Alternative Assessment Approaches Research Articles

Optimization and alternative image processing approach for the comprehensive assessment of delamination and uncut fiber in drilling fiber metal laminate

Optimization and alternative image processing approach for the comprehensive assessment of delamination and uncut fiber in drilling fiber metal laminate

An Alternative Probabilistic Approach for Reliability Assessment of Rotorcraft Structures

An alternative probabilistic approach is proposed to assess the reliability of rotorcraft structures. According to the approach, safe boundaries of reliability predictions (i. e., conservative ones with additional safety margins) are calculated instead of exact values of the reliability as usually estimated in conventional analysis. Due to additional safety margins, these boundaries are suggested for practical engineering applications. The proposed approach is based on two main ideas, namely (a) prediction of a relatively small population of independent coarse estimations of reliability and (b) application of sampling methods to predict reliability for each individual coarse estimation. Robustness and convenience of the developed approach and its computational implementation are demonstrated for four scenarios considering two problems (simplified analytical and realistic finite element analysis–based ones) under two sets of input data providing the probability of failure (POF) close to 1e-6 and 1e-9, respectively. High accuracy of predictions according to the developed approach is independently verified by comparison with known "exact" references: closed-form solutions for the analytical problem and by direct Monte Carlo simulation for the numerical one. The proposed approach can be recommended as an efficient practical solution for a broad range of reliability assessments of rotorcraft structures requiring both (i) low POF (e. g., below 1e– 6) and (ii) relatively complex time-consuming structural definitions (e. g., compute times in hours for each quasi-deterministic simulation).

Preliminary Evaluation of a Novel Neural Network-Based Hybrid Simulator for Surgical Training and Performance Assessment of Neonatal Thoracentesis.

Tension pneumothorax is a rare and life-threatening situation in neonates requiring immediate intervention through thoracentesis. Significant complications can arise while performing thoracentesis in the case of inadequate skill level or exposure to the condition. Although simulation-based training (SBT) has proven to be effective in learning surgical skills, training sessions are long, subjective, and expensive, because of which they cannot be held regularly. This article attempts to improve traditional SBT for neonatal thoracentesis through an autonomous simulator that can provide real-time objective feedback during surgical training and assessment. The simulator incorporates a custom manikin and virtual reality software interfaced through electromagnetic sensors that track the motion of surgical instruments. The software application reads and stores instrument motion information to replicate physical actions in the virtual environment, play back previously stored surgical performances and analyze data through a pretrained neural network. The simulator encapsulates the experience of SBT by allowing trainees to watch and replicate an ideal method of conducting the procedure, providing simplified, real-time autonomous guidance during practice and an objective taskwise assessment of the performance during testing. The preliminary trial held at the University of Illinois Hospital in the presence of 1 neonatologist and 4 fellows revealed that all the participants used the autonomous guidance more than once, and all found simulation experience to be accurate and overall effective in learning thoracentesis. Although the sample size is small, the simulator shows potential in being a viable alternative approach for training and assessment for thoracentesis.

Development and Validation of a Method for the Simultaneous Quantification of 21 Microbial Volatile Organic Compounds in Ambient and Exhaled Air by Thermal Desorption and Gas Chromatography–Mass Spectrometry

Microbial volatile organic compounds (mVOCs) are metabolites developed by indoor molds responsible for several health effects. Their detection may be an alternative approach for fungal exposure assessment, given that the classical methods have limitations. The goal of this study was to develop and validate an analytical method to quantify 21 mVOCs in ambient and exhaled air using active sampling on sorbent tubes followed by thermal desorption and gas chromatography–mass spectrometry analysis. Tenax/Carbograph sorbent was selected for its extraction/desorption efficiency. Reliable linearity was obtained over the concentration range of mVOCs with low limits of detection (≥1.76 ng/m3) and quantification (≥5.32 ng/m3). Furthermore, accuracy and precision in the percentage recoveries ranged between 80–118% with coefficients of variations lower than 4.35% for all mVOCs. Feasibility tests with ambient air of different places (toxicology laboratory, office, and mold contaminated bedroom) showed that variations between settings were observable and that the highest mVOCs concentrations in the bedroom. Consequently, concentrations of 17 mVOCs were higher in the volunteer’s exhalate after exposure in the bedroom than in the laboratory. In conclusion, this method allows the detection of mVOCs in a new matrix, i.e., exhaled air and targeting the contaminated environment and, therefore, intervening for the protection of human health.

