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The explosive growth of wireless communications and electronic devices has brought electromagnetic radiation's harmfulness and hidden trouble to light, which has a major impact on electrical equipment's ability to function normally. MXene, a material with favorable features like conductivity, a unique two-dimensional multiple-layer structure and abundant surface functional groups, has made it a viable contender for high-performance microwave-absorbers. This article introduces the synthesis strategy of MXene/MXene-based materials and their parent phase MAX, comprehensively summarizes and analyzes the current progress in the study on the microwave-absorbing properties of MXene/MXene-based materials, analyzes the main problems and bottlenecks. Future research directions for MXene microwave-absorbing are discussed in detail.

[Display omitted] • Sea urchin-like structure of CoSe 2 /NCDs/NF was designed and fabricated. • The CoSe 2 /NCDs/NF delivers good catalytic HER performance in different electrolytes (1.0 M KOH, 0.5 M H 2 SO 4), and also displays excellent OER electrocatalytic activity. • Its catalytic activity can be kept almost unchanged for at least 70 h in different solutions. • The exceptional electrochemical performances of CoSe 2 /NCDs/NF are due to its dual regulation of morphology and electronic structure. Designing high-efficient, durable and low-cost bifunctional electrocatalysts is of great significance to realize green hydrogen production by electrolytic water splitting. Herein, 3D sea urchin-like CoSe 2 arrays modified with nitrogen doped carbon dots grown on Ni foam (CoSe 2 /NCDs/NF) was successfully constructed via an easy hydrothermal reaction combined with anion exchange process. The designed CoSe 2 /NCDs/NF catalyst exhibits enhanced catalytic activity and stability for oxygen evolution reaction (OER) and hydrogen evolution reaction (HER) in different electrolyte, with reduced overpotential of 268 mV to afford 70 mA cm−2 for OER and low overpotentials of 94/102 mV in acid/alkaline solution at 10 mA cm−2 for HER, respectively. Impressively, when assembling a two-electrode alkaline electrolyzer with CoSe 2 /NCDs/NF simultaneously acts as the anode and cathode, the cell voltage of only 1.61 V is obtained to drive 30 mA cm−2, with robust stability(for at least 70 h). The excellent catalytic activity is attributed that the 3D sea urchin-like structure significantly augments exposure of active sites and facilitates mass/charge transport; the synergy effect of NCDs and CoSe 2 effectively promotes electron transfer, optimizes electronic environment, and adjusts the adsorption/desorption free energy of the intermediates; and in situ growth of materials and introduction of carbon materials ensures structural stability and enhances the electrical conductivity. This work provides a feasible guidance for the rational design of transition metal selenide catalysts with outstanding performance. [ABSTRACT FROM AUTHOR]

Here we directly converted red phosphorus (RP) into black phosphorus (BP) through a facile and green one-step high-energy ball milling method. The surface oxidation degree of BP could be tuned by changing milling time and rotation speed. The partially oxidized BP was then utilized to improve fire safety of epoxy resin. Specifically, the peak heat release rate (PHRR) and the total heat release (THR) of epoxy composites were reduced by 36 % and 42 % with incorporating only 1.5 wt% BP, respectively. Comparatively, adding the same amount of conventional RP failed to achieve a reduction in smoke production, while the total smoke production (TSP) of epoxy composites with BP decreased by 20 %, suggesting a promising smoke suppression ability of milled BP. The morphology and composition results of char residue demonstrated that the elemental phosphorus and its oxidized products possessed a significant synergistic catalytic effect on promoting char formation in the condensed phase.

A 57-year-old woman with a metastatic bone malignant solitary fibrous tumor received 177Lu-FAP-2286 therapy. After 1 treatment cycle, 68Ga-FAP-2286 PET/CT revealed remission of the lesions. Moreover, the patient did not report any adverse effects.

Understanding the decomposition process of ammonium nitrate (AN) on catalyst surfaces is crucial for the development of practical and efficient catalysts in AN-based propellants. In this study, two types of nano-Fe2O3catalysts were synthesized: spherical particles with high-exposure (104) facets and flaky particles with high-exposure (110) facets. Through thermal analysis and particle size analysis, it was found that the nanosheet-Fe2O3catalyst achieved more complete AN decomposition despite having a larger average particle size compared to nanosphere-Fe2O3. Subsequently, the effects of AN pyrolysis on the (110) and (104) facets were investigated by theoretical simulations. Through studying the interaction between AN and crystal facets, it was determined that the electron transfer efficiency on the (110) facet is stronger compared to that on the (104) facet. Additionally, the free-energy step diagrams for the reaction of the AN molecule on the two facets were calculated with the DFT + U method. Comparative analysis led us to conclude that the (110) facet of α-Fe2O3is more favorable for AN pyrolysis compared to the (104) facet. Our study seeks to deepen the understanding of the mechanism underlying AN pyrolysis and present new ideas for the development of effective catalysts in AN pyrolysis.

