Innovative Design Research Articles

Changing Landscape of Randomized Clinical Trials in Stroke: Explaining Contemporary Trial Designs and Methods.

Evidence generated from randomized clinical trials (RCTs) plays an indispensable role in advancing clinical stroke care. Although the number of stroke-related RCTs published every year has grown exponentially over the past 25 years, the execution and completion of RCTs, particularly those conducted in a hyperacute setting, have grown more complicated and challenging over the years. In addition to the practical challenges associated with conducting a clinical trial, like obtaining human subjects approval, identifying clinical sites, training trial personnel, and enrolling the target number of patients within the available funding and timeline, the complexity of contemporary RCT designs and analyses has become much more exacting. It is no longer sufficient to have a decent understanding of the 2-arm, placebo-controlled RCT, combined with a rudimentary grasp of the P value; things are now much more complicated. Innovations in trial design and analysis, including adaptive, Bayesian, platform, and noninferiority designs, have occurred to address the problems of poor trial efficiency. However, these advances require the end user to have a much greater level of understanding regarding the rationale, conduct, analysis, and interpretation of each design. While these newer designs seek greater efficiency, there are inevitably tradeoffs that need to be understood. In this month's edition of Stroke, we introduce a new series designed to help fill in these knowledge gaps. Over the next few months, 4 papers will be published that address major design innovations (adaptive, Bayesian, platform, and noninferiority) with the aim of illustrating how these approaches can make trials more efficient (where efficiency is defined as getting to the right answer, sooner, with a potentially lower sample size). In addition to introducing this series, this current article also reviews traditional hypothesis testing and the common misinterpretations of the P value; fortunately, new philosophical schools of inference are beginning to vanquish the overreliance on the P value. We are excited about the opportunity to educate the Stroke readership about these new trial designs and the profound implications that they bring.

Innovative design strategies for solar cells: Theoretical examination of linearly graded perovskite solar cell with PTAA as HTL

Over the previous few decades, numerous scientific and theoretical approaches have been employed to increase solar cell efficiency. To improve PV cell efficiency, this study employs grading methodologies and modifies temperature, series resistance, different defect densities, and graded layer thickness. The paper presents a theoretical examination of the linearly graded device structure (Au/PTAA/CsPbBr3-xIx/TiO2/FTO). A linearly graded perovskite layer, responsible for absorbing a wide range of light spectra with different wavelengths, assists in bettering the solar cell's characteristics. In this device, polytriarylamine (PTAA) acts as an HTL, and TiO2 acts as an ETL. SCAPS-1D, a simulation program, is used for our theoretical analysis. The output results obtained from the simulation are as follows: PCE of 20.50 %, JSC of 18.071 mA cm−2, VOC of 1.4531 V, and FF of 78.08 %.

A Neuromorphic Radar Sensor for Low-Power IoT Systems

As radar sensors become an integral component of Internet of Things (IoT) systems, the challenge of high power consumption poses a significant barrier, especially for battery-operated devices. This article introduces NeuroRadar, a groundbreaking solution that leverages a radar front-end capable of generating spike sequences, which can be efficiently processed by energy-saving Spiking Neural Networks (SNNs). We explore the innovative design and implementation of NeuroRadar, showcasing its effectiveness in applications like gesture recognition and human tracking. By achieving dramatically lower power consumption compared to traditional radar systems, NeuroRadar represents a new paradigm in energy-efficient IoT sensing.

