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Abstract Background Following the COVID-19 pandemic, millions of people continue to experience ongoing physical and mental health sequelae after recovery from acute infection. There is currently no specific treatment for the diverse symptoms associated with post-COVID-19 condition. Physical and mental health rehabilitation may help improve quality of life in such patients. This study reports the cost-effectiveness of a programme of physical and mental health rehabilitation compared to best practice usual care in people with post-COVID-19 condition who were previously hospitalised. Methods We conducted an economic evaluation within a randomised controlled trial from the perspective of the UK national health service (NHS) and personnel social services perspective (PSS). Resource used and health-related quality of life were collected using bespoke questionnaire and the EQ-5D-5 L questionnaire at three, six, and 12 months. Incremental costs and quality adjusted life years accrued over the follow-up period were estimated and reported as the incremental cost-effectiveness ratio. Estimate uncertainty was managed by multiple imputation and bootstrapping cost-effectiveness estimates; and displayed graphically on the cost-effectiveness plane. Results Over a 12-month time horizon, incremental costs and QALYs were £305 (95% CI: -123 to 732) and 0.026 (95% CI: -0.005 to 0.052) respectively. The ICER was £11,941 per QALY indicating cost-effective care. Sensitivity analyses supported the base case findings. The probability of the intervention being cost-effective at a £30,000 per QALY willingness-to-pay threshold was 84%. Conclusion The within-trial economic evaluation suggested that people with post-COVID-19 condition after hospitalisation should be offered a programme of physical and mental health rehabilitation as it likely reflects a cost-effective use of NHS resources. Hospitalisation for COVID-19 has become less commonplace: further evaluation in non-hospitalised patients may be worthwhile. Trial registration ISRCTN registry ISRCTN11466448 23rd November 2020.

Abstract A ground-breaking roadmap of III-nitride solid-state deep-ultraviolet light emitters is demonstrated to realize the wafer-scale fabrication of devices in vertical injection configuration, from 2 to 4 inches. The epitaxial device structure is stacked on a GaN template instead of conventionally adopted AlN, where the primary concern of the tensile strain for Al-rich AlGaN on GaN is addressed via an innovative decoupling strategy, making the device structure decoupled from the underlying GaN template. Moreover, the strategy provides a protection cushion against the stress mutation during the removal of substrates. As such, large-sized wafers can be obtained without surface cracks, even after the removal of the sapphire substrates by laser lift-off. Wafer-scale fabrication of 280 nm vertical injection deep-ultraviolet light-emitting diodes is eventually demonstrated, where a light output power of 65.2 mW is achieved at a current of 200 mA, largely thanks to the significant improvement of light extraction. This work will definitely speed up the application of III-nitride solid-state deep-ultraviolet light emitters featuring high performance and scalability.

Due to signal shielding caused by building structures, conventional mature positioning technologies such as the Global Positioning System (GPS) are only suitable for outdoor navigation and detection. However, there are many scenarios that urgently require high-precision indoor positioning technologies, such as indoor wireless optical communications (OWCs), navigation in large buildings, and warehouse management. Here, we proposed a millimeter-precision indoor positioning technology based on metalens-integrated camera, which determines the position of the device through imaging of beacon LEDs. Thanks to the wide-angle imaging design of our metalens, the camera can accurately capture images of beacon LEDs even when it is situated in distant corner locations. Consequently, our localization scheme achieves millimeter-level positioning accuracy across majority of wide-angle (∼120°) indoor area. Compared to traditional positioning schemes by photodiode (PD), our imaging-based approach demonstrates superior resistance to interference, thereby safeguarding positioning precision from the external signals influence. Furthermore, the compact dimensions and high performances of the positioning device make it suitable for integration into highly portable devices, such as smartphones and drones, revealing its broad potential applications in the future.

Abstract 2D stacking presents a promising avenue for creating periodic superstructures that unveil novel physical phenomena. While extensive research has focused on lateral 2D material superstructures formed through composition modulation and twisted moiré structures, the exploration of vertical periodicity in 2D material superstructures remains limited. Although weak van der Waals interfaces enable layer‐by‐layer vertical stacking, traditional methods struggle to control in‐plane crystal orientation over large areas, and the vertical dimension is constrained by unscalable, low‐throughput processes, preventing the achievement of global order structures. In this study, a supercell multiplying approach is introduced that enables high‐throughput construction of 3D superstructures on a macroscopic scale, utilizing artificially stacked single‐crystalline 2D multilayers as foundational repeating units. By employing wafer‐scale single‐crystalline 2D materials and referencing the crystal orientation of substrates, the method ensures precise alignment of crystal orientation within and across each supercell, thereby achieving controllable periodicity along all three axes. A centimeter‐scale 3R‐MoS₂ crystal is successfully constructed, comprising over 200 monolayers of single‐crystalline MoS₂, through a bottom‐up stacking process. Additionally, the approach accommodates the integration of amorphous oxide, enabling the assembly of 3D non‐linear optical crystals with quasi‐phase matching. This method paves the way for the bottom‐up construction of macroscopic artificial 3D crystals with atomic plane precision, enabling tailored optical, electrical, and thermal properties and advancing the development of novel artificial materials and high‐performance applications.

Abstract AlGaN‐based ultraviolet light‐emitting diodes (UV‐LEDs) have the advantages of mercury (Hg) pollution free, small size, high efficiency, and so on, and are widely used in military, medical, and industrial fields, which are considered to be the most promising alternative to the traditional Hg lamps. Great efforts are made over the past few decades to improve the device performance, thereby meeting the commercial production and application requirements of UV‐LEDs, which is always accompanied by a series of interesting physical topics. In this review, the recent research progress in performance of AlGaN‐based UV‐LEDs is summarized from the perspectives of electrical injection, electro‐optical conversion, and light extraction, which are responsible for the operation of devices. The detailed discussions include the major challenges, the corresponding technological breakthroughs, and also the outlook of material growth, energy band modulation, as well as device fabrication involved in UV‐LEDs, which are expected to be helpful for the thorough comprehension of device physics and further development of AlGaN‐based UV‐LEDs.

