Patterning Technique Research Articles

Software design pattern selection approaches: A systematic literature review

AbstractSoftware design patterns have a considerable impact on the software development life cycle. Design pattern (DP) is a reliable and reusable solution provided by software experts to obtain quality software design. However, due to the large number of design patterns, selecting the appropriate one is quite difficult. To overcome this difficulty, several approaches with different methods have been presented to suggest the appropriate DP. Despite conducting a number of studies that have explored some aspects of this field, such as design pattern selection tools and techniques, there is a need for a deeper understanding, analysis, classification, and thorough review of the design pattern selection process. So far, no systematic review of design pattern selection approaches is available. This paper aims to classify existing approaches, provide several criteria for comparing approaches, analyze each one, and identify and analyze the most important elements in this field, including open issues, data sets, and so on. The present investigation paper will help future research to employ the existing approaches taking into account the specification of each one and it also raises awareness about the approaches used in previous research and their potential limitations.

All-inorganic lead halide perovskite nanocrystals applied in advanced display devices.

Advanced display devices are in greater demand due to their large color gamut, high color purity, ultrahigh visual resolution, and small size pixels. All-inorganic lead halide perovskite (AILHP) nanocrystals (NCs) possess inherent advantages such as narrow emission width, saturated color, and flexible integration, and have been developed as functional films, light sources, backlight components, and display panels. However, some drawbacks still restrict the practical application of advanced display devices based on AILHP NCs, including working stability, large-scale synthesis, and cost. In this review, we focus on AILHP NCs, review the recent progress in materials synthesis, stability improvement, patterning techniques, and device application. We also highlight the important role of materials systems in creating advanced display devices, followed by the challenges and opportunities in industrial processes. This review provides beneficial inspiration for the future development of AILHP NCs in colorful and white backlight, as well as high resolution full-color displays.

EXACT FORMULA OF DISTANCE SUMS ON SIERPIŃSKI SKELETON NETWORKS

The aim of this paper is to illustrate a strategy for how to get the exact formula of the distance sums of fractal networks (for example, the Sierpiń ski skeleton networks) with the technique of finite pattern [S. Wang, Z. Yu and L. Xi, Average geodesic distance of Sierpinski gasket and Sierpinski networks, Fractals 25(5) (2017) 1750044].

Ultrathin Glass-Based Wafer-Level Integration for Miniaturized Hermetic MEMS Application

In this article, a glass-based hermetic structure has been packaged at wafer level with a thickness thinner than 200 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> and a size smaller than 1 mm2, showing the prospective way to realize the miniaturization of microelectromechanical systems (MEMS) with high throughput. For the development of this novel wafer-level packaging platform, material selection of metal wire was studied. Next, the technique of metal patterning on the cavity structure was demonstrated for the fabrication of seal ring and electrical connection simultaneously. At last, the ultrathin hermetic structure was sealed by metal-to-metal bonding at wafer level. These technologies can be widely used in advanced miniaturized packaging applications for next-generation electronic components.

Comparing Local Binary Pattern and Gray Level Co-occurrence Matrix for Feature Extraction in Diabetic Retinopathy Classification

Diabetic retinopathy, a condition characterized by retinal damage and vision loss, is a prevalent complication of diabetes arising from elevated blood sugar levels. With a growing number of individuals affected, efficient and accurate diagnosis is crucial. This study aims to implement and compare the Local Binary Pattern (LBP) and Gray Level Co-occurrence Matrix (GLCM) feature extraction techniques, which have demonstrated success in prior research. The comparison will provide a comprehensive under- standing of the image features, extract relevant data, and improve the performance of the image analysis pipeline for diabetic retinopathy classification. The result showed that from three scenarios the best accuracy provided by Support Vector Machine with the accuracy score between 73% until 74%, however, other algorithm have little difference which the result on 73%.

