Distribution Of Limited Resources Research Articles

LINEAR PROGRAMMING FOR ALLOCATING TRANSPORTATION CAPACITIES IN FREIGHT PLANNING

Effective allocation of transport capacities is vital for motor transport enterprises engaged in freight transportation. As the demand for goods transportation rises, optimizing resource utilization becomes essential for ensuring timely deliveries, minimizing costs, and enhancing overall operational efficiency. Linear programming, a powerful tool in mathematical optimization, plays a key role in facilitating the rational distribution of limited resources. By framing the allocation problem as a linear program, enterprises can systematically identify the optimal use of their transport capacities, taking into account critical factors such as vehicle availability, delivery schedules, and associated costs. In the realm of operational planning, linear programming offers a structured and analytical approach to addressing the complexities inherent in freight transportation. This study delves into both the theoretical underpinnings and the practical applications of linear programming, showcasing its potential to significantly improve resource allocation strategies, boost efficiency, and reduce operational costs. Through the analysis of real-world examples and empirical data, the study provides valuable insights that can aid practitioners and researchers alike in refining logistics optimization practices, ultimately contributing to more efficient and cost-effective freight transport operations. Keywords: linear programming, transportation capacities, operational planning, freight transportation, resource optimization.

Location, Age, and Antibodies Predict Avian Influenza Virus Shedding in Ring-Billed and Franklin’s Gulls in Minnesota

Influenza A virus (IAV) is a multi-host pathogen maintained in water birds and capable of spillover into humans, wildlife, and livestock. Prior research has focused on dabbling ducks as a known IAV reservoir species, yet our understanding of influenza dynamics in other water birds, including gulls, is lacking. Here, we quantify morphological and environmental drivers of serological (antibody detection by ELISA) and virological (viral RNA detection by PCR) prevalence in two gull species: ring-billed (Larus delawarensis) and Franklin’s (Leucophaeus pipixcan) gulls. Across 12 months and 10 locations, we tested over 1500 gulls for influenza viral RNA, and additionally tested antibody levels in nearly 1000 of these. We find substantial virus prevalence and a large, nonoverlapping seroprevalence, with significant differences across age and species classifications. The body condition index had minimal explanatory power to predict (sero)positivity, and the effect of the surrounding environment was idiosyncratic. Our results hint at a nontrivial relationship between virus and seropositivity, highlighting serological surveillance as a valuable counterpoint to PCR. By providing indication of both past infections and susceptibility to future infections, serosurveillance can help inform the distribution of limited resources to maximize surveillance effectiveness for a disease of high human, wildlife, and livestock concern.

Towards Efficient Resource Utilization Forecasting in Acute Heat Events Using OMOP.

Predicting resource utilization can help to optimize the distribution of limited resources in the healthcare system. This requires different climatic and medical data from different sources, which can lead to problems with interoperability. In the paper we describe which data is needed for the prediction and how the data can be made interoperable using OMOP CDM.

Researcher, research thyself? Mapping the landscape of canine health and welfare research funding provided by UK not-for-profit organisations from 2012-2022.

