Hasil untuk "Information theory"

Gabriel Potestades

Understanding natural phenomenon through the interactions of different complex systems has become an increasing focus in scientific inquiry. Defining complexity and actually measuring it is an ongoing debate and no standard framework has been established that is both theoretically sound and computationally practical to use. Currently, one of the fields which attempts to formally define complexity is in the realm of Algorithmic Information Theory. The field has shown advances by studying the complexity values of binary strings and 2-dimensional binary matrices using 1-dimensional and 2-dimensional Turing machines, respectively. Using these complexity values, an algorithm called the Block Decomposition Method developed by Zenil, et al. in 2018, has been created to approximate the complexity of adjacency matrices of graphs which have found relative success in grouping graphs based on their complexity values. We use this method along with another method called edge perturbation to exhaustively determine if an edge can be identified to connect two subgraphs within a graph using the entire symmetric group of its vertices permutation and via unique permutations we call automorphic subsets, which are a special subset of the symmetric group. We also analyze if edges will be grouped closer to their respective subgraphs in terms of the average algorithmic information contribution. This analysis ascertains if Algorithmic Information Theory can serve as a viable theory for understanding graph substructures and as a foundation for frameworks measuring and analyzing complexity. The study found that the connecting edge was successfully identified as having the highest average information contribution in 29 out of 30 graphs, and in 16 of these, the distance to the next edge was greater than log_2(2). Furthermore, the symmetric group outperformed automorphic subsets in edge grouping.

B. Kosko

Ashley C. T. Jones, Morgan R. Haga

Sloman and Rabb found support for the existence of the community of knowledge (CK) effect, which occurs when individuals are more likely to report understanding and being able to explain even fake scientific information when told that an expert understands the information. To date, no studies have been conducted that attempted to replicate original findings, let alone test the presence of the CK effect in realistic, legal scenarios. Therefore, Study One replicated original CK effect studies in a jury-eligible M-Turk sample (<i>N</i> = 291) using both Sloman and Rabb’s experimental stimuli as well as new stimuli. Study Two then tested the presence of the CK effect using scientific testimony in a mock court hearing from a forensic evaluator (<i>N</i> = 396). Not only did the CK effect improve laypeople’s perceptions of the scientific information in court, but it also improved their perceptions of the expert witness’s credibility, increased the weight assigned to the scientific information, and increased the weight assigned to the expert testimony. This effect was mediated by participants’ perceived similarity to the expert, supporting the theory behind the CK effect. These studies have important implications for the use of scientific information in court, which are discussed.

WEI Wei, WANG Yudong, JIN Xiaolong

[Objective] The large-scale integration of distributed renewable energy generation （REG） has significantly enhanced the flexible regulation capabilities of distribution systems. However， the inherent randomness and volatility of REG output characteristics present serious challenges to the security and stability of distribution system operations. [Methods] To effectively improve the adaptability of day-ahead dispatch plans to uncertainties， this study proposes a distributionally robust day-ahead dispatch optimization method for active distribution networks （ADN） based on an improved conditional generative adversarial network （CGAN）. First， an improved CGAN model designed by three-dimensional convolution （Conv3D） is proposed to address the problem of generating day-ahead scenarios for wind turbines （WT） and photovoltaic （PV） outputs considering spatio-temporal correlation， which effectively reduces the conservatism of the generated scenario set. Second， based on the generated day-ahead scenario samples of the WT and PV outputs， a Wasserstein ambiguity set construction method based on kernel density estimation （KDE） is proposed， which realizes full utilization of the sample distribution information. On this basis， a two-stage distributionally robust day-ahead dispatch optimization （DRO） model for ADN is established， considering multiple grid-side resource coordination. The original model is reconstructed into a mixed-integer linear programming problem to obtain a solution based on the affine strategy and strong duality theory. [Results] The findings demonstrate that although the day-ahead dispatch plan cost of the proposed method increases by 1.87% and 0.21% compared with the deterministic optimization （DO） and stochastic optimization （SO） methods， the integrated operation cost decreases by 5.38% and 0.46% under the worst-case scenario， respectively. [Conclusions] The analysis revealed that the proposed DRO model exhibits better adaptability to REG uncertainty and can effectively decrease the operational adjustment cost of the day-ahead dispatch plan while maintaining robustness， especially under the worst-case scenario.

