Synthesis of precision dosing system for liquid products based on electropneumatic complexes

This paper reports the construction of a mathematical model for the process of dosing liquid foods (non-carbonated drinking water). The model takes into consideration the differential equations of changes in the kinematic parameters of the liquid in a dosing device's channels and the corresponding accepted initial and boundary conditions of the process. The boundary conditions account for the influence of software-defined airlift dosing modes using the driver and the geometry of the product pipeline. The current's value measured in mA (with an accuracy of 0.001 mA) relative to the standard scale Imin is Imax=4...20 mA. Individual stages of the dosing process were analytically described, followed by the analysis of separate stages and accepted assumptions. The accuracy achieved when testing the experimental sample of the dispenser, with the repetition of the dose displacement process, ranged between 0.35 % and 0.8 %. The reported results are related to the established dosage weight of 50 ml when changing the initial level of liquid in the tank of the dosing feeder by 10 mm. An experimental bench has been proposed for investigating the functional mechatronic dosing module under the software-defined modes to form and discharge a dose of the product. The bench operates based on proportional feedback elements (4–20 mA) for step and sinusoidal pressure control laws in the dosing device. The control model with working dosing modes has been substantiated. The control models built are based on proportional elements and feedback. During the physical and mathematical modeling, the influence of individual parameters on the accuracy of the product dose formation was determined; ways to ensure the necessary distribution of compressed air pressure, subject to the specified productivity of the dosing feeder, were defined. The study results make it possible to improve the operation of precision dosing systems for liquid products based on electro-pneumatic complexes

How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observing system simulation experiments with the GEOS-Chem adjoint model (v35)

We perform observing system simulation experiments (OSSEs) with the GEOS-Chem adjoint model to test how well methane emissions over North America can be resolved using measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and similar high-resolution satellite sensors. We focus analysis on the impacts of (i) spatial errors in the prior emissions and (ii) model transport errors. Along with a standard scale factor (SF) optimization we conduct a set of inversions using alternative formalisms that aim to overcome limitations in the SF-based approach that arise for missing sources. We show that 4D-Var analysis of the TROPOMI data can improve monthly emission estimates at 25 km even with a spatially biased prior or model transport errors (42 %–93 % domain-wide bias reduction; R increases from 0.51 up to 0.73). However, when both errors are present, no single inversion framework can successfully improve both the overall bias and spatial distribution of fluxes relative to the prior on the 25 km model grid. In that case, the ensemble-mean optimized fluxes have a domain-wide bias of 77 Gg d−1 (comparable to that in the prior), with spurious source adjustments compensating for the transport errors. Increasing observational coverage through longer-timeframe inversions does not significantly change this picture. An inversion formalism that optimizes emission enhancements rather than scale factors exhibits the best performance for identifying missing sources, while an approach combining a uniform background emission with the prior inventory yields the best performance in terms of overall spatial fidelity – even in the presence of model transport errors. However, the standard SF optimization outperforms both of these for the magnitude of the domain-wide flux. For the common scenario in which prior errors are non-random, approximate posterior error reduction calculations (derived via gradient-based randomization) for the inversions reflect the sensitivity to observations but have no spatial correlation with the actual emission improvements. This demonstrates that such information content analysis can be used for general observing system characterization but does not describe the spatial accuracy of the posterior emissions or of the actual emission improvements. Findings here highlight the need for careful evaluation of potential missing sources in prior emission datasets and for robust accounting of model transport errors in inverse analyses of the methane budget.

Evaluation of Physical Education Teaching Based on Analytic Hierarchy Process

The evaluation of physical education (PE) teaching plays an important role in improving the teaching quality and students’ physical fitness. Taking five colleges in a Chinese province for example, this paper surveys the status quo of college PE teaching evaluation, and reveals several problems with the evaluation: the evaluation index system (EIS) is incomplete, and the subjects are not diverse. Based on the survey results and previous findings, questionnaire survey, the Delphi method, analytic hierarchy process (AHP), logic analysis, and mathematical statistics were combined to construct an EIS for college PE teaching evaluation, determine the weights of indices on each level, design a standard scale, and develop the evaluation framework and flow. The research results promote the development of college PE teaching, and provide a reference for reforming the teaching evaluation of other disciplines.

