Separate Programs Research Articles

Influence of Diesel Fuel Ignition Portion Value on Working Process Parameters of Gas-Diesel Engine

More and more requirements are imposed to engines of internal combustion due to the passage of time. These requirements are caused by the necessity to save fuel, to reduce emissions of pollutants into the atmosphere, to improve operational reliability, to reduce size and cost of spent materials, weight, noise level, to simplify manufacturing and operational processes. Use of gas as a fuel in the cities where number of engines is extremely large can significantly reduce environmental pollution. Some countries have separate environmental programs that encourage transfer of engines from gasoline to gas. At present, however, the use of gas engines in road transport is limited due to a number of technical and operational problems. Mathematical calculations and simulations are applied in order to solve this task and prevent possible problems in a manufactured. As part of the research to establish an influence of the diesel fuel ignition portion value in a gas-diesel engine on parameters of its operational process, it is necessary to develop an appropriate calculation method. In this regard, an analysis of methods and programs for calculation of the operational engine process has been carried out, and a method for calculation of an operational process for a gas-diesel engine has been developed in the paper. A computational study has been made in accordance with the developed methodology. The paper has revealed an influence of the diesel fuel ignition portion value on effective and environmental performance of an engine operation. The calculation has been performed for a nominal mode of the engine operation, gas fuel – propane-butane. Design parameters of a ГД-243-engine have been taken as initial data for the calculation. The following dependences have been established: as a diesel fuel ignition portion is increasing (replacement proportion of gas fuel with diesel), there is some decrease in engine power, and under the accepted conditions, there is an increase in CO2 with a decrease in CO and NO.

KVp, mA, and voxel size effect on 3D voxel-based superimposition.

To evaluate the effect of changing kVp, mA, and voxel size on the accuracy of voxel-based superimposition on the anterior cranial base. Cone beam computed tomography (CBCT) scans were taken on a phantom skull using different kVp, mA, and voxel size combinations. CBCT scans were superimposed using commercially available software. Two separate open-source software programs were used to generate a three-dimensional (3D) color map objective assessment of the differences in seven different regions: Nasion, Point A, Zygomatic (right and left), Point B, and Gonial (right and left). Each region had around 200 points that were used to calculate the mean differences between the superimpositions. Intraclass correlation showed excellent reliability (0.95). Lowering the kVp made the biggest difference, showing an average discrepancy of 0.7 ± 0.3 mm, and a high mean of 1.4 ± 0.3 in the Right Gonial region. Lowering the mA showed less of a discrepancy, with an average of 0.373 ± 0.2 mm, and the highest discrepancy, also on the Right Gonial Area, of 0.7 ± 0.1 mm. The voxel size had the least impact on the accuracy of registered volumes, with mean discrepancy values of less than 0.2 mm. Using different CBCT settings can affect the accuracy of the voxel-based superimposition method. This is particularly the case when using low kVp values, while changes in mA or voxel sizes did not significantly interfere with the superimposition outcome.

Households’ solid waste separation practices in the Cape Coast Metropolitan area, Ghana

This study sought to investigate household solid waste separation practices in the Cape Coast Metropolis, Ghana. Specifically, the study examined previous and existing solid waste separation practices, challenges associated with household separation of solid waste and willingness of households to separate waste. Employing a descriptive research design and a mixed-method approach, a multi-stage sampling method was used to obtain data from 215 household respondents and 7 keys informants. Data for the study were gathered through interview guide, questionnaires, and observation across low, middle and high-income communities over a period of 2 months from 6th June, 2016 to 8th August, 2016. The study found that most residents, regardless of their residential income zones, rarely separate their solid waste. However, there were general indications of residents’ willingness to separate waste at source, especially when there is demand and market for the separated waste. Major challenges that were identified to impede future solid waste separation among respondents include low demand for separated waste because there is no waste recycling plant in the metropolis as well as residents’ inability to afford waste separation bins. To promote and facilitate household solid waste separation programmes, the study recommends that the central government and Cape Coast Metropolitan Assembly (CCMA) in conjunction with their development partners should assist in the provision of waste separation bins. In addition, CCMA, within its entrusted authority, should promulgate and enforce by-laws to regulate the waste separation process.

