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Abstract Dynamic tracking of spinal instrumentation could facilitate real-time evaluation of hardware integrity and in so doing alert patients/clinicians of potential failure(s). Critically, no method yet exists to continually monitor the integrity of spinal hardware and by proxy the process of spinal arthrodesis; as such hardware failures are often not appreciated until clinical symptoms manifest. Accordingly, herein, we report on the development and engineering of a bio-adhesive metal detector array (BioMDA), a potential wearable solution for real-time, non-invasive positional analyses of osseous implants within the spine. The electromagnetic coupling mechanism and intimate interfacial adhesion enable the precise sensing of the metallic implants position without the use of radiation. The customized decoupling models developed facilitate the precise determination of the horizontal and vertical positions of the implants with incredible levels of accuracy (e.g.,

Objectives: Femtosecond laser technology has become the primary method for micropore processing due to its high precision and low energy consumption. However, during the process, it is easy to cause microcracks and burrs in the micropores. Additionally, due to the small size, low structural stability and weak wear resistance of the micropores, conventional methods are ineffective in polishing them. To address the challenge of polishing femtosecond laser-processed micropores, the abrasive water jet polishing method is employed. This method leverages the stable removal function and strong adaptability of the abrasive water jet to improve the quality of femtosecond laser-processed micropores. Methods: Computational fluid dynamics (CFD) simulations of the abrasive water jet micropore polishing process under different process parameters were carried out by using Fluent software. A finite element model of abrasive water jet polishing for femtosecond laser-processed micropores was established under various working conditions. The flow field distribution, the erosion rate and the wall shear force under different parameters were analyzed. Corresponding experiments were conducted for each variable discussed in the Fluent simulation, and the variation patterns of micropore inner wall roughness were summarized. Subsequently, optimization experiments were conducted on the three factors, namely jet target distance, jet pressure and abrasive particle size, using the response surface method. The mean square error of shear force on the inner wall of the hole was taken as the response value Y, and the response surface equation was established. The optimal polishing parameter combination was obtained through the response surface equation and experimentally verified. Results: A jet impact angle of 90° is suitable for polishing the inner wall of the micropore, as wall erosion is uniform and the shear force distribution is concentrated at this angle. At a target distance of 4.2 to 6.0 mm, the jet on the end face enters the deceleration stage, and the jet velocity decreases as the target distance increases. The shear force increases with increasing jet pressure. When the jet pressure is 0.80 MPa, the shear force is the smallest, concentrated in the range of 1 500 to 3 500 Pa. At a jet pressure of 1.50 MPa, the shear force is the largest, concentrated in the range of 3 500 to 5 500 Pa. When jet pressure increases from 0.80 to 1.50 MPa, the shear force on the inner wall of the hole increases more than twice. The effects of abrasive particle size and jet pressure on wall shear force are similar. When the abrasive particle size is 1.0 μm, the shear force is the smallest, concentrated in the range of 1 000 to 2 500 Pa. At an abrasive particle size of 30.0 μm, the shear force reaches its maximum, concentrated between 3 000 and 5 500 Pa. Corresponding tests are carried out for each variable discussed in the simulation, and the minimum roughness Ra of the inner wall of the micropore was 0.386 μm. The optimal process parameter combination obtained through response surface analysis is as follows: jet impact angle of 90°, jet target distance of 3.5 mm, jet pressure of 1.10 MPa, and abrasive particle size of 15.0 μm. Under the optimal parameter combination, with an abrasive mass fraction of 5% and a polishing time of 5.0 minutes, the surface roughness Ra of the polished micropore inner wall surface was reduced to 0.354 µm, which is better than the minimum roughness of 0.386 µm observed in the simulation. Polishing efficiency is improved by about 3%, and the quality of the micropore inner wall surface is further enhanced. Conclusions: When the impact angle is constant, the shear force on the inner wall of the hole increases with increasing jet pressure and abrasive particle size. It increases first and then decreases with the increase in jet target distance, with jet pressure having the greatest influence on the wall shear force. Different structural segments of the jet can be applied to different working conditions due to different properties. Additionally, the simulation and experimental results are in good agreement, and the improvement in roughness is significant. This indicates that abrasive water jet polishing significantly enhances the quality of micropore walls, and the data model for response surface prediction has high accuracy.

Abstract The main cause of corneal blindness worldwide is keratitis, especially the infectious form caused by bacteria, fungi, viruses, and Acanthamoeba. The key to effective management of infectious keratitis hinges on prompt and precise diagnosis. Nevertheless, the current gold standard, such as cultures of corneal scrapings, remains time-consuming and frequently yields false-negative results. Here, using 23,055 slit-lamp images collected from 12 clinical centers nationwide, this study constructed a clinically feasible deep learning system, DeepIK, that could emulate the diagnostic process of a human expert to identify and differentiate bacterial, fungal, viral, amebic, and noninfectious keratitis. DeepIK exhibited remarkable performance in internal, external, and prospective datasets (all areas under the receiver operating characteristic curves > 0.96) and outperformed three other state-of-the-art algorithms (DenseNet121, InceptionResNetV2, and Swin-Transformer). Our study indicates that DeepIK possesses the capability to assist ophthalmologists in accurately and swiftly identifying various infectious keratitis types from slit-lamp images, thereby facilitating timely and targeted treatment.