Innovative Design and Optimization of High-Quality Peanut Digging-Inverter

To rapidly dry peanut pods and effectively address mold issues resulting from rainy weather, this article provides an analysis of the current research status of global peanut digging, inverting, and harvesting technologies. Based on a two-stage peanut harvesting model, the operating principles of a high-quality peanut digging-inverter are elaborated upon, and the design of key machine components is discussed. The evaluation metrics for the operation of a high-quality peanut digging-inverter include the rate of vine inverting, the soil content rate, the rate of fallen pods, and the rate of buried pods. Utilizing theoretical analysis, the Box–Behnken experimental design is employed to investigate the operating parameters of these machines, with the tractor’s running speed, the linear speed of the inverting roller, and the linear speed of the conveyor chain serving as the experimental factors in a three-factor, three-level experimental study. A regression model is established to analyze the impact of each factor on operational quality and to comprehensively optimize the influencing factors. The experimental results indicate that all factors significantly affect the rate of vine inverting. The tractor’s running speed (X1) and the linear speed of the inverting roller (X3) significantly influence the rate of buried pods, while the linear speed of the conveyor chain (X2) does not have a significant effect on this rate. Similarly, the tractor’s running speed (X1) and the linear speed of the inverting roller (X3) significantly affect the rate of fallen pods, whereas the linear speed of the conveyor chain (X2) does not. Furthermore, the linear speed of the conveyor chain (X2) and the linear speed of the inverting roller (X3) significantly impact the soil content rate, while the tractor’s running speed (X1) does not. The optimal combination of operating parameters is a tractor running speed of 1 m/s, a conveyor chain linear speed of 1.3 m/s, and an inverting roller linear speed of 2.1 m/s. Under these conditions, the high-quality peanut digging-inverter achieves a vine inverting rate of 89.29%, a buried pod rate of 0.31%, a fallen pod rate of 0.74%, and a soil content rate of 8.11%. The experimental values for each evaluation index exhibit relative errors of 1.14%, 6.45%, 1.35%, and 0.13% compared to the optimized values provided by the Design-Expert software. The findings of this research will facilitate the development of hardware conditions for the future intelligent and information-based harvesting of peanuts, thereby establishing a solid foundation for the high-quality initial processing of oilseeds.

Advanced Applications of Nanomaterials in Atherosclerosis Diagnosis and Treatment: Challenges and Future Prospects.

Atherosclerosis-induced coronary artery disease is a major cause of cardiovascular mortality. Clinically, conservative treatment strategies for atherosclerosis still focus on lifestyle interventions and the use of lipid-lowering and anticoagulant medications. Despite achieving some therapeutic effects, these approaches are limited by low bioavailability, long intervention periods, and significant side effects. With the advancement of nanotechnology, nanomaterials have demonstrated extraordinary potential in the biomedical field. Their excellent biocompatibility, surface modifiability, and high targeting capability not only enable efficient diagnosis of plaque progression but also allow precise drug delivery within atherosclerotic plaques, significantly enhancing drug bioavailability and reducing systemic side effects. Here, we systematically review the current research progress of nanomaterials in the field of atherosclerosis to summarize not only the types of nanomaterials but also their applications in both the diagnosis and treatment of atherosclerosis. Notably, in the context of plaque therapy, we provide a comprehensive overview of current nanomaterial applications based on their targeted therapeutic systems for different cell types within plaques. Additionally, we address the persistent challenge of clinical translation of nanomaterials by summarizing current issues and providing directions for innovation and improvement in nanomaterial design. Overall, we believe that this review systematically summarizes the applications and challenges of biomedical nanomaterials in atherosclerosis diagnosis and therapy, thereby offering insights and references for the development of therapeutic materials for atherosclerosis.

Exploring the interplay of urban form and greenery in residents’ affective and cognitive responses

Stress is a prevalent issue in modern cities, exacerbated by urban development and significantly affecting urban dwellers. While it is known that greenery can contribute to people’s wellbeing, it is unclear if it can mitigate the negative effects of urban development. In this study, we aim to explore the intricate dynamics between urban form and greenery to dissect their collective effect on human wellbeing, operationalized through physiological relaxation, preference, and emotional responses. The study employs an experimental study design using virtual reality technology to immerse participants (n=156) into residential neighborhood scenes, and measures affective and cognitive responses using skin conductance measures and a survey, respectively. In general, the findings confirm the critical role of urban greenery on affective and cognitive responses. Interestingly, we observe that this effect is highly dependent on the context and shows diverging patterns between different neighborhood types. In particular, in certain neighborhoods (popular, 60 s, and cooperative), greenery, no matter if species-poor or biodiverse, consistently improves preference and physiological relaxation. In contrast, urban centers and single-family residential areas may accommodate more biodiverse green spaces without compromising their existing high preference levels when compared to less affluent neighborhoods. The study concludes with a call for urban planning to cultivate equitable, green, and distinctively designed urban environments. This shift underscores the critical role of innovative urban design in improving the wellbeing of urban dwellers.

From TCR fundamental research to innovative chimeric antigen receptor design.

