A Study on the Impact of Face Recognition Payment System Characteristics and Innovation Resistance on Intention to Use: Focusing on Chinese Users

With the arrival of the fourth industrial revolution, new technologies have been applied in many fields. An example is the face recognition technology applied in customs, attendance, payment, and other fields, which greatly improved customer convenience. In the recent years, face recognition technology has been applied in the financial industry, and new face recognition settlement services have emerged. Face recognition payment scans a person's face through a camera, analyzes the eyes, mouth, ears, etc. as face feature points, and compares the extracted data with the stored database to determine whether it is the person. When payment requires identity verification, face recognition is used instead of password input or other verification systems, and this only takes five seconds to complete. The purpose of this study is to successfully diffuse face recognition payment services and investigate resistance to use, giving businesses information to refer to. Therefore, this paper makes an empirical analysis of how the characteristics of settlement system and innovation resistance affect the intention to use. In this study, an empirical analysis was conducted after reviewing previous studies on the characteristics of the financial system, innovation resistance, and intention to use. Based on previous studies, Rephrase. The characteristics of face recognition payment system includes convenience, reliability, security, and contactless transaction. A survey was conducted among Chinese users and the results were analyzed using Smart PLS 2.0 structural equations. The results of the study are as follows. First, among the features of the face recognition payment system, convenience, reliability, and security have a negative effect on user innovation resistance. Second, among the features of the face recognition payment system, non-contact has a positive impact on user innovation resistance. Third, user innovation resistance has a negative effect on the intention to use

Development Model of Higher Education Cluster in Chengdu and Chongqing

This study endeavors to investigate the influencing factors behind the development of higher education clusters in the Chengdu-Chongqing region and establish a model aimed at enhancing their effectiveness. To achieve this objective, a Likert Scale was employed, comprising four primary dimensions, 14 secondary dimensions, and 39 items, initially validated through a pre-survey and SPSS software analysis. Subsequently, 405 valid questionnaires were collected from government officials, university administrators, and business leaders in the Chengdu-Chongqing region through an online platform and email. SmartPLS software was then used for analysis, confirming strong reliability and discriminant validity of the survey data. Further structural analysis revealed no issues of collinearity and identified government, universities, and enterprises as positively influencing factors on the Chengdu-Chongqing higher education cluster’s effectiveness. Eight secondary dimensions and 17 items were identified as positively impacting cluster effectiveness, leading to the formulation of a government-university-enterprise model for higher education cluster development in the Chengdu-Chongqing region

Estimation of subsurface porosities and thermal conductivities of polygonal tundra by coupled inversion of electrical resistivity, temperature, and moisture content data

Studies indicate greenhouse gas emissions following permafrost thaw will amplify current rates of atmospheric warming, a process referred to as the permafrost carbon feedback. However, large uncertainties exist regarding the timing and magnitude of the permafrost carbon feedback, in part due to uncertainties associated with subsurface permafrost parameterization and structure. Development of robust parameter estimation methods for permafrost-rich soils is becoming urgent under accelerated warming of the Arctic. Improved parameterization of the subsurface properties in land system models would lead to improved predictions and a reduction of modeling uncertainty. In this work we set the groundwork for future parameter estimation (PE) studies by developing and evaluating a joint PE algorithm that estimates soil porosities and thermal conductivities from time series of soil temperature and moisture measurements and discrete in-time electrical resistivity measurements. The algorithm utilizes the Model-Independent Parameter Estimation and Uncertainty Analysis toolbox and coupled hydrological-thermal-geophysical modeling. We test the PE algorithm against synthetic data, providing a proof of concept for the approach. We use specified subsurface porosities and thermal conductivities and coupled models to set up a synthetic state, perturb the parameters, and then verify that our PE method is able to recover the parameters and synthetic state. To evaluate the accuracy and robustness of the approach we perform multiple tests for a perturbed set of initial starting parameter combinations. In addition, we varied types and quantities of data to better understand the optimal dataset needed to improve the PE method. The results of the PE tests suggest that using multiple types of data improve the overall robustness of the method. Our numerical experiments indicate that special care needs to be taken during the field experiment setup so that (1) the vertical distance between adjacent measurement sensors allows the signal variability in space to be resolved and (2) the longer time interval between resistivity snapshots allows signal variability in time to be resolved

S-Lemma with Equality and Its Applications

Let $f(x)=x^TAx+2a^Tx+c$ and $h(x)=x^TBx+2b^Tx+d$ be two quadratic functions having symmetric matrices $A$ and $B$. The S-lemma with equality asks when the unsolvability of the system $f(x)<0, h(x)=0$ implies the existence of a real number $\mu$ such that $f(x) + \mu h(x)\ge0, ~\forall x\in \mathbb{R}^n$. The problem is much harder than the inequality version which asserts that, under Slater condition, $f(x)<0, h(x)\le0$ is unsolvable if and only if $f(x) + \mu h(x)\ge0, ~\forall x\in \mathbb{R}^n$ for some $\mu\ge0$. In this paper, we show that the S-lemma with equality does not hold only when the matrix $A$ has exactly one negative eigenvalue and $h(x)$ is a non-constant linear function ($B=0, b\not=0$). As an application, we can globally solve $\inf\{f(x)\vert h(x)=0\}$ as well as the two-sided generalized trust region subproblem $\inf\{f(x)\vert l\le h(x)\le u\}$ without any condition. Moreover, the convexity of the joint numerical range $\{(f(x), h_1(x),\ldots, h_p(x)):~x\in\Bbb R^n\}$ where $f$ is a (possibly non-convex) quadratic function and $h_1(x),\ldots,h_p(x)$ are affine functions can be characterized using the newly developed S-lemma with equality.Comment: 34 page

