Class Of Observables Research Articles

A hole in the nematosphere: tardigrades and rotifers dominate the cryoconite hole environment, whereas nematodes are missing

AbstractThe worldwide distribution of microinvertebrates on glaciers, the coldest biome, is poorly known. Owing to their tolerance to hostile conditions, small size and dispersal abilities, nematodes, tardigrades and rotifers are considered cosmopolitan and together inhabit various ecosystems. In this study, we investigated their global distribution in cryoconite holes – a type of freshwater reservoir forming directly in the glacial ice that creates biodiversity hotspots on glaciers. We analysed cryoconite samples (using classical microscopic observations and environmental DNA metabarcoding) from 42 glaciers located around the world (the Arctic, Subarctic, Scandinavia, the Alps, the Caucasus, Siberia, Central Asia, Africa, South America and Antarctica), as well as using literature data. Samples from Antarctic, Karakoram and the Alps were analysed using next‐generation sequencing (NGS) and classical observations under microscopes, while all other samples were analysed by microscope alone. Three general outcomes were found: (1) tardigrades and rotifers represented the most common invertebrates in cryoconite holes; (2) tardigrades and rotifers often coexisted together, with one or the other dominating, but the dominant taxon varied by region or by glacier; (3) nematodes – the most abundant, hyperdiverse and widespread metazoans on Earth, including in environments surrounding and seeding glacial surfaces – were consistently absent from cryoconite holes. Despite the general similarity of environmental conditions in cryoconite holes, the distribution of tardigrades and rotifers differed among glaciers, but not in any predictable way, suggesting that their distribution mostly depended on the random dispersal, extreme changes of supraglacial zone or competition. Although nematodes have been found in supraglacial habitats, cryoconite hole environments seem not to provide the necessary conditions for their growth and reproduction. Lack of physiological adaptations to permanently low temperatures (~0°C) and competition for different food resources in the cryoconite hole environment may explain the absence of nematodes in cryoconite holes.

Model Reference Adaptive System with Finite-Set for Encoderless Control of PMSGs in Micro-Grid Systems

In micro-grid systems, wind turbines are essential power generation sources. The direct-driven surface-mounted permanent-magnet synchronous generators (SMPMSGs) in variable-speed wind generation systems (VS-WGSs) are promising due to their high efficiency/power density and the avoidance of using a gearbox, i.e., regular maintenance and noise are averted. Usually, the main goal of the control system for SMPMSGs is to extract the maximum available power from the wind turbine. To do so, the rotor position/speed of the SMPMSG must be known. Those signals are obtained by the help of an incremental encoder or speed transducer. However, the system reliability is remarkably reduced due to the high failure rate of these mechanical sensors. To avoid this problem, this paper presents a model reference adaptive system with finite-set (MRAS-FS) observer for encoderless control of SMPMSGs in VS-WGSs. The motif of the presented MRAS-FS observer is taken from the direct-model predictive control (DMPC) principle, where a certain number of rotor position angles are utilized to estimate the stator flux of the SMPMSG. Subsequently, a new optimization criterion (also called quality or cost function) is formulated to select the best rotor position angle based on minimizing the error between the estimated and reference value of the stator flux. Accordingly, the traditional fixed-gain proportional-integral regulator generally employed in the classical MRAS observers is not needed. The proposed MRAS-FS observer is validated experimentally, and its estimation response has been compared with the conventional MRAS observer under different conditions. In addition to that, the robustness of the MRAS-FS observer is tested at mismatches in the parameters of the SMPMSG.

