Complex Set Of Tasks Research Articles

Становлення мікро- та макроекономічного аналізу фінансового посередництва Стаття друга. Макроекономічний аналіз ролі фінансових посередників у роботах Б. Бернанке та застосування теорії фінансового посередництва у боротьбі з фінансовими кризами

The second of two articles which reveal the theoretical and practical significance of the researches awarded 2022 Sveriges Riksbank Prize in Economic Sciences. The author shows the theoretical and practical influence of B. Bernanke's research on the non-monetary effects of the banking crisis on the course of the Great Depression, which marked the beginning of recognition and measurement of the macroeconomic effects of financial intermediaries as institutions performing important functions under information asymmetry. The peculiarities of the global financial crisis and the latest crisis processes in the banking sector, which are taking place in the conditions of a change in the global monetary environment, are considered in light of the laureates' works. This change – a rapid tightening of monetary policy in developed economies was a reaction not only to global price shocks associated with the full-scale Russia's invasion of Ukraine, but also to the previous delay in anti-inflationary efforts in the conditions of a combination of supply shocks with monetary demand stimulation and monetary authorities' faith in well-anchored inflationary expectations. The article considers the extent to which the crisis processes at Silicon Valley Bank, Signature Bank, First Republic Bank and Credit Suisse are described by the models developed by the 2022 Nobel laureates. Based on that analysis, the author adjusts the answer to the question about the role of banking panics in the market economy. Probable directions for reforming banking regulation in the USA are characterized. It is substantiated that the government faces a complex set of tasks: to minimize social losses from banking panics; to prevent large business losses that would have broad macroeconomic consequences; and to prevent irrational contagion with panic moods and panic as a self-fulfilling prophecy, without eliminating the very possibility of depositors fleeing from a bank with poor management. It is shown that increasing and complicating the public presence in the financial sector has an extremely powerful and difficult to assess influence on the incentives of financial intermediaries, which embody the latter’s nature as special economic entities.

Environmental DNA: State-of-the-art of its application for fisheries assessment in marine environments

Fisheries management involves a broad and complex set of tasks that are necessary to prevent overfishing and to help the recovery of overfished stock. Monitoring fishing activities based on two main sources, landings data and scientific surveys, is a challenging task. Fisheries collection data is often limited, which compromises the accuracy of the results obtained. Therefore, several emerging applications of molecular methods have the potential to provide unique understanding of ecological processes in marine environments and to build stronger empirical underpinnings for the Ecosystem-Based Fisheries Management. Environmental DNA (eDNA) is a complex mixture of genetic material shed by those organisms that inhabit a given environment, whereby DNA is extracted from an environmental sample without accessing the target organism. eDNA studies can be categorized into two main approaches, i) eDNA metabarcoding or semi-targeted (community) approaches and ii) species-specific or targeted approaches (single). Although both categories are often discussed, they differ drastically in their methodology, interpretations and accuracy. Both approaches involve a series of steps that include eDNA capture, preservation, extraction and amplification. This detection will depend on the affinity to the targeted taxa sequences and completeness and accuracy of DNA reference collection databases. The eDNA method applied in marine environments are probably the most challenging aquatic environments for applying this technique. This is because of the extreme relationship between water-volume to biomass, dynamics and the physical and chemical properties of seawater that affect dispersion, dilution and preservation. Here, we review the present application of this novel method in fishery assessment in marine environments. To date, many studies suggest that this method offers the potential to revolutionize fisheries monitoring, which will contribute to improving the range of tasks involved in fisheries management. The compelling conclusion is that the methodological steps including in eDNA surveys should be standardized and that research efforts should focus on developing appropriately validated tests to address environmental and sampling factors that may affect eDNA detection in marine environments in order to draw reliable conclusions. This bioassessment tool can assist fisheries professionals in achieve their research, management, and conservation objectives, but not as a replacement for time-proven assessment methods.

