Pool Type Research Articles

Construction of stock portfolios based on k-means clustering of continuous trend features

How to construct a promising portfolio to reduce the risk of investment and to improve returns has markedly attracted scholars’ attention. Firstly, it is hard to choose prospective set of assets for the portfolio. When the number of candidate stock pools is relatively large, it is challenging to screen out qualified stocks to construct the portfolio and to calculate the corresponding weights. Traditional portfolio theories, such as risk parity and Markowitz’s portfolio theories, are only used to calculate the corresponding weights in the given stock portfolio, and cannot be used to automatically select good stocks in a large stock pool. Secondly, for these theories, the weights are calculated based on the covariance relationship between different stocks, and the differences caused by alternative industries and market data are not taken into account. Thirdly, when metrics, including the Sharpe ratio, are used to evaluate the investment results, these theories do not consider the risk aversion in the downward stage of stocks. In order to address the three problems above, this paper aimed to propose a portfolio construction method based on the continuous trend characteristics of the market. For this purpose, the k-means clustering algorithm was used to cluster the stocks, divide the different types of stock pools, and revise the calculation of returns for the Sharp ratio based on the continuous trend characteristics of the market, so as to avoid the downward risk. Finally, combined with inverse volatility weighting, risk parity, and Markowitz’s portfolio theories, the required weights were calculated. Through the experiments, the optimal number of stocks in the portfolio was obtained. The results of both the statistics and experiments confirmed the superiority of the proposed method.

A DDQN Path Planning Algorithm Based on Experience Classification and Multi Steps for Mobile Robots

Constrained by the numbers of action space and state space, Q-learning cannot be applied to continuous state space. Targeting this problem, the double deep Q network (DDQN) algorithm and the corresponding improvement methods were explored. First of all, to improve the accuracy of the DDNQ algorithm in estimating the target Q value in the training process, a multi-step guided strategy was introduced into the traditional DDQN algorithm, for which the single-step reward was replaced with the reward obtained in continuous multi-step interactions of mobile robots. Furthermore, an experience classification training method was introduced into the traditional DDQN algorithm, for which the state transition generated by the mobile robot–environment interaction was divided into two different types of experience pools, and experience pools were trained by the Q network, and the sampling proportions of the two experience pools were updated through the training loss. Afterward, the advantages of a multi-step guided DDQN (MS-DDQN) algorithm and experience classification DDQN (EC-DDQN) algorithm were combined to develop a novel experience classification multi-step DDQN (ECMS-DDQN) algorithm. Finally, the path planning of these four algorithms, including DDQN, MS-DDQN, EC-DDQN, and ECMS-DDQN, was simulated on the OpenAI Gym platform. The simulation results revealed that the ECMS-DDQN algorithm outperforms the other three in the total return value and generalization in path planning.

Numerical study of coupled slosh modes in a 3D vessel subjected to multi-directional excitations

Present study explores liquid sloshing in a three-dimensional (3D) rectangular tank subjected to surge and coupled surge, sway and heave excitations. A number of applications of practical interest in nuclear systems such as, spent fuel storage tanks, fast reactor vessels, pool type coolant etc will be benefited from such analysis. Effect of harmonic excitation is investigated emphasizing finite liquid depth when the internal resonance condition 1:1 is satisfied between the natural frequencies of dominant modes (1,0), (0,1) and (0,2). The numerical model was validated against available in–house experimental shake table studies. Temporal snapshots of velocity magnitudes and free surface time history at different locations are presented when the tank is excited under two different loading conditions. The amplification of diagonal slosh modes were observed under planar excitation. This analysis assumes significance, as the attendant hydrodynamic forces could eventually cause fatigue failure of the tank structure. Non-linear square-like, swirling and wave breaking features were observed, when the tank was subjected to earthquake excitation.

