Adaptive Restoration Research Articles

Triple-Level Full-Stage Adaptive Restoration Optimization for Coupled Transmission and Distribution Systems Considering Restoration Security Risks

Triple-Level Full-Stage Adaptive Restoration Optimization for Coupled Transmission and Distribution Systems Considering Restoration Security Risks

Reference ecosystem construction and adaptive restoration effect evaluation: A case study of a small watershed in the loess hilly region

AbstractThe loess hilly region is one of the most fragile areas in China. Many ecological restoration projects in this region are equivalent to simple afforestation and grass planting, with large investment and low benefits. Based on the concept of reference ecosystem, this study uses remote sensing data and vegetation community survey of Wanhuigou catchment, and applies methods such as redundancy analysis and GeoDetector to explore the characteristics of topography, soil, and vegetation of reference ecosystem, so as to provide restoration standards for damaged or degraded ecosystems in a small watershed. Thirteen typical and representative areas are selected to evaluate the degree of ecosystem damage and resilience, and divided into four categories according to the evaluation results and characteristics of ecosystems. Corresponding restoration measures such as protection and conservation, natural restoration, auxiliary regeneration, and ecological reconstruction are adopted for ecosystems under different scenarios with reference ecosystems as the target, and the effectiveness of implementation is assessed. The results show that the combination conditions of elevation and slope have a very important influence on the distribution of ecosystems. In the process of ecological restoration, it is necessary to deeply grasp the characteristics of soil and species diversity within the same community and among different communities, as well as their interrelationships. Adaptive restoration measures for ecosystems in different situations are conducive to the sustainability and effectiveness of ecosystem restoration. Given the complexity and diversity of habitat conditions and plant community types in Wanhuigou catchment, the results have certain universality, which can provide reference for the comprehensive management of other small watersheds in the loess hilly region, so as to achieve sustainable construction and restoration of ecosystems as well as harmonious development between humans and nature.

Adaptive restoration of Kali Mas Surabaya: strategy to recall and sustain historical area

Appropriate and targeted strategies are needed to preserve places and buildings of historical value. Historical objects are objects that are susceptible to damage and may be unmatched elsewhere. So, damage to or loss of an heirloom is very fatal. Implementing conservation strategies in an area is necessary because a place or site has complex and varied constituent elements. In this case, an area that is neglected but still has historical features requires a special strategy and perhaps several strategies. This is also because the existing strategy does not yet provide criteria and considerations regarding this matter. Kali Mas Surabaya is a historical case study that was the initial downtown port in Surabaya before it was finally decommissioned and is now rarely maintained. By carrying out a comprehensive analysis of history, documentary evidence, and actual physical evidence, it will become the basis for policy analysis and implementation. Therefore, this research will focus on how to carry out conservation strategies for recalling and sustaining abandoned historical areas so that these strategies can be generalized and applied to other historical locations.

WARM: A wavelet adaptive restoration module for surface anomaly detection

As a key component of lithium-ion batteries, surface defect detection of pole-piece is vital for quality control. Detection methods based on supervised have been used in pole-piece. However, the long cycle for data collection cannot meet the needs for fast construction and application of production line, making self-supervised a promising alternative. Although existing restoration-based methods have been widely studied, it’s still difficult to balance the problem of restoring normal regions and distinguishing abnormalities. We propose a Wavelet Adaptive Reconstruction Module by exploiting the obvious spatial and frequency differences between intra-class normal and abnormal features. Through training, the wavelet coefficients of the inputs are adaptively refined, potently obstructing the identity map from input image to restored image, thus improving the generalization of restoration network. The structure only consists of 2 simple Unets and WARM, it solves the anomaly detection task for pole-piece, and also outperforms other state-of-the-arts on MvTec AD.

Discriminative context-aware network for camouflaged object detection.

