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Highlights • Mechanical properties of waste papers are closely correlated with devolatilization. • Start of devolatilization caused a sudden decrease in relative storage modulus ( E ′ r). • Kinetics of storage modulus change is investigated referring to activation energy. • E ′ r can be predicted with mass loss ratio and CO 2 emission. Abstract This article details a correlation study on early devolatilization behaviors (drying & volatile emission at 25–240 °C) and the change in mechanical properties (expressed by viscoelasticity) of four types of waste papers. The early stage of devolatilization was investigated using the TG-FTIR and mechanical properties using the dynamic mechanical analysis (DMA) method. The results show that the elastic and viscous mechanical properties showed obvious correlations with free and bound water evaporation and volatile emission. The storage modulus (E ′) and loss modulus (E ″) of the papers decreased as temperature increased and at the two important temperatures, namely 100 °C, the start of bound water evaporation, and 150 °C, the start of devolatilization in TG & DTG curves, E ′ showed extrema. Especially the relative storage modulus ( E ′ r) exhibited a sudden decrease at around 150 °C, where the activation energy of thermochemical conversion jumps from low values to high values, indicating the start of devolatilization. CO 2 is the major compound of the volatiles and it is well correlated with E ′ r in exponential function model and can be used as an index for predicting the E ′ r of the waste papers in their early devolatilization stage; while during the drying stage, mass loss ratio can be used to predict E ′ r of the waste papers. [ABSTRACT FROM AUTHOR]

Abstract: A method for the comparison of paper structure using light transmission images and frequency analysis was developed. The resolution of the light transmission images and the algorithm for the feature extraction were greatly improved to enhance the visibility of peaks in the 2D power spectrum that results from frequency analysis. A comparison method based on correlation measures how well the spectra match as a function of the orientation of the paper, yielding an objective and quantitative measure of similarity between 0 and 1. A technical validation was carried out with 25 different papers showing the potential of this method with common copy papers. Finally, the method was applied in a case. [Copyright &y& Elsevier]

Abstract: Heat management is crucial to polymer electrolyte membrane (PEM) fuel cell commercialization. Numerical modeling is often used to simulate heat transfer in the various components of the cell and specifically the gas diffusion layer (GDL). Due to the porous nature of the gas diffusion layer and its complexity of anisotropy, the effect of the structure on the thermal conductivity is usually taken into account by introducing an effective thermal conductivity. In this study, the effective thermal conductivity of carbon paper diffusion media was estimated numerically. Carbon paper is often used as the GDL in PEM fuel cells due to its ability to efficiently transport electrons, heat and gaseous species. Using the GeoDict code, a realistic three-dimensional pore morphology of carbon paper was used as the modeling domain and the governing mathematical equations were solved using the commercial software package Fluent (6.3.26) and the ThermoDict solver. The geometrical effects on the effective thermal conductivity were investigated for different geometries. It was found that the effective thermal conductivity is highly sensitive to the geometry of the porous material under investigation. The effective thermal conductivity is much larger in the in-plane direction when compared with the value in the through-plane direction. Further, the change of the effective thermal conductivity due to porosity and compression was studied. Finally, correlations for the through-plane and in-plane effective thermal conductivity were developed. [Copyright &y& Elsevier]

A system for real-time digital speckle correlation rate measurements is developed and applied on printing paper in the micro-scale. The system consists of a continuous laser and a CCD camera connected to a PC. To measure on objects in the micro-scale the system is connected to a stereomicroscope where one of the channels is used for imaging and the other channel is used for illumination of the object surface. The system is evaluated through measurements on printing paper over an area of 1 mm2 and with a spatial resolution of 30 μm on the object. The results show that the system is able to monitor the dynamics in paper during both wetting and drying in real-time over a time scale ranging from one-tenth of a second to several hours. [Copyright &y& Elsevier]

We aim to evaluate the concordance level between Science and Technology in Natural Science, for this we investigated the relationship between the number of articles and patents resulting from Cerrado plant research. We found a significant concordance between scientific and technological publication patterns in Natural Sciences. Private companies, public universities, and natural person are the categories of patent assignees with more patents. Lastly, we found great importance of the Cerrado plant species to global technological development, where cosmetology is the main branch of economic bioprospecting. Therefore, it is crucial to produce studies aiming to promote both the conservation and technological development of sub-products of these plants. • There is concordance between Science and Technology in Natural Sciences. • Private companies are the main patent assignees of plant-based products. • Cosmetics is the main manufacturing segment of patents from Cerrado plants. • Cerrado plants are crucial for the global technological development. [ABSTRACT FROM AUTHOR]

Abstract: We report on the results of investigations into the characteristics of an air–water isothermal two-phase flow in minichannels, that is, in capillary tubes with inner diameters of 1 mm, 2.4 mm, and 4.9 mm, also in capillary rectangular channels with an aspect ratio of 1 to 9. The directions of flow were vertical upward, horizontal and vertical downward. Based on the authors 15 years of fundamental research into the gas–liquid two-phase flows in circular tubes and rectangular channels, we summarized the characteristics of the flow phenomena in a minichannel with special attention on the flow patterns, the time varying holdup and the pressure loss. The effects of the tube diameters and aspect ratios of the channels on these flow parameters and the flow patterns were investigated. Also the correlations of the holdup and the frictional pressure drop were proposed. [Copyright &y& Elsevier]

At the heart of India's livelihood lies agriculture, a foundational and ever-evolving sector. The realm of agriculture faces modern challenges, encompassing unpredictable climate fluctuations, insufficient irrigation infrastructure, and erratic weather conditions. Amidst these challenges, machine learning has emerged as a valuable tool for evaluating soil fertility and Crop assessment in agriculture. Ensemble machine learning methodologies have garnered attention for their potential to enhance predictive capabilities. These techniques involve constructing meta-classifiers that collectively contribute to improved predictive accuracy. This paper centers on the analysis of soil data acquired from testing laboratories, to predict fertility based on a comprehensive dataset. The study employs prominent ensemble machine learning algorithms, specifically focusing on boosting techniques, to elevate predictive accuracy and ensure heightened consistency. The assessment of soil fertility categories involved the examination of 12 carefully chosen attributes. Diverse soil parameters were measured to facilitate the prediction of soil fertility levels. The outcomes of the experimentation revealed that the application of the boosting technique using the Xgboost algorithm yielded superior accuracy compared to alternative ensemble classifiers, achieving a remarkable 96% accuracy rate. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study of n-butane (R600) and isobutane (R600a) flows in adiabatic capillary tubes. In total, 48 experimental data points were gathered spanning the typical conditions of household refrigerators, with capillary inner diameters ranging from 0.53 to 0.79 mm, tube lengths ranging from 2.5 to 3.5 m, inlet pressure ranging from 2.83 to 6.05 bar, exit pressure ranging from 0.3 to 0.9 bar, inlet subcooling ranging from 4.7 to 15.2 °C, and mass flow rates ranging from 0.53 to 2.95 kg h−1. In addition, the accuracy of π-type correlations priorly developed for R600a flows was verified when used with R600 to predict the refrigerant mass flow rate. Also, it was found the mass flow rate predictions of the algebraic model developed by Hermes et al. (2010) for R600a agreed well with the R600 experimental data, with more than 90 % of data points within ± 10 % error bands. [ABSTRACT FROM AUTHOR]