E-learning adoption by undergraduate architecture students: facilitators and inhibitors

PurposeThis study identifies the facilitators and inhibitors for the adoption of e-learning for the undergraduate students of architecture. Nine constructs are identified as facilitators and five constructs are identified as inhibitors to the adoption of online learning systems in the context of the study. These constructs were used to propose a research model.Design/methodology/approach596 architecture undergraduates responded to a structured questionnaire. The questionnaire was finalized after a pilot study and included standard scale items drawn from previous studies. An exploratory factor analysis was followed by structural equation modeling (SEM) to test the proposed model.FindingsAll the identified facilitators emerged significant except social influence and price value. Furthermore, technology risk emerged insignificant while all other inhibitors had significant impact on Behavioral Intention to adopt e-learning.Research limitations/implicationsThe study has strong implications in academia as HEIs in developing countries need to make their students computer proficient, boost the implications of e-learning services by mitigating risks and motivating students to acquire knowledge through flexible e-learning modules.Originality/valueThe COVID-19 pandemic forced educational institutions to switch to online modes of learning. For students of architectural programs in a developing country like India, this has been unprecedented and has brought in a new set of challenges and opportunities. With the extension of the pandemic induced lockdown in educational institutions, students – and other stakeholders – have no choice but to adapt to this new normal of dependence on remote learning.

Measuring the motivation to avoid duping: scale development and validation

Purpose This paper aims to develop and validate a psychometrically sound scale measuring buyers’ motivation to avoid being duped (MAD) in a marketplace transaction. Design/methodology/approach Standard scale construction methodology was followed in developing the MAD Scale. Eight studies were conducted. Findings Three underlying MAD factors were discovered: suspicion of sellers, anticipated aversive emotions and deception detection. For purposes of analyses, data were collapsed across factors. High MAD individuals exhibited more vigilance in decision-making, were less trusting of strangers and displayed a greater desire to appear perfect to others. Those high in MAD were also more apt to have a prevention regulatory focus. Test-retest reliability was satisfactory, and no social desirability bias was observed. Finally, in an economic game with real financial consequences, those higher (vs lower) in MAD invested less after being duped, thus supporting criterion validity. Originality/value Marketplace deception has been identified as an existential threat facing consumers. Yet, few studies have examined how consumers cope with this threat. There currently exists no scales to measure consumer motivation to avoid being duped. The current research defines MAD and differentiates it from related constructs. The MAD scale will be useful in a variety of research contexts related to marketplace deception.

Service-Learning in Audiology: A Systematic Review

Purpose Service-learning has the potential to improve student outcomes by providing students opportunities to apply their knowledge and skills in real-world contexts and is well suited to graduate education in communication sciences and disorders. However, relatively few service-learning studies in the literature focus on audiology, and the range of outcomes specific to audiology service-learning has not yet been characterized in a systematic way. The purpose of this critical review was to characterize the impact of service-learning on audiology students and clients/patients as evidenced by reflection activities and outcome measures, as well as to describe the common challenges and best practices in the available literature that may inform future research on service-learning in the field. Method A systematic search of the literature using multiple databases was completed according to standard guidelines. The impact of each study was evaluated using a standard scale of training efficacy. Study methods, including reflection activities and outcome measures, were recorded. Results Nine peer-reviewed studies on service-learning in audiology were selected. Six of the nine studies reported changes in student attitudes or awareness related to issues of clinical practice; five of the nine studies reported improvements in student knowledge/skills. Conclusions Overall, results of the review indicated benefits of service-learning to student clinicians. However, evidence for transference of service-learning benefits to organizational or departmental practice and benefit to patients/clients was lacking. Methodological limitations in the measurement of outcomes in prior works complicated evaluation of their impact; best practices were identified and synthesized for use in future research on audiology service-learning experiences.

Coachability and the development of the coachability scale

PurposeThe purpose of this research was to develop a conceptualization and measure of workplace coachability.Design/methodology/approachUsing four independent samples of employed adults, we developed a short and long version of the Coachability Scale. We followed standard scale development practices, presenting evidence of the scales’ factor structure, reliability and validity.FindingsWith the first two samples, we derived an initial three-dimensional version of the Coachability Scale and provided evidence of convergent validity. With Samples 3 and 4, we expanded the scale with additional dimensions related to coaching feedback processes and accumulated additional evidence of the scale's validity, and provided evidence of convergence between the two versions of the Coachability Scale.Research limitations/implicationsWe encourage continued research on the Coachability Scale, as well as research on coachability in formal coaching relationships and with more diverse populations and cultures. It is also important to examine how coachability relates to specific coachee behaviors and outcomes. Although common method bias may be a limitation, we used temporally separated measurements to minimize method bias in Sample 4.Practical implicationsKnowledge about coachability can inform coaching practice decisions and help tailor the coaching engagement to better fit the coachee's needs.Social implicationsMeasuring how individuals respond to coaching and coaching relationships has important implications for managerial behavior and the quality of work life.Originality/valueThis is one of the first studies to develop valid scales for assessing workplace coachability.

