Design Features Research Articles

Automatic Pixel-Level Segmentation of Multiple Pavement Distresses and Surface Design Features with PDSNet II

Automatic Pixel-Level Segmentation of Multiple Pavement Distresses and Surface Design Features with PDSNet II

Research Progress on Pole-Climbing Robots: A Review

Background: Pole-climbing robots are a type of application robot commonly used for quality inspection, cleaning, and maintenance of utility poles, high voltage lines, bridge cables, transmission pipelines, and other important facilities with a certain height. The working conditions are often harsh and dangerous, making manual participation unsafe. The pole-climbing robot can provide a platform for maintenance and cleaning work. Remote control operation of the pole-climbing robot is achieved through communication and control technology. It has been created to improve efficiency and reduce personnel accidents greatly. At the same time, the continuous development of science and technology has led to the expansion of robot design concepts. It has also brought about great changes and growth in the development of pole-climbing robots. Objective: The purpose of this paper is to report the latest progress in the research of pole-climbing robots from bionic and non-bionic perspectives and to provide a research reference for researchers in this field. Method: By analyzing academic theses and published patents, this paper presents a new classification of pole-climbing robots from the perspective of bionic and non-bionic. By summarizing the literature, the structural characteristics of various pole-climbing robots and their differences and applications are summarized. Results: The performance of the pole-climbing robots is analyzed from the viewpoint of structural characteristics and action execution methods. In turn, the characteristics of various types of pole-climbing robots are summarized. Finally, based on the above discussion, the future problems and development directions of pole-climbing robots are predicted. Conclusion: The pole-climbing robots can be divided into two categories, bionic and non-bionic, based on the analysis of design features. Both bionic and non-bionic pole-climbing robots have good development and applications in their respective directions. Also, bionic and non-bionic pole-climbing robots have different detailed classifications based on material, structure, and other perspectives. They have different advantages and disadvantages in terms of the performance of pole-climbing action execution. It provides a research reference for future researchers in this field.

Mining User Reviews for Key Design Features in Cognitive Behavioral Therapy-Based Mobile Mental Health Apps.

Background: Cognitive behavioral therapy (CBT)-based mobile apps have been shown to improve CBT-based interventions effectiveness. Despite the proliferation of these apps, user-centered guidelines pertaining to their design remain limited. The study aims to identify design features of CBT-based apps using online app reviews. Methods: We used 4- and 5-star reviews, preprocessed the reviews, and represented the reviews using word-level bigrams. Then, we leveraged latent Dirichlet allocation (LDA) and visualization techniques using python library for interactive topic model visualization to analyze the review and identify design features that contribute to the success and effectiveness of the app. Results: A total of 24,902 reviews were analyzed. LDA optimization resulted in 86 topics that were labeled by two independent researchers, with an interrater Cohen's kappa value of 0.86. The labeling and grouping process resulted in a total of six main design features for effective CBT-based mobile apps, namely, mental health management and support, credibility support, self-understanding and personality insights, therapeutic approaches and tools, beneficial rescue sessions, and personal growth and development. Conclusions: The high-level design features identified in this study could evidently serve as the backbone of successful CBT-based mobile apps for mental health.

Selection of Nucleotide-Encoded Mass Libraries of Macrocyclic Peptides for Inaccessible Drug Targets.

