Interaction Capabilities Research Articles

Wireless, Wrist‐Worn Ultraconformal Neuromuscular Interfaces for Thumb‐Controlled Immersive Human–Machine Interactions

AbstractThumb actions, outperforming conventional methods such as hand gestures or wrist gestures in terms of dexterity, agility and intuitiveness, have long been sought‐after for achieving immersive interactive experiences in robotic control and AR/VR platforms. However, accurate mapping of such dynamic, subtle thumb actions remains a difficult challenging. Here, a wireless, wrist‐affixed soft ultra‐conformal neuromuscular interface system (UniSyst) is reported to capture high‐fidelity surface electromyography crucial for decoding dynamic subtle thumb actions. The UniSyst, which can be easily fabricated at scale and in mass quantities, features a 16‐channel soft, stretchable sensing array for broad, high‐resolution data capture and a stiff design for plug‐and‐play interface with external rigid wireless acquisition module. This soft‐stiff design ensures consistent electrode‐skin contact under substantial skin deformations, thus avoiding undesired motion artifacts commonly observed with rigid alternatives. Facilitated with a lightweight 1D convolution neural network deep learning classifier, this system shows remarkable recognition accuracy over that of traditional forearm placements, fairly compared through concurrently collected signals from the wrist and the forearm of 12 participants. In practical scenarios, the soft UniSyst exhibits rapid, precise thumb‐controlled interactive capabilities, adeptly managing human–machine communications in both digital platforms and immersive gaming controls.

Lectin-Mediated Labeling of Alkaline Phosphatase for Enzymatic Silver Deposition-Based Electrochemical Detection of Glycoprotein Tumor Markers.

The screening of glycoprotein markers has become an integral part of the in vitro diagnosis of malignant tumors. Herein, an electrochemical method based on alkaline phosphatase (ALP)-mediated enzymatic silver deposition is reported for the highly sensitive detection of glycoprotein tumor markers, in which ALP enzymes are decorated to the glycan moieties of targets via the lectin-carbohydrate interactions. As glycoproteins are conjugated with multiple glycan chains, lectin-mediated labeling can result in the decoration of each target with multiple ALP enzymes. Moreover, the enzymatic hydrolysis of ascorbic acid 2-phosphate into ascorbic acid can result in the deposition of a high density of silver particles, which can then be sensitively assayed via the robust Ag/AgCl solid-state voltammetric process. As a result, the enzymatic silver deposition-based electrochemical method exhibits high sensitivity. Using the aptamer-based electrochemical detection of the breast cancer-associated glycoprotein CA15-3 as a proof of concept, a detection limit of 0.32 mU/mL has been demonstrated. Results show that the synergism of the aptamer-based capture and the glycoform-specific discrimination capability of the lectin-carbohydrate interactions can endow this method with high selectivity, and its practical use in the assay of CA15-3 levels in serum samples has been illustrated. With benefits from the high efficiency, mild reaction conditions, and user-friendly operation, the lectin-mediated labeling of ALP enzymes for enzymatic silver deposition is highly applicable to the electrochemical detection of low-abundance glycoprotein tumor markers.

Integrating Speech Recognition and NLP for Efficient Transcription Solutions

Speech recognition, an essential component of natural language processing (NLP), plays a pivotal role in enhancing communication and human-computer interaction. This paper reviews the advancements, challenges, and applications of speech recognition, natural language understanding (NLU), and chatbot technologies. Current speech recognition systems utilize techniques like Mel Frequency Cepstral Coefficients (MFCC) and Hidden Markov Models (HMM) to address linguistic errors, gender recognition failures, and inaccurate voice recognition. Applications such as voice assistants offer continuous interaction capabilities, enabling users, including those with disabilities, to perform tasks like web searches and document preparation. Additionally, we examine vulnerabilities in voice assistants, particularly in NLU components like Intent Classifiers, which can misinterpret user inputs and pose security risks. The transformative impact of deep neural networks (DNN) on speech recognition since 2010 is also discussed, alongside their application to fields like machine translation and image captioning. Furthermore, this paper highlights the evolution of chatbots, integrating NLU platforms like Google DialogFlow and IBM Watson, to deliver intelligent, adaptive interactions. By addressing challenges in intent recognition and system integration, this review underscores the potential of AI-driven solutions to revolutionize speech-based applications.

