Design Tool Research Articles

Screening for Psychosocial Distress: A Brief Review with Implications for Oncology Nursing.

Psychosocial care is an integral component of caring for individuals living with cancer. The identification of psychosocial distress has been acknowledged as a hallmark of quality cancer care, and screening for distress standards has been established in several countries. The purpose of this brief review is to highlight recent developments in screening for distress in oncology populations; to provide insight into significant trends in research and implementation; and to explore implications for oncology nursing practice. This paper reports a brief review of the literature from March 2021 to July 2024 on the topic of screening for distress in oncology. The literature was accessed through PubMed and reviewed by two authors. Trends in the topics presented were identified independently and then discussed to achieve consensus. The search within the designated period produced 47 publications by authors in North America, Australasia, and Europe. Topic trends included the design and adaptation of tools for special populations, the use of technology, descriptions of programs, identification of benefits, challenges, and overcoming barriers to screening for distress. Screening for distress is endorsed as part of the provision of quality oncology care. Nurses have an important role in screening individuals at risk for developing psychosocial problems and acting to reduce the associated morbidity. By continuing to be informed and educated about the emerging developments in screening for distress, nurses can understand and overcome barriers to implementation.

Evaluation of prototyping methods for interactive virtual systems based on fuzzy preference relation

The object of this study is the process of determining the optimal method for prototyping interactive virtual systems using the principle of multi-criteria optimization. The paper addresses the task to design tools for evaluating prototyping methods and introduces software developed to identify the best option according to priority criteria. The optimal prototyping method was chosen based on the maximum value of the membership function with indicators of 0.3, 0.7, and 1. Thus, the best method for the given task is rapid prototyping, with a membership function value equal to 1. These results have made it possible to solve the problem by evaluating fuzzy preference relations on a set of alternatives. Additionally, a relation convolution was constructed, from which a subset of non-dominated alternatives was identified. The key features of the proposed approach are obtaining clear quantitative evaluation parameters by processing descriptive, non-unified, and non-formalized input data. The fuzzy preference relations for the set of alternatives are explained by the analysis of the most common methods for prototyping interactive systems. The developed information system could be used for managerial decision-making regarding the selection of optimal prototyping option from several possibilities, by comparing methods based on predefined criteria with arbitrary weighting coefficients. The result of the research is a universal system adaptable to specific user tasks. The resulting data will contribute to improving the efficiency of prototyping and, consequently, reducing costs.

Performance Evaluation of FPGA-Based Design of Modified Chua Oscillator

The chaotic systems are one of the most important areas that increasing the popularity and are actively used in several fields. One of the most essential structures in chaotic systems is chaotic oscillator which generates chaotic signals. IQ-Math and floating point number systems are one of the preferred number standards. Presented in this study, the Modified Chua chaotic oscillator has been designed to work on FPGA chips using fixed point and floating point number systems. Euler numeric algorithm has been used for the design of the Modified Chua chaotic oscillator. The first section of the study, Modified Chua chaotic system based on fixed point has been composed the model in the Matlab Simulink and transformed to VHDL with the help of Matlab HDL Coder Toolbox. The second section of the study, Modified Chua chaotic oscillator has been designed with VHDL based on floating point. Modified Chua chaotic oscillators which are composed with two different number standards have been tested using Xilinx ISE Design Tools in VHDL. Modified Chua chaotic oscillators which have two different numbers standards and designed, are synthesized for Virtex-6 on ML605 FPGA development board with Xilinx ISE Design Tools 14.2 program. Values that are achieved from the process of synthesizing and maximum operating frequency have been presented. As a result, the study has obtained that fixed point number standard maximum operating frequency is 50.242 MHz and floating point number standard maximum operating frequency is 273.631 MHz.