Technological advances and breakthrough developments in the pharmaceutical field are knocking at the door of the "undruggable" fortress with increasing insistence. Notably, the 21st century has seen the emergence of macrocyclic compounds, among which cyclic peptides are of particular interest. This new class of potential drug candidates occupies the vast chemical space between classic small-molecule drugs and larger protein-based therapeutics, such as antibodies. As research advances toward clinical targets that have long been considered inaccessible, macrocyclic peptides are well-suited to tackle these challenges in a post-rule of 5 pharmaceutical landscape. Facilitating their discovery is an arsenal of high-throughput screening methods that exploit massive randomized libraries of genetically encoded compounds. These techniques benefit from the incorporation of non-natural moieties, such as non- proteinogenic amino acids or stabilizing hydrocarbon staples. Exploiting these features for the strategic architectural design of macrocyclic peptides has the potential to tackle challenging targets such as protein-protein interactions, which have long resisted research efforts. This Review summarizes the basic principles and recent developments of the main high-throughput techniques for the discovery of macrocyclic peptides and focuses on their specific deployment for targeting undruggable space. A particular focus is placed on the development of new design guidelines and principles for the cyclization and structural stabilization of cyclic peptides and the resulting success stories achieved against well-known inaccessible drug targets.

Improving the ON/OFF Current Ratio and Ambipolarity of Doping-Less Tunneling Carbon-Nanotube FET Using Drain Engineering Technique

This paper presents a novel structure utilizing a doping-less (DL) tunneling carbon nanotube field-effect transistor (T-CNTFET) with dual drain work functionality aimed at enhancing the ON/OFF current ratio. The proposed design features a zigzag carbon nanotube (CNT) of type (13, 0) with a diameter of 1 nm. It employs HfO2 as the gate oxide, which is 2 nm thick and has a dielectric constant of 16. The CNT serves as an intrinsic semiconductor for the source and drain regions, which are composed of metals with appropriate work functions. By selecting appropriate metals for the source and drain regions, the necessity for doping as a fabrication step is avoided, simplifying construction and reducing costs for the nanoscale device. This design includes two drain electrodes, each measuring 15 nm in length and having different work functions (DWFs). The work function of the drain positioned closest to the channel (DWFAC) is set at 3.9 eV, which is 0.5 eV lower than that of the CNT, while the other drain section has a work function of 3.4 eV, 1 eV lower than the CNT. The electrical properties of the device were examined through quantum numerical simulations using the non-equilibrium Green's function (NEGF) method. The results indicate that the proposed structure significantly decreases the OFF-state current and improves the ON/OFF current ratio. Additionally, the leakage current is substantially lowered, resulting in favorable changes to the device's ambipolarity, along with a reduction in hot carrier effects and subthreshold swing (SS).

Method for Determining the Number of Propellers in an Aircraft from a Radar Image Obtained by Inverse Synthesis of the Antenna Aperture

The inverse antenna aperture synthesis technology used to construct a radar image of an aircraft’s propellers has shown high efficiency. The radar image allows to visualize the blades of the rotors included in the functional group (traction rotors of an aircraft, rotors of a twin-rotor helicopter, rotors of a multicopter). In the case of a single rotor in an aircraft (an airplane’s tractor rotor, a single-rotor helicopter’s main rotor), the radar image is simple and clearly perceptible. In the case of several propellers belonging to the same functional group, the ana ysis of the radar image becomes significantly more complicated. This is due to the random relative position of the blades of different propellers at the moment the image begins to be constructed, as well as the possible random coincidence of the spatial position of the blades belonging to different propellers. In this regard, determining the number of propellers in an aircraft is a new urgent task, the solution of which allows us to obtain additional information for recognition. The method under consideration for determining the number of propellers is based on the most common design features – the blades in the propeller follow at the same angular interval, in the propellers of the functional group the number of blades is the same.

Particle swarm optimization of high Q factor interdigitated E-shaped metamaterial for refractive index sensing

AbstractMetamaterials for refractive index sensing applications have garnered significant attention in recent years. However, achieving an optimal balance between high sensitivity and quality factor, which together determine the Figure of Merit of sensors, necessitates extensive optimization efforts. In this paper, we present the metaheuristic optimization of a refractive index-based plasmonic sensor operating at a wavelength of 1500 nm, which has the potential to open new avenues for applications in biomedical sensing and beyond. Particle Swarm Optimization is utilized to maximize the performance of the proposed infrared metamaterial sensor. The proposed design features two overlapping E-shaped silver patches placed on top of a grounded $$\mathrm {Al_{2}O_{3}}$$ Al 2 O 3 substrate. This configuration results in a narrow-band absorption spectrum with peak resonances caused by the confinement of the electric field within the gaps of the E-shaped metallic arms. The metaheuristic optimization process yielded sensor dimensions that achieve a high sensitivity of 834.7 nm/RIU,Q = 865 and a Figure of Merit of 481.34 $$\textrm{RIU}^{-1}$$ RIU - 1 , demonstrating outstanding performance in cancer cell detection.

