Developable polynomial surface approximation to smooth surfaces for fabrication parameters of a large curved shell plate by Differential Evolution

This paper presents a simple and efficient method to approximate a developable surface to a compound design surface by a polynomial. It is required to predict a final shape of roll bending in the fabrication of a curved shell plate. The roll bending process usually makes the cylindrical or conical curvature from an initial flat plate. It means that the final shape is developable or the surface representation has zero Gaussian curvature. The fabrication shape is important in order to estimate process parameters of roller bending.An optimization problem is formulated to determine the polynomial surface which is in the closest proximity to the design surface or the given shell plate, which is subjected to developability. The results and the efficiency of this algorithm are verified and evaluated by applying it to some shell plates which are obtained from a real ship model. The predicted bending shape becomes fundamental information in determining more process parameters for the fabrication of a compound curved shell plate.     

Effect of deposition temperature on dielectric properties of PECVD Ta2O5 thin film

Tantalum oxide film formation by plasma-enhanced chemical vapour deposition (PECVD) using TaCl₅ as a source material was examined. The effects of deposition temperature on the formation, structure and electric properties of the Ta₂O₅ film were investigated for Al/Ta₂O₅/ p-Si (MTS) capacitors. The deposition rate and refractive index increased with increasing deposition temperature. It was found that the structure of Ta₂O₅ deposited by PECVD was amorphous as-deposited. However, crystalline -Ta₂O₅ of hexagonal structure was formed by a 700 °C, 1 h heat treatment in argon. Capacitance and relative dielectric constant of the PECVD Ta₂O₅ were found to be 2.54 fF m^–2 and 23.5, respectively. The PECVD films obtained in this study have higher dielectric constants and remarkably better general film characteristics than those obtained by other deposition methods.     

The expanding small heat-shock protein family, and structure predictions of the conserved "alpha-crystallin domain"

The ever-increasing number of proteins identified as belonging to the family of small heat-shock proteins (shsps) and alpha-crystallins enables us to reassess the phylogeny of this ubiquitous protein family. While the prokaryotic and fungal representatives are not properly resolved, most of the plant and animal shsps and related proteins are clearly grouped in distinct clades, reflecting a history of repeated gene duplications. The members of the shsp family are characterized by the presence of a conserved homologous "alpha-crystallin domain," which sometimes is present in duplicate. Predictions are made of secondary structure and solvent accessibility of this domain, which together with hydropathy profiles and intron positions support the presence of two similar hydrophobic beta-sheet-rich motifs, connected by a hydrophilic alpha-helical region. Together with an overview of the newly characterized members of the shsp family, these data help to define this family as being involved as stable structural proteins and as molecular chaperones during normal development and induced under pathological and stressful conditions.     

Room-Temperature-Processable Highly Reliable Resistive Switching Memory with Reconfigurability for Neuromorphic Computing and Ultrasonic Tissue Classification

Reversible metal-filamentary mechanism has been widely investigated to design an analog resistive switching memory (RSM) for neuromorphic hardware-implementation. However, uncontrollable filament-formation, inducing its reliability issues, has been a fundamental challenge. Here, an analog RSM with 3D ion transport channels that can provide unprecedentedly high reliability and robustness is demonstrated. This architecture is realized by a laser-assisted photo-thermochemical process, compatible with the back-end-of-line process and even applicable to a flexible format. These superior characteristics also lead to the proposal of a practical adaptive learning rule for hardware neural networks that can significantly simplify the voltage pulse application methodology even with high computing accuracy. A neural network, which can perform the biological tissue classification task using the ultrasound signals, is designed, and the simulation results confirm that this practical adaptive learning rule is efficient enough to classify these weak and complicated signals with high accuracy (97%). Furthermore, the proposed RSM can work as a diffusive-memristor at the opposite voltage polarity, exhibiting extremely stable threshold switching characteristics. In this mode, several crucial operations in biological nervous systems, such as Ca²⁺ dynamics and nonlinear integrate-and-fire functions of neurons, are successfully emulated. This reconfigurability is also exceedingly beneficial for decreasing the complexity of systems—requiring both drift- and diffusive-memristors.     

