Search Results (35)

Decarbonization of the Greek economy requires significant investments in clean technologies. This will boost demand for goods and services and will create multiplier effects on output value added and employment, though reliance on imported technologies might increase the trade deficit. This study employs input–output analysis to estimate the direct, indirect, and multiplier effects of green transition investments on Greek output, value added, employment, and imports across five-year intervals from 2025 to 2050. Two scenarios are considered: the former is based on the National Energy and Climate Plan (NECP), driven by a large-scale exploitation of RES and technologies promoting electrification of final demand, while the latter (developed in the context of the CLEVER project) prioritizes energy sufficiency and efficiency interventions to reduce final energy demand. In the NECP scenario, GDP increases by 3–10% (relative to 2023), and employment increases by 4–11%. The CLEVER scenario yields smaller direct effects—owing to lower investment levels—but larger induced impacts, since energy savings boost household disposable income. The consideration of three sub-scenarios adopting different levels of import-substitution rates in key manufacturing sectors exhibits pronounced divergence, indicating that targeted industrial policies can significantly amplify the domestic economic benefits of the green transition. Full article

People living with HIV (PLHIV) in under-resourced rural regions face intersecting social and structural barriers that intensify their vulnerability. This pilot study explored how overlapping marginalized identities and socioeconomic hardship shape experiences of discrimination among PLHIV in Southern Illinois. Twenty-two participants completed a community-informed survey that captured racial, sexual, and gender identities alongside indicators of stigma across healthcare, housing, employment, and community settings. The findings reveal that most participants experienced at least one form of discrimination, with the highest burden concentrated among those identifying as Black, Nonbinary, Gay/Lesbian, or low-income. Discrimination was particularly prevalent in healthcare and housing environments. Importantly, poverty and housing instability were not just common but appeared to amplify the experience of stigma, compounding the effects of identity-based marginalization. These results highlight the urgent need for integrated, affirming, and structurally responsive interventions tailored to the realities of multiply marginalized PLHIV in rural areas. Future research and services must consider the interplay of identity and economic precarity in order to promote equitable care and support. Full article

This study examines the asymmetric effects of foreign worker employment and low educational attainment on labor productivity across Malaysia’s three main economic sectors—agriculture, industry, and services—from 1991 to 2019 using the nonlinear autoregressive distributed lag (NARDL) model. Three sectoral models are estimated to capture how overdependence on foreign workers and low-skilled local labor influences productivity. Model 1 for agriculture underscores positive variations vis-à-vis how foreign worker employment boosts agricultural productivity in both the short and long term. However, negative variations lead to diminished productivity in the long run. Primary education negatively affects long-term agricultural productivity. In Model 2 for industry, neither foreign worker employment nor low educational attainment significantly affects productivity. Model 3 for services reveals a short-term boost in productivity with increased foreign workers’ employment, whereas reduced employment enhances long-term productivity. The absence of formal education is detrimental to long-term service productivity, while primary education affects it negatively in the short term. NARDL multiplier graphs and Wald tests confirm significant long-run asymmetric effects of foreign labor in the agriculture and services sectors. The findings highlight the need for Malaysia to reduce reliance on low-skilled labor and accelerate its transition toward a high-skilled workforce to sustain productivity growth and economic competitiveness. Full article

Food grain production has multiplied over the last two decades in India, but natural resources are overexploited in modern farming. Farmers, especially those with small and marginal holdings, are suffering losses more often than not, the cost of production is increasing year after year, and profits are not up to the necessary levels. To address such challenges, there has been a broad recognition of the importance of employing farming system approaches in research. The cultivation of cropping systems with orchard crops and livestock components can play a significant role in the optimal utilization of resources, enhancing energy use efficiency as well as the eco-efficiency index, and reducing carbon footprints. This study was carried out to create a suitable IFS model with high economic and energy efficiency for small-holder farmers in India’s southern plateau and hills with a negligible impact on the environment. The following were the seven models: M₁: Rice − Groundnut; M₂: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Bt cotton + Greengram (1:2) − Maize; M₃: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Pigeonpea + Maize (1:3) − Sunhemp; Napier grass, Sheep (5 + 1); M₄: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Bt cotton + Greengram (1:2) − Maize, Pigeonpea + Maize (1:3) − Sunhemp, Poultry unit; M₅: Guava, Hedge Lucerne, Napier grass, Bt cotton + Greengram (1:2) − Maize, Sheep (5 + 1); M₆: Guava, Bt cotton + Greengram (1:2) − Maize, Rice − Groundnut, Poultry; M₇: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Pigeonpea + Maize (1:3) − Sunhemp; Napier grass, Hedge lucerne, Poultry (100), Sheep (5 + 1). Model M₁ was used to represent the local region, and the other models were compared in terms of economics, energetics, greenhouse gas emissions, and employment creation. The M₇ and M₃ models, according to the results, have higher economic efficiency (₹342.3 day⁻¹, ₹263.7 day⁻¹), increase output energy (228,529 and 183,231 MJ) net energy (258,184 and 198,920 MJ), produce net negative emissions (−2842 and −2399 kg CO₂ eq.), and create jobs year-round (112.5 and 110.5 man days year⁻¹), respectively. This is primarily because they have multiple highly efficient components that make them viable for Telangana’s small and marginal farmers. Full article

