Identification and Functional Characterization of Squamosa Promoter Binding Protein-Like Gene TaSPL16 in Wheat (Triticum aestivum L.)

Wheat (Triticum aestivum L.) is one of the most important crops in the world. Squamosa promoter binding protein-like (SPL) proteins are plant-specific transcript factors and play critical roles in plant growth and development. The functions of many SPL gene family members were well characterized in Arabidopsis and rice, in contrast, research on wheat SPL genes is lagging behind. In this study, we cloned and characterized TaSPL16, an orthologous gene of rice OsSPL16, in wheat. Three TaSPL16 homoeologs are located on the short arms of chromosome 7A, 7B, and 7D, and share more than 96% sequence identity with each other. All the TaSPL16 homoeologs have three exons and two introns, with a miR156 binding site in their last exons. They encode putative proteins of 407, 409, and 414 amino acid residues, respectively. Subcellular localization showed TaSPL16 distribution in the cell nucleus, and transcription activity of TaSPL16 was validated in yeast. Analysis of the spatiotemporal expression profile showed that TaSPL16 is highly expressed in young developing panicles, lowly expressed in developing seeds and almost undetectable in vegetative tissues. Ectopic expression of TaSPL16 in Arabidopsis causes a delay in the emergence of vegetative leaves (3–4 days late), promotes early flowering (5–7 days early), increases organ size, and affects yield-related traits. These results demonstrated the regulatory roles of TaSPL16 in plant growth and development as well as seed yield. Our findings enrich the existing knowledge on SPL genes in wheat and provide valuable information for further investigating the effects of TaSPL16 on plant architecture and yield-related traits of wheat

Enzyme Kinetics Studies of Nucleoside Diphosphate Kinase in Human Erythrocytes and Frequency Distribution in Healthy Subjects and Transplant Recipients in Chinese Han Population

ABSTRACT Nucleoside diphosphate kinase (NDPK), as a house-keeping protein, involves in various molecular processes including signal transduction, energy and drug metabolism. The main objective was to investigate NDPK kinetics in human erythrocytes and to monitor the frequency distribution of NDPK activity levels in Chinese healthy subjects and transplant recipients. METHODS: NDPK activity in erythrocytes was detected by a validated ion-pair high-performance liquid chromatogram method. NDPK kinetics studies were carried out systematically. NDPK activity levels were determined in 500 healthy subjects, 250 kidney and 250 liver transplant recipients in Chinese Han population. RESULTS: Thermal and pH stability studies indicated NDPK was relatively stable at temperature 30-45ºC and pH 6.0-9.0. In substrate dependency study, the apparent Michaelis-Menten constant (K m ) and maximum velocity of enzymatic reaction (V max ) increased with concentration of substrates. Meanwhile, in product inhibition study, with the increasing concentration of dATP, the V max of dADP decreased with constant K m and K m of dGTP increased with constant V max . NDPK activity levels revealed a 7-fold variability and were not normally distributed in all groups. NDPK activity levels were significantly (P<0.05) higher in transplant group than those in health group. Additionally, much higher NDPK activity levels had been shown (P<0.001) in liver transplant recipients when compared to kidney transplant cases. CONCLUSIONS: NDPK kinetics studies indicated substrate dependency of NDPK and a "ping-pong" mechanism for production inhibition. Skewness distributions of NDPK activity levels were shown in the study population. The transplant recipients showed higher NDPK activity levels when compared to healthy subjects

Barriers of Cross Cultural Communication in Multinational Firms : A Case Study of Swedish Company and its Subsidiary in China

In times of rapid growth, both in terms of economic development and globalization, an increasing number of firms extend their businesses abroad. A subsequent challenge of this development is the managerial implications of cross-cultural management. This study employs a qualitative approach in a single case study of Swedish company and its subsidiary in China. After reviewing the previous studies, the authors summarize the differences of management style, staff behaviors and communication system in different culture context and find the barriers of cross cultural communication in multinational firms. The findings of this study indicate that the barriers of communication come from the national culture’s influence on the work place and behaviors of people with different identity. Moreover, culture also influences people’s way of thinking and behaving and result in different understandings toward vision and purposes of firms

Expressway Surface Point Extraction from Mobile Laser Scanning Point Clouds

According to the problem between the cost of production, efficiency and data accuracy of expressway surface terrain data, this paper presents a fast ground point extraction method of expressway road surface from mobile laser scanning (MLS) point cloud data. Through the analysis of the spatial characteristics of MLS point cloud data in expressway, a triangle plane constraint (TPC) method is used to extract initial road surface points in the grid, and then multi-scale neighborhood iterative analysis (MNIA) method is proposed to further filter them, finally the high density road surface points are extracted from the original points based on neighborhood slope which is estimated by iterative least square within eight neighboring grid. Experiments are processed to verify the effectiveness of the algorithm by using two groups of actual point cloud data

Polyphasic Characterization of Yeasts and Lactic Acid Bacteria Metabolic Contribution in Semi-Solid Fermentation of Chinese Baijiu (Traditional Fermented Alcoholic Drink): Towards the Design of a Tailored Starter Culture

