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A mixed-integer programming (MIP) problem contains both constraints and integer restrictions. Integer restrictions divide the feasible region defined by constraints into multiple discontinuous feasible parts. In particular, the number of discontinuous feasible parts will drastically increase with the increase of the number of integer decision variables and/or the size of the candidate set of each integer decision variable. Due to the fact that the optimal solution is located in one of the discontinuous feasible parts, it is a challenging task to solve a MIP problem. This article presents a cutting and repulsion-based evolutionary framework (called CaR) to solve MIP problems. CaR includes two main strategies: 1) the cutting strategy and 2) the repulsion strategy. In the cutting strategy, an additional constraint is constructed based on the objective function value of the best individual found so far, the aim of which is to continuously cut unpromising discontinuous feasible parts. As a result, the probability of the population entering a wrong discontinuous feasible part can be decreased. In addition, in the repulsion strategy, once it has been detected that the population has converged to a discontinuous feasible part, the population will be reinitialized. Moreover, a repulsion function is designed to repulse the previously explored discontinuous feasible parts. Overall, the cutting strategy can significantly reduce the number of discontinuous feasible parts and the repulsion strategy can probe the remaining discontinuous feasible parts. Sixteen test problems developed in this article and two real-world cases are used to verify the effectiveness of CaR. The results demonstrate that CaR performs well in solving MIP problems.

This paper estimates a DSGE model to explore how the economy is affected by financial and non-financial shocks. Bayesian methods and data from the US corroborate the results. This paper first illustrates how the financial sector is not only a transfer channel for exogenous shocks to the real economy, but also a contributor to business cycles through banks’ asset reallocation channel and the quality of capital adequacy constraint. The paper then shows that the contribution of financial and non-financial shocks has varied before, during and after the recent financial crisis; housing demand and asset price shocks are the main contributors and the credit shocks are the most persistent. In addition, the paper presents the application of macroprudential tools, along with their impact on the economy in general, and on welfare in particular. The findings illustrate that the tools which control household borrowing ability, such as loan-to-value or debt-to-income ratios, do not impact welfare significantly. However, the impact of policies on the leveraged sector is substantial. The paper proposes macroprudential policies that allow policy makers to stabilize the economy without changing welfare. Such policies, however, should be timely, targeted and temporary, otherwise they may cause disruptions.

In terms of heterogeneous devices and sensors, man and machine collaborate seamlessly, giving birth to the Internet of People, Internet of Things, and Internet of the Future. Within a short period, 30 billion intelligent devices in the form of smart applications will get connected to make an individual's life smoother, more comfortable, faster and accessible from anywhere at any time. IoT combines the power of IPv6 for network connectivity, sensing and nextgen communication technologies to meet future demands. Due to constraint environment in terms of memory, computation, and energy, this review paper will provide in-depth analysis of different OS'es. Candidate OS and Simulator is selected, keeping in mind various barriers and critical design characteristics. By doing this survey, it is possible for other research communities to make an appropriate choice for OS and making IoT a reality. Finally, the case study is also discussed which provides protocol stack implementation details along with deployable testbed, its size in terms of nodes supported and other security challenges. Critical preference level in terms of programming language and application areas from a developer perspective is also analysed and discussed to provide further research direction. IoT integration with future domains, along with various challenges, is explored at the end.

Banking regulation faces multiple challenges that call for rethinking the way it is designed. In this paper, we argue that regulators should focus more on simple equity requirements instead of elaborating complex rules. Such a constraint in equity is however opposed by the banking industry because of its presumed adverse impact on banks’ performance. Using various techniques (Lasso, Random Forest, Support Vector Regression, Artificial Neural Network) on a large dataset of banks’ balance sheet variables, we show that the equity ratio (equity over total assets) has a clear positive effect on banks’ performance when measured by the return on assets, while the impact of this ratio on the return on equity is most of the time negative. Strong equity requirements do not therefore impede banks’ performance, but do reduce the shareholder value. This may be the reason why the banking industry so fiercely opposes strong equity requirements. In addition, from a methodological perspective, we provide evidence that Random Forest performs better than other techniques at dealing with banks’ balance sheet data. Doing so, we provide avenues for future research dealing with these kind of data.

In this work, we propose a novel framework to address the formation control problem for a class of multirobot systems with two types of constraints, namely the performance constraints and the feasibility constraints. For the performance constraints, we consider the constraint requirements on the distance tracking errors between the real and the desired trajectories for each robot, so that to ensure precise tracking of the robot without deviating too much from its desired trajectory, as well as the constraints on the interrobot distance, so that to ensure the safe operation of the team. For the feasibility constraints, we consider the constraints on the heading angle, so that the controllers designed in the brief are feasible. Universal barrier functions are adopted in the controller design and analysis, which is a generic framework that can address systems with different types of constraints in a unified controller architecture. Through rigorous analysis, exponential convergence rate can be guaranteed on the distance tracking errors, while all constraints are satisfied during the operation. A simulation example and an experiment using three AmigoBot mobile robots further demonstrate the efficacy of the proposed control framework.

Surrogate-based-constrained optimization for some optimization problems involving computationally expensive objective functions and constraints is still a great challenge in the optimization field. Its difficulties are of two primary types. One is how to handle the constraints, especially, equality constraints; another is how to sample a good point to improve the prediction of the surrogates in the feasible region. Overcoming these difficulties requires a reliable constraint-handling method and an efficient infill-sampling strategy. To perform inequality- and equality-constrained optimization of expensive black-box systems, this work proposes a hybrid surrogate-based-constrained optimization method (HSBCO), and the main innovation is that a new constraint-handling method is proposed to map the feasible region into the origin of the Euclidean subspace. Thus, if the constraint violation of an infeasible solution is large, then it is far from the origin in the Euclidean subspace. Therefore, all constraints of the problem can be transformed into an equivalent equality constraint, and the distance between an infeasible point and the origin in the Euclidean subspace represents the constraint violation of the infeasible solution. Based on the distance, the objective function of the problem can be penalized by a Gaussian penalty function, and the original constrained optimization problem becomes an unconstrained optimization problem. Thus, the feasible solutions of the original minimization problem always have a lower objective function value than any infeasible solution in the penalized objective space. To improve the optimization performance, kriging-based efficient global optimization (EGO) is used to find a locally optimal solution in the first phase of HSBCO, and starting from this locally optimal solution, RBF-model-based global search and local search strategies are introduced to seek global optimal solutions. Such a hybrid optimization strategy can help the optimization process converge to the global optimal solution within a given maximum number of function evaluations, as demonstrated in the experimental results on 23 test problems. The method is shown to achieve the global optimum more closely and efficiently than other leading methods.

