75 research outputs found
A critical take on the role of random and local search-oriented components of modern computational intelligence-based optimization algorithms
This is the final version. Available on open access from Springer via the DOI in this recordData availability: All used data have been presented in the paper. The codes used to test these algorithms are available at the corresponding author’s GitHub page: https://github.com/BabakZolghadrAsli/randomness_in_CI_optimizationThe concept of computational intelligence (CI)-based optimization algorithms emerged in the early 1960s as a more practical approach to the contemporary derivate-based approaches. This paved the way for many modern algorithms to arise with an unprecedented growth rate in recent years, each claiming to have a novel and present a profound breakthrough in the field. That said, many have raised concerns about the performance of these algorithms and even identified fundamental flaws that could potentially undermine the integrity of their results. On that note, the premise of this study was to replicate some of the more prevalent, fundamental components of these algorithms in an abstract format as a measure to observe their behavior in an isolated environment. Six pseudo algorithms were designed to create a spectrum of intelligence behavior ranging from absolute randomness to local search-oriented computational architecture. These were then used to solve a set of centered and non-centered benchmark suites to see if statistically different patterns would emerge. The obtained result clearly highlighted that the algorithm’s performance would suffer significantly as these benchmarks got more intricate. This is not just in terms of the number of dimensions in the search space but also the mathematical structure of the benchmark. The implication is that, in some cases, sheer processing resources can mask the algorithm’s lack of sufficient intelligence. But as importantly, this study attempted to identify some mechanics and concepts that could potentially cause or amplify this problem. For instance, the excessive use of greedy strategy, a prevalent measure embedded in many modern CI-based algorithms, has been identified as potentially one of these reasons. The result, however, highlights a more fundamental problem in the CI-based optimization field. That is, these algorithms are often treated as a black box. This perception cultivated the culture of not exploring the underlying structure of these algorithms as long as they were deemed capable of generating acceptable results, which permits similar biases to go undetected
A call for a fundamental shift from model-centric to data-centric approaches in hydroinformatics
This is the final version. Available on open access from Cambridge University Press via the DOI in this record. Data availability statement: All used data have been presented in the paper.Over the years, data-driven models have gained notable traction in water and environmental engineering. The adoption of these cutting-edge frameworks is still in progress in the grand scheme of things, yet for the most part, such attempts have been centered around the models themselves, and their internal computational architecture, that is, the model-centric approach. These endeavors can certainly pave the way for more tailor-fitted models capable of producing accurate results. However, such a perspective often neglects a fundamental assumption of these models, which is the importance of reliability, correctness, and accessibility of the data used in constructing them. This challenge arises from the prevalent model-centric paradigm of thinking in the field. An alternative approach, however, would prioritize placing data at the focal point, focusing on systematically enhancing current datasets and devising frameworks to improve data collection schemes. This suggests a paradigm shift toward more data-centric thinking in water and environmental engineering. Practically, this shift is not without challenges and necessitates smarter data collection rather than an excessive one. Equally important is the ethical and accurate collection of data, making it available to everyone while safeguarding the rights of individuals and other legal entities involved in the process.European Union Horizon 202
Sensitivity of non-conditional climatic variables to climate-change deep uncertainty using Markov Chain Monte Carlo simulation
This is the final version. Available on open access from Nature Research via the DOI in this recordData availability:
The data that support the findings of this study are available from the corresponding author upon reasonable request.There is substantial evidence suggesting climate change is having an adverse impact on the world's water resources. One must remember, however, that climate change is beset by uncertainty. It is therefore meaningful for climate change impact assessments to be conducted with stochastic-based frameworks. The degree of uncertainty about the nature of a stochastic phenomenon may differ from one another. Deep uncertainty refers to a situation in which the parameters governing intervening probability distributions of the stochastic phenomenon are themselves subjected to some degree of uncertainty. In most climatic studies, however, the assessment of the role of deep-uncertain nature of climate change has been limited. This work contributes to fill this knowledge gap by developing a Markov Chain Monte Carlo (MCMC) analysis involving Bayes' theorem that merges the stochastic patterns of historical data (i.e., the prior distribution) and the regional climate models' (RCMs') generated climate scenarios (i.e., the likelihood function) to redefine the stochastic behavior of a non-conditional climatic variable under climate change conditions (i.e., the posterior distribution). This study accounts for the deep-uncertainty effect by evaluating the stochastic pattern of the central tendency measure of the posterior distributions through regenerating the MCMCs. The Karkheh River Basin, Iran, is chosen to evaluate the proposed method. The reason for selecting this case study was twofold. First, this basin has a central role in ensuring the region's water, food, and energy security. The other reason is the diverse topographic profile of the basin, which imposes predictive challenges for most RCMs. Our results indicate that, while in most seasons, with the notable exception of summer, one can expect a slight drop in the temperature in the near future, the average temperature would continue to rise until eventually surpassing the historically recorded values. The results also revealed that the 95% confidence interval of the central tendency measure of computed posterior probability distributions varies between 0.1 and 0.3 °C. The results suggest exercising caution when employing the RCMs' raw projections, especially in topographically diverse terrain.Iran National Science Foundation (INSF
