184 research outputs found
The Green Effects of DIF: Corporate Green Production’s Stimulation of Residents’ Low-Carbon Consumption
No full textAgainst the background of full implement of China’s “dual-carbon” strategy and the rapid expansion of the digital economy, clarifying the mechanisms through which digital inclusive finance (DIF) contributes to green consumption is of both theoretical and practical importance. Using a matched panel dataset of Chinese prefecture-level cities and listed firms from 2011 to 2019, this study develops an integrated analytical framework linking DIF, corporate green production, and residents’ low-carbon consumption preferences. Two-way fixed-effects models and firm-level mediation regressions are employed to examine the green effects of DIF. The results indicate that: (1) DIF significantly enhances residents’ low-carbon consumption preferences, and this effect remains robust after controlling for socioeconomic characteristics; (2) DIF strengthens corporate green production by increasing green total factor productivity, stimulating green technological innovation, and alleviating financing constraints; (3) Corporate green production further reinforces residents’ low-carbon consumption preferences through supply-side channels such as the expansion and upgrading of green products, as well as demand-side channels including environmental improvement and green information spillovers; (4) DIF exhibits a clear chain transmission mechanism, operating through the pathway “DIF → corporate green production → residents’ low-carbon consumption preferences.” The innovation of this paper lies in: constructing a green transmission mechanism identification framework covering both the urban and enterprise dimensions, and for the first time systematically verifying the path through which DIF influences residents’ preference for low-carbon consumption by promoting green production of enterprises, and revealing the formation logic of green consumption from both the supply and demand sides. The research conclusions provide empirical evidence for the coordinated design of digital finance and green development policies
Analysis and Remedy of Negativity Problem in Hybrid Stochastic Simulation Algorithm and its Application
No full textBMC Bioinformatics
No full textBackground
The hybrid stochastic simulation algorithm, proposed by Haseltine and Rawlings (HR), is a combination of differential equations for traditional deterministic models and Gillespie’s algorithm (SSA) for stochastic models. The HR hybrid method can significantly improve the efficiency of stochastic simulations for multiscale biochemical networks. Previous studies on the accuracy analysis for a linear chain reaction system showed that the HR hybrid method is accurate if the scale difference between fast and slow reactions is above a certain threshold, regardless of population scales. However, the population of some reactant species might be driven negative if they are involved in both deterministic and stochastic systems.
Results
This work investigates the negativity problem of the HR hybrid method, analyzes and tests it with several models including a linear chain system, a nonlinear reaction system, and a realistic biological cell cycle system. As a benchmark, the second slow reaction firing time is used to measure the effect of negative populations on the accuracy of the HR hybrid method. Our analysis demonstrates that usually the error caused by negative populations is negligible compared with approximation errors of the HR hybrid method itself, and sometimes negativity phenomena may even improve the accuracy. But for systems where negative species are involved in nonlinear reactions or some species are highly sensitive to negative species, the system stability will be influenced and may lead to system failure when using the HR hybrid method. In those circumstances, three remedies are studied for the negativity problem.
Conclusions
The results of different models and examples suggest that the Zero-Reaction rule is a good remedy for nonlinear and sensitive systems considering its efficiency and simplicity.Published versio
Understanding and Enhancement of Internal Clustering Validation Indexes for Categorical Data
No full textClustering is one of the main tasks of machine learning. Internal clustering validation indexes (CVIs) are used to measure the quality of several clustered partitions to determine the local optimal clustering results in an unsupervised manner, and can act as the objective function of clustering algorithms. In this paper, we first studied several well-known internal CVIs for categorical data clustering, and proved the ineffectiveness of evaluating the partitions of different numbers of clusters without any inter-cluster separation measures or assumptions; the accurateness of separation, along with its coordination with the intra-cluster compactness measures, can notably affect performance. Then, aiming to enhance the internal clustering validation measurement, we proposed a new internal CVI—clustering utility based on the averaged information gain of isolating each cluster (CUBAGE)—which measures both the compactness and the separation of the partition. The experimental results supported our findings with regard to the existing internal CVIs, and showed that the proposed CUBAGE outperforms other internal CVIs with or without a pre-known number of clusters
Vibro-fluidised bed drying of milk powders
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Topics in Walsh Semimartingales and Diffusions: Construction, Stochastic Calculus, and Control
No full textThis dissertation is devoted to theories of processes we call ``Walsh semimartingales" and ``Walsh diffusions", as well as to related optimization problems of control and stopping. These processes move on the plane along rays emanating from the origin; and when at the origin, the processes choose the rays of their subsequent voyage according to a fixed probability measure---in a manner described by Walsh (1978) as a direct generalization of the skew Brownian motion.
