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Today's operations in the spectrum occur across many disparate and unique devices. For example, a military or commercial maritime platform can have dozens of apertures used for various functions. Utilizing software-defined radios and dynamic analog front ends, we propose that future systems involving multiple applications for RF, virtualize operations to gain performance efficiencies. The concept of virtualization of electromagnetic operations (VEMO) is considered a means to enable flexible use of hardware and spectrum resources to achieve diverse mission requirements in military and commercial settings. This will result in more efficient use of resources, including size/weight/power and integration of objectives across systems that employ the electromagnetic spectrum., Comment: 7 pages, 4 figures

A transportation digital twin represents a digital version of a transportation physical object or process, such as a traffic signal controller, and thereby a two-way real-time data exchange between the physical twin and digital twin. This paper introduces a digital twin approach for adaptive traffic signal control (ATSC) to improve a traveler's driving experience by reducing and redistributing waiting time at an intersection. While an ATSC combined with a connected vehicle concept can reduce waiting time at an intersection and improve travel time in a signalized corridor, it is nearly impossible to reduce traffic delay for congested traffic conditions. To remedy this defect of the traditional ATCS with connected vehicle data, we have developed a digital twin-based ATSC (DT-based ATSC) that considers the waiting time of approaching vehicles towards a subject intersection along with the waiting time of those vehicles at the immediate upstream intersection. We conducted a case study using a microscopic traffic simulation, Simulation of Urban Mobility (SUMO), by developing a digital replica of a roadway network with signalized intersections in an urban setting where vehicle and traffic signal data were collected in real-time. Our analyses reveal that the DT-based ATSC outperforms the connected vehicle-based baseline ATSC in terms of average cumulative waiting time, distribution of drivers' waiting time, and level of services for each approach for different traffic demands and therefore demonstrates our method's superior efficacy.

There are increasing calls for the UCAS personal statement to be reformed. These calls are based on the claim that the current personal statement gives unfair advantages to more privileged applicants within higher education admissions. While this topic has attracted political attention, there is much about the personal statement that remains unknown. Of the evidence that does exist, it suggests that applicants from under-represented backgrounds face larger challenges with their personal statements, and that this results in fewer offers from more selective higher education providers. However, there has been less attention on understanding applicants' perspectives and the specific challenges they face in writing their UCAS personal statement. This report offers two new pieces of evidence to address this gap: (1) By analysing 164 personal statement drafts from 83 applicants from under-represented backgrounds, this report outlines the challenges applicants face when writing a UCAS personal statement. Particular challenges were found on including an appropriate academic discussion, with 83 per cent of drafts failing to supply an evidence-based opinion about a topic in their subject area. Similarly, applicants struggled to organise their statement in an effective way, with 35 per cent of applicants struggling in at least one draft to write with cohesive paragraphs; and (2) Surveys and interviews with under-represented applicants. The applicants describe three main challenges in writing their statements: (a) the opening paragraph; (b) meeting the character limit; and (c) knowing what would impress the admissions tutors. Applicants tell of the large toll of the personal statement, with some spending 30 to 40 hours on it, which requires sacrifices in both their studies and their wider lives. Combining this new evidence and the existing literature, the report then assesses the case for reforming the UCAS personal statement by considering its compatibility with Universities UK and GuildHE's "Fair admissions code of practice." Four options for reform are considered, and it is argued that a series of short-response questions is most compatible with the "Fair admissions code of practice." To be compatible, these short-response questions should assess 'baseline' suitability for a course rather than being used to distinguish between applicants that demonstrate competencies above this. The report concludes with three example short-response questions, arguing that these have considerable potential to increase fairness in higher education admissions. [For the related policy note, see ED630778.]

Recently, research on mental health conditions using public online data, including Reddit, has surged in NLP and health research but has not reported user characteristics, which are important to judge generalisability of findings. This paper shows how existing NLP methods can yield information on clinical, demographic, and identity characteristics of almost 20K Reddit users who self-report a bipolar disorder diagnosis. This population consists of slightly more feminine- than masculine-gendered mainly young or middle-aged US-based adults who often report additional mental health diagnoses, which is compared with general Reddit statistics and epidemiological studies. Additionally, this paper carefully evaluates all methods and discusses ethical issues., Comment: The Seventh Workshop on Computational Linguistics and Clinical Psychology: Improving Access @NAACL 2021; Visual abstract on p. 14

Nanostructured dielectric metasurfaces offer unprecedented opportunities to manipulate light by imprinting an arbitrary phase-gradient on an impinging wavefront. This has resulted in the realization of a range of flat analogs to classical optical components like lenses, waveplates and axicons. However, the change in linear and angular optical momentum associated with phase manipulation also results in previously unexploited forces acting on the metasurface itself. Here, we show that these optomechanical effects can be utilized to construct optical metavehicles - microscopic particles that can travel long distances under low-power plane-wave illumination while being steered through the polarization of the incident light. We demonstrate movement in complex patterns, self-correcting motion, and an application as transport vehicles for microscopic cargo, including unicellular organisms. The abundance of possible optical metasurfaces attests to the prospect of developing a wide variety of metavehicles with specialized functional behavior., Comment: Main Text: 16 pages, 4 figures. Supporting Information: 6 pages, 9 figures

The challenge of inducing and controlling localized fluid flows for generic force actuation and for achieving efficient mass transport in microfluidics is key to the development of next generation miniaturized systems for chemistry and life sciences. Here we demonstrate a methodology for the robust generation and precise quantification of extremely strong flow transients driven by vapor bubble nucleation on spatially isolated plasmonic nanoantennas excited by light. The system is capable of producing peak flow speeds of the order mm/s at modulation rates up to 100 Hz in water, thus allowing for a variety of high-throughput applications. Analysis of flow dynamics and fluid viscosity dependence indicate that the transient originates in the rapid bubble expansion that follows nucleation rather than being strictly thermocapillary in nature., Comment: Main Text: 11 pages, 4 figures Supporting Information: 9 pages, 8 figures. Revised manuscript: further details about experiment and analysis, corrected minor analysis error, further clarification of physical understanding

Ovarian cancer is the most lethal cancer of the female reproductive organs. There are $5$ major histological subtypes of epithelial ovarian cancer, each with distinct morphological, genetic, and clinical features. Currently, these histotypes are determined by a pathologist's microscopic examination of tumor whole-slide images (WSI). This process has been hampered by poor inter-observer agreement (Cohen's kappa $0.54$-$0.67$). We utilized a \textit{two}-stage deep transfer learning algorithm based on convolutional neural networks (CNN) and progressive resizing for automatic classification of epithelial ovarian carcinoma WSIs. The proposed algorithm achieved a mean accuracy of $87.54\%$ and Cohen's kappa of $0.8106$ in the slide-level classification of $305$ WSIs; performing better than a standard CNN and pathologists without gynecology-specific training.