Different receptors have evolved in organisms to sense different stimuli in their surroundings. The interaction among the receptors can significantly increase sensory sensitivity and adaptation precision. To study the influence of interaction among different types of chemoreceptors on the adaptation rate in the bacterial chemotaxis signaling network, we systematically compared the adaptation time between the wild-type strain expressing mixed types of receptors and the mutant strain expressing only Tar receptors (namely, the Tar-only strain) under stepwise addition of different concentrations of L-aspartate using FRET (Förster resonance energy transfer) and bead assays. We find that the wild type exhibits faster adaptation than the mutant under the same concentration of saturated stimulus. In contrast, the wild type exhibits slower adaptation than the mutant under unsaturated stimuli that induce the same magnitude of response, and this is independent of the level of receptor expression. The same result is obtained for the network relaxation time by monitoring the steady-state rotational signal of the flagellar motors. By simulating bacterial chemotaxis with different adaptation rates in a stable gradient of chemoattractants, we confirm that the interaction of different types of receptors can effectively promote chemotaxis of Escherichia coli under a stable spatial gradient of attractants while ensuring minimum noise in the cell position distribution.

As a promising solid-state sensor at room temperature, diamond magnetometers based on nitrogen-vacancy (NV) centers have been developed tremendously in recent years. Many studies have demonstrated its potential for achieving high spatial resolution and sensitivity. However, the temperature dependence of the zero-field splitting D of NV centers poses an enormous challenge for the application of diamond magnetometry, since it is difficult to avoid temperature drift in most application scenarios. Here, we demonstrate a type of temperature-robust diamond magnetometry based on the double-transition method. By utilizing both transitions between $|m_{\rm{s}}=0\rangle$ and $|m_{\rm{s}}=\pm1\rangle$ sublevels with incomplete degeneracy of the $|m_{\rm{s}}=\pm1\rangle$states, the impacts of D variations induced by temperature drift can be counteracted. The drift of magnetic field measurement result has been reduced by approximately 7-fold. With further improvements, the temperature-robust diamond magnetometry has the potential to be applied in biomagnetism and space science research.

We present a routinized and reliable method to obtain source catalogs from the Nuclear Spectroscopic Telescope Array (NuSTAR) extragalactic surveys of the Extended Chandra Deep Field-South (E-CDF-S) and Chandra Deep Field-North (CDF-N). The NuSTAR E-CDF-S survey covers a sky area of $\sim30'\times30'$ to a maximum depth of $\sim230\;{\rm{ks}}$ corrected for vignetting in the 3–24 keV band, with a total of 58 sources detected in our E-CDF-S catalog; the NuSTAR CDF-N survey covers a sky area of $\sim7'\times10'$ to a maximum depth of $\sim440\;{\rm{ks}}$ corrected for vignetting in the 3–24 keV band, with a total of 42 sources detected in our CDF-N catalog that is produced for the first time. We verify the reliability of our two catalogs by crossmatching them with the relevant catalogs from the Chandra X-ray observatory and find that the fluxes of our NuSTAR sources are generally consistent with those of their Chandra counterparts. Our two catalogs are produced following the exact same method and made publicly available, thereby providing a uniform platform that facilitates further studies involving these two fields. Our source-detection method provides a systematic approach for source cataloging in other NuSTAR extragalactic surveys.

High-fidelity quantum operation of qubits plays an important role in magnetometry based on nitrogen-vacancy (NV) centers in diamonds. However, the nontrivial spin-spin coupling of the NV center decreases signal contrast and sensitivity. Here, we overcome this limitation by exploiting the amplitude modulation of microwaves, which allows us to perfectly detect magnetic signals at low fields. Compared with the traditional double-quantum sensing protocol, the full contrast of the detection signal was recovered, and the sensitivity was enhanced three times in the experiment. Our method is applicable to a wide range of sensing tasks, such as temperature, strain, and electric field.

Given a partition of $\mathbb{Z}_N^*$ into four subsets, we present a generic construction of uncorrelated quaternary sequence pairs of length $2N$ using the interleaved technique based on this partition. By choosing partitions arising from cyclotomic classes of order 4 and 8 over $\mathbb{Z}_p$, we construct uncorrelated quaternary sequence pairs of length $2p$, which are almost balanced and have low autocorrelation, except at a few positions.

