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The challenge of search inefficiency arises when multiple UAV swarms conduct dynamic target area searches in unknown environments. The primary sources of this inefficiency are repeated searches in the target region and the dynamic motion of targets. To address this issue, we present the distributed adaptive real-time planning search (DAPSO) technique, which enhances the search efficiency for dynamic targets in uncertain mission situations. To minimize repeated searches, UAVs utilize localized communication for information exchange and dynamically update their situational awareness regarding the mission environment, facilitating collaborative exploration. To mitigate the effects of target mobility, we develop a dynamic mission planning method based on local particle swarm optimization, enabling UAVs to adjust their search trajectories in response to real-time environmental inputs. Finally, we propose a distance-based inter-vehicle collision avoidance strategy to ensure safety during multi-UAV cooperative searches. The experimental findings demonstrate that the proposed DAPSO method significantly outperforms other search strategies regarding the coverage and target detection rates. [ABSTRACT FROM AUTHOR]

PurposeTo identify any clinical or dosimetric parameters that predict which individuals may benefit from on-table adaptation during pancreas stereotactic body radiotherapy (SBRT) with MRI-guided radiotherapy.Methods and materialsThis was a retrospective study of patients undergoing MRI-guided SBRT from 2016 to 2022. Pre-treatment clinical variables and dosimetric parameters on the patient's simulation scan were recorded for each SBRT course, and their ability to predict for on-table adaptation was analyzed using ordinal logistic regression. The outcome measure was number of fractions adapted.ResultsSixty-three SBRT courses consisting of 315 fractions were analyzed. Median prescription dose was 40 Gy in five fractions (range, 33-50 Gy); 52% and 48% of courses were prescribed ≤40 Gy and >40 Gy, respectively. The median minimum dose delivered to 95% (D95) of the gross tumor volume (GTV) and planning target volume (PTV) was 40.1 Gy and 37.0 Gy, respectively. Median number of fractions adapted per course was three, with 58% (183 out of 315) total fractions adapted. On univariable analysis, the prescription dose (>40 Gy vs ≤40 Gy), GTV volume, stomach V20 and V25, duodenum V20 and dose maximum, large bowel V33 and V35, GTV dose minimum, PTV dose minimum, and gradient index were significant determinants for adaptation (all p

Plans are prepared to provide direction, set goals, manage risks, and ensure timely and successful implementation to achieve desired outcomes. However, plans fail to deliver desired outcomes when an unexpected event occurs. The adaptive planning process is known for its ability to respond to an unexpected event with pre-emptive preparation. The adaptive planning approach seeks to minimise uncertainties and associated risks during each stage of the planning process by (re)assessing the feasibility of water supply needs and the effectiveness of planning decisions. The two most prevalent concepts in the integration of adaptiveness in planning processes are the dynamic adaptive policy planning and the adaptive planning cycle (Mobius loop) frameworks; these frameworks are used to address the uncertainties and associated risks at the planning stage. The Mobius loop, or infinity loop, is gaining momentum, as it clearly illustrates the iterative and continuous nature of adaptation to changing conditions. However, the data on the successful implementation of 'adaptive' planning practices are limited, and there is little knowledge about these practices. This study reviews the literature in this field and discusses the different interpretations of adaptiveness and its benefits and challenges while developing long-term strategic plans. The findings identify gaps for future research and recommend the way forward for policymakers to promote adaptive planning practices. [ABSTRACT FROM AUTHOR]

The challenge of search inefficiency arises when multiple UAV swarms conduct dynamic target area searches in unknown environments. The primary sources of this inefficiency are repeated searches in the target region and the dynamic motion of targets. To address this issue, we present the distributed adaptive real-time planning search (DAPSO) technique, which enhances the search efficiency for dynamic targets in uncertain mission situations. To minimize repeated searches, UAVs utilize localized communication for information exchange and dynamically update their situational awareness regarding the mission environment, facilitating collaborative exploration. To mitigate the effects of target mobility, we develop a dynamic mission planning method based on local particle swarm optimization, enabling UAVs to adjust their search trajectories in response to real-time environmental inputs. Finally, we propose a distance-based inter-vehicle collision avoidance strategy to ensure safety during multi-UAV cooperative searches. The experimental findings demonstrate that the proposed DAPSO method significantly outperforms other search strategies regarding the coverage and target detection rates.

