Chain Fluctuations Research Articles

Intelligent building construction cost optimization and prediction by integrating BIM and elman neural network

This study aims to address the challenges of capturing design changes, supply chain fluctuations, and labor cost variations to improve the accuracy and real-time nature of intelligent building construction cost predictions. It seeks to accurately forecast and optimize project costs. The study innovatively constructs an intelligent building construction cost prediction model based on Building Information Modeling (BIM) and Elman neural networks (ENNs), denoted as the BIM-ENN model. The BIM-ENN model first introduces BIM technology to digitize and visualize information related to building structures, electromechanical systems, and pipelines. The digitized data obtained through BIM technology is then used as input data for the ENN, which optimizes the neural network parameters to predict and optimize intelligent building construction costs. Finally, the BIM-ENN model is experimentally evaluated. The results demonstrate that the prediction value of the construction cost of the intelligent building by this model closely matches the original information price, with a prediction accuracy of 95.83 %. Compared with the single ENN, the root mean squared error of the BIM-ENN model is less than 75, and the determination coefficient is above 0.95. This indicates that this model can explain more than 95 % of the construction cost prediction results, making it a feasible solution for actual prediction problems and achieving satisfactory results. The intelligent building construction cost prediction model reported here exhibits high accuracy and reliability. It can successfully forecast construction costs, providing robust decision support for the digitalization and intelligent development of construction enterprises. The practical significance of this study lies in providing the construction industry with an accurate cost management tool that helps enterprises optimize budget control and resource allocation, enhancing risk assessment and management capabilities. Moreover, the potential impact of the BIM-ENN model is its ability to elevate prediction standards within the construction industry, promote technological integration and innovation, enhance enterprise competitiveness, and drive the industry's transition towards digitalization and intelligent sustainable development.

Supply responsive scheduling for ethylene cracking furnace systems based on deep reinforcement learning

AbstractEthylene is one of the most important chemicals, and scheduling optimization is crucial for the profitability of ethylene cracking furnace systems. With the diversification of feedstocks and the high variability in prices, supply chain fluctuations pose significant challenges to the scheduling decisions. Dynamically responding to these fluctuations has become crucial. Traditional mixed integer nonlinear programming (MINLP) models lack the capability of supply chain response, while receding horizon optimization (RHO) models require parameter prediction and repeated optimization solving. To address this challenge, we propose a deep reinforcement learning‐based framework that includes an ethylene dynamic scheduling environment and a decision agent based on deep Q‐network. Across three test cases, compared to the MINLP and RHO models, this framework significantly minimizes losses caused by supply chain fluctuations, thereby increasing daily average net profits by 9%–27%, demonstrating its significant potential for application in responsive scheduling in the presence of supply chain fluctuations.

Emissions and Fluctuations in Global Value Chains: Cross-country and Industry-level Evidence

Purpose - This paper explores how global value chain (GVC) participation affects the comovement between real industrial value-added and emissions over business cycles. Design/Methodology - We follow de Soyres and Gaillard (2022) and Wang et al. (2022), first measuring the forward and backward links in GVC activities at the country and industry levels. Specifically, we examine both Simple and Complex GVC activities by considering the inclusion of indirect transactions through third countries. Second, we conduct a panel analysis on the covariation between value-added and emissions during economic f luctuations and the relationship with GVC participation rates. Findings - We find that the increase in participation rates in forward-link GVC activities enhances the covariation between economic fluctuations and emissions, whereas the effects of the change in participation rates in backward-link GVC activities are statistically insignificant. In contrast to EU members, this pattern is reversed in countries that depend largely on energy trade from a global perspective, such as the United States, Russia, Korea, and Japan. Originality/value - We contribute by quantitatively presenting the covariation of economic fluctuations and emissions within GVC activities, going beyond existing literature that predominantly explores growth, the environment, and trade. Our contrasting results among country groups indicate that as countries worldwide pursue carbon neutrality, the divergence in positions among countries based on their dependence on energy trade may intensify the likelihood of trade disputes.

