Sensory Features in Affective Analysis: A Study Based on Neural Network Models

This study proposes an ensemble model to incorporate sensory features of lexical items in English from external resources into neural affective analysis frameworks. This allows the models to take the combined effects of bi-directional feeling between the sensory lexicon and the writer to infer human affective knowledge. We evaluate our model on two affective analysis tasks. The ensemble model exhibits the best accuracy and the results with 1% F1-score improvement over the baseline LSTM model in the sentiment analysis task. The performance shows that perceptual information can contribute to the performance of sentiment classification tasks significantly. This study also provides a support for the linguistic finding that correlations exist between sensory features and sentiments in the language

Multiband effects in thermoelectric and electrical transport properties of kagome superconductors AAV3_3Sb5_5 (AA = K, Rb, Cs)

We studied the effects of multiband electronic structure on the thermoelectric and electrical transport properties in the normal state of kagome superconductors $A$V$_3$Sb$_5$ ($A$ = K, Rb, Cs). In all three members, the multiband nature is manifested by sign changes in the temperature dependence of the Seebeck and Hall resistivity, together with sublinear response of the isothermal Nernst and Hall effects to external magnetic fields in the charge ordered state. Moreover, ambipolar transport effects appear ubiquitously in all three systems, giving rise to sizable Nernst signal. Finally, possible origins of the sign reversal in the temperature dependence of the Hall effect are discussed.Comment: 8 pages, 5 figures. To appear in New Journal of Physic

Charge fluctuations above TCDWT_\mathrm{CDW} revealed by glasslike thermal transport in kagome metals AAV3_3Sb5_5 (AA = K, Rb, Cs)

We present heat capacity, electrical and thermal transport measurements of kagome metals $A$V$_3$Sb$_5$ ($A$ = K, Rb, Cs). In all three compounds, development of short-range charge fluctuations above the charge density wave (CDW) transition temperature $T_\mathrm{CDW}$ strongly scatters phonons via electron-phonon coupling, leading to glasslike phonon heat transport, i.e., phonon thermal conductivity decreases weakly upon cooling. Once the long-range charge order sets in below $T_\mathrm{CDW}$, short-range charge fluctuations are quenched, and the typical Umklapp scattering dominated phonon heat transport is recovered. The charge-fluctuations-induced glasslike phonon thermal conductivity implies sizable electron-phonon coupling in $A$V$_3$Sb$_5$.Comment: 8 pages, 5 figure

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development

Single-Molecular Förster Resonance Energy Transfer Measurement on Structures and Interactions of Biomolecules

Single-molecule Förster resonance energy transfer (smFRET) inherits the strategy of measurement from the effective “spectroscopic ruler” FRET and can be utilized to observe molecular behaviors with relatively high throughput at nanometer scale. The simplicity in principle and configuration of smFRET make it easy to apply and couple with other technologies to comprehensively understand single-molecule dynamics in various application scenarios. Despite its widespread application, smFRET is continuously developing and novel studies based on the advanced platforms have been done. Here, we summarize some representative examples of smFRET research of recent years to exhibit the versatility and note typical strategies to further improve the performance of smFRET measurement on different biomolecules

Study of the Spatio-Temporal Variation of Agricultural Sustainability at National and Provincial Levels in China

As an important pillar of human civilization, the development of agriculture has gradually become the focus of the international community to solve the development dilemma and promote the implementation of the global Sustainable Development Goals (SDGs). Agricultural sustainability issues are widely addressed in scientific literature and various reports by international organizations. However, there are some problems in the existing studies, such as the design of agricultural sustainable development evaluation indicators does not consider the differences in development stages and data statistical capacity of various countries, and the research depth of spatial and temporal change of agricultural sustainable development is insufficient. Agriculture has become a bottleneck for the world and China to achieve the SDGs. Based on the global indicator framework of the Sustainable Development Goals and comprehensive consideration of agricultural development common problems and regional characteristics, this work has established a basic index library consisting of 86 indicators to evaluate the agricultural sustainable development in China and provide the basis for the assessment in different regions. In the indicator optimization process, having considered the development stage of China, the basic characteristics of agriculture, data availability, and reliability, we determined an evaluation index system of China’s agricultural sustainable development that includes 25 specific indicators. The constant elasticity of substitution (CES) model was used to assess the temporal and spatial changes in agricultural sustainability in China at the national, regional, and provincial levels. The results showed that China’s Agricultural Sustainable Development Index (ASDI) score increased from 44.76 in 2011 to 59.22 in 2021, and the ASDI scores of all agricultural regions and provinces also increased to varying degrees. In terms of goal scores, SDG2, SDG6, SDG7, SDG8, SDG9, and SDG12 all exhibited an overall upward trend, in which SDG6 performed the best, and SDG2 performed the worst, scoring 84.76 and 43.05 in 2021, respectively. This paper will provide a basis for systematically evaluating the progress of agricultural sustainable development goals and accurately identifying unsustainable problems in agricultural development to help China implement the 2030 Agenda for Sustainable Development

