Application of support vector machine in trip chaining pattern recognition and analysis of explanatory variable effects

In order to improve the accuracy of travel demand forecast and considering the distribution of travel behaviors within time dimension, a trip chaining pattern recognition model was established based on activity purposes by applying three methods： the support vector machine （SVM） model, the radial basis function neural network （RBFNN） model and the multinomial logit （MNL） model. The effect of explanatory factors on trip chaining behaviors and their contribution to model performace were investigated by sensitivity analysis. Results show that the SVM model has a better performance than the RBFNN model and the MNL model due to its higher overall and partial accuracy, indicating its recognition advantage under a smai sample size scenario. It is also proved that the SVM model is capable of estimating the effect of multi-category factors on trip chaining behaviors more accurately. The different contribution of explanatory, factors to trip chaining pattern recognition reflects the importance of refining trip chaining patterns ad exploring factors that are specific to each pattern. It is shown that the SVM technology in travel demand forecast modeling and analysis of explanatory variable effects is practical.

Multi-Path Service Function Chaining for Mobile Surveillance of Animal Husbandry

Animal husbandry is the pillar industry in some ethnic areas of China.However,the communication/networking infrastructure in these areas is often underdeveloped,thus the difficulty in centralized management,and challenges for the effective monitoring.Considering the dynamics of the field monitoring environment,as well as the diversity and mobility of monitoring targets,traditional WSN(Wireless Sensor Networks)or IoT(Internet of Things)is difficult to meet the surveillance needs.Mobile surveillance that features the collaboration of various functions(camera,sensing,image recognition,etc.)deployed on mobile devices is desirable in a volatile wireless environment.This paper proposes the service function chaining for mobile surveillance of animal husbandry,which orchestrates multi-path multifunction(MPMF)chains to help mobile devices to collaborate in complex surveillance tasks,provide backup chains in case the primary service function chain fails due to mobility,signal strength,obstacle,etc.,and make up for the defects of difficult deployment of monitoring facilities in ethnic areas.MPMF algorithmmodels both mobile devices and various functions deployed on them as abstract graph nodes,so that chains that are required to traverse various functions and hosting mobile devices can be orchestrated in a single graphbased query through modified and adapted Dijkstra-like algorithms,with their cost ordered automatically.Experiment results show that the proposed MPMF algorithm finds multiple least-costly chains that traverse demanded functions in a timely fashion on Raspberry Pi-equipped mobile devices.

基于SDN的动态ServiceChaining方案

随着终端规模的不断增加和云计算的逐渐普及,园区网的业务越来越多样化,从而带来网络容量和带宽升级。基础网络升级后,园区边缘网络的专用设备(防火墙、广域网加速设备等)容易成为整个园区网的性能瓶颈点。而对这些专用设备进行升级和更换所带来的支出费用较大,同时由于这些设备都是专业的硬件设备,其部署配置和运维管理相对于交换机与路由器也较为复杂。如何利旧现有专用设备、降低改造费用成为园区网建设所需考虑的重要因素。本文通过引入SDN,阐述了如何基于SDN实现动态Service Chaining技术,实现按需引流。动态Service Chaining技术可实现网络出口智能引流、安全资源池化、网络安全协防,从而搭建一个富有弹性、高度可扩展的业务流处理平台。

A novel mechanism of PHB2-mediated mitophagy participating in the development of Parkinson's disease

