Advancing continual lifelong learning in neural information retrieval: definition, dataset, framework, and empirical evaluation

Continual learning refers to the capability of a machine learning model to learn and adapt to new information, without compromising its performance on previously learned tasks. Although several studies have investigated continual learning methods for information retrieval tasks, a well-defined task formulation is still lacking, and it is unclear how typical learning strategies perform in this context. To address this challenge, a systematic task formulation of continual neural information retrieval is presented, along with a multiple-topic dataset that simulates continuous information retrieval. A comprehensive continual neural information retrieval framework consisting of typical retrieval models and continual learning strategies is then proposed. Empirical evaluations illustrate that the proposed framework can successfully prevent catastrophic forgetting in neural information retrieval and enhance performance on previously learned tasks. The results indicate that embedding-based retrieval models experience a decline in their continual learning performance as the topic shift distance and dataset volume of new tasks increase. In contrast, pretraining-based models do not show any such correlation. Adopting suitable learning strategies can mitigate the effects of topic shift and data augmentation.Comment: Submitted to Information Science

Local nearly non-strained perovskite lattice approaching a broad environmental stability window of efficient solar cells

Twist and fracture of surface lattice tend to occur under harsh condition due to the soft lattice natures of hybrid perovskite materials. Accordingly, surface defects and lattice distortion are produced, which allow the performance loss and notorious degradation in perovskite solar cells (PSCs). In our work, judiciously selected conjugated ligand was employed as the film intermediary, from which rigid and delocalization 4-phenylpyridine (4-pPy) exhibited the most significant improvement on both optoelectrical performance and stability of PSCs. By regulating the film crystallization kinetics, high-quality perovskite films can be obtained with preferable crystal orientation. Moreover, benefiting from the defects passivation and unidirectional bonding effect, coordinated 4-pPy “scaffold” on the lattice surface could mitigate vacancy formation and lattice twist/fracture under severe conditions. The resulted p-i-n planar device shows a considerable PCE of 21.12% (certified 20.2%) with negligible hysteresis, as well as an excellent storage (90% of original PCE after 1000 h at 60% RH), operating (90% of original PCE after 600 h at maximum power point) and thermal stress (89% of original PCE after 500 h at 85 °C) stability. It is hoped that our findings could open a new way to accelerate continued progress on PSCs regimes for efficieny maximization and stability prolongation

Impermeable inorganic “walls” sandwiching perovskite layer toward inverted and indoor photovoltaic devices

Interfaces between the perovskite active layer and the charge-transport layers (CTLs) play a critical role in both efficiency and stability of halide-perovskite photovoltaics. One of the major concerns is that surface defects of perovskite could cause detrimental nonradiative recombination and material degradation. In this work, we addressed this challenging problem by inserting ultrathin alkali-fluoride (AF) films between the tri-cation lead-iodide perovskite layer and both CTLs. This bilateral inorganic “walls” strategy makes use of both physical-blocking and chemical-anchoring functionalities of the continuous, uniform and compact AF framework: on the one hand, the uniformly distributed alkali-iodine coordination at the perovskite-AF interfaces effectively suppresses the formation of iodine-vacancy defects at the surfaces, thus reducing the trap-assisted recombination at the perovskite-CTL interfaces and therewith the open-voltage loss; on the other hand, the impermeable AF buffer layers effectively prevent the bidirectional ion migration at the perovskite-CTLs interfaces even under harsh working conditions. As a result, a power-conversion efficiency (PCE) of 22.02% (certified efficiency 20.4%) with low open-voltage deficit (<0.4 V) was achieved for the low-temperature processed inverted planar perovskite solar cells. Exceptional operational stability (500 h, ISOS-L-2) and thermal stability (1000 h, ISOS-D-2) were obtained. Meanwhile, a 35.7% PCE was obtained under dim-light source (1000 lux white LED light) with the optimized device, which is among the best records in perovskite indoor photovoltaics

Drought resistance index screening and evaluation of lettuce under water deficit conditions on the basis of morphological and physiological differences