Several recent papers introduce different mechanisms to explain why asset bubbles are observed in periods of larger growth. These papers share common assumptions, heterogeneity among traders and credit market imperfection , but differ in the role of the bubble, used to provide liquidities or as collateral in a borrowing constraint. In this paper, we introduce heterogeneous traders by considering an overlapping generations model with households living three periods. Young households cannot invest in capital, while adults have access to investment and face a borrowing constraint. Introducing bubbles in a quite general way, encompassing the different roles they have in the existing literature, we show that the bubble may enhance growth when the borrowing constraint is binding. More significantly, our results do not depend on the-liquidity or collateral-role attributed to the bubble. We finally extend our analysis to a stochas-tic bubble, which may burst with a positive probability. Because credit and bubble are no more perfectly substitutable assets, the liquidity and collateral roles of the bubble are not equivalent. Growth is larger when bubbles play the liquidity role, because the burst of a bubble used for liquidity is less damaging to agents who invest in capital.

With the development of big data and artificial intelligence, distributed optimization has emerged as an indispensable tool for solving large-scale problems. In particular, the multi-agent system based on distributed information processing can be elaborately designed for distributed optimization, in which the agents collaboratively minimize a global objective function made up of a sum of local objective cost functions subject to some local and/or global constraints. Inspired by the applications involving resource allocation, machine learning, power systems, sensor networks and cloud computing, a variety of distributed optimization models and algorithms have been investigated and developed. The optimization models include unconstrained and constrained problems in continuous and discontinuous systems with undirected and directed communication topology graphs. The constraints include bounded constraint, separable and inseparable equality and inequality constraints. Meanwhile, in distributed algorithms, every agent executes its local computation and updating on basis of its own data information and that exchanging with its neighboring agents by means of the underlying communication networks, in order to deal with the optimization problems in a distributed way. This paper is designed to provide a comprehensive overview of extant distributed models and algorithms for distributed optimization.

This study examines how diversification in Indian business groups creates multiple forms of agency problems and has performance implications for group-affiliated firms. Departing from prior literature which emphasizes the principal–principal agency conflict in business groups, we argue that business group diversification leads to dual agency problems between controlling and minority shareholders (principal–principal) and shareholders and managers (principal–agent) in affiliated firms. Both these agency problems arise in diversified business groups through cross-subsidization of affiliated firms by inefficient capital investment, continuing presence of affiliated firms in declining industries, tunneling of resources from profitable affiliated firms, lack of attention by business group headquarters to affiliated firms, and affiliated firm managers' sense of perceived security, which negatively impacts affiliated firms’ performance. These agency issues are reduced with the increase in product market competition from exposure to international markets and through concentrated promoter ownership in the affiliated firms. Our hypothesized model finds empirical support in a sample of 828 business group–affiliated firms in India.

This paper investigates the interrelation between household balance sheets, collateral constraints, and monetary policy. Using data on the U.S. economy, we estimate a monetary DSGE model with financial frictions and occasionally binding borrowing constraints. The model implies stronger effects of monetary policy interventions when the borrowing constraint is binding compared to situations when it turns slack. In a prediction analysis we find that, out of a set of alternative plausible endogenous model variables, the level of household net worth is the single best predictor of the tightness of the borrowing constraint, which implies that monetary policy is more effective when household net worth is low. We test this model prediction in the data and provide robust empirical evidence on asymmetric effects of monetary policy across the household net worth cycle that validates the model predictions. A contractionary monetary policy shock leads to a large and significant fall in economic activity during periods of low household net worth. In contrast, monetary policy shocks have only small and mostly insignificant effects when net worth is high.

This paper deals with the optimal reinsurance problem and involves the goals of both insurer and reinsurer. An important novelty may be the incorporation of the background risk that the reinsurer uses in order to diversify (or hedge) the risk ceded by the insurer. Accordingly, general methods to prevent the reinsurer moral hazard must be extended, and a new constraint must be satisfied by the selected reinsurance contract, namely, "the reinsurer increment of risk must be lower than the contract premium". Simultaneously, since the contract must be attractive to the insurer too, "the contract premium must be lower than the insurer risk reduction". Integrating both ideas, "the contract premium must be higher than the reinsurer risk growth and lower than the insurer risk mitigation". Bearing in mind both requirements, that is, the protection against the moral hazard and the spread containing the contract premium, the optimal reinsurance problem is studied under very general conditions about the involved risk measures and premium principles, general solutions are provided, and a practical illustrative example is presented.

Multi-agent navigation systems present opportunities for many applications due to their agility and cooperation. In any multi-agent navigation system, it is critical that actual inter-agent collisions are strictly prevented. In this paper, we present a solution for the 2-D multi-agent navigation problem with collision avoidance. Our solution to this problem is based on a novel extension to Gauss's Principle of Least Constraint (GPLC) in which a fixed set of strict equality constraints are replaced by time-varying sets of active inequality constraints. To the best of our knowledge, this is the first instance that extends GPLC with dynamic incorporation and stabilization of active inequality constraints and with actuator delay and saturation. Herein, the dynamics of a collision-free multi-agent system satisfies the Karush-Kuhn-Tucker conditions. Active inequality constraints enforce collision avoidance, leader following and agglomeration behaviors, and they are stabilized using Baumgarte's error stabilization approach. We show that in dense configurations the positional arrangement of the agents can lead to linearly dependent constraints, and we propose specialized solutions involvin

This paper investigates the optimal strategies for an economic constrained closed-loop supply chain network. Manufacturers are classified into two categories namely low-emission manufacturers and high-emission manufacturers, and are subject to two greenhouse gas (GHG) emission control policies. Low-emission manufacturers are equipped with green production technologies to achieve ecological goals. All manufacturers are responsible in recycling and remanufacturing processes. New products and remanufactured products are homogeneous, and have the same sales price in the demand markets. Based on the variational inequality (VI) theory, we obtain the control equilibrium conditions of the non-cooperative game theory model for each firm. We further solve the model with the modified projection algorithm, and statically analyze and compare the influence of relevant parameters such as carbon quota, consumers’ low carbon preference and recovery rate on the network state through numerical examples. The results show that the GHG emission constraint may stimulate manufacturers to increase green technology investment level. Moreover, the introduction of reverse channel will promote resource recycling, but impair manufacturers’ profits. The promotion of consumer's environmental protection awareness has positive influence on the operation of supply chain network. In general, there is a conflict between economic goals and ecological ones. However, the developed model proves that economic goals and ecological ones can be realized consistently under certain conditions.