Bluetooth (BT) mesh networks are used in several ad hoc network communication scenarios, including natural disasters, calamities, war zones, etc. However, there are situations where Bluetooth mesh networks are misused by anti-social elements during riots etc. As of now there no such research article that showcases detection of BT mesh networks using machine learning tools. Therefore, there is a need to build novel methods for detecting the very presence of Bluetooth mesh networks to aid the law enforcement agencies. This paper contributes to building a new dataset for the aid of machine learning tools to detect the presence of Bluetooth mesh networks. The dataset is extracted from a simulated Bluetooth mesh network with 52 BT network traffic attributes, using the Bridgefy application. Further, the dataset is optimized by identifying prime features, using label encoding, one-hot encoding, correlation analysis and evaluated by various Machine Learning (ML) tools. An accuracy of 99.6% is achieved after optimizing the feature set. [ABSTRACT FROM AUTHOR]

Hybrid nanofluids are intensively studied in the last years as the new working fluids for many heat transfer applications. In this paper, a new heat transfer fluid is manufactured and investigated. Thus, this paper aims with an experimental study involving the graphene oxide (GO)-silicon (Si)/water hybrid nanofluid. The experiments were conducted taking into account both the mixture ratio between the two components that make up the hybrid nanofluid as well as the temperature effect on the thermal conductivity. Measurements were done within the range of 25–50 °C for every 5 °C. It is found that the thermal conductivity increases both with rising temperature and with increasing graphene oxide content. A comparison of the current results with other studies reported in the open literature was performed, and also a new correlation was proposed. [ABSTRACT FROM AUTHOR]

Modern power systems integrated with renewable energies (REs) contain many uncertainties. The proposed method introduces a novel approach to address the challenges associated with wind power generation uncertainty in probabilistic load flow (PLF) studies. Unlike conventional methods that use wind speed as an input, the paper advocates for utilizing wind generator output power (WGOP) as an input to the point estimate method (PEM) in solving PLF. The uniqueness lies in recognizing the distinct behavior of wind power uncertainty, where not all random samples of wind speed contribute to actual wind power production. The paper suggests a Nataf-KernelDensity-Spline-based PEM, combining the Nataf transformation, Kernel density estimation (KDE), and cubic spline interpolation. This innovative integration effectively manages wind power correlation within the analytical framework. By incorporating spline interpolation and kernel density estimation into the traditional PEM, the proposed method significantly enhances accuracy. To validate the effectiveness of the proposed approach, the method is applied to IEEE-9 and IEEE-57 bus test systems, considering uncertainties related to load, wind power generation (WPG), solar power generation (SPG), and conventional generator (CoG) outages. Comparative analysis with Monte Carlo simulation (MCS) results demonstrates that the proposed method outperforms the conventional PEM in terms of accuracy. Overall, the paper contributes a pioneering solution that not only highlights the importance of using WGOP as an input in PLF but also introduces a sophisticated method that surpasses traditional approaches, improving accuracy in power system studies involving renewable energy integration. The accuracy of the proposed method is validated by comparing its results with those obtained through Monte Carlo simulation (MCS), where the proposed method yields more accurate results than the conventional PEM. [ABSTRACT FROM AUTHOR]

This paper proposes an innovative approach towards real-time earthquake forecasting in Chile by integrating intelligent technologies and machine learning methods. Earthquakes pose significant risks to communities and infrastructure in Chile, making accurate and timely forecasting crucial for disaster preparedness and mitigation. Traditional forecasting methods have limitations in providing real-time insights into seismic activity. In contrast, intelligent technologies such as artificial intelligence (AI) and machine learning offer promising avenues for enhancing prediction accuracy and speed. A new earthquake forecasting method using a modified clustering approach LMSCAN(Local Maxima-based Spatio-Cluster Analysis Network) and enhanced neural network time series analysis LSTM-IC (Long Short Term Memory Inverse Correlation) is presented in this paper. This neural network-based technology has been utilized to forecast earthquakes in the Chile region, one of the countries with the largest seismic activity. This study explores the integration of intelligent systems with machine learning algorithms to analyze seismic data and predict earthquake occurrences in Chile. By leveraging historical seismic data, sensor networks, and advanced predictive models, our approach aims to provide timely warnings and insights into seismic events, thereby improving disaster response and resilience. The proposed framework holds the potential to revolutionize earthquake forecasting by enabling real-time monitoring and proactive measures to safeguard communities and infrastructure in Chile and beyond. The remarkable 95 % accuracy achieved by this model is a testament to its exceptional learning process, which sets it apart from other models. Its ability to learn and adapt to new data is unparalleled, allowing it to forecast incredibly precisely and produce highly reliable results. [ABSTRACT FROM AUTHOR]

• More research is needed before integrating machine data into genetic evaluation. • This paper proposes a Sheep Data Recorder and Sheep Body Size Collector. • The optimal genetic model using machine data is the same as predicted by humans. • Machine measurements may overestimate heritability compared to manual measurements. • This paper shows positive genetic and phenotypic correlations in body size traits. In the realm of animal phenotyping, manual measurements are frequently utilised. While machine-generated data show potential for enhancing high-throughput breeding, additional research and validation are imperative before incorporating them into genetic evaluation processes. This research presents a method for managing meat sheep and collecting data, utilising the Sheep Data Recorder system for data input and the Sheep Body Size Collector system for image capture. The study aimed to investigate the genetic parameter changes of growth traits in Ujumqin sheep by comparing machine-generated measurements with manual measurements. The dataset consisted of 552 data points from the offspring of 75 breeding rams and 399 breeding ewes. Six distinct random regression models were assessed to pinpoint the most suitable model for estimating genetic parameters linked to growth traits. These models were distinguished based on the inclusion or exclusion of maternal genetic effects, maternal permanent environmental effects, and covariance between maternal and direct genetic effects. Fixed factors such as individual age, individual sex, and ewe age were taken into account in the analysis. The genetic parameters for the yearling growth traits of Ujumqin sheep were calculated using ASReml software. The Akaike information criterion, the Bayesian information criterion, and fivefold cross-validation were employed to identify the optimal model. Research findings indicate that the most accurate models for manually measured data revealed heritability estimates of 0.12 ± 0.15 for BW, 0.05 ± 0.07 for body slanting length, 0.03 ± 0.07 for withers height, 0.15 ± 0.12 for hip height, 0.11 ± 0.11 for chest depth, 0.13 ± 0.13 for shoulder width, and 0.53 ± 0.15 for chest circumference. The optimal models for machine-predicted data showed heritability estimates of 0.1 ± 0.09 for body slanting length, 0.14 ± 0.12 for withers height, 0.55 ± 0.15 for hip height, 0.34 ± 0.15 for chest depth, 0.26 ± 0.15 for shoulder width, and 0.47 ± 0.16 for chest circumference. In manually measured data, genetic correlations ranged from 0.35 to 0.99, while phenotypic correlations ranged from 0.07 to 0.90. In machine data, genetic correlations ranged from −0.05 to 0.99, while phenotypic correlations ranged from 0.03 to 0.84. The results suggest that machine-based estimations may lead to an overestimation of heritability, but this discrepancy does not impact the selection of breeding models. [ABSTRACT FROM AUTHOR]