The rapid development of social media leads to the spread of a large amount of false news, which not only affects people’s daily life but also harms the credibility of social media platforms. Therefore, detecting Chinese fake news is a challenging and meaningful task. However, existing fake news datasets from Chinese social media platforms have a relatively small amount of data and data collection in this field is relatively old, thus being unable to meet the requirements of further research. In consideration of this background, we release a new Chinese Weibo Fake News dataset, which contains 26320 fake news data collected from Weibo. In addition, we propose a fake news detection model based on data augmentation that can effectively solve the problem of a lack of fake news, and we improve the generalization ability and robustness of the model. We conduct numerous experiments on our Chinese Weibo Fake News dataset and successfully deploy the model on the web page. The experimental performance proves the effectiveness of the proposed end-to-end model for detecting fake news on social media platforms.

Barium (Ba) isotopes can be used as potential tracers for crustal material recycling in the mantle. Determination of the Ba isotope composition of the depleted mantle is essential for such applications. However, Ba isotope data for mantle-derived basalts are still rare. In this study, we reported high-precision Ba isotope data of 30 oceanic basalts including 25 mid-ocean ridge basalts (MORBs) from geochemically and geologically diverse mid-ocean ridge segments and five back-arc basin basalts. The δ^138/134Ba values of these samples varied from −0.06‰ to +0.11‰, with no systematic cross-region variation. Together with published data, we constrained the average δ^138/134Ba of global MORBs to +0.05‰±0.09‰ (2 standard deviation, n = 51). Based on depleted MORBs that have (La/Sm)_N < 0.8, low ⁸⁷Sr/⁸⁶Sr (< 0.70263), and low Ba/Th < 71.3, we estimated the average δ^138/134Ba of the depleted MORB mantle (DMM) as + 0.05‰ ± 0.05‰ (2SD, n = 16) that is significantly lower than the DMM (≈ 0.14‰) reported previously. If a new estimation of the DMM is applied, it is unreasonable to infer that the Ba isotope signatures of the “enriched-type” MORBs (E-MORBs) could be attributed to pervasive sediment recycling in the upper mantle. We, therefore, conclude that the Ba isotope compositions of the E-MORBs could be sourced from the incorporation of subducted altered oceanic crust and/or sediments depending on the Ba isotope composition and other geochemical information of the local mantle.

A heavy dust storm originating in Mongolia and Inner Mongolia traveled to Northeast China and met a midlatitude frontal system on May 3, 2017. The potential ice nuclei (IN) effects of mineral dust aerosols on the vertical structure of clouds, precipitation, and latent heat (LH) were studied using Global Precipitation Mission (GPM) satellite observations and Weather Research and Forecasting (WRF) model simulations. The WRF simulations correctly captured the main features of the system, and the surface rain rate distribution was positively correlated with data retrieved from the GPM Microwave Imager. Moreover, the correlation coefficient increased from 0.31 to 0.54 with increasing moving average window size. The WRF-simulated rainfall vertical profiles are generally comparable to the GPM Dual-Frequency Precipitation Radar (DPR) observations, particularly in low layers. The joint probability distribution functions of the rain rate at different altitudes from the WRF simulation and GPM observations show high positive correlation coefficients of ~0.80, indicating that the assumptions regarding the raindrop size distribution in the WRF model and DPR retrieval were consistent. Atmospheric circulation analysis and aerosol optical depth observations from the Himawari-8 satellite indicated that the dust storm entered only a narrow strip of the northwest edge of the frontal precipitation system. The WRF simulations showed that in carefully selected areas of heavy dust, dust can enhance the heterogeneous ice nucleation process and increase the cloud ice, snowfall, high-altitude precipitation rate, and LH rate in the upper layers. This effect is significant at temperatures of −15 °C to −38 °C and requires dust number concentrations exceeding 10⁶ m⁻³. It is important to accurately classify the dusty region in this type of case study. In the selected vertical cross section, the WRF-simulated and DPR-retrieved LH have comparable vertical shapes and amplitudes. Both results reflect the structure of the tilted frontal surface, with positive LH above it and negative LH below it. The simulated area-averaged LH profiles show positive heating in the entire column, which is a convective-dominated region, and this feature is not significantly affected by dust. DPR-based LH profiles show stratiform-dominated or convective-dominated shapes, depending on the DPR retrieval product.

Sheared E × B flow has been frequently observed to excite instability in space plasma. In this study, two methods – the interpenetrating plasma and ring electrode methods – were developed in the Keda Space Plasma EXperiment (KSPEX) device to trigger sheared E × B flow. Both methods produce sheared E × B flow by generating a radial electric field. The results of the experiment indicated that plasma instabilities in the ion cyclotron range can be excited by these methods. Therefore, the methods reported here are important for research on the mechanism for generating sheared flow-driven plasma instabilities, which may enrich our understanding of geospace physics.

