An automated two-stage approach to kidney and tumor segmentation in CT imaging.

BACKGROUND: The incidence of kidney tumors is progressively increasing each year. The precision of segmentation for kidney tumors is crucial for diagnosis and treatment. OBJECTIVE: To enhance accuracy and reduce manual involvement, propose a deep learning-based method for the automatic segmentation of kidneys and kidney tumors in CT images. METHODS: The proposed method comprises two parts: object detection and segmentation. We first use a model to detect the position of the kidney, then narrow the segmentation range, and finally use an attentional recurrent residual convolutional network for segmentation. RESULTS: Our model achieved a kidney dice score of 0.951 and a tumor dice score of 0.895 on the KiTS19 dataset. Experimental results show that our model significantly improves the accuracy of kidney and kidney tumor segmentation and outperforms other advanced methods. CONCLUSION: The proposed method provides an efficient and automatic solution for accurately segmenting kidneys and renal tumors on CT images. Additionally, this study can assist radiologists in assessing patients' conditions and making informed treatment decisions.

Two-Dimensional Piezoelectric Nanofibrous Webs by Self-Polarized Assembly for High-Performance PM0.3 Filtration.

Particulate matter (PM) pollution has posed a serious threat to public health, especially the global spread of infectious diseases. Most existing air filtration materials are still subjected to a compromise between removal efficiency and air permeability on account of their stacking bulk structures. Here, we proposed a self-polarized assembly technique to create two-dimensional piezoelectric nanofibrous webs (PNWs) directly from polymer solutions. The strategy involves droplets deforming into ultrathin liquid films by inertial flow, liquid films evolving into web-like architectures by instantaneous phase inversion, and enhanced dipole alignment by cluster electrostatics. The assembled continuous webs exhibit integrated structural superiorities of nanoscale diameters (∼20 nm) of the internal fibers and through pores (∼100 nm). Combined with the wind-driven electrostatic property derived from the enhanced piezoelectricity, the PNW filter shows high efficiency (99.48%) and low air resistance (34 Pa) against PM0.3 as well as high transparency (84%), superlight weight (0.7 g m-2), and long-term stable service life. This creation of such versatile nanomaterials may offer insight into the design and upgrading of high-performance filters.

Analysis of Rhesus (Rh) Antigen Distributions in Donors and Multi-transfused Patients for Phenotype-Matched Transfusion.

Knowledge about the frequency of Rh blood group systems in the local population help build a donor pool for multi-transfused patients and provide antigen-negative compatible blood for patients with alloantibodies. ABO and Rh antigens were identified for blood donors and patients before transfusion. The antiglobulin test based on the micro-column gel method was used to perform unexpected antibody screening and identification for patients in pre-transfusion testing. The incidence of the adverse transfusion reactions and the accordance rate of Rh phenotype-matched transfusion were analyzed retrospectively. A total of 246,340 specimens were detected with Rh blood group antigens D, C, E, c, and e. Rh D antigen was the most common phenotype with a frequency of 99.40%, followed by e antigen, C antigen, c antigen, and E antigen. In Rh D positive specimens, DCe was the most common phenotype, while DCE was the least common. At the same time, in Rh D negative specimens, ce was the most common phenotype with CE and CcE unobserved. Rh phenotype-matched transfusion has been conducted in our department since 2012. The accordance rate of Rh phenotype-matched transfusion has been kept above 95% and the resulting incidence of adverse transfusion reactions has been decreasing year by year, from 19.95‰ in 2011 to 2.21‰ in 2021. Blood transfusion with matched Rh phenotypes was able to avoid the generation of unexpected antibodies, reduce the incidence of adverse transfusion reactions, and enhance precise diagnosis and treatment.

High-performance sono-piezoelectric nanocomposites enhanced by interfacial coupling effects for implantable nanogenerators and actuators.

