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Background: Patient involvement is most common during the first phases of a research project. Despite good intentions, maintaining meaningful collaborations throughout the research process doesn't seem easy. Several training programmes for researchers and patients have been developed to stimulate continuous involvement. These are mostly one-time training sessions at the start of a project, for researchers and patients separately. We aimed to co-create a prolonged side-by-side programme for pairs of patient representatives and researchers, to stimulate mutual learning from the start and throughout the research projects. Methods: We developed a group training and peer-to-peer support programme lasting 2–3 years for 4–5 pairs of researchers and patient representatives working together on a research project. The programme took 30 h, spread over 6–8 meetings. The main goal was mutual and bi-directional learning and maintaining the collaboration throughout the research projects. From the start, the pairs were instructed to discuss communication, roles, expectations and responsibilities to prevent misunderstandings. The character of the meetings was intended to evolve from training and peer support into peer-group coaching and support for the whole group. The programme was not a fixed method, it was adjusted to the context and the needs of the participants. Results: Thus far, the programme has been applied in 5 groups, with varying health topics and types of research. Patients' prior knowledge of research methods and researchers' experience with patient involvement varied within the groups. As a result of the side-by-side training power imbalances within pairs were reduced. All participants gained knowledge and experience in patient involvement. In subsequent group coaching sessions, they discussed issues and dilemmas on an equal footing. Most pairs found their way of working together, adapted to the wishes and capabilities of both partners. Differences between pairs were found to improve the discussions. Conclusions: We co-created a prolonged side-by-side programme for pairs of patient representatives and researchers, to stimulate mutual learning from the start and throughout the research projects. The programme proved feasible for groups with different research types and health conditions. It fulfils an unmet need for researchers, patients and funders. Plain English summary: Patient involvement is most common at the start of a research project. Despite good intentions, maintaining meaningful collaborations throughout the research process doesn't seem easy. Several training programmes for researchers and patients have been developed to stimulate continuous involvement. These are mostly one-time training sessions, for researchers and patients separately. We suggest side-by-side training should allow patient representatives and researchers to learn from each other throughout the research project to stimulate mutual learning. We developed a 2–3 year group training and peer-group support programme for pairs of researchers and patient representatives working together on a research project. The main goal was mutual learning and maintaining the collaboration impactful throughout the research projects. The character of the meetings was intended to evolve from training into peer-group coaching. Thus far, the programme has been applied in 5 groups of 4–5 pairs each. From the start, the pairs were instructed to discuss roles, expectations and responsibilities to prevent misunderstandings. Most pairs found their form of collaboration throughout the programme. Differences between pairs proved to be very useful for discussion and mutual learning. At the end of the programme, the participants were able to reflect on patient involvement in research on an equal basis. The programme was suitable for groups with different research types and health conditions. The programme fulfilled an unmet need for researchers, patient representatives and funders. The programme was found to be feasible and the experiences to date are positive and promising. [ABSTRACT FROM AUTHOR]

The energy transition toward Net Zero Emission by 2060 hinges on the renewable energy power plants in Indonesia. Good practices in several countries suggest a peer-to-peer (P2P) energy trading system using blockchain technology, supported by renewable energy (solar panels), an innovation to provide equal access to sustainable electricity while reducing the impact of climate change. The P2P energy trading concept has a higher social potential than the conventional electricity buying and selling approach, such as that of PLN (the state-owned electricity company in Indonesia), which applies the network management concept but does not have a sharing element. This model implements a solar-powered mini-grid system and produces a smart contract that facilitates electricity network users to buy, sell, and trade electricity in rural areas via smartphones. This study aims to measure the stakeholders' perceptions of the peer-to-peer (P2P) energy trading model using blockchain technology in the Gumelar District, Banyumas Regency, Central Java Province, Indonesia. The stakeholders in question are representatives of Households (producers and consumers), Government, State Electricity Company (PLN), Non-Governmental Organizations, Private Sector and Academician. Measurement of perception in this study used a questionnaire approach with a Likert scale. The results of filling out the questionnaire were analyzed using four methods: IFE/EFE matrix; IE matrix; SWOT matrix; and SPACE matrix to assess the results and their suitability to each other. The results of the stakeholder perception assessment show that there are 44 internal factors and 33 external factors that can influence this model. We obtained an IFE and EFE score of 2.92 and 2.83 for the internal and external results using the IE matrix. These place the model in quadrant V, meaning the P2P model can survive in the long term to generate profits. Based on the SWOT analysis results, this model is located at the coordinate point −0.40, 0.31, placing it in quadrant II. This means that the P2P model is in a competitive situation and faces threats but still has internal strengths. Based on the SPACE matrix, stakeholder perception states that the P2P model is at coordinate point 1, −0.3. This shows that the P2P model has the potential to be a competitive advantage in its type of activity that continues to grow. In conclusion, our findings show that stakeholders' perceptions of P2P models using blockchain technology can be implemented effectively and provide social, economic, and environmental incentives. [ABSTRACT FROM AUTHOR]

