Global Solution Research Articles

A gazdasági, társadalmi és egészségügyi válságok hatása a családon belüli erőszak áldozataira

Aim: The situation of victims of domestic violence and partner abuse becomes even more serious in crisis situations. There have been and are ongoing conflicts in the world, which have been scrutinized by economists, sociologists, criminologists, health professionals and lawyers alike in recent years. The latest related research worldwide provides a lot of important new information that can help prepare for the problem and provide professionally competent answers. Methodology: A selection of research conducted in different parts of the world. Summary reports were prepared to shed light on similarities and differences. Findings: It is clear from the processed literature that the individual forms of violence are connected in crisis situations and pose an even greater danger. Violence at the macro level, such as war, also increases violent conflict at the micro level. The crises caused by the fear of COVID, the lockdown, war conflicts, hunger, and the climate disaster spill over into family homes and make the victims of domestic violence and partner abuse even more vulnerable. Most of the processed materials analyse research born after COVID. The COVID-19 epidemic also provided many lessons regarding the management and prevention of the economic effects of future natural disasters and the associated increased domestic violence. Value: Analyses point to relationships that need further research and evaluation. In the future, macro- and micro-level violence research must be continued, common global results must be aggregated, and complex, global solutions must be developed. International organizations must continue to collect data and provide clear guidelines to public bodies and social organizations for the joint management of macro- and micro-level problems.

Stochastic Analysis for the Dual Virus Parallel Transmission Model with Immunity Delay.

In this article, the qualitative properties of a stochastic dual virus parallel transmission model with immunity delay are analyzed. First, we use Lyapunov theory to study the existence and uniqueness of the global positive solution of the proposed model. Second, the threshold values of the persistence and extinction of two viruses were obtained. Finally, the numerical simulation verifies the theoretical results. The results show that the immunity delay and the intensity of noise have important effects on the two diseases spreading in parallel.

U-AEFA: Online and offline learning-based unified artificial electric field algorithm for real parameter optimization

Optimization problems in real-world scenarios require algorithms that effectively balance exploration and exploitation to avoid local optima and achieve global solutions. To address this, we propose a unified artificial electric field algorithm (U-AEFA) that integrates both offline learning (inspired by high-performing metaheuristic algorithms) and online learning (through historical data generated during evolution). U-AEFA introduces a unique three-layer population structure to enhance search efficiency, consisting of the best agent in the first layer, the top-performing agents in the second layer, and the remaining agents in the third layer. Key features of U-AEFA include (i) an effective Coulomb’s constant for improved exploration, (ii) a non-uniform mutation operator to mitigate premature convergence, and (iii) two acceleration coefficients for enhanced performance. These three factors constitute offline learning and have been implemented to improve different design elements of the algorithm. As part of online learning, it employs a difference vector reuse (DVR) strategy to evolve the first-layer agents. The algorithm is evaluated using the CEC 2017 test suite across multiple dimensions (10, 30, 50, 100), where it consistently outperforms seven state-of-the-art algorithms, demonstrating superior accuracy and convergence speed. Moreover, U-AEFA’s robustness is validated on 12 high-dimensional feature selection problems, further highlighting its effectiveness in solving complex optimization tasks. The source code of U-AEFA is available at

Global solutions for bi-harmonic inhomogeneous non-linear Schrödinger equations in Lebesgue spaces