Machining processes have been widely employed in the modern manufacturing industry to transform raw materials into final products, and they are of great importance in improving the environmental impact and production efficiency of this industry. The selection of appropriate machining process parameters can effectively improve the environmental impact and production efficiency of a process. However, most existing studies on the optimization of these parameters have targeted optimization techniques or modeling methods, and have seldom taken into consideration the adaptability of the machining process. Thus, they suffer from poor generalization and flexibility in actual deployment. Based on this, a generic optimization framework based on the end-to-end evolutionary algorithm was proposed in this study, which can be adapted to various machining optimization problems, to guide the operators in selecting the best parameters in an automated way. Firstly, a modeling framework was introduced to guide the operators to develop optimization objectives. Subsequently, a flexible optimization algorithm was employed to generate Pareto front solutions. Finally, the CRITIC-TOPSIS method was employed to provide a final solution from the different Pareto solutions generated. Experiments were conducted on a milling machine to demonstrate the effectiveness and advantages of the proposed method. The results showed that the proposed method is flexible and applicable for the optimization of the different machining steps and objectives.

ABSTRACTWearable sweat sensors are gaining significant attention due to their unparalleled potential for noninvasive health monitoring. Sweat, as a kind of body fluid, contains informative physiological indicators that are related to personalized health status. Advances in wearable sweat sampling and routing technologies, flexible, and stretchable materials, and wireless digital technologies have led to the development of integrated sweat sensors that are comfortable, flexible, light, and intelligent. Herein, we report a flexible and integrated wearable device via incorporating a microfluidic system and a sensing chip with skin-integrated electronic format toward in-situ monitoring of uric acid (UA) in sweat that associates with gout, cardiovascular, and renal diseases. The microfluidic system validly realizes the real-time capture perspiration from human skin. The obtained detection range is 5–200 μM and the detection limit is 1.79 μM, which offers an importance diagnostic method for clinical relevant lab test. The soft and flexible features of the constructed device allows it to be mounted onto nearly anywhere on the body. We tested the sweat UA in diverse subjects and various body locations during exercise, and similar trends were also observed by using a commercial UA assay kit.

Soft actuators have been an important research focus in robotics due to their advantages in nondestructive contact and excellent motion adaptability, which enable flexible manipulation, extreme environments exploration, and in vivo surgical treatment. Various soft robots actuated electrically, magnetically, optically, and fluidically are built toward different application scenarios. Among them, electrical actuation method is an advanced choice to actuate and control soft actuators that are expected to be compatible and integrated with existing industrial robotic systems and wearable intelligent devices. Current robotic systems have higher requirements on the actuators’ function, which can be explored through material and structural designs. Based on a variety of deformable materials, the structural design enables the soft actuators to span from low dimension to high dimension with further improvement in function. Therefore, in this review, 2D and 3D electrical‐based soft actuators from the perspective of dimension design are introduced, which involve functional materials, structure design, and fabrication technology. Some novel 3D fabrication methods, such as the 3D compressive buckling process, are summarized to build 3D soft robots. This review aims at offering important guidelines for the development of soft actuators and the construction of integrated robotic systems in the future.

Deep and ultra-deep shale gas resources have great potential, but well drilling faces many challenges. The Polycrystalline Diamond Compact (PDC) bit has become the primary rock-breaking instrument for oil and gas drilling. Reasonable bit structure designs can promote rock-breaking efficiency and extend service life. In this study, reverse modeling technology is used to analyze the structural characteristics of PDC bits collected in the field, and the influence of the structural characteristics of the bit at a specific interval on the rate of penetration (ROP) and drill footage is investigated using the Spearman rank correlation coefficient method. The number of blades, cutting angle of the cutters, crown rotation radius, internal cone angle, and diameter of the cutters are discovered to be the main structural characteristics that affect the ROP and footage of the bits, and the degree of influence varies depending on the formation conditions. The number of blades, crown rotation radius, inner cone angle, and cutting angle of the cutters have a significant impact on the ROP, whereas blade thickness, gauge length, gauge width, nozzle equivalent diameter have a significant impact on the bit footage. In addition, a back propagation (BP) neural network is utilized to build a prediction model of bit footage and ROP over a certain interval based on the structural characteristics of the bit. The goodness of fit of the model is greater than 85%, and its accuracy is high. Based on the usage of the bit, the evaluation and prediction of the bit can provide a reference for the structural design and optimization of the bit in a specific interval, guide the bit selection work, rationally plan the drilling operation, and reduce the drilling cost.

