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Spin defects in foils of hexagonal boron nitride are an attractive platform for magnetic field imaging, since the probe can be placed in close proximity to the target. However, as a III-V material the electron spin coherence is limited by the nuclear spin environment, with spin echo coherence times of ∽100 ns at room temperature accessible magnetic fields. We use a strong continuous microwave drive with a modulation in order to stabilize a Rabi oscillation, extending the coherence time up to ∽ 4μs, which is close to the 10 μs electron spin lifetime in our sample. We then define a protected qubit basis, and show full control of the protected qubit. The coherence times of a superposition of the protected qubit can be as high as 0.8 μs. This work establishes that boron vacancies in hexagonal boron nitride can have electron spin coherence times that are competitive with typical nitrogen vacancy centres in small nanodiamonds under ambient conditions.

For widespread adoption, public security and surveillance systems must be accurate, portable, compact, and real-time, without impeding the privacy of the individuals being observed. Current systems broadly fall into two categories -- image-based which are accurate, but lack privacy, and RF signal-based, which preserve privacy but lack portability, compactness and accuracy. Our paper proposes mmSense, an end-to-end portable miniaturised real-time system that can accurately detect the presence of concealed metallic objects on persons in a discrete, privacy-preserving modality. mmSense features millimeter wave radar technology, provided by Google's Soli sensor for its data acquisition, and TransDope, our real-time neural network, capable of processing a single radar data frame in 19 ms. mmSense achieves high recognition rates on a diverse set of challenging scenes while running on standard laptop hardware, demonstrating a significant advancement towards creating portable, cost-effective real-time radar based surveillance systems., Comment: Accepted by ICASSP 2023

We outline the role of forward and inverse modelling approaches in the design of human--computer interaction systems. Causal, forward models tend to be easier to specify and simulate, but HCI requires solutions of the inverse problem. We infer finger 3D position $(x,y,z)$ and pose (pitch and yaw) on a mobile device using capacitive sensors which can sense the finger up to 5cm above the screen. We use machine learning to develop data-driven models to infer position, pose and sensor readings, based on training data from: 1. data generated by robots, 2. data from electrostatic simulators 3. human-generated data. Machine learned emulation is used to accelerate the electrostatic simulation performance by a factor of millions. We combine a Conditional Variational Autoencoder with domain expertise/models experimentally collected data. We compare forward and inverse model approaches to direct inference of finger pose. The combination gives the most accurate reported results on inferring 3D position and pose with a capacitive sensor on a mobile device.

Additional file 2. Algorithm for TB REACH active case finding through contact tracing, Nepal, 2018.

Multilingual abstracts in the six official working languages of the United Nations. (PDF 314 kb)

Multilingual abstracts in the six official working languages of the United Nations. (PDF 278Â kb)

This work was supported by grants from Ministerio de Ciencia e Innovación-Spain and the European Union (FP7- Microenvimet)

A scalable optical quantum information processor is likely to be a waveguide circuit with integrated sources, detectors, and either deterministic quantum-logic or quantum memory elements. With microsecond coherence times, ultrafast coherent control, and lifetime-limited transitions, semiconductor quantum-dot spins are a natural choice for the static qubits. However their integration with flying photonic qubits requires an on-chip spin-photon interface, which presents a fundamental problem: the spin-state is measured and controlled via circularly-polarised photons, but waveguides support only linear polarisation. We demonstrate here a solution based on two orthogonal photonic nanowires, in which the spin-state is mapped to a path-encoded photon, thus providing a blue-print for a scalable spin-photon network. Furthermore, for some devices we observe that the circular polarisation state is directly mapped to orthogonal nanowires. This result, which is physically surprising for a non-chiral structure, is shown to be related to the nano-positioning of the quantum-dot with respect to the photonic circuit.