Transcutaneous energy-harvesting technology based on ultrasound-driven piezoelectric nanogenerators is the most promising technology in medical and industrial applications. Based on ultrasonic coupling effects at the interfaces, the interfacial architecture is a critical parameter to attain desirable electromechanical properties of nanocomposites. Herein, we successfully synthesized core-conductive shell-structured BaTiO3@Carbon [BT@Carbon] nanoparticles [NPs] as nanofillers to design implantable poly(vinylidenefluoride-co-chlorotrifluoroethylene)/BT@Carbon [P(VDF-CTFE)/BT@Carbon] piezoelectric nanogenerators (PENGs) and actuators for harvesting ultrasound (US) underneath the skin. For US-driven PENGs, the electrons and holes are generated not only from the interfaces between the BT@Carbon NPs and the matrix, but also from the dipoles vibrating in the smaller lamellae of ferroelectric ß-phase crystals in poled nanocomposites. Remarkably, P(VDF-CTFE)/BT@Carbon piezoelectric nanogenerators could attain an extraordinary output power of 521 µW cm-2 under ultrasound stimulation, which is far greater than that of force-induced PVDF-based nanogenerators and other ultrasound-driven triboelectric generators. Furthermore, the US-PENG actuator system, which is composed of an amplifier and a microcontroller, could efficiently convert ultrasonic energy into electricity or instructions to switch on/off small electronics in the tissues and organs of mice. Finally, the nanocomposite-based US-driven PENGs have a good biocompatibility, with no cytotoxicity or immune response in vivo, indicating their potential for developing wireless power generators and actuators for medical implant devices.

Electron-beam writing of a relaxor ferroelectric polymer for multiplexing information storage and encryption.

To meet the strong demand for high-level encryption security, several efforts have been focused on developing new encryption techniques with high density and data security. Herein we employed a template-free electron beam lithography (EBL) technique to write various nanopatterns on poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) (P(VDF-TrFE-CTFE)) films and applied it to electron-beam/electric multiplexing memory. Furthermore, electron beams can arbitrarily tailor down the domain structure evolutions and dipole directions, as proved by a combination of AFM-IR and PFM. Finally, our devices could function concurrently as an electron-beam write-only-memory (EB-WOM) and FeRAM, where the information could be encoded with the metastable phase evolutions from the ferroelectric phase to the paraelectric phase and variable bi-level ferroelectric signals. Our systematic study provides an inspiring idea for the design of information encryption devices with high-security requirements in flexible electronic fields.

An optical nanofibre-enabled on-chip single-nanoparticle sensor.

Single-nanoparticle detection has received tremendous interest due to its significance in fundamental physics and biological applications. Here, we demonstrate an optical nanofibre-enabled microfluidic sensor for the detection and sizing of nanoparticles. Benefitting from the strong evanescent field outside the nanofibre, a nanoparticle close to the nanofibre can scatter a portion of the field energy to the environment, resulting in a decrease in the transmitted intensity of the nanofibre. On the other hand, the narrow and shallow microfluidic channel provides a femtoliter-scale detection region, making nanoparticles flow through the detection region one by one. By real-time monitoring of the transmitted intensity of the nanofibre, the detection of a single polystyrene (PS) nanoparticle as small as 100 nm in diameter and exosomes in solution is realised. Based on a statistical analysis, the mean scattering signal is related to the size of the nanoparticle. Experimentally, a mixture of nanoparticles of different diameters (200, 500, and 1000 nm) in solution is identified. To demonstrate its potential in biological applications, high-throughput counting of yeasts using a pair of microchannels and dual-wavelength detection of fluorescently labelled nanoparticles are realised. We believe that the developed nanoparticle sensor holds great potential for the multiplexed and rapid sensing of diverse viruses.

Twisted Optical Micro/Nanofibers Enabled Detection of Subtle Temperature Variation.