Animals use camouflage (background matching, disruptive coloration, etc.) for protection, confusing predators and making detection difficult. Camouflage Object Detection (COD) tackles this challenge by identifying objects seamlessly blended into their surroundings. Existing COD techniques struggle with hidden objects due to noisy inferences inherent in natural environments. To address this, we propose the Discriminative Context-aware Network (DiCANet) for improved COD performance. DiCANet addresses camouflage challenges through a two-stage approach. First, an adaptive restoration block intelligently learns feature weights, prioritizing informative channels and pixels. This enhances convolutional neural networks' ability to represent diverse data and handle complex camouflage. Second, a cascaded detection module with an enlarged receptive field refines the object prediction map, achieving clear boundaries without post-processing. Without post-processing, DiCANet achieves state-of-the-art performance on challenging COD datasets (CAMO, CHAMELEON, COD10K) by generating accurate saliency maps with rich contextual details and precise boundaries. DiCANet tackles the challenge of identifying camouflaged objects in noisy environments with its two-stage restoration and cascaded detection approach. This innovative architecture surpasses existing methods in COD tasks, as proven by benchmark dataset experiments.

Multi-Scenario Simulation of Ecosystems Based on Adaptive Restoration to Promote Human–Nature Harmony: A Case Study of Loess Hills Micro-Watershed

The ecological environment in loess hilly regions is fragile, and the contradiction between the development of human society and ecological environment protection is becoming more and more prominent with the intensification of human interference. In order to give full play to the role of ecosystem adaptation in ecological restoration, this study seeks natural conditions that are suitable for the stable existence of ecosystems in the Wanhuigou catchment using the reference ecosystem method and uses these conditions as constraints of the GeoSOS-FLUS model for multi-scenario simulation. Based on ecosystem service value and ecological compensation mechanisms, the comprehensive benefits of different scenarios are compared, and economic development is taken into account while ensuring that ecological protection remains a priority. The results show the following: (1) The unstable ecosystems concentrated on a gentle slope (5–15°) at altitudes of 1201–1379 m, 1201–1594 m, 1379–1715 m and 1715–1856 m are suitable for restoration to farmland, shrub, grassland and forest ecosystems, respectively, and the change characteristics of soil and vegetation communities also verify the above conclusions. (2) The scenario of agricultural development from 2020 to 2030 and the early stages from 2030 to 2050 is the best among the three scenarios, while the scenario of ecological protection is the best in the middle and late stages of 2030–2050. Formulating relevant policies and ecological protection measures according to the scenario of ecological protection is more conducive to promoting the harmonious coexistence of humans and nature. (3) Under the scenario of ecological protection, the unstable ecosystem distributed along the gentle slope (5–15°) of 1379–1483 m and 1483–1594 m achieves the most significant improvement in ecosystem service value by focusing on and giving priority to the restoration of natural conditions that are suitable for the stable existence of ecosystems. This study provides ideas and references for the formation of ecosystem restoration and development strategies for small watersheds in loess hilly regions, and it is of great significance for the promotion of a harmonious coexistence between humans and nature.

Fitness program for correction of overweight in women

The article discusses a fitness program for the correction of overweight in women of early adulthood. This problem is very relevant for women of early adulthood today. More and more people have problems with obesity and overweight. One of the leading methods of body weight correction is physical exercises, which, in addition to reducing excess weight, also contribute to the normalization of metabolism, restoration of the body's adaptation to physical activity; normalization of the functions of the cardiovascular and other body systems, these programs are fitness.
 Fitness is one of the world's most popular health improvement systems, which allows us to meet the modern needs of different age groups who want to make their figure beautiful and their health strong. The modern fitness industry offers a wide variety of techniques, and these techniques allow to expand the range of effects of physical exercises on the body of those who exercise.
 We have developed an experimental program, the essence of which is that, taking into account the initial data and individual characteristics of the body constitution of the course participants, physical activity and training volumes were constantly adjusted throughout the program, which gives participants the opportunity to properly approach the training process, learn the basic steps, movements, adapt to the load, try and choose training for their further development, and modern training programs used in the fitness facility help to achieve results in the most
 To achieve an effective weight loss result, two components must be used: nutritional adjustments and certain fitness training methods. Proper nutrition is an integral part of this process. Dual work improves metabolism and thus metabolic processes in the body, which helps to accelerate the process of reducing body fat.
 To achieve the goal and objectives, we initially formed two groups of 10 participants who were engaged in a sports club, all of whom were of the first age group, of whom 70% had problems with overweight.

