Singular Domain Research Articles

The protective and destructive critical processes of female labor in small-scale fishing in coast Pernambuco, Brazil.

This study aims to analyze the protective and destructive critical processes of 34 water women in the municipalities of Cabo de Santo de Agostinho and Ipojuca, Pernambuco, Brazil, from February/21 to August/22. The work process stages were systematized by the work flowchart, and we employed Breilh's critical processes matrix to organize the data. The destructive processes identified in the general domain were injustice and socio-environmental vulnerability, such as the economic development model, the Suape Industrial Port Complex, the 2019 oil spill crime disaster, the COVID-19 pandemic, and the difficult access to public policies; in the particular domain: overloads and extended working hours, use of rudimentary equipment and tools, and unequal gender, class, and race relationships; in the singular domain: physical and mental illnesses and deaths. The protective processes identified in the general domain were sustainable development objectives, public health, and social assistance policies; in the particular domain, group work and processing, consumption for subsistence; in the singular domain, fishing as a therapeutic, pleasurable, and sharing process. The study highlighted the central issues of the water women and the need to establish public policies targeting their care.

Decoupling numerical method based on deep neural network for nonlinear degenerate interface problems

Many practical problems, including modeling composite materials, nuclear waste disposal, oil reservoir simulations, and flows in porous medium, commonly involve interface problems. However, the solution to interface problems with discontinuous coefficients of PDEs using fully decoupled numerical methods is challenging. The main objective is to solve the interface problems with fully decoupled numerical methods. This paper proposes an efficient decoupled numerical method for solving degenerate interface problems with double singularities. First, we divide the whole domain into singular and regular subdomains. Then, we use the Deep Neural Network (DNN) to find the solution on the singular subdomain and approximate the solution on the regular subdomain using the finite difference method. The scheme combines the solutions of singular and regular subdomains, which is an exciting idea. The key to the new approach is to split nonlinear degenerate partial differential equations with an interface into two independent boundary value problems based on deep learning. In this way, the expansion of the solution on the singular domain does not contain undetermined parameters, and two independent boundary value problems can be solved with any well-known traditional numerical methods. The main advantage of the proposed scheme is that we not only get the order of convergence of the degenerate interface problems on the whole domain, but we also can calculate VERY BIG jump ratio (such as 1012:1 or 1:1012) for the interface problems including degenerate and non-degenerate cases. Finally, with examples, we demonstrate the efficiency and accuracy of methods for 1 and 2D problems. It is also interesting that the proposed method is valid for the interface problems with degenerate and non-degenerate cases, we show it with some examples.

A mobile edge computing-focused transferable sensitive data identification method based on product quantization

Sensitive data identification represents the initial and crucial step in safeguarding sensitive information. With the ongoing evolution of the industrial internet, including its interconnectivity across various sectors like the electric power industry, the potential for sensitive data to traverse different domains increases, thereby altering the composition of sensitive data. Consequently, traditional approaches reliant on sensitive vocabularies struggle to adequately address the challenges posed by identifying sensitive data in the era of information abundance. Drawing inspiration from advancements in natural language processing within the realm of deep learning, we propose a transferable Sensitive Data Identification method based on Product Quantization, named PQ-SDI. This innovative approach harnesses both the composition and contextual cues within textual data to accurately pinpoint sensitive information within the context of Mobile Edge Computing (MEC). Notably, PQ-SDI exhibits proficiency not only within a singular domain but also demonstrates adaptability to new domains following training on heterogeneous datasets. Moreover, the method autonomously identifies sensitive data throughout the entire process, eliminating the necessity for human upkeep of sensitive vocabularies. Extensive experimentation with the PQ-SDI model across four real-world datasets, resulting in performance improvements ranging from 2% to 5% over the baseline model and achieves an accuracy of up to 94.41%. In cross-domain trials, PQ-SDI achieved comparable accuracy to training and identification within the same domain. Furthermore, our experiments showcased the product quantization technique significantly reduces the parameter size by tens of times for the subsequent sensitive data identification phase, particularly beneficial for resource-constrained environments characteristic of MEC scenarios. This inherent advantage not only bolsters sensitive data protection but also mitigates the risk of data leakage during transmission, thus enhancing overall security measures in MEC environments.

