Are smart contracts too smart for Supply Chain 4.0? A blockchain framework to mitigate challenges: IMS

PurposeSmart contracts are self-executing computer programmes that have the potential to be used in several applications instead of traditional written contracts. With the recent rise of smart systems (e.g. Internet of things) and digital platforms (e.g. blockchain), smart contracts are gaining high interest in both business and academia. In this work, a framework for smart contracts was proposed with using reputation as the system currency, and conducts currency mining through fulfilling the physical commitments that are agreed upon.Design/methodology/approachA game theory model is developed to represent the proposed system, and then a system dynamics simulator is used to check the response of the blockchain with different sizes.FindingsThe numerical results showed that the proposed system could identify the takeover attacks and protect the blockchain from being controlled by an outsider. Another important finding is that careful setting of the maximum currency amount can improve the scalability of the blockchain and prevent the currency inflation.Research limitations/implicationsThis work is proposed as a conceptual framework for supply chain 4.0. Future work will be dedicated to implement and experiment the proposed framework for other characteristics that may be encountered in the context of supply chain 4.0, such as different suppliers' tiers, different customer typologies and smart logistics applications, which may reveal other challenges and provide additional interesting insights.Practical implicationsBy using the proposed framework, smart contracts and blockchains can be implemented to handle many issues in the context of operations and supply chain 4.0, especially in times of turbulence such as the COVID-19 global pandemic crisis.Originality/valueThis work emphasizes that smart contracts are not too smart to be applied in the context of supply chain 4.0. The proposed framework of smart contracts is expected to serve supply chain 4.0 by automating the knowledge work and enabling scenario planning through the game theory model. It will also improve online transparency and order processing in real-time through secured multitier connectivity. This can be applied in global supply chain functions backed with digitization, notably during the time of the pandemic, in which e-commerce and online shopping have changed the rules of the game.

ANALYZING A MACROPRUDENTIAL INSTRUMENT DURING THE COVID-19 PANDEMIC USING BORDER COLLISION BIFURCATION

Bank Indonesia, el banco central de Indonesia, ha realizado ajustes en un instrumento de política macroprudencial llamado índice de intermediación macroprudencial (IIM) para impulsar el crecimiento de los préstamos en el contexto de la recuperación económica nacional debido a la pandemia de COVID-19. En este artículo, se desarrolla un modelo dinámico de préstamo bancario con comportamiento procíclico, y se equipa con el instrumento predecesor del IIM denominado requerimiento de reserva basado en la relación préstamo-depósito (RR-RPD). Examinamos los efectos de los parámetros RR-RPD en la dinámica del préstamo utilizando el análisis de bifurcación de colisión de fronteras para determinar los valores umbral de los parámetros RR-RPD para que se pueda mantener la estabilidad del equilibrio del préstamo. Este modelo se aplica a los datos mensuales de los bancos comerciales de Indonesia antes y durante la pandemia de COVID-19 para evaluar la región de estabilidad de los parámetros del instrumento.Alternate :Bank Indonesia, the central bank of Indonesia, has made adjustment settings in a macroprudential policy instrument called macroprudential intermediation ratio (MIR) to boost loan growth in the context of national economic recovery due to the COVID-19 pandemic. In this paper, a dynamic model of bank loan with procyclicality behavior is developed, and it is equipped with the predecessor of the MIR instrument called loan-to-deposit ratio based reserve requirement (LDR-RR). We examine the effects of LDR-RR parameters on the dynamics of loan using the border collision bifurcation analysis to determine the threshold values of the LDR-RR parameters so that the stability of loan equilibrium can be maintained. This model is applied to monthly data of Indonesian commercial banks before and during the COVID-19 pandemic to assess the stability region of the instrument parameters.

Design of a Telepresence Robot to Avoid Obstacles in IoT-Enabled Sustainable Healthcare Systems

In the Internet of Things (IoT) era, telepresence robots (TRs) are increasingly a part of healthcare, academia, and industry due to their enormous benefits. IoT provides a sensor-based environment in which robots receive more precise information about their surroundings. The researchers work day and night to reduce cost, duration, and complexity in all application areas. It provides tremendous benefits, such as sustainability, welfare improvement, cost-effectiveness, user-friendliness, and adaptability. However, it faces many challenges in making critical decisions during motion, which requires a long training period and intelligent motion planning. These include obstacle avoidance during movement, intelligent control in hazardous situations, and ensuring the right measurements. Following up on these issues requires a sophisticated control design and a secure communication link. This paper proposes a control design to normalize the integration process and offer an auto-MERLIN robot with cognitive and sustainable architecture. A control design is proposed through system identification and modeling of the robot. The robot control design was evaluated, and a prototype was prepared for testing in a hazardous environment. The robot was tested by considering various parameters: driving straight ahead, turning right, self-localizing, and receiving commands from a remote location. The maneuverability, controllability, and stability results show that the proposed design is well-developed and cost-efficient, with a fast response time. The experimental results show that the proposed method significantly minimizes the obstacle collisions. The results confirm the employability and sustainability of the proposed design and demonstrate auto-MERLIN's capabilities as a sustainable robot ready to be deployed in highly interactive scenarios.

