Discrete Transform Research Articles

Creation of Machine Learning-Based Fish Classification Systems Based on Morphometric and Mathematical Transform Data

The accurate classification of fish species is crucial for various ecological, conservation, and fisheries management applications. Traditional methods relying solely on manual observation or morphological characteristics can be time-consuming and prone to errors. In recent years, advancements in machine learning (ML) techniques coupled with morphometric and mathematical transform data have shown promising results in automating and enhancing fish species classification processes. This paper presents a comprehensive review of the development and application of ML-based fish classification systems utilizing morphometric measurements and mathematical transforms. The core of this paper focuses on the integration of morphometric and mathematical transform data with ML algorithms for fish classification. In this review commonly employed ML algorithms, including but not limited to support vector machines (SVM), artificial neural networks (ANN), random forests (RF), and convolutional neural networks (CNN). Furthermore, this work discuss feature selection techniques to optimize classification performance and reduce dimensionality. These may include the incorporation of multimodal data sources, transfer learning approaches, and the development of user-friendly tools for field biologists and conservationists. Overall, this paper serves as a comprehensive guide for researchers and practitioners interested in leveraging ML techniques for accurate and efficient fish species classification.

Numerical method for predicting first crack load on hollow-cored beams subjected to point load at Midspan

Predicting the initial crack load in concrete is important to detect early warning of a problem. In this study, a model for predicting the first crack load on a hollow-cored rectangular beam point loaded at mid-span was developed by combining a numerical method and an experimental approach. The modulus of rupture was introduced into the governing moment-curvature relationship. Experimentally, flexural testing with point loads at mid-span was performed on fifteen (15) beams made up of three (3) beam types at 1 kN intervals for a span of 750mm using the Universal Testing machine. The beams were simply supported by roller points. The dimensions of the beams were kept constant and later varied while investigating the following hollow diameters: 0, 30, 60, 75, and 105mm. Numerically, the beams were designed as a beam element point loaded at mid-span with a span of 700mm centers, and the support conditions were defined as pinned support. Governing equations relating failure load with the modulus of rupture, stiffness matrix, shape functions, and moment of inertia were developed. The equation for predicting the first crack load, incorporating the modulus of rupture, was derived. The moment of inertia was calculated by discretizing the hollow-cored beam section using an isoparametric geometric transformation. The experimental results were used to validate the numerical model. 90.55% agreement between experimental and numerical results was observed. The overall average percentage difference between the two methods recorded is 9.45%. This shows that at about 91% confidence level, both approaches are the same and can be applied with confidence in the prediction of the first crack load on hollow- cored reinforced concrete beams.

Light-driven anisotropy of 2D metal-organic framework single crystal for repeatable optical modulation

Structural transformations of metal-organic frameworks (MOFs) go through a complex energy landscape with multiple intermediate states. Although the transformations allow controlling the functional properties of the MOFs, an imbalance between MOF flexibility and rigidity sets a fundamental barrier to achieving fast and multiple transformations. Here, we study the stimuli-responsive structural transformation in a 2D MOF assembled from paddle-wheel secondary building units joined by a semi-flexible organic ligand with 1,2,4-triazole and carboxylate groups with a rigid adamantane cage between them. The structure results in a distinctive combination of MOF flexibility and rigidity, thus, facilitating a continuous transformation driven by laser light. We reveal the laser-induced anisotropic thermal expansion nature of such transformation, initiating optical changes of the 2D MOF. The latter is utilized for fast and highly repeatable optical modulation of over 10,000 cycles. The endurance of such a 2D MOF-based optical modulator during 1 year of storage at ambient conditions paves the way to design tunable and robust MOFs for diverse applications.

