GEISSEHOP medical training recommendations for the treatment rhabdomyosarcoma

Jute fibers from the transgenic lines offer tremendous cost-effective implications from an economic perspective.This research presents optimal factor evaluation for maximum Dyacrodes edulis seed oil (DESO) extraction by applying central composite design (CCD) based on Box-Behnken (BB) experimental design of response surface methodology (RSM) and Artificial neural network (ANN) on feed forward-back propagation (FFBP) of Levenberg Marquardt (LM) training algorithm. Polar solvents (ethanol and combination of methanol and chloroform (M/C)) and non-polar solvents (n-hexane) were used for the extraction. The RSM optimal predicted oil yields were 45.21%, 38.61% and 30.87% while experimental values were 46.01%, 40.71% and 32.45% for n-hexane, ethanol and M/C respectively. The RSM optimum conditions were particle size of 450.67, 451.19 and 450.22μm, extraction time of 55.57, 55.16 and 56.11min and solute/solvent ratio of 0.19, 0.16 and 0.18 g/ml for n-hexane, ethanol and M/C respectively. The ANN-GA optimized conditions showed 5.14, 5.81 and 2.12 % higher DESO yields at 1.10, 0.26 and 0.65% smaller particle sizes, 5.47, 0.30 and 0.62 % faster extraction rate, and 24, 11.11 and 10% more solute requirement, for n-hexane, ethanol and M/C solvents respectively. The particle size was found to be the most significant factor. ANN and RSM established good correlations with the experimental data but ANN showed higher predictive supremacy than RSM based on its higher values of R2 and lower error indices. Also, ANN-GA provided more economical optimal DESO extraction route. The physico-chemical characteristics, functional groups and fatty acid compositions of the seed oil compared with literature values and suggest high commercial values for DESO. progestogen agonist Therefore, the obtained results present a viable method to harness the useful and highly potential seed oil from dyacrodes edulis for many industrial applications.[This corrects the article DOI 10.1016/j.heliyon.2021.e05941.].Tuberculosis (TB) is a re-emerging disease occurring worldwide, resulting in multi-billion-dollar loss and human death annually. The situation is worse in developing countries like Ethiopia, where lower knowledge, attitude, and practice (KAP) of the people is poor about the disease. A questionnaire-based cross-sectional study was conducted to assess livestock owners' KAP level towards human and bovine Tuberculosis in Gondar, Ethiopia. A total of 349 study participants were addressed through a face-to-face interview. Descriptive statistics and Pearson's chi-squares analysis were used to analyze the data and observe the association between outcome (KAP level) and predictor variables (sociodemographic characteristics). Out of the 349 respondents, 223 (63.9%) were males, while 126 (36.1%) were females. The KAP measuring interview indicated that 97.4% of the participants are aware of human tuberculosis, while only 84 (24.1%) know about bovine tuberculosis cause and mode of transmission. Inhalation was reported as the main route of transmission for human TB (41.1%) whereas, 50% of the respondent mentioned inhalation, contact, and ingestion of raw animal products as the main route of TB transmission from animal to human. Among those who have heard of bovine tuberculosis, only 56 (66.7%) of respondents consider bovine tuberculosis as a significant threat to public health. The study showed there is a lower KAP on bovine TB among cattle owners in the study area. Therefore, community health education about the impact of the disease, transmission, control, and prevention should be integrated with one health-oriented education and research to eradicate the disease from the country.The outbreak of COVID-19 has engendered a global health crisis along with diverse impacts on economy, society and environment. Efforts to combat this pandemic have also significantly shot-up the quantity of Bio-medical Waste (BMW) generation. Safe disposal of large quantity of BMW has been gradually posing a major challenge. BMW management is mostly implemented at municipal level following regulatory guidelines defined by respective states and the Union. This article is a narrative of the status of BMW generation, management and regulation in India in the context of COVID-19 crisis. The article is based on comparative analysis of data on BMW generation and management from authentic sources, a systematic literature review and review of news reports. In the current pandemic situation where media has been playing a significant role in highlighting all the concerns related to COVID-19 spread and management. Assessing the ground situation regarding effectiveness of prevailing BMW management facilities, requirement and suggestions can provide insights to the subject with policy implications for India and countries as well. The discussion has been built on different dimensions of BMW management during the pandemic including existing infrastructures, capacity utilisation, policy guidelines, operational practices and waste-handlers aspects. The results on state-wise analysis of reported BMW quantity and active COVID-19 patients also reveal some non-linear relationship between the two variables. Delhi, the National Capital is situated at a better position in terms of BMW management as compared to other studied states. The findings are expected to provide valuable insights to the policy makers and other relevant authorities to evaluate adequateness as well as efficiency quotients of entire BMW management landscape. Some of the critical observations of this article are also expected to offer impetus for enhancing national disaster preparedness in future.Droplet size distribution of dispersed oil in deep-water is critical to the transport and biodegradation of spilled oil in deep-sea. Few studies have focused on the effects of pressure on chemically dispersed oil through experiments. This study thus simulated how the crude oil homogenously pre-dispersed by Corexit 9500A using baffled flasks would behave after being exposed to deep-water conditions. Key factors included dispersant-to-oil ratio (DOR), mixing energy (energy dissipation rate and Kolmogorov microscale), and pressure (up to 150 bar). The variations of pressure were demonstrated to have insignificant effects on the size distribution of pre-dispersed oil. Both the average and medium droplet sizes were correlated negatively with DOR and mixing energy in an established model with a p-value ≤ 0.0011. The log-normal and log-logistic distributions provided a reasonable fit to simulate the droplet size distribution. The two parameters of log-logistic distribution were dependent on DOR and mixing energy with a p-value less then 0.