This research explores the concept of Worldwide one network (WON), a hypothetical ultra-large scale ad-hoc wireless network characterized by its non-hierarchical, open, scalable, homogeneous, and autopoiesis nature. The primary objectives are to address challenges in network formation, individual node unique addressing, and network management. This paper proposes a novel addressing mechanism named 'Cubid', which utilizes geo-coordinates as the primary identifier for network nodes with 1 m resolution and aims for at least 512 unique node addresses per cubic meter space on Earth. Unique three-dimensional address space, received signal strength based trilateration for network formation, address negotiation, and the use of Cubid as a MAC address to bypass traditional Layer 2–3 Internet Protocol activities are few of the differentiator aspects involved in this research work. Preliminary tests of this hypothetical network yield in practical viability of identifying network node's geographical coordinates with an accuracy of 3 m without GPS devices, and corresponding simulations results in an average frame delivery time of 27 ms over a 100-hop, varying hop length network path. These findings indicate that WON could serve as a viable alternative communication network, especially when substantial infrastructure-based networks, such as the Internet fails. [ABSTRACT FROM AUTHOR]

The prevalence of peer-to-peer operation among industrial energy hubs is considered a promoting method to enhance local energy autonomy, efficiency, and flexibility. By conducting stochastic programming, this paper aims to minimize the operating cost of multiple industrial energy hubs that trade power and heat energies with each other and utility. Concerning the important role of hydrogen systems, fuel cell-based combined heat and power (CHP) generators are employed within the hubs to increase sustainability. The presence of electric vehicles (EVs) and shiftable loads enhances the flexibility during peer-to-peer operating mode. The trading price for power and heat energies are derived at first by solving a deterministic problem and considering average values for demands and generation. However, to address the uncertainties in renewable generation, electric and heat demands, and electricity prices under operation, scenario-based stochastic programming tries to optimize the expected objective function. Furthermore, the Conditional Value-at-Risk (CVaR) approach is proposed to provide various risk-averse scheduling tactics and measure the risk of each scenario. The results show that the proposed risk-constrained approach reduces the risk and makes cautious decisions about energy resources and trades. In this regard, the expected profit has been reduced by 75%, i.e., from 1636.78 NOK under a risk-neutral case to 414.97 NOK under a risk-averse case to reduce the expected risk in operating cost. [Display omitted] • Techno-economic analysis of hubs facilitating energy transaction is investigated. • Considering fuel cell-based CHP, EVs and shiftable loads for increased flexibility. • Peer-to-peer energy exchange is considered fostering local energy autonomy. • Stochastic programming modeled uncertainties of renewables, demands and prices. • Risk analysis of energy transactions is addressed using conditional value-at-risk. [ABSTRACT FROM AUTHOR]

Aims: The aim of this work was to measure the impact of P2P (i.e. peer‐to‐peer), a peer‐led smoking prevention intervention, on daily smoking prevalence of adolescents over 2 school years. Design: A cluster‐randomized controlled trial was performed over a 16‐month follow‐up (trial status: closed to follow‐up). P2P was implemented 1–3 and 13–15 months after baseline. Assessments took place at baseline and 4, 10 and 16 months after baseline. The research team, assessors and adolescents were blinded to the study‐arm assignment only at baseline. Setting: Fifteen vocational high schools in France were randomized into two clusters, using a 1:1 allocation ratio per French department (n intervention = 7, n control = 8). Participants: Participants comprised a sample of 2010 students in year 11 (i.e. 15–16 years) in vocational high schools. A total of 437 students could not be assessed at baseline (absent or left school), yielding a total sample of 1573 students (n intervention = 749, n control = 824). Intervention and comparator: The P2P programme trained voluntary students to become peer educators and design smoking prevention actions for their schoolmates in the intervention group (n = 945 students), compared with a passive control group (n = 1065 students). Measurements The primary outcome was change from baseline in the prevalence of self‐reported daily smoking (i.e. at least one cigarette per day) at 16 months. Findings The 'time × group' interaction indicated that, compared with the control group, the intervention group had statistically significantly fewer daily smokers after 16 months [odds ratio (OR) = 0.33, 95% confidence interval (CI) = 0.20, 0.53]. Similarly, compared with the control group, the intervention group had statistically significantly fewer daily smokers after 4 months (OR = 0.50, 95% CI = 0.30, 0.82) and 10 months (OR = 0.60, 95% CI = 0.37, 0.98). No adverse events of P2P2 were reported. Conclusions: A cluster‐randomized trial found evidence that the peer‐led P2P (peer‐to‐peer) smoking prevention intervention reduced the uptake of daily smoking among high school students in France over 16 months. [ABSTRACT FROM AUTHOR]

Peer-to-Peer (P2P) energy trading is a new financial mechanism that can be adopted to incentivize the development of distributed energy resources (DERs), by promoting the selling of excess energy to other peers on the network at a negotiated rate. Current incentive programs, such as net metering (NEM) and Feed-in-Tariff (FiT), operate according to a centralized policy framework, where energy is only traded with the utility, the state-owned grid authority, the service provider, or the power generation/distribution company, who also have the upper hand in deciding on the rates for buying the excess energy. This study presents a comparative analysis of three energy trading mechanisms, P2P energy trading, NEM, and FiT, within a rural microgrid consisting of two prosumers and four consumers. The microgrid serves as a practical testbed for evaluating the economic impacts of these mechanisms, through simulations considering various factors such as energy demand, production variability, and energy rates, and using key metrics such as economic savings, annual energy bill, and wasted excess energy. Results indicate that while net metering and FiT offer stable financial returns for prosumers, P2P trading demonstrates superior flexibility and potentially higher economic benefits for both prosumers and consumers by aligning energy trading with real-time market conditions. The findings offer valuable insights for policymakers and stakeholders seeking to optimize rural energy systems through innovative trading mechanisms. [ABSTRACT FROM AUTHOR]

