Increase In Population Size Research Articles

Comparative analysis of cancer statistics in China and the United States in 2024.

Cancer patterns in China are becoming similar to those in the United States (US). Comparing the recent cancer profiles, trends, and determinants in China and the US can provide useful reference data. This study used open-source data. We used GLOBOCAN 2022 cancer estimates and United Nations population estimates to calculate cancer cases and deaths in both countries during 2024. Data on cancer incidence and mortality trends were obtained from the Surveillance, Epidemiology, and End Results (SEER) program and National Centre for Health Statistics in the US and cancer registry reports of the National Cancer Center (NCC) of China. Data from the Global Burden of Disease study (GBD) and a decomposition approach were used to estimate the contributions of four determinants to the change in cancer deaths. In 2024, there are an estimated 3,246,625 and 2,510,597 new cancer cases and 1,699,066 and 640,038 cancer deaths in China and the US, respectively. The highest estimated cancer cases are lung cancer in China and breast cancer in the US. The age-standardized incidence rates of lung and colorectal cancer in the US, and stomach, liver, and esophageal cancer in China have decreased, but the incidence rates of liver cancer in the US and colorectal cancer, prostate cancer in men, and cervical cancer in women in China have increased. Increases in the adult population size and population aging are main reasons for the increase in cancer deaths; case fatality rates are a main reason for the decrease in cancer deaths in both countries. China has made progress in cancer control but lags the US. Considering the transformation in China's pattern of cancers epidemiology, it is imperative to develop stronger policies by adopting the cancer prevention and control strategies used in the US to address population aging and curb growing cancer trends.

Genetic insights and conservation strategies for Amur tigers in Southwest Primorye Russia

Southwest Primorye hosts approximately 9% of the remaining wild Amur tiger population and represents hope for the revival of tigers in Northeast China and the Korean peninsula. Decades of conservation efforts have led to a significant increase in population size, from less than 10 individuals surviving in the region in 1996 to multiple folds today. However, while the population size has recovered since the mid-1900s, the effects of genetic depletion on evolutionary potential are not easily reversed. In this study, a non-invasive genetic analysis of the Amur tiger subpopulation in Southwest Primorye was conducted using microsatellite loci and mitochondrial genes to estimate genetic diversity, relatedness, and determine the impact of historical demographic dynamics. A total of 32 individuals (16 males, 15 females, and 1 unidentified sex) were identified, and signs of bottlenecks were detected, reflecting past demographic events. Low genetic variation observed in mitochondrial DNA also revealed genetic depletion within the population. Most individuals were found to be closely related to each other, raising concerns about inbreeding given the small population size and somewhat isolated environment from the main population in Sikhote-Alin. These findings emphasize the urgent need to establish ecological corridors to neighboring areas to restore genetic diversity and ensure the conservation of the Amur tiger population in Southwest Primorye.

Impact of regional integration policy on urban ecological resilience: A case study of the Yangtze River Delta region, China

Regional integration is a key facet of economic globalization that facilitates the efficient movement and optimal distribution of resources. Although its economic and environmental impacts are well-documented, the implications for ecological resilience (ER) are not yet fully understood. This study examines China's Yangtze River Delta and introduces an ER metric that assesses resistance, adaptability, and recovery. The analysis revealed that regional integration policies have notably boosted urban ER by 2.73%, a result that is upheld by rigorous testing methods such as parallel trends and placebo assessments. Furthermore, the impact of these policies on ER was variable, with a slight reduction in influence as the economic scale and population size increase. Moreover, the results indicate that regional integration can bolster urban ER by refining industrial structures and advancing green technological innovations. Interestingly, the positive impact of green innovation on ER enhancement was more significant than that of industrial upgrading. These insights contribute to a deeper understanding of the ecological implications of regional integration, and offer practical guidance for enhancing ER in integrated regions.

Genome streamlining: effect of mutation rate and population size on genome size reduction.

