Abstract Background Malaria remains one of the most pressing public health challenges in Sub-Saharan Africa (SSA), which continues to shoulder over 90% of the global burden of malaria cases and deaths. Despite major investments in control and treatment, the region faces persistent transmission heterogeneity, with pockets of low but sustained incidence that often fuel larger seasonal outbreaks. Each year, during the hot and dry season, multiple low-transmission hotspots—ranging from 3 to 150 cases per 10,000 person-weeks—emerge in many peri-urban and rural–urban fringe zones in western SSA. These hotspots frequently precede widespread outbreaks that occur with the onset of the rainy season. While intensive malaria control programs have reduced incidence in many high-transmission areas, the persistence of such low-transmission hotspots throughout the dry months remains poorly understood. Methods In this study, we focus on Ouagadougou, the capital of Burkina Faso, where malaria incidence demonstrates striking spatiotemporal patterns. We hypothesize that seasonal rural–urban migration of labourers—driven largely by agricultural and economic cycles—plays a pivotal role in sustaining dry-season transmission, seeding subsequent rainy-season epidemics. To examine this hypothesis, we develop a data-driven malaria model and analyze with statistical inference methods to compare the impacts of seasonal, regular, and permanent migration patterns, using empirical incidence and mobility data. Results Our analysis indicates that seasonal migration most accurately explains the low-transmission endemicity in dry months and their amplification into widespread rainy-season outbreaks. High seasonal migration maintained a low but persistent level of transmission, preventing local fade-out, and significantly intensified transmission once favourable ecological conditions returned during the rains. These findings demonstrate how cyclical patterns of human mobility can drive malaria persistence even in periods otherwise unsuitable for transmission. Conclusion These findings highlight the importance of incorporating human mobility, particularly seasonal labour migration, into malaria transmission models and control strategies. From a global health perspective, accounting for mobility-driven persistence mechanisms can strengthen malaria elimination programs across Sub-Saharan Africa, where seasonal migration is widespread. By integrating migration dynamics into intervention planning, policymakers can better anticipate epidemic risk and target resources to vulnerable communities, thereby moving closer to the long-term goal of malaria elimination.
Since 2020, Douyin, an app known for its interactive entertainment and vibrant youth cultures, has risen to dominance in the retail sector. Douyin stands out by making paid traffic a significant revenue stream alongside commissions. This strategy, which restricts organic growth, compels sellers to make additional investments in traffic. Drawing from Douyin walkthroughs and the company's business development presentations, this article analyzes how audience attention and platform traffic are manufactured and integrated with retail in the context of China's recent national policy that positions data as a factor of production equal to labor, land, technology, and capital. In contrast to Instagram, traffic conversion into sales takes precedence over product visibility on Douyin. In this process, Douyin actively uses user data to manufacture high-traffic keywords with buying intent. This involves measurements employing surveillance technologies that span image and speech recognition, keywords, performance metrics, and pricing algorithms. The article argues that Douyin e-commerce cannot be fully explained by the current visibility research paradigm centered on metrics such as likes, shares, and comments, which are considered indications of interests and preferences. It is suggested that Douyin uses historical data to invoke momentary interests and produce desired user actions for conversion. Traffic investment alone cannot result in the conversion of momentary interests into sales; it needs to be combined with pricing that incorporates discounts, coupons, and reductions. The integration of traffic investment with pricing strategy has emerged as a dominant e-commerce practice that fosters retail growth.
