Search

Assessing eutrophication in lakes is of key importance, as this parameter constitutes a major aquatic ecosystem integrity indicator. The trophic state index (TSI), which is widely used to quantify eutrophication, is a universal paradigm in the scientific literature. In this study, a methodological framework is proposed for quantifying and mapping TSI using the Sentinel Multispectral Imager sensor and fieldwork samples. The first step of the methodology involves the implementation of stepwise multiple regression analysis of the available TSI dataset to find some band ratios, such as blue/red, green/red and red/red, which are sensitive to lake TSI. Trained with in situ measured TSI and match-up Sentinel images, we established the XGBoost of machine learning approaches to estimate TSI, with good agreement (R2= 0.87, slope = 0.85) and fewer errors (MAE = 3.15 and RMSE = 4.11). Additionally, we discussed the transferability and applications of XGBoost in three lake classifications: water quality, absorption contribution and reflectance spectra types. We selected XGBoost to map TSI in 2019–2020 with good-quality Sentinel-2 Level-1C images embedded in the ESA to examine the spatiotemporal variations of the lake trophic state. In a large-scale observation, 10 m TSI products from 555 lakes in China facing eutrophication and unbalanced spatial patterns associated with lake basin characteristics, climate and anthropogenic activities were investigated. The methodological framework proposed herein could serve as a useful resource for continuous, long-term and large-scale monitoring of lake aquatic ecosystems, supporting sustainable water resource management.

Multitarget tracking (MTT) for image processing in low signal-to-noise ratio (SNR) is difficult and computationally expensive because the distinction between the target and the background is small. Among the current MTT algorithms, Random Finite Set (RFS) based filters are computationally tractable. However, the probability hypothesis density (PHD) filter, despite its low computational complexity, is not suitable for MTT in low SNR. The generalized labeled multi-Bernoulli (GLMB) filter and its fast implementation are unsuitable for realtime MTT due to their high computational complexity. To achieve realtime MTT in low SNR, a joint PHD filter and Hungarian assignment algorithm is first proposed in this work. The PHD filter is used for preliminary tracking of targets while the Hungarian assignment algorithm is employed to complete the association process. To improve the tracking performance in low SNR, a new track must undergo a trial period and a valid track will be terminated only if it is not detected for several frames. The simulation results show that the proposed MTT algorithm can achieve stable tracking performance in low SNR with small computational complexity. The proposed filter can be applied to MTT in low SNR that require realtime implementation.

Water clarity serves as a sensitive tool for understanding the spatial pattern and historical trend in lakes' trophic status. Despite the wide availability of remotely sensed data, this metric has not been fully explored for long-term environmental monitoring. To this end, we utilized Landsat top-of-atmosphere reflectance products within Google Earth Engine in the period 1984–2018 to retrieve the average Secchi disk depth (SDD) for each lake in each year. Three SDD datasets were used for model calibration and validation from different field campaigns mainly conducted during 2004–2018. The red / blue band ratio algorithm was applied to map SDD for lakes (>0.01 km2) based on the first SDD dataset, where R2=0.79 and relative RMSE (rRMSE) =61.9 %. The other two datasets were used to validate the temporal transferability of the SDD estimation model, which confirmed the stable performance of the model. The spatiotemporal dynamics of SDD were analyzed at the five lake regions and individual lake scales, and the average, changing trend, lake number and area, and spatial distribution of lake SDDs across China were presented. In 2018, we found the number of lakes with SDD m accounted for the largest proportion (80.93 %) of the total lakes, but the total areas of lakes with SDD of and >4 m were the largest, both accounting for about 24.00 % of the total lakes. During 1984–2018, lakes in the Tibetan–Qinghai Plateau region (TQR) had the clearest water with an average value of 3.32±0.38 m, while that in the northeastern region (NLR) exhibited the lowest SDD (mean 0.60±0.09 m). Among the 10 814 lakes with SDD results for more than 10 years, 55.42 % and 3.49 % of lakes experienced significant increasing and decreasing trends, respectively. At the five lake regions, except for the Inner Mongolia–Xinjiang region (MXR), more than half of the total lakes in every other region exhibited significant increasing trends. In the eastern region (ELR), NLR and Yungui Plateau region (YGR), almost more than 50 % of the lakes that displayed increase or decrease in SDD were mainly distributed in the area range of 0.01–1 km2, whereas those in the TQR and MXR were primarily concentrated in large lakes (>10 km2). Spatially, lakes located in the plateau regions generally exhibited higher SDD than those situated in the flat plain regions. The dataset is freely available at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Hydro.tpdc.271571, Tao et al., 2021).

