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ObjectiveTo develop a semi-automatic model integrating radiomics, deep learning, and clinical features for Bone Metastasis (BM) prediction in prostate cancer (PCa) patients using Biparametric MRI (bpMRI) images.MethodsA retrospective study included 414 PCa patients (BM, n=136; NO-BM, n=278) from two institutions (Center 1, n=318; Center 2, n=96) between January 2016 and December 2022. MRI scans were confirmed with BM status via PET-CT or ECT pre-treatment. Tumor areas on bpMRI images were delineated as tumor’s region of interest (ROI) using auto-delineation tumor models, evaluated with Dice similarity coefficient (DSC). Samples were auto-sketched, refined, and used to train the ResNet BM prediction model. Clinical, radiomics, and deep learning data were synthesized into the ResNet-C model, evaluated using receiver operating characteristic (ROC).ResultsThe auto-segmentation model achieved a DSC of 0.607. Clinical BM prediction’s internal validation had an accuracy (ACC) of 0.650 and area under the curve (AUC) of 0.713; external cohort had an ACC of 0.668 and AUC of 0.757. The deep learning model yielded an ACC of 0.875 and AUC of 0.907 for the internal, and ACC of 0.833 and AUC of 0.862 for the external cohort. The Radiomics model registered an ACC of 0.819 and AUC of 0.852 internally, and ACC of 0.885 and AUC of 0.903 externally. ResNet-C demonstrated the highest ACC of 0.902 and AUC of 0.934 for the internal, and ACC of 0.885 and AUC of 0.903 for the external cohort.ConclusionThe ResNet-C model, utilizing bpMRI scanning strategy, accurately assesses bone metastasis (BM) status in newly diagnosed prostate cancer (PCa) patients, facilitating precise treatment planning and improving patient prognoses.

In order to improve the detection level of transmission error of worm gear pairs, an instrument suitable for measuring transmission error of middle and large worm gear pairs is designed. This research describes the basic framework of the transmission error detection system and the overall design of the instrument. The working principle of the instrument is introduced, and the idea of integrating the time-grating sensor and the related parts of the instrument is put forward. SolidWorks is used to design the key parts and complete the structure layout and virtual assembly. Finite element analysis and structural optimization are carried out on the beam assembly by the Ansys Workbench. After optimization, the first-order natural frequency increases by 23.95%, and the corresponding amplitudes of all natural frequencies decrease significantly.

Tennis sports technology analysis is an evaluation of tennis sports technology from multiple perspectives, such as level and content, and is an important means of movement instruction for students in physical education. The application of intelligent technology for tennis sports technology analysis can reduce the workload of teachers and assist in tennis teaching. In this paper, multiple sensor nodes and the host are used to construct a wearable sensing network and realize the network communication connection. A support vector machine algorithm based on particle swarm optimization is proposed, and parameter optimization is performed on kernel function parameters and penalty factors to ensure the efficiency and accuracy of action recognition. Then a smaller number of action words are utilized to represent the original human motion sequence, and the use of angular features to represent the gestures of human motion is proposed to form a sequence of angular features. Finally, using the key gesture extraction and hierarchical clustering method, action words are extracted, and the generation of action text is realized by replacing each frame of data in the original action sequence with the action word that is closest to it. The accuracy of action recognition of this paper’s algorithm is 7.5% higher than that of the decision tree. The Spearman correlation coefficient between the quantization method of this paper and the traditional quantization method is 0.844, which shows a very strong correlation. Therefore, the overall fit between the performance rankings measured by this paper’s method and those measured by the teachers is high, proving the effectiveness of this paper’s quantization scheme in analyzing tennis sports techniques in physical education.

Focusing on Maotai-flavor liquor fermented grains, this study compared samples with Shuangkunsha Daqu to those with ordinary Daqu. 16S and ITS sequencing, along with enzyme activity detection, were conducted. Results indicated higher microbial community abundance, greater diversity in community distribution, and significantly increased glucoamylase activity in the experimental group. Furthermore, distinct differences were observed in indicators among fermented grains samples from different layers of the cellar. These findings offer a foundational framework for future research into Maotai-flavor liquor and Shuangkunsha Daqu.

To meet the requirements of unique detection of coal mine personnel management system and working state detection for identification card, a card reading substation of flameproof and intrinsically safe is designed based on STM32f103RCT6. The hardware circuits such as power supply, main control unit, display module and power amplifier are designed. Meanwhile, the embedded software of uc/os-III is designed, and the processing efficiency of the microprocessor has been improved by multi-task scheduling. The data can be sent and received through the USART serial ports of the microprocessor. Finally, the identification of identification cards, card number display and voice broadcast are realized.

Chiral metamaterials provide a very convenient way to actively regulate the light field via external means, which is very important in nanophotonics. However, the very weak chiral response of a generally planar metamaterial severely limits its application. Therefore, it is important to design a system with large circular dichroism. Here we report an optical metamaterial with strong chirality in a bilayer gear-shaped plasmonic structure and consider this chiral response of such fields on tunable atom (87Rb) trapping. Simulation results show that maximum chiral response is observed when the two layers of the gear-shaped structures are rotated from each other by an angle of 60° at λ = 760 nm. Also, we demonstrate an active tunable potential for three-dimensional stable atom-trapping with tunable range of position and potential of a neutral atom of ~58 nm and ~1.3N mK (N denotes the input power with unit mW), respectively. In addition, the trap centers are about hundreds of nanometers away from the structure surface, which ensures the stability of the trapping system. The regulation of neutral atom trapping broadens the application of chiral metamaterials and has potential significance in the manipulation of cold atoms.

