Agilent Technologies

About: Agilent Technologies is a company organization based out in Santa Clara, California, United States. It is known for research contribution in the topics: Signal & Mass spectrometry. The organization has 7398 authors who have published 11518 publications receiving 262410 citations. The organization is also known as: Agilent Technologies, Inc..

Occurrence of Microplastic Pollution at Oyster Reefs and Other Coastal Sites in the Mississippi Sound, USA: Impacts of Freshwater Inflows from Flooding.

Abstract: Much of the seafood that humans consume comes from estuaries and coastal areas where microplastics (MPs) accumulate, due in part to continual input and degradation of plastic litter from rivers and runoff. As filter feeders, oysters (Crassostrea virginica) are especially vulnerable to MP pollution. In this study, we assessed MP pollution in water at oyster reefs along the Mississippi Gulf Coast when: (1) historic flooding of the Mississippi River caused the Bonnet Carre Spillway to remain open for a record period of time causing major freshwater intrusion to the area and deleterious impacts on the species and (2) the spillway was closed, and normal salinity conditions resumed. Microplastics (~25 µm–5 mm) were isolated using a single-pot method, preparing samples in the same vessel (Mason jars) used for their collection right up until the MPs were transferred onto filters for analyses. The MPs were quantified using Nile Red fluorescence detection and identified using laser direct infrared (LDIR) analysis. Concentrations ranged from ~12 to 381 particles/L and tended to decrease at sites impacted by major freshwater intrusion. With the spillway open, average MP concentrations were positively correlated with salinity (r = 0.87, p = 0.05) for sites with three or more samples examined. However, the dilution effect on MP abundances was temporary, and oyster yields suffered from the extended periods of lower salinity. There were no significant changes in the relative distribution of MPs during freshwater intrusions; most of the MPs (>50%) were in the lower size fraction (~25–90 µm) and consisted mostly of fragments (~84%), followed by fibers (~11%) and beads (~5%). The most prevalent plastic was polyester, followed by acrylates/polyurethanes, polyamide, polypropylene, polyethylene, and polyacetal. Overall, this work provides much-needed empirical data on the abundances, morphologies, and types of MPs that oysters are exposed to in the Mississippi Sound, although how much of these MPs are ingested and their impacts on the organisms deserves further scrutiny. This paper is believed to be the first major application of LDIR to the analysis of MPs in natural waters.

Method facilitating inter-mode handoff

Abstract: A cellular handset supports non compressed handover for different frequency ranges, and different wireless standards.

Pull detach mechanism for fiber optic transceiver module

Abstract: A delatch mechanism includes wedges that reside in pockets adjacent to a post on a module when the module is latched in a cage. Pulling on a handle pulls the wedges out of the pockets so that the wedges rise and lift a tab. Pulling the delatch mechanism to a limit of its motion frees the post on the module from the tab, and further pulling transfers to the module to pull the module out of the cage. The delatch mechanism can include a spring system that returns the wedges to their pockets for latching, allows movement of the wedges relative to the module for lifting of the tab, and locks into the module to pull the module free of the cage. Handles for the latch mechanism can include a bail, a flexible tab, or fixed handle that is part of an integrated structure including the wedges.

Method and system for predicting multi-variable outcomes

Abstract: Systems methods and recordable media for predicting multi-variable outcomes based on multi-variable inputs (item 902). Additionally, the models described can be used to predict the multi-variable inputs themselves, based on the multi-variable inputs, providing a smoothing function, acting as a noise filter. Both multi-variable inputs and multi-variable outputs may be simultaneously predicted, based upon the multi-variable inputs. The models find a critical subset of data points, or 'tent poles' (item 912) to optimally model all outcome variables simultaneously to leverage communalities among outcomes (item 914).