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Photoluminescent Sensor of Scarification Efficiency of Fodder Plants' Seeds

SENSORS 2023年第1期23卷 106页

作者： Belyakov, Mikhail V. Fed Sci Agroengn Ctr VIM Moscow 109428 Russia

Optoelectronic sensors open up new possibilities for predicting the yield for their possible correction, including increasing the seed germination of forage plants. The luminescent properties of unscarified and scarified seeds of various germination galega, clover and alfalfa are compared. The dependence of germination on the photoluminescence flux is approximated by linear equations with a determination coefficient R-2 = 0.932-0.999. A technological process for analyzing the scarification quality of forage seed plants is proposed, including sample preparation, photoluminescence excitation and registration, amplification of the received electrical signal and determination of germination based on calibration equations. This is followed by a decision on sowing, or re-scarification. The scheme of the scarification quality control device has been developed for which the LED, as well as the radiation receiver and other elements, has been selected according to the energy efficiency criterion. Mechanical scarification of the forage plants' seed surfaces has a significant effect on their photoluminescent properties. The flux increases by 1.5-1.7 times for galega, 2.0-3.0 times for clover and 2.3-3.9 times for alfalfa. linear approximation of the flux dependence on germination with a high coefficient of determination allows us to obtain reliable linear calibration equations. Preliminary mock-up laboratory tests allow us to talk about the developed method's effectiveness and device.

关键词： forage plants seeds scarification germination photoluminescence linear regression model

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Optimal sensor placement for personal inhalation exposure detection in static and dynamic office environments

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BUILDING AND ENVIRONMENT 2023年第1期241卷

作者： Yun, Seoyeon Licina, Dusan Ecole Polytech Fed Lausanne Sch Architecture Civil & Environm Engn Human Oriented Built Environm Lab Lausanne Switzerland

Modern health and productivity concerns related to air pollutant exposure in buildings have sparked the need for occupant-centric monitoring and ventilation control. The existing personal exposure monitoring is often restricted to stationary air quality sensors and static occupancy. This study aims to identify optimal stationary sensor placement that best represents exposure to CO2, PM2.5, and PM10 under static and dynamic office occu-pancies. A total of 48 controlled chamber experiments were executed in four office layouts with variation of occupant numbers (2, 4, 6 or 8), activities (sitting/standing and static/dynamic), ventilation strategies (mixing/ displacement) and air change rates (0.5-0.7 h(-1), 2.4-2.6 h(-1), and 3.8-4.2 h(-1)). The breathing zone concen-tration of a reference occupant was monitored with concurrent measurements at seven stationary locations: front edge of the desk, sides of two desks, two sidewalls, and two exhaust vents. The proximity of sensors to the reference occupant and ventilation rate/strategy were important determinants of personal exposure detection. regression analyses showed that the wall-and desk-mounted CO2 sensors near the occupant (<1 m) best captured CO2 exposure under dynamic-standing activities (R-2 similar to 0.4). The wall immediately behind the seated occupant and the ceiling-mounted exhaust near the standing occupant (<1-1.5 m) were the best sensor place-ments for capturing exposure to particles (R-2=0.8-0.9). Separating static from dynamic occupancy activities resulted in improved exposure prediction by 1.4-6.1x . This study is a step towards provision of practical guidelines on stationary air quality sensor placement indoors with the consideration of dynamic occupancy profiles.

关键词： IAQ sensor placement Personal exposure detection Dynamic activities Ventilation type linear regression model

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Research on the Integration of model Worker Spirit into the Improvement of College Teachers’ Literacy in the Era of Big Data

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Shi, Xiaoqian School of Chemical and Environmental Engineering Pingdingshan University Henan Pingdingshan467000 China

In the era of big data, China’s labor model spirit should not only continue the essence of the past but also show the connotation and practical orientation of the new era. This paper summarizes the dilemmas of teachers’ literacy improvement under the new requirements and proposes a mechanism for improving teachers’ literacy in colleges and universities based on the spirit of model workers. A provincial university was selected as the research subject. Questionnaires were distributed online and offline, and the recovered questionnaires were reviewed and rejected to obtain relevant research data. Pearson’s correlation coefficient and linear regression model were respectively used to empirically analyze the proposed mechanism above. After analysis, the mean value of the implication mechanism, conduction mechanism, feedback mechanism, and safeguard mechanism are all greater than 3, and all of them have a significant correlation with teacher literacy, P © 2024 Xiaoqian Shi, published by Sciendo.