Abstract Background Patient involvement is most common during the first phases of a research project. Despite good intentions, maintaining meaningful collaborations throughout the research process doesn't seem easy. Several training programmes for researchers and patients have been developed to stimulate continuous involvement. These are mostly one-time training sessions at the start of a project, for researchers and patients separately. We aimed to co-create a prolonged side-by-side programme for pairs of patient representatives and researchers, to stimulate mutual learning from the start and throughout the research projects. Methods We developed a group training and peer-to-peer support programme lasting 2–3 years for 4–5 pairs of researchers and patient representatives working together on a research project. The programme took 30 h, spread over 6–8 meetings. The main goal was mutual and bi-directional learning and maintaining the collaboration throughout the research projects. From the start, the pairs were instructed to discuss communication, roles, expectations and responsibilities to prevent misunderstandings. The character of the meetings was intended to evolve from training and peer support into peer-group coaching and support for the whole group. The programme was not a fixed method, it was adjusted to the context and the needs of the participants. Results Thus far, the programme has been applied in 5 groups, with varying health topics and types of research. Patients’ prior knowledge of research methods and researchers' experience with patient involvement varied within the groups. As a result of the side-by-side training power imbalances within pairs were reduced. All participants gained knowledge and experience in patient involvement. In subsequent group coaching sessions, they discussed issues and dilemmas on an equal footing. Most pairs found their way of working together, adapted to the wishes and capabilities of both partners. Differences between pairs were found to improve the discussions. Conclusions We co-created a prolonged side-by-side programme for pairs of patient representatives and researchers, to stimulate mutual learning from the start and throughout the research projects. The programme proved feasible for groups with different research types and health conditions. It fulfils an unmet need for researchers, patients and funders.

Prosocial crowdfunding relies on funders' altruistic contribution to sustain. The channel structure of platforms may affect funders' altruistic incentives. It is critical to understand how funders choose different channels, direct vs. intermediated, and how the co-existence of the two channels affect funders' contribution. Our study builds a theoretical framework based on theories of altruism to understand funders' incentives, including pure altruism, warm glow, and reputation. The framework helps us to explicate funders' incentives for choosing between channels and predict potential changes in funder contribution after the introduction of the direct channel. Using data from Kiva.org and the unique setup of a natural experiment, we find that funders with high level of pure altruism are more likely to select the direct channel. We also find that the introduction of the new direct channel stimulates instead of cannibalizing contribution on the intermediated channel. It suggests that the direct channel segments riskier projects and meets the needs of pure altruists, while the intermediated channel promotes contribution to less risky projects with increased publicity. The market segments have a positive impact on the total contribution. We discuss the theoretical and practical implications of our findings. [ABSTRACT FROM AUTHOR]

Abstract Peer‐to‐peer energy trading enhances distribution network resilience by reducing energy demand from central power plants and enabling distributed energy resources to support critical loads after extreme events. However, adequate reserves from main grids are still required to ensure real‐time energy balance in distribution networks due to the uncertainty in renewable generation. This paper introduces a novel two‐stage joint energy and reserve market for prosumers, wherein local flexible resources are fully utilized to manage renewable generation uncertainty. In contrast to cooperative optimization methods, the interactions between prosumers are modelled as a generalized Nash game, considering that prosumers are self‐interested and should follow distribution network constraints. Then, linear decision rules are employed to ensure a feasible market equilibrium and develop a privacy‐preserving algorithm to guide prosumers the market equilibrium with a proven convergence. Finally, the numerical study on a modified IEEE 33‐power system demonstrates that the designed market effectively manages renewable generation uncertainty, and that the algorithm converges to the market equilibrium.

Hi'ilei Julia Kawehipuaakahaopulani Hobart and Tamara Kneese (2020) define radical care as 'as a set of vital but underappreciated strategies for enduring precarious worlds' (16). Yet they sound a note of caution when they argue that 'because radical care is inseparable from systemic inequality and power structures, it can be used to coerce subjects into new forms of surveillance and unpaid labor' (16). This article explores scaffolded peer-to-peer programmes as a form of radical care. In these programmes and approaches people are connected in non-hierarchical structures of mutual support and care that locate lived experience, rather than solely professional accreditation, as powerful, inclusive and collaborative expertise. The often implicit and traditional hierarchies of care are challenged in this structuring; we argue that the dynamic and horizontal structure of peer care practices can subvert and ultimately enrich circulating discourses of self-care, commodified care and the neoliberal devolution of responsibility for health and well-being to individuals. [ABSTRACT FROM AUTHOR]