Sentinel-2 Enables Nationwide Monitoring of Single Area Payment Scheme and Greening Agricultural Subsidies in Hungary

The verification and monitoring of agricultural subsidy claims requires combined evaluation of several criteria at the scale of over a million cultivation units. Sentinel-2 satellite imagery is a promising data source and paying agencies are encouraged to test their pre-operational use. Here, we present the outcome of the Hungarian agricultural subsidy monitoring pilot: our goal was to propose a solution based on open-source components and evaluate the main strengths and weaknesses for Sentinel-2 in the framework of a complex set of tasks. These include the checking of the basic cultivation of grasslands and arable land and compliance to the criteria of ecological focus areas. The processing of the satellite data was conducted based on random forest for crop classification and the detection of cultivation events was conducted based on NDVI (Normalized Differential Vegetation Index) time series analysis results. The outputs of these processes were combined in a decision tree ruleset to provide the final results. We found that crop classification provided good performance (overall accuracy 88%) for 22 vegetation classes and cultivation detection was also reliable when compared to on-screen visual interpretation. The main limitation was the size of fields, which were frequently small compared to the spatial resolution of the images: more than 4% of the parcels had to be excluded, although these represent less than 3% of the cultivated area of Hungary. Based on these results, we find that operational satellite-based monitoring is feasible for Hungary, and expect further improvements from integration with Sentinel-1 due to additional temporal resolution.

Complicity of States in Partnered Drone Operations

Abstract Military operations carried out with armed drones call into question not only the international responsibility of the drone-sending State but also the potential international responsibility for complicity of assisting States. Drone strikes are conducted through a complex set of tasks that would not be possible without the military cooperation of partner States. Three main scenarios of partnered drone operations are described, namely lending foreign military bases, providing logistical and technological support and intelligence sharing for targeting purposes. The article explores the issue of State complicity under the lens of Article 16 of the Articles on the Responsibility of States for Internationally Wrongful Acts. The core features of State complicity—the ‘significant contribution element', the ‘mental element' and the ‘opposability element'—are discussed and applied to the three scenarios. The practice of partnered drone operations is extensively analysed, focusing on the assistance provided by Italy, Germany and the Netherlands to the US drone programme. The study concludes that in the cases under consideration, the international responsibility for complicity of assisting States is likely to be entailed, should the action of the assisted State result in an internationally wrongful act.

CURRENT TRENDS IN THE DEVELOPMENT OF SERVICES IN UKRAINE

The article highlights the features and trends in the development of services in Ukraine. The structure of volumes of sold services in the context of economic activities and individual consumer groups is analyzed. It is determined that despite the socio-economic instability in the country, the level of services in Ukraine remains quite high and dynamically positive. According to the analysis of the structure of the volume of sold services by spheres of economic activity, it was found that the largest share in the total volume of sold services falls on transport services, warehousing, postal and courier activities. At the same time, it was found that out of the total volume of services provided in Ukraine, only 20% are sold to the population. It is determined that the contribution of the services sector to the formation of the country’s GDP is quite significant. The largest share in the structure of GDP is occupied by wholesale and retail trade, repair of motor vehicles and motorcycles. It is proved that maintaining the share of services at a fairly high level in the structure of GDP in recent years is primarily a consequence of its «penetration» into virtually all economic activities. It is emphasized that in the modern economic space, services are provided not only by traditional service, but also by industrial entities. However, it is determined that the production process itself is impossible without the involvement of additional resources in the form of services, including design, research, preparation of technical documentation and more. It is established that in modern conditions the service sector in Ukraine, as well as the economy as a whole, suffers significant losses. It is generalized that in order to support the development of components of the service sector, which today suffer significant losses, it is necessary to solve a set of complex tasks that play a significant role and are necessary to minimize the economic consequences of the war in Ukraine. The implementation of the proposed measures will have a positive impact on the socio-economic development of the country.

