Energy efficiency in buildings in China: Policies, barriers and opportunities

"China's rising energy demands that are required for its booming economy have made the country one of the biggest emitters of greenhouse gases. The Chinese building sector substantially contributes to the country's CO2emissions. Chinese policy makers have realized that enhancing energy efficiency in buildings (EEB) is a promising approach with regard to combining further economic growth with less energy consumption and environmental impact. They have enacted a wide range of policies to foster energy efficiency within the building sector. While the policies can theoretically unfold a great energy saving potential, their implementation has been weak so far. This study analyzes the existing policies and measures in place in order to promote EEB and examines promoting factors as well as barriers for the implementation of EEB policies. The study comes to the conclusion that the determinants of successful EEB policy implementation in China arise in the fields: legal environment and enforcement, economic parameters for investment, informational and lifestyle aspects as well as the specific organization of the value chain in the housing sector." (author's abstract

DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks

Although deep neural networks have been very successful in image-classification tasks, they are prone to adversarial attacks. To generate adversarial inputs, there has emerged a wide variety of techniques, such as black- and whitebox attacks for neural networks. In this paper, we present DeepSearch, a novel fuzzing-based, query-efficient, blackbox attack for image classifiers. Despite its simplicity, DeepSearch is shown to be more effective in finding adversarial inputs than state-of-the-art blackbox approaches. DeepSearch is additionally able to generate the most subtle adversarial inputs in comparison to these approaches

Patient and caregiver-derived health service improvements for better critical care recovery

No abstract available

Transitions of care after critical illness – challenges to recovery and adaptive problem solving

Objectives: Investigate the challenges experienced by survivors of critical illness and their caregivers across the transitions of care from intensive care to community, and the potential problem-solving strategies used to navigate these challenges. Design: Qualitative design—data generation via interviews and data analysis via the framework analysis method. Setting: Patients and caregivers from three continents, identified through the Society of Critical Care Medicine’s THRIVE international collaborative sites (follow-up clinics and peer support groups). Subjects: Patients and caregivers following critical illness. Interventions: Nil Measurements and Main Results: From 86 interviews (66 patients, 20 caregivers), we identified the following major themes: 1) Challenges for patients—interacting with the health system and gaps in care; managing others’ expectations of illness and recovery. 2) Challenges for caregivers—health system shortfalls and inadequate communication; lack of support for caregivers. 3) Patient and caregiver-driven problem solving across the transitions of care—personal attributes, resources, and initiative; receiving support and helping others; and acceptance. Conclusions: Survivors and caregivers experienced a range of challenges across the transitions of care. There were distinct and contrasting themes related to the caregiver experience. Survivors and caregivers used comparable problem-solving strategies to navigate the challenges encountered across the transitions of care