Global Task Research Articles

The Impact of Fatigue on the Sense of Local and Global Rhythmic Movement.

Efficient movement control and the mechanisms responsible for the sense of rhythm are still not fully understood. The purpose of this paper was to estimate the influence of fatigue on the sense of rhythm defined as specific order of movements and their rhythmic perception. It was examined in a holistic way, by analyzing both global and local aspects of the movement. Twenty adult participants (20.2 ± 0.4 years, ten females) took part in the experiment. The fatigue protocol was applied in four blocks, which consisted of 30-s consecutive jumping with 80% of maximal effort. Immediately after each fatigue block, the rhythm performance was evaluated in global and local tests. The global test was based on 45 continuous jumps and was divided into an assisted and an unassisted phase using the Optojump Next System. The local test was performed by bilateral tapping of lower limbs by means of the Vienna Test System. The hypothesis about the significant effect of fatigue on the sense of rhythm was falsified. In particular, we observed the lack of differences between global and local aspects of the movement. Moreover, female participants showed a better sense of rhythm than males. Regardless of the fatigue protocol, participants made larger errors with a lower movement frequency in local rhythmic tasks. The coefficient of variation showed that sex differences were only significant in the unassisted phase of the global rhythmic task. We suggest that movement variability metrics may provide additional information about the sense of rhythm, which should be explored more in future studies, not only dependent on fatigue.

Multi-Level Thresholding Image Segmentation Based on Improved Slime Mould Algorithm and Symmetric Cross-Entropy.

Multi-level thresholding image segmentation divides an image into multiple regions of interest and is a key step in image processing and image analysis. Aiming toward the problems of the low segmentation accuracy and slow convergence speed of traditional multi-level threshold image segmentation methods, in this paper, we present multi-level thresholding image segmentation based on an improved slime mould algorithm (ISMA) and symmetric cross-entropy for global optimization and image segmentation tasks. First, elite opposition-based learning (EOBL) was used to improve the quality and diversity of the initial population and accelerate the convergence speed. The adaptive probability threshold was used to adjust the selection probability of the slime mould to enhance the ability of the algorithm to jump out of the local optimum. The historical leader strategy, which selects the optimal historical information as the leader for the position update, was found to improve the convergence accuracy. Subsequently, 14 benchmark functions were used to evaluate the performance of ISMA, comparing it with other well-known algorithms in terms of the optimization accuracy, convergence speed, and significant differences. Subsequently, we tested the segmentation quality of the method proposed in this paper on eight grayscale images and compared it with other image segmentation criteria and well-known algorithms. The experimental metrics include the average fitness (mean), standard deviation (std), peak signal to noise ratio (PSNR), structure similarity index (SSIM), and feature similarity index (FSIM), which we utilized to evaluate the quality of the segmentation. The experimental results demonstrated that the improved slime mould algorithm is superior to the other compared algorithms, and multi-level thresholding image segmentation based on the improved slime mould algorithm and symmetric cross-entropy can be effectively applied to the task of multi-level threshold image segmentation.

EEG complexity during mind wandering: A multiscale entropy investigation

Our attention often drifts away from the ongoing task to task-unrelated thoughts, a phenomenon commonly referred to as mind wandering. Ample studies dedicated to delineating its electrophysiological correlates have revealed distinct event-related potentials (ERP) and spectral patterns associated with mind wandering. It remains less clear whether the complexity of the electroencephalography (EEG) changes when our minds wander, a metric that captures the predictability of the time series at varying timescales. Accordingly, this study investigated whether mind wandering impacts EEG signal complexity. We further explored whether such effects differ across timescales, and change in a context-dependent manner as indexed by global and local levels of processing. To address this, we recorded participants' EEG while they completed Navon's global and local processing task and occasionally reported whether they were on-task or mind wandering throughout the task. We found that brain signal complexity as indexed by multiscale entropy decreased at medium timescales in centro-parietal regions and increased at coarse timescales in anterior and posterior regions during mind wandering, as compared to the on-task state, for global processing. Moreover, global processing showed increased complexity at fine to medium timescales compared to local processing. Finally, behavioral performance revealed a context-dependent effect in accuracy measures, with mind wandering showing lower accuracy compared to the on-task state only during the local condition. Taken together, these results indicate that changes in brain signal complexity across timescales may be an important feature of mind wandering.

