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This paper proposes a physics-informed neural network (PINN) for predicting the early-age time-dependent behaviors of prestressed concrete beams. The PINN utilizes deep neural networks to learn the time-dependent coupling among the effective prestress force and the several factors that affect the time-dependent behavior of the beam, such as concrete creep and shrinkage, tendon relaxation, and changes in concrete elastic modulus. Unlike traditional numerical algorithms such as the finite difference method, the PINN directly solves the integro-differential equation without the need for discretization, offering an efficient and accurate solution. Considering the trade-off between solution accuracy and the computing cost, optimal hyperparameter combinations are determined for the PINN. The proposed PINN is verified through the comparison to the numerical results from the finite difference method for two representative cross sections of PSC beams. [ABSTRACT FROM AUTHOR]

Background: Malnutrition is associated with adverse outcomes in patients on chronic haemodialysis. Thus, identifying accurate methods for diagnosing malnutrition is essential. The present retrospective study investigated the utility of the new Global Leadership Initiative on Malnutrition (GLIM) criteria in patients undergoing chronic haemodialysis. Methods: Phase angle and fat‐free mass index (FFMI) were derived using bioelectrical impedance analysis. Malnutrition was determined when the subjects had at least one phenotypic criterion (weight loss, low body mass index [BMI] or FFMI). Results: This study included 103 patients undergoing chronic haemodialysis and 46 (44.7%) patients were diagnosed as malnourished. Malnutrition determined using the GLIM criteria was associated with increased risks of all‐cause death (hazard ratio = 3.0, p = 0.044) and infection requiring hospitalisation (hazard ratio = 2.4, p = 0.015), independent of age, sex and comorbidities. However, malnutrition was not related to major adverse cardiovascular events (p = 0.908). We further evaluated the longitudinal changes in phenotypic parameters. Subjects with median levels of high‐sensitivity C‐reactive protein exceeding 5 mg L–1 exhibited decreased body weight and BMI (p = 0.015 and 0.016, respectively). In addition, body weight, BMI and FFMI were reduced in subjects with a median protein catabolic rate of < 1.0 mg kg–1 day–1, even after adjustment for age, sex and comorbidities (p = 0.026, 0.053 and 0.039, respectively). Conclusions: Malnutrition assessed using the GLIM criteria could be a useful predictor of mortality and infection in patients on chronic haemodialysis. To improve nutritional status, approaches for decreasing inflammation and increasing protein intake are needed. Key points: The present study retrospectively investigated the usefulness of the Global Leadership Initiative on Malnutrition (GLIM) criteria for patients with end‐stage renal disease receiving chronic haemodialysis.The GLIM criteria‐defined malnutrition was associated with increased incidences of all‐cause death and infection requiring hospitalisation.In the longitudinal data, subjects with higher levels of high‐sensitivity C‐reactive protein and total carbon dioxide exhibited decreased body weight and body mass index (BMI), conversely, those with higher normalised protein catabolic rate exhibited increases in body weight, BMI and fat‐free mass index over time. [ABSTRACT FROM AUTHOR]

The authors describe the advantages and drawbacks of nailing over the dynamic hip screw for the fixation of hip fractures. The technical pitfalls of nailing and the tips to avoid failure of fixation in nailing have been discussed.