Effectiveness Of Different Methodologies Research Articles

Selecting methods for a modular EEG pre-processing pipeline: An objective comparison

Electroencephalography (EEG) to study brain functions has become fundamental in many research settings across very different protocols. Indeed, a plethora of processing methods have been developed, for both data preparation (pre-processing) and analysis. While an effect of the pre-processing on the signal is admitted and accepted, there is an increasing effort to better understand to which extent such an influence may affect the analysis results, and which may be the best practices for the correct data pre-processing.Pre-processing procedures include different steps, and each of them may induce modifications affecting the study results. Thus, we analyze the effect of different methodologies at each step and propose quantitative parameters for the choice of the preferable strategy.We illustrate how method selection may affect the quality of EEG signal in an Action Observation and Motor Imagery protocol, using quantitative indices. We analyzed the effect of different strategies for early-stage data preparation; two independent component analysis (ICA) algorithms (SOBI and Extended Infomax) used for artifact removal; and four re-reference approaches (Common averaged reference-CAR, robust-CAR, reference electrode standardization technique – REST, and reference electrode standardization and interpolation technique – RESIT). The effects of the different pipelines were also evaluated through the computation of event-related spectral perturbation (ERSP) of the sensorimotor rhythm. Results showed that signal segmentation significantly affects the cleaning procedure, while comparable results are obtained across ICA approaches. Finally, similar topographical representations were obtained after the application of CAR, REST, and RESIT re-referencing approaches, where rCAR showed the most different ERSP topographical pattern.

Classification Insights into Brain MRI Classification: Techniques, Interpretability, and Future

This research paper comprehensively analyses various techniques for classifying brain MRI images. Through an extensive literature survey, the study explores and evaluates the effectiveness of different methodologies, ranging from traditional machine learning approaches to advanced deep learning models, in the context of brain tumour classification. The review critically examines feature extraction, selection methods, and classification algorithms, focusing on their performance in enhancing diagnostic accuracy. The synthesis of existing literature provides valuable insights into the current landscape of brain MRI classification techniques, shedding light on their strengths, limitations, and potential areas for future research.

A comparison of the effects of different methodologies on the statistics learning profiles of prospective primary education teachers from a gender perspective

Over the last decades, it has been shown that teaching and learning statistics is complex, regardless of the teaching methodology. This research presents the different learning profiles identified in a group of future Primary Education (PE) teachers during the study of the Statistics block depending on the methodology used and gender, where the sample consists of 132 students in the third year of the PE undergraduate degree in the University of the Basque Country (Universidad del País Vasco/Euskal Herriko Unibertsitatea, UPV/EHU). To determine the profiles, a cluster analysis technique has been used, where the main variables to determine them are, on the one hand, their statistical competence development and, on the other hand, the evolution of their attitude towards statistics. In order to better understand the nature of the profiles obtained, the type of teaching methodology used to work on the Statistics block has been taken into account. This comparison is based on the fact that the sample is divided into two groups: one has worked with a Project Based Learning (PBL) methodology, while the other has worked with a methodology in which theoretical explanations and typically decontextualized exercises predominate. Among the results obtained, three differentiated profiles are observed, highlighting the proportion of students with an advantageous profile in the group where PBL is included. With regard to gender, the results show that women's attitudes toward statistics evolved more positively than men's after the sessions devoted to statistics in the PBL group.

Ammonia quantum tunneling in cold rare-gas He and Ar clusters and factorial design approach for methodology evaluation.

Quantum tunneling of the ammonia inversion motion and energy level splittings in He and Ar clusters were investigated. It was found that the double well potential (DWP) in He clusters is symmetrical and that the first layer of He atoms is able to model the system. The calculated tunneling splitting was in good agreement with the experimental, 36.4 and 24.6 cm[Formula: see text] respectively. For NH[Formula: see text] in Ar clusters, the DWP becomes slightly asymmetric, which is enough to decrease the resonance and make the symmetric DWP unable to model the system. An asymmetric potential was used and the result was in excellent agreement with the experimental splitting, of 9.0 and 10.6 cm[Formula: see text] respectively. Non-covalent interactions revealed that the asymmetry is caused by dissimilar interactions in each minimum of the double well potential. The effects of different methodologies were analyzed via a design of experiments approach. For the gas-phase NH[Formula: see text] molecule, only diffuse functions were statistically significant while for the NH[Formula: see text] embedded in He cluster both the MP2 method and polarization functions were significant. This tendency suggests higher order polarization functions may be essential to generate accurate barrier heights.

