Mutual Validation Research Articles

N6-methyladenosine regulators in hepatocellular carcinoma: investigating the precise definition and clinical applications of biomarkers

BackgroundAccurately identifying effective biomarkers and translating them into clinical practice have significant implications for improving clinical outcomes in hepatocellular carcinoma (HCC). In this study, our objective is to explore appropriate methods to improve the accuracy of biomarker identification and investigate their clinical value.MethodsConcentrating on the N6-methyladenosine (m6A) modification regulators, we utilized dozens of multi-omics HCC datasets to analyze the expression patterns and genetic features of m6A regulators. Through the integration of big data analysis with function experiments, we have redefined the biological roles of m6A regulators in HCC. Based on the key regulators, we constructed m6A risk models and explored their clinical value in estimating prognosis and guiding personalized therapy for HCC.ResultsMost m6A regulators exhibit abnormal expression in HCC, and their expression is influenced by copy number variations (CNV) and DNA methylation. Large-scale data analysis has revealed the biological roles of many key m6A regulators, and these findings are well consistent with experimental results. The m6A risk models offer significant prognostic value. Moreover, they assist in reassessing the therapeutic potential of drugs such as sorafenib, gemcitabine, CTLA4 and PD1 blockers in HCC.ConclusionsOur findings suggest that the mutual validation of big data analysis and functional experiments may facilitate the precise identification and definition of biomarkers, and our m6A risk models may have the potential to guide personalized chemotherapy, targeted treatment, and immunotherapy decisions in HCC.

Evaluation and fusion of multi-source sea ice thickness products with limited in-situ observations

Sea ice thickness (SIT) is a critical and sensitive parameter in the climate system, with its dynamic changes profoundly influencing global climate models, navigational routes, and the potential for Arctic resource development. Given the widespread application of current satellite remote sensing technology in monitoring SIT, significant uncertainties remain. This study first underscores the importance of in-situ observations as a direct measurement method for SIT. However, the limitations of in-situ data in terms of acquisition cost, spatiotemporal coverage continuity, and distribution uniformity significantly hinder the effective evaluation of multi-source SIT products. To address this, the study innovatively introduces the Triple Collocation (TC) method, which effectively mitigates the impact of errors from individual data sources on the overall evaluation results through a mutual validation mechanism among multiple satellite data sources. This allows for a scientific assessment of multi-source SIT products even in the context of scarce in-situ observations. The findings indicate that the TC method not only successfully resolves the challenges of multi-source data evaluation but also facilitates data integration among these products, significantly enhancing the overall accuracy and spatiotemporal consistency of SIT data.

An Experimental and Numerical Study of Motion Responses of Multi-Body Arrays with Hinge Connections

Hinged multi-body systems are gaining popularity in the field of ocean engineering. Their performance is commonly evaluated using numerical simulations, but comparisons with experimental data are required to ensure the accuracy of the computational tools. However, there is a dearth of experimental studies on the motion performance of hinged multi-body systems, particularly those involving more than two hinged floating bodies. This study aims to fill this gap in experimental data for hinged multi-body systems beyond two bodies. The rectangular box was chosen as the test model due to its stable hydrodynamic properties and ease of numerical modelling. Five identical boxes were prefabricated and subsequently tested in the pool in a sequence ranging from one to five boxes to capture the motion performance. Additionally, a numerical programme based on potential flow theory was developed for mutual validation with the experimental data. Firstly, the physical properties of each box were determined through equations calculation and a free decay test, enabling the acquisition of all parameters for conducting numerical simulations. Then, the response amplitude operator (RAO) curves for the heave and pitch motion of a single box were depicted, and the results indicated that the resonant frequency in pitch direction obtained from the regular wave test was consistent with that obtained from the free decay test. Finally, the motion RAO curves of hinged multi-body systems were presented and analysed. The agreement between the measured and computed results confirms the suitability of the experimental data presented in this study as benchmark data for validating numerical simulations.

Screening and analysis of GULP1 downstream target genes based on transcriptomic sequencing.

