Adsorption,in vitro digestion and human gut microbiota regulation characteristics of three Poria cocos polysaccharides

Poria cocos(PC)is a famous traditional Chinese medicine(TCM)and a widely used healthcare ingredient,which has antiobesity,enhancing immunity and improving sleep effects.Traditionally,only water-soluble poria polysaccharide(WSP)is extracted and applied for clinical application,while insoluble polysaccharide(alkali-soluble poria polysaccharide,ASP)is discarded as herb residue.However,the whole PC has also been historically utilized as functional herbal food.Considering the beneficial role of dietary fiber and the traditional use of PC,ASP may also contribute substantially to the therapy function of PC.Compared to WSP,little attention has been paid to ASP and ASP modified product carboxymethyl poria polysaccharide(CMP)which has been used as an antitumor adjuvant drug.In this study,the oil,cholesterol,metal ions and polyphenols adsorption ability,in vitro simulated digestive and the gut microbiota fermentation characteristics of WSP,ASP and CMP were studied to evaluate the functional values of three P.cocos polysaccharides(PCPs).The results showed that all three PCPs had good adsorption capacity on cholesterol,polyphenols and metal ions(Cd^(2+)/Zn^(2+)/Mg^(2+)),among which ASP showed the highest capacity than WSP and CMP.The adsorption capacity of all three PCPs on heavy metal ions(Cd^(2+)/Zn^(2+))was stronger than that of non-heavy metal ions(Mg^(2+));The in vitro digestibility of all three PCPs was very low,but WSP was slightly higher than ASP and CMP;Moreover,the indigestible residue of all three PCPs could improve the richness and diversity of gut microbiota,among which ASP had the greatest influence.In general,ASP and CMP could significantly promote the proliferation of some probiotics and inhibit the growth of some harmful bacteria.The gut microbiota diversity of CMP was reduced,but the richness of probiotics,especially Parabacteroides distasonis was significantly enhanced compared with the ASP group,and the growth of harmful bacteria Klebsiella pneumoniae was inhibited after CMP treatment.The short-chain fatty acids(SCFAs)analysis results showed that all three PCPs could significantly promote the production of acetic acid,propionic acid and the total acid content compared with blank control group,and SCFAs producing activity was positively correlated with the proliferative capacity of probiotics.Taken together,the good adsorption characteristics and gut microbiota regulatory activity of ASP may lay foundation for its lipid-lowering and immune-improving function.Additionally,the probiotic effect of CMP and ASP indicated that except for only use the water extract of PC in clinic,CMP and ASP also can be used in healthcare to take full advantage of this valuable medicine.

Evolution of Biofilm and Its Effect on Microstructure of Mortar Surfaces in Simulated Seawater

To explore the role of biofilm formation on the corrosion of marine concrete structures, we investigated the attachment of biofilm on mortar surfaces in simulated seawater and the influence of biofilm on the microstructure of mortar surfaces. The results show that the evolution of biofilm on mortar surfaces in simulated seawater is closely related to the corrosion suffered by the mortar, and the process of biofilm attachment and shedding is continuous and cyclical. It is found that the specimens in the absence of biofilm attachment are more severely eroded internally by the corrosive medium in simulated seawater than those in the presence of biofilm attachment. For the specimens without biofilm attachment, after 60 days, gypsum forms,and after 120 days, the number of pores in the mortar is reduced. In contrast, for the specimens in the presence of biofilm attachment, gypsum could only be detected after 90 days, and fewer pores are filled. Therefore, the formation of biofilm could delay the invasion of the corrosive medium into the interior of mortar during the evolution of biofilm on mortar surfaces, mitigating the corrosion of mortars in seawater.

