Polycaprolactone strengthening keratin/bioactive glass composite scaffolds with double cross-linking networks for potential application in bone repair

In this study,we aimed at constructing polycaprolactone(PCL)reinforced keratin/bioactive glass composite scaffolds with a double cross-linking network structure for potential bone repair application.Thus,the PCL-keratin-BG composite scaffold was prepared by using keratin extracted from wool as main organic component and bioactive glass(BG)as main inorganic component,through both cross-linking systems,such as the thiol-ene click reaction between abundant sulfhydryl groups of keratin and the unsaturated double bond of 3-methacryloxy propyltrimethoxy silane(MPTS),and the amino-epoxy reaction between amino groups of keratin and the epoxy group in(3-glycidoxymethyl)methyldiethoxysilane(GPTMS)molecule,along with introduction of PCL as a reinforcing agent.The success of the thiol-ene reaction was verified by the FTIR and 1H-NMR analyses.And the structure of keratin-BG and PCL-keratin-BG composite scaffolds were studied and compared by the FTIR and XRD characterization,which indicated the successful preparation of the PCL-keratin-BG composite scaffold.In addition,the SEM observation,and contact angle and water absorption rate measurements demonstrated that the PCL-keratin-BG composite scaffold has interconnected porous structure,appropriate pore size and good hydrophilicity,which is helpful to cell adhesion,differentiation and proliferation.Importantly,compression experiments showed that,when compared with the keratin-BG composite scaffold,the PCL-keratin-BG composite scaffold increased greatly from 0.91±0.06 MPa and 7.25±1.7 MPa to 1.58±0.21 MPa and 14.14±1.95 MPa,respectively,which suggesting the strong reinforcement of polycaprolactone.In addition,the biomineralization experiment and MTT assay indicated that the PCL-keratin-BG scaffold has good mineralization ability and no-cytotoxicity,which can promote cell adhesion,proliferation and growth.Therefore,the results suggested that the PCL-keratin-BG composite scaffold has the potential as a candidate for application in bone regeneration field.

Fluorescent Double Network Hydrogels with Ionic Responsiveness and High Mechanical Properties for Visual Detection

We developed a fluorescent double network hydrogel with ionic responsiveness and high mechanical properties for visual detection.The nanocomposite hydrogel of laponite and polyacrylamide serves as the first network,while the ionic cross-linked hydrogel of terbium ions and sodium alginate serves as the second network.The double-network structure,the introduction of nanoparticles and the reversible ionic crosslinked interactions confer high mechanical properties to the hydrogel.Terbium ions are not only used as the ionic cross-linked points,but also used as green emitters to endow hydrogels with fluorescent properties.On the basis of the “antenna effect” of terbium ions and the ion exchange interaction,the fluorescence of the hydrogels can make selective responses to various ions(such as organic acid radical ions,transition metal ions) in aqueous solutions,which enables a convenient strategy for visual detection toward ions.Consequently,the fluorescent double network hydrogel fabricated in this study is promising for use in the field of visual sensor detection.

Polycaprolactone strengthening keratin/ bioactive glass composite scaffolds with double cross-linking networks for potential application in bone repair