Test-data generation directed by program path coverage through imperialist competitive algorithm

• This study applies an evolutionary algorithm (EA) called Imperialist Competitive Algorithm to generate test data guided by path coverage • In this study, mutation score is used to evaluate the generated test data • Considering being indeterministic of EA, statistical tests ANOVA and T-test are used to show general efficiency of proposed algorithm in test data generation Path coverage testing is an approach to ensure all paths of a program from starting node to terminal node are traversed at least once. Such testing considerably helps reveal program faults. However, disregarding iterated paths in loops, any module of a program with n decisions can have up to 2 n paths. Therefore, finding adequate test data to cover all or most of such paths throughout a program with numerous modules is an NP-Hard problem because it requires an exhaustive search among all possible data. Another concern is determining the efficiency and adequacy of test data according to the coverage criterion. For the path coverage criterion, a test data set is fully efficient if each item of the set covers a separate program path and is fully adequate if the test data cover all program paths. Providing such test data for a program is a very time-consuming action when the program has high complexity (i.e., many paths). A candidate solution for these problems is using Evolutionary Algorithms (EAs). We use an EA named the Imperialist Competitive Algorithm (ICA) to generate test data and assess its effectiveness based on both path coverage and discovered faults. The focus here is on the EA cost function , because it influences the generation of adequate test data. Considering the nondeterministic nature of the EAs in data reproduction, several experiments are carried out by applying statistical tests , ANOVA and T-test to indicate the significant difference between them in producing efficient test data.

Fast Numerical Powertrain Optimization Strategy for Connected Hybrid Electric Vehicles

Connected vehicle (CV) technology allows traffic information sharing that can be utilized to improve fuel benefits of hybrid electric vehicles (HEVs). However, there are challenges from the powertrain optimization perspective. First, optimizing powertrain operations is computational heavy due to the nonlinearities, constraints, and high dimensionality of the problem, especially with long optimization time horizon. Secondly, a slow powertrain optimization means the solution may not be optimal anymore at current time if the traffic states change. In this paper, a fast, near global-optimal, and practical HEV powertrain optimization utilizing vehicle speed prediction in CV environment is systematically formulated and solved. First, the minimum fuel rate and battery state-of-charge rate are calculated for different engine and battery power-split ratios. Then, the nonlinear minimum fuel rate and battery state-of-charge rate are piecewise-linearized by introducing dimensionless variables. The engine operating range, engine dynamics, and battery charge-sustaining constraint are represented by the dimensionless variables and treated as linear constraints. This transformation exploits the problem's structure, known as Separable Programming, which is solved efficiently as a large-dimension constrained linear problem. Fast optimization allows utilization of repeated speed predictions to maintain prediction accuracy. Results show comparable fuel economy with Dynamic Programming with significantly less computation time. Average fuel savings of 4.0% and 10.4% over Pontryagin's Minimum Principle and Rule-Based optimization methods are observed. Experimental results show the feasibility of the optimized engine operating points with fuel benefits over the rule-based method. Simulations with vehicle speed prediction and limited Gaussian uncertainties to emulate CV settings also show satisfactory fuel benefits.

Acute Neuromuscular and Endocrine Responses to Two Different Compound Exercises: Squat vs. Deadlift.

