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Abstract Mitochondria are major organelles involved in several processes related to energy supply, metabolism, and cell proliferation. The mitochondria function is transcriptionally regulated by mitochondria DNA (mtDNA), which encodes the key proteins in the electron transport chain that is indispensable for oxidative phosphorylation (OXPHOS). Mitochondrial transcriptional abnormalities are closely related to a variety of human diseases, such as cardiovascular diseases, and diabetes. The mitochondria transcription is regulated by the mtDNA, mitochondrial RNA polymerase (POLRMT), two transcription factors (TFAM and TF2BM), one transcription elongation (TEFM), and one known transcription termination factor (mTERFs). Dysregulation of these factors directly leads to altered expression of mtDNA in tumor cells, resulting in cellular metabolic reprogramming and mitochondrial dysfunction. This dysregulation plays a role in modulating tumor progression. Therefore, understanding the role of mitochondrial transcription in cancer can have implications for cancer diagnosis, prognosis, and treatment. Targeting mitochondrial transcription or related pathways may provide potential therapeutic strategies for cancer treatment. Additionally, assessing mitochondrial transcriptional profiles or biomarkers in cancer cells or patient samples may offer diagnostic or prognostic information.

Coupling of surface plasmon polaritons (SPPs) supported by graphene and hyperbolic phonon polaritons (HPPs) supported by hyperbolic materials (HMs) could effectively promote photon tunneling, and hence the radiative heat transfer. In this work, we investigate the polariton hybridization phenomena on near-field radiative heat transfer (NFRHT) in multilayer heterostructures, which consist of periodic graphene/α-MoO3 cells. Numerical results show that increasing the graphene/α-MoO3 cells can effectively enhance the NFRHT when the vacuum gap is less than 50 nm, but suppresses the enhanced performance with larger gap distance. This depends on the coupling of SPPs and HPPs in the periodic structure, which is analyzed by the energy transmission coefficients distributed in the wavevector space. The influence of the thickness of the α-MoO3 film and the chemical potential of graphene on the NFRHT is investigated. The findings in this work may guide designing high-performance near-field energy transfer and conversion devices based on coupling polaritons.

Abstract Background Spring irrigation with freshwater is widely used to reduce soil salinity and increase the soil water content in arid areas. However, this approach requires a huge amount of freshwater, which is problematic given limited freshwater resources. Utilizing brackish water for spring irrigation in combination with magnetized water technology may be a promising alternative strategy. Results The objective of this study was to evaluate the effects of four spring irrigation methods (freshwater spring irrigation (FS), magnetized freshwater spring irrigation (MFS), brackish water spring irrigation (BS), and magnetized brackish water spring irrigation (MBS)) on soil water and salt distribution, emergence, growth, and photosynthetic characteristics of cotton seedlings. The results showed that for both freshwater and brackish water, magnetized water irrigation can increase the soil water content for improved desalination effect of irrigation water. Additionally, spring irrigation with magnetized water promoted cotton emergence and seedling growth. Compared with FS treatment, cotton finial emergence rate, emergence index, vigor index, plant height, stem diameter, and leaf area index of MFS treatment increased by 6.25, 7.19, 12.98, 15.60, 8.91, and 20.57%, respectively. Compared with BS treatment, cotton finial emergence rate, emergence index, vigor index, plant height, stem diameter, and leaf area index of MBS treatment increased by 27.78, 39.83, 74.79, 26.40, 14.01, and 57.22%, respectively. Interestingly, we found that spring irrigation with magnetized water can increase the chlorophyll content and net photosynthetic rate of cotton seedlings. The rectangular hyperbolic model (RHM), non-rectangular hyperbolic model (NRHM), exponential model (EM), and modified rectangular hyperbolic model (MRHM) were used to fit and compare the cotton light response curve, and MRHM was determined to be the optimal model to fit the data. This model was used to calculate the photosynthetic parameters of cotton. Compared with FS treatment, the net photosynthetic rate (P nmax ), dark respiration rate (R d ), light compensation point (I c ), light saturation point (I sat ), and the range of available light intensity (ΔI) of MFS were increased by 5.18, 3.41, 3.18, 2.29 and 2.19%, respectively. Compared with BS treatment, the P nmax , R d , I c , I sat and ΔI of MBS were increased by 26.44, 29.48, 30.05, 5.13, and 2.27%, respectively. Conclusion The results show that spring irrigation with magnetized brackish water may be a feasible method to reduce soil salt and increase soil water content when freshwater resources are insufficient.

