Search for: All records

The vorticity-streamfunction formulation for incompressible inviscid fluids is the basis for many fluid simulation methods in computer graphics, including vortex methods, streamfunction solvers, spectral methods, and Monte Carlo methods. We point out that current setups in the vorticity-streamfunction formulation are insufficient at simulating fluids on general non-simply-connected domains. This issue is critical in practice, as obstacles, periodic boundaries, and nonzero genus can all make the fluid domain multiply connected. These scenarios introduce nontrivial cohomology components to the flow in the form of harmonic fields. The dynamics of these harmonic fields have been previously overlooked. In this paper, we derive the missing equations of motion for the fluid cohomology components. We elucidate the physical laws associated with the new equations, and show their importance in reproducing physically correct behaviors of fluid flows on domains with general topology. 

The marine carbonate system is influenced by anthropogenic CO₂uptake, biogeochemical processes, and physical changes that involve freshwater input and removal. Two frequently used parameters to quantify seawater carbonate system are total alkalinity (TA) and total dissolved inorganic carbon (DIC). To account for the physical changes, both TA and DIC are usually normalized to a reference salinity (i.e., nTA and nDIC), and then the relationship between nTA and nDIC is used to identify major biogeochemical processes that regulate the carbonate system, based on process‐specific reaction stoichiometry. However, the theoretical basis of this interpretation has not been holistically examined. In this study, we validated this method under  idealized conditions and discussed the associated assumptions and limitations. Furthermore, we applied this method to interpret field TA and DIC data from a lagoonal estuary in the northwestern Gulf of Mexico. Our results demonstrated that evaluating field data that encompass multiple stations and time periods could be problematic. In addition, various combinations of biogeochemical processes can lead to the same nTA–nDIC relationship, even though the relative importance of each individual process may vary significantly. Therefore, the stoichiometric relationship relying solely on TA and DIC data is not a definitive approach for uncovering dominant biogeochemical processes. Instead, measurements of process‐specific parameters are necessary.

 

Estuarine total alkalinity (TA), which buffers against acidification, is temporally and spatially variable and regulated by complex, interacting hydrologic and biogeochemical processes. During periods of net evaporation (drought), the Mission-Aransas Estuary (MAE) of the northwestern Gulf of Mexico experienced TA losses beyond what can be attributed to calcification. The contribution of sedimentary oxidation of reduced sulfur to the TA loss was examined in this study. Water column samples were collected from five stations within MAE and analyzed for salinity, TA, and calcium ion concentrations. Sediment samples from four of these monitoring stations and one additional station within MAE were collected and incubated between 2018 and 2021. TA, calcium, magnesium, and sulfate ion concentrations were analyzed for these incubations. Production of sulfate along with TA consumption (or production) beyond what can be attributed to calcification (or carbonate dissolution) was observed. These results suggest that oxidation of reduced sulfur consumed TA in MAE during droughts. We estimate that the upper limit of TA consumption due to reduced sulfur oxidation can be as much as 4.60 × 10⁸ mol day⁻¹in MAE. This biogeochemical TA sink may be present in other similar subtropical, freshwater-starved estuaries around the world.

 

Water quality parameters from 2000 to 2020 were used to identify the spatial and temporal sulfate variations in estuaries of the northwestern Gulf of Mexico. Sulfate enrichment relative to conservative mixing was found to be associated with a low river discharge period from 2012 to 2014 in all estuaries. Based on reaction stoichiometry, sedimentary sulfide oxidation holds significant potential for reducing the alkalinity in estuarine waters. However, during this extreme drought, alkalinity enrichment was also occasionally observed in some of the southern estuaries along with sulfate enrichment, and when alkalinity depletion occurred, the magnitude of depletion was usually much less than what would be expected based on sulfide oxidation alone. This discrepancy can be partially explained by carbonate dissolution and other proton removal pathways (e.g., Fe‐oxide dissolution), and by the uncertainties in the model used to estimate alkalinity enrichment/depletion. Under a changing climate, the close coupling between river discharge variation and estuarine sulfate dynamics will significantly impact estuarine carbonate chemistry.

