Online Community Detection by Spectral CUSUM

We present an online community change detection algorithm called spectral CUSUM to detect the emergence of a community using a subspace projection procedure based on a Gaussian model setting. Theoretical analysis is provided to characterize the average run length (ARL) and expected detection delay (EDD), as well as the asymptotic optimality. Simulation and real data examples demonstrate the good performance of the proposed method

Dynamics of fractional N-soliton solutions with anomalous dispersions of integrable fractional higher-order nonlinear Schr\"odinger equations

In this paper, we explore the anomalous dispersive relations, inverse scattering transform and fractional N-soliton solutions of the integrable fractional higher-order nonlinear Schrodinger (fHONLS) equations, containing the fractional Hirota (fHirota), fractional complex mKdV (fcmKdV), and fractional Lakshmanan-Porsezian-Daniel (fLPD) equations, etc. The inverse scattering problem can be solved exactly by means of the matrix Riemann-Hilbert problem with simple poles. As a consequence, an explicit formula is found for the fractional N-soliton solutions of the fHONLS equations in the reflectionless case. In particular, we analyze the fractional one-, two- and three-soliton solutions with anomalous dispersions of fHirota and fcmKdV equations. The wave, group, and phase velocities of these envelope fractional 1-soliton solutions are related to the power laws of their amplitudes. These obtained fractional N-soliton solutions may be useful to explain the related super-dispersion transports of nonlinear waves in fractional nonlinear media.Comment: 14 pages, 4 figure

Modeling and Simulation of Working Characteristics of Lithium Titanate Batteries for Emergency Power Transmission

This paper presents a battery model applied to dynamic simulation software. The simulation model uses only the battery State-Of-Charge (SOC) as a state variable in order to avoid the algebraic loop problem. It is shown that this model, composed of a controlled voltage source in series with a resistance, can accurately describe the lithium titanate battery discharge process. The model’s parameters can be easily extracted from the manufacturer’s discharge curve. In this paper, it is actually applied to the self-starting system after the emergency stop of the EMU, the simulation model of the system is established by MATLAB/Simulink, and the ground test platform is used to simulate the actual working condition of EMU to complete the experimental verification. The results of both simulation and experiment proved that the scheme of battery self-shifting driven system is feasible and correct

Identification of a family of Bsp-A like surface proteins of Entamoeba histolytica with novel leucine rich repeats.

Leucine rich repeats serve as recognition motifs for surface proteins from bacteria and eukaryotes. The BspA protein from Bacteroides forsythus mediates bacterial binding to fibronectin and contains leucine rich repeats of the Treponema pallidum (TpLRRP) family. Here we show that the protozoan parasite Entamoeba histolytica contains multiple BspA-like proteins, including a family of surface proteins which possess a new form of a leucine rich repeat that differs from the standard Treponema pallidum- like leucine rich repeat (TpLRRP) by possessing two conserved cysteine residues

Association Between Three-Dimensional Transrectal Ultrasound Findings and Tumor Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer: An Observational Study

BackgroundThere is a significant demand for the development of non-surgical methods for the evaluation of complete response to tumor therapy. Predicting ability and image quality of routine imaging has not been satisfactory. To avoid the deficiencies, we assessed the capability of three-dimensional transrectal ultrasound in predicting the response to neoadjuvant chemoradiotherapy in rectal cancer patients.MethodsThe inclusion criteria were patients with locally advanced rectal adenocarcinoma, receiving capecitabine-based neoadjuvant chemoradiotherapy, distance from anal verge (≤6 cm), clinical stage T3-4 and/or N+ without evidence of distant metastasis, and restaging ycT0-3a (T3a <5 mm) after the end of neoadjuvant chemoradiotherapy. Three-dimensional transrectal ultrasound was performed 7 weeks after neoadjuvant chemoradiotherapy to discern the patients with complete response from the others. Eight main parameters were obtained from three-dimensional transrectal ultrasound: thickness of muscularis on the residual side, thickness of contralateral muscularis, angle of residual arc, regularity of the shape, integrity of the mucosal layer, blurring of the margin, internal echo, and posterior echo. The association between tumor response and three-dimensional transrectal ultrasound parameters was analyzed, and a model was developed by logistic regression.ResultsBetween 2014 and 2019, 101 patients were recruited; 72 cases received total mesorectal excision, and 29 cases underwent watch-and-wait. Among the three-dimensional transrectal ultrasound parameters, the adjusted-thickness of the muscularis (P<0.01), angle of the residual arc (P<0.01), and regularity of the residual shape (P<0.01) were strongly associated with tumor response. In the dataset with total mesorectal excision cases (TME dataset), the residual adjusted-thickness (odds ratio [OR]=4.88, 95% confidence interval [CI]=1.44–16.6, P=0.01) and regularity of the residual shape (OR=5.00, 95% CI=1.13–22.2, P=0.03) were kept in the final logistic model. The area under the curve of the logistic model was 0.84. Among these parameters, residual adjusted-thickness correlated significantly with tumor response. Additionally, we observed similar results in the whole population of 101 cases (whole dataset) and in the cross-validation.ConclusionThree-dimensional transrectal ultrasound model is a valuable method for predicting tumor response in rectal cancer patients undergoing neoadjuvant chemoradiotherapy, which should be included as a factor for evaluating clinical complete response.Trial RegistrationThis trial was registered with ClinicalTrials.gov, number NCT02605265. Registered 9 November 2015 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/record/NCT0260526

