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Introduction: Burn is skin and tissue damage caused by various agents such as fire, scalds, electricity, chemicals, or radiation injuries. Globally, burn injuries pose a substantial public health challenge, with a high risk of mortality and morbidity, accounting for over 310,000 annual deaths. Nearly 75 % of burns in young children result from scald burns and infants have the highest mortality rates. Factors such as large surface area of burn, inhalational injury, poverty, and the presence of sepsis contribute significantly to mortality and morbidity in burns. Objective: To assess the pattern of presentation of pediatric burn injuries and their management outcomes. Methods: A hospital-based retrospective cross-sectional study was conducted. Data were extracted from patient charts, cleaned, coded, checked for completeness, and entered into SPSS version 25 for analysis. Descriptive statistics and logistic regression were used for data analysis, and graphical presentations were utilized to present the result findings. Results: Among the 218 paediatric burn patients admitted to the Addis Ababa Burn, Emergency and Trauma Hospital’s burn unit, 71.1 % had sustained scald burns due to hot water splashes, while 20.2 % of the patients were admitted due to flame burns. Superficial partial thickness burns occurred in 53.6 % of the patients, with the upper extremity and trunk being the most commonly affected sites. Approximately 38.2 % of the patients developed acute complications, with sepsis of the wound focus being the most common. Chronic complications occurred in 30.7 % of patients, primarily in the form of post-burn contractures. A mortality rate of 3.2 % was observed during the admission period with 2.3 % of deaths occurring in children under 5 years and those with major burns. Conclusion & Recommendation: The primary causes of burns in the pediatric age group are predominantly preventable scalds. Children, especially when unsupervised at home, particularly in kitchens, demand meticulous attention and care to mitigate the risk of burn injuries.

This paper presents an advanced method for forecasting flight fares that combines aspect-based sentiment analysis (ABSA) with deep learning techniques, particularly the gated recurrent unit (GRU) model. This approach leverages historical airline ticket transaction data and customer reviews to better understand airline fare dynamics and the impact of customer sentiments on pricing. The aspect analysis extracts key service aspects from customer feedback and provides insightful correlations with airfare. These were further categorized into nine groups for sensitivity analysis, which offered a deeper understanding of how each group influences customers’ attitudes. This ABSA-driven forecasting method marks a departure from traditional models by utilizing sentiment data alongside airline transaction data to improve the predictive accuracy. Its effectiveness is demonstrated through metrics including a root mean square error (RMSE) of 0.0071, a mean absolute error (MAE) of 0.0137, and a coefficient of determination (R2) of 0.9899. Additionally, this model shows strong prediction performance in both short- and long-term fare predictions. It not only advances airfare forecasting methods but provides valuable insights for decision makers of airline industry to refine the pricing strategies or make improvements when it is indicated some services require further attention.

Forecasting flight fares is a critical task in the rapidly expanding civil aviation industry and involves numerous factors. However, traditional airfare prediction systems are ineffective due to the complex and nonlinear relationships of multiple factors, which are not able to accurately account for the impact of different attributes such as time period. To tackle these issues, in this study, we proposed a novel approach that utilizes a deep-learning model, specifically, the Gated Recurrent Unit (GRU), by incorporating 44 decision features. The proposed model is able to capture the intricate relationships between various factors effectively and predict air ticket prices with high accuracy. In the experiments, it was found that the GRU model significantly outperforms not only classic machine learning models but also the MLP and LSTM in terms of assessment indicators of mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). The GRU model is thus promising concerning the fare prediction of flight tickets.