Eikonal phase matrix, deflection angle, and time delay in effective field theories of gravity

The eikonal approximation is an ideal tool to extract classical observables in gauge theory and gravity directly from scattering amplitudes. Here we consider effective theories of gravity where in addition to the Einstein-Hilbert term we include nonminimal couplings of the type ${R}^{3}$, ${R}^{4}$ and FFR. In particular, we study the scattering of gravitons and photons of frequency $\ensuremath{\omega}$ off heavy scalars of mass $m$ in the limit $m\ensuremath{\gg}\ensuremath{\omega}\ensuremath{\gg}|\stackrel{\ensuremath{\rightarrow}}{q}|$, where $\stackrel{\ensuremath{\rightarrow}}{q}$ is the momentum transfer. The presence of nonminimal couplings induces helicity-flip processes which survive the eikonal limit, thereby promoting the eikonal phase to an eikonal phase matrix. We obtain the latter from the relevant two-to-two helicity amplitudes that we compute up to one-loop order, and confirm that the leading-order terms in $\ensuremath{\omega}$ exponentiate \`a la Amati, Ciafaloni and Veneziano. From the eigenvalues of the eikonal phase matrix we then extract two physical observables, to 2PM order: the classical deflection angle and Shapiro time delay/advance. Whenever the classical expectation of helicity conservation of the massless scattered particle is violated, i.e., the eigenvalues of the eikonal matrix are nondegenerate, causality violation due to time advance is a generic possibility for small impact parameter. We show that for graviton scattering in the ${R}^{4}$ and FFR theories, time advance is circumvented if the couplings of these interactions satisfy certain positivity conditions, while it is unavoidable for graviton scattering in the ${R}^{3}$ theory and photon scattering in the FFR theory. The scattering processes we consider mimic the deflection of photons and gravitons off spinless heavy objects such as black holes.

The frequency of collapse as a predictor of feline blastocyst quality

Domestic cats are frequently used as a research model for felid species that are threatened with extinction. Until now, the development of feline embryos has been evaluated using both classical observation methods and time-lapse monitoring (TLM). Blastocyst collapse observed using time-lapse cinematography is used as a predictor of blastocyst quality and is closely related to implantation potential. The aim of this study was to determine the relationship between the quality of domestic cat blastocysts obtained after in vitro fertilization and the frequency and duration of collapse, and of hatching.There was a significant difference in the average number of collapses and weak contractions between good and poor quality blastocysts. There was no significant difference between hatching and non-hatching blastocysts in terms of blastocyst cavity formation time or average number and duration of collapse.These results showed that the time of cavity formation was not related to blastocyst quality. The number of collapses and the occurrence of hatching were positively related to blastocyst quality, and poor quality blastocysts have, as a consequence, a reduced potential for implantation. TLM plays a significant role in cat embryo evaluation.

Observer-based event-triggered fixed-time control for nonlinear system with full-state constraints and input saturation

This paper investigates the continuous composite control scheme for the tracking of nonlinear system with mismatched disturbances, input saturation and full-state constraints. Based on the fixed-time stability theory, a novel fixed-time disturbance observer is proposed, which switches from a uniform second-order sliding mode observer with high-degree term to the classical continuous super-twisting observer. Then, a command filtered backstepping control scheme is designed to enforce the tracking error into a small neighbourhood of the origin in fixed time while the full-state constraint and input saturation constraint are satisfied. To further reduce the communication burden, an event-triggered communication strategy between the controller and the actuator input is also developed. Furthermore, all the signals in the closed-loop system are proven to be bounded. Finally, the effectiveness of the proposed control strategy is illustrated by numerical simulations.

Sensorsless Electrostatic Suspension System Based on Observer Controller

This paper introduces a new type of active electrostatic suspension system without using position sensors. The concept is to design a feedback controller without using position signals of the object instead using the voltage signals. In the working process of the electrostatic suspension system, the capacitance formed between the electrode and the suspended object is treated as a capacitor of two parallel plates, and if the gap length between them is changed the capacitance is then changed. This causes to change the voltage across the capacitance formed between the electrode and suspended object. This voltage is measured, and it then is used to estimate all variables of the system that are the displacement, velocity of the suspended object, and voltage across the capacitance formed. These estimated values are employed in the feedback schema instead of actual states values. The design of the controller follows the classical observer state-space approach. First, a state feedback controller is constructed with the assumption that all the state variables of the suspension system that are displacement, velocity of the suspended object, and voltage across the capacitance formed by the electrodes and the suspended object, are available for feedback. Second, a full observer is designed for estimating all the states from the measured voltage across the capacitance. Finally, the estimated signals produced by the full observer are used in the feedback controller instead of the actual states, and the self-sensing electrostatic suspension without using position sensors is achieved. The experimental and simulation results show that the suspended object successfully levitated at reference gap without using position sensors.

