Epidemiology of caprine brucellosis in family farms in the south east of Algeria.

This cross-sectional study aimed to estimate the seroprevalence and the potential risk factors of Brucella infection among goats in family farms in the southern east of Algeria. A total of 196 sera samples were randomly collected from 59 family farms and tested in parallel by Rose Bengal test (RBT) and indirect ELISA (iELISA). A structured questionnaire was used to collect information on potential risk factors.

Extrinsic and intrinsic drivers of prevalence and abundance of hard-bodied ticks (Acari: Ixodidae) in one-humped camel ().

Background: Ticks are ectoparasites and can be vectors of a wide range of pathogens, posing significant health risks to livestock. In the Sahara Desert of Algeria, particularly among one-humped camels (), there is a need to better understand the factors influencing tick infestation patterns to improve livestock management and health outcomes.

Objectives: This study aimed to investigate the prevalence, intensity, and abundance of hard-bodied ticks (Acari: Ixodidae) among dromedaries, examining both intrinsic factors (sex, age, coat color) and extrinsic variables (farming systems, vegetation types, climate zones, and elevation) that might influence tick infestation in this region.

Ultrasonic chemical synthesis of zinc-manganese ferrites with improved magnetic properties.

Zinc-Manganese spinel ferrites (ZnMnFeO) are nowadays very attractive magnetic materials for cancer diagnostic and therapy. With the help of intense ultrasonic waves, sonochemical synthesis method was used to prepare stoichiometric and chemically homogenous nanoparticles by varying the manganese content. The crystal structure along with the size and shape of the as-prepared nanoparticles were described using XRD, TEM and FT-IR techniques, while cations distribution was carefully investigated using XPS and Mössbauer spectroscopic techniques and supported with density functional theory calculations.

Physical Activity Integration in Blood Glucose Level Prediction: Different Levels of Data Fusion.

Blood glucose level (BGL) prediction contributes to more effective management of type 1 diabetes. Physical activity (PA) is a crucial factor in diabetes management. It affects BGL, and it is imperative to effectively deploy PA in BGL prediction to support diabetes management systems by incorporating this crucial factor.

Data-driven blood glucose level prediction in type 1 diabetes: a comprehensive comparative analysis.

Accurate prediction of blood glucose level (BGL) has proven to be an effective way to help in type 1 diabetes management. The choice of input, along with the fundamental choice of model structure, is an existing challenge in BGL prediction. Investigating the performance of different data-driven time series forecasting approaches with different inputs for BGL prediction is beneficial in advancing BGL prediction performance.