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The total electron content (TEC) is a critical parameter of ionosphere morphology. Precise modeling and prediction of the TEC time series can significantly aid the functioning of the Global Navigation Satellite System (GNSS), satellite as well as shortwave communications. An improved Transformer-based TEC prediction model (ITM) is proposed in this study, in response to the high noise characteristics of the temporal data for TEC in the global ionosphere. The ITM model forecasts the global ionospheric TEC data provided by the Center for Orbit Determination in Europe (CODE) for the year 2018. Experimental results indicate that the model obtains an annual average root mean square error of 1.4 TECU, which represents a 6.67 % advancement over the daily forecast product C1PG published by the CODE center. The model also attains an annual average mean absolute error of 1 TECU, representing a 9.09 % improvement over the accuracy of C1PG. The annual average correlation coefficient is 0.98, which indicates a 0.62 % upgrade in C1PG's accuracy. Additionally, the model exhibits a maximum increase of 23.53 % in monthly average root mean square error over C1PG, a maximum increase of 25 % in monthly average mean absolute error, and a maximum increase of 1.55 % in monthly average correlation coefficient. During the more geomagnetically active phases of 2018, the ITM model's forecast accuracy exhibited an overall improvement of 5 % in RMSE, 7.14 % in MAE, and 0.83 % in correlation coefficient R compared to the C1PG product. [ABSTRACT FROM AUTHOR]

Ionospheric delay has a severe effect on reducing the accuracy of positioning and navigation of single-frequency receivers. Therefore, it is necessary to construct a precise regional ionospheric model for real-time Global Navigation Satellite System (GNSS) applications. The total electron contents (TECs) of 839 GNSS stations affiliated with the GPS Earth Observation Network were used to build a Japanese ionospheric model (JIM) based on a multi-layer perceptron neural network. During quiet space conditions, the correlation coefficient between the targets and the predictions of the JIM was about 0.98, and the root-mean square error (RMSE) of TEC residuals was ~1.5TECU, while under severe space events, the correlation coefficient increased to 0.99, and the corresponding RMSE dropped to 0.96 TECU. Moreover, the JIM model successfully reconstructed the two-dimensional (time vs latitude) TEC maps, and the TEC maps had evident hourly and seasonal variations. Most of TEC residuals accumulated between universal time 01–06 with an averaged magnitude of 1-2TECU. Furthermore, the JIM model had a perfect prediction performance under various kinds of complex space environments. In the quiet days, the prediction accuracy of the JIM was nearly equal to the global ionosphere map (GIM), and in some moments, the JIM was more competitive than the GIM. In the disturbed days, the RMSEs of TEC residuals were proportional to the solar wind speed and were inversely proportional to the geomagnetic Dst value. The maximum RMSE of the JIM was lower than 2TECU, while the corresponding RMSEs for the IRI and TIE-GCM exceeded 5TECU. [ABSTRACT FROM AUTHOR]

Chordoma is a rare tumor, but has a serious effect on the quality of life of patients. This study aims to assess the overall knowledge structure and trends in the development of chordoma research using a bibliometric analysis and visualization tool. Research datasets were acquired from the Web of Science. VOS viewer and CiteSpace visualization software were used to demonstrate collaborations and correlations. Annual trends in publications, distribution, H‐index status, co‐authorship status, and research hotspots were analyzed. A total of 1844 publications from 2012 to 2022 were included. The number of chordoma‐related publications increased year by year. The United States contributed the most publications (717) and had the highest total citations (10130) and H‐index (50), followed by China. The United States was also the country most frequently involved in international cooperation. The most productive organization involved in chordoma research was Massachusetts General Hospital. World Neurosurgery (114) published the most papers on chordoma. Hornicek FJ was the most productive author over the last decade (41). Initially, diagnosis and the location of onset captured the attention of the research society. Quality of life, risk factors, disability, minimally invasive surgical techniques, molecular targeted therapy, and radiotherapy technology are the research hotspots in recent years. Indeed, this study provides important insights into the overall landscape of chordoma research and also contributes to the further investigation of the international frontier of chordoma. [ABSTRACT FROM AUTHOR]

