Comparative analysis of models for adjustment procedure in assets value independent evaluation performed by comparative approach

This paper addresses the field of economic measurements of the value of assets, carried out by the methods of independent expert evaluation. The mathematical principles of application, within a comparative methodical approach, of additive and multiplicative models for correcting the cost of single indicator of compared objects have been considered. The differences of mathematical basis of the compared models were analyzed. It has been shown that the ambiguity in the methodology of correction procedure requires studying the advantages and disadvantages of known models, as well as the justification and elaboration of recommendations for their application. Possible forms of correction representation using several alternative units of measurement have been defined; formulas for their interconnection have been built. Analytic expressions have been derived that mathematically describe the algorithms for performing the evaluation correction procedure using various forms of correction representation. The influence of the correction execution model on the characteristics of uncertainty in the independent evaluation result has been analyzed. The scope of two possible types of correction introduction models has been determined. A specific numerical example was used to demonstrate the methodological advantages of using a multiplicative model when summarizing percentage corrections. The independence of the correction result on the sequence of correction introduction has been confirmed. It is proposed to use the selected measure of partial corrections as a criterion for the adequacy of the correction introduction model. It is proved that the result of the independent expert evaluation depends on the chosen model and does not depend on the sequence of correction introduction. The reported study results are important in terms of theory and practice since they make it possible to improve the accuracy and reliability of the result of independent expert evaluation.

Diagnosing and treating depression and anxiety in patients with cardiovascular disorders and diabetes mellitus in primary healthcare: is training of physicians enough for improvement?

INTRODUCTION. Common mental disorders - anxiety and depression - are prevalent among patients with cardiovascular disease (CVD) and diabetes mellitus type 2 (DM) and can negatively influence treatment outcomes and healthcare expenses. Despite the importance of management of depression and anxiety in primary care facilities, the diagnostics and treatment of these disorders remain insufficient in the Russian Federation. OBJECTIVE. To explore whether the rates of referrals to psychiatrist and indicated pharmacological treatment received due to depression or anxiety among patients with CVD and DM will significantly change in the primary healthcare facility after the training of primary care physicians (PCPhs) to deal with comorbid depression and anxiety (including the algorithm for referral to a psychiatrist). METHODS. Patients in primary care outpatient settings with diagnoses of CVD and DM passed screening on anxiety and depression using the Hospital Anxiety and Depression Scale (HADS), and information about the indicated treatment for anxiety or depression was collected when present (Sample 1: n = 400). The educational programme for PCPhs on diagnostics of anxiety and depression was then performed, and PCPhs were instructed to refer patients with HADS 7 to a psychiatrist. After the training, the second sample was collected (Sample 2: n = 178) using the same assessments as for Sample 1. The independent expert (psychiatrist) evaluated whether the patients had received the indicated pharmacological treatment, according to the screening criteria used in the study for anxiety and depression for both samples. RESULTS. The proportions of patients with borderline abnormal and abnormal HADS scores ( 7) were 365 (91.2%) and 164 (92.1%) in Sample 1 and Sample 2, respectively. In Sample 1, among patients with HADS 7, 119 (29.8%) received psychopharmacological treatment, but in only 46 (38.7%) cases it was indicated in compliance with the screening criteria. In Sample 2, among patients with HADS 7, 59 (33.1%) received psychopharmacological treatment, and in only 14 (23.7%) cases was it indicated in compliance with the screening criteria. The differences in the indicated pharmacological treatment were not statistically significant, and no one from Sample 2 with HADS 7 met a psychiatrist through PCPh referral. CONCLUSIONS. Anxiety and depression are prevalent in patients with CVD and DM treated in primary care facilities, but these patients may not be receiving the indicated pharmacological treatment. Barriers to referral and the use of psychiatric consultation exist despite the focused training of PCPhs and the straightforward referral protocol provided.

Experience of (for) science and higher education in times of the coronavirus crisis causing COVID-19 disease

The coronavirus causing COVID-19 disease, among many other effects, has re-evaluated the world of science and higher education. Experts representing the world of science have become indispensable for developing strategies to fight the pandemic, and their knowledge has become valuable not only for developing and producing an effective vaccine. Relying on modern and innovative facilities of higher education institutions, representatives of the business sector, state and local administration and science, must jointly participate in finding practical solutions to the problems of the state and society. Countries affected by the pandemic need such a system of research and higher education, in which science will serve social and economic development, university graduates will find absorbing work, and those in power will benefit from an independent expert base, regardless of which political option is at the helm of government. Given the new challenges faced by researchers and higher education in times of the coronavirus pandemic that causes COVID-19 disease and the changing economic and social conditions resulting from the pandemic, this paper examines the role and importance of the scientific world both during and after the pandemic.