A Fractional High-Gain Nonlinear Observer Design—Application for Rivers Environmental Monitoring Model

The deterioration of current environmental water sources has led to the need to find ways to monitor water quality conditions. In this paper, we propose the use of Streeter–Phelps contaminant distribution models and state estimation techniques (observer) to be able to estimate variables that are very difficult to measure in rivers with online sensors, such as Biochemical Oxygen Demand (BOD). We propose the design of a novel Fractional Order High Gain Observer (FOHO) and consider the use of Lyapunov convergence functions to demonstrate stability, as it is compared to classical extended Luenberger Observer published in the literature, to study the convergence in BOD estimation in rivers. The proposed methodology was used to estimated Dissolved oxygen (DO) and BOD monitoring of River Culiacan, Sinaloa, Mexico. The use of fractional order in high-gain observers has a very effective effect on BOD estimation performance, as shown by our numerical studies. The theoretical results have shown that robust observer design can help solve problems in estimating complex variables.

Clasmatosis in Sea Star Immune Responses Observed in T.E.M Invertebrate Antibody. Biosynthesis in Anti-Hrp Responses And In Anti-Alkaline Phosphatase Responses

Anti-HRP (Horse-radish peroxydase) and Anti-Alkalin phosphatase immunocytochemical responses occur in Asterina gibbosa (Asterid Echinodermata) after immunizations to HRP and, on the other hand to Alkalin phosphatase enzymes. Classical TEM observations from ergastoplasmic labelling to Golgi apparatus one were done : they shown also “clasmatosis phenomenon” and recall , in a general way invertebrate antibody biosynthesis.

Downward continuation of gravitational field quantities to an irregular surface by spectral weighting

In geophysical and geodetic studies, gravity inversion is typically performed such that observed gravity values are first continued downward onto a regular (planar, spherical or spheroidal) surface by solving an inverse integral transform, which originates from a classical solution to the first boundary-value problem in potential theory. A typical example is continuing gravity observed at the topographic surface down to the mean sea level (geoid). Nowadays, gravity-dedicated satellite missions and aerial gravimetry provide gravity data above the topographic surface in addition to classical terrestrial gravity observations. For specific purposes (such as gravity data combination and validation, or quasigeoid determination), satellite and aerial gravity observations have to be continued to the irregular topographic surface. In this study, we address this issue by formulating a functional model for a spectral downward continuation of selected gravitational field quantities to an irregular topographic surface. Moreover, we generalize this functional model to allow for transformation between different types of gravitational field quantities. In particular, we derive spectral weights for estimation of the disturbing potential or disturbing/anomalous gravity at the Earth’s surface by combining the first-, second- and third-order radial gradients of the disturbing potential (disturbing gradients). The correctness of the developed combined spectral estimator is verified in a closed-loop test based on synthetic satellite disturbing gradients. The combined spectral estimator is applied to simulated satellite disturbing gradients polluted by a realistic Gaussian noise. Results of the numerical experiments show that the combined spectral estimator puts the highest importance on the least polluted disturbing gradient, while the contribution of the least accurate disturbing gradient is negligible. An important advantage of this spectral combination method is that no matrix inversion with numerical instabilities requiring regularization is needed.