ObjectivesTo investigate the epidemiological characteristics of Augmented Renal Clearance (ARC) in severe sepsis children with MRSA infection and find risk factors to establish a model predicting ARC onset in PICU.DesignRetrospective study, in which ARC was defined by estimated glomerular filtration rate (eGFR) measured by the modified Schwartz formula above 130 ml/min/1.73 m2. Univariable and multivariable logistic regression analyses were performed to find the predictor for ARC. Multi-strategy modeling was used to form an early prediction model for ARC, which was evaluated by the area under the ROC curve (AUC), accuracy (ACC) and other indicators.SettingOne China PICU.PatientsSevere sepsis children with MRSA infection admitted to PICU from May 2017 to June 2022 at Children's Hospital of Nanjing Medical University.InterventionsNone.Measurements and main results125 of 167 (74.9%) patients with severe sepsis with MRSA infection have occurred ARC during the hospitalization of PICU, of which 44% have an absolute decrease in vancomycin trough level (VTL), patients with ARC have a longer length of stay in both hospital and PICU, lower VTL and require longer anti-infective treatment. 20 different models were established for the early recognition of ARC. Among them, the best performer had an AUC of 0.746 and a high application prospect.ConclusionARC is a phenomenon significantly underestimated in pediatric patients with severe sepsis associated with MRSA infection, which can affect 74.9% of these patients and affects the process of anti-infection treatment and clinical outcomes. To achieve early prediction only by specific risk factors is unreliable, a model based on Multivariate Logistic Regression in this study was chosen to be used clinically.

Abstract Background The SPHERe (Supervised Pulmonary Hypertension Exercise Rehabilitation) trial is a multi-centre, pragmatic, randomised controlled trial assessing the clinical and cost-effectiveness of supervised exercise rehabilitation with psychosocial and motivational support compared to best-practice usual care for people with pulmonary hypertension (PH). The original protocol was published in BMC Pulmonary Medicine (accessible online). We randomised our first participant in January 2020. In response to the COVID-19 pandemic, the trial was stopped in March 2020. In person delivery of the SPHERe intervention to a vulnerable population was not possible during the COVID-19 pandemic. We describe here how trial procedures and intervention delivery were adapted in response to the COVID-19 pandemic. Methods Restrictions imposed by the COVID-19 pandemic on the clinically vulnerable PH population meant that trial delivery was changed from a centre-based rehabilitation programme to remotely delivered group online sessions. This led to minor alterations to the eligibility criteria. These changes followed a consultation process with stakeholders and people with PH and were approved by the funder and independent trial committees. Conclusions We describe the modified SPHERe trial protocol in response to restrictions imposed by the COVID-19 pandemic. SPHERe is the first randomised controlled trial to assess the clinical and cost-effectiveness of an online group rehabilitation programme for people with PH compared to usual care. Trial registration ISRCTN no. 10608766. Prospectively registered on 18th March 2019, updated 16th August 2023.

IntroductionCurrently, the large-scale consumption of fresh citrus fruits in the form of juices, jams, and purees results in significant quantities of waste consisting of citrus peels, pulp, and seeds.MethodsTo improve the utilization rate of whole citrus fruits and reduce the generation of processing waste, the best pre-optimized enzymatic fermentation conditions were used to treat whole citrus fruits and to analyse the changes in nutritional and active components (Enzymatic: pectinase, cellulase, hemicellulase added at a ratio of 1:1:1 for 63.326 min at a temperature of 60°C, with 0.506% of each enzyme added; Fermentation: Lacticaseibacillus rhamnosus TR08, Lactiplantibacillus plantarum subsp. Plantarum CICC 6257, and Limosilactobacillus fermentum CCFM1139 were added at a ratio of 1:1:1 for 30 h, with the concentration was 108 CFU/mL, and the total amount added was 6%).ResultsResults showed that after enzymatic hydrolysis, the mineral elements (Nitrogen, phosphorus), total amino acid, vitamin C, and organic acid content increased. For soluble sugars, the contents of fructose and glucose increased, whereas the sucrose content decreased. Fermentation had a minimal effect on the mineral content; however, the total amino acid, vitamin C, and soluble sugar contents decreased. Additionally, when comparing the samples after enzymatic fermentation to those after enzymatic hydrolysis alone, the total phenols, total flavonoids, carotenoids and antioxidant activities were significantly increased by 1.39, 1.49, 1.21 and 3.79 folds, respectively.DiscussionThis study addresses the challenges of utilizing fruit residue in the current market, including high treatment costs and environmental pollution, by providing a novel perspective on the enzymatic hydrolysis and fermentation of whole red oranges. Furthermore, it aims to improve the nutritional, functional, and health benefits of citrus fruit products.

It is well known that there are several vertical flight phases for the aircraft in the flight. The cruise flight phase takes most of the flight time, flight distance and fuel consumption, so it is important and necessary to develop the flight management system(FMS) vertical trajectory prediction algorithm for the cruise flight phase, aiming to improve the economy, comfort and safety of the flight. In order to meet the versatility of the vertical trajectory prediction algorithm between different types of aircraft in the cruise phase and improve the accuracy and reliability of the vertical trajectory prediction, the algorithm of vertical trajectory prediction for cruise flight phase is proposed in this paper. Firstly, the cruise speed profile is calculated, and the realistic atmospheric model of prediction is constructed. Then the cruise fuel flow data is calculated based on the aircraft model of first-principles, and the vertical trajectory prediction for the cruise phase is given by designing the vertical trajectory prediction algorithm logic. Finally, the effectiveness and accuracy of the algorithm are verified by ground simulation and air flight test. The results show that the vertical trajectory prediction algorithm of FMS cruise phase based on the aircraft model of firstprinciples can predict the cruise trajectory of the aircraft, and the prediction accuracy error is less than 1%.

In the present work, seven Mg-Zn-Ag alloys with the nominal composition of Mg96-xZnxAg4 (x = 17, 20, 23, 26, 29, 32, 35 in at.%) were prepared by induction melting and single-roller melt-spinning. The X-ray diffraction (XRD) analyses indicate the metallic glasses with three composition of Mg73Zn23Ag4, Mg70Zn26Ag4, and Mg67Zn29Ag4 were obtained successfully. The differential scanning calorimetry (DSC) measurement was used to obtain the characteristic temperature of Mg-Zn-Ag metallic glasses for the glass-forming ability analysis. The maximum glass transition temperature (Trg) was found to be 0.525 with a composition close to Mg67Zn29Ag4, which results in the best glass-forming ability. Moreover, the immersion test in simulated body fluid (SBF) demonstrate the relative homogeneous corrosion behavior of the Mg-Zn-Ag metallic glasses. The corrosion rate of Mg-Zn-Ag metallic glasses in SBF solution decreases with the increase of Zn content. The sample Mg67Zn29Ag4 has the lowest corrosion rate of 0.19 mm/yr, which could meet the clinical application requirement well. The in vitro cell experiments show that the Madin-Darby canine kidney (MDCK) cells cultured in sample Mg67Zn29Ag4 and its extraction medium have higher activity. However, the Mg-Zn-Ag metallic glasses exhibit obvious inhibitory effect on human rhabdomyosarcoma (RD) tumor cells. The present investigations on the glass-forming ability, corrosion behavior, cytocompatibility and tumor inhibition function of the Mg-Zn-Ag based metallic glass could reveal their biomedical application possibility.