A Study of Point Laser for Automatic Local Road Condition Assessment: Feasibility, Challenges, and Limitations

Road condition assessment plays an important role in maintaining the integrity of mature and fast-expanding road networks. Such assessments provide invaluable information for local authorities that enable them to deliver timely preventative road network maintenance. To enable the best use of scarce maintenance resources, it is necessary to assess the condition of the roads periodically. In this article, we present the Point Laser (PL) system as an alternative approach for automatic road assessment. Compared to current systems, ground penetrating radar and the mobile laser scanning system, the PL system has the advantages of low hardware cost, low computational requirements, and fewer environmental restrictions in relation to its use. The article first outlines the principle of the PL system including a low-complexity signal processing approach. Afterward, the feasibility, challenges, and limitations of the PL system are discussed based on its use in a real environment. A visual-based road survey is used as a ground truth to determine the PL’s performance in relation to the requirements of road condition assessment at various levels of road management. The results of the comparison demonstrate that the PL system is an ideal candidate for the automatic assessment of the condition of local road networks, especially those that require frequent assessment for road asset management.

Identification of Fibre Content in Edible Flours Using Microwave Dielectric Cell: Concise Review and Experimental Insights.

The quality of edible intake decides the health of the human body and is also responsible for building a healthy immune system in the body. A healthy immune system can protect the body even from invisible attacks of viral or bacterial infections. The assessment of the quality of edible items is not well defined and standardized in many developing countries due to quality assessment difficulties in practice. An alternative well-defined quality assessment approach for edible flours is presented in this paper. Every edible substance has dielectric properties, and it varies from material to material in nature. Edible flours and liquid have different microwave absorption capabilities, based on their natural molecular structure. Based on the microwave energy absorption characteristics of materials, the attenuation constant of edible flours is derived by the waveguide method in this work. In this approach, microwave energy absorption of the edible samples of different types of wheat, rice and millets are observed, and the attenuation constant factors of the samples are then calculated from the tabulated values. The work focuses on the identification of fibre content present in the edible flours. Inferences are made based on the attenuation and its variations with the number of samples, dielectric loss and dielectric constant of the samples. A systematic and concise review of the topic is also included for the benefit of future researchers.

Predicting Actual Social Skill Expression from Personality and Skill Self-Concepts.

Social skills are of key importance in everyday and work life. However, the way in which they are typically assessed via self-report questionnaires has one potential downside; self-reports assess individuals’ global self-concepts, which do not necessarily reflect individuals’ actual social behaviors. In this research, we aimed to investigate how self-concepts assessed via questionnaires relate to skill expression assessed via behavioral observations after short interpersonal simulations. For this, we used an alternative behavior-based skill assessment approach designed to capture expressions of predefined social skills. Self- and observer ratings were collected to assess three different social skills: agency (i.e., getting ahead in social situations), communion (i.e., getting along in social situations), and interpersonal resilience (i.e., staying calm in social situations). We explored how these skills were related to self-concepts by differentiating between a classic personality measure (i.e., Big Five Inventory 2; BFI-2) and a novel skill questionnaire (i.e., Behavioral, Emotional, and Social Skills Inventory; BESSI). The results (N = 137) showed that both personality and skill self-concepts predicted self-rated skill expression, with the BESSI showing incremental validity. For both personality and skills self-concepts, the relationships with observer-rated skill expression were significant for agency but not for communion or interpersonal resilience. We discuss these results and highlight the theoretical and practical importance of differentiating between skill self-concepts and actual skill expression.

A novel criterion for global incremental stability of dynamical systems

In this paper, we establish the sufficient conditions guaranteeing global uniform exponential stability, or at least global asymptotic stability, of all solutions for nonlinear dynamical systems, also known as global incremental stability (GIS) of the systems. We provide here an alternative approach for assessment of GIS in terms of logarithmic norm under which the stability becomes a topological notion and also generalize both horizontally and vertically the well-known Demidovich criterion for GIS of dynamical systems. Convergence of all solutions to the origin x=0, which is not assumed to be an equilibrium state of system, is also analyzed. Theory is illustrated by a simulation experiment.

