Analysis of Mixed Water Source for Urban Underground Water Pipe Leakage by Using Water Geochemistry Model Calculation

China is a country short of water resources, and the leakage of urban water pipe network not only aggravates the current situation of water shortage, but also causes major accidents such as ground collapse, so it is of great significance to study the discrimination of urban underground pipe leakage. In this paper, the conventional ions and hydrogen and oxygen isotopes of water samples are determined by ion chromatograph and inductively coupled plasma mass spectrometer, and the characteristic factors are selected by cluster analysis and principal component analysis, and the mixed water discrimination model based on conventional ions is established According to the difference of hydrogen and oxygen isotope content between buried pipe water and groundwater, a discrimination model based on hydrogen and oxygen isotope is established, and the two models are combined to discriminate the leakage of buried pipe. The results show that, in terms of conventional ion content characteristics, the water in the pipe network is high in K++Na+ and Cl−, while the shallow groundwater near the pipe network is low in K++Na+ and Cl−, and the accuracy of the discriminant model based on conventional ions reaches 87.5%. In the aspect of hydrogen and oxygen isotope content characteristics, the water in the pipe network is closer to the precipitation line than the shallow groundwater, and establishing a discriminant model based on hydrogen and oxygen isotope can determine the leakage of buried pipes. This study provides a scientific basis for judging the leakage of urban underground pipes.

Online Detection of Watercore Apples by Vis/NIR Full-Transmittance Spectroscopy Coupled with ANOVA Method

Watercore is an internal physiological disorder affecting the quality and price of apples. Rapid and non-destructive detection of watercore is of great significance to improve the commercial value of apples. In this study, the visible and near infrared (Vis/NIR) full-transmittance spectroscopy combined with analysis of variance (ANOVA) method was used for online detection of watercore apples. At the speed of 0.5 m/s, the effects of three different orientations (O1, O2, and O3) on the discrimination results of watercore apples were evaluated, respectively. It was found that O3 orientation was the most suitable for detecting watercore apples. One-way ANOVA was used to select the characteristic wavelengths. The least squares-support vector machine (LS-SVM) model with two characteristic wavelengths obtained good performance with the success rates of 96.87% and 100% for watercore and healthy apples, respectively. In addition, full-spectrum data was also utilized to determine the optimal two-band ratio for the discrimination of watercore apples by ANOVA method. Study showed that the threshold discrimination model established based on O3 orientation had the same detection accuracy as the optimal LS-SVM model for samples in the prediction set. Overall, full-transmittance spectroscopy combined with the ANOVA method was feasible to online detect watercore apples, and the threshold discrimination model based on two-band ratio showed great potential for detection of watercore apples.

Qualitative Discrimination of Intact Tobacco Leaves Based on Near-Infrared Technology

To explore the application of near-infrared (NIR) technology to the quality analysis of raw intact tobacco leaves, a nondestructive discrimination method based on NIR spectroscopy is proposed. A “multiregion + multipoint” NIR spectrum acquisition method is developed, allowing 18 NIR diffuse reflectance spectra to be collected from an intact tobacco leaf. The spectral characteristics and spectral preprocessing methods of intact tobacco leaves are analyzed, and then different spectra (independent or average spectra) and different algorithms (discriminant partial least-squares (DPLS) and Fisher’s discriminant algorithms) are used to construct discriminant models for verifying the feasibility of intact leaf modeling and determining the optimal model conditions. Qualitative discrimination models based on the position, green-variegated (GV), and the grade of intact tobacco leaves are then constructed using the NIR spectra. In the application and verification stage, a multiclassification voting mechanism is used to fuse the results of multiple spectra from a single tobacco leaf to obtain the final discrimination result for that leaf. The results show that the position-GV discrimination model constructed using independent spectra and the DPLS algorithm and the grade discrimination model constructed using independent spectra and Fisher’s algorithm achieve optimal results with intact leaf NIR wavenumbers from 5006–8988 cm−1 and the first-derivative and standard normal variate transformation preprocessing method. Finally, when applied to new tobacco leaves, the position-GV model and the grade model achieve discrimination accuracies of 95.18% and 92.77%, respectively. This demonstrates that the two models have satisfactory qualitative discrimination ability for intact tobacco leaves. This study has established a feasible method for the nondestructive qualitative discrimination of the position, GV, and grade of intact tobacco leaves based on NIR technology.

End-to-End Chinese Dialect Discrimination with Self-Attention

Dialect discrimination has an important practical significance for protecting inheritance of dialects. The traditional dialect discrimination methods pay much attention to the underlying acoustic features, and ignore the meaning of the pronunciation itself, resulting in low performance. This paper systematically explores the validity of the pronunciation features of dialect speech composed of phoneme sequence information for dialect discrimination, and designs an end-to-end dialect discrimination model based on the multi-head self-attention mechanism. Specifically, we first adopt the residual convolution neural network and the multihead self-attention mechanism to effectively extract the phoneme sequence features unique to different dialects to compose the novel phonetic features. Then, we perform dialect discrimination based on the extracted phonetic features using the self-attention mechanism and bi-directional long short-term memory networks. The experimental results on the large-scale benchmark 10-way Chinese dialect corpus released by IFLYTEK 1 show that our model outperforms the state-of-the-art alternatives by large margin.

