Field Of Science Research Articles

The Tropic-Concepts of Life: Jacques Derrida’s Contribution to the Question of Metaphor in the Life Sciences

In the field of life science there is a growing awareness of the metaphorical tenor of many of its key concepts and the problems that arise from them, as in the now-controversial case of the genetic ‘program’. In the seminar Life Death (2019) Derrida addresses this question from Georges Canguilhem’s difficulties in establishing a clear distinction between metaphor and concept, precisely with regard to the notion of ‘program’, concluding that this difficulty ‘demand[s] a recasting of this division and of the law of this division’ between metaphor and concept. Beginning with these pages from Life Death, the present essay aims to reconstruct the deconstruction of this opposition and its epistemological consequences by going back to the Derridean essay ‘White Mythology’ (1971), to which Derrida refers in the seminar and in which the question of metaphor in the life sciences had been addressed in a critical confrontation with Bachelard and Canguilhem.

Modern Pain Science and Alexander Technique: How Might Alexander Technique Reduce Pain?

This article brings together research from the fields of pain science and Alexander Technique (AT) to investigate the mechanisms by which AT helps reduce pain. AT is a cognitive embodiment practice and a method for intentionally altering habitual postural behavior. Studies show that AT helps with various kinds of pain, although the mechanisms of pain reduction are currently not well understood. Advances in pain science may give insight into how this occurs. Modern interventions with efficacy for improving pain and function are consistent with active approaches within kinesiology. They also share similarities with AT and may have common mechanisms such as learning, mind–body engagement, normalization of sensorimotor function, improvement of psychological factors, and self-efficacy, as well as nonspecific treatment effects. AT likely has additional unique mechanisms, including normalization of muscle tone, neuronal excitability, and tissue loading, as well as alterations to body schema, attention redirection, and reduction in overall reactivity.

Implementing a Hospital-Acquired Pressure Injury Prevention Bundle in Critical Care.

The emerging field of implementation science (IS) facilitates the sustainment of evidence-based practice in clinical care. This article, the third in a series on applying IS, describes how a nurse-led team at a multisite health system used IS concepts, methods, and tools to implement a hospital-acquired pressure injury (HAPI) prevention bundle on six critical care units, with the aim of decreasing HAPI incidence.

Upwind block-centered multistep differences for semiconductor device problem with heat and magnetic influences

In this paper, a mathematical model of semiconductor device with two important factors is discussed. Heat and magnetic influences are considered together. Its numerical approximation is important in information science and other technological innovation fields. The major physical unknowns (the potential, electron concentration, hole concentration, and the heat) are defined by four nonlinear PDEs: an elliptic equation, two convection-diffusion equations and a heat conductor equation. A conservative block-centered method is used to approximate the elliptic equation. The derivatives to time t, ∂∂t(⋅), are discretized by multistep differences for improving the computational accuracy. The diffusions and convection terms are treated by block-centered differences and upwind approximations, respectively. This composite numerical method is suitable for this nonlinear system. Firstly, numerical dispersion and nonphysical oscillations are avoided. Secondly, the unknowns and their adjoint vectors are obtained simultaneously. Thirdly, the law of conservation is preserved. An error estimates is derived. Finally, simple examples are given for showing the efficiency and accuracy.

A Comprehensive Review on Imperative Role of Ionic Liquids in Pharmaceutical Sciences.

Ionic liquids (ILs) are poorly-coordinated ionic salts that can exist as a liquid at room temperatures (or <100 °C). ILs are also referred to as "designer solvents" because so many of them have been created to solve particular synthetic issues. ILs are regarded as "green solvents" because they have several distinctive qualities, including better ionic conduction, recyclability, improved solvation ability, low volatility, and thermal stability. These have been at the forefront of the most innovative fields of science and technology during the past few years. ILs may be employed in new drug formulation development and drug design in the field of pharmacy for various functions such as improvement of solubility, targeted drug delivery, stabilizer, permeability enhancer, or improvement of bioavailability in the development of pharmaceutical or vaccine dosage formulations. Ionic liquids have become a key component in various areas such as synthetic and catalytic chemistry, extraction, analytics, biotechnology, etc., due to their superior abilities along with highly modifiable potential. This study concentrates on the usage of ILs in various pharmaceutical applications enlisting their numerous purposes from the delivery of drugs to pharmaceutical synthesis. To better comprehend cuttingedge technologies in IL-based drug delivery systems, highly focused mechanistic studies regarding the synthesis/preparation of ILs and their biocompatibility along with the ecotoxicological and biological effects need to be studied. The use of IL techniques can address key issues regarding pharmaceutical preparations such as lower solubility and bioavailability which plays a key role in the lack of effectiveness of significant commercially available drugs.

