Extreme Response Research Articles

The burden of sepsis in Italy: an analysis of treatable mortality trends

Abstract Background The burden of sepsis, a life-threatening condition triggered by the body’s extreme response to infection, remains a critical global healthcare concern. Sepsis-related deaths often result from delayed recognition, insufficient treatment, or gaps in healthcare delivery. The study aims to analyze treatable mortality for sepsis in Italy and its regions. Methods A retrospective study was conducted on data of treatable mortality for sepsis in Italy and its regions. According to joint OECD/Eurostat list, we included sepsis deaths with the ICD-10 codes A40 (excl. A40.3 [sepsis due to Streptococcus pneumoniae]) and A41 (excl. A41.3 [sepsis due to Hemophilus influenzae]) from 2006 to 2019. Through data on the resident population two-year age-standardized rates by region were calculated. Results From 2006/7 to 2018/9 an overall increase was observed in Italy, from 1.6 to 2.2 age-standardized mortality rates with a maximum peak in 2014/5 (+46.7%). This trend was confirmed for Lombardy (+47.8%), Veneto (+48.8%), Emilia-Romagna (+49.3%), Tuscany (52.0%), Marche (+58.4%%), Abruzzo (39.4%), Molise (26.7%), Apulia (+57.0%), Sicily (+57.2%), and Sardinia (+46.8%). Aosta Valley (+72,5%) had a maximum peak in 2010/1, while Piedmont (+42.5%), Autonomous Province (A.P.) of Bolzano (+27.8%), A.P. of Trento (+45.0%), Friuli-Venezia Giulia (+23.3%) in 2012/3, Calabria (+46.4%) in 2016/7 and lastly Campania (+52.9%) and Basilicata (+73.0%) in 2018/9. Liguria (+49.8%), Latium (47.2%) and Umbria (49.3%) showed two maximum values, one in the 2012/3 and the other in the 2014/5. Conclusions We observed an overall increase in age-standardized mortality rates throughout Italy, with a peak in 2014/5. This trend was resumed in ten regions, while three regions showed multiple peaks, indicating fluctuations in mortality rates. These findings underline the importance of targeted health interventions and policy initiatives to address region-specific health challenges. Key messages • Regional disparities in mortality rates highlight the necessity for customized health interventions and policy measures between Italian regions. • Recognizing fluctuating mortality trends in specific regions is crucial to effectively address various health challenges.

Seismic Response Analysis of Hydraulic Tunnels Under the Combined Effects of Fault Dislocation and Non-Uniform Seismic Excitation

Hydraulic tunnels are prone to pass through faults and high-intensity earthquake areas, which will cause serious damage under fault dislocation and earthquake action. Fault dislocation and seismic excitation are often considered separately in previous studies. For tectonic earthquakes with higher frequency in seismic phenomena, fault dislocation and ground motion are often associated, and fault dislocation is usually the cause of earthquake occurrence, so it is limiting to consider the two separately. Moreover, strong earthquake records show that there will be significant differences in the mainland vibration within 50 m. The uniform ground motion inputs in previous studies are not suitable for long hydraulic tunnels. This paper begins with the simulation of non-uniform stochastic seismic excitations that consider spatial correlation. Based on stochastic vibration theory, multiple multi-point acceleration time-history curves that can reflect traveling wave effects, coherence effects, attenuation effects, and non-stationary characteristics are synthesized. Furthermore, a fault velocity function is introduced to account for the velocity effect of fault dislocation. Finally, numerical analyses of the response patterns of the tunnel lining under four different conditions are conducted based on an actual engineering project. The results indicate the following: (a) the maximum lining response values occur under the combined effects of fault dislocation and non-uniform seismic excitation, indicating its importance in the seismic resistance of the tunnel. (b) Compared to uniform seismic excitation, the peak displacement of the tunnel under non-uniform seismic excitation increases by up to 6.42%, and the peak maximum principal stress increases by up to 28%. Additionally, longer tunnels exhibit a noticeable delay effect in axial deformation during an earthquake. (c) Under non-uniform seismic excitation, the larger the fault dislocation magnitude, the greater the peak displacement and peak maximum principal stress at the monitoring points of the lining. The simulation results show that the extreme response values primarily occur at the crown and haunches of the tunnel, which require special attention. The research can provide valuable references for the seismic design of cross-fault tunnels.