Hamid Amoonia, Mohammadreza Yousefi Roshan, Amir Hasan Jangi

Understanding vegetation spatial patterns is vital for assessing ecosystem health, especially in water-stressed arid and semi-arid regions. These areas, often characterized by sparse and sensitive vegetation, face significant challenges from climate change and human pressures. Rashtkhar County in Iran exemplifies such an environment, experiencing a severe decline in groundwater levels, which necessitates precise monitoring of its vegetation dynamics. Quantifying the spatial dispersion or heterogeneity of vegetation cover objectively is challenging. While indices like NDVI provide information on vegetation density, they often miss crucial details about spatial structure and fragmentation. Shannon's entropy model, derived from information theory, offers a robust method to measure the complexity or dispersion within a spatial system. Specifically, Shannon's relative entropy (G), a normalized index, allows for standardized comparisons of dispersion across time and space, effectively differentiating between uniform and highly fragmented landscapes. Given the ecological importance of vegetation in Rashtkhar and the intense pressure on its water resources, this study's primary objective was to utilize Shannon's relative entropy model to quantitatively assess the trend of spatial vegetation cover dispersion from 1990 to 2023. A key goal was to analyze the relationship between this dispersion trend, groundwater level fluctuations (approx. 1986-2022), and the region's topography. The findings aim to provide insights for sustainable resource management in similar vulnerable areas, highlighting the need for quantitative tools to understand complex ecosystem dynamics.This research employed a descriptive-analytical approach using remote sensing and GIS to investigate quantitative trends in vegetation spatial dispersion in Rashtkhar County, a predominantly arid area in Khorasan Razavi Province, Iran (~4,360 km²). The study period covered 1990-2023 for vegetation and water years 1365-66 to 1400-1401 (approx. 1986-2022) for groundwater. Time-series Landsat imagery (TM and OLI sensors, 30m resolution) for 1990, 2000, 2010, 2015, 2020, and 2023 were acquired from USGS. After standard radiometric and atmospheric corrections, NDVI was calculated using ENVI 5.6 to map vegetation cover for each year. Groundwater level data were sourced from the provincial Regional Water Authority. To incorporate topography, the area was classified into five elevation zones using a DEM (Figure 3). Shannon's relative entropy model was then applied to quantify spatial dispersion annually. Relative entropy (G) was calculated as G = H / ln(n), where H = - Σ [pi * ln(pi)], 'pi' is the proportion of vegetation cover in topographic zone 'i', and 'n' is the number of zones (n=5). G ranges from 0 (maximum concentration) to 1 (maximum dispersion). Calculations were performed using Excel and ArcGIS. Finally, the temporal trend of G was compared with groundwater level trends to analyze the interplay between vegetation spatial structure and water resource availability.The analysis revealed significant and contrasting trends in groundwater levels and vegetation dispersion in Rashtkhar County. Groundwater elevation showed a severe and nearly continuous decline over the ~35-year period, dropping approximately 50 meters from above 1110m to just over 1060m. This drastic reduction highlights critical pressure on groundwater resources and aquifer depletion. Conversely, Shannon's relative entropy (G) for vegetation cover, measuring spatial dispersion, followed a different trajectory. G increased sharply from 0.801 in 1990 to 0.913 in 2000. Despite minor fluctuations, it maintained a high level with a slight upward trend, reaching 0.924 in 2023. This indicates a sustained shift towards greater heterogeneity and spatial dispersion of vegetation cover. While the total vegetation area mapped via NDVI showed an overall increase (from ~8,000 ha to nearly 30,000 ha), its spatial distribution changed, with increased contributions from low and high elevation zones at the expense of mid-elevation areas. The key finding is the stark contrast: severe groundwater depletion occurred concurrently with increased (or stabilization at high levels of) vegetation spatial dispersion. This seemingly paradoxical outcome likely does not signify ecological improvement. Instead, it strongly suggests a complex structural rearrangement of the landscape driven by adaptation to water stress. The increased dispersion might result from factors like shifts towards more drought-resistant but potentially scattered crops (e.g., saffron), fragmentation of agricultural lands due to changing economic viability or land tenure, uneven development, or the patchy survival of native vegetation in micro-refugia. The analysis also confirmed that topography significantly influences how this dispersion manifests, modulating the vegetation system's response to environmental pressures like water scarcity.This study quantitatively assessed vegetation spatial dispersion in Rashtkhar County using Shannon's relative entropy, relating it to groundwater trends and topography. A major finding was the contrasting long-term trends: a severe, continuous ~50-meter decline in groundwater levels (approx. 1986-2022) alongside a significant increase and stabilization of vegetation spatial dispersion (G rising from 0.801 in 1990 to 0.924 in 2023). This increased heterogeneity, occurring amidst resource depletion, is interpreted not as ecological recovery but as evidence of landscape structural rearrangement. This rearrangement likely reflects adaptive responses to water stress, such as changes in land use, cropping patterns towards more scattered cultivation, land fragmentation, or patchy vegetation survival. Topography was confirmed as a key factor modulating these spatial patterns. The research demonstrates the utility of Shannon's relative entropy as a valuable quantitative tool for capturing complex spatial dynamics and their interactions with environmental drivers like water availability in arid/semi-arid regions. It highlights that relying solely on overall vegetation indices can be misleading, and understanding spatial structure is crucial for assessing ecosystem sustainability. These findings underscore the need to incorporate such spatial metrics into sustainable resource management frameworks, particularly for developing integrated water conservation and land use planning strategies in fragile ecosystems under pressure. Future work could enhance this understanding by incorporating detailed land use data, grazing information, and higher-resolution remote sensing inputs.

Naqueeb Ahmad Warsi, Ayanava Dasgupta, Masahito Hayashi

We study quantum differential privacy (QDP) by defining a notion of the order of informativeness between pairs of quantum states. In particular, we show that if the hypothesis testing divergence of one pair dominates over that of the other pair, then this dominance holds for every $f$-divergence. This approach completely characterizes $(\varepsilon,δ)$-QDP mechanisms by identifying the most informative $(\varepsilon,δ)$-DP quantum state pairs. We apply this to study precise limits for privatized hypothesis testing and privatized quantum parameter estimation, including tight upper-bounds on the quantum Fisher information under QDP. Finally, we establish near-optimal contraction bounds for differentially private quantum channels with respect to the hockey-stick divergence.

