Part Of Solution Research Articles

Empowering minorities and everyone in participatory budgeting: an agent-based modelling perspective.

Currently, there are increasing attempts to better involve citizens in political decision processes. A successful approach in that regard has been participatory budgeting (PB), which allows citizens to propose projects and then decide how to distribute a given budget over them. Meanwhile, the literature on collective intelligence (CI) has also shown the ability of groups to solve complex problems. Thus, by combining CI and PB, it should be possible for citizens to identify problems and create their own solutions. In this article, we study this possibility by using agent-based models. Specifically, we first show that a system combining CI and PB produces solutions that strongly penalize minorities if the solution quality depends on group size. Then, we introduce an approach that can overcome this issue. Indeed, by using a common knowledge base for the storage of partial solutions, the quality of solutions of minorities can benefit from the work of the majority, thereby promoting fairness. Interestingly, this approach also benefits majorities, as the quality of their solutions is further improved by the work of the minorities, thus reaching better solutions for everyone. This stresses the potential and importance of an open innovation approach, which is committed to information sharing.This article is part of the theme issue 'Co-creating the future: participatory cities and digital governance'.

ISI Energy Change Due to an Edge Deletion

ABSTRACTThe problem of characterization of all graphs where the deletion of an edge results in decrease or increase in the energy is far from completion. To be more exact, we solve this problem for Inverse Sum Indeg energy. We compute the ISI energies of edge deleted graphs of , , , and star graph, finally we compare the respective energies from the original graphs. We give different graphs where both cases can happen. This serves as partial solutions of the modified version of the hard to crack problem posed by Gutman to characterize all graphs whose energy decreases after deletion of an edge.

Making Decisions When Outcomes are Irreducible: Shackle's Imagination and Virtual Reality

ABSTRACTThis paper addresses the challenge of navigating irreducible outcomes, where predicting future patterns proves futile despite understanding the underlying rules. It advocates for G.L.S. Shackle's imagination‐focused decision approach as a partial solution. Integrating the concept of the extended mind, I argue that modern technological advances such as Virtual Reality (VR) further enhance Shackle's approach, rather than compromising its subjective nature. In light of the challenges in applying reductivist tools to the outcomes of VR, I propose Shackle's framework as a promising framework for integrating such outcomes into decision‐making processes. Via this framework, decision‐makers capitalize on large` gains and hedge against large losses, despite not fully overcoming irreducibility.

Influence of rope fastening on the spectrum of its natural transverse vibrations

According to the previously developed method, which takes into account the bending stiffness of steel ropes during their transverse oscillation, the ropes of the pedestrian bridge ‘Lovers’ in the city of Tyumen were investigated. The obtained values of tension forces and bending stiffness were within the expected range. The high variation of bending stiffness values forced to pay attention to the accuracy of the initial values of rope lengths, which were obtained from the photograph. To measure the rope lengths, a method of nodal harmonic registration was proposed, but the results obtained by this method were higher than the values obtained from the photograph. The evaluation of measurement errors did not explain this overestimation, which led to the necessity to revise the solution of the differential equation of transverse oscillations. It turned out that previously only its partial solution was considered, assuming a hinged rope attachment, whereas it is cantilevered and has a bending reaction. Taking this feature into account by introducing an additional boundary condition allowed to improve the calculation model and explain the overestimation of the rope length in the method of nodal harmonics.Taking into account the nature of the rope attachment allowed us to introduce a generalised parameter s, which takes zero value for rigid cantilever attachment, and is equal to one for articulated attachment. Then the stiffness weakening inside the anchorage will be manifested by the growth of the parameter s and can be detected by the results of the oscillation spectrum registration.

