on Emerging Topics in Health Decision Analysis. Funding: This work was supported by Sandia National Laboratories [Cockrell School of Engineering’s Engineering Foundation Endowed Professorship No. 1].

In Weighted Scoring Rules and Convex Risk Measures, Dr. Zachary J. Smith and Prof. J. Eric Bickel (both at the University of Texas at Austin) present a general connection between weighted proper scoring rules and investment decisions involving the minimization of a convex risk measure. Weighted scoring rules are quantitative tools for evaluating the accuracy of probabilistic forecasts relative to a baseline distribution. In their paper, the authors demonstrate that the relationship between convex risk measures and weighted scoring rules relates closely with previous economic characterizations of weighted scores based on expected utility maximization. As illustrative examples, the authors study two families of weighted scoring rules based on phi-divergences (generalizations of the Weighted Power and Weighted Pseudospherical Scoring rules) along with their corresponding risk measures. The paper will be of particular interest to the decision analysis and mathematical finance communities as well as those interested in the elicitation and evaluation of subjective probabilistic forecasts.

Ion beam implantations are widely performed to understand the effects of irradiation-induced displacement damage on nuclear structural materials. However, the volume of material that can be investigated is often limited by the maximum energies of accelerator facilitates, leading to a limitation in the thickness of samples whose mechanical properties can be evaluated. The Lawrence Berkeley National Laboratory's 88-Inch Cyclotron offers a wide range of ions and energies, allowing for material ion implantations at larger scales than typical. Four HT-9 SS-J-geometry tensile specimens were polished and then irradiated with deuterons at the 88-Inch Cyclotron to doses of approximately 0.2 dpa prior to small scale tensile testing. The results from this study show irradiation hardening characterized by the tensile test results and black dot irradiation defects. Additionally, a comprehensive look at low temperature irradiations of high-Cr F/M steels is presented and our results show agreement with the available data.

Subjective cognitive decline (SCD) and depressive symptoms (DS) frequently co-occur prior to dementia. However, the temporal sequence of their emergence and their combined prognostic value for cognitive decline and dementia is unclear.Temporal relationships of SCD, DS and memory decline were examined by latent difference score modeling in a high-aged, population-based cohort (N = 3217) and validated using Cox-regression of dementia-conversion. In 334 cognitively unimpaired SCD-patients from memory-clinics, we examined the association of DS with cognitive decline and with cerebrospinal fluid (CSF) Alzheimer's disease (AD) biomarkers.In the population-based cohort, SCD preceded DS. High DS were associated with increased risk of dementia conversion in individuals with SCD. In SCD-patients from memory-clinics, high DS were associated with greater cognitive decline. CSF Aß42 predicted increasing DS.SCD typically precedes DS in the evolution to dementia. SCD-patients from memory-clinics with DS may constitute a high-risk group for cognitive decline.Subjective cognitive decline (SCD) precedes depressive symptoms (DS) as memory declines. Emerging or persistent DS after SCD reports predict dementia. In SCD patients, more amyloid pathology relates to increasing DS. SCD patients with DS are at high risk for symptomatic progression.

