Numerical Data Research Articles

Maintaining Accuracy While Reducing Effort in Online Decision Making: A New Quantitative Approach for Multi-Attribute Decision Problems Based on Principal Component Analysis

This paper explores consumer decision making, particularly focusing on the increasing prevalence of choices on the Internet such as online shopping. Examining the fundamental question of how individuals decide how to decide, our paper draws upon the effort–accuracy framework. This framework indicates that people typically consider both the cognitive effort associated with employing a specific decision strategy and the decision quality (i.e., accuracy) implied by using a particular strategy. However, decision strategies with high accuracy imply high effort. Empirical evidence shows that people often use decision strategies that require little effort. As a result, accuracy is often not high. Against this backdrop, this paper introduces a quantitative approach leveraging principal component analysis (PCA) as a decision support tool. Based on a simulation study, the approach demonstrates that it is possible to maintain high accuracy with significantly reduced effort in multi-attribute decision situations where attribute information is available in a quantitative format. This demonstration is based on the example of two decision strategies, which are both theoretically and practically highly relevant: the multi-attribute utility model (MAU) and the elimination-by-aspects strategy (EBA). By employing PCA for dimensionality reduction, the approach becomes particularly advantageous for online shops and online comparison portals, presenting users with concise yet accurate information. It is important to emphasize that our PCA approach is designed for data with a natural ordering, primarily focusing on quantitative variables. Consequently, decision situations where qualitative variables (e.g., product design or color) play a role in the decision-making process will need further exploration in future studies. However, we present a first solution to this problem so that our approach, based on this solution, can be implemented by online shops and online comparison portals in the near future.

Development of Kagome-based functionally graded beams optimized for flexural loadings

This study is concerned with the development of an innovative beam geometry based on a tessellation of Kagome unit cells and the improvement of its geometry with the aim of increasing its flexural properties. This aspect was achieved by generating a functionally graded metamaterial structure based on a novel approach that considers the well-established analytical beam theory models as the basis of for the optimization of the structural parameters of the unit cells at an individual level. The starting premise is that the optimal strut thickness variation with the height of the beam will cause the material to yield uniformly in the critical cross-section. Preliminary studies were conducted in order to numerically determine the variation of the stiffness and the strength of the Kagome structure with the thickness of its struts. Considering the equivalent stress distribution during bending in the critical cross-section, an optimal variation of the stiffness with the height of the beam was evaluated. Based on these results, different values for the strut diameter were imposed at corresponding coordinates relative to the neutral axis, assuring a continuous transition across the height of the beam. The flexural properties of the developed functionally graded structure were evaluated using finite element analyses and determined superior characteristics when compared with the data obtained from simulations performed on an uniform Kagome beam with of the same mass. The investigated structures were manufactured through stereolithography and subjected to three-point bending tests, the results being in agreement with the numerical data, thus validating the design.

Mobility of trace elements in a coastal contaminated site under groundwater salinization dynamics

Water pollution is a significant issue resulting from past long-term actions. The remediation projects carried out under law constraints for industrial plants, which have been the major contributors to environmental and water pollution, are currently providing a significant amount of data about contaminated soil, surface waters, and groundwater. Most of such plants worldwide are in coastal zones. Based on a significant amount of chemical and environmental data for a coastal contaminated site subject to variable groundwater salinization, this study aimed to understand the mobility of some trace elements because of coastal zone dynamics. Data concerned 688 groundwater samples, including As, Hg, Cd, Crtot, Cu, Ni, Pb, V, Se, Zn, pH, electrical conductivity, chlorides, total organic carbon and organic contaminants as quantitative variables, enhanced by additional qualitative variables such as groundwater salinity, season, water level, precipitation, and industrial activity type to make the dataset as representative as possible of the site under investigation. The study used robust multivariate statistical analyses to analyse the complex dataset and explain the relevant factors influencing contaminant behaviour under different environmental conditions. The Multivariate Statistical Analysis distinguished three clusters of trace elements with diverse reactivity to changes in groundwater salinization. The first includes Se, Cu, Crtot, V, and Ni, showing the highest correlation with electrical conductivity and chlorides because of their high affinity to form chloride or organic chloride complexes and for ion competition. Zn and Pb cluster in the second group: they are less reactive to groundwater salinization and more influenced by cation and anion competition and organic matter. The mobility of Hg and As (third cluster) significantly correlates with Fe and Mn, underlining the dominant role of reductive dissolution of trace elements-bearing minerals (Fe/Mn/Al-oxy-hydroxides) and metal-organic complexes. The correlation between the clustering of variables in groundwater and soils shows the influence of sediment structure, mineral composition, and physical and chemical soil conditions on the distribution in soils of trace elements and their transport to groundwater. The study proposes a valuable approach for assessing the effects of salinization in contaminated coastal aquifers. It supports planning multi-purpose characterization and monitoring campaigns of contaminated coastal sites and provides guidance on the correct associated remediation projects.

