Storage Levels Research Articles

A MODEL OF THE INFORMATION SECURITY EVENT PROCESSING PROCESS AT A CRITICAL INFORMATION INFRASTRUCTURE FACILITY

The article presents a model of the information security event processing process at a critical information infrastructure facility. The information system of one of the medical institutions of the city was chosen as an object of critical information infrastructure. It contains a huge amount of confidential information about patients, medications and medical procedures. The "as is" model was built before the implementation of decision support and the "as it should be" model after its use. The model was built in the ERwin Data Modeler CASE tool, which implements the industry modeling standards IDEF0 and IDEF3, which made it possible to fully cover all aspects of the system and create a visual representation of its operation. The shortcomings of the information security event processing process at the critical information infrastructure facility have been identified and a new approach to their elimination has been identified, providing for the use of a decision support subsystem based on the use of machine learning models using analytical models, which leads to a reduction in the time for identifying incidents and making various management decisions on them. This will allow you to quickly respond to possible threats and minimize the likelihood of incidents. This approach will make it possible to create a system that is adaptive to changes in the operation of the information infrastructure and offer solutions to optimize data processing processes, will increase the security level of storage, processing and transmission of confidential information.

An Automated Disaster Recovery Strategies for Fintech Infrastructure

This paper aims to present an extensive and well-defined review of the automatic disaster recovery strategies for fintech infrastructure. Since financial operations are gradually relying more on technology, business continuity, and data protection in case of disasters have become fundamental matters. The automation of disaster recovery systems relies on well-designed technologies and methods to reduce downtime, data loss, and financial damage. Organizations are, therefore, able to maintain business continuity and regulatory standards. The article covers AR, deep learning, and AI robotics that will be used for disaster recovery automation. It examines cloud disaster recovery systems' application benefits and deployment considerations, featuring elastic resources, redundancy, and automated failover process. Also, the document surveys the replication set of technologies such as storage level replication, database replication, and file system replication, facilitating real-time cross-site synchronizations. Moreover, the study looks into automated failover operations that detect and execute failure recovery courses, such as load-balancing traffic redirecting to backup sites. In addition, the guide highlights the part played by the operation/automation framework in centralizing control and coordination of disaster recovery processes, linking them with monitoring and alerting systems, and guaranteeing that the recovery methods are properly executed. By looking into the issues, best practices, and consequences of making these automated strategies, this paper hopes to give fintech organizations many valuable hints and practical recommendations about how to improve the level of their disaster management, the amount of lost data, and the continuity of their business in unfamiliar damaging episodic situations.

Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model

The changes in the recent and future spatial–temporal patterns of carbon storage of the Tibetan Plateau and its dominant factors in different periods were unclear, and were conducive to optimizing the spatial layout of land. Exploring the spatial and temporal changes in terrestrial ecosystem carbon storage and their influencing factors during a long study period had important theoretical and practical significance for achieving the goal of carbon neutrality. In this study, the Integrated Valuation of Ecosystem Services and Trade-offs model (InVEST) was used to analyze the changes in carbon storage based on vegetation-type data during 2000–2020. The Path-generating Land-Use Simulation model (PLUS) was then used to predict the spatial distribution of carbon storage in the Tibetan Plateau in 2030 and 2060 under inertial development, farmland protection and ecology priority scenarios. The results showed that: (1) The degradation of vegetation types reduced the carbon storage during the study period. During 2000–2020, the desert shrub and non-vegetation area expanded by 63.21% and 13.35%, respectively, while the deciduous scrub, mixed forest and low coverage grassland decreased accordingly. The carbon storage of the Tibetan Plateau showed a decreasing trend by 0.37 × 106 t. (2) The spatial distribution patterns of carbon storage were consistent with that of the vegetation types. (3) In 2030 and 2060, under the constraint of the ecological priority development, the reduction in carbon storage was the smallest, at 0.01 × 106 t and 0.16 × 106 t, respectively. Under the constraint of the inertial development, carbon storage had the largest reduction, at 0.12 × 106 t and 0.43 × 106 t, respectively. (4) During 2000–2020, the dominant single factor that had the greatest impacts on the changes in carbon storage was FVC (vegetation coverage), with q values of 0.616, 0.619 and 0.567, respectively. The interactive dominant effects were mainly nonlinear enhancement and double-factor enhancement. The interactive dominant factors that had the greatest impact were FVC and the DEM (Digital Elevation Model), with q values of 0.94, 0.92 and 0.90, respectively. Therefore, ecological land with a high FVC should be protected and the expansion of non-vegetation areas should be restricted in future planning to improve the carbon storage level of the Tibetan Plateau and achieve the goal of carbon neutrality.

