Flexible Procedure Research Articles

Impact of complex, partially nested clustering in a three-arm individually randomized group treatment trial: A case study with the wHOPE trial.

When participants in individually randomized group treatment trials are treated by multiple clinicians or in multiple group treatment sessions throughout the trial, this induces partially nested clusters which can affect the power of a trial. We investigate this issue in the Whole Health Options and Pain Education trial, a three-arm pragmatic, individually randomized clinical trial. We evaluate whether partial clusters due to multiple visits delivered by different clinicians in the Whole Health Team arm and dynamic participant groups due to changing group leaders and/or participants across treatment sessions during treatment delivery in the Primary Care Group Education arm may impact the power of the trial. We also present a Bayesian approach to estimate the intraclass correlation coefficients. We present statistical models for each treatment arm of Whole Health Options and Pain Education trial in which power is estimated under different intraclass correlation coefficients and mapping matrices between participants and clinicians or treatment sessions. Power calculations are based on pairwise comparisons. In practice, sample size calculations depend on estimates of the intraclass correlation coefficients at the treatment sessions and clinician levels. To accommodate such complexities, we present a Bayesian framework for the estimation of intraclass correlation coefficients under different participant-to-session and participant-to-clinician mapping scenarios. We simulated continuous outcome data based on various clinical scenarios in Whole Health Options and Pain Education trial using a range of intraclass correlation coefficients and mapping matrices and used Gibbs samplers with conjugate priors to obtain posteriors of the intraclass correlation coefficients under those different scenarios. Posterior means and medians and their biases are calculated for the intraclass correlation coefficients to evaluate the operating characteristics of the Bayesian intraclass correlation coefficient estimators. Power for Whole Health Team versus Primary Care Group Education is sensitive to the intraclass correlation coefficient in the Whole Health Team arm. In these two arms, an increased number of clinicians, more evenly distributed workload of clinicians, or more homogeneous treatment group sizes leads to increased power. Our simulation study for the intraclass correlation coefficient estimation indicates that the posterior mean intraclass correlation coefficient estimator has less bias when the true intraclass correlation coefficients are large (i.e. 0.10), but when the intraclass correlation coefficient is small (i.e. 0.01), the posterior median intraclass correlation coefficient estimator is less biased. Knowledge of intraclass correlation coefficients and the structure of clustering are critical to the design of individually randomized group treatment trials with partially nested clusters. We demonstrate that the intraclass correlation coefficient of the Whole Health Team arm can affect power in the Whole Health Options and Pain Education trial. A Bayesian approach provides a flexible procedure for estimating the intraclass correlation coefficients under complex scenarios. More work is needed to educate the research community about the individually randomized group treatment design and encourage publication of intraclass correlation coefficients to help inform future trial designs.

The properties of hot household hygroscopic materials and their potential use for non-medical facemask decontamination.

The widespread use of facemasks throughout the population is recommended by the WHO to reduce transmission of the SARS-CoV-2 virus. As some regions of the world are facing mask shortages, reuse may be necessary. However, used masks are considered as a potential hazard that may spread and transmit disease if they are not decontaminated correctly and systematically before reuse. As a result, the inappropriate decontamination practices that are commonly witnessed in the general public are challenging management of the epidemic at a large scale. To achieve public acceptance and implementation, decontamination procedures need to be low-cost and simple. We propose the use of hot hygroscopic materials to decontaminate non-medical facemasks in household settings. We report on the inactivation of a viral load on a facial mask exposed to hot hygroscopic materials for 15 minutes. As opposed to recent academic studies whereby decontamination is achieved by maintaining heat and humidity above a given value, a more flexible procedure is proposed here using a slow decaying pattern, which is both effective and easier to implement, suggesting straightforward public deployment and hence reliable implementation by the population.

