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Purpose: The purpose of this study was to investigate associations between digital urine color and paper urine color with other urine indices to assess hydration status. Methods: Twelve male subjects (mean ± standard deviation; age, 26 ± 8 years; body mass, 57.8 ± 5.3 kg; height, 177.5 ± 8.9 cm; VO2max, 57.8 ± 5.8 ml·kg−1·min−1) performed four exercise trials in the heat. Before and following exercise trials, subjects provide urine samples. Urine samples were measured using a digital urine color chart on a portable device screen. Urine samples were also assessed with urine specific gravity (USG), urine osmolality (UOsmo), and a validated paper urine color chart. Results: There were extremely large associations found between digital urine color and paper urine color (r = 0.926, p < 0.001). Correlation coefficients showing associations with USG and UOsmo were similar between digital urine color (USG, r = 0.695, p < 0.001; UOsmo, r = 0.555, p < 0.001) and paper urine color (USG, r = 0.713, p < 0.001; UOsmo, r = 0.570, p < 0.001). Bland–Altman analysis indicated that no proportional bias was observed between digital and paper urine colors (bias, − 0.148; SD of bias, 0.492; 95% LOA, − 1.11, 0.817; p = 0.094). Conclusions: Strong associations were found between digital and paper urine colors with no proportional bias. Furthermore, the degree of associations with USG and UOsmo was similar between digital and paper urine color. These results indicate that digital urine color is a useful tool to assess hydration status and this method could be used as an alternative method to using paper urine color. [ABSTRACT FROM AUTHOR]

Objectives: Most researchers who study the effects of hormonal contraception on menstrual bleeding rely on self-reported data via paper diaries, for which completeness and timeliness have been shown to be poor. The purpose of this exploratory study was to compare the completeness and timeliness of bleeding data collected via paper diaries, text messages or smartphone application (a.k.a "app"). Methods: This was a sub-study of a double-blinded, placebo-controlled randomized trial comparing the effects of a non-steroidal anti-inflammatory drug, naproxen, with placebo when using a copper IUD. Participants tracked bleeding and symptoms over 112 days. Participants tracked bleeding daily using a paper diary as well as with either text messages or a smartphone app. Participants who used paper and the app were also able to record non-bleeding symptoms. Results: Twenty-five participants submitted diaries. Of these participants, 10 completed both paper and app diaries, 7 completed both paper and text messages, 4 completed the paper diary only, 4 completed the app only. Text messages had the most complete data (108 days), followed by the app (96 days) and paper diaries (84 days). The lag time between a bleeding event and the date recording that event was 0.10 days for text, 1.0 days for app, and 4.73 days for paper diaries. Participants using the app reported a median of 33 other symptoms over the study period compared to 7 for the paper diaries. Discussion: Our findings suggest texts demonstrated more complete and timely bleeding data than either paper diaries, or the app. Compared to paper diaries, the app delivered more complete, timely data, and also collected a large set of symptoms. [ABSTRACT FROM AUTHOR]

There are limited comparative studies on modeling fluid transport in fractured porous media. Hence, this paper systematically compares the steady-state creeping flow Stokes–Brinkman and Darcy–Darcy models for computational efficiency and accuracy. Sensitivity analyses were also conducted on the effect of fracture orientations, fracture sizes, mesh resolution, and fractures with Local Grid Refinement (LGR) under the FEniCS computational framework. Both models were validated numerically, and the accuracy of their solution is compared using the R-squared metric and L2 norm estimates. Key results showed that both models have similar pressure and velocity field solutions for a given fracture orientation. The computational time required for solving the Stokes–Brinkman models for a single fracture case was unusually lower than that of the Darcy–Darcy model when the pressure and velocity terms in the Darcy–Darcy model were solved simultaneously using two equations, contrary to where only one equation solves for the pressure and the velocity is obtained by projecting the gradient of pressure onto a vector space. The Stokes–Brinkman model is more sensitive to mesh resolution, and as a result, the Darcy–Darcy model tends to be more accurate than the Stokes–Brinkman model at low resolutions. Local Grid Refinement (LGR) can improve the Stokes–Brinkman model's accuracy at low mesh resolution. Furthermore, both models showed similar results when compared for complex fracture systems such as multiple fracture cases: interconnecting and isolated fractured porous media systems under low-velocity and steady-state creeping flow conditions. The FEniCS code in this paper is shared for future researchers to reproduce results or extend the research work. [ABSTRACT FROM AUTHOR]

Is it really better to print everything, including software models, or is it better to view them on screen? With the ever increasing complexity of software systems, software modeling is integral to software development. Software models facilitate and automate many activities during development, such as code and test case generation. However, a core goal of software modeling is to communicate and collaborate. Software models are presented to team members on many mediums and two of the most common mediums are paper and computer screens. Reading from paper or screen is ostensibly considered to have the same effect on model comprehension. However, the literature on text reading has indicated that the reading experiences can be very different which in turn effects various metrics related to reader performance. This paper reports on an experiment that was conducted to investigate the effect of reading software models on paper in comparison with reading them on a computer screen with respect to cognitive effectiveness. Cognitive effectiveness here refers to the ease by which a model reader can read a model. The experiment used a total of 74 software engineering students as subjects. The experiment results provide strong evidence that displaying diagrams on a screen allows subjects to read them quicker. There is also evidence that indicates that on screen viewing induces fewer reading errors. [ABSTRACT FROM AUTHOR]

The catch-up of latecomer firms has been a topic of interest because it is closely related to the changes in industry leadership. The reason why some countries are more successful in catch-up is because of their increasing mastery of technology management (TM). Therefore, to ensure successful catch-up, it is imperative for latecomer firms to understand the TM practices and TM modes across national boundaries. This paper aims to reveal the differences in TM practices and TM modes between latecomer firms and forerunner firms. This paper collected data from Chinese firms and Korean firms as latecomers and forerunners, respectively, to examine the differences in TM practices and TM modes. The results show that latecomer firms place more emphasis on grasping the condition of firms' equipment, understanding technology talents required by business, and completing files on technology information. While forerunner firms stress learning from other competitors, effective training, and constructing detailed technology information management system most. Furthermore, the relationship between TM and product innovation performance is more integrated for forerunner firms compared to latecomer firms. A key contribution of this paper is to reveal the differences in TM practices and TM modes between latecomer firms and forerunner firms, which enriches the catch-up literature from an international comparative perspective. As such, this paper is of great importance in broadening the understanding of how latecomer firms transform into global leaders. [ABSTRACT FROM AUTHOR]

While major advances have been made over the past years in comparing citizenship laws globally, most measures remain restricted to the law-on-the-books. Knowledge about the implementation of these laws remains limited. This poses the question to what extent these measures correspond with the law as experienced by targeted populations. In order to overcome the implementation gap when comparing and measuring citizenship law globally, this paper addresses the question of how to gain a coherent understanding of implementation. Developing a comprehensive typology, the paper distinguishes three crucial elements of implementation: (1) the entry into force of legal provisions (capturing the applicable state of citizenship law), (2) the interpretation of law (the specific interpretation of legal provisions used by the authorities responsible for their execution), and (3) the application of law (executing legal provisions in practice by the authorities). Subsequently, the paper illustrates how this typology can be applied to the analysis of citizenship law implementation by a case study of dual citizenship acceptance, focusing on the renunciation requirement for naturalisation and dual citizenship treaties. The paper concludes by outlining directions for a comparative research agenda that better corresponds with the lived experience of citizenship laws. [ABSTRACT FROM AUTHOR]

Background: The wide use of the term Cognitive Reserve (CR) is in need of a clear and shared definition of its concept and of the development of new tools, quick and easy to use and updated for the people of today. This study describes the online short CRIq (s-CRIq), the new shorter version of the CRIq, following an item analysis revision, and compares the data distribution of different samples. Methods: The s-CRIq was administered online to 435 people while another 440 filled out the s-CRIq in self-administration. A further 588 participants had been administered the original paper-and-pencil long CRIq and 344 the online long CRIq. Results: The major difference in the databases of s-CRIq versus the long versions is an increased score in education and in leisure activity. However, the density distributions of the total score of CRI in the 4 databases share 64% of their areas, and at least two of them share 84%. Conclusion: The s-CRIq proved to be a simple and easy-to-administer tool. Similarly, to the original version, the s-CRIq is freely available on the web, and it is our hope that it will be of fruitful use for researchers and clinicians alike. [ABSTRACT FROM AUTHOR]