Addressing arbitrary body forces in 2D elasticity coupling the Radial Basis Integration Method with boundary elements

A boundary-domain integral formulation inevitably arises when the boundary element method (BEM) is applied for solving the differential equation that governs linear elastostatic problems with body forces. Although the domain integrals introduced by the body forces can be evaluated using internal cells this destroys the boundary-only meshing feature of BEM and makes the integration processes inefficient. This paper shows that these problems can be solved more efficiently without using internal cells by the Radial Basis Integration Method (RBIM) which employs a meshless quadrature obtained by performing boundary-only offline computations. Using RBIM, weakly singular domain integrals can be computed via a simple selective quadrature procedure, whereas, strong singular domain integrals may be computed using two schemes: The first, is based on the same selective quadrature procedure, and the second is based on the singularity separation scheme. The present method, unlike classical radial integration method (RIM), does not have problems in calculating integrals in concave or multiple-connected domains. The results obtained in some 2D linear elastostatic problems with arbitrary body forces show that this method can be as accurate as RIM but less time-consuming than the latter. This method could be applied to other engineering problems involving source terms.

Computation of Neumann Localised Boundary Domain Integral Equations

Most integrals in Localised Boundary Domain Integral Equations (LBDIEs) comprise singularities. This paper aims to produce numerical solutions of the LBDIEs for the Partial Differential Equations with variable coefficients. The singularities of the boundary integrals in LBDIEs will be handled by using a semi-analytic for logarithmic singularity and a semi-quadratic analytic method for r−2 singularity. Whereas the singular domain integrals are handled by using the Duffy transformation. The LBDIEs that we consider are associated with the Neumann problem, which can be solved with a condition. If it can be solved, the solution is, however, unique up to an additive constant. We add a perturbation operator to the LBDIEs to convert the LBDIE to a uniquely solvable equation. The perturbed integral operator leads the perturbed LBDIEs to a dense matrix system that disable the use of methods in solving sparse matrix system. We solve the system of linear equations by Lower-Upper (LU) decomposition method. The numerical results indicate that high accuracy results can be attained. It gives the impression that the methods we use in this numerical experiment are reliable in handling the boundary and domain singular integrals.

Magnetoelectric Energy in Electrodynamics: Magnetoelectricity, Bi(an)isotropy, and Magnetoelectric Meta‐Atoms

AbstractMagnetoelectricity denotes the relationship between electric polarization and magnetization. In materials with an intrinsic magnetoelectric (ME) effect, the energy density comprises the polarization, magnetization, and ME energy densities. These three components of energy define local (subwavelength) characteristics of electromagnetic (EM) responses in multiferroic materials. In a subwavelength domain, coupling between the electric and magnetic dipole oscillations forms the ME field structures that are characterized by the violation of both spatial and temporal symmetry. Unlike multiferroics, bi(an)isotropic metamaterials are associated with an EM response characterized only by spatial symmetry breaking. This also applies to chiral materials. Since no “intrinsic magnetoelectricity” is assumed in such structures, any concepts about the stored ME energy are not applicable. This clearly points to the effect of nonlocality. That is why the basic concepts of bi(an)isotropy can only be analyzed by the EM far‐field characteristics. In this paper, it is argued that in the implementation of local (subwavelength) ME meta‐atoms and systems for near‐field probing of chirality, the concept on ME energy is crucial. Real ME energy can occur when ME fields in a singular subwavelength domain are characterized by a violation of both the symmetry of time reversal and spatial reflection.

A NUMERICAL METHOD FOR 3D TIME-DEPENDENT MAXWELL’S EQUATIONS IN AXISYMMETRIC SINGULAR DOMAINS WITH ARBITRARY DATA

In this article, we propose to solve the three-dimensional time-dependent Maxwell equations in a singular axisymmetric domain with arbitrary data. Due to the axisymmetric assumption, the singular computational domain boils down to a subset of R2. However, the electromagnetic field and other vector quantities still belong to R3. Taking advantage that the domain is transformed into a two-dimensional one, by doing Fourier analysis in the third dimension, one arrives to a sequence of singular problems set in a 2D domain. The mathematical tools of such problems have been exposed in [4,19]. Here, we derive a variational method from which we propose an original finite element numerical approach to solve the problem. Numerical experiments are also shown to illustrate that the method is able to capture the singular part of the solution. This approach can also be viewed as a generalization of the Singular Complement Method to three-dimensional problem.

