Efficient Design Research Articles

Empowering the Sustainable Development of High-End Alloys via Interpretive Machine Learning.

The extensive use of scarce, expensive, and toxic elements in high-performance metal alloys restricts their sustainable development. Here we propose a novel alternative alloying-element design strategy that combines physicochemical-factor screening, a "black-box" interpretative method based on SHapley Additive exPlanation analysis, and sensitivity analyses of elemental influence. A "white-box" model of alloy compositions and properties is therefore established that enables the rational selection of abundant elements and the efficient designs of alloys with substitution for scarce alloying elements. The success of this design strategy is demonstrated by reducing the Co content in the C70350 alloy series (e.g., Cu-1.3Ni-1.4Co-0.56Si-0.03Mg (wt.%)). Indeed, Cu-1.95Ni-0.5Co-0.6Si-0.2Mg-0.1Cr (wt.%) is obtained as an ultra-low-Co-containing alloy by substituting only a trace amount of Cr for Co in the Cu-Ni-Co-Si-Mg system, followed by compositional optimization. Although the Co content is reduced by 64% (i.e., from 1.4 to 0.5 wt.%), the properties of the alloy (ultimate tensile strength and electrical conductivity of 850MPa and 47.2%IACS, respectively) are comparable to those of the C70350 alloy. This study contributes to the sustainable and green development of metallic materials by providing a new avenue for substituting abundant elements for scarce and undesired elements in metal alloys.

A Model-Driven Approach to Developing Scalable Educational Software for Adaptive Learning Environments

This research presents a model-driven approach to the development of scalable educational software tailored to adaptive learning environments. With the increasing demand for personalized education, adaptive learning systems play a crucial role in meeting diverse student needs by adjusting instructional content dynamically. This paper proposes a software engineering framework that integrates model-driven development (MDD) techniques with scalability principles, allowing for the efficient design and implementation of educational applications that can handle varying workloads and user demands. The framework emphasizes modular architecture, reusability, and flexibility to ensure that software can evolve with emerging educational requirements. Key components include the design of a learning content management system (LCMS) and the application of adaptive algorithms to personalize learning pathways. Additionally, this study explores the integration of cloud technologies to enhance the scalability and performance of educational platforms. A prototype system was developed and tested in a controlled environment, showing significant improvements in scalability, system performance, and student engagement compared to traditional static e-learning platforms. The results indicate that the model-driven approach not only improves software development efficiency but also offers a robust solution for creating adaptive educational systems that can scale to meet the growing needs of learners and institutions. This research contributes to the field of educational software development by providing a systematic methodology for building scalable and adaptive learning environments using advanced software engineering techniques.

A Novel Bladeless-Spinal Wind Turbine Design for Efficient Energy Generation in Low wind Speeds

Wind energy is a widely used and renewable source for electricity generation. However, traditional wind turbines face challenges such as large footprints, noise, high costs, and efficiency limitations. To address these issues, bladeless wind turbines (BWTs) have gained popularity, and extensive research is being carried out to develop efficient designs. In this work, we propose a novel BWT design, inspired by the spine structure found in human bodies. The BWT architecture is modular, autonomous, and robust, making it suitable for small, portable, and small-scale applications. Our BWT design was inspired by the spine structure found in the human body and other vertebrates. The BSWT architecture is modular, autonomous, and robust. Detailed 3D models were created using Fusion 360 and SolidWorks software to refine and iterate the design. Our BWT features a complete electrical system with an energy harvesting base, a rectifier, converter, and a storage battery. The stored energy is then converted to AC and connected to the load. Our design utilizes oscillating rods divided into sections, enabling energy generation even at low wind speeds. The casing protects the rods from shear stresses and corrosion. While practical applicates involve a spine design with multiple sections, our experiments primarily focus on a single turbine.

