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Impact of cancer diagnosis on life expectancy by area-level socioeconomic groups in New South Wales, Australia: a population-based study

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Cancer Biology & Medicine 2024年第8期 692-702页

作者： Md Mijanur Rahman Michael David David Goldsbury Karen Canfell Kou Kou Paramita Dasgupta Peter Baade Xue Qin Yu The Daffodil Centre The University of Sydney A Joint Venture with Cancer Council NSW School of Medicine and Dentistry Griffith University Cancer council Queensland

Objective: Improvement in cancer survival over recent decades has not been accompanied by a narrowing of socioeconomic disparities. This study aimed to quantify the loss of life expectancy(LOLE) resulting from a cancer diagnosis and examine disparities in LOLE based on area-level socioeconomic status(SES).Methods: Data were collected for all people between 50 and 89 years of age who were diagnosed with cancer, registered in the NSW Cancer Registry between 2001 and 2019, and underwent mortality follow-up evaluations until December 2020. Flexible parametric survival models were fitted to estimate the LOLE by gender and area-level SES for 12 common ***: Of 422,680 people with cancer, 24% and 18% lived in the most and least disadvantaged areas, respectively. Patients from the most disadvantaged areas had a significantly greater average LOLE than patients from the least disadvantaged areas for cancers with high survival rates, including prostate [2.9 years(95% CI: 2.5±3.2 years) vs. 1.6 years(95% CI: 1.3±1.9 years)] and breast cancer [1.6 years(95% CI: 1.4±1.8 years) vs. 1.2 years(95% CI: 1.0±1.4 years)]. The highest average LOLE occurred in males residing in the most disadvantaged areas with pancreatic [16.5 years(95% CI: 16.1±16.8 years) vs. 16.2 years(95% CI: 15.7±16.7 years)] and liver cancer [15.5 years(95% CI: 15.0±16.0 years) vs. 14.7 years(95% CI: 14.0±15.5 years)]. Females residing in the least disadvantaged areas with thyroid cancer [0.9 years(95% CI: 0.4±1.4 years) vs. 0.6 years(95% CI: 0.2±1.0 years)] or melanoma [0.9 years(95% CI: 0.8±1.1 years) vs. 0.7 years(95% CI: 0.5±0.8 years)] had the lowest average ***: Patients from the most disadvantaged areas had the highest LOLE with SES-based differences greatest for patients diagnosed with cancer at an early stage or cancers with higher survival rates, suggesting the need to prioritise early detection and reduce treatment-related barriers and survivorship challenges to improve life expec

关键词： Cancer diagnosis area-level socioeconomic status flexible parametric model life expectancy loss of life expectancy

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Multiple myeloma survival in New South Wales, Australia, by treatment era to 2020

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Cancer Biology & Medicine 2024年第8期 703-711页

作者： Eleonora Feletto Qingwei Luo Anna Kelly Marianne Weber David Goldsbury Katherine Barron Karen Canfell Xue Qin Yu The Daffodil Centre The University of Sydney A Joint Venture with Cancer Council NSW

Objective: Australia has relatively high multiple myeloma(MM) incidence and mortality rates. Advancements in MM treatment over recent decades have driven improvements in MM survival in high-income countries; however, reporting in Australia is limited. We investigated temporal trends in population-wide MM survival across 3 periods of treatment advancements in New South Wales(NSW), ***: Individuals with an MM diagnosis in the NSW Cancer Registry between 1985 and 2015 with vital follow-up to 2020, were categorized into 3 previously defined treatment eras according to their diagnosis date(1985±1995, chemotherapy only; 1996±2007, autologous stem cell transplantation; and 2008±2015, novel agents including proteasome inhibitors and immunomodulatory drugs). Both relative survival and cause-specific survival according to Fine and Gray's competing risks cumulative incidence function were calculated by treatment era and age at ***: Overall, 11,591 individuals were included in the study, with a median age of 70 years at diagnosis. Five-year relative survival improved over the 36-year(1985±2020) study period(31.0% in 1985±1995; 41.9% in 1996±2007; and 56.1% in 2008±2015). For individuals diagnosed before 70 years of age, the 5-year relative survival nearly doubled, from 36.5% in 1985±1995 to 68.5% in 2008±2015. Improvements for those > 70 years of age were less pronounced between 1985±1995 and 1996±2007; however, significant improvements were observed for those diagnosed in 2008±2015. Similar overall and age-specific patterns were observed for causespecific survival. After adjustment for gender and age at diagnosis, treatment era was strongly associated with both relative and cause-specific survival(P al of individuals with MM is improving in Australia with treatment advances. However, older age groups continue to experience poor survival outcomes with only modest improvements over time. Given the increasing prevalence of

