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With the exception of foreign bodies, formerly food contact materials (FCM) were generally not considered a source of food safety concern. During the past decade several issues regarding FCM affected the food supply and caught the attention of industries, national bodies and of course consumers. But is it clear what an FCM is? The chapter presents different classifications of FCM depending on the type of contact, type of material and function. The potential hazards (physical, microbiological, chemical and allergen) associated with FCM and their risk factors are explained according to the type of material (e.g. wood, metal, plastic). The chapter also reviews the main standards used in the field (ISO 22000, BRCIoP and EN 15593) and gives an overview of the main regulations applicable. The chapter finishes with five case studies that bring the reader to reality in the management of FCM food safety.

In this chapter we focuses on the issues that arise out of the relationship between the developer and the buyer, including claims, user expectations, and the legal ramifications that may follow an unhealthy relationship. The discussion touches on standards, reliability, security, safety, quality of software, quality of service of software products, causes of software failures, developer and buyer protection, and techniques for improving software quality. Causes of software failures or poor performance of a software product are discussed attributing the causes to a variety of reasons but most notably human error, the nature of software itself, and the environment in which software is produced and used. Finally historic examples of software caused accidents are given including the Therac–25, the Space Shuttle Challenger, the Indian Bhopal chemical accident and the Chernobyl Nuclear Power accident. Both consumer protection and techniques for improving software quality are also discussed.

The selection of any ingredient may involve complex analysis of desired functionality, cost, supply, and other critical components. In this analysis, the regulatory considerations cannot be overlooked. Not reviewing ingredient source can cause commercialization difficulties and geometrically increase the difficulty of exportation. Ensuring safety in use is a fundamental expectation for any consumer product, both for consumption and for safe handling in the manufacturer’s plant and in the customer’s plant. Meeting and legally substantiating marketing and labeling claims cannot be an afterthought in the development cycle. Regulatory departments must ensure thorough data and documentation collection from each vendor to legally support any claims made. Product developers, marketing, and regulatory can make great partners. Together they can confirm the benefit of each type of encapsulant as it is weighed against the additional considerations to ensure the best choice is made for a successful customer solution.

Global Software Development (GSD) is becoming increasingly prevalent, with software development teams being distributed around the world and working in collaboration with partner companies despite geographic and time differences. The main advantage of GSD which makes it attractive is the greater availability of human resources at lower costs. However, there are several disadvantages which are caused by the distance which separates the development teams. Coordination and communication become more difficult when the software development teams are located in different places, resulting in hidden costs involved in this process. As such, the effort estimation models used for collocated software development are inadequate for estimation in GSD. Thus, effort estimation in GSD is becoming an important area of research. Many researchers have focused on effort estimation in GSD over the last decade. This paper presents the findings of a systematic review of the related literature by summarizing the hidden costs in GSD, and discussing the open research issues in effort estimation in GSD.

Management of supplier and raw material with respect to food safety is a complex task, yet it can be made simple by appropriate organizational and management culture. A food safety manager with the right culture, adequate formal education, and relevant experience would apply the available tools, such as good manufacturing practices, hazard analysis and critical control point, and audits to ensure the final safety of a product. Supplier performance and adherence to agreed specifications with regard to raw materials are key criteria to be managed in maintaining food safety. Continuous contact and review of supplier and raw material performance would lead to continuous improvement.

Since their discovery in 1961, liposomes have mainly been studied and applied to the fields of drug and gene delivery. However, as some research studies have shown, there is the potential for liposome application in the food, beverage, and neutraceutical industries. Unfortunately, to date, these research advances have been stuck in the small-scale phase as large-scale production and manufacturing of liposomes in food and beverages face grave issues that are often more costly to overcome than they are beneficial to the product they are trying to enhance. In this chapter, we will take a look at some of the studies that have been done on liposomes in the food and beverage industry and the problems that have been encountered in large-scale production. We will also take a look at one supplemental liposomal product and how attempts are being made to avoid the difficulties of commercialization.

This study aims to highlight the relevance of budget transparency in improving human development and fill the gap in the literature, which has traditionally considered the concept of development in economic terms. Here, development refers to levels of knowledge, the possibility of enjoying a long and healthy life and having a decent standard of living. Improving human development is the main point of interest in the assessment of public policy outcomes and this study is focussed on one specific policy, namely, budget transparency. By using a pool of 110 countries for the years 2008, 2010, 2012, 2015 and 2017, the empirical results demonstrate a positive effect of the open budget index on the human development index, suggesting that budget transparency is a good way to improve levels of human development. These findings are essential not only for academic debate but also for practitioners because they show transparency as a relevant tool to improve human development. Points for practitioners Budget transparency is a relevant tool to improve human development. Transparency may improve the quality of life through a better quality of governance. The central roles played by transparency and participation coupled with accountability have been confirmed. The complexity of the concept of human development involves, among other things, disclosing information regarding the public policies. Examining budgets, guaranteeing their transparency as well as the transparency of the budgeting process, is highly recommended to improve human development.

Although balance control is an integral component of all daily activities, its complex and flexible nature makes it difficult to assess adequately. This paper discusses balance by examining it in relation to function and the physical environment. Balance is affected by both the task being undertaken and the surroundings in which it is performed. Different tasks and environments alter the biomechanical and information processing needs for balance control. These issues are discussed and a modification of Gentile's taxonomy of tasks is suggested for analysis of clinical balance tests, some of which are used as examples.

Operational risk is a substantial source of risk for US banks. Improving the performance of operational risk models allows banks’ management to make more informed risk decisions by better matching economic capital and risk appetite, and allows regulators to enhance their understanding of banks’ operational risk. We show that past operational losses are informative of future losses, even after controlling for a wide range of financial characteristics. We propose that the information provided by past losses results from them capturing hard to quantify factors such as the quality of operational risk controls, the risk culture, and the risk appetite of the bank.