The sustainability of desalination as a remedy to the water crisis in the agriculture sector: An analysis from the climate-water-energy-food nexus perspective
This is the final version. Available on open access from Elsevier via the DOI in this recordData Availability:
No data was used for the research described in the article.Over the years, desalination has become integral to water resources management, primarily in coastal semi-arid to arid regions. While desalinated seawater has mainly been supplied to municipal and high-revenue industries, the agriculture sector faces increasing irrigation demands, making it a potential user. This review assesses the sustainability of using desalinated seawater for irrigation, shedding light on its limitations and potential. Using desalinated water for irrigation presents challenges, including its high energy consumption, potential contribution to climate change, and agronomy-related concerns. However, evidence suggests that these challenges can be addressed effectively through tailor-fitted strategies. That said, conventional binary decision-making paradigms that label practices as good or bad and focus on a singular, isolated aspect are insufficient for evaluating the sustainability of desalination due to the complex and interconnected nature of the issues involved. To overcome this, the climate-water-energy-food (CWEF) nexus concept is proposed as a comprehensive framework for sustainability assessment. Adopting the CWEF nexus approach allows for a better understanding of the potential challenges associated with using desalinated water for irrigation, encompassing social, economic and environmental concerns. To ensure effective management of these challenges, it is crucial to tailor desalination projects to specific regional conditions and employ either prophylactic or corrective strategies. By embracing the CWEF nexus approach, informed decisions can be made regarding the future utilization of desalinated water for irrigation, contributing to broader sustainability goals
FTIR diferentiation based on genomic DNA for species identifcation of Shigella isolates from stool samples
Shigellosis is one of the major public health concerns in developing and low-income countries caused
by four species of Shigella. There is an apparent need to develop rapid, cost-efective, sensitive and
specifc methods for diferentiation of Shigella species to be used in outbreaks and health surveillance
systems. We developed a sensitive and specifc Fourier-transform infrared spectroscopy (FTIR) based
method followed by principal component analysis (PCA) and hierarchical clustering analysis (HCA)
assays to diferentiate four species of Shigella isolates from stool samples. The FTIR based method
was evaluated by diferentiation of 91 Shigella species from each other in clinical samples using both
gold standards (culture-based and agglutination methods) and developed FTIR assay; eventually, the
sensitivity and specifcity of the developed method were calculated. In summary, four distinct FTIR
spectra associated with four species of Shigella were obtained with wide variations in three defnite
regions, including 1800–1550 cm−1, 1550–1100 cm−1, and 1100–800 cm−1 distinguish these species
from each other. In this study, we found the FTIR method followed by PCA analysis with specifcity,
sensitivity, diferentiation error and correct diferentiation rate values of 100, 100, 0 and 100%,
respectively, for identifcation and diferentiation of all species of the Shigella in stool samples
A robust multiple-objective decision-making paradigm based on the water-energy-food security nexus under changing climate uncertainties
This is the final version. Available on open access from Nature Research via the DOI in this recordData availability;
The data that support the findings of this study are available from the corresponding author upon reasonable request.From the perspective of the water-energy-food (WEF) security nexus, sustainable water-related infrastructure may hinge on multi-dimensional decision-making, which is subject to some level of uncertainties imposed by internal or external sources such as climate change. It is important to note that the impact of this phenomenon is not solely limited to the changing behavior patterns of hydro-climatic variables since it can also affect the other pillars of the WEF nexus both directly and indirectly. Failing to address these issues can be costly, especially for those projects with long-lasting economic lifetimes such as hydropower systems. Ideally, a robust plan can tolerate these projected changes in climatic behavior and their associated impacts on other sectors, while maintaining an acceptable performance concerning environmental, socio-economic, and technical factors. This study, thus, aims to develop a robust multiple-objective decision-support framework to address these concerns. In principle, while this framework is sensitive to the uncertainties associated with the climate change projections, it can account for the intricacies that are commonly associated with the WEF security network. To demonstrate the applicability of this new framework, the Karkheh River basin in Iran was selected as a case study due to its critical role in ensuring water, energy, and food security of the region. In addition to the status quo, a series of climate change projections (i.e., RCP 2.6, RCP 4.5, and RCP 8.5) were integrated into the proposed decision support framework as well. Resultantly, the mega decision matrix for this problem was composed of 56 evaluation criteria and 27 feasible alternatives. A TOPSIS/Entropy method was used to select the most robust renovation plan for a hydropower system in the basin by creating a robust and objective weighting mechanism to quantify the role of each sector in the decision-making process. Accordingly, in this case, the energy, food, and environment sectors are objectively more involved in the decision-making process. The results revealed that the role of the social aspect is practically negligible. The results also unveiled that while increasing the power plant capacity or the plant factor would be, seemingly, in favor of the energy sector, if all relevant factors are to be considered, the overall performance of the system might resultantly become sub-optimal, jeopardizing the security of other aspects of the water-energy-food nexus.Iran National Science Foundation (INSF
Discourse over the sustainability of irrigation with desalinated water in light of the water-energy-food nexus
