Resilient Solutions Research Articles

The World of Coffee: 21st Century Solutions for A Commodity Facing Climate Change Risks

This paper examines the environmental impacts of climate change on the yields of Arabica coffee and the economic impacts on smallholder coffee farmers. To address these challenges, environmental and socio-economic solutions are proposed alongside a gap analysis of key coffee related certification programs. As temperatures increase, farmers are forced to move to higher elevations to grow coffee, where less land is available for farming. These climate change outcomes are visibly affecting Central and South American countries, which are experiencing up to 2°C of warming above pre-industrial averages (Sachs, 2019). Environmental risks may lead to smallholder farmers abandoning coffee production altogether, resulting in a decrease of supply and expertise for the coffee industry. At the same time, this industry is seeing increased demand from consumers for products with “green” certifications. Currently, sustainability certifications do not offer a full-fledged solution for environmental and socio-economic concerns. This gap analysis focuses on four main sustainability certifications and aims to provide an understanding of why certifications fail to address environmental and socio-economic challenges. This study seeks to identify the factors that certification models should incorporate in their supply chain assessments to examine climate change threats and improve outcomes for farmers. Analyzing the different criteria for certifications shows that: 1) Integrating environmental criteria within certifications is a resilient solution to addressing immediate climate change risks, and 2) mechanisms for protecting farmers against price volatility are required. The research shows that the Rainforest Alliance’s certification program is currently best positioned to serve the needs of an increasingly at-risk sector.

Ancestral Integrated Water Management Systems as Adaptation Tools for Climate Change: The “Acequias De Careo” and Historical Water Management of the Mecina River in Sierra Nevada (Granada, Spain)

ABSTRACT Historical water management systems, in operation since the Islamic period (eighth to fifteenth centuries), have generated important irrigated areas and transformed the landscapes in a co-evolutionary process over more than a thousand years. In the Sierra Nevada, the so-called acequias de careo stand out as a singular technical system for water recharge from the thaw. This way of managing surface- and groundwater, as well as soil and vegetation, while generating social, economic, and environmental benefits, is an example of Integrated Water Management and Nature-based Solutions. This system has proven its efficiency and resilience, having been operational since the Middle Ages. The abandonment of these water management systems is an irreparable cultural and environmental loss. The transdisciplinarity of this case study can be considered a success and a good example for its application in other geographical and cultural contexts promoting sustainable and resilience solutions based on historical socio-ecological systems and local ecological knowledge and practices.

A pooling & sharing solution for delivering space data using multiple commercial Satcom providers

We introduce the Pooling & Sharing paradigm that is already a mature solution addressing the needs of government institutional users through a common digital orchestrating platform where Satcom demands and Satcom offers are seamlessly matched in real time. We describe the background and state-of-the art and discuss challenges and possibilities on how this solution could be adapted to address the unique case of Data Relay from Space for space missions on a planetary surface or in near earth orbit. This can result in a cost effective and resilient solution and offer significant benefits to Space Agency and commercial customers that need to download massive amount of mission data or communicate with their scientific instruments. It could also create a new profitable service for commercial satellite operators.

Quantum Computing and Machine Learning for Cybersecurity: Distributed Denial of Service (DDoS) Attack Detection on Smart Micro-Grid

Machine learning (ML) is efficiently disrupting and modernizing cities in terms of service quality for mobility, security, robotics, healthcare, electricity, finance, etc. Despite their undeniable success, ML algorithms need crucial computational efforts with high-speed computing hardware to deal with model complexity and commitments to obtain efficient, reliable, and resilient solutions. Quantum computing (QC) is presented as a strong candidate to help MLs reach their best performance especially for cybersecurity issues and digital defense. This paper presents quantum support vector machine (QSVM) model to detect distributed denial of service (DDoS) attacks on smart micro-grid (SMG). An evaluation of our approach against a real dataset of DDoS attack instances shows the effectiveness of our proposed model. Finally, conclusions and some open issues and challenges of the fitting of ML with QC are presented.