Pricing power, a firm's ability to set prices above the competition without tempering demand, is a critical concern for any business. However, it has received little attention in the Airbnb pricing literature, although revenue maximization through effective pricing is a key priority for many Airbnb hosts. The Airbnb pricing literature has mainly examined price differences among diverse Airbnb properties, which fails to capture pricing power, as the properties being compared do not compete for the same guest segments. To address this gap, the present study examines pricing power and its sources on Airbnb. Drawing on the pricing power literature, the study develops a measure of pricing power based on a property's ability to set prices higher than the average price set by similar properties on Airbnb. Using data from thousands of Airbnb listings in Denver City from 2019 (before the COVID outbreak), the study estimates a model in which a property's pricing power is regressed on a range of property-, host-, and guest-related factors. The findings show that the most significant drivers of a property's pricing power are guest capacity (–), competition (–), distance (+), and booking price (+). The study discusses the implications of these findings. [ABSTRACT FROM AUTHOR]

The fields of indoor localization and positioning have seen extensive research in recent years. Their scientific soundness is of great importance, as information about an entity's location in indoor environments can lead to innovative services and products. Various techniques and frameworks have been proposed, some of which are already in practical use. This article emphasizes the value of indoor localization data and proposes the adoption of a new virtual field known as the 'Transactional Area Network' (TAN). By presenting a custom yet simple real-time, peer-to-peer (and therefore decentralized) software implementation that provides positioning information to users via their smart devices, this article demonstrates the potential value of TAN. Finally, it explores how TAN can increase the adoption rate of indoor positioning applications, enhance interactions between people in nearby locations and therefore amplify data generation. [ABSTRACT FROM AUTHOR]

We explore the potential outcomes for financial stability when using peer‐to‐peer lenders to finance economic activity. Combining Random Regression Forests, a machine‐learning process, with an agent‐based model, we perform simulations on artificial economies with various degrees of adoption of peer‐to‐peer lending. We find that as peer‐to‐peer lenders proliferate, there is increased financial instability, lower GDP and higher unemployment. On the other hand, peer‐to‐peer lending increases the total volume of loans given out but demonstrates a preference towards consumer loans (over corporate loans), which has a negative effect in the long run. Finally, introducing peer‐to‐peer lenders increases the access of the unbanked to services which conventional banking is not able to offer within the extant regulatory framework. Our results can help policymakers as they address the issue of regulation in the peer‐to‐peer finance industry. [ABSTRACT FROM AUTHOR]

The rapid adoption of user-friendly Peer-to-Peer networks, offering equal power distribution in decentralized systems, has led to diverse network services, from file sharing to real-time conferencing. Satisfaction among peers using these services relies on resource allocation measured by utility functions. The central role of neighbor selection in shaping P2P streaming's overlay topologies, optimizing service quality through identifying peers with strong network conditions, is highlighted. Despite its importance, the lack of a comprehensive exploration prompted our systematic review. We classify contemporary practices into structured, unstructured, and super-peer models, unveiling their strengths and limitations, and identifying challenges in neighbor selection techniques. This study informs refined methodologies for more effective P2P network design, benefiting researchers and practitioners alike. [ABSTRACT FROM AUTHOR]

This study explores the recent legislative changes allowing prosumers and consumers in Latvia to form energy communities (EnCs). In spite of legal advancements, the absence of supporting regulations and potential barriers, such as the lack of tailored support schemes and forecasting tools, pose challenges. International experiences highlight additional hurdles, including weak stakeholder dialogue and limited EnC modelling tools. To address these issues, the study proposes a prosumer and consumer EnC business model aligned with Latvia's legislation, emphasising a peer-to-peer (P2P) trading approach. The model incorporates state aid, electricity trader responsibilities, and reinvestment of EnC profits, eliminating the need for a dedicated trading platform. The study introduces a user-friendly planning tool in MS Excel, evaluating economic viability through case studies and scenarios. Findings emphasise the optimisation of EnC effectiveness by adjusting tariffs, minimising initial investment costs, securing external funding, and managing loan durations. The planning tool serves as a universal instrument, offering insights into individual EnC economic indicators based on their unique characteristics. The research provides valuable guidance to stakeholders and policymakers in Latvia's evolving energy landscape. [ABSTRACT FROM AUTHOR]

The care needs of children and adolescents with type 1 diabetes and their families are frequently approached as if they were identical to those of adults, overlooking the distinct challenges young people may face. It has been stated that children and adolescents often find conventional conversations with diabetes specialists tiresome and unpleasant. The present study focuses on familial experiences of an advanced carbohydrate counting program tailored to children and adolescents. The data encompass semi-structured interviews with families who participated in a group-based child-centered advanced carbohydrate counting program. The analysis revealed five themes: (1) peer-to-peer interaction is an essential determinant of sharing and learning; (2) illness perception significantly influences dietary intake; (3) normalization of diabetes in everyday life eases the disease burden; (4) repetition of dietary knowledge is important for retention; and (5) creating a safe and playful learning environment is crucial to engaging children and adolescents in their own treatment. The present findings suggest that it would be beneficial to explore and consider alternative teaching approaches that are adapted to a more interactive and engaging learning environment that is specifically tailored to children and adolescents. This entails moving away from traditional individual approaches. [ABSTRACT FROM AUTHOR]

