We investigate an intrinsic step-jamming phenomenon at the nanometer scale on Kardar-Parisi-Zhang (KPZ)-like kinetically roughened crystal surfaces that arises during interface-limited steady crystal growth or retreat. Monte Carlo simulations using the Metropolis algorithm on a restricted solid-on-solid (RSOS) lattice model demonstrate that intrinsic step jamming persists on surfaces below 20 nm. In the present model, transport processes such as surface and volume diffusion are excluded, as are elastic interactions, step-step repulsion or attraction, and stoichiometric effects. We show that intrinsic step jamming arises from asymmetric fluctuations in atomic attachment and detachment driven by biased transition probabilities under the SOS restriction, leading to collective step congestion. Asymmetric fluctuations also determine whether adatom or hole clusters grow or recede. This mechanism bears close similarity to jamming phenomena in the asymmetric simple exclusion process (ASEP), including multi-lane variants. In contrast, symmetric thermal fluctuations generate adatom or hole clusters on terraces, thereby suppressing intrinsic step jamming. Possible routes to suppress intrinsic step jamming, including experimentally accessible strategies, are also discussed.
کارکردهای شهری به مجموعهای از کاربری های واقعی فضای شهری اشاره دارد که نهتنها پیکربندی محیط فیزیکی را توصیف می کنند، بلکه الگوهای فضایی اجتماعی و اقتصادی فعالیت های انسانی را نیز در سطح کلی منعکس می کند که بر بسیاری از فرایندهای شهری تأثیر میگذارد. ازاینرو، پژوهش باهدف تحلیل الگوهای فضایی تمرکز کارکردهای فرا شهری در کلانشهر تهران تهیهشده است. روش پژوهش به لحاظ هدف شناختی، ازنظر ماهیت پژوهش کاربردی و ازنظر نوع پژوهش توصیفی - تحلیلی است. شیوه گردآوری داده ها بهصورت کتابخانه ای، میدانی و روش تحلیل ثانویه بوده است. کارکردهای فرا شهری شامل تسهیلات شهری، صنعتی - کارگاهی، حملونقل - انبار، خدماتی - تجاری، فراغت - گردشگری، فرهنگی - تاریخی و اداری - سیاسی بر اساس سیستم LBCS است. برای تجزیهوتحلیل داده از آمار فضایی (میانگین نزدیکترین فاصله همسایگی و توزیع جهتدار) استفادهشده است. نتایج پژوهش در بخش پراکنش فضایی کارکردهای فرا شهری نشان داد که تمرکز کارکردهای کل فرا شهری در سطح مناطق شهر تهران با توجه به شاخص نزدیکترین همسایگی (408/0) و امتیاز Z آن (91/212-)، بهصورت خوشه ای توزیع یافته اند. همچنین با توجه به توزیع جهتدار، تمرکز کارکردهای کل فرا شهری در مناطق بخش مرکزی شهر تهران است و در جهت غربی - شرقی توزیعشدهاند؛ بنابراین، توازن در توزیع فضایی تمرکز کارکردهای کل فرا شهری در سطح مناطق شهر تهران مشاهده نشده و انتظار می رود تفاوت معناداری بین سطح مناطق به لحاظ برخورداری از این کارکردهای فراشهری وجود داشته باشد.
Economic growth, development, planning, Urban groups. The city. Urban sociology
Abstract Climate change has emerged as a critical and divisive global concern, intensified by international accords that mandate urgent responses. Consequently, nations worldwide are actively pursuing carbon-neutrality goals. Renewable energy adoption, green innovation, and environmental taxation are pivotal in driving decarbonization efforts, underscoring the need to evaluate their influence on carbon emissions. This study explores the roles of financial development, renewable energy, green innovation, and environmental taxation in shaping carbon emissions across 30 Chinese provinces from 2007 to 2021. The study found that renewable energy effect on emissions varies substantially. Significant reductions only appear at high adoption levels, whereas in developing provinces, renewables complement rather than replace coal, resulting in slightly increased short-term emissions. Urbanization shows a nuanced relationship; while contributing to higher emissions in the short run, dynamic estimates suggest that more urbanized provinces can reduce emissions through efficiency and planning. Financial development can initially raise emissions by scaling economic activity but is associated with lower emissions in dynamic models as mature financial systems channel capital toward cleaner technologies. Economic growth displays a negative long-run association with emissions. Human capital has short-run positive effects on emissions with offsetting longer-run effects. Green innovation transiently elevates emissions due to scale and rebound effects before verified reductions materialize. Environmental taxation shows limited short-run impact but significant long-run emission reducing effects. These insights emphasize region-specific policies that integrate sustainable finance, robust environmental regulations, grid modernization and storage to enable fossil-fuel substitution, and innovation driven strategies to achieve meaningful emission reductions.
