Dual Layer Research Articles

Biomimetic tubular materials: from native tissues to a unifying view of new vascular, tracheal, gastrointestinal, oesophageal, and urinary grafts.

Repairing tubular tissues-the trachea, the esophagus, urinary and gastrointestinal tracts, and the circulatory system-from trauma or severe pathologies that require resection, calls for new, more effective graft materials. Currently, the relatively narrow family of materials available for these applications relies on synthetic polymers that fail to reproduce the biological and physical cues found in native tissues. Mimicking the structure and the composition of native tubular tissues to elaborate functional grafts is expected to outperform the materials currently in use, but remains one of the most challenging goals in the field of biomaterials. Despite their apparent diversity, tubular tissues share extensive compositional and structural features. Here, we assess the current state of the art through a dual layer model, reducing each tissue to an inner epithelial layer and an outer muscular layer. Based on this model, we examine the current strategies developed to mimic each layer and we underline how each fabrication method stands in providing a biomimetic material for future clinical translation. The analysis provided here, addressed to materials chemists, biomaterials engineers and clinical staff alike, sets new guidelines to foster the elaboration of new biomimetic materials for effective tubular tissue repair.

Construction of pyridine-functionalized metal-organic frameworks for the detection of flazasulfuron.

Two novel Cu-based metal-organic frameworks (MOFs), namely, poly[[aquadichlorido[μ4-4'-(pyridin-4-yl)-[2,2':6',2''-terpyridine]-4,4''-dicarboxylato][μ3-4'-(pyridin-4-yl)-[2,2':6',2''-terpyridine]-4,4''-dicarboxylato]tricopper(II)] monohydrate], {[Cu3(C22H12N4O4)2Cl2(H2O)]·H2O}n or {[Cu3(PTP)2Cl2(H2O)]·H2O}n, (I), and poly[[diaquabis[μ2-4'-(pyridin-3-yl)-[2,2':6',2''-terpyridine]-4,4''-dicarboxylato]bis(μ2-terephthalato)tricopper(II)] dihydrate], {[Cu3(C22H12N4O4)2(C8H4O4)2(H2O)2]·2H2O}n or {[Cu3(BDC)2(MTP)2(H2O)2]·2H2O}n, (II), have been synthesized successfully with 4'-(pyridin-4-yl)-[2,2':6',2''-terpyridine]-4,4''-dicarboxylic acid (H2PTP) and 4'-(pyridin-3-yl)-[2,2':6',2''-terpyridine]-4,4''-dicarboxylic acid (H2MTP) as the ligands, respectively. Crystal structure analysis reveals that (II) possesses a 2D coordinated layer structure, in which adjacent 2D coordination layers are linked into 3D frameworks through π-π interactions, while the structure of (I) displays dual coordination layers, in which adjacent coordination layers are connected into a 3D framework through hydrogen-bonding interactions. The photophysical properties of the two MOFs were investigated by fluorescence spectroscopy. Complex (II) shows an obvious `turn-on' fluorescence enhancement effect towards flazasulfuron and its potential application for sensing flazasulfuron in water with high selectivity and sensitivity was also investigated in detail.

Influence of Dual Layer Confinement of Stone Column Material on the Shear Modulus of the Soil-Column Combined System

Influence of Dual Layer Confinement of Stone Column Material on the Shear Modulus of the Soil-Column Combined System

A hierarchical active inference model of spatial alternation tasks and the hippocampal-prefrontal circuit

Cognitive problem-solving benefits from cognitive maps aiding navigation and planning. Physical space navigation involves hippocampal (HC) allocentric codes, while abstract task space engages medial prefrontal cortex (mPFC) task-specific codes. Previous studies show that challenging tasks, like spatial alternation, require integrating these two types of maps. The disruption of the HC-mPFC circuit impairs performance. We propose a hierarchical active inference model clarifying how this circuit solves spatial interaction tasks by bridging physical and task-space maps. Simulations demonstrate that the model’s dual layers develop effective cognitive maps for physical and task space. The model solves spatial alternation tasks through reciprocal interactions between the two layers. Disrupting its communication impairs decision-making, which is consistent with empirical evidence. Additionally, the model adapts to switching between multiple alternation rules, providing a mechanistic explanation of how the HC-mPFC circuit supports spatial alternation tasks and the effects of disruption.