As a result of the exponential increase in energy consumption, energy shortages, and augmented energy costs have become a significant problem for households. Solar cells are used in many homes and/or buildings to address these problems. However, managing renewable energy sources in homes can be difficult due to the irregular nature of renewable energy production. Internet of Things (IoT) devices can provide real-time data on energy production and consumption, offering a promising solution to this issue. The current study proposes a framework based on IoT and blockchain technology for home energy management by predicting future energy consumption patterns and optimizing energy use in real time. The blockchain module facilitates peer-to-peer energy trading between renewable energy-generating homeowners and consumers. The proposed framework was tested employing a dataset based on smart homes with solar panels and wind turbines. The results manifest a reduction in energy costs and a possible 30% increase in their traditional gain. [ABSTRACT FROM AUTHOR]

ObjectiveThis study investigated the effectiveness of a 7-weeks peer-to-peer program for young people aged 15 to 25 years with depression or anxiety symptoms in Denmark.MethodsA total of 483 participants (72% women) participated in the program and the evaluation. The participants completed questionnaires at baseline, postintervention, and at 5-month follow-up to assess changes in depression symptoms (using Beck’s Depression Inventory-II), anxiety symptoms (using Spielbergers State–Trait Anxiety Inventory for Adults) and self-efficacy in controlling or managing the illness (using the personal control subscale from the Illness Perception Questionnaire-Revised). Analyses were done using repeated measures mixed linear regression models. Moreover, a register-based matched comparison group was derived as a comparison to assess changes in being in education and employment at 8-month follow-up.ResultsWithin the intervention group, both depression and anxiety scores declined across the 5-month follow-up compared to baseline (b = −9.6, 95% CI: −11.2, −8.1 for depression symptoms). The self-efficacy score increased from baseline to post-intervention (b = 1.4, 95% CI: 1.0, 1.8) and this level was maintained at follow-up. More than half of the participants were in education at baseline while 24% received social transfer payments. Compared with matched comparison group, a lower proportion of the intervention group remaining in education (71% vs. 80%). Among participants who were employed at baseline, a higher proportion of the intervention group were enrolled in education (27% vs. 19%) and were unemployed (14% vs. 4%) compared to the matched comparison group.ConclusionThis study supports the effectiveness of a peer-to-peer intervention for depression and anxiety symptoms, and self-efficacy in symptom control. However, mixed effects on education and employment were observed, indicating a negative impact on education among those initially enrolled and a higher proportion of employed participants starting education.

The increasing penetration of distributed energy resources and the growing electrification of end-use consumption complicate energy management. Current strategies, which rely on centralized systems for peer-to-peer interactions, face issues of scalability, security, traceability, single points of failure, and privacy. Blockchain, with its decentralized nature, offers immutability, transparency, automation, and scalability as potential solutions. However, practical implementation remains challenging. This study systematically reviews 156 studies published since 2021 using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to explore these limitations. Results highlight that selecting the appropriate blockchain platform and consensus mechanism is crucial. Observations show that 42% of studies proposing new consensus methods and 46% developing new platforms or using simulations struggle with practical implementation. In contrast, leveraging existing standard blockchain platforms and consensus mechanisms enhances practicality and scalability. Additionally, seamless interoperability with Internet of Things (IoT) remains a significant challenge due to the high costs associated with the few platforms that offer this feature. Standardization of blockchain methodology, interoperability, performance measurement, and governance remains a major issue despite several parallel efforts by multiple stakeholders, including blockchain platform providers. Consolidation of these efforts into a common framework, together with the utilization of existing blockchain components, is key to resolving current limitations and fostering wider adoption. Among the various blockchain components suited for different applications, this study provides key criteria for selection, guiding the development of practical and scalable blockchain-based energy applications.

Abstract The increasing penetration of renewable energy and the further coupling of the electricity and carbon markets have hindered the realization of efficient and low‐carbon transformation processes in new power systems. This study addresses the optimization problems of joint peer‐to‐peer (P2P) electricity and carbon trading in multi‐energy microgrids (MEMGs), taking into account the risks associated with renewable generation in a distributed manner. First, a coordinated operation model is developed to describe the joint P2P electricity and carbon trading issues among MEMGs, aiming to minimize operating costs, mitigate potential risk losses, and reduce renewable energy wastage. Second, the conditional value‐at‐risk technique, paired with stochastic programming, is employed to quantify potential risk losses arising from uncertainties. Finally, a distributed optimization approach is developed based on the alternating direction method of multipliers to maintain the privacy and independence of decision‐making in individual MEMGs. During the trading processes, the Lagrangian multipliers are used as price signals to ensure fairness in optimal trading schemes among MEMGs. Moreover, a parallel solution mechanism is implemented to improve overall operational efficiency with minimal calculation expenditure. The simulation results demonstrate that the proposed method can reduce operation costs and carbon emissions while also preventing a significant amount of renewable energy abandonment.

We propose PyCAN, the first open-source Python implementation of N-dimensional Content-Addressable Network (CAN) with full feature sets to maintain peer-to-peer structure. Existing CAN implementations supports limited functions of Distributed Hash Table (DHT), so they cannot be used in practice. However, PyCAN offers full set of features such as N-dimension coordinates, node removal followed by node taking over, and a verification method to keep peer-to-peer structure. By extensive experiments, we confirm that PyCAN supports scalable overlay structures, so it is practically usable in peer-to-peer systems.

