Ripple (United States)

e13715 Background: Current clinical guidelines recommend that clinicians provide individualized exercise prescriptions to cancer survivors. However, there are no clinical decision tools to support individualized exercise prescriptions considering individual clinical and demographic characteristics of breast cancer survivors. We aimed to gather breast cancer survivors’ perspectives on a prototype of a clinical decision tool to support individualized exercise prescriptions in clinical settings. Methods: A racially and ethnically diverse sample of breast cancer survivors across the U.S. were recruited to complete an online survey. Survey items were adapted from validated pre-existing instruments and refined via cognitive interviews with survivors and healthcare providers. Within the survey, survivors were presented with images of a prototype of the tool with an accompanying explanation of the tool’s potential functionality. The tool prototype was developed with input from breast cancer survivors, mathematic modelers, exercise specialists, and clinicians according to the Collaborative Deliberation Model. The tool was designed to generate breast cancer outcomes associated with various levels of exercise based on individual characteristics of the breast cancer survivors. Survivors were asked to rate the extent to which they agreed that: (I) the tool would be useful; (II) what they would use the tool for (e.g., education); and (III), the tool should include certain characteristics (e.g., exercise benefits). The data was analyzed using descriptive statistics. Results: Ninety-eight breast cancer survivors responded to the survey. Most agreed that a tool would be useful (84.7%) and increase their confidence to discuss exercise with a healthcare provider (74.5%). The highest agreement for tool uses was found for education (84.1%) and encouragement to exercise (79.3%). Improving the ability to do everyday tasks (74.0%), quality-of-life (72.6%), and energy (71.4%) were rated as the top exercise benefits to include in a tool. Agreement on tool usefulness, uses, and tool characteristics varied by breast cancer survivors’ demographic, clinical, and contextual characteristics. Conclusions: This evidence-based clinical decision tool offering individualized exercise prescriptions may help diverse breast cancer survivors engage in discussions and shared decision-making about exercise with healthcare providers in clinical settings.

Although many recent works have made advancements in the image restoration (IR) field, they often suffer from an excessive number of parameters. Another issue is that most Transformer-based IR methods focus only on either local or global features, leading to limited receptive fields or deficient parameter issues. To address these problems, we propose a lightweight network, Reciprocal Attention Mixing Transformer (RAMiT). It employs our proposed dimensional reciprocal attention mixing Transformer (D-RAMiT) blocks, which compute bi-dimensional self-attentions in parallel with different numbers of multi-heads. The bidimensional attentions help each other to complement their counterpart's drawbacks and are then mixed. Additionally, we introduce a hierarchical reciprocal attention mixing (H-RAMi) layer that compensating for pixel-level information losses and utilizes semantic information while maintaining an efficient hierarchical structure. Furthermore, we revisit and modify MobileNet V2 to attach efficient convolutions to our proposed components. The experimental results demonstrate that RAMiT achieves state-of-theart performance on multiple lightweight IR tasks, including super-resolution, low-light enhancement, deraining, color denoising, and grayscale denoising. Codes are available at https://github.com/rami0205/RAMiT.

The offspring of US military service members may be at increased risk for eating disorders. However, no epidemiological studies to date have evaluated eating disorder incidence rates and prevalence estimates among military-dependent youth. This retrospective cohort study examined eating disorder diagnoses in the military healthcare system (MHS) from 2016 through 2021. Active duty and national guard military-dependent youth, aged 10-17 years, who received care in the MHS via TRICARE Prime insurance, were identified by one or more ICD-10 codes indicative of an eating disorder diagnosis (anorexia nervosa, bulimia nervosa, binge-eating disorder, and other-specified eating disorders). During the 6-year surveillance period, 2534 dependents received incident diagnoses of eating disorders, with a crude overall incidence rate of 1.75 cases per 10,000 person-years. The most common diagnosis was other-specified eating disorder, followed by anorexia nervosa, bulimia nervosa, and binge-eating disorder. The crude annual incidence rate of all eating disorder diagnoses increased by nearly 65% from 2016 to 2021. Rates for all diagnoses were highest in 2020 and 2021. Period prevalence estimateswere .08% for any eating disorder diagnosis, .01% for anorexia nervosa, .004% for bulimia nervosa, .004% for binge-eating disorder, and .06% for other-specified eating disorders. The observed increase in eating disorder diagnoses during the surveillance period appeared to be driven by female dependents. More military dependents experienced a new-onset diagnosis during the COVID-19 pandemic compared to previous years. These findings highlight the need for eating disorder screening, identification, and treatment for dependents within the MHS. Children of US military service members may be at increased risk for eating disorders. Results indicate new-onset eating disorder cases increased 65% from 2016 to 2021, primarily among girls compared to boys. The most diagnosed and fastest growing diagnosis was other-specified eating disorder. Rates of anorexia nervosa increased following the COVID-19 pandemic. Findings highlight the need for eating disorder screening, identification, and treatment within the military healthcare system.