Evolution and diversity of biomineralized columnar architecture in early Cambrian phosphatic-shelled brachiopods

Biologically-controlled mineralization producing organic-inorganic composites (hard skeletons) by metazoan biomineralizers has been an evolutionary innovation since the earliest Cambrian. Among them, linguliform brachiopods are one of the key invertebrates that secrete calcium phosphate minerals to build their shells. One of the most distinct shell structures is the organo-phosphatic cylindrical column exclusive to phosphatic-shelled brachiopods, including both crown and stem groups. However, the complexity, diversity, and biomineralization processes of these microscopic columns are far from clear in brachiopod ancestors. Here, exquisitely well-preserved columnar shell ultrastructures are reported for the first time in the earliest eoobolids Latusobolus xiaoyangbaensis gen. et sp. nov. and Eoobolus acutulus sp. nov. from the Cambrian Series 2 Shuijingtuo Formation of South China. The hierarchical shell architectures, epithelial cell moulds, and the shape and size of cylindrical columns are scrutinised in these new species. Their calcium phosphate-based biomineralized shells are mainly composed of stacked sandwich columnar units. The secretion and construction of the stacked sandwich model of columnar architecture, which played a significant role in the evolution of linguliforms, is highly biologically controlled and organic-matrix mediated. Furthermore, a continuous transformation of anatomic features resulting from the growth of diverse columnar shells is revealed between Eoobolidae, Lingulellotretidae, and Acrotretida, shedding new light on the evolutionary growth and adaptive innovation of biomineralized columnar architecture among early phosphatic-shelled brachiopods during the Cambrian explosion.

Evolution and diversity of biomineralized columnar architecture in early Cambrian phosphatic-shelled brachiopods.

Biologically-controlled mineralization producing organic-inorganic composites (hard skeletons) by metazoan biomineralizers has been an evolutionary innovation since the earliest Cambrian. Among them, linguliform brachiopods are one of the key invertebrates that secrete calcium phosphate minerals to build their shells. One of the most distinct shell structures is the organo-phosphatic cylindrical column exclusive to phosphatic-shelled brachiopods, including both crown and stem groups. However, the complexity, diversity, and biomineralization processes of these microscopic columns are far from clear in brachiopod ancestors. Here, exquisitely well-preserved columnar shell ultrastructures are reported for the first time in the earliest eoobolids Latusobolus xiaoyangbaensis gen. et sp. nov. and Eoobolus acutulus sp. nov. from the Cambrian Series 2 Shuijingtuo Formation of South China. The hierarchical shell architectures, epithelial cell moulds, and the shape and size of cylindrical columns are scrutinised in these new species. Their calcium phosphate-based biomineralized shells are mainly composed of stacked sandwich columnar units. The secretion and construction of the stacked sandwich model of columnar architecture, which played a significant role in the evolution of linguliforms, is highly biologically controlled and organic-matrix mediated. Furthermore, a continuous transformation of anatomic features resulting from the growth of diverse columnar shells is revealed between Eoobolidae, Lingulellotretidae, and Acrotretida, shedding new light on the evolutionary growth and adaptive innovation of biomineralized columnar architecture among early phosphatic-shelled brachiopods during the Cambrian explosion.

Everting the Theatrical Sphere Like Terayama

<p>This essay attempts to understand humanistic performances through STEM fields, specifically engaging with Terayama Shūji’s 1970s avant-garde theatre and film through the study of topology. The mathematical transformation called eversion is posited as frame for Terayama’s multiple radical reversals, moving toward residual effects, a process that holds the potential for radically other performance to alter the experience of time and space. Performances of bodily intervention evert the form of theatre and elicit frustration and other affective states that generate a “transformation of theatricalized space.” The essay studies Terayama Shūji’s interest in mathematical models of eversion, or turning the inside out, and how these have influenced his work in avant-garde theatre and film, positioning the audience beyond the mere notion of “revolution” into something more complex and evocative, in which the highly scripted expectation of normative everyday life comes into question. Bodily and spatial interventions bring together viewers and performers with the purpose of transforming social life through the affects—the everting—of the particular feelings generated by the experience of the artwork.</p>

The Opinion of Russian Journalists on Professional Standards in Traditional and Digital Media

The field of journalism in Russia is undergoing continuous transformation influenced by the intricate political and legal landscape, as well as the dynamic advancements in technology and resulting social shifts. These changes disrupt established professional norms, roles, values, and practices within the journalism community. These changes disrupt established professional norms, roles, values, and practices within the journalism community. The discussion surrounding professional journalistic standards is not only prompted by the aforementioned factors but also by the gradual integration of AI technologies into everyday journalistic practices. Against this background, the author conducted a study based on 11 semi-structured interviews with the representatives of the professional community and devoted to the issues of professional identity of journalists, the boundaries of the profession and the transformation of professional standards. The study showed that despite some discrepancies in viewpoints, professionals emphasize the paramount importance of clearly defined “rules of engagement” that are comprehensible to both the journalism community and its audience. While core values remain largely unchanged, practical aspects such as formatting requirements and acceptable journalistic practices demonstrate adaptability to shifting socio-political, economic, and cultural contexts. Notably, values are consistent across traditional and new media platforms, whereas technical and practical standards exhibit greater flexibility and responsiveness to evolving norms. Ultimately, the specific standards adopted by individual editorial teams are contingent upon the media format and niche they occupy within the industry.