GULP1 is an engulfment adaptor protein containing a phosphotyrosine-binding (PTB) domain, and existing studies have shown that it can promote glucose uptake in 3T3-L1 adipocytes. To further explore key metabolically related differential genes downstream of GULP1, this study conducted transcriptome analysis on adipocytes and skeletal muscle cells overexpressing GULP1. Subsequently, abnormally expressed genes were subjected to bioinformatic analysis, and real-time fluorescent quantitative PCR (qRT-PCR) was used for mutual validation with transcriptome sequencing. The results indicated that, with a threshold of P < 0.05 and |Log2FoldChange| ≥ 1 for screening differentially expressed genes, compared with control cells, there were 278 upregulated and 263 downregulated genes in adipocytes overexpressing GULP1. Metabolism-related GO (Gene Ontology) terms included cholesterol biosynthetic process, cholesterol metabolic process, response to lipopolysaccharide, lipid metabolic process, etc. A total of 52 metabolically related differentially expressed genes were enriched in 10 KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways, with lipid metabolism being highly enriched. In skeletal muscle cells overexpressing GULP1, there were 280 upregulated and 302 downregulated genes, with metabolism-related GO terms including hormone metabolic process, response to lipopolysaccharide, one-carbon metabolic process, etc. A total of 86 metabolically related differentially expressed genes were enriched in 10 KEGG pathways, with amino acid metabolism, lipid metabolism, and carbohydrate metabolism being highly enriched. GULP1's biological functions are extensive, including lipid metabolism and oncology. This study, through transcriptomics and bioinformatic analysis, identified key metabolically related differential genes downstream of GULP1, obtained metabolically related differential genes and signaling pathways after GULP1 overexpression, providing important theoretical basis for future research on GULP1 downstream target genes.

A multi-method approach for assessing groundwater vulnerability of shallow aquifers in the Marchfeld region (Austria)

Study regionMarchfeld region (Austria) Study focusA multi-method and multi-scale assessment of the intrinsic groundwater vulnerability to generic pollutants was carried out. At the regional scale, a parametric method, to assess the intrinsic groundwater vulnerability, and a transfer function model, to assess the travel time of a generic and non-reactive pollutant through the unsaturated zone, were applied. At the site-specific scale, the travel time of the peak concentration was evaluated by using a physically-based hydrological model. The comparison of results of different approaches allowed mutual validation and advanced the knowledge about the assessment of groundwater vulnerability. New hydrogeological insights for the regionTo assess the groundwater vulnerability, a detailed hydrogeological map of the study area was reconstructed. A large variability of hydrogeological, morphological and anthropic conditions was recognized. Alluvial aquifers formed by high-permeability deposits hosting shallow groundwater circulation are characterized by the highest groundwater vulnerability. Contrarily, lower groundwater vulnerability was recognized for aquifers formed by low-permeability deposits, favoring a reduction of infiltration processes and a major attenuation of pollutants’ potential effects. The presented multi-method approach revealed how comparing the results of a DRASTIC-like method and two process-based models can deliver hints regarding their suitability, different spatial densities and quality of required inputs, and effectiveness. Finally, the potential strong impact of some agricultural practices was confirmed.

Identifying the possible driving mechanisms in Precipitation-Runoff relationships with nonstationary and nonlinear theory approaches

Climate change and complex anthropogenic activities have raised significant concerns regarding Precipitation-Runoff Relationships (PRR). Traditional methods, assuming stationary and linear conditions, often fail to adequately capture these intricate links. To address the limitations, we proposed an integrated framework, employing the Driving indices for Precipitation-Runoff relationships within the nonStationary and nonLinear theory approaches (DPRS and DPRL) to identify the possible driving mechanisms in PRR. The framework is validated across five sub-basins (WRB1-WRB5) within the Wei River Basin, known for its high spatiotemporal variability and intense anthropogenic activities. Spatiotemporal dynamics, nonstationary processes, and nonlinear interactions among various factors are assessed, including climate forcing, groundwater, vegetation dynamics, and anthropogenic influences. DPRS and DPRL assessments revealed that baseflow significantly influences PRR but with high uncertainty. Potential evapotranspiration plays a dominant role in driving negative PRR changes in WRB5 (weakening the correlation between precipitation and runoff), while vegetation dynamics negatively affect PRR with lower uncertainty. Anthropogenic influences represented by Impervious Surface Ratio (ISR), Night-Time Light (NTL), and population density (POP) exhibit varying driving levels, with ISR having the strongest and direct impact, closely linked to urbanization processes and scale within the study cases. The mutual validation of DPRS and DPRL confirms the dominance of baseflow in the Wei River Basin, with urbanization contributing to high ISR, NTL, and POP driving levels in WRB2 and WRB3. Afforestation policies intensify vegetation dynamics’ impact in WRB4 and WRB5. This framework extends its utility to analyze various land evapotranspiration and soil moisture content at different depths in the PRR, supported by a physically-based hydrological model. Basin complexity is further employed to validate the reliability of the assessment outcomes. These insights contribute to a more comprehensive understanding of hydrological processes and facilitate informed decisions for sustainable water resource management within the basin.

