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Abstract BackgroundEctothermic arthropods, like ticks, are sensitive indicators of environmental changes, and their seasonality plays a critical role in the dynamics of tick-borne disease in a warming world. Juvenile tick phenology, which influences pathogen transmission, may vary across climates, with longer tick seasons in cooler climates potentially amplifying transmission. However, assessing juvenile tick phenology is challenging in arid climates because ticks spend less time seeking for blood meals (i.e. questing) due to desiccation pressures. As a result, traditional collection methods like dragging or flagging are less effective. To improve our understanding of juvenile tick seasonality across a latitudinal gradient, we examinedIxodes pacificusphenology on lizards, the primary juvenile tick host in California, and explored how climate factors influence phenological patterns. MethodsBetween 2013 and 2022, ticks were removed from 1527 lizards at 45 locations during peak tick season (March–June). Tick counts were categorized by life stage (larvae and nymphs) and linked with remotely sensed climate data, including monthly maximum temperature, specific humidity and Palmer Drought Severity Index (PDSI). Juvenile phenology metrics, including tick abundances on lizards, Julian date of peak mean abundance and temporal overlap between larval and nymphal populations, were analyzed along a latitudinal gradient. Generalized additive models (GAMs) were applied to assess climate-associated variation in juvenile abundance on lizards. ResultsMean tick abundance per lizard ranged from 0.17 to 47.21 across locations, with the highest abundance in the San Francisco Bay Area and lowest in Los Angeles, where more lizards had zero ticks attached. In the San Francisco Bay Area, peak nymphal abundance occurred 25 days earlier than peak larval abundance. Temporal overlap between larval and nymphal stages at a given location varied regionally, with northern areas showing higher overlap, possibly due to the bimodal seasonality of nymphs. We found that locations with higher temperatures and increased drought stress were linked to lower tick abundances, although the magnitude of these effects depended on regional location. ConclusionsOur study, which compiled 10 years of data, reveals significant regional variation in juvenileI. pacificusphenology across California, including differences in abundance, peak timing, and temporal overlap. These findings highlight the influence of local climate on tick seasonality, with implications for tick-borne disease dynamics in a changing climate. Graphical Abstract 

Abstract The Sunspot Solar Observatory Data Archive (SSODA) stores data acquired with the suite of instruments at the Richard B. Dunn Solar Telescope (DST) from February 2018 to the present. The instrumentation at the DST continues to provide high cadence imaging, spectroscopy, and polarimetry of the solar photosphere and chromosphere across a wavelength range from 3500 Å to 11,000 Å. At the time of writing, the archive contains approximately 374 TiB of data across more than 520 observing days (starting on February 1, 2018). These numbers are approximate as the DST remains operational, and is actively adding new data to the archive. The SSODA includes both raw and calibrated data. A subset of the archive contains the results of photospheric and chromospheric spectropolarimetric inversions using the Hazel-2.0 code to obtain maps of magnetic fields, temperatures, and velocity flows. The SSODA represents a unique resource for the investigation of plasma processes throughout the solar atmosphere, the origin of space weather events, and the properties of active regions throughout the rise of Solar Cycle 25. 

Microservices are a dominant cloud computing architecture because they enable applications to be built as collections of loosely coupled services. To provide greater observability and control into the resultant distributed system, microservices often use an overlay proxy network called a service mesh. A key advantage of service meshes is their ability to implement zero trust networking by encrypting microservice traffic with mutually authenticated TLS. However, the service mesh control plane—particularly its local certificate authority—becomes a critical point of trust. If compromised, an attacker can issue unauthorized certificates and redirect traffic to impersonating services. In this paper, we introduce our initial work in Mazu, a system designed to eliminate trust in the service mesh control plane by replacing its certificate authority with an unprivileged principal. Mazu leverages recent advances in registration-based encryption and integrates seamlessly with Istio, a widely used service mesh. Our preliminary evaluation, using Fortio macro-benchmarks and Prometheus-assisted micro-benchmarks, shows that Mazu significantly reduces the service mesh’s attack surface while adding just 0.17 ms to request latency compared to mTLS-enabled Istio. 

An open question in epidemiology is why transmission is often overdispersed, meaning that most new infections are driven by few infected individuals. For example, around 10% of COVID-19 cases cause 80% of new COVID-19 cases. This overdispersion in parasite transmission is likely driven by intrinsic heterogeneity among hosts, i.e. variable SARS-CoV-2 viral loads. However, host heterogeneity could also indirectly increase transmission dispersion by driving parasite adaptation. Specifically, transmission variation among hosts could drive parasite specialization to highly infectious hosts. Adaptation to rare, highly infectious hosts could amplify transmission dispersion by simultaneously decreasing transmission from common, less infectious hosts. This study considers whether increased transmission dispersion can be, in part, an emergent property of parasite adaptation to heterogeneous host populations. We develop a mathematical model using a Price equation framework to address this question that follows the epidemiological and evolutionary dynamics of a general host–parasite system. The results predict that parasite adaptation to heterogeneous host populations drives high transmission dispersion early in epidemics. Furthermore, parasite adaptation can maintain increased transmission dispersion at endemic equilibria if virulence differs between hosts in a heterogeneous population. More broadly, this study provides a framework for predicting how parasite adaptation determines transmission dispersion for emerging and re-emerging infectious diseases.