Trace and Edit Relation Associations in GPT

This study introduces a novel approach for analyzing and modifying entity relationships in GPT models, diverging from ROME's entity-focused methods. We develop a relation tracing technique to understand the influence of language model computations on relationship judgments. Using the FewRel dataset, we identify key roles of MLP modules and attention mechanisms in processing relationship information. Our method, tested against ROME on a new dataset, shows improved balance in specificity and generalization, underscoring the potential of manipulating early-layer modules for enhanced model understanding and accuracy

Ultra-Sensitive Piezo-Resistive Sensors Constructed with Reduced Graphene Oxide/Polyolefin Elastomer (RGO/POE) Nanofiber Aerogels.

Flexible wearable pressure sensors have received extensive attention in recent years because of the promising application potentials in health management, humanoid robots, and human machine interfaces. Among the many sensory performances, the high sensitivity is an essential requirement for the practical use of flexible sensors. Therefore, numerous research studies are devoted to improving the sensitivity of the flexible pressure sensors. The fiber assemblies are recognized as an ideal substrate for a highly sensitive piezoresistive sensor because its three-dimensional porous structure can be easily compressed and can provide high interconnection possibilities of the conductive component. Moreover, it is expected to achieve high sensitivity by raising the porosity of the fiber assemblies. In this paper, the three-dimensional reduced graphene oxide/polyolefin elastomer (RGO/POE) nanofiber composite aerogels were prepared by chemical reducing the graphene oxide (GO)/POE nanofiber composite aerogels, which were obtained by freeze drying the mixture of the GO aqueous solution and the POE nanofiber suspension. It was found that the volumetric shrinkage of thermoplastic POE nanofibers during the reduction process enhanced the compression mechanical strength of the composite aerogel, while decreasing its sensitivity. Therefore, the composite aerogels with varying POE nanofiber usage were prepared to balance the sensitivity and working pressure range. The results indicated that the composite aerogel with POE nanofiber/RGO proportion of 3:3 was the optimal sample, which exhibits high sensitivity (ca. 223 kPa-1) and working pressure ranging from 0 to 17.7 kPa. In addition, the composite aerogel showed strong stability when it is either compressed with different frequencies or reversibly compressed and released 5000 times

Sensing Of Carboxylate Drugs In Urine By A Supramolecular Sensor Array

A supramolecular sensor array consisting of eight chemosensors embedded in a hydrogel matrix was used to sense carboxylate drugs. The discriminatory power of the array has been evaluated using principal component analysis and linear discriminant analysis. The eight-member sensor array has been shown to accurately identify 14 carboxylates in water with 100% classification accuracy. To demonstrate the potential for practical utility in the physiological environment, analysis of carboxylate drugs in human urine was also performed achieving 100% correct classification. In addition, the array performance in semiquantitative identification of nonsteroidal anti-inflammatory drugs has been investigated, and the results show that the sensor array is able to differentiate six typical nonsteroidal anti-inflammatory drugs at concentrations of 0.5-100 ppm. This illustrates the potential utility of the designed sensor array for diagnostic and environmental monitoring applications

Application of Pearson and partial correlation coefficient model in the research of heavy metal pollution in rice

Objective To construct and compare the methods for correlation analysis of different elements in rice, including barium, vanadium, cadmium, lithium, aluminum, manganese, lead, thallium, antimony, copper, selenium, ehromium, mercury and arsenic. Methods Analyze the correlation among the fourteen elements in rice by two methods: Pearson correlation coefficient and partial correlation coefficient, and compare the two methods. Results Both of the methods can find the correlations among various pollutants from the data and have their own characteristics on computational complexity, information abundancy and other aspects: Pearson correlation coefficient method has less computation, but also provides less information; Partial correlation coefficient provides more information but needs more samples and computing resources. The Pearson correlation coefficient method showed the positive correlation elements including barium-vanadium, barium-lead, vanadium-lithium, aluminum-antimony and copper-thallium. There was no significant correlation between the remaining elements. The partial correlation coefficient method showed strong positive correlation including vanadiumbarium, lead-barium, total mercury-barium and antimony-aluminum. There was no significant correlation between the remaining elements. Conclusion Under the current data and software, hardware conditions, the correlation analysis of the partial correlation coefficient is recommended