(057) INCREASING INTIMATE INTERACTIONS AS AN INTERVENTION FOR IMPROVING SEXUAL AND RELATIONAL SATISFACTION IN COUPLES

Abstract Introduction Intimacy is a critical component of satisfying romantic relationships; it is consistently, positively associated with sexual and relational satisfaction. While the cognitive perception of intimacy and related feelings of love, affection, and closeness are important, there is ample theory suggesting intimacy is more than a feeling. The central components of intimacy are love, affection, self-disclosure, and mutual validation, all of which include both behavioral and cognitive aspects of connection. The widely-accepted Interpersonal Process Model of Intimacy suggests that the exchange of intimate behaviors and experiences over time create subjective feelings of intimacy. As such, intimacy is most accurately understood as a critical agent in both the creation and maintenance of satisfying romantic relationships, not simply a byproduct of them. While intimacy is heavily researched in evaluations of satisfying relationships, it is almost exclusively assessed using an individual’s subjective feelings of intimacy. To date, little research has evaluated intimacy as a behavioral exchange between partners. Furthermore, extant research on treatments for relational and sexual dissatisfaction to date almost exclusively consider subjective feelings of intimacy as an outcome associated with increased satisfaction. Clinical research has yet to utilize intimacy as an active agent in the development and maintenance of satisfying relationships. Conducting research and creating interventions using the Interpersonal Process Model of Intimacy may allow for development of better couples’ interventions. Objective The current study aimed to evaluate whether intimacy, when conceptualized as a result of repeated, reciprocal interactions between partners, could be an active facilitator of satisfaction in relationships. By manipulating intimate interactions (e.g., kissing, sharing secrets, massages) between partners over time, the current study tested a potential self-directed, personalized, and affordable intervention for improving sexual and relational satisfaction in couples. Methods Couples were randomized to a treatment or assessment-only control group. In the treatment group, each individual within a couple rated intimate interactions that make them feel intimate with their partner from a previously compiled list of intimate interactions. Each individual was given a list of their partner’s highest rated intimate interactions and instructed to initiate one from the list each day for one month. Partners’ sexual and relational satisfaction were assessed over time. Results Data collection is ongoing; completion is anticipated by the end of January, 2024. Participants’ sexual and relational satisfaction will be assessed within each couple over time and between the treatment and control group overall. Conclusions The current study evaluates a potential intervention for improving relational and sexual satisfaction in couples. If effective, this treatment could be an accessible, affordable, and personalized treatment for couples. Disclosure No.

Comparison of the imaginary parts of the atmospheric refractive index structure parameter and aerosol flux based on different measurement methods