Endoplasmic reticulum stress and mitochondrial dysfunction play important roles in Parkinson s disease,but the regulato ry mechanism remains elusive.Prohibitin-2(PHB2)is a newly discove red autophagy receptor in the mitochondrial inner membrane,and its role in Parkinson’s disease remains unclear.Protein kinase R(PKR)-like endoplasmic reticulum kinase(PERK)is a factor that regulates cell fate during endoplasmic reticulum stress.Parkin is regulated by PERK and is a target of the unfolded protein response.It is unclear whether PERK regulates PHB2-mediated mitophagy thro ugh Parkin.In this study,we established a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)-induced mouse model of Parkinson’s disease.We used adeno-associated virus to knockdown PHB2 expression.Our res ults showed that loss of dopaminergic neurons and motor deficits were aggravated in the MPTP-induced mouse model of Parkinson’s disease.Ove rexpression of PHB2 inhibited these abnormalities.We also established a 1-methyl-4-phenylpyridine(MPP+)-induced SH-SY5Y cell model of Parkinson’s disease.We found that ove rexpression of Parkin increased co-localization of PHB2 and microtubule-associated protein 1 light chain 3,and promoted mitophagy.In addition,MPP+regulated Parkin involvement in PHB2-mediated mitophagy through phosphorylation of PERK.These findings suggest that PHB2 participates in the development of Parkinson’s disease by intera cting with endoplasmic reticulum stress and Parkin.

基于NEATM和WISE数据的小尺寸近地小行星物理特性研究

小行星是太阳系中广泛分布的金属或岩石天体,直径从米级跨越到几百公里.它们蕴含了太阳系早期的信息,同时也可能会与地球轨道相交且撞击地球,因此研究小行星的物理参数、物质成分和表面性质对于了解太阳系行星的形成演化和近地天体防御具有重要意义.以国际小行星中心(Minor Planet Center,MPC)获取直径D<160 m的小尺寸近地小行星共67颗作为研究对象,其中包含部分潜在威胁小行星(Potentially Hazardous Asteroids,PHA).基于NEATM(Near-Earth Asteroid Thermal Model),使用广域红外巡天望远镜(Wide-field Infrared Survey Explorer,WISE)的观测数据,利用反射光模型对太阳反射光进行了修正,使用动力学模型计算WISE观测历元的小行星轨道数据,计算了这67颗小尺寸近地小行星的直径和反照率.拟合过程采用马尔科夫链蒙特卡洛(Markov Chain Monte Carlo,MCMC)方法,与WISE的研究结果和MPC的数据进行了比较分析,给出了其分类特征.研究为小行星的观测和理论提供了有力的支持,可以更好地了解近地小行星的特征和演化.

D-Psicose intake exacerbates dextran sulfate sodium-induced colitis in mice through alteration in the gut microbiota and dysfunction of mucosal barrier

D-Psicose,as a low-calorie rare sugar,has attracted a lot of attention in recent years for alternating to sucrose.The anti-obesity effect of D-psicose has been extensively confirmed in previous studies,however,the impact of D-psicose on colitis remains vague.Here,we firstly evaluated the effect of the D-psicose prophylactic intervention on dextran sulfate sodium-induced colitis in C57BL/6 mice.The pathological symptoms,inflammatory cytokines levels,gut microbiota composition,short chain fatty acids(SCFAs)production and colonic barrier integrity were comprehensively evaluated.The results confirmed that D-psicose intervention aggravated colitis,characterized by the exacerbation of colon shortening,increase of colonic inflammatory infiltration,and marked exaltation of disease activity indices and IL-6,IL-1βand TNF-αlevels.Further,the dysfunction of gut microbiota was identified in the psicose group.The abundance of pro-inflammatory bacteria Lachnospiraceae_NK4A136_group was significantly up-regulated while the abundance of probiotics Akkermansia and Lactobacillus were significantly down-regulated in the psicose group compared to the model group.Moreover,the production of SCFAs was suppressed in the psicose group,accompanied by a decrease in the level of mucin 2(Muc-2).Collectively,the underlying mechanism of the exacerbation of colitis by D-psicose intervention might be attributed to microbiota dysfunction accompanied by the reduction of SCFAs,which leads to the damage of the mucosal barrier and the intensifi cation of inflammatory invasion.