Research into canine health and welfare is supported by Government, charitable and private UK funding organisations. However, there is no current overall visibility or coordination of these funding activities, potentially compromising optimal distribution of limited resources. This study aimed to survey UK canine health and welfare funding by not-for-profit funders between 2012 and 2022, providing a novel baseline analysis to inform future sector stakeholder priorities. Funding data were collected from 10 wide-scope funders (UK Government funding councils and medical charities), 18 animal-directed funders (organisations specifically concerned with animal health and welfare) and 81 breed community groups. These 109 UK funders together provided traceable canine-relevant funding of £57.8 million during the surveyed period, comprising 684 individual grant awards supporting over 500 separate research projects. Wide-scope funders contributed £41.2 million (71.2% of total funding); animal-directed organisations, £16.3 million (28.1% of total funding); and breed-specific groups, £370K (0.6% of total funding). Individual grants ranged from £2.3 million to £300. Funding patterns varied between sectors. Animal-directed funders provided £14.7 million of canine-relevant research funding that foregrounded the dog, 73% of all such funding; wide-scope funders provided £17.5 million of canine-relevant One Health research funding, 97% of all such funding. Customised metrics developed for this study assessed the 'benefit to the dog' and 'pathway to impact' of individual research projects. Overall, studies supported by animal-directed funders achieved significantly higher 'benefit to the dog' scores (Mann-Whitney U = 45235, p<0.001) and 'pathway to impact' scores (Mann-Whitney U = 43506.5, p<0.001) than those supported by wide-scope funders. The landscape of UK not-for-profit funding of canine health and welfare research is complex, with considerable variation between providers. Although wide-scope funders provide the majority of overall canine-relevant research funding, animal-directed funders provide the majority of canine-focused funding and support research with greater direct impact on canine welfare. Visibility of past funding patterns will enable stakeholders in this sector to make more informed decisions about future research. To increase clarity, certain words and phrases are used in specific ways within the context of this paper. Animal-directed funders-Charities and other funding organisations whose remit primarily concerns animals or veterinary work Canine-focused research-Investigations where the primary purpose is to advance understandings of canine health and/or welfare Canine-relevant research-All research that is framed as advancing understandings of canine health and/or welfare as a primary or subsidiary purpose Institution-Refers to universities and other centres where research is carried out Organisation-Refers to funding bodies, including research councils, charities and other groups Research grant-A single funding event originating from one or more funders Research project-A cohesive piece of research concerning a particular topic; may involve multiple researchers and/or multiple research grants, in series or in parallel Wide-scope funders-Large organisations whose remit does not primarily concern animals, i.e. (in this dataset) UKRI councils and the Wellcome Trust.

Визначення граничних величин споживання електричної енергії засобами оптимізаційного моделювання

In the heating season of 2022/2023, as a result of the military aggression of the Russian Federation and targeted attacks on electric power facilities, a significant shortage of electric energy occurred in the Integrated power system of Ukraine. Restriction schedules and emergency disconnection of consumers were forcibly applied. In the conditions of such an unprecedented violation of the security of electricity supply, the problem of determining the limit values of electric energy and power consumption has gained new relevance for the electricity market participants. In this study, the problem of determining the optimal limit values of electricity consumption based on the criterion of maximum income from its sale to three groups of consumers was set and solved: "Critical infrastructure", "Households" and "Non-household consumers". The formation of the three specified groups is related to price discrimination in the electricity market and the need to supply critical infrastructure facilities without limits. The decision variables in the optimization model are proposed to be specified in fractions of the provision of electrical energy needs (unit fractions), which allows for establishing equal conditions regarding restrictions for all distribution system operators. To take into account the social significance of electric energy as a commodity, an additional constraint was included to the basic optimization model: the lower limit of the decision variable for the "Households" group. Approbation of the proposed optimization model was carried out using spreadsheet modeling in MS Excel on reported data on the results of electrical load measurements on regime days. The results of computational experiments are presented for the conditions of different values of the deficit of electric energy in the Integrated power system of Ukraine and different values of the additional constraint for the «Households» group, in particular, quantitative estimates of the consequences of the included constraints for the functioning of the electricity market. The proposed method of determining the limit values of electric energy consumption allows to formalize the procedure for decision-making according to predetermined rules and thereby achieve a fair distribution of limited resources. Keywords: electric energy consumption, shortage, limit value, optimization modelling, spreadsheet model.

Methodological aspects of financial support investment and innovation development of agricultural enterprises

With the change in the geopolitical and economic situation, the emergence of new threats and challenges for domestic agricultural enterprises, the problem of increasing the efficiency of development, implementation, practical implementation of innovations and investment support of this process is becoming increasingly important. It has been established that the investment climate in Ukraine is extremely unfavorable for investors due to military actions on the territory of our country. Although, the indicator of the investment climate in 2021 acquired a "rather unfavorable" value by 53%, despite the fact that this year Ukraine reached the highest level of income from investments. The main groups of external and internal threats (at the state and enterprise level) to the innovative and investment development of agrarian enterprises are systematized and the system of financial support for their investment development is presented. Among the methods used to finance the investment and innovative development of agricultural enterprises, the following are distinguished: self-financing, equity, loan, state financing, financing at the expense of free assistance and charitable contributions, mixed financing, leasing, project financing. The principles of the functioning of the investment mechanism of agricultural enterprises are developed and the most important positive and negative aspects of investment financing sources are presented in a generalized form. With the help of rational formation and distribution of limited resources to obtain the necessary result, it is possible to achieve investment efficiency. In turn, improving the quality of investment becomes the basis of the effective process of development and implementation of innovations, innovative development of the economic system. An innovative approach to determining the investment and innovation mechanism of agricultural enterprises is proposed. The list of principles of the investment and innovation mechanism (as an interacting set of methods, forms, sources of investment) is supplemented by the principles of scientificity and priority. The advantages and disadvantages of the main sources of investment financing (state financing; public-private partnership; profit; depreciation deductions; insurance reimbursements; bank credit; leasing; issue of shares; project financing; bond loans; public funds; funds of foreign investors) are revealed. The main factors affecting the choice of specific sources of investment resources formation of agricultural enterprises are noted. A system of indicators for evaluating the effectiveness of innovation implementation by types of effect is provided.

