Basic Principles Research Articles

Superior electroadhesion force with permittivity-engineered bilayer films using electrostatic simulation and machine learning approaches

Electroadhesive forces are crucial in various applications, including grasping devices, electro-sticky boards, electrostatic levitation, and climbing robots. However, the design of electroadhesive devices relies on speculative or empirical error approaches. Therefore, we present a theoretical model comprising predictive coplanar electrodes and protective layers for analyzing the electrostatic fields between an object and electroadhesive device. The model considers the role of protective layer and the air gap between the electrode surface and the object. To exert a higher electroadhesive force, the higher permeability of the protective layer is required. However, a high permeability of the protective layer is hard to withstand high applied voltage. To overcome this, two materials with different permeabilities were employed as protective layers—a low-permeability inner layer and a high-permeability outer layer—to maintain a high voltage and generate a large electroadhesive force. Because a low-permeability inner layer material was selected, a more permeable outer layer material was considered. A theoretical analysis revealed complex relationships between various design parameters. The impact of key design parameters and working environments on the electroadhesion behavior was further investigated. This study reveals the fundamental principles of electroadhesion and proposes prospective methods to enhance the design of electroadhesive devices for various engineering applications.

A cloud-based learning module for biomarker discovery.

This manuscript describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on basic principles in biomarker discovery in an interactive format that uses appropriate cloud resources for data access and analyses. In collaboration with Google Cloud, Deloitte Consulting and NIGMS, the Rhode Island INBRE Molecular Informatics Core developed a cloud-based training module for biomarker discovery. The module consists of nine submodules covering various topics on biomarker discovery and assessment and is deployed on the Google Cloud Platform and available for public use through the NIGMS Sandbox. The submodules are written as a series of Jupyter Notebooks utilizing R and Bioconductor for biomarker and omics data analysis. The submodules cover the following topics: 1) introduction to biomarkers; 2) introduction to R data structures; 3) introduction to linear models; 4) introduction to exploratory analysis; 5) rat renal ischemia-reperfusion injury case study; (6) linear and logistic regression for comparison of quantitative biomarkers; 7) exploratory analysis of proteomics IRI data; 8) identification of IRI biomarkers from proteomic data; and 9) machine learning methods for biomarker discovery. Each notebook includes an in-line quiz for self-assessment on the submodule topic and an overview video is available on YouTube (https://www.youtube.com/watch?v=2-Q9Ax8EW84). This manuscript describes the development of a resource module that is part of a learning platform named ``NIGMS Sandbox for Cloud-based Learning'' https://github.com/NIGMS/NIGMS-Sandbox. The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox [1] at the beginning of this Supplement. This module delivers learning materials on the analysis of bulk and single-cell ATAC-seq data in an interactive format that uses appropriate cloud resources for data access and analyses.

The principle of legality and sustainable development goals (SDGs): Impact and practices in UAE constitution

The principle of legality constitutes one of the basic principles of the government’s rule of law, and as a result, it has been recognized as one of the most essential guarantees of human rights. The goals of sustainable development have a strong link with the principle of legality, and achievements in accomplishing a goal can frequently contribute to the accomplishment of other goals in addition. The United Arab Emirates’ constitutional framework, regulations, and rules, along with the goals for sustainable development (SDGs), were profoundly affected by the principle of legality. The method in which international standards and laws have been integrated into the UAE’s national legal framework provides definitive proof of this effect. The research concluded that all published and unofficial legal regulations have to be respected in order for public authorities to use within the limits of the principle of legality. These involve adhering to the standards of positive legitimacy and the fundamental regulations the community agrees on.