PurposePrior to 2020, University of California, Los Angeles (UCLA) Library's research services spanned multiple service points. Multiple locations were staffed by Library Student Research Assistants (LSRAs) and each location was supervised independently. While efforts to increase collaboration had been underway, much of the work and services remained siloed and often duplicated training and service hours.Design/methodology/approachWith the onset of coronavirus disease 2019 (COVID-19), UCLA Library rapidly transitioned from entirely in-person to entirely online services. With multiple service points pivoting, UCLA was redundant to have multiple online desks providing Zoom appointments and that quickly became apparent. Moreover, transitioning in-person student work to remote work was paramount to providing both normal services to users and allowing LSRAs to keep jobs during a time of uncertainty and insecurity.FindingsWhile the authors' original consolidation of services and implementation of shared supervision was a result of the pandemic and primarily involved online services, the authors have maintained this shared approach and collaborative vision in returning to in-person services. For the past year, the authors have offered shared in-person (at two library locations) and online services. As subject-specific library locations begin to reopen their desks, the authors continue to identify ways to leverage shared supervision and a robust referral model for those on-site services while negotiating student staffing and the need for both general and subject-specific services.Originality/valueThe authors present a novel approach to peer-to-peer teaching and learning and research services and shared student worker supervision with services coordinated across multiple locations and disciplines within a large academic library serving a large student population.

Summary: As a foundational technology for managing decentralized systems like smart grids and healthcare systems, blockchain is attracting a lot of interest. However, owing to excessive resource requirements and low scalability with frequent‐intensive transactions, its use in resource‐constrained mobile devices is restricted. To let mobile devices offload processing tasks to cloud resources, edge computing can be used. For scalability and secure transactions, the integration with edge computing guarantees consistent access, distributed computing, and non‐compromised storage. To accomplish effective integration, critical challenges such as reliability, adaptability, and resource planning must be resolved. Despite these efforts, further study is still needed to address issues with confidentiality, flexibility, and reliability to develop a workable, secure decentralized data storage system. This study utilizes edge computing to build an Internet of Things (IoT) architecture that satisfies the safety and scalability necessary criteria for integration along with the integration of peer‐to‐peer and blockchain technologies. Already‐existing blockchain and related technologies have also been investigated to suggest solutions that address issues like secrecy, reliability, and scalability in order to successfully incorporate blockchain in IoT systems. Our experimental findings indicate that achieving low rates of stale blocks and promoting decentralization requires a meticulous selection of block sizes and generation intervals. It is essential to maintain block creation intervals as short as practically possible, and utilizing blocks with a size below 1 MB is advisable. [ABSTRACT FROM AUTHOR]

The study gives a detailed examination of Peer-to-Peer crowdfunding and explores the possibilities of recommending it as a better financing option for start-up capital for businesses. Peer-to-Peer by its nature enables borrowers to obtain loans directly from lenders without the use of intermediaries. It therefore makes it easier for business to have access to start-up capital which is not available to them from the more traditional sources. Consequently, the study considers the relevance of this crowdfunding model by reviewing the defining literature and evaluating the dynamics of the model. In particular, the study critically considers the key concepts of the model and how it could be applied practically. The study is conducted in the form of review of literature and expression of opinion. Consequently, the experiential justification of the models presented is outside the scope of this paper. [ABSTRACT FROM AUTHOR]

The state-owned power Electricity Generating Authority of Thailand (EGAT), a monopoly market in charge of producing, distributing, and wholesaling power, is the focal point of Thailand's electricity market. Although the government has encouraged people to install on-grid solar panels to sell electricity as producers and retail consumers, the price mechanism, i.e., purchasing price and selling prices, is still unilaterally determined by the government. Therefore, we are interested in studying the case where blockchain can be used as a free trading platform. Without involving buying or selling from the government, this research presents a model of fully traded price mechanisms. Based on the study results of the double auction system, data on buying and selling prices of electrical energy in Thailand were used as the initial data for the electricity peer-to-peer free-trading model. Then, information was obtained to analyze the trading price trends by using the law of demand and supply in addition to the principle of the bipartite graph. The price trend results agree well with those of price equilibrium equations. Therefore, we firmly believe that the model we offer can be traded in a closed system of free-trade platforms. In addition, the players in the system can help to determine the price trend that will occur according to various parameters and will cause true fairness in the sustainable electricity supply chain industry in Thailand. [ABSTRACT FROM AUTHOR]

Peer-led approaches emphasize learner autonomy by affirming that the process of knowledge and skills acquisition does not correspond to a passive intake of information, but that understanding must be actively constructed in collaboration. Accordingly, learning is configured as a situated, active, and creative process. The introduction of peer-learning in the Italian education system is progressing very slowly, despite a continuing academic interest in the potential of the didactic method as an innovative asset in a structured school organization with prevailing standardized procedures. Drawing on these premises, this contribution aims to present the experience related to the application of particular forms of peer-led approaches. Specifically, the authors have been analysing peer-to-peer and peer-for-peer practices carried out as part of a pilot phase within the EU-funded Horizon project entitled ‘KIDS4ALLL’. The analysis of this study is grounded on qualitative data from students, teachers and educators who have been testing the proposed peer-led learning method in non-formal educational contexts in Turin and Padua. Major findings suggest that learning with new methodologies which put the learner at the centre of the process, may potentially respond to contemporary challenges of non-formal educational settings, if continuously adopted and accompanied by trained educational staff. Instead, intermittent and random interventions for the sake of forced didactic innovation in the classroom might entail unexpected effects on the development of competences for students and educational staff. [ABSTRACT FROM AUTHOR]