COVID-19: Estimation of the transmission dynamics in Spain using a stochastic simulator and black-box optimization techniques

Background and objectives: Epidemiological models of epidemic spread are an essential tool for optimizing decision-making. The current literature is very extensive and covers a wide variety of deterministic and stochastic models. However, with the increase in computing resources, new, more general, and flexible procedures based on simulation models can assess the effectiveness of measures and quantify the current state of the epidemic. This paper illustrates the potential of this approach to build a new dynamic probabilistic model to estimate the prevalence of SARS-CoV-2 infections in different compartments.Methods: We propose a new probabilistic model in which, for the first time in the epidemic literature, parameter learning is carried out using gradient-free stochastic black-box optimization techniques simulating multiple trajectories of the infection dynamics in a general way, solving an inverse problem that is defined employing the daily information from mortality records.Results: After the application of the new proposal in Spain in the first and successive waves, the result of the model confirms the accuracy to estimate the seroprevalence and allows us to know the real dynamics of the pandemic a posteriori to assess the impact of epidemiological measures by the Spanish government and to plan more efficiently the subsequent decisions with the prior knowledge obtained.Conclusions:The model results allow us to estimate the daily patterns of COVID-19 infections in Spain retrospectively and examine the population’s exposure to the virus dynamically in contrast to seroprevalence surveys. Furthermore, given the flexibility of our simulation framework, we can model situations —even using non-parametric distributions between the different compartments in the model— that other models in the existing literature cannot. Our general optimization strategy remains valid in these cases, and we can easily create other non-standard simulation epidemic models that incorporate more complex and dynamic structures.

Accelerated Development of COVID-19 Vaccines: Technology Platforms, Benefits, and Associated Risks.

Multiple preventive COVID-19 vaccines have been developed during the ongoing SARS coronavirus (CoV) 2 pandemic, utilizing a variety of technology platforms, which have different properties, advantages, and disadvantages. The acceleration in vaccine development required to combat the current pandemic is not at the expense of the necessary regulatory requirements, including robust and comprehensive data collection along with clinical product safety and efficacy evaluation. Due to the previous development of vaccine candidates against the related highly pathogenic coronaviruses SARS-CoV and MERS-CoV, the antigen that elicits immune protection is known: the surface spike protein of SARS-CoV-2 or specific domains encoded in that protein, e.g., the receptor binding domain. From a scientific point of view and in accordance with legal frameworks and regulatory practices, for the approval of a clinic trial, the Paul-Ehrlich-Institut requires preclinical testing of vaccine candidates, including general pharmacology and toxicology as well as immunogenicity. For COVID-19 vaccine candidates, based on existing platform technologies with a sufficiently broad data base, pharmacological–toxicological testing in the case of repeated administration, quantifying systemic distribution, and proof of vaccination protection in animal models can be carried out in parallel to phase 1 or 1/2 clinical trials. To reduce the theoretical risk of an increased respiratory illness through infection-enhancing antibodies or as a result of Th2 polarization and altered cytokine profiles of the immune response following vaccination, which are of specific concern for COVID-19 vaccines, appropriate investigative testing is imperative. In general, phase 1 (vaccine safety) and 2 (dose finding, vaccination schedule) clinical trials can be combined, and combined phase 2/3 trials are recommended to determine safety and efficacy. By applying these fundamental requirements not only for the approval and analysis of clinical trials but also for the regulatory evaluation during the assessment of marketing authorization applications, several efficacious and safe COVID-19 vaccines have been licensed in the EU by unprecedentedly fast and flexible procedures. Procedural and regulatory–scientific aspects of the COVID-19 licensing processes are described in this review.