关键词： Australia Multiple myeloma cancer epidemiology competing risk analysis survival analysis

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Economic Risk Assessment of Future Debris Flows by Machine Learning Method

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International Journal of Disaster Risk Science 2024年第1期15卷 149-164页

作者： Chenchen Qiu Lijun Su alessandro Pasuto Giulia Bossi Xueyu Geng School of Engineering University of WarwickCoventry CV47ALUK Key Laboratory of Mountain Hazards and Earth Surface Process Institute of Mountain Hazards and EnvironmentChinese Academy of SciencesChengdu 610041China Research Institute for Geo-Hydrological Protection(IRPI-CNR) National Research Council of ItalyPadova 35127Italy

A reliable economic risk map is critical for effective debris-flow ***,the uncertainties surrounding future scenarios in debris-flow frequency and magnitude restrict its *** estimate the economic risks caused by future debris flows,a machine learning-based method was proposed to generate an economic risk map by multiplying a debris-flow hazard map and an economic vulnerability *** selected the Gyirong Zangbo Basin as the study area because frequent severe debris flows impact the area every *** debris-flow hazard map was developed through the multiplication of the annual probability of spatial impact,temporal probability,and annual *** employed a hybrid machine learning model-certainty factor-genetic algorithm-support vector classification-to calculate ***,a Poisson model was applied for temporal probabilities,while the determination of annual probability of spatial impact relied on statistical ***,four major elements at risk were selected for the generation of an economic loss map:roads,vegetation-covered land,residential buildings,and *** economic loss of elements at risk was calculated based on physical vulnerabilities and their economic ***,we proposed a physical vulnerability matrix for residential buildings,factoring in impact pressure on buildings and their horizontal distance and vertical distance to debrisflow *** this context,an ensemble model(XGBoost) was used to predict debris-flow volumes to calculate impact pressures on *** results show that residential buildings occupy 76.7% of the total economic risk,while roadcovered areas contribute approximately 6.85%.Vegetation-covered land and farmland collectively represent 16.45% of the entire *** findings can provide a scientific support for the effective mitigation of future debris flows.

关键词： Economic risk Future debris fows Gyirong Zangbo Basin Machine learning model Physical vulnerability matrix Southwest Tibet,China

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Potential of GSHP coupled with PV systems for retrofitting urban areas in different European climates based on archetypes definition

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Energy and Built Environment 2024年第3期5卷 374-392页

作者： Laura Carnieletto Antonino Di Bella Davide Quaggiotto Giuseppe Emmi Adriana Bernardi Michele De Carli Department of Industrial Engineering–DII University of Padovavia Venezia 1PadovaItaly university of Ferrara Italy CNR–National Research council PadovaItaly