Tatiane Lopes Duarte, Lúcia Rejane Gama Madruga, José Marcos Froehlich
O presente estudo teve como objetivo compreender como as práticas e princípios da economia solidária contribuem para a emancipação dos indivíduos e grupos participantes da economia solidária. Para isso, desenvolveu-se uma pesquisa com aporte teórico interpretativista de natureza qualitativa, e o campo da pesquisa foi o grupo de consumidores Bem da Terra vinculados à Incubadora Tecnológica de Empreendimentos Econômicos Solidários (Incubadora TECSOL). As técnicas de coleta de dados foram: entrevistas por meio de história oral temática, observação não participante e, além das entrevistas, utilizaram-se documentos. Os dados foram sistematizados por categorias que emergiram no campo, no qual foi realizada uma análise de conteúdo. No que tange aos resultados, as categorias que emergiram das entrevistas realizadas com os participantes do Grupo de Consumidores foram: Consumo consciente, processo decisório, educação, dimensão política e consciência crítica. A partir das análises, entende-se que o processo, esse caminho para a emancipação, não é linear, nem estanque, dependerá do tempo e do contexto de cada grupo. A economia solidária propicia elementos para uma emancipação, porém, cabe aqui destacar que essa emancipação está longe de ser a emancipação humana (Marx), pois a economia solidária ainda opera dentro do sistema capitalista.
Cezar Honorato, Herlandí de Souza Andrade, Francisco Lourenço de Melo
Globalization has amplified competition between companies and increasingly demanding its ability to stay ahead of its competitors who are located far beyond their city, region or country, and innovation has become essential for organizations not only to be leaders in their markets, but also to increase competitiveness and, above all, avoid its decline, a world -class innovation management process is essential. The objective of this research effort is to present a technological capability model for innovation managing for global companies that is adaptable to their realities and aimed at knowledge-intensive industries. To achieve this goal, the research method applied was action research, starting with the mapping of the literature to identify the most relevant studies, recognize the state-of-the-art, theoretical propositions and in a collaborative way with the participation of experts and professionals that act, directly or indirectly, in the innovations development; the model is co-creation under two evaluation perspectives: the first called technological functions that represent the main areas that have an impact on the success in evaluating strategies, planning, development, execution and in the innovations results in industrial companies and the second perspective that are the competence levels, which at the highest level strongly favor and support innovation in industrial companies, so that organizations can measure themselves, compare themselves with others and, through planning, achieve excellence. In addition, as the expected goal is to obtain an indicator called Innovation Technology Index (ITC index), as well as a tool that facilitates the application and its dissemination and, later, the applicability of concepts in the real environment of aerospace enterprises. The first findings demonstrate the ease of understanding and applicability of the model for companies to analyze innovation management and identify gaps to convert them into real opportunities to leverage their businesses.
Economic growth, development, planning, Social sciences (General)
Cloud computing is continually evolving, enhancing hardware technologies, improving software and enhancing business processes. A payroll management system deployed on the Cloud harnesses on-demand of delivery of computational power and database storage using cloud computing technologies. This project aims to develop and deploy a cloud-based payroll management system. The objectives of this study are: to carry out a study on the existing cloud-based payroll management system, to design a payroll data model for calculating basic salary and enables retrieval of payroll history when needed from the database, to develop and deploy a payroll management system, on the Cloud that generates earning statements, filling the gap between security infrastructure and optimal system performance harnessing cloud computing technologies. The focus was on the design, implementation and deployment, using UML diagrams to illustrate the payroll application and Google App Engine for deployment. The system analysis in comparison of a conventional payroll system and the cloud-based system is endless in terms of speed, processing power, storage capacity, universalization and pricing. The cloud-based payroll has an infinite number of advantages; all conventional payroll system is rendered obsolete as it mends all the cons.
Antonio Russo, Pasquale Scaramozzino, Andrea Zaccaria
Economic complexity measures aim to quantify the capability content or endowment of industries and territories; however, capabilities are not observable, and therefore cannot be directly used in the computations. We estimate such endowments by quantifying the quality and diversity of the skills in the occupations required in specific industries. We refer to this job-based assessment as the hidden complexity, in contrast with the usual revealed complexity, which is computed from economic outputs such as exports or production. We show that our job-based measure of complexity is positively associated to wage levels and labor productivity growth, whereas the classic revealed measure is not. Finally, we discuss the application of these methods at the territorial level, showing their connection with economic growth.