The orientation of Ukrainian enterprises towards the European Union market is emerging as a pivotal driver of economic renewal and integrative development of the state. The present article examines the trajectory of strategic restructuring of Ukrainian enterprises, with a particular emphasis on innovation management and the attraction of venture capital, as mechanisms for ensuring effective access to the EU market. The relevance of the research is determined by the provision of duty-free access under the Association Agreement and the Deep and Comprehensive Free Trade Area (DCFTA). This provides enterprises with incentives to modernise production processes and enhance competitiveness. However, it also requires compliance with stringent quality benchmarks and regulatory frameworks. The objective of this study is to provide empirical evidence to support the notion of strategic restructuring of Ukrainian enterprises within the context of the proposed Smart Value Europe strategy. This strategy calls for a transition from a raw-material export model to one grounded in innovation, high technology, and value-added production, aligned with EU market requirements. The methodological framework utilised is founded upon strategic analysis, with the objective of identifying priority modernisation pathways for Ukrainian enterprises in the context of European market entry. A comparative assessment of EU market requirements enabled the correlation of European quality and certification standards with the current capacities of domestic producers. The institutional approach was employed to assess the regulatory environment, with a particular focus on the implications of the Association Agreement and the DCFTA regime for business process transformation. Furthermore, elements of case study analysis were applied, allowing the tracing of practical instances of venture investment attraction and export infrastructure development. The application of these methodological instruments facilitated the formation of a systemic perspective on the strategic orientations of Ukrainian enterprises in the process of integration into the EU internal market. The findings indicate that investments in modernisation, international product certification, export infrastructure development, and the utilisation of support mechanisms offered by European institutions are critical factors for successful integration. The study's practical significance lies in formulating recommendations to enhance the innovative capacity of Ukrainian enterprises, broaden export channels and stimulate employment. Implementing the proposed strategic approaches is expected to reinforce enterprises' international competitiveness and foster sustainable development within the broader context of European integration.
Traditional quantitative investment research is encountering diminishing returns alongside rising labor and time costs. To overcome these challenges, we introduce the Large Investment Model (LIM), a novel research paradigm designed to enhance both performance and efficiency at scale. LIM employs end-to-end learning and universal modeling to create an upstream foundation model capable of autonomously learning comprehensive signal patterns from diverse financial data spanning multiple exchanges, instruments, and frequencies. These "global patterns" are subsequently transferred to downstream strategy modeling, optimizing performance for specific tasks. We detail the system architecture design of LIM, address the technical challenges inherent in this approach, and outline potential directions for future research. The advantages of LIM are demonstrated through a series of numerical experiments on cross-instrument prediction for commodity futures trading, leveraging insights from stock markets.
Michela Taufer, Valerio Pascucci, Christine R. Kirkpatric
et al.
The urgent need for data democratization in scientific research was the focal point of a panel discussion at SC23 in Denver, Colorado, from November 12 to 17, 2023. This article summarizes the outcomes of that discussion and subsequent conversations. We advocate for strategic investments in financial, human, and technological resources for sustainable data democratization. Emphasizing that data is central to scientific discovery and AI deployment, we highlight barriers such as limited access, inadequate financial incentives for cross-domain collaboration, and a shortage of workforce development initiatives. Our recommendations aim to guide decision-makers in fostering an inclusive research community, breaking down research silos, and developing a skilled workforce to advance scientific discovery.
The article is about the reasoning importance and necessity of harmonizing the goals and methods of development and reform of education/science in Ukraine with development of priority economic sectors in Ukraine, including fixing the education and science (as an element of the knowledge economy) as priorities sectors in the structure of the Ukrainian economy.
The author characterized indicators of Ukrainian economics development by type of: economics activity, capital investments, turnover of industrial enterprises, employment of population. All these characteristics show that in the last decades, the scientific and technical sectors of industry, according to most characteristics, occupied the smallest share in the structure of the Ukrainian economy. However, the sectors of wholesale and retail trade, the agricultural sector and the raw material sectors of industry had actively developed in Ukraine.
Also, the author pays attention to the problems in education and science in Ukraine: to respect and demand for these professions in the Ukrainian society and to financing support.
Reforms and support of education/science must be harmonized with the economic structure of Ukraine. They must be fixed on priority sectors for economic development. The education/science must be fixed as priority sectors like elements of the knowledge economy. The goals and objectives, the internal reforms and development in education/science must be oriented to the needs of the structure of the Ukrainian economy.
