Significant Figures Research Articles

Role of structural asymmetry on the delivery of all-optical logical binary half adder in an asymmetric triple core photonic crystal fiber

This article explores the influence of structural asymmetry on the delivery of all-optical logical binary half adder function through triple-core photonic crystal fiber. For the proposed aim, the study considers different configurations of symmetric as well as asymmetric triple-core photonic crystal fiber involving optical guiding cores arranged in a planar and triangular fashion. The role of geometrical asymmetry is investigated by considering an asymmetric triple core photonic crystal fiber with a minor variation in one of the guiding core radii. Through the extinction ratio calculations, with suitable input signal combinations and control signal power, the half adder operation is demonstrated via logic outputs. The obtained results show the significant role of geometrical asymmetry indicated by the variation in the extinction ratios for the individual configurations. However, the half adder operation is found to be robust even in the presence of considerable geometrical asymmetry, with a significant figure of merit. Apart from this, a minor shift in the control signal phase is also observed between symmetric and asymmetric configurations for delivering logic gates based on the half adder function.

Sejarah Pembaharu Islam di Mesir: Jamaluddin Al-Afghani dan Muhammad Abduh

This article discusses two significant figures in the history of Egypt, namely Jamaluddin al-Afghani and Muhammad Abduh. Jamal a-Din al-Afghani and Muhammad ‘Abduh were two influential figures in the development of Islam in Egypt. Their thoughts were not only admired in Egypt but also by the Islamic generation in other countries. This research is a literature study with a historical approach. Research data were obtained from various books and articles. Based on the research results, it can be stated that Jamaludin Al-Afghani is one of the Islamic reformist figures with creative ideas to revive the spirit of the Islamic community. He is known as the initiator of the concept of Pan-Islamism. On the other hand, Muhammad Abduh is a rationalist thinker who had a significant impact on the history of Islamic thought. For Abduh, reason holds a high position in religion because through reason, humans can recognize God and understand what must be implemented.

Affective relationships with caregivers, self-efficacy, and hope of adolescents in residential care

The transition to residential care (RC) is often experienced with fear and distrust, which, associated with a feeling of punishment and abandonment, may result in pejorative attributions and self-depreciation. These feelings may reveal a greater difficulty for youth to invest in social relationships and be open to reorganizing affective bonds with alternative significant figures. Developing quality affective relationships with caregivers in residential care may work as a protective factor for the biopsychosocial development of youth. The present study aims to analyze the associations between affective relationships with caregivers and self-efficacy, and future expectations of youth in residential care, as well as to test the mediating effect of hope on the previous association. The sample included 249 youth living in residential care, aged between 12 and 18 years. The results show that the quality of affective relationships with caregivers is associated with youth self-efficacy and hopes. A partial positive mediation of hope is also found. The results are discussed considering attachment theory and its contribution to relational mechanisms to promote self-efficacy and expectations of the future of youth living in residential care. The contributions of this study to the implementation of intervention guidelines will also be discussed.

Latent Stratification for Incrementality Experiments

A method is proposed to compute more precise standard errors for marketing A/B tests.

Influence of fourth-order vibrational corrections on semi-experimental (reSE) structures of linear molecules.

Semi-experimental structures (reSE) are derived from experimental ground state rotational constants combined with theoretical vibrational corrections. They permit a meaningful comparison with equilibrium structures based on high-level abinitio calculations. Typically, the vibrational corrections are evaluated with second-order vibrational perturbation theory (VPT2). The amount of error introduced by this approximation is generally thought to be small; however, it has not been thoroughly quantified. Herein, we assess the accuracy of theoretical vibrational corrections by extending the treatment to fourth order (VPT4) for a series of small linear molecules. Typical corrections to bond distances are on the order of 10-5 Å. Larger corrections, nearly 0.0002 Å, are obtained to the bond lengths of NCCN and CNCN. A borderline case is CCCO, which will likely require variational computations for a satisfactory answer. Treatment of vibrational effects beyond VPT2 will thus be important when one wishes to know bond distances confidently to four decimal places (10-4 Å). Certain molecules with shallow bending potentials, e.g., HOC+, are not amenable to a VPT2 description and are not improved by VPT4.

