Experimental Steps Research Articles

Research on Virtual Simulation Experiment Course for Enterprise Decision-Making based on Multilateral Dynamic Game

Virtual simulation experiment serves as a bridge that organically connects innovation and entrepreneurship classes with professional quality education, fostering a talent cultivation ecosystem that supports high-quality economic development and exerts significant social influence. Currently, there are many shortcomings and bottlenecks in both virtual simulation experiment and the teaching process. This paper discusses the necessity and objectives of the virtual simulation experiment course for enterprise decision-making based on multilateral dynamic game, experimental principles, experimental characteristics, and experimental steps under the principle of "being real and not fictitious, simulating reality with virtuality, and grounding in reality". The experimental platform utilizes real business case that participants can freely choose. Through online human-computer interaction and interaction, as well as offline team discussions, participants are empowered to make independent decisions throughout the experiment. With the assistance of system prompts and task-driven guidance, participants can autonomously complete the experiment. This paper aims to promote the establishment of a virtual simulation experiment platform for enterprise decision-making based on multilateral dynamic game, specifically designed for business students, contributing to the construction of a strong higher education nation.

A Novel PCR-Free Ultrasensitive GQD-Based Label-Free Electrochemical DNA Sensor for Sensitive and Rapid Detection of Francisella tularensis

Biological warfare agents are infectious microorganisms or toxins capable of harming or killing humans. Francisella tularensis is a potential bioterrorism agent that is highly infectious, even at very low doses. Biosensors for biological warfare agents are simple yet reliable point-of-care analytical tools. Developing highly sensitive, reliable, and cost-effective label-free DNA biosensors poses significant challenges, particularly when utilizing traditional techniques such as fluorescence, electrochemical methods, and others. These challenges arise primarily due to the need for labeling, enzymes, or complex modifications, which can complicate the design and implementation of biosensors. In this study, we fabricated Graphene Quantum dot (GQD)-functionalized biosensors for highly sensitive label-free DNA detection. GQDs were immobilized on the surface of screen-printed gold electrodes via mercaptoacetic acid with a thiol group. The single-stranded DNA (ssDNA) probe was also immobilized on GQDs through strong π−π interactions. The ssDNA probe can hybridize with the ssDNA target and form double-stranded DNA, leading to a decrease in the effect of GQD but a positive shift associated with the increase in DNA concentration. The specificity of the developed system was observed with different microorganism target DNAs and up to three-base mismatches in the target DNA, effectively distinguishing the target DNA. The response time for the target DNA molecule is approximately 1010 s (17 min). Experimental steps were monitored using UV/Vis spectroscopy, Atomic Force Microscopy (AFM), and electrochemical techniques to confirm the successful fabrication of the biosensor. The detection limit can reach 0.1 nM, which is two–five orders of magnitude lower than previously reported methods. The biosensor also exhibits a good linear range from 105 to 0.01 nM and has good specificity. The biosensor’s detection limit (LOD) was evaluated as 0.1 nM from the standard calibration curve, with a correlation coefficient of R2 = 0.9712, showing a good linear range and specificity. Here, we demonstrate a cost-effective, GQD-based SPGE/F. tularensis DNA test suitable for portable electrochemical devices. This application provides good perspectives for point-of-care portable electrochemical devices that integrate sample processing and detection into a single cartridge without requiring a PCR before detection. Based on these results, it can be concluded that this is the first enzyme-free electrochemical DNA biosensor developed for the rapid and sensitive detection of F. tularensis, leveraging the nanoenzyme and catalytic properties of GQDs.

High-throughput solutions in tumor organoids: From culture to drug screening.