Relationship between employer branding and employee performance: Mediating and moderating effects of supportive work environment and compensation and benefits

Employer branding is a complex idea that is important in many different industries. It represents a company's ability to attract, engage and retain talent as well as its status as an employer. A strong employer brand transcends industry boundaries to impact the success and sustainability of businesses in today's competitive job market. The authors examined the effect of employer branding on employee performance by mediating and moderating roles of a supportive work environment and compensation and benefits respectively. The authors followed the quantitative methodology with a set of strategies and hypotheses and gathered numerical data. The data were gathered by surveying employees working in information technology sector companies in the city of Bangalore. The data analysis includes descriptive statistics, factor analysis and structural equation modeling analysis using SPSS and IBM AMOS version 28. The Cronbach’s alpha values of the reliability statistics ranged from 0.920 to 0.930 indicating the questionnaire’s internal consistency and reliability. The model fit indices CMIN/DF 1.389, CFI 0.966, GFI 0.952, TLI 0.961, IFI 0.966, NFI 0.904, SRMR 0.060, RMSEA 0.051 and PClose 0.448 indicate an excellent fit of the model. The constructs of compensation and benefits and a supportive work environment partially mediate employee performance through employer branding. The moderator’s supportive work environment strengthens the positive relationship between employee branding and employee performance. Strong employer branding is important for attracting top talent and improving employee performance in various industries but it is especially important in the IT sector.

Study of MHD Casson Nanofluid Flow Over an Inclined Stretching Sheet in Porous Media with Thermal Slip, Chemical Reaction and Radiation Effects

In the current study, the behaviour of Casson nanofluid subjected to magnetohydrodynamic (MHD) flow across an inclined stretched sheet within a porous medium has been investigated numerically. The governing equations are transformed into ordinary differential equations with the corresponding boundary conditions by employing similarity transformations. The solutions of essential equations are achieved by using the 4th-order Runge-Kutta method combined with the shooting technique. The novelty and innovative contribution are showcased through illustrative graphs that scrutinize the effect of factors that impact the velocity, temperature, and concentration profiles within assorted flow scenarios. The primary focal points of the study encompass examining variations in magnetic field strength, angle of inclination, and suction intensity that affect the fluid's velocity moderation, while improved porosity and radiation parameters lead to a rise in fluid temperature. Higher Biot numbers correlate with an increase in fluid temperature. The implications of positive coefficients of heat transfer are crucial across various fields to ensure efficient thermal management ensuring optimal performance and longevity. The numerical data presented is aligned with earlier published results for comparison. Furthermore, the variations in skin friction, Nusselt, and Sherwood numbers driven by different parameters are displayed in tables to highlight significant modifications.

Dynamic state awareness for distribution network based on robust adaptive cubature kalman filter

With the rapid development of the economy and society, the demand for power quality is constantly increasing. As a crucial part of grid situational awareness, distribution network state estimation plays a vital role in providing critical data support for other advanced applications, which is significant for ensuring the safe and reliable operation of the distribution network. Therefore, this paper proposes a dynamic state awareness method for distribution networks based on the robust adaptive cubature Kalman filter (RACKF). The proposed solution, grounded on the core computational concept of the cubature Kalman filter (CKF), constructs a robust noise statistical estimator (NSE) composed of a biased NSE and an unbiased NSE to adapt to the unknown and time-varying process noise parameters in the dynamic state estimation process. The proposed solution can ensure that the calculated process noise parameters always meet the constraints and guarantee the robustness of the algorithm. In addition, an estimation strategy for the fusion of multi-time scale measurement data is developed according to the RACKF-based dynamic state estimation features in order to realize system state corrections and updates. The results of simulation experiments and comparisons with traditional CKF methods demonstrate the accuracy and superiority of the proposed solution.

