Characteristics Of Technology Research Articles

Tumour DNA methylation markers associated with breast cancer survival: a replication study

BackgroundTumour DNA methylation has been investigated as a potential marker for breast cancer survival, but findings often lack replication across studies.MethodsThis study sought to replicate previously reported associations for individual CpG sites and multi-CpG signatures using an Australian sample of 425 women with breast cancer from the Melbourne Collaborative Cohort Study (MCCS). Candidate methylation sites (N = 22) and signatures (N = 3) potentially associated with breast cancer survival were identified from five prior studies that used The Cancer Genome Atlas (TCGA) methylation dataset, which shares key characteristics with the MCCS: comparable sample size, tissue type (formalin-fixed paraffin-embedded; FFPE), technology (Illumina HumanMethylation450 array), and participant characteristics (age, ancestry, and disease subtype and severity). Cox proportional hazard regression analyses were conducted to assess associations between these markers and both breast cancer-specific survival and overall survival, adjusting for relevant participant characteristics.ResultsOur findings revealed partial replication for both individual CpG sites (9 out of 22) and multi-CpG signatures (2 out of 3). These associations were maintained after adjustment for participant characteristics and were stronger for breast cancer-specific mortality than for overall mortality. In fully-adjusted models, strong associations were observed for a CpG in PRAC2 (per standard deviation [SD], HR = 1.67, 95%CI: 1.24–2.25) and a signature based on 28 CpGs developed using elastic net (per SD, HR = 1.48, 95%CI: 1.09–2.00).ConclusionsWhile further studies are needed to confirm and expand on these findings, our study suggests that DNA methylation markers hold promise for improving breast cancer prognostication.

Research progress of CRISPR technology in plant abiotic stress

In recent years, the agricultural sector has faced immense challenges due to prolonged droughts, excessive soil salinity, and extreme temperature fluctuations, which have collectively stunted crop growth and significantly reduced yields. Such environmental stressors not only impact agricultural productivity but also pose a substantial threat to global food security. To address these challenges, advancements in gene editing have introduced CRISPR (clusters of regularly interspaced short palindromic repeats) tools, with CRISPR-Cas9 emerging as a particularly powerful and widely adopted technology. This tool offers high precision, efficiency, and cost-effectiveness, enabling targeted genetic modifications that can enhance crop resilience and facilitate the development of superior varieties. This paper discusses the fundamental principles and unique characteristics of CRISPR-Cas9 technology, providing a comprehensive summary of its applications in strengthening crop resistance to various abiotic stresses, including drought, salinity, and extreme temperatures. Additionally, it addresses the technology's limitations, outlining the areas that require further refinement to optimize its agricultural impact and broaden its applicability.

Height Measurement Method for Meter-Wave Multiple Input Multiple Output Radar Based on Transmitted Signals and Receive Filter Design

To address the issue of low-elevation target height measurement in the Multiple Input Multiple Output (MIMO) radar, this paper proposes a height measurement method for meter-wave MIMO radar based on transmitted signals and receive filter design, integrating beamforming technology and cognitive processing methods. According to the characteristics of beamforming technology forming nulls at interference locations, we assume that the direct wave and reflected wave act as interference signals and hypothesize a direction for a hypothetical target. Then, the data received are processed to obtain the height of low-elevation-angle targets using a cognitive approach that jointly optimizes the transmitted signal and receive filter. Firstly, a signal model for the meter-wave MIMO radar based on the transmit weight matrix is established under low-elevation scenarios. Secondly, the signal model is analyzed and transformed. Thirdly, the beamforming algorithm that jointly optimizes the transmitted signals and receive filter is derived and analyzed. The algorithm maximizes the output Signal-to-Interference-plus-Noise ratio (SINR) of the receiver by designing the transmit weight matrix and receive filter. The optimization problem based on the SINR criterion is non-convex and difficult to solve. We transformed it into two sub-optimization problems and approximated the optimal solution through an alternating iteration algorithm. Finally, the proposed height measurement algorithm is compared with the Generalized Multiple Signal Classification (GMUSIC) and Maximum Likelihood (ML) height measurement algorithms. Simulation results show that the proposed algorithm can realize the height measurement of low-elevation targets. Compared to the GMUSIC and ML algorithms, it demonstrates superior performance in terms of computational complexity and multi-target elevation estimation.

