Association of blood lipids, cortisol and Hemodynamics Under stress: A possible role in early Atherogenesis

Introduction: High blood cholesterol is claimed as a risk factor but recently it is accepted that cholesterol is increased under psychological stress. When raised in blood, cholesterol plays role in atherosclerosis formation; a role which is being debated since last many decades but still various questions is un-answered. Role of stress in early atherogenesis with association to alteration in blood lipids has been proposed but the available literature is scanty on the subject. Objective: To explore the association of alterations in blood lipids, cortisol level and hemodynamics under mental stress in youth with no apparent heart disease. Methodology: 114 male participants were selected from 397 volunteers as per ‘selection criterion’ approved by scientific committee. The volunteers were examined two times: during stress task as ‘stress-study’ and during non-stress period as ‘control’ according to ‘paired sample’ design. Thus, 56.54% apparently healthy subjects were included with exclusion ratio of 43.58%. All experiments were conducted under standard methods at LINAR-Larkana and Physiology Department of Sindh University, Jamshoro. Blood sample were taken between 9.00 am to 12.00 pm. Results: Cortisol, systolic and diastolic blood pressures and heart rate were significantly increased during stress session. Different lipid levels were changed with different significant values. Correlations of some altered lipid levels with raised values of hemodynamics and cortisol detected were positive and significant. Conclusion: Most changes in the level of variables were found prone to be “atherogenic in pattern” due to psychological stress. This work may pave a way for better understanding of relationship in between lipid alterations, mental stress and early atherogenesis. For that further studies are needed.   Key Words: Cholesterol, Hemodynamics, Cortisol, psychological stress

Quantifying flood model accuracy under varying surface complexities

This is the final version. Available on open access from Elsevier via the DOI in this recordData availability: Data will be made available on request.Open Access experimental datasets used in this paper are available at https://zenodo.org/communities/floodinteract/Floods in urban areas which feature interactions between piped and surface networks are hydraulically complex. Further, obtaining in situ calibration data, although necessary for robust simulations, can be very challenging. The aim of this research is to evaluate the performance of a commonly used deterministic 1D-2D flood model, calibrated using low resolution data, against a higher resolution dataset containing flows, depths and velocity fields; which are replicated from an experimental scale model water facility. Calibration of the numerical model was conducted using a lower resolution dataset, which consisted of a simple rectangular profile. The model was then evaluated against a dataset that was higher in spatial resolution and more complex in geometry (a street profile containing parking spaces). The findings show that when the model increased in scenario complexity model performance was reduced, though most of the simulation error was < 10% (NRMSE). Similarly, there was more error in the validated model that was higher in spatial resolution than lower. This was due to calibration not being stringent enough when conducted in a lower spatial resolution. However, overall the work shows the potential for the use of low-resolution datasets for model calibration.Engineering and Physical Sciences Research Council (EPSRC

Investigation of uniform and graded sediment wash-off in an urban drainage system: numerical model validation from a rainfall simulator in an experimental facility

[Abstract:] Understanding sediment wash-off in urban environments plays an essential role in sediment transport management; and is critical for accurate pluvial flood control to assist in adaptation and mitigation strategies. Sediment transport models have been researched previously, though challenges still arise due to the complicated nature of graded sediment transport. This study tested the accuracy of the van Rijn model using a sparse distribution of particle sizes using the geometric mean. As such, this study used high-resolution datasets collected in a water laboratory to investigate sediment wash-off and transport on an urban street. This included the interaction of two gully pots receiving sediment loads that were washed off from a hypothetical urban surface by three rainfall intensities. The results showed that the model was able to simulate uniform sediments entering the gully pots accurately when the sediment size was assigned to a median diameter. Using the grain diameter to represent the geometric mean can improve the model performance for simulating a graded sediment.EPSRC Centre for Doctoral Training in Water Informatics Science and Engineering, WISE CDT; EP/L016214/1The work presented in this paper was carried out as part of PhD research and was supported by the EPSRC Centre for Doctoral Training in Water Informatics Science and Engineering (WISE CDT; EP/L016214/1). The experimental part and data collection received funding from the Spanish Ministry of Science, Innovation and Universities under POREDRAIN project RTI2018-094217-B-C33 (MINECO/FEDER-EU). The authors would also like to thank the Danish Hydraulic Institute for supplying the academic license for the MIKE 21 model

Evaluating future hydrological changes in China under climate change

Projecting and understanding future hydrological changes in China are critical for effective water resource management and adaptation planning in response to climate variability. However, few studies have investigated runoff variability and flood and drought risks under climate change scenarios for the entire region of China at high resolution. In this study, we use the Joint UK Land Environment Simulator (JULES), specifically tailored for simulating hydrological processes in China at a 0.25-degree resolution. Downscaled and bias-corrected forcing data from Global Climate Models (GCMs), using the bias-correction and spatial disaggregation (BCSD) method, were used to drive the JULES model to project future hydrological processes under medium (SSP245) and high (SSP585) emission scenarios. The results indicate that annual runoff in China is projected to increase significantly under the high emission scenario, notably in the eastern and southern basins. Wetter summers and drier winters are expected in the south, while the opposite trend is expected in the north. Wetter conditions in the near future and drier summers in the far future are expected in northern China. Shifts from drier to wetter conditions are projected in the southeast and southwest areas, while the middle Yangtze River basin may experience the opposite trend. The flood risk is expected to increase in spring, summer, and autumn, along with heightened drought risk in winter, summer, and autumn. Southern China would face greater flood risk, while the central Yangtze River basin would face intensified drought risk, especially in the far future. These findings underscore the influence of different emission scenarios on flood and drought risks, emphasizing the need for proactive measures to enhance climate adaptation in the future

