Lokalno diskriminantna projekcija difuzije i njena primjena za prepoznavanje emocionalnog stanja iz govornog signala

The existing Diffusion Maps method brings diffusion to data samples by Markov random walk. In this paper, to provide a general solution form of Diffusion Maps, first, we propose the generalized single-graph-diffusion embedding framework on the basis of graph embedding framework. Second, by designing the embedding graph of the framework, an algorithm, namely Locally Discriminant Diffusion Projection (LDDP), is proposed for speech emotion recognition. This algorithm is the projection form of the improved Diffusion Maps, which includes both discriminant information and local information. The linear or kernelized form of LDDP (i.e., LLDDP or KLDDP) is used to achieve the dimensionality reduction of original speech emotion features. We validate the proposed algorithm on two widely used speech emotion databases, EMO-DB and eNTERFACE\u2705. The experimental results show that the proposed LDDP methods, including LLDDP and KLDDP, outperform some other state-of-the-art dimensionality reduction methods which are based on graph embedding or discriminant analysis.Postojeće metode mapiranja difuzije u uzorke podataka primjenjuju Markovljevu slučajnu šetnju. U ovom radu, kako bismo pružili općenito rješenje za mapiranje difuzije, prvo predlažemo generalizirano okruženje za difuziju jednog grafa, zasnovano na okruženju za primjenu grafova. Drugo, konstruirajući ugrađeni graf, predlažemo algoritam lokalno diskriminantne projekcije difuzije (LDDP) za prepoznavanje emocionalnog stanja iz govornog signala. Ovaj algoritam je projekcija poboljšane difuzijske mape koja uključuje diskriminantnu i lokalnu informaciju. Linearna ili jezgrovita formulacija LDDP-a (i.e., LLDDP ili KLDDP) koristi se u svrhu redukcije dimenzionalnosti originalnog skupa značajki za prepoznavanje emocionalnog stanja iz govornog signala. Predloženi algoritam testiran je nad dvama široko korištenim bazama podataka za prepoznavanje emocionalnog stanja iz govornog signala, EMO-DB i eNTERFACE\u2705. Eksperimentalni rezultati pokazuju kako predložena LDDP metoda, uključujući LLDDP i KLDDP, pokazuje bolje ponašanje od nekih drugih najsuvremenijih metoda redukcije dimenzionalnosti, zasnovanim na ugrađenim grafovima ili analizi diskriminantnosti

Transcriptome Comparison between Fetal and Adult Mouse Livers: Implications for Circadian Clock Mechanisms

Microarray transcriptome analyses of fetal mouse liver did not detect circadian expression rhythms of clock genes or clock-controlled genes, although some rhythmic transcripts that were likely not driven by endogenous cellular clocks were identified. This finding reveals a key distinction between the circadian oscillators in fetal and adult mouse livers. Thus, in this study, the transcriptomes of fetal and adult livers were systematically compared to identify differences in the gene expression profiles between these two developmental stages. Approximately 1000 transcripts were differentially enriched between the fetal and adult livers. These transcripts represent genes with cellular functions characteristic of distinct developmental stages. Clock genes were also differentially expressed between the fetal and adult livers. Developmental differences in liver gene expression might have contributed to the differences in oscillation status and functional states of the cellular circadian clock between fetal and adult livers

Epigenetic Control of Circadian Clock Operation during Development

The molecular players of circadian clock oscillation have been identified and extensively characterized. The epigenetic mechanisms behind the circadian gene expression control has also been recently studied, although there are still details to be illucidated. In this review, we briefly summarize the current understanding of the mammalian clock. We also provide evidence for the lack of circadian oscillation in particular cell types. As the circadian clock has intimate interaction with the various cellular functions in different type of cells, it must have plasticity and specicity in its operation within different epigenetic environments. The lack of circadian oscillation in certain cells provide an unique opportunity to study the required epigenetic environment in the cell that permit circadian oscillation and to idenfify key influencing factors for proper clock function. How epigenetic mechansims, including DNA methylaiton and chromatin modifications, participate in control of clock oscillation still awaits future studies at the genomic scale

Mitigating Greenhouse Gas Emissions from Winter Production of Agricultural Greenhouses

Consuming conventional fossil fuel, such as coal, natural gas, and oil, to heat agricultural greenhouses has contributed to the climate change and air pollutions regionally and globally, so the clean energy sources have been increasingly applied to replace fossil energies in heating agricultural greenhouses, especially in urban area. To assess the environment performance (e.g., greenhouse gas (GHG) emissions) of the ground source heat pump system (GSHPs) for heating agricultural greenhouses in urban area, a GSHPs using the shallow geothermal energy (SGE) in groundwater was applied to heat a Chinese solar greenhouse (G1) and a multispan greenhouse (G2) in Beijing (latitude 39°40′ N), the capital city of China. Emission rates of the GSHPs for heating the G1 and G2 were quantified to be 0.257–0.879 g CO2 eq. m−2 day−1. The total GHG emissions from heating greenhouses in Beijing with the GSHPs were quantified as 1.7–2.9 Gt CO2 eq. year−1 based on the electricity from the coal-fired power plant (CFPP) and the gas-fired power plant (GFPP). Among different stages of the SGE flow, the SGE promotion contributed most GHG emissions (66%) in total due to the higher consumption of electricity in compressors. The total GHG emissions from greenhouses heating with the coal-fired heating system (CFHs) and gas-fired heating system (GFHs) were quantified as 2.3–5.2 Gt CO2 eq. year−1 in Beijing. Heating the G1 and G2 with the GSHPs powered by the electricity from the CFPP, the equivalent CO2 emissions were 43% and 44% lower than directly burning coal with the CFHs but were 46% and 44% higher than the GFHs that burn natural gas. However, when using the GFPP-generated electricity to run the GSHPs, the equivalent CO2 emissions would be 84% and 47% lower than the CFHs and the GFHs, respectively

Mixture theory-based SPH model for submerged landslide

A novel SPH model aimed at solving the coupled water-soil problems is proposed based on the mixture theory. This method is featured with the spatially overlapped dual continua for both fluid and solid phases. The water phase is modeled as a weakly-compressible Newtonian fluid, and the soil phase is modeled using an elastoplastic constitutive model. The benchmark problem, fully submerged soil subjected to gravity, is examined to validate this SPH model. Finally, a submerged landslide is simulated to demonstrate the capability of the proposed SPH model in solving the dynamic soil–water coupling problems