DISTRIBUTION OF RESOURCES TO ENSURE ANTI-TERRORIST SECURITY OF SOCIALLY SIGNIFICANT FACILITIES

A new software package ‒ electronic testing ground ‒ designed to increase the anti-terrorist protection of socially significant objects is presented. The complex supports mathematical modeling of antagonistic conflict between the offender and risk recipients in the context of a terrorist attack. The complex is based on the author’s methodology for increasing security, based on countering a terrorist attack through the controlled movement of human flows (controlled evacuation) to security zones along safe trajectories. Active protection of risk recipients under attack conditions takes into account the capabilities of engineering and technical means of protection. Algorithms for modeling controlled movement are built on the conditions of minimizing damage to risk recipients in conditions of a terrorist attack. Active protection is advisable when the attack time horizon is about 10 minutes. The most important feature of the presented electronic test site is the design of movement trajectories of risk recipients in automatic mode, taking into account the dynamics of the development of a terrorist attack. A digital model of the protected object is built using the domestic BIM system Renga. To simulate the activity of the intruder and the movement of human flows in real time the building model is represented as a topological graph. Quantitative assessment of the level of terrorist security of each socially significant object is based on a comparison of the levels of threats and security. Correspondence between the level of security and the level of threats is decisive for identifying a set of objects whose protection system requires modernization. The software package is focused on solving practical problems. In particular, the distribution of limited resources allocated to improve anti-terrorist security. The practical orientation of the electronic training ground is demonstrated by the example of the distribution of funds for the modernization of the anti-terrorism security system for the buildings of an educational institution.

Development of a Model for Analyzing the Optimal Utilization of Classroom Space at the Federal Polytechnic, Nasarawa.

Managing the distribution of limited resources to meet the needs of people has always been a global issue that faces managers, administrators, business owners, leaders of institution and individuals alike. With the increase in number of students admitted in Federal Polytechnic Nasarawa, with a large population of about 10,000, there would be undue stress on the facilities on campus. The class rooms are not sufficient or adequate and not well-assigned compared to the measurable number of students available. This has given rise to the reduction in the length of time a lecturer spends in class, distractions from students because of classroom proximity, amongst others. These cause extreme distress on the students and lecturers alike as they are unable to study or teach, respectively, to their highest potential as a result of resources or amenities that are inadequate or wanting. Data were collected from Federal Polytechnic Nasarawa Central Examination Committee for 2022/2023 Academic Session. The linear and integer programming methodology was employed. From the result of the linear programming (LP), seven (7) out of the seventy-eight (78) available classrooms has been fully utilized. The study revealed that if the remaining seventy-one (71) classrooms are fully utilized and maximized, they will improve the current objective function with a seating capacity of 4, 640. The result of the integer programming (IP) using the branch and bound method revealed that fourteen (14) out of the seventy-eight (78) available classrooms has been fully utilized. It asserted that if the remaining sixty-four (64) classrooms are fully utilized and maximized they will improve the current objective function with a seating capacity of 7,131. The result of the sensitivity analysis indicates that the entire classroom has an allowable increase thus validating the proposed models. The study therefore concludes that classroom space utilization is being underutilized leading to congestion and overflow in the utilized classrooms.