Implementation of these steps will help improve the quality of educational and scientific activities, the effect of their impact on economic development in Ukraine, and the competitiveness of the Ukrainian state like knowledge economy will grow.
Objective: The purpose of the article is to determine which economic factors, specifically those related to labour and capital, have a more significant impact on the level of industrial automation. This assessment is based on robot density per 10 000 employees in the manufacturing sector.
Research Design & Methods: The empirical insights came from a broad array of statistical data spanning from 2000 to 2022, acquired from reputable international institutions. The study employs a methodological framework that integrates a review of pertinent literature, deductive reasoning, and an in-depth comparative analysis of selected time series. The central element of the research is the application of multiple regression analyses, primarily focusing on data from 2020 for 27 nations progressing in manufacturing automation.
Findings: Analysis of time series data on multifactor, labour, and capital productivity in countries with the highest robot densities shows a complex interplay between labour and capital productivity in the realm of industrial automation. Multiple regression analysis, particularly Model 1, substantiated hypothesis H2, revealing that capital-related factors, specifically gross domestic expenditures on R&D and foreign direct investment, emerged as statistically significant predictors of robot density (RD), both exhibiting positive correlations. This underscores the pivotal role of capital investments and technological advancements in fostering automation. Further analysis using Model 2, aggregating labour and capital variables, reaffirmed the predominance of capital factors in influencing industrial automation. The pronounced positive association between the capital index (CAP) and RD highlights the critical influence of capital-related variables, such as technological innovations and investments, in driving the adoption and density of industrial robots, thereby underscoring the foundational role of capital in the advancement of automation in the manufacturing sector.
Implications & Recommendations: The findings highlight a bidirectional influence between automation and productivity in the manufacturing sector, with capital access and utilization playing a pivotal role in automation disparities across economies. Economies reliant on labour-intensive methods lag in automation, underscoring the insufficiency of abundant labour for promoting automation. Instead, capital availability, particularly through R&D spending and foreign investment, emerges as crucial for advancing industrial automation. This necessitates a strategic realignment, where policymakers and industry leaders must prioritize capital investment and technological innovation as key automation enablers. The study calls for comprehensive strategies that emphasize capital investment, technological innovation, skill development, and quality education to effectively engage in the global automation landscape.
Contribution & Value Added: Contrary to the prevalent focus in existing literature on automation’s impact on socio-economic factors, particularly labour productivity, this research adopts a reverse perspective by examining the influence of labour and capital factors on automation progression. The study’s novel approach, asserting the paramountcy of capital in driving automation, suggests that active participation in the global automation landscape necessitates comprehensive efforts encompassing R&D investment, FDI attraction, workforce skill enhancement, and investment in quality education.
Mohammadamin Khalili, Mostafa Sargolzaei, Mohammadhashem Botshekan
et al.
