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Catastrophe risk-based bonds are used by governments, financial institutions and (re)insurers to transfer the financial risk associated to the occurrence of catastrophic events, such as earthquakes, to the capital market. In this study, we show how municipalities prone to earthquakes can use this type of insurance-linked security to protect their building stock and communities from economic losses, and ultimately increase their earthquake resilience. We consider Benevento, a middle-sized historical town in southern Italy, as a case study, although the same approach is applicable to other urban areas in seismically active regions. One of the crucial steps in pricing catastrophe bonds is the computation of aggregate losses. We compute direct economic losses for each exposed asset based on high spatial resolution hazard and exposure models. Finally, we use the simulated loss data to price two types of catastrophe bonds (zero-coupon and coupon bonds) for different thresholds and maturity times. Although the present application focuses on earthquakes, the framework can potentially be applied to other natural disasters, such as hurricanes, floods, and other extreme weather events.

Large scale offshore wind farms are relatively new infrastructures and are being deployed in regions prone to earthquakes. Offshore wind farms comprise of both offshore wind turbines (OWTs) and balance of plants (BOP) facilities, such as inter-array and export cables, grid connection etc. An OWT structure can be either grounded systems (rigidly anchored to the seabed) or floating systems (with tension legs or catenary cables). OWTs are dynamically-sensitive structures made of a long slender tower with a top-heavy mass, known as Nacelle, to which a heavy rotating mass (hub and blades) is attached. These structures, apart from the variable environmental wind and wave loads, may also be subjected to earthquake related hazards in seismic zones. The earthquake hazards that can affect offshore wind farm are fault displacement, seismic shaking, subsurface liquefaction, submarine landslides, tsunami effects and a combination thereof. Procedures for seismic designing OWTs are not explicitly mentioned in current codes of practice. The aim of the paper is to discuss the seismic related challenges in the analysis and design of offshore wind farms and wind turbine structures. Different types of grounded and floating systems are considered to evaluate the seismic related effects. However, emphasis is provided on Tension Leg Platform (TLP) type floating wind turbine. Future research needs are also identified.

Nonergodicity and Simpson’s paradox present significant, yet underappreciated challenges in cognitive neuroscience. Leveraging brain imaging and behavioral data from over 4000 individuals and a Bayesian computational model of cognitive dynamics, we investigated brain-behavior relationships underlying cognitive control at both between-subjects and within-subjects levels. Strikingly, brain-behavior associations reversed across levels of analysis, revealing pervasive nonergodicity. Within-subjects analysis uncovered dissociated neural representations of reactive and proactive control and revealed that individuals who adaptively versus maladaptively regulated cognitive control exhibited distinct brain-behavior associations. Our findings demonstrate that between-subjects analyses can fundamentally mischaracterize within-individuals mechanisms, as group-level patterns not only disagreed with individual-level patterns but often reversed them. This work highlights the necessity of distinguishing between-subjects and within-subjects inferences in neuroscience, with implications for understanding cognitive mechanisms and designing personalized interventions. In this study, the authors show that brain-behavior relationships display nonergodicity and Simpson’s paradox, meaning that between- and within-individuals analyses give divergent results about the neural correlates of cognitive control

Risk-based catastrophe bonds require the estimation of losses from the convolution of hazard, exposure and vulnerability models. These models are affected by different uncertainties that arise from the definition of their input parameters. In this paper, we propose a stochastic approach to treat the uncertainty in the asset location and attributes of the exposure model. The proposed method uses the Monte Carlo sampling approach to generate a stochastic exposure database, where each asset location is generated randomly within the geometric bound of the administration, while the asset attributes (i.e. construction type and material, number of storey, building activity type and number of dwelling) are sampled from distributions built from census data. Finally, a sensitivity analysis is performed to investigate the influence of the spatial resolution of the exposure model on the average annual losses (AAL) and catastrophe bond prices. To this end, we implement four exposure models, with spatial resolution at the asset, municipality and province levels, on a study region comprising ten provinces in southern Italy. Compared to the proposed model, the exposure model where assets are relocated and aggregated at the geometric centroid of the municipality underestimates AAL by 8%, while a higher difference (up to 20%) is observed for the exposure model where assets are relocated and aggregated at the geometric centroid of the province. We also consider an exposure model whose asset locations are extracted from publicly available building footprints. Yet, this latter model was incomplete for some provinces resulting in underestimation of AAL up to 90%. Differences in catastrophe bond prices obtained from the four exposure models are less evident, with the exposure model built based on the building footprints showing a difference up to 9.5%.