Genome streamlining, i.e. genome size reduction, is observed in bacteria with very different life traits, including endosymbiotic bacteria and several marine bacteria, raising the question of its evolutionary origin. None of the hypotheses proposed in the literature is firmly established, mainly due to the many confounding factors related to the diverse habitats of species with streamlined genomes. Computational models may help overcome these difficulties and rigorously test hypotheses. In this work, we used Aevol, a platform designed to study the evolution of genome architecture, to test two main hypotheses: that an increase in population size (N) or mutation rate (μ) could cause genome reduction. In our experiments, both conditions lead to streamlining but have very different resulting genome structures. Under increased population sizes, genomes lose a significant fraction of non-coding sequences but maintain their coding size, resulting in densely packed genomes (akin to streamlined marine bacteria genomes). By contrast, under an increased mutation rate, genomes lose both coding and non-coding sequences (akin to endosymbiotic bacteria genomes). Hence, both factors lead to an overall reduction in genome size, but the coding density of the genome appears to be determined by N × μ. Thus, a broad range of genome size and density can be achieved by different combinations of N and μ. Our results suggest that genome size and coding density are determined by the interplay between selection for phenotypic adaptation and selection for robustness.

Achieving universal energy access in remote locations using HOMER energy model: a techno-economic and environmental analysis of hybrid microgrid systems for rural electrification in northeast Nigeria

The developing world continues to face substantial obstacles to achieving affordable and dependable electricity access. This issue is especially pertinent for Nigeria, where diesel generators are widely relied upon in urban and rural regions because of an underdeveloped and unreliable national grid. The lack of grid reliability is worsened in Northeastern Nigeria, an area plagued by conflict, extreme poverty, and grid infrastructure deterioration. This study investigates the feasibility of implementing community-scale microgrids in rural areas without grid connection access. It focuses on assessing the technical, economic, and environmental aspects of utilizing these microgrids to deliver inexpensive and dependable electricity to underserved populations to increase energy access. A case study was conducted in Kabuiri, a village with an estimated population of 2,300 residents and an estimated load demand of 610 kWh per day. A hybrid microgrid system was designed and optimized to meet the community’s load demand using HOMER software, sized to produce 610 kWh/day of electricity with a renewable penetration of 99%. The optimal solar PV/battery/generator system had a levelized cost of electricity (LCOE) of $ 0.093 per kWh, a net present cost (NPC) of $266,709, and an annual operating cost of $9,110. The system contributed 1,624 kg CO2 eq/year of global warming potential and 56.81 kg O3 eq/year of smog formation during operation. Sensitivity analysis showed that the system could effectively react to or adapt to substantial increases in diesel prices, requiring only marginal increases in photovoltaic capacity and reduced generator usage to maintain the most cost-efficient operation. Additionally, the system model can be adapted based on the population of the remote community without substantially impacting the LCOE, however, the NPC increases with increase in population size. This research will aid in increasing energy access in remote locations by providing insights to stakeholders and energy access project developers.

The concept of critical age group for density dependence: bridging the gap between demographers, evolutionary biologists and behavioural ecologists.

Density dependence plays an important role in population regulation in the wild. It involves a decrease in population growth rate when the population size increases. Fifty years ago, Charlesworth introduced the concept of 'critical age group', denoting the age classes in which variation in the number of individuals most strongly contributes to density regulation. Since this pioneering work, this concept has rarely been used. In light of Charlesworth's concept, we discuss the need to develop work between behavioural ecology, demography and evolutionary biology to better understand the mechanisms acting in density-regulated age-structured populations. We highlight demographic studies that explored age-specific contributions to density dependence and discuss the underlying evolutionary processes. Understanding competitive interactions among individuals is pivotal to identify the ages contributing most strongly to density regulation, highlighting the need to move towards behavioural ecology to decipher mechanisms acting in density-regulated age-structured populations. Because individual characteristics other than age can be linked to competitive abilities, expanding the concept of critical age to other structures (e.g. sex, dominance rank) offers interesting perspectives. Linking research fields based on the concept of the critical age group is key to move from a pattern-oriented view of density regulation to a process-oriented approach.This article is part of the discussion meeting issue 'Understanding age and society using natural populations'.