Grid emission factor has become the most critical variable in carbon market quota allocation and carbon footprint accounting of international trade products. Different grid emission factors will lead to great differences in carbon emissions of enterprises or products. It is found that the temporal resolution, spatial resolution and energy distribution of cogeneration have great influence on the emission factors of power grid. This paper uses the data of China’s power industry to carry out empirical analysis. For each dimension, we set different choices and explore their specific impacts. It is found that the different choices of the three dimensions will cause 5.01%, 20.59%, 4.38% differences in the calculation results of grid emission factors. Finally, based on the research results, this paper puts forward suggestions from three aspects: authoritative guidance, data accuracy and international communication, in order to provide reference for Scope 2 greenhouse gas emissions accounting and reporting.

With the implementation of China’s carbon peaking and carbon neutrality goals, the power industry as a key industry urgently needs to carry out comprehensive carbon accounting work. Carbon accounting of electric power equipment is an important part of carbon accounting in electric power industry. In the process of carbon accounting for electric power equipment, different carbon emission factors may lead to different final accounting results. Based on this, this paper calculates the carbon emission factors of two main raw materials required for the production of electric power equipment in different regions and different years, and applies them to the carbon footprint calculation of SFPZ-240,000/330 transformer. According to the above results, the influence of carbon emission factor selection on carbon accounting of electric power equipment is analyzed.

In view of a whole series of problems such as the reduction of system inertia， the increase of frequency fluctuation， and the deterioration of power quality caused by large-scale wind power integration， a flywheel with high power density is designed for energy storage in wind farm and connected to the low voltage side of the box type transformer for the purpose of peak and valley regulation， system inertia enhancement and frequency regulation. The converter on the side of the flywheel energy storage system adopts current vector control， so that the output power of the system can be flexibly adjusted. The grid-side converter adopts a voltage directional vector control strategy to ensure the stability of the DC bus voltage. In order to verify the operation reliability of the system， Mat lab/Simulink is used to build a simulation model for testing. The results show that the energy storage system is simple to operate， efficient and convenient for installation and construction； a rotation speed modular is designed based on the operation mechanism of flywheel energy storage so that the system can operate within safety domain efficiently； control schemes of current and voltage vector on the system side and grid side are formulated respectively so that the output power can be smooth and the voltage stable.

A solar heat pump heating system with an aluminum tubular collector is proposed in this paper. Mathematical models are established for solar energy absorption and air energy absorption of the aluminum tubular collector, as well as the heat-absorption coefficient of the working substance. The electronic expansion valve is controlled via the fuzzy PID method to adjust the working substance flow rate, as well as to control the evaporator overheating and set the indoor heating temperature. TRNSYS is used to analyze the effects of the wind speed, solar radiation amount, environment temperature, and working substance flow rate on the heat transfer performance of the aluminum tubular collector. The results indicate that the heat transfer performance of the aluminum tubular collector is significantly affected not only by the solar radiation but also the wind speed. For wind speed > 2 m/s, the absorbed power of the collector increases rapidly with an increase in the wind speed; when the working-medium flow rate reaches 4 m/s, the collector absorption power tends to be saturated. Subsequently, an experimental heating system with a heating area of 170 m2 is constructed. Experiments revealed that the maximum coefficient of performance (COP) of the heating system is 4.46, and the average COP value is 3.95, indicating good heating effect.

Flywheel energy storage technology has attracted more and more attention in the energy storage industry due to its high energy density, fast charge and discharge speed, long service life, clean and pollution-free characteristics. It is wwidely used in uninterruptible power system, grid frequency modulation, energy recovery and reuse and other fields. With the development of flywheel rotor materials, motors, bearings and control technology, flywheel energy storage technology has been greatly developed. Introducing the basic structure of the flywheel energy storage system in the above three applications. Typical charge-discharge control strategies are given for the three sensor-less algorithms of model reference adaptive control, sliding mode observer andextended Kalman filter, which are suitable for flywheel energy storage devices.

