Novel Approach for Statistical Interpretation: A Case Study from Long-Term Crop Production Experiments (Hungary)

In recent decades, the agricultural sector has witnessed rapid technological interventions from field to the production stage. Thus, the importance of these technological interventions must be strictly evaluated. The traditional statistical method often deems low statistical differences as a significant one, which cannot be considered effective from different perspectives. In this sense, the aim of this research was to develop a new statistical method for evaluating agricultural experiments based on different criteria; hence, the significant importance of the technological interventions can be clearly determined. Data were collected from of a long-term (13-year) crop production experiment (Central Europe, Hungary), which involved five different fertilization levels, along with non-fertilized treatment (control), two irrigation treatments (irrigated and non-irrigated), and 15–20 genotypes of maize. The output of this research showed that the classic statistical approach for testing the significant differences among treatments should be accompanied with our new suggested approach (i.e., professional test), which reflect whether treatments were professionally effective or not. Also, results showed that good statistical background is not enough for interoperating the analysis of agricultural experiments. This research suggested that erroneous conclusions can be avoided by merging classical and professional statistical tests, and correct recommendations could be provided to decision makers and farmers based on their financial resources.

Statistical interpretation of general circulation model: A prospect for automation of medium range local weather forecast in India

The General Circulation Models (GCM), though able to provide reasonably good medium range weather forecast. have comparatively less skill in forecasting location-specific weather. This is mainly due to the poor representation of 16cal topography and other features in these models. Statistical interpretation (SI) of GCM is very essential in order to improve the location-specific medium range local weather forecast. An attempt has been made at the National Centre for Medium Range Weather Forecasting (NCMRWF), New Delhi to do this type of objective forecasting. Hence location-specific SI models are developed and a bias free forecast is obtained. One of the techniques for accomplishing this, is the Perfect Prog. Method (PPM). PPM models for precipitation (quantitative, probability, yes/no) and maximum minimum temperature are developed for monsoon season (June to August) for 10 stations in lndia. These PPM models and the output from the GCM (R-40) operational at NCMRWF, are then used to obtain the SI forecast. An indirect method based upon SI forecast and observed values of previous one or two seasons, for getting bias free forecast is explained. A comparative study of skill of bias free SI and final forecast, with the observed, issued from NCMRWF to 10 Agromet Field Units (AMFU) during monsoon season 1993, has indicated that automation of medium range local weather forecast can be achieved with the help of SI forecast.

Statistical Interpretation and Profiling the Leaching Characteristic of Chromium in the Basic Chrome Sulphate (BCS) Sludge Dumping at Village Khanchandpur-Rania, District Kanpur Dehat, Uttar Pradesh (India)

Without immobilized hazardous waste contaminates soil and groundwater, which can further bio-accumulates and poses serious negative health impact on flora as well as fauna. The present investigation has been conducted to study of leaching behavior of chromium species in immobilized hazardous waste containing Basic Chrome Sulphate (BCS) dumped at dumping site Khanchandpur Kharanja, Rania, Kanpur Dehat district of Uttar Pradesh, India. Results indicated that the pH of sludge ranged from 10.16–11.90 while EC ranged from 840-16160 dSm-1 in a different layer of the dumpsite and significantly varies on increasing depth. A similar trend was also observed in TDS contents which strongly justified the leaching of salts in lower depth. Total Cr concentration (25029.94 mg kg-1) was observed in the top layer which was significantly increased on increasing depth i.e., 36102.0 mg kg-1 and 42811.77 mg kg-1 while TCLP based concentration ( 216.44 mg kg-1 in top layer) was significantly increased on increasing depth i.e., 406.25 mg kg-1 and 517.60 mg kg-1. A similar trend was also observed in total and TCLP hexavalent and trivalent (Cr6+ and Cr3+) chromium concentration. Hierarchical Cluster Analysis is separated all sample based on depth into three different cluster based on dissimilarity. A significant correlation was observed with TCLP Cr6+ in TCLP Cr3+, EC, and TDS at 0.01 levels while EC, TDS, total Cr6+, and TCLP Cr were significant correlated with TCLP Cr3+. The leaching behavior of Cr species was higher as well as increasing of depth in the dumping site.

ỨNG DỤNG GIS VÀ VIỄN THÁM ĐÁNH GIÁ BIẾN ĐỘNG DIỆN TÍCH CÂY CAO SU DO ẢNH HƯỞNG CỦA BÃO SỐ 10 NĂM 2013 TẠI HUYỆN BỐ TRẠCH, TỈNH QUẢNG BÌNH GIAI ĐOẠN 2013-2019