Navigating Emerging Climate Crises Through Adaptive Polycentric Meta-networks

AbstractWithout urgent, systemic, and collective global interventions to address the emerging climate emergency, we are likely to continue to see a range of increasingly significant adverse impacts globally. Temperatures will continue to increase, ice shelves will melt, seas will rise, crops will fail, water scarcity will increase and spread, wildfires will accelerate, and food and water insecurity, violence, and the largest human migration in history will ensue. According to the Institute for Economics and Peace (IEP), these climate changes will displace over 1.2 billion people by 2050 at a rate currently exceeding 21.5 million people per year. This mass migration will create incredible burdens on political, legal, economic, agricultural, educational, and health infrastructures in future host countries, and we are globally unprepared. It is well-recognized that the solution to these crises lies in our collective awakening by embracing complexity and employing bold and holistic perspectives. However, theoretical and applied advancements that may meaningfully inform practical approaches to urgently address climate related threats remain scattered and insufficient. The purpose of our proposed paper is to advance the concept of adaptive polycentric meta-networks (APMNs) as a partial solution to collectively address climate crises. We draw upon key insights from works on polycentricity, complexity leadership, and meta-networks, to arrive at our integrative framework. We also discuss ways that the proposed framework aligns with the dynamics of collective mindfulness and practical wisdom, particularly to facilitate cross-sector and global collaborations, across cultures and spiritual practices, to achieve the climate change goals at a macro scale. We believe that our framework offers an important conceptual and practical pathway to tackle the complex dynamics of climate change, and to generate the needed collective sensemaking and awareness to awaken, engage, and align collective leadership where it is needed, at global, national, regional and local levels and across governments, NGOs, and corporate interests.

Joint Learning of Volume Scheduling and Order Placement Policies for Optimal Order Execution

Order execution is an extremely important problem in the financial domain, and recently, more and more researchers have tried to employ reinforcement learning (RL) techniques to solve this challenging problem. There are a lot of difficulties for conventional RL methods to tackle the order execution problem, such as the large action space including price and quantity, and the long-horizon property. As naturally order execution is composed of a low-frequency volume scheduling stage and a high-frequency order placement stage, most existing RL-based order execution methods treat these stages as two distinct tasks and offer a partial solution by addressing either one individually. However, the current literature fails to model the non-negligible mutual influence between these two tasks, leading to impractical order execution solutions. To address these limitations, we propose a novel automatic order execution approach based on the hierarchical RL framework (OEHRL), which jointly learns the policies for volume scheduling and order placement. OEHRL first extracts the state embeddings at both the macro and micro levels with a sequential variational auto-encoder model. Based on the effective embeddings, OEHRL generates a hindsight expert dataset, which is used to train a hierarchical order execution policy. In the hierarchical structure, the high-level policy is in charge of the target volume and the low-level learns to determine the prices for a series of the allocated sub-orders from the high level. These two levels collaborate seamlessly and contribute to the optimal order execution policy. Extensive experiment results on 200 stocks across the US and China A-share markets validate the effectiveness of the proposed approach.

Riemannian invariants for warped product submanifolds in Q ε m × R {{\mathbb{Q}}}_{\varepsilon }^{m}\times {\mathbb{R}} and their applications

Abstract This article investigates the geometric and topologic of warped product submanifolds in Riemannian warped product Q ε m × R {{\mathbb{Q}}}_{\varepsilon }^{m}\times {\mathbb{R}} . In this respect, we obtain the first Chen inequality that involves extrinsic invariants like the length of the warping functions and the mean curvature. This inequality involves two intrinsic invariants (sectional curvature and δ \delta -invariant). In addition, an integral bound is provided for the Bochner operator formula of compact warped product submanifolds in terms of the Ricci curvature gradient. We aim to apply this theory to many structures and obtain Dirichlet eigenvalues for problem applications. Some new results regarding the vanishing mean curvature are presented as a partial solution, and this can be considered for the well-known problem given by Chern.