 

We propose a new observable for the measurement of the forward–backward asymmetry$$(A_{FB})$$$\left(A_{\mathrm{FB}}\right)$in Drell–Yan lepton production. At hadron colliders, the$$A_{FB}$$$A_{\mathrm{FB}}$distribution is sensitive to both the electroweak (EW) fundamental parameter$$\sin ^{2} \theta _{W}$$${sin}^2{\theta }_W$, the weak mixing angle, and the parton distribution functions (PDFs). Hence, the determination of$$\sin ^{2} \theta _{W}$$${sin}^2{\theta }_W$and the updating of PDFs by directly using the same$$A_{FB}$$$A_{\mathrm{FB}}$spectrum are strongly correlated. This correlation would introduce large bias or uncertainty into both precise measurements of EW and PDF sectors. In this article, we show that the sensitivity of$$A_{FB}$$$A_{\mathrm{FB}}$on$$\sin ^{2} \theta _{W}$$${sin}^2{\theta }_W$is dominated by its average value around theZpole region, while the shape (or gradient) of the$$A_{FB}$$$A_{\mathrm{FB}}$spectrum is insensitive to$$\sin ^{2} \theta _{W}$$${sin}^2{\theta }_W$and contains important information on the PDF modeling. Accordingly, a new observable related to the gradient of the spectrum is introduced, and demonstrated to be able to significantly reduce the potential bias on the determination of$$\sin ^{2} \theta _{W}$$${sin}^2{\theta }_W$when updating the PDFs using the same$$A_{FB}$$$A_{\mathrm{FB}}$data.

 

Cable bacteria that are capable of transporting electrons on centimeter scales have been found in a variety of sediment types, where their activity can strongly influence diagenetic reactions and elemental cycling. In this study, the patterns of spatial and temporal colonization of surficial sediment by cable bacteria were revealed in two-dimensions by planar pH and H₂S optical sensors for the first time. The characteristic sediment surface pH maximum zones begin to develop from isolated micro-regions and spread horizontally within 5 days, with lateral spreading rates from 0.3 to ~ 1.2 cm day⁻¹. Electrogenic anodic zones in the anoxic sediments are characterized by low pH, and the coupled pH minima also expand with time. H₂S heterogeneities in accordance with electrogenic colonization are also observed. Cable bacteria cell abundance in oxic surface sediment (0–0.25 cm) kept almost constant during the colonization period; however, subsurface cell abundance apparently increased as electrogenic activity expanded across the entire surface. Changes in cell abundance are consistent with filament coiling and growth in the anodic zone (i.e., cathodic snorkels). The spreading mechanism for the sediment pH–H₂S fingerprints and the cable bacteria abundance dynamics suggest that once favorable microenvironments are established, filamentous cable bacteria aggregate or locally activate electrogenic metabolism. Different development dynamics in otherwise similar sediment suggests that the accessibility of reductant (e.g., dissolved phase sulfide) is critical in controlling the growth of cable bacteria.

 

Spike train classification is an important problem in many areas such as healthcare and mobile sensing, where each spike train is a high-dimensional time series of binary values. Conventional re- search on spike train classification mainly focus on developing Spiking Neural Networks (SNNs) under resource-sufficient settings (e.g., on GPU servers). The neurons of the SNNs are usually densely connected in each layer. However, in many real-world applications, we often need to deploy the SNN models on resource-constrained platforms (e.g., mobile devices) to analyze high-dimensional spike train data. The high resource requirement of the densely-connected SNNs can make them hard to deploy on mobile devices. In this paper, we study the problem of energy-efficient SNNs with sparsely- connected neurons. We propose an SNN model with sparse spatiotemporal coding. Our solution is based on the re-parameterization of weights in an SNN and the application of sparsity regularization during optimization. We compare our work with the state-of-the-art SNNs and demonstrate that our sparse SNNs achieve significantly better computational efficiency on both neuromorphic and standard datasets with comparable classification accuracy. Furthermore, com- pared with densely-connected SNNs, we show that our method has a better capability of generalization on small-size datasets through extensive experiments.