Postharvest Fish Processing in the Southwest Region of Cameroon and the Effect of Smoke-Drying on Quality

Fish processing in Cameroon is mostly carried out by untrained individuals using different methods which often produce fish products of poor quality. This study was aimed at identifying the main fish processing technologies used in 5 fishing communities in Limbe Subdivision in the Southwest Region of Cameroon. A total of 120 questionnaires were administered in the study area to identify the most popular unit operation in fish processing and to evaluate its effect under controlled conditions on the quality of fish products. It was found that the main fish technology employed was smoke-drying and that most of the processors dried the Ilisha africana species. Smoke-drying of Ilisha africana was carried out under controlled conditions of temperature and time, and smoked fish samples of different colours ranging from pale brown to dark brown were obtained. Laboratory analysis of the fish samples revealed that the moisture content and microbial content of the fish decreased significantly ( p < 0.05 ), while protein content increased significantly ( p < 0.05 ) with an increase in smoking time and temperature. The optimum moisture content was achieved at temperature ranges of 61-70°C for 18 h (12.3%), 71-80°C for 12 h (10.7%), and 18 h (7.3%). The pH and microbial content of all the samples were within the recommended levels for consumption and safe storage. It was concluded that the best temperature ranges and times for smoke-drying Ilisha africana were 61-70°C for 18 h and 71-80°C for 12 h.

Improvement of ship-generated oily waste collection process from ports through the use of virtual Internet of Things system.

The management of ship-generated oily waste is subject to international regulations due to its high environmental impact and significant valorisation potential. The advancement of research leads port authorities to think of emerging technologies to add value to existing systems. In light of this, the objective of this paper is to devise and simulate a collection system based on Internet of Things technology. It is primarily an intelligent simulator with capabilities of sensors' imitation, relaying data, evaluating vehicle routing algorithms and calculation of performance indicators. Using a numerical experience adapted from the regional context in Morocco, the metrics about collected quantities, transportation distances and tank storage levels tend to prefer the intelligent scenario over the status quo. The total distance travelled has decreased by 45.25%, and the average quantity collected per round has risen by 24.22%. On average, every cubic meter stored in a port saves 16.4km of monthly travelled distances. These results warrant additional study to evaluate the impact of a national coverage extent. Nevertheless, additional tests on investment requirements in terms of network implementation and storage resources are essential to prove the acquisition of this solution is viable in the long range.

DNA strand break levels in cryopreserved mononuclear blood cell lines measured by the alkaline comet assay: results from the hCOMET ring trial.

