Multi-step Operation Research Articles

Precise in-situ fabrication of perovskite single crystal arrays via cosolvent based electrohydrodynamic printing

Single crystal (SC) perovskites exhibit superior stability and optoelectronic performance compared to polycrystalline ones, offering significant potential for high-performance and low-cost photovoltaic/optoelectronic applications. However, conventional SC growth processes often require intricate cutting or transferring of SC in the manufacturing of optoelectronic devices. High-resolution, in-situ, and scalable fabrication of perovskite SC arrays remain challenging. In this work, we propose a method for in-situ deposition of cosolvent based perovskite precursor solutions using electrohydrodynamic (EHD) printing technology. The addition of a cosolvent (which exhibits good chemical compatibility with the precursor and the main solvent, accompanied by lower solubility and vapor pressure) to the mixed solution promotes early-stage supersaturation and nucleation in the solution, enabling precise control over crystal morphology, size, and positioning through in-situ EHD printing. The effect of different cosolvent ratios on SC growth and the inhibition of parasitic crystallization by altering the contact angle of substrate were investigated. Finally, the parameters for precise control of the EHD printing process were investigated, enabling the growth of SC arrays ranging from 1 to 35 μm in size. This strategy offers a direct patterning approach for SC perovskite preparation without complex temperature control or multi-step operation. The printed patterns exhibit high resolution and excellent uniformity, offering significant potential for manufacturing SC-based perovskite optoelectronic devices with precise size and positioning control.

Identification of Core-Fucosylated Glycoproteins by Single-Step Truncation of N-Glycans.

Alpha-1,6 core fucosylation (CF) is a unique glycoform of N-glycans, and studies showed that CF modifications are involved in the occurrence and progression of various diseases and may provide potential disease biomarkers. Current strategies for the CF glycoproteome are often based on multistep enrichment of glycoproteins or glycopeptides and sequential cleavage with different glycosidases to truncate the N-glycans. Although the detection ability of low-abundance glycoproteins is improved, sample loss, high cost, and the time-consuming multistep operation also affect the reproducibility of results and the practicality of the method. Here we developed a single-step truncation (SST) strategy and evaluated its potential for the CF glycoproteome of human serum. The SST strategy has the advantages of fewer operational steps, lower cost, higher number of identifications, and better quantitative stability compared with previous approaches and provides an efficient solution for large-scale quantitative analysis of the CF glycoproteome. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Single-step truncation strategy for core fucosylation glycoproteome analysis in human serum Basic Protocol 2: Liquid chromatography-tandem mass spectrometry quantification of site-specific core fucosylation glycopeptides Alternate Protocol: Pretreatment of cellular samples of core fucosylation glycoproteome with single-step truncation strategy.

Metal-Phenolic Network Directed Coating of Single Probiotic Cell Followed by Photoinitiated Thiol-Ene Click Fortification to Enhance Oral Therapy.

Probiotics-based oral therapy has become a promising way to prevent and treat various diseases, while the application of probiotics is primarily restricted by loss of viability due to adverse conditions in the gastrointestinal (GI) tract during oral delivery. Layer-by-layer (LbL) single-cell encapsulation approaches are widely employed to improve the bioavailability of probiotics. However, they are generally time- and labor-intensive owing to multistep operation. Herein, a simple yet efficient LbL technique is developed to coat a model probiotic named Escherichia coli Nissle 1917 (EcN) through polyphenol-Ca2+ network directed allyl-modified gelatin (GelAGE) adsorption followed by cross-linking of GelAGE via photoinitiated thiol-ene click reaction to protect EcN from harsh microenvironments of GI tract. LbL single-cell encapsulation can be performed within 1h through simple operation. It is revealed that coated EcN exhibits significantly improved viability against acidic gastric fluid and bile salts, and enhanced colonization in the intestinal tract without loss of proliferation capabilities. Furthermore, oral therapy of coated EcN remarkably relieves the pathological symptoms associated with colitis in mice including down-regulating inflammation, repairing epithelial barriers, scavenging reactive oxygen species (ROS), and restoring the homeostasis of gut microbiota. This simplified LbL coating strategy has great potential for various probiotics-mediated biomedical and nutraceutical applications.

