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Aiming at the problem of imprecise reputation evaluation caused by too much subjective and qualitative evaluation of the traditional reputation evaluation model in data transactions, An Evaluation Entity-Based Reputation Evaluation model (EEBRE) is proposed. In order to realize multi-dimensional reputation evaluation, the structure of the evaluation entity is proposed to dynamically obtain the reputation data of the trading parties; a reputation evaluation assembly method combining objective indicators and feedback rating indicators is proposed, which replaces the qualitative scoring of data set quality indicators with quantitative scoring, introduces the static individual information indicators as well as transaction context attribute indicators, such as transaction amount, time, etc., and retains the qualitative evaluation of the feedback ratings to provide an interactive experience feedback pathway for the data requesting party. The experimental results show that the EEBRE model proposed in this paper can safely and effectively evaluate the seller's reputation. [ABSTRACT FROM AUTHOR]

1D NOESY with presaturation (NOESY-presat) is the most popular water suppression method. When D2O solutions of L-phenylalanine or L-valine were measured using NOESY, the absolute concentration biases increased with longer mixing and evolution times, reaching a maximum of 54% with respect to the preparation values. At mixing and evolution times of 0 ms and 0 µs, respectively, the absolute concentration biases were reduced to less than 3%. The remaining biases were caused by the off-resonance effect, which was prevented by setting the frequency offset to an intermediate value between the analyte and internal standard 3-(trimethylsilyl)-1-propanesulfonic acid-d6 (DSS-d6) signals. Nevertheless, NOESY-presat gave maximum absolute biases of 26% and 11% for glycine and maleic acid concentrations, respectively, in three H2O/D2O (90/10 vol%) solutions. The proposed NOESY-dual-presat method reduced the absolute biases to below 4%. However, water suppression was insufficient but was improved by setting the frequency offset to the same as the presaturation offset with the H2O signal, although the absolute biases rose to 5 to 13%. Quantitative analyses using NOESY-presat and NOESY-dual-presat require careful consideration of the off-resonance effect. [ABSTRACT FROM AUTHOR]

Visual scoring of interstitial lung disease in systemic sclerosis (SSc-ILD) from CT scans is laborious, subjective and time-consuming. This study aims to develop a deep learning framework to automate SSc-ILD scoring. The automated framework is a cascade of two neural networks. The first network selects the craniocaudal positions of the five scoring levels. Subsequently, for each level, the second network estimates the ratio of three patterns to the total lung area: the total extent of disease (TOT), ground glass (GG) and reticulation (RET). To overcome the score imbalance in the second network, we propose a method to augment the training dataset with synthetic data. To explain the network's output, a heat map method is introduced to highlight the candidate interstitial lung disease regions. The explainability of heat maps was evaluated by two human experts and a quantitative method that uses the heat map to produce the score. The results show that our framework achieved a κ of 0.66, 0.58, and 0.65, for the TOT, GG and RET scoring, respectively. Both experts agreed with the heat maps in 91%, 90% and 80% of cases, respectively. Therefore, it is feasible to develop a framework for automated SSc-ILD scoring, which performs competitively with human experts and provides high-quality explanations using heat maps. Confirming the model's generalizability is needed in future studies. [ABSTRACT FROM AUTHOR]

The 2030 Agenda for Sustainable Development issued by the United Nations is an important foundation for countries to achieve common economic, social and environmental development. Important progress has been made in the evaluation of the Sustainable Development Goals (SDGs) in Hainan Island; nevertheless, there is still a lack of understanding around the trade-offs and synergies between the SDGs. Studying the trade-offs and synergies between Hainan Island's sustainable development goals is of great significance for the coordinated development of these goals and the promotion of the construction of free trade ports. Therefore, based on the United Nations Sustainable Development Assessment System and the existing SDG indicator system on Hainan Island, this paper identifies and quantifies the trade-offs and synergies within and between SDGs and targets on the county scale. Based on the different impacts of different spatial, dimensional and geographical directions, the results show the following: (1) Hainan Province made good progress on multiple SDGs between 2010 and 2021. (2) The most significant synergies between SDGs exist between SDG1 (No Poverty) and SDG10 (Reduce Inequalities), while the most significant trade-offs exist between SDG2 (Zero Hunger) and SDG4 (Quality Education). (3) Obvious spatial characteristics in trade-offs and synergies exist, with the highest level of synergy being in the Haikou and Sanya Economic Circles and their surrounding areas, and in the central region of Hainan Island which has a higher level of trade-offs. (4) The synergistic effect between the SDG targets and indicators in Hainan is much greater than the trade-off effect: the four aspects of people's livelihood improvement, economic development, resource utilization and environmental quality all show synergistic effects in different regions. [ABSTRACT FROM AUTHOR]

Purpose: Total-body dynamic positron emission tomography (PET) imaging with total-body coverage and ultrahigh sensitivity has played an important role in accurate tracer kinetic analyses in physiology, biochemistry, and pharmacology. However, dynamic PET scans typically entail prolonged durations ( 60 minutes), potentially causing patient discomfort and resulting in artifacts in the final images. Therefore, we propose a dynamic frame prediction method for total-body PET imaging via deep learning technology to reduce the required scanning time. Methods: On the basis of total-body dynamic PET data acquired from 13 subjects who received [68Ga]Ga-FAPI-04 (68Ga-FAPI) and 24 subjects who received [68Ga]Ga-PSMA-11 (68Ga-PSMA), we propose a bidirectional dynamic frame prediction network that uses the initial and final 10 min of PET imaging data (frames 1–6 and frames 25–30, respectively) as inputs. The peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM) were employed as evaluation metrics for an image quality assessment. Moreover, we calculated parametric images (68Ga-FAPI: , 68Ga-PSMA: ) based on the supplemented sequence data to observe the quantitative accuracy of our approach. Regions of interest (ROIs) and statistical analyses were utilized to evaluate the performance of the model. Results: Both the visual and quantitative results illustrate the effectiveness of our approach. The generated dynamic PET images yielded PSNRs of 36.056 ± 0.709 dB for the 68Ga-PSMA group and 33.779 ± 0.760 dB for the 68Ga-FAPI group. Additionally, the SSIM reached 0.935 ± 0.006 for the 68Ga-FAPI group and 0.922 ± 0.009 for the 68Ga-PSMA group. By conducting a quantitative analysis on the parametric images, we obtained PSNRs of 36.155 ± 4.813 dB (68Ga-PSMA, ) and 43.150 ± 4.102 dB (68Ga-FAPI, ). The obtained SSIM values were 0.932 ± 0.041 (68Ga-PSMA) and 0.980 ± 0.011 (68Ga-FAPI). The ROI analysis conducted on our generated dynamic PET sequences also revealed that our method can accurately predict temporal voxel intensity changes, maintaining overall visual consistency with the ground truth. Conclusion: In this work, we propose a bidirectional dynamic frame prediction network for total-body 68Ga-PSMA and 68Ga-FAPI PET imaging with a reduced scan duration. Visual and quantitative analyses demonstrated that our approach performed well when it was used to predict one-hour dynamic PET images. https://github.com/OPMZZZ/BDF-NET. [ABSTRACT FROM AUTHOR]

Introduction: Many surgical fellowship programs incorporate robotic surgery, yet not all residency programs offer robotic training for residents. Given the variability of pre-fellowship robotic exposure, the goal of this study was to explore whether standardized robotic skills assessment would be useful to fellows at the start of their training. Methods: In partnership with the Fellowship Council, we surveyed current fellows of accredited Thoracic, Colorectal, HPB, and Advanced GI/MIS/Bariatrics/Foregut Fellowship programs. Main outcome measurements included amount of robotic exposure during residency, fellows' robotic skills at the start of fellowship, and fellows' attitudes towards a standardized skills assessment. Results: In total, 78 fellows completed the survey. Mean percentage of cases performed robotically during fellowship was 38.1% (SD ± 32.25%). From our respondents, 46% had no robotic curriculum during residency and 86.9% felt a standardized robotic curriculum during residency would have been beneficial. When asked if they started fellowship with adequate robotic skills to operate autonomously, 31% strongly agreed, but 24.4% strongly disagreed. The majority of fellows reported their fellowship program did not conduct an assessment of their robotic skills (71.5%), or provide a specific robotic curriculum (75.6%). On the other hand, 73.3% felt a formal proficiency assessment at the start of fellowship would be helpful for individualized support and training. Conclusions: Given the significant variability in resident exposure to robotic surgery, a standardized robotic curriculum during residency would likely be beneficial. Additionally, a robotic skills assessment at the start of fellowship could help provide a tailored training experience for fellows interested in this skillset. [ABSTRACT FROM AUTHOR]