The comet assay is widely used in biomonitoring studies for the analysis of DNA damage in leukocytes and peripheral blood mononuclear cells. Rather than processing blood samples directly, it can be desirable to cryopreserve whole blood or isolated cells for later analysis by the comet assay. However, this creates concern about artificial accumulation of DNA damage during cryopreservation. In this study, 10 laboratories used standardized cryopreservation and thawing procedures of monocytic (THP-1) or lymphocytic (TK6) cells. Samples were cryopreserved in small aliquots in 50% foetal bovine serum, 40% cell culture medium, and 10% dimethyl sulphoxide. Subsequently, cryopreserved samples were analysed by the standard comet assay on three occasions over a 3-year period. Levels of DNA strand breaks in THP-1 cells were increased (four laboratories), unaltered (four laboratories), or decreased (two laboratories) by long-term storage. Pooled analysis indicates only a modest positive association between storage time and levels of DNA strand breaks in THP-1 cells (0.37% Tail DNA per year, 95% confidence interval: -0.05, 0.78). In contrast, DNA strand break levels were not increased by cryopreservation in TK6 cells. There was inter-laboratory variation in levels of DNA strand breaks in THP-1 cells (SD = 3.7% Tail DNA) and TK6 reference sample cells (SD = 9.4% Tail DNA), whereas the intra-laboratory residual variation was substantially smaller (i.e. SD = 0.4%-2.2% Tail DNA in laboratories with the smallest and largest variation). In conclusion, the study shows that accumulation of DNA strand breaks in cryopreserved mononuclear blood cell lines is not a matter of concern.

Verification of decreased polycyclic aromatic hydrocarbon (PAH) levels in yoghurt during storage using isotopically-labelled PAHs

This study detected 24 types of PAHs in yoghurt during fermentation and storage using the QuEChERS pretreatment coupled with gas chromatography triple-quadrupole mass spectrometry (GC-QQQ-MS) method. Deuterated PAH8 standards were subsequently adopted to simulate and analyze the decreases in PAH levels during storage because PAH8 was identified as the suitable indicator of PAH levels and risks, based on correlation analysis and principal component analysis (PCA). The results showed that benzo[a]pyrene (BaP), PAH24 and toxic equivalent (TEQ) levels decreased by 14.81 %, 14.95 % and 16.15 % after fermentation, respectively. During storage, BaP, PAH8 and TEQ levels declined continuously, reaching the maximum decrease rates of 56.44 %, 68.32 % and 71.84 %, respectively. Besides, the significant losses in BaP-d12 and PAH8-d levels verified the downward trends in non-labelled PAHs, with maximum decrease rates of 72.78 % and 56.74 %, respectively. This study provides reliable evidence of the decreases in PAH levels in yoghurt during storage and helpful guidance for future analysis of PAH changes.

Designed Tetranuclear Iron‐oxo Clusters with Redox Activity for High‐Performance Lithium Storage

AbstractPolyoxometalates (POMs) are considered as promising catalysts with unique redox activity at the molecular level for energy storage. However, eco‐friendly iron‐oxo clusters with special metal coordination structures have rarely been reported for Li‐ion storage. Herein, three novel redox‐active tetranuclear iron‐oxo clusters have been synthesized using the solvothermal method with different ratios of Fe3+ and SO42−. Further, they can serve as anode materials for Li‐ion batteries. Among them, cluster H6[Fe4O2(H2O)2(SO4)7]⋅H2O, the stable structure extended by SO42− with a unique 1D pore, displays a specific discharge capacity of 1784 mAh g−1 at 0.2 C and good cycle performance (at 0.2 C and 4 C). This is the first instance of inorganic iron‐oxo clusters being used for Li‐ion storage. Our findings present a new molecular model system with a well‐defined structure and offer new design concepts for the practical application of studying the multi‐electron redox activity of iron‐oxo clusters.

Designed Tetranuclear Iron-oxo Clusters with Redox Activity for High-Performance Lithium Storage.