Connection of ssDNA to Silicon Substrate Based on a Mechano-Chemical Method.

A novel fabrication process to connect single-stranded DNA (ssDNA)to a silicon substrate based on a mechano-chemical method is proposed. In this method, the single crystal silicon substrate was mechanically scribed in a diazonium solution of benzoic acid using a diamond tip which formed silicon free radicals. These combined covalently with organic molecules of diazonium benzoic acid contained in the solution to form self-assembled films (SAMs). The SAMs were characterized and analyzed by AFM, X-ray photoelectron spectroscopy and infrared spectroscopy. The results showed that the self-assembled films were covalently connected to the silicon substrate by Si-C. In this way, a nano-level benzoic acid coupling layer was self-assembled on the scribed area of the silicon substrate. The ssDNA was further covalently connected to the silicon surface by the coupling layer. Fluorescence microscopy showed that ssDNA had been connected, and the influence of ssDNA concentration on the fixation effect was studied. The fluorescence brightness gradually increased with the gradual increase in ssDNA concentration from 5 μmol/L to 15 μmol/L, indicating that the fixed amount of ssDNA increased. However, when the concentration of ssDNA increased from 15 μmol/L to 20 μmol/L, the detected fluorescence brightness decreased, indicating that the hybridization amount decreased. The reason may be related to the spatial arrangement of DNA and the electrostatic repulsion between DNA molecules. It was also found that ssDNA junctions on the silicon surface were not very uniform, which was related to many factors, such as the inhomogeneity of the self-assembled coupling layer, the multi-step experimental operation and the pH value of the fixation solution.

A protein enzyme-free strategy for fluorescence detection of single nucleotide polymorphisms using asymmetric MNAzymes

To establish protein enzyme-free and simple approach for sensitive detection of single nucleotide polymorphisms (SNPs), the nucleic acid amplification reactions were developed to reduce the dependence on protein enzymes (polymerase, endonuclease, ligase). These methods, while enabling highly amplified analysis for the short sequences, cannot be generalized to long genomic sequences. Herein, we develop a protein enzyme-free and general SNPs assay based on asymmetric MNAzyme probes. The multi-arm probe (MNAzyme-9M-13) with two asymmetric recognition arms, containing a short (9 nt) and a long (13 nt) arm, is designed to detect EGFR T790 M mutation (MT). Owing to the excellent selectivity of short recognition arm, MNAzyme-9M-13 probe can efficiently avoid interferences from wild-type target (WT) and various single-base mutations. Through a one-pot mixing, MNAzyme-9M-13 probe enables the sensitive detection of MT, without protein enzyme or multi-step operation. The calculated detection limit for MT is 0.59 nM and 0.83%. Moreover, this asymmetric MNAzyme strategy can be applied for SNPs detection in long genomic sequences as well as short microRNAs (miRNAs) only by changing the low-cost unlabeled recognition arms. Therefore, along with simple operation, low-cost, protein enzyme-free and strong versatility, our asymmetric MNAzyme strategy provides a novel solution for SNPs detection and genes analysis.

The influence of residual tin following induction melt thermoforming of composite parts

Recently, a novel thermoforming process involving induction heating of tin interlayers to create ‘lubricated blanks’ using low viscosity molten tin was demonstrated (“iMelt”) (Harrison et al., 2020). Important to the success of the method is expulsion of the tin interlayer from the blank using a multi-step thermoforming operation. Approaches to characterise the quantity of residual tin and impact on the mechanical properties of the formed parts are established. 3D x-ray CT was used to accurately determine residual tin content while results from 2D x-ray scanning were shown to be highly-correlated with the 3D data and therefore can be a faster, low-cost alternative. After gradual refinement of the process, it was shown that residual tin volumes as low as 1.6 % were achievable in flat laminates. Compared to reference samples consolidated without tin, the remnant tin caused a reduction in yield strength and flexural stiffness, while producing comparable ultimate interlaminar shear strength.

