Different Types Of Instruments Research Articles

From Labquakes to Megathrusts: Scaling Deep Learning Based Pickers Over 15 Orders of Magnitude

AbstractThe application of machine learning techniques in seismology has greatly advanced seismological analysis, especially for earthquake detection and seismic phase picking. However, machine learning approaches still face challenges in generalizing to data sets that differ from their original training setting. Previous studies focused on retraining or transfer‐learning models for these scenarios, but require high‐quality labeled data sets. This paper demonstrates a new approach for augmenting already trained models without the need for additional training data. We propose four strategies—rescaling, model aggregation, shifting, and filtering—to enhance the performance of pre‐trained models on out‐of‐distribution data sets. We further devise various methodologies to ensemble the individual predictions from these strategies to obtain a final unified prediction result featuring prediction robustness and detection sensitivity. We develop an open‐source Python module quakephase that implements these methods and can flexibly process input continuous seismic data of any sampling rate. With quakephase and pre‐trained ML models from SeisBench, we perform systematic benchmark tests on data recorded by different types of instruments, ranging from acoustic emission sensors to distributed acoustic sensing, and collected at different scales, spanning from laboratory acoustic emission events to major tectonic earthquakes. Our tests highlight that rescaling is essential for dealing with small‐magnitude seismic events recorded at high sampling rates as well as larger magnitude events having long coda and remote events with long wave trains. Our results demonstrate that the proposed methods are effective in augmenting pre‐trained models for out‐of‐distribution data sets, especially in scenarios with limited labeled data for transfer learning.

Several outstanding issues concerning the ionosphere of Mars

Several outstanding issues concerning the ionosphere of Mars can be addressed with the support of radio occultation observations acquired near the solar zenith angle limit of 45∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document}. First, two fundamentally different types of instruments (topside radar sounding, radio occultations) have been used to characterize how the subsolar peak density changes over the solar cycle. Here we find that their results for solar minimum and solar maximum values of peak density are consistent. This verifies that systematic errors do not affect peak density measurements from either type of instrument. Second, reported descriptions of how the peak altitude changes with solar zenith angle are inconsistent. Specifically, values reported by radio occultation and radar sounder instruments for the characteristic lengthscale used to describe changes in peak altitude with solar zenith angle vary by a factor of two. We find that the change in peak altitude with solar zenith angle is governed by a lengthscale that is close to the thermospheric scale height, as predicted theoretically. However, this behavior is only apparent when the Mars–Sun distance is held fixed. Reported smaller values of this lengthscale, which are not consistent with theoretical expectations, were adversely affected by using near-terminator peak altitude values only, which display marked variability. Third, Viking Lander entry science data have been interpreted to suggest that the M1 layer is not present in the ionosphere at solar zenith angles of 45∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document} or smaller. We show radio occultation observations at 45∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^{\\circ }$$\\end{document} in which the M1 layer is present. This suggests that the basic structure of the dayside ionosphere remains the same at all solar zenith angles.Graphical

ATOMIX benchmark datasets for dissipation rate measurements using shear probes

Turbulent mixing in the ocean, lakes and reservoirs facilitates the transport of momentum, heat, nutrients, and other passive tracers. Turbulent fluxes are proportional to the rate of turbulent kinetic energy dissipation per unit mass, ε. A common method for ε measurements is using microstructure profilers with shear probes. Such measurements are now widespread, and a non-expert practitioner will benefit from best practice guidelines and benchmark datasets. As a part of the Scientific Committee on Oceanographic Research (SCOR) working group on “Analysing ocean turbulence observations to quantify mixing” (ATOMIX), we compiled a collection of five benchmark data of ε from measurements of turbulence shear using shear probes. The datasets are processed using the ATOMIX recommendations for best practices documented separately. Here, we describe and validate the datasets. The benchmark collection is from different types of instruments and covers a wide range of environmental conditions. These datasets serve to guide the users to test their ε estimation methods and quality-assurance metrics, and to standardize their data for archiving.