Efficient quantum-dot adder optimisation and analysis for future circuits

ABSTRACT In recent years, the rapid scaling of transistors has necessitated the exploration of advanced alternatives to Complementary metal oxide semiconductor(CMOS) technology for future progress. Quantum-dot cellular automata(QCA) technology has emerged as a promising solution, offering highly dense, high-speed, and low-power circuits. Among the critical digital building blocks, adder circuits play a crucial role in arithmetic and logic units. Consequently, optimising these circuits in terms of area, delay, and quantum cost is essential for the development of efficient designs. This paper presents effective multi-layer n-bit ripple carry adder(RCA) circuits, utilising full adder(FA) circuit. The outputs are generated in distinct layers and verified using the QCADesigner-Ev2.2 tool with bi-stable and coherence vector energy setups, employing Euler and Runge-Kutta methods.Additionally, the proposed designs are evaluated for various design metrics at three different scale factors(1,0.8889,and 0.7778), corresponding to cell sizes of 18 × 18 nm , 16 × 16 nm , and 14 × 14 nm respectively. The temperature’s impact on the average output polarisation of the FA is explored. The research demonstrates an n-bit-RCA surpassing existing designs with cost optimisations of 89.5%, 86%, and 90.3% for 4-bit,8-bit and 16-bit circuits, respectively. The paper also provides a thorough energy dissipation analysis for the proposed adder design.

Spectral prediction of all dielectric nanopore metasurface based on DBO-DNN model

Based on the optical properties of symmetric structures independent of each other in the orthogonal direction, a class of all-dielectric nanohole array metasurfaces symmetrical along the diagonal is designed. By adding nanopores of different shapes to break the symmetry of the periodic unit structure, the double Fano resonance is excited. The spectral characteristics of metasurfaces with the same structure type are studied by finitedifference timedomain (FDTD) method. The deep neural network (DNN) is used to establish the nonlinear mapping relationship between the input structural parameters and the transmission spectrum. The number of hidden layers in the DNN and the number of neurons in each layer are optimized by the dung beetle optimization (DBO) algorithm. Therefore, the number of hidden layers of the model is determined to be 5, and the number of neurons in each layer is 120, 30, 150, 60, 90, respectively. The mean square error (MSE) is used to evaluate the training effect of DNN after optimization search. After 35,000 epochs of training, MSE is reduced to 0.0003926. The influence of different gradient descent optimization algorithms on the prediction results is explored respectively, and it is found that Adamax is the most effective. The results show that the prediction model can predict the spectrum within 1 s. Compared with the traditional simulation method, the simulation time is effectively saved. Meet the requirements of efficient and rapid design of ultra-thin lenses. For the same type of metasurface structure, the transmission spectrum can be accurately predicted without multiple data sets.

Evaluation of space efficiency criteria in high-rise buildings based on functions: a case study of Türkiye

ABSTRACT High-rise buildings have become a significant solution to address the challenges posed by the rapid growth of urban populations and space limitations in cities. Efficient planning and design of these buildings, aiming to achieve more productivity, can be realized through ensuring space efficiency. This research compares architectural and structural design criteria affecting space efficiency in high-rises based on their functions, aiming to assess the degree of correlation among these criteria, space efficiency, and their interrelations. Currently, no studies examine the differences or similarities in space efficiency of high-rise buildings based on their functions. Additionally, selecting buildings from the same region as samples is a unique aspect of this study. Employing a case study method, the analysis encompasses 42 high-rises in Türkiye, ranging from 100 m to 300 m, and utilizes correlation analysis methods to examine the data. The comprehensive review of space efficiency in high-rises, based on their functions, yielded the following results: (i) Space efficiency ranged from 82.7% to 65.2% in high-rise case studies with different functions, with an average of 73.2%. (ii) A significant majority (83%) of the buildings followed orthogonal designs. (iii) Central core floor planning emerged as the preferred approach. (iv) Increasing elevator density reduced space efficiency. (v) Office buildings favored reinforced concrete frame systems, while residential buildings commonly used reinforced concrete shear wall systems. (vi) As building height increased, elevator and core areas expanded. These findings provide guidance for future high-rise building design and planning.

Investigation of thermal properties of ethylene glycol-based Williamson hybrid-nanofluid over stretchable/shrinking flat plate and their effects on solar panels