Novel SF6 gas concentration method using hydrate-based gas uptake and sweating process

Hydrate-based gas separation is a method of separating gas mixtures into their individual components using their differences in thermodynamic properties. The maximum concentration of the target gas is equilibrium-constrained when using a single stage of operation. In this study, we propose a novel hydrate-based gas uptake and sweating process under constant pressure with rising temperature. We theoretically calculated the SF6–N2 gas hydrate pressure–temperature and pressure–gas composition equilibrium conditions to determine operating conditions for the process. Verification experiments conducted below 1 MPa and below 283 K revealed that SF6 was concentrated up to 90 % using this process in a multistep operation.

Understanding Advanced Persistent Threats

Advanced Persistent Threats (APTs) are a new type of threat that has piqued the interest of experts, particularly in the industrial security industry. APTs are cyber-attacks carried out by skilled and well-resourced adversaries who target specific information in high-profile organizations and governments, usually as part of a multi-step operation. The academic community has largely ignored the specifics of these threats, and as a result, an objective solution to the APT problem is absent. In terms of cybercrime activity, Africa has been one of the fastest rising regions. The continent is also a major source of cyberattacks on the rest of the world. A number of initiatives, however, have been implemented to mitigate cyber-threats and strengthen cybersecurity across the continent. The results of a complete study on APT are presented in this paper, which characterizes its differentiating traits and attack model while also assessing strategies often used in APT attacks. We also list various non-traditional countermeasures that can aid in the mitigation of APTs, highlighting future research prospects. Keywords : Advanced Persistent Threat, APT(s), Sophisticated Attacks, Cyber Security, Africa BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security & Forensics. Open Access. Distributed Free Citation: Akuffo-Badoo Erastus B. (2022). Understanding Advanced Persistent Threats . SMART-IEEE-Creative Research Publications Book Chapter Series on Research Nexus in IT, Law, Cyber Security & Forensics. Pp 15-22. www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P3

Gradient Cleaning Method of Potato Based on Multi-Step Operation of Dry-Cleaning and Wet Cleaning

In view of the poor effectiveness of existing potato cleaning methods in China and reflecting the findings of a research analysis of basic sizes and types of impurities on potato tubers, a gradient cleaning method for potato based on a multi-step dry-cleaning and wet cleaning operation was proposed. The method mainly consists of dry-cleaning and wet cleaning. The dry-cleaning stage, which combines vibration and brushing, could effectively remove impurities such as residual rhizomes, peeled potato skin, and large pieces of soil and crushed stone from the surface of potato tubers. The wet cleaning stage adopts the gradient cleaning method of pre-cleaning, rough cleaning and fine cleaning, which could further remove soil and crushed stone attached to the surface and hidden in the sprout eyes of potato tubers. The optimal parameter combination for the gradient cleaning method was determined as follows. The potato feeding amount was 3 t/h, the speed of the rubber chain rod mechanism was 25 r/min, the speed of the first and third brush roller was 40 r/min, the speed of the second and fourth brush roller was 56 r/min, the moving speed of the immersion mechanism conveying net chain was 0.04 m/s, the speed of the brush roller in the high pressure spray and brush roller combination mechanism was 40 r/min, the ultrasonic power was 1200 W, the ultrasonic frequency was 33 kHz, the bubble intensity was 300 L/min, and the moving speed of the conveying net chain in the ultrasonic and bubble combination mechanism was 0.05 m/s. Taking the impurity removal rate and damage rate of potato tuber as the test indexes, a potato cleaning performance test was carried out under the optimal parameters combination. The results showed that the average impurity removal rate and damage rate of potato tubers were 99.05% and 2.48%, respectively. Additionally, the operational performance fully met the requirements for potato cleaning. This study provides a new method for potato cleaning in China and can also provide a reference for cleaning other root and tuber crops.

