A Dataset of Open-Domain Question Answering with Multiple-Span Answers

Multi-span answer extraction, also known as the task of multi-span question answering (MSQA), is critical for real-world applications, as it requires extracting multiple pieces of information from a text to answer complex questions. Despite the active studies and rapid progress in English MSQA research, there is a notable lack of publicly available MSQA benchmark in Chinese. Previous efforts for constructing MSQA datasets predominantly emphasized entity-centric contextualization, resulting in a bias towards collecting factoid questions and potentially overlooking questions requiring more detailed descriptive responses. To overcome these limitations, we present CLEAN, a comprehensive Chinese multi-span question answering dataset that involves a wide range of open-domain subjects with a substantial number of instances requiring descriptive answers. Additionally, we provide established models from relevant literature as baselines for CLEAN. Experimental results and analysis show the characteristics and challenge of the newly proposed CLEAN dataset for the community. Our dataset, CLEAN, will be publicly released at zhiyiluo.site/misc/clean_v1.0_ sample.json

Wavelength-division multiplexing optical Ising simulator enabling fully programmable spin couplings and external magnetic fields

Recently, spatial photonic Ising machines (SPIMs) have demonstrated the abilities to compute the Ising Hamiltonian of large-scale spin systems, with the advantages of ultrafast speed and high power efficiency. However, such optical computations have been limited to specific Ising models with fully connected couplings. Here we develop a wavelength-division multiplexing SPIM to enable programmable spin couplings and external magnetic fields as well for general Ising models. We experimentally demonstrate such a wavelength-division multiplexing SPIM with a single spatial light modulator, where the gauge transformation is implemented to eliminate the impact of pixel alignment. To show the programmable capability of general spin coupling interactions, we explore three spin systems: $\pm J$ models, Sherrington-Kirkpatrick models, and only locally connected ${{J}_{1}}\texttt{-}{{J}_{2}}$ models and observe the phase transitions among the spin-glass, the ferromagnetic, the paramagnetic and the stripe-antiferromagnetic phases. These results show that the wavelength-division multiplexing approach has great programmable flexibility of spin couplings and external magnetic fields, which provides the opportunities to solve general combinatorial optimization problems with large-scale and on-demand SPIM.Comment: 6 pages, 4 figure

Gene Order Phylogeny and the Evolution of Methanogens

Methanogens are a phylogenetically diverse group belonging to Euryarchaeota. Previously, phylogenetic approaches using large datasets revealed that methanogens can be grouped into two classes, “Class I” and “Class II”. However, some deep relationships were not resolved. For instance, the monophyly of “Class I” methanogens, which consist of Methanopyrales, Methanobacteriales and Methanococcales, is disputable due to weak statistical support. In this study, we use MSOAR to identify common orthologous genes from eight methanogen species and a Thermococcale species (outgroup), and apply GRAPPA and FastME to compute distance-based gene order phylogeny. The gene order phylogeny supports two classes of methanogens, but it differs from the original classification of methanogens by placing Methanopyrales and Methanobacteriales together with Methanosarcinales in Class II rather than with Methanococcales. This study suggests a new classification scheme for methanogens. In addition, it indicates that gene order phylogeny can complement traditional sequence-based methods in addressing taxonomic questions for deep relationships

Spatial distribution and diversity of the heterotrophic flagellates in the Cosmonaut Sea, Antarctic

As predators of bacteria and viruses and as food sources for microzooplankton, heterotrophic flagellates (HFs) play an important role in the marine micro-food web. Based on the global climate change’s impact on marine ecosystems, particularly sea ice melting, we analyzed the community composition and diversity of heterotrophic flagellates, focusing on the Antarctic Cosmonaut Sea. During the 36th China Antarctic research expedition (2019-2020), we collected seawater samples, subsequently analyzing HFs through IlluminaMiSeq2000 sequencing to assess community composition and diversity. Notable variations in HFs abundance were observed between the western and eastern sectors of the Cosmonaut Sea, with a distinct concentration at a 100-meter water depth. Different zones exhibited diverse indicators and dominants taxa influenced by local ocean currents. Both the northern Antarctic Peninsula and the western Cosmonaut Sea, where the Weddell Eddy and Antarctic Land Slope Current intersect, showcased marine stramenopiles as dominant HFs species. Our findings offer insights into dominant taxa, spatial distribution patterns among heterotrophic flagellates, correlations between taxa distribution and environmental factors, and the exploration of potential indicator taxa

