Development of an unstructured grid, finite volume eutrophication model for the shallow water coastal bay: Application in the Lynnhaven River Inlet system

The shallow water region is an important portion of the estuarine and coastal waters, since it encompasses the entire land-water margin as the buffer zone and supports one of the most productive ecosystems. When light can penetrate to the sediment, it triggers the benthic microalgae community to perform photosynthesis, resulting in a benthic-pelagic exchange flux different from that of the deeper water. This study utilized the laboratory-measured benthic flux, and a suite of well-calibrated numerical models to examine the eutrophication process in the Lynnhaven River Inlet system with special emphasis on: the role played by benthic microalgae, and nutrient budgets (sources, sinks, and pathways) of the system. An unstructured grid hydrodynamic model UnTRIM developed for the shallow water environment was applied to the Lynnhaven to quantify the transport time scale and as the input for the water quality model. Based on the skill assessment result, it was clear that the presence of benthic microalgae is indispensable for an accurate and realistic calibration of the water quality model. Analysis of field samples in the laboratory experiments demonstrated that benthic microalgae performed photosynthesis under light conditions in surficial sediments, resulting in the net uptake of nutrients and the release of oxygen both to the overlying water column and down to the sediment. Based on the results of annual nutrient budgets, it was shown that the major external source for nitrogen and phosphorus was from nonpoint source loadings. There were three comparable sinks: export to the Bay, burial in the deep sediment, and ditrification in the case of nitrogen. One of the major pathways for nitrogen and phosphorus was the internal recycling. The regenerated dissolved nutrients that were recycled in the water column were more than two times larger than the current total nutrient external loadings. Sensitivity tests showed that, due to their retention capacity, benthic microalgae\u27s presence could decrease the overall export to the Bay, enhance the internal recycling, and increase the denitrification rate in the sediment

HurriCast: An Automatic Framework Using Machine Learning and Statistical Modeling for Hurricane Forecasting

Hurricanes present major challenges in the U.S. due to their devastating impacts. Mitigating these risks is important, and the insurance industry is central in this effort, using intricate statistical models for risk assessment. However, these models often neglect key temporal and spatial hurricane patterns and are limited by data scarcity. This study introduces a refined approach combining the ARIMA model and K-MEANS to better capture hurricane trends, and an Autoencoder for enhanced hurricane simulations. Our experiments show that this hybrid methodology effectively simulate historical hurricane behaviors while providing detailed projections of potential future trajectories and intensities. Moreover, by leveraging a comprehensive yet selective dataset, our simulations enrich the current understanding of hurricane patterns and offer actionable insights for risk management strategies.Comment: This paper includes 7 pages and 8 figures. And we submitted it up to the SC23 workshop. This is only a preprintin

Transmission Routes of the Microbiome and Resistome from Manure to Soil and Lettuce

The land application of animal manure can introduce manure microbiome and resistome to croplands where food crops are grown. The objective of this study was to characterize the microbiome and resistome on and in the leaves of lettuce grown in manured soil and identify the main transmission routes of microbes and antibiotic resistance genes (ARGs) from soil to the episphere and endosphere of lettuce. Shotgun metagenomic results show that manure application significantly altered the composition of the microbiome and resistome of surface soil. SourceTracker analyses indicate that manure and original soil were the main source of the microbiome and resistome of the surface soil and rhizosphere soil, respectively. Manure application altered the microbiome and resistome in the episphere of lettuce (ADONIS p \u3c 0.05), and surface soil accounted for ~81% of the microbes and ~62% of the ARGs in episphere. Manure application had limited impacts on the microbiome and resistome in the endosphere (ADONIS p \u3e 0.05). Our results show that manure-borne microbes and ARGs reached the episphere primarily through surface soil and some epiphytic microbes and ARGs further entered the endosphere. Our findings can inform the development of pre- and postharvest practices to minimize the transmission of manure-borne resistome from food crops to consumers

Experimenting adaptive services in sea-cloud innovation environment

Most of existing network testbeds can only support the experimentation of L2~L4 forwarding protocols, leaving the evaluation of L4~L7 applications still a tremendous challenge. This paper pioneers to present the design of sea-cloud innovation environment (SCIE) based on the software defined networking (SDN) and network functions virtualization (NFV) paradigms to support adaptive service-oriented experimentation, where the virtualized network functions (VNFs) can be implemented or deimplemented dynamically on network devices according to ondemand requirements. The experimentation is running to form an adaptive chain of network functions, which can be achieved by the protocol oblivious forwarding (POF) via user-defined fields and generic flow instruction set to forward the data to appropriate devices with VNFs. In SCIE, we demonstrate the experimentation of DPI service with on-demand requirement of security check

Spatial-Temporal Variability of Soil Organic Matter in Urban Fringe over 30 Years: A Case Study in Northeast China.

