New Gedanken experiment on Reissner-Nordstr\"om AdS Black Holes surrounded by quintessence

In this paper, we apply the new Gedanken experiment to investigate the weak cosmic censorship conjecture for Reissner-Nordstr\"om AdS black holes surrounded by quintessence. Since the perturbation of matter fields doesn't affect the spacetime geometry, we propose the stability condition and assume the process of matter fields falling into the black hole satisfies the null energy condition. Based on Iyer-Wald formalism we can derive the first order and second-order variational identities. From the two identities and the above two conditions lead to the first-order and second-order perturbation inequalities, and under the second-order approximation of matter fields perturbation, we find that the weak cosmic censorship conjecture is still satisfied

Information-Preserved Blending Method for Forward-Looking Sonar Mosaicing in Non-Ideal System Configuration

Forward-Looking Sonar (FLS) has started to gain attention in the field of near-bottom close-range underwater inspection because of its high resolution and high framerate features. Although Automatic Target Recognition (ATR) algorithms have been applied tentatively for object-searching tasks, human supervision is still indispensable, especially when involving critical areas. A clear FLS mosaic containing all suspicious information is in demand to help experts deal with tremendous perception data. However, previous work only considered that FLS is working in an ideal system configuration, which assumes an appropriate sonar imaging setup and the availability of accurate positioning data. Without those promises, the intra-frame and inter-frame artifacts will appear and degrade the quality of the final mosaic by making the information of interest invisible. In this paper, we propose a novel blending method for FLS mosaicing which can preserve interested information. A Long-Short Time Sliding Window (LST-SW) is designed to rectify the local statistics of raw sonar images. The statistics are then utilized to construct a Global Variance Map (GVM). The GVM helps to emphasize the useful information contained in images in the blending phase by classifying the informative and featureless pixels, thereby enhancing the quality of final mosaic. The method is verified using data collected in the real environment. The results show that our method can preserve more details in FLS mosaics for human inspection purposes in practice

The Impact of Parenting style on the Psychological Resilience of Adolescents

The mental health of adolescents is a hot topic of discussion in today's society. Researchers have found that family environment and atmosphere have an impact on the emotional, cognitive, and behavioral development of adolescents. At present, the research on the impact of parental upbringing on adolescent psychological resilience is not clear and further exploration is needed. The research topic of this article is the impact of parental upbringing on the psychological resilience of adolescents. The research method is as follows. Firstly, this study collected questionnaire survey data on adolescent psychological resilience and parental parenting styles. Secondly, this study conducted reliability and validity analysis, descriptive statistics, and correlation analysis on the data to understand the correlation between adolescent psychological resilience and parental parenting styles. Research has found that emotional warmth and family support factors in parenting style are positively correlated with psychological resilience. Refusal and emotional control factors are negatively correlated with adolescent psychological resilience. Therefore, parents should try to adopt positive parenting methods to avoid excessive control, punishment, and rejection, and thus more effectively cultivate the psychological resilience of adolescents

Life Cycle Assessment of a Coke Cleaning Agent

The life cycle assessment of the coke cleaning agent developed by a university-enterprise cooperation project was conducted. This cleaning agent has the characteristics of phosphorus-free, environmentally friendly, and broad market prospects. The life cycle assessment of the established model showed that the GWP of producing 1kg of coke cleaning agent is 1.19 kg CO2 eq, PED is 13.17 MJ, WU is 186.74 kg, AP is 3.63E-03 kg SO2 eq, ADP is 7.75E-05 kg antimony eq, EP is 1.30E-03 kg PO43-eq, RI is 1.16E-03 kg PM2.5 eq, ODP is 4.63E-06 kg CFC-11 eq, and POFP is 1.85E-03 kg NMVOC eq .The uncertainty of the results is between 4.20% and 24.05%. The carbon footprint (GWP) analysis showed that the production process of isotridecanol polyoxyethylene ether, isopropanol, fatty alcohol polyoxyethylene ether M and isodecanol polyoxyethylene ether contributed significantly. The average sensitivity analysis showed that the most influential processes were sodium lauryl amphoacetate, isopropanol, and tripropylene glycol methyl ether. Citation: Gong, Y., Yang, C., Qu, Y., Li, J., Yang, B., Ding, Y., and Zhang, B. (2022). Life Cycle Assessment of a Coke Cleaning Agent. Trends in Renewable Energy, 8(1), 67-83. DOI: 10.17737/tre.2022.8.1.0014