Developing kNN forest data imputation for Catalonia

The combined use of LiDAR(Light Detection And Ranging)scanning and field inventories can provide spatially continuous wall-to-wall information on forest characteristics.This information can be used in many ways in forest mapping,scenario analyses,and forest manage-ment planning.This study aimed to find the optimal way to obtain continuous forest data for Catalonia when using kNN imputation(kNN stands for“k nearest neighbors”).In this method,data are imputed to a certain location from k field-measured sample plots,which are the most similar to the location in terms of LiDAR metrics and topographic variables.Weighted multidimensional Euclidean distance was used as the similarity measure.The study tested two different methods to optimize the distance measure.The first method optimized,in the first step,the set of LiDAR and topographic variables used in the measure,as well as the transformations of these variables.The weights of the selected variables were optimized in the second step.The other method optimized the variable set as well as their transformations and weights in one single step.The two-step method that first finds the variables and their transfor-mations and subsequently optimizes their weights resulted in the best imputation results.In the study area,the use of three to five nearest neighbors was recommended.Altitude and latitude turned out to be the most important variables when assessing the similarity of two locations of Catalan forests in the context of kNN data imputation.The optimal distance measure always included both LiDAR metrics and topographic variables.The study showed that the optimal similarity measure may be different for different regions.Therefore,it was suggested that kNN data imputation should always be started with the optimization of the measure that is used to select the k nearest neighbors.

Quantum control based on three forms of Lyapunov functions

This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors.In this paper, the specific control laws under the three forms are given.Stability is analyzed by the La Salle invariance principle and the numerical simulation is carried out in a 2D test system.The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm.Finally, a unified form of the control laws under the three forms is given.

Growth and inhibition of zinc anode dendrites in Zn-air batteries:Model and experiment

Zinc(Zn)-air batteries are widely used in secondary battery research owing to their high theoretical energy density,good electrochemical reversibility,stable discharge performance,and low cost of the anode active material Zn.However,the Zn anode also leads to many challenges,including dendrite growth,deformation,and hydrogen precipitation self-corrosion.In this context,Zn dendrite growth has a greater impact on the cycle lives.In this dissertation,a dendrite growth model for a Zn-air battery was established based on electrochemical phase field theory,and the effects of the charging time,anisotropy strength,and electrolyte temperature on the morphology and growth height of Zn dendrites were studied.A series of experiments was designed with different gradient influencing factors in subsequent experiments to verify the theoretical simulations,including elevated electrolyte temperatures,flowing electrolytes,and pulsed charging.The simulation results show that the growth of Zn dendrites is controlled mainly by diffusion and mass transfer processes,whereas the electrolyte temperature,flow rate,and interfacial energy anisotropy intensity are the main factors.The experimental results show that an optimal electrolyte temperature of 343.15 K,an optimal electrolyte flow rate of 40 ml·min^(-1),and an effective pulse charging mode.

考虑混合工艺的自动化码头多设备资源协同调度优化模型和算法设计

Considering the uncertainty of the speed of horizontal transportation equipment,a cooperative scheduling model of multiple equipment resources in the automated container terminal was constructed to minimize the completion time,thus improving the loading and unloading efficiencies of automated container terminals.The proposed model integrated the two loading and unloading processes of“double-trolley quay crane+AGV+ARMG”and“single-trolley quay crane+container truck+ARMG”and then designed the simulated annealing particle swarm algorithm to solve the model.By comparing the results of the particle swarm algorithm and genetic algorithm,the algorithm designed in this paper could effectively improve the global and local space search capability of finding the optimal solution.Furthermore,the results showed that the proposed method of collaborative scheduling of multiple equipment resources in automated terminals considering hybrid processes effectively improved the loading and unloading efficiencies of automated container terminals.The findings of this study provide a reference for the improvement of loading and unloading processes as well as coordinated scheduling in automated terminals.

A LiDAR Point Clouds Dataset of Ships in a Maritime Environment

For the first time, this article introduces a LiDAR Point Clouds Dataset of Ships composed of both collected and simulated data to address the scarcity of LiDAR data in maritime applications. The collected data are acquired using specialized maritime LiDAR sensors in both inland waterways and wide-open ocean environments. The simulated data is generated by placing a ship in the LiDAR coordinate system and scanning it with a redeveloped Blensor that emulates the operation of a LiDAR sensor equipped with various laser beams. Furthermore,we also render point clouds for foggy and rainy weather conditions. To describe a realistic shipping environment, a dynamic tail wave is modeled by iterating the wave elevation of each point in a time series. Finally, networks serving small objects are migrated to ship applications by feeding our dataset. The positive effect of simulated data is described in object detection experiments, and the negative impact of tail waves as noise is verified in single-object tracking experiments. The Dataset is available at https://github.com/zqy411470859/ship_dataset.