关键词： Correlation coefficient linear regression model Questionnaire Teacher literacy

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The effect of a Durbin-Watson pretest on confidence intervals in regression

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STATISTICA NEERLANDICA 2021年第1期75卷 4-23页

作者： Kabaila, Paul Farchione, Davide Alhelli, Samer Bragg, Nathan La Trobe Univ Dept Math & Stat Melbourne Vic Australia

Consider a linear regression model and suppose that our aim is to find a confidence interval for a specified linear combination of the regression parameters. In practice, it is common to perform a Durbin-Watson pretest of the null hypothesis of zero first-order autocorrelation of the random errors against the alternative hypothesis of positive first-order autocorrelation. If this null hypothesis is accepted then the confidence interval centered on the ordinary least squares estimator is used;otherwise the confidence interval centered on the feasible generalized least squares estimator is used. For any given design matrix and parameter of interest, we compare the confidence interval resulting from this two-stage procedure and the confidence interval that is always centered on the feasible generalized least squares estimator, as follows. First, we compare the coverage probability functions of these confidence intervals. Second, we compute the scaled expected length of the confidence interval resulting from the two-stage procedure, where the scaling is with respect to the expected length of the confidence interval centered on the feasible generalized least squares estimator, with the same minimum coverage probability. These comparisons are used to choose the better confidence interval, prior to any examination of the observed response vector.

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Characterization of Septoria brown spot disease development and yield effects on soybean in Illinois

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CANADIAN JOURNAL OF PLANT PATHOLOGY 2021年第1期43卷 62-72页

作者： Lin, Heng-An Villamil, Maria B. Mideros, Santiago X. Univ Illinois Dept Crop Sci Urbana IL 61801 USA

Brown spot, caused bySeptoria glycinesHemmi, is a highly prevalent foliar disease of soybean (Glycine max(L.) Merr.). Despite its wide distribution, the development of Septoria brown spot and its relationship with yield reduction remain poorly characterized. In this study, we conducted replicated multi-location inoculated field trials to characterize the disease development and evaluated the relationship between Septoria brown spot and soybean yield. Multiple components of disease and yield were rated weekly to characterize disease development. Fungicide treatments had a significant effect on ratings of vertical progress of the disease and chlorotic area at the end of the season. There were also significant differences between the fungicide treatments for the Area Under the Disease Progress Curve (AUDPC) of all the disease components, including necrotic area and defoliation rate. Soybean yield was negatively correlated with the vertical progress of the disease (r= -0.36). The vertical progress was the best linear predictor of yield with an R-2 = 0.08 for the end of the season rating and an R-2 = 0.2 for the AUDPC. A variance component analysis of the data showed that location was the most critical factor, illustrating the large effect of local environmental conditions on the disease. There was no statistically significant effect of the fungicide treatments on yield. Power analyses indicated that at least eight locations are needed to detect an effect of 269 kg ha(-1). Our results provide useful information in the characterization of the disease development and for estimations of yield damage.

关键词： fungicides late-season disease complex linear regression model power analysis Septoria glycines soybean

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Predictive model estimating the decrease of postoperative gastrointestinal quality of life index (GIQLI) in patients after elective laparoscopic sigmoid resection for diverticular disease

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LANGENBECKS ARCHIVES OF SURGERY 2021年第5期406卷 1571-1580页

作者： Posabella, Alberto Steinemann, Daniel Christian Droeser, Raoul Andre Varathan, Nadshathra Aycicek, Selin Goksu Nocera, Fabio von Flue, Markus Rotigliano, Niccolo Fuglistaler, Ida St Clara Hosp Univ Ctr Gastrointestinal & Liver Dis Dept Visceral Surg Clarunis Kleinriehenstr 30 CH-4058 Basel Switzerland Univ Hosp Kleinriehenstr 30 CH-4058 Basel Switzerland Univ Hosp Basel Dept Surg Spitalstr 23 CH-4031 Basel Switzerland