The evolution of the atmospheric oxygen content through Earth’s history is a key issue in paleoclimatic and paleoenvironmental research. There were at least two oxygenation events in the Precambrian that involved fundamental changes in both biotic innovation and the surface environment. However, a large dissolved organic carbon (DOC) pool maintained in deep oceans during the Neoproterozoic may have extended the time interval between the two oxygenation events. To test the DOC hypothesis, we conducted detailed micro-drilled analyses of carbonate carbon isotopes (δ¹³C_carb) of a long Ediacaran drill core (the Wangji drill core), for which whole-rock δ¹³C_carb and organic carbon isotope (δ¹³C_org) records were available. The micro-drilled δ¹³C_carb values obtained in this study are consistent with whole-rock δ¹³C_carb results, precluding the influence of severe authigenic carbonate incorporation. Importantly, the multiple negative δ¹³C_carb excursions in the Wangji drill core were likely linked with upwelling events, during which DOC was supplied to the surface water and oxidized. Using box models, we estimate that ~3.6 × 10¹⁹ mol and ~2.0 × 10¹⁹ mol DOC were converted to bicarbonate during two negative δ¹³C_carb excursions spanning millions of years. The estimations are approximately 1000 times the modern marine DOC reservoir. Our results support a relatively high oxidation capacity (elevated atmospheric pO₂ and/or oceanic [${\rm{SO}}_4^{2 - }$]) of the Earth’s surface during the early Ediacaran Period.

The curvature estimate of the Yang-Mills-Higgs flow on Higgs bundles over compact Kähler manifolds is studied. Under the assumptions that the Higgs bundle is non-semistable and the Harder-Narasimhan-Seshadri filtration has no singularities with length one, it is proved that the curvature of the evolved Hermitian metric is uniformly bounded.

Sound speed is an important acoustic parameter for tissue characterization. Herein we developed an ultrasound computed tomography (USCT) system for ex vivo sound speed imaging and evaluation of small animal organs. The proposed USCT system employs a 256-element ring array transducer and allows simultaneous signal transmission and reception for all channels. The method does not require complicated sample preparation procedures and can yield accurate measurement results. Experimental results show that sound speeds of excised rat brain, heart, liver, spleen, and kidney measured by the method are close to published data. This work demonstrates a new method for sound speed imaging and holds potential for in vivo applications.

Liquid Li metal is a promising nuclear reactor coolant; however, relevant research regarding its heat transfer characteristics remains insufficient. In this study, a steady-state two-dimensional mathematical model is established to describe the heat transfer process of liquid Li in a straight pipe. A numerical analysis is conducted to investigate the effects of inlet velocity, inlet temperature, and wall heat flux on heat transfer in liquid Li. The results indicate the advantage of using liquid Li for improving heat transfer at high inlet temperatures (> 1000 K) compared with using liquid sodium and lead–bismuth eutectic. Considering the mechanism of the outlet radial heat flow model, the ratio of turbulent to molecular diffusion coefficients presents a parabolic distribution along the radius of the pipe. Increasing the inlet velocity, decreasing the inlet temperature, and decreasing the wall heat flux can effectively weaken the dominant role of molecular heat transfer owing to the low Prandtl number of liquid Li. The heat transfer of liquid Li is investigated comprehensively in this study, and the results provide a basis for the practical application of liquid Li as a promising coolant.

Clarifying the mechanism of fungi growth is of great significance for maintaining the quality during grain storage. Among the factors that affect the growth of fungi spores, the most important factors are temperature, moisture content and storage time. Therefore, through this study, a multivariate linear regression model among several important factors, such as the spore number and ambient temperature, rice moisture content and storage days, were developed based on the experimental data. In order to build a more accurate model, we introduce a random forest algorithm into the fungal spore prediction during grain storage. The established regression models can be used to predict the spore number under different ambient temperature, rice moisture content and storage days during the storage process. For the random forest model, it could control the predicted value to be of the same order of magnitude as the actual value for 99% of the original data, which have a high accuracy to predict the spore number during the storage process. Furthermore, we plot the prediction surface graph to help practitioners to control the storage environment within the conditions in the low risk region.

The energy consumption problem of heating, ventilation, and air conditioning systems over general directed graphs is investigated. The considered problem is firstly reformulated as a Nash equilibrium seeking problem, and a distributed consensus-based algorithm is then proposed to solve it. To address the challenge arising from general directed graphs, a distributed estimation algorithm is embedded such that the explicit dependence on the left eigenvector associated with the eigenvalue zero of the Laplacian matrix can be avoided. Then, the exponential convergence of the proposed distributed Nash equilibrium seeking algorithm is established under a standing assumption. A numerical example is finally provided to verify the effectiveness of the proposed algorithm.