Engineered T cells that express chimeric antigen receptors (CARs) have transformed the treatment of haematological cancers. CARs combine the tumour-antigen-binding function of antibodies with the signalling functions of the T-=cell receptor (TCR) ζ chain and co-stimulatory receptors. The resulting constructs aim to mimic the TCR-based and co-receptor-based activation of T cells. Although these have been successful for some types of cancer, new CAR formats are needed, to limit side effects and broaden their use to solid cancers. Insights into the mechanisms of TCR signalling, including the identification of signalling motifs that are not present in the TCR ζ chain and mechanistic insights in TCR activation, have enabled the development of CAR formats that outcompete the current CARs in preclinical mouse models and clinical trials. In this Perspective, we explore the mechanistic rationale behind new CAR designs.

An Innovative Logic Model Design to Produce High Performing Public Health Programs: Focus on Need-Based Functional Model for Effective Management of COVID-19

Logic models are valuable tools in the field of public health to picturize the relationships between program input, activities and desired outcomes. A logic model provides a clear and seamless method of designing, applying and analyzing public health programs. This article aims at understanding the different types of logic models and their use in different situations by taking into account the pros and cons of each type of model. A specific focus is placed on using Type III Logic model in preventing communicable diseases like Covid-19. This article tries to use this type of logic model in the planning phase to develop programs to address communicable diseases. Public health practitioners, managers and leaders could use this type of model in planning, implementing and evaluating their current and future health promotion and protection programs. Keywords: Logic model, Public Health Programs, COVID-19

Efficient and selective photocatalytic oxidation of benzylic alcohols with built-in electric field CsPbBr3/SiO2 nanocomposites through Fe3+ gradient doping

Lead halide perovskite nanocrystals (PNCs) have emerged as promising materials for photocatalysis due to their exceptional optoelectronic properties, yet achieving efficient charge separation and selective oxidation reactions remains a significant challenge. In this study, we report the synthesis of Fe3+-doped CsPbBr3/SiO2 nanocomposites (Fe-PNCs/SNPs) with gradient energy levels, designed to enhance photocatalytic performance. Our results demonstrate that Fe3+ doping introduces mid-gap states, promotes photoinduced charge separation, and generates reactive oxygen species (ROS) such as O2− and OH radicals under sunlight-simulating light irradiation from a 300 W Xe arc lamp. The Fe20-PNCs/SNPs catalyst achieved over 99 % conversion of benzyl alcohol to benzaldehyde with high selectivity and stability in the ethanol under ambient conditions. Additionally, the catalyst exhibited excellent recyclability and broad substrate tolerance. These findings highlight the innovative design of gradient energy levels in perovskite nanocomposites, offering a new strategy for enhancing photocatalytic efficiency in selective organic transformations.

New Thermochemical Salt Hydrate System for Energy Storage in Buildings

This paper introduces an innovative design for an “inorganic salt-expanded graphite” composite thermochemical system. The storage unit is made of a perforated, compressed, expanded graphite block impregnated with molten CaCl2∙6H2O; the humid air passes through the holes that allow the moisture to diffuse and react with the salt. The prepared block underwent 90 hydration-dehydration cycles. Although most of the performed cycles were carried out with salt overhydration and deliquescence, the treated samples have remained mechanically and thermally stable with no drop in energy density. The volumetric energy density of the composite ranged from 135.5 to 277.6 kWh/m3, depending on airflow rate and absolute humidity. To ensure composite material cycling stability, the energy density of the block was measured during hydration at similar conditions of absolute humidity, inlet temperature, and airflow rate (0.01 kgwater/kgair, 20 °C, 400 l/min). The average energy density at these conditions was sustained at 219 kWh/m3. The block integrity was monitored by visual inspection after removing it from the reactor chamber every few cycles. Both the composite material and its manufacturing process are simple and easy to scale up for future commercialization.

Vortex Nanodiscs Functionalization to Overcome Macrophage Recognition for Efficient Theragnosis Applications

Biological barriers prevent nanotherapeutics successful accumulation at target cells, limiting diagnosis and treatment responses. Magnetic nanodiscs with a spin‐vortex ground state have shown great promise for magnetomechanical cancer cells annihilation and for neuronal stimulation, requiring very low concentrations for an effective result. However, the biological barriers that these particles encounter upon intravenous administration remain a challenge. Herein, the synthesis of biocompatible multilayered Au/Fe/Au nanodiscs with a spin‐vortex ground state and their inert surface modification is reported. Two different surface modifications with two distinct polyethylene glycol (PEG) molecules are performed, which successfully reduce macrophage uptake, while maintaining the nanodiscs’ biocompatibility. By effectively preventing nanodisc uptake, innovative design features can be rationally incorporated to create a new generation of specific nanotherapeutics by modifying the PEG surface with specific targeting molecules.