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Peer-to-peer (P2P) rental markets have been shown to adversely impact the traditional hospitality industry and housing affordability, fueling the public demand for regulation. While localities around the globe have implemented policies to address these issues, little is known about how rental suppliers respond to those regulations. This study aims to empirically analyze the impact of such policy regulations on the prices charged by different types of rental suppliers. We employed a quasi-experimental research design based on an extensive dataset including more than 50,000 Airbnb listings to uncover the impact of a policy implemented in New Orleans, which introduced annual bring-to-market (BTM) costs through a mandatory licensing system while simultaneously banning listings from one city-center neighborhood. We find that, while non-commercial hosts completely pass their additional costs onto their consumers, irrespectively of demand and supply shifts, commercial hosts' responses are more nuanced. Those with legalized listings located in the city center only partially pass on their costs to guests, while even decreasing their prices in the rest of the city. Our study contributes to the understanding of pricing in P2P rental markets and its effects. Further, it informs localities and supports policy analytics. With P2P renting remaining attractive in city parts where BTM costs can easily be passed through to consumers, this suggests that these regulatory policies fall short of reducing pressure on housing affordability in the city-center. [ABSTRACT FROM AUTHOR]

The exchange of model parameters between peers is critical in peer-to-peer deep learning. Historically, connections between agents were assigned randomly based on network topology. However, recent methodologies enable agents to autonomously establish their connections, which is especially beneficial for non-IID data settings. Recent studies suggest favorable learning outcomes for autonomous connections compared to fixed topology when evaluated in synthetic non-IID environments. To that end, this study will explore various methodologies to enhance learning outcomes. Through several large-scale experiments with synthetic and realistic non-IID data sets, it evaluates communication efficiency, message exchange frequency, and centralization tendencies. The findings underscore the potential of these methods to enhance local model accuracy, uphold communication efficiency, and resist centralization, rendering them highly suitable for decentralized learning systems. The evaluation results establish PANMGrad and PANMLoss as the most effective solutions in such environments.

Due to data privacy constraints, data sharing among multiple clinical centers is restricted, which impedes the development of high performance deep learning models from multicenter collaboration. Naive weight transfer methods share intermediate model weights without raw data and hence can bypass data privacy restrictions. However, performance drops are typically observed when the model is transferred from one center to the next because of the forgetting problem. Incremental transfer learning, which combines peer-to-peer federated learning and domain incremental learning, can overcome the data privacy issue and meanwhile preserve model performance by using continual learning techniques. In this work, a conventional domain/task incremental learning framework is adapted for incremental transfer learning. A survey on the efficacy of prevalent regularization-based continual learning methods for multicenter collaboration is performed. The influences of data heterogeneity, classifier head setting, network optimizer, model initialization, center order, and weight transfer type have been investigated thoroughly. Our framework is publicly accessible to the research community for further development.

Increasing the deployment of Renewable Energy Resources (RES), along with innovations in Information and Communication Technologies (ICT), would allow prosumers to engage in the energy market and trade their excess energy with each other and with the main grid. To ensure an efficient and safe operation of energy trading, the Peer-to-Peer (P2P) energy trading approach has emerged as a viable paradigm to provide the necessary flexibility and coordinate the energy sharing between a pair of prosumers. The P2P approach is based on the concept of decentralized energy trading between prosumers (i.e., production capabilities or energy consumers). However, security protection and real-time transaction issues in the P2P market present serious challenges. In this paper, we propose a decentralized P2P energy trading approach for the energy market with high penetration of RE. First, the P2P energy market platform proposed coordinating the energy trading between energy providers and consumers to maximize their social welfare. A distributed algorithm is applied to solve the market-clearing problem based on the Alternating Direction Method of Multipliers (ADMM). In this way, the computational complexity can be reduced. Furthermore, a P2P Manager (P2PM) utility is introduced as an entity to solve the synchronization problem between peers during the market clearing. Finally, through a real-time application using Hardware-In-the-Loop (HIL), the effectiveness of the proposed P2PM is verified in terms of synchronizing the market participants and improving the power transaction.

