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.

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.

Non-flammable long chain phosphate ester based electrolyte via competitive solventized structures for high-performance lithium metal batteries

Safety remains a persistent challenge for high-energy-density lithium metal batteries(LMBs).The development of safe and non-flammable electrolytes is especially important in harsh conditions such as high temperatures.Herein,a flame-retardant,low-cost and thermally stable long chain phosphate ester based(tributyl phosphate,TBP)electrolyte is reported,which can effectively enhance the cycling stability of highly loaded high-nickel LMBs with high safety through co-solvation strategy.The interfacial compatibility between TBP and electrode is effectively improved using a short-chain ether(glycol dimethyl ether,DME),and a specially competitive solvation structure is further constructed using lithium borate difluorooxalate(LiDFOB)to form the stable and inorganic-rich electrode interphases.Benefiting from the presence of the cathode electrolyte interphase(CEI)and solid electrolyte interphase(SEI)enriched with LiF and Li_(x)PO_(y)F_(z),the electrolyte demonstrates excellent cycling stability assembled using a 50μm lithium foil anode in combination with a high loading NMC811(15.4 mg cm^(-2))cathode,with 88%capacity retention after 120 cycles.Furthermore,the electrolyte exhibits excellent high-temperature characteristics when used in a 1-Ah pouch cell(N/P=0.26),and higher thermal runaway temperature(238℃)in the ARC(accelerating rate calorimeter)demonstrating high safety.This novel electrolyte adopts long-chain phosphate as the main solvent for the first time,and would provide a new idea for the development of extremely high safety and high-temperature electrolytes.

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.

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.

Alkyl chain modulation of asymmetric hexacyclic fused acceptor synergistically with wide bandgap third component for high efficiency ternary organic solar cells

Herein,two asymmetric hexacyclic fused small molecule acceptors(SMAs),namely BP4F-HU and BP4F-UU,were synthesized.The elongated outside chains in the BP4F-UU molecule played a crucial role in optimizing the morphology of blend film,thereby improving charge mobility and reducing energy loss within the corresponding film.Notably,the PM6:BP4F-UU device exhibited a higher open-circuit voltage(V_(oc))of 0.878 V compared to the PM6:BP4F-HU device with a V_(oc)of 0.863 V.Further,a new wide bandgap SMA named BTP-TA was designed and synthesized as the third component to the PM6:BP4F-UU host binary devices,which showed an ideal complementary absorption spectrum in PM6:BP4F-UU system.In addition,BTP-TA can achieve efficient intermolecular energy transfer to BP4F-UU by fluorescence resonance energy transfer(FRET)pathway,due to the good overlap between the photoluminescence(PL)spectrum of BTP-TA and the absorption region of BP4F-UU.Consequently,ternary devices with 15wt%BTP-TA exhibits broader photon utilization,optimal blend morphology,and reduced charge recombination compared to the corresponding binary devices.Consequently,PM6:BP4F-UU:BTP-TA ternary device achieved an optimal power conversion efficiency(PCE)of 17.83%with simultaneously increased V_(oc)of 0.905 V,short-circuit current density(J_(sc))of 26.14 mA/cm^(2),and fill factor(FF)of 75.38%.

Earthquake disaster chain model based on complex networks for urban engineering systems

According to news reports on severe earthquakes since 2008,a total of 51 cases with magnitudes of 6.0 or above were analyzed,and 14 frequently occurring secondary disasters were identified.A disaster chain model was developed using principles from complex network theory.The vulnerability and risk level of each edge in this model were calculated,and high-risk edges and disaster chains were identified.The analysis reveals that the edge“floods→building collapses”has the highest vulnerability.Implementing measures to mitigate this edge is crucial for delaying the spread of secondary disasters.The highest risk is associated with the edge“building collapses→casualties,”and increased risks are also identified for chains such as“earthquake→building collapses→casualties,”“earthquake→landslides and debris flows→dammed lakes,”and“dammed lakes→floods→building collapses.”Following an earthquake,the prompt implementation of measures is crucial to effectively disrupt these chains and minimize the damage from secondary disasters.