Effect of Ta_(2)O_(5)nanoparticles on bioactivity,composition,structure,in vitro and in vivo behavior of PEO coatings on Mg-alloy

The present study investigates the physical and chemical characteristics,behavior in vitro and in vivo,and biocompatibility of coatings containing Ta_(2)O_(5),which are obtained by plasma electrolytic oxidation(PEO)on MA8 magnesium alloy.The obtained coatings demonstrate in vivo biocompatibility and in vitro bioactivity.Compared to the base PEO coating,the layers containing Ta_(2)O_(5)facilitate the development of apatite in simulated body fluid,suggesting that the inclusion of nanoparticles improves bioactivity of the coatings.It was found that incorporation of Ta_(2)O_(5)nanoparticles increases roughness and porosity of the formed layers by increasing particle concentration in electrolytes for the PEO process contributing to sufficient soft tissue ingrowth in vivo.Based on in vivo studies,these coatings also provide favorable tissue response and minimal inflammatory reaction in comparison with the bare magnesium alloy due to protection of living tissues from deleterious corrosion events of magnesium implant such as local alkalization and intense hydrogen evolution.The results obtained in the present study concluded biocompatibility,tissue integration of the PEO coatings containing Ta_(2)O_(5)nanoparticles making them a promising protective layer for biodegradable magnesium implants.

Müller cells are activated in response to retinal outer nuclear layer degeneration in rats subjected to simulated weightlessness conditions

A microgravity environment has been shown to cause ocular damage and affect visual acuity,but the underlying mechanisms remain unclear.Therefore,we established an animal model of weightlessness via tail suspension to examine the pathological changes and molecular mechanisms of retinal damage under microgravity.After 4 weeks of tail suspension,there were no notable alterations in retinal function and morphology,while after 8 weeks of tail suspension,significant reductions in retinal function were observed,and the outer nuclear layer was thinner,with abundant apoptotic cells.To investigate the mechanism underlying the degenerative changes that occurred in the outer nuclear layer of the retina,proteomics was used to analyze differentially expressed proteins in rat retinas after 8 weeks of tail suspension.The results showed that the expression levels of fibroblast growth factor 2(also known as basic fibroblast growth factor)and glial fibrillary acidic protein,which are closely related to Müller cell activation,were significantly upregulated.In addition,Müller cell regeneration and Müller cell gliosis were observed after 4 and 8 weeks,respectively,of simulated weightlessness.These findings indicate that Müller cells play an important regulatory role in retinal outer nuclear layer degeneration during weightlessness.

Strengthened Dominance Relation NSGA-Ⅲ Algorithm Based on Differential Evolution to Solve Job Shop Scheduling Problem

The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems.It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives.The Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ)is an effective approach for solving the multi-objective job shop scheduling problem.Nevertheless,it has some limitations in solving scheduling problems,including inadequate global search capability,susceptibility to premature convergence,and challenges in balancing convergence and diversity.To enhance its performance,this paper introduces a strengthened dominance relation NSGA-Ⅲ algorithm based on differential evolution(NSGA-Ⅲ-SD).By incorporating constrained differential evolution and simulated binary crossover genetic operators,this algorithm effectively improves NSGA-Ⅲ’s global search capability while mitigating pre-mature convergence issues.Furthermore,it introduces a reinforced dominance relation to address the trade-off between convergence and diversity in NSGA-Ⅲ.Additionally,effective encoding and decoding methods for discrete job shop scheduling are proposed,which can improve the overall performance of the algorithm without complex computation.To validate the algorithm’s effectiveness,NSGA-Ⅲ-SD is extensively compared with other advanced multi-objective optimization algorithms using 20 job shop scheduling test instances.The experimental results demonstrate that NSGA-Ⅲ-SD achieves better solution quality and diversity,proving its effectiveness in solving the multi-objective job shop scheduling problem.

Simultaneous determination of typical toxic aldehydes formed during food frying and digestion using isotope dilution UHPLC-QqQ-MS/MS

An isotope dilution ultra-performance liquid chromatography-triple quadrupole mass spectrometry method was developed to simultaneously detect two typical kinds ofα,β-unsaturated aldehydes,namely 4-hydroxy-2-hexenal(4-HHE)and 4-hydroxy-2-nonenal(4-HNE),in foods.The proposed method exhibited a linear range of 10-1000 ng/mL with a limit of detection of 0.1-2.0 ng/g and a limit of quantification of 0.3-5.0 ng/g.The recovery rates of these typical toxic aldehydes(i.e.,4-HHE,4-HNE)and their d3-labeled analogues were 91.54%-105.12%with a low matrix effect.Furthermore,this proposed method was successfully applied to a real frying system and a simulated digestion system,wherein the contents of 4-HHE and 4-HNE were determined for both.Overall,the obtained results provide strong support for further research into the production of 4-HHE and 4-HNE resulting from foods during oil digestion and frying.