In our cheap-talk setting, an expert privately observes multiple binary signals, her soft evidence, about a continuous state of the world and then communicates with a decision-maker. While direct transmission of evidence entails communicating the underlying signals, indirect transmission of evidence entails communicating a summary statistic of her evidence. We first establish that fully informative equilibria exist if the conflict of interest is small. Otherwise, direct transmission of evidence is impossible, as withholding one part of the soft evidence in the communication necessarily induces incentives to manipulate the report on the other part. On the contrary, indirect transmission of evidence remains partially informative for intermediate conflicts of interest. Finally, we introduce the possibility of certification. We show that, if the costs of certification are low, the expert can fully reveal her evidence regardless of the conflict of interest.

With recent developments in the field of tissue engineering (TE), innovative products are seeking access to the market to be applied in patients. Therefore, a framework has to be defined in which tissue-engineered products can prove their safety and effectiveness. For these products, the challenge to live up to the standards of drug development arises, not only with respect to practical implementation but also with respect to legislation and ethics. Within this chapter, an overview is given on the development of the standards for this new class of products and on the current status of regulation and legislation in this rapidly changing field.

Many lives and aircrafts have been lost due to human errors associated with mental workload overload (MWLOL). Human errors are successfully considered in existing Fault Tree Analysis (FTA) methods. However, MWLOL is considered through Performance Shaping Factors indirectly and its information is hidden in FT construction, which is not conducive to analyze the root causes of human errors and risks. To overcome this difficulty, we develop a risk analysis method where Multiple Resources Model (MRM) is incorporated into FTA methods. MRM analyzes mental workload by estimating the resources used during performing concurrent tasks, probably including abnormal situation handling tasks introduced by basic events in FT. Such basic events may cause MWLOL and then trigger corresponding human error events. A MWLOL gate is proposed to describe MWLOL explicitly and add these new relationships to traditional FT. This new method extends previous FTA methods and provides a more in-depth risk analysis. An accident, a helicopter crash in Maryland, is analyzed by the proposed method.

This article discusses the features of the digital transformation of the following state functions: information support in the field of environmental protection, state accounting in the field of environmental protection, regulation in the field of environmental protection (in terms of the use of the best available technologies), state environmental supervision, and administration of fees for negative environmental impact (NVOS). It is proved that the data of the state register of objects of negative impact, formed as a result of the state accounting of objects that have a negative impact on the environment, the implementation of state environmental supervision, and the administration of fees for NWOS should become the basis for making environmentally significant decisions. To expand the scope of use of this information, it is proposed to ensure the interoperability of the state register data. In addition, the authors come to the conclusion that digitalization of technological rationing based on the best available technologies (hereinafter also BAT) is associated with the use of such technologies as data turnover regulation, experimental legal regimes (regulatory sandboxes) and assessment of the compliance of the applied technology with the best available technology. Moreover, when implementing state environmental supervision, inspections should be planned based on the hazard category of objects of negative impact and when conducting inspections, remote control methods should be used. It is also essential to introduce electronic test sheets for self-checking enterprises. Finally, the digitalization of calculating and collecting fees for NVOS should ensure the smooth functioning of calculating fees by the payer in digital format and control over the correctness of calculation and collection by the supervisory authority.

The point at which clinical development programs transition from early-phase to pivotal trials is a critical milestone. Substantial uncertainty about the outcome of pivotal trials may remain even after seeing positive early-phase data, and companies may need to make difficult prioritization decisions for their portfolio. The probability of success (PoS) of a program, a single number expressed as a percentage reflecting the multitude of risks that may influence the final program outcome, is a key decision making tool. Despite its importance, companies often rely on crude industry benchmarks that may be "adjusted" by experts based on undocumented criteria and which are typically misaligned with the definition of success used to drive commercial forecasts, leading to overly optimistic expected net present value calculations. We developed a new framework to assess the PoS of a program before pivotal trials begin. Our definition of success encompasses the successful outcome of pivotal trials, regulatory approval, and meeting the requirements for market access as outlined in the target product profile. The proposed approach is organized in four steps and uses an innovative Bayesian approach to synthesize all relevant evidence. The new PoS framework is systematic and transparent. It will help organizations to make more informed decisions. In this paper, we outline the rationale and elaborate on the structure of the proposed framework, provide examples, and discuss the benefits and challenges associated with its adoption.

The rising prevalence of multi-drug resistant bacteria is an urgent health crisis that can only be countered through renewed investment in the discovery and development of antibiotics. There is no panacea for the antibacterial resistance crisis; instead, a multi-faceted approach is called for. In this perspective we make the case that, in the face of evolving clinical needs and enabling technologies, numerous validated antibacterial targets and associated lead molecules deserve a second look. At the same time, many worthy targets lack good leads despite harboring druggable active sites. Creative and inspired techniques buoy discovery efforts; while soil screening efforts frequently lead to antibiotic rediscovery, researchers have found success searching for new antibiotic leads by studying underexplored ecological niches or by leveraging the abundance of available data from genome mining efforts. The judicious use of “polypharmacology” (i.e., the ability of a drug to alter the activities of multiple targets) can also provide new opportunities, as can the continued search for inhibitors of resistance enzymes with the capacity to breathe new life into old antibiotics. We conclude by highlighting available pharmacoeconomic models for antibacterial discovery and development while making the case for new ones.