• The probabilistic interval power flow model of distribution network constructed by evidence theory can organically unify the probabilistic power flow and interval power flow. • The probability intervals of the uncertainty power flow results of the distribution network based on the ellipsoid model are narrower than those of the convex polygonal model and the parallelogram model. • This paper investigates the impact of the correlation of distributed wind power output on the probability interval power flow solution of distribution networks. In order to more accurately simulate the impact of distributed wind farm access on the uncertain power flow distribution of distribution networks, this paper proposed a probabilistic interval power flow calculation method for distribution networks that considers correlation. Firstly, by dividing the output interval of distributed wind farms into several sub-intervals and assigning corresponding probabilities to the sub-intervals, a focal element model of distributed wind farm output is constructed. By combining affine arithmetic, the probabilistic interval power flow model of the distribution networks based on the focal element model is transformed into an affine optimization model to be solved. The parallelogram model, convex polygon model, and ellipsoid model are used to describe the correlation of distributed wind farm output. Through coordinate transformation, the correlation model is transformed into affine constraint conditions and embedded into the affine optimization model for simultaneous solution. Finally, based on the synthesis rules of evidence theory, the probabilistic boundary of the distribution networks probabilistic interval power flow solution is obtained. The simulation of two distribution networks shows that the established probabilistic interval power flow model can describe the uncertainty of power flow solutions through maximum and minimum probabilities, and the ellipsoidal model is more accurate in modeling correlation than the other two kinds of methods. [ABSTRACT FROM AUTHOR]

• Uncertainties in the power system make its state unpredictable. • Power system predictability can be improved by optimal tap setting of transformers. • Increasing predictability helps the operator to make decisions with high assurance. • power system predictability can be improved without considerably affecting losses. In recent years, renewable energy sources (RESs) such as wind turbines (WTs) have received much attention in both the operating and planning of power systems. These sources have caused many uncertainties in the operation of power systems due to their unpredictable nature. Mentioned uncertainties besides load demands uncertainty, and possible failures in power system components, make the system state unpredictable. The operational decisions are completely challenging in these situations. Any efforts to increase the network operator awareness from the system state will be completely valuable for making accurate decisions. This paper tries to increase the predictability of the power system state through optimal regulating of the voltage setpoint of automatic tap changer transformers and generators besides the reactive power of shunt capacitors. However, conventional objectives such as decreasing losses are considered, simultaneously. This paper uses the K-medoids data clustering method to evaluate the effect of uncertainties. Also, the correlation between input uncertain variables is considered and handled by the Cholesky decomposition technique combined with the Nataf transformation technique. The multi-objective optimization problem is tackled using an improved version of the non-dominated sorting genetic algorithm (NSGA-II). To ensure for validity of the results, studies are repeated using the multi-objective particle swarm optimization (MOPSO) algorithm as another evolutionary-based method. The proposed approach is applied to the IEEE 14 and 30 bus standard system. The results showed that the predictability of the power system can be considerably increased while keeping the losses approximately at its minimum amount. [ABSTRACT FROM AUTHOR]

• First overview of the flow characteristics of CO 2 -lubricant mixtures in gas coolers. • Presents multiple factors affecting the flow characteristics of CO 2 -lubricant mixtures. • Reviews the analysis models of the flow and heat transfer of CO 2 -lubricant mixtures. • Comments on pressure drop correlations of CO 2 -lubricant mixtures. • Recommendations for future studies on the CO 2 -lubricant mixture flow characteristics. With the recent advancements in designs and optimization of gas coolers in CO 2 transcritical refrigeration and heat pump systems, the impact of the lubricant on the performance of gas coolers has been gaining increasing attention. The existing literature reviews focus on examining the lubricant effect on the heat transfer performance of gas coolers. However, the studies do not present a detailed discussion and a systematic summary of the flow characteristics. The present paper aims to offer an overall review of the lubricant impact on the flow characteristics of CO 2 in gas coolers. The authors hope it will help researchers conduct additional research about practically designing and optimizing gas coolers. This paper reveals the flow mechanism by providing critical discussions on how temperature, lubricant type, lubricant concentration, mass flux, operational pressure, tube diameter, and tube configuration influences the flow characteristics of the CO 2 -lubricant mixture. Then, the paper summarizes and evaluates the latest developments related to CO 2 -lubricant mixture in the flow and heat transfer analysis models and pressure drop correlations. Moreover, the current research gap is summarized, and the study proposes development directions. These include measuring thermo-physical properties of CO 2 -lubricant mixture, examining pressure drop characteristics under different tube configurations, developing universal pressure drop correlations, and studying flow characteristics in vertical tubes. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a detailed description of a vision system developed to detect and locate the non-uniformities that appear on the web offset printing machine. Specifically, the system is capable of monitoring the high-speed web offset printing in a real-time environment and alerting the operator of any events (e.g., structural faults, color variations, missing characters, ink splashes, streaks, etc.) that disrupt the uniformities in the web offset printing. Such events are thought to affect crucial printing properties, resulting in non-uniformities in printing and impacting its quality and printability. This paper describes the vision system in terms of its hardware modules, as well as the image processing algorithms that it utilizes to scan the color images and locate areas of defect from the printing web. Basically, the system utilizes high-speed image scanning algorithms to detect edges and boundaries using linear and non-linear filters of dynamic size, threshold and transformation for further analysis. In addition to being tested in a laboratory environment, a prototype of this system was constructed and deployed to a web printing system, where its performance was evaluated under realistic conditions. The system was installed on a Flexo gravure-print-press machine for testing, and it was found that the vision system was able to successfully monitor and detect non-uniformities. [Copyright &y& Elsevier]

There is great interest in predicting flow condensation heat transfer for lower global warming potential (GWP) fluids. This paper analyzes the efficacy of common flow condensation correlations developed for particular fluids in order to identify their suitability to predict heat transfer performance of low GWP fluids. Condensation heat transfer data were extracted from the literature, including 19 papers and 1,473 data points for natural refrigerants [ i.e. , ammonia (R717), CO 2 (R744), propane (R290), isobutane (R600a)] and 35 papers and 5,030 data points for synthetic refrigerants [ i.e. , R12, R1234yf, R1234ze(E), R1234ze(Z), R22, R32, R41, R123, R125, R134a, R142b, R152a, R161, R404A, R410A, R448A, R449A, R450A, R452B, R454C, R455A, R513A] encompassing tube diameters of 0.1–11.5 mm, mass fluxes of 55–1200 kg/m2s, and saturation temperatures of -25 °C–65 °C. Correlations analyzed included (Akers et al., 1959; Cavallini et al., 2006; 2011; Kim and Mudawar, 2013; Macdonald and Garimella, 2016; Shah, 1979, 2009, 2013, 2016) and (Traviss et al., 1973) for smooth tubes and (Chamra et al., 2005) and (Kedzierski and Goncalves, 1999) for enhanced tubes. Since most studies did not report wall temperature, correlations which relied on wall temperature directly or indirectly were excluded from the analysis. For synthetic refrigerants, mean average error (MAE) ranged from 6% to 257%, and (Cavallini et al., 2011) and (Kim and Mudawar, 2013) were the best predictors for emerging synthetic refrigerants. The (Kim and Mudawar, 2013) correlation was found to best predict the heat transfer performance for propane and R600a data, but most correlations did not accurately predict ammonia and CO 2 flow condensation. [ABSTRACT FROM AUTHOR]

Stratospheric ballooning flights are becoming more relevant due to these platforms can place payloads to an altitude above almost 99% of the atmosphere, where the environmental conditions are very similar to the space ones. From a thermal point of view, during the ascent phase convection is very relevant and, despite what a priori may be thought, depending on the element considered, convection may not be negligible at the float phase. With this in mind, the Thermal Analysis Support and Environment Characterization Laboratory (TASEC-Lab) was born. It is an experiment based on COTS, which consists in a 3U CubeSat-like experiment, which was launched onboard a stratospheric balloon in León (Spain) on 16th, July 2021. The upper unit of the 3U box contains a heated plate, with the aim of quantifying the relevance of convection during the flight. In this paper, the relevance of convection during the ascent phase is described, the correlation of in-flight temperature measurements with those provided by the thermal mathematical model developed in ESATAN-TMS is performed, using the air mass flow inside the cavity as a fitting parameter with a fitting error lower than 5 °C during the ascent phase. [ABSTRACT FROM AUTHOR]