Probabilistic Modeling of Congested Traffic Scenarios on Long-Span Bridges

This paper aims to extend a previously developed probabilistic model for simulating extreme response scenarios to include congested traffic flow on long-span bridges, addressing the challenge of accurately modeling traffic loads under changing conditions. While the model was initially designed for free-flow traffic, this study demonstrates how it can be adapted for congested conditions, with the objective of improving the accuracy of traffic load models. To overcome the limitation of traditional Weigh-in-Motion (WIM) systems in capturing congested traffic, congested flow characteristics were inferred from available free-flow data. The cellular automata (CA) method was applied to generate realistic congested traffic scenarios, which were used as input for the probabilistic model. Key simulation parameters, such as cell length and vehicle weight distribution, were adjusted to reflect congested conditions. The results validate the model’s flexibility, showing how, with the adaptation of some parameters, it can simulate both free-flow and congested traffic patterns effectively. This research provides a basis for improving traffic load models used in the design and assessment of long-span bridges, addressing the current limitations in existing codes and standards.

Developmental patterns of inhibition and fronto-basal-ganglia white matter organisation in healthy children and children with attention-deficit/hyperactivity disorder.

There is robust evidence implicating inhibitory deficits as a fundamental behavioural phenotype in children with attention-deficit/hyperactivity disorder (ADHD). However, prior studies have not directly investigated the role in which white matter properties within the fronto-basal-ganglia circuit may play in the development of inhibitory control deficits in this group. Combining recent advancements in brain-behavioural modelling, we mapped the development of stop-signal task (SST) performance and fronto-basal-ganglia maturation in a longitudinal sample of children aged 9-14 with and without ADHD. In a large sample of 135 ADHD and 138 non-ADHD children, we found that the ADHD group had poorer inhibitory control (i.e., longer stop-signal reaction times) across age compared to non-ADHD controls. When applying the novel parametric race model, this group effect was driven by higher within-subject variability (sigma) and higher number of extreme responses (tau) on stop trials. The ADHD group also displayed higher within-subject variability on correct responses to go stimuli. Moreover, we observed the ADHD group committing more task-based failures such as responding on stop trials (trigger failures) and omissions on go trials (go failures) compared to non-ADHD controls, suggesting the contribution of attentional lapses to poorer response inhibition performance. In contrast, longitudinal modelling of fixel-based analysis measures revealed no significant group differences in the maturation of fronto-basal-ganglia fibre cross-section in a subsample (74 ADHD and 73 non-ADHD children). Finally, brain-behavioural models revealed that age-related changes in fronto-basal-ganglia morphology (fibre cross-section) were significantly associated with reductions in the variability of the correct go-trial responses (sigma.true) and skew of the stop-trial distribution (tauS). However, this effect did not differ between ADHD and typically developing children. Overall, our findings support the growing consensus suggesting that attentional deficits subserve ADHD-related inhibitory dysfunction. Furthermore, we show novel evidence suggesting that while children with ADHD are consistently performing worse on the SST than their non-affected peers, they appear to have comparable rates of neurocognitive maturation across this period.

Making preclinical sepsis research stronger, faster, and more responsive to patients

Making preclinical sepsis research stronger, faster, and more responsive to patients Sepsis represents a significant global burden. The National Preclinical Sepsis Platform (NPSP) is leading vital sepsis research, informing policy, driving innovation, and ultimately saving lives. Sepsis is a devastating condition triggered by the body’s extreme response to an infection. Patients with sepsis are often admitted to an intensive care unit (ICU), where they are given a barrage of life-saving treatments to combat the infection and restore basic organ functions like breathing and circulation. Despite our medical advancements, mortality rates for sepsis remain unacceptably high, with 30-50% of patients dying from this condition. In Canada, sepsis accounts for one in every 18 deaths and imposes a staggering $1.7bn burden on the healthcare system each year.

