New Understandings of Ethanol Oxidation Reaction Mechanism on Pd/C and Pd2Ru/C Catalysts in Alkaline Direct Ethanol Fuel Cells

Ethanol oxidation reaction (EOR) on Pd2Ru/C and Pd/C catalysts in alkaline media is studied comprehensively by cyclic voltammetry, chronoamperometry, in situ FTIR, single fuel cell test and electrochemical impedance spectroscopy measurements. The results show that, as compared to Pd/C, Pd2Ru/C favors acetaldehyde formation and hinders its oxidation. Based on X-ray absorption data, which evidence that Ru promotes a larger electronic vacancy of the Pd 4d band, it is expected that the formation of adsorbed ethoxy is favored on Pd2Ru/C and followed by its oxidation to acetaldehyde facilitated by oxygenated species provided by Ru. In contrast, acetaldehyde oxidation is more difficult on Pd2Ru/C than on Pd/C likely because the adsorption energy of the reactive species is increased. We also show that the performance of Pd2Ru/C anode in alkaline direct ethanol fuel cell (ADEFC) is initially better but degrades much more rapidly than that with Pd/C anode under the same test conditions. The degradation is demonstrated to result from the accumulation of large amounts of acetaldehyde, which in alkaline media forms dimers by the aldol condensation reaction. The dimers tend to be responsible for blocking the active sites for further ethanol oxidation. This comprehensive study provides new understandings of the roles of Ru in Pd2Ru/C for EOR in alkaline media, unveils the causes of the performance degradation of fuel cells with Pd2Ru/C and demonstrates that initial good performances are not necessarily a valid criterion for selecting appropriate anode catalysts for ADEFC applications

Real-time Alarm Monitoring System for Detecting Driver Fatigue in Wireless Areas

The purpose of this paper was to develop a real-time alarm monitoring system that can detect the fatigue driving state through wireless communication. The drivers’ electroencephalogram (EEG) signals were recorded from occipital electrodes. Seven EEG rhythms with different frequency bands as gamma, hbeta, beta, sigma, alpha, theta and delta waves were extracted. They were simultaneously assessed using relative operating characteristic (ROC) curves and grey relational analysis to select one as the fatigue feature. The research results showed that the performance of theta wave was the best one. Therefore, theta wave was used as fatigue feature in the following alarm device. The real-time alarm monitoring system based on the result has been developed, once the threshold was settled by using the data of the first ten minutes driving period. The developed system can detect driver fatigue and give alarm to indicate the onset of fatigue automatically

Writing Instruction in China: Challenges and Efforts

This qualitative study examined the current writing instruction in 1-12 level education with the data collected in three Chinese cities. The data from the Interviews of teachers and teacher-educators at different levels and from classroom observations at upper elementary to high schools in three metropolitan cities across China provide insights into 1-12 writing instruction in contemporary China. To further reveal the efforts taken by writing teacher under China’s high-stakes testing culture, this paper also presented a case study of an exemplary 10th grade writing teacher, who took tremendous efforts in nurturing true readers and writers in his classroom under the test-obsessive culture in China

Phase Fluctuation Analysis in Functional Brain Networks of Scaling EEG for Driver Fatigue Detection

The characterization of complex patterns arising from electroencephalogram (EEG) is an important problem with significant applications in identifying different mental states. Based on the operational EEG of drivers, a method is proposed to characterize and distinguish different EEG patterns. The EEG measurements from seven professional taxi drivers were collected under different states. The phase characterization method was used to calculate the instantaneous phase from the EEG measurements. Then, the optimization of drivers’ EEG was realized through performing common spatial pattern analysis. The structures and scaling components of the brain networks from optimized EEG measurements are sensitive to the EEG patterns. The effectiveness of the method is demonstrated, and its applicability is articulated.</p

Experiments of Image Retrieval Using Weak Attributes

Searching images based on descriptions of image attributes is an intuitive process that can be easily understood by humans and recently made feasible by a few promising works in both the computer vision and multimedia communities. In this report, we describe some experiments of image retrieval methods that utilize weak attributes

Angelica sinensis polysaccharide promotes apoptosis by inhibiting JAK/STAT pathway in breast cancer cells