Enhancing blood flow prediction in multi-exposure laser speckle contrast imaging through ensemble learning with K-mean clustering

Purpose. Accurately visualizing and measuring blood flow is of utmost importance in maintaining optimal health and preventing the onset of various chronic diseases. One promising imaging technique that aids in visualizing perfusion in biological tissues is Multi-exposure Laser Speckle Contrast Imaging (MELSCI). MELSCI technique allows real-time quantitative measurements using multiple exposure times to obtain precise and reliable blood flow data. Additionally, the application of machine learning (ML) techniques can further enhance the accuracy of blood flow prediction in this imaging modality. Method. Our study focused on developing and evaluating Ensemble Learning ML techniques along with clustering algorithms for predicting blood flow rates in MELSCI. The effectiveness of these techniques was assessed using performance parameters, including accuracy, F1-score, precision, recall, specificity, and classification error rate. Result. Notably, the study revealed that Ensemble Learning with clustering emerged as the most accurate technique, achieving an impressive accuracy rate of 98.5%. Furthermore, it demonstrated a high recall of more than 91%, F1-score, the precision of more than 90%, higher specificity of 99%, and least classification error of 1.5%, highlighting its suitability and sustainability for flow prediction in MELSCI. Conclusion. The study’s findings imply that Ensemble Learning can significantly contribute to enhancing the accuracy of blood flow prediction in MELSCI. This advancement holds substantial promise for healthcare professionals and researchers, as it facilitates improved understanding and assessment of perfusion within biological tissues, which will contribute to the maintenance of good health and prevention of chronic diseases.

This is I, Hamlet the Dane: Hamlet and Kingship in Hamlet

Hamlet is Shakespeares most famous play. Scholars have engaged in extensive debates regarding the themes of revenge and procrastination in Hamlet. However, existing research falls short in fully exploring Hamlets thoughts on kingship and his relationship with power. Despite the extensive examination of Hamlets complex character, a more in-depth analysis from this perspective is warranted. This paper, therefore, aims to further explore the connection between Hamlet and political power from three key angles. Firstly, it examines Hamlets reflections on kingship as presented through the drama and his humanistic education. Secondly, it focuses on the political aspects of Hamlets self-generated philosophical musings about life. Lastly, it conducts a deep analysis of the father-son relationship. Through a collective analysis of these three aspects, this research seeks to unravel Hamlets thoughts on kingship and their influence. It reveals how Hamlet himself and significant figures in his life, such as his father and uncle, shape his political ideology and attitudes, as well as how Hamlets self-identity shapes his understanding of kingship issues.

Ibn Khaldun: his contribution to communication science

ABSTRACT Abdul Rahman Ibn Khaldun is one of the most significant figures in the history of social sciences. He is also an outstanding thinker in the history. This article deals with the contribution of Ibn Khaldun to communication science and his pioneering works in the field of international and intercultural communication studies of the Islamic world. He is considered by many as the founder of sociology. His typology on cyclical pattern of history and his theories on political economy, demography, and environmental sciences have earned him a prominent place among the major intellectuals in the history of social thought.

Real-time synchronized monitoring for the overlap accuracy of the combining beam spot in a wavelength beam combination based on confocal planes.

Beam overlap accuracy in a wavelength beam combination system determines the beam quality and efficiency, so systematic monitoring of overlap accuracy is essential. In this work, a method of performing real-time synchronized monitoring and recording overlap accuracy for a combining beam spot is proposed. Firstly, theoretical calculations for monitoring different wavelength sub-beam positions and angular errors are established. Then, an optical design and grayscale centroid algorithm are developed to analyze and simulate the combination spots. A monitoring device was designed and constructed to meet the requirements of combining system applications, which achieved an accuracy of 8.86 µrad. Finally, the method successfully monitored the system spot fluctuation range within ±22 µrad. This study resolves the issue of distinguishing the different wavelength sub-beams and their response delays in traditional combining beams. It offers precise error data for real-time synchronized calibration of the overlap accuracy in laser beam combining technology.

