Landscape Vulnerability Research Articles

Intersectionality shapes the access to various adaptive resources in climate-vulnerable contexts

Abstract Intersectional approaches are becoming essential to understanding the differential impacts of climate change and the heterogeneity of adaptive capacities. Varying factors of social and economic privileges and inequalities synergistically shape the local power structure, ultimately determining disproportionality and unequal access to adaptive resources. Using empirical data from coastal Bangladesh, which is part of the Ganges Delta, and one of the world’s -most climate-vulnerable regions, this study shows how religion, gender, and ethnicity intersect with patterns in (i) farm and non-farm incomes, (ii) land conflicts, (iii) the size of farms, and (iv) access to critical sources of weather information. The study highlights that multilayered identity, which is shaped by various structural determinants, including local power structure, can determine gendered dimensions of access to various adaptation resources. It also shows that if policymakers and development partners partially understand or do not understand the complex landscape of local vulnerability or unequal power structures including the adaptive capacity of the vulnerable populations, they would not be able to provide critical support in times of crisis. The concept of intersectionality is therefore critical in addressing adaptation and risk management challenges for regions like the Ganges Delta and other parts of the world, where people are struggling with similar social and environmental challenges.

The present and future of the Cancer Dependency Map.

Despite tremendous progress in the past decade, the complex and heterogeneous nature of cancer complicates efforts to identify new therapies and therapeutic combinations that achieve durable responses in most patients. Further advances in cancer therapy will rely, in part, on the development of targeted therapeutics matched with the genetic and molecular characteristics of cancer. The Cancer Dependency Map (DepMap) is a large-scale data repository and research platform, aiming to systematically reveal the landscape of cancer vulnerabilities in thousands of genetically and molecularly annotated cancer models. DepMap is used routinely by cancer researchers and translational scientists and has facilitated the identification of several novel and selective therapeutic strategies for multiple cancer types that are being tested in the clinic. However, it is also clear that the current version of DepMap is not yet comprehensive. In this Perspective, we review (1) the impact and current uses of DepMap, (2) the opportunities to enhance DepMap to overcome its current limitations, and (3) the ongoing efforts to further improve and expand DepMap.

A framework for target discovery in rare cancers.

While large-scale functional genetic screens have uncovered numerous cancer dependencies, rare cancers are poorly represented in such efforts and the landscape of dependencies in many rare cancers remains obscure. We performed genome-scale CRISPR knockout screens in an exemplar rare cancer, TFE3- translocation renal cell carcinoma (tRCC), revealing previously unknown tRCC-selective dependencies in pathways related to mitochondrial biogenesis, oxidative metabolism, and kidney lineage specification. To generalize to other rare cancers in which experimental models may not be readily available, we employed machine learning to infer gene dependencies in a tumor or cell line based on its transcriptional profile. By applying dependency prediction to alveolar soft part sarcoma (ASPS), a distinct rare cancer also driven by TFE3 translocations, we discovered and validated that MCL1 represents a dependency in ASPS but not tRCC. Finally, we applied our model to predict gene dependencies in tumors from the TCGA (11,373 tumors; 28 lineages) and multiple additional rare cancers (958 tumors across 16 types, including 13 distinct subtypes of kidney cancer), nominating potentially actionable vulnerabilities in several poorly-characterized cancer types. Our results couple unbiased functional genetic screening with a predictive model to establish a landscape of candidate vulnerabilities across cancers, including several rare cancers currently lacking in potential targets.

Evolution characteristics of landscape ecological risk patterns in Shangluo City in the Qinling Mountains, China

Landscape ecological risk assessment (LERA) is the basis of regional landscape pattern optimization, and a tool that can help achieve a win-win situation between regional development and ecological protection. The landscape ecological risk (LER) of the southern end of the Qinling Mountains, China exhibited an increasing trend after the year 2000, but the degree of increase and the spatial and temporal dynamics were not clear, limiting the formulation and implementation of landscape optimization measures in the area. Here, we constructed a landscape pattern risk index ERI by combining data on landscape disturbance and landscape vulnerability from land use information for Shangluo City for years 2000, 2005, 2010, 2015, and 2020; then, we calculated a LER level and its spatial and temporal dynamics for Shangluo City for years 2000 to 2020. Moran’s I and LISA indices were used to characterize the spatial correlation of ERI in Shangluo City. We found that Shangluo had a large proportion of medium-risk areas, and its LER shifted from medium-high, high in year 2000 to medium risk, medium-low and low risk in year 2020, and LER of Shangluo was clustered in space but the degree of clustering decreased in the past 20 years. We conclude that the development strategy of Shangluo should depend on providing a sustainably-developed environment.

