The conditional expectation $m_{X}(s)=\mathrm{E}[X|S=s]$, where X and Y are two independent random variables with $S=X+Y$, plays a key role in various actuarial applications. For instance, considering the conditional mean risk-sharing rule, $m_X(s)$ determines the contribution of the agent holding the risk X to a risk-sharing pool. It is also a relevant function in the context of risk management, for example, when considering natural capital allocation principles. The monotonicity of $m_X(\!\cdot\!)$ is particularly significant under these frameworks, and it has been linked to log-concave densities since Efron (1965). However, the log-concavity assumption may not be realistic in some applications because it excludes heavy-tailed distributions. We consider random variables with regularly varying densities to illustrate how heavy tails can lead to a nonmonotonic behavior for $m_X(\!\cdot\!)$. This paper first aims to identify situations where $m_X(\!\cdot\!)$ could fail to be increasing according to the tail heaviness of X and Y. Second, the paper aims to study the asymptotic behavior of $m_X(s)$ as the value s of the sum gets large. The analysis is then extended to zero-augmented probability distributions, commonly encountered in applications to insurance, and to sums of more than two random variables and to two random variables with a Farlie–Gumbel–Morgenstern copula. Consequences for risk sharing and capital allocation are discussed. Many numerical examples illustrate the results.

We present a 1000 km transect of phase-sensitive radar measurements of ice thickness, basal reflection strength, basal melting and ice-column deformation across the Ross Ice Shelf (RIS). Measurements were gathered at varying intervals in austral summer between 2015 and 2020, connecting the grounding line with the distant ice shelf front. We identified changing basal reflection strengths revealing a variety of basal conditions influenced by ice flow and by ice–ocean interaction at the ice base. Reflection strength is lower across the central RIS, while strong reflections in the near-front and near-grounding line regions correspond with higher basal melt rates, up to 0.47 ± 0.02 m a−1 in the north. Melting from atmospherically warmed surface water extends 150–170 km south of the RIS front. Melt rates up to 0.29 ± 0.03 m a−1 and 0.15 ± 0.03 m a−1 are observed near the grounding lines of the Whillans and Kamb Ice Stream, respectively. Although troublesome to compare directly, our surface-based observations generally agree with the basal melt pattern provided by satellite-based methods but provide a distinctly smoother pattern. Our work delivers a precise measurement of basal melt rates across the RIS, a rare insight that also provides an early 21st-century baseline.

Low- and middle-income countries (LMICs) remained at elevated risk for the effects of the COVID-19 pandemic because of persistent stressors to their health systems. Simultaneously facing high infection rates, strict containment measures and natural disasters, the Philippines provides important grounds for health research in LMICs. This review examined how the COVID-19 pandemic affected mental and psychosocial health in the Philippines. This scoping review included literature in English from 2020 to mid-2022 from PubMed, PsycInfo and SCOPUS, and used the PRISMA-ScR and PCC-question model. Two independent reviewers conducted blind article screening and data extraction using COVIDENCE software, followed by consensus building, data charting and analyses. This work identified 405 publications across PubMed (N = 56), PsycInfo (N = 106) and SCOPUS (N = 243), of which 76 articles addressed the Philippines. Article types included 54 research articles, 10 opinion pieces, 4 literature reviews, 6 letters to journals, 1 study protocol and 1 other report. These findings focused primarily on health professionals (N = 23) and educators/learners (N = 22) and reported mostly on moderate-to-severe clinical outcomes such as fear, depression, anxiety or stress. Coping behaviors, like resiliency and other ways of adapting to the pandemic, including religious, spiritual and community-oriented approaches highlighted experiences with stringent infection prevention and control measures to contain COVID-19 in the Philippines. The COVID-19 pandemic brought severe challenges to mental and psychosocial health in the Philippines. The literature focused mostly on healthcare workers and educators/learners, and moderate-to-severe mental health outcomes in these groups. There is a need to expand studies to other sociodemographic groups and communities across the Philippines. Future work stands to benefit from more in-depth qualitative, mixed methods, longitudinal and representative quantitative research in LMICs following this pandemic. Literature reviews remain important to synthesize post-pandemic experiences by providing context for future studies and health practice in the Philippines and other LMICs.

The influence of water vapor on bentonites or smectites is of interest in many different fields of applied mineralogy such as nuclear-waste sealing or casting in the foundry industry. The water vapor affects the smectite surface and perhaps its structure probably leading to mostly unfavorable changes in its properties. In this first part of the present study, the influence of hot water vapor (200°C) on the physicochemical and mineralogical properties of smectite-group minerals was studied. After the steam treatment, turbidity measurements, methylene-blue sorption, water adsorption, and cation exchange capacity (CEC) were measured on both untreated and treated samples. Mineralogical changes were monitored by X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) was used to measure O, Al, and Si. Only a few parameters showed differences between the untreated and vapor-treated samples. Sedimentation volumes (SV) decreased following the treatment. As shown by XRD and XPS, the crystalline structure of smectite remained unaffected by the steam treatment. Equivalent sphere diameters (ESD) were not affected systematically by the steam treatment. Differences in CEC values between untreated and treated samples were observed, but only for smectites with monovalent interlayer cations. From the variety of different measurements the conclusion of the present study was that steam treatment changes the charge properties at or near the smectite particle surface.

