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Blooms of the toxigenic dinoflagellateKarenia brevisare an almost annual occurrence in the eastern Gulf of Mexico, typically initiating in late summer and early fall months and terminating in late spring or earlier. The question of whether blooms have been expanding in frequency or duration has long been debated. Recently, a Bloom Severity Index (BSI) was developed that captures changes in bloom magnitude based on cell concentrations normalized to maximum observed values. Here, changes in the BSI (severity and bloom duration) were examined for the period from 1970-2019, a period of rapid climate change and increased anthropogenic pressures. This time period encompassed several changes in the Oceanic Niño Index (the El Niño-Southern Oscillation), including a shift from a highly positive to a negative North Atlantic Oscillation in the mid 1990s, bringing with it increased precipitation and more intensive storms. Annual BSI and bloom duration have increased with increasing temperatures, and blooms have also become longer in duration in relation to increased temperatures and river flows since the mid 1990s. As increased precipitation is related to increased nutrient runoff, regional fertilizer use and the anthropogenic nitrogen (N) footprint based on population census data as proxies of nitrogen loads were examined. The duration of severe blooms was highly correlated with the increasing anthropogenic N footprint, especially when BSI values were averaged across multiple years. These relationships highlight the importance of climate changes and of increasing population since the 1980s and help to explain why earlier analyses of nutrient loads and bloom severity were inconclusive. To reduce bloom severity or duration in the future, reductions in N loads and releases from the Caloosahatchee River are needed more than ever to counteract the increasing pressures from climate change. 

Various recent reports, based on different approaches, data sets and time periods, have yielded different conclusions with regard to whether blooms of the Florida red tide dino􀀙agellate, Karenia brevis, have increased over time. Without question, however, there have been a number of recent blooms that have been long lasting, continuing through the summer months normally taken to be outside the ideal temperature niche for K. brevis. Here, using a recently developed bloom severity index, the time series of blooms from 1970 to 2019 is examined, focusing on how monthly patterns have changed over time. More severe blooms have been found since the mid 1990s, now lasting 4- to 5-months longer than in previous decades, a trend related to the Oceanic Ni˜no Index (El Ni˜no -Southern Oscillation). Since the mid-1990s, water temperature anomalies have been related to bloom severity with lags of 3 to 6 months. The most signi􀀼cant temperature increases have occurred in the latter months of the year when K. brevis growth typically is highest. Increased 􀀙ow from the Caloosahatchee River, and its total nitrogen load, are also predictors of recent bloom severity with lags of several months. Cells that survive the nowwarmer winter dry season have adequate nutrients and may experience more favorable nitrogen forms as the summer wet season develops, and as nutrients are recycled, may “over summer”. The stresses of increased warming and increased nutrient pollution on K. brevis blooms will continue to make managing these blooms a challenge for management as climate change trajectories continue. 

Mangroves have evolved at least 27 times across ~20 plant families to survive coastal. To environments characterized by high salinity, inundation, intense light, and strong winds survive these extreme conditions, mangroves exhibit a variety of physiological strategies to tolerate the low osmotic potentials associated with saltwater inundation. Because low osmotic potentials are counterbalanced by high turgor pressure, saltwater exposure exerts mechanical demands on cells. Analyzing 34 mangrove species and 33 closely related inland taxa from 17 plant families, we show that compared to their inland relatives, mangroves have unusually small leaf epidermal pavement cells and thicker cell walls, which together confer greater mechanical strength and tolerance to low osmotic potentials. However, mangroves do not exhibit smaller, more numerous stomata that enable higher photosynthetic rates , suggesting selection on biomechanical integrity rather than on gas exchange capacity. Notably, mangroves break the allometric scaling between the sizes of epidermal pavement cells and stomata typically seen in land plants, highlighting that strong selection in saline habitats can override genome size–mediated scaling rules. Phylogenetic comparative analyses revealed repeated convergent evolution of cell traits across independent transitions from inland to coastal habitats. These anatomical changes constitute a simple but effective adaptation to salt stress. Our findings underscore the role of biomechanics in driving convergent evolution of cell traits and suggest that manipulating cell size and wall properties could be a promising strategy to engineering salt-tolerant plants. 