In this paper, a wideband polarization conversion metasurface is designed. Additionally, coding and chessboard metasurfaces are specifically tailored for radar cross-section reduction (RCS). Initially, a compact unit cell demonstrating exceptional polarization conversion performance is introduced, achieving a polarization conversion ratio (PCR) exceeding 90 % across frequencies ranging from 7.9 to 22.7 GHz. The PCR remains effective even when oblique incidence angles of up to 30 ∘ are utilized across this frequency band. Roger RT5880, with a thickness of 0.254 mm, serves as the substrate. An airgap is introduced between the substrate and the ground plane to enhance the polarization conversion bandwidth. This unit cell serves as the fundamental building block for subsequent metasurface configurations. To assess the scalability and effectiveness, a 36 × 36 unit array is assembled, confirming efficient polarization conversion capabilities extending to larger structures. Moreover, a 1-bit coding unit "0" and "1" are formed by the Pancharatnam-Berry phase based on the same-sized meta-atom with 90 ∘ orientations. The robustness and practicality of the design are demonstrated by creating 12 × 12 lattices and evaluating their RCS reduction potential under two distinct scenarios: a chessboard pattern and a coding-based scheme. Notably, its results indicate substantial RCS reduction across a broad frequency spectrum (7.9 to 22.7 GHz) for both configurations. This study demonstrates the wide-ranging applicability of metasurface design, making it a valuable contribution to the fields of microwave engineering, polarization control, and radar stealth technology. Owing to its simplicity, bandwidth, and versatility, this approach offers innovative solutions for diverse real-world applications. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic entailed restrictions that hampered face-to-face interactions and social gatherings. In this paper, we examine whether loneliness increased to different extents among age groups due to these restrictions, and if these differences were mediated by specific life course conditions. Based on longitudinal data from the Swiss Household Panel, our results show that loneliness increased disproportionately among younger individuals during the pandemic. This finding aligns with the social convoy model and the socioemotional selectivity theory, which postulate a decline of social network size over the life course. It also corresponds to findings indicating a decrease in contact frequency with increasing age. Individuals aged 30 years and above experienced a lower increase in loneliness when they lived in shared households; however, this protective effect was not observed for younger individuals. Living together with a partner, being male, and not anticipating health complications in case of a COVID-19 infection moderated the increases of loneliness, but they were independent of age. [ABSTRACT FROM AUTHOR]

Handwriting-based technologies have progressed significantly over the years. Scientists have worked beyond just recognizing pieces of plain text from paper. With archaeological advancements, discovery of ancient documents has not been as scarce as it was in the past. However, such documents are discovered in perfect condition once in a blue-moon. They are often subjected to degradation due to the perils of time and understanding them requires skilled manpower which is not easy to find. Here, an automated system is proposed for this task. The proposed system uses a new CNN-based framework to analyze the macro and micro features of an image to recognize the text. Experiments are performed with over 250K historical images of numerals from a publicly available dataset and a highest accuracy of 99.68% is obtained. The data is further subjected to different type of noises and distortions. A novel technique is used to introduce synthesized degradation in the documents. The system performs steadily in all these experimental scenarios. Comparative analysis indicates that our results are higher than the reported works and other standard techniques. [ABSTRACT FROM AUTHOR]

Extensive research on the multi-bridge extension of cascaded rectifier stages is deemed important to meet the requirements of high-voltage and high-power applications. Two control structures for capacitor voltage balancing in cascaded rectifier stages are analyzed in this paper. On this basis, the balance strategy for the multi-bridge extension of single-phase cascaded rectifiers is explored. The balance method of ultra-fast balance modulation trajectories is introduced into single-phase multi-bridge cascaded rectification, and the optimal control strategy is selected through simulation verification and comparative analysis. During the actual experiments, some disturbance factors were introduced into the system, causing an instantaneous unbalanced state. However, through the control strategy proposed in this paper, the system can quickly regain balance. Through simulation validation and analysis of the experimental results, the reliability and innovation of this control strategy have been demonstrated. [ABSTRACT FROM AUTHOR]

Knowledge about the carbohydrate composition of pulp and paper samples is essential for their characterization, further processing, and understanding the properties. In this study, we compare sulfuric acid hydrolysis and acidic methanolysis, followed by GC–MS analysis of the corresponding products, by means of 42 cellulose and polysaccharide samples. Results are discussed and compared to solid-state NMR (crystallinity) and gel permeation chromatography (weight-averaged molecular mass) data. The use of the hydrolysis methods in the context of cellulose conservation science is evaluated, using e-beam treated and artificially aged cellulose samples. [ABSTRACT FROM AUTHOR]

This paper explores the knowledge network structure of foreign research literature by applying the qualitative comparative analysis (QCA) method to the field of information science and library science (ISLS) from the perspective of the cocitation of social network actors such as authors, institutions, countries, and literature, and it further reveals the future application trends of this method. [Method/process] Based on 86 journals in the ISLS field that were downloaded from the Web of Science using the QCA method, the social network analysis (SNA) method and the visual analysis tool Gephi are used to analyse the author cooperation network, the research institution cooperation network, the national cooperation network, the cocitation network, the cutting-edge trends, etc., of journal papers. The analysis shows that the QCA method covers a wide range within the field of ISLS, but the research topics involved in this field are not concentrated, and the author cooperation network has scale-free characteristics. The application of the QCA method is still dominant in European and American countries, and China, the USA, and Italy all play key roles in the national cooperation network. Finally, the institutional cooperation network has certain small group attributes. [ABSTRACT FROM AUTHOR]

Background: Established health-related quality of life scores do not consider both subjective and objective indices of health. We propose the subjective and objective quality of life score (SOQOL) for the comprehensive assessment of health-related quality of life and aim to provide normative population data. The SOQOL is compatible with smartphone applications, allowing widespread use on a global scale. Methods: Normative SOQOL population data was sourced from pre-existing datasets on the EQ-5D-5L, daily step count, and walking speed. Normative values were calculated using weighted grand means. We trialled the SOQOL in a group of five patients presenting to a spinal neurosurgery clinic. Results: SOQOL scores decreased with age, and women had lower scores in every age group. In our case series, the spine patients with the biggest SOQOL deficit compared to age- and sex-matched population averages were found to be surgical while the rest were non-surgical. Conclusions: The SOQOL shows promise as a simple and effective scoring tool that is compatible with smartphones, potentially useful for screening in primary and specialized care settings, and for assessment following healthcare interventions. This study, however, is preliminary, and the findings are primarily suggestive. They underline the necessity for future, more comprehensive studies to validate and expand upon these initial observations. The conclusion of both this abstract and the full paper will clearly state these limitations and the preliminary nature of the study. [ABSTRACT FROM AUTHOR]

This study examines Einstein's field equations in the context of general relativity, comparing five distinct methodologies: (a) vanishing complexity, (b) embedding class one or the Karmarkar condition, (c) conformally flat spacetime, (d) conformal killing symmetry, and (e) the Karmarkar scalar condition. The first four methods reveal a significant connection between two metric potentials, while the fifth method provides a coordinate-independent condition expressed in terms of structural scalars. The paper provides a comprehensive comparative analysis of a new exact solution derived by assuming a common metric function and solving the remaining metric functions through corresponding bridge equations to evaluate their effectiveness and validity. Critical parameters such as thermodynamic factors, causality conditions, stability, and mass function analysis are investigated. [ABSTRACT FROM AUTHOR]