Computationally efficient and error aware surrogate construction for numerical solutions of subsurface flow through porous media

Limiting the injection rate to restrict the pressure below a threshold at a critical location can be an important goal of simulations that model the subsurface pressure between injection and extraction wells. The pressure is approximated by the solution of Darcy’s partial differential equation for a given permeability field. The subsurface permeability is modeled as a random field since it is known only up to statistical properties. This induces uncertainty in the computed pressure. Solving the partial differential equation for an ensemble of random permeability simulations enables estimating a probability distribution for the pressure at the critical location. These simulations are computationally expensive, and practitioners often need rapid online guidance for real-time pressure management. An ensemble of numerical partial differential equation solutions is used to construct a Gaussian process regression model that can quickly predict the pressure at the critical location as a function of the extraction rate and permeability realization. The Gaussian process surrogate analyzes the ensemble of numerical pressure solutions at the critical location as noisy observations of the true pressure solution, enabling robust inference using the conditional Gaussian process distribution.Our first novel contribution is to identify a sampling methodology for the random environment and matching kernel technology for which fitting the Gaussian process regression model scales as O(nlogn) instead of the typical O(n3) rate in the number of samples n used to fit the surrogate. The surrogate model allows almost instantaneous predictions for the pressure at the critical location as a function of the extraction rate and permeability realization. Our second contribution is a novel algorithm to calibrate the uncertainty in the surrogate model to the discrepancy between the true pressure solution of Darcy’s equation and the numerical solution. Although our method is derived for building a surrogate for the solution of Darcy’s equation with a random permeability field, the framework broadly applies to solutions of other partial differential equations with random coefficients.

Towards designing a comprehensive composite index for social vulnerability to natural hazards in the big data era: potential challenges and partial solutions

AbstractThis study provides a practical definition and framework to measure social vulnerability to natural hazards, addressing gaps in the literature after three decades of Susan Cutter's Place-Based Model. The current social vulnerability index, designed based on available data such as census data, is limited in capturing all aspects of social vulnerability and spatial inequalities. This research explored and proposed a new theoretical perspective and methodological framework for designing a comprehensive index for social vulnerability to natural disasters using emerging big data, which is practical and feasible and can be applied to social vulnerability studies in general and social vulnerability to natural hazards in particular. This research first defines constructs of social vulnerability to natural hazards, including (1) socioeconomic status or conditions, (2) physical infrastructure or accessibility to facilities and services, (3) ecological-environmental conditions, (4) access to security facilities and crime rate, (5) technological inequalities, (6) health conditions of the citizens, and (7) susceptibility. Then, it proposes potential solutions for developing a comprehensive composite index under ideal conditions without (big) data limitations, using the US and the UK as case examples. These solutions are not just theoretical but also practical and feasible, instilling confidence in their implementation. This research offers valuable insights for researchers and policymakers in diverse sectors, supporting the design of effective disaster risk reduction strategies and intervention programs.

Forced vibrations of the shaft line based on the model of a two-stage rod with an elastic connection of sections

The paper considers a method for solving the problem of dynamics of forced vibrations of a wall line based on a model of an equivalent elastic two-stage rod with a pliable connection of sections. The model is represented by a system of partial differential equations. The solution of the equations is obtained by the Fourier method for eigenfunctions orthogonal with weight. It is established that the presence of an elastic element at the junction of the sections does not affect the orthogonality of the eigenfunctions. The influence of the elastic coupling compliance coefficient on the natural frequency spectrum of the shaft line is estimated. The obtained forms of natural vibrations of an equivalent elastic two-stage rod are consistent in appearance with the corresponding forms known in the literature for a discrete model of a similar torsional circuit. A partial solution of the equations is found for the case of the action of the harmonic load on the engine and the averaged torque on the propeller. As an example, the dynamics of forced vibrations of the shaft line of a barge of the Sosnovka type is studied. The results of calculating the natural frequencies of the considered model are compared with the classical discrete mass method. The analysis of the obtained plots of the twisting angles and torques showed that the angles are satisfactorily approximated by the first proper oscillation shape, and for moments, high shapes must be taken into account. The comparison of the simulation results with the data of the torsiogram obtained under production testing conditions indicates the need for further development of the model. Further improvement of the torsional circuit, as well as a more detailed study of the nature of the operating loads, are considered as promising areas of research.