In this study, we aimed at constructing polycaprolactone (PCL) reinforced keratin/bioactive glass composite scaffolds with a double cross-linking network structure for potential bone repair application. Thus, the PCL-keratin-BG com-posite scaffold was prepared by using keratin extracted from wool as main organic component and bioactive glass (BG) as main inorganic component, through both cross-linking systems, such as the thiol-ene click reaction between abundant sulfhydryl groups of keratin and the unsaturated double bond of 3-methacryloxy propyltrimethoxy silane (MPTS), and the amino-epoxy reaction between amino groups of keratin and the epoxy group in (3-glycidoxymethyl) methyldiethoxysilane (GPTMS) molecule, along with introduction of PCL as a reinforcing agent. The success of the thiol-ene reaction was verified by the FTIR and 1H-NMR analyses. And the structure of keratin-BG and PCL-keratin-BG composite scaffolds were studied and compared by the FTIR and XRD characterization, which indicated the successful preparation of the PCL-keratin-BG composite scaffold. In addition, the SEM observation, and contact angle and water absorption rate measurements demonstrated that the PCL-keratin-BG composite scaffold has interconnected porous structure, appropriate pore size and good hydrophilicity, which is helpful to cell adhesion, differentiation and prolifera-tion. Importantly, compression experiments showed that, when compared with the keratin-BG composite scaffold, the PCL-keratin-BG composite scaffold increased greatly from 0.91 ± 0.06 MPa and 7.25 ± 1.7 MPa to 1.58 ± 0.21 MPa and 14.14 ± 1.95 MPa, respectively, which suggesting the strong reinforcement of polycaprolactone. In addition, the biomineralization experiment and MTT assay indicated that the PCL-keratin-BG scaffold has good mineralization abil-ity and no-cytotoxicity, which can promote cell adhesion, proliferation and growth. Therefore, the results suggested that the PCL-keratin-BG composite scaffold has the potential as a candidate for application in bone regeneration field.

基于Dueling Double DQN的交通信号控制方法

为了提高交叉口通行效率缓解交通拥堵,深入挖掘交通状态信息中所包含的深层次隐含特征信息,提出了一种基于Dueling Double DQN(D3QN)的单交叉口交通信号控制方法;构建了一个基于深度强化学习Double DQN(DDQN)的交通信号控制模型,对动作-价值函数的估计值和目标值迭代运算过程进行了优化,克服基于深度强化学习DQN的交通信号控制模型存在收敛速度慢的问题;设计了一个新的Dueling Network解耦交通状态和相位动作的价值,增强Double DQN(DDQN)提取深层次特征信息的能力;基于微观仿真平台SUMO搭建了一个单交叉口模拟仿真框架和环境,开展仿真测试;仿真测试结果表明,与传统交通信号控制方法和基于深度强化学习DQN的交通信号控制方法相比,所提方法能够有效减少车辆平均等待时间、车辆平均排队长度和车辆平均停车次数,明显提升交叉口通行效率。

Transcriptome and morphological analyses of double flower formation in Dianthus chinensis

The double flower developmental process is regulated via a complex transcriptional regulatory network.To understand this highly dynamic and complex developmental process of Dianthus spp.,we performed a comparative analysis of floral morphology and transcriptome dynamics in simple flowers and double flowers.We found that the primordium of double flowers of‘X’was larger in size compared to that of simple flowers of‘L’in Dianthus chinensis.RNA-seq and Weighted Gene Co-expression Network Analysis(WGCNA)during flower development,identified stage-specific gene network modules.Expression analysis by RNA-seq indicated that a group of genes related to floral meristem identity,primordia position and polarity were highly expressed in double flowers genotypes compared to simple flowers genotypes,suggesting their roles in double-petal formation.A total of 21 DEGs related to petal number were identified between simple and double flowers.The experiments of in situ hybridization revealed that DcaAP2L,DcaLFY and DcaUFO genes were expressed in the intra-sepal boundary and petal boundary.We proposed a potential transcriptional regulatory network for simple and double flower development.This study provides novel insights into the molecular mechanism underlying double flower formation in Dianthus spp.

Cascading Delays for the High-Speed Rail Network Under Different Emergencies:A Double Layer Network Approach

High-speed rail(HSR) has formed a networked operational scale in China. Any internal or external disturbance may deviate trains’ operation from the planned schedules, resulting in primary delays or even cascading delays on a network scale. Studying the delay propagation mechanism could help to improve the timetable resilience in the planning stage and realize cooperative rescheduling for dispatchers. To quickly and effectively predict the spatial-temporal range of cascading delays, this paper proposes a max-plus algebra based delay propagation model considering trains’ operation strategy and the systems’ constraints. A double-layer network based breadth-first search algorithm based on the constraint network and the timetable network is further proposed to solve the delay propagation process for different kinds of emergencies. The proposed model could deal with the delay propagation problem when emergencies occur in sections or stations and is suitable for static emergencies and dynamic emergencies. Case studies show that the proposed algorithm can significantly improve the computational efficiency of the large-scale HSR network. Moreover, the real operational data of China HSR is adopted to verify the proposed model, and the results show that the cascading delays can be timely and accurately inferred, and the delay propagation characteristics under three kinds of emergencies are unfolded.