Barnes, MJ, Miller, A, Reeve, D, and Stewart, RJ. Acute neuromuscular and endocrine responses to two different compound exercises: squat vs. deadlift. J Strength Cond Res 33(9): 2381-2387, 2019-Anecdotally, it is believed that the deadlift exercise brings about greater levels of central fatigue than other exercises; however, no empirical evidence exists to support this view. In addition, little is known about the acute endocrine response to heavy deadlift exercise and how this may differ from other similar compound exercises. Therefore, the aim of this study was to identify and compare the acute, neuromuscular and endocrine responses to squat and deadlift exercises. Ten resistance-trained males completed 8 sets of 2 repetitions at 95% of 1 repetition maximum. Maximum voluntary isometric contraction (MVIC) force of the quadriceps, along with measures of central (voluntary activation [VA] and surface electromyography) and peripheral (electrically evoked control stimulus) fatigue were made before and 5 and 30 minutes after exercise. In addition, salivary testosterone and cortisol were measured at these same time points. MVIC was reduced after the completion of both exercises (p = 0.007); however, no difference between exercises was evident. Similarly, although VA changed over time (p = 0.0001), no difference was observed between exercises. As a measure of peripheral fatigue, force from the control stimulus changed over time (p = 0.003) with a greater decrease evident after the squat (p = 0.034). Electromyography was reduced over time (p = 0.048) but no difference was seen between exercises. No change was seen in testosterone and cortisol. Although a greater absolute load and larger volume load were completed for the deadlift, no difference in central fatigue was evident between the 2 compound exercises. The greater peripheral fatigue observed after squat exercise may be due to the greater work completed by the quadriceps with this exercise. These results suggest that separate periodization, tapering, and programming considerations may be unnecessary when using the squat and deadlift to develop muscular strength.

Efficient Secure Outsourcing of Large-Scale Convex Separable Programming for Big Data

Big data has become a key basis of innovation and intelligence, potentially making our lives more convenient and bringing new opportunities to the modern society. Towards this goal, a critical underlying task is to solve a series of large-scale fundamental problems. Conducting such large-scale data analytics in a timely manner requires a large amount of computing resources, which may not be available for individuals and small companies in practice. By outsourcing their computations to the cloud, clients can solve such problems in a cost-effective way. However, confidential data stored at the cloud is vulnerable to cyber attacks, and thus needs to be protected. Previous works employ cryptographic techniques like homomorphic encryption, which significantly increase the computational complexity of solving a large-scale problem at the cloud and is impractical for big data applications. For the first time in the literature, we present an efficient secure outsourcing scheme for convex separable programming problems (CSPs). In particular, we first develop efficient matrix and vector transformation schemes only based on arithmetic operations that are computationally indistinguishable both in value and in structure under a chosen-plaintext attack (CPA). Then, we design a secure outsourcing scheme in which the client and the cloud collaboratively solve the transformed problems. The client can efficiently verify the correctness of returned results to prevent any malicious behavior of the cloud. Theoretical correctness and privacy analysis together show that the proposed scheme obtains optimal results and that the cloud cannot learn private information from the client's concealed data. We conduct extensive simulations on Amazon Elastic Cloud Computing (EC2) platform and find that our proposed scheme provides significant time savings to the clients.

Generalized Peaceman–Rachford splitting method with substitution for convex programming

The generalized alternating direction method of multipliers (GADMM), which expands the dual step length to (0,2), is a benchmark for solving the two-block separable convex programming. Recently, there are many ADMM-based improved algorithms with indefinite term, that is, the second subproblem is linearized by a specialized indefinite matrix. In this paper, we propose a generalized proximal Peaceman–Rachford splitting method (abbreviated as GPRSM-S) with substitution step and indefinite term. We will find out the relationship between linearized parameter, dual step length and substitution factor. The global convergence and the worst-case convergence rate in nonergodic sense are established theoretically by variational inequality. Finally, some numerical results on LASSO and total variation based denoising problems are presented to verify the feasibility of the introduced method.