Purpose: Examining the interaction between the banking sector, particularly asset-liability management in the banking system, and the other sectors of the macro-economy is of special importance. This research aims to enrich the literature on this subject and apply it to the Iranian economy and banking system. The main focus of the study, unlike other research that focuses on economic variables, is on the banking sector. It has been attempted to harmonize and align the banking sector especially with the Iranian banking system so that the banking system managers and policymakers can optimize the asset and liability management of banks in interaction with the macroeconomic sectors efficientlyMethodology: The model described in this research is an extension of the models proposed by various researchers. In this model, the economy consists of several agents, each of which maximizes its own objective function subject to budget constraints. There are two types of households in the model including savers and borrowers. There are also two types of firms including intermediary producers and final goods producers. Intermediary firms operate under monopolistic competition and can set prices. They rent physical capital from capital goods firms and sell their intermediary goods to final goods producers. Final goods producers operate under perfect competition but with fixed prices. They purchase intermediate goods, package them into undifferentiated final goods, and sell them to households. Intermediary firms can partially finance their investment by borrowing from banks with surplus resources. The banking system in this research is based on the developed model of Gerali et al. (2010), Dib (2010), and Giri (2018). Retail banking is directly connected to firms and households. Banks with surplus resources may provide their surplus funds to banks with deficits through interbank channels to meet their funding needs. Surplus banks receive deposits from saver households and may invest a portion of their deposits in the interbank market or in government bonds. Monetary policy is also regulated by the central bank.Findings and Discussion: We measured the effects of four macroeconomic shocks on asset-liability management variables using our DSGE model.Total factor production shock: A positive productivity shock can have a positive effect on the bank capital in the short term. This is because increasing productivity can lead to higher economic growth, which can increase banks' profitability and, thus, increase their accumulated profits. By maintaining more profits of banks, their capital situation improves. In the long term, however, this trend decreases and approaches its stable conditions. A positive shock increases the productivity of economic activities and leads to an increase in the demand for loans, investments and consumer goods. This, in turn, leads to an increase in bank deposits, as people deposit some of their surplus savings in the banking system. A positive productivity shock leads to an increase in the interbank rate because banks increase their liquidity to finance new lending and investment opportunities that result from improved economic conditions.Monetary policy shock: A positive monetary policy shock can lead to an increase in economic growth and confidence in the economy, which can lead to an increase in savings and ultimately support the level of deposits. The interbank interest rate will decrease with a positive monetary policy shock.Investment shock: An increase of investment in the short term has a positive effect on bank capital because banks may see an increase in demand for loans and other financial services. This can lead to higher profits and capital accumulation for banks, which can support their financial health and stability. However, if the investment shock does not continue in the long term or leads to increased risk-taking by banks, it can eventually destroy their capital and threaten the financial stability. The amount of deposits is also affected by the investment shock, similar to loans.Public expenditure shock: A public expenditure shock leads to an increase in government spending on infrastructure or other projects that stimulate economic activities and increase bank lending, leading to higher bank profits and an increase in bank capital in the long run. The increase in public spending in the short term that is financed through higher taxes can reduce the disposable income for households and businesses. This leads to a decrease in savings and a decrease in the deposits in banks. In the long run, however, the public expenditure shock through increased government borrowing leads to higher interest rates and tighter monetary policies, which reduce economic activities and reduce deposits. A positive public spending shock induces an increase in the interbank rate in the short term because an increase in government spending can create upward pressure on the inflation, which, in turn, can cause an increase in the interbank rate. In the long term, the increase in public spending can cause more economic growth, which, in turn, can increase the demand for loans and deposits, and finally the interbank rate due to the competition of banks.Conclusions and policy implications: The research findings indicate that macroeconomic shocks have noticeable effects on key variables such as bank capital, loans, deposits, interbank arrears, policy rates, and interbank interest rates. Specifically, it was found that a positive productivity shock leads to an increase in loans and deposits in the long run, while a positive monetary policy shock results in a decrease in policy rates and an increase in interbank liquidity. Additionally, a positive government expenditure shock has an expansionary effect on bank lending and may lead to a reduction in interest rates in the long term. This study provides insights into how macroeconomic shocks can influence the asset and liability management of banks, which can be valuable information for policymakers and regulators to maintain financial stability. In general, the research findings demonstrate that the banking system is sensitive to macroeconomic conditions, and a comprehensive understanding of these relationships is vital for proper bank risk management.
We study the asymptotic behavior of ruin probabilities, as the initial reserve goes to infinity, for a reserve process model where claims arrive according to a renewal process, while between the claim times the process has the dynamics of geometric Brownian motion-type Itô processes with time-dependent random coefficients. These coefficients are ``reset" after each claim time, switching to new values independent of the past history of the process. We use the implicit renewal theory to obtain power-function bounds for the eventual ruin probability. In the special case when the random drift and diffusion coefficients of the investment returns process remain unchanged between consecutive claim arrivals, we obtain conditions for existence of Lundberg's exponent for our model ensuring the power function behaviour for the ruin probability.