Photothermal therapy (PTT) of nanomaterials is an emerging novel therapeutic strategy for breast cancer. However, there exists an urgent need for appropriate strategies to enhance the antitumor efficacy of PTT and minimize damage to surrounding normal tissues. Piezo1 might be a promising novel photothermal therapeutic target for breast cancer. This study aims to explore the potential role of Piezo1 activation in the hyperthermia therapy of breast cancer cells and investigate the underlying mechanisms. Results showed that the specific agonist of Piezo1 ion channel (Yoda1) aggravated the cell death of breast cancer cells triggered by heat stress in vitro. Reactive oxygen species (ROS) production was significantly increased following heat stress, and Yoda1 exacerbated the rise in ROS release. GSK2795039, an inhibitor of NADPH oxidase 2 (NOX2), reversed the Yoda1-mediated aggravation of cellular injury and ROS generation after heat stress. The in vivo experiments demonstrate the well photothermal conversion efficiency of TiCN under the 1,064 nm laser irradiation, and Yoda1 increases the sensitivity of breast tumors to PTT in the presence of TiCN. Our study reveals that Piezo1 activation might serve as a photothermal sensitizer for PTT, which may develop as a promising therapeutic strategy for breast cancer.

Citrus peel essential oils (CPEOs) have demonstrated substantial medicinal potential for glioblastoma treatment because of their extensive antitumor effects, low potential for drug resistance, and ability to cross the human blood–brain barrier. In this study, the chemical compositions of five CPEOs were analyzed via gas chromatography–mass spectrometry (GC-MS). CCK8 assays were used to evaluate the ability of five CPEOs to inhibit U251 human glioblastoma cells, and XLB and RA were selected for further investigation. Through wound healing assays and cell cycle and apoptosis analyses via flow cytometry, it was revealed that these CPEOs inhibited cell migration, arrested the cell cycle at G1/G0, and induced apoptosis with similar levels of inhibition. After CPEOs treatment, the intracellular Ca2+ content and reactive oxygen species levels in U251 cells increased significantly, whereas the mitochondrial membrane potential decreased. Additionally, the antioxidant enzyme system (SOD, POD, CAT, and GR) and the nonenzymatic defense system (GSH) were inhibited, leading to an increase in lipid peroxidation. qRT–PCR indicated the significant upregulation of intracellular calcium ion signaling pathways and the upregulation of mitochondrial apoptosis-related genes. Additionally, the activation of calcicoptosis-related indicators induced by the CPEOs could be reversed by inhibitor treatment, confirming that both of the selected CPEOs inhibit tumors by activating calcicoptosis-related pathways. These findings highlight the immense potential of CPEOs in healthcare and pharmaceutical applications by not only providing a scientific basis for the potential application of CPEOs in the treatment of glioblastoma but also offering new insights for the development of novel antitumor drugs.

Citrus peel essential oil (CPEO) is favored by people for its aromatic scent, while also possessing numerous bioactive compounds that are advantageous to human health. This study evaluated the antioxidant, anti-inflammatory, and anticancer activities of CPEOs through cell experiments. The results showed that CPEOs could increase the activity of the antioxidant enzyme system and nonenzymatic defence system in H2O2-treated RAW 264.7 cells by reducing cellular lipid peroxidation. CPEOs also reduced the nitric oxide production induced by lipopolysaccharide treatment in RAW 264.7 cells while decreasing proinflammatory cytokines expression and increasing anti-inflammatory cytokine expression. Wound healing assays, flow cytometry, and quantitative real-time fluorescent quantitative PCR (qRT-PCR) revealed that CPEOs could induce apoptosis in U87 cells through the mitochondrial apoptotic pathway. These findings indicate that CPEOs possess excellent antioxidant, anti-inflammatory, and anticancer activity potential, making them suitable for use in functional antioxidant and anti-inflammatory foods and nutritional health products.

Constrained many-objective optimization problems (CMaOPs) have gradually emerged in various areas and are significant for this field. These problems often involve intricate Pareto frontiers (PFs) that are both refined and uneven, thereby making their resolution difficult and challenging. Traditional algorithms tend to over prioritize convergence, leading to premature convergence of the decision variables, which greatly reduces the possibility of finding the constrained Pareto frontiers (CPFs). This results in poor overall performance. To tackle this challenge, our solution involves a novel dual-population constrained many-objective evolutionary algorithm based on reference point and angle easing strategy (dCMaOEA-RAE). It relies on a relaxed selection strategy utilizing reference points and angles to facilitate cooperation between dual populations by retaining solutions that may currently perform poorly but contribute positively to the overall optimization process. We are able to guide the population to move to the optimal feasible solution region in a timely manner in order to obtain a series of superior solutions can be obtained. Our proposed algorithm’s competitiveness across all three evaluation indicators was demonstrated through experimental results conducted on 77 test problems. Comparisons with ten other cutting-edge algorithms further validated its efficacy.

Abstract Background Psoriasis refers to a highly prevalent and immunologically mediated dermatosis with considerable deterioration in life quality. Wogonin, a sort of flavonoid, has been mentioned to elicit protective activities in skin diseases. However, whether Wogonin is implicated in the treatment of psoriasis and its specific mechanisms are not fully understood. Aim The present work attempted to elaborate the role of Wogonin during the process of psoriasis and to concentrate on the associated action mechanism. Methods Cell counting kit‐8 (CCK‐8) method was initially applied to assay the viability of human keratinocyte HaCaT cells treated by varying concentrations of Wogonin. To mimic psoriasis in vitro, HaCaT cells were exposed to M5 cytokines. CCK‐8 and 5‐Ethynyl‐2′‐deoxyuridine assays were adopted for the measurement of cell proliferation. Inflammatory levels were examined with enzyme‐linked immunosorbent assay. Immunofluorescence staining tested nucleotide‐binding oligomerization domain (NOD)‐like receptor family pyrin domain containing 3 (NLRP3) and Caspase‐1 expressions. Western blot examined the protein expressions of proliferation‐, inflammation‐, pyroptosis‐associated factors, and NLRP3. Results Wogonin treatment antagonized the proliferation, inflammatory response, and NLRP3/caspase‐1/Gasdermin‐D (GSDMD)‐mediated pyroptosis in M5‐challenged HaCaT cells. Besides, NLRP3 elevation partially abrogated the effects of Wogonin on M5‐induced proliferation, inflammatory response, and NLRP3/caspase‐1/GSDMD‐mediated pyroptosis in HaCaT cells. Conclusion In a word, Wogonin might exert anti‐proliferation, anti‐inflammatory and anti‐pyroptosis activities in M5‐induced cell model of psoriasis and the blockade of NLRP3/Caspase‐1/GSDMD pathway might be recognized as a potential mechanism underlying the protective mechanism of Wogonin in psoriasis, suggesting Wogonin as a prospective anti‐psoriasis drug.

