Flowchart of the STL-PCA-BWO-BiLSTM model. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Parameter optimization results of BiLSTM. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Descriptive statistical analysis of data. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

The MAE value of the model under raw data. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Three error values under raw data. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Decomposition of time scries plot. by Xiangjuan Liu (618000)

“…First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. …”

Estimated results of the mediation effect. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Panel unit root test result. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Kernel density estimation for CO2. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Change in panel quantile regression coefficients. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Definitions of variables and measurements. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Regression estimates: Double threshold model. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Results from cross sectional dependence test. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Panel quantile regression results. by Getachew Magnar Kitila (19935139)

“…The empirical findings show that greater trade openness is associated with significantly higher CO2 emission, additionally; it demonstrates that the influence is heterogeneous across different CO2 emission quantiles in African countries. …”

Postnatal death of <i>aP2-Drp1</i>^f/f neonatal mice. by Yuta Ibayashi (20404811)

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Brain disintegration in <i>aP2- Drp1</i>^f/f neonatal mice. by Yuta Ibayashi (20404811)

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Validation of distinct contribution of capsule and hypercapsule-associated HMV in IFA-conferred protection against hvKP infection using a <i>ΔrmpD</i>-K7 mutant. by Tingting Wang (123983)

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The concentration of inflammatory parameters (TNF-α and IL-10) in serum (a and b) and burned skin samples (c) of different experimental groups on day 2 and 10. by Omid Mehrpour (9385929)

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The concentrations of malondialdehyde (a), super oxide dismutase (b), and NOx (nitrate +nitrite)(c) in the burned skin samples of different experimental groups on day 2 and 10. by Omid Mehrpour (9385929)

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(A) Beta-diversity non-metric multidimensional scaling (NMDS) analysis at genus level, and (B) LEfSe for bacterial species biomarkers representing control vs. stroke groups. by Duangnapa Roongpiboonsopit (12829198)

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