The main research direction for the disposal of spent lithium-ion batteries is focused on the recovery of precious metals. However, few studies exist on the recycling of LiFePO4 electric vehicle (EV) batteries because of their low recycling value. In addition, a detailed life cycle inventory (LCI) of waste plays a significant role in its life cycle assessment (LCA) for an environmental perspective. click here In this study, an end-of-life (EOL) LiFePO4 EV battery is disposed to achieve the LCI result. The approach comprises manual dismantling of the battery pack/module and crushing and pyrolysis of cells. The authors classify the dismantling results and use different disposal methods, such as recycling or incineration. Regarding the environmental emissions during pyrolysis, the authors record and evaluate the results according to the experimental data, the bill of materials (BOM), the mass conservation, and the chemical reaction equations. In addition, the electricity power demand is related to the electricity mix in China, and the waste gases and solid residue are treated by using neutralization and landfill, respectively. Finally, the authors integrate the LCI data with analysis data and a background database (Ecoinvent). After the integration of the total emission and consumption data, the authors obtained the total detailed LCI resulting from the disposal of the LiFePO4 vehicle battery. This LCI mainly includes the consumption of energy and materials, and emissions to air, water, and soil, which can provide the basis for the future LCA of LiFePO4 (LFP) batteries. Furthermore, the potential of industrial scale process research on the disposal of spent LiFePO4 batteries is discussed.Automatic speaker verification provides a flexible and effective way for biometric authentication. Previous deep learning-based methods have demonstrated promising results, whereas a few problems still require better solutions. In prior works examining speaker discriminative neural networks, the speaker representation of the target speaker is regarded as a fixed one when comparing with utterances from different speakers, and the joint information between enrollment and evaluation utterances is ignored. In this paper, we propose to combine CNN-based feature learning with a bidirectional attention mechanism to achieve better performance with only one enrollment utterance. The evaluation-enrollment joint information is exploited to provide interactive features through bidirectional attention. In addition, we introduce one individual cost function to identify the phonetic contents, which contributes to calculating the attention score more specifically. These interactive features are complementary to the constant ones, which are extracted from individual speakers separately and do not vary with the evaluation utterances. The proposed method archived a competitive equal error rate of 6.26% on the internal “DAN DAN NI HAO” benchmark dataset with 1250 utterances and outperformed various baseline methods, including the traditional i-vector/PLDA, d-vector, self-attention, and sequence-to-sequence attention models.In the last decade, universities worldwide have adopted various measures intended to promote sustainability in higher education and include it in the curriculum. However, although this paradigm shift appears to be contributing to students’ acquisition of the knowledge, skills and values necessary to fight for a more sustainable world, serious global crises such as the present SARS-CoV-2 pandemic oblige us to rethink our behaviour and spur us to accelerate the move towards a deep-seated commitment to the environment and people. Therefore, the aims of this study were (a) to explore consumption habits in students at four Spanish universities by analysing their individual ecological footprint (EF); (b) to develop indices of connection with nature and a pro-environmental attitude and to determine relationships between these indices and students’ consumption. Among other factors, our results showed that private university students have a higher EF than public university students; that food consumption has the greatest impact on individuals’ EF; and that those who consume more sustainably do not show a more pro-environmental attitude or feel a greater connection with nature. Therefore, we conclude that there was no apparent direct relationship between study participants’ convictions and their daily behaviour. There is a pressing need in education to demonstrate the connection between our actions and their environmental impact.Nonalcoholic steatohepatitis (NASH) is characterized by hepatic steatosis with inflammation and fibrosis. Membrane endoglin (Eng) expression is shown to participate in fibrosis, and plasma concentrations of soluble endoglin (sEng) are increased in patients with hypercholesterolemia and type 2 diabetes mellitus. We hypothesize that NASH increases both hepatic Eng expression and sEng in blood and that high levels of sEng modulate cholesterol and bile acid (BA) metabolism and affect NASH progression. Three-month-old transgenic male mice overexpressing human sEng and their wild type littermates are fed for six months with either a high-saturated fat, high-fructose high-cholesterol (FFC) diet or a chow diet. Evaluation of NASH, Liquid chromatography-mass spectrometry (LC/MS) analysis of BA, hepatic expression of Eng, inflammation, fibrosis markers, enzymes and transporters involved in hepatic cholesterol and BA metabolism are assessed using Real-Time Quantitative Reverse Transcription Polymerase Chain reaction (qRT-PCR) and Western blot. The FFC diet significantly increases mouse sEng levels and increases hepatic expression of Eng. High levels of human sEng results in increased hepatic deposition of cholesterol due to reduced conversion into BA, as well as redirects the metabolism of triglycerides (TAG) to its accumulation in the liver, via reduced TAG elimination by β-oxidation combined with reduced hepatic efflux. We propose that sEng might be a biomarker of NASH development, and the presence of high levels of sEng might support NASH aggravation by impairing the essential defensive mechanism protecting NASH liver against excessive TAG and cholesterol accumulation, suggesting the importance of high sEng levels in patients prone to develop NASH.