Sharp habitat shifts, evolutionary tipping points and rescue: Quantifying the perilous path of a specialist species towards a refugium in a changing environment

Specialist species thriving under specific environmental conditions in narrow geographic ranges are widely recognized as heavily threatened by climate deregulation. Many might rely on both their potential to adapt and to disperse towards a refugium to avoid extinction. It is thus crucial to understand the influence of environmental conditions on the unfolding process of adaptation. Here, I study the eco-evolutionary dynamics of a sexually reproducing specialist species in a two-patch quantitative genetic model with moving optima. Thanks to a separation of ecological and evolutionary time scales and the phase-line study of the selection gradient, I derive the critical environmental speed for persistence, which reflects how the existence of a refugium impacts extinction patterns and how it relates to the cost of dispersal. Moreover, the analysis provides key insights about the dynamics that arise on the path towards this refugium. I show that after an initial increase of population size, there exists a critical environmental speed above which the species crosses a tipping point, resulting into an abrupt habitat switch. In addition, when selection for local adaptation is strong, this habitat switch passes through an evolutionary “death valley”, leading to a phenomenon related to evolutionary rescue, which can promote extinction for lower environmental speeds than the critical one.

An Update on the Conservation Status Assessment of two Endangered Freshwater Mussel Species in Bavaria, Germany

ABSTRACTThe two highly endangered European mussel species Margaritifera margaritifera and Unio crassus are target species of conservation. Based on a recently completed systematic state‐wide monitoring of each 22 M. margaritifera and 22 U. crassus streams in Bavaria, Germany, we present an update on population trends, conservation status, habitat quality and threats for both species. Populations status and habitat quality varied strongly between M. margaritifera and U. crassus streams, but there was also great variability within each of those groups. The population decline of M. margaritifera has continued, albeit higher proportions of juveniles originating from artificial breeding programmes have been established in some streams. Habitat quality often did not match known requirements as evident from poor stream bed quality, lack of hosts and elevated nutrient levels. In contrast, U. crassus populations showed a better status, with an increase in population size over all sampled streams. Successful recruitment was indicated by high proportions of juveniles. However, no mussels older than 16 years were found, probably due to predation and structural stream maintenance measures. Climate change effects, such as extreme droughts, affected both species. This study demonstrates different needs in conservation management for both species. Although mitigation of drought effects is commonly needed for both species, tackling host fish management and direct threats such as predation should be prioritized in U. crassus, whereas restoration of prime habitat quality and intact catchments is key to enable natural recruitment and sustainable populations of M. margaritifera.

Using Genetic Data to Determine Origin for Out-Migrating Smolt and Returning Adult Steelhead Trout (Oncorhynchus mykiss) in a Southeast Alaska Drainage.

Oncorhynchus mykiss is a partially migratory salmonid species, and many migratory populations (known as steelhead) have declined in recent decades in the western United States and Canada. Closely related resident populations (known as rainbow trout) may be an effective resource in the recovery of these declining migratory populations. However, the extent to which different populations of resident rainbow trout produce migratory individuals and how likely these individuals are to return as adults to spawn remains unknown. One limitation to answering these questions is the identification of loci that accurately segregate between migratory and resident populations. To address this limitation, we used existing genomic data from a well-studied population of O. mykiss from Southeastern Alaska (Sashin Creek) to identify loci that segregate between phenotypes. We then utilized Double Mismatch Allele-Specific qPCR (DMAS-qPCR) to genotype 233 smolts out-migrating from Sashin Creek and 99 returning adult steelhead trout across a five-year period to determine (a) the origin of out-migrating smolts and returning adults and (b) to quantify the extent to which the resident population contributes to the migratory population. Our results show that 37.3% of out-migrating smolts were produced from resident parents, whereas 19.3% of returning adults had resident parents. Ultimately, these results demonstrate that resident populations of rainbow trout produce migrant offspring that successfully complete their migration and return to spawn, increasing population sizes and likely improving genetic diversity. Therefore, conservation efforts should consider landlocked resident populations for producing smolts when developing recovery plans for migratory steelhead populations.

Dual carbon economy modeling in advanced economies

Utilizing the cross-sectional fully modified OLS (FMOLS) method, this paper tackles the pressing need to address climate change disasters, particularly in the context of recent COVID-19 restrictions. By developing an econometric model specifically for advanced economies, the study aims to enhance understanding and reduce carbon emissions. Examining ten advanced economies from 1995 to 2019, it identifies a significant gap in the literature concerning the integration of demographic, social, economic, and political (DSEP) factors in dual carbon economy models. The results show that a 1% improvement in good governance is associated with a 0.23% reduction in carbon footprint, due to stricter environmental regulations. In contrast, a 1% increase in economic growth results in a 0.17% rise in carbon footprint, driven by industrial activities. Similarly, a 1% rise in electricity consumption leads to a 0.32% increase in carbon footprint, reflecting dependence on fossil fuels. Additionally, a 1% increase in population size corresponds to a 0.21% rise in carbon footprint, linked to higher urban energy consumption. Finally, a 1% increase in the poverty ratio results in a 0.17% rise in carbon footprint, underscoring the influence of socio-economic factors on sustainability. The paper advocates for a comprehensive approach to fostering a dual carbon economy, emphasizing green economic growth, smart, sustainable cities, social sustainability literacy, and sustainable governance.