Rowan Hoogervorst, Evelien van der Hurk, Philine Schiewe
et al.
Bus Rapid Transit (BRT) systems can provide a fast and reliable service to passengers at low investment costs compared to tram, metro and train systems. Therefore, they can be of great value to attract more passengers to use public transport. This paper thus focuses on the BRT investment problem: Which segments of a single bus line should be upgraded such that the number of newly attracted passengers is maximized? Motivated by the construction of a new BRT line around Copenhagen, we consider a setting in which multiple parties are responsible for the financing of different segments of the line. As each party has a limited willingness to invest, we solve a bi-objective problem to quantify the trade-off between the number of attracted passengers and the investment budget. We model different problem variants: First, we consider two potential passenger responses to upgrades on the line. Second, to prevent scattered upgrades along the line, we consider different restrictions on the number of upgraded connected components on the line. We propose an epsilon-constraint-based algorithm to enumerate the complete set of non-dominated points and investigate the complexity of this problem. Moreover, we perform extensive numerical experiments on artificial instances and a case study based on the BRT line around Copenhagen. Our results show that we can generate the full Pareto front for real-life instances and that the resulting trade-off between investment budget and attracted passengers depends both on the origin-destination demand and on the passenger response to upgrades. Moreover, we illustrate how the generated Pareto plots can assist decision makers in selecting from a set of geographical route alternatives in our case study.
Purpose – The hospitality industry is one of Ghana's key economic contributors. It is an industry that has significant indigenous investment. The sector also brings in foreign exchange for Ghana. In 2019, it generated $325 m through tourist visits. This makes the hospitality industry critical for the attraction of foreign direct investments. The research was therefore aimed at examining the business environment of the hospitality industry for evidence of negative factors that can hamper its greater contribution to the attainment of Goal 8 of the 17 Sustainable Development Goals of the UN such as guest-bullying and the incivility in hospitality occupations. Design/methodology/approach – A convenience sampling method was used to select 346 samples out of the accessible 3,500 targeted population from 38 hotels in the capital city of Ghana, Accra, comprising of junior to senior employees of various departments. The questionnaires were scripted from a paper-based to digital format supported by the Opine software installed on tablets and smartphones, to enable complete adherence to all coronavirus disease 2019 (COVID-19) safety protocols. The study used a regression to ascertain the relationships between the dependent variables and the independent variables. Findings – The study found the “Level of Permissiveness for Guests” positively and significantly “encouraged” guests to bully staff, while “Management and Staff Laxity” negatively but significantly explained guest bullying behaviour. Originality/value – The study makes the first attempt in context to shed light on workplace bullying which represents one of the main factors that can inhibit or erode any gains or attempts to foster the achievement of Goal 8 of the 17 Sustainable Development Goals of the UN which is to create “Decent Work and Economic Growth”.
The purpose of this study is to propose a new index to measure and reflect China's investment activity in time, and to analyze the changes of China's investment activity in the past five years. This study first uses the NEZHA model for semantic representation, and expand the indicator system based on semantic similarity. Then we calculate China's investment activity index by using the network search data. This study shows that China's investment activity began to decline in 2019, rebounded for a period of time after the outbreak of COVID-19 in 2020, and then continued to maintain a downward trend. Private investment activity has declined significantly, while government investment activity has increased. Among the provinces in Chinese Mainland, the investment activity of economically developed provinces has decreased significantly, while the investment activity of some economically less developed provinces in the north and south is higher. After the outbreak of COVID-19, the investment period became shorter. Our research will provide timely investment information for the government, decision makers and managers, as well as provide other researchers who also pay attention to investment with a perspective other than investment in fixed asset.
