Various electrically-assisted (EA) plastic forming technologies have been developed for difficult-to-form materials such as magnesium alloys in recent years. However, very few studies have been ...conducted on EA micro-forming, especially determining the size effect on electrically-induced softening behavior. In this study, uniaxial micro-tension tests at various current densities were conducted to investigate the effects of grain size and specimen size on the electrically-induced softening behavior of magnesium alloy AZ31 specimens. It was found that the electrically-induced softening parameter (i.e., the ratio of the tensile strength in EA to that in non-EA test with the higher softening at the smaller value) followed an inverse-S-shaped function of current density. A relatively lower current density would be sufficient for larger sample sizes and smaller grain sizes to achieve a higher softening effect, indicating that grain number may be an important factor influencing electrically-induced softening. These size effects on electrically-induced softening were used to modify a semi-empirical softening function of current density, which could effectively predict the electrically-induced softening behaviors of five metals. The current density threshold in EA tension was defined and formulated based on the semi-empirical softening function, which nonlinearly increased with grain size, but decreased with specimen size and electrical resistivity.
Display omitted
•Less electrical current density is required to soften samples with smaller grain size.•A semi-empirical model of electrically-induced softening behavior is proposed with consideration of sample size and grain size effects.•The proposed softening model was validated using literature data of five metal alloys subject to electrically-assisted tension.•The current density threshold can be defined and quantified based on the semi-empirical model.
Non-coding RNAs (ncRNAs) have long been considered the "white elephant" on the genome because they lack the ability to encode proteins. However, in recent years, more and more biological experiments ...and clinical reports have proved that ncRNAs account for a large proportion in organisms. At the same time, they play a decisive role in the biological processes such as gene expression and cell growth and development. Recently, it has been found that short sequence non-coding RNA(miRNA) and long sequence non-coding RNA(lncRNA) can regulate each other, which plays an important role in various complex human diseases. In this paper, we used a new method (JSCSNCP-LMA) to predict lncRNA-miRNA with unknown associations. This method combined Jaccard similarity algorithm, self-tuning spectral clustering similarity algorithm, cosine similarity algorithm and known lncRNA-miRNA association networks, and used the consistency projection to complete the final prediction. The results showed that the AUC values of JSCSNCP-LMA in fivefold cross validation (fivefold CV) and leave-one-out cross validation (LOOCV) were 0.9145 and 0.9268, respectively. Compared with other models, we have successfully proved its superiority and good extensibility. Meanwhile, the model also used three different lncRNA-miRNA datasets in the fivefold CV experiment and obtained good results with AUC values of 0.9145, 0.9662 and 0.9505, respectively. Therefore, JSCSNCP-LMA will help to predict the associations between lncRNA and miRNA.
Abstract
Background
Plant metabolites reshaped by nature and human beings are crucial for both their lives and human health. However, which metabolites respond most strongly to selection pressure at ...different evolutionary stages and what roles they undertake on perennial fruit crops such as peach remain unclear.
Results
Here, we report 18,052 significant locus-trait associations, 12,691 expression-metabolite correlations, and 294,676 expression quantitative trait loci (eQTLs) for peach. Our results indicate that amino acids accumulated in landraces may be involved in the environmental adaptation of peaches by responding to low temperature and drought. Moreover, the contents of flavonoids, the major nutrients in fruits, have kept decreasing accompanied by the reduced bitter flavor during both domestication and improvement stages. However, citric acid, under the selection of breeders’ and consumers’ preference for flavor, shows significantly different levels between eastern and western varieties. This correlates with differences in activity against cancer cells in vitro in fruit from these two regions. Based on the identified key genes regulating flavonoid and acid contents, we propose that more precise and targeted breeding technologies should be designed to improve peach varieties with rich functional contents because of the linkage of genes related to bitterness and acid taste, antioxidant and potential anti-cancer activity that are all located at the top of chromosome 5.
Conclusions
This study provides powerful data for future improvement of peach flavor, nutrition, and resistance in future and expands our understanding of the effects of natural and artificial selection on metabolites.
By continuously varying the structure of graphene oxide paper (PRGP) using Joule heating annealing, we are able to tune its electrical conductivity (σ) and thermal diffusivity (α) in a very wide ...range: more than three orders of magnitude for σ (186–503009 S/m) and 10-fold for α (8.31 × 10−7 m2/s to 9.31 × 10−6 m2/s). Excellent coherency-linear relationship between σ and α is discovered although they are sustained by different carriers: electrons and phonons. Such coherency exists over two sections: σ > 2 × 104 S/m, and 103<σ < 2 × 104 S/m. A two-component parallel structure is proposed to interpret the observed discovery. The slope of α∼σ relation reflects the ratio of difference in α between the two components over σ of the ordered structure. The intercept of α∼σ relation reflects the α of the disordered structure. It is found the α of disordered structure in our PRGP agrees well with that of amorphous carbon. Past work on carbon nanocoil, graphene paper, graphene oxide film, and graphene fiber also reveals linear coherency between α and σ. However, there are no uniform slope and intercept while they are close for similar materials. The parameters of the linear coherency strongly depend on the two structures in the material.
Display omitted
The recent discovery of 2D magnets has revealed various intriguing phenomena due to the coupling between spin and other degrees of freedoms (such as helical photoluminescence, nonreciprocal SHG). ...Previous research on the spin-phonon coupling effect mainly focuses on the renormalization of phonon frequency. Here we demonstrate that the Raman polarization selection rules of optical phonons can be greatly modified by the magnetic ordering in 2D magnet CrI3. For monolayer samples, the dominant A 1g peak shows an abnormally high intensity in the cross-polarization channel at low temperatures, which is forbidden by the selection rule based on the lattice symmetry. For the bilayer, this peak is absent in the cross-polarization channel for the layered antiferromagnetic (AFM) state and reappears when it is tuned to the ferromagnetic (FM) state by an external magnetic field. Our findings shed light on exploring the emergent magneto-optical effects in 2D magnets.