Verifying an improved intermittent water distribution network analysis method based on EPA-SWMM

Modelling Intermittent Water Supply (IWS) presents challenges, as traditional hydraulic methods based on EPANET are often inadequate due to their inability to simulate the network filling process. While EPA-SWMM (EPA’s Storm Water Management Model)-based methods enhance IWS analysis, they remain network-specific and lack universal applicability. This study aims to calibrate and verify an improved EPA-SWMM-based model on a 6 m × 5 m laboratory-scale IWS. Experiments were conducted to capture flow rate data from demand nodes under various conditions. The EPA-SWMM model, based on uncontrolled outlets with flow rate varying by pressure, was calibrated using, an automated procedure that integrated the Genetic Algorithm (GA) into the SWMM-toolkit for optimizing minor loss and pipe roughness coefficients. Comparing model results with experimental data demonstrated the model’s capability to simulate the laboratory-scale IWS system behaviour. The model was also applied to a real case study, with results closely aligning with field data, affirming its reliability. The proposed IWS modelling method offers a versatile tool for applications, such as design and scenario analysis for tackling IWS challenges and managing IWS systems. Future research should focus on a large-scale laboratory experiment with pressure and flow sensors, considering air presence in the network to mitigate errors

A CONVOLUTIONAL NEURAL NETWORK-BASED MALWARE ANALYSIS, INTRUSION DETECTION, AND PREVENTION SCHEMA

This paper discusses distributed denial of service (DDoS) attacks, their current threat level, and intrusion detection systems (IDS), which are one of the primary tools for mitigating them. It focuses on the difficulties and challenges that IDS systems face when detecting DDoS attacks, as well as the difficulties and challenges that they face today when integrating with artificial intelligence systems. Automatic and real-time detection of malicious threats is made possible by these ID systems. However, the network requires a highly sophisticated security solution due to the frequency with which malicious threats emerge and change. A significant amount of research is required to create an intelligent and trustworthy identification system for research purposes; numerous ID datasets are freely accessible. Due to the rapid evolution of attack detection mechanisms and the complexity of malicious attacks, publicly available ID datasets must be thoroughly modified on a regular basis. Due to the ever-evolving attack detection mechanism and the complexity of malicious attacks, publicly available ID datasets must frequently be modified. A Convolutional Neural Network (CNN) network was trained using four distinct training algorithms. The CICDDoS2019 dataset, which contains the most recent DDoS attack types created in CICDDoS2019, was tested, According to the analysis; the "Gradient Descent with Momentum Backpropagation" algorithm could be trained quickly. Network data attacks were correctly detected 93.1 percent of the time. The results indicate that The Convolutional Neural Network is able to successfully defend against DDoS attacks detection by using intrusion detection systems IDS, as evidenced by the high accuracy values obtained

Greywater recycling: A review of treatment options and applications

Wastewater is an immense resource which could have significant applications in regions of water scarcity. Greywater has particular advantages in that it is a large source with a low organic content. Through critical analysis of data from existing greywater recycling applications this paper presents a review of existing technologies and applications; collating a disparate information base and comparing / contrasting the strengths and weaknesses of different approaches. Findings suggest that simple technologies and sand filters have been shown to achieve only a limited treatment of the greywater whereas membranes were reported to provide good removal of the solids but could not efficiently tackle the organic fraction. Alternatively, biological and extensive schemes achieved good general treatment of greywater with a particularly good removal of the organics. The best overall performances were observed within the schemes combining different types of treatment to ensure effective treatment of all the fractions

Seasonal Variation of Rainy and Dry Season Per Capita Water Consumption in Freetown City Sierra Leone

Ensuring a sustainable urban water supply for developing/low-income countries requires an understanding of the factors affecting water consumption and technical evidence of individual consumption which can be used to design an improved water demand projection. This paper compared dry and rainy season water sources available for consumption and the end-use volume by each person in the different income groups. The study used a questionnaire survey to gather household data for a total of 398 households, which was analysed to develop the relationship between per capita water consumption characteristics: Socio-economic status, demographics, water use behaviour around indoor and outdoor water use activities. In the per capita water consumption patterns of Freetown, a seasonal variation was found: In the rainy season, per capita water consumption was found to be about 7% higher than the consumption for the full sample, whilst in the dry season, per capita water consumption was almost 14% lower than the full survey. The statistical analysis of the data shows that the average per capita water consumption for both households increases with income for informal slum-, low-, middle- and high-income households without piped connection (73, 78, 94 and 112 L/capita/day) and with connection (91, 97, 113 and 133 L/capita/day), respectively. The collected data have been used to develop 20 statistical models using the multiple linear stepwise regression method for selecting the best predictor variable from the data set. It can be seen from the values that the strongest significant relationships of per capita consumption are with the number of occupants (R = −0.728) in the household and time spent to fetch water for use (R = −0.711). Furthermore, the results reveal that the highest fraction of end use is showering (18%), then bathing (16%), followed by toilet use (14%). This is not in agreement with many developing countries where toilet use represents the largest component of indoor end use

Part 2 - Water Services Provision and Climate Change Adaptation

This is an Editorial Article. No Abstract is available