Sebastiano Taddei, Mattia Piccinini, Francesco Biral
In this work, we present a novel approach to bias the driving style of an artificial race driver (ARD) for online time-optimal trajectory planning. Our method leverages a nonlinear model predictive control (MPC) framework that combines time minimization with exit speed maximization at the end of the planning horizon. We introduce a new MPC terminal cost formulation based on the trajectory planned in the previous MPC step, enabling ARD to adapt its driving style from early to late apex maneuvers in real-time. Our approach is computationally efficient, allowing for low replan times and long planning horizons. We validate our method through simulations, comparing the results against offline minimum-lap-time (MLT) optimal control and online minimum-time MPC solutions. The results demonstrate that our new terminal cost enables ARD to bias its driving style, and achieve online lap times close to the MLT solution and faster than the minimum-time MPC solution. Our approach paves the way for a better understanding of the reasons behind human drivers' choice of early or late apex maneuvers.
We analyze loss development in NAIC Schedule P loss triangles using functional data analysis methods. Adopting the functional viewpoint, our dataset comprises 3300+ curves of incremental loss ratios (ILR) of workers' compensation lines over 24 accident years. Relying on functional data depth, we first study similarities and differences in development patterns based on company-specific covariates, as well as identify anomalous ILR curves. The exploratory findings motivate the probabilistic forecasting framework developed in the second half of the paper. We propose a functional model to complete partially developed ILR curves based on partial least squares regression of PCA scores. Coupling the above with functional bootstrapping allows us to quantify future ILR uncertainty jointly across all future lags. We demonstrate that our method has much better probabilistic scores relative to Chain Ladder and in particular can provide accurate functional predictive intervals.
Energy production and consumption is the primary source of global carbon emissions. In order to achieve the goal of Intended Nationally Determined Contributions (INDCs) in the Paris Agreement, countries around the world have set off an upsurge of energy transition. The EU has ambitious INDCs. The Energy crisis has made it accelerate the energy transition, thus promoting the development of its circular economy. However, the EU focuses on carbon leakage during this process. To address this issue and maintain the competitiveness of EU industries during the transition, the EU proposed the Carbon Border Adjustment Mechanism (CBAM). The EU proposed the background and development process of the CBAM, and organized the core content of the tripartite plan and final bill of the European Commission, European Parliament, and European Council. What's more, the framework system of the CBAM is clarified, and further analysis is conducted on the future development of CBAM of the EU based on various factors. In response to the new development of the CBAM, it is suggested that developing countries should adhere to the principle of common but differentiated responsibilities on the international front and attempt to build and improve a carbon market system to partially offset carbon tariffs. Finally, we should strengthen the research on the response plan of the EU CBAM and establish an effective communication mechanism with the EU, in order to better cope with the impact of the CBAM on the trade of developing countries in the future.
AbstractThis study investigates the equity of access to government e-learning platforms for Ethiopian primary and secondary school pupils. In order to achieve this, secondary data were accessed from the Mini-Demographic and Health Survey (Mini-DHS-2019) and the Planning and Development Commission’s document on Poverty and Economic Growth in Ethiopia. According to the findings, only a small proportion of primary and secondary school students from urban areas and economically privileged families who could afford computer, television, smartphone, and internet access can benefit from the digital library and educational televised programs. Thus, the digital learning program that was intended to increase educational accessibility exacerbated the existing inequities and intensified the pre-existing disparities between economically privileged and economically disadvantaged students and urban and rural resident students. The findings provide grounds for several recommendations on the implementation of e-learning through digital libraries and televised education programs in low-income countries like Ethiopia.
Sivan Hisham Al Jarah, Boyang Zhou, R. Abdullah
et al.
This novel study explores the driving forces and dynamics of rapid urbanization, highlighting the main causes and effects of urban explosion, environmental disruption, and city pattern transformation. This study was carried out that how urbanization and urban sprawl have influenced the structure of the city of Sulaymaniah in Kurdistan region of Iraq. This is because over the years many urban areas have experienced dramatic growth and population explosion that has resulted in the exhaustion of social amenities in the concerned communities. For this purpose, a qualitative method is used based on in-depth face-to-face interviews with local authority, including planners, architects, and experts of master planning, as well as professors in the academic institutions. This study also utilizes extensive document analysis to present the evolution of urban growth. The findings reveal that the autonomy, political conflict, non-implementation of master plans, and economic prosperity are the driving forces which are accelerating this urbanization process. It is proposed that the practical policies and strategic urban development plans are urgent requirement to control the unplanned urban growth and stimulate the desired sustainable future urban development.