Amphiphilic Polyphosphazene for Fluorocarbon Emulsion Stabilization

High internal phase emulsions (HIPEs) have been of great interest for fabricating fluorinated porous polymers having controlled pore structures and excellent physicochemical properties. However, it remains a challenge to prepare stable fluorocarbon HIPEs, due to the lack of suitable surfactants. By randomly grating hydrophilic and fluorophilic side chains to polyphosphazene (PPZ), a comb-like amphiphilic PPZ surfactant with biodegradability is designed and synthesized for stabilizing water/fluorocarbon oil-based emulsions. The hydrophilic-lipophilic balance of PPZs can be controlled by tuning the grating ratio of the two side chains, leading to the preparation of stable water-in-oil HIPEs and oil-in-water emulsions, and the production of fluorinated porous polymers and particles by polymerizing the oil phase. These fluorinated porous polymers show excellent thermal stability and, due to the hydrophobicity and porous structure, applications in the field of oil/water separation can be achieved

Development and validation of LC-ESI-MS method for the quantification of dapoxetine in rat plasma

A sensitive and simple liquid chromatography/electrospray mass spectrometry (LC-ESI-MS) method for determination of dapoxetine in rat plasma using one-step protein precipitation was developed and validated. After addition of midazolam as internal standard (IS), protein precipitation by acetonitrile was used in sample preparation. Chromatographically separation was achieved on an SB-C18 (2.1 mm × 150 mm, 5 μm) column with acetonitrile-0.1 % formic acid as the mobile phase with gradient elution. Electrospray ionization (ESI) source was applied and operated in positive ion mode; selected ion monitoring (SIM) mode was used to quantification using target fragment ions m/z 306 for dapoxetine and m/z 326 for the IS. Calibration plots were linear over the range of 5-1000 ng/mL for dapoxetine in rat plasma. Lower limit of quantification (LLOQ) for dapoxetine was 5 ng/mL. Mean recovery of dapoxetine from plasma was in the range of 92.4-98.6 %. CV of intra-day and inter-day precision were both less than 15 %. This method is simple and sensitive enough to be used in pharmacokinetic research for determination of dapoxetine in rat plasma.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Excellent energy storage performance in Bi0.5Na0.5TiO3-based lead-free high-entropy relaxor ferroelectrics via B-site modification

Next-generation advanced high/pulsed power capacitors urgently require dielectric materials with outstanding energy storage performance. Bi0.5Na0.5TiO3-based lead-free materials exhibit high polarization, but the high remanent polarization and large polarization hysteresis limit their applications in dielectric capacitors. Herein, high-entropy perovskite relaxor ferroelectrics (Na0.2Bi0.2Ba0.2Sr0.2Ca0.2)(Ti1−x%Zrx%)O3 are designed by adding multiple ions in the A-site and replacing the B-site Ti4+ with a certain amount of Zr4+. The newly designed system showed high relaxor feature and slim polarization–electric (P–E) loops. Especially, improved relaxor feature and obviously delayed polarization saturation were found with the increasing of Zr4+. Of particular importance is that both high recoverable energy storage density of 6.6 J/cm3 and energy efficiency of 93.5% were achieved under 550 kV/cm for the ceramics of x = 6, accompanying with excellent frequency stability, appreciable thermal stability, and prosperous discharge property. This work not only provides potential dielectric materials for energy storage applications, but also offers an effective strategy to obtain dielectric ceramics with ultrahigh comprehensive energy storage performance to meet the demanding requirements of advanced energy storage applications

Genome-wide identification of the AcMADS-box family and functional validation of AcMADS32 involved in carotenoid biosynthesis in Actinidia