Nghiên cứu này sử dụng ảnh vệ tỉnh Landsat LC8 của các năm 2013, 2014, và 2019 để giải đoán phân loại lớp phủ cây cao su ở huyện Bố Trạch, tỉnh Quảng Bình và đánh giá biến động diện tích cao su sau ảnh hưởng của bão số 10 (tên là Wutip) năm 2013. Kết quả giải đoán còn sử dụng để đánh giá thiệt hại diện tích trồng cây cao su do ảnh hưởng của bão số 10 năm 2013 và biến động diện tích trồng cây cao su giai đoạn 2013-2019. Các số liệu điều tra thực địa, phỏng vấn cán bộ, số liệu báo cáo thứ cấp, tài liệu phục vụ các hội thảo về phát triển cây cao su ở Quảng Bình đã được thu thập để hỗ trợ cho công việc phân tích, giải đoán ảnh vệ tinh. Nghiên cứu này kết hợp phương pháp giải đoán ảnh theo định hướng đối tượng kết hợp với thuật toán Maximum Likelihood. Kết quả giải đoán đã được đánh giá, độ chính xác giải đoán tổng thể biến động từ 82-88% và hệ số Kappa biến động từ 0,8-0,87 trong các năm nghiên cứu. Qua thống kê kết quả giải đoán ảnh viễn thám Landsat LC8, diện tích trồng cây cao su tại huyện Bố Trạch, tỉnh Quảng Bình bị thiệt hại đáng kể do ảnh hưởng của bão số 10 năm 2013, hơn 1.500 ha bị thiệt hại. Tuy nhiên, mỗi năm diện tích cây sao su được khôi phục lại và trồng mới tại huyện Bố Trạch, do đó sau bão số 10 năm 2013, diện tích cây cao su tăng lên đáng kể từ năm 2014-2019, hơn 2.500 ha. ABSTRACT This study used Landsat LC8 satellite images of 2013, 2014, and 2019 to interpret the classification of rubber tree landcover in Bo Trach district, Quang Binh province and evaluate changes in rubber area after the impact of storms number 10 (named Wutip) in 2013. The results of interpretation were also used to assess the damage of rubber plantations due to the impact of typhoon number 10 in 2013 and changes in rubber plantation area in the period of 2013- 2019. Data from field surveys, interviews with local staff, secondary report data, and documents of conference on rubber tree development in Quang Binh was collected to support analysis and interpretation. This study combined the object-oriented image analysis method combined with the Maximum Likelihood algorithm. The interpretation results were evaluated, the overall interpretation overall accuracy varied from 82-88% and the Kappa coefficient varied from 0.8-0.87 in the studied years. Through the statistical interpretation results of the Landsat LC8 detective, the rubber plantation area in Bo Trach district, Quang Binh province was significantly damaged due to the impact of typhoon number 10 in 2013, over 1500 hectares were damaged. However, each year, the area of ​​​​the rubber tree is restored and newly replanted in Bo Trach district, so after the typhoon number 10 in 2013, the area of ​​rubber trees increased significantly from 2014-2019, over 2,500 ha.

Hydrodynamic and Sediment Transport Patterns in the Minho and Douro Estuaries (NW Portugal) Based on ADCP Monitoring Data: Part 2—Statistical Interpretation of Bottom Moored Datasets

Exploratory statistical partitioning methods (K-means Clustering analysis) were applied to ADCP monitoring datasets collected inside the Douro and Minho estuaries. This analysis is aimed to discriminate ADCP acoustic responses according to the variations of the suspended particles within the ensonified medium. Based on the interpretation of the results, this work establishes general sediment transport patterns at both estuaries’ exits under continuously varying river flows and tidal amplitudes recorded during a summer dry seasonal scenario (September 2005) and winter high river discharge (January/February 2007) conditions. Results confirm the already known present scarcity of (sandy) sediment export from the Douro and Minho estuaries into the inner shelf and the consequent sediment depletion of the adjacent littoral, with no effective contribution of the Douro and some evidence of sand export observed at the Minho outlet during the winter of 2007.

Fast Algorithms for LS and LAD-Collaborative Regression

With the development of modern science and technology, it is easy to obtain a large number of high-dimensional datasets, which are related but different. Classical unimodel analysis is less likely to capture potential links between the different datasets. Recently, a collaborative regression model based on least square (LS) method for this problem has been proposed. In this paper, we propose a robust collaborative regression based on the least absolute deviation (LAD). We give the statistical interpretation of the LS-collaborative regression and LAD-collaborative regression. Then we design an efficient symmetric Gauss–Seidel-based alternating direction method of multipliers algorithm to solve the two models, which has the global convergence and the Q-linear rate of convergence. Finally we report numerical experiments to illustrate the efficiency of the proposed methods.

Nodal/SMAD2 and Bone Morphogenic Protein 4 RNA Expression in Microgravity. Implications for Spacial Orientation Signaling in Hematopoesis and the Implications for the Hematosuppressive Effects of Space Flight