Distributed primal-dual methods have been widely used for solving large-scale constrained optimization problems. The majority of existing results focus on the problems with decoupled constraints. Some recent works have studied the problems subject to separable globally coupled constraints. This paper considers the distributed optimization problems with globally coupled constraints over networks without requiring the separability of the globally coupled constraints. This is made possible by the local estimates of the constraint violations. For solving such a problem, we propose a primal-dual algorithm in the augmented Lagrangian framework, combining the average consensus technique. We first establish a non-ergodic convergence rate of $\mathcal{O}\left(1/k\right)$ in terms of the objective residual for solving a distributed constrained convex optimization problem, where k is the iteration counter. Specifically, the global objective function is the aggregate of the local convex and possibly non-smooth costs, and the coupled constraint is the sum of the local linear equality constraints. The numerical results illustrate the performance of the proposed method.

(1) Problem Definition: In recent years, manufacturing firms in developing economies have made significant efforts to move up the production value chain by adopting foreign technology through licensing. However, there is negligible empirical evidence of the relationship between technology licensing and productivity growth in developing economy manufacturing firms (licensee firms), the focal relationship of interest in this study. We examine whether and how the relationship between technology licensing and productivity growth in the short run is affected by the challenges and constraints inherent in the contexts developing economy firms operate in. We do so by investigating the moderating role of formal workforce training program in a firm, and the corruption level and the infrastructural constraint level in the firm’s external environment. (2) Academic/Practical Relevance: Although the adoption of foreign technology by developing economy manufacturing firms is often driven by the goal to strengthen their capabilities in the long run, prior research provides a limited understanding of the performance consequences of technology licensing in the short run, which is an important business reality. Our study serves to address an important gap in research and practice by shedding light on some of the unique challenges and constraints that licensee firms in developing economies face as a consequence of foreign technology licensing. (3) Methodology: The empirical analyses are conducted using matching and fixed-effects regression on a multi-industry data set from the World Bank comprising detailed firm-level information from over 16,000 manufacturing firms across 25 developing economies in South Asia and East Asia. To strengthen the causal inference of the results and rule out alternative explanations, we use several alternative matching techniques and empirical methods addressing selection bias and unobserved heterogeneity. (4) Results: Our results indicate that the adoption of foreign technology by developing economy manufacturing firms has a substantial short-run disruptive effect on firm operations with productivity growth declining by 4.5 percentage points in these firms relative to comparable firms that do not use foreign technology licensing. Toward mitigating such disruptive effects, we find that formal workforce training programs attenuate the negative relationship between technology licensing and productivity growth. However, infrastructural constraints in the external business environment amplify this negative relationship. Intriguingly, our results suggest that corruption in the firm’s external environment acts as an “efficient grease,” attenuating the negative impact of technology licensing on productivity growth. (5) Managerial Implications: Our results provide compelling evidence on not only the presence of but also the large magnitude of the disruptive effects of technology licensing on productivity growth. The findings offer important insights for manufacturing firms and policymakers in developing economies on how to mitigate these negative effects. The results highlight opportunities for policymakers to (a) encourage firms to have formal workforce training programs, (b) reduce infrastructural constraints in the business environment, and (c) institute regulatory practices that can substitute for the effects of corruption.

The increasing penetration of renewables tends to demand more flexibility from gas-fired units to maintain system reliability, which significantly strengthens the interdependency between the electricity and the natural gas markets. To this end, intra-day gas market trading may be necessary, and a completely deregulated natural gas market may emerge in the future. As the interdependency between the electricity and the natural gas markets keeps growing, this paper proposes a bi-level strategic bidding model to study the market behaviors of the gas-fired unit, which simultaneously acts as a strategic power producer in the electricity market and a gas buyer in the natural gas market. The upper-level problem maximizes the profit of the gas-fired unit, and the two lower-level problems respectively model the market-clearings of the electricity and the natural gas markets. The upper and lower levels interact through locational marginal prices of electricity and natural gas. The proposed bi-level optimization model is converted to a mathematical problem with equilibrium constraint (MPEC). Then it is transformed into a mixed-integer second-order-cone programming (MISOCP) for efficient calculation. Numerical results demonstrate the proposed methodology is capable of mimicking the market-clearing process and strategic behaviors of the gas-fired unit in the interdependent energy markets effectively.

Recently, Circular Economy (CE) is implemented by the manufacturing industries since it helps the management to reduce waste and increase productivity. Industries are adopting CE because it helps them gain economic, environmental, and social benefits. This study is primarily aimed at the identification and ranking of the drivers and barriers for the implementation of CE in the automobile industry. For this, an integrated approach of interpretive structural modeling (ISM) and decision-making trial and evaluation laboratory (DEMATEL) is utilized. The results of this study indicate that the share/ benefit and reduction of cost are the most critical drivers while unaware/limited knowledge and cost and financial constraint are the major barriers for the implementation of CE in the automobile industry. This integrated approach will help the decision makers and policy makers to take immediate and effective actions, and focus on the productivity of the company.

The issue of stability and group output consensus is investigated for the discrete-time heterogeneous networked multi-agent systems with communication constraints(e.g., time delays and data loss) in this paper. Firstly, the couple-group output consensus is analyzed theoretically, the communication constraints are compensated by the prediction method. Secondly, the necessary and sufficient condition is given to ensure the stability of the system, achieve the couple-group consensus with reference input control, and relax the topology constraint of in-degrees balance by cooperative-competitive interactions. Furthermore, the result of couple-group consensus is extended to multi-group consensus based on a novel predictive control algorithm. Finally, a numerical simulation shows that the proposed networked predictive control method can effectively overcome the communication constraints, the dynamic performance and control effect are similar to the traditional control without communication constraints.