Assessing air-gap responses of semi-submersible platforms in extreme sea states based on in-situ measurement

The air-gap response of semi-submersible platforms is critical for ensuring operational sustainability. This study analysed platform-based in-situ measurements from the HYSY 981 semi-submersible platform during extreme sea conditions caused by super typhoon Doksuri. Our primary aim was to investigate how motions induced by the dynamic positioning system, particularly rotations, affected the platform's air-gap response. Results demonstrated that under extreme sea states, thruster-induced rotation significantly influenced air-gap responses. To estimate extreme air-gap response values, we employed two statistical models: the Weibull tail fitting (WTF) method and the Naess–Gaidai tail fitting (NGTF) method. Our analysis revealed that the NGTF method provided more robust and stable estimates of the most probable maximum (MPM) values compared to the three-parameter WTF method, especially when applied to in-situ measurement data. This research contributes to a better understanding of semi-submersible platform behavior during extreme weather events, which is essential for enhancing operational sustainability and structural integrity in offshore operations.

Climate-Smart Invasive Species Management for 21st Century Global Change Challenges.

Addressing the global challenges of climate change and biotic invasions requires understanding their interactions and implications for natural resource management. To facilitate and support invasive species management in a changing climate, we review how climate change and invasions interact to impact the planning, action, and outcomes of invasive species management. Climate change is facilitating the introduction of new potential invasive species and altering pathways of introduction and spread, with implications for which species natural resource managers need to assess, monitor, and target. Climate-driven shifts in invasive species phenology require more flexible management timelines. Climate change may reduce the efficacy and feasibility of current treatment methods and make native ecosystems more vulnerable to invasion. Additionally, disturbance caused by extreme climate events can compound the spread and impacts of biological invasions, making invasive species management a necessary part of extreme event preparation and response planning. As a solution to these challenges, we propose climate-smart invasive species management, which we define as the approaches that managers and decision-makers can take to address the interactive effects of climate change and invasions. Climate-smart invasive species management includes considering potential shifts in species ranges, abundances, and impacts to inform monitoring, treatment, and policies to prevent new invasive species. Climate-smart management may also involve adjusting the timing and type of treatment to maintain efficacy, promoting resilient ecosystems through climate-smart restoration, and considering the effects of climate change when setting management goals. Explicitly considering the interactions of climate change and biological invasions within organizational decision-making and policy can lead to more effective management and promote more resilient landscapes.

The natural flavonoid pinocembrin shows antithrombotic activity and suppresses septic thrombosis

Sepsis, an extreme host response to systemic infection, remains one of the leading causes of mortality worldwide. Platelets, which are integral to both thrombosis and inflammation, play a crucial role in the pathophysiology of sepsis. Excessive platelet activation and aggregation significantly increase the risk of thrombosis, thereby elevating mortality in septic patients. However, the etiology and treatment of this condition have not been comprehensively studied. This study identifies pinocembrin, a natural flavonoid compound derived from propolis, as a potential therapeutic agent for mitigating platelet activation and treating sepsis. In vivo, pinocembrin effectively inhibited FeCl3-induced carotid arterial occlusive thrombus formation and collagen/epinephrine-induced pulmonary thromboembolism in mouse models. In vitro, pinocembrin treatment suppressed multiple facets of platelet activation, including aggregation, secretion, and αIIbβ3-mediated signaling events. Mechanistically, pinocembrin repressed platelet functions by inhibiting Src/Syk/PLCγ2/MAPK signaling pathway. Using cecal ligation and puncture (CLP) mouse model to simulate human sepsis, pinocembrin reduced inflammatory cytokine release and septic thrombosis, thereby improving the survival rate of septic mice. Lipopolysaccharide (LPS)-induced model further substantiated these results. Overall, the inhibition of platelet activity by pinocembrin demonstrates significant therapeutic potential for managing life-threatening septic thrombosis.