Effect of ionizing radiation on the shear bond strength of two different adhesive systems in primary teeth. in-vitro study

BackgroundRadiotherapy is a treatment modality used for head and neck cancer patients. It has a negative influence on bonding strength of adhesives. Little information is available about the effect of radiotherapy on bonding strength of adhesives in primary teeth. Therefore, this in vitro study aimed to detect the best adhesive system and ideal time to apply restorations in primary irradiated teeth regarding adhesive shear bond strength.MethodsDentin samples from primary teeth were randomly assigned to four groups based on restoration application time and radiation exposure, (G1: control, G2: preradiation, G3: 24 h postradiation, and G4: 6 months postradiation) with 20 samples per group. These groups were further divided into 2 subgroups according to the adhesive system used, with 10 samples per subgroup. (1) 3M™ Single Bond Universal Adhesive (SB), (2) 3M AdperSingle Bond 2 (AS). Samples were exposed to gamma radiation from a cobalt-60 machine. One shot of 60 Gy of radiation was delivered. Then samples were subjected to a shear bond strength test. The load was applied until failure and the maximum load was recorded. Numerical data are presented as mean and standard deviation values, then distributed according to Shapiro–Wilk test or Levene's test and analyzed via two-way ANOVA. The significance level was set at p < 0.05 for all tests. Statistical analysis was performed with R statistical analysis software version 4.4.1 for Windows (Team RC, R: A language and environment for statistical computing. R foundation for statistical computing, 2023).ResultsCompared with the AS subgroup, the SB subgroup presented significantly greater values (p < 0.001). For SB, there was no significant difference among the G1 and G4 groups (p > 0.001). However, there was a significant difference between G1, G2, and G3 (p < 0.001, P = 0.025, P = 0.265 ns respectively), and G3 presented the lowest values. For AS, there was no significant difference between groups G1 and G4 (p = < 0.001). Compared with the other groups, G3 presented a significant difference (p = 0.265 ns) and the lowest results.ConclusionRestorations performed 24 h after radiation had lower bond strength than those performed six months after radiation. Regardless of the adhesive system used, SB performed better than AS in terms of the shear bond strength.

Hybrid Machine Learning Approach to Zero-Inflated Data Improves Accuracy of Dengue Prediction.

Spatiotemporal dengue forecasting using machine learning (ML) can contribute to the development of prevention and control strategies for impending dengue outbreaks. However, training data for dengue incidence may be inflated with frequent zero values because of the rarity of cases, which lowers the prediction accuracy. This study aimed to understand the influence of spatiotemporal resolutions of data on the accuracy of dengue incidence prediction using ML models, to understand how the influence of spatiotemporal resolution differs between quantitative and qualitative predictions of dengue incidence, and to improve the accuracy of dengue incidence prediction with zero-inflated data. We predicted dengue incidence at six spatiotemporal resolutions and compared their prediction accuracy. Six ML algorithms were compared: generalized additive models, random forests, conditional inference forest, artificial neural networks, support vector machines and regression, and extreme gradient boosting. Data from 2009 to 2012 were used for training, and data from 2013 were used for model validation with quantitative and qualitative dengue variables. To address the inaccuracy in the quantitative prediction of dengue incidence due to zero-inflated data at fine spatiotemporal scales, we developed a hybrid approach in which the second-stage quantitative prediction is performed only when/where the first-stage qualitative model predicts the occurrence of dengue cases. At higher resolutions, the dengue incidence data were zero-inflated, which was insufficient for quantitative pattern extraction of relationships between dengue incidence and environmental variables by ML. Qualitative models, used as binary variables, eased the effect of data distribution. Our novel hybrid approach of combining qualitative and quantitative predictions demonstrated high potential for predicting zero-inflated or rare phenomena, such as dengue. Our research contributes valuable insights to the field of spatiotemporal dengue prediction and provides an alternative solution to enhance prediction accuracy in zero-inflated data where hurdle or zero-inflated models cannot be applied.