Adaptive restoration and reconstruction of incomplete flow fields based on unsupervised learning

Due to experimental limitations and data transmission constraints, we often encounter situations where we can only obtain incomplete flow field data. However, even with incomplete data, we can still extract valuable information about the main structural characteristics of the flow field. In this study, we propose a novel unsupervised learning reconstruction method to restore the incomplete flow field data. Our method comprises several key steps: First, based on the temporal evolution characteristics of the flow field, we employ the Autoregressive Integrated Moving Average model method to pre-reconstruct the incomplete data. Next, we introduce the Fuzzy Spatial Consistency Index (FSCI), which measures the spatial coherence among neighboring data variations. By utilizing FSCI as a guiding metric, we iteratively optimize and replace missing values using the Proper Orthogonal Decomposition method. Importantly, our reconstruction process does not rely on expensive high-fidelity data fusion or external intervention, making it highly efficient and cost-effective. We focus our research on the classic problem of flow around the hydrofoil and apply the unsupervised learning reconstruction method to restore incomplete flow fields with varying missing rates. We also investigate the impact of flow field stability, snapshot sampling frequency, and missing structure on reconstruction accuracy. Our results indicate that these factors significantly influence the reconstruction of velocity fields with a high missing rate compared with a lower missing rate. Additionally, we observe that the reconstruction performance of the streamwise velocity field is relatively inferior compared to the normal velocity field, and the reconstruction accuracy is higher for relatively stable flow fields. These findings provide valuable insights and further validate the effectiveness and applicability of the unsupervised learning reconstruction method for restoring incomplete flow fields.

Water Releases From Dams Improve Ecological Health and Societal Benefits in Downstream Estuaries

Abstract This review study investigated the response of low-inflow estuaries (LIEs) to dam releases as this type of estuary is particularly sensitive to freshwater inflow modification. LIEs occur in arid and semi-arid regions and are subject to periods of little to no freshwater inflow. Case studies were used to identify ecological health and societal benefits associated with flow releases. Successful releases have been made to keep the estuary mouth open, ensure mixing, facilitate a salinity gradient and provide recruitment pulses to the marine environment for fish and invertebrates. Baseflow inputs ensured ecosystem connectivity and maintained estuary water quality gradients. Flow pulse releases in certain seasons stimulated spawning migrations of fish between freshwater and estuarine habitats. Holistic and adaptive restoration approaches were successful in terms of providing ecosystem services and societal benefits such as improved fisheries and livelihoods. Ongoing engagement, inclusion of communities, support from river users, and cooperation between multiple agencies were also important. However, this management solution for LIEs is threatened by increasing abstraction of water, competing water uses, over allocation, and frequent droughts. Moving forward, freshwater releases from dams should be considered an important restoration action that can improve ecological health, estuary function, ecosystem services, and societal benefits. This should take place within a socio-ecological system framework using an adaptive management and monitoring approach. Other key considerations for planning and implementation of future dam releases to LIEs were recommended.

Restoration temporarily supports the resilience of sagebrush‐steppe ecosystems subjected to repeated fires

AbstractMany ecosystems are experiencing increased fire frequencies and species invasions that can erode their resilience and cause a shift to alternative states. In the sagebrush‐steppe, a semi‐arid shrubland ecosystem in North America, restoration treatments are often implemented following wildfire to enhance their resilience to invasion. However, little is known about the long‐term effectiveness of these treatments. We investigated whether repeated restoration efforts provide greater resilience in sagebrush‐steppe communities initially dominated by species with different post‐fire regeneration traits and subjected to compounding wildfires and invasion byBromus tectorumover 25 years.We studied 37 permanent transects (Columbia Basin, Washington, USA) in which species abundance was recorded multiple times from 1992 to 2017. We quantified community change and its relationship with fire, restoration, and moisture availability. Resilience was evaluated by quantifying community resistance and stability indices.The greatest change occurred in communities where the obligate seeding shrubArtemisia tridentatawas initially common. Repeated fires led to the extirpation of this shrub and eventual dominance ofB. tectorum. Herbicide applications temporarily suppressedB. tectorumpost‐fire. Seeding treatments and above average precipitation initially increased native cover. Although communities where resprouting species were common showed the least change, repeated fires did lead to a gradual but substantial decline (86%) in resprouting shrubs.Synthesis and applications. Our findings show that repeated restoration efforts, together with elevated precipitation, can support native species re‐establishment in systems experiencing altered disturbance regimes and species invasions. Our unique long‐term dataset demonstrates, however, that many such interventions have short‐lived effects due to the strong ‘unhelpful resilience’ of highly invaded systems. This implicitly suggests that many such systems have experienced fundamental shifts in ecosystem state. The likelihood of this occurring is strongly associated with the dominant species post‐fire regeneration traits. We predict that community composition and resilience will continue to degrade in the sagebrush‐steppe unless management prioritizes fire suppression and an adaptive restoration approach that considers resource availability.

