Engineering Methods Research Articles

Discovery of new myositis genetic associations through leveraging other immune-mediated diseases

Genome-wide association studies (GWAS) have been successful at finding associations between genetic variants and human traits, including the immune-mediated diseases (IMD). However, the requirement of large sample sizes for discovery poses a challenge for learning about less common diseases, where increasing volunteer numbers might not be feasible. An example of this is myositis (or idiopathic inflammatory myopathies, IIM), a group of rare, heterogeneous autoimmune diseases affecting skeletal muscle and other organs, severely impairing life quality. Here, we applied a feature engineering method to borrow information from larger IMD GWASs to find new genetic associations with IIM and its subgroups. Combining this approach with two clustering methods, we found 17 IMD genetically close to IIM, including some common comorbid conditions, such as systemic sclerosis and Sjögren’s syndrome, as well as hypo- and hyperthyroidism. All IIM subtypes were genetically similar within this framework. Next, we colocalized IIM signals that overlapped IMD signals, and found seven potentially novel myositis associations mapped to immune-related genes, including BLK, IRF5/TNPO3, and ITK/HAVCR2, implicating a role for both B and T cells in IIM. This work proposes a new paradigm of genetic discovery in rarer diseases by leveraging information from more common IMD, and can be expanded to other conditions and traits beyond IMD.

Pengembangan Aplikasi Stunting Care untuk Pemantauan Pertumbuhan Anak

Recording the results of conventional child growth measurements in the Maternal and Child Health book has long been carried out by health workers and posyandu cadres at the Bontoharu Community Health Center, Selayar Regency, and posyandu cadres in Bontotangnga Village. This form of recording takes quite a lot of time, is prone to errors, and the results do not display attractive visualizations, so a reliable form of recording is needed to monitor children's growth as an effort to prevent and treat stunting. The method used in this community service is Community Based Research (CBR). To overcome the problem of stunting early, the Stunting Care application was developed. Stunting Care is an application for monitoring children's growth periodically by entering data on the child's height and weight. This application will provide predicted results for children, whether they are stunting, at risk of stunting, normal or high normal and is equipped with various features. The Stunting Care application was developed using agile development software engineering methods and through black box testing. The test results of the Stunting Care application are classified as good, as indicated by the system functionality running smoothly.

Optogenetics and Targeted Gene Therapy for Retinal Diseases: Unravelling the Fundamentals, Applications, and Future Perspectives.

With a common aim of restoring physiological function of defective cells, optogenetics and targeted gene therapies have shown great clinical potential and novelty in the branch of personalized medicine and inherited retinal diseases (IRDs). The basis of optogenetics aims to bypass defective photoreceptors by introducing opsins with light-sensing capabilities. In contrast, targeted gene therapies, such as methods based on CRISPR-Cas9 and RNA interference with noncoding RNAs (i.e., microRNA, small interfering RNA, short hairpin RNA), consists of inducing normal gene or protein expression into affected cells. Having partially leveraged the challenges limiting their prompt introduction into the clinical practice (i.e., engineering, cell or tissue delivery capabilities), it is crucial to deepen the fields of knowledge applied to optogenetics and targeted gene therapy. The aim of this in-depth and novel literature review is to explain the fundamentals and applications of optogenetics and targeted gene therapies, while providing decision-making arguments for ophthalmologists. First, we review the biomolecular principles and engineering steps involved in optogenetics and the targeted gene therapies mentioned above by bringing a focus on the specific vectors and molecules for cell signalization. The importance of vector choice and engineering methods are discussed. Second, we summarize the ongoing clinical trials and most recent discoveries for optogenetics and targeted gene therapies for IRDs. Finally, we then discuss the limits and current challenges of each novel therapy. We aim to provide for the first time scientific-based explanations for clinicians to justify the specificity of each therapy for one disease, which can help improve clinical decision-making tasks.

Applications of Microbial Organophosphate-Degrading Enzymes to Detoxification of Organophosphorous Compounds for Medical Countermeasures against Poisoning and Environmental Remediation.