Is Australia Prepared for the Decommissioning Challenge? A Regulator's Perspective

The National Offshore Petroleum Safety and Environmental Management Authority (NOPSEMA) is Australia's independent expert regulator for health and safety, structural (well) integrity and environmental management for all offshore oil and gas operations and greenhouse gas storage activities in Australian waters, and in coastal waters where regulatory powers and functions have been conferred. The Australian offshore petroleum industry has been in operation since the early 1960s and currently has approximately 57 platforms, 11 floating facilities, 3,500km of pipelines and 1000 wells in operation. Many offshore facilities are now approaching the end of their operational lives and it is estimated that over the next 50 years decommissioning of this infrastructure will cost more than US$40.5 billion. Decommissioning is a normal and inevitable stage in the lifetime of an offshore petroleum project that should be planned from the outset and matured throughout the life of operations. While only a few facilities have been decommissioned in Australian waters, most of Australia's offshore infrastructure is now more than 20 years old and entering a phase where they require extra attention and close maintenance prior to decommissioning. When the NOGA group of companies entered liquidation in 2020 and the Australian Government took control of decommissioning the Laminaria and Corallina field development it became evident that there were some fundamental gaps in relation to decommissioning in the Australian offshore petroleum industry. There are two key focus areas that require attention. Firstly, regulatory reform including policy change and modification to regulatory practice. Secondly, the development of visible and robust decommissioning plans by Industry titleholders. The purpose of this paper is to highlight the importance and benefit of adopting good practice when planning for decommissioning throughout the life cycle of a petroleum project. Whilst not insurmountable, the closing of these gaps will ensure that Australia is well placed to deal with the decommissioning challenge facing the industry in the next 50 years.

Application of the Delphi Technique to Determine the Technological Competencies of a Faculty Member

<p style="text-align: justify;">The formed primary level and dynamic and sustainable development of technological competence provides quality management of teaching activities, increases the efficiency of the educational process, accelerates the achievement of pedagogical goals. Delphi expert assessment technique is increasingly used in the paradigm of pedagogy. Due to the set of advantages and objectivity of assessments, it has become the dominant method of this study. The objective of the study is to determine the current level of manifestation of technological competencies, as well as generalized prospects for development and improvement of the identified level within the selected group of freelance teachers using the technology of independent expert assessments –the Delphi method. In general, the following methods were used in the current study: methods of data collection and coordination, anonymous brainstorming, Delphi expert assessment technique, statistical and mathematical processing of results through Delphi formulas, comparative method, generalisations. The diversified approach to the interpretation of the technological competence of faculty members allowed determining: a) the level of faculty members’ knowledge of modern educational technologies at 89.1%; b) activity-practical aspect of training at 83.0%; c) dissonance between the theoretical and empirical level of teacher training and the algorithm for fulfilling the potential in practice at 21.5%; d) mastery of individual creative technologies for the organisation of an effective educational process at 55.9%; e) forecasted development of technological competencies of faculty members in the 5-year perspective under the condition of application of special control and skill trainings at 50.7%. Conclusion of the study is that according to the arithmetic mean of experts’ assessments of differentiated levels of technological competence, the overall level was 75.1%. The average result of the initial student survey on the estimating of the teachers’ technological competence was 69.7%. The difference of 5.4% between the data allows stating that both methods were relevant in this particular case.</p>

Evaluation of deep learning-based autosegmentation in breast cancer radiotherapy

Purpose To study the performance of a proposed deep learning-based autocontouring system in delineating organs at risk (OARs) in breast radiotherapy with a group of experts. Methods Eleven experts from two institutions delineated nine OARs in 10 cases of adjuvant radiotherapy after breast-conserving surgery. Autocontours were then provided to the experts for correction. Overall, 110 manual contours, 110 corrected autocontours, and 10 autocontours of each type of OAR were analyzed. The Dice similarity coefficient (DSC) and Hausdorff distance (HD) were used to compare the degree of agreement between the best manual contour (chosen by an independent expert committee) and each autocontour, corrected autocontour, and manual contour. Higher DSCs and lower HDs indicated a better geometric overlap. The amount of time reduction using the autocontouring system was examined. User satisfaction was evaluated using a survey. Results Manual contours, corrected autocontours, and autocontours had a similar accuracy in the average DSC value (0.88 vs. 0.90 vs. 0.90). The accuracy of autocontours ranked the second place, based on DSCs, and the first place, based on HDs among the manual contours. Interphysician variations among the experts were reduced in corrected autocontours, compared to variations in manual contours (DSC: 0.89–0.90 vs. 0.87–0.90; HD: 4.3–5.8 mm vs. 5.3–7.6 mm). Among the manual delineations, the breast contours had the largest variations, which improved most significantly with the autocontouring system. The total mean times for nine OARs were 37 min for manual contours and 6 min for corrected autocontours. The results of the survey revealed good user satisfaction. Conclusions The autocontouring system had a similar performance in OARs as that of the experts’ manual contouring. This system can be valuable in improving the quality of breast radiotherapy and reducing interphysician variability in clinical practice.