Uncovering Hidden Risks in IoT devices: A Post-Pandemic National Study of SOHO Wi-Fi Router Security

This study thoroughly analyzes the cybersecurity status of Small Office/Home Office (SOHO) Wi-Fi routers. These routers are crucial but frequently overlooked elements in network infrastructure, particularly in light of the impact of the COVID-19 pandemic on network security. The pandemic has led to shifts in network usage patterns, blurring traditional security perimeters and extending them into private residences, creating additional points of vulnerability in urban environments. Our nationwide research evaluated an extensive dataset of router brands and models currently used at scale. We measured the prevalence of known vulnerabilities, assessed the currency of userspace and kernel software versions, and compared the security robustness of proprietary firmware against open-source alternatives. Our findings reveal a concerning landscape of widespread vulnerabilities and outdated software components, posing latent risks to end-users. The results indicate a predominance of Linux on MIPS and ARM architectures, with an average delay of 5 to 10 years between the release of the kernel and the implementation of the most recent firmware versions. As a result, we observed an average of 1344 and 72 vulnerabilities in the kernel and applications. One significant discovery from our research is that replacing the manufacturer's original firmware with open-source alternatives, such as DD-WRT, OpenWrt, and Tomato, can substantially enhance the security of the software stack. This enhancement results in improvements of up to 97% in the case of binaries and 98.42% in the kernel. Our research helps increase cybersecurity awareness by pinpointing critical home network environment weaknesses and alerting the need for more rigorous security practices in producing and maintaining SOHO routers. This investigation also allowed the report of a new remote code execution vulnerability (disclosed in CVE-2022-46552).

Constructing Ubudehe? Farmers’ perceptions of drought impacts and resilience capacities in Bugesera, Rwanda

Purpose This paper analyses Rwandan farmers’ perceptions of historical drivers of landscape vulnerability (past), current livelihood assets (present) and existing or potential capacities (future) to increase resilience to drought. The specific focus is on linking experiences from the past and present with ideas for a drought-resilient future. It explores how farmers' perceptions of past droughts and future visioning can contribute to rural development policy and multi-level collaborations. Design/methodology/approach This study was conducted in Bugesera, a drought-prone district in south-eastern Rwanda. Empirical data was collected through participatory observation, semi-structured interviews and focus groups. The analytical points of departure are based on sustainable landscapes and livelihood approaches, combining spatial and temporal perspectives on challenges and opportunities identified by farmers’ communities in addressing droughts. Findings All respondents had a high awareness of the impact of droughts. Perceived drivers of landscape change include historical climate events, such as droughts and floods, immigration and agricultural expansion, which have led to demographic pressure on land, deforestation and infringement on natural resources. Factors enhancing resilience capacities include access to diversified sources of livelihood, knowledge of appropriate irrigation techniques and availability of safety nets and credits. Furthermore, farmers identified collaborative opportunities as important for resilience capacity, including peer learning, and sharing best practices through knowledge exchange and on-field training. In addition, farmers brought up the need for innovative institutions that can facilitate access to markets and enable collaboration between different agricultural sectors. Originality/value This study analyses farmers’ perceptions of resilience capacities to droughts through a spatiotemporal lens of past droughts, present capital and future challenges by linking scales, knowledge and human–environment nexus. This paper contributes to the knowledge of climate adaptation in Rwanda and to discussions about smallholder farming in the literature on climate change adaptation.