The effective discrimination of targets from backgrounds in environments characterized by a low signal-to-clutter ratio (SCR) is paramount for the advancement of infrared small target detection (IRSTD). In this work, we propose a novel detection framework predicated on low-rank sparse decomposition (LRSD), incorporating an improved logarithmic norm and a mechanism for sparse structure refinement, herein referred to as the improved logarithmic norm and sparse structure refinement (ILN-SSR). The ILN-SSR framework more precisely characterizes the sparse properties of both the background and the target, enabling a more effective distinction between the target and its background. Initially, our approach entails the utilization of an improved logarithmic norm to precisely estimate the low-rank attributes of the infrared image background. This is followed by the employment of a linear sparse regularization term alongside a target-traits-based sparse regularization term aimed at meticulously identifying targets within sparse regions and refining the sparse structure. Subsequently, we combine these components into the ILN-SSR framework, which formulates IRSTD as an optimization problem. The resolution of this framework is achieved through the implementation of the alternating direction method of multipliers (ADMM). The efficacy of the proposed framework is corroborated through the analysis of six image sequences. Comprehensive experimental assessments affirmed the framework’s substantial robustness in navigating various complex backgrounds. Full article

This paper applies selected methodologies for the measurement of the environmental and economic sustainability of the Peggy Guggenheim Collection (PGC) in Venice with a view to assessing the PGC’s sustainability and commitment to implementing selected SDGs. To assess environmental sustainability, a life cycle assessment (LCA) has been carried out. The museum is conceptualized as a “firm” that produces several outputs and needs several inputs. The results provide the number of annual CO₂e (and other pollutants) emissions linked to the regular activity of the museum. The environmental cost (in EUR), linked to the impacts obtained from LCA, has been calculated. To assess economic sustainability, a survey and econometric methods were used to value services directly generated by the museum, and input/output methods were used to compute the direct and indirect impacts on the local economy. Nonetheless, PGC visitors (those who travel to Venice with the main objective of visiting the PGC) contribute to around 1.2%/1.4% of Venice’s GDP. The results from input–output tables show that, although the final demand generated by the PGC’s own activities amounted to about EUR 620 million in 2022, the economic benefits of the PGC beyond this final demand are significant and very positive due to carry-over effects. Specifically, the PGC leads to an increase in GDP of around EUR 1.200 million, with a multiplier of 1.9. In terms of employment, around 8200 jobs are associated with the presence of the PGC. The net public finance revenue also clearly benefits, with a net income of around EUR 150 million in 2022. Comparing both the environmental and economic impacts of the PGC, one can conclude that the annual activities performed by the museum are highly sustainable, with the economic pillar strongly offsetting the costs generated using natural resources. The creation of economic value, therefore, is generated in respect of environmental boundaries, even if some minor flaws can be highlighted. The connection between museums and sustainable development goals is highly recognized. The findings show the PGC’s commitment to achieving and implementing selected SDGs, including SDG 4, SDG 11, and SDG 16, by implementing actions and strategies that are aligned with these goals. Full article

This article proposes a novel design for an in-memory computing SRAM, the DAM SRAM CORE, which integrates storage and computational functionality within a unified 11T SRAM cell and enables the performance of large-scale parallel Multiply–Accumulate (MAC) operations within the SRAM array. This design not only improves the area efficiency of the individual cells but also realizes a compact layout. A key highlight of this design is its employment of a dynamic aXNOR-based computation mode, which significantly reduces the consumption of both dynamic and static power during the computational process within the array. Additionally, the design innovatively incorporates a self-stabilizing voltage gradient quantization circuit, which enhances the computational accuracy of the overall system. The 64 × 64 bit DAM SRAM CORE in-memory computing core was fabricated using the 55 nm CMOS logic process and validated via simulations. The experimental results show that this core can deliver 5-bit output results with 1-bit input feature data and 1-bit weight data, while maintaining a static power consumption of 0.48 mW/mm² and a computational power consumption of 11.367 mW/mm². This showcases its excellent low-power characteristics. Furthermore, the core achieves a data throughput of 109.75 GOPS and exhibits an impressive energy efficiency of 21.95 TOPS/W, which robustly validate the effectiveness and advanced nature of the proposed in-memory computing core design. Full article