The extreme cycles of flood and drought in the Poyang Lake catchment (China) place immense pressure on the region's water users and ecosystems. This study examines potential impacts of future climate change in the Poyang Lake catchment using the popular regional climate model, COSMO-CLM, and a distributed hydrological model, WATLAC. Near-future projections (2016–2035) indicate that the mean annual precipitation and temperature are expected to increase over the catchment, with the exception of some northern regions. Relative to the baseline period (1986–2005), the monthly mean precipitation is projected to increase in spring, summer and autumn (March-October), and to decrease in winter (November-February), with the most significant changes in September (62%) and January (−39%). Projected increases in monthly mean temperatures range from 0.3 to 1.4 °C, 0.2 to 0.7 °C, and 0.2 to 1.2 °C for Representative Concentration Pathways (RCP) climate scenarios RCP2.6, 4.5 and 8.5, respectively. Winter temperatures are expected to increase significantly regardless of the climate scenarios. WATLAC simulations indicate that future climate changes will lead to increased high flows in summer and reduced low flows in winter, in terms of both frequency and magnitude, suggesting a high likelihood of an increase in frequency and severity of flooding and droughts in the Poyang Lake catchment.

Rice production is increasingly limited by water scarcity. Covering paddy rice soils with films (so-called ground cover rice production system: GCRPS) can significantly reduce water demand as well as overcome temperature limitations at the beginning of the growing season, which results in greater grain yields in relatively cold regions and also in those suffering from seasonal water shortages. However, it has been speculated that both increased soil aeration and temperature under GCRPS result in lower soil organic carbon and nitrogen stocks. Here we report on a regional-scale experiment conducted in Shiyan, a typical rice-producing mountainous area of China. We sampled paired adjacent paddy and GCRPS fields at 49 representative sites. Measured parameters included soil carbon (C) and nitrogen (N) stocks (to 1 m depth), soil physical and chemical properties, δ15N composition of plants and soils, potential C mineralization rates, and soil organic carbon (SOC) fractions at all sampling sites. Root biomass was also quantified at one intensively monitored site. The study showed that: (1) GCRPS increased SOC and N stocks 5–20 years following conversion from traditional paddy systems; (2) there were no differences between GCRPS and paddy systems in soil physical and chemical properties for the various soil depths, with the exception of soil bulk density; (3) GCRPS increased above-ground and root biomass in all soil layers down to a 40 cm depth; (4) δ15N values were lower in soils and plant leaves indicating lower NH3 volatilization losses from GCRPS than in paddy systems; and (5) GCRPS had lower C mineralization potential than that observed in paddy systems over a 200-day incubation period. Our results suggest that GCRPS is an innovative production technique that not only increases rice yields using less irrigation water, but that it also increases SOC and N stocks.

Crohn's disease affects any part of the GI tract, commonly the terminal ileum. To decrease radiation exposure we developed a low-radiation-dose unenhanced CT (modified small Bowel CT, MBCT) to evaluate the small bowel using hyperdense oral contrast. Technique. MBCT was investigated in patients with pathologically proven Crohn's disease presenting with new symptoms from recurrent inflammation or stricture. After ethics board approval, 98 consecutive patients were retrospectively evaluated. Kappa values from two independent reviewers were calculated for presence of obstruction, active inflammation versus chronic stricture, and ancillary findings. Forty-two patients underwent surgery or colonoscopy within 3 months. Results. Kappa was 0.84 for presence of abnormality versus a normal exam and 0.89 for differentiating active inflammation from chronic stricture. Level of agreement for presence of skip areas, abscess formation, and fistula was 0.62, 0.75, and 0.78, respectively. In the subset with “gold standard” follow-up, there was 83% agreement. Conclusions. MBCT is a low-radiation technique with good to very good interobserver agreement for determining presence of obstruction and degree of disease activity in patients with Crohn's disease. Further investigation is required to refine parameters of disease activity compared to CT enterography and small bowel follow through.

