In the contemporary era of big data, the educational landscape is undergoing significant transformations. Literature education, as a vital component, faces both emerging opportunities and challenges. ...This study develops a framework for analyzing learning behaviors specific to literature education. It employs both an enhanced K-means clustering algorithm and a refined Apriori algorithm for mining data on student learning behaviors. Through cluster analysis and the investigation of association rules, this research explores the interconnections between students’ learning behaviors and their literary education. The findings categorize students into four distinct groups based on their learning behaviors. Students in Category 1 are identified as the most proficient learners, consistently achieving test scores above 85. Conversely, Category 2 students display the least motivation and effectiveness, with their examination scores not exceeding 70. Students in Categories 3 and 4 exhibit comparable levels of performance. Crucially, the analysis reveals that the most significant predictors of students’ literary achievement are their regular and examination scores, with correlation coefficients of 0.627 and 0.653, respectively. This segmentation and analysis of student behaviors facilitate the early detection of atypical learning patterns by educational practitioners, enabling timely intervention strategies to enhance academic outcomes.
Observing that Semantic features learned in an image classification task and Appearance features learned in a similarity matching task complement each other, we build a twofold Siamese network, named ...SA-Siam, for real-time object tracking. SA-Siam is composed of a semantic branch and an appearance branch. Each branch is a similaritylearning Siamese network. An important design choice in SA-Siam is to separately train the two branches to keep the heterogeneity of the two types of features. In addition, we propose a channel attention mechanism for the semantic branch. Channel-wise weights are computed according to the channel activations around the target position. While the inherited architecture from SiamFC 3 allows our tracker to operate beyond real-time, the twofold design and the attention mechanism significantly improve the tracking performance. The proposed SA-Siam outperforms all other real-time trackers by a large margin on OTB-2013/50/100 benchmarks.
Malignancy can be suppressed by the immune system in a process termed immunosurveillance. However, to what extent immunosurveillance occurs in spontaneous cancers and the composition of participating ...cell types remains obscure. Here, we show that cell transformation triggers a tissue-resident lymphocyte response in oncogene-induced murine cancer models. Non-circulating cytotoxic lymphocytes, derived from innate, T cell receptor (TCR)αβ, and TCRγδ lineages, expand in early tumors. Characterized by high expression of NK1.1, CD49a, and CD103, these cells share a gene-expression signature distinct from those of conventional NK cells, T cells, and invariant NKT cells. Generation of these lymphocytes is dependent on the cytokine IL-15, but not the transcription factor Nfil3 that is required for the differentiation of tumor-infiltrating NK cells, and IL-15 deficiency, but not Nfil3 deficiency, results in accelerated tumor growth. These findings reveal a tumor-elicited immunosurveillance mechanism that engages unconventional type-1-like innate lymphoid cells and type 1 innate-like T cells.
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•Cell transformation expands tissue-resident ILC1ls and ILTC1s•ILC1ls and ILTC1s share a distinct gene expression program•ILC1ls and ILTC1s exhibit potent cytotoxicity against tumor cells•IL-15 deficiency depletes ILC1ls and ILTC1s, resulting in tumor outgrowth
Cell transformation triggers a cancer immunosurveillance mechanism that engages tissue-resident lymphocytes derived from innate, TCRαβ, and TCRγδ lineages.
Regulatory T (Treg) cells expressing the transcription factor Foxp3 have a pivotal role in maintaining immunological self-tolerance; yet, excessive Treg cell activities suppress anti-tumour immune ...responses. Compared to the resting Treg (rTreg) cell phenotype in secondary lymphoid organs, Treg cells in non-lymphoid tissues exhibit an activated Treg (aTreg) cell phenotype. However, the function of aTreg cells and whether their generation can be manipulated are largely unexplored. Here we show that the transcription factor Foxo1, previously demonstrated to promote Treg cell suppression of lymphoproliferative diseases, has an unexpected function in inhibiting aTreg-cell-mediated immune tolerance in mice. We find that aTreg cells turned over at a slower rate than rTreg cells, but were not locally maintained in tissues. aTreg cell differentiation was associated with repression of Foxo1-dependent gene transcription, concomitant with reduced Foxo1 expression, cytoplasmic localization and enhanced phosphorylation at the Akt sites. Treg-cell-specific expression of an Akt-insensitive Foxo1 mutant prevented downregulation of lymphoid organ homing molecules, and impeded Treg cell homing to non-lymphoid organs, causing CD8(+) T-cell-mediated autoimmune diseases. Compared to Treg cells from healthy tissues, tumour-infiltrating Treg cells downregulated Foxo1 target genes more substantially. Expression of the Foxo1 mutant at a lower dose was sufficient to deplete tumour-associated Treg cells, activate effector CD8(+) T cells, and inhibit tumour growth without inflicting autoimmunity. Thus, Foxo1 inactivation is essential for the migration of aTreg cells that have a crucial function in suppressing CD8(+) T-cell responses; and the Foxo signalling pathway in Treg cells can be titrated to break tumour immune tolerance preferentially.