Diverse physical features of urban areas alongside socio-demographic characteristics affect car ownership, and hence the daily mobility choices. As a case of sustainable mobility, we explore how various urban environments and socio-demographics associate with the spatial and social distribution of household car ownership and carlessness in the Helsinki Metropolitan Area, Finland. Three urban fabrics characterizing the study area are established based on the transportation mode (walking, public transportation, or automobile) the physical urban environment primarily supports. The national level Monitoring System of Spatial Structure and Urban Form database, and the National Travel Survey (2016) are utilized to further include spatial and socio-demographic variables into our analysis across these fabrics. Our results show that households with and without cars differ in terms of residential distance to the city center, neighborhood density, house type, and socio-demographic profiles. Single pensioners and students are most likely to be carless, whereas families represent the opposite. Within the carless households the differences are also evident between different groups. For the more affluent households residing in dense and well-connected areas, and mostly possessing driver’s licenses, carlessness is presumably a choice. Contrarily, many other carless households represent the less affluent often located in the more distant, low-density, and less accessible areas, while also possessing less driver’s licenses, making carlessness more of a constraint, as the local urban fabric does not support such lifestyle. Consequently, carless households should be increasingly recognized as a focus group in sustainable urban planning in terms of identifiable best practices and potential vulnerability.

As a social construction, race is part of family genealogy and it creates intergenerational groups and identities for individuals. Racial differences matter in concrete areas of life, such as marriage rates, social class, employment, wealth, and health. Marriage rates vary by race and ethnicity: African Americans marry less than whites, due to external economic constraint; Mexican immigrant women marry younger but for economic rather than cultural reasons. Social class now includes cultural capital in tastes and consumption, which may make it difficult for minorities to fully thrive within white-dominated institutions. Race affects health in environmental ways based on nonhereditary factors. Race-targeted medicine therefore needs to be distinguished from race-based medicine.

PurposeThis article investigates the relationship between family ownership and export performance in the context of SMEs while also considering the moderating role of the financial dimension and, in particular, financial constraints and financial flexibility.Design/methodology/approachWe select a sample of 1,132 Italian SMEs to examine through an econometric analysis the role and impact of family ownership and the financial moderating variables being used on their export performance.FindingsThe results indicate that there is a U-shaped relationship between family ownership and export performance: the highest levels of export performance correspond to the lowest and highest family ownership levels, whereas when a mixture of family and nonfamily ownership exists, the performance suffers because of “conflicting voices” dominating strategic visions and approaches, harming the firm's export commitment. Moreover, the findings show that lower financial constraints and/or stronger financial flexibility improve the relationship between family ownership and export performance.Research limitations/implicationsOur findings show that the ownership structure is important for export performance; in particular, firms should avoid a mixture between family and nonfamily ownership because it is detrimental to export performance. Moreover, Italian SMEs need to develop sources of financing other than the banking channel, and policy makers should favour this process to overcome financial constraint problems and improve financial flexibility. Limitations concern the use of other econometric approaches and measurement variables to further investigate the connection between family ownership and export performance.Originality/valueThe present study enhances the comprehension of the complex relationship between family ownership and export performance by documenting the relevance of the level of family ownership and considering the moderating role of financial constraints and flexibility.

The low rate of technology adoption has long been a key constraint on improving productivity, income and yields in farming, particularly in developing countries where market-based systems of production are not well developed, the subsistence economy remains strong, land is held under communal tenure and family labour is the backbone of production. We examine four case studies of technology adoption to explore key socio-economic factors facilitating or constraining adoption. Our case studies cover an array of adoption situations from different parts of the developing world: 1. The socio-cultural barriers to the adoption of new technologies to control Cocoa Pod Borer in Papua New Guinea; 2. The role of land pressure on differential adoption rates of cocoassie yams amongst ethnic groups in Ivory Coast; 3. Past agricultural practices and their influence on adoption of a new planting pattern and selected oil palm planting material in Cameroon; 4. Taking account of gender relations to facilitate successful adoption of a new oil palm initiative for women smallholders in Papua New Guinea.

There has been recent attention to the political divide between urban and rural voters in the United States. It is possible that as rural and urban voting behavior has diverged, this has been driven by increasing social conservatism among rural voters. However, given that the average American is not ideologically constrained nor stable, this may not be the case. Using data from the 2010–2014 Cooperative Congressional Election Study Panel Study, this analysis compares the ideological constraint and stability of rural, suburban, and urban Americans. The results show that there has not been a divergence in rural, suburban, and urban ideologies or issue opinions in recent years. Rural and suburban respondents are more conservative than urban respondents on average, but they are not consistent conservatives, and their presidential votes are not primarily driven by a consistent set of conservative issue opinions.

The simulation of global and regional energy system transition and its potential mitigation cost could intuitively reflect the need for earlier climate mitigation actions. To explore the possible transitions of global and regional energy system, this study applied a 14-region energy system model (GTIMES) with scenarios designed using Shared Socio-economic Pathways (SSPs) with Representative Concentration Pathways (RCPs), and detailed depicts the quantification of SSPs trajectories into GTIMES model. Modeling results show that: 1) Global energy-related CO2 emissions will reach 37–74 Gt by 2050 under reference scenarios, while they will decrease to 12–14 Gt under higher possibility pathways to reach 2 °C target, with ratios of non-fossil fuel round to 42%–46%. 2) Electrification level has to increase noticeably in regional transition with a global average level of about 44% to achieve significant emission reduction. 3) Higher level of mitigation cost would happen with the constraint mitigation target, as well as social and economic trajectories chosen. Therefore, following trajectories of sustainable development is necessary.

The present study enriches the literature on hospital performance by analysing the total factor productivity growth of Shenzhen hospitals for the period 2005–2013 during which the 2009 Reform was implemented in the hospital sector of China. Unlike most previous studies, we adopt the global metafrontier Malmquist productivity index approach which allows the relaxation of the constraint of technological heterogeneity for hospitals by ownership. The analysis showed that there was a slightly rise in productivity of 0.68% on average. The technological regression experienced by the sampled hospitals out weighted the improvement in efficiency change. By hospital ownership type, public hospitals exhibit an average productivity decline by 0.67%, while non-public hospitals enjoyed an average productivity growth of 3.28% in general. Technological change is mainly the source of productivity change. While public hospitals are found to be the technology “leaders”, non-public hospitals have been catching up with the frontier over time. High bed utilisation was found to enhance technological progression, boost productivity growth, and allow hospital to catch up with the frontier. However, 2009 Reform exerts negative impact on the productivity growth and technological regression of the sampled Chinese hospitals.