Exact Distribution of Linkage Disequilibrium in the Presence of Mutation, Selection, or Minor Allele Frequency Filtering

Linkage disequilibrium (LD), often expressed in terms of the squared correlation (r2) between allelic values at two loci, is an important concept in many branches of genetics and genomics. Genetic drift and recombination have opposite effects on LD, and thus r2 will keep changing until the effects of these two forces are counterbalanced. Several approximations have been used to determine the expected value of r2 at equilibrium in the presence or absence of mutation. In this paper, we propose a probability-based approach to compute the exact distribution of allele frequencies at two loci in a finite population at any generation t conditional on the distribution at generation t−1. As r2 is a function of this distribution of allele frequencies, this approach can be used to examine the distribution of r2 over generations as it approaches equilibrium. The exact distribution of LD from our method is used to describe, quantify, and compare LD at different equilibria, including equilibrium in the absence or presence of mutation, selection, and filtering by minor allele frequency. We also propose a deterministic formula for expected LD in the presence of mutation at equilibrium based on the exact distribution of LD

Life Cycle Assessment of A Hydrocarbon-based Electrified Cleaning Agent

The electrified cleaning agent requires a moderate volatilization rate, low ozone-depleting substances value, non-flammable, non-explosive and other characteristics. This study performed a whole life cycle assessment on a hydrocarbon-based electrified cleaning agent. The life cycle model is cradle-to-grave, and the background data sets include power grid, transportation, high-density polyethylene, chemicals, etc. The analysis shows that the global warming potential (GWP) of the life cycle of 1 kg of electrified cleaning agent is 2.08 kg CO2 eq, acidification potential (AP) is 9.49E-03 kg SO2 eq, eutrophication potential (EP) is 1.18E-03 kg PO43-eq, respirable inorganic matter (RI) is 2.13E- 03 kg PM2.5 eq, ozone depletion potential (ODP) is 4.91E-05 kg CFC-11 eq, photochemical ozone formation potential (POFP) is 2.89E-02 kg NMVOC eq, ionizing radiation-human health potential (IRP) is 3.16E-02 kg U235 eq, ecotoxicity (ET) is 2.69E-01 CTUe, human toxicity-carcinogenic (HT-cancer) is 4.32E-08 CTUh, and human toxicity-non-carcinogenic (HT-non cancer) is 2.31E-07 CTUh. The uncertainty of the results is between 3.46-9.95%.The four processes of tetrachloroethylene production, D40 solvent oil production, tetrachloroethylene environmental discharge during product use, and electricity usage during product disposal have substantial effects on each LCA indicator, so they are the focus of process improvement. Changes in power consumption during production and transportation distance of raw materials have little effect on total carbon emissions. Compared with the production process of single-solvent electrified cleaning agent tetrachloroethylene and n-bromopropane, the production of the electrified cleaning agent developed in this study has its own advantages in terms of carbon footprint and other environmental impact indicators. Carbon emissions mainly come from the power consumption of each process, natural gas production and combustion, and other energy materials for heating. It is recommended to use renewable raw materials instead of crude oil to obtain carbon credits based on geographical advantages, and try to use production processes with lower carbon emissions, while the exhaust gas from the traditional production process is strictly absorbed and purified before being discharged