Accelerated conversion by catalysis is a promising way to inhibit shuttling of soluble polysulfides in lithium–sulfur (Li–S) batteries, but most of the reported catalysts work only for one direction ...sulfur reaction (reduction or oxidation), which is still not a root solution since fast cycled use of sulfur species is not finally realized. A bidirectional catalyst design, oxide–sulfide heterostructure, is proposed to accelerate both reduction of soluble polysulfides and oxidation of insoluble discharge products (e.g., Li2S), indicating a fundamental way for improving both the cycling stability and sulfur utilization. Typically, a TiO2–Ni3S2 heterostructure is prepared by in situ growing TiO2 nanoparticles on Ni3S2 surface and the intimately bonded interfaces are the key for bidirectional catalysis. For reduction, TiO2 traps while Ni3S2 catalytically converts polysulfides. For oxidation, TiO2 and Ni3S2 both show catalytic activity for Li2S dissolution, refreshing the catalyst surface. The produced sulfur cathode with TiO2–Ni3S2 delivers a low capacity decay of 0.038% per cycle for 900 cycles at 0.5C and specially, with a sulfur loading of 3.9 mg cm−2, achieves a high capacity retention of 65% over 500 cycles at 0.3C. This work unlocks how a bidirectional catalyst works for boosting Li–S batteries approaching practical uses.
A lithium–sulfur battery with long cycling stability is assembled with a specially designed bidirectional catalyst. The TiO2–Ni3S2 heterostructured catalyst realizes the smooth trapping–diffusion–conversion of polysulfides in the reduction process. The two components show catalytic activity toward the oxidation of Li2S. Thus, the shuttle effect and the formation of dead sulfides are effectively suppressed.
We consider the tracking problem as a special type of object detection problem, which we call instance detection. With proper initialization, a detector can be quickly converted into a tracker by ...learning the new instance from a single image. We find that model-agnostic meta-learning (MAML) offers a strategy to initialize the detector that satisfies our needs. We propose a principled three-step approach to build a high-performance tracker. First, pick any modern object detector trained with gradient descent. Second, conduct offline training (or initialization) with MAML. Third, perform domain adaptation using the initial frame. We follow this procedure to build two trackers, named Retina-MAML and FCOS-MAML, based on two modern detectors RetinaNet and FCOS. Evaluations on four benchmarks show that both trackers are competitive against state-of-the-art trackers. On OTB-100, Retina-MAML achieves the highest ever AUC of 0.712. On TrackingNet, FCOS-MAML ranks the first on the leader board with an AUC of 0.757 and the normalized precision of 0.822. Both trackers run in real-time at 40 FPS.
Metal sulfides, such as MoS2, are widely investigated in lithium–sulfur (Li–S) batteries to suppress the shuttling of lithium polysulfides (LiPSs) due to their chemical adsorption ability and ...catalytic activity. However, their relatively low conductivity and activity limit the LiPS conversion kinetics. Herein, the Co-doped MoS2 is proposed to accelerate the catalytic conversion of LiPS as the Co doping can promote the transition from semiconducting 2H phase to metallic 1T phase and introduce the sulfur vacancies in MoS2. A one-step hydrothermal process is used to prepare such a Co-doped MoS2 with more 1T phase and rich sulfur vacancies, which enhances the electron transfer and catalytic activity, thus effectively improving the LiPS adsorption and conversion kinetics. The cathode using the three-dimensional graphene monolith loaded with Co-doped MoS2 catalyst as the sulfur host shows a high rate capability and long cycling stability. A high capacity of 941 mAh g–1 at 2 C and a low capacity fading of 0.029% per cycle at 1 C over 1000 cycles are achieved, suggesting the effectively suppressed LiPS shuttling and improved sulfur utilization. Good cyclic stability is also maintained under a high sulfur loading indicating the doping is an effective way to optimize the metal sulfide catalysts in Li–S batteries.