Control System Design and Methods for Collaborative Robots: Review

Collaborative robots cooperate with humans to assist them in undertaking simple-to-complex tasks in several fields, including industry, education, agriculture, healthcare services, security, and space exploration. These robots play a vital role in the revolution of Industry 4.0, which defines new standards of manufacturing and the organization of products in the industry. Incorporating collaborative robots in the workspace improves efficiency, but it also introduces several safety risks. Effective safety measures then become indispensable to ensure safe and robust interaction. This paper presents the review of low-level control methodologies of a collaborative robot to assess the current status of human–robot collaboration over the last decade. First, we discuss the classification of human–robot collaboration, architectures of systems and the complex requirements on control strategies. The most commonly used control approaches were presented and discussed. Several methods of control, reported in industrial applications, are elaborated upon with a prime focus on HR-collaborative assembly operations. Since the physical HRC is a critical control problem for the co-manipulation task, this article identifies key control challenges such as the prediction of human intentions, safety, and human-caused disturbances in motion synchronization; the proposed solutions were analyzed afterwards. The discussion at the end of the paper summarizes the features of the control systems that should be incorporated within the systematic framework to allow the execution of a robotic task from global task planning to low-level control implementation for safe and robust interactions.

ISH-PP-7: SCALING-UP HYPERTENSION CARE IN RESOURCE-CHALLENGED SETTINGS GLOBALLY

High blood pressure (BP) is the leading modifiable risk factor for death. More than 1.4 billion people suffer from hypertension worldwide. BP control remains less than 30% in high-income countries and < 10% in low- and middle-income countries (LMIC) rural areas, leading to significant disparities in hypertension-related cardiovascular mortality. Immediate action is needed to address suboptimal hypertension care globally and related inequalities. Evidence shows that strategies that leverage the existing infrastructure to deliver hypertension care are more likely feasible and rapidly scalable at marginal cost. The Control of Blood Pressure and Risk Attenuation-Bangladesh, Pakistan, Sri Lanka (COBRA-BPS) trial demonstrated that a community health worker-led multicomponent intervention tailored to rural settings improved BP control. It was also cost-effective and affordable (less than US$2 per capita annually). Likewise, community health worker-led models of hypertension care were beneficial in urban slums in Argentina, China, Colombia, India, Indonesia, Malaysia, Nepal, Pakistan, and Kenya. The partnership between WHO and Resolve to Save Lives is an excellent initiative to focus national attention on hypertension treatment in many low- and middle-income countries. Strong advocacy and multi-sectoral collaborations are also needed to implement policy strategies for hypertension prevention, including access to healthy foods and the built environment to promote physical activity. A (proposed) Global Hypertension Care Task Force jointly led by WHO and ISH could catalyse improvement in BP control rates. Every country should establish a dedicated national coordinating center for stewardship and implementing the hypertension control agenda through multifaceted, cost-effective strategies, including population-level policy initiatives and health systems strategies targeting high-risk individuals. Such efforts could save the lives of more than 100 million people aged 30–70 years, who would otherwise die prematurely by 2030, and help achieve Sustainable Development Goal 3.4

Hybrid Motion Representation Learning for Prediction From Raw Sensor Data

Motion prediction from raw LiDAR sensor data has drawn increasing attention and led to a surge of studies following two main paradigms. One paradigm is global motion paradigm, which simultaneously detects objects from point clouds and predicts the trajectories of each object in the future. The other paradigm is local motion paradigm, which directly performs dense motion prediction pointwisely. We observe that global motion prediction can benefit from local motion representation, since it contains rich local displacement contexts that are not explicitly exploited in global motion prediction. Correspondingly, local motion prediction can benefit from global motion representation, since it provides object contexts to improve prediction consistency inside an object. However, the complement of these two motion representations has not fully explored in the literature. To this end, we propose Hybrid Motion Representation Learning (HyMo), a unified framework to address the problem of motion prediction by making the best of both global and local motion cues. We have conducted extensive experiments on nuScenes dataset. The experimental results demonstrate that the learned hybrid motion representation achieves state-of-the-art performance on both global and local motion prediction tasks.

