Common Methodology Research Articles

One-Dimensional Acrylamide Gel Electrophoresis for Analysis of Plant Samples.

Polyacrylamide gel electrophoresis (PAGE) is a widely used technique for separating proteins from complex plant samples. Prior to the analysis, proteins must be extracted from plant tissues, which are rather complex than other types of biological material. Different protocols have been applied depending on the protein source, such as seeds, pollen, leaves, roots, and flowers. Total protein amounts must also be determined before conducting gel electrophoresis. The most common methodologies include PAGE under native or denaturing conditions. Both procedures are used consequently for protein identification and characterization via mass spectrometry. Additionally, various staining procedures are available to visualize protein bands in the gel, facilitating the software-based digital evaluation of the gel through image acquisition.

Modelling recycling for the life cycle assessment of perovskite/silicon tandem modules

With the massive growth of the global capacity of photovoltaics (PV) over the last decade, the PV waste is expected to increase dramatically in the near future. Having potential to reduce the use of raw materials and preserve natural resources, PV recycling is attracting more and more attention. This being said, the environmental impacts over the life cycle of PV technologies, including the end-of-life (EoL) stage, should be evaluated carefully. Life cycle assessment (LCA) is currently the most common methodology to assess the potential environmental impacts of a product throughout its entire life cycle. However, the modelling of recycling in LCA has always been a challenge and no consensus has yet been reached, since the treatment of recycling does not only involve an EoL management of waste, but also the production of recycled material. Perovskite on silicon tandem is a widely investigated emerging PV technology having the potential to overcome the power conversion efficiency (PCE) limit of the single-junction crystalline silicon technology. The EoL modelling seems more challenging in the case of emerging technologies for which the EoL is more uncertain than for established technologies. In this article, six common and important approaches of EoL modelling in LCA were applied to future perovskite/silicon tandem modules to analyze the effect of the different EoL modelling approaches on the LCA results. The aim was to identify the most suitable methodological approaches to account for recycling, when modelling the life cycle of PV modules. The environmental performance of perovskite/silicon tandem modules was assessed over their life cycle and expressed in terms of impacts per m2 of module. After testing the six EoL modelling approaches and comparing the LCA results, the EoL modelling choice was found to lead to non-negligible differences. For example, in terms of climate change, the impact of the tandem modules ranges from 45 to 59 kg CO2-eq/m2. Among the six EoL modelling options, the approaches of simple cut-off and cut-off with economic allocation are more oriented towards the promotion of high rates of recycled material integrated as an input to the assessed product among industrial actors, while the approach of closed-loop allocation provides incentives to maximize the ratio of recycling at the EoL, regardless the initial ratio of recycled content within the product. Some approaches such as the circular footprint formula (CFF) tend to provide both incentives to increase the content of recycled input material in the manufacturing of the product and the recycling ratio at the EoL of such product. After applying the different alternatives, a set of recommendations to select the relevant EoL modelling approaches are provided: 1) the CFF is recommended as a representative approach due to its wide applicability, tending to provide an intermediate result and reflecting the characteristics of materials; 2) sensitivity analysis should be applied to check the robustness of the results, 3) the cut-off approach and the closed-loop allocation should be used at least for the sensitivity analysis.

Application of craniosacral therapy in practice

Systematic evaluation of the evidence for the use of craniosacral therapy (CST) in practice. The following English-only electronic databases were searched: PubMed, Scopus, PEDro, Cochrane Library. The review of journal databases was conducted between March and June 2023. The databases were searched using MeSH (Medical Subject Headings) terms, keywords and logical operators. The results from the statistical analyses performed were taken into account. Only twenty-five studies met the inclusion criteria. Positive clinical results were reported for reduction of pain, reduction of crying in children, reduction of stress hormones, and improvement of patients’ general well-being. The methodological quality of the PEDro scale ranged from 1 to 11 points. The review indicates a significant effect on patient outcomes/symptoms. There is a need for multi-center studies with common CST methodology in groups with large numbers. Trial registration: PROSPERA registration number: CRD42023430923