Research on Optimization of Public Opinion Supervision Model of Social Network Platform Based on Evolutionary Game

Network environments have recently emerged as a considerable research area. In addition to government supervision, platform supervision is also critical to improve network environments. So, we should improve the social network platform's single regulatory model. Against this background, we described public opinion supervision as a game between marketing accounts, netizens, and the platform. Unlike previous studies, we considered the influence of marketing accounts on online public opinion. Because of the players' bounded rationality, we built an evolutionary game model, and by solving it, we obtained the evolutionarily stable strategy (ESS). Then, we analyzed the influence of relevant parameters on the evolutionary stable state. Our research results show that if the authenticity of the information is not high, to not publish is the best choice for the marketing account, and to not participate is the best choice for the netizen. The platform penalty for the marketing account is also directly related to the marketing account's decision making. The platform penalty for the government, as well as the increase in the penalty risk coefficient, considerably affected the choice of platform. Finally, we put forward the "pre-event–in-the-event–post-event” three-stage supervision model, which provides countermeasures and suggestions for all parties to jointly maintain the network environment.

The Role Of Constitutional Law In The Era Of The Covid-19 Pandemic In Indonesia

The outbreak of the Covid-19 virus, which is spreading very quickly in various parts of the world, has a bad impact on several different sectors that can harm the country if the country does not take quick and right decisions. This encourages governments of countries in the world to create new regulations so that they are able to ensure the safety of their citizens and also sectors affected by the Covid-19 pandemic can recover. Policy issuance is certainly closely related to constitutional law and laws. Constitutional law is a regulation of the required state institutions and their authorities, internal relations between state institutions, and the relationship between state institutions and citizens. The purpose of this study was to determine the role of constitutional law in handling cases of Covid-19 that hit Indonesia and its implementation. The method used in this study is the literature review method or literature review which searches the literature for research purposes. The results of this study indicate that the role of constitutional law in handling Covid-19 cases in Indonesia can be seen through the making of simple laws and regulations rather than having to change the legal status of the national constitution . . The application of constitutional law in handling Covid-19 cases in Indonesia can be observed from existing policies, namely through the issuance of simple laws such as PP, Presidential Decree, and others.

Uncovering Disturbance Observer and Ultra-Local Plant Models in Series PI Controllers

The paper settles two major liabilities and asymmetries of the theory of automatic control to the design of simple system controllers. It shows the most frequently used series proportional integral (PI) controllers as disturbance reconstruction and compensation-based structures and solves their designs using two types of linear system models. Beginning with the example of a simple integrator controlled by a P controller, it shows that constant input disturbances can be reconstructed by evaluating steady state values of the controller output. Thereby, the nearly steady state controller output can be simply achieved by using a low-pass filter with a time constant significantly longer than the time constant of stabilized processes. This disturbance observer (DOB) functionality can be demonstrated as being kept by series PI controllers designed by the pole assignment method. The DOB design can also be extended to first-order systems with internal feedback. However, there, the reconstructed disturbances depend both on the controller and the plant output steady state values. Because this feature is missing in industrial PI controllers, it indicates their connections with simpler, ultra-local (integral) linear system models. The interpretation of PI controllers as DOB-based structures allows a systematic consistent classification of all existing disturbance compensation structures and simplifies their comparisons with other modern and postmodern DOB-based alternatives. Given the breadth of use, improved understanding of PI control functionality also represents an important step to their optimal implementation and to research of innovative modifications, as illustrated by facilitating the flexible use of the new functional capabilities offered by embedded controls. By enhancing “the birth” of new solutions, it is then possible to better satisfy the permanently growing requirements of practice.