Hepatitis B core-related antigen (HBcrAg) is a new biomarker for chronic hepatitis B (CHB) whose performance has not been critically or systematically appraised. Herein, we performed a systematic review to determine its clinical utility. We evaluated the biological pathway of HBcrAg and performed a systematic review of PubMed for clinical trials, cohort studies, and case-control studies that evaluated the clinical utility of HBcrAg. The effectiveness of HBcrAg in predicting HBV-specific clinical events (e.g. HBeAg seroconversion, phases of CHB, HBsAg loss, treatment response, and relapse after stopping therapy) was examined using receiver-operating characteristic curves. The correlation coefficients of HBcrAg with HBV DNA, quantitative HBsAg (qHBsAg), HBV RNA, and cccDNA were summarised from published studies. Median values were used as estimates. HBcrAg consists of three precore/core protein products: HBcAg, HBeAg, and a 22 kDa precore protein. HBcrAg assays have been associated with false-positive rates of 9.3% and false-negative rates of between 12-35% for CHB. The new iTACT-HBcrAg is more sensitive but does not reduce the false-positive rate. A PubMed search found 248 papers on HBcrAg, of which 59 were suitable for analysis. The clinical performance of HBcrAg was evaluated using AUROC analyses, with median AUROCs of 0.860 for HBeAg seroconversion, 0.867 for predicting HBeAg(-) hepatitis, 0.645 for HBsAg loss, 0.757 for treatment response, and 0.688 for relapse after stopping therapy. The median correlation coefficient (r) was 0.630 with HBV DNA, 0.414 with qHBsAg, 0.619 with HBV RNA and 0.550 with cccDNA. Correlation decreased during antiviral therapy, but combined biomarkers improved performance. HBcrAg has a mixed performance and has a poor correlation with HBsAg loss and antiviral therapy, hence HBcrAg results should be interpreted with caution. Hepatitis B core-related antigen (HBcrAg) has been used to assess management of patients with chronic hepatitis B (CHB) without a systematic and critical Sreview of its performance. Our finding that HBcrAg had a false-positive rate of 9% and a false-negative rate of 12-35% raises concerns, although larger studies are needed for validation. A systematic review showed that the performance of HBcrAg was variable depending on the CHB endpoint; it was excellent at predicting HBeAg seroconversion and HBeAg-negative chronic hepatitis (vs. chronic infection), which should be its main use, but it was poor for relapse after stopping antiviral therapy and for HBsAg loss. HBcrAg results should be interpreted with considerable caution, particularly by physicians, researchers, guideline committees and agencies that approve diagnostic tests. [Display omitted] • The biological pathway of HBcrAg is distinct to that of HBsAg. • HBcrAg are translation products from precore and pregenomic RNA comprising HBV core antigen, p22cr and HBeAg. • HBeAg contributes >70% to HBcrAg in HBeAg-positive patients, but its components are non-quantifiable in HBeAg-negative patients. • HBcrAg exhibits variable clinical performance. [ABSTRACT FROM AUTHOR]

Correlations in observational studies are commonly misinterpreted as causation. Although correlation is necessary to establish a causal relationship between two variables, correlations may also arise due to chance, reverse causality, or confounding. There are several methods available to orthopaedic researchers to determine whether the observed correlations are causal. These methods depend on the key components of the study including, but not limited to, study design and data availability on confounders. In this article, we illustrate the main concepts surrounding correlation and causation using intuitive real-world examples from the orthopaedic literature. Please visit the following https://www.youtube.com/watch?v=WW7pFudZbHA&t=52s for a video that explains the highlights of the paper in practical terms. [ABSTRACT FROM AUTHOR]

• We first proposed the importance of factor matrices in compression performance. • We thoroughly discuss about correlation and factor matrix in this paper. • We propose our correlation-based Tucker decomposition method. • The proposed method can be directly used in most Tucker-based methods. Tucker decomposition (TD) is widely used in hyperspectral image (HSI) processing. Generally, the performance of TD-based method depends on the core tensor and factor matrices, while the construction of core tensor and factor matrices is still a research topic. We give the detailed discussion about the correlation and performance of TD-based methods in this paper. Since TD is solved by singular value decomposition (SVD), the construction of core tensor and factor matrices should be determined by the distribution of singular energy of each mode-n matricization. Depending on the discussion, we propose a correlation-based Tucker decomposition (CBTD) method to construct the core tensor and factor matrices. As a general method, this proposed CBTD can be employed in any TD-based method of N th -order tensor. The analysis on real HSI data verifies our conclusion about correlation and good performance of CBTD. Besides, the proposed CBTD method has better ability to improve the performance of HSI compression than other state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Supercritical water gasification (SCWG) of coal has great application prospect for converting coal into hydrogen-rich gas efficiently and cleanly. However, the previous study on the reaction mechanism for SCWG of coal is relatively macroscopic rather than reflects the reaction essence deeply. The evolution of organic functional groups in Zhundong lignite (ZD), Hongliulin bitumite (HLL) and Ningxia anthracite (NX) during SCWG, as well as the correlation with gaseous products were analyzed quantitatively in this paper. It was found that the lower rank coal contained more free radicals and produced more H 2 with SCW. H 2 yield of the three types of coal exceeded 2 times the hydrogen content in coal at 800 °C. The organic functional groups evolve in 2–4 stages during SCWG process. The decomposition and gasification of organic functional groups mainly took place in low or medium temperature range. About 95% of C=O groups and 90% of aromatic C=C groups cracked and were gasified. Aromatic ether (C ar -O) groups were formed in high temperature range. The reasonable functional relationship between the parameters of gaseous products and organic functional groups was established, providing a new approach to predict organic functional groups through gaseous products. This research may lay the foundation for further optimization design of reactor. • Lower rank coal contained more free radicals and produces more H 2. • Typical functional groups of coal evolved in several stages with temperature. • The cleavage of functional groups took place in low or medium temperature range. • C ar -O groups were formed in high temperature range. • The function relationship between gas products and functional groups was set up. [ABSTRACT FROM AUTHOR]

• Unsupervised feature selection based on the distance of the selected features and an orthogonal set. • Feature selection is performed through the matrix factorization of the generated orthogonal set. • A dual-correlation model for considering both the correlation among the features and samples. Feature selection has been an outstanding strategy in eliminating redundant and inefficient features in high-dimensional data. This paper introduces a novel unsupervised feature selection based on the matrix factorization, namely Unsupervised Feature Selection Guided by Orthogonal Representation (UFGOR). The orthogonality between a pair of variables refers to a specific case of linear independence such that they are perfectly uncorrelated. Motivated by the benefits of the orthogonality concept, the proposed UFGOR method is established based on the distance between the selected feature set and an orthogonal set corresponding to the whole feature space. Moreover, this orthogonal set is generated via QR-matrix factorization over the whole features and is employed as the compact representation of data matrix. In the next step, an unsupervised feature selection method is performed through the matrix factorization of the generated orthogonal set. Additionally, a dual-correlation model is utilized in the objective function of UFGOR to simultaneously consider both the local correlation in a set of selected features and the global correlation among the samples of a data. A detailed convergence analysis in line with an effective iterative algorithm proposed for the UFGOR method is also given. Numerical experiments on several real-world datasets illustrate the superior efficiency of our approach in comparison with some state-of-the-art unsupervised feature selection methods. [ABSTRACT FROM AUTHOR]