A robust ionospheric model is indispensable for providing the atmospheric delay corrections for global navigation satellite system (GNSS) navigation and positioning and forecasting the space environment. The accuracy of ionospheric models is limited due to the simplified model structures. Complicated spatiotemporal variations in total electron content (TEC) biases between GNSS and international reference ionosphere (IRI) suggest a robust strategy to optimally combine GNSS and IRI TEC for high-precision modeling. In this paper, we propose a novel ionospheric data assimilation method, which is a local ensemble transform Kalman filter (LETKF), to construct an ionospheric model over Yunnan in southwestern China. We used the LETKF method to assimilate the ionospheric TEC extracted from GNSS observations in Yunnan into the IRI-2016 model. The experimental results indicate that the ionospheric data assimilation has a more pronounced improvement effect on the IRI empirical model during periods of geomagnetic quiet than during periods of geomagnetic disturbance. On quiet magnetic days, the skill score (SKS) of the assimilation is 0.60 and the root mean square error (RMSE) values before and after assimilation are 5.08 TECU and 2.02 TECU, respectively. The correlation coefficient after assimilation increases from 0.94 to 0.99. On magnetic storm days, the SKS of the assimilation is 0.42 and the RMSE values before and after assimilation are 5.99 TECU and 3.46 TECU, respectively. The correlation coefficient after assimilation increases from 0.98 to 0.99. The results suggest that the LETKF algorithm can be considered an effective method for ionospheric data assimilation. [ABSTRACT FROM AUTHOR]

In this paper, we forecasted the ionospheric total electron content (TEC) over the region of China using the bidirectional convolutional gated recurrent unit (BiConvGRU) model. We first generated the China Regional Ionospheric Maps (CRIMs) using GNSS observations provide by the Crustal Movement Observation Network of China (CMONOC). We then used gridded TEC maps from 2015 to 2018 with a 1 h interval from the CRIMs as the dataset, including quiet periods and storm periods of ionospheric TEC. The BiConvGRU model was then utilized to forecast the ionospheric TEC across China for the year 2018. The forecasted TEC was compared with the TEC from the International Reference Ionosphere (IRI-2016), Convolutional Long Short-Term Memory (ConvLSTM), Convolutional Gated Recurrent Unit (ConvGRU), Bidirectional Convolutional Long Short-Term Memory (BiConvLSTM), and the 1-day Predicted Global Ionospheric Map (C1PG) provided by the Center for Orbit Determination in Europe (CODE). In addition, indices including Kp, ap, Dst and F10.7 were added to the training dataset to improve the forecasting accuracy of the model (-A indicates no indices, while -B indicates with indices). The results verified that the prediction accuracies of the models integrated with these indices were significantly improved, especially during geomagnetic storms. The BiConvGRU-B model presented a decrease of 41.5%, 22.3%, and 13.2% in the root mean square error (RMSE) compared to the IRI-2016, ConvGRU, and BiConvLSTM-B models during geomagnetic storm days. Furthermore, at a specific grid point, the BiConvGRU-B model showed a decrease of 42.6%, 49.1%, and 31.9% in RMSE during geomagnetic quiet days and 30.6%, 34.1%, and 15.1% during geomagnetic storm days compared to the IRI-2016, C1PG, and BiConvLSTM-B models, respectively. In the cumulative percentage analysis, the BiConvGRU-B model had a significantly higher percentage of mean absolute error (MAE) within the range of 0–1 TECU in all seasons compared to the BiConvLSTM-B model. Meanwhile, the BiConvGRU-B model outperformed the BiConvLSTM-B model with lower RMSE for each month of 2018. [ABSTRACT FROM AUTHOR]