Introduction: Endoscopy is an essential skill for all surgeons. However, endoscopic competency, training, and practice may vary widely among them. The EAES Flexible Endoscopy Subcommittee is working towards a standardized set of fundamental endoscopic knowledge and skills. To best advise on current practice patterns of flexible endoscopy among surgeons worldwide, a snapshot audit was conducted on the training, use, and limitations of flexible endoscopy in practice. Methods: An online survey was distributed via email distribution and social media platforms for EAES, SAGES, and WebSurg members. Respondent demographics, training, and practice patterns were assessed. The main outcome measure was the annual endoscopic volume. Multivariate regression and machine learning models analyzed relationships between outcomes and independent variables of age, geographic region, laparoscopic surgery practice, and surgical specialization. Results: A total of 1486 surgeons from 195 countries completed the survey. Respondents were mainly general (n = 894/1486, 60.2%), colorectal (n = 189/1486, 12.7%), bariatric (n = 117/1486, 7.9%), upper gastrointestinal (GI)/foregut (n = 108, 7.3%), hepatobiliopancreatic/HPB (n = 59/1486, 4%), and endocrine surgeons (n = 11/1486, 0.7%) in active practice. Eighty-two percent (n = 1,204) mentioned having used endoscopy in their practice, and 64.7% (n = 961/1486) received formal flexible endoscopy training. Of those performing endoscopy annually, 64.2% (n = 660/1486) performed between 0 and 20 endoscopies, 15.2% (n = 156/1486) performed between 20 and 50 endoscopies, 10.1% (n = 104/1486) performed between 50 and 100 endoscopies, and 10.5% (n = 108/1486) performed over 100 endoscopies. From the regression analysis, there was no statistical correlation between the annual endoscopy volume and age, geographic region, laparoscopic surgery practice, or surgical specialization. Performing advanced endoscopy was directly related to the bariatric subspecialty and to performing over 50% of cases in a minimally invasive fashion. Conclusions: This international snapshot audit revealed significant heterogeneity in endoscopic practices among surgeons worldwide. There was a nonindependent relationship between endoscopy volumes and other variables tested. Barriers to practicing and receiving endoscopy training were common among respondents. The EAES Flexible Endoscopy Subcommittee will consider such results when developing an equitable and effective standardized flexible endoscopy curriculum. [ABSTRACT FROM AUTHOR]

To challenge "objective" conventions in quantitative methodology, higher education scholars have increasingly employed critical lenses (e.g., quantitative criticalism, QuantCrit). Yet, specific approaches remain opaque. We use a multimethod design to examine researchers' use of critical approaches and explore how authors discussed embedding strategies to disrupt dominant quantitative thinking. We draw data from a systematic scoping review of critical quantitative higher education research between 2007 and 2021 (N = 34) and semi-structured interviews with 18 manuscript authors. Findings illuminate (in)consistencies across scholars' incorporation of critical approaches, including within study motivations, theoretical framing, and methodological choices. Additionally, interview data reveal complex layers to authors' decision-making processes, indicating that decisions about embracing critical quantitative approaches must be asset-based and intentional. Lastly, we discuss findings in the context of their guiding frameworks (e.g., quantitative criticalism, QuantCrit) and offer implications for employing and conducting research about critical quantitative research. [ABSTRACT FROM AUTHOR]

Borehole destressing is one of the most widely used techniques for mitigating coal bursts. Understanding the working principle of destressing boreholes, exploring the main efficiency factors, and proposing a quantitative method for determining the drilling parameters for coal burst control are essential for maximizing coal burst control. This study establishes a unified damage mechanics model of borehole bursts (that is, dynamic collapse in boreholes) and roadway coal bursts, deduces the critical indices of borehole bursts, and identifies the main factors. The theoretical relationship between the critical stresses of borehole burst and roadway coal burst is quantitatively explored, and a theoretical criterion for borehole effectiveness in coal burst control is proposed using the critical indices of borehole bursts. Finally, a design principle, determination method, and calculation formulae for the drilling parameters, which are directly related to the roadway burst risk state, coal seam thickness, coal properties, and drilling size, are proposed. The optimized drilling parameters of typical coal burst mines in Hebei and Inner Mongolia verify the engineering applicability and effectiveness of the proposed design method. This study proposes a quantitative determination method for destressing drilling parameters that supports coal burst occurrence theory. Highlights: Critical conditions for borehole bursts, directly related to the mechanical properties of coal and borehole size, are theoretically provided. Theoretical relationship between boreholes and roadway coal bursts is explored. Quantitative description of the borehole destressing principle to mitigate coal burst is provided. Theoretical criterion for boreholes to mitigate coal bursts, which is directly related to the critical conditions of borehole bursts, is provided. Quantitative method for determining the drilling parameters to mitigate coal bursts is proposed. [ABSTRACT FROM AUTHOR]

As human–machine interaction (HMI) technology advances, new interaction modes such as gesture and touch interactions are increasingly integrated into manufacturing facilities. These modern methods present unique benefits and drawbacks compared to traditional button interaction. Yet, there is a notable absence of a comprehensive quantitative evaluation method for selecting device interaction modes. This paper introduces a systematic approach to address this gap. Firstly, a multi-criteria evaluation system is established based on commonly used evaluation metrics for human–machine teams. We then employ a hybrid multi-criteria decision-making (HMCDM) method that combines subjective weighting from the rank correlation analysis (G1) method with the VIKOR method. This method provides a clear decision ordering for various interaction modes. When applied to evaluate three interaction modes in an assembly facility, our results suggest that button interaction is the most effective, scoring S(0.115), R(0.046), and Q(0.000). This finding aligns with results from other HMCDM methods, validating the reliability of the proposed HMCDM approach. Our method serves as a reliable guide for operators in choosing interaction modes and offers designers a foundation for further optimization. [ABSTRACT FROM AUTHOR]

In this paper, we study several tighter uncertainty principles (UPs) for the non-isotropic angular Stockwell transform (NAST). By employing the polar coordinate representation of signal functions, we establish the tighter Heisenberg-Weyl UPs in spatial and directional settings, the tighter concentration Heisenberg-Weyl UP of position and scale concentration, as well as the tighter local-type Heisenberg-Weyl UP for the NAST. Quantitative and qualitative analysis indicates that our results give rise to a new understanding for the NAST with more precise lower bounds so as to offer more valuable insights for signal processing and image analysis. [ABSTRACT FROM AUTHOR]

The reliability of interconnection networks ordinarily is measured by all kinds of connectivities. The qualitative and quantitative analysis relies on the assumptions consistent with the actual situation. Structure connectivity and substructure connectivity are key indicators to assess network reliability and fault tolerance. In this paper, we first determine the K 1 , r -structure connectivity and K 1 , r -substructure connectivity of half hypercube H H n for 1 ≤ r ≤ ⌊ n 2 ⌋ - 2 . Then, we characterize the minimum K 1 , r -cuts and the minimum sub- K 1 , r -cuts of H H n . Specifically, when n is even, half hypercube H H n is isomorphic to hierarchical cubic network H C N n 2 , then our results on H H n can be directly applied to H C N n 2 . [ABSTRACT FROM AUTHOR]

In this modern era, the security and safety of financial and personal digital data are crucial considerations. Blockchain technology offers a secure framework for the transmission of data between devices, without the interference of malicious actors. With the growing demand for this technology, it has become essential to evaluate the impact of its processes on system characteristics to forecast transactions behavior and ensure necessary quality indicators, as well as the stability of system components while the blockchain technology is in operation. Queueing models are a highly effective mathematical tool for analyzing and optimizing the performance of blockchain systems. In this study, a more generic queueing model is utilized to evaluate a blockchain application. The transactions arrive in batches according to a Markovian arrival process, and the service times for the block-generation (the first stage) and blockchain-building (the second stage) follow phase-type distributions. Using matrix-analytic method, we study the model in steady-state. The stationary distribution and the stability condition of the system have been derived. Further, by determining key system performance measures, illustrative numerical examples covering a wide range of batch size and service time distributions have been discussed. In conclusion, our hope is that the methodology and findings presented in this paper will pave the way for the queueing analysis of more extensive and diverse blockchain systems in practice. Furthermore, we believe that it will inspire a series of promising future quantitative and qualitative studies aimed at the development of blockchain technologies. [ABSTRACT FROM AUTHOR]