The article is devoted to the problem of developing an analytical data processing system for monitoring information security within the information security management system of modern companies conducting their main activities in cyberspace and using cloud infrastructure. Based on the analysis of modern information technologies related to ensuring information security of cloud infrastructure and the most popular products for ensuring information security of cloud infrastructures, as well as existing scientific approaches, a formalized approach to the synthesis of an analytical data processing system for monitoring the information security of an informatization object using cloud infrastructure is proposed. This approach takes into account the usefulness of the used information technologies from the viewpoint of information security. A general model of the structure of information support of an analytical data processing system for monitoring information security, as well as a model of the dependence of the usefulness of information technology on time and the ratio of the skill level of an information security specialist and an attacker are presented. The quality of the information security monitoring system is used as a criterion in the first optimization model. The following limitations are suggested: limitation on the time of making a decision on an incident; limitation on the degree of quality of analysis of information security events by the analytical data processing system and limitation on the compatibility of data analysis functions with data types about information security events. The cited results of the study of the second model show a logically consistent dependence of the usefulness of information technology on time and the ratio of the skill level of an information security specialist to the skill level of an attacker. The particular models of the structure of the information support of ASOD are presented. They make it possible to determine the rational structure information support of ASOD according to particular criteria. The following particular criteria are used: the maximin criterion of the usefulness of the information support of ASOD for monitoring the information security of an informatization object in the cloud infrastructure; the criterion for the maximum relevance of information support distributed over the nodes of the cloud infrastructure for systems with a low degree of centralization of management.

Cardiovascular (CV) disease impacts tens of millions of people annually and carries a massive global economic burden. Continued advances in medical imaging, hardware and computational efficiency are leading to an increased interest in the field of cardiovascular computational modelling to help combat the devastating impact of CV disease. This review article will focus on a computational modelling technique known as lumped parameter modelling (LPM). Due to its rapid computation time, ease of automation and relative simplicity, LPM holds the potential of aiding in the early diagnosis of CV disease, assisting clinicians in determining personalized and optimal treatments and offering a unique in-silico setting to study cardiac and circulatory diseases. In addition, it is one of the many tools that are needed in the eventual development of patient specific cardiovascular “digital twin” frameworks. This review focuses on how the personalization of cardiovascular lumped parameter models are beginning to impact the field of patient specific cardiovascular care. It presents an in-depth examination of the approaches used to develop current predictive LPM hemodynamic frameworks as well as their applications within the realm of cardiovascular disease. The roles of these models in higher order blood flow (1D/3D) simulations are also explored in addition to the different algorithms used to personalize the models. The article outlines the future directions of this field and the current challenges and opportunities related to the translation of this technology into clinical settings.

Minimally invasive techniques have been at the forefront of surgical progress, and the evolution of endovascular robotic technologies has seen a paradigm shift in the focus of future innovation. Endovascular robotic technology may help overcome many of the challenges associated with traditional endovascular techniques by enabling greater control, stability, and precision of target navigation and treatment, while simultaneously reducing operator learning curves and improving safety. Several robotic systems have been developed to perform a broad range of endovascular procedures, but none have been used at scale or widely in routine practice, and the evidence for their safety, effectiveness, and efficiency remains limited. High cost and device complexity, lack of haptic feedback, and limited integration and interoperability with existing equipment and devices are the principal technology, cost, and sustainability barriers to the scalability and widespread adoption in day-to-day practice. In order to fully realize its potential, future robotic innovation must ensure compatibility with a range of off-the-shelf equipment that can be tracked and exchanged quickly during a procedure and come together with developments in navigation, tracking, and imaging. Reducing cost and complexity and supporting sustainability of the technology is key. In parallel, new technologies must be evaluated by clear and transparent standardized outcomes and be accompanied by robust clinical training. Key to the successful future development and dissemination of robotic technology is open collaboration among industry, clinicians, and patients in order to fully understand and address current challenges and enable the technology to realize its full potential.

Delivering transformative therapies to patients while maintaining growth in the pharmaceutical industry requires an efficient use of research and development (R&D) resources and technologies to develop high-impact new molecular entities (NMEs). However, increasing global R&D competition in the pharmaceutical industry, growing impact of generics and biosimilars, more stringent regulatory requirements, as well as cost-constrained reimbursement frameworks challenge current business models of leading pharmaceutical companies. Big data-based analytics and artificial intelligence (AI) approaches have disrupted various industries and are having an increasing impact in the biopharmaceutical industry, with the promise to improve and accelerate biopharmaceutical R&D processes. Here, we systematically analyze, identify, assess, and categorize key risks across the drug discovery and development value chain using a new risk map approach, providing a comprehensive risk-reward analysis for pharmaceutical R&D.

In recent years, smart energy has become an important part of smart city construction. For the oil industry, exploring how to apply enabling technologies such as data transmission, internet of things, big data analysis in the energy field can fill the gap of applying intelligent technologies to energy facilities system. For the petroleum field, one of the biggest threats to safe drilling operations during oil and gas exploration is loss circulation. In the study, based on a new assessment framework that integrates intelligent energy into smart cities, an improved fuzzy evaluation method of drilling risk based on cloud method is proposed to realize the transformation of drilling risk from quantitative to qualitative. The theory proposed in this paper considers the subjective engineering experience of experts and the information contained in objective data, which make the judgment results more objective. The cloud theory proposed can clearly show the result of risk assessment, which fully reflects the fuzziness and randomness of the drilling system. The model is embedded in the evaluation framework of smart cities, which realizes the online remote online assessment of risks by city office workers.

Relevance. The article is devoted to creating prognostic models based on epidemiological and immunological data. Objective: to study the comparative dynamic epidemiological and immunological characteristics of patients with COVID-19. Materials and methods. Methodological approaches to the use of system analysis of epidemiological and immunological characteristics of patients with COVID-19 using multivariate analysis are described. The used technologies of computer-aided analysis systems, algorithms for recognizing, measuring and identifying the condition of patients, and methods of statistical data processing made it possible to create a universal information predictive model for calculating the dynamics of infectious diseases prone to generalization (pandemics), as well as to understand in which groups these new infectious diseases are most dangerous. Results and discussion. Using the methods of system analysis, the epidemiological and immunological aspects of predictive models of the coronavirus pandemic were evaluated using the most objective international data, which increased the information content of the analysis. Conclusions . Creating predictive epidemiological and immunological models of the pandemic is an urgent and promising task to combat the medical and social consequences of the spread of coronavirus infection in Russia.

