从蚕的生命到艺术：中国古代生命观的哲学表达

中国考古出土的蚕业实物及蚕的艺术形象比较丰富,蚕的艺术形象如蚕纹、陶蚕蛹、牙雕蚕、玉石蚕、铜蚕、金蚕等,可统称为"蚕的模拟形态"。对蚕的模拟形态的功用,已有的诸多解释都有待完善。研究表明,蚕的模拟形态或艺术形象表达的功用或为饰品,或为装饰图案,或有待进一步考究。但无论哪种功用,用"蚕"这一形象都蕴含了特有的用意。通过对中国古代生命观的考察,文章认为蚕的艺术形象折射出相应的中国古代哲学生命观,即中国古人追求的死而复生、生生不息、羽化成仙、长乐无极等观念。     

Differential gene expression of the healthy conjunctiva during the day

PurposeTo determine if there is diurnal variation in gene expression in normal healthy conjunctival cells.MethodsBulbar conjunctival swab samples were collected from four healthy subjects in the morning and evening of the same day. The two swab samples were taken from one eye of each participant, with a minimum of five hours gap between the two samples. RNA was extracted and analysed using RNA sequencing (RNA-Seq).ResultsA total of 121 genes were differentially expressed between the morning and the evening conjunctival samples, of which 94 genes were upregulated in the morning, and 27 genes were upregulated in the evening. Many of the genes that were upregulated in the morning were involved in defence, cell turnover and regulation of gene expression, while the genes upregulated in the evening were involved in signalling and mucin production.ConclusionsThis study has identified several genes whose expression changes over the course of the day. Knowledge of diurnal variations of conjunctival gene expression provides an insight into the regulatory status of the healthy eye and provides a baseline for examining changes during ocular surface disease.     

Optimal design and operation of integrated microgrids under intermittent renewable energy sources coupled with green hydrogen and demand scenarios

Renewable energy integration into existing or new energy hubs together with Green technologies such as Power to Gas and Green Hydrogen has become essential because of the aim of keeping the average global temperature rise within 2 ^°C with regard to the Paris Agreement. Hence, all energy markets are expected to face substantial transitions worldwide. On the other hand, investigation of renewable energy systems integrated with green chemical conversion, and in particular combination of green hydrogen and synthetic methanation, is still a scarce subject in the literature in terms of optimal and simultaneous design and operation for integrated energy grids under weather intermittency and demand uncertainty. In fact, the integration of such promising new technologies has been studied mainly in the operational phase, without considering design and management simultaneously. Thus, in this work, a multi-period mixed-integer linear programming (MILP) model is formulated to deal with the aforementioned challenges. Under current carbon dioxide limitations dictated by the Paris Agreement, this model computes the best configuration of the renewable and non-renewable-based generators, their optimal rated powers, capacities and scheduling sequences from a large candidate pool containing thirty-nine different equipment simultaneously. Moreover, the effect of the intermittent nature of renewable resources is analyzed comprehensively under three different scenarios for a specific location. Accordingly, a practical scenario generation method is proposed in this work. It is observed that photovoltaic, oil co-generator, reciprocating ICE, micro turbine, and bio-gasifier are the equipment that is commonly chosen under the three different scenarios. Results also show that concepts such as green hydrogen and power-to-gas are currently not preferable for the investigated location. On the other hand, analysis shows that if the emission limits are getting tightened, it is expected that constructing renewable resource-based grids will be economically more feasible.     

Convolutional Neural Network Auto Encoder Channel Estimation Algorithm in MIMO-OFDM System

Higher transmission rate is one of the technological features of prominently used wireless communication namely Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO–OFDM). One among an effective solution for channel estimation in wireless communication system, specifically in different environments is Deep Learning (DL) method. This research greatly utilizes channel estimator on the basis of Convolutional Neural Network Auto Encoder (CNNAE) classifier for MIMO-OFDM systems. A CNNAE classifier is one among Deep Learning (DL) algorithm, in which video signal is fed as input by allotting significant learnable weights and biases in various aspects/objects for video signal and capable of differentiating from one another. Improved performances are achieved by using CNNAE based channel estimation, in which extension is done for channel selection as well as achieve enhanced performances numerically, when compared with conventional estimators in quite a lot of scenarios. Considering reduction in number of parameters involved and re-usability of weights, CNNAE based channel estimation is quite suitable and properly fits to the video signal. CNNAE classifier weights updation are done with minimized Signal to Noise Ratio (SNR), Bit Error Rate (BER) and Mean Square Error (MSE).     