Применение нейронных сетей для сегментации изображений в задаче быстрой трассировки интегральных схем

The paper explores the possibilities of using neural network methods to solve the problem of global routing for VLSI ASIC design. An algorithm has been developed for generating a training dataset based on the Lee algorithm, which allows one to synthesize three-dimensional matrices with obstacles and points that need to be connected. The U-Net fully convolutional neural network, effective for semantic segmentation of images, was selected for training. The quality of the results was assessed using a validation data. A significant reduction in routing time compared to the Lee algorithm was shown, but the share of unbroken routes was only 37%. Ways to improve the training dataset and adapt the approach to real conditions using DEF and GUIDE files are proposed. In general, the work demonstrated the potential of neural network methods to speed up the global routing task, but continued research is required to improve the quality and reliability of the results. The work is useful for specialists in the field of integrated circuit design and machine learning.

ИННОВАЦИИ В СИСТЕМЕ ПРОФОРИЕНТАЦИОННОЙ РАБОТЫ В ОБЩЕМ ОБРАЗОВАНИИ НА СОВРЕМЕННОМ ЭТАПЕ

In modern conditions, education and training systems in various countries are faced with challenges that determine the demand for reliable information about changes in the labor market and future prospects for those who are faced with choosing their professional path. In Russia, close attention is paid to the professional guidance of the younger generation. A new round of activity to build a system of career guidance work occurred in connection with the Address of the President of the Russian Federation V. Putin to the Federal Assembly on February 21, 2023. During the Soviet period, the career guidance system met the objectives of the state in relation to personality formation and the needs of the economy. Managed at various levels of executive power. The inclusion of interested participants was assumed: students, parents, representatives of production, teachers and school administration. Considerable attention was paid to organizing interaction between participants and creating an appropriate subject-spatial environment and methodological support. Foreign practice of career guidance work is distinguished by the desire to take into account the individual needs of students, recognition of the significant role of specialists competent in the field of vocational guidance and counseling. International research distinguishes the uniqueness of career guidance practice in different countries and the demand for its services at any stage of life. In the Russian general education system, vocational guidance is defined simultaneously as a personal request of the child and his family and a global task for the country. A unified model of vocational guidance has been built, which ensures that students master the minimum vocational guidance. Formats for implementing a unified model, types of activities and materials, forms of career guidance activities allow career guidance work to be carried out at a level that meets the needs and interests of modern schoolchildren. The role of the pedagogical worker as a teacher-navigator who provides pedagogical support to students in the process of vocational guidance is defined. A unified model of professional guidance is implemented in parallel through the digital platform bvbinfo.ru.

Assessment of Water, Sanitation and Hygiene (WASH) in Schools of Jammu District- A Cross Sectional Study

Background: Provision of safe sanitation services reduces transmission of fecooral diseases, school drop outs,under-nutrition which in turn are important for overall development of children. The study was conducted toevaluate the adequacy of water, sanitation and hygiene (WASH) facilities in schools of rural Jammu.Methodology: A Cross Sectional survey was conducted in 54 (public and private) schools in rural Jammu usingthe questionnaire approved by the Global Task Team for Monitoring WASH in Schools.Results: Piped water was the main source of water supply. Facilities for drinking water were available in allschools. 94.3% schools had 1-9 drinking water points. All schools were doing filtration/chlorination of water. 51%schools reported water and soap availability in girl’s toilets and group hand washing activities were conductedonce a week in 31.5% schools. Toilets were cleaned once per day in 80% of the schools. 88% schools had toiletswithin school premises. Menstrual hygiene materials were available in 42 schools.Conclusions: Environment and sanitation facilities at most of the surveyed schools were reasonably good but notfully satisfactory.

Methodological Directions and Implementation Measures for the Formation of an Organizational and Economic Management Mechanism for the Innovative Development of Corporate Integration Associations

As a result of the research, it was determined that the organizational and economic mechanism of managing the innovative development of corporate integration associations is a complex system of interacting elements that combines organizational, economic, managerial and strategic aspects of management, aimed at the implementation of innovative strategies and achievements competitive advantages. Thus, a proper definition of the organizational and economic mechanism for managing the innovative development of corporate integration associations was proposed as a set of methods, tools, processes and relationships aimed at the creation and implementation of strategic innovation initiatives within the corporate association in order to ensure sustainable competitiveness and successful functioning on the market. The formation of an organizational and economic mechanism for managing the innovative development of corporate integration associations can be based on various approaches and methodological directions, in particular, it is a systemic approach, a strategic approach, an economic approach, a technological approach, an organizational approach, and a human resource approach. It is substantiated that the combination of different approaches allows to provide a comprehensive approach to the management of innovative development and the achievement of the strategic goals of associations. It was determined that the goal of forming an organizational and economic mechanism for managing the innovative development of corporate integration associations can be formulated as defining a clear direction of the innovative activity of the enterprise in order to achieve competitive advantages and ensure sustainable development in the market. The global tasks of forming an organizational and economic mechanism for managing the innovative development of corporate integration associations are presented, which include: creating a sustainable innovative culture, increasing competitiveness, ensuring sustainable development, creating a favorable innovative environment, searching for new opportunities, developing and implementing the latest technologies, promoting the development of human capital, expanding global influence, stimulating innovative entrepreneurship and building partnerships.

