Population Diversity Research Articles

Optimal Combination of Different Selection and Mating Strategies on Exploiting Genetic Diversity and Genetic Gain in Small Pig Conservation Populations.

Both selection and mating systems are essential tools for breeders to conserve the genetic variance and improve the performance of livestock animals. How to effectively balance the genetic gain and inbreeding has always been an important issue in quantitative genetics research. In this study, a total of 11 selection methods, including random and truncation selection, six conventional selection methods, three different optimal contribution selection (OCS) methods and three mating strategies including random mating, minimum-coancestry mating based on pedigree (MCPed) and genomic information (MCmarker), were performed using stochastic simulations. The long-term effects of different combinations of selection and mating strategies on the genetic gain, the rate of inbreeding and genetic diversity in the small-scale pig conservation populations were investigated. The results showed that different strategies of selection and mating methods had different effects on genetic gain and inbreeding rate. For maintaining additive genetic variance, the optimal strategy was random selection with random mating, followed by SIREhalf-DAMfullRandom selection (which means selecting dams randomly from each full-sib family) and random mating. For mainting the number of common ancestors, the optimal strategy was SIREhalf-DAMfull selection (which means selecting dams with the highest estimated breeding value within each full-sib family) and random mating, followed by SIREhalf-DAMfullRandom selection and random mating, OCS and MCPed mating. For genetic diversity metrics, taking He and Ho as an example, the optimal strategy was GOCS (optimal contribution selection based on genomic information) with MCmarker mating. For genetic gain, the optimal strategy was truncation selection and MCmarker mating, followed by POCS (optimal contribution selection based on pedigree information) and MCmarker mating, truncation selection and MCPed mating. For the rate of inbreeding, the optimal strategy was SIREhalf-DAMfull selection and MCPed mating. Our findings can help breeding managers and farmers choose a more suitable and sustainable strategy for maintaining the genetic diversity and improving the genetic gain of local pig breeds.

Genome-Wide Structural Variation Analysis and Breed Comparison of Local Domestic Ducks in Shandong Province, China

Structural variations in the duck genome significantly impact the environmental adaptability and phenotypic diversity of duck populations. Characterizing these SVs in local domestic duck breeds from Shandong province offers valuable insights for breed selection and the development of new breeds. This study aimed to profile the genomic SVs in three local duck breeds (Matahu duck, Weishan partridge duck, and Wendeng black duck) and explore their differential distributions. A total of 21,673 SVs were detected using LUMPY (v0.2.13) and DELLY (v1.0.3) software, with 46% located in intergenic regions, 33% in intronic regions, and frameshift deletions being the most prevalent in exonic regions (3%). SVs distribution showed a decreasing trend with shorter chromosome lengths. Population structure analysis revealed distinct genetic profiles, with Matahu and Weishan partridge ducks showing closer affinities and the Wendeng black duck having a more homogeneous genetic background, likely due to geographic isolation. Functional annotation identified genes related to nervous system development, mitosis, spindle assembly, and energy metabolism. Notable genes included PLXNA4, NRP2, SEMA3A, PTEN, MYBL2, ADK, and COX4I1. Additionally, genes such as PRKG1, GABRA2, and FSHR were linked to energy metabolism and reproductive activity. The study provides a comprehensive analysis of SVs, revealing significant genetic differentiation and identifying genes associated with economically important traits, offering valuable resources for the genetic improvement and breeding of local duck breeds.