Rapid and accurate access to large-scale, high-resolution crop-type distribution maps is important for agricultural management and sustainable agricultural development. Due to the limitations of ...remote sensing image quality and data processing capabilities, large-scale crop classification is still challenging. This study aimed to map the distribution of crops in Heilongjiang Province using Google Earth Engine (GEE) and Sentinel-1 and Sentinel-2 images. We obtained Sentinel-1 and Sentinel-2 images from all the covered study areas in the critical period for crop growth in 2018 (May to September), combined monthly composite images of reflectance bands, vegetation indices and polarization bands as input features, and then performed crop classification using a Random Forest (RF) classifier. The results show that the Sentinel-1 and Sentinel-2 monthly composite images combined with the RF classifier can accurately generate the crop distribution map of the study area, and the overall accuracy (OA) reached 89.75%. Through experiments, we also found that the classification performance using time-series images is significantly better than that using single-period images. Compared with the use of traditional bands only (i.e., the visible and near-infrared bands), the addition of shortwave infrared bands can improve the accuracy of crop classification most significantly, followed by the addition of red-edge bands. Adding common vegetation indices and Sentinel-1 data to the crop classification improved the overall classification accuracy and the OA by 0.2 and 0.6%, respectively, compared to using only the Sentinel-2 reflectance bands. The analysis of timeliness revealed that when the July image is available, the increase in the accuracy of crop classification is the highest. When the Sentinel-1 and Sentinel-2 images for May, June, and July are available, an OA greater than 80% can be achieved. The results of this study are applicable to large-scale, high-resolution crop classification and provide key technologies for remote sensing-based crop classification in small-scale agricultural areas.
Potassium‐ion batteries (PIBs) are promising alternatives to lithium‐ion batteries because of the advantage of abundant, low‐cost potassium resources. However, PIBs are facing a pivotal challenge to ...develop suitable electrode materials for efficient insertion/extraction of large‐radius potassium ions (K+). Here, a viable anode material composed of uniform, hollow porous bowl‐like hard carbon dual doped with nitrogen (N) and phosphorus (P) (denoted as N/P‐HPCB) is developed for high‐performance PIBs. With prominent merits in structure, the as‐fabricated N/P‐HPCB electrode manifests extraordinary potassium storage performance in terms of high reversible capacity (458.3 mAh g−1 after 100 cycles at 0.1 A g−1), superior rate performance (213.6 mAh g−1 at 4 A g−1), and long‐term cyclability (205.2 mAh g−1 after 1000 cycles at 2 A g−1). Density‐functional theory calculations reveal the merits of N/P dual doping in favor of facilitating the adsorption/diffusion of K+ and enhancing the electronic conductivity, guaranteeing improved capacity, and rate capability. Moreover, in situ transmission electron microscopy in conjunction with ex situ microscopy and Raman spectroscopy confirms the exceptional cycling stability originating from the excellent phase reversibility and robust structure integrity of N/P‐HPCB electrode during cycling. Overall, the findings shed light on the development of high‐performance, durable carbon anodes for advanced PIBs.
A viable anode material composed of nitrogen/phosphorus co‐doped hollow porous bowl‐like hard carbon is developed for potassium ion batteries. The resulting anode manifests prominent merits in structure, endowing it with extraordinary K+ storage capability. The K+ storage mechanisms are revealed through in‐depth studies by combining in situ TEM studies, ex situ microscopic, and Raman spectroscopy in conjunction with DFT calculations.
Abstract
Air-stability is one of the most important considerations for the practical application of electrode materials in energy-harvesting/storage devices, ranging from solar cells to rechargeable ...batteries. The promising P2-layered sodium transition metal oxides (P2-Na
x
TmO
2
) often suffer from structural/chemical transformations when contacted with moist air. However, these elaborate transitions and the evaluation rules towards air-stable P2-Na
x
TmO
2
have not yet been clearly elucidated. Herein, taking P2-Na
0.67
MnO
2
and P2-Na
0.67
Ni
0.33
Mn
0.67
O
2
as key examples, we unveil the comprehensive structural/chemical degradation mechanisms of P2-Na
x
TmO
2
in different ambient atmospheres by using various microscopic/spectroscopic characterizations and first-principle calculations. The extent of bulk structural/chemical transformation of P2-Na
x
TmO
2
is determined by the amount of extracted Na
+
, which is mainly compensated by Na
+
/H
+
exchange. By expanding our study to a series of Mn-based oxides, we reveal that the air-stability of P2-Na
x
TmO
2
is highly related to their oxidation features in the first charge process and further propose a practical evaluating rule associated with redox couples for air-stable Na
x
TmO
2
cathodes.
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