In this paper, an asymmetric scheme based on double image using phase retrieval algorithms in gyrator domain is reported. The double images are encrypted using QZ synthesis method based on QZ algorithm. The synthesized image is bonded with a random phase mask and undergoes a gyrator transform. The resultant image act as an input for the phase retrieval algorithm. We have tested the scheme with five different phase retrieval algorithms, namely the Gerchberg-Saxton algorithm, modified Gerchberg-Saxton algorithm, input–output algorithm, Yang-Gu mixture amplitude-phase retrieval algorithm, and improved amplitude-phase retrieval algorithm. Simulations are executed to show the performance, feasibility, and robustness of the scheme. The gyrator parameter and private keys are highly sensitive to a small change to their original value. Performance of different phase retrieval algorithms on the scheme is evaluated using multi-attribute decision-making tool: TOPSIS method. Results suggest that the Yang-Gu mixture amplitude-phase retrieval algorithm performs better among phase retrieval algorithms and has ranked 1 in TOPSIS analysis. This has been validated by the figures reported in the paper. [ABSTRACT FROM AUTHOR]

The study focuses on the critical concern of designing secure and resilient bridge piers, especially regarding scour phenomena. Traditional equations for estimating scour depth are limited, often leading to inaccuracies. To address these shortcomings, modern data-driven models (DDMs) have emerged. This research conducts a comprehensive comparison involving DDMs, including support vector machine (SVM), gene expression programming (GEP), multilayer perceptron (MLP), gradient boosting trees (GBT) and multivariate adaptive regression spline (MARS) models, against two regression equations for predicting scour depth around cylindrical bridge piers. Evaluation employs statistical indices, such as root-mean-square error (RMSE), coefficient of determination (R2), mean average error (MAE) and normalized discrepancy ratio (S(DDRmax)), to assess their predictive performance. A total of 455 datasets from previous research papers are employed for assessment. Dimensionless parameters Froude number F r = U gy , Pier Froude number F r P = U g ′ D , and the ratio of scour depth to pier diameter (y D) are carefully selected as influential model inputs through dimensional analysis and the gamma test. The results highlight the superior performance of the SVM model. In the training phase, it exhibits an RMSE of 0.1009, MAE of 0.0726, R2 of 0.9401, and SDDR of 2.9237. During testing, the SVM model shows an RMSE of 0.023, MAE of 0.017, R2 of 0.984, and SDDR of 5.301. Additionally, it has an average error of − 0.065 and a total error of − 20.642 in the training set and an average error of − 0.005 and a total error of − 0.707 in the testing set. Conversely, the M5 model exhibits the lowest accuracy. The statistical metrics unequivocally establish the SVM model as significantly outperforming the experimental models, placing it in a higher echelon of predictive accuracy. [ABSTRACT FROM AUTHOR]

Low-value recyclable waste (LVRW) is an essential component of municipal domestic waste. Due to the lightweight and high quantity characteristics, the main disposal methods of LVRW are incineration and landfill, which are not conducive to the environmental protection requirements and the goal of carbon neutrality and emission peak. The paper focuses on the delicate separation of LVRW to realize a cost-effective solution for waste sorting. Firstly, a machine vision (MV) pneumatic sorting equipment was designed based on the MV detection system. Then, a large number of authentic waste images were captured and labeled to train a high accuracy LVRW prediction model through semi-automatic labeling and transfer learning. Subsequently, the LVRW waste sorting solution was designed and constructed, and a comparative experimental study about the MV sorting method and the whole solution was conducted. The experimental results show that the MV sorting method achieves 92% sorting accuracy, and the solution can dispose of 65 tons of LVRW per day with a waste recycling rate of 37.7%. The sorting equipment and solutions developed in the paper can effectively improve the resource utilization of LVRW at a lower cost. [ABSTRACT FROM AUTHOR]

This Special Section explores the interplay between Indigenous peoples, industry, and the state in five proposed and active mining projects in Canada and Sweden. The overall aim is to identify factors shaping the quality of Indigenous community-industry-state interactions in mining and mine development. An ambition underlying the research is to develop knowledge to help manage mining related land-use conflicts in Sweden by drawing on Canadian comparisons and experience. This paper synthesizes the comparative research that has been conducted across jurisdictions in three Canadian provinces and Sweden. It focuses on the interplay between the properties of the governance system, the quality of interaction and governance outcomes. We combine institutional and interactive governance theory and use the concept of governability to assess how and why specific outcomes, such as mutually beneficial interaction, collaboration, or opposition, occurred. The analysis suggests there are measures that can be taken by the Swedish Government to improve the governability of mining related issues, by developing alternative, and more effective, avenues to recognize, and protect, Sámi rights and culture, to broaden the scope and increase the legitimacy and transparency of the EIAs, to raise the quality of interaction and consultation, and to develop tools to actively stimulate and support collaboration and partnerships on equal terms. Generally, we argue that Indigenous community responses to mining must be understood within a larger framework of Indigenous self-determination, in particular the communities' own assessments of their opportunities to achieve their long-term objectives using alternative governing modes and types of interactions. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to explore the evolution behavior of two important laser features: the Bessel higher-order cosh-Gaussian beam and the Bessel higher-order sinh-Gaussian beam propagating through turbulent oceanic environments. Benefiting from the extended Huygens-Fresnel principle, the analytical formulas for the average intensity of the beams passing through oceanic turbulence are derived. The propagation of some laser beams through oceanic turbulence is also deduced as particular cases from the present study. The effects of oceanic turbulence parameters and the source beam parameters are examined to understand their influence on the intensity distribution of the considered beams by using numerical simulations. Our results show that the spreading of these beams depends on their initial parameters and oceanic parameters. Hence, the propagation of the studied beams through oceanic turbulent will be faster with the smaller dissipation rate of the mean square temperature, larger salinity fluctuations, higher rate of dissipation of turbulent kinetic energy per unit mass of fluid and with decreasing the beam width and the parameter Ω . The outputs of this study have useful applications in optical underwater communication, remote sensing, imaging and others. [ABSTRACT FROM AUTHOR]

Accurate hydrological modeling is crucial for water resources management. Process-based models (PBMs) are physically interpretable yet cannot fully utilize large datasets. Deep learning models, especially Long Short-Term Memory (LSTM) networks, have exhibited remarkable simulation accuracy but lack physical interpretability. To integrate the strengths of PBMs and LSTM, this paper develops three hybrid models (HLUDC, HLBDC, and HLBDCT) by coupling LSTM with the HBV model. HLUDC incorporates the output of HBV into LSTM to enhance modeling capability. HLBDC connects the HBV model to an LSTM that estimates the parameters of HBV. HLBDCT further introduces time-varying parameters. Notably, the possible limitation of these models in data-scarce basins is unclear, as all models are trained with available observations. Therefore, we further evaluate the impact of the training data length on model stability. The hybrid models are applied to the daily streamflow simulation in the Jialing River Basin. The results indicate that the hybrid models effectively enhance streamflow simulation compared to benchmark models. HLBDCT performs the best with a 2.44%-13.43% improvement in Nash-Sutcliffe efficiency coefficient over HBV and LSTM, followed by HLBDC, while HLUDC performs the least. HLBDCT also performed well in simulating extreme flow. Both HLBDCT and HLBDC accurately estimate actual evapotranspiration without being trained on it, demonstrating their robust physical coherence. Furthermore, HBV, HLBDC, and HLBDCT exhibit higher stability when trained with different lengths of data compared to HLUDC and LSTM. Overall, this study provides a better understanding of the potential for using hybrid models to enhance hydrological simulation accuracy. [ABSTRACT FROM AUTHOR]

Forecasting the transmission patterns of infectious diseases is of paramount importance in gaining valuable insights into outbreak growth and optimizing the allocation of medical resources. In this paper, we conduct a comparative study between a physics-based model and a machine learning (ML) model for epidemic forecasting and countermeasures, considering criteria such as accuracy and practicality. We develop four ML models: back-propagation (BP), long short-term memory, support vector machine, and extreme learning machine. In addition, we propose a reaction-diffusion (R-D) model that incorporates factors such as susceptibility heterogeneity, lockdown measures, population movement, and dynamically dependent rates. The experimental results highlight the superior accuracy of the BP model for forecasting, while the R-D model provides comprehensive insights into disease dynamics, including stability and potential control strategies. [ABSTRACT FROM AUTHOR]

