A dynamic neighborhood learning-based gravitational search algorithm

Balancing exploration and exploitation according to evolutionary states is crucial to meta-heuristic search (M-HS) algorithms. Owing to its simplicity in theory and effectiveness in global optimization, gravitational search algorithm (GSA) has attracted increasing attention in recent years. However, the tradeoff between exploration and exploitation in GSA is achieved mainly by adjusting the size of an archive, named Kbest, which stores those superior agents after fitness sorting in each iteration. Since the global property of Kbest remains unchanged in the whole evolutionary process, GSA emphasizes exploitation over exploration and suffers from rapid loss of diversity and premature convergence. To address these problems, in this paper, we propose a dynamic neighborhood learning (DNL) strategy to replace the Kbest model and thereby present a DNL-based GSA (DNLGSA). The method incorporates the local and global neighborhood topologies for enhancing the exploration and obtaining adaptive balance between exploration and exploitation. The local neighborhoods are dynamically formed based on evolutionary states. To delineate the evolutionary states, two convergence criteria named limit value and population diversity, are introduced. Moreover, a mutation operator is designed for escaping from the local optima on the basis of evolutionary states. The proposed algorithm was evaluated on 27 benchmark problems with different characteristic and various difficulties. The results reveal that DNLGSA exhibits competitive performances when compared with a variety of state-of-the-art M-HS algorithms. Moreover, the incorporation of local neighborhood topology reduces the numbers of calculations of gravitational force and thus alleviates the high computational cost of GSA

Feasibility analysis of storing solar energy in heterogeneous deep aquifer by hot water circulation: Insights from coupled hydro-thermo modeling

Storing solar energy in the subsurface as heat is a promising way for energy storage and conversion, which has a great potential to address the temporal and spatial mismatch between energy demand and supply. Thermal energy storage in deep aquifers can convert intermittent solar energy into stable high temperature geothermal energy. In this study, a new solar energy storage and conversion system is proposed where solar energy is firstly converted into heat using parabolic troughs and then stored in deep aquifers by high temperature hot water circulation. The geostatistical modelling and hydro-thermo coupling simulations are adopted to investigate the feasibility and efficiency of solar energy storage in deep aquifers. Specifically, how rock permeability heterogeneity (in terms of autocorrelation length and global permeability heterogeneity) impacts the temporal and spatial evolution of temperature distribution and storage efficiency is examined. The simulation results indicate that increased horizontal autocorrelation length and global heterogeneity may accelerate thermal breakthrough, deteriorating storage efficiency. High permeability heterogeneity may also lead to high injection pressure. Deep aquifers with small horizontal autocorrelation lengths and low global heterogeneity tend to have higher storage efficiency. These findings may improve our understanding of solar energy storage mechanism in deep aquifers and guide field applications.Document Type: Original articleCited as: Wang, Y., Zhong, K., Gao, Y., Sun, Z., Dong, R., Wang, X. Feasibility analysis of storing solar energy in heterogeneous deep aquifer by hot water circulation: Insights from coupled hydro-thermo modeling. Advances in Geo-Energy Research, 2023, 10(3): 159-173. https://doi.org/10.46690/ager.2023.12.0

Hyperspectral band selection using crossover based gravitational search algorithm

Band selection is an important data dimensionality reduction tool in hyperspectral images (HSIs). To identify the most informative subset band from the hundreds of highly corrected bands in HSIs, a novel hyperspectral band selection method using a crossover based gravitational search algorithm (CGSA) is presented in this paper. In this method, the discriminative capability of each band subset is evaluated by a combined optimization criterion, which is constructed based on the overall classification accuracy and the size of the band subset. As the evolution of the criterion, the subset is updated using the V-shaped transfer function based CGSA. Ultimately, the band subset with the best fitness value is selected. Experiments on two public hyperspectral datasets, i.e. the Indian Pines dataset and the Pavia University dataset, have been conducted to test the performance of the proposed method. Comparing experimental results against the basic GSA and the PSOGSA (hybrid PSO and GSA) revealed that all of the three GSA variants can considerably reduce the band dimensionality of HSIs without damaging their classification accuracy. Moreover, the CGSA shows superiority on both the effectiveness and efficiency compared to the other two GSA variants

The Role of PTHLH in Ovarian Follicle Selection, Its Transcriptional Regulation and Genetic Effects on Egg Laying Traits in Hens

In hens, follicle selection is an important process affecting egg laying traits. This study investigated the role of parathyroid hormone-like hormone (PTHLH) in chicken follicle selection, its transcriptional regulation and genetic effects on egg laying traits. PTHLH and its receptor PTH1R were mainly expressed in follicles of 6–8 mm in diameter, exhibits differential expression pattern in the theca and granulosa cells of pre- and hierarchal follicles. PTHLH stimulates the proliferation of follicular granulosa and theca cells, the expression of StAR and CYP11A1 mRNA and the production of progesterone (P4) in pre-hierarchal follicles. Treatment with FSH increased PTHLH mRNA expression in pre-hierarchal follicular theca cells and hierarchal follicular granulosa cells. Two critical regions regulating chicken PTHLH transcription were revealed, each of which harbored a SNP: C>T (chr1: 72530014) for AP-1 and a SNP: A>G (chr1: 72531676). Hens with diplotype AC/GT were younger at first laying and laid more eggs at 32 weeks. The haplotype (G-1827T-165) with double mutations had the greatest promoter activity of chicken PTHLH transcription. Collectively, PTHLH plays an important role in chicken follicle selection by stimulating cell proliferation and steroidogenesis. Polymorphisms in chicken PTHLH promoter region are associated with egg laying traits by affecting the binding of transcription factor AP-1