MO885APP BASED DOCUMENTATION AND SUPPORT OF A GERMAN HOME DIALYSIS PROGRAMM - A PILOT STUDY

Abstract Background and Aims Telemedicine is advancing. However, studies that examine the integration into home dialysis care are still scarce. This multicenter, Germany-wide prospective observational pilot-study investigated the effects, acceptance and usability of an app as a new care concept compared to conventionally cared-for patients. Method Here, we employed the “DiaApp”, a tablet based documentation, communication, information and supply ordering system developed by the PHV – a non-profit dialysis network in Germany with around 7,000 patients. During a pilot rollout phase of the app between 2018 and 2019, 25 patients participated in four dialysis practices. Participants were free to choose between app use (app) and the previous paper-based documentation (control). We collected prospective data on demographics, adverse events as well as questionnaires regarding quality of life (KDQL v1.3), affinity for technology (TA-EG), satisfaction with the app (UTAUT), and self-confidence in dealing with chronic illness (SES6G). Furthermore, 5 app users were interviewed in a qualitative interview over 90 min about their attitude towards technology, illness and the app. Results Of the 25 participants, 13 used the app (52%). App users tended to be younger, more likely to be male (60.0%) and on peritoneal dialysis (n=15, 60.0%). Median age and dialysis vintage for app users and controls were 51 (38-60; 0) vs. 59 (37-64; 1) years and 51.5 (34-68; 3) vs. 38 (28-66; 5) months, respectively. Mean follow-up durations were 6.5 months and 12 months. All participants continued to use the app. One exit site infection (app), 3 hospitalizations (peritonitis and shunt revision, controls; inguinal hernia, app) and no serious app-related adverse event occurred. App users exhibited small trends (n.s.) towards lower quality of life (median SF-12 physical composite app: 43, IQR 40-48 controls: 47, IQR 38-50; SF-12 mental composite median app: 53, IQR 35-55; controls: 56, IQR 42-59;) greater self-confidence in managing chronic illness (SESG6 Score app: 7.33, IQR: 6-8.83; controls:7.17, IQR 6-7.83) and higher affinity for technology (in all four TA-EG dimensions). App users were more likely to have completed a master’s degree, while non-users mostly had a bachelor's degrees (Chi-square 14.183, df 6, p=0.028). Overall, the educational level of participants was high. There was a tendency (n.s.) for actual app users to have slightly lower performance expectations (median control arm 5.5 vs. app arm 5.88 on a Likert scale 1-7), a slightly higher assessment of their own and other available resources (supportive conditions median control arm 6 vs. app arm 6.67 on a Likert scale 1-7). In the qualitative interviews, all app users surveyed stated that they regularly used digital offerings in all areas of their lives. Therefore, expectations were similar to other apps to be more efficient in terms of time, material and effort than paper-based documentation. The attitude towards the app was that towards an auxiliary tool, “it should simply work”, and found it to be useful. Patients disliked the necessity of a dedicated (in this case a tablet) device for running the app. Information about the disease was more likely to be outside of the app in e.g. the internet. Conclusion In this study, we found no significant differences between app users and controls. No adverse events occurred. Via trends and interviews, the picture emerges that an upcoming, younger generation of dialysis patients appreciates the advantages of flexible home dialysis procedures and, as in other areas of life, expects simple, digital and thus resource-saving options for self-management and communication. At the same time, such applications are also subject to the expectations of digital user experiences from other areas of life. This poses enormous challenges for the often-costly development of such applications by non-commercial providers and limited number of target audiences.

Evaluation of sample treatments in a safe and straightforward procedure for the detection of SARS-CoV-2 in saliva

ObjectivesTo evaluate four sample treatments in a safe and straightforward procedure to detect SARS-CoV-2 in saliva. MethodsFour sample treatments were evaluated in a 3-step procedure to detect SARS-CoV-2 in saliva: 1) heating at 95 °C for 5 min for sample inactivation; 2) sample treatment; 3) analysis by reverse-transcription loop-mediated isothermal amplification (LAMP). Saliva samples used were from infected individuals or were spiked with known quantities of viral particles. ResultsThree treatments had a limit of detection (LOD) of 500.000 viral particles per ml of saliva and could be used to detect individuals with potential to transmit the disease. The treatment of phosphate buffer, dithiothreitol, ethylenediaminetetraacetic acid and proteinase K, with an additional 95 °C heating step, yielded a lower LOD of 95; its sensitivity ranged from 100% in patients with nasopharyngeal swab reverse-transcriptase polymerase chain reaction cycle threshold values <20 to 47.8% for values >30. ConclusionsThis report highlights the importance of an adequate sample treatment for saliva to detect SARS-CoV-2 and describes a flexible procedure that can be adapted to point-of-care. Although its sensitivity when LAMP is used is lower than reverse-transcriptase polymerase chain reaction, this procedure can contribute to COVID-19 control by detecting individuals able to transmit the disease.