Integration of Metrology in Grinding and Polishing Processes for Rotationally Symmetrical Aspherical Surfaces with Optimized Material Removal Functions

Aspherical surfaces, with their varying curvature, minimize aberrations and enhance clarity, making them essential in optics, aerospace, medical devices, and telecommunications. However, manufacturing these surfaces is challenging because of systematic errors in CNC equipment, tool wear, measurement inaccuracies, and environmental disturbances. These issues necessitate precise error compensation to achieve the desired surface shape. Traditional methods for spherical optics are inadequate for aspherical components, making accurate surface shape error detection and compensation crucial. This study integrates advanced metrology with optimized material removal functions in the grinding and polishing processes. By combining numerical control technology, computer technology, and data analysis, we developed CAM software (version 1) tailored for aspherical surfaces. This software uses a compensation correction algorithm to process error data and generate NC programs for machining. Our approach automates and digitizes the grinding and polishing process, improving efficiency and surface accuracy. This advancement enables high-precision mass production of rotationally symmetrical aspherical optical components, addressing existing manufacturing challenges and enhancing optical system performance.

Development and Optimization of a Micro-Baffle for the Enhancement of Heat Transfer in Film Boiling

This study represents the development and optimization of a micro-baffle design to enhance heat transfer in film boiling. Numerical simulations are performed using an open-source computational fluid dynamics (CFD) model, which incorporates the Lee model for momentum source associated with the phase change, and the Volume of Fluid (VOF) method to capture bubble dynamics. A comparison of the numerical results with the previous numerical and experimental data confirmed the validity of the numerical model. The influence of key design parameters was systematically investigated. The results revealed that a vertical baffle provided the maximum performance. The optimal baffle design achieved a 57.4% improvement in the Nusselt number and a 66.4% increase in critical heat flux (CHF). Furthermore, the proposed design facilitated continuous bubble formation, even with a reduced temperature difference between the heated surface and the subcooled liquid, which is crucial for energy-efficient thermal management in engineering systems. Ultimately, this study demonstrates the potential of micro-baffle designs in controlling bubble dynamics and improving heat transfer in film boiling, thereby aiding the design of efficient thermal systems.

A Theoretical and Experimental Investigation of the Effects of Inverted Wings Modifications on the Stability and Aerodynamic Performance of a Sedan Car at Cornering

ABSTRACTThis research examines the impact of cornering on the aerodynamic forces and stability of a Nissan Versa (Almera) passenger sedan car by introducing novel modifications. These modifications included single inverted wings with end plates as a front spoiler, double‐element inverted wings with end plates as a rear spoiler, and incorporating the ground as a diffuser under the car trunk. The goal is to enhance the performance and stability of conventional passenger cars. To ensure the accuracy of the numerical data, the study utilized multiple methodologies to model the turbulence model, ultimately selecting the most suitable option. This involved comparing numerical data with wind tunnel experimental data using force balance and pressure distribution. Once validated, the computational fluid dynamics (CFD) was employed to analyze the vehicle's aerodynamic performance relative to the straight‐line condition under cornering conditions. The car simulation in a cornering condition was conducted at a representative Reynolds number based on the vehicle length of about 1.3 × 107. The study discovered that asymmetry was a recurring theme regarding surface pressure distribution, with greater prominence under cornering conditions. All modified models exhibited a more favorable lift‐to‐drag ratio than the baseline, indicating improved aerodynamic efficiency. The underbody double‐element diffuser proved most effective for enhancing fuel efficiency and stability. Mesh refinement with a polyhedral algorithm consisting of 11.27 million elements and a computational domain with a frontal area of 91.8 m2 and a curved length of 31 m (˜7 times car length) was crucial for achieving accurate and repeatable results. The study employed multiple turbulence models within the CFD framework. The realizable k‐ε model was chosen due to its balance between accuracy and computational cost for all Nissan Versa models. These findings are limited to the selected parameters and wind tunnel conditions, and further investigations might be needed for extreme driving scenarios.

Theoretical development and validation of asphalt concrete density measurement using non-contact interdigital coplanar capacitive sensor