An alternative assessment approach to national higher education system evaluation

While the assessment of higher education systems is informative to both policy makers and individuals, it is subjective and performed according to experts’ judgment. The present study proposes a relatively objective approach, hierarchical data envelopment analysis (H-DEA), to rank higher education systems. Unlike the subjective approach, H-DEA utilizes endogenous weight determination, allowing assessors to identify the relative importance of each attribute and subattribute. Utilizing the U21 Ranking of National Higher Education System 2020 data, our analysis indicates that the output attribute is a crucial factor influencing the overall performance of higher education systems, even considering countries’ stage of development and culture. The computed weights of the H-DEA framework show various attributes’ different contributions by group. Resources allocated to the higher education system are important for developing countries, while a high degree of internationalization and a strong link between academia and industry matter for advanced countries. Surprisingly, Asian and Western cultures experience similar performance in their higher education systems, reflecting the Asian higher education system’s development toward the Western style. The performance of countries with non-Asian–non-Western cultures, as expected, lags behind, and putting more resources into these countries’ higher education system is a way to enhance the overall performance.

Psychometric Evidence for Indirect Assessment of Child Abuse Risk in Child Welfare-Involved Mothers.

Most research on factors related to physical child abuse risk rely heavily on direct self-report measures, which is a methodological strategy susceptible to participant response distortions. Such methodological reliance obfuscates the interpretations rendered about the risk factors predictive of child abuse. Efforts to develop alternative indirect assessment approaches, such as analog tasks, show promise, although most of those studies have applied these methods to community samples rather than with child welfare-involved samples. The present study evaluated the psychometric evidence for four separate analog tasks that have not yet been considered with mothers identified for child maltreatment by child welfare services, also contrasted to a sociodemographically matched sample of mothers. The results indicate acceptable reliability for the analog tasks, with additional evidence of validity. However, the two groups of mothers did not substantively differ across measures, suggesting that identification for abuse through child protective services does not differentiate from those closely matched on critical sociodemographic characteristics. The promising preliminary results of these analog tasks in the current study suggest that indirect analog assessment approaches to estimate child abuse risk could be useful in efforts to minimize dependence on self-report methods.

A novel tyramine sensing-based polymeric L-histidine film-coated screen-printed graphene electrode: Capability for practical applications

A novel electrochemical sensor for the determination of tyramine (Tyr) based on a polymeric film of L-histidine coated on a screen-printed graphene electrode (poly(His)/SPGE) is presented for the first time. This developed sensor was constructed through a single modification step via an electropolymerization process. The poly(His) feature exhibited an outstanding electrocatalytic activity in the electrooxidation of Tyr. Under optimal conditions, the Tyr sensor revealed relatively broad two linear ranges of 0.5–20 μM and 50–300 μM with a limit of detection and limit of quantification of 0.065 μM (3SD/slope) and 0.22 μM (10SD/slope), respectively. Furthermore, the reliability of this proposed sensor was successfully investigated by detecting Tyr in both biological fluids and cheese samples, with satisfactory recovery ranges (82.58%–109.75%) and relative standard deviations (0.28%–8.03%). Therefore, the proposed sensor has distinct advantages, such as low cost, easy operation, disposable, high sensitivity, and good selectivity.On the merits of the aforementioned benefits, the newly developed electrochemical sensor could be a promising alternative approach for Tyr assessment in food quality and safety control, as well as a better understanding of clinical function associated with migraine triggers.

Assessment and rehabilitation of acquired communication disorders in Aboriginal and Torres Strait Islander adults with stroke or traumatic brain injury: a retrospective chart review