Joint diffusion: mutual consistency-driven diffusion model for PET-MRI co-reconstruction

Objective. Positron Emission Tomography and Magnetic Resonance Imaging (PET-MRI) systems can obtain functional and anatomical scans. But PET suffers from a low signal-to-noise ratio, while MRI are time-consuming. To address time-consuming, an effective strategy involves reducing k-space data collection, albeit at the cost of lowering image quality. This study aims to leverage the inherent complementarity within PET-MRI data to enhance the image quality of PET-MRI. Approach. A novel PET-MRI joint reconstruction model, termed MC-Diffusion, is proposed in the Bayesian framework. The joint reconstruction problem is transformed into a joint regularization problem, where data fidelity terms of PET and MRI are expressed independently. The regular term, the derivative of the logarithm of the joint probability distribution of PET and MRI, employs a joint score-based diffusion model for learning. The diffusion model involves the forward diffusion process and the reverse diffusion process. The forward diffusion process adds noise to transform a complex joint data distribution into a known joint prior distribution for PET and MRI simultaneously, resembling a denoiser. The reverse diffusion process removes noise using a denoiser to revert the joint prior distribution to the original joint data distribution, effectively utilizing joint probability distribution to describe the correlations of PET and MRI for improved quality of joint reconstruction. Main results. Qualitative and quantitative improvements are observed with the MC-Diffusion model. Comparative analysis against LPLS and Joint ISAT-net on the ADNI dataset demonstrates superior performance by exploiting complementary information between PET and MRI. The MC-Diffusion model effectively enhances the quality of PET and MRI images. Significance. This study employs the MC-Diffusion model to enhance the quality of PET-MRI images by integrating the fundamental principles of PET and MRI modalities and leveraging their inherent complementarity. Furthermore, utilizing the diffusion model to learn the joint probability distribution of PET and MRI, thereby elucidating their latent correlation, facilitates a more profound comprehension of the priors obtained through deep learning, contrasting with black-box prior or artificially constructed structural similarities.

The myth of high-resolution liquid phase biological electron microscopy.

Cryo-electron microscopy (cryo-EM) has transformed structural biology over the past 12 years, with it now being routine rather than exceptional to reach a near-atomic level of resolution for proteins and macromolecular complexes. Samples are immobilized by vitrification and this sample can be maintained at liquid nitrogen temperatures in the vacuum of the electron microscope with negligible sublimation. Due to the low electron doses needed to avoid radiation damage, averaging over tens of thousands to hundreds of thousands of particle images is used to achieve a high signal-to-noise ratio. An alternative approach has been proposed where samples are at room temperature in the liquid state, maintained in the vacuum of the electron microscope by thin film enclosures that are relatively transparent to electrons while preventing evaporation of the liquid. A paper has argued that using this liquid-phase approach, higher resolution (3.2 Å) can be achieved than using cryo-EM (3.4 Å) when imaging and reconstructing adeno-associated virus particles. I show here that these assertions are untrue, and that basic principles in mathematics and physics would need to be violated to achieve the stated resolution in the liquid state. Thus, high resolution liquid phase EM of macromolecules remains science fiction.

A Microsurgical Skills Curriculum to Develop Unconscious Competence.

The attainment of microsurgical competency is an important milestone for plastic surgery trainees. Technical skill and a practiced disposition are required to successfully perform microsurgical procedures. Microsurgical skills curricula may foster both proficiency with technical movements and facilitate performance with minimal cognitive burden while using the operating microscope. The microsurgical skills curriculum presented in this article focuses on three fundamental principles: intrinsic muscle strength, accuracy and precision of movement, and supervised practice. Progressive operative entrustment of trainees is earned through successful completion of deliberate microsurgical exercises rather than timed anastomosis trials. The overarching goal of this curriculum is to develop unconscious competence in microsurgery.

Bumps and detours of the domestic pathway of money laundering legislation

Aim: The aim of the paper is a brief review of the past 30 years of domestic legislation concerning the criminal act of money laundering, also to summarise the lessons learned from the modifications and to outline some aspects of legal-interpretation. Methodology: The paper analyses the periodical changes of the phrasing of the act and the legal policy intentions in connection with these changes. It takes a position on the academic debates concerning the application of the offence and critically assesses legal practice. Findings: The current legislation and practice of money laundering is still not without inconsistencies. Qualification of specific acts as money laundering could often contradict fundamental legal principles, the proper interpretation of actual or pseudo multiple-offence theory, the concurring aspects of aiding and abetting versus subsidiary or collateral offences, and the necessity to justify culpability or mens rea. While not disputing the legitimate purpose of the offence, nevertheless with an expectation of a more critical attitude regarding its application, effective investigation of the preliminary offences shall not be de-emphasised, as its effectiveness is still the most effective way to the prevention of money laundering. Value: The conclusions may contribute to a better founded jurisprudence concerning money laundering, as well as it may provide guidance for future codification considerations.