Nanotechnology and Nanostructures in Food Science: Advancements &amp; Applications

Nanotechnology is a field of science that deals with materials at a nano-scale i.e. within the range of 1 to 100 nano meters. Nanotechnology and nanostructures are revolutionizing food science by providing an innovative, effective, and sustainable approach. Nanotechnology is the science of materials which are extremely small, typically ranging from 1-100 nanometers, which finds various applications in diverse fields including but not limited to food science. Different industries like food industry, dairy industry, fruits &amp; vegetables industry, and wine industry would benefit by implementing and integrating nanotechnology. The advancements and applications of nanotechnology and nanostructures in food science have not been explored thoroughly and require a lot more research. However, public concern about the safety of nanomaterials, toxicological aspect of nanomaterials, and food safety concerns still remains a hot topic for further research. This article provides a brief overview of the applications and advancements of nanotechnology in food science.

PicPatrolling: Smart Surveillance with ESP32CAM

Robotics is an exciting and developing branch of science. Robots are now common in society because of their high efficiency and durability, and they have many users. Security and surveillance robots, especially those with wheeled movements and agility, are important for multiplexes in security and surveillance domains, including public security, military, facilities, and home security. These robots carry built-in high-end sensors, cameras, and communication equipment that simplify real-time data collection in indoor and outdoor environments. "PicPatrolling: Smart Surveillance with ESP32CAM” is a technique that attempts to improve the current concept of security and surveillance. The proposed system incorporates ESP32CAM for image capture and transmission without delay and GPS for location tracking. The system includes sending photo e-mail alerts, making immediate reports, and guaranteeing adequate area coverage. The robot can move during operation in a complex environment using computer vision, machine learning, and sensor fusion to recognize objects, faces, and changes and monitor important regions.. Application areas for surveillance robots include commercial and populated regions, transport points and architectural structures, other soft regions that people cannot access, and other dangerous areas that humans cannot monitor for various reasons.

Investigating the impact of nano copper on the electrical conductivity of aluminum: A comprehensive study utilizing ANN, genetic algorithm, and fuzzy logic methods

Nanotechnology has emerged as a transformative field in material science, offering unprecedented opportunities to enhance the electrical properties of conventional materials through the incorporation of nano-sized particles. In this extensive study, we explore the effects of varying weight percentages (1%, 2%, and 3%) and lengths (30 nm, 60 nm, 150 nm, and 250 nm) of nano copper on the electrical conductivity of aluminum (Al) across different temperatures (20°C, 50°C, and 100°C). Additionally, we compare the predictive capabilities of Artificial Neural Networks (ANN), Genetic Algorithms (GA), and Fuzzy Logic (FL) methods in forecasting the electrical conductivity variations of Al based on these parameters.

Investigating the impact of nano copper on the electrical conductivity of aluminum: A comprehensive study utilizing artificial neural networks

Nanotechnology has emerged as a transformative field in material science, offering unprecedented opportunities to enhance the electrical properties of conventional materials through the incorporation of nano-sized particles. In this extensive study, we explore the effects of varying weight percentages (1%, 2%, and 3%) and lengths (30 nm, 60 nm, 150 nm, and 250 nm) of nano copper on the electrical conductivity of aluminum (Al) across different temperatures (20°C, 50°C, and 100°C). Additionally, we investigate the predictive capabilities of Artificial Neural Networks (ANN) in forecasting the electrical conductivity variations of Al based on these parameters. Through a detailed analysis of experimental results and ANN modeling,