Development and validation of a discrimination model between primary PLA2R-negative membranous nephropathy and minimal change disease confirmed by renal biopsy

Membranous nephropathy (MN) and minimal change disease (MCD) are two common causes leading to nephrotic syndrome (NS). They have similar clinical features but different treatment strategies and prognoses. M-type phospholipase A2 receptor (PLA2R) is considered as a specific marker of membranous nephropathy. However, its sensitivity is only about 70%. Therefore, there is a lack of effective and noninvasive tools to distinguish PLA2R-negative MN and MCD patients without renal biopsy. A total 949 patients who were pathologically diagnosed as idiopathic MN or MCD were enrolled in this study, including 805 idiopathic MN and 144 MCD. Based on the basic information and laboratory examination of 200 PLA2R-negative MN and 144 MCD, we used a univariate and multivariate logistic regression to select the relevant variables and develop a discrimination model. A novel model including age, albumin, urea, high density lipoprotein, C3 levels and red blood cell count was established for PLA2R-negative MN and MCD. The discrimination model has great differential capability (with an AUC of 0.904 in training group and an AUC of 0.886 in test group) and calibration capability. When testing in all 949 patients, our model also showed good discrimination ability for all idiopathic MN and MCD.

Acoustic individuality in the hissing calls of the male black grouse (Lyrurus tetrix)

Acoustic individuality may well play a big role during the mating season of many birds. Black grouse (Lyrurus tetrix) produces two different long-distance calls during mating on leks: rookooing and hissing calls. The first one represents low frequency series of bubbling sounds and the second one represents hissing sound. This hissing represents a signal not produced by the syrinx. We analyzed 426 hissing calls from 24 individuals in Finland and Scotland. We conducted cross-validated discrimination analyses (DFA). The discrimination model classified each call with almost 78% accuracy (conventional result) and the validated DFA revealed 71% output, that is much higher than classification by chance (4%). The most important variables were Frequency 95%, 1st Quartile Frequency, Aggregate Entropy and Duration 90%. We also tested whether between individual variation is higher than within individual variation using PIC (Potential for individual coding) and we found that all acoustic parameters had PIC > 1. We confirmed that hissing call of black grouse is individually distinct. In comparison to the signals produced by the syrinx, non-vocal sounds have been studied rarely and according to our knowledge, this is the second evidence of vocal individuality in avian hissing sounds which are not produced by syrinx. Individuality in the vocalization of the male black grouse may aid females in mating partner selection, and for males it may enable competitor recognition and assessment. Individually distinct hissing calls could be of possible use to monitor individuals on leks. Such a method could overcome problems during traditional monitoring methods of this species, when one individual can be counted multiple times, because catching and traditional marking is problematic in this species.

Study On Setting Method of Flatness Target Curve of SUNDWIG 20-High Mill Considering Target Crown

The flatness target curve is important in the flatness control theory. The accuracy of flatness target curve is an important factor to determine the load of flatness control means and flatness quality. Aiming at the defect that crown of each pass after rolling cannot be controlled quantitatively in the traditional target curve formulation of cold rolling, a new method considering the target crown was proposed. Specifically, the target crown of each pass can be set by combining the total proportional crown change in hot rolling field to each pass and the instability discrimination model in cold rolling field. the total proportional crown change of incoming material and finished product is allocated to each pass, and the instability discrimination model is applied to ensure the stability of the plate. The purpose of new method is to control of the crown of each pass quantitatively, so that the flatness and thickness of plate can meet the production requirements. Taking SUNDWIG 20-high mill and typical rolling products as an example, the simulation results show that, on the basis of ensuring the flatness and obtaining the minimum available crown after rolling, the model can make the flatness and crown meet the production requirements at the same time and control the crown of each pass after rolling quantitatively by setting the target crown of each pass.

Development and evaluation of two different electronic tongues aiming to the discrimination of cutting agents found in cocaine seized samples

The screening and impurity profiling of drugs, like cocaine, is essential information that provides chemical and/or physical characterization to assist police agencies in understanding the trafficking and identifying drug origin. This work proposes to show the development and applications of two different electronic tongues (e-tongues) on the profiling study of cocaine seized samples. The developed intelligent devices' primary objective is the simple, quick, and remote cocaine classification samples based on the individual cutting agents added. The paper-based colorimetric sensor was fabricated in the lab using chromatographic paper as a substrate, wax printing to produce spot zones of reactions, a smartphone as image detection, and an editing image software to extract the chemical information through RBG values. The voltammetric e-tongue applied a boron-dopped diamond electrode to extract the cutting agents' electrochemical information through the square wave voltammetry (SWV) technique. In any case, both described sensors were coupled to chemometric tools for data analysis to construct the discrimination model. According to the objective, the unsupervised pattern recognition technique, Principal Component Analysis (PCA), was applied to test the capability of the device on individually discriminating the most common cutting agents of cocaine.