Unlocking the potentials of gel conformance for water shutoff in fractured reservoirs: Favorable attributes of the double network gel for enhancing oil recovery

The double-network prepared with an in-situ monomer gel and a fast-crosslinked Cr(III) gel is introduced to develop a thixotropic and high-strength gel (THSG), which is found to have many advantages over the traditional gels. The THSG gel demonstrates remarkable thermal stability, and no syneresis is observed after 12 months with high salinity brine (95,500 mg/L). Moreover, the SEM and XRD results indicate that the gel is intercalated into the lamellar structures of Na-MMT, where the gel can form a uniform and compact structure. In addition, the THSG gel has an excellent swelling behavior, even in the high salinity brine. In the slim tube experiments, the THSG gel exhibits high rupture pressure and improves blocking capacity after being ruptured. The core flooding results show that a layer of gel filter cake is formed on the face of the fracture, which may be promoted by a high matrix permeability, a small aperture fracture, and a high injection rate. After the gel treatment, the fracture can be completely blocked by the THSG gel. It is found that a high incremental oil recovery (65.3%) can be achieved when the fracture was completely blocked, compared to 40.2% if the gel is ruptured. Although the swelling of ruptured gel can improve oil recovery, part of the injected brine may be channeled through the gel-filled fractures, resulting in a decrease in the sweep efficiency. Therefore, the improved blocking ability by gel swelling (e.g., in fresh water) may be less efficient to contribute to an enhancement of oil recovery. It is also found that the pressure gradient and residual resistance factor to water (Frrw) are higher if the matrix is less permeable, indicating that the fractured reservoir with lower matrix permeability may require a higher gel strength for treatment. The findings of this study may provide novel insights on designing robust double network gels for water shutoff in fractured reservoirs.

A Double Threshold Energy Detection-Based Neural Network for Cognitive Radio Networks

In cognitive radio networks(CoR),the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability.Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection.However,these methods do not take into account the effect of sample size and its effect on improving CoR performance.In general,a large sample size results in more reliable detection,but takes longer sensing time and increases complexity.Thus,the locally sensed sample size is an optimization problem.Therefore,optimizing the local sample size for each cognitive user helps to improve CoR performance.In this study,two new methods are proposed to find the optimum sample size to achieve objective-based improved(single/double)threshold energy detection,these methods are the optimum sample size N^(*)and neural networks(NN)optimization.Through the evaluation,it was found that the proposed methods outperform the traditional sample size selection in terms of the total error rate,detection probability,and throughput.

A Double Network Hydrogel with High Mechanical Strength and Shape Memory Properties

Double network(DN)hydrogels as one kind of tough gels have attracted extensive at-tention for their potential applications in biomedical and load-bearing fields.Herein,we import more functions like shape memory into the conventional tough DN hydro-gel system.We synthesize the PEG-PDAC/P(AAm-co-AAc)DN hydrogels,of which the first network is a well-defined PEG(polyethylene glycol)network loaded with PDAC(poly(acryloyloxyethyltrimethyl ammonium chloride))strands,while the second network is formed by copolymerizing AAm(acrylamide)with AAc(acrylic acid)and cross-linker MBAA(N;N′-methylenebisacrylamide).The PEG-PDAC/P(AAm-co-AAc)DN gels exhibits high mechanical strength.The fracture stress and toughness of the DN gels reach up to 0.9 MPa and 3.8 MJ/m^3,respectively.Compared with the conventional double network hydrogels with neutral polymers as the soft and ductile second network,the PEG-PDAC/P(AAm-co-AAc)DN hydrogels use P(AAm-co-AAc),a weak polyelectrolyte,as the second network.The AAc units serve as the coordination points with Fe^3+ions and physically crosslink the second network,which realizes the shape memory property activated by the reducing ability of ascorbic acid.Our results indicate that the high mechanical strength and shape memory properties,probably the two most important characters related to the potential application of the hydrogels,can be introduced simultaneously into the DN hydrogels if the functional monomer has been integrated into the network of DN hydrogels smartly.