Purpose Speech-language pathologists’ (SLP) management practices for Aboriginal and Torres Strait Islander adults with acquired communication disorder (ACD), following stroke or traumatic brain injury (TBI), are not well understood. This study explores SLPs’ management approaches for ACDs for Aboriginal and Torres Strait Islander adults post-stroke or TBI. Materials and methods SLPs’ documented notes were analysed from a two-year retrospective medical record review of Aboriginal and Torres Strait Islander adults (≥18 years), admitted to a regional Queensland hospital with principal diagnoses of stroke or TBI. Results SLPs frequently used informal approaches to assess ACDs. English-language formal assessment tools were also used in conjunction with the informal approaches. ACD diagnosis was more common in stroke than TBI patients. One-third of patients with ACD received inpatient rehabilitation at the study site. SLPs infrequently documented cultural or linguistic adaptions to assessment or interventions. Conclusions Informal approaches to assess ACDs were commonly employed which may be because they are perceived to be more culturally appropriate. Clinical guidelines for stroke and TBI should accommodate the diversity of cultures and languages. Better consideration of Aboriginal and Torres Strait Islander communication styles and incorporation of these into SLP ACD management approaches may facilitate accurate diagnosis and culturally safe rehabilitation services. Implications for Rehabilitation Informal approaches for assessment and intervention of ACDs, that incorporate yarning and salient tasks, are likely to be more culturally appropriate and safe for Aboriginal and Torres Strait Islander peoples. More flexibility and guidance in the use of culturally and linguistically appropriate alternative assessment approaches are required in the National stroke guidelines for Aboriginal and Torres Strait Islander peoples. The adoption of enhanced models of culturally secure ACD service provision, that incorporate frequent SLP engagement with an Aboriginal or Torres Strait Islander support person during assessment and rehabilitation, are needed. There is an imperative for health professionals to actively account for culture and language difference in rehabilitation practices to ensure Indigenous peoples worldwide receive equitable and culturally-responsive services.

On the determination of oil charge history and the practical application of molecular maturity markers

Determining the thermal maturity and the charge history of crude oil to any reservoir, has key implications for understanding petroleum generation, accumulation history and hence identification of exploration potential. In this paper we combine studies of several source rock sequences and associated crude oils using quantitative component concentration data in addition to traditional molecular marker ratio parameter approaches. The case history studies include examination of organic-rich sapropelic marine source rocks from the Second White Speckled Shale Formation (2 WS Fm.), in the Western Canada Sedimentary Basin and the upper Jurassic Draupne Fm. in the North Sea and their related oils. Each molecular component in the petroleum has a unique concentration evolution curve during source rock maturation, in which n-alkanes, light aromatic hydrocarbons and diamondoid hydrocarbons increase in concentration with increasing maturity, while biomarkers decrease in concentration with maturity. This maturity dependent concentration variation plus the ubiquitous mixing of multiple oils in the reservoir is a key process that complicates the direct application of qualitative molecular marker ratio approaches to analysis of petroleum systems. We suggest an alternative maturity assessment approach using maturation calibrated curves of absolute concentrations of biomarkers and other alkanes in petroleum, coupled with selected aromatic hydrocarbon ratios to track the maturity/petroleum mass fraction relationships for a reservoired oil mixture in a more complex but realistic manner. Isoprenoid alkanes show less variation in concentration with maturity than other components and may be used as an internal reference point for mass fraction maturity and charge history assessment. Using component concentration data normalized to the concentration of the isoprenoid alkanes and calibrated using source rock analyses at different maturity levels from a single petroleum system (2WS), a simple mass balance model was constructed that allowed aggregate concentration data to be calculated for any mixture of oils produced in a prescribed oil charge history. In principle any charge history can be simulated using this approach and comparing the modelled and actual quantitative compositional profiles of crude oils allows differentiation of the more plausible and implausible oil charge histories for that particular reservoir. Clearly considerable refinement of this approach is needed but it appears that such a procedure has the potential, if developed further, to be a useful addition to the arsenal of petroleum geochemists and basin modelers. Knowing what a typical complete charge mass fraction maturity profile would look like for a given source rock type, enables the estimation of missing charge in the basin, allows the detection of complex multi-history charge scenarios, and provides a much more robust and complete data set for calibration of basin model charge history assessments. It also, with further development may be integrated into stochastic basin modelling approaches to study petroleum systems.

Verifying student identity in oral assessments with deep speaker

Contract cheating, a form of academic misconduct in which students outsource assessment activities to third parties, is a topic of concern among educators. As similarity-detection systems are ineffective at detecting contract cheating, some institutions have turned to intensely criticised proctoring systems, however student and educator bodies report high costs and privacy concerns. Oral assessment is an alternative assessment approach that provides valuable interpersonal and communication skills in graduates and can naturally help detect and deter cheating. However, oral assessment is typically time-consuming, and in larger courses, it is challenging to validate respondents' identity. Advancements in machine learning approaches can scale time-consuming tasks that previously required prohibitive educator effort. One such system, Deep Speaker, is a speaker identification and verification system that can verify if two audio samples resemble speech from the same person with high accuracy. This paper presents an innovative tool that integrates an online oral assessment tool, Real Talk, with Deep Speaker. This proposed system facilitates scalable student-tutor discussions while providing longitudinal student identity validation with minimal cost and impact for institutions and addressing student privacy concerns. We evaluated the system and showed that student audio responses collected via oral discussion tools are suitable for verification. We then discuss the impact our system may have when applied in higher education. We posit that institutions can use such approaches to detect cases of contract cheating, enhance learning outcomes, and pave the way for more student-friendly assessment and discussion models in online education.