The extraction of large dam candidate regions is critical for broad-scale efforts to rapidly detect large-area dams. The framework proposed in this paper attempts to combine random forest classification models and spatial analysis methods with large dam candidate area extraction methods for large-scale areas. First, we studied the combination of optical, microwave, texture, and topographic features of the dam and constructed a multisource remote sensing and topographic feature vector of the dam. Secondly, we constructed random forest classifiers in different study areas and evaluate their performance. Then we explored the geographic characteristics of the dams and their relationships with other features. Finally, we introduced the spatial analysis method to constrain the large dam candidate area. The proposed framework was tested in a total area of 968,533 km2 in five countries and achieved promising results, which constrained the candidate area to less than 1.06% of the total area. We calculated the completeness rate of large dams using the multi-source dam datasets. The framework achieved a completeness rate of more than 97.62%. Our results show that the entire framework is reliable for automated and fast large dam candidate area acquisition based on data from open remote sensing products.

Abstract Maize kernels are complex biological systems composed of three genetic sources, namely maternal tissues, progeny embryos, and progeny endosperms. The lack of gene expression profiles with spatial information has limited the understanding of the specific functions of each cell population, and hindered the exploration of superior genes in kernels. In our study, we conduct microscopic sectioning and spatial transcriptomics analysis during the grain filling stage of maize kernels. This enables us to visualize the expression patterns of all genes through electronical RNA in situ hybridization, and identify 11 cell populations and 332 molecular marker genes. Furthermore, we systematically elucidate the spatial storage mechanisms of the three major substances in maize kernels: starch, protein, and oil. These findings provide valuable insights into the functional genes that control agronomic traits in maize kernels.

With the development of new high-thrust rockets, the decreasing frequency of the bending modes of the rocket, as well as the factors such as flow separation and shock oscillations generated during transonic flight make it more prone to non-constant vibration. In this paper, a launch vehicle model with boost was taken as the research object, and the aerodynamic damping of the rocket during forced vibration was obtained through numerical calculation. The factors affecting the aerodynamic damping of the rocket were analyzed, including the position of structural nodes, the magnitude of vibration amplitude, pulsating pressure and so on. The study shows that the boost mainly plays the role of increasing aerodynamic damping and the front node mainly affects the aerodynamic damping of the contraction section. The vibration amplitude size and the pulsating pressure have a negligible effect on the aerodynamic damping.

Abstract Background Fractures are rare events and can occur because of a fall. Fracture counts are distinct from other count data in that these data are positively skewed, inflated by excess zero counts, and events can recur over time. Analytical methods used to assess fracture data and account for these characteristics are limited in the literature. Methods Commonly used models for count data include Poisson regression, negative binomial regression, hurdle regression, and zero-inflated regression models. In this paper, we compare four alternative statistical models to fit fracture counts using data from a large UK based clinical trial evaluating the clinical and cost-effectiveness of alternative falls prevention interventions in older people (Prevention of Falls Injury Trial; PreFIT). Results The values of Akaike information criterion and Bayesian information criterion, the goodness-of-fit statistics, were the lowest for negative binomial model. The likelihood ratio test of no dispersion in the data showed strong evidence of dispersion (chi-square = 225.68, p-value

Abstract On February 6, 2023, an Mw7.8 earthquake hit the East Anatolian Fault (EAF) and Narlı Fault (NF), followed by an Mw7.5 event on the Sürgü Fault. We combine multiple seismic datasets, global navigation satellite system recordings, and radar satellite images with finite fault inversion and slowness enhanced back-projection to study the rupture kinematics. Our analysis reveals that the rupture originated on the NF, propagating 120 km northeast at 3.05 km/s and 200 km southwest at 3.11 km/s after reaching the EAF junction, exhibiting overall subshear speeds. Further Mach wave analysis confirms the subshear rupture, matching the prediction using close-Rayleigh speeds. The unexpectedly-large slip on some EAF segments suggests a supercycle lasting ≥900 years. The EAF geometry is similar to the San Andreas-San Jacinto Fault system, while the latter has higher slip rates but without large earthquakes on its southern segments since 1857, carrying the potential of an M8 earthquake.

Four days after the 12 May 2008 M 7.9 Wenchuan earthquake struck the Sichuan region of China, we submitted a prospective earthquake forecast based on transfer of stress from the mainshock onto significant faults crossing through populated areas. We identified where the largest aftershocks were likely to occur that could cause loss of life. We returned the revised article to the journal on 5 June 2008, marking the last day of our observation period. The primary testable features are locations and focal mechanisms of larger (M ≥ 4.5) earthquakes; did these events happen on or very near the faults we said they would? Did they have the same strikes, dips, and rakes as the faults we modeled? In retrospect, is the stress transfer method consistent with all M ≥ 4.5 earthquakes that occurred? We find all but one M ≥ 4.5 aftershock with known focal mechanisms located on stress‐increased faults, and their focal mechanism parameters overlap with geological characteristics we used in making calculations. Six of the seven lethal M > 4.5 earthquakes that occurred in the region since 5 June 2008 were located on stress‐increased faults, with the lone exception triggered by hydraulic fracturing.

Background: Age is the most important risk factor for cancer, but aging rates are heterogeneous across individuals. We explored a new measure of aging-Phenotypic Age (PhenoAge)-in the risk prediction of site-specific and overall cancer. Methods: Using Cox regression models, we examined the association of Phenotypic Age Acceleration (PhenoAgeAccel) with cancer incidence by genetic risk group among 374,463 participants from the UK Biobank. We generated PhenoAge using chronological age and nine biomarkers, PhenoAgeAccel after subtracting the effect of chronological age by regression residual, and an incidence-weighted overall cancer polygenic risk score (CPRS) based on 20 cancer site-specific polygenic risk scores (PRSs). Results: Compared with biologically younger participants, those older had a significantly higher risk of overall cancer, with hazard ratios (HRs) of 1.22 (95% confidence interval, 1.18–1.27) in men, and 1.26 (1.22–1.31) in women, respectively. A joint effect of genetic risk and PhenoAgeAccel was observed on overall cancer risk, with HRs of 2.29 (2.10–2.51) for men and 1.94 (1.78–2.11) for women with high genetic risk and older PhenoAge compared with those with low genetic risk and younger PhenoAge. PhenoAgeAccel was negatively associated with the number of healthy lifestyle factors (Beta = –1.01 in men, p

Aims: The PARAMEDIC-3 trial evaluates the clinical and cost-effectiveness of an intraosseous first strategy, compared with an intravenous first strategy, for drug administration in adults who have sustained an out-of-hospital cardiac arrest. Methods: PARAMEDIC-3 is a pragmatic, allocation concealed, open-label, multi-centre, superiority randomised controlled trial. It will recruit 15,000 patients across English and Welsh ambulance services. Adults who have sustained an out-of-hospital cardiac arrest are individually randomised to an intraosseous access first strategy or intravenous access first strategy in a 1:1 ratio through an opaque, sealed envelope system. The randomised allocation determines the route used for the first two attempts at vascular access. Participants are initially enrolled under a deferred consent model.The primary clinical-effectiveness outcome is survival at 30-days. Secondary outcomes include return of spontaneous circulation, neurological functional outcome, and health-related quality of life. Participants are followed-up to six-months following cardiac arrest. The primary health economic outcome is incremental cost per quality-adjusted life year gained. Conclusion: The PARAMEDIC-3 trial will provide key information on the clinical and cost-effectiveness of drug route in out-of-hospital cardiac arrest.Trial registration: ISRCTN14223494, registered 16/08/2021, prospectively registered.