A Self-Healing and Nonflammable Cross-Linked Network Polymer Electrolyte with the Combination of Hydrogen Bonds and Dynamic Disulfide Bonds for Lithium Metal Batteries

The self-healing solid polymer electrolytes(SHSPEs)can spontaneously eliminate mechanical damages or micro-cracks generated during the assembly or operation of lithium-ion batteries(LIBs),significantly improving cycling performance and extending service life of LIBs.Here,we report a novel cross-linked network SHSPE(PDDP)containing hydrogen bonds and dynamic disulfide bonds with excellent self-healing properties and nonflammability.The combination of hydrogen bonding between urea groups and the metathesis reaction of dynamic disulfide bonds endows PDDP with rapid self-healing capacity at 28°C without external stimulation.Furthermore,the addition of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide(EMIMTFSI)improves the ionic conductivity(1.13×10^(−4)S cm^(−1)at 28°C)and non-flammability of PDDP.The assembled Li/PDDP/LiFePO_(4)cell exhibits excellent cycling performance with a discharge capacity of 137 mA h g^(−1)after 300 cycles at 0.2 C.More importantly,the self-healed PDDP can recover almost the same ionic conductivity and cycling performance as the original PDDP.

Model-constrained and data-driven double-supervision acoustic impedance inversion

Seismic impedance inversion is an important technique for structure identification and reservoir prediction.Model-based and data-driven impedance inversion are the commonly used inversion methods.In practice,the geophysical inversion problem is essentially an ill-posedness problem,which means that there are many solutions corresponding to the same seismic data.Therefore,regularization schemes,which can provide stable and unique inversion results to some extent,have been introduced into the objective function as constrain terms.Among them,given a low-frequency initial impedance model is the most commonly used regularization method,which can provide a smooth and stable solution.However,this model-based inversion method relies heavily on the initial model and the inversion result is band limited to the effective frequency bandwidth of seismic data,which cannot effectively improve the seismic vertical resolution and is difficult to be applied to complex structural regions.Therefore,we propose a data-driven approach for high-resolution impedance inversion based on the bidirectional long short-term memory recurrent neural network,which regards seismic data as time-series rather than image-like patches.Compared with the model-based inversion method,the data-driven approach provides higher resolution inversion results,which demonstrates the effectiveness of the data-driven method for recovering the high-frequency components.However,judging from the inversion results for characterization the spatial distribution of thin-layer sands,the accuracy of high-frequency components is difficult to guarantee.Therefore,we add the model constraint to the objective function to overcome the shortages of relying only on the data-driven schemes.First,constructing the supervisor1 based on the bidirectional long short-term memory recurrent neural network,which provides the predicted impedance with higher resolution.Then,convolution constraint as supervisor2 is introduced into the objective function to guarantee the reliability and accuracy of the inversion results,which makes the synthetic seismic data obtained from the inversion result consistent with the input data.Finally,we test the proposed scheme based on the synthetic and field seismic data.Compared to model-based and purely data-driven impedance inversion methods,the proposed approach provides more accurate and reliable inversion results while with higher vertical resolution and better spatial continuity.The inversion results accurately characterize the spatial distribution relationship of thin sands.The model tests demonstrate that the model-constrained and data-driven impedance inversion scheme can effectively improve the thin-layer structure characterization based on the seismic data.Moreover,tests on the oil field data indicate the practicality and adaptability of the proposed method.

Simultaneous Determination of Gold and Platinum by Double Artificial Neural Network Analysis with Flow-injection Chemiluminescence

A highly sensitive double artificial neural network （DANN） analysis with flow-injection chemiluminescence （FI-CL） has been developed to simultaneously determine the trace amounts of the gold and platinum in simulated mixed samples, without the boring process.