Asphalt concrete (AC) density serves as a critical criterion for quality control and quality assurance in asphalt pavement construction. Current non-destructive testing (NDT) approaches have shown potential for AC density measurement, but they present disadvantages such as inefficiency and unstable accuracy. This paper developed a novel NDT approach for AC density measurement based on non-contact interdigital coplanar capacitive sensor (ICCS). The feasibility of this approach was evaluated through both numerical and experimental validations. Firstly, the theoretical model of non-contact ICCS for AC density measurement was established based on conformal mapping technique, partial capacitance technique, and dielectric mixing model. Secondly, numerical simulations were performed to validate the developed theoretical model under two scenarios. Thirdly, laboratory experiments were conducted to measure capacitance data and predict density for three common types of ACs. Finally, the error of non-contact ICCS was discussed and compared with that of other NDT instruments. The results indicated that the developed theoretical model could establish the relationship between AC density and capacitance value, which provided the basis for AC density measurement using non-contact ICCS. It was also observed that the capacitance data obtained by the proposed model closely matched those computed by numerical simulations. The maximum errors between theoretical and numerical data were 4.10% and 1.08% for two cases respectively, which proved the feasibility of the theoretical model. Furthermore, experimental results indicated that the capacitance value of AC specimens increased by about 1 pF as the rolling time increases due to a decrease in the volume of air in AC, which reaffirms the validity of AC density measurement using non-contact ICCS. Additionally, the non-contact ICCS demonstrated excellent accuracy with a maximum error of 6.69%, which is comparable to the current mainstream NDT approaches. And it has the advantages of lower cost, simpler data processing and higher efficiency. The findings of this paper offer a new and reliable method and tool for non-destructive and large-scale AC density measurement.

Resource allocation for Hyphantria cunea invasive management:a novel simulation-based optimization model

In this study, we propose an integrated mixed-integer programming (MIP) model for allocating a limited budget to control a destructive invasive insect endangering the forest vegetation, Hyphantria cunea (H. cunea). Our model seeks to minimize the number of infected and dead trees within a preset planning period, factoring in various infestation scenarios, migration behaviors, resource limitations, intervention timing, and monitoring capabilities. Our modeling framework is novel in the sense that it depicts the transmission process of H. cunea as an infectious compartmental model. Our optimization model is also meaningful because it innovatively bridges the spread dynamics of H. cunea and the optimal resource allocation by using the time-varying number of infected trees that can be accepted in testing and surveillance. Our numerical test data and parameter settings have been collected from large-scale field surveys on H. cunea in Jiangsu Province over the past three years. The scenarios-based method offers significant computational advantages in searching for the best alternatives to real-world size problems in a rational time. Furthermore, our test results specify that the proposed model can not only aid in controlling H. cunea, but also can be adopted as a potential tool for managing other invasive species in the future.

Density of pure and mixed NaCl and CaCl2 aqueous solutions at 293 K to 353 K and 0.1 MPa: an integrated comparison of analytical and numerical data

This study reports on newly acquired density data of synthetically prepared pure and mixed NaCl and CaCl2 aqueous solutions that span a wide range of geothermally encountered concentrations and mixing ratios. The analytical data are provided for the temperature range of 293–353 K at ambient pressure. For the reproduction of that data, PHREESCALE was used. The predictive potential of this numerical tool regarding the density of geothermal fluids of known composition was the major target herein. As a result, the measured data are in good agreement with previous analytical studies found in the literature. Possible sources of errors are discussed in this paper. Density data of the mixed solutions at temperatures other than ambient are unique and close existing data gaps. The numerical model reproduces the newly measured and already existing density data within an error band of approximately 1%. For further use in geothermal applications, this can be considered an excellent agreement. Moreover, the model yields a direct calculation of density without the need to establish complex empirical equations of state and mixing rules. Finally, sensitivity calculations performed with a thermal–hydraulic (TH) numerical reservoir model demonstrate the required accuracy of fluid density for reliably predicting the long-term performance of deep geothermal energy systems. In terms of the productivity index and the timing of thermal breakthrough it shows that the present analytical and numerical uncertainty in density is small enough to reliably state both reservoir parameters.

The Effects of the COVID-19 Pandemic on Pediatric Orthopedic Injuries: A Single-Center Retrospective Study.