Time series classification is a task which deals with temporal sequences, a prevalent data type common in domains such as human activity recognition, sports analytics and general sensing. In this area, interest in explanability has been growing as explanation is key to understand the data and the model better. Recently, a great variety of techniques (e.g., LIME, SHAP, CAM) have been proposed and adapted for time series to provide explanation in the form of saliency maps, where the importance of each data point in the time series is quantified with a numerical value. However, the saliency maps can and often disagree, so it is unclear which one to use. This paper provides a novel framework to quantitatively evaluate and rank explanation methods for time series classification. We show how to robustly evaluate the informativeness of a given explanation method (i.e., relevance for the classification task), and how to compare explanations side-by-side. The goal is to recommend the best explainer for a given time series classification dataset. We propose AMEE, a Model-Agnostic Explanation Evaluation framework, for recommending saliency-based explanations for time series classification. In this approach, data perturbation is added to the input time series guided by each explanation. Our results show that perturbing discriminative parts of the time series leads to significant changes in classification accuracy, which can be used to evaluate each explanation. To be robust to different types of perturbations and different types of classifiers, we aggregate the accuracy loss across perturbations and classifiers. This novel approach allows us to recommend the best explainer among a set of different explainers, including random and oracle explainers. We provide a quantitative and qualitative analysis for synthetic datasets, a variety of time-series datasets, as well as a real-world case study with known expert ground truth. [ABSTRACT FROM AUTHOR]

The real contact area (RCA) of randomly rough contacts has received a great deal of attention because it correlates strongly with friction, lubrication, sealing, and conductivity. Simulations have revealed that the RCA associated with deterministic normal squeezing loads increases when tangential loads are also applied, in a phenomenon called junction growth. However, experimental investigations of the junction growth of randomly rough contacts are rare. Here, we used X-ray computed tomography (CT) to measure junction growth when two aluminum alloy surfaces were in contact. A high-resolution experimental setup was used to apply loads and observe contact behaviors at a resolution of 4 µm. The RCA and average contact gaps were computed using a three-dimensional (3D) geometric model constructed from gray CT images using the Otsu thresholding method. The results showed that the RCA increased as the normal load increased. The RCA increased by 22.67% after a tangential load was applied (junction growth), and the average gap decreased by 14.01% after a tangential load was applied. Thus, X-ray CT accurately measured the junction growth as a novel quantitative method. [ABSTRACT FROM AUTHOR]

Experiencing adverse childhood experiences (ACEs) may impact personal opinions, attitudes, and judgments, which can further result in HIV-related stigma. HIV-related stigma consequentially may impact HIV preventive measures such as HIV testing, pre-exposure prophylaxis uptake, and condom use. The extent to which ACEs influence HIV-related stigma perception has not been well studied. Therefore, the study aimed to examine the association between ACEs and perceived and interpersonal HIV-related stigma among Tanzanian HIV-negative men. Quantitative survey data were obtained from the Tanzania STEP (Self-Testing Education and Promotion) project established in four wards: Mabibo, Manzese, Tandale, and Mwanyanamala. A total of 507 men responded to the ACEs and HIV-related stigma questionnaires. ACEs were operationalized as types of ACEs (environmental, physical/psychological, sexual abuse) and ACE score (0 (reference) vs. 1, 2, 3, ≥ 4). Perceived HIV-related stigma was analyzed both as a binary (HIV stigma vs. no HIV stigma) and a continuous variable. Unadjusted and adjusted multinomial logistic and linear regression models were used to assess the associations between ACEs and HIV-related stigma. ACE types were associated with HIV stigma (b = 0.237, 95% CI [0.122–0.352], p = <.0001). Findings of the adjusted multinomial logistic regression model show that experiencing one ACE (aOR = 1.9; p-value = 0.023), two ACEs (aOR = 1.8; p-value = 0.044), four or more ACEs (aOR = 4.1; p-value = < 0.0001) were associated with greater perceived HIV-related stigma. Moreover, experiencing environmental (aOR = 8.6; p-value = 0.005), physical/psychological (aOR = 2.5; p-value = 0.004), and sexual abuse (aOR = 3.4; p-value = < 0.0001) were associated with higher odds of HIV-related stigma. Our study findings suggest that those who experience childhood trauma are more likely to have a higher perception of HIV-related stigma. Intervention programs targeting HIV stigma should consider addressing ACEs entailing the behavioral and psychological impact of childhood trauma. [ABSTRACT FROM AUTHOR]

Background: Endpoints that patients and clinicians consider important may differ based on patients' preferences and values. Several methods are available to elicit patient preferences in a succinct and methodologically valid manner. Purpose: We conducted a scoping review of methods used to elicit patient preferences in invasive procedures to provide a framework for researchers and clinicians to incorporate these measures into future efforts. Methods: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and health and psychological instruments database were searched from inception until September 2020. Articles that examined patient preferences for any invasive procedure were eligible for inclusion. Selection and extraction were completed in duplicate. Preference elicitation methods were identified and summarized. Results: Three hundred ninety-four articles (n = 76,921 patients) were included representing several surgical specialties. Of included studies, 11.7% (n = 46) used both quantitative and qualitative methods, 81.2% (n = 320) used quantitative methods only, and 7.1% (n = 28) used qualitative methods only to elicit preferences. The most frequently employed quantitative method to elicit preferences was simple choice selection, while one-on-one interviews with participants was the most frequently used qualitative method. Preference elicitation was the primary outcome in 74.6% (n = 294) of included studies. Conclusion: There are several methods to elicit patient preferences in surgical research. Qualitative methods are valuable for exploring views and generating consensus statements. Quantitative methods are better suited for assessing relative preferences, establishing preference thresholds, or ascertaining the presence of preferences. The choice of method should align with the specific research objectives. [ABSTRACT FROM AUTHOR]

The anomalous strange metal phase found in high-Tc cuprates does not follow the conventional condensed-matter principles enshrined in the Fermi liquid and presents a great challenge for theory. Highly precise experimental determination of the electronic self-energy can provide a test bed for theoretical models of strange metals, and angle-resolved photoemission can provide this as a function of frequency, momentum, temperature and doping. Here we show that constant energy cuts through the nodal spectral function in (Pb,Bi)2Sr2−xLaxCuO6+δ have a non-Lorentzian lineshape, consistent with a self-energy that is k dependent. This provides a new test for aspiring theories. Here we show that the experimental data are captured remarkably well by a power law with a k-dependent scaling exponent smoothly evolving with doping, a description that emerges naturally from anti-de Sitter/conformal-field-theory based semi-holography. This puts a spotlight on holographic methods for the quantitative modelling of strongly interacting quantum materials like the cuprate strange metals. Strange metal behaviour of high-Tc superconductors, characterised by unconventional electrical and thermodynamic properties, still poses challenges for theory. Smit et al. report experimental features in the self-energy of a strange metal that are consistent with predictions by holographic theoretical methods. [ABSTRACT FROM AUTHOR]

Deep convolutional neural networks (CNNs) have great improvements for single image super resolution (SISR). However, most of the existing SISR pre-training models can only reconstruct low-resolution (LR) images in a single image, and their upsamling factors cannot be non-integers, which limits their application in practical scenarios. In this letter, we propose a multi-scale cross-fusion network (MCNet) to accomplish the super-resolution task of images at arbitrary scale. On the one hand, the designed scale-wise module (SWM) combine the scale information and pixel features to fullly improve the representation ability of arbitrary-scale images. On the other hand, we construct a multi-scale cross-fusion module (MSCF) to enrich spatial information and remove redundant noise, which uses deep feature maps of different sizes for interactive learning. A large number of experiments on four benchmark datasets show that the proposed method can obtain better super-resolution results than existing arbitrary scale methods in both quantitative evaluation and visual comparison. [ABSTRACT FROM AUTHOR]