The Sanjaya Myth: Sanjaya Belatthiputta and the Catuskoti

Respected modern scholars regard the pre-Buddhist philosopher Sañjaya Belaṭṭhiputta—a significant figure in the Buddhist canon—as the originator of the important classical argument- forms known as the catuṣkoṭi and catuṣkoṭi vinirmukta. We argue that the early Buddhist texts do not in fact support this view of the origin of these argument-forms; the question of their origin is open. While it is certainly true that the Pāli Sāmaññaphala Sutta and some of its parallels portray Sañjaya as deploying the catuṣkoṭi, there is nothing in these passages to suggest that he was its originator. The situation concerning the catuṣkoṭi vinirmukta is perhaps even more surprising: There is nothing in the early Pāli texts and their parallels—nor in Buddhagosa’s famous Pāli commentary on the early texts—to show that Sañjaya even deployed the catuṣkoṭi vinirmukta let alone originated it. Further, our investigations also call into question the standard portrayal of Sañjaya as an obfuscator and prevaricator. It appears he may have been a more interesting and able philosopher than the Sāmaññaphala Sutta—and modern accounts based on it—maintain.

Statistical models of the variability of plasma in the topside ionosphere: 1. Development and optimisation

This work presents statistical models of the variability of plasma in the topside ionosphere based on observations made by the European Space Agency’s (ESA) Swarm satellites. The models were developed in the “Swarm Variability of Ionospheric Plasma” (Swarm-VIP) project within the European Space Agency’s Swarm+4D-Ionosphere framework. The configuration of the Swarm satellites, their near-polar orbits and the data products developed, enable studies of the spatial variability of the ionosphere at multiple scale sizes. The statistical modelling technique of Generalised Linear Modelling (GLM) was used to create models of both the electron density and measures of the variability of the plasma structures at horizontal spatial scales between 20 km and 100 km. Despite being developed using the Swarm data, the models provide predictions that are independent of these data. Separate models were created for low, middle, auroral and polar latitudes. The models make predictions based on heliogeophysical variables, which act as proxies for the solar and geomagnetic processes. The first and most significant term in the majority of the models was a proxy for solar activity. The most common second term varied with the latitudinal region. This was the Solar Zenith Angle (SZA) in the polar region, a measure of latitude in the auroral region, solar time in the mid-latitude region and a measure of latitude in the equatorial region. Other, less significant terms in the models covered a range of proxies for the solar wind, geomagnetic activity and location. In this paper, the formulation, optimisation and evaluation of these models are discussed. The models show very little bias, with a mean error of zero to two decimal places in 14 out of 20 cases. The models capture some, but not all, of the trends present in the data, with Pearson correlation coefficients of up to 0.75 between the observations and the model predictions. The models also capture some, but not all, of the variability of the ionospheric plasma, as indicated by the precision, which ranged between 0.20 and 0.83. The addition of the thermospheric density as an explanatory variable in the models improved the precision in the polar and auroral regions. It is suggested that, if the thermosphere could be observed at a higher spatial resolution, then even more of the variability of the plasma structures could be captured by statistical models. The formulation and optimisation of the models are presented in this paper. The capability of the model in reproducing the expected climatological features of the topside ionosphere, in supporting GNSS-based ionospheric observations and the performance of the model against the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM), are provided in a companion paper (Spogli L et al. 2024. J Space Weather Space Clim https://doi.org/10.1051/swsc/2024003).

Static palpation ain't easy: Evaluating palpation precision using a topographical map of the lumbar spine as a reference.