Validation of ANSYS Model of Experimental Test Rig Simulating the Flow Inversion in RRs

The experimental setup was built to simulate the flow inversion in natural circulation loops in research reactors (RRs). In an effort to recognize the buildup of natural circulation in RRs, pool type upward flow after the pump coasts down due to power loss, by Abdel-Latif et al. [1], was investigated. The setup consists of two vertically stacked pipes that simulate the two branches, one of which contains a test section that is composed of electrically heated, corresponding channels that simulate the core. The second one, represents the portion of the coming back pipe that is involved in the growing of core natural circulation. Several experimental tests under various conditions as the branch’s initial temperature are performed. The channel’s coolant and surface temperatures were monitored. In this study, the thermal-hydraulic (TH) behaviour of the setup is complemented by theoretical analysis using the ANSYS Fluent 17.2 code. The ANSYS Fluent model is validated against the measured values. Typically, the setup is nodlized and a code input is being prepared. The results show that ANSYS Fluent 17.2 qualitatively predicts the thermal hydraulic behaviour and associated flow inversion phenomenon of such facilities. There is a difference between the predicted and measured values, especially for the channel’s surface temperature.

Influence of check dams on the activity pattern and morphometric traits of overwintering tadpoles in the Western Himalaya

Delaying metamorphosis in low-temperature conditions by anuran larvae known as ‘overwintering’ have been poorly studied, especially in terms of habitat ecology and behavioural aspects. The present study investigates some of the ecological aspects of overwintering tadpoles of the genus Nanorana in the Western Himalaya in an anthropogenically modified stream where check dams have altered the natural habitat, which can potentially influence the amphibian ecology. We present insights on the influence of check dams on the tadpole activity pattern and morphometric traits useful in the conservation planning of the narrowly distributed and understudied species, which are most sensitive to habitat modification.We monitored natural and modified pool habitats in the stream during winter and post-winter seasons based on the visual density of tadpoles to assess the diurnal and seasonal emergence pattern with associated habitat variables. Generalized Linear Mixed Modeling (GLMM) was used to understand the influence of various habitat variables on the visible density of tadpoles. Fine-scale temporal scan sampling of tadpoles was carried out to complement the understanding of the visible density variation and analyzed using circular plots and activity overlap estimation. Variation in morphometric traits was assessed using field morphometry and photogrammetry.Mean tadpole visible density at nighttime was higher in modified pools than natural pools during winter, but there was no statistically significant difference during daytime; the nocturnal pattern changed in the post-winter, where visible density was higher in natural pools. Tadpole visible density was influenced by the interaction of mean canopy cover with water temperature, instream cover items richness, mean canopy cover percentage, water temperature, leaf litter depth, water velocity and interaction of time of the day with pool modification. Tadpole activity patterns varied significantly between pool types during post-winter, where modified pool population increased daytime activity and thus the activity overlap reduced from winter (90.8%) to post-winter (64.5%). During both seasons, the mean body size of the natural pool population was significantly lower than the modified pool population; mean relative tail length was significantly lower in natural pools during post-winter; mean tail depth was significantly lower in natural pools during winter.The study presents evidence of the influence of anthropogenic habitat alterations on behaviour and morphometric traits of overwintering tadpoles, which needs to be further investigated. We also discuss the variation in nocturnal emergence, habitat selection and morphometric trait patterns in the modified habitat, potential reasons and similar behaviour in other aquatic organisms, which need to be considered while developing conservation strategies for the overwintering tadpoles in the region.

A collaboration strategy in the mining pool for proof-of-neural-architecture consensus

In most popular public accessible cryptocurrency systems, the mining pool plays a key role because mining cryptocurrency with the mining pool turns the non-profitable situation into profitable for individual miners. In many recent novel blockchain consensuses, the deep learning training procedure becomes the task for miners to prove their workload. Thus, the computation power of miners will not purely be spent on the hash puzzle. In this way, the hardware and energy will support the blockchain service and deep learning training simultaneously. While the incentive of miners is to earn tokens, individual miners are motivated to join mining pools to become more competitive. In this paper, we are the first to demonstrate a mining pool solution for novel consensuses based on deep learning.The mining pool manager partitions the full searching space into subspaces, and all miners are scheduled to collaborate on the Neural architecture search (NAS) tasks in the assigned subspace. Experiments demonstrate that the performance of this type of mining pool is more competitive than that of an individual miner. Due to the uncertainty of miners' behaviors, the mining pool manager checks the standard deviation of the performance of high reward miners and prepares backup miners to ensure completion of the tasks of high reward miners.