Polyoxometalates (POMs) are considered as promising catalysts with unique redox activity at the molecular level for energy storage. However, eco-friendly iron-oxo clusters with special metal coordination structures have rarely been reported for Li-ion storage. Herein, three novel redox-active tetranuclear iron-oxo clusters have been synthesized using the solvothermal method with different ratios of Fe3+ and SO4 2- . Further, they can serve as anode materials for Li-ion batteries. Among them, cluster H6 [Fe4 O2 (H2 O)2 (SO4 )7 ]⋅H2 O, the stable structure extended by SO4 2- with a unique 1D pore, displays a specific discharge capacity of 1784 mAh g-1 at 0.2 C and good cycle performance (at 0.2 C and 4 C). This is the first instance of inorganic iron-oxo clusters being used for Li-ion storage. Our findings present a new molecular model system with a well-defined structure and offer new design concepts for the practical application of studying the multi-electron redox activity of iron-oxo clusters.

All-solid-state synthesis of nitrogen doped carbon with high-faradaic-active species for supercapacitor

Template synthesis of porous carbon with rich functionalities by a scalable strategy without using any solvents and activators will be a green and promising route. Herein, we reported an all-solid-state synthesis strategy by mixing glucose and graphitic carbon nitride (g-C3N4) by milling and then undergoing a segmented carbonization in which first at low temperature of 573 K to polymerize sucrose onto g-C3N4, then at high temperature of 973 K to carbonized the composite to obtain a porous carbon (denoted as GNC) with abundant nitrogen species over 20 atom% and large packing density (0.91–1.25 g cm−3). Due to the features of large packing density and rich electrochemically-active N species, as electrode for supercapacitive energy storage, the developed GNC exhibit a comparable energy storage level with both high gravimetric energy density of 26.8 Wh kg−1@1000 W kg−1 and volumetric energy density of 30.8 Wh L−1@1150 W L−1, suggesting a potentiality in energy storage field. Importantly, the present strategy owns characteristics of ease of operation, green and scalable, which would be a promising synthesis route towards the fabrication of functional carbon utilizing in many fields like sorption & separation, catalysis, energy storage and so on.

Security Model for a Central Bank in Latin America using Blockchain

Banking institutions in Latin America are the target of increasingly sophisticated and advanced cyber-attacks and threats, which increase every year and leave substantial economic losses, due to the high level of global interconnection and digitization of their operations. The objective of this work is to design a model to guarantee information security in a Central Bank in Latin America using Blockchain technology. Exploratory research, observation and inductive and deductive methods are used to propose Blockchain solutions in a Central Bank. The results are a model for secure transactions in Blockchain, Smart Contract functions and a data management process. It was concluded that the security model for a central bank provides high level of information management and storage of transactions in a secure and immutable way.

Global profile of anemia during pregnancy versus country income overview: 19 years estimative (2000–2019)

Anemia is a worldwide public health problem that is worst in low- and middle-income countries (LMICs), reaching 60% of prevalence. The etiology of anemia is diverse and multifactorial, with iron deficiency being the most prevalent, and often found in pregnant women. Iron is indispensable for the production of red blood cells and approximately 80% of the available heme iron is used for hemoglobin synthesis in mature erythroblasts. Iron deficiency affects oxygen transport, compromising energy and muscle metabolism and can occur with depletion of iron storage, defective erythropoiesis, and low hemoglobin levels. We analyzed anemia prevalence in pregnant women from 2000 to 2019 worldwide correlating them with current (2022) country income, with especial attention to LMICs using WHO dataset. Our analysis indicates that pregnant women from LMICs had a higher probability (40%) of anemia during pregnancy especially those from Africa and South Asia. Africa and the Americas showed a higher decrease in the prevalence of anemia from 2000 to 2019. The Americas and Europe have a lower prevalence, concentrated in 57% of most upper-middle- and high-income countries. Black women are also more prone to develop anemia during pregnancy, especially if they are from LMICs. However, the prevalence of anemia appears to decrease with an increase in educational level. In conclusion, anemia prevalence fluctuated from 5.2 to 65.7% worldwide in 2019, validating it as a public health problem.

