Spencesnyder0298

Accurate prediction of particulate matter (PM) using time series data is a challenging task. The recent advancements in sensor technology, computing devices, nonlinear computational tools, and machine learning (ML) approaches provide new opportunities for robust prediction of PM concentrations. In this study, we develop a hybrid model for forecasting PM10 and PM2.5 based on the multiscale characterization and ML techniques. At first, we use the empirical mode decomposition (EMD) algorithm for multiscale characterization of PM10 and PM2.5 by decomposing the original time series into numerous intrinsic mode functions (IMFs). Different individual ML algorithms such as random forest (RF), support vector regressor (SVR), k-nearest neighbors (kNN), feed forward neural network (FFNN), and AdaBoost are then used to develop EMD-ML models. The air quality time series data from Masfalah air station Makkah, Saudi Arabia are utilized for validating the EMD-ML models, and results are compared with non-hybrid ML models. The PMs (PM10 and PM2.5) concentrations data of Dehli, India are also utilized for validating the EMD-ML models. The performance of each model is evaluated using root mean square error (RMSE) and mean absolute error (MAE). The average bias in the predictive model is estimated using mean bias error (MBE). Obtained results reveal that EMD-FFNN model provides the lowest error rate for both PM10 (RMSE = 12.25 and MAE = 7.43) and PM2.5 (RMSE = 4.81 and MAE = 3.02) using Misfalah, Makkah data whereas EMD-kNN model provides the lowest error rate for PM10 (RMSE = 20.56 and MAE = 12.87) and EMD-AdaBoost provides the lowest error rate for PM2.5 (RMSE = 15.29 and MAE = 9.45) using Dehli, India data. The findings also reveal that EMD-ML models can be effectively used in forecasting PM mass concentrations and to develop rapid air quality warning systems.As a typical fine-grained image recognition task, flower category recognition is one of the most popular research topics in the field of computer vision and forestry informatization. Although the image recognition method based on Deep Convolutional Neural Network (DCNNs) has achieved acceptable performance on natural scene image, there are still shortcomings such as lack of training samples, intra-class similarity and low accuracy in flowers category recognition. In this paper, we study deep learning-based flowers' category recognition problem, and propose a novel attention-driven deep learning model to solve it. Specifically, since training the deep learning model usually requires massive training samples, we perform image augmentation for the training sample by using image rotation and cropping. The augmented images and the original image are merged as a training set. Then, inspired by the mechanism of human visual attention, we propose a visual attention-driven deep residual neural network, which is composed of multiple weighted visual attention learning blocks. Each visual attention learning block is composed by a residual connection and an attention connection to enhance the learning ability and discriminating ability of the whole network. Finally, the model is training in the fusion training set and recognize flowers in the testing set. We verify the performance of our new method on public Flowers 17 dataset and it achieves the recognition accuracy of 85.7%.This study aimed to propose an equal-integral-bandwidth feature extraction method based on fast Fourier transform (FFT) to solve the problem of cumbersome processing and a large amount of calculation in the common feature extraction algorithm for vibration signals of on-load tap changer (OLTC). First, the vibration signals of OLTC were preprocessed in segments, which highlighted the status features and avoided the shortcomings of the FFT spectrum that lacked time axis information. Second, the vibration signal segments were analyzed with FFT, and the generated signal spectrum was divided into several segments according to equal integral. The bandwidth coefficient obtained in each segment was the characteristic value. Third, this study proposed that adding appropriate time domain features and further improving the algorithm could improve the accuracy of fault diagnosis. Finally, the main mechanical faults of OLTC were simulated, and the vibration signals were collected to carry out the fault diagnosis experiment of OLTC. The results showed that the FFT-based equal-integral-bandwidth feature extraction method was simple in processing, small in calculation, easy to implement in an embedded system, and had a high accuracy of fault diagnosis.In this paper, a three-dimensional nonlinear delay differential system including Tumour cells, cytotoxic-T lymphocytes, T-helper cells is constructed to investigate the effects of intrinsic recruitment delay and chemotherapy. It is found that the introduction of chemotherapy and time delay can generate richer dynamics in tumor-immune system. In particular, there exists bistable phenomenon and the tumour cells would be cleared if the effect of chemotherapy on depletion of the tumour cells is strong enough or the side effect of chemotherapy on the hunting predator cells is under a threshold. It is also shown that a branch of stable periodic solutions bifurcates from the coexistence equilibrium when the intrinsic recruitment delay of tumor crosses the threshold which is new mechanism, which can help understand the short-term oscillations in tumour sizes as well as long-term tumour relapse. Numerical simulations are presented to illustrate that larger intrinsic recruitment delay of tumor leads to larger amplitude and longer period of the bifurcated periodic solution, which indicates that there exists longer relapse time and then contributes to the control of tumour growth.

We compared the long-term outcome of the watch and wait (WW) strategy and surgery in patients with locally advanced rectal cancer.

This prospective cohort study included 84 patients who achieved clinical complete response (cCR) after neoadjuvant chemoradiotherapy (NCRT). They were divided into the WW group (n=58) and surgery group (SG, n=26). Patients in the SG underwent total mesorectal excision. The study site was the Peking University Cancer Hospital.