The cooling power provided by radiative cooling is unwanted during cold hours. Therefore, self-adaptive regulation is desired for radiative cooling, especially in all-weather applications. However, current routes for radiative cooling regulation are constrained by substrates and complicated processing. Here, self-adaptive radiative cooling regulation on various potential substrates (transparent wood, PET, normal glass, and cement) was achieved by a Fabry–Perot structure consisting of a silver nanowires (AgNWs) bottom layer, PMMA spacer, and W-VO2top layer. The emissivity-modulated transparent wood (EMTW) exhibits an emissivity contrast of 0.44 (ε8–13-L= ∼0.19 and ε8–13-H= ∼0.63), which thereby yields considerable energy savings across different climate zones. The emissivity contrast can be adjusted by varying the spinning parameters during the deposition process. Positive emissivity contrast was also achieved on three other industrially relevant substrates via this facile and widely applicable route. This proves the great significance of the approach to the promotion and wide adoption of radiative cooling regulation concept in the built environment.

Haptic temporal signal recognition plays an important supporting role in robot perception. This paper investigates how to improve classification performance on multiple types of haptic temporal signal datasets using a Transformer model structure. By analyzing the feature representation of haptic temporal signals, a Transformer-based two-tower structural model, called Touchformer, is proposed to extract temporal and spatial features separately and integrate them using a self-attention mechanism for classification. To address the characteristics of small sample datasets, data augmentation is employed to improve the stability of the dataset. Adaptations to the overall architecture of the model and the training and optimization procedures are made to improve the recognition performance and robustness of the model. Experimental comparisons on three publicly available datasets demonstrate that the Touchformer model significantly outperforms the benchmark model, indicating our approach's effectiveness and providing a new solution for robot perception.

Purpose: Cardiovascular disease is one of the leading causes of mortality in patients with obesity. Metabolically healthy obesity (MHO), in which people do not have metabolic disorders, is a transient state of obesity. However, over the long term, a proportion of individuals with MHO develop metabolic syndrome (MetS). We aimed to investigate the effect of substantial weight loss following bariatric surgery in MHO on carotid intima-media thickness (CIMT) and pulse-wave velocity (PWV), which are independent predictors of subclinical atherosclerosis. Methods: This prospective study included 38 patients (34 women, four men) undergoing bariatric surgery who had severe obesity but without comorbidities (hypertension, diabetes, and hyperlipidemia), and 28 control individuals who were matched for age and sex. CIMT and PWV of the left common carotid artery were measured. At 12-month follow-up after bariatric surgery, measurements were repeated in the 38 patients with obesity. Results: Mean baseline body mass index (BMI) in the MHO group was 40.55 ± 3.59 kg/m2, which decreased by 33.1% after bariatric surgery. Compared with controls, CIMT and PWV were increased in MHO (543.53 ± 55.29 vs. 407.82 ± 53.09 μm, 6.70 ± 1.22 vs. 5.45 ± 0.74 m/s, respectively; all P< 0.001). At 12 months post-bariatric surgery, CIMT in MHO was lower than baseline (466.79 ± 53.74 vs. 543.53 ± 55.29 μm, P= 0.009), but PWV was not significantly different from baseline (6.27 ± 0.86 vs. 6.70 ± 1.22 m/s, P= 0.132). Multivariate regression showed that BMI was an independent predictor of CIMT (β = 0.531, P< 0.001). Conclusion: Carotid artery structure and function were impaired in MHO, and improved carotid artery structure was associated with weight loss in MHO after bariatric surgery.

Accurate and interpretable delay predictions are vital for decision-making in the aviation industry. However, effectively incorporating spatiotemporal dependencies and external factors related to delay propagation remains a challenge. To address this challenge, we propose the SpatioTemporal Propagation Network (STPN), a novel space-time separable graph convolutional network that models delay propagation by considering both spatial and temporal factors. STPN uses a multi-graph convolution model that considers both geographic proximity and airline schedules from a spatial perspective, while employing a multi-head self-attention mechanism that can be learned end-to-end and explicitly accounts for various types of temporal dependencies in delay time series from a temporal perspective. Experiments on two real-world delay datasets show that STPN outperforms state-of-the-art methods for multi-step ahead arrival and departure delay prediction in large-scale airport networks. Additionally, the counterfactuals generated by STPN provide evidence of its ability to learn explainable delay propagation patterns. Comprehensive experiments also demonstrate that STPN sets a robust benchmark for general spatiotemporal forecasting. The code for STPN is available at https://github.com/Kaimaoge/STPN.