Spider (Araneae: Arachnida) Fauna of Sohagi Barwa Wildlife Sanctuary, District Maharajganj, Uttar Pradesh, India

Spiders are known to be excellent indicators of the diversity and well-being of terrestrial populations, and they are vital components of any ecosystem in which they live. Unfortunately, there is very little information available about the systematics, diversity, and ecology of the spiders found at the Sohagi Barwa Wildlife Sanctuary. The current study was conducted from May 2023 to August 2024 in order to investigate the variety of spider fauna in the Sohagi Barwa Wildlife Sanctuary in Maharajganj, Uttar Pradesh, India. A total of 1012 specimens, representing 55 species across 39 genera and 16 families, have been collected. The South Chowk range has the most species richness, whilst the Nichlaul range had the lowest. Araneidae and Lycosidae were prevalent (17%), with Selenopidae (2%) being uncommon. Based on their guild stucture, the spiders were categorized into seven functional groups: stalkers, ambushers, scattered line weavers, ground runners, foliage runners, orb-web builders, and sheet-web builders. The flora and fauna found in these areas are also associated with the highest species richness. The results of this study offer current and helpful information about the variety of species present in the Sohagi Barwa Wildlife Sanctuary, and the knowledge might be applied to further spider research.

Significance of host antimicrobial peptides in the pathogenesis and treatment of acne vulgaris

Acne vulgaris (AV) is a chronic inflammatory condition of the pilosebaceous units characterized by multiple immunologic, metabolic, hormonal, genetic, psycho-emotional dysfunctions, and skin microbiota dysbiosis. The latter is manifested by a decreased population (phylotypes, i.e., genetically distinct bacterial subgroups that play different roles in skin health and disease) diversity of the predominant skin bacterial commensal - Cutinbacterium acnes. Like in other dysbiotic disorders, an elevated expression of endogenous antimicrobial peptides (AMPs) is a hallmark of AV. AMPs, such as human β-defensins, cathelicidin LL-37, dermcidin, or RNase-7, due to their antibacterial and immunomodulatory properties, function as the first line of defense and coordinate the host-microbiota interactions. Therefore, AMPs are potential candidates for pharmaceutical prophylaxis or treating this condition. This study outlines the current knowledge regarding the importance of AMPs in AV pathomechanism in light of recent transcriptomic studies. In particular, their role in improving the tight junctions (TJs) skin barrier by activating the fundamental cellular proteins, such as PI3K, GSK-3, aPKC, and Rac1, is discussed. We hypothesized that the increased expression of AMPs and their patterns in AV act as a compensatory mechanism to protect the skin with an impaired permeability barrier. Therefore, AMPs could be key determinants in regulating AV development and progression, linking acne-associated immune responses and metabolic factors, like insulin/IGF-1 and PI3K/Akt/mTOR/FoxO1 signaling pathways or glucotoxicity. Research and development of anti-acne AMPs are also addressed.

Living by the lake: Plant food diversity in a prehistoric lake‐dwelling community in the Republic of North Macedonia

AbstractThis paper explores the relationship between wetland ecosystems and prehistoric lakeshore settlements within the Lake Ohrid basin (a biodiversity hotspot) by considering plant food systems at Ploča Mičov Grad, North Macedonia. The mid‐fifth millennium (c.4555–4373 to 4437–4241 cal BCE) waterlogged assemblage contained a diverse spectrum of crops and ‘wild’ resources, providing resilience against crop failure. Comparisons to earlier (c.5787–5722 to 5753–5715 cal BCE) and later (c.1878–1688 cal BCE) phases show recurrent patterns of plant use alongside shifts in preferred crops. The range of taxa and intraspecies diversity attests to the ecosystemic and population diversity of the prehistoric landscape.

Genetic Structural Changes While Maintaining Effective Population Size of Bighead Catfish in Nong Han Lake: Implications of Metapopulation Dynamics or Release Activities

ABSTRACTThe Bighead Catfish (Clarias macrocephalus) plays crucial roles in the ecosystem and as a protein source for humans in Nong Han Lake, Thailand, but their ecological and population dynamics, along with their genetic diversity and structure, are poorly understood. Therefore, the dynamics of genetic diversity and differentiation of bighead catfish populations in Nong Han Lake were investigated during 2018–2023 to provide essential insights into preserving biodiversity and maintaining ecological balance. Microsatellite genotyping was used to assess the genetic diversity of one bighead catfish population in 2018, two populations in 2023, and one hatchery population. Potentially stable, effective population sizes and distinct genetic clusters of these populations were identified, which represented the resilience of populations and the complexity of their genetic dynamics. Genetic differentiation between sample dates and among populations suggested that limited recent and historical genetic exchanges could potentially influence genetic structure. The impact of ecological factors, including flooding, metapopulation dynamics, and human interventions, was indicated by unique and shared gene pools among populations and subpopulations in different years. Ongoing assessment of genetic diversity and structure of bighead populations is essential for developing conservation strategies and ensuring sustainable management.

