•Both methods are equally effective for developing and analyzing the structural relationship.•CB-SEM demands a lot from the data, whereas PLS-SEM is quite lenient.•For a factor-based model, CB-SEM ...should be used.•For a composite-based model, PLS-SEM should be considered.•CB-SEM and PLSc-SEM methods provide almost similar results.
This study compares the two widely used methods of Structural Equation Modeling (SEM): Covariance based Structural Equation Modeling (CB-SEM) and Partial Least Squares based Structural Equation Modeling (PLS-SEM). The first approach is based on covariance, and the second one is based on variance (partial least squares). It further assesses the difference between PLS and Consistent PLS algorithms. To assess the same, empirical data is used. Four hundred sixty-six respondents from India, Saudi Arabia, South Africa, the USA, and few other countries are considered. The structural model is tested with the help of both approaches. Findings indicate that the item loadings are usually higher in PLS-SEM than CB-SEM. The structural relationship is closer to CB-SEM if a consistent PLS algorithm is undertaken in PLS-SEM. It is also found that average variance extracted (AVE) and composite reliability (CR) values are higher in the PLS-SEM method, indicating better construct reliability and validity. CB-SEM is better in providing model fit indices, whereas PLS-SEM fit indices are still evolving. CB-SEM models are better for factor-based models like ours, whereas composite-based models provide excellent outcomes in PLS-SEM. This study contributes to the existing literature significantly by providing an empirical comparison of all the three methods for predictive research domains. The multi-national context makes the study relevant and replicable universally. We call for researchers to revisit the widely used SEM approaches, especially using appropriate SEM methods for factor-based and composite-based models.
Partial least squares structural equation modeling (PLS‐SEM) is an essential element of marketing researchers' methodological toolbox. During the last decade, the PLS‐SEM field has undergone massive ...developments, raising the question of whether the method's users are following the most recent best practice guidelines. Extending prior research in the field, this paper presents the results of a new analysis of PLS‐SEM use in marketing research, focusing on articles published between 2011 and 2020 in the top 30 marketing journals. While researchers were more aware of the when's and how's of PLS‐SEM use during the period studied, we find that there continues to be some delay in the adoption of model evaluation's best practices. Based on our review results, we provide recommendations for future PLS‐SEM use, offer guidelines for the method's application, and identify areas of further research interest.
The researchers use the SEM-based multivariate approach to analyze the data in different fields, including management sciences and economics. Partial least square structural equation modeling ...(PLS-SEM) and covariance-based structural equation modeling (CB-SEM) are powerful data analysis techniques. This paper aims to compare both models, their efficiencies and deficiencies, methodologies, procedures, and how to employ the models. The outcomes of this paper exhibited that the PLS-SEM is a technique that combines the strengths of structural equation modeling and partial least squares. It is imperative to know that the PLS-SEM is a powerful technique that can handle measurement error at the highest levels, trim and unbalanced datasets, and latent variables. It is beneficial for analyzing relationships among latent constructs that may not be candidly witnessed and might not be applied in situations where traditional SEM would be infeasible. However, the CB-SEM approach is a procedure that pools the strengths of both structural equation modeling and confirmatory factor analysis. The CB-SEM is a dominant multivariate technique that can grip multiple groups and indicators; it is beneficial for analyzing relationships among latent variables and multiple manifest variables, which can be directly observed. The paper concluded that the PLS-SEM is a more suitable technique for analyzing relations among latent constructs, generally for a small dataset, and the measurement error is high. However, the CB-SEM is suitable for analyzing compound latent and manifest constructs, mainly when the goal is to generalize results to specific population subgroups. The PLS-SEM and CB-SEM have specific efficiencies and deficiencies that determine which technique to use depending on resource availability, the research question, the dataset, and the available time.