Blockchain-assisted spent electric vehicle battery participation for load frequency control problems in interconnected power systems is resilient, low-carbon, and offers revenues to the operators

Parked electric vehicles (EVs) participation is thought to be a low-carbon and resilient solution in addressing the load frequency control (LFC) problems in interconnected power systems (IPS). But this participation results in multiple issues such as trust, traceability, and transparency (3Ts) for EV owners in terms of financial compensation, battery effects, and range anxiety; early EV batteries end-of-life (EoL) management by recyclers; and burden on critical materials for new EV batteries manufacturing. Hence, to avoid the highlighted issues while addressing LFC, we propose a product life-extension circular business model and blockchainification of non-digital assets inspired spent EV battery (SEVB) buffer storage system. Two area IPS where areas 1 and 2 having a tie-line power agreement, SEVB storage system, particle swarm optimization (PSO)-based controller, and blockchain-based participatory smart contracts (BC-PSC) are modeled. Resilience Performance, Life Cycle Analysis, and Techno-Economic (RePLiCATE) approach is used for realizing the feasibility. Results showed BC-PSC protocols and PSO effectively obtained the controller's optimal parameters under disruptive scenarios ranging from 5 to 20%. The recovery times went from 18.60 to 46.43 sec. SEVB in LFC produces 18.71% less global warming potential than parked EVs. Revenues for SEVB owners were 122.27%, 100.22%, and 66.67% higher than cash spent on charging at off-peak, mid-peak, and on-peak, respectively.

Nature-based solutions for coastal resilience in South Africa

ABSTRACT Coastlines globally are sensitive to the effects of sea-level rise, increased coastal storminess and changes in coastal sediment supply and sediment dynamics in the Anthropocene. Coastlines are also influenced by land use change, urbanization and development of built infrastructure. These changes can affect the dynamics of coastal landforms, weaken coastal resilience and make coasts more sensitive to climate hazards. This study critically examines the properties of coastlines that contribute to coastal biophysical resilience in South Africa, highlighting their relativerates of change and dynamic behaviour in response to physical and human forcing factors. Coastal landforms can be considered as ‘green infrastructure’ that can buffer the effects of climate change as well as providing ecosystem and environmental services in their own right. Viewing coastal landforms as green infrastructure provides a ‘nature-based solution’ to mitigate against climate change impacts that can work with – not against – the natural geomorphic, sedimentary and ecological processes of coastlines. Coastal landforms can also contribute to socioecological resilience, where they provide environmental and ecosystem services. The green infrastructure approach to coastal resilience has not been well developed in South Africa but is more effective in supporting coastal sustainable development.

Resilience and Resilient Systems of Artificial Intelligence: Taxonomy, Models and Methods

Artificial intelligence systems are increasingly being used in industrial applications, security and military contexts, disaster response complexes, policing and justice practices, finance, and healthcare systems. However, disruptions to these systems can have negative impacts on health, mortality, human rights, and asset values. The protection of such systems from various types of destructive influences is thus a relevant area of research. The vast majority of previously published works are aimed at reducing vulnerability to certain types of disturbances or implementing certain resilience properties. At the same time, the authors either do not consider the concept of resilience as such, or their understanding varies greatly. The aim of this study is to present a systematic approach to analyzing the resilience of artificial intelligence systems, along with an analysis of relevant scientific publications. Our methodology involves the formation of a set of resilience factors, organizing and defining taxonomic and ontological relationships for resilience factors of artificial intelligence systems, and analyzing relevant resilience solutions and challenges. This study analyzes the sources of threats and methods to ensure each resilience properties for artificial intelligence systems. As a result, the potential to create a resilient artificial intelligence system by configuring the architecture and learning scenarios is confirmed. The results can serve as a roadmap for establishing technical requirements for forthcoming artificial intelligence systems, as well as a framework for assessing the resilience of already developed artificial intelligence systems.

Resilience strategies for sustainable supply chains under budget constraints in the post COVID-19 era

The COVID-19 outbreak has caused uncertainty risk surges, increased sustainable supply chain vulnerabilities, and challenges to sustainable supply chain resilience (SSCR) management. Therefore, improving SSCR is necessary to alleviate vulnerabilities, and SSCR management must generate large capital investments. However, the economic downturn brought about by the COVID-19 epidemic has made some companies have limited budgets that can be used to improve SSCR. Therefore, the design of resilience solutions needs to fully consider the constraints of budgetary costs. Most of the existing related literature only discusses optimal resilience solutions under certain cost constraints, so such resilience solutions cannot be applied to most enterprises. In this study, we set the cost constraint as a variable quantity, using resilience efficiency and customer satisfaction as indicators, to determine the changing laws of optimal resilience strategies when cost constraints change. These rules can be applied to enterprises with different budgeted costs. Our findings suggest that companies should prioritize sacrificing resilience measures (RMs) related to adaptive capacity when budget costs gradually decline, and RMs related to absorptive capacity are indispensable at all budget levels. Furthermore, the pursuit of environmental and social sustainability cannot be abandoned, no matter how limited the flexible budget may be.