Adaptive 3D noise level‐guided restoration network for low‐dose positron emission tomography imaging

AbstractMany deep learning methods have been proposed to improve the quality of low‐dose PET images (LPET), which usually construct end‐to‐end networks with certain radiation dose inputs. However, these approaches have omitted the noise disparity in PET images, which may differ among manufacturers or populations. Therefore, we tend to exploit these noise differences among PET images to achieve adaptive restoration. We proposed a 3D noise level‐guided PET restoration network for LPET including (1) adaptive noise level‐aware subnetwork and (2) LPET restoration subnetwork. The first subnetwork aims to predict the noise level of the given LPET, while the second subnetwork treats the estimated noise level as a priori information to guide the restoration process from LPET to standard‐dose PET images. Experiments were performed on real human head and neck datasets while the peak signal‐to‐noise ratio and structural similarity index measure were used to evaluate LPET recovery performance. Moreover, we also compared the proposed network with several deep‐learning approaches. Experimental results demonstrate that our network with dual‐stage design can perform adaptive restoration for LPET, yielding better visual and quantitative results. In future work, we attempt to apply our method to other imaging tasks and adapt it for clinical practice.

Method for controlling invasive Ammophila arenaria in coastal dunes alters restoration trajectory

Coastal dune restoration often focuses on weed removal to reestablish native vegetation communities. Point Reyes National Seashore (PRNS) initiated large‐scale dune restoration after becoming concerned about loss of dune and rare species habitat from spread of non‐native Ammophila arenaria (European beachgrass). Two projects removed beachgrass from 146 ha of heavily invaded dunes using either mechanical removal or herbicide treatment. PRNS conducted pre‐ and post‐restoration vegetation monitoring for 10 years post‐implementation, evaluating success in (1) eradicating beachgrass and (2) reestablishing vegetation communities similar to native dunes in cover, diversity, and species composition. Both methods eradicated beachgrass with annual retreatment. However, they were less successful in rebuilding vegetation communities with comparable native species cover and/or richness. Mechanical removal areas remained largely barren expanses of sand that struggled to support native plants except for a rare perennial, Tidestrom's lupine (Lupinus tidestromii). Tidestrom's lupine and other rare plants now number in the hundreds of thousands. Conversely, herbicide‐treated backdunes were dominated by standing dead beachgrass that resisted decomposition even after 7 years, which hampered native and rare plant establishment. Delayed decomposition was less of an issue in herbicide‐treated foredunes, because sand overwash buried necromass. Restored areas also contended with subsequent invasion by secondary plant invaders. By 2021, only older herbicide‐treated backdunes, and to a lesser extent, mechanical backdunes, showed signs of convergence with native dunes. Successful convergence may be hindered by lingering physical and microbial legacy effects of beachgrass invasion and treatment method. Adaptive restoration may be needed to counter effects and improve project success.