Research on stacking ensemble method for day-ahead ultra-short-term prediction of photovoltaic power

The intermittency and uncertainty of photovoltaic power output make it difficult to match real-time electricity demand, and accurate prediction of photovoltaic power is the basis for improving photovoltaic energy consumption. This article proposes a new stacking ensemble forecast model based on the time series generative adversarial network (TimeGAN-SEFM), to improve the accuracy of ultra-short-term forecasting of photovoltaic power. Firstly, a dual layer feature weighted clustering weighted fuzzy C-means clustering algorithm is proposed to accurately partition the original dataset according to weather types. Secondly, in the proposed TimeGAN-SEFM, a Particle Swarm Optimization based BP neural network is used as a meta learner to integrate three types of base learners, thereby improving the structural diversity of the model. The dataset for each type of weather is proportionally divided into multiple sub-datasets for training base learners. In response to the limitation that the amount of data used for training a single base learner is relatively small after multiple splitting of the original data, a TimeGAN augmentation network is introduced to perform multi-dimensional data augmentation on the sub-training sets, which improves the size and diversity of the dataset used for training base learners, thereby improving the predictive performance of the model. Finally, the predictive performance of the proposed TimeGAN-SEFM was evaluated using measurement data from a 20 MW photovoltaic power station in North China. The results show that TimeGAN-SEFM effectively improves the accuracy of photovoltaic prediction and helps promote real-time matching of photovoltaic energy and power demand, thereby improving the utilization of photovoltaic energy.

Simultaneous Modulation on Solvation Shell and Electrode Interface for Reversible Zinc Anode Realized by a Mutiplefunctional Additive

AbstractThe inferior reversibility of Zn metal anode caused by undesired Zn dendrite and severe interfacial side reactions has to be addressed for the commercial application of Zinc ion batteries (ZIBs). Here, a multiple functional sodium benzaldehyde 2,4‐disulfonate(B24DADS) additives with various blocks of polar sulfonate group, Lewis basic aldehyde groups, and hydrophobic benzene ring is proposed to regulate the solvation structure of Zn2+, construct an H2O‐poor and zincophilic dual electric layer structure, and create a passive SEI on the Zn anode surface, thus restaining dendrite growth and interfacial side reactions. Furthermore, uniform deposition mechanics of the Zn are revealed by the synergistic effect of induced deposition, additive‐derived SEI formation, and texture regulation. In addition, Na+ can also limit the growth of zinc dendrites based on electrostatic shielding mechanisms. Therefore, the multifunctional B24DADS additive grants the anode to deliver remarkable electrochemical performance. Under critical test conditions (20 mA cm−2/20 mAh cm−2), the zinc provides superior long cycling (3700 h) with a low polarization voltage (0.02 V). B24DADS containing electrolyte is well matched with manganese dioxide cathode. This effort renders a promising way to explore advanced additives with unique molecular structures for addressing zinc dendrite growth and rampant side effects.

Ionic liquid (1-Ethyl-3-methylimidazolium tricyanomethanide) incorporated corn starch polymer electrolyte for solar cell and supercapacitor application

Taking into account energy demand a new highly conducting ionic liquid (IL) c (EmImTCM) mixed corn starch (CS) biopolymer electrolyte is synthesized for dual electrochemical application electric double layer capacitor (EDLC) and the dye-sensitized solar cell (DSSC) application. Electrical, structural, thermal, and optical studies are carried out in detail and presented in this communication. Maximum conducting IL-incorporated biopolymer electrolyte film has been sandwiched between electrodes to develop EDLC and DSSC. The sandwich-structured EDLC delivers a high specific capacitance of 250 F/gram while DSSC shows 1.44 % efficiency at one sun condition.

