Lewishinton5633

Single-stranded circular oligonucleotides are heavily utilized in rolling circle amplification and rolling circle transcription technologies. Although various reported methodologies are available to synthesize circular, single-stranded DNA (ssDNA), the unduly complicated protocols and the associated cost minimize the utility of these methodologies to a non-expert or a beginner in the field. Our protocol provides the simplest yet robust synthesis of circular ssDNA templates to be utilized in various applications, using minimal resources.•In this manuscript, we describe the most basic approach to synthesize circular ssDNA.•Our method utilizes the minimal resources, yet it is robust.•The utility of the methodology is very high for a non-expert or a beginner in the field.This article describes a rationale and approach for modifying the traditional rural-urban commuting area (RUCA) coding scheme used to classify U.S. ZIP codes to enable suburban/rural vs. urban core comparisons in health outcomes research that better reflect current geographic differences in access to care in U.S. populations at risk for health disparities. The proposed method customization is being employed in the Patient-Centered Outcomes Research Institute-funded Management Of Diabetes in Everyday Life (MODEL) study to assess heterogeneity of treatment effect for patient-centered diabetes self-care interventions across the rural-urban spectrum. The proposed suburban/rural vs. urban core classification scheme modification is based on research showing that increasing suburban poverty and rapid conversion of many rural areas into suburban areas in the U.S. has resulted in similar health care access problems in areas designated as rural or suburban.•The RUCA coding scheme was developed when a much higher percentage of U.S. individuals resided in areas with very low population density.•Using the MODEL study example, this study demonstrates that the RUCA classification scheme using ZIP codes does not reflect real differences in health care access experienced by medically underserved study participants.•Both internal and external validation data suggest that the proposed suburban/rural vs. urban core customization of the RUCA geographic coding scheme better reflects real differences in healthcare access and is better able to assess the differential impact of clinical interventions designed to address geographic differences in access among vulnerable populations.Maximum power point tracking in wind turbines is a topic that has attracted many researchers' interest; however, the studies presented are usually carried out only at the simulation level, so they lack a verification in the system through real measurements. On the other hand, the system's modeling is usually quite complex, making it challenging to meet the control objectives. There are unified models in which the system is treated in a generalized way according to various research purposes. This work presents a methodology that simplifies the unified system through a series of dynamic tests that applied to obtained a simplified model much easier to handle without sacrificing the system's dynamic richness. • An alternative approach for a unified wind energy conversion system is established by employing physical dynamic tests applied to the wind set. • A maximum power point tracking is verified by real-time measurements managed by an open-source platform. • Methodology related to electronic instrumentation and programming is described so the tests can be reproduced without much difficulty.We sought to develop a reversible staining protocol using micro-computed tomography (micro-CT) paired with a radiopaque contrast agent that allows for three-dimensional in situ visualization and characterization of atherosclerotic plaques. Atherosclerotic porcine coronary arteries were dissected from surrounding myocardium and incubated in iohexol at various concentrations and incubation times and then imaged using direct radiography. Line profiles were generated across the artery x-ray to determine effectiveness of the radiopaque contrast agent to penetrate the tissue. Our studies revealed that, to sufficiently delineate tissue constructs, the minimum effective iohexol concentration and incubation time were 240 mgI/mL for 1 hour. Among all groups, 24 hours of de-staining brought radiopacity back to control levels. After iohexol incubation, micro-CT was performed. Our findings demonstrate that extended staining times and a minimum iohexol concentration of 240 mgI/mL are required for effective tissue perfusion, which eliminates the diffusion distribution profile inherent to the ability of the contrast agent to traverse tissue layers.•Iohexol enhances ex vivo micro-CT imaging of atherosclerotic coronary arteries•Iohexol allows for improved tissue segmentation during micro-CT image analysis•Effectiveness of iohexol penetration of the tissue was dependent on concentration and duration of incubation.Forecasting energy demand in general, and electricity demand in particular, requires the developing reliable forecasting tools that can be used to monitor the evolution of consumers' energy needs more accurately. The proposed new hybrid GM(1,1)-VAR(1) model is meant for that purpose. The latter is based on the Grey and Vector autoregressive approaches, and makes it possible to predict future demand, by taking into account economic and demographic determinants with an exponential growth trend. Linsitinib mw With an associated APE of 1.5, a MAPE of 1.628%, and an RMSE of 15.42, this new model thus presents better accuracy indicators than hybrid models of the same nature. Also, it proves to be as accurate as some recent hybrid artificial intelligence models. The model is thus a reliable forecasting tool that can be used to monitor the evolution of energy demand.