In Pursuit of Local Solutions for Climate Resilience: Sensing Microspatial Inequities in Heat and Air Pollution within Urban Neighborhoods in Boston, MA

Environmental hazards vary locally and even street to street resulting in microspatial inequities, necessitating climate resilience solutions that respond to specific hyperlocal conditions. This study uses remote sensing data to estimate two environmental hazards that are particularly relevant to community health: land surface temperature (LST; from LandSat) and air pollution (AP; from motor vehicle volume via cell phone records). These data are analyzed in conjunction with land use records in Boston, MA to test (1) the extent to which each hazard concentrates on specific streets within neighborhoods, (2) the infrastructural elements that drive variation in the hazards, and (3) how strongly hazards overlap in space. Though these data rely on proxies, they provide preliminary evidence. Substantial variations in LST and AP existed between streets in the same neighborhood (40% and 70–80% of variance, respectively). The former were driven by canopy, impervious surfaces, and albedo. The latter were associated with main streets and zoning with tall buildings. The correlation between LST and AP was moderate across census tracts (r = 0.4) but modest across streets within census tracts (r = 0.16). The combination of results confirms not only the presence of microspatial inequities for both hazards but also their limited coincidence, indicating that some streets suffer from both hazards, some from neither, and others from only one. There is a need for more precise, temporally-dynamic data tracking environmental hazards (e.g., from environmental sensor networks) and strategies for translating them into community-based solutions.

Applying Neural Networks with Time-Frequency Features for the Detection of Mental Fatigue

The detection of mental fatigue is an important issue in the nascent field of neuroergonomics. Although machine learning approaches and especially deep learning designs have constantly demonstrated their efficiency to automatically detect critical features from raw data, the computational resources for training and predictions are usually very demanding. In this work, we propose a shallow convolutional neural network, with three convolutional layers, for fatigue detection using electroencephalogram (EEG) data that can alleviate the computational burden and provide fast mental fatigue detection. As such, a deep learning model was created utilizing time-frequency domain features, extracted with Morlet wavelet analysis. These features, combined with the higher-level characteristics learnt by the model, resulted in a resilient solution, able to attain very high prediction accuracy (97%), while reducing training time and computing costs. Moreover, by incorporating a subsequent SHAP values analysis on the characteristics that contributed in the model creation, indications of low frequency (theta and alpha band) brain wave characteristics were indicated as prominent mental fatigue detectors.

A generic optimization framework for resilient systems

ABSTRACT This paper addresses the optimal design of resilient systems, in which components can fail. The system can react to failures and its behaviour is described by general mixed integer nonlinear programs, which allows for applications to many (technical) systems. This then leads to a three-level optimization problem. The upper level designs the system minimizing a cost function, the middle level represents worst-case failures of components, i.e. interdicts the system, and the lowest level operates the remaining system. We describe new inequalities that characterize the set of resilient solutions and allow to reformulate the problem. The reformulation can then be solved using a nested branch-and-cut approach. We discuss several improvements, for instance, by taking symmetry into account and strengthening cuts. We demonstrate the effectiveness of our implementation on the optimal design of water networks, robust trusses, and gas networks, in comparison to an approach in which the failure scenarios are directly included into the model.

The interconnected global emergencies of climate change, food security and health: a call to action by the Science for Africa Foundation.

The evidence is clear that climate change is the greatest challenge facing mankind today. Africa is disproportionately burdened by multiple direct and cascading impacts of the climate crisis. Global investments for climate change adaptation, however, have not prioritized Africa adequately and there is a significant knowledge gap in understanding the context and science of climate change and sustainable solutions for the continent's adaptation. Solutions for adaptation and resilience are made complex by an urgent need for accelerated economic growth, rapid population expansion and urbanization, habitat and biodiversity loss and dwindling financing. There are also challenges in matching policies, wavering commitments and actions with good science that focuses on sustainable lives, livelihoods and ecosystem preservation. The solutions must come from where the impacts are felt. The Science for Africa Foundation supports African researchers and institutions to lead in the science that addresses African priority development areas and has set climate change as a strategic priority. This call to action, by the SFA Foundation, outlines key areas that its strategy addresses through programs that support African scientific excellence, leadership and the best of Africa's research to understand the science of climate change and its impacts; collate and assess evidence for policy; grow high level technical capacity on the continent; and create innovative priority actions for Africa.