Clinicians commonly use manual therapy to treat low back pain by palpating the spine to identify the spinous processes. This study aims to evaluate the ability of experienced clinicians to consistently locate the spinous processes from S1 to T12 through palpation. The results will be compared to topographical data representing the lumbar lordosis at baseline and four follow-up time points. In a prior prospective randomized trial, experienced clinicians used palpation to locate the lumbar spinous processes (S1-T12) and then digitized these locations in three-dimensional space. The same digitizing equipment was then used to continuously collect three-dimensional position data of a wheel that rolled along the back's surface through a trajectory that connected the previously digitized locations of the spinous processes. This process was repeated at 4 days, 1, 4, and 12 weeks. The resulting lordosis trajectories were plotted and aligned using the most anterior point in the lordosis to compare the locations of the spinous processes identified in different trials. This way, spinous palpation points could be compared to surface topography over time. Intra- and interrater reliability and agreement were estimated using intraclass correlations of agreement and Bland-Altman limits of agreement. Five clinicians palpated a total of 119 participants. The results showed a large degree of variation in precision estimates, with a mean total value of 13 mm (95%CI = 11;15). This precision error was consistent across all time points. The smallest precision error was found at L5, followed by S1 File, after which the error increased superiorly. Intra- and interrater reliability was poor to moderate. Comparison of palpation results to a topographic standard representing the lumbar lordosis is a new approach for evaluating palpation. Our results confirm the results of prior studies that find palpation of lumbar spinous processes imprecise, even for experienced clinicians.

Energy-Efficient Spectral Analysis of ECGs on Resource Constrained IoT Devices.

Power spectral analysis (PSA) is one of the most popular and insightful methods, currently employed in several biomedical applications, aiming to identify and monitor various health related conditions. Among the most common applications of PSA is heart rate variability (HRV) analysis, which allows the extraction of further insights compared with conventional time-domain methods. Unfortunately, existing PSA approaches exhibit high computational complexity, hindering their execution on power-constrained embedded internet of things (IoT) devices. Such IoT devices are increasingly used for monitoring various conditions mainly by processing the input signals in the less complex time-domain. In this paper, a new low-complexity PSA system based on fast Gaussian gridding (FGG) is proposed, which can be used to calculate the Lomb-Scargle periodogram (LSP) of a non-uniformly spaced RR tachogram. The proposed approach is implemented on a popular ARM Cortex-M4 based embedded system, which is widely used in common wearables, and compared with conventional LSP-based approaches. Utilizing this experimental setup, a meticulous analysis is performed in terms of power, performance and quality under different operational settings, such as the total input/output samples, precision of computations, computer arithmetic (floating/fixed-point), and clock frequency. The experimental results show that the proposed FGG-based LSP approach, when specifically optimized for the targeted embedded device, outperforms existing approaches by up-to 92.99% and 91.70% in terms of energy consumption and total execution time respectively, with minimal accuracy loss.

Шмелев в СССР. (Статья вторая: издания и рецепция в послевоенный период)

The article examines the history of the publication and reception of I.S. Shmelev’s works in the USSR from the point of view of his emigrant status after the Great Patriotic War. In the after-war decade, Shmelev practically disappeared not only from the readers’ but also from the research area. He is not considered a figure of sufficient significance in the literary process, even in the fundamental academic “History of Russian Literature.” Only in 1957, Shmelev’s first book with a preface by B.V. Mikhailovsky was published in the USSR after a long break, and then two more collections prepared by O.N. Mikhailov (in 1960 and 1966), which gradually filled in the gaps in educational and academic works. Shmelev’s works entered the scholarly interpretation of the literary process as full-fledged components only in the 1970s, but this applies only to the pre-revolutionary period. The complete description of the emigrant period is still a few pages in the preface by O.N. Mikhailov (1966). In 1957–1966, Shmelev was published but practically not studied, and in the 1970s and early 1980s, Shmelev was studied but not published. Only since 1988 Shmelev’s books begin to be published in the USSR one after another. A new stage of his “presence” in his homeland begins, during which his emigre works first rose to the level of pre-revolutionary works and then came forward.