Quantification of EEG Characteristics for Epileptic Seizure Detection and Monitoring of Anaesthesia Using Spectral Analysis

Epilepsy is considered one of the primary neurological disorders, and its treatment requires abundant technological assistance. General Anaesthesia induces distinct patterns in brain activity, with the most common being a gradual increase in low-frequency signals as the level of Anaesthesia deepens. In this instance, a method of validating epileptic seizures and Anaesthesia through the utilization of electroencephalogram (EEG) data, acquired non-invasively, is introduced. Epileptic seizures and detection of the presence of Anaesthesia approaches make use of discrete Laplace Transformation (LT), Discrete Cosine Transformation (DCT), and Fast Fourier Transform (FFT). Here, it is discussed how power spectral analysis (PSA) helps study EEG characteristics in detecting epileptic behavior and the presence of Anaesthesia. A dataset of EEG (Epileptic and Anaesthesia), which is available publicly [1,2], has been used in the propounded technique using FIR filters and LT, DCT, and FFT are used to store and process 16 channel data. Power Spectrum Density (PSD) and its average were contrasted against a specific spectrum and frequency range of a typical EEG signal to obtain the results. This work uses a technique to determine whether the patient being studied is epileptic and awake or anesthetized.

City-forming role of the Metro in Warsaw

The article analyses the continuous transformations in the spatial development of the western part of Warsaw from 2001 to 2022. The study utilises cartographic materials and temporal analysis, considering pedestrian travel times to planned metro stations in the Bemowo district. An investment analysis of single and multi-family buildings was conducted throughout the Bemowo district and near metro stations. The analysis is based on four time intervals to determine the speed and nature of changes and their impact on land development. The selected analysis periods are 2001–2005, 2005–2010, 2010–2016, and 2016–2022. In 2022, the construction of the last section of the second metro line commenced. The results indicate that the total number of buildings constructed in Bemowo within 833 m of the metro station increased by 298 between 2001 and 2022, representing a growth of 64.5 %. During the same period, the building area increased by 1,237,405 m2, corresponding to a growth of 136.2 % relative to the existing area. The highest increase in the number of new multi-family buildings was observed after 2016, providing evidence of the alignment of the construction and the second metro line station with the transit-oriented development (TOD) concept in the western part of Warsaw.

FGeo-DRL: Deductive Reasoning for Geometric Problems through Deep Reinforcement Learning

Human-like automatic deductive reasoning has always been one of the most challenging open problems in the interdisciplinary field of mathematics and artificial intelligence. This paper is the third in a series of our works. We built a neural-symbolic system, named FGeo-DRL, to automatically perform human-like geometric deductive reasoning. The neural part is an AI agent based on deep reinforcement learning, capable of autonomously learning problem-solving methods from the feedback of a formalized environment, without the need for human supervision. It leverages a pre-trained natural language model to establish a policy network for theorem selection and employ Monte Carlo Tree Search for heuristic exploration. The symbolic part is a reinforcement learning environment based on geometry formalization theory and FormalGeo, which models geometric problem solving (GPS) as a Markov Decision Process (MDP). In the formal symbolic system, the symmetry of plane geometric transformations ensures the uniqueness of geometric problems when converted into states. Finally, the known conditions and objectives of the problem form the state space, while the set of theorems forms the action space. Leveraging FGeo-DRL, we have achieved readable and verifiable automated solutions to geometric problems. Experiments conducted on the formalgeo7k dataset have achieved a problem-solving success rate of 86.40%.