A general-purpose pointer meter reading detection method based on adaptive feature fusion and data augmentation

Pointer meters continue to serve as the primary monitoring instruments within substations. To solve the issue of poor model accuracy and low reading accuracy when reading multiple types of pointer meters, this paper proposes a universal cascaded convolutional neural network for accurate reading of various types of pointer instruments. The proposed detection method consists of two stages: instrument digital positioning and instrument pointer fitting. In the digital(figure of a number) positioning stage, an instrument data augmentation method for “large background and small target” is proposed to improve the model's sensitivity to digital position and reduce the interference of redundant background information to the model. In addition, an adaptive feature fusion pyramid structure is proposed for more effective feature fusion and enhanced fuzzy small target recognition. Compared with the baseline model, the method introduced in this study realizes a 0.47 % improvement in target detection accuracy. In our proposed dataset, the average recognition accuracy for the digital position location phase is 98.65 %,the average reading errors in square instruments, circular instruments, and instruments with uneven scales are 0.76 %, 0.73 %, and 0.67 % respectively. The proposed universal detection method in this paper achieves ultra-high precision and can be applied to reading pointer instruments of different types and scales. Compared with existing pointer meter reading methods, the proposed detection method showcases superior simplicity and effectiveness. Furthermore, it showcases a reduced measurement error, thereby bolstering its practical utility in industrial contexts.

Surgical limits, pitfalls, and potential solutions in kyphectomy in myelomeningocele: three cases and systematic review of the literature.

To describe surgical treatment of 3 cases of severe and progressive thoracolumbar kyphosis in myelomeningocele and provide a systematic review of the available literature on the topic. Medical records and pre- and post-operative imaging of 3 patients with thoracolumbar kyphosis and myelomeningocele were reviewed. A database search was performed for all manuscripts published on kyphectomy and/or surgical treatment of kyphosis in myelomeningocele. Patients' information, preoperative kyphosis angle, type of surgery, levels of surgery degrees of correction after surgery and at follow-up, and complications were reviewed for the included studies. Three cases underwent posterior vertebral column resection (pVCR) of 2-4 segments at the apex of the kyphosis (kyphectomy). Long instrumentation was performed with all pedicle screws constructed from the thoracic spine to the pelvis using iliac screws. According to literature review, a total of 586 children were treated for vertebral kyphosis related to myelomeningocele. At least one vertebra was excised to gain some degree of correction of the deformity. Different types of instrumentation were used over time and none of them demonstrated to be superior over the other. Surgical treatment of progressive kyphosis in myelomeningocele has evolved over the years incorporating all major advances in spinal instrumentation techniques. Certainly, the best results in terms of preservation of correction after surgery and less revision rates were obtained with long construct and screws. However, complication rate remains high with skin problems being the most common complication. The use of low-profile instrumentation remains critical for treatment of these patients.

Development of electrochemical sensors for quick detection of environmental (soil and water) NPK ions.

All over the world, technology is becoming more and more prevalent in agriculture. Different types of instruments are already being used in this sector. For the time being, every farmer is trying to produce more crops on a piece of land. Eventually, soil loses its nutrients; however, to grow more crops, farmers use more fertilizers without knowing the proper conditions of the soil in real time. To overcome this issue, many scientists have recently focused on developing electrochemical sensors to detect macronutrients, i.e., nitrogen (N), phosphorus (P), and potassium (K), in soil or water rapidly. In this review, we focus mainly on the recent developments in electrochemical sensors used for the detection of nutrients (NPK) in different types of samples. As it is outlined, the use of smart and portable electrochemical sensors can be helpful for the reduction of excess fertilizer and can play a vital role in maintaining suitable conditions in soils and water. We are optimistic that this review can guide researchers in the development of a portable and suitable NPK detection system for soil nutrients.