Photonic instantaneous frequency measurement using a dense wavelength-division multiplexer.

A photonic instantaneous frequency measurement receiver based on frequency to optical power mapping is proposed and experimentally demonstrated. One channel of a dense wavelength-division multiplexer (DWDM) is used as an optical filter to establish a power ratio function related to the frequency of the microwave signal. Different from most optical filters, the DWDM filter features smooth and quasilinear roll-off over a wide bandwidth. With the help of a laser of good wavelength stability and a bias controller, large measurement range and high accuracy are simultaneously achieved without multi-step operation. The instanstaneous frequency measurement receiver can measure the frequency with an accuracy of 0.2% of the signal frequency in the range of 1-40 GHz over 1.5 h in the experiment.

Rapid highly sensitive general protein quantification through on-chip chemiluminescence.

Protein detection and quantification is a routinely performed procedure in research laboratories, predominantly executed either by spectroscopy-based measurements, such as NanoDrop, or by colorimetric assays. The detection limits of such assays, however, are limited to M concentrations. To establish an approach that achieves general protein detection at an enhanced sensitivity and without necessitating the requirement for signal amplification steps or a multicomponent detection system, here, we established a chemiluminescence-based protein detection assay. Our assay specifically targeted primary amines in proteins, which permitted characterization of any protein sample and, moreover, its latent nature eliminated the requirement for washing steps providing a simple route to implementation. Additionally, the use of a chemiluminescence-based readout ensured that the assay could be operated in an excitation source-free manner, which did not only permit an enhanced sensitivity due to a reduced background signal but also allowed for the use of a very simple optical setup comprising only an objective and a detection element. Using this assay, we demonstrated quantitative protein detection over a concentration range of five orders of magnitude and down to a high sensitivity of , corresponding to pM concentrations. The capability of the platform presented here to achieve a high detection sensitivity without the requirement for a multistep operation or a multicomponent optical system sets the basis for a simple yet universal and sensitive protein detection strategy.

Concretization as a Mechanism of Change in Psychodrama: Procedures and Benefits.

Concretization is a concept that has different meanings in different psychological theories and varying manifestations in different psychotherapies. In psychodrama, much of the available information on concretization draws on J. L. Moreno’s initial conceptualization, descriptive case studies, and interpretations in the various approaches. However, concretization has not been empirically studied as a concept or as a therapeutic mechanism of change. Therefore, the purpose of this qualitative study was to generate an empirically based conceptualization and operationalization of concretization as well as to identify its clinical benefits in psychodrama. To this end, semistructured in-depth interviews were conducted with seven experienced psychodrama therapists. Using a grounded theory approach for the data analysis, the model that emerged consists of three pathways toward concretization: realistic concretization, symbolic concretization, and integrated concretization. The findings suggest a sequential multistep operation that can be linear or nonlinear, depending on the protagonist’s need. The findings also underscore four benefits of concretization as a mechanism of change in psychodrama: reducing the ambiguity of the problem, externalizing the protagonist’s problem, enhancing the therapist-protagonist therapeutic bond, and bypassing the protagonist’s defense mechanisms. The model is discussed in light of the findings and the literature, and future directions are suggested.

An efficient resource sharing scheme based on the linear feedback shift register

With the invention of various kinds of electrical equipment, electricity has become an indispensable necessity in human society. The concept of smart grid is proposed in this context. Resource sharing is regarded as one of the important goals in smart grid. However, how to improve communication efficiency has become the bottleneck of resource sharing in smart grid. In this paper, we focus on optimisation of the symmetric balanced incomplete block design (SBIBD) to support efficient communication in smart grid. Note that the linear feedback shift register (LFSR) is employed in the generation of the SBIBD, which is far more efficient than the algorithm implementation. Moreover, the one-step state transition matrix of the LFSR is presented and the s-step state transition matrix is further deduced. Compared with the one-step state transition matrix, the s-step state transition matrix can well support multi-step parallel shift operation thereby increasing efficiency by s times.