Lysosomal storage disorders (LSD) are rare diseases, caused by inherited deficiencies of lysosomal enzymes/transporters, that affect 1 in 7000 to 1 in 8000 newborns. Individuals with LSDs face long diagnostic journeys during which debilitating and life-threatening events can occur. Clinical trials and classical descriptions of LSDs typically focus on common manifestations, which are not representative of the vast phenotypic heterogeneity encountered in real-world experience. Additionally, recognizing that there was a limited understanding of the natural history, disease progression, and real-world clinical outcomes of rare LSDs, a collaborative partnership was pioneered 30 years ago to address these gaps. The Rare Disease Registries (RDR) (for Gaucher, Fabry, Mucopolysaccharidosis type I, and Pompe), represent the largest observational database for these LSDs. Over the past thirty years, data from the RDRs have helped to inform scientific understanding and the development of comprehensive monitoring and treatment guidelines by creating a framework for data collection and establishing a standard of care, with an overarching goal to improve the quality of life of affected patients. Here, we highlight the history, process, and impact of the RDRs, and discuss the lessons learned and future directions.

GBA is the major risk gene for Parkinson’s disease (PD) and dementia with Lewy bodies (DLB), two common α-synucleinopathies with cognitive deficits. Here we investigate the role of mutant GBA in cognitive decline by utilizing Gba (L444P) mutant, SNCA transgenic (tg), and Gba-SNCA double mutant mice. Notably, Gba mutant mice show cognitive decline but lack PD-like motor deficits or α-synuclein pathology. Conversely, SNCA tg mice display age-related motor deficits, without cognitive abnormalities. Gba-SNCA mice exhibit both cognitive decline and exacerbated motor deficits, accompanied by greater cortical phospho-α-synuclein pathology, especially in layer 5 neurons. Single-nucleus RNA sequencing of the cortex uncovered synaptic vesicle (SV) endocytosis pathway defects in excitatory neurons of Gba mutant and Gba-SNCA mice, via downregulation of genes regulating SV cycle and synapse assembly. Immunohistochemistry and electron microscopy validate these findings. Our results indicate that Gba mutations, while exacerbating pre-existing α-synuclein aggregation and PD-like motor deficits, contribute to cognitive deficits through α-synuclein-independent mechanisms, involving dysfunction in SV endocytosis. GBA, a major gene for Parkinson’s disease and dementia with Lewy bodies, is associated with increased risk of developing dementia. Here, we demonstrate that GBA mutations in mice contribute to cognitive deficits through α-synuclein-independent mechanisms that impact synaptic vesicle endocytosis.

has been a useful model system for studies of the neural basis of behavior, learning, and aging. While the latter topic has been explored with respect to several of its simple reflex behaviors, this study represents the first examination of how one of Aplysia's more complex behaviors, escape locomotion, is affected in animals nearing the end of their natural lifespan. Middle-aged (5-7 mo) and elderly (12-13 mo) were subjected to an experimental or control stimulus protocol ( = 16 each group). Head reach latency, gallop share, and cycle number were calculated for each animal. Voltage-sensitive dye (VSD) imaging was performed on the isolated brains of middle-aged or elderly animals ( = 6 each group) under an experimental or control fictive locomotion stimulus protocol. Onset latency, cycle number, and average spikes/cell were calculated for each recording. VSD imaging was also done on middle-aged and elderly brains at rest ( = 7 each group), and average # of spikes/cell as well as burst duration, intraburst frequency, and cycle/min were calculated for each recording. Elderly showed greatly reduced gallop response, and a loss in head reach latency sensitization in both intact animals and isolated brains. Onset latency sensitization was also more transient in middle-aged isolated brains than in middle-aged intact animals. Repeated stimulation in middle-aged isolated brains increased average spikes/cell, but elderly brains saw decreased average spikes/cell under the same protocol. Resting state activity was also weaker and slower in elderly isolated brains. This study provides the first evidence of how aging changes behavioral and network parameters of escape locomotion, including a potential early indicator of age-related dysfunction present in middle-aged brains that has yet to emerge in the behavior. This supports future work investigating compensatory mechanisms and opportunities for future therapeutic interventions.