Structural and Computational Insights into Dynamics and Intermediate States of Orexin 2 Receptor Signaling.

Orexin 2 receptor (OX2R) is a G protein-coupled receptor (GPCR) whose activation is crucial to regulation of the sleep-wake cycle. Recently, inactive and active state structures were determined from X-ray crystallography and cryo-electron microscopy single particle analysis, and the activation mechanisms have been discussed based on these static data. GPCRs have multiscale intermediate states during activation, and insights into these dynamics and intermediate states may aid the precise control of intracellular signaling by ligands in drug discovery. Molecular dynamics (MD) simulations are used to investigate dynamics induced in response to thermal perturbations, such as structural fluctuations of main and side chains. In this study, we proposed collective motions of the TM domain during activation by performing 30 independent microsecond-scale MD simulations for various OX2R systems and applying relaxation mode analysis. The analysis results suggested that TM3 had a vertical structural movement relative to the membrane surface during activation. In addition, we extracted three characteristic amino acid residues on TM3, i.e., Q1343.32, V1423.40, and R1523.50, which exhibited large conformational fluctuations. We quantitatively evaluated the changes in their equilibrium during activation in relation to the movement of TM3. We also discuss the regulation of ligand binding recognition and intracellular signal selectivity by changes in the equilibrium of Q1343.32 and R1523.50, respectively, according to MD simulations and GPCR database. Additionally, the OX2R-Gi signaling complex is stabilized in the conformation resembling a non-canonical (NC) state, which was previously proposed as an intermediate state during activation of neurotensin 1 receptor. Insights into the dynamics and intermediate states during activation gained from this study may be useful for developing biased agonists for OX2R.

Mutant anaplastic lymphoma kinase inhibitor identification by integrated in silico approaches

ABSTRACT Non-small-cell lung cancer (NSCLC) is the primary form of lung cancer globally and remains a leading cause of mortality. Anaplastic lymphoma kinase (ALK) mutations, such as I1171N + L1198H, have been discovered to confer resistance to current ALK inhibitors, reducing their therapeutic effectiveness. Addressing drug resistance necessitates exploring selective inhibitors for innovative therapeutic approaches. In this study, a structure-based pharmacophore model, using ALK-approved inhibitors, was developed to screen an In-house database for potential mutant ALK inhibitors. Compounds with requisite pharmacophoric features were evaluated for binding potential against the I1171N + L1198H ALK mutant phenotype. Selected hits underwent assessment for chemical reactivity, and dynamics stability. The study identified five chemical scaffolds (NS1-5) with favorable binding modes and pharmacokinetic properties. The conformational ensembles featured the average RMSD values, ranging from 0.4 to 0.6 nm. RMSF analysis revealed consistent side chain fluctuations with reduced flexibility, while Rog analysis indicated convergence of most complexes. NS1 and NS5, in particular emerged as promising candidates, exhibiting remarkable performance than others, with binding free energies of −210.12 ± 9.94 and −163.68 ± 11.14 kcal/mol, respectively. These findings thus suggest further exploration and optimisation of NS1 and NS5 for mutant ALK inhibitors for the treatment of NSCLC.

Collagen Networks under Indentation and Compression Behave Like Cellular Solids.