This paper studies the inhomogeneous bi-harmonic nonlinear Schrödinger equation iu˙+Δ2u±|x|−τ|u|p−1u=0,\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mbox{i}\\dot{u} +\\Delta ^{2} u\\pm |x|^{-\ au}|u|^{p-1}u=0, $$\\end{document} where u:=u(t,x):R×RN→C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$u:=u(t,x):\\mathbb{R}\ imes \\mathbb{R}^{N}\ o \\mathbb{C}$\\end{document}, τ>0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$\ au >0$\\end{document} and p>1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$p>1$\\end{document}. One proves the existence of global solutions with datum in Lebesgue space Lϱ(RN)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$L^{\\varrho}(\\mathbb{R}^{N})$\\end{document}, for a certain 1<ϱ<2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$1<\\varrho <2$\\end{document}. This work complements the known global well-posedness result in the mass-sub-critical regime, namely 1<p<1+8−2τN\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$1< p<1+\\frac{8-2\ au}{N}$\\end{document} and with finite mass. This work aims to develop a local theory in non-Hilbert Lebesgue spaces. Moreover, one complements the local solution to a global one under some suitable assumptions on the parameters. To this end, one uses a Strichartz-type estimate based on Lϱ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$L^{\\varrho}$\\end{document}. Moreover, one breaks down the data into two parts: the first is in L2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$L^{2}$\\end{document}, and the second has a small Strichrtz norm under the free bi-harmonic Schrödinger propagator. Then, one uses a standard fix point argument coupled with Strichartz estimates. First, one resolves the above problem in L2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$L^{2}$\\end{document} and then takes the considered equation with a perturbed source term. The local solution is complemented by a global one with induction. Since the free associated kernel ei⋅Δ2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$e^{\\mbox{i}\\cdot \\Delta ^{2}}$\\end{document} is unitary in L2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$L^{2}$\\end{document}, the Schrödinger equations seem more adapted to be mathematically studied in functional spaces based on L2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$L^{2}$\\end{document}, such as the Sobolev spaces Ws,2(RN)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$W^{s,2}(\\mathbb{R}^{N})$\\end{document}. The main novelty here is investigating the above inhomogeneous bi-harmonic nonlinear Schrödinger problem in some Lebesgue spaces different from L2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$L^{2}$\\end{document}. One essential challenge is overcoming the lack of conservation laws, namely the mass and the energy, representing standard tools in the Schrödinger context. The second technical difficulty is the presence of an inhomogeneous source term, namely the singular decaying term |x|−τ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$|x|^{-\ au}$\\end{document}, which causes some serious complications. In order to deal with the inhomogeneous term, one uses Lorentz spaces with the property |x|−τ∈LNτ,∞\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$|x|^{-\ au}\\in L^{\\frac {N}{\ au},\\infty}$\\end{document}.

Evaluation of rotating components by combining individual classification with adaptive updating searching method in aero engine

Abstract In order to evaluate the roundness error of rotating components in aero engine with increased speed and more accurate estimation, this paper presents an enhanced method that integrates individual classification with adaptive updating searching (ICAUS) strategy. The individual classification method simulates the renewal regulations of various candidate points as iterations increase, subsequently generating new solutions for the next iteration. Additionally, an adaptive updating search zone method that varies in accordance with the increment of iterations is incorporated. These newly generated solutions are distributed within the updated search zone to ensure that the global optimal solution is not overlooked and the search zone is constrained to prevent excessive divergence, thereby enhancing computational efficiency. To validate the efficacy and accuracy of the proposed method, we utilized datasets and conducted comparative experiments using experimental methods previously studied by predecessors. The experimental results and comparisons demonstrate that the proposed ICAUS method exhibits superior convergence characteristics compared to previous studies. Across five distinct datasets, the average computation time satisfying the terminal conditions ranged from 0.0013s to 0.0018s, the standard deviation of the roundness was less than 6.2051×10–9 mm and the optimal solutions were obtained within 10 to 20 iterations, achieving the solution accuracy of ε = 10–8 mm.

Managing grid impacts from increased electric vehicle adoption in African cities

Electric vehicles are pivotal for global climate solutions, particularly in emerging markets like Africa. Despite the continent’s clean energy potential, electric vehicle adoption faces unique challenges due to inefficiencies and reliability issues of distribution power grids. Here, we analyze the impacts of expanding electric vehicle fleets—private, commercial, and paratransit—on Nairobi’s power grid. We simulate traffic patterns, charging behaviors, and transformer utilization using local mobility data. Our results show that while electric commercial and paratransit fleets may improve power system efficiency, widespread private EV adoption could significantly strain the grid, increasing peak loads and transformer aging. Smart charging strategies could mitigate these issues, reducing potential transformer replacement costs by up to 40%. Our study highlights the importance of tailored demand management and infrastructure planning to support EV growth in African cities, providing critical insights for policymakers, utilities, and transport planners to facilitate sustainable electric mobility transitions.