COMPARISON OF NEURAL NETWORK ARCHITECTURES TO PREDICTING ELECTRICITY CONSUMPTION BY ENTERPRISE

Forecasting of electricity consumption is a key tool for enterprises, energy supply and power grid organizations. Accurate forecasting enables to plan the distribution of limited resources of the power grid facilities, as well as to manage the demand for electricity. In the context of modern demand management technologies, improving the accuracy of forecasting of electricity consumption becomes especially important.&#x0D; &#x0D; The purpose of the study is to improve the accuracy of predicting power consumption by the power supply object using neural networks.&#x0D; &#x0D; Materials and methods. The work used a data set containing a profile of the enterprise’s capacity for a three-month period, as well as additional data, such as time of day, day of the week, weekends and holidays, month. The data set is divided into training and control parts. Preliminary data processing, neural network architecture design, training and testing were carried out. The criteria for the quality of training are the mean absolute error, the mean square error and the coefficient of determination.&#x0D; &#x0D; Research results. In the work, a comparative analysis of three neural network architectures was performed: a one-dimensional convolutional network, a recurrent neural network with long-term and short-term memory, and WaveNet, on the basis of which their indicators of the quality of power consumption forecasting were evaluated. It was shown that all considered architectures of neural networks are suitable for the use in the issue of predicting power consumption. Long-term and short-term memory networks have shown good results in power prediction due to their ability to handle long-term time dependencies. The WaveNet architecture outperformed both long-term and short-term memory model-based recurrent neural networks and one-dimensional convolutional networks by selected criteria.&#x0D; &#x0D; Conclusions. The study led to the conclusion that the use of neural networks, especially architectures with long-term and short-term memory and WaveNet, is an effective approach for predicting power consumption. The quality of forecasting significantly depends on the choice of hyperparameters and preliminary processing of the initial data. Prospect for further research in this area is studying the influence of various factors on the accuracy of forecasting and optimization of the learning process of neural networks.

Lessons Learned From the Connecticut Response to COVID-19 in Nursing Homes During the First 2 Years of the Pandemic.

Nearly half of all SARS-CoV-2-related deaths in the United States occurred in long-term care facilities during the early pandemic. In Connecticut, statewide mitigation of this impact involved a collaboration between the Connecticut Department of Public Health and the Yale School of Public Health, alongside existing relationships with the long-term care industry and individual facilities. This close government-academic-industry collaboration facilitated the creation of a robust COVID-19 surveillance system that allowed for real-time analysis and identification of nursing homes where outbreak support was needed. The collaboration further facilitated vaccine and booster deployment to Connecticut nursing homes at a speed that outpaced much of the country. The impact of these interventions is demonstrated through COVID-19 case and death burdens among nursing home residents and the greater Connecticut population during each wave of the pandemic. We outline the evolution and impact of these alliances and how they enabled us to prioritize facilities, interventions, and the distribution of limited resources and training throughout the pandemic. We further detail lessons learned over the first 2 years of the pandemic. Such partnerships strengthen our ability to respond effectively to public health crises and should be created and/or maintained in the face of continued pandemic threats.

Disasters and kidney care: pitfalls and solutions.

Patients with kidney disease, especially those with kidney failure, are particularly susceptible to the adverse effects of disasters because their survival depends on functional infrastructure, advanced technology, the availability of specific drugs and well-trained medical personnel. The risk of poor outcomes across the entire spectrum of patients with kidney diseases (acute kidney injury, chronic kidney disease and kidney failure on dialysis or with a functioning transplant) increases as a result of disaster-related logistical challenges. Patients who are displaced face even more complex problems owing to additional threats that arise during travel and after reaching their new location. Overall, risks may be mitigated by pre-disaster preparedness and training. Emergency kidney disaster responses depend on the type and severity of the disaster and include medical and/or surgical treatment of injuries, treatment of mental health conditions, appropriate diet and logistical interventions. After a disaster, patients should be evaluated for problems that were not detected during the event, including those that may have developed as a result of the disaster. A retrospective review of the disaster response is vital to prevent future mistakes. Important ethical concerns include fair distribution of limited resources and limiting harm. Patients with kidney disease, their care-givers, health-care providers and authorities should be trained to respond to the medical and logistical problems that occur during disasters to improve outcomes.