Structure-Guided Bacteria Specificity and Wide Activity Spectrum of Endotoxin-Responsive Peptide Nanonets.

Peptide nanonets offer a promising avenue for constructing anti-infective biomaterials. Our group recently reported innovative designs of synthetic BTT nanonets that fibrillate selectively in response to bacterial endotoxins. Herein, we delved deeper into the molecular interactions between our peptides and these bacteria-specific biomolecules, which is an aspect critically missing from major works in the field. Using microscopic and biophysical techniques, we identified phosphate moieties in endotoxins as being the most essential to the initiation of peptide fibrillation. This was strongly supported by molecular dynamics simulations in an outer membrane environment with variable states of phosphorylation. To support the claim over bacterial specificity, we demonstrated a lack of nanonet formation in the presence of various phosphate-containing biomolecules native to human biology. The structural importance of phosphate moieties among pathogenic strains strongly indicates a wide clinical spectrum of our peptides, which was experimentally verified.

PROPOSTA DE ELETROPOSTOS MODULARES PARA CARROS ELÉTRICOS ABASTECIDOS POR ENERGIA SOLAR

In recent years, the growing demand for electric vehicles has intensified the need for adequate infrastructure for their charging. Charging stations, dedicated to supplying energy to these vehicles, play a crucial role in the transition to sustainable urban mobility. This study proposes the development of modular charging stations powered by solar energy, focusing on solutions that favor sustainability and efficiency. The primary objective is to create systems that integrate photovoltaic technology, promoting the use of clean energy and contributing to the reduction of air pollution. The research evaluates the viability of on-grid and off-grid systems, aiming to optimize the efficiency of solar panels and reduce operational costs. Factors such as ideal location, shading prevention, and the environmental impacts of electric mobility are analyzed. Additionally, existing charging station examples are examined to identify best practices and innovations in urban design. The methodology includes exploratory and bibliographic research, utilizing case studies and literature reviews to support the proposal. As a result, the study culminates in a sustainable modular charging station proposal that is adaptable to different locations, promoting more efficient and eco-friendly mobility.

Alleviating Voltage Hysteresis by Interconnecting Truncated Octahedral LiNi0.5Mn1.5O4 Cathode Particles Using Exfoliated Graphene

High‐voltage spinel LiNi0.5Mn1.5O4 (LNMO) has been highlighted as one of the most promising cathode materials for next‐generation Li‐ion batteries. However, its performance is known to have shortcomings, i.e., voltage hysteresis induced by the increasing impedance of LNMO during electrochemical cycling at high voltage operation. This paper demonstrates an innovative design of LNMO cathode materials to alleviate voltage hysteresis by combining unique characteristics of truncated octahedral LNMO with 2D exfoliated graphene (EG). The exposed (100) plane of truncated LNMO particles is known to have superior Li+ conduction. Meanwhile, the (111) plane is known to have excellent resistance to metal dissolution. Moreover, it was revealed that the presence of the EG framework as an interconnection aide could significantly improve the charge transfer process, helping to alleviate the voltage polarization. The sample with optimum LNMO‐EG composition shows a stable electrochemical performance with a capacity retention of 86.56% after 300 cycles of charge‐discharge measurement at 1 C while exhibiting almost 3 times lower voltage hysteresis (0.233 mV/cycle) compared to the pristine LNMO (0.678 mV/cycle). This result demonstrates that combining the uniqueness of truncated LNMO and 2D EG can be a promising strategy to improve the electrochemical performance of LNMO cathode materials for next‐generation batteries.

