Observing white dwarf tidal stripping with TianQin gravitational wave observatory

Recently discovered regular X-ray bursts known as quasi-periodic eruptions have a proposed model that suggests a tidal stripping white dwarf inspiralling into the galaxy's central black hole on an eccentric orbit. According to this model, the interaction of the stripping white dwarf with the central black hole would emit gravitational wave signals as well, their detection can help explore the formation mechanism of quasi-periodic eruptions and facilitate multi-messenger observations. In this paper, we aim to perform a preliminary study of the gravitation wave observation of TianQin on this stripping white dwarf model. We investigated the horizon distance of TianQin on this type of gravitation wave signal and found it can be set to 200Mpc. We also find that those stripping white dwarf model sources with central black hole mass within $10^4\sim10^{5.5}M_\odot$ are more likely to be detected by TianQin. We assessed the parameter estimation precision of TianQin on those stripping white dwarf model sources. Our result shows that, even in the worst case, TianQin can determine the central black hole mass, the white dwarf mass, the central black hole spin, and the orbital initial eccentricity with a precision of $10^{-2}$. In the optimistic case, TianQin can determine the central black hole mass and the white dwarf mass with a precision of $10^{-7}$, determine the central black hole spin with a precision of $10^{-5}$, and determine the orbital initial eccentricity with a precision of $10^{-8}$. Moreover, TianQin can determine the luminosity distance with a precision of $10^{-1}$ and determine the sky localization with a precision of $10^{-2}\sim10$ $\rm deg^2$.Comment: 9 pages, 4 figure

Effect Analysis of High-efficiency Dust-free Cleaning Screen in Grain Cleaning

In order to effectively resolve the conflicts between environmental protection,output and benefit during grain cleaning,the vibration screening,specific gravity air separation,cyclone separation,pulse dust removal,closed-loop air circulation and other dust removal technologies are integrated.Efficient dust-free cleaning screens are developed.To achieve effective impurity removal,the problems of excessive dust concentration in grain depots and enterprises’ grain processing and cleaning sites are aimed to be solved.Field tests on the grain depots show that the average impurity content of the grain can be controlled under 0.7% after cleaning,and the dust suppression effect is as follows:dust concentration at 5 m of the operation range lower than 30 mg/m³,15 m lower than 20 mg/m³ while 25 m lower than 10 mg/m³.Therefore,the cleaning effect and dust removal effect are better than common cleaning mechine

Distilling Artificial Recombinants from Large Sets of Complete mtDNA Genomes

BACKGROUND: Large-scale genome sequencing poses enormous problems to the logistics of laboratory work and data handling. When numerous fragments of different genomes are PCR amplified and sequenced in a laboratory, there is a high imminent risk of sample confusion. For genetic markers, such as mitochondrial DNA (mtDNA), which are free of natural recombination, single instances of sample mix-up involving different branches of the mtDNA phylogeny would give rise to reticulate patterns and should therefore be detectable. METHODOLOGY/PRINCIPAL FINDINGS: We have developed a strategy for comparing new complete mtDNA genomes, one by one, to a current skeleton of the worldwide mtDNA phylogeny. The mutations distinguishing the reference sequence from a putative recombinant sequence can then be allocated to two or more different branches of this phylogenetic skeleton. Thus, one would search for two (or three) near-matches in the total mtDNA database that together best explain the variation seen in the recombinants. The evolutionary pathway from the mtDNA tree connecting this pair together with the recombinant then generate a grid-like median network, from which one can read off the exchanged segments. CONCLUSIONS: We have applied this procedure to a large collection of complete human mtDNA sequences, where several recombinants could be distilled by our method. All these recombinant sequences were subsequently corrected by de novo experiments--fully concordant with the predictions from our data-analytical approach

A comparison between deep learning convolutional neural networks and radiologists in the differentiation of benign and malignant thyroid nodules on CT images

Introduction: We designed 5 convolutional neural network (CNN) models and ensemble models to differentiate malignant and benign thyroid nodules on CT, and compared the diagnostic performance of CNN models with that of radiologists. Material and methods: We retrospectively included CT images of 880 patients with 986 thyroid nodules confirmed by surgical pathology between July 2017 and December 2019. Two radiologists retrospectively diagnosed benign and malignant thyroid nodules on CT images in a test set. Five CNNs (ResNet50, DenseNet121, DenseNet169, SE-ResNeXt50, and Xception) were trained-validated and tested using 788 and 198 thyroid nodule CT images, respectively. Then, we selected the 3 models with the best diagnostic performance on the test set for the model ensemble. We then compared the diagnostic performance of 2 radiologists with 5 CNN models and the integrated model. Results: Of the 986 thyroid nodules, 541 were malignant, and 445 were benign. The area under the curves (AUCs) for diagnosing thyroid malignancy was 0.587–0.754 for 2 radiologists. The AUCs for diagnosing thyroid malignancy for the 5 CNN models and ensemble model was 0.901–0.947. There were significant differences in AUC between the radiologists’ models and the CNN models (p < 0.05). The ensemble model had the highest AUC value. Conclusions: Five CNN models and an ensemble model performed better than radiologists in distinguishing malignant thyroid nodules from benign nodules on CT. The diagnostic performance of the ensemble model improved and showed good potential.

Calcium-sensing receptors regulate cardiomyocyte Ca2+ signaling via the sarcoplasmic reticulum-mitochondrion interface during hypoxia/reoxygenation

Communication between the SR (sarcoplasmic reticulum, SR) and mitochondria is important for cell survival and apoptosis. The SR supplies Ca2+ directly to mitochondria via inositol 1,4,5-trisphosphate receptors (IP3Rs) at close contacts between the two organelles referred to as mitochondrion-associated ER membrane (MAM). Although it has been demonstrated that CaR (calcium sensing receptor) activation is involved in intracellular calcium overload during hypoxia/reoxygenation (H/Re), the role of CaR activation in the cardiomyocyte apoptotic pathway remains unclear. We postulated that CaR activation plays a role in the regulation of SR-mitochondrial inter-organelle Ca2+ signaling, causing apoptosis during H/Re. To investigate the above hypothesis, cultured cardiomyocytes were subjected to H/Re. We examined the distribution of IP3Rs in cardiomyocytes via immunofluorescence and Western blotting and found that type 3 IP3Rs were located in the SR. [Ca2+]i, [Ca2+]m and [Ca2+]SR were determined using Fluo-4, x-rhod-1 and Fluo 5N, respectively, and the mitochondrial membrane potential was detected with JC-1 during reoxygenation using laser confocal microscopy. We found that activation of CaR reduced [Ca2+]SR, increased [Ca2+]i and [Ca2+]m and decreased the mitochondrial membrane potential during reoxygenation. We found that the activation of CaR caused the cleavage of BAP31, thus generating the pro-apoptotic p20 fragment, which induced the release of cytochrome c from mitochondria and the translocation of bak/bax to mitochondria. Taken together, these results reveal that CaR activation causes Ca2+ release from the SR into the mitochondria through IP3Rs and induces cardiomyocyte apoptosis during hypoxia/reoxygenation