Cloud-Edge Collaborative Scheduling with a Focus on Clean Energy

With the promotion of the national "double carbon" goal, the power system is developing towards the direction of low-carbon transformation. In order to achieve the goal of "striving to peak carbon dioxide emissions by 2030 and striving to achieve carbon neutrality by 2060", we must actively promote the consumption of a high proportion of renewable energy from the grid, which is the most urgent issue to be addressed. In this chapter, access to clean energy will involve multiple aspects such as source, network, load and storage. However, due to the intermittent, random and volatile nature of wind power and photovoltaic power generation, the challenges faced by significant users of the power system are enormous. Traditional energy Internet dispatching adopts centralized dispatching. In this paper, by deploying edge nodes, the autonomous decision-making and autonomous collaboration of power grid nodes at all levels are enhanced, and the collaborative integration level of source, network, load and storage of smart power grid is improved. Aimed at the current power supply and demand imbalance, new energy access problems and energy storage problems. In this paper, a service adaptation algorithm based on dynamic priority is proposed based on the scenario of load storage integration of source network under renewable energy access. Experimental results show that, compared with other algorithms, this algorithm has lower scheduling time and execution time and better performance under the condition of ensuring the highest clean energy consumption rate and first-order load priority response.

Preliminary hazard identification for qualitative risk assessment on onboard hydrogen storage and supply systems of hydrogen fuel cell vehicles

Due to the ever-increasing stringency of environmental policy requirements, hydrogen fuel cell vehicles (HFCVs), which are intended to serve as a substitute for conventional automobiles, are continuously evolving as a new promising technology. It is essential to conduct hazard identification as an early phase in the development of HFCVs in order to describe possible hazards and identify potential safety concerns. The onboard hydrogen storage and supply system is an essential component of HFCVs, serving to store hydrogen and provide it to the fuel cell system to guarantee its proper functioning. In this context, the research is conducted by establishing models of onboard hydrogen storage and supply system that reflected their specifications and elements. In this study, the methods of hazard and operability study (HAZOP) and failure mode and effect analysis (FMEA) are employed to identify and analyze the potential accident scenarios. The risk of each potential accident scenario, including whether to implement safety measures, is analyzed and classified as risk matrix. Medium- and high-risk scenarios in the absence of safety measures include accidental burst of the hydrogen cylinder, debonding of plastic liners and metal bosses, release of hydrogen from a thermally activated pressure relief device or pressure relief device, tiny release of hydrogen from improperly attached tube fittings, and small release of hydrogen from valves with seal failures. Comparing the findings of risk matrices with and without safety measures confirms that the safety measures lower the risk levels of the onboard hydrogen storage and supply systems to a tolerable level.

A matrix-analytic method for the steady state analysis of a Markovian queueing system with scrap items

This paper studies a mathematical analysis of scrap item-based single server stochastic queueing, which consists of storage space for the scrap items collected from the customers. The primary customers arrive in the finite waiting hall to sell scrap or recyclable products. The server collects the customer’s scrap items and stores them in the storage space. If the waiting hall is full whenever the primary customers arrive, they can join an infinite orbit or permanently leave the system under the Bernoulli trial. Whenever the orbital customers find at least one free space in the waiting hall, they can enter it. The server begins vacation once the storage reaches its maximum capacity or no more customers exist in the waiting hall. The server switches to regular mode whenever at least one free space exists in the storage, and one customer is in the waiting hall. Otherwise, he is not working in vacation mode. Customers in the waiting hall may lose their patience after waiting for a long time and may either enter orbit or leave the system permanently. Whenever the storage level (scrap item level) reaches a certain limit, the server places the procurement order for sending the items to the recycling unit or re-manufacturer. The system’s steady-state probability vector and stability condition have been derived by truncating the orbit at a point. Various system performances, such as expected total cost, profit cost, and waiting time for customers in the waiting hall, are defined, and a numerical study is carried out to analyze the performance of the proposed model. The numerical findings indicate that disabling working in vacation mode increases waiting time and total cost while working in vacation mode results in minimized waiting time and total cost.

