The HDIN Dataset: A Real-World Indoor UAV Dataset with Multi-Task Labels for Visual-Based Navigation

Supervised learning for Unmanned Aerial Vehicle (UAVs) visual-based navigation raises the need for reliable datasets with multi-task labels (e.g., classification and regression labels). However, current public datasets have limitations: (a) Outdoor datasets have limited generalization capability when being used to train indoor navigation models; (b) The range of multi-task labels, especially for regression tasks, are in different units which require additional transformation. In this paper, we present a Hull Drone Indoor Navigation (HDIN) dataset to improve the generalization capability for indoor visual-based navigation. Data were collected from the onboard sensors of a UAV. The scaling factor labeling method with three label types has been proposed to overcome the data jitters during collection and unidentical units of regression labels simultaneously. An open-source Convolutional Neural Network (i.e., DroNet) was employed as a baseline algorithm to retrain the proposed HDIN dataset, and compared with DroNet’s pretrained results on its original dataset since we have a similar data format and structure to the DroNet dataset. The results show that the labels in our dataset are reliable and consistent with the image samples

Oocyte stage-specific effects of MTOR determine granulosa cell fate and oocyte quality in mice.

MTOR (mechanistic target of rapamycin) is a widely recognized integrator of signals and pathways key for cellular metabolism, proliferation, and differentiation. Here we show that conditional knockout (cKO) of Mtor in either primordial or growing oocytes caused infertility but differentially affected oocyte quality, granulosa cell fate, and follicular development. cKO of Mtor in nongrowing primordial oocytes caused defective follicular development leading to progressive degeneration of oocytes and loss of granulosa cell identity coincident with the acquisition of immature Sertoli cell-like characteristics. Although Mtor was deleted at the primordial oocyte stage, DNA damage accumulated in oocytes during their later growth, and there was a marked alteration of the transcriptome in the few oocytes that achieved the fully grown stage. Although oocyte quality and fertility were also compromised when Mtor was deleted after oocytes had begun to grow, these occurred without overtly affecting folliculogenesis or the oocyte transcriptome. Nevertheless, there was a significant change in a cohort of proteins in mature oocytes. In particular, down-regulation of PRC1 (protein regulator of cytokinesis 1) impaired completion of the first meiotic division. Therefore, MTOR-dependent pathways in primordial or growing oocytes differentially affected downstream processes including follicular development, sex-specific identity of early granulosa cells, maintenance of oocyte genome integrity, oocyte gene expression, meiosis, and preimplantation developmental competence. Proc Natl Acad Sci U S A 2018 Jun 5; 115(23):E5326-E5333

Driver emotion recognition framework based on electrodermal activity measurements during simulated driving conditions

An extensive variety of wellbeing frameworks had been introduced in modern vehicles a decade ago. Traction control, auto-braking, and anti-sleep systems are significant innovations that are presumed to be superior over human reaction. However, accident rates in Malaysia have yet to be fully reduced. In fact, in 2013, nearly one million enlisted vehicles were involved in road accidents, with damages reaching over RM9.3 billion. Meanwhile, a car is a system that encompasses the road, the vehicle, and the driver. At present, roads and vehicles have gained immense stability, but the driver remains as the most fragile component of this system. Electrodermal activity (EDA) was used in this study to investigate stress and anger as primary emotions leading to possible accidents involving the driver. A simulated driving assignment with preset neutral, stress, and anger scenarios was developed for emotional stimulation. A total of 20 subjects were included in this experiment. Acquired EDA signals were bandpass-filtered at 0.5 Hz to 2 Hz and subjected to short-time Fourier transform. Then, their mean, median, and variance of power spectral density were extracted. The parameters obtained were statistically analyzed with two-sample f-test. EDA readings from drivers demonstrated significant differences among neutral-stress, neutral-anger, and stress-anger simulated driving scenarios. The dataset was also divided into two groups (10-10) for training and testing of support vector machine classifier at 10-fold cross-validation. The classification accuracy was 85% each for neutral-stress and neutral-anger and 70% for stress-anger

Roadmap on perovskite light-emitting diodes

In recent years, the field of metal-halide perovskite emitters has rapidly emerged as a new community in solid-state lighting. Their exceptional optoelectronic properties have contributed to the rapid rise in external quantum efficiencies (EQEs) in perovskite light-emitting diodes (PeLEDs) from <1% (in 2014) to over 30% (in 2023) across a wide range of wavelengths. However, several challenges still hinder their commercialization, including the relatively low EQEs of blue/white devices, limited EQEs in large-area devices, poor device stability, as well as the toxicity of the easily accessible lead components and the solvents used in the synthesis and processing of PeLEDs. This roadmap addresses the current and future challenges in PeLEDs across fundamental and applied research areas, by sharing the community’s perspectives. This work will provide the field with practical guidelines to advance PeLED development and facilitate more rapid commercialization

Roadmap on Perovskite Light-Emitting Diodes

In recent years, the field of metal-halide perovskite emitters has rapidly emerged as a new community in solid-state lighting. Their exceptional optoelectronic properties have contributed to the rapid rise in external quantum efficiencies (EQEs) in perovskite light-emitting diodes (PeLEDs) from <1% (in 2014) to approaching 30% (in 2023) across a wide range of wavelengths. However, several challenges still hinder their commercialization, including the relatively low EQEs of blue/white devices, limited EQEs in large-area devices, poor device stability, as well as the toxicity of the easily accessible lead components and the solvents used in the synthesis and processing of PeLEDs. This roadmap addresses the current and future challenges in PeLEDs across fundamental and applied research areas, by sharing the community's perspectives. This work will provide the field with practical guidelines to advance PeLED development and facilitate more rapid commercialization.Comment: 103 pages, 29 figures. This is the version of the article before peer review or editing, as submitted by an author to Journal of Physics: Photonics. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from i