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Abstract Recently, doping guest materials such as quantum dots (QDs) into liquid crystals (LCs) has been of great interest since their addition substantially enhances the properties of LC and opens new avenues for scientific advancement. Here, we report the induction of homeotropic alignment in cells without alignment layers of the negative dielectric nematic liquid crystal, N-(4-Methoxybenzylidene)-4-butylaniline (MBBA) by doping with carbon dots (CDs ∼2.8 ± 0.72 nm). The CDs-MBBA composites (CDs concentration: 0.002, 0.01, 0.03, 0.1 and 0.3 wt%) were investigated using optical polarising microscopy, electro-optical and dielectric techniques. Polarizing optical micrographs and voltage dependent optical transmission revealed the induced homeotropic alignment for all the composites under investigation. Interestingly, the least concentrated sample, 0.002 wt% exhibited partial homeotropic alignment. However, due to light leakage, the optical transmission value below threshold voltage was relatively higher than the rest of the composites. MBBA is a negative dielectric material, hence the application of a voltage across the cell was able to switch the alignment from a dark to a bright state for all composites. However, above a certain voltage (>threshold voltage), the bright state produced some instabilities. The value of dielectric permittivity was observed to decrease with increasing concentration, confirming the effect of CDs in producing homeotropic alignment in MBBA. Measurements as a function of temperature were conducted to examine the thermal stability of the induced alignment. The alignment was found to be stable throughout the nematic phase of MBBA. The induction of such alignment without conventional alignment (i.e., rubbing of polyimides) technique can be helpful in addressing the evolving display demands by making liquid crystal displays (LCDs) and other display devices cost effective. 

Dementia is a brain disease which results in irreversible and progressive loss of cognition and motor activity. Despite global efforts, there is no simple and reliable diagnosis or treatment option. Current diagnosis involves indirect testing of commonly inaccessible biofluids and low-resolution brain imaging. We have developed a portable, wireless readout-based Graphene field-effect transistor (GFET) biosensor platform that can detect viruses, proteins, and small molecules with single-molecule sensitivity and specificity. We report the detection of three important amyloids, namely, Amyloid beta (Aβ), Tau (τ), and α-Synuclein (αS) using DNA aptamer nanoprobes. These amyloids were isolated, purified, and characterized from the autopsied brain tissues of Alzheimer’s Disease (AD) and Parkinson’s Disease (PD) patients. The limit of detection (LoD) of the sensor is 10 fM, 1–10 pM, 10–100 fM for Aβ, τ, and αS, respectively. Synthetic as well as autopsied brain-derived amyloids showed a statistically significant sensor response with respect to derived thresholds, confirming the ability to define diseased vs. nondiseased states. The detection of each amyloid was specific to their aptamers; Aβ, τ, and αS peptides when tested, respectively, with aptamers nonspecific to them showed statistically insignificant cross-reactivity. Thus, the aptamer-based GFET biosensor has high sensitivity and precision across a range of epidemiologically significant AD and PD variants. This portable diagnostic system would allow at-home and POC testing for neurodegenerative diseases globally. 

Abstract. Marine diazotrophs convert dinitrogen (N2) gas intobioavailable nitrogen (N), supporting life in the global ocean. In 2012, thefirst version of the global oceanic diazotroph database (version 1) waspublished. Here, we present an updated version of the database (version 2),significantly increasing the number of in situ diazotrophic measurements from13 565 to 55 286. Data points for N2 fixation rates, diazotrophic cellabundance, and nifH gene copy abundance have increased by 184 %, 86 %, and809 %, respectively. Version 2 includes two new data sheets for the nifH genecopy abundance of non-cyanobacterial diazotrophs and cell-specific N2fixation rates. The measurements of N2 fixation rates approximatelyfollow a log-normal distribution in both version 1 and version 2. However,version 2 considerably extends both the left and right tails of thedistribution. Consequently, when estimating global oceanic N2 fixationrates using the geometric means of different ocean basins, version 1 andversion 2 yield similar rates (43–57 versus 45–63 Tg N yr−1; rangesbased on one geometric standard error). In contrast, when using arithmeticmeans, version 2 suggests a significantly higher rate of 223±30 Tg N yr−1 (mean ± standard error; same hereafter) compared to version 1(74±7 Tg N yr−1). Specifically, substantial rate increases areestimated for the South Pacific Ocean (88±23 versus 20±2 Tg N yr−1), primarily driven by measurements in the southwestern subtropics,and for the North Atlantic Ocean (40±9 versus 10±2 Tg N yr−1). Moreover, version 2 estimates the N2 fixation rate in theIndian Ocean to be 35±14 Tg N yr−1, which could not be estimatedusing version 1 due to limited data availability. Furthermore, a comparisonof N2 fixation rates obtained through different measurement methods atthe same months, locations, and depths reveals that the conventional15N2 bubble method yields lower rates in 69 % cases compared tothe new 15N2 dissolution method. This updated version of thedatabase can facilitate future studies in marine ecology andbiogeochemistry. The database is stored at the Figshare repository(https://doi.org/10.6084/m9.figshare.21677687; Shao etal., 2022). 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.