Environmental Fragility in Commercial Forest Plantations Aiming at Sustainable Management

Objective: The objective of this study is to investigate the environmental fragility of two landscapes in which there is a predominance of commercial forest plantations, with the aim of analyzing this fragility through multicriterial evaluation, focusing on the planning of forest roads. Theoretical Framework: The theory of environmental fragility, multi-criteria evaluation methods, and principles of landscape management stand out, providing a solid basis for understanding the context of the investigation. These frameworks are crucial for analyzing the impact of forest roads on environmental variables such as water dynamics, sediment production, and soil erodibility. The integration of these theories allows for a comprehensive assessment of environmental fragility, essential for effective forest planning and road maintenance in forested areas Method: The methodology adopted involves a multi-criteria evaluation approach to assess environmental fragility in forest landscapes. Key criteria, including slope, distance from water bodies, soil erodibility, and topographic humidity, were integrated to create fragility maps. Data were collected through geographical and environmental analysis, processed with spatial analysis tools, and supplemented by principal component analysis to identify influential criteria. This approach enabled a detailed assessment of forest roads' environmental impact, supporting informed decisions in road planning and landscape management. Results and Discussion: The results revealed notable variations in environmental fragility. The analysis of forest roads highlighted their varying impact on environmental fragility. These results are framed within the context of environmental fragility and multi-criteria evaluation, emphasizing the role of criteria such as slope, proximity to water bodies, soil erodibility, and topographic humidity in assessing landscape degradation. The study underscores the need for careful forest road planning to mitigate environmental impacts and promotes the use of comprehensive evaluation methods in sustainable landscape management. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of forest management and environmental conservation. These implications could encompass forest road planning, sustainable landscape management, and the development of environmental policies aimed at mitigating the impact of infrastructure on natural ecosystems.The study's findings emphasize the need for incorporating multi-criteria evaluation methods into forest planning processes to identify and mitigate areas of high environmental fragility. This approach can guide decision-makers in prioritizing areas for road maintenance, rehabilitation, or even rerouting to minimize ecological damage. Furthermore, the research underscores the importance of integrating environmental fragility assessments into broader forest management strategies, enhancing the sustainability of commercial forestry operations while preserving essential ecosystem services. Originality/Value: This study contributes to the literature by introducing an innovative application of multi-criteria evaluation in assessing environmental fragility within forest landscapes, specifically in the context of forest road planning. The research combines various environmental criteria into a comprehensive fragility map, offering a nuanced understanding of landscape vulnerability that is less commonly addressed in existing studies. Notably, this methodology focused on forest roads has not been previously explored in the literature, highlighting the unique contribution of this research to the field.The relevance and value of this research are evidenced by its potential to influence forest management practices, particularly in the sustainable planning and maintenance of forest roads.

Landscape ecological risk evaluation coupled with ecosystem service improvement and its spatial heterogeneity analysis: a case study of the Yellow River Source Area

The ecological environment of the Yellow River Source Area (YRSA) is crucial to the Qinghai-Tibet Plateau, and its ecological risk management is important for the ecological protection and sustainable development of the Qinghai-Tibet Plateau. this study improves the traditional evaluation method of landscape ecological risk(LER) based on ecosystem services and detects its spatial heterogeneity by using Geodetector. The study results are as follows: (1) The temporal distribution of LER in the YRSA is similar to its landscape vulnerability. In the past 20 years, the areas of its high, medium-high, medium, and medium-low ecological risk areas have been converted to low ecological risk areas to varying degrees. (2) Overall, the spatial difference in LER in the YRSA is significant, mainly dominated by HH and HL clustering. Meanwhile, the Moran’I index of the LER Index decreases year by year, indicating that the spatial aggregation of the LER decreases and the spatial autocorrelation weakens year by year. (3) Climatic factors have the most significant influence on the ecological risk of the landscape in the YRSA, followed by topographic factors and anthropogenic factors.

Contributions of science–society interactions to spur sustainability transformations in vulnerable landscapes

Contributions of science–society interactions to spur sustainability transformations in vulnerable landscapes

Securing Container Images through Automated Vulnerability Detection in Shift-Left CI/CD Pipelines

Integrating shift-left security practices and automated vulnerability detection in container images is imperative for modern software development, given the dynamics and vulnerability landscape. This crucial methodology emphasizes security from the initial stages of integration in container-based environments like Docker and Kubernetes. The paper examines containerization security challenges, including image vulnerabilities, insecure configurations, runtime risks, weak orchestration security, and supply chain weaknesses, while stressing compliance with regulatory rules. It explores how this automated approach leverages vulnerability detection methods integrated into Continuous Integration/Continuous Deployment (CI/CD) pipelines through static and dynamic analyses, vulnerability databases, and policy-enforcement mechanisms. Beyond identifying vulnerabilities in CI/CD pipelines, the paper outlines methods to avoid policy violations, mitigate vulnerable images, and prevent recurring practices. Importantly, it underscores the continuous enforcement and remediation of policies and security standards. Security teams must invest efforts in developing policies, automated executions, and remediation procedures, fostering cross-departmental collaboration. In essence, this proactive stance aims to enhance software security, reduce risks, and improve adherence in containerized ecosystems, making it an indispensable component of modern software development.

