Prospective Scenarios Research Articles

A net‐zero Swiss energy system by 2050: Technological and policy options for the transition of the transportation sector

AbstractThe Swiss government sets out a net‐zero emission goal by 2050 while phasing out nuclear energy. This study presents insights on the transport sector's contribution to meet this goal, in terms of which type of vehicle drivetrains and fuel supply options are cost‐effective? What could be critical for the transition of the transportation sector? We use the Swiss TIMES Energy system Model and assess prospective technological scenarios for the whole energy system. The transport module has fast‐charging stations and mechanisms to control e‐mobility charging. Results indicate that extensive direct and indirect electrification of mobility increases the electricity demand up to 22 TWh. While to a certain extent electric cars are competitive even if the climate would not be the priority, carbon neutrality requires a boost for electrified mobility where battery‐ and plug‐in hybrid electric vehicles are largely evolving as a solution for small‐medium size car segments while fuel cell cars are an attractive option for big size car segments. Hybridization of buses and trucks emerges as a competitive option but they are propelled with bio‐ and synthetic fuels. The transport sector emerges as a major driver for the deployment of hydrogen in the energy sector in the long term.

Inteligencia en salud: Una estrategia de análisis crítico para la toma de decisiones en el sector de salud

The last year and a half, it was shown that the lack of use of data and information of origin in the health sector, produced one of the greatest catastrophes that humanity has experienced in the last 100 years. The aforementioned, due to a failure of vision, which unfortunately is seen as a problem not only of national security, but also of human security. Intelligence is the discipline that carries out the planning, collection, analysis and generation of products for the decision-making of the leaders of a country, sector, organization or society. This can be used very well in the health sector, applying the intelligence cycle model used in the security or financial field. That is, generating products from the analysis of raw information, lines of action, strategies and prospective scenarios that guide the decision maker to carry out health policies that comply with the human security strategies recommended by the United Nations Organization (UN) for a sustainable development.

An Analysis of Agricultural Systems Modelling Approaches and Examples to Support Future Policy Development under Disruptive Changes in New Zealand

Agricultural systems have entered a period of significant disruption due to impacts from change drivers, increasingly stringent environmental regulations and the need to reduce unwanted discharges, and emerging technologies and biotechnologies. Governments and industries are developing strategies to respond to the risks and opportunities associated with these disruptors. Modelling is a useful tool for system conceptualisation, understanding, and scenario testing. Today, New Zealand and other nations need integrated modelling tools at the national scale to help industries and stakeholders plan for future disruptive changes. In this paper, following a scoping review process, we analyse modelling approaches and available agricultural systems’ model examples per thematic applications at the regional to national scale to define the best options for the national policy development. Each modelling approach has specificities, such as stakeholder engagement capacity, complex systems reproduction, predictive or prospective scenario testing, and users should consider coupling approaches for greater added value. The efficiency of spatial decision support tools working with a system dynamics approach can help holistically in stakeholders’ participation and understanding, and for improving land planning and policy. This model combination appears to be the most appropriate for the New Zealand national context.

Numerical simulation on transportation behavior of dense coarse particles in vertical pipe with an optimized Eulerian–Lagrangian method

Solid–liquid two-phase flow with dense coarse particles in the pipeline exists widely in energy and resources engineering, especially in the prospective hydraulic lifting scenario of deep-sea mining. In this paper, the coarse particles' transportation behavior in a vertical pipe is investigated based on an optimized Eulerian–Lagrangian method proposed in our previous work. The coarse particle transportation in the vertical pipe is characterized as multi-processes and multi-physical effects and is not fully captured due to the limitations on experimental apparatus, experimental measurement techniques, and numerical simulation techniques. Little research has been done on the local characteristics of the flow and their effect on the hydraulic lifting performance. The characteristics of the internal flow field, particle retention, and hydraulic lifting efficiency are disturbed under the condition of the continuous supply with the constant inlet two-phase concentration and velocity. The simulation results illustrate that particle transportation process can be roughly divided into three stages, single phase flow stage, mixing stage, and stable transportation stage, and shows a dilute-dense non-continuous flow pattern due to particle retention. Based on parametric studies, the retention phenomenon is alleviated by the increase in the water inlet velocity and almost disappears at approximately 12 000 of the Reynolds number, where the flow pattern transition occurs. Finally, the hydraulic lifting performance, such as a critical lifting condition and the friction loss, is analyzed and the transition of flow pattern is discussed.