Review: Renewable Energy in an Increasingly Uncertain Future

A number of technical solutions have been proposed for tackling global climate change. However, global climate change is not the only serious global environmental challenge we face demanding an urgent response, even though atmospheric CO2 ppm have risen from 354 in 1990 to 416 in 2020. The rise of multiple global environmental challenges makes the search for solutions more difficult, because all technological solutions give rise to some unwanted environmental effects. Further, not only must these various problems be solved in the same short time frame, but they will need to be tackled in a time of rising international tensions, and steady global population increase. This review looks particularly at how all these environmental problems impact the future prospects for renewable energy (RE), given that RE growth must not exacerbate the other equally urgent problems, and must make a major difference in a decade or so. The key finding is that, while the world must shift to RE in the longer run, in the short term what is more important is to improve Earth’s ecological sustainability by the most effective means possible. It is shown that reducing both the global transport task and agricultural production (while still providing an adequate diet for all) can be far more effective than converting the energy used in these sectors to RE.

Ключевые проблемы развития Приморского края: взгляд населения, региональной власти, экспертов

The article represents the results of a comparative analysis of the opinions of the population, regional authorities on key socio-economic problems of Primorsky Krai, and these results correlate with the opinions of the participants of the Eastern Economic Forum – 2022 on those areas that should be the focus of attention and funding from the federal authorities. The results of this analysis are disappointing: the population of the region and regional officials, together with the country's political elites (represented by the Forum participants) think in different paradigms. The population cares about solving current vital problems, while officials prefer solving global ambitious tasks to be implemented in the long term. The article proposes measures for the formation of such public agenda in which the choice of a scenario for the investment development of the region would be synchronized with a long-term strategy for the socio-economic development of Primorsky Krai in terms of resources and interests of all major social groups in the region.

Urbanization and health impacts of air pollution in Ukraine: threats and opportunities

The aim to conduct a content analysis of studies on the impacts of air pollution on the urban residents’ health in the world and Ukraine, to show the relationship between urbanization and the selected environmental risk factor, to assess its contribution to the global disease burden for Ukraine minimizing harmful effects.Material and methods: Content analysis of research on the air pollution exposure on the urban residents’ health in the world and Ukraine was used. The Data Visualizations / Institute for Health Metrics and Evaluation (IHME) hub data was used to study the contribution to the global burden of disease. GBD 2019 Cause and Risk Summary.Results: At present, changes in thinking and a synergistic approach are needed to fulfill all the goals of achieving the Sustainable Development Goals, approved, agreed and set by governments around the world, including Ukraine. Important Global Task 3.9 "Significantly reduce the number of deaths and illnesses from hazardous chemicals and air, water and soil pollution and poisoning", was not chosen by Ukraine due to a lack of reliable indicators with a proven cause-and-effect relationship with the environmental factor that caused this disorder. Reducing the level of air pollution can significantly reduce the burden of diseases, primarily those caused by heart disease and stroke, lung cancer, and chronic respiratory diseases, including asthma.Conclusions: Policies that encourage investment in cleaner transport, energyefficient homes, electricity generation, industry and better household waste management can reduce key sources of air pollution.

Neural similarity across task load relates to cognitive reserve and brain maintenance measures on the Letter Sternberg task: a longitudinal study.