Trends of Utilization Plants Resources among Santhal of Nepal

An ethnobotanical survey was conducted in Gauradaha municipality of Jhapa, Nepal. The objectives of study were documentation of ethnobotanical practices of santhal tribes. Some common ethnobotanical methodologies and techniques were applied during the course of study. Altogether 30 households were surveyed. 56 peoples were participated among them 8 were informants of age ranged from 40 to 90 years. Total 88 varieties of plants were listed which are used for different purpose and these species were distributed among 76 genera of 49 families. The highly represented family was Poaceae (7 species), Solanaceae (6 species), Compositae (5 species). The remaining families comprise very few species of identified plants. Distribution of plants according to habit were reported, among them herbs (42%), shrubs (27%), trees (24%) and climbers (7%).The majority of the plant species were reported to be used for medicinal purpose (36%)followed by multiple used i.e. a plant used for different purpose (27%), vegetable(12%), fodder (6%), food (6%), ornamental (5%), religious (5%) and fruit (3%).Distribution of plants according to part used were reported i.e. leaf (30%), multiple part i.e. different parts of a plant used (17%), fruit (16%), whole part (10%), stem (9%), seed(6%), root (6%), flower (4%) and bark (2%) for various purpose. So, from this study it is clear that this tribe has good knowledge about the importance of plant available in the study area.

Non-average Stability Analysis for a Boost Converter

The purpose of this paper is to present a method for analyzing the stability of DC-DC boost converters providing a universal transfer function. This method relies on the application of the Laplace transform without any ad-hoc linear approximation or system linearization. A common methodology for evaluating the stability of DC-DC converters is the average method, which is essentially a linearization. In this paper, the Laplace transform is applied directly, resulting in a universal Z-transform model being used to design controllers and stability analyses as a discrete unifying transfer function. The examples cover both power and low voltage converters. Matlab simulations have been conducted to verify the theoretical findings. In particular, the second example considers a small 5V to 12V boost converter, which was previously examined in a Texas Instruments application note. The transfer functions and the Bode plot are provided.

Power market models for the clean energy transition: State of the art and future research needs

As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero‑carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.

Economic recommender systems – a systematic review

Many of today’s online services provide personalized recommendations to their users. Such recommendations are typically designed to serve certain user needs, e.g., to quickly find relevant content in situations of information overload. Correspondingly, the academic literature in the field largely focuses on the value of recommender systems for the end user. In this context, one underlying assumption is that the improved service that is achieved through the recommendations will in turn positively impact the organization’s goals, e.g., in the form of higher customer retention or loyalty. However, in reality, recommender systems can be used to target organizational economic goals more directly by incorporating monetary considerations such as price awareness and profitability aspects into the underlying recommendation models. In this work, we survey the existing literature on what we call Economic Recommender Systems based on a systematic review approach that helped us identify 135 relevant papers. We first categorize existing works along different dimensions and then review the most important technical approaches from the literature. Furthermore, we discuss common methodologies to evaluate such systems and finally outline the limitations of today’s research and future directions.

Exploring the global thunderstorm influence on the fair weather electric field in Buenos Aires

The Global atmospheric Electric Circuit (GEC) sustains the fair weather (FW) electric field, or potential gradient (PG). In this article, we analyze PG measurements recorded between 2017 and 2021 at the Instituto de Investigaciones Científicas y Técnicas para la Defensa (CITEDEF) in Buenos Aires, Argentina, to calculate the daily PG (FW) curve and examine whether local PG measurements capture the GEC signal. With the aim of supporting future common methodologies that do not rely on meteorological data for FW identification - and hence aid inter-comparisons, we rely on previously developed statistical methodologies to propose a FW selection based on the absolute deviation from the median of the data series. Using this methodology we filtered FW days and showed that the local PG (FW) curve had a significant correlation of 0.83 with the Carnegie curve. In order to test the extent to which the local daily PG (FW) curve captures the global thunderstorm signal, the area of thunderstorms was calculated at both global and regional scales using data from the Thunder Hour Database (http://thunderhours.earthnetworks.com). The PG (FW) curve was shown to have a good correlation with the daily median variation of the global thunderstorm area on both annual and quarterly scales. Additionally, the analysis of coincident aerosol optical thickness (AOD) measurements by the AERONET network and temperature observations helped to conclude that local effects such as pollution from a near highway are not dominating the PG (FW) curve behaviour. Both analyses allowed us to conclude that the GEC signal can be detected in Buenos Aires.