A Low-Dropout Regulator Integrated With E-mode IGZO and D-mode ITO/IGZO Dual Layer Thin Film Transistors With Superior Uniformity and Stability

A Low-Dropout Regulator Integrated With E-mode IGZO and D-mode ITO/IGZO Dual Layer Thin Film Transistors With Superior Uniformity and Stability

A comparative study between condensed polytetrafluoroethylene hernia mesh versus other composite meshes in Endo-laparoscopic ventral hernia repair

IntroductionLaparoscopic ventral hernia mesh repair (LVHR) is gaining popularity possibly due to reduced complications, reduced hospital stay, early return to work and better cosmesis. In intra-peritoneal onlay method (IPOM) a dual layer composite mesh with an absorbable barrier on the visceral surface is used for minimising bowel adhesions. Three most popular prosthetic mesh scaffolds are polypropylene (PP), polyester and expanded polytetrafluoroethylene (ePTFE). A new generation of monolayer condensed polytetrafluoroethylene (cPTFE) Omyra® mesh, which theoretically has better tissue integration with parietal tissue and possibly lesser adhesions with visceral organs is now available for use. ObjectiveThe aim of our study is to assess the safety and efficacy of Omyra (cPTFE) mesh versus other mesh types in LVHR. MethodWe retrospectively collected data from 62 patients who underwent LVHR using cPTFE, as well as other mesh types from January 1, 2011 to December 31, 2020. Patient demographics, Hernia Characteristics, perioperative events, postoperative results and complications were documented and analysed. ResultsAmong the 62 patients studied, there were 27 (43.55 %) in the Omyra group and 35 (56.45 %) in the other synthetic meshes group. The mean age of the Omyra group was 53.19 (31–85) and 55.03 (22–81) for the other synthetic meshes group. There were no differences in terms of patient demographics and major comorbidities. At presentation, the indication was more commonly for recurrence (p = 0.043), and patients were more symptomatic (p = 0.0034) in the Omyra group than the other synthetic meshes group. There were no differences in mean operating time, post-operative recovery and complications, as well as early (<30 days) and late (>30 days) complications during follow up. ConclusionThe use of cPTFE (Omyra™) mesh yielded comparable operative characteristic compared to other synthetic meshes for LVHR. The rate of perioperative complications and early recurrence was similar between Omyra and other synthetic meshes group.

Sustainable package design for efficient pomegranate cold chain: Enhancing storage space, sea freight efficiency, material sustainability, and energy conservation

This study evaluated the performance of a novel fabricated dual layer ventilated packaging (carton) design for pomegranate fruit. The study argues that higher process throughput, storage space usage (higher cargo density) and packaging material usage can be achieved through systematic design of packaging. The mechanical strength, fruit cooling speeds, and quality preservation characteristics of the new and existing carton designs were evaluated in a controlled laboratory environment. The new carton design achieved 22 % above minimum recommended industry compression strength, confirming its stacking safety during palletization. Fruit packed inside both carton designs attained an average respiration rate of 5.66 ± 1.23 mL CO2 kg−1 h−1 during cold storage. Fruit decay incidence (average 5.5 %), colour changes and sensory attributes were also similar in both carton designs after 12 weeks cold storage and 2 weeks ambient storage period. Finally, fresh pomegranate fruit (cv. Wonderful) were packed in the new and commercial package designs, palletized, containerized and exported from South Africa to Germany. The novel dual layer design had a higher freight density (1720 kg more fruit per reefer) compared to the commercial counterpart. It also improved the precooling process throughput (13 % faster), reduced carton material usage (40 %), and reduced energy usage (13 %). These advantages of the new dual layer ventilated packaging can be implemented with considerable sustainability benefits.

Performance optimization of MA0.5FA0.5PbI3/CsPbI3 based hybrid perovskite solar cell emphasizing on double absorber layer

Abstract The utilization of cesium-based lead halide (CsPbI3) PSC has considerable potential in the photovoltaic industry due to their high efficiency, underpinned by features such as a high absorption coefficient, thermal stability, and commendable efficiency. Nevertheless, the bandgap of CsPbI3, standing at 1.7 eV, poses a challenge as it is relatively high for a single-junction device. To overcome this limitation, we introduced a dual absorber layer structure by interleaving CsPbI3 with a lead-based hybrid perovskite material, denoted as MA0.5FA0.5PbI3. This investigation focused on the MA0.5FA0.5PbI3/CsPbI3 hetero-junction structure to ascertain the maximum possible efficiency. Therefore, this study proposed a PSC with the configuration of Ag/MoO3/MA0.5FA0.5PbI3/CsPbI3/IGZO/Au. In this setup, MoO3 (Molybdenum Trioxide) is used as the HTL and IGZO (Indium Gallium Zinc Oxide) as the ETL. Silver (Ag) serves as the back contact and gold (Au) is the front contact. This device demonstrated remarkable characteristics with Voc = 1.307 V, Jsc = 22.71 mA cm−2, FF = 86.58%, and η = 26.21%, showcasing a substantial improvement compared to previously reported CsPbI3-based homojunction PSCs. Furthermore, this study delved into the effects of absorber doping, absorber material thickness, bulk defect, and interfacial defects on solar cell parameters to obtain high-performance solar cells.