An IPC-based Prolog design pattern for integrating backward chaining inference into applications or embedded systems

Prolog is one of the most important candidates to build expert systems and AI-related programs and has potential applications in embedded systems. However, Prolog is not suitable to develop many kinds of components, such as data acquisition and task scheduling, which are also crucial. To make the best use of the advantages and bypass the disadvantages, it is attractive to integrate Prolog with programs developed by other languages. In this paper, an IPC-based method is used to integrate backward chaining inference implemented by Prolog into applications or embedded systems. A Prolog design pattern is derived from the method for reuse, whose principle and definition are provided in detail. Additionally, the design pattern is applied to a target system, which is free software, to verify its feasibility. The detailed implementation of the application is given to clarify the design pattern. The design pattern can be further applied to wide range applications and embedded systems and the method described in this paper can also be adopted for other logic programming languages.

Nonlinear interaction of head-on solitary waves in integrable and nonintegrable systems

This study numerically investigates the nonlinear interaction of head-on solitary waves in a granular chain(a nonintegrable system)and compares the simulation results with the theoretical results in fluid(an integrable system).Three stages(the pre-in-phase traveling stage,the central-collision stage,and the post-in-phase traveling stage)are identified to describe the nonlinear interaction processes in the granular chain.The nonlinear scattering effect occurs in the central-collision stage,which decreases the amplitude of the incident solitary waves.Compared with the leading-time phase in the incident and separation collision processes,the lagging-time phase in the separation collision process is smaller.This asymmetrical nonlinear collision results in an occurrence of leading phase shifts of time and space in the post-in-phase traveling stage.We next find that the solitary wave amplitude does not influence the immediate space-phase shift in the granular chain.The space-phase shift of the post-in-phase traveling stage is only determined by the measurement position rather than the wave amplitude.The results are reversed in the fluid.An increase in solitary wave amplitude leads to decreased attachment,detachment,and residence times for granular chains and fluid.For the immediate time-phase shift,leading and lagging phenomena appear in the granular chain and the fluid,respectively.These results offer new knowledge for designing mechanical metamaterials and energy-mitigating systems.

Chain Elongation Using Native Soil Inocula:Exceptional n-Caproate Biosynthesis Performance and Microbial Mechanisms

This study demonstrates the feasibility and effectiveness of utilizing native soils as a resource for inocula to produce n-caproate through the chain elongation(CE)platform,offering new insights into anaerobic soil processes.The results reveal that all five of the tested soil types exhibit CE activity when supplied with high concentrations of ethanol and acetate,highlighting the suitability of soil as an ideal source for n-caproate production.Compared with anaerobic sludge and pit mud,the native soil CE system exhibited higher selectivity(60.53%),specificity(82.32%),carbon distribution(60.00%),electron transfer efficiency(165.00%),and conductivity(0.59 ms∙cm^(-1)).Kinetic analysis further confirmed the superiority of soil in terms of a shorter lag time and higher yield.A microbial community analysis indicated a positive correlation between the relative abundances of Pseudomonas,Azotobacter,and Clostridium and n-caproate production.Moreover,metagenomics analysis revealed a higher abundance of functional genes in key microbial species,providing direct insights into the pathways involved in n-caproate formation,including in situ CO_(2)utilization,ethanol oxidation,fatty acid biosynthesis(FAB),and reverse beta-oxidation(RBO).The numerous functions in FAB and RBO are primarily associated with Pseudomonas,Clostridium,Rhodococcus,Stenotrophomonas,and Geobacter,suggesting that these genera may play roles that are involved or associated with the CE process.Overall,this innovative inoculation strategy offers an efficient microbial source for n-caproate production,underscoring the importance of considering CE activity in anaerobic soil microbial ecology and holding potential for significant economic and environmental benefits through soil consortia exploration.