Combined sun-photometer–lidar inversion: lessons learned during the EARLINET/ACTRIS COVID-19 campaign

Abstract. The European Aerosol Research Lidar Network (EARLINET), part of the Aerosols, Clouds and Trace gases Research Infrastructure (ACTRIS), organized an intensive observational campaign in May 2020, with the objective of monitoring the atmospheric state over Europe during the COVID-19 lockdown and relaxation period. Besides the standard operational processing of the lidar data in EARLINET, for seven EARLINET sites having collocated sun-photometric observations in the Aerosol Robotic Network (AERONET), a network exercise was held in order to derive profiles of the concentration and effective column size distributions of the aerosols in the atmosphere, by applying the GRASP/GARRLiC (from Generalized Aerosol Retrieval from Radiometer and Lidar Combined data – GARRLiC – part of the Generalized Retrieval of Atmosphere and Surface Properties – GRASP) inversion algorithm. The objective of this network exercise was to explore the possibility of identifying the anthropogenic component and of monitoring its spatial and temporal characteristics in the COVID-19 lockdown and relaxation period. While the number of cases is far from being statistically significant so as to provide a conclusive description of the atmospheric aerosols over Europe during this period, this network exercise was fundamental to deriving a common methodology for applying GRASP/GARRLiC to a network of instruments with different characteristics. The limits of the approach are discussed, in particular the missing information close to the ground in the lidar measurements due to the instrument geometry and the sensitivity of the GRASP/GARRLiC retrieval to the settings used, especially for cases with low aerosol optical depth (AOD) like the ones we show here. We found that this sensitivity is well-characterized in the GRASP/GARRLiC products, since it is included in their retrieval uncertainties.

Intensive Malware Detection Approach based on Data Mining

Malicious software, sometimes known as malware, is software designed to harm a computer, network, or any of the connected resources. Without the user's knowledge, malware can spread throughout their computer system. Malware is typically disseminated via online connections and mobile devices. While malware has always been a problem in the digital age, its effects have gotten increasingly serious. Traditional malware detection methods seek to locate specific malware samples and families to recognize harmful codes and can be located using traditional signature- and rule-based detection methods. The research focuses on developing malware detectors using data mining techniques. The proposed method outlined below sets itself apart by emphasizing the processing of malware behaviors significantly dependent on aspects. Finding more dependable intelligent detecting techniques is a crucial component of this paper. In order to identify the cluster of the most essential malware features and use decision tree classifiers for malware detection, the study, a common methodology for creating malware detectors based on data mining, is implemented and investigated. Our approach can identify the most significant features of malware that can significantly determine and detect a malware code.

Collaborative Partnerships, Religious Reputation Culture, and Digital Tourism Promotion in Support of Halal Tourism Villages

This study focuses on two primary aspects of investigation. Firstly, it examines the digital methods that Small to Medium Tourism Enterprises (SMTEs) utilize and collaborative patterns with branding strategies to cultivate halal tourism villages. It employs a qualitative descriptive approach within the social phenomenology framework. Secondly, it identifies the most suitable alternative for SMTEs’ development using a Quantitative Strategic Planning Matrix (QSPM). The research concludes that enhancing SMTEs involves a multifaceted approach, including effective planning, digital transformation, fostering collaboration, and investing in halal-friendly infrastructure with standardization in halal certification. Through a qualitative approach and QSPM analysis, the study identifies strategic priorities like collaborative partnerships, religious reputation culture implementation, and digital tourism promotion as crucial strategies for SMTEs’ success. This research significantly contributes to the development of halal tourism enterprises by involving a unique context, employing less common methodology, and focusing on sustainable development. The limitations of this study pertain to the impact of uncontrollable external changes, while the future research agenda explores predictive modeling and regional comparisons to advance further the understanding of strategy outcomes in halal tourism development.