Optimal Generator Start-Up Sequence for Bulk System Restoration With Active Distribution Networks

This paper proposes a new scheme for bulk system restoration considering the available black-start resources (BSRs) in the distribution system (DS). The DS assisted generator start-up sequence (D-GSS) scheme is realized in a decentralized way, so that it does not only benefit the bulk system GSS by utilizing available BSRs in the DS, but also respects the independent operation of the transmission system operator (TSO) and distribution system operators (DSOs). First, the decentralized D-GSS scheme is presented including the interaction of the TSO and DSOs and the corresponding compact models. The models of the decentralized D-GSS scheme are built with the bulk system GSS modeled as a mixed-integer quadratic program (MIQP), the DS multi-step operation modeled as mixed-integer second-order conic programs (MISOCPs) and reliable power supply assessments of renewable energy sources as linear programs (LPs). Finally, a projection function based analytical target cascading (P-ATC) method is developed to iteratively solve the decentralized models with model complexity reduction. The P-ATC algorithm can handle integer variables and improve the computational efficiency of the iterative calculation process. The effectiveness of the proposed method is validated using the small-scale T6D2 system and large-scale T118D5 system, showing good GSS performance and computation efficiency.

Fully automatic integrated continuous-flow digital PCR device for absolute DNA quantification

Existing digital polymerase chain reaction (PCR) devices consist of multiple independent devices, such as a droplet generator, a PCR thermocycler, and a droplet reader, which have the disadvantages of low integration, complex equipment structure, and high operation difficulty. This paper proposes a fully automatic integrated digital PCR device based on continuous-flow digital PCR theory. By simply adding the sample to the entrance of the integrated instrument, a series of procedures required for digital PCR detection can be fully automated, including sample injection, droplet generation, PCR thermal cycling, fluorescence acquisition, and signal analysis. In contrast to traditional techniques, sample testing requires only one integrated device rather than three separate instruments. For full automation, we design complete control and data processing software, which can complete a test by one-step operation. Therefore, the disadvantages of traditional instruments, such as multi-step operation, and hence, potential environmental pollution, are avoided. Moreover, the system can be powered by solar cells and does not require an external power supply.As a proof of concept, the proposed device is used for absolute quantitative detection of the hepatitis B virus in serum samples. The capacity of the system is validated by absolute quantification of three orders of magnitude from 103 to 105 IU/mL. The results have a good linear correlation (0.9986) with those of the traditional quantitative (qPCR), thus confirming the reliability of the instrument. In summary, we believe that our work can promote the development of integrated digital PCR systems.

Pop-up paper electrochemical device for label-free hepatitis B virus DNA detection

Hepatitis B virus (HBV) is a chronic viral infection, causing significant health concerns worldwide. For point-of-care testing, a simple, rapid, and disposable sensor is required. In this work, a pop-up DNA device as an alternative 3D microfluidic paper-based analytical device (μPAD) platform was firstly proposed for label-free HBV DNA detection. The pop-up design was created to allow control of the fluidic path, incubation time, and electrical connectivity by simple folding. The proposed platform enabled a multi-step operation to be performed within a single device. Moreover, this architecture allows facile sample introduction, avoiding contamination and minimizing the exposure of biofluids. A pyrrolidinyl peptide nucleic acid, acpcPNA, which exhibits high affinity and selectivity, was covalently immobilized onto the modified cellulose on a working electrode for capturing the target DNA. Differential pulse voltammetry was employed with a signal-off system. The presence of HBV DNA resulted in a decrease of the electrochemical signal of hexacyanoferrate (III)/(II) in a concentration-dependent fashion. Under optimal conditions, a linear range of 50 pM-100 nM with the detection limit of 1.45 pM was achieved. Moreover, good selectivity of proposed device was demonstrated. The pop-up DNA sensor was successfully applied for the detection of HBV DNA extracted from plasmid constructs.