Background Growing consideration in quality of life (QoL) has changed the therapeutic strategy in patients suffering from diverticular disease. Patients' well-being plays a crucial role in the decision-making process. However, there is a paucity of studies investigating patients' or surgery-related factors influencing the postoperative gastrointestinal function. The aim of this study was to investigate in a predictive model patients or surgical variables that allow better estimation of the postoperative gastrointestinal QoL. Methods This observational study retrospectively analyzed patients undergoing elective laparoscopic sigmoidectomy for diverticulitis between 2004 and 2017. The one-time postoperative QoL was assessed with the gastrointestinal quality of life index (GIQLI) in 2019. A linear regression model with stepwise selection has been applied to all patients and surgery-related variables. Results Two hundred seventy-two patients with a mean age of 62.30 +/- 9.74 years showed a mean GIQLI of 116.39 +/- 18.25 at a mean follow-up time of 90.4 +/- 33.65 months. Women (n=168) reported a lower GIQLI compared to male (n=104;112.85 +/- 18.79 vs 122.11 +/- 15.81, p<0.001). Patients with pre-operative cardiovascular disease (n=17) had a worse GIQLI (106.65 +/- 22.58 vs 117.08 +/- 17.66, p=0.010). Finally, patients operated less than 5 years ago (n=63) showed a worse GIQLI compared to patients operated more than 5 years ago (n=209;111.98 +/- 19.65 vs 117.71 +/- 17.63, p=0.014). Conclusions Female gender and the presence of pre-operative cardiovascular disease are predictive for a decreased postoperative gastrointestinal QoL. Furthermore, patients' estimation of gastrointestinal functioning seems to improve up to 5 years after surgery.

关键词： Laparoscopic sigmoid resection Gastrointestinal quality of life GIQLI Bowel function linear regression model

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Development status evaluation and path analysis of regional clean energy power generation in China

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ENERGY STRATEGY REVIEWS 2023年 49卷

作者： Li, Xinxin Pan, Lingying Zhang, Jianyun Univ Shanghai Sci & Technol Business Sch Jungong Rd 516 Shanghai 200093 Peoples R China China Energy Technol & Econ Res Inst Beijing 102211 Peoples R China

Due to differences in resource endowments, levels of economic development, energy structure, and effects of policy implementation, the level of clean energy development in different regions in China is nonuniform. To achieve carbon peaking and carbon neutrality, it is necessary to clarify the law of clean energy development and formulate policies tailored to local conditions. Based on relevant data on clean energy power, this paper establishes a system for evaluating the levels of clean energy development in each region in China by the entropy method and quantitatively analyzes the key factors influencing regional clean energy development. Based on this, the development characteristics of clean energy in different regions are discussed, and four historical paths for developing clean energy are summarized. The findings reveal the following: (1) overall, clean energy development in most regions in China is proceeding at a satisfactory pace. The contribution of resource endowment to clean energy development is considerable in Southwest and Northwest China. (2) The paths involved in the regional development of clean energy can be categorized into rising, declining, stable, and fluctuating types. (3) Currently, clean energy development in China remains largely dependent on resource endowments and is restricted by the capacity of traditional large-scale energy generation units. (4) In the foreseeable future, a sound and effective trading mechanism for the clean energy market will play an important role in economically developed regions and promote a higher level of development and generation of clean energy.

关键词： Regional clean energy development Entropy method linear regression model Development status evaluation Development path analysis

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Partial least squares regression with compositional response variables and covariates

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JOURNAL OF APPLIED STATISTICS 2021年第16期48卷 3130-3149页

作者： Chen, Jiajia Zhang, Xiaoqin Hron, Karel Shanxi Univ Finance & Econ Sch Stat Taiyuan 030006 Shanxi Peoples R China Palacky Univ Fac Sci Dept Math Anal & Applict Math Olomouc Czech Republic

The common approach for regression analysis with compositional variables is to express compositions in log-ratio coordinates (coefficients) and then perform standard statistical processing in real space. Similar to working in real space, the problem is that the standard least squares regression fails when the number of parts of all compositional covariates is higher than the number of observations. The aim of this study is to analyze in detail the partial least squares (PLS) regression which can deal with this problem. In this paper, we focus on the PLS regression between more than one compositional response variable and more than one compositional covariate. First, we give the PLS regression model with log-ratio coordinates of compositional variables, then we express the PLS model directly in the simplex. We also prove that the PLS model is invariant under the change of coordinate system, such as the ilr coordinates with a different contrast matrix or the clr coefficients. Moreover, we give the estimation and inference for parameters in PLS model. Finally, the PLS model with clr coefficients is used to analyze the relationship between the chemical metabolites of Astragali Radix and the plasma metabolites of rat after giving Astragali Radix.