This work establishes a microscopic fringe projection profilometry (MFPP) system consisting of a bi-telecentric camera and a pinhole Scheimpflug projector to maximize the common focus area between them. Currently, phase-height mapping (PHM) and stereoscopy (SV)-based calibration approaches are still two representative families. The former generally relies on a precise translation stage accompanied by two separate procedures including the camera parameters calibration and the PHM process, making the calibration task relatively complicated and expensive in terms of required operation and devices. The latter only via a calibration target is relatively simple and cheap to implement, but its accuracy fails to be guaranteed because it is difficult to undistort the projector by indirectly resorting to the camera. To cope with these issues, we propose a flexible integrated calibration (IC) solution for the specially designed 3-D system while maintaining a high measurement accuracy and a low requirement of operation and devices. It implements a pixel-wise lookup table (LUT) 3-D coordinate computation only via a low-cost calibration target. The phase artifacts of the dot target are addressed by phase optimization strategy. Furthermore, an optimization strategy is presented to exclude the measurement errors caused by the projector’s distortion and Scheimflug projection structure. The proposed framework effectively simplifies the calibration procedure and reserves the reconstruction accuracy. A theoretical model of the calibration solution is mathematically derived, and rich comparative experiments imply that it can obtain an average height error of $7~\mu \text{m}$ around within the volume of $28\times 23\times5$ mm, as well as a standard deviation (STD) of plane fitting error better than $5~\mu \text{m}$ .

For the practical applications in solar cells and photodetectors, semiconductor colloidal nanocrystals (NCs) are assembled into a high-concentration film with carrier transport characteristics, the full understanding and effective control of which are critical for the achievement of high light-to-electricity conversion efficiencies. Here we have applied transient absorption microscopy to the solid film of giant CdSe/CdS NCs and discovered that at high pump fluences the carrier transport could reach a long distance of ∼2 μm within ∼30 ps after laser pulse excitation. This intriguing behavior is attributed to the metal–insulator transition and the associated bandlike transport, which are promoted by the enhanced electronic coupling among neighboring NCs with extended wave functions overlap of the excited-state charge carriers. Besides providing fundamental transport information in the regime of high laser pump fluences, the above findings shed light on the rational design of high-power light detecting schemes based on colloidal NCs.

With consideration of double-line-frequency instantaneous power in two-stage single-phase system, a double-line-frequency power control method is proposed in this article to achieve optimization and tradeoff control between the current stress of dual-active-bridge (DAB) dc/dc converter and the dc bus voltage ripples in both sides. Different double-line-frequency powers in DAB will lead to different values of DAB current stress and dc bus voltage ripples in both sides. To find out the best double-line-frequency power in DAB, the optimal control trajectory (OCT) is proposed in this article so that the current stress of DAB can be minimized under any certain voltage ripple. An approximate analytical calculation method is derived to solve the optimal double-line-frequency power in OCT. The comparative analysis indicates that the approximate OCT has similar optimization effects as OCT. Based on the OCT, two tradeoff control methods for the DAB current stress and the dc bus voltage ripples are presented so that the current stress and the voltage ripples can be flexibly adjusted to adapt various load conditions. The initial phase of the single-phase ac load is also optimized to maximize the adjustable range of voltage ripple. The experimental results verify the feasibility and effectiveness of the proposed OCT and control methods.

This article provides a comprehensive review of the current state of noninvasive brain imaging and brain stimulation in motor rehabilitation after stroke. The functional organization of the brain is determined by brain network connections. Brain imaging enables us to map the network organization of the brain, so as to assess the motor function in a stroke state. The noninvasive functional imaging techniques include electroencephalography (EEG) and magnetoencephalography (MEG) with the better temporal resolution, and functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) with better spatial resolution. Based on single-mode or multimode imaging methods, the changes of brain networks caused by stroke and during motor recovery progress can be observed. Brain stimulation is an effective way to reorganize brain networks. Transcranial magnetic stimulation (TMS) and transcranial direct current stimulation (tDCS) are the most widely studied noninvasive neuromodulation techniques. Combined with imaging, brain stimulation can alter brain networks in controlled ways and making neuromodulation a closed loop. This review also outlines the methods of facilitate motor rehabilitation: 1) multimode imaging for motor assessment; 2) brain stimulation combined with rehabilitation training; 3) close-loop motor rehabilitation; and 4) influencing factors motor rehabilitation.