The effects of climate and population on human land use patterns in Europe from 22ka to 9ka ago

Between 22ka and 9ka ago, after the Last Glacial Maximum (LGM) and during the transition to the Holocene, mobile hunter-gatherer populations, differentiated by their stone tool assemblages, periodically dispersed and contracted across Europe. It is well understood that climate played an important role in human distributions and population sizes during the post-LGM Late Pleistocene and Early Holocene, but the question remains as to whether increasing population sizes drove early human dispersal. Here, using a spatiotemporal species distribution model to infer the fundamental and potential human climatic niche space of Late Upper Paleolithic, Final Paleolithic and Early Mesolithic Europe, and hypotheses derived from the Ideal Distribution Model, we test i) how changes in climate affected the size and extent of the projected potential human niche space, ii) for effects of changes in size of projected potential niche on regional human population sizes, iii) whether increasing human population sizes drove human dispersal into less climatically suitable habitats, and iv) whether populations associated with different high-order material culture groupings (macro-level technocomplexes) occupied different climatic spaces. We find that changes in climate correlate strongly with the size and extent of the projected potential human niche space, that increases in the projected human niche space correlate with increases in human population, that human population size is just beginning to become large enough to influence land use and dispersal patterns at the Pleistocene-Holocene transition, and that archaeological technocultural entities overlap in their fundamental climatic niche space. This overlap implies that changing tools forms cannot readily been seen as reflecting adaptations to changing climates.

Fragmented micro-growth habitats present opportunities for alternative competitive outcomes

Bacteria in nature often thrive in fragmented environments, like soil pores, plant roots or plant leaves, leading to smaller isolated habitats, shared with fewer species. This spatial fragmentation can significantly influence bacterial interactions, affecting overall community diversity. To investigate this, we contrast paired bacterial growth in tiny picoliter droplets (1–3 cells per 35 pL up to 3–8 cells per species in 268 pL) with larger, uniform liquid cultures (about 2 million cells per 140 µl). We test four interaction scenarios using different bacterial strains: substrate competition, substrate independence, growth inhibition, and cell killing. In fragmented environments, interaction outcomes are more variable and sometimes even reverse compared to larger uniform cultures. Both experiments and simulations show that these differences stem mostly from variation in initial cell population growth phenotypes and their sizes. These effects are most significant with the smallest starting cell populations and lessen as population size increases. Simulations suggest that slower-growing species might survive competition by increasing growth variability. Our findings reveal how microhabitat fragmentation promotes diverse bacterial interaction outcomes, contributing to greater species diversity under competitive conditions.

Does self-containment of spatial scale and land use function contribute to mitigate urban heat island effects? Lessons from new towns in Shanghai

The concept of self-containment in new towns has been widely discussed from social and economic perspectives. However, localized interpretations within the context of China's development, particularly regarding climate adaptability and urban heat island (UHI) mitigation, are scarce. To fill this gap, our research analyzed self-containment from the perspectives of urban spatial scale and land use function. Focusing on Shanghai’s five new towns, we empirically demonstrated how self-containment influenced the UHI effects from 2005 to 2020, employing the Geodetector method. The findings reveal that during the daytime, the intensity of UHI in new towns decreased, serving as vital connectivity nodes of UHI within the region. Conversely, during the nighttime, both the intensity and area of UHI showed an increasing trend. The research confirmed that expanding the urban scale and functional diversity are effective strategies for mitigating the UHI. Based on these findings, we offer practical suggestions for the development of new towns: Increase population size while ensuring coordination with development scale; enhance mixed-use functions in large-scale development projects like university towns and industrial parks; and be vigilant of potential functional decline in central areas and increasing thermal impact due to new town development. Overall, this study enriches our understanding of self-containment in Chinese new towns and provides valuable insights for mitigating UHI in other similar contexts.