In the context of regional integration, it is more than crucial to compare and analyze the spatial correlation network structure and formation mechanism of high-quality economic development in the Yangtze River Economic Belt and the Yellow River Basin urban cities as an attempt to strengthen collaborative work on high-quality economic development in both river basins. The paper measured high-quality economic development of the Yangtze River Economic Belt and the Yellow River Basin from 2010 to 2021. Then, it employed social network analysis and the QAP method to study the network structure's characteristics and formation mechanism. The conclusion of the research illustrates a few points clearly that first, the high-quality economic development of the two rivers presents a complex and multithreaded network structure. Although the network structure is hold at a comparatively stable state, the correlation degree needs improvement. Second, cities such as Chongqing, Wuhan, Hefei, Nanjing, Hangzhou, Shanghai, and Changsha and cities like Zhengzhou, Xi'an, Luoyang, Yulin, Hulunbuir, Ordos, and Nanyang are at the very central as well as central position of the network. The spatial correlation networks of the Yangtze River Economic Belt and the Yellow River Basin can be divided into four plates: "agent plate," "main outflow plate," "bidirectional spillover plate," and "main inflow plate." Third, reverse geographical distance and differences in the digital economy attach great significance to the spatial correlation networks of the two basins. The difference in urbanization level makes significant impacts only on the spatial correlation network of the Yangtze River Economic Belt, while the difference in environmental regulation and material capital accumulation only significantly influences the spatial correlation network of the Yellow River Basin. [ABSTRACT FROM AUTHOR]

This article intended to compare the discrimination perceived, respectively, by Muslim and non-Muslim immigrants in Europe, and investigate its determinants. Data covered six European Social Surveys and fourteen countries. The study found that the perception of being discriminated against is much more widespread among Muslim immigrants. The paper also found vast demo-socioeconomic heterogeneities between Muslim and non-Muslim immigrants. Consequently, the hypothesis was advanced that those heterogeneities were responsible for the discrimination differential between the two groups. In order to test this hypothesis, the present study used a statistical decomposition model rather than the procedures usually employed to analyse perceived discrimination. It emerged that demo-socioeconomic dissimilarities (in age, education, unemployment, income etc.) between Muslim and non-Muslim immigrants do not explain their gap in perceived discrimination. Nor is the gap eliminated by controlling for the host country's features, economic conditions and native hostility included. Instead, it emerged that identical individual traits—such as second generation, age, and income—are accompanied by opposite outcomes of perceived discrimination in the two groups. These divergent outcomes, in turn, are associated with deep-rooted characteristics of the immigrants' cultural identity. These findings suggest that these characteristics can be more impactful than the immigrants' socioeconomic status and the host country's features and that, ultimately, immigrants' shared in-group values play a more prominent role in the discrimination perceived by ethnic-religious groups than usually assumed by current literature. [ABSTRACT FROM AUTHOR]

There were 9.7 million Native Americans (American Indian, Alaska Native-AI/AN- these acronyms will be used interchangeably with Native Americans throughout the paper) in 2019 comprising 2.9% of the U.S. population. Native American populations have disproportionately higher rates of mental illnesses compared to other racial groups in the U.S. Mental health is a significant public health concern for this population, impacting different areas of their lives including employment. Additionally, Native Americans continue to experience significant disparities in access to Vocational Rehabilitation (VR) services and have poor employment outcomes. However, little is known about the relationships among demographic factors, vocational rehabilitation services, and employment outcomes of Native Americans with mental illness. Consequently, the current study examined how demographic factors and VR services are related to successful employment outcomes for Native American VR clients with mental illnesses using data from the Rehabilitation Services Administration (RSA) program year (2019) Case Service Report (9–11). Both descriptive analysis and data mining approaches were used to answer the research questions. Chi-square Automatic Interaction Detector (CHAID) analysis was used to determine which of the VR services could best predict the successful employment outcome of Native Americans with mental illness. The findings of the data mining approach revealed that among all the vocational rehabilitation services, job placement assistance was the strongest predictor of successful employment among Native American clients with mental illnesses. The second most important service predicting successful employment for those who received job placement assistance was shown to be maintenance. Implications for rehabilitation counselors and future research are discussed. [ABSTRACT FROM AUTHOR]

This study addresses the challenge of deformation and failure on loess slopes, predominantly triggered by rainfall, by evaluating the efficacy of various slope protective measures. Recognizing the escalating preference for ecological protection techniques, this paper focuses on identifying optimal strategies that align with local rainfall patterns. A comprehensive analysis of loess slopes under diverse rainfall conditions was conducted, encompassing scenarios with prime soil, stabilized soil, and no protection. Utilizing the finite element software ABAQUS, a sophisticated rainfall infiltration slope model was developed and validated against experimental data. The investigation reveals that under low rainfall intensities, the choice of protective material—whether stabilized or prime soil—exerts limited influence on slope pore pressure. In contrast, at higher rainfall intensities, the impact of these protective materials on slope stability becomes significantly more pronounced. [ABSTRACT FROM AUTHOR]

This paper addresses terminological consistency issues of three software testing glossaries used in academia and industry. The evaluation focus mainly deals with a sub-characteristic of information quality such as consistency, which includes syntactic and semantic consistency. To systematically conduct this study, we have established a set of activities or steps. These include defining the evaluation goal and scope, selecting the glossaries, conceiving the terminological categories, classifying the glossary terms into categories, calculating syntactic and semantic similarities, analyzing consistency, and making recommendations. For instance, for the testing domain, eight terminological categories were conceived, in which, for each selected glossary, a corresponding term is included in a category, considering the semantics intended by the authors of these standard documents. To count the occurrence frequency of a term in the glossaries, a tool was built that also takes into account the matching of synonyms. Then, a comparative analysis of syntactic and semantic consistency was carried out for all the terms ending in the word "testing," which enables us to give recommendations. This exploratory study identifies some inconsistencies that might deserve further attention and efforts to promote agreement and harmonization among the authors/editors of these glossaries in order to provide their readers with the most consistent and easiest way to understand and learn software testing concepts. [ABSTRACT FROM AUTHOR]

K-means is one of the most algorithms used in unsupervised machine learning. Numerous metrics are adapted to k-means for estimating the optimal number of clusters k-optimal. In this paper, a comparative study is carried out to select similarities and contrast the differences between four clustering metrics: weighted sum of squares, Calinski–Harabasz index, Rao diversity index, and Silhouette method. Data normalization's effect was also assessed in this work. To illustrate the methodology, six 2D-datasets were studied and labelled 'likely Gaussian' and 'non-Gaussian' depending on how data are distributed within their domain of definition; this characteristic was assigned as data shape. Hence, k-means clustering was carried out before and after normalization; the adopted metrics were then computed and k-optimal were selected for each combination. Results showed that the accuracy of the clustering, regarding the known optimal clusters, is very sensitive to the interplay between the components of threefold {dataset distribution, normalization form, and metrics/method}. Among several remarks, it was statistically proved that likely Gaussian datasets showed quite negligible RMSE values compared to the non-Gaussian datasets; diversity index was well adapted to the two data shapes; WSS-elbow method reached an appreciable level of accuracy for non-Gaussian ones; Silhouette and Calinski–Harabasz scores were highly sensitivity to data shape compared to normalization forms. In another hand, normal standardization improved the accuracy of clustering especially for likely Gaussian data. Finally, this experimental study proved that a pre-analysis of data according to data shape and normalization should be considered before the adoption of a clustering method/metrics. [ABSTRACT FROM AUTHOR]

Popular Secp256k1 and Schnorr algorithms offer strong security in current Blockchains. However, they are vulnerable to quantum attacks. To solve this problem, several quantum-resistant algorithms have been proposed. However, the performance evaluations and tangible analyses of these algorithms on current Blockchains have not been studied yet. In this context, a performance analysis of quantum-resistant algorithms on a Blockchain can provide valuable insight into the efficiency of quantum-resistant algorithms in real-world scenarios. To address this need, we prototyped and analyzed a quantum-resistant Blockchain using the Falcon algorithm. Falcon is selected because it provides smaller signature and key size compared to Crystals-Dilithium and Sphincs+. We then measured in real-time the key size, transaction signature size, and transaction verification time. The paper also discusses the potential scalability limitations of the proposed quantum-resistant Blockchain and suggests an approach to select quantum-resistant algorithms based on different Blockchain use cases. Our approach and benchmark results have implications for the future development and adoption of quantum-resistant Blockchains. [ABSTRACT FROM AUTHOR]