The adoption of new and high yielding pearl millet (Pennisetum glaucum (L.) R. Br.) varieties can be boosted if they correspond to farmers’ preferences and answer the constraints prevailing in the production environments. Therefore, the focus of this study was to assess production constraints, farmers’ preferences and choices of varieties among pearl millet cultivating farmers using participatory rural appraisal (PRA) in the guinea savanna agro-ecological zone of Ghana where the crop is grown. Data collection was through mixed methods of focus group discussion (FGD) and individual interviews with 295 (45 for FGD and 250 for individual interviews) farmers covering 45 communities. Results indicated that the major constraints of production included low yields, bird damage, poor soils, erratic rainfall, downy mildew disease, head insects, and early maturity. Majority of pearl millet farmers depend on own seed source due to lack of access to and low knowledge of improved seeds. Breeding for high grain yield, earliness, resistance to downy mildew disease and bird attack varieties were the leading traits of preference that research should focus on. It is therefore anticipated that breeding program would integrate the product profiling proposed in this work for enhance adoption of new pearl millet varieties in Ghana. Key words: Participatory rural appraisal, constraint, pearl millet Guinea savanna, Ghana.

Evolutionary algorithms (EAs) are widely used for a variety of optimization problems, most of them with the presence of constraints. As move operators are usually blind to the constraints, (i.e. when operating upon feasible individuals they do not necessarily generate feasible offspring) standard EAs must be equipped with a constraint handling technique. This paper focuses on exactly satisfying the linear equality constraints present in continuous optimization problems that may also include additional non-linear equality and inequality constraints. The proposed method, named DELEqC-III, is an extension of two other previously developed methods. In this work, the original constrained problem (in $${\mathbb {R}}^n$$ ) is transformed into a lower-dimensional ( $${\mathbb {R}}^{n-m}$$ ) unconstrained optimization problem, where n is the number of variables and m is the number of linear equality constraints. DELEqC-III performs the search in the null space associated with the linear equality constraints allowing the method to exactly satisfy such constraints. In order to show the efficiency of the method, scalable test-problems are used to analyze the performance of the new proposal.

Purpose The purpose of this paper is to look at the asymmetric effect of oil production on environmental degradation in OPEC member countries from 1970–2019. Design/methodology/approach The authors build a nonlinear panel ARDL–PMG model using the Shin et al. (2014) nonlinear autoregressive distributed lag (ARDL) approach in panel form to assess both the short- and long-run impact of positive and negative oil production movements on CO2 emissions. Findings The result demonstrates that the variables are cointegrated. According to the linear long run coefficients, oil production, FDI inflows and economic growth both have a positive and significant relationship with CO2 emissions, implying that they deteriorate environmental quality in OPEC countries, while renewable energy has a negative relationship with CO2, implying that increasing renewable energy improves environmental quality. The asymmetric findings prove that positive and negative shocks of oil production exert a positive effect on carbon emissions in short run and long run. Research limitations/implications To begin with, the empirical assessments do not include all OPEC member nations; researchers are advised to resolve this constraint by looking at the economies of other OPEC members. Albeit the lack of data for other energy sources may serve as another constraint of this research, future research is expected to broaden the current framework via other energy sources such as nuclear, electricity, biomass, solar as well as wind. Originality/value The research adds to the body of knowledge as many of the prevailing studies in the literature failed to look at the asymmetric effect of oil production on the quality of environment. This is another gap in the literature that the current study is set out to fill. This study adds oil production as an explanatory variable and helps to extend the existing literature for OPEC countries, which could propose a solution to deal with ensuing environmental issues.

The initial optimism on the revival of civic activism in Turkey following the Gezi protests in 2013 was short-lived. The deteriorating legal and political environment has considerably narrowed the ...

The rapid growth of the Chinese travel market has gained attention in the tourism industry. However, very few studies have been conducted to examine travel constraints that prevent Chinese outbound travelers from going somewhere quite accessible to their major destination from a multidestination perspective. Drawing upon the leisure constraint model (LCM), this study explored Chinese independent tourists' perceived travel constraints in selecting second-tier destinations in their destination choice and analyzed the market segments. A self-administered survey was collected from 393 Chinese travelers who did not visit Gyeonggi Province close to Seoul during their travels in South Korea. Based on the findings, four distinct groups were formed. The findings provide important insights into destinations that desire to attract more Chinese independent travelers.

Joining a conversation about menstruation and the law, this Essay interprets “law” to mean regulation––a source of burden, constraint, and interference justified by reason. The object of my regulatory agenda is a substance perceived by Western thinkers at least since Aristotle as the superior counterpart to menstrual fluid.1 Traditions that celebrate semen as vital or affirmative, while recoiling from and controlling the other gendered emission that hurts no one, get reality backward. Law as burden, constraint, and interference ought to regulate semen and leave menstrual fluid alone. Contrast the two substances. One of them started out with the potentially useful function of building a uterine lining. That possibility concluded, menstrual fluid is benign. The other effluvium started out with the potentially useful function of launching a pregnancy. Pregnancy is a good thing when it is desired by the person who has to live with the bulk of pregnancy’s detriments. Along with its capacity to do an important job, semen causes quite the array of harms. A statute on point for this purpose, the Federal Hazardous Substances Act, regulates material that “may cause substantial personal injury or substantial illness during or as a proximate result of any customary or reasonably foreseeable handling or use.”2 Because semen “has the capacity to produce personal injury or illness to man through ingestion, inhalation, or absorption through any body surface,” it also aligns with the definition of “toxic” in the statute.3 Judges, policymakers, litigants, and ordinary people can all learn from well-established legal labels to understand semen as a stark example of an externality. Nothing in this statute impedes the characterization I propose: The FHSA lists substances that lie outside its purview,4 and semen is not among them. Labeling, containment, and emergency protocols—splash protection, if you like—are the hazardous-substance safety impositions I would apply to semen.

The early twenty-first century in Latin America was characterized by a “pink tide”, in which a reorientation of national policies produced positive social outcomes and changed both the regional order and the role of regional integration in the different countries. Alongside this process, the international economy provided relief from the external constraint, which meant that growth paths were not interrupted by balance-of-payments crises. Nonetheless, the progress made in regional integration falls well short of political intentions. This article posits that major transformations occurring at the centre of the international economy prevented the region’s production structure from becoming more diversified. Unfortunately, as existing production structures were reproduced (or reprimarized), external engagement outside the region became deeper and Latin American integration remained constrained and confined to a secondary role.