Objective To explore the concentration level of radionuclide in mushrooms in northeast China, and to analyze the risk of the effective dose of edible mushrooms to the human body. Methods A total of 68 samples of 18 species of mushrooms from three regions in northeast China and Beijing as control were collected from 2017 to 2020. The activity of radionuclide in mushrooms was measured by gamma-spectrometry, and the activity was analyzed by statistical analysis. The relationship between 137Cs and 40K content in mushrooms was explored. Results 238U was undetected in all samples. The activity concentration of 226Ra, 232Th, 40K, 137Cs were in range of 1–34.3, 2.26–32.3, 208–2,388 and 0.6–130.3 Bq/kg, respectively. The 137Cs and 40K concentrations in mushrooms were not correlated. The risk analysis of radioactivity in the collected mushrooms showed that the highest effective dose of the 18 kinds of mushrooms was 0.042 ​mSv. Conclusion The radionuclide content of mushrooms in northeast China is within the normal range. The mushrooms will not cause risk to human health.

Pharmacometrics is an emerging science that interprets drug, disease, and trial information in a mathematical fashion to inform and facilitate efficient drug development and/or regulatory decisions. Pharmacometrics study is increasingly adopted in the regulatory review of new antimicrobial agents. We summarized the 31 antimicrobial agents approved by the US Food and Drug Administration (FDA) and the 26 antimicrobial agents approved by European Medicines Agency (EMA) from January 2001 to May 2019. We also reviewed recent examples of utilizing pharmacometrics to support antimicrobial agent’s registration in China, including modeling and simulation methods, effects of internal/external factors on pharmacokinetic (PK) parameters, safety and efficacy evaluation in terms of exposure‐response analysis, refinement of the wording of product labeling and package leaflet, and possible postmarketing clinical trial. Ongoing communication among regulator, academia, and industry regarding pharmacometrics is encouraged to streamline and facilitate the development of new antimicrobial agents. The industry can maximize its benefit in drug development through continued pharmacometrics education/training.

In 2021, the ICRP initiated the revision of the general recommendations of the system of radiation protection, and part of it will focus on dose quantities. The recently published ICRP Publication 147 and ICRU Report 95 have described the extent of the proposed modifications and paved the way for the strategy to be adopted. These revisions would seek to simplify, improve the accuracy and extend the field of use of dose quantities. While the Radiological Protection Working Group of the World Nuclear Association recognises the notable improvement in the estimation of the protection quantities and the usefulness of such changes for the medical and research sector, the benefits of the proposed new system seem very limited for the nuclear industry and industries involving naturally occurring radioactive materials. The complexity associated with changing a long-standing and robust system and the risk incurred by the human factor seem unjustified, bearing in mind the likely cost.

Vaccines are key in charting a path out of the COVID-19 pandemic. However, development of new vaccines is highly dependent on availability of analytical methods for their design and evaluation. This paper highlights the challenges presented in having to rapidly develop vaccine analytical tools during an ongoing pandemic, including the need to address progressive virus mutation and adaptation which can render initial assays unreliable or redundant. It also discusses the potential of new computational modeling techniques to model and analyze key viral proteins and their attributes to assist vaccine production and assay design. It then reviews the current range of analytical tools available for COVID-19 vaccine application, ranging from in vitro assays for immunogen characterization to assays to measure vaccine responses in vivo. Finally, it provides a future perspective for COVID-19 vaccine analytical tools and attempts to predict how the field might evolve over the next 5–10 years.

PURPOSE: Regulatory agencies such as the US Food and Drug Administration and health technology assessment bodies are increasingly using real-world evidence (RWE). The ability of healthcare systems to reliably generate response rate and progression-free survival from real-world data is unknown. We examined the capacity of a single-payer system to provide RWE by evaluating the frequency of computed tomography (CT) imaging during standard first-line metastatic systemic treatment of breast, colorectal, and lung cancer. METHODS: A 1-year cohort of patients with metastatic-at-diagnosis breast, colorectal, and lung cancer treated with first-line systemic therapy (excluding hormone therapy) referred to BC Cancer in 2016 was retrospectively reviewed for first-line treatment and CT imaging. Duration of first-line treatment was calculated from the first to the last dose of therapy. CT imaging was counted from the start of therapy to 8 weeks after the last therapy dose. RESULTS: A cohort of 664 patients was identified from the BC Cancer Registry. Distribution of metastatic disease at diagnosis was breast (n = 82), colorectal (n = 214), and lung (n = 368) cancer. For breast, colorectal, and lung cancer, there was a baseline CT within 4 weeks of treatment initiation in 59%, 51%, and 48% of patients, with median duration of first-line treatment of 14.6, 25.3, and 11.9 weeks and median CT imaging interval of 9.1, 9.0, and 6.1 weeks. CONCLUSION: In our publicly funded healthcare system, availability of baseline CT imaging was 48% to 59% and the frequency of assessment ranged from 6.1 to 9.1 weeks, subject to patterns of practice and resource availability. Our system was not capable of providing RWE for image-based end points. Alternative end points should be considered to capitalize on the wealth of real-world data.