Systematic Review and Meta-Analysis of Efficiency in Maritime Industry

The purpose of this paper is to complement and extend previous literature reviews on technical efficiency (TE) in Maritime Industry, analysing the effects of different methodologies and study-specific characteristics on Mean Technical Efficiency (MTE). The researchers independently conducted a systematic review of more than 171 full text papers from four key electronic databases and the results from meta-regression analysis of 35 published papers in maritime industry worldwide are discussed. The variation in the mean indexes in the literature can be explained by the methodology of estimations (parametric, non-parametric), the data collecting scheme and sample size. This study makes two important contributions: first, it updates and compares previous works on frontier estimation efficiency in maritime industry; and second, it has brought in ‘sector’ as another dimension for analysis.

Selection of insulation materials with PSI-CRITIC based CoCoSo method

The performance effect of construction on energy conservation substantially depends upon application of correct materials and energy saving methodologies. A sizable financial impact is accomplished through insulated walls. The criteria explaining the present wall insulating material options may have different values. Furthermore, they may alter in different aspects, i.e. higher values of certain criteria show a preferable status, while for others they denote an inferior status. In this framework, a variant of compromise is needed, which can be situated through multi-criteria assessment methodologies. To diminish the effect of different methodologies on computational results, few diverse techniques can be considered, with descriptions of the mean predicted values. Thus, drawbacks of certain multi-criteria assessment techniques could be compensated through others. A hybrid methodology through the combination of individual techniques will be accurate if there is a relationship between the values determined through diverse methodologies. In this study, the most efficient insulation material used at external walls is selected by using PSI-CRITIC based CoCoSo Method. The analytical results are important both from financial and engineering point of views as the applied methodology is commercially viable and practically implementable. Precise and up-to-date material properties are derived from the leading companies in the sector.

A CT-based deep learning model for predicting the nuclear grade of clear cell renal cell carcinoma

PurposeTo investigate the effects of different methodologies on the performance of deep learning (DL) model for differentiating high- from low-grade clear cell renal cell carcinoma (ccRCC). MethodPatients with pathologically proven ccRCC diagnosed between October 2009 and March 2019 were assigned to training or internal test dataset, and external test dataset was acquired from The Cancer Genome Atlas-Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) database. The effects of different methodologies on the performance of DL-model, including image cropping (IC), setting the attention level, selecting model complexity (MC), and applying transfer learning (TL), were compared using repeated measures analysis of variance (ANOVA) and receiver operating characteristic (ROC) curve analysis. The performance of DL-model was evaluated through accuracy and ROC analyses with internal and external tests. ResultsIn this retrospective study, patients (n = 390) from one hospital were randomly assigned to training (n = 370) or internal test dataset (n = 20), and the other 20 patients from TCGA-KIRC database were assigned to external test dataset. IC, the attention level, MC, and TL had major effects on the performance of the DL-model. The DL-model based on the cropping of an image less than three times the tumor diameter, without attention, a simple model and the application of TL achieved the best performance in internal (ACC = 73.7 ± 11.6%, AUC = 0.82 ± 0.11) and external (ACC = 77.9 ± 6.2%, AUC = 0.81 ± 0.04) tests. ConclusionsCT-based DL model can be conveniently applied for grading ccRCC with simple IC in routine clinical practice.

Children's Mental Models of Prenatal Development.

Children's thinking about prenatal development requires reasoning about change that cannot be observed directly. How do children gain knowledge about this topic? Do children have mental models or is their knowledge fragmented? In Experiment 1, results of a forced-choice questionnaire about prenatal development (6- to 13-year-olds; N = 317) indicated that children do have a variety of coherent, grade-related, theories about early shape of the fetus, but not about bodily functions. Coherence of the mental models was enhanced by a preceding generative task. Children's mental models were in agreement with reasoning about natural transformations (Rosengren et al., 1991) and constraints in representational flexibility (Karmiloff-Smith, 1992). In Experiment 2, an open-question interview was administered (6- to 12-year-old children; N = 38). The interview resulted in grade-unrelated, incoherent responses. This study contributes to a deeper understanding of naïve biology and to the effects of different methodologies being used in the area of mental models.

