Numerical Simulation of Aerodynamic Noise of Soundproof Enclosure of Air Compressor Unit

During the operation of the air compressor unit, the suction and exhaust process of the air compressor and the operation of other equipment will cause air flow pulsation, which is often accompanied by the generation of air compressor noise. Numerical simulation method, as an important means to study the flow field characteristics and noise characteristics of air compressors, has been widely used in recent years. This article takes the noise enclosure of a certain air compressor unit as the research object, and use numerical simulation method to study the air intake part of the enclosure. The influence of inlet louver and suction deflector on the aerodynamic performance of air compressor noise enclosure was analyzed, and the influence of different inlet louver structures and different suction deflector structures on noise was compared. This paper uses the broadband noise model to predict the distribution of air flow pulsation noise. In order to quantitatively study the noise, the FW-H model based on Lighthill\u27s acoustic analogy method was used for the aerodynamic noise simulation, and the frequency response of the aerodynamic noise of air compressor was obtained

Self-guided Few-shot Semantic Segmentation for Remote Sensing Imagery Based on Large Vision Models

The Segment Anything Model (SAM) exhibits remarkable versatility and zero-shot learning abilities, owing largely to its extensive training data (SA-1B). Recognizing SAM's dependency on manual guidance given its category-agnostic nature, we identified unexplored potential within few-shot semantic segmentation tasks for remote sensing imagery. This research introduces a structured framework designed for the automation of few-shot semantic segmentation. It utilizes the SAM model and facilitates a more efficient generation of semantically discernible segmentation outcomes. Central to our methodology is a novel automatic prompt learning approach, leveraging prior guided masks to produce coarse pixel-wise prompts for SAM. Extensive experiments on the DLRSD datasets underline the superiority of our approach, outperforming other available few-shot methodologies

Advance in integrating platinum-based chemotherapy with radiotherapy for locally advanced nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant tumor characterized by the malignant transformation of nasopharyngeal epithelial cells. It is highly sensitive to radiation therapy, making radiotherapy the primary treatment modality. However, 60-80% of patients are initially diagnosed with locally advanced NPC (LA-NPC), where radiotherapy alone often fails to achieve desirable outcomes. Therefore, combining radiotherapy with chemotherapy has emerged as an effective strategy to optimize treatment for LA-NPC patients. Among the various chemotherapy regimens, concurrent chemoradiotherapy (CCRT) using platinum-based drugs has been established as the most commonly utilized approach for LA-NPC patients. The extensive utilization of platinum drugs in clinical settings underscores their therapeutic potential and emphasizes ongoing efforts in the development of novel platinum-based complexes for anticancer therapy. The aim of this review is to elucidate the remarkable advances made in the field of platinum-based therapies for nasopharyngeal carcinoma, emphasizing their transformative impact on patient prognosis

Truthful Auctions for Automated Bidding in Online Advertising

Automated bidding, an emerging intelligent decision making paradigm powered by machine learning, has become popular in online advertising. Advertisers in automated bidding evaluate the cumulative utilities and have private financial constraints over multiple ad auctions in a long-term period. Based on these distinct features, we consider a new ad auction model for automated bidding: the values of advertisers are public while the financial constraints, such as budget and return on investment (ROI) rate, are private types. We derive the truthfulness conditions with respect to private constraints for this multi-dimensional setting, and demonstrate any feasible allocation rule could be equivalently reduced to a series of non-decreasing functions on budget. However, the resulted allocation mapped from these non-decreasing functions generally follows an irregular shape, making it difficult to obtain a closed-form expression for the auction objective. To overcome this design difficulty, we propose a family of truthful automated bidding auction with personalized rank scores, similar to the Generalized Second-Price (GSP) auction. The intuition behind our design is to leverage personalized rank scores as the criteria to allocate items, and compute a critical ROI to transform the constraints on budget to the same dimension as ROI. The experimental results demonstrate that the proposed auction mechanism outperforms the widely used ad auctions, such as first-price auction and second-price auction, in various automated bidding environments