Impact of personal, psychological, and social factors on English language learning: A non-native student case study

Purpose: This case study aimed to explore the impact of personal, psychological, and social factors on a non-native English language student and to determine whether the students’ errors in speaking and writing were developmental or transferred. Methodology/approach: The case study was conducted on a single participant (an English language student) at Paktia University, Afghanistan. The data were collected using four different types of instruments. The data were analyzed considering the influence of personal, psychological, and social factors on the participants’ language learning. Results/Findings: The participant faced a great number of problems caused by personal, psychological, and social factors, including lack of social motivation, lack of social practice, economic limitations, and grammatical errors in productive skills usually transferred from the native language or caused by lack of practice. However, as an extraverted and motivated learner, he overcame most of the problems during learning. He improved his speaking skills and pronunciation through self-interactions and online communication. Limitations: This was a single-participant case study; therefore, further studies are needed to generalize the findings to Afghan English language students. Contribution: This study can help policymakers, curriculum designers, educational institution authorities, and English language educators to better identify the factors that affect English language learning. Novelty: This is the only study conducted to examine the process of an individual’s English language learning process in Afghanistan.

Management of oral mucositis: a systematic review.

Oral mucositis is one of the most common complications following chemotherapy and/or head and neck radiotherapy. Various treatments for oral mucositis have been proposed. However, there has still been no review of the most frequent and most effective type of therapy to treat oral mucositis. This systematic review aims to determine the most frequent and effective types of therapy to treat and reduce the severity of oral mucositis. The literature search was carried out using PRISMA guidelines. Publications included from 2010 to June 2021 with a clinical trial, prospective, and retrospective observational research design. The following databases were used: PubMed, Cochrane Library, and Wiley Online Library. The search was for limited articles published in English, which were screened and analyzed by three authors. The risk of bias of each study was also assessed by three authors simultaneously, using different types of instruments depending on its study design. Forty-seven of 1274 journals were included. From 3577 subjects, oral mucositis was more common in males than females (2.12: 1), with a mean age of 56.39 (18-90 years). The most commonly used types of therapy are low-level laser therapy (396 subjects) and lysozyme-based compounds (314 subjects). Meanwhile, the most effective type of therapy is low-level laser therapy. Low-level laser therapy is the most commonly used oral mucositis therapy and is also the most effective in reducing the degree of oral mucositis and associated pain.

The Role of Cholangioscopy in Biliary Diseases.

Endoscopy plays a central role in diagnostic and therapeutic approaches to biliary disease in both benign and malignant conditions. A cholangioscope is an endoscopic instrument that allows for the direct exploration of the biliary tree. Over the years, technology has improved endoscopic image quality and allowed for the development of an operative procedure that can be performed during cholangioscopy. Different types of instruments are available in this context, and they can be used in different anatomical access points according to the most appropriate clinical indication. The direct visualization of biliary mucosa is essential in the presence of biliary strictures of unknown significance, allowing for the appropriate allocation of patients to surgery or conservative treatments. Cholangioscopy has demonstrated excellent performance in discriminating malignant conditions (such as colangiocarcinoma) from benign inflammatory strictures, and more recent advances (e.g., artificial intelligence and confocal laser endomicroscopy) could further increase its diagnostic accuracy. Cholangioscopy also plays a primary role in the treatment of benign conditions such as difficult bile stones (DBSs). In this case, it may not be possible to achieve complete biliary drainage using standard ERCP. Therapeutic cholangioscopy-guided lithotripsy allows for stone fragmentation and complete biliary drainage. Indeed, other complex clinical situations, such as patients with intra-hepatic lithiasis and patients with an altered anatomy, could benefit from the therapeutic role of cholangioscopy. The aim of the present review is to explore the most recent diagnostic and therapeutic advances in the roles of cholangioscopy in the management of biliary diseases.

Augmentation Embedded Deep Convolutional Neural Network for Predominant Instrument Recognition

Instrument recognition is a critical task in the field of music information retrieval and deep neural networks have become the dominant models for this task due to their effectiveness. Recently, incorporating data augmentation methods into deep neural networks has been a popular approach to improve instrument recognition performance. However, existing data augmentation processes are always based on simple instrument spectrogram representation and are typically independent of the predominant instrument recognition process. This may result in a lack of coverage for certain required instrument types, leading to inconsistencies between the augmented data and the specific requirements of the recognition model. To build more expressive instrument representation and address this inconsistency, this paper constructs a combined two-channel representation for further capturing the unique rhythm patterns of different types of instruments and proposes a new predominant instrument recognition strategy called Augmentation Embedded Deep Convolutional neural Network (AEDCN). AEDCN adds two fully connected layers into the backbone neural network and integrates data augmentation directly into the recognition process by introducing a proposed Adversarial Embedded Conditional Variational AutoEncoder (ACEVAE) between the added fully connected layers of the backbone network. This embedded module aims to generate augmented data based on designated labels, thereby ensuring its compatibility with the predominant instrument recognition model. The effectiveness of the combined representation and AEDCN is validated through comparative experiments with other commonly used deep neural networks and data augmentation-based predominant instrument recognition methods using a polyphonic music recognition dataset. The results demonstrate the superior performance of AEDCN in predominant instrument recognition tasks.