Assessing the efficacy of iso-mukaadial acetate and betulinic acid against selected Plasmodium falciparum glycolytic pathway proteins: in silico and in vitro studies

Malaria is the extensive health concern in sub-Saharan Africa, with Plasmodium falciparum being the most lethal strain. The continued emergence of drug-resistant P. falciparum advocates for the development of new antimalarials. Our current study aimed to effectively explore the interaction capabilities of iso-mukaadial acetate (IMA) and betulinic acid (BA) against two essential P. falciparum glycolytic pathway proteins, PfLDH and PfHk. Recombinant PfLDH and PfHk were independently expressed in E. coli BL21 (DE3) cells and subsequently purified using affinity chromatography. Protein–ligand interaction studies probed in silico and in vitro approaches. Parasite inhibition studies confirmed potent antimalarial activity against the P. falciparum NF54 strains, with BA and IMA showing IC50 values of 1.27 µg/ml and 1.03 µg/ml against the asexual stage of P. falciparum, respectively. FTIR experiments confirmed interactions between the compounds and the secondary structure of the proteins. Direct protein–ligand interaction studies analysis using microscale thermophoresis (MST) showed a KD value of 0.1036 ± 0.6001 µM for the PfLDH-BA complex and 0.7473 ± 0.3554 µM KD value for PfLDH-IMA. Meanwhile, PfHk-IMA had 0.39701 ± 0.16298 µM KD value, while the PfHk-BA complex had no interaction detected. Molecular docking and molecular dynamics simulation studies were used to measure and confirm the interactive strength of complexes. Molecular docking reported a binding score of − 1.155 kcal/mol for the PfLDH-BA complex and a binding score of − 3.200 kcal/mol for PfLDH-IMA. The PfHk-BA complex had − 2.871 kcal/mol and PfHk-IMA complex had − 4.225 kcal/mol binding score. In conclusion, BA and IMA compounds had better interactions and remained bound within the binding sites of the glycolytic pathway proteins (PfLDH and PfHk).

Advancing Rice Grain Impurity Segmentation with an Enhanced SegFormer and Multi-Scale Feature Integration.

During the rice harvesting process, severe occlusion and adhesion exist among multiple targets, such as rice, straw, and leaves, making it difficult to accurately distinguish between rice grains and impurities. To address the current challenges, a lightweight semantic segmentation algorithm for impurities based on an improved SegFormer network is proposed. To make full use of the extracted features, the decoder was redesigned. First, the Feature Pyramid Network (FPN) was introduced to optimize the structure, selectively fusing the high-level semantic features and low-level texture features generated by the encoder. Secondly, a Part Large Kernel Attention (Part-LKA) module was designed and introduced after feature fusion to help the model focus on key regions, simplifying the model and accelerating computation. Finally, to compensate for the lack of spatial interaction capabilities, Bottleneck Recursive Gated Convolution (B-gnConv) was introduced to achieve effective segmentation of rice grains and impurities. Compared with the original model, the improved model's pixel accuracy (PA) and F1 score increased by 1.6% and 3.1%, respectively. This provides a valuable algorithmic reference for designing a real-time impurity rate monitoring system for rice combine harvesters.

The Addition of Pumpkin Flour Impacts the Functional and Bioactive Properties of Soft Wheat Composite Flour Blends.

Growing interest in functional food ingredients has led to the exploration of pumpkin flour as a nutritional enhancer in wheat-based products. This study investigated the impact of pumpkin flour incorporation (0-20%) on soft wheat flour blends' technological and bioactive properties. The comprehensive analysis included granulometric distribution, techno-functional properties (WHC, WAC, WAI, WSI, SP, OAC), pasting characteristics (RVA), gel texture (TPA), rheological behaviour (frequency sweeps), colour parameters, and bioactive compounds (TPC, DPPH, ABTS) in both water and ethanol extracts. Pumpkin flour addition systematically modified blend properties, with higher fine particle content (13.26% < 80 μm), enhancing water interaction capabilities (WHC increased from 2.52 to 3.56). Pasting behaviour showed reduced peak viscosity (2444.0 mPa·s to 1859.5 mPa·s) but enhanced gel structure stability, evidenced by increased storage modulus (112.7 Pa to 1151.0 Pa) and reduced frequency dependence. Colour parameters showed progressive darkening (L* 91.00 to 84.28) and increased yellow-orange intensity (b* 10.13 to 27.13). Bioactive properties improved significantly, with TPC increasing up to 0.57 mg/1 g DM and 0.34 GAE mg/1 g DM in water and ethanol extracts, respectively, accompanied by enhanced antioxidant activity. Pumpkin flour incorporation successfully enhanced both functional and bioactive properties of wheat flour blends, with particle size distribution and water interactions serving as fundamental determinants of technological functionality, while contributing to improved nutritional value through increased bioactive compounds.