Monitoring and contract renegotiation are two common solutions for addressing information asymmetry and uncertainty between a client and a vendor of software outsourcing services. Monitoring is mostly applied in time-and-materials contracts, as a basis for inspecting and reimbursing the vendor’s efforts in system development. Renegotiation, by contrast, is deployed in fixed-price and time-and-materials contracts to mitigate the loss of surplus from uncertainty after system development. We investigate the interaction between monitoring and renegotiation and examine the corresponding contract choice problem. We find that the client benefits from renegotiation based on two effects: an uncertainty-resolution effect and a post-development incentive effect, which incentivizes the vendor to exert additional effort in system development. Monitoring does not resolve uncertainty, although it does encourage the vendor to exert additional effort, a pre-development incentive effect. Our analysis shows that the choice of renegotiation or monitoring depends on the interactions of the above effects, which are moderated by the renegotiation cost, monitoring cost, and bargaining power in renegotiation. When renegotiation cost is low: if the client has high bargaining power and low monitoring cost, monitoring and renegotiation are complements and both are selected; otherwise, the two instruments are substitutes and contract renegotiation is preferred. When renegotiation cost is high: monitoring substitutes for renegotiation and the client only chooses monitoring if the cost to do it is low; or else neither is used. Overall, this research shows that four appropriate contract strategies should be used under somewhat different circumstances. We further analyze the impacts of some other key aspects of software outsourcing and extend the base model to address two alternative situations to show the robustness of our findings. The results apply to a range of software reliability growth models, including when machine learning or cloud computing are used.

Autonomous Vehicles (AVs) have a large potential to improve traffic safety but also pose some critical challenges. While AVs may help reduce crashes caused by human error, they still may experience failures of technologies and sensing, as well as decision-making errors in a mixed traffic environment. A disengagement refers to an AV transitioning control from autonomous systems to the trained test driver. The safety critical nature of disengagements makes it imperative to analyze disengagements and crashes together. This study analyzes both crashes and disengagements from real-world AV driving in California to fill the knowledge gap regarding the relationship between disengagements and crashes in a mixed traffic environment. A nested logit model was calibrated using three different outcomes: (1) disengagement with a crash, (2) disengagement with no crash, and (3) no disengagement with a crash. Furthermore, endogenous switching regime models were also calibrated to draw distinctions between the relation of disengagements and crashes while accounting for endogeneity effects. The results show that factors related to AV systems (such as software failures) and other roadway participants increase the propensity of a disengagement without a crash. Furthermore, AVs were observed to disengage less often as the technology matured over time. Marginal effects revealed an 8% decrease. The results thus suggest that disengagements are a part of AVs' safe performance and disengagement alerts may need to be triggered in order to avoid certain failures with current technology.

Work-related fatigue is a multidimensional phenomenon with significant effects on operational performance. Our work focuses on how the literature of operational research measures and models fatigue and its effects on operational performance, and on how it mitigates those effects. We position the literature of fatigue relative to that of work-rest scheduling, shift scheduling, multitasking, ergonomics, deterioration scheduling, and occupational health and safety. We classify the literature of fatigue across multiple dimensions: the methods by which it is identified and measured; the operational research methodology applied for fatigue prevention or mitigation; the flexibility allowed in work-rest scheduling and in shift scheduling; applications within manufacturing, construction, transportation, hospitals, and services; and the extent to which real data is used and results are implemented. Our work shows that operational research has contributed numerous effective algorithms and heuristic solution procedures to fatigue mitigation. We also identify several important research directions for operational research, to promote its broader and more effective use to identify and mitigate the effects of fatigue on operational performance.

Background The screening of biological hazards, chemical contaminants and allergens in food products is a major concern of food industry since they can cause serious illnesses and even lead to death. Therefore, there is a significant interest in developing low-cost, robust, and rapid detection methods for food safety and quality analysis. Conventional methods provide accurate analytical characteristics, but require well-equipped laboratories, trained personnel, costly reagents, and complicated sample preparation procedures prior to the detection in order to obtain reliable results. Hence, they are not always ideal for on-site food surveillance. Scope and approach This paper discusses the fundamentals of microfluidic paper-based analytical devices (μPADs) and reviews the recent progress in their usage for screening biological hazards, harmful chemical residues, and allergens in food products to systematically evaluate the strengths and weaknesses of this technology. It then covers future trends and useful strategies that could be employed in μPADs design and fabrication procedures to address the critical challenges in equipment-free food analysis. Key findings and conclusions μPADs offer promising avenues to revolutionize food safety and quality analysis with merits of equipment-free sample preparation and detection at low-cost. Despite the advancement in the microfluidic technology, the manufacturing of user-friendly sample-to-answer μPADs still requires intensive research studies to be employed for robust and sensitive food safety and quality analysis.

Risk-taking is traditionally explained through outcome-value expectancy models. Recently, however, it has been demonstrated that immediate versus delayed feedback increases risk-taking independently of expected value. The current work takes a novel approach to investigate behavioral motivation in different risk-taking contexts, building on recent progress in identifying the reinforcing impact of actioneffectiveness. Participants performed 1 of 2 different versions of the Balloon Analogue Risk task (BART) in which an action increases (Experiment 1 and 2) or decreases (Experiment 3) the risk of losing real money. Importantly, action-effectiveness was subtly manipulated. In 3 experiments, we found that action-effectiveness reinforces action tendency in both risk-taking contexts. In addition, the reinforcing effect was independent of participants’ explicit knowledge regarding the action-effectiveness manipulation and their deliberate expectancy-based risk strategy. Overall, the findings strongly suggest that action-effectiveness motivates action and not risk-taking per SE Accordingly, the findings shed light on the BART suggesting that in this task, higher scores could be due to higher motivation for action and not necessarily to more risk-taking