The experience of cities during the COVID 19 pandemic: What are we going to do now?

The Covid 19 pandemic, taken as a social crisis, has pointed to the high vulnerability of the basic organizational principles of modern society and the inherent inequalities, particularly those related to the urban space. Therefore, the first part of the paper presents ideas and practices initiated by the Covid 19 pandemic regarding (re)conceptualization of urban mobility and (re)organization of urban spaces in searching for more sustainable and resilient solutions, in Europe and the developed world. Secondly, the analysis addresses ecological modernization and the entrepreneurial (smart) city models as conceptual frames that limit considerably the approach to urban sustainability and resilience, both in general and in a pandemic context. The concluding part highlights the missing political will and economic interest to deal with the pandemic as an opportunity to reset existing urban policies/measures and seek to balance the economic, social and ecological dimensions of urban development. By employing critical sociological thinking on contemporary cities, the authors emphasize the need to recognize social and environmental justice issues in urban sustainability discourse and practice.

Quaternion-Based Non-Singular Terminal Sliding Mode Control for a Satellite-Mounted Space Manipulator

In this paper, a robust control solution for a satellite equipped with a robotic manipulator is presented. First, the dynamical model of the system is derived based on quaternions to describe the evolution of the attitude of the base satellite. Then, a non-singular terminal sliding mode controller that employs quaternions for attitude control, is proposed for concurrently handling all the degrees of freedom of the system. Moreover, an additional adaptive term is embedded in the controller to estimate the upper bounds of disturbances and uncertainties. The result is a resilient solution able to withstand unmodelled dynamics and interactions. Lyapunov theory is used to prove the stability of the controller and numerical simulations allow assessing performance and fuel efficiency.

Integrating microbial fuel cell with sedum green roof for stormwater retention and renewable energy generation

Climate change brings frequent and intense storms, which challenge aging stormwater infrastructures. As a sustainable stormwater solution, green roofs are being more frequently used in urban areas. However, high installation and maintenance costs have limited applications of green roofs on a large scale. A plant microbial fuel cell (P-MFC) is a novel technology that uses bacteria living around the root of plants to generate electricity. This study explores the integration of P-MFCs with an extensive green roof module for the dual benefit of stormwater runoff reduction and renewable energy generation. While most P-MFC systems in the literature are based on flooded plants, the green roof MFC developed in this study uses sedum plants which are among the most common vegetation layers for green roof solutions. We hypothesized that MFC efficiency could be improved by introducing a water storage layer and capillary sub-irrigation. Moreover, the capillary irrigation wick can function as a salt bridge to further enhance power generation. Three prototypes were fabricated to test our hypotheses, including a control unit without sub-irrigation and two units with capillary irrigation and one with additional salt bridge configuration. Experiments demonstrated that capillary irrigation and the salt bridge configuration significantly increased P-MFC’s power density and decreased the internal resistance. The research demonstrated that green roof modules with integrated P-MFCs can be a renewable energy generator, promoting the adoption of green roofs as sustainable solutions for climate resilience by simultaneously reducing storm floods, capturing carbon dioxide (CO2) in the atmosphere, and producing green electricity.

Leveraging Electric Vehicles as a Resiliency Solution for Residential Backup Power During Outages

Leveraging Electric Vehicles as a Resiliency Solution for Residential Backup Power During Outages

Investigation of Technical Feasibility of Hybrid Compressed Air Cogeneration Systems under Energy-Flexible Operation