The COVID-19 pandemic has heavily hit international economy giving a particular setback to the tourism sector. Between March and May 2020, during the first lockdown, and between October and December of the same year, during the second lockdown, a questionnaire was administrated in Italy, Greece and Great Britain. Through the questionnaire, people’s feelings and expectations of their desire to take a vacation were collected regarding the period of constraint due to the new coronavirus and the possible end of the pandemic, or the first government approved travel openings. In particular, the question of how long it would take to decide on a holiday, the type and duration, after the period of constriction due to the coronavirus was over, was asked. Both surveys, in the two different lockdown periods, showed the potential desire of tourists to leave relatively quickly, and to take forms of domestic tourism, characterized by small and short-lived trips. The favorite destination being the seaside.

The economically optimal dry period length (DPL) of dairy cows remains a topic of interest. Increasing daily milk production and improved management of the transition period require frequent evaluation of the optimal DPL. The economically optimal DPL also depends on the most limiting farm resource such as milking capacity, housing capacity, or fat quota. Therefore, the objective of this study was to determine economically optimal DPL under farm constraints on milking capacity, housing capacity, and fat quota given variations in 12 input factor levels. We developed a deterministic whole herd simulation model, including a nonlinear optimizer of the DPL in the first 3 parities. The model included estimates of milk, fat, and protein yield deviations in the subsequent parity and hazard ratios of culling risk and pregnancy rates as functions of the DPL in the current parity. The DPL could vary between 20 and 90 d with step size of 1 d. In addition to a one-factor-at-a-time analysis, we used a definitive screening design and a space-filling design with Latin hypercube sampling to determine important linear and curvature effects of input factors and their interactions. Results indicated that the economically optimal DPL were typically between 35 and 50 d under a large variation in input factor levels. The opportunity costs of equal DPL in all parities were small compared with optimal policies where the DPL were allowed to vary between parities. The DPL under the parlor constraint were generally less than 5 d longer than the optimal DPL under the housing constraint. The optimal DPL under the quota constraint were between those under the parlor and housing constraints. Opportunity costs compared with 50 d dry were often small, but in some cases large. A formal global sensitivity analysis revealed important interactions of input factors that were not discovered with one-factor-at-a-time analyses. In conclusion, economically optimal DPL were often shorter than typically are recommended. Adding uncertainty about the date of calving at the date of dry-off might extend these optimal DPL by some days depending on the risk attitude of the decision maker.

In this paper, the decentralized energy management of a community of prosumers is studied. The coordination of the prosumers participating in the community is cast as a mixed-integer linear program (MILP) with local and global coupling constraints. A dual decomposition method with a tightening of the coupling constraints is applied to solve the problem in a decentralized way. The resulting tightened problem provides feasibility guarantees for the obtained solutions. A receding horizon approach that exploits the structure of the problem is proposed to divide the problem in subproblems and solve them sequentially. The proposed approach ensures that the tightened problem is feasible under realistic conditions, whereas the existing methods may result in infeasible problems. Moreover, it may reduce the necessary constraint tightening compared to existing methods. Two setups are evaluated for the organizational structure of the community, one with a community coordinator and one without. Moreover, three different structures of the communication graph are analyzed for the setup without a coordinator. The simulation results demonstrate that the proposed method results in feasible problems that can be solved due to the reduced constraint tightening when other methods are not feasible. In the case of feasible problems, the optimality gap is comparable to that achieved with existing methods and even smaller for communities with a small number of participating prosumers.

Village-owned enterprises (BUMDes) in Indonesia, as village economic institutions can drive village potential, by the Central Maluku communities BUMDes is called as a BUMNeg which have the same meaning. BUMNeg becomes village income (Village Law, No. 6 of 2014). Objectives of the study: (1) Knowing the Role and Development of Village-Owned Enterprises that have been intervened through capital participation from the Village Fund, (2) Understanding the potential and capacity of villages constraint factors and main supporters in supporting the activities of Village-Owned Enterprises, (3) Obtaining a management model of Village-Owned Enterprises that is in accordance with the local conditions of the village community. The study used a qualitative approach. The results of the study illustrate (1) the role of BUMDes in the sample villages having different results. In Waai Villlage the existence of the BUMDes has been carried out in accordance with the functions of the BUMDes, namely carrying out economic functions. Whereas the existence of BUMDes in Tulehu Village was not carried out, village funds were only embedded in goods purchased, and only functioned socially, not functioned to generate village income. (2) Obstacles and main supporters of the BUMDes are: (a) The existence of potential natural resources, but not yet managed, (b) Potential Number of residents not managed as a business unit management market in Tulehu Village, (c) Custom institutions do not function, (d) Village funds are not managed according to their functions in Tulehu Village, in Waai village according to function, (e) Location of Waai Village is very strategic with potential villages. (3) BUMDes Strengthening Model in Tulehu village will exist through three stages: activation, implementation and development. Strengthening the BUMDes in Waai village, namely: building a network with the village’s government / king to continue to maintain trust relations and build networks with other parties as a reinforcement of BUMDes development

In recent years, We Media’s chaotic behavior has emerged one after another. How to properly supervise We Media and effectively manage its violations has become an urgent problem in the process of national governance system and governance capacity building. From the three aspects of opportunity, motivation, and control methods, this paper analyzes the relevant stakeholders and their relationships in the process of We Media information dissemination. It constructs a tripartite evolutionary game model of government, We Media, and public participation, which focuses on the analysis of the equilibrium point of the game model and carries out simulation experiments to explore the influence of government responsibility constraints on the evolution results. The research results show that government regulation plays an important role in restricting We Media’s information release. When the government's willingness to regulate increases, We Media will be punished more if it violates rules. In order to reduce the cost of punishment and other factors, We Media will reduce the willingness to violate the rules. After the occurrence of social hot events, the public is more willing to be guided by positive information from We Media, prompting the government to choose strict supervision strategies, effectively reducing the violations of We Media and achieving the Pareto optimum. According to the research results, this paper puts forward reasonable countermeasures to realize the comprehensive governance pattern of noncompliance of We Media and correct guidance of public emotional cognitive behavior under responsibility constraints. The research results provide theoretical support and decision-making basis for We Media information management and control.