Towards Sustainable Agricultural Systems: A Lightweight Deep Learning Model for Plant Disease Detection

A country’s economy heavily depends on agricultural development. However, due to several plant diseases, crop growth rate and quality are highly suffered. Accurate identification of these diseases via a manual procedure is very challenging and time-consuming because of the deficiency of domain experts and low-contrast information. Therefore, the agricultural management system is searching for an automatic early disease detection technique. To this end, an efficient and lightweight Deep Learning (DL)-based framework (E-GreenNet) is proposed to overcome these problems and precisely classify the various diseases. In the end-to-end architecture, a MobileNetV3Small model is utilized as a backbone that generates refined, discriminative, and prominent features. Moreover, the proposed model is trained over the PlantVillage (PV), Data Repository of Leaf Images (DRLI), and a new Plant Composite (PC) dataset individually, and later on test samples, its actual performance is evaluated. After extensive experimental analysis, the proposed model obtained 1.00%, 0.96% and 0.99% accuracies on all three included datasets. Moreover, the proposed method achieves better inference speed when compared with other State-Of-The-Art (SOTA) approaches. In addition, a comparative analysis is conducted where the proposed strategy shows tremendous discriminative scores as compared to the various pre-trained models and other Machine Learning (ML) and DL methods.     

Spontaneously Embedded Scattering Structures in a Flexible Substrate for Light Extraction

A flexible hazy substrate (FHS) with embedded air bubbles to increase light extraction efficiency of organic light‐emitting diodes (OLEDs) is reported. In order to embed the air bubbles in the flexible substrate, micropatterned substrates are fabricated by plasma treatment, and then coated with a planarization layer. During the planarization layer coating, air bubbles are trapped between the substrate and the planarization layer. The haze of the FHS can be controlled from 1.7% to 68.4% by changing the size of micropatterns by adjusting the plasma treatment time. The FHS shows average haze of 68.4%, average total transmittance of 90.3%, and extremely flat surface with average roughness (R _a) of 1.2 nm. Rigorous coupled‐wave analysis and finite‐difference time‐domain simulations are conducted to demonstrate that the air bubbles in the substrate can effectively extract photons that are trapped in the substrate. The FHS increases the power efficiency of OLEDs by 22% and further increases by 91% combined with an external extraction layer. Moreover, the FHS has excellent mechanical flexibility. No defect has been observed after 10 000 bending cycles at bending radius of 4 mm.     

Effect of stents coated with a combination of sirolimus and alpha-lipoic acid in a porcine coronary restenosis model

The aim of this study was to evaluate antiproliferative sirolimus- and antioxidative alpha-lipoic acid (ALA)-eluting stents using biodegradable polymer [poly-l-lactic acid (PLA)] in a porcine coronary overstretch restenosis model. Forty coronary arteries of 20 pigs were randomized into four groups in which the coronary arteries had a bare metal stent (BMS, n = 10), ALA-eluting stent with PLA (AES, n = 10), sirolimus-eluting stent with PLA (SES, n = 10), or sirolimus- and ALA-eluting stent with PLA (SAS, n = 10). A histopathological analysis was performed 28 days after the stenting. The ALA and sirolimus released slowly over 30 days. There were no significant differences between groups in the injury or inflammation score; however, there were significant differences in the percent area of stenosis (56.2 ± 11.78 % in BMS vs. 51.5 ± 12.20 % in AES vs. 34.7 ± 7.23 % in SES vs. 28.7 ± 7.30 % in SAS, P < 0.0001) and fibrin score [1.0 (range 1.0–1.0) in BMS vs. 1.0 (range 1.0–1.0) in AES vs. 2.0 (range 2.0–2.0) in SES vs. 2.0 (range 2.0–2.0) in SAS, P < 0.0001] between the four groups. The percent area of stenosis based on micro-computed tomography corresponded with the restenosis rates based on histopathological stenosis in different proportions in the four groups (54.8 ± 7.88 % in BMS vs. 50.4 ± 14.87 % in AES vs. 34.5 ± 7.22 % in SES vs. 28.9 ± 7.22 % in SAS, P < 0.05). SAS showed a better neointimal inhibitory effect than BMS, AES, and SES at 1 month after stenting in a porcine coronary restenosis model. Therefore, SAS with PLA can be a useful drug combination for coronary stent coating to suppress neointimal hyperplasia.