Recent Progress in Improving the Performance of Infrared Photodetectors via Optical Field Manipulations

Benefiting from the inherent capacity for detecting longer wavelengths inaccessible to human eyes, infrared photodetectors have found numerous applications in both military and daily life, such as individual combat weapons, automatic driving sensors and night-vision devices. However, the imperfect material growth and incomplete device manufacturing impose an inevitable restriction on the further improvement of infrared photodetectors. The advent of artificial microstructures, especially metasurfaces, featuring with strong light field enhancement and multifunctional properties in manipulating the light–matter interactions on subwavelength scale, have promised great potential in overcoming the bottlenecks faced by conventional infrared detectors. Additionally, metasurfaces exhibit versatile and flexible integration with existing detection semiconductors. In this paper, we start with a review of conventionally bulky and recently emerging two-dimensional material-based infrared photodetectors, i.e., InGaAs, HgCdTe, graphene, transition metal dichalcogenides and black phosphorus devices. As to the challenges the detectors are facing, we further discuss the recent progress on the metasurfaces integrated on the photodetectors and demonstrate their role in improving device performance. All information provided in this paper aims to open a new way to boost high-performance infrared photodetectors.

BamToCov: an efficient toolkit for sequence coverage calculations

Many genomics applications requires the calculation of nucleotide coverage of a reference or counting how many reads maps in a reference region. Here we present BamToCov, a suite of tools for rapid and flexible coverage calculations relying on a memory efficient algorithm and designed for flexible integration in bespoke pipelines. The tools of the suite will process sorted BAM or CRAM files, allowing to extract coverage information using different filtering approaches. BamToCov tools, unlike existing tools already available, have been developed to require a minimum amount of memory, to be easily integrated in workflows, and to allow for strand-specific coverage analyses. The unique coverage calculation algorithm makes it the ideal choice for the analysis of long reads alignments. The programs and their documentation are freely available at https://github.com/telatin/bamtocov.

Spillage-Adaptive Fixed-Geometry Bump Inlet of Wide Speed Range

In this work, a new spillage-adaptive bump inlet concept is proposed to widen the speed range for hypersonic air-breathing flight vehicles. Various approaches to improve the inlet start-ability are summarized and compared, among which the bump-inlet pattern holds the merits of high lift-to-drag ratio, boundary layer diversion, and flexible integration ability. The proposed spillage-adaptive concept ensures the inlet starting performance by spilling extra mass flow away at low speed number conditions. The inlet presetting position is determined by synthetically evaluating the flow uniformity and the low-kinetic-energy fluid proportion. The numerical results show that the flow spillage of the inlet increases with the inflow speed decrease, which makes the inlet easier to start at low speed conditions (M 2.5–6.0). The effects of the boundary layer on spillage are also studied in this work. The new integration pattern releases the flow spillage potentials of three-dimensional inward-turning inlets by reasonably arranging the inlet compression on the bump surface. Future work will focus on the spillage-controllable design method.

Examining the effects of time of day and sleep on generalization

Extracting shared structure across our experiences allows us to generalize our knowledge to novel contexts. How do different brain states influence this ability to generalize? Using a novel category learning paradigm, we assess the effect of both sleep and time of day on generalization that depends on the flexible integration of recent information. Counter to our expectations, we found no evidence that this form of generalization is better after a night of sleep relative to a day awake. Instead, we observed an effect of time of day, with better generalization in the morning than the evening. This effect also manifested as increased false memory for generalized information. In a nap experiment, we found that generalization did not benefit from having slept recently, suggesting a role for time of day apart from sleep. In follow-up experiments, we were unable to replicate the time of day effect for reasons that may relate to changes in category structure and task engagement. Despite this lack of consistency, we found a morning benefit for generalization when analyzing all the data from experiments with matched protocols (n = 136). We suggest that a state of lowered inhibition in the morning may facilitate spreading activation between otherwise separate memories, promoting this form of generalization.

