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Abstract Suppression of energy disorders in the vertical direction of a photovoltaic device, along which charge carriers are forced to travel, has been extensively studied to reduce unproductive charge recombination and thus achieve high-efficiency perovskite solar cells. In contrast, energy disorders in the lateral direction of the junction for large-area modules are largely overlooked. Herein, we show that the micro-inhomogeneity characteristics in the surface lateral energetics of formamidinium (FA)-based perovskite films also significantly influence the device performance, particularly with accounting for the stability and scale-up aspects of the devices. By using organic amidinium passivators, instead of the most commonly used organic ammonium ones, the micro-inhomogeneity in the lateral energy landscapes can be suppressed, greatly improving device stability and efficiency of FA-based single-junction perovskite solar cells.

Background: Managing recurrent pterygium combined with symblepharon presents significant challenges in ophthalmology. Clinicians aim to reconstruct the ocular surface, alleviate eye movement restrictions, and minimize recurrence risks. Objective: Evaluation of efficacy and safety of continuous blanket sutures (CBS) for fixation of large autologous conjunctival grafts in patients with severe recurrent pterygium with symblepharon. Methods: Retrospective, observational case series. Thirty-nine patients (40 eyes) were included, all with severe recurrent pterygium with symblepharon. During surgery, CBS was employed to affix large autologous conjunctival grafts to the exposed sclera, aiming to restore the ocular surface to smoothness as much as possible. All patients were followed up for more than one year. Main outcome measures include the rate of recurrence, improvement of eye movement, and intraoperative and postoperative complications. Results: Nearly all patients exhibited a smooth ocular surface and largely restored physiological structures during the follow-up period. There were no graft loss or contraction cases until the last follow-up, with only three eyes experiencing a pterygium recurrence (recurrence rate 7.5%, 3/40). Preoperative eye movement limitations improved significantly from 2.10 ± 0.71 (range 1–3) to 0.33 ± 0.53 (range 0–2; p

Abstract Purpose To compare the postoperative rehabilitation of femoral neck fractures treated with robot-assisted nailing and freehand nailing. Methods We systematically searched the PubMed, EMBASE, Cochrane, China National Knowledge Infrastructure(CNKI), WanFang database, China Science and Technology Journal Database (VIP) and Web of Science databases to identify potentially eligible articles. Indispensable data such as the year of publication, country, study type, robot type, age, number of patients, sex distribution, study design, and outcome indicators were extracted. The outcome indicators of interest included healing rate, length of healing time, Harris score, operation time, frequency of X-ray fluoroscopy, frequency of guide pin insertion, and intraoperative blood loss. RevMan 5.4.1 was used for the meta-analysis. Results Fourteen studies with 908 participants were included in this meta-analysis. The results showed that in terms of healing rate (SMD = 2.75, 95% CI, 1.03 to 7.32, P = 0.04) and Harris score (SMD = 2.27, 95% CI, 0.79 to 3.75, P = 0.003), robot-assisted screw placement technique scores were higher than the traditional freehand technique. Additionally, operative time (SMD = -12.72, 95% CI, -19.74 to -5.70, P = 0.0004), healing time (SMD = -13.63, 95% CI, -20.18 to -7.08, P

Facial age recognition has been widely used in real-world applications. Most of current facial age recognition methods use deep learning to extract facial features to identify age. However, due to the high dimension features of faces, deep learning methods might extract a lot of redundant features, which is not beneficial for facial age recognition. To improve facial age recognition effectively, this paper proposed the deep manifold learning (DML), a combination of deep learning and manifold learning. In DML, deep learning was used to extract high-dimensional facial features, and manifold learning selected age-related features from these high-dimensional facial features for facial age recognition. Finally, we validated the DML on Multivariate Observations of Reactions and Physical Health (MORPH) and Face and Gesture Recognition Network (FG-NET) datasets. The results indicated that the mean absolute error (MAE) of MORPH is 1.60 and that of FG-NET is 2.48. Moreover, compared with the state of the art facial age recognition methods, the accuracy of DML has been greatly improved.