A separable augmented Lagrangian algorithm for optimal structural design

We propose an iterative separable augmented Lagrangian algorithm (SALA) for optimal structural design, with SALA being a subset of the alternating directions of multiplier method (ADMM)–type algorithms. Our algorithm solves a sequence of separable quadratic-like programs, able to capture reciprocal- and exponential-like behavior, which is desirable in structural optimization. A salient feature of the algorithm is that the primal and dual variable updates are all updated using closed-form expressions. Since algorithms in the ADMM class are known to be very sensitive to scaling, we propose a scaling method inspired by the well-known ALGENCAN algorithm. Comparative results for SALA, ALGENCAN, and the Galahad LSQP solver are presented for selected test problems. Finally, although we do not exploit this feature herein, the primal and dual updates are both embarrassingly parallel, which makes the algorithm suitable for implementation on massively parallel computational devices, including general purpose graphical processor units (GPGPUs).

Meteorological Temperature and Humidity Prediction from Fourier-Statistical Analysis of Hourly Data

The temperature readings for all the 365 days and the 24 hours may be fitted through a 3 × 3 matrix (the so-called T-matrix). The mean square deviation between this fit and the actual meteorological measurements is smaller than three degrees Celsius. Four entries of this (nonsymmetric) matrix may be fixed by other means, leaving only five independent components. However, the same method applied to the humidity measurements produces a larger mean square deviation. A strong stochastical connection is found between the T-temperature matrix and the U-humidity matrix. The computer program, in C, may be used to adjust a (2M + 1) × (2m + 1) matrix simply by changing the arguments at the command line and has been tested with m and M ranging from zero to 11 (eleven) (more than 24 readings per day are necessary for larger values of m). The physical meaning of these constants is given only in the case m = M = 1. Our results have also been connected to fundamental cosmological properties: Earth’s orbit, the ecliptic angle, and the latitude of Querétaro (or whatever geographical location is chosen). A separate program calculates the angular position of the Sun as measured in the sky of Querétaro, to determine the length of the day or the mean value of the solar cosine. This work introduces several new variables which happen to be stochastically connected.

Deconstructing residential immersive life skills programming through a pedagogical lens: mechanisms that can facilitate learning for youth with disabilities

Residential Immersive Life Skills (RILS) programs are unique programs for youth with disabilities. Situated, experiential, psychoeducational and strengths‐based learning approaches expose youth to opportunities and experiences that can facilitate the development of adaptive behaviours. This study examined the pedagogy of RILS programs to facilitate life skills development in youth. This study draws on 25 qualitative interviews that were conducted with nine youth who attended one of three separate RILS programs. Interviews were conducted at three different time points: pre‐program, 3 months post‐program and 12 months post‐program. Data were analysed using a constructivist grounded theory approach. The analysis provided evidence of the intended learning approaches that are mobilised in the RILS pedagogy (applied mechanisms): situated and experiential learning and psychoeducational and strengths‐based learning approaches. The transcripts also uncovered three behavioural and emotional elements in the RILS pedagogy (implicit mechanisms): the power of (1) interpersonal connections; (2) culture of collective understanding; and (3) emotional contagion. Findings validated evidence of applied mechanisms and uncovered the hidden behavioural and emotional mechanisms in the RILS pedagogy. This in‐depth insight is central to further developing not only independence‐oriented life skills programs, but also broader education programs for youth with disabilities.

Software and technical implementation of intelligent energy-saving control systems based on industrial controllers

Automation and control systems of technological objects are widely used in almost all industries currently. They allow continuous monitoring of the main operating parameters of the object, as well as provide a synthesis of control actions to achieve the best performance indicators of the technological installation, both in terms of performance and energy saving. Therefore, the problem of developing systems for optimal energy-saving control is very significant and relevant. The article deals with the issues of software and hardware implementation of energy-saving systems for managing complex technological objects. The generalized structure of the energy-saving control system software, obtained by decomposing the system into separate functional subsystems and program modules, is presented. The proposed software structure is largely universal and invariant to various control objects. The main components of the technical support of the energy saving control system are considered. A practical example of software and hardware implementation of the system of energy-saving control of dynamic modes of a group of heat engineering devices (multi-section roller-belt drying units) based on industrial controllers is shown.

