Distinguishing Attacks on MAC/HMAC Based on A New Dedicated Compression Function Framework

A new distinguishing attack on HMAC and NMAC based on a dedicated compression function framework H, proposed in ChinaCrypt2008, is first presented in this paper, which distinguish the HMAC/NMAC-H from HMAC/NMAC with a random function. The attack needs 2^{17} chosen messages and 223 queries, with a success rate of 0.873. Furthermore, according to distinguishing attack on SPMAC-H, a key recovery attack on the SPMAC-H is present, which recover all 256-bit key with 2^{17)chosen messages, 2^{19} queries, and (t+1)x8 times decrypting algorithms

Geographic and Climatic Attributions of Autumn Land Surface Phenology Spatial Patterns in the Temperate Deciduous Broadleaf Forest of China

Autumn vegetation phenology plays a critical role in identifying the end of the growing season and its response to climate change. Using the six vegetation indices retrieved from moderate resolution imaging spectroradiometer data, we extracted an end date of the growing season (EOS) in the temperate deciduous broadleaf forest (TDBF) area of China. Then, we validated EOS with the ground-observed leaf fall date (LF) of dominant tree species at 27 sites and selected the best vegetation index. Moreover, we analyzed the spatial pattern of EOS based on the best vegetation index and its dependency on geo-location indicators and seasonal temperature/precipitation. Results show that the plant senescence reflectance index-based EOS agrees most closely with LF. Multi-year averaged EOS display latitudinal, longitudinal and altitudinal gradients. The altitudinal sensitivity of EOS became weaker from 2000 to 2012. Temperature-based spatial phenology modeling indicated that a 1 K spatial shift in seasonal mean temperature can cause a spatial shift of 2.4–3.6 days in EOS. The models explain between 54% and 73% of the variance in the EOS timing. However, the influence of seasonal precipitation on spatial variations of EOS was much weaker. Thus, spatial temperature variation controls the spatial patterns of EOS in TDBF of China, and future temperature increase might lead to more uniform autumn phenology across elevations

High-Resolution 3D Heart Models of Cardiomyocyte Subpopulations in Cleared Murine Heart

Biological tissues are naturally three-dimensional (3D) opaque structures, which poses a major challenge for the deep imaging of spatial distribution and localization of specific cell types in organs in biomedical research. Here we present a 3D heart imaging reconstruction approach by combining an improved heart tissue-clearing technique with high-resolution light-sheet fluorescence microscopy (LSFM). We have conducted a three-dimensional and multi-scale volumetric imaging of the ultra-thin planes of murine hearts for up to 2,000 images per heart in x-, y-, and z three directions. High-resolution 3D volume heart models were constructed in real-time by the Zeiss Zen program. By using such an approach, we investigated detailed three-dimensional spatial distributions of two specific cardiomyocyte populations including HCN4 expressing pacemaker cells and Pnmt(+) cell-derived cardiomyocytes by using reporter mouse lines Hcn4(DreER/tdTomato) and Pnmt(Cre/ChR2−tdTomato). HCN4 is distributed throughout right atrial nodal regions (i.e., sinoatrial and atrioventricular nodes) and the superior-inferior vena cava axis, while Pnmt(+) cell-derived cardiomyocytes show distinct ventral, left heart, and dorsal side distribution pattern. Our further electrophysiological analysis indicates that Pnmt + cell-derived cardiomyocytes rich left ventricular (LV) base is more susceptible to ventricular arrhythmia under adrenergic stress than left ventricular apex or right ventricle regions. Thus, our 3D heart imaging reconstruction approach provides a new solution for studying the geometrical, topological, and physiological characteristics of specific cell types in organs

The Impact of Food Quality Information Services on Food Supply Chain Pricing Decisions and Coordination Mechanisms Based on the O2O E-Commerce Mode

This paper considers the price conflict problem between the online channel of a food processing factory and the offline channel of the food retailers in food supply chains by analyzing the pricing decisions and coordination mechanisms between the food processing factory and food retailers under the influence of a food quality information service. First, the Stackelberg game method and the Bertrand game method are used to optimize the pricing decisions with the goal of maximizing the profits of the food processing factory and retailer. The analysis shows that the food quality information service level is positively correlated with the price of the factory’s own channel, and the influence of the food quality information service level on the price of the food processing factory’s or the food retailer’s own channel is stronger than its influence on the price of a competitor’s channel. Second, the food supply chain members’ pricing decisions are analyzed using the case analysis method by considering practical problems in the food supply chain. The results indicate that the food processing factory should use the Stackelberg game to make pricing decisions. However, it is optimal for the food retailer to make pricing decisions under the Bertrand game, and the total profit of the food supply chain is optimized under centralized decision making. Finally, we use both the quantitative discount mechanism and the Stackelberg game method to analyze the profits obtained by the food processing factory and retailer. The results indicate that the food processing factory should implement a quantitative discount mechanism when the quantity discount coefficient is greater than 0.4, and the retailer should implement a quantity discount mechanism when the quantity discount coefficient is in the range of 0.25 to 0.4

