Enhancing door-to-door waste collection forecasting through ML.

We explore the application of machine learning (ML) techniques to forecast door-to-door waste collection, addressing the challenges in municipal solid waste (MSW) management. ML models offer a promising solution to optimize waste collection operations, especially amid growing urban populations and evolving waste generation rates. Leveraging comprehensive data from a northeastern Italian municipality, including various waste types, our study investigates ML algorithms' efficacy in predicting household waste collection requirements.

Empowering Simple Graph Convolutional Networks.

Many neural networks for graphs are based on the graph convolution (GC) operator, proposed more than a decade ago. Since then, many alternative definitions have been proposed, which tend to add complexity (and nonlinearity) to the model. Recently, however, a simplified GC operator, dubbed simple graph convolution (SGC), which aims to remove nonlinearities was proposed.

Treatment of Large Cartilage Defects in the Knee by Hydrogel-Based Autologous Chondrocyte Implantation: Two-Year Results of a Prospective, Multicenter, Single-Arm Phase III Trial.

Objective: To evaluate the clinical outcome of a hydrogel-based autologous chondrocyte implantation (ACI) for large articular cartilage defects in the knee joint.

Design: Prospective, multicenter, single-arm, phase III clinical trial. ACI was performed in 100 patients with focal full-thickness cartilage defects ranging from 4 to 12 cm in size.

Multiresolution Reservoir Graph Neural Network.

Graph neural networks are receiving increasing attention as state-of-the-art methods to process graph-structured data. However, similar to other neural networks, they tend to suffer from a high computational cost to perform training. Reservoir computing (RC) is an effective way to define neural networks that are very efficient to train, often obtaining comparable predictive performance with respect to the fully trained counterparts.

[Derotational Intertrochanteric Osteotomy in Habitual Dislocation of the Patella].

PURPOSE OF THE STUDY The preoperative planning in habitual dislocation of the patella should take into account all pathologies and the procedure should address all abnormalities. One of them might be also the rotational deformity of the femur. The purpose of this prospective study was to confirm the hypothesis that the only correction of pathological femoral anteversion by derotational intertrochanteric osteotomy (in the absence of another pathology) or the correction of femoral anteversion with simultaneous reconstruction of the patellofemoral joint provide adequate stability for the patellofemoral joint, with respect to the elimination of the risk of recurrent dislocation of the patella.