To assess the performance of a knowledge-based planning (KBP) model for generating intensity-modulated proton therapy (IMPT) treatment plans as part of an adaptive radiotherapy (ART) strategy for patients with high-risk prostate cancer. A knowledge-based planning (KBP) model for proton adaptive treatment plan generation was developed based on thirty patient treatment plans utilizing RapidPlanTM PT (Varian Medical Systems, Palo Alto, CA). The model was subsequently validated using an additional eleven patient cases. All patients in the study were administered a prescribed dose of 70.2 Gy to the prostate and seminal vesicle (CTV70.2), along with 46.8 Gy to the pelvic lymph nodes (CTV46.8) through simultaneous integrated boost (SIB) technique. To assess the quality of the validation knowledge-based proton plans (KBPPs), target coverage and organ-at-risk (OAR) dose-volume constraints were compared against those of clinically used expert plans using paired t -tests. The KBP model training statistics (R2) (mean ± SD, 0.763 ± 0.167, range, 0.406 to 0.907) and χ² values (1.162 ± 0.0867, 1.039-1.253) indicate acceptable model training quality. Moreover, the average total treatment planning optimization and calculation time for adaptive plan generation is approximately 10 minutes. The CTV70.2 D 98% for the KBPPs (mean ± SD, 69.1 ± 0.08 Gy) and expert plans (69.9 ± 0.04 Gy) shows a significant difference (p < 0.05) but are both within 1.1 Gy of the prescribed dose which is clinically acceptable. While the maximum dose for some organs-at-risk (OARs) such as the bladder and rectum is generally higher in the KBPPs, the doses still fall within clinical constraints. Among all the OARs, most of them received comparable results to the expert plan, except the cauda equina D max , which shows statistical significance and was lower in the KBPPs than in expert plans (48.5 ± 0.06 Gy vs 49.3 ± 0.05 Gy). The generated KBPPs were clinically comparable to manually crafted plans by expert treatment planners. The adaptive plan generation process was completed within an acceptable timeframe, offering a quick same-day adaptive treatment option. Our study supports the integration of KBP as a crucial component of an ART strategy, including maintaining plan consistency, improving quality, and enhancing efficiency. This advancement in speed and adaptability promises more precise treatment in proton ART. [ABSTRACT FROM AUTHOR]

The riparian green space covers the inner buffer zone to maintain the ecological characteristics of the river and the outer coordination green zone to serve the adjacent urban–rural functional areas. The complex topography and landform of mountainous areas make riparian green space closely connected with the natural process and spatial function, which is the focus of urban and rural construction. However, the “out-of-context” and “one-size-fits-all” means of multi-department planning have separated the natural process maintenance and constructive utilization of riparian green space in urban–rural areas, resulting in serious conflicts between protection and development and low control effectiveness. Under the background of prioritization of ecology and the control of urban–rural spatial resources in the whole region, we draw lessons from the theories and methods of related disciplines and takes the integration of protection and utilization as the basis point. We present a new conceptual framework that follows the natural ecological characteristics of rivers and appropriately integrates the demands of urban–rural development and construction, and discusses the differentiated planning and regulation method of riparian green space in mountainous urban–rural areas based on transect zoning. This conceptual framework not only ensures the healthy operation of the ecosystem inside the riparian zone, but also improves the composite service function outside the riparian zone, and minimizes the impact of urban–rural construction on the riparian zone.

The application of ecosystem service (ES) knowledge to planning processes and decision-making can lead to more effective climate change adaptation. Despite the increased attention given to the ES concept, its degree of integration and use in spatial planning processes are still below the expectations of those who are promoting this concept. Barriers hindering its operationalisation cover a span of aspects ranging from theoretical to procedural and methodological issues. Overall, there is a general lack of guidance on how and at what point ES knowledge should be integrated into planning processes. This study aims to promote the inclusion of ES knowledge into spatial planning practices and decision-making processes to enhance climate change adaptation. A replicable GIS-based methodology is proposed. First, the potential supply of ESs that can support climate change adaptation (ESCCAs) is defined, mapped, and quantified. Then, a need for an ESCCA supply is identified, and territorial capacities to respond to the expected climate change impacts on natural and socio-economic sectors are assessed. The methodology is applied to the Friuli Venezia Giulia Autonomous Region (Italy) as an illustrative case study. The results reveal that areas with similar geomorphological characteristics tend to respond similarly. Forest ecosystems, inland wetlands and specifically salt marshes can potentially supply a greater variety of ESCCAs. In the case study area, about 62% of the supplied ESCCAs can contribute to reducing the impacts in more than 50% of the impacted sectors. The territory of the study site generally shows good preparedness for expected impacts in most of the analysed sectors; less prepared areas are characterised by agricultural ecosystems. This reading approach based on land cover analyses can thus assist in developing policies to enhance different territorial capacities, ultimately leading to better and more sustainable decision-making. [ABSTRACT FROM AUTHOR]

