"Angel's Love"Chinese Goddess Nuwa Culture——Large-scale Activities for Public Interests

Initiated by Chinese Red Cross Foundation and sponsored by American .General Business Association, Chinese Nuwa （a goddess-creator of the Chinese nation） Culture Large-scale Activities for Public Interests undertaken by Beijing Absolute Challenge International Advertising Co., Ltd. has recently commenced in an all-round way. A grand ceremony will be held at Nuwa Plaza in Shexian County, Hebei Province on Septemper 24, 2007.

2024 Adult Compendium of Physical Activities:A third update of the energy costs of human activities

Background:The Compendium of Physical Activities was published in 1993 to improve the comparability of energy expenditure values assigned to self-reported physical activity(PA)across studies.The original version was updated in 2000,and again in 2011,and has been widely used to support PA research,practice,and public health guidelines.Methods:This 2024 update was tailored for adults 19-59 years of age by removing data from those≥60 years.Using a systematic review and supplementary searches,we identified new activities and their associated measured metabolic equivalent(MET)values(using indirect calorimetry)published since 2011.We replaced estimated METs with measured values when possible.Results:We screened 32,173 abstracts and 1507 full-text papers and extracted 2356 PA energy expenditure values from 701 papers.We added303 new PAs and adjusted 176 existing MET values and descriptions to reflect the addition of new data and removal of METs for older adults.We added a Major Heading(Video Games).The 2024 Adult Compendium includes 1114 PAs(912 with measured and 202 with estimated values)across 22 Major Headings.Conclusion:This comprehensive update and refinement led to the creation of The 2024 Adult Compendium,which has utility across research,public health,education,and healthcare domains,as well as in the development of consumer health technologies.The new website with the complete lists of PAs and supporting resources is available at https://pacompendium.com.

A brief history of the Compendium of Physical Activities

The Compendium of Physical Activities(Compendium)was developed to address consistent assignment of physical activity(PA)intensity values used in PA epidemiology research of the association between PA and health outcomes.1The known protective effects of PA on incident health outcomes traces to the mid-1900s,with over 50 studies examining coronary heart disease(CHD)as the outcome of interest.

Assessment of Wet Season Precipitation in the Central United States by the Regional Climate Simulation of the WRFG Member in NARCCAP and Its Relationship with Large-Scale Circulation Biases

Assessment of past-climate simulations of regional climate models(RCMs)is important for understanding the reliability of RCMs when used to project future regional climate.Here,we assess the performance and discuss possible causes of biases in a WRF-based RCM with a grid spacing of 50 km,named WRFG,from the North American Regional Climate Change Assessment Program(NARCCAP)in simulating wet season precipitation over the Central United States for a period when observational data are available.The RCM reproduces key features of the precipitation distribution characteristics during late spring to early summer,although it tends to underestimate the magnitude of precipitation.This dry bias is partially due to the model’s lack of skill in simulating nocturnal precipitation related to the lack of eastward propagating convective systems in the simulation.Inaccuracy in reproducing large-scale circulation and environmental conditions is another contributing factor.The too weak simulated pressure gradient between the Rocky Mountains and the Gulf of Mexico results in weaker southerly winds in between,leading to a reduction of warm moist air transport from the Gulf to the Central Great Plains.The simulated low-level horizontal convergence fields are less favorable for upward motion than in the NARR and hence,for the development of moist convection as well.Therefore,a careful examination of an RCM’s deficiencies and the identification of the source of errors are important when using the RCM to project precipitation changes in future climate scenarios.

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are zero.As a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec separately.Nevertheless,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables Mask.However,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is optimized.In data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between data.Inspired by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these SLMOPs.TELSO mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast convergence.Experi-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and engineering.However,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational resources.Furthermore,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables efficiently.This paper is dedicated to addressing the challenges posed by SLMOPs.To start,we introduce innovative objective functions customized to mine maximum and minimum candidate sets.This substantial enhancement dramatically improves the efficacy of frequent pattern mining.In this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific dimensions.Additionally,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero variables.This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value.We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs.The results demonstrate that our approach achieves competitive solutions across various challenges.