The 25–27 August 2018 geomagnetic storm was the third largest storm in the 24th solar cycle. It was a surprising space event that originated from low-level solar activity. This study provides an overview of the temporal–spatial behaviors of plasma irregularities as functions of geographic longitude, latitude, and altitude using ground-based (GNSS receivers and ionosonde) instruments and space-borne Swarm satellites. The results not only reveal enhanced equatorial ionization anomaly (EIA) and hemispheric asymmetry over the Asian–Australian and American sectors at a particular time but also hemispheric asymmetric features of global ROT in the main and recovery phases. Additionally, this storm triggered positive plasma irregularities in altitudes of 100 to 150 km near the Auroral zone, and the changed ratio of bottom-side plasma irregularities exceeded 250%. This finding has been cross-validated by other instruments and models. Furthermore, the storm significantly affected the thermospheric O/N2 density ratio, equatorial electrojet, and vertical E×B drifts. The equatorial and mid-latitude plasma irregularities may be a combined action of thermospheric composition change, equatorial electrojet, and vertical E×B drifts. Finally, the storm induced positive Joule heating irregularities in the Auroral ionosphere in altitudes of 100 to 400 km with a maximum changed ratio of over 200%, as well as enhanced cross-Polar voltage to ~90 kv. The Polar ionospheric irregularities may be associated with additional energy input through particle precipitation, Joule heating, and ionospheric current intensification. [ABSTRACT FROM AUTHOR]

River discharge monitoring is an important component of the hydrology objectives of Surface Water and Ocean Topography mission (SWOT). River discharge can be estimated Solely using river widths and At Many-stations Hydraulic Geometry (AMHG), but the accuracy is low due to the parameters of At a-station Hydraulic Geometry (AHG) given by AMHG deviate from the truth. In view of this, a Constrained At-Many-Stations Hydraulic Geometry (CAMHG) is proposed to optimize AHG parameters. The performance of CAMHG is verified in three reaches of the Yangtze River using river widths derived from SWOT. After using CAMHG, the relative root mean square error (RRMSE) of estimated discharge reduce 100.1% to 24.4%, 1137.1% to 49.9% and 48.6% to 45.5% for Hankou, Shashi and Luoshan respectively. In addition, CAMHG can also weaken the accuracy difference of estimated discharge in dry and wet seasons benefited from its more reliable AHG parameters. Thus, the proposed CAMHG can dramatically improves the accuracy of discharge estimations and it is meaningful for the discharge calculation after SWOT data release. [ABSTRACT FROM AUTHOR]

Ionospheric total electron content (TEC) is important data for ionospheric morphology, and also an important parameter for ionospheric correction in Global Navigation Satellite System (GNSS) precise positioning, navigation, and radio science. In this study, we present a data assimilation model for regional ionosphere based on a local ensemble Kalman filter (LEnKF) with the International Reference Ionosphere 2016 (IRI-2016) model as the background, to assimilate ionospheric TEC observations from GNSS. To demonstrate the results, the TEC estimates from the Crustal Movement Observation Network of China (CMONOC), which is about 260 stations in China, are applied as observation. The assessments are performed against the TEC estimates from BeiDou Navigation Satellite System (BDS) geostationary earth orbit (GEO) and against the final products from the Center for Orbit Determination in Europe (CODE). The assimilation results are in good agreement with BDS GEO TEC and the CODE TEC on a quiet or disturbed day. The correlation coefficient after assimilation is increased by about 17% compared with that before assimilation, and the RMSE after assimilation is decreased by about 42% compared with that before assimilation. Furthermore, the assimilated method is also evaluated in the single-frequency precise point positioning (PPP). The experimental results indicate that the PPP/Assimilated method can improve the GNSS positioning accuracy more effectively in comparison to the PPP/CODE. These results reveal that the LEnKF method can be considered as a useful tool for ionospheric assimilation. [ABSTRACT FROM AUTHOR]

With the development of societies, the exploitation of mountains and forests is increasing to meet the needs of tourism, mineral resources, and environmental protection. The point cloud registration, 3D modeling, and deformation monitoring that are involved in surveying large scenes in the field have become a research focus for many scholars. At present, there are two major problems with outdoor terrestrial laser scanning (TLS) point cloud registration. First, compared with strong geometric conditions with obvious angle changes or symmetric structures, such as houses and roads, which are commonly found in cities and villages, outdoor TLS point cloud registration mostly collects data on weak geometric conditions with rough surfaces and irregular shapes, such as mountains, rocks, and forests. This makes the algorithm that set the geometric features as the main registration parameter invalid with uncontrollable alignment errors. Second, outdoor TLS point cloud registration is often characterized by its large scanning range of a single station and enormous point cloud data, which reduce the efficiency of point cloud registration. To address the above problems, we used the NARF + SIFT algorithm in this paper to extract key points with stronger expression, expanded the use of multi-view convolutional neural networks (MVCNN) in point cloud registration, and adopted GPU to accelerate the matrix calculation. The experimental results have demonstrated that this method has greatly improved registration efficiency while ensuring registration accuracy in the registration of point cloud data with weak geometric features. [ABSTRACT FROM AUTHOR]