The transition to sustainability is a complex process that requires a clear understanding of its drivers and barriers. The paper explores the impact of different social and economic factors on sustainable development as a holistic process. The research involved data from 27 EU member states during 2012–2020. Hausman specification and Breusch and Pagan Lagrangian multiplier test were used to select the proper econometric model, which led to the use of generalized least squares regression with random effects to estimate the sustainable development drivers in the EU. The results suggested that corruption has no statistically significant impact on sustainability, whereas economic freedom increases Sustainable Development Goals (SDG) Index. Our empirical results demonstrated that GDP per capita inhibits sustainability transition, which could be a case of the environmental Kuznets curve hypothesis. Unemployment has a negative impact on sustainable development; however, employment in science and research is its driver. It was unfolded that median income per capita and life expectancy have a statistically significant positive impact on the SDG Index. Following these findings, a wide range of policy recommendations was suggested. They include but are not limited to: ensuring economic freedom, human capital development, digitalization of public services, and lifelong education promotion. Full article

Power losses (PL) are one of the most—if not the most—vital concerns in power distribution networks (DN). With respect to sustainability, distribution network reconfiguration (DNR) is an effective course of action to minimize power losses. However, the optimal DNR is usually a non-convex optimization process that necessitates the employment of powerful global optimization methods. This paper proposes a novel hybrid metaheuristic optimization (MO) method called the chaotic golden flower algorithm (CGFA) for PL minimization. As the name implies, the proposed method combines the golden search method with the flower pollination algorithm to multiply their benefits, guarantee the best solution, and reduce convergence time. The performance of the algorithm has been evaluated under different test systems, including the IEEE 33-bus, IEEE 69-bus, and IEEE 119-bus systems and the smart city (SC) network, each of which includes distributed-generation (DG) units and energy storage systems (ESS). In addition, the locations of tie-switches in the DN, which used to be considered as given information in previous studies, are assumed to be variable, and a branch-exchange adaption is included in the reconfiguration process. Furthermore, uncertainty analysis, such as bus and/or line fault conditions, are studied, and the performance of the proposed method is compared with other pioneering MO algorithms with minimal standard deviations ranging from 0.0012 to 0.0101. The case study of SC is considered and the obtained simulation results show the superiority of the algorithm in finding higher PL reduction under different scenarios, with the lowest standard deviations ranging from 0.012 to 0.0432. Full article

The development of the digital economy has alternative and complementary effects on employment in the agricultural labor force. While replacing a large part of the agricultural labor force, digital agricultural technology is also expected to create new jobs and multiply the economic development effect. Finally, it will have a large number of positive spillover effects on rural development. To better understand the effects and relationships of digital agriculture on agricultural labor employment in this process, we gathered microdata from 1098 agricultural laborers in 122 counties (cities and districts) of 16 cities in Shandong Province, China. Compared with previous research, the advantage of our study is that structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) are jointly applied to assess the effects of digital agriculture on agricultural labor force employment and the combinatorial path of inter-effect relationships. The analysis results demonstrate that the effects of digital agriculture on agricultural labor force employment mainly include substitution, complementary, flywheel, agglomeration, structural, synergistic, and spillover effects. Through substitution and complementing effects in a chain reaction, which have effects through intermediate links, the first six effects can lead to spillover effects. We determine two modes with a total of eight configurations that can trigger the spillover effect of digital agriculture on agricultural labor force employment. Therefore, it is necessary to choose an effective combination of paths to improve the utilization rate of agricultural resources and promote the diffusion of improved agricultural technologies. If the positive effects of digital agriculture on agricultural labor force employment are reasonably exerted, the development of sustainable agriculture could be accelerated. This would promote the overall development of the agricultural labor force and lead to the revitalization of rural areas and the integration of urban and rural areas. Full article

As China reaffirms its commitments to limit the climate change risk and improve air quality, a combination of new policy and technology opportunities is presenting itself. A national emission trading scheme (ETS) begun in 2017 and is showing great promise, creating decentralized incentives for cost effective pollution mitigation. At the same time, sustained energy sector innovation is driving the costs of renewable electric power generation below those of fossil fuel substitutes. Early economic evidence of ETS measured pollution reductions, but has not addressed important economy-wide net benefits. This paper focuses on technology and energy cost savings and is the first to account for three multiplier effects—shifting consumption patterns, job growth, and the benefits of induced productivity growth—that would result from accelerated renewable electricity deployment in China. Results from a dynamic recursive computable general equilibrium model for 2017 to 2030 show that expanding renewable deployment can interact with the ETS to slash GHG emissions, as well as energy costs, stimulating significant long-term economic growth. These results suggest that China should accelerate its clean energy transition, not only for the air-quality and climate benefits, but to fulfill the energy sector’s potential to promote innovation, employment, and economic growth. Full article