Organic Rankine cycle (ORC) is considered to be a good solution to the high-efficient recovery of low-grade heat for saving energy and reducing carbon emissions. As the core component, the heat exchanger plays a significant role in the thermo-economic performance evaluation of an ORC plant and its heat transfer correlations greatly influence the cycle performance. In this paper, 8 two-phase heat transfer correlations (4 flow boiling ones and 4 flow condensation ones) are utilized to design the plate-type heat exchangers, and a comparative study among different correlations is carried out. The result shows the designed evaporators are finitely affected by heat transfer correlations whereas the situation with the designed condensers is the opposite. The net output power is slightly influenced with a relative difference within 1.1% but the system's economic performance is significantly affected with the maximum relative difference of electricity production cost up to 11.2%. The environmental performance is hardly affected by correlations with the maximum relative difference of total greenhouse gas emission within 0.96%. This paper analyzed the performance variation of the ORC under different correlations and provided a guideline for designing heat exchangers and evaluating the off-design performance of ORC systems. • 8 two-phase heat transfer correlations are compared for designing the heat exchangers. • Designed condensers are affected by the heat transfer correlations more significantly. • Net output power is slightly influenced with a relative difference within 1.1%. • Electricity production cost is affected with a relative difference 11.2%. • Total carbon emissions exhibit minimal variation with a relative difference of only 0.96%. [ABSTRACT FROM AUTHOR]

The real-time reverse-transcript polymerase chain reaction (RT-PCR) test is a widely used laboratory technique that is highly sensitive and reliable for measuring the quantification of gene expression levels and diagnosing various of diseases, including COVID-19. The RT-PCR experiments often have correlated technical replicates of a small number of samples. However, current statistical analysis of RT-PCR assumes a large sample size and does not account for correlated structure across the replicates. In this paper, we review popular statistical methods for analyzing RT-PCR data and propose a permutation method that accounts for the small sample size and the correlated structure of RT-PCR data. Our proposed method provides a more accurate and efficient analysis of RT-PCR data. We provide an R program to implement our method for practitioners. • Current statistical analysis of RT-PCR assumes a large sample size and does not account for correlated structure across the replicates. • We propose a permutation method that accounts for both the small sample size and replicated structure of the RT-PCR data. • We have created a Github website where practitioners can obtain an R program used in this paper. [ABSTRACT FROM AUTHOR]

• Study found how multiple factors influence asphalt mixture's pore characteristics evolution. • Explored mesoscopic pore characteristics and macro mechanical strength correlation. • Built on AASHTO T283 and JTG E20-2011, proposed mesoscopic moisture-sensitivity method for asphalt. This paper explored the mesoscopic pore characteristics of asphalt mixtures by considering the coupling effects of grading segregation, dynamic pore water, and salt erosion, utilizing CT scanning technology. The study yielded the following key findings: 1) Under the coupling effects of grading segregation, dynamic pore water, and salt erosion, the sample with heavy segregation of coarse aggregate (HC) exhibited the highest variation in porosity, followed by the sample without gradation segregation (D), while the sample with heavy segregation of fine aggregate (HF) showed the least change. 2)The influence of gradation segregation on different mesoscopic pore characteristics demonstrated significant dispersion before and after the coupling effects of multiple factors. 3)From a mesoscopic scale perspective, this paper proposes a method to assess moisture sensitivity. The results obtained through this method indicate that the coordination number (CN) exhibits significantly stronger moisture sensitivity compared to other mesoscopic pore parameters. [ABSTRACT FROM AUTHOR]

With the launch of the Shanghai-Hong Kong and the Shenzhen-Hong Kong Stock Connect programs, the correlations among the three stock markets have been more complex. Therefore, this paper applies the Minimum Spanning Tree and Sliding Window methods to analyze the complex correlations of the 38 financial institutions in the three markets. Based on closing prices ranging from January 1, 2011 to December 31, 2021, three conclusions are obtained. The top 20 institutions in the network were mainly banking institutions from 2011 to 2013, while the node strength of non-banking financial institutions tended to increase from 2014 to 2021. The network shows different structures over time, even the changes in the three correlation coefficients generally show the same trend. The degree correlation between any two layers is positive, but the similarity shows different characteristics. These results would help to enrich multi-layer network theory and reveal the evolutionary characteristics of the correlation between financial institutions. [ABSTRACT FROM AUTHOR]

Critical heat flux (CHF) represents heat transfer limit for a heat sink working under flow boiling conditions. In the literature, for the first time, in micro-pin-fin heat sinks with expanding structure, this paper experimentally focusing on CHF and proposing a correlation for saturated flow boiling at quite low mass velocities. Parallel channel heat sink is evaluated as reference case. Three mass velocities (G = 45, 68, 90 kg m−2 s−1) are studied by beginning from 130 W up to boiling crisis. Test-range falls in the pure saturated boiling conditions, and inlet temperature is approximately kept constant at 60 °C. Flow mechanism is figured out over the flow images. The heat sink with expanding structure (T-2) clearly boosts CHF compared to parallel counterpart (T-1); such that, by successfully manipulating bubble dynamics, T-2 increases the CHF up to 32.9% at the lowest mass velocity (G = 45 kg m−2 s−1). For highest mass velocity (G = 90 kg m−2 s−1), T-2 provides lower wall superheat up to 89.5% against T-1. The CHF ranges from 225 to 443.31 kWm−2, even though quite low mass velocities. Regarding prediction of the experimental data, mean absolute error (MAE) of proposed correlation is 4.7%; and all those of predictions fall in ±12% error bands. [ABSTRACT FROM AUTHOR]

• The research conducted experiments on Condensation-Induced Water Hammer in WASIF. • In experiments, subcooled water injected radially into steam filled horizontal pipe. • Experimental results enhance CIWH triggering understanding in horizontal pipes. • A correlation predicts the necessary minimum feed water flow for CIWH initiation. • The study presents a regime map as a reference to prevent CIWH. Condensation-Induced Water Hammer (CIWH) phenomenon involves dynamic pressure changes caused by rapid condensation of steam in subcooled water. The magnitude of pressure spike is often large and can cause damage to the pipes and components in steam-water systems. Understanding the phenomena is vital for obtaining a safe and reliable design. This paper describes experimental investigations carried out in a specially designed facility called Water and Steam Interaction Facility (WASIF-I), that offers control over water and steam flow rates, can operate in co–, cross-, or counter-current flow mode and contains multiple injection locations. The occurrence of CIWH in horizontally oriented pipes filled with saturated steam is studied for the case where subcooled water is injected in cross-flow mode. The effect of geometrical and operating variables on the initiation of CIWH as well as peak pressure are brought out in this experimental work. A correlation to predict the critical minimum feed water flowrate necessary for triggering CIWH is developed based on multiple, nonlinear regression analysis of data from around 150 experiments. A regime map is presented that can be used as a guideline to preclude occurrence of CIWH. [ABSTRACT FROM AUTHOR]

This paper investigates negative sentiment tweets with the presence of hyperboles for sarcasm detection. Six thousand and six hundred pre-processed negative sentiment tweets comprising #Chinesevirus, #Kungflu, #COVID19, #Hantavirus and #Coronavirus were gathered for sarcasm detection. Five hyperbole features, namely interjection, intensifier, capital letter, punctuation mark and elongated word were analysed using three renowned machine learning algorithms, that is, Support Vector Machine, Random Forest, and Random Forest with Bagging. With the presence of hyperbolic words in the tweets in an unbiased dataset, the proposed model with elongated word achieved an accuracy and F-score of 78.74% and 71%, respectively. Intensifier was found to be the most significant hyperbole (p <.0001). Experiments and analysis conducted in this study concluded that hyperboles exist in an unbiased dataset which helps enhance the sarcasm detection as well. [ABSTRACT FROM AUTHOR]