Simple synthetic and natural hydrogels can be formulated to have elastic moduli that match biological tissues, leading to their widespread application as model systems for tissue engineering, medical device development, and drug delivery vehicles. However, two different hydrogels having the same elastic modulus but differing in microstructure or nanostructure can exhibit drastically different mechanical responses, including their poroelasticity, lubricity, and load bearing capabilities. Here, we investigate the mechanical response of collagen-1 networks to local and bulk compressive loads. We compare these results to the behavior of polyacrylamide, a fundamentally different class of hydrogel network consisting of flexible polymer chains. We find that the high bending rigidity of collagen fibers, which suppresses entropic bending fluctuations and osmotic pressure, facilitates the bulk compression of collagen networks under infinitesimal applied stress. These results are fundamentally different from the behavior of flexible polymer networks in which the entropic thermal fluctuations of the polymer chains result in an osmotic pressure that must first be overcome before bulk compression can occur. Furthermore, we observe minimal transverse strain during the axial loading of collagen networks, a behavior reminiscent of open-celled cellular solids. Inspired by these results, we applied mechanical models of cellular solids to predict the elastic moduli of the collagen networks and found agreement with the moduli values measured through contact indentation. Collectively, these results suggest that unlike flexible polymer networks that are often considered incompressible, collagen hydrogels behave like rigid porous solids that volumetrically compress and expel water rather than spreading laterally under applied normal loads.

A Fluorescent Probe for C24 Fatty Acids to Report the Deep Interior of Lipid Bilayers

AbstractTo investigate the interdigitation and the resulting fluctuation of lipid chains in the deep part of biomembranes, we aimed to develop a new fluorescent probe based on the well-known trans-parinaric acid (t-PA), but with a tetraene near the end of the C24 chain. The probe, tetracosa-16,18,20,22-tetraenoic acid (TCTEA), synthesized mainly by means of reported strategies, was found to better reflect the behavior of lipids in the deeper interior of bilayers than did t-PA. TCTEA could serve as a useful probe for studying the plasma-membrane dynamics of very-long-chain fatty acids, which have recently elicited significant attention in relation to necroptosis.

Rice and paddy industry in Malaysia: governance and policies, research trends, technology adoption and resilience

Rice is an important staple food for nearly half the world’s population. In Malaysia, rice and paddy cultivation kickstarted in the early 60s with small-scale farming, which later expanded by leaps and bounds before emerging as the country’s utmost important food crop. Over the decades, Malaysian rice production system has been suffering from various challenges which include extreme weather conditions, poor soil fertility and nutrient management, farmers’ lack of awareness and knowledge, hesitancy against genetically-modified planting materials and poor deployment of technology. The national rice production and consumption, simply measured as self-sufficiency status staggers in between 67 and 70%. The Southeast Asia region has been an important rice export trader with Thailand, Vietnam and Cambodia, among the biggest rice-producing nations. Food security, under the context of sustaining international rice trading ties, succumbs to functional fluctuations of global supply chains. During the unprecedented COVID-19 pandemic, the containment period during the outbreak led to significant disruptions to the food production chain. During the early phase of the pandemic, Malaysia experienced a volatile rice import trend, facing difficulty to secure a committed rice trading partner. In this review, we discuss the trajectory of the rice and paddy industry in Malaysia since its inception, lab-to-field translated breeding strategies adopted for rice yield improvement, governmental participation and contribution (approaches, policies and programs) and technologies in use for rice production. Further, relevant cutting-edge technologies, agricultural methods and practices catered for modern Malaysian rice farming, with opportunities to improve and enhance crop health and resilience are included. The review findings inform new rice agricultural practices, suggest research directions toward sustainable rice farming and provide a comprehensive knowledge base to accelerate innovation, technology diffusion and technology adoption for a resilient rice production system in Malaysia.

Biomass use and its implications for bioeconomy development: A resource efficiency perspective for the European countries

Increasing population and economic growth in Europe and the world are leading to growing demand for food, livestock feed, and energy, and consequently to growing negative impacts on the environment and climate change. Tensions and price fluctuations in international material supply chains have recently become an even greater challenge. As for biomass, its availability is limited due to land, water, human, and financial resources as well as the environmental boundaries. Therefore, efficiency of biomass use is becoming increasingly important; it is crucial to develop and apply integrated assessment frameworks for tracking progress in resource use efficiency that would allow comparing the efficiency of biomass and non-biomass use. This paper embarks on the analysis of biomass and non-biomass resource use in selected European countries over 2010–2019. The index decomposition analysis model is set up to decompose the changes in biomass consumption with respect to intensive and extensive drivers. Resource use efficiency is then assessed via the non-parametric frontier, taking into account the other inputs (labour and capital). The results suggest that biomass efficiency is higher than that of non-biomass materials. The efficiency scores suggest that further decoupling of domestic material consumption and economic growth is needed.

