Detecting Ultra-light Dark Matter with Stimulated Annihilation

Ultra-light Dark Matter (ULDM) is one of the most promising DM candidates. In the presence of background photon radiation, the annihilation rate of the ULDM can be greatly enhanced due to the Bose enhancement. We propose to utilize such stimulated annihilation to probe the ULDM by emitting a beam of radio into the space. This could lead to a distinctive reflected electromagnetic wave with an angular frequency equal to the ULDM mass. We show that low-frequency radio telescopes, such as LOFAR, UTR-2 and ngBOLO, can offer a new avenue of detecting this signal, especially for the Earth halo model. With a power of 50 MW emitter, the expected limits could be several orders of magnitude stronger than that from Big Bang nucleosynthesis (BBN) in the ULDM mass $m_\phi$ range, $2.07 \times 10^{-8}\mathrm{~eV} \sim 4.5 \times 10^{-8}\mathrm{~eV}$.Comment: 6 pages, 2 figure

Towards human-compatible autonomous car: A study of non-verbal Turing test in automated driving with affective transition modelling

Autonomous cars are indispensable when humans go further down the hands-free route. Although existing literature highlights that the acceptance of the autonomous car will increase if it drives in a human-like manner, sparse research offers the naturalistic experience from a passenger's seat perspective to examine the human likeness of current autonomous cars. The present study tested whether the AI driver could create a human-like ride experience for passengers based on 69 participants' feedback in a real-road scenario. We designed a ride experience-based version of the non-verbal Turing test for automated driving. Participants rode in autonomous cars (driven by either human or AI drivers) as a passenger and judged whether the driver was human or AI. The AI driver failed to pass our test because passengers detected the AI driver above chance. In contrast, when the human driver drove the car, the passengers' judgement was around chance. We further investigated how human passengers ascribe humanness in our test. Based on Lewin's field theory, we advanced a computational model combining signal detection theory with pre-trained language models to predict passengers' humanness rating behaviour. We employed affective transition between pre-study baseline emotions and corresponding post-stage emotions as the signal strength of our model. Results showed that the passengers' ascription of humanness would increase with the greater affective transition. Our study suggested an important role of affective transition in passengers' ascription of humanness, which might become a future direction for autonomous driving.Comment: 16 pages, 9 figures, 3 table

Listening for the Axion Echo with the 21 CentiMeter Array

The axion is a hypothetical elementary particle that could solve the long-standing strong CP problem in particle physics and the dark matter mystery in the cosmos. Due to the stimulation of the ambient photons, the axion dark matter decay into photons is significantly enhanced so that its echo signal could be detected by terrestrial telescopes. As a pathfinder, we study the expected sensitivity of searching for the axion dark matter in the mass range between $0.41$ and $1.6\mu\text{eV}$ with the 21 CentiMeter Array (21CMA). We aim to cover the whole 21CMA frequency range in two years by using a 1MW emitter. We find that the resulting sensitivity on the axion-photon coupling could surpass other existing limits by about one order of magnitude.Comment: 7 pages, 4 figure

Association of miR-196a2 and miR-27a polymorphisms with gestational diabetes mellitus susceptibility in a Chinese population

IntroductionMiR-196a2 and miR-27a play a key role in the regulation of the insulin signaling pathway. Previous studies have indicated that miR-27a rs895819 and miR-196a2 rs11614913 have a strong association with type 2 diabetes (T2DM), but very few studies have investigated their role in gestational diabetes mellitus (GDM).MethodsA total of 500 GDM patients and 502 control subjects were enrolled in this study. Using the SNPscan™ genotyping assay, rs11614913 and rs895819 were genotyped. In the data treatment process, the independent sample t test, logistic regression and chi-square test were used to evaluate the differences in genotype, allele, and haplotype distributions and their associations with GDM risk. One-way ANOVA was conducted to determine the differences in genotype and blood glucose level.ResultsThere were obvious differences in prepregnancy body mass index (pre-BMI), age, systolic blood pressure (SBP), diastolic blood pressure (DBP) and parity between GDM and healthy subjects (P < 0.05). After adjusting for the above factors, the miR-27a rs895819 C allele was still associated with an increased risk of GDM (C vs. T: OR=1.245; 95% CI: 1.011-1.533; P = 0.039) and the TT-CC genotype of rs11614913-rs895819 was related to an increased GDM risk (OR=3.989; 95% CI: 1.309-12.16; P = 0.015). In addition, the haplotype T-C had a positive interaction with GDM (OR=1.376; 95% CI: 1.075-1.790; P=0.018), especially in the 18.5 ≤ pre-BMI < 24 group (OR=1.403; 95% CI: 1.026-1.921; P=0.034). Moreover, the blood glucose level of the rs895819 CC genotype was significantly higher than that of the TT and TC genotypes (P < 0.05). The TT-CC genotype of rs11614913-rs895819 showed that the blood glucose level was significantly higher than that of the other genotypes.DiscussionOur findings suggest that miR-27a rs895819 is associated with increased GDM susceptibility and higher blood glucose levels