Price Discovery and Market Efficiency in India's Financial Futures Market within the Derivatives Landscape: An Empirical Analysis

This study offers a robust, long-term analysis of price discovery and the persisting lead-lag relationship between India’s equity futures and spot markets. Utilising monthly data from April 2005 to December 2022, it filters transient noise typically associated with high-frequency data. Information Share and Common Factor Weight methodologies within the Vector Error Correction (VEC) framework consistently reveal the dominance of futures markets in the price discovery process. The insights remain consistent across three distinct periods spanning the global financial crisis and the COVID-19 pandemic. The volatility dynamics and asymmetry effects in the Indian equity futures and spot markets using the Vector Error Correction - Exponential General Autoregressive Conditional Heteroskedastic (VEC-EGARCH) approach uncover notable asymmetry effects, signifying a strong market sensitivity to negative news. This highlights the necessity for comprehensive risk management strategies and stringent regulatory supervision, especially in light of the significant growth and systemic risks in the Indian derivatives market.

What Can Student Theses Tell Us About the Educational Role of School Libraries in Croatia? A Thematic Content Analysis

This study examines Croatian LIS student theses, particularly those in school librarianship. These theses often discuss various educational interventions in school libraries. Using quantitative and qualitative methods, the research identifies prevalent themes, educational interventions, and the influence of non-LIS faculty departments on school librarianship. The findings show that most theses focus on school libraries during graduate studies, reflecting students' growing interest in the field. Since 2016, there has been a steady rise in the number of school library-related theses. Mentorship patterns indicate that mentors primarily come from theChair of Librarianship within the same department, and interdisciplinary collaborations are infrequent. Theses commonly emphasize presenting the work of school library institutions, but few detail specific educational interventions. Common methodologies include practice reviews and surveys, with prevalent themes focusing on information literacy, reading habits, and services for minorities. However, the study reveals limitations, with theses often lacking depth in reporting students' authentic experiences as teacher librarians. This underscores the need to improve reporting on educational interventions and encourage practical engagement. Enhancing the quality of reporting through narrative and reflective writing, qualitative research methods, and data analysis is recommended. In conclusion, the study provides valuable insights into Croatian student theses related to school librarianship. The findings can inform future thesis topics and mentorship decisions in the school librarianship field.

Remote sensing data for drought stress and croplands productivity assessment in Kherson region

Formulation of the problem. Remote sensing data might be used for indirect assessment of croplands conditions and drought stress through the calculation of specific vegetation indices, such as vegetation health index (VHI), agriculture stress index (ASI), and drought intensity or weighted mean vegetation health index (WMVHI). However, the accuracy of these indices is not clear for some territories. For example, the South of Ukraine is a zone of risky agriculture, because of low natural moisture supply and high evapotranspiration. Moisture supply is the main limiting factor for sustainable crop production in this region. The goals of this study were: 1) to assess the reliability of the mentioned vegetation indices in drought assessment through the direct comparison with the UNEP aridity index; 2) to find out whether remote sensing drought indicators could be used for the yield prediction of major crops on the regional scale. Methods. The study was conducted for Kherson region of Ukraine, as it is one of the most arid regions of the country with very high drought risks. The data on average weighted annual VHI, ASI, and WMVHI for the period 1984-2022 (Season 1) were collected and generalized from the FAO Earth Observation services. UNEP aridity index was calculated using the data from Kherson regional hydrometeorological center. Correlation and linear regression analysis were performed using common statistical methodology. Results. As a result, it was found that 1) all the studied remote sensing drought indicators demonstrate poor correlation with the aridity index, therefore, they should not be used to determine meteorological drought in the region; 2) all the studied remote sensing indices, especially VHI, demonstrate moderate-to-strong correlation with the yields of certain crops, cultivated in Kherson region (R=0.54-0.86), and could be used for the yield prediction; 3) the aridity index have poor relation to the yields of major crops, cultivated in the studied area; 4) VHI-based linear regression models for the crops’ yields prediction are reliable and reasonable for scientific and practical use just for cereal crops, and are much less accurate for grain corn and sunflower; 5) based on the study findings, it could be concluded that aridity index provides pure climatological characteristics of the region, while the studied vegetation indices are mainly focused on the level of drought stress that impacts crops during the growing season. Scientific novelty and practical significance. The article provides novel insights on the implementation of remote sensing data in drought risks assessment in crop production, and their utilization for the purpose of croplands productivity prediction. The study has theoretical and practical importance for current agriculture, and the findings could be used both in scientific, educational, and practical purposes.