Abstract Thin and flexible skin electronics have attracted great attention for their applications in monitoring human health status continuously and intelligently. However, the versatility of these electronics is impeded by the performance of power supply and sensor modules, and their portability is also restricted by the need for external devices to handle data processing and analysis. Here, this work presents a wearable electronics system with health status sensing and visualization system (HSSVS), where the power is supplied by sweat‐activated batteries (SABs). The reported system enables the detection of crucial human physiological information, such as the Na+ concentration and the pH level in sweat, as well as skin temperature. The electrodes of the sensors and the batteries are fabricated by the laser ablation method. The laser‐induced polyimide (PI)/gelatin‐based graphene (LIGA) based sensors show a wide linear range for the sensing markers with high sensitivity, and high selectivity. The SABs based on laser‐induced PI/gelatin based graphene anchored with manganese dioxide (LIGA@MnO2) can support the entire sensing and visualization system with ultrathin, excellent biocompatibility, and mechanical properties. Additionally, incorporating a visualization design such as color changes in LEDs enables users to easily identify variations in health status. This integrated system demonstrates promising potential in smart sensing devices for health management.

Antimicrobial resistance has brought great burden to global public health. Alternative strategies are needed to reduce the development of drug resistance. Herein, we have developed an effective synergistic antibacterial strategy combining low–temperature photothermal therapy (LT–PTT) with antibiotic therapy, improving the bactericidal efficiency to avoid antimicrobial resistance. Copper sulfide templated with bovine serum albumin (CuS–BSA) nanoparticles were selected as the photothermal agent, and co–loaded into the hydrogel (Gel) with mupirocin. The Gel could slow down the release rate of CuS–BSA and mupirocin, thereby prolonging the effective drug reaction time. More importantly, when applying near–infrared laser irradiation, the antibacterial activity of the platform could be enhanced greatly by LT–PTT effect of CuS–BSA nanoparticles. In vitro and in vivo results both confirmed that the antibacterial efficacy of the synergistic therapeutic strategy was improved greatly with complete bacterial removal. Overall, this platform has posed a potential strategy to reduce the development of drug resistance and improve patient compliance.

As electronic devices get smaller, more portable, and smarter, a new approach of realizing electronics in thin, soft, and even stretchable style that could be worn and attached to the skin, which is called skin electronics, has emerged and attracted much attention. To achieve well compliance, extend the maximum stretchability, promote the comfortability of wearing, and make the most use of the skin electronics, researchers are making efforts in different aspects. In this article, we summarized the recent advances in categories of materials science, design strategies and novel applications. Examples of skin electronics using various functional materials including piezoelectric, thermoelectric, etc., and soft conductive materials including PEDOT: PSS-based conductive polymer, carbon nanomaterials, metal-based materials and hydrogels were given. Different mechanics design strategies for enhancing mechanical performance and comfortability design strategies for better wearing experience were introduced. Lastly, practical applications of skin electronics in fields of smart healthcare and human-machine interface were discussed. Research focused on these aspects all boosted the development of skin electronics in different dimensions, with which combined together may help skin electronics take a leap into truly ubiquitous use in our daily life.

The well trajectory of horizontal wells are constantly changing due to the variation of well inclination and azimuth with depth, leading to a large difference of displacement efficiency in the annulus compared to a vertical well. In low pressure and leakage formations, optimizing injection parameters to improve displacement efficiency is a hot and difficult research topic for researchers and field engineers, particularly the complex well. A fluid flow model inside the casing and annulus was established during primary cementing under an eccentric casing. Pressure distribution in the eccentric and concentric annuli were compared with the field data. Based on the principle of the maximum circulation pressure being lower than formation leakage pressure, the injection rate and fluid density were optimized to improve displacement efficiency, using Computational Fluid Dynamics (CFD) methods and investigating the mud retention volume on the wall. The results indicated that the pressure model in a casing eccentricity with an error of 1% to 3.5% is in good agreement with the actual pump pressure. Frictional pressure loss in the eccentric annulus was 13% to 25% lower than in the concentric annulus. Appropriately increasing the fluid density difference (spacer and lead slurry), the mud retention volume in the annulus of the horizontal section decreased significantly, while increasing the injection rate at the wellhead had little influence on displacement efficiency. The sequence of displacement efficiency from high to low was horizontal section > deflecting section > vertical section. The results of this study allow a better understanding of casing eccentricity effect on circulation pressure and equivalent circulation density (ECD) distributions in the annuls. The complex displacement mechanism analysis for the horizontal, deflecting, and vertical sections provides practical guidance in improving displacement efficiency by optimizing the most effective operation parameters.

Visual simultaneous localization and mapping is a widely used technology for mobile robots to carry out precise positioning in the environment of GNSS technology failure. However, as the robot moves around indoors, its position accuracy will gradually decrease over time due to common and unavoidable environmental factors. In this paper, we propose an improved method called RTABMAP-VIWO, which is based on RTABMAP. The basic idea is to use an Extended Kalman Filter (EKF) framework for fusion attitude estimates from the wheel odometry and IMU, and provide new prediction values. This helps to reduce the local cumulative error of RTABMAP and make it more accurate. We compare and evaluate three kinds of SLAM methods using both public datasets and real indoor scenes. In the dataset experiments, our proposed method reduces the Root-Mean-Square Error (RMSE) coefficient by 48.1% compared to the RTABMAP, and the coefficient is also reduced by at least 29.4% in the real environment experiments. The results demonstrate that the improved method is feasible. By incorporating the IMU into the RTABMAP method, the trajectory and posture errors of the mobile robot are significantly improved.

