Yang (2020) Integrated meta-analysis, network pharmacology, and molecular docking to investigate the efficacy and potential pharmacological mechanism of Kai-Xin-San on Alzheimer's disease,
Background: Intracranial Ewing’s sarcoma (ES) is a rare entity with <15 cases reported in the literature. It belongs to a family of round-cell neuroectodermally derived tumors bearing many similarities to peripheral primitive neuroectodermal tumor (pPNET). There is currently no established treatment protocol. Reported cases are treated with either surgery alone or surgery with adjuvant chemotherapy and radiation. Case Description: We describe a case of intracranial left frontal ES in a 19-year-old patient who presented with change in behavior. Diagnosis was unclear based on radiological findings on MRI and CT alone. MRI brain with contrast demonstrated a large extra-axial ovoid heterogeneously enhancing left frontal convexity mass. The patient underwent gross total resection with adjuvant chemotherapy and radiation. No local or systemic recurrence was found at 12 months postoperatively. Conclusion: Intracranial ES/pPNET is rare tumor with nonspecific clinical presentation and radiological findings. They are locally invasive. Surgery with adjuvant chemoradiation is the mainstay treatment. Distinction of pPNET and cPNET is important for therapeutic and prognostic purposes.
HighlightsAn evaluation system for agricultural machinery operation was developed.Quantitatively evaluating agricultural machinery operators can support the precision management for agricultural machinery service organizations.The evaluation system can detect and quantify subtle and transient operating behaviors based on smartphone sensors.The evaluation system can distinguish the relative pros and cons of the operating skills of agricultural machinery operators.Abstract. To support the precision management of agricultural machinery operators, scaled agricultural machinery service organizations require comprehensive evaluations for the operating behaviors of each operator, particularly subtle and transient operating behaviors (e.g., sudden acceleration and unstable operating velocities), which greatly influence the operation quality. In this paper, embedded smartphone sensors were utilized to collect high-frequency motion information for agricultural machinery operation, and then, an Agricultural Machinery Operation Evaluation System (AMOES) was designed to evaluate the operating behaviors of the corresponding operators. In AMOES, four evaluation items (the ratio of useful work, the effect on machinery health, the quality of working operation, and the efficiency of U-turn) were defined specifically for the evaluation of subtle and transient operating behaviors, and they were quantified using motion information. Moreover, a case of a scaled agricultural machinery cooperative in Beijing was performed, and AMOES was used to evaluate the operating behaviors of six operators (two autonomous-driving and four manual-driving operators). The case study indicated that the motion data collected by smartphone sensors could capture subtle and transient operating behaviors and that AMOES could effectively detect and quantify subtle operating behaviors. Keywords: Agricultural machinery, Operating behavior, Operation evaluation, Smartphone sensors.
Background: Calcifying pseudoneoplasm of the neuraxis (CAPNON) is a rare entity which can occur at intracranial and spinal locations. Clinical presentation is due to local mass effect rather than tissue infiltration. Lesions causing significant symptoms or are showing radiological progression require surgical resection. Maximal surgical resection is considered curative for this non-neoplastic entity with only two cases of recurrence reported in the literature. Cranial nerve involvement is extremely rare and the presenting neurological deficit is unlikely to improve even with surgical intervention. Case Description: We describe a case of CAPNON at the right posterior clinoid process with involvement of the right oculomotor nerve in a 38-year-old male. Computed tomography demonstrated an amorphous mass which had intermediate to low T1 and T2 signal on magnetic resonance imaging. The oculomotor nerve was compressed with sign of atrophy. The patient underwent maximal surgical debulking for progressive symptoms of worsening pain and ophthalmoplegia. Postoperatively, the patient’s symptoms were stable but did not improve. Conclusion: Preoperative diagnosis of CAPNON is difficult due to its rarity and nonspecific clinical and radiological findings. Surgical resection is considered in cases with worsening symptoms, progression on serial imaging, or uncertain diagnosis. Relatively inaccessible lesions with little or no clinical symptoms can be observed.
The exchange rate is essential to global financial markets. Based on the approximate long memory Heterogeneous Autoregressive (HAR) model proposed by Corsi, we estimate the volatility using 5-minute high-frequency data on the US dollar exchange rate against the Australian dollar from January 15, 2019, to September 16, 2021. The HAR-RV model performs well in describing volatility and forecasting accuracy. The empirical results indicate that daily, weekly, and monthly volatility positively influences exchange rate volatility, especially in the mid-term and the long-term. This paper provides a forecasting method to predict exchange rate volatility
Fusion tag-induced formation of inclusion bodies provides a powerful means to express unstructured or toxic proteins. For a given fusion tag, how to enhance the formation of inclusion bodies remains to be explored.
Agricultural machinery management is the key to agricultural production, andtrajectory segmentation lays an important foundation for machinerymanagement. For big data platform of agricultural machinery, it is hoped tosimultaneously improve both of segmentation accuracy and segmentationefficiency to satisfy the processing requirements. However, traditional machinelearning algorithms need to manually adjust parameters and do not integratemultiple features when dealing with trajectory segmentation. This paper aims atthe above problems by modifying the CE-Net model to improve the segmentationaccuracy and ensure the processing efficiency. A creative method for constructingtrajectory image from discrete trajectory data was developed in this paper. Thenew trajectory image showed both the temporal and the spatial characteristics ofthe operation. Then, a semantic segmentation algorithm, Field & Road- CENet,was put forward. The proposed algorithm modified the network CE-Net by addingtwo modules, Standard Convolution Residual Block and Global MaxpoolingAttention Mechanism, to fuse original feature information and enhance thesemantic expression of low-level feature maps. Two cotton sowing datasets werebuilt, including the meter level and the centimeter level. Experiment results showthat Field & Road-CENet performed well on both datasets. In the fieldsegmentation that is the most concerned, the identification accuracy reached97.8% and 95.2%, respectively, and the average accuracy of field and road was94.2% and 88.3%, respectively. In conclusion, this work verifies the feasibility ofusing semantic segmentation to realize trajectory segmentation of agriculturalmachinery. Compared with the current researches, the proposed method isapplicable to trajectory data with two precisions, which has stronger domaingeneralization ability. And it performs quite fast with an average inference time of 0.044 s for each image block, demonstrating that the proposed algorithm issuitable for the big data processing of agricultural machinery.
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