Childfreeness remains a largely unexplored subject in Poland. We provide insights into the scale of childlessness by choice and the motivations and characteristics of childfree people in the country. We conducted a quantitative study (national stratified random sample, n = 665, age 18–50 (M = 34.14, SD = 9.22), October 2021) and a qualitative exploration (n = 461, age 18–58 (M = 29.07, SD = 7.01), May 2020–January 2021). The quantitative analyses revealed that 14.89% of adult Poles of reproductive age did not have children and were not planning to have them. The decision not to have children was significantly predicted by lower age and left-wing political and liberal social beliefs. The qualitative analyses showed that the most common reasons for being childfree were lack of parental instinct (I do not feel the maternal instinct), not liking children (I cannot stand children) and desire for autonomy (I want to be independent). The results suggest that the Polish childfree population is substantial and diverse in their reasons for not wanting to have children. [ABSTRACT FROM AUTHOR]

Natural beauty evaluation is an important branch of geography and landscape studies and has profound impact on the protection and sustainable development of World Heritage sites (WHs). However, systematic literature reviews in this field are insufficient. In this study, we comprehensively analyzed 262 relevant studies in the Web of Science and CNKI databases published since 1982, systematically reviewed the research progress in the field of natural beauty evaluation, analyzed the current main research methods, theoretical frameworks, and application practices, and explored their specific implications for the World Heritage karst sites (WHKs). The following observations were made. (1) The number of publications has been increasing year by year, reaching its peak in 2019, indicating increasing research interest in this field. (2) The research content covers five aspects: theory, evaluation indicators, methods, technology, and World Heritage value. The proportion of research on technology integration (33.94%) and evaluation methods (28.05%) is the highest, accounting for 61.99% of the total, and indicating a positive inclination toward innovation and development of research methods. (3) Methodology tends toward interdisciplinary collaboration, and evaluation methods have gradually shifted from a single qualitative description to quantitative, diversified, and interdisciplinary comprehensive evaluation. The combination of traditional and emerging technologies such as SD method, SBE method, AHP method, neuroscience, and UGC data has increased, breaking through time and space constraints and expanding data sources. (4) In future studies, the assessment of natural beauty should concentrate on aesthetic preferences across diverse cultural contexts, develop a concept of global localization, and enhance evaluators' aesthetic perception through multisensory integration. Simultaneously utilizing UGC data to balance the authority of evaluation standards and the inclusiveness of evaluation systems, developing quantifiable indicators, and improving quantitative research in analogy methods; Finally, a karst landscape aesthetic evaluation model is constructed from both global and local perspectives, providing scientific reference for the formation of a unified evaluation system. [ABSTRACT FROM AUTHOR]

The success of deep learning (DL) relies heavily on training data from which DL models encapsulate information. Consequently, the development and deployment of DL models expose data to potential privacy breaches, which are particularly critical in data-sensitive contexts like medicine. We propose a new technique named DiffGuard that generates realistic and diverse synthetic medical images with annotations, even indistinguishable for experts, to replace real data for DL model training, which cuts off their direct connection and enhances privacy safety. We demonstrate that DiffGuard enhances privacy safety with much less data leakage and better resistance against privacy attacks on data and model. It also improves the accuracy and generalizability of DL models for segmentation and classification of mediastinal neoplasms in multi-center evaluation. We expect that our solution would enlighten the road to privacy-preserving DL for precision medicine, promote data and model sharing, and inspire more innovation on artificial-intelligence-generated-content technologies for medicine. [ABSTRACT FROM AUTHOR]

Background: This study investigates the integration of Artificial Intelligence (AI) in compensating the lack of time-of-flight (TOF) of the GE Omni Legend PET/CT, which utilizes BGO scintillation crystals. Methods: The current study evaluates the image quality of the GE Omni Legend PET/CT using a NEMA IQ phantom. It investigates the impact on imaging performance of various deep learning precision levels (low, medium, high) across different data acquisition durations. Quantitative analysis was performed using metrics such as contrast recovery coefficient (CRC), background variability (BV), and contrast to noise Ratio (CNR). Additionally, patient images reconstructed with various deep learning precision levels are presented to illustrate the impact on image quality. Results: The deep learning approach significantly reduced background variability, particularly for the smallest region of interest. We observed improvements in background variability of 11.8 % , 17.2 % , and 14.3 % for low, medium, and high precision deep learning, respectively. The results also indicate a significant improvement in larger spheres when considering both background variability and contrast recovery coefficient. The high precision deep learning approach proved advantageous for short scans and exhibited potential in improving detectability of small lesions. The exemplary patient study shows that the noise was suppressed for all deep learning cases, but low precision deep learning also reduced the lesion contrast (about −30 % ), while high precision deep learning increased the contrast (about 10 % ). Conclusion: This study conducted a thorough evaluation of deep learning algorithms in the GE Omni Legend PET/CT scanner, demonstrating that these methods enhance image quality, with notable improvements in CRC and CNR, thereby optimizing lesion detectability and offering opportunities to reduce image acquisition time. [ABSTRACT FROM AUTHOR]

Background: Gastric cancer stands as one of the most prevalent malignancies globally, conventional endoscopic specimens have been the primary means of diagnosing preoperative gastric histopathology, however, their limitations in capturing intra-tumor heterogeneity compromise their efficacy in evaluating angiogenesis. Perfusion Computed Tomography (P-CT) emerges as a pivotal functional imaging modality, facilitating objective assessment of tissue perfusion, serving as a marker of angiogenesis. So, our research objective was to evaluate the efficacy of CT perfusion imaging in the prediction of histological grades of gastric tumors using quantitative perfusion parameters such as permeability surface (PS), blood flow (BF), mean transient time (MTT), and blood volume (BV), in addition to the qualitative scoring system then comparing the findings with the histopathological results. Results: PS and BF were statistically significant predictors of the grade of differentiation, their odds ratio (OR) was (1.05, 95% CI 1.02–1.09, for each of them) (P = 0.004, P = 0.009, respectively). MTT also emerged as a significant predictor of the grade of differentiation with an OR of 0.76 (95% CI 0.57–0.93, P = 0.025). Using multivariate logistic regression model, PS was the most potent individual P-CT predictor of differentiation of the grade and the diagnosis of poorly differentiated tumors at ≥ 39 mL/100 g/min cut off point, followed by BF at ≥ 82.2 mL/100 g/min, and MTT at < 8.4 s. Regarding the qualitative scoring system P-CT, poorly differentiated tumors generally received higher scores of PS (P < 0.001), BF (P < 0.001), and BV (P = 0.017), than well and moderately differentiated tumors, however, MTT showed that poorly differentiated tumors were more frequently scored as low compared to well and moderately differentiated tumors (P < 0.001). Conclusions: P-CT is an innovative, non-invasive biomarker for predicting gastric cancer grade by quantitative and qualitative assessment by P-CT parameters (PS, BF and MTT) with particular role of PS as the strongest individual P-CT predictor of differentiation grade followed by BF and MTT at specific cut off points. [ABSTRACT FROM AUTHOR]

This study explores the enhancement of Internet of Things (IoT) product design and development through the integration of ethnography and big data analytics. A new model is proposed, recognizing the limitations of existing big data approaches in capturing nuanced and complex user needs. This model combines in-depth analysis of user attitudes with extensive review data from current IoT product users, aiming to uncover a more comprehensive understanding of the user experience beyond typical quantitative insights provided by big data. An IoT product named 'Zipband' has been developed as a practical application of this integrated research methodology. A combination of qualitative and quantitative research methods, including interviews and term frequency–inverse document frequency (TF-IDF) scheme analysis, was utilized to identify diverse user needs and uncover new opportunities for user experience improvement. This research contributes to the field by introducing a data-driven ethnographic approach that has the potential to inspire convergence research in IoT product design and user experience areas. [ABSTRACT FROM AUTHOR]

Environmental factors amplified by climate change contribute significantly to the global burden of disease, disproportionately impacting vulnerable populations, such as individuals with rare diseases. Researchers require innovative, dynamic data linkage methods to enable the development of risk prediction models, particularly for diseases like vasculitis with unknown aetiology but potential environmental triggers. In response, we present the Semantic Environmental and Rare Disease Data Integration Framework (SERDIF). SERDIF was evaluated with researchers studying climate-related health hazards of vasculitis disease activity across European countries (NP1 = 10, NP2 = 17, NP3 = 23). Usability metrics consistently improved, indicating SERDIF's effectiveness in linking complex environmental and health datasets. Furthermore, SERDIF-enabled epidemiologists to study environmental factors in a pregnancy cohort in Lombardy, showcasing its versatility beyond rare diseases. This framework offers for the first time a user-friendly, FAIR-compliant design for environment-health data linkage with export capabilities enabling data analysis to mitigate health risks posed by climate change. [ABSTRACT FROM AUTHOR]

