Chain Order Research Articles

Evaluation of the Physico-Chemical Properties of Liposomes Assembled from Bioconjugates of Anisic Acid with Phosphatidylcholine.

The aim of this work was the evaluation of the physico-chemical properties of a new type of liposomes that are composed of DPPC and bioconjugates of anisic acid with phosphatidylcholine. In particular, the impact of modified anisic acid phospholipids on the thermotropic parameters of liposomes was determined, which is crucial for using them as potential carriers of active substances in cancer therapies. Their properties were determined using three biophysical methods, namely differential scanning calorimetry (DSC), steady-state fluorimetry and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). Moreover, temperature studies of liposomes composed of DPPC and bioconjugates of anisic acid with phosphatidylcholine provided information about the phase transition, fluidity regarding chain order, hydration and dynamics. The DSC results show that the main phase transition peak for conjugates of anisic acid with phosphatidylcholine molecules was broadened and shifted to a lower temperature in a concentration- and structure-dependent manner. The ATR-FTIR results and the results of measurements conducted using fluorescent probes located at different regions in the lipid bilayer are in line with DSC. The results show that the new bioconjugates with phosphatidylcholine have a significant impact on the physico-chemical properties of a membrane and cause a decrease in the temperature of the main phase transition. The consequence of this is greater fluidity of the lipid bilayer.

Research on the Risk Measurement Algorithm of Supply Chain Order Financing Based on Insurance Actuarial

In today’s globalized economy, all the links of supply chain are interlinked. Most of the upstream raw material manufacturers or producers in the said chain are small- and medium-sized enterprises (SMEs) that provide the basis for the efficient operation of the whole supply chain. However, SMEs in China, especially those playing a pivotal role in China’s export-oriented economy at this stage, do not have access to the corresponding financial treatment. Supply chain finance provides a new perspective to solve this contradiction. Henceforth, this paper introduces modern financial engineering risk measurement tools to measure the financial risk in supply chain finance, specifically while evaluating the single financing business. Moreover, the chief objective of this paper will be the analysis of the characteristics and connotations of order financing business model. In addition, the focus will be to analyze the risk of order financing from the perspective of banks and other financial institutions. Additionally, this paper will use the CreditRisk + model based on insurance actuarial principles to manage credit risk in order financing business based on foreign currency settlement, in conjunction with the characteristics of supply chain finance and multinational supply chain. Furthermore, a risk measurement method for the application of order financing in multinational supply chains will be provided. Ultimately, the experiments show that the solution of this paper defines and analyzes the financial risks brought by order financing business to bank financing.

Efficiency, functionality, and multi-scale structure of citric acid esterified glutinous rice starch synthesized via infrared radiation

To simplify the process, decrease output cost, and limit the amount of wastewater and gas generated in the production of esterified starch, highly citrate-substituted glutinous rice starch was prepared using infrared radiation (IR) technology. Physicochemical properties and multi-scale structure of different starch were characterized to assess effectiveness of IR in starch esterification. Absorption at 1749 cm-1 in the Fourier-transform infrared spectrum was determined in either IR-citric acid modification (ICM) or dry heat-citric acid modification (DCM), confirming occurrence of esterification. The use of IR shortened synthesis time (7 min) for ICM compared with DCM (5 h) to an equivalent degree of substitution of 0.154. Furthermore, while functional properties of ICM and DCM were not significantly different (p > 0.05), they featured better thermal stability, anti-retrogradation, and digestion resistance compared with native glutinous rice starch. IR and esterification treatment destroyed crystalline regions in glutinous rice starch and decreased the order of molecular chains. The loss of the crystalline region was consistent with the absence of endothermic peaks in IRM, ICM, and DCM as indicated by differential scanning calorimetry. The results suggest that the use of IR technology for citric acid esterification of glutinous rice starch is an effective alternative method for preparing high contents of thermally stable resistant starch, and provide insights regarding the potential industrial application of IR technology for diversifying starch modification methods.

Determination of the Oxygen Chain Ordering in REBa2Cu3O7–δ by Electrical Conductivity Relaxation Measurements

Determination of the Oxygen Chain Ordering in REBa₂Cu₃O_7–δ by Electrical Conductivity Relaxation Measurements

Dynamic response on a nanometer scale of binary phospholipid-cholesterol vesicles: Low-frequency Raman scattering insight.

