Real-time instance segmentation of recyclables from highly cluttered construction and demolition waste streams.

Efficient recycling strategies are crucial for mitigating the adverse environmental impacts of escalating construction and demolition waste (CDW). While automated identification via deep-learning is a promising direction, localizing CDW recyclables is uniquely challenging due to significant clutter and compositional complexity. Recognizing that accurate and fast localization is a strong prerequisite for swift robotic action, this study provides a comprehensive assessment of state-of-the-art (s.

Optimally leveraging depth features to enhance segmentation of recyclables from cluttered construction and demolition waste streams.

This paper addresses the critical environmental issue of effectively managing construction and demolition waste (CDW), which has seen a global surge due to rapid urbanization. With the advent of deep learning-based computer vision, this study focuses on improving intelligent identification of valuable recyclables from cluttered and heterogeneous CDW streams in material recovery facilities (MRFs) by optimally leveraging both visual and spatial features (depth). A high-quality CDW RGB-D dataset was curated to capture MRF stream complexities often overlooked in prior studies, and comprises over 3500 images for each modality and more than 160,000 dense object instances of diverse CDW materials with high resource value.

Effectiveness of Hand Self-Shiatsu to Promote Sleep in Young People with Chronic Pain: a Case Series Design.

Background: Sleep problems exist for up to 30% of young people, and increase in the case of those with chronic pain. Because exclusive pharmacological management of sleep problems for children with pain is contraindicated, the development of appropriate non-pharmacological sleep interventions is a significant, largely unmet, need.

Purpose: This study examined whether the application of a standardized hand self-shiatsu (HSS) intervention within a population of young people with chronic pain would be associated with improved objectively and subjectively measured sleep.

A Pilot Study to Determine the Consistency of Simultaneous Sleep Actigraphy Measurements Comparing All Four Limbs of Patients with Parkinson Disease.

Wrist actigraphy is a form of objective sleep measurement that has gained a central role in sleep research and clinical settings. Guidelines for actigraphy recommend placing the monitor on the non-dominant wrist, however, this potentially will be the most involved limb for someone with Parkinson disease, and so alternative placement would be preferred. To-date, there is little published about sleep actigraphy use in Parkinson disease (PD).

Oxalate crystal deposition disease.

In addition to monosodium urate, calcium pyrophosphate dihydrate, and apatite crystals, oxalate crystals are less often found in synovial fluids in association with acute or chronic arthritis. Oxalate crystal deposition disease is seen in patients with primary hyperoxaluria types 1 and 2 (PH1 and 2) and in patients with end-stage renal disease managed with long-term dialysis. Oxalate crystal deposits are found mainly in kidneys, bone, skin, and vessels, and less often inside the joints.