Precipitation and Minimum Temperature are Primary Climatic Controls of Alpine Grassland Autumn Phenology on the Qinghai-Tibet Plateau

Autumn phenology is a crucial indicator for identifying the alpine grassland growing season’s end date on the Qinghai-Tibet Plateau (QTP), which intensely controls biogeochemical cycles in this ecosystem. Although autumn phenology is thought to be mainly influenced by the preseason temperature, precipitation, and insolation in alpine grasslands, the relative contributions of these climatic factors on the QTP remain uncertain. To quantify the impacts of climatic factors on autumn phenology, we built stepwise linear regression models for 91 meteorological stations on the QTP using in situ herb brown-off dates, remotely sensed autumn phenological metrics, and a multi-factor climate dataset during an optimum length period. The results show that autumn precipitation has the most extensive influence on interannual variation in alpine grassland autumn phenology. On average, a 10 mm increase in autumn precipitation during the optimum length period may lead to a delay of 0.2 to 4 days in the middle senescence date (P < 0.05) across the alpine grasslands. The daily minimum air temperature is the second most important controlling factor, namely, a 1 °C increase in the mean autumn minimum temperature during the optimum length period may induce a delay of 1.6 to 9.3 days in the middle senescence date (P < 0.05) across the alpine grasslands. Sunshine duration is the third extensive controlling factor. However, its influence is spatially limited. Moreover, the relative humidity and wind speed also have strong influences at a few stations. Further analysis indicates that the autumn phenology at stations with less autumn precipitation is more sensitive to precipitation variation than at stations with more autumn precipitation. This implies that autumn drought in arid regions would intensely accelerate the leaf senescence of alpine grasslands. This study suggests that precipitation should be considered for improving process-based autumn phenology models in QTP alpine grasslands

Potential anti-Alzheimer’s disease effect of defatted walnut powder through remodeling gut microbiota and modulating amino acid metabolite levels

Alzheimer’s disease (AD) is a major health challenge due to its high morbidity. This study aimed to investigate the potential effects of defatted walnut powder (DWP), which is the residue obtained after extracting oil from walnut kernels, on memory improvement. HPLC was used to establish the fingerprints of 14 batches of DWP extract (DWPE) obtained from various origins. Behavioral experiments and functional indicators were conducted to evaluate the efficacy of DWPE on AD. The results indicated that DWPE regulated the cholinergic system disorder in brain tissue. Additionally, DWPE reduced oxidative stress levels, neuroinflammation, and the damage of pyramidal cells in both the cortex and the hippocampal CA3 region. Subsequently, targeted amino acid metabolomics, gut microbiota sequencing and fecal microbiota transplantation confirmed that DWPE played a regulatory role in amino acid metabolism regulated by gut microbiota, effectively decreasing the levels of fat-soluble neurotoxic factor ammonia

Characterization, Classification, and Authentication of Polygonatum sibiricum Samples by Volatile Profiles and Flavor Properties

The importance of monitoring key aroma compounds as food characteristics to solve sample classification and authentication is increasing. The rhizome of Polygonatum sibiricum (PR, Huangjing in Chinese) has great potential to serve as an ingredient of functional foods owing to its tonic effect and flavor properties. In this study, we aimed to characterize and classify PR samples obtained from different processing levels through their volatile profiles and flavor properties by using electronic nose, electronic tongue, and headspace gas chromatography-mass spectrometry. Nine flavor indicators (four odor indicators and five taste indicators) had a strong influence on the classification ability, and a total of 54 volatile compounds were identified in all samples. The traditional Chinese processing method significantly decreased the contents of aldehydes and alkanes, while more ketones, nitrogen heterocycles, alcohols, terpenoids, sulfides, and furans/pyrans were generated in the processing cycle. The results confirmed the potential applicability of volatile profiles and flavor properties for classification of PR samples, and this study provided new insights for determining the processing level in food and pharmaceutical industries based on samples with specific flavor characteristics

Effect of Near-Surface Dopants on the Epitaxial Growth of h-BN on Metal Surfaces

Epitaxial growth of ultrathin overlayers on solid substrate is critically dependent on the surface structure, and in this work near-surface doping is identified as another important growth factor. It is shown that growth of hexagonal boron nitride (h-BN) on Ni(111) through chemical vapor deposition or surface ammonization can be strongly modulated by near-surface B doping. Epitaxial h-BN islands form on clean Ni(111) surface, while both epitaxial and nonepitaxial h-BN islands grow on Ni(111) containing near-surface B atoms. Quantitative correlation of epitaxial growth and near-surface doping is unambiguously demonstrated. In situ spatially resolved surface science measurements based on photoemission electron microscopy and low energy electron microscopy in combination with density function calculations reveal that near-surface B atoms weaken the interaction between h-BN overlayer and Ni surface, which favor the nonepitaxial and metastable h-BN structures. The present work suggests that near-surface doping acts as an effective route to influence epitaxial growth of two-dimensional (2D) material overlayers on solids