The multi-fuzzy N-soft set and its applications to decision-making

The goal of this paper is to introduce a novel hybrid model called multi-fuzzy N-soft set, and to design an adjustable decision-making methodology for solving problems where the inputs appear in this form. The new model enhances the virtues of multi-fuzzy set theory with the benefits of N-soft sets, two models that have been extensively investigated in recent years. The theoretical setting that arises allows us to incorporate data on the occurrence of ratings or grades (the defining characteristic of N-soft sets) in a multi-fuzzy environment. We perform a set-theoretical analysis of multi-fuzzy N-soft sets in order to establish the fundamental properties of their behavior. Then we develop a highly adaptable approach to decision-making in this new setting. This methodology takes advantage of a flexible procedure for the conversion of the original data to a hesitant N-soft setting, where we can resort to scores. Examples illustrate its application and the role of each parameter in the decision-making procedure.

Beyond Confinement: Cape Gangsters and the Sub-Saharan Trade of Stolen Electronics

ABSTRACT Instead of being perceived as confined to oppressive spaces in South Africa, detached from mainstream society, in this article I show that gangsters in Cape Town have harnessed liberalisation since the 1990s to become players in the market economy. This is illustrated by means of two criminal practices that support the illicit trade in electronics: residential burgling and transnational smuggling. By tracing the circulation of stolen electronics, gangsters and their migrant collaborators are shown to use flexible procedures to prevent detection and custody. These procedures capitalise on the changes brought by liberalisation, allowing for the efficient flow of electronics consignments to distant African cities and villages. It is argued that thinking through these procedures allows for a nuanced understanding of contemporary gang dynamics beyond confinement.

Introducing the index-based ecological condition assessment framework (IBECA)

Sustainable nature management and ecosystem conservation depends critically on scientifically sound and stakeholder-relevant analytical frameworks for monitoring and assessing ecological condition. Several general frameworks are currently being developed internationally, including the Essential Biodiversity Variables (EBV), and the UN’s SEEA EEA Ecosystem Condition Typology (ECT). However, there has so far been few attempts to develop empirical implementations of these general frameworks, or to assess their applicability for environmental decision-making at national or regional scales. In this paper, we aim to fill this implementation gap by demonstrating a practical application of an empirically-based ecological condition assessment framework, the Index-Based Ecological Condition Assessment (IBECA). IBECA defines seven major classes of indicators of ecological condition, representing distinct ecosystem characteristics, and empirically synthesizes indicators for each of these characteristics from various monitoring data. We exemplify and explore the utility and robustness of IBECA using a case study from forest and alpine ecosystems in central Norway, and we investigate how IBECA aligns with the two international frameworks EBV and ECT. In particular, we analyze how the different approaches to categorize indicators into classes affect the assessment of ecological condition, both conceptually and using the case study indicators. We used eleven indicators for each of the two ecosystems and assessed the ecological condition according to IBECA for i) each individual indicator, ii) the seven ecosystem characteristics (indicator classes), and iii) a synthetic ecological condition value for the whole ecosystem. IBECA challenges key concepts of the international frameworks and illustrates practical challenges for national or regional level implementation. We identify three main strengths with the IBECA approach: i) it provides a transparent and management-relevant quantitative approach allowing assessment of spatio-temporal variation in ecological condition across indicators, characteristics and ecosystems, ii) the high degree of flexibility and transparency facilitates updating the ecological condition assessments, also back in time, as improved data and knowledge of indicators emerge, and iii) the quantitative and flexible procedure makes it a cost-effective approach suitable for fast management implementations. More generally, we stress the need for carefully choosing appropriate classification and aggregation approaches in ecological condition assessments, and for transparent and data-driven analytical approaches that can be adjusted as knowledge improves.