The global requirement for sustainable energy supply to enhance industrial productivity and reduce production costs has focused researchers’ attention to renewable energy in recent years. Solar energy mitigates the dangers connected with the use of fossil fuels in electricity generation. This work is set to evaluate the heat transmission capacities of Williamson hybrid nanofluid flow across a flat plate with viscous dissipation and heat source. The mathematical model explaining the flow interaction of Williamson hybrid nanofluid, combining viscous dissipation, heat source, and temperature-variation thermal conductivity and viscosity, is created using conservation laws. The specified system of non-linear coupled partial differential equations undergoes non-similarity transformation. The resulting non-dimensional model is solved using the bivariate spectral weighted residual method. The accuracy of the method is proven by comparing obtained results with those in the literature, and a good agreement is observed. Graphs are utilized to explain the thermophysical properties that are being considered. The results show that the fluid temperature rises when there is a source of heating and viscous dissipation. The velocity and the fluid parameter (We) have an inverse connection, whereas the temperature of the fluid has the opposite impact. Moreover, when nanoparticles are present, the thermal boundary layer rises along with the nanoparticles, thickening the velocity boundary layer and decreasing fluid velocity. Findings also show that for the Vd∈[0.1,0.5], the skin drag force and Nusselt number retard by 0.64%,14.06% for the shrinking sheet and 0.21%,6.57% for the stretching sheet respectively. In the same vein, an 100% surge in the porosity parameter escalate the skin friction coefficient by 19.13% and 26.91% and the Nusselt number by 4.92% and 2.06% respectively for both the contracting and elastic sheet. The findings in the research will provide more insight in the design and improvement of solar panel plate efficiency.

Graphene nanoribbon FET technology‐based OTA for optimizing fast and energy‐efficient electronics for IoT application: Next‐generation circuit design

AbstractThe Internet of Things (IoT) and portable electronic devices are pivotal in enhancing living standards, with battery efficiency and compact design being critical for these devices. Analogue sensors, integral to advanced artificial intelligence, often necessitate complex real‐time processing and actuation. This study examines the performance of one‐dimensional armchair graphene nanoribbons in graphene nanoribbon field‐effect transistors (GNRFETs). It compares graphene nanoribbon‐based triple cascode operational transconductance amplifiers (GNRFET‐TCOTAs) with conventional CMOS‐based TCOTA. The results reveal substantial enhancements in the GNRFET‐based TCOTAs: the pure GNR‐TCOTA variant shows a remarkable 33.8% increase in DC gain and significant improvements in transconductance, slew rate, and gain‐bandwidth, with enhancements of 8.48, 5.85, and 8.56 times, respectively. Furthermore, the pure GNRFET TCOTA exhibits higher speed, lower energy‐delay product, and settling time compared to Si‐CMOS‐based TCOTA. The study also investigates the impact of critical design parameters on circuit performance. Overall, the research highlights the potential of GNRFETs to optimize TCOTA circuits, offering a path towards more efficient and compact electronic devices, thereby advancing the state of nanoelectronics and supporting the growth of high‐performance IoT systems.

MAGIC matrices: freeform bioprinting materials to support complex and reproducible organoid morphogenesis.

Organoids are powerful models of tissue physiology, yet their applications remain limited due to their relatively simple morphology and high organoid-to-organoid structural variability. To address these limitations we developed a soft, composite yield-stress extracellular matrix that supports optimal organoid morphogenesis following freeform 3D bioprinting of cell slurries at tissue-like densities. The material is designed with two temperature regimes: at 4 °C it exhibits reversible yield-stress behavior to support long printing times without compromising cell viability. When transferred to cell culture at 37 °C, the material cross-links and exhibits similar viscoelasticity and plasticity to basement membrane extracts such as Matrigel. We first characterize the rheological properties of MAGIC matrices that optimize organoid morphogenesis, including low stiffness and high stress relaxation. Next, we combine this material with a custom piezoelectric printhead that allows more reproducible and robust self-organization from uniform and spatially organized tissue "seeds." We apply MAGIC matrix bioprinting for high-throughput generation of intestinal, mammary, vascular, salivary gland, and brain organoid arrays that are structurally similar to those grown in pure Matrigel, but exhibit dramatically improved homogeneity in organoid size, shape, maturation time, and efficiency of morphogenesis. The flexibility of this method and material enabled fabrication of fully 3D microphysiological systems, including perfusable organoid tubes that experience cyclic 3D strain in response to pressurization. Furthermore, the reproducibility of organoid structure increased the statistical power of a drug response assay by up to 8 orders-of-magnitude for a given number of comparisons. Combined, these advances lay the foundation for the efficient fabrication of complex tissue morphologies by canalizing their self-organization in both space and time.