It is difficult to obtain both sky luminance and solar radiation data, which greatly restrict the development and utilization of solar resources. In this paper, the functional relationship between sky luminance and solar radiation is established. Firstly, linear and polynomial functions were established for 145 regions of the whole sky. The results show that there is a nearly linear correlation between sky luminance and solar radiation. In 145 regions, 68.3% of the regions have close accuracy between linear and polynomial functions. Secondly, the linear and polynomial equations functions are established for the four typical orientations. The accuracy of the polynomial function in the eastern and northern regions is higher than that of the linear function, but in the southern and western regions they are equivalent. Finally, a unified equation is established for the whole sky, and the result shows the accuracy of the polynomial function is more accurate. This research can realize the mutual conversion between sky luminance and solar radiation. It can not only make up for the missing sky luminance data and solar radiation data, but also provide a theoretical basis for solar thermal, photovoltaic, building energy conservation and agricultural production. • Functions of solar radiation and sky luminance were established for 145 regions. • Functions are established for the east, south, west and north orientation. • The unified function of solar radiation and sky luminance is established. • Influence of equation form and orientation on the accuracy of functions is analyzed. [ABSTRACT FROM AUTHOR]

• Novel heat exchangers for waste heat utilization of dusty flue gas are proposed. • The aligned elliptic tube and honeycomb circular tube bundles are presented. • Ash fouling and thermal-hydraulic characteristics in fouling state are examined. • The effects of transverse and longitudinal pitches are studied. • The correlations of Nu , f and fouling thermal resistance are obtained. In this paper, aiming at resolving the contradictions of heat transfer enhancement, resistance reduction and soot-blowing effect of common heat transfer surfaces, aligned elliptical tube bundle (AETB) and honeycomb tube bundle (HCTB) were proposed for the high dust content conditions, and the fouling characteristics and thermal-hydraulic performance before and after fouling were investigated. Firstly, the thermal-hydraulic performance of aligned circular tube bundle (ACTB), AETB, conventional staggered circular tube bundle (SCTB) and HCTB in the clean state were compared, and advantages of AETB and HCTB were verified. Secondly, based on the ash fouling model and prediction method established by the author's group, fouling distribution and morphology of AETB and HCTB were obtained, and ash fouling and thermal-hydraulic characteristics were examined by parameterization. Finally, in the range of geometry parameters studied in this paper, the correlations of the asymptotic value of fouling thermal resistance R f ∗ in fouling state, Nusselt number Nu and friction factor f in clean state were developed. Results show that the relative deviations between the predicted results and the numerical values is within 4%, which indicates that the proposed correlation is of sufficient accuracy for engineering purposes, and can accurately predict the thermal-hydraulic characteristics of flue gas heat exchanger. The results of this paper can provide a reference for development and engineering application of the heat-transfer surface for the efficient recovery of industrial flue gas waste heat. [ABSTRACT FROM AUTHOR]

• A model for spatial reliability of power transmission lines is presented. • Authors prove the existence of the correlation between outages in the power grid and geographical position of lines. • More accurate predictions were obtained by the proposed model as compared to the Poisson and Poisson hierarchical models. The paper is devoted for the problem of assessment of the dependence of power transmission lines outages on the geographical position in the network. Authors present the model based on Poisson–gamma random field for the purpose of capturing the information about the strength of correlation between the power transmission network outages and geographical positions. The model presentation is followed by the analysis of the model and application to the North American power grid. The main finding is that outages of the power grid are geographically correlated and this effect should be incorporated into the overall reliability assessment of the grid to obtain more accurate estimates. It is proved in this paper, that taking into account dependency of line outages on the geographical location, enables to obtain more accurate results as compared to classical Poisson and to hierarchical Poisson–Bayesian models. [ABSTRACT FROM AUTHOR]

Abstract This paper presents a methodology for determining the probability of system failure of corrosion affected steel pipelines with multiple failure modes. The failure modes include fracture, strength failure, deflection and buckling and they are all modelled as stochastic processes with correlations among them. The first passage probability theory is employed to quantify the probability of pipe failure. A case study is presented to illustrate the proposed methodology, followed by a sensitivity analysis to investigate the effects of key random variables on the probability of pipe failure. It is found that correlation of the load effect process at different points in time and the correlation among different failure modes have a considerable effect on the probability of failure for each failure mode and probability of system failure respectively. It is also found that the corrosion model and pipe thickness are most influential with positive and negative indices respectively on the probability of pipe failure for all failure modes. The methodology presented in this paper can help pipe engineers and asset managers develop a risk-informed maintenance strategy for corrosion-affected steel pipelines. [ABSTRACT FROM AUTHOR]

Lactose percentage (LP) in milk is currently determined in most herd-testing schemes, and globally, it is usually routinely recorded in the framework of the official milk recording procedures. However, few studies have investigated the phenotypic and genetic variability of this component. Data used in the present paper consisted of 59 811 test-day records from 4355 Holstein cows in 266 herds. Heritabilities of LP and lactose yield (LY) were estimated through single-trait repeatability animal models, whereas genetic and phenotypic correlations of LP and LY with milk composition and production traits, somatic cell score and milk freezing point were estimated using bivariate models. Fixed effects included in the analyses were herd-test-date, season of calving, parity, stage of lactation and the interaction between parity and stage of lactation. Random effects were animal additive genetic, within and across lactation permanent environment and the residual. Lactation curves of LP and LY increased from parturition to the peak of lactation and decreased thereafter, mirroring the typical curve of milk yield. Lactose percentage was greater in first- than later-parity cows. Heritabilities of LP and LY were 0.43±0.03 and 0.14±0.02, respectively, and LP and protein percentage were the most repeatable traits. Genetic correlations (r a) of LP with somatic cell score, LY and milk freezing point were −0.22±0.08, 0.28±0.08 and −0.46±0.05, respectively. Genetic relationships of LY with milk yield (r a=0.97±0.00), fat percentage (r a=−0.71±0.06), protein percentage (r a=−0.57±0.06) and protein yield (r a=0.64±0.06) were moderate to strong. Results suggest that milk LP could be considered in breeding strategies to accelerate the gain of correlated low heritable traits. Further research is needed to evaluate the feasibility of including LP in the selection index of Italian Holstein population to address country-specific needs and market demands. [ABSTRACT FROM AUTHOR]

A substantially updated version of the correlation table showing chronostratigraphical subdivisions of late Cenozoic geological time, spanning the last 2.7 million years is presented. It provides scientists, students, professionals and the general public with a ready reference to stratigraphical terms and schemes in use in different areas for similar periods. The updates comprised the status of Quaternary chronostratigraphic subdivision, the combined age-modelled geomagnetic and isotope records from ocean drilling records, and revised regional correlation schemes, notably for eastern Europe. The paper describes the chart in its 2019 QI-500 form and contains sections on its types of usage and formal subdivision status, besides reference and description of the contents of the various columns. The paper also describes and discusses the resolution of correlations in younger and older parts of the last 2.7 Ma. [ABSTRACT FROM AUTHOR]