A multi-objective pedestrian tracking method based on you only look once-v8 (YOLOv8) and the improved simple online and real time tracking with a deep association metric (DeepSORT) was proposed with the purpose of coping with the issues of local occlusion and ID dynamic transformation that frequently arise when tracking target pedestrians in real complex traffic scenarios. To begin with, in order to enhance the feature extraction network's capacity to learn target feature information in busy traffic situations, the detector implemented the YOLOv8 method with a high level of small-scale feature expression. In addition, the omni-scale network (OSNet) feature extraction network was then put on top of DeepSORT in order to accomplish real-time synchronized target tracking. This increases the effectiveness of picture edge recognition by dynamically fusing the collected feature information at various scales. Furthermore, a new adaptive forgetting smoothing Kalman filtering algorithm (FSA) was created to adapt to the nonlinear condition of the pedestrian trajectory in the traffic scene in order to address the issue of poor prediction attributed to the linear state equation of Kalman filtering once more. Afterward, the original intersection over union (IOU) association matching algorithm of DeepSORT was replaced by the complete-intersection over union (CIOU) association matching algorithm to fundamentally reduce the target pedestrians' omission and misdetection situation and to improve the accuracy of data matching. Eventually, the generalized trajectory feature extractor model (GFModel) was developed to tightly merge the local and global information through the average pooling operation in order to get precise tracking results and further decrease the impact of numerous disturbances on target tracking. The fusion algorithm of YOLOv8 and improved DeepSORT method based on OSNet, FSA and GFModel was named YOFGD. According to the experimental findings, YOFGD's ultimate accuracy can reach 77.9% and its speed can reach 55.8 frames per second (FPS), which is more than enough to fulfill the demands of real-world scenarios.

Abstract The crosstalk between the nerve and stomatognathic systems plays a more important role in organismal health than previously appreciated with the presence of emerging concept of the “brain-oral axis”. A deeper understanding of the intricate interaction between the nervous system and the stomatognathic system is warranted, considering their significant developmental homology and anatomical proximity, and the more complex innervation of the jawbone compared to other skeletons. In this review, we provide an in-depth look at studies concerning neurodevelopment, craniofacial development, and congenital anomalies that occur when the two systems develop abnormally. It summarizes the cross-regulation between nerves and jawbones and the effects of various states of the jawbone on intrabony nerve distribution. Diseases closely related to both the nervous system and the stomatognathic system are divided into craniofacial diseases caused by neurological illnesses, and neurological diseases caused by an aberrant stomatognathic system. The two-way relationships between common diseases, such as periodontitis and neurodegenerative disorders, and depression and oral diseases were also discussed. This review provides valuable insights into novel strategies for neuro-skeletal tissue engineering and early prevention and treatment of orofacial and neurological diseases.

Abstract Study design Meta-analysis and systematic review. Background Robot-assisted pedicle screw placement technique offers greater accuracy than the traditional freehand screw placement technique. However, it is controversial whether there is a difference between the two procedures in terms of improved clinical outcomes. Materials and methods We systematically searched PubMed, EMBASE, Cochrane, and Web of Science to identify potentially eligible articles. Indispensable data such as the year of publication, study type, age, number of patients, sex distribution, and outcomes were extracted. The outcome indicators of interest included Oswestry disability index (ODI), visual analog scale (VAS) score, operative time, intraoperative blood loss, and post-operative length of stay. RevMan 5.4.1 was used for the meta-analysis. Results A total of eight studies with 508 participants were included. Eight were related to ΔVAS, six were related to ΔODI, seven were related to operative time, five were related to intraoperative blood loss, and seven were related to the length of hospitalization. The results showed that, in terms of ΔVAS (95% CI, −1.20 to −0.36, P = 0.0003) and ΔODI (95% CI, −2.50 to −0.48, P = 0.004), robot-assisted pedicle screw placement technique scored higher than traditional freehand technique. Additionally, the intraoperative blood loss (95% CI, −140.34 to −10.94, P = 0.02) and the length of hospitalization (95% CI, −2.59 to −0.31, P = 0.01) for patients who underwent robotic-assisted pedicle screw placement were less than that of those who underwent the conventional freehand screw placement. No significant difference was found between robot-assisted techniques and conventional freehand techniques in pedicle screw placement in surgical time (95% CI, −2.24 to 26.32, P = 0.10). Conclusions Robot-assisted technique helps improve short-term clinical outcomes, reduce intraoperative blood loss and patient suffering, and shorten recovery time compared to the freehand technique.