Model-driven full system dynamics estimation of PMSM-driven chain shell magazine

Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is proposed to estimate the unmeasured states and disturbance, in which the model parameters are adjusted in real time. Theoretical analysis shows that the estimation errors of the disturbances and unmeasured states converge exponentially to zero, and the parameter estimation error can be obtained from the extended state. Then, based on the extended state of the AESO, a novel parameter estimation law is designed. Due to the convergence of AESO, the novel parameter estimation law is insensitive to controllers and excitation signal. Under persistent excitation(PE) condition, the estimated parameters will converge to a compact set around the actual parameter value. Without PE signal, the estimated parameters will converge to zero for the extended state. Simulation and experimental results show that the proposed method can accurately estimate the unmeasured states and disturbance of the chain shell magazine, and the estimated parameters will converge to the actual value without strictly continuous PE signals.

Service Function Chain Deployment Algorithm Based on Multi-Agent Deep Reinforcement Learning

Aiming at the rapid growth of network services,which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain(SFC)under 5G networks,this paper proposes a multi-agent deep deterministic policy gradient optimization algorithm for SFC deployment(MADDPG-SD).Initially,an optimization model is devised to enhance the request acceptance rate,minimizing the latency and deploying the cost SFC is constructed for the network resource-constrained case.Subsequently,we model the dynamic problem as a Markov decision process(MDP),facilitating adaptation to the evolving states of network resources.Finally,by allocating SFCs to different agents and adopting a collaborative deployment strategy,each agent aims to maximize the request acceptance rate or minimize latency and costs.These agents learn strategies from historical data of virtual network functions in SFCs to guide server node selection,and achieve approximately optimal SFC deployment strategies through a cooperative framework of centralized training and distributed execution.Experimental simulation results indicate that the proposed method,while simultaneously meeting performance requirements and resource capacity constraints,has effectively increased the acceptance rate of requests compared to the comparative algorithms,reducing the end-to-end latency by 4.942%and the deployment cost by 8.045%.

Hepatomegaly and jaundice as the presenting symptoms of systemic light-chain amyloidosis: A case report

BACKGROUND Light chain(AL)amyloidosis is a plasma cell dyscrasia characterized by the pathologic production and extracellular tissue deposition of fibrillar proteins derived from immunoglobulin AL fragments secreted by a clone of plasma cells,which leads to progressive dysfunction of the affected organs.The two most commonly affected organs are the heart and kidneys,and liver is rarely the dominant affected organ with only 3.9%of cases,making them prone to misdia-gnosis and missed diagnosis.CASE SUMMARY A 65-year-old woman was admitted with a 3-mo history of progressive jaundice and marked hepatomegaly.Initially,based on enhanced computed tomography scan and angiography,Budd-Chiari syndrome was considered and balloon dilatation of significant hepatic vein stenoses was performed.However,addi-tional diagnostic procedures,including liver biopsy and bone marrow-exami-nation,revealed immunoglobulin kapa AL amyloidosis with extensive liver involvement and hepatic vascular compression.The disease course was progre-ssive and fatal,and the patient eventually died 5 mo after initial presentation of symptoms.CONCLUSION AL amyloidosis with isolated liver involvement is very rare,and can be easily misdiagnosed as a vascular disease.