Ionospheric forecasts are critical for space-weather anomaly detection. Forecasting ionospheric total electron content (TEC) from the global navigation satellite system (GNSS) is of great significance to near-earth space environment monitoring. In this study, we propose a novel ionospheric TEC forecasting model based on deep learning, which consists of a convolutional neural network (CNN), long-short term memory (LSTM) neural network, and attention mechanism. The attention mechanism is added to the pooling layer and the fully connected layer to assign weights to improve the model. We use observation data from 24 GNSS stations from the Crustal Movement Observation Network of China (CMONOC) to model and forecast ionospheric TEC. We drive the model with six parameters of the TEC time series, Bz, Kp, Dst, and F10.7 indices and hour of day (HD). The new model is compared with the empirical model and the traditional neural network model. Experimental results show the CNN-LSTM-Attention neural network model performs well when compared to NeQuick, LSTM, and CNN-LSTM forecast models with a root mean square error (RMSE) and R2 of 1.87 TECU and 0.90, respectively. The accuracy and correlation of the prediction results remained stable in different months and under different geomagnetic conditions. [ABSTRACT FROM AUTHOR]

We present the ionospheric disturbance responses over low-latitude regions by using total electron content from Geostationary Earth Orbit (GEO) satellites of the BeiDou Navigation Satellite System (BDS), ionosonde data and Swarm satellite data, during the geomagnetic storm in August 2018. The results show that a prominent total electron content (TEC) enhancement over low-latitude regions is observed during the main phase of the storm. There is a persistent TEC increase lasting for about 1–2 days and a moderately positive disturbance response during the recovery phase on 27–28 August, which distinguishes from the general performance of ionospheric TEC in the previous storms. We also find that this phenomenon is a unique local-area disturbance of the ionosphere during the recovery phase of the storm. The enhanced f o F 2 and h m F 2 of the ionospheric F2 layer is observed by SANYA and LEARMONTH ionosonde stations during the recovery phase. The electron density from Swarm satellites shows a strong equatorial ionization anomaly (EIA) crest over the low-latitude area during the main phase of storm, which is simultaneous with the uplift of the ionospheric F2 layer from the SANYA ionosonde. Meanwhile, the thermosphere O/N2 ratio shows a local increase on 27–28 August over low-latitude regions. From the above results, this study suggests that the uplift of F layer height and the enhanced O/N2 ratio are possibly main factors causing the local-area positive disturbance responses during the recovery phase of the storm in August 2018. [ABSTRACT FROM AUTHOR]

Purpose: Enhanced Recovery After Surgery (ERAS) is a multimodal approach to perioperative care that aims to reduce patient perioperative complications, accelerate patient recovery, and improve patient satisfaction by refining and optimizing all perioperative management processes. By comparing two groups of patients before and after the implementation of ERAS for intertrochanteric fracture (ITF) with a matching analysis of propensity score (PS), we aimed to demonstrate that the implementation of ERAS protocol shortens the length of hospital stay (LOS), reduces pain, decreases the incidence of postoperative complications, and promotes functional recovery of the joint. Methods: We selected 2 periods of 1 year, before (n=98patients) and after ERAS implementation (n=92patients). Data were collected on patient demographics, operative and perioperative details, LOS, VAS score, Harris score, and 30-day complications. ERAS-trained nurses are engaged to support patients at each step of the pre/per/postoperative process, including completing a satisfaction survey, with the help of a mobile app. PS analyses were used for dealing with confounding bias in this retrospective observational study. Results: After PS matching, the outcomes of 124 well-balanced pairs of patients were compared (conventional vs ERAS). LOS was significantly reduced from 24.3±3.9 to 15.2±2.9 days (P<0.001). With the same preoperative VAS scores, we found that patients in the ERAS group had significantly lower postoperative VAS scores than those in the conventional group at days 3 and 7 (P<0.001), but the difference was not statistically significant at day 14. patients in the ERAS group had higher Harris scores than those in the conventional group at 1 and 3 months, but the difference was not significant at 6 months. In addition, we found that only one patient in the ERAS group developed complications, while nine patients in the conventional group developed different complications. There was no significant difference concerning the satisfaction survey. Conclusion: The introduction of ERAS for ITF in our institution has resulted in a significant decrease in LOS, alleviated patient pain, promoted early recovery of patient's hip function while effectively preventing complications, and obtained patient satisfaction. [ABSTRACT FROM AUTHOR]