Most conventional Raman thermometry for thermal properties measurement is on steady-state basis, which utilizes either Joule heating effect or two lasers configurations coupled with increased ...complexity of system or measurement uncertainty. In this work, a new comprehensive approach including both transient and steady-state Raman method is proposed for thermal properties measurement of micro/nanowires. The transient method employs a modulated (pulsed) laser for transient heating and Raman excitation, and is termed time-domain differential Raman. The average elevated temperature during the transient heating period is probed simultaneously based on Raman thermometry. Thermal diffusivity can be readily determined by fitting normalized temperature rise against heating time with a transient heat conduction model. On the other hand, thermal conductivity can be obtained in the steady-state measurement by adjusting modulation settings. To verify this method, a carbon nanotube (CNT) fiber is measured with the thermal diffusivity of 1.74−0.20+0.20×10−5 m2/s and the thermal conductivity of 34.3−0.4+0.4 W/m K. The relatively low thermal transport values stem from numerous CNT-glue matrix and CNT–CNT thermal contact resistances. Compared with the conventional steady-state Raman method, the transient method requires no detailed laser absorption value and no temperature coefficient calibration. It can be easily applied to study transient thermal transport in materials.
Abstract
Background
Programmed death-ligand 1 (PD-L1) inhibitors has emerged as a first-line therapeutic strategy for advanced small cell lung cancer (SCLC), which can stimulate T-cell activation, ...thereby preventing tumor avoidance of immunologic surveillance, whereas, proton pump inhibitors (PPIs) can play an important role in regulating immune function. This study assessed whether the concomitantly use of PPIs affected outcomes of immunotherapy in advanced SCLC.
Methods
Data from advanced SCLC patients who firstly treated with PD-L1 inhibitors between July 2018 and February 2021 was retrospectively analyzed. The impact of concomitant medications (especially PPIs) on objective response rate, progression-free survival (PFS) and overall survival (OS) were evaluated.
Results
Of 208 patients, 101 received immunotherapy concomitant PPIs. The median PFS of patients receiving PPIs (6.6 months) were significantly shorter than those without PPIs (10.6 months), and so was OS. There was associated with a 74.9% increased risk of progression and 58.3% increased risk of death. Both first-line and post-first-line immunotherapy, patients treated PPIs had poorer PFS.
Conclusion
PPIs therapy has a negative impact on the clinical outcomes of advanced SCLC patients treated with PD-L1 inhibitors.
It is difficult for traditional signal-recognition methods to effectively classify and identify multiple emitter signals in a low SNR environment. This paper proposes a multi-emitter ...signal-feature-sorting and recognition method based on low-order cyclic statistics CWD time-frequency images and the YOLOv5 deep network model, which can quickly dissociate, label, and sort the multi-emitter signal features in the time-frequency domain under a low SNR environment. First, the denoised signal is extracted based on the low-order cyclic statistics of the typical modulation types of radiation source signals. Second, the time-frequency graph of multisource signals was obtained through CWD time-frequency analysis. The cyclic frequency was controlled to balance the noise suppression effect and operation time to achieve noise suppression of multisource signals at a low SNR. Finally, the YOLOv5s deep network model is used as a classifier to sort and identify the received signals from multiple radiation sources. The method proposed in this paper has high real-time performance. It can identify the radiation source signals of different modulation types with high accuracy under the condition of a low SNR.
Three-dimensional (3D) range-gated imaging can obtain high spatial resolution intensity images as well as pixel-wise depth information. Several algorithms have been developed to recover depth from ...gated images such as the range-intensity correlation algorithm and deep-learning-based algorithm. The traditional range-intensity correlation algorithm requires specific range-intensity profiles, which are hard to generate, while the existing deep-learning-based algorithm requires large number of real-scene training data. In this work, we propose a method of range-intensity-profile-guided gated light ranging and imaging to recover depth from gated images based on a convolutional neural network. In this method, the range-intensity profile (RIP) of a given gated light ranging and imaging system is obtained to generate synthetic training data from Grand Theft Auto V for our range-intensity ratio and semantic network (RIRS-net). The RIRS-net is mainly trained on synthetic data and fine-tuned with RIP data. The network learns both semantic depth cues and range-intensity depth cues in the synthetic data, and learns accurate range-intensity depth cues in the RIP data. In the evaluation experiments on both a real-scene and synthetic test dataset, our method shows a better result compared to other algorithms.
A novel transient thermal characterization technology is developed based on the principles of transient optical heating and Raman probing: time-domain differential Raman. It employs a square-wave ...modulated laser of varying duty cycle to realize controlled heating and transient thermal probing. Very well defined extension of the heating time in each measurement changes the temperature evolution profile and the probed temperature field at μs resolution. Using this new technique, the transient thermal response of a tipless Si cantilever is investigated along the length direction. A physical model is developed to reconstruct the Raman spectrum considering the temperature evolution, while taking into account the temperature dependence of the Raman emission. By fitting the variation of the normalized Raman peak intensity, wavenumber, and peak area against the heating time, the thermal diffusivity is determined as 9.17 × 10(-5), 8.14 × 10(-5), and 9.51 × 10(-5) m(2)/s. These results agree well with the reference value of 8.66 × 10(-5) m(2)/s considering the 10% fitting uncertainty. The time-domain differential Raman provides a novel way to introduce transient thermal excitation of materials, probe the thermal response, and measure the thermal diffusivity, all with high accuracy.
PDF