A Systematic Review of the Digital Twin Technology in Buildings, Landscape and Urban Environment from 2018 to 2024

Digital Twin (DT) technologies have demonstrated a positive impact across various stages of the Architecture, Engineering, and Construction (AEC) industry. Nevertheless, the industry has been slow to undergo digital transformation. The paper utilizes the Systematic Literature Review (SLR) approach to study a total of 842 papers on the application of DT in buildings, landscapes, and urban environments (BLU) from 2018 to 2024. Based on the research results, suggestions have been made for future research and practical directions. Meanwhile, it provides assistance to BLU’s designers, constructors, managers, and policymakers in establishing their understanding of the digital transformation of the AEC industry. The existing relevant research can be mainly divided into three categories: case study, framework study, and technology study. Compared with the buildings and urban environment industries, the number and depth of research in the landscape industry are relatively low. Through in-depth analysis of BLU projects, three research trends in the future are determined: (1) research and application of DT framework in the design and planning stage; (2) development of design tools and basic theory based on DT model; (3) application and exploration of DT technology in the landscape industry.

Genome guided, organ-specific transcriptome assembly of the European flounder (P. flesus) from the Baltic Sea

Although the European flounder is frequently used in research and has economic importance, there is still lack of comprehensive transcriptome data for this species. In the present research we show RNA-Seq data from ten selected organs of P. flesus female inhabiting brackish waters of the Gulf of Gdańsk (southern Baltic Sea). High throughput Next Generation Sequencing technology NovaSeq 6000 was used to generate 500 M sequencing reads. These were mapped against European flounder reference genome and reads extracted from the mapping were assembled producing 61k reliable contigs. Gene ontology (GO) terms were assigned to the majority of annotated contigs/unigenes based on the results of PFAM, PANTHER, UniProt and InterPro protein databases searches. BUSCOs statistics for eukaryota, metazoa, vertebrata and actinopterygii databases showed that the reported transcriptome represents a high level of completeness. The data set can be successfully used as a tool in design of experiments from various research fields including biology, aquaculture and toxicology.

Design and application of low-cost polymer composite shell and backfill tooling for stamping of HSS 590 sheets

Design and application of low-cost polymer composite shell and backfill tooling for stamping of HSS 590 sheets

CRISPR System and Its Applications in Medicine and Stem Cell Engineering

Context: The clustered regularly interspaced short palindromic repeat (CRISPR)/Cas system is a groundbreaking gene-editing tool that shows great promise for modifying genomes. Derived from prokaryotic adaptive immune defense mechanisms, this technique has been used in research on human diseases, demonstrating remarkable therapeutic potential. Through CRISPR, specific genetic mutations in patients can be corrected during gene therapy, offering a solution for treating diseases that were previously untreatable using conventional methods. This review explores the recent progress and future prospects of the CRISPR system, focusing on its applications in medicine and stem cell engineering. Special emphasis is placed on medical applications, the latest target design or analysis tools for genome editing, advancements in stem cell engineering, and associated innovations and challenges. Evidence Acquisition: This study reviewed articles indexed in ISI, SID, PubMed, and PubMed Central from 2007 to 2024. Results: Cas9, a key protein in CRISPR gene editing, is an endonuclease capable of targeting and cutting specific DNA sequences, guided by short RNA sequences. The gene editing process involves homology-directed repair (HDR), non-homologous end joining (NHEJ), and base editing pathways. Base editing, which modifies the epigenome without inducing DNA breaks, is gaining increasing attention. However, CRISPR still faces technical challenges, and the development of more efficient "super" CRISPR technology will likely require time. This article reviews the effectiveness, limitations, and applications of the CRISPR system. Conclusions: CRISPR/Cas9 tools allow for the creation of precise models, leading to more effective treatment options for patients.

