Yellow River Piano Concerto

The Yellow River Piano Concerto (1969) by Yin Chengzong (1941–present) and other committee members (Chu Wanghua, Liu Zhuang, Sheng Lihong, Shi Shucheng, and Xu Feixing), the most popular piano concerto in China, was composed at the time of the Cultural Revolution. It was written as an arrangement of the Yellow River Cantata composed by Xian Xinghai (1905–1945) in 1939 at the height of the Anti-Japanese War (1937–1945). Yin and his work played a critical role in making the piano the most popular instrument among a new generation of Chinese performers and composers. I examined some articles, journals and dissertations form both America and China. In addition to focusing on the political field, this DMA document also analyzes the composition, exploring the importance and performance difficulties from the standpoint of a pianist. This document has three chapters and a conclusion. The first chapter introduces the historical background of twentieth-century China, especially music during the Cultural Revolution. For the second chapter, I discuss the Yellow River Cantata and the birth of the Yellow River Piano Concerto, covering all six composers involved in the two works. For chapter three, I analyze the music score, focusing primarily on the piano part. Then I combine my practical experience to explore the difficulties of performance

Metamaterial absorber integrated microfluidic terahertz sensors

Spatial overlap between the electromagnetic fields and the analytes is a key factor for strong light-matter interaction leading to high sensitivity for label-free refractive index sensing. Usually, the overlap and therefore the sensitivity are limited by either the localized near field of plasmonic antennas or the decayed resonant mode outside the cavity applied to monitor the refractive index variation. In this paper, by constructing a metal microstructure array-dielectric-metal (MDM) structure, a novel metamaterial absorber integrated microfluidic (MAIM) sensor is proposed and demonstrated in terahertz (THz) range, where the dielectric layer of the MDM structure is hollow and acts as the microfluidic channel. Tuning the electromagnetic parameters of metamaterial absorber, greatly confined electromagnetic fields can be obtained in the channel resulting in significantly enhanced interaction between the analytes and the THz wave. A high sensitivity of 3.5 THz/RIU is predicted. The experimental results of devices working around 1 THz agree with the simulation ones well. The proposed idea to integrate metamaterial and microfluid with a large light-matter interaction can be extended to other frequency regions and has promising applications in matter detection and biosensing

Study of outgoing longwave radiation anomalies associated with Haiti earthquake

The paper presents an analysis by using the methods of Eddy field calculation mean and wavelet maxima to detect seismic anomalies within the outgoing longwave radiation (OLR) data based on time and space. The distinguishing feature of the method of Eddy field calculation mean is that we can calculate "the total sum of the difference value" of "the measured value" between adjacent points, which could highlight the singularity within data. The identified singularities are further validated by wavelet maxima, which using wavelet transformations as data mining tools by computing the maxima that can be used to identify obvious anomalies within OLR data. The two methods has been applied to carry out a comparative analysis of OLR data associated with the earthquake recently occurred in Haiti on 12 January 2010. Combining with the tectonic explanation of spatial and temporal continuity of the abnormal phenomena, the analyzed results have indicated a number of singularities associated with the possible seismic anomalies of the earthquake and from the comparative experiments and analyses by using the two methods, which follow the same time and space, we conclude that the singularities observed from 19 to 24 December 2009 could be the earthquake precursor of Haiti earthquake

Enhancing Data Quality in Federated Fine-Tuning of Foundation Models

In the current landscape of foundation model training, there is a significant reliance on public domain data, which is nearing exhaustion according to recent research. To further scale up, it is crucial to incorporate collaboration among multiple specialized and high-quality private domain data sources. However, the challenge of training models locally without sharing private data presents numerous obstacles in data quality control. To tackle this issue, we propose a data quality control pipeline for federated fine-tuning of foundation models. This pipeline computes scores reflecting the quality of training data and determines a global threshold for a unified standard, aiming for improved global performance. Our experiments show that the proposed quality control pipeline facilitates the effectiveness and reliability of the model training, leading to better performance.Comment: Accepted at ICLR 2024 Workshop on Navigating and Addressing Data Problems for Foundation Models (DPFM

Risk prediction model for postoperative pneumonia in esophageal cancer patients: A systematic review

BackgroundNumerous studies have developed or validated prediction models to estimate the likelihood of postoperative pneumonia (POP) in esophageal cancer (EC) patients. The quality of these models and the evaluation of their applicability to clinical practice and future research remains unknown. This study systematically evaluated the risk of bias and applicability of risk prediction models for developing POP in patients undergoing esophageal cancer surgery.MethodsPubMed, Embase, Web of Science, Cochrane Library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), WanFang Database and Chinese Biomedical Literature Database were searched from inception to March 12, 2024. Two investigators independently screened the literature and extracted data. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was employed to evaluate both the risk of bias and applicability.ResultA total of 14 studies involving 23 models were included. These studies were mainly published between 2014 and 2023. The applicability of all studies was good. However, all studies exhibited a high risk of bias, primarily attributed to inappropriate data sources, insufficient sample size, irrational treatment of variables and missing data, and lack of model validation. The incidence of POP in patients undergoing esophageal cancer surgery ranged from 14.60% to 39.26%. The most frequently used predictors were smoking, age, chronic obstructive pulmonary disease(COPD), diabetes mellitus, and methods of thoracotomy. Inter-model discrimination ranged from 0.627 to 0.850, sensitivity ranged between 60.7% and 84.0%, and specificity ranged from 59.1% to 83.9%.ConclusionIn all included studies, good discrimination was reported for risk prediction models for POP in patients undergoing esophageal cancer surgery, indicating stable model performance. However, according to the PROBAST checklist, all studies had a high risk of bias. Future studies should use the predictive model assessment tool to improve study design and develop new models with larger samples and multicenter external validation.Systematic review registrationhttps://www.crd.york.ac.uk/prospero, identifier CRD42024527085

Damage Characteristics of Argillaceous Quartz Sandstone Mesostructure under Different Wetting-drying Conditions

Extensive water–rock interaction in the Three Gorges Reservoir area of the Yangtze River leads to rock mass deterioration along the reservoir banks. However, mineral evolution behavior and its effect on the mesostructure deterioration of rocks under the wetting–drying cycle condition remain unknown. So, the wetting–drying cycle tests were conducted on peculiar argillaceous quartz sandstone in TGRA under neutral (pH = 7) and alkaline (pH = 10) water environments. Here, we provided detailed physical and microscopy images data to determine the control mechanism of mineral behavior on the evolution of sandstone’s mesostructure. Under the neutral condition, repeated “absorption and swelling–dehydration and contraction” of clay minerals leads to the repeated physical action of “squeezing–unloading” in the interior of a rock. This results in the initiation and gradual expansion of cracks in the framework mineral quartz, exhibiting failure mode from the interior to the exterior. In contrast, under the alkaline condition, the dissolution on the surface of quartz particles leads to the expansion and connection of pores, implying that the sandstone exhibits failure mode from the exterior to the interior. Moreover, the internal mechanical analysis indicates the minerals are at high pressure because of the expansion of clay minerals in the neutral solution. However, in an alkaline water environment, the extrusion pressure of framework mineral quartz decreases significantly and is not easily broken due to increased porosity. Thus, the evolution behavior of minerals in different water environments plays an important role in the damage of the rock