Efficient multi-objective design method for optical coatings

The modern design of high-performance optical coatings demands a comprehensive consideration of multiple properties. We propose an efficient multi-objective optimization method utilizing an adaptive weighted sum method, exploring the lexicographic optimization and geometry-based adaptive weights determination method. Broadband negative dispersive mirrors have been designed that demonstrates notable improvements in performances of spectrum, group delay dispersion and electric field distribution. In addition, we employ Deep-learning method to enhance the optimization. The mapping between different design parameters and results has been learned, which helps the optimization to directly approach the optimal design. It extends the novel method to diverse designs utilizing the similar kinds of merit functions and subsequently accelerates the design by 120 times.

A study investigating the integrated application of intelligent construction and assembly building based on BIM technology

The construction industry, is facing the inevitable trend of digital transformation in the new wave of technology. The general production and construction build cycle is long and on-site construction activities is associated with a number of environmental issues. Additionally, the construction progress points and management are not clear, which presents a challenge for the industry. Consequently, the objective of this article is to integrate and apply a range of technologies, including BIM (Building Information Modeling), cloud computing, big data, Internet of Things, 5G, RPA (Robotic Process Automation), and others, to on-site operation control by integrating them. This integration will facilitate the analysis of the considerable advantages of intelligent construction and assembly building in its application. The conference center of the Qionglai Talent Service Exchange Center will be used as a case study to demonstrate the potential of these technologies. The paper will also propose new views and ideas for addressing the challenges currently faced by the construction industry. The research findings indicate that the integration of multiple intelligent construction systems and assembly components enhances construction progress, simplifies construction processes, and minimizes construction-related pollution. This evidence supports the viability of efficient, intelligent, and sustainable building design and construction methodologies, and provides a robust foundation for the transformation and advancement of the industry.

Innovative packaging design enhances vaccine accessibility for developing countries

Innovative packaging design enhances vaccine accessibility for developing countries Unither Pharmaceuticals is dedicated to innovating and expanding capacity to provide equitable vaccine accessibility in developing countries and enhance preparedness for future pandemics. Here, they explain how the Euroject® device can support their goals.The SARS-CoV-2 pandemic has had a devastating impact worldwide, causing seven million deaths and infecting more than 775 million people. (1) Despite the rapid development and approval of vaccines, their distribution faced significant hurdles due to shortages of consumables like glass vials. To prepare for ‘Disease X’, a term coined by governments to describe an unknown pathogen that could emerge and cause an epidemic or pandemic, many steps have been taken to increase preparedness. In this context, Blow-Fill-Seal (BFS) technology has emerged as a game-changing solution, particularly for developing countries, owing to its efficient and scalable packaging design.

Sex and Gender Considerations in Orthopaedic Research

Abstract JBJS convened a symposium to discuss the reporting of sex and gender in research studies as an imperative to improve research methods and results to benefit all patients. Barriers to improved reporting include a lack of societal and cultural acceptance of its need; a lack of education regarding appropriate terminology and appropriate statistical methods and efficient study designs; a need for increased research funding to support larger group sizes; unknown concordance of cell and animal models with humans to reflect biologic variables such as sex; and a lack of understanding of key considerations of gender, race, and other social determinants of health and how these factors intersect. Attention to developing and disseminating best-practice statistical methods and to educating investigators (at all career levels), reviewers, funders, editors, and staff in their proper implementation will aid reporting. Concomitantly, well-designed studies with sufficient rigor and adequate resources are essential to enable meaningful and reproducible research. Existing recommendations, such as the Sex and Gender Equity in Research (SAGER) guidelines, provide valuable guidance that can be applied across the research ecosystem. Academic institutions and private foundations are likely groups to assist in scientific and institutional review board guidance and study recruitment and pilot funding to generate meaningful power estimates, and to serve as sources for additional funding and presentation of workshops, educational events, and seminars. All of this needs to be conducted on an ongoing basis to ensure that sex and gender are considered in scientific analyses, where relevant.