Assessing a community-based waste separation program through examination of correlations between participation, information exposure, environmental knowledge, and environmental attitude

Municipal solid waste has become one of major environmental issues and pollution sources. In cities of developing countries, the amount of waste is inversely proportional to the land area available for landfills. Cipayung Landfill in the city of Depok, Jakarta’s southern border, cannot support the volume of waste generated by the city’s 11 districts. This study presents the case of a community group in Tugu Village, Cimanggis, Depok, where a waste separation program had been adopted since 2014 but low rates of participation are still recorded. Earlier observations reveal uneven distribution and location of communal organic bins and transportation of mixed waste. Earlier researches discussed over relationship between waste management and people participation, information dissemination, environmental knowledge, attitude, behavior, facility availability, partially. Thus, this study aims to integrate all these notions by examining the correlations between participation, information exposure, environmental knowledge, environmental attitude and other conditions that may promote participation in waste separation practices. Quantitative approach with quantitative and qualitative methods is implemented. Questionnaires, interviews, and observations are used to collect data. Spearman correlations reveal that participation is very strongly correlated with information exposure, and environmental knowledge, but weakly correlated with environmental attitude. Other conditions include respondents’ daily activities, residence period in the community, family welfare level, facilities provision, and role of community leaders. This study confirms the importance of information dissemination on a routine basis, valid and persuasive messages, facilities provision, and leading actor’s role at the community level to help increase public participation in waste separation

Iteration complexity on the generalized Peaceman–Rachford splitting method for separable convex programming

ABSTRACTRecently, a generalized version of Peaceman–Rachford splitting method (GPRSM) for solving a convex minimization model with a general separable structure has been proposed and its global convergence has been proved by Sun and Liu. In this paper, we establish the worst-case convergence rate for the GPRSM in both the ergodic and a nonergodic senses, then we give some numerical results to demonstrate the convergence rate of the GPRSM.

Training of adult psychiatrists and child and adolescent psychiatrists in europe: a systematic review of training characteristics and transition from child/adolescent to adult mental health services

BackgroundProfound clinical, conceptual and ideological differences between child and adult mental health service models contribute to transition-related discontinuity of care. Many of these may be related to psychiatry training.MethodsA systematic review on General Adult Psychiatry (GAP) and Child and Adult Psychiatry (CAP) training in Europe, with a particular focus on transition as a theme in GAP and CAP training.ResultsThirty-four full-papers, six abstracts and seven additional full text documents were identified. Important variations between countries were found across several domains including assessment of trainees, clinical and educational supervision, psychotherapy training and continuing medical education. Three models of training were identified: i) a generalist common training programme; ii) totally separate training programmes; iii) mixed types. Only two national training programs (UK and Ireland) were identified to have addressed transition as a topic, both involving CAP exclusively.ConclusionThree models of training in GAP and CAP across Europe are identified, suggesting that the harmonization is not yet realised and a possible barrier to improving transitional care. Training in transition has only recently been considered. It is timely, topical and important to develop evidence-based training approaches on transitional care across Europe into both CAP and GAP training.

Распределение индивидуальных доз в когорте людей в результате радиоактивного загрязнения реки Течи