Nonlinear wave dispersion in monoatomic chains with lumped and distributed masses:discrete and continuum models

The main objective of this paper is to investigate the influence of inertia of nonlinear springs on the dispersion behavior of discrete monoatomic chains with lumped and distributed masses.The developed model can represent the wave propagation problem in a non-homogeneous material consisting of heavy inclusions embedded in a matrix.The inclusions are idealized by lumped masses,and the matrix between adjacent inclusions is modeled by a nonlinear spring with distributed masses.Additionally,the model is capable of depicting the wave propagation in bi-material bars,wherein the first material is represented by a rigid particle and the second one is represented by a nonlinear spring with distributed masses.The discrete model of the nonlinear monoatomic chain with lumped and distributed masses is first considered,and a closed-form expression of the dispersion relation is obtained by the second-order Lindstedt-Poincare method(LPM).Next,a continuum model for the nonlinear monoatomic chain is derived directly from its discrete lattice model by a suitable continualization technique.The subsequent use of the second-order method of multiple scales(MMS)facilitates the derivation of the corresponding nonlinear dispersion relation in a closed form.The novelties of the present study consist of(i)considering the inertia of nonlinear springs on the dispersion behavior of the discrete mass-spring chains;(ii)developing the second-order LPM for the wave propagation in the discrete chains;and(iii)deriving a continuum model for the nonlinear monoatomic chains with lumped and distributed masses.Finally,a parametric study is conducted to examine the effects of the design parameters and the distributed spring mass on the nonlinear dispersion relations and phase velocities obtained from both the discrete and continuum models.These parameters include the ratio of the spring mass to the lumped mass,the nonlinear stiffness coefficient of the spring,and the wave amplitude.

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Cyber-physical power system(CPPS)has significantly improved the operational efficiency of power systems.However,cross-space cascading failures may occur due to the coupling characteristics,which poses a great threat to the safety and reliability of CPPS,and there is an acute need to reduce the probability of these failures.Towards this end,this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services.On this basis,a joint improved risk-balanced service function chain routing strategy(SFC-RS)is proposed,which is modeled as a robust optimization problem and solved by column-and-constraint generation(C-CG)algorithm.Compared with the traditional shortest-path routing algorithm,the superiority of SFC-RS is verified in the IEEE 30-bus system.The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network,enhances information transmission accessibility,and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

Service Function Chain Migration in LEO Satellite Networks

With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)satellite networks.While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites,the static SFC placement schemes may cause performance degradation,resource waste and even service failure.In this paper,we consider migration and establish an online migration model,especially considering the dynamic topology.Given the scarcity of bandwidth resources,the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible.Due to its NP-hardness,we propose a heuristic minimized dynamic SFC migration(MDSM)algorithm that only triggers the migration procedure when new SFCs are rejected.Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.

Periorbital purpura can be the only initial symptom of primary light chain amyloidosis:A case report

BACKGROUND Primary light chain amyloidosis is a rare and complex disease with complex clinical features and is highly susceptible to misdiagnosis and underdiagnosis in the early stages.CASE SUMMARY We report a case of a 47-year-old female patient whose only initial symptom was periorbital purpura,which was not taken seriously enough.As the disease progressed,pleural effusion gradually appeared,and after systematic diagnosis and treatment,she was diagnosed with“primary light chain amyloidosis”.She achieved rapid hematological remission after treatment with a daratumumab+bortezomib+cyclophosphamide+dexamethasone regimen.CONCLUSION Periorbital purpura can be the only initial symptom of primary light chain amyloidosis;we should pay attention to the cases where the initial clinical symptoms are only periorbital purpura.

The Effect of Procrastination on Physical Exercise among College Students—The Chain Effect of Exercise Commitment and Action Control