Quantitative analyses of the species composition and abundance of benthic foraminifers in surface sediments along a submeridional profile in the northeastern East Siberian Sea have revealed three assemblages associated with the middle–outer shelf and upper and middle continental slope. The maximum abundance of "living" benthic foraminifers is found near the shelf break, which is possibly related to enhanced sea surface bioproductivity. Active dissolution of calcareous microfossils has been detected in the shelf area whereas preservation of calcareous tests becomes better with depth. Some micropaleontological and grain-size data indirectly point to the development of compensatory currents on the middle–outer shelf in the East Siberian Sea. [ABSTRACT FROM AUTHOR]

The main aim of this study was to evaluate the effectiveness of Pennsylvania's state-wide intensive in-home treatment for youth with serious emotional disturbance (SED), EcoSystemic Structural Family Therapy-Family Based Mental Health Services (ESFT-FBMHS). Despite its long history of implementation, the program remains empirically under-evaluated. In this archival study, out-of-home placement and youth functioning outcomes were compared across four tiers of length of stay. Given the high-risk population treated in ESFT-FBMHS, it was hypothesized that the families and youth who completed the full duration of treatment (169–224 days) would have better outcomes than those who stopped treatment after 168 days or less. We utilized an ex post facto quantitative research design analyzing archived medical claims data of 2251 youth treated between 2018 and 2022 to assess out-of-home placement rates and analyzed archived data from six domains of the Child and Adolescent Needs and Strengths (CANS; Problem Presentation, Risk Behaviors, Functioning, Child Safety, Caregiver Needs, and Child Strengths) to assess changes in youth functioning post-discharge (90 and 180 days). An analysis using generalized estimating equations (GEE), controlling for potential confounding variables such as demographics and clinical features, suggest that length of stay in ESFT-FBMHS was significantly associated with out-of-home placement and youth improvement on the CANS at both 90- and 180-days post-discharge. As a group, youth with SED who did not complete the full duration of the program had 2–3 times the odds of out-of-home placement at 90 days post-discharge and 1–3 times the odds at 180 days post-discharge as compared to program completers. CANS scores showed improvement in 40.1% of youth who completed the program as compared to only 11.7%–18.2% for those who did not. The results of this study suggest that ESFT-FBMHS is effective for youth with SED as a group and can improve youth functioning and reduce out-of-home placement. Highlights: ESFT-FBMHS, an intensive in-home family-based program, is effective in reducing the odds of out-of-home placement for youth who complete the program. Treatment duration in ESFT-FBMHS is significantly associated with the odds of out-of-home placement and changes in youth functioning. Youth who extend their stay in the program show improvement in functioning on the CANS but have similar odds of out-of-home placement as those who do not complete the program. Youth who complete ESFT-FBMHS are significantly more likely to show improvements in functioning on the CANS than those who leave early. Improved youth functioning as measured by the CANS is associated with a 56% reduction in out-of-home placement. [ABSTRACT FROM AUTHOR]

In this paper, we use the distributionally robust approach to study stochastic variational inequalities under the ambiguity of the true probability distribution, which is referred to as distributionally robust variational inequalities (DRVIs). First of all, we adopt a relaxed value function approach to relax the DRVI and obtain its relaxation counterpart. This is mainly motivated by the robust requirement in the modeling process as well as the possible calculation error in the numerical process. After that, we investigate qualitative convergence properties as the relaxation parameter tends to zero. Considering the perturbation of ambiguity sets, we further study the quantitative stability of the relaxation DRVI. Finally, when the ambiguity set is given by the general moment information, the discrete approximation of the relaxation DRVI is discussed. [ABSTRACT FROM AUTHOR]

The article studies quantitative characteristics of the mechanism of excitation of VLF chorus emissions by analyzing high-resolution data from the Van Allen Probes. A typical example of chorus with spectral forms in the lower frequency band (below half of the electron cyclotron frequency) in the region of the local minimum of the magnetic field behind the plasmapause in the middle magnetosphere is presented. A new method of analysis of quasi-harmonic signals recorded with high digitization frequency is proposed and implemented by the example of chorus in the lower frequency band. The results of wave field measurements in a high-resolution data channel are presented in the form of a rectangular event matrix, each row of which corresponds to one cycle of the wave process. In the event matrix, the rows corresponding to the fragments of the implementation that characterize the natural source of short electromagnetic pulses are selected. This made it possible to determine the complex eigenvalues of the characteristic equation of the source at the linear stage of chorus excitation. The values of the roots of the characteristic equation obtained by analyzing the data of chorus observations correspond to the implementation of chorus excitation by the amplification of noise electromagnetic pulses in a planar densification waveguide. [ABSTRACT FROM AUTHOR]

Spiritual self-care is defined as a set of patient-centered or family-centered spiritual activities aimed at promoting health and well-being. In chronic diseases such as cancer, the responsibility for care typically falls on the patient or their family, necessitating an accurate assessment of the patient's self-care practices to achieve this goal. The objective of this study was to translate, culturally adapt, and examine the psychometrics of the Persian version of the spiritual self-care practice scale (SSCPS) in cancer patients. This scale is designed to be administered directly to patients to assess their spiritual self-care practices. This cross-sectional study was conducted at the oncology ward in Afzalipoor Hospital, Javad Al-Aemeh Clinic, and Physicians Clinics affiliated with Kerman University of Medical Sciences in Kerman, southeast Iran. The study included qualitative and quantitative assessments of face validity, content validity, item analysis, exploratory and confirmatory factor analysis (construct validity), and reliability. Data collection took place between March 20, 2023, and December 30, 2023. The scale's content validity index was calculated to be 0.948, with mostly minor revision comments for most items. The item-content validity indices ranged from 0.7 to 1. Exploratory factor analysis revealed a five-factor solution with 23 items, explaining 61.251% of the total variance. The identified factors were labeled as 'personal and interpersonal spiritual practices,' 'shaping and strengthening relationship practices,' 'religious practices,' 'physical spiritual practices,' and 'reshaping relationship practices.' Most of the confirmatory factor analysis indices were satisfactory (χ2/df = 1.665, CFI = 0.934, IFI = 0.935, RMSEA = 0.058). The Cronbach's α coefficient for the total scale was 0.89, while it ranged from 0.596 to 0.882 for the subscales. The Persian version of SSCPS with 23 items demonstrates reliability and effectiveness in assessing the spiritual practice performance of Iranian cancer patients. Compared to the original version, the Persian adaptation of SSCPS is concise, making it a suitable instrument for future research and practice on spiritual self-care among Iranian cancer patients. [ABSTRACT FROM AUTHOR]

The present article aims to describe the different steps on how to design, develop and conduct quantitative and qualitative Spirituality and Health (S/H) studies from a Brazilian perspective, discussing definitions and instruments, and proposing a "how-to guide" for those interested in this field of research. A narrative review of the literature has been conducted by experts in the field of S/H aiming to develop a "how-to-guide". Spirituality is a very complex concept that has several challenges in the current scientific literature, including the lack of consensus in the definitions, the numerous dimensions assessed, the diverse instruments for measurement, the criticisms from other scholars, the great diversity of religious and cultural traditions and the growing number of "spiritual but not religious" individuals. This review supports that S/H studies may follow the high scientific standards, using consolidated research procedures and solid methods for both qualitative and quantitative research. Some peculiarities of the research methods for this field are discussed. S/H research is still under development, and there are several future directions for S/H studies, aiming to minimize previous criticisms and generating stronger evidence. [ABSTRACT FROM AUTHOR]

