Methodological Status of the Concept of World Picture and its Philosophical Origins

The world picture in a literary text is created by linguistic means, while it reflects the individual picture of the world in the mind of the writer and is embodied in the selection of elements of the content of the work of art; the selection of the language means used; in the individual use of figurative means. The artistic picture of the world is a secondary, mediated the world picture, and it is mediated twice - by language and individually - by the author's conceptual picture of the world. Keywords: artistic reality, worldview, methodological characteristics, reality, linguistic approach.

Digital Supply Chain Twins—Conceptual Clarification, Use Cases and Benefits

Background: Digital supply chain twins (DSCT) are gaining increased attention in academia and practice as they emerge as one of the most important trends in logistics and supply chain management (LSCM). Still, there seems to be no common understanding of the term in scientific literature. Moreover, the broad field of LSCM allows for a multitude of feasible application areas and use cases, yet there exists no conclusive list of them as to date. Methods: This study builds upon a systematic literature review of 66 DSCT articles to identify application areas of DSCT in LSCM as well as specific use cases and their respective intended benefits. Results: To start with, the study derives a unified definition of DSCTs, including possible scopes of applications. Afterwards, five application areas of DSCT in LSCM are synthesized as well as 14 individual use cases and their respective intended benefits. Conclusions: The study leads towards a conceptual clarification of DSCT that is of importance for research and practice alike. For managers it additionally provides up-to-date use cases to guide DSCT applications in practice.

Individual Use of Smartwatches with Self-Monitoring EKG Functionality for Diagnosing Arrhythmias: A Scoping Review (Preprint)

BACKGROUND cardiovascular diseases (CVDs) have become prevalent in the world. They cause millions of deaths globally with the World Health Organization putting the figure at 17.9 million people every year. These statistics indicate the need for healthcare systems to leverage contemporary advanced technology to detect and diagnose CVDs and provide appropriate and timely care to reduce mortality rates. OBJECTIVE To conduct a scoping review exploring individual use of smartwatches with self-monitoring ECG functionality for diagnosing arrhythmias. METHODS Source were selected from six credible bibliographic databases: PubMed, Medline, EMBASE, PsycInfo, CINAHL, and Google Scholar. Intervention-related terms were used to identify relevant sources. Additionally, a forward search strategy was used to search the databases and identify appropriate peer-reviewed journals. RESULTS The research returned 230 sources, out of which 40 met the inclusion criterion. The studies revealed that increased research, development, and adoption of smartwatches and other wearable devices have intensified in the past two decades. The studies showed that using smartwatches can detect cardiac arrhythmias although this depends on the algorithms and biometric sensors utilized in the smartwatches. Watches with advanced algorithms, PPG, and EKG functionalities exhibit high accuracy, sensitivity, and specificity, detecting AFib and other arrhythmias with high efficacy. Therefore, the best way for technology companies to improve their watches’ accuracy is to design and use advanced algorithms and combine PPG, EKG, activity, and biochemical sensors. Conclusion: The contemporary healthcare space is replete with wearable and non-wearable ¬systems and devices central to detecting health conditions and informing the relevant stakeholders to take corrective actions. Smartwatches are wearable devices used chiefly by patients, health, and fitness enthusiasts to detect and monitor a series of conditions, such as heart rate. Their use has fostered timely detection of cardiac arrhythmias, and therefore, caregivers and policy-makers should emphasize their use. CONCLUSIONS Technological systems have proliferated many human spaces in the last three decades, including education, healthcare, and entertainment. Their use has improved operational efficiency, reduced costs, saved lives, and increased organizations’ bottom lines. Healthcare systems use technological devices and appliances to diagnose patients, perform surgeries, improve pharmacy operations, and reduce medical errors. That way, most healthcare facilities provide quality care, attaining positive clinical outcomes. The contemporary healthcare space is replete with wearable and non-wearable ¬systems and devices central to detecting health conditions and informing the relevant stakeholders – caregivers, patients, and family members – to take corrective actions. Smartwatches are wearable devices used chiefly by patients, health, and fitness enthusiasts to detect and monitor a series of conditions, such as heart rate. They are highly effective in detecting cardiac arrhythmias, and therefore, caregivers and policy-makers should emphasize their use.

Archetypes of Digital Twins

Currently, Digital Twins receive considerable attention from practitioners and in research. A Digital Twin describes a concept that connects physical and virtual objects through a data linkage. However, Digital Twins are highly dependent on their individual use case, which leads to a plethora of Digital Twin configurations. Based on a thorough literature analysis and two interview series with experts from various electrical and mechanical engineering companies, this paper proposes a set of archetypes of Digital Twins for individual use cases. It delimits the Digital Twins from related concepts, e.g., Digital Threads. The paper delivers profound insights into the domain of Digital Twins and, thus, helps the reader to identify the different archetypical patterns.