A semantic vector map-based approach for aircraft positioning in GNSS/GPS denied large-scale environment

Accurate positioning is one of the essential requirements for numerous applications of remote sensing data,especially in the event of a noisy or unreliable satellite signal.Toward this end,we present a novel framework for aircraft geo-localization in a large range that only requires a downward-facing monocular camera,an altimeter,a compass,and an open-source Vector Map(VMAP).The algorithm combines the matching and particle filter methods.Shape vector and correlation between two building contour vectors are defined,and a coarse-to-fine building vector matching(CFBVM)method is proposed in the matching stage,for which the original matching results are described by the Gaussian mixture model(GMM).Subsequently,an improved resampling strategy is designed to reduce computing expenses with a huge number of initial particles,and a credibility indicator is designed to avoid location mistakes in the particle filter stage.An experimental evaluation of the approach based on flight data is provided.On a flight at a height of 0.2 km over a flight distance of 2 km,the aircraft is geo-localized in a reference map of 11,025 km~2using 0.09 km~2aerial images without any prior information.The absolute localization error is less than 10 m.

Online identification and extraction method of regional large-scale adjustable load-aggregation characteristics

This article introduces the concept of load aggregation,which involves a comprehensive analysis of loads to acquire their external characteristics for the purpose of modeling and analyzing power systems.The online identification method is a computer-involved approach for data collection,processing,and system identification,commonly used for adaptive control and prediction.This paper proposes a method for dynamically aggregating large-scale adjustable loads to support high proportions of new energy integration,aiming to study the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction methods.The experiment selected 300 central air conditioners as the research subject and analyzed their regulation characteristics,economic efficiency,and comfort.The experimental results show that as the adjustment time of the air conditioner increases from 5 minutes to 35 minutes,the stable adjustment quantity during the adjustment period decreases from 28.46 to 3.57,indicating that air conditioning loads can be controlled over a long period and have better adjustment effects in the short term.Overall,the experimental results of this paper demonstrate that analyzing the aggregation characteristics of regional large-scale adjustable loads using online identification techniques and feature extraction algorithms is effective.

Hydrolytic and Antimicrobial Activities of Bacteria Isolated from Fermented Peppers Sold in Markets at Brazzaville, Republic of the Congo

Microorganisms are omnipresent in all environments and play mainly the role of transformers, thanks to the multiple enzymes they are able to produce. In order to valorize fermented foods in the Republic of the Congo, this work aimed to characterize and study some properties of microorganisms isolated from samples of peppers sold in three markets of Brazzaville. A numeration of the total aerobic mesophilic flora (TAMF) was made in a solid medium, allowing the evaluation of each sample’s microbial concentration. The microbial mass varied from 2.8 × 105 CFU/g for the Ouénzé sample to 1.8 × 104 CFU/g for the Total sample and 2 × 104 CFU/g for the Moungali market sample. The evaluation of the enzymatic properties of the Bacillus isolates showed that 68.42% were capable of producing cellulases and 78.94% were capable of producing amylases and proteases. Antimicrobial activities revealed that 63.15% of the isolates were able to secrete inhibitory substances against E. coli and Staphylococcus aureus. Molecular analysis by PCR amplification, sequencing of the 16S rRNA gene and BLAST bioinformatics analysis provides newly identified bacteria strains with new accession numbers in GenBank: Bacillus thuringiensis MBCBR322 (OP474008), Bacillus megaterium MBCBJ1822 (OP476493), Bacillus thuringiensis MBCBR222 (OP476494), Priestia megaterium MBCBJ2022 (OP476495) and Lactobacillus paraplantarum MBCBR1522 (OP476496). Multiple sequences alignment of identified sequences with their homologs of GenBank has shown high similarities. The phylogenetic inference assay has provided the two groups of strains observed in this study, and the two groups are very coherent with the phylogeny of the reference.