Bisphenol A (BPA) is one of the most studied and most controversial chemicals used by the food packaging industry, because of its endocrine disruptive properties. Part of the controversy is due to the uncertainty that surrounds the effects of BPA on the endocrine system. Uncertainty includes data gaps, methodological hurdles, incompatibilities between toxicology and endocrinology-based approaches, and so on. In this article, we analyze how uncertainty has been conceptualized and treated. We focus on the European Food Safety Authority assessments of BPA, and study how exposure and hazard assessments have evolved over time, how uncertainty has been analyzed, and how the agency responded to controversies. Results show that in the attempt to reduce knowledge gaps, assessments have become progressively larger, including more references, evidence, and effects. There is a tendency toward greater precisions and specification of results, and toward protocolization of all processes included in the assessment (from literature review, to uncertainty assessments, and public consultation). Yet, the uncertainty has not diminished following the increase in evidence. We argue that the strategy used to reduce uncertainty within risk assessment, namely including more variables, studies, data, and methods, amplifies the uncertainty linked to indeterminacy (as more results increase the fragmentation of the knowledge base due to the open-ended nature of complex issues) and ambiguity (as complexity gives way to multiple nonequivalent interpretations of results). For this reason, it is important to consider different types of uncertainty and how these uncertainties interact with each other. publishedVersion

Modern tendencies of attracting resources in Ukraine in the field of international financial cooperation are investigated. The directions of cooperation between Ukraine and international financial organizations (IFIs) are considered, which will contribute to the implementation of the potential of the Ukrainian economy. Emphasis was placed on the need to improve such cooperation through the continuation of reforms in core areas, strengthening state finance management measures; improving planning, attraction , use, monitoring and control of the use of IFIs resources in order to increase the efficiency of program implementation. The strategies of cooperation of IFIs with Ukraine in terms of priority directions on the medium-term perspective are analyzed. Strategic directions defined in the study aimed at strengthening the competitiveness of the national economy on investment principles, kraising the standard of living, well-being and equivalent opportunities of citizens, supporting structural shifts through the development of high-tech promising sectors of the economy. The strategic directions identified in the study are aimed at strengthening the competitiveness of the national economy on an investment principles, raising living standards, welfare and equal opportunities for citizens, supporting structural changes through the development of high-tech promising sectors of the economy.

The legal framework for biosimilar medicinal product was first established in 2004 in the European Union and later in the USA. Since then, based on the scientific and regulatory experience with biosimilarity assessment, regulatory approaches have evolved considerably. A clear understanding of the capabilities of each development stage in assessing comparability in terms of power to identify differences and assess their relevance to the final clinical outcome gradually accumulated. In addition to the commitment to the biosimilarity approach, it is important to comply with the general requirements applicable to any drugs produced at an industrial scale. Experience showed that the demonstration of biosimilarity based on a range of analytical and functional tests and mainly clinical pharmacological studies is universal and allows extrapolating therapeutic indications. The establishment of biosimilar interchangeability, since the active substance by definition is a version of the active substance of the corresponding reference biological product, can introduce additional difficulties. A single approach to the establishment of biosimilar interchangeability has not yet been developed.

Background This article reports the steps of an educational intervention, which is designed to change livestock breeders’ preventive behavior in terms of vaccinating their livestock against brucellosis. The study has been conducted in a rural area in a country with the second highest brucellosis prevalence in the world. Methods In a quasi-experimental study and applying PRECEDE-PROCEED model, 45 livestock breeders were trained through basket method, accompanied with constructive feedback from researchers and peers and a brief interactive lecture at the end. The livestock breeders’ awareness, attitude and practice level in the intervention group was compared with those of other 45 livestock breeders in a control group, 1 and 6 months after the intervention. According to the results of the Rose Bengal tests (RBTs), as a rapid and simple screening test, the presence or absence of Brucella antibodies in the animals’ serum was investigated. Results Immediately and 1 month after the intervention, the mean scores of knowledge, awareness and practice of livestock breeders in the intervention group were significantly higher. Six months after the intervention, the results of the RBTs were positive in more livestock in the intervention group compared to the animals in the control group. The positive result of RBT after educational intervention, in livestock whose test results were negative immediately before intervention, accompanying the results of observation indicating a good general condition of livestock was considered as a probable evidence of the success of the educational intervention. Conclusion The model-driven educational intervention could significantly increase livestock breeders’ awareness, attitude and practice regarding prevention of brucellosis and vaccination of their livestock against brucellosis; however, a period of non-continuous reinforcement and gradual reduction of the number of the reinforcements by health educator workers is recommended in order to increase the maintenance of the learnt behavior. Trial registration Conducting this study was registered at Iranian Registry of Clinical Trials (IRCT20180304038945N1). Registered 24 December 2018. The proposal was registered before enrollment of the first participant.

Microbial-based cleaning products (MBCPs) have been introduced, on the market, as an alternative to traditional chemical cleaning. In addition to traditional detergents, MBCPs can perform their cleaning function, digesting the smallest particles of dirt and mitigating odours generated by environmental bacterium metabolic processes. Nevertheless, several aspects remain to be clarified and assessed, requiring further studies and new regulations to ensure safety. The particular composition of MBCPs makes it difficult to include these products in a specific class, making the European legal context incomplete and unclear. Moreover, MBCPs effects on human health are poorly documented. Exposure risks can be obtained indirectly by studies conducted in both microorganisms exposure and their metabolic products, such as enzymes, especially in workers. A further limiting factor for the accurate human health risk assessment due to MBCPs use is an incomplete indication about the MBCPs compositions. Moreover, additional factors such as host microorganisms, frequency and space of use, subject health condition, and age can determine different illness scenarios. The findings from the broad range of studies we have reviewed in this paper confirm the necessity of integrative investigation and regulation to address the use of MBCPs.