A novel Approach for Audio-based Video Analysis via MFCC Features

The video analysis is a momentous task of computer vision where larger videos are analyzed and converted to comparatively shorter summaries with key-frames satisfying a typical criterion. However, in the recent times audio-based video analysis is an important field where, audio features are used to categorize video frames into various classes. In this work, we present an audio-based video analysis model named as ABVS. The proposed approach employs 40 MFCC audio features from input audios to learn a multiclass classifier. The ABVS model is trained on ANN, SVM, KNN, DT and a majority voting ensemble to categorize a given video based on audio at high precision and low error rate. Our proposed approach is trained and validated on a benchmark urbansound8k dataset with an accuracy of 90% and loss of 0.10 on ANN and SVM model whereas, KNN achieves an accuracy of 89%. The ABVS model can be deployed in real-time applications to extract key-frames from the video scenes to troubleshoot the malfunctioning of critical infrastructure in industrial sectors. Our proposed model may be deployed in audio forensics for criminal voice investigation.

Reporting Practices of Serum Protein Electrophoresis in Pakistan - a Multicenter Survey.

Serum Protein Electrophoresis (SPE) is crucial for the diagnosis and follow-up of monoclonal gammopathy (MG), as it helps to separate and identify these paraproteins. Currently, Pakistan lacks standardized guidelines for SPE reporting and analytical performance. This survey aims to analyze reporting variations from Consultant Chemical Pathologists in Pakistani laboratories. This cross-sectional survey was conducted by the section of Chemical Pathology, Department of Pathology and Laboratory Medicine, at Aga Khan University Hospital, Karachi. A previously validated and published tool was used with some modifications to assess analytical techniques, reporting patterns, and interpretations provided with SPE by different laboratories. Frequency and percentages were calculated for each response and descriptive results were also evaluated. Differences between laboratories were also assessed qualitatively. Out of the eight laboratories contacted, seven participated in the survey, yielding a response rate of 87.5%. Immunofixation Electrophoresis (IFE) was used by all labs for serum immunotyping. All labs reported a new small abnormal band in patients with no known monoclonal gammopathy or with a known M-protein. Variations were found in terminologies used to label paraprotein, terminologies used to report normal and pathological SPE patterns, electrophoretic technique, methods for quantifying paraprotein in the gamma region on SPE and for albumin quantification. Similarly, the number of decimal places reported, reporting of multiple monoclonal proteins and small paraprotein in the beta region or monoclonal proteins less than 1 g/L, approach for screening, number of fractions reported in gamma region and reporting of interferences were also not standardized and var-iations were noticed. Our survey highlighted variations in practices of SPE reporting. These differences in laboratory practices could result in inconsistent test results, which could adversely affect patient care.

A METHOD FOR EMPIRICAL ESTIMATION OF PLANCK’S LENGTH, MASS, AND TIME THROUGH THE CHARACTERISTICS OF AN ELECTRON. IMPROVING THE ACCURACY OF SOME PHYSICAL CONSTANTS

A method for empirical estimation of Planck's length, mass, and time is proposed, which is based on the characteristics of the electron, Avogadro, and Euler numbers, and the fine structure constant. Basic physical constants can be expressed in terms of Planck's length, mass, and time. The disadvantage of this method is that Planck's elementary particle does not exist in nature. Planck's particle is presented in a hypothetical, virtual form, its characteristics are theoretically calculated through the reduced Planck's constant, Newton's gravitation constant, and the constant speed of light in a vacuum, and the accuracy of these characteristics is low. This is due to the low accuracy of the Newtonian constant of gravity. This shortcoming can be eliminated if the characteristics of the hypothetical Planck particle are associated with a real elementary particle, for example, with an electron, and through its characteristics with the characteristics of leptons and baryons. Since the characteristics of leptons and baryons are determined experimentally and are among the most accurate, for example, for a proton now is 11 decimal places, establishing a connection with them of a hypothetical Planck particle will increase the accuracy of the values: of Planck's length, mass and time, of Planck constant, of elementary electric charge, of the Newtonian gravitational constant, of electron mass, of Planck temperature up to the accuracy level of a proton. As is known, the 26th General Conference on Weights and Measures decided to define one of the basic SI units of measurement through physical constants. In particular, with this solution, the kilogram is now defined in terms of Planck's constant, and the ampere is now determined in terms of the value of the elementary electric charge. Accordingly, with increasing accuracy of the values of Planck's constant and elementary electric charge, the accuracy of the values of a kilogram and Ampere will increase.