Carbonless DNA.

Carbonless DNA was designed by replacing all carbon atoms in the standard DNA building blocks with boron and nitrogen, ensuring isoelectronicity. Electronic structure quantum chemistry methods (DFT(ωB97XD)/aug-cc-pVDZ) were employed to study both the individual building blocks and the larger carbon-free DNA fragments. The reliability of the results was validated by comparing selected structures and binding energies using more accurate methods such as MP2, CCSD, and SAPT2+3(CCD)δMP2. Carbonless analogs of DNA components, including cytosine, thymine, guanine, adenine, and deoxyribose, were investigated, showing strong resemblance to the carbon-based versions in terms of spatial structure, polarity, and molecular interaction capabilities. Complementary base pairs of the carbonless analogs exhibited a similar number and length of hydrogen bonds as those found in their carbon-containing counterparts, with binding energies for A-T and G-C analogs remaining comparable. Carbonless DNA fragments containing two and six base pairs were studied, revealing double-helix structures analogous to natural DNA. Structural parameters such as fragment size, hydrogen bond lengths, and rise per base pair were consistent with those observed in unmodified DNA. Docking simulations with a 12 base pair fragment and netropsin as a ligand indicated a slight shift in binding preference for the carbonless DNA through the minor groove, with an approximate 25% increase in binding affinity compared to natural DNA.

From Blood to Therapy: The Revolutionary Application of Platelets in Cancer-Targeted Drug Delivery.

Biomimetic nanodrug delivery systems based on cell membranes have emerged as a promising approach for targeted cancer therapy due to their biocompatibility and low immunogenicity. Among them, platelet-mediated systems are particularly noteworthy for their innate tumor-homing and cancer cell interaction capabilities. These systems utilize nanoparticles shielded and directed by platelet membrane coatings for efficient drug delivery. This review highlights the role of platelets in cancer therapy, summarizes the advancements in platelet-based drug delivery systems, and discusses their integration with other cancer treatments. Additionally, it addresses the limitations and challenges of platelet-mediated drug delivery, offering insights into future developments in this innovative field.

An end-to-end scheduling digital twin for multistage batch plants considering safety

Modern multistage batch plants, characterized by products processed through a series of stages with competing processing units, face challenges in optimizing scheduling and considering inserted events such as breakdowns and maintenance operations simultaneously in current highly dynamic and volatile market. It necessitates robust scheduling tools for efficiency, flexibility, and safety. Previous mathematical programming and meta-heuristic methods, while effective, are time-consuming for large or complex problems. Hybrid models and machine learning approaches have shown promise but often lack robustness against real-world disruptions. In response to these challenges, this work proposes an end-to-end digital twin (DT) solution based on a deep reinforcement learning model for multiproduct multistage batch plants. This model provides a versatile solution for scheduling processes of varying sizes without the need for extensive retraining, seamlessly incorporating dynamic factors. Tests on the model demonstrate its rapid interaction and robust solution capabilities, highlighting its comprehensive advantages in processing speed and result quality.

Evaluation of drivers' interaction ability at social scenarios: a process-based framework

Assessing drivers' interaction capabilities is crucial for understanding human driving behaviour and enhancing the interactive abilities of autonomous vehicles. In scenarios involving strong interaction, existing metrics focussed on interaction outcomes struggle to capture the evolutionary process of drivers' interactive behaviours, making it challenging for autonomous vehicles to dynamically assess and respond to other agents during interactions. To address this issue, we propose a framework for assessing drivers' interaction capabilities, oriented towards the interactive process itself, which includes three components: Interaction Risk Perception, Interaction Process Modeling, and Interaction Ability Scoring. We quantify interaction risks through motion state estimation and risk field theory, followed by introducing a dynamic action assessment benchmark based on a game-theoretical rational agent model, and designing a capability scoring metric based on morphological similarity distance. By calculating real-time differences between a driver's actions and the assessment benchmark, the driver's interaction capabilities are scored dynamically. We validated our framework at unsignalized intersections as a typical scenario. Validation analysis on driver behaviour datasets from China and the USA shows that our framework effectively distinguishes and evaluates conservative and aggressive driving states during interactions, demonstrating good adaptability and effectiveness in various regional settings.