Flooding in low-lying coastal cities is expected to worsen with climate change, and planning for long-term flood mitigation is challenging due to high uncertainty in projections. Risks are associated with under- or over-investment in expensive grey infrastructure. Implementing green stormwater infrastructure (GSI) on strategically large private properties may be a lower-risk alternative. In our previous studies published in 2022 and 2024, we found that the capability of industrial properties to supplement city flood mitigation was substantial. They could offset climate change impacts in the long term, even under a major climate change scenario, and reduce flood probabilities. In this paper, we restate their potential as a case study of large private properties to draw more attention from practitioners and transfer scientific knowledge into practice. The maximum flood mitigation capabilities of large private properties can be met through networks of GSI facilities and a long-term adaptation plan that considers all possible approaches to implementing GSI over time. However, government regulations and policies are needed to support their implementation to the maximum capabilities. [ABSTRACT FROM AUTHOR]

Neoadjuvant chemotherapy, when combined with radiotherapy, serves as an optional treatment for patients with locally advanced sigmoid colon cancer and is usually performed in conjunction with complete mesocolic excision. The substantial movement of surrounding organs in cases of sigmoid colon cancer frequently leads to toxicity in normal tissues. The present report details the case of a 76-year-old man diagnosed with locally advanced sigmoid colon cancer. Initially, treatment using the Tomotherapy Hi-Art system was selected; however, during image guidance from the first to the sixth fractions, the tumor location underwent a marked change, exceeding the range of the planning target volume. Efforts to recapture the image were unsuccessful, leading to a decision to transition the patient to the MRIdian system for daily treatment with online adaptive radiotherapy. The positional variations in the tumor were evident in each treatment using the MRIdian system, with mean shifts of 2.58 cm in the right-left direction, 1.24 cm in the cranial-caudal direction and 0.40 cm in the anterior-posterior direction. The mean time from the entry of the patient to treatment completion was 41 min. Adaptive treatment plans were performed for all 19 fractions, with two treatments repeated due to the tumor moving out of tracking range. Following irradiation using the MRIdian system, the gross tumor volume decreased by 62%. Notably, the patient experienced no side effects during treatment. A CT scan conducted 3 months after radiotherapy revealed a marked reduction in the tumor size, consistent with a partial response, leading to the scheduling of surgery. Following surgery, a CT scan after 6 months revealed no local recurrence in the surgical bed region. The findings in the present case support the feasibility of implementing an adaptive treatment plan using the MRIdian system for locally advanced sigmoid colon cancer in the context of neoadjuvant chemoradiotherapy. [ABSTRACT FROM AUTHOR]

Towns and cities in the industrial and former coal mining areas of England have often struggled to cope with economic restructuring. This article offers a near contemporary history of the central area of one such city, where culture has become a key device for promoting development and regeneration. Three episodes of policy are distinguished: from 1990 to about 2011, the emergence of a twin-track economic strategy that combined out-of-town business parks with the remodelling of the central area partly on 'Urban Renaissance' principles: from 2011 onwards, continued city centre decline when previous investments had little economic impact; and after about 2020, a process of re-orientation; and as part of this, a reinvigorated attempt to rebrand the city, albeit within the continuing framework of the twin-track strategy. A reflexive methodology is used to construct the narrative. That methodology enables a joint consideration of discourse and economic realities, showing how place, branding, and planning come together in representational logics that generate both supportive and counter narratives. [ABSTRACT FROM AUTHOR]

Background: The stomach is one of the most deformable organs. Its shape can be easily affected by breathing movements, and daily diet, and it also varies when the body position is different. The susceptibility of stomach has made it challenging to treat gastric cancer using the conventional image-guided radiotherapy, i.e., the techniques based on kilovoltage X-ray imaging. The magnetic resonance imaging guided radiotherapy (MRgRT) is usually implemented using a hybrid system MR-LINAC. It is feasible to implement adaptive radiotherapy using MR-LINAC for deformable organs such as stomach. In this case report, we present our clinical experience to treat a gastric cancer patient using MR-LINAC. Case description: The patient is a 58-year-old male who started having black stools with no apparent cause a year ago. Gastroscopy result showed pancreatic cancer, pathology: adenocarcinoma on gastric cancer biopsy, adenocarcinoma on gastric body minor curvature biopsy. The patient was diagnosed with gastric cancer (adenocarcinoma, cTxN+M1, stage IV, HER-2 positive). The patient was treated in 25 fractions with radiotherapy using MR-LINAC with online adaptive treatment plans daily. The target area in daily MR images varied considerably when compared with the target area on the CT simulation images. During the course of treatment, there have even been instances where the planned target area where the patient received radiotherapy did not cover the lesion of the day. Conclusion: Online adaptive MRgRT can be a meaningful innovation for treating malignancies in the upper abdomen. The results in the current study are promising and are indicative for further optimizing online adaptive MRgRT in patients with inoperable tumors of the upper abdomen. [ABSTRACT FROM AUTHOR]