Legal status of the self-employed person in the field of social protection in Ukraine

Due to the existence of many scientific studies and various statements regarding the legal status of the self-employed person and their legal status in the field of social protection. It is necessary to conduct a thorough analysis of important aspects of this issue. Especially in times of war, when the unemployment rate is steadily increasing and self-employed persons are increasing their value to the state. This is the reason for the relevance of the study. The purpose of this research is: to determine the legal status of the self-employed person in the field of social protection in Ukraine; to analyze the characteristics of legal regulation applicable to the self-employed; to process data on the basic principles of social security for the self-employed. Important steps are also to analyse the most significant problems faced by self-employed persons in the field of social protection and to discuss possible solutions.

DNA Tetrahedra as Functional Nanostructures: From Basic Principles to Applications

Self‐assembled supramolecular DNA tetrahedra composed of programmed sequence‐engineered complementary base‐paired strands represent elusive nanostructures having key contributions to the development and diverse applications of DNA nanotechnology. By appropriate engineering of the strands, DNA tetrahedra of tuneable sizes and chemical functionalities were designed. Programmed functionalities for diverse applications were integrated into tetrahedra structures including sequence‐specific recognition strands (aptamers), catalytic DNAzymes, nanoparticles, proteins, or fluorophore. The article presents a comprehensive review addressing methods to assemble and characterize the DNA tetrahedra nanostructures, and diverse applications of DNA tetrahedra framework are discussed. Topics being addressed include the application of structurally functionalized DNA tetrahedra nanostructure for the assembly of diverse optical or electrochemical sensing platforms and functionalized intracellular sensing and imaging modules. In addition, the triggered reconfiguration of DNA tetrahedra nanostructures and dynamic networks and circuits emulating biological transformations are introduced. Moreover, the functionalization of DNA tetrahedra frameworks with nanoparticles provides building units for the assembly of optical devices and for the programmed crystallization of nanoparticle superlattices. Finally, diverse applications of DNA tetrahedra in the field of nanomedicine are addressed. These include the DNA tetrahedra assisted permeation of nanocarriers into cells for imaging, controlled drug release, active chemodynamic/photodynamic treatment of target tissues, and regenerative medicine.

DNA Tetrahedra as Functional Nanostructures: From Basic Principles to Applications.

Self-assembled supramolecular DNA tetrahedra composed of programmed sequence-engineered complementary base-paired strands represent elusive nanostructures having key contributions to the development and diverse applications of DNA nanotechnology. By appropriate engineering of the strands, DNA tetrahedra of tuneable sizes and chemical functionalities were designed. Programmed functionalities for diverse applications were integrated into tetrahedra structures including sequence-specific recognition strands (aptamers), catalytic DNAzymes, nanoparticles, proteins, or fluorophore. The article presents a comprehensive review addressing methods to assemble and characterize the DNA tetrahedra nanostructures, and diverse applications of DNA tetrahedra framework are discussed. Topics being addressed include the application of structurally functionalized DNA tetrahedra nanostructure for the assembly of diverse optical or electrochemical sensing platforms and functionalized intracellular sensing and imaging modules. In addition, the triggered reconfiguration of DNA tetrahedra nanostructures and dynamic networks and circuits emulating biological transformations are introduced. Moreover, the functionalization of DNA tetrahedra frameworks with nanoparticles provides building units for the assembly of optical devices and for the programmed crystallization of nanoparticle superlattices. Finally, diverse applications of DNA tetrahedra in the field of nanomedicine are addressed. These include the DNA tetrahedra assisted permeation of nanocarriers into cells for imaging, controlled drug release, active chemodynamic/photodynamic treatment of target tissues, and regenerative medicine.