Background: Spontaneous reporting of adverse drug reactions (ADRs) is essential for the post-marketing safety evaluation of drugs. Therefore, good monitoring of ADRs is vital for strengthening drug supervision, management, and guiding rational drug use. Chinese medical institutions are the primary source of ADR case reports, but the proportion of the reports in grade IIIA hospitals is still low due to serious under-reporting. The 3rd Affiliated Hospital of Chengdu Medical College, Chengdu Pidu District People's Hospital, also has such a problem. Objective: To improve the quantity and quality of ADR reports and enhance the level of pharmacovigilance in hospitals, the Third Affiliated Hospital of Chengdu Medical College, People's Hospital of Chengdu Pidu District experienced 10 years to gradually establish a management model to improve the medical staff's reporting rate of spontaneous reporting of ADRs. The management model is led by clinical pharmacists and combines the PDCA with Teach-back methods. The purpose of this paper is to introduce the management model and discuss its advantages and shortcomings of this model. Methods: This study was conducted at the Third Affiliated Hospital of Chengdu Medical College—Chengdu Pidu District People's Hospital. From 2016, the daily management of reporting, auditing, and data improvement of adverse drug reactions in the hospital was carried out by clinical pharmacists, who used the PDCA method combined with the Teach-back method to continuously improve the reporting program of ADRs in the hospital during 2016–2021. Then, the proportion of spontaneous reports of total, new, and serious ADRs was compared before and after the intervention. Also, we performed a time series analysis using an autoregressive moving average model to assess changes in the total number of spontaneous ADR reports before the intervention (2013–2015), the first intervention (2016–2018), and the second intervention (2019–2021). Results: After the combined PDCA and Teach-back method intervention, the median number of reported ADRs per year increased from 50 (range 37–55) in the pre-intervention period to 88 (range 83–162) in the first intervention period and to 374 in the second (range 312–566). Breakpoint regression analysis of the spontaneous reporting rate of ADRs showed that the instantaneous increase after the first intervention was not statistically significant (P = 0.526). However, the reporting rate of ADRs increased at a month-by-month growth rate during the second intervention compared to the first intervention. Its spontaneous reporting rate improved 1.034 times (P = 0.002). After the second intervention, the spontaneous reporting rate of ADRs transiently increased 6.111-fold (P < 0.001), and the month-to-month growth rate increased 1.024-fold (P < 0.001) again. Conclusion: The management model that combines the PDCA and the Teach-back method significantly improves the reporting rate of adverse drug reactions. [ABSTRACT FROM AUTHOR]

Limited diversity is a term employed in the context of Ragin's Qualitative Comparative Analysis (QCA), but it describes a phenomenon which is widespread in social contexts: cases are usually not distributed evenly across all the possible combinations of factors linked to some outcome. Instead, they are often clustered together. To deal with limited diversity, the three solution types parsimonious, intermediate, and complex (or conservative) solution have been proposed. There is an ongoing debate as to the merits of each solution type. This paper contributes to the debate by focussing on what the implications of choosing each solution type are. In making this choice, researchers have to make certain assumptions, and the paper discusses what these are and how they vary depending on which solution type is being implemented, drawing on invented examples and examples from published work to bring out the consequences of these assumptions. It concludes that it is not obvious that any one solution type is superior, certainly not to the degree that the others always have to be ruled out. They rely on different kinds of assumptions and models of causation. Thus, depending on the research situation, it may be helpful to analyse different scenarios, including one(s) where we assume that our initial assumptions are wrong. Ideally, researchers are able to take steps to reduce or eliminate limited diversity since none of the existing solution types are without problems. However, since this is not always possible, it is best to be aware of the consequences of choices. [ABSTRACT FROM AUTHOR]

Effective learning depends on effective feedback, which in turn requires a set of skills, dispositions and practices on the part of both students and teachers which have been termed feedback literacy. A previously published teacher feedback literacy competency framework has identified what is needed by teachers to implement feedback well. While this framework refers in broad terms to the potential uses of educational technologies, it does not examine in detail the new possibilities of automated feedback (AF) tools, especially those that are open by offering varying degrees of transparency and control to teachers. Using analytics and artificial intelligence, open AF tools permit automated processing and feedback with a speed, precision and scale that exceeds that of humans. This raises important questions about how human and machine feedback can be combined optimally and what is now required of teachers to use such tools skillfully. The paper addresses two research questions: Which teacher feedback competencies are necessary for the skilled use of open AF tools? and What does the skilled use of open AF tools add to our conceptions of teacher feedback competencies? We conduct an analysis of published evidence concerning teachers' use of open AF tools through the lens of teacher feedback literacy, which produces summary matrices revealing relative strengths and weaknesses in the literature, and the relevance of the feedback literacy framework. We conclude firstly, that when used effectively, open AF tools exercise a range of teacher feedback competencies. The paper thus offers a detailed account of the nature of teachers' feedback literacy practices within this context. Secondly, this analysis reveals gaps in the literature, signalling opportunities for future work. Thirdly, we propose several examples of automated feedback literacy, that is, distinctive teacher competencies linked to the skilled use of open AF tools. [ABSTRACT FROM AUTHOR]

To address environmental problems, efforts to green financial systems are proliferating across the globe. However, green finance policy approaches differ substantially and in ways left unexplained in current literature. Focusing on the EU and China as the most active and influential in green finance, the paper provides a comparative analysis and conceptualization of their approaches. The analysis is based on the dissection of policy documents, a review of stakeholder statements and articles, and insights from semi-structured interviews and participant observation. The paper finds that in terms of similar characteristics, both parties seek inclusive expertise input, establish thematic committees, and initiate green finance efforts through financial system-wide guidelines. In terms of different characteristics, the paper finds that through a consultation-based, transparent, and limited mandate approach, the EU is characterized by longer time horizons and organic growth. This can be contrasted with the Chinese technocratic, closed-door, and non-limited mandate approach, characterized by rapid rollout and command-and-control growth. These findings can be conceptualized as a bottom-up market-facilitating approach in the EU and a top-down market-steering approach in China. The different approaches help explain current difficulties in coordination between the EU and China and imply that cooperation is only possible through compatibility rather than harmonization. The findings show that different governance models can actively use the state to pursue sustainable development, and second that such an active state can function in very different ways towards the same goals. [ABSTRACT FROM AUTHOR]

Background: The study tests the effects of data collection modes on patient responses associated with the multi-item measures such as Patient-Reported Outcomes Measurement System (PROMIS®), and single-item measures such as Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (PRO-CTCAE), and Numerical Rating Scale (NRS) measures. Methods: Adult cancer patients were recruited from five cancer centers and administered measures of anxiety, depression, fatigue, sleep disturbance, pain intensity, pain interference, ability to participate in social roles and activities, global mental and physical health, and physical function. Patients were randomized to complete the measures on paper (595), interactive voice response (IVR, 596) system, or tablet computer (589). We evaluated differential item functioning (DIF) by method of data collection using the R software package, lordif. For constructs that showed no DIF, we concluded equivalence across modes if the equivalence margin, defined as ± 0.20 × pooled SD, completely surrounds 95% confidence intervals (CI's) for difference in mean score. If the 95% CI fell totally outside the equivalence margin, we concluded systematic score difference by modes. If the 95% CI partly overlaps the equivalence margin, we concluded neither equivalence nor difference. Results: For all constructs, no DIF of any kind was found for the three modes. The scores on paper and tablet were more comparable than between IVR and other modes but none of the 95% CI's were completely outside the equivalence margins, in which we established neither equivalence nor difference. Percentages of missing values were comparable for paper and tablet modes. Percentages of missing values were higher for IVR (2.3% to 6.5% depending on measures) compared to paper and tablet modes (0.7% to 3.3% depending on measures and modes), which was attributed to random technical difficulties experienced in some centers. Conclusion: Across all mode comparisons, there were some measures with CI's not completely contained within the margin of small effect. Two visual modes agreed more than visual-auditory pairs. IVR may induce differences in scores unrelated to constructs being measured in comparison with paper and tablet. The users of the surveys should consider using IVR only when paper and computer administration is not feasible. [ABSTRACT FROM AUTHOR]