The aging process is characterized by change across several measures that index cognitive status and brain integrity. In the present study, 54 cognitively-healthy younger and older adults, were analyzed, longitudinally, on a verbal working memory task to investigate the effect of brain maintenance (i.e., cortical thickness) and cognitive reserve (i.e., NART IQ as proxy) factors on a derived measure of neural efficiency. Participants were scanned using fMRI while presented with the Letter Sternberg task, a verbal working memory task consisting of encoding, maintenance and retrieval phases, where cognitive load is manipulated by varying the number of presented items (i.e., between one and six letters). Via correlation analysis, we looked at region-level and whole-brain relationships between load levels within each phase and then computed a global task measure, what we term phase specificity, to analyze how similar neural responses were across load levels within each phase compared to between each phase. We found that longitudinal change in phase specificity was positively related to longitudinal change in cortical thickness, at both the whole-brain and regional level. Additionally, baseline NART IQ was positively related to longitudinal change in phase specificity over time. Furthermore, we found a longitudinal effect of sex on change in phase specificity, such that females displayed higher phase specificity over time. Cross-sectional findings aligned with longitudinal findings, with the notable exception of behavioral performance being positively linked to phase specificity cross-sectionally at baseline. Taken together, our findings suggest that phase specificity positively relates to brain maintenance and reserve factors and should be better investigated as a measure of neural efficiency.

Dual global-aware propagation for few-shot learning

• A global-aware sample module (GSM) is proposed to capture the global description of each sample. • A global-aware task module (GTM) is used to obtain the global description across tasks. • A feature fusion module incorporating both global task and global sample information is used for label propagation. Few-shot learning remains a challenging problem because it needs to classify unseen categories with only a few samples as limited supervision. The tasks and samples can be extremely different in various few-shot problems, which makes it even more difficult. Due to the local connectivity in CNN, it can not capture the global description of the samples and the features are not discriminative enough from a global viewpoint. Meanwhile, a sample usually reveals similar features in different tasks, which does not consider the global information of the task and weakens the discrimination of features. To address the above issue, we proposed a Dual Global-Aware method for label Propagation (DGAP) to encode two kinds of global description to enhance the discriminative power of the learned features. On the sample level, the global-aware sample module (GSM) is employed to get the contextual description and enhance the feature representation capability of each sample. On the task level, the global-aware task module (GTM) is used to embed the features in the current task to a more appropriate and discriminative position in the feature space which is task-oriented. In the end, a feature fusion module is adopted to combine the features obtained from both global sample and global task respects. Based on the label propagation method, the proposed DGAP improves the performance approximately 2–5% over the baseline on different benchmarks (mini-Imagenet and tiered-Imagenet) across different structures (Conv4 structure and ResNet12 structure), which reaches the state-of-the-art.

Proxy measures of cognitive reserve and trajectories of gait and cognitive decline in older adults

AbstractBackgroundLifestyle interventions are an emerging area of interest in dementia prevention. Education, physical activity, and social interactions are potentially modifiable lifestyle factors that are considered proxies of cognitive reserve. People with greater cognitive reserve could be protected against decline in gait and cognition, two interrelated problems associated with dementia, by coping better with age‐ or pathology‐related brain changes. We examined whether decline in gait and cognitive functions are different in those with higher versus lower levels of education, physical activity, and social interactions.MethodGait and cognitive performance in 1,095 LonGenity study participants (mean age = 75.4±6.7 years) that were free of dementia at baseline were examined up to 12 years. Gait speed was measured during usual pace (single‐task walking, STW‐speed) and walking‐while‐talking (WWT‐speed). Cognitive performance was measured with standard neuropsychological tests and a standardized composite global cognitive measure was derived. Years of education, number of blocks walked per day, living with someone and engaging in paid or volunteer work (markers of social interactions) were obtained from self‐report. Linear mixed‐effects models adjusted for sex, parental longevity, cognitive impairment, and global health were used to examine age‐associated changes in gait and cognition in those with and without greater cognitive reserve.ResultSTW‐speed and WWT‐speed did not vary as a function of education, physical activity, or social interactions. Greater number of blocks walked per day was associated with slower decline in global cognition, Trail Making Test (TMT)‐A, TMT‐interference, digit symbol substitution, logical memory, figure recall, free recall, category and phonemic fluency tests. Higher education was associated with slower decline in global cognition, TMT‐interference, TMT‐A and figure copy task. Living with someone was associated with slower decline in global cognition, digit symbol substitution and logical memory. Paid or volunteer work was associated slower decline in global cognition.ConclusionHaving higher education, more physical activity and social interactions appear to protect against cognitive, but not gait decline, potentially by building up cognitive reserve. The multifaceted etiology and relatively earlier decline of gait may render it less influenced by potentially modifiable risk factors in late life than cognition.