Tumor organoids have emerged as an ideal in vitro model for patient-derived tissues, as they recapitulate the characteristics of the source tumor tissue to a certain extent, offering the potential for personalized tumor therapy and demonstrating significant promise in pharmaceutical research and development. However, establishing and applying this model involves multiple labor-intensive and time-consuming experimental steps and lacks standardized protocols and uniform identification criteria. Thus, high-throughput solutions are essential for the widespread adoption of tumor organoid models. This review provides a comprehensive overview of current high-throughput solutions across the entire workflow of tumor organoids, from sampling and culture to drug screening. Furthermore, we explore various technologies that can control and optimize single-cell preparation, organoid culture, and drug screening with the ultimate goal of ensuring the automation and high efficiency of the culture system and identifying more effective tumor therapeutics.

Synthesis of BODIPY-pyrrolo[3,4-b]pyridin-5-ones via Ugi-Zhu/cascade reactions and studies of fluorescence response toward viscosity.

A series of seven new meso-phenyl BODIPY-pyrrolo[3,4-b]pyridin-5-one conjugates were synthesized in one experimental step by using a Sc(III)-catalyzed Ugi-Zhu three-component reaction coupled to a cascade sequence (aza Diels-Alder/N-acylation/aromatization) as post-MCR functionalization process. Further experimental studies were performed behind understanding the fluorescence response toward viscosity. All compounds exhibited a linear response between increasing viscosity (DMSO and glycerol mixtures) and fluorescence intensity. The different substituents also influenced the photophysical properties. Furthermore, in DMSO all compounds exhibited dual emission. Each band is attributed to the pyrrolo[3,4-b]pyridin-5-one and BODIPY moieties, respectively. The electronic structure of all compounds was computed by DFT and TD-DFT calculations, allowing to determine the molecular orbitals involved in the electronic transitions.

MitoSort: Robust Demultiplexing of Pooled Single-cell Genomics Data Using Endogenous Mitochondrial Variants.

Multiplexing across donors has emerged as a popular strategy to increase throughput, reduce costs, overcome technical batch effects, and improve doublet detection in single-cell genomic studies. To eliminate additional experimental steps, endogenous nuclear genome variants are used for demultiplexing pooled single-cell RNA sequencing (scRNA-seq) data by several computational tools. However, these tools have limitations when applied to single-cell sequencing methods that do not cover nuclear genomic regions well, such as single-cell assay for transposase-accessible chromatin with sequencing (scATAC-seq). Here, we demonstrate that mitochondrial germline variants are an alternative, robust, and computationally efficient endogenous barcode for sample demultiplexing. We propose MitoSort, a tool that uses mitochondrial germline variants to assign cells to their donor of origin and identify cross-genotype doublets in single-cell genomics datasets. We evaluate its performance by using in silico pooled mitochondrial scATAC-seq (mtscATAC-seq) libraries and experimentally multiplexed data with cell hashtags. MitoSort achieves high accuracy and efficiency in genotype clustering and doublet detection for mtscATAC-seq data, addressing the limitations of current computational techniques tailored for scRNA-seq data. Moreover, MitoSort exhibits versatility and can be applied to various single-cell sequencing approaches beyond mtscATAC-seq, provided the mitochondrial variants are reliably detected. Furthermore, we demonstrate the application of MitoSort in a case study where B cells from eight donors were pooled and assayed by single-cell multi-omics sequencing. Altogether, our results demonstrate the accuracy and efficiency of MitoSort, which enables reliable sample demultiplexing in various single-cell genomic applications. MitoSort is available at https://github.com/tangzhj/MitoSort.

Differentiable modeling and optimization of non-aqueous Li-based battery electrolyte solutions using geometric deep learning

Electrolytes play a critical role in designing next-generation battery systems, by allowing efficient ion transfer, preventing charge transfer, and stabilizing electrode-electrolyte interfaces. In this work, we develop a differentiable geometric deep learning (GDL) model for chemical mixtures, DiffMix, which is applied in guiding robotic experimentation and optimization towards fast-charging battery electrolytes. In particular, we extend mixture thermodynamic and transport laws by creating GDL-learnable physical coefficients. We evaluate our model with mixture thermodynamics and ion transport properties, where we show improved prediction accuracy and model robustness of DiffMix than its purely data-driven variants. Furthermore, with a robotic experimentation setup, Clio, we improve ionic conductivity of electrolytes by over 18.8% within 10 experimental steps, via differentiable optimization built on DiffMix gradients. By combining GDL, mixture physics laws, and robotic experimentation, DiffMix expands the predictive modeling methods for chemical mixtures and enables efficient optimization in large chemical spaces.