The spray cold plate has a compact structure and high-efficiency heat exchange, which can meet the requirements of high heat flux dissipation of multiple heat sources, and is a reliable means to solve the heat dissipation of the next generation of chips. This paper proposes to use surfactants to enhance the heat transfer of the spray cold plate, and conduct a systematic experimental study on the heat transfer performance of the spray cold plate under different types and concentrations of additives. It was found that among the three surfactants, sodium dodecyl sulfate (SDS) can improve the heat transfer performance of the spray cold plate, and at the optimal concentration of 200ppm, the heat transfer coefficient of the spray cold plate was increased significantly by 19.8%. Both the n-octanol-distilled water and Tween 20-distilled water can reduce the heat transfer performance of the cold plate using multi nozzles. In addition, based on the experimental data, the dimensionless heat transfers correlations for the spray cold plate using additives were conducted, and the maximum errors of dimensionless correlations for using additives were 2.1%, 2.8%, and 5.4% respectively. This discovery provides a theoretical analysis and basis for the improvement of spray cold plates.

The high granularity timing detector (HGTD) is a crucial component of the ATLAS phase II upgrade to cope with the extremely high pile-up (the average number of interactions per bunch crossing can be as high as 200). With the precise timing information (σ_t～30 ps) of the tracks, the track-to-vertex association can be performed in the “4-D” space. The Low Gain Avalanche Detector (LGAD) technology is chosen for the sensors, which can provide the required timing resolution and good signal-to-noise ratio. Hamamatsu Photonics K.K. (HPK) has produced the LGAD with thicknesses of 35 μm and 50 μm. The University of Science and Technology of China(USTC) has also developed and produced 50 μm LGADs prototypes with the Institute of Microelectronics (IME) of Chinese Academy of Sciences. To evaluate the irradiation hardness, the sensors are irradiated with the neutron at the JSI reactor facility and tested at USTC. The irradiation effects on both the gain layer and the bulk are characterized by I-V and C-V measurements at room temperature (20 ℃) or −30 ℃. The breakdown voltages and depletion voltages are extracted and presented as a function of the fluences. The final fitting of the acceptor removal model yielded the c-factor of 3.06×10⁻¹⁶ cm⁻², 3.89×10⁻¹⁶ cm⁻² and 4.12×10⁻¹⁶ cm⁻² for the HPK-1.2, HPK-3.2 and USTC-1.1-W8, respectively, showing that the HPK-1.2 sensors have the most irradiation resistant gain layer. A novel analysis method is used to further exploit the data to get the relationship between the c-factor and initial doping density.

Ultraviolet photodetection plays an important role in optical communication and chemical- and bio- related sensing applications. Gallium nitride (GaN) nanowires-based photoelectrochemical-type photodetectors, which operate particularly in acqueous conditions, have been attracted extensive interest because of their low cost, fast photoresponse, and excellent responsivity. However, GaN nanowires, which have a large surface-to-volume ratio, suffer suffered from instability in photoelectrochemical environments because of photocorrosion. In this study, the structural and photoelectrochemical properties of GaN nanowires with improved photoresponse and chemical stability obtained by coating the nanowire surface with an ultrathin TiO₂ protective layer were investigated. The photocurrent density of TiO₂-coated GaN nanowires changed minimally over a relatively long operation time of 2000 s under 365-nm illumination. Meanwhile, the attenuation coefficient of the photocurrent density could be reduced to 49%, whereas it is as high as 85% in uncoated GaN nanowires. Furthermore, the photoelectrochemical behavior of the nanowires was investigated through electrochemical impedance spectroscopy measurements. The results shed light on the construction of long-term-stable GaN-nanowire-based photoelectrochemical-type photodetectors.

Many pretrained deep learning models have been released to help engineers and researchers develop deep learning-based systems or conduct research with minimall effort. Previous work has shown that at secret message can be embedded in neural network parameters without compromising the accuracy of the model. Malicious developers can, therefore, hide malware or other baneful information in pretrained models, causing harm to society. Hence, reliable detection of these vicious pretrained models is urgently needed. We analyze existing approaches for hiding messages and find that they will ineluctably cause biases in the parameter statistics. Therefore, we propose steganalysis methods for steganography on neural network parameters that extract statistics from benign and malicious models and build classifiers based on the extracted statistics. To the best of our knowledge, this is the first study on neural network steganalysis. The experimental results reveal that our proposed algorithm can effectively detect a model with an embedded message. Notably, our detection methods are still valid in cases where the payload of the stego model is low.