ABSTRACTAt present, China’s power grid has entered a new stage of ultra-high voltage, long-distance, large-capacity, large-unit, AC and DC hybrid interconnection grid, and the generator excitation system has an important impact on the stability of the power system. As the core component of the excitation system, the exciter plays a vital role in the safe operation of the excitation system. In view of the above problems, this paper proposes an improved CNN exciter fault diagnosis research method. To be able to learn more abundant fault features, this article first builds a dilated convolutions which is types of deep convolutional neural network (DCNN) to expand the receptive field of the convolution kernel. Then build the Pythagorean Spatial Pyramid Pooling Layer (PTSPP) to further enhance the feature information of the extracted samples. Finally, this article will generate two-dimensional matrix samples from the collected excitation voltage and excitation current signals for model training. The experimental results show that the proposed PTSPP-DCNN method has high classification accuracy in the fault diagnosis of the exciter system. The comparison results show that the fault classification accuracy of the proposed method is higher than other deep learning methods.

At present, biomass foamlike materials are a hot research topic, but they need to be improved urgently due to their defects such as large size shrinkage rate, poor mechanical strength, and easy hydrolysis. In this study, the novel konjac glucomannan (KGM) composite aerogels modified with hydrophilic isocyanate and expandable graphite were prepared by a facile vacuum freeze-drying method. Compared with the unmodified KGM aerogel, the volume shrinkage of the KGM composite aerogel (KPU-EG) decreased from 36.36 ± 2.47% to 8.64 ± 1.46%. Additionally, the compressive strength increased by 450%, and the secondary repeated compressive strength increased by 1476%. After soaking in water for 28 days, mass retention after hydrolysis of the KPU-EG aerogel increased from 51.26 ± 2.33% to more than 85%. The UL-94 vertical combustion test showed that the KPU-EG aerogel can achieve a V-0 rating, and the limiting oxygen index (LOI) value of the modified aerogel can reach up to 67.3 ± 1.5%. To sum up, the cross-linking modification of hydrophilic isocyanate can significantly improve the mechanical properties, flame retardancy, and hydrolysis resistance of KGM aerogels. We believe that this work can provide excellent hydrolytic resistance and mechanical properties and has broad application prospects in practical packaging, heat insulation, sewage treatment, and other aspects.

With the prevalence of Traditional Chinese Medicine (TCM), automation techniques are highly required to support the therapy and save human resources. As the fundamental of the TCM treatment, acupoint detection is attracting research attention in both academic and industrial domains, while current approaches suffer from poor accuracy even with sparse acupoints or require extra equipment. In this study, considering the decision‐making knowledge of human experts, an image‐based deep learning approach is proposed to detect facial acupoints by localising the centre of acupoints. In the proposed approach, high‐resolution networks are selected as the backbone to learn informative facial features with different resolution paths. To fuse the learnt features from the high‐resolution network, a resolution, channel, and spatial attention‐based fusion module is innovatively proposed to imitate human decision, that is, focusing on the facial features to detect required acupoints. Finally, the heatmap is designed to integrally achieve the acupoint classification and position localisation in a single step. A small‐scale real‐world dataset is constructed and annotated to evaluate the proposed approach based on the authorised face dataset. The experimental results demonstrate the proposed approach outperforms other baseline models, achieving a 2.4228% normalised mean error. Most importantly, the effectiveness and efficiency of the proposed technical improvements are also confirmed by extensive experiments. The authors believe that the proposed approach can achieve acupoint detection with considerable high performance, and further support TCM automation. In this work, an image‐based deep learning approach is proposed to detect facial acupoints by localising the centre of acupoints. In the proposed approach, high‐resolution networks are selected as the backbone to learn informative facial features with different resolution paths. To fuse the learnt features from the high‐resolution network, a resolution, channel, and spatial attention‐based fusion module is innovatively proposed to imitate human decision, that is, focussing on the facial features to detect required acupoints.

The present study investigated the microstructure and wear properties of annealed carbon steels with the addition of TiC–TiB2ceramic nanoparticles. It was found that the presence of 0.02 wt% nanoparticles could decrease the amount of widmanstatten structure, promote the formation of finer pearlite from 33.0% to 46.3% and refine the grains from 67.0 μm to 47.5 μm. In ball-on-plate reciprocating sliding wear tests, the wear volume loss was reduced up to 27.2% while the test load of 50 N and sliding velocity of 60 mm/s were utilized. After examining the wear tracks, it was observed that the spalls, grooves, smearing, delamination, oxidative areas and wear debris were found within the worn areas. The ceramic nanoparticles increased the hardness of substrates, inhibited dislocations and plastic deformation, retarded the cracks on surfaces and sub-surfaces, and withstand the load which enhanced the anti-wear performance of annealed carbon steels. This research could provide a new method to improve the wear performance of carbon steel components.