Pasty Asamoah, Daniel Zokpe, Richard Boateng et al.

The increasing reliance on Generative Artificial Intelligence (GenAI) among students and knowledge workers poses significant risks and raises integrity concerns, prompting some institutions to impose bans on its use. With scant research on a guided framework, strategies, and checklists for the utilization of GenAI, we propose a framework based on the expertise acquisition model, information retrieval theory, and deontological ethics theory, emphasizing the need for domain knowledge, query capabilities, and ethical acumen (DEQ). Using a ‘thing’ ethnography methodology with ChatGPT, we validated our framework, highlighting the importance of these competencies to mitigate risks, including the generation of factually incorrect and plagiarized content. Our findings suggest that while GenAI can drive innovation, its content should be used as a guiding tool to enhance critical thinking and reasoning, ultimately helping knowledge workers and students avoid plagiarism and maintain academic integrity. We discuss this novel framework and provide avenues for extending this study.

Ingo Althöfer, Holger Boche, Christian Deppe et al.

It is with heavy hearts that we mourn the passing of Ning Cai, a luminary whose pioneering spirit illuminated the realms of network coding and beyond. On May 25, 2023, at the age of 75, Prof. Cai bid farewell, leaving behind a profound legacy that continues to resonate across generations of researchers. His contributions spanned a vast spectrum, from the groundbreaking explorations in network coding to the intricate realms of quantum information theory. Ning's indelible mark on the academic landscape is a testament to his unwavering dedication and relentless pursuit of knowledge. Among his many accolades, Ning's seminal works garnered widespread recognition, exemplified by the prestigious 2005 IEEE Information Theory Society Paper Award for his work "Linear Network Coding." Furthermore, his enduring impact was underscored by the 2018 ACM SIGMOBILE Test-of-Time Paper Award, bestowed upon his paper "Network Information Flow." In addition to his scholarly achievements, Ning's unwavering commitment to mentorship has left an indelible mark on countless aspiring scholars. His guidance and wisdom continue to inspire and guide future generations in their scholarly pursuits. As we bid farewell to a titan in the field, let us cherish the legacy of Ning Cai, whose brilliance and generosity of spirit will forever endure in the annals of academia.

Hsiao-Ching Huang, I-Hsien Liu, Meng-Huan Lee et al.

The Internet of Things (IoT) has revolutionized technologies in society, including in households, offices, factories, and health centers. Among these, the Healthcare Internet of Things (HIoT) significantly transforms medical assistance for patients. By using wearable devices with remote network connections, caregivers monitor patients’ physiological data to gain valuable insights into their health conditions. Despite the many benefits of the HIoT, several security vulnerabilities still exist. Hackers can exploit the internet connection to steal or modify credential information regarding patients, violating the integrity and confidentiality of the security policy. Moreover, they can launch cyberattacks on hospitals or critical life-support systems, further endangering patients’ lives. Consequently, it is crucial to implement robust cybersecurity measures to enhance the security of healthcare services. Therefore, we proposed an anomaly detection method based on network traffic for the HIoT, adopting Markov models. Owing to their simplicity, interpretability, and well-developed theory, the Markov models have been applied to network traffic prediction and modeling, serving as a viable approach to cater to our needs. We evaluated the proposed method using the public dataset ToN_IoT and analyzed the results.

Ellins Jo, Hocking Lucy, Al-Haboubi Mustafa et al.