Seismo-induced Thermal infrared (TIR) anomalies has been proposed as a significant precursor of earthquakes. Several methods have been proposed to detect Thermal infrared anomalies that may be associated with earthquakes. However, there is no comparison of the influence for Thermal infrared extraction methods with a long time statistical analysis. To quantify the effects of various techniques used in Thermal infrared anomaly extraction, in this paper, we offer a complete workflow of their comparative impacts. This study was divided into three parts: anomaly detection, statistical analysis, and tectonic factor research. For anomaly detection, daily continuous nighttime surface temperature (ConLST) data was obtained from the Google Earth Engine (GEE) platform, and each different anomaly detection method was used to detect Thermal infrared outliers in the Sichuan region (27°-37°N, 97°-107°E). During statistical analysis, The heated core model was applied to explore Thermal infrared anomalies which is to filter anomalies unrelated to earthquakes by setting time-space-intensity conditions. The 3D error diagram offers scores to assume the best parameter set using training-test-validation steps. In the final part, we considered information on stresses, active faults, and seismic zones to determine the optimal parameters for extracting the Thermal infrared anomalies. The Kalman filter method detected the highest seismic anomaly frequency without considerating the heating core condition. The Autoencoder and Isolation Forest methods obtain the optimal alert type and parameter set to determine if the anomaly is likely earthquake-related. The RST method performs optimally in the final part of the workflow when it considers physical factors such as active faults, seismic zones, and stresses. However, The six methods we have chosen are not sufficient to contain the entire Thermal infrared anomaly extraction. The consideration of tectonic factors in the research remains poorly developed, as statistical methods were not employed to explore the role of constructive factors. Nevertheless, it is a significant factor in comparing anomaly extraction methods and precursor studies.

Unmanned aerial vehicle (UAV) swarm coordinated confrontation is a hot topic in academic research at home and abroad, and dynamic maneuver decision-making is one of the most important research fields for UAV countermeasures. Aiming at the complexity, uncertainty and confrontation of UAV cooperative confrontation, concepts such as relative advantage degree and advantage coefficient are introduced, and game theory is used as a framework to construct a dynamic non-zero-sum game UAV cluster cooperative confrontation decision-making model, and finally convert it into an optimization problem. On this basis, using the Nash equilibrium solution method of multi-strategy fusion particle swarm algorithm, by introducing adaptive inertia weight and local mutation strategy, while enhancing the diversity of the population, it can ensure the local accurate search ability of the particle swarm. The simulation results of the example are verified. The effectiveness of the proposed model and method is confirmed.

In order to improve the cuttings transport ability and well hole purification effect of horizontal shale gas wells in the Sichuan and Chongqing area, a new type of aluminum alloy drill pipe is put forward, and the floatability is validated by theoretical analysis and actual parameter calculation. According to the cuttings migration mechanism, the cuttings cleaning simulation model of the new aluminum alloy drill pipe and the traditional steel drill pipe was established by Fluent, and the hexahedral mesh is used to divide the model. Thus, the mesh independence and convergence of the two models are verified. Then, the simulation model is verified by comparing the calculation results of the two simulation models with the experimental data of the indoor cuttings migration device. Finally, the rock-cleaning ability of the two drill pipes is analyzed under the conditions of changing the cuttings particle size, well inclination angle, displacement, and mechanical speed. Compared with the traditional steel drill pipe, the new aluminum alloy drill pipe can improve the borehole purification capacity by 13% on average. This research result is of great significance in reducing the quality of cuttings in the annulus and improving the borehole purification effect.

A series of 98% deuterated DKDP crystals were grown in solutions with different pD values (2.9, 3.3, 3.8, and 4.3) using the rapid growth method. Samples were cut along the z-direction and fourth-harmonic-generation (FHG) direction which contained both pyramidal and prismatic regions. The nonlinear absorption (NLA) coefficient β of 98% deuterated DKDP crystals was obtained using the Z-scan method operated at the FHG wavelength (266 nm) of a picosecond Nd:YAG laser. According to the results, the nonlinear absorption at 266 nm could be identified as two-photon absorption. The β values of crystal grown in the solution with 3.3 pD value were higher than those of crystals grown in solutions with other pD values under higher laser fluence. The results also indicated that FHG device samples should be prepared from the pyramidal region due to its lower β value. This work will help optimizing the application of 98% DKDP crystals as FHG elements in high-power laser systems.

The properties of solutions of the following differential equation $ f^{(k)}+A_{k-1}(z)f^{(k-1)}+\cdots+A_{1}(z)f'+A_{0}(z)f = F(z) $ are studied, where $ A_{j}(z) $ and $ F(z) $ are analytic in the unit disc $ \mathbb{D} = \{z:|z| < 1\} $, $ j = 0, 1, \ldots, k-1 $. First, the growth of solutions of the equation is estimated. Second, some coefficient's conditions such that the solution of the equation belong to Hardy type spaces are showed. Finally, some related question are studied in this paper.