Formal and informal science advice in emergencies: COVID-19 in the UK

The importance of scientific advice to government gains greater recognition in emergencies but inevitably has to be done in an environment of uncertainty, with limited data and at high speed. Adapting existing structures is more effective than creating new ones in an emergency. Between emergencies, the UK has a structured scientific advice system, including Chief Scientific Advisers, scientists in government, regulatory bodies and independent expert committees, which were adapted to COVID-19 under the umbrella of the Scientific Advisory Group for Emergencies. These worked alongside networks of informal scientific advice, including internationally. Multiple sciences were needed, including from the social sciences and engineering in addition to clinical science and epidemiology, and these had to be integrated. A centrally directed clinical research programme helped provide practitioners robust evidence, with observational and interventional trials providing data for policy and testing treatments and vaccines. The scale of the emergency meant unavoidable tension between detailed work and speed, and between an integrated scientific view usable in decision-making and constructive challenge. While a final judgement of the UK scientific response will take time, everyone should be grateful to the thousands of scientists involved for the research, synthesis and advice, which improved outcomes for the public.

The new expertise required for designing safe tailings storage facilities

The global mining community has seen a dangerous sequence of failures in tailings dams, beginning with Mount Polley mine, followed by the Samarco, Cadia Valley and Córrego do Feijão mines. This sequence of failures began on August 4, 2014, at the Mount Polley tailings storage facility in British Columbia, Canada. The initial failure in the embankment at the Mount Polley tailings storage facility had substantial impact on the global mining industry. The Independent Expert Engineering Investigation and Review Panel (IEEIRP) tasked with the investigation of the breach in the tailings dam at Mount Polley made major contributions for new guidelines. The incident has given rise to comprehensive recommendations for best available tailings technologies (BAT) based on principles such as the elimination of surface water from impoundments with the promotion of unsaturated conditions in the tailings through drainage provisions. The application of these BAT principles for the surface storage of tailings leads to the use of filtered tailings technology. Filtered tailings technology or “dry stack tailings” can satisfy each of the BAT components when the impoundment is properly designed and constructed. The implementation of the best available technologies for the physical stability (BAT-PS) of tailings impoundments competes directly with the best available technologies for the chemical stability (BAT-CS) of reactive tailings that may produce acid and metalliferous drainage. The new expertise in mine waste management required to achieve both BAT-PS and BAT-CS are discussed in the present paper.

CHANGES IN REAL ESTATE VALUE DYNAMICS DURING SERVICE CYCLES AS A SOURCE OF NEGATIVE PERIODIC PROPERTY DEPRECIATION

Main methodological principles of mathematically describing the patterns of changes in the asset’s value/depreciation dynamics are studied in cases when economic measurements are performed by independent expert evaluation. The basic hypothesis suggests that for all tangible assets, which are characterized by redeemable depreciation, there is a possibility of negative periodic depreciation during short-term service periods when remedial and repair work to eliminate depreciation signs is carried out. The most influential price-forming factors that determine the asset’s depreciation indexes and indicators of value dynamics over long periods are identified and analysed. It is shown that when this period is comparable to the asset’s service life, most of tangible assets are characterized by both positive and negative periodic depreciation indexes at separate times. It is noted that the models used in accounting documents do not describe the actual changes in the value dynamics, and amortization in particular, since they do not take into account the possibility of increasing asset value and periodic negative depreciation. A new kind of mathematical model is proposed that takes into account the opposite signs of periodic depreciation in the operation and service periods. It is proved that the actual indicators of fair market value and periodic depreciation indexes of these types of assets can be determined by performing periodic independent expert evaluation (revaluation).

Deep learning assisted quantitative assessment of histopathological markers of Alzheimer’s disease and cerebral amyloid angiopathy

Traditionally, analysis of neuropathological markers in neurodegenerative diseases has relied on visual assessments of stained sections. Resulting semiquantitative scores often vary between individual raters and research centers, limiting statistical approaches. To overcome these issues, we have developed six deep learning-based models, that identify some of the most characteristic markers of Alzheimer’s disease (AD) and cerebral amyloid angiopathy (CAA). The deep learning-based models are trained to differentially detect parenchymal amyloid β (Aβ)-plaques, vascular Aβ-deposition, iron and calcium deposition, reactive astrocytes, microglia, as well as fibrin extravasation. The models were trained on digitized histopathological slides from brains of patients with AD and CAA, using a workflow that allows neuropathology experts to train convolutional neural networks (CNNs) on a cloud-based graphical interface. Validation of all models indicated a very good to excellent performance compared to three independent expert human raters. Furthermore, the Aβ and iron models were consistent with previously acquired semiquantitative scores in the same dataset and allowed the use of more complex statistical approaches. For example, linear mixed effects models could be used to confirm the previously described relationship between leptomeningeal CAA severity and cortical iron accumulation. A similar approach enabled us to explore the association between neuroinflammation and disparate Aβ pathologies. The presented workflow is easy for researchers with pathological expertise to implement and is customizable for additional histopathological markers. The implementation of deep learning-assisted analyses of histopathological slides is likely to promote standardization of the assessment of neuropathological markers across research centers, which will allow specific pathophysiological questions in neurodegenerative disease to be addressed in a harmonized way and on a larger scale.