Estimating the vulnerability of industrial network infrastructure in Central and Eastern Europe

Industrial infrastructure has suffered an unprecedented number of attacks in Central and Eastern Europe (CEE). This situation can be attributed to many geopolitical factors, including hybrid military conflicts and criminal activity. Industrial networks belonging to the countries that were once under Soviet influence suffer from an elevated risk of cyberattacks. The goal of this work is to propose an easy way to estimate the vulnerabilities of industrial networks to cyber threats on a national level. Since analysis of the industrial vulnerability landscape is difficult, this study proposes an assessment based on the popularity of vulnerable technologies—VPc. This metric is composed of search volume data on keywords related to industrial network technologies and reported security vulnerabilities associated with these words. Data on 116 keywords was analysed and a country-specific VPc index was calculated for twenty states in CEE. The analysis of the popularity of industrial technologies and vendors in CEE reveals interesting information about the industrial security and vulnerability landscape. The results show that some countries (e.g. Estonia) have more resilient industrial infrastructure than others (e.g. Belarus). The results presented in this study are not in conflict with other data and estimation attempts, including the National Cyber Security Index (NCSI). As new vulnerabilities are noted every day, the industrial security landscape changes rapidly. Therefore, a new easy-to-use metric (VPc) can be successfully used for general estimations. This work shows that the VPc score agrees with other estimates and analyses, but as with any other general estimation tool, it must be used with caution.

Exploring the spatial and temporal evolution of landscape ecological risks under tourism disturbance: A case study of the Min River Basin, China

Numerous ecological issues will arise from the expansion of tourism-related infrastructure and activities, potentially having a major effect on the ecosystem. However, its impact on landscape ecological risk (LER) is still poorly understood. Taking the Min River Basin as an example, an improved LER evaluation method was adopted in this study, which uses landscape disturbance based on landscape pattern and incorporates ecosystem services (ESs) represent landscape vulnerability. On this basis, the impacts of tourism-related infrastructure and activities on ecology environment were comprehensively considered, and buffer zone analysis, scenario analysis, response index (RI), and the bivariate Moran’s I approaches were applied to identify the spatio-temporal evolution characteristics of LER under tourism interference. The results show that: (1) The Min River Basin’s LER from 2000 to 2020 demonstrates a trend of gradually decreased, primarily in the middle and low risk areas. Most of the areas where scenic spots and roads are located are high risk areas, suggesting that tourism disturbances negatively affect LER. (2) There is a spatial gradient effect associated with the influence of tourism infrastructure on LER, and the impact degree varies throughout different tourism infrastructure. (3) The difference of scenic spots causes diverse degrees of LER. Through comparison, it is found that the LER of high-grade and cultural scenic spots is larger than that of low-grade and natural scenic spots. The quantitative results of the RI show that the values inside the influence zones of scenic spots and roads are 5 times and 9 times more than the values outside, respectively. This suggests that tourism infrastructure increases LER. (4)There is a spatial correlation between LER and tourism activities intensity. In order to offer a scientific reference for balancing local tourism development and ecological environmental conservation, this study develops a more thorough and rigorous research framework of the impact of tourism on LER.

Undoing business: revealing critical narratives in an edge-city business park through nature-based auto-photography