Оценка качества лесосеменного материала на экспериментальном участке сосны обыкновенной (Pinus sylvestris L.) при адаптивном восстановлении лесных ландшафтов

When choosing a technology for restoring forest landscapes, the quality of forest seed material is a significant factor. To develop a reference information system to support decision-making for adaptive restoration of forest landscapes, it is necessary to have data on the types and quality of forest seed material. Existing studies directly or indirectly confirm, on the one hand, the influence of seed quality on the quality of future plantations, on the other hand, the influence of forest characteristics on the quality and quantity of seeds. Preservation of the quality of forest seed material in conditions of large-scale harvesting of Scots pine seeds (Pinus sylvestris L.) is possible with the development of permanent forest seed plots, and (or) the use of modern technologies for separating forest seeds without loss of genetic diversity and increasing not only germination and seed germination energy, but also the vitality of seedlings, their stability to the change of abiotic factors. Descriptive statistics of biometric parameters of trees and cones of Scots pine on the experimental site (N51°50.00'; E39°22.09', 113 m ASL) demonstrates the following values (average; average error): the height of the tree (186.2; 11.7), the diameter of the root neck of the tree (5.9; 0.3), the ratio of the height of the tree to the diameter of the root neck (31.90; 0.97), the number of cones (9; 4), the number of seeds (12; 5). There is a strong positive correlation at the level of p < 0.0001 between diameter and height, a strong positive correlation between the number of cones and the number of seeds (p < 0.001), a strong positive correlation (p < 0.05) between the height of the tree and the number of cones. In the future, it is planned to evaluate the relationship of accumulated degree days, accumulated precipitation, normalized difference vegetation index with the cones and seeds number.

Space-making and aesthetics: Adaptive restoration, new functions and their experience in architecture

In this study I investigate several questions related to adaptive restoration, i.e. when a functioning piece of architecture operates with a different purpose to its original one, as well as the role of aesthetics in re-purposing, and the importance of the special forms of experience such a conversion provides. The questions connected to these architectural projects are not only theoretically inspiring, leading to diverse and broad fields of research in architecture, art and aesthetics, but are also crucial on a practical level, and hence require caution and precise consideration, given the impact the final results of such projects may have, as well as in terms of the effect and efficiency of the new space. Creative and adaptive re-purpose, modification or complete change of function can have wonderful potential, as well as, obviously, presenting serious hazards to avoid. What is equally important, however, is that this will also contribute to a strengthening of awareness of architecture and its aesthetic qualities, hence further promoting the idea of safeguarding and care of edifices and of tangible heritage.

Psychotherapy in Dealing with Crises in the COVID-19 Pandemic

In the article, a theoretical analysis of the study of crisis states and the methodological foundations of crisis psychotherapy, taking into account foreign and domestic experience, is carried out. Based on the results of empirical studies, modern foreign and domestic researchers have established that crisis conditions during the COVID-19 pandemic are accompanied by suicidal reactions, depression, neurotic conditions with post-traumatic stress disorders, exacerbation of psychosomatic diseases, psychopathological disorders.Psychological approaches in psychotherapy together with crisis psycho-psychotherapeutic interventions for working with acute crisis states and crisis psychotherapy of clients in the post-quarantine period are considered.The concepts of a crisis state, the features of the influence of "covid" psychotrauma on the mental and psychological health of a person, and the provision of psychological assistance in crisis situations during the COVID-19 pandemic are described in detail. It is noted that in working with crisis conditions during the COVID-19 pandemic, modern foreign and Ukrainian specialists prefer cognitive-behavioral psychotherapy.At the theoretical and methodological level, it has been proved that psychotherapy of post-traumatic stress disorder (PTSD) is close to crisis psychotherapy and is aimed at reintegration of mental activity disturbed by the "conductive" psychotrauma and restoration of psychological adaptation to a certain extent.The psychotherapeutic model of psychological crisis intervention in the context of the COVID-19 pandemic is based on a biopsychosocial approach and requires a comprehensive and integrated use of crisis psychotherapy methods with the integration of neuropsychotic methods and Internet technologies into the entire therapy process.