Leveraging Uncertainty as a Means of Facilitating Sensemaking Within a Digital Wildfire Curriculum

AbstractThe changing landscape of geoscience learning has initiated growing interest in engaging science learners with climate data. One approach to teaching climate is the application of broadly accessible digital science curricula, which often include data tools such as visualizations, data representations, and simulations embedded within digital science curricula. We are specifically interested in how students and teachers grapple with scientific uncertainty in digital curricula. Our paper therefore examines how a 7th grade science class and their teacher leverage moments of uncertainty in their work within a digital geohazard curriculum to learn about wildfire risk and impact. We analyzed episodes of learners’ interactions, and those included scientific uncertainty related to key ideas about wildfires. We also attend to how the teacher orchestrates across class members’ ideas and the representations they were using. Our findings suggest that the digital curriculum elicited important sensemaking about wildfires and climate, including the interpretation of trends (Episode 1), working with simulations as a means of scientific investigation (Episode 2), and making meaning across disparate climate maps (Episode 3). Importantly, our analysis highlights the imperative work of the teacher in creating and leveraging productive sensemaking around the climate representations and simulations, yet outside of the predetermined curriculum. Our findings illustrate that maximizing students’ learning about climate in digital science curricula demands attention beyond teachers’ ad hoc adaptation, and rather, the intentional design of tools that support sensemaking about uncertainty as a dialogic process that is negotiated in response to students’ ideas.

Design method for individualised 3D printed lattice shoe midsoles

Additive manufacturing has enabled the production of individualised 3D printed shoe soles with improved properties. A promising approach is to use lattice structures that have high energy absorption properties and low weight. A design method of a cellular shoe midsole with optimised strut diameters of lattice structures is proposed. The shoe sole model is obtained by re-modelling a 3D scan of a foot to ensure a customised fit. The optimisation of strut thicknesses is based on a simplified stress distribution acting on the shoe sole during walking or running, using finite element simulations. Therefore, the optimal strut thickness for each region of the sole can be determined and adjusted. Two types of lattice structures with different topology and thus significant variations in stiffness are chosen, resulting in a wide range of required strut thicknesses. The developed design process allowed for the creation of a 3D printed shoe sole with improved strut thicknesses and a customised fit. The resulting cellular shoe soles are additively manufactured and experimental compressive tests are conducted to investigate the mechanical behaviour and differences between the shoe soles with the corresponding lattice types. The results show that both shoe soles have a similar behaviour under compression. The design tool developed has the potential to improve foot health and comfort, especially for people with foot problems, as all parameters affecting the performance of a shoe sole can be adjusted. However, more research is needed to fully understand the durability and performance of these shoe soles in real-world conditions.

Application of Mixture Design for Optimization of Smoke Signal Formulation: A Comparative Study of KClO3 and KNO3 as Oxidizers

Smoke signals are traditionally used in military contexts, but in recent times, they have gained popularity among civilians. The M18 smoke grenade was designed with a highly reactive oxidizer, KClO3, and substituting it with a safer oxidizer, notably KNO3, is one way that helps provide a safer choice for civilian use. However, providing optimal formulations for both formulations helps in deciding whether KNO3 can be substituted for the traditional KClO3 oxidizer. One of the techniques for enhancing smoke formulation is the Design of Experiments (DOE). Many researchers these days are focusing on substituting the smoke chemicals for a safer option using a trial-and-error process. However, from the standpoint of environmental contamination, numerical testing to identify the most significant output causes air pollution and chemical waste, which is not only costly but also endangers sea life if not properly disposed of. Therefore, it is crucial to optimize the smoke formulation in order to decrease waste and air pollution as well as enable future mass production of the product for both military and civilian use. The purpose of this paper is to implement the mixture design tool of the DOE approach to determine the optimal formulation of smoke signals using KClO3-based formulations, as well as to provide a comparative analysis of substituting KNO3 to optimize KClO3-based formulations in terms of time and smoke emission. From the KClO3-based formulation (28.68 wt.% KClO3, 23.47 wt.% C12H22O11, 34.39 wt.% dye, and 13.46 wt.% MgCO3) with an average time of 73.43 seconds, an acceptable formulation with a data means of 73.43, substituting with KNO3 oxidizer gave an average of 80.18 seconds, in which the smoke emission was slightly thinner compared to KClO3. As a result, KNO3 can be used as an alternative oxidizer to KClO3, and the KClO3-optimized formulation can be considered a baseline for smoke formulation for future research.

