human machine interaction

In recent years, soft robotic sensors have rapidly advanced to endow robots with the ability to interact with the external environment. Here, we propose a polymer optical fiber (POF) sensor with sensitive and stable detection performance for strain, bending, twisting, and pressing. Thus, we can map the real-time output light intensity of POF sensors to the spatial morphology of the elastomer. By leveraging the intrinsic correlations of neighboring sensors and machine learning algorithms, we realize the spatially resolved detection of the pressing and multi-dimensional deformation of elastomers...

Physical activity (PA) offers many benefits for human health. However, beginners often feel discouraged when introduced to basic exercise routines. Due to lack of experience and personal guidance, they might abandon efforts or experience musculoskeletal injuries. Additionally, due to phenomena such as pandemics and limited access to supervised exercise spaces, especially for the elderly, the need to develop personalized systems has become apparent. In this work, we develop a monitored physical exercise system that offers real-time guidance and recommendations during exercise, designed to assist users in their home environment...

This paper develops a theoretical model of determinants influencing multimodal fake review generation using the theories of signaling, actor-network, motivation, and human-environment interaction hypothesis. Applying survey data from users of China's three leading E-commerce platforms (Taobao, Jingdong, and Pinduoduo), we adopt structural equation modeling, machine learning technique, and Bayesian complex networks analysis to perform factor identification, path analysis, feature factor importance ranking, regime division, and network centrality analysis of full sample, male sample, and female sample to reach the following conclusions: (1) platforms' multimodal recognition and governance capabilities exert significant negative moderating effects on merchants' information behavior, while it shows no apparent moderating effect on users' information behavior; users' emotional venting, perceived value, reward mechanisms, and subjective norms positively influence multimodal fake review generation through perceptual behavior control; (2) feature factors of multimodal fake review generation can be divided into four regimes, i...

Imitating human neural networks via bio-inspired electronics advances human-machine interfaces (HMI), overcoming von Neumann limitations and enabling efficient, low-energy data processing in the big data era. However, single-contact mode HMIs have inherent limitations in terms of their capabilities and performances, such as constrained adaptability to dynamic environments, and reduced cognitive processing capabilities. Here, a dual-interactive-mode HMI system based on a triboelectric nanogenerator (TENG) and heterojunction synaptic transistor (HJST) is proposed for both contact and non-contact applications...

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan...

Mimicking the function of human skin is highly desired for electronic skins (e-skins) to perceive the tactile stimuli by both their intensity and spatial location. The common strategy using pixelated pressure sensor arrays and display panels greatly increases the device complexity and compromises the portability of e-skins. Herein, we tackled this challenge by developing a user-interactive iontronic skin that simultaneously achieves electrical pressure sensing and on-site, nonpixelated pressure mapping visualization...

It has been presumed that rheumatoid arthritis (RA) joint pain is related to inflammation in the synovium; however, recent studies reveal that pain scores in patients do not correlate with synovial inflammation. We developed a machine-learning approach (graph-based gene expression module identification or GbGMI) to identify an 815-gene expression module associated with pain in synovial biopsy samples from patients with established RA who had limited synovial inflammation at arthroplasty. We then validated this finding in an independent cohort of synovial biopsy samples from patients who had early untreated RA with little inflammation...

Human-Object Interaction (HOI) detection aims to understand human activities by detecting interaction triplets. Previous HOI detection methods adopt a two-stage instance-driven paradigm. Unfortunately, many non-interactive human-object pairs generated by the first stage are the main obstacle impeding HOI detectors from high efficiency and promising performance. To remedy this, we propose a novel top-down interaction-driven paradigm, detecting interactions first and bridging interactive human-object pairs through interactions...

Flexible pressure sensors (FPSs) based on biomass materials have gained considerable attention for their potential in wearable electronics, human-machine interaction, and environmental protection. Herein, flexible silver nanowire-dual-cellulose paper (SNdCP) containing common cellulose fibers, cellulose nanofibers (CNFs), and silver nanowires (AgNWs) for FPSs was assembled by a facile papermaking strategy. Compared with bacterial cellulose (BC) and cellulose nanocrystals (CNCs), CNFs possess better dimensions and reinforcement, which enables the composite paper to exhibit better mechanical properties (tensile stress of 164...