In Vivo Simultaneous Analysis of Gene Expression by Dual-Color Luciferases in Caenorhabditis elegans

Both fluorescent and luminescent observation are widely used to examine real-time gene expression patterns in living organisms. Several fluuorescent and luminescent proteins with specific optical properties have been developed and applied for simultaneous, multi-color observation of more than two gene expression profiles. Compared to fluorescent proteins, however, the application of multi-color luminescent imaging in living organisms is still limited. In this study, we introduced two-color luciferases into the soil nematode C. elegans and performed simultaneous analysis of two gene expression profiles. Using a green-emitting luciferase Eluc (emerald luciferase) and red-emitting luciferase SLR (stable luciferase red), the expression patterns of two genes were simultaneously observed in single animals from embryonic to adult stages over its whole life span. In addition, dual gene activities were observed at the single embryo level, with the simultaneous observation of morphological changes. These are the first application of a two-color luciferase system into a whole animal and suggest that precise relationship of expression patterns of multiple genes of interest can be analyzed over the whole life of the animal, dependent on the changes in genetic and/or environmental conditions.     

Genome-Wide Analyses of the Temperature-Responsive Genetic Loci of the Pectinolytic Plant Pathogenic Pectobacterium atrosepticum

Temperature is one of the critical factors affecting gene expression in bacteria. Despite the general interest in the link between bacterial phenotypes and environmental temperature, little is known about temperature-dependent gene expression in plant pathogenic Pectobacterium atrosepticum, a causative agent of potato blackleg and tuber soft rot worldwide. In this study, twenty-nine P. atrosepticum SCRI1043 thermoregulated genes were identified using Tn5-based transposon mutagenesis coupled with an inducible promotorless gusA gene as a reporter. From the pool of 29 genes, 14 were up-regulated at 18 °C, whereas 15 other genes were up-regulated at 28 °C. Among the thermoregulated loci, genes involved in primary bacterial metabolism, membrane-related proteins, fitness-corresponding factors, and several hypothetical proteins were found. The Tn5 mutants were tested for their pathogenicity in planta and for features that are likely to remain important for the pathogen to succeed in the (plant) environment. Five Tn5 mutants expressed visible phenotypes differentiating these mutants from the phenotype of the SCRI1043 wild-type strain. The gene disruptions in the Tn5 transposon mutants caused alterations in bacterial generation time, ability to form a biofilm, production of lipopolysaccharides, and virulence on potato tuber slices. The consequences of environmental temperature on the ability of P. atrosepticum to cause disease symptoms in potato are discussed.     

Stem Photosynthesis—A Key Element of Grass Pea (Lathyrus sativus L.) Acclimatisation to Salinity

Grass pea (Lathyrus sativus) is a leguminous plant of outstanding tolerance to abiotic stress. The aim of the presented study was to describe the mechanism of grass pea (Lathyrus sativus L.) photosynthetic apparatus acclimatisation strategies to salinity stress. The seedlings were cultivated in a hydroponic system in media containing various concentrations of NaCl (0, 50, and 100 mM), imitating none, moderate, and severe salinity, respectively, for three weeks. In order to characterise the function and structure of the photosynthetic apparatus, Chl a fluorescence, gas exchange measurements, proteome analysis, and Fourier-transform infrared spectroscopy (FT-IR) analysis were done inter alia. Significant differences in the response of the leaf and stem photosynthetic apparatus to severe salt stress were observed. Leaves became the place of harmful ion (Na⁺) accumulation, and the efficiency of their carboxylation decreased sharply. In turn, in stems, the reconstruction of the photosynthetic apparatus (antenna and photosystem complexes) activated alternative electron transport pathways, leading to effective ATP synthesis, which is required for the efficient translocation of Na⁺ to leaves. These changes enabled efficient stem carboxylation and made them the main source of assimilates. The observed changes indicate the high plasticity of grass pea photosynthetic apparatus, providing an effective mechanism of tolerance to salinity stress.     

计及RSC控制的DFIG短路电流直流分量解析表达

现有文献针对计及转子变流器(RSC)控制的双馈感应风电机组(DFIG)定子短路电流解析表达,将定子磁链当作一阶直流衰减分量或忽略功率外环控制。基于DFIG电压、磁链和RSC控制方程,得到定子电流关于定子电压和定子功率的传递函数,提出定子电流的精确解析表达式。基于RSC内、外环PI参数关系,推导直流分量衰减时间常数和角频率关于PI参数的表达式。分析了RSC内外环PI参数对定子电流直流衰减分量的影响。仿真结果验证了解析表达式的准确性,为PI参数选取和保护装置测量、整定提供依据。