Determination of twinning path from broken symmetry: A revisit to deformation twinning in bcc metals

Deformation twinning in crystals is one of the major strain carrier during plastic deformation, which plays a critical role in determining the mechanical properties of metals and alloys. One of the key issues to understand deformation twinning mechanisms is the determination of deformation path, which is critical for the calculations of twinning strain and critical shear stress. This work provides a new perspective on deformation twinning by systematically investigating the relationship between symmetry breaking and deformation path, with the purpose of establishing a theoretical foundation to identify the broken symmetries associated with twinning and predicting the twinning modes using group theory and graph theory. From a physical point of view, deformation twins can be regarded as one type of the so-called topological defects that are induced by symmetry-breaking. Taking BCC crystals as an example, we demonstrate how the presence of intermediate high symmetry states in the deformation strain space (strain calculated through lattice distortion) along the twinning path, such as FCC, HCP or orthorhombic state, can lead to different characteristic twinning modes. Our predictions not only agree well with classical theoretical analyses and experimental observations in BCC metals and alloys, but also reveal the origin of recently observed high-index twinning modes (such as {5 8 11} and {3 9 10} twins). This work may open a new avenue for analyzing deformation twinning through the symmetry breaking along twinning pathways.

Comparison of traditional ground-based observations and digital remote sensing of phenological transitions in a floodplain forest

Phenological observations are important as indicators of global warming and as estimation tools for the terrestrial carbon balance in vulnerable ecosystems, such as the last fragments of floodplain forests in the Czechia. The aim of this paper was to compare ground-based phenological observations of three dominant species (European hornbeam, English oak and narrow-leaved ash) in this ecosystem, with the seasonal trajectory of the greenness index (Gcc) and thresholds extracted from images taken by phenocameras located on a meteorological mast. The average annual air temperature in the studied years 2014–2017 was 1 °C higher than the long-term average, and the precipitation deficit reached ⅓ of annual rainfall. We found a high proportion of above-average warm days in the warmest part of the growing season. Above-average air temperatures significantly accelerated the onset of budbreak in ash. Yet a higher proportion of above-average air temperatures prolonged the period between budbreak to fully developed leaf area, especially in ash and oak. In 2017, rapid cooling after exceptionally warm temperatures at the onset of spring had a detrimental effect on the stand productivity and showed a marked effect on the phenological shifts. The period when leaf area developed was in the range of DOY 66-286 for hornbeam, DOY 79-329 for oak and DOY 88-321 for ash in 2014–2017. The seasonal trajectory of Gcc showed differences between tree species that corresponded to the dynamics of the onset of phenophases observed in the field. According to image analyses, the phenophase of greenup and maturity for hornbeam and ash had minimal uncertainty. In contrast, the uncertainty was high in the determination of phenophases for oak. Our observations show that the modern method of phenological observation by phenocameras is suitable for mixed forests, but classical ground-based observations by a phenologist are still crucial in order to verify the results.

Uncovering the intricacies of microbial community dynamics at Helgoland Roads at the end of a spring bloom using automated sampling and 18S meta-barcoding.

In May 2016, the remote-controlled Automated Filtration System for Marine Microbes (AUTOFIM) was implemented in parallel to the Long Term Ecological Research (LTER) observatory Helgoland Roads in the German Bight. We collected samples for characterization of dynamics within the eukaryotic microbial communities at the end of a phytoplankton bloom via 18S meta-barcoding. Understanding consequences of environmental change for key marine ecosystem processes, such as phytoplankton bloom dynamics requires information on biodiversity and species occurrences with adequate temporal and taxonomic resolution via time series observations. Sampling automation and molecular high throughput methods can serve these needs by improving the resolution of current conventional marine time series observations. A technical evaluation based on an investigation of eukaryotic microbes using the partial 18S rRNA gene suggests that automated filtration with the AUTOFIM device and preservation of the plankton samples leads to highly similar 18S community profiles, compared to manual filtration and snap freezing. The molecular data were correlated with conventional microscopic counts. Overall, we observed substantial change in the eukaryotic microbial community structure during the observation period. A simultaneous decline of diatom and ciliate sequences succeeded a peak of Miracula helgolandica, suggesting a potential impact of these oomycete parasites on diatom bloom dynamics and phenology in the North Sea. As oomycetes are not routinely counted at Helgoland Roads LTER, our findings illustrate the benefits of combining automated filtration with metabarcodingto augment classical time series observations, particularly for taxa currently neglected due to methodological constraints.