Flexible electronics, applicable to enlarged health, AI big data medications, etc., have been one of the most important technologies of this century. Due to its particular mechanical properties, biocompatibility, and biodegradability, cocoon silk (or SF, silk fibroin) plays a key role in flexible electronics/photonics. The review begins with an examination of the hierarchical meso network structures of SF materials and introduces the concepts of meso reconstruction, meso doping, and meso hybridization based on the correlation between the structure and performance of silk materials...

mRNAs continually change their protein partners throughout their lifetimes, yet our understanding of mRNA-protein complex (mRNP) remodeling is limited by a lack of temporal data. Here, we present time-resolved mRNA interactome data by performing pulse metabolic labeling with photoactivatable ribonucleoside in human cells, UVA crosslinking, poly(A)+ RNA isolation, and mass spectrometry. This longitudinal approach allowed the quantification of over 700 RNA binding proteins (RBPs) across ten time points. Overall, the sequential order of mRNA binding aligns well with known functions, subcellular locations, and molecular interactions...

Mimicking biological skin enabling direct, intelligent interaction between users and devices, multimodal sensing with optical/electrical (OE) output signals is urgently required. Owing to this, this work aims to logically design a stretchable OE biomimetic skin (OE skin), which can sensitively sense complex external stimuli of pressure, strain, temperature, and localization. The OE skin consists of elastic thin polymer-stabilized cholesteric liquid crystal films, an ion-conductive hydrogel layer, and an elastic protective membrane formed with thin polydimethylsiloxane...

Vision-language navigation is a task that requires an agent to follow instructions to navigate in environments. It becomes increasingly crucial in the field of embodied AI, with potential applications in autonomous navigation, search and rescue, and human-robot interaction. In this paper, we propose to address a more practical yet challenging counterpart setting - vision-language navigation in continuous environments (VLN-CE). To develop a robust VLN-CE agent, we propose a new navigation framework, ETPNav, which focuses on two critical skills: 1) the capability to abstract environments and generate long-range navigation plans, and 2) the ability of obstacle-avoiding control in continuous environments...

Rapid advancements in flexible electronics technology propel soft tactile sensing devices toward high-level biointegration, even attaining tactile perception capabilities surpassing human skin. However, the inherent mechanical mismatch resulting from deficient biomimetic mechanical properties of sensing materials poses a challenge to the application of wearable tactile sensing devices in human-machine interaction. Inspired by the innate biphasic structure of human subcutaneous tissue, this study discloses a skin-compliant wearable iontronic triboelectric gel via phase separation induced by competitive hydrogen bonding...

PURPOSE: The composition and properties of resin-based composite materials could affect tooth wear and lead to clinical problems. Therefore, the study objective was to characterize human tooth wear behavior against a bulk-fill restorative (BF) compared to a conventional resin composite (RC) and a CAD/CAM resin nano ceramic (RN). METHODS: Square-shaped specimens of each material were prepared and sub-divided according to the number of testing cycles (n=8): 100,000, 250,000, and 500,000 cycles...

In this study, we demonstrated the effective separation of charge carriers within the IGZO/IZO heterostructure by incorporating IZO. We have chosen IGZO for its high mobility and excellent on-off switching behavior in the front channel of our oxide-oxide heterostructure. Similarly, for an additional oxide layer, we have selected IZO due to its outstanding electrical properties. The optimized optoelectronic characteristics of the IGZO/IZO phototransistors were identified by adjusting the ratio of In:Zn in the IZO layer...

PURPOSE: Gaze tracking and pupillometry are established proxies for cognitive load, giving insights into a user's mental effort. In tele-robotic surgery, knowing a user's cognitive load can inspire novel human-machine interaction designs, fostering contextual surgical assistance systems and personalized training programs. While pupillometry-based methods for estimating cognitive effort have been proposed, their application in surgery is limited by the pupil's sensitivity to brightness changes, which can mask pupil's response to cognitive load...

Even though in silico drug ligand-based methods have been successful in predicting interactions with known target proteins, they struggle with new, unassessed targets. To address this challenge, we propose an approach that integrates structural data from AlphaFold 2 predicted protein structures into machine learning models. Our method extracts 3D structural protein fingerprints and combines them with ligand structural data to train a single machine learning model. This model captures the relationship between ligand properties and the unique structural features of various target proteins, enabling predictions for never before tested molecules and protein targets...

The analysis of cryo-electron tomography images of human and rat mitochondria revealed that the mitochondrial matrix is at least as crowded as the cytosol. To mitigate the crowding effects, metabolite transport in the mitochondria primarily occurs through the intermembrane space, which is significantly less crowded. The scientific literature largely ignores how enzyme systems and metabolite transport are organized in the crowded environment of the mitochondrial matrix. Under crowded conditions, multivalent interactions carried out by disordered protein regions (IDRs), may become extremely important...

Multimodal machine learning models are being developed to analyze pathology images and other modalities, such as gene expression, to gain clinical and biological insights. However, most frameworks for multimodal data fusion do not fully account for the interactions between different modalities. Here, we present an attention-based fusion architecture that integrates a graph representation of pathology images with gene expression data and concomitantly learns from the fused information to predict patient-specific survival...