The coronavirus disease pandemic of 2019 (COVID-19) is a worldwide threat to public health that has significantly affected the United States. The pandemic poses a variety of health risks including stressful disruptions in social and economic activity. Understanding the pandemic's effects on already vulnerable populations, such as individuals with chronic pain, may inform healthcare preparation for future catastrophic events. Given the association between excessive discounting of delayed rewards and chronic pain, this study examined relationships between delay discounting, pain severity, and COVID-19 perceived stress in individuals with chronic pain. Individuals reporting chronic pain (N = 180; 41% female; 86% white; 59% with a college degree) were recruited via the Amazon Mechanical Turk platform in this cross-sectional study. Measures of pain severity, delay discounting, probability discounting, and COVID-19 perceived stress were collected. Delay discounting was a significant predictor of overall pain severity (p.02) and COVID-19 perceived stress (p.001). Also, the magnitude of COVID-19 perceived stress fully mediated the relationship between delay discounting and overall pain severity (p = .004). Probability discounting was not a significant predictor of pain severity or COVID-19 perceived stress (p.05). These findings highlight the importance of excessive discounting of delayed rewards as a potential determinant of pain severity as well as predictor of perceived stress related to the COVID-19 pandemic. Thus, the discounting of delayed rewards is of particular therapeutic importance for individuals with chronic pain in the context of stressful events. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Imagining narratives involving sudden economic scarcity has been shown to increase delay discounting rates. However, previous studies have only compared active and control narratives between groups. Moreover, an investigation of the quantitative effects of different narrative scenario types has not been conducted. In this study, active and control scarcity narratives were administered within-subject in a sample of individuals meeting criteria for alcohol use disorder (AUD). Individuals with AUD (N = 81; 26.9% female) were recruited via Amazon Mechanical Turk. After assignment to the job (N = 42) or storm (N = 39) narrative groups, participants completed delay discounting tasks while imagining an active (job loss/hurricane) and control (job neutral/mild storm) condition. Both active narratives increased delay discounting relative to the corresponding control condition (p < .001), with no effect of order of presentation (p = .202). Additionally, both narrative types exerted similar effect sizes on discounting rates (job: d = 0.54; storm: d = 0.45). This study replicates and extends previous research on the manipulability of delay discounting rates with scarcity narratives. We demonstrated that the active narrative significantly increased delay discounting relative to a control narrative within-subject, regardless of presentation order. Moreover, both the job loss and hurricane narratives exerted a similar effect on the delay discounting rate. These results highlight the robust ability of the Narrative Theory framework to shift delay discounting rates and suggest that in AUD, imagining economic scarcity due to job loss or hurricane exerts comparable effects on behavioral economic decision-making. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The Thebes Limestone Formation of Lower Eocene age is one of the most extensive rock units in Egypt. It is of importance to the apogee of the ancient Egyptian civilization, particularly in Luxor (South-Central Egypt), where the rock formation hosts the Theban Necropolis, a group of funerary chambers and temples from the New Kingdom Egyptian era (3500–3000 BP). In this work, we investigated the petrophysical and rock mechanical properties (e.g., rock strength, critical crack stress thresholds) through laboratory tests on eleven rock blocks collected from one area within the Theban Necropolis known as the Valley of the Kings (KV). The blocks belong to Member I of the Thebes Limestone Formation, including six blocks of marly limestone, three blocks of micritic limestone, one block of argillaceous limestone from the Upper Esna Shale Formation, and one block of silicified limestone of unknown origin. Special attention was given to the orientation of bedding planes in the samples: tests were conducted in parallel (PA) and perpendicular (PE) configurations with respect to bedding planes. We found that the marly limestone had an average unconfined compressive strength (UCS) of 30 MPa and 39 MPa for the PA and PE tests, respectively. Similarly, the micritic limestone tests showed an average UCS of 24 MPa for the PA orientation and 58 MPa for the PE orientation. The critical crack thresholds were the first ever reported for Member I, as measured with strain gauge readings. The average crack initiation (CI) stress thresholds for the marly limestone (PA: 14 MPa) and the micritic limestone (PA: 11 MPa; PE: 24 MPa) fall within the typical ratio of CI to UCS (0.36–0.52). The micritic limestone had an average Young’s modulus (E) of 19.5 GPa and 10.3 GPa for PA and PE, respectively. The Poisson’s ratios were 0.2 for PA and 0.1 for PE on average. Both marly and micritic limestone can be characterised by a transverse isotropic strength behaviour with respect to bedding planes. The failure strength for intact anisotropic rocks depends on the orientation of the applied force, which must be considered when assessing the stability of tombs and cliffs in the KV and will be used to understand and improve the preservation of this UNESCO World Heritage site.

The Chrysosoma lucigena species group is revised and comprises 13 species, all from New Guinea and immediately adjacent islands: C. lucigena (Walker) and C. splendidum (Wulp), and 11 newly described species: C. akrikense, C. baiyerense, C. betege, C. bitcoin, C. cuprevittatum, C. fumifemoratum, C. macalpinei, C. orokaindi, C. oromissim, C. tabubil, and C. watutense. The lucigena group comprises species with dark maculated wings, long setae on the femur and tibia of leg I, and metallic green and bronze thoracic coloration. The total loss of anterior dorsocentral setae in both sexes of the lucigena group is discussed in the context of a possible source for higher-level taxonomic characters in Diptera.