Innovative Applications and Teaching Effectiveness Analysis of Interactive Mobile Technology in Music Education

With the rapid advancement of mobile Internet technology, the application of interactive mobile technology in education has emerged as a significant area of research, particularly in music education. Mobile technology has introduced transformative changes to both learning styles and teaching methods. Through the utilization of smart devices and mobile platforms, students are provided with personalized and flexible learning environments for music education, while teachers can leverage advanced technological tools to enhance teaching effectiveness. Although previous studies have examined the role of mobile technology in music education, most have focused on its isolated effects, neglecting a systematic analysis of the evolution of teaching effectiveness over time. Furthermore, existing methodologies often fail to account for temporal characteristics and dynamic changes, resulting in an incomplete evaluation of long-term educational outcomes. This study aims to analyze the network characteristics of interactive mobile technology applied in music education and to explore the evolution of teaching effectiveness with consideration of temporal characteristics. This study is expected to offer novel theoretical perspectives for the digital transformation of music education along with practical guidance for its implementation.

Construction of Key Technology System for Mine Ecological Restoration Under System Perspective

Mine ecological restoration has experienced a long-term development process in China, in which various technologies have been constantly developing and integrating. Based on the related theoretical research and field program, the technical system of mine ecological restoration was constructed, and the characteristics of key technologies were specifically grasped. In this research, the environment, including natural elements and the spatial environment, is the object of mine ecological restoration, which requires further long-term investigation and monitoring. Therefore, natural element restoration technology, space environment restoration technology, and environmental survey and restoration monitoring technology should be considered when establishing technical systems. The research showed that： ① In mine natural element restoration, where soil and water are important, traditional technologies like pollution abatement with physical, chemical, and biological methods have been extensively used. Meanwhile, artificial soil reconstruction and multi-technology joint remediation became the main study focus in soil restoration and artificial wetlands have been gradually constructed as a new method in water restoration, covering water system restoration and pollution control. ② The two tasks of space environment restoration were geological disaster prevention and vegetation re-greening. Major technologies of the former were applied to surface mine slope treatment and mining subsidence area control, the latter of which could be divided into three technical links： vegetation selection, construction, and maintenance. Although many technologies are valid, a few frontiers need to be further pursued. ③ The mine environmental investigation and restoration monitoring were based on 3S technologies, containing GIS, GPS, and RS, all of which are developing rapidly but still have a large space for integration and innovation.

Development of a standardized data collection and intelligent fabric quality prediction system for the weaving department

The diversity of weaving equipment has led to inconsistencies in communication protocols, impeding data collection and interoperability between devices, and ultimately reducing production efficiency. Additionally, fabric defects significantly impact product quality, while current visual inspection technologies are primarily reactive and traditional quality prediction methods often exhibit considerable errors. This study leverages the standardization and interoperability features of open platform communications unified architecture technology to facilitate data acquisition within the weaving department, establishing a reliable Internet of Things framework that supports subsequent fabric quality prediction, and optimizing the back propagation neural network through the K-means clustering algorithm and particle swarm optimization to predict the type and number of fabric defects. A comparative analysis with traditional BP and PSO-BP prediction models was conducted, ultimately verifying the feasibility of using OPC UA to transmit weaving data for fabric quality prediction. The research results demonstrate that using OPC UA technology enables the unified transmission of weaving equipment data, addressing the issue of heterogeneity in weaving department equipment. The K-means-PSO-BP model can effectively predict defects such as double weft, hundred feet, and broken warp with minimal error, achieving a root mean square error of less than 0.15.