Low-frequency Raman spectroscopy was used to study the dynamic response on a nanometer scale of aqueous suspensions of two-component lipid vesicles. Binary mixtures of saturated phospholipid (1,2-dipalmitoyl-sn-glycero-3-phosphocholine, DPPC) and cholesterol are interesting for possible coexistence of solidlike and liquid-ordered phases, while the phase coexistence was not reported for unsaturated phospholipid (1,2-dioleoyl-sn-glycero-3-phosphocholine, DOPC) and cholesterol mixtures. The DOPC-DPPC mixtures represent the well-documented case of coexisting domains of solidlike and liquid-disordered phases. These three series of lipid mixtures are studied here. A broad peak with the maximum in the range of 30-50cm^{-1} and a narrow peak near 10cm^{-1} are observed in the Raman susceptibility of the binary mixtures and attributed to the acousticlike vibrational density of states and layer modes, respectively. Parameters of the broad and narrow peaks are sensitive to lateral and conformational hydrocarbon chain ordering. It was also demonstrated that the low-frequency Raman susceptibility of multicomponent lipid bilayers allows one to determine the phase state of lipid bilayers and distinguish the homogeneous distribution of molecular complexes from coexisting domains with sizes above several nanometers. Thus, the low-frequency Raman spectroscopy provides unique information in studying phase coexistence in lipid bilayers.

Raman scattering in protonated and deuterated 1,2-dipalmitoyl-sn-glycero-3-phosphatidylcholine (DPPC): Indicators of conformational and lateral orders

The use of deuterocarbons is an effective method in the Raman spectroscopy of multicomponent lipid materials and biological samples. Here, Raman spectra of hydrated multilamellar vesicles of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC), its deuterated analog 1,2-dipalmitoyl-d62-sn-glycero-3-phosphocholine (DPPCd62), and DPPC-DPPCd62 mixtures were studied in a wide temperature range to specify the Raman indicators of conformational and lateral orders. The temperature dependence of the 985 cm−1 line in the deuterated phospholipid unequivocally indicates that this line corresponds to the CC stretching vibrations of deuterated hydrocarbon chains in the all-trans conformation. It was also concluded that the ratio of Raman intensities at the maximum of the peak of the symmetric CD2 stretching and at a maximum near 2168 cm−1 reflects the conformational order of the hydrocarbon chain and can be used for an evaluation of the fraction of the all-trans sequences. The frequency of the symmetric CD2 stretching peak is sensitive to the phase state (gel or fluid) but has a low sensitivity to the partial conformational disordering within the gel phase. The Raman study of DPPC-DPPCd62 mixtures reveals that the lateral order contributes to the ratio of intensities of the antisymmetric and symmetric CH2 stretching peaks as a prefactor enhancing the effect of conformational ordering.

The studies on the membrane activity of triester of phosphatidylcholine in artificial membrane systems.

Due to the increasing number of infections together with the appearance of bacteria exhibiting multi-drug resistance, new antibiotics are being sought. In this context the interest of the cationic lipoids increases because of their amphiphilic structure and positive charge that can stimulates the antibacterial action of these compounds. Thus, in this work we have performed the studies on the effect of one selected triesters of phosphatidylcholine, namely 1,2-dipalmitoyl-sn-glycero-3-ethylphosphocholine (EDPPC), on the model lipid membranes. The investigations included the analysis of the impact of EDPPC on multicomponent monolayers and bilayers consisting of the lipids naturally occurring in bacterial membranes (phosphatidylethanolamines (PE), phosphatidylglycerols (PG) and cardiolipin (CL)), mixed in proportions reflecting the lipid composition of these biomembranes. In the study, the Langmuir monolayers (registered on water and PBS buffer) and liposomes as model bacterial biomembranes were applied. The obtained results demonstrate that the presence of cationic lipoid in PE/PG and PE/PG/CL systems significantly modifies their properties and molecular organization. The incorporation of EDPPC into model bacterial membranes primarily impact on the intermolecular interactions. It was shown that the strength of the interaction between the cationic lipid and the components of the model membranes depends both on the composition of the membrane as well as on the type of subphase. Furthermore, the investigated cationic lipoid leads to the decrease of the ordering of acyl chains and thus to the increase of fluidity of membranes. The obtained results allow one to propose that EDPPC may behave as antibiotic active at the level of membrane.

