Research Paper On Sugarcane Diseaese Detection Model

Harvest infections acknowledgment is one of the extensive concerns looked by the farming business. Notwithstanding, late advancement in visual registering with improved computational equipment has cleared path for computerized illness recognition. Results on openly accessible datasets utilizing Convolutional Neural Network (CNN) models have exhibited its suitability. To research how flow cutting edge order models would act in uncontrolled conditions as would be looked nearby, we gained a dataset of five infections of sugarcane plant taken from fields across various districts of Uttarakhand and  Bihar, India, caught by camera gadgets under various goals and lighting conditions. Models prepared on our sugarcane dataset accomplished a top precision of 93.20% (on testset) and 76.40% on pictures gathered from various confided in online sources, exhibiting the heartiness of this methodology in distinguishing complex examples furthermore, varieties found in practical situations. Besides, to precisely restrict the tainted locales, we utilized two unique sorts of item discovery algorithms YOLO and Faster-RCNN. The two organizations were assessed on our dataset, achieving a top Mean Average Precision score of 58.13% on the test-set. Considering everything, the methodology of utilizing CNN's on an impressively assorted dataset would prepare for mechanized infection acknowledgment frameworks

The Challenge of Managing Mine Action in Jordan

Over the course of two decades, the Hashemite Kingdom of Jordan worked diligently to rid itself of landmines despite monumental challenges. In comparison to other mine-affected countries, the difficulties that Jordan faced may have been miniscule, but for a developing country with minimal natural resources in a very volatile region of the world, the task was enormous. The initial estimate of landmines buried in Jordanian territory was over 300,000, the vast majority of which were laid by the Jordanian military along the kingdom’s western border after the 1967 Arab– Israeli War and along its northern border after the Syrian incursion into Jordan in 1970

National Ownership and Partnerships for Capacity Development

Through the lens of Jordan’s mine-action history, the importance of strong leadership, national ownership and partnerships are detailed here as necessary for capacity development

Transcriptional analyses of adult and pediatric adamantinomatous craniopharyngioma reveals similar expression signatures regarding potential therapeutic targets

Adamantinomatous craniopharyngioma (ACP) is a biologically benign but clinically aggressive lesion that has a significant impact on quality of life. The incidence of the disease has a bimodal distribution, with peaks occurring in children and older adults. Our group previously published the results of a transcriptome analysis of pediatric ACPs that identified several genes that were consistently overexpressed relative to other pediatric brain tumors and normal tissue. We now present the results of a transcriptome analysis comparing pediatric to adult ACP to identify biological differences between these groups that may provide novel therapeutic insights or support the assertion that potential therapies identified through the study of pediatric ACP may also have a role in adult ACP. Using our compiled transcriptome dataset of 27 pediatric and 9 adult ACPs, obtained through the Advancing Treatment for Pediatric Craniopharyngioma Consortium, we interrogated potential age-related transcriptional differences using several rigorous mathematical analyses. These included: canonical differential expression analysis; divisive, agglomerative, and probabilistic based hierarchical clustering; information theory based characterizations; and the deep learning approach, HD Spot. Our work indicates that there is no therapeutically relevant difference in ACP gene expression based on age. As such, potential therapeutic targets identified in pediatric ACP are also likely to have relvance for adult patients

Lead, Cadmium and Copper Levels in Table Eggs

A total of 100 fresh hen's egg samples (pooled samples) including farmers' houses and poultry farms' eggs  were collected for estimation of lead, cadmium and copper levels (50 pooled samples for each type, each pooled was represented by 5 eggs). Poultry farms' egg samples were purchased from different shops and supermarkets, while farmers' houses eggs were purchased from farmers' houses in Assiut Governorate, Egypt. The samples were digested then, analyzed for detection and measurement of lead, cadmium and copper by using ZEE nit 700P Atomic Absorption Spectrophotometer with Graphite Furnace Unit (AASG) (Perkin –Elmer Atomic Absorption Spectrophometry model 2380, USA). Results indicated that incidence of lead, cadmium and copper in farmers' houses egg samples were 96, 12 and 98% while in poultry farms’ egg samples were 98, 32 and 100%, respectively. Moreover, the samples above MPLs for lead in farmers' houses eggs and poultry farms' eggs were 47 (94%) out of 50 examined samples and fortunately all of examined samples contained cadmium and copper below the MPLs (0%) as stated by EOSQC (1993)