Numerical simulation on the thermal stratification in the lead pool of lead-cooled fast reactor (LFR)

Lead-cooled fast reactor (LFR) adopts the liquid metal lead as the coolant and is beneficial to the fuel sustainability and high safety. LFR is suffering from the serious thermal stratification due to the pool type design and high operation temperature, leading to the threatening thermal stress on the structure. In this paper, the three-dimensional CFD model of ELSY lead pool is established and the thermal stratification phenomena under the forced and natural circulations are investigated. The results show that under steady-state conditions, ELSY has temperature stratification along the wall in the upper lead pool where the steam generator is located, and a high temperature concentration zone and a speed stagnant zone in the lower plenum. Under natural circulation conditions, when the water decay heat removal system (W-DHR), isolation condenser (IC) and reactor vessel air cooling system (RVACS) are put into operations, there is also obvious temperature stratification in the steam generator area. This paper puts forward some corresponding optimization suggestions on the problems in the simulation. The above results can provide an appropriate and effective reference for the design of ELSY in the future.

Ketosis in Dairy Cows during Early Lactation - Detection in Pooled Blood Serum Samples

Background: Ketosis is the most important metabolic disease with prevalence from 15 to 45%. Ketosis is diagnosed using a metabolic profile. Due to the high prevalence, it is necessary to determine a large number of metabolic profiles within farm, which represents an additional cost, so the implementation of pooled serum in assessing the metabolic status of cows was examined. The aim of this study was to validate and evaluate the influence of the relative position (Z-score) of the value of pooled sample metabolic parameters within the known reference value of healthy cows in the detection of ketosis in herd during early lactation.Materials, Methods & Results: The experiment has been carried out using blood samples collected by puncture of coccygeal vein from 50 ketotic and 50 healthy cows. Laboratory analysis includes determination of beta-hydroxybutyrate-BHB, non-esterified fatty acids-NEFA, cholesterol-CHOL, triglycerides-TGC, glucose-GLU, albumin-ALB, total protein-TPROT, UREA, Ca, P, total bilirubin-TBIL and aspartat aminotransferase-AST. The pooled serum was made from 10 individual samples originating from 10 different cows. A serum aliquot of 0.1 mL was taken from each sample, and a 1 mL volume of pooled serum was finally formed. Three types of serum pools were made: 1) 30 pooled sample were from ketosis; 2) 30 pooled sample were from healthy cows and 3) 60 pooled samples containing mixed sera of healthy cows and cows with ketosis were made as follows: 10 pools contain 10% to 60% of ketotic cows (1/10 to 6/10 samples). Statistical analysis includes: a) difference in metabolite concentration and Z-score in pooled sample and arithmetic mean individual sample in healthy and ketotic cow, b) correlation between Z-score of pooled sample and arithmetic mean of individual sample, c) ability of Z-score of metabolite to divide ketotic from healthy cow, d) correlation between Z-score and % of ketotic cow in pooled sample; and e) calculation of 95%CI of pooled sample Z-scores for each % of ketotic cow in pools. Z-score and all analysis were calculated for each metabolic parameter. The results of the study show that the mean values and Z-scores of the pool and the calculated average value of the individual samples participating in that pool differ significantly in healthy cows and cows in ketosis, except for TPROT and Ca. A higher value and a higher Z-score were found for BHB, NEFA, UREA, TBIL and AST, and a lower value and a lower Z-score for TGC, CHOL, GLU, ALB and P in ketotic cows compared to healthy cows. The value of the Z-score of the pooled sample and the calculated mean values of individual samples participating in the pool are highly correlated with each other (coefficient of determination over 99%). Z-score of metabolites in the pooled sample can be used to distinguish healthy from ketotic cows (ROC AUC= 0.711 to 0.989), except for TPROT and Ca. The Z-score value of the pooled sample shows a linear correlation with the percentage of ketotic cows in the pool and the reference ranges of Z-scores change significantly as a function of the percentage of ketosis cows.Discussion: Modern research on the metabolic profile in cows requires obtaining a large amount of information from as few samples as possible. The advantages of using the Z-score are reflected in the following: this score does not depend on the absolute value of the metabolite, but on the position within the known population reference value, Z-score of sample and the arithmetic mean of individual samples included in the same pool are almost identical, the Z-score of these 2 groups of results is ideally correlated, the Z-score significantly correlates with the % of ketosis samples in the pooled sample. The use of pooled sample Z-score can be a useful in a herd level assessment of metabolic status and detection of ketosis as most important metabolic disease in dairy cows.Keywords: dairy cattle, ketosis, metabolic disease, metabolic profile, pooled serum, z-score, diagnostics.