Expanding dual-task research by a triple-task

Abstract Multitasking research in the laboratory is dominated by extremely simplistic dual-task paradigms. Although dual-tasks allow for some variations, they do not compare well to more complex everyday task settings. This study expands a classical dual-task paradigm by adding a third task. The dual-tasks and the triple-task always consisted of the same three single tasks. The aim was to investigate the effects of the combinations of the three single-tasks and in which manner response times and costs increased. Stimulus-response pairings were varied either once within participants (E1) or between participants (E2). Our results showed that the increase in response time from dual-tasks to triple-tasks was only 43% of the increase from single-tasks to dual-tasks suggesting a non-linear cost of adding tasks. Moreover, response times in each subtask were higher in triple-task situations compared to single-task or dual-task situations. This is in contrast to classical dual-tasks, in which typically only one of the two responses is delayed. Cognitively, for costs in triple-tasks, unlike in dual-tasks, task coordination seems to play a larger role compared to the classically suggested relationships between stimulus and response in terms of their modality- and ideomotor-compatibility which we will discuss. Overall, the study demonstrates that current multitasking research is limited in its generalizability by focusing only on dual-tasks and would benefit from research with more complex task settings.

Psychoactive Substances and Drugs-Medicament and Narcotic

Toxicological analysis is a complex set of tasks aiming to estimate how much time has elapsed since a drug was last consumed or to inform about its chronic consumption. It is also worth paying attention to the fact of using psychoactive substances induce euphoria or increase physical energy. The use of opioids to alleviate pain is complicated by the risk of severe adverse events and the large variability in dose requirements. Pharmacogenetics could be used to adapt pain medication based on an individual’s genetic background. Many potential genetic markers related to xenobiotics metabolism have been described. Such predictors are especially of value for neonates and young children, in which case the assessment of efficacy is complicated by imprecise/poor communication. The knowledge of opioids metabolism is essential also for older patients and those with comorbidities, who receive multiple medications and may have impaired renal and hepatic function.

Neural oscillations track the maintenance and proceduralization of novel instructions

Humans are capable of flexibly converting symbolic instructions into novel behaviors. Previous evidence and theoretical models suggest that the implementation of a novel instruction requires the reformatting of its declarative content into an action-oriented code optimized for the execution of the instructed behavior. While neuroimaging research focused on identifying the brain areas involved in such a process, the temporal and electrophysiological mechanisms remain poorly understood. These mechanisms, however, can provide information about the specific cognitive processes that characterize the proceduralization of information. In the present study, we recorded EEG activity while we asked participants to either simply maintain declaratively the content of novel S-R mappings or to proactively prepare for their implementation. By means of time-frequency analyses, we isolated the oscillatory features specific to the proceduralization of instructions. Implementation of the instructed mappings elicited stronger theta activity over frontal electrodes and suppression in mu and beta activity over central electrodes. On the contrary, activity in the alpha band, which has been shown to track the attentional deployment to task-relevant items, showed no differences between tasks. Together, these results support the idea that proceduralization of information is characterized by specific component processes such as orchestrating complex task settings and configuring the motor system that are not observed when instructions are held in a declarative format.

Problems and prospects of management accounting improvement for innovation and investment activities in agricultural enterprises

The modern Russian agro-industrial facility, including its key manufacturing industry - agriculture, is characterized by a steady transition from a reproductive type of development to an innovative one aimed at labor productivity increase, an effective implementation of import substitution and exports increase state policy in respect of agro-industrial products. The competitive development of agricultural production, the need to solve a complex set of tasks immediately concerning a multiple increase of domestic agricultural product manufacture, primarily through the use of new biological assets, presupposes an exclusively innovative development of agriculture. It is clear that this situation is associated with the need to find new sources of investment, and to intensify the innovative activity of agricultural enterprises. In these conditions, it is extremely important to consider investment and innovation as a single, integral system, the success of which depends on the level of agricultural production competitiveness and sustainability. Of course, the organization of research work in this aspect requires an adequate understanding of innovations and innovative product content and role, the mechanism of innovation use during their creation.

The How Matters: How Primary Care Provider Communication With Team Relates to Patients' Disease Management.