Chinese Baijiu is principally produced through a spontaneous fermentation process, which involves complex microorganism communities. Among them, yeasts and lactic acid bacteria (LAB) are important communities. The study examined the isolated strains from fermented grains of Baijiu regarding their activity of α-amylase and glucoamylase, ethanol tolerance, glucose utilization, as well as metabolite production in the process of laboratory-scale sorghum-based fermentation. Selected strains (Saccharomycopsis fibuligera 12, Saccharomyces cerevisiae 3, and Pediococcus acidilactici 4) were blended in different combinations. The influence of selected strains on the metabolic variation in different semi-solid fermentations was investigated by gas chromatography−mass spectrometry (GC−MS) accompanied by multivariate statistical analysis. According to the principal component analysis (PCA), the metabolites produced varied in different mixtures of pure cultures. S. fibuligera produced various enzymes, particularly α-amylase and glucoamylase, and exhibited a better performance compared with other species regarding the ability to convert starch to soluble sugars and positively affect the production process of volatile compounds. S. cerevisiae had a high fermentation capacity, thereby contributing to substrates utilization. Lactic acid bacteria had a good ability to produce lactic acid. This study attaches importance to the special functions of S. fibuligera, S. cerevisiae, and P. acidilactici in Chinese Baijiu making, and investigates their metabolic characteristics in the process of lab-scale semi-solid fermentation

Numerical Simulation and Optimization of a Phase-Change Energy Storage Box in a Modular Mobile Thermal Energy Supply System

Featuring phase-change energy storage, a mobile thermal energy supply system (M-TES) demonstrates remarkable waste heat transfer capabilities across various spatial scales and temporal durations, thereby effectively optimizing the localized energy distribution structure—a pivotal contribution to the attainment of objectives such as “carbon peak” and “carbon neutral”. To heighten the efficiency of energy transfer for mobile heating, this research introduces the innovative concept of modular storage and transportation. This concept is brought to life through the development of a meticulously designed modular mobile phase-change energy storage compartment system. Employing computational fluid dynamics (CFD), an in-depth exploration into the performance of the modular M-TES container and the adapted phase-change material (PCM) is conducted. By implementing fin arrangements on the inner wall of the heat storage module, a remarkable upsurge in the liquid phase-transition rate of the phase-change material is achieved in comparison to the design lacking fins—this improvement approximating around 30%. However, it is essential to acknowledge that the augmentation in heat transfer gradually recedes with the proliferation of fins or an escalation in their height. Moreover, the integration of expanded graphite into erythritol emerges as profoundly effective in amplifying the thermal conductivity of the PCM. Notably, with the addition of a 15.2% volume fraction of expanded graphite to erythritol, the duration of heat storage experiences a drastic reduction to nearly 10% of its original duration, thereby signifying a momentous advancement in thermal performance

A Recurrent Adaptive Network: Balanced Learning for Road Crack Segmentation with High-Resolution Images

Road crack segmentation based on high-resolution images is an important task in road service maintenance. The undamaged road surface area is much larger than the damaged area on a highway. This imbalanced situation yields poor road crack segmentation performance for convolutional neural networks. In this paper, we first evaluate the mainstream convolutional neural network structure in the road crack segmentation task. Second, inspired by the second law of thermodynamics, an improved method called a recurrent adaptive network for a pixelwise road crack segmentation task is proposed to solve the extreme imbalance between positive and negative samples. We achieved a flow between precision and recall, similar to the conduction of temperature repetition. During the training process, the recurrent adaptive network (1) dynamically evaluates the degree of imbalance, (2) determines the positive and negative sampling rates, and (3) adjusts the loss weights of positive and negative features. By following these steps, we established a channel between precision and recall and kept them balanced as they flow to each other. A dataset of high-resolution road crack images with annotations (named HRRC) was built from a real road inspection scene. The images in HRRC were collected on a mobile vehicle measurement platform by high-resolution industrial cameras and were carefully labeled at the pixel level. Therefore, this dataset has sufficient data complexity to objectively evaluate the real performance of convolutional neural networks in highway patrol scenes. Our main contribution is a new method of solving the data imbalance problem, and the method of guiding model training by analyzing precision and recall is experimentally demonstrated to be effective. The recurrent adaptive network achieves state-of-the-art performance on this dataset

A Concave Hull Methodology for Calculating the Crown Volume of Individual Trees Based on Vehicle-Borne LiDAR Data

Crown volume is an important tree factor used in forest surveys as a prerequisite for estimating biomass and carbon stocks. This study developed a method for accurately calculating the crown volume of individual trees from vehicle-borne laser scanning (VLS) data using a concave hull by slices method. CloudCompare, an open-source three-dimensional (3D) point cloud and mesh processing software package, was used with VLS data to segment individual trees from which single tree crowns were extracted by identifying the first branch point of the tree. The slice thickness and number to be fitted to the canopy point cloud were adaptively determined based on the change rate in area with height, with the area of each slice calculated using the concave hull algorithm with portions of the crown regarded as truncated cones. The overall volume was then calculated as the sum of all sub-volumes. The proposed method was experimentally validated on 30 urban trees by comparing the crown volumes calculated using the proposed method with those calculated using five existing methods (manual measurement, 3D convex hull, 3D alpha shape, convex hull by slices, and voxel-based). The proposed method produced the smallest average crown volume. Gaps and holes in the point cloud were regarded as part of the crown by the manual measurement, 3D convex hull, and convex hull by slices method, resulting in the calculated volume being higher than the true value; the proposed method reduced this effect. These results indicate that the concave hull by slices method can more effectively calculate the crown volume of a single tree from VLS data