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BackgroundTransoral endoscopic thyroidectomy vestibular approach (TOETVA) and total endoscopic thyroidectomy via areola approach (ETA) are commonly used endoscopic thyroidectomy approaches. This study compares the effectiveness of these approaches with conventional open thyroidectomy (COT) in terms of safety, associated trauma, and feasibility of central neck dissection in the treatment of papillary thyroid carcinoma (PTC).MethodsThis retrospective study included patients who underwent TOETVA (n = 100), ETA (n = 119), and COT (n = 289). All patients had a pathological diagnosis of PTC and underwent unilateral lobectomy and central neck dissection. We analyzed operative time, postoperative drainage volume, postoperative C-reactive protein (CRP), preoperative and postoperative white blood cell (WBC) count and parathyroid hormone (PTH) levels, parathyroid damage, hoarseness, total number of central lymph nodes, and number of metastatic central lymph nodes.ResultsThe clinical characteristics across the three groups were similar except for patient sex and age. There was a higher proportion of young women in the TOETVA and ETA groups than in the COT group. There were significant differences between the three groups regarding operative time (P = 0.000), postoperative drainage volume (P = 0.000), postoperative CRP (P = 0.000), ∆WBC (P = 0.000), and length of postoperative hospital stay (P = 0.021); in the TOETVA and ETA groups, operative time (P = 0.445), postoperative drainage volume (P = 0.677), and length of postoperative hospital stay (P = 0.145) were not significantly different. The percentage of cases with parathyroid gland damage (P = 0.459) and hoarseness (P > 0.05) was similar in all groups. All three procedures were efficient in performing a central lymph node dissection.ConclusionsAlthough considered more traumatic, TOETVA and ETA are both safe treatment options for PTC. They can both achieve similar therapeutic effects of central neck dissection in the treatment of PTC when compared with open surgery.

The Permanent Magnet Synchronous Motor (PMSM) is the power source maintaining the stable and efficient operation of various pieces of equipment; hence, its reliability is crucial to the safety of public equipment. Convolutional Neural Network (CNN) models face challenges in extracting features from PMSM current data. A new Discrete Wavelet Transform Convolutional Neural Networks (DW-CNN) feature with fusion weight updating Long Short-Term Memory (LSTM) anomaly detection is proposed in this paper. This approach combines Discrete Wavelet Transform (DWT) with high and low-frequency separation processing and LSTM. The anomaly detection method adopts DWT and CNN by separating high and low-frequency processing. Moreover, this method combines the hybrid attention mechanism to extract the multi-current signal features and detects anomalies based on weight updating the LSTM network. Experiments on the motor bearing real fault dataset and the PMSM stator fault dataset prove the method’s strong capability in fusing current features and detecting anomalies.

Glioma is the main brain tumor worldwide and has a worse prognosis. MicroRNAs (miRNAs) are proved to involve in massive malignant tumors including glioma. In this study, we tried to detect the microRNA-939-5p (miR-939-5p) expression pattern and explore its prognostic significance in glioma. We performed the quantitative real-time PCR to examine the relative expression of miR-939-5p in glioma. The Kaplan–Meier method and Cox regression analysis were used to reveal the prognostic importance of miR-939-5p. The influence of miR-939-5p on cell proliferation, migration, and invasion was investigated by the Cell Counting kit-8 (CCK-8), colony formation assay, and Transwell assay. Besides, the target gene of miR-939-5p was provided by luciferase reporter assay. Our data substantiated the expression of miR-939-5p was obviously increased in glioma tissues and cell lines. The upregulation of miR-939-5p predicted a poor survival rate and might act as an alternative prognostic indicator in glioma. The elevated expression of miR-939-5p boosted proliferation, migration, and invasion in glioma cell lines. The alternation of miR-939-5p changed the protein expression of TIMP metallopeptidase inhibitor 2 (TIMP2). These findings indicated the overexpression of miR-939-5p was associated with the poor prognosis of glioma patients. MiR-939-5p may function as an oncogene by targeting TIMP2.

House prices have always been a popular indicator for real estate market monitoring. This study explores the spatiotemporal patterns of house prices at the community level in San Francisco from January 2009 to April 2024. A functional spatiotemporal semiparametric mixed effects (FST-SM) model was proposed to analyze the Zillow Home Value Index (ZHVI), considering spatiotemporal variations. This response is associated with known influences and unknown latent random effects. The random-effects component was expanded using functional principal components. The conditional autoregressive (CAR) structure of the principal component scores was adopted to analyze nonparametric time trends and spatiotemporal correlations. The proposed model was compared with other time-series models in terms of spatiotemporal prediction. The results show that the prediction accuracy of the proposed model is higher than that of other regular models. In summary, a functional mixed effects model was proposed to describe spatiotemporal patterns and forecast house prices. This study can provide valuable references for decision-making by local governments, real estate suppliers, and house buyers.

In this study, Al6061 alloy matrix composites reinforced Al 2 O 3 -decorated reduced graphene oxide (Al 2 O 3 /RGO) with 0.1, 0.3 and 0.5 weight present (wt%) were successfully fabricated using high energy ball milling and hot extrusion techniques. The microstructures of these Al 2 O 3 /RGO/Al6061 aluminum matrix composites (Al MMCs) were characterized. The results showed that Al 2 O 3 /RGO were uniformly distributed within the Al6061 matrix and tightly bonded to the matrix. Al 2 O 3 encapsulation on RGO surface would prevent the formation of Al 4 C 3 brittle phase in matrix, ensuring that there was no reaction between the reinforcement and the matrix Al6061. Tensile strength and Vickers hardness tests demonstrated that the mechanical properties of Al MMCs significantly increased with addition of Al 2 O 3 /RGOs. Remarkably, Al MMCs with 0.1 wt% reinforcement showed tensile yield and tensile strengths of 270 MPa and 286 MPa, respectively, which were 49% and 43% higher than those of pure Al6061 prepared using the same process. Furthermore, the 0.1 wt% Al 2 O 3 /RGO composite also showed the best plastic deformation capability in considering of the strength.

