Extreme Dimensions Research Articles

Extreme fractal dimension at periodicity cascades in parameter spaces.

In the parameter spaces of nonlinear dynamical systems, we investigate the boundaries between periodicity and chaos and unveil the existence of fractal sets characterized by a singular fractal dimension that deviates greatly from the fractal sets in their vicinity. This extreme fractal dimension stands out from the typical value previously considered universal for these parameter boundaries. We show that such singular fractal sets dwell along parameter curves, called extreme curves, that intersect periodicity cascades at their centers of stability across all scales of parameter spaces. The results reported here are generally demonstrated for the class of one-dimensional maps with at least two control parameters. Generalizations to other classes of systems are possible.

Analysis of the Dimensional and Shape Accuracy and Repeatability of Models Produced in the Process of Additive Extrusion of Thermoplastic Polymers Using Fused Filament Fabrication Technology

To achieve high precision and repeatability of prototyped models, work is carried out to improve existing solutions and thus expand the areas of application of 3D printers. Ways to increase the efficiency of 3D printing are being sought. The subject of the work concerns the analysis of dimensional and shape accuracy and repeatability of samples produced by a technology based on layered extrusion of thermoplastic polymers using FFF—fused filament fabrication technology. The key parameter for assessing the quality of parts is the property most expected by 3D printer users regarding the accuracy of dimensions of manufactured prototypes. As part of the research, conclusions were drawn regarding the precision of the samples as original patterns. The dimensional accuracy in the x, y, and z axes of the 3D printer was determined in terms of the design of the 3D printer’s actuator system. Three-dimensional maps of deviations of the pattern surface were used in relation to the nominal 3D CAD model to test the accuracy. The analytical results obtained during the research work, together with the graphs of the normal distribution probability function, indicate a high repeatability for each of the axes, and the highest repeatability was for the z-axis. The dimensions in the remaining axes were within the assumed tolerance of 0.1 mm, except for the two extreme dimensions, which were caused by a different method of heat dissipation, proving the influence of the arrangement of samples on the working platform.

Community childhood obesity assessment in elementary school, anthropometric indices as screening tools: a community cross-sectional study in Indonesia

BackgroundRepresentative anthropometric epidemiological data are needed to formulate screening and intervention methods to prevent obesity in children. This study aims to conduct community childhood obesity assessment in elementary school based...

Hyperspectral image classification method based on semantic filtering and ensemble learning

The imbalance between limited training samples and extreme high spectral dimensions is a challenge for hyperspectral image classification. To significantly improve the classification of hyperspectral images in the case of small samples, we proposed a novel hyperspectral image classification method based on semantic filtering and ensemble learning. Semantic filtering synergistically combines the efficiency of the recursive filter and the effectiveness of the recent edge detector for scale-aware edge-preserving filtering, which can efficiently extract subjectively meaningful structures from natural scenes containing multiple-scale objects. Ensemble learning is used to fuse multi-scale features and to enhance the information-rich features. Experiments on three data sets prove that both semantic information and ensemble learning can improve classification accuracy, and their combination obtained the state-of-the-art performance.

Mechanically-Guided 3D Assembly for Architected Flexible Electronics.

Architected flexible electronic devices with rationally designed 3D geometries have found essential applications in biology, medicine, therapeutics, sensing/imaging, energy, robotics, and daily healthcare. Mechanically-guided 3D assembly methods, exploiting mechanics principles of materials and structures to transform planar electronic devices fabricated using mature semiconductor techniques into 3D architected ones, are promising routes to such architected flexible electronic devices. Here, we comprehensively review mechanically-guided 3D assembly methods for architected flexible electronics. Mainstream methods of mechanically-guided 3D assembly are classified and discussed on the basis of their fundamental deformation modes (i.e., rolling, folding, curving, and buckling). Diverse 3D interconnects and device forms are then summarized, which correspond to the two key components of an architected flexible electronic device. Afterward, structure-induced functionalities are highlighted to provide guidelines for function-driven structural designs of flexible electronics, followed by a collective summary of their resulting applications. Finally, conclusions and outlooks are given, covering routes to achieve extreme deformations and dimensions, inverse design methods, and encapsulation strategies of architected 3D flexible electronics, as well as perspectives on future applications.

