SUNDER:Self-organized grouping and entrapping method for swarms in multitarget environments

For swarm robots moving in a harsh or uncharted outdoor environment without GPS guidance and global communication,algorithms that rely on global-based information are infeasible.Typically,traditional gene regulatory networks(GRNs)that achieve superior performance in forming trapping pattern towards targets require accurate global positional information to guide swarm robots.This article presents a gene regulatory network with Self-organized grouping and entrapping method for swarms(SUNDER-GRN)to achieve adequate trapping performance with a large-scale swarm in a confined multitarget environment with access to only local information.A hierarchical self-organized grouping method(HSG)is proposed to structure subswarms in a distributed way.In addition,a modified distributed controller,with a relative coordinate system that is established to relieve the need for global information,is leveraged to facilitate subswarms entrapment toward different targets,thus improving the global multi-target entrapping performance.The results demonstrate the superiority of SUNDERGRN in the performance of structuring subswarms and entrapping 10 targets with 200 robots in an environment confined by obstacles and with only local information accessible.

Thermal adaptation in overheated residential buildings in severe cold area in China

The winter in the severe cold area of China is long and cold. The mean outdoor temperature is about-10. 0 ℃ during the winter in Harbin,while the indoor air temperature is often above24 ℃. How does the indoor environment influence human thermal comfort and adaptation in such an overheated environment?A combined approach of spot-reading measurements and occupant interview s w as adopted in nine residential buildings of five communities during the heating period in 2013-2014. Tw enty residents w ere chosen as respondents. Totally 308 valid questionnaires w ere collected. The heating periods w ere separated into three phases based on the outdoor temperature.The results show that the mean indoor air temperatures in theearly-,mid-and late-heating periods w ere 23. 6 ℃,24. 3 ℃and 25. 0 ℃,respectively,w hich w ere larger than or close to the upper limit recommended by thermal comfort standards, and slightly higher than the related thermal neutral temperatures. With the heating process,the mean clothing insulation of residents decreased. Opening w indow s and reducing clothing w ere mainly taken by the residents to adapt to the overheated environment.The thermal neutral temperature has an upw ard tendency w ith the increasing indoor air temperature. On the other hand,overheating in residential buildings w ould make residents open w indow s,w hich may cause thermal discomfort and energy w aste. Therefore,the low er limit of the comfort indoor air temperature range should be suggested as the heating temperature,w hich could fully arouse residents' adaptation and achieve sustainable building designs.

Mining Syndrome Differentiating Principles from Traditional Chinese Medicine Clinical Data

Syndrome differentiation-based treatment is one of the key characteristics of Traditional Chinese Medicine(TCM).The process of syndrome differentiation is difficult and challenging due to its complexity,diversity and vagueness.Analyzing syndrome principles from historical records of TCM using data mining(DM)technology has been of high interest in recent years.Nevertheless,in most relevant studies,existing DM algorithms have been simply developed for TCM mining,while the combination of TCM theories or its characteristics with DM algorithms has rarely been reported.This paper presents a novel Symptom-Syndrome Topic Model(SSTM),which is a supervised probabilistic topic model with three-tier Bayesian structure.In the SSTM,syndromes are considered as observed topic labels to distinguish certain symptoms from possible symptoms according to their different positions.The generation of our model is in full compliance with the syndrome differentiation theory of TCM.Experimental results show that the SSTM is more effective than other models for syndrome differentiating.

Evaluation of Ambient Air Quality and Its Changing Trend in Jinan City during 2013-2020

Based on the automatic monitoring data of ambient air in Jinan City from 2013 to 2020,the changing trend and characteristics of air quality in Jinan City during 2013-2020 were analyzed by using the fuzzy comprehensive evaluation,air quality index(AQI)and ambient air quality comprehensive index methods.The three methods are different in principle,purpose of use,and characterization methods,but the conclusions are consistent.The ambient air quality in Jinan City was improved significantly from 2013 to 2020.The prime pollutants were mainly PM_(2.5)and PM_(10),but the impact on air quality declined,and the impact of O_(3)on air quality increased.The complex pollution characteristics were obvious.Air pollution was the most severe in winter and lighter in summer.