Abstract. The complexity of aerosol particle properties and the diversity of characterizations make aerosol vertical transport flux measurements and analysis difficult. Although there are different methods, such as aerosol particle number concentration flux and aerosol mass flux based on the eddy covariance principle as well as aerosol mass flux measurements based on the light-propagated large-aperture scintillation principle, there is a lack of mutual validation among the different methods. In this paper, a comparison of aerosol mass flux measurements based on the eddy covariance principle and aerosol mass flux measurements based on the light-propagated large-aperture scintillation principle is carried out. The key idea of aerosol mass flux measurements based on the light-propagated large-aperture scintillation principle is the determination of the imaginary part of the atmospheric equivalent refractive index structure parameter (AERISP). In this paper, we first compare the AERISPs measured by two different methods and then compare the aerosol mass vertical transport fluxes obtained by different methods. The experiments were conducted on the campus of the University of Science and Technology of China (USTC). A light propagation experiment was carried out between two tall buildings to obtain the imaginary and real parts of the AERISPs for the whole path, which in turn can be used to obtain the aerosol vertical transport flux. An updated visibility meter is installed on the meteorological tower in the middle of the light path, which is utilized to obtain the single-point visibility, which is then converted to the imaginary part of the atmospheric equivalent refractive index (AERI). The imaginary parts of the AERISP were obtained via spectral analysis with visibility data. The results show that the imaginary parts of the AERISPs obtained by different methods are in good agreement. The imaginary part of the AERI measured by the visibility meter and the vertical wind speed obtained by the ultrasonic anemometer were used for covariance calculations to obtain the aerosol vertical transport flux. The trends in aerosol vertical transport fluxes obtained by the different methods are consistent, and there are differences in some details, which may be caused by the inhomogeneity in the vertical transport of aerosol fluxes. The experimental results also showed that urban green land is a sink area for aerosol particles.

EGFR Oncogenic Mutations in NSCLC Impair Macrophage Phagocytosis and Mediate Innate Immune Evasion Through Up-Regulation of CD47

IntroductionEGFR-mutated NSCLC is characterized by an immunosuppressive microenvironment that confers limited clinical effectiveness to anti–PD-1 or PD-L1 antibodies. Despite the discouraging outcomes of immunotherapy, novel immune checkpoints are constantly emerging, among which the specific vulnerability for therapeutic intervention in the context of EGFR-mutated NSCLC remains unresolved. MethodsData sets of patient- and cell line-levels were used for screening and mutual validation of association between EGFR mutation and a panel of immune checkpoint-related genes. Regulatory mechanism was elucidated through in vitro manipulation of EGFR signaling pathway and evaluated by immunoblot analysis, quantitative polymerase chain reaction, flow cytometry, immunofluorescence staining, and chromatin immunoprecipitation. In vivo investigation of different therapeutic strategies were conducted using both immunocompetent and immunodeficient mouse models. ResultsAmong all screened immune checkpoints, CD47 emerged as the candidate most relevant to EGFR activation. Mechanistically, EGFR mutation constitutively activated downstream ERK and AKT pathways to respectively up-regulate the transcriptional factors c-Myc and NF-κB, both of which structurally bound to the promotor region of CD47 and actively transcribed this “don’t eat me” signal. Impaired macrophage phagocytosis was observed on introduction of EGFR-sensitizing mutations in NSCLC cell line models, whereas CD47 blockade restored the phagocytic capacity and augmented tumor cell killing in both in vitro and in vivo models. Remarkably, the combination of anti-CD47 antibody with EGFR tyrosine kinase inhibitor revealed an additive antitumor activity compared with monotherapy of either antitumor agent in both immunocompetent and adaptive immunity-deficient mouse models. ConclusionsEGFR-sensitizing mutation facilitates NSCLC’s escape from innate immune attack through up-regulating CD47. Combination therapy incorporating CD47 blockade holds substantial promise for clinical translation in developing more effective therapeutic approaches against EGFR-mutant NSCLC.

Identification and extraction of cementation patterns in sand modified by MICP: New insights at the pore scale.

Microbially induced calcium carbonate precipitation (MICP) is an environmentally friendly technology that improves soil permeability resistance through biocementation. In this study, 2D microscopic analysis and 3D volume reconstruction were performed on river sand after 24 cycles of bio-treatment based on stacked images and computed tomography (CT) scanning data, respectively, to extract biocementation patterns between particles. Based on the mutual validation findings of the two techniques, three patterns in the biocemented sand were identified as G-C-G, G-C, and G-G. Specifically, 2D microscopic analysis showed that G-C-G featured multi-particle encapsulation and bridging, with a pore filling ratio of 81.2%; G-C was characterized by locally coated particle layers, with a pore filling ratio of 19.7%; and the G-G was marked by sporadic filling of interparticle pores, with a pore filling ratio of 11.7%. G-C-G had the best cementation effect and permeability resistance (effective sealing rate of 68.5%), whereas G-C (effective sealing rate of 2.4%) had a relatively minor contribution to pore-filling and flow sealing. 3D volume reconstruction showed that G-C-G had the highest pore filling rate, followed by G-G and G-C. The average filling ratios of area and volume for G-C-G were 83.979% and 77.257%, respectively; for G-G 20.360% and 23.600%; and for G-C 11.545% and 11.250%. The analysis of the representative element volume (REV) was conducted, and the feasibility and reliability of the micro-scale pattern extraction results were confirmed to guide the analysis of macro-scale characteristics. The exploration of the effectiveness of cementation patterns in fluid sealing provides valuable insights into effective biocementation at the pore scale of porous media, which may inspire future research.