Modal Analysis of Chushandian Gravity Dam

This article uses the finite element software ABAQUS to establish a three-dimensional finite element model based on the overflow dam section 12 # ~15 # and surface outlet dam section of the Chushandian gravity dam. The stress and displacement distribution of the 12 # ~15 # dam section of the Chushandian gravity dam under normal water storage level are analyzed; On this basis, modal analysis is conducted on the 12 # ~15 # dam section to study the impact of the dam's own modal conditions on the normal operation of the dam. The research shows that: (1) Under the condition of normal height water level, there is a small tensile stress at the dam heel, and the compressive stress at the dam toe is within the normal range. There is significant stress at the intersection of the upper curved part of the overflow dam and the transverse joint. The dam body strength meets the requirements and can be considered safe for the reservoir. (2) Modal analysis of the model reveals that significant deformation can occur at the right side of the dam crest during lower frequency vibrations. With the increasing frequency, the easily deformed parts of the dam are still at the top of the dam, and the displacement of the easily deformed parts is increasing. The position of the easily deformed parts is moving along the Dam axis, and the deformation direction of the easily deformed parts will change regularly.

Bi-functional electrochromic supercapacitor based on hydrothermal-grown 3D Nb2O5 nanospheres

The design and development of novel cathodic materials with suitable crystal structure and nanostructure is an essential basis for both electrochromism and electrochemical energy storage devices. In this study, Niobium oxide (Nb2O5) thin films as high-performance cathodic materials were synthesized using a facile hydrothermal method. The influence of the precursor concentration on the structural, morphological, electrochromic, and energy storage properties was investigated successfully. The X-ray diffraction analysis confirmed the highly crystalline orthorhombic nature of Nb2O5 thin films. Nanostructured Nb2O5 nanospheres effectively improved the charge transportation and mobility of charge carriers. Nb01 thin film most effectively accommodated lithium ions and facilitated the desired bifunctional performance. An electrochromic supercapacitor (ESC) of Nb01 composition showed the highest optical modulation of (76.92%), excellent reversibility of (98%), high coloration efficiency (CE) (98.75 cm2 C−1), and high-energy storage capacity (93.33 C cm−2). The fully colored ESC devices (4 × 5 cm2) have lightened a red and yellow light-emitting diode (LED) which confirms the energy storage level with the color changing ability of the 3D Nb2O5 nanospheres as a potential application in ESC.

Gamma irradiation induces a pro-apoptotic state in longer stored platelets, without progressing to an overt apoptosis by day 7 of storage.

Although gamma-irradiation to platelet products is a standard method to prevent the risk of TA-GVHD in vulnerable recipients, it induces some proteomic and redox changes, of which irradiation-induced ROS increments may potentiate platelet mitochondrial dysfunction. However, whether these changes cause platelet apoptosis, or affect their viability during storage, is the main subject of this study. PLT-rich plasma PC was split into two bags, one kept as control while other was subjected to gamma-irradiation. Within 7-days storage, cytosolic and mitochondrial levels of cytochrome c and pro-apoptotic molecules of Bak and Bax were evaluated by western-blotting. Intraplatelet active caspase (using FAM-DEVD-FMK) and PS-exposure were detected by flowcytometry. Caspase activity in platelet lysate was also confirmed by immunofluorescence detection of Caspase-3/7 Substrate N-Ac-DEVD-N'-MC-R110 while platelet viability was evaluated with MTT assays. Cytosolic cytochrome c gradually increased while its mitochondrial content steadily declined during 7 days of storage. In a contrary trend, reverse patterns were observed for Bak and Bax expressions. Gamma-irradiated platelets showed higher release of mitochondrial cytochrome c that reflected by higher cytosolic cytochrome c levels on day 7 of storage. Concurrently mitochondrial pro-apoptotic Bak and Bax proteins increased on day 7 in irradiated products. However, gamma-irradiation didn't significantly increase caspase activity or PS-exposure, nor did it decrease platelet viability. Here, consistent with studies on "gamma-irradiation-induced oxidative stress", we showed that gamma-ray also increases platelet pro-apoptotic signals during storage, although not strongly enough to affect platelet viability by overt apoptosis induction. Conclusively, whether supplementing ROS scavengers or antioxidants to irradiated platelets can improve their quality during storage may be of interest for future research.