Background: Isolated pulmonic valve endocarditis is a rare heart valve infection, and constitutes about 1% to 2% of all infective endocarditis cases. Modified Duke's criteria were used to diagnose culture negative pulmonic valve endocarditis. Case presentation: A 52-year-old male patient presented with generalized body swelling of 1 month duration associated with prolonged fever, malaise, fatigue, and lassitude. He had productive cough, dyspnea on mild exertion, and reddish discoloration of urine. Upon physical examination, blood pressure (BP) = 140/90 mmHg, pulse rate (PR) = 104 beats per minute, respiratory rate (RR) = 26 breaths per minute, temperature (T0) = 38.3°C, and Sp02 = 90% at ambient air. He had signs of bilateral pleural effusion. Cardiovascular examination revealed tachycardia, raised jugular venous pressure, murmurs of pulmonic regurgitation, and tricuspid regurgitation. There was grade 2 ascites and bilateral leg edema. On laboratory investigation, there were normochromic, normocytic anemia; raised ESR; positive Rheumatoid factor, elevated serum creatinine; and active urinary sediments on urinalysis. Two sets of blood culture were negative on days 1, 5, and 7. Chest-X-ray showed cardiomegaly with bilateral pleural effusion. ECG revealed sinus tachycardia with regular P-waves and QRS complexes. 2D Transthoracic echo showed vegetation on pulmonic valves, pulmonary valve lesions, dilated right atrium and right ventricle, and elevated right ventricular systolic pressure. Abdominal ultrasound revealed enlarged and echogenic kidneys, and ascites. Definitive diagnosis of PVE was made using modified Duke's criteria which was evidenced by 1 major (echo-proven vegetation on pulmonic valve), and 3 minors (suspected congenital pulmonic stenosis, fever, and immunologic phenomena [acute glomerulonephritis, positive rheumatoid factor]). The patient's clinical condition markedly improved after 2 weeks of intravenous antibiotics and loop diuretics, and discharged home after completing 6 weeks of parenteral antibiotics. Conclusion: Modified Duke's criteria could play a major role in the management decision about diagnosis and empiric treatment of infective endocarditis in the absence of positive bacterial cultures. [ABSTRACT FROM AUTHOR]

This paper presents an advanced method for forecasting flight fares that combines aspect-based sentiment analysis (ABSA) with deep learning techniques, particularly the gated recurrent unit (GRU) model. This approach leverages historical airline ticket transaction data and customer reviews to better understand airline fare dynamics and the impact of customer sentiments on pricing. The aspect analysis extracts key service aspects from customer feedback and provides insightful correlations with airfare. These were further categorized into nine groups for sensitivity analysis, which offered a deeper understanding of how each group influences customers' attitudes. This ABSA-driven forecasting method marks a departure from traditional models by utilizing sentiment data alongside airline transaction data to improve the predictive accuracy. Its effectiveness is demonstrated through metrics including a root mean square error (RMSE) of 0.0071, a mean absolute error (MAE) of 0.0137, and a coefficient of determination (R2) of 0.9899. Additionally, this model shows strong prediction performance in both short- and long-term fare predictions. It not only advances airfare forecasting methods but provides valuable insights for decision makers of airline industry to refine the pricing strategies or make improvements when it is indicated some services require further attention. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Hand injuries constitute a major proportion of trauma emergencies in developing countries. The hand establishes the individual in society, allowing them to meet social and economic responsibilities. Previously hand traumas accounted for 12% of major limb traumas in Addis Ababa, Ethiopia; but data on the specific types of tissue injuries and pattern of occurrence of these injuries over the years is limited. METHODS: a retrospective study of sampled 178 patients with hand injury that presented to Yekatit 12 Hospital with hand injuries was done by reviewing the patient's medical records. RESULTS: hand trauma is the second commonest injury following burns that present to the Plastic and Reconstructive Surgery unit in Yekatit 12 hospital. It commonly occurs in males with ratio of 4:1. Average age of patients was 24.5 years. The right hand was more commonly injured than the left hand. Home and fall accidents were commonest cause of injury followed by machine injuries. Commonly occurring injuries were tendon injuries followed by fingertip injuries. The number of patients presenting to the hospital with hand injuries has doubled over the two year study period. CONCLUSION: the number of hand injury cases that presented to the hospital has doubled over the two years study period. Types of hand injuries presenting to the hospitals ranged from simple lacerations to deep tissue injuries requiring long duration of treatment and rehabilitation which has an impact on the productivity of the younger age group that was identified as the most at risk population.