Maximizing desalination performance in pyramid distiller: Integration of vertical wick still and enhanced phase change material by nanoparticle and emerging fins

The growing global water crisis, driven by population growth and dwindling freshwater resources, demands innovative solutions for sustainable desalination. While traditional solar still designs have been explored, their efficiency remains limited. This study introduces an advanced approach to solar distillation by integrating a modified pyramid solar still (MPSS) with two key innovations: a vertically positioned wick still (VWSS) and phase change material (PCM) enhanced with silver nanomaterials (PCM-Ag Nano). In addition, the design features two absorber plate configurations—flat and finned—coupled with emerging fins (EF) within the PCM unit to improve heat conductivity, addressing a common limitation in solar distillation systems. By incorporating PCM-Ag Nano and finned absorbers, the MPSS achieved significant improvements in desalination performance. The combined system of MPSS-FA-PCM-Ag-EF and VWSS produced a total distillate volume of 12,870 ml, representing a 154 % increase over a conventional pyramid solar still (PSS). Specifically, daily outputs of 9,270 ml, 5,050 ml, and 3,600 ml were recorded for MPSS, PSS, and VWSS, respectively. Furthermore, the enhanced MPSS configuration attained the highest thermal efficiency at 60.5 %, and the desalination cost was reduced to $0.0142/L, compared to $0.019/L for the PSS. These results underscore the potential of this novel MPSS design, which combines PCM-Ag Nano and VWSS, to deliver substantial improvements in freshwater production, thermal efficiency, and cost-effectiveness. This innovative system offers a promising alternative to traditional desalination techniques, contributing to the global effort to mitigate water scarcity.

Construction of a prototype of the basic module of a scalable robotic system for simulation of composite surfaces for dynamic tests

The authors of the article developed a mathematical model of Stewart platform management. The angles of rotation of the servo shafts were obtained when setting various laws of motion of the mobile platform, in matrix mode. The hardware part of the prototype of the basic module of a scalable robotics system for modeling composite surfaces for dynamic tests was developed. The results of calculations of the maximum permissible load on the shafts of servos are presented. The CubeIDE settings for programming the STM32 microcontroller are given. The results of software development for the control of this prototype were obtained, namely, a library for controlling 6 servo drives under driver control was written. The problems that may arise during the above-described developments by future developers are considered, solutions to these problems are obtained. Detailed design features of this prototype are described, the control code of the servo drive is given; steps for further development of the final robotic system are considered

Exploring the Influence of Interactive and Empathetic Chatbots on Health misinformation Correction and Vaccination Intentions

Chatbots are increasingly used to correct health misinformation. However, few studies have investigated whether and how certain design features could enhance their effectiveness. We developed four chatbots and conducted an experiment that examined whether chatbots with interactive and empathetic conversational cues could outperform a basic chatbot at correcting unvaccinated participants’ COVID-19 vaccination misperceptions and increasing their vaccination intentions. Perceived chatbot interactivity was associated with lower levels of misperception, which in turn were linked to greater vaccination intention. Perceived chatbot empathy did not reduce misperception, yet was directly and positively associated with vaccination intention. Implications of these findings are discussed.

Upgraded front ends for SLS 2.0 with next-generation high-power diaphragms and slits.