Experimental Study on the Performance of ORC System Based on Ultra-Low Temperature Heat Sources

This paper discussed the experimental results of the performance of an organic Rankine cycle(ORC)system with an ultra-low temperature heat source.The low boiling point working medium R134a was adopted in the system.The simulated heat source temperature(SHST)in this work was set from 39.51°C to 48.60°C by the simulated heat source module.The influence of load percentage of simulated heat source(LPSHS)between 50%and 70%,the rotary valve opening(RVO)between 20%and 100%,the resistive load between 36Ωand 180Ωor the no-load of the generator,as well as the autumn and winter ambient temperature on the system performance were studied.The results showed that the stability of the system was promoted when the generator had a resistive load.The power generation(PG)and generator speed(GS)of the system in autumn were better than in winter,but the expander pressure ratio(EPR)was lower than in winter.Keep RVO unchanged,the SHST,the mass flow rate(MFR)of the working medium,GS,and the PG of the system increased with the increasing of LPSHS for different generator resistance load values.When the RVO was 60%,LPSHS was 70%,the SHST was 44.15°C and the resistive load was 72Ω,the highest PG reached 15.11 W.Finally,a simulation formula was obtained for LPSHS,resistance load,and PG,and its correlation coefficient was between 0.9818 and 0.9901.The formula can accurately predict the PG.The experimental results showed that the standard deviation between the experimental and simulated values was below 0.0792,and the relative error was within±5%.

Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.

Simulated patient methodology as a“gold standard”in community pharmacy practice:Response to criticism

The simulated patient methodology(SPM)is considered the“gold standard”as covert participatory observation.SPM is attracting increasing interest for the investigation of community pharmacy practice;however,there is criticism that SPM can only show a small picture of everyday pharmacy practice and therefore has limited external validity.On the one hand,a certain design and application of the SPM goes hand in hand with an increase in external validity.Even if,on the other hand,this occurs at the expense of internal validity due to the trade-off situation,the justified criticism of the SPM for investigating community pharmacy practice can be countered.

Design of MC9 Test Equipment for Inertial Reference System

Inertial reference system is one of the airborne equipment.According to the requirements of SAE ARP4754A Guidelines for Development of Civil Aircraft and Systems,MC9 equipment qualification test is needed to verify that the inertial reference system can perform reservation function under specified service conditions.That is,the inertial reference system shall pass certain environmental tests specified in DO⁃160G.Some tests are faced with the problem that the test equipment should have the function requirements of isolation protection and load simulation.Therefore,a kind of test equipment which can provide isolation protection and simulate load function in the test is designed.

Scheduling on tractor and trailer transportation considering the influence of disrupted events based on the contract net and simulated annealing algorithm

To provide a much more resilient transport scheme for tractor and trailer transportation systems,this paper explores the generation method of tractor and trailer transport schemes considering the influence of disrupted events.Three states of tractors including towing loaded trailers,towing empty trailers,and idle driving are taken into account.Based on the disruption management theory,a scheduling model is constructed to minimize the total deviation cost including transportation time,transportation path,and number of used vehicles under the three states of tractors.A heuristics based on the contract net and simulated annealing algorithm is designed to solve the proposed model.Through comparative analysis of examples with different numbers of newly added transportation tasks and different types of road networks,the performance of the contract net algorithm in terms of deviations in idle driving paths,empty trailer paths,loaded trailer paths,time,number of used vehicles,and total deviation cost are analyzed.The results demonstrate the effectiveness of the model and algorithm,highlighting the superiority of the disruption management model and the contract net annealing algorithm.The study provides a reference for handling unexpected events in the tractor and trailer transportation industry.