Microstructure, Compressive Properties and Oxidation Behaviors of the Nb-Si-Ti-Cr-Al-Ta-Hf Alloy with Minor Holmium Addition

In the present research, the Nb-Si-Ti-Cr-Al-Ta-Hf alloys with different Ho addition were prepared. Their microstructure, compressive properties and oxidation behaviors were investigated preliminarily. The results exhibit that the Nb-Si-Ti-Cr-Al-Ta-Hf alloy has coarse microstructure which is mainly composed of Nb solid solution, Nb5Si3 and Ti5Si3 phases. The minor Ho addition could refine the microstructure and suppress the precipitation of Ti5Si3 phase. Moreover, the Ho addition also leads to the formation of Ho2Hf2O7, which prefers to precipitate along the Nbss/Nb5Si3 phase interface. Compared with the Nb-Si-Ti-Cr-Al-Ta-Hf alloy, the minor Ho addition improves the room-temperature and high-temperature compressive properties of the alloy. Its room-temperature compressive strength and ductility obtain the maximum value of 1825 MPa and 16.5% when the Ho content is 0.1 at.%. Moreover, its best compressive strength at 873 K, 1273 K and 1473 K is 1495 MPa, 765 MPa and 380 MPa, respectively, when the Ho addition is 0.1 at.%. The oxidation behavior of the Nb-Si-Ti-Cr-Al-Ta-Hf alloy is diversified with the Ho addition. The oxidation rate of the alloy with 0.1 at.% Ho addition is the lowest while the alloy with 0.2 at.% Ho addition is the highest. Therefore, the 0.1 at.% Ho would be the appropriate content for the Nb-Si-Ti-Cr-Al-Ta-Hf alloy

A Non-Invasive Follicular Thyroid Cancer Risk Prediction System Based on Deep Hybrid Multi-feature Fusion Network

Objective A non-invasive assessment of the risk of benign and malignant follicular thyroid cancer is invaluable in the choice of treatment options. The extraction and fusion of multidimensional features from ultrasound images of follicular thyroid cancer is decisive in improving the accuracy of identifying benign and malignant thyroid cancer. This paper presents a non-invasive preoperative benign and malignant risk assessment system for follicular thyroid cancer, based on the proposed deep feature extraction and fusion of ultrasound images of follicular thyroid cancer. Methods First, this study uses a convolution neural network (CNN) to obtain a global feature map of the image, and the fusion of global features cropped to local features to identify tumor images. Secondly, this tumour image is also extracted by googleNet and ResNet respectively to extract features and recognize the image. Finally, we employ an averaging algorithm to obtain the final recognition results.Results The experimental results show that the method proposed in this study achieved 89.95% accuracy, 88.46% sensitivity, 91.30% specificity and an AUC value of 96.69% in the local dataset obtained from Peking University Shenzhen Hospital, all of which are far superior to other models.Conclusion In this study, a non-invasive risk prediction system is proposed for ultrasound images of thyroid follicular tumours. We solve the problem of unbalanced sample distribution by means of an image enhancement algorithm. In order to obtain enough features to differentiate ultrasound images, a three-branched feature extraction network was designed in this study, and a balance of sensitivity and specificity is ensured by an averaging algorithm

Genome-Wide Characterization and Analysis of bHLH Transcription Factors Related to Anthocyanin Biosynthesis in Cinnamomum camphora ('Gantong 1')