Reliable surface area determination of powders and meso/macroporous materials: Small-angle X-ray scattering and gas physisorption

The specific surface area is key for various application fields of porous materials. Its reliable and fast determination is therefore crucial for materials development and product quality management. Surface area assessment is usually based on physical adsorption using the Brunauer-Emmett and Teller (BET) theory. However, the BET method/gas adsorption exhibits a number of limitations and challenges including (i) time consuming sample preparation and measurement time, and (ii) reliable surface areas only possible for non-porous and meso-/macroporous materials to obtain reliable surface areas. In addition, the accuracy of surface area data obtained from adsorption depends on the proper choice of adsorptive/probe. Within this context, this work evaluates in a rigorous way in-depth Small Angle X-ray Scattering (SAXS) as an alternative and complimentary approach for reliable and fast surface area assessment. To our knowledge, this work can be considered the first systematic study where the surface areas from SAXS are compared and validated with true benchmark surface area data. We utilize silica-based nanoparticles as well as a well-defined mesoporous controlled pore glass for systematic SAXS and adsorption studies (argon and nitrogen at 87 K and 77 K, respectively). Owing to the lack of micro- and narrow mesopores of these model materials, the BET method based on argon 87 K adsorption can be applied to determine benchmark surface areas. Indeed, excellent agreement was found between surface areas derived from argon 87 K adsorption and SAXS. In fact, we demonstrate that the determination of specific surface area can be brought with SAXS to a new level, where parameters such as size of the probing adsorptive, its orientation and thus its effective cross-sectional area (when adsorbed on the surface) are no longer affecting the value of the specific surface area determined. Furthermore, SAXS was shown to be significantly faster than gas adsorption. For the silica materials used, the study shows that SAXS does not require degassing and – along with analysis times of only few minutes per sample – provides an accurate and extremely fast, high-throughput approach. This fundamental study can be considered a major step in enabling SAXS for reliable surface area assessment for applications both in nanoporous materials development and quality control, thus boosting SAXS for surface area determination in general, but in particular also for materials, where the usage of gas adsorption is restricted or not possible at all.

Examining Problem-Solving and Problem-Posing Skills of Pre-Service Mathematics Teachers: A Qualitative Study

The aim of this study is to examine the problem-solving processes and problem-posing skills of pre-service mathematics teachers, which consists of four stages (understanding the problem, preparing a plan for the solution, applying the plan, evaluating) defined by Polya (1997) with the progressive scoring scale based on the alternative assessment approach. Qualitative research approach has been adopted in the study. Participants of the study consist of 71 pre-service teachers studying at the department of primary education mathematics teaching at the education faculty of a state university in the Southeastern Anatolia region of Turkey. Since the problem solving and problem posing behaviors of the participants were examined separately in the study, the gradual scoring scale developed by Baki (2008) was used. As a result of the analysis, it was determined that the participants showed the highest performance in the category of understanding the problem, and the lowest performance in the category of evaluation and problem posing. It was determined that participants who failed in the problem posing phase either wrote the same problem or could not write a problem. Another result reached in the study is that the participants had difficulties in expressing the operations in mathematical language.

Reverse-Bayes methods for evidence assessment and research synthesis.