•The Grey and Vector autoregressive models are coupled to improve their accuracy.•Five economic and demographic parameters are included in the new hybrid model.•This new model is a reliable forecasting tool for assessing energy demand.The rapid diffusion of demand-side low-carbon innovations has been identified as a key strategy for maintaining average global temperature rise at or below 1.5 °C. Diffusion research tends to focus on a single sector, or single technology case study, and on a small scope of factors that influence innovation diffusion. This paper describes a novel methodology for identifying multiple demand-side innovations within a specific energy system context and for characterizing their impact on socio-technical energy systems. This research employs several theoretical frameworks that include the Energy Technology Innovation System (ETIS) framework to develop a sample of innovations; the Sustainability Transitions framework to code innovations for their potential to impact the socio-technical system; the energy justice framework to identify the potential of innovations to address aspects of justice; and how characteristics of innovations are relevant to Innovation Adoption. This coding and conceptualization creates the foundation for the future development of quantitative models to empirically assess and quantify the rate of low-carbon innovation diffusion as well as understanding the broader relationship between the diffusion of innovations and socio-technical system change. The three stages of research are•Contextualization surveys and desk research to identify low-carbon innovations across the ETIS;•Decontextualization the development of a codebook of variables•Recontextualization coding the innovations and analysis.This article adapts an existing experimental protocol for assessing individuals' ability to transfer knowledge across instrumental and pavlovian learning stages. The protocol (Transfer of Control using differential outcomes learning) is adapted to fit social contexts wherein the pavlovian learning phase is modulated so that individuals are able to observe, and potentially learn from, the stimulus associated with reinforcing outcomes presented to another (observable) individual. Transfer of Control concerns participants combining knowledge of learned instrumental and pavlovian (stimulus, response, outcome) associations in order to ground the learning of new associations. The article describes the theoretical and procedural underpinnings of a novel Social Transfer of Control methodology. The use of such a methodology is two-fold i) to serve as a guide to researchers interested in evaluating how individuals can learn from others in a partially observable setting, i.e. when behavioural and reinforcing outcome information is hidden, and bring to bear this knowledge on their own instrumental decision making; ii), to facilitate investigation of the routes of cognitive and emotional empathy, with potential applications for educational and clinical settings.•Three stage Transfer of Control behavioural methodology is adapted to include a social (pavlovian) learning stage.•Hypotheses can be tested that concern learning rewarding instrumental responses achieved by observation of others' emotionally expressive reactions to differentially rewarding outcomes.•Methodological and validation considerations for evaluating the above are presented.In this paper, we apply the method of computable general equilibrium (CGE) modeling in economics to ascertain how fiscal support measures such as wage subsidies, small business loans, and finance guarantee schemes have impacted at an economy-wide and sectoral level for 8 COVID-19 affected economies in Oceania. We model our scenarios based on IMF World economic outlook projections, combined with the fiscal stimulus packages offered to counter this global health pandemic's recessionary effect. Our study confirms that the adverse impact of COVID-19 on output is cushioned through a large fiscal stimulus package wherever offered. This package would still be inadequate to avoid unemployment and job losses in tourism and education services in Oceania, with continued support essential for their survival in 2021.•The approach entails steps (1) to (3), as outlined in the paper.•Future researchers will find this method useful in evaluating the adverse impact of not only COVID-19 but any other external shocks to the economy, either directly or indirectly, that involves fiscal support mechanisms.The present manuscript is the expansion of the method Modelling of freezing time described in a previous paper. This modeling was used for simulating freezing times required for the inactivation of anisakids. The method described here can also be used for a number of other applications where the time or the temperature of the food needs to be modeled. In general, when a food is brought from room temperature to temperatures below - 5 ∘ C , the temperature kinetics follow three different parts which include cooling from initial temperature to the initial freezing point, freezing from the freezing point to - 5 ∘ C in the center of the food, and cooling from - 5 ∘ C to the final temperature in the center of the food. The present customized procedure is mainly based upon established estimation procedures. Following the description of the methods, an example of the calculation for freezing hake (Merluccius merluccius) mince muscle is provided for each of the phases. The method consists in the following•Calculation of the pre freezing and sub freezing times with a similar procedure but separately since the sample has different thermo physical properties in each stage (cooling).