Multi-class EEG signal classification with statistical binary pattern synergic network for schizophrenia severity diagnosis

&lt;abstract&gt; &lt;p&gt;Electroencephalography (EEG) is a widely used medical procedure that helps to identify abnormalities in brain wave patterns and measures the electrical activity of the brain. The EEG signal comprises different features that need to be distinguished based on a specified property to exhibit recognizable measures and functional components that are then used to evaluate the pattern in the EEG signal. Through extraction, feature loss is minimized with the embedded signal information. Additionally, resources are minimized to compute the vast range of data accurately. It is necessary to minimize the information processing cost and implementation complexity to improve the information compression. Currently, different methods are being implemented for feature extraction in the EEG signal. The existing methods are subjected to different detection schemes that effectively stimulate the brain signal with the interface for medical rehabilitation and diagnosis. Schizophrenia is a mental disorder that affects the individual's reality abnormally. This paper proposes a statistical local binary pattern (SLBP) technique for feature extraction in EEG signals. The proposed SLBP model uses statistical features to compute EEG signal characteristics. Using Local Binary Pattern with proposed SLBP model texture based on a labeling signal with an estimation of the neighborhood in signal with binary search operation. The classification is performed for the earlier-prediction shizophrenia stage, either mild or severe. The analysis is performed considering three classes, i.e., normal, mild, and severe. The simulation results show that the proposed SLBP model achieved a classification accuracy of 98%, which is ~12% higher than the state-of-the-art methods.&lt;/p&gt; &lt;/abstract&gt;

Application of Computer Aided Design (CAD) and Flat Techniques in Teaching Pattern Drafting by Clothing Lecturers in Universities in South East, Nigeria

The purpose of the study was to investigate the application of computer aided design (CAD) and Flat techniques in teaching pattern drafting by clothing lecturers in Universities in South East, Nigeria. The population for the study was 48 lecturers. The entire number of Clothing lecturers in the above three universities were used because of the manageable size. A questionnaire was utilized for data collection (0.94 Cronbach’s alpha). Data collected were analyzed using mean and standard deviation. The major findings of the study showed that some of the challenges in the application of CAD and Flat instructional techniques in teaching pattern drafting include lack of skills on the part of the teachers, insufficient numbers of computers and insufficient technical support for teachers, among others. Orientation of teachers on the importance of computer aided design instruction, using blended approach in teaching, and use of another pattern drafting technique among others are strategies to overcoming the challenges of CAD and Flat technique of pattern drafting instruction by Clothing Lecturers. Among the recommendations made was that curriculum planners and lecturers should make effort to adopt the use of CAD as one of the instructional techniques in teaching pattern drafting.

An information encrypted heterogeneous hydrogel with programmable mechanical properties enabled by 3D patterning.

Heterogeneous architectures with defined patterns found in nature have stimulated the burgeoning development of biomimetic materials. However, the construction of soft matter like hydrogels that mimic biological materials with a combination of strong mechanical performance and unique functionality remains difficult. In this work, we developed a simple and adaptable strategy of a 3D printing complex structure within hydrogels utilising all-cellulosic materials (hydroxypropyl cellulose/cellulose nanofibril, HPC/CNF) as ink. The structural integrity of the patterned hydrogel hybrid is ascertained by the interfacial interaction between cellulosic ink and the surrounding hydrogels. Through designing the geometry of the 3D printed pattern, programmable mechanical properties of hydrogels are achieved. In addition, the thermally induced phase separation properties of HPC confer thermally responsive behaviour on patterned hydrogels, providing them potential to be assembled into double information encryption devices and shape-morphing materials. We anticipate that this all-cellulose ink-enabled 3D patterning technique within hydrogels can serve as a promising and sustainable alternative for designing biomimetic hydrogels with desired mechanical properties and functions for a variety of applications.

Recent progress in construction methods and applications of perovskite photodetector arrays.

Metal halide perovskites are considered promising materials for next-generation optoelectronic devices due to their excellent optoelectronic performances and simple solution preparation process. Precise micro/nano-scale patterning techniques enable perovskite materials to be used for array integration of photodetectors. In this review, the device types of perovskite-based photodetectors are introduced and the structural characteristics and corresponding device performances are analyzed. Then, the typical construction methods suitable for the fabrication of perovskite photodetector arrays are highlighted, including surface treatment technology, template-assisted construction, inkjet printing technology, and modified photolithography. Furthermore, the current development trends and their applications in image sensing of perovskite photodetector arrays are summarized. Finally, major challenges are presented to guide the development of perovskite photodetector arrays.

One mode-model in nanostructures with inclined sidewalls applied to nano Fabry-Perot structures

Metasurfaces are engineered with specific shapes and sizes to interact with light in a unique way. By manipulating the design of the metasurface, it is possible to control optical properties of the surface such as its thermal emissivity. However, thin layers patterning techniques can lead to side-wall angles, thus modifying light propagation within the structure. Here, we introduce a one-mode model that fairly describes the propagation of light in structures with inclined sidewalls. We applied this method to two families of plasmonics resonators: nano Fabry-Perot and coupled nano Fabry-Perot with refractory materials ZrC and tungsten.