Interplay between Overt and Covert Progressions: A Rereading of Father and Son Imagery in “Barn Burning”

There is a key consensus among scholars both domestically and internationally that &amp;ldquo;barn burning&amp;rdquo; is a story of growing up with the protagonist Sarty breaking away from his father&amp;rsquo;s control and turning towards order and law, while his father is depicted as a violent and unstable person using barn burning to resolve conflicts, which is seen as extreme and radical. This is indeed the direction of plot development. However, behind the public plot lies another hidden and parallel narrative process. In this apparent progress, Sarty was proven to be cowardly, vain, and selfish, and her father&amp;rsquo;s act of burning the barn was actually the only twisted means for a humiliated and oppressed civilian to maintain his distorted sense of dignity. The images of both father and son were overturned, and upon realizing this dual narrative process, the characters transformed from mundane and singular to rounded and multifaceted. The work itself has become rich from being direct. Only by examining the significance of this dual layer can we fully understand the complexity and richness of the story&amp;rsquo;s meaning.

Nanocatalysis of silver-nanobioprobe based supersensitive electrochemical detection of Salmonella serotypes targeting virulence protein

Herein, we report a supersensitive and specific detection of Salmonella employing nanocatalysis of silver nanoparticle (AgNp). A nanobioprobe was developed employing specific antibody (Ab) that binds to a peptide present in transmembrane protein of Salmonella. We have studied 7 surface-exposed peptide hits from conserved virulence proteins (PagC, ST50, PagN, CdtB and FliC). These peptides were experimentally evaluated by BLI (Bio layer interferometry) for their reactivity towards antisera raised against an admix of major Salmonella serogroups. The most promising peptide was used to generate Ab with binding affinity Kd of 5.6 × 10−9 M. The Ab exhibited high specificity towards entire Salmonella serotypes prevalent in foods, as illustrated by FACS (Fluorescence-activated cell sorting) study. The Ab-AgNp probe was blocked with a dual layer to prevent non-specific interactions, confirmed by employing BLI and TEM (Transmission electron microscopy). For the electrochemical detection, the autonanocatalysis of AgNp in presence of H2O2 was used to generate numerous Ag+ resulting in an amplified signal that could detect 10 cells/mL. The relative standard deviation (RSD) was observed to be 4.5%. The platform achieved recovery of 100–112% calculated for 102 cells/mL. The performance was validated in milk, buffer peptone water (BPW) and tap water by spiking studies. The study highlights the effectiveness of efficiently blocked AgNp-mediated probes for the highly selective and sensitive detection of Salmonella, representing a significant advancement in bacterial sensing.

Attention Induced Dual Convolutional-Capsule Network (AIDC-CN): A deep learning framework for motor imagery classification

In recent times, Electroencephalography (EEG)-based motor imagery (MI) decoding has garnered significant attention due to its extensive applicability in healthcare, including areas such as assistive robotics and rehabilitation engineering. Nevertheless, the decoding of EEG signals presents considerable challenges owing to their inherent complexity, non-stationary characteristics, and low signal-to-noise ratio. Notably, deep learning-based classifiers have emerged as a prominent focus for addressing the EEG signal decoding process. This study introduces a novel deep learning classifier named the Attention Induced Dual Convolutional-Capsule Network (AIDC-CN) with the specific aim of accurately categorizing various motor imagination class labels. To enhance the classifier’s performance, a dual feature extraction approach leveraging spectrogram and brain connectivity networks has been employed, diversifying the feature set in the classification task. The main highlights of the proposed AIDC-CN classifier includes the introduction of a dual convolution layer to handle the brain connectivity and spectrogram features, addition of a novel self-attention module (SAM) to accentuate the relevant parts of the convolved spectrogram features, introduction of a new cross-attention module (CAM) to refine the outputs obtained from the dual convolution layers and incorporation of a Gaussian Error Linear Unit (GELU) based dynamic routing algorithm to strengthen the coupling among the primary and secondary capsule layers. Performance analysis undertaken on four public data sets depict the superior performance of the proposed model with respect to the state-of-the-art techniques. The code for this model is available at https://github.com/RiteshSurChowdhury/AIDC-CN.