Central bank strategy and mechanisms to restore confidence in the banking sector and its role in economic development (prospective scenarios)

Central bank strategy and mechanisms to restore confidence in the banking sector and its role in economic development (prospective scenarios)

Food in the cold: exploring food security and sovereignty in Whitehorse, Yukon

ABSTRACT Harsh weather patterns that are unpredictable owing to climate change, remoteness, dependence on food imports and limited local food production place Arctic and Subarctic food systems under serious pressure. The model of food sovereignty provides a surprisingly interesting contribution to address the food insecurity in these regions; it promotes long-term stable provision of healthy foods (sustainable) that are accessible to all (equity) and fosters local food production–consumption patterns (localisation). This study aims to deepen the understanding of food insecurity in the Subarctic regions and explores the possibilities for a food sovereignty approach at both individual and regional level. The study focuses on Whitehorse, capital of Yukon, Canada, and uses a cross-sectional online survey among residents of Whitehorse and semi-structured in-depth interviews with food-systems experts in Yukon. The findings indicated a need for affordable year-round local food production. Application of food sovereignty has provided the opportunities for local food procurement, innovation hubs, and several types of greenhouses including hydroponics and vertical farming, to work towards a more localised food system, thereby improving food security and sovereignty in Yukon. The findings constitute the scientific knowledge base for the formulation of prospective scenarios in the spirit of the food sovereignty theory.

Estimating the sample size of sham-controlled randomized controlled trials using existing evidence.

Background: In randomized controlled trials (RCTs), the power is often 'reverse engineered' based on the number of participants that can realistically be achieved. An attractive alternative is planning a new trial conditional on the available evidence; a design of particular interest in RCTs that use a sham control arm (sham-RCTs). Methods: We explore the design of sham-RCTs, the role of sequential meta-analysis and conditional planning in a systematic review of renal sympathetic denervation for patients with arterial hypertension. The main efficacy endpoint was mean change in 24-hour systolic blood pressure. We performed sequential meta-analysis to identify the time point where the null hypothesis would be rejected in a prospective scenario. Evidence-based conditional sample size calculations were performed based on fixed-effect meta-analysis. Results: In total, six sham-RCTs (981 participants) were identified. The first RCT was considerably larger (535 participants) than those subsequently published (median sample size of 80). All trial sample sizes were calculated assuming an unrealistically large intervention effect which resulted in low power when each study is considered as a stand-alone experiment. Sequential meta-analysis provided firm evidence against the null hypothesis with the synthesis of the first four trials (755 patients, cumulative mean difference -2.75 (95%CI -4.93 to -0.58) favoring the active intervention)). Conditional planning resulted in much larger sample sizes compared to those in the original trials, due to overoptimistic expected effects made by the investigators in individual trials, and potentially a time-effect association. Conclusions: Sequential meta-analysis of sham-RCTs can reach conclusive findings earlier and hence avoid exposing patients to sham-related risks. Conditional planning of new sham-RCTs poses important challenges as many surgical/minimally invasive procedures improve over time, the intervention effect is expected to increase in new studies and this violates the underlying assumptions. Unless this is accounted for, conditional planning will not improve the design of sham-RCTs.

How eco-efficient are crop farms in the Southern Amazon region? Insights from combining agent-based simulations with robust order-m eco-efficiency estimation