Background The Children and Young People’s Mental Health Trailblazer programme is funding the creation of new mental health support teams to work in schools and further education colleges. Mental health support teams directly support children and young people with ‘mild to moderate’ mental health problems and work with school and college staff to promote well-being for all. A new workforce of education mental health practitioners is being trained for the teams. Objective(s) The National Institute for Health and Care Research Birmingham, RAND and Cambridge Evaluation Rapid Evaluation Centre and Policy Innovation and Evaluation Research Unit undertook an early evaluation of the Trailblazer programme to examine the development, implementation and early progress of mental health support teams in the programme’s first 25 ‘Trailblazer’ sites. Design A mixed-methods evaluation, comprising three work packages: 1.Establishing the baseline and understanding the development and early impacts of the Trailblazer sites, including two rounds of surveys with key informants and participating education settings in all 25 sites. 2.More detailed research in five purposively selected Trailblazer sites, including interviews with a range of stakeholders and focus groups with children and young people. 3.Scoping and developing options for a longer-term assessment of the programme’s outcomes and impacts. Fieldwork was undertaken between November 2020 and February 2022. The University of Birmingham Institute for Mental Health Youth Advisory Group was involved throughout the study, including co-producing the focus groups with children and young people. Results Substantial progress had been made implementing the programme, in challenging circumstances, and there was optimism about what it had the potential to achieve. The education mental health practitioner role had proven popular, but sites reported challenges in retaining education mental health practitioners, and turnover left mental health support teams short-staffed and needing to re-recruit. Education settings welcomed additional mental health support and reported positive early outcomes, including staff feeling more confident and having faster access to advice about mental health issues. At the same time, there were concerns about children who had mental health problems that were more serious than ‘mild to moderate’ but not serious enough to be accepted for specialist help, and that the interventions offered were not working well for some young people. Mental health support teams were generally spending more time supporting children with mental health problems than working with education settings to develop ‘whole school’ approaches to mental health and well-being, and service models in some sites appeared to be more clinically oriented, with a strong focus on mental health support teams’ therapeutic functions. Limitations Despite efforts to maximise participation, survey response rates were relatively low and some groups were less well represented than others. We were not able to gather sufficiently detailed data to develop a typology of Trailblazer sites, as was planned. Conclusions Key lessons for future programme implementation include: –Whether mental health support teams should expand support to children and young people with more complex and serious mental health problems. –How to keep the twin aims of prevention and early intervention in balance. –How to retain education mental health practitioners once trained. Future work The findings have important implications for the design of a longer-term impact evaluation of the programme, which is due to commence in summer 2023. Study registration Ethical approval from the University of Birmingham (ERN_19-1400 – RG_19-190) and London School of Hygiene and Tropical Medicine (Ref: 18040) and Health Research Authority approval (IRAS 270760). Funding The Birmingham, RAND and Cambridge Evaluation Rapid Evaluation Centre is funded by the National Institute for Health and Care Research Health Services and Delivery Research programme (HSDR 16/138/31). The Policy Innovation and Evaluation Research Unit is funded by the NIHR Policy Research Programme (PR-PRU-1217-20602). A note on terminology This report uses the term ‘children and young people’s mental health services’ to describe all services that support children and young people who have difficulties with their mental health and emotional well-being. These services encompass prevention and universal provision, through to specialist and crisis support, including inpatient care. They are provided by NHS, local authority, voluntary, community and independent sector services, as well as schools and colleges. Some participants in the study refer to ‘child and adolescent mental health services’ (or CAMHS), which is an older term for specialist NHS mental health services for young people aged 0–18 (or, in some areas, 0–25) years. We also use the term ‘whole school approach’ to describe all the ways in which schools and colleges can address the emotional health of children and/or young people in their setting, which includes supporting those who are experiencing mental health problems to access appropriate help. In wider literature and debate, these activities are also referred to as holistic, universal, graduated or school-wide approaches to mental health and well-being. The national programme launched by the Department of Health and Department for Education to implement the proposals in the 2017 Green Paper Transforming Children and Young People’s Mental Health Provision was originally termed the Trailblazer programme. It was subsequently renamed the Children and Young People’s Mental Health Implementation programme, and only the first wave of sites was referred to as Trailblazers. As the study reported herein focuses exclusively on this first wave of Trailblazer sites, we have opted to use the programme’s original name. Plain language summary The Children and Young People’s Mental Health Trailblazer programme started in 2018 and is funding the creation of new mental health support teams to work in schools and further education colleges. Mental health support teams directly support children and young people with ‘mild to moderate’ mental health problems and help schools and colleges to promote well-being for all. The programme is also creating and training a new workforce of education mental health practitioners. Our study looked at the experiences of setting up and running mental health support teams in the first 25 areas involved in the programme (called Trailblazers). We wanted to understand what the teams were doing day-to-day, who was working in them, what was going well, whether there were any challenges, and what progress they were making. To do this, we looked at documents and information provided by the national programme team and collected our own data using surveys, interviews and focus groups. We found that the programme was making good progress, and that schools and colleges welcomed having additional mental health support. Children and young people told us how important it was to have somebody in their school or college who they could speak to about their mental health. Mental health support teams were generally spending more time supporting young people who had mental health difficulties than working with education settings to promote emotional well-being across the whole school or college community. There were also challenges. Some children had mental health problems that were more serious than ‘mild to moderate’ but not serious enough to be accepted for specialist support. The type of support that mental health support teams were providing was not suitable for all children and young people. Once education mental health practitioners had been trained, some moved on from their role quite quickly, leaving teams short-staffed. The findings have important implications for the design of a longer-term study to assess the impact of the programme, due to commence in summer 2023. Scientific summary Background The Children and Young People’s Mental Health Trailblazer programme was launched in 2018 to take forward the proposals set out in the Transforming Children and Young People’s Mental Health Provision Green Paper. The programme is being implemented in successive waves, with the first wave funding the creation of 58 mental health support teams (MHSTs) in 25 ‘Trailblazer’ sites. Across these sites, 1050 schools and further education colleges were recruited to participate in the programme, each of which received support from an MHST and was encouraged to appoint a senior lead for mental health for their setting (if they did not already have one in place). MHSTs have three core functions: (1) providing direct support to children and young people with mild to moderate mental health issues; (2) supporting education settings to introduce or develop their whole school/college approach to mental health and well-being; and (3) giving advice to staff in education settings and liaising with external specialist services to help children and young people to get the right support and stay in education. A new professional role has been created for the programme: education mental health practitioner (EMHP). The programme is being implemented in the context of a children’s mental health service under strain. Considerable and increasing levels of mental ill health in children and young people, historic underinvestment in children’s mental health services and the COVID-19 pandemic have contributed to services struggling to cope with increasing demand. Objectives The National Institute for Health and Care Research (NIHR) Birmingham, RAND and Cambridge Evaluation Rapid Evaluation Centre and Policy Innovation and Evaluation Research Unit undertook an early, process-oriented evaluation of the Trailblazer programme to examine the development, implementation and early progress of the MHSTs in the Trailblazer sites. The aims of the evaluation were to: 1.Understand the baseline position and contextual features of the Trailblazer sites, including the accessibility, quality and effectiveness of existing mental health services and support in education settings and perceived gaps in provision prior to the programme commencing. 2.Describe and understand the emerging delivery models, their leadership and governance, and explore how these vary across the Trailblazer sites and the potential implications of this variation for future effectiveness of the programme. 3.Describe the experience of MHSTs, education settings, clinical commissioning groups and local authority commissioners, children and young people’s mental health services and others of taking part in the delivery of the programme. 4.Capture views about the progress being made by Trailblazers towards the goals of the programme, early impacts and any unanticipated consequences in the initial phases of the programme. 5.Identify measures and data sources of relevance to assessing programme outcomes and costs as well as appropriate comparator areas and education settings to assess the feasibility and develop the design of a long-term outcome and economic evaluation. 6.Conduct formative and learning-oriented research, producing timely findings and highlighting their practical implications to inform ongoing implementation and support roll-out to sites in later waves of the programme. 