The upgrade of the Swiss Light Source, called SLS 2.0, necessitates comprehensive updates to all 18 user front ends. This upgrade is driven by the increased power of the synchrotron beam, reduced floor space, changing source points, new safety regulations and enhanced beam properties, including a brightness increase by up to a factor of 40. While some existing front-end components are being thoroughly refurbished and upgraded for safety reasons, other components, especially those designed to tailor the new synchrotron beam, are being completely rebuilt. These new designs feature innovative and enhanced cooling systems to manage the high-power load and meet new requirements such as mechanical stability and compact footprints.

Comparative Analysis of Space Efficiency in Skyscrapers with Prismatic, Tapered, and Free Forms

This study offers a thorough comparative analysis of space efficiency in skyscrapers across three distinct forms: prismatic, tapered, and free. By examining case studies from each form category, this research investigates how architectural and structural design features impact space utilization in supertall towers. The findings reveal form-based differences in space efficiency and design element usage. In prismatic skyscrapers, which are primarily residential and utilize concrete outrigger frames, the average space efficiency was around 72%, with the core occupying 24% of the gross floor area (GFA). Tapered skyscrapers, commonly mixed-use with composite outrigger frames, showed an average space efficiency of over 70%, with a core-to-GFA ratio of 26%. Freeform towers, often mixed-use and using composite outrigger frames, demonstrated a space efficiency of 71%, with an average core-to-GFA ratio of 26%. Despite these variations, a consistent trend emerged: as the height of a building increases, there is a general decline in space efficiency, highlighting the challenges in optimizing space in taller structures. This analysis adds to the understanding of skyscraper design and space utilization, providing important insights for architects and urban planners aiming to improve the efficiency of future high-rise developments.

Adaptive Trials in Stroke: Current Use and Future Directions.

Inclusion of adaptive design features in a clinical trial provides preplanned flexibility to dynamically modify a trial during its conduct while preserving validity and integrity. Adaptive trials are needed to accelerate the conduct of more efficient, informative, and ethical clinical research in the field of neurology. Stroke is a natural candidate for adoption of these innovative approaches to trial design. This Research Methods in Neurology article is informed by a scoping review that identified 45 completed or ongoing adaptive clinical trials in stroke that were appraised: 15 trials had published results with or without a published protocol and 30 ongoing trials (14 trials had a published protocol, and 16 trials were registered only). Interventions spanned acute (n = 28), rehabilitation (n = 8), prevention (n = 8), and rehabilitation and prevention (n = 1). A subsample of these trials was selected to illustrate the utility of adaptive design features and discuss why each adaptive feature was incorporated in the design to best achieve the aim; whether each individual feature was used and whether it resulted in expected efficiencies; and any learnings during preparation, conduct, or reporting. We then discuss the operational, ethical, and regulatory considerations that warrant careful consideration during adaptive trial planning and reflect on the workforce readiness to deliver adaptive trials in practice. We conclude that adaptive trials can be designed, funded, conducted, and published for a wide range of research questions and offer future directions to support adoption of adaptive trial designs in stroke and neurologic research more broadly.

Development of novel CDK9 and CYP3A4 inhibitors for cancer therapy through field and computational approaches