This analysis describes participants' opioid use disorder (OUD) outcomes for 18 months after discontinuing extended-release buprenorphine injection (BUP-XR, SUBLOCADE).The RECOVER (Remission From Chronic Opioid Use: Studying Environmental and Socioeconomic Factors on Recovery) study recruited participants from BUP-XR clinical trials (NCT023579011, NCT025100142, and NCT02896296) to assess whether there were sustained benefits after leaving the trial. Abstinence from opioids and from all illicit substances (excluding medical cannabis), health-related quality of life, depression, and employment were measured after BUP-XR discontinuation and change in outcomes assessed at 6, 12, and 18 months. Results were analyzed within the full cohort and by duration of BUP-XR treatment (0-2 months, 3-5 months, 6-11 months, 12 months, or 13-18 months) with and without inverse probability weights adjusting for differences in baseline characteristics.Of 533 participants, 529 were assessed over the 18-month study period. Further posttrial pharmacotherapy was reported by 33% of participants. At RECOVER baseline, longer BUP-XR was associated with higher abstinence (0-2 months BUP-XR [n = 116]: 38.8%; 3-5 months BUP-XR [n = 61]: 41.0%; 6-11 months BUP-XR [n = 86]: 68.6%; 12 months BUP-XR [n = 135]: 71.9%; 18 months BUP-XR [n = 131]: 88.2%) and greater 12-Item Short Form Health Survey mental component scores. Over 60% of participants had stable or improved outcomes at 6, 12, and 18 months assessments. Overall 47% of participants self-reported sustained opioid abstinence for the full 18-month follow-up, with greater sustained abstinence associated with longer BUP-XR treatment duration. A sensitivity analysis, removing patients receiving medications for OUD, yielded similar results.Participants from BUP-XR clinical trials who continued into RECOVER maintained or improved on numerous outcomes over 18 months, demonstrating the long-term positive impact of OUD pharmacotherapy.

We study the boundary behavior of rational inner functions (RIFs) in dimensions three and higher from both analytic and geometric viewpoints. On the analytic side, we use the critical integrability of the derivative of a rational inner function of several variables to quantify the behavior of a RIF near its singularities, and on the geometric side we show that the unimodular level sets of a RIF convey information about its set of singularities. We then specialize to three-variable degree $(m,n,1)$ RIFs and conduct a detailed study of their derivative integrability, zero set and unimodular level set behavior, and non-tangential boundary values. Our results, coupled with constructions of non-trivial RIF examples, demonstrate that much of the nice behavior seen in the two-variable case is lost in higher dimensions., 36 pages, 7 figures