The detection of subtle temperature variation plays an important role in many applications, including proximity sensing in robotics, temperature measurements in microfluidics, and tumor monitoring in healthcare. Herein, a flexible miniaturized optical temperature sensor is fabricated by embedding twisted micro/nanofibers in a thin layer of polydimethylsiloxane. Enabled by the dramatic change of the coupling ratio under subtle temperature variation, the sensor exhibits an ultrahigh sensitivity (-30 nm/°C) and high resolution (0.0012 °C). As a proof-of-concept demonstration, a robotic arm equipped with our sensor can avoid undesired collisions by detecting the subtle temperature variation caused by the existence of a human. Moreover, benefiting from the miniaturized and engineerable sensing structure, real-time measurement of subtle temperature variation in microfluidic chips is realized. These initial results pave the way toward a category of optical sensing devices ranging from robotic skin to human-machine interfaces and implantable healthcare sensors.

Deep learning-based diagnosis of disease activity in patients with Graves' orbitopathy using orbital SPECT/CT.

PURPOSE: Orbital [99mTc]TcDTPA orbital single-photon emission computed tomography (SPECT)/CT is an important method for assessing inflammatory activity in patients with Graves' orbitopathy (GO). However, interpreting the results requires substantial physician workload. We aim to propose an automated method called GO-Net to detect inflammatory activity in patients with GO. MATERIALS AND METHODS: GO-Net had two stages: (1) a semantic V-Net segmentation network (SV-Net) that extracts extraocular muscles (EOMs) in orbital CT images and (2) a convolutional neural network (CNN) that uses SPECT/CT images and the segmentation results to classify inflammatory activity. A total of 956 eyes from 478 patients with GO (active: 475; inactive: 481) at Xiangya Hospital of Central South University were investigated. For the segmentation task, five-fold cross-validation with 194 eyes was used for training and internal validation. For the classification task, 80% of the eye data were used for training and internal fivefold cross-validation, and the remaining 20% of the eye data were used for testing. The EOM regions of interest (ROIs) were manually drawn by two readers and reviewed by an experienced physician as ground truth for segmentation GO activity was diagnosed according to clinical activity scores (CASs) and the SPECT/CT images. Furthermore, results are interpreted and visualized using gradient-weighted class activation mapping (Grad-CAM). RESULTS: The GO-Net model combining CT, SPECT, and EOM masks achieved a sensitivity of 84.63%, a specificity of 83.87%, and an area under the receiver operating curve (AUC) of 0.89 (p < 0.01) on the test set for distinguishing active and inactive GO. Compared with the CT-only model, the GO-Net model showed superior diagnostic performance. Moreover, Grad-CAM demonstrated that the GO-Net model placed focus on the GO-active regions. For EOM segmentation, our segmentation model achieved a mean intersection over union (IOU) of 0.82. CONCLUSION: The proposed Go-Net model accurately detected GO activity and has great potential in the diagnosis of GO.

Atomically Smooth Gold Microflake-Enabled Fiber-Tip Fabry-Perot Interferometer for Temperature and Pressure Sensing.

Fiber-tip sensors based on the Fabry-Perot interferometer (FPI) are one of the most widely used devices for temperature and pressure measurements in space-confined scenarios. However, the deposited metal films with a polycrystalline structure tend to form microcracks under strain, which can undermine the optical quality factor and thus sensing performance of these fiber-tip sensors. Here, we demonstrate an atomically smooth gold microflake (GMF)-enabled fiber-tip FPI sensor with a Q factor as high as 628. Benefiting from the high reflectivity and flexibility of GMFs and the elasticity of the PDMS spacer, the fiber-tip FPI can maintain stable sensing performance under large deformation. For temperature sensing, the fiber-tip sensor exhibits a linear response to the temperature in the range 28-40 °C with a sensitivity as high as 1.74 nm °C-1. To realize linear and sensitive pressure sensing, we design and fabricate a PDMS clamped-beam structure on the fiber tip using a soft lithography technique, achieving a sensitivity of 11.48 nm kPa-1. Moreover, simultaneous measurement of the temperature and pressure is also demonstrated using the wavelength demodulation method. The simple and cost-effective fabrication of the clamped beam and the transferable GMFs allow for the facile integration of high-quality FP cavities on fiber tips, opening new opportunities for developing optical sensors with miniaturized sizes.