Water is essential for ensuring food security in the world, and agriculture is by far the largest consumer of the earth's available freshwater. Food demand and world’s population are expected to increase over the next years. However, climate change will continue to affect water resources and make the problem of food security more complex. Therefore, agriculture must be smarter and agricultural water management must be more efficient and sustainable. This paper presents a low-cost and smart irrigation system based on LoRa technology to better manage irrigation water at field scale. The system essentially consists of a set of nodes distributed on the field for irrigation control and monitoring of soil parameters, a complete weather station for measuring climate data and a remote server for remote decision-making support. The weather station is connected to the internet via a gateway and the measured climatic data are collected and stored regularly on a server, where access to data is provided by a confidential service. The remote server allows the user to select the irrigation mode and method and to store the soil condition variables collected by the wireless sensor network in order to process them for a more optimal management of irrigation. The irrigation system also allows to compute the Penman–Monteith reference evapotranspiration (ET0) on the daily scale, turn on or off the pump remotely, and automatically fill the water tank. Based on our experimental tests, the low investment cost and the high energy autonomy make the proposed irrigation system more suitable for off grid areas with limited water resources.

Nowadays, video recording devices such as CCTV, digital cameras, mobile phones and car video recorders are ubiquitous. It becomes more and more frequent that traffic accident scenarios are captured by such video recording devices in one form or another. The present study focuses on the direct extraction of vehicle speeds from video footages by cross-ratio, a well known invariant under specific conditions in projective geometry. The minimum requirements for an accurate and direct determination of vehicle speed by cross-ratio are 2 image frames of the video footage containing the subject vehicle which by and large moves along a straight path from one frame to the other and the time lapsed between the 2 image frames are known. With the aid of a calibrated Doppler radar, a control study has been carried out to validate the method and determine the baseline uncertainty. The validated method has been applied to a small number of real world cases and the results are promising. Experimental results indicate that it is possible to extend its application in speed determination by a car camera. [ABSTRACT FROM AUTHOR]

GeS2-Ga2S3-AgX (X=Cl, Br, I) chalcohalide glasses were prepared and their microstructures were investigated by Raman scattering method. Third-order optical nonlinearities were also characterized utilizing the Z-scan method at the wavelength of 800nm. The halogens compositional dependences of third-order optical nonlinearities of these glasses were discussed from the structural point of view. Among the different additives of silver halides, AgBr was demonstrated to have largest contribution to a larger n2 and smaller FOM simultaneously in the studied glass system, which indicating that Br-containing chalcohalide glasses would be more suitable for the application in all-optical switching devices. [ABSTRACT FROM AUTHOR]

Precise patterning of polymer-based biomaterials for functional bionanostructures has extensive applications in biomimetics, biosensing, tissue engineering, and regenerative medicine. Here, we provide a critical review of recent progress in the nano-manufacture of biopolymers, including those for both natural and genetic purposes, with an emphasis on processing using electron and ion beams. In this review, we aim to provide in-depth coverage of nanomanufacturing processing technologies as well as the application of these new technologies. This will demonstrate how structural biopolymers, with silk proteins in particular as an example, can be considered as a material platform with a revolutionary impact in the biomedical, photonic and electronic fields. [ABSTRACT FROM AUTHOR]

Abstract Taste, a pivotal sense modality, plays a fundamental role in discerning flavors and evaluating the potential harm of food, thereby contributing to human survival, physical and mental health. Patients with tongue cancer may experience a loss of taste following extensive surgical resection with flap reconstruction. Here, we designed a gustatory interface that enables the non-invasive detection of tongue electrical activities for a comprehensive operative assessment. Moreover, it decodes gustatory information from the reconstructed tongue without taste buds. Our gustatory interface facilitates the recording and analysis of electrical activities on the tongue, yielding an electrical mapping across the entire tongue surface, which delineates the safe margin for surgical management and assesses flap viability for postoperative structure monitoring and prompt intervention. Furthermore, the gustatory interface helps patients discern tastes with an accuracy of 97.8%. Our invention offers a promising approach to clinical assessment and management and holds potential for improving the quality of life for individuals with tongue cancer.