Business parks are a ubiquitous feature of city-edge development. They have attracted attention for their lack of sustainability, spurring interest in how they can be reconfigured or reimagined in the face of ecological collapse and social fragmentation. Inspired by calls to notice everyday practices at the city edge (Tzaninis et al. 2021. “Moving Urban Political Ecology Beyond the ‘Urbanization of Nature’.” Progress in Human Geography 45 (2): 229–252; Tsing 2015. The Mushroom at the End of the World: On the Possibility of Life in Capitalist Ruins. Princeton: Princeton University Press; Gandy 2022a. “Ghosts and Monsters: Reconstructing Nature on the Site of the Berlin Wall.” Transactions of the Institute of British Geographers 47: 1120–1136.) and drawing on data from a participant-led photography exercise at a suburban business park in the north-east of England, this article explores how workers employed at businesses on the park engage with and value its natural assets. We set out from Tzaninis et al.’s (2021) contention that the dominant framing of suburbia as ‘non-place’ or ‘no man’s land’ has the effect of denying the many intriguing practices unfolding at the city’s edge. Resonating with Tsing (2015), we highlight the significance of everyday interaction with nature in an ecologically vulnerable landscape as a creative, open-ended and, potentially, hopeful process. Focused on denizens of the business park, our data draws attention to the possibilities and potentialities of more-than-human encounters, the feeling of tranquillity generated by green spaces, and the sense of freedom that derives from bodily movement in a natural setting. These open-ended practices are distinct from, and ‘other than’, the dominant way of doing business in the park. Such encounters, drawn out by auto-photography, foment a radical connectedness with nature through which a powerful sense of custodianship and responsibility can find expression.

Climate-informed flood risk mapping using a GAN-based approach (ExGAN)

This study develops a class of robust models for flood risk mapping in highly vulnerable regions by focusing on accurately depicting extreme precipitation patterns aligned with regional climates. By implementing sophisticated hydrodynamics modeling and advanced probabilistic approaches, the present work underscores the efficacy of physical-based methodologies in the flood risk assessment. We propose a machine learning based ExGAN to address the challenge of synthesizing extreme precipitation scenarios which faithfully capture the nuances of local climatology. It is expected that through refined temporal disaggregation, the ExGAN approach exhibits exceptional proficiency in replicating a diverse spectrum of extreme precipitation patterns specific to the vulnerable region under scrutiny. Therefore, using these synthesized scenarios as inputs in a meticulously calibrated hydrological model would enable a comprehensive and detailed flood risk mapping exercise. To demonstrate the robustness of the developed mode, we perform a rigorous testing and validation within the highly susceptible Martil river basin, situated in the northern Mediterranean region of Morocco. The obtained results confirm that extending return periods would provide invaluable insights into the expanding geographical expanse of at-risk areas, clarifying the evolving landscape of vulnerability rather than merely amplifying inherent risk levels. Comparisons against the conventional Monte-Carlo sampling are also carried out in this study and the obtained results highlight significant overestimations within the latter, emphasizing the imperative need to account for diverse uncertainties beyond the basic sampling strategies within the realm of hydrodynamic modeling.

Data blanks by design: Intellectual property and restrictions on genetic diversity assessments of the maize standing crop in the USA Upper Midwest

Societal Impact StatementAll US commercial maize (Zea mays) is a single race, “Corn Belt Dent,” and its genetic base has been in decline for at least 40 years. Independent genotyping can only be conducted after patent and licensing restrictions have expired, a period of 20 years. These restrictions also impede a molecular based assessment of the standing crop by the United States Department of Agriculture (USDA) as recommended by experts. Data blanks about landscape vulnerability put farmers at risk of crop failure and the public at risk of food insecurity. Understanding maize diversity experts' perspectives and analysis helps describe the contours of these data blanks and inform policy recommendations.Summary Recommendations by the Maize Crop Germplasm Committee to the United States Department of Agriculture (USDA) for a molecular based vulnerability assessment on the US standing maize (Zea mays) crop have not been acted on because of intellectual property and licensing restrictions. This research explores maize diversity experts' access to data and perceptions and analysis of the standing crop. The data come from semi‐structured interviews conducted with 44 maize diversity experts in the public and private sectors. Experts explain that genetic data blanks restrict non‐industry research, describe public sector concerns that standing diversity is narrow(ing), and find historic sources of pedigree data in Plant Variety Protection and patent records are no longer reliable. Some interviewees perceive that industry monitoring of standing diversity is in their best financial interest. Industry participants describe concentration in US maize allows them to control diversity over time, while public researchers discuss efficiency of scale narrowing genetic diversity and global concentration spreading this trend. Knowledge gaps about genetic diversity in US commercial maize are designed through patents, contracts, non‐disclosure agreements, and confidentiality agreements by patent holders who do not want their inbred lines genotyped by competitors. This restricts research and knowledge flow about genetic information into public networks. The Maize Crop Germplasm Committee is a node for knowledge flow; however, the lack of mechanisms for action suggests it is performative. We recommend all protections used on seed include exemptions for research, breeding, and seed saving; an independent assessment of how industry monitors standing diversity; and a molecular analysis of the standing crop conducted by the USDA.