The present study aimed to investigate the role of spirituality, intolerance of uncertainty (IU), and fear of COVID-19 as correlates and predictors of psychological distress among older adults in Pakistan and also assess the gender differences among research variables. Using a quantitative correlational survey research design, a sample of 150 (75 = Men, 75 = Women) older adults aged 55 years and above from different cities of Pakistan were approached through a non-probability purposive sampling strategy. Participants completed the Daily Spiritual Experience Scale, Intolerance of Uncertainty Scale IUS-12, Fear of COVID-19, and Kessler Psychological Distress Scale-K10. Spirituality has a significant negative relationship with psychological distress. Whereas, IU (Inhibitory anxiety and prospective anxiety) and fear of COVID-19 have a significant positive relationship with psychological distress. Results also showed that spirituality, IU dimensions, and fear of COVID-19 emerged as significant predictors of psychological distress among older adults after controlling for the effect of covariates. In addition, elderly females significantly showed more spirituality, less IU, and fear of COVID-19 as compared to elderly males. It is proposed that mental health care plays an important role in treating the psychological needs of older adults in pandemic situations and that further study is needed to develop effective solutions for older persons in stressful situations such as pandemics. [ABSTRACT FROM AUTHOR]

Approaches to integrating mixed methods into medical research are gaining popularity. To get a holistic understanding of the effects of behavioural interventions, we investigated religious fasting using a triangulation of quantitative, qualitative, and natural language analysis. We analysed an observational study of Bahá'í fasting in Germany using a between-method triangulation that is based on links between qualitative and quantitative analyses. Individual interviews show an increase in the mindfulness and well-being categories. Sentiment scores, extracted from the interviews through natural language processing, positively correlate with questionnaire outcomes on quality of life (WHO-5: Spearman correlation r = 0.486, p = 0.048). Five questionnaires contribute to the first principal component capturing the spectrum of mood states (50.1% explained variance). Integrating the findings of the between-method triangulation enabled us to converge on the underlying effects of this kind of intermittent fasting. Trial registration: NCT03443739 [ABSTRACT FROM AUTHOR]

Most studies on solute transport in coastal aquifers affected by tides focus on the transport of instantaneous released solute, and there are few studies on continuously released solute affected by tides. In this study, the image monitoring method is used to establish the quantitative relationship between the concentration of the colored tracer and the hue value of the image, and the digital image is used to determine the tracer concentration distribution. Using image monitoring method laboratory experiments, quantitative analysis of the characteristics of continuously released solute transport in coastal unconfined aquifers under the tidal influence. Experiments show that the high tide inhibits the increase in the concentration of each point in the aquifer. Under the influence of tides, the solute plume retreats towards the land. During the low tide period, the solute plume migrates toward the sea again. And the solute plume will maintain a relatively stable shape after entering the aquifer for a long enough time. Ignoring the tidal effect seems to have little effect on the estimation of the position of the solute plume, but ignoring the tidal effect has a certain influence on the estimation of the dispersion range of the solute plume. No matter whether considering the tidal action, the final dispersion range of the solute plume is almost the same. But before the solute plume reaches a stable state, ignoring the tidal effect will lead to a smaller dispersion range of the solute plume. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study was to characterize the relationship between a novel radiographic measurement on initial AP pelvis radiograph (termed "bladder shift," BS) to intraoperative blood loss (IBL) during acetabular surgical fixation. Methods: All adult patients receiving unilateral acetabular fixation (Level 1 academic trauma; 2008–18) were reviewed. AP pelvis radiographs were reviewed for visible bladder outlines and then measured to determine the percentage deformation toward the midline. Hemoglobin & hematocrit data were then used to calculate quantitative blood loss between pre- and post- operative blood counts for data analysis. Results: 371 patients with unilateral traumatic acetabular fractures requiring fixation were reviewed; 99 of these had visible bladder outlines, complete blood count and transfusion data (2008–2018; 66% associated patterns). Median bladder shift (BS) was 13.3%. Every 10% of bladder shift was associated with 123 mL greater IBL. Patients with full bladder shift to midline sustained a median 1.5L IBL (interquartile range [IQR] 0.8 to 1.6). Associated patterns had a threefold greater median BS (associated: 16.5% [15.4 to 45.9] vs. elementary: 5.6% [1.1 to 15.4], p < 0.05) and received intraoperative pRBC twice as frequently (57% vs. 24%, p < 0.01). Conclusions: Radiographic bladder shift is an easily available visual marker, in patients sustaining acetabular fractures, that may predict intraoperative hemorrhage and need for transfusions. [ABSTRACT FROM AUTHOR]

Caregivers of children with autism spectrum disorder (ASD) often report higher rates of depression and the related negative thought patterns that may precede a clinical diagnosis. These negative thought patterns are referred to as depressive cognitions. Depressive cognitions are exacerbated by child problem behaviors (CPB) but may be impacted by parental resilience. The current study examines relations between CPB and depressive cognitions and the role of resilience as a moderator among caregivers of children with ASD (n = 287) and a sample of caregivers of children who are typically developing (n = 207). Significant positive associations were found between CPB and depressive cognitions for caregivers of children with ASD and who are typically developing. A moderation analysis revealed that, among the ASD sample, the model accounted for 33% of the variance in caregiver depressive cognitions (R2 = 0.33, SE = 35.52, p < 0.001). The interaction of child problem behaviors and caregiver resilience on caregiver depressive cognitions was statistically significant (B = − 0.016, SE = 0.007, p = 0.037), thus resilience was a significant moderator, for caregivers of children with ASD. Resilience serves as a protective factor in the relationship between child problem behavior and caregiver depressive cognitions for caregivers of children with ASD only. This finding highlights the importance of assessing and supporting resilience among caregivers of children with ASD. Interventions addressing child behavior would benefit from additional components to bolster caregiver resilience to enhance caregiver mental health and protect against depressive cognitions. [ABSTRACT FROM AUTHOR]

The primary objective of this research is to develop innovative methods for efficient condition monitoring of electro-motors. The study investigates the current signals of electro-motors in their early stages of failure, specifically identifying high-frequency fluctuations. These fluctuations, due to their low intensity and lack of modulation, elude detection through FFT analysis. As such, this study analyzes the quantitative and qualitative nature of such disturbances, including their frequency content and intensity in healthy and defective states, and identifies and isolates high-frequency disturbances from the current signal using the EMD and CEEMDAN methods. The research involved a comprehensive analysis of the FFT spectrum, envelope, and factors of main current signals and IMFs. The results indicate mode mixing only in the defective state. The EMD results demonstrate that the IMF associated with the original signal in the defective state exhibited a frequency content of less than 50, as evidenced by the FFT and the envelope spectrums. Additionally, the amplitude of the dominant frequencies in the FFT spectrum of the disturbances was significantly higher in the defective state. Additionally, the outcomes disclose that the original signal's RMS to the disturbances' RMS was significantly higher in healthy cases. Furthermore, the crest factor ratio in the healthy state was slightly higher than that of the defective state. The CEEMDAN findings reveal that the IMFs associated with the disturbance in a healthy state exhibit characteristics akin to white noise. Conversely, some IMFs demonstrate dominant frequencies of 50 and 150 Hz in the defective state. Furthermore, the RMS ratio of the original signal to the RMS of the disturbance is higher in the healthy state than in the defective state. Additionally, the shape factor of disturbances in the healthy state surpasses that of the faulty state. However, the ratio of shape factor notably exceeds in the healthy state. [ABSTRACT FROM AUTHOR]

Purpose: To assess image quality and diagnostic confidence of 3D T1-weighted spoiled gradient echo (SPGR) MRI using artificial intelligence (AI) reconstruction. Materials and methods: This prospective, IRB-approved study enrolled 50 pediatric patients (mean age = 11.8 ± 3.1 years) undergoing clinical brain MRI. In addition to standard of care (SOC) compressed SENSE (CS = 2.5), 3D T1-weighted SPGR images were obtained with higher CS acceleration factors (5 and 8) to evaluate the ability of AI reconstruction to improve image quality and reduce scan time. Images were reviewed independently on dedicated research PACS workstations by two neuroradiologists. Quantitative analysis of signal intensities to calculate apparent grey and white matter signal to noise (aSNR) and grey-white matter apparent contrast to noise ratios (aCNR) was performed. Results: AI improved overall image quality compared to standard CS reconstruction in 35% (35/100) of evaluations in CS = 2.5 (average scan time = 221 ± 6.9 s), 100% (46/46) of CS = 5 (average scan time = 113.3 ± 4.6 s) and 94% (47/50) of CS = 8 (average scan time = 74.1 ± 0.01 s). Quantitative analysis revealed significantly higher grey matter aSNR, white matter aSNR and grey-white matter aCNR with AI reconstruction compared to standard reconstruction for CS 5 and 8 (all p-values < 0.001), however not for CS 2.5. Conclusions: AI reconstruction improved overall image quality and gray-white matter qualitative and quantitative aSNR and aCNR in highly accelerated (CS = 5 and 8) 3D T1W SPGR images in the majority of pediatric patients. [ABSTRACT FROM AUTHOR]