Agricultural production plays an essential role in food security and economic development, but given its direct links within the environment, it is also an important driver of environmental degradation. It has become essential to not only produce more crops but doing it while maintaining or reducing the respective environmental impacts. A promising method for evaluating production efficiency is the nonparametric eco-efficiency analysis, which compares the economic value added against a composite environmental pressure indicator. This article proposes a novel method of evaluating the eco-efficiency scores, which does not depend on field survey data, but rather on multi-agent simulations. We present the first estimates of eco-efficiency for crop farms in the Amazon and Cerrado biomes in Brazil, identify regions and farm profiles that could be the focus of targeted interventions, and evaluate whether eco-efficiency scores could be improved using an alternative scenario. We combine a biophysical model with bioeconomic agent-based simulations to mimic land-use decisions of real-world farms. We then estimate the efficiency scores with an enhanced order-m estimator that conditions the efficiency estimates on explanatory variables, thus producing robust efficiency measures. Our simulations reveal that there are indeed differences in eco-efficiency estimates between macro-regions in the federal state of Mato Grosso. According to our simulations, the Southeast exhibited the greatest occurrences of inefficiencies, followed by the West macro-region. In our life-cycle inventory, sunflower cultivation had the lowest levels of environmental pressures. However, when evaluating it in a prospective scenario of infrastructure development, we could not observe a positive impact on efficiency. By using efficient computational methods, we replicate our simulations many times to create robust estimates that are more representative than a single field survey. In addition, our novel method combines simulated farm data with eco-efficiency analyses, allowing ex-ante impact evaluations where policy interventions can be tested before their implementation.

Construction of Prospective Scenarios through the MOMENTUM Method: a case study on Federal Highways in Brazil

The main transport mode in Brazil is road transport. Therefore, highways play an important role in moving the country's economy. In the last survey on their conservation status in 2021, it was found that more than 60% of Brazilian roads were considered unsatisfactory. Therefore, the objective of this work is to prospect scenarios for federal highways in Brazil, from the Momentum Method. To this end, visits and inspections were carried out, from Unmanned Aerial Vehicles, on two of the main highways that cross the country: the BR-230 and the BR-101. The results, after the modeling of the problem, indicated three possible scenarios for the Federal Highways, due to the variables dollar price, investment, fuel price, and economic crisis, which have significant impact and dependence on the evaluated system: scenario "Sea of Holes", scenario "Only necessary" and scenario "Cruising Speed”.

Prospective scenarios applied in course portfolio management: An approach in light of the Momentum and ELECTRE-MOr methods

The Training & Development (T&D) sector is gaining increasing importance on organizations’ day, acting as a tool for improving organizational performance. The objective of this paper is, through the application of the Momentum method, to analyze the demand of customers for a company in the field of corporate training in Brazil, considering different contexts and, from this, to propose a decision-making process to the increase efficiency and effectiveness of its procedures, prioritizing T&D courses that present more return and relevance to the organization. For this purpose, we use the Momentum method to prospect scenarios, establishing a relationship between the variables that make up each scenario and the portfolio of courses offered by the company. Besides, we applied the ELECTRE-MOr Multicriteria Decision Support (MDS) method to propose a line of action taken by the company, taking into account the trend scenario. The results obtained were satisfactory, providing support to strategic decision making in the composition of the courses portfolio offered, resulting in a classification of them, presenting those who should be prioritized, maintained or discarded by the company’s management. It is emphasized that the methodology presented in this work can be applied in other sectors - tactical, operational or strategic - presenting relevance to academia and society.

Federalism in Nepal: An Appraisal Issue for Implementing Prospective Scenario

Federalism in Nepal: An Appraisal Issue for Implementing Prospective Scenario

HAZARD IDENTIFICATION AND PROBABLISTIC SCENARIO SELECTION FOR SHIP- SHIP COLLISION ACCIDENTS


 
 
 In collision risk-based design frameworks it is necessary to accurately define and select a set of credible scenarios to be used in the quantitative assessment and management of the collision risk between two ships. Prescriptive solutions and empirical knowledge are commonly used in current maritime industries, but are often insufficient for innovation because they can result in unfavourable design loads and may not address all circumstances of accidents involved. In this study, an innovative method using probabilistic approaches is proposed to identify relevant groups of ship-ship collision accident scenarios that collectively represent all possible scenarios. Ship-ship collision accidents and near-misses recently occurred worldwide are collated for the period of 21 years during 1991 to 2012. Collision scenarios are then described using a set of parameters that are treated individually as random variables and analysed by statistical methods to define the ranges and variability to formulate the probability density distribution for each scenario. As the consideration of all scenarios would not be practical, a sampling technique is applied to select a certain number of prospective collision scenarios. Applied examples for different types of vessels are presented to demonstrate the applicability of the method.
 