Recent studies in psychology and neuroscience offer systematic evidence that fictional works exert a surprisingly strong influence on readers and have the power to shape their opinions and worldviews. Building on these findings, we study what we term Potterian economics, the economic ideas, insights, and structure, found in Harry Potter books, to assess how the books might affect economic literacy. A conservative estimate suggests that more than 7.3 percent of the world population has read the Harry Potter books, and millions more have seen their movie adaptations. These extraordinary figures underscore the importance of the messages the books convey. We explore the Potterian economic model and compare it to professional economic models to assess the consistency of the Potterian economic principles with the existing economic models. We find that some of the principles of Potterian economics are consistent with economists models. Many other principles, however, are distorted and contain numerous inaccuracies, contradicting professional economists views and insights. We conclude that Potterian economics can teach us about the formation and dissemination of folk economics, the intuitive notions of naive individuals who see market transactions as a zero-sum game, who care about distribution but fail to understand incentives and efficiency, and who think of prices as allocating wealth but not resources or their efficient use.
Budi Trianto, Evan Hamzah Muchtar, Ade Chandra
et al.
This study aims to investigate whether the organizational support provided by BAZNAS and LAZNAS has a positive impact on the success of micro business development programs and poverty alleviation. Population in this study are mustahiq who have received empowerment program from BAZNAS andLAZNAS with the total sample size are 89 mustahiq.Data were collected using questionnaire with Likert scale 1 –5 and were analyzed using Path Analysis. The results of this study indicate that the organizational support provided by LAZNAS tends to be better when compared BAZNAS. This study also found an important fact that the mustahiq micro-business development program was able to alleviate poverty.The results of this study imply that to get a maximumresult of mustahiqmicro-business development, BAZNAS must evaluate and innovate the mustahiq micro-business development program. Meanwhile LAZNAS must provide more optimum support for capital assistance and mentoring to get a maximum impact. This is the first study in comparing the micro-business development between BAZNAS and LAZNAS in Indonesia
Research and development in computer technology and computational methods have resulted in a wide variety of valuable tools for Computer-Aided Engineering (CAE) and Industrial Engineering. However, despite the exponential increase in computational capabilities and Artificial Intelligence (AI) methods, many of the visionary perspectives on cybernetic automation of design, engineering, and development have not been successfully pursued or realized yet. While contemporary research trends and movements such as Industry 4.0 primarily target progress by connected automation in manufacturing and production, the objective of this paper is to survey progress and formulate perspectives targeted on the automation and autonomization of engineering development processes. Based on an interdisciplinary mini-review, this work identifies open challenges, synergies, and research opportunities towards the realization of resource-efficient cooperative engineering and development systems. In order to go beyond conventional human-centered, tool-based CAE approaches and realize Computational Intelligence Driven Development processes, it is suggested to extend the framework of Computational Rationality to challenges in design, engineering and development.
Large scale directed energy offers the possibility of radical transformation in a variety of areas, including the ability to achieve relativistic flight that will enable the first interstellar missions, as well as rapid interplanetary transit. In addition, the same technology will allow for long-range beamed power for ion, ablation, and thermal engines, as well as long-range recharging of distant spacecraft, long-range and ultra high bandwidth laser communications, and many additional applications that include remote composition analysis, manipulation of asteroids, and full planetary defense. Directed energy relies on photonics which, like electronics, is an exponentially expanding growth area driven by diverse economic interests that allows transformational advances in space exploration and capability. We have made enormous technological progress in the last few years to enable this long-term vision. In addition to the technological challenges, we must face the economic challenges to bring the vision to reality. The path ahead requires a fundamental change in the system designs to allow for the radical cost reductions required. To afford the full-scale realization of this vision we will need to bring to fore integrated photonics and mass production as a path forward. Fortunately, integrated photonics is a technology driven by vast consumer need for high speed data delivery. We outline the fundamental physics that drive the economics and derive an analytic cost model that allows us to logically plan the path ahead.
This article is an introduction to machine learning for financial forecasting, planning and analysis (FP\&A). Machine learning appears well suited to support FP\&A with the highly automated extraction of information from large amounts of data. However, because most traditional machine learning techniques focus on forecasting (prediction), we discuss the particular care that must be taken to avoid the pitfalls of using them for planning and resource allocation (causal inference). While the naive application of machine learning usually fails in this context, the recently developed double machine learning framework can address causal questions of interest. We review the current literature on machine learning in FP\&A and illustrate in a simulation study how machine learning can be used for both forecasting and planning. We also investigate how forecasting and planning improve as the number of data points increases.