Principles of digital professionalism for the metaverse in healthcare

BackgroundExperts are currently investigating the potential applications of the metaverse in healthcare. The metaverse, a groundbreaking concept that arose in the early 21st century through the fusion of virtual reality and augmented reality technologies, holds promise for transforming healthcare delivery. Alongside its implementation, the issue of digital professionalism in healthcare must be addressed. Digital professionalism refers to the knowledge and skills required by healthcare specialists to navigate digital technologies effectively and ethically. This study aims to identify the core principles of digital professionalism for the use of metaverse in healthcare.MethodThis study utilized a qualitative design and collected data through semi-structured online interviews with 20 medical information and health informatics specialists from various countries (USA, UK, Sweden, Netherlands, Poland, Romania, Italy, Iran). Data analysis was conducted using the open coding method, wherein concepts (codes) related to the themes of digital professionalism for the metaverse in healthcare were assigned to the data. The analysis was performed using the MAXQDA software (VER BI GmbH, Berlin, Germany).ResultsThe study revealed ten fundamental principles of digital professionalism for the metaverse in healthcare: Privacy and Security, Informed Consent, Trust and Integrity, Accessibility and Inclusion, Professional Boundaries, Evidence-Based Practice, Continuous Education and Training, Collaboration and Interoperability, Feedback and Improvement, and Regulatory Compliance.ConclusionAs the metaverse continues to expand and integrate itself into various industries, including healthcare, it becomes vital to establish principles of digital professionalism to ensure ethical and responsible practices. Healthcare professionals can uphold these principles to maintain ethical standards, safeguard patient privacy, and deliver effective care within the metaverse.

Principles and Optimization of China’s Unconventional Water Management: From a Brand-New Perspective of Responsibility Allocation

Unconventional water includes reclaimed water, harvested rainwater, desalinated seawater, and mine water. Unconventional water use is considered more of a “mandatory responsibility” in China. The initial allocation of unconventional water emphasizes quantity-centered responsibility allocation while the minimum utilization reflects this responsibility. The unconventional water use responsibility (UWUR) should be tailored to the characteristics of each area, moving away from a ‘more is better’ mindset. However, there is a large research gap in this field. This paper first presented six fundamental principles for unconventional water allocation. Ensuring fairness in allocation involves aligning the allocated amount with urban water usage characteristics. Hence, based on four key features, this paper integrated various socioeconomic and environmental factors to build an initial allocation model. To enhance efficiency, an optimal allocation model was constructed using the zero-sum gains–data envelopment analysis (ZSG-DEA) method. The models were then applied to Jiangsu Province, China, to verify their applicability. The results showed that the projected minimum UWUR allocation (unit: 100 million m3) for each city in 2025 is 1.482 (Nanjing), 1.501 (Wuxi), 0.919 (Xuzhou), 1.029 (Changzhou), 2.977 (Suzhou), 1.497 (Nantong), 0.818 (Lianyungang), 0.766 (Huai’an), 0.875 (Yancheng), 0.920 (Yangzhou), 0.790 (Zhenjiang), 0.858 (Taizhou), and 0.766 (Suqian). The rational and feasible results indicated that the allocation framework proposed in this paper has a certain practicability. Lastly, this paper considered the differences in unconventional water utilization conditions across 13 cities and proposed corresponding measures to improve the utilization. This paper represents a tentative exploration of unconventional water allocation in China and offers theoretical and practical insights for policy-makers to improve territorial spatial planning and sustainable water management.

DLS homemade setup: reviewing first and second-order coherence and autocorrelation concepts of a light source in the context of nanoparticle sizes synthesized by PLAL

Abstract The size of the nanoparticles (NP) is one of the most important and essential characteristics to know the properties of the synthesized nanostructures. The most common characterization procedures are related to Scanning Electronic Microscopy (SEM), Transmission Electronic Microscopy (TEM), and Atomic Force Microscopy (AFM). Unfortunately, from a practical point of view, they represent a time-consuming procedure and require expensive equipment, which limits its application to specialized research groups. Significant attention has been paid to Dynamic Light Scattering (DLS) as a simple, fast, and reproducible method for sizing nanoparticles. However, inadequate representation of the fundamental principles of DLS and data interpretation represents two of the most important challenges related to this technique. In this work we try to provide the fundamental principles of the DLS technique, the fundamental mathematical treatment of data obtained during the optical scattering studies and provide the MATLAB code to configure non-commercial DLS equipment. Additionally, analyzes of nanoparticles obtained by pulsed laser ablation of Ag, Au, Si and W and commercial Au nanoparticles were carried out. The particle size results are compared with SEM images to calculate the percentage error of the DLS measurements. The results show an error of 5%, 3.8%, 2.1% for the Ag, Au and Si nanoparticles respectively, which proves to be an excellent approximation to the real values of nanoparticle diameter. Meanwhile, the error in size for W nanoparticles by the same technique and commercial Au nanoparticle is 29% and 12%, which shows the effect of the hydrodynamic diameter of the nanoparticles. This work ends with the analysis of the concentration of nanoparticles and its importance in reliable results of DLS measurements.

