Climate Changes and Trends in Phenology of Woody and Herb Plants in Inner Mongolia, 1981–2010

The phenology of plants is a comprehensive reflection of seasonal climatological and ecological conditions and may be used as an indicator of climate change (Thomas et al. 2000; Volker and Annette 2004; Li et al. 2005). Analysis was made of the dates of sprouting, flowering and defoliating of woody and herb plants observed on 24 Agricultural Meteorological Stations in Inner Mongolia, China from 1980 to 2010. To assess the potential future change data was analysed for the 2011 to 2050 period using the England Hadley Climate Centre scenario (Wei et al. 2012)

Time-Domain Simulations of Aerodynamic Forces on Three-Dimensional Configurations, Unstable Aeroelastic Responses, and Control by Neural Network Systems

The nonlinear interactions between aerodynamic forces and wing structures are numerically investigated as integrated dynamic systems, including structural models, aerodynamics, and control systems, in the time domain. An elastic beam model coupled with rigid-body rotation is developed for the wing structure, and the natural frequencies and mode shapes are found by the finite-element method. A general unsteady vortex-lattice method is used to provide aerodynamic forces. This method is verified by comparing the numerical solutions with the experimental results for several cases; and thereafter applied to several applications such as the inboard-wing/twin-fuselage configuration, and formation flights. The original thought that the twin fuselage could achieve two-dimensional flow on the wing by eliminating free wing tips appears to be incorrect. The numerical results show that there can be a lift increase when two or more wings fly together, compared to when they fly alone. Flutter analysis is carried out for a High-AltitudeLong -Endurance aircraft wing cantilevered from the wall of the wind tunnel, a full-span wing mounted on a free-to-roll sting at its mid-span without and with a center mass (fuselage). Numerical solutions show that the rigidity added by the wall results in a higher flutter speed for the wall-mounted semi-model than that for the full-span model. In addition, a predictive control technique based on neural networks is investigated to suppress flutter oscillations. The controller uses a neural network model to predict future plant responses to potential control signals. A search algorithm is used to select the best control input that optimizes future plant performance. The control force is assumed to be given by an actuator that can apply a distributed tor..

A White Dwarf Search Model Based on a Deep Transfer-learning Method

White dwarfs represent the ultimate stage of evolution for over 97% of stars and play a crucial role in studies of the Milky Way’s structure and evolution. Recent years have witnessed significant progress in using deep-learning methods for identifying unique objects in large-scale data. In this paper, we present a model based on transfer learning for identifying white dwarfs. We constructed a data set using the spectra released by LAMOST DR9 and trained a convolutional neural network model. The model was then further trained using a transfer-learning approach for a binary classification model. Our final model is comprised of a seven-class classification model and a binary classification model. The testing set yielded an accuracy rate of 96.08%. Our proposed model successfully identifies 4314 of the 4479 white dwarfs published in previous papers. We applied this model to filter the 1,121,128 spectral data from the LAMOST DR9 V1 catalog. Subsequently, we obtained 6317 white dwarf candidates, of which 5014 were cross-validated and found to be known white dwarfs. We finally identified 489 new white dwarfs out of the remaining 1303 candidates, containing 377 DAs, 1 DB, 4 DZs, 1 magnetic WD, 101 DA+M binaries, and 1 DB+M binary. Our study also compared transfer-learning methods with non-transfer-learning methods, and the results show that transfer learning provides faster training speed and a higher accuracy rate. We provide the trained model and a corresponding usage program for subsequent studies

TVD-PB Logic Circuit Based on Camouflaging Circuit for IoT Security

Abstract Internet of Things (IoT) devices are vulnerable to many physical attacks, including reverse engineering and side‐channel analysis because the sensitive information of circuits may be leaked through the physical characteristics of the device. A logic camouflaging circuit is proposed that uses a balanced power consumption and threshold voltage‐defined technique to provide an antiphysical attack scheme to protect the hardware security for IoT devices. The proposed circuit uses a symmetric differential pull‐down network in implementing the different logic functions through the threshold voltage reconfiguration circuit. As a result, the power consumption of the circuit attains balance and stability between two different logical operations. The proposed threshold voltage‐defined power‐balance (TVD‐PB) design is fabricated using a 65‐nm CMOS technology, and the core area occupies approximately 0.0044 mm2, composed of NAND, NOR, XOR, and INV components and multiplier gates of the proposed TVD‐PB circuit. The entire chip passed the logic function tests. The measured results show that the average similarity of the TVD‐PB universal gate is 99.68%. In addition, the current margin is higher than 55 μA and power consumption of 0.455 mW during each clock cycle at 1.2 V derives 0.1072% of the normalized energy deviation and 0.0453% of the normalized standard deviation. Compared with other state‐of‐the‐art techniques, the power dependency against power attacks is improved effectively

Understanding the deterioration of fresh brown rice noodles from the macro and micro perspectives.