Investigating primary care provider (PCP)-team communication can provide insight into how colleagues work together to become high-functioning teams more able to address an increasingly complex set of tasks associated with chronic disease management. To assess how PCP communication with their care team relates to patients' health. Longitudinal study of how 3 aspects of PCP-care team communication-participation, time spent listening, and uninterrupted speaking length-relate to disease management of patients with hypertension or diabetes, and the effect of these team communication behaviors on PCP-patient communication as a pathway by which this relationship might exist. We used multilevel regression models. Twenty-seven PCPs and 98 team members, and 18,067 patients with hypertension and 8354 patients with diabetes affiliated with a federally qualified health center with 12 practice sites. Primary data on communication collected using sociometric sensors worn by PCPs and team members, patient-PCP communication data collected with surveys, and patient health, PCP and patient characteristics extracted from electronic records. PCPs participated in 75% of care team conversations, spent 56% of conversation time listening, and had an average uninterrupted speaking length of 2.42 seconds. PCP participation, listening, and length of uninterrupted speaking time were associated with significantly higher odds that their patients had controlled hypertension and diabetes and improvements in disease control over time. PCP-patient communication mediates this relationship. PCP-team communication is associated with patient health management. How team members speak with one another may be as important as the content of their communication.

Mechanisms Linking Olfactory Impairment and Risk of Mortality.

Olfaction is a sense involved in a complex set of tasks, influencing eating behavior, increasing awareness of environmental hazards and affecting social communication. Surprisingly, smell disorders are very frequent, especially in the elderly population. Several recent studies conducted mostly in older subjects have demonstrated a strong association between olfactory impairment and overall mortality risk, with anosmia being even more predictive of 5 years mortality risk than cardiovascular disease. Presently, the underlying pathophysiology linking olfactory impairment to mortality remains unknown and only putative mechanisms are suggested. This review aims to examine the link between olfactory impairment and mortality and to discuss existing ideas on underlying existing mechanisms including, (1) the effect of olfactory loss on nutrition, life-threatening situations and social interactions, (2) associated neurodegenerative diseases, (3) accelerated brain aging, and (4) reflection of general health status being reflected in olfactory function.

Towards a Multimodal Model of Cognitive Workload Through Synchronous Optical Brain Imaging and Eye Tracking Measures.

Recent advances in neuroimaging technologies have rendered multimodal analysis of operators’ cognitive processes in complex task settings and environments increasingly more practical. In this exploratory study, we utilized optical brain imaging and mobile eye tracking technologies to investigate the behavioral and neurophysiological differences among expert and novice operators while they operated a human-machine interface in normal and adverse conditions. In congruence with related work, we observed that experts tended to have lower prefrontal oxygenation and exhibit gaze patterns that are better aligned with the optimal task sequence with shorter fixation durations as compared to novices. These trends reached statistical significance only in the adverse condition where the operators were prompted with an unexpected error message. Comparisons between hemodynamic and gaze measures before and after the error message indicated that experts’ neurophysiological response to the error involved a systematic increase in bilateral dorsolateral prefrontal cortex (dlPFC) activity accompanied with an increase in fixation durations, which suggests a shift in their attentional state, possibly from routine process execution to problem detection and resolution. The novices’ response was not as strong as that of experts, including a slight increase only in the left dlPFC with a decreasing trend in fixation durations, which is indicative of visual search behavior for possible cues to make sense of the unanticipated situation. A linear discriminant analysis model capitalizing on the covariance structure among hemodynamic and eye movement measures could distinguish experts from novices with 91% accuracy. Despite the small sample size, the performance of the linear discriminant analysis combining eye fixation and dorsolateral oxygenation measures before and after an unexpected event suggests that multimodal approaches may be fruitful for distinguishing novice and expert performance in similar neuroergonomic applications in the field.

Towards a real-time processing framework based on improved distributed recurrent neural network variants with fastText for social big data analytics