Mining of organophosphorous (OPs)-degrading bacterial enzymes in collections of known bacterial strains and in natural biotopes are important research fields that lead to the isolation of novel OP-degrading enzymes. Then, implementation of strategies and methods of protein engineering and nanobiotechnology allow large-scale production of enzymes, displaying improved catalytic properties for medical uses and protection of the environment. For medical applications, the enzyme formulations must be stable in the bloodstream and upon storage and not susceptible to induce iatrogenic effects. This, in particular, includes the nanoencapsulation of bioscavengers of bacterial origin. In the application field of bioremediation, these enzymes play a crucial role in environmental cleanup by initiating the degradation of OPs, such as pesticides, in contaminated environments. In microbial cell configuration, these enzymes can break down chemical bonds of OPs and usually convert them into less toxic metabolites through a biotransformation process or contribute to their complete mineralization. In their purified state, they exhibit higher pollutant degradation efficiencies and the ability to operate under different environmental conditions. Thus, this review provides a clear overview of the current knowledge about applications of OP-reacting enzymes. It presents research works focusing on the use of these enzymes in various bioremediation strategies to mitigate environmental pollution and in medicine as alternative therapeutic means against OP poisoning.

Mn-doped CeO2 derived from Ce-MOF porous nanoribbons as highly active catalysts for the synthesis of dimethyl carbonate from CO2 and methanol.

It is desirable but challenging to develop highly-efficient catalysts for the direct synthesis of dimethyl carbonate (DMC) from methanol and CO2. The vacancy-mediated incorporation of heteroatom into surface reconstruction is an efficient method of defect engineering for enhancing the catalytic properties. In this work, manganese-doped cerium oxide porous nanoribbons (Mn/CeO2-BTC) were prepared derived from a Ce-BTC by a sacrificial template approach. It is found that the catalytic activity of Mn/CeO2-BTC catalysts can be readily controlled by varying the amount of Mn dopants and the as-synthesized 0.1-Mn/CeO2-BTC exhibited an outstanding activity for the synthesis of DMC from CO2 and methanol, which reached a high DMC yield (6.53 mmolDMC/gcat.) without any dehydrating agents. Based on characterization results, the enhanced performance may be attributed to the defective structures caused by Mn doping and the porous nanoribbons of the CeO2 crystals, which provide more surface oxygen vacancies and acidic-basic sites, favoring adsorption and activation of CO2 and methanol.

Research on the Performance of Fmoc-amino Acid Passivated Peroverskite Solar Cells

This study investigates the effect of surface passivation of chalcogenide solar cells by introducing Fmoc-Gly-OH amino acids. The results show that the moderate amount of Fmoc-Gly-OH modification can significantly improve the photovoltaic performance and stability of chalcogenide solar cells. With the increase of Fmoc-Gly-OH concentration, the photovoltaic conversion efficiency firstly increases and then decreases, and the best effect is reached when the concentration is 1.0 mg/ml.XRD and SEM analyses show that the crystal structure of the Fmoc-Gly-OH modified chalcocite thin films is more regular, and the defect density is obviously reduced.XPS analysis shows that the Fmoc-Gly-OH modification is able to reduce the defect state density of the chalcogenide layer. The reduction of defects was further verified by steady-state fluorescence spectroscopy analysis. In addition, the electrochemical impedance spectra and dark-state I-V curve results of the devices showed that the Fmoc-Gly-OH modification was able to reduce the non-radiative complexation and charge transport resistance, and increase the fill factor and open-circuit voltage. Finally, the effectiveness of Fmoc-Gly-OH surface passivation in enhancing the performance of chalcogenide solar cells was confirmed by the analysis of J-V curves and box plots. This study provides new ideas and methods for surface engineering of chalcogenide solar cells, which has some practical application prospects.

Review some engineering methods to facilitate basic mathematical operations

The research reviews the most important engineering methods in basic mathematical calculations. In these methods, we will present several calculations, for example, the multiplication process and the division process between different quantities, to facilitate the arithmetic process for the primary and intermediate stages of school students. These methods are considered applied research to facilitate students’ memorization of multiplication and division tables.

Air processed, high open‐circuit voltage indoor organic photovoltaic cells based on side chain modified N‐annulated perylene diimides