Regionalization approaches—where utilities in close geographic proximity cooperate to manage drought risks and co‐invest in new infrastructure—are increasingly necessary strategies for leveraging economies of scale to meet growing demands and navigate financial risks. However, regionalization also brings new challenges to water supply planning. Successful regionalization policies must equitably balance the interests of multiple partners while navigating power relationships between regional actors. In long‐term infrastructure planning contexts, this challenge is heightened by the evolving system‐state dynamics, which may be fundamentally reshaped by infrastructure investment. This work introduces Equitable, Robust, Adaptive, and Stable Deeply Uncertain Pathways (DU PathwaysERAS), an exploratory modeling framework for developing regional water supply management and infrastructure investment pathways. DU PathwaysERAS provides an integrated framework for stakeholders to evaluate the equity of policy outcomes across cooperating partners and explore regional power relationships within cooperative infrastructure policies. To capture the time‐evolving dynamics of infrastructure pathways, DU PathwaysERAS features new tools to measure the adaptive capacity of pathway policies and evaluate time‐evolving vulnerability. We demonstrate our framework on a six‐utility water supply partnership seeking to develop cooperative infrastructure investment pathways in the Research Triangle, North Carolina. Our results indicate that commonly employed framings of robustness can have large and unintended adverse consequences for regional partnerships. Results further illustrate that regional and individual vulnerabilities are highly interdependent and emphasize the need to limit counterparty risks through carefully designed cooperative agreements. Beyond the Research Triangle, these results are broadly applicable to cooperative water supply infrastructure investment and management globally. Key Points: We present new tools to develop equitable & robust regional water supply investment pathways & clarify their time‐evolving vulnerabilitiesWe demonstrate how commonly used framings of water supply robustness can have unintended adverse impacts on regional equityCooperative investments can help water utilities maintain regional supply reliability but can also expose utilities to new financial risks [ABSTRACT FROM AUTHOR]

Given the risk posed by escalating climate conditions, there is a need to assess how localities integrate adaptive planning into hazard mitigation and how this is enabled or constrained by existing planning institutions. We explore this for flood planning in the Lower Rio Grande Valley of Texas, United States – a largely underresourced and highly socioeconomically vulnerable area. Using Natural Language Processing to analyze county and regional hazard plans as well as transcripts of regional flood planning meetings, we find that adaptive planning is largely absent in the study area. Like many localities in the U.S., the communities in the study area have approached flood planning in static terms that do not fully consider future uncertainties; failed to engage diverse participation in planning; and neglected to pursue co-benefits possible with flood mitigation and other sectors. Critically, this may be a product of traditional planning institutions as well as limited local capacities. [ABSTRACT FROM AUTHOR]

This paper aims to share post-pandemic lessons for destination resilience and the sustainability of events. It offers a new perspective that reimagines the space and place of events as learning destinations enmeshed in complex systems. Complexity arises due to the interactions and interrelationships between numerous stakeholders, activities, and events in the social–ecological destination system, where boundaries are porous, and issues and actions from afar can impact the local community. The case presented here describes the micro-level activities and actions undertaken to engage with destination resilience and sustainable event management and certification at a learning destination in Texas, USA. These situated efforts are shown (i) at the campus-wide level for the university and (ii) with the collaborative, learning-oriented activities undertaken by students in event management classes to pilot test the Sustainable Event Certification Checklist that was developed. They corroborate the general characteristics and criteria of the complex learning destination summarized in the paper, along with identifying and discussing the skills, literacies, and lessons learned to advance destination resilience and the sustainability of events. Participants in the learning destination draw on practical knowledge and develop soft skills to engage in adaptive planning proactively and collaboratively with other stakeholders to address emergent challenges and practical problems in the complex destination and sustainable event domain.