Global Warming OR Not？

Recent years have seen rising Earth's temperatures and a shrinking Antarctic land area. Studying factors affecting global warming and finding solutions to slow it is crucial. Using the Pettitt mutation point detection method, we examined March temperatures over the past decade and identified a significant change in March 2015. Predictive models (ARIMA and LSTM) forecast similar future temperatures, with the LSTM model showing slightly higher accuracy. Gray correlation and multiple linear regression analyses identified CO2 as the primary factor influencing global temperatures. Reducing CO2 emissions is essential to curb global warming.

Global Mild Solutions For Hilfer Fractional Neutral Evolution Equation

Abstract In this paper, we present the existence of global mild solutions for the Hilfer fractional neutral evolution equations (HFNEEs), regardless of whether the semigroups are compact or noncompact. We achieve our main results by utilizing the generalization Ascoli-Arzelà theorem, Krasnoselskii’s fixed point theorem, Laplace transform, and measures of noncompactness. To demonstrate the feasibility of our method, we provide an example.

Optimization of vehicle conceptual design problems using an enhanced hunger games search algorithm

Abstract Electric vehicles have become a standard means of transportation in the last 10 years. This paper aims to formalize design optimization problems for electric vehicle components. It presents a tool conceptual design technique with a hunger games search optimizer that incorporates dynamic adversary-based learning and diversity leader (referred to as HGS-DOL-DIL) to overcome the local optimum trap and low convergence rate limitations of the Hunger Games search algorithm to improve the convergence rate. The performance of the proposed algorithms is studied on six widely used engineering design problems, complex constraints, and discrete variables. For the HGS-DOL-DIL practical feasibility analysis, a case study of shape optimization of an electric car suspension arm from the industry is carried out. Overall, the inclusion of the OL strategy has proven its superiority in solving real-world problems, especially in solving real-world problems such as shape optimization of an electric vehicle automobile suspension arm, showing that the algorithm improves the search space improves the solution quality, and reflects its potential to find global optimum solutions in a well-balanced exploration and exploitation phase.

Optimizing Supply Chain Design under Demand Uncertainty with Quantity Discount Policy

In typical business situations, sellers usually offer discount schemes to buyers to increase overall profitability. This study aims to design a supply chain network under uncertainty of demand by integrating an all-unit quantity discount policy. The objective is to maximize the profit of the entire supply chain. The proposed model is formulated as a mixed integer nonlinear programming model, which is subsequently linearized into a mixed integer linear programming model and hence able to obtain a global solution. Numerical examples in the manufacturing supply chain where customer demand follows normal distributions are used to assess the effect of quantity discount policies. Key findings demonstrate that the integration of quantity discount policies significantly reduces total supply chain costs and improves inventory management under demand uncertainty, and decision makers need to decide a balance level between service levels and profits.

Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm

AbstractThe present study introduces a nature inspired improved liver cancer algorithm (ILCA) for solving the non‐convex engineering optimization issues. The traditional LCA (t‐LCA) inspires from the conduct of liver tumours and integrates biological ethics during the optimization procedure. However, t‐LCA facing stagnation issues and may trap into local optima. To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. For validation of ILCA, the non‐parametric and the statistical analysis are performed using benchmark standard functions. Moreover, ILCA is applied to resolve the stochastic renewable‐based (wind turbines + PVs) optimal power flow problem using a modified RER‐based IEEE 57‐bus. The objective of this work is to obtain the minimum predicted power losses and enhance the predicted voltage stability. By incorporation of renewable resources into the modified IEEE57‐bus network can help the system to reduce the power losses from 5.6622 to 3.8142 MW, while the voltage stability is enhanced from 0.1700 to 0.1164 p.u.

Blow Up of Solutions to Wave Equations with Combined Logarithmic and Power-Type Nonlinearities

In this paper, we study the initial boundary value problem for wave equations with combined logarithmic and power-type nonlinearities. For arbitrary initial energy, we prove a necessary and sufficient condition for blow up at infinity of the global weak solutions. In addition, we derive a growth estimate for the blowing up global solutions.

