Nonlinear Dynamics and Exact Traveling Wave Solutions of the Higher-Order Nonlinear Schrödinger Equation with Derivative Non-Kerr Nonlinear Terms

By using the method of dynamical system, the exact travelling wave solutions of the higher-order nonlinear Schrödinger equation with derivative non-Kerr nonlinear terms are studied. Based on this method, all phase portraits of the system in the parametric space are given with the aid of the Maple software. All possible bounded travelling wave solutions, such as solitary wave solutions, kink and anti-kink wave solutions, and periodic travelling wave solutions, are obtained, respectively. The results presented in this paper improve the related previous conclusions

Exact Periodic Wave, Bisoliton, and Various Breather Solutions for the Zakharov Equations

The Zakharov equations, which involve the interactions between Langmuir and ion acoustic waves in plasma, are analytically studied. By using the method of Exp-function, the periodic wave, bisoliton, Akhmediev breather, Ma breather, and Peregrine breather of the Zakharov equations are obtained. These results presented in this paper enrich the diversity of solution structures of the Zakharov equations. Furthermore, based on the numerical simulations of these solutions, some physics analysis of bisolitons and various breathers are given

Evaluating the significance of ECSCR in the diagnosis of ulcerative colitis and drug efficacy assessment

BackgroundThe main challenge in diagnosing and treating ulcerative colitis (UC) has prompted this study to discover useful biomarkers and understand the underlying molecular mechanisms.MethodsIn this study, transcriptomic data from intestinal mucosal biopsies underwent Robust Rank Aggregation (RRA) analysis to identify differential genes. These genes intersected with UC key genes from Weighted Gene Co-expression Network Analysis (WGCNA). Machine learning identified UC signature genes, aiding predictive model development. Validation involved external data for diagnostic, progression, and drug efficacy assessment, along with ELISA testing of clinical serum samples.ResultsRRA integrative analysis identified 251 up-regulated and 211 down-regulated DEGs intersecting with key UC genes in WGCNA, yielding 212 key DEGs. Subsequently, five UC signature biomarkers were identified by machine learning based on the key DEGs—THY1, SLC6A14, ECSCR, FAP, and GPR109B. A logistic regression model incorporating these five genes was constructed. The AUC values for the model set and internal validation data were 0.995 and 0.959, respectively. Mechanistically, activation of the IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway in UC was indicated by KEGG and GSVA analyses, which were positively correlated with the signature biomarkers. Additionally, the expression of the signature biomarkers was strongly correlated with various UC types and drug efficacy in different datasets. Notably, ECSCR was found to be upregulated in UC serum and exhibited a positive correlation with neutrophil levels in UC patients.ConclusionsTHY1, SLC6A14, ECSCR, FAP, and GPR109B can serve as potential biomarkers of UC and are closely related to signaling pathways associated with UC progression. The discovery of these markers provides valuable information for understanding the molecular mechanisms of UC

Exact Periodic Wave, Bisoliton, and Various Breather Solutions for the Zakharov Equations

The Zakharov equations, which involve the interactions between Langmuir and ion acoustic waves in plasma, are analytically studied. By using the method of Exp-function, the periodic wave, bisoliton, Akhmediev breather, Ma breather, and Peregrine breather of the Zakharov equations are obtained. These results presented in this paper enrich the diversity of solution structures of the Zakharov equations. Furthermore, based on the numerical simulations of these solutions, some physics analysis of bisolitons and various breathers are given

Chlorine-Resistant Loose Nanofiltration Membranes Fabricated via Interfacial Polymerization Using Sulfone Group-Containing Amine Monomer for Dye/Salt Separation

Fabrication of high-dye/salt-separation-performances and chlorine-resistant nanofiltration (NF) membranes are crucial for dye desalination. In this study, a thin-film composite NF membrane (PES–DPS) was prepared through the interfacial polymerization of 3,3′-diaminodiphenyl sulfone (DPS) and trimesoyl chloride. Because of the low reactivity and the presence of the sulfone group (O=S=O) of DPS, the prepared PES–DPS membrane provided a relatively loose polyamide layer and exhibited excellent chlorine resistance, enhancing the membrane water flux and dye/salt separation performances. Furthermore, the influence of DPS concentration was systematically investigated. The optimal membrane PES–DPS–1 exhibited high direct Blue 71 rejection (99.1%) and low NaCl rejection (8.7%). Meanwhile, the PES–DPS–1 membrane displayed highly pure water flux (49.4 L·m−2·h−1·bar−1) even at a low-operating pressure (2 bar). Moreover, no significant difference in dye rejection was observed when the membrane was immersed in NaClO solution (pH = 4.0, 2000 ppm) for 12 h, thereby demonstrating its outstanding chlorine stability. In summary, this work provided a new monomer for the preparation of novel polyamide membranes to achieve excellent separation performances and chlorine resistances