Enhanced photonic time-stretch reservoir computing using all-optical input masks

Input masks are essential in reservoir computing to enhance performance. Here we report a novel all-optical masking scheme for photonics time-stretch reservoir computing based on optical spectral filtering. This approach overcomes the electronic bottleneck in digital temporal masking and offers better performance in classification tasks

Experimental Implementation of An All-Optical Reservoir Computer Using Photonic Time Stretch and Spectral Mixing

Reservoir computing (RC) has been widely used in processing temporal information and classification tasks due to its high efficiency in training and testing. In this paper, we have experimentally demonstrated the performance of an all-optical reservoir computer based on time stretch and spectral mixing. Spectral comb lines of the stretched optical pulse are chosen as virtual nodes in the reservoir layer. Nonlinear spectral mixing is achieved through phase modulation and semiconductor optical amplification. A simple temporal waveform classification task was implemented using the demonstrated RC system to verify the approach

Development and Quality Analysis of Malus prunifolia Jam

In order to develop the nutrition and unique flavor of Malus prunifolia jam, the process optimization and product development were used by Box-Behnken response surface method with the addition of Malus prunifolia pulp, honey pomelo peel pectin, white sugar and concentration time as factors and sensory scores as response values. The sensory indexes, physical and chemical indexes, microbial indexes and quality characteristics of the finished products were measured. The results showed that the optimum processing conditions of the Malus prunifolia jam were 77.7% of the Malus prunifolia pulp, 5.0% of the honey pomelo peel pectin, 17.3% of the white sugar, and the concentration time was 17 min. The results of sensory indexes showed that the Malus prunifolia jam made under the optimized conditions were tasted sweet and sour, and presented bright red orange color. Physicochemical index results showed that pH of Malus prunifolia jam was 4.41, total acid content was 5.14%, total flavone content was 31.40 mg/100 g, total sugar content was 10.26%, soluble solid content was 40.61%, vitamin C content was 7.61 mg/g. The results of microbiological index showed that the total number of bacterial colonies was 50 CFU/g, mold, coliform and Staphylococcus aureus were not detected. The results of quality characteristics showed that the Malus prunifolia jam belonged to pseudoplastic fluid, the storage modulus (G') and loss modulus (G") of Malus prunifolia jam increased with the increase of oscillation frequency, and G'>G", showing the characteristics of elastic viscoelastic body. And the most volatile flavor compounds were α-farnesene, methylheptenone and 2, 4-di-tert-butylphenol. The development of Malus prunifolia jam has a certain significance to enrich the product types of Malus prunifolia, improve the edible convenience of Malus prunifolia and promote the development of the industrial chain of Malus prunifolia

Identification of oxidative phosphorylation-related genes in moyamoya disease by combining bulk RNA-sequencing analysis and machine learning

Introduction: Moyamoya disease (MMD) is a chronic cerebrovascular disease that can lead to ischemia and hemorrhagic stroke. The relationship between oxidative phosphorylation (OXPHOS) and MMD pathogenesis remains unknown.Methods: The gene expression data of 60 participants were acquired from three Gene Expression Omnibus (GEO) datasets, including 36 and 24 in the MMD and control groups. Differentially expressed genes (DEGs) between MMD patients MMD and control groups were identified. Machine learning was used to select the key OXPHOS-related genes associated with MMD from the intersection of DEGs and OXPHOS-related gene sets. Gene ontology (GO), Kyoto encyclopedia of genes and genomes (KEGG), gene set enrichment analysis (GSEA), Immune infiltration and microenvironments analysis were used to analyze the function of key genes. Machine learning selected four key OXPHOS-related genes associated with MMD: CSK, NARS2, PTPN6 and SMAD2 (PTPN6 was upregulated and the other three were downregulated).Results: Functional enrichment analysis showed that these genes were mainly enriched in the Notch signaling pathway, GAP junction, and RNA degradation, which are related to several biological processes, including angiogenesis, proliferation of vascular smooth muscle and endothelial cells, and cytoskeleton regulation. Immune analysis revealed immune infiltration and microenvironment in these MMD samples and their relationships with four key OXPHOS-related genes. APC co-inhibition (p = 0.032), HLA (p = 0.001), MHC I (p = 0.013), T cellco- inhibition (p = 0.032) and Type I IFN responses (p < 0.001) were significantly higher in the MMD groups than those in the control groups. The CSK positively correlated with APC co-inhibition and T cell-co-inhibition. The NARS2 negatively correlated with Type I IFN response. The SMAD2 negatively correlated with APC co-inhibition and Type I IFN response. The PTPN6 positively correlated with HLA, MHC I and Type I IFN responses.Discussion: This study provides a comprehensive understanding of the role of OXPHOS in MMD and will contribute to the development of new treatment methods and exploration of MMD pathogenesis