Abstract The olfactory sensory system of Drosophila has several advantages, including low power consumption, high rapidity and high accuracy. Here, we present a biomimetic intelligent olfactory sensing system based on the integration of an 18-channel microelectromechanical system (MEMS) sensor array (16 gas sensors, 1 humidity sensor and 1 temperature sensor), a complementary metal‒oxide‒semiconductor (CMOS) circuit and an olfactory lightweight machine-learning algorithm inspired by Drosophila. This system is an artificial version of the biological olfactory perception system with the capabilities of environmental sensing, multi-signal processing, and odor recognition. The olfactory data are processed and reconstructed by the combination of a shallow neural network and a residual neural network, with the aim to determine the noxious gas information in challenging environments such as high humidity scenarios and partially damaged sensor units. As a result, our electronic olfactory sensing system is capable of achieving comprehensive gas recognition by qualitatively identifying 7 types of gases with an accuracy of 98.5%, reducing the number of parameters and the difficulty of calculation, and quantitatively predicting each gas of 3–5 concentration gradients with an accuracy of 93.2%; thus, these results show superiority of our system in supporting alarm systems in emergency rescue scenarios.

Addressing peripheral nerve defects remains a significant challenge in regenerative neurobiology. Autografts emerged as the gold-standard management, however, are hindered by limited availability and potential neuroma formation. Numerous recent studies report the potential of wireless electronic system for nerve defects repair. Unfortunately, few has met clinical needs for inadequate electrode precision, poor nerve entrapment and insufficient bioactivity of the matrix material. Herein, we present an advanced wireless electrical nerve stimulator, based on water-responsive self-curling silk membrane with excellent bioabsorbable and biocompatible properties. We constructed a unique bilayer structure with an oriented pre-stretched inner layer and a general silk membrane as outer layer. After wetting, the simultaneous contraction of inner layer and expansion of outer layer achieved controllable super-contraction from 2D flat surface to 3D structural reconfiguration. It enables shape-adaptive wrapping to cover around nerves, overcomes the technical obstacle of preparing electrodes on the inner wall of the conduit, and prevents electrode breakage caused by material expansion in water. The use of fork capacitor-like metal interface increases the contact points between the metal and the regenerating nerve, solving the challenge of inefficient and rough electrical stimulation methods in the past. Newly developed electronic stimulator is effective in restoring 10 mm rat sciatic nerve defects comparable to autologous grafts. The underlying mechanism involves that electric stimulation enhances anterograde mitochondrial transport to match energy demands. This newly introduced device thereby demonstrated the potential as a viable and efficacious alternative to autografts for enhancing peripheral nerve repair and functional recovery.

We propose a metamaterial structure based on graphene-dielectric systems. Double tunable coupled terahertz (THz) surface plasmon polaritons (SPPs) are realized in such graphene metamaterials. The coupled SPPs exhibit extraordinary and interesting properties, which are very different from the conventional SPPs reported in recent years. The coupled SPPs split into an optic mode and an acoustic mode. Importantly, the optic SPP strong coupling with light fields can be effectively excited without specific coupling devices in the proposed metamaterial. Moreover, the optic SPP can be conveniently tuned by a gate voltage. More interestingly, the electrically-regulated THz SPPs are tunably achieved. Our theoretical study highlights the applications of graphene metamaterials as tunable THz plasmonic devices and advanced nanophotonic devices. [ABSTRACT FROM AUTHOR]

Weak target detection is a great challenging in radar field. To detect the weak targets with beam migration, a novel tri-dimensional time model (i.e. fast time, slow time, and beam time) and a novel tri-dimensional signal model which based on the time model are set up firstly. Then, according to the presented models, we propose two multi-beam associated (MBA) coherent integration algorithms based on time-shared multi-beam (TSMB) and space-shared multi-beam (SSMB), respectively. The two proposed algorithms could both eliminate beam migration via associating multi-beam and realize coherent integration via discrete Fourier transform. According to different beam scanning modes, the subsequent analyses show that the MBA coherent integration algorithm based on SSMB (MBACIA-SSMB) may have a better detection performance than that based on TSMB (MBACIA-TSMB). Moreover, the capabilities to estimate the target’s radial velocity and tangency velocity are analyzed. Finally, some numerical experiments are given to verify the performances of MBACIA-TSMB and MBACIA-SSMB.