On the “Onion Husk” Algorithm for Approximate Solution of the Traveling Salesman Problem

The paper describes some implementation aspects of an algorithm for approximate solution of the traveling salesman problem based on the construction of convex closed contours on the initial set of points (“cities”) and their subsequent combination into a closed path (the so-called contour algorithm or “onion husk” algorithm). A number of heuristics related to the different stages of the algorithm are considered, and various variants of the algorithm based on these heuristics are analyzed. Sets of randomly generated points of different sizes (from 4 to 90 and from 500 to 10,000) were used to test the algorithms. The numerical results obtained are compared with the results of two well-known combinatorial optimization algorithms, namely the algorithm based on the branch and bound method and the simulated annealing algorithm. .

Performance of a Combined Energy System Consisting of Solar Collector, Biogas Dry Reforming and Solid Oxide Fuel Cell: An Indian Case Study

An energy production system consisting of a solar collector, biogas dry reforming reactor and solid oxide fuel cell (SOFC) was assumed to be installed in Kolkata, India. This study aims to understand the impact of climate conditions on the performance of solar collectors with different lengths of parabolic trough solar collector (dx) and mass flow rate of heat transfer fluid (m). In addition, this study has evaluated the amount of H2 produced by biogas dry reforming (GH2), the amount of power generated by SOFC (PSOFC) and the maximum number of possible households (N) whose electricity demand could be met by the energy system proposed, considering the performance of solar collector with the different dx and m. As a result, the optimum dx was found to be 4 m. This study revealed that the temperature of heat transfer fluid (Tfb) decreased with the increase in m. Tfb in March, April and May was higher than that in other months, while Tfb from June to December was the lowest. GH2, PSOFC and N in March, April and May were higher than those in other months, irrespective of m. The optimum m was 0.030 kg/s.

A theoretical and deep learning hybrid model for predicting surface roughness of diamond-turned polycrystalline materials

Polycrystalline materials are extensively employed in industry.Its surface roughness significantly affects the working performance.Material defects,particularly grain boundaries,have a great impact on the achieved surface roughness of polycrystalline materials.However,it is difficult to establish a purely theoretical model for surface roughness with consideration of the grain boundary effect using conventional analytical methods.In this work,a theoretical and deep learning hybrid model for predicting the surface roughness of diamond-turned polycrystalline materials is proposed.The kinematic–dynamic roughness component in relation to the tool profile duplication effect,work material plastic side flow,relative vibration between the diamond tool and workpiece,etc,is theoretically calculated.The material-defect roughness component is modeled with a cascade forward neural network.In the neural network,the ratio of maximum undeformed chip thickness to cutting edge radius RT S,work material properties(misorientation angle θ_(g) and grain size d_(g)),and spindle rotation speed n s are configured as input variables.The material-defect roughness component is set as the output variable.To validate the developed model,polycrystalline copper with a gradient distribution of grains prepared by friction stir processing is machined with various processing parameters and different diamond tools.Compared with the previously developed model,obvious improvement in the prediction accuracy is observed with this hybrid prediction model.Based on this model,the influences of different factors on the surface roughness of polycrystalline materials are discussed.The influencing mechanism of the misorientation angle and grain size is quantitatively analyzed.Two fracture modes,including transcrystalline and intercrystalline fractures at different RTS values,are observed.Meanwhile,optimal processing parameters are obtained with a simulated annealing algorithm.Cutting experiments are performed with the optimal parameters,and a flat surface finish with Sa 1.314 nm is finally achieved.The developed model and corresponding new findings in this work are beneficial for accurately predicting the surface roughness of polycrystalline materials and understanding the impacting mechanism of material defects in diamond turning.

Cascade refrigeration system synthesis based on hybrid simulated annealing and particle swarm optimization algorithm

Cascade refrigeration system(CRS)can meet a wider range of refrigeration temperature requirements and is more energy efficient than single-refrigerant refrigeration system,making it more widely used in low-temperature industry processes.The synthesis of a CRS with simultaneous consideration of heat integration between refrigerant and process streams is challenging but promising for significant cost saving and reduction of carbon emission.This study presented a stochastic optimization method for the synthesis of CRS.An MINLP model was formulated based on the superstructure developed for the CRS,and an optimization framework was proposed,where simulated annealing algorithm was used to evolve the numbers of pressure/temperature levels for all sub-refrigeration systems,and particle swarm optimization algorithm was employed to optimize the continuous variables.The effectiveness of the proposed methodology was verified by a case study of CRS optimization in an ethylene plant with 21.89%the total annual cost saving.