The specious art of single-cell genomics.

Dimensionality reduction is standard practice for filtering noise and identifying relevant features in large-scale data analyses. In biology, single-cell genomics studies typically begin with reduction to 2 or 3 dimensions to produce "all-in-one" visuals of the data that are amenable to the human eye, and these are subsequently used for qualitative and quantitative exploratory analysis. However, there is little theoretical support for this practice, and we show that extreme dimension reduction, from hundreds or thousands of dimensions to 2, inevitably induces significant distortion of high-dimensional datasets. We therefore examine the practical implications of low-dimensional embedding of single-cell data and find that extensive distortions and inconsistent practices make such embeddings counter-productive for exploratory, biological analyses. In lieu of this, we discuss alternative approaches for conducting targeted embedding and feature exploration to enable hypothesis-driven biological discovery.

Comparative study of self-compassion and sense of coherence in nurses of psychiatric hospitals

Abstract Objective Nurses, due to the nature of their job, are subjected to various forms of stress and physical and psychological injuries. Self-compassion and a sense of coherence have attracted much attention in research in recent years as having high potential for improving the health and performance of people in the workplace. The present study aimed to compare self-compassion and the sense of coherence in nurses working in psychiatric hospitals and other hospitals of Kerman University of Medical Sciences. Methods The present study was a descriptive-comparative study of applied type conducted on 100 nurses of Shahid Beheshti Psychiatric Hospital in Kerman by the census method and 100 nurses of other hospitals of Kerman University of Medical Sciences by the stratified random sampling method. The instruments included the self-compassion questionnaire and the sense of coherence questionnaire. Data were analyzed using the Statistical Package for Social Sciences software. Results The results of the present study showed that self-compassion and sense of coherence were higher in psychiatric nurses (39.35 ± 7.7 and 53.02 ± 8.01) than among other nurses (36.03 ± 5.81 and 49.76 ± 6.30). There was a direct and moderate relationship between a sense of coherence and self-compassion (P-value <0.005). The higher the score of compassion for oneself, the higher was the score of sense of coherence. Furthermore, the sense of coherence had a direct and weak relationship with all dimensions of self-compassion, except for the extreme imitation dimension, which showed a direct and moderate relationship to other dimensions (P-value <0.001). Conclusions Self-compassion and a sense of coherence, as a form of self-communication, increase nurses’ satisfaction and reduce nurses’ job stress and, as a result, job performance is improved.

A bilateral branch learning paradigm for short term wind power prediction with data of multiple sampling resolutions

This paper revisits the data-driven short-term wind power prediction (WPP) modeling process with introducing a new data usage paradigm, using SCADA data of both high and low sampling resolutions as model inputs. To organically incorporate data of two sampling resolutions as inputs and tackle the extreme high dimension of features induced by using high sampling resolution data in WPP modeling, we propose a novel bilateral branch learning based WPP modeling framework, which includes two data feature engineering branches and one prediction module. One branch for processing the high sampling resolution data is developed based on a novel deep learning structure stacking multiple convolutional and sparse pooling layers as well as long short term memory networks (CNN-SP-LSTM). Another branch adopts the classical feature selection to process low sampling resolution data. The bilateral branch engineered features are concatenated as one input for the final wind power prediction. To justify the validity of the proposed WPP data usage and modeling framework, extensive computational experiments are conducted based on real wind farm SCADA data. Via analyzing computational results, we show that it is advantageous to incorporate data of the high sampling resolution into WPP tasks. Via a comprehensive comparative analytics, we identify the machine learning techniques most suitable on the feature selection and prediction module development parts of the proposed modeling framework. Via an ablation study, we verify the contribution and advantage of the proposed CNN-SP-LSTM module. Based on results of a comprehensive computational study, we verify that our proposed framework achieves the state-of-the art performance as it beats a large set of classical data-driven and recent deep learning based WPP methods considered in this study.