Simulation of the gamma dose rate in a loss of pool water accident of the second Egyptian research reactor ET-RR-2

Abstract The second Egyptian research reactor ET-RR-2, is a pool type reactor. A sudden loss of pool water would leave the core region uncovered. The reactor core is surrounded by chimney chambers with water isolated from the pool water. This accident would lead to significant external doses. A model is developed and used to calculate the dose rates for key access-areas and traffic plans from indirect line of sight of the core which have a maximum dose rate. The model developed uses the discrete ordinate method as implemented in the code DOT3.5.

Desiccation risk favours prevalence and diversity of tardigrade communities and influences their trophic structure in alpine ephemeral rock pools

Rock pools are ephemeral freshwater habitats characterized by their small size, well-defined boundaries, and periodic desiccation, making them ideal model systems to answer numerous ecological questions. Although there are numerous studies on rock pool fauna around the world, tardigrades have only rarely been recorded. We conducted the first tardigrade-focused study on rock pools by quantitatively extracting and classifying them from rock pools in the Italian Apennines. Rock pools were divided into three types, based on maximum duration of their inundation period. Following the patterns usually observed with rock pool invertebrates, we tested the hypothesis that desiccation has a negative effect on prevalence, abundance, and diversity of tardigrades, and thus could alter the trophic structure of their communities. In contrast to what is commonly found for other animal groups in the same type of habitat, we found that tardigrades were more diverse and prevalent in shallower, more desiccation prone, rock pools. Moreover, the trophic structure of tardigrade communities was different among the different pool types. Lastly, we also provide DNA barcodes of the most commonly found taxa. Ultimately, our study demonstrates that tardigrade communities in rock pools provide a valuable model system for the study of abiotic factors influencing meiofauna communities.

Carbon concentrations in natural and restoration pools in blanket peatlands

AbstractOpen‐water perennial pools are common natural features of peatlands globally, and peatland restoration often results in new pool creation, yet the concentrations of different forms of aquatic carbon (C) in natural and artificial restoration pools are not well studied. We compared carbon concentrations in both natural pools and restoration pools (4–15 years old) on three blanket peatlands in northern Scotland. At all sites, restoration pools were more acidic and had mean dissolved organic carbon (DOC) concentrations in restoration pools of 23, 22, and 31 mg L−1 compared with natural pool means of 11, 11 and 15 mg L−1 respectively across the three sites. Restoration pools had a greater fulvic acid prevalence than the natural pools and their DOC was more aromatic. Restoration pools were supersaturated with dissolved CO2 at around 10 times atmospheric levels, whereas for natural pools, CO2 concentrations were just above atmospheric levels. Dissolved CH4 concentrations were not different between pool types, but were ~200 times higher than atmospheric levels. Regular sampling at one of the peatland sites over 2.5 years showed that particulate organic carbon (POC) concentrations were generally below 7 mg L−1 except during the warm, dry summer of 2013. At this regularly‐sampled site, natural pools were found to process DOC so that mean pool outflow concentrations in overland flow were significantly lower than mean inflow DOC concentrations. Such an effect was not found for the restoration pools. Soil solution and pool water chemistry, and relationships between DOC and CO2 concentrations suggest that different processes are controlling the transformation of C, and therefore the form and amount of C, in natural pools compared to restoration pools.