关键词： Compositional data centered log-ratio coefficients partial least squares linear regression model coordinates

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Simple estimation of green area rate using image analysis and quantitative traits related to plant architecture and biomass in rice seedling

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THEORETICAL AND EXPERIMENTAL PLANT PHYSIOLOGY 2021年第3期33卷 225-234页

作者： Jong, Kwang-O. Han, Kwang-Myong Kwak, Son-Il Jang, Yu-Jin Chol-Ho Kim, Kwang -Phil Kim Il Sung Univ Dept Genet Fac Life Sci Taesong Dist Pyongyang North Korea Kim Il Sung Univ Fac Informat Sci Taesong Dist Pyongyang North Korea

Available methods using image analysis (IA) are expensive and evaluated only partally in rice plants in controlled and field conditions. The objectives of this study were to: (i) estimate green area rate per seedling (GAR) in various rice cultivars and lines using new IA software, and (ii) elucidate relationship between GAR and some quantitative traits in seedlings grown at nursery. After taken randomly seedlings grown for 45 days at nursery, digital image of individual seedling was taken using a digital camera. Digital images were processed with IA software using k-means algorithm. After obtained R (red), G (green) and B (blue) values of each pixel from seedling image, these values were transformed into HSB color system. Pixel counts were obtained from HSB data, and GAR was estimated as rate of pixel counts of green area per seedling and pixel counts of input image. Results indicated that GAR was quantitative index and phenotyping trait that can be measured simply by non-destructive method using IA software without any significant alteration of plant morphology. GARs were significantly different among genotypes. GAR was significantly and positively correlated with number of tillers per seedling (NTS), leaf number per seedling (LNS), seedling dry mass (SDM) and aboveground total dry mass (TDM), i. e., aerial biomass in seedling and wasn't significantly correlated with seedling height. Significant level for linear regression of GAR and SDM, TDM related to seedling was shown with high determination coefficients of 0.796-0.8762. GAR had a stronger relationship with SDM and TDM related to biomass than NTS and LNS.

关键词： Correlation coefficient Growth Image-based phenotype linear regression model Nursery Phenotyping

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On the estimation of ridge penalty in linear regression: Simulation and application

KUWAIT JOURNAL OF SCIENCE

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KUWAIT JOURNAL OF SCIENCE 2024年第4期51卷

作者： Khan, Muhammad Shakir Ali, Amjad Suhail, Muhammad Alotaibi, Eid Sadun Alsubaie, Nahaa Eid Islamia Coll Peshawar Peshawar Pakistan Livestock & Dairy Dev Dept Research Wing Peshawar Khyber Pakhtunkhwa Pakistan Univ Agr Dept Stat Peshawar Amir Muhammad Khan Campus Mardan Pakistan Taif Univ AlKhurmah Univ Coll Dept Math POB 11099 Taif 21944 Saudi Arabia

According to existing literature, the ordinary least squares (OLS) estimators are not the best in presence of multicollinearity. The inability of OLS estimators against multicollinearity has paved the way for the development of various ridge type estimators for circumventing the problem of multicollinearity. In this paper improved two-parameter ridge (ITPR) estimators are proposed. A simulation study is used to evaluate the performance of proposed estimators based on minimum mean squared error (MSE) criterion. The simulative results reveal that, based on minimum MSE, ITPR2 was the most efficient estimator compared to the considered estimators in the study. Finally, a real-life dataset is analyzed to demonstrate the applications of the proposed estimators and also checked their efficacy for mitigation of multicollinearity.

关键词： linear regression model Multicollinearity Ridge regression Two parameter ridge estimators Mean square error Monte Carlo simulation Prediction

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