UPAYA MENINGKATKAN KETERAMPILAN MENULIS HURUF JAWA MELALUI DISKUSI KELOMPOK BERBANTU KARTU HURUF PADA PESERTA DIDIK KELAS VI SD 1 PRAMBATAN KIDUL KUDUS

The study aims to improve the student skills in writing The Javanese Script and learning activities through group discussion assisted by letter cards in the 6th-grade students of SD 1 Prambatan Kidul Kudus Even Semester Academic Year 2018/2019. This study is a Classroom Action Research (CAR) conducted in two cycles using The Javanese Script cards as the learning media and group discussion as the learning method. Research data were collected using nontest techniques (classroom observation, unstructured interviews, and documentation collection) and test techniques (individual written tests). Quantitative data were the scores of The Javanese Script writing skill were analyzed descriptively and qualitative data were the result of learning activities observations that converted into scores and categorized classically. The Pre-cycle stage test score category consisted of poor (62.16%) and fair scores (37.84%), with students had reached learning mastery standard by 37.84%. The Cycle I stage test score category consisted of poor (27.03%), fair (56.76%), and good scores (16.22%), with students had reached learning mastery standard by 72.97%. The Cycle II stage test score category consisted of fair (48.65%), good (40.54%), and very good scores (10.81%), with students had reached learning mastery standard by 100%. The classical learning activities observations are classified as good, both in Cycle I and Cycle II were 70.27% and 71.89%, respectively. Thus, the method of group discussion assisted by letter cards is proven to improve the student skills in writing The Javanese Script and learning activities.

Distributed Output-Feedback Consensus Control for Nonlinear Multiagent Systems Subject to Unknown Input Delays.

This article considers the distributed output-feedback consensus control problem for nonlinear multiagent systems subject to input delays. Different from the existing related works, the input delay of each agent is described as an unknown time-varying function and is different from each other in this article. To deal with this problem, for each follower, we first construct a novel distributed observer based on the relative output information to asymptotically estimate the state information of the leader, then we introduce a classical observer to asymptotically estimate the state information of the follower based on its output information. By means of two observers, the leader-following consensus problem is transformed into the stability problem of the nonlinear system with unknown input delays. Subsequently, the distributed controller independent of delays is proposed for each follower by the use of the truncated prediction method under some conditions. Based on the Lyapunov stability theory, it is strictly proved that the distributed controller can render all agents achieving consensus. Finally, the effectiveness of the theoretical results is illustrated on the basis of numerical simulations on a group of single-link manipulators.

Hybrid Fault Diagnosis of Bearings: Adaptive Fuzzy Orthonormal-ARX Robust Feedback Observer

Rolling-element bearings (REBs) make up a class of non-linear rotating machines that can be applied in several activities. Conceding a bearing has complicated and uncertain behavior that exhibits substantial challenges to fault diagnosis. Thus, the offered anomaly-diagnosis algorithm, based on a fuzzy orthonormal-ARX adaptive fuzzy logic-structure feedback observer, is developed. A fuzzy orthonormal-ARX algorithm is presented for non-stationary signal modeling. Next, a robust, stable, reliable, and accurate observer is developed for signal estimation. Therefore, firstly, a classical feedback observer is implemented. To address the robustness drawback found in feedback observers, a multi-structure technique is developed. Furthermore, to generate signal estimation performance and reliability, the fuzzy logic technique is applied to the structure feedback observer. Also, to improve the stability, reliability, and robustness of the fuzzy orthonormal-ARX fuzzy logic-structure feedback observer, an adaptive algorithm is developed. After generating the residual signals, a support vector machine (SVM) is developed for the detection and classification of the bearing fault conditions. The effectiveness of the proposed procedure is validated using two different datasets for single-type fault diagnosis based on the Case Western Reverse University (CWRU) vibration dataset and multi-type fault diagnosis of bearing using the Smart Health Safety Environment (SHSE) Lab acoustic emission dataset. The proposed algorithm increases the classification accuracy from 86% in the SVM-based fuzzy orthonormal-ARX feedback observer to 97.5% in single-type fault and from 80% to 98.3% in the multi-type faults.