Semiconductor photocatalysis is an effective strategy for solving the problems of increasing energy demand and environmental pollution. ZnIn2S4-based semiconductor photocatalyst materials have attracted much attention in the field of photocatalysis due to their suitable energy band structure, stable chemical properties, and good visible light responsiveness. In this study, ZnIn2S4 catalysts were modified by metal ion doping, the construction of heterojunctions, and co-catalyst loading to successfully prepare composite photocatalysts. The Co-ZnIn2S4 catalyst synthesized by Co doping and ultrasonic exfoliation exhibited a broader absorption band edge. Next, an a-TiO2/Co-ZnIn2S4 composite photocatalyst was successfully prepared by coating partly amorphous TiO2 on the surface of Co-ZnIn2S4, and the effect of varying the TiO2 loading time on photocatalytic performance was investigated. Finally, MoP was loaded as a co-catalyst to increase the hydrogen production efficiency and reaction activity of the catalyst. The absorption edge of MoP/a-TiO2/Co-ZnIn2S4 was widened from 480 nm to about 518 nm, and the specific surface area increased from 41.29 m2/g to 53.25 m2/g. The hydrogen production performance of this composite catalyst was investigated using a simulated light photocatalytic hydrogen production test system, and the rate of hydrogen production by MoP/a-TiO2/Co-ZnIn2S4 was found to be 2.96 mmol·h−1·g−1, which was three times that of the pure ZnIn2S4 (0.98 mmol·h−1·g−1). After use in three cycles, the hydrogen production only decreased by 5%, indicating that it has good cycle stability.

With the rapid development of MOOCs, more and more learners participate in online learning to improve their abilities. However, students from different educational backgrounds have different starting points, requirements and foundation. How to use the hierarchical relationship between course concepts to provide learners with personalized learning courses can help learners overcome difficulties and reduce the dropout rate of online learning. course concept has the characteristics of hierarchy and prerequisite relation. We can integrate the prior knowledge of hierarchy into the feature vector of course concept. Traditional methods based on machine learning or deep learning embed the features of course into Euclidean space, thereby losing the embedded feature information of hierarchical relationship between course concepts. In recent years, the deep learning method based on hyperbolic space has unique advantages in representing hierarchical structure data. Based on this, we propose a hyperbolic deep learning representation based course concept relationship prediction algorithm, which can better retain hierarchical relationship information between concepts. First, we use the word embedding method of hyperbolic space to express the course concepts (feature vector extraction), then we has defined the distance of the two vectors of in hyperbolic space and calculate the distance between course concepts, finally we determine whether there is a prerequisite relationship between course concepts through hyperbolic FFNN and hyperbolic MLR.The experimental results show that the hyperbolic space is better than the Euclidean space. (F1 scores improved 6.8%).

Infectious etiologies and tumors are common triggers of autoimmune encephalitis. We herein reported a rare case of autoimmune encephalitis with multiple autoantibodies in cerebrospinal fluid (CSF) and serum, with concomitant human herpesvirus 7 (HHV-7) infection and ovarian teratoma. A 36-year-old woman presented with mental and behavioral changes and gibberish for 13 days, followed by fever for 1 day. Her brain MRI indicated limbic encephalitis. Metagenomic next-generation sequencing (mNGS) of CSF revealed HHV-7. Antibody testing showed positive anti-N-methyl-D-aspartate receptor (NMDAR) and anti-α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) antibodies in CSF and serum. Ovarian teratoma was considered after pelvic MRI, which was then pathologically confirmed after laparoscopic ovariectomy. Her conditions improved after laparoscopic surgery, intravenous steroids, immunoglobulin, and rituximab therapy. Our findings suggested that the combination of multiple therapies including antiviral, immunotherapy, and resection of tumors were appropriate and improved the prognosis, when HHV-7 infection and ovarian teratoma were concomitant with multiple anti-neuronal antibodies of autoimmune encephalitis.

Wearable exoskeletons play an important role in people’s lives, such as helping stroke and amputation patients to carry out rehabilitation training and so on. How to make the exoskeleton accurately judge the human action intention is the basic requirement to ensure that it can complete the corresponding task. Traditional exoskeleton control signals include pressure values, joint angles and acceleration values, which can only reflect the current motion information of the human lower limbs and cannot be used to predict motion. The electromyography (EMG) signal always occurs before a certain movement; it can be used to predict the target’s gait speed and movement as the input signal. In this study, the generalization ability of a BP neural network and the timing property of a hidden Markov chain are used to properly fuse the two, and are finally used in the research of this paper. Experiments show that, using the same training samples, the recognition accuracy of the three-layer BP neural network is only 91%, while the recognition accuracy of the fusion discriminant model proposed in this paper can reach 95.1%. The results show that the fusion of BP neural network and hidden Markov chain has a strong solving ability for the task of wearable exoskeleton recognition of target step speed.

There are multiple participants, such as farmers, wholesalers, retailers, financial institutions, etc., involved in the modern food production process. All of these participants and stakeholders have a shared goal, which is to gather information on the food production process so that they can make appropriate decisions to increase productivity and reduce risks. However, real-time data collection and analysis continue to be difficult tasks, particularly in developing nations, where agriculture is the primary source of income for the majority of the population. In this paper, we present a smart decision-support system for pig farming. Specifically, we first adopt rail-based unmanned vehicles to capture pigsty images. We then conduct image stitching to avoid double-counting pigs so that we can use image segmentation method to give precise masks for each pig. Based on the segmentation masks, the pig weights can be estimated, and data can be integrated in our developed mobile app. The proposed system enables the above participants and stakeholders to have real-time data and intelligent analysis reports to help their decision-making.