A multi‐receiver adaptive design of variable magnetic coupled structure for omnidirectional WPT system

SummaryOmnidirectional Wireless Power Transfer (OWPT) system can provide power to multiple loads in space. The different loads have different requirements for current and power levels under various operating conditions. This paper proposes a Variable Receiving Coil (VRC) structure and its control strategy. Active regulation of the output current is achieved by adjusting the geometric size of the receiving coil. Meets the power supply needs of equipment in different scenarios. This design allows the effective value of the VRC current to remain stable within the range of 1.01–1.62A (transmission distance of 22–27 cm). By adjusting the geometric transformation state of the VRC, different output currents can be obtained under fixed positions, loads, and input voltages. The designed receiver can meet the differential current requirements of multiple spatial loads, and is insensitive to factors such as load, transmission distance, and rotation angle. This system can reduce the design complexity of charging and power supply systems and effectively promote the application of Wireless Power Transfer (WPT) in the field of Internet of Things devices.

The time constant of the cerebral arterial bed: exploring age-related implications.

The time constant of the cerebral arterial bed (τ) represents an estimation of the transit time of flow from the point of insonation at the level of the middle cerebral artery to the arteriolar-capillary boundary, during a cardiac cycle. This study assessed differences in τ among healthy volunteers across different age groups.Simultaneous recordings of transcranial Doppler cerebral blood flow velocity (CBFV) and arterial blood pressure (ABP) were performed on two groups: young volunteers (below 30years of age), and older volunteers (above 40years of age). τ was estimated using mathematical transformation of ABP and CBFV pulse waveforms. 77 healthy volunteers [52 in the young group, and 25 in the old group] were included. Pulse amplitude of ABP was higher [16.7 (14.6-19.4) mmHg] in older volunteers as compared to younger ones [12.5 (10.9-14.4) mm Hg; p < 0.001]. CBFV was lower in older volunteers [59 (50-66) cm/s] as compared to younger ones [72 (63-78) cm/s p < 0.001]. τ was longer in the younger volunteers [217 (168-237) ms] as compared to the older volunteers [183 (149-211) ms; p = 0.004]. τ significantly decreased with age (rS = - 0.27; p = 0.018).τ is potentially an integrative marker of the changes occurring in cerebral vasculature, as it encompasses the interplay between changes in compliance and resistance that occur with age.

A Deformable Constraint Transport Network for Optimal Aortic Segmentation From CT Images.

Aortic segmentation from computed tomography (CT) is crucial for facilitating aortic intervention, as it enables clinicians to visualize aortic anatomy for diagnosis and measurement. However, aortic segmentation faces the challenge of variable geometry in space, as the geometric diversity of different diseases and the geometric transformations that occur between raw and measured images. Existing constraint-based methods can potentially solve the challenge, but they are hindered by two key issues: inaccurate definition of properties and inappropriate topology of transformation in space. In this paper, we propose a deformable constraint transport network (DCTN). The DCTN adaptively extracts aortic features to define intra-image constrained properties and guides topological implementation in space to constrain inter-image geometric transformation between raw and curved planar reformation (CPR) images. The DCTN contains a deformable attention extractor, a geometry-aware decoder and an optimal transport guider. The extractor generates variable patches that preserve semantic integrity and long-range dependency in long-sequence images. The decoder enhances the perception of geometric texture and semantic features, particularly for low-intensity aortic coarctation and false lumen, which removes background interference. The guider explores the geometric discrepancies between raw and CPR images, constructs probability distributions of discrepancies, and matches them with inter-image transformation to guide geometric topology in space. Experimental studies on 267 aortic subjects and four public datasets show the superiority of our DCTN over 23 methods. The results demonstrate DCTN's advantages in aortic segmentation for different types of aortic disease, for different aortic segments, and in the measurement of clinical indexes.

Combined Effect of Non-Linear Mixed Convection, and Non-Uniform Heat Source/Sink on Casson Ternary Hybrid Nanofluid Flow Across a Stretched Rotatory Disk