Physicochemical properties and antioxidant activities of polysaccharides extracted from Panax ginseng C.A.Meyer with graded percipitation method

Ginseng polysaccharides were extracted by water decoction from Panax ginseng C.A.Meyer(Cultivated Ginseng),named CGPS.Four polysaccharide fractions,CGPS-20,CGPS-40,CGPS-60 and CGPS-80,were precipitated at final ethanol concentrations of 20%,40%,60%and 80%,respectively.Physicochemical properties,molecular weight,monosaccharide composition and antioxidant capacity of polysaccharide fractions were all investigated.The results indicated that changing the concentration of ethanol could precipitate polysaccharides into fractions with different molecular weights,functional group composition and physicochemical properties,eventually leading to differences in antioxidant activity,which would help to find a simple,efficient,and reliable method for rapid extraction and purification of antioxidant polysaccharides from Panax ginseng C.A.Meyer.Among the four polysaccharide fractions,CGPS-80 had lower molecular weight,higher contents of uronic acid and total phenolic,and stronger scavenging ability on DPPH∙and ABTS∙+radicals.

Analysis on Sustainable Development of Tire Industry Cluster based on Life Cycle Theory

The research on the tire industry cluster based on life cycle theory can be carried out by a four stage periods,namely initial period,growth period,maturity period,and recession period.This paper analyzes on the possible risks taken in each life cycle period as well as proposes corresponding suggestions to strengthen the research by looking into the conditions and factors of the continuous sustainable development process in a tire industry.

A multi-layer genome mining and phylogenomic analysis to construct efficient and autonomous efflux system for medium chain fatty acids

Medium-chain fatty acids(MCFAs)are important components for food,pharmaceutical and fuel industries.Nevertheless,engineering microorganisms to produce MCFAs often induces toxicity and stresses towards host strains,which could be alleviated via accelerating the export of MCFAs from cells.However,current secretory systems are inefficient and require inducible promoters.Here,a multi-layer genome mining and phylogenomic analysis was developed to identify efficient efflux transporters.Firstly,based on the genomic mining of 397 strains throughout various representative species,the evolutionary history of efflux transporters was recapitulated,and further experimental analysis revealed that acrE from Citrobacter exhibited the best performance.Secondly,according to the further mining of 797 Citrobacter genomes and 1084 Escherichia genomes,a detailed phylogenomic analysis of efflux transporter-centric genomic vicinities was performed.This led to the identification of efficient efflux pump combination acrE and acrF.These efflux pumps were then combined with the quorum-sensing circuit from Enterococcus faecalis to regulate MCFA efflux in an autonomous manner,which achieved a 4.9-fold boost in MCFA production and firstly demonstrated the efficient and autonomous efflux pump specially for MCFAs.The integrative omics technologies described here are enabling the utilization of the increasingly large database and the effective mining of target gene diversities.

Study on the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,with prediction of its tendency

The prediction system EpiSIX was used to study the COVID-19 epidemic in China's Mainland between November 2022 and January 2023,based on reported data from December 9,2022,to January 30,2023,released by The Chinese Center for Disease Control and Prevention on February 1,2023.Three kinds of reported data were used for model fitting:the daily numbers of positive nucleic acid tests and deaths,and the daily number of hospital beds taken by COVID-19 patients.It was estimated that the overall infection rate was 87.54%and the overall case fatality rate was 0.078%–0.116%(median 0.100%).Assuming that a new COVID-19 epidemic outbreak would start in March or April of 2023,induced by a slightly more infectious mutant strain,we predicted a possible large rebound between September and October 2023,with a peak demand of between 800,000 and 900,000 inpatient beds.If no such new outbreak was induced by other variants,then the current COVID-19 epidemic course in China's Mainland would remain under control until the end of 2023.However,it is suggested that the necessary medical resources be prepared to manage possible COVID-19 epidemic emergencies in the near future,especially for the period between September and October 2023.

COVID-19 transmission driven by age-group mathematical model in Shijiazhuang City of China