Microscopic Diffusion Characteristics of Linear Alkylbenzene Sulfonates on the Surface of Anthracite: The Influence of Different Attachment Sites of Benzene Ring in the Backbone

In order to explore the effect of the attachment site of the benzene ring in the backbone of the surfactant on its diffusion characteristics on the surface of anthracite, the molecular dynamics simulation method was used, and the four isomers (m-C16, m = 2,4,6,8; m represents the attachment site of the benzene ring in the backbone) of sodium hexadecyl benzene sulfonate (SHS) were selected. Binary models of surfactant/anthracite, surfactant/graphene modified by oxygen-containing functional groups, and a ternary model of water/surfactant/anthracite were constructed. By analyzing a series of properties such as interaction energy, contact surface area, relative concentration distribution, radial distribution function, hydrophobic tail chain order parameter, etc., it is concluded that the adsorption strength of 4-C16 on the surface of anthracite is the highest; the reason is that 4-C16 has the highest degree of aggregation near the oxygen-containing functional groups on the surface of anthracite. Further investigations find that 4-C16 can be densely covered on the ketone group, and the longer branch chain of 4-C16 has the highest degree of order in the Z-axis direction.

Application of Reinforcement Learning Algorithm in Delivery Order System under Supply Chain Environment

With the intensification of market competition and the development of market globalization, the efficiency of supply chain management orders has become an important part of enterprise competition resources. The competition among enterprises is fierce. To achieve effective customer response quickly, the time for supply chain order management is minimized, and refine the order processing process. This article introduces the strategy research of supply chain management order based on a reinforcement learning algorithm. This article first combines the reinforcement learning algorithm and deep learning algorithm, using the optimal decision-making ability of reinforcement learning algorithm and deep learning algorithm. The combination of data perception and the optimal ability to analyze examine the data of the order process, order cycle, and order delivery process of the supply chain order management and give the optimal decision. The supply chain order management process conducts questionnaire surveys and seminars to understand the current process of supply chain order management and the problems derived from the analysis of data based on the deep learning algorithm. Finally, through the output of the optimal strategy of the reinforcement learning algorithm, the supply chain order management process was improved, and the satisfaction survey was conducted again. The survey showed that the satisfaction was improved, and the satisfaction reached more than 90%.

Improved Potency and Safety of DNA-Encoded Antibody Therapeutics Through Plasmid Backbone and Expression Cassette Engineering.

DNA-encoded delivery of antibodies presents a labor- and cost-effective alternative to conventional antibody therapeutics. This study aims to improve the potency and safety of this approach by evaluating various plasmid backbones and expression cassettes. In vitro, antibody levels consistently improved with decreasing sizes of backbone, ranging from conventional to minimal. In vivo, following intramuscular electrotransfer in mice, the correlation was less consistent. While the largest conventional plasmid (10.2 kb) gave the lowest monoclonal antibody (mAb) levels, a regular conventional plasmid (8.6 kb) demonstrated similar levels as a minimal Nanoplasmid (6.8 kb). A reduction in size beyond a standard conventional backbone thus did not improve mAb levels in vivo. Cassette modifications, such as swapping antibody chain order or use of two versus a single encoding plasmid, significantly increased antibody expression in vitro, but failed to translate in vivo. Conversely, a significant improvement in vivo but not in vitro was found with a set of muscle-specific promoters, of which a newly engineered variant gave roughly 1.5- to 2-fold higher plasma antibody concentrations than the ubiquitous CAG promoter. In conclusion, despite the limited translation between in vitro and in vivo, we identified various clinically relevant improvements to our DNA-based antibody platform, both in potency and biosafety.