Regulation of the quantum barrier and carrier transport toward high-efficiency quasi-2D Dion-Jacobson tin perovskite solar cells

Quasi-2D Dion-Jacobson(DJ)tin halide perovskite has attracted much attention due to its elimination of Van der Waals gap and enhanced environmental stability.However,the bulky organic spacers usually form a natural quantum well structure,which brings a large quantum barrier and poor film quality,further limiting the carrier transport and device performance.Here,we designed three organic spacers with different chain lengths(ethylenediamine(EDA),1,3-propanediamine(PDA),and 1,4-butanediamine(BDA))to investigate the quantum barrier dependence.Theoretical and experimental characterizations indicate that EDA with short chain can reduce the lattice distortion and dielectric confinement effect,which is beneficial to the effective dissociation of excitons and the inhibition of trap-free non-radiative relaxation.In addition,EDA cation shows strong interaction with the inorganic octahedron,realizing large aggregates in precursor solution and high-quality films with improved structural stability.Furthermore,femtosecond transient absorption proves that EDA cations can also weaken the formation of small n-phases with large quantum barrier to achieve effective carrier transport between different nphases.Finally,the quasi-2D DJ(EDA)FA_(9)Sn_(10)I_(31)solar cells achieves a 7.07%power conversion efficiency with good environment stability.Therefore,this work sheds light on the regulation of the quantum barrier and carrier transport through the chain length of organic spacer for qua si-2D DJ lead-free perovskites.

揭示氨对正己酸生产影响的机制——影响途径、关键酶和微生物

n-Caproate,which is produced via chain elongation(CE)using waste biomass,can supply various fossilderived products,thus advancing the realization of carbon neutrality.Ammonia released from the degradation of nitrogen-rich waste biomass can act as a nutrient or an inhibitor in anaerobic bioprocesses,including CE,with the distinction being primarily dependent on its concentration.Currently,the optimal concentration of ammonia and the threshold of toxicity for open-culture n-caproate production using ethanol as an electron donor,along with the underlying mechanisms,remain unclear.This study revealed that the optimal concentration of ammonia for n-caproate production was 2.0 g∙L^(-1),whereas concentrations exceeding this threshold markedly suppressed the CE performance.Exploration of the mechanism revealed the involvement of two forms of ammonia(i.e.,ammonium ions and free ammonia)in this inhibitory behavior.High ammonia levels(5.0 g∙L^(-1))induced excessive ethanol oxidation and suppressed the reverse β-oxidation(RBO)process,directly leading to the enhanced activities of enzymes(phosphotransacetylase and acetate kinase)responsible for acetate formation and diminished activities of butyryl-coenzyme A(CoA):acetyl-CoA transferase,caproyl-CoA:butyryl-CoA transferase,and caproyl-CoA:acetyl-CoA transferase that are involved in the syntheses of n-butyrate and n-caproate.Furthermore,the composition of the microbial community shifted from Paraclostridium dominance(at 0.1 g∙L^(-1)ammonia)to a co-dominance of Fermentimonas,Clostridium sensu stricto 12,and Clostridium sensu stricto 15 at 2.0 g∙L^(-1)ammonia.However,these CE-functional bacteria were mostly absent in the presence of excessive ammonia(5.0 g∙L^(-1)ammonia).Metagenomic analysis revealed the upregulation of functions such as RBO,fatty acid synthesis,K^(+)efflux,adenosine triphosphatase(ATPase)metabolism,and metal cation export in the presence of 2.0 g∙L^(-1)ammonia,collectively contributing to enhanced n-caproate production.Conversely,the aforementioned functions(excluding metal cation export)and K^(+)influx were suppressed by excessive ammonia,undermining both ammonia detoxification and n-caproate biosynthesis.The comprehensive elucidation of ammonia-driven mechanisms influencing n-caproate production,as provided in this study,is expected to inspire researchers to devise effective strategies to alleviate ammonia-induced inhibition.