Filling the gaps: grassroots prevention of domestic and family violence within the Korean-Australian community

This study focuses on the bridging roles of grassroots community groups from migrant communities in Australia, specifically in the context of domestic and family violence (DFV). Through in-depth interviews with 15 victim-survivors and 16 practitioners and community volunteers of Korean heritage, the study examines how members of the Korean community are attempting to fill the gaps in social support for victim-survivors of DFV and what issues, barriers and limitations they face. The results indicate that community members face multiple barriers in their efforts to fill gaps in service, which in turn affects the quality of their response to victim-survivors. This study argues that the emergence of a peer-support network is a response and even a partial solution to those barriers and limitations, challenging the traditional community groups (for example, ethnic churches) that used to serve as a main platform for the Korean diasporic community in Australia. A deeper understanding and engagement with these emerging networks are needed to fill the gap in the work investigating DFV response and prevention within Australian-Asian communities.

Slow codes, multiple layers of deception, and partial solutions.

It is not unusual for patients or families to disagree with healthcare professionals (HCPs) over best treatment options. Conversation typically results and mutually agreeable choices are implemented. Rarely, but increasingly, patients or families will request, even demand, interventions the treating team believes will be ineffective (they will not achieve the intended goal) or inappropriate (the medical or moral harms clearly outweigh any potential benefits). One's duty as an HCP requires one to refuse such interventions, but resulting patient or family conflict makes such refusals challenging, even traumatic, and HCPs often acquiesce. Some states have legal options that protect HCPs and their respective institutions when they make such unilateral choices, but the process is complex, time-consuming, and emotionally fraught. In this paper, We describe one especially difficult case, using it as a paradigmatic example of when, and why, a slow code is sometimes, if rarely, justified. We also discuss strategies HCPs can use to reduce the need for this, admittedly problematic, solution.

Maximal extractable value: Current understanding, categorization, and open research questions

In traditional financial markets, front-running is a well-structured phenomenon. It represents a form of privileged actors utilizing knowledge or power advantages to extract undue profit at the cost of other stakeholders. Various mitigation strategies have emerged, ranging from market design to regulatory measures. More recently, a similar and substantially richer variety of means to gain unethical profit from power asymmetries has appeared in the context of blockchain-based decentralized applications. This phenomenon is called “maximal extractable value” (MEV). Despite the decentralized nature and inherent transparency of blockchain ledgers, MEV is particularly prevalent and challenging to mitigate. While related work in computer science and algorithmic game theory has already identified several different ways in which MEV manifests in decentralized finance (DeFi) and outlined partial solution approaches, a discussion of its impacts in the information systems (IS) domain is still absent. A holistic definition of MEV and how it can be exploited is necessary for the discussion of its potential implications for blockchain-based IS for businesses and public institutions. This paper conducts a systematic literature review to close this gap. It consolidates the diverging definitions of MEV and provides a categorization of the different ways in which it can manifest. As such, we synthesize and review the existing state of knowledge on MEV and point to undiscovered areas relevant to decentralized electronic markets in the form of a research agenda.

Perform assessment of COLREGs onboard a maritime autonomous surface ship: Narrow Channels and Traffic Separation Schemes

Abstract The usage of Maritime Autonomous Surface Ships in coastal and heavily used maritime environments necessitates advanced navigation systems capable of fully complying with the International Regulations for Preventing Collisions at Sea 1972 and not only open sea encounters. A significant challenge in this domain is enabling autonomous vessels to understand and navigate complex collision avoidance scenarios dictated by Rule 9 Narrow Channels and Rule 10 Traffic Separation Schemes. These rules are not well covered by research and only partial solutions have been proposed. To address this, we propose a ruleset for a system that can blend the traffic situation and geometric constraints extracted from Electronic Navigational Charts in S-57 format. The proposed ruleset extends our previous work on operationalization of COLREGs by introducing spatial features describing the maritime geometries relevant for traffic situations in Narrow Channels and Traffic Separation Schemes. We apply the ruleset to various traffic situations, showing how the inclusion of geometric context improves decision-making by reducing ambiguity and therefore enables the assessment of traffic situations and ship encounters in the vicinity of Narrow Channels and Traffic Separation Schemes. Our work outlines how the integration of spatial features into a rule-based system enables autonomous navigation capabilities of MASS for safe operations and compliance with maritime regulations.