Single-cell analysis of chromatin and expression reveals age- and sex-associated alterations in the human heart

Sex differences and age-related changes in the human heart at the tissue, cell, and molecular level have been well-documented and many may be relevant for cardiovascular disease. However, how molecular programs within individual cell types vary across individuals by age and sex remains poorly characterized. To better understand this variation, we performed single-nucleus combinatorial indexing (sci) ATAC- and RNA-Seq in human heart samples from nine donors. We identify hundreds of differentially expressed genes by age and sex and find epigenetic signatures of variation in ATAC-Seq data in this discovery cohort. We then scale up our single-cell RNA-Seq analysis by combining our data with five recently published single nucleus RNA-Seq datasets of healthy adult hearts. We find variation such as metabolic alterations by sex and immune changes by age in differential expression tests, as well as alterations in abundance of cardiomyocytes by sex and neurons with age. In addition, we compare our adult-derived ATAC-Seq profiles to analogous fetal cell types to identify putative developmental-stage-specific regulatory factors. Finally, we train predictive models of cell-type-specific RNA expression levels utilizing ATAC-Seq profiles to link distal regulatory sequences to promoters, quantifying the predictive value of a simple TF-to-expression regulatory grammar and identifying cell-type-specific TFs. Our analysis represents the largest single-cell analysis of cardiac variation by age and sex to date and provides a resource for further study of healthy cardiac variation and transcriptional regulation at single-cell resolution

Lung allograft standardized histological analysis (LASHA) template: A research consensus proposal

BACKGROUND: Routine monitoring of lung-transplanted patients is crucial for the identification of immunological and non-immunological complications. Determining the etiology of acute allograft dysfunction, particularly in alloimmune-mediated disorders, relies heavily on the lung biopsy with histopathologic analysis. Standardization of the pathologic diagnosis of rejection (e.g., cellular and antibody-mediated) is based on consensus statements and guidelines, indicating the importance of a multidisciplinary approach to achieve a definitive etiological diagnosis. In addition to these statements and guidelines, refinements and standardizations are feasible through systematic analysis morphological, immunophenotypic and molecular alterations observed in transbronchial biopsies. This study is to identify key morphologic features to be assessed, select consistent and reproducible terminology for each histological feature, and provide standardized definitions for pathological assessment and grading. METHODS: A template was created by experts in lung transplantation including pathologists, pulmonologists, immunologists. An initial draft was circulated, followed by discussions and multiple revisions by email and conference calls. RESULTS: The lung allograft standardized histological analysis - LASHA template was created and structured as multiple-choice questions with number of fields to be filled in to allow for standardization of results and easy transfer into a future electronic spreadsheet. CONCLUSION: This template will help facilitate multicenter studies through a uniform protocol and correlations with new diagnostic modalities. After validation in large-scale studies, an optimized template could be included in routine clinical practice to enhance graft assessment and medical decision-making

Hyperferritinemic sepsis, macrophage activation syndrome, and mortality in a pediatric research network: A causal inference analysis

BACKGROUND: One of five global deaths are attributable to sepsis. Hyperferritinemic sepsis (\u3e 500 ng/mL) is associated with increased mortality in single-center studies. Our pediatric research network\u27s objective was to obtain rationale for designing anti-inflammatory clinical trials targeting hyperferritinemic sepsis. METHODS: We assessed differences in 32 cytokines, immune depression (low whole blood ex vivo TNF response to endotoxin) and thrombotic microangiopathy (low ADAMTS13 activity) biomarkers, seven viral DNAemias, and macrophage activation syndrome (MAS) defined by combined hepatobiliary dysfunction and disseminated intravascular coagulation, and mortality in 117 children with hyperferritinemic sepsis (ferritin level \u3e 500 ng/mL) compared to 280 children with sepsis without hyperferritinemia. Causal inference analysis of these 41 variables, MAS, and mortality was performed. RESULTS: Mortality was increased in children with hyperferritinemic sepsis (27/117, 23% vs 16/280, 5.7%; Odds Ratio = 4.85, 95% CI [2.55-9.60]; z = 4.728; P-value \u3c 0.0001). Hyperferritinemic sepsis had higher C-reactive protein, sCD163, IL-22, IL-18, IL-18 binding protein, MIG/CXCL9, IL-1β, IL-6, IL-8, IL-10, IL-17a, IFN-γ, IP10/CXCL10, MCP-1/CCL2, MIP-1α, MIP-1β, TNF, MCP-3, IL-2RA (sCD25), IL-16, M-CSF, and SCF levels; lower ADAMTS13 activity, sFasL, whole blood ex vivo TNF response to endotoxin, and TRAIL levels; more Adenovirus, BK virus, and multiple virus DNAemias; and more MAS (P-value \u3c 0.05). Among these variables, only MCP-1/CCL2 (the monocyte chemoattractant protein), MAS, and ferritin levels were directly causally associated with mortality. MCP-1/CCL2 and hyperferritinemia showed direct causal association with depressed ex vivo whole blood TNF response to endotoxin. MCP-1/CCL2 was a mediator of MAS. MCP-1/CCL2 and MAS were mediators of hyperferritinemia. CONCLUSIONS: These findings establish hyperferritinemic sepsis as a high-risk condition characterized by increased cytokinemia, viral DNAemia, thrombotic microangiopathy, immune depression, macrophage activation syndrome, and death. The causal analysis provides rationale for designing anti-inflammatory trials that reduce macrophage activation to improve survival and enhance infection clearance in pediatric hyperferritinemic sepsis

Organization of the human intestine at single-cell resolution

The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall healt