In 2020, coronavirus disease (COVID-19) left around 81% of the global workforce, nearly 2.7 billion workers, affected. Employment in China was the first to be hit by COVID-19. The Regional Comprehensive Economic Partnership (RCEP) is expected to bring dynamism to China’s employment market in an era of long COVID-19. This study aims to examine the number of sectoral jobs that the RCEP will create in China, with the number of skilled or unskilled labour employed in each sector. The exogenous shocks to the RCEP can be reflected in the number of jobs created through multipliers based on a social accounting matrix compiled from China’s input-output tables in 2017, combined with the employment satellite accounts compiled. The results show that the RCEP is expected to create over 17 million potential jobs in China, with unskilled labour accounting for 10.44 million and skilled labour for 6.77 million. It is even expected that there will be job losses in the metalworking machinery sector. The contribution of this paper can serve as a reference for policies to protect vulnerable sectors, further open up trade markets and strengthen cooperation among RCEP members as important measures to address the employment impact of long COVID-19. Full article

Transport security is a leading strategic issue in an archipelago country with many back entrances to secure. Both ports and shipping lanes are significant for multinational investment activities. This paper aims to determine the impact of maritime transport security and the expectations of stakeholders on Indonesia’s economic growth. This paper used quantitative and qualitative approaches. The analytical technique in the quantitative method used Input-Output analysis, and for the qualitative method, Focus Group Discussions (FGD) activities were held and analyzed by NVivo. The results of the quantitative approach showed an impact of changes in GDP by 21.99 billion IDR and an increase in the income of workers by 0.13 billion IDR. The other 53 sectors changed the output by 36.96 trillion IDR, the workforce by 79,072 people, and labor income by 860.31 billion IDR. The qualitative method explained that the Stakeholder Synergy has the most significant contribution among stakeholders to creating a better maritime transport security ecosystem. The multiplier impact on all sectors, income, and employment, will always appear in a public policy. Full article

COVID-19 is a fast-invading virus that quickly invaded the human body and made no human activity immune to its infections. The purpose of this study is to simulate the effects of COVID-19 on employment behaviour and vaccination’s weight in the recovery process. Based on quarterly panel data from 43 nations from 2018 to 2020, we built an adaptive employment model. The major findings demonstrate that COVID-19 has negative and large net and second effects, with parameters of −7049 and −15,768 employees each quarter for 100,000 infected people, respectively. While immunization has a positive net effect of 10,900 employees every quarter, it has a negative second effect of −29,817 employees. This last result may look strange, but it is rational and demonstrates that immunizations modify employees’ behaviour toward prevention measures, leading to actions such as resuming mobility, reopening, cancelling confinement, and so on, even though COVID-19 continues to spread. Demand, the labour force, the short-term multiplier, and immunization appear to have a positive and large impact on employment behaviour, while average labour productivity appears to have a negative impact. Full article

This paper presents a high-speed and low-area accelerator architecture for shared key generation using an elliptic-curve Diffie-Hellman protocol over $GF\left(2^{233}\right)$. Concerning the high speed, the proposed architecture employs a two-stage pipelining and a Karatsuba finite field multiplier. The use of pipelining shortens the critical path which ultimately improves the clock frequency. Similarly, the employment of a Karatsuba multiplier decreases the required number of clock cycles. Moreover, an efficient rescheduling of point addition and doubling operations avoids data hazards that appear due to pipelining. Regarding the low area, the proposed architecture computes finite field squaring and inversion operations using the hardware resources of the Karatsuba multiplier. Furthermore, two dedicated controllers are used for efficient control functionalities. The implementation results after place-and-route are provided on Virtex-7, Spartan-7, Artix-7 and Kintex-7 FPGA (field-programmable gate arrays) devices. The utilized FPGA slices are 5102 (on Virtex-7), 5634 (on Spartan-7), 5957 (on Artix-7) and 6102 (on Kintex-7). In addition to this, the time required for one shared-key generation is 31.08 (on Virtex-7), 31.68 (on Spartan-7), 31.28 (on Artix-7) and 32.51 (on Kintex-7). For performance comparison, a figure-of-merit in terms of $\frac{throughput}{area}$ is utilized which shows that the proposed architecture is 963.3 and 2.76 times faster as compared to the related architectures. In terms of latency, the proposed architecture is 302.7 and 132.88 times faster when compared to the most relevant state-of-the-art approaches. The achieved results and performance comparison prove the significance of presented architecture in all those shared key generation applications which require high speed with a low area. Full article