7.Understand how MHSTs adapted their services and ways of working in response to the COVID-19 pandemic, and explore experiences of and learning from these changes, as well as their legacy. Methods We completed a mixed-methods evaluation combining quantitative and qualitative data collection across all 25 sites with in-depth qualitative insights from five purposively selected Trailblazers. The study comprised three work packages: •Work package 1: establishing the baseline and understanding the development and early impact of the Trailblazers. Participating education settings and key individuals who had a central role in the design and implementation of the MHSTs in their area were surveyed twice: December 2020 to May 2021 and October–November 2021. We received responses from 299 (30%, first survey) and 159 (17%, second survey) education settings; and from 76 (30%, first survey) and 65 (27%, second survey) key informants. We also interviewed the programme’s national leads (n  establishing the baseline and understanding the development and en  establishing the bn  establishing the baseline and understanding the development and early impact of the Trailblazers. d documentation, and the development of demographic and mental health service profiles for the 25 sites, using publicly available data. •Work package 2: more detailed research with a range of stakeholders in five purposively selected Trailblazer sites, including focus groups with children and young people. A total of 71 interviews were completed with local stakeholders including MHST lead organisations and staff, school and college staff, individuals in Trailblazer governance and management roles, and wider partners including specialist NHS mental health services, voluntary organisations and local authorities. Five online focus groups were held with a total of 32 children and young people who attended schools where MHSTs were operating. •Work package 3: scoping and developing options for a longer-term assessment of the programme’s outcomes and impacts. This work was highly responsive and included reviewing the design and methods of recent evaluations of initiatives and pilots similar to the Trailblazers; ongoing advice and discussions with, and commentary on preparatory work undertaken by, the national programme team; a draft theory of change; and a full proposal for an initial impact evaluation. The Institute for Mental Health Youth Advisory Group at the University of Birmingham acted as an expert reference group for this research, and were involved throughout: from design through to preparation of this report. A key part of their role was co-producing the focus group research with children and young people, including co-designing the recruitment materials and topic guides, co-facilitating the focus groups and contributing to the analysis and presentation of the findings (see Chapter 9). Results Implementation and governance The Trailblazers had achieved a great deal in a relatively short space of time. While the local set-up process had been extensive, complex and rushed, some 12 months after the first cohort of EMHPs started their training all 58 MHSTs were operational in some form. The involvement of young people, parents and carers in the design and delivery of MHSTs was variable and often low, despite it being an aspiration that they be involved throughout the programme. There was a view that local governance and leadership was not yet truly shared across health, education and other key stakeholder groups and that the way in which the programme had been set up was dominated by the NHS as funder and by local mental health services. The pandemic created significant challenges for implementation, including delays to whole school activities; however, MHSTs adapted their offer and ways of working to ensure the continuation of support for young people and to education settings. These adaptations included the use of remote support. Stakeholders suggested that a hybrid model of in-person and remote delivery will be used going forward. The pandemic also had a considerable impact on the mental health and well-being of children and young people, and staff in education settings, as well as on access to specialist services. Children and young people described how home schooling had left them feeling disconnected, demotivated and sometimes without adequate support, as well as the difficulties transitioning back into school or college. Service models, delivery and gaps in support MHSTs were delivering a range of activities within the three core functions, with teams spending proportionally more time providing direct support than on their other two functions. Some teams were clinically oriented, while others took a more holistic/education-focused approach. The approach taken appeared to be most strongly influenced by the type of organisation(s) leading the programme (e.g. NHS vs. voluntary sector), and existing local infrastructure, relationships and skill sets. Teams also varied in the number of education settings they were working with, their staffing composition, and how whole school activities were being delivered (with this being led, in some areas, by specialist local partners or specialist roles within MHSTs). MHSTs had implemented strategies to reach and engage diverse groups and different mental health needs. However, stakeholders noted that some groups were underserved by MHSTs including children and young people with special educational needs or neurodiversity, those from ethnic minority backgrounds and some religious backgrounds, and children with challenging family or social circumstances (e.g. financial hardship, domestic abuse, or living in care). These issues concerning MHSTs’ reach and effectiveness were attributed to several factors, including gaps in the initial training programme and the limitations of the type of interventions that EMHPs had been trained to deliver (mainly time-limited, low-intensity cognitive behaviour therapy), which were felt to be poorly suited to some groups of children and young people and some mental health problems. Education settings were generally satisfied with the MHST service, and MHST staff spoke positively about working with education settings. However, a mismatch between education settings’ expectations or perceived support needs and what MHSTs could offer was sometimes reported, which hampered relationship building. Defining what was within the scope of ‘mild to moderate’ mental health was challenging, and practising within this scope was harder still. Some sites held a firm boundary around ‘mild to moderate’ mental health, whereas others provided support to children and young people with more serious and complex needs. There was a lack of clarity from programme regional and national leads about whether MHSTs should remain within their intended scope or offer flexibility to support children beyond this. Although MHSTs could refer young people with more complex needs to specialist services, there were long waiting times and restricted capacity in existing mental health services. Concern was expressed about children and young people falling through the gap between MHSTs’ ‘mild to moderate’ remit and the criteria for specialist support. Workforce and retention The EMHP role and training programme had been popular, but retaining EMHPs once in post was one of the biggest challenges reported by Trailblazers. Interviewees identified various reasons for poor retention including the role being seen as a stepping stone to other careers, lack of opportunities for career development and progression, frustration at the parameters of the role or limitations of the CBT approach and high workloads. Challenges recruiting senior team members were also common. There had been initial concerns about senior staff being recruited from other local mental health services, given the potential for this to create staffing shortages elsewhere in the local system, but many had come to the view that the movement of staff between services was positive inasmuch as it had helped build understanding and relationships. The degree of integration between MHSTs and specialist NHS services varied between areas, with some teams reporting a tension between working closely with other services and establishing a clear and distinctive identity within the diverse landscape of mental health providers in their area. Engagement and experiences of education settings, and children and young people Engagement of schools and colleges was felt to be critical to the success of the programme, as was the senior mental health lead role. Some education settings needed more help to prepare for the programme and make the most of the support on offer from their MHST, and there was disappointment about the delayed roll-out of the senior mental health leads training. Many education settings reported that constraints of time and competing commitments meant that mental health leads could not always engage with their MHST as much as they would have liked and this was a barrier to implementation and success. Children and young people were not always aware that there was an MHST in their education setting or what it did. Those who had had direct contact with the team (either receiving one-to-one support or through involvement in group or whole school activities) had a better understanding of MHSTs; their experiences of this contact had been universally positive and they were able to articulate more clearly how the school cared for their emotional well-being. Children and young people gave several examples of ways in which their education setting was promoting and supporting well-being for all pupils, and these were acknowledged and valued. Programme progress and outcomes Education settings reported positive early effects from participating in the programme, including staff feeling more confident talking to children and young people about mental health issues, being able to access advice about mental health issues more easily, and having quicker access to support for children and young people with some mental health problems. Improvements in children and young people’s understanding of mental health and well-being were also widely reported, as were strengthened relationships between education settings, mental health services and other local partners. Many education settings had invested in mental health support since joining the programme, although it was unclear whether this was a direct impact of the programme or due to other factors (e.g. a response to the COVID-19 pandemic). Various enabling factors critical to programme implementation and success were identified, including a supportive local context, multi-agency working to ensure that key organisations and sectors could influence the design and delivery of the programme, clear governance structures, sharing learning and co-production with children, young people and their families. Implications of the study findings for longer-term evaluation Key implications include: •There is considerable value in the longer-term evaluation focusing on understanding for which groups of children and young people, and which mental health problems, the standard MHST intervention is less suitable or beneficial. •Consideration must be given to which outcomes to measure, in consultation with children, young people, parents and carers. Some of the outcomes expected at the start of the programme may no longer be realistic, especially those relating to service use, given the impact of COVID-19. •Careful work will be required to define the programme’s ‘ecological’ impacts, and when these might be expected to occur since whole school effects are likely to be more diffuse and take longer to become visible. Limitations The study focused only on the first 25 Trailblazer sites in the programme. These sites were chosen for characteristics thought likely to drive rapid progress and learning and therefore the findings from this evaluation may not be reflective of experiences across the programme as a whole. Survey response rates were generally low, and some groups were less well represented in interview samples, including staff from educational settings and specialist NHS mental health services. The study did not include research to explore children and young people’s experiences of receiving mental health support from an MHST. Conclusions There have been substantial and unprecedented changes in the wider context since the programme started. The COVID-19 pandemic has further increased inequalities in mental health and access to support, and gaps between services appear to be widening. Critical decisions will need to be taken about what, if any, role MHSTs should have in providing support to children and young people beyond the ‘mild to moderate’ remit that the programme was designed to address. There is also the question of how the programme can continue to retain a dual focus on mental health promotion (e.g. through the development of whole school approaches) and early intervention, and what additional support or resources might help educational partners and settings maximise the opportunities offered by the programme. Alongside strategies for workforce creation and training, more work is needed to ensure that trained staff are retained and can develop in their roles. Funding The Birmingham, RAND and Cambridge Evaluation Rapid Evaluation Centre is funded by the NIHR Health Services and Delivery Research programme (HSDR 16/138/31). The Rapid Evaluation Centre and Policy Innovation and Evaluation Research Unit is funded by the NIHR Policy Research Programme (PR-PRU-1217-20602).