We first review in Chapter 1 some key results regarding the celebrated skew Brownian motions and Walsh Brownian motions. These results include the characterization of skew Brownian motions via stochastic equations in Harrison & Shepp (1981), the construction of Walsh Brownian motions in Barlow, Pitman & Yor (1989), and the important result of Tsirel'son (1997) regarding the nature of the filtration generated by the Walsh Brownian motion.
Various generalizations of Walsh Brownian motions are described in detail in Chapter 2. We formally define there Walsh semimartingales as a subclass of planar processes we call ``semimartingales on rays". We derive for such processes Freidlin-Sheu-type change-of-variable formulas, as well as two-dimensional versions of the Harrison-Shepp equations. The actual construction of Walsh semimartingales is given next.
Walsh diffusions are then defined as a subclass of Walsh semimartingales, described by stochastic equations which involve local drift and dispersion characteristics. The associated local submartingale problems, strong Markov properties, existence, uniqueness, asymptotic behavior, and tests for explosions in finite time, are studied in turn.
Finally, with Walsh semimartingales as state-processes, we study in Chapter 3 succesively a pure optimal stopping problem, a stochastic control problem with discretionary stopping, and a stochastic game between a controller and a stopper. We derive for these problems optimal strategies in surprisingly explicit from. Crucial for the analysis underpinning these results, are the change-of-variable formulas derived in Chapter 2.
Most of the results in Chapters 2 and 3 are based on two papers, [21] and [31], both cowritten by the author of this dissertation. Some results and proofs are rearranged and rewritten here
MIF Plays a Key Role in Regulating Tissue-Specific Chondro-Osteogenic Differentiation Fate of Human Cartilage Endplate Stem Cells under Hypoxia
No full textSummaryDegenerative cartilage endplate (CEP) shows decreased chondrification and increased ossification. Cartilage endplate stem cells (CESCs), with the capacity for chondro-osteogenic differentiation, are responsible for CEP restoration. CEP is avascular and hypoxic, while the physiological hypoxia is disrupted in the degenerated CEP. Hypoxia promoted chondrogenesis but inhibited osteogenesis in CESCs. This tissue-specific differentiation fate of CESCs in response to hypoxia was physiologically significant with regard to CEP maintaining chondrification and refusing ossification. MIF, a downstream target of HIF1A, is involved in cartilage and bone metabolisms, although little is known about its regulatory role in differentiation. In CESCs, MIF was identified as a key point through which HIF1A regulated the chondro-osteogenic differentiation. Unexpectedly, unlike the traditionally recognized mode, increased nuclear-expressed MIF under hypoxia was identified to act as a transcriptional regulator by interacting with the promoter of SOX9 and RUNX2. This mode of HIF1A/MIF function may represent a target for CEP degeneration therapy
The empirical study on the relationship between value and performance of enterprise informatization investment
No full textParameter estimation of stochastic models based on limited data
No full textProgress in experimental techniques enables a more accurate quantification of genes, mRNA, and proteins at the single cell level. Provided with limited time series data from single-cell measurements, this note proposes a new quasi-Newton optimization algorithm (QNSTOP) for parameter estimation of stochastic models. To capture the stochasticity inside models and data, the random objective function is constructed based on the maximum log-likelihood of transition probabilities rather than summary statistics, which relies heavily on stochastic simulations. Simple to use and efficient, QNSTOP can find the "best" parameter vector from far away starting points in just a few iterations. Results on a bistable model match well the bistable dynamics that can only be obtained from stochastic models.</jats:p
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