Structural equation modeling (SEM) has become the methodology of choice for many family business researchers investigating complex relationships between latent constructs, such as family harmony or ...family cohesion. Its capability to evaluate complex measurement models and structural paths involving a multitude of variables and levels of constructs has enabled family business researchers to investigate complex and intricate relationships that previously could not be easily untangled and examined. In many cases, however, researchers struggle to meet some of the challenging requirements of covariance-based SEM (CB-SEM), the most commonly used approach to SEM, such as distribution assumptions or sample size. In this article, we point out the benefits and disadvantages of CB-SEM, and present a comparison with partial least squares-SEM (PLS-SEM) using an identical sample. We find that even though both methods analyze measurement theory and structural path models, there are many advantages in applying PLS-SEM.
•We investigate if 3D models from FIB-SEM image stacks are a suitable REV for shale.•Data include groups of local 2D and 3D images and corresponding core measurements.•Image analysis of image stacks ...and LBM fluid flow simulations are performed.•We conclude that FIB-SEMs are not suitable domains for permeability simulations.•Averaging local 2D and 3D images can provide representative volumetric properties.
Shales and other unconventional or low permeability (tight) reservoirs house vast quantities of hydrocarbons, often demonstrate considerable water uptake, and are potential repositories for fluid sequestration. The pore-scale topology and fluid transport mechanisms within these nanoporous sedimentary rocks remain to be fully understood. Image-informed pore-scale models are useful tools for studying porous media: a debated question in shale pore-scale petrophysics is whether there is a representative elementary volume (REV) for shale models? Furthermore, if an REV exists, how does it differ among petrophysical properties? We obtain three dimensional (3D) models of the topology of microscale shale volumes from image analysis of focused ion beam-scanning electron microscope (FIB-SEM) image stacks and investigate the utility of these models as a potential REV for shale. The scope of data used in this work includes multiple local groups of neighboring FIB-SEM images of different microscale sizes, corresponding core-scale (milli- and centimeters) laboratory data, and, for comparison, series of two-dimensional (2D) cross sections from broad ion beam SEM images (BIB-SEM), which capture a larger microscale field of view than the FIB-SEM images; this array of data is larger than the majority of investigations with FIB-SEM-derived microscale models of shale. Properties such as porosity, organic matter content, and pore connectivity are extracted from each model. Assessments of permeability with single phase, pressure-driven flow simulations are performed in the connected pore space of the models using the lattice-Boltzmann method. Calculated petrophysical properties are compared to those of neighboring FIB-SEM images and to core-scale measurements of the sample associated with the FIB-SEM sites. Results indicate that FIB-SEM images below ∼5000 µm3 volume (the largest volume analyzed) are not a suitable REV for shale permeability and pore-scale networks; i.e. field of view is compromised at the expense of detailed, but often unconnected, nanopore morphology. Further, we find that it is necessary to acquire several local FIB-SEM or BIB-SEM images and correlate their extracted geometric properties to improve the likelihood of achieving representative values of porosity and organic matter volume. Our work indicates that FIB-SEM images of microscale volumes of shale are a qualitative tool for petrophysical and transport analysis. Finally, we offer alternatives for quantitative pore-scale assessments of shale.
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The study aimed to conduct in vitro biological assessments of hydantoin and thiohydantoin compounds against mature Schistosoma mansoni worms, evaluate their cytotoxic effects and predict their ...pharmacokinetic parameters using computational methods. The compounds showed low in vitro cytotoxicity and were not considered hemolytic. Antiparasitic activity against adult S. mansoni worms was tested with all compounds at concentrations ranging from 200 to 6.25 μM. Compounds SC01, SC02, and SC03 exhibited low activity. Compounds SC04, SC05, SC06 and SC07 caused 100 % mortality within 24 h of incubation at a concentration of 100 and 200 μM. Thiohydantoin SC04 exhibited the highest activity, resulting in 100 % mortality after 24 h of incubation at a concentration of 50 μM and IC50 of 28 µM. In the ultrastructural analysis (SEM), the compound SC04 (200 µM) induced integumentary changes, formation of integumentary blisters, and destruction of tubercles and spicules. Therefore, the SC04 compound shows promise as an antiparasitic against S. mansoni.