The study investigates the effects of energy-flexible operation of hybrid compressed air systems in production processes with a view to efficiency and energy consumption. As energy costs become increasingly important in the economic considerations of industrial companies, integrating renewable energies necessitates the implementation of demand-side management capabilities to overcome the problem of intermittent energy production. One promising solution is hybridization, enabling energy systems to utilize multiple forms of energy. In the context of hybrid compressed air systems (CAS), it enables the use of gas, for example natural gas, hydrogen gas or biogas, and electricity for compressed air production, thus substituting electricity or gas demand on short- and long-term horizons. Advantages of such systems include the provision of energy flexibility as well as the variable supply of compressed air, process heat, and electricity through recuperation in the electric motor according to production plant consumption. However, the effects of energy-flexible operation on energy consumption and thus on the system's efficiency still needs to be fully understood. To this end, a demonstrator of a hybrid CAS cogeneration plant was built. Specific scenarios are used to analyze the effect on energy efficiency and the feasibility of energy-flexible operation. Despite slight reductions in efficiency during operation, the feasibility of operation was validated and valuable insights on further improvement were gained. With a view to the expected rising volatility in energy production, the hybrid approach represents an efficient, climate-friendly, energy-flexible, and resilient solution for compressed air production that could assist in expanding industrial demand-side management.

Supporting the Process of Designing and Planning Heritage and Landscape by Spatializing Data on a Single Support Platform. Case Study: Romania

Data handling is a general objective of education, regardless of the educational level (middle school, high school, university or postgraduate) and branch. Being at the intersection between the humanities and the exact sciences, the field of design requires a continuous summation and overlapping of information from specialists. Obtaining data is essential for perceiving the current situation, but also for adapting the solution proposed in the planning process to the given situation, to the particularities and main characteristics of the context. How difficult it is to obtain information, but especially their overlap and correlation to obtain indicators specific to target areas, depends in most cases on the experience of the specialist in the field, but for a recent graduate, the training received during the years of university training is perhaps his most important support. However, there may be data that are predominantly available during university training and data that can be obtained predominantly outside the academic environment (financial data, communication with public institutions). The paper describes a proposal for a support platform to assist the process of architectural design, urban planning and landscaping in Romania, but which can also support adjacent studies and analyzes. The purpose of the platform is to support the design and planning process of heritage and landscape, architecture and urban planning, by simplifying the data acquisition process and also directing the design/planning process to a long-term perspective, which is based on resilient solutions for natural and built heritage and for the conservation of the local cultural landscape.

FINANCING ROMANIAN SMES – CHALLENGES AND OPPORTUNITIES DURING THE PANDEMIC CRISIS

The small and medium-sized enterprise sector (SMEs) is considered an essential factor for growth and economic development. But despite its economic, social and innovative role, the SME sector is confronting with many vulnerabilities. Access to finance represent one of the main problems facing the SME sector. The new economic context imposed by the pandemic crisis has further highlighted these vulnerabilities and imposed new solutions for resilience and post-crisis recovery. The paper presents the characteristics and evolutions of the Romanian SMEs, the effects generated by the crisis on small and medium enterprises, the main measures adopted to support and to provide liquidity for SMEs affected by the crisis. This challenge comes both with restrictions and negative aspects, but also with some positive aspects, which can be turned into real opportunities for this sector so important in the economy. The main sources of finance for the Romanian SME sector as well as the major financing programs and instruments at the national and European level are analyzed in light of the role that financing plays in supporting and developing small and medium-sized enterprises. The measures adopted (greater financing flexibility, credit guarantees, public and private investment), the financing programs and instruments but also ensuring a stable legal and juridical framework, can contribute to the development of SME sector in Romania, after the pandemic crisis.

A resilient solution to Range-Only SLAM based on a decoupled landmark range and bearing reconstruction

A Range Only Simultaneous Localization and Mapping (RO-SLAM) problem is considered in this paper. The robot is a unicycle like vehicle equipped with encoders on the actuated wheels, which measures the distance to a set of UWB landmarks located in unknown position in the surrounding. A Multi Hypotheses Extended Kalman Filter (MHEKF), one for each landmark, is designed to dynamically estimate the range and the bearing of the observed landmark. These estimates, regarded as measurements with a proper covariance matrix, are used in an EKF SLAM algorithm, endowed with a resilient module to discern and possibly to temporarily discard landmarks with an unreliable range and bearing estimate. This allows to cope with the initial uncertainty characterizing the bearing reconstruction, but also to resist the effects of outliers and to detect possible abnormal situations. Simulation and experimental results illustrate the effectiveness of the proposed approach compared to other methods available in the literature, especially in case of significant perturbations, like the sudden and unmodeled shift of the landmarks.