 

Global trends in the digital transformation of the healthcare industry

National health systems are experiencing a number of common global challenges: population growth, demographic ageing, the prevalence of chronic noncommunicable diseases, the constant growth of health-care costs, while increasing resource scarcity, including staffing. At the same time, the rapid development of information technologies, including the accumulation of big data, artificial intelligence, telemedicine, remote patient monitoring, and the increasing availability of high-performance mobile devices and a high-speed Internet connection create truly unique prospects for the development of digital healthcare products and services. Growth of investment from tech giants and venture capital funds is one of the main drivers of digital healthcare transformation. More and more innovative products are being offered not to enhance the effectiveness of existing processes within health systems, but to create new alternative ways to receive medical care or reduce problems in its delivery. Thus, a key customer and a user of digital healthcare products is gradually becoming not the heads of medical organizations, public health authorities or doctors, but patients themselves. In this article, we present an analysis of the existing global trends and directions of development of the digital healthcare market, form our image of the future and the most prospective scenarios and technologies for products and services in this area.

Wind erosion response to past and future agro-pastoral trajectories in the Sahel (Niger)

ContextWind erosion plays a major role in land degradation in semi-arid areas, especially in the Sahel. There, wind erosion is as sensitive to land use and land management as to climate factors. Future land use intensification may increase wind erosion and induce regional land degradation.ObjectiveWe aimed to estimate wind erosion responses to changing land management in a Sahelian region.MethodsWe defined land use intensification scenarios for a study site in southwestern Niger for two historical situations (1950s and 1990s), and two alternative prospective scenarios (2030s: extensive or intensive). We simulated vegetation growth and horizontal sediment flux of wind erosion for the corresponding landscapes.ResultsAnnual amounts of horizontal sediment flux increased with land management changes from 1950s (nil flux) to 1990s (176 kg m−1 yr−1) and 2030s (452 to 520 kg m−1 yr−1), mostly because of differences in land use, declining soil fertility, and practices decreasing the dry vegetation. For 2030s, intensive scenario exhibited larger vegetation yields than extensive conditions, but similar large values of horizontal sediment flux, thus questioning the sustainability of both scenarios. Realistic sets of practices had as large an influence as the largest theoretical range of practices on the variability of annual horizontal sediment flux. This variability was as large as that due to meteorological conditions.ConclusionsThis study demonstrates that the environmental impact of land use and management practices, of which wind erosion is an aspect, must be assessed at the landscape scale to account for the variability in land cover and associated land management.

On the brink of disruption: Applying Resilience Engineering to anticipate system performance under crisis

As COVID-19 spread across Brazil, it quickly reached remote regions including Amazon's ultra-peripheral locations where patient transportation through rivers is added to the list of obstacles to overcome. This article analyses the pandemic's effects in the access of riverine communities to the prehospital emergency healthcare system in the Brazilian Upper Amazon River region. To do so, we present two studies that by using a Resilience Engineering approach aimed to predict the functioning of the Brazilian Mobile Emergency Medical Service (SAMU) for riverside and coastal areas during the COVID-19 pandemic, based on the normal system functioning.Study I, carried out before the pandemic, applied ethnographic methods for data collection and the Functional Resonance Analysis Method - FRAM for data analysis in order to develop a model of the mobile emergency care in the region during typical conditions of operation. Study II then estimated how changes in variability dynamics would alter system functioning during the pandemic, arriving at three trends that could lead the service to collapse. Finally, the accuracy of predictions is discussed after the pandemic first peaked in the region.Findings reveal that relatively small changes in variability dynamics can deliver strong implications to operating care and safety of expeditions aboard water ambulances. Also, important elements that add to the resilient capabilities of the system are extra-organizational, and thus during the pandemic safety became jeopardized as informal support networks grew fragile. Using FRAM for modelling regular operation enabled prospective scenario analysis that accurately predicted disruptions in providing emergency care to riverine population.