In this paper, we explore and describe what is needed to allow connected and automated vehicles (CAVs) to break traffic rules in order to minimise road safety risk and to operate with appropriate transparency (according to recommendation 4 in Bonnefon et al., European Commission, 2020). Reviewing current traffic rules with particular reference to two driving situations (speeding and mounting the pavement), we illustrate why current traffic rules are not suitable for CAVs and why making new traffic rules specifically for CAVs would be inappropriate. In defining an alternative approach to achieving safe CAV driving behaviours, we describe the use of ethical goal functions as part of hybrid AI systems, suggesting that functions should be defined by governmental bodies with input from citizens and stakeholders. Ethical goal functions for CAVs would enable developers to optimise driving behaviours for safety under conditions of uncertainty whilst allowing for differentiation of products according to brand values. Such functions can differ between regions according to preferences for safety behaviours within that region and can be updated over time, responding to continual socio-technological feedback loops. We conclude that defining ethical goal functions is an urgent and necessary step from governmental bodies to enable the safe and transparent operation of CAVs and accelerate the reduction in road casualties they promise to achieve.

Orbital congestion, contestation and competition are on the rise, and space activities are expected to align with treaties, arrangements, and guidelines elaborated at a time when the space ecosystem was simpler - and it is becoming more complex. To cope efficiently with this changing situation, at a time when space systems have become an indispensable enabler for an ever-increasing range of socio-economic activities, new rules of the road are necessary. Indeed, these should ensure the sustained stability and security of the space environment, providing norms and standards beyond transparency and confidence building measures, laying the ground for the founding elements of a space traffic coordination (management?). Hence, for us to be dependent on a reliable space-enabled information flow will require a significant decrease of their vulnerability; protection as well as “fail safe” are becoming the chief concerns. This paper will first review the current legal and regulatory provisions under which space activities take place, pointing out some limitations of the international dialogue, which is quite complex, anarchic, and with no clear global leadership, complicated by the dual use (civil and military) of space. Moreover, enforcement appears to be ineffective. It will then consider new public, as well as private, initiatives that are underway, evaluating the robustness of their foundations. Possible avenues are proposed in support of the most recent prominent initiatives, including the possibility for an international agreement on standards and behaviours, or an international civil space organisation inspired by the International Civil Aviation Organisation - ICAO. Emphasis will be placed on the urgency of bringing together these initiatives and processes under a common umbrella, or at least to achieve the convergence of a set of rules noting that international hard law provisions are far reaching. A step-by-step approach is suggested, addressing immediate, mid-term, and long-term actions to provide a stable space environment favourable to LEO large constellations, in-orbit refuelling/repairing, active debris removal, human commercial space-flight, cis-lunar/interplanetary traffic, space resources exploitation, and security/defence operations.

Background : Motivation scientists study goals, self-regulatory tools that are used to help people approach or avoid objects of desire or disdain. Purpose : Using these tools, motivation science can offer insights to guide behaviour and help individuals maintain optimal health and well-being during pandemics, including COVID-19. Results : Avoidance goals help guide behaviour away from negative objects like COVID-19, and are necessary in situations where survival is at stake. Formulating the goal of avoiding COVID-19 is therefore recommended during the pandemic. However, avoidance goals have inherent limitations, in that they tax one’s energy and well-being. To minimize these costs, the pursuit of approach sub-goals may be recommended, such as increasing social connection online or exercising outdoors (particularly prior to widespread vaccination). Conclusion : Adhering to the goal of avoiding COVID-19 prevents infection and saves lives when safe and effective vaccines and treatments are lacking. But avoidance goals have known costs that must be acknowledged and addressed. One solution is to pair avoidance goals with approach sub-goals to bolster mental and physical health while adhering to the ultimate goal of avoiding COVID-19, viral variants, and future contagions. Doi: 10.28991/SciMedJ-2021-0304-7 Full Text: PDF

Background Recently, the research on intelligent packaging is gaining momentum, primarily being driven by consumer preferences to food safety and reducing the resource waste. Freshness indicator is a kind of simple and efficient intelligent packaging technology, which can directly and scientifically indicate the freshness of food without complex operation. Freshness indicator shows great potential in the food supply chain. Scope and approach As an innovative food packaging method, freshness indicator can effectively monitor food freshness in real time without damaging food and packaging. The objective of this review is to provide relevant information on freshness indicators, such as release of food freshness indicators (carbon dioxide volatile salt-nitrogen sulfides, etc.), types (chemical chromogenic formulation, data carrier indicator, natural color formulation), safety assessment methods (toxicological assessment, exposure assessment), barriers and trends. Key findings and conclusions The potential of freshness indicators in the detection of perishable food freshness was emphasized. The applications of some freshness indicator products in food and the research demands of safety were also discussed.

PurposeThe construction industry is an industry with a high incidence of safety accidents, and the interactions of unsafe behaviors of construction workers are the main cause of accidents. The neglect of the interactions may lead to serious underestimation of safety risks. This research aims to analyze the cascading vulnerability of unsafe behaviors of construction workers from the perspective of network modeling.Design/methodology/approachAn unsafe behavior network of construction workers and a cascading vulnerability analysis model were established based on 296 actual accident cases. The cascading vulnerability of each unsafe behavior was analyzed based on the degree attack strategy.FindingsComplex network with 85 unsafe behavior nodes is established based on the collected accidents in total. The results showed that storing in improper location, does not wear a safety helmet, working with illness and working after drinking are unsafe behaviors with high cascading vulnerability. Coupling analysis revealed that differentiated management strategies of unsafe behaviors should be applied. Besides, more focus should be put on high cascading vulnerability behaviors.Originality/valueThis research proposed a method to construct the cascading failure model of unsafe behavior for individual construction workers. The key parameters of the cascading failure model of unsafe behaviors of construction workers were determined, which could provide a reference for the research of cascading failure of unsafe behaviors. Additionally, a dynamic vulnerability research framework based on complex network theory was proposed to analyze the cascading vulnerability of unsafe behaviors. The research synthesized the results of dynamic and static analysis and found the key control nodes to systematically control unsafe construction behaviors.