Abstract Nowadays, Ionic liquids (ILs) are considered as new solutions with novel and effective applications, therefore, determining their physical and chemical properties are very important. In this paper, it has been tried to present a novel and simple correlation to predict surface tension of ILs. To this purpose, one of the most powerful techniques of soft computing, Multi-Gene Genetic Programming (MGP), has been used to generate a network and to obtain a simple and accurate correlation. Reduced temperature (T r), reduced pressure (P r), critical compatibility factor (Z c) and acentric factor (ω) values have been selected as input parameters of the network. The obtained correlation has a simple mathematical form, which is a function of reduced temperature with a good accuracy (R2 = 0.99). This correlation has three coefficients, which can be determined using GA or a simple curve fitting or can be found in this paper for some of the important ionic liquids. The other proposed method for determining the coefficients is to use six correlations that were presented in this work. Highlights • Surface tension of ionic liquids has a general trend, which can be obtained. • Reduced temperature has the most effect on surface tension of ionic liquids. • Accurate correlation and network have been trained for surface tension of ionic liquids. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • We propose a dual version of the Fast NLMS algorithm for speech enhancement. • We propose to use this new dual algorithm combined with the forward BSS structure to enhance the speech signal blindly. • Intensive experiments have shown the good performance and the robustness of this proposed algorithm. • A comparison with other competitive and state-of-the-art algorithms have shown the superiority of the proposed algorithm. Abstract This paper addresses the problem of speech enhancement by partial adaptive algorithms combined with the forward blind source separation (FBSS) structure. We propose three new two-channel forward partial update algorithms: (i) The first algorithm is based on the use of the correlation properties to adapt and control the variable step-size parameter of adaptive cross-filters of the FBSS structure, this algorithm is called the two channel correlated set membership partial update NLMS (TC-SM-PU-NLMScor). (ii) The second algorithm is based on the use of a new coefficients update relations to control the normalization energy of the adaptive NLMS cross filters of the FBSS structure. This algorithm is called the two channel set member ship partial update regularized NLMS (TC-SM-PU-RNLMS). (iii) The third algorithm is a combination of proposed 1 (TC-SM-PU-NLMScor) and proposed 2 (TC-SM-PU-RNLMS), this algorithm is called the two channel correlated set membership partial update regularized NLMS (TC-SM-PU-RNLMScor). In this paper, we show the obtained results of the comparison between the three proposed algorithms and the original two channel correlated set membership partial NLMS (TC-SM-PU-NLMS) algorithm. This comparison is expressed in terms of objective criteria as the System Mismatch (SM), the Segmental Mean Square Error (SegMSE) and the Segmental SNR (SegSNR). [ABSTRACT FROM AUTHOR]

• This paper applied the theoretical knowledge of visual marking to the study of industrial icons, and the relationship between the inhibitory mechanism of visual marking and the information characteristic, semantic categories and spatial layout of industrial icons is explored from the inhibition of location, feature, category and spatial structure in visual marking. As a carrier of complex information, industrial icons play an important role in intelligent manufacturing systems, and the superiority of its visual presentation affects the visual search efficiency of operators. This paper applied the theoretical knowledge of visual marking to the study of industrial icons, and the relationship between the inhibitory mechanism of visual marking and the information characteristic, semantic categories and spatial layout of industrial icons is explored from the inhibition of location, feature, category and spatial structure in visual marking. The experimental results show that: in the aspect of feature inhibition, the 2.5D style inhibits the flat style and the complex icon inhibits the simple icon. In the aspect of category inhibition, the inhibitory degree of four different categories are warning, monitoring, equipment and production in order from high to low. In the aspect of spatial layout inhibition, the regular layout inhibits the chaotic layout and the orderly arrangement inhibits the disorderly arrangement. It is concluded that there is a certain correlation among the industrial icons' inhibition of feature, category and spatial layout, and the priority of category is higher than that of feature, the spatial layout inhibition is jointly influenced by the inhibition of feature and category, among which category inhibition takes the lead role. [ABSTRACT FROM AUTHOR]

• A computational model of hexagonal rod bundle channels with liquid lithium flow is built. • Liquid lithium flow and heat transfer in hexagonal rod bundle channels at different P / D ratios are investigated. • New correlations are proposed to predict liquid lithium flow and heat transfer in hexagonal rod bundle channels. This study examines flow and heat transfer characteristics of liquid lithium in hexagonal rod bundle channels, at different pitch-to-diameter (P / D) ratios. Numerical investigations are conducted for the parameter P / D within the scope of 1.05 to 1.55. In this paper, it mainly focuses on the effects of P / D on frictional resistance coefficient (f) and convective heat transfer coefficient (h). The results show that with the increase of P / D , the local cross-flow is gradually weakened, and the whole flow tends to be consistent. At the same P / D , f decreases with increasing inlet Reynolds number (Re in), and h increases with increasing inlet Peclet number (Pe in). Both the f and h exhibit an increasing and decreasing trend with increasing P / D , reaching the largest values at P / D = 1.15 and P / D = 1.1, respectively. Based on numerical simulations, this study assesses the present correlations of liquid metal flow and heat transfer. New correlations for liquid lithium flow and heat transfer in hexagonal rod bundle channels have been established. [ABSTRACT FROM AUTHOR]

In this paper, a new semi-empirical density-based model was developed to correlate drug compounds solubility in supercritical carbon dioxide (SC-CO 2) as a function of temperature and density of supercritical carbon dioxide. The proposed approach has successfully predicted the solubility of 282 pharmaceutical compounds accounting for 7469 experimental data points collected from literature published between 1994 and 2024. Several statistical metrics, including average absolute relative deviation (AARD=7.24 %), coefficient of correlation (R=0.9987), and coefficient of determination (R2=0.994) were used to validate the reliability of the proposed model and compared with twenty existing density-based models. The overall results demonstrate the accuracy of the proposed model and its suitability for the correlation of solubility. [Display omitted] • A new semi-empirical model is proposed to correlate solubility of solids in SC-CO 2. • The solubility data of 282 solids was applied to the study for the first time. • Experimental data were correlated by the proposed model and the existing models. • The ability of the employed models was evaluated by various statistical metrics. • The proposed model exhibited outstanding results with extrapolation ability. [ABSTRACT FROM AUTHOR]

• Consolidating manifestations and mathematical representations for causality. • Abstracting common paradigms of conventional accident models. • Transforming descriptive causality factors to quantifiable variables. • Extending accident modeling to probabilistic and machine learning approaches. • Applying the mathematical accident modeling in the accident investigation. Accident models are a critical element of safety science as they provide a profound understanding of accident causality, which helps develop accident prevention and control strategies. The evolving accident situations and complex engineering systems offer significant challenges in understanding causality. This limits the realistic representation of causality in the accident model, impacting its usefulness. This paper presents a framework to demystify the understanding of causality and its mathematical representation in accident modeling. The framework uses the theory of causality, understanding interdependencies, constructing these elements in mathematical representations to formulate a mathematical accident model, and subsequently utilizing advanced probability theory and machine learning for accident analysis. The methodology is demonstrated in the case of the Champlain Tower South collapse. The ultimate objective of this work is that readers can use this framework for any engineering system accident modeling (i.e., construction, road, or process systems). The framework will help develop accident preventive and control strategies. [ABSTRACT FROM AUTHOR]

The liquid desiccant cooling system (LDCS) is a promising alternative for the conventional vapor compression system due to its high energy efficiency. To enhance the mass transfer between the regeneration air and liquid desiccant in the regenerator, the paper firstly introduced a kind of surfactant called polyvinyl pyrrolidone (PVP-K30) which was added into the LiCl solution for better desiccant regeneration performance. The falling film characteristics and regeneration performance were investigated and compared with and without surfactant. The results indicated that the contact angle of desiccant solution on plate decreased from 58.5° to 28.0° by adding surfactant with 0.4% of concentration. The average wetting area increased from 0.174 m 2 to 0.209 m 2 with a relative increment of 20.1% with the addition of surfactant. Correspondingly, the film thickness had a reduction of 0.103 mm from 0.696 mm to 0.593 mm averagely. The regeneration rate had an average enhancement of 26.3% under the same working conditions, resulting from the decrement of solution contact angle with the addition of the surfactant. Finally, correlations to predict the mass transfer coefficient were proposed with and without surfactant and the mean absolute relative deviation between the results of correlations and the experiments were kept within 8%. The results and findings of present paper could be applied to guide the design of compact regenerator for higher regeneration performance. [ABSTRACT FROM AUTHOR]