Multi-step medical image segmentation based on reinforcement learning

Image segmentation technology has made a remarkable effect in medical image analysis and processing, which is used to help physicians get a more accurate diagnosis. Manual segmentation of the medical image requires a lot of effort by professionals, which is also a subjective task. Therefore, developing an advanced segmentation method is an essential demand. We propose an end-to-end segmentation method for medical images, which mimics physicians delineating a region of interest (ROI) on the medical image in a multi-step manner. This multi-step operation improves the performance from a coarse result to a fine result progressively. In this paper, the segmentation process is formulated as a Markov decision process and solved by a deep reinforcement learning (DRL) algorithm, which trains an agent for segmenting ROI in images. The agent performs a serial action to delineate the ROI. We define the action as a set of continuous parameters. Then, we adopted a DRL algorithm called deep deterministic policy gradient to learn the segmentation model in continuous action space. The experimental result shows that the proposed method has 7.24% improved to the state-of-the-art method on three prostate MR data sets and has 3.52% improved on one retinal fundus image data set.

Enhanced Feature Extraction for Ship Detection from Multi-Resolution and Multi-Scene Synthetic Aperture Radar (SAR) Images

Independent of daylight and weather conditions, synthetic aperture radar (SAR) images have been widely used for ship monitoring. The traditional methods for SAR ship detection are highly dependent on the statistical models of sea clutter or some predefined thresholds, and generally require a multi-step operation, which results in time-consuming and less robust ship detection. Recently, deep learning algorithms have found wide applications in ship detection from SAR images. However, due to the multi-resolution imaging mode and complex background, it is hard for the network to extract representative SAR target features, which limits the ship detection performance. In order to enhance the feature extraction ability of the network, three improvement techniques have been developed. Firstly, multi-level sparse optimization of SAR image is carried out to handle clutters and sidelobes so as to enhance the discrimination of the features of SAR images. Secondly, we hereby propose a novel split convolution block (SCB) to enhance the feature representation of small targets, which divides the SAR images into smaller sub-images as the input of the network. Finally, a spatial attention block (SAB) is embedded in the feature pyramid network (FPN) to reduce the loss of spatial information, during the dimensionality reduction process. In this paper, experiments on the multi-resolution SAR images of GaoFen-3 and Sentinel-1 under complex backgrounds are carried out and the results verify the effectiveness of SCB and SAB. The comparison results also show that the proposed method is superior to several state-of-the-art object detection algorithms.

An Adaptive Multistep Balancing Modulation Technique for Multipoint-Clamped Converters

In this article, a new pulsewidth modulation technique is proposed for the output voltage control and the dc-bus capacitors voltage balancing of a multipoint-clamped multilevel converter. The voltage equalization is achieved by allowing each converter's leg voltage to switch through multiple levels in a single modulation period (multistep operation). The approach is generalized with respect to the number of levels and phases and can be applied regardless of the converter operating conditions. Nevertheless, the multistep behavior generally leads to an increase of the average switching transitions rate. In the proposed method, this drawback is mitigated with an online adaptive selection of the number of switching levels. The algorithm is validated through an extensive hardware-in-the-loop testing and compared to other approaches.

A Multi-Step Modeling and Optimal Operation Calculation Method for Large-Scale Energy Hub Model Considering Two Types Demand Responses

Energy hub (EH) model, which connects the input and output energy by using the coupling matrix, is an important model for multiple energy system (MES) study. In a complex MES, it is very difficult to formulate the coupling matrix directly. This paper proposes a multi-step modeling method that separates the conversion process of the EH model into several steps and set up the EH model by multiplying the coupling matrix in each step. Then, the storage location and the concept of demand response are extended and integrated in the EH model. The EH model is difficult for the optimal operation calculation due to the nonlinearity caused by dispatch factors. This paper adds variable substitution in each step to reduce the EH model’s nonlinearity. A real residential district in Guangzhou, China, and a large-scale MES are conducted to validate the efficiency of proposed modeling and calculation method. The results show that the calculation method can reduce the computational burden significantly with global optimum obtained.