Network medicine for disease module identification and drug repurposing with the NeDRex platform

Traditional drug discovery faces a severe efficacy crisis. Repurposing of registered drugs provides an alternative with lower costs and faster drug development timelines. However, the data necessary for the identification of disease modules, i.e. pathways and sub-networks describing the mechanisms of complex diseases which contain potential drug targets, are scattered across independent databases. Moreover, existing studies are limited to predictions for specific diseases or non-translational algorithmic approaches. There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. We close this gap with NeDRex, an integrative and interactive platform for network-based drug repurposing and disease module discovery. NeDRex integrates ten different data sources covering genes, drugs, drug targets, disease annotations, and their relationships. NeDRex allows for constructing heterogeneous biological networks, mining them for disease modules, prioritizing drugs targeting disease mechanisms, and statistical validation. We demonstrate the utility of NeDRex in five specific use-cases.

REMOTE REHABILITATION: ROLE AND OPPORTUNITIES

Medical rehabilitation is a complex, long-term and financially costly process of restoring the physiological functions of the body after injuries and the consequences of past diseases. The need for an individual approach to each life situation necessitates the search and development of new technologies in the method of providing rehabilitation assistance. One of the principles of a successful rehabilitation process is continuity, which, in most cases, is disrupted after the transfer of patients to the outpatient stage. The 21st century, in contrast to the previous one, is distinguished by more accessible technologies for everyday and individual use. A separate category of patients are patients with the consequences of brain damage, socialization and the return of the ability to self-serve for whom is one of the most difficult in rehabilitation practice. One of these technologies is distance rehabilitation, which provides the principle of continuity, social and informational support for relatives who provide care for patients on an outpatient basis.

Synergetic Effect of Organic Flocculant and Montmorillonite Clay on the Removal of nano-CuO by Coagulation-Flocculation-Sedimentation Process

The widespread usage of nano-copper oxide particles (nano-CuO) in several industrial products and applications raises concerns about their release into water bodies. Thus, their elimination from drinking water is essential to reduce the risk to human health. This work investigated the removal of nano-CuO from pure water and montmorillonite clay (MC) suspensions using poly aluminum ferric chloride (PAFC) as well as cationic polyacrylamide (PAM) by the coagulation-flocculation-sedimentation (C/F/S) process. Moreover, the PAFC and PAFC/PAM flocculation performance for various nano-CuO particles concentrations, dosages, pH, settling times and stirring speeds were also investigated. The findings showed that the removal of nano-CuO and turbidity in MC suspension were higher as compared to pure water. Moreover, the combined effect of PAFC/PAM on the elimination of nano-CuO and turbidity was also substantially better than the individual use of PAFC or PAM. The efficient removal of CuO was observed in the solution containing higher mass concentration in the order (10 mg/L > 2.5 mg/L > 1 mg/L) with an increased coagulant dose. The improved removal performance of nano-CuO was observed in a pH range of 7–11 under various water matrices. The C/F/S conditions of nano-CuO were further optimized by the Box–Behnken statistical experiment design and response surface methodology. The PAFC/PAM dose resulted in the maximum removal of nano-CuO (10 mg/L) in both pure water (>97%) and MC suspension (>99%). The results of particle monitoring and Fourier transform infrared of composite flocs revealed that the main removal mechanism of nano-CuO may be the combined effect of neutralization, complexation as well as adsorption.

Using Reinforcement Learning in the Path Planning of Swarms of UAVs for the Photographic Capture of Terrains

The number of applications using unmanned aerial vehicles (UAVs) is increasing. The use of UAVs in swarms makes many operators see more advantages than the individual use of UAVs, thus reducing operational time and costs. The main objective of this work is to design a system that, using Reinforcement Learning (RL) and Artificial Neural Networks (ANNs) techniques, can obtain a good path for each UAV in the swarm and distribute the flight environment in such a way that the combination of the captured images is as simple as possible. To determine whether it is better to use a global ANN or multiple local ANNs, experiments have been done over the same map and with different numbers of UAVs at different altitudes. The results are measured based on the time taken to find a solution. The results show that the system works with any number of UAVs if the map is correctly partitioned. On the other hand, using local ANNs seems to be the option that can find solutions faster, ensuring better trajectories than using a single global network. There is no need to use additional map information other than the current state of the environment, like targets or distance maps.

Speeding up to keep up: exploring the use of AI in the research process

There is a long history of the science of intelligent machines and its potential to provide scientific insights have been debated since the dawn of AI. In particular, there is renewed interest in the role of AI in research and research policy as an enabler of new methods, processes, management and evaluation which is still relatively under-explored. This empirical paper explores interviews with leading scholars on the potential impact of AI on research practice and culture through deductive, thematic analysis to show the issues affecting academics and universities today. Our interviewees identify positive and negative consequences for research and researchers with respect to collective and individual use. AI is perceived as helpful with respect to information gathering and other narrow tasks, and in support of impact and interdisciplinarity. However, using AI as a way of ‘speeding up—to keep up’ with bureaucratic and metricised processes, may proliferate negative aspects of academic culture in that the expansion of AI in research should assist and not replace human creativity. Research into the future role of AI in the research process needs to go further to address these challenges, and ask fundamental questions about how AI might assist in providing new tools able to question the values and principles driving institutions and research processes. We argue that to do this an explicit movement of meta-research on the role of AI in research should consider the effects for research and researcher creativity. Anticipatory approaches and engagement of diverse and critical voices at policy level and across disciplines should also be considered.