Artificial intelligence-enabled multipurpose smart detection in active-matrix electrowetting-on-dielectric digital microfluidics

An active-matrix electrowetting-on-dielectric (AM-EWOD) system integrates hundreds of thousands of active electrodes for sample droplet manipulation, which can enable simultaneous, automatic, and parallel on-chip biochemical reactions. A smart detection system is essential for ensuring a fully automatic workflow and online programming for the subsequent experimental steps. In this work, we demonstrated an artificial intelligence (AI)-enabled multipurpose smart detection method in an AM-EWOD system for different tasks. We employed the U-Net model to quantitatively evaluate the uniformity of the applied droplet-splitting methods. We used the YOLOv8 model to monitor the droplet-splitting process online. A 97.76% splitting success rate was observed with 18 different AM-EWOD chips. A 99.982% model precision rate and a 99.980% model recall rate were manually verified. We employed an improved YOLOv8 model to detect single-cell samples in nanolitre droplets. Compared with manual verification, the model achieved 99.260% and 99.193% precision and recall rates, respectively. In addition, single-cell droplet sorting and routing experiments were demonstrated. With an AI-based smart detection system, AM-EWOD has shown great potential for use as a ubiquitous platform for implementing true lab-on-a-chip applications.

Spontaneous Efficient Differentiation of Human Pluripotent Stem Cells (hPSC) Upon Co-culture of hPSCs with Human Neonatal Foreskin Fibroblasts in 3D.

Pluripotent stem cells (PSCs) form well-formed embryoid bodies (EBs) in 3D culture. These EBs are formed in culture media lacking leukemia inhibitory factor (LIF) or basic fibroblast growth factor (bFGF) in mouse and human PSCs, respectively. EBs are excellent technical tools for understanding developmental biology and inducing controlled differentiation in succeeding experimental steps. Technically speaking, EBs are spontaneously differentiated PSCs in 3D and exhibit all three lineages in a time-point/sequential manner. For example, ectoderm will form first, followed by mesoderm and endoderm. We have attempted to co-culture human neonatal foreskin-derived fibroblast cells in our laboratory with the PSCs first in 2D conditions followed by the induction of EBs (PSC+fibroblasts co-cultured) in low attachment dishes. We also performed spontaneous differentiation of such EBs (co-cultured with fibroblasts). We checked the presence of markers of various lineages, namely, ectoderm, mesoderm, and endoderm in days 6, 10, and 12day EBs. We have also compared the fibroblast co-cultured EBs, along with control EBs (derived from only PSCs). This co-culture system mimics the natural conditions of uterine implantation and the role of the endometrial fibroblasts in the induction of further embryonic development. The fibroblast co-cultured iPSC EBs had better roundness scores than the normal iPSC EBs and had a higher expression of lineage-specific markers.

Fractional-Order Modeling and Identification for an SCR Denitrification Process

This paper presents an application of a fractional-order system on modeling an industrial process system with large inertia and time delay. The traditional integer-order model of the process system is extended to a fractional-order one in this work. To identify the parameters of the proposed fractional-order model, an output-error identification algorithm is presented. Based on the experimental step response data of the selective catalytic reduction (SCR) denitrification process in a power plant, this proposed fractional-order model shows a better fitting result compared with the typical integer-order models. An integer-order proportional–integral (PI) controller is designed for the process plant using a simple scheme according to the identified fractional-order and integer-order models, respectively. Validation tests are performed based on the obtained fractional-order and integer-order models, demonstrating the advantages of the proposed fractional-order model with the corresponding system identification approach for industrial processes with large inertia and time delay.