This present study emphasizes the importance of a specific type of fluid called a Casson ternary hybrid nanofluid. Our research explores a novel approach using the combination of several complex phenomena, including magnetohydrodynamic radiative flow, non-linear mixed convection, a non-uniform heat source or sink, a chemical reaction described by the Arrhenius model, and multiple slip effects. The researchers transformed the system of governing equations into a set of first-order ordinary differential equations using appropriate mathematical transformations and then solved them numerically using the bvp4c solver. The study investigated the behavior of velocity profiles, thermal dispersion, concentration dispersion, and heat and mass transfer for different values of the parameters involved. Our results indicated that the rising values of the heat transmission rate escalated by 2.98% for Casson ternary hybrid nanofluid when compared to ternary hybrid nanofluid. Further, ternary hybrid nanofluid had a 7.49% and 6.89% higher heat transmission rate compared to the hybrid nanofluid and conventional nanofluid, respectively. Besides, the heat transmission rate is enhanced by 17.5% and 3.11% respectively under the existence of the mixed convective and non-linear thermal convection parameters. Also, the presence of chemical reaction parameter shows a positive impact on the rate of mass transmission

Quantitative Expression of the Modified Bragg's Law for Bragg resonances of water waves excited by five types of artificial bars

For Class I Bragg resonance excited by five types of finite periodic array of widely spaced bars (rectangular, parabolic, rectified cosinoidal, trapezoidal, and triangular bars), the average phase velocity between any two adjacent bars in each type of bar field has been specifically calculated by employing a mathematical transformation, and therefore, the excitation condition of Class I Bragg resonance excited by each bar field is clarified and the modified Bragg's law established by Xie and Liu becomes a quantitative form. On one hand, if the incident surface wavelength, L, is fixed in advance, then according to the excitation condition, we can directly obtain the critical bar spacing, d, at which Class I Bragg resonance occurs. On the other hand, if the bar spacing, d, is fixed, then according to the excitation condition, we can use an iteration scheme to find out the critical surface wavelength, L, at which Class I Bragg resonance will be excited. In comparison with existing experimental, numerical, and analytical results of Bragg resonance excited by the five types of bar fields, it is shown that the modified Bragg's law is much more accurate than the Bragg's law, and the phenomenon of phase downshift can be well explained. In the linear long-wave limit, owing to the simple dispersion relation, the modified Bragg's law becomes an explicit expression and coincides with Liu's approximate law very well, although the former is a straight line segment while the latter is a curved line segment. Finally, it is shown that the phase downshift of Bragg resonance becomes more significant as the cross-sectional area of bars increases.

АНАЛІЗ СТАНУ СВІТОВОГО РИНКУ ПРАЦІ В УМОВАХ ГЛОБАЛЬНОЇ ДІДЖИТАЛІЗАЦІЇ

In the context of the Fourth Industrial Revolution, there is a continuous transformation of processes in the labor market. Digitalization of society affects the structure of the employment sector, when some professions become obsolete due to automation of work processes. At the same time, there is a demand for new competencies aimed at working in an online environment. The purpose of this article is to analyze current global economic and technological trends affecting the transformation of the labor market and the formation of new socio-economic relations in the context of the formation of the digital economy. The author draws attention to changes in the nature of work and forms of work activity, requirements for professional skills and abilities. It shows how changes related to the digitalization of the economy directly affect the issues of training and retraining of the most popular specialists. The article systematizes the main global trends in the labor market caused by the digitalization of the economy and the widespread introduction of Information Computer Technologies. In the course of the research, the author revealed that digitalization of the economy has the opposite impact on labor markets, leading to multidirectional processes in the medium term, which is expressed in the reduction of low-skilled jobs, an increase in the level of robotization of production, differentiation of forms of Organization of production, revision of types of economic relations. As a result of digital transformation in industry, it became possible to produce products with higher quality, and the human factor became less significant in many production and technology sectors. The negative consequences of digitalization include the disappearance of a large number of professions, the release of workers, and an increase in unemployment. The author concludes that digital inequality in regional labor markets, with its further development, may negatively affect ensuring the country's economic sovereignty. At the same time, the results of the study suggest that no automation can completely replace a person, so forecasting total unemployment due to the robotization of production is temporary.