The construction industry is one of the sectors where accidents causing injuries among workers appear more frequently than in other industries. The safety issues are of high interest. There are special regulations introduced to protect all people engaged on a construction site. Besides the human attitude, every accident causes forced brakes in the construction process. It leads to financial losses and lowering the trademark of a certain contractor. Curing process of injured workers, as well as, investigation about for reasons of an accident generates additional cost. The development of accidents prevention then is highly desirable for several reasons. As wearable technologies become more popular and affordable, they can be applied to monitor the locations of machinery and the staff on the construction site. Based on that risky configurations can be detected, and relevant actions can be undertaken to protect working people from any injuries. Different types of wearable technologies are presented together with the discussion of their applicability in monitoring in the construction sector. Moreover, the survey is done to better recognition of health risks. Based on that the recommendations are formulated for future applications of wearable technologies as an innovative tool of risk management in construction.

Societal biosecurity – measures built into everyday society to minimize risks from pests and diseases – is an important aspect of managing epidemics and pandemics. We aimed to identify societal options for reducing the transmission and spread of respiratory viruses. We used SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) as a case study to meet the immediate need to manage the COVID-19 pandemic and eventually transition to more normal societal conditions, and to catalog options for managing similar pandemics in the future. We used a ‘solution scanning’ approach. We read the literature; consulted psychology, public health, medical, and solution scanning experts; crowd-sourced options using social media; and collated comments on a preprint. Here, we present a list of 519 possible measures to reduce SARS-CoV-2 transmission and spread. We provide a long list of options for policymakers and businesses to consider when designing biosecurity plans to combat SARS-CoV-2 and similar pathogens in the future. We also developed an online application to help with this process. We encourage testing of actions, documentation of outcomes, revisions to the current list, and the addition of further options.

Mobile crowdsensing has become an efficient paradigm for performing large-scale sensing tasks. Many quality-aware incentive mechanisms for mobile crowdsensing have been proposed. However, most of them measure the data quality by one single metric from a specific perspective. Moreover, they usually use the real-time quality, which cannot provide sufficient incentive for the workers with long-term high quality. In this paper, we refine the generalized data quality into the fine-grained ability requirement. We present a mobile crowdsensing system to achieve the fine-grained quality control, and formulate the problem of maximizing the social cost such that the fine-grained ability requirement of all sensing tasks can be satisfied. To stimulate the workers with long-term high quality, we design two ability reputation systems to assess workers’ fine-grained abilities online. The incentive mechanism based on the reverse auction and fine-grained ability reputation system is proposed. We design a greedy algorithm to select the winners and determine the payment based on the bids and fine-grained ability reputation of workers. Through both rigorous theoretical analysis and extensive simulations, we demonstrate that the proposed mechanisms achieve computational efficiency, individual rationality, truthfulness, whitewashing proof, and guaranteed approximation. Moreover, the designed mechanisms show prominent advantage in terms of social cost and average ability achievement ratio.

Abnormal or drastic changes in the natural environment may lead to unexpected events, such as tsunamis and earthquakes, which are becoming a major threat to national economy. Currently, no effective assessment approach can deduce a situation and determine the optimal response strategy when a natural disaster occurs. In this study, we propose a social evolution modeling approach and construct a deduction model for self-playing, self-learning, and self-upgrading on the basis of the idea of parallel data and reinforcement learning. The proposed approach can evaluate the impact of an event, deduce the situation, and provide optimal strategies for decision-making. Taking the breakage of a submarine cable caused by earthquake as an example, we find that the proposed modeling approach can obtain a higher reward compared with other existing methods.

International audience; Despite significant advances in oncological research, cancer nowadays remains one of the main causes of mortality and morbidity worldwide. New treatment techniques, as a rule, have limited efficacy, target only a narrow range of oncological diseases, and have limited availability to the general public due their high cost. An important goal in oncology is thus the modification of the types of antitumor therapy and their combinations, that are already introduced into clinical practice, with the goal of increasing the overall treatment efficacy. One option to achieve this goal is optimization of the schedules of drugs administration or performing other medical actions. Several factors complicate such tasks: the adverse effects of treatments on healthy cell populations, which must be kept tolerable; the emergence of drug resistance due to the intrinsic plasticity of heterogeneous cancer cell populations; the interplay between different types of therapies administered simultaneously. Mathematical modeling, in which a tumor and its microenvironment are considered as a single complex system, can address this complexity and can indicate potentially effective protocols, that would require experimental verification. In this review, we consider classical methods, current trends and future prospects in the field of mathematical modeling of tumor growth and treatment. In particular, methods of treatment optimization are discussed with several examples of specific problems related to different types of treatment.

To overcome the weak control of the problem of fragmentation and surface layering on the risk monitoring of the refinery, and to improve the safety management level in the petroleum refining proces...

Background With the growth of global imports and exports of agri-food commodities, food safety issues have received widespread attention globally. To secure public health, it is essential to develop rapid and nondestructive tools for analysis of the quality and safety of agri-food products. The emerging Raman spectroscopic techniques (RSTs) have shown noble potential on agri-foods analysis in various aspects, owing to the incomparable merits of RSTs such as fingerprint spectrum, rapid acquisition, noninvasiveness, and simple sample preparation. Scope and approach To obtain a better comprehension of employing RSTs in agri-food industry, this current review presents the fundamentals of three RSTs including spontaneous Raman spectroscopy, Raman chemical imaging, and surface-enhanced Raman spectroscopy for rapid and nondestructive analysis. Recent advances in their applications for the safety and quality control of agri-food products during the last five years are outlined. Finally, challenges and future perspectives of RSTs application are discussed in depth. Key findings and conclusions RSTs have been demonstrated as effective tools for both qualitative and quantitative analysis of agri-food products. Despite the persisting limitations resulting from technical difficulties and complexity of the food sample matrix, the continuous developments in Raman systems, nanomaterials, and spectral analysis algorithms will promote these technologies from laboratory to industry.