Correlated nanoelectronics and the second quantum revolution

The growing field of correlated nanoelectronics exists at the intersection of two established fields: correlated oxide electronics and semiconductor nanoelectronics. The development of quantum technologies that exploit quantum coherence and entanglement for the purposes of computation, simulation, and sensing will require complex material properties to be controlled at nanoscale dimensions. Heterostructures and nanostructures formed at the interface between LaAlO3 and SrTiO3 exhibit striking behavior that arises from the ability to program the conductive behavior at extreme nanoscale dimensions. The active electronic layer, SrTiO3, exhibits a wide range of gate-tunable phenomena such as ferroelectricity, ferroelasticity, magnetism, superconductivity, and spin–orbit coupling, all of which can be controlled at the nanoscale using two reversible methods: conductive atomic force microscope lithography and ultra-low-voltage electron beam lithography. Mesoscopic devices such as single-electron transistors and quasi-one-dimensional electron waveguides can be “sketched” using these techniques, and the properties of these devices differ significantly from those created from traditional semiconductors, such as Si or GaAs. The strongly correlated nature of the SrTiO3 system is evident from superconducting behavior as well as a state in which electrons are paired outside the superconducting state. A highly exotic phase was discovered in which a degenerate quantum liquid is formed from bound states of n = 2, 3, 4, … electrons. Further development of correlated nanoelectronics based on the LaAlO3/SrTiO3 system can potentially lead to a general platform for quantum simulation as well as a pathway for the development of highly entangled states of multiple photons.

Classification of Infilled Shells Structures Considering Soil-Construction Interaction

The paper examines retaining structures consisting of thin shells filled with soil or other material (in a varying degree providing structural integrity), keeping the soil from failure and sustaining the complex of technological loads. Filled shells structures serve as a constructive base for retaining structures and are used in various construction areas (industrial, transport, hydraulic engineering). The technique is proposed which allows to determine structural design model at an early design stage considering the key initial design parameters: overall dimensions of the structure, acting loads and the soil base properties. Based on the proposed ratios an example is given of the structure classification and the design model choice depending on its dimensions, depth of embedding and the magnitude of soil base design resistance. Extreme principal dimensions ratios of the structure are shown at which there is a need of fixing the structure in the soil, dependencies for determining setting depth are given.

Schönberg »beim Wort genommen«. Dimensionen seines Motiv-Begriffs und das Klavierstück op. 11,3

While it has become common practice to employ Arnold Schönberg’s theoretical terms in analyses of works of the classical style, ignoring the anachronism, they are not consequently applied to Schönberg’s own works or works of his students. Indeed, such an “historically informed” analytical approach faces considerable difficulties, especially when considering works of Schönberg’s “free atonal” period (1907–1922). That the majority of Schönberg’s theoretical works were written during later periods of his life and that comparable sources for the earlier periods are scarce is only one of the problems that such an approach faces. This article reviews Schönberg’s concept of musical “motif” and discusses its analytical applicability to the works of the “free atonal” period. It can be shown that even after the abandonment of tonality, motivic thinking continued to guide Schönberg’s compositional technique, even though it was sometimes developed to extreme dimensions. A short “motivic” analysis of the well-known piano piece op. 11,3 aims to demonstrate that in the light of this historical evidence widely used characterizations of Schönberg’s atonal works as “athematic” or their description as an “uncontrolled free style” have to be reconsidered.

Power, Symbolism and Conflict in Bafut, Cameroon

Political power and authority in the African context are a myth. It is manifested and represented in various ways including in the form of natural forces and animals. Their importance and representation vary from culture to culture and from one community to another. Each community has beliefs and myths related to animals and power systems. Animals are believed to have such exuberant energy or power that permits them to command authority and control in the jungle. Such is the case of lions and elephants. Thus there are cultural restrictions and control over these animals as paraphernalia or symbolic representation of power and authority in several African societies. Power mongers yearn to appropriate these animals or parts of their bodies in the form of totems, insignia or paraphernalia to show case their power, prestige, aura and social status. Such ventures constitute sources of friction given that the process of appropriation of the symbols may stir conflict of extreme dimension. In the late 1940s in Bafut, a conflict occurred between the Fon (traditional ruler) and some subaltern chiefs over the control and ownership of some wild animals in the area. This conflict destabilised the political system of the fondom and perpetrated disunity whose impact continues to negatively affect the fondom into the 21st century. We intend to have an in-depth examination of the conflict in this paper and from our sources, we conclude that the symbols and symbolism associated with power breeds conflict in many indigenous African communities (such as in Bafut) and efforts are needed to restore peace in these communities.