Background Hyperthermia treatment planning is increasingly used in clinical applications and recommended in quality assurance guidelines. Assistance in phase-amplitude steering during treatment requires dedicated software for on-line visualization of SAR/temperature distributions and fast re-optimization in response to hot spots. As such software tools are not yet commercially available, we developed Adapt2Heat for on-line adaptive hyperthermia treatment planning and illustrate possible application by different relevant real patient examples. Methods Adapt2Heat was developed as a separate module of the treatment planning software Plan2Heat. Adapt2Heat runs on a Linux operating system and was developed in C++, using the open source Qt, Qwt and VTK libraries. A graphical user interface allows interactive and flexible on-line use of hyperthermia treatment planning. Predicted SAR/temperature distributions and statistics for selected phase-amplitude settings can be visualized instantly and settings can be re-optimized manually or automatically in response to hot spots. Results Pretreatment planning E-Field, SAR and temperature calculations are performed with Plan2Heat and imported in Adapt2Heat. Examples show that Adapt2Heat can be helpful in assisting with phase-amplitude steering, e.g., by suppressing indicated hot spots. The effects of phase-amplitude adjustments on the tumor and potential hot spot locations are comprehensively visualized, allowing intuitive and flexible assistance by treatment planning during locoregional hyperthermia treatments. Conclusion Adapt2Heat provides an intuitive and flexible treatment planning tool for on-line treatment planning-assisted hyperthermia. Extensive features for visualization and (re-)optimization during treatment allow practical use in many locoregional hyperthermia applications. This type of tools are indispensable for enhancing the quality of hyperthermia treatment delivery.

Scenario planning is increasingly used to manage uncertainty, but such planning often struggles to influence decision making and help communities navigate multiple futures. This article proposes a framework for planning practice that integrates scenario planning and real option theory to identify adaptation options that make plans or projects responsive to multiple futures. The framework is explained through a demonstration case, Plan Bay Area 2050 and Link21, based on document content analysis and expert interviews. The findings show that exploratory scenarios generate opportunities for real options reasoning and adaptive planning, by making uncertainties explicit when thinking about the future. [ABSTRACT FROM AUTHOR]

This article addresses the issue of developing designs of resilient hydrological infrastructures for cities facing sea level rise in the Anthropocene. It undertakes short case studies of differently scaled cities, three in the Global North and three in the Global South. The aim is to investigate the current water management situations in order to reveal potentials for increased urban and environmental resilience. Cities are approached as complex adaptive systems (CAS) negotiating uncertainty that concerns designing for resilience, understood as viable transitions for their interlinked social, ecological, and technological systems (SETS). The main finding is that, despite obvious differences, the six cases are surprisingly similar. Potentials for increased hydrological resilience reside in design approaches that work differently with what is currently deprivileged and considered 'merely' peripheral. Peripheral cities and the peripheries of coastal cities are found to be of key rather than minor adaptive infrastructural import. To reprivilege the peripheral here means to adopt more dynamically flexible, long-term, decentralized, and nonanthropocentric urban design approaches to water and infrastructures. Specifically, this article advocates thinking about water via at least four critical displacements. These displacements point toward alternatives concerning excessively static and land-based designs, short-term planning, overly anthropocentric conceptions of the city environment distinction, and undue centrism in planetary urbanization of the Global North and Global South. In conclusion, this article presents a brief outlook to other cases which suggest that greater resilience potentials are likely to be found in planning for the complexly ecotone city. This works mostly bottom-up from the local regimes for water sensitive infrastructures to regional network designs that can engage with larger climatic and ecological landscapes. [ABSTRACT FROM AUTHOR]