Developing leadership skills during adolescence is crucial for future career success. Previous studies have primarily focused on the impact of school settings, academic courses, and simulated team tasks on leader emergence, neglecting the significant role of parental influence in this process. Employing a mixed-methods approach, this research investigated the positive relationship between parental warmth and adolescent leader emergence and the underlying mechanisms of this relationship. The quantitative study (Study 1) collected multi-source data from 1255 adolescents (Mage = 14.2, SDage = 0.56, 48.2% male) and their parents, teachers and peers. Findings from Study 1 revealed a positive correlation between parental warmth and adolescent leader emergence. Structural equation modeling showed two mediating pathways: an intrapersonal pathway involving self-esteem and leader self-efficacy, and an interpersonal pathway involving empathy and prosocial behavior. Encouragement of independence, as an additional adolescents-focused parenting practice, strengthened the observed positive relationship. The qualitative study (Study 2) conducted in-depth interviews with adolescents to identify the parental practices that facilitate or hinder adolescent leader emergence for the triangulation of the central research question. Study 2 collected data from 32 adolescents (Mage = 15.16, SDage = 1.37, 50% male). Findings from Study 2 corroborated the significance of parental warmth and the encouragement of independence for adolescent leader emergence, elucidating specific parenting behaviors conducive to these positive parenting practices, such as providing companionship and communication, as well as encouraging adolescents to participate in household tasks. This mix-methods research prepositioned the stages of leadership development, advocating for the importance of the warmth and autonomy from parents as formative factors for cultivating the next generation of leaders. [ABSTRACT FROM AUTHOR]

Standard models of well-child care may not sufficiently address preventive health needs of immigrant families. To augment standard individual well-child care, we developed a virtual group-based psychoeducational intervention, designed to be delivered in Spanish as a single, stand-alone session to female caregivers of 0–6 month-olds. The intervention included a video testimonial of an individual who experienced perinatal depression followed by a facilitated discussion by the clinic social worker and an orientation to relevant community resources by a community health worker. To assess feasibility and acceptability of the intervention, we conducted an open pilot within an academic pediatric practice serving predominantly Latinx children in immigrant families. Participants included 19 female caregivers of infants attending the practice, of whom 16 completed post-intervention measures and 13 completed post-intervention semi-structured interviews. Quantitative measures of acceptability and satisfaction with the intervention were high. We found preliminary effects of the intervention on postpartum depression knowledge and stigma in the expected direction. In interviews, participants described increases in their familiarity with postpartum depression and about relevant community resources, including primary care for caregivers. Participants reported an appreciation for the opportunity to learn from other caregivers and provided suggestions for additional topics of interest. Trial registration: Registered 6/21/22 as NCT05423093. [ABSTRACT FROM AUTHOR]

Prostate-specific antigen (PSA)-based prostate cancer screening is a preference-sensitive decision for which experts recommend a shared decision making (SDM) approach. This study aimed to examine PSA screening SDM in primary care. Methods included qualitative analysis of audio-recorded patient-provider interactions supplemented by quantitative description. Participants included 5 clinic providers and 13 patients who were: (1) 40–69 years old, (2) Black, (3) male, and (4) attending clinic for routine primary care. Main measures were SDM element themes and "observing patient involvement in decision making" (OPTION) scoring. Some discussions addressed advantages, disadvantages, and/or scientific uncertainty of screening, however, few patients received all SDM elements. Nearly all providers recommended screening, however, only 3 patients were directly asked about screening preferences. Few patients were asked about prostate cancer knowledge (2), urological symptoms (3), or family history (6). Most providers discussed disadvantages (80%) and advantages (80%) of PSA screening. Average OPTION score was 25/100 (range 0–67) per provider. Our study found limited SDM during PSA screening consultations. The counseling that did take place utilized components of SDM but inconsistently and incompletely. We must improve SDM for PSA screening for diverse patient populations to promote health equity. This study highlights the need to improve SDM for PSA screening. [ABSTRACT FROM AUTHOR]

Purpose: Several studies have shown that subcutaneous injections of omalizumab can treat chronic idiopathic/spontaneous urticaria (CIU/CSU) patients by only assessing the efficacy on specific endpoints. This study aimed to quantitatively analyze different doses of omalizumab in CIU/CSU and compare it with ligelizumab. Methods: Literature searches were performed in PubMed, Embase, and Web of Science databases. A model-based meta-analysis (MBMA) was utilized to develop a model incorporating time since the initiation of treatment and dose for omalizumab, with the change from baseline in Urticaria Activity Score (CFB-UAS7) as the primary efficacy endpoint. The time-course and dose-effect relationship throughout the omalizumab treatment period was analyzed, and the findings were compared with those of the investigational ligelizumab. Results: The model equation for the CFB-UAS7 was established as E = –Emax × time/(ET50 + time) × (b0 + b1 × dose). The estimated values of the model parameters E max , ET 50 , b 0 , and b 1 were −1.16, 1.26 weeks, −9.90, and −0.0361 mg−1, respectively. At week 12 after the first dose, the model-predicted CFB-UAS7 for 150 mg and 300 mg of omalizumab were −16.0 (95% CI, −17.2 to −14.8) and −21.7 (95% CI, −22.9 to −20.5), respectively. In the PEARL-1 trial, the CFB-UAS7 for 72 mg and 120 mg of ligelizumab were −19.4 (95% CI, −20.7 to −18.1) and −19.3 (95% CI, −20.6 to −18.0), respectively. In the PEARL-2 trial, these values were −19.2 (95% CI, −20.5 to −17.9) and −20.3 (95% CI, −21.6 to −19.0), respectively. Conclusion: Omalizumab showed a significant dose-dependent effect in the treatment of CSU. Both 72 mg and 120 mg ligelizumab might have the potential to outperform 150 mg (but not 300 mg) omalizumab. [ABSTRACT FROM AUTHOR]

Introduction: There remains a critical need for precise localization of the epileptogenic foci in individuals with drug-resistant epilepsy (DRE). 18F-Fluorodeoxyglucose positron emission tomography (FDG-PET) imaging can reveal hypometabolic regions during the interval between seizures in patients with epilepsy. However, visual-based qualitative analysis is time-consuming and strongly influenced by physician experience. CortexID Suite is a quantitative analysis software that helps to evaluate PET imaging of the human brain. Therefore, we aimed to evaluate the efficacy of CortexID quantitative analysis in the localization of the epileptogenic zone in patients with temporal lobe epilepsy (TLE). Methods: A total of 102 patients with epilepsy who underwent 18F-FDG-PET examinations were included in this retrospective study. The PET visual analysis was interpreted by two nuclear medicine physicians, and the quantitative analysis was performed automatically using CortexID analysis software. The assumed epileptogenic zone was evaluated comprehensively by two skilled neurologists in the preoperative assessment of epilepsy. The accuracy of epileptogenic zone localization in PET visual analysis was compared with that in CortexID quantitative analysis. Results: The diagnostic threshold for the difference in the metabolic Z-score between the right and left sides of medial temporal lobe epilepsy (MTLE) was calculated as 0.87, and that for lateral temporal lobe epilepsy (LTLE) was 2.175. In patients with MTLE, the area under the curve (AUC) was 0.922 for PET visual analysis, 0.853 for CortexID quantitative analysis, and 0.971 for the combined diagnosis. In patients with LTLE, the AUC was 0.842 for PET visual analysis, 0.831 for CortexID quantitative analysis, and 0.897 for the combined diagnosis. These results indicate that the diagnostic efficacy of CortexID quantitative analysis is not inferior to PET visual analysis (p > 0.05), while combined analysis significantly increases diagnostic efficacy (p < 0.05). Among the 23 patients who underwent surgery, the sensitivity and specificity of PET visual analysis for localization were 95.4% and 66.7%, and the sensitivity and specificity of CortexID quantitative analysis were 100% and 50%. Conclusion: The diagnostic efficacy of CortexID quantitative analysis is comparable to PET visual analysis in the localization of the epileptogenic zone in patients with TLE. CortexID quantitative analysis combined with visual analysis can further improve the accuracy of epileptogenic zone localization. [ABSTRACT FROM AUTHOR]