Designing the public works values

What are public works, and under what conditions can they be considered a “common value” recognized by the community? The contributions to issue n. 28 of TECHNE Journal delve into these conditions, offering critical reflections and research advancements that examine cities, buildings, places, and public services from the perspective that «the entire urban space must be regarded as something produced, owned, and transformed collectively» (Marella, 2024). There are three main areas of reflection and proposal: the first involves the methods and procedural and design tools that can be employed for the recovery and adaptive reuse of public works facing functional obsolescence, abandonment, and/or decay; the second addresses the regenerative processes of public spaces and entire urban sectors with a focus on usability and environmental sustainability; and the third concerns the participatory design of public works as a vital lever for the creation of social value. This set of design actions is well-supported by analytical and evaluative tools that guide the decision-making process, all driven by an interest in optimizing the socio-economic, cultural, and environmental benefits that can result from more effective and efficient public works production and management processes, especially in response to evolving social demands.

SMEC: A card-based participatory design tool for seamless multimodal experience innovation in connected and autonomous vehicles

The diversity of multimodal interfaces and contextual complexity of designing multimodal interfaces call for novel participatory design approaches to facilitate co-creation between designers and stakeholders. This paper presents the SME design Cards (SMEC), a card-based participatory design tool developed for Seamless Multimodal Experience (SME) design in automobiles. We outline the tool’s background and development process, followed by presenting the evaluation results from both end-users and design experts. We then report on refinements to the SMEC and apply it in a hybrid workshop. We present insights into developing the card and discuss its effect in supporting SME design ideation and evaluation, informing the design of card-based participatory design tools.

Reliable Synchronous and Asynchronous Counter Design in QCA

Due to rapid growth in the integrated circuit (IC) industry, the demand for compact digital system design is high. However, the continued technology reductions made the feasibility of further scaling down transistor size more challenging. In response to the growing demand for ultra-compact IC designs, the revolutionary quantum-dot cellular automata (QCA) technology has emerged as a promising solution. In a digital era, the counters are widely adopted in the peer-to-peer process flow to establish a mechanism for generating unique values for each identifier/number. In this work, a unique synchronous and asynchronous counters architecture is proposed with a reliable D and T flip-flop design. The proposed QCA architecture is implemented and validated with the QCA designer tool. Furthermore, in QCA technology, unreliable QCA designs can lead to frequent errors and malfunctions in the implemented logic. To overcome this challenge, the proposed design prioritizes cell placement (the relative positions of QCA cells) to make the circuit more robust. As a result, the circuit can still produce the expected functionality even if some QCA cells malfunction. Hence, to ensure the reliability of the proposed QCA architecture, the missing cell defect analysis is carried out in comparison with existing state-of-the-art designs. Based on comparison results, the unique designs like the proposed multiplexer, D flip-flop and T flip-flop design exhibit success rates of 67.28, 77.04 and 85.15%, respectively. The experimental results demonstrate that the proposed counter-architecture outperforms existing architectures.

Green Connections: Adaptive, Integrated, and Nature-Based Solutions for Urban Historic Centres

Choosing adaptation and mitigation actions, through nature-based solutions, fosters the ecological transition process, which is necessary to face the challenges of climate change. However, these interventions are often discontinuous and disconnected, especially within dense and delicate urban fabrics such as historic centres. The research proposes a multi-scalar methodological approach aimed at defining an integrated design tool to improve the microclimatic well-being, accessibility and aesthetic quality of open spaces located in consolidated urban environments. Through the synergy between natural, technological and social components, the aim is to create replicable minimum intervention units designed to foster democratic and ecosystemic connections.