Acoustic quasi-periodic bioassembly based diverse stem cell arrangements for differentiation guidance.

Arrangement patterns and geometric cues have been demonstrated to influence cell function and fate, which calls for efficient and versatile cell patterning techniques. Despite constant achievements that mainly focus on individual cells and uniform cell patterns, simultaneously constructing cellular arrangements with diverse patterns and positional relationships in a flexible and contact-free manner remains a challenge. Here, stem cell arrangements possessing multiple geometries and structures are proposed based on powerful and diverse pattern-building capabilities of quasi-periodic acoustic fields, with advantages of rich patterns and structures and flexibility in structure modulation. Eight-fold waves' interference produces regular potentials that result in higher rotational symmetry and more complex arrangement of geometric units. Moreover, through flexible modulation of the phase relations among these wave vectors, a wide variety of cellular pattern units are arranged in this potential, such as circular-, triangular- and square-shape, simultaneously. It is proved that these diverse cellular patterns conveniently build human mesenchymal stem cell (hMSC) models, for research on the effect of cellular arrangement on stem cell differentiation. This work fills the gap of acoustic cell patterning in quasi-periodic patterns and shows promising potential in tissue engineering and regenerative medicine.

Femtosecond laser regulatory focus ablation patterning of a fluorescent film up to 1/10 of the scale of the diffraction limit.

Patterned quantum dots (QDs) and perovskites have attracted a great deal of attention in the fabrication of optoelectronic device arrays for transistors, image sensors and displays. However, the resolution of current patterning technologies is insufficient for nanopatterned QDs and perovskites to be integrated in advanced optoelectronic and photonic applications. Herein, we demonstrate a femtosecond laser regulatory focus ablation (FsLRFA) patterning technique of a fluorescent film involving both semiconductor core-shell QDs and perovskite up to 1/10th of the scale of the diffraction limit. Annular lines with a 200 nm-width are obtained after the irradiation of the femtosecond laser. Moreover, the combination of ablated different geometries enables the laser focal spot as brushes for FsLRFA patterning technology to fabricate delicate and programmable patterns on the fluorescent film. This technology with nanoscale resolution and patterning capability paves the road toward highly integrated applications based on QDs and perovskites.

КОММУНИКАТИВНОЕ ВЗАИМОДЕЙСТВИЕ В ЭКСПРЕССИВНЫХ РЕЧЕВЫХ АКТАХ

The wide spread of speech acts theory observed in linguistics of the second half of the XX century allowed to reveal the communicative and pragmatic essence of communicative phenomena. The multidimensional nature of research approaches applied to the analysis of communicants' speech acts led to a deep understanding of the nature of expressive speech acts. The present study systematizes the main milestones of expressions interpretation, their social characteristics, intentionality on the example of the speech act of apology. The purpose of this work is to establish the nature of the interaction of the communicative intentions of the speaker and the listener in the speech act of apology, to clarify the communicative strategies and techniques used to achieve a favorable outcome, to analyze ways of getting optimal combined linguocreative approach with etiquette speech pattern techniques. The material of the study was the theoretical provisions and principles put forward in the works of J.&nbsp;Serl, J.&nbsp;Austin, Y.&nbsp;Habermas, T.&nbsp;Ballmer and V.&nbsp;Brennenstul, G.G.&nbsp;Pocheptsov, Y.D.&nbsp;Apresyan, V.V.&nbsp;Bogdanov, M.Ya.&nbsp;Glovinskaya, A.G.&nbsp;Pospelova, N.I.&nbsp;Formanovskaya et al. In the process of analyzing scientific concepts, methods of description, generalization, formalization, analysis, synthesis were used. The paper emphasizes that expressives, unlike other speech acts, are associated with the expression of the emotional and expressive state of the speaker. It is revealed that the speech act of apology has polyintensionality, is etiquette-oriented, is focused on compliance with social norms and rituals, assumes subordination to the social institution of the listener. The realization of the speech act of apology implies politeness, respect for the partner, consideration of his interests. Among the factors determining the nature of interaction in the speech act of apology, consideration of the social affiliation of the communicants, the discursive context, and the sincerity of the speaker's intentions are mentioned.