Chenyi Wang, Jian Li, Xinxin Zhou et al.

Abstract The physics principle of pulse flight positioning is the main theoretical bottleneck that restricts the spatial resolution of the existing Raman distributed optical fiber sensing scheme. Owing to the pulse width of tens of nanoseconds, the spatial resolution of the existing Raman distributed optical fiber sensing scheme with kilometer-level sensing distance is limited to the meter level, which seriously restricts the development of the optical time-domain reflection system. In this paper, a chaos laser is proposed in the context of the physical principle of the Raman scattering effect, and a novel theory of chaos Raman distributed optical fiber sensing scheme is presented. The scheme reveals the characteristics of chaos Raman scattering light excited by a chaotic signal on the sensing fiber. Further, the chaos time-domain compression demodulation mechanism between the temperature variation information and chaos correlation peak is demonstrated. Then, the position of the temperature variation signal is precisely located using the delay time of the chaos correlation peak combined with the chaos pulse flight time. Based on this novel optical sensing mechanism, an experiment with 10 cm spatial resolution and 1.4 km sensing distance was conducted, and the spatial resolution was found to be independent of the sensing distance. Within the limit of the existing spatial resolution theory, the spatial resolution of the proposed scheme is 50 times higher than that of the traditional scheme. The scheme also provides a new research direction for optical chaos and optical fiber sensing.