Exploring Exploratory Data Analysis: An Empirical Test of Run Chart Utility

Abstract This paper explores Exploratory Data Analysis (EDA). Graphical methods are used to gain insights in EDA and these insights can be useful for forming tentative hypotheses when performing a root cause analysis (RCA). The topic of EDA is well addressed in the literature; however, empirical studies of the efficacy of EDA are lacking. We therefore aim to evaluate EDA by comparing one group of students identifying salient features in a table against a second group of students attempting to identify salient features in the same data presented in the form of a run chart, and then extracting relevant conclusions from such a comparison. Two groups of students were randomly selected to receive data; either in the form of a table or a run chart. They were then tasked with visually identifying any data points that stood out as interesting. The number of correctly identified values and the time to find the values were both evaluated by a two-sample t-test to determine if there was a statistically significant difference. The participants with a graph found the correct values that stood out in the data much quicker than those that used a table. Those using the data in the form of a table too much longer and failed to identify values that stood out. However, those with a graph also had far more false positives. Much has been written on the topic of EDA in the literature; however, an empirical evaluation of this common methodology is lacking. This paper confirms with empirical evidence the effectiveness of EDA.

Determination of road surface correction factors for CNOSSOS-EU in Ireland

Transport Infrastructure Ireland (TII) is a state agency in the Republic of Ireland. The primary function of TII is to provide an integrated approach to the future development and operation of the national roads network and light rail infrastructure throughout Ireland. TII are designated as the Noise Mapping Body (NMB) responsible for the development of strategic noise maps for all national roads carrying in excess of 3 million vehicles a year. Directive 2002/49/EC (commonly referred to as the Environment Noise Directive, 'the END') relates to the assessment and management of environmental noise. It is the main instrument of the European Union (EU) to quantify noise pollution levels, and trigger action within both Member States and at EU level. The END has the aim of establishing a common approach to the management of noise within the EU. Commission Directive (EU) 2015/996 established the common noise assessment methodology for Europe (CNOSSOS-EU). The CNOSSOS-EU road traffic noise emission model calculates rolling noise for different vehicle categories as a function of speed and frequency. The emission is initially calculated under reference conditions, then corrected for differing situations. For road surfaces which do not align with the reference surface, road surface correction factors should ideally be developed, otherwise a number of default values are provided within CNOSSOS-EU which are taken from the Dutch national noise assessment method, Rmg2012, and therefore contain only surfaces that are common in the Netherlands. For the implementation of CNOSSOS-EU in Ireland, a project was undertaken to develop road surface corrections for at least the three most common pavement types on the TII network with no direct match to the CNOSSOS-EU database. This paper will describe the measurements taken on Irish roads, the resulting road surface corrections, and our conclusions and recommendations for using the road surface corrections.

Rhizosheath: Roles, Formation Processes and Investigation Methods

Climate change negatively affects crop productivity, threatening the survival of entire populations from many vulnerable hotspot regions of the world with the risk of exacerbating hunger, malnutrition and international inequality. Selecting plant species manifesting abiotic stress-tolerant adaptive traits represents a challenge towards ensuring that crops are more resistant and resilient to environmental perturbations. The rhizosheath, defined as the complex of root hair, exudates and soil that strongly adheres to plant roots, is a promising root adaptive trait in facing conditions of water and nutrient deficits, as well as acidic soil. Several beneficial ecological functions are attributed to the rhizosheath, such as enhancing water and nutrient uptake; protecting from dehydration, heat and acid stresses; and stimulating microbial activities. It has been described in several Angiosperm species, including crops grown in severe habitats. The aim of this review was to collect the relevant literature produced to date regarding rhizosheaths, focusing on (i) the various processes involved in its formation, including both physicochemical and biological ones; (ii) the evolutionary and ecological role of rhizosheaths; and (iii) the most frequently used methodologies for its investigation and characterization. The present work provides a comprehensive overview of this revolutionary root’s great agronomic importance in order to address future research aiming to fill the existing knowledge gaps and define a common and shared methodology.