Energy management strategy based on dynamic programming for dual source trolleybus

Dizajniran je novi model trolejbusa s dvojnim izvorom napajanja s akumulatorom i super električnim kondenzatorom, a s tim povezani parametri dinamičkog sustava dizajnirani su na temelju teorije dedukcije. Simulacijski model razvijen je u ADVISOR softveru. Zasnovana na analizi radnih modova trolejbusa s dvojnim sustavom napajanja, dizajnirana je optimalna strategija upravljanja na temelju dinamičkog programiranja čiji je cilj reduciranje vršne snage mreže on-line moda i potrošnje energije off-line moda. Uz to, upravljačka strategija zasnovana na tom pravilu također je implementirana i uspoređena s poboljšanom strategijom upravljanja. Rezultati su pokazali da metode optimizacije temeljene na dinamičkom programiranju mogu u potpunosti iskoristiti super električni kondenzator velike snage, s brzim punjenjem i pražnjenjem, i učinkovitije rasporediti energiju među izvorima energije te poboljšati dinamičke i ekonomske karakteristike trolejbusa.The dual source trolleybus of a new model with battery and super capacitor energy storage system was designed. The related parameters of dynamical system were designed on the basis of theory deduction, and the simulation model was re-developed in ADVISOR software. Based on the analysis of work modes of the dual source trolleybus, an optimal control strategy based on Dynamic Programming was designed, which is aimed at reducing grid peaking power of on-line mode and energy consumption of off-line mode. In addition, the rule based control strategy has also been implemented and compared to the optimized control strategy. The results have demonstrated that the optimization techniques based on Dynamic Programming can make full use of the supercapacitors with high power and fast charging/discharging characteristics, and more effectively distribute the power between the power sources, improve the dynamic performance and economic performance of the trolleybus

Parallel Prediction Method of Knowledge Proficiency Based on Bloom’s Cognitive Theory

Knowledge proficiency refers to the extent to which students master knowledge and reflects their cognitive status. To accurately assess knowledge proficiency, various pedagogical theories have emerged. Bloom’s cognitive theory, proposed in 1956 as one of the classic theories, follows the cognitive progression from foundational to advanced levels, categorizing cognition into multiple tiers including “knowing”, “understanding”, and “application”, thereby constructing a hierarchical cognitive structure. This theory is predominantly employed to frame the design of teaching objectives and guide the implementation of teaching activities. Additionally, due to the large number of students in real-world online education systems, the time required to calculate knowledge proficiency is significantly high and unacceptable. To ensure the applicability of this method in large-scale systems, there is a substantial demand for the design of a parallel prediction model to assess knowledge proficiency. The research in this paper is grounded in Bloom’s Cognitive theory, and a Bloom Cognitive Diagnosis Parallel Model (BloomCDM) for calculating knowledge proficiency is designed based on this theory. The model is founded on the concept of matrix decomposition. In the theoretical modeling phase, hierarchical and inter-hierarchical assumptions are initially established, leading to the abstraction of the mathematical model. Subsequently, subject features are mapped onto the three-tier cognitive space of “knowing”, “understanding”, and “applying” to derive the posterior distribution of the target parameters. Upon determining the objective function of the model, both student and topic characteristic parameters are computed to ascertain students’ knowledge proficiency. During the modeling process, in order to formalize the mathematical expressions of “understanding” and “application”, the notions of “knowledge group” and “higher-order knowledge group” are introduced, along with a parallel method for identifying the structure of higher-order knowledge groups. Finally, the experiments in this paper validate that the model can accurately diagnose students’ knowledge proficiency, affirming the scientific and meaningful integration of Bloom’s cognitive hierarchy in knowledge proficiency assessment

De-fine: Decomposing and Refining Visual Programs with Auto-Feedback

Visual programming, a modular and generalizable paradigm, integrates different modules and Python operators to solve various vision-language tasks. Unlike end-to-end models that need task-specific data, it advances in performing visual processing and reasoning in an unsupervised manner. Current visual programming methods generate programs in a single pass for each task where the ability to evaluate and optimize based on feedback, unfortunately, is lacking, which consequentially limits their effectiveness for complex, multi-step problems. Drawing inspiration from benders decomposition, we introduce De-fine, a general framework that automatically decomposes complex tasks into simpler subtasks and refines programs through auto-feedback. This model-agnostic approach can improve logical reasoning performance by integrating the strengths of multiple models. Our experiments across various visual tasks show that De-fine creates more accurate and robust programs, setting new benchmarks in the field