Antecedents For the Adoption of Telemedicine in India: Scale development and validation

Background: Telemedicine is increasingly recognized as a promising solution to healthcare challenges in India, particularly in remote areas. However, the country's vast population and geographic diversity present significant obstacles to providing accessible and high-quality healthcare services to all citizens. By leveraging technology, telemedicine has the potential to bridge this gap and enable remote delivery of medical services. Objective: This study aims to develop and validate a scale that assesses the factors influencing the adoption of telemedicine in the Indian context. Understanding these factors is crucial for identifying key drivers and barriers to telemedicine adoption in India. Design: Quantitative methods were employed for scale development. The instrument development process involved several stages: factor identification, item generation, pre-testing, pilot testing, and scale validation. A structured questionnaire was administered to healthcare professionals, industry experts, and patients who have used or intend to use telemedicine. Setting: Confirmatory factor analysis and subsequent tests, such as reliability and validity tests were conducted to establish the internal consistency of the scales. These statistical analyses aimed to identify underlying factors and ensure accurate measurement of latent variables that affect the adoption of telemedicine. Results: The study established a robust scale to assess the five key factors, which are the vital explanatory variables in telemedicine adoption in India. These meticulously validated scales, encompassing technology, government policy, user attitudes, societal demand, and healthcare professional perspectives, demonstrate high reliability and validity in understanding the adoption dynamics of telemedicine in the context of India. Conclusion: This research offers a validated scale for assessing telemedicine adoption in India, crucial for healthcare service providers, policy makers, and researchers in this field. It enables informed decisions in implementing telemedicine, addressing unique challenges and opportunities, and significantly contributing to optimizing healthcare delivery across India's diverse socio-economic and geographical landscape.

An Improved Spider Wasp Optimizer for UAV Three-Dimensional Path Planning

This paper proposes an Improved Spider Wasp Optimizer (ISWO) to address inaccuracies in calculating the population (N) during iterations of the SWO algorithm. By innovating the population iteration formula and integrating the advantages of Differential Evolution and the Crayfish Optimization Algorithm, along with introducing an opposition-based learning strategy, ISWO accelerates convergence. The adaptive parameters trade-off probability (TR) and crossover probability (Cr) are dynamically updated to balance the exploration and exploitation phases. In each generation, ISWO optimizes individual positions using Lévy flights, DE’s mutation, and crossover operations, and COA’s adaptive update mechanisms. The OBL strategy is applied every 10 generations to enhance population diversity. As the iterations progress, the population size gradually decreases, ultimately yielding the optimal solution and recording the convergence process. The algorithm’s performance is tested using the 2017 test set, modeling a mountainous environment with a Gaussian function model. Under constraint conditions, the objective function is updated to establish a mathematical model for UAV flight. The minimal cost for obstacle-avoiding flight within the specified airspace is obtained using the fitness function, and the flight path is smoothed through cubic spline interpolation. Overall, ISWO generates high-quality, smooth paths with fewer iterations, overcoming premature convergence and the insufficient local search capabilities of traditional genetic algorithms, adapting to complex terrains, and providing an efficient and reliable solution.

The rise of artificial intelligence in teledentistry: A comprehensive review

The integration of Artificial Intelligence (AI) into teledentistry represents an unprecedented step towards increased accessibility in dental care, given India's diversity and vast population. This comprehensive review attempts to outline the practical applications of AI in teledentistry, from patient education, remote diagnosis, treatment planning, to follow-up care. It critically analyses works relating to AI's effectiveness on the detection of caries, monitoring orthodontic, and the preliminary screening of OPMDs in relation to improving health care outcomes, especially in underserved regions. It also highlights challenges such as data privacy, accuracy, acceptance, and need for regulatory clarity among dental professionals and patients. This review primarily proposes the recommendations that we should be attempting to fuse AI based solutions with a human touch as a fixture of provider of dental rendering, based on peer-reviewed study evidence. The practice will change as collaboration is required with AI to pursue a teledental practice that is ethical, effective and accessible to everyone.