STRUCTURAL GLOBAL SENSITIVITY METHOD BASED ON PARTIAL DERIVATIVE WHOLE DOMAIN INTEGRAL

In view of the problems that the traditional variance-based Sobol’method had a low solving efficiency,lacked of enough robustness,and it cannot further effectively decompose and reasonably distribute the influences of the high-order cross subterms,a practical and effective structural global sensitivity method was proposed in this paper based on partial derivative whole domain integral and optimal polynomial surrogate model. Firstly,optimal surrogate model was constructed through polynomial structure-selection,which had good fitting and predictive ability,and it was convenient for direct integral operations. Then,local sensitivity method based on partial derivative was extended to a global sensitivity method by integrating partial derivatives of model variables in variable sapces. In addition,the paper redefined a more conveniently calculated sensitivity indice that can achieve effective decomposition for the high-order sensitivity indices,and the sensitivity results directly corresponded to model variables without the high-order indices,which had more practical engineering significance. Numerical example 1 shows the deficiency of Sobol’total sensitivity indices in application. Numerical example 2 illustrates the validity of the proposed method for complex high-dimensional model. Engineering example demonstrates the applicability and effectiveness of the present method for complex engineering structure problems

Characteristics of GLONASS Inter-frequency Code Bias and Its Application on Wide-lane Ambiguity Resolution

GLONASS inter-frequency code biases (IFCBs) vary with receiver manufacturers,firmware versions,and antenna types.IFCBs are hardly corrected or modeled precisely,so that Hatch-Melbourne-Wübbena (HMW) combination observation contains a systemic bias and cannot applied into GLONASS wide-lane ambiguity resolution.Utilizing the residuals of GLONASS HMW combination observations,we propose an algorithm to estimate IFCB of different sites (DS-IFCB).The experiment results show that DS-IFCB is long term stability and the sizes of DS-IFCBs in some homogeneous baselines (composed by same type of devices,i.e.receiver type,version and antenna) are larger than 0.5 meters.In order to achieve wide-lane ambiguities in real-time,DS-IFCBs,estimated with previous observations,are used as priors to cancel IFCBs in current observations.After DS-IFCB offset,both the success rate and correct rate of GLONASS wide-lane ambiguity resolutions are improved,regardless of whether baselines are equipped with homogeneous devices.The correct rates of all baselines are higher than 98%

Dynamic Teacher’s Technology Adoption During the COVID-19 Pandemic

Understanding the teacher’s technology adoption process is essential to comprehend and narrow the digital divide in the post-epidemic age. During the pandemic, the stay-at-home orders not only intervened schooling and teaching but also increased digital accessibility to teachers. This research studies teacher heterogeneity and adoption controls in the epidemic to simultaneously affect teacher’s underlying intention and adoption behavior based on a dynamic framework under the theory of planned behavior. We present a quantitative framework for modeling the teachers’ adoption behavior of a technology conditioned on intention, defined as latent dynamic processes via a hidden Markov model. This model allows us to examine the effects of three concerned adoption controls: epidemic, community, and experience. We also explicitly characterized teachers’ digital traits as the estimated results accounts for teacher’s heterogeneity. The implicit quality of digital teaching artifacts is examined to correlate the dynamic analyses with the qualitative supports. We collected data from four primary schools in Shanghai over 173 weeks, using an after-school activity management system. The data collection spanned periods both before and after the school closure caused by the epidemic, providing us with a dynamic view of technology adoption patterns under different circumstances. Our results suggest that the interventions derived from the controls of the epidemic did not significantly narrow the digital gap. In particular, well-prepared teachers may be more sensitive to adjusting their usage to meet the evolving standards. The inexperienced teacher struggles to maintain a high level of adoption once the passive external pressure is eliminated. Even the compulsory policy can temporarily change their adoption behavior. These implications highlight the second-order digital divide problem