Optimal pricing for electricity retailers based on data-driven consumers’ price-response

In the present work, we tackle the problem of finding the optimal price tariff to be set by a risk-averse electric retailer participating in the pool and whose customers are price sensitive. We assume that the retailer has access to a sufficiently large smart-meter dataset from which it can statistically characterize the relationship between the tariff price and the demand load of its clients. Three different models are analyzed to predict the aggregated load as a function of the electricity prices and other parameters, as humidity or temperature. More specifically, we train linear regression (predictive) models to forecast the resulting demand load as a function of the retail price. Then, we will insert this model in a quadratic optimization problem which evaluates the optimal price to be offered. This optimization problem accounts for different sources of uncertainty including consumer’s response, pool prices and renewable source availability, and relies on a stochastic and risk-averse formulation. In particular, one important contribution of this work is to base the scenario generation and reduction procedure on the statistical properties of the resulting predictive model. This allows us to properly quantify (data-driven) not only the expected value but the level of uncertainty associated with the main problem parameters. Moreover, we consider both standard forward-based contracts and the recently introduced power purchase agreement contracts as risk-hedging tools for the retailer. The results are promising as profits are found for the retailer with highly competitive prices and some possible improvements are shown if richer datasets could be available in the future. A realistic case study and multiple sensitivity analyses have been performed to characterize the risk-aversion behavior of the retailer considering price-sensitive consumers. It has been assumed that the energy procurement of the retailer can be satisfied from the pool and different types of contracts. The obtained results reveal that the risk-aversion degree of the retailer strongly influences contracting decisions, whereas the price sensitiveness of consumers has a higher impact on the selling price offered.

Deriving formula to simulate the radiological behavior during LOCA in open pool type reactor

This study aims to model the radiological consequences that result from loss of coolant accident in open pool research reactor of 22 MW power. The loss of coolant accident results from rupture in the cooling systems of the reactor and consequently results in decreasing the water level in the reactor pool. Decreasing the water level, that represents the shielding material above the reactor core, results in increasing the dose rate in the top region in the reactor pool as well as the reactor building. LOCA normally results in shutting down the reactor due to the radioprotection system provided in the upper region of the reactor pool. A failure in shutdown systems of the reactor during LOCA is rare but expected and it represents the worst case. So, evaluating LOCA from the radiological point of view must be investigated for the safe shutdown mode as well as the failure of shutdown case. The study also includes occurring LOCA for shutdown reactor taking the decay time into consideration. ORIGEN-S module from scale system was used to estimate the delayed neutrons and gamma rays from the core for the shutdown mode. KENO-VI module from Scale system was used to estimate the prompt neutrons and gamma rays generated from the core for the failure case. Then, MAVRIC/Scale module was used to estimate the dose rate at the top point of the reactor pool for the two cases during LOCA.Studying the dose rate during LOCA aims to determine the water level that verifies the radiological safety limit at the top point of the reactor pool for the two cases. The calculations introduced a relationship between the water level that verifies the permissible radiological limit (WL) and the decay time (DT) in the range between 0 to 30 d.

Evaluation of fast fission factor in a typical pool type research reactor

One of the important factors of a nuclear reactor core is the fast fission factor. This paper calculates this parameter based on space and energy-dependent method using the PTRAC card of MCNPX code. Tehran research reactor (TRR) is taken as a case study, and the parameter analyses are performed on the reactor core. Fast fission factor in TRR is evaluated regarding temperature effect, control rod positions, and fuel assembly positions. Using the PTRAC card, helpful information on fast fission factors is achieved throughout the reactor core. One MCNPX runs to return a data file about neutron interaction that can be analyzed many times in different manners to reveal this useful information. The method is simple and can be applied to any nuclear reactor core. The results obtained by this method can help nuclear reactor designers and nuclear reactor fuel managers to have a precise evaluation of the parameter. The method proposed in this paper for fast fission factor calculation is compared with the results previously published in the literature.