Rural Road Extraction in Xiong'an New Area of China Based on the RC-MSFNet Network Model.

High-resolution remote sensing imagery, reaching meter or sub-meter levels, provides essential data for extracting and identifying road information. However, rural roads are often narrow, elongated, and have blurred boundaries, with textures that resemble surrounding environments such as construction sites, vegetation, and farmland. These features often lead to incomplete extraction and low extraction accuracy of rural roads. To address these challenges, this study introduces the RC-MSFNet model, based on the U-Net architecture, to enhance rural road extraction performance. The RC-MSFNet model mitigates the vanishing gradient problem in deep networks by incorporating residual neural networks in the downsampling stage. In the upsampling stage, a connectivity attention mechanism is added after dual convolution layers to improve the model's ability to capture road completeness and connectivity. Additionally, the bottleneck section replaces the traditional dual convolution layers with a multi-scale fusion atrous convolution module to capture features at various scales. The study focuses on rural roads in the Xiong'an New Area, China, using high-resolution imagery from China's Gaofen-2 satellite to construct the XARoads rural road dataset. Roads were extracted from the XARoads dataset and DeepGlobe public dataset using the RC-MSFNet model and compared with some models such as U-Net, FCN, SegNet, DeeplabV3+, R-Net, and RC-Net. Experimental results showed that: (1) The proposed method achieved precision (P), intersection over union (IOU), and completeness (COM) scores of 0.8350, 0.6523, and 0.7489, respectively, for rural road extraction in Xiong'an New Area, representing precision improvements of 3.8%, 6.78%, 7.85%, 2.14%, 0.58%, and 2.53% over U-Net, FCN, SegNet, DeeplabV3+, R-Net, and RC-Net. (2) The method excelled at extracting narrow roads and muddy roads with unclear boundaries, with fewer instances of omission or false extraction, demonstrating advantages in complex rural terrain and areas with indistinct road boundaries. Accurate rural road extraction can provide valuable reference data for urban development and planning in the Xiong'an New Area.

Ultrasonic Guided Wave Health Monitoring of High-Temperature Aircraft Structures Based on Variational Mode Decomposition and Fuzzy Entropy

This paper presents an innovative approach to high-temperature health monitoring of aircraft structures utilizing an ultrasonic guided wave transmission and reception system integrated with a zirconia heat buffer layer. Aiming to address the challenges posed by environmental thermal noise and the installation of heat buffers, which can introduce structural nonlinearities into guided wave signals, a composite guided wave consisting of longitudinal and Lamb waves was proposed for online damage detection within thermal protection systems. To effectively analyze these complex signals, a hybrid damage monitoring technique combining variational mode decomposition (VMD) and fuzzy entropy (FEN) was introduced. The VMD was employed to isolate the principal components of the guided wave signals, while the fuzzy entropy of these components served as a quantitative damage factor, characterizing the extent of the structural damage. Furthermore, this study validated the feasibility of piezoelectric probes equipped with heat buffer layers for both exciting and receiving ultrasonic guided wave signals in a dual heat buffer layer, a one-transmit-one-receive configuration. The experimental results demonstrated the efficacy of the proposed VMD-FEN damage factor for real-time monitoring of damage in aircraft thermal protection systems, both at ambient and elevated temperatures (up to 150 °C), showcasing its potential for enhancing the safety and reliability of aerospace structures operating under extreme thermal conditions.