Abstract In implantable electrophysiological recording systems, the headstage typically comprises neural probes that interface with brain tissue and integrated circuit chips for signal processing. While advancements in MEMS and CMOS technology have significantly improved these components, their interconnection still relies on conventional printed circuit boards and sophisticated adapters. This conventional approach adds considerable weight and volume to the package, especially for high channel count systems. To address this issue, we developed a through-polymer via (TPV) method inspired by the through-silicon via (TSV) technique in advanced three-dimensional packaging. This innovation enables the vertical integration of flexible probes, amplifier chips, and PCBs, realizing a flexible, lightweight, and integrated device (FLID). The total weight of the FLIDis only 25% that of its conventional counterparts relying on adapters, which significantly increased the activity levels of animals wearing the FLIDs to nearly match the levels of control animals without implants. Furthermore, by incorporating a platinum-iridium alloy as the top layer material for electrical contact, the FLID realizes exceptional electrical performance, enabling in vivo measurements of both local field potentials and individual neuron action potentials. These findings showcase the potential of FLIDs in scaling up implantable neural recording systems and mark a significant advancement in the field of neurotechnology.

Wireless neural signal transmission is essential for both neuroscience research and neural disorder therapies. However, conventional wireless systems are often constrained by low sampling rates, limited channel counts, and their support of only a single transmission mode. Here, we developed a wireless bi-directional brain–computer interface system featuring dual transmission modes. This system supports both low-power Bluetooth transmission and high-sampling-rate Wi-Fi transmission, providing flexibility for various application scenarios. The Bluetooth mode, with a maximum sampling rate of 14.4 kS/s, is well suited for detecting low-frequency signals, as demonstrated by both in vitro recordings of signals from 10 to 50 Hz and in vivo recordings of 16-channel local field potentials in mice. More importantly, the Wi-Fi mode, offering a maximum sampling rate of 56.8 kS/s, is optimized for recording high-frequency signals. This capability was validated through in vitro recordings of signals from 500 to 2000 Hz and in vivo recordings of single-neuron spike firings with amplitudes reaching hundreds of microvolts and high signal-to-noise ratios. Additionally, the system incorporates a wireless stimulation function capable of delivering current pulses up to 2.55 mA, with adjustable pulse width and polarity. Overall, this dual-mode system provides an efficient and flexible solution for both neural recording and stimulation applications.

Abstract Advancements in microscale electrode technology have revolutionized the field of neuroscience and clinical applications by offering high temporal and spatial resolution of recording and stimulation. Flexible neural probes, with their mechanical compliance to brain tissue, have been shown to be superior to rigid devices in terms of stability and longevity in chronic recordings. Shuttle devices are commonly used to assist flexible probe implantation; however, the protective membrane of the brain still makes penetration difficult. Hidden damage to brain vessels during implantation is a significant risk. Inspired by the anatomy of the mosquito mouthparts, we present a biomimetic neuroprobe system that integrates high-sensitivity sensors with a high-fidelity multichannel flexible electrode array. This customizable system achieves distributed and minimally invasive implantation across brain regions. Most importantly, the system’s nonvisual monitoring capability provides an early warning detection for intracranial soft tissues, such as vessels, reducing the potential for injury during implantation. The neural probe system demonstrates exceptional sensitivity and adaptability to environmental stimuli, as well as outstanding performance in postoperative and chronic recordings. These findings suggest that our biomimetic neural-probe device offers promising potential for future applications in neuroscience and brain-machine interfaces. A mosquito mouthpart-like bionic neural probe consisting of a highly sensitive tactile sensor module, a flexible microelectrode array, and implanted modules that mimic the structure of mosquito mouthparts. The system enables distributed implantation of electrode arrays across multiple brain regions while making the implantation minimally invasive and avoiding additional dural removal. The tactile sensor array can monitor the implantation process to achieve early warning of vascular damage. The excellent postoperative short-term recording performance and long-term neural activity tracking ability demonstrate that the system is a promising tool in the field of brain-computer interfaces.