A Comprehensive Study of Datasets for Research Works in IoT Networks

Internet of Things is a trending subject in the field of Computer Science and Information Technology. When a research scholar tries to find a problem statement in the arena of IoT, he or she probably Google the phrase “Security Issues in Internet of Things”. On this day August 22, 2024, when we searched the Google with this phrase, we got about 48,40,00,000 results in 0.46 seconds. When we searched Google Scholar with the same phrase, we got about 40,70,000 results (0.52 sec). This shows that lakhs of researchers are toiling to find solutions for Security Issues in IoT. There is a new and trending way of research that is finding solutions for issues in IoT using Machine Learning and Deep Learning Models. ML and DL algorithms need large sets of Data to train and test the algorithms. This made us to take up a study on available Datasets for this research topic. When we made review of literature, in this arena of study, we found that researchers are working on only a few datasets, though numerous datasets are available freely on the internet for academic purposes. Hence in this paper we made a comprehensive study of Datasets available for research works in Internet of Things.

Investigating the impact of nano copper on the electrical conductivity of aluminum: a comprehensive study utilizing genetic algorithms methods

Nanotechnology has emerged as a transformative field in material science, offering unprecedented opportunities to enhance the electrical properties of conventional materials through the incorporation of nano-sized particles. In this extensive study, we explore the effects of varying weight percentages (1%, 2%, and 3%) and lengths (30 nm, 60 nm, 150 nm, and 250 nm) of nano copper on the electrical conductivity of aluminum (Al) across different temperatures (20°C, 50°C, 80°C, and 100°C). Additionally, GA method and Numerical correction factor and constitutive equation using Zener –Holloman parameter were employed for modeling the rheological behavior of Al based on these parameters.

Investigating the impact of nano copper on the electrical conductivity of aluminum: A comprehensive study utilizing fuzzy logic methods

Nanotechnology has emerged as a transformative field in material science, offering unprecedented opportunities to enhance the electrical properties of conventional materials through the incorporation of nano-sized particles. In this extensive study, we explore the effects of varying weight percentages (1%, 2%, and 3%) and lengths (30 nm, 60 nm, 150 nm, and 250 nm) of nano copper on the electrical conductivity of aluminum (Al) across different temperatures (20°C, 50°C, and 100°C). Additionally, we investigate the predictive capabilities of fuzzy logic methods in forecasting the electrical conductivity variations of Al based on these parameters.

An efficient fourth-order convergent scheme based on half-step spline function for two-point mixed boundary value problems

The present work aims to introduce a novel numerical method for solving second-order two-point mixed boundary value problems. Mixed boundary value problems occur in various scientific fields, including quantum mechanics, fluid dynamics, and chemical reactor theory. The proposed method provides a highly accurate, fourth-order convergent numerical solution, achieved by implementing a compact finite difference method based on non-polynomial spline in tension approximations. Notably, the discretisation involves the use of half-step grid points, eliminating the need to modify the method at singularities while dealing with singular boundary value problems. The article also includes a comprehensive convergence analysis that demonstrates the theoretical order of convergence of the method. Additionally, the results obtained from solving six diverse mixed boundary value problems, including Burger's equation and Bratu-type equation, are compared to showcase the superiority and effectiveness of the proposed method.

Deep Learning and Human-machine Integration in Smart Prosthetic Control: Process and Perspectives

With the rapid development of science and technology and the maturity of deep learning technology, intelligent prosthetic limb control has made significant progress in human-machine integration. While traditional prosthetic technology has seen improvements in form and function, it still faces challenges in user experience and physiological adaptability. Deep learning, with its powerful pattern recognition and decision-making capabilities, offers new possibilities to address these issues. This paper reviews the current status and future development of the application of deep learning in intelligent prosthetic limb control, emphasizing its close relationship with the concept of human-machine integration. Intelligent prosthetic control involves not only mechanical engineering and bioengineering, but also interdisciplinary integration of the fields of neural engineering, electrical engineering, motion control and computer science. This paper reviews the limitations in traditional prosthetic technology, such as accuracy and user adaptability, introduces the successful cases and latest research results of deep learning in the medical field, and explores the potential of deep reinforcement learning in optimizing complex movements and adapting to different environments. Finally, the future direction of deep learning technology in smart prosthetic limb control is envisioned, and research challenges and recommendations are presented in the hope of providing theoretical support for the innovative development of smart prosthetic limb technology and improving the quality of life of people with disabilities.