Migration pattern of a population of Barn Swallows(Hirundo rustica)breeding in East Asian tropical region

Birds exhibit a high degree of migratory diversity,which is influenced by various ecological factors and life history strategies.Conducting studies on tropical bird migration,of which research is scarce,and comparing it with temperate birds can enhance our understanding of bird migration behaviour and its underlying mecha-nisms.In this study,we explored the migration behaviour of a breeding population of the Barn Swallow(Hirundo rustica)in Zhanjiang,southern China,a region located in the northern tropics,using light-level geolocators.From 2021 to 2023,we deployed geolocators on 92 breeding swallows and retrieved geolocators successfully from 23 individuals.These swallows all exhibited migratory behaviour,and wintering on various islands in Southeast Asia.They displayed sex differences in their wintering locations.All males concentrated in Borneo,while females primarily chose Borneo but also dispersed to the Philippines,South China Sea,and Vietnam for wintering.The studied swallow population adopted a seasonal migration pattern of“indirect in autumn,direct in spring”,bypassing the ecological barrier of the South China Sea in autumn and tending to directly cross it in spring migration.Moreover,the distance and duration of autumn migration was significantly longer than those of the spring migration.Compared to temperate Barn Swallows,the Barn Swallow population breeding in Zhanjiang adopts a pattern of“intra-tropical migration”and initiates autumn migration earlier.The formation of their migration pattern may be limited by ecological and physiological factors.

M1磁珠富集联合重组酶介导的聚合酶链式反应技术检测肺炎克雷伯菌

一直以来,人类健康都在承受着病原微生不同程度的威胁,其中肺炎克雷伯菌是常见的条件致病菌之一,当机体免疫力低下时,容易发生炎性病变,从而引起肺炎、尿路感染和败血症等院内感染。综合分析肺炎克雷伯菌的致病特征,认为快速、准确地从患者血液中检出病原菌,对感染患者进行及时的治疗具有重要意义。方法 传统病原微生物的检测有培养法、免疫检测或者生化鉴定等方法,随着分子生物学技术不断发展,使病原微生物的快速和灵敏检测成为了可能,结合我们新型的聚合酶链式反应技术,产生新的实验方法,探讨分析M1磁珠富集联合重组酶介导的聚合酶链式反应技术检测的可行性以及临床样本中病原菌核酸的最优提取方法。结果 在已经建立的PCR方法中的引物作为内引物的基础上,根据RAA的引物设计原则设计RAA反应过程的外引物,筛选出最优引物对,建立RAP的方法和检测技术,预期核酸扩增特异性达到100%,检测下限达到10CFU/mL。结论 分析肺炎克雷伯菌的病原学特征、基因的特点,建立了这套灵敏度高、特异性强、反应迅速可靠的M1磁珠富集联合重组酶介导的聚合酶链式反应技术,使得检测血液样本中的肺炎克雷伯菌更具特异性,有助于发现早期细菌感染患者并给予其及时的治疗,为今后肺炎克雷伯菌的准确诊断提供了新的选择。

A Tutorial Review of the Solar Power Curve: Regressions, Model Chains, and Their Hybridization and Probabilistic Extensions

Owing to the persisting hype in pushing toward global carbon neutrality,the study scope of atmospheric science is rapidly expanding.Among numerous trending topics,energy meteorology has been attracting the most attention hitherto.One essential skill of solar energy meteorologists is solar power curve modeling,which seeks to map irradiance and auxiliary weather variables to solar power,by statistical and/or physical means.In this regard,this tutorial review aims to deliver a complete overview of those fundamental scientific and engineering principles pertaining to the solar power curve.Solar power curves can be modeled in two primary ways,one of regression and the other of model chain.Both classes of modeling approaches,alongside their hybridization and probabilistic extensions,which allow accuracy improvement and uncertainty quantification,are scrutinized and contrasted thoroughly in this review.