Determining the impact of blockchain technologies on the grain supply chain tracking system in the EU

The object of this paper is blockchain technology in the tracking system of grain supply chains. The current study considers the task of determining the impact of blockchain technology introduction on the tracking system of grain supply chains. The key problems in the system of grain supply chains have been identified and the tasks to solve them have been proposed. The characteristics of key technologies in the implementation of blockchain in the system of grain supply chains have been defined, such as smart contracts, the Internet of Things (IoT), interplanetary file system (IPFS), contactless tags (RFID), Ethereum platform (identified as the best for supply chain tracking). The influence of factors on the introduction of blockchain technologies into the grain supply chain tracking system was determined using a SWOT analysis. Strengths include transparency, increased trust, automation of processes and protection against falsification. Weaknesses include high implementation costs, difficulty scaling, and the need for staff training. Opportunities that open up through the use of blockchain include attracting new partners, increasing competitiveness, and developing new markets. Threats include legal difficulties, technical failures, high energy costs, and resistance from market participants. An assessment of the investment attractiveness of introducing blockchain technology into the grain supply chain tracking system was carried out by calculating such indicators as economic effect; net present value (NPV) of implementing blockchain technologies; payback period of investments. According to the results of analysis, the following data were obtained: NPV (150439 a.u.)>0, the payback period of investments is 2.8 years, which is acceptable for large agricultural holdings. Prospects for development have been determined, in particular, the unification of agricultural holdings for the joint implementation of blockchain technologies in the tracking system of grain supply chains, which would be a strategically beneficial solution for all participants in the supply chain

A pea variety ‘Kazak’

Peas is one of the most common leguminous crops, the value of which is determined by a wide range of use. Traditional pea varieties often suffer from poor productivity and insufficient tolerance to adverse weather conditions such as drought, frost, and diseases. Modern plant breeding has made it possible to develop new leafless pea varieties with a determinate growth type (limited stem growth), which significantly simplifies mechanized harvesting. In this regard, the purpose of the current study was to develop a new highly productive pea variety with resistance to extreme environmental conditions and high feed and food qualities. During a long-term breeding work, including a various initial forms’ crossing, a selection of the best genotypes and a strict control of productivity and stability parameters, the variety ‘Kazak’ was studied in the Competitive Variety Testing under number G-1122 in 2020–2022. The yield structure elements have shown that pea seed productivity has increased due to all elements of seed productivity. Number of productive beans per plant of the variety ‘Kazak’ was 4.9 pcs., number of seeds per plant was 16.3 pcs., 1000-seed weight was 206.7 g, productivity of one plant was 3.4 g, and protein in seeds was 25%. Due to higher indicators of the yield structure elements, it was possible to form productivity from 2.40 to 4.41 t/ha, which is on average 0.50 t/ha higher than that of the standard (2.07–3.42 t/ha). Economic efficiency of the variety cultivation has shown an additional output of 10,110 rubles per hectare, and the profitability level was 70.6%. Further work is going to be aimed at the study of adaptive potential of the variety in various climatic areas and the features of varietal agricultural technology to achieve maximum productivity. Particular attention is going to be paid to the study of genetic potential of the variety ‘Kazak’ for breeding new, even more productive and resistant pea varieties.

Systematic Literature Review: The Effectiveness of Technology-Assisted Project-Based English Language Learning

The problem with learning English lies in the need for updated instructional methods. Project-based learning, a contemporary model suited for the 21st century, fosters collaboration to ignite students' enjoyment of learning. The increasing use of technology in learning is establishing a new effectiveness learning model. This research aims to determine the influence of technology-assisted and project-based learning (TPjBL) on English language acquisition, analyze factors that influence the TPjBL on English language learning, and analyze media used in implementing TPjBL in English language learning. The research methods involved a systematic literature review, analyzing 23 (twenty-three) articles selected through the PRISMA process from 2015 to 2023. The data analysis technique utilized a predetermined review protocol containing three main aspects, including bibliography, research details, as well as focus and content of the article. Based on the consequences of the analysis using protocol review, it was found that the positive influence of TPjBL on English learning was 91%, with influencing factors including student conditions, technology features, authentic projects, group communication and collaboration, teacher conditions, as well as the most widely used media of social media and web. These three parties can benefit from the results of this study. Teachers must be able to create good learning plans (project planning, technology selection), preliminary activities and appropriate assessment principles. For schools and governments, curriculum adjustments, technological facilities, such as computers, and the availability of internet access must be reviewed if determining to implement TPjBL in English learning.