Association between exposure to a mixture of organochlorine pesticides and hyperuricemia in U.S. adults: A comparison of four statistical models

The association between the exposure of organochlorine pesticides (OCPs) and serum uric acid (UA) levels remained uncertain. In this study, to investigate the combined effects of OCP mixtures on hyperuricemia, we analyzed serum OCPs and UA levels in adults from the National Health and Nutrition Examination Survey (2005–2016). Four statistical models including weighted logistic regression, weighted quantile sum (WQS), quantile g-computation (QGC), and bayesian kernel machine regression (BKMR) were used to assess the relationship between mixed chemical exposures and hyperuricemia. Subgroup analyses were conducted to explore potential modifiers. Among 6,529 participants, the prevalence of hyperuricemia was 21.15%. Logistic regression revealed a significant association between both hexachlorobenzene (HCB) and trans-nonachlor and hyperuricemia in the fifth quintile (OR: 1.54, 95% CI: 1.08–2.19; OR: 1.58, 95% CI: 1.05–2.39, respectively), utilizing the first quintile as a reference. WQS and QGC analyses showed significant overall effects of OCPs on hyperuricemia, with an OR of 1.25 (95% CI: 1.09–1.44) and 1.20 (95% CI: 1.06–1.37), respectively. BKMR indicated a positive trend between mixed OCPs and hyperuricemia, with HCB having the largest weight in all three mixture analyses. Subgroup analyses revealed that females, individuals aged 50 years and above, and those with a low income were more vulnerable to mixed OCP exposure. These results highlight the urgent need to protect vulnerable populations from OCPs and to properly evaluate the health effects of multiple exposures on hyperuricemia using mutual validation approaches.

Revisiting testimonio as critical race feminista methodology in educational research

This study is a review of educational scholarship that has utilized testimonio as a methodological approach. We begin with a brief overview of testimonio, highlighting its discursive subversions that align with longstanding traditions of storytelling within Communities of Color, and in critical race storytelling. We then describe how testimonio is an important tool within a broader Critical Race Feminista Methodology—a space of theorizing humanizing, anti-colonial methodological approaches that disrupt structural oppression and are guided by “a nostalgia for wholeness” (Delgado Bernal, Pérez Huber, & Malagon, 2019). Testimonio as a Critical Race Feminista Methodology allows for an interweaving of Chicana feminist and critical race epistemological and theoretical tools with qualitative research methods to cultivate methodological space for convivencia, critical reflection, collective knowledge production, and healing. Through this literature review, we see how this methodology brings mutual validation, shared humanity, and imperatives of social justice to the fore, shifting our research praxis from one that reproduces the colonial project, to one that seeks to transform and lead to collective well-being.