Comparison of DNA Isolation Methods for GMO Detection from Biscuit Samples

The global increase in genetically modified organism (GMO) content in feed and food products has necessitated the development of precise detection methods to differentiate between biotechnologically derived foods and those without GMOs. Despite the various regulations in different countries, an internationally consistent approach to labeling GMO products is needed. For this reason, there is a widespread need to develop effective GMO detection methods to provide reliable and transparent food safety to consumers. The first experimental step in creating accurate and reliable detection methods for GMOs is effective DNA isolation. Determining DNA isolation methods specific to different processing levels of foods is very important. This study was aimed to compare different DNA extraction methods in biscuit samples. For this reason, DNA from different biscuit samples was isolated using three different protocols (CTAB-PVP, modified CTAB-1, and modified CTAB-2). DNA samples extracted from biscuits, were evaluated regarding DNA concentration and purity. According to the results obtained, the CTAB-2 procedure generally showed the best performance in terms of both DNA amount and purity rates for biscuit samples.

Protocol for muscle fiber type and cross-sectional area analysis in cryosections of whole lower mouse hindlimbs.

We outline a robust, simple, and cost-effective method to simultaneously visualize all mouse lower hindlimb skeletal muscles. We describe procedures for orientating the whole lower hindlimb in gum tragacanth prior to freezing, simplifying the proceeding experimental steps, and enhancing the clarity and comprehensiveness of characterizations. We then detail steps for quantifying muscle fiber size and fiber type characteristics in a single cryosection using immunofluorescence and histochemistry. This protocol can be applicable for commonly used histological and (immuno) histochemical evaluations such muscle degeneration/regeneration, fibrosis, immune cell infiltration, enzymatic activity and glycogen content.

Teaching Implementation and Improvement Direction of Student Science Experiments -- Take Weigh the Mass of Solids with a Balance for Example

This article explores how to optimize the teaching design of the measurement experiment Weighing the Mass of Solids with a Balance in the context of the new middle school entrance examination, aiming to enhance students physical experiment operation ability and innovative thinking ability. The article points out that experimental teaching should combine the requirements of textbooks and new curriculum standards, pay attention to the design of experimental operation details, and stimulate students interest in scientific exploration through problem driven strategies. Specifically, in the chapter on Measurement of Quality , the knowledge sequence of the textbook includes the concept of quality, unit conversion, quality attributes, measuring instruments, and the use of scales. In teaching, it is necessary to pay attention to the initial use of scales, guide students to understand the structure and principles of scales, and attach importance to experimental operation training. In response to teaching difficulties, such as error analysis, measures should be taken to improve students understanding, such as through example analysis and strengthening guidance on experimental steps. In addition, the article also emphasizes the direction of teaching improvement, including adjusting the content position to optimize the learning process, segmenting teaching based on student learning situations, optimizing teaching methods, adding experimental report writing, encouraging communication and display, designing multi-level experimental tasks, and promoting the spiral increase of students scientific exploration ability through repeated experiments and problem guidance.

The Analytical and Experimental Analysis of the Machined Surface Roughness in High-Feed Tangential Turning

A main topic in mass production of machine parts is how to increase the productivity to produce more parts in a given time while maintaining the prescribed surface quality on the machined surfaces. Novel machining procedures have been introduced to achieve this goal; however, the further development of already established and wide-spread procedures can offer simply accessible solutions. Tangential turning is a rediscovered variant of the traditional turning procedure, where a specially designed cutting tool ensures chip removal with a feed tangential to the workpiece. This process results in low surface roughness even at higher feed rates. In this paper, the achievable surface roughness is analyzed by analytical and experimental steps. In the mathematical analysis, the theoretical surface roughness is determined using the constructive geometric modelling method. The worked-out equations are validated in cutting experiments on 42CrMo4 grade steel workpieces. The theoretical and experimental analyses show that the strictly prescribed surface roughness can be achieved with high feed rates by the application of tangential turning.