Взаимодействие катионных антисептиков с кардиолипинсодержащей модельной бактериальной мембраной

Plasma membrane is one of the major targets for cationic antiseptics (CA). The study was aimed to assess molecular effects of CAs of different chemical classes on cardiolipin-containing regions of bacterial plasma membranes. The study was carried out using coarse-grained molecular modeling. Interaction of CAs, such as miramistin, chlorhexidine, picloxidine, and octenidine, with cardiolipin-containing bilayer was assessed based on the CA coarse-grained models. CAs reduced lipid lateral diffusion coefficients and increased the membrane area per lipid. All CAs, except miramistin, reduced the lipid fatty acid chain order parameters. Adding octenidine at a CA : lipid ratio of 1 : 4 resulted in cardiolipin clustering with subsequent pulling the neutral phosphatidylethanolamine molecules out of the model bilayer. It was found that CАs have the potential for sorption to lipid bilayer, causing clustering of negatively charged lipids. Antiseptic octenidine causes formation of cardiolipin microdomains. Abnormal lateral lipid distribution together with pulling out phosphatidylethanolamine molecules can result in increased lipid bilayer permeability. The most significant reduction of cardiolipin lateral diffusion coefficient by 2.8 ± 0.4 times was observed in the presence of CA chlorhexidine at an antiseptic : lipid ratio of 1 : 4.

Structure and Interdigitation of Chain-Asymmetric Phosphatidylcholines and Milk Sphingomyelin in the Fluid Phase.

We addressed the frequent occurrence of mixed-chain lipids in biological membranes and their impact on membrane structure by studying several chain-asymmetric phosphatidylcholines and the highly asymmetric milk sphingomyelin. Specifically, we report trans-membrane structures of the corresponding fluid lamellar phases using small-angle X-ray and neutron scattering, which were jointly analyzed in terms of a membrane composition-specific model, including a headgroup hydration shell. Focusing on terminal methyl groups at the bilayer center, we found a linear relation between hydrocarbon chain length mismatch and the methyl-overlap for phosphatidylcholines, and a non-negligible impact of the glycerol backbone-tilting, letting the sn1-chain penetrate deeper into the opposing leaflet by half a CH2 group. That is, penetration-depth differences due to the ester-linked hydrocarbons at the glycerol backbone, previously reported for gel phase structures, also extend to the more relevant physiological fluid phase, but are significantly reduced. Moreover, milk sphingomyelin was found to follow the same linear relationship suggesting a similar tilt of the sphingosine backbone. Complementarily performed molecular dynamics simulations revealed that there is always a part of the lipid tails bending back, even if there is a high interdigitation with the opposing chains. The extent of this back-bending was similar to that in chain symmetric bilayers. For both cases of adaptation to chain length mismatch, chain-asymmetry has a large impact on hydrocarbon chain ordering, inducing disorder in the longer of the two hydrocarbons.

Unitary Long-Time Evolution with Quantum Renormalization Groups and Artificial Neural Networks.

In this work, we combine quantum renormalization group approaches with deep artificial neural networks for the description of the real-time evolution in strongly disordered quantum matter. We find that this allows us to accurately compute the long-time coherent dynamics of large many-body localized systems in nonperturbative regimes including the effects of many-body resonances. Concretely, we use this approach to describe the spatiotemporal buildup of many-body localized spin-glass order in random Ising chains. We observe a fundamental difference to a noninteracting Anderson insulating Ising chain, where the order only develops over a finite spatial range. We further apply the approach to strongly disordered two-dimensional Ising models, highlighting that our method can be used also for the description of the real-time dynamics of nonergodic quantum matter in a general context.

Effects of (R)- and (S)-α-Hydroxylation of Acyl Chains in Sphingosine, Dihydrosphingosine, and Phytosphingosine Ceramides on Phase Behavior and Permeability of Skin Lipid Models.

Ceramides (Cers) with α-hydroxylated acyl chains comprise about a third of all extractable skin Cers and are required for permeability barrier homeostasis. We have probed here the effects of Cer hydroxylation on their behavior in lipid models comprising the major SC lipids, Cer/free fatty acids (C 16-C 24)/cholesterol, and a minor component, cholesteryl sulfate. Namely, Cers with (R)-α-hydroxy lignoceroyl chains attached to sphingosine (Cer AS), dihydrosphingosine (Cer AdS), and phytosphingosine (Cer AP) were compared to their unnatural (S)-diastereomers and to Cers with non-hydroxylated lignoceroyl chains attached to sphingosine (Cer NS), dihydrosphingosine (Cer NdS), and phytosphingosine (Cer NP). By comparing several biophysical parameters (lamellar organization by X-ray diffraction, chain order, lateral packing, phase transitions, and lipid mixing by infrared spectroscopy using deuterated lipids) and the permeabilities of these models (water loss and two permeability markers), we conclude that there is no general or common consequence of Cer α-hydroxylation. Instead, we found a rich mix of effects, highly dependent on the sphingoid base chain, configuration at the α-carbon, and permeability marker used. We found that the model membranes with unnatural Cer (S)-AS have fewer orthorhombically packed lipid chains than those based on the (R)-diastereomer. In addition, physiological (R)-configuration decreases the permeability of membranes, with Cer (R)-AdS to theophylline, and increases the lipid chain order in model systems with natural Cer (R)-AP. Thus, each Cer subclass makes a distinct contribution to the structural organization and function of the skin lipid barrier.

