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Mobile weather radars at high frequencies (C, X, K, and W bands) often collect data using staggered pulse repetition time (PRT) or dual pulse repetition frequency (PRF) modes to extend the effective Nyquist velocity and mitigate velocity aliasing while maintaining a useful maximum unambiguous range. These processing modes produce widely dispersed “processor” dealiasing errors in radial velocity estimates. The errors can also occur in clusters in high shear areas. Removing these errors prior to quantitative analysis requires tedious manual editing and often produces “holes” or regions of missing data in high signal-to-noise areas. Here, data from three mobile weather radars were used to show that the staggered PRT errors are related to a summation of the two Nyquist velocities associated with each of the PRTs. Using observations taken during a mature mesoscale convective system, a landfalling tropical cyclone, and a tornadic supercell storm, an algorithm to automatically identify and correct staggered PRT processor errors has been developed and tested. The algorithm creates a smooth profile of Doppler velocities using a Savitzky–Golay filter independently in radius and azimuth and then combined. Errors are easily identified by comparing the velocity at each range gate to its smoothed counterpart and corrected based on specific error characteristics. The method improves past dual PRF correction methods that were less successful at correcting “grouped” errors. Given the success of the technique across low, moderate, and high radial shear regimes, the new method should improve research radar analyses by affording the ability to retain as much data as possible rather than manually or objectively removing erroneous velocities.

Despite concerted global vaccination efforts, wild poliovirus remains endemic in two countries in 2024, Pakistan and Afghanistan. This study uses phylogeographic analysis of poliovirus genetic and epidemiological data from clinical and wastewater surveillance to identify the causes of poliovirus persistence and routes of spread over the last decade (2012 to 2023). Poliovirus genetic diversity declined after 2020, with one of two major genetic clusters dying out, and recent detections are now closely related genetically. High-risk and hard-to-access regions have sustained polio transmission over the past decade, even when interrupted elsewhere. Karachi, one of the most densely populated cities globally, has acted as a hub for the amplification and spread of poliovirus to other regions, many of which we show to be dead-end for onwards transmission despite frequent virus detection. Phylogenetic analysis has long been central to the polio surveillance network, and advancing the approaches used can provide critical epidemiological insights to accelerate eradication efforts.

Monitoring SARS-CoV-2 spread and evolution through genome sequencing is essential in handling the COVID-19 pandemic. Here, we sequenced 892 SARS-CoV-2 genomes collected from patients in Saudi Arabia from March to August 2020. We show that two consecutive mutations (R203K/G204R) in the nucleocapsid (N) protein are associated with higher viral loads in COVID-19 patients. Our comparative biochemical analysis reveals that the mutant N protein displays enhanced viral RNA binding and differential interaction with key host proteins. We found increased interaction of GSK3A kinase simultaneously with hyper-phosphorylation of the adjacent serine site (S206) in the mutant N protein. Furthermore, the host cell transcriptome analysis suggests that the mutant N protein produces dysregulated interferon response genes. Here, we provide crucial information in linking the R203K/G204R mutations in the N protein to modulations of host-virus interactions and underline the potential of the nucleocapsid protein as a drug target during infection. In this study, the authors sequence 892 SARS-CoV-2 genomes from Saudi Arabia and describe population dynamics and importations into the country. They identify a nucleocapsid protein mutation associated with increased viral load and host interactions and characterise its role through biochemical analyses.

For complexes of modules we study two new constructions which we call the pinched tensor product and the pinched Hom. They provide new methods for computing Tate homology Tor^\\operatorname {\\widehat {Tor}} and Tate cohomology Ext^\\operatorname {\\widehat {Ext}}, which lead to conceptual proofs of balancedness of Tate (co)homology for modules over associative rings. Another application we consider is in local algebra. Under conditions of the vanishing of Tate (co)homology, the pinched tensor product of two minimal complete resolutions yields a minimal complete resolution.

Unprecedented public health interventions including travel restrictions and national lockdowns have been implemented to stem the COVID-19 epidemic, but the effectiveness of non-pharmaceutical interventions is still debated. We carried out a phylogenetic analysis of more than 29,000 publicly available whole genome SARS-CoV-2 sequences from 57 locations to estimate the time that the epidemic originated in different places. These estimates were examined in relation to the dates of the most stringent interventions in each location as well as to the number of cumulative COVID-19 deaths and phylodynamic estimates of epidemic size. Here we report that the time elapsed between epidemic origin and maximum intervention is associated with different measures of epidemic severity and explains 11% of the variance in reported deaths one month after the most stringent intervention. Locations where strong non-pharmaceutical interventions were implemented earlier experienced much less severe COVID-19 morbidity and mortality during the period of study. Estimating the effects of non-pharmaceutical interventions for COVID-19 is challenging, partly due to variations in testing. Here, the authors use viral sequence data as an alternative means of inferring intervention effects, and show that delays in implementation resulted in more severe epidemics.