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•Hydantoin and thiohydantoin compounds have shown in vitro anti-parasitic activity against Schistosoma mansoni.•Thiohydantoin SC04 caused 100 % mortality at 50 µM after 24 hours, likely by inhibiting motor activity.•The compounds are predicted to have good pharmacokinetic profiles and oral availability in in silico models.•They exhibited low cytotoxicity on mammalian cells in vitro.•Thiohydantoin SC04 caused significant damage to the worms' integument, with blistering and erosion.
Summary
The introduction of cryo‐techniques to the focused ion‐beam scanning electron microscope (FIB‐SEM) has brought new opportunities to study frozen, hydrated samples from the field of Life ...Sciences. Cryo‐techniques have long been employed in electron microscopy. Thin electron transparent sections are produced by cryo‐ultramicrotomy for observation in a cryo‐transmission electron microscope (TEM). Cryo‐TEM is presently reaching the imaging of macromolecular structures. In parallel, cryo‐fractured surfaces from bulk materials have been investigated by cryo‐SEM.
Both cryo‐TEM and cryo‐SEM have provided a wealth of information, despite being 2D techniques. Cryo‐TEM tomography does provide 3D information, but the thickness of the volume has a maximum of 200–300 nm, which limits the 3D information within the context of specific structures. FIB‐milling enables imaging additional planes by creating cross‐sections (e.g. cross‐sectioning or site‐specific X‐sectioning) perpendicular to the cryo‐fracture surface, thus adding a third imaging dimension to the cryo‐SEM. This paper discusses how to produce suitable cryo‐FIB‐SEM cross‐section results from frozen, hydrated Life Science samples with emphasis on ‘common knowledge’ and reoccurring observations.
Lay Description
Life Sciences studies life down to the smallest details. Visualising the smallest details requires electron microscopy, which utilises high‐vacuum chambers. One method to maintain the integrity of Life Sciences samples under vacuum conditions is freezing. Frozen samples can remain in a suspended state. As a result, research can be carried out without having to change the chemistry or internal physical structure of the samples.
Two types of electron microscopes equipped with cryo‐sample handling facilities are used to investigate samples: The scanning electron microscope (SEM) which investigates surfaces and the transmission electron microscope (TEM) which investigates thin electron transparent sections (called lamellae). A third method of investigation combines a SEM with a focused ion beam (FIB) to form a cryo‐FIB‐SEM, which is the basis of this paper. The electron beam images the cryo‐sample surface while the ion beam mills into the surface to expose the interior of the sample. The latter is called cross‐sectioning and the result provides a way of investigating the 3rd dimension of the sample. This paper looks at the making of cross‐sections in this manner originating from knowledge and experience gained with this technique over many years. This information is meant for newcomers, and experienced researchers in cryo‐microscopy alike.
Silurian shale in Sichuan Basin is currently the most important target zone for shale gas exploration and development in China. Pore structure characteristics of Lower Silurian Longmaxi shales from ...southern Sichuan Basin were investigated. The combination of field emission scanning electron microscope (FE–SEM) and argon ion beam milling was utilized to describe the nanometer-to micrometer-scale (>1.2nm) pore systems. The shales were characterized by organic geochemical and mineralogical analyses. Total porosity, pore size distribution (PSD), specific surface area, and gas content were determined. Controls of organic matter richness, thermal maturity, and mineralogy on porosity were examined. The contribution of individual mineral components to total porosity was analyzed quantitatively. Total gas contents of the shales determined from canister desorption data were compared with theoretical (sorptive and volumetric) gas storage capacities.