Study of doping effect of cd on ZrO2 nanostructures for gas sensing applications

Abstract Here, we enforced the conventional precipitation approach to yield pure and cadmium doped (3% and 8%) ZrO2 powder, to examine the gas sensing proficiency of Zirconium metal oxide. Drop casting mechanism is hired for the formation of pure and cadmium doped ZrO2 films. The X-ray diffraction (XRD) outcomes recommended that the prepared pure and cadmium doped ZrO2 powder samples are pure with no subordinate phase, but slight shift in peaks were detected. Scanning Electron Microscope (SEM) portrait substantiates the uniform spherical like morphology of the samples. The Current Voltage (I-V) study affirms the good conducting nature of the samples. The photoluminescence (PL) inspection, confirms that the oxygen vacant spots are present in the processed samples. The UV-Diffuse Reflectance Spectra validates the decrement of band gap of the prepared samples with rise in dopant concentration. The gas sensing capabilities of the drop casted samples were examined for different gas concentrations of reducing gases like ammonia, acetone, ethanol, formaldehyde and xylene. From the output data, we interpreted that the prepared samples show favorable response towards the target gas, explicitly the 8% cadmium doped sample shows 39% of an extreme response towards ammonia gas. Likewise, it also accomplishes an expeditious response time (RST) and recovery time (RCT) among all samples. Thus, we resolved that the inclusion of cadmium content stacks up the gas sensing adaptability of the zirconium metal oxide.

Core Competencies of the Public Health Workforce in Climate Change and Extreme Weather Events Preparedness, Response, and Recovery: A Scoping Review.

Climate change poses a significant threat to public health and safety, necessitating an urgent, coordinated response. Public health officials must be well-trained to effectively prepare for, respond to, and recover from extreme weather events. Despite emerging frameworks, a gap remains in their systematic application, risking future unpreparedness. This review aimed to identify the necessary competencies for public health professionals to manage climate change and the best methods to teach these skills. An academic librarian helped develop a keyword chain for a PubMed search, which included original articles and reviews concerning our research questions published in English or French between 1 January 2013 and 31 January 2024. Out of 255 potential articles, 31 were included in this scoping review. The results aligned with our objectives, revealing three main themes: core competencies, training and pedagogy strategies, and assessment approaches for public health professionals' preparedness, responses, and recovery in the context of climate change and extreme weather events. This scoping review enabled us to provide a set of clear recommendations for future research and practice in training the public health workforce for managing extreme weather events and climate change.

Experimental and numerical study of a hinged floating bridge under waves and moving loads

ABSTRACT As an important means of water transportation, floating bridges have broad application prospects. In this paper, a numerical calculation model of the floating bridge considering the combined actions of waves and moving loads is established based on the potential flow theory, and model tests are carried out to verify the accuracy of the numerical method. The effects of motorcade loads and wave parameters on the dynamic responses of the floating bridge were further investigated. The results show that the larger vertical displacements of the floating bridge are affected by both the increase in the number of vehicles and the decrease in vehicle distances. The wave frequency and wave amplitude ranges dominated by the waves and vehicle loads were provided. The extreme dynamic responses of the hinged floating bridge under the combined effect of the waves and moving loads are less than the linear superposition of the individual effect.