A modified 3D EfficientNet for the classification of Alzheimer's disease using structural magnetic resonance images

Abstract Structural magnetic resonance imaging (MRI) provides useful information for biomarker exploration and intelligent classification of Alzheimer's disease (AD). Machine learning and deep learning methods have been used in feature extraction and computer‐aided diagnosis or prediction of AD. In this research, a new deep learning model is developed to detect or predict AD in an effective manner. A modified 3D EfficientNet with a sequentially connected 3D mobile inverted bottleneck convolution (MBConv) block is proposed to explore the multiscale characteristics of brain MR images for AD classification. The 3D MBConv block consists of depthwise convolution and a squeeze‐and‐excitation module to transform the input features into more compact features with fewer parameters than those in standard convolution. The proposed method was evaluated considering four classification tasks: (1) NC versus AD, (2) NC versus all MCI, (3) NC versus pMCI, and (4) sMCI versus pMCI. The proposed model achieved accuracies of 95.00%, 86.67%, and 83.33% for the classification of NC versus AD, NC versus pMCI, and sMCI versus pMCI, respectively, and exhibited a high performance in comparison with the classical networks and several existing methods. Efficient deep learning networks are powerful tools for the early diagnosis and prediction of AD

Nitrogen isotopic insight into sediment recycling in the southern Lesser Antilles arc: Implication to subduction-zone nitrogen recycling

International audienceLattice fixed nitrogen component in arc lavas from Kick'em Jenny (KEJ) was investigated for improving our understanding of two long-standing controversies in the recycling of subducting slab material. One is whether the crustal signatures in the Lesser Antilles arc rocks originated from slab recycling or crustal assimilation. The other is the budget of fixed nitrogen in arc crust, which is still a missing piece in the modeling of geodynamic nitrogen cycle. Our results show that the KEJ basaltic lavas contain variable amounts of labile nitrogen (removable by 400 °C heating) and 2.6-5.3 ppm refractory nitrogen with δ15N values of +0.8‰ to +6.6‰. The labile nitrogen was likely introduced on seafloor although the KEJ lavas appear to be strikingly fresh, whereas the refractory nitrogen was likely inherited from their magmatic source. Nitrogen isotopic signature of the refractory nitrogen cannot be explained by magmatic degassing, fractional crystallization and/or crustal assimilation. Instead, the data can be best explained by a mixing between the mantle and two δ15N-distinct endmembers, which are consistent with the two types of subducting sediments (i.e., marl/ooze and shale) recovered from the reference site (DSDP Site 144). This supports sediment recycling into the mantle source of the Lesser Antilles arc. Our modeling also yielded a nitrogen fixation flux of 2.3-4.7 × 103 moles N⋅yr⋅1-km-1 (or 1.8-3.8 × 106 moles N⋅yr-1 for the 800 km arc) in the Lesser Antilles arc crust. This is 2-3 orders of magnitude smaller than the nitrogen input flux into the Lesser Antilles trench solely from subducting sediments (1.3 × 106 moles N⋅yr⋅1-km-1 or 1.0 × 109 moles N⋅yr-1 for the entire 800 km trench). This suggests that arc crust is not a major repository of subducted nitrogen, at least in the Lesser Antilles. Instead, most of the crustal nitrogen subducted to the sub-arc depths is either retained in the subducting slab, stored in the metasomatized lithospheric mantle, and/or released back to the surface by volcanic emission