Load-Altering Attacks Against Power Grids under COVID-19 Low-Inertia Conditions

The COVID-19 pandemic has impacted our society by forcing shutdowns and shifting the way people interacted worldwide. In relation to the impacts on the electric grid, it created a significant decrease in energy demands across the globe. Recent studies have shown that the low demand conditions caused by COVID-19 lockdowns combined with large renewable generation have resulted in extremely low-inertia grid conditions. In this work, we examine how an attacker could exploit these scenarios to cause unsafe grid operating conditions by executing load-altering attacks (LAAs) targeted at compromising hundreds of thousands of IoT-connected high-wattage loads in low-inertia power systems. Our study focuses on analyzing the impact of the COVID-19 mitigation measures on U.S. regional transmission operators (RTOs), formulating a plausible and realistic least-effort LAA targeted at transmission systems with low-inertia conditions, and evaluating the probability of these large-scale LAAs. Theoretical and simulation results are presented based on the WSCC 9-bus and IEEE 118-bus test systems. Results demonstrate how adversaries could provoke major frequency disturbances by targeting vulnerable load buses in low-inertia systems and offer insights into how the temporal fluctuations of renewable energy sources, considering generation scheduling, impact the grid’s vulnerability to LAAs. Author

Centrifugal forces in a hegemonic environment: the rise of small-state coalitions in the Economic and Monetary Union

A hegemonic power can guarantee the status quo in an international economic system. However, domestic or international changes may unsettle a hegemon’s priorities. In such phases, smaller states benefiting from the existing system may fear that the hegemon will fail to keep the system stable. How do they react if they lose trust in the hegemon’s ability or will to maintain the status quo? This article argues that in such cases, free riding becomes less rewarding. Therefore, smaller states build publicly visible coalitions to ‘voice’ their preferences. Applying this argument to the role of small ‘creditor states’ in the Economic and Monetary Union (EMU), the article draws on original in-depth interviews to analyze the ‘New Hanseatic League’ as a strategy to defend the present euro regime and counterbalance the Franco–German tandem. By elaborating and tracing a fine-grained causal mechanism, the article thus explains the emergence of vocal small-state coalitions in a hegemonic environment.

An Overview of System Strength Challenges in Australia’s National Electricity Market Grid

The national electricity market (NEM) of Australia is reforming via the rapid uptake of variable renewable energy (VRE) integration concurrent with the retirement of conventional synchronous generation. System strength has emerged as a prominent challenge and constraint to power system stability and ongoing grid connection of VRE such as solar and wind. In order to facilitate decarbonization pathways, Australia is the first country to evolve system strength and inertia frameworks and assessment methods to accommodate energy transition barriers, and other parts of the world are now beginning to follow the same approach. With the evolvement of the system strength framework as a new trending strategy to break the transition barriers raised by renewable energy project development and grid connection studies, this paper provides a high-level overview of system strength, covering such fundamental principles as its definition, attributes, and manifestations, as well as industry commentary, cutting-edge technologies and works currently underway for the delivery of a secure and reliable electricity system with the rapid integration of inverter-based resources (IBRs) in the NEM grid. The intent of this study is to provide a comprehensive reference on the engineering practices of the system strength challenge along with complementary technical, regulatory, and industry perspectives.

CLIMATE CHANGE AND FISCAL SUSTAINABILITY: RISKS AND OPPORTUNITIES

Both the physical and transition-related impacts of climate change pose substantial macroeconomic risks. Yet, markets still lack credible estimates of how climate change will affect debt sustainability, sovereign creditworthiness and the public finances of major economies. We present a taxonomy for tracing the physical and transition impacts of climate change through to impacts on sovereign risk. We then apply the taxonomy to the UK’s potential transition to net zero. Meeting internationally agreed climate targets will require an unprecedented structural transformation of the global economy over the next two or three decades. The changing landscape of risks warrants new risk management and hedging strategies to contain climate risk and minimise the impact of asset stranding and asset devaluation. Yet, conditional on action being taken early, the opportunities from managing a net zero transition would substantially outweigh the costs.

Deep Gene Networks and Response to Stress

We consider systems of differential equations with polynomial and rational nonlinearities and with a dependence on a discrete parameter. Such systems arise in biological and ecological applications, where the discrete parameter can be interpreted as a genetic code. The genetic code defines system responses to external perturbations. We suppose that these responses are defined by deep networks. We investigate the stability of attractors of our systems under sequences of perturbations (for example, stresses induced by environmental changes), and we introduce a new concept of biosystem stability via gene regulation. We show that if the gene regulation is absent, then biosystems sooner or later collapse under fluctuations. By a genetic regulation, one can provide attractor stability for large times. Therefore, in the framework of our model, we prove the Gromov–Carbone hypothesis that evolution by replication makes biosystems robust against random fluctuations. We apply these results to a model of cancer immune therapy.