Onset of runaway fragmentation of salt marshes

Salt marshes are valuable but vulnerable coastal ecosystems that adapt to relative sea level rise (RSLR) by accumulating organic matter and inorganic sediment. The natural limit of these processes defines a threshold rate of RSLR beyond which marshes drown, resulting in ponding and conversion to open waters. We develop a simplified formulation for sediment transport across marshes to show that pond formation leads to runaway marsh fragmentation, a process characterized by a self-similar hierarchy of pond sizes with power-law distributions. We find the threshold for marsh fragmentation scales primarily with tidal range and that sediment supply is only relevant where tides are sufficient to transport sediment to the marsh interior. Thus the RSLR threshold is controlled by organic accretion in microtidal marshes regardless of the suspended sediment concentration at the marsh edge. This explains the observed fragmentation of microtidal marshes and suggests a tipping point for widespread marsh loss.

Determining threshold value on information gain feature selection to increase speed and prediction accuracy of random forest

Feature selection is a pre-processing technique used to remove unnecessary characteristics, and speed up the algorithm's work process. A part of the technique is carried out by calculating the information gain value of each dataset characteristic. Also, the determined threshold rate from the information gain value is used in feature selection. However, the threshold value is used freely or through a rate of 0.05. Therefore this study proposed the threshold rate determination using the information gain value’s standard deviation generated by each feature in the dataset. The threshold value determination was tested on 10 original datasets transformed by FFT and IFFT and classified using Random Forest. On processing the transformed dataset with the proposed threshold this study resulted in lower accuracy and longer execution time compared to the same process with Correlation-Base Feature Selection (CBF) and a standard 0.05 threshold method. Similarly, the required accuracy value is lower when using transformed features. The study showed that by processing the original dataset with a standard deviation threshold resulted in better feature selection accuracy of Random Forest classification. Furthermore, by using the transformed feature with the proposed threshold excluding the imaginary numbers leads to a faster average time than the three methods compared.

Assessing the Risk of Cascading COVID-19 Outbreaks from Prison-to-Prison Transfers

COVID-19 transmission has been widespread across the California prison system, and at least two of these outbreaks were caused by transfer of infected individuals between prisons. Risks of individual prison outbreaks due to introduction of the virus and of widespread transmission within prisons due to poor conditions have been documented. We examine the additional risk potentially posed by transfer between prisons that can lead to large-scale spread of outbreaks across the prison system if the rate of transfer is sufficiently high. We estimated the threshold number of individuals transferred per prison per month to generate supercritical transmission between prisons, a condition that could lead to large-scale spread across the prison system. We obtained numerical estimates from a range of representative quantitative assumptions, and derived the percentage of transfers that must be performed with effective quarantine measures to prevent supercritical transmission given known rates of transfers occurring between California prisons. Our mean estimate of the critical threshold rate of transfers was 14.59 individuals transferred per prison per month in the absence of quarantine measures. Available data documents transfers occurring at a rate of 60 transfers per prison per month. At that rate, estimates of the threshold rate of adherence to quarantine precautions had mean 75.68%. While the impact of vaccination and possible decarceration measures is unclear, we include estimates of the above quantities given reductions in the probability and extent of outbreaks. We conclude that the risk of supercritical transmission between California prisons has been substantial, requiring quarantine protocols to be followed rigorously to manage this risk. The rate of outbreaks occurring in California prisons suggests that supercritical transmission may have occurred. We stress that the thresholds we estimate here do not define a safe level of transfers, even if supercritical transmission between prisons is avoided, since even low rates of transfer can cause very large outbreaks. We note that risks may persist after vaccination, due for example to variant strains, and in prison systems where widespread vaccination has not occurred. Decarceration remains urgently needed as a public health measure.

Outage Performance Analysis for User Cooperative NOMA with Incremental Hybrid Forwarding Protocols

Non-orthogonal multiple access (NOMA) collaborative communication is extremely beneficial to the users with poor channel conditions. It is essential to examine the performance of different NOMA users with superior cooperative forwarding protocols. This paper addresses the user cooperative NOMA system where one strong user (U2) assists one weak user (U1) to forward messages, and investigates the outage performance of both users with hybrid decode-and-amplify forwarding (HDAF) protocol. First, we derive the outage probability of U2 and U1 with HDAF. Secondly, we provide the closed-form expression for outage probability of U1 with the incremental hybrid decode-and-amplify forward (IHDAF) protocol at U2, which can further enhance the outage performance of U1 compared with HDAF. Moreover, we also present the system throughput expression and provide deep analysis on the effect of different forwarding protocols. Numerical results and Monte Carlo simulations jointly confirm the correctness of all the analytic derivations. In addition to saving the energy consumption of U2, IHDAF can make U1 achieve superior outage performance to HDAF. However, the system throughput almost overlap for both schemes given a threshold rate pair.

Region Based Segmentation using TCRM

Water Resource is one of the essential supplies of the globe environment which needs to be regularly observed. There is rising need and necessitate in research of water region detection due to the unpredicted natural calamity that guide to financial, environment and individual sufferers. Assessment of water region (WR) and study on its characteristic is very fundamental step for many scheduling, particularly for country like India which made frequent changes on WR. Basically, recognize the WR from Remote sensing images is one of the impressive steps of water possessions organization for a country where it has been used superior than decades for WR detection. Techniques of WR extraction can be examine into three groups: Texture Conditional Rotation Mean (TCRM), feature extraction using TCRM algorithms, Region based segmentation. These methods, though, are of mathematical and statistical approach and little of them look at important uniqueness of multispectral image which is found on land object radiance absorption performance in every sensing spectral bands. In visible and infrared bands, the WR spectral absorption characteristics differ very much from the other earth substance. There are different data bases for the study area which consists of different form and exposure. Results show that TCRM presents adequate well detection for WR as speedy and receiving high accuracy with the suitable threshold rate

Effective productivity management of mixed flower farms

Purpose The purpose of this paper is to investigate the issue of low yields in the packinghouses of green ornamentals and cut flowers due to the high rate of crops waste. Waste may be caused by pests, diseases and extreme weather or environmental conditions that are not under the farmer’s control. Other causes may relate to work processes as follows: irrigation, spraying, harvesting, handling, transportation, sorting, bundling and packaging. Design/methodology/approach The farm under study is a private owned business managed by the owner’s family members with growing area of 22 ha and eight daily workers. The farm produces about 2.5m units (flower stems) per year. The farm represents a typical flower farm in Israel. A costing model and decision rules were developed to identify the critical waste rate that will consider being economic to ship to the market. The model takes into account the production process, the production yield, the operational costs and sales price and calculates the breakeven point. A simulation model was developed to verify the relationships between waste rate to the total process time per stem and flow time. Findings Results show that the critical waste rate for Ruscus, Antirrhinum, Aralia and Aspidistra crops is 16, 74, 22 and 39 percent, respectively. The total process time per harvested stem decreases as the waste rate increases. Originality/value A working model was developed to determine the waste threshold rate and support the farmer in day-to-day economic decisions regarding shipment to the market and effective management of his workers.