Background:A COVID-19 outbreak in the rural areas of Shijiazhuang City was attributed to the complex interactions among vaccination,host,and non-pharmaceutical interventions(NPIs).Herein,we investigated the epidemiological characteristics of all reported symptomatic cases by picking Shijiazhuang City,Hebei Province in Northern China as research objective.In addition,we established an age-group mathematical model to perform the optimal fitting and to investigate the dynamical profiles under three scenarios.Methods:All reported symptomatic cases of Shijiazhuang epidemic(January 2-February 3,2021)were investigated in our study.The cases were classified by gender,age group and location,the distributions were analyzed by epidemiological characteristics.Furthermore,the reported data from Health Commission of Hebei Province was also analyzed by using an age-group mathematical model by two phases and three scenarios.Results:Shijiazhuang epidemic caused by SARS-CoV-2 wild strain was recorded with the peak 84 cases out of 868 reported symptomatic cases on January 11,2021,which was implemented with strong NPIs by local government and referred as baseline situation in this study.The research results showed that R0 under baseline situation ranged from 4.47 to 7.72,and Rt of Gaocheng Distinct took 3.72 with 95%confidence interval from 3.23 to 4.35 on January 9,the declining tendencies of Rt under baseline situation were kept till February 3,the value of Rt reached below 1 on January 19 and remained low value up to February 3 for Gaocheng District and Shijiazhuang City during Shijiazhuang epidemic.This indicated Shijiazhuang epidemic was under control on January 19.However,if the strong NPIs were kept,but remote isolation operated on January 11 was not implemented as of February 9,then the scale of Shijiazhuang epidemic reached 9,482 cases from age group who were 60 years old and over out of 31,017 symptomatic cases.The investigation also revealed that Shijiazhuang epidemic reached 132,648 symptomatic cases for age group who were 60 years old and over(short for G2)under risk-based strategies(Scenario A),58,048 symptomatic cases for G2 under late quarantine strategies(Scenario B)and 207,124 symptomatic cases for G2 under late quarantine double risk strategies(Scenario C),and that the corresponding transmission tendencies of Rt for three scenarios were consistently controlled on Jan 29,2021.Compared with baseline situation,the dates for controlling Rt below 1 under three scenarios were delayed 10 days.Conclusions:Shijiazhuang epidemic was the first COVID-19 outbreak in the rural areas in Hebei Province of Northern China.The targeted interventions adopted in early 2021 were effective to halt the transmission due to the implementation of a strict and village-wide closure.However we found that age group profile and NPIs played critical rules to successfully contain Shijiazhuang epidemic,which should be considered by public health policies in rural areas of China's Mainland during the dynamic zero-COVID policy.

Generalized perfect optical vortices with free lens modulation

In this paper,we present an approach called the free lens modulation(FLM)method to generate high-perfection3D generalized perfect optical vortices(GPOVs)with topological charges of 1–80.In addition,2D and 3D GPOVs were produced by altering the parameters of the freely shaped lenses.To verify the quality of the GPOVs produced with the FLM method,we conducted optical trapping experiments and realized linear control of the rotation rate of the trapped particle.Due to the great advantages of high perfection and high power usage in generating arbitrarily shaped GPOVs,the FLM method is expected to be applied in optical manipulation,optical communications,and other fields.

Rapid,artifact-reduced,image reconstruction for super-resolution structured illumination microscopy

Super-resolution structured ilumination microscopy(SR-SIM)is finding increasing application in biomedical research due to its superior ability to visualize subcellular dynamics in living cells.However,during image reconstruction artifacts can be introduced and when coupled with time-consuming postprocessing procedures,limits this technique from becoming a routine imaging tool for biologists.To address these issues,an accelerated,artifact-reduced reconstruction algorithm termed joint space frequency reconstruction-based artifact reduction algorithm(JSFR-AR-SIM)was developed by integrating a high-speed reconstruc tion framework with a high-fidelity optimization approach designed to suppress the sidelobe artifact.Consequently,JSFR-AR-SIM produces high-quality,super-resolution images with minimal artifacts,and the reconstruction speed is increased.We anticipate this algorithm to facilitate SR-SIM becoming a routine tool in biomedical laboratories.

High-speed image reconstruction for optically sectioned,super-resolution structured illumination microscopy

Super-resolution structured illumination microscopy(SR-SIM)is an outstanding method for visualizing the subcellular dynamics in living cells.To date,by using elaborately designed systems and algorithms,SR-SIM can achieve rapid,optically sectioned,SR observation with hundreds to thousands of time points.However,real-time observation is still out of reach for most SIM setups as conventional algorithms for image reconstruction involve a heavy computing burden.To address this limitation,an accelerated reconstruction algorithm was developed by implementing a simplified workflow for SR-SIM,termed joint space and frequency reconstruction.This algorithm results in an 80-fold improvement in reconstruction speed relative to the widely used Wiener-SIM.Critically,the increased processing speed does not come at the expense of spatial resolution or sectioning capability,as demonstrated by live imaging of microtubule dynamics and mitochondrial tubulation.

Multi-objective optimization of building design for life cycle cost and C0_(2) emissions:A case study of a low-energy residential building in a severe cold climate

Currently,building construction and operation are responsible for 36%of global final energy usage and nearly 40%of energy-related carbon dioxide(CO_(2))emissions.From the sustainable development perspective,it is crucial to consider the impact of construction material on the achievement of life cycle benefits.This study proposed a simulation-based multi-objective optimization method to minimize both life cycle cost and CO_(2) emissions of buildings.We built an energy simulation model with hybrid ventilation and light-dimming control in EnergyPlus based on an operational passive residential building in a severe cold climate.Next,this investigation selected insulation thickness,window type,window-to-wall ratio,overhang depth and building orientation as design variables.The study ran parametric simulations to establish a database and then used artificial neural network models to correlate the design variables and the objective functions.Finally,we used the multi-objective optimization algorithm NSGA-Ⅱ to search for the optimal design solutions.The results showed potential reductions of 10.9%-18.9%in life cycle cost and 13.5%-22.4%in life cycle CO_(2) emissions compared with the initial design.The results indicated that the optimization approach in this study would improve building performance.The optimal values of the design variables obtained in this study can guide designers in meeting economic and environmental targets in passive buildings.