Archaea in the Human Microbiome and Potential Effects on Human Infectious Disease.

Archaea represent a separate domain of life, next to bacteria and eukarya. As components of the human microbiome, archaea have been associated with various diseases, including periodontitis, endodontic infections, small intestinal bacterial overgrowth, and urogenital tract infections. Archaea are generally considered nonpathogenic; the reasons are speculative because of limited knowledge and gene annotation challenges. Nevertheless, archaeal syntrophic principles that shape global microbial networks aid both archaea and potentially pathogenic bacteria. Evaluating archaea interactions remains challenging, requiring clinical studies on inflammatory potential and the effects of archaeal metabolism. Establishing a culture collection is crucial for investigating archaea functions within the human microbiome, which could improve health outcomes in infectious diseases. We summarize potential reasons for archaeal nonpathogenicity, assess the association with infectious diseases in humans, and discuss the necessary experimental steps to enable mechanistic studies involving archaea.

Human action recognition based on smart sensors

Abstract This paper focuses on human activity recognition using LSTM (Long Short-Term Memory) for handling time series data issues. Because LSTM can better deal with the correlation and long-term correlation of time-series data, the model is utilized to build a human-computer interaction action recognition system. The experimental steps include the following: first, the bracelet sensor obtains the human body acceleration signal to obtain a data set containing a variety of motion postures and preprocesses the data. Then, LSTM is used to extract the features of the dataset, and the feature vector is utilized as the input to train the model iteratively. Finally, to improve the accuracy of recognition, a variety of machine learning models will be applied to compare the performance with the LSTM model. The experimental results indicate that the proposed model can better capture the acceleration changes of human motion in various life scenes, and can accurately distinguish various sudden action patterns of the human body in daily life. This also makes the human movement behavior recognition system proposed in this study more comprehensive.

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Design and Development of a Portable Neutron Detection System Based on a 6Li-Doped ZnS(Ag) Scintillator

In this study, the design and development of a portable neutron detection system based on a 6LiF + ZnS(Ag) scintillator was carried out. The detector system was first modeled using the Monte Carlo simulation code MCNP. As a result of the detector simulation, the materials and photomultiplier tubes (PMTs) were supplied for the system, and the material properties and thicknesses were optimized for the best scintillator, with the EJ-420 (Eljen Technology), consisting of 95% 6Li dispersed in ZnS(Ag), chosen because it has a distinctive feature with regard to high thermal neutron detection efficiency. Since this material has been shown to offer a significant advantage in favor of neutron detection in mixed radiation fields with gammas and neutrons, the pulse shape discrimination method was employed. To achieve this, a proper electronic circuit was developed to discriminate the pulses from neutrons and gammas. In the experimental step, the EJ-420 scintillator with a 50-mm diameter was optically coupled with a special fast PMT (Hamamatsu H1949-51 model). In conclusion, this study, which underlines the performed simulations for a neutron detector configuration, gives the obtained experimental results showing discrimination capability in neutron/gamma detection using a 241Am-Be neutron source. The results show that the EJ-420 is a good scintillator due to its highly enriched 6Li transmator, which results in more effective neutron measurements when a portable neutron detector design is chosen.

Effect of contact blast loading on the plastic deformation forming ability of large steel pipes