Bifurcation analysis, phase portraits and optical soliton solutions of the perturbed temporal evolution equation in optical fibers

The perturbed nonlinear Schrödinger equation plays a crucial role in various scientific and technological fields. This equation, an extension of the classical nonlinear Schrödinger equation, incorporates perturbative effects that are essential for modeling real-world phenomena more accurately. In this paper, we investigate the traveling wave solutions of the perturbed nonlinear Schrödinger equation using the bifurcation theory of dynamical systems. Graphical presentations of the phase portrait are provided, revealing the traveling wave solutions under various conditions. By employing the auxiliary equation method, we derive a variety of solutions including periodic, dark, singular and bright optical solitons. To provide comprehensive and clearer depiction of the model’s behavior 2D, contour and 3D graphical representations are offered. We also highlight specific constraint conditions that ensure the presence of these obtained solutions. This study expands the scope of known exact solutions and their stability qualities which is offering an extensive analytical technique which enhances previous research. The novelty of our research lies in its examination of bifurcation analysis and the auxiliary equation method within the context of a perturbed nonlinear Schrödinger wave equation for the first time. By integrating these two perspectives, this paper contributes to establishing the complex dynamics and stability characteristics of soliton solutions under perturbations.

Characterizing and communicating uncertainty: lessons from NASA’s Carbon Monitoring System

Abstract Navigating uncertainty is a critical challenge in all fields of science, especially when translating knowledge into real-world policies or management decisions. However, the wide variance in concepts and definitions of uncertainty across scientific fields hinders effective communication. As a microcosm of diverse fields within Earth Science, NASA’s Carbon Monitoring System (CMS) provides a useful crucible in which to identify cross-cutting concepts of uncertainty. The CMS convened the Uncertainty Working Group (UWG), a group of specialists across disciplines to evaluate and synthesize efforts to characterize uncertainty in CMS projects. This paper represents efforts by the UWG to build a heuristic framework designed to evaluate data products and communicate uncertainty to both scientific and non-scientific end users. We consider four pillars of uncertainty: addressing its origins, severity, stochasticity versus incomplete knowledge, and spatial and temporal autocorrelation. Using a common vocabulary and a generalized workflow, the framework introduces a graphical heuristic accompanied by a narrative, exemplified through contrasting case studies. Envisioned as a versatile tool, this framework provides clarity in reporting uncertainty, guiding users and tempering expectations. Beyond CMS, it stands as a simple yet powerful means to communicate uncertainty across diverse scientific communities.

Filsafat Materialisme Karl Marx (Epistimologi Dialectical And Historical Materiali)

With the premise that the production and distribution of products and services is vital to aid people in growing their life, this article examines Karl Marx's historical materialism and its methodology. Economic considerations serve as the foundation of human existence, while the concrete problems of human awareness in the fields of science, philosophy, ideology, and religion serve as the superstructure, according to him. According to Marx, society's superstructure is defined by its economic foundation. Marx argued that the struggle between social classes was the driving force behind all major historical shifts. Marx posits a social hierarchy in which the capitalist bourgeoisie and the working class proletariat are the two main social groups. Thus, rather than people, social class is a product of historical development that dictates how events unfold. A class revolution is inevitable given the presence of these two social strata. Religion is the opium of the masses, according to Marx; the more one devotes oneself to religion, the more lost he will become. Religion does not create man, but rather, Marx argues that humans create religion.

4.K. Scientific session: The realm of the information ecosystem and its public health impact