Process Design of Microalgae Slurry Pump

Microalgae are a renewable source of dietary supplements, bioactive compounds, and potential energy. Once harvested, the microalgal medium is dewatered to form a slurry for downstream processing. This article outlines a process design for pumping the microalgae slurry. The pump requirements for delivering the Chlorella slurry with 5, 10 or 20 wt% solids at one tonne per hour (1,000 kg/h) and 10 bar were calculated. The 5 wt% microalgae slurry is a Newtonian fluid with a viscosity of 1.95 mPa×s. The 10 wt% and 20 wt% microalgae slurries are non-Newtonian fluids, whose viscosity depends on the shear rate (g). The viscosity of 10 wt% and 20 wt% microalgae slurries is 1.504 (g = 50 s-1)/1.155 (g = 100 s-1) and 1.844 (g = 50 s-1)/1.219 (g = 100 s-1) mPa×s, respectively. The pump power requirements are mainly governed by the delivery pressure. The effect of the pipe length and the number of elbows is negligible. The effective power of the pump is calculated as 0.267-0.275 kW. To fulfill this duty, a ZGB type single-stage single-suction centrifugal slurry pump can be selected, which would provide enough shear rate to reduce the viscosity of the microalgae slurry and give required shaft power. Citation: Li, J., Qu, Y., Gong, Y., Yang, C., Yang, B., Liu, P., Zhang, B., and Ding, Y. (2020). Process Design of Microalgae Slurry Pump. Trends in Renewable Energy, 6(3), 234-244. DOI: 10.17737/tre.2020.6.3.0012

Quantitative Analysis of Molecular Transport in the Extracellular Space Using Physics-Informed Neural Network

The brain extracellular space (ECS), an irregular, extremely tortuous nanoscale space located between cells or between cells and blood vessels, is crucial for nerve cell survival. It plays a pivotal role in high-level brain functions such as memory, emotion, and sensation. However, the specific form of molecular transport within the ECS remain elusive. To address this challenge, this paper proposes a novel approach to quantitatively analyze the molecular transport within the ECS by solving an inverse problem derived from the advection-diffusion equation (ADE) using a physics-informed neural network (PINN). PINN provides a streamlined solution to the ADE without the need for intricate mathematical formulations or grid settings. Additionally, the optimization of PINN facilitates the automatic computation of the diffusion coefficient governing long-term molecule transport and the velocity of molecules driven by advection. Consequently, the proposed method allows for the quantitative analysis and identification of the specific pattern of molecular transport within the ECS through the calculation of the Peclet number. Experimental validation on two datasets of magnetic resonance images (MRIs) captured at different time points showcases the effectiveness of the proposed method. Notably, our simulations reveal identical molecular transport patterns between datasets representing rats with tracer injected into the same brain region. These findings highlight the potential of PINN as a promising tool for comprehensively exploring molecular transport within the ECS

Self-Bidirectional Decoupled Distillation for Time Series Classification

Over the years, many deep learning algorithms have been developed for time series classification (TSC). A learning model’s performance usually depends on the quality of the semantic information extracted from lower and higher levels within the representation hierarchy. Efficiently promoting mutual learning between higher and lower levels is vital to enhance the model’s performance during model learning. To this end, we propose a self-bidirectional decoupled distillation (Self-BiDecKD) method for TSC. Unlike most self-distillation algorithms that usually transfer the target-class knowledge from higher to lower levels, Self-BiDecKD encourages the output of the output layer and the output of each lower-level block to form a bidirectional decoupled knowledge distillation (KD) pair. The bidirectional decoupled KD promotes mutual learning between lower- and higher-level semantic information and extracts the knowledge hidden in the target and non-target classes, helping Self-BiDecKD capture rich representations from the data. Experimental results show that compared with a number of self-distillation algorithms, Self-BiDecKD wins 35 out of 85 UCR2018 datasets and achieves the smallest AVG_rank score, namely 3.2882. In particular, compared with a non-self-distillation Baseline, Self-BiDecKD results in 58/8/19 regarding ‘win’/‘tie’/‘lose’