Large-Scale Multi-Objective Optimization Algorithm Based on Weighted Overlapping Grouping of Decision Variables

The large-scale multi-objective optimization algorithm(LSMOA),based on the grouping of decision variables,is an advanced method for handling high-dimensional decision variables.However,in practical problems,the interaction among decision variables is intricate,leading to large group sizes and suboptimal optimization effects;hence a large-scale multi-objective optimization algorithm based on weighted overlapping grouping of decision variables(MOEAWOD)is proposed in this paper.Initially,the decision variables are perturbed and categorized into convergence and diversity variables;subsequently,the convergence variables are subdivided into groups based on the interactions among different decision variables.If the size of a group surpasses the set threshold,that group undergoes a process of weighting and overlapping grouping.Specifically,the interaction strength is evaluated based on the interaction frequency and number of objectives among various decision variables.The decision variable with the highest interaction in the group is identified and disregarded,and the remaining variables are then reclassified into subgroups.Finally,the decision variable with the strongest interaction is added to each subgroup.MOEAWOD minimizes the interactivity between different groups and maximizes the interactivity of decision variables within groups,which contributed to the optimized direction of convergence and diversity exploration with different groups.MOEAWOD was subjected to testing on 18 benchmark large-scale optimization problems,and the experimental results demonstrate the effectiveness of our methods.Compared with the other algorithms,our method is still at an advantage.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.

Semisynthetic Derivatives of Sissotrin Isolated from Trifolium baccarinii Chiov. (Fabaceae) and Evaluation of Their Antibacterial Activities

Starting from sissotrin (1), a natural isoflavonoid isolated from Trifolium baccarinii (Fabaceae), one new semisynthetic derivative, 6-nitrobiochanin A (1b) and two known derivatives, 8-nitrobiochanin A (1a) and 2",3",4",6"-tetraacetylsissotrin (1c) have been obtained after performing nitration and acetylation reactions. Their structures were assigned after interpretation of their spectrometric (HR-ESI-MS) and spectroscopic (NMR 1D and 2D) data and by comparison with those reported in the literature. The substrate as well as the semisynthetic derivatives were evaluated for their antibacterial activities against six strains. The results reveal that they are inactive or weakly active on the strains tested with the exception of 8-nitrobiochanin A (1a) which showed moderate activity (MIC = 62.5 μg∙mL−1) on Staphylococcus aureus ATCC 43300.

Promoting public health through the 2024 Compendium of Physical Activities:Strategies for adults,older adults,and wheelchair users

Physical activity(PA)is fundamentally linked to public health,^(1)providing benefits including chronic disease prevention and treatment,^(2)mental health,^(3)musculoskeletal health,^(4)and healthy aging,^(5)along with socioeconomic advantages.^(6)These benefits highlight the importance of promoting PA for all populations.The recent publication of the Compendium of Physical Activities(Compendium)serves as a valuable resource,^(7)offering an updated and expanded guide for adults(ages 19-59)with tailored energy cost values for diverse populations.

The influence of Lactobacillus plantarum fermentation in selenium-enriched Brassica napus L.:changes in the nutritional constituents,bioactivities and bioaccessibility

Selenium(Se)-enriched Brassica napus L.is a valuable organic Se supplement.In this study,the fermentation broth enriched with organic Se(FFS)was prepared using Lactobacillus plantarum to ferment the substrate of Se-enriched Brassica napus L.Significant increases were observed after fermentation in total sugars,reducing sugars,soluble proteins,total phenolic content(TPC),and total flavonoid content(TFC).The organic Se was retained at a concentration of 54.75 mg/g in the freeze-dried sample.Principal component analysis and cluster analysis showed good separation between the FFS and unfermented(FS)groups.Fragrant 2-ethyloxetane had the highest content among all volatiles,while sinapine had the highest content among all phenolic compounds.The fermentation process showed remarkable improvement in the abundance and concentration of volatile compounds and phenolic contents,making FFS exhibit strong antioxidant activity and inhibitory capacity againstα-glucosidase activity.The bioaccessibility of phenolic compounds was significantly greater in FFS compared to FS.ADMET analysis revealed that the majority of phenolic compounds contained in FFS did not exhibit mutagenicity toxicity,hepatotoxicity,skin sensitization,or blood-brain barrier penetration,indicating a favorable level of biosafety.Overall,our study provides a new insight into the further utilization of Se-enriched Brassica napus L.in foods.