Design and characterization of molecular, crystal and interfacial structures of PVDF-based dielectric nanocomposites for electric energy storage.

PVDF-based polymers with polar covalent bonds are next-generation dielectric materials for electric energy storage applications. Several types of PVDF-based polymers, such as homopolymers, copolymers, terpolymers and tetrapolymers, were synthesized by radical addition reactions, controlled radical polymerizations, chemical modifications or reduction with the monomers of vinylidene fluoride (VDF), tetrafluoroethylene (TFE), trifluoroethylene (TrFE), hexafluoropropylene (HFP) and chlorotrifluoroethylene (CTFE). Owing to rich molecular structures and complicated crystal structures, PVDF-based dielectric polymers can show versatile dielectric polarization properties, including normal ferroelectrics, relaxor ferroelectrics, anti-ferroelectrics and linear dielectrics, which are beneficial for designing polymer films with high capacity and high charge-discharge efficiency for capacitor applications. Furthermore, to satisfy the requirements of practical high-capacity capacitors, the polymer nanocomposite method is another promising strategy to achieve high-capacitance dielectric materials by the addition of high-dielectric ceramic nanoparticles, moderate-dielectric nanoparticles (MgO, and Al2O3), high-insulation nanosheets (BN), etc. It is concluded with the current problems and future perspectives of interfacial engineering, such as core-shell strategies and hierarchical interfaces in polymer-based composite dielectrics for high-energy-density capacitor applications. In addition, an in-depth understanding of the roles of interfaces on the dielectric properties of nanocomposites can be achieved by indirect analysis techniques (theoretical simulation) and direct analysis techniques (scanning probe microscopy). Our systematic discussions on molecular, crystal and interfacial structures provide guidance for designing fluoropolymer-based nanocomposites for high-performance capacitor applications.

Microbial detoxification of 3,5-xylenol via a novel process with sequential methyl oxidation by Rhodococcus sp. CHJ602.

The compound 3,5-xylenol is an essential precursor used in pesticides and industrial intermediate in the disinfectants and preservatives industry. Its widespread application makes it an important source of pollution. Microbial bioremediation is more environmentally friendly than the physicochemical treatment process for removing alkylphenols from a polluted environment. However, the 3,5-xylenol-degrading bacteria is unavailable, and its degradation mechanism remains unclear. Here, a 3,5-xylenol-metabolizing bacterial strain, designated Rhodococcus sp. CHJ602, was isolated using 3,5-xylenol as the sole source of carbon and energy from a wastewater treatment factory. Results showed that strain CHJ602 maintained a high 3,5-xylenol-degrading performance under the conditions of 30.15 °C and pH 7.37. The pathway involved in 3,5-xylenol degradation by strain CHJ602 must be induced by 3,5-xylenol. Based on the identification of intermediate metabolites and enzyme activities, this bacterium could oxidize 3,5-xylenol by a novel metabolic pathway. One methyl oxidation converted 3,5-xylenol to 3-hydroxymethyl-5-methylphenol, 3-hydroxy-5-methyl benzaldehyde, and 3-hydroxy-5-methylbenzoate. After that, another methyl oxidation is converted to 5-hydroxyisophthalicate, which is metabolized by the protocatechuate pathway. It is catalyzed by a series of enzymes in strain CHJ602. In addition, toxicity bioassay result indicates that 3,5-xylenol is toxic to zebrafish and Rhodococcus sp. CHJ602 could eliminate 3,5-xylenol in water to protect zebrafish from its toxicity. The results provide insights into the bioremediation of wastewater contaminated 3,5-xylenol.