Abstract Workshop background As a field of science, study, practice, and policy, infodemic management has emerged during the Covid-19 pandemic but has since been emancipated and can be translated to any topic where information ecosystems play a vital role. In particular relevant to public health, infodemic managers have grown in the ranks of institutes of public health, academic institutions, UN agencies and civil society organizations, tackling outbreaks and public health issues as wide as mpox, Marburg, teen mental health, chronic diseases, seasonal influenza, Ebola and routine immunization. Aiming at improving public health strategies, they are responsible for exploring and investigating personal and organizational (health) information ecosystem, generating evidence, identifying patterns of communication and information flow, tackling the onset and distribution of circulating mis- and disinformation, better understanding information voids, and respond to citizen needs concerning information demands around emergencies. In this workshop, we will focus on several common challenges associated with implementing whole-of-society interventions and strategies for resilience to health misinformation. Solving these challenges, which often are too big just for the health system to solve, will sometimes require creativity, out-of-the-box thinking as well as cross-disciplinary perspectives and new partnerships. Infodemics are also a global challenge that can easily cross borders, which is why country-to-country discussions of experiences by participants is encouraged-while no previous infodemic management experience is required. Workshop objectives The workshop will be organized as a research symposium with five speakers from infodemic management, health information, and health literacy. They will provide a solid introduction to infodemic management from different perspectives and angles. (i) The first presentation will introduce a study on health information seeking and health literacy in midwife-led care and the modern information environment. (ii) The second presentation will discuss how fact-checking organizations can partner within public health for a healthier internet. (iii) The third presentation will focus on unravelling misinformation by investigating the associations between health literacy and resilience. (iv) The fourth presentation will present a novel web-platform for credible health information and tackling misinformation. (v) The fifth presentation focuses on the impact of misinformation on social media in the context of natural disasters. The format of this workshop will be 5x8-minute presentations, including Q&amp;A with the audiences, followed by a 20-minute panel discussion, reflecting the relevance of the results to public health research, practice and policy. Key messages • Infodemic management seeks to quickly understand the public’s information and health needs improve future public health responses, especially during emergencies. • Whole-of-society approaches are needed to address and mitigate harms caused by infodemics by developing closer partnerships and understanding between health systems and the public.

Attitudes, fears and experiences of medical scientists towards using AI tools in their work routine

Abstract Background Artificial intelligence (AI) has experienced an explosive growth in the healthcare sector and the scientific field. Large Language Models (LLMs) are investigated as potential tool to be used in medical treatment, by e.g. producing doctor’s reports, supporting personalized medicine or educating patients. However, limitations are broadly discussed addressing patient safety and ethical concerns due to false and misleading content. Therefore, LLMs face criticism among users not only towards their integration in the patient-provider-interaction, but also in its use in medical research and health care education. In the ongoing EXPOLS (Exploring the Potential of LLMs in Statistical Consulting) study, we address the question ‘What are the attitudes, fears and experiences regarding the integration of AI tools in the clinical/scientific work routine?’ Methods We implemented an online survey that will be accessible in 07/2024. All employees at the University and Medical Center Freiburg will be asked to participate in the survey via online media. We expect a sample size of n = 600-1,200. The survey combines published measurements (e.g. TRI 2.0, result expectation measure), as well as a self-designed instrument with 15 items aiming to measure fears and attitudes towards AI. Latter was developed within a multidisciplinary team making use of ChatGPT as item generator. We will investigate its psychometric properties using exploratory factor analysis and describe distribution characteristics. Results At the time of the conference, the project will be completed and both psychometric insights and content-related results will be reported. The results could have important public health implications, since attitudes towards AI will steer its integration in the medical and clinical routine. Conclusions The EXPOLS study makes a current inventory among medical scientists in Freiburg following a modern approach in instrument development by including ChatGPT as collegial advisor. Key messages • This study explores attitudes, fears and experiences towards the integration of AI tools in the work routine from medical and scientific staff at the University of Freiburg. • The findings might be crucial in determining the integration of AI based tools in the medical and clinical work routine.

A Non-Stochastic Special Model of Risk Based on Radon Transform

The concept of risk is fundamental in various scientific fields, including physics, biology and engineering, and is crucial for the study of complex systems, especially financial markets. In our research, we introduce a novel risk model that has a natural transactional–financial interpretation. In our approach, the risk of holding a financial instrument is related to the measure of the possibility of its loss. In this context, a financial instrument is riskier the more opportunities there are to dispose of it, i.e., to sell it. We present a model of risk understood in this way, introducing, in particular, the concept of financial time and a financial frame of reference, which allows for associating risk with the subjective perception of the observer. The presented approach does not rely on statistical assumptions and is based on the transactional interpretation of models. To measure risk, we propose using the Radon transform. The financial concept of risk is closely related to the concepts of uncertainty, entropy, information, and error in physics. Therefore, the well-established algorithmic aspects of the computed tomography method can be effectively applied to the broader field of uncertainty analysis, which is one of the foundational elements of experimental physics.