Improving the training performance of generative adversarial networks with limited data: Application to the generation of geological models

In the past years, there is a growing interest in the applications of Generative Adversarial Networks (GANs) to generate geological models. Although GANs have proven to be an effective tool to learn and reproduce the complex data patterns present in some geological models, some challenges still remain open. Among others, a well-noticed problem is the need for a large number of samples to ensure high-quality training, which can be prohibitively expensive in some cases. As an attempt to offer a (possibly partial) solution to the aforementioned challenge, in this study, we investigate the feasibility and effectiveness of a zero-centered discriminator regularization technique for improving the performance of a GAN. Additionally, we evaluate an adaptive data augmentation technique to overcome the potential issue of limited training data, for the purpose of generating geologically feasible realizations of hydrocarbon reservoir models. Our findings demonstrate that a combination of the two techniques lead to notable performance improvements of a GAN. Particularly, it is observed that using the adaptive data augmentation technique in a GAN can yield similar results to those obtained by the GAN with a much larger dataset.

The Enka v. Chubb/Anupam Mittal v. Westbridge Controversies: Why Not the Hong Kong (Partial) Solution?

This paper explores the critical theme of determining the governing law of arbitration agreements amidst the intricate landscape of international arbitration. Focusing on divergent approaches from key jurisdictions, including England and Wales, Singapore, and Hong Kong, it elucidates the challenges posed by varying legal frameworks. Recent developments, such as potential statutory adjustments in England and Wales influenced by recommendations from the English Law Commission, underscore the need for clarity in governing law determinations. The controversial ‘composite test’ approach in Anupam Mittal v. Westbridge and the traditional English approach in Enka v. Chubb exemplifies the global concerns surrounding these divergent approaches, highlighting the complexities faced by common law courts worldwide. Drawing on these cases, the paper emphasizes the importance of parties expressly choosing the governing law of arbitration agreements to mitigate uncertainties. It underscores the potential positive contributions of model clauses and jurisdiction-specific approaches, such as the Hong Kong International Arbitration Centre (HKIAC) model clause and Hong Kong’s guidance for HKIAC arbitrations. The paper also addresses enforcement challenges, particularly in light of Article V(2)(b) of the New York Convention. It discusses the discretionary invocation of the public policy exception and its impact on enforcement efficacy, emphasizing the need for a holistic approach transcending contractual formalism.

New Applications of “Abeer-AL-Tememe” Transformation in partial differential equations

The Introduction of integral transforms as a partial differential equation solution technique results from the tremendous significance of differential equations and integral transforms in scientific domains. This study proposes a new integral transform Abeer Al- Tememe transform. The suggested transform applications has demonstrated its capacity to resolve partial differential equations.