IntroductionWater is one of the important factors affecting the yield of leafy vegetables. Lettuce, as a widely planted vegetable, requires frequent irrigation due to its shallow taproot and high leaf evaporation rate. Therefore, screening drought-resistant genotypes is of great significance for lettuce production.MethodsIn the present study, significant variations were observed among 13 morphological and physiological traits of 42 lettuce genotypes under normal irrigation and water-deficient conditions.ResultsFrequency analysis showed that soluble protein (SP) was evenly distributed across six intervals. Principal component analysis (PCA) was conducted to transform the 13 indexes into four independent comprehensive indicators with a cumulative contribution ratio of 94.83%. The stepwise regression analysis showed that root surface area (RSA), root volume (RV), belowground dry weight (BDW), soluble sugar (SS), SP, and leaf relative water content (RWC) could be used to evaluate and predict the drought resistance of lettuce genotypes. Furthermore, the drought resistance ranks of the genotypes were similar according to the drought resistance comprehensive evaluation value (D value), comprehensive drought resistance coefficient (CDC), and weight drought resistance coefficient (WDC). The cluster analysis enabled the division of the 42 genotypes into five drought resistance groups; among them, variety Yidali151 was divided into group I as a strongly drought-resistant variety, group II included 6 drought-resistant genotypes, group III included 16 moderately drought-resistant genotypes, group IV included 12 drought-sensitive genotypes, and group V included 7 highly drought-sensitive genotypes. Moreover, a representative lettuce variety was selected from each of the five groups to verify its water resistance ability under water deficit conditions. In the drought-resistant variety, it was observed that stomatal density, superoxide anion (O2.−wfi2) production rate, and malondialdehyde (MDA) content exhibited a low increase rate, while catalase (CAT), superoxide dismutase (SOD), and that peroxidase (POD) activity exhibited a higher increase than in the drought-sensitive variety.DiscussionIn summary, the identified genotypes are important because their drought-resistant traits can be used in future drought-resistant lettuce breeding programs and water-efficient cultivation

Genome-Wide Identification, Evolution, and Expression Analysis of the TCP Gene Family in Rose (Rosa chinensis Jacq.)

Roses have not only high ornamental and economic values but also cultural importance worldwide. As a plant-specific transcription factor gene family, the TCP (TEOSINTE BRANCHED 1, CYCLOIDEA, PROLIFERATING CELL FACTOR LAND 2) genes have been indicated to be involved in various aspects of plant biological processes, such as leaf morphogenesis and senescence, lateral branching, flower development, stress response and hormone signaling. Currently, TCP genes have been identified and analyzed in many plants, yet there is no systematic analysis in Rosa chinensis. Here, we identified 16 RcTCP genes from R. chinensis genome, which were unevenly distributed in five out of all seven chromosomes. Phylogenetic and structural analyses showed that RcTCP family could be classified into two classes, I (namely PCF) and II, and class II genes can be further divided into CIN and CyC/TB1 subclasses. The different classes of TCP genes were showed to have undergone different evolutionary processes, and genes in the same branch shared similar motifs, gene structures and conserved structural domains. Promoter analysis showed that RcTCPs had many cis-acting elements that are mainly associated with plant growth and development, plant hormones and abiotic/biotic stress responses. Furthermore, the expression levels of RcTCPs under vegetative and reproductive growth and drought stress treatments were analyzed based on public RNA-seq dataset, and it was shown that RcTCPs exhibited serious tissue-specific expression, with most of them dominantly expressed in flowers, leaves and stems, with high levels of expression at different stages of flower and bud differentiation, particularly during petal formation and gametophyte development. The high inducement of seven RcTCP genes from PCF class in drought stress indicated their important roles in biological processes against drought stress. Our results provide valuable information for the evolution and functional characterization of TCP genes in R. chinensis

Robust Stability of Efficient Lead-Free Formamidinium Tin Iodide Perovskite Solar Cells Realized by Structural Regulation

The instability issue of Pb-free Sn-based perovskite is one of the biggest challenges for its application in optoelectronic devices. Herein, a structural regulation strategy is demonstrated to regulate the geometric symmetry of formamidiniumtin iodide (FASnI3) perovskite. Experimental and theoretical works show that the introduction of cesium cation (Cs+) could improve the geometric symmetry, suppress the oxidation of Sn2+, and enhance the thermodynamical structural stability of FASnI3. As a result, the inverted planar Cs-doped FASnI3-based perovskite solar cell (PSC) is shown to maintain 90% of its initial power-conversion efficiency (PCE) after 2000 h stored in N2, which is the best durability to date for 3D Sn-based PSCs. Most importantly, the air, thermal, and illumination stabilities of the PSCs are all improved after Cs doping. The PCE of the Cs-doped PSC shows a 63% increase compared to that of the control device (from 3.74% to 6.08%) due to the improved quality of the Cs-doped FASnI3 film.Peer reviewe