基于Double Deep Q Network的无人机隐蔽接敌策略

基于深度强化学习的连续状态空间无人机隐蔽接敌问题,提出了基于马尔可夫决策过程的隐蔽接敌双深度Q网络(DDQN)方法。利用DDQN生成目标值函数的方法解决了传统DQN的过拟合问题;采用按优先级随机抽样的方法获取训练样本,加速了神经网络的训练速度;设定贪婪系数按照指数下降的方法,解决了传统强化学习的“探索利用窘境”;在势函数奖赏函数设计中引入角度因子,使其更加符合实际作战情况。仿真实验结果表明,DDQN具有较好的收敛性,能有效生成隐蔽接敌策略。

Polyzwitterionic cross-linked double network hydrogel electrolyte enabling high-stable Zn anode

Zn metal anode suffers from dendrite issues and passive byproducts,which severely plagues the practical application of aqueous Zn metal batteries.Herein,a polyzwitterionic cross-linked double network hydrogel electrolyte composed of physical crosslinking(hyaluronic acid)and chemical crosslinking(synthetic zwitterionic monomer copolymerized with acrylamide)is introduced to overcome these obstacles.On the one hand,highly hydrophilic physical network provides an energy dissipation channel to buffer stress and builds a H_(2)O-poor interface to avoid side reactions.On the other hand,the charged groups(sulfonic and imidazolyl)in chemical crosslinking structure build anion/cation transport channels to boost ions’kinetics migration and regulate the typical solvent structure[Zn(H_(2)O)_(6)]^(2+)to R-SO_(3)^(−)[Zn(H_(2)O)_(4)]^(2+),with uniform electric field distribution and significant resistance to dendrites and parasitic reactions.Based on the above functions,the symmetric zinc cell exhibits superior cycle stability for more than 420 h at a high current density of 5 mA·cm^(−2),and Zn||MnO_(2)full cell has a reversible specific capacity of 150 mAh·g^(−1)after 1000 cycles at 2 C with this hydrogel electrolyte.Furthermore,the pouch cell delivers impressive flexibility and cyclability for energy-storage applications.

A new algorithm for diameter of double loop network

Presents a new algorithm for diameter of double loop network(DLN) by which two new classes of infinite families of tight DLN of the known twelve infinie families of tight DLNs, under 3.3 in [1] including eleven are constructed.

Double Glow Plasma Surface Alloying Process Modeling Using Artificial Neural Networks

A model is developed for predicting the correlation between processing parameters and the technical target of double glow by applying artificial neural network (ANN). The input parameters of the neural network (NN) are source voltage, workplace voltage, working pressure and distance between source electrode and workpiece. The output of the NN model is three important technical targets, namely the gross element content, the thickness of surface alloying layer and the absorption rate (the ratio of the mass loss of source materials to the increasing mass of workpiece) in the processing of double glow plasma surface alloying. The processing parameters and technical target are then used as a training set for an artificial neural network. The model is based on multiplayer feedforward neural network. A very good performance of the neural network is achieved and the calculated results are in good agreement with the experimental ones.

A Routing Algorithm for Distributed Optimal Double Loop Computer Networks

A routing algorithm for distributed optimal double loop computer networks is proposed and analyzed. In this paper, the routing algorithm rule is described, and the procedures realizing the algorithm are given. The proposed algorithm is shown to be optimal and robust for optimal double loop. In the absence of failures,the algorithm can send a packet along the shortest path to destination; when there are failures,the packet can bypasss failed nodes and links.