The present research utilized the resistance spot welding process on stainless steel and low carbon steel. The diameters of joint and nugget, microstructure and shearing strength of joints were examined. When increasing the welding current, welding time or clamping force, the diameters of welding joints and nuggets became larger due to the higher heat input and normal load. The shearing strength of joints increased and then decreased with increasing welding current or welding time and decreased with increasing clamping force. For the metallurgical evaluation, it was found that there were five regions around the joint, which consisted of the nugget (austenite and martensite with dendritic structures), coarse heat-affected zone (martensite and pro-eutectoid ferrite), fine heat-affected zone (ferrite and pearlite), base material (ferrite and pearlite) for low carbon steel, and base material (austenite) for stainless steel. In orthogonal tests, it was found that the welding current had the most significant influences on shearing strength, and then welding time and clamping force. Finally, an artificial neural network was established to predict the shearing strength of joints under various welding conditions. The results showed that the shearing strengths predicted by the artificial neural network had good correlation with experimental values. A shearing strength higher than 10000 N could be achieved when welding current was higher than 12.5 kA and welding time was longer than 85 ms. The artificial neural network model has applicable values for predicting the shearing strengths of joints between dissimilar steel plates.

The thermodynamic cycles of the detonation combustion could potentially deliver a performance increase of 20% beyond the conventional deflagration combustor such as gas turbines and ramjets, thus the detonative combustor is a prospective technology for high-efficiency distributed energy or power systems in the future. Therefore, the core process of rotating detonation combustion using hydrogen as a clean fuel was studied in this paper. A rotating combustor integrated with a supersonic inlet, an isolator, and a nozzle was targeted for the overall performance evaluation using a loose coupling method.

In this work, fluorescent solid carbon dots (CDs) welcome a new member, namely anhydride-terminated CDs, which have a photoluminescence quantum yield (PLQY) of 28% for orange-emitted CDs at 580 nm in powder form. For the first time, we revealed that the electronic coupling of the functional groups should be a crucial factor affecting the optical properties of solid CDs. Due to the negligible hydrogen bonding interaction between the anhydride groups, the electronic coupling of excitons between neighboring anhydride groups is weak, leading to a high PLQY of 28% and an immobile emission peak at 580 nm in solid state. Anhydride-terminated CDs can be partly converted into carboxyl-terminated CDs after dispersion in ethanol. However, the strong electronic coupling of carboxyl groups at high concentration generates the stacking mode of J-aggregates, giving rise to a red-shifted emission from 450 to 515 nm as well as quenched fluorescence in solid state. In comparison, a useful blue emission for solid-state CDs occurs from low sp2hybridized carbon atoms, which possess weak electronic coupling and a stationary emission band at 450 nm in both solution and solid state. By adjusting the feed ratio of the reactants, the relevant intensities between the emission from low sp2hybridized carbon atoms at 450 nm and the emission from anhydride groups at 580 nm can be controlled. As a result, single-component anhydride-terminated CD powder with tunable emission color from orange to white light can be achieved. As-prepared anhydride-terminated CDs can be used for fabricating light-emitting diodes (LEDs), white LEDs, and luminescent solar concentrators (LSCs).

Camera calibration is used to determine the intrinsic and extrinsic parameters of a 3D imaging system based on structured light. Traditional methods like chessboard and circular dots usually employ an intensity-based feature point detection procedure, and are susceptible to noise, image contrast, and image blur. To address these issues, we proposed an active calibration method to accurately detect the centers of chromatic concentric fringe patterns (CCFP). Specifically, we first acquired the circular phase using a phase analysis algorithm, then extracted nine phase contours from the circular phase for the corresponding subpixel center coordinates using an ellipse fitting algorithm, and precisely calculated the final center with their weighted sum. We ran a simulation and evaluated the impacts of different degrees of Gaussian blur and noise on the calibrated parameters. The simulation demonstrates that our approach is more robust to noise and blur than previous ones, and our approach yields a higher calibration accuracy. Moreover, we carried out a comparison experiment to evaluate the performance of our method. It showed that the reprojection error can be reduced by at least 10% in the out-of-focus condition (i.e., the target is beyond the working distance of the camera) and the 3D reconstruction accuracy can be improved by nearly 10%.