Perpetual Contract NFT as Collateral for DeFi Composability

Decentralized Finance (DeFi) is an emerging financial service model based on blockchain technology. DeFi composability denotes the ability for different DeFi services to interact with one another resulting in new forms of financial services. The DeFi ecosystem is largely based on ERC-20 tokens that can represent the value of an asset. Collateralized assets in DeFi composability are locked and additional profit cannot be generated. In this paper, we propose a method to generate profit from locked assets by using ERC-721 Non-Fungible Tokens (NFTs) and perpetual contracts. NFT represents the rights to a certain asset. A perpetual contract is a futures contract that does not have an expiration date. We propose perpetual contract NFT, a new form of NFT that can be used as collateral, which exploits perpetual futures contracts in the cryptocurrency derivatives market. Collateral needs to be provided to back the value of a perpetual contract. If the perpetual contract is minted as NFT, the resulting NFT represents the rights to the perpetual contract and its collateral. Therefore, the perpetual contact NFT itself can be used as collateral for DeFi composability. A proof-of-concept smart contract and a web application for perpetual contract NFT are provided to demonstrate its functionality. To validate the profitability of the perpetual contract NFT using a real-world scenario, we experiment with the position NFT of Uniswap v3 decentralized exchange. The position NFT is a form of perpetual contract NFT. Specifically, we present validation with three types of pools: stablecoins, stablecoin/wrapped tokens pair, and wrapped tokens.

Spatial-Pseudotime Anatomy and Transcriptome Reveal Two Types of Meristematic Pools in Poplar Secondary Stems

Spatial-Pseudotime Anatomy and Transcriptome Reveal Two Types of Meristematic Pools in Poplar Secondary Stems

Donor Milk Banking - Safety, Efficacy, New Methodologies.

Donor milk (DM) is of increasing interest as primary nutritional source for preterm infants. Safe access requires special infrastructure, trained staff, sophisticated algorithms, and standard operating procedures as well as quality control measures. DM has limitations like low protein content and unpredictable composition of the other macronutrients, despite fortification frequently not meeting recommendations - both of them compromising growth. The first paragraph is devoted to COVID-19 and how it impacts processes of DM banking. The following paragraphs review aspects of "pasteurization," "safety audits/donor screening," and "DM nutrient variability." In summary, (i) Holder pasteurization still is the most suitable procedure for milk banks, but high-pressure pasteurization or ultraviolet C irradiation conserve the unique properties of DM better and deserve more research to make it suitable for clinical routine. (ii) In regard to safety/screening, guidelines are valuable for safe DM bank operation, but they differ between legislations. There is a surprisingly high rate of non-disclosed donor smoking (0.3%, p > 0.05) and of adulteration of delivered DM (up to 2%, p < 0.05) not detected by standard donor screening procedures. Frequencies differ between remunerated and non-remunerated programs. (iii) Neonatal caregivers should be aware of unpredictable composition of DM. They should be trained on how these can be overcome to avoid negative impact on growth and long-term outcomes like (a) measuring and disclosing nutrient contents of delivered DM batches to customers, (b) implementing certain types of donor pooling to reduce the risk of macronutrient depleted DM, (c) additional supplementation using 0.3-0.5 g protein/100 mL seems to be reasonable, (d) adjusted fortification may help to improve growth, but is not efficient in all preterm infants, (e) target fortification seems to improve growth (and probably also neurodevelopmental index) compared to standard fortification, (f) more research and clinical studies are needed.