Efficacy of Fascial Stretch Therapy: PNF Pattern of Deep Back ARM Line in Patient with Mechanical Neck Pain: A Quasi Experimental Study

Background: Mechanical neck pain is most prevalent in this era, fascia is the soft tissue component of the connectivetissue network that pervades the human body and creates a continuous, three-dimensional structural supportmatrix throughout the entire body .stretching the fascia with the principles of fascial stretch therapy enables us totreat those patients.Methodology: 15 Subjects were assigned in single group and underwent fascial stretch therapy –Proprioceptiveneuromuscular facilitation pattern technique for a period of 1 weeks and this study used a purposeful samplingtechnique to assign patients.Conclusion: The data were analysed using paired T test at 5% level of significance. There was a significantimprovement on pain and range of motion in the group. This study revealed that there is a significant improvementin pain and ROM on subjects who underwent fascial stretch therapy.

Biofunctionalization of Multiplexed Silicon Photonic Biosensors.

Silicon photonic (SiP) sensors offer a promising platform for robust and low-cost decentralized diagnostics due to their high scalability, low limit of detection, and ability to integrate multiple sensors for multiplexed analyte detection. Their CMOS-compatible fabrication enables chip-scale miniaturization, high scalability, and low-cost mass production. Sensitive, specific detection with silicon photonic sensors is afforded through biofunctionalization of the sensor surface; consequently, this functionalization chemistry is inextricably linked to sensor performance. In this review, we first highlight the biofunctionalization needs for SiP biosensors, including sensitivity, specificity, cost, shelf-stability, and replicability and establish a set of performance criteria. We then benchmark biofunctionalization strategies for SiP biosensors against these criteria, organizing the review around three key aspects: bioreceptor selection, immobilization strategies, and patterning techniques. First, we evaluate bioreceptors, including antibodies, aptamers, nucleic acid probes, molecularly imprinted polymers, peptides, glycans, and lectins. We then compare adsorption, bioaffinity, and covalent chemistries for immobilizing bioreceptors on SiP surfaces. Finally, we compare biopatterning techniques for spatially controlling and multiplexing the biofunctionalization of SiP sensors, including microcontact printing, pin- and pipette-based spotting, microfluidic patterning in channels, inkjet printing, and microfluidic probes.

Deep Common Spatial Pattern based Motor Imagery Classification with Improved Objective Function

Survey/review study Deep Common Spatial Pattern Based Motor Imagery Classification with Improved Objective Function Nanxi Yu 1,2, Rui Yang 1, and Mengjie Huang 1,* 1 School of Electrical Engineering, Electronics &amp; Computer Science, University of Liverpool, Liverpool, L69 3BX, United Kingdom 2 Department of Biostatistics, Graduate School of Arts and Sciences, Yale University, New Haven, CT 06511, United States * Correspondence: Mengjie.Huang@liverpool.ac.uk Received: 12 October 2022 Accepted: 28 November 2022 Published: 22 December 2022 Abstract: Common spatial pattern (CSP) technique has been very popular in terms of electroencephalogram (EEG) features extraction in motor imagery (MI)-based brain-computer interface (BCI). Through the simultaneous diagonalization of the covariance matrices, CSP intends to transform data into another mapping with data of different categories having maximal differences in their measures of dispersion. This paper shows the objective function realized by original CSP method could be inaccurate by regularizing the estimated spatial covariance matrix from EEG data by trace, leading to some flaws in the features to be extracted. In order to deal with this problem, a novel deep CSP (DCSP) model with optimal objective function is proposed in this paper. The benefits of the proposed DCSP method over original CSP method are verified with experiments on two EEG based MI datasets where the classification accuracy is effectively improved.

Force and Velocity Analysis of Particles Manipulated by Toroidal Vortex on Optoelectrokinetic Microfluidic Platform.