Abstract IA011: Towards mapping the landscape of cancer vulnerabilities

Abstract I will introduce the Cancer Dependency Map (DepMap) project. This project aims to build a resource to identify the landscape of cancer vulnerabilities by linking molecular alterations of tumors to gene dependencies or drug sensitivities. This resource is being used by scientists around the world and has made significant contributions to basic and translational cancer research. I will describe how we are building DepMap and the multiple components it requires. Additionally, I will discuss ongoing projects to expand DepMap, including screening next-generation models. I will also present how to identify potential therapeutic targets using DepMap data and the emerging types of targets. Lastly, I will highlight a recently identified synthetic lethal target in the ribosome rescue pathway in molecularly defined patient populations, demonstrating the power of DepMap in identifying such targets. Citation Format: Francisca Vazquez. Towards mapping the landscape of cancer vulnerabilities [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA011.

Abstract IA001: Exploiting pathway activation as a new form of synthetic lethality

Abstract Targeting activated oncogenes is an effective treatment strategy across many cancers now including therapeutics targeting KRAS. Genetic events including DNA damage deficiencies and tumor suppressor mutations require alternative strategies and the concept of synthetic lethality has been applied to these alterations. PARPi inhibitors were a founding member of this class of therapeutics demonstrating enhanced activity in the setting of BRCA-deficiency. By applying large-scale loss-of-function approaches1 we and other discovered the vulnerability to PRMT5 and WRN inhibition imposed by co-deletions of MTAP and CDKN2A, and the MSI+ genotype respectively2,3. Such inhibitors are now in clinical trials. To explore the potential for paralogous genes to act as synthetic lethal gene pairs we enacted dual knockout screens. These early efforts led to the discovery of DUSP4/6 paralog dependence in the setting of BRAF and NRAS mutations in melanoma4. Intriguingly the loss of DUSP4/6 impaired cancer cell viability through the increased activation of ERK highlighting the susceptibility of cancers to pathway activation in addition to the more common sensitivity to pathway inhibition. This inappropriate activation of the ERK signaling pathway, the conflict between EGFR and KRAS activation, the synthetic lethality enacted by TRIM8 knockouts, and the effects of AR agonists on prostate cancer viability, points to a wider than expected vulnerability of cancer to inappropriate gene activation. To systematically identify context-specific gene activation induced lethalities in cancer, we developed methods for enacting gain-of-function perturbations across ∼500 barcoded cancer cell lines. With this approach, we queried the pan-cancer vulnerability landscape upon activating 10 key cancer pathway revealing activation dependencies in MAPK and PI3K pathways. Notably, we discovered novel pathway hyperactivation dependencies in subsets of APC-mutant colorectal cancers where further activation of the WNT pathway by APC knockdown or direct β-catenin overexpression led to robust antitumor effects in xenograft and patient-derived organoid models. These latter discoveries paradoxically point to the residual activity of the APC ubiquitin-ligase complex as a target in APC-mutant CRC5. 1. McDonald, E. R., 3rd et al. Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep RNAi Screening. Cell 170, 577-592.e10 (2017). 2. Mavrakis, K. J. et al. Disordered methionine metabolism in MTAP/CDKN2A-deleted cancers leads to dependence on PRMT5. Science 351, 1208–1213 (2016). 3. Chan, E. M. et al. WRN helicase is a synthetic lethal target in microsatellite unstable cancers. Nature 568, 551–556 (2019). 4. Ito, T. et al. Paralog knockout profiling identifies DUSP4 and DUSP6 as a digenic dependence in MAPK pathway-driven cancers. Nat. Genet. 53, 1664–1672 (2021). 5. Chang, L. et al. Systematic profiling of conditional pathway activation identifies contextdependent synthetic lethalities. Nat. Genet. 55, 1709–1720 (2023). Citation Format: William R. Sellers. Exploiting pathway activation as a new form of synthetic lethality [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA001.