Symplectic formulation of teleparallel gravity

Teleparallel gravity has been formulated in the symplectic-geometrical fashion. For that purpose, the symplectic potential and the pre-symplectic structure on the manifold of all solutions of the field equation of teleparallel gravity have been firstly constructed from the Lagrangian density of the theory. That the obtained pre-symplectic structure is a symplectic structure also has been proved. It has been shown that the symplectic potential obtained from the Lagrangian density up to a factor is equal to the superpotential of teleparallel gravity. The Hamiltonian formulation of teleparallel gravity has been derived. Furthermore, the Poisson bracket between arbitrary two classical observables (i.e. real-valued functional) defined on the symplectic manifold of all solutions of the field equation of teleparallel gravity has constructed. The Hamiltonian vector field associated to an observable has been obtained. The formulation of Noether theorem in the symplectic formulation of teleparallel gravity has been investigated.

Complete Hamiltonian for spinning binary systems at first post-Minkowskian order

Building upon recent progress in applying on-shell amplitude techniques to classical observables in general relativity, we propose a closed-form formula for the conservative Hamiltonian of a spinning binary system at the 1st post-Minkowskian (1PM) order. It is applicable for general compact spinning bodies with arbitrary spin multipole moments. The formula is linear in gravitational constant by definition, but exact to all orders in momentum and spin expansions. At each spin order, our formula implies that the spin-dependence and momentum dependence factorize almost completely. We expand our formula in momentum and compare the terms with 1PM parts of the post-Newtonian computations in the literature. Up to canonical transformations, our results agree perfectly with all previous ones. We also compare our formula for black hole to that derived from a spinning test-body near a Kerr black hole via the effective one-body mapping, and find perfect agreement.

Classical and Nonclassical Time Dilation for Quantum Clocks

Proper time, ideal clocks, and boosts are well understood classically, but subtleties arise in quantum physics. We show that quantum clocks set in motion via momentum boosts do not witness classical time dilation. However, using velocity boosts we find the ideal behavior in both cases, where the quantum clock and classical observer are set in motion. Without internal state-dependent forces additional effects arise. As such, we derive observed frequency shifts in ion trap atomic clocks, indicating a small additional shift, and also show the emergence of nonideal behavior in a theoretical clock model.

Positive observers for linear positive systems in a Hilbert lattice space

Abstract In this work, we investigate the question of designing a positive observer for a class of infinite dimensional linear positive systems. We present a new observer design based on a classical Luenberger-like observer. The proposed observer is positive. That is, it ensures that the state estimates are nonnegative at any time. The existence of such positive observers is proven by a specific choice of the observer gain and using positive bounded perturbation results. We show in particular that the error of the state estimation converges exponentially to zero. Finally, the main result is applied to an isothermal tubular (bio) reactor model, namely the plug-flow (bio) reactor model. The approach is illustrated by some numerical simulations.

The Classification of OECD Countries in Terms of Life Satisfaction Using Partial Least Squares Discriminant Analysis

Life satisfaction (LS) measures how people assess their lives as a whole, not their present emotions. Measuring emotions can be very subjective, but it is still a useful completion to more objective data when comparing quality of life across countries. Many questionnaires are used to measure especially LS and happiness. The Partial Least Squares Discriminant Analysis (PLSDA) is a statistical method for classification and includes an ordinary Partial Least Squares Regression, where the dependent variable is categorical that represents each observation's class membership. In this study, the purpose is to classify 35 OECD countries correctly to their predefined classes (above or below the average LS level of OECD) by using year 2017 Better Life Index data. In the analyses PLSDA, a flexible supervised classification method, is used. PLSDA is a preferable alternative method in case of some assumptions not satisfied for classical discriminant analysis. The results showed that PLSDA has a satisfying classification performance and self-reported health (SH) is only effective variable in determining the LS levels of countries