Efficient and Secure Deep Learning Inference in Trusted Processor Enabled Edge Clouds

Edge intelligence has emerged as a prevalent enabling technology to support various intelligent applications. Along with the prosperity, it also raises great concern on the security and privacy since the edge servers are usually shared and untrusted. The security-sensitive code (i.e., the pre-trained model) and data may be easily stolen by malicious tenants, and even untrusted infrastructure providers. To this end, Software Guard Extensions (SGX) is proposed to provide an isolated Trust Execution Environment (TEE) for security and privacy guarantee. However, we find that running tasks in SGX suffer certain performance degradation due to the limited Enclave Page Cache (EPC) size. This further leads to frequent page swapping operations and the high enclave call overhead, which are also influenced by the task (i.e., DNN layer) dispatching and scheduling. To this end, in this paper, we design <b>Lasagna</b> , as an SGX based secure DNN inference acceleration framework, which explores the layered-structure of DNN models to well balance the usage of the scarce EPC resources and the computation resources. Lasagna mainly consists of a global task balancer and a local task scheduler, responding for task dispatching across distributed edge servers and task scheduling in local server, respectively. We evaluate Lasagna over different well-known DNN models, and the results show that Lasagna effectively speeds up the inference performance by <inline-formula><tex-math notation="LaTeX">$1.11\times -1.51\times$</tex-math></inline-formula> .

Draudze no jauna un citādāk – reliģijas potenciāls pieaugošas kompleksitātes apstākļos

The Christian church in its current composition, structure, and expression is in crisis. However, the crisis of the congregation and the church that has escalated in recent decades can be understood as a spiritual challenge. This means not only making structural changes in the existing forms of congregation and church, adapting to the changing reality in the context of the current lack of resources, but also paying attention to the spiritual perspective of complex processes of change. How is it possible to think about the congregation and the church in a completely different way? What could be the new forms of plural, lively and open congregation and church that are important for the sustainable development of the whole society? The starting point is to rethink what we mean by the concepts of “congregation” and “church” and what could be the practical forms of religion in the near future – in an individualized, differentiated, and complex society. In 2020, the Internal Development Goals initiative emerged, suggesting that there is one blind spot in the efforts to solve complex societal issues and create a sustainable global society – the internal development of a person and the need for internal change in the person himself. The initiative proposes the idea of a new, inner, consciousness-raising revolution, capable of creating a new foundation for the coexistence of humanity. At the end of 2021, the first part of the initial project was completed, formulating 23 different qualities and skills – in relationships with oneself, thinking and cognition, relations with others and the world, cooperation with others, and in action. As the church and Christianity become involved into and a part of the program for achieving the inner goals of a person, aligning their actions with these goals, and creating the structures necessary to achieve these goals, the church would become one of the driving forces of sustainable development, a kind of “folk high school” for the birth of a new consciousness, gaining new relevance on a societal scale. In this global task of learning and building a metastable civilization, the congregation and the church have a decisive potential. The article discusses the latest insights contributed by several theologians (Uta Pohl-Patalong, Tomáš Halík, etc.) regarding models of the congregation and church relevant to the future of Christianity, and analyses the project Erprobungsräumen of the Evangelical Church of Central Germany, aspiring towards new forms of congregations.

Crisscross Harris Hawks Optimizer for Global Tasks and Feature Selection.

The online version contains supplementary material available at 10.1007/s42235-022-00298-7.

A convolutional plane wave model for sound field reconstruction

Spatial sound field interpolation relies on suitable models to conform to available measurements and predict the sound field in the domain of interest. A suitable model can be difficult to determine when the spatial domain of interest is large compared to the wavelength or when spherical and planar wavefronts are present or the sound field is complex, as in the near-field. To span such complex sound fields, the global reconstruction task can be partitioned into local subdomain problems. Previous studies have shown that partitioning approaches rely on sufficient measurements within each domain due to the higher number of model coefficients. This study proposes a joint analysis of all of the local subdomains while enforcing self-similarity between neighbouring partitions. More specifically, the coefficients of local plane wave representations are sought to have spatially smooth magnitudes. A convolutional model of the sound field in terms of plane wave filters is formulated and the inverse reconstruction problem is solved via the alternating direction method of multipliers. The experiments on simulated and measured sound fields suggest that the proposed method retains the flexibility of local models to conform to complex sound fields and also preserves the global structure to reconstruct from fewer measurements.