An effective approach for non-singular trajectory generation of a 5-DOF hybrid machining robot

By taking a newly developed 5-DOF (degree of freedom) hybrid robot as an exemplar, this paper presents a novel and effective approach for non-singular tool trajectory generation. Based upon singularity analysis via inverse kinematics, an algorithm for the C-axis path optimization is developed using the weighted S-curve. Incorporated singular domain detection with the C-axis angle correction, the algorithm can easily be programmed and embedded into the CNC (computer numerical control) system as a postprocessing module and works in real-time. Then, an offline feedrate scheduling method is proposed by considering the drive and geometric accuracy constraints, allowing the rapid yet smooth movement in the neighborhood of singularity to be achieved. Additionally, it is found that the orientation accuracy can be improved by setting adequate cone angle and feedrate value. The results of both simulations and experiments on a prototype machine show that the C-axis can follow the non-singular tool trajectory well with relatively high rotary speed to pass through the singular domain, thereby verifying the effectiveness of the proposed approach.

Assessment of Cognitive Assistive Technologies in Elderly Patients with Dementia Post-COVID-19 Infection: A Research Proposal

Introduction: SARS-CoV-2 infection is thought to be implicated in an increased risk for various neurodegenerative diseases given its role in neuroinflammation. As a result, cognitive assistive technologies to monitor the risk of neurodegenerative diseases in those with prior COVID-19 infection and the regular implementation of practices designed to promote synaptic plasticity may decrease the risk of dementia in susceptible populations. It is hypothesized that incorporating frequent use of a mobile application designed to improve memory five times per week in the daily routines of patients aged 65+ who have survived a COVID-19 infection may decrease the prevalence of subsequent dementia. Methods: The goal of this application would be to (i) deliver interventions related to long-term potentiation, and (ii) centralizing patient health data in a singular domain to improve ease of access for caregivers and medical staff. This may be investigated through a two-pronged randomized controlled trial aimed to compare neural and cognitive functioning through repeat neuropsychological exams, magnetic resonance imaging, and electroencephalogram tests over a 6-year timeframe between no-intervention and intervention groups while collecting caregiver and healthcare worker data regarding its efficacy in improving quality of life. Results: It is expected that patients consistently using cognitive assistive technologies in long-term care facilities will experience lower incidence of cognitive decline compared to the control group due to improved maintenance of mental health and the learning of new skills. In addition, with the use of technology, patients may experience increased autonomy and independence, improving their quality of life while simultaneously providing relief to their families and caregivers. Discussion: Some further considerations may include the degree of technological proficiency of the patients during the development process to ensure that patients reap the maximum benefits. Factors including rapid development and testing, funding, and strong technology support systems must be taken into consideration to ensure a seamless transition to increased reliance on technology in post-COVID-19 patients with dementia. Conclusion: Strong evidence indicates technology-based interventions can be used to by dementia patients and their caretakers overcome physical and environmental challenges normally and during future pandemic waves.

Shape analyticity and singular perturbations for layer potential operators

We study the effect of regular and singular domain perturbations on layer potential operators for the Laplace equation. First, we consider layer potentials supported on a diffeomorphic imageϕ(∂Ω) of a reference set ∂Ω and we present some real analyticity results for the dependence upon the mapϕ. Then we introduce a perforated domain Ω(ε) with a small hole of sizeεand we compute power series expansions that describe the layer potentials on ∂Ω(ε) when the parameterεapproximates the degenerate valueε = 0.

On the solvability of a fourth-order differential evolution equation on singular cylindrical domain in R4

Abstract In this paper, we investigate the solvability of a fourth-order differential evolution equation on singular cylindrical domain containing a cuspidal point. Some regularity results are obtained for the classical solutions by using the Dunford operational calculus.

Abstract P2056: A Micropeptide Encoded By An Endogenous Retroviral-derived Lncrna Regulates Cardiomyocyte Multinucleation

Endogenous retroelements (REs) are pervasive in mammalian genomes, and consist mostly of silenced mobile genetic sequences long considered to be ‘junk DNA.’ In a few known instances, mammalian genomes have captured and repurposed endogenous retroviral sequences to play important roles in regulating mammalian cell functions, notably cell fusion. Our previous work has shown that some mammalian transcripts misannotated as lncRNAs can be translated into small functional peptides, called micropeptides. Here we report the discovery of a cardiac-specific micropeptide encoded by a misannotated lncRNA transcribed from a murine endogenous retroviral element. We named this transcript CARDI, and the encoded micropeptide CARDI-B, since translation of the micropeptide occurs from the second ATG start codon. We show that CARDI-B shares homology with a singular domain of a retroviral protein and localizes to the nucleus. Genetic deletion of CARDI-B in mice from an isogenic background significantly increased the frequency of binucleated cardiomyocytes, at the expense of mononucleated cardiomyocytes. In line with previous reports that the frequency of mononucleated cardiomyocytes is correlated with cardiac regeneration, we show that CARDI-B-deficient hearts perform worse following myocardial infarction injury. These data reveal that functional micropeptides can be concealed within mammalian retroelements, and suggests that RE-derived micropeptides may contribute to the natural variation in heart development and regeneration observed across species.