ANALYTICAL CALCULATION OF A BEAM BASED ON AN ELASTIC WINKLER FOUNDATION WITH RANGE INHOMOGENITY

The aim of the study is the further development of analytical methods for calculating the bending of beams resting on a non-homogeneous continuous Winkler elastic foundation. This paper considers the case when the beam is under the influence of a uniformly distributed constant transverse load, and the inhomogeneity of the elastic foundation is given by a power function with an arbitrary non-negative power exponent . Fundamental functions and a partial solution of the corresponding differential equation of beam bending are found in an explicit closed form. These functions are dimensionless and are represented by absolutely and uniformly convergent power series. In turn, the formulas for the parameters of the stress-strain state of the beam – deflection, angle of rotation, bending moment and transverse force – are expressed through the indicated functions. The unknown constants of integration in these formulas are expressed in terms of the initial parameters, which are after the implementation of the specified boundary conditions. Thus, the calculation of the beam for bending is reduced to the procedure of numerical implementation of explicit analytical formulas for the parameters of the stress-strain state. An example demonstrates the practical application of the obtained solutions. A prismatic concrete beam based on a cubic variable elastic foundation is considered. This case corresponds to the power value . The results of the calculation by the author's method are presented in numerical and graphical formats for the case when the left end of the beam is hinged and the right end is clamped. The numerical values obtained by the author's method are accurate, since the applied calculation method is based on the exact solution of the corresponding differential equation. The availability of such solutions makes it possible to evaluate the accuracy of solutions obtained using various approximate methods by comparison. For the purpose of such a comparison, the paper presents the calculation results obtained by the finite element method (FEM). The absolute error of the FEM method when calculating this design was determined.

Can Avatar Robots Assist Older People and Care Professionals? Evaluation of an Intervention Study in Eight Nursing Homes in Tokyo

Abstract Background Securing human resources to meet increasing demand for older people's care is challenging, particularly in Japan, where the pace of ageing is accelerating. Central and local government have been seeking partial solutions in assistive technologies such as robotics. Against such a background, the study was conducted in 8 nursing care homes in Tokyo, where avatar robots were tested to examine whether and how these robot interventions can affect the daily life of older people and care professionals. Methods Four different types of avatar robot (ORIHIME, NEWME, Piyokame and BOCCO) were introduced to and used in eight nursing care facilities, in order to create conversational opportunities over 12 weeks. Before–after studies were conducted, and a variety of data was collected (interpersonal communication, self-care and depressive tendencies using the International Classification of Functioning, Disability and Health (ICF) and InterRAI assessments). System usability scores (SUS) were collected from care professionals, who also performed a time-on-task analysis. Results Study participants who consented to taking part were 136 older adults (88.4±6.6 years old, 18 men and 118 women) and 63 care professionals. Participants with a high degree of dependency accounted for 31 percent. In total, 136 avatar robots were used. There was an overall, yet marginal, improvement for older people. While the SUS scores were poor, the majority (90 percent) responded that such devices would prove useful in the future. The time-on-task analysis indicates that more time can be secured for ‘person-to-person’ care. Conclusion Positive impacts of avatar robots (to increase the level of social interaction and communication) were observed. However, the results are inconclusive, and more needs to be done with regard to technology skills, competence enhancement and data collection methods for this type of research. The study was funded in part by the Tokyo Metropolitan Government.

The economywide impact of bioethanol production in South Africa

Bioethanol production as a substitute for petroleum in road transport fuels has been identified as a potential partial solution to environmental and socioeconomic challenges facing developing countries, including South Africa. Biofuels in motor vehicles emit fewer GHGs relative to conventional fuels, and their production can lead to economic growth and associated socioeconomic outcomes, including increased labour employment and improved household welfare. The objective of this paper was to quantify the socioeconomic impact of bioethanol production in South Africa using sugarcane as a feedstock and to assess the effects of increasing the size of the bioethanol plant. The study is based on the 2018 KwaZulu-Natal and South African Social Accounting Matrices (SAM), and two assumed scenarios are considered, namely a scenario where only export destined sugarcane is used to produce bioethanol (scenario I) and a scenario when all sugarcane is used to produce bioethanol (Scenario II). The SAMs modified from the SAMs initially compiled by Conningarth Economists were used to develop an input–output multipliers economic impact model. The production of bioethanol from sugarcane was anticipated to have positive socioeconomic impacts namely, an increase in the country’s GDP, employment growth, gross-capital formation, positive contribution to fiscus, improvement in household welfare and positive contribution to the balance of payment (BOP). Expanding the size of the bioethanol plant is expected to magnify the impacts. The study, therefore, recommends a removal of bottlenecks in bioethanol expansion, including high feedstock cost, limited investment, and absence of mandatory blending policy, amongst others.