AbstractTo achieve high‐performance indoor organic photovoltaics (OPVs), it is important to match the photoactive layer optical absorption with the light‐source emission. This can be accomplished by developing organic photoactive materials that can efficiently absorb visible light and thus minimize energy losses. While indoor OPVs have achieved efficiencies above 33% under low light intensities, the power output is limited by low open circuit voltages (VOC), often well below 1 V. In this study, we present a series of visible‐light absorbing (energy gap >1.90 eV) non‐fullerene acceptors (NFAs) based on perylene diimide dimers, which have been systematically modified with side chains of varying polarity and steric bulk (trimethyl benzyl, ethyl adamantane, trialkoxyl phenyl, and oligo ethylene glycol). Our results show that the incorporation of sterically bulky side chains such as ethyl adamantane and trimethyl benzyl, blended with the common widegap polymer PTQ10, provides photoactive layers with absorption greater than 2.0 eV, and consequently, VOCs higher than 1.2 V are achieved under AM 1.5 G illumination. Importantly, we found that the NFA with ethyl adamantane based side chains (tPDI2N‐ethyl adamantane, compound 4) exhibited the best performance, with minimized energy loss. As a result, devices using PTQ10:tPDI2N‐ethyl adamantane photoactive layers demonstrated excellent indoor efficiencies of over 16% and 18 μW cm−2 power output under a 2700 K LED lamp at 300 lux, and showed better repeatability compared to other systems. The PTQ10:tPDI2N‐ethyl adamantane based devices maintained a high VOC (>1.0 V) across a wide range of indoor lighting conditions, including 2700 K and 6500 K LED lamps. Overall, this work provides a sidechain engineering method to create NFAs for efficient indoor OPV devices.

Baseline design of laser fusion research reactor with MW class laser facility

We propose a sub-ignition/burning reactor which is named the Laser-fusion Subcritical Power Reactor Engineering Method (L-Supreme). The reliabilities of L-Supreme in a MW class laser facility are assessed with respect to the following points: a reactor core, a target chamber, a target delivery system, an Exhaust Detritiation System (EDS), and neutron shielding. The Japan Establishment for Power-laser Community Harvest (J-EPoCH) would be applied as a MW class laser facility. A non-cryogenic glass balloon target filled with gaseous deuterium-tritium (DT) is contained in a target capsule. A chain-type magazine system might be used for a mass supply of the target capsules. Each target capsule is delivered to the center of a reactor core at 1 Hz. A batch of 10 000 laser shots would realize 0.22 MJ fusion power. The amount of tritium per batch is 1.51 × 1012 Bq. During laser experiments, unburned tritium is evacuated and transferred into an Exhaust Detritiation System (EDS). An evacuation rate of more than 0.1 m3 s−1 is required in order to recover less than 5000 Bq m−3 of the threshold of tritium concentration within 1 h. For safety, emergency situations such as tritium leakage in facilities are examined. The EDS works by internal circulation processes. Assuming leakage of tritium for a batch, an air circulation flow rate of 4100 Nm3 h−1 is required in an experimental hall for recovering less than 5000 Bq m−3 within 48 h. A primary and secondary neutron shield concept are proposed and would provide full neutron shielding. We conclude that it is possible to construct the L-Supreme system by marshalling current technologies.

Knowledge Mapping for the University: Analysis of Approaches and an Example of Its Use

The purpose of the article is to analyze the current research, development and application of knowledge maps for visualizing heterogeneous, disparate, and often hidden knowledge in universities, and discuss the features of the development of maps in higher education institutions.Materials and methods. The market for intellectual services is actively developing in Russia and worldwide, and the methods of express assessment of human capital are extremely relevant. The intellectual capital of universities is one of the most important assets in the dynamic market of educational and consulting services. Research institutes and universities are modern centers of knowledge and technology, where lecturers and researchers accumulate, transfer and produce knowledge, multiplying and replenishing explicit and implicit intellectual assets. Knowledge management helps educational and research organizations to solve the problems of managing intellectual capital, gain a competitive advantage, improve management efficiency, and reduce risks caused by the concentration of knowledge among a small number of experts. The article is devoted to the problem of analyzing new opportunities for promoting and monetizing the intellectual capital of universities through visualization and knowledge mapping. Knowledge maps of university lecturers are a relevant tool to improve the quality of research and marketing communications, as well as positioning in the market of consulting and intellectual services. Knowledge maps of educational institutions and research teams are of particular research interest, since there is no characteristic business desire to protect knowledge from transfer and reproduction in this field.The result of the study is a typology of knowledge maps, which helps to identify patterns, structures and elements necessary for the development of knowledge bases in universities. The authors based on the results of a pilot study give examples of specific maps. Based on an analysis of existing approaches to the typology of knowledge maps and Bloom’s taxonomy, a hierarchical model reflecting different levels of understanding when interpreting and using knowledge maps was developed. The main research methodology relies on fairly well developed and widely used in the world practice knowledge engineering methods – knowledge extraction, structuring and formalisation. A separate analysis of potential consumers (or stakeholders) of knowledge maps was carried out based on stakeholder theory.Conclusions. The article discusses the methodological aspects of the development and features of the practical application of knowledge maps in higher educational institutions. Knowledge analysis makes it possible to develop the organizational “memory” of a university, collecting strategic knowledge and identifying critical knowledge, and generally enriches the knowledge structure. Knowledge maps as a category of special visual tools used to analyze the knowledge and competencies of university lecturers can improve the process of managing employee competencies, management decision making, and thereby reducing cognitive load. Such maps increase the image and marketing performance of a university in the educational services market, and make the professional landscape of knowledge more transparent.