Purpose: To determine whether Angelica polysaccharide (APS) induced apoptosis via regulation of the Janus kinase (JAK)/signal transducers and activators of transcription (STAT) pathway in breast cancer cells. Methods: Human MCF-7 cells were treated with APS. Cell proliferation, apoptosis, expression of apoptotic proteins, and the phosphorylation level of Janus kinase (JAK) and STAT were measured, respectively. For further analysis, MCF-7 cells were transfected with a JAK2 overexpression plasmid or treated with a classical JAK inhibitor, ruxolitinib. Results: Treatment with APS dose-dependently reduced cell proliferation, induced apoptosis, and downregulated the levels of phosphorylated JAK and STAT in MCF-7 cells. JAK inhibitor, ruxolitinib, blocked JAK/STAT pathway and induced cell apoptosis in MCF-7 cells. Besides, JAK2 overexpression reversed the effects of APS on cell viability and apoptosis. Conclusion: The results indicate that polysaccharide isolated from Angelica sinensis promotes apoptosis by inhibiting JAK/STAT pathway in breast cancer cells. Thus, APS may be useful as a potential therapeutic agent for breast cancer

VEGA: Learning Interleaved Image-Text Comprehension in Vision-Language Large Models

The swift progress of Multi-modal Large Models (MLLMs) has showcased their impressive ability to tackle tasks blending vision and language. Yet, most current models and benchmarks cater to scenarios with a narrow scope of visual and textual contexts. These models often fall short when faced with complex comprehension tasks, which involve navigating through a plethora of irrelevant and potentially misleading information in both text and image forms. To bridge this gap, we introduce a new, more demanding task known as Interleaved Image-Text Comprehension (IITC). This task challenges models to discern and disregard superfluous elements in both images and text to accurately answer questions and to follow intricate instructions to pinpoint the relevant image. In support of this task, we further craft a new VEGA dataset, tailored for the IITC task on scientific content, and devised a subtask, Image-Text Association (ITA), to refine image-text correlation skills. Our evaluation of four leading closed-source models, as well as various open-source models using VEGA, underscores the rigorous nature of IITC. Even the most advanced models, such as Gemini-1.5-pro and GPT4V, only achieved modest success. By employing a multi-task, multi-scale post-training strategy, we have set a robust baseline for MLLMs on the IITC task, attaining an $85.8\%$ accuracy rate in image association and a $0.508$ Rouge score. These results validate the effectiveness of our dataset in improving MLLMs capabilities for nuanced image-text comprehension.Comment: Project Page: https://zhourax.github.io/VEGA

Preparation and analysis of sodium carboxymethyl cellulose and its effect on xerophthalmia

1348-1353carboxymethyl cellulose (CMC) has been effectively synthesized with high yield and purity. With the prolongation of time after model establishment, the values of Schirmer Ⅰ test (S Ⅰ t) and breakup time of tear film gradually decreased. The α-MSH and CMC alone could ameliorate corneal tissue damage and corneal morphological abnormalities in the dry eye to some extent. However, compared with monotherapy, the treatment of α-MSH combined with CMC has a more significant positive effect on the improvement of tear secretion and the stability of tear film in dry eye model in the early stage after modeling. There are significant differences between the model control group and the normal control group at each time point after model establishment (all Pth, 14th, 21th and 28th days after treatment. After 7, 14 and 21 days treatment, the S Ⅰ t values in the α-MSH+CMC treatment group were 4.80±0.79, 4.10±0.52 and 4.30±0.86 mm, respectively

Preparation and analysis of sodium carboxymethyl cellulose and its effect on xerophthalmia

carboxymethyl cellulose (CMC) has been effectively synthesized with high yield and purity. With the prolongation of time after model establishment, the values of Schirmer Ⅰ test (S Ⅰ t) and breakup time of tear film gradually decreased. The α-MSH and CMC alone could ameliorate corneal tissue damage and corneal morphological abnormalities in the dry eye to some extent. However, compared with monotherapy, the treatment of α-MSH combined with CMC has a more significant positive effect on the improvement of tear secretion and the stability of tear film in dry eye model in the early stage after modeling. There are significant differences between the model control group and the normal control group at each time point after model establishment (all P&lt;0.01) at 7th, 14th, 21th and 28th days after treatment. After 7, 14 and 21 days treatment, the S Ⅰ t values in the α-MSH+CMC treatment group were 4.80±0.79, 4.10±0.52 and 4.30±0.86 mm, respectively