Epistemic neural network based evaluation of online teaching status during epidemic period.

During the epidemic, online teaching became the mainstream. Online teaching evaluation aims to systematically test teachers' teaching process according to certain teaching objectives and standards, and evaluate its value, advantages and disadvantages, so as to improve the quality of teaching. It is not only an important part of the teaching process, but also the basis of all effective and successful teaching. In this paper, we propose an online teaching evaluation method based on Epistemic Neural Network (ENN), which is an evolutionary intelligence method. In terms of uncertainty modeling, ENN's design innovation provides the improvement effect of geometric progression in terms of statistical quality and calculation cost. Therefore, it is very suitable for teaching evaluation, which is an evaluation process guided by a variety of uncertain factors. Specifically, this paper considers the content and grade standards of online teaching evaluation from five aspects. (1) Teachers' syllabus, teaching progress, teaching plan, courseware and other teaching documents and teaching materials; (2) Abide by teaching discipline, the implementation of teaching plan and the completion of teaching tasks; (3) Teaching attitude, teaching investment, teaching and educating people, and the comprehensive quality of teachers; (4) Whether the concepts taught in the course are accurate, the expression is clear, whether the key points are prominent and whether the difficulties are clearly explained; (5) The depth, breadth and frontier of teaching content, and the amount of classroom information. According to the above five evaluation indexes which involves the big data analysis, we train ENN to get an evaluation score that can evaluate the teacher's online teaching process. In addition, we also test the average evaluation time to verify the effectiveness.

The role of healthy emotionality in the relationship between fear of COVID-19 and mental health problems: a cross-sectional study.

Understanding pandemic-related psychopathology development is limited due to numerous individual and contextual factors. It is widely accepted that individual differences to endure or cope with distress predict psychopathology development. The present study investigated the influence of individual differences in neuroticism and healthy emotionality concerning the association between fear of COVID-19 and mental health problems. It was hypothesized that healthy emotionality would moderate the mediated link between fear of COVID-19 and mental health problems. A sample of 752 participants (351 males and 401 females) completed an online survey including the Emotional Style Questionnaire, Fear of COVID-19 Scale, the Neuroticism subscale of the Big Five Inventory, and General Health Questionnaire. The results showed that the fear of COVID-19 positively predicted mental health problems (ß = .43, SE = .05, p < .001, Cohen's f 2 = .24). Neuroticism also showed a significant mediation effect on the relationship between fear of COVID-19 and mental health problems. Fear of COVID-19 indirectly predicted psychopathology through neuroticism (ß = - .16, SE = .04, p < .001, t = 4.53, 95% CI [0.11, 0.23]). Moreover, healthy emotionality had a moderating effect on the relationship between fear of COVID-19 and mental health problems, ß = - .21, SE = .03, p < .001, t = 5.91, 95% CI [- 0.26, - 0.14]. The study's findings are expected to contribute to a better understanding of the roles of both individual differences in personality traits and healthy emotionality in psychopathology development during the current pandemic.

Strong mode coupling-enabled hybrid photon-plasmon laser with a microfiber-coupled nanorod.

Laser based on single plasmonic nanoparticle can provide optical frequency radiation far beyond the diffraction limit and is one of the ultimate goals of nanolasers, yet it remains a challenge to be realized because of the inherently high Ohmic loss. Here, we report the direct observation of lasing in microfiber-coupled single plasmonic nanoparticles enabled by strong mode coupling. We show that, by strongly coupling a gold nanorod (GNR) with the whispering gallery cavity of a dye-doped polymer microfiber (with diameter down to 2.0 µm), the substantially enhanced optical coherence of the hybrid photon-plasmon mode and effective gain accumulated from the active microfiber cavity enable single-mode laser emission from the GNR at room temperature with a threshold as low as 2.71 MW/cm2 and a linewidth narrower than 2 nm.

Optimizing Evanescent Efficiency of Chalcogenide Tapered Fiber.

