Best point detour query in road networks

A point detour is a temporary deviation from a user preferred path P (not necessarily a shortest network path) for visiting a data point such as a supermarket or McDonald's. The goodness of a point detour can be measured by the additional traveling introduced, called point detour cost or simply detour cost. Given a preferred path to be traveling on, Best Point Detour (BPD) query aims to identify the point detour with the minimum detour cost. This problem can be frequently found in our daily life but is less studied. In this work, the efficient processing of BPD query is investigated with support of devised optimization techniques. Furthermore, we investigate continuous-BPD query with target at the scenario where the path to be traveling on continuously changes when a user is moving to the destination along the preferred path. The challenge of continuous-BPD query lies in finding a set of update locations which split P into partitions. In the same partition, the user has the same BPD. We process continuous-BPD query by running BPD queries in a deliberately planned strategy. The efficiency study reveals that the number of BPD queries executed is optimal. The efficiency of BPD query and continuous-BPD query processing has been verified by extensive experiments

In-service mathematics teachers’ noticing of exemplary lessons: an exploratory study in China

Seed Fund of The Education University of Hong Kong, R4248: RG43/21-22R

Single Inclusive Jet Production in pApA Collisions at NLO in the small-xx regime

We present the first complete NLO prediction with full jet algorithm implementation for the single inclusive jet production in $pA$ collisions within the CGC effective theory. Our prediction is fully differential over the final state physical kinematics, which allows the implementation of any IR safe observable including the jet clustering procedure. The NLO calculation is organized with the aid of the power counting proposed in [1] which gives rise to the novel soft contributions in the CGC factorization. We achieve the fully-differential calculation by constructing suitable subtraction terms to handle the singularities in the real corrections. The subtraction contributions can be exactly integrated analytically. We present the NLO cross section with the jets constructed using the anti-$k_T$ algorithm. The NLO calculation demonstrates explicitly the validity of the CGC factorization in jet production. Furthermore, as a byproduct of the subtraction method, we also derive the fully analytic cross section for the forward jet production in the small-$R$ limit. We show that in the small-$R$ approximation, the forward jet cross section can be factorized into a semi-hard cross section that produces a parton and the semi-inclusive jet functions. We argue that this feature holds for generic jet production and jet substructure observables in the CGC framework. Last, we show numerical analyses of the derived formula to validate our calculations. We justify when the small-$R$ approximation is appropriate. Like forward hadron production, the obtained NLO result also exhibits the negativity of the cross section in the large jet transverse regime, which signals the need for the threshold resummation. A sketch of the threshold resummation in the CGC framework is presented based on the multiple emission picture.Comment: 67 pages, multiple figures, comments welcome, reference update

Automatic segmentation of meniscus based on MAE self-supervision and point-line weak supervision paradigm

Medical image segmentation based on deep learning is often faced with the problems of insufficient datasets and long time-consuming labeling. In this paper, we introduce the self-supervised method MAE(Masked Autoencoders) into knee joint images to provide a good initial weight for the segmentation model and improve the adaptability of the model to small datasets. Secondly, we propose a weakly supervised paradigm for meniscus segmentation based on the combination of point and line to reduce the time of labeling. Based on the weak label ,we design a region growing algorithm to generate pseudo-label. Finally we train the segmentation network based on pseudo-labels with weight transfer from self-supervision. Sufficient experimental results show that our proposed method combining self-supervision and weak supervision can almost approach the performance of purely fully supervised models while greatly reducing the required labeling time and dataset size.Comment: 8 pages,10 figure

Towards superior biopolymer gels by enabling interpenetrating network structures:A review on types, applications, and gelation strategies