MXene materials have found emerging applications as catalysts for chemical reactions due to their intriguing physical and chemical applications. In particular, their broad light response and strong photothermal conversion capabilities are likely to render MXenes promising candidates for photothermal catalysis, which is drawing increasing attention in both academic research and industrial applications. MXenes are likely to satisfy all three criteria of a desirable photothermal catalyst: strong light absorption, effective heat management, and versatile surface reactivity. However, their specific functionalities are largely dependent on their structure and composition, which makes understandings of the structure–function relationship of crucial significance. In this review, we mainly focus on the recent progress of MXene–based photothermal catalysts, emphasizing the functionalities and potential applications of MXene materials in fields of photothermal catalysis, and provide insights on design principles of highly efficient MXene–based photothermal catalysts from the atomic scale. This review provides a relatively thorough understanding of MXene–based materials for photothermal catalysis, as well as an in–depth investigation of emerging high-prospect applications in photothermal catalysis.

Background: Ovarian cancer is one of the deadliest gynecological cancers, with the most advanced disease and poor survival. Although BRCA genes play a key role in maintaining genomic stability and providing the possibility of clinically individualized treatments, with the emergence of new and more appropriate treatment options, new treatment–related adverse events are challenging and difficult for clinicians.Case presentation: An 80-year-old Chinese woman was diagnosed with stage IIIC ovarian high-grade serous adenocarcinoma (CT3cN1MX) with BRCA2 as the causative gene. She underwent three courses of neoadjuvant chemotherapy with nab-paclitaxel 400 mg and carboplatin 450 mg before surgery. Chest HRCT prior to chemotherapy demonstrated bilateral interstitial pneumonia. During chemotherapy, there were four episodes of dry cough, shortness of breath, dyspnea, and three episodes of bone marrow suppression. The symptoms became intermittent and progressively worse, and after three sessions of empirical cough and phlegm relief, oxygen inhalation, corticosteroids, anti-infectives, and leukopenia therapy, the symptoms became intermittent and progressively worse. The diagnosis of idiopathic pulmonary fibrosis came a week after the third round of chemotherapy. After a strong dose of corticosteroids and nintedanib anti-fibrosis therapy, the pulmonary symptoms abated, and intermediate tumor starvation was performed. The combination therapy was subsequently discontinued, and the patient experienced significant relief from pulmonary symptoms. Treatment response was positive following single-agent nab-paclitaxel 400 mg chemotherapy in combination with nintedanib 150 mg anti-fibrosis therapy.Conclusion: In this report, we describe a rare case of idiopathic pulmonary fibrosis associated with the use of nab-paclitaxel and carboplatin in ovarian cancer. During treatment, it is necessary to maintain a high level of vigilance for patients with interstitial pneumonia and engage the attention of clinicians to improve medication safety. Early diagnosis and anti-fibrosis therapy can reverse lung damage.

Abstract Particulate matter (PM) has been proved to be a risk factor for the development of circulatory system diseases (CSDs) around the world. In this study, we collected daily air pollutants, emergency room (ER) visits for CSDs, and meteorological data from 2009 to 2012 in Beijing, China. After controlling for the long-term trend and eliminating the influence of confounding factors, the generalized additive model (GAM) was used to evaluate the short-term effects of PM10 on CSDs and cause-specific diseases. The results showed that for every 10 μg/m3 increase in PM10, the largest effect estimates in ER visits of total CSDs, arrhythmia, cerebrovascular diseases, high blood pressure, ischemic heart disease and other related diseases were 0.14% (95% CI: 0.06–0.23%), 0.37% (95% CI: − 0.23 to 0.97%), 0.20% (95% CI: 0.00–0.40%), 0.15% (95% CI: 0.02–0.27%), 0.18% (95% CI: 0.02–0.35%) and 0.35% (95% CI: − 0.04 to 0.79%), respectively. When NO2 or SO2 was added into the model, the effect estimates of PM10 were mostly attenuated, while in those models with PM2.5 added, the effect estimates of PM10 were mostly increased. Stratified analysis indicated that PM10 had a greater effect on males and the elderly.

Sudden changes in the morphological characteristics of trees are closely related to plant health, and automated phenotypic measurements can help improve the efficiency of plant health monitoring, and thus aid in the conservation of old and valuable tress. The irregular distribution of branches and the influence of the natural environment make it very difficult to monitor the status of branches in the field. In order to solve the problem of branch phenotype monitoring of tall and valuable plants in the field environment, this paper proposes an improved UNet model to achieve accurate extraction of trunk and branches. This paper also proposes an algorithm that can measure the branch length and inclination angle by using the main trunk and branches separated in the previous stage, finding the skeleton line of a single branch via digital image morphological processing and the Zhang–Suen thinning algorithm, obtaining the number of pixel points as the branch length, and then using Euclidean distance to fit a straight line to calculate the inclination angle of each branch. These were carried out in order to monitor the change in branch length and inclination angle and to determine whether plant branch breakage or external stress events had occurred. We evaluated the method on video images of Abies beshanzuensis, and the experimental results showed that the present algorithm has more excellent performance at 94.30% MIoU as compared with other target segmentation algorithms. The coefficient of determination (R2) is higher than 0.89 for the calculation of the branch length and inclination angle. In summary, the algorithm proposed in this paper can effectively segment the branches of tall plants and measure their length and inclination angle in a field environment, thus providing an effective method to monitor the health of valuable plants.