Jinli WANG, Fengsheng LI, Fang XIE et al.

In the context of “carbon peaking and carbon neutrality”, the construction of a new type of clean and low-carbon power system with high penetration of renewable energies is moving forward at a fast pace, which has profoundly changed the behavior and functional roles of power distribution system. However, the current standard system is hardly capable of meeting the requirements of the development of distribution network due to the absence of corresponding critical supportive standard in addition to its lack of compatibility, coordination and integrity in the entire power distribution business. By taking the technical development and business needs into full consideration, this paper puts forward the principles of systematic, coordinated, dynamic and prospective standard system construction. Based on the theory of multidimensional model, the snowflake multidimensional structure model is established, which lays the foundation for the information management of standard system. With the power distribution as the main technical direction, a multi-level standard architecture covering the whole life cycle is also designed. Finally with regards to the key technical fields, this paper analyzes the requirements for standards and implements the planning and layout of key standards, so as to provide effective standards and direction guidance for the promotion of the green and low-carbon transformation of smart distribution network.

Ravid Shwartz-Ziv, Yann LeCun

Deep neural networks excel in supervised learning tasks but are constrained by the need for extensive labeled data. Self-supervised learning emerges as a promising alternative, allowing models to learn without explicit labels. Information theory, and notably the information bottleneck principle, has been pivotal in shaping deep neural networks. This principle focuses on optimizing the trade-off between compression and preserving relevant information, providing a foundation for efficient network design in supervised contexts. However, its precise role and adaptation in self-supervised learning remain unclear. In this work, we scrutinize various self-supervised learning approaches from an information-theoretic perspective, introducing a unified framework that encapsulates the \textit{self-supervised information-theoretic learning problem}. We weave together existing research into a cohesive narrative, delve into contemporary self-supervised methodologies, and spotlight potential research avenues and inherent challenges. Additionally, we discuss the empirical evaluation of information-theoretic quantities and their estimation methods. Overall, this paper furnishes an exhaustive review of the intersection of information theory, self-supervised learning, and deep neural networks.

Yeow Meng Chee, Quoc Tung Le, Hoang Ta

In this paper, we study the asymptotic nonnegative rank of matrices, which characterizes the asymptotic growth of the nonnegative rank of fixed nonnegative matrices under the Kronecker product. This quantity is important since it governs several notions in information theory such as the so-called exact Rényi common information and the amortized communication complexity. By using the theory of asymptotic spectra of V. Strassen (J. Reine Angew. Math. 1988), we define formally the asymptotic spectrum of nonnegative matrices and give a dual characterization of the asymptotic nonnegative rank. As a complementary of the nonnegative rank, we introduce the notion of the subrank of a nonnegative matrix and show that it is exactly equal to the size of the maximum induced matching of the bipartite graph defined on the support of the matrix (therefore, independent of the value of entries). Finally, we show that two matrix parameters, namely rank and fractional cover number, belong to the asymptotic spectrum of nonnegative matrices.

Hao-Lun Lin, Jyun-Yu Jiang, Ming-Hao Juan et al.

Nowadays, modern recommender systems usually leverage textual and visual contents as auxiliary information to predict user preference. For textual information, review texts are one of the most popular contents to model user behaviors. Nevertheless, reviews usually lose their shine when it comes to top-N recommender systems because those that solely utilize textual reviews as features struggle to adequately capture the interaction relationships between users and items. For visual one, it is usually modeled with naive convolutional networks and also hard to capture high-order relationships between users and items. Moreover, previous works did not collaboratively use both texts and images in a proper way. In this paper, we propose printf, preference modeling based on user reviews with item images and textual information via graph learning, to address the above challenges. Specifically, the dimension-based attention mechanism directs relations between user reviews and interacted items, allowing each dimension to contribute different importance weights to derive user representations. Extensive experiments are conducted on three publicly available datasets. The experimental results demonstrate that our proposed printf consistently outperforms baseline methods with the relative improvements for NDCG@5 of 26.80%, 48.65%, and 25.74% on Amazon-Grocery, Amazon-Tools, and Amazon-Electronics datasets, respectively. The in-depth analysis also indicates the dimensions of review representations definitely have different topics and aspects, assisting the validity of our model design.