The microbial compositions, quality characteristics, and structural changes in fresh brown rice noodles (FBRN) during storage were investigated. Total plate count and mold and yeast counts increased while the pH decreased during storage. Metagenomic sequencing revealed that the microbial composition of FBRN changed throughout storage. A comprehensive investigation of the variation in lipid content demonstrated that hydrolytic rancidity was responsible for lipid deterioration. LF-NMR showed an increase in the proportion of bound water and a decrease in the proportion of free water in FBRN. Moreover, significant changes in edible qualities were observed. The cooking loss increased three-fold and noodles hardness reduced by approximately 23%. Further, the high initial aldehyde content of FBRN diminished almost completely, while that of alcohols and esters increased, leading to significant flavor deterioration. The correlation and factor analysis suggested that the TPC and MY counts could be used as key indicators of FBRN deterioration

Mulberry leaf-derived polysaccharide modulates the immune response and gut microbiota composition in immunosuppressed mice

Mulberry leaf polysaccharide (MLP) possess many biological characteristics, such as immunomodulatory and antioxidant properties, but whether MLP can impact the distribution and characteristics of the gut microbiota is not yet clear. In this study, the effects of MLP on diversity- and immune-related factors and short-chain fatty acids (SCFAs) of the gut microbiota in mice were investigated. The results showed that MLP could restore the indexes of the thymus and spleen, the damaged intestinal barrier and levels of inflammatory cytokines in cyclophosphamide (CTX)-treated mice, and alleviate oxidative damage to the liver. Additionally, MLP were associated with a relatively higher abundance of Bacteroidetes but lower levels of Firmicutes, Butyricimonas and Eubacterium in CTX-treated mice. Moreover, MLP restored the levels of acetic acid, propionic acid, and n-butyric acid reduced by CTX. These results indicated that MLP, as a special ingredient, might regulate the immune response by altering the spatial structure of the gut microbiota and the production of SCFAs

Methods and Applications of Full-Scale Field Testing for Large-Scale Circulating Fluidized Bed Boilers

Circulating fluidized bed (CFB) boilers offer a technically viable and environmentally friendly means for the clean and efficient utilization of solid fuels. However, the complex gas–solid two-phase flow processes within them have hindered a thorough resolution of prediction issues related to coupled combustion, heat transfer, and pollutant generation characteristics. To address the deficiencies in scientific research, meet the practical operational needs of CFB boilers, and comply with new carbon emission policies, conducting full-scale field tests on large-scale CFB boilers is needed, so that the complex gas–solid flow, combustion, and heat transfer mechanisms in the furnace can be comprehended. In this paper, issues related to large-scale CFB boilers, including the uniformity of air distribution, secondary air injection range, spatial distribution of oxygen consumption and combustion reactions, distribution of pollutant generation, hydrodynamic and heat transfer characteristics, coal feeding distribution characteristics, coal diffusion characteristics under thermal operating conditions, and engineering research on anti-wear technology, are reviewed. By integrating practical engineering applications, the basic methods and measurement techniques used in full-scale field tests for large-scale CFB boilers are summarized, providing a practical reference for conducting engineering tests with large-scale CFB boilers

Ultrasound-Activated NIR Chemiluminescence for Deep Tissue and Tumor Foci Imaging

Fluorescence imaging requires real-time external light excitation; however, it has the drawbacks of autofluorescence and shallower penetration depth, limiting its application in deep tissue imaging. At the same time, ultrasound (US) has high spatiotemporal resolution, deep penetrability, noninvasiveness, and precise localization of lesions; thus, it can be a promising alternative to light. However, US-activated luminescence has been rarely reported. Herein, an US-activated near-infrared (NIR) chemiluminescence (CL) molecule, namely, PNCL, is designed by protoporphyrin IX as a sonosensitizer moiety and a phenoxy-dioxetane precursor containing a dicyanomethyl chromone acceptor scaffold (NCL) as the US-responsive moiety. After therapeutic US radiation (1 MHz), the singlet oxygen (1O2), as an “intermediary”, oxidizes the enol-ether bond of the NCL moiety and then emits NIR light via spontaneous decomposition. Combining the deep penetrability of US with a high signal-to-background ratio of NIR CL, the designed probe PNCL successfully realizes US-activated deep tissue imaging (∼20 mm) and selectively turns on signals in specific tumor foci. Bridging US chemistry with luminescence using an “intermediary” will provide new imaging methods for accurate cancer diagnosis