According to the recent policies regarding energy use in buildings and the need of retrofit strategies,the aim of this work is to support policies concerning the installation of ground source heat exchangers in urban and historical areas,raising the awareness on the potential energy saving achievable with optimal sizing and limited impact on the urban *** have been developed distinguishing among existing and historic buildings,focusing on single-family terrace houses,which are the typical residential buildings in European historic centres.A methodology for the optimal sizing of ground source heat pumps,eventually considering dual-source system or air system has been developed combining simulations of a photovoltaic system to estimate the self-sufficiency and the self-consumption for five orientations of the *** results have been obtained for warm cli-mates,with negligible heating energy demand and possibly free cooling systems rather than traditional cooling systems needed in *** temperature was acceptable despite unbalanced energy *** proper inclination,photovoltaic systems could provide up to 40%of self-sufficiency share also in northern *** energy-economic analysis was carried out obtaining a variety of cases representing a general overview of the European building stock and the potential benefits achievable in terms of renewable energy share,energy savings and economic investments needed to be extended to simulations at urban scale.

关键词： Energy use database Ground source heat exchangers Urban context Energy retrofit Integrated renewables

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Influence of edaphic factors on distribution and condition of Himalayan silver birch(Betula utilis ***)communities in the northwestern Indian Himalayas

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Journal of Mountain Science 2024年第2期21卷 590-606页

作者： Khashti DASILA Renu RAWal Tanay BARMAN Sher Singh SAMANT Anita PANDEY Veena PANDE G.B.Pant National Institute of Himalayan Environment Almora 263643India Centre of Excellence on Sustainable Land Management Indian Council of Forestry Research and EducationDehradun 248006India Uttarakhand State council for Science&Technology Dehradun 248015India Department of Biotechnology Graphic Era(Deemed to be University)Dehradun 248002India Department of Biotechnology Kumaun UniversityNainital 263136India

The basic concept of phytosociology is crucial for the assessment of species composition and dynamic ecological succession of forests supporting ecological services,functions,disturbance,and resilience that lead to the development of integrated areas such as ecological niche modeling and contribute to identifying the valuable bio-indicators which can be used in framing conservation and management *** is one of the most dominant tree species of treeline ecotone in the Himalayan *** species is also considered as indicator species for monitoring the past and recent climate change *** current study was carried out in the natural populations of *** from the sub-alpine zone of North-western Indian *** birch dominated forest harbors a total of 305 plant species comprising Angiosperms(51 families,160 genera and 277 species),Gymnosperms(03 families,05 genera and 07 species)and Pteridophytes(07 families,11 genera and 21 species)with Asteraceae,Ranunculaceae and Rosaceae as dominant *** forests are found dominant in shady moist habitat and North West *** characteristics,anthropogenic and developmental activities affect the population structure of *** and associated ***,the species has fair regeneration status in the study *** acidic nature of soil pH and spatial variation in edaphic characteristics may be due to geographical differences,rooting patterns and litter accumulation of below and above-ground *** estimation of a representative population of *** from each site showed that TAGBD,TCD and TBD were found maximum in ST3(Hamta Pass II site).The CCA analysis determined that environmental variables such as altitude,organic matter,available phosphorous,organic carbon,available nitrogen,and electrical conductivity played a significant role in determining tree species composition and distribution in *** dominated forests.

关键词： Species composition Indicator species Biomass North-western Indian Himalaya Regeneration Environmental variables

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Multi-Period Resilient Model for VSC-Based AC-DC HDS Considering Public-Safety Power Shutoff to Mitigate Wildfires

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 821-833页

作者： Zekai Wang Tao Ding Xiaosheng Zhang Chenggang Mu Pengwei Du Fangxing Li School of Electrical Engineering Xi'an Jiaotong UniversityXi'an 710049China Electric Reliability council of Texas AustinTX76574 USA Department of Electrical Engineering and Computer Science The University of TennesseeKnoxville(UTK)TN37996USA

This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shutoff (PSPS) strategy is applied to actively cut some vulnerable lines which may easily cause wildfires, and reinforce some lines that are connected to critical loads. To mitigate load shedding caused by active line disconnection in the PSPS strategy, network reconfiguration is applied before the wildfire occurrence. During the restoration period, repair crews (RCs) repair faulted lines, and network reconfiguration is also taken into consideration in the recovery strategy to pick up critical loads. Since there exists possible errors in the wildfire prediction, several different scenarios of wildfire occurrence have been taken into consideration, leading to the proposition of a stochastic multi-period resilient model for the VSC-based AC-DC HDS. To accelerate the computational performance, a progressive hedging algorithm has been applied to solve the stochastic model which can be written as a mixed-integer linear program. The proposed model is verified on a 106-bus AC-DC HDS under wildfire conditions, and the result shows the proposed model not only can improve the system resilience but also accelerate computational speed.