Big data generated by social media stands for a valuable source of information, which offers an excellent opportunity to mine valuable insights. Particularly, User-generated contents such as reviews, recommendations, and users’ behavior data are useful for supporting several marketing activities of many companies. Knowing what users are saying about the products they bought or the services they used through reviews in social media represents a key factor for making decisions. Sentiment analysis is one of the fundamental tasks in Natural Language Processing. Although deep learning for sentiment analysis has achieved great success and allowed several firms to analyze and extract relevant information from their textual data, but as the volume of data grows, a model that runs in a traditional environment cannot be effective, which implies the importance of efficient distributed deep learning models for social Big Data analytics. Besides, it is known that social media analysis is a complex process, which involves a set of complex tasks. Therefore, it is important to address the challenges and issues of social big data analytics and enhance the performance of deep learning techniques in terms of classification accuracy to obtain better decisions.In this paper, we propose an approach for sentiment analysis, which is devoted to adopting fastText with Recurrent neural network variants to represent textual data efficiently. Then, it employs the new representations to perform the classification task. Its main objective is to enhance the performance of well-known Recurrent Neural Network (RNN) variants in terms of classification accuracy and handle large scale data. In addition, we propose a distributed intelligent system for real-time social big data analytics. It is designed to ingest, store, process, index, and visualize the huge amount of information in real-time. The proposed system adopts distributed machine learning with our proposed method for enhancing decision-making processes. Extensive experiments conducted on two benchmark data sets demonstrate that our proposal for sentiment analysis outperforms well-known distributed recurrent neural network variants (i.e., Long Short-Term Memory (LSTM), Bidirectional Long Short-Term Memory (BiLSTM), and Gated Recurrent Unit (GRU)). Specifically, we tested the efficiency of our approach using the three different deep learning models. The results show that our proposed approach is able to enhance the performance of the three models. The current work can provide several benefits for researchers and practitioners who want to collect, handle, analyze and visualize several sources of information in real-time. Also, it can contribute to a better understanding of public opinion and user behaviors using our proposed system with the improved variants of the most powerful distributed deep learning and machine learning algorithms. Furthermore, it is able to increase the classification accuracy of several existing works based on RNN models for sentiment analysis.

Edge analytics for anomaly detection in water networks by an Arduino101-LoRa based WSN

This paper presents a novel distributed data analytic architecture, and corresponding algorithms that apply to infrastructure anomaly detection. The proposed method mainly focuses on smart water networks, demonstrating that the highest possible sensor rate analytic performs at on-edge nodes without requiring the whole date to send back to the server. This approach saves communication costs and lengthens the lifetime of the battery-powered nodes. A complex set of tasks is developed on a single-core Intel Curie processor, Arduino101 and the raw sensor data is compressed using a customized Lempel–Ziv compression algorithm tailored to resource-constrained embedded systems. The compression rate figures are then analyzed but only the compressed data which is associated with the anomalous condition is sent back to the server by means of a LoRa platform. The developed system is evaluated experimentally and the results verify the high resource utilization.

The making and unmaking of teams

Contemporary expert organizations rely heavily on cross-border, often temporary teams typically working through virtual means of communication. While static aspects of teams are well researched, there have been considerably fewer studies on team dynamics and team processes. Existing process studies tend to take a cautious, entity-based approach, emphasizing team structure as much as (or even more than) processual aspects. This article represents a shift from studying teams as entities and structures changing over time to studying teams as an on-going process. Participants engage in teaming and thus in the continued making and sometimes unmaking of teams. We report on a study of three anatomically similar, self-managed teams performing the same set of complex tasks with radically different teaming processes. With more or less successful shared sensemaking, the team members collectively create (or fail to create) not only team task outputs but also the team itself.

Microdevice Platform for Continuous Measurement of Contractility, Beating Rate, and Beating Rhythm of Human-Induced Pluripotent Stem Cell-Cardiomyocytes inside a Controlled Incubator Environment.

The heart completes a complex set of tasks, including the initiation or propagation of an electrical signal with regularity (proper heart rate and rhythm) and generating sufficient force of contraction (contractility). Probing mechanisms of heart diseases and quantifying drug efficacies demand a platform that is capable of continuous operation inside a cell incubator for long-term measurement of cardiomyocyte (CM) monolayers. Here, we report a microdevice array that is capable of performing continuous, long-term (14 days) measurement of contractility, beating rate, and beating rhythm in a monolayer of human-induced pluripotent stem cell-CMs (hiPSC-CMs). The device consists of a deformable membrane with embedded carbon nanotube (CNT)-based strain sensors. Contraction of the hiPSC-CMs seeded on the membrane induces electrical resistance change of the CNT strain sensor. Continuously reading the sensor signals revealed that hiPSC-CMs started to beat from day 2 and plateaued on day 5. Average contractile stress generated by a monolayer of hiPSC-CMs was determined to be 2.34 ± 0.041 kPa with a beating rate of 1.17 ± 0.068 Hz. The device arrays were also used to perform comprehensive measurement of the beating rate, rhythm, and contractility of the hiPSC-CMs and quantify the cell responses to different concentrations of agonists and antagonists, which altered the average contractile stress to the range of 1.15 ± 0.13 to 3.96 ± 0.53 kPa. The continuous measurement capability of the device arrays also enabled the generation of Poincaré plots for revealing subtle changes in the beating rhythm of hiPSC-CMs under different drug treatments.