Reasonable test scenarios and objective evaluation methods can rapidly promote the development of autonomous vehicle technology. A new quantitative evaluation method for the comprehensive performance of autonomous vehicle is proposed in this paper. First, different test environments and test contents are combined to obtain vehicle test scenarios of different complexity. Then, the evaluation index system of autonomous vehicle is divided into target layer, total index layer, and index layer. After that, the weights of the index layer are determined by the objective weight method of Criteria Importance though Intercriteria Correlation (CRITIC) method, and the total weights of index layer are determined by the analytic hierarchy process (AHP) of subjective weight method. Finally, the improved grey relational theory method is used to quantitatively evaluate autonomous vehicles from four aspects: driving safety, riding comfort, intelligence, and efficiency. The quantitative evaluation of autonomous vehicles can reduce the influence of abnormal data on the correlation degree and increase the robustness of the evaluation algorithm. The evaluation results of the proposed method and the traditional fuzzy comprehensive evaluation method are compared by simulation experiment and evaluation. The results show that the proposed evaluation method in this paper is more objective and reasonable, which can quantitatively evaluate the comprehensive performance of autonomous vehicles. [ABSTRACT FROM AUTHOR]

The phenomenon of isothermal supersaturation of solutions in a porous medium at ion exchange is studied on the basis of mathematical modeling. The phenomenon consists in the fact that the solution with concentration significantly higher than the maximal solubility of the substance is formed in the pores of sorbent and no precipitation occurs. The question of why sediment does not appear in the pores between the grains is investigated in the article. It is shown that the phenomenon under consideration can be explained by the effect of dynamic equilibrium between the association of condensed phase particles in the inner part of the pores, their diffusion, and decomposition near the surface of the sorbent grains caused by a change in potential. The degree of possible supersaturation of the solution is estimated depending on the process parameters. The proposed hypothesis is confirmed by quantitative studies using the available experimental data. [ABSTRACT FROM AUTHOR]

Background: Individual and collective prosocial competence can be fostered through high-quality interactions with program staff in out-of-school time environments. Objective: We explored whether the social-emotional competencies of teachers working in an out-of-school STEM program infused with social emotional learning content were associated with school children's prosocial behavior, community engagement, and peer problems and whether these associations were moderated by social justice teaching beliefs and child gender. Method: Participants were 126 students (72 male). Forty-one were White, 40 were Black, 34 were Latine, and 11 were Asian and most of them were third graders (Mage = 8.11 years). Teachers rated their emotional competence, commitment to social emotional learning, and social justice teaching beliefs. They also provided ratings of children's prosocial behavior and peer problems. Students provided ratings of their community engagement. Results: Teachers' emotional competence was negatively associated with prosocial behavior, but only when their social justice teaching beliefs were low. However, teachers' commitment to social emotional learning was positively related to prosocial behavior. Teachers' emotional competence was associated positively with peer problems, but only for girls, and was also related positively to community engagement. Conclusions: Results demonstrate associations between STEM teachers' social emotional learning competencies and social justice teaching beliefs in the development of students' prosocial competence and community engagement and provide directions for future research. [ABSTRACT FROM AUTHOR]

A number of empirical studies have underscored the significance of entrepreneurial orientation in understanding the dynamic business environment driven by entrepreneurial actions. However, the notion of individual entrepreneurial orientation (IEO) has received less attention in scholarly literature. It's widely acknowledged that entrepreneurial education (EE) makes a substantial contribution to a country's economy. It's believed that EE can empower individuals and thus play a crucial role in addressing various societal challenges faced by countries globally. Nonetheless, the influence of EE on the IEO of university students, and whether it effectively guides them towards an entrepreneurial career, hasn't been thoroughly examined. This study aimed to explore the influence of EE on the IEO of university students. This study focuses on two distinct economies—a developing one (South Africa) and a developed one (Scotland), the latter being recognized for its high-quality EE and a high proportion of individuals opting for entrepreneurial careers. A quantitative research approach was followed making use of an adapted questionnaire, which was analysed with SPSS and EQS 6.4 using descriptive statistics, reliability analysis, exploratory factor analysis, multivariate analysis of variance and path model analysis. A total of 2841 questionnaires were distributed online, yielding 575 valid responses. Findings indicate that EE significantly influences the IEO of university students in South Africa, but to a lesser extent in Scotland. The study expands the existing body of knowledge on IEO of university students. In addition, it provides insight for policymakers in the respective countries. [ABSTRACT FROM AUTHOR]

Context: Ecological corridors are one of the most recommended ways to mitigate biodiversity loss. With growing recognition of corridor importance, corridor modeling lags others in the development of robust, quantitative validation methods. Objective: We propose a post-hoc corridor validation framework, considering the range of methods across data needs and statistical intensity. We demonstrate the importance of post-hoc corridor validation by testing several validation methods on different corridor model outputs. Methods: We used three different transformations on a Florida black bear (Ursus americanus floidanus) habitat suitability model to create different resistance grids, independent GPS collar data from a case study population, and Circuitscape to create corridor models. We used several validation methods, including a novel method, to compare resulting corridors. Results: Transformed resistance grids were all correlated, yet differing validation and resistance grids resulted in different recommended corridors. The use of one resistance surface and one validation type can result in the selection of inefficient or ineffective corridors. At a minimum, modelers should determine what proportion of an independent population falls within resulting corridors and should move towards more robust, documented methods as resources allow. The use of multiple validation methods can ensure greater confidence of modeling results. Conclusions: We encourage the use and further development of the framework presented here to drive the corridor modeling field towards more effective corridor creation and improved conservation outcomes. If validation methods are not improved, the ecological and economic cost of poor corridor science will continue to increase with increasing biodiversity loss. [ABSTRACT FROM AUTHOR]

Objective: To explore the effects of Huxin formula (HXF) in curtailing atherosclerosis and its underlying mechanism. Methods: According to random number table method, 24 specific pathogen free male ApoE-/- mice were randomly divided into model group, HXF low-dose (HXF-L) group (8.4 g/kg daily), HXF high-dose (HXF-H) group (16.8 g/kg daily), and pravastatin (8 mg/kg daily) group in Experiment I (n=6 per group). C57BL/6J mice served as the control group (n=6). ApoE-/- mice in HXF-L, HXF-H, pravastatin groups were fed a Western diet and administered continuously by gavage for 12 weeks, while C57BL/6J mice in the control group were fed conventional lab mouse chow for 12 weeks. Further, Tregs were depleted by weekly intraperitoneal injection of purified anti-mouse CD25 antibody (PC61, 250 µg per mouse) for 4 weeks in Experiment II (n=6 per group). Oil Red O and Masson staining were used to evaluate the plaque area and aortic root fibrosis. The CD4+CD25+Foxp3+Treg counts in the lymph nodes and spleen cells were detected using flow cytometric analysis. The transforming growth factor-β1 (TGF-β1), interleukin (IL)-10, and IL-6 serum levels were examined by MILLIPLEX® MAP technology. Quantitative real-time reverse transcription PCR (qRT-PCR) and Western blot were utilized to assess the expression of TGF-β mRNA and protein in the aorta. The expression of CD4+T lymphocytes, macrophages and smooth muscle cells in the aortic root were detected by immunofluorescence staining. Results: HXF reduced plaque area in ApoE-/- mice (P<0.01). HXF increased the Treg counts in the lymph nodes and spleen cells (P<0.05 or P<0.01). Moreover, HXF alleviated inflammatory response via elevating IL-10 and TGF-β 1 serum levels (P<0.05), while decreasing the IL-6 serum levels in ApoE-/- mice (P>0.05). Also, HXF upregulated the expression of TGF-β mRNA and protein in the aorta (P<0.05). Additionally, HXF attenuated CD4+T lymphocytes, macrophages and smooth muscle cells in aortic root plaque (P<0.01). Furthermore, the depletion of Tregs with CD25 antibody (PC61) curtailed the reduction in plaque area and aortic root fibrosis by HXF (P<0.01). Conclusion: HXF relieved atherosclerosis, probably by restraining inflammatory response, reducing inflammatory cell infiltration and attenuating aortic root fibrosis by increasing Treg counts. [ABSTRACT FROM AUTHOR]