Rose petal effect: A subtle combination of nano‐scale roughness and chemical variability

AbstractRose petals may involve high water contact angles together with drop adhesion which are antagonistic wetting properties. Petal surfaces have a cuticle which is generally considered a continuous, hydrophobic lipid coating. The peculiar properties of rose petals are not fully understood and have been associated with high surface roughness at different scales. Here, the chemical and structural features of natural upper and lower petal surfaces are analyzed by atomic force microscopy (AFM). Both rose petal surfaces are statistically equivalent and have very high roughness at all scales from 5 nm to 10 μm. At the nanoscale, surfaces are fractal‐like with an extreme fractal dimension close to df = 2.5. A major nanoscale variability is also observed which leads to large (nanoscale) wettability changes. To model the effect of roughness and chemical variability on wetting properties, a single wetting parameter is introduced. This approach enables to explain the Rose petal effect using a conceptually simple scheme. The described fundamental mechanisms leading to high contact angles together with drop adhesion can be applied to any natural and synthetic surface. Apart from introducing a new approach for characterizing a biological surface, these results can trigger new developments on nanoscale wetting and bio‐inspired functional surfaces.

Increase of Adverse Events After Intravenous Injection of Gentamicin in Horses Between 2015 and 2017-From Marketing Authorization Holder's Point of View.

Between 2015 and 2017, a marked increase of anaphylactic-like reactions after intravenous administration of gentamicin was observed first in horses and, later, also in humans. This worldwide issue led to safety measures including product recalls and safety warnings. Here, a German Marketing Authorization Holder (MAH) of an early and intensely affected veterinary product containing gentamicin describes the clinical approach of the company to analyze the root cause and identify the causative agent in the active pharmaceutical ingredient (API). The pharmacovigilance data of the MAH are presented, along with pharmacovigilance phenomena observed during the affected period. An overview is given on further investigations of the API manufacturer and measures taken by all parties involved, including competent authorities to reestablish a safe use of gentamicin products. The histamine contamination of gentamicin was an exceptional incident of global extent, affecting not only veterinary but also human drug safety. The reactions in horses transpired to also be an indicator of a human health threat, which ultimately contributed to an improvement in the safety of human and veterinary medicinal products containing fermentative APIs. The extreme dimensions of this issue emphasise the important role that veterinary clinicians and practitioners play in spontaneous reporting based pharmacovigilance systems and, by this, in drug safety.

Extreme dimensions - how big (or small) can tailed phages be?

This month’s Genome Watch highlights the search for unusually large (or small) tailed phages driven by metagenomics. This month’s Genome Watch highlights the search for unusually large (or small) tailed phages driven by metagenomics.

Intermediate Assouad-like dimensions

We study a class of bi-Lipschitz-invariant dimensions that range between the box and Assouad dimensions. The quasi-Assouad dimensions and \theta -Assouad spectrum are other special examples. These dimensions are localized, like Assouad dimensions, but vary in the depth of scale which is considered, thus they provide very refined geometric information. Our main focus is on the intermediate dimensions which range between the quasi-Assouad and Assouad dimensions, complementing the \theta -Assouad spectrum which ranges between the box and quasi-Assouad dimensions. We investigate the relationship between these and the familiar dimensions. We construct a Cantor set with a non-trivial interval of dimensions, the endpoints of this interval being given by the quasi-Assouad and Assouad dimensions of the set. We study stability and continuity-like properties of the dimensions. In contrast with the Assouad-type dimensions, we see that decreasing sets in \mathbb{R} with decreasing gaps need not have dimension 0 or 1. As is the case for Hausdorff and Assouad dimensions, the Cantor set and the decreasing set have the extreme dimensions among all compact sets in \mathbb{R} whose complementary set consists of open intervals of the same lengths.