Enhancing Human-Robot Interaction through Voice-Driven Natural Language Processing System

With robotics rapidly advancing, more effective human-robot interaction is increasingly needed to realize the full potential of robots for society. While spoken language must be part of the solution, our ability to provide spoken language interaction capabilities is still limited. Voice communication with robots has the potential to greatly improve human-robot interactions and enable a wide range of new applications. However, there are still many challenges that need to be overcome in order to fully realize this potential, and further research and development is needed in areas such as noise reduction and dialogue management. This paper explores the current state of the technology, including the challenges and limitations that still need to be overcome.

PGMI.Vision: A Mobile Application for Breast Mammographic Image Quality Evaluation with Usability Analysis

The PGMI classification approach is used in Malaysia to assess mammography quality. However, the PGMI criteria lack objectivity and clear definitions, leading to inconsistent evaluations by different readers. This challenge ensures that all mammography facilities fulfil the basic quality criteria. This study aims to develop a mobile application for objective mammography quality assessment and usability evaluation. Figma was utilized as a design tool for this project to create the PGMI mobile application, called PGMI.Vision, due to its interactive design capabilities and collaborative features. The app includes two important mammography views: craniocaudal (CC) and mediolateral oblique (MLO) each breast, resulting in a set of four images. The study involved 27 participants and used the Usefulness, Satisfaction, and Ease of Use (USE) Questionnaire for evaluation. Usability testing showed the average score for Usefulness was 81.67%, Ease-of-Use was 81.82%, Ease of Learning was 80.93%, and Satisfaction was 79.68%. The overall average score was 81.02%, which exceeds typical benchmarks in USE Questionnaire studies, indicating high user satisfaction and usability. These high scores suggest PGMI.Vision is user-friendly and exhibit significant potential for future use.

Wearable technology: Exploring the interrogation of electronics in clothing

As a consequence of the convergence of fashion design, electronics, and information technology, wearable technology has emerged as a significant field of research that crosses over into a number of other fields of study. This is particularly true when discussing different types of clothing. The clothing industry is a good illustration of this phenomenon. A significant contributor to this is the flood of research that has been conducted on wearable technology. Wearable technology is becoming more important in the fashion industry, and its importance cannot be understated. It is anticipated that the results of this study will serve as a source of inspiration for the development of new apps that include novel monitoring, communication, and interaction capabilities for health. These applications are the output of the inquiry that was conducted in this study to determine whether or not it is possible to include electrical components into clothes. Our research will be beneficial to the development of these mobile applications. As a result of ongoing research aimed at enhancing sensor capabilities, increasing data accuracy, and combining contemporary materials that are both flexible and long-lasting, the future of wearable electronics in clothing seems to be bright and full of promise. It is possible that smart textiles will be able to establish a connection with the Internet of Things (IoT), which will open up new avenues for the collection and analysis of data in real time. This will further expand the variety of applications that smart textiles have in everyday life. The development of wearable technology, which makes it possible to investigate the incorporation of electronics into clothing, is a dynamic example of the intersection of fashion and function. As the development of this topic proceeds, it is anticipated that it will continue to challenge traditional beliefs on garment design while simultaneously enhancing the user experience via the incorporation of innovative technological solutions.