To improve the data storage and analysis performance of coal mine safety monitoring system, a data compression data model suitable for coal mine safety monitoring system is established by using revolving door algorithm, which is applied to data acquisition and processing of coal mine safety monitoring system. Through data acquisition, compression and statistics, cleaning redundant data, aiming at key points, the data is stored efficiently to ensure the stability of the system, and has been applied and practiced in many coal mining enterprises throughout the country.

Based on a simple introduction of rapid coal loading system, the paper emphatically discussed research status of monitoring technologies of its subsystems including coal storage silo, coal conveying system, weighing system, hydraulic system, vehicle location and identification system. It summarized application status of intelligent control technologies including fuzzy control, neural network control and expert control technology in the rapid coal loading system. Finally, it pointed out some important development tendencies of the monitoring and control technologies for the rapid coal loading system.

OBJECTIVE:To evaluate the reporting quality of clinical practice guidelines (CPGs) in traditional Chinese medicine (TCM). METHODS:A systematic search was undertaken to extract CPGs for TCM. The RIGHT (Reporting Items for practice Guidelines in Healthcare) statement was used to calculate scores for the reporting quality in terms of domains and items, followed by a subgroup analysis of the results and determination of the correlation between the RIGHT and AGREE II (Appraisal of Guidelines for Research and Evaluation II) scores. RESULTS:Overall, 539 TCM CPGs were included. (1) The mean scores (Med, IQR) for each RIGHT domain were as follows: basic information (4, 1), background (3, 2), evidence (0, 0), recommendations (2, 2), review and quality assurance (0, 0), funding and declaration and management of interests (0, 0.5), and other information (0, 0). (2) The items with a low reporting rate ( 90%) included 1a, 1b, 1c, 7b, 13a, and 13b. (3) In recent years, the reporting quality of TCM CPGs has improved, and there was a significant difference among the organizations (P = 0.000), where that of the updated versions was greater than that of the historical versions (P = 0.047). (4) The RIGHT and AGREE II scores were positively correlated (P = 0.014). CONCLUSIONS:At present, although the reporting quality of TCM CPGs is improving, the overall quality remains suboptimal. Guideline developers should strictly follow the evidence-based process of developing guidelines and should follow the RIGHT statement to produce a standardized report when writing guidelines.

As a graphene-like material, molybdenum disulfide has similar properties to graphene, but due to its excellent properties such as adjustable band gap, molybdenum disulfide has a broader application in many aspects (such as gas sensors). With the deepening of research, molybdenum disulfide cannot fully meet the needs of researchers due to defects and other reasons. Therefore, researches on doping and compounding of molybdenum disulfide have gradually attracted attention. At present, most of the research on gas sensitivity has focused on harmful gases (such as nitrogen dioxide, ammonia and carbon monoxide, etc.). There are few studies on the erosive chemical toxic mustard gas. In this paper, vanadium-doped molybdenum disulfide were prepared based on chemical vapor deposition, and the gas-sensitive response of vanadium-doped molybdenum disulfide to mustard gas was studied.

In this study, we present a novel orientation discretization approach based on the rhombic triacontahedron for Monte Carlo simulations of semiflexible polymer chains, aiming at enhancing structural analysis through rheo-small-angle scattering (rheo-SAS). Our approach provides a more accurate representation of the geometric features of semiflexible chains under deformation, surpassing the capabilities of traditional lattice structures. Validation against the Kratky–Porod chain system demonstrated superior consistency, underscoring its potential to significantly improve the precision of uncovering geometric details from rheo-SAS data. This approach opens new avenues for investigating the conformations of semiflexible polymers and mechanically induced phase transitions in more complex polymer structures, offering deeper insights into their behavior under various conditions. [ABSTRACT FROM AUTHOR]

We analyzed a population-representative cohort (N=13,611; Mage at kindergarten, first, and second grade = 67.5, 79.5, and 91.5 months, respectively) to identify kindergarten to second grade factors predictive of being bullies or victims during third to fifth grade. We did so by estimating a block recursive structural equation model (SEM) with three sets of predictors. These were: (a) individual and school socio-demographics; (b) family distress and harsh parenting; and (c) individual behavior and achievement. Relations between each of the included variables and the bullying outcomes were simultaneously estimated within the SEM. Thus, each variable served as a control for estimating the effects of the other variables. We used robust standard errors to account for student clustering within schools. Results indicated that externalizing problem behavior strongly predicted being a bully ([ES] = .56, p

Students with disabilities (SWD) who are Black or Hispanic have been reported to be more likely to be placed primarily outside of general education classrooms while attending U.S. schools. Federal law and regulation require monitoring of special education placement based on race or ethnicity. Yet, whether and to what extent racial or ethnic disparities in placement are explained by bias or by other explanatory factors is currently unclear. We evaluated for racial and ethnic bias in special education placement by analyzing longitudinal data from two independent samples of SWD (N values range 590-1,130) attending U.S. elementary schools. We statistically controlled for plausibly exogenous sociodemographic, academic, and behavioral risk factors measured in kindergarten in analyses of the students as they attended first, third, and fifth grades between the 1999-2000 and 2015-2016 school years. Of the resulting 12 Black or Hispanic grade-year-specific tests, 11 (i.e., 92%) indicated that controls for kindergarten explanatory factors-particularly significant academic difficulties-fully explained the risk initially attributable to race or ethnicity. We observed little evidence that bias explains racial or ethnic disparities in special education placement in U.S. elementary schools.