Cinnamomum camphora is one of the most commonly used tree species in landscaping. Improving its ornamental traits, particularly bark and leaf colors, is one of the key breeding goals. The basic helix-loop-helix (bHLH) transcription factors (TFs) are crucial in controlling anthocyanin biosynthesis in many plants. However, their role in C. camphora remains largely unknown. In this study, we identified 150 bHLH TFs (CcbHLHs) using natural mutant C. camphora 'Gantong 1', which has unusual bark and leaf colors. Phylogenetic analysis revealed that 150 CcbHLHs were divided into 26 subfamilies which shared similar gene structures and conserved motifs. According to the protein homology analysis, we identified four candidate CcbHLHs that were highly conserved compared to the TT8 protein in A. thaliana. These TFs are potentially involved in anthocyanin biosynthesis in C. camphora. RNA-seq analysis revealed specific expression patterns of CcbHLHs in different tissue types. Furthermore, we verified expression patterns of seven CcbHLHs (CcbHLH001, CcbHLH015, CcbHLH017, CcbHLH022, CcbHLH101, CcbHLH118, and CcbHLH134) in various tissue types at different growth stages using qRT-PCR. This study opens a new avenue for subsequent research on anthocyanin biosynthesis regulated by CcbHLH TFs in C. camphora

Improved Estimation of the Gross Primary Production of Europe by Considering the Spatial and Temporal Changes in Photosynthetic Capacity from 2001 to 2016

The value of leaf photosynthetic capacity (Vcmax) varies with time and space, but state-of-the-art terrestrial biosphere models rarely include such Vcmax variability, hindering the accuracy of carbon cycle estimations on a large scale. In particular, while the European terrestrial ecosystem is particularly sensitive to climate change, current estimates of gross primary production (GPP) in Europe are subject to significant uncertainties (2.5 to 8.7 Pg C yr−1). This study applied a process-based Farquhar GPP model (FGM) to improve GPP estimation by introducing a spatially and temporally explicit Vcmax derived from the satellite-based leaf chlorophyll content (LCC) on two scales: across multiple eddy covariance tower sites and on the regional scale. Across the 19 EuroFLUX sites selected for independent model validation based on 9 plant functional types (PFTs), relative to the biome-specific Vcmax, the inclusion of the LCC-derived Vcmax improved the model estimates of GPP, with the coefficient of determination (R2) increased by 23% and the root mean square error (RMSE) decreased by 25%. Vcmax values are typically parameterized with PFT-specific Vcmax calibrated from flux tower observations or empirical Vcmax based on the TRY database (which includes 723 data points derived from Vcmax field measurements). On the regional scale, compared with GPP, using the LCC-derived Vcmax, the conventional method of fixing Vcmax using the calibrated Vcmax or TRY-based Vcmax overestimated the annual GPP of Europe by 0.5 to 2.9 Pg C yr−1 or 5 to 31% and overestimated the interannually increasing GPP trend by 0.007 to 0.01 Pg C yr−2 or 14 to 20%, respectively. The spatial pattern and interannual change trend of the European GPP estimated by the improved FGM showed general consistency with the existing studies, while our estimates indicated that the European terrestrial ecosystem (including part of Russia) had higher carbon assimilation potential (9.4 Pg C yr−1). Our study highlighted the urgent need to develop spatially and temporally consistent Vcmax products with a high accuracy so as to reduce uncertainties in global carbon modeling and improve our understanding of how terrestrial ecosystems respond to climate change

The Mycobacterium tuberculosis prolyl dipeptidyl peptidase cleaves the N-terminal peptide of the immunoprotein CXCL-10

Dipeptidyl peptidases constitute a class of non-classical serine proteases that regulate an array of biological functions, making them pharmacologically attractive enzymes. With this work, we identified and characterized a dipeptidyl peptidase from Mycobacterium tuberculosis (MtDPP) displaying a strong preference for proline residues at the P1 substrate position and an unexpectedly high thermal stability. MtDPP was also characterized with alanine replacements of residues of its active site that yielded, for the most part, loss of catalysis. We show that MtDPP catalytic activity is inhibited by well-known human DPP4 inhibitors. Using MALDI-TOF mass spectrometry we also describe that in vitro, MtDPP mediates the truncation of the C-X-C motif chemokine ligand 10, indicating a plausible role in immune modulation for this mycobacterial enzyme