AVP(4-8) Improves Cognitive Behaviors and Hippocampal Synaptic Plasticity in the APP/PS1 Mouse Model of Alzheimer’s Disease

Memory deficits with aging are related to the neurodegeneration in the brain, including a reduction in arginine vasopressin(AVP) in the brain of patients with Alzheimer’s disease(AD). AVP(4-8), different from its precursor AVP, plays memory enhancement roles in the CNS without peripheral side-effects. However, it is not clear whether AVP(4-8) can improve cognitive behaviors and synaptic plasticity in the APP/PS1 mouse model of AD. Here, we investigated for the first time the neuroprotective effects of AVP(4-8) on memory behaviors and in vivo long-term potentiation(LTP) in APP/PS1-AD mice.The results showed that:(1) APP/PS1-AD mice had lower spontaneous alternation in the Y-maze than wild-type(WT) mice, and this was significantly reversed by AVP(4-8);(2) the prolonged escape latency of APP/PS1-AD mice in the Morris water maze was significantly decreased by AVP(4-8), and the decreased swimming time in target quadrant recovered significantly after AVP(4-8) treatment;(3) in vivo hippocampal LTP induced by high-frequency stimulation had a significant deficit in the AD mice, and this was partly rescued by AVP(4-8);(4) AVP(4-8)significantly up-regulated the expression levels of postsynaptic density 95(PSD95) and nerve growth factor(NGF)in the hippocampus of AD mice. These results reveal the beneficial effects of AVP(4-8) in APP/PS1-AD mice,showing that the intranasal administration of AVP(4-8)effectively improved the working memory and long-term spatial memory of APP/PS1-AD mice, which may be associated with the elevation of PSD95 and NGF levels in the brain and the maintenance of hippocampal synaptic plasticity.

Genetic Analysis of Chromosomal Loci Affecting the Content of Insoluble Glutenin in Common Wheat

In common wheat, insoluble glutenin （IG） is an important fraction of flour glutenin macropolymers, and insoluble glutenin content （IGC） is positively associated with key end-use quality parameters. Here, we present a genetic analysis of the chromosomal loci affecting IGC with the data collected from 90 common wheat varieties cultivated in four environments. Statistical analysis showed that IGC was controlled mainly genetically and influenced by the environment. Among the major genetic components known to affect end-use quality, 1BL/1RS translocation had a significantly negative effect on IGC across all four environments. As to the different alleles of Glu-A1, -B1 and -D1 loci, Glu-Ala, Glu-Blb and Glu-Dld exhibited relatively strong positive effects on IGC in all environments. To identify new loci affecting IGC, association mapping with 1355 DArT markers was conducted. A total of 133 markers were found associated with IGC in two or more environments （P 〈 0.05）, ten of which consistently affected IGC in all four environments. The phenotypic variance explained by the ten markers varied from 4.66% to 8.03%, and their elite alleles performed significantly better than the inferior counterparts in enhancing IGC. Among the ten markers, wPt-3743 and wPt-733835 reflected the action of Glu-D1, and wPt-664972 probably indicated the effect of GIu-A1. The other seven markers, forming three clusters on 2AL. 3BL or 7BL chromosome arms, represented newly identified genetic determinants of IGC. Our work provided novel insights into the genetic control of IGC, which may facilitate wheat end- use quality improvement through molecular breeding in the future.

Processing stage-guided effects of spices on the formation and accumulation of heterocyclic amines in smoked and cooked sausages

Heterocyclic amines (HAs) could be generated though sausage processing.The results showed that garlic,black pepper,chili inhibited the formation of HAs (584.29 ng/g,613.11 ng/g,677.23 ng/g) whereas ginger and Sichuan pepper intensified (965.66 ng/g,916.59 ng/g) compare with control sausage 863.86 ng/g.Furthermore,the study showed that garlic,black pepper,chilli all inhibited the formation of total HAs at stage of raw,drying,baking and steaming and had different inhibitory effect at every stage.Black pepper had the best inhibitory effect across four stages and inhibition rate reached 65%,69%,66%,84% after each stage.Chilli was the only one had inhibitory effect on both free and protein-bound HAs at every stage and inhibition rate about free and protein-bound HAs reached 38% and 76% in finished sausage.Adding certain spices properly during processing would be helpful to obtain fewer HAs in sausage.