Rapid cold sterilization of 3D printed surgical instruments for the austere environment

IntroductionMedical operations are vulnerable to global supply chain fluctuations. The ability to locally produce and reliably sterilize medical equipment may mitigate this risk. This project developed a reliable high-level disinfection process for 3D printed surgical tools. MethodsSurgical instruments and consumables were designed and printed from various materials. Devices contaminated with known and unknown bacteria underwent one of three cleaning methods followed by high-level disinfection using submersion in a Cidex OPA Solution. Devices were then cultured on blood agar plates and incubated for 48 h. Positive and negative controls were performed. ResultsThe results of control experiments showed no growth on negative controls and significant growth on all positive control plates. Of the three cleaning methods tested, one showed no growth: cleaning with isopropyl alcohol and chlorhexidine followed by Cidex bath. DiscussionThis project successfully developed a rapid high-level disinfection process for 3D printed surgical instruments made from two different types of 3D printing material.

Receding Horizon Optimization of Ethylene Cracking Operation and Scheduling under Supply Chain Fluctuations

The global supply chain is experiencing ongoing turmoil after COVID-19, which inevitably affects the supply and demand of the chemical industry. Ethylene plants are regarded as one of the most profitable chemical industry chains, and thus, there is a need to track fluctuations in the supply chain and responsively adjust their operations and scheduling decisions to achieve optimal economic benefits. However, previous studies about ethylene cracking optimization are mostly limited to fixed supply chain parameters and cannot meet the need for real-time updates according to supply chain fluctuations. To address this problem, we propose an ethylene cracking optimization framework which combines parameter prediction and receding horizon optimization (predictive RHO) for real-time optimal operation and scheduling under supply chain fluctuations. This optimization framework uses historical supply chain data (supply quantities, feedstock prices, and product prices) to predict future parameters and uses the predicted parameters to optimize the operation and scheduling of ethylene cracking furnace systems in a receding horizon way. Two industrial case studies were used to validate the efficacy of the proposed optimization framework. In case 1, the predictive-RHO framework achieved comparable economic profits of 147,370 and 146,483 $/day without violating daily inventory constraints (vs 151,204 $/day from the original model violating inventory constraints) and a faster calculation speed of 40 s (vs 32 min) under two fluctuating feed supply modes. In case 2, predictive RHO improves economic profits by 1.8% through integrating operations with scheduling and 1.1% by tracking the feed and product price fluctuations. These two cases show the strong capability of predictive RHO in tracking supply chain fluctuations and improving the inventory management level as well as the economic profits of ethylene cracking plants.