Extreme Responses of An Integrated System with A Semi-Submersible Wind Turbine and Four Torus-Shaped Wave Energy Converters in Different Survival Modes

Extreme Responses of An Integrated System with A Semi-Submersible Wind Turbine and Four Torus-Shaped Wave Energy Converters in Different Survival Modes

Characterization of extreme rainfall changes and response to temperature changes in Guizhou Province, China

Different geographical zones have regional heterogeneity in underlying earth surface structure and microclimate which result in different evolution trends and their response to climate change varies in extreme rainfalls in these zones. In the Guizhou province of China, there are complex landforms, which lead to spatial redistribution of rainfall, frequent extreme rainfall, and disasters high risk of geologic disasters. Research on extreme climate in Guizhou mostly paid attention to its spatio-temporal characteristics and modeling, but lack of analysis on its characteristics of extreme rainfall variability and response to temperature changes under different subsurface conditions. This study investigated the characteristics of the extreme rainfall spatiotemporal and recurrence periods in Guizhou province and discussed the relationship between the response of extreme rainfall to temperature change. Daily rainfall data from 1990 to 2020 and 2021–2100 at 31 meteorological observation stations throughout the province were collected to calculate extreme precipitation. This research had the following results. (1) Both historical and future periods show an upward trend in extreme rainfall in Guizhou province, with a spatial distribution pattern of “high in the south and low in the north, high in the east and low in the west” and “high in the southeast and low in the northwest”, respectively; the spatial distribution of extreme rainfall under each recurrence period is consistent with the non-recurrence period. (2) Both historical and future periods show an upward trend in temperature in Guizhou province, with a spatial distribution consistent with that of the extreme rainfall in the corresponding period. (3) The change in extreme rainfall intensity with increasing temperature is almost always greater than the C–C rate for different periods and underlying earth surface structure; Extreme rainfall has a Hook response structure to temperature change, and the climate response structure shifts to the right with climate warming. The results of the study can provide a basis for decision-making on regional disaster prevention and mitigation in the context of temperature change.

Probabilistic study on non-stationary extreme response of transmission tower under moving downburst impact

Localized severe non-synoptic winds, such as downbursts and tornadoes, cause frequent structural failures of the electric transmission lines worldwide. This paper aims to develop an analytical approach to evaluate the extreme non-stationary dynamic response of transmission towers under downbursts in frequency domain. First, the empirical models of time-varying mean wind and non-stationary fluctuating wind of moving downbursts are introduced to deduce the transient wind loads on transmission towers in time domain. The closed-form frequency domain solutions of non-stationary fluctuating downburst wind-induced response of transmission towers are derived based on the pseudo excitation method. Furthermore, through the up-crossing extreme value theory, the probability distribution of the non-stationary extreme response is studied. Finally, the peak factors of the non-stationary and the equivalent stationary theoretical methods are compared based on the proposed equivalent stationary extreme value distribution for engineering application. The proposed theoretical framework is validated by stochastic sampling simulation and finite element analysis. It is found that the proposed theoretical framework can accurately assess the extreme value responses of transmission towers under non-stationary moving downbursts.

Time-variant reliability analysis of corroded suspender of suspension bridge based on data-driven

The suspender of a suspension bridge is susceptible to corrosion due to environment, material, load, and other factors, which leads to the reduction of its bearing capacity with time, thus adversely affecting the safety and durability of the suspension bridge. Time-variant reliability analysis can consider the time-variant characteristics and uncertainties of each variable, and can better reveal the degradation of corrosion suspender resistance with time. However, due to the complex and highly nonlinear characteristics of the stress situation, the functional function of the suspender is often implicit, and the traditional time-variant reliability analysis method cannot be directly solved. To solve the problem of the implicit function of the suspender, An Adaptive Support Vector Regression with Extreme Response Surface (ASVR-ERS) method was proposed, and it was applied to the time-variant reliability analysis of corroded suspender of a suspension bridge. According to the corrosion characteristics of steel wire in suspenders, a hybrid constitutive model for calculating the ultimate bearing capacity of corroded suspenders was proposed. Furthermore, the time-variant reliability and residual life of corroded suspenders of a self-anchored suspension bridge were systematically studied. The results show that: Compared with the existing methods, the ASVR-ERS method can use fewer training samples to achieve higher computational accuracy. When calculating the ultimate bearing capacity of a corrosion suspender, the phenomenon of ductility degradation caused by steel wire corrosion in the suspender cannot be ignored, and the mixed constitutive model of the ultimate bearing capacity of a corrosion suspender is more reasonable. When the service time of the bridge is the same, the reliability of the suspender in the middle span of the main span is the smallest, and the reliability of the suspender in the full bridge gradually decreases from the bridge tower position to the middle span direction and the side span direction. The decrease rate of suspender reliability is the fastest at the beginning of corrosion and gradually slows down with the deepening of the corrosion degree. When the sheath has the minimum damage and the maximum circumferential damage and reaches life, the suspender section loss rate is between 10 % and 15 %. Compared with improving the safety factor of the suspender, delaying the breakage time of the sheath can improve the life expectancy of the suspender more obviously.