Application of improved Jellyfish search algorithm for 9-parameters cell extraction and GMPPT in PV systems

Optimization algorithms are essential tools used to address real-world problems through minimization or maximization processes. In the context of photovoltaic (PV) systems, various optimization algorithms have been employed to extract solar cell parameters using minimization techniques, and to identify the maximum power point (MPP) using maximization approaches. However, under partial shading conditions or during rapidly changing irradiance, many of these algorithms tend to get trapped in local minima, failing to locate the global maximum power point (GMPPT). This shortcoming leads to significant energy losses from PV cells. Similarly, the extraction of solar cell parameters is often compromised by the random search behavior and inadequate exploration and exploitation capabilities of many existing algorithms. The Jellyfish Search Optimization (JSO) algorithm is a recent, parameter-free method developed to tackle a wide range of optimization problems. Despite its innovative design, JSO is prone to premature convergence and exhibits a longer convergence time. To address these limitations, this paper proposes a modified version of the JSO algorithm, which integrates the state-of-the-art features of JSO with the Lévy flight characteristic from the cuckoo search algorithm. This combination aims to achieve a better balance between exploration and exploitation. To validate the effectiveness of the proposed Improved Jellyfish Search Optimization (IJSO) algorithm in PV systems, extensive experiments were conducted. These experiments included benchmarking with complex test functions, extracting cell parameters using various solar cell models, and maximizing energy output from PV systems under different environmental conditions. The results demonstrate that the proposed IJSO algorithm effectively enhances parameter extraction and global maximum power point tracking, making it a promising solution for optimizing energy extraction from PV cells in dynamic conditions.

Unveiling exotic multi-scale microstructure transformation and crack formation mechanisms in eutectic ceramic composite by laser powder bed fusion

Laser powder bed fusion (LPBF) represents an advanced and versatile technology. Exploiting its distinctive advantages for direct and rapid fabrication of complex-structured melt-grown oxide eutectic ceramic composite represents a pioneering yet challenging endeavor. In this work, LPBF is creatively employed to fabricate turbine blade-shaped, in-situ ternary eutectic ceramic composite. Through the integration of experimental procedures, Finite element method (FEM) simulations, and numerical analyses, an innovative design and manufacturing of oxide eutectic ceramic composites have been successfully established. Comprehensive FEM simulations, with detailed interface characteristic analysis, have revealed macro-scale cracks induced by intense maximum principal stress, and micro-cracks stemming from significant interfacial energy disparities among the three constituent phases. The applications of rapid solidification and nucleation theories have facilitated profound insights into the formation mechanisms of multi-scale exotic microstructures, including top-layer coarse dendrites, rosette-like spherical internally grown eutectic colony within layers, and columnar eutectic colonies with ultra-fine lamellar eutectic structures. Micro-mechanical property testing reveals enhanced performance in the inter-layer ultra-fine lamellar eutectic structure, which is attributed to a refined eutectic spacing of approximately 61 nm, coupled with distinct and robust bonding interfaces. These groundbreaking achievements, focusing on the processing-microstructure-property relationship in the fabrication of gas turbine blade-shaped solidified eutectic ceramic composite using LPBF, provide invaluable theoretical insights and data. This knowledge is crucial for the LPBF production of high-temperature structural materials, highlighting its significant potential applications in fields of aerospace and mechanical engineering.

Triangular state stress and deformation analysis of deformable tracked wheel

The Variable Morphology Wheel-Track Mechanism (VMWTM) is an innovative mobile platform design designed to overcome the limitations of traditional track and wheel designs in different terrains and mission requirements. Based on the importance of the crawler wheel in the tracked vehicle, the vehicle transmission shaft transmits the power and torque of the power source to the crawler chassis, so the overall working performance of the vehicle depends to a certain extent on the performance of the crawler wheel. In-depth and detailed research on the structure of the track wheel module is an important issue in the current vehicle design and manufacturing work. Based on the relevant theories and technologies of the finite element method, this paper conducts in-depth analysis and design. Taking the whole crawler wheel mechanism and the key components as the analysis object, the basic research method is the finite element method. The working principle of the crawler wheel is analyzed, and the load calculation, stress characteristics and structural strength of the key components of the triangular crawler wheel module are deeply explored according to the technical requirements and actual working conditions.