Earthquakes are the most dangerous natural disasters, and scholars try to predict them to protect lives and property. Recently, a long-term statistical analysis based on a “heating core” filter was applied to explore thermal anomalies related to earthquakes; however, some gaps are still present. Specifically, (1) whether there are differences in thermal anomalies generated by earthquakes of different magnitudes has not yet been discussed; and (2) thermal anomalies in high-spatial-resolution data are often distributed in spots, which is not convenient for statistics of thermal anomalies. To address these issues, in this study, we applied high-spatial-resolution thermal infrared data to explore the performance of the “heating core” for earthquake prediction at different magnitudes (i.e., 3, 3.5, 4, 4.5, and 5). The specific steps were as follows: first, the resampling and moving-window methods were applied to reduce the spatial resolution of the dataset and extract the suspected thermal anomalies; second, the “heating core” filter was used to eliminate thermal noise unrelated to the seismic activity in order to identify potential thermal anomalies; third, the time–distance–magnitude (TDM) windows were used to establish the correspondence between earthquakes and thermal anomalies; finally, the new 3D error diagram (false discovery rate, false negative rate, and space–time correlation window) and the significance test method were applied to investigate the performance under each minimum magnitude with training data, and the robustness was validated using a test dataset. The results show that the following: (1) there is no obvious difference in the thermal anomalies produced by earthquakes of different magnitudes under the conditions of a “heating core”, and (2) the best model with a “heating core” can predict earthquakes effectively within 200 km and within 20 days of thermal anomalies’ appearance. The binary prediction model with a “heating core” based on thermal infrared anomalies can provide some reference for earthquake prediction.

Finding out the reasons for wellbore instability in the Longmaxi Formation and Wufeng Formation and putting forward drilling fluid technical countermeasures to strengthen and stabilize the wellbore are very crucial to horizontal drilling. Based on X-ray diffraction, electron microscope scanning, linear swelling experiment, and hot-rolling dispersion experiment, the physicochemical mechanism of wellbore instability in complex strata was revealed, and thus, the coordinated wellbore stability method can be put forward, which is “strengthening plugging of micropores, inhibiting filtrate invasion, and retarding pressure transmission.” Using a sand bed filtration tester, high-temperature and high-pressure plugging simulation experimental device, and microporous membrane and other experimental devices, the oil-based drilling fluid treatment agent was researched and selected, and a set of an enhanced plugging drilling fluid system suitable for shale gas horizontal well was constructed. Its temperature resistance is 135°C and it has preferable contamination resistibility (10% NaCl, 1% CaCl2, and 8% poor clay). The bearing capacity of a 400 μm fracture is 5 MPa, and the filtration loss of 0.22 μm and 0.45 μm microporous membranes is zero. Compared with previous field drilling fluids, the constructed oil-based drilling fluid system has a greatly improved plugging ability and excellent performance in other aspects.

Intelligent unconventional reservoir optimal production control technology is a comprehensive technology, involving geology, reservoir simulation, and efficient drilling and completion. Efficient drilling and completion provides a flow channel for unconventional oil and gas exploitation and a wellbore with good integrity for reservoir transformation, which is an important link in the efficient development of unconventional oil and gas. The application of industry standard method to evaluate the performance of oil-based drilling fluid has the problem of poor correlation. It cannot reflect the difference of performance among oil-based drilling fluid systems, which lacks the significance for field construction. Based on shale expansion, rolling dispersion experiment, and microporous membrane filtration loss test, the physicochemical mechanism of borehole wall instability in shale formation was investigated. The evaluation methods of shale lubrication, antiaccretion test, slake durability, buck hardness test, etc. are put forward, and the formula of oil-based drilling fluid is optimized. The lubrication and antiaccretion experiment method can effectively and intuitively characterize the cleaning and lubrication effect of drilling fluid on drilling tools. The slake durability evaluation method simulates the collision between drill cuttings and the drill string and well wall. The bucking hardness experiment is through testing the cuttings and the hardness change after drilling fluid action reflects its inhibitory effect. The new methods were used to evaluate the oil-based drilling fluid used in 4 wells in the Changning block. It was found that the drilling fluid of CN209H2 well adhered to the steel column with at least 0.41 g of cuttings; the recovery rate of the drilling fluid resistance of CN209H1 was up to 87.70%, and YX1200 oil-based drilling fluid plugging agent was selected through the microporous membrane experiment. In the process of drilling the well CN209H5, the new oil-based drilling fluid formulation improved the lubrication performance by 44%, accompanied by 95.48% recovery rate and less than 10 mL HTHP fluid loss at the same time. The research results show that the oil-based drilling fluid system optimized according to the new method can significantly inhibit shale hydration and dispersion and can effectively solve the problem of unstable performance of traditional oil-based drilling fluids in the Changning block.