Samantha Petersone, Alwin Tan, Richard Allmendinger
et al.
The core activity of a Private Equity (PE) firm is to invest into companies in order to provide the investors with profit, usually within 4-7 years. To invest into a company or not is typically done manually by looking at various performance indicators of the company and then making a decision often based on instinct. This process is rather unmanageable given the large number of companies to potentially invest. Moreover, as more data about company performance indicators becomes available and the number of different indicators one may want to consider increases, manual crawling and assessment of investment opportunities becomes inefficient and ultimately impossible. To address these issues, this paper proposes a framework for automated data-driven screening of investment opportunities and thus the recommendation of businesses to invest in. The framework draws on data from several sources to assess the financial and managerial position of a company, and then uses an explainable artificial intelligence (XAI) engine to suggest investment recommendations. The robustness of the model is validated using different AI algorithms, class imbalance-handling methods, and features extracted from the available data sources.
Ai Linh Nguyen, Wenyuan Liu, Khiam Aik Khor
et al.
Nowadays, patenting activities are essential in converting applied science to technology in the prevailing innovation model. To gain strategic advantages in the technological competitions between regions, nations need to leverage the investments of public and private funds to diversify over all technologies or specialize in a small number of technologies. In this paper, we investigated who the leaders are at the regional and assignee levels, how they attained their leadership positions, and whether they adopted diversification or specialization strategies, using a dataset of 176,193 patent records on graphene between 1986 and 2017 downloaded from Derwent Innovation. By applying a co-clustering method to the IPC subclasses in the patents and using a z-score method to extract keywords from their titles and abstracts, we identified seven graphene technology areas emerging in the sequence synthesis - composites - sensors - devices - catalyst - batteries - water treatment. We then examined the top regions in their investment preferences and their changes in rankings over time and found that they invested in all seven technology areas. In contrast, at the assignee level, some were diversified while others were specialized. We found that large entities diversified their portfolios across multiple technology areas, while small entities specialized around their core competencies. In addition, we found that universities had higher entropy values than corporations on average, leading us to the hypothesis that corporations file, buy, or sell patents to enable product development. In contrast, universities focus only on licensing their patents. We validated this hypothesis through an aggregate analysis of reassignment and licensing and a more detailed analysis of three case studies - SAMSUNG, RICE UNIVERSITY, and DYSON.
The main purpose of this study is to conduct a dynamic and bibliometric analysis of the main terms that identify the system for combating financial and fraud to identify trends in the formation of social and scientific thought. The review of the scientific literature indicates an increase in the number of scientific publications over the past ten years. It was revealed that the most cited works cover the problems associated with cyber threats in everyday life, among which are botnets, cyber bullying, as well as financial fraud implemented through cryptocurrencies, smart contracts, and the black market on the Internet. Cloud forensics, technical and intellectual analysis are proposed as countermeasures. The research tools were a dynamic analysis of global network user requests, implemented using Google Trends, and a bibliometric analysis of scientific publications by the world's leading scientists, performed using the VOSviewer analytical package. The search terms “Fraud”, “Finance Fraud”, “Cyber Fraud”, “Finance Cyber Fraud”, “Money Laundering”, “Anti-Money Laundering” and “Anti-Fraud” for the period from 08/07/2017 to 08/07/2022. For bibliometric analysis, two datasets with a length of 2,000 observations were formed based on queries in the Scopus database regarding the terms “Cyber Crime” and “Anti-money Laundering”. The results of the dynamic analysis revealed a decrease in the level of interest in fraud and financial fraud since the beginning of 2021, while the trend of cyber fraud is increasing. This led to the conclusion that there was an impact of the pandemic, which caused an increase in cybercrime. The results of the analysis of requests for “Fraud” and “Finance Fraud” by geographical distribution showed that they interested users belonging to countries with a significant difference in economic development. That is, representatives of poor countries are potential cyber fraudsters, and developed countries are potential victims of fraud. Conducting a bibliometric analysis made it possible to obtain clusters of promising areas of scientific research in the field of cybercrimes, among which mathematical and network tools for combating them, general concepts, digitalization and digital forensics, cyber protection, data protection, authentication and encryption of data, etc. are highlighted. At the same time, the focus of research is shifting towards methods of countering cybercrimes. Promising directions in the field of Money Laundering are mathematical methods and information technologies, cryptocurrencies and blockchains, corruption, financial terrorism, etc. The greatest potential belongs to money laundering through cryptocurrencies and blockchains. The lessons learned can be useful for improving the strategy of combating financial and cybercrimes and forming an analytical basis for the scientific community and practitioners.
