Data-driven and machine-learning based prediction of wave propagation behavior in dam-break flood

The computational prediction of wave propagation in dam-break floods is a long-standing problem in hydrodynamics and hydrology. Until now, conventional numerical models based on Saint-Venant equations are the dominant approaches. Here we show that a machine learning model that is well-trained on a minimal amount of data, can help predict the long-term dynamic behavior of a one-dimensional dam-break flood with satisfactory accuracy. For this purpose, we solve the Saint-Venant equations for a one-dimensional dam-break flood scenario using the Lax-Wendroff numerical scheme and train the reservoir computing echo state network (RC-ESN) with the dataset by the simulation results consisting of time-sequence flow depths. We demonstrate a good prediction ability of the RC-ESN model, which ahead predicts wave propagation behavior 286 time-steps in the dam-break flood with a root mean square error (RMSE) smaller than 0.01, outperforming the conventional long short-term memory (LSTM) model which reaches a comparable RMSE of only 81 time-steps ahead. To show the performance of the RC-ESN model, we also provide a sensitivity analysis of the prediction accuracy concerning the key parameters including training set size, reservoir size, and spectral radius. Results indicate that the RC-ESN are less dependent on the training set size, a medium reservoir size K=1200~2600 is sufficient. We confirm that the spectral radius \r{ho} shows a complex influence on the prediction accuracy and suggest a smaller spectral radius \r{ho} currently. By changing the initial flow depth of the dam break, we also obtained the conclusion that the prediction horizon of RC-ESN is larger than that of LSTM

Transcending the Silos through Project Management Office: Knowledge Transactions, Brokerage Roles, and Enabling Factors

Organisations often suffer from knowledge flow gaps between operational and strategic management levels, leaving much knowledge trapped within operations’ boundaries. Prior studies viewed the project management office (PMO) as a knowledge broker that can enhance the interaction between these levels. However, they take a single-faceted knowledge brokering perspective that fails to define the specific knowledge brokering roles of the PMO and offer highly fragmentary evidence on the associated enabling factors. To fill this void, we draw on the brokerage theory to develop a comprehensive theoretical framework in which we define specific knowledge brokering roles of the PMO and delineate their enabling factors for facilitating multidirectional knowledge transactions. We elaborate on three sets of knowledge brokering roles, each of which corresponds to one of three categories of knowledge transactions. Our model shows how PMOs can broker knowledge trapped in organisational silos by balancing bottom-up experiential learning with top-down deliberate learning while maintaining horizontal knowledge synchronisation

TeaDiseaseNet: multi-scale self-attentive tea disease detection

Accurate detection of tea diseases is essential for optimizing tea yield and quality, improving production, and minimizing economic losses. In this paper, we introduce TeaDiseaseNet, a novel disease detection method designed to address the challenges in tea disease detection, such as variability in disease scales and dense, obscuring disease patterns. TeaDiseaseNet utilizes a multi-scale self-attention mechanism to enhance disease detection performance. Specifically, it incorporates a CNN-based module for extracting features at multiple scales, effectively capturing localized information such as texture and edges. This approach enables a comprehensive representation of tea images. Additionally, a self-attention module captures global dependencies among pixels, facilitating effective interaction between global information and local features. Furthermore, we integrate a channel attention mechanism, which selectively weighs and combines the multi-scale features, eliminating redundant information and enabling precise localization and recognition of tea disease information across diverse scales and complex backgrounds. Extensive comparative experiments and ablation studies validate the effectiveness of the proposed method, demonstrating superior detection results in scenarios characterized by complex backgrounds and varying disease scales. The presented method provides valuable insights for intelligent tea disease diagnosis, with significant potential for improving tea disease management and production

Descriptions of two new species of Phaecadophora Walsingham, 1900 (Lepidoptera, Tortricidae, Olethreutinae) from China

Two new species of the genus Phaecadophora, P. dactylina sp. nov. and P. vascularis sp. nov., are described from the southwest China. Photographs of the adults and the genitalia are provided. Keys to the species of the genus based on the male and female genitalia are given

Fabrication and characterisation of periodically poled lithium niobate waveguide using femtosecond laser pulses

We present in this letter the fabrication and characterization of thermally stable type II waveguides in Z-cut periodically poled lithium niobate crystals. The waveguides were fabricated by using a femtosecond laser and were utilized for second harmonic generation. Our experiments have shown that a quasiphase matching wavelength of 1548.2nm, a tuning bandwidth of 2nm, and a tuning temperature range of 150.4±1.6°C can be achieved

Identification of Metabolites and Metabolic Pathways Related to Treatment with Bufei Yishen Formula in a Rat COPD Model Using HPLC Q-TOF/MS