Nowadays, advanced metering and communication infrastructures make it possible to enable decentralized control and market schemes. In this context, prosumers can interact with their neighbors in an active manner, thus sharing resources. This practice, known as peer-to-peer (P2P), can be put into practice under cooperative or competitive premises. This paper focuses on the second case, where the peers partaking in the P2P platform compete among themselves to improve their monetary balances. In such contexts, the domestic assets, such as on-site generators and storage systems, should be optimally scheduled to maximize participation in the P2P platform and thus enable the possibility of obtaining monetary incomes or exploiting surplus renewable energy from adjacent prosumers. This paper addresses this issue by developing a home energy management model for optimal participation of prosumers in competitive P2P platforms. The new proposal is cast in a three-stage procedure, in which the first and last stages are focused on domestic asset scheduling, while the second step decides the optimal offering/bidding strategy for the concerned prosumer. Moreover, uncertainties are introduced using interval notation and equivalent scenarios, resulting in an amicable computational framework that can be efficiently solved by average machines and off-the-shelf solvers. The new methodology is tested on a benchmark four-prosumer community. Results prove that the proposed procedure effectively maximizes the participation of prosumers in the P2P platform, thus increasing their monetary benefits. The role of storage systems is also discussed, in particular their capability of increasing exportable energy. Finally, the influence of uncertainties on the final results is illustrated.

The energy transition toward Net Zero Emission by 2060 hinges on the renewable energy power plants in Indonesia. Good practices in several countries suggest a peer-to-peer (P2P) energy trading system using blockchain technology, supported by renewable energy (solar panels), an innovation to provide equal access to sustainable electricity while reducing the impact of climate change. The P2P energy trading concept has a higher social potential than the conventional electricity buying and selling approach, such as that of PLN (the state-owned electricity company in Indonesia), which applies the network management concept but does not have a sharing element. This model implements a solar-powered mini-grid system and produces a smart contract that facilitates electricity network users to buy, sell, and trade electricity in rural areas via smartphones. This study aims to measure the stakeholders’ perceptions of the peer-to-peer (P2P) energy trading model using blockchain technology in the Gumelar District, Banyumas Regency, Central Java Province, Indonesia. The stakeholders in question are representatives of Households (producers and consumers), Government, State Electricity Company (PLN), Non-Governmental Organizations, Private Sector and Academician. Measurement of perception in this study used a questionnaire approach with a Likert scale. The results of filling out the questionnaire were analyzed using four methods: IFE/EFE matrix; IE matrix; SWOT matrix; and SPACE matrix to assess the results and their suitability to each other. The results of the stakeholder perception assessment show that there are 44 internal factors and 33 external factors that can influence this model. We obtained an IFE and EFE score of 2.92 and 2.83 for the internal and external results using the IE matrix. These place the model in quadrant V, meaning the P2P model can survive in the long term to generate profits. Based on the SWOT analysis results, this model is located at the coordinate point −0.40, 0.31, placing it in quadrant II. This means that the P2P model is in a competitive situation and faces threats but still has internal strengths. Based on the SPACE matrix, stakeholder perception states that the P2P model is at coordinate point 1, −0.3. This shows that the P2P model has the potential to be a competitive advantage in its type of activity that continues to grow. In conclusion, our findings show that stakeholders’ perceptions of P2P models using blockchain technology can be implemented effectively and provide social, economic, and environmental incentives.

Borrowing decisions typically involve processing large amounts of financial information. However, it has been understudied whether cognitive capacity factors such as air pollution affect borrowing behaviours. In this paper, we estimate the causal impact of air pollution on borrowing behaviours by using the universe of borrowing application data on an online peer-to-peer platform and a thermal inversion instrument. We find that a 1% increase in air pollution reduces the number of borrowing applications and the total amount requested by 0.05% and 0.31% respectively. The impact is stronger when the borrowing is for more complex and less necessary purposes, and when we examine the areas with lower educational attainment. The results suggest that the adverse effect of air pollution on cognitive capacity prevents people from borrowing. [ABSTRACT FROM AUTHOR]

As the demand for renewable energy grows, there is a need for efficient and transparent mechanisms to facilitate renewable energy trading. This research presents a novel Renewable Energy Trading Platform (RETP) that leverages blockchain technology to enable secure and decentralized energy trading. The platform utilizes distributed ledger technology to record and verify energy transactions, ensuring transparency and immutability. Smart contracts are employed to automate trade execution and settlement, eliminating the need for intermediaries and reducing transaction costs. The RETP integrates renewable energy data from various sources, such as smart meters and IoT devices, to enable accurate tracking and verification of energy production and consumption. Through the implementation of the RETP, energy producers can directly sell excess renewable energy to consumers, promoting the adoption of green energy and enhancing energy grid efficiency. A comprehensive evaluation of the platform demonstrates its efficiency, scalability, and security. The proposed RETP has the potential to revolutionize the renewable energy market by fostering peer-to-peer energy trading, empowering energy communities, and accelerating the transition to a sustainable energy future. [ABSTRACT FROM AUTHOR]

Personalization of customer offers has been a topic of discussion in travel for well over two decades. Over the past few years, there has been renewed focus on personalization with IATA's New Distribution Capability (NDC) initiative. The context for travel plays a key role in personalizing offers for a collection of travelers with similar traits associated with their travel patterns. When the customer identity is known, offers can be personized for a segment of ONE across all channels with the NDC messaging standard. Personal identity, which plays a key role in 1:1 personalized offer creation, has been rapidly evolving and will have significant impact on travel intermediaries like Global Distribution Systems (GDS), Travel Management Companies (TMC), and Online Travel Agencies (OTA), and the relationship between a traveler and a supplier. Personalization of travel offers in the future will be very different from what it is today due to advances in blockchain technology and the evolving business landscape. [ABSTRACT FROM AUTHOR]