After significant efforts from many parties, the World-wide harmonized Light duty Test Procedure (WLTP) has seen its light first as the UNECE Global Technical Regulation and then as the procedure adopted in the type-approval of light-duty vehicles in Europe. The paper focuses its attention on the main procedural differences between the WLTP and the New European Driving Cycle (NEDC), which is the test-procedure currently used in Europe. In general terms the WLTP appears to be a significant improvement compared to the NEDC. The main differences between two test procedures are identified and their impact on CO 2 emissions quantified using the in-house built simulation software CO 2 MPAS. On the basis of each of these differences, the paper assesses the potential total impact on the final reported type-approval CO 2 emissions. The biggest impact on CO 2 emissions is coming from the changes in the road load determination procedure (∼10% increase). Procedural changes concerning the test in the laboratory will bring another 8% and post-processing and declaration of results will result in difference of approximately 5% (each). Overall, the WLTP is likely to increase the type-approval CO 2 emissions by approximately 25%. Therefore, the WLTP will be able to reduce more than half of the gap identified between the type-approval and real-life figures in Europe. This should be seen as a considerable improvement given the ontological limitations of a laboratory-based test procedure. [ABSTRACT FROM AUTHOR]

Capecitabine is a widely used anticancer prodrug of 5-fluorouracil, but up to the present time there is no solubility data reported other than in supercritical carbon dioxide. In this paper, by the polythermal method, the solubility data of capecitabine in fifteen pure lower alcohols and water with methanol mixture solvents were measured from 278.15 K to 323.15 K under atmospheric pressure. The results show that the solubility of capecitabine in linear lower alcohols are bigger than that in corresponding branch chain lower alcohols, and decrease with the increasing of carbons in alkyl of alcohols. Moreover, the solubility of capecitabine increases with the increasing of temperature and mole fraction of methanol in the binary solvent mixtures of water + methanol. To expand industrial application of experimental solubility data of capecitabine in recrystallization, the values measured in selected pure lower alcohols are correlated using the modified Apelblat equation, the Buchowski-Ksiazczak-pletrzyk equation, the van't Hoff equation, the Wilson model and the NRTL model; And for the binary solvent system, the modified Apelblat equation and Jouyban-Acree model are used to correlate the solubility data. By evaluating the deviations between experimental and correlated data, all the correlated data by six models used in this research show comparable precision to those attained by careful experimental measurement. Moreover, some apparent thermodynamic quantities (Δ S d o , Δ H d o , Δ G d o , % ζ H and % ζ TS ) of the dissolution processes of capecitabine in selected solvents and temperature range studied were calculated by the parametric van't Hoff equation. According to the calculation, the dissolution of capecitabine in lower alcohols and water with methanol mixture solvents is an endothermic and entropy-driven process. The solubility and apparent dissolution characteristics of capecitabine in this paper would provide basic support for industrial design and further studies. [ABSTRACT FROM AUTHOR]

The determination of brittleness and geomechanical parameters, especially uniaxial compressive strength (UCS) and Young's modulus (E S ) of rocks are needed for the design of different rock engineering applications. Evaluation of these parameters are time-consuming processes, tedious, expensive and require well-prepared rock cores. Therefore, compressional wave velocity ( V p ) and index parameters such as point load index and porosity are often used to predict the properties of rocks. In this paper, brittleness and other properties, physical and mechanical in type, of 56 Asmari limestones in dry and saturated conditions were analyzed. The rock samples were collected from Khersan 2 dam site. This dam with the height of 240 m is being constructed and located in the Zagros Mountain, in the southwest of Iran. The bedrock and abutments of the dam site consist of Asemari and Gachsaran Formations. In this paper, a practical relation for predicting brittleness and some relations between mechanical and index parameters of the Asmari limestone were established. The presented equation for predicting brittleness based on UCS, Brazilian tensile strength and V p had high accuracy. Moreover, results showed that the brittleness estimation based on B3 concept (the ratio of multiply compressive strength in tensile strength divided 2) had more accuracy as compared to the B2 (the ratio of compressive strength minus tensile strength to compressive strength plus tensile strength) and B1 (the ratio of compressive strength to tensile strength) concepts. [ABSTRACT FROM AUTHOR]

In this paper, the vortex-induced vibration (VIV) characteristics of separated two-box girder were investigated by wind tunnel sectional model tests. Further, a simultaneous pressure measurement test was conducted and the distribution characteristics of the pressure on the surface of the sectional model under VIV were studied. The correlation analysis of the vortex-induced force (VIF) shows that the VIF can be regarded as fully correlated with large amplitude of VIV. And the correlation between distributed vortex-induced force (VIF) and overall VIF and researched. Then the modal decomposition of the pressure time histories was carried out by introducing the high order dynamic mode decomposition (HODMD) method, and the results showed that the reconstruction and prediction of the pressure time histories can be achieved. By ordering modes of pressure snapshots, the main components of the pressure modes and their spatiotemporal distribution were obtained, which are obviously helpful to explain the characteristics of VIV and design VIV countermeasure of the girder. • According to the VIF measured in the experiment, the phase lag between the VIF and the VIV response was analyzed. The phase lag showed a gradually increasing trend in the locking interval, which can be used to explain the characteristics of VIV; • 3. And the key parameter of the relationship between distributed VIF and the overall VIF is discussed: correlation. First, the correlation is affected by the vibration amplitude. Then the correlation of the upstream box girder is more stable, while the downstream correlation shows a certain change pattern along the surface of the box girder. • By introducing the HODMD method, the fluctuating pressure field was reconstructed, and the fluctuating pressure modes with obvious n times to oscillating frequency of VIV was obtained, which helps to understand the distribution characteristics of vortex-induced forces from a more microscopic aspect and the interaction between modes are discussed. • The power distribution of the first-order mode of the fluctuating pressure explains the difference in vortex vibration response at different AoA, and provides mechanistic enlightenment for the control of VIV. [ABSTRACT FROM AUTHOR]

In the process of reconstructing structural forces, the influence of measurement errors and inherent model inaccuracies cannot be ignored. These errors exhibit a degree of correlation, and the presence of such correlation inevitably affects the quantification of uncertainties in force reconstruction. Objectively, the inherent ill-posed nature of structural inverse problems makes it difficult to obtain the forces to be identified, subject to uncertainties and highly susceptible to perturbations. Consequently, this paper introduces a force reconstruction regularization approach that explicitly considers the correlation of uncertainty parameters based on the truncated singular value regularization method. The primary objective is to refine the influence of uncertainties on the reconstructed force bounds with greater precision. When determining robust regularization parameters, the generalized cross-validation method and convex modelling approach are introduced to consider the uncertainty and its correlation in solving inverse problems. The proposed approach is rigorously validated through a comprehensive numerical case study. Error indexes and dispersion indices are employed to analyze the impact of different levels of noise and correlation on force reconstruction results. The force bounds obtained using the proposed method are compared with Monte Carlo simulation results. Finally, the validity of the proposed method is verified by an experiment with a four-story shear frame. [ABSTRACT FROM AUTHOR]