COMPARATIVE CHAINS DYNAMICS OF TRIOSEPHOSPHATE ISOMERASE INVESTIGATED BY MOLECULAR DYNAMICS SIMULATION

Triosephosphate isomerase is an enzyme which catalyzes the inter-conversion between glyceraldehyde-3-phosphate and dihydroxyacetone phosphate in the fifth step of the glycolytic pathway. In this study, molecular dynamics simulation technique was employed to investigate the dynamics of the two monomer chains of triosephosphate isomerase of trypanosoma brucei brucei (TbTIM) using GROMACS 2016.04 software. The MD simulation of the x-ray structure of TbTIM was performed using the GROMOS 9643a1 force field and simple point charge water model under isothermal-isobaric condition with periodic boundary conditions imposed on x, y, z directions. The Root Mean Square Deviation (RMSD) Root Mean Square fluctuation (RMSF), Radius of Gyration (ROG), Solvent accessible surface area (SASA) and hydrogen bonds were computed. The RMSD values indicate that chain-B shows transition between two conformational states with higher RMSD value of 0.45 nm when compared to chain-A with RMSD of 0.27 nm. The RMSF values indicates that residues of loop 6 (residues 166 to 177) have the highest fluctuations in both chains compared to other residues with chain-A having higher fluctuations peak. The ROG values of chain-A varies from 1.675 nm to 1.761 nm while that of chain-B varies from 2.480 nm to 2.590 nm implying that chain-A is more compact during the simulation than chain-B. The SASA values indicates that chain-B has more contact with solvent than chain-A. 160 hydrogen bonds were found which indicates the stability of the protein during the simulation. From the RMSD, ROG, SASA values, it is evident that chain-B of triosephosphate isomerase of trypanosoma bruceibrucei displayed greater structural dynamics than chain-A during the MD simulation.

End-to-End Fluctuation of cis-Poly(isoprene) under Constraints from Slow Poly(tert-butyl styrene)

The properties of miscible polymer blends are strongly affected by the dynamic asymmetry of the components reflecting a contrast of their bulk Tg. This study focused on a blend of unentangled polyisoprene (PI3; M = 3.0 kg/mol) and poly(4-tert-butyl)styrene (PtBS27; M = 27.2 kg/mol) with a PI content of wPI = 50 wt % to examine this effect on viscoelastic and dielectric properties. The dielectric loss (ε″) peak characterizing the end-to-end fluctuation of PI chains emerged at an angular frequency ω much higher than that of the terminal viscoelastic relaxation, confirming that PI3 and PtBS27 were the fast and slow components in the blend. At low temperatures T, PI3 exhibited a very broad ε″ peak and its terminal relaxation frequency, much lower than the peak frequency, was close to the Rouse relaxation frequency of PtBS27 over a length scale identical to the end-to-end distance RPI of the PI3 chain. This dielectric relaxation narrowed at higher T, namely, on the reduction of the dynamic asymmetry between PI3 and PtBS27. These observations suggested a molecular scenario that the dynamic concentration heterogeneity of the PtBS chains was essentially frozen during the relaxation of PI3 and the PI3 chains experienced broad distributions in both friction and motional constraints to exhibit broadened and retarded relaxation at low T. This scenario was in harmony with the molecular dynamics simulation in both atomistic and coarse-grained (cg) levels. Specifically, the end-to-end vector autocorrelation function of PI obtained from the cg simulation showed stronger broadening in its higher-order modes, which cannot be attained without the distributions of the friction and motional constraint for PI. This result demonstrated the importance of the dynamic concentration heterogeneity of PtBS giving those distributions during the PI relaxation.

Reaction within the coulomb-cage; science in retrospect

The Coulomb-cage is defined as the space where the electrostatic interaction between two bodies is more intensive than the thermal energy (kBT). For small molecule, the Coulomb-cage is a small sphere, extending only few water molecules towards the bulk and its radius is sensitive to the ionic strength of the solution. For charged proteins or membranal structures, the Coulomb-cage can engulf large fraction of the surface and provides a preferred pathway for ion propagation along the surface. Similarly, electrostatic potential at the inner space of a channel can form preferential trajectories passage for ions. The dynamics of ions inside the Coulomb-cage of ions was formulated by the studies of proton-anion recombination of excited photoacids. In the present article, we recount the study of intra- Coulomb-cage reaction taking place on the surface of macro-molecular bodies like micelles, membranes, proteins and intra-protein cavities. The study progressed stepwise, tracing the dynamics of a proton ejected from a photo-acid molecule located at defined sites (on membrane, inter-membrane space, active site of enzyme, inside Large Pore Channels etc.). Accumulation of experimental observations encouraged us to study of the reaction mechanism by molecular dynamics simulations of ions within the Coulomb-cage of proteins surface or inside large pores. The intra-Coulomb-cage proton transfer events follows closely the fine structure of the electrostatic field inside the cage and reflects the shape of nearby dielectric boundaries, the temporal ordering of the solvent molecules and the structural fluctuations of the charged side chains. The article sums some 40 years of research, which in retrospect clarifies the intra-Coulomb-cage reaction mechanism.