Big Data, Data Science, and Artificial Intelligence for Project Management in the Architecture, Engineering, and Construction Industry: A Systematic Review

The high volume of information produced by project management and its quality have become a challenge for organizations. Due to this, emerging technologies such as big data, data science and artificial intelligence (ETs) have become an alternative in the project life cycle. This article aims to present a systematic review of the literature on the use of these technologies in the architecture, engineering, and construction industry. A methodology of collection, purification, evaluation, bibliometric, and categorical analysis was used. A total of 224 articles were found, which, using the PRISMA method, finally generated 57 articles. The categorical analysis focused on determining the technologies used, the most common methodologies, the most-discussed project management areas, and the contributions to the AEC industry. The review found that there is international leadership by China, the United States, and the United Kingdom. The type of research most used is quantitative. The areas of knowledge where ETs are most used are Cost, Quality, Time, and Scope. Finally, among the most outstanding contributions are as follows: prediction in the development of projects, the identification of critical factors, the detailed identification of risks, the optimization of planning, the automation of tasks, and the increase in efficiency; all of these to facilitate management decision making.

Polytitanium sulfate rich with dominant-flocculated-species prepared by electrodialysis towards ceramic membrane fouling control

Ceramic membrane has always been of concern due to its high flux, fouling-resistance, and chemical-resistance. Membrane fouling is always an ever-lasting problem, and pre-coagulation is a high-recognized very effective and common methodology for membrane fouling control. Herein, a kind of high-efficient polytitanium sulfate (E-PTS) rich with dominant-flocculated-species was firstly developed by electrodialysis towards membrane fouling control. Electrodialysis well controlled the rate of polymerization among Ti-species and hydroxyl by regulating directed migration of electron through micro-interface. Both Ti-ferron and electrospray ionization time-of-flight mass spectrometry (ESI-TOF-MS) demonstrated the production of Tib and Tic as dominant-flocculated-Ti-species, accounting for 41.36 % and 42.18 %, respectively. The E-PTS had strong coagulation capability for the removal of biopolymer (BP), humic substance (HS), low molecular weight acid (LMWA), and low molecular weight neutral (LMWN) as proved by SEC-OCD-OND test. This was the very reason for the ca. 20 % higher removal efficiency of E-PTS coagulation over conventional polyaluminum chloride (PAC) and polyferric sulfate (PFS). Strong capability of coagulation with E-PTS enabled the follow-up filtration with ceramic membrane yielded large flux up to 361.0 LMH. More notable was that, continuous operation of membrane filtration for 30 h saw a stable high flux with no membrane fouling. The E-PTS pre-coagulation coupled with ceramic membrane filtration, a compact flow route, could realize both high-efficient water purification and membrane fouling control.

Subgenome phasing for complex allopolyploidy: case-based benchmarking and recommendations.

Accurate subgenome phasing is crucial for understanding the origin, evolution and adaptive potential of polyploid genomes. SubPhaser and WGDI software are two common methodologies for subgenome phasing in allopolyploids, particularly in scenarios lacking known diploid progenitors. Triggered by a recent debate over the subgenomic origins of the cultivated octoploid strawberry, we examined four well-documented complex allopolyploidy cases as benchmarks, to evaluate and compare the accuracy of the two software. Our analysis demonstrates that the subgenomic structure phased by both software is in line with prior research, effectively tracing complex allopolyploid evolutionary trajectories despite the limitations of each software. Furthermore, using these validated methodologies, we revisited the controversial issue regarding the progenitors of the octoploid strawberry. The results of both methodologies reaffirm Fragaria vesca and Fragaria iinumae as progenitors of the octoploid strawberry. Finally, we propose recommendations for enhancing the accuracy of subgenome phasing in future studies, recognizing the potential of integrated tools for advanced complex allopolyploidy research and offering a new roadmap for robust subgenome-based phylogenetic analysis.