Resolving inter-crystal scatter in a light-sharing depth-encoding PET detector

Objective. Inter-crystal scattering (ICS) in light-sharing positron emission tomography (PET) detectors leads to ambiguity in positioning the initial interaction, which significantly degrades the contrast, quantitative accuracy, and spatial resolution of the resulting image. Here, we attempt to resolve the positioning ambiguity of ICS in a light-sharing depth-encoding detector by exploiting the confined, deterministic light-sharing enabled by the segmented light guide unique to Prism-PET. Approach. We first considered a test case of ICS between two adjacent crystals using an analytical and a neural network approach. The analytical approach used a Bayesian estimation framework constructed from a scatter absorption model—the prior—and a detector response model—the likelihood. A simple neural network was generated for the same scenario, to provide mutual validation for the findings. Finally, we generalized the solution to three-dimensional event positioning that handles all events in the photopeak using a convolutional neural network with unique architecture that separately predicts the identity and depth-of-interaction (DOI) of the crystal containing the first interaction. Main results. The analytical Bayesian method generated an estimation error of 20.5 keV in energy and 3.1 mm in DOI. Further analysis showed that the detector response model was sufficiently robust to achieve adequate performance via maximum likelihood estimation (MLE), without prior information. We then found convergent results using a simple neural network. In the generalized solution using a convolutional neural network, we found crystal identification accuracy of 83% and DOI estimation error of 3.0 mm across all events. Applying this positioning algorithm to simulated data, we demonstrated significant improvements in image quality over the baseline, centroid-based positioning approach, attaining 38.9% improvement in intrinsic spatial resolution and enhanced clarity in hot spots of diameters 0.8 to 2.5 mm. Significance. The accuracy of our findings exceeds those of previous reports in the literature. The Prism-PET light guide, mediating confined and deterministic light-sharing, plays a key role in ICS recovery, as its mathematical embodiment—the detector response model—was the essential driver of accuracy in our results.

Multipath-Closure Calibration of Stereo Camera and 3D LiDAR Combined with Multiple Constraints

Stereo cameras can capture the rich image textures of a scene, while LiDAR can obtain accurate 3D coordinates of point clouds of a scene. They complement each other and can achieve comprehensive and accurate environment perception through data fusion. The primary step in data fusion is to establish the relative positional relationship between the stereo cameras and the 3D LiDAR, known as extrinsic calibration. Existing methods establish the camera–LiDAR relationship by constraints of the correspondence between different planes in the images and point clouds. However, these methods depend on the planes and ignore the multipath-closure constraint among the camera–LiDAR–camera sensors, resulting in poor robustness and accuracy of the extrinsic calibration. This paper proposes a trihedron as the calibration object to effectively establish various coplanar and collinear constraints between stereo cameras and 3D LiDAR. With the various constraints, the multipath-closure constraint between the three sensors is further formulated for the extrinsic calibration. Firstly, the coplanar and collinear constraints between the camera–LiDAR–camera are built using the trihedron calibration object. Then, robust and accurate coplanar constraint information is extracted through iterative maximum a posteriori (MAP) estimation. Finally, a multipath-closure extrinsic calibration method for multi-sensor systems is developed with structurally mutual validation between the cameras and the LiDAR. Extensive experiments are conducted on simulation data with different noise levels and a large amount of real data to validate the accuracy and robustness of the proposed calibration algorithm.

Review of the hyperfine structure theory of hydrogen molecular ions

The study of high-precision spectroscopy for hydrogen molecular ions enables the determination of fundamental constants, such as the proton-to-electron mass ratio, the deuteron-to-electron mass ratio, the Rydberg constant, and the charge radii of proton and deuteron. This can be accomplished through a combination of high precision experimental measurements and theoretical calculations. The spectroscopy of hydrogen molecular ions reveals abundant hyperfine splittings, necessitating not only an understanding of rovibrational transition frequencies but also a thorough grasp of hyperfine structure theory to extract meaningful physical information from the spectra. This article reviews the history of experiments and theories related to the spectroscopy of hydrogen molecular ions, with a particular focus on the theory of hyperfine structure. As far back as the second half of the last century, the hyperfine structure of hydrogen molecular ions was described by a comprehensive theory based on its leading-order term, known as the Breit-Pauli Hamiltonian. Thanks to the advancements in non-relativistic quantum electrodynamics (NRQED) at the beginning of this century, a systematic development of next-to-leading-order theory for hyperfine structure has been achieved and applied to &lt;inline-formula&gt;&lt;tex-math id="M8"&gt;\begin{document}$\text{H}_2^+$\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; and &lt;inline-formula&gt;&lt;tex-math id="M9"&gt;\begin{document}$\text{HD}^+$\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; in recent years, including the establishment of the &lt;inline-formula&gt;&lt;tex-math id="M10"&gt;\begin{document}$m\alpha^7\ln(\alpha)$\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; order correction. For the hyperfine structure of &lt;inline-formula&gt;&lt;tex-math id="M11"&gt;\begin{document}$\text{H}_2^+$\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt;, theoretical calculations show good agreement with experimental measurements after decades of work. However, for HD&lt;sup&gt;+&lt;/sup&gt;, discrepancies have been observed between measurements and theoretical predictions that cannot be accounted for by the theoretical uncertainty in the non-logarithmic term of the &lt;inline-formula&gt;&lt;tex-math id="M13"&gt;\begin{document}$m\alpha^7$\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; order correction. To address this issue, additional experimental measurements are needed for mutual validation, as well as independent tests of the theory, particularly regarding the non-logarithmic term of the &lt;inline-formula&gt;&lt;tex-math id="M14"&gt;\begin{document}$m\alpha^7$\end{document}&lt;/tex-math&gt;&lt;/inline-formula&gt; order correction.