An analysis of Bayesian estimates for missing higher orders in perturbative calculations

With current high precision collider data, the reliable estimation of theoretical uncertainties due to missing higher orders (MHOs) in perturbation theory has become a pressing issue for collider phenomenology. Traditionally, the size of the MHOs is estimated through scale variation, a simple but ad hoc method without probabilistic interpretation. Bayesian approaches provide a compelling alternative to estimate the size of the MHOs, but it is not clear how to interpret the perturbative scales, like the factorisation and renormalisation scales, in a Bayesian framework. Recently, it was proposed that the scales can be incorporated as hidden parameters into a Bayesian model. In this paper, we thoroughly scrutinise Bayesian approaches to MHO estimation and systematically study the performance of different models on an extensive set of high-order calculations. We extend the framework in two significant ways. First, we define a new model that allows for asymmetric probability distributions. Second, we introduce a prescription to incorporate information on perturbative scales without interpreting them as hidden model parameters. We clarify how the two scale prescriptions bias the result towards specific scale choice, and we discuss and compare different Bayesian MHO estimates among themselves and to the traditional scale variation approach. Finally, we provide a practical prescription of how existing perturbative results at the standard scale variation points can be converted to 68%/95% credibility intervals in the Bayesian approach using the new public code MiHO.

How well can inverse analyses of high-resolution satellite data resolve heterogeneous methane fluxes? Observation System Simulation Experiments with the GEOS-Chem adjoint model (v35)

We perform Observation System Simulation Experiments (OSSEs) with the GEOS-Chem adjoint model to test how well methane emissions over North America can be resolved using measurements from the TROPOspheric Monitoring Instrument (TROPOMI) and similar high-resolution satellite sensors. We focus analysis on the impacts of i) spatial errors in the prior emissions, and ii) model transport errors. Along with a standard scale-factor (SF) optimization we conduct a set of inversions using alternative formalisms that aim to overcome limitations in the SF-based approach that arise for missing sources. We show that 4D-Var analysis of the TROPOMI data can improve monthly emission estimates at 25 km even with a spatially biased prior or model transport errors (42–93 % domain-wide bias reduction; R increases from 0.51 up to 0.73). However, when both errors are present, no single inversion framework can successfully improve both the overall bias and spatial distribution of fluxes relative to the prior on the 25 km model grid. In that case, the ensemble-mean optimized fluxes have a domain-wide bias of 77 Gg/d (comparable to that in the prior), with spurious source adjustments compensating for the transport errors. Increasing observational coverage through longer-timeframe inversions does not significantly change this picture. An inversion formalism that optimizes emission enhancements rather than scale factors exhibits the best performance for identifying missing sources, while an approach combining a uniform background emission with the prior inventory yields the best performance in terms of overall spatial fidelity—even in the presence of model transport errors. However, the standard SF optimization outperforms both of these for the magnitude of the domain-wide flux. For the common scenario in which prior errors are non-random, approximate posterior error reduction calculations for the inversions reflect the sensitivity to observations but have no spatial correlation with the actual emission improvements. This demonstrates that such information content analysis can be used for general observing system characterization but does not describe the spatial accuracy of the posterior emissions or of the actual emission improvements. Findings here highlight the need for careful evaluation of potential missing sources in prior emission datasets and for robust accounting of model transport errors in inverse analyses of the methane budget.

Depression in the Iranian Elderly: A Systematic Review and Meta-Analysis

Depression can lead to increased medical costs, impaired individual and social functioning, nonadherence to therapeutic proceeding, and even suicide and ultimately affect quality of life. It is important to know the extent of its prevalence for successful planning in this regard. This study was conducted to determine the prevalence of depression in the Iranian elderly. This systematic review and meta-analysis study was done through Medline via PubMed, SCOPUS, Web of Science, ProQuest, SID, Embase, and Magiran with determined keywords. Screening was done on the basis of relevance to the purpose of the study, titles, abstracts, full text, and inclusion and exclusion criteria. The quality of the articles was assessed using the Newcastle-Ottawa standard scale. After primary and secondary screening, 30 articles were finally included in the study. According to the 30 articles reviewed, the prevalence of depression in the Iranian elderly was 52 percent based on the random-effects model (CI 95%: 46–58). According to the results of the present study, depression in the Iranian elderly was moderate to high. Therefore, more exact assessment in terms of depression screening in elderly people seems necessary. Coherent and systematic programs, including psychosocial empowerment counselling for the elderly and workshops for their families, are also needed. Researchers can also use the results of this study for future research.