Artificial intelligence-based comprehensive analysis of immune-stemness-tumor budding profile to predict survival of patients with pancreatic adenocarcinoma

Objective: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy. CD8+ T cells, cancer stem cells (CSCs), and tumor budding (TB) have been significantly correlated with the outcome of patients with PDAC, but the correlations have been independently reported. In addition, no integrated immune-CSC-TB profile for predicting survival in patients with PDAC has been established. Methods: Multiplexed immunofluorescence and artificial intelligence (AI)-based comprehensive analyses were used for quantification and spatial distribution analysis of CD8+ T cells, CD133+ CSCs, and TB. In vivo humanized patient-derived xenograft (PDX) models were established. Nomogram analysis, calibration curve, time-dependent receiver operating characteristic curve, and decision curve analyses were performed using R software. Results: The established ‘anti-/pro-tumor’ models showed that the CD8+ T cell/TB, CD8+ T cell/CD133+ CSC, TB-adjacent CD8+ T cell, and CD133+ CSC-adjacent CD8+ T cell indices were positively associated with survival of patients with PDAC. These findings were validated using PDX-transplanted humanized mouse models. An integrated nomogram-based immune-CSC-TB profile that included the CD8+ T cell/TB and CD8+ T cell/CD133+ CSC indices was established and shown to be superior to the tumor-node-metastasis stage model in predicting survival of patients with PDAC. Conclusions: ‘Anti-/pro-tumor’ models and the spatial relationship among CD8+ T cells, CSCs, and TB within the tumor microenvironment were investigated. Novel strategies to predict the prognosis of patients with PDAC were established using AI-based comprehensive analysis and machine learning workflow. The nomogram-based immune-CSC-TB profile can provide accurate prognosis prediction for patients with PDAC

Table_2_Drought resistance index screening and evaluation of lettuce under water deficit conditions on the basis of morphological and physiological differences.docx

IntroductionWater is one of the important factors affecting the yield of leafy vegetables. Lettuce, as a widely planted vegetable, requires frequent irrigation due to its shallow taproot and high leaf evaporation rate. Therefore, screening drought-resistant genotypes is of great significance for lettuce production.MethodsIn the present study, significant variations were observed among 13 morphological and physiological traits of 42 lettuce genotypes under normal irrigation and water-deficient conditions.ResultsFrequency analysis showed that soluble protein (SP) was evenly distributed across six intervals. Principal component analysis (PCA) was conducted to transform the 13 indexes into four independent comprehensive indicators with a cumulative contribution ratio of 94.83%. The stepwise regression analysis showed that root surface area (RSA), root volume (RV), belowground dry weight (BDW), soluble sugar (SS), SP, and leaf relative water content (RWC) could be used to evaluate and predict the drought resistance of lettuce genotypes. Furthermore, the drought resistance ranks of the genotypes were similar according to the drought resistance comprehensive evaluation value (D value), comprehensive drought resistance coefficient (CDC), and weight drought resistance coefficient (WDC). The cluster analysis enabled the division of the 42 genotypes into five drought resistance groups; among them, variety Yidali151 was divided into group I as a strongly drought-resistant variety, group II included 6 drought-resistant genotypes, group III included 16 moderately drought-resistant genotypes, group IV included 12 drought-sensitive genotypes, and group V included 7 highly drought-sensitive genotypes. Moreover, a representative lettuce variety was selected from each of the five groups to verify its water resistance ability under water deficit conditions. In the drought-resistant variety, it was observed that stomatal density, superoxide anion (O2.−wfi2) production rate, and malondialdehyde (MDA) content exhibited a low increase rate, while catalase (CAT), superoxide dismutase (SOD), and that peroxidase (POD) activity exhibited a higher increase than in the drought-sensitive variety.DiscussionIn summary, the identified genotypes are important because their drought-resistant traits can be used in future drought-resistant lettuce breeding programs and water-efficient cultivation.</p