The rapid electrokinetic patterning (REP) technique has been demonstrated to enable dynamic particle manipulation in biomedical applications. Previous studies on REP have generally considered particles with a size less than 5 μm. In this study, a REP platform was used to manipulate polystyrene particles with a size of 3~11 μm in a microfluidic channel sandwiched between two ITO conductive glass plates. The effects of the synergy force produced by the REP electrothermal vortex on the particle motion were investigated numerically for fixed values of the laser power, AC driving voltage, and AC driving frequency, respectively. The simulation results showed that the particles were subject to a competition effect between the drag force produced by the toroidal vortex, which prompted the particles to recirculate in the bulk flow adjacent to the laser illumination spot on the lower electrode, and the trapping force produced by the particle and electrode interactions, which prompted the particles to aggregate in clusters on the surface of the illuminated spot. The experimental results showed that as the laser power increased, the toroidal flow range over which the particles circulated in the bulk flow increased, while the cluster range over which the particles were trapped on the electrode surface reduced. The results additionally showed that the particle velocity increased with an increasing laser power, particularly for particles with a smaller size. The excitation frequency at which the particles were trapped on the illuminated hot-spot reduced as the particle size increased. The force and velocity of polystyrene particles by the REP toroidal vortex has implications for further investigating the motion behavior at the biological cell level.

One-Pot Facile Synthesis of CuO-CdWO4 Nanocomposite for Photocatalytic Hydrogen Production.

Hydrogen (H2) is a well-known renewable energy source that produces water upon its burning, leaving no harmful emissions. Nanotechnology is utilized to increase hydrogen production using sacrificial reagents. It is an interesting task to develop photocatalysts that are effective, reliable, and affordable for producing H2 from methanol and acetic acid. In the present study, CuO, CdWO4, and CuO-CdWO4 nanocomposite heterostructures were prepared using a cost-efficient, enviro-friendly, and facile green chemistry-based approach. The prepared CuO, CdWO4, and CuO-CdWO4 nanocomposites were characterized using X-ray diffraction pattern, Fourier-transform infrared spectroscopy, diffuse reflectance ultraviolet-visible spectroscopy, scanning electron microscopy, transmission electron microscopy, selected area electron diffraction (SAED) pattern, N2 physisorption, photoluminescence, and X-ray photoelectron spectroscopy techniques. The synthesized photocatalysts were utilized for photocatalytic H2 production using aqueous methanol and acetic acid as the sacrificial reagents under visible light irradiation. The influence of different variables, including visible light irradiation time, catalyst dosage, concentration of sacrificial reagents, and reusability of catalysts, was studied. The maximum H2 was observed while using methanol as a sacrificial agent over CuO-CdWO4 nanocomposite. This enhancement was due to the faster charge separation, higher visible light absorption, and synergistic effect between the CuO-CdWO4 nanocomposite and methanol.

Silicone engineered anisotropic lithography for ultrahigh-density OLEDs

Ultrahigh-resolution patterning with high-throughput and high-fidelity is highly in demand for expanding the potential of organic light-emitting diodes (OLEDs) from mobile and TV displays into near-to-eye microdisplays. However, current patterning techniques so far suffer from low resolution, consecutive pattern for RGB pixelation, low pattern fidelity, and throughput issue. Here, we present a silicone engineered anisotropic lithography of the organic light-emitting semiconductor (OLES) that in-situ forms a non-volatile etch-blocking layer during reactive ion etching. This unique feature not only slows the etch rate but also enhances the anisotropy of etch direction, leading to gain delicate control in forming ultrahigh-density multicolor OLES patterns (up to 4500 pixels per inch) through photolithography. This patterning strategy inspired by silicon etching chemistry is expected to provide new insights into ultrahigh-density OLED microdisplays.

Patterning of Silicon Substrate with Self-Assembled Monolayers Using Vertically Aligned Carbon Nanotube Electron Sources.

We introduce a novel patterning technique based on e-beam lithography using vertically aligned carbon nanotube (VACNT) emitters with self-assembled monolayers (SAMs). A 20 μm line width of silicon wafer patterning was successfully demonstrated using octadecyl trichlorosilane (OTS) as a photoresist. To investigate surface modification by the irradiated electrons from the emitters, both contact angle measurement and energy dispersive X-ray (EDX) analysis were conducted. The patterning mechanism of the electron beam irradiated on OTS-coated substrate by our cold cathode electron beam (C-beam) was demonstrated by the analyzed results. The effect of current density and exposure time on the OTS patterning was studied and optimized for the Si wafer patterning in terms of the electronic properties of the VACNTs. The authors expect the new technique to contribute to the diverse applications to microelectromechanical (MEMS) technologies owing to the advantages of facile operation and precise dose control capability based on field electron emission current from the VACNT emitter arrays.