It is now widely accepted that the standard inferential toolkit used by the scientific research community—null‐hypothesis significance testing (NHST)—is not fit for purpose. Yet despite the threat posed to the scientific enterprise, there is no agreement concerning alternative approaches for evidence assessment. This lack of consensus reflects long‐standing issues concerning Bayesian methods, the principal alternative to NHST. We report on recent work that builds on an approach to inference put forward over 70 years ago to address the well‐known “Problem of Priors” in Bayesian analysis, by reversing the conventional prior‐likelihood‐posterior (“forward”) use of Bayes' theorem. Such Reverse‐Bayes analysis allows priors to be deduced from the likelihood by requiring that the posterior achieve a specified level of credibility. We summarise the technical underpinning of this approach, and show how it opens up new approaches to common inferential challenges, such as assessing the credibility of scientific findings, setting them in appropriate context, estimating the probability of successful replications, and extracting more insight from NHST while reducing the risk of misinterpretation. We argue that Reverse‐Bayes methods have a key role to play in making Bayesian methods more accessible and attractive for evidence assessment and research synthesis. As a running example we consider a recently published meta‐analysis from several randomised controlled trials (RCTs) investigating the association between corticosteroids and mortality in hospitalised patients with COVID‐19.

Online Remote Proctoring Software in the Neoliberal Institution: Measurement, Accountability, and Testing Culture

As COVID-19 spread in early 2020, a lockdown was implemented across Canadian provinces andterritories, resulting in the shuttering of physical post-secondary campuses. Universities quicklypivoted to remote learning, and faculty members adjusted their instructional and assessmentapproaches to align with virtual environments. Presumably to aid with this process, a number ofinstitutions acquired licenses to remote online proctoring services. This paper examines theresearch around online remote proctoring, examining the justification offered for the adoption ofonline remote proctoring, and contemporary research on assessment practices in higher education.Throughout the paper, I demonstrate a lack of research that speaks to the efficacy of this mode ofassessment while also acknowledging shifts in the testing environment, and an increase in studentanxiety. I argue that online remote proctoring is not only embedded within neoliberalism and auditculture, but supports a continued reliance on testing culture. It concludes with a discussion ofassessment culture, offering some alternative assessment approaches that might disrupt the veryneed for online remote proctoring.
 Keywords: Online remote proctoring, assessment, testing

Evaluation of community readiness for change prior to a participatory physical activity intervention in Germany.

SummaryA lack of communities’ readiness for change is reported as a major barrier toward an effective implementation of health promoting interventions in community settings. Adding an alternative readiness assessment approach to existing research practice, this study aimed to investigate how a selected community could be evaluated in-depth regarding its readiness for change based on multiple key informant perspectives, with the intention of using this knowledge for the preparation of improved local physical activity (PA) interventions for men above 50 years of age. We conducted semi-structured face-to-face key informant interviews with stakeholders and relevant persons from a local German community (N = 15). The interview guide was based on a comprehensive summary of community readiness dimensions. After verbatim transcription, we conducted thematic analysis to synthesize the complex results regarding community readiness related to PA. The data supported that the community disposed of a variety of resources regarding PA and showed signs of readiness for change. However, a certain degree of saturation regarding PA programs existed. The need for health enhancing PA interventions for men was only partly recognized. The local authority considered PA to be particularly important in the context of mobility and traffic safety. Including multiple stakeholders contributed to a balanced and in-depth assessment of community readiness and was helpful for determining starting points for tailored PA interventions due to the detection of complex relationships and structures. The study delivers preliminary evidence that a qualitative multi-perspective community readiness assessment adds value to quantified single-perspective readiness assessment research practice.

Combining indicators for better decisions – Algorithms vs experts on lakes ecological status assessment

The results of ecological condition assessments of ecosystems are related to key decisions taken for the purpose of remedial measures or maintaining their current state. In the assessment process, experts come across extensive datasets, the quality, and completeness of which do not always allow for a reliable evaluation, especially if a single empirical approach is used. In this paper, results of machine learning algorithms are presented, with a focus on Self-Organizing Maps. In this context, measurements of component parameters for the assessment of the ecological state of lake ecosystems were subjected to the process of unsupervised machine learning with the aim to create an alternative assessment approach based on the capabilities of neural networks. Results are mapped and compared with expert evaluations, allowing to extend knowledge about sub-clusters present in the data. The primary target of this paper is the ecological assessment expert. At an early stage, information was obtained about the presence of ecological outliers that may be subject to separate monitoring or verification of environmental activities and objectives. In the back-mapping process, the presented technique of map construction and clustering with various versions of the division was referenced to a set of expert classification findings, revealing the underlying structure of the results when addressed with an unsupervised data comprehension. The approach introduced here does not intend to interfere with the format of an original assessment methodology. Rather it aims at obtaining useful additional information which may help in making better decisions.