Space nuclear reactors are becoming popular in deep space exploration owing to their advantages of high-power density and stability. Following the fourth-generation nuclear reactor technology, a conceptual design of the dual drum-controlled space molten salt reactor (D2-SMSR) is proposed. The reactor concept uses molten salt as fuel and heat pipes for cooling. A new reactivity control strategy that combines control drums and safety drums was adopted. Critical physical characteristics such as neutron energy spectrum, neutron flux distribution, power distribution and burnup depth were calculated. Flow and heat transfer characteristics such as natural convection, velocity and temperature distribution of the D2-SMSR under low gravity conditions were analyzed. The reactivity control effect of the dual-drums strategy was evaluated. Results showed that the D2-SMSR with a fast spectrum could operate for 10 years at the full power of 40 kWth. The D2-SMSR has a high heat transfer coefficient between molten salt and heat pipe, which means that the core has a good heat-exchange performance. The new reactivity control strategy can achieve shutdown with one safety drum or three control drums, ensuring high-security standards. The present study can provide a theoretical reference for the design of space nuclear reactors.

Abstract Water and its dissociated species at the solid‒liquid interface play critical roles in catalytic science; e.g., functions of oxygen species from water dissociation are gradually being recognized. Herein, the relationship between oxide identity (PtOHads, PtOads, and PtO2) and electrocatalytic activity of platinum for ethanol electrooxidation was obtained in perchlorate acidic solution over a wide potential range with an upper potential of 1.5 V (reversible hydrogen electrode, RHE). PtOHads and α-PtO2, rather than PtOads, act as catalytic centers promoting ethanol electrooxidation. This relationship was corroborated on Pt(111), Pt(110), and Pt(100) electrodes, respectively. A reaction mechanism of ethanol electrooxidation was developed with DFT calculations, in which platinum oxides-mediated dehydrogenation and hydrated reaction intermediate, geminal diol, can perfectly explain experimental results, including pH dependence of product selectivity and more active α-PtO2 than PtOHads. This work can be generalized to the oxidation of other substances on other metal/alloy electrodes in energy conversion and electrochemical syntheses.

This paper address the performance optimization of the battery heat sink module by analyzing the lattice structure of the battery heat sink module through in-depth modeling and simulation, and combining the laser powder bed fusion (LPBF)-forming technology with mechanical and corrosion resistance experiments for a comprehensive study. It is found that the introduction of the lattice skeleton significantly improves the thermal conductivity of the phase change material (PCM), realizing the efficient distribution and fast transfer of heat in the system. At the same time, the lattice skeleton makes the heat distribution in the heat exchanger more uniform, improves the utilization rate of the PCM, and helps to maintain the stability of the cell temperature. In addition, the melting of PCM in the lattice heat exchanger is more uniform, thus maximizing its latent heat capacity. In summary, by optimizing the lattice structure and introducing the lattice skeleton, this study successfully improves the performance of the battery heat dissipation system, which provides a strong guarantee for the high efficiency and stable operation of the battery, and provides new ideas and references for the development of the battery heat dissipation technology.

To explore the size, morphology, and distribution patterns of internal pore defects in WE43 magnesium alloy formed by laser powder bed fusion (LPBF), as well as their impact on its mechanical properties, computer tomography (CT), metallographic microscopy, and scanning electron microscopy were used to observe the material’s microstructure and the morphology of tensile test fractures. The study revealed that a large number of randomly distributed non-circular pore defects exist internally in the LPBF-formed WE43 magnesium alloy, with a defect volume fraction of 0.16%. Approximately 80% of the defects had equivalent diameters concentrated in the range of 10∼40 μm, and 56.2% of the defects had sphericity values between 0.65∼0.7 μm, with the maximum defect equivalent diameter being 122 μm. There were a few spherical pores around 20 μm in diameter in the specimens, and unfused powder particles were found in pore defects near the edges of the parts. Under the test conditions, the fusion pool structure of LPBF-formed WE43 magnesium alloy resembled a semi-elliptical shape with a height of around 66 μm, capable of fusion three layers of powder material in a single pass. Columnar grains formed at the edge of individual fusion pools, while the central area exhibited equiaxed grains. The “scale-like pattern” formed by overlapping fusion pool structures resulted in the microstructure of LPBF-formed WE43 magnesium alloy mainly consisting of fine equiaxed grains with a size of 2.5 μm and columnar grains distributed in a band-like manner.

At present, no consensus has been reached on the generation mechanism of anisotropy in materials fabricated by laser powder bed fusion (LPBF), and most attention has been focused on crystallographic texture. In this paper, an analysis and test were carried out on the hardness, defect distribution, residual stress distribution, and microstructure of WE43 magnesium alloy fabricated by LPBF. The results indicate that LPBF WE43 exhibits obvious anisotropy—the hardness HV of X–Z surface (129.9 HV on average) and that of Y–Z surface (130.7 HV on average) are about 33.5% higher than that of X–Y surface (97.6 HV on average), and the endurable load is smaller in the stacking direction Z compared to the X and Y directions. The factors contributing more to the anisotropy are listed as follows in sequence. Firstly, the defect area of the X–Y projection surface is about 13.2% larger than that of the other two surfaces, so this surface shows greatly reduced mechanical properties due to the exponential relationship between the material strength and the number of defects. Secondly, for laser scanning in each layer/time, the residual stress accumulation in the Z direction is higher than that in the X and Y directions, which may directly reduce the mechanical properties of the material. Finally, more fine grains are distributed in X–Z and Y–Z surfaces when comparing them with those in an X–Y surface, and this fine-grain strengthening mechanism also contributes to the anisotropy. After T5 aging heat treatment (250 °C/16 h), a stronger crystallographic texture is formed in the direction, with the orientation density index increasing from 10.92 to 21.38, and the anisotropy disappearing. This is mainly caused by the enhancement effect of the texture in the direction on the mechanical properties in the Z direction cancelling out the weakening effect of the defects in the X–Y surface in the Z direction.