MADS-box is a large transcription factor family in plants and plays a crucial role in various plant developmental processes; however, it has not been systematically analyzed in kiwifruit. In the present study, 74 AcMADS genes were identified in the Red5 kiwifruit genome, including 17 type-I and 57 type-II members according to the conserved domains. The AcMADS genes were randomly distributed across 25 chromosomes and were predicted to be mostly located in the nucleus. A total of 33 fragmental duplications were detected in the AcMADS genes, which might be the main force driving the family expansion. Many hormone-associated cis-acting elements were detected in the promoter region. Expression profile analysis showed that AcMADS members had tissue specificity and different responses to dark, low temperature, drought, and salt stress. Two genes in the AG group, AcMADS32 and AcMADS48, had high expression levels during fruit development, and the role of AcMADS32 was further verified by stable overexpression in kiwifruit seedlings. The content of α-carotene and the ratio of zeaxanthin/β-carotene was increased in transgenic kiwifruit seedlings, and the expression level of AcBCH1/2 was significantly increased, suggesting that AcMADS32 plays an important role in regulating carotenoid accumulation. These results have enriched our understanding of the MADS-box gene family and laid a foundation for further research of the functions of its members during kiwifruit development

Identification and validation of IgG N-glycosylation biomarkers of esophageal carcinoma

Introduction: Altered Immunoglobulin G (IgG) N-glycosylation is associated with aging, inflammation, and diseases status, while its effect on esophageal squamous cell carcinoma (ESCC) remains unknown. As far as we know, this is the first study to explore and validate the association of IgG N-glycosylation and the carcinogenesis progression of ESCC, providing innovative biomarkers for the predictive identification and targeted prevention of ESCC. Methods: In total, 496 individuals of ESCC (n=114), precancerosis (n=187) and controls (n=195) from the discovery population (n=348) and validation population (n=148) were recruited in the study. IgG N-glycosylation profile was analyzed and an ESCC-related glycan score was composed by a stepwise ordinal logistic model in the discovery population. The receiver operating characteristic (ROC) curve with the bootstrapping procedure was used to assess the performance of the glycan score. Results: In the discovery population, the adjusted OR of GP20 (digalactosylated monosialylated biantennary with core and antennary fucose), IGP33 (the ratio of all fucosylated monosyalilated and disialylated structures), IGP44 (the proportion of high mannose glycan structures in total neutral IgG glycans), IGP58 (the percentage of all fucosylated structures in total neutral IgG glycans), IGP75 (the incidence of bisecting GlcNAc in all fucosylated digalactosylated structures in total neutral IgG glycans), and the glycan score are 4.03 (95% CI: 3.03-5.36, P \u3c 0.001), 0.69 (95% CI: 0.55-0.87, P \u3c 0.001), 0.56 (95% CI: 0.45-0.69, P \u3c 0.001), 0.52 (95% CI: 0.41-0.65, P \u3c 0.001), 7.17 (95% CI: 4.77-10.79, P \u3c 0.001), and 2.86 (95% CI: 2.33-3.53, P \u3c 0.001), respectively. Individuals in the highest tertile of the glycan score own an increased risk (OR: 11.41), compared with those in the lowest. The average multi-class AUC are 0.822 (95% CI: 0.786-0.849). Findings are verified in the validation population, with an average AUC of 0.807 (95% CI: 0.758-0.864). Discussion: Our study demonstrated that IgG N-glycans and the proposed glycan score appear to be promising predictive markers for ESCC, contributing to the early prevention of esophageal cancer. From the perspective of biological mechanism, IgG fucosylation and mannosylation might involve in the carcinogenesis progression of ESCC, and provide potential therapeutic targets for personalized interventions of cancer progression

A Convolutional Sequence-to-Sequence Attention Fusion Framework for Commonsense Causal Reasoning

Commonsense causal reasoning is the process of understanding the causal dependency between common events or actions. Traditionally, it was framed as a selection problem. However, we cannot obtain enough candidates and need more flexible causes (or effects) in many scenarios, such as causal-based QA problems. Thus, the ability to generate causes (or effects) is an important problem. In this paper, we propose a causal attention mechanism that leverages external knowledge from CausalNet, followed by a novel fusion mechanism that combines global causal dependency guidance from the causal attention with local causal dependency obtained through multi-layer soft attention within the CNN seq2seq architecture. Experimental results consistently demonstrate the superiority of the proposed framework, achieving BLEU-1 scores of 20.06 and 36.94, BLEU-2 scores of 9.98 and 27.78, and human-evaluated accuracy rates of 35% and 52% for two evaluation datasets, outperforming all other baselines across all metrics on both evaluation datasets