Pairwise comparisons have been a long-standing technique for comparing alternatives/criteria and their role has been pivotal in the development of modern decision-making methods such as the Analytic Hierarchy/Network Process (AHP/ANP), the Best-Worst method (BWM), PROMETHEE and many others. Pairwise comparisons can be performed within several frameworks such as multiplicative, additive and fuzzy representations of preferences, which are particular instances of a more general framework based on Abelian linearly ordered groups. Though multiplicative, additive and fuzzy representations of preferences are widely used in practice, it is unknown whether decision makers are equally precise in the three aforementioned representations when they measure objective data. Therefore, the aim of this paper is to design, carry out and analyse an experiment with over 200 respondents (undergraduate university students) from two countries, Czechia and Italy, to compare precision of the respondents in all three representations. In the experiment, respondents pairwise compared (by approximation) the areas of four geometric figures and then, the imprecision of their assessments was measured by computing the distance with the exact pairwise comparisons. We grouped the respondents in such a way that each participant was allowed to deal with a unique type of representation. The outcomes of the experiment indicate that the multiplicative approach is the most precise. [ABSTRACT FROM AUTHOR]

Drilling the oil and gas well is the most important job for finding the hydrocarbon resources below the earth. Many risks/complexities are involved in fulfilling this complex job. Oil and gas well drilling companies are using different types of key performance indicators (KPIs) to measure the performance of the drilling operations, for example, time versus depth, rate of penetration, non-productive time, etc. There is no standardization or benchmarking available for comparing these KPIs. Drilling companies are using different references for these KPIs as per their policies or norms. This research paper presents the application of the well complexity calculator, which is developed on a broader range of parameters to calculate different types of complexities. These complexities can be used as a standardized reference and the KPIs are compared with them. For this purpose, drilled wells camouflaged data obtained from different oil and gas well drilling companies in Pakistan, which were used to measure their complexities by the well complexity calculator. Accordingly, relationships of these complexities are presented against different industry-wide used Drilling KPIs achieved on the wells, like Dry Hole Drilling Days, Feet per Day, Dry Hole Drilling Days per 10 K Feet, Dry Hole Drilling Cost, NPT Percentage, and Non-Productive Time (NPT). It is found that with the increase of well complexities, all the KPIs showed an increase/decrease in specific trends; except NPT Percentage, this trend verifies the authenticity of the well complexity calculator. NPT Percentage did not show any relationship against the well complexities, although it is one of the widely used Drilling KPIs. Besides this, a comparison of one of the Absolute Drilling KPIs "Dry Hole Drilling Cost" and one of the Normalized Drilling KPI "Dry Hole Drilling Cost Per Foot" is also compared against the well complexities, and trends confirm that the use of such normalized KPI alone is only acceptable when design and all the properties of the Wells are similar, which is usually not the case. It is also found that instead of using NPT Percentage or single-factor normalized KPIs, Absolute Drilling KPIs like Non-Productive Time recorded in hours, Dry Hole Drilling Days, and Dry Hole Drilling Cost vs Well Complexities are better tools to compare the performance of the Wells, since the ratio of output is not taken against the single-input parameter like depth but instead against the combination of different types of parameters. Based on Complexities vs the KPI relationship, an improved modular approach is presented to carry out KPI benchmarking and performance evaluation and comparison. [ABSTRACT FROM AUTHOR]

The aim of the paper is to carry out a comparative engineering-geological study of four different waste landfills using the evaluation criteria for the geological subsoil as a natural sealing barrier. The study evaluates 4 localities (Velké Pavlovice, Kvítkovice, Prakšice and Horní Suchá) using three variants (based on two standards) which approach the geological barrier requirements as a combination of impermeability requirements based on a filtration coefficient limit value. and the required geometry represented by investigation depths. The research was carried out in landfills in Moravia, in the east of the Czech Republic. The study's motivation is to point at the differences in engineering-geological investigations of waste landfills (as for the requirements for impermeable geological subsoil as a natural sealing barrier) when compared with other engineering structures (where the main goal is to evaluate load-bearing capacity and settlement). The purpose of the geological barrier is to prevent the spread of contamination, and the paper shows this can be approached differently, as shown in two different methodologies investigated herein. The first model (Model 1) assumes there is a 3-m-thick subsoil below the landfill's footing bottom, which manifests impermeability characterized by the filtration coefficient Kf ≤ 1.0 * 10–9 m/s, or a 30-m-thick subsoil of Kf ≤ 1.0 * 10–8 m/s. The second model (Model 2) assumes a 1-m thick, impermeable subsoil massif of Kf ≤ 1.0 * 10–9 m/s. We found that none of the landfills in the four selected localities had an impermeable layer in the required depth (a filtration coefficient Kf from 1.8 * 10–9 to 3.9 * 10–9 m/s), and thus did not comply with the limiting conditions. As a result, an anthropogenic technical barrier had to be installed. An important goal of the study from an environmental point of view was to assess the existence of a suitable geological barrier under the proposed landfills. The most important criterion from this point of view is permeability. An additional technical objective of the project was also the assessment of the possible creation of a technical anthropogenic isolation barrier. In the event that the natural sealing barrier would not be sufficient. This was shown in all solved case studies of engineering geological investigations of waste landfills. [ABSTRACT FROM AUTHOR]

The filtering characteristics of the output filter directly determine the grid-connected performance and cost and volume of the grid-connected converter. Based on a deep analysis of harmonic attenuation characteristics of LCL-type and LLCL-type filters, a unified circuit model of the output filter was proposed in this paper. According to this model, the possible structures of filters below the fifth order are deduced, summarized, and compared, and two new filters, LLCLC_A type and LLCLC_B type, are proposed. A comparative study of these filters in terms of filter characteristics, impedance characteristics, parameter design, and resonant spike damping was carried out. The results show that the LLCLC_A-type filter has advantages over the other three filters. The LLCLC_A-type filter is named the LLCLC-type filter. Finally, both simulation and experimental results verify the correctness and effectiveness of the proposed LLCLC-type filter. The research in this paper is a guide to the design of a grid-connected converter output filter. [ABSTRACT FROM AUTHOR]

The popularization of Hadoop as the the-facto standard platform for data analytics in the context of Big Data applications has led to the upsurge of SQL-on-Hadoop systems, which provide scalable query execution engines allowing the use of SQL queries on data stored in HDFS. In this context, Kubernetes appears as the leading choice to simplify the deployment and scaling of containerized applications; however, there is a lack of studies about the performance of SQL-on-Hadoop systems deployed on Kubernetes, and this is the gap we intend to fill in this paper. We present an experimental study involving four representative SQL scalable platforms: Apache Drill, Apache Hive, Apache Spark SQL and Trino. Concretely, we analyze the performance of these systems when they are deployed on a Hadoop cluster with Kubernetes by using the TPC-H benchmark. The results of our study can help practitioners and users about what they can expect in terms of performance if they plan to use the advantages of Kubernetes to deploy applications using the analyzed SQL scalable platforms. [ABSTRACT FROM AUTHOR]

Works for children are filled with a myriad of creatures that are often used by writers to convey certain messages to the young readers/audiences. From tamed to wild, real and imaginary beings, such creatures emerge either as benevolent or evil forces. This study seeks to highlight the role of humorous, benevolent monsters in works for children showing how their presence is laden with meanings. For this purpose, two plays for children are selected: The Monsters under the Bed (2007) by Fr. Dominic Garramone and Osb and the St.Bede Theater Troupe, and The Boy Who Loved Monsters and the Girl Who Loved Peas (2013) by Jonathan Graham. Drawing upon humor studies, monster studies, and child psychology, the paper attempts to analyze the use of humor in portraying friendly monsters in the selected works reflecting how it is through them that the children protagonists revisit their views of monsters and understand that they are a reflection of themselves (their needs/fears). The analysis of these benevolent monsters and their effect on the protagonists will be carried out in relation to the different theatrical elements and the verbal and visual signs which clarify and affirm the benevolence of such creatures and the humorous touch added to their roles. [ABSTRACT FROM AUTHOR]