Depression is a psychiatric disorder accountable for high death, morbidity, destructive health behaviors, missing occupation efficiency, and enlarged health care consumption. The presence of miRNAs in brain tissues and the potential of postmortem brain samples to recognize the severity of depressive and peripheral tissues provide a promising approach for the wide regulatory use of miRNA. Because of the inherent restrictions associated with obtaining brain tissue in vivo, the use of postmortem brain tissue may confuse by an unlimited postmortem gap and prior medication exposure. Therefore, this review aims to assess the potential broad applications of micro-RNA and its current advancement in depression. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the treatment potential of gradual hydroponics planted with Duranta erecta in the removal of pathogens from domestic wastewater. Two experimental and control units were configured in series. Each unit contains three bioreactors and was arranged in a cascaded configuration. The two experimental units used both plant and media, but the two control units used only media to treat the wastewater. Gravel and polyester sponge were used as media. Experimental unit 1 and control unit 1 used gravel as media; however, experimental unit 2 and control unit 2 used polyester sponges as media. The experiment was operated at hydraulic retention times of 1, 3, 5, and 7 days in a continuous mode. The performance of the hydroponic system was evaluated by characterizing the influent and effluent quality using standard methods. At optimum hydraulic retention time (7 days), the average removal of experimental units 1 and 2 was 98.7% and 89.8% for heterotrophic bacteria, 96.2% and 86.8% for total coliform, and 92.9% and 84.0% for fecal coliform, respectively. Analysis of variance showed that there was a significant difference (P < 0.05) between the two experimental and control units in removing pathogens, but no significant difference (P > 0.05) was observed between the two experimental units and between the two control units. Heterotrophic bacteria and coliforms were satisfactorily removed from domestic wastewater via a gradual hydroponic system. Hence, the hydroponic treatment system planted with Duranta erecta has a promising potential in the removal of pathogens from domestic wastewater in developing countries including Ethiopia. [ABSTRACT FROM AUTHOR]

Soil fertility depletion due to land degradation and poor cropping diversity have resulted in poor crop yield in sub‐Saharan Africa. On‐farm experiments were conducted to determine the effects of conservation agriculture (CA)‐based maize (Zea mays L.)–legume cropping systems and conventional tillage (CT) on soil properties and yield of maize. The experiments were laid out in a randomized complete block design with three replications. The experiments were continued for 3 yr from 2012 to 2014. The treatments were: CT with monoculture maize (CT‐M), CA with monoculture maize (CA‐M), CA‐based maize–common bean (Phaseolus vulgaris L.) intercropping (CA‐M+CB), CA‐based maize–cowpea (Vigna unguiculata L.) intercropping (CA‐M+CP) and CA‐based maize–common bean rotation (CA‐M–CB).Weed infestation in CA‐based maize–legume cropping systems reduced over the years. Application of CA‐based maize–legume cropping systems increased soil organic matter, total nitrogen, available phosphorus (Ava.P), and soil water infiltration rate by 37, 54, 12.3, and 327%, respectively, over CT‐M. Maize grain yield increased by 54% in CA‐M–CB over CT. The highest production efficiency was obtained from CA‐M–CB. In conclusion, CA‐M–CB followed by CA‐based maize–legume intercropping were the best soil management practices as elucidated in higher soil fertility and stable yield. However, future research on CA‐based cropping systems should be executed under various agro‐ecologies and crop types. Core Ideas: Conservation agriculture‐based maize–legume systems increased organic matter by 37% over conventional tillage.Weed infestation in conservation agriculture declined across the years.Conservation agriculture‐based crop rotation increased maize grain yield by 54% over conventional tillage.Conservation agriculture‐based crop rotation showed maximum production efficiency.Conservation agriculture‐based maize–bean intercropping gave a more stable yield. [ABSTRACT FROM AUTHOR]