Crowdsourcing platforms allow researchers to quickly recruit and collect behavioral economic measures in substance-using populations, such as cigarette smokers. Despite the broad utility and flexibility, data quality issues have been an object of concern. In two separate studies recruiting cigarette smokers, we sought to investigate the association between a practical quality control measure (accuracy on an instruction quiz), on internal consistency of number of cigarettes smoked per day and purchasing patterns of tobacco products in an experimental tobacco marketplace (ETM; Study 1), and in a cigarette purchase task (CPT; Study 2). Participants (N = 312 in Study 1; N = 119 in Study 2) were recruited from Amazon mechanical turk. Both studies included task instructions, a quiz, a purchase task, cigarette usage and dependence questions, and demographics. The results show that participants who answered all instruction items correctly: (a) reported the number of cigarettes per day more consistently (partial η² = 0.11, p.001, Study 1; partial η² = 0.09, p = .016, Study 2), (b) demonstrated increased model fit among the cigarette demand curves (partial η² = 0.23, p.001, Study 1; partial η² = 0.08, p = .002, Study 2), and purchased tobacco products in the ETM more consistently with their current usage. We conclude that instruction quizzes before purchase tasks may be useful for researchers evaluating demand data. Instruction quizzes with multiple items may allow researchers to choose the level of data quality appropriate for their studies. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Crowdsourced methods of data collection such as Amazon Mechanical Turk (MTurk) have been widely adopted in addiction science. Recent reports suggest an increase in poor quality data on MTurk, posing a challenge to the validity of findings. However, empirical investigations of data quality in addiction-related samples are lacking. In this study of individuals with alcohol use disorder (AUD), we compared poor quality delay discounting data to randomly generated data. A reanalysis of prior published delay discounting data was conducted comparing included, excluded, and randomly generated data samples. Nonsystematic criteria were implemented as a measure of data quality. The excluded data was statistically different from the included sample but did not differ from randomly generated data on multiple metrics. Moreover, a response bias was identified in the excluded data. This study provides empirical evidence that poor quality delay discounting data in an AUD sample is not statistically different from randomly generated data, suggesting data quality concerns on MTurk persist in addiction samples. These findings support the use of rigorous methods of a priori defined criteria to remove poor quality data post hoc. Additionally, it highlights that the use of nonsystematic delay discounting criteria to remove poor quality data is rigorous and not simply a way of removing data that does not conform to an expected theoretical model. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Interlocking puzzles are intriguing geometric games where the puzzle pieces are held together based on their geometric arrangement, preventing the puzzle from falling apart. High-level-of-difficulty , or simply high-level , interlocking puzzles are a subclass of interlocking puzzles that require multiple moves to take out the first subassembly from the puzzle. Solving a high-level interlocking puzzle is a challenging task since one has to explore many different configurations of the puzzle pieces until reaching a configuration where the first subassembly can be taken out. Designing a high-level interlocking puzzle with a user-specified level of difficulty is even harder since the puzzle pieces have to be interlocking in all the configurations before the first subassembly is taken out. In this paper, we present a computational approach to design high-level interlocking puzzles. The core idea is to represent all possible configurations of an interlocking puzzle as well as transitions among these configurations using a rooted, undirected graph called a disassembly graph and leverage this graph to find a disassembly plan that requires a minimal number of moves to take out the first subassembly from the puzzle. At the design stage, our algorithm iteratively constructs the geometry of each puzzle piece to expand the disassembly graph incrementally, aiming to achieve a user-specified level of difficulty. We show that our approach allows efficient generation of high-level interlocking puzzles of various shape complexities, including new solutions not attainable by state-of-the-art approaches.

Objectives To develop an intuitive and generally applicable system for the reporting, assessment, and documentation of ADC to complement standard BI-RADS criteria. Methods This was a multicentric, retrospective analysis of 11 independently conducted institutional review board–approved studies from seven institutions performed between 2007 and 2019. Breast Apparent Diffusion coefficient (ADC-B) categories comprised ADC-B0 (ADC non-diagnostic), ADC-B1 (no enhancing lesion), and ADC-B2-5. The latter was defined by plotting ADC versus cumulative malignancy rates. Statistics comprised ANOVA with post hoc testing and ROC analysis. p values ≤ 0.05 were considered statistically significant. Results A total of 1625 patients (age: 55.9 years (± 13.8)) with 1736 pathologically verified breast lesions were included. The mean ADC (× 10−3 mm2/s) differed significantly between benign (1.45, SD .40) and malignant lesions (.95, SD .39), and between invasive (.92, SD .22) and in situ carcinomas (1.18, SD .30) (p 24.5%). At the latter threshold, a positive predictive value of 95.8% (95% CI 0.94–0.97) for invasive versus non-invasive breast carcinomas was reached. Conclusions The breast apparent diffusion coefficient system (ADC-B) provides a simple and widely applicable categorization scheme for assessment, documentation, and reporting of apparent diffusion coefficient values in contrast-enhancing breast lesions on MRI. Clinical relevance statement The ADC-B system, based on diverse MRI examinations, is clinically relevant for stratifying breast cancer risk via apparent diffusion coefficient measurements, and complements BI-RADS for improved clinical decision-making and patient outcomes. Key Points • The breast apparent diffusion coefficient category system (ADC-B) is a simple tool for the assessment, documentation, and reporting of ADC values in contrast-enhancing breast lesions on MRI. • The categories comprise ADC-B0 for non-diagnostic examinations, ADC-B1 for examinations without an enhancing lesion, and ADC-B2-5 for enhancing lesions with an increasing malignancy rate. • The breast apparent diffusion coefficient category system may be used to complement BI-RADS in clinical decision-making.