Optimizing the KNN Algorithm to Diagnose Obstructive Pulmonary Diseases

Introduction: According to the World Health Organization, lung diseases are the third cause of death in the world. These diseases are chronic, so early diagnosis of these diseases is very important. Pulmonary function tests are important tools in examining and monitoring patients with respiratory injuries. This research aimed to optimize the K -Nearest Neighbor algorithm, which facilitates and accelerates self-assessment and interpretation of spirometry test results with higher accuracy. Method: In this study, a method is proposed that improves the limitations of the basic algorithm by optimizing, valuing features, and weighted voting. Using this method, obstructive pulmonary diseases are detected based on the data set of spirometry tests, and general parameters are classified into three categories, namely, asthma, chronic bronchitis, and emphysema. Results: In determining the appropriate method for calculating the data distance, the Minkowski method was chosen, and by applying the coefficients of the feature values, the accuracy of the classification increased. Weighted voting was done in the final part of the algorithm based on the Gaussian kernel, based on which a constant performance was obtained for changing the parameter of the number of neighbors. The results of the evaluations were carried out in the form of mutual validation. 95.4% accuracy and 93.2% precision were obtained in 3.12 seconds. Conclusion: The use of machine learning algorithms can be effective in the analysis of medical data. Therefore, in this study, these approaches were used to provide a new method of classification, so that the proposed algorithm could improve the basic method, and also, had better accuracy and performance than other previous methods.

유아교사의 디지털 리터러시 역량 모형 개발

Objectives This study aims to develop a model of digital literacy competencies for teachers in early childhood.&#x0D; Methods To this end, literature review, 3 rounds of delphi surveys were conducted. The research team and an expert advisory committee executed mutual validation at the end of each delphi survey to ensure objectivity and validity.&#x0D; Results As a result of this study, a digital literacy competency model for teachers in early childhood was derived, consisting of four main competencies and nine sub-competencies. The main competencies include digital cit-izenship consciousness, digital thinking competency, digital utilization and creation competency, and digital teaching competency. The sub-competencies for digital citizenship consciousness include compliance with digi-tal norms and digital responsibility consciousness, while sub-competencies for digital thinking competency in-clude digital critical thinking and problem-solving abilities. The sub-competencies for digital utilization and crea-tion competency include digital technology utilization and digital creation abilities. Finally, the sub-competencies for digital teaching competency include digital teaching design ability, digital teaching execution ability, and digital teaching reflection ability.&#x0D; Conclusions Based on the results of this study, it is expected that an education and training system can be estab-lished to cultivate digital literacy competencies that teachers in early childhood must possess in the educational field of the digital era.

Performance evaluation on full-scale proton exchange membrane fuel cell: Mutual validation of one-dimensional, three-dimensional and experimental investigations