Acoustic characteristics measured by acoustic logging are usually used to estimate the structures and mechanical properties of rock materials. However, it is problematic to measure acoustic characteristics of shales because of their structural anisotropy caused by the bedding structures. This study focused on the effects of bedding structures on the acoustic characteristics of shales at operating frequencies of acoustic logging. A numerical model was first established to estimate the acoustic characteristics of shales based on the viscoelastic theory. Then, acoustic transmission experiments were conducted to examine the acoustic characteristics of shales with different bedding angles. The model calculations were compared with experimental results, showing good agreement. Based on the model, the effects of the angle, density, and thickness of bedding planes on the acoustic characteristics of shales at operating frequencies of acoustic logging were analyzed in detail. The results indicate that the wave velocity and main amplitude increased with increasing bedding angle whereas the attenuation coefficient decreased. The wave velocity monotonically decreased with an increase in the bedding density and thickness when the acoustic waves were transmitted through the shale model, but the attenuation of acoustic waves exhibited an opposite trend with the slope. In comparison, the dominant frequency was relatively stable with variations in the bedding structures. In general, the effect of bedding thickness on the acoustic characteristics of shales was smaller than those of the bedding angle and bedding density. The findings of this study can be beneficial for the accurate measurement of shale acoustic characteristics in acoustic logging.

In this work, a plasmonic Ag/Ag3PO4/Chitosan composite photocatalyst was prepared by a low-temperature strategy. Environmentally friendly chitosan plays triple vital roles in this composite. First, it was devoted to in situ reduce metallic silver from silver ions of Ag3PO4. Also, as a carrier of Ag/Ag3PO4 nanoparticles, chitosan can effectively prevent aggregation. Furthermore, benefiting from the settlement of hydrophilic chitosan, the prepared composite could be easily separated and recovered from the solution system. X-ray diffraction, scanning electron microscope, energy-dispersive X-ray spectroscopy, UV–visible diffused reflectance spectroscopy and X-ray photoelectron spectroscopy were employed to characterize the properties of materials. The results of photo-decomposition testing showed that the Ag/Ag3PO4/Chitosan composite possessed a good activity for the decomposition of Rhodamine B (RhB) under visible light.

To provide the general information on corneal transplantation (CT) in China, China Cornea Society designed a questionnaire on CT from 2014 to 2018 and entrusted it to 31 committee members for implementation of the survey nationwide. This article presents the results of the survey and compares the indicators used in the survey and those in the annual statistical report released by the Eye Bank Association of America (EBAA). The number of corneal transplantations completed by the 64 hospitals from 2014 to 2018 was respectively 5377, 6394, 7595, 8270 and 8980, totally 36,616 (22,959 male and 13,657 female). The five largest hospitals by the number of corneal transplantations completed 15,994 surgeries in total, accounting for 43.68% of all the surgeries performed in the 64 hospitals. The most common indication for corneal transplantations was corneal leukoma (7683, 20.98%), followed by bacterial keratitis (4209, 11.49%), corneal dystrophies (4189, 11.44%), keratoconus (3578, 9.77%) and corneal perforation (2839, 7.75%). The main surgical techniques were penetrating keratoplasty (PK) (19,896, 54.34%), anterior lamellar keratoplasty (ALK) (13,869, 37.88%). The proportion of PK decreased from 57.97% in 2014 to 52.88% in 2018 while the proportion of ALK increased from 36.04% in 2014 to 37.92% in 2018. The geographical distribution of keratoplasties performed in China is unbalanced. PK and ALK were the main techniques of CT and corneal leukoma, bacterial keratitis and corneal dystrophies were the main indications for CT in China.

This paper is concerned with an optimal control problem governed by a Kirchhoff-type variational inequality. The existence of multiplicity solutions for the Kirchhoff-type variational inequality is established by using some nonlinear analysis techniques and the variational method, and the existence results of an optimal control for the optimal control problem governed by a Kirchhoff-type variational inequality are derived.

In this paper, we obtain some characterizations of composition operators Cφ, which are induced by an analytic self-map φ of the unit disk Δ, from hyperbolic Bloch type space βμ∗ into hyperbolic type space QK,p,q∗.