In a medical setting, observational studies commonly involve patients who initiate a particular treatment (e.g., medication therapy) and others who do not, and the goal is to draw causal inferences about the effect of treatment on a time-to-event outcome. A difficulty with such studies is that the notion of a treatment initiation time is not well-defined for the control group. In this paper, we propose a Bayesian approach to estimate treatment effects in longitudinal observational studies where treatment is given by indication and thereby the exact timing of treatment is only observed for treated units. We present a framework for conceptualizing an underlying randomized experiment in this setting based on separating the time of indication for treatment, which we model using a latent state-space process, from the mechanism that determines assignment to treatment versus control. Next, we develop a two-step inferential approach that uses Markov Chain Monte Carlo (MCMC) posterior sampling to (1) infer the unobserved indication times for units in the control group, and (2) estimate treatment effects based on inferential conclusions from Step 1. This approach allows us to incorporate uncertainty about the unobserved indication times which induces uncertainty in both the selection of the control group and the measurement of time-to-event outcomes for these controls. We demonstrate our approach to study the effects on mortality of inappropriately prescribing phosphodiesterase type 5 inhibitors (PDE5Is), a medication contraindicated for certain types of pulmonary hypertension, using data from the Veterans Affairs (VA) health care system. [ABSTRACT FROM AUTHOR]

This paper discusses continuum models for simulating earthquake sequences on faults governed by rate-and-state dependent friction. Through detailed numerical analysis of a conventional strike-slip fault, new observations regarding the use of various continuum earthquake models are presented. We update a recently proposed plasticity-based model using a consistently linearized formulation, show its agreement with discrete fault models for fault thicknesses of hundreds of meters, and demonstrate mesh objectivity for slip-related variables. To obtain a fully regularized fault width description with an internal length scale, we study the performance and mesh convergence of a plasticity-based model complemented by a Kelvin viscosity term and the phase-field approach to cohesive fracture. The Kelvin viscoplasticity-based model can introduce an internal length scale and a mesh-objective response. However, on grid sizes down to meters, this only holds for very high Kelvin viscosities that inhibit seismic slip rates, which renders this approach impractical for simulating earthquake sequences. On the other hand, our phase-field implementation for earthquake sequences provides a numerically robust framework that agrees with a discrete reference solution, is mesh objective, and reaches seismic slip rates. The model, unsurprisingly, requires highly refined grids around the fault zones to reproduce results close to a discrete model. Following this line, the effect of an internal length scale parameter on the phase-field predictions and mesh convergence are discussed. [ABSTRACT FROM AUTHOR]

Aim: The aim of the paper is to enhance understanding of how members of the public make sense of the Covid-19 vaccines and to understand the factors influencing their attitudes towards such artefacts of pandemic governance. Methods: The paper draws on 23 online in-depth interviews with members of the UK public and builds on relevant literature to examine participants' perceptions of the benefits and risks of Covid-19 vaccines, the sources that have shaped their attitudes, and the level of trust they have towards the government's handling of the pandemic through vaccines. Results: The findings indicate that participants generally felt that the benefits of having the vaccine outweigh the risks and that Covid-19 vaccines are a crucial mechanism for enabling society to return to normal. Vaccine acceptance was, for some, strongly linked to a sense of social responsibility and the duty to protect others. However, some participants expressed concerns with regard to the side-effects of Covid-19 vaccines and their perceived potential impact on fertility and DNA makeup. Participants used various sources of information to learn about Covid-19 vaccines and understand their function, benefits, and risks. The majority of participants criticised the government's response during the early stages of the pandemic yet felt positive about the vaccine rollout. Conclusion: Just as with any other vaccination programme, the success of the Covid-19 immunisation campaigns does not only depend on the efficacy of the vaccines themselves or the ability to secure access to them, but also on a myriad of other factors which include public compliance and trust in governments and health authorities. To support an effective immunisation campaign that is capable of bringing the pandemic to an end, governments need to understand public concerns, garner trust, and devise adequate strategies for engaging the public and building more resilient societies. [ABSTRACT FROM AUTHOR]

High-temperature open tube furnaces are essential in semiconductor manufacturing process. This type of equipment requires periodic servicing for operational longevity and to comply with the requirements of microelectronics processes. This paper presents a comparative analysis of Proportional–Integral (PI) and Fuzzy-PI algorithms for controlling a three-zone open tube furnace. Initially, the furnace was identified using an AutoRegressive eXogenous (ARX) model. The model was tested using a cross-validation method with 10-steps-ahead prediction tests. The prediction showed results higher than 93.70% with Final Prediction Error (FPE) lower than 0.0007. The controllers were simulated and their parameters were tuned using the identified model. The tuned algorithms were implemented through a PC-based instrumentation in real-time. The Fuzzy-PI controller presented the best results regarding the steady-state error, controlling the temperature of the furnace with a variation less than ± 1.06 ∘ C in the flat zone at the process temperature of 900 ∘ C with fast settling time. This innovative result presents a major step toward the modernization of high-temperature furnaces to meet the growing demands in the electronics industry. [ABSTRACT FROM AUTHOR]

Low-dose computed tomography (LDCT) is an effective way to reduce radiation exposure for patients. However, it will increase the noise of reconstructed CT images and affect the precision of clinical diagnosis. The majority of the current deep learning-based denoising methods are built on convolutional neural networks (CNNs), which concentrate on local information and have little capacity for multiple structures modeling. Transformer structures are capable of computing each pixel's response on a global scale, but their extensive computation requirements prevent them from being widely used in medical image processing. To reduce the impact of LDCT scans on patients, this paper aims to develop an image post-processing method by combining CNN and Transformer structures. This method can obtain a high-quality images from LDCT. A hybrid CNN-Transformer (HCformer) codec network model is proposed for LDCT image denoising. A neighborhood feature enhancement (NEF) module is designed to introduce the local information into the Transformer's operation, and the representation of adjacent pixel information in the LDCT image denoising task is increased. The shifting window method is utilized to lower the computational complexity of the network model and overcome the problems that come with computing the MSA (Multi-head self-attention) process in a fixed window. Meanwhile, W/SW-MSA (Windows/Shifted window Multi-head self-attention) is alternately used in two layers of the Transformer to gain the information interaction between various Transformer layers. This approach can successfully decrease the Transformer's overall computational cost. The AAPM 2016 LDCT grand challenge dataset is employed for ablation and comparison experiments to demonstrate the viability of the proposed LDCT denoising method. Per the experimental findings, HCformer can increase the image quality metrics SSIM, HuRMSE and FSIM from 0.8017, 34.1898, and 0.6885 to 0.8507, 17.7213, and 0.7247, respectively. Additionally, the proposed HCformer algorithm will preserves image details while it reduces noise. In this paper, an HCformer structure is proposed based on deep learning and evaluated by using the AAPM LDCT dataset. Both the qualitative and quantitative comparison results confirm that the proposed HCformer outperforms other methods. The contribution of each component of the HCformer is also confirmed by the ablation experiments. HCformer can combine the advantages of CNN and Transformer, and it has great potential for LDCT image denoising and other tasks. [ABSTRACT FROM AUTHOR]