Two-step printing bionic self-lubricating composite surface fabricated by selective laser melting ink-printed metal nanoparticles

The combination of self-lubricating materials and surface texture was a promising strategy to improve tribology performance. The designed parameters and manufacturing methods of the textured composite surface were pivotal in fully harnessing this synergistic effect. Inspired by natural structures such as the scapharca subcrenata shell, trimeresurus stejnegeri snakeskin, crocodile, and tree frog toe pad surface, bionic self-lubricating composite surfaces (BSCSs) with different textures were prepared on AISI 4140 steel substrate to enhance tribological properties. These BSCSs combined self-lubricating composite material (SLCM) with copper (Cu) material in bionic patterns using the selective laser melting ink-printing metal nanoparticles manufacturing method. Tribological properties and worn surfaces of the BSCSs with various design parameters were analyzed under dry sliding conditions. Results indicated that the synergy effects of printed Cu and SLCM texture effectively reduced friction coefficient and improved wear resistance of the BSCSs. The SLCM texture density and the size of array element in the BSCSs were found to influence the types of lubricating film formed during the sliding process, thereby affecting the tribological performance. This investigation provided a potential surface design strategy and a more flexible manufacturing method for surface engineering.

Optimization of efficiency of CZTS-based solar cell through exclusive BSF layer engineering method

CZTS (copper-zinc-tin-sulfur) has recently emerged as a capable material for next-generation solar devices due to its abundance and lack of toxicity. In this study, we numerically assess the photovoltaic performance of CZTS solar cells integrated with a Back-Surface Field (BSF) layer, which is a novel approach to enhancing solar cell efficiency. We investigate the impact of various parameters, such as temperature, CZTS layer thickness, acceptor doping concentration, metal work function, and series and shunt resistances, on the electrical properties of the sc. We assess the proposed device structure's performance using ideal values for the absorber layer thickness, buffer layer thickness, and doping concentration with silicon as the BSF(Back-Surface Field) layer. By optimizing the parameters in each layer, we achieve an efficiency of 20.83 %, which is higher than previous reports in the literature. These results provide a foundation for researchers to fabricate highly efficient CZTS solar cell in the future. In summary, our findings demonstrate the potential of CZTS solar cell with a BSF layer to significantly enhance the efficiency of solar devices, and pave the way for further exploration of this technology.

Comparative results of computational and theoretical study of the annular nozzle with a flat central body

One of the ways to improve specific characteristics of the power plant of a launch vehicle for ladeploying payload to the near-Earth space is to provide the possibility of operation of a fixed nozzle in the design mode over the whole active leg of the flight trajectory. The nozzle should be compact, lightweight, well-cooled. For detailed testing of the possibility of introducing a nozzle into the rocket engine chamber it is necessary to be able to quickly assess the true value of the thrust and the specific impulse the chamber with such a nozzle can achieve. This article presents the results of comparison of the thrust and specific impulse, obtained during calculations using engineering methods, numerical modeling for the atmospheric section and high-altitude sections of the trajectory. The results of the calculation are compared with the experimental values of the specific impulse obtained on the rocket engine test-bed under atmospheric operating conditions. These results can be effectively applied both to evaluate new and to improve existing nozzle designs of wide-range rocket engines.

The investigation of oncolytic viruses in the field of cancer therapy.