This research analyzes cryptocurrency fundamentals during the pandemic COVID-19 significantly affected cryptocurrencies during a brief period of financial panic. Technological advances resulted in the shift of traditional currencies towards digitalization. Volume and market cap variables are used as independent variables. The cryptocurrencies in this study are Bitcoin, Ethereum, Binance Coin, Ripple, and Dogecoin, which have the top 10 largest market capitalization. The research data was taken on the CoinMarketcap.com website from the beginning of the pandemic in Indonesia in March 2020 – to February 2021. The results showed that the Market Cap of Bitcoin, Ethereum, Binance Coin, Ripple, and Dogecoin had a significant effect on the price. Furthermore, the volume of Bitcoin, Ethereum, Binance, and Dogecoin has an effect and is significant on the price. In comparison, Ripple Volume has no effect and is not significant to the price. This implies that highly speculatively priced cryptocurrencies have the same fundamental value as stock prices.

Electrical stimulation can be used to modulate activity within the nervous system in one of two modes: (1) Activation, where activity is added to the neural signalling pathways, or (2) Block, where activity in the nerve is reduced or eliminated. In principle, electrical nerve conduction block has many attractive properties compared to pharmaceutical or surgical interventions. These include reversibility, localization, and tunability for nerve caliber and type. However, methods to effect electrical nerve block are relatively new. Some methods can have associated drawbacks, such as the need for large currents, the production of irreversible chemical byproducts, and onset responses. These can lead to irreversible nerve damage or undesirable neural responses. In the present study we describe a novel low frequency alternating current blocking waveform (LFACb) and measure its efficacy to reversibly block the bradycardic effect elicited by vagal stimulation in anaesthetised rat model. The waveform is a sinusoidal, zero mean(charge balanced), current waveform presented at 1 Hz to bipolar electrodes. Standard pulse stimulation was delivered through Pt-Black coated PtIr bipolar hook electrodes to evoke bradycardia. The conditioning LFAC waveform was presented either through a set of CorTec® bipolar cuff electrodes with Amplicoat® coated Pt contacts, or a second set of Pt Black coated PtIr hook electrodes. The conditioning electrodes were placed caudal to the pulse stimulation hook electrodes. Block of bradycardic effect was assessed by quantifying changes in heart rate during the stimulation stages of LFAC alone, LFAC-and-vagal, and vagal alone. The LFAC achieved and block using hook (N = 7) and cuff (N = 5) electrodes, respectively, at current levels less than 110 µAp (current to peak). The potential across the LFAC delivering electrodes were continuously monitored to verify that the blocking effect was immediately reversed upon discontinuing the LFAC. Thus, LFACb produced a high degree of nerve block at current levels comparable to pulse stimulation amplitudes to activate nerves, resulting in a measurable functional change of a biomarker in the mammalian nervous system.

The web has enabled free and open information exchange for a vast number of users around the world. However, it has so far failed to do the same for payments. Instead of finding the cheapest route for each payment from a competitive network of providers, we rely on a small number of proprietary operators with global reach. The work happening at the Web Payments Working Group at W3C is attempting to remove some of the friction in performing payments on the Web by defining a standard payment API and messaging in browsers. This will make payments on the Web easier but not entirely frictionless or integrated. As active participants in the W3C's Web Payments Working Group we present a browser polyfill of one of the prosed payment APIs and will walk the audience through the goals of the WG and vision of how payments will work on the Web in the future. Building on this, we will introduce the Interledger Protocol (ILP), a new neutral payments protocol being incubated in the Interledger Payments Community Group, also at the W3C. We will demonstrate how, in the future, the combination of the W3C's Web Payments APIs and the power of ILP payments will not only be frictionless but fully integrated into how we use the Web. Ubiquitous payments in an Internet of Value.

BackgroundThe volume-outcome relationship associated with intensive care unit (ICU) experience with managing acute myocardial infarction (AMI) remains inadequately understood.Methods and ResultsWithin a multicenter clinical ICU database, we identified patients with a primary ICU admission diagnosis of AMI between 2008 and 2010 to evaluate whether annual AMI volume of an individual ICU is associated with mortality, length-of-stay, or quality indicators. Patients were categorized into those treated in ICUs with low-annual-AMI volume (≤50th percentile, <2 AMI patients/month, n=569 patients) versus high-annual-AMI volume (≥90th percentile, ≥8 AMI patients/month, n=17 553 patients). Poisson regression and generalized estimating equation with negative binomial regression were used to calculate the relative risk (95% CI) for mortality and length-of-stay, respectively, associated with admission to a low-AMI-volume ICU. When compared with high-AMI-volume, patients admitted to low-AMI-volume ICUs had substantially more medical comorbidities, higher in-hospital mortality (11% versus 4%, P<0.001), longer hospitalizations (6.9±7.0 versus 5.0±5.0 days, P<0.001), and fewer evidence-based therapies for AMI (reperfusion therapy, antiplatelets, β-blockers, and statins). However, after adjustment for baseline patient characteristics, low-AMI-volume ICU was no longer an independent predictor of in-hospital mortality (relative risk 1.17 [0.87 to 1.56]) or hospital length-of-stay (relative risk 1.01 [0.94 to 1.08]). Similar findings were noted in secondary analyses of ICU mortality and ICU length-of-stay.ConclusionsAdmission to an ICU with lower annual AMI volume is associated with higher in-hospital mortality, longer hospitalization, and lower use of evidence-based therapies for AMI. However, the relationship between low-AMI-volume and outcomes is no longer present after accounting for the higher-risk medical comorbidities and clinical characteristics of patients admitted to these ICUs.