Solid-State Structures and Properties of Lignin Hydrogenolysis Oil Compounds: Shedding a Unique Light on Lignin Valorization

This article explores the important, and yet often overlooked, solid-state structures of selected bioaromatic compounds commonly found in lignin hydrogenolysis oil, a renewable bio-oil that holds great promise to substitute fossil-based aromatic molecules in a wide range of chemical and material industrial applications. At first, single-crystal X-ray diffraction (SCXRD) was applied to the lignin model compounds, dihydroconiferyl alcohol, propyl guaiacol, and eugenol dimers, in order to elucidate the fundamental molecular interactions present in such small lignin-derived polyols. Then, considering the potential use of these lignin-derived molecules as building blocks for polymer applications, structural analysis was also performed for two chemically modified model compounds, i.e., the methylene-bridging propyl-guaiacol dimer and propyl guaiacol and eugenol glycidyl ethers, which can be used as precursors in phenolic and epoxy resins, respectively, thus providing additional information on how the molecular packing is altered following chemical modifications. In addition to the expected H-bonding interactions, other interactions such as π–π stacking and C–H∙∙∙π were observed. This resulted in unexpected trends in the tendencies towards the crystallization of lignin compounds. This was further explored with the aid of DSC analysis and CLP intermolecular energy calculations, where the relationship between the major interactions observed in all the SCXRD solid-state structures and their physico-chemical properties were evaluated alongside other non-crystallizable lignin model compounds. Beyond lignin model compounds, our findings could also provide important insights into the solid-state structure and the molecular organization of more complex lignin fragments, paving the way to the more efficient design of lignin-based materials with improved properties for industrial applications or improving downstream processing of lignin oils in biorefining processes, such as in enhancing the separation and isolation of specific bioaromatic compounds).

Comparison of efficiency of PFA catheter designs by computer modeling.

Various catheter designs are appearing for Pulsed Field Ablation (PFA). It is unclear if they differ in terms of safety and efficiency. PFA studies have reported hemolysis, kidney injury, high troponin, among other side effects. Using a CT-derived computer model, we compared catheter designs using two metrics: (1) efficiency: power delivered to an atrial wall target, expressed as a percent of total generator power; and (2) safety: electric current to achieve 90% transmurality (since more energy causes more collateral effects), as well as the corresponding electrode current density (ECD), a heat and bubble metric. The following catheter designs were compared: penta-spline basket, Nitinol spheres (focal 9 mm and large 1-shot), circular, balloon, and flex-circuit. Target was a 6 × 47 mm circumferential segment of atrial wall at LPV antrum. Transmurality was defined as percent of target having >600 volts per centimeter (V/cm) electric field needed for electroporation. Efficiency was 0.9, 1.4, 2.7, 5.9, 10, and 12% for the large 1-shot and 9 mm Nitinol spheres, penta-spline, circular, flex spline, and balloon catheters, respectively. Regarding safety, currents for 90% transmurality were 70, 39,36,12.5, 5.3, and 4 Amps for the same respective catheters, with less being safer. ECD was 124, 25, 74, 83, 41, and 31 A/cm2, respectively. Computer models demonstrated a remarkable range in efficiency among catheters studied. Those having less atrial blood exposure had the highest efficiencies, with factors of up to 13X more efficiency compared to exposed ones. Higher efficiency designs have less collateral current and are safer. Confirmatory in-vivo studies are required.

A new plastic global analysis approach for the fire design of steel and stainless steel structures

The new generation of structural codes for stainless steel allow carrying out global plastic analyses on certain types of stainless steel structures with plastic cross-sections at room temperature if the joints conforming the structure are classified as full-strength joints, a capability that has been long recognised for carbon steel structures. However, the requirements for the fire design of carbon and stainless steel structures in current and upcoming European design standards are still primarily based on the resistance of individual members, disregarding the redistribution of internal forces and strain hardening effects. Recent studies have proven that carbon and stainless steel frames with plastic cross-sections and full-strength joints are capable of redistributing internal forces at elevated temperatures, and failed describing global plastic collapse mechanisms under fire situation, suggesting that system effects are also relevant at elevated temperatures and could be taken into account for more efficient designs. On this basis, this paper develops an extensive numerical study focused on carbon and stainless steel frames under fire situation, and proposes a new methodology based on plastic global analysis to estimate the resistance of such structures under fire situation accounting for their redistribution capacity, improving the accuracy of the predicted fire time resistances significantly for the two materials.

