Balanced hydropower and ecological benefits in reservoir-river-lake system: An integrated framework with machine learning and game theory.

The negative impacts of large hydroelectric reservoirs on downstream ecosystems have attracted worldwide attention. Few attempts have been made to dynamically predict ecological benefits and rationally negotiation in the reservoir-river-lake (RRL) system. This study addresses these gaps by developing an integrated framework with machine learning and game theory to balanced hydropower and ecological benefits.

Recurrent infection triggered encephalopathy syndrome in a pediatric patient with mutation and severe acute respiratory syndrome coronavirus 2 infection.

Introduction: Acute necrotizing encephalopathy (ANE), a fatal subtype of infection-triggered encephalopathy syndrome (ITES), can be triggered by many systemic infections. gene mutations were associated with recurrent ANE.

Case Presentation: Here we report a 1-year-old girl with recurrent ITES and mutation.

Pressure eye: In-bed contact pressure estimation via contact-less imaging.

Computer vision has achieved great success in interpreting semantic meanings from images, yet estimating underlying (non-visual) physical properties of an object is often limited to their bulk values rather than reconstructing a dense map. In this work, we present our pressure eye (PEye) approach to estimate contact pressure between a human body and the surface she is lying on with high resolution from vision signals directly. PEye approach could ultimately enable the prediction and early detection of pressure ulcers in bed-bound patients, that currently depends on the use of expensive pressure mats.

Case Report: Immune reconstitution inflammatory syndrome after hematopoietic stem cell transplantation for severe combined immunodeficiency.

We report a case of immune reconstitution inflammatory syndrome (IRIS) after hematopoietic stem cell transplantation (HSCT). The patient had sever bacillus Calmette-Guerin (BCG) vaccine-caused disseminated infection and had received allogeneic HSCT for X-linked severe combined immunodeficiency disease. After HSCT, complicated by treatment-responding veno-occlusive disease and acute graft-versus-host disease, at the time when immunosuppressants were withdrawn, the patient experienced recurrent fever accompanied by elevated inflammatory indicators.

Privacy-Preserving In-Bed Pose and Posture Tracking on Edge.

In-bed behavior monitoring is commonly needed for bed-bound patient and has long been confined to wearable devices or expensive pressure mapping systems. Meanwhile, vision-based human pose and posture tracking while experiencing a lot of attention/success in the computer vision field has been hindered in terms of usability for in-bed cases, due to huge privacy concerns surrounding this topic. Moreover, the inference models for mainstream pose and posture estimation often require excessive computing resources, impeding their implementation on edge devices.

Simultaneously-Collected Multimodal Lying Pose Dataset: Enabling In-Bed Human Pose Monitoring.

Computer vision field has achieved great success in interpreting semantic meanings from images, yet its algorithms can be brittle for tasks with adverse vision conditions and the ones suffering from data/label pair limitation. Among these tasks is in-bed human pose monitoring with significant value in many healthcare applications. In-bed pose monitoring in natural settings involves pose estimation in complete darkness or full occlusion.

In-Bed Pose Estimation: Deep Learning With Shallow Dataset.

This paper presents a robust human posture and body parts detection method under a specific application scenario known as in-bed pose estimation. Although the human pose estimation for various computer vision (CV) applications has been studied extensively in the last few decades, the in-bed pose estimation using camera-based vision methods has been ignored by the CV community because it is assumed to be identical to the general purpose pose estimation problems. However, the in-bed pose estimation has its own specialized aspects and comes with specific challenges, including the notable differences in lighting conditions throughout the day and having pose distribution different from the common human surveillance viewpoint.

Construction of amorphous TiO₂/BiOBr heterojunctions via facets coupling for enhanced photocatalytic activity.

Facets coupled BiOBr with amorphous TiO2 composite photocatalysts are synthesized via an in situ direct growth approach under microwave irradiation. XRD, SEM and HRTEM characterizations indicate that the heterointerface between BiOBr and amorphous TiO2 occurs mainly on the {001} facets of BiOBr. BET and TEM verify that the heterojunctions possess higher specific surface areas and smaller amorphous TiO2 particle size than bare BiOBr and amorphous TiO2, exhibiting the inhibition function of BiOBr on the growth of TiO2 particles.