Neural representations of perceptual decision formation that are abstracted from specific motor requirements have previously been identified in humans using non-invasive electrophysiology, however, it is currently unclear where these originate in the brain. Here, we capitalized on the high spatiotemporal precision of intracranial EEG to localize such abstract decision signals. Presurgical epilepsy patients judged the direction of random-dot stimuli and responded either with a speeded button press (N=23), or vocally, after a randomized delay (N=11). We found a widely distributed motor-independent network of regions where high-frequency activity exhibited key characteristics consistent with evidence accumulation, including a gradual build-up that was modulated by the strength of the sensory evidence, and an amplitude that predicted subjects’ choice accuracy and response time. Our findings offer a new view on the brain networks governing human decision making.

In the use of statistical models to analyze data, there is not only the uncertainty quantified by the models but also uncertainty about which models are adequate for some purpose, such as weighing the evidence for or against a hypothesis of scientific interest. This paper provides methods for propagating such unquantified uncertainty to the results under a unified framework of adequate model averaging. Specifically, the weight of each model used in the average is the probability that it is the most useful model. To allow for the case that none of the models considered would be useful, a catch-all model is included in the model average at a different level of the hierarchy. The catch-all model is the vacuous model in imprecise probability theory, the model that puts no restrictions on the probabilities of statements about the unknown values of interest. That enables defining the proportion of the uncertainty left unquantified by a model as the probability that it is inadequate in the sense of being less useful than the catch-all model. A lower bound for the proportion of unquantified uncertainty of the averaged model decreases as more models are added to the average.

Introduction Access to surgical service is limited by provider availability and geographic barriers. Telemedicine ensures that patients can access medical care. Objective The objective is to describe our use of telemedicine in delivering vascular surgery services to remote locations before and during the COVID-19 pandemic. Methods We conducted a retrospective chart review analyzing care delivered at six vascular surgery telemedicine clinics over a 22-month period. We examined vascular diagnoses, recommended interventions, referrals placed, and emergency department visits within 30 days of evaluation. We calculated travel distance saved for patients between their local clinic and our main hospital. Results We identified 94 patients and 144 telemedicine visits, with an average of 1.5 visits per patient (SD = 0.73). The most common referrals were for peripheral artery disease (20.2%) and abdominal aortic aneurysm (14.9%). Three patients were immediately referred to the emergency department due to concern for acute limb ischemia (2) or questionable symptomatic AAA (1). Telemedicine visit recommendations were distributed between no intervention (n = 30, 31.9%), medical management (n = 41, 43.6%), and surgical intervention (n = 23, 24.5%). The surgical intervention cohort was most commonly referred to arterial revascularization (n = 4), venous ablation (n = 4), and arteriovenous fistula procedures (n = 4). Fourteen patients came to our main hospital for surgery and four to local providers. Average travel distance saved per telemedicine visit was 104 miles (SD = 43.7). Conclusions Telemedicine provided safe, efficient care during the COVID-19 pandemic and saved patients an average of 104 travel miles per visit.