Potential of Visible and Near Infrared Spectroscopy and Pattern Recognition for Rapid Quantification of Notoginseng Powder with Adulterants

Notoginseng is a classical traditional Chinese medical herb, which is of high economic and medical value. Notoginseng powder (NP) could be easily adulterated with Sophora flavescens powder (SFP) or corn flour (CF), because of their similar tastes and appearances and much lower cost for these adulterants. The objective of this study is to quantify the NP content in adulterated NP by using a rapid and non-destructive visible and near infrared (Vis-NIR) spectroscopy method. Three wavelength ranges of visible spectra, short-wave near infrared spectra (SNIR) and long-wave near infrared spectra (LNIR) were separately used to establish the model based on two calibration methods of partial least square regression (PLSR) and least-squares support vector machines (LS-SVM), respectively. Competitive adaptive reweighted sampling (CARS) was conducted to identify the most important wavelengths/variables that had the greatest influence on the adulterant quantification throughout the whole wavelength range. The CARS-PLSR models based on LNIR were determined as the best models for the quantification of NP adulterated with SFP, CF, and their mixtures, in which the rP values were 0.940, 0.939, and 0.867 for the three models respectively. The research demonstrated the potential of the Vis-NIR spectroscopy technique for the rapid and non-destructive quantification of NP containing adulterants

Effects of bilirubin on the development and electrical activity of neural circuits

In the past several decades, bilirubin has attracted great attention for central nervous system (CNS) toxicity in some pathological conditions with severely elevated bilirubin levels. CNS function relies on the structural and functional integrity of neural circuits, which are large and complex electrochemical networks. Neural circuits develop from the proliferation and differentiation of neural stem cells, followed by dendritic and axonal arborization, myelination, and synapse formation. The circuits are immature, but robustly developing, during the neonatal period. It is at the same time that physiological or pathological jaundice occurs. The present review comprehensively discusses the effects of bilirubin on the development and electrical activity of neural circuits to provide a systematic understanding of the underlying mechanisms of bilirubin-induced acute neurotoxicity and chronic neurodevelopmental disorders

Cognitive Reserve and Mild Cognitive Impairment

Background and Objectives Little is known about the effect of education or other indicators of cognitive reserve on the rate of reversion from mild cognitive impairment (MCI) to normal cognition (NC) or the relative rate (RR) of reversion from MCI to NC vs progression from MCI to dementia. Our objectives were to (1) estimate transition rates from MCI to NC and dementia and (2) determine the effect of age, APOE, and indicators of cognitive reserve on the RR of reversion vs progression using multistate Markov modeling. Methods We estimated instantaneous transition rates between NC, MCI, and dementia after accounting for transition to death across up to 12 assessments in the Nun Study, a cohort study of religious sisters aged 75+ years. We estimated RRs of reversion vs progression for age, APOE, and potential cognitive reserve indicators: education, academic performance (high school grades), and written language skills (idea density, grammatical complexity). Results Of the 619 participants, 472 were assessed with MCI during the study period. Of these 472, 143 (30.3%) experienced at least one reverse transition to NC, and 120 of the 143 (83.9%) never developed dementia (mean follow-up = 8.6 years). In models adjusted for age group and APOE, higher levels of education more than doubled the RR ratio of reversion vs progression. Novel cognitive reserve indicators were significantly associated with a higher adjusted RR of reversion vs progression (higher vs lower levels for English grades: RR ratio = 1.83; idea density: RR ratio = 3.93; and grammatical complexity: RR ratio = 5.78). Discussion Knowledge of frequent reversion from MCI to NC may alleviate concerns of inevitable cognitive decline in those with MCI. Identification of characteristics predicting the rate of reversion from MCI to NC vs progression from MCI to dementia may guide population-level interventions targeting these characteristics to prevent or postpone MCI and dementia. Research on cognitive trajectories would benefit from incorporating predictors of reverse transitions and competing events, such as death, into statistical modeling. These results may inform the design and interpretation of MCI clinical trials, given that a substantial proportion of participants may experience improvement without intervention