Recent advancements in neural probe technology have become pivotal in both neuroscience research and the clinical management of neurological disorders. State-of-the-art developments have led to the advent of multichannel, high-density bidirectional neural interfaces that are adept at both recording and modulating neuronal activity within the central nervous system. Despite this progress, extant bidirectional probes designed for simultaneous recording and stimulation are beset with limitations, including elicitation of inflammatory responses and insufficient charge injection capacity. In this paper, we delineate the design and application of an innovative ultraflexible bidirectional neural probe engineered from polyimide. This probe is distinguished by its ability to facilitate high-resolution recordings and precise stimulation control in deep brain regions. Electrodes enhanced with a PEDOT:PSS/IrOx composite exhibit a substantial increase in charge storage capacity, escalating from 0.14 ± 0.01 mC/cm2 to an impressive 24.75 ± 0.18 mC/cm2. This augmentation significantly bolsters the electrodes’ charge transfer efficacy. In tandem, we observed a notable reduction in electrode impedance, from 3.47 ± 1.77 MΩ to a mere 41.88 ± 4.04 kΩ, while the phase angle exhibited a positive shift from −72.61 ± 1.84° to −34.17 ± 0.42°. To substantiate the electrodes’ functional prowess, we conducted in vivo experiments, where the probes were surgically implanted into the bilateral motor cortex of mice. These experiments involved the synchronous recording and meticulous analysis of neural signal fluctuations during stimulation and an assessment of the probes’ proficiency in modulating directional turning behaviors in the subjects. The empirical evidence corroborates that targeted stimulation within the bilateral motor cortex of mice can modulate the intensity of neural signals in the stimulated locale, enabling the directional control of the mice’s turning behavior to the contralateral side of the stimulation site.

Abstract The combination of optogenetics and electrophysiological recording enables high-precision bidirectional interactions between neural interfaces and neural circuits, which provides a promising approach for the study of progressive neurophysiological phenomena. Opto-electrophysiological neural probes with sufficient flexibility and biocompatibility are desirable to match the low mechanical stiffness of brain tissue for chronic reliable performance. However, lack of rigidity poses challenges for the accurate implantation of flexible neural probes with less invasiveness. Herein, we report a hybrid probe (Silk-Optrode) consisting of a silk protein optical fiber and multiple flexible microelectrode arrays. The Silk-Optrode can be accurately inserted into the brain and perform synchronized optogenetic stimulation and multichannel recording in freely behaving animals. Silk plays an important role due to its high transparency, excellent biocompatibility, and mechanical controllability. Through the hydration of the silk optical fiber, the Silk-Optrode probe enables itself to actively adapt to the environment after implantation and reduce its own mechanical stiffness to implant into the brain with high fidelity while maintaining mechanical compliance with the surrounding tissue. The probes with 128 recording channels can detect high-yield well-isolated single units while performing intracranial light stimulation with low optical losses, surpassing previous work of a similar type. Two months of post-surgery results suggested that as-reported Silk-Optrode probes exhibit better implant-neural interfaces with less immunoreactive glial responses and tissue lesions. A silk optical fiber-based Silk-Optrode probe consisting of a natural silk optical fiber and a flexible micro/nano electrode array is reported. The multifunctional soft probe can modify its own Young’s modulus through hydration to achieve accurate implantation into the brain. The low optical loss and single-unit recording abilities allow simultaneous optogenetic stimulation and multichannel readout, which expands the applications in the operation and parsing of neural circuits in behavioral animals.

For the object recognition in lightless environments, the authors propose the olfactory-tactile machine learning approach, inspired by the star-nose mole’s neural system. They show how bionic flexible sensor arrays allow for real-time acquisition of object’s form and odor when touching it.

Electron beam lithography (EBL) is renowned to provide fabrication resolution in the deep nanometer scale but their incapability of arbitrary 3D nanofabrication poses a major limitation to the technique. Here, the authors demonstrate a manufacturing technique of functional 3d nanostructures at a resolution of sub-15 nm using voltage-regulated 3d EBL.