Асимптотика решений однородного бисингулярно возмущенного дифференциального уравнения в теории обобщенных функций

In the space of generalized functions, a homogeneous system of singularly perturbed differential equations in the case of stability change is considered. A theorem on generalized solutions of the corresponding degenerate system of the equation is proved. At special points, the asymptotic closeness of the solutions of the perturbed and unperturbed problems in the singular domain is established. The novelty of the work lies in the fact that, for the first time, an estimate for the singular region was obtained. A degenerate system has a special point. At this point, we solve the equation in generalized functions. In turn, this is also a novelty, because previously performed works only considered the classical solution. The following novelty of the work lies in the fact that we take the starting point in an unstable interval and also head towards the unstable interval. This property is not characteristic of previously published works.

A new radial basis integration method applied to the boundary element analysis of 2D scalar wave equations

A new integration method named the Radial Basis Integration Method (RBIM) that include the Kriging Integration Method (KIM) Narváez and Useche (2020) as a particular case and performs boundary only offline precomputations for the creation of a meshless quadrature was developed for its application in boundary elements. Herein, as in DR-BEM, the inertial term is approximated using radial basis functions, however, its particular solution is not needed. The quadrature is now obtained in a simpler way than in KIM, because the evaluations of domain integrals necessary to compute the weights of quadrature points, is done transforming those to the boundary instead of using the Cartesian Transformation Method. Using RBIM, weakly singular domain integrals may be computed with good accuracy over complex domains. The results obtained in some scalar wave propagation problems using both Houbolt-α and Newmark-α time marching methods show that this procedure can be even more accurate than other used in BEM analysis.

On the study of the wave equation set on a singular cylindrical domain

We give new regularity results of solutions for the linear wave equation set in a nonsmooth cylindrical domain. Different types of conditions are imposed on the boundary of the singular domain. Our study is performed in some particular anisotropic H?lder spaces.

Functioning of Older Adults in Low and Middle Income Countries: A Literature Review

The global population of older adults is rising, with the fastest surge in low and middle income countries (LMIC). Physical functioning determines independence in living. Therefore, it is critical to understand the functioning of older adults in LMIC. Extensive literature informs the functioning profile of older adults in developed nations; however, functioning of older adults in developing nations remains understudied. Physical functioning profile of older adults varies across the world due to differences in socio-demographic and economic factors alongside age-related physiological changes. The present study reviews the functioning profile, factors affecting physical functioning and health related quality of life (H-RQoL), and influence of physical co-morbidities on functioning of older adults in LMIC. Literature search was conducted in PubMed, Google Scholar, CINHAL, and Cochrane database. Eighteen cross-sectional, longitudinal, prospective cohort studies from Asia, Africa, North, South America, and Turkey were included. Most studies focused on singular domain of function. Hand-grip strength, lower extremity muscle strength, balance, and cognition were the most affected variables. Most older adults required partial assistance in bathing and housekeeping, and complete assistance in dressing. Individuals aged ≥ 75 years demonstrated greater limitation in activities of daily living (ADL). Older adults with cognitive impairment were at greater risk of functional decline. Low income, arthritis, and diabetes were major factors responsible for limitation in ADL and poor H-RQoL. Clinicians, researchers, and policymakers can use the present findings to plan culturally suitable rehabilitation programs to impart good health and well-being to older adults, which is central to the attainment of health-related sustainable development goals set forth by the United Nations.

Simultaneous T1 , T2 , and T1ρ cardiac magnetic resonance fingerprinting for contrast agent-free myocardial tissue characterization.