The explosive process of 5G communication evokes the urgent demand of miniaturized and integrated dielectric ceramics filter. It is a pressing need to advance the development of dielectric ceramics utilization of emerging technology to design new materials and understand the polarization mechanism. This review provides the summary of the study of microwave dielectric ceramics (MWDCs) sintered higher than 1000 from 2010 up to now, °C with the purpose of taking a broad and historical view of these ceramics and illustrating research directions. To date, researchers endeavor to explain the structure-property relationship of ceramics with multitude of approaches and design a new formula or strategy to obtain excellent microwave dielectric properties. There are variety of factors that impact the permittivity, dielectric loss, and temperature stability of dielectric materials, covering intrinsic and extrinsic factors. Many of these factors are often intertwined, which can complicate new dielectric material discovery and the mechanism investigation. Because of the various ceramics systems, pseudo phase diagram was used to classify the dielectric materials based on the composition. In this review, the ceramics were firstly divided into ternary systems, and then brief description of the experimental probes and complementary theoretical methods that have been used to discern the intrinsic polarization mechanisms and the origin of intrinsic loss was mentioned. Finally, some perspectives on the future outlook for high-temperature MWDCs were offered based on the synthesis method, characterization techniques, and significant theory developments.

The effect of surface/interface defects on multiexciton recombination is studied with CdZnSeS/ZnS alloy core/shell quantum dots (QDs) with different shell thicknesses. Through pump-power-related time-resolved photoluminescence/amplified-spontaneous-emission (ASE) spectra and statistical analysis of single-dot fluorescence, it is indicated that with the epitaxial growth of the ZnS shell, the multiexciton property of the QDs can be improved due to surface passivation, but with further shell growth, interface defects caused by stress accumulation will result in deterioration. The QDs with three monolayers ZnS shell show the best performance with a biexciton quantum yield of 11.6%, biexciton lifetime of ∼360 ps, and ASE threshold of only 118 μJ cm–2, with which a vertical cavity surface-emitting laser is fabricated. Our experimental results highlight the importance of surface/interfacial defects to the application of QDs on laser devices.

Pathologists are responsible for rapidly providing a diagnosis on critical health issues. Challenging cases benefit from additional opinions of pathologist colleagues. In addition to on-site colleagues, there is an active worldwide community of pathologists on social media for complementary opinions. Such access to pathologists worldwide has the capacity to improve diagnostic accuracy and generate broader consensus on next steps in patient care. From Twitter we curate 13,626 images from 6,351 tweets from 25 pathologists from 13 countries. We supplement the Twitter data with 113,161 images from 1,074,484 PubMed articles. We develop machine learning and deep learning models to (i) accurately identify histopathology stains, (ii) discriminate between tissues, and (iii) differentiate disease states. Area Under Receiver Operating Characteristic (AUROC) is 0.805–0.996 for these tasks. We repurpose the disease classifier to search for similar disease states given an image and clinical covariates. We report precision@k= 1 = 0.7618 ± 0.0018 (chance 0.397 ± 0.004, mean ±stdev ). The classifiers find that texture and tissue are important clinico-visual features of disease. Deep features trained only on natural images (e.g., cats and dogs) substantially improved search performance, while pathology-specific deep features and cell nuclei features further improved search to a lesser extent. We implement a social media bot (@pathobot on Twitter) to use the trained classifiers to aid pathologists in obtaining real-time feedback on challenging cases. If a social media post containing pathology text and images mentions the bot, the bot generates quantitative predictions of disease state (normal/artifact/infection/injury/nontumor, preneoplastic/benign/low-grade-malignant-potential, or malignant) and lists similar cases across social media and PubMed. Our project has become a globally distributed expert system that facilitates pathological diagnosis and brings expertise to underserved regions or hospitals with less expertise in a particular disease. This is the first pan-tissue pan-disease (i.e., from infection to malignancy) method for prediction and search on social media, and the first pathology study prospectively tested in public on social media. We will share data through http://pathobotology.org. We expect our project to cultivate a more connected world of physicians and improve patient care worldwide.