Optimal Energy Storage Allocation for Combined Wind-PV-EVs-ES System Based on Improved Triangulation Topology Aggregation Optimizer

To determine the ES allocation based on a specific number of EVs connected to a combined WPESS, this paper develops an ESS allocation model that considers the impact of EV charging behavior on LSD, ES allocation cost, new energy utilization rate, and self-power rate. First, several scenarios are generated using Monte Carlo sampling (MCS), and a typical day is selected through Backward Reduction (BR). Next, the Monte Carlo method is employed to generate conventional EV charging curves and optimize EV charging behavior by considering LSD and user charging costs. Subsequently, an ES capacity allocation model is developed, considering system costs, new energy utilization rate, and self-power rate. Finally, an improved triangulation topology aggregation optimizer (TTAO) is proposed, incorporating the logistic map, Golden Sine Algorithm (Gold-SA) strategy, and lens inverse imaging learning strategy. These enhancements improve the algorithm’s ability to identify global optimal solutions and facilitate its escape from local optima, significantly enhancing the optimization effectiveness of TTAO. The analysis of the calculation example indicates that after optimizing the charging behavior of EVs, the average daily cost is reduced by 204.94, the self-power rate increases by 2.25%, and the utilization rate of new energy sources rises by 2.50%, all while maintaining the same ES capacity.

A stochastic hepatitis B model with media coverage and Lévy noise

Globally, it is evident that vaccination and social media significantly influence the spread of diseases. Research has demonstrated that the spread of diseases can be affected by unforeseen events. Therefore, a stochastic hepatitis B virus (HBV) dynamical model is constructed that incorporates media coverage, while also Lévy noise is included. Itô's formula and the Lyapunov function approach are employed to analyze the existence of a positive global solution. Furthermore, the necessary conditions for disease eradication as well as long-term survival are also established to facilitate the general understanding. The statistics indicate that the media's impact is not immediate and does not lead to disease eradication. To effectively manage the spread of diseases, it is essential to employ a combination of significant noise disruption and a low rate of decline in vaccine effectiveness. Numerical simulations are conducted to demonstrate the analytical findings.

An integrated binary metaheuristic approach in dynamic unit commitment and economic emission dispatch for hybrid energy systems

The current generation portfolio is obligated to incorporate zero-emissions energy sources, predominantly wind and solar, due to the depletion of fossil fuels and the alarming rate of global warming. In the current scenario, power engineers must devise a compromised solution that not only advocates for the adoption of renewable energy sources (RES) but also efficiently schedules all conventional power generation units to balance the increasing load demand while simultaneously minimizing fuel costs and harmful emissions that are currently addressed by Unit Commitment (UC) and Combined Economic Emission Dispatch (CEED) problem solutions. However, the integration of renewable energy resources (RES) further complicates the UC-CEED problem due to their intermittent nature. Recently, metaheuristic algorithms are acquiring momentum in resolving constrained UC-CEED problems due to their improved global solution ability, adaptability, and derivative-free construction. In this research, a computationally efficient binary hybrid version of crow search algorithm and improvised grey wolf optimization is proposed, namely Crow Search Improved Binary Grey Wolf Optimization Algorithm (CS-BIGWO) by inclusion of nonlinear control parameter, weight-based position updating, and mutation approach. Statistical results on standard mathematical functions prove the supremacy of the proposed algorithm over conventional algorithms. Further, a novel optimization strategy is devised by integrating enhanced lambda iteration with the CS-BIGWO algorithm (CS-BIGWO-λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}) to solve a day-ahead UC-CEED problem of the hybrid energy system incorporating cost functions of RES. For the model, a day-ahead forecast of wind power and solar photovoltaic power is obtained by using the Levy-Flight Chaotic Whale Optimization Algorithm optimized Extreme Learning Machines(LCWOA-ELM). The proposed algorithm is tested for the UC-CEED solution of an IEEE-39 bus system with two distinct cases: (1) without RES integration and (2) with RES integration. Several independent trial runs are executed, and the performance of the algorithms is assessed based on optimal UC schedules, fuel cost, emission quantization, convergence curve, and computational time. For case 1, the proposed algorithm resulted in a percentage reduction of 0.1021% in fuel cost and 0.7995% in emission. In contrast, for test case 2, it resulted in a percentage reduction of 0.12896% in fuel cost and 0.772% in emission with the proposed algorithm. The results validate the dominance of the proposed methodology over existing methods in terms of lower fuel costs and emissions.