Haplotypic diversity of <i>Leptidea morsei</i> (Fenton, 1882) (Lepidoptera, Pieridae) on the northwestern periphery of the area

The first data on haplotypic diversity in natural populations of the L. morsei in the north-east of the Russian plain and in the northern regions of the Urals have been obtained. Our interest is caused by the fact that the northwestern border of this species distribution passes here. Six haplotypes were identified, of which five were found only in the studied region. A comparative analysis of haplotypic diversity in different parts of the species range and the geographical distribution of haplotypes allowed us to draw a preliminary conclusion that the population groupings of L. morsei in the north-west of the range have greater genetic similarity with Asian populations than with isolated Central European ones. The settlement of this species to the north of the Russian Plain and the Urals in the post-Glacial epoch obviously took place along the south of the West Siberian Plain through the Southern Trans-Urals.

Analyses of the Genetic Diversity and Population Structures of Sporothrix spp. Clinical Isolates from Paraíba, Brazil

Sporotrichosis is a subcutaneous mycosis of global distribution, capable of affecting both humans and animals, and caused by species of the genus Sporothrix spp. This study aimed to evaluate the genetic diversity and mating type distribution of clinical isolates of human sporotrichosis in Paraíba, Brazil, to better understand the population structure, epidemiology, and diversification of this pathogen, as well as to explore possible transmission routes. Methods: A total of 36 clinical isolates were morphologically identified, and clinical and demographic data were collected. Fungal DNA extraction was then performed, followed by species-specific PCR using markers targeting the calmodulin gene. The mating type idiomorph of the species was identified by PCR using primers targeting the MAT1-1 and MAT1-2 loci. Amplified Fragment Length Polymorphism (AFLP) was used to evaluate the genetic variability of Sporothrix spp. Results: The distribution of the disease identified that all cases occurred in João Pessoa and adjacent cities. From the 36 isolates, the majority (75%) being affected females, a prevalent occurrence of the lymphocutaneous form, and 98% zoonotic transmission were confirmed. Micro- and macromorphological structures were similar to each other, confirming Sporothrix spp. All isolates were confirmed as S. brasiliensis and the presence of a single sexual idiomorph, MAT1-2, was detected. The AFLP results indicate the possibility of the circulation of one or two genetic groups in João Pessoa and the metropolitan region. Conclusions: To our knowledge, this is the first time isolates in the Paraíba state are genetically characterised, all identified as Sporothrix brasiliensis. It is likely that this species in Paraiba originated from Rio de Janeiro, as all they possess the MAT1-2 idiomorph, indicating low intergenotypic variation.

An Enhanced Crowned Porcupine Optimization Algorithm Based on Multiple Improvement Strategies

The Crowned Porcupine Optimization (CPO) algorithm exhibits certain deficiencies in initialization efficiency, convergence speed, and adaptability. To address these issues, this paper proposes an enhanced Crowned Porcupine Optimization algorithm (ICPO) based on multiple improvement strategies. ICPO optimizes the initialization process by introducing Logistic chaotic mapping, thereby expanding the search space. It accelerates convergence through an elite retention strategy and enhances global search capability by integrating stochastic operations, mutation-like operations, and crossover-like operations to increase population diversity. Additionally, adaptive step tuning based on fitness values is employed to comprehensively improve the algorithm’s performance. To verify the effectiveness of ICPO, 23 standard functions were used for a comprehensive evaluation, and its practicality was further validated through optimization of actual engineering design problems. The experimental results demonstrate significant improvements in convergence speed, solution quality, and adaptability with ICPO.