The Effectiveness of Different Methodologies in Gathering Information for Developing BIM Models to Support the Operation and Maintenance of Existing Buildings

Systematic, preventive and corrective maintenance is essential for existing buildings in order to retain their original functionality and appearance and satisfy the needs of the users. Essential input for maintenance is information about buildings. This paper discusses the assessment of the advantages and limitations of using photogrammetry and a low-cost 3D scanner to collect information from existing buildings and create, through integrative software, BIM models as information systems to support the operation and maintenance functions. Also, these methodologies were compared with one another as well as with a manual information survey conducted at a university campus. The main conclusion is that a combination of methods must be used to obtain geometrical information on existing buildings for their operation and maintenance functions, depending on which ones are the most suitable for the case at hand.

Monitoring and controlling ovarian activities in wild ungulates

Reproductive success in females relies primarily upon better understanding of fundamental ovarian processes to facilitate captive reproductive management and ultimately the development of assisted reproductive technologies as an alternative tool for conservation breeding of endangered wildlife species. Wild ungulates (cervids and non-domestic bovids) are an extraordinarily diverse group of mammals with remarkable diversity in reproductive biology (anatomy, behaviour, physiology and seasonality). This indicates a clear need, and indeed a big challenge, for acquiring such basic reproductive knowledge in severely threatened ungulates before attempting even a simpler technology such as artificial insemination. Despite a few sporadic successes of artificial insemination technology in ungulates, there is much to learn, including optimizing estrus synchronization protocols and an animal-friendly fixed-time insemination procedure that would maximize breeding success with minimal stress to the animal. Recent advances in non-invasive methodologies for monitoring endocrine profiles and assessment of ovarian function in wildlife species enable us to understand and characterize basic reproductive events in a species. This review discusses non-invasive approaches being used for monitoring endocrine and ovarian activity in wild ungulates. Further, it reviews the effectiveness of different methodologies for control of estrus and ovulation in non-domestic bovids and cervids. Additionally, the challenges regarding their application in different ungulates as a standard routine practice like in livestock are addressed.

Systematic review and meta-regression analysis of technical efficiency in dairy farms

Purpose – The purpose of this paper is to complement and extend previous literature reviews on Technical Efficiency (TE) in dairy farms, analysing the effects of different methodologies and study-specific characteristics on Mean TE (MTE). Design/methodology/approach – The researchers independently conducted a systematic review of more than 400 abstracts and 85 full-text papers. Original keywords were applied to seven key electronic databases. Results from a meta-regression analysis of 85 published papers totalling 443 TE distributions in dairy farms worldwide are discussed. Findings – The variation in the MTE indexes reported in the literature can be explained by the methodology of estimations (method of estimation, functional form of frontier models, model dimensionality), the farms geographical location and farm size. Additionally, the results suggest that, given the state of technology prevailing in each country at the time that the studies on TE were conducted, dairy farmers in the sample could increase milk output by 20.9 per cent (level of inefficiency), on average, if they produce on their frontiers. Originality/value – This study makes two important contributions: first, it updates and compares previous works on frontier estimation of TE in dairy farms; and second, it adds two dimensions of dairy farms, size (herd and land area) and economic development, to the known differentials of TE measurement.

Reversal Strategies for Intracranial Hemorrhages in Patients Taking Oral Factor Xa Inhibitors.

Factor Xa (fXa) inhibitors are becoming more common in clinical practice due to a variety of reasons. Unfortunately, limited data are currently available on the safe and efficacious reversal of these agents. This series presents 3 patient cases of intracranial hemorrhage and illustrates the observed effect of different methodologies undertaken in an attempt to reverse the fXa inhibitors implicated. Additionally, a brief review of the current available literature in reversal strategies is provided. The appropriate reversal for fXa inhibitors at this time is unknown. The cases described indicate that the administration of fresh frozen plasma and 4-factor prothrombin complex concentrate may provide minimal benefit in reversing the coagulation abnormalities caused by fXa inhibitors. However, in a life-threatening situation, the addition of these agents should be considered to prevent further progression of the bleed.

Flow Cytometry of Extracellular Vesicles: Potential, Pitfalls, and Prospects

AbstractEvidence suggests that extracellular vesicles (EVs) can play roles in physiology and pathology, providing impetus to explore their use as diagnostic and therapeutic targets. However, EVs are also small, heterogeneous, and difficult to measure, and so this potential has not yet been realized. The development of improved approaches to EV detection and characterization will be critical to further understanding their roles in physiology and disease. Flow cytometry has been a popular tool for measuring cell‐derived EVs, but has often been used in an uncritical manner in which fundamental principles and limitations of the instrument are ignored. Recent efforts to standardize procedures and document the effects of different methodologies have helped to address this shortcoming, but much work remains. In this paper, I address some of the instrument, reagent, and analysis considerations relevant to measurement of individual EVs in flow, with the aim of clarifying a path to quantitative and standardized measurement of these interesting and potentially important biological nanoparticles. © 2015 by John Wiley & Sons, Inc.