Global solutions and their limit behavior for parabolic inclusions with an unbounded right-hand part

We study global resolvability for parabolic inclusions with an upper semicontinuous multi-valued right-hand part of more than linear growth. Theorems about the existence of global mild solutions in different phase spaces are proved. Limit sets for the obtained global solutions in the corresponding phase spaces are investigated.

Dynamic behavior in a pursuit-evasion system with signaling mechanism

We mainly focus on the predator-prey problem associated with indirect predator taxis{ut=Δu+χ1∇⋅(u∇w)+u(1−μ1u−αv),vt=Δv−χ2∇⋅(ψ(v)∇u)+v(−1−μ2v+βu),0=Δw+v−w in a smooth bounded domain Ω⊂Rn(n≤3) with homogeneous Neumann boundary conditions, where the parameters χ1, χ2, μ1, μ2, α and β are positive. The chemotaxis sensitivity function with/without “volume-filling” effect ψ(v)=v1+σv, where σ≥0 is a constant. Compared with the well-known predator-prey system, the discussion of signaling mechanism w forms a novel feature of our system. For the case σ=0, we identify a positive constant χ0 such that the above system possesses global classical solutions with relative bound if χ2<χ0; For the case σ>0, we also show that the classical solutions of the system are globally bounded without any restrictions on system parameters. Furthermore, utilizing the Lyapunov functionals, we establish stability for the prey-only situation, the steady state of coexistence is also investigated.

Fiber To The Home Access Network Planning With Gpon Technology Using Genetic Algorithm Method

The purpose of this research is to plan the Fiber To The Home access network at a location in the city of Soe, Kupang, East Nusa Tenggara. This planning is done to facilitate the construction of the Fiber To The Home network from the center to the customer. Researchers conducted a design based on ODP sample point data based on MAPS from the company PT Arsenet Global Solution Soe Branch, the results of simulations conducted in Matlab and OptiSystem software. In this study, the best route search was carried out for the construction of the Fiber To The Home network using the Genetic Algorithm method, the results of the best route search obtained the shortest route as far as 1.6646 km from the center to the customer. Also obtained 7 ODP points with ODP routes starting from ODP points 2-3-4-5-6-7-1 with the distance of each point to the point 0.0045 km - 0.1466 km - 0.1361 km - 0.1042 km - 0.4396 km - 0.8305 km - 0.0031 km. The results of the simulation of the genetic algorithm design in matlab will be simulated in the optisystem 7.0 software to get the receiving power and Bit Eror value. The simulation results using optysystem will be a reference for calculations using the Power Link Budget method. The Power Link Budget calculation shows the total attenuation value from the center to the customer of 18.7925 dB with a power margin of 3.2 dB, Bit Eror of 5.64838 x 10-24 and Q Factor of 10.0288. The results of the calculation of attenuation and power margin prove that the planning is said to be feasible because the total planning attenuation results are below the attenuation standard set by the company PT Arsenet Global Solusi which is a maximum of 28 dB, as well as having a power margin value of more than 0 and a BER value that meets the standard.