Kallikrein-related peptidase 4 (KLK4) is one of the 15 members of the human KLK family and a trypsin-like, prostate cancer-associated serine protease. Signaling initiated by trypsin-like serine proteases are transduced across the plasma membrane primarily by members of the protease-activated receptor (PAR) family of G protein-coupled receptors. Here we show, using Ca(2+) flux assays, that KLK4 signals via both PAR-1 and PAR-2 but not via PAR-4. Dose-response analysis over the enzyme concentration range 0.1-1000 nM indicated that KLK4-induced Ca(2+) mobilization via PAR-1 is more potent than via PAR-2, whereas KLK4 displayed greater efficacy via the latter PAR. We confirmed the specificity of KLK4 signaling via PAR-2 using in vitro protease cleavage assays and anti-phospho-ERK1/2/total ERK1/2 Western blot analysis of PAR-2-overexpressing and small interfering RNA-mediated receptor knockdown cell lines. Consistently, confocal microscopy analyses indicated that KLK4 initiates loss of PAR-2 from the cell surface and receptor internalization. Immunohistochemical analysis indicated the co-expression of agonist and PAR-2 in primary prostate cancer and bone metastases, suggesting that KLK4 signaling via this receptor will have pathological relevance. These data provide insight into KLK4-mediated cell signaling and suggest that signals induced by this enzyme via PARs may be important in prostate cancer.

Additional file 1. Multilingual abstracts in the five official working languages of the United Nations.

Additional file 3. Algorithm for TB REACH active case finding through TB camps and outpatient department of public hospitals, Nepal, 2018.

Additional file 4. TB REACH districts coverage and costing survey districts, Nepal, 2018.

Additional file 3. Algorithm for TB REACH active case finding through TB camps and outpatient department of public hospitals, Nepal, 2018.

Additional file 4. TB REACH districts coverage and costing survey districts, Nepal, 2018.

The isolates according to geographic location and phenotypic drug resistance. CAR Central African Republic; DRC Democratic Republic of Congo, L1-L4 lineages 1 to 4, (first line drugs) RMP = rifampicin, INH = isoniazid, SM = streptomycin, EMB = ethambutol; (second line drugs) OFL = ofloxacin, KAN = kanamycin, CAP = capreomycin, Et = ethionamide, P = Para-aminosalisylic acid. Table S2. The isolate ENA accession numbers and MIC values. RMP rifampicin, INH isoniazid, SM streptomycin, EMB ethambutol. Table S3. Drug susceptibility profiles for rifampicin, isoniazid, streptomycin and ethambutol. R = resistance, S = sensitive; 13 different profiles were identified across 127 independent isolates; Multi-drug resistant in italics. Table S4. Combinations of mutations and their frequency (N) in drug resistance candidate genes. a) Rifampicin. b) Isoniazid. c) Streptomycin. d) Ethambutol. * single mutation, ** double mutations, *** triple mutations; SNP mutations in a single sample have been aggregated into a “rare” column. Table S5. Predicted effects of mutations. (DOCX 55 kb)

Additional file 1. Multilingual abstracts in the five official working languages of the United Nations.

The isolates according to geographic location and phenotypic drug resistance. CAR Central African Republic; DRC Democratic Republic of Congo, L1-L4 lineages 1 to 4, (first line drugs) RMP = rifampicin, INH = isoniazid, SM = streptomycin, EMB = ethambutol; (second line drugs) OFL = ofloxacin, KAN = kanamycin, CAP = capreomycin, Et = ethionamide, P = Para-aminosalisylic acid. Table S2. The isolate ENA accession numbers and MIC values. RMP rifampicin, INH isoniazid, SM streptomycin, EMB ethambutol. Table S3. Drug susceptibility profiles for rifampicin, isoniazid, streptomycin and ethambutol. R = resistance, S = sensitive; 13 different profiles were identified across 127 independent isolates; Multi-drug resistant in italics. Table S4. Combinations of mutations and their frequency (N) in drug resistance candidate genes. a) Rifampicin. b) Isoniazid. c) Streptomycin. d) Ethambutol. * single mutation, ** double mutations, *** triple mutations; SNP mutations in a single sample have been aggregated into a “rare” column. Table S5. Predicted effects of mutations. (DOCX 55 kb)