Effect of simulated gastrointestinal digestion on antioxidant,and anti-inflammatory activities of bioactive peptides generated in sausages fermented with Staphylococcus simulans QB7

Dry-fermented sausages are a good source of bioactive peptides,whose stability against gastrointestinal(GI)digestion determines their bioaccessibility.This study focused on evaluating the effect of peptide extracts from sausages fermented with Staphylococcus simulans QB7 during in vitro simulated GI digestion,including peptide profiles and antioxidant and anti-inflammatory activities.Peptides present in sausages were degraded during digestion,with molecular weight reduced from>12 kDa to<1.5 kDa.Besides,the content of amino acids increased from 381.15 to 527.07 mg/g,especially tyrosine being found only after GI digestion.The anti-inflammatory activities were increased after GI digestion,however,the changes in antioxidant activities were the opposite.A total number of 255,252 and 386 peptide sequences were identified in undigested,peptic-digested and GI-digested samples,respectively.PeptideRanker,BIOPEP-UWM and admetSAR were used to further predict the functional properties and intestinal absorption of the identified peptide sequences from GI digestion.Finally,18 peptides were discovered to possess either antioxidant or anti-inflammatory capacities.

Structural characterization and anti-inflammatory activities of novel polysaccharides obtained from Pleurotus eryngii

Natural polysaccharides named PEP-0.1-1,PEP-0-1 and PEP-0-2 from edible mushroom species Pleurotus eryngii were obtained in the present study.Results showed that molecular weights of these polysaccharides were 3235,2041 and 23933 Da,respectively.Further,structural characterization revealed that PEP-0.1-1 had a→4-α-D-Glcp-1→backbone and contained→4)-α-D-Glcp and→4)-β-D-Glcp reducing end groups.PEP-0-1 backbone contained→4-α-D-Glcp-1→and→6-α-3-O-Me-D-Galp-1→,and the side chains containedα-D-Glcp,β-D-Manp-1→andα-D-Glcp-3→.However,PEP-0-2 backbone consisted of→4-α-DGlcp-1→and→6-α-3-O-Me-D-Galp-(1→6)-α-D-Galp-1→while the side chains containedα-D-Glcp andβ-D-Manp-1→.Biological activity analysis was then carried out and found that all these polysaccharides could significantly suppress the relative mRNA expression of toll-like receptor 4,nitric oxide(NO),tumor necrosis factor-α,interleukin(IL)-1βand IL-6 in lipopolysaccharide(LPS)-induced inflammation of RAW264.7 cells,as well as the over secretion of the above cell cytokines.Moreover,Western blotting analysis revealed that all these purified fractions displayed significant inhibition effects on the expression of c-Jun N-terminal kinases protein induced by LPS in mitogen activated protein kinase pathway,along with the relieving on the inhibition effect of LPS on IκB-αprotein expression.In summary,the information generated by the present study could provide a theoretical basis for the exploration of novel healthy food materials from edible mushroom with antiinflammation activities.

Factorized Smith Method for A Class of High-Ranked Large-ScaleТ-Stein Equations

We introduce a factorized Smith method(FSM)for solving large-scale highranked J-Stein equations within the banded-plus-low-rank structure framework.To effectively reduce both computational complexity and storage requirements,we develop techniques including deflation and shift,partial truncation and compression,as well as redesign the residual computation and termination condition.Numerical examples demonstrate that the FSM outperforms the Smith method implemented with a hierarchical HODLR structured toolkit in terms of CPU time.