A double-network hydrogel for the dynamic compression of the lumbar nerve root

Current animal models of nerve root compression due to lumbar disc herniation only assess the mechanical compression of nerve roots and the inflammatory response. Moreover, the pressure applied in these models is static, meaning that the nerve root cannot be dynamically compressed. This is very different from the pathogenesis of lumbar disc herniation. In this study, a chitosan/polyacrylamide double-network hydrogel was prepared by a simple two-step method. The swelling ratio of the double-network hydrogel increased with prolonged time, reaching 140. The compressive strength and compressive modulus of the hydrogel reached 53.6 and 0.34 MPa, respectively. Scanning electron microscopy revealed the hydrogel's crosslinked structure with many interconnecting pores. An MTT assay demonstrated that the number of viable cells in contact with the hydrogel extracts did not significantly change relative to the control surface. Thus, the hydrogel had good biocompatibility. Finally, the double-network hydrogel was used to compress the L4 nerve root of male sand rats to simulate lumbar disc herniation nerve root compression. The hydrogel remained in its original position after compression, and swelled with increasing time. Edema appeared around the nerve root and disappeared 3 weeks after operation. This chitosan/polyacrylamide double-network hydrogel has potential as a new implant material for animal models of lumbar nerve root compression. All animal experiments were approved by the Animal Ethics Committee of Neurosurgical Institute of Beijing, Capital Medical University, China(approval No. 201601006) on July 29, 2016.

DISTRIBUTED OPTIMAL LOCAL DOUBLE LOOP NETWORK

A distibuted optimal local double loop(DOLDL) network is presented. Emphasis is laid on the topology and distributed routing algorithms for the DOLDL. On the basis of building an abstract model, a set of definitions and theorems are described and proved. An algorithm which can optimize the double loop networks is presented. The optimal values of the topologic parameters for the DOLDL have been obtained by the algorithm, and these numerical results are analyzed. The study shows that the bounds of the optimal diameter (d) and average hop distance (a) for this class of networks are [square-root 3N -2] less-than-or-equal-to d less-than-or-equal-to [square-root 3N+1] and (5N/9(N-1)) (square-root 3N-1.8) < a < (5N/9 (N-1)). (square-root 3N - 0.23), respectively (N is the number of nodes in the network. (3 less-than-or-equal-to N less-than-or-equal-to 10(4)). A class of the distributed routing algorithms for the DOLDL and the implementation procedure of an adaptive fault-tolerant algorithm are proposed. The correctness of the algorithm has been also verified by simulating.

A practical technique of reverse orbicularis oculi muscle resection with preserved subcutaneous capillary network for double eyelid blepharoplasty

Background: Traditional full-incision double eyelid blepharoplasty has several significant disadvantages, including slow recovery and bilateral asymmetry, which results in high rates of patient dissatisfaction. These problems can be minimized using improved surgical techniques aimed at reducing tissue damage and bleeding, decreasing operation time, and especially at protecting the subcutaneous capillary network during the operation. We therefore aimed to guard the capillary network and reduce intraoperative bleeding using the practical technique of reverse orbicularis oculi muscle resection.Methods: Fifty cases of double eyelid blepharoplasty with traditional full-incision(group A) and 61 cases of reverse double eyelid blepharoplasty with a preserved capillary network(group B) were divided into two groups from October 1 to December 31, 2021 and from March 1 to May 31, 2022, respectively. The orbicularis oculi muscle was removed reversely from the front of the tarsal plate using double eyelid blepharoplasty, and the muscular membrane and subcutaneous capillary network were preserved. The operation time recorded in previous medical records was checked and compared with that of our novel technique. The recovery of double eyelid blepharoplasty was determined at 1, 4, and 12 weeks after the operation and patient satisfaction was also compared with that in previous medical records of patients in group A.Results: The reverse double eyelid blepharoplasty procedure was less complicated and easier to control than the traditional full-incision double eyelid blepharoplasty methodology. The average operation time of the double eyelid blepharoplasty cases with traditional full-incision was significantly greater than that of the cases of reverse double eyelid blepharoplasty with the capillary network preserved(45.68 ± 5.27 min and 31.11 ± 5.58 min,respectively;t=14.018 9, P=0.000 0). Patient satisfaction was 42% and 78.69%, respectively, at 1 week postoperation(χ~2=15.724 8, P=0.000 1), 62% and 90.16% at 4 weeks post-operation(χ~2=12.490 2, P=0.000 4),and 90% and 95.08%, at 12 weeks post-operation(χ~2=1.061 1, P=0.303 0).Conclusion: Reverse double eyelid blepharoplasty with preserved subcutaneous capillary network effectively decreases the operation time and improves post-operative patient satisfaction. It is a double eyelid blepharoplasty method worthy of popularization.