Mutual aid and competition as driving forces of economic development

The theory of competition is one of the main theories of modern economic science and is an important component of its methodological and theoretical apparatus. In the classical and neoclassical paradigm of economic science, competition is objective, independent of individual economic entities, the basis of the market mechanism, an “invisible hand” that coordinates the activities of producers and consumers, the distribution of limited resources, the creation, distribution and use of economic benefits. Over the past 250 years, the theory of competition has gone through the path of formation and development and currently has a developed methodology that has made it possible to distinguish and study various types of competition and various types of market structures: pure competition, oligopoly, pure monopoly, monopolistic competition. The developed economic and mathematical apparatus of the microeconomic theory of competition makes it possible to realize its cognitive, practical and ideological functions. But throughout the entire period of formation and development of the theory of competition, there has been criticism of it. The object of criticism are both theoretical and practical aspects of the theory of competition. The most prominent opponents of the supporters of the theory of competition are Russian scientists: P. Kropotkin, A. Chayanov, N. Kondratiev, M. Tugan-Baranovsky, S. Kirdina-Chandler, G. Kleiner and others. They contrast the theory of competition with the theory of mutual aid, according to which mutual aid, not competition, is the driving force behind economic development. The authors of the article reconstructed the process of formation and development of the theory of competition and the theory of mutual assistance, revealed the relative heuristic significance of both theories, clarified the concept of “mutual assistance” in relation to the concept of “cooperation”, substantiated the existence of the dichotomy “mutual assistance – ​competition” and proved that it is driving force of economic development.

Математическая модель оптимального распределения ресурсов в строительной сфере в условиях их дефицита

Logistics in the field of construction is one of its most important components, directly affecting the success of the implementation of construction projects. The problem of the optimal distribution of available limited resources is an important and urgent task in planning and organizing construction work, especially in conditions of scarcity of resources. The solution of this problem directly affects the quality and result of construction projects, the duration and rhythm of construction, costs and labor productivity. Aim. The purpose of the study is to develop a mathematical model based on vector optimization methods that allows optimal distribution of various types of limited resources between construction activities, works or objects in order to increase the efficiency of construction projects. Materials and methods. The model of resource distribution described in the paper is based on the theory of vector linear optimization, which makes it possible to distribute limited resources of various types between works, activities, or construction objects. The model takes into account the minimum and optimal requirements for providing construction objects or works with resources, their supply, as well as the priority for supplying objects. A technique for organizing computational procedures according to the model by numerical methods is given. Simulation methods based on computational experiments substantiate the adequacy of the proposed model and the properties of the results obtained from it. Also, the effectiveness of the implementation of the resource allocation model in the system of planning and management of construction projects was assessed. Results. A mathematical model for the distribution of limited resources between construction objects, works or events has been developed and justified. The adequacy of the results obtained by the model is proved. A technique for carrying out computational procedures for the numerical implementation of the model in the MS Excel environment is described. On the basis of computational experiments, the efficiency of applying the resource allocation model in the management of construction projects was evaluated, which averaged more than 34%. Conclusion. The relevance of developing a model for the distribution of resources of various types in the field of construction is shown, the adequacy of the results is proved, the method for obtaining estimates from the model by numerical methods is described, and the economic effect of applying the model in practice is estimated. The proposed resource allocation model leads to a significant increase in the efficiency of organization and management of construction projects and increases the likelihood of their timely completion at minimal cost.

Применение методов планирования эксперимента в экспертных процедурах для машинного обучения модели распределения ресурсов при ликвидации пожара

Introduction. Intellectualization of control systems, including decision support systems, is an urgent need in the field of fire management. There are various types of support for decision makers. The paper focuses on mathematical and referential support, which makes it possible, on the basis of machine-learned optimization models, to prepare for the decision maker a set of suboptimal solutions consistent with his system of preferences. As a basis for the distribution of limited resources of fire and rescue units with simultaneous calls, a transport model is used, the parameters of the payoff function of which are trained on a sample of retrospective data formed with the participation of an experienced decision maker. To select solutions, expert procedures are used that are optimized by experiment planning methods, which can significantly reduce the time to prepare a decision without losing its quality, which makes the study relevant. Purpose of research. The purpose of the article is to construct and illustrate algorithms for applying the principles of optimal design of an experiment in the procedures for expert evaluation of options for distributing homogeneous resources of fire and rescue units over simultaneous calls. Methods. Methods of optimization, expert evaluation, machine learning of optimization models, simulation modeling, experiment planning were used. Results and discussion. The proposed technology for accelerating expert procedures for choosing the optimal distribution of homogeneous resources of fire and rescue units for simultaneous calls based on the principles of optimal planning of the experiment is illustrated by the example of two fire and rescue units and three calls. This example shows the effect of reducing the number of necessary assessments performed by decision makers by more than 70 %. In the case of distribution of different types of resources for each of them, a separate procedure should be built, similar to that described in this article. Conclusion. The results of a study of the application of the principles of optimal design of an experiment to speed up expert procedures for choosing by a decision maker the best option for distributing limited resources of fire and rescue units between simultaneous calls are presented. The proposed algorithm seems appropriate to be included in the expert system for supporting the management of fires. Keywords: fire and rescue unit; simultaneous calls; resources; transportation task; expert assessments; experiment planning; decision maker.