Abstract Background Systemic lupus erythematosus (SLE) is an autoimmune inflammatory disorder characterized by multiple affected systems. More than half of SLE patients will suffer from neuropsychiatric lupus erythematosus (NPSLE) during the course of their disease. Although nearly half of the NPSLE patients have normal MRI manifestations, the abnormalities found in the remainder can be located anywhere in the brain, and especially in the subcortical white matter of the frontal and temporal lobe. However, NPSLE involving the medulla oblongata and spinal cord which presents as the “owl’s eye” sign has to our best knowledge not been reported to date. Case presentation A 19-year-old girl presented at our hospital with a 7-day history of fever and headache since a one day’s exertion, accompanied by 2 days of weakness. The patient had slurred speech. Neurological examination revealed the presence of horizontal nystagmus and a limitation of bilateral eye movement when looking up and down. At the same time, she showed difficulty in raising the jaw, accompanied by a weak pharyngeal reflex. Muscle strength was remarkably decreased in all four extremities: the MRCS grade of the upper limbs was 4/5, while in the lower limbs it was 0/5. Hypotonia was apparent in the lower extremities. Regarding subjective sensation, the patient appeared to be experiencing an increased sense of pain in the whole body, and especially in the cervical region, abdomen, and feet. An examination of shallow reflex documented the reinforcement of the abdominal reflex. Deep tendon reflexes were symmetric: absent in lower, normal in upper extremities. The patient also had a stiff neck with a positive Kernig’s sign. The laboratory examination showed elevated C - reactive protein and rheumatoid factor, as well as complement components 3 and 4. Symptomatic treatments were applied, but she did not respond well, after which we did immunological laboratory examinations. The results showed the presence of anti-nRNP/Sm, anti-dsDNA and anti-AMA M2 antibodies. An MRI scan and enhancement of the cervical and thoracic regions displayed abnormal signs in the medulla and bilateral anterior horn of the lower thoracic spine. Following the exclusion of other possible diseases, neuropsychiatric lupus was diagnosed. High-dose intravenous gamma-globulin combined with methylprednisolone gradually improved her condition. Conclusion We report the first case of NPSLE presenting with medulla oblongata and spinal cord involvement, manifesting as the “owl’s eye” sign in MRI.

Retractable roofs are commonly used in designing large-span stadiums because of their versatility. However, retractable roofs are subject to sudden changes in shape, and thus, factors in addition to those considered for conventional roofs need to be taken into account. In particular, retractable roofs are considerably more sensitive to snow loads because their shapes are complex, and snowdrift on roofs may lead to difficulties for the operating of retractable roofs. To investigate the distribution of snow on retractable roofs, this study proposes a method based on a numerical simulation of snowdrift obtained using the Euler–Euler method in multiphase flow theory. This numerical model employs a mixture model by using the commercial computational fluid dynamics (CFD) software FLUENT. A suitable turbulence model is selected for the simulation through verification against two-dimensional (2D) data obtained from field measurements reported in previous studies. However, the snow load on retractable roofs cannot be determined by a 2D distribution easily. The accuracy of predicting the overall distribution of snow load on roofs was verified by experiments conducted on a horizontally retractable roof. The results show that a nonuniform snow distribution on such roofs is distinct and should be considered.

Suppose that φ(z) is an analytic self-map of the unit disk Δ. We consider the boundedness of the composition operator Cφ from Bloch space ℬ into the spaces QT (QT,0) defined by a nonnegative, nondecreasing function T(r) on 0≤r

We consider that the linear differential equations f(k)+Ak-1(z)f(k-1)+⋯+A1(z)f′+A0(z)f=0, where Aj (j=0,1,…,k-1), are entire functions. Assume that there exists l∈{1,2,…,k-1}, such that Al is extremal for Yang's inequality; then we will give some conditions on other coefficients which can guarantee that every solution f(≢0) of the equation is of infinite order. More specifically, we estimate the lower bound of hyperorder of f if every solution f(≢0) of the equation is of infinite order.

The boundedness and compactness of generalized composition operators on Zygmund-Orlicz type spaces and Bloch-Orlicz type spaces are established in this paper.

Experimental work was carried out to develop information about mechanical properties of recycled concrete (RC) in marine environment. By using the seawater and dry-wet circulation to simulate the marine environment, specimens of RC were tested with different replacement percentages of 0%, 30%, and 60% after immersing in seawater for 4, 8, 12, and 16 months, respectively. Based on the analysis of the stress-strain curves (SSCs) and compressive strength, it is revealed that RC’ peak value and elastic modulus decreased with the increase of replacement percentage and corroding time in marine environment. And the failure of recycled concrete was speeded up with more obvious cracks and larger angles of 65° to 85° in the surface when compared with normal concrete. Finally, the grey model (GM) with equal time intervals was constructed to investigate the law of compressive strength of recycled concrete in marine environment, and it is found that the GM is accurate and feasible for the prediction of RC compressive strength in marine environment.

Pom2 is predicted to be a dual-specificity tyrosine-phosphorylation regulated kinase (DYRK) related to Pom1 in Schizosaccharomyces pombe. DYRKs share a kinase domain capable of catalyzing autophosphorylation on tyrosine and exogenous phosphorylation on serine/threonine residues. Here we show that Pom2 is functionally different from the well-characterized Pom1, although they share 55% identity in the kinase domain and the Pom2 kinase domain functionally complements that of Pom1. Pom2 localizes to mitochondria throughout the cell cycle and to the contractile ring during late stages of cytokinesis. Overexpression but not deletion of pom2 results in severe defects in cytokinesis, indicating that Pom2 might share an overlapping function with other proteins in regulating cytokinesis. Gain and loss of function analyses reveal that Pom2 is required for maintaining mitochondrial morphology independently of microtubules. Intriguingly, most meiotic pom2Δ cells form aberrant asci with meiotic and/or forespore membrane formation defects. Taken together, Pom2 is a novel DYRK kinase involved in regulating cytokinesis, mitochondrial morphology, meiosis, and sporulation in fission yeast.