Background: Gastrointestinal (GI) tract motility is one of the main sources for intra/inter‐fraction variability and uncertainty in radiation therapy for abdominal targets. Models for GI motility can improve the assessment of delivered dose and contribute to the development, testing, and validation of deformable image registration (DIR) and dose‐accumulation algorithms. Purpose: To implement GI tract motion in the 4D extended cardiac‐torso (XCAT) digital phantom of human anatomy. Materials and Methods: Motility modes that exhibit large amplitude changes in the diameter of the GI tract and may persist over timescales comparable to online adaptive planning and radiotherapy delivery were identified based on literature research. Search criteria included amplitude changes larger than planning risk volume expansions and durations of the order of tens of minutes. The following modes were identified: peristalsis, rhythmic segmentation, high amplitude propagating contractions (HAPCs), and tonic contractions. Peristalsis and rhythmic segmentations were modeled by traveling and standing sinusoidal waves. HAPCs and tonic contractions were modeled by traveling and stationary Gaussian waves. Wave dispersion in the temporal and spatial domain was implemented by linear, exponential, and inverse power law functions. Modeling functions were applied to the control points of the nonuniform rational B‐spline surfaces defined in the reference XCAT library. GI motility was combined with the cardiac and respiratory motions available in the standard 4D‐XCAT phantom. Default model parameters were estimated based on the analysis of cine MRI acquisitions in 10 patients treated in a 1.5T MR‐linac. Results: We demonstrate the ability to generate realistic 4D multimodal images that simulate GI motility combined with respiratory and cardiac motion. All modes of motility, except tonic contractions, were observed in the analysis of our cine MRI acquisitions. Peristalsis was the most common. Default parameters estimated from cine MRI were used as initial values for simulation experiments. It is shown that in patients undergoing stereotactic body radiotherapy for abdominal targets, the effects of GI motility can be comparable or larger than the effects of respiratory motion. Conclusion: The digital phantom provides realistic models to aid in medical imaging and radiation therapy research. The addition of GI motility will further contribute to the development, testing, and validation of DIR and dose accumulation algorithms for MR‐guided radiotherapy. [ABSTRACT FROM AUTHOR]

ABSTRACT Urban Water Systems (UWS) operate under a broad list of uncertainties. They usually depend on large amount of investments requiring long-term planning for a future full of changes with high degree of uncertainties (climate, social and economic). Many of these uncertainties do not have analytical representation neither they count on agreement among experts or decision makers concerning their influence in the performance of the UWS. The literature has named these changes as deep uncertainties (DU). This work presents a general approach to incorporate the influence of DU on planning and management processes of three types of UWS: 1) Water Supply Systems; 2) Drainage Systems and 3) Rainwater Harvesting Systems. The proposed framework defines steps toward the selection of the best policies and their evaluation in a broad set of scenarios. The particularities of each urban system led to adjustments in some steps of the general methodology. The approach proposed in this work was applied to a practical case, the Rainwater Harvesting Systems in the city of Ipameri, located in the State of Goiás, Brazil. The results highlight the impacts of DU factors on the system performance and reinforce this type of approach as a contribution towards adaptive planning for UWS.

Purpose: To identify any clinical or dosimetric parameters that predict which individuals may benefit from on-table adaptation during pancreas stereotactic body radiotherapy (SBRT) with MRI-guided radiotherapy. Methods and materials: This was a retrospective study of patients undergoing MRI-guided SBRT from 2016 to 2022. Pre-treatment clinical variables and dosimetric parameters on the patient’s simulation scan were recorded for each SBRT course, and their ability to predict for on-table adaptation was analyzed using ordinal logistic regression. The outcome measure was number of fractions adapted. Results: Sixty-three SBRT courses consisting of 315 fractions were analyzed. Median prescription dose was 40 Gy in five fractions (range, 33–50 Gy); 52% and 48% of courses were prescribed ≤40 Gy and >40 Gy, respectively. The median minimum dose delivered to 95% (D95) of the gross tumor volume (GTV) and planning target volume (PTV) was 40.1 Gy and 37.0 Gy, respectively. Median number of fractions adapted per course was three, with 58% (183 out of 315) total fractions adapted. On univariable analysis, the prescription dose (>40 Gy vs ≤40 Gy), GTV volume, stomach V20 and V25, duodenum V20 and dose maximum, large bowel V33 and V35, GTV dose minimum, PTV dose minimum, and gradient index were significant determinants for adaptation (all p

Urban flooding disasters have become increasingly frequent in rural-urban fringes due to rapid urbanization, posing a serious threat to the aquatic environment, life security, and social economy. To address this issue, this study proposes a flood disaster risk assessment framework that integrates a Weighted Naive Bayesian (WNB) classifier and a Complex Network Model (CNM). The WNB is employed to predict risk distribution according to the risk factors and flooding events data, while the CNM is used to analyze the composition and correlation of the risk attributes according to its network topology. The rural-urban fringe in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is used as a case study. The results indicate that approximately half of the rural-urban fringe is at medium flooding risk, while 25.7% of the investigated areas are at high flooding risk. Through driving-factor analysis, the rural-urban fringe of GBA is divided into 12 clusters driven by multiple factors and 3 clusters driven by a single factor. Two types of cluster influenced by multiple factors were identified: one caused by artificial factors such as road density, fractional vegetation cover, and impervious surface percentage, and the other driven by topographic factors, such as elevation, slope, and distance to waterways. Single factor clusters were mainly based on slope and road density. The proposed flood disaster risk assessment framework integrating WNB and CNM provides a valuable tool to identify high-risk areas and driving factors, facilitating better decision-making and planning for disaster prevention and mitigation in rural-urban fringes. [ABSTRACT FROM AUTHOR]