Gels derived from single networks of natural polymers (biopolymers) typically exhibit limited physical properties and thus have seen constrained applications in areas like food and medicine. In contrast, gels founded on a synergy of multiple biopolymers, specifically polysaccharides and proteins, with intricate interpenetrating polymer network (IPN) structures, represent a promising avenue for the creation of novel gel materials with significantly enhanced properties and combined advantages. This review begins with the scrutiny of newly devised IPN gels formed through a medley of polysaccharides and/or proteins, alongside an introduction of their practical applications in the realm of food, medicine, and environmentally friendly solutions. Finally, based on the fact that the IPN gelation process and mechanism are driven by different inducing factors entwined with a diverse amalgamation of polysaccharides and proteins, our survey underscores the potency of physical, chemical, and enzymatic triggers in orchestrating the construction of crosslinked networks within these biomacromolecules. In these mixed systems, each specific inducer aligns with distinct polysaccharides and proteins, culminating in the generation of semi-IPN or fully-IPN gels through the intricate interpenetration between single networks and polymer chains or between two networks, respectively. The resultant IPN gels stand as paragons of excellence, characterized by their homogeneity, dense network structures, superior textural properties (e.g., hardness, elasticity, adhesion, cohesion, and chewability), outstanding water-holding capacity, and heightened thermal stability, along with guaranteed biosafety (e.g., nontoxicity and biocompatibility) and biodegradability. Therefore, a judicious selection of polymer combinations allows for the development of IPN gels with customized functional properties, adept at meeting precise application requirements.</p

In silico analyses for potential key genes associated with gastric cancer

Background Understanding hub genes involved in gastric cancer (GC) metastasis could lead to effective approaches to diagnose and treat cancer. In this study, we aim to identify the hub genes and investigate the underlying molecular mechanisms of GC. Methods To explore potential therapeutic targets for GC,three expression profiles (GSE54129, GSE33651, GSE81948) of the genes were extracted from the Gene Expression Omnibus (GEO) database. The GEO2R online tool was applied to screen out differentially expressed genes (DEGs) between GC and normal gastric samples. Database for Annotation, Visualization and Integrated Discovery was applied to perform Gene Ontology (GO) and KEGG pathway enrichment analysis. The protein-protein interaction (PPI) network of these DEGs was constructed using a STRING online software. The hub genes were identified by the CytoHubba plugin of Cytoscape software. Then, the prognostic value of these identified genes was verified by gastric cancer database derived from Kaplan-Meier plotter platform. Results A total of 85 overlapped upregulated genes and 44 downregulated genes were identified. The majority of the DEGs were enriched in extracellular matrix organization, endodermal cell differentiation, and endoderm formation. Moreover, five KEGG pathways were significantly enriched, including ECM-receptor interaction, amoebiasis, AGE-RAGE signaling pathway in diabetic complications, focal adhesion, protein digestion and absorption. By combining the results of PPI network and CytoHubba, a total of nine hub genes including COL1A1, THBS1, MMP2, CXCL8, FN1, TIMP1, SPARC, COL4A1, and ITGA5 were selected. The Kaplan-Meier plotter database confirmed that overexpression levels of these genes were associated with reduced overall survival, except for THBS1 and CXCL8. Conclusions Our study suggests that COL1A1, MMP2, FN1, TIMP1, SPARC, COL4A1, and ITGA5 may be potential biomarkers and therapeutic targets for GC. Further study is needed to assess the effect of THBS1 and CXCL8 on GC

AoBck1 and AoMkk1 Are Necessary to Maintain Cell Wall Integrity, Vegetative Growth, Conidiation, Stress Resistance, and Pathogenicity in the Nematode-Trapping Fungus Arthrobotrys oligospora

The cell wall integrity (CWI) pathway is composed of three mitogen-activated protein kinases (MAPKs), Bck1, Mkk1/2, and Slt2, and is one of the main signaling pathways for fungal pathogenesis, cell wall synthesis, and integrity maintenance. In this study, we characterized orthologs of Saccharomyces cerevisiae Bck1 and Mkk1 in the nematode-trapping (NT) fungus Arthrobotrys oligospora by multiple phenotypic comparison, and the regulation of conidiation and cell wall synthesis was analyzed using real-time PCR (RT-PCR). Both ΔAoBck1 and ΔAoMkk1 mutants showed severe defects in vegetative growth, cell nucleus number, and stress resistance. Both the mutants were unable to produce spores, and the transcription of several genes associated with sporulation and cell wall biosynthesis was markedly downregulated during the conidiation stage. Further, cell walls of the ΔAoBck1 and ΔAoMkk1 mutants were severely damaged, and the Woronin body failed to respond to cellular damage. In particular, the mutants lost the ability to produce mycelial traps for nematode predation. Taken together, AoBck1 and AoMkk1 play a conserved role in mycelial growth and development, CWI, conidiation, multi-stress tolerance, trap formation, and pathogenicity. We highlighted the role of AoBck1 and AoMkk1 in regulating the Woronin body response to cellular damage and cell nucleus development in A. oligospora