Evanescent wave absorption-based mid-infrared chalcogenide fiber sensors have prominent advantages in multicomponent liquid and gas detection. In this work, a new approach of tapered-fiber geometry optimization was proposed, and the evanescent efficiency was also theoretically calculated to evaluate sensing performance. The influence of fiber geometry (waist radius (Rw), taper length (Lt), waist deformation) on the mode distribution, light transmittance (T), evanescent proportion (TO) and evanescent efficiency (τ) is discussed. Remarkably, the calculated results show that the evanescent efficiency can be over 10% via optimizing the waist radius and taper length. Generally, a better sensing performance based on tapered fiber can be achieved if the proportion of the LP11-like mode becomes higher or Rw becomes smaller. Furthermore, the radius of the waist boundary (RL) was introduced to analyze the waist deformation. Mode proportion is almost unchanged as the RL increases, while τ is halved. In addition, the larger the micro taper is, the easier the taper process is. Herein, a longer waist can be obtained, resulting in larger sensing area which increases sensitivity greatly.

Factors Associated with In-Patient Mortality in the Rapid Assessment of Adult Earthquake Trauma Patients.

OBJECTIVE: To date, there is limited evidence for health care providers regarding the determinants of early assessment of poor outcomes of adult in-patients due to earthquakes. This study aimed to explore factors related to early assessment of adult earthquake trauma patients (AETPs). METHODS: The data on 29,933 AETPs in the West China Earthquake Patients Database (WCEPD) were analyzed retrospectively. Then, 37 simple variables that could be obtained rapidly upon arrival at the hospital were collected. The least absolute shrinkage and selection operator (LASSO) regression analyses were performed. A nomogram was then constructed. RESULTS: Nine independent mortality-related factors that contributed to AETP in-patient mortality were identified. The variables included age (OR:1.035; 95%CI, 1.027-1.044), respiratory rate ([RR]; OR:1.091; 95%CI, 1.050-1.133), pulse rate ([PR]; OR:1.028; 95%CI, 1.020-1.036), diastolic blood pressure ([DBP]; OR:0.96; 95%CI, 0.950-0.970), Glasgow Coma Scale ([GCS]; OR:0.666; 95%CI, 0.643-0.691), crush injury (OR:3.707; 95%CI, 2.166-6.115), coronary heart disease ([CHD]; OR:4.025; 95%CI, 1.869-7.859), malignant tumor (OR:4.915; 95%CI, 2.850-8.098), and chronic kidney disease ([CKD]; OR:5.735; 95%CI, 3.209-10.019). CONCLUSIONS: The nine mortality-related factors for ATEPs, including age, RR, PR, DBP, GCS, crush injury, CHD, malignant tumor, and CKD, could be quickly obtained on hospital arrival and should be the focal point of future earthquake response strategies for AETPs. Based on these factors, a nomogram was constructed to screen for AETPs with a higher risk of in-patient mortality.

Comparison of different versions of the quick sequential organ failure assessment for predicting in-hospital mortality of sepsis patients: A retrospective observational study.