Development of Bamboo Based Nylon 66 Composite through Friction Stir Processing-An Attempt

The concept of developing a bamboo-based Nylon 66 polymer matrix composite is a relatively novel and very new technical attempt through friction stir processing (FSP). This innovative approach can create a composite material that strengthen the mechanical properties of bamboo and the versatility of Nylon 66. However, successful implementation requires careful consideration of FSP process parameters such us tool rpm, traverse speed, tilt angle and tool design. Among the processing parameters, the tool rpm shows the significant role for severe plastic deformation and temperature generation which leads to the achieving excellent bond. Therefore, in this present study attempt has made to develop the polymer matrix composite (nylon 66 and bamboo powder) using FSW process at a variant rotational speed of 300,400 and 500 rpm with the constant traverse speed of 25 mm min-1. The deformation behavior and the peak temperature evolved under the tool shoulder during the stirring motion is studied using COMSOL Multiphysics simulation. It is found that, the specimen processed with higher rpm (500rpm) shows the higher volumetric strain and the peak temperature and it is evident that with increasing rpm the higher amount of severe plastic deformation occurred. Initially the process parameters are optimized without bamboo powder on the nylon 66 plate of 6 mm thickness and found that the 500 rpm processed specimen shows the defect free. Prior to the actual FSP, the small keyways taken on the center of the nylon 66 plate in order to add the bamboo powders in it. Actual processing was done with bamboo powder after adding natural bamboo powder of size 50µm. The result reveals that, the bamboo powder has partially expelled out during the period of FSP. This complete study concedes that the processing parameters needs to be optimized and also bamboo added method need to be studied for the successful development of bamboo-based polymer matrix composite.

The Impact of OER’s Continuous Improvement Cycles on Students’ Performance: A Longitudinal Analysis of the RISE Framework

Open educational resources (OER) have been praised for revolutionizing education. However, practitioners and instructors battle keeping OER updated and measuring their impact on students’ performance. Few studies have analyzed the improvement of OER over time in relation to achievement. This longitudinal study uses learning analytics through the open-source Resource Inspection, Selection, and Enhancement (RISE) analysis framework to assess the impact of continuous improvement cycles on students’ outcomes. Panel data (i.e., performance and use) from 190 learning objectives of OER of an introductory sociology course were analyzed using a hierarchical linear model. Results show that more visits to an OER do not improve student achievement, but continuous improvement cycles of targeted OER do. Iterative implementation of the RISE analysis for resource improvement in combination with practitioners’ expertise is key for students’ learning. Given that the RISE classification accounted for 65% of the growth of students’ performance, suggesting a moderate to large effect, we speculate that the RISE analysis could be generalized to other contexts and result in greater student gain. Institutions and practitioners can improve the OER’s impact by introducing learning analytics as a decision-making tool for instructional designers. Yet, user-friendly implementation of learning analytics in a “click-and-go” application is necessary for generalizability and escalation of continuous improvement cycles of OER and tangible improvement of learning outcomes. Finally, in this article, we identify the need for efficient applications of learning analytics that focus more on “learning” and less on analytics.

Exploring Meditron-7b performance on a small-scale purpose made dataset in human nutrition queries

Abstract The interest in Large Languages Models (LLMs) has been rapidly evolving over the last years, boosting concerns about their potential to improve the efficiency and effectiveness of clinical, educational and research work in medicine. In this study, we aimed to test the performance of MEDITRON, a recently released suite of open-source LLMs with 7B parameters adapted to the medical domain, on a small sample of human nutrition queries. To facilitate our assessment, we curated a specialized dataset comprising a diverse range of human nutrition-related queries, which have been manually collected from various medical databases and nutrition exams. The dataset was adapted for the scope of our analysis to encompass variations in language complexity, query types, and semantic nuances commonly encountered in real-world settings. Additionally, to ensure a standardized and clinically relevant context for our evaluations, we engineered a specialized prompt designed to mimic interactions with a highly esteemed physician specializing in nutrition, food science, and diet-related disorders. The prompt guided the generation of nutrition-related queries in a structured format, enabling MEDITRON to provide responses consistent with the latest advancements in medical research. Our preliminary findings revealed promising capabilities of MEDITRON in understanding medical language, providing contextually appropriate responses to several human nutrition related questions. Through this study, we add valuable insights to the ongoing discussion around the deployment of LLMs in public health, highlighting their potential to improve access to essential human nutrition literacy. Key messages • Design of LLMs tools holds the potential to improve healthcare in clinical, research and education applications. • Further evidence is needed to foster their actual integration in real world settings.