Mind the gap: Examining work-as-imagined and work-as-done when dispensing medication in the community pharmacy setting

Reducing errors within a healthcare setting remains high on the patient safety research agenda. More consistent performance has been sought by increased development of standardised operating procedures, but they are not always adhered to in practice. Previous studies have identified that a difference exists between the way a task is imagined to be completed, based on standardised protocols and procedures, and how the task is actually completed in reality. This study explores one area of healthcare, community pharmacy, and more specifically the task of dispensing medicines from prescriptions, to identify the gap between how dispensing is imagined to be completed through standardised operating procedures, and how it is actually completed in practice, by using Hierarchical Task Analysis as a framework. Document analysis of standardised operating procedures in 3 community pharmacies was used to produce 3 task analyses, which were compared with 3 task analyses produced from data collected through non-participant observations of the same 3 community pharmacies. Deviations between the two forms of task analyses were presented to community pharmacists in focus group discussions and it was found staff may deviate from standardised protocols because of various reasons, including: efficiency; availability of resources; thoroughness; and delegating safeguards. Potential implications for the work system include the benefit of greater collaboration between procedure writers and frontline workers, and the introduction of more flexible procedures, that allow the risks of any adaptions to be clearly realised. Further work must establish whether pharmacists recognise the safety implications of these gaps between work as imagined, and work as done, and initiatives should be established to ensure patient safety is not compromised due to these differences.

Species versus within-species niches: a multi-modelling approach to assess range size of a spring-dwelling amphibian

Species Distribution Models (SDMs) can be used to estimate potential geographic ranges and derive indices to assess species conservation status. However, habitat-specialist species require fine-scale range estimates that reflect resource dependency. Furthermore, local adaptation of intraspecific lineages to distinct environmental conditions across ranges have frequently been neglected in SDMs. Here, we propose a multi-stage SDM approach to estimate the distributional range and potential area of occupancy (pAOO) of Neurergus kaiseri, a spring-dwelling amphibian with two climatically-divergent evolutionary lineages. We integrate both broad-scale climatic variables and fine-resolution environmental data to predict the species distribution while examining the performance of lineage-level versus species-level modelling on the estimated pAOO. Predictions of habitat suitability at the landscape scale differed considerably between evolutionary level models. At the landscape scale, spatial predictions derived from lineage-level models showed low overlap and recognised a larger amount of suitable habitats than species-level model. The variable dependency of lineages was different at the landscape scale, but similar at the local scale. Our results highlight the importance of considering fine-scale resolution approaches, as well as intraspecific genetic structure of taxa to estimate pAOO. The flexible procedure presented here can be used as a guideline for estimating pAOO of other similar species.

Incorporating Virtual Reality Technology in Safety Training Solution for Construction Site of Urban Cities

The lack of experiential training has become the primary cause of incidents that could have been easily avoided in construction areas, and the implementation of experimental training is crucial in minimizing incidents at construction sites. The limitation on the available training tools has made it impossible to build up a real test site or reproduce the constructing scenarios. This research aims to develop an immersive and interactive multiplayer-based training platform that incorporates virtual reality (VR) technology to improve the safety awareness of workers. The developed simulation platform serves as a training solution, enabling the provision of repeatable and flexible procedures within a secure environment. An evaluation survey was conducted to make a comparison between traditional training methods and the proposed VR solution. Promisingly, the results indicate that workers were better trained under the developed immersive environment, and they could memorize critical points more effectively because the implementation of VR technology can allow people to experience hazardous situations without being physically injured, thus creating a safer and more efficient training environment. This study reveals that the nomination of the proposed VR platform could reap many benefits and become an advantageous tool for construction training, as well as stimulate human-machine interaction research.

An alternative analysis of illicit opioid use during treatment in a randomized trial of extended-release naltrexone versus buprenorphine-naloxone: A per-protocol and completers analysis