Child leader standing on a precipice: a case study of NextGenInnov8

Learning outcomes After completion of the case study, students will be able to identify the traits required in child leadership and the ability to apply “The Whole Leadership Framework” child leadership model today, identify and discover opportunities to promote child leadership and analyse its sustainable impact and analyse how innovation clubbed with sustainability will create a competitive advantage with special reference to the innovative ultraviolet-C light sterilisation Suraksha Box. Case overview/synopsis Aditya Pachpande was a child prodigy of India, who had stunned the world with his trailblazing attitude ever since the tender age of 12. Aditya’s father, Sandeep Pachpande, a Harvard alumnus, wondered – “My son is ahead of his time. Would institutions ever acknowledge my innovative boy as a child leader? Will my child become a teen chief executive officer (CEO)? Will he ever get accepted?” Aditya leads by example as a student, changemaker, edupreneur, innovator and keynote speaker. He thinks, “Age is just a number”, but has had to shout out loud to be heard. With the nickname “Lecture man” given by his teachers and peers, he went on to contribute in endorsing skill-based experiential and discovery-based teaching-learning that addresses real-world issues and sustainable development goals. A CEO at the age of 11 years, he co-founded NextGenInnov8 Global Solutions Private Limited and NextGenInnov8 Social Foundation. Although achieving these milestones, he had to manoeuvre through several curve balls hurled at him by the system. Not the one to ever compromise on ethics, values and purpose, today he was at the crossroads – whether he should choose social change over-commercialisation of his business, simplicity and minimalism over product perfection, crowdfunding over loans or angel investors, manufacture in China or make in India just to name a few. The unstoppable Aditya, aspiring for acceptance, dreamt that someday, these policymakers and businesses would acknowledge child innovators and not write them off just because they were adolescents. Aditya, standing on a precipice, dreamt along. Complexity academic level This case has been particularly focused on postgraduate-early stage-level students pursuing business or entrepreneurial education-related programs. Supplementary materials Teaching notes are available for educators only. Subject code CSS 3: Entrepreneurship.

Green Behaviour Engagement Towards the Achievement of Sustainable Health: A Systematic Review and Bibliometric Analysis

Background The short-term actions generated by the proposed SDGs by the United Nations promote sustainability and raise the probability of finding the best global crisis solution. This research builds on previous studies that demonstrate the interconnectedness and reciprocal support of Goals 3 and 12 in their pursuit of societal transformation by altering production and consumption patterns. Focus of the Article This study set out to fill a knowledge need by examining the current state of the literature on the topic of how SDGs interact with one another. The paper primarily addressed SDGs 3 and 12. Research Question (a) How could green behaviour promote sustainable health, and what is the present status of research in this field across nations, research communities, academic journals, and professional organizations? (b) How, with research topic as the key domain, can we make progress towards Sustainable Development Goals 3 and 12 through the social marketing?. Importance to the Social Marketing Field The purpose of this paper is to provide a plan for bringing about societal transformation by means of sustained, short-term efforts in the realms of production and consumption, undertaken with the backing of the nation’s stakeholders. Doing so makes long-term success in altering health-related behaviours (prevention, protection, and persistence in the face of health hazards) more likely. Despite their best efforts to enhance the well-being of societies through social transformation, the authors believe that social marketers may be steering communities in an unsustainable direction. Method Thus, a systematic review and bibliometric analysis were conducted to ascertain the breadth of the research underlying the title by analyzing 135 Scopus publications from 74 journals from 2011–2022 and graphically presented and tabulated the trends, important authors, nations, research papers, and keyword co-occurrences. Biblioshiny, a Bibliometrix R-tool used for the purpose of scientific mapping. In addition, the alignment of study of keywords by taking social marketing discipline into account was justified through systematic review. Results Research on the interplay between SDGs and other factors is required, as 27% of the data remains unexplained. Short-term sustainable behaviours that may enhance health outcomes are combined in this study to better inform policymakers and marketers about consumers’ long-term commitment to sustainable green consumption. Recommendations for Research According to the study’s results, government agencies should create social marketing initiatives to influence the public’s behaviour and promote the health and well-being benefits associated with sustainable production and consumption. Additionally, they should provide incentives to businesses to expand their range of sustainable commodities. Businesses have a shared responsibility to develop, communicate and supply customers with the advantages of sustainable offerings, and enhance the demand for these products through a green marketing approach while reducing their prices. The ecosystem as a whole will reap the benefits of everyone’s efforts, as well as the health and happiness that comes with it. Limitations From 2011 through 2022, the Scopus database’s articles and review papers were used in the study. Additional knowledge in this area might be gained from a comparison of databases like Web of Science, Dimensions, Google Scholar, etc. The study had no geographic focus. Therefore, future research should assess this field’s national and regional potential.