Eighty-four patients were included (58 and 26 in the WW group and SG, respectively). A total of 76·9% of the patients in the SG achieved pathological complete response (pCR) and 23·1% of the patients had a residual tumor. The total recurrence and metastasis rate was 15·4% (4/26) in the SG and 18·9% (11/58) in the WW group. There was no significant difference in the recurrence and metastasis rate between the two groups. In the WW group, 9 cases developed tumor regrowth during follow-up and underwent salvage surgery. The overall survival rate of the WW group (96·6% vs 92·3%) was not significantly different from that of the SG (P>0·05). The WW patients also retained their anal sphincter function and avoided surgery-related complications.

The WW strategy is a feasible treatment option in patients with cCR after NCRT. Surgery may not bring benefits to these cCR patients.

The WW strategy is a feasible treatment option in patients with cCR after NCRT. Surgery may not bring benefits to these cCR patients.

For type A aortic dissection (TAAD), antegrade cerebral perfusion (ACP) was proposed as a more physiological method than retrograde cerebral perfusion (RCP) for intra-operative brain protection, but it is still debatable whether antegrade cerebral perfusion (ACP) or retrograde cerebral perfusion (RCP) is related to the better clinical outcome. The present study was undertaken to compare the results in our patients receiving surgery for TAAD with ACP or RCP. The primary aim of this study was focused on the incidence of and the factors associated with surgical mortality, post-operative neurological outcomes and long-term survival.

From February 2001 to March 2019, there were 223 consecutive patients with TAAD treated surgically at our hospital. The median age at presentation was 56 years (range 29-88 years) and 70 patients (31.4%) over 65 years of age. There were 168 patients treated with RCP and 55 patients treated with ACP. The primary endpoints were surgical mortality and neurological outcome. Propensitytive shock, CRI and past history of CAD are independent risk factors for long-term survival.

Although laparoscopic liver resection (LLR) is a common surgical procedure for hepatocellular carcinoma (HCC), its suitability for large HCCs (≥5cm) remains controversial. This study compared surgical outcomes of open hepatectomy with LLR for large HCCs.

A total of 313 patients with HCC who underwent hepatectomy between January 2010 and June 2017 were analyzed retrospectively. Demographic data, short-term outcomes, and long-term survivals were analyzed.

Among patients with large HCCs (n=122), the open group (n=85) had larger tumor sizes (10.91±4.72 vs. 7.45±2.95cm; p<0.001) and more advanced stages (stages 3/4 71.8% vs. 45.9%; p=0.029) than the LLR group (n=37), while LLR group achieved less blood loss (623.24±841.75mL vs. 1091.76±1004.72mL, p=0.014) and shorter LOS (9.00±5.13d vs. 12.82±8.51d, p=0.013). There were no significant differences in complication and mortality rates between groups. The 5-year overall and recurrence-free survival rates between the two groups were not significantly different (p=0.408 and 0.644 respectively). The surgical outcomes showed equal benefit of the two operation types.

With sufficient surgeon experience and appropriate patient selection, LLR is a feasible treatment choice for large HCCs.

With sufficient surgeon experience and appropriate patient selection, LLR is a feasible treatment choice for large HCCs.

Patients are more likely to complete colorectal cancer screening when recommended by a race-concordant healthcare provider. Leveraging virtual healthcare assistants to deliver tailored screening interventions may promote adherence to colorectal cancer screening guidelines among diverse patient populations. The purpose of this pilot study is to determine the efficacy of the Agent Leveraging Empathy for eXams virtual healthcare assistant intervention to increase patient intentions to talk to their doctor about colorectal cancer screening. It also examines the influence of animation and race concordance on intentions to complete colorectal cancer screening.

White and Black adults (N=1,363) aged 50-73 years and not adherent to colorectal cancer screening guidelines were recruited from Qualtrics Panels in 2018 to participate in a 3-arm (animated virtual healthcare assistant, static virtual healthcare assistant, attention control) message design experiment. In 2020, a probit regression model was used to identifes.

Animated virtual healthcare assistants were efficacious compared with the static virtual healthcare assistant and attention control conditions. The influence of race concordance between source and participant was inconsistent across conditions. This warrants additional investigation in future studies given the potential for virtual healthcare assistant‒assisted interventions to promote colorectal cancer screening within guidelines.

Paid sick leave laws have received more attention in recent years as a way to improve public health. This study estimates the impact of paid sick leave laws on the use of preventive services using a quasi-experimental design created by the implementation of Connecticut's paid sick leave law in 2012, the first statewide mandate in the U.S.

Data were obtained from the 2007-2018 Behavioral Risk Factor Surveillance System. KU-0063794 clinical trial The analyses were conducted from spring 2018 to fall 2019. This study applied a difference-in-differences model to examine preventive service use (routine checkups, influenza vaccinations, dental visits, Pap tests, mammograms, and clinical breast examinations) in Connecticut and other New England states before and after the implementation of Connecticut's paid sick leave law in 2012.

The use of preventive services increased in Connecticut compared with other New England states after implementation of Connecticut's paid sick leave law. Specifically, the rate of routine checkups (2.7 percentage points, p<0.