Precipitation and anthropogenic activities regulate the changes of NDVI in Zhegucuo Valley on the southern Tibetan Plateau

Whether climate change or anthropogenic activities play a more pivotal role in regulating vegetation growth on the Tibetan Plateau is still controversial.A better understanding on grassland changes at a fine scale may provide important guidance for local government policy and grassland management.Using two of the most reliable satellite NDVI products(MODIS NDVI and SPOT NDVI),we evaluated the dynamic of grasslands in the Zhegucuo valley on the southern Tibetan Plateau from 2000 to 2020,and analyzed its driving factors and relative influences of climate change and anthropogenic activities.Here,the key indicators of climate change were assumed to be precipitation and temperature.The main results were:(1)the grassland NDVI in Zhegucuo valley did not reflect a significant temporal change during the last 21 years.The variation of precipitation during the early growing season(GSP)resembled that of NDVI,and the GSP was positively correlated with NDVI.At the pixel level,the partial correlation analysis showed that 37.79%of the pixels depicted a positive relationship between GSP and NDVI,while 11.32%of the pixels showed a negative relationship between temperature during the early growing season(GST)and NDVI.(2)In view of the spatial distribution,the areas mainly controlled by GSP were generally distributed in the southern part,while those affected by GST stood in the eastern part,mainly around the Zhegucuo lake where most population in Cuomei County settled down.(3)Decreasing NDVI trends were mainly occurred in alpine steppe at lower elevations rather than alpine meadow at higher elevations.(4)The residual trend(RESTREND)analysis further indicated that the anthropogenic activities played a more pivotal role in regulating the annual changes of NDVI rather than climate factors in this area.Future studies should pay more attention on climate extremes rather than the simple temporal trends.Also,the influence of human activities on alpine grassland needs to be accessed and fully considered in future sustainable management.

Large-scale spatial data visualization method based on augmented reality

Background A task assigned to space exploration satellites involves detecting the physical environment within a certain space.However,space detection data are complex and abstract.These data are not conducive for researchers'visual perceptions of the evolution and interaction of events in the space environment.Methods A time-series dynamic data sampling method for large-scale space was proposed for sample detection data in space and time,and the corresponding relationships between data location features and other attribute features were established.A tone-mapping method based on statistical histogram equalization was proposed and applied to the final attribute feature data.The visualization process is optimized for rendering by merging materials,reducing the number of patches,and performing other operations.Results The results of sampling,feature extraction,and uniform visualization of the detection data of complex types,long duration spans,and uneven spatial distributions were obtained.The real-time visualization of large-scale spatial structures using augmented reality devices,particularly low-performance devices,was also investigated.Conclusions The proposed visualization system can reconstruct the three-dimensional structure of a large-scale space,express the structure and changes in the spatial environment using augmented reality,and assist in intuitively discovering spatial environmental events and evolutionary rules.

Responses of soil stoichiometry and soil enzyme activities in the different distance around opencast coal mine of the Hulun Buir Grassland of China

The objectives of this study were to explore the changes in soil stoichiometry and enzyme activities at different distances from an opencast coal mine in the Hulun Buir Grassland of China. Four transects were established on north and east sides of the opencast coal mining area, and samples were collected at 50 m, 550 m, and 1550 m from the pit on each transect. Control samples were collected from a grassland station 8 km from the opencast coal mining area that was not disturbed by mining. Four replicate soil samples were collected at each point on the four transects. Soil physicochemical properties and enzyme activities were determined, and correlations between soil properties and stoichiometric ratios and enzyme activities were explored using redundancy analysis. The increase in distance from mining did not significantly affect soil properties, although soil urease activity was significantly lower than that of the control area. Soil properties 1550 m from the mine pit were similar to those at the grassland control. In addition, soil total nitrogen had the greatest effect on soil stoichiometry, and soil total potassium had the greatest effect on soil enzyme activities. Coal dust from opencast mining might be the main factor affecting soil stoichiometry and enzyme activities. The results of this study provide direction for the next step in studying the influence of mining areas on soil properties and processes.