Research on Alliance Decision of Dual-Channel Remanufacturing Supply Chain Considering Bidirectional Free-Riding and Cost-Sharing

This study delves into the formation dynamics of alliances within a closed-loop supply chain(CLSC)that encom-passes a manufacturer,a retailer,and an e-commerce platform.It leverages Stackelberg game for this exploration,contrasting the equilibrium outcomes of a non-alliance model with those of three differentiated alliance models.The non-alliance model acts as a crucial benchmark,enabling the evaluation of the motivations for various supply chain entities to engage in alliance formations.Our analysis is centered on identifying the most effective alliance strategies and establishing a coordination within these partnerships.We thoroughly investigate the consequences of diverse alliance behaviors,bidirectional free-riding and cost-sharing,and the resultant effects on the optimal decision-making among supply chain actors.The findings underscore several pivotal insights:(1)The behavior of alliances within the supply chain exerts variable impacts on the optimal pricing and demand of its members.In comparison to the non-alliance(D)model,the manufacturer-retailer(MR)and manufacturer-e-commerce platform(ME)alliances significantly lower both offline and online resale prices for new and remanufactured goods.This adjustment leads to an enhanced demand for products via the MR alliance’s offline outlets and the ME alliance’s online platforms,thereby augmenting the profits for those within the alliance.Conversely,retailer-e-commerce platform(ER)alliance tends to increase the optimal retail price and demand across both online and offline channels.Under specific conditions,alliance behavior can also increase the profits of non-alliance members,and the profits derived through alliance channels also exceed those from non-alliance channels.(2)The prevalence of bidirectional free-riding behavior largely remains constant across different alliance configurations.Across these models,bidirectional free-riding typically elevates the equilibrium prices in offline channel while negatively affecting the equilibrium prices in other channel.(3)The effect of cost-sharing shows relative uniformity across the various alliance models.Across all configurations,cost-sharing tends to reduce the manufacturer’s profits.Nonetheless,alliances initiated by the manufacturer can counteract these negative impacts,providing a strategic pathway to bolster CLSC profitability.

Application of Stork Optimization Algorithm for Solving Sustainable Lot Size Optimization

The efficiency of businesses is often hindered by the challenges encountered in traditional Supply Chain Manage-ment(SCM),which is characterized by elevated risks due to inadequate accountability and transparency.To address these challenges and improve operations in green manufacturing,optimization algorithms play a crucial role in supporting decision-making processes.In this study,we propose a solution to the green lot size optimization issue by leveraging bio-inspired algorithms,notably the Stork Optimization Algorithm(SOA).The SOA draws inspiration from the hunting and winter migration strategies employed by storks in nature.The theoretical framework of SOA is elaborated and mathematically modeled through two distinct phases:exploration,based on migration simulation,and exploitation,based on hunting strategy simulation.To tackle the green lot size optimization issue,our methodology involved gathering real-world data,which was then transformed into a simplified function with multiple constraints aimed at optimizing total costs and minimizing CO_(2) emissions.This function served as input for the SOA model.Subsequently,the SOA model was applied to identify the optimal lot size that strikes a balance between cost-effectiveness and sustainability.Through extensive experimentation,we compared the performance of SOA with twelve established metaheuristic algorithms,consistently demonstrating that SOA outperformed the others.This study’s contribution lies in providing an effective solution to the sustainable lot-size optimization dilemma,thereby reducing environmental impact and enhancing supply chain efficiency.The simulation findings underscore that SOA consistently achieves superior outcomes compared to existing optimization methodologies,making it a promising approach for green manufacturing and sustainable supply chain management.

A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

The diversity of data sources resulted in seeking effective manipulation and dissemination.The challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of computing.One of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search task.This research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO performance.On the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain performance.The proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant features.To confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve Bayes.Moreover,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different datasets.The proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

Transforming liquid flow fuel cells to controllable reactors for highlyefficient oxidation of 5-hydroxymethylfurfural to 2, 5-furandicarboxylic acid at low temperature