PERAN KONTEN POST INSTAGRAM DALAM KEBERLANJUTAN BISNIS

The pandemic hit the education sector, including courses. Many courses shifted to online marketing and online classes. A course that the writer conducted the study, from rarely engaged in online marketing, conducted Instagram Marketing to solved the problem due to the huge potential for growing the brand of the course. Instagram users engage with the content often, using its interactive capabilities to reach the largest possible audience was as potential customers for the course. The writer utilized qualitative method for the study. Indeed it helped the course gained customers and maintained business sustainability. Budding entrepreneurs leveraging profitable online business ideas often begin their product promotion on social platforms. Brands are a little hesitant at the beginning but sooner they also adopt different product promotion strategies to expand brand reach.Therefore, businesses of all kinds — whether a startup or an established brand — should elevate their Instagram marketing strategy for a powerful brand presence to attract and engage with potential customers. Copyright © 2024 by Authors, Published by Jurnal Bisnis Terapan. This work is licensed under a Creative Commons. Attribution-ShareAlike 4.0 International License

Сучасні цифрові технології для реалізації формувального оцінювання на уроках математики

The article is dedicated to the integration of contemporary digital technologies into the process of formative assessment in mathematics lessons, specifically focusing on the use of the Desmos platform. With the advancement of information technologies, new opportunities have emerged to enhance the effectiveness of formative assessment, particularly through providing timely feedback and adapting instruction to meet the individual needs of students. However, in Ukraine formative assessment is still often considered as a formal practice limited to one or several basic stages. The article examines the problems of introducing digital tools into the educational process and analyzes the experience of using Desmos to implement formative assessment. The platform allows teachers to create interactive tasks that help students better understand the material and track their own progress. Desmos also provides visualization of abstract mathematical concepts, which supports a deeper understanding of the material. Special attention is given to the importance of reflection and self-analysis for students, enabling them to recognize their successes and mistakes. The article emphasizes that the use of Desmos promotes active student engagement in the learning process, helps organize individualized instruction, and provides effective feedback. The conclusions highlight that, due to the flexibility and interactive capabilities of this application, teachers can not only organize and manage student learning activities but also ensure their active participation and independent learning. Additionally, the conclusions address the need for further research into the impact of the Desmos platform on students' academic achievements in the long term.

Diffusion of Innovation in Hospitals: Exploring the Benefits and Challenges of Using Instagram

Instagram is a potential platform for disseminating information to the public, mainly health-related information. The Tanah Abang Regional General Hospital (RSUD Tanah Abang) has adopted Instagram as a medium for providing health information and services. This study aims to analyze the utilization of Instagram by RSUD Tanah Abang as an information platform for the public. The research used a qualitative approach with a constructivist paradigm, employing the Diffusion of Innovation theory as an analytical tool. Data was collected through observations of the @rsudtanahabang account and in-depth interviews with the public relations team and its followers. The findings show that RSUD Tanah Abang adopted Instagram due to its relative advantages over conventional media, such as fast information dissemination, two-way interaction capabilities, and ease of developing engaging content. The @rsudtanahabang account successfully increased public engagement in conveying health information. Interactive features like Instagram Feed, Stories, Reels, and Instagram Live strengthen the two-way interaction between the hospital and the public. Content on @rsudtanahabang is dynamically and regularly managed, following social media trends to ensure the information remains relevant and engaging. Instagram has proven to be a compatible tool for disseminating service-related information, such as doctor schedules, strategic health issues, treatment procedures, and health education. However, several challenges were identified and deemed necessary by the hospital, including (1) maintaining the consistency of information shared through Instagram. The hospital must ensure that the content published is always accurate, relevant, and adheres to medical protocols, and (2) managing negative comments responsively and professionally to preserve the hospital’s reputation.

Application of extended reality in pediatric neurosurgery: A comprehensive review.

The integration of Extended Reality (XR) technologies, including Augmented Reality (AR) and Virtual Reality (VR), represents a significant advancement in pediatric neurosurgery. These technologies offer immersive and interactive 3D visualization capabilities, which enhance the precision and accuracy of surgical procedures. This comprehensive review systematically examines the current applications of XR in pediatric neurosurgery. The review adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, which provide criteria for reporting systematic reviews and meta-analyses. It also utilizes the PICOS (Population, Intervention, Comparison, Outcome, Study design) framework to formulate research questions and structure literature searches. A thorough search of multiple databases yielded 1,434 relevant articles, supplemented by an additional 55 articles obtained through manual searches. The review includes a detailed analysis of the XR workflow, its surgical applications, and associated outcomes. It emphasizes the practical benefits of XR in preoperative planning, intraoperative navigation, and postoperative assessment. Furthermore, the paper discusses the challenges, opportunities, and future prospects of XR in pediatric neurosurgery, including its effects on surgical outcomes, medical education, and patient care. By synthesizing technological developments with clinical applications, this review provides a comprehensive understanding of the multifaceted roles of AR and VR in pediatric neurosurgical practice. It covers innovative methods, applicable scenarios, datasets, and metrics, along with a comparative analysis of state-of-the-art techniques, considering differences in input data. Ultimately, this review aims to present an overview of the current landscape of XR in pediatric neurosurgery to inform future research and clinical practice.