Fast computation of local dips using the one-lag correlation method

We adapt the one-lag correlation (OLC) method to estimate the local dips of seismic events or velocity contrasts. The resulting local dips have extensive applications in exploration geophysics, including seismic inversion regularization, computation of seismic attributes like coherence-cube, and facilitating structural-oriented smoothing and extrapolation techniques. Compared to the widely adopted structure tensor (ST) method, the proposed OLC algorithm exhibits notable advantages. The OLC method is characterized by a recursive calculation process that yields significant computational efficiency, boasting an approximately 100 times faster performance for 3D scenarios. The fundamental principle of this novel approach lies in the computation of local dips by using the ratio of two inner products, i.e., OLC, performed on a 2D/3D array along the vertical and horizontal axes, respectively. Crucially, the elements of this array consist of complex numbers derived from the application of the Hilbert transform on the corresponding real-number inputs. Furthermore, the implementation of this algorithm is remarkably straightforward, as exemplified by the concise nature of the code, which comprises a mere ten lines of programming instructions. The OLC method excels in accuracy, surpassing the performance of the ST method, and exhibits superior resistance to random noise. Compelling demonstrations are provided herein to corroborate these desirable properties of the OLC approach, using both synthetic and field data examples.

Noise suppression zeroing neural network for online solving the time-varying inverse kinematics problem of four-wheel mobile manipulators with external disturbances

A novel noise suppression zeroing neural network (NSZNN) is presented for the trajectory tracking problem on a four Mecanum wheeled mobile manipulator (FMWMM) by solving its time-varying inverse kinematics (TVIK) problem. The holistic kinematic model of the FMWMM is developed, which can receive synergistic control of the mobile manipulator. Different from the situation without external interference addressed in our previous work, this paper considers a variety of common time-varying interferences by studying the basic principles of various noises, and proves the NSZNN model’s of the validity and superiority, which solves the TVIK problem of the FMWMM with external disturbances through theoretical analyses. Compared with the existing gradient neural network (GNN) and the traditional zeroing neural network (ZNN), the most representative hybrid noise is selected to conduct a large number of experiments to substantiate the high efficiency and robustness of the NSZNN model. Finally, the NSZNN model is verified on the FMWMM via a robot operating system (ROS) by a successful execution of the trajectory tracking task.

A new insight into largely defocused HAADF-STEM imaging and visualization of strain field

A crystalline bilayer specimen with a semi-coherent interface can generate moiré fringes in the high-angle annular-dark field scanning transmission electron microscopy (HAADF-STEM) imaging. Moreover, when the probe is significantly defocused, this specimen can produce largely defocused probe (LDP)-STEM patterns. Although the electron channeling effect serves as the fundamental principles for HAADF-STEM imaging, its connection to the emergence of LDP-STEM patterns remains unclear. The missing link lies in identifying the location of the imaged region. To address this issue, we examined the strain field in three-dimensional space and its interaction with the convergent electron beam, taking the PbZrO3/SrTiO3 (PZO/STO) heterostructure as an example. We discovered a new intensity relationship for LDP-STEM patterns in the PZO/STO heterostructure, which can be well explained by our theory. We also found that, generated by imaging the strain zone, these patterns revealed information that might be obscured in traditional high resolution STEM images, showing a unique advantage in characterizing the strain field. Furthermore, we provided discussions on visualizing the strain field, including the misfit dislocation network and array. Our research offers a novel perspective on the LDP-STEM imaging and clarifies the approach to characterizing the strain field.