Background: Bizarre parosteal osteochondromatous proliferation (BPOP) is a relatively rare benign extraperiosteal osteochondroma-like proliferative lesion that shares similarities with malignant tumours in terms of morphology. The aetiology of BPOP has yet to be determined and there are no previous reports of BPOP associated with fracture.Case Presentation: A 57-year-old woman presented with a one-month history of pain and swelling in her right foot, which were worsened by activity and improved with rest. Physical examination revealed a hard, non-mobile mass measuring 1.5 cm × 1.5 cm on the dorsal aspect of the third metatarsal of the right foot. There was overlying erythema and tenderness on palpation. Computed tomography (CT) of the right foot demonstrated a fracture of the neck of the third metatarsal, osteolysis at the fracture site and soft tissue swelling. Bone scintigraphy revealed increased tracer uptake suggesting abnormal bone metabolism at the neck of the third metatarsal. Surgical excision of the lesion was performed. Histopathology and immunohistochemistry confirmed the diagnosis of BPOP.Conclusion: BPOP is a rare benign lesion that is commonly misdiagnosed. Differential diagnosis is mainly achieved through imaging and histopathological assessment. [ABSTRACT FROM AUTHOR]

Background: Intertrochanteric fracture (ITF) is increasing with the rapid increase in the aging population, often causes a high mortality rate in old patients and increases the economic burden of the family and society. ERAS (Enhanced Recovery after Surgery) is a powerful guarantee for patients to accelerate their recovery after surgery. TCM (traditional Chinese medicine) promotes repair of injured tissues and eliminates traumatic aseptic inflammation. Therefore, this prospective randomized controlled clinical trial aims to evaluate the clinical effect of the evidence-based ERAS pathway of integrating TCM with western medicine on perioperative outcomes in ITF patients undergoing intramedullary fixation and provide reliable evidence-based data for applying the program to clinical practice. Methods/design: We will conduct a prospective randomized, blinded, controlled trial to compare the effectiveness of ERAS care pathway with traditional care pathway and to investigate whether the ERAS care pathway can improve the perioperative outcome in ITF patients undergoing intramedullary fixation. A total of 60 patients with ITF will be enrolled and treated with the two care pathway, respectively. Length of stay, economic indicators, Harris score, VAS score, time to get out of bed, 30-day readmission rates, postoperative transfusion rates, discharge to home, and mortality will be evaluated. Any signs of acute adverse reactions will be recorded at each visit during treatment. Discussion: Although an evidence-based process using the best available literature and Delphi expert-opinion method has been used to establish an ERAS pathway of integrating TCM with western medicine, there is a lack of consensus about its effectiveness. This trial will provide convincing evidence about the effect of ERAS pathway. Trial registration: Registered on 12 October 2019. Trial number is ChiCTR1900026487. [ABSTRACT FROM AUTHOR]

The effects of activators on the properties of sulphoaluminate cement were investigated by experiments. The results of experiments show that reduction compressive strength of sulphoaluminate cement in later ages was controlled by using burnt plaster and alunite, and setting time is also prolonged by organic admixtures. The properties of sulphoaluminate cement, such as increase of expansion ratios, resistance to drying contraction and the chemical corrosion, are all increased. The hydrates and mechanism of hydration of sulphoaluminate cement are analyzed and studied by means of XRD, SEM and DTA. [Copyright &y& Elsevier]