ABSTRACT: Inosine monophosphate (IMP) plays a significant role in meat taste, yet the molecular mechanisms controlling IMP deposition in muscle tissues still require elucidation. The present study systematically and comprehensively explores the molecular network governing IMP deposition in different regions of Jingyuan chicken muscle. Two muscle groups, the breast and leg, were examined as test materials. Using nontargeted metabolomic sequencing, we screened and identified 20 metabolites that regulate IMP-specific deposition. We maintained regular author and institution formatting, used clear, objective, and value-neutral language, and avoided biased or emotional language. We followed a consistent footnote style and formatting features and used precise word choice with technical terms where appropriate. Out of these, 5 were identified as significant contributors to the regulation of IMP deposition. We explained technical term abbreviations when first used and ensured a logical flow of information with causal connections between statements. The results indicate that PGM1, a key enzyme involved in synthesis, is higher in the breast muscle compared to the leg muscle, which may provide an explanation for the increased deposition of IMP in the breast muscle. We aimed for a clear structure with logical progression, avoided filler words, and ensured grammatical correctness. The activity of key enzymes (PKM2, AK1, AMPD1) involved in this process was higher in the breast muscle than in the leg muscle. In the case of IMP degradation metabolism, the activity of its participating enzyme (PurH) was lower in the breast muscle than in the leg muscle. These findings suggest that the increased deposition of IMP in Jingyuan chickens' breast muscle may result from elevated metabolism and reduced catabolism of key metabolites. In summary, a metaomic strategy was utilized to assess the molecular network regulation mechanism of IMP-specific deposition in various segments of Jingyuan chicken. These findings provide insight into genetic improvement and molecular breeding of meat quality traits for top-notch broilers.

Objective: Kudzu root, fern root, lily, and yam bean are characteristic plant resources in Wuling Mountain Area, the gelatinization and instant properties of these four starches was analyzed in this study. Methods: SEM, RVA, and DSC were used to investigate the gelatinization properties of the starches, and the transparency and apparent fluidity of starch pastes was used to analysis the instant properties. Results: The granule of kudzu root, fern root, and yam bean starches showed similar morphology, most of which are spherical, but lily starch exhibited spindle-shaped morphology. The RVA results showed that the peak viscosity of lily starch was the highest [(7.00±0.03) Pa·s] among these four starches. The setback value of kudzu root starch and lily starch was more than fern root starch and yam bean starch, which indicating that kudzu root starch and lily starch was easy to retrograde. The DSC results showed that the initial gelatinization temperature of fern root starch was 59.4 ℃, which was the lowest among these starches, indicating that it was easy to gelatinize. Lily starch has the highest gelatinization enthalpy, which is 15.64 J/g, indicating that more heat was required for gelatinization. After gelatinization, the kudzu root starch paste has the best transparency with a light transmittance of 29.11%, while lily starch paste has a light transmittance of only 12.25%. Kudzu root starch paste and lily starch paste was easy to form gels, but the fluidity was poor. Conclusion: Lily starch and kudzu root starch have similar instant properties and have potential for the development of instant foods, fern root starch and cold potato starch showed a lower retrogradation value, and their paste showed better fluidity, which can be used to inhibit the retrogradation of food.

Abstract Background Postal screening has not previously been validated as a method for identifying fall and fracture risk in community-dwelling populations. We examined prognostic performance of a postal risk screener used in the UK Prevention of Falls Injury Trial (PreFIT; ISRCTN71002650), to predict any fall, recurrent falls, and fractures over 12 months. We tested whether adding variables would improve screener performance. Methods Nine thousand eight hundred and eight community-dwelling participants, aged 70 years and older, and 63 general practices in the UK National Health Service (NHS) were included in a large, pragmatic cluster randomised trial comparing screen and treat fall prevention interventions. The short postal screener was sent to all participants in the trial intervention arms as an A4 sheet to be completed and returned to the GP (n = 6,580). The postal screener items were embedded in the baseline pre-randomisation postal questionnaire for all arms of the trial (n = 9,808). We assessed discrimination and calibration using area under the curve (AUC). We identified additional predictors using data from the control arm and applied these coefficients to internal validation models in the intervention arm participants. We used logistic regression to identify additional predictor variables. Findings A total of 10,743 falls and 307 fractures were reported over 12 months. Over one third of participants 3,349/8,136 (41%) fell at least once over 12 month follow up. Response to the postal screener was high (5,779/6,580; 88%). Prediction models showed similar discriminatory ability in both control and intervention arms, with discrimination values for any fall AUC 0.67 (95% CI 0.65 to 0.68), and recurrent falls (AUC 0.71; 95% CI 0.69, 0.72) but poorer discrimination for fractures (AUC 0.60; 95% CI 0.56, 0.64). Additional predictor variables improved prediction of falls but had modest effect on fracture, where AUC rose to 0.71 (95% CI 0.67 to 0.74). Calibration slopes were very close to 1. Conclusion A short fall risk postal screener was acceptable for use in primary care but fall prediction was limited, although consistent with other tools. Fracture and fall prediction were only partially reliant on fall risk although were improved with the additional variables.

Improving light extraction efficiency (LEE) of AlGaN-based deep-ultraviolet (DUV) light emitting diodes (LEDs) has been attempted by thinning the p-AlGaN/p-GaN layer and adopting Ni/Au/Al composite electrodes. It is found that the thin p-AlGaN/p-GaN layer can reduce the light absorption and the Ni/Au/Al electrodes achieve high reflectivity and Ohmic contact to ensure the enhancement of the light extraction and maintain fine electrical properties. By this approach, the maximum external quantum efficiency of the DUV-LEDs with optimized Ni/Au/Al reflective electrodes is increased by 40%, compared to that with conventional Ni/Au electrodes over the whole current range.

We present multi-parameter optimization of a shallow ridge InP-based traveling wave Mach-Zehnder modulator (MZM) for ultra-wide modulation bandwidth by velocity and impedance matching and microwave attenuation minimization. Relationship between MZM microwave loss and p-cladding layer doping profile is quantitatively analyzed and incorporated in device optimization. We propose a systematic analysis methodology allowing the full optimization of an InP shallow ridge MZM capable of 200 Gb/s PAM4 operation, compatible with high-volume low-cost manufacturing. Our design is expected to achieve 4.3 V half-wave voltage and 81 GHz 3-dB bandwidth with simplified fabrication process and improved long-term reliability.