Single and double null equilibria in the SMART Tokamak

The SMall Aspect Ratio Tokamak (SMART) device is a novel, compact (R geo = 0.42 m, a = 0.22 m, A ≥ 1.70) spherical tokamak, currently under development at the University of Seville. The SMART device is being developed over 3 phases, with target on-axis toroidal magnetic fields between 0.1 ≤ B ϕ ≤ 1.0 T, and target plasma currents of between 35 ≤ I p ≤ 400 kA; with phases 2 and 3 enabling access to a wide range of elongations (κ ≤ 2.30) and triangularities ( − 0.50 ≤ δ ≤ 0.50). SMART employs four internal divertor coils with two internal and two external poloidal field coils, enabling operation in lower-single, upper-single and double-null configurations. This work examines phase 3 of the SMART device, presenting a prospective L-mode discharge scenario without external heating, before examining five highly-shaped equilibria, including: two double null triangular configurations, two single null triangular configurations and a baseline double null configuration. All equilibria are obtained via an axisymmetric Grad-Shafranov force balance solver (Fiesta), in combination with a circuit equation rigid current displacement model (RZIp) to obtain time-resolved vessel and plasma currents.

Geometric motion transfer between two indirectly coupled mechanical resonators

Phonon-mediated motion transfer plays an essential role in scalable phononic devices. We present geometric motion transfer between two mechanical resonators, which are indirectly coupled by parametrically coupling to the same intermediate mechanical mode. The phonon-mediated coupling is controlled so that the intermediate mode remains unoccupied after the system undergoes a cyclic evolution. Pure geometric motion transfer between the indirectly coupled mechanical resonators is achieved experimentally through a controlling motion evolution path in the Hilbert space. Because the geometric phase is robust against local fluctuation of the evolution path, our research provides a prospective scenario for noise-resilient phonon-based information processing.

Historical Changes and Future Trajectories of Deforestation in the Ituri-Epulu-Aru Landscape (Democratic Republic of the Congo)

The Ituri-Epulu-Aru landscape (IEAL) is experiencing deforestation and forest degradation. This deforestation is at the root of many environmental disturbances in a region characterized by endemism in biodiversity. The importance of this article is to provide useful information for those who wish to discuss a model that can be replicated for other territories affected by deforestation and changes in natural and anthropogenic forest structure. This article focuses on the triangulation of spatialized prospective scenarios in order to identify future trajectories based on the knowledge of historical dynamics through the diachronic analysis of three satellite images (2003–2010–2014–2016). The scenarios were designed in a supervised model implemented in the DINAMICA EGO platform. The three scenarios: business as-usual (BAU), rapid economic growth (REG) and sustainable management of the environment (SME), extrapolating current trends, show that by 2061 this landscape will always be dominated forests (+84%). Old-growth forests occupy 74.2% of the landscape area in the BAU scenario, 81.4% in the SEM scenario and 61.2% in the REG scenario. The SEM scenario gives hope that restoration and preservation of biodiversity priority habitats is still possible if policy makers become aware of it.

Projecting LBM performance on Exascale class Architectures: A tentative outlook

In the next years, the first Exascale class supercomputers will go online. In this paper, we portray a prospective Exascale scenario for a Lattice Boltzmann (LB) code, based on the performance obtained exploiting an up-to-date Petascale HPC facility. Although extrapolation is always a perilous exercise, in this work we aim to lay down a few guidelines to help the LBM community to carefully plan larger and more complex simulations using the forthcoming Exascale supercomputer machines.

Energy Harvesting and Power Management for IoT Devices in the 5G Era

The fifth-generation (5G) network is a fast-growing technology that impacts personal devices for both society and the economy. With the widespread Internet of Things (IoT) devices in such networks, powering and exploring energy to operate them is vital in the 5G era. Therefore, projecting and forecasting how to power IoT devices in the 5G network have already begun, with an aspiration to provide self-powered and green future communication services. Here, we provide a vision for energy harvesting technologies for IoT devices (e.g., emerging wearable and implantable devices employed in healthcare and consumer technologies) that can aid the research line in the 5G era. We propose that various power harvesting and management techniques at the circuit, device, and system levels will be the most crucial segment of IoT devices. Thus, self-power and sustainability should be key features of IoT devices in the 5G network, and ought to be given close attention by electronics and communications communities. To envision this concept, we provide a systematic outline in which prospective power harvesting scenarios of IoT devices in the 5G network are expected. We successively describe vital potential landscapes of 5G and evaluate the energy harvesting and power management requirements. We additionally investigate the challenges beyond energy technologies that could impede the 5G enhancement.