Application Analysis of Digital Resources in University Classical Music Teaching

As an important part of art education in colleges and universities, classical music teaching needs to keep up with the development of The Times and actively integrate into modern digital resources. Firstly, this paper analyzes the current situation and problems of classical music teaching in universities. Then, the potential value of digital resources for problem solving is elaborated in detail, including providing diversified learning resources to help overcome regional restrictions, making it possible to learn anytime and anywhere, and using the visual characteristics of digital technology can make the learning process more intuitive and vivid. Finally, specific and effective strategies are put forward, such as establishing a perfect digital resource database and conducting moderate technical training, so as to deepen the application of digital resources in classical music teaching in colleges and universities. The results show that the use of digital resources can not only change the learning style while increasing the learning fun, but also improve the teaching effect.

Features of Terrestrial Laser 3D Scanning Technology for Pavement Condition Assessment

Abstract. Problem. Traditional methods of road condition monitoring have limitations in terms of data accuracy and completeness, particularly in the detection of surface defects. There is a need for methods that provide accurate, rapid data collection to support effective maintenance and repair planning. Goal. The goal of this study is to develop and optimise a methodology for terrestrial 3D laser scanning and to provide practical recommendations for its application in road surface monitoring. Methodology. The proposed methodology examines the effectiveness of terrestrial laser scanning on road segments, addressing parameters such as optimal station count, placement and scanning mode to ensure accurate and comprehensive data collection. The Trimble TX6 scanner is used as an example, with specifications including a range of up to 120 metres, 2 mm accuracy and an adjustable scanning speed of up to 500,000 points per second. Results. The research identifies optimal setups for different road segments, covering short (~100–150 m) and long (up to 1000 m) sections, as well as complex road infrastructure such as multi-level interchanges. The results demonstrate the ability of the 3D scanning method to detect various linear and areal pavement defects. Originality. This study advances the field by developing specific recommendations for station positioning and scanning protocols, addressing blind spots, and ensuring data integrity for 3D modelling. Practical value. The application of this technology supports detailed analysis of pavement condition, significantly increasing the efficiency of data processing and improving repair planning and material estimation. The results are beneficial for transport infrastructure management, enabling more reliable monitoring and maintenance practices

A Rapid Field-Visualization Detection Platform for Genetically Modified Soybean 'Zhonghuang 6106' Based on RPA-CRISPR.

Genetically modified (GM) herbicide-tolerant soybean 'Zhonghuang 6106', which introduces a glyphosate-resistant gene, ensures soybean yield while allowing farmers to reduce the use of other herbicides, thereby reducing weed management costs. To protect consumer rights and facilitate government supervision, we have established a simple and rapid on-site nucleic acid detection method for GM soybean 'Zhonghuang 6106'. This method leverages the isothermal amplification characteristics of RPA technology and the high specificity of CRISPR-Cas12a to achieve high sensitivity and accuracy in detecting GM soybean components. By optimizing experimental conditions, the platform can quickly produce visual detection results, significantly reducing detection time and improving efficiency. The system can detect down to 10 copies/μL of 'Zhonghuang 6106' DNA templates, and the entire detection process takes about 1 h. The technology also has strong editing capabilities; by redesigning the primers and crRNA in the method, it can become a specific detection method for other GM samples, providing strong technical support for the regulation and safety evaluation of GM crops.

Algorithm of calculation of water consumption on dairy cattle farm with tied and loose housing at milking in milking parlors

