CyFormer: Accurate State-of-Health Prediction of Lithium-Ion Batteries via Cyclic Attention

Predicting the State-of-Health (SoH) of lithium-ion batteries is a fundamental task of battery management systems on electric vehicles. It aims at estimating future SoH based on historical aging data. Most existing deep learning methods rely on filter-based feature extractors (e.g., CNN or Kalman filters) and recurrent time sequence models. Though efficient, they generally ignore cyclic features and the domain gap between training and testing batteries. To address this problem, we present CyFormer, a transformer-based cyclic time sequence model for SoH prediction. Instead of the conventional CNN-RNN structure, we adopt an encoder-decoder architecture. In the encoder, row-wise and column-wise attention blocks effectively capture intra-cycle and inter-cycle connections and extract cyclic features. In the decoder, the SoH queries cross-attend to these features to form the final predictions. We further utilize a transfer learning strategy to narrow the domain gap between the training and testing set. To be specific, we use fine-tuning to shift the model to a target working condition. Finally, we made our model more efficient by pruning. The experiment shows that our method attains an MAE of 0.75\% with only 10\% data for fine-tuning on a testing battery, surpassing prior methods by a large margin. Effective and robust, our method provides a potential solution for all cyclic time sequence prediction tasks

Wetting equilibrium in a rectangular channel

When a capillary channel with corners is wetted by a fluid, there are regions where the fluid fills the whole cross-section and regions where only the corners are filled by the fluid. The fluid fraction of the partially-filled region, $s^*$, is an important quantity related to the capillary pressure. We calculate the value of $s^*$ for channels with a cross-section slightly deviated from a rectangle: the height is larger in the center than those on the two short sides. We find that a small change in the cross-section geometry leads to a huge change of $s^*$. This result is consistent with experimental observations.Comment: 23 pages, 8 figures, submitted to Soft Matte

Better Zero-Shot Reasoning with Role-Play Prompting

Modern large language models (LLMs), such as ChatGPT, exhibit a remarkable capacity for role-playing, enabling them to embody not only human characters but also non-human entities like a Linux terminal. This versatility allows them to simulate complex human-like interactions and behaviors within various contexts, as well as to emulate specific objects or systems. While these capabilities have enhanced user engagement and introduced novel modes of interaction, the influence of role-playing on LLMs' reasoning abilities remains underexplored. In this study, we introduce a strategically designed role-play prompting methodology and assess its performance under the zero-shot setting across twelve diverse reasoning benchmarks, encompassing arithmetic, commonsense reasoning, symbolic reasoning, and more. Leveraging models such as ChatGPT and Llama 2, our empirical results illustrate that role-play prompting consistently surpasses the standard zero-shot approach across most datasets. Notably, accuracy on AQuA rises from 53.5% to 63.8%, and on Last Letter from 23.8% to 84.2%. Beyond enhancing contextual understanding, we posit that role-play prompting serves as an implicit Chain-of-Thought (CoT) trigger, thereby improving the quality of reasoning. By comparing our approach with the Zero-Shot-CoT technique, which prompts the model to "think step by step", we further demonstrate that role-play prompting can generate a more effective CoT. This highlights its potential to augment the reasoning capabilities of LLMs

Interaction between circulating galectin-3 and cancer-associated MUC1 enhances tumour cell homotypic aggregation and prevents anoikis

<p>Abstract</p> <p>Background</p> <p>Formation of tumour cell aggregation/emboli prolongs the survival of circulating tumour cells in the circulation, enhances their physical trapping in the micro-vasculature and thus increases metastatic spread of the cancer cells to remote sites.</p> <p>Results</p> <p>It shows here that the presence of the galactoside-binding galectin-3, whose concentration is markedly increased in the blood circulation of cancer patients, increases cancer cell homotypic aggregation under anchorage-independent conditions by interaction with the oncofetal Thomsen-Friedenreich carbohydrate (Galβ1,3GalNAcα-, TF) antigen on the cancer-associated transmembrane mucin protein MUC1. The galectin-3-MUC1 interaction induces MUC1 cell surface polarization and exposure of the cell surface adhesion molecules including E-cadherin. The enhanced cancer cell homotypic aggregation by galectin-MUC1 interaction increases the survival of the tumour cells under anchorage-independent conditions by allowing them to avoid initiation of anoikis (suspension-induced apoptosis).</p> <p>Conclusion</p> <p>These results suggest that the interaction between free circulating galectin-3 and cancer-associated MUC1 promotes embolus formation and survival of disseminating tumour cells in the circulation. This provides new information into our understanding of the molecular mechanisms of cancer cell haematogenous dissemination and suggests that targeting the interaction of circulating galectin-3 with MUC1 in the circulation may represent an effective therapeutic approach for preventing metastasis.</p

Evaluation of a pilot cooperative medical scheme in rural China: impact on gender patterns of health care utilization and prescription practices