The study on soil organic matter (SOM) is of great importance to regional cultivated land use and protection. Based on data collected via continuous and high-density soil samples (0-20 cm) and socio-economic data collected from household survey and local bureau of statistics, this study employs geostatistics and economic statistical methods to investigate the spatial-temporal variation of SOM contents during 1980-2010 in the urban fringe of Sujiatun district in Shenyang City, China. We find that: (1) as to temporal variation, SOM contents in the study sites decreased from 30.88 g/kg in 1980 to 22.63 g/kg in 2000. It further declined to 20.07 g/kg in 2010; (2) in terms of spatial variation, the closer to city center, the more decline of SOM contents. Contrarily, SOM contents could even rise in outer suburb area; and (3) SOM content variation may be closely related to human factors such as farmers’ land use target and behaviour including inputs of chemical and organic fertilizers, types of crops and etc. These findings are conductive to grasp the overall trend of SOM variation and the influence of farmers’ land use behaviour on it. Furthermore, they could provide support for policymakers to agricultural planning and land use monitoring, which consequently aids the improvement of soil quality and food production in the urban fringe areas

Optimal Choices for the E-Tailer with Inventory Rationing, Hybrid Channel Strategies, and Service Level Constraint under Multiperiod Environments

This paper investigates optimal choices for the e-tailer with inventory rationing, hybrid channel strategies, and service level constraint under multiperiod environment. Based on different operational conditions, five mathematical models are proposed for the e-tailer who faces two types of fuzzy demand and a framework is designed to illustrate the e-tailer’s operation in different models. This paper presents the advantages of inventory rationing and hybrid channel strategies and analyzes the influences of channel differences variability on optimal choices for the e-tailer, where the channel differences include margin difference of priority and margin difference of channel. Through computer simulation, the optimal choices for the e-tailer under different multiperiod environments are obtained, and the influences of margin difference of priority and margin difference of channel on the e-tailer’s optimal choices are also examined. Experiment results show that the pure-play drop shipping model and the hybrid channel with inventory rationing model are the optimal choices for the e-tailer; these findings have valuable guiding significance for the e-tailer to make optimal tactical decisions under multiperiod environment

Composting reduces the risks of resistome in beef cattle manure at the transcriptional level

Transcriptomic evidence is needed to determine whether composting is more effective than conventional stockpiling in mitigating the risk of resistome in livestock manure. The objective of this study is to compare composting and stockpiling for their effectiveness in reducing the risk of antibiotic resistance in beef cattle manure. Samples collected from the center and the surface of full-size manure stockpiling and composting piles were subject to metagenomic and metatranscriptomic analyses. While the distinctions in resistome between stockpiled and composted manure were not evident at the DNA level, the advantages of composting over stockpiling were evident at the transcriptomic level in terms of the abundance of antibiotic resistance genes (ARGs), the number of ARG subtypes, and the prevalence of high-risk ARGs (i.e., mobile ARGs associated with zoonotic pathogens). DNA and transcript contigs show that the pathogen hosts of high-risk ARGs included Escherichia coli O157:H7 and O25b:H4, Klebsiella pneumoniae, and Salmonella enterica. Although the average daily temperatures for the entire composting pile exceeded 55°C throughout the field study, more ARG and ARG transcripts were removed at the center of the composting pile than at the surface. This work demonstrates the advantage of composting over stockpiling in reducing ARG risk in active populations in beef cattle manure

BEV-Net: Assessing Social Distancing Compliance by Joint People Localization and Geometric Reasoning

Social distancing, an essential public health measure to limit the spread of contagious diseases, has gained significant attention since the outbreak of the COVID-19 pandemic. In this work, the problem of visual social distancing compliance assessment in busy public areas, with wide field-of-view cameras, is considered. A dataset of crowd scenes with people annotations under a bird's eye view (BEV) and ground truth for metric distances is introduced, and several measures for the evaluation of social distance detection systems are proposed. A multi-branch network, BEV-Net, is proposed to localize individuals in world coordinates and identify high-risk regions where social distancing is violated. BEV-Net combines detection of head and feet locations, camera pose estimation, a differentiable homography module to map image into BEV coordinates, and geometric reasoning to produce a BEV map of the people locations in the scene. Experiments on complex crowded scenes demonstrate the power of the approach and show superior performance over baselines derived from methods in the literature. Applications of interest for public health decision makers are finally discussed. Datasets, code and pretrained models are publicly available at GitHub.Comment: Published as a conference paper at International Conference on Computer Vision, 202

A Kernel-space POF virtual switch

Protocol Oblivious Forwarding (POF) aims at providing a standard southbound interface for sustainable Software Defined Networking (SDN) evolvement. It overcomes the limitations of popular Open Flow protocols (an existing widely-adopted southbound interface), through the enhancement of SDN forwarding plane. This paper pioneers the design and implementation of a Kernel-space POF Virtual Switch (K_POFVS) on Linux platform. K_POFVS can improve the packet processing speed, through fast packet forwarding and the capability of adding/deleting/modifying protocol fields in kernel space. In addition, it is able to enhance flow table matching speed, by separating the mask table (consisting of flow entry masks used to figure out the matching field) and the flow table under a caching mechanism. Furthermore, K_POFVS can achieve efficient communication between the kernel space and the user space, via extending the Netlink communication between them. Experimental results show that K_POFVS can provide much better performance than existing user-space POF virtual switches, in terms of packet forwarding delay, packet processing delay and packet transmission rateThis work is partially supported by the National Program on Key Basic Research Project of China (973 Program) under Grant No. 2012CB315803, the Strategic Priority Research Program of the Chinese Academy of Sciences under grant No. XDA06010306, the National Natural Science Foundation of China under Grant No. 61303241, and the University of Exeter’s Innovation Platform – Link Fund under Award No. LF207