Indonesian EFL’s Learning Strategies and Personality Types in Achieving TOEFL Score Above 500

There are many English proficiency exams available, including the TOEIC, TOEFL, and IELTS. TOEFL is one of the most well-known English proficiency tests in Indonesia, which is taken for both academic and professional requirements. The average TOEFL score for Indonesian students is still below the global norm of 500. Based on the problems and the difficulties faces by most of Indonesia learners, this study tries to analyze the learning strategies used by learners who successfully achieve TOEFL scores above 500. This study also delves into the learner's personality types in order to understand the characteristics of each type that affected their learning strategy. The 15 participants are randomly selected from Indonesian EFL students between the ages of 20 to 25. The participants must have taken the TOEFL test and received the score above 500. Both quantitative and qualitative writing are used in this study. The quantitative method used in analysing the data collection, the researchers employed descriptive statistic data analysis in Excel to find out the mean. Two different types of instruments were used to collect the data: Oxford's Strategy Inventory for Language Learning and the Myers-Briggs Type Indicator. The result of this study shows; metacognitive strategy as the dominant strategy utilised by the majority of learners and there are 8 personality types such as; ISTJ, INFJ, ISFP, INFP, ENFP, ESTJ, ESFJ, and ENFJ.

Willingness to pay for what? Testing the impact of four factors on willingness to pay for facilitating and sanctioning energy policy instruments

The purpose of this study is to analyze individuals’ willingness to pay (WTP) for energy policies. The type of energy policy was divided into facilitating and sanctioning instruments. We studied the factors that influence WTP for two types of intrument for energy policy by using four theoretical frameworks: the Economic Model, the Theory of Planned Behavior, Value Theory, and Psychometric Paradigm (so called risk perception model). The results, first, showed that the WTP for the sanctioning instruments was lower than that for the facilitating instruments. Second, the values, trust, and norms were significant predictors of the WTP for both types of policy instruments. Third, the economic factors only influenced the WTP for sanctioning instruments. This study recommends policy mix considering the WTP for different types of instruments for energy policy.

Scenario analysis and climate change: a literature review via text analytics

PurposeClimate change has a direct impact on companies. Therefore, the scenario analysis is used to provide companies and stakeholders in this specific sector with forward-looking measures and narratives of the world's future state. This work aims to provide an independent, wide and rigorous literature review on the topics of scenario analysis and climate change, analyzing a large set of referred papers included in economic journals on the Web of Science Clarivate Analytics data source. This review, by means of a mixed approach, can help address new policy strategies and business models.Design/methodology/approachThe work employs 416 abstracts and relative titles in the field of economics, employing data mining for qualitative variables and performing descriptive statistics and lexicometric measures, similarity analysis and clustering with Reinert's hierarchical method in order to extract knowledge. Furthermore, qualitative content analysis allows for the return of a comprehensive and complete universe of meaning, as well as the analysis of co-occurences.FindingsContent analysis reveals three main classification clusters and four unknown patterns: model area, risks, emissions and energy and carbon pricing, indicating research directions and limitations through an overview with an extensive reference bibliography. In the research, the prevalent use of quantitative instruments and their limitations emerge, while qualitative instruments are residual for climate change assessment; they also highlight the centrality of transition risk over adaptation measures and the combination of different types of instruments with reference to carbon pricing.Originality/valueScenario analysis is a relatively new topic in economics and finance research, and it is under-investigated by the academy. The analysis combines quantitative and qualitative research using text analytics.