Development of Machine Learning Atomistic Potential for Molecular Simulation of Hematite–Water Interfaces

A novel approach for constructing a machine-learned potential energy surface (MLP) from unlabeled training data is presented. Utilizing neural networks augmented with a pool-based active learning sampling method, a potential energy surface (PES) is developed for the accurate modeling of interfaces of hematite iron oxide and water, fitting the much more expensive density functional theory (DFT). Molecular dynamics simulations were performed using this DFT-based PES to characterize the structural and energetic properties of the system. By utilizing the developed machine learning potential (MLP), it was possible to simulate much larger systems for extended periods of time, which will be important for leveraging machine learning potentials as accurate and pragmatic simulation-led molecular design and prototyping tools whilst preserving the ab initio accuracy.

Utilization of, Perceptions on, and Intention to Use AI Chatbots Among Medical Students in China: National Cross-Sectional Study.

Artificial intelligence (AI) chatbots are poised to have a profound impact on medical education. Medical students, as early adopters of technology and future health care providers, play a crucial role in shaping the future of health care. However, little is known about the utilization of, perceptions on, and intention to use AI chatbots among medical students in China. This study aims to explore the utilization of, perceptions on, and intention to use generative AI chatbots among medical students in China, using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. By conducting a national cross-sectional survey, we sought to identify the key determinants that influence medical students' acceptance of AI chatbots, thereby providing a basis for enhancing their integration into medical education. Understanding these factors is crucial for educators, policy makers, and technology developers to design and implement effective AI-driven educational tools that align with the needs and expectations of future health care professionals. A web-based electronic survey questionnaire was developed and distributed via social media to medical students across the country. The UTAUT was used as a theoretical framework to design the questionnaire and analyze the data. The relationship between behavioral intention to use AI chatbots and UTAUT predictors was examined using multivariable regression. A total of 693 participants were from 57 universities covering 21 provinces or municipalities in China. Only a minority (199/693, 28.72%) reported using AI chatbots for studying, with ChatGPT (129/693, 18.61%) being the most commonly used. Most of the participants used AI chatbots for quickly obtaining medical information and knowledge (631/693, 91.05%) and increasing learning efficiency (594/693, 85.71%). Utilization behavior, social influence, facilitating conditions, perceived risk, and personal innovativeness showed significant positive associations with the behavioral intention to use AI chatbots (all P values were <.05). Chinese medical students hold positive perceptions toward and high intentions to use AI chatbots, but there are gaps between intention and actual adoption. This highlights the need for strategies to improve access, training, and support and provide peer usage examples to fully harness the potential benefits of chatbot technology.

Experimental-Modeling Framework for Identifying Defects Responsible for Reliability Issues in 2D FETs.

In this work, a self-consistent method is used to identify and describe defects plaguing 300 mm integrated 2D field-effect transistors. This method requires measurements of the transfer characteristic hysteresis combined with physics-based modeling of charge carrier capture and emission processes using technology computer aided design (TCAD) tools. The interconnection of experiments and simulations allows one to thoroughly characterize charge trapping/detrapping by/from defects, depending on their energy position. Once the trap energy distribution is extracted, it is used as input in transient TCAD simulations to reproduce the experimental hysteretic transfer characteristics. Our method is widely applicable to any 2D channel/gate stack combination. Here, it is demonstrated on FAB-integrated devices with AlOx/HfO2 gate oxide. A Gaussian-approximated defect band in the AlOx interlayer centered at a position of about 0.1 eV below the conduction band minimum of WS2 is obtained. Based on this energy position, it is concluded that aluminum interstitial and oxygen vacancies are the defects giving rise to the observed hysteresis. These defects are detrimental to the stability of the studied devices as they are easily accessible by channel carriers during on-state operation. A prominent hysteresis obtained during measurements is consistent with this conclusion.