Lessons learned from the Canadian cancer registry experience.

Health leaders and caregivers are focused on evidence-based data to drive care delivery and practice. Ensuring the health system is functioning effectively and efficiently and that patient outcomes are reaching expected targets are topics that permeate conversations at the local, provincial, and national levels. However, as many leaders have come to understand in recent years, healthcare data collection and producing meaningful, high-quality metrics is a complex set of tasks, requiring its own level of attention and dedicated resources. In the healthcare data realm, there are opportunities to learn from experience. One of these opportunities is the population-based cancer registry, which is one of the oldest examples of standardized data collection in the Canadian health system.

Supporting Environmental Compliance Managers by Ticket Systems - An Industry Survey, Deployment Options and a Reference Business Process

Corporate environmental compliance managers are required to perform and supervise a set of complex tasks. It can be expected that the growing density of environmental regulations will contribute to even more challenges for compliance managers in the near future. As a result, companies are increasingly pressured to improve the efficiency of their compliance management processes by the use of automation approaches. For some specific compliance management processes it is expected that a partial process automation can be obtained through the use of a ticket system. However, so far only little is known about the general usage options and benefits of ticket systems for environmental compliance management. Given this gap, the article contains a corresponding demonstration and evaluation study. A reference process model for environmental compliance management and an industry survey of the top software capabilities desired by compliance managers serves as foundation for this study. The process automation options based on a ticket system are exemplified through a reference process for the new regulation management process. The process specification is given in the popular standardized graphical notation called “Business Process Model and Notation” (BPMN).

The disruptive effects of pain on multitasking in a virtual errands task

Background and aimsPain is known to have a disruptive effect on cognitive performance, but prior studies have used highly constrained laboratory tasks that lack ecological validity. In everyday life people are required to complete more complex sets of tasks, prioritising task completion and recalling lists of tasks which need to be completed, and these tasks continue to be attempted during episodes or states of pain. The present study therefore examined the impact of thermal induced pain on a simulated errand task. MethodsFifty-five healthy adults (36 female) performed the Edinburgh Virtual Errands Task (EVET) either during a painful thermal sensation or with no concurrent pain. Participants also completed the Experience of Cognitive Intrusion of Pain (ECIP) questionnaire to measure their self-reported cognitive impact of pain in general life. ResultsParticipants who completed the EVET task in pain and who self-reported high intrusion of pain made significantly more errors than those who reported lower intrusion on the ECIP. ConclusionsFindings here support the growing literature that suggests that pain has a significant impact on cognitive performance. Furthermore, these findings support the developing literature suggesting that this relationship is complex when considering real world cognition, and that self-report on the ECIP relates well to performance on a task designed to reflect the complexities of everyday living. ImplicationsIf extrapolated to chronic pain populations, these data suggest that pain during complex multitasking performance may have a significant impact on the number of errors made. For people highly vulnerable to cognitive intrusion by pain, this may result in errors such as selecting the wrong location or item to perform tasks, or forgetting to perform these tasks at the correct time. If these findings are shown to extend to chronic pain populations then occupational support to manage complex task performance, using for example diaries/electronic reminders, may help to improve everyday abilities.

Project management tools-integration with other tools of the organization

IN response to some of the recent articles on Project Management, I was asked to prepare some articles about project management tools. In fact, this could be quite a lengthy set of articles, since there are so very many tools available to enable effective project management. We will address but a few of them. The tools might be templates and forms, which can be used to help project managers manage with consistency across projects. They will include procedures to ensure that activities are performed consistently with all the needed information, checks and balances. And of course, tools will include software applications and programs which help the project managers to plan and track the complex set of tasks and deliverables, with budget and timing for each and for the overall project.