Cyclin-dependent kinase 9 (CDK9) and cytochrome P450 3A4 (CYP3A4) have emerged as promising targets in the development of anticancer drugs, presenting a consistent challenge in the quest for potent inhibitors. CDK9 inhibitors can selectively target fast-growing cancer cells by disrupting transcription elongation, which in turn hinders the production of proteins essential for cell cycle progression and survivaŚ. Understanding how CYP3A4 metabolizes specific chemotherapy drugs allows for personalized treatment plans, optimizing drug dosages according to a patient’s metabolic profile. Since many cancer patients undergo combination therapies, and CYP3A4 is vital in drug metabolism, its inhibition or induction by one drug can alter the plasma levels of others, potentially leading to treatment failure or increased toxicity. Therefore, managing CYP3A4 activity is critical for effective cancer treatment. Employing a range of computational methodologies, this study systematically investigated the binding mechanisms of pyrimidine derivatives against CDK9 and CYP3A4. The field-based model demonstrated high R2 values (0.99), with Q2 (0.66), demonstrating its ability to predict in silico inhibitory activity against the target of this study. The screening process followed in this work led to the discovery of powerful new inhibitor compounds. Of the 15 new compounds designed, three have a high affinity with the target (ranging from −8 to −9 kcal/mol kcal/mol) and were singled out through docking filtration for more detailed investigation. As well as, a reference compound with a substantial pIC50 value of 8.4, serving as the foundation for the development of the new compounds, was included for comparative analysis. To elucidate the essential features of CDK9 and CYP3A4 inhibitor design, a comparative analysis was conducted between 3D-QSAR-generated contours and molecular docking conformations of ligands. Molecular dynamics simulations were carried out for a duration of 100 ns on selected docked complexes, specifically those involving novel compounds with CDK9 and CYP3A4 enzymes. Additionally, the binding free energy for these complexes was assessed using the MM/PBSA method, which evaluates the free energy landscape of protein-ligand interactions. The results of MM/PBSA highlighted the strength of the new compounds in enhancing interactions with the target protein, which favors the results of molecular docking and MD simulation. These insights contribute to a deeper understanding of the mechanisms underlying CDK9 and CYP3A4 inhibition, offering potential avenues for the development of innovative and effective CDK9 inhibitors.

Heritagizing the Maestro

Bhupen Hazarika was a multifaceted personality known for his contributions as a singer, songwriter, composer, filmmaker, writer, and social activist from Assam, a state in the north-eastern part of India. To honour his life and works, a memorial site is constructed in the Jalukbari area of Assam. The site is called ‘Dr Bhupen Hazarika Samadhikshetra’. It is located in Guwahati city, near Gauhati University, in the state of Assam, India. The literal meaning of the Assamese words Samadhikshetra is a burial site. Through empirical research, the paper investigates the conceptual framework of heritagization as applied to Dr Hazarika’s legacy, focusing on preserving, maintaining, and celebrating his contributions to society. The study emphasises the role of the memorial site, as a tangible example of Dr Hazarika’s cultural relevance by delving further into its architectural design, symbolic elements, and commemorative features. Beyond these tangible aspects, the study also addresses the intangible values, identity and collective memories that the site evokes and preserves. The paper also explores the close interaction between the cultural and constructed heritage of the site, emphasising the need for a holistic strategy to protect and preserve the cultural past. Despite controversies and challenges over selecting the last resting place of Dr Hazarika, the Samadhikshetra stands as a tribute to his lasting influence and gratitude for his artistic legacy. Through commemorative events and ongoing public engagement, the memorial site continues to serve as a sacred space where Dr Hazarika’s spirit can live on and inspire future generations.

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.

Enhancing Printability Through Design Feature Analysis for 3D Food Printing Process Optimization

We present a novel, systematic method for evaluating design printability in 3D food printing using a scoring system based on the Design for Additive Manufacturing (DfAM) guidelines. This study addresses a gap in the current literature by proposing a structured approach to assess and enhance the printability of 3D food designs. Our framework consists of a set of nine critical questions derived from the multi-level DfAM guidelines, focusing on key printability factors including unsupported features, geometric accuracy, and surface finish. The evaluation process converts qualitative assessments into numerical values, resulting in a comprehensive printability score that categorizes designs into high, moderate, or low printability levels. To validate the effectiveness of this method, we conducted a case study involving five different designs. The scoring system successfully explores the design space and maximizes the printability of 3D food products. This method alleviates the challenges in design evaluation compared with traditional trial-and-error approaches. The results demonstrate the practicality and efficiency of our framework’s output. The proposed methodology provides a structured approach to design evaluation, offering practical insights and a valuable tool for improving the success rate of 3D printed food products. This research contributes to the field by offering a systematic framework for assessing and enhancing the printability of 3D food designs, potentially accelerating the adoption and effectiveness of 3D food printing technology in various applications.