The coupling of multiple physical processes such as gas multi-component transport, gas–liquid multiphase flow, and electrochemical reactions within the proton exchange membrane fuel cell (PEMFC) makes its hydrothermal management exceptionally complicated. Therefore, the complex heat and mass transfer processes in the full-scale PEMFC are investigated in single cell with single channel serpentine flow field (FF). Firstly, the reliability of the proposed three-dimensional (3D) computational fluid dynamics (CFD) numerical model is verified by using the experimental test results of a single cell. Among them, the trend of simulation and experiment performance curves is consistent, and the minimum error of current density is 0.665%. Secondly, the ionomer model of cathode catalyst layer (CCL) is considered in CFD simulation, which is closer to the actual working condition of fuel cell (FC). The resistance of ionomer film and liquid water film mainly affects the diffusion rate of oxygen in CCL, resulting in a decrease in both current density values and power density values. Subsequently, the electrochemical reaction platform of one-dimensional (1D) FC is constructed, and the performance curves of multi-scale FCs are analyzed. The results demonstrate that the error of stack level is the largest, followed by single cell and single channel is the smallest. Finally, the 1D numerical model and the 3D PEMFC multiphase flow CFD model are utilized to investigate the cell voltage losses in the bionic spider flow field, the variable path flow field, and the serpentine flow field, respectively, under different operating conditions.

Resection of the primary tumor improves the prognosis of gastrointestinal neuroendocrine neoplasms with liver metastases: mutual validation based on SEER database and institutional data

BackgroundGastrointestinal Neuroendocrine Neoplasms (GI-NENs) often result in liver metastases, and the role of Primary Tumor Resection (PTR) in managing GI-NENs with liver metastases (GI-NENLM) is still debated. This study aimed to investigate the potential benefits of PTR in treating GI-NENLM by analyzing data from the Surveillance, Epidemiology, and End Results Program (SEER) and the First Affiliated Hospital of Sun Yat-sen University (FAH).MethodsThe SEER Registry 17 database and the FAH clinical pathology database were used to collect clinicopathology data for GI-NENLM diagnosed between 2010 and 2019 and between 2011 and 2022, respectively. Propensity score matching (PSM) was used to match the clinicopathological characteristics of patients from both cohorts. Inverse probability weighting (IPTW) was used to weigh the PTR and non-PTR groups. The primary endpoint was overall survival (OS).ResultsAfter matching, 155 patients from the SEER database were matched to the FAH cohort. PTR was significantly associated with better prognosis in PSM-matched/unmatched SEER cohorts (P < 0.01) and in the FAH cohort even after eliminating selection bias using IPTW (p < 0.01). Subgroup analysis suggests that the cohort consisting of patients aged 55 years or older, individuals with colorectal primary tumors, those at the T1 disease stage, and those without extrahepatic metastasis may potentially benefit from PTR. Interaction analysis showed no significant interaction between PTR and other clinical and pathological factors except for age.ConclusionThe employment of PTR in patients with GI-NENLM is significantly correlated with individual survival benefits. We support performing PTR on carefully evaluated patients.

Monitoring of winter wheat stripe rust by collaborating canopy SIF with wavelet energy coefficients

Stripe rust has caused tremendous damage to wheat quality and production. Disease-specific factors revealing group structure and photosynthetic physiology contribute to high-precision monitoring for wheat stripe rust. In this study, we proposed a remote sensing model that collaborates wavelet features (WFs) and solar-induced chlorophyll fluorescence (SIF). First, sensitive features including vegetation indices (VIs), SIF parameters, WFs, and fractional-order derivative spectra (FODs) were screened based on correlation coefficient (CC) analysis and variable importance in projection (VIP). Then, through collaboration among features, six feature sets were received and imported to partial least squares regression (PLSR), back-propagation neural network (BPNN), random forest (RF), and extreme gradient boosting (XGBoost). Finally, monitoring models was evaluated through two methods: holdout cross-validation and 5-fold cross validation to ascertain the optimal feature-algorithm combination. The results demonstrated that the collaboration of canopy SIF with any feature markedly improved the monitoring accuracy due to its responsive nature to the plant's photosynthetic physiology. The model based on XGBoost with WFs-SIF as input features achieved optimal monitoring accuracy, with at least 16.6% increase in R2 and 32.4% reduction in RMSE compared to the VIs-PLSR model. Correlation analysis of evaluation indexes (R2 and RMSE) under two cross-validation methods showed determination coefficients of 0.743 and 0.837, indicating mutual validation and high reliability of the conclusions. This study suggests that the collaboration between WFs and SIF exhibits considerable feasibility in high-precision monitoring of stripe rust, providing a novel insight for future field-scale diagnosis of crop diseases.