Plastic deformation forming with metal pipe blanks by contact blast loading inside pipes is an interesting moldless forming technique, also a complex and error-prone process. Some advantages are very characteristic of this forming technique such as no cost of mold, tooling and low energy consumption, no complicated control equipment compared to other forming techniques such as casting, rolling, tube hydrostatic forming, bending – welding. Up to now, the calculation and design of this forming technique mainly use some existing reference empirical formulas, so the experimental results are only suitable in the range of small pipe diameters, and still there are significant deviations for larger pipe diameters. In order to increase the predictability and accuracy of forming process by contact blast loading inside large pipes, this paper presents a study on the influence of the mass of highly explosive material – TNT to the forming ability of large steel pipes from API-5LX-42 mild steel materials by modern 3D numerical simulation – using Abaqus/Cae software. Four output criteria with maximum values are used to evaluate the efficiency of this forming process, including maximum diameter of the blast zone (Dmax£2D0), Von Mises stress (Smax£UTS), Hoop plastic strain component (PE22max£1), and Pipe wall thinning rate (eT-max£60 %). The results of this research on the plastic deformation forming process using numerical simulation can be used for the next experimental step to evaluate the difference between simulation and experiment, as well as use this data in the calculation and design of pipe products with circular or square cross-sections to save both time and money of trial and error before application in actual manufacturing

Microwave-assisted synthesis of molecularly imprinted polymers for smartphone-based luminescent hemoglobin one-pot detection

This work introduces a novel strategy to selectively and sensitively determine Hemoglobin (Hb) using a microwave-synthesized molecularly imprinted polymer (MIP) and chemiluminescence (CL) as the detection method. Studies conducted on both MIP and non-imprinted polymer (NIP) evidenced that the MIP material exhibits a high adsorption capacity (48 µg/mg) and an imprinted factor of about 3, in addition to a selective adsorption property towards Hb in the presence of other proteins, whose structures are very similar to that of Hb. The high selectivity and sensitivity of the proposed biosensor were also assured by the CL detection, whose mechanism is based on Hb's ability to enhance luminol oxidation in an alkaline medium in the presence of hydrogen peroxide, emitting a blue light whose intensity is related to the Hb concentration. The emitted light intensities from the CL reaction, directly proportional to Hb concentration, were captured and analyzed using a smartphone and RGB Color application, avoiding the use of sophisticated equipment and facilitating the measurement process. In order to streamline and speed up the detection process, all the experimental steps including Hb adsorption on MIPHb, supernatant removal, CL reaction, and smartphone readout occur in a single 8-well strip. Therefore, the proposed approach offers one-pot detection for the sensitive (LOD = 0.03 µg.mL−1, equivalent to 1.5 nmol.L−1) and selective determination of Hb in blood samples, for biomedical or forensic applications, through a rapid, low-cost, simple, and affordable approach.

Rapid enzyme-free detection of miRNA-21 in human ovarian cancerous cells using a fluorescent nanobiosensor designed based on hairpin DNA-templated silver nanoclusters

BackgroundCancer is known as one of the main non-communicable diseases and the leading cause of death in the new era. Early diagnosis of cancer requires the identification of special biomarkers. Currently, microRNAs (miRNAs) have attracted the attention of researchers as useful biomarkers for cancer early detection. Hence, various methods have been recently developed for detecting and monitoring miRNAs. Among all miRNAs, detection of miRNA-21 (miR-21) is important because it is abnormally overexpressed in most cancers. Here, a new biosensor based on silver nanoclusters (AgNCs) is introduced for detecting miR-21. ResultsAs a fluorescent probe, a rationally designed hairpin sequence containing a poly-cytosine motif was used to facilitate the formation of AgNCs. A guanine-rich sequence was also employed to enhance the sensing signal. It was found that in the absence of miR-21, adding a guanine-rich sequence to the detecting probe caused only a slight change in the fluorescence emission intensity of AgNCs. While in the presence of miR-21, the emission signal enhanced. A direct correlation was observed between the increase in the fluorescence of AgNCs and the concentration of miR-21. The performance of the proposed biosensor was characterized thoroughly and confirmed. The biosensor detected miR-21 in an applicable linear range from 9 pM to 1.55 nM (LOD: 2 pM). SignificanceThe designed biosensor was successfully applied for detecting miR-21 in human plasma samples and also in human normal and lung and ovarian cancer cells. This biosensing strategy can be used as a model for detecting other miRNAs. The designed nanobiosensor can measure miR-21 without using any enzymes, with fewer experimental steps, and at a low cost compared to the reported biosensors in this field.