<p>Abstract</p> <p>Background</p> <p>In 2003 the Chinese government introduced voluntary cooperative medical schemes (CMS), soon to be in place throughout rural China. Families who chose to enroll do so as a single unit and nothing is known about any differential effect of these new schemes on family members. This study evaluates the impact of one pilot CMS in Anhui Province on health care use by girls aged less than 5 years and women 65 years or older, and on the pattern and cost of prescriptions.</p> <p>Methods</p> <p>Health care records were extracted covering a 10 year period, before, during and after the pilot CMS in 4 townships, one with the intervention and 3 comparison townships without. The impact of the intervention on the age and gender distribution of patients presenting for health care and on the prescription of certain drugs was assessed by logistic regression. The cost of prescriptions before, during and after the intervention period was also assessed.</p> <p>Results</p> <p>203,058 registration and 643,588 prescription records were identified. During the intervention there was a reduced likelihood overall that a patient was female (OR = 0.92: 95%CI 0.87 - 0.97) at the intervention site. Girls aged < 5 years had an increased likelihood of health care (OR = 1.41: 95%CI 1.23 - 1.59) during the CMS, but women ≥ 65 years were relatively disadvantaged (OR = 0.84: 95%CI 0.75 - 0.95). The use of antibiotics and systemic steroids increased disproportionately at the intervention site for patients ≥ 5 years. Prescription costs at the township hospital also increased at the intervention site, particularly for older men.</p> <p>Conclusions</p> <p>This evaluation suggests that all family members did not benefit equally from the pilot CMS and that women ≥ 65 years may be disadvantaged by the newly available reimbursements of health care costs through the CMS. It points to the need, in future evaluations, to use individuals rather than families as the unit of analysis, in order to determine whether such health care inequalities are wide-spread and persistent or are reduced in the longer term. The results also support earlier concerns about the influence of new funding resources on prescription practices and the need for regulation of for-profit prescribing.</p

Jump Aggregation, Volatility Prediction, and Nonlinear Estimation of Banks’ Sustainability Risk

Extreme financial events usually lead to sharp jumps in stock prices and volatilities. In addition, jump clustering and stock price correlations contribute to the risk amplification acceleration mechanism during the crisis. In this paper, four Jump-GARCH models are used to forecast the jump diffusion volatility, which is used as the risk factor. The linear and asymmetric nonlinear effects are considered, and the value at risk of banks is estimated by support vector quantile regression. There are three main findings. First, in terms of the volatility process of bank stock price, the Jump Diffusion GARCH model is better than the Continuous Diffusion GARCH model, and the discrete jump volatility is significant. Secondly, due to the difference of the sensitivity of abnormal information shock, the jump behavior of bank stock price is heterogeneous. Moreover, CJ-GARCH models are suitable for most banks, while ARJI-R2-GARCH models are more suitable for small and medium sized banks. Thirdly, based on the jump diffusion volatility information, the performance of the support vector quantile regression is better than that of the parametric quantile regression and nonparametric quantile regression

Synergistic activation of smithsonite with copper-ammonium species for enhancing surface reactivity and xanthate adsorption

Copper ions (Cu2+) are usually added to activate the sulfidized surface of zinc oxide minerals to enhance xanthate attachment using sulfidization xanthate flotation technology. The adsorption of Cu2+ and xanthate on the sulfidized surface was investigated in various systems, and its effect on the surface hydrophobicity and flotation performance was revealed by multiple analytical methods and experiments. X-ray photoelectron spectroscopy (XPS) and time-of-flight secondary ion mass spectrometry (ToF-SIMS) characterization demonstrated that the adsorption of Cu2+ on sulfidized smithsonite surfaces increased the active Cu—S content, regardless of treatment in any activation system. The sulfidized surface pretreated with NH4+–Cu2+ created favorable conditions for the adsorption of more Cu2+, significantly enhancing the smithsonite reactivity. Zeta potential determination, ultraviolet (UV)-visible spectroscopy, Fourier transform-infrared (FT-IR) measurements, and contact angle detection showed that xanthate was chemically adsorbed on the sulfidized surface, and its adsorption capacity in various systems was illustrated from qualitative and quantitative aspects. In comparison to the Na2S–Cu2+ and Cu2+–Na2S–Cu2+ systems, xanthate exhibited a higher adsorption capacity on sulfidized smithsonite surfaces in NH4+–Cu2+–Na2S–Cu2+ system. Hence, activation with Cu2+–NH4+ synergistic species prior to sulfidization significantly enhanced the mineral surface hydrophobicity, thereby increasing its flotation recovery

Numerical Analysis of Heat Transfer Enhancement Due to Nanoparticles under the Magnetic Field in a Solar-Driven Hydrothermal Pretreatment System

Solar-driven hydrothermal pretreatment is an efficient approach for the pretreatment of microalgae biomass for biofuel production. In order to enhance the heat transfer, the magnetic fields effects on flow and heat transfer of nanofluids were investigated in a three-dimensional circular pipe. The magnetic fields were applied in different directions and magnetic field intensities to the flow. In this paper, Finite Volume Method was used to simulate flow and heat transfer of nanofluids under a magnetic field, and the Discrete Phase Model was selected to calculate two-phase flow, which was water mixed with metal nanoparticles. The research was also carried out with the various physical properties of nanoparticles, including the volume share of nanoparticles, particle diameter, and particle types. When the magnetic fields were applied along the X, Y, and Z directions and the intensity of magnetic fields was 0.5 T, the heat transfer coefficients of Cu-H2O nanofluids flow were increased evenly by 9.17%, 10.28%, and 10.32%, respectively. When the magnetic field was applied, the heat transfer coefficients and the Nusselt numbers were both increased with the increment of intensities of the magnetic field