Oncolytic viruses (OVs) have emerged as a potential strategy for tumor treatment due to their ability to selectively replicate in tumor cells, induce apoptosis, and stimulate immune responses. However, the therapeutic efficacy of single OVs is limited by the complexity and immunosuppressive nature of the tumor microenvironment (TME). To overcome these challenges, engineering OVs has become an important research direction. This review focuses on engineering methods and multi-modal combination therapies for OVs aimed at addressing delivery barriers, viral phagocytosis, and antiviral immunity in tumor therapy. The engineering approaches discussed include enhancing in vivo immune response, improving replication efficiency within the tumor cells, enhancing safety profiles, and improving targeting capabilities. In addition, this review describes the potential mechanisms of OVs combined with radiotherapy, chemotherapy, cell therapy and immune checkpoint inhibitors (ICIs), and summarizes the data of ongoing clinical trials. By continuously optimizing engineering strategies and combination therapy programs, we can achieve improved treatment outcomes and quality of life for cancer patients.

Staggered band alignment of n-Er2O3/p-Si heterostructure for the fabrication of a high-performance broadband photodetector

The low responsivity of conventional Silicon photodiodes in ultraviolet and near-infrared regimes restricts their utility as broadband photodetectors (BBPDs). Despite ongoing investigations into various p-n heterostructures for Silicon-based BBPDs, challenges such as high dark current (Idark), low collection efficiency, low detectivity, and compatibility issues with large-scale Silicon-based devices persist. In this context, we have fabricated relatively unexplored n-Er2O3/p-Si heterojunction-based BBPDs. Polycrystalline Er2O3 thin films (∼110 nm) were deposited on p-Si 〈100〉 substrates by radio frequency magnetron sputtering. Although this process induces a microstrain of approximately 0.022 and a dislocation density of about 0.00303/nm2, the presence of optically active defects is minimal, indicated by a low Urbach energy (∼0.35 eV). X-ray photoelectron spectroscopy (XPS) analysis confirms staggered band alignment at the heterointerface, facilitating efficient charge carrier separation and transport. Consequently, the In/p-Si/n-Er2O3/In device demonstrated significant BBPD properties– low Idark ∼0.15 μA (at +5 V), photo-to-dark current ratio (PDCR) ∼6.5 (at +5 V, 700 nm) with a maximum photoresponsivity ∼22.3 A W−1, and impressive detectivity (∼1013 Jones) even in UV-C region where traditional silicon-based photodetectors respond feebly. The device also demonstrates transient photo-response across an ultrawide spectrum (254 nm–1200 nm) with a fast rise time/fall time ∼79 ms/∼86 ms (at −5 V for 600 nm illumination). This work establishes a straightforward and reliable method for proper material engineering, surface texturing, staggered heterojunction formation, and high-performance BBPD fabrication with prominent broad-spectrum responsivity, sizeable detectivity, and fast response. The integration of these BBPDs with Silicon opens possibilities for their use in electronic devices containing optical switches for communications and broadband image sensors, enhancing their utility in various applications.

Tumor micro-environment induced TRAIL secretion from engineered macrophages for anti-tumor therapy

The high plasticity and long-term persistency make macrophages excellent vehicles for delivering anti-tumor cytokines. Macrophage delivery of chemokines and cytokines shows potential in tumor therapy. TRAIL, a promising anti-tumor cytokine, induces apoptosis in tumor cells with low toxicity to normal cells. However, its off-target toxicity and limited stability have limited its clinical progress. Here, we engineered macrophages with Mono-TRAIL and Tri-TRAIL and found that Tri-TRAIL had higher cytotoxic activity against tumor cells than Mono-TRAIL in vitro. To target the tumor microenvironment (TME), we generated macrophages secreting trimeric TRAIL (Tri-TRAIL-iM) induced by the TME-specific promoter Arg1. The Tri-TRAIL-iM cells displayed high specific activatable activity in cell-based co-culture assay and tumor-baring mice models. In addition, we demonstrated that compared to macrophages over-expressing TRAIL under a non-inducible promoter, Tri-TRAIL-iM could more effectively induce apoptosis in cancer cells, inhibit tumor growth, and reduce systemic side effects. This strategy of inducing TRAIL delivery holds great potential for cancer therapy. It is promising to be combined with other engineering methods to maximize the therapeutic effects of solid tumors.

HAPI: An efficient Hybrid Feature Engineering-based Approach for Propaganda Identification in social media.