Miral Sabry AlAshry

The purpose of this study is to assess the impact of Egyptian journalists through the “Anti-Cyber and Information Technology Crimes Law No. 175 of 2018” and the “Personal Data Protection Law No. 151” as well as its implications for journalistic practice and press freedom in Egypt. More specifically, the focal point of the study was to explore how the government monitors the data through new legislation. Questionnaires were undertaken with 188 journalists representing semi-governmental and private newspapers, divided into three categories: (86) Al-Ahrām (34) Albawabhnews (53) Al-Dustour and (15) Al Fagr. The study used Digital Authoritarianism Theory as a theoretical framework. The study revealed that the government placed restrictions on journalists by using Law No. 175 of 2018 to oppress journalists and media houses. In addition, the law has negatively impacted media freedom and given the government to censor online information.

Donghua Mao, Jinyi Qiu

With the construction of new power systems, distributed power sources are connected in large numbers and the possibility of faults increases. The optimal allocation of repair resources is important to improve the fault management efficiency and the quality of power supply services in the producer–consumer community. Using a large number of historical fault resources accumulated in the producer–consumer community, we first preprocess the fault information by the rough set theory, then establish an optimal allocation model that minimizes the total fault loss, consider fault risk classification and repair response capability, and finally use the improved gray wolf optimization algorithm to perform the optimal calculation. To address the problems of the traditional gray wolf algorithm, tent mapping is introduced in the generation of the initial population to enhance the uniformity of the initial population. The cooperative competition mechanism is introduced to improve the utilization of effective information among individuals. Finally, the feasibility and superiority of the algorithm are verified through the analysis of calculation cases. Finally, the feasibility of this configuration method is verified through the analysis of arithmetic cases.

Vudtiwat Ngampruetikorn, David J. Schwab

Avoiding overfitting is a central challenge in machine learning, yet many large neural networks readily achieve zero training loss. This puzzling contradiction necessitates new approaches to the study of overfitting. Here we quantify overfitting via residual information, defined as the bits in fitted models that encode noise in training data. Information efficient learning algorithms minimize residual information while maximizing the relevant bits, which are predictive of the unknown generative models. We solve this optimization to obtain the information content of optimal algorithms for a linear regression problem and compare it to that of randomized ridge regression. Our results demonstrate the fundamental trade-off between residual and relevant information and characterize the relative information efficiency of randomized regression with respect to optimal algorithms. Finally, using results from random matrix theory, we reveal the information complexity of learning a linear map in high dimensions and unveil information-theoretic analogs of double and multiple descent phenomena.

Yong Xiao, Xu Zhang, Yingyu Li et al.

This paper analyzes the fundamental limit of the strategic semantic communication problem in which a transmitter obtains a limited number of indirect observation of an intrinsic semantic information source and can then influence the receiver's decoding by sending a limited number of messages to an imperfect channel. The transmitter and the receiver can have different distortion measures and can make rational decision about their encoding and decoding strategies, respectively. The decoder can also have some side information (e.g., background knowledge and/or information obtained from previous communications) about the semantic source to assist its interpretation of the semantic information. We focus particularly on the case that the transmitter can commit to an encoding strategy and study the impact of the strategic decision making on the rate distortion of semantic communication. Three equilibrium solutions including the strong Stackelberg equilibrium, weak Stackelberg equilibrium, as well as Nash equilibrium have been studied and compared. The optimal encoding and decoding strategy profiles under various equilibrium solutions have been derived. We prove that committing to an encoding strategy cannot always bring benefit to the encoder. We therefore propose a feasible condition under which committing to an encoding strategy can always reduce the distortion performance of semantic communication.

Travis C. Cuvelier, Takashi Tanaka, Robert W. Heath

Motivated by control with communication constraints, in this work we develop a time-invariant data compression architecture for linear-quadratic-Gaussian (LQG) control with minimum bitrate prefix-free feedback. For any fixed control performance, the approach we propose nearly achieves known directed information (DI) lower bounds on the time-average expected codeword length. We refine the analysis of a classical achievability approach, which required quantized plant measurements to be encoded via a time-varying lossless source code. We prove that the sequence of random variables describing the quantizations has a limiting distribution and that the quantizations may be encoded with a fixed source code optimized for this distribution without added time-asymptotic redundancy. Our result follows from analyzing the long-term stochastic behavior of the system, and permits us to additionally guarantee that the time-average codeword length (as opposed to expected length) is almost surely within a few bits of the minimum DI. To our knowledge, this time-invariant achievability result is the first in the literature. The originally published version of the supplementary material included a proof that contained an error that turned out to be inconsequential. This updated preprint corrects this error, which originally appeared under Lemma A.7.