Microfluidic flow focusing is a versatile method for the production of monodisperse microbubbles for biomedical applications involving ultrasound. Existing studies propose several theoretical models to predict bubble size and production rate as a function of the liquid and gas flow rate. Yet, they typically do not include physical fluid parameters such as density, viscosity and surface tension. Here, we present an exhaustive experimental and numerical investigation of the influence of physical properties of the gas and liquid, and of the channel geometry on bubble size and production rate. We find a particularly strong effect of (i) gas density on the production rate and (ii) liquid viscosity on the bubble size. We further discuss our findings within the context of existing theoretical models to reflect on gaps in our current understanding of the fluid mechanics of bubble formation by flow focusing.

The megatrend sustainability will significantly change the future value creation of manufacturing companies. Their current linear value creation models need to change to conform to the requirements of sustainability. To face the challenges the circular economy has emerged as a promising economic model. With the shift from a linear to a circular economy, companies have to adjust their current business models. However, they still lack knowledge and adequate methods to develop circular business models. Hence, the aim of the paper is a circular business model canvas (CBMC) for designing circular businesses. A systematic literature review was conducted to identify significant criteria for circular business models. The criteria were analyzed utilizing a qualitative content analysis to derive the business model elements required for the circular economy. Existing elements from the Business Model Canvas were enriched and five new elements, e.g., reverse logistics, were found. Then, the business model elements were logically arranged resulting in the CBMC. It guides companies to systematically develop business models for the circular economy. The CBMC was evaluated by applying it within a mediumsized company in the electronics sector.

Sustainability and circular economy are currently some of the strongest trends in industry as well as in politics. They are seen as the best chance to tackle emissions, pollution and climate change while maintaining the prosperity of society. Product-Service System (PSS) business models are seen as an enabler of the circular economy. However, the development of such business models is a major challenge, especially for SMEs. Therefore, there is a need for support through a methodical approach in the development and decision-making. This paper combines and extends an existing approach for assessing the feasibility of PSS-driven business models and a decision-support matrix for recirculation strategies to provide support to practitioners in the early development phases of circular PSS business models. The existing approach for feasibility analysis was focused on PSS only. To include the perspective of circularity and sustainability a systematic literature review was conducted to identify necessary criteria. Combined with the decision-support matrix the improved method aims to be a lean method to support feasibility analysis and decision-making in circular PSS business model development.

In GARCH-mixed-data sampling models, the volatility is decomposed into the product of two factors which are often interpreted as “short-run” (high-frequency) and “long-run” (low-frequency) components. While two-component volatility models are widely used in applied works, some of their theoretical properties remain unexplored. We show that the strictly stationary solutions of such models do not admit any small-order finite moment, contrary to classical GARCH. It is shown that the strong consistency and the asymptotic normality of the quasi-maximum likelihood estimator hold despite the absence of moments. Tests for the presence of a long-run volatility relying on the asymptotic theory and a bootstrap procedure are proposed. Our results are illustrated via Monte Carlo experiments and real financial data.

Auxin is a key regulator of root morphogenesis across angiosperms. To better understand auxin-regulated networks underlying maize root development, we have characterized auxin-responsive transcription across two time points (30 and 120 min) and four regions of the primary root: the meristematic zone, elongation zone, cortex and stele. Hundreds of auxin-regulated genes involved in diverse biological processes were quantified in these different root regions. In general, most auxin-regulated genes are region unique and are predominantly observed in differentiated tissues compared with the root meristem. Auxin gene regulatory networks were reconstructed with these data to identify key transcription factors that may underlie auxin responses in maize roots. Additionally, Auxin-Response Factor subnetworks were generated to identify target genes that exhibit tissue or temporal specificity in response to auxin. These networks describe novel molecular connections underlying maize root development and provide a foundation for functional genomic studies in a key crop.

Survivor funds are financial arrangements where participants agree to share the proceeds of a collective investment pool in a predescribed way depending on their survival. This offers investors a way to benefit from mortality credits, boosting financial returns. Following Denuit (2019, ASTIN Bulletin, 49, 591–617), participants are assumed to adopt the conditional mean risk sharing rule introduced in Denuit and Dhaene (2012, Insurance: Mathematics and Economics, 51, 265–270) to assess their respective shares in mortality credits. This paper looks at pools of individuals that are heterogeneous in terms of their survival probability and their contributions. Imposing mild conditions, we show that individual risk can be fully diversified if the size of the group tends to infinity. For large groups, we derive simple, hierarchical approximations of the conditional mean risk sharing rule.

We give an algebro-geometric construction of the Hitchin connection, valid also in positive characteristic (with a few exceptions). A key ingredient is a substitute for the Narasimhan–Atiyah–Bott Kähler form that realizes the Chern class of the determinant-of-cohomology line bundle on the moduli space of bundles on a curve. As replacement we use an explicit realisation of the Atiyah class of this line bundle, based on the theory of the trace complex due to Beilinson–Schechtman and Bloch–Esnault.

The paper establishes the local asymptotic normality property for general conditionally heteroskedastic time series models of multiplicative form, $\epsilon _t=\sigma _t(\boldsymbol {\theta }_0)\eta _t$, where the volatility $\sigma _t(\boldsymbol {\theta }_0)$ is a parametric function of $\{\epsilon _{s}, s< t\}$, and $(\eta _t)$ is a sequence of i.i.d. random variables with common density $f_{\boldsymbol {\theta }_0}$. In contrast with earlier results, the finite dimensional parameter $\boldsymbol {\theta }_0$ enters in both the volatility and the density specifications. To deal with nondifferentiable functions, we introduce a conditional notion of the familiar quadratic mean differentiability condition which takes into account parameter variation in both the volatility and the errors density. Our results are illustrated on two particular models: the APARCH with asymmetric Student-t distribution, and the Beta-t-GARCH model, and are extended to handle a conditional mean.