Optical phased array (OPA), as a promising beam steering technology, however, usually suffers from a narrow field of view (FOV) that limits its performances in applications. A miniaturized compact strategy to enlarge the beam steering angle is quite desirable for the solid-state OPA technique. Here an on-chip metasurface-doublet is proposed to offer angle magnification integrated with a port-selected optical phased array. It is implemented by combing convex and concave metalenses with the quadratic phase distribution, which is precisely integrated on the OPA chip by layer-by-layer fabrication process. Here, the OPA is fabricated in Lithium Niobate on Insulator (LNOI) platform. Our experiments show that the metasurface-doublet is able to achieve 1.54 times FOV amplification in a horizontal direction and with >41% working efficiency. Our results provide a feasible approach to achieve enlarged FOV for wide-angle beam steering and also imply a powerful platform in developing integrated multilayer metasurface devices.

Although deep neural networks have made significant progress in tasks related to remote sensing image scene classification, most of these tasks assume that the training and test data are independently and identically distributed. However, when remote sensing scene classification models are deployed in the real world, the model will inevitably encounter situations where the distribution of the test set differs from that of the training set, leading to unpredictable errors during the inference and testing phase. For instance, in the context of large-scale remote sensing scene classification applications, it is difficult to obtain all the feature classes in the training phase. Consequently, during the inference and testing phases, the model will categorize images of unidentified unknown classes into known classes. Therefore, the deployment of out-of-distribution (OOD) detection within the realm of remote sensing scene classification is crucial for ensuring the reliability and safety of model application in real-world scenarios. Despite significant advancements in OOD detection methods in recent years, there remains a lack of a unified benchmark for evaluating various OOD methods specifically in remote sensing scene classification tasks. We designed different benchmarks on three classical remote sensing datasets to simulate scenes with different distributional shift. Ten different types of OOD detection methods were employed, and their performance was evaluated and compared using quantitative metrics. Numerous experiments were conducted to evaluate the overall performance of these state-of-the-art OOD detection methods under different test benchmarks. The comparative results show that the virtual-logit matching methods without additional training outperform the other types of methods on our benchmarks, suggesting that additional training methods are unnecessary for remote sensing image scene classification applications. Furthermore, we provide insights into OOD detection models and performance enhancement in real world. To the best of our knowledge, this study is the first evaluation and analysis of methods for detecting out-of-distribution data in remote sensing. We hope that this research will serve as a fundamental resource for future studies on out-of-distribution detection in remote sensing.

Abstract Background This article discusses the management of an adolescent woman with a delayed diagnosis of adnexal torsion (AT) whose ovaries were successfully preserved. Case presentation The patient was a 14-year-old female teen admitted with the chief complaint of lower abdominal pain for 3 days and worsening pain for 2 days. Magnetic resonance imaging suggested a high possibility of torsion in the anterosuperior uterine mass and was accompanied by severe ovarian edema, bleeding, and enlargement. Intraoperatively, the left fallopian tube was characterized by thickening and torsion and appeared blackish purple. The left fallopian tube paraovarian cyst was about 20 cm in size, and the left adnexa was twisted 1080° along the left infundibulopelvic ligament (suspensory ligament of the left ovary). The left ovary appeared blackish purple, with an enlarged diameter of about 10 cm. At the request and with the informed consent of the patient’s parents, we preserved the left ovary and removed the left fallopian tube. The results of the endocrine, ultrasound, and tumor marker tests were normal 1 month after surgery. Follicles and blood flow signals seen in ultrasound examinations indirectly proved the successful preservation of the left ovary in the follow-up. Conclusions Our attempt to preserve the ovaries in an adolescent with a delayed diagnosis of AT was successful.

This paper addresses the robust enhancement problem in the control of robot manipulators. A new hierarchical multiloop model predictive control (MPC) scheme is proposed by combining an inverse dynamics-based feedback linearization and a nonlinear disturbance observer (NDO) based uncertainty compensation. By employing inverse dynamics-based feedback linearization, the multi-link robot manipulator was decoupled to reduce the computational burden compared with the traditional MPC method. Moreover, an NDO was introduced into the input torque signal to compensate and correct the errors from external disturbances and uncertainties, aiming to enhance the robustness of the proposed controller. The feasibility of the proposed hierarchical multiloop MPC scheme was verified and validated via simulation of a 3-DOF robot manipulator. Results demonstrate that the proposed controller provides comparative accuracy and robustness and extends the existing state-of-the-art algorithms for the trajectory tracking problem of robot manipulators with disturbances.

Epidemiological and clinical characteristics of patients with COVID-19 have been reported in the last two years. A few studies reported clinical course of illness of median 22 days, including viral shedding of median 20 days, but there are several cases with a longer time of viral shedding. In this study, we included four cases with a longer illness course of more than 40 days who had been discharged or still in hospital by March 15, 2020. Demographic, clinical treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records. We described the epidemiological and clinical characteristics and the course of viral shedding. Two patients had comorbidity, one with hypertension and the other with diabetes. We found smoking was not an independent risk factor. D-dimer maybe related to the severity of illness but not to the course of the illness. Nucleic acid detection suggested that maybe more sampling sites represented more virus replication sites and longer course of illness. In this study we found some non-critical severe relatively young patients whose character was different from former studies described to provide a basis for reference to assess the risk of transmission and the isolation duration of patients.

ObjectiveTo construct a YOLOv3-based model for diatom identification in scanning electron microscope images, explore the application performance in practical cases and discuss the advantages of this model.MethodsA total of 25 000 scanning electron microscopy images were collected at 1 500× as an initial image set, and input into the YOLOv3 network to train the identification model after experts’ annotation and image processing. Diatom scanning electron microscopy images of lung, liver and kidney tissues taken from 8 drowning cases were identified by this model under the threshold of 0.4, 0.6 and 0.8 respectively, and were also identified by experts manually. The application performance of this model was evaluated through the recognition speed, recall rate and precision rate.ResultsThe mean average precision of the model in the validation set and test set was 94.8% and 94.3%, respectively, and the average recall rate was 81.2% and 81.5%, respectively. The recognition speed of the model is more than 9 times faster than that of manual recognition. Under the threshold of 0.4, the mean recall rate and precision rate of diatoms in lung tissues were 89.6% and 87.8%, respectively. The overall recall rate in liver and kidney tissues was 100% and the precision rate was less than 5%. As the threshold increased, the recall rate in all tissues decreased and the precision rate increased. The F1 score of the model in lung tissues decreased with the increase of threshold, while the F1 score in liver and kidney tissues with the increase of threshold.ConclusionThe YOLOv3-based diatom electron microscope images automatic identification model works at a rapid speed and shows high recall rates in all tissues and high precision rates in lung tissues under an appropriate threshold. The identification model greatly reduces the workload of manual recognition, and has a good application prospect.