Identifying need for spay and neuter services: A GIS-based analysis

Abstract This study provides a method for assessing the need for spay and neuter services in Massachusetts by creating a composite index that accounts for spatial accessibility and social vulnerability. An accessibility index (AI) of existing low-cost spay/neuter (S/N) facilities was created using the two-step floating catchment area (2SFCA) method which was then combined with the social vulnerability index (SVI) from the Centers for Disease Control and Prevention to create a need index (NI). Two methods for selecting the final target areas from the NI results were examined and used to make recommendations for S/N funding allocation. The construction of the NI (i.e. factors included or weights applied to factors) had a significant impact on the results. The NI displayed statistically significant spatial autocorrelation, and hot spot analysis revealed statistically significant clusters of comparatively high- and low-need regions in the state. The target areas identified were strongly influenced by high levels of social vulnerability in urban areas and low spatial accessibility of low-cost S/N facilities in more rural western Massachusetts. The results of this project demonstrate the utility of geographic information systems (GIS)-based analysis in veterinary and shelter medicine, as well as the potential for the use of non-veterinary specific data, such as the CDC SVI, when planning the equitable distribution of limited resources. One Health impact statement Providing spay and neuter (S/N) services to owned and free-roaming cats, dogs and other companion animal species is integral to the health and well-being of the animals themselves. Their human companions also reap the physical and mental health benefits of the human–animal bond, in addition to the environmental and public health impact of limiting free-roaming dog and cat populations. By recognizing the relationships between human and animal populations, existing gaps in need can be addressed through the use of human data to inform decisions on animal health when relevant animal health service data are lacking. A composite index of factors accounting for the social vulnerability was combined with the spatial accessibility of existing S/N resources to create a final index of need for S/N resources. This transdisciplinary approach takes methodologies from public health, acknowledges the impact of the vulnerability of human populations on surrounding companion animal populations, and applies a practical method of identifying the need for specific veterinary medical services.

УПРАВЛЕНИЕ ПОРТФЕЛЕМ ПРОЕКТОВ – ИННОВАЦИОННЫЙ ПОДХОД К ПОВЫШЕНИЮ ЭФФЕКТИВНОСТИ СУДОСТРОИТЕЛЬНОЙ ПРОМЫШЛЕННОСТИ

The article contains generalized data on the typology, principles, role and advantages of implementing a project portfolio manage-ment system in the activities of enterprises in the shipbuilding industry of the Russian Federation. The current state of the produc-tion capacities of domestic shipyards, along with modern global trends in innovation and digitalization of the industry, require ship-building and ship repair enterprises to simul-taneously conduct several diverse projects that improve the distribution of limited re-sources between competing projects, max-imize benefits and ensure that ongoing pro-jects comply with the strategic goals of the company. As an effective approach to im-proving the quality of planning and invest-ment efficiency of shipbuilding enterprises, the paper considers the introduction of a project portfolio management system. Within the framework of the article, the systematization of the concepts of project management was made, the stages of the process and the mechanism for managing the project portfolio were identified.

Covid-19 vaccine dissemination: A public health ethical evaluation of Pennsylvania's plan during Phase 1A