The COVID-19 pandemic has had a profound effect on the pediatric population worldwide. The consequences of the lockdown and the reallocation of hospital resources have caused notable changes in the presentation of pediatric orthopedic injuries. Through our use of patient records, we were able to display the epidemiological trends, as well as analyze the changes in the type and mechanism of various injuries. Our purpose is to further understand the considerable effects of the COVID-19 pandemic on pediatric orthopedic trauma and help guide the allocation of future healthcare resources. We conducted a retrospective cohort study on pediatric patients admitted for any orthopedic injury over a 3-year period (September 2018 to August 2021) at a Midwest level 1 trauma center. Cases were stratified into two groups based on the United States' COVID-19 lockdown (19 March 2020): Pre-COVID-19 cases were any cases prior to the lockdown and Intra-COVID-19 which are cases following the lockdown. Numerical data and categorical variables were summarized and differences between the case groups were examined using either two-Proportion Z-Test, Independent Two-Sample t-test, Pearson's chi-squared, or Fisher's exact tests. A total of 3179 pediatric orthopedic referrals occurred between the Pre-COVID-19 and Intra-COVID-19 study periods. We observed a general decrease in orthopedic injuries following the COVID-19 lockdowns with 1235 injuries compared to 1606 Pre-COVID-19. Patterns in the locations of injuries changed; notably, fractures of the humerus, tibia, and fibula decreased significantly (p < 0.05). Several mechanisms of injuries decreased significantly following the onset of COVID-19 including injuries caused by monkey bars, basketball, and automobiles (p < 0.01). There was a significant increase in the overall injury severity during the Intra-COVID-19 period (p < 0.05). Although there was a reduction in acute orthopedic trauma referrals, many injury mechanisms displayed similar trends regardless of restrictions. We clinically observed an overall increase in the severity of pediatric orthopedic injuries during the COVID-19 pandemic.

How Late Nights Influence Brain Cortical Structures: Distinct Neuroanatomical Measures Associated With Late Chronotype in Young Adults.

Chronotype is an inherent physiological trait reflecting an individual's subjective preference for their sleep awakening time, exerting a substantial influence on both physical and mental well-being. While existing research has established a close relationship between chronotype and individual brain structure, prior studies have predominantly focused on individual measurements of brain structural scales, thereby limiting the exploration of the underlying mechanisms of structural changes. This study seeks to validate previous research findings and enhance our understanding of the correlation between circadian rhythm preference and diverse cortical indicators in healthy young individuals. Magnetic resonance imaging (MRI) scans and chronotype assessments were conducted once for all participants, comprising 49 late chronotype (LC) young adults and 49 matched early chronotype young adults. The Chronotype Questionnaire was utilized to assess morningness and eveningness preferences. Surface-based analysis of structural MRI data revealed that LC young adults exhibited thinner cortical thickness of left pars orbitalis and lower cortical mean curve of right paracentral gyrus. Overall, this study represents a significant advancement in elucidating the connection between brain structure and function within the context of chronotypes.

Numerical and experimental frequency analysis of damaged fiber‐reinforced metal laminated composite

AbstractThis research numerically evaluated the eigenvalue responses of the damaged fiber metal laminate (FML) structure. The current numerical model is delved into including crack‐type damage effect on the structural integrity/ stiffness via frequency response. In this regard, a complete mathematical model of FML has been derived through higher‐order shear deformation kinematics for computational purposes. The mathematical model is converted to computer code in the MATLAB platform to predict the eigenvalue responses of FML components with and without damage. The damage influences are considered via circular meshing of finite element steps associated with the isoparametric element (nine nodes and nine degrees of freedom for each node). The solution consistency is checked via convergence, and the results are compared with data available in the open domain. Further, an experimental test is carried out to improve confidence using an in‐house test rig. The experiment was conducted by varying the length of the FML in 0.1 m increments. The results showed good agreement between the numerical and experimental data, with the lowest deviation being 0.29% and the highest 8.97%. The developed numerical model is extended to analyze the influences of design parameters such as geometry shape, aspect ratio (a/b), thickness ratio (a/h) ratio, curvature ratio, and fiber layup sequence on the natural frequency response.

Long-Term Efficacy and Tolerability of an Emollient Containing Glycerol and Paraffin for Moderate-to-Severe Uremic Xerosis: A Randomized Phase3 Study.