Designing a Human-centred Learning Analytics Dashboard In-use

Despite growing interest in applying human-centred design methods to create learning analytics (LA) systems, most efforts have concentrated on initial design phases, with limited exploration of how LA tools and practices can co-evolve during the actual learning and teaching activities. This paper examines how a human-centred LA dashboard can be further refined and adapted by teachers while actively using it in a real-world scenario (i.e., design-in-use), beyond its intended design (i.e., design-for-use). We use instrumental genesis as a theoretical lens to analyze the temporary and permanent instrumentalization of design features and individual and collective instrumentation of the LA dashboard. The analysis of semi-structured individual interviews with five nursing teachers who used an LA dashboard to guide team reflections with 224 students (56 teams) revealed technical and pedagogical changes that occurred in both the system’s features (instrumentalization) and teaching practices (instrumentation). We found that teachers adopted the LA dashboard beyond initially intended ways by (i) providing emotional support with the analytics, (ii) reducing details in AI-powered data visualizations for easier comprehension, (iii) creating data narratives to address data limitations, and (iv) collectively developing new practices to use the LA dashboard for co-teaching. Therefore, teachers’ design-in-use of the LA dashboard highlights the ongoing need for design improvements to address challenges posed by dynamic data and complex algorithms underlying AI and analytics interfaces.

Enhancing AR‐based learning environments for STEM education: A design‐based study on design features, kinematics learning and mathematics self‐efficacy

AbstractThis design‐based research project explored how various design features of AR‐based learning environments (ARLE) influence students' mathematics self‐efficacy and learning of kinematics. Specifically, five ARLEs with different design features were developed and implemented with 136 seventh‐grade students in two rounds. Data were gathered from pre‐ and post‐mathematics self‐efficacy tests, interviews, classroom observation records and reflective journals, to identify which design features promote or hinder students' learning and self‐efficacy. Results revealed that adopting a well‐designed ARLE is a viable way to promote students' learning and mathematics self‐efficacy, and the success of ARLE lies in (1) coherent tasks with proper time for self‐exploration, progressive levels, useful problem contexts and a certain degree of open‐endedness, and (2) sufficient technological affordances with strengthened authenticity, clarity and integrated media presentation, as well as engaging interactions with decent flexibility, embodied actions and feedback. These results validated the applicability of the proposed checklist for ARLE designers and practitioners in their design and implementation of ARLEs, within the domain of mathematics, physics and beyond. Practitioner notesWhat is already known about this topic AR‐based learning environments (ARLEs) have demonstrated substantial advantages in STEM education, but ARLEs can be a drawback if they are not adequately designed. ARLE may facilitate students' mathematics self‐efficacy, and relevant design features are underexplored. Design‐based research sustains interventions combining empirical research and theory‐driven design of innovative learning environments, for example, ARLEs. What this paper adds Demonstrates the potential of ARLEs that can be used in classrooms to support STEM learning. Identifies a collection of effective and ineffective design features of ARLEs that promote or hinder students' STEM learning and mathematics self‐efficacy. Tackles the challenges for the design of ARLEs for classrooms by taking AR technological affordances and the pedagogical perspective together. Implications for practice and/or policy Five ARLEs for STEM topics were developed and implemented in secondary schools. Evidence of positive impacts of ARLEs on students' learning and mathematics self‐efficacy. Our research produces useful guidelines for designers and practitioners in their development and implementation of ARLEs in real classrooms.

States' AGs take TikTok to court for causing harm to children's mental health

The attorneys general of 13 states and the District of Columbia filed a lawsuit against TikTok Oct. 8, stating that the app's addictive design features are doing damage to the mental health of children and teens. The goal of the suits, the attorneys general said, is to stop TikTok from using addictive features, impose financial penalties, and collect damages for users who say the app has harmed them.