Neuronopathic Gaucher disease (nGD) is a rare neurodegenerative disorder caused by biallelic mutations in and buildup of glycosphingolipids in lysosomes. Neuronal injury and cell death are prominent pathological features; however, the role of in individual cell types and involvement of microglia, blood-derived macrophages, and immune infiltrates in nGD pathophysiology remains enigmatic. Here, using single-cell resolution of mouse nGD brains, lipidomics, and newly generated biomarkers, we found induction of neuroinflammation pathways involving microglia, NK cells, astrocytes, and neurons. Targeted rescue of in microglia and neurons, respectively, in -deficient, nGD mice reversed the buildup of glucosylceramide (GlcCer) and glucosylsphingosine (GlcSph), concomitant with amelioration of neuroinflammation, reduced serum neurofilament light chain (Nf-L), and improved survival. Serum GlcSph concentration was correlated with serum Nf-L and ApoE in nGD mouse models as well as in GD patients. rescue in microglia/macrophage compartment prolonged survival, which was further enhanced upon treatment with brain-permeant inhibitor of glucosylceramide synthase, effects mediated via improved glycosphingolipid homeostasis, and reversal of neuroinflammation involving activation of microglia, brain macrophages, and NK cells. Together, our study delineates individual cellular effects of deficiency in nGD brains, highlighting the central role of neuroinflammation driven by microglia activation. Brain-permeant small-molecule inhibitor of glucosylceramide synthase reduced the accumulation of bioactive glycosphingolipids, concomitant with amelioration of neuroinflammation involving microglia, NK cells, astrocytes, and neurons. Our findings advance nGD disease biology whilst identifying compelling biomarkers of nGD to improve patient management, enrich clinical trials, and illuminate therapeutic targets. Research grant from Sanofi; other support includes R01NS110354, Yale Liver Center P30DK034989, pilot project grant.

Number sense, the ability to decipher quantity, forms the foundation for mathematical cognition. How number sense emerges with learning is, however, not known. Here we use a biologically-inspired neural architecture comprising cortical layers V1, V2, V3, and intraparietal sulcus (IPS) to investigate how neural representations change with numerosity training. Learning dramatically reorganized neuronal tuning properties at both the single unit and population levels, resulting in the emergence of sharply-tuned representations of numerosity in the IPS layer. Ablation analysis revealed that spontaneous number neurons observed prior to learning were not critical to formation of number representations post-learning. Crucially, multidimensional scaling of population responses revealed the emergence of absolute and relative magnitude representations of quantity, including mid-point anchoring. These learnt representations may underlie changes from logarithmic to cyclic and linear mental number lines that are characteristic of number sense development in humans. Our findings elucidate mechanisms by which learning builds novel representations supporting number sense. How the brain represents numbers remains poorly understood. Here, the authors uncover the emergence of absolute and relative magnitude representations of quantity in a biologically-inspired neural network, mirroring observations in children during numerical skill acquisition.

Three-five layers of graphene were electrochemically exfoliated from graphite using NaOH solution as electrolyte, graphite foil as anode, and Cu plate as cathode. The effect of process parameters namely, molarity and voltage on the quantity and quality of exfoliated graphene was investigated. Results confirm multilayer graphene with high transparency is produced at low voltage (< 4V). At high voltage (10V), opaque graphene flakes are synthesized with I 2D /I G ratio in the range of 0.32-0.34 which is similar to graphite. Further, the yield vs. time plot of graphene showed that the incubation period for the exfoliation of graphite foil is 2 hours which was further reduced by 30 minutes with stirring of electrolyte. The minimum defect concentration produced in graphene at optimum conditions was 6.86x10 9 per cm 2 . The transmission electron microscopy (TEM) and atomic force microscopy (AFM) confirmed the synthesis of 3-5 layers of graphene of size 50-150 nm.