Energy-efficient flexible and fixed antenna selection methods for XL-MIMO systems

Massive multiple-input multiple-output (M-MIMO) is a key technology for 5G networks which consists on equipping the base station (BS) with hundreds or thousands of antennas. Increasing the antenna separation is paramount in order to make real advantage from an array dimension of the order of thousands of antennas. One potential approach is the integration of the antenna array into large structures, which is referred to as extra-large-scale MIMO (XL-MIMO). However, when employing extremely large arrays, centralized processing architectures face a challenging complexity. A promising solution is to divide the antenna array into disjoint units, referred to as subarrays, with individual processing units. In this paper, we modify the M-MIMO channel model aiming to take two implications of the extreme array dimensions into account: the spherical wavefronts, which is called near-field propagation, and the concentration of the majority of energy received from a specific user on a small portion of the array, namely spatial non-stationarity. Considering the latter, it is not efficient from an energy perspective to activate the antennas with lower channel gains to transmit/receive the signal to/from a given user. Thus, antenna selection methods are quite important in the considered scenario. Two antenna selection (AS) methods for XL-MIMO are proposed in this paper: the adjustable-flexible antenna selection (FAS), and the fixed subarray selection (FSS). Numerical results demonstrate that, by judiciously selecting the antennas subset used to detect the signal of each user in the uplink (UL), the number of active antennas can be reduced considerably in a scenario with up to 64 active users, reducing the power consumption without compromising the throughput. The EE is hugely increased in such scenario. Finally, the FSS scheme achieved the same performance of FAS, while having a simpler hardware implementation.

XL-MIMO energy-efficient antenna selection under non-stationary channels

Massive multiple-input-multiple-output (M-MIMO) is a key technology for 5G networks. Within this research area, new types of deployment are arising, such as the extremely-large regime (XL-MIMO), where the antenna array at the base station (BS) has extreme dimensions. As a consequence, spatial non-stationary properties appear as the users see only a portion of the antenna array, which is called visibility region (VR). In this challenging transmission–reception scenario, an algorithm to select the appropriate antenna-elements for processing the received signal of a given user in the uplink (UL), as well as to transmit the signal of this user during downlink (DL) is proposed. The advantage of not using all the available antenna-elements at the BS is the computational burden and circuit power consumption reduction, improving the energy efficiency (EE) substantially. Numerical results demonstrate that one can increase the EE without compromising considerably the spectral efficiency (SE). Under few active users scenario, the performance of the XL-MIMO system shows that the EE is maximized using less than 20% of the antenna-elements of the array, without compromising the SE severely.

Extreme Subwavelength Magnetoelastic Electromagnetic Antenna Implemented with Multiferroic Nanomagnets

AbstractAntennas typically have emission/radiation efficiencies bounded by A/λ2(A < λ2) where A is the emitting area and λ is the emitted wavelength. That makes it challenging to miniaturize antennas to extreme subwavelength dimensions without severely compromising their efficiencies. To overcome this challenge, an electromagnetic (EM) antenna is actuated with a surface acoustic wave (SAW) whose wavelength is about five orders of magnitude smaller than the EM wavelength at the same frequency. This allows to implement an extreme subwavelength EM antenna, radiating an EM wave of wavelength λ = 2 m, whose emitting area is ≈10−8 m2 (A/λ2 = 2.5 × 10−9), and whose measured radiation efficiency exceeds the A/λ2 limit by over 105. The antenna consists of magnetostrictive nanomagnets deposited on a piezoelectric substrate. A SAW launched in the substrate with an alternating electrical voltage periodically strains the nanomagnets and rotates their magnetizations owing to the Villari effect. The oscillating magnetizations emit EM waves at the frequency of the SAW. These extreme subwavelength antennas that radiate with efficiencies a few orders of magnitude larger than the A/λ2 limit allow drastic miniaturization of communication systems.

A novel approach for secured multimodal biometric authentication based on data fusion technique

The upcoming biometric technology is focusing more on multiple biometric traits to authenticate the user for security, access control and universal identity. This is because utmost considered powerful biometric when used solely, grieves from spoof attacks, intra-class erraticism, noise, vulnerability, etc. In the arena of biometrics, the integration of evidences offered by multiple biometric is considered as an effective mode of enhancing the authentication accuracy and security. This research work proposes an authentication technique for a multimodal biometric scheme using three traits, i.e., face, ear and palmprint at feature level fusion. This novel method utilises the raw data fusion technique to create unique pattern for each registered user. Even with the use of three different biometrics traits, the template is created with extreme low dimension and by using a single algorithm. The proposed system provides security with reduced computational complexity and improved robustness.