There is an unmet need for effective topical therapies for patients with uremic xerosis and chronic kidney disease-associated pruritus (CKD-aP). The long-term efficacy and tolerability of an emollient containing glycerol 15% and paraffin 10% (V0034CR) was evaluated in a phase3 study. In this randomized, double-blind, two-parallel group, vehicle-controlled study, patients with moderate-to-severe uremic xerosis were randomized to once-daily application of V0034CR or vehicle control for 28days (periodI). This was followed by a treatment-free period of ≤ 21days (periodII), then all patients received open-label treatment with V0034CR for ≥ 84days (periodIII). Outcomes included treatment response at the end of periodI (El Gammal's xerosis severity score), instrumental measures of scaling (D-Squame technique), time to relapse during periodII, rate of recurrence during periodIII, pruritus severity over time, patient acceptability, and adverse events (AEs). The intent-to-treat population comprised 235 patients randomized to V0034CR (n = 118) or vehicle control (n = 117) during periodI. Treatment response at the end of periodI was achieved by 71 patients (60.2%) in the V0034CR group versus 48 (41.0%) with vehicle control (p = 0.0041). This coincided with greater reductions in the total surface area of squames (p = 0.001 vs vehicle control). Xerosis relapsed progressively without treatment in periodII; however, remission was durable under maintenance therapy in periodIII. Improvements in pruritus severity were comparable between V0034CR and vehicle control, suggesting that the antipruritic effect of V0034CR was mainly exerted by its oil-in-water emulsion base. V0034CR had high patient acceptability and was well tolerated; the most common treatment-related AEs were irritation or erythema (2.1%), exacerbated pruritus (1.3%), and vesicles at the application site (0.9%). These data support the use of V0034CR, with its hydrating and occlusive properties, for the long-term management of patients with moderate-to-severe uremic xerosis and CKD-aP. ClinicalTrials.gov identifier NCT01084148; EudraCT number 2006-002201-31.

Hydrodynamic exposure – on the quest to deriving quantitative metrics for mariculture sites

This work attempts to define metrics for hydrodynamic exposure, using known oceanographic variables to provide a universal site assessment method for mariculture structures. Understanding environmental conditions driving open-ocean mariculture siting is crucial in establishing consistent ocean governance, minimizing adverse environmental impacts, and facilitating economically sustainable farm operations. To provide a metric of oceanic conditions and associated requirements for structural design and operation of aquaculture systems, six Exposure Indices (EI) are proposed that consider physical energy levels related to hydrodynamic forces at a site. Four of the proposed indices consider only environmental conditions, while the other two also consider the dimensions of the gear that is exposed to the external loads. These indices are: Exposure Velocity (EV), Exposure Velocity at Reference Depth (EVRD), Specific Exposure Energy (SEE), Depth-integrated Energy Flux (DEF), Structure-centered Depth-integrated Energy (SDE), and a Structure-centered Drag-to-Buoyancy Ratio (SDBR). While these indices are derived with a focus on aquaculture structures, they may also have applications for estimating biological stressors and operational challenges. The proposed exposure indices were evaluated for a range of known aquaculture sites around the world. A sensitivity analysis was conducted that quantified the relationship between the exposure indices and storm event return period. At a regional scale, hindcast numerical data for the German Bight combined with calculations of 50-year extreme values were used to calculate and map each proposed index spatially. Resulting maps showed that exposure is not simply a function of distance from shore. The six indices show plausible performance regarding the objective assessment of aquaculture sites. The authors herein present the indices to the aquaculture and ocean engineering communities for discussion, application, and potential adoption of one or more of the proposed indices.

Investigating the link between coronary artery calcification and atrial fibrillation: A systematic review and meta-analysis.

Both coronary artery calcification (CAC) and atrial fibrillation (AF) are associated with common risk factors, such as age, hypertension, diabetes, and dyslipidemia. Investigating their association may provide insights into shared pathophysiological mechanisms and overlapping risk profiles. A systematically search was performed covering various data bases including PubMed, Scopus, ISI, and Google Scholar from January 2000 until December 2023 for English-published articles. We focused on observational studies-cohort, case-control, and cross-sectional-that involved adult participants (aged 18 and older) and provided data on the any association between CAC and AF. We excluded studies if the full text was unavailable, the publication was not in English, there was insufficient numerical data or relative risk information. All the included articles (n = 14), were observational studies (n = 5 case-control and n = 9 cohort). All of the included papers (100%), reported a link between CAC and higher rate of major adverse cardiovascular events such as stroke and mortality in AF patients. The overall prevalence of AF across 5 studies was estimated to be 9.00% (95% confidence intervals [CI]: 2.00, 16.00), and 60% of the AF population were male. The overall proportion of AF in individuals with a coronary artery calcification score (CACS) of 0 is relatively high at 0.48 (95% CI: 0.32, 0.64), followed by CACS (1-99) which was 0.22 (95% CI: 0.16, 0.28), CACS (100-399) which was 0.17 (95% CI: 0.07, 0.28), and CACS (≥ 400) as 0.14 (95% CI: 0.07, 0.22). It can be concluded that there is a robust and consistent association between CAC and AF. Our systematic review underscores the importance of considering CAC as a potential factor in assessing the risk of AF, while also recognizing the multifactorial nature of this relationship.