关键词： AC-DC hybrid distribution system restoration network reconfiguration progressive hedging public safety power shutoffs strategy resilience

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Smart mid-infrared metasurface microspectrometer gas sensing system

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Microsystems & Nanoengineering 2024年第3期10卷 273-281页

作者： Jiajun Meng Sivacarendran Balendhran Ylias Sabri Suresh K.Bhargava Kenneth B.Crozier School of Physics University of MelbourneVictoriaAustralia Australian Research council(ARC)Centre of Excellence for Transformative Meta-Optical Systems(TMOS) University of MelbourneVictoriaAustralia Centre for Advanced Materials&Industrial Chemistry(CAMIC) STEM collegeRMIT UniversityVictoriaAustralia Department of Electrical and Electronic Engineering University of MelbourneVictoriaAustralia

Smart,low-cost and portable gas sensors are highly desired due to the importance of air quality monitoring for environmental and defense-related ***,electrochemical and nondispersive infrared(IR)gas sensors are designed to detect a single specific *** IR spectroscopy-based sensors provide superior performance,their deployment is limited due to their large size and high *** this study,a smart,low-cost,multigas sensing system is demonstrated consisting of a mid-infrared microspectrometer and a machine learning *** microspectrometer is a metasurface filter array integrated with a commercial IR camera that is consumable-free,compact(~1 cm^(3))and lightweight(~1 g).The machine learning algorithm is trained to analyze the data from the microspectrometer and predict the gases *** system detects the greenhouse gases carbon dioxide and methane at concentrations ranging from 10 to 100%with 100%*** also detects hazardous gases at low concentrations with an accuracy of 98.4%.Ammonia can be detected at a concentration of 100 ***,methyl-ethyl-ketone can be detected at its permissible exposure limit(200 ppm);this concentration is considered low and *** study demonstrates the viability of using machine learning with IR spectroscopy to provide a smart and low-cost multigas sensing platform.

关键词： Smart gases system

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Towards hydrometeorological thresholds of reservoir-induced landslide from subsurface strain observations

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Science China(Technological Sciences) 2024年第6期67卷 1907-1922页

作者： YE Xiao ZHU HongHu WANG Jia ZHENG WanJi ZHANG Wei SCHENATO Luca PASUTO alessandro CATANI Filippo School of Earth Sciences and Engineering Nanjing UniversityNanjing210023China Department of Geosciences University of PadovaPadova35131Italy School of Geosciences and Info-Physics Central South UniversityChangsha410083China Department of Information Engineering University of PadovaPadova35131Italy National Research council-Research Institute for Geo-Hydrological Protection(CNR-IRPI) Padova35127Italy

Synergistic multi-factor early warning of large-scale landslides is a crucial component of geohazard prevention and mitigation efforts in reservoir *** forecasting and early warning based on surface displacements have been widely ***,the lack of direct subsurface real-time observations limits our ability to predict critical hydrometeorological conditions that trigger landslide *** this paper,we leverage subsurface strain data measured by high-resolution fiber optic sensing nerves that were installed in a giant reservoir landslide in the Three Gorges Reservoir(TGR)region,China,spanning a whole hydrologic year since February *** spatiotemporal strain profile has preliminarily identified the slip zones and potential drivers,indicating that high-intensity short-duration rainstorms controlled the landslide kinematics from an observation *** the time lag effect,we reexamined and quantified potential controls of accelerated movements using a data-driven approach,which reveals immediate response of landslide deformation to extreme rainfall with a zero-day *** identify critical hydrometeorological rules in accelerated movements,accounting for the dual effect of rainfall and reservoir water level variations,we thus construct a landslide prediction model that relies upon the boosting decision tree(BDT)algorithm using a dataset comprising daily rainfall,rainfall intensity,reservoir water level,water level fluctuations,and slip zone strain time *** results indicate that landslide acceleration is most likely to occur under the conditions of mid-low water levels(i.e.,alls(i.e.,daily rainfall>57.9 mm and rainfall intensity>24.4 mm/h).Moreover,this prediction model allows us to update hydrometeorological thresholds by incorporating the latest monitoring *** on the shoulder of this landslide case,our study informs a practical and reliable path