It is incontrovertible that the bioelectronic enabled bio‐integrated system is one of the most promising technologies in the upcoming decades. Driven by the great versatility of the emerging artificial intelligence, machine‐learning‐supported bio‐integrated intelligent sensing system (BISS) is capable of achieving data processing and intelligent recognition while conducting multimodal human‐centered sensing; such facilitated systems capitalize the benefits of both bioelectronics and supporting algorithm, enabling accurate physiological/somatosensory recognition at the cost of certain computing resources. Herein, an overview of recent progress in BISS is presented, with an emphasis on high‐tech applications enabled by innovations in combining flexible bioelectronic sensors with supporting algorithmic systems. The main applications can be divided into three categories, including implantable, skin‐mounted, and wearable BISS, which have different requirements for materials, fabrication methods, and algorithms, respectively. Advances in these areas open new avenues for employing BISS as future human–machine interfaces for personalized healthcare, human enhancement, as well as other broad applications.

Abstract Background In this study, we investigate the impact of increased PET acquisition time per bed position on lesion detectability, standard uptake value, and image noise in 68Ga-PSMA-11 PET/MRI scans. Methods Scans of twenty patients were analyzed in this study. Patients were injected with 68Ga-PSMA-11 (mean, 5.50 ± 1.49 mCi) and imaged on a 3.0 T time-of-flight PET/MRI. PET images were retrospectively reconstructed using 0.5, 1, 2, 4, 7, and 10 min of PET data. Lesion detectability was evaluated on a 5-point Likert Scale for each lesion in each reconstruction. Quantitative analysis was performed measuring image noise and lesion uptake. Results A total of 55 lesions were identified, and lesion detectability increased from 2.07 ± 1.14 for 0.5 min to 4.93 ± 0.26 for 10 min (p

Abstract Progress toward intelligent human–robotic interactions requires monitoring sensors that are mechanically flexible, facile to implement, and able to harness recognition capability under harsh environments. Conventional sensing methods have been divided for human‐side collection or robot‐side feedback and are not designed with these criteria in mind. However, the iontronic polymer is an example of a general method that operates properly on both human skin (commonly known as skin electronics or iontronics) and the machine/robotic surface. Here, a unique iontronic composite (silk protein/glycerol/Ca(II) ion) and supportive molecular mechanism are developed to simultaneously achieve high conductivity (around 6 kΩ at 50 kHz), self‐healing (within minutes), strong stretchability (around 1000%), high strain sensitivity and transparency, and universal adhesiveness across a broad working temperature range (−40–120 °C). Those merits facilitate the development of iontronic sensing and the implementation of damage‐resilient robotic manipulation. Combined with a machine learning algorithm and specified data collection methods, the system is able to classify 1024 types of human and robot hand gestures under challenging scenarios and to offer excellent object recognition with an accuracy of 99.7%.

Abstract Background Several methods are available for the treatment of early-stage osteonecrosis of the femoral head. Core decompression with implantation is a widely-used treatment. However, no single implant is recognized as the most effective way to prevent disease progression. Silk has high strength and resiliency. This study explored the possibility of a strong and resilient silk protein biomaterial as a new alternative implant. Methods We investigated the biomechanical properties of the silk protein material by regular compression, torsion, and three-point bending tests. We established three-dimensional finite element models of different degrees of femoral head osteonecrosis following simple core decompression, fibula implantation, porous tantalum rod implantation, and silk protein rod implantation. Finally, we compared the differences in displacement and surface stress under load at the femoral head weight-bearing areas between these models. Results The elastic modulus and shear modulus of the silk protein material was 0.49GPa and 0.66GPa, respectively. Three-dimensional finite element analyses demonstrated less displacement and surface stress at the femoral head weight-bearing areas following silk protein rod implantation compared to simple core decompression (p 0.05). Conclusions When compared with simple core decompression, silk protein rod implantation demonstrated less displacement and surface stress at the femoral head weight-bearing area, but more than fibula or tantalum rod implantation. Similar effects on the surface stress of the femoral head between the silk rod, fibula and tantalum rod implantations, combined with additional modifiable properties support the use of silk protein as a suitable biomaterial in osteonecrosis surgery.