Whole-genome resequencing to investigate the genetic diversity and mechanisms of plateau adaptation in Tibetan sheep

IntroductionTibetan sheep, economically important animals on the Qinghai–Tibet Plateau, have diversified into numerous local breeds with unique characteristics through prolonged environmental adaptation and selective breeding. However, most current research focuses on one or two breeds, and lacks a comprehensive representation of the genetic diversity across multiple Tibetan sheep breeds. This study aims to fill this gap by investigating the genetic structure, diversity and high-altitude adaptation of 6 Tibetan sheep breeds using whole-genome resequencing data.ResultsSix Tibetan sheep breeds were investigated in this study, and whole-genome resequencing data were used to investigate their genetic structure and population diversity. The results showed that the 6 Tibetan sheep breeds exhibited distinct separation in the phylogenetic tree; however, the levels of differentiation among the breeds were minimal, with extensive gene flow observed. Population structure analysis broadly categorized the 6 breeds into 3 distinct ecological types: plateau-type, valley-type and Euler-type. Analysis of unique single-nucleotide polymorphisms (SNPs) and selective sweeps between Argali and Tibetan sheep revealed that Tibetan sheep domestication was associated primarily with sensory and signal transduction, nutrient absorption and metabolism, and growth and reproductive characteristics. Finally, comprehensive analysis of selective sweep and transcriptome data suggested that Tibetan sheep breeds inhabiting different altitudes on the Qinghai–Tibet Plateau adapt by enhancing cardiopulmonary function, regulating body fluid balance through renal reabsorption, and modifying nutrient digestion and absorption pathways.ConclusionIn this study, we investigated the genetic diversity and population structure of 6 Tibetan sheep breeds in Qinghai Province, China. Additionally, we analyzed the domestication traits and investigated the unique adaptation mechanisms residing varying altitudes in the plateau region of Tibetan sheep. This study provides valuable insights into the evolutionary processes of Tibetan sheep in extreme environments. These findings will also contribute to the preservation of genetic diversity and offer a foundation for Tibetan sheep diversity preservation and plateau animal environmental adaptation mechanisms.

The Evolution and Role of Molecular Tools in Measuring Diversity and Genomic Selection in Livestock Populations (Traditional and Up-to-Date Insights): A Comprehensive Exploration

Distinctive molecular approaches and tools, particularly high-throughput SNP genotyping, have been applied to determine and discover SNPs, potential genes of interest, indicators of evolutionary selection, genetic abnormalities, molecular indicators, and loci associated with quantitative traits (QTLs) in various livestock species. These methods have also been used to obtain whole-genome sequencing (WGS) data, enabling the implementation of genomic selection. Genomic selection allows for selection decisions based on genomic-estimated breeding values (GEBV). The estimation of GEBV relies on the calculation of SNP effects using prediction equations derived from a subset of individuals in the reference population who possess both SNP genotypes and phenotypes for target traits. Compared to traditional methods, modern genomic selection methods offer advantages for sex-limited traits, low heritability traits, late-measured traits, and the potential to increase genetic gain by reducing generation intervals. The current availability of high-density genotyping and next-generation sequencing data allow for genome-wide scans for selection. This investigation provides an overview of the essential role of advanced molecular tools in studying genetic diversity and implementing genomic selection. It also highlights the significance of adaptive selection in light of new high-throughput genomic technologies and the establishment of selective comparisons between different genomes. Moreover, this investigation presents candidate genes and QTLs associated with various traits in different livestock species, such as body conformation, meat production and quality, carcass characteristics and composition, milk yield and composition, fertility, fiber production and characteristics, and disease resistance.

Genomic-Guided Conservation Actions to Restore the Most Endangered Conifer in the Mediterranean Basin.