This study presents characteristics of convective systems observed during the Dynamics of the Madden–Julian oscillation (DYNAMO) experiment by the instrumented NOAA WP-3D aircraft. Nine separate missions, with a focus on observing mesoscale convective systems (MCSs), were executed to obtain data in the active and inactive phase of a Madden–Julian oscillation (MJO) in the Indian Ocean. Doppler radar and in situ thermodynamic data are used to contrast the convective system characteristics during the evolution of the MJO. Isolated convection was prominent during the inactive phases of the MJO, with deepening convection during the onset of the MJO. During the MJO peak, convection and stratiform precipitation became more widespread. A larger population of deep convective elements led to a larger area of stratiform precipitation. As the MJO decayed, convective system top heights increased, though the number of convective systems decreased, eventually transitioning back to isolated convection. A distinct shift of echo top heights and contoured frequency-by-altitude diagram distributions of radar reflectivity and vertical wind speed indicated that some mesoscale characteristics were coupled to the MJO phase. Convective characteristics in the climatological initiation region (Indian Ocean) were also apparent. Comparison to results from the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) in the western Pacific indicated that DYNAMO MCSs were linearly organized more parallel to the low-level shear and without strong cold pools than in TOGA COARE. Three-dimensional MCS airflow also showed a different dynamical structure, with a lack of the descending rear inflow present in shear perpendicularly organized TOGA COARE MCSs. Weaker, but deeper updrafts were observed in DYNAMO.

A new parametric tropical cyclone (TC) wind profile model is presented for depicting representative surface pressure profiles corresponding to multiple-maxima wind profiles that exhibit single-, dual-, and triple-maximum concentric-eyewall wind peaks associated with the primary (inner), secondary (first outer), and tertiary (second outer) complete rings of enhanced radar reflectivity. One profile employs five key parameters: tangential velocity maximum, radius of the maximum, and three different shape velocity parameters related to the shape of the profile. After tailoring the model for TC applications, a gradient wind is computed from a cyclostrophic wind formulated in terms of the cyclostrophic Rossby number. A pressure, via cyclostrophic balance, was partitioned into separate pressure components that corresponded to multiple-maxima cyclostrophic wind profiles in order to quantitatively evaluate the significant fluctuations in central pressure deficits. The model TC intensity in terms of varying growth, size, and decay velocity profiles was analyzed in relation to changing each of five key parameters. Analytical results show that the first shape velocity parameter, changing a sharply to broadly peaked wind profile, increases the TC intensity and size by producing the corresponding central pressure fall. An increase (decrease) in the second (third) shape velocity parameter yields the pressure rise (fall) by decreasing (increasing) the inner (outer) wind profile inside (outside) the radius of the maximum. When a single-maximum tangential wind profile evolves to multiple-maxima tangential wind profiles during an eye replacement cycle, the pressure falls and rises are sensitively fluctuated.

Heart rate (HR) is a crucial physiological signal that can be used to monitor health and fitness. Traditional methods for measuring HR require wearable devices, which can be inconvenient or uncomfortable, especially during sleep and meditation. Noncontact HR detection methods employing microwave radar can be a promising alternative. However, the existing approaches in the literature usually use high-gain antennas and require the sensor to face the user’s chest or back, making them difficult to integrate into a portable device and unsuitable for sleep and meditation tracking applications. This study presents a novel approach for noncontact HR detection using a miniaturized Soli radar chip embedded in a portable device (Google Nest Hub). The chip has a 6.5 mm × 5 mm × 0.9 mm dimension and can be easily integrated into various devices. The proposed approach utilizes advanced signal processing and machine learning techniques to extract HRs from radar signals. The approach is validated on a sleep dataset (62 users, 498 h) and a meditation dataset (114 users, 1131 min). The approach achieves a mean absolute error (MAE) of 1.69 bpm and a mean absolute percentage error (MAPE) of 2.67 % on the sleep dataset. On the meditation dataset, the approach achieves an MAE of 1.05 bpm and a MAPE of 1.56 % . The recall rates for the two datasets are 88.53 % and 98.16 % , respectively. This study represents the first application of the noncontact HR detection technology to sleep and meditation tracking, offering a promising alternative to wearable devices for HR monitoring during sleep and meditation.

One of the most challenging problems in predicting the Madden–Julian oscillation (MJO) is the initiation of large-scale convective activity associated with the MJO over the tropical Indian Ocean. The lack of observations is a major obstacle. The Dynamics of the MJO (DYNAMO) field campaign collected unprecedented observations from air-, land-, and ship-based platforms from October 2011 to February 2012. Here we provide an overview of the aircraft observations in DYNAMO, which captured an MJO initiation event from November to December 2011. The National Oceanic and Atmospheric Administration (NOAA) WP-3D aircraft was stationed at Diego Garcia and the French Falcon 20 aircraft on Gan Island in the Maldives. Observations from the two aircraft provide a unique dataset of three-dimensional structure of convective cloud systems and their environment from the flight level, airborne Doppler radar, microphysics probes, ocean surface imaging, global positioning system (GPS) dropsonde, and airborne expendable bathythermograph (AXBT) data. The aircraft observations revealed interactions among dry air, the intertropical convergence zone (ITCZ), convective cloud systems, and air–sea interaction induced by convective cold pools, which may play important roles in the multiscale processes of MJO initiation. This overview focuses on some key aspects of the aircraft observations that contribute directly to better understanding of the interactions among convective cloud systems, environmental moisture, and the upper ocean during the MJO initiation over the tropical Indian Ocean. Special emphasis is on the distinct characteristics of convective cloud systems, environmental moisture and winds, air–sea fluxes, and convective cold pools during the convectively suppressed, transition/onset, and active phases of the MJO.

We initiate the study of modules of constant Jordan type for quantum complete intersections, and prove a range of basic properties. We then show that for these algebras, constant Jordan type is an invariant of Auslander-Reiten components. Finally, we classify modules with stable constant Jordan type [1] or [n-1] in the 2-generator case.