Renal cell carcinoma (RCC) is the most common type of kidney cancer. Owing to the high morbidity rate of RCC, there is an urgent need for intensive research on robust materials to diagnose and treat RCC. Nanomaterials have been developed largely in the last three decades because of their numerous advantages, such as high specific surface area, simple surface functionalization, rapid onset of therapeutic action, superior biological activity, and other unique physical–chemical characteristics. Herein, first, various types of nanomaterials used in RCC treatment are introduced, including inorganic nanomaterials, lipid nanomaterials, synthetic polymer nanomaterials, and natural nanomaterials. Second, the different diagnosis and therapeutic mechanisms of nanomaterials in the kidneys are reviewed and these advantages of nanomaterials are highlighted. Furthermore, nanomaterials are investigated for the preclinical and clinical detection and treatment of RCC. Finally, the challenges and outlook of various nanomaterials for RCC diagnostic and treatment are discussed.

Runway heading is a crucial runway attribute that closely affects aircraft' takeoff and landing safely while having a large number of missing in existing runway thematic databases, limiting the evaluation and analysis globally. This article proposes an automated runway heading extraction method, considering various runway surface materials and spatial structure differences encountered in wide-area detection, promoting a quick and reliable broad investigation. First, multiscale detection is performed based on the mask regional convolutional neural network runway detection model to locate airport runways, using the mask nonmaximum suppression mechanism algorithm to distinguish runways with highly overlapping candidate results. Second, abnormality judgment and mask selection according to semantic constraints were applied to the identified runway area to reserve high-confidence masks to accurately extract the runway heading. We tested our framework results on 1483 runways in the United States with complex runway materials and structures combination. The runway detection recall was 99.12%, and 98.9% of the runway heading errors were limited to 2°, showing that the overall frame for extracting the true runway heading is reliable. In addition, we complement the true headings of 892 runways in OurAirports, promoting research on the completion, verification, and updating of runway semantics in related databases.

As an important transportation facility, airports substantially affect the economic lives of people. However, the full extraction of airports located in a vast area is concerning. The size of an airport in a previous wide area detection framework is relatively large and has a strong saliency in remote sensing images, whereas the contradiction between a complex geographical background and a small airport size has yet to be resolved. In this study, we propose a set of automatic detection frameworks to realize efficient detection for various airports in nine Indian states/union territories under the condition that only runway samples are labeled. Preliminary extraction of runway features is performed with a high F1 and recall rate, and teacher nodes judge and guide the results. Next, the output is connected to classification and segmentation for outlier elimination and pixel extraction to locate the runways. For the study area, the proposed framework airport retention rate (RR) is 92.7%, with the false alarm reduction rate (FARR) reduced by a maximum of 95.3%. A total of 192 airports are discovered, and the effective airport growth rate (GR) is 47.4%. Compared to previous work, RR, GR, FARR, and run efficiency increased by 2.2%, 16.0%, 4.5%, and 432.5%, respectively, with more small- and medium-sized airports detected. Furthermore, the framework is tested in Japan, and 155 airports are detected. Thus, the proposed framework effectively improves detection capability for small- and medium-sized airports in large-scale areas and updates the airport database.

Dams are important water conservation hubs; however, dam locations provided by open datasets are often unreliable. The aim of this article is to provide a single, geographic location-reliable dataset of dams for the scientific community by fusing existing dam datasets and verifying these locations. Using Southeast Asia as the case study, we propose an efficient and automatic method to verify dam locations and developed a process framework. First, the possible location of a dam was obtained by analyzing its geographic location characteristics. Then, the deep learning method was used to detect dams. Finally, a variety of geographic knowledge was applied to comprehensively verify the detection results to obtain accurate and reliable dam location information. The fused dam dataset we produced includes the locations of 4493 dams in Southeast Asia, which were verified using the proposed framework. The verification results were then evaluated via manual visual inspection. The verification accuracy of the framework was 86.7%. The experimental results show that the proposed framework can quickly and reliably verify dam spatial locations and provide solutions for the spatial location verification of other remote sensing objects.

In order to solve the traditional A* algorithm is not taken into account when planning path obstacle distribution on the influence of the path selection,this paper puts forward an improved A* algorithm,the artificial potential field of thought and the traditional A* algorithm,the combination of the obstacles in grid map gives repulsive force function and the repulsive force around the grid size calculation,in order to improve the searching ability of A* algorithm,the repulsive force of the grid is introduced into the evaluation function of A* algorithm.The results of MATLAB simulation and Turtlebot experiments show that,compared with the traditional A* algorithm,the new improved algorithm combined with artificial potential field algorithm can plan a better path,improve the efficiency of path planning,and increase the search speed by 13.40%~29.68%.The path length is shortened by 10.56%~24.38%,and the number of path nodes is reduced by 6.89%~27.27%.The experimental results show that the improved A* algorithm has obvious optimization effect and is effective and feasible.

BackgroundWe aimed to compare the detection rates of prostate cancer (PCa) and clinically significant prostate cancer(csPCa) by biparametric (bp-) and multiparameter magnetic resonance imaging (mpMRI).Materials and MethodsA total of 699 patients who underwent transperineal prostate biopsy in the Department of Urology, the Second Affiliated Hospital of Nantong University from January 2018 to December 2021 were retrospectively reviewed. Multivariate analysis was used to explore the influencing factors associated with the detection rates of PCa and csPCa. According to MRI examination before biopsy, the patients were divided into bpMRI group and mpMRI group. The detection rates of PCa and csPCa by bpMRI and mpMRI were compared. Furthermore, stratified analysis was performed for patients in these two groups to compare the detection rates of PCa and csPCa at different tPSA intervals, different prostate volume (PV) intervals and different PI-RADS V2 scores.ResultsA total of 571 patients were finally analyzed in this study after exclusion, and the overall detection rate of PCa was 54.5%. Multivariate analysis showed that patient age, tPSA level, prostate volume and PI-RADS V2 score were independent risk factors affecting the detection rates of PCa and csPCa. The detection rates of PCa and csPCa by bpMRI and mpMRI were comparable (51.3% vs. 57.9%, 44.0% vs. 48.0%, both P > 0.05), with no statistical significance. In the tPSA 10–20 ng/ml interval, the detection rates of PCa (59.72% vs. 40.35%, P = 0.011) and csPCa (51.39% vs. 28.82%, P = 0.005) by mpMRI were significantly higher than those by bpMRI, while in other tPSA interval (tPSA 60 ml) and different PI-RADS V2 scores (3, 4, and 5), the detection rates of PCa and csPCa were comparable between the two groups.ConclusionFor detecting PCa and csPCa, bpMRI and mpMRI had similar diagnostic efficacies, whereas mpMRI detected more PCa and csPCa in the tPSA interval of 10–20 ng/ml.