Species with extremely small population sizes are critically endangered because of reduced genetic diversity, increased inbreeding and hybridisation threats. Genomic tools significantly advance conservation by revealing genetic insights into endangered species, notably in monitoring frameworks. Sicilian fir (Abies nebrodensis) is the most endangered conifer in Europe with only 30 adult trees in an 84-ha area. Using 20,824 SNPs from RAD-seq, employing genome assembly and a custom 120 SNP-array, we evaluated genetic diversity, mating patterns, and effective population size in adult trees, 118 natural seedlings, and 2064 nursery seedlings from past conservation actions. We assessed introgression from neighbouring non-native fir plantations (~6%) and established an intra-population assisted gene flow (AGF) program selecting the most genetically dissimilar individuals and investigating the outcome through simulations. Genomic analysis unveiled significant genetic diversity among adult Sicilian firs, comparable to non-endangered Mediterranean firs with larger populations. However, the genetic diversity of the forthcoming generation declined due to high self-fertilisation, leading to marked inbreeding (FIS = 0.38) and an alarmingly low effective population size (Ne = 6). Nursery seedling monitoring revealed similar selfing rates and introgression (~2%) from non-native firs. Although intra-population AGF could help to mitigate genetic loss, it may not alleviate the species vulnerability to imminent environmental challenges, perpetuating the risk of an extinction vortex. Hence, investigating the impact of Sicilian fir population decline and selfing on inbreeding depression, along with exploring the potential of hybrids for genetic load alleviation and future adaptation, is crucial for effective conservation strategies.

Improved Sparrow Search Algorithm Based on Multistrategy Collaborative Optimization Performance and Path Planning Applications

To address the problems of limited population diversity and a tendency to converge prematurely to local optima in the original sparrow search algorithm (SSA), an improved sparrow search algorithm (ISSA) based on multi-strategy collaborative optimization is proposed. ISSA employs three strategies to enhance performance: introducing one-dimensional composite chaotic mapping SPM to generate the initial sparrow population, thus enriching population diversity; introducing the dung beetle dancing search behavior strategy to strengthen the algorithm’s ability to jump out of local optima; integrating the adaptive t-variation improvement strategy to balance global exploration and local exploitation capabilities. Through experiments with 23 benchmark test functions and comparison with algorithms such as PSO, GWO, WOA, and SSA, the advantages of ISSA in convergence speed and optimization accuracy are verified. In the application of robot path planning, compared with SSA, ISSA exhibits shorter path lengths, fewer turnings, and higher planning efficiency in both single-target point and multi-target point path planning. Especially in multi-target point path planning, as the obstacle rate increases, ISSA can more effectively find the shortest path. Its traversal order is different from that of SSA, making the planned path smoother and with fewer intersections. The results show that ISSA has significant superiority in both algorithm performance and path planning applications.

Underwater image enhancement based on optimally weighted histogram framework and improved Fick’s law algorithm

The quality of underwater images is often affected by light scattering and attenuation, resulting in a loss of contrast and brightness. To address this issue, this paper proposes an underwater image enhancement method: improved Fick’s law algorithm-based optimally weighted histogram framework (IFLAHF). The method incorporates the bi-histogram equalization-based three plateau limits (BHE3PL) technique to enhance image contrast and details while maintaining brightness. However, its dependence on fixed parameters limits its adaptability. To overcome this limitation, the paper introduces Fick’s law algorithm (FLA) and then improves it to optimize the fixed parameters. FLA is improved by incorporating Tent chaotic mapping and reverse learning to increase population diversity, and Levy flight is introduced in the later stages to enhance exploitation. Additionally, a color correction technique is applied to correct color deviations in underwater images, leading to a more natural appearance. To verify the performance of the method, it is compared with different methods. As demonstrated by simulations, the proposed method outperforms existing algorithms in multiple underwater image enhancement metrics.