Background:Exercise procrastination is prevalent among college students,causing decline in physical fitness.It is imperative to investigate the mechanism affecting college students’physical activity behaviors.This study was aimed at investigating the effect of procrastination on college students’physical exercise behavior,and the chain mediation effects of exercise commitment and action control(AC),to provide a theoretical basis for interventions targeting physical exercise behavior among college students.Methods:A questionnaire survey was conducted using convenience sampling.The General Procrastination Scale,Exercise Commitment Scale,Action Control Scale,and Physical Activity Rating Scale-3 questionnaires were used.Participants were 581 college students(age 19.27±0.94 years;243 males and 338 females).Statistical methods of regression analysis and structural equation modeling(SEM)were applied.Results:Procrastination,exercise commitment,and action control were found to be significant predictors of physical exercise behavior.Among these predictors,exercise commitment and action control showed full mediation effects in the relationship between procrastination and physical exercise behavior,and explained 25.48%and 30.77%of the total variance,respectively.The chain mediation effect of exercise commitment-action control was significant,accounting for 22.60%of the total variance,and the total indirect effect was 79.33%.Conclusion:Therefore,higher procrastination was associated with less participation in physical exercise behavior among college students.Improvements in exercise commitment and volitional decision-making ability for physical exercise behavior promoted physical exercise behavior,and increased exercise commitment promoted volitional decision-making ability among the students.The chain reaction effect of exercise commitment and action control also buffered the negative effects of procrastination on physical exercise behavior,thereby increasing physical exercise behavior among college students.

Establishment of Regional Green Innovation Value Chains:A Case Study on Tackling the Impeded Diffusion of Green Products

The green innovation value chain is a key step in transforming green,innovative scientific,and technological achievements into productive forces.The establishment of green innovation value chains based on value distribution rather than technical conditions can effectively overcome the common bottleneck faced by different nations during their green innovation endeavors,namely,the substitution of conventional products with green alternatives.This study investigates the impeded diffusion of green products and their underlying causes,analyzes the internal structure and mechanism of the green innovation value chain,and explores the establishment of regional green innovation value chains and the models available for value chain upgrading.

Production Chain Length and PPI-CPI Divergence:Analysis Based on the Global Input-output Price Model

Productivity and international energy price shocks are reflected in PPI and CPI via industrial chains.China’s in-depth participation into the global value chains has increasingly lengthened its industrial production chains.The question is how the changing length of production chains will affect CPI and PPI,as well as CPI-PPI correlation?By constructing a global input-output price model,this paper offers a theoretical discussion on the impact of production chain length on the CPI-PPI divergence.Our findings suggest that the price shock of international bulk commodities has a greater impact on China’s PPI than that on CPI.The effects on both China’s PPI and CPI estimated by using the single-country input-output model are higher than the results estimated with the global input-output model.However,the difference between CPI and PPI variations estimated with the global input-output model is greater than the result estimated with the single-country input-output model,which supports the view that the lengthening of production chains,especially international production chains,leads to a divergence between CPI and PPI.Empirical results based on cross-national panel data also suggest that the lengthening of production chains has reduced the CPI-PPI correlation for countries,i.e.the lengthening of production chains has increased the PPI-CPI divergence.That is to say,policymakers should target not just CPI in maintaining price stability,but instead focus on the stability of both PPI and CPI.Efforts can be made to proactively adjust the price index system,and formulate the industrial chain price index.

Global Industrial and Supply Chain Restructuring:Background,Characteristics and Development Trends

The restructuring of global industrial and supply chains is a hot issue in today’s world,and as a result of the once-in-a-century changes and intensified geopolitical and economic competition,the demand for global industrial and supply chain security has risen sharply,with government departments and transnational corporations(TNCs)becoming the most critical stakeholders.Governments carefully calibrate industrial and trade policies from the perspective of national strategies to create industrial chains that support national competitive advantages,and multinational corporations respond to geopolitical risks by prioritizing industrial and supply chain security and sustainability over capital and efficiency.Against the backdrop of changes unseen in a century,decelerating globalization and global economic downturn,the characteristics and future trends of global industrial and supply chain restructuring are worth paying attention to.

Supply Chain Cooperation between China and ASEAN:A Top-Down Approach

The significant relocation of supply chains from China to ASEAN countries did not start with the pandemic.China has been steadily increasing its investment in ASEAN's low valueadded manufacturing sector due to the region's comparative advantage in labor costs.In recent years,changing geopolitics and the restructuring of regional economies in the Asia-Pacific region have accelerated this relocation.