Analysis of the behaviour of retaining structures through a novel data interpretation approach

Retaining structures are generally designed to satisfy serviceability limits on allowed deflections while also providing sufficient strength to carry the bending moment caused by the soil pressure acting on the wall in tandem with any applied loads. Since wall displacement and mobilised soil pressure are the most important design parameters, direct measurement would be ideal, however instrumentation limitations leave the measurement of wall curvature using strain gauges and rotation using inclinometers as the industry standard for retaining wall monitoring. Pressure and deflection are normally inferred from these discrete, sparse and potentially inaccurate measurements through beam theory by fitting the discrete data to obtain differentiable continuous curves. Conventional fitting methods cannot simultaneously fit data from different types of instrumentation like inclinometers and strain gauges and there is generally little flexibility in addressing issues when the fits do not make geotechnical sense. A novel fitting approach is developed to address these shortcomings, with the ability to pull together imperfect data from a multitude of instruments (strain gauges, inclinometers, displacement transducers etc.) into a cohesive prediction. The method is validated based on field and centrifuge data in which it outperforms existing fitting solutions. This novel approach significantly simplifies data analysis by enabling practising engineers and researchers to simply input all instrument data from a retaining structure and retrieve sensible and accurate predictions of the parameters of soil-structure interaction which are compatible with all data measured and insensitive to measurement errors to a high degree.

Subgingival instrumentation.

The S3-level clinical guidelines for the treatment of patients with periodontitis stages I-III published by the European Federation of Periodontology in 2020, suggest a pre-established stepwise approach for oral-healthcare professionals with precise therapeutic pathways. The second step of this approach consists of the subgingival instrumentation of periodontal pockets by non-surgical means to disrupt the microbial biofilm and remove soft and mineralized deposits This step aims to resolve periodontal inflammation by closure of periodontal pockets (probing pocket depth ≤ 4 mm, absence of bleeding on probing) employing different types of instruments and treatment protocols toward this end. Novel non-surgical treatment approaches that adopt micro instruments or subgingival application of biological agents have been recently tested. Subgingival instrumentation has been shown to effectively restore the subgingival microbiota to one associated with periodontal health and to modulate the inflammatory response. The outcomes of the subgingival instrumentation have to be evaluated in order to guide the therapist in providing additional but focused treatment in the remaining pockets OR at sites with residual inflammation. Of great importance is the impact that non-surgical periodontal treatment has on the patient's well-being, based on evidence that emerges from studies evaluating patient related outcomes and quality of life.

Reaction calorimetry: Main types, simple theory, and application for kinetic study—A review

AbstractReaction calorimetry is a powerful experimental method widely used for reaction hazard assessment in chemical engineering for chemical process design and in other fields. Currently, several types of reaction calorimeters are available, each with its own features. Many articles and several monographs have been published dealing with various aspects of reaction calorimetry, but it is difficult to find an overview of different types of instruments and the theoretical basis of reaction calorimetry in one review in a compact form. The purpose of this article is to fill this gap as much as possible and to help in understanding the principles of this useful experimental method and in choosing the type of instrument most suitable for the purposes of a particular study. The review concludes with some recommendations for the proper organization of an experiment in reaction calorimetry, with an emphasis on the kinetic study. The usefulness of kinetics based on reaction calorimetry data is illustrated by an example of using kinetics to design an industrial process.

The Financial Data Services Domain: From Taxonomies to Ontologies

There are many different types of instruments and hundreds of different markets for investment, leading to an extremely large and hard-to-define universe of financial data. The related commercial offer is extremely heterogeneous and complex. In this scenario, it is difficult to source the most appropriate financial services providers. In the past, eProcurement mainly focused on using ERP management tools to record and examine previous buying decisions and expenditure data. In recent years, machine learning and artificial intelligence have been applied to procurement workflows, introducing computation of external or third￾party unstructured data to achieve a higher level of market knowledge and decision automation. To exploit the possibilities provided by these new technologies to the full extent possible, theoretical models for understanding large amounts of unstructured data are essential. In this research-in-progress paper, we propose a taxonomy of financial data services and depict the related prototype ontological model, providing a possible conceptualization and specification of the domain of interest potentially useful for the development of applications based on semantic technologies.