This is the final version. Available from EWRA via the link in this recordDesalinated seawater has gained increasing popularity as an option for water-stressed regions
worldwide to meet a general increase in water demand across most sectors. Considering current water and
food crises that are exacerbating in many regions, desalination has gained traction as a suitable solution to
alleviate these problems as a potentially limitless alternative water source. The agricultural industry is the
largest global water consumer and the sector that is most likely to benefit from this technology to meet the
increasing demand for irrigation. Despite the technology’s considerable potential, there are numerous
issues related the technology’s sustainability that may prevent it from becoming a widely used solution for
irrigation purposes. However, being affected by numerous interconnected factors, water resources
problems are nuanced and multi-disciplinary. To account for these intricacies in the evaluation of the
sustainability of this option for irrigation, the concept of the Water-Energy-Food (WEF) Security Nexus can
be used. This paper provides a preliminary evaluation of the sustainability of the use of desalinated water
for irrigation considering the WEF Security Nexus
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System dynamics modeling of lake water management under climate change
This is the final version. Available on open access from Nature Research via the DOI in this recordAvailability of data and materials:
The data that support the findings of this study are available from the corresponding author upon reasonable request.Code availability:
The codes that support the findings of this study are available from the corresponding author upon reasonable request.Lake Urmia, the twentieth largest lake in the world, is the most valuable aquatic ecosystem in Iran. The lake water level has decreased in recent years due to human activities and climate change. Several studies have highlighted the significant roles of climatic and anthropogenic factors on the shrinkage of the lake. Management policies for water resources harvesting must be adopted to adapt to climate change and avoid the consequent problems stemming from the drought affecting Lake Urmia, and rationing must be applied to the upstream water demands. This study analyzes strategies and evaluates their effectiveness in overcoming the Urmia Lake crisis. Specifically, system dynamics analysis was performed for simulating the water volume of Lake Urmia, and the Hadley Centre coupled model was applied to project surface temperature and precipitation for two future periods: 2021-2050 and 2051-2080. Six management scenarios were considered for decreasing the allocation of agricultural water demand corresponding to two options: (1) one-reservoir option (Bukan reservoir only), and (2) six-reservoir option. The net inflow of Urmia Lake was simulated for the two future periods with the IHACRES model and with artificial neural network models under the six management scenarios. The annual average volumes of Lake Urmia would be 30 × 109 and 12 × 109 m3 over the first and second future periods, respectively, without considering the management scenarios. The lake volumes would rise by about 50% and 75% for the first and second periods, respectively under the management scenarios that involve strict protective measures and elimination of the effect of all dams and their reservoirs. Implementing strict measures would increase the annual average lake volume to 21 × 109 m3 in the second period; yet, this volume would be less than the long-term average and strategic volume. The human water use would be completely eliminated under Scenario 6. Nevertheless, Lake Urmia would experience a considerable loss of storage because of drought.Iran National Science Foundation (INSF
A review of limitations and potentials of desalination as a sustainable source of water
This is the final version. Available on open access from Springer via the DOI in this recordData availability:
All used data have been presented in the paper.For centuries, desalination, in one way or another, has helped alleviate water scarcity. Over time, desalination has gone through an evolutionary process influenced largely by available contemporary technology. This improvement, for the most part, was reflected in the energy efficiency and, in turn, in terms of the cost-effectiveness of this practice. Thanks to such advancements, by the 1960s, the desalination industry experienced notable exponential growth, becoming a formidable option to supplement conventional water resources with a reliable non-conventional resource. That said, often, there are pressing associated issues, most notably environmental, socioeconomic, health, and relatively recently, agronomic concerns. Such reservations raise the question of whether desalination is indeed a sustainable solution to current water supply problems. This is exceptionally important to understand in light of the looming water and food crises. This paper, thus, tends to review these potential issues from the sustainability perspective. It is concluded that the aforementioned issues are indeed major concerns, but they can be mitigated by actions that consider the local context. These may be either prophylactic, proactive measures that require careful planning to tailor the situation to best fit a given region or reactive measures such as incorporating pre- (e.g., removing particles, debris, microorganisms, suspended solids, and silt from the intake water prior to the desalination process) and post-treatments (e.g., reintroducing calcium and magnesium ions to water to enhance its quality for irrigation purposes) to target specific shortcomings of desalination
Comparative study of the extracellular proteome of Sulfolobus species reveals limited secretion
Although a large number of potentially secreted proteins can be predicted on the basis of genomic distribution of signal sequence-bearing proteins, protein secretion in Archaea has barely been studied. A proteomic inventory and comparison of the growth medium proteins in three hyperthermoacidophiles, i.e., Sulfolobus solfataricus, S. acidocaldarius and S. tokodaii, indicates that only few proteins are freely secreted into the growth medium and that the majority originates from cell envelope bound forms. In S. acidocaldarius both cell-associated and secreted α-amylase activities are detected. Inactivation of the amyA gene resulted in a complete loss of activity, suggesting that the same protein is responsible for the a-amylase activity at both locations. It is concluded that protein secretion in Sulfolobus is a limited process, and it is suggested that the S-layer may act as a barrier for the free diffusion of folded proteins into the medium
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