Health Literacy Regarding Infection Disease Prevention and Treatment among Residents of Taizhou，Zhejiang：Temporal Trends and Associated Factors

BackgroundDue to repeated COVID-19 outbreaks worldwide, COVID-19 containment in China has become a routine social issue, entering a new phase of containment, and residents' health literacy about infection disease prevention and treatment has obtained increasing attentions.ObjectiveTo explore the health literacy about infection disease prevention and treatment in residents of Taizhou, Zhejiang during 2017—2020, and to analyze the trend of changes as well as influencing factors, providing scientific evidence for the precise implementation of actions for achieving "Healthy Taizhou 2030".MethodsThis study was implemented from 2017 to 2020 with Taizhou permanent residents aged between 15 and 69 selected using multistage random sampling, for investigating their demographics, socioeconomic features and health literacy about infection disease prevention and treatment using the National Residents' Health Literacy Monitoring Questionnaire developed by us. In January 2021, the data of health literacy about infection disease prevention and treatment of residents in Taizhou City in four years was analyzed. The health literacy data during 2017—2020 were comparatively analyzed after being processed with weight standardization, and the trend of changes during the period was analyzed using a Chi-squared test for linear trend. Binary logistic regression was used for identifying factors associated with relevant health literacy of these residents in 2020.ResultsThe number of respondents for the survey conducted in four consecutive years from 2017 to 2020, was 3 595, 5 389, 5 929, and 5 847, respectively. The samples in the four yearly surveys showed basically similar demographics, with those aged 45-54 (27.42%-30.46%) , education level was junior high school (27.78%-29.93%) , occupation was farmer (44.52%-58.03%) accounting for the largest proportion. The urban to rural population ratio for the sample of four consecutive yearly surveys was 0.50∶1, 0.55∶1, 0.54∶1 and 0.52∶1, respectively. And the male to female ratio was 1∶1, 0.95∶1, 0.99∶1 and 0.94∶1, respectively. The prevalence of having health literacy about infection disease prevention and treatment for 2017—2020 was 7.86% (642/3 595) , 19.00% (1 024/5 389) , 19.51% (1 157/5 929) , and 27.14% (1 587/5 847) , respectively. After the data were processed with weight standardization, the prevalence of health literacy regarding infectious disease prevention and treatment in 15-69-year-old residents in 2017—2020 was 22.25%, 24.72%, 25.34% and 33.14%, respectively. The health literary level regarding infectious disease prevention and treatment in the residents showed a successive linear increment during the study period regardless of living in rural or urban areas, sex, age (except for 65-69 year olds) , and education level (except for illiteracy/lower illiteracy) , and occupation (P<0.05) . Multivariate Logistic regression analysis showed that gender, age, education level, out-of-pocket health care costs in the past year, and annual household income were associated with health literacy regarding infectious disease prevention and treatment (P<0.05) .ConclusionOur analysis indicates that some advances in prevention and control as well as health education regarding infectious diseases have been achieved in Taizhou, but there is still much room for improvement. In the "golden window" period for normalized prevention and control of COVID-19, it is suggested that Taizhou should strengthen health education regarding infectious disease prevention and treatment for key groups, such as those who are middle-aged and elderly, lower educated, or engage in a career as a farmer or worker, to further improve relevant heath literacy of Taizhou residents