Aiming at the problems of poor system throughput and poor performance appraisal indicators in traditional enterprise employee performance appraisal management systems, a corporate employee performance appraisal management system based on the CS architecture was designed. Firstly, the system architecture of performance appraisal system is built, the system logical architecture design is determined, and the functional modules of the appraisal management system are analyzed. Then, the influencing factors of employee performance appraisal management system are analyzed through the evaluation constraint parameters, and the quantitative regression analysis model of enterprise employee performance appraisal management is constructed to realize the design of enterprise employee performance management software. Finally, the evaluation management system database was built to realize the enterprise employee performance evaluation system’s design based on CS architecture. The experimental results show that this system can improve the throughput of the employee performance appraisal management system and the rationality of enterprise employee appraisal standards. It plays an important role in enterprise employee performance appraisal management.

This paper aims to examine the rule of law regarding law violations by motorcycle gangs, to examine the role of the Brimob Police Corps and the obstacles faced in overcoming law violations by motorcycle gangs. The problem is focused on how the law rules regarding law violations by motorcycle gangs, what is the role of the Brimob Police Corps and the obstacles faced in overcoming law violations by motorcycle gangs. To approach this problem, Soerjono Soekanto's role theory is used. The data were collected through interview guidelines and analyzed qualitatively. This study concludes that the criminal act of violating the law by motorcycle gangs is contrary to Article 170 regarding crimes against public order, Article 351, Article 352, Article 368 regarding persecution and Article 510 and Article 511 regarding violations of public order in the Criminal Code, contrary to Article 106 and Article 115 in the Law of the Republic of Indonesia Number 22 of 2009 concerning Road Traffic and Transportation. The role of the Brimob Police Corps in overcoming violations of the law by motorcycle gangs can be seen by using Soerjono Soekanto's theory based on aspects of role as a norm, role as an individual/norm, and role in the social structure of society. The constraint factors faced by Brimob are that the perpetrators of violations are minors, the lack of parental supervision of their children and the actions of motorcycle gangs usually involve a large number of people.

In 2020, under the major impact of the global COVID-19 epidemic, people are paying more and more attention to safety issues including health and personal safety, and relevant supervision and testing methods are also constantly updated across different countries. In industrial enterprises, both spread of diseases and occurrence of accidents are largely caused by unsafe state of things and unsafe behaviors of people, among which, human factor is the most important factor. In recent years, many scholars have conducted theoretical and practical research on individual behavior from the perspective of individual psychological characteristics. Where, individual initiative as an important individual psychological trait is increasingly incorporated in the research category of safety behavior. A close correlation exists between individual initiative and evolution of safety production behavior. According to constraint conditions and replicator dynamics equation, this paper uses evolutionary game method and computer fuzzy system Matlab simulation software to conduct numerical experiment analysis on the ideal state of the game between organizations and individuals, thereby studying the behavior evolution trend. The basic idea of fuzzy control is to use computer to realize human's qualitative control experience. Research is found that whether an individual adopts safety obedience behavior will be directly affected by whether the organization adopts regulatory safety production management model. And if the organization adopts regulatory safety production management model and the individual does not implement safety obedience behavior, it is impossible to achieve a stable state. The evolution process of the two to the ideal state is affected by multiple factors. © 2021 - IOS Press. All rights reserved.

Background: The use of physical constraint in pediatric dentistry is highly controversial. Papoose boards in particular, which envelop and immobilize children during treatment procedures, have been described as barbaric devices even though their goal is to protect the patient. In this debate, the voice of parents is important but still missing in the scientific literature. Aim: To understand how parents or caregivers experienced physical constraint and the use of the papoose board on their children during regular dental treatment. Design: We conducted qualitative research rooted in interpretive phenomenology. Accordingly, we performed in-depth individual interviews with a purposive sample of 7 parents or caregivers. The interviews took place in Montréal, Canada, after the children had been treated with a papoose board for nonemergency dental treatments. The discussions were audio recorded, transcribed, and thematically analyzed. Results: Two perspectives emerged among participants. Some explained that the papoose board calmed their children, helped the dentist to complete the procedures, and made their experience less stressful. For others, the papoose board was a horrible and traumatizing experience, leading to feelings of guilt toward their children. They expressed anger toward the dentists for not allowing them enough time to decide and for imposing use of the device. Conclusion Our study raises serious ethical concerns about this practice. We believe that using a papoose board should remain an extraordinary measure and, more generally, that dental professionals should reflect on the place of children and their families in clinical encounters. Knowledge Transfer Statement: The findings of this study should encourage policy makers, dental professionals and ethicists to consider the following points: 1) the traumatizing experiences described by parents raise serious ethical concerns about the use of papoose boards; 2) the dental profession should reflect on the place of children and their families in the clinical encounter and grapple with the importance of consent and how to ensure consent in encounters involving children and their parents.

The ‘limits of markets’ debate broadly concerns the question of when it is (im)permissible to have a market in some good. Markets can be of tremendous benefit to society, but many have felt that certain goods should not be for sale (e.g., sex, kidneys, bombs). Their sale is argued to be corrupting, exploitative, or to express a form of disrespect. In Markets without Limits, Jason Brennan and Peter Jaworski have recently argued to the contrary: For any good, as long as it is permissible to give it for free, then it is permissible to give it for money. Their thesis has led to a number of engaging objections, and I leverage recent work on the nature of feasibility within political philosophy to offer a new challenge.I argue that feasibility offers a constraint on which markets can be permissibly implemented. Though it may be possible to create a morally acceptable version of an otherwise repugnant market, some of these markets may be infeasible, and so we are not permitted to implement them. After laying out this challenge, I consider several replies. They concern the relevance of feasibility, and whether any markets really are infeasible. This provides an opportunity to explore the dangers of pursuing the infeasible and with markets generally. I conclude by considering what might lead us to pursue these markets despite their infeasibility, or how knowledge of infeasibility may prove useful regardless.

In developing countries, little information is available about solid-waste characteristics, determinants for adoption and performance-evaluation of municipal-waste management systems in Municipals. This study aimed: to characterize the municipal solid-wastes, collection, dumping and evaluate the efficiency and reliability of Municipal solid-waste management system. A total of 200 households were randomly sampled and interviewed. Data was analysed using Binary-Logistic Regression model to determine factors influencing collection and dumping of solid wastes. Results showed that biodegradable/organic wastes comprise a major fraction of solid-wastes produced. Factors that influenced solid-waste collection and dumping included: household-age, unavailability of solid-waste containers, inadequate collection/dumping space and weak legal-enforcement against poor-dumping. The waste system is constrained by inadequate transport facilities, inadequate space for temporal dumping; and lack of legal enforcement in matters of solid-waste poor handling. These have made the systems ineffective and unreliable. This study recommends involvement of all stakeholders in innovative approaches to uphold sustainable municipal sanity.