Construction of the porcine genome mobile element variations and investigation of its role in population diversity and gene expression

BackgroundMobile element variants (MEVs) have a significant and complex impact on genomic diversity and phenotypic traits. However, the quantity, distribution, and relationship with gene expression and complex traits of MEVs in the pig genome remain poorly understood.ResultsWe constructed the most comprehensive porcine MEV library based on high-depth whole genome sequencing (WGS) data from 747 pigs across 59 breeds worldwide. This database identified a total of 147,993 polymorphic MEVs, including 121,099 short interspersed nuclear elements (SINEs), 26,053 long interspersed nuclear elements (LINEs), 802 long terminal repeats (LTRs), and 39 other transposons, among which 54% are newly discovered. We found that MEVs are unevenly distributed across the genome and are strongly influenced by negative selection effects. Importantly, we identified 514, 530, and 584 candidate MEVs associated with population differentiation, domestication, and breed formation, respectively. For example, a significantly differentiated MEV is located in the ATRX intron between Asian and European pigs, whereas ATRX is also differentially expressed between Asian and European pigs in muscle tissue. In addition, we identified 4,169 expressed MEVs (eMEVs) significantly associated with gene expression and 6,914 splicing MEVs (sMEVs) associated with gene splicing based on RNA-seq data from 266 porcine liver tissues. These eMEVs and sMEVs explain 6.24% and 9.47%, respectively, of the observed cis-heritability and highlight the important role of MEVs in the regulation of gene expression. Finally, we provide a high-quality SNP–MEV reference haplotype panel to impute MEV genotypes from genome-wide SNPs. Notably, we identified a candidate MEV significantly associated with total teat number, demonstrating the functionality of this reference panel.ConclusionsThe present investigation demonstrated the importance of MEVs in pigs in terms of population diversity, gene expression and phenotypic traits, which may provide useful resources and theoretical support for pig genetics and breeding.

Dual-weight decay mechanism and Nelder-Mead simplex boosted RIME algorithm for optimal power flow

The increasing demand for electricity presents substantial challenges in power system planning, particularly optimizing the Optimal Power Flow (OPF) problem. The OPF problem entails establishing the best settings for control variables in a power system to reduce objectives such as generating cost and transmission losses while meeting operational restrictions. This research introduces an upgraded RIME optimization algorithm (WDNMRIME) to address these challenges. WDNMRIME integrates a dual-weight decay mechanism and the Nelder-Mead simplex (NMs), enhancing population diversity and mitigating the risk of local optima. Additionally, NMs expedites convergence by refining the population's optimal solution set. Experimental validation on the IEEE 30-bus test system demonstrates that WDNMRIME achieves a generation cost of $806.00298 per hour and reduces total power loss from 1.43 MW to 1.39 MW. These results surpass the performance of the original RIME algorithm, showcasing a 15% improvement in convergence speed. The algorithm effectively optimizes multiple concurrent Flexible Alternating Current Transmission Systems (FACTS) devices, even under the uncertain nature of wind energy resources modeled using the Weibull probability density function. These findings highlight WDNMRIME's significant contribution to improving OPF optimization in dynamic power systems.

ZTF SN Ia DR2: Overview

We present the first homogeneous release of several thousand spectroscopically classified type Ia supernovae (SNe Ia) with spectroscopic redshifts. This release, named “DR2,” contains 3628 nearby ($z<0.3$) SNe Ia discovered, followed, and classified by the Zwicky Transient Facility survey between March 2018 and December 2020. Of these, 3000 have good-to-excellent sampling and 2667 pass standard cosmology light curve quality cuts. This release is thus the largest SN Ia release to date, increasing by an order of magnitude the number of well-characterized low-redshift objects. With DR2, we also provide a volume-limited ($z<0.06$) sample of nearly a thousand SNe Ia. With such a large, homogeneous, and well-controlled dataset, we are studying key current questions on SN cosmology, such as the linearity SNe Ia standardization, the SN and host dependencies, the diversity of the SN Ia population, and the accuracy of current light curve modeling. These, and more, are studied in detail in a series of articles associated with this release. Alongside the SN Ia parameters, we publish our forced-photometry gri -band light curves, 5138 spectra, local and global host properties, observing logs, and a Python tool to facilitate the use and access of these data. The photometric accuracy of DR2 is not yet suited for cosmological parameter inference, which will follow as the “DR2.5” release. We nonetheless demonstrate that our Hubble diagram of several thousands of SNe Ia has a typical 0.15 mag scatter.