Effectiveness of different methodologies for the selective enumeration of Lactobacillus acidophilus La5 from yoghurt and Prato cheese

Prior to the selective enumeration of probiotic microorganisms in fermented dairy products, a preliminary evaluation of different culture media and incubation conditions is required to choose a suitable culture medium. The objective of this study was to evaluate the effectiveness of different methodologies for the selective enumeration of Lactobacillus acidophilus in probiotic yoghurt and Prato cheese. For selective enumeration of L. acidophilus, four methods were investigated under anaerobic conditions, as follows: MRS agar containing bile solution; MRS agar containing clindamycin solution; and MRS agar containing sorbitol solution, each one incubated at 37 °C for 72 h, and MRS agar containing sorbitol incubated at 45 °C for 72 h. These methodologies were used for enumeration of both the pure cultures and the microorganisms from probiotic yoghurt and Prato cheese. The results showed that the best selective medium for enumeration of L. acidophilus from yoghurt was MRS agar containing bile incubated at 37 °C for 72 h under anaerobic conditions. For enumeration of this probiotics from Prato cheese, MRS agar containing sorbitol incubated at 45 °C for 72 h under anaerobic conditions was proven to be the best selective medium.

Modeling machining of particle-reinforced aluminum-based metal matrix composites using cohesive zone elements

Finite element modeling for the machining of heterogeneous materials like particle-reinforced metal matrix composites has not been much successful as compared to homogeneous metals due to several issues. The most challenging issue is to deal with severe mesh distortion due to nonuniform deformation inside the workpiece. Other problems are related to the modeling of the interface between reinforcement particles and matrix and tool-reinforcement particle interaction. In this study, different strategies are adopted for finite element models (FEM) to cope with the above issues and comparative analyses have been performed. These 2D FE models are based on plane strain formulations and utilize a coupled temperature displacement method. The workpiece is modeled using reinforcement particle size and volume fraction inside the base matrix. The interface between the reinforcement particles and the matrix is modeled by using two approaches, with and without cohesive zone elements, and the chip separation is modeled with and without using a parting line. This allows models to simulate the local effects such as tool-reinforcement particle interaction and reinforcement particle debonding. In addition, the models can predict cutting forces, chip morphology, stresses, and temperature distributions. The effects of different methodologies on the model development, simulation runs, and predicted results have been discussed. The results are compared with experimental data, and it has been found that the utilization of cohesive zone elements (CZE) with the parting line approach seems to be the best one for the modeling of metal matrix composite (MMC) machining.

Assessment of the Effectiveness of Different Methodologies for Oral Hygiene Training

Assessment of the Effectiveness of Different Methodologies for Oral Hygiene Training