Parasites and the ecology of fear: Nonconsumptive effects of ectoparasites on larvae reduce growth in simulated Drosophila populations.

Predators negatively affect prey outside of direct attack, and these nonconsumptive effects (NCEs) may cause over half the impacts of predators on prey populations. This "ecology of fear" framework has been extended to host-parasite interactions. The NCEs of parasites are thought to be small relative to those of predators. However, recent research shows ectoparasites exert NCEs on multiple life stages of Drosophila. In this study, we apply recent data to a matrix-based model of fly populations experiencing infection/consumption and NCEs from an ectoparasitic mite. We found the NCEs of parasites on larvae, which are not actively parasitized, decreased the size of simulated host populations. By contrast, the NCEs on adult flies increased population size through compensatory egg production. The negative NCEs on larvae outweighed the positive effects on adults to reduce population size. This study suggests that parasitic NCEs can suppress host populations independent of infection.

The Urban Planning of Surabaya City with The Aim of Creating a Green City

Surabaya is the second largest city in Indonesia, with a population of 2,987,863 individuals as of 2022. The presence of a large population inevitably leads to an increase in both environmental impacts and societal needs. The high population in Surabaya city will result in significant environmental impacts due to human activities. The increase in population size has resulted in a corresponding increase in the demand for land to accommodate the development of infrastructure necessary to meet the needs of urban residents. This development often involves the displacement and conversion of existing green spaces into built-up areas, leading to a reduction in the availability of green spaces within the city

POPULATION STRUCTURE AND INBREEDING RATE OF INDIGENOUS PIG IN SOME COMMUNITIES OF NASARAWA STATE

The study was carried out in some selected communities of Nasarawa state, north central Nigeria to characterize the population structure and to identify inbreeding rate among indigenous pig herds. Data were gathered through survey and direct count. The pigs were classified into sex, age, state of maturity and physiological status. The effective population size (Ne) and rate of inbreeding (AF) were calculated from the counted population structure data. The population structure was dominated by younger age group with male piglet having the highest number on the average per household. The effective population size varies between 54.1 to 106.2 while the inbreeding rate for the populations were between 0.002 to 0.018. Inbreeding rate was at a low level and the effective population size was also small an indication of threat in the genetic diversity of the population and possible decline in performance, thus the need for effective breeding and conservation programme to sustain the diversity and increase population size.

Bayesian expectation maximization-maximization for robust estimation in proton exchange membrane fuel cells: A comparative study

In this paper, we present a novel approach based on Bayesian Expectation Maximization-Maximization (BEMM) to address this challenge. Unlike traditional optimization methods, which may struggle with high-dimensional and nonlinear optimization problems, BEMM offers a robust framework that combines the benefits of Bayesian inference with the flexibility of expectation maximization and maximization techniques. By iteratively updating parameter estimates based on observed data and maximizing the likelihood of the model, BEMM effectively navigates the solution space to converge on accurate estimates of the unspecified variables in Proton Exchange Membrane Fuel Cells (PEMFCs)models. Through extensive experimentation and comparison with other metaheuristic techniques, including Arithmetic Optimization Algorithm (AOA), Gravitational Search Algorithm (GSA), Flower Pollination Algorithm (FPA), and Biogeography-Based Optimization (BBO), we demonstrate the superior performance of our BEMM approach. Our results show that BEMM outperforms these alternative methods in terms of precision, convergence speed, and stability across various scenarios involving different numbers of unspecified variables. The implications of our findings are significant for both researchers and practitioners in the field of PEMFC modeling and optimization. By providing a more efficient and reliable method for estimating model parameters, our approach can facilitate more accurate predictions of PEMFC performance, leading to better-informed decision-making in the design, operation, and optimization of PEMFC systems. Furthermore, the robustness and versatility of BEMM make it well-suited for a wide range of optimization problems beyond PEMFC modeling, highlighting its potential impact across various domains of engineering and scientific research. In the sensitivity analysis, as the population size increases from 10 to 40, there is a significant improvement in solution quality by approximately 100 %. However, beyond a population size of 40, the marginal gains diminish, with only marginal improvements of less than 1 % observed despite further increases in population size up to 200.

Epidemiology of carbapenem-resistant Klebsiella pneumoniae in China and the evolving trends of predominant clone ST11: a multicentre, genome-based study.

