Strong spin-photon coupling in silicon

We report the strong coupling of a single electron spin and a single microwave photon. The electron spin is trapped in a silicon double quantum dot and the microwave photon is stored in an on-chip high-impedance superconducting resonator. The electric field component of the cavity photon couples directly to the charge dipole of the electron in the double dot, and indirectly to the electron spin, through a strong local magnetic field gradient from a nearby micromagnet. This result opens the way to the realization of large networks of quantum dot based spin qubit registers, removing a major roadblock to scalable quantum computing with spin qubits

Accumulation of Immature Langerhans Cells in Human Lymph Nodes Draining Chronically Inflamed Skin

The coordinated migration and maturation of dendritic cells (DCs) such as intraepithelial Langerhans cells (LCs) is considered critical for T cell priming in response to inflammation in the periphery. However, little is known about the role of inflammatory mediators for LC maturation and recruitment to lymph nodes in vivo. Here we show in human dermatopathic lymphadenitis (DL), which features an expanded population of LCs in one draining lymph node associated with inflammatory lesions in its tributary skin area, that the Langerin/CD207+ LCs constitute a predominant population of immature DCs, which express CD1a, and CD68, but not CD83, CD86, and DC–lysosomal-associated membrane protein (LAMP)/CD208. Using LC-type cells generated in vitro in the presence of transforming growth factor (TGF)-β1, we further found that tumor necrosis factor (TNF)-α, as a prototype proinflammatory factor, and a variety of inflammatory stimuli and bacterial products, increase Langerin expression and Langerin dependent Birbeck granules formation in cell which nevertheless lack costimulatory molecules, DC–LAMP/CD208 and potent T cell stimulatory activity but express CCR7 and respond to the lymph node homing chemokines CCL19 and CCL21. This indicates that LC migration and maturation can be independently regulated events. We suggest that during DL, inflammatory stimuli in the skin increase the migration of LCs to the lymph node but without associated maturation. Immature LCs might regulate immune responses during chronic inflammation

Cytophagic histiocytic panniculitis: is it a macrophage activation syndrome in situ?

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Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?

Malaria burden is increasing in sub-Saharan cities because of rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between urban environments and malaria. Additionally, no standardized urban land-use/land-cover has been defined for urban malaria studies. Here, we demonstrate the potential of local climate zones (LCZs) for modeling malaria prevalence rate (PfPR2-10) and studying malaria prevalence in urban settings across nine sub-Saharan African cities. Using a random forest classification algorithm over a set of 365 malaria surveys we: (i) identify a suitable set of covariates derived from open-source earth observations; and (ii) depict the best buffer size at which to aggregate them for modeling PfPR2-10. Our results demonstrate that geographical models can learn from LCZ over a set of cities and be transferred over a city of choice that has few or no malaria surveys. In particular, we find that urban areas systematically have lower PfPR2-10 (5%-30%) than rural areas (15%-40%). The PfPR2-10 urban-to-rural gradient is dependent on the climatic environment in which the city is located. Further, LCZs show that more open urban environments located close to wetlands have higher PfPR2-10. Informal settlements - represented by the LCZ 7 (lightweight lowrise) - have higher malaria prevalence than other densely built-up residential areas with a mean prevalence of 11.11%. Overall, we suggest the applicability of LCZs for more exploratory modeling in urban malaria studies. © 2020 The Author(s). Published by IOP Publishing Ltd.info:eu-repo/semantics/publishe

An open-source automatic survey of green roofs in London using segmentation of aerial imagery

Green roofs can mitigate heat, increase biodiversity, and attenuate storm water, giving some of the benefits of natural vegetation in an urban context where ground space is scarce. To guide the design of more sustainable and climate-resilient buildings and neighbourhoods, there is a need to assess the existing status of green roof coverage and explore the potential for future implementation. Therefore, accurate information on the prevalence and characteristics of existing green roofs is needed, but this information is currently lacking. Segmentation algorithms have been used widely to identify buildings and land cover in aerial imagery. Using a machine learning algorithm based on U-Net (Ronneberger et al., 2015) to segment aerial imagery, we surveyed the area and coverage of green roofs in London, producing a geospatial dataset (https://doi.org/10.5281/zenodo.7603123, Simpson et al., 2023). We estimate that there was 0.23 km2 of green roof in the Central Activities Zone (CAZ) of London, 1.07 km2 in Inner London, and 1.89 km2 in Greater London in the year 2021. This corresponds to 2.0 % of the total building footprint area in the CAZ and 1.3 % in Inner London. There is a relatively higher concentration of green roofs in the City of London, covering 3.9 % of the total building footprint area. Test set accuracy was 0.99, with an F score of 0.58. When tested against imagery and labels from a different year (2019), the model performed just as well as a model trained on the imagery and labels from that year, showing that the model generalised well between different imagery. We improve on previous studies by including more negative examples in the training data and by requiring coincidence between vector building footprints and green roof patches. We experimented with different data augmentation methods and found a small improvement in performance when applying random elastic deformations, colour shifts, gamma adjustments, and rotations to the imagery. The survey covers 1558 km2 of Greater London, making this the largest open automatic survey of green roofs in any city. The geospatial dataset is at the single-building level, providing a higher level of detail over the larger area compared to what was already available. This dataset will enable future work exploring the potential of green roofs in London and on urban climate modelling.</p

Small bowel adenocarcinoma in a patient with Coeliac disease: A case report

Coeliac disease is a chronic inflammatory disease of the gut with increased risk of gastrointestinal malignancy. Although enteropathy T-lymphoma is the most common neoplasm in patient affected by coeliac disease, an increased frequency of small bowel carcinoma has been described. We present a case of jejunal carcinoma in a patient suffering for coeliac disease in which gastrointestinal and extraintestinal symptoms of disease developed although he was treated with a gluten-free diet

Composite Electrodes for Electrochemical Supercapacitors

Manganese dioxide nanofibers with length ranged from 0.1 to 1 μm and a diameter of about 4–6 nm were prepared by a chemical precipitation method. Composite electrodes for electrochemical supercapacitors were fabricated by impregnation of the manganese dioxide nanofibers and multiwalled carbon nanotubes (MWCNT) into porous Ni plaque current collectors. Obtained composite electrodes, containing 85% of manganese dioxide and 15 mass% of MWCNT, as a conductive additive, with total mass loading of 7–15 mg cm−2, showed a capacitive behavior in 0.5-M Na2SO4 solutions. The decrease in stirring time during precipitation of the nanofibers resulted in reduced agglomeration and higher specific capacitance (SC). The highest SC of 185 F g−1 was obtained at a scan rate of 2 mV s−1 for mass loading of 7 mg cm−2. The SC decreased with increasing scan rate and increasing electrode mass