Intense marine reclamation activities bring obvious benefits, meanwhile, these activities also influence the coastal natural formation, hydrodynamic processes and water environment etc. In order to investigate the exact influence in the Qinzhou Bay brought by marine reclamation behaviors in recent years, based on the remote sensing image data in the Qinzhou Bay in 2006, 2008, 2009, 2012 and 2014, with the help of GIS and RS software, the thesis interprets Qinzhou Bay coastline and artificial reclamation by man-machine interaction and makes quantitative analysis in the Qinzhou Bay coast evolution recently. The results show: (1) Qinzhou Bay coastal morphology change degree was strong in 2006 - 2012 and the coastline changed greatly. Originally part of the natural shore segments which had twists and turns were gradually filled into artificial coast, the coast constantly advanced to the sea, coastline became regular and straight; (2) The change degree of coastline was relatively small in 2006-2008, the average artificial coastline increased 8.86 km/a, the average artificial reclamation area was 20.79 km2 /a; in 2008-2012, the change range of coastline was the greatest, coastline changed most severely, the average artificial coastline increased 16.07 km/a, the average artificial reclamation area was 58.52 km2 /a; however, in 2012-2014, coastline change degree relatively slowed, the average artificial coastline increased 4.04 km per year, the average artificial reclamation area was 3.464 km2 /a. (3) Compared to the studies of predecessors, the innovation of this paper is that it is the first to carry out the detailed research on coastline evolution caused by reclamation engineerings of the Qinzhou Bay, then formed the change results on coastline that caused by intense human activities in the Qinzhou Bay, provided the area of the marine environment protection with full and accurate data.

The purpose of this study was to understand the status and influential factors of preschool teachers' attitudes towards inclusive education, given the evidence that attitudes predict successful inclusion for young children with or at risk for developmental delays or disabilities. We translated the "Multidimensional Attitudes Toward Inclusive Education Scale" (MATIES, Mahat, 2008) to Simplified Chinese (MATIES-C). We then administered the MATIE-C to a representative sample of in-service preschool teachers (N = 481) in Beijing, China. The confirmative factor analysis and reliability tests suggested an acceptable construct validity and internal reliability of the MATIES-C. We also found preschool teachers in Beijing held positive attitudes towards inclusion across cognitive, affective, and behavioral dimensions of attitudes. The ANOVA results indicate teachers' experience and knowledge about children with disabilities had statistically positive associations with favorable attitudes. Preschool area, teacher age, and educational background were also found to have a statistically significant impact on teacher attitudes.

In the literature of modern psychometric modeling, mostly related to item response theory (IRT), the fit of model is evaluated through known indices, such as X[superscript 2], M2, and root mean square error of approximation (RMSEA) for absolute assessments as well as Akaike information criterion (AIC), consistent AIC (CAIC), and Bayesian information criterion (BIC) for relative comparisons. Recent developments show a merging trend of psychometric and machine learnings, yet there remains a gap in the model fit evaluation, specifically the use of the area under curve (AUC). This study focuses on the behaviors of AUC in fitting IRT models. Rounds of simulations were conducted to investigate AUC's appropriateness (e.g., power and Type I error rate) under various conditions. The results show that AUC possessed certain advantages under certain conditions such as high-dimensional structure with two-parameter logistic (2PL) and some three-parameter logistic (3PL) models, while disadvantages were also obvious when the true model is unidimensional. It cautions researchers about the dangers of using AUC solely in evaluating psychometric models.

This study proposed Gibbs sampling algorithms for variable selection in a latent regression model under a unidimensional two-parameter logistic item response theory model. Three types of shrinkage priors were employed to obtain shrinkage estimates: double-exponential (i.e., Laplace), horseshoe, and horseshoe+ priors. These shrinkage priors were compared to a uniform prior case in both simulation and real data analysis. The simulation study revealed that two types of horseshoe priors had a smaller root mean square errors and shorter 95% credible interval lengths than double-exponential or uniform priors. In addition, the horseshoe+ prior was slightly more stable than the horseshoe prior. The real data example successfully proved the utility of horseshoe and horseshoe+ priors in selecting effective predictive covariates for math achievement.

For autistic students receiving special education services, little is known about their relative strengths, weaknesses, and enjoyment across different math content areas; their overall math interest and persistence are also not well-studied. Using the 2017 eighth-grade National Assessment of Education Progress data, this study finds, relative to general education peers with the same math proficiency level, autistic students scored higher and exhibited faster speed in solving visuospatial problems (e.g. identifying figures), but scored lower on math word problems with complex language or social context. Autistic students reported a higher level of enjoyment in solving math problems related to finding areas of shapes or figures but a lower level of persistence than their non-autistic, general education peers. Our work points out the need to help autistic students overcome their weaknesses in word problems and develop their mathematical persistence.