One-shot learning HMI for people with disabilities

Abstract For people with physical disabilities, it is often desirable to regain control over their personal environment and communication tools. This paper introduces a novel Human- Machine Interface (HMI) using one-shot learning for individualized control signals without extensive training or specialized hardware. Our work suggests a modular system that utilizes common, easily accessible devices like webcams to interpret user-defined gestures and commands through a single demonstration. As a feasibility study on healthy volunteers, we investigate the control of a computer mouse by head movements only. We demonstrate the technical details of the HMI and discuss its potential applications in enhancing the autonomy and interaction capabilities of users with disabilities. By combining usercentric design principles with the advancements in one-shot learning, we aim to forge a more inclusive, accessible path forward in the development of assistive technologies.

Perceptions and Needs for a Technology-Based Dyadic Intervention on Symptom Management Among Patients With Colorectal Cancer and Their Caregivers: A Qualitative Study.

Colorectal cancer (CRC) patients and their caregivers often experience multiple co-occurring symptoms (eg, fatigue, depression, anxiety, and sleep disturbance). There is a noticeable gap in research regarding symptom management for patient-caregiver dyads, particularly using technology-based tools. This study aimed to describe the needs and perceptions of patient-caregiver dyads regarding a technology-based tool to manage their multiple symptoms. This study utilized a qualitative descriptive design with purposive sampling. Semistructured interviews were conducted with CRC patients undergoing chemotherapy and their caregivers. Thematic analysis was performed to identify key themes. The study included 11 patients and 8 caregivers (8 patient-caregiver dyads and 3 patients without dyads). Four main themes emerged: (1) high symptom burden experienced by CRC patients and their caregivers; (2) symptom self-management strategies, including information seeking and self-education, family and social support, and coping strategies; (3) input and suggestions for technology use, covering aspects such as content, format, and specific technology features; and (4) concerns about barriers to healthcare access, including technological literacy, geographical distance, and time constraints. Our findings provide novel insights into experiences, needs, and suggestions of CRC patient-caregiver dyads for managing multiple symptoms. Participants emphasized the importance of developing a tailored, technology-based tool that includes personalized, evidence-based content; accessible and intuitive design features; and interactive social support capabilities. Leveraging these findings, we aim to develop a technology-based dyadic intervention tool that addresses the psychosocial needs of CRC patient-caregiver dyads. This approach can also enhance health equity by making care more accessible.

Mechanistic Insights into Oxygen-Independent DNA Photodegradation by Pheophorbide a: Implications for Future Photodynamic Therapy Applications.

This study explores the unique properties of Pheophorbide a (Phed a) in the photodegradation of G-quadruplex DNA under anoxic conditions, emphasizing its potential for photodynamic therapy (PDT) in hypoxic tumor environments. We used electron spin resonance (ESR), circular dichroism (CD), and nuclear magnetic resonance (NMR) spectroscopies to assess the radical generation and DNA interaction capabilities of Phed a compared to Pyropheophorbide a (Pyro a) under both oxygenated and anoxic conditions. Our results reveal that Phed a effectively degrades G-quadruplex DNA in the absence of oxygen, whereas Pyro a does not. Under anoxic conditions, Phed a generates unique carbon-centered radicals, as indicated by distinctive ESR signals, which are not observed in aerobic environments or with Pyro a. These radicals facilitate DNA decomposition without relying on reactive oxygen species (ROS). Phed a's ability to degrade DNA independently of oxygen underscores its potential as a versatile and effective PDT agent, especially for hypoxic tumors where traditional photosensitizers are ineffective. This study paves the way for the development of new PDT agents that can operate under different oxygen levels. Phed a's radical generation and oxygen-independent DNA degradation mechanisms make it a promising candidate for future PDT applications.