A visible transparent infrared microwave compatible stealth metasurface with low infrared emissivity

Abstract This article proposes a visible transparent infrared microwave-compatible stealth metasurface with low infrared emissivity, aiming to integrate visible transparency, low infrared radiation, and broadband microwave absorption. The entire structure consists of a dual layer of infrared shielding layer (IRSL) and microwave absorption layer (MAL). Among them, IRSL adopts a frequency selective surface (FSS) structure with high-duty cycle dielectric-metal-dielectric (DMD) to obtain low infrared emissivity and high microwave transmittance. MAL combines the equivalent circuit method (ECM) and particle swarm optimization algorithm (PSO) to design a circular ring metasurface for broadband microwave absorption. To achieve better absorption performance, a transition layer (TL) is introduced to improve impedance matching between IRSL and MAL. Meanwhile, the use of transparent materials throughout the entire structure has the characteristic of visible transparency. In summary, this article proposes a multiband compatible stealth metasurface design method that can meet the stealth requirements of modern battlefields.

Combating Cl− and SO42−-induced molten salt corrosion by laser cladding FeCrNiMoAl high-entropy alloy coating

FeCrNiMoAl high entropy alloy coating was successfully prepared by laser cladding method with phases of dominant face-centered cubic (FCC) and minor intermetallics (AlFe and AlNi). After 144 h of corrosion in the molten salt mixture of 40 % NaCl + 40 % KCl + 10 % Na2SO4 + 10 % K2SO4 at 600 °C, FeCrNiMoAl exhibited a much lower corrosion rate than conventional Inconel 625 by a reduction of 34 %. XRD and SEM were used to characterize the corroded samples. To combat Cl-induced active corrosion and S-induced sulfidation, Inconel 625 develops a single Cr2O3 layer while FeCrNiMoAl developed dual layers of outer Cr2O3 and inner Al2O3, which effectively prevents penetration of Cl and S.

Surface modification of WE43 Mg alloy via combination of cold spray and micro-arc oxidation for wear related applications at high temperatures

This study investigates the high temperature wear behaviour of a WE43 Mg alloy after covering it with single and dual layer coatings. For this purpose, cold spray and micro-arc oxidation processes were employed individually and sequentially. Single-layer coatings fabricated by cold spray and micro-arc oxidation processes were Al/Al2O3 composite and MgO-based ceramic, respectively. Sequential application of cold spray and micro arc oxidation processes induced dual layer coating upon synthesizing an external Al2O3–based layer over the Al/Al2O3 composite layer. Results of the wear tests conducted under the load of 2 N revealed the superior resistance of the dual layer coated sample against the rubbing action of the counterface compared to single layer coatings. Thus, the presence of a relatively hard and tough external Al2O3-based layer over the Al/Al2O3 composite layer sustained protection up to the temperature of 320 °C, where the dominant wear mechanism was fatigue wear. However, the increase in the test temperature to 350 °C caused detachment of the external Al2O3-based layer. Reduction of the wear test load from 2 to 1 N resulted in the remaining of external Al2O3-based layer intact with the underlying Al/Al2O3 composite layer even at a test temperature of 350 °C. It is therefore concluded that the combination of cold spray and micro-arc oxidation processes is promising to broaden the reliable use of WE43 and other Mg alloys in wear related applications at high service temperatures.

Lithiophilic Protective Dual Layer Enabling Stable Electrodeposition of Lithium at High Current Density

Lithium (Li) is an ideal anode material for rechargeable batteries and thus manufacturing Li metal is crucial for the practical development of Li metal batteries. Electrodeposition is an efficient technique for producing ultrathin and scalable Li metal electrodes. However, the dendritic growth and the side reactions of Li with electrolyte during the electrodeposition are the main obstacles to overcome. In this study, we designed a pre-coated protective dual layer (PDL) composed of a poly(ethylene oxide)-based solid polymer electrolyte (SPE) and a polydopamine-coated cellulose membrane (PD-CM). The adhesive and ion-conductive SPE layer suppressed the growth of Li dendrites and side reactions with liquid electrolyte. The PD-CM layer with high porosity and lithiophilicity promoted a facile and uniform Li-ion flux. By applying the pre-coated PDL, Li was uniformly electrodeposited on the Ag-coated Cu at a high current density of 6 mA cm−2. The Li/LiFePO4 cell composed of an electrodeposited Li anode with PDL and a LiFePO4 cathode was assembled without an additional separator, and its cycling performance was evaluated. The cell initially delivered a high discharge capacity of 154.8 mAh g−1 at 45 °C and exhibited excellent cycling stability with a capacity retention of 97.0% after 200 cycles.