Confined Crystallization and Melting Behaviors of 3-Pentadecylphenol in Anodic Alumina Oxide Nanopores.

To explore the effects of end groups on the confined crystallization of an alkyl chain, 3-pentadecylphenol (PDP) was infiltrated into the anodic aluminum oxide template (AAO) to investigate the melting and crystallization behaviors of PDP in a nanoconfined environment. Wide-angle X-ray diffraction (WAXD) found that the solid–solid phase transition of PDP occurred under confined conditions, and the absence of the (00L) reflections indicated that the stacking of the end groups of the alkyl chain layered structure was seriously disturbed. Thermal analysis (TG) showed that the thermal stability of the confined samples decreased due to the confinement effect, and the introduction of end groups made the confinement effect more obvious. Differential scanning calorimeter (DSC) results well reflected the space–time equivalence in the PDP crystallization processes, i.e., the solid–solid phase transition can be achieved by reducing the cooling rate or confining PDP in the nanometer space. Compared with C15, the introduction of the end groups with a phenol ring led to the disappearance of the solid–solid phase transition of an alkyl chain at high cooling rates. In the confined environment, the introduction of the end groups with a phenol ring caused the melting double peaks of the alkyl chain to become a single melting peak, and it also caused the disappearance of the surface freezing monolayer for alkyl chains. Through the analysis of crystallinity, it was found that AAO-PDP was more sensitive to AAO pore size changes than AAO-C15, the Xc of AAO-PDP had a good linear relationship with the pore size d, but the Xc of the AAO-C15 had a nonlinear relationship with the pore size d. Attenuated total reflection (ATR)-IR proved that in the confined environment, the order of the alkyl chain decreased and the degree of chain distortion increased.

Aniline-pyrrole Copolymer/SWCNT thermoelectric composites from electrochemical polymerization

Aniline-pyrrole copolymer (poly(ANi-co-Py)) electropolymerized on conductive glass was ultrasonically mixed with single-walled carbon nanotubes (SWCNTs) to prepare poly(ANi-co-Py)/SWCNT thermoelectric (TE) composites. Effects of SWCNTs contents and reaction parameters on morphology, structure, and TE properties of composites are investigated. In the as-prepared flexible poly(ANi-co-Py)/SWCNT composite films, SWCNTs and poly(ANi-co-Py) are fully entangled and tightly bonded. The highest electrical conductivity (σ) of 1035.3 ± 9.0 S cm−1 is obtained at 60 wt% of SWCNTs. The maximal Seebeck coefficient (S) of 33.0 ± 3.2 μV K−1 appears at 90 wt% SWCNTs. Thus, The peak room temperature power factor (PF) of the composites is 83.2 ± 3.3 μW m−1 K−2 at 60 wt% SWCNTs. Improved TE performance of the composites reflects increased chain ordering and enhanced interaction between SWCNTs and poly(ANi-co-Py).

Selectivity enhancement for the separation of shape‐constrained isomers by particle size‐derived molecular ordering and density in reversed‐phase liquid chromatography