Introduction and content analysis of "Nurse's voice" WhatsApp group during COVID-19 pandemic: a qualitative study

BackgroundAt the beginning of the COVID-19 pandemic in Iran, the School of Nursing and Midwifery of Tehran University of Medical Sciences created several joint virtual groups to connect with people and answer their questions. One of these groups was called "Nurse's Voice,” in which nursing professors answered people's questions. The purpose of the current study was to analyze the content of questions in this WhatsApp group during the COVID-19 pandemic.MethodThis retrospective media content analysis qualitatively analyzed the text of questions and answers extracted from the above-named WhatsApp group.ResultsOut of 629 questions asked, 364 questions (58.0%) were related to COVID-19 and 265 questions (42.0%) were not. Those related to COVID-19 concerned COVID-19 symptoms and diagnosis, prevention and care, fear and worry, and interpretation of laboratory tests. The questions related to prevention and care fell into four subcategories: basic health principles, prevention of COVID-19 infection, care during COVID-19 infection, and care during COVID-19 recovery.ConclusionsNursing and midwifery schools can take advantage of the scientific capacity of professors and students for virtual communication and social accountability by integrating telehealth into their curricula. Cyberspace provides an opportunity for people to ask questions anonymously. With the results of the current study, the educational needs of the people during possible future epidemics can be predicted and answered faster. Furthermore, the large number of questions unrelated to COVID-19 indicates the need for counseling and training of the general public by nurses in all situations.

تداعيات الاختلاف بين المدارس الحديثية

When the disagreement occurred among the Fiqh schools in methodology and deduction, particularly between the school of Ahl Al-Hadith and the school of Ahl Al-Ra’y, it was important to examine and extrapolate the approach of each school in order to identify the points of agreement and disagreement between them. This research aims to identify Ahl Al-Hadith and the concept of Ahl Al-Hadith’s school, clarify the meaning of Ahl Al-Ra’y and the concept of Ahl Al-Ra’y’s school, deduce the methodology that each school adhered to and elucidate their contributions to the Sunnah and its sciences, and conduct a comparison between the two schools to highlight the points of agreement and disagreement between them. To this regard, I combine the inductive, analytical, and comparative approaches. The research is arranged into an introduction, three treatises, a conclusion, a list of bibliography and references. Then the research ends with several findings, including: Ahl Al-Hadith refers to those who have a close connection with the traditions (Athar) through seeking, collecting, understanding, memorizing, narrating, following, and acting accordingly, both outwardly and inwardly, and they possess the critical faculty and the fine discernment to distinguish between authentic and unauthentic narrations of the Prophet (PBUH). Meanwhile, Ahl Al-Ra’y refers to those who consider issues and engage in Ijtihad (Shariah-based-reasoning), and use analogical deduction (Qiyas) in matters of creed and Fiqh, whether their Ijtihad is reprehensible or praiseworthy. As for the recommendations, the most significant among them is the need to understand that disagreement among the four schools of Fiqh pertains to subsidiary matters, while they agree on the fundamental principles of issues.

Treatment of chronic non-specific (musculoskeletal) back pain

Treatment of patients with chronic non-specific back pain (CNBP) is an important issue not only in medicine, but also in modern society as a whole, as it is associated with significant socio-economic burden.The lecture presents the most common anatomical sources of CNBP, the causes of CNBP and issues of differential diagnosis. Much attention is paid to the basic principles of therapy for CNBP: drug therapy, kinesiotherapy and psychological methods. Clinical observations are presented that demonstrate the effectiveness of a multimodal integrated approach to the treatment of CNBP based on the use of cognitive behavioral therapy, educational programs and kinesiotherapy and self-monitoring test tasks.

Multi-Physics Coupling in IGBT Modules: A Review

Abstract Since insulated gate bipolar transistor (IGBT) is a core component for power conversion in a power electronic system, guaranteeing the safety of IGBT becomes a crucial task for the maintenance of the power system. However, the mechanism of IGBT failure is a considerably complicated process related to the dynamic process, involving electric, thermal, and force. Hence, understanding the behaviors of IGBT under multi-physics field coupling plays an important role in the design and reliability studies of IGBT. In this paper, we review the multi-physics coupling effects, namely, electric-thermal coupling, thermal-force coupling, and force-electric coupling, inside IGBT devices. The basic principles of each coupling, coupling models, application occasions as well as key issues and development trends are discussed in detail, respectively.