Social media platforms serve as communication tools where users freely share information regardless of its accuracy. Propaganda on these platforms refers to the dissemination of biased or deceptive information aimed at influencing public opinion, encompassing various forms such as political campaigns, fake news, and conspiracy theories. This study introduces a Hybrid Feature Engineering Approach for Propaganda Identification (HAPI), designed to detect propaganda in text-based content like news articles and social media posts. HAPI combines conventional feature engineering methods with machine learning techniques to achieve high accuracy in propaganda detection. This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). Hybrid feature engineering entails the amalgamation of various features, including Term Frequency-Inverse Document Frequency (TF-IDF), Bag of Words (BoW), Sentimental features, and tweet length, among others. Multiple Machine Learning classifiers undergo training and evaluation utilizing the proposed methodology, leveraging a selection of 40 pertinent features identified through the hybrid feature selection technique. All the selected algorithms including Multinomial Naive Bayes (MNB), Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR) achieved promising results. The SVM-based HaPi (SVM-HaPi) exhibits superior performance among traditional algorithms, achieving precision, recall, F-Measure, and overall accuracy of 0.69, 0.69, 0.69, and 69.2%, respectively. Furthermore, the proposed approach is compared to well-known existing approaches where it overperformed most of the studies on several evaluation metrics. This research contributes to the development of a comprehensive system tailored for propaganda identification in textual content. Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination.

A review of digital twins and their application in cybersecurity based on artificial intelligence

The potential of digital twin technology is yet to be fully realised due to its diversity and untapped potential. Digital twins enable systems’ analysis, design, optimisation, and evolution to be performed digitally or in conjunction with a cyber-physical approach to improve speed, accuracy, and efficiency over traditional engineering methods. Industry 4.0, factories of the future, and digital twins continue to benefit from the technology and provide enhanced efficiency within existing systems. Due to the lack of information and security standards associated with the transition to cyber digitisation, cybercriminals have been able to take advantage of the situation. Access to a digital twin of a product or service is equivalent to threatening the entire collection. There is a robust interaction between digital twins and artificial intelligence tools, which leads to strong interaction between these technologies, so it can be used to improve the cybersecurity of these digital platforms based on their integration with these technologies. This study aims to investigate the role of artificial intelligence in providing cybersecurity for digital twin versions of various industries, as well as the risks associated with these versions. In addition, this research serves as a road map for researchers and others interested in cybersecurity and digital security.

Crystal Engineering-Driven Sunlight Responsiveness and Flexible Waveguide Transmission.

Here, a barbituric acid derivative containing pyrene rings (DPPT) was successfully synthesized, and two types of crystals were prepared by using crystal engineering methods. Orange sheet-like crystals (DPPT-O, observed in visible light), prepared in a DCM/CH3OH solution, exhibited brittleness and weak fluorescence emission, along with sunlight-induced bending and fracturing. Red needle-like crystals (DPPT-R, also observed in visible light), synthesized in a DCM/CH3CN solution, demonstrated elastic properties, strong fluorescence emission, and excellent optical waveguide performance (with an optical loss coefficient of 0.23-0.30 dB mm-1). Single-crystal data analysis revealed that the stacking arrangement of molecules critically influenced the elasticity of the crystals, while the reaction cavity size regulated the photomechanical properties of the crystals. This study achieved effective control over sunlight responsiveness and flexible optical waveguide transmission for the first time, providing innovative insights for the application of homogeneous organic polycrystalline molecular crystals in this field.

Systematic Review of Kansei Engineering Method Developments in the Design Field

Kansei engineering is a critical method for designing products that meet functionality, usability, and pleasurability, essential elements for business success. Despite its significance, there is limited understanding of how this method has evolved in recent years. This study aims to analyze the development of Kansei Engineering research from 2018 to 2022 using the Scopus database. The research methodology involved stages of identification, screening, filtering, and inclusion, resulting in 41 articles for detailed analysis out of an initial 215. The results indicate that 85% of Kansei Engineering research focuses on tangible products, with 83% categorized as type 1 studies, and 56% not integrating other methods. Additionally, 88% of the studies use only Kansei words, and 41% visualize design results as 3D images, with 95% not considering unique aspects. is dominance of tangible product design and the lack of integration with other methods suggest a need for diversification in research approaches. Furthermore, the high reliance on Kansei words and 3D visualizations points to a potential area for innovation and expansion in research techniques. This review highlights a significant research gap in Kansei Engineering studies, emphasizing the need for more diversified approaches. By identifying these gaps, the study provides a clear direction for future research, recommending that Kansei Engineering should explore beyond the predominant trends and consider integrating with other methods and unique aspects. This can enhance the method's application in industrial engineering and lead to more comprehensive and innovative product designs. Future research should aim to fill these gaps, ensuring that Kansei Engineering continues to evolve and contribute effectively to the field of product design and development.