To develop a simultaneous T1 , T2 , and T1ρ cardiac magnetic resonance fingerprinting (MRF) approach to enable comprehensive contrast agent-free myocardial tissue characterization in a single breath-hold scan. A 2D gradient-echo electrocardiogram-triggered cardiac MRF sequence with low flip angles, varying magnetization preparation, and spiral trajectory was acquired at 1.5 T to encode T1 , T2 , and T1⍴ simultaneously. The MRF images were reconstructed using low-rank inversion, regularized with a multicontrast patch-based higher-order reconstruction. Parametric maps were generated and matched in the singular value domain to extended phase graph-based dictionaries. The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional methods in terms of coefficients of determination and best fits for the phantom study, and in terms of Bland-Altman agreement, average values and coefficient of variation of T1 , T2 , and T1⍴ for the healthy subjects study. The T1 , T2 , and T1⍴ MRF values showed excellent correlation with conventional spin-echo and clinical mapping methods in phantom studies (r2 > 0.97). Measured MRF values in myocardial tissue (mean ± SD) were 1133 ± 33 ms, 38.8 ± 3.5 ms, and 52.0 ± 4.0 ms for T1 , T2 and T1⍴ , respectively, against 1053 ± 47 ms, 50.4 ± 3.9 ms, and 55.9 ± 3.3 ms for T1 modified Look-Locker inversion imaging, T2 gradient and spin echo, and T1⍴ turbo field echo, respectively. A cardiac MRF approach for simultaneous quantification of myocardial T1 , T2 , and T1ρ in a single breath-hold MR scan of about 16 seconds has been proposed. The approach has been investigated in phantoms and healthy subjects showing good agreement with reference spin echo measurements and conventional clinical maps.

Perceived wellness among pharmacy residents during COVID-19

BackgroundWell-being, burnout, and resiliency have been topics of discussion among health care providers over the last few years. Wellness can relate to many areas or domains in our lives such as financial, social, spiritual, physical, and occupational, whereas well-being is career focused. Wellness is multidimensional and encompasses different domains, and well-being usually focuses on a singular domain. Literature supports the study of well-being in health care workers; however, research is limited for assessing wellness in different domains of health care workers. ObjectiveThis study sought to describe perceived pharmacy resident wellness during the coronavirus disease 2019 (COVID-19) pandemic. MethodsA 67-item survey was sent by e-mail to eligible study participants, including any postgraduate year (PGY) 1, 2, or 24-month pharmacy resident completing/completed their training in June 2019-July 2020. The primary outcome was perceived resident wellness based on the 7 domains from Princeton UMatter Wellness Self-Assessment, developed to measure self-perceptions of wellness across dimensions. Descriptive statistics and participant scores were aggregated and presented as a total domain score. Statistics and scores were determined from completed surveys. ResultsA total of 418 participants accessed the survey, 384 met inclusion criteria, and 326 completed the survey. Of the participants, 77% were female with 85% completing a traditional PGY-1 residency program. The wellness domain with the lowest total was physical wellness, with a domain median of 23 of 28. The highest-scoring domain was social wellness, with a median of 27. ConclusionPerceived resident wellness during COVID-19 was highest in the social domain and lowest in the physical wellness domain. Residency programming administrators could use this information to make improvements to orientation practices and wellness domain programming throughout the duration of residency training during a pandemic.

Vector fields localization on brane worlds

To confine vector bosons in the four dimensional sector of a domain wall spacetime, we propose a mechanism in which the interaction among vectors is propagated via the self-interaction of the scalar wall. In the process, the vector acquires an asymptotic mass, defined by the bulk cosmological constant, and it ends up coupled to the wall by the tension of the brane. The mechanism is applied on the Randall Sundrum scenario and regular versions of it, and on singular domain walls. In any case, the electrostatic potential between two charged particles is defined by both the vector state attached to the wall and a continuous tower of massive vector states that propagate freely along the scenario's extra dimension.

A new video watermarking using redundant discrete wavelet in singular value decomposition domain with multi‐objective optimization

AbstractDay by day, the transmission or sharing of digital information online is increasing due to the fact that Internet usage has become somewhat of an addiction for the majority of people. This results in larger copyright violation problems. Nowadays, most of the data or information is being transmitted in the form of digital images or videos, which are rather simple for the violators of copyright to forge or fake and then share for profit. Thus, digital watermarking came into existence as a possible solution to address these violations of copyright. This article proposes a new blind video watermarking (BVW) using redundant discrete wavelet transform (RDWT) in singular value decomposition (SVD) domain, which utilizes the advantages of both RDWT and SVD to embed and extract the watermark information into the cover video without degrading the quality of the watermark. In addition, an efficient meta‐heuristic optimization with multi‐objective optimization (MOO) is employed to further optimize the proposed RDWT‐SVD approach. Further, various attacks were applied to the watermarked frame to disclose the robustness of proposed BVW using RDWT‐SVD with MOO approach. Extensive simulations on several test videos with comparison to the conventional BVW methodologies exhibit the transcendency of the proposed BVW using RDWT‐SVD with MOO approach in terms of watermarking quality evaluation metrics such as peak signal‐to‐noise ratio (PSNR), structural similarity index, normalized correlation, and even that of root mean square error as well.