Purpose: Descriptive analysis of the distributions of organ/tissue doses for individuals exposed to radiation as a result of liquid waste releases into the Techa River by the Mayak Production Association (PA) in 1949–1956. 
 Material and methods: The dosimetry system TRDS-2016D has been used to compute individual doses of external and internal exposures. TRDS-2016D databases include information on radionuclide intakes and dose rates in air for settlements located in the contaminated areas of the Techa River and the East Ural Radioactive Trace (EURT). Combining these village-average data with the residence history and age of a particular person, the system produces an individual scenario of external exposure and individual radionuclide intakes and then calculates corresponding external and internal doses from the Techa River and EURT. Available 90Sr-body-burden measurements and available information on individual household locations relative to the contaminated river have been used for refinement of individual dose estimates. 
 Results: Individual doses have been calculated for 29,647 persons included in the Techa River Cohort (TRC). According to residence history data, 5,280 members of the TRC were additionally exposed due to residency in the EURT villages. The cohort-average dose for the majority of extra-skeletal tissues does not exceed 100 mGy, while for the red bone marrow (RBM) it is equal to 350 mGy. In addition to the doses from the Techa River and EURT, individual thyroid doses for TRC members exposed to the Mayak PA atmospheric 131I releases have been calculated in a separate computer program. The cohort–average thyroid dose is 210 mGy. Maximum doses (about 1 Gy to the majority of extra-skeletal tissues and over 7 Gy to the thyroid and RBM) are observed for the persons who lived in their childhood and adolescence in the upper Techa region at close distance to the Mayak PA.
 Conclusion: The TRC members were exposed to chronic radiation over a wide range of doses, but at low-to-moderate-dose rates. Estimates of absorbed doses can be used to analyze the dose dependences of the incidence of solid cancers and leukemias. This can make it possible to verify risk coefficients of low-dose-rate effects of ionizing radiation which can be used for radiation protection purposes.

Double Duty Actions to Tackle All Forms of Malnutrition (P10-053-19)

ObjectivesBackground: Most countries are now experiencing a double burden of malnutrition (DBM), characterized by the coexistence of nutritional deficiencies (underweight, wasting, stunting, micronutrient deficiencies) and overweight/obesity and diet-related non-communicable diseases (obesity/DR-NCDs). Actions to address the two sides of the DBM are typically managed by separate communities, policies, programs, governance structures, and funding streams. Double duty actions, defined as actions that simultaneously address nutritional deficiencies and obesity/DR-NCDs, have been proposed as a win-win solution to tackling malnutrition in all its forms. The objective of the work was to explore opportunities—and make recommendations—for double duty actions to be delivered by programs and policies in key sectors such as health, social protection, education, and agriculture. MethodsWe reviewed evidence on the known shared drivers of undernutrition and obesity/DR-NCDs; searched the literature to identify examples of undernutrition-focused programs (in the four sectors selected) that have inadvertently caused harm by increasing risks of obesity/DR-NCDs; and looked for additional information on measures that programs may have adopted to correct these problems following recognition of harm. ResultsUndernutrition and obesity/DR-NCDs are intrinsically linked through four shared drivers: early life nutrition; dietary quality; food environments; and socioeconomic factors. Failure to adopt double duty actions in the past has caused harm. Examples from Latin America and Egypt show that some social cash/food transfer programs aimed at reducing poverty and undernutrition have led to deteriorations in diet quality (e.g., excess intakes of energy- fat- and sugar-dense and micronutrient-poor foods) and rises in obesity/DR-NCD risks. Realizing the harm, some of these programs pilot-tested successful corrective measures, thereby providing useful examples of early double duty actions. ConclusionsLeveraging the shared drivers of undernutrition and obesity/DR-NCDs through programs and policies delivered by the health, social protection, education, or agriculture sectors is possible and offers considerable opportunities for double duty actions and impacts on all forms of malnutrition. Funding SourcesCGIAR A4NH program led by IFPRI.

On solving two-stage distributionally robust disjunctive programs with a general ambiguity set

We introduce two-stage distributionally robust disjunctive programs (TSDR-DPs) with disjunctive constraints in both stages and a general ambiguity set for the probability distributions. The TSDR-DPs subsume various classes of two-stage distributionally robust programs where the second stage problems are non-convex programs (such as mixed binary programs, semi-continuous program, nonconvex quadratic programs, separable non-linear programs, etc.). TSDR-DP is an optimization model in which the degree of risk aversion can be chosen by decision makers. It generalizes two-stage stochastic disjunctive program (risk-neutral) and two-stage robust disjunctive program (most-conservative). To our knowledge, the foregoing special cases of TSDR-DPs have not been studied until now. In this paper, we develop decomposition algorithms, which utilize Balas’ linear programming equivalent for deterministic disjunctive programs or his sequential convexification approach within L-shaped method, to solve TSDR-DPs. We present sufficient conditions under which our algorithms are finitely convergent. These algorithms generalize the distributionally robust integer L-shaped algorithm of Bansal et al. (SIAM J. on Optimization 28: 2360-2388, 2018) for TSDR mixed binary programs, a subclass of TSDR-DPs. Furthermore, we formulate a semi-continuous program (SCP) as a disjunctive program and use our results for TSDR-DPs to solve general two-stage distributionally robust SCPs (TSDR-SCPs) and TSDR-SCP having semi-continuous inflow set in the second stage.