Introduction: Nodal proteins are members of the TGF alpha family which direct right left orientation in the developing embryo. Nodal/SMAD2 signaling controls BMP4 expression and with canonical Wnt signaling, regulates the posteriorization of the primitive streak, development of the mesoderm, development of early hematopoetic stem cells, and the property of self renewal in adult hematopoiesis. This study investigated the extent that microgravity alters expression of these spatially orienting proteins of BMP4, Nodal, Wnt, and SMAD2 thus influencing the anemia, thrombocytopenia, and immune alteration associated with space flight. Method: The Gene Expression Omnibus Database (GEO) of the National Institutes of Health was accessed to define RNA expression of Nodal, SMAD2, Wnt and BMP4 in hematopoetic cells in microgravity. Initial queries for "Low Gravity" studies resulted in 565 investigations within the GEO Omnibus. Of the 565 studies, the GSE136939, GSE101102, and the GSE101309 datasets were explored which assessed the lymphoid and macrophage cell lines TK6, U937, and Jurkat. RNA expression with normal and microgravity environments were compared. In the U937 cells hypergravity environments were also studied. Nodal, Lefty, Wnt, BMP4, as well as the NODAL signaling cascade proteins of SMAD 1/5, SMAD2, SMAD3, and the inhibitory SMAD 7. Affymetrix Expression Arrays were utilized for the TK^ and Jurkat cells assays. The U937 cell lines were assayed with NimbleGen Human Gene Assay Arrays. Results: Significant decreases in BMP4 expression were seen in microgravity environments (P value, <0.005) where SMAD2 expression was significantly elevated (P value <0.05) in microgravity. Conversely, hypergravity effects on U937 cells resulted in a reverse expression pattern. (BMP4 expression increased while SMAD2 decreased (P value <0.01) ). Comparisons of 14, 12, and 4 expression assays were made in U937, Jurkat, and TK6 cells respectively. LEFTY, NODAL, Wnt, SMA1/5/3/7 expression assays all showed changes in expression, but the small sample numbers resulted in poor statistical power and insignificant P values to detect differences in the RNA expression assessed. Comparisons of the gravitational pressures and time spent in these environments for the cellular cultures resulted in insignificant statistical differences. Conclusions: Microgravity induces decreases in BMP4 RNA expression and increases in SMAD2 RNA expression in TK6, U937, and Jurkat cell as defined by the GSE101309, GSE101102 and GSE136939 datasets. BMP4 is required for stem cell posteriorization, HSC number, and adult hematopoetic self renewal. This diminishment in BMP4 expression in microgravity may result in diminished HSC number and self renewal capacity. This qualitative change in gene expression in microgravity and may be a significant component of the anemia, thrombocytopenia, and immune alterations of space flight. Moreover such changes in RNA expression in microgravity implicates the importance of hematopoetic spacial orientation signals in normal hematopoiesis. Therapeutic targeting of the BMP/SMAD2 pathway in refractory multilineage hematopoetic diseases may prove to be fruitful. Statistical interpretation of the data is hindered by the small number of samples, the cell type, hematopoetic maturation stage of the samples, and microenvironmental differences in the studies utilized in these datasets. If this result is confirmed in future and larger studies, it would have significant biologic and therapeutic implications for long term space flight and the developing concept of spacial hematopoiesis. Disclosures No relevant conflicts of interest to declare.

Green quantitative spectrofluorometric analysis of rupatadine and montelukast at nanogram scale using direct and synchronous techniques

Two green-sensitive spectrofluorometric methods were investigated for assay of rupatadine (RUP) [method I] and its binary mixture with montelukast (MKT) [method II]. Method I depends on measuring native fluorescence of RUP in the presence of 0.10 M H 2 SO 4 and 0.10%w/v sodium dodecyl sulfate at 455 nm after excitation at 277 nm. The range of the first method was 0.20–2.00 µg ml −1 with detection and quantitation limits of 59.00 and 179.00 ng ml −1 , respectively. Method II depends on the first derivative synchronous spectrofluorometry. The derivative intensities were measured for the two drugs in an aqueous solution containing Mcllvaine's buffer pH 2.60 at fixed Δ λ of 140 nm. Each drug was estimated at zero-contribution of the other. The intensity was measured at 261 and 371 nm for RUP and MKT, respectively. The method was linear over 0.10–4.00 and 0.20–1.60 µg ml −1 with limits of detection 31.00 and 66.00 ng ml −1 and limits of quantitation 94.00 and 200.00 ng ml −1 for RUP and MKT, respectively. The method was extended to determine this mixture in laboratory-prepared mixtures and combined tablets. Method validation was performed according to ICH guidelines. Statistical interpretation of data revealed good agreement with the comparison method. Method greenness was confirmed by applying three different assessment tools.

Validity and bias in epidemiological research

Some of the major concepts of validity and bias in epidemiological research are outlined in this chapter. The contents are organized in four main sections: Validity in statistical interpretation, validity in prediction problems, validity in causal inference, and special validity problems in case–control and retrospective cohort studies. Familiarity with the basics of epidemiological study design and a number of terms of epidemiological theory, among them risk, competing risks, average risk, population at risk, and rate, is assumed. Despite similarities, there is considerable diversity and conflict among the classification schemes and terminologies employed in various textbooks. This diversity reflects that there is no unique way of classifying validity conditions, biases, and errors. It follows that the classification schemes employed here and elsewhere should not be regarded as anything more than convenient frameworks for organizing discussions of validity and bias in epidemiological inference. Several important study designs, including randomized trials, prevalence (cross-sectional) studies, and ecological studies, are not discussed in this chapter. Such studies require consideration of the validity conditions mentioned earlier and also require special considerations of their own. A number of central problems of epidemiological inference are also not covered, including choice of effect measures, problems of induction, and causal modelling.