Demographic changes increase the necessity to base the pension system more and more on the second and the third pillar, namely the occupational and private pension plans; this paper deals with Target Date Funds (TDFs), which are a typical investment opportunity for occupational pension planners. TDFs are usually identified with a decreasing fraction of wealth invested in equity (a so-called glide path) as retirement comes closer, i.e., wealth is invested more risky the younger the saver is. We investigate whether this is actually optimal in the presence of non-tradable income risk in a stochastic volatility environment. The retirement planning procedure is formulated as a stochastic optimization problem. We find it is the (random) contributions that induce the optimal path exhibiting a glide path structure, both in the constant and stochastic volatility environment. Moreover, the initial wealth and the initial contribution made to a retirement account strongly influence the fractional amount of wealth to be invested in risky assets. The risk aversion of an individual mainly determines the steepness of the glide path.
Natural selection drives species to develop brains, with sizes that increase with the complexity of the tasks to be tackled. Our goal is to investigate the balance between the metabolic costs of larger brains compared to the advantage they provide in solving general and combinatorial problems. Defining advantage as the performance relative to competitors, a two-player game based on the knapsack problem is used. Within this framework, two opponents compete over shared resources, with the goal of collecting more resources than the opponent. Neural nets of varying sizes are trained using a variant of the AlphaGo Zero algorithm. A surprisingly simple relation, $N_A/(N_A+N_B)$, is found for the relative win rate of a net with $N_A$ neurons against one with $N_B$. Success increases linearly with investments in additional resources when the networks sizes are very different, i.e. when $N_A \ll N_B$, with returns diminishing when both networks become comparable in size.
While in today’s Sponge Cities flood control works effectively, the sponge-based rainwater harvesting is associated with substantial challenges. In addition to water management, the pollution of collected stormwater counts as one of the major barriers for urban water augmentation. The aim of this communication is to outline how this constraint can be overcome and how the water service portfolio of the Sponge City can successfully undergo feasible expansion considering technical and also economic aspects. Innovative engineered solutions for a sponge-based rainwater harvesting are the key to an adaptive and flexible water supply infrastructure for Sponge Cities especially to preserve its manifold urban water and life quality services. The complementary water service, emerged from the Sponge City, can provide an imperative contribution to compensate the high capital investments and to cover the operation and maintenance costs. This enables a tremendous funding opportunities that can be invested for the preservation of the blue-green future city. Moreover, this would offer a feasible way of urban water service development over the negative impacts caused by climate change.
River, lake, and water-supply engineering (General), Water supply for domestic and industrial purposes
We study the problem of minimizing the (time) average security costs in large networks/systems comprising many interdependent subsystems, where the state evolution is captured by a susceptible-infected-susceptible (SIS) model. The security costs reflect security investments, economic losses and recovery costs from infections and failures following successful attacks. We show that the resulting optimization problem is nonconvex and propose a suite of algorithms - two based on a convex relaxation, and the other two for finding a local minimizer, based on a reduced gradient method and sequential convex programming. Also, we provide a sufficient condition under which the convex relaxations are exact and, hence, their solution coincides with that of the original problem. Numerical results are provided to validate our analytical results and to demonstrate the effectiveness of the proposed algorithms.