The effective thermal conductivity (ETC) model of loose residual coal in goaf is a method to study the heat transfer law of spontaneous combustion in goaf. In order to study the effect of coal particle size and ambient temperature on heat transfer, coal samples of different sizes were taken from the FuSheng (FS) mine, and the void fraction, the thermal conductivity (TC) of the residual coal under different ambient temperature were tested. Additionally, four types of ETC models of loose residual coal in goaf were obtained and the average relative errors of the TC were analyzed. The results showed that the void fraction, the coal particle size and ambient temperature have different effects on the spontaneous combustion of the residual coal. The effect of coal sample size on the heat transfer is 100 times that of the ambient temperature. The changes in the ETC and average relative error of the different models were consistent. The heat transfer in the spontaneous combustion of residual coal has a direct relationship with the spatial distribution and heat transfer modes of the loose residual coal in the goaf.

BackgroundUterine fibroids(UF) are the most common benign tumors in women, with high incidence and unknown causes. We aimed to explore the correlation between Methylenetetra-hydrofolate reductase (MTHFR) C677T polymorphism and UF.MethodsThis is a retrospective cohort study. Data were collected from 2411 women detected for MTHFR C677T polymorphism in the Fifth Affiliated Hospital of Sun Yat-sen University from 2018 to 2020. B-ultrasound (BU) and the first page of medical records were used to analyze whether they had ever been diagnosed with UF. The collected data were analyzed. Using the chi-square test and regression analysis to explore the correlation, and the risk factors was screened by multifactor logistic regression analysis.ResultsA total of 2411 pregnant women were in the MTHFR C677T polymorphism detection. Among them, 226(9.37%) were diagnosed as UF by BU or clinical diagnosis. The allele and genotype of MTHFR C677T were significantly different between the case and control group (p0.05). However, older maternal age was associated with the incidence of UF, especially the multiple UF (p

The major obstacle to treat cervical squamous cell carcinoma (CSCC) is the high prevalence of metastasis, which severely affects 5-year survival rate and quality of life for cancer patients. The DEAD-box helicase family has been reported to be a critical mediator in the development and metastasis of various cancers. DEAD-box helicase 19A (DDX19A) is a member of the DEAD-box helicase family; however, its functional role in CSCC is unclear. In this study, bioinformatics analysis of clinical samples from public databases demonstrated that the expression of DDX19A was elevated in CSCC tissues and that high expression of DDX19A was positively correlated with metastasis and poor clinical outcome. Functionally, we found that DDX19A promoted CSCC cell migration and invasion in vitro and lung metastasis in vivo. Mechanistically, overexpression of DDX19A increased NADPH oxidase 1 (NOX1) expression, enhanced reactive oxygen species (ROS) production, and induced the migration and invasion of CSCC cells. Rescue experiments revealed that DDX19A-induced CSCC functional alterations were dependent on NOX1 and that DDX19A-promoted CSCC metastasis was abrogated upon the inhibition of ROS. Our results demonstrated that DDX19A could promote CSCC metastasis by inducing NOX1-mediated ROS production and that blockage of the NOX1/ROS axis might serve as a potential therapeutic target for patients with DDX19A-overexpressed CSCC.

The strain of fiber-reinforced polymer (FRP) bars at high temperatures is currently difficult to measure. To overcome this difficulty, a method of smart FRP bars embedded with optical fibers was proposed and studied, in which an ordinary single-mode optical fiber was applied as a distributed sensor. In this paper, both the distributed temperature and strain-sensing characteristics of optical fiber were studied based on pulse pre-pump Brillouin optical time-domain analysis (PPP-BOTDA) under high temperature. The temperature and strain coefficients were investigated under a thermomechanical coupling environment with consideration of large strain levels. The experimental results show that the temperature and strain coefficients decreased as the temperature increased, because the properties of silica and coating materials changed with temperature. Then, the formulas for determining the temperature and strain coefficients at high temperatures were introduced and discussed. The excellent sensing performance of the optical fiber indicated that smart FRP bars have the potential for use at high temperatures.