BackgroundThe novel COVID-19 pandemic afforded public health leaders an opportunity to expedite vaccine development and dissemination. The United States found itself faced with the arduous task of ensuring swift and equitable distribution of limited resources, in the midst of often-competing priorities, including public health ethics, medical ethics, economic demands, and societal strains.MethodologyUsing the American Public Health Association's (APHA) newly revised public health code of ethics, which provides a decision-making framework and guidance for ethical analysis, we analyzed how Pennsylvania's COVID-19 vaccine dissemination plan aligned with the four core functions of public health ethics inquiry.Results/DiscussionUpon investigation, the state's plan evidenced use of public health ethics in goal setting and design. However, the core public health value given the highest priority, promoting health and safety, competed with the other core public health values of inclusivity and engagement, health justice and equity, and professionalism and trust. Despite known social disparities and risk factors, the state plan for COVID-19 vaccine dissemination aligned closely with federal guidance and prioritized all healthcare personnel and long-term care facility populations over high-risk individuals residing in the community.Conclusion/PerspectivesShould another pandemic necessitate allocation of scarce resources, especially preventative measures such as vaccines, decision-making agencies must consider disparate populations in planning and dissemination of material to the public. Any anticipated limitations in the ability to fulfill public health ethical principles should be clearly communicated to the public prior to implementation, thereby increasing trust.

Flood risk assessment and quantification at the community and property level in the State of Iowa

Flood risk assessment contributes to identifying at-risk communities and supports mitigation decisions to maximize benefits from the investments. Large-scale risk assessments generate invaluable inputs for prioritizing regions for the distribution of limited resources. High-resolution flood maps and accurate parcel information are critical for flood risk analysis to generate reliable outcomes for planning, preparedness, and decision-making applications. Large-scale damage assessment studies in the United States often utilize the National Structure Inventory (NSI) or HAZUS default dataset, which results in inaccurate risk estimates due to the low geospatial accuracy of these datasets. On the other hand, some studies utilize higher resolution datasets, however they are limited to focus on small scales, for example, a city or a Hydrological United Code (HUC)-12 watershed. In this study, we collected extensive detailed flood maps and parcel datasets for many communities in Iowa to carry out a large-scale flood risk assessment. High-resolution flood maps and the most recent parcel information are collected to ensure the accuracy of risk products. The results indicate that the Eastern Iowa communities are prone to a higher risk of direct flood losses. Our model estimates nearly $10 million in average annualized losses, particularly in large communities in the study region. The study highlights that existing risk products based on FEMA's flood risk output underestimate the flood loss, specifically in highly populated urban communities such as Bettendorf, Cedar Falls, Davenport, Dubuque, and Waterloo. Additionally, we propose a flood risk score methodology for two spatial scales (e.g., HUC-12 watershed, property) to prioritize regions and properties for mitigation purposes. Lastly, the watershed-scale study results are shared through a web-based platform to inform the decision-makers and the public.

Circular business paradigm in innovative solvations of industrial ecosystems of regions

In the conditions of the continuing crisis, determined both by external sanctions against Russia from several Western states, and the ongoing coronavirus pandemic, it is the industrial ecosystems of the country's regions that form innovative solvations with subjects of other industries and spheres of activity and are the main rational consumers of regional resources that combine the potential of innovative speed, high quality, adaptation to changing consumer demands, etc. This article examines the scientific and practical problem of the formation and functioning of innovation-oriented industrial solvates, the solution of which is in line with the new approach proposed by the authors to identify, determine the sources and rank the effects of innovative solvations in the regional industry. This approach is built on the concept of a circular economy, which is based on the assumption of the most rational organization and use of all types of resources of integrated industrial enterprises and related industries (spheres of activity), including through the use of end-to-end digital technologies. It has been proved that in various phases of the economic cycle, effective resource provision of solvation processes in the system of industrial innovations is of decisive importance, which means not only the rational distribution of limited resources between the participants of innovative solvations but also their lean and waste-free use in the production process.

New Role of Bioethics in Emergency Situations on the Example of COVID-19.

The COVID-19 pandemic has dramatically changed existing norm perception both in medical practice and in society. In the context of limited resources and absence of a known treatment protocol, this change particularly affected healthcare system, doctors, and the distribution of a life-support therapy. One of the main bioethical dilemmas presented by coronavirus epidemic is the discrepancy between public health ethics, characterized by the fair distribution of limited resources and public safety orientation, and patient-specific clinical ethics. The COVID-19 pandemic forced health workers into tragic situations that they had never previously experienced, when lack of available health care workers, ventilators, or hospital beds creates a necessity to classify and prioritize patients to determine who will get (or will not get) what type of care and where. Another important issue is the digital control of citizens who must reduce their freedom for the sake of the health of other citizens. This caused great concern among many people, who fear that the current situation will lead to their manipulation in the future. There is also a question of responsibility among politicians and authorized organizations for the health of not only the population of their country, but also the entire planet. These and other current issues require bioethical expertise.