Knowledge and attitudes of healthcare workers in Chinese intensive care units regarding 2009 H1N1 influenza pandemic

<p>Abstract</p> <p>Background</p> <p>To describe the knowledge and attitudes of critical care clinicians during the 2009 H1N1 influenza pandemic.</p> <p>Methods</p> <p>A survey conducted in 21 intensive care units in 17 provinces in China.</p> <p>Results</p> <p>Out of 733 questionnaires distributed, 695 were completed. Three hundred and fifty-six respondents (51.2%) reported their experience of caring for H1N1 patients. Despite the fact that 88.5% of all respondents ultimately finished an H1N1 training program, only 41.9% admitted that they had the knowledge of 2009 H1N1 influenza. A total of 572 respondents (82.3%) expressed willingness to care for H1N1 patients. Independent variables associated with increasing likelihood to care for patients in the logistic regression analysis were physicians or nurses rather than other professionals (odds ratio 4.056 and 3.235, p = 0.002 and 0.007, respectively), knowledge training prior to patient care (odds ratio 1.531, p = 0.044), and the confidence to know how to protect themselves and their patients (odds ratio 2.109, p = 0.001).</p> <p>Conclusion</p> <p>Critical care clinicians reported poor knowledge of H1N1 influenza, even though most finished a relevant knowledge training program. Implementation of appropriate education program might improve compliance to infection control measures, and willingness to work in a pandemic.</p

Research progress on and molecular mechanism of vacuum sealing drainage in the treatment of diabetic foot ulcers

Diabetic foot ulcers (DFUs) are common chronic wounds and a common complication of diabetes. The foot is the main site of diabetic ulcers, which involve small and medium-sized arteries, peripheral nerves, and microcirculation, among others. DFUs are prone to coinfections and affect many diabetic patients. In recent years, interdisciplinary research combining medicine and material science has been increasing and has achieved significant clinical therapeutic effects, and the application of vacuum sealing drainage (VSD) in the treatment of DFUs is a typical representative of this progress, but the mechanism of action remains unclear. In this review, we integrated bioinformatics and literature and found that ferroptosis is an important signaling pathway through which VSD promotes the healing of DFUs and that System Xc-GSH-GPX4 and NAD(P)H-CoQ10-FSP1 are important axes in this signaling pathway, and we speculate that VSD is most likely to inhibit ferroptosis to promote DFU healing through the above axes. In addition, we found that some classical pathways, such as the TNF, NF-κB, and Wnt/β-catenin pathways, are also involved in the VSD-mediated promotion of DFU healing. We also compiled and reviewed the progress from clinical studies on VSD, and this information provides a reference for the study of VSD in the treatment of DFUs

Prevalence of atrial fibrillation in different socioeconomic regions of China and its association with stroke: Results from a national stroke screening survey

Background: Atrial fibrillation (AF) is the most common sustained arrhythmia in clinical practice. This study aimed to estimate the prevalence of AF in different socioeconomic regions of China and identify its association with stroke, through a national survey. Methods: The study included 726,451 adults aged ≥40 years who were participants of the China National Stroke Screening and Prevention Project, a nationally representative cross-sectional study. Stepwise logistic regression analyses were conducted to investigate the association between AF and stroke. Results: The overall standardized prevalence rate of AF was 2.31%. The prevalence of AF was highest in high-income regions (2.54%), followed by middle-income regions (2.33%), and lowest in low-income regions (1.98%). Women had a higher prevalence of AF than men in all regions (low-income regions, 2.30% vs 1.65%; middle-income regions, 2.78% vs 1.89%; and high-income regions, 2.96% vs 2.12%). Compared with urban residents, the prevalence of AF among rural residents was higher in low- (2.03% vs 1.91%) and middle-income regions (2.69% vs 1.90%), but lower in high-income regions (2.44% vs 2.58%). Participants with AF were more likely to have a stroke than those without AF (9.48% vs 2.26%). After adjusting for age, sex, location, overweight or obese, smoking, drinking, physical inactivity, hypertension, diabetes, dyslipidemia, and a family history of stroke, results showed that AF was significantly associated with stroke. Conclusions: The prevalence of AF has increased in recent years, and it was positively correlated with socioeconomic status, sex (women), location (rural areas), and stroke

A comprehensive environmental impact assessment method for shale gas development

The great success of US commercial shale gas exploitation stimulates the shale gas development in China, subsequently, the corresponding supporting policies were issued in the 12th Five-Year Plan. But from the experience in the US shale gas development, we know that the resulted environmental threats are always an unavoidable issue, but no uniform and standard evaluation system has yet been set up in China. The comprehensive environment refers to the combination of natural ecological environment and external macro-environment. In view of this, we conducted a series of studies on how to set up a comprehensive environmental impact assessment system as well as the related evaluation methodology and models. First, we made an in-depth investigation into shale gas development procedures and any possible environmental impacts, and then compared, screened and modified environmental impact assessment methods for shale gas development. Also, we established an evaluating system and assessment models according to different status of the above two types of environment: the correlation matrix method was employed to assess the impacts on natural ecological environment and the optimization distance method was modified to evaluate the impacts on external macro-environment. Finally, we substitute the two subindexes into the comprehensive environmental impact assessment model and achieved the final numerical result of environmental impact assessment. This model can be used to evaluate if a shale gas project has any impact on environment, compare the impacts before and after a shale gas development project, or the impacts of different projects