A new approach for optimal design of intensive care unit

Planning and budgeting for healthcare facilities necessitate precise estimation and a thoughtful analysis of the required area for each department, as well as extensive knowledge of the most important elements that can influence the design and provide an appropriate environment for staff and patients. A gross conversion factor is influential in calculating the entire area of a department. However, there is no precise standard indicating how this factor should be calculated. To address this problem, quality function deployment (QFD) has been implemented. The intensive care unit (ICU) is one of the highly equipped departments that should be properly planned; therefore, it was selected for application. The five steps of the QFD are used to identify and rank the most important and efficient design features. Only the top factors are considered in calculating the required area for the ICU department. This approach presents a unique method for estimating the gross square area based on calculating the gross conversion factor. To demonstrate the proposed approach’s efficacy, it was applied to two Egyptian public hospitals. The results reveal that 15–16% of the total space of both hospitals can be reduced from the total department space. Moreover, an outstanding reduction in ICU design and preparation expenses has been achieved. The design reduces the required budget for a project while maintaining the same construction material quality and accommodating extra beds. Additionally, the QFD proves its ability to redesign the ICU department while reducing costs.

Efficient Inverse Design of Large-Scale, Ultrahigh-Numerical-Aperture Metalens

Efficient design methods for large-scale metalenses are crucial for various applications. The conventional phase-mapping method shows a weak performance under large phase gradients, thus limiting the efficiency and quality of large-scale, high-numerical-aperture metalenses. While inverse design methods can partially address this issue, existing solutions either accommodate only small-scale metalenses due to high computational demands or compromise on focusing performance. We propose an efficient large-scale design method based on an optimization approach combined with the adjoint-based method and the level-set method, which first forms a one-dimensional metalens and then extends it to two dimensions. Taking fabrication constraints into account, our optimization method for large-area metalenses with a near-unity numerical aperture (NA = 0.99) has improved the focusing efficiency from 42% to 60% in simulations compared to the conventional design method. Additionally, it has reduced the deformation of the focusing spot caused by the ultrahigh numerical aperture. This approach retains the benefits of the adjoint-based method while significantly reducing the computational burden, thereby advancing the development of large-scale metalenses design. It can also be extended to other large-scale metasurface designs.

Comparative Evaluation of Evapotranspiration and Optimization Schemes for Green Roof Runoff Simulations Using HYDRUS-1D

The use of green roofs, a low-impact development practice, can be an effective means of reducing direct runoff in urban centers. Green roof modeling can enable efficient design by preliminarily grasping the behavior of the green roof system according to specific configurations. In this study, we aimed to find appropriate evapotranspiration and parameter optimization schemes for HYDRUS-1D, a commonly used modeling tool for green roofs. Comparative studies of this sort in the context of green roof runoff modeling have not been conducted previously and are important in guiding users to overcome the difficulties of choosing the right numerical schemes for an accurate prediction of runoff from a green roof. As a study site, the Portland Building Ecoroof in Portland, Oregon, USA, was chosen, as green roof configurations and observed data for climate and runoff were available. From the simulation results of the runoff volume, the Blaney–Criddle method, which was considered an alternative, was found to be appropriate for calculating evapotranspiration from a green roof (R2 = 0.82) relative to the Hargreaves method built in HYDRUS-1D (R2 = 0.46). In addition, this study showed that the optimization method using the harmony search algorithm, which was proposed as an alternative optimizer, was better (R2 = 0.95) than that of the HYDRUS-1D’s own optimization module (R2 = 0.82) in calibrating HYDRUS-1D for green roof runoff. The findings are thought to be useful in guiding modelers who are considering using HYDRUS-1D for green roof runoff simulations.

PERANCANGAN NAKAS MULTIFUNGSI HIDDEN DRAWER DENGAN MIX MATERIAL

In the development of minimalist and modern interior design, space limitations are a major problem, especially in creating a multifunctional bedroom design. The bedroom is not only used as a place to rest, but is used as a place for storage, work, and other activities, so it requires several functional and efficient design solutions. One of the products developed is a multifunctional nightstand that has been equipped with more storage, hidden drawers, and a table top that can be directed to the bed. This product is designed using a combination of teak wood, plywood, and veneer with natural finishing, giving a natural and aesthetic impression. Research on this product uses quantitative method research through filling out questionnaires to respondents. The process of designing this product follows by using the design thinking method which involves five stages, namely the empathize, define, ideate, prototype, and test stages. The final result is a prototype of a multifunctional nightstand that has been equipped with woven rattan to add an aesthetic impression. The data shows that this product obtained score of 91.05%, which shows that this product is very attractive and meets the needs as a creative solution to the problem of limited space.