Prevalence of foot and mouth disease (FMD) in cattle at Meghna upazila in Comilla in Bangladesh

The present study was performed in the Upazila Veterinary Hospital, Meghna, Comilla during the period from September 2006 to February 2007 to observe the prevalence of Foot and Mouth Disease (FMD) in cattle at Meghna upazila in Comilla. A total of 253 skin diseased cattle head were examined in this study where 109 were males and 144 were females. The prevalence of FMD was 24.51% at Meghna upazila. The effect of age, sex, breed, season and farming system on the incidence rate of the disease was discussed. Seasonal variation on outbreak of this disease was significantly higher. The clinical prevalence of FMD was highest in the month of November (34.69%) and December (36.20%). The males (35.77%) were more susceptible than females (15.97%). The adult cattle (34.18%) were more susceptible compared to heifer (23.43%) and young (09.72%). In breed, 39.18% indigenous breeds and 15.38% crossed breeds were infected by FMD. So, it could be concluded that the rural farming system, adult, male and the indigenous cattle were more susceptible to FMD in winter season

Effectiveness of federated learning and CNN ensemble architectures for identifying brain tumors using MRI images

Medical institutions often revoke data access due to the privacy concern of patients. Federated Learning (FL) is a collaborative learning paradigm that can generate an unbiased global model based on collecting updates from local models trained by client’s data while keeping the local data private. This study aims to address the centralized data collection issue through the application of FL on brain tumor identification from MRI images. At first, several CNN models were trained using the MRI data and the best three performing CNN models were selected to form different variants of ensemble classifiers. Afterward, the FL model was constructed using the ensemble architecture. It was trained using model weights from the local model without sharing the client’s data (MRI images) using the FL approach. Experimental results show only a slight decline in the performance of the FL approach as it achieved 91.05% accuracy compared to the 96.68% accuracy of the base ensemble model. Additionally, same approach was taken for another slightly larger dataset to prove the scalability of the method. This study shows that the FL approach can achieve privacy-protected tumor classification from MRI images without compromising much accuracy compared to the traditional deep learning approach

Períodos de interferência de plantas daninhas na cultura da cenoura em função do espaçamento entre fileiras Periods of weed interference in carrot in function of spacing between rows

Objetivou-se com este trabalho determinar os períodos de interferência das plantas daninhas na cultura da cenoura (Daucus carota), cultivada em dois espaçamentos. O delineamento experimental foi em blocos ao acaso, no esquema fatorial 2 x 14, com quatro repetições. Os tratamentos consistiram na combinação de dois espaçamentos (15 x 6 cm e 20 x 6 cm) e sete períodos iniciais de controle ou convivência da cultura com as plantas daninhas (0, 12, 24, 36, 48, 60 e 72 dias após a emergência). Os períodos críticos de prevenção à interferência (PCPI) foram de 19 a 36 e 18 a 42 dias após emergência da cultura, respectivamente para os espaçamentos de 15 x 6 cm e 20 x 6 cm entre fileiras. O menor espaçamento entre fileiras resultou na redução do período crítico de prevenção à interferência das plantas daninhas em sete dias. A interferência das plantas daninhas durante todo o ciclo reduziu a produtividade de cenoura em até 96%.<br>This work aimed to determine the periods of weed interference in carrot (Daucus carota) cultivated in two spacings (15 x 6 cm and 20 x 6 cm). The experimental design was arranged in a randomized block in a 2 x 14 factorial scheme, with two repetitions. The treatments consisted in the combination of the two spacings and seven initial periods of control or coexistence of the culture with the weeds( 0, 12, 24, 36, 48, 60, and 72 days after emergence). The critical periods of weed interference prevention (CPWIP) were from 19 to 36 and 18 to 42 days after crop emergence, respectively, for spacing rows from 15 x 6 cm to 20 x 6 cm. The shortest spacing between the rows resulted in the reduction of the critical period of weed interference prevention in carrot in seven days. Weed interference throughout the crop cycle reduced crop yield up to 96%