Standardization of Transfer across Labs between Flow Cytometers for Detection of Lymphocytes in Japanese Encephalitis Vaccinated Children.

An increasing number of laboratories need to collect data from multiple flow cytometers, especially for research projects performed across multiple centers. The challenges of using two flow cytometers in different labs include the lack of standardized materials, software compatibility issues, inconsistencies in instrument setup, and the use of different configurations for different flow cytometers. To establish a standardized flow cytometry experiment to achieve the consistency and comparability of experimental results across multiple centers, a rapid and feasible standardization method was established to transfer parameters across different flow cytometers. The methods developed in this study allowed the transfer of experimental settings and analysis templates between two flow cytometers in different laboratories for the detection of lymphocytes in Japanese encephalitis (JE)-vaccinated children. A consistent fluorescence intensity was obtained between the two cytometers using fluorescence standard beads to establish the cytometer settings. Comparable results were obtained in two laboratories with different types of instruments. Using this method, we can standardize analysis for evaluating the immune function of JE-vaccinated children in different laboratories with different instruments, diminish the differences in data and results among flow cytometers in multiple centers, and provide a feasible approach for the mutual accreditation of laboratory results. The standardization method of flow cytometer experiments will ensure the effective performance of research projects across multiple centers.

SG-APSIC1045: A quantitative assessment of ATP bioluminescence on dental instruments reprocessed by automated washer-disinfector and ultrasonic machine

Objectives: Dental instruments are contaminated by blood and saliva during dental procedures. To prevent cross infection, all contaminants should be removed from the surfaces of instruments. Inadequate cleaning can hinder disinfection and sterilization process. To compare the cleaning efficacy of an automated washer–disinfector versus an ultrasonic machine on dental instruments, adenosine triphosphate (ATP) measurements were compared. Methods: From National University Polyclinic Bukit Panjang Dental Services, we collected 2 loads of 40 dental instruments previously used in dental treatments: extraction forceps, high-volume suction tips, Coupland elevators, matrix band holders, and ultrasonic scaler tips. At the point of use, gross soil was wiped from instrument surfaces with water. Each instrument was swabbed after cleaning either using a washer–disinfector or an ultrasonic machine. The relative light units (RLU) on the luminometer indicated the amount of ATP contaminants and residue bioburden present on the instruments. Results: The mean RLU values across all instruments in the washer–disinfector group was 2.5 times lower than the mean value of the instruments in the ultrasonic group (35.4 vs 89.9 RLU). This difference was statistically significant for all instrument groups except for the high-volume suction tips. The Mann-Whitney U test indicated that the RLU in the ultrasonic group was higher than the RLU for the washer–disinfector group for extraction forceps (P < .001), ultrasonic scaler tips (P < .023), and matrix bands (P < .006). A t test indicated the same relationship for Coupland elevators (P < .005). Conclusions: The mean RLU values for both cleaning methods were lower than the manufacturer’s benchmark (RLU ≤ 150), suggesting that both methods can achieve effective cleaning. However, cleaning using an automated washer–disinfector is significantly more effective than an ultrasonic machine for nonlumen instruments. The effectiveness of cleaning using ultrasonic machine varied greatly among different types of instruments with different design complexities.

Instrumental variables estimation: Assumptions, pitfalls, and guidelines

Researchers striving to ensure rigor in their scientific findings face a common pitfall: Endogeneity. To tackle this problem, scholars have increasingly adopted instrumental variables estimation (IVE). Although there are many published works showing how IVE should be used, many applied researchers still have trouble understanding how to use the method correctly. In this article, we provide a methodological overview of IVE by discussing the underlying conditions valid instruments must satisfy as well as common mistakes made in using IVE. Using simulated data, we further demonstrate the sensitivity of IVE to violations of its conditions. We then take stock of the literature in a social science discipline (i.e., leadership research) and provide insights regarding trends and shortcomings in the application of IVE. Based on our review, we categorize the different types of instruments used and discuss the potential appropriateness of each type. We conclude by providing non–technical guidelines targeted at the study design, analysis, and reporting phases, which will help applied social science researchers to ensure they use IVE correctly.