BACKGROUND: The quick sequential organ failure assessment (qSOFA) is recommended to identify sepsis and predict sepsis mortality. However, some studies have recently shown its poor performance in sepsis mortality prediction. To enhance its effectiveness, researchers have developed various revised versions of the qSOFA by adding other parameters, such as the lactate-enhanced qSOFA (LqSOFA), the procalcitonin-enhanced qSOFA (PqSOFA), and the modified qSOFA (MqSOFA). This study aimed to compare the performance of these versions of the qSOFA in predicting sepsis mortality in the emergency department (ED). METHODS: This retrospective study analyzed data obtained from an electronic register system of adult patients with sepsis between January 1 and December 31, 2019. Receiver operating characteristic (ROC) curve analyses were performed to determine the area under the curve (AUC), with sensitivity, specificity, and positive and negative predictive values calculated for the various scores. RESULTS: Among the 936 enrolled cases, there were 835 survivors and 101 deaths. The AUCs of the LqSOFA, MqSOFA, PqSOFA, and qSOFA were 0.740, 0.731, 0.712, and 0.705, respectively. The sensitivity of the LqSOFA, MqSOFA, PqSOFA, and qSOFA were 64.36%, 51.40%, 71.29%, and 39.60%, respectively. The specificity of the four scores were 70.78%, 80.96%, 61.68%, and 91.62%, respectively. The LqSOFA and MqSOFA were superior to the qSOFA in predicting in-hospital mortality. CONCLUSIONS: Among patients with sepsis in the ED, the performance of the PqSOFA was similar to that of the qSOFA and the values of the LqSOFA and MqSOFA in predicting in-hospital mortality were greater compared to qSOFA. As the added parameter of the MqSOFA was more convenient compared to the LqSOFA, the MqSOFA could be used as a candidate for the revised qSOFA to increase the performance of the early prediction of sepsis mortality.

Optical Microfibers for Sensing Proximity and Contact in Human-Machine Interfaces.

The monitoring of proximity-contact events is essential for human-machine interactions, intelligent robots, and healthcare monitoring. We report a dual-modal sensor made with two functionalized optical microfibers (MFs), which is inspired by the somatosensory system of human skin. The integrated sensor with a hierarchical structure gradationally detects finger approaching and touching by measuring the relative humidity (RH) and force-triggered light intensity variations. Specifically, the RH sensory part shows enhanced evanescent absorption, achieving a sensitive RH measurement with a fast response (110 ms), a high resolution (0.11%RH), and a wide working range (10-100%RH). Enabled by the transition from guided modes into radiation modes of the waveguiding MF, the force sensory part exhibits a high sensitivity (6.2%/kPa) and a fast response (up to 1.5 kHz). By using a real-time data processing unit, the proximity-contact sensor (PCS) achieves continuous detection of the full-contact events, including finger approaching, contacting, pressing, releasing, and leaving. As a proof of concept, the electromagnetic-interference-free PCS enables a smart switch system to recognize the proximity and contact of bare/gloved fingers. Moreover, skin humidity detection and respiration monitoring are realized. These initial results pave the way toward a category of optical collaborative devices ranging from human-machine interfaces to multifunctional on-skin healthcare sensors.

Polarization-independent photon up-conversion with a single lithium niobate waveguide.

We propose a polarization-independent up-conversion protocol for single-photon detection at telecom band with a single thin-film periodically poled lithium niobate waveguide. By choosing the proper waveguide parameters, the waveguide dispersion can compensate the crystal birefringence so that quasi-phase-matching conditions for transverse electric and transverse magnetic modes can be simultaneously fulfilled with single poling period. With this scheme, randomly-polarized single photons at 1550 nm can be up-converted with a normalized conversion efficiency of 163.8%/W cm2.

Optical fibre taper-enabled waveguide photoactuators.

Photoactuators have attracted significant interest for soft robot and gripper applications, yet most of them rely on free-space illumination, which requires a line-of-site low-loss optical path. While waveguide photoactuators can overcome this limitation, their actuating performances are fundamentally restricted by the nature of standard optical fibres. Herein, we demonstrated miniature photoactuators by embedding optical fibre taper in a polydimethylsiloxane/Au nanorod-graphene oxide photothermal film. The special geometric features of the taper endow the designed photoactuator with microscale active layer thickness, high energy density and optical coupling efficiency. Hence, our photoactuator show large bending angles (>270°), fast response (1.8 s for 180° bending), and low energy consumption (<0.55 mW/°), significantly exceeding the performance of state-of-the-art waveguide photoactuators. As a proof-of-concept study, one-arm and two-arm photoactuator-based soft grippers are demonstrated for capturing/moving small objects, which is challenging for free-space light-driven photoactuators.