关键词： slow-moving landslide fiber-optic monitoring subsurface strain hydrometeorological threshold extreme weather

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Cyberattack Ramifications, The Hidden Cost of a Security Breach

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Journal of Information Security 2024年第2期15卷 87-105页

作者： Meysam Tahmasebi Department of Cybersecurity EC-Council University Albuquerque USA

In this in-depth exploration, I delve into the complex implications and costs of cybersecurity breaches. Venturing beyond just the immediate repercussions, the research unearths both the overt and concealed long-term consequences that businesses encounter. This study integrates findings from various research, including quantitative reports, drawing upon real-world incidents faced by both small and large enterprises. This investigation emphasizes the profound intangible costs, such as trade name devaluation and potential damage to brand reputation, which can persist long after the breach. By collating insights from industry experts and a myriad of research, the study provides a comprehensive perspective on the profound, multi-dimensional impacts of cybersecurity incidents. The overarching aim is to underscore the often-underestimated scope and depth of these breaches, emphasizing the entire timeline post-incident and the urgent need for fortified preventative and reactive measures in the digital domain.

关键词： Artificial Intelligence (AI) Business Continuity Case Studies Copyright Cost-Benefit Analysis Credit Rating Cyberwarfare Cybersecurity Breaches Data Breaches Denial Of Service (DOS) Devaluation Of Trade Name Disaster Recovery Distributed Denial of Service (DDOS) Identity Theft Increased Cost to Raise Debt Insurance Premium Intellectual Property Operational Disruption Patent Post-Breach Customer Protection Recovery Point Objective (RPO) Recovery Time Objective (RTO) Regulatory Compliance Risk Assessment Service Level Agreement Stuxnet Trade Secret

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Computational and dark-field ghost imaging with ultraviolet light

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Photonics Research 2024年第2期12卷 226-234页

作者： JIAQI SONG BAOLEI LIU YAO WANG CHAOHAO CHEN XUCHEN SHAN XIAOLAN ZHONG LING-AN WU FAN WANG School of Physics Beihang UniversityBeijing 102206China Australian Research council Centre of Excellence for Transformative Meta-Optical Systems Department of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT 2600Australia Institute of Physics Chinese Academy of SciencesBeijing 100190China

Ultraviolet(UV)imaging enables a diverse array of applications,such as material composition analysis,biological fluorescence imaging,and detecting defects in semiconductor ***,scientific-grade UV cameras with high quantum efficiency are expensive and include complex thermoelectric cooling ***,we demonstrate a UV computational ghost imaging(UV-CGI)method to provide a cost-effective UV imaging and detection *** applying spatial–temporal illumination patterns and using a 325 nm laser source,a singlepixel detector is enough to reconstruct the images of *** use UV-CGI to distinguish four UV-sensitive sunscreen areas with different densities on a ***,we demonstrate dark-field UV-CGI in both transmission and reflection *** only collecting the scattered light from objects,we can detect the edges of pure phase objects and small scratches on a compact *** results showcase a feasible low-cost solution for nondestructive UV imaging and *** combining it with other imaging techniques,such as hyperspectral imaging or time-resolved imaging,a compact and versatile UV computational imaging platform may be realized for future applications.

关键词： ghost illumination versatile

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