OPFaceNet: OPtimized Face Recognition Network for noise and occlusion affected face images using Hyperparameters tuned Convolutional Neural Network

Face recognition is considered as important research in computer vision applications, and it is regarded as the basic biometric security system. Research related to face recognition has been done in the past several years. Still, many more challenges associated with this field need to be addressed. Some literary works have designed the face recognition model on the relatively controlled environments; yet, their performance in general settings has been substandard This paper develops an Optimal Face Recognition Network (OPFaceNet) to recognize the face images affected by high noise and occlusion. The feature patterns subjected to noise like LBP, FLBP, and NRLBP are extracted. The average of all three patterns is given to the proposed Convolutional Neural Network (CNN) classifier. As the main contribution, the CNN model is enhanced by optimizing the Fitness Sorted Rider Optimization Algorithm (FS-ROA). This algorithm optimizes the hyperparameters of CNN like Convolutional layer, Pooling Layer, Fully connected layer, number of Hidden layers, and Type of Pooling. Finally, the simulation results show that the system achieves a good recognition rate of 97.2% and is robust against variations in terms of occlusion and noise when benchmarked over diverse datasets.

Occurrence of Disinfection By-Products in Swimming Pools in the Area of Thessaloniki, Northern Greece. Assessment of Multi-Pathway Exposure and Risk.

This study investigated the occurrence of disinfection by-products (DBPs) (trihalomethanes (THMs), haloacetic acids (HAAs), halonitriles (HANs), halonitromethane (TCNM) and haloketones (HKs)) in different type of swimming pools in the area of Thessaloniki, northern Greece by employing the EPA methods 551.1 and 552.3. Moreover, general water quality parameters (pH, residual chlorine, dissolved organic carbon, UV254 absorption, total nitrogen, alkalinity and conductivity) were also measured. The concentrations of DBPs showed great variability among swimming pools as well as within the same pool between sampling campaigns. HAAs exhibited the highest concentrations followed by THMs, HANs, TCNM and HKs. Exposure doses for four age groups (3–<6 y, 6–<11 y, 11–<16 y and adults) were calculated. Route-specific exposures varied among DBPs groups. Inhalation was the dominant exposure route to THMs and TCNM (up to 92–95%). Ingestion and dermal absorption were the main exposure routes to HAAs (40–82% and 18–59%, respectively), depending on the age of swimmers. HANs contributed up to 75% to the calculated cytotoxicity of pool water. Hazard indices for different exposure routes were <1, suggesting non-carcinogenic risk. Inhalation posed the higher carcinogenic risk for THMs, whereas risk via oral and dermal routes was low. Ingestion and dermal contact posed the higher risk for HAAs. Risk management strategies that minimise DBPs exposure without compromising disinfection efficiency in swimming pools are necessary.

Calculation of dose rates in loss of coolant accident due to double ended rupture of the experimental tangential irradiation beam tube of MTR reactor

The doses and dose rates following a LOCA in MTR reactor have been studied. A MTR reactor is an open pool type. The water pool serves as a shield from radioactive radiations.The most serious accident in this type of reactor is the Loss of Coolant Accident (LOCA) due to rupture either of a primary coolant pipe or of any experimental beam tube. In the present work it has been assumed that pool water drains out due to double ended rupture of the tangential irradiation beam tube (TIC) which has a diameter 150 mm. For an operating power level of 22 MW, the equilibrium core will enter into melting conditions if the pool drain time is less than 1 h.It was also assumed that Emergency Core Cooling System (chimney water injection system and siphon effect breaker) were not working. Therefore, conservatively a severe damage (∼80%) is expected to occur to the core, either by a core uncover situation following extended boiling operation, or by a core covered situation with extended boiling.The reactor interiors have been modeled using the Monte Carlo N-Particle Transport code MCNPX 2.7.0. The source term has been determined using the ORIGEN-2 code. The doses and dose rates calculations in different places of operator (as phantom of Tissue-Equivalent Material) inside of the reactor building were determined by using Monte Carlo N-Particle Transport (MCNPX). The results show that the dose rate in the control room is 5.24 Sv/h, the dose rate in the reactor hall above the pools on the gate is 7.20Sv/h and the dose rate in the Emergency control room is 2.68Sv/h. Those dose rates are extremely high and would lead to fatal doses in short time.