This paper aims to find an efficient method to assign different projects to several regions seeking an equitable distribution of the expected revenue of projects. The solutions to this problem are discussed in this paper. This problem is NP-hard. For this work, the constraint is to suppose that all regions have the same socio-economic proprieties. Given a set of regions and a set of projects. Each project is expected to elaborate a fixed revenue. The goal of this paper is to minimize the summation of the total difference between the total revenues of each region and the minimum total revenue assigned to regions. An appropriate schedule of projects is the schedule that ensures an equitable distribution of the total revenues between regions. In this paper, we give a mathematical formulation of the objective function and propose several algorithms to solve the studied problem. An experimental result is presented to discuss the comparison between all implemented algorithms.

A district heating network has generally more than one production unit, and then there are different ways to fulfill the energy demand of the network. This paper deals with the planning problem which is a problem of optimization under constraints. The production units are modeled using MINLP (mixed integer non-linear programming), in particular the following technical aspects are considered: storage capacity (for municipal wastes and biomass), allowable operating range, allowable variation of power over time, partial load performances, minimum working time when a unit runs, and minimum waiting time when it is in stand-by mode. The environmental constraint is the annual share of renewable energies in the global energy mix (for example, at least 50% over a year). The model aims to minimize the operating cost of the network. The problem cannot be solved by a one-shot optimization, so the paper proposes a sequential approach: first, a target of renewable share is calculated for each month of the year; secondly, the planning production is determined each day according to the calculated target. The results of a case study show that the planning strategy that only aims to minimize the operating cost violates the environmental constraint. Using the developed planning model raises a little bit the cost (4.5%) but fulfills the heat demand and environmental constraint at the same time. Considering a reduced VAT eligible in France when the constraint on renewable share is met, the proposed planning is even better in term of the total cost (10% lower).

We assess whether imperfect knowledge of labor regulation hinders job creation at small and medium-sized firms. We partner with a labor law expert organization that provides information about labor regulation via newsletters and access to a specialized website. We randomly assign 1,800 firms to get access to this service for a 21-week period. Six months later, the average employment level at treatment firms was 12 percent higher than at control firms. The intervention decreased the perception that labor regulation is a constraint to hiring and increased optimal employment level. (JEL D22, D83, J63, L25, K31, O15)

This paper presents a trilevel risk-averse strategy to configure the grid-scale energy storage systems (ESS) in active distribution network. Unlike the traditional planning framework, which presumes that ESS and renewable energy sources (RES) are cooperatively planned, we consider a practical situation that the siting choice of individual RES owners could be conflict with systems operation target of hosting capacity improvement. To address this challenge, a trilevel ESS planning formulation with “min-max” risk constraint is developed. Also, a scenario-based stochastic program model is incorporated in the lower level problem to handle the random fluctuation of RES outputs. As the resulting risk-constrained trilevel formulation is computationally difficult, we develop a customized column-and-constraint generation algorithm with finite convergence. Numerical studies on 33-bus test system and a real-world 56-bus distribution network indicate that the proposed methodology can effectively enhance the robustness of look-ahead ESS configuration against those non-cooperative and uncertain integration choices for renewable energy construction. Moreover, our customized algorithm demonstrates a superior solution capacity and scalability to support the efficient decisions for risk-averse storage planning.

Many organizations have adapted flexible working arrangements during COVID19 pandemic because of restrictions on the number of employees required on site at any time. Unfortunately, current employee scheduling methods are more suited for compressed working arrangements. The problem of automating compressed employee scheduling has been studied by many researchers and is widely adopted by many organizations in an attempt to achieve high quality scheduling. During process of employee scheduling many constraints may have to be considered and may require negotiating a large dimension of constraints like in flexible working. These constraints make scheduling a challenging task in these working arrangements. Most scheduling algorithms are modeled as constraint optimization problems and suited for compressed work but for flexible working with large constraint dimensions, achieving accurate scheduling is even more challenging. In this research, we propose a machine learning approach that takes advantage of mining user-defined constraints or soft constraints and transform employee scheduling into a classification problem. We propose automatically extracting employee personal schedules like calendars in order to extract their availability. We then show how to use the extracted knowledge in a multi-label classification approach in order to generate a schedule for faculty staff in a University that supports flexible working. We show that the results of this approach are comparable to that of a constraint satisfaction and optimization method that is commonly used in literature. Results show that our approach achieved accuracy of 93.1% of satisfying constraints as compared to 92.7% of a common constraint programming approach.

A consumer is considered as a person or a group of people who uses purchased goods, products, or services only for personal use, and not for manufacturing or resale. Consumers usually purchase valuable and useful commodities or goods by spending all or partial of their income. The property of a commodity that enables it to satisfy human wants is called utility. Producers must be conscious to increase the utility among the consumers. This study has considered the maximization of utility problem of consumers of Bangladesh subject to two constraints; namely, budget constraint and coupon constraint. Consequently, in the study two Lagrange multipliers are used and interpreted these with mathematical analysis. Prediction of consumer behavior will help both producers and consumers to take decision of their future economic productions and consumptions, respectively. This article is ornamented with sufficient theorems and economic analyses. So that all the readers find interest when go through the economic analysis of utility maximization.

More than half of Indian population were engaged in agricultural sector but the available technology doesn’t ensure food security of the country. Hence, to diffuse new agricultural invention and innovation in the farming community, there arises a need for effective medium for transfer of technology. Thus, KVK bridges the gap between the technology generation and dissemination. The present study was proposed to understand the impact of KVK in doubling farmers income to formulate suitable programmes. For the study, descriptive research design was adopted. 120 respondents from Biswan taluk of Sitapur district of Uttar Pradesh were selected as respondents. Primary data collected from respondents and secondary data from available literatures. The findings revealed that majority of the respondents were middle aged, illiterate, upto 5 members in their family, medium level of annual income, possesses their own land, agriculture as their main occupation, medium level of mass media exposure, office bearer in one organization, high level of extension contact. Meanwhile, more than half of the respondents had reported medium level of impact towards the activities carried out by KVK, beneficiary selection is not unbiased is a major constraint suggested that maximum emphasis should be given on learning by doing. View Article DOI: 10.47856/ijaast.2021.v08i9.011