Employing chunk size adaptation to overcome concept drift

Modern analytical systems must process streaming data and correctly respond to data distribution changes. The phenomenon of changes in data distributions is called concept drift, and it may harm the quality of the used models. Additionally, the possibility of concept drift appearance causes that the used algorithms must be ready for the continuous adaptation of the model to the changing data distributions. This work focuses on non-stationary data stream classification, where a classifier ensemble is used. To keep the ensemble model up to date, the new base classifiers are trained on the incoming data blocks and added to the ensemble while, at the same time, outdated models are removed from the ensemble. One of the problems with this type of model is the fast reaction to changes in data distributions. We propose the new Chunk Adaptive Restoration framework that can be adapted to any block-based data stream classification algorithm. The proposed algorithm adjusts the data chunk size in the case of concept drift detection to minimize the impact of the change on the predictive performance of the used model. The experimental research, backed up with the statistical tests, has proven that Chunk Adaptive Restoration significantly reduces the model’s restoration time.

A Review on Decision-making Methods for Restoration Control of Transmission and Distribution Systems

Power system blackouts can’t be avoided fundamentally, so it is of great significance to realize the adaptive and collaborative restoration control of transmission and distribution system to improve the power system blackout defense capability. In this paper, the existing researches are summarized from three aspects, i.e., decision-making of transmission system restoration control, decision-making of distribution system restoration control, decision-making of transmission and distribution coordinated restoration control, the research difficulties are expounded, and the future research directions are prospected. In view of the characteristics of multi-level, cross-regional, multi-stage and strong uncertainty of collaborative restoration control of transmission and distribution systems, it is pointed out that the establishment of restoration decision support system by comprehensive application of optimization algorithms, expert rules and numerical simulation programs is an important mean to realize adaptive restoration control.

Decision Support System for Adaptive Restoration Control of Distribution System

Aiming at the high-dimensional uncertainties of restoration process, an optimization model for distribution system restoration control is proposed considering expected restoration benefits, expected restoration costs, and security risks of the overall restoration scheme. In the proposed model, the effect of security control on restoration process is actively analyzed considering the security control costs of preventive, emergency, and correction controls. A two-layer decision support framework for distribution system restoration decision support system (DRDSS) is also designed. The upper layer of the proposed framework generates the pre-adjustment schemes of operation mode for energized power grid by load transfer and selects the optimal pre-adjustment scheme and the corresponding partitioning scheme based on the partition adjustment results of each pre-adjustment scheme. In addition, it optimizes the spatial-temporal decision-making of the inter-partition connectivity. For each partition, the lower layer of the proposed framework pre-selects the units and loads to be restored according to the pre-evaluated restoration income, generates the table of alternative restoration scheme for coping with uncertain events through simulation and deduction, and evaluates the risk and benefit of each scheme. For the uncertain events in the actual restoration process, the current restoration scheme can be adaptively switched to a sub-optimal scheme or re-optimized if necessary. Meanwhile, the proposed framework provides an information interaction interface for collaborative restoration with the related transmission system. A 123-node test system is built to evaluate the effectiveness and adaptability of the proposed model and framework.

Adaptive restoration of pedestrian appearance in the spatiotemporal domain

Adaptive restoration of pedestrian appearance in the spatiotemporal domain

Application of Adaptive Image Restoration Algorithm Based on Sparsity of Block Structure in Environmental Art Design

Image restoration is a research hotspot in computer vision and computer graphics. It uses the effective information in the image to fill in the information of the designated damaged area. This has high application value in environmental design, film and television special effects production, old photo restoration, and removal of text or obstacles in images. In traditional sparse representation image restoration algorithms, the size of dictionary atoms is often fixed. When repairing the texture area, the dictionary atom will be too large to cause blurring. When repairing a smooth area, the dictionary atom is too small to cause the extension of the area, which affects the image repair effect. In this paper, the structural sparsity of the block to be repaired is used to adjust the repair priority. By analyzing the structure information of the repair block located in different regions such as texture, edge, and smoothing, the size of the dictionary atom is adaptively determined. This paper proposes a color image restoration method that adaptively determines the size of dictionary atoms and discusses a model based on the partial differential equation restoration method. Through simulation experiments combined with subjective and objective standards, the repair results are evaluated and analyzed. The simulation results show that the algorithm can effectively overcome the shortcomings of blurred details and region extension in fixed dictionary restoration, and the restoration effect has been significantly improved. Compared with the results of several other classic algorithms, it shows the effectiveness of the algorithm in this paper.