Model‐coupled GRACE‐based analysis of hydrological dynamics of drying Lake Urmia and its basin

AbstractLake Urmia basin (LUB), in northwestern Iran, is under the influence of extreme degradation due to a number of natural and anthropogenic factors. The existence of the Lake is critical for the microclimate of the region as well as the quality of human life and wildlife, which necessitates an up‐to‐date and holistic analysis of its hydrological dynamics. In this premise, satellite‐based terrestrial water storage (TWS) received from the Gravity Recovery and Climate Experiment (GRACE) mission was coupled with hydrometeorological modelling and assessment tools to analyse the hydrological status of the lake and its basin. As a new gap‐filling approach, the Seasonal‐Trend decomposition using Locally estimated scatterplot smoothing (LOESS) (STL) decomposition technique was proposed in this study to reconstruct the missing TWS data. Integrating satellite precipitation data with the Catchment Land Surface Model (CLSM) and WaterGAP model outputs, the hydrological status of the lake was investigated. The STL‐based TWS turned out to concord well with the simulated TWS from the CLSM indicating the acceptable performance of the proposed technique. The findings revealed that the LUB had undergone an alarming hydrological situation from 2003 to 2021 with a total loss of and from its TWS and groundwater storage (GWS), respectively. The water level time series also indicated that the water level of the lake had diminished with an annual rate of corresponding to a total water level depletion of about during the 2003–2021 period. The GRACE‐derived TWS and GWS also agreed well with the CLSM simulations. Assessment of the extreme events of the LUB suggested that the basin suffered from a severe dry event in 2008 resulting in the depletion of its water storage and water level. It was also found that from 2003 onward, a critical hydrological setting had dominated the LUB with a negative hydrological balance of .

Optimal water supply reservoir operation by leveraging the meta-heuristic Harris Hawks algorithms and opposite based learning technique

To ease water scarcity, dynamic programming, stochastic dynamic programming, and heuristic algorithms have been applied to solve problem matters related to water resources. Development, operation, and management are vital in a reservoir operating policy, especially when the reservoir serves a complex objective. In this study, an attempt via metaheuristic algorithms, namely the Harris Hawks Optimisation (HHO) Algorithm and the Opposite Based Learning of HHO (OBL-HHO) are made to minimise the water deficit as well as mitigate floods at downstream of the Klang Gate Dam (KGD). Due to trade-offs between water supply and flood management, the HHO and OBL-HHO models have configurable thresholds to optimise the KGD reservoir operation. To determine the efficacy of the HHO and OBL-HHO in reservoir optimisation, reliability, vulnerability, and resilience are risk measures evaluated. If inflow categories are omitted, the OBL-HHO meets 71.49% of demand compared to 54.83% for the standalone HHO. The HHO proved superior to OBL-HHO in satisfying demand during medium inflows, achieving 38.60% compared to 20.61%, even though the HHO may have experienced water loss at the end of the storage level. The HHO is still a promising method, as proven by its reliability and resilience indices compared to other published heuristic algorithms: at 62.50% and 1.56, respectively. The Artificial Bee Colony (ABC) outcomes satisfied demand at 61.36%, 59.47% with the Particle Swarm Optimisation (PSO), 55.68% with the real-coded Genetic Algorithm (GA), and 23.5 percent with the binary GA. For resilience, the ABC scored 0.16, PSO scored 0.15, and real coded GA scored 0.14 whilst the binary-GA has the worst failure recovery algorithm with 0.09.