Water is used in the whole cycle of milk production, from watering and fodder preparation to washing of milking equipment and milk cooling tanks. At the same time, farms do not control and record the amount of water consumed, which can result in a significant excess of actual water consumption over the normative data. One of the ways to solve this problem can be the introduction of a water consumption monitoring system, which will track the actual water consumption on the farm and compare it with the calculated volume obtained on the basis of normative data, technical characteristics of equipment and animal husbandry technology adopted in the farm. The purpose of the research is to develop an algorithm for calculating water consumption when performing technological operations on cattle dairy farms. As a result of the research, an algorithm for calculating water consumption for technological operations was developed, taking into account different variants of the technical and technological solutions. On the basis of the algorithm a program was developed, with the help of which the sequence of water consumption calculation was tested. The calculation was carried out for a farm for 800 heads of dairy herd of loose housing with productivity of 28 kg/head and 200 heads of loose housing with productivity of 32 kg/head excluding young stock. Water consumption for such a farm is 113.09 m3 /day, of which 99.92 m3 /day is used for watering, fodder preparation, and is non-returnable, and 13.17 m3 /day is used for technological operations. The further direction of research will be the development of a monitoring system based on the developed program of water consumption calculation. In addition to the monitoring system, the program will be useful in technological design of cattle farms for milk production.

Immersive Experience and Cultural Inheritance: Museum Exhibition Design Based on Metaverse Technology

Based on the current status of museum operations and exhibition display schemes, this paper constructs museum exhibition methods and design proposals utilizing metaverse technology through its innovation and optimization. Further discussions are conducted on the characteristics of metaverse technology and its application strategies, providing novel possibilities for the promotion and content dissemination of museum products.

DEVELOPMENT THE MATHEMA-TICAL MODEL OF THE PROCESS OF STRIPED SOIL TREATMENT BY THE METHOD OF DISCRETE ELEMENTS

The paper describes the general characteristics of the Strip-Till technology, its application and the design of Strip-Till cultivators, talks about the prospects of this technology, describes the advantages and disadvantages of the technology and highlights the ways of implementing the technology. Each technology has its advantages and disadvantages and specifics of implementation - Strip-Till is no exception. In some farms, the technology is implemented quite easily and proves its effectiveness after harvesting and summing up, while in other farms it may be the opposite. One of the many reasons for this phenomenon is the design features of strip cultivators, which arise from the creative flight of the developer and the specific agro-climatic conditions for which these units are designed. The culture of work and agrarian business in a particular region also has a significant impact on some design features. For example, it is no secret that the school of mechanical engineering in Europe and the USA has many differences. The article is devoted to the study of the interaction of the working bodies of Strip-Till units with the soil using the discrete element method. The paper considers modern aspects of the application of Strip-Till technology in the world and Ukraine, its advantages and disadvantages, and also analyzes methods for modeling physical processes of soil cultivation. Considerable attention is paid to the development of a mathematical model of soil cultivation by the discrete element method using Hertz-Mindlin contact models, which take into account the adhesion and cohesion of particles. The article provides a calculation algorithm, the main physical and mechanical properties of soil particles, parameters for simulation, and also presents the modeling results. The proposed model allows predicting the dynamics of the interaction of soil particles with working bodies, which will contribute to increasing the efficiency and optimizing the operation of Strip-Till units. The conclusions outline directions for further research to improve the methodology and practical application of the results obtained.

The Effectiveness of E-Learning Safety Education on Safety Behavior from the Perspective of Protection Motivation Theory: A Conceptual Approach

The purpose of the study is to evaluate the effectiveness of E-Learning Safety Education on Safety Behavior from the perspective of Protection Motivation Theory. Several Effective E-Learning Safety Education antecedents, such as E-Learning format characteristics, technology characteristics, and instructor- and learner-related factors, are proposed, with implications for safety behavior. The relationship between these characteristics and safety behavior designs is observed within the Protection Motivation Theory framework that deals with threat and coping appraisal with the implication of improved Safety Behavior. A proposed theoretical framework could provide insight into E-Learning's potential to enhance safety behavior across different sectors.