Among the UNCCD SDGs 2030, there is the recognition that land consumption can strongly affect the provision of ecosystem services. From the perspective of land degradation neutrality, urban level is the right scale when planning actions against land consumption. The aims of this research are: (1) to assess land consumption at urban landscape scale and its effects on natural capital flow provision; and (2) to identify sustainable strategic planning choices for land consumption mitigation and natural capital enhancement. We propose and test an approach based on multi-temporal landscape spatial analysis (land use/land cover map, land consumption map, and landscape metrics) and ecosystem services' flow assessment for the identification of areas at risk of loss of natural capital flow. The results have shown that from 2006 to 2019, land consumption has increased with a consequent decrease of natural capital flow. LULC dynamics has been analyzed in terms of landscape risk to lose natural capital flow, highlighting that the management of Galatone urban landscape is still far from land consumption neutrality. Landscape metrics have allowed the analysis of the aggregation among land consumption areas. The mitigation of land consumption should be based on the identification of suitable nature-based solutions towards the balance between past land consumption and future land recovery. [ABSTRACT FROM AUTHOR]

This paper aims to share post-pandemic lessons for destination resilience and the sustainability of events. It offers a new perspective that reimagines the space and place of events as learning destinations enmeshed in complex systems. Complexity arises due to the interactions and interrelationships between numerous stakeholders, activities, and events in the social–ecological destination system, where boundaries are porous, and issues and actions from afar can impact the local community. The case presented here describes the micro-level activities and actions undertaken to engage with destination resilience and sustainable event management and certification at a learning destination in Texas, USA. These situated efforts are shown (i) at the campus-wide level for the university and (ii) with the collaborative, learning-oriented activities undertaken by students in event management classes to pilot test the Sustainable Event Certification Checklist that was developed. They corroborate the general characteristics and criteria of the complex learning destination summarized in the paper, along with identifying and discussing the skills, literacies, and lessons learned to advance destination resilience and the sustainability of events. Participants in the learning destination draw on practical knowledge and develop soft skills to engage in adaptive planning proactively and collaboratively with other stakeholders to address emergent challenges and practical problems in the complex destination and sustainable event domain. [ABSTRACT FROM AUTHOR]

It is still very challenging to use conventional radiation therapy techniques to treat stomach tumors, although image-guided radiotherapy, mainly by kV X-ray imaging techniques, has become routine in the clinic. This is because the stomach is one of the most deformable organs, and thus it is vulnerable to respiratory motions, daily diet, and body position changes. In addition, X-ray radiographs and CT volumetric images have low contrast in soft tissues. In contrast, magnetic resonance imaging (MRI) techniques provide good contrast in images of soft tissues. The emerging MR-guided radiotherapy, based on the MR-LINAC system, may have the potential to solve the above difficulties due to its unique advantages. The real-time imaging feature and the high-contrast of soft tissues MR images provided by the MR-LINAC system have facilitated the therapeutic adaptive planning. Online learning capabilities could be used to optimize the automatic delineation of the target organ or tissue prior to each radiotherapy session. This could greatly improve the accuracy and efficiency of the target delineation in adaptive planning. In this clinical case report, we elaborated a workflow for the diagnosis and treatment of two patients with gastric mucosa-associated lymphoid tissue (MALT) lymphoma. One patient underwent MR-guided daily adaptive radiotherapy based on daily automated segmentation using the novel artificial intelligence (AI) technique for gastric delineation.

Planning systems rely on an element of certainty and can sometimes be ill-equipped to creatively adapt to increasingly complex system trajectories. We analyse how designers and planners deal creatively with a statutory planning system that is increasingly being challenged by the progressive complexity of the broader social-ecological system in which it operates. Taking Sydney, Australia, as a case study and drawing from six interviews with senior planners and designers, we explore planning barriers and the strategies used to address these barriers. While many of the strategies are useful and appropriate, what seemed more significant were some of the creative methods employed to repurpose strategies in relatively modest but more adaptive ways. We propose to refer to this as 'hacking' and discuss how planners and designers might successfully hack the planning system within its current (legal) boundaries. [ABSTRACT FROM AUTHOR]