BackgroundThe distinct pharmacological properties and clinical uses of extended-release naltrexone (XR-NTX) and sublingual buprenorphine-naloxone (BUP-NX) present challenges in analyzing patient outcomes. MethodsWe conducted a secondary analysis of a multi-site randomized trial comparing XR-NTX with sublingual BUP-NX treatment for opioid use disorder initiated during inpatient detoxification and continued in outpatient treatment. Urine testing data for non-study opioids from the last 22 weeks of the 24-week trial were analyzed in both a per-protocol sample (n = 474 participants who received at least one dose of medication) and a completers sample (n = 211 participants who received all XR-NTX doses or all BUP-NX prescriptions). The present analyses sought to identify differences in the weekly percentages of opioid-positive urine tests between participants treated with the two medications. ResultsThe proportion of opioid-positive tests in both conditions was less than 20 % for 21 of the 22 weeks in the per-protocol sample and all 22 weeks in the completers sample. Generalized linear mixed model analyses revealed a significant treatment (XR-NTX vs. BUP-NX) X week (weeks 3–24) interaction in the per-protocol sample but not the completers sample. In the per-protocol analysis, the BUP-NX, compared to XR-NTX, had significantly greater proportions of opioid-positive tests in 14 out of the 22 weeks. ConclusionsLongitudinal modeling approaches that utilize flexible procedures for handling missing data can offer a different perspective on study findings. Results from the present analyses suggest that XR-NTX appeared to be somewhat more effective than BUP-NX in reducing illicit opioid use in the per-protocol sample.

A Gold(I)-Catalyzed Hydroamination/Cycloisomerization Cascade: Concise Synthesis of (±)-seco-Antofine and (±)-Septicine.

A concise and flexible procedure for the synthesis of highly functionalized N-heterocyclic 1,6-annulated 2-pyridones and 2,3-annulated 4-pyrimidinones has been elaborated through a gold-catalyzed tandem hydroamination/cycloisomerization cascade. This novel and highly efficient method allows the rapid construction of these diverse N-heterocyclic scaffolds starting from readily available building blocks, and shows a wide scope and good functional group tolerance. The total synthesis of (±)-seco-antofine and (±)-septicine were realized employing this strategy.

Enhancing Streamflow Forecast and Extracting Insights Using Long‐Short Term Memory Networks With Data Integration at Continental Scales

AbstractRecent observations with varied schedules and types (moving average, snapshot, or regularly spaced) can help to improve streamflow forecasts, but it is challenging to integrate them effectively. Based on a long short‐term memory (LSTM) streamflow model, we tested multiple versions of a flexible procedure we call data integration (DI) to leverage recent discharge measurements to improve forecasts. DI accepts lagged inputs either directly or through a convolutional neural network unit. DI ubiquitously elevated streamflow forecast performance to unseen levels, reaching a record continental‐scale median Nash‐Sutcliffe Efficiency coefficient value of 0.86. Integrating moving‐average discharge, discharge from the last few days, or even average discharge from the previous calendar month could all improve daily forecasts. Directly using lagged observations as inputs was comparable in performance to using the convolutional neural network unit. Importantly, we obtained valuable insights regarding hydrologic processes impacting LSTM and DI performance. Before applying DI, the base LSTM model worked well in mountainous or snow‐dominated regions, but less well in regions with low discharge volumes (due to either low precipitation or high precipitation‐energy synchronicity) and large interannual storage variability. DI was most beneficial in regions with high flow autocorrelation: it greatly reduced baseflow bias in groundwater‐dominated western basins and also improved peak prediction for basins with dynamical surface water storage, such as the Prairie Potholes or Great Lakes regions. However, even DI cannot elevate performance in high‐aridity basins with 1‐day flash peaks. Despite this limitation, there is much promise for a deep‐learning‐based forecast paradigm due to its performance, automation, efficiency, and flexibility.

