Search results for: Wendu Admasu

Authors: Wendu Admasu, Assefa Sintayehu, Alemu Gezahgne, Zewdu Terefework

Abstract:

Eucalyptus is the most widely planted forest tree species in the world. In Ethiopia, pathogenic fungi pose an increasing threat to Eucalyptus species. Due to limited research, there is insufficient information on the associated diseases and pathogens. This study investigated Eucalyptus diseases, the extent of their damage, and the causal fungal pathogens. A Eucalyptus disease survey was conducted in the Eucalyptus forestry areas of Ethiopia during the growth years 2019/20 and 2020/21. Disease assessment and sampling were carried out in eighteen plantations at nine locations. E. camaldulensis was the most dominant species planted in the surveyed areas. The field study shows a high incidence and severity of canker diseases. Diseased stem and branch samples were collected, cultured on malt extract agar media and studied. The results of morphological and ITS sequence analysis confirmed that the fungal species Neofusicoccum parvum, Lasiodiplodia theobromae, and Aplosporella hesperidica caused the observed canker symptoms. This is the first report of Lasiodiplodia theobromae and Aplosporella hesperidica causing diseases in Eucalyptus plants in Ethiopia. Changes in global climate and environmental factors, such as altitude, are believed to have a strong impact on the susceptibility of Eucalyptus plants to diseases. Strict quarantine practices and continuous monitoring of pathogenic and endophytic fungal species associated with Eucalyptus trees are issued to be prioritized to effectively control and manage the disease.

Keywords: Neofusicoccum, Lasiodiplodia, Aplosporella, pathogenicity, phylogeny, severity

Procedia PDF Downloads 67

Authors: Junhong Li, Danni Cheng, Yaxin Luo, Xiaowei Yi, Ke Qiu, Wendu Pang, Minzi Mao, Yufang Rao, Yao Song, Jianjun Ren, Yu Zhao

Abstract:

Background: The number of multiple cancer patients was increasing, and the impact of prior cancer history on salivary gland cancer patients remains unclear. Methods: Clinical, demographic and pathological information on salivary gland cancer patients were retrospectively collected from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017, and the characteristics and prognosis between patients with a prior cancer and those without prior caner were compared. Univariate and multivariate cox proportional regression models were used for the analysis of prognosis. A risk score model was established to exam the impact of treatment on patients with a prior cancer in different risk groups. Results: A total of 9098 salivary gland cancer patients were identified, and 1635 of them had a prior cancer history. Salivary gland cancer patients with prior cancer had worse survival compared with those without a prior cancer (p<0.001). Patients with a different type of first cancer had a distinct prognosis (p<0.001), and longer latent time was associated with better survival (p=0.006) in the univariate model, although both became nonsignificant in the multivariate model. Salivary gland cancer patients with a prior cancer were divided into low-risk (n= 321), intermediate-risk (n=223), and high-risk (n=62) groups and the results showed that patients at high risk could benefit from surgery, radiation therapy, and chemotherapy, and those at intermediate risk could benefit from surgery. Conclusion: Prior cancer history had an adverse impact on the survival of salivary gland cancer patients, and individualized treatment should be seriously considered for them.

Keywords: prior cancer history, prognosis, salivary gland cancer, SEER

Procedia PDF Downloads 146

Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

Abstract:

We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

Procedia PDF Downloads 153

Authors: Ferah Tesfaye Admasu

Abstract:

Autism Spectrum Disorder (ASD) often presents significant communication challenges, particularly for non-verbal individuals who struggle to express their needs and emotions effectively. Assistive technologies (AT) have emerged as vital tools in enhancing communication abilities for this population. Recent advancements in artificial intelligence (AI) hold the potential to revolutionize the design and functionality of these technologies. This study explores the application of AI in developing intelligent, adaptive, and user-centered assistive technologies for non-verbal individuals with autism. Through a review of current AI-driven tools, including speech-generating devices, predictive text systems, and emotion-recognition software, this research investigates how AI can bridge communication gaps, improve engagement, and support independence. Machine learning algorithms, natural language processing (NLP), and facial recognition technologies are examined as core components in creating more personalized and responsive communication aids. The study also discusses the challenges and ethical considerations involved in deploying AI-based AT, such as data privacy and the risk of over-reliance on technology. Findings suggest that integrating AI into assistive technologies can significantly enhance the quality of life for non-verbal individuals with autism, providing them with greater opportunities for social interaction and participation in daily activities. However, continued research and development are needed to ensure these technologies are accessible, affordable, and culturally sensitive.

Keywords: artificial intelligence, autism spectrum disorder, non-verbal communication, assistive technology, machine learning

Procedia PDF Downloads 19

Authors: Sisay Wondmagegn Molla, Mulugeta Admasu Delele, Tadelle Nigusu Mekonen

Abstract:

It is common to observe quality deterioration and mechanical injury of horticulture products as a result of suboptimal design and handling of the packaging systems. Society uses the old and primitive way of handling horticulture products, which is produced through trial and error This method is known to have many limitations on quality, environmental pollution, labor and cost. Ethiopia stands first in bamboo resources in Africa, which is 67 % of the African and 7 % of the world's bamboo resources. The purpose of this project was to design and develop bamboo-based ventilated horticultural produce crates using validated computational fluid dynamics (CFD). The model was used to predict the airflow and temperature distribution inside the loaded crate. The study included: sizing, collection of the thermo-physical properties, and designing and developing a CFD model of the bamboo-based ventilated horticultural crate. The designed crate (40×30×25cm) had a capacity of about 18 kg, and cold air temperature (130C) was used for cooling the fruit. Airflow in the loaded crate is far from uniform. There is a relatively high-velocity flow at the top, near inlet and near outlet sections, and a relatively low airflow near the center of the loaded crate. The predicted velocity variation within the bulk of the produce was relatively large, it was in the range of 0.04-7m/s. The vented produce package contributed the highest cooling airflow resistance. Similar to the airflow, the cooling characteristics of the product were not uniform. There was a difference in the cooling rate of the produce in the airflow direction and from the top to the bottom section of the loaded crate. The products that were located near the inlet side and top of the bulk showed a faster cooling rate than the rest of the bulk. The result showed that the produced volume average temperature was 17.9°C after a cooling period of 3 hr. It was reduced by 12.05°C. The result showed the potential of the CFD modeling approach in developing the bamboo-based design of horticultural produce crates in terms of airflow and heat transfer characteristics.

Keywords: bamboo, modeling, cooling, horticultural, packaging

Procedia PDF Downloads 23