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a major nosocomial infectious pathogen with rapidly increasing prevalence. The genomic epidemiological characteristics of CRKP nationwide, especially the evolving trends within the predominant clones, should be evaluated clearly. We collected 3415 K. pneumoniae strains from 28 hospitals across China. Antimicrobial susceptibility testing and WGS were performed. Subsequent genomic analyses, including sequence typing, K-locus (KL) identification, antimicrobial resistance gene screening, and virulence score assessment were performed. The phylogenetic relationship of clonal group 11 was determined based on core-genome analysis, and the presence of the pLVPK-like virulence plasmid in ST11 isolates was confirmed using plasmid core-gene analysis. Additionally, the trends of the ST11 lineage with different KL types on a global scale were investigated using Beast2. Of the K. pneumoniae strains, 708 were identified as CRKP isolates (20.7%), of which 97.7% were MDR. ST11 was the predominant clone, and KPC-2 was the prevalent carbapenemase in China, although the prevalence of specific clones and carbapenemases varied by geographic region. Among ST11 isolates, KL47 and KL64 were the predominant KL types, and KL64 gradually replaced KL47, with a higher percentage of KL64 isolates harbouring the pLVPK-like plasmid. Global genome data showed a significant increase in the effective population size of KL64 over the last 5 years. The prevalence of CRKP was very high in certain regions in China. The increasing convergence of virulence and resistance, particularly in ST11-KL64 isolates, should be given more attention and further investigation.

Centrality to the metapopulation is more important for population genetic diversity than habitat area or fragmentation.

Drift and gene flow affect genetic diversity. Given that the strength of genetic drift increases as population size decreases, management activities have focused on increasing population size through preserving habitats to preserve genetic diversity. Few studies have empirically evaluated the impacts of drift and gene flow on genetic diversity. Kryptolebias marmoratus, henceforth 'rivulus', is a small killifish restricted to fragmented New World mangrove forests with gene flow primarily associated with ocean currents. Rivulus form distinct populations across patches, making them a well-suited system to test the extent to which habitat area, fragmentation and connectivity are associated with genetic diversity. Using over 1000 individuals genotyped at 32 microsatellite loci, high-resolution landcover data and oceanographic simulations with graph theory, we demonstrate that centrality (connectivity) to the metapopulation is more strongly associated with genetic diversity than habitat area or fragmentation. By comparing models with and without centrality standardized by the source population's genetic diversity, our results suggest that metapopulation centrality is critical to genetic diversity regardless of the diversity of adjacent populations. While we find evidence that habitat area and fragmentation are related to genetic diversity, centrality is always a significant predictor with a larger effect than any measure of habitat configuration.

Modified-improved fitness dependent optimizer for complex and engineering problems

Fitness dependent optimizer (FDO) is considered one of the novel swarm intelligent algorithms. Recently, FDO has been enhanced several times to improve its capability. One of the improvements is called improved FDO (IFDO). However, according to the research findings, the variants of FDO are constrained by two primary limitations that have been identified. Firstly, if the number of agents employed falls below five, it significantly diminishes the algorithm's precision. Secondly, the efficacy of FDO is intricately tied to the quantity of search agents utilized. To overcome these limitations, this study proposes a modified version of IFDO, called M-IFDO. The enhancement is conducted by updating the location of the scout bee to the IFDO to move the scout bees to achieve better performance and optimal solutions. More specifically, two parameters in IFDO, which are alignment and cohesion, are removed. Instead, the Lambda parameter is replaced in the place of alignment and cohesion. To verify the performance of the newly introduced algorithm, M-IFDO is tested on 19 basic benchmark functions, 10 IEEE Congress of Evolutionary Computation (CECC06 2019), and five real-world problems. M-IFDO is compared against five state-of-the-art algorithms: Improved Fitness Dependent Optimizer (IFDO), Improving Multi-Objective Differential Evolution algorithm (IMODE), Hybrid Sampling Evolution Strategy (HSES), Linear Success-History based Parameter Adaptation for Differential Evolution (LSHADE) and CMA-ES Integrated with an Occasional Restart Strategy and Increasing Population Size and An Iterative Local Search (NBIPOP-aCMAES). The verification criteria are based on how well the algorithm reaches convergence, memory usage, and statistical results. The results show that M-IFDO surpasses its competitors in several cases on the benchmark functions and five real-world problems.