Affordability of in vivo gene therapy. Problems and potential solutions

Aim. To review foreign approaches to the evaluation and financing of in vivo gene therapy drugs. Materials and Methods. The first stage of the review included the systematic search for publications of clinical-economic studies (CES) on in vivo gene therapy drugs registered on the international pharmaceutical market. The analysis of the methodology used in the found CESs was performed based on the given criteria. The second and third stages of the review included the search for the information on the approaches and results of the evaluation of in vivo gene therapy drugs by foreign agencies on the assessment of healthcare technologies (AHT) and the implemented approaches to the financing of expensive medical technologies. Results. Totally, four in vivo gene therapy drugs registered on the foreign markets were found: talimogene laherparepvec (Imlygic), voretigene neparvovec (Luxturna), onasemnogene abeparvovec (Zolgensma), and alipogene tiparvove (Glybera). The analysis of the methodology of CES on in vivo gene therapy drugs did not reveal general methodological peculiarities. The analysis of the approaches to the reimbursement for the cost of these four drugs in the European countries showed that there were no special procedures intended for gene drugs. However, in the majority of countries, there are some mechanisms of reimbursement for orphan drugs and the majority of the above-mentioned in vivo gene therapy drugs are orphan. It was revealed that the most perspective methods of payment for in vivo gene therapy drugs were installment payments, risk-sharing agreements, and their combinations. Still, none of these payment methods are implemented in Russia because of the lack of regulatory and legal framework. Conclusion. The design and methodological peculiarities of CES on in vivo gene therapy drugs are similar to orphan drugs (in some countries, there is a special flexible procedure). In the Russian Federation, there is no special procedure of ATH for orphan drugs, which can provide difficulties in the reimbursement for these drugs. Besides, in the Russian Federation, the issue of the implementation of innovative models for drugs provision (risk-sharing, installment payments is acute). The changes in this area would also lead to the optimization of the influence of expensive healthcare technologies on the budget of the system of healthcare.

An efficient algorithm of solution for the flow of generalized Newtonian fluid in channels of simple geometries

In this paper a problem of stationary flow of generalized Newtonian fluid in a thin channel is considered. An efficient algorithm of solution is proposed that includes a flexible procedure for a continuous approximation of the apparent viscosity by means of elementary functions combined with analytical integration of the governing equations. The algorithm can be easily adapted to circular or elliptic conduits. The accuracy and efficiency of computations are analyzed using an example of the Carreau fluid. The proposed computational scheme proves to be highly efficient and versatile providing excellent accuracy of solution at a very low computational cost.

Dynamic Network Prediction.

We present a statistical framework for generating predicted dynamic networks based on the observed evolution of social relationships in a population. The framework includes a novel and flexible procedure to sample dynamic networks given a probability distribution on evolving network properties; it permits the use of a broad class of approaches to model trends, seasonal variability, uncertainty, and changes in population composition. Current methods do not account for the variability in the observed historical networks when predicting the network structure; the proposed method provides a principled approach to incorporate uncertainty in prediction. This advance aids in the designing of network-based interventions, as development of such interventions often requires prediction of the network structure in the presence and absence of the intervention. Two simulation studies are conducted to demonstrate the usefulness of generating predicted networks when designing network-based interventions. The framework is also illustrated by investigating results of potential interventions on bill passage rates using a dynamic network that represents the sponsor/co-sponsor relationships among senators derived from bills introduced in the US Senate from 2003-2016.

A Study of Localization of Task-Based Language Teaching in China

Abstract In view of a series of challenges since Task-Based Language Teaching (TBLT) was introduced into China, we interviewed 14 front-line teachers in primary and secondary schools about their viewpoints and classroom strategies of TBLT. The results show teachers’ willingness to use TBLT. They adopt flexible teaching procedures, apply TBLT creatively, and explore task-based language assessment. The authors argue for inclusive non-doctrinaire approaches to TBLT, and propose to construct localized TBLT theory and practice with Chinese characteristics.

Feasibility Study on Measuring the Particulate Matter Level in the Atmosphere by Means of Yagi-Uda-Like Antennas.

In this work, the application of a technique for monitoring changes of the dielectric constant of the atmosphere caused by the presence of pollution is discussed. The method is based on changes in the reflection coefficient of the device induced by these dielectric constant variations of the surrounding medium. To that end, several Yagi–Uda-like antenna designs with different size limitations were simulated by using a Method-of-Moments software and optimized by means of a simulated annealing strategy. It has been found that the larger the optimal elements of the array are allowed to be, the higher the sensitivity reached. Thus, in a trade-off between sensitivity and moderate length (regarding flexibility purposes), the most promising solution has been built. This prototype has been experimentally tested in presence of an artificial aerosol made of PAO (polyalphaolefin) oil and black carbon inclusions of a size of 0.2 μm. As a result, potentials for developing a measurement procedure by means of changes in the characteristic parameters of the antenna led by different concentration levels of suspended particles in the surrounding medium are shown. In this manner, a local mapping of polluted levels could be developed in an easy, real-time, and flexible procedure.