The position of the EU organic label among Hungarian consumers

The European Union's Common Agricultural Policy (CAP) has undergone many reforms and - over the past decades - has reached a level where food security issues are basic criteria for the European food production. From the beginning of the 1990s, the EU has been trying to reinforce this positive overall impression with quality systems which are regulated at the Community level.
 Basically, European decision-makers regard two areas as being of paramount importance: geographical indication and organic food. Each system has separate certifications and labels to help consumers make their decisions. Despite the fact that these products are also important factors of EU trade policy and in the case of geographical indications in Hungary, there has been a separate Origin Protection Program, the relationship between Central and Eastern Europe consumers with this system is a rather undiscovered area. That’s why the aim of this study is to investigate the awareness of the Hungarian consumers about the EU organic label and the factors that determine the awareness of the EU organic logo and the regular purchases. Not surprisingly, the awareness of the EU organic label and is still low despite the growing tendency in the recent years.
 The survey conducted in Hungary is based on a sample with 1,019 consumers. The online consumer survey was implemented during the second half of 2017. Results show that among the European food quality labels the organic label is one of the most recognized ones in Hungary, but its average awareness is still very low: less than every fourth Hungarian consumer knows what this label is for.
 The awareness of the EU organic logo is mainly determined by the sex (male), diet (fish consumption, (ovo)-vegetarian) and the place of purchase (alternative routes and internet). Regarding regular purchases, trust in the label and the system is crucial next to the age (younger ones), and purchase (supermarket). Therefore, in order to increase the sales of products with EU organic label, it is essential to sell bio food more widely, which will enable consumers to know more about organic products and the EU organic logo; as well as the application of a proper marketing strategy by companies to reach their potential target group, mainly the younger consumers. In any case, the future goal is to raise the awareness of bio and other quality systems (e.g. GI) products because the higher level of comsumers’ awareness and trust can lead to a higher level of consumer willingness to pay. And this results in mutual benefit for both producers and consumers.

A tale of two public dental benefit programs: Iowa dentist participation in traditional Medicaid versus a Medicaid expansion program

BackgroundIn Iowa from 2014 to 2017, there were 2 separate public dental benefit programs for Medicaid-enrolled adults: one for the Medicaid expansion population called the Dental Wellness Plan (DWP), and one for the traditional, non-expansion adult Medicaid population. The programs differed with respect to reimbursement, administration, and benefit structure. This study explored differences in patterns and predictors of dentist participation in the two programs.MethodsAuthors sent a survey to all private practice dentists in Iowa (n = 1301) 2 years after DWP implementation. Descriptive, bivariate, and logistic regression analyses were used to examine patterns and predictors of dentist participation in Medicaid and DWP.ResultsOverall rates of dentists’ acceptance of new Medicaid and DWP patients were 45 and 43%, respectively. However, Medicaid participants were much more likely than DWP participants to place limits on patient acceptance. Adjusting for other factors, practice busyness was the only significant predictor of DWP participation, and practice location was the only significant predictor of Medicaid participation. Dentists who were not busy enough were more than twice as likely to participate in DWP compared to others, and dentists in rural areas were almost twice as likely to participate in Medicaid compared to dentists in urban areas.ConclusionsDentist participation in Medicaid is an ongoing concern for states aiming to ensure access to dental care for low-income populations. We found distinct participation patterns and predictors between a traditional Medicaid dental program and the DWP, suggesting different motivations for participation between the two programs.