Masked features of task states found in individual brain networks

Completing complex tasks requires flexible integration of functions across brain regions. While studies have shown that functional networks are altered across tasks, recent work highlights that brain networks exhibit substantial individual differences. Here we asked whether individual differences are important for predicting brain network interactions across cognitive states. We trained classifiers to decode state using data from single person "precision" fMRI datasets across 5 diverse cognitive states. Classifiers were then tested on either independent sessions from the same person or new individuals. Classifiers were able to decode task states in both the same and new participants above chance. However, classification performance was significantly higher within a person, a pattern consistent across model types, datasets, tasks, and feature subsets. This suggests that individualized approaches can uncover robust features of brain states, including features obscured in cross-subject analyses. Individualized approaches have potential to deepen our understanding of brain interactions during complex cognition.

Silicon/2D-material photodetectors: from near-infrared to mid-infrared

Two-dimensional materials (2DMs) have been used widely in constructing photodetectors (PDs) because of their advantages in flexible integration and ultrabroad operation wavelength range. Specifically, 2DM PDs on silicon have attracted much attention because silicon microelectronics and silicon photonics have been developed successfully for many applications. 2DM PDs meet the imperious demand of silicon photonics on low-cost, high-performance, and broadband photodetection. In this work, a review is given for the recent progresses of Si/2DM PDs working in the wavelength band from near-infrared to mid-infrared, which are attractive for many applications. The operation mechanisms and the device configurations are summarized in the first part. The waveguide-integrated PDs and the surface-illuminated PDs are then reviewed in details, respectively. The discussion and outlook for 2DM PDs on silicon are finally given.

Mapping Population Vulnerability and Community Support during COVID-19

Background Disasters such as the COVID-19 pandemic pose an overwhelming demand on resources that cannot always be met by official organisations. Limited resources and human response to crises can lead members of local communities to turn to one another to fulfil immediate needs. This spontaneous citizen-led response can be crucial to a community’s ability to cope in a crisis. It is thus essential to understand the scope of such initiatives so that support can be provided where it is most needed. Nevertheless, quickly developing situations and varying definitions can make the community response challenging to measure. Aim To create an accessible interactive map of the citizen-led community response to need during the COVID-19 pandemic in Wales, UK that combines information gathered from multiple data providers to reflect different interpretations of need and support. Approach We gathered data from a combination of official data providers and community-generated sources to create 14 variables representative of need and support. These variables are derived by a reproducible data pipeline that enables flexible integration of new data. The interactive tool is available online (www.covidresponsemap.wales) and can map available data at two geographic resolutions. Users choose their variables of interest, and interpretation of the map is aided by a linked bee-swarm plot. Discussion The novel approach we developed enables people at all levels of community response to explore and analyse the distribution of need and support across Wales. While there can be limitations to the accuracy of community-generated data, we demonstrate that they can be effectively used alongside traditional data sources to maximise the understanding of community action. This adds to our overall aim to measure community response and resilience, as well as to make complex population health data accessible to a range of audiences. Future developments include the integration of other factors such as well-being.

Method to determine the local load cycles of a blade bearing using flexible multi-body simulation

Conventional methods for designing rolling bearings against fatigue assume that a bearing ring is fully rotating and that the load is ideally distributed over the rolling elements. Blade bearings in wind turbines, are operated under oscillating motions and dynamic loads. The load distribution is strongly dependent on the stiffness of the bearing rings and the surrounding structural components. This has been shown in numerous studies using FEM simulations for static load cases. In this paper a method is presented that reduces the calculation effort of the deformation of the bearing rings, so that a flexible integration into an aeroelastic mbs model of a wind turbine is possible. Thereby an average accuracy of 6.5% between FEM and mbs could be achieved. The model allows the determination of time series of the global load distribution of each raceway. By data processing of the simulation results, the number of load cycles and the maximum contact pressure for individual segments of the raceways could be determined and their fatigue probability could be estimated using the linear damage hypothesis according to Palmgren-Miner.