The total organic carbon (TOC) content of the shale samples ranges between 0.1 and 8.0 wt.% and helium porosity varies between 0.7 and 5.7%. Maturity in terms of equivalent vitrinite reflectance of bitumen (Reqv) ranges from 1.8 to 3.2%. TOC content is a strong control for the pore system of these shales, and shows a positive correlation with porosity. Porosity increases with increasing thermal maturity when Reqv is less than 2.5%, but decreases for higher thermal maturity samples. FE–SEM reveals four pore types related to the rock matrix that are classified as follows: organic matter (OM)–hosted pores, pores in clay minerals, pores of framework minerals, and intragranular pores in microfossils. Pores in clay minerals are always associated with the framework of clay flakes, and develop around rigid mineral grains because the pressure shadows of mineral grains prevent pores from collapsing. Pores of framework minerals are probably related to dissolution by acidic fluids, and the dissolution–related pores promote porosity of shales. A unimodal PSD exists in the micropore range of TOC–rich samples, while the PSD of carbonate–rich samples are bimodal. A PSD maximum in the micropore range is attributed by OM and another maximum in the range of mesopore–macropores is probably caused by the dissolution of carbonate minerals. Quantitative evaluation of the contribution of individual mineral components to porosity shows that the organic matter contributes approximately 62% to the total porosity. Framework minerals (quartz, feldspar, and carbonates, et al.) and clay minerals contribute 25% and 13%, respectively. The total gas content of these shales ranges from 0.4 to 6.2m3/t, and the total gas contents of selected samples determined from canister desorption tests agree with the theoretically estimated original gas-in-place (OGIP). OM-hosted pores are the main space for gas storage, and accounted for about 78% (55% adsorbed gas plus 23% free gas) of the OGIP, while pores in the inorganic matter accommodate 22% free gas of the OGIP.
•TOC are primary controlling factors on porosity for Lower Silurian shales in the southern Sichuan Basin, China•Pore size distributions of TOC-rich samples are unimodal while PSD of carbonate-rich samples are bimodal•The contribution of individual mineral components to total porosity has been quantitatively evaluated.•OGIP from USBM method and indirect estimations has been compared•The predominant gas is stored in OM-hosted pores
Purpose
Following the call for awareness of accepted reporting practices by Ringle, Sarstedt, and Straub in 2012, the purpose of this paper is to review and analyze the use of partial least squares ...structural equation modeling (PLS-SEM) in Industrial Management & Data Systems (IMDS) and extend MIS Quarterly (MISQ) applications to include the period 2012-2014.
Design/methodology/approach
Review of PLS-SEM applications in information systems (IS) studies published in IMDS and MISQ for the period 2010-2014 identifying a total of 57 articles reporting the use of or commenting on PLS-SEM.
Findings
The results indicate an increased maturity of the IS field in using PLS-SEM for model complexity and formative measures and not just small sample sizes and non-normal data.
Research limitations/implications
Findings demonstrate the continued use and acceptance of PLS-SEM as an accepted research method within IS. PLS-SEM is discussed as the preferred SEM method when the research objective is prediction.
Practical implications
This update on PLS-SEM use and recent developments will help authors to better understand and apply the method. Researchers are encouraged to engage in complete reporting procedures.
Originality/value
Applications of PLS-SEM for exploratory research and theory development are increasing. IS scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for research. Recommended reporting guidelines following Ringle et al. (2012) and Gefen et al. (2011) are included. Several important methodological updates are included as well.
Aluminum based metal matrix composites (AMMCs) have the potential for replacing conventional monolithic materials due to excellent fatigue, creep and wear resistance, high temperature retention, and ...high strength to weight ratio. Thus Aluminum based metal matrix composites have several applications in different industries including Aerospace and Automotive. This study revealed that Al 6063 based metal matrix composites reinforced with Al2O3, SiC, TiO2 have higher hardness, tensile strength, and yield strength as compared to the pure Al 6063. This study shows that hardness, tensile strength, and yield strength are increasing as increasing SiC particles content. Microstructure and surface morphological studies have been carried out to see their surface and particles distribution. Energy Dispersive X-ray Spectroscopy (EDS) and XRD analysis have been conducted to identify elements content. Fourier Transform Infrared Spectroscopy (FTIR) analysis is carried out to identify chemical functional group of the Al6063 metal matrix composites.