E-cigarette use is prohibited in most smoke-free environments. The effect of this policy on tobacco consumption could be examined using the Experimental Tobacco Marketplace (ETM). The ETM allows observation of policy on smokers' purchasing behavior under conditions that simulate "real-world" circumstances. A within-subject design was used to evaluate the effect of workplace policy (Vaping Allowed vs. Not Allowed) and nicotine concentration (24 mg/mL vs. 0 mg/mL) on tobacco product consumption. Participants (n = 31) completed one sampling and two ETM/workplace sessions per week for 2 weeks. During the sampling session, participants were given an e-cigarette with a 2-day supply of a commercially available e-liquid of their preferred flavor. Before purchasing, participants were informed whether e-cigarette use was permitted. During the four ETM sessions, participants purchased for the following 24 hr, including the 4-hr work shift that started immediately after buying products in the ETM. The workplace session consisted of data entry tasks in a mock office environment. Participants could use any purchased tobacco products during two 15-min breaks. Condition order was counterbalanced. The results show that permitting E-cigarette use in the workplace increased e-liquid purchase on average, but nicotine concentration had no effect on e-liquid demand. Cigarette demand was unaltered across conditions. The present study suggests that allowing e-cigarette use in the workplace would increase demand for e-liquid regardless of nicotine strength. However, it would not change conventional cigarette demand. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Reinforcer Pathology theory proposes that expanding the temporal window of reinforcement (i.e., reducing delay discounting) using episodic future thinking (EFT) would decrease alcohol consumption. However, evidence of effectiveness in real-world settings is lacking. Using a randomized proof-of-concept field trial, the current study examined the effect of expanding the temporal window of reinforcement, using remotely delivered EFT, on decreasing real-world alcohol consumption among individuals with alcohol use disorder (AUD). Fifty-two individuals (9 females) aged 18-65 years who met the DSM-5 criteria for moderate or severe AUD and aimed to drink in moderation or abstain from drinking completed the study and were included in analysis. EFT significantly (p = .031) reduced alcohol consumption (mean change of consumption pre-post intervention = -2.18 drinks/day) compared to control episodic recent thinking (ERT; mean change of -0.52 drinks/day). Changes in discounting rates pre-post intervention significantly predicted changes in alcohol consumption (coef. = .424, 95% CI [.043-.813], p = .030) even after controlling for age, gender, race, income, education, marital status, and family history of addiction. Overall satisfaction across groups was rated as 3.92 on a 1 to 5-point scale, suggesting that the current remote approach is feasible and acceptable. The current findings were congruent with the theory, Reinforcer Pathology, that EFT expands the temporal window and decreases alcohol consumption, and the remote approach was considered feasible and acceptable. We believe the present study contributes new knowledge with tangible benefits for scientifically understanding and better defining novel interventions that may be clinically deployed to improve treatment outcomes. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Preservation of museum specimens depends on chemical fixation and preservation, processes that might distort the original material. Relatively few studies have examined the effects of preservation in potentially susceptible soft-bodied taxa, such as herpetofauna, and those that have rarely extend over more than a few months. We collected six common morphological measurements from the same set of radiographed specimens of the Neotropical lizard Anolis sagrei over nearly 10 years to investigate whether morphometric changes result from fixation in formalin and/or subsequent long-term preservation in ethanol. Snout–vent length declined by 3.5% on average over 10 years, starting almost immediately with fixation and continuing to decline during fluid preservation, eventually levelling off at 40 weeks and beyond. The mostly ossified component of snout–vent length, spine length, declined by 2% on average, but the decline did not begin until fluid preservation commenced and continued throughout the duration of the study. Other characters showed significant decline over the course of the study. Our findings suggest caution when combining fresh and preserved specimens or specimens of different preservation ages, because a decline in snout–vent length but not in other allometrically proportional characters will introduce error when correcting characters for body size in preserved animals.

Digital engineering is increasingly established in the industrial routine. Especially the application of machine learning on geometry data is a growing research issue. Driven by this, the paper presents a new method for the classification of mechanical components, which utilizes the projection of points onto a spherical detector surfaces to transfer the geometries into matrices. These matrices are then classified using deep learning networks. Different types of projection are examined, as are several deep learning models. Finally, a benchmark dataset is used to demonstrate the competitiveness.

The world consequently gets faster, so does product development. Therefore, the stock of development and simulation data increases continuously. Unfortunately, inexperienced users cannot cope with the rising number of simulation requests in the time needed. Digital Engineering opens potentials to support the users with newly developed methods and tools. In this contribution, we present a method to assist designers, inexperienced in finite-element simulations to perform an initial check of changed parametric designs independently, quickly and with support in interpreting the results.