AbstractThe purpose of this study is to describe the enhancement of molecular‐shape selectivity and grafted polymer characteristics by altering the particle size, pore size, and polymer chains of polymer‐silica hybrid materials used in reversed‐phase liquid chromatography. The poly(octadecyl acrylate‐alt‐N‐octadecylmaleimide)‐grafted silica hybrid materials were prepared with 3 and 5 μm particle size silica, respectively. The alternating copolymerisations were conducted with 3‐mercaptopropyltrimethoxysilane‐modified silica via surface‐initiated radical chain transfer reactions. The polymer‐silica hybrid materials were characterised by elemental analyses, diffuse reflectance FTIR spectroscopy, solid‐state 13C and 29Si cross‐polarisation–magic‐angle spinning and suspended‐state 1H NMR spectroscopy. The NMR spectroscopy results revealed that the alkyl chains of 3 μm particle size phase are more ordered than those of 5 μm particle size phase at lower temperatures and vice versa at higher temperatures. After detailed characterisation, the hybrid materials were packed into a stainless‐steel column, and their chromatographic performance with polycyclic aromatic hydrocarbons was compared. Regardless of the grafting‐density, ordering of the alkyl chains, and column temperature, differences in molecular‐planarity selectivity molecular‐linearity were observed. Aspects of molecular‐shape selectivity were also evaluated using the standard reference material for priority pollutant polycyclic aromatic hydrocarbons.

Study and Order of a Medium Power Wind Turbine Conversion Chain Connected to Medium Voltage Grid

In this article, we will study a system consisting of a wind turbine operating at a variable wind speed and a two-feed asynchronous machine (DFIG) connected to the grid by the stator and fed by a transducer at the rotor side. The conductors are separately controlled for active and reactive power flow between the stator (DFIG) and the network, which is achieved using conventional PI and fuzzy logic. The proposed controllers generate reference voltages for the rotor to ensure that the active and reactive powers reach the required reference values, in order to ensure effective tracking of the optimum operating point and to obtain the maximum electrical power output. System modeling and simulation were examined with Matlab. Dynamic analysis of the system is performed under variable wind speed. This analysis is based on active and reactive energy control. The results obtained show the advantages of the proposed intelligent control unit.

Selecting Markov chain orders for generating daily precipitation series across different Köppen climate regimes

AbstractMarkov chain models are a commonly used statistical technique to generate realistic sequences of precipitation, but the choice of model order can strongly affect their performance. Although it is widely accepted that a first‐order Markov chain reproduces precipitation occurrence in temperate latitudes quite well, it is also well known that first‐order models have several shortcomings. These include a limited memory of rare events and inaccurately reproducing the distribution of dry‐spell lengths, and their performance outside of temperate regions is less well understood. We present, therefore, the first assessment of model‐order optimization which is both global in extent and which uses four evaluation methods: the Bayesian information criterion (BIC) and each model‐order's ability to reproduce wet‐ and dry‐spell lengths, and the interannual variability of precipitation occurrence. As well as a global analysis, we also assessed Markov chain performance and model‐order selection separately within five climate regimes based on the Köppen classification system: tropical, dry, temperate, continental and polar. These metrics were used to determine the best performing model‐order to generate realistic time series of precipitation across the five different climate regimes. We find that the choice of model order is most sensitive to the performance metric and less dependent on the climate regime. Across all regimes, we show that a first‐order model performs best when evaluated with BIC and for generating realistic wet‐spell distributions across all climate regimes except tropical, where third order performs best. We also find that a third‐order model reproduces observed dry‐spell distributions the best and second order commonly reproduces the interannual variability of precipitation occurrence across all regimes except tropical, where third order once again performs best. Our findings highlight the benefits of a flexible and tailored approach to the choice of Markov chain order for constructing precipitation series.

Coarse grained simulation of the aggregation and structure control of polyethylene nanocrystals

Polyethylene (PE) telechelics with carboxylate functional groups at both ends have been shown to assemble into hexagonal nanocrystal platelets with a height defined by their chain length in basic CsOH-solution. In this coarse grained (CG) simulation study we show how properties of the functional groups alter the aggregation and crystallization behavior of those telechelics. Systematic variation of the parameters of the CG model showed that important factors which control nanoparticle stability and structure are the PE chain length and the hydrophilicity and the steric demand of the head groups. To characterize the aggregation process we analyzed the number and size of the obtained aggregates as well as intramolecular order and intermolecular alignment of the polymer chains. By comparison of CG and atomistic simulation data, it could be shown that atomistic simulations representing different chemical systems can be emulated with specific, different CG parameter sets. Thus, the results from the (generic) CG simulation models can be used to explain the effect of different head groups and different counterions on the aggregation of PE telechelics and the order of the obtained nanocrystals.