Correlating the Local and Global Dynamics of an Enzyme in the Crowded Milieu.

Enzymes are dynamic biological macromolecules, with their catalytic function(s) being largely influenced by the changes in local fluctuations of amino acid side chains as well as global structural modulations that the enzyme undergoes. Such local and global motions can be highly affected inside the crowded physiological interior of the cell. Here, we have addressed the role of dynamic structural flexibility in affecting the activation energy barrier of a flexible multidomain enzyme adenylate kinase (AK3L1, UniProtKB: Q9UIJ7). Activation energy profiles of both local (at three different sites along the polypeptide backbone) and global dynamics of the enzyme have been monitored using solvation studies on the subnanosecond time scale and tryptophan quenching studies over the temperature range of 278-323 K, respectively, under crowded conditions (Ficoll 70, Dextran 40, Dextran 70, and PEG 8). This study not only provides the site-specific mapping of dynamics but reveals that the activation energies associated with these local motions undergo a significant decrease in the presence of macromolecular crowders, providing new insights into how crowding affects internal protein dynamics. The crowded scenario also aids in enhancing the coupling between the local and global motions of the enzyme. Moreover, select portions/regions of the enzyme when taken together can well mirror the overall dynamics of the biomolecule, showing possible energy hotspots along the polypeptide backbone.

Transition in the Glassy Dynamics of Melts of Acid-Hydrolyzed Phytoglycogen Nanoparticles.

The deformability, responsiveness, and tunability of soft nanoparticles (NPs) offer unique opportunities to learn about their complex properties and the interactions between particles. In the present study, we provide new insights into the physical properties of phytoglycogen (PG) NPs, which are soft, compact particles with a dendritic architecture that are produced in the kernels of sweet corn. In particular, we study PG NPs modified using acid hydrolysis, which not only reduces their diameter but also alters their stiffness, internal structure, and the interactions between particles in aqueous dispersions. We used steady shear rheology to determine the dependence of the relative zero-shear viscosity ηr of aqueous dispersions of acid-hydrolyzed PG NPs on the effective volume fraction ϕeff, which indicated a reduction in stiffness of the particles relative to that of native PG NPs. We quantified this difference by analyzing the nature of the colloidal glasses formed at high ϕeff. We measured a smaller value of the fragility index m for acid-hydrolyzed PG NP glasses than that for native PG NP glasses, indicating that acid-hydrolyzed PG NPs form stronger glasses and are therefore softer than native PG NPs. Unlike the native PG NPs, we observed a distinctive change in the character of the glass transition of the acid-hydrolyzed PG NPs as ϕeff was increased above ϕeff∼1: a crossover in the dependence of ηr on ϕeff from Vogel-Fulcher-Tammann behavior to a more gradual, Arrhenius-like behavior. By expressing the steady shear and oscillatory rheology data in terms of generalized Péclet numbers, we obtained collapse of the data onto master curves. We interpret this result in terms of the acid-hydrolyzed PG NPs predominantly interpenetrating neighboring particles at large ϕeff, for which fluctuations of the outer chains enhance the mobility of the particles and make α-relaxation times τα experimentally accessible.

Short-Range Backbone Dihedral Rotations Modulate Internal Friction in Intrinsically Disordered Proteins.