Cooperative perception (CP) extends detection range and situational awareness in connected and autonomous vehicles by aggregating information from multiple agents. However, attackers can inject fabricated data into shared messages to achieve adversarial attacks. While prior defenses detect object spoofing, object removal attacks remain a serious threat. Nevertheless, prior attacks require unnaturally large perturbations and rely on unrealistic assumptions such as complete knowledge of participant agents, which limits their attack success. In this paper, we present SOMBRA, a stealthy and practical object removal attack exploiting the attentive fusion mechanism in modern CP algorithms. SOMBRA achieves 99% success in both targeted and mass object removal scenarios (a 90%+ improvement over prior art) with less than 1% perturbation strength and no knowledge of benign agents other than the victim. To address the unique vulnerabilities of attentive fusion within CP, we propose LUCIA, a novel trustworthiness-aware attention mechanism that proactively mitigates adversarial features. LUCIA achieves 94.93% success against targeted attacks, reduces mass removal rates by over 90%, restores detection to baseline levels, and lowers defense overhead by 300x compared to prior art. Our contributions set a new state-of-the-art for adversarial attacks and defenses in CP. 

We perform a phenomenological study of helicity-dependent parton distribution functions (PDFs) using small-x helicity evolution equations, incorporating for the first time single-inclusive jet production data in polarized proton-proton (pp) scattering at parton momentum fractions x < 0.1. We also simultaneously include double-longitudinal spin asymmetries in inclusive and semi-inclusive deep-inelastic scattering probing x < 0.1. Employing the polarized small-x pure-glue calculation of pp → gX for the jet production cross section, we modify the large-Nc&Nf KPS-CTT evolution equations by setting Nf = 0 to replicate the large-Nc (pure-glue) limit, while retaining external quark flavors for the spinor field operators. We find that the pp data have a considerable impact on the helicity PDFs at small x, reducing their uncertainties and leading to a total quark and gluon helicity in the proton for x < 0.1 of −0.04 +/-0.23. Combining our analysis with a recent JAM helicity PDF analysis of the world polarized data, which includes x > 0.1, we find a total quark and gluon helicity contribution for x > 10−7 of between 0.02 and 0.51. 

Abstract We study spin dynamics and quantum magnetism with ultracold highly-magnetic atoms. In particular, we focus on the interactions among rare-earth atoms localized in a site of an optical-lattice potential, modeled as a cylindrically symmetric harmonic oscillator in the presence of a weak external magnetic field. The interactions between the atoms are modeled using a multi-channel Hamiltonian containing multiple spin–spin and anisotropic spin–orbit interactions with strengths that depend on the separation between the atoms. We studied the eigenenergies of the atom pair in a site for different lattice geometries and magnetic field strengths. In parallel, we compared these energies to those found from a simplified approach, where the complex-collisional physics is replaced by a two-length-scale pseudopotential containing the contact and magnetic dipole–dipole interactions. The eigenenergies of this model can be computed analytically within the Born approximation as well as non-perturbatively for strong contact interactions. We have shown that the pseudopotential model can accurately represent the multi-channel Hamiltonian in certain parameter regimes of the shape of the site of an optical lattice. The pseudopotential forms the starting point for many-body, condensed matter simulations involving many atom pairs in different sites of an optical lattice. 

Integrated sensing and communication (ISAC) has emerged as a promising paradigm for next-generation (6G) wireless networks, unifying radar sensing and communication on a shared hardware platform. This paper proposes a dynamic array partitioning framework for monostatic ISAC systems to fully exploit available spatial degrees of freedom (DoFs) and reconfigurable antenna topologies, enhancing sensing performance in complex scenarios. We first establish a theoretical foundation for our work by deriving Bayesian Cramér-Rao bounds (BCRBs) under prior distribution constraints for heterogeneous target models, encompassing both point-like and extended targets. Building on this, we formulate a joint optimization framework for transmit beamforming and dynamic array partitioning to minimize the derived BCRBs for direction-of-arrival (DOA) estimation. The optimization problem incorporates practical constraints, including multi-user communication signal-to-interference-plus-noise ratio (SINR) requirements, transmit power budgets, and array partitioning feasibility conditions. To address the non-convexity of the problem, we develop an efficient alternating optimization algorithm combining the alternating direction method of multipliers (ADMM) with semi-definite relaxation (SDR). We also design novel maximum a posteriori (MAP) DOA estimation algorithms specifically adapted to the statistical characteristics of each target model. Extensive simulations illustrate the superiority of the proposed dynamic partitioning strategy over conventional fixed-array architectures across diverse system configurations.