Highly-efficient oxidation of 5-hydroxymethylfurtural(HMF) to 2,5-furandicarboxylic acid(FDCA) at low temperature with air as the oxidant is still challenging.Herein,inspired by the respirato ry electron transport chain(ETC) of living cells mediated by electron carriers,we constructed artificial ETCs and transformed liquid flow fuel cells(LFFCs) to flexible reactors for efficient oxidation of HMF to produce FDCA under mild conditions.This LFFC reactor employed an electrodeposition modified nickel foam as an anode to promote HMF oxidation and(VO_(2))_(2)SO_(4) as a cathode electron carrier to facilitate the electron transfer to air.The reaction rate could be easily controlled by selecting the anode catalyst,adjusting the external loading and changing the cathodic electron carrier or oxidants.A maximal power density of 44.9 mW cm^(-2) at room temperature was achieved,while for FDCA production,short-circuit condition was preferred to achieve quick transfer of electrons.For a single batch operation with 0.1 M initial HMF,FDCA yield reached 97.1%.By fed-batch operation,FDCA concentration reached 144.5 g L^(-1) with a total yield of 96%.Ni^(2+)/Ni^(3+) redox couple was the active species mediating the electron transfer,while both experimental and DFT calculation results indicated that HMFCA pathway was the preferred reaction mechanism.

Durable poly(binaphthyl-co-p-terphenyl piperidinium)-based anion exchange membranes with dual side chains

Building well-developed ion-conductive highways is highly desirable for anion exchange membranes(AEMs).Grafting side chain is a highly effective approach for constructing a well-defined phaseseparated morphological structure and forming unblocked ion pathways in AEMs for fast ion transport.Fluorination of side chains can further enhance phase separation due to the superhydrophobic nature of fluorine groups.However,their electronic effect on the alkaline stability of side chains and membranes is rarely reported.Here,fluorine-containing and fluorine-free side chains are introduced into the polyaromatic backbone in proper configuration to investigate the impact of the fluorine terminal group on the stability of the side chains and membrane properties.The poly(binaphthyl-co-p-terphenyl piperidinium)AEM(QBNp TP)has the highest molecular weight and most dimensional stability due to its favorable backbone arrangement among ortho-and meta-terphenyl based AEMs.Importantly,by introducing both a fluorinated piperidinium side chain and a hexane chain into the p-terphenyl-based backbone,the prepared AEM(QBNp TP-QFC)presents an enhanced conductivity(150.6 m S cm^(-1))and a constrained swelling at 80℃.The electronic effect of fluorinated side chains is contemplated by experiments and simulations.The results demonstrate that the presence of strong electro-withdrawing fluorine groups weakens the electronic cloud of adjacent C atoms,increasing OH^(-)attack on the C atom and improving the stability of piperidinium cations.Hence QBNp TP-QFC possesses a robust alkaline stability at 80℃(95.3%conductivity retention after testing in 2 M Na OH for 2160 h).An excellent peak power density of 1.44 W cm^(-2)and a remarkable durability at 80℃(4.5%voltage loss after 100 h)can be observed.

Lactobacillus plantarum CCFM1180 attenuates obesity induced by estrogen deficiency by activating estrogen receptor alpha in abdominal adipose tissue and regulating gut microbiota-derived metabolites

Lipid metabolism disorders commonly occur during menopause.Estrogen deficiency has been shown to lead to excessive energy intake and abnormal lipid metabolism in ovariectomized rats,resulting in obesity.Probiotics exhibit anti-obesity properties,and their underlying mechanism has been widely reported.In this study,we demonstrated the metabolic benefits of Lactobacillus plantarum CCFM1180 in suppressing appetite,controlling body weight,correcting obesity-induced abnormalities,enhancing liver lipid metabolism,and protecting liver function in estrogen-deficient rats.The mechanisms associated with the anti-obesity and anti-dyslipidemia effects of CCFM1180 on estrogen-deficient rats were clarified.The results showed that CCFM1180 dramatically reduced food intake by activating the expression of estrogen receptor alpha(ERα)and increasing the level of leptin in abdominal adipose tissue.These changes,combined with the increased butyrate concentration and recovered bile acid structure,helped enhance lipid metabolism.Additionally,CCFM1180 treatment was found to be safer than exogenous estrogen supplementation.Thus,L.plantarum CCFM1180 could be considered a new therapeutic strategy for preventing and alleviating menopausal lipid abnormalities.