Background: The effects of hypoxia conditioning, which involves recurrent exposure to hypoxia combined with exercise training, on improving body composition in the ageing population have not been extensively investigated. Objective: This meta-analysis aimed to determine if hypoxia conditioning, compared to similar training near sea level, maximizes body composition benefits in middle-aged and older adults. Methods: A literature search of PubMed, EMBASE, Web of Science, Scopus and CNKI (China National Knowledge Infrastructure) databases (up to 27th November 2022) was performed, including the reference lists of relevant papers. Three independent reviewers extracted study characteristics and health outcome measures. Search results were limited to original studies of the effects of hypoxia conditioning on body composition in middle-aged and older adults. Results: Twelve studies with a total of 335 participants were included. Hypoxia conditioning induced greater reductions in body mass index (MD = -0.92, 95%CI: -1.28 to -0.55, I2 = 0%, p < 0.00001) and body fat (SMD = -0.38, 95%CI: -0.68 to -0.07, I2 = 49%, p = 0.01) in middle-aged and older adults compared with normoxic conditioning. Hypoxia conditioning improved lean mass with this effect not being larger than equivalent normoxic interventions in either middle-aged or older adults (SMD = 0.07, 95%CI -0.12 to 0.25, I2 = 0%, p = 0.48). Subgroup analysis showed that exercise in moderate hypoxia (FiO2 > 15%) had larger effects than more severe hypoxia (FiO2 ≤ 15%) for improving body mass index in middle-aged and older adults. Hypoxia exposure of at least 60 min per session resulted in larger benefits for both body mass index and body fat. Conclusion: Hypoxia conditioning, compared to equivalent training in normoxia, induced greater body fat and body mass index improvements in middle-aged and older adults. Adding hypoxia exposure to exercise interventions is a viable therapeutic solution to effectively manage body composition in ageing population. Key Points: A meta-analysis was conducted to evaluate the effects of hypoxia conditioning on body composition in middle-aged and older adults. Compared to normoxic equivalent, hypoxia conditioning provides greater reductions in body fat and body mass index. However, the magnitude of improvement in lean mass was not greater in hypoxic than normoxic conditions. Hypoxia conditioning of at least 60 minutes per session in moderate hypoxia (FiO2 > 15%) is a promising intervention to improve body composition in middle-aged and older adults. [ABSTRACT FROM AUTHOR]

This paper proposes to analyse user experience using two different immersive device categories: a cave automatic virtual environment (CAVE) and a head-mounted display (HMD). While most past studies focused on one of these devices to characterize user experience, we propose to fill the gap in comparative studies by conducting investigations using both devices, considering the same application, method and analysis. Through this study, we want to highlight the differences in user experience induced when using either one of these technologies in terms of visualization and interaction. We performed two experiments, each focusing on a specific aspect of the devices employed. The first one is related to distance perception when walking and the possible influence of the HMD's weight, which does not occur with CAVE systems as they do not require wearing any heavy equipment. Past studies found that weight may impact distance perception. Several walking distances were considered. Results revealed that the HMD's weight does not induce significant differences over short distances (above three meters). In the second experiment, we focused on distance perception over short distances. We considered that the HMD's screen being closer to the user's eyes than in CAVE systems might induce substantial distance perception differences, especially for short-distance interaction. We designed a task in which users had to move an object from one place to another at several distances using the CAVE and an HMD. Results revealed significant underestimation compared to reality as in past work, but no significant differences between the immersive devices. These results provide a better understanding of the differences between the two emblematic virtual reality displays. [ABSTRACT FROM AUTHOR]

Background: While the literature suggests a correlation between posterior tibial slope and sagittal stability of the knee, there is a lack of consensus relating to how to measure the slope, what a normal slope value would be, and which critical values should guide extra surgical treatment. We performed a systematic literature review looking at the posterior tibial slope and cruciate ligament surgery. Our aims were to define a gold standard measurement technique of posterior tibial slope, as well as determining its normal range and the important values for consideration of adjuncts during cruciate ligament surgery. Methods: Electronic searches of MEDLINE (PubMed), CINAHL, Cochrane, Embase, ScienceDirect, and NICE in June 2020 were completed. Inclusion criteria were original studies in peer-reviewed English language journals. A quality assessment of included studies was completed using the Methodological Index for Non-Randomized Studies (MINORS) Criteria. Results: Two-hundred and twenty-one papers were identified; following exclusions 34 papers were included for data collection. The mean MINORS score was 13.8 for non-comparative studies and 20.4 for comparative studies, both indicating fair to good quality studies. A large variation in the posterior tibial slope measurement technique was identified, resulting in a wide range of values reported. A significant variation in slope value also existed between different races, ages and genders. Conclusion: Cautiously, the authors suggest a normal range of 6-12º, using the proximal tibial axis at 5 and 15 cms below the joint. We suggest 12º as a cut-off value for slope-reducing osteotomy as an adjunct to revision ligament reconstruction. [ABSTRACT FROM AUTHOR]

The proliferation of semantic data in the form of Resource Description Framework (RDF) triples demands an efficient, scalable, and distributed storage along with a highly available and fault-tolerant parallel processing strategy. There are three open issues with distributed RDF data management systems that are not well addressed altogether in existing work. First is the querying efficiency, second is that solutions are optimized for certain types of query patterns and don't necessarily work well for all types, and third is concerned with reducing pre-processing cost. More precisely, the rapid growth of RDF data raises the need for an efficient partitioning strategy over distributed data management systems to improve SPARQL (SPARQL Protocol and RDF Query Language) query performance regardless of its pattern shape with minimized pre-processing time. In distributed RDF systems, both the data and the query processing are highly distributed. On the other hand, SPARQL workloads are dynamic and structurally diverse that can have different degrees of complexity. A complex SPARQL query over a large RDF graph in distributed systems requires combining a lot of distributed pieces of data through join operations. Therefore, designing an efficient data-partitioning schema and join strategy to minimize data transfer is the fundamental challenge in distributed RDF data management systems. In this context, we propose a new relational partitioning schema called Property Table Partitioning (PTP) for RDF data, that further partitions existing Property Table into multiple tables based on distinct properties (comprising of all subjects with non-null values for those distinct properties) in order to minimize input size and number of join operations of a query. This paper proposed a distributed RDF data management system called S3QLRDF, which is built on top of Spark and utilizes SQL to execute SPARQL queries over PTP schema. The experimental analysis with respect to preprocessing costs and query performance, using synthetic and real datasets shows that S3QLRDF outperforms state-of-the-art distributed RDF management systems. [ABSTRACT FROM AUTHOR]

This paper studied the multilevel threshold image segmentation-based metaheuristics optimization methods and their applications. Image segmentation is a common problem in the image processing domain, and it is an essential process in image analysis, directly impacting image analysis results. Thresholding is one of the most manageable and extensively utilized methods for handling image segmentation problems. In this paper, four main parts are given; (1) We present the main procedures and definitions of the multilevel threshold image segmentation problem. The standard fitness function and the evaluation criteria are also given to facilitate the problem representation for the new researchers in this domain. (2) All the related works that have used optimization methods in solving the multilevel threshold image segmentation problems are presented in more detail, focusing on the image segmentation problem and its solutions. The given related works are outlined according to the used algorithms. (3) Comprehensive results and analysis of several well-known optimization algorithms are conducted to solve the multilevel threshold image segmentation problems. These comparative methods include Aquila Optimizer (AO), Whale Optimization Algorithm (WOA), Salp Swarm Algorithm (SSA), Arithmetic Optimization Algorithm (AOA), Particle Swarm Optimizer (PSO), Marine Predators Algorithm (MPA), Krill Herd Algorithm (KHA), Multi-verse Optimizer (MVO), and Gray Wolf Optimizer (GWO). Eight standard benchmark images are used to test the comparative methods. The results are evaluated using three standard measures: fitness function, PeakSignal-to-Noise Ratio (PSNR), and the Structural Similarity Index (SSIM). (4) Discussion, open challenging, and new trends are given to help the scholars in future research get near the common problems and defect in that domain. The collected data in this review has been taken from google scholar using the stander search method. The main keywords that have been used in the search are multilevel, threshold, image, segmentation, optimization, and algorithm. We covered all the published papers in detail according to the given information, focusing on finding the common problems that still need further investigation. Furthermore, future research directions based on recently evolving designs are outlined, which should undoubtedly aid current researchers and practitioners and pave the way for new researchers interested in multilevel threshold image segmentation to seek their research in the field. [ABSTRACT FROM AUTHOR]