Zoning strategy of zonal modeling for thermally stratified large spaces

Large space buildings play a significant role in modern society because of their environmental advantages and market value.While the zonal model is promising for the efficient and rapid evaluation of the stratified thermal environment,there is a lack of a reasonable and convenient zoning strategy with the advent of modern computing.This paper presents a universal and practical zonal model,in which a simplified momentum equation is applied to consider air momentum preservation,transformation,and dissipation.Hence,the zoning structure is generalized and flexible.Moreover,limiting the dimensionless temperature constraint between adjacent zones establishes the connection between thermal nonuniformity and zoning results automatically.Simultaneously,the dimension and number of zones should be restricted within reasonable ranges to satisfy the characteristics of zonal simulation and reach the criteria of convergence.To further explore and validate the zonal model,a reduced-scale experimental model was constructed to replicate the thermal stratification in a mechanically ventilated large space by considering many crucial realistic factors.A particle image velocimetry(PIV)measurement was then conducted to visualize the airflow pattern and support the partition of zones.The results showed that the zonal simulation with adaptive zoning method can realize a similar accuracy with fewer zones and exhibit a better tolerance for zoning results compared to the conventional empirical zoning method.Furthermore,a case study of an atrium was performed to demonstrate the practicality and efficiency of the method for long-term dynamic simulations of complex thermal environments and building energy use.

Study and prediction of the 2022 global monkeypox epidemic

The World Health Organization(WHO)declared monkeypox as a public health emergency of international concern(PHEIC)on July 23,2022,their highest level of alert.This raised concerns about the management of the global monkeypox outbreak,as well as the scientific analysis and accurate prediction of the future course of the epidemic.This study used EpiSIX(an analysis and prediction system for epidemics based on a general SEIR model)to analyze the monkeypox epidemic and to forecast the major tendencies based on data from the USA CDC(https://www.cdc.gov)and the WHO(https://www.who.int/health-topics/monkeypox).The global outbreak of monkeypox started in the UK on May 2,2022,which marked the beginning of an epidemic wave.As of October 28,2022,the cumulative number of reported cases worldwide was 77,115,with 36 deaths.EpiSIX simulations predict that the global monkeypox epidemic will enter a low epidemic status on March 1,2023 with the cumulative number of confirmed cases ranging from 85,000 to 124,000,and the total number of deaths ranging from 60 to 87.Our analysis revealed that the basic reproduction number(R0)of monkeypox virus(MPXV)is near to 3.1 and the percentage of asymptomatic individuals is 13.1%–14.5%,both of which are similar to the data for SARS.The vaccination efficiency against susceptibility(VEs)of individuals who have had monkeypox is~79%,and the vaccination efficiency against infectiousness(VEi)of individuals who have had monkeypox is~76%–82%.The mean incubation period for monkeypox is 8 days.In total,94.7%of infected individuals develop symptoms within 20 days and recover within 2 weeks after the confirmation of symptoms.Simulation results using EpiSIX showed that ring vaccination was remarkably effective against monkeypox.Our findings confirmed that a 20-day isolation for close contacts is necessary.

An adaptive lack of fit test for big data

New technological advancements combined with powerful computer hardware and high-speed network make big data available.The massive sample size of big data introduces unique computational challenges on scalability and storage of statistical methods.In this paper,we focus on the lack of fit test of parametric regression models under the framework of big data.We develop a computationally feasible testing approach via integrating the divide-and-conquer algorithm into a powerful nonparametric test statistic.Our theory results show that under mild conditions,the asymptotic null distribution of the proposed test is standard normal.Furthermore,the proposed test benefits fromthe use of data-driven bandwidth procedure and thus possesses certain adaptive property.Simulation studies show that the proposed method has satisfactory performances,and it is illustrated with an analysis of an airline data.

Off-axis optical levitation and transverse spinning of metallic microparticles

Optical manipulation of metallic microparticles remains a significant challenge because of the strong scattering forces arising from the high extinction coefficient of the particles.This paper reports a new mechanism for stable confinement of metallic microparticles using a tightly focused linearly polarized Gaussian beam.Theoretical and experimental results demonstrate that metallic microparticles can be captured off the optical axis in such a beam.Meanwhile,the three-dimensionally confined particles are observed spinning transversely as a response to the asymmetric force field.The off-axis levitation and transverse spinning of metallic microparticles may provide a new way for effective manipulation of metallic microparticles.