Analysis of landscape pattern vulnerability in Dasi river basin at the optimal scale

Since the reform and opening up in 1978, the Dasi River Basin within Jinan’s startup area from replacing old growth drivers with new ones (startup area) has experienced rapid urbanization and industrialization, and the landscape pattern has changed significantly, resulting in a series of eco-environmental problems. In order to more accurately identify the vulnerable areas of landscape pattern, understand their cause mechanism and changing laws, and provide a theoretical basis for the implementation of sustainable landscape pattern planning and management in the region. Four Landsat images of 2002, 2009, 2015 and 2020 were taken as data sources, and the optimal granularity of landscape pattern analysis was determined from the perspective of landscape level and class level by using the coefficient of variation method, granularity effect curve and information loss model, and the optimal amplitude was determined by using the grid method and semi-variance function. Then, the landscape vulnerability assessment model was constructed based on the optimal scale, and its spatiotemporal evolution characteristics and spatial autocorrelation were analyzed. The result showed that: (1) The optimal granularity of landscape pattern analysis in this study area was 80 m, and the optimal amplitude was 350 × 350 m. (2) During 2002–2020, the overall vulnerability of landscape pattern in the southern part of the study area showed an increasing trend, while that in the middle and northern parts showed a decreasing trend. (3) The mean values of the vulnerability index of the overall landscape pattern in 2002, 2009, 2015 and 2020 were 0.1479, 0.1483, 0.1562 and 0.1625, respectively, showing an increasing trend year by year. In terms of land use, during 2002–2020, the average vulnerability indices of forestland and built up land increased by 23.18% and 21.43%, respectively, followed by water body and bare land, increased by 12.18% and 9.52%, respectively, while the changes of cropland and grassland were relatively small, increasing by 5.36% and 5.65%, respectively. (4) During 2002–2020, the landscape pattern vulnerability showed a significant spatial positive correlation in terms of spatial distribution. The Low-Low areas were generally transferred from the southeastern and midwestern to the middle and northern, and the High–High areas were mainly transferred from the middle to the southern. Overall, the degree of the spatial agglomeration of the landscape pattern vulnerability showed an increasing trend.

Securing the Industrial Backbone: Cybersecurity Threats, Vulnerabilities, and Mitigation Strategies in Control and Automation Systems

Industrial Control and Automation Systems are the invisible workhorses of modern industry, managing critical infrastructure and manufacturing processes. The increasing convert of IT and OT networks has exposed ICAS to a growing range of cybersecurity threats. This paper explores the current landscape of cybersecurity threats and vulnerabilities plaguing ICAS. It delves into the technical aspects of these vulnerabilities, ranging from network weaknesses to human error. Additionally, the paper proposes a comprehensive set of mitigation strategies that can be implemented to bolster the security posture of ICAS. These strategies encompass network segmentation, access control, vulnerability management, incident response planning, and ongoing security awareness training. Finally, the paper highlights the importance of adhering to industry security standards and fostering a culture of cybersecurity within organizations.

Integrating ecosystem service value in the disclosure of landscape ecological risk changes: a case study in Yangtze River Economic Belt, China

Urban expansion and inappropriate land uses have caused a decline in the regional ecosystem services capacity, which is contrary to United Nations’ Sustainable Development Goal (SDG) 15 aiming to protect and promote sustainable use of terrestrial ecosystems. Landscape ecological risk (LER) visually depicts the disturbances to ecosystem services and environmental shifts resulting from human activities. Consideration of ecosystem services in LER assessment has not been sufficiently researched. Here, we employed ecosystem service values (ESV) to define landscape vulnerability, and adopted an enhanced risk assessment framework, amalgamating landscape patterns and ecosystem processes, to evaluate the spatial-temporal shifts in ESV and LER in the Yangtze River Economic Belt (YREB) from 2000 to 2020. We attempted to analyze the relationship between LER and anthropogenic disturbances. The results showed that over the past 20 years, the general trend revealed a diminishing high-risk area, while medium and low-risk regions expanded. Notably, the urban agglomeration of the YREB experienced a marked surge in risk. Regarding migration direction, the low-risk category has expanded in the east–west direction, while the medium and high-risk categories have shown inward contraction mainly in the north–south direction. The findings highlight the complex changes between ecological processes and LER under anthropogenic disturbances, and can serve as a guide for sustainable risk management and the development of ecological security patterns.