RÓWNANIA POLA ELEKTROMAGNETYCZNEGO W ŚRODOWISKU NIELINIOWYM

The paper proposes electromagnetic field equations from the point of view of their adaptation to numerical methods. Maxwell's equations with partial derivatives are used, written concerning field vectors, which most fully reproduce the picture of physical processes in electrical engineering devices. The values of these vectors provide comprehensive information about the field at any spatio-temporal point. The concept of creating mathematical models of electrical devices adequate to physical processes has been developed. Mathematical transformations are carried out according to the rules of differential calculus. Dynamic processes in the elements of electrotechnical devices were analyzed using the apparatus of mathematical modeling. An algorithm for implementing differential equations with partial derivative numerical methods using computer simulation was implemented. The obtained results made it possible to understand the nature of electromagnetic phenomena in nonlinear media. The paper provides calculations of the field parameters in a flat ferromagnetic plate and the groove of the rotor of an electric machine.

Mathematical simulation of transverse cut in the fiber of a composite reinforced with unidirectional fibers with linear cohesion cracks

In the reviewed paper, the case of a transverse displacement plane with two pairs of biperiodic (corresponding to the X and Y axes) cohesive cracks of unequal size, weakened by biperiodic circular holes, is considered. The circular holes are filled with reinforcing fibers and the surface is covered with a thin homogeneous non-metallic material of the same thickness. In this case, boundary issues between filler and coating, coating and matrix, and boundary issues along cohesion cracks are determined. For both cases, the solution to the problem is sought in the form of an analytical function with complex variables. According to the boundary conditions of the case, a system of unequal algebraic equations is found along the holes, and singular integral equations are constructed along the cohesion cracks. Currently, the singular integral equations are brought to the system of finite linear algebraic equations with the help of mathematical transformations. Both systems are solved together using the Gaussian method and the crack growth is determined using the stress intensity factor formulas at the crack tips. During the solution of the problem, the stress intensity coefficients at the end are found by the variation of the length of the cracks based on the radius of the circular holes.

Development of a formula for estimated glomerular filtration rate in pregnant women from physiological hyperfiltration of serum creatinine

Increased body fluids during pregnancy complicates the application of estimated glomerular filtration rate (eGFR) formulas that are based on body surface area. Furthermore, gestational renal dysfunction cannot be identified if the serum creatinine (SCr) concentration is within the non-pregnant reference interval (RI) despite inadequate pregnancy-related renal hyperfiltration. 1484 SCr measurements from 957 healthy pregnant women were collected. The average SCr value of gestational week (GW) 0–3 was the representative SCr value of non-pregnant status. While the distribution of SCr measurements varied across GWs, it was transformed into a normal distribution using the bootstrap resampling method. A polynomial linear regression method was applied to achieve a continuous and smooth transformation of values. The normally distributed SCr values of each GW were compared to the non-pregnant status, leading to the calculation of SCr hyperfiltration. The final equation, (2 − SCr (μmol/L)/\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$/$$\\end{document}55.25)×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} 103.1 ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} 55.25/(56.7 − 0.223 ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} GW − 0.113 ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} GW2+\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$+$$\\end{document} 0.00545 ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} GW3 − 0.0000653 ×\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ imes$$\\end{document} GW4), and reference intervals for both SCr and eGFR for each GW were obtained. These RIs and novel equations can be effectively used to monitor renal dysfunction in pregnant women.

To enhance customer (or patient) experience based on IoT analytical study through technology (IT) transformation for E-healthcare

Over the past few decades, there were drastic changes in information technology across all the domains except healthcare. A new era of Information Communication Technology (ICT) has grown to higher potential by implementing eHealth systems to improve healthcare quality and simplify the problems and challenges health professionals and customer/patient have faced. The purpose of this qualitative, multiple case study was to explore information technology transformation for eHealth, which provides a broad scope to pursue research on how Information Technology (IT) strategy and implementation in eHealth using the latest technologies strategies to implement advanced eHealth systems. These strategies and implementation can provide cost-efficient and effective services to customer/patient instantly. E-Health combines medical information, public health, healthcare services, data delivery, and data security strategies through the internet using the latest web/mobile-based and big data technologies by providing simplified and instant access to customer/patient information. Due to the continuous and advanced technology transformation phase, healthcare industries are still migrating their legacy and outdated eHealth systems and applications to provide a better scope of experiences to their customer/patient. In this research, achieving effective and efficient experience is generated through IoT Sensors as it gets generalized into several different areas of classifications specific to the latest information technology trends, such as the role of smart portal technologies, cloud migration, patient data privacy and security, electronic health records (EHR), cloud infrastructures, internet of things (IoT), big data, and deep learning strategies, eHealth usability, and accessibility.