The surrogate model for short-term extreme response prediction based on ANN and Kriging algorithm

Numerical simulation is a common method for calculating the short-term extreme response of floating offshore wind turbines (FOWTs). However, it requires significant computational resources. This study presents a dynamic response database for a 5MW semi-submersible FOWT under complex environmental conditions, including wind speed, effective wave height, and wave spectral peak period, using a numerical model. The peak over threshold (POT) method can be used to obtain the parametric database of short-term extreme responses, which includes the short-term extreme response distribution parameters for four responses: float surge, mooring tension, outward bending moment at the leaf root surface (OoPBM) and tower base pitching moment (TBPM). And the parameter database is applied to train models such as the Genetic Algorithm optimization Back Propagation neural network (GA-BP) and Kriging algorithm models. The research indicates that a correlation can be established between environmental conditions and short-term extreme response parameters using two algorithms. The accuracy of surrogate model prediction for some parameters can be improved by grouping the data based on wind speed and training separately. Additionally, selecting the appropriate surrogate model for each parameter separately can improve the accuracy of short-term extreme response prediction.

An Overview of Explainable AI Studies in the Prediction of Sepsis Onset and Sepsis Mortality.

Explainable artificial intelligence (AI) focuses on developing models and algorithms that provide transparent and interpretable insights into decision-making processes. By elucidating the reasoning behind AI-driven diagnoses and treatment recommendations, explainability can gain the trust of healthcare experts and assist them in difficult diagnostic tasks. Sepsis is characterized as a serious condition that happens when the immune system of the body has an extreme response to an infection, causing tissue and organ damage and leading to death. Physicians face challenges in diagnosing and treating sepsis due to its complex pathogenesis. This work aims to provide an overview of the recent studies that propose explainable AI models in the prediction of sepsis onset and sepsis mortality using intensive care data. The general findings showed that explainable AI can provide the most significant features guiding the decision-making process of the model. Future research will investigate explainability through argumentation theory using intensive care data focused on sepsis patients.

6 Durable response to immunotherapy-based regimens for IMDC favorable risk patients with metastatic clear cell renal cell carcinoma: a pooled analysis of four published randomized control phase 3 trials

