Impacts, Monitoring and Management of Forest Pests and Diseases

Forest pests have diverse negative impacts on forestry economy, ecosystem services, biodiversity, and sustainable ecosystem management. The first step towards effectively managing forest pests would be to monitor their occurrence and assess their impact on forest ecosystems. The monitoring results can provide basic information for effective management strategies. The data from monitoring programs can result in the development of new methods for monitoring, assessing impact, and developing management techniques. This special issue aims to share information to assist in the effective management of forest pests, by understanding the responses of forest pests to natural and anthropogenic changes, and discussing new studies on the monitoring, assessment, and management of forest pests. The fourteen papers included in this issue focus on monitoring, assessing, and managing forest pests, including one editorial providing an overall idea of the monitoring, assessment and management of forest pests, two articles reviewing long-term changes in forest pests and forests, four papers focusing on the monitoring of forest pests, three papers on the assessment of forest pests, and four papers on the management of forest pests. These papers provide a better understanding of the structures and processes in forest ecosystems and fundamental information for the effective management of forest pests

Nanotechnology for Early Cancer Detection

Vast numbers of studies and developments in the nanotechnology area have been conducted and many nanomaterials have been utilized to detect cancers at early stages. Nanomaterials have unique physical, optical and electrical properties that have proven to be very useful in sensing. Quantum dots, gold nanoparticles, magnetic nanoparticles, carbon nanotubes, gold nanowires and many other materials have been developed over the years, alongside the discovery of a wide range of biomarkers to lower the detection limit of cancer biomarkers. Proteins, antibody fragments, DNA fragments, and RNA fragments are the base of cancer biomarkers and have been used as targets in cancer detection and monitoring. It is highly anticipated that in the near future, we might be able to detect cancer at a very early stage, providing a much higher chance of treatment

Display screens with variable refresh rate

Device displays of a mobile device such as a smartphone or tablet have capabilities to support different refresh rates. For optimal operation, the refresh rate of the screen of a mobile device can be refreshed based on the image or frame of video being displayed and on certain other conditions. This disclosure describes low-complexity, low-latency techniques to seamlessly transition between different screen refresh rates with minimal-to-zero changes in display settings

DBN-Mix: Training Dual Branch Network Using Bilateral Mixup Augmentation for Long-Tailed Visual Recognition

There is growing interest in the challenging visual perception task of learning from long-tailed class distributions. The extreme class imbalance in the training dataset biases the model to prefer recognizing majority class data over minority class data. Furthermore, the lack of diversity in minority class samples makes it difficult to find a good representation. In this paper, we propose an effective data augmentation method, referred to as bilateral mixup augmentation, which can improve the performance of long-tailed visual recognition. The bilateral mixup augmentation combines two samples generated by a uniform sampler and a re-balanced sampler and augments the training dataset to enhance the representation learning for minority classes. We also reduce the classifier bias using class-wise temperature scaling, which scales the logits differently per class in the training phase. We apply both ideas to the dual-branch network (DBN) framework, presenting a new model, named dual-branch network with bilateral mixup (DBN-Mix). Experiments on popular long-tailed visual recognition datasets show that DBN-Mix improves performance significantly over baseline and that the proposed method achieves state-of-the-art performance in some categories of benchmarks

Fabrication of Microstructure Array using the Projection Microstereolithography System

Microstereolithography technology is similar to the conventional stereolithography process and enables to fabricate a complex 3D microstructure. This is divided into scanning and projection type according to aiming at precision and fabrication speed. The scanning MSL fabricates each layer using position control of laser spot on the resin surface, whereas the projection MSL fabricates one layer with one exposure using a mask. In the projection MSL, DMD used to generate dynamic pattern consists of micromirrors which have per side. The fabrication range and resolution are determined by the field of view of the DMD and the magnification of the projection lens. If using the projection lens with high power, very fine microstructures can be fabricated. In this paper, the projection MSL system adapted to a large surface for array-type fabrication is presented. This system covers the meso range, which is defined as the intermediate range between micro and macro, with a resolution of a few . The fabrication of array-type microstructures has been demonstrated to verify the performance of implemented system