Study of a Dual‐Loop Digital Control System for High‐Power Input‐Parallel Output‐Series Phase‐Shifted Full‐Bridge Converters Based on Pole Configuration

ABSTRACTDigital control is characterized by mature analysis technology and easy implementation and is widely used in high‐power input‐parallel‐output series (IPOS) phase‐shifted full‐bridge (PSFB) converters. However, in modern industrial applications, most digital controllers are still designed with traditional technologies, such as PID control. Some characteristics of this control technology, such as control time delay and approximate design process, make the results fail to achieve the expected performance. At the same time, this digital control needs to be tested in the process of use, and the process is cumbersome and difficult to achieve. Based on the existing problems, this paper deduces a discrete state space model from the application of the IPOS‐PSFB converter, focusing on the characteristics of control delay. At the same time, this paper puts forward a double‐loop control strategy to ensure the accuracy of controller design. Among them, the current and voltage loop designs are independent. The current loop and voltage loop adopts two controllers, namely, the proportional controller and PI plus state feedback controller, and the parameters of the voltage loop controller are accurately calculated according to overshoot and bandwidth index. Finally, the IPOS‐PSFB converter is simulated and analyzed by MATLAB/Simulink software, and the controller's steady‐state performance and anti‐interference are analyzed.

The Role of Big Data and Blockchain in Decentralized Decision-Making: A Comprehensive Review

This research paper investigates the synergistic role of Big Data and Blockchain in decentralized decision-making processes across a wide ambient of sectors. It goes deep in defining principles, and major characteristics of both technologies underpinning their potential in augmenting autonomy, collaboration, and democratization. The authors review current applications and implications of these technologies in improving traceability, security, and real-time analytics in various industries, such as healthcare, finance, and supply chain management. The paper discusses further emerging trends, challenges, and future directions of big data and blockchain integration, which stress further research and multi-disciplinary collaboration. These results show that the transformative potential of this technology would have a very important effect on the area of decentralized decision-making, elaborating strategic recommendations for organizations and policymakers. A lot of literature and reference reviews justify the conclusions that are drawn in this paper and thus serve as an essential tool to aid further study and innovation in this thriving field.

Algae Biofuels Hold Promise in China: Supercritical CO2 Extraction Technology

In this study, a systematic review of algae biofuels, including their development and production process, is presented. Compared with traditional techniques, supercritical CO2 extraction, known for its high efficiency and environmental sustainability, has been widely applied in extracting plant compounds, oils, and fats, demonstrating its role as a promising alternative in biofuel conversion. The principle and features of supercritical CO2 extraction technology are introduced, and its applications in biofuel production in China are reviewed. The results indicate its broad applicability and substantial scientific value in biofuel production, underscored by its unique extraction mechanisms and operational flexibility and obstacles to its large-scale implementation. Against a future where supercritical CO2 extraction will play a pivotal role in industrial biofuel production due to the technology’s advancement and policy support in China, this review offers comprehensive insights and references to guide future research into and practices of supercritical CO2 extraction and biofuel development.

MaAsLin 3: Refining and extending generalized multivariable linear models for meta-omic association discovery.

A key question in microbial community analysis is determining which microbial features are associated with community properties such as environmental or health phenotypes. This statistical task is impeded by characteristics of typical microbial community profiling technologies, including sparsity (which can be either technical or biological) and the compositionality imposed by most nucleotide sequencing approaches. Many models have been proposed that focus on how the relative abundance of a feature (e.g. taxon or pathway) relates to one or more covariates. Few of these, however, simultaneously control false discovery rates, achieve reasonable power, incorporate complex modeling terms such as random effects, and also permit assessment of prevalence (presence/absence) associations and absolute abundance associations (when appropriate measurements are available, e.g. qPCR or spike-ins). Here, we introduce MaAsLin 3 (Microbiome Multivariable Associations with Linear Models), a modeling framework that simultaneously identifies both abundance and prevalence relationships in microbiome studies with modern, potentially complex designs. MaAsLin 3 also newly accounts for compositionality with experimental (spike-ins and total microbial load estimation) or computational techniques, and it expands the space of biological hypotheses that can be tested with inference for new covariate types. On a variety of synthetic and real datasets, MaAsLin 3 outperformed current state-of-the-art differential abundance methods in testing and inferring associations from compositional data. When applied to the Inflammatory Bowel Disease Multi-omics Database, MaAsLin 3 corroborated many previously reported microbial associations with the inflammatory bowel diseases, but notably 77% of associations were with feature prevalence rather than abundance. In summary, MaAsLin 3 enables researchers to identify microbiome associations with higher accuracy and more specific association types, especially in complex datasets with multiple covariates and repeated measures.