FINITE ELEMENT MODELING OF THE ORTHOGONAL MACHINING OF PARTICLE REINFORCED ALUMINUM BASED METAL MATRIX COMPOSITES

2D finite element models (FEM) are developed to simulate orth- ogonal machining of particle reinforced aluminum based metal matrix composites (MMC). The models predict cutting forces, chip morphology, temperatures and stresses distributions. The simulations were carried out by developing a fully coupled temperature displacement model. In contrast to the equivalent homogeneous material (EHM) methodology, a heterogeneous model is developed based on reinforcement particle size and volume fraction. This allows models to simulate the local effects such as tool-reinforcement particle interaction, reinforcement particle debonding. The interface between the reinforcement particles and the matrix is modeled by using two approaches; with and without cohesive zone elements. Similarly the chip separation is modeled with and without using a parting line. The effect of different methodologies on the model development, simulation runs and predicted results have been discussed. The results are compared with experimental data and it has been found that the utilization of cohesive zone modeling (CZM) with the parting line approach seems to be the best one for the modeling of MMC machining. homogeneity and abrasive nature of reinforcement particles. Mostly MMC are fabricated with near net shape processes but some machining and finishing cuts are indispensable for final dimensions and surface finishes. Cutting tools such as high speed steel, cast cobalt alloys, cemented carbides and cermets cannot be used for machining of MMC due to high wear rate. Diamond cutting tools are found to be the best option for machining of MMC and they are being utilized in the last ten years for both particles and fibers based MMC (Looney 1992, Schwartz 1997, Muthukrishnan 2008). Fiber reinforced composites are anisotropic as fibers are not equi- axes, whereas particulate reinforced composites are isotropic like conventional metals. The later provide higher ductility and their isotropic nature make them a better choice as compared to fiber reinforced composites. Machinability of particulate reinforced composites depend on many factors like particulate type, its orientation, tool material, tool geometry and cutting conditions like cutting speed, feed etc. Numerous studies exist in the literature to analyze machining of MMC using experiments and mostly related to measure performance variables like tool wear, surface roughness, sub surface damage, cutting forces, cutting temperatures and chip morphology (Davim 2011). It has been found that parameters related to structure of composite greatly affect the machinability. These include reinforcement material, reinforcement type, volume fraction of the particles, base metal properties and overall arrangement of constituent phases. Polycrystalline diamond inserts (PCD) are commonly employed for their machining (Weinert 1993, Quigley 1994). Use of other ceramics materials like cubic boron nitride (CBN), alumina and silicon nitride are also reported but did not have a major success. Effects of cutting parameters (speed, feed and depth of cut) on machinability of MMC is almost similar to that found in machining of conventional metals with some differences due to abrasive nature of particles. The reinforced particles tend to expelled out from the base metal and slide in front of the cutting tool edge. This results in plowing through the newly generated machined surface and groove marks on it (El-Gallab 1998) (Manna 2003).

Characterising F(0) contour shape in infant- and foreigner-directed speech

Previous research has used both natural and simulated interactions to investigate the functions of infant-directed speech (IDS), but the effect of these approaches on the results of such studies is unclear. The aim of this study was to compare F(0) contours of natural and simulated speech directed to three distinct speech recipient groups to investigate the effects of different methodologies on research findings. F(0) contours were derived from IDS, foreign-directed speech (FDS) and speech directed to a native adult speaker (ADS). The speech was produced by ten students and ten actresses in simulated ‘interactions’ with an imaginary speech partner and compared to an existing dataset of natural mother–infant interactions. The F(0) contours were analysed with a qualitative and a quantitative method. In the existing natural dataset, IDS F(0) contours (mainly sinusoidal–bell shapes) had been markedly different from FDS and ADS F(0) contours (mainly level shapes). However, these results were not reproducible in the simulated interactions with either students or actresses. Here, the different shapes were more evenly distributed across IDS, FDS and ADS with no difference between these three groups. Consequently, it is suggested that simulated speech should be used with caution in IDS or any other speech research.

Initiating Children into Hermeneutical Discourses in Religious Education

In response to previous articles in this journal by Rachel Cope and Julian Stern, and using an example of classroom practice, this article promotes a form of multi-faith religious education in which primary-school pupils (age 5–11) are re-conceived as joint researchers working alongside their teachers, through processes of imaginative and empathetic dialogue, to investigate the effectiveness of different methodologies and methods of studying religion(s). This pedagogical strategy seeks to teach pupils the disciplinary knowledge and skills associated with the communities of academic practice concerned with theological and religious studies, and more specifically to initiate them into the hermeneutical discourses which underlie theological and religious research and teaching. Moreover, it is argued that some of the suggested practices could be applied to the study of spirituality in any context and could contribute to the spiritual development of participants.

Optimization of prediction methods for patents and trademarks in Spain through the use of exogenous variables

An accurate forecast of patent and trademark application filings is strategic for resource planning at the Spanish Patents and Trademarks Office and other patent offices, national and supranational. The need for reliable forecasts of patents and trademarks application filings has been accentuated by the current situation of budgeting rationalization imposed by the economic crisis. In this study we have evaluated the suitability and effectiveness of different methodologies for advanced data analysis to predict the number of national patent and trademark applications in the short and medium terms (2011–2014), including the use of exogenous variables or predictors which help to understand the changes in these variables. The inclusion of exogenous variables which explain the behavior of patent and trademark application filings, in particular the investment in R&D and GDP, and the use of advanced predictive analysis techniques, amongst which the most notable are Polynomial Distributed Lags and Intelligent Transfer Function models, have all achieved an improvement upon the prediction and modeling power possessed by the models formerly used to predict trademark and patent series based only on the analysis of time series.