Table_1_Drought resistance index screening and evaluation of lettuce under water deficit conditions on the basis of morphological and physiological differences.docx

IntroductionWater is one of the important factors affecting the yield of leafy vegetables. Lettuce, as a widely planted vegetable, requires frequent irrigation due to its shallow taproot and high leaf evaporation rate. Therefore, screening drought-resistant genotypes is of great significance for lettuce production.MethodsIn the present study, significant variations were observed among 13 morphological and physiological traits of 42 lettuce genotypes under normal irrigation and water-deficient conditions.ResultsFrequency analysis showed that soluble protein (SP) was evenly distributed across six intervals. Principal component analysis (PCA) was conducted to transform the 13 indexes into four independent comprehensive indicators with a cumulative contribution ratio of 94.83%. The stepwise regression analysis showed that root surface area (RSA), root volume (RV), belowground dry weight (BDW), soluble sugar (SS), SP, and leaf relative water content (RWC) could be used to evaluate and predict the drought resistance of lettuce genotypes. Furthermore, the drought resistance ranks of the genotypes were similar according to the drought resistance comprehensive evaluation value (D value), comprehensive drought resistance coefficient (CDC), and weight drought resistance coefficient (WDC). The cluster analysis enabled the division of the 42 genotypes into five drought resistance groups; among them, variety Yidali151 was divided into group I as a strongly drought-resistant variety, group II included 6 drought-resistant genotypes, group III included 16 moderately drought-resistant genotypes, group IV included 12 drought-sensitive genotypes, and group V included 7 highly drought-sensitive genotypes. Moreover, a representative lettuce variety was selected from each of the five groups to verify its water resistance ability under water deficit conditions. In the drought-resistant variety, it was observed that stomatal density, superoxide anion (O2.−wfi2) production rate, and malondialdehyde (MDA) content exhibited a low increase rate, while catalase (CAT), superoxide dismutase (SOD), and that peroxidase (POD) activity exhibited a higher increase than in the drought-sensitive variety.DiscussionIn summary, the identified genotypes are important because their drought-resistant traits can be used in future drought-resistant lettuce breeding programs and water-efficient cultivation.</p

Table_3_Drought resistance index screening and evaluation of lettuce under water deficit conditions on the basis of morphological and physiological differences.docx

IntroductionWater is one of the important factors affecting the yield of leafy vegetables. Lettuce, as a widely planted vegetable, requires frequent irrigation due to its shallow taproot and high leaf evaporation rate. Therefore, screening drought-resistant genotypes is of great significance for lettuce production.MethodsIn the present study, significant variations were observed among 13 morphological and physiological traits of 42 lettuce genotypes under normal irrigation and water-deficient conditions.ResultsFrequency analysis showed that soluble protein (SP) was evenly distributed across six intervals. Principal component analysis (PCA) was conducted to transform the 13 indexes into four independent comprehensive indicators with a cumulative contribution ratio of 94.83%. The stepwise regression analysis showed that root surface area (RSA), root volume (RV), belowground dry weight (BDW), soluble sugar (SS), SP, and leaf relative water content (RWC) could be used to evaluate and predict the drought resistance of lettuce genotypes. Furthermore, the drought resistance ranks of the genotypes were similar according to the drought resistance comprehensive evaluation value (D value), comprehensive drought resistance coefficient (CDC), and weight drought resistance coefficient (WDC). The cluster analysis enabled the division of the 42 genotypes into five drought resistance groups; among them, variety Yidali151 was divided into group I as a strongly drought-resistant variety, group II included 6 drought-resistant genotypes, group III included 16 moderately drought-resistant genotypes, group IV included 12 drought-sensitive genotypes, and group V included 7 highly drought-sensitive genotypes. Moreover, a representative lettuce variety was selected from each of the five groups to verify its water resistance ability under water deficit conditions. In the drought-resistant variety, it was observed that stomatal density, superoxide anion (O2.−wfi2) production rate, and malondialdehyde (MDA) content exhibited a low increase rate, while catalase (CAT), superoxide dismutase (SOD), and that peroxidase (POD) activity exhibited a higher increase than in the drought-sensitive variety.DiscussionIn summary, the identified genotypes are important because their drought-resistant traits can be used in future drought-resistant lettuce breeding programs and water-efficient cultivation.</p