Optimization of Data-Driven Soil Temperature Forecast—The First Model in Bangladesh

Soil temperature patterns are of great importance for any agro-based economy like Bangladesh since they significantly affect biological, chemical, and physical processes that take place in the soil. Unfortunately, there have been no forecast studies on soil temperature in Bangladesh until now. In this article, we used five tree-based models (decision tree, random forest, gradient boosting tree, a hybrid of decision tree and gradient boosting tree, and a hybrid of random forest and gradient boosting tree) to mine strong links among different meteorological factors and soil temperature at different time window sizes. We found that a hybrid of random forest and gradient boosting tree with all the meteorological factors and a five-day time window is optimal for forecasting soil temperature at depths of 10 cm and 30 cm for all lead times (one, three, or five days), whereas the random forest with the same input scenario and time window is optimal for forecasting soil temperature at a depth of 50 cm for long lead times (five days). Since our study includes the first soil temperature forecast model in Bangladesh, it provides valuable insights for agricultural soil management, fertilizer application, and water resource optimization in Bangladesh, as well as in other South Asian countries that share the same climate patterns as Bangladesh

Optimization Hybrid of Multiple-Lag LSTM Networks for Meteorological Prediction

Residences in poor regions always depend on rain-fed agriculture, so they urgently need suitable tools to make accurate meteorological predictions. Unfortunately, meteorological observations in these regions are usually sparse and irregularly distributed. Conventional LSTM networks only handle temporal sequences and cannot utilize the links of meteorological variables among stations. GCN-LSTM networks only capture local spatial structures through the simple structures of fixed adjacency matrices, and the CNN-LSTM can only mine gridded meteorological observations for further predictions. In this study, we propose an optimization hybrid of multiple-lag LSTM networks for meteorological predictions. Our model can make full use of observed data at partner stations under different time-lag windows and strong links among the local observations of meteorological variables to produce future predictions. Numerical experiments on the meteorological predictions of Bangladesh demonstrate that our networks are superior to the classic LSTM and its variants GCN-LSTM and CNN-LSTM, as well as the SVM and DT

Prevalence of infectious diseases in Sonali chickens at Bogra Sadar Upazila, Bogra, Bangladesh

Objective: The study was conducted to determine the prevalence of infectious diseases in Sonali chickens at Bogra Sadar Upazila, Bogra, Bangladesh. Materials and methods: A total of 258 sick and dead Sonali chickens were examined for the diagnosis of different infectious diseases based on history, clinical findings and postmortem lesions of dead and sacrificed birds. Results: Infectious Bursal disease (IBD) was recorded in 14.72% (n=38/258) cases. Similarly, Newcastle disease (ND), Coccidiosis, Colibacillosis and Mycoplasmosis were recorded in 11.24% (n=29/258), 13.95% (n=36/258), 14.72% (n=38/258), 12.79% (n=33/258) cases, respectively. Mixed infection of IBD, ND and Coccidiosis found in 16.67% (n=43/258) birds. On the other hand, mixed infection of IBD, ND and colibacillosis was recorded in 15.89% (n=41/258) cases. Conclusion: It is concluded that several infectious diseases are commonly present in Sonali chicken in the study area of Bangladesh. Mixed infections are more prevalent as compared to single infection. Proper hygienic management and appropriate vaccination should be taken in consideration for effective control the diseases. Further microbiological and molecular diagnoses are suggested for detail studies of these diseases and their pathogens. [J Adv Vet Anim Res 2017; 4(1.000): 39-44

Selenium Dioxide As an Alternative Reagent for the Direct α‑Selenoamidation of Aryl Methyl Ketones

A general strategy for the preparation of <i>N</i>,<i>N</i>-dialkyl-2-oxo-2-arylethaneselenoamides is described. The single step method involves direct coupling of aryl methyl ketones with secondary amines and selenium dioxide in DMSO. The reactions proceeded smoothly at room temperature to provide a number of the α-oxo-selenoamides in good to excellent yields

Selenium Dioxide As an Alternative Reagent for the Direct α‑Selenoamidation of Aryl Methyl Ketones

A general strategy for the preparation of <i>N</i>,<i>N</i>-dialkyl-2-oxo-2-arylethaneselenoamides is described. The single step method involves direct coupling of aryl methyl ketones with secondary amines and selenium dioxide in DMSO. The reactions proceeded smoothly at room temperature to provide a number of the α-oxo-selenoamides in good to excellent yields

Selenium Dioxide As an Alternative Reagent for the Direct α‑Selenoamidation of Aryl Methyl Ketones

A general strategy for the preparation of <i>N</i>,<i>N</i>-dialkyl-2-oxo-2-arylethaneselenoamides is described. The single step method involves direct coupling of aryl methyl ketones with secondary amines and selenium dioxide in DMSO. The reactions proceeded smoothly at room temperature to provide a number of the α-oxo-selenoamides in good to excellent yields

Selenium Dioxide As an Alternative Reagent for the Direct α‑Selenoamidation of Aryl Methyl Ketones

A general strategy for the preparation of <i>N</i>,<i>N</i>-dialkyl-2-oxo-2-arylethaneselenoamides is described. The single step method involves direct coupling of aryl methyl ketones with secondary amines and selenium dioxide in DMSO. The reactions proceeded smoothly at room temperature to provide a number of the α-oxo-selenoamides in good to excellent yields

Selenium Dioxide As an Alternative Reagent for the Direct α‑Selenoamidation of Aryl Methyl Ketones

A general strategy for the preparation of <i>N</i>,<i>N</i>-dialkyl-2-oxo-2-arylethaneselenoamides is described. The single step method involves direct coupling of aryl methyl ketones with secondary amines and selenium dioxide in DMSO. The reactions proceeded smoothly at room temperature to provide a number of the α-oxo-selenoamides in good to excellent yields