Abstract Background An immune checkpoint inhibitor (ICI) backbone of either ICI doublet (ipilimumab-nivolumab [ipi-nivo]) or tyrosine kinase inhibitor (TKI) with ICI (such as axitinib-pembrolizumab [axi-pembro], cabozantinib-nivolumab [cabo-nivo], or lenvatinib-pembrolizumab [len-pembro]) is the current standard of care for previously untreated, metastatic clear cell renal cell carcinoma (mccRCC). The phase 3 trials that evaluated these four regimens were compared to sunitinib, with no direct head-to-head clinical trial data available. With at least 4-year follow up data available, we compared the long-term responders of the IMDC favorable risk patients enrolled in the four phase 3 trials (CheckMate 214, KEYNOTE-426, CheckMate 9ER, and CLEAR). Methods Pseudo individual patient data (IPD) was obtained from the Kaplan-Meier (K-M) curves using the graph digitizer software IPDfromKM R package to extract coordinates of points on the curves and applied the numerical algorithm to reconstruct survival results. The hazard ratios (HRs) of the favorable risk group for both progression-free survival (PFS) and overall survival (OS) comparing the experimental arms to sunitinib were extracted. Responses were measured at 24 (durable response [DR]) and 36 months (extreme durable response [EDR]) and long-term OS as OS ≥48 months. K-M method using the extracted IPD was used to estimate the survival rates at 24-month PFS, 36-month PFS, and 48-month OS. Then, we compared the survival rates at each time point using the generalized linear model for the survival rates at fixed time points obtained from the K-M method. Results Len-pembro was associated with the highest DR (57.2%) and EDR (44.5%), while ipi-nivo had the lowest DR (36.0%), and cabo-nivo had the lowest EDR (18.8%). There was no difference in 48 month-OS among regimens (p=0.11), ranging between 58.3% (cabo-nivo) and 70.6% (len-pembro). Comparing the sunitinib control arms among the four studies, a numerically higher PFS at 24 months (59%) and 36 months (40%) was observed in the CheckMate 214 trial compared to the ICI-TKI trials (25-35% and 15-20%, respectively). The 48-month OS for the sunitinib arms ranged from 55-70%, and no differences were observed among trials (p=0.55). Comparisons of survival rates for the immunotherapy arm on fixed time-points for IMDC favorable risk subset of patients Conclusions ICI-based regimens provided durable responses to a significant number of patients with favorable risk mccRCC. While TKI-ICI were associated with higher DR and EDR, no differences in OS at 48 months were observed compared to ipi-nivo or sunitinib for favorable risk disease. Longer follow-up is necessary to evaluate long-term outcomes given the favorable prognosis of these patients. We acknowledge the limitations and caveats of cross-trial comparisons.

Pan‐Antarctic Assessment of Ice Shelf Flexural Responses to Ocean Waves

AbstractUnderstanding the drivers of iceberg calving from Antarctic ice shelves is important for future sea level rise projections. Ocean waves promote calving by imposing stresses and strains on the shelves. Previous modeling studies of ice shelf responses to ocean waves have focused on highly idealized geometries with uniform ice thickness and a flat seabed. This study leverages on a recently developed mathematical model that incorporates spatially varying geometries, combined with measured ice shelf thickness and seabed profiles, to conduct a statistical assessment of how 15 Antarctic ice shelves respond to ocean waves over a broad range of relevant wave periods, from swell to infragravity waves to very long period waves. The results show the most extreme responses at a given wave period are generated by features in the ice shelves and/or seabed geometries, depending on the wave regime. Relationships are determined between the median ice shelf response and the median shelf front thickness or the median water cavity depth. The findings provide further evidence of the role of ocean waves in large‐scale calving events for certain ice shelves (particularly the Wilkins) and indicate a possible role of ocean waves in calving events for other shelves (Larsen C and Conger). Further, the relationships determined provide a method to assess the potential for increased calving as ice shelves evolve with climate change, and, hence, contribute to assessments of future sea level rise.

Sample size calculation for the sequential parallel comparison design with binary endpoint using exact methods

High placebo responses in clinical trial could reduce the treatment effect leading to the failure of a promising drug. Several strategies have been developed to minimize high placebo responses, including the sequential parallel comparison design (SPCD). For a study with binary outcome, the existing statistical methods to test the drug effectiveness always rely on the asymptotic limiting distribution. When a study's sample size is small to medium, the asymptotic approaches do not have satisfactory performance with regard to type I error rate and statistical power. For that reason, we propose utilizing exact conditional approach to calculate sample size based on the existing test statistics to order the sample space. The proposed method controls the type I error rate under the unconditional framework. We compare the proposed exact sample sizes using different test statistics and the sample size for a randomized parallel study. We would recommend using exact sample sizes for the SPCD with small- to medium sample sizes and the SPCD with extreme response rates.