Refractive-index and density-matched emulsions with programmable DNA interactions.

Emulsion droplets on the colloidal length scale are a model system of frictionless compliant spheres. Direct imaging studies of the microscopic structure and dynamics of emulsions offer valuable insights into fundamental processes, such as gelation, jamming, and self-assembly. A microscope, however, can only resolve the individual droplets in a densely packed emulsion if the droplets are closely index-matched to their fluid medium. Mitigating perturbations due to gravity additionally requires the droplets to be density-matched to the medium. Creating droplets that are simultaneously index-matched and density-matched has been a long-standing challenge for the soft-matter community. The present study introduces a method for synthesizing monodisperse micrometer-sized siloxane droplets whose density and refractive index can be precisely and independently tuned by adjusting the volume fraction of three silane precursors. A systematic optimization protocol yields fluorescently labeled ternary droplets whose densities and refractive indexes match, to the fourth decimal place, those of aqueous solutions of glycerol or dimethylsiloxane. Because all of the materials in this system are biocompatible, we functionalize the droplets with DNA strands to endow them with programmed inter-droplet interactions. Confocal microscopy then reveals both the three-dimensional structure and the network of droplet-droplet contacts in a class of self-assembled droplet gels, free from gravitational effects. This experimental toolbox creates opportunities for studying the microscopic mechanisms that govern viscoelastic properties and self-assembly in soft materials.

Error Model and Concise Temporal Network for Indirect Illumination in 3D Reconstruction.

3D reconstruction is a fundamental task in robotics and AI, providing a prerequisite for many related applications. Fringe projection profilometry is an efficient and non-contact method for generating 3D point clouds out of 2D images. However, during the actual measurement, it is inevitable to experiment with translucent objects, such as skin, marble, and fruit. Indirect illumination from these objects has substantially compromised the precision of 3D reconstruction via the contamination of 2D images. This paper presents a fast and accurate approach to correct for indirect illumination. The essential idea is to design a highly suitable network architecture founded on a precise error model that facilitates accurate error rectification. Initially, our method transforms the error generated by indirect illumination into a sine series. Based on this error model, the multilayer perceptron is more effective in error correction than traditional methods and convolutional neural networks. Our network was trained solely on simulated data but was tested on authentic images. Three sets of experiments, including two sets of comparison experiments, indicate that the designed network can efficiently rectify the error induced by indirect illumination.

Electromagnetic Absorbing Materials Design by Optimization Using a Machine Learning Approach

One of the state-of-the-art strategies to decrease the isolation between sections of personal digital assistance devices, taking into account the unavoidable thermal, mechanical, weight, and manufacturability constraints is the proper introduction of electromagnetic (EM) absorbing materials. The global target of this study is the optimized synthesis of the EM properties of a material using a machine learning approach. The sought material must improve the shielding effectiveness between two regions of a device. The first part of this paper is dedicated to the assessment of the performances of an artificial neural network used as function approximation to compute the values of the shielding without resorting to complex and time-consuming full-wave numerical simulations. The network is assessed with respect to either the variations of the training set and algorithm or of its architecture. Significant figures of merit are introduced. The second part is devoted to the description and definition of nature-inspired algorithms demanded to manage the optimization problem.