Simple Summary: Nasopharyngeal carcinoma (NPC) is commonly treated using high-dose radiotherapy. Careful radiotherapy planning is crucial for the eradication of cancer cells while avoiding injuries to normal structures. This balance is often delicate given the complex anatomic location in which NPC is situated. This article highlights the considerations, practical pearls, and recent advances in the precise delivery of radiotherapy in NPC patients. Radiotherapy is the primary treatment modality for nasopharyngeal carcinoma (NPC). Successful curative treatment requires optimal radiotherapy planning and precise beam delivery that maximizes locoregional control while minimizing treatment-related side effects. In this article, we highlight considerations in target delineation, radiation dose, and the adoption of technological advances with the aim of optimizing the benefits of radiotherapy in NPC patients. [ABSTRACT FROM AUTHOR]

This document is an editorial titled "Resilient urban futures" published in the journal Frontiers in Sustainable Cities. The editorial discusses the challenges and opportunities for resilience in urban areas, focusing on the interdependencies of governance, community involvement, knowledge capacity building, and design integration. It emphasizes the need for interdisciplinary approaches and the role of local communities in adapting to climate change and promoting social equality. The editorial also introduces a research topic in the journal that explores urban transition and transformation through resilient design and planning, with four research papers highlighting perspectives on interdisciplinary collaborations and methodologies for strengthening urban resilience. The document concludes by emphasizing the importance of transdisciplinary collaboration, community empowerment, environmental education, and integrated design and planning for creating resilient, equitable, and sustainable cities. [Extracted from the article]

Simple Summary: A sub-region localized in the posterior right lung was significantly associated with the risk of grade ≥ 2 acute pulmonary toxicity in patients with locally advanced lung cancer treated with radiotherapy. Avoiding this sub-region with volumetric-arctherapy-based planification leads to a significant reduction of the predicted APT risk by reclassifying 43.2% (19/44) of the patients. Introduction: In patients treated with radiotherapy for locally advanced lung cancer, respect for dose constraints to organs at risk (OAR) insufficiently protects patients from acute pulmonary toxicity (APT), such toxicities being associated with a potential impact on the treatment's completion and the patient's quality of life. Dosimetric planning does not take into account regional lung functionality. An APT prediction model combining usual dosimetry features with the mean dose (DMeanPmap) received by a voxel-based volume (Pmap) localized in the posterior right lung has been previously developed. A DMeanPmap of ≥30.3 Gy or a predicted APT probability (ProbAPT) of ≥8% were associated with a higher risk of APT. In the present study, the authors aim to demonstrate the possibility of decreasing the DMeanPmap via a volumetric arctherapy (VMAT)-based adapted planning and evaluate the impact on the risk of APT. Methods: Among the 207 patients included in the initial study, only patients who presented with APT of ≥grade 2 and with a probability of APT ≥ 8% based on the prediction model were included. Dosimetry planning was optimized with a new constraint (DMeanPmap < 30.3 Gy) added to the usual constraints. The initial and optimized treatment plans were compared using the t-test for the independent variables and the non-parametric Mann–Whitney U test otherwise, regarding both doses to the OARs and PTV (Planning Target Volume) coverage. Conformity and heterogeneity indexes were also compared. The risk of APT was recalculated using the new dosimetric features and the APT prediction model. Results: Dosimetric optimization was considered successful for 27 out of the 44 included patients (61.4%), meaning the dosimetric constraint on the Pmap region was achieved without compromising the PTV coverage (p = 0.61). The optimization significantly decreased the median DMeanPmap from 28.8 Gy (CI95% 24.2–33.4) to 22.1 Gy (CI95% 18.3–26.0). When recomputing the risk of APT using the new dosimetric features, the optimization significantly reduced the risk of APT (p < 0.0001) by reclassifying 43.2% (19/44) of the patients. Conclusion: Our approach appears to be both easily implementable on a daily basis and efficient at reducing the risk of APT. Regional radiosensitivity should be considered in usual lung dose constraints, opening the possibility of new treatment strategies, such as dose escalation or innovative treatment associations. [ABSTRACT FROM AUTHOR]

Abstract Background Daily anatomical deviations may distort the dose distribution in carbon ion radiotherapy (CIRT), which may cause treatment failure. Therefore, this study aimed to perform re-planning to maintain the dose coverage in patients with pancreatic cancer with passive scattering CIRT. Methods Eight patients with pancreatic cancer and 95 daily computed tomography (CT) sets were examined. Two types of adaptive plans based on new range compensators (RCs) (AP-1) and initial RCs (AP-2) were generated. In AP-2, each beam was optimized by manually adjusting the range shifter thickness and spread-out Bragg peak size to make dose reduction by