Protein folding and dynamics are governed by an intricate interplay of thermal and viscosity-mediated effects. The solvent viscosity contributes to the frictional drag in protein dynamics. In addition to this viscosity-dependent effect, there is also an intriguing viscosity-independent component that represents the intrinsic resistance of the polypeptide chain to changing its conformation. This solvent-independent component is termed internal friction. A longstanding question is what is the fundamental molecular origin of internal friction in highly solvated and rapidly fluctuating intrinsically disordered proteins (IDPs) devoid of any persistent intrachain interactions? Here, we present a unique case to directly demonstrate that sequence-specific backbone dihedral barriers control local internal friction in an archetypal IDP, namely, α-synuclein. We performed site-directed fluorescence depolarization kinetics using picosecond time-resolved fluorescence anisotropy measurements to directly observe the directional decorrelation arising due to short-range backbone torsional fluctuations in the dihedral space. A linear viscosity-dependent model of the dihedral relaxation time yielded a finite zero-viscosity intercept that corresponds to internal friction. Our site-specific dynamic readouts were able to detect localized sequence-specific frictional components that are otherwise skewed in viscosity-dependent long-range chain fluctuations. Our results revealed the presence of low internal friction in nonproline sequence segments. In contrast, a proline introduces torsional stiffness in the segment exhibiting high internal friction that can be compensated by a conformationally flexible glycine. Such an intriguing interplay of local dihedral dynamics can modulate sequence-dependent internal friction in a wide range of IDPs involved in a myriad of important events including folding, binding, assembly, and phase transitions.

LEAN MANUFACTURING vs COVID-19

During the COVID-19 pandemic, companies coped and still must deal with uncertainty greater than ever. Due to the unpredictability of consumer demand, the incredible growth in demand for certain products, dramatic fluctuations in supply chains, and general economic instability, the future still looks uncertain. It is up to the manufacturers to determine how things will be sorted out in the new normality, i.e., which changes will be long-lasting or even permanent. Lean production has emerged in recent decades as an excellent solution to increase the economy and quality of production and meet customer needs. In the market conditions affected by the COVID-19 pandemic, producers work in a significantly changed environment, and many wonder whether lean production remains as relevant and valuable as in the past. The paper discusses lean production from different aspects as the essence of the principles of the lean concept, events during the pandemic, and expectations in the post-Covid period. We used some examples to support the analysis of factors that negatively affect the course of lean production as well as some bright examples of companies that took advantage of lean production in the new conditions. The conclusions consider answer whether lean production will survive the consequences of the COVID-19 pandemic.

Wild Flower Value Chains as Complex Adaptive Systems in Rural Sri Lanka

Purpose: Timeline of wild flowers showed the changing face to an economic good and moving through the different value chains while fueling to rural livelihoods. Focus of this study was to identify the upstream and downstream actors, their roles, map the wild flower value chain, analyze the income distribution, find out the gender-based constraints and identify the buying behavior of consumers. Methodology: Rapid market chain analysis equipped to collect the primary data. In-depth interviews with value chains actors, interviewer administered questionnaires and filed observations facilitated the process. Three key economically important wild flower value chains; Lotus, Lily and Jasmine were purposely selected. Findings: Value chain map shows core processes, flow of products and its volume, knowledge and information, geographical distribution and value web of relationships, and linkages. Income distribution shows that intermediaries claim the lion’s loin while collectors and growers receive less. Upstream actors of lotus and lily source their raw materials from common pool and free rider problem hinders the rational allocation of resources. Downstream; retailers govern the chain and seasonal price fluctuations are common. Poor post-harvest chain links with unhealthy returns. Color, price and quality were the prime concerns of consumers. Limitations: Poor availability of literature based on Sri Lankan wild flower sector was a constraint during the study and that was avoided with reference to researches which were done in other countries. Originality/Value: Since, limited number of studies paid attention on wild flower value chain; it’s better to investigate the Sri Lankan wild flower value chain in quantitative and qualitative aspects.

A Statistical Model for Short-Wavelength Collective Chain Fluctuations in a Lipid Bilayer under a High External Electric Field

A Statistical Model for Short-Wavelength Collective Chain Fluctuations in a Lipid Bilayer under a High External Electric Field