We investigate the rapid formation and evolutionary mechanisms of an extremely severe and persistent haze episode that occurred in northern China during winter 2015 using comprehensive ground and vertical measurements, along with receptor and dispersion model analysis. Our results indicate that the life cycle of a severe winter haze episode typically consists of four stages: (1) rapid formation initiated by sudden changes in meteorological parameters and synchronous increases in most aerosol species, (2) persistent evolution with relatively constant variations in secondary inorganic aerosols and secondary organic aerosols, (3) further evolution associated with fog processing and significantly enhanced sulfate levels and (4) clearing due to dry, cold north-northwesterly winds. Aerosol composition showed substantial changes during the formation and evolution of the haze episode but was generally dominated by regional secondary aerosols (53–67%). Our results demonstrate the important role of regional transport, largely from the southwest but also from the east and of coal combustion emissions for winter haze formation in Beijing. Also, we observed an important downward mixing pathway during the severe haze in 2015 that can lead to rapid increases in certain aerosol species.

Multistage magmatic thermal events occurred in the Yardoi Dome and contain important information on the tectonomagmatic processes. The dome has played a crucial role in understanding the collisional evolution of the Tethyan Himalayan. We present new geochronological and geochemical data for muscovite-granite exposed in the Liemai area, Eastern Tethyan Himalayan Belt. Liemai muscovite-granite is strongly peraluminous, with A/CNK values characterized by evolved geochemical composition with high contents of SiO2-enriched large-ion lithophile elements, and is depleted of high-field-strength elements. These geochemical features indicate that granites possibly derived from partial melting of metasedimentary rocks and plagioclase fractional crystallization probably played a critical role in production of peraluminous granitic melts. Zircon U–Pb dating from muscovite-granite yielded ages of approximately 48.5 ± 1.1 Ma, representing its crystallization ages. This age is the oldest age of Tethyan Himalayan leucogranite from the Yardoi Dome and adjacent areas. However, the inherited zircon cores have ages of 135.7–3339.2 Ma. The εHf(t) values of all zircons vary from –6.4 to –2.3 and have varying Hf-isotope crustal model ages of 731–839 Ma. The geochemical and isotopic compositions indicate that magma of the Liemai granite can most likely be interpreted as products of the break-off related to thermal perturbation along the break-off window associated with the subduction of Neo-Tethyan slab. These magmas were derived mainly from the anatexis of ancient crustal materials under contraction and thickening conditions due to subduction of the Indian continent beneath southeastern Tibet.

China implemented strict emission control measures in Beijing and surrounding regions to ensure good air quality during the 2014 Asia-Pacific Economic Cooperation (APEC) summit. We conducted synchronous aerosol particle measurements with two aerosol mass spectrometers at different heights on a meteorological tower in urban Beijing to investigate the variations in particulate composition, sources and size distributions in response to emission controls. Our results show consistently large reductions in secondary inorganic aerosol (SIA) of 61–67% and 51–57% and in secondary organic aerosol (SOA) of 55% and 37%, at 260 m and ground level, respectively, during the APEC summit. These changes were mainly caused by large reductions in accumulation mode particles and by suppression of the growth of SIA and SOA by a factor of 2–3, which led to blue sky days during APEC commonly referred to as “APEC Blue”. We propose a conceptual framework for the evolution of primary and secondary species and highlight the importance of regional atmospheric transport in the formation of severe pollution episodes in Beijing. Our results indicate that reducing the precursors of secondary aerosol over regional scales is crucial and effective in suppressing the formation of secondary particulates and mitigating PM pollution.

The Open Spectrum approach to spectrum access can achieve near-optimal utilization by allowing devices to sense and utilize available spectrum opportunistically. However, a naive distributed spectrum assignment can lead to significant interference between devices. In this paper, we define a general framework that defines the spectrum access problem for several definitions of overall system utility. By reducing the allocation problem to a variant of the graph coloring problem, we show that the global optimization problem is NP-hard, and provide a general approximation methodology through vertex labeling. We examine both a centralized strategy, where a central server calculates an allocation assignment based on global knowledge, and a distributed approach, where devices collaborate to negotiate local channel assignments towards global optimization. Our experimental results show that our allocation algorithms can dramatically reduce interference and improve throughput (as much as 12-fold). Further simulations show that our distributed algorithms generate allocation assignments similar in quality to our centralized algorithms using global knowledge, while incurring substantially less computational complexity in the process.

Financial distress prediction models are much challenged in identifying a distressed company two or more years prior to the occurrence of its actual distress, on the grounds that the distress signal is too weak to be captured at an early stage. The paper innovatively proposes to predict the distressed companies by a factorial discriminant model based on interval data. The main idea is that we use a new data representation, i.e., interval data, to summarize four-quarter financial data, and then build a interval-data-based discriminant model, namely i-score model. Interval data makes both average and volatility information comprehensively included in the proposed prediction model, which is expected to improve prediction performance on the distressed companies. A comparison based on a real data case from China’s stock market is conducted. The i-score model is compared with five commonly used models that are based on numerical data. The empirical study shows that i-score model is more accurate and more reliable in identification of companies in high risk of financial distress in advance of 2 years.