This study describes the laser surface hardening process effect on microstructures produced and their wear behavior. Ductile iron samples were austempered at three different austempering temperatures: 232 °C/288 °C/398 °C respectively. Then, the laser surface hardening process was applied on each sample. Different laser gaps were designed: 1.5mm/3mm/4 mm. The microstructures were observed using optical microscopy and tribo-tests were run using a UMT-3 tribo tester. A Rockwell hardness tester was used to measure the hardness after heat-treatment. Optical microscopy and SEM were used to observe the different microstructures and their distribution on the worn surface. The results showed that the laser processing generated ledeburite, martensite, or tempered bainite microstructures. Vickers hardness tests were carried out on these microstructures. The original needle-like microstructures were observed on the samples with 4 mm laser gap but not with 1.5 mm or 3 mm laser gap. This is because part of the 4 mm laser gap is beyond the laser heat effected zone. Generally, severe ploughing wear and smearing wear were observed on the tempered bainite zone but not the bainite zone. Debris was generated during the tribo-tests and led to three body abrasive wear which not only resulted in higher wear loss, but also polished the worn surface.

This research presents an experimental study on the tribological behavior and plastic deformation layer response of quenched-tempered AISI 6150 steel and austempered AISI 6150 steel under sliding with a ball-on-disk type apparatus. Worn surfaces were analyzed by micro-hardness, 3D profilometer, microscopy and scanning electron microscope (SEM). The results showed that the disk surfaces were hardened after tribo-tests due to fresh-martensite formation caused by frictional heating/self-quenching during the sliding tests. The wear loss of the disk specimens was due to smearing plastic deformation resulting in material pile-up along the wear track and debris inside the wear track. The quenched-tempered disk specimens generated more debris than the austempered specimens. The greater amount of wear debris in the quench-tempered samples led to more severe contact stresses between the ball and disk samples which accelerated the smearing of material. As the tempering temperature increases, more cracks were observed for all quenched-tempered disk specimens. More voids and cracks was developed in the near surface region of tempered martensite leading to accelerated material loss through smearing and delamination. Also, more plate-like wear particles were observed on the disks of tempered martensite due to greater surface and subsurface crack fomation and propagation.

Pathologists are responsible for rapidly providing a diagnosis on critical health issues. Challenging cases benefit from additional opinions of pathologist colleagues. In addition to on-site colleagues, there is an active worldwide community of pathologists on social media for complementary opinions. Such access to pathologists worldwide has the capacity to improve diagnostic accuracy and generate broader consensus on next steps in patient care. From Twitter we curate 13,626 images from 6,351 tweets from 25 pathologists from 13 countries. We supplement the Twitter data with 113,161 images from 1,074,484 PubMed articles. We develop machine learning and deep learning models to (i) accurately identify histopathology stains, (ii) discriminate between tissues, and (iii) differentiate disease states. Area Under Receiver Operating Characteristic (AUROC) is 0.805–0.996 for these tasks. We repurpose the disease classifier to search for similar disease states given an image and clinical covariates. We report precision@k= 1 = 0.7618 ± 0.0018 (chance 0.397 ± 0.004, mean ±stdev ). The classifiers find that texture and tissue are important clinico-visual features of disease. Deep features trained only on natural images (e.g., cats and dogs) substantially improved search performance, while pathology-specific deep features and cell nuclei features further improved search to a lesser extent. We implement a social media bot (@pathobot on Twitter) to use the trained classifiers to aid pathologists in obtaining real-time feedback on challenging cases. If a social media post containing pathology text and images mentions the bot, the bot generates quantitative predictions of disease state (normal/artifact/infection/injury/nontumor, preneoplastic/benign/low-grade-malignant-potential, or malignant) and lists similar cases across social media and PubMed. Our project has become a globally distributed expert system that facilitates pathological diagnosis and brings expertise to underserved regions or hospitals with less expertise in a particular disease. This is the first pan-tissue pan-disease (i.e., from infection to malignancy) method for prediction and search on social media, and the first pathology study prospectively tested in public on social media. We will share data through http://pathobotology.org. We expect our project to cultivate a more connected world of physicians and improve patient care worldwide.

In this contribution, the evolution of the crystal structure and the consequent effects on the microwave dielectric responses of the Sn4+-substituted Li3Mg2–x/3SnxNb1–2x/3O6(0 ≤ x≤ 1.5) ceramics were investigated as a function of the doping content. Interestingly, a wide range of solid solution (0 ≤ x≤ 1.1) was obtained by the complex substitutions of Sn ions, and a composition-driven phase transition from the orthorhombic to cubic phase accompanied by an order–disorder transformation occurring in the range of 0.1 ≤ x≤ 0.7. During the process of the phase transition, high-resolution transmission electron microscopy images showed the presence of a coherent phase boundary between the orthorhombic and cubic phases, which was formed owing to their similar rock-salt crystal configurations and small mismatches in the subcell–lattice parameters. Besides, the electron diffraction patterns indicated that the specimen with relatively low Sn concentration (x= 0.2) contained reconstructed superlattices. The unique layered structure of the end-member Li3Mg2NbO6constrained the form of the substitution for the dopant ions, where the nonequivalent ions (Sn4+) were expected to enter into the Nb–Mg–Nb clusters in the Nb-rich layers preferentially, which was likely to be the cause of the formation of the reconstructed superlattices. The substitution-induced superlattices were highly related to the low dielectric loss of the specimens, and a small amount of Sn doping (0 ≤ x≤ 0.3 mol) also lowered the internal strain of the samples. As the Sn concentration increased from 0 to 0.3, the quality factors (Q× f) were significantly enhanced from 91,700 to 118,700 GHz with the emergence of the reconstructed superlattices and the lowered internal strain.