Assessment and learning outcomes for generative AI in higher education: A scoping review on current research status and trends

Generative artificial intelligence (GenAI) impacts higher education assessment and learning outcomes, which are closely related and intertwined. Literature suggests that educators and researchers have many varied concerns regarding student assessment in the higher education GenAI context, such as how to assess students’ learning and the new (refocused) learning outcomes that emerged in GenAI-facilitated learning environments. To provide evidence-based insights into and answers to these concerns, we conducted a scoping review by collating literature in relevant research areas. Following a five-stage scoping review framework, we collaboratively collected and coded 34 studies. The three assessment approaches identified in the review were traditional assessment, innovative and refocused assessment and GenAI-incorporated assessment. The new, refocused learning outcomes identified were career-driven competencies and lifelong learning skills. The review also revealed that most research designs were qualitatively oriented (e.g., with exploratory design, descriptive research, ethnographic research and phenomenological research). This study proposes a holistic diagram showing the current research status and trends. It suggests five future research directions: innovative assessment designs, collaborations among assessment approaches, new learning outcomes, relationships between assessment approaches and learning outcomes, and quantitative or mixed research studies. Implications for practice or policy: Traditional assessment methods in higher education do not operate effectively in the GenAI era. Innovative and refocused assessment and GenAI-incorporated assessment are promising strategies to assess student learning. Career-driven competencies and lifelong learning skills are new focused learning outcomes evolved from the use of GenAI. More quantitative and mixed research studies should be conducted to provide additional empirical evidence on the impact of GenAI on student assessment and learning outcomes.

Effect Program Educational Based on According to Raigloth Expansion Theory in Teaching Post-Modern Arts for Students of the Institute of Fine Arts

General Background: The evolving landscape of postmodern art necessitates innovative educational approaches to equip students with the skills and knowledge required to navigate this complex field. Specific Background: This research investigates the impact of an educational program grounded in Reigeluth's expansive theory on the teaching of postmodern art at the Institute of Fine Arts in Baghdad. Prior studies have highlighted the need for effective instructional designs that engage students and enhance their cognitive achievements. Knowledge Gap: Despite the proliferation of educational theories, there remains limited empirical evidence on the effectiveness of expansive instructional design in the context of postmodern arts education. Aims: This study aims to assess the effectiveness of an expansive educational program on students' cognitive achievement in postmodern art compared to traditional teaching methods. Results: Utilizing an experimental design with two equivalent groups, the findings reveal statistically significant differences (p < 0.05) in post-test scores favoring the experimental group that engaged with the educational program based on Reigeluth's theory. Novelty: This research contributes to the literature by demonstrating that an expansive instructional approach can significantly enhance students' understanding and appreciation of postmodern art. Implications: The results underscore the necessity for art education curricula to incorporate innovative instructional designs that foster deeper cognitive engagement and mastery of complex artistic concepts. By bridging the gap between theory and practice, this study offers valuable insights for educators seeking to improve instructional effectiveness in the rapidly evolving domain of postmodern art. Highlights: Impact of expansive design on cognitive achievement in postmodern art. Controlled study shows significant differences in student performance outcomes. Innovative teaching methods enhance student engagement and understanding. Keywords: postmodern art, educational program, Reigeluth's theory, cognitive achievement, instructional design

Utilization of natural kapok and coconut fiber in thermally insulated sustainable concrete design.

Nowadays, when regenerable alternative green sources are attracting more caution under sustainability targets, kapok and coconut fibers, known as natural fibers, have come to the fore as a very significant raw material source. In this experimental study, compressive strength, thermal insulation, and pore structure characteristics of kapok fiber (KP)- and coconut fiber (CC)-incorporated concrete samples under different curing conditions were analyzed. For that purpose, randomly distributed fiber-incorporated concrete mixtures containing 0%, 0.5%, 1%, and 1.5% KP and CC fiber by the weight of cement were prepared and under H2O2 and NaClO curing conditions, the effects of KP and CC fiber inclusion on properties mentioned above of fiber-incorporated concrete samples were researched in detail. Experimental results depict that a maximum thermal conductivity coefficient decrease of 24.31% was detected at a content ratio of 1.5% by the reason of the pore modification effect of used natural fibers in the H2O2 curing group. Because of the remarkable pore modification effect of KP fiber incorporation into the cement matrix compared to the CC fiber inclusion cases, strong linear correlations revealing the insulation-strength mechanism could be detected for both H2O2 and NaClO curing cases. This work intends to promote sustainable development in the building industry by integrating natural fibers into concrete mixtures as an innovative design approach.