As a traditional Chinese medicine, Bufei Yishen Formula (BYF) is widely used in China as an effective treatment for chronic obstructive pulmonary disease (COPD). Because of the component complexity and multiple activities of Chinese herbs, the mechanism whereby BYF affects COPD is not yet fully understood. Herein, pulmonary function experiments and histomorphological assessments were used to evaluate the curative effect of BYF, which showed that BYF had an effect on COPD. Additionally, a high performance liquid chromatography quadrupole time-of-flight mass spectrometry (HPLC QTOF/MS) metabonomics method was used to analyze the mechanism of the actions of BYF on rats with COPD induced by a combination of bacteria and smoking. Partial least squares discriminate analysis (PLS-DA) was used to screen biomarkers related to BYF treatment. Candidate biomarkers were selected and pathways analysis of these metabolites showed that three types of metabolic pathways (unsaturated fatty acid metabolism-related pathways, phenylalanine metabolism-related pathways, and phospholipid metabolism-related pathways) were associated with BYF treatment. Importantly, arachidonic acid and related metabolic pathways might be useful targets for novel COPD therapies

Establishment of Three Rapid Visual Detection Methods for Burkholderia gladioli pv. cocovenenans Based on Body Temperature Amplification

Three rapid visual methods, namely chromogenic, fluorescence and test strip, for the rapid detection of Burkholderia gladioli pv. cocovenenans in foods were established based on enzymatic recombinase amplification (ERA). Primers and probes were designed and screened based on the bonM gene of B. gladioli pv. cocovenenans. Then the specificity and sensitivity of the three methods were evaluated, as well as their applicability and accuracy in the detection of commercial food samples. The results showed that three strains of B. gladioli pv. cocovenenans, but not other common foodborne pathogens and other B. gladioli strains, were amplified by the three methods, indicating their good specificity. The detection limits of these methods were all 10-2 ng/μL, and their sensitivity was good. Out of 15 commercial samples, two tested positive by each of these methods with a detection rate of 13.3%. This result was consistent with that of the national standard method, indicating that our methods had good applicability and accuracy. All three methods give results that can be observed by the naked eye after amplification at 37 ℃ for 15 min, which provide a new and simple strategy for the rapid, visual and on-site screening of B. gladioli pv. cocovenenans in foods

Construction, validation and, visualization of a web-based nomogram to identify the best candidates for primary tumor resection in advanced cutaneous melanoma patients

BackgroundExisting studies have shown whether primary site resection (PSR) in cutaneous melanoma (CM) patients with stage IV is controversial. Our study aimed to identify the clinical characteristics of CM patients with stage IV who benefited from PSR on a population-based study.MethodsWe retrospectively reviewed stage IV CM patients in the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015. Patients were divided into surgical and non-surgical groups according to whether PSR was performed or not. According to the median cancer-specific survival (CSS) time of the non-surgery group, the surgical group was divided into the surgery-benefit group and the non-surgery-benefit group. Multivariate cox regression analysis was used to explore independent CSS prognostic factors in the surgical group. Then, based on the independent prognostic factors of the surgical group, we established a web-based nomogram based on logistics regression.ResultsA total of 574 stage IV CM patients were included in our study, and 491 (85.60%) patients were included in the surgical group. The clinical characteristics (benefit group and non-benefit group) included age, M stage, lesion location, and ulceration status. These independent prognostic factors were includeed to construct a web-based nomogram.ConclusionsWe constructed a web-based nomogram. This model was suitable for identifying the best candidates suitable for PSR in stage IV CM patients

Bufei Yishen Granules Combined with Acupoint Sticking Therapy Suppress Inflammation in Chronic Obstructive Pulmonary Disease Rats: Via JNK/p38 Signaling Pathway

The present study was initiated to explore the mechanism of the effects of Bufei Yishen granules combined with acupoint sticking therapy (Shu-Fei Tie) on inflammation regulated by c-Jun N-terminal kinase (JNK) and p38 MAPK signaling in COPD rats. Seventy-two rats were divided into healthy control (Control), Model, Bufei Yishen (BY), acupoint sticking (AS), Bufei Yishen + acupoint sticking (BY + AS), and aminophylline (APL) groups (n=12 each). COPD rats were exposed to cigarette smoke and bacteria and were given the various treatments from weeks 9 through 20; all animals were sacrificed at the end of week 20. MCP-1, IL-2, IL-6, and IL-10 concentrations in BALF and lung tissue as well as JNK and p38 mRNA and protein levels in lung were measured. The results showed that all the four treatment protocols (BY, AS, BY + AS, and APL) markedly reduced the concentrations of IL-2, IL-6, and MCP-1 and levels of JNK and p38 MAPK mRNA, and the effects of Bufei Yishen granules combined with acupoint sticking therapy were better than acupoint sticking therapy only and aminophylline. In conclusion, the favorable effect of Bufei Yishen granules combined with Shu-Fei Tie may be due to decreased inflammation through regulation of the JNK/p38 signaling pathways