To discover novel BChE inhibitors, a hierarchical virtual screening protocol followed by biochemical evaluation was applied. The most potent compound 8012-9656(eqBChE IC50= 0.18 ± 0.03 μM, hBChE IC50= 0.32 ± 0.07 μM) was purchased and synthesized. It inhibited BChE in a noncompetitive manner and could occupy the binding pocket forming diverse interactions with the target. 8012-9656was proven to be safe in vivo and in vitro and showed comparable performance in ameliorating the scopolamine-induced cognition impairment to tacrine. Additionally, treatment with 8012-9656could almost entirely recover the Aβ1–42(icv)-impaired cognitive function to the normal level and showed better behavioral performance than donepezil. The evaluation of the Aβ1–42total amount confirmed its anti-amyloidogenic profile. Moreover, 8012-9656possessed blood–brain barrier (BBB) penetrating ability, a long T1/2, and low intrinsic clearance. Hence, the novel potential BChE inhibitor 8012-9656can be considered as a promising lead compound for further investigation of anti-AD agents.

Tensile deformation behavior of Fe–0.25C–3.5(10)Mn–5Al lightweight steel was studied in a large range of strain rate (0.001–1200 s−1) by using a universal material testing machine, intermediate strain rate tensile testing apparatus and rotation disk bar-bar tensile impact apparatus. Microstructures of the two steels before and after tension were observed by means of Optical Microscope (OM), Scanning Electron Microscope (SEM), X-ray diffraction (XRD) and Transmission Electron Microscope (TEM). The results show that the two lightweight steels have a high strength and plasticity and exhibit excellent combinations of specific strength and ductility at the strain-rate of 0.001 s−1after annealing at 850 °C for 5 min then directly quenching into water. During the tensile deformation process, the austenite in 3.5 Mn steel is transformed to α′-martensite. While in 10 Mn steel, the austenite is transformed to twinning. With an increase in strain rate from 0.001 to 1200 s−1, tensile strength of the two steels increase, whilst the elongation initially decrease, and then increase. At the strain-rate of 450 s−1, the elongation of the two lightweight steels are minimal, and the energy absorption capacity are the lowest. With the deformation progresses, the value of n increases from small to large, the strain hardening effect becomes high. Uniform deformation of 10 Mn lightweight steel was suppressed at high strain-rate. Comparing with 10 Mn lightweight steel, the austenite in 3.5 Mn lightweight steel is obviously unstable and cannot provide progressive phase transition.

Organic anion-hosting cathodes are remarkably attractive platform candidates for lithium-ion-based dual-ion batteries (LDIBs) due to their various advantages such as variety, designable, and adjustable. Here, a new organic anion-hosting mixed-valence metal–organic framework cathode (Co2IICoIII(DFc)2(OH)3·H2O, abbreviated as Co(DFc)x) is first employed in LDIBs. With the redox reactions happening in the couples of Fe2+/Fe3+and Co2+/Co3+, PF6–anions can be incorporated into the cathode and reversibly released into the LiPF6-based electrolyte. Meanwhile, benefiting from its unique structure and insolubility, Co(DFc)x shows a high energy density of 632 Wh kg–1(vs lithium anode), a high operating potential of 3.63 V (vs Li+/Li), a high reversible (discharge) capacity of 170 mAh g–1at 50 mA g–1(the third cycle), an excellent rate performance (up to 2000 mA g–1, 5 min for one cycle), and extraordinary cycling stability (an average capacity of 74.9 mAh g–1for 8000 cycles at 2000 mA g–1).

•In situ nano-TiC/Al composites with different alloying elements are prepared.•Mg addition results in 8–10% decrease in the crystallographic mismatch of TiC/Al.•Mg results in 84.3% and 54.7% increase in the σ0.2and σUCSof TiC/Al composite.•New insight for the effects of alloying elements on composite properties is provided.