Theoretical Conditions Research Articles

Event-Triggered Antidisturbance Control Design for Aeroengine Systems via Switched Models

In this paper, an event-triggered antidisturbance (ETAD) control scheme is presented for a category of aeroengine control systems (AECSs) involved in multiple disturbances. First, an AECS in this category is described by a switched model at a series of steady-state points. Then, a dynamic event-triggered mechanism is introduced by constructing the ET condition based on the control input directly, saving the signal transmission resource from the controller to the AECS. Next, a switching law with sampling is developed, economizing the signal transmission resource from the switching law to the AECS. Furthermore, based on the ET mechanism and switching law, an antidisturbance controller is designed to compensate for or suppress the influence of the multiple disturbances on the AECS. Also, under the ETAD control approach, relative theoretical conditions are established to save the signal transmission resource and to suppress or compensate multiple disturbances. Finally, using a hardware-in-loop platform with a switched aeroengine model inserted, a simulation is implemented to validate how the established ETAD control strategy is effectively applied to the AECS.

LHC data interpretation within the 2HDM type II via a new analysis toolkit

We review the status of the 2-Higgs doublet model (2HDM) type-II, in the light of the current experimental results and various theoretical consistency conditions. Compared to the existing literature, in this paper, we apply for the first time a new method that can improve the standard procedure for setting bounds on the 2HDM parameter space, as no experimental evidence has been found so far. Our new numerical framework, called Magellan, and statistical techniques can be applied to any beyond the Standard Model (BSM) scenario. Here, we take as testing ground the 2HDM, particularly as it is physically interesting and moreover characterized by a far from trivial multidimensional parameter space where the effectiveness of the new methods can be proved. Magellan uses a Markov chain Monte Carlo technique for scanning the parameter space and leverages the use of data processing and visualisation methods, allowing the user to perform inference on the model in a complete and efficient way. The novelty of the proposed method is that the parameter space of any BSM theory can be projected onto any bidimensional plane while still retaining all underlying attributes of those points, so that it is possible to investigate the associations between the properties of the various lower dimensional subspaces of the complete parameter space. The Magellan's website interactive dashboards can be accessed via a public link. Through this website, the user can explore the full parameter space and exploit the phenomenological features of a BSM model with ease.

An Echo State Network Imparts a Curve Fitting.

Recurrent neural networks (RNNs) are successfully employed in processing information from temporal data. Approaches to training such networks are varied and reservoir computing-based attainments, such as the echo state network (ESN), provide great ease in training. Akin to many machine learning algorithms rendering an interpolation function or fitting a curve, we observe that a driven system, such as an RNN, renders a continuous curve fitting if and only if it satisfies the echo state property. The domain of the learned curve is an abstract space of the left-infinite sequence of inputs and the codomain is the space of readout values. When the input originates from discrete-time dynamical systems, we find theoretical conditions under which a topological conjugacy between the input and reservoir dynamics can exist and present some numerical results relating the linearity in the reservoir to the forecasting abilities of the ESNs.

Deliberating with the Autocrats? A Case Study on the Limitations and Potential of Political CSR in a Non-Democratic Context

Extant literature on Political CSR and the role of governments in the governance of business conduct tends to neglect key implications of the political-institutional macro-context for public deliberation. Contextual assumptions often remain rather implicit, leading to the need for a more nuanced, explicit and context-sensitive exploration of the theoretical and practical boundary conditions of Political CSR. In non-democratic political-institutional contexts, political pluralism and participation are limited, and governmental agencies continue to play the most central role in regulation and its enforcement. Drawing on a qualitative case study on a nuclear energy project in the Hashemite Kingdom of Jordan, we show how both governments and MNCs co-create a context hostile to socially responsible business conduct in the sense of Political CSR. Utilizing rich qualitative data derived from interviews, public documents, and participant observation between 2008 and 2018, we specifically illuminate how—through which interactions and strategies—the multiple governmental and corporate actors involved counter civil society demands for public deliberation, indicating the limitations of Political CSR in non-democratic political-institutional contexts. We particularly contribute to the development of Political CSR by analysing the role of coercive and discursive forms of power. We thus offer a more nuanced perspective on the role of governments in constraining the room for public deliberation in the sense of Political CSR.

Exploiting internal resonances in nonlinear structures with cyclic symmetry as a mean of passive vibration control

The purpose of this paper is to study how internal resonances can be used to mitigate the vibration of cyclically symmetric systems exhibiting geometrical nonlinear effects. The method of multiple scales is employed to derive specific conditions that allow such energy transfers. This novelty is confirmed through numerical investigations, and an application to decrease the vibration of the system is proposed. A simplified yet realistic blade model with geometrical nonlinearities is considered. It includes pre-twist, pre-bending and warping, and is duplicated to create a full bladed rotor with cyclically symmetric properties. As the model of the whole structure may become enlarged, it is further reduced via the normal form approach. The harmonic balance method is then employed to obtain periodic solutions, localize bifurcation points and then follow bifurcated branches. These numerical solutions are used in complement with the aforementioned theoretical conditions to investigate the energy transfer properties of the mechanical system. Through these simulations, an effective range of amplitude excitation is defined to obtain internal resonances leading to an overall vibration mitigation of the system.

Ecology in the Wake: Black Studies, Literary Method, and the Nonhuman

As the Anthropocene has migrated from the life and physical sciences into the humanities as both a theoretical and material condition, there have been a growing number of critics who have critiqued the Anthropos of the Anthropocene, arguing that the monolithic humanity imagined whitewashes the asymmetric inequities of the humans of humanity. While much of this work has advocated for a dismissal of the Anthropocene concept, this article traces an alternate trajectory that has begun to emerge at the juncture of Black studies and literary theory. In this article, the author considers how a number of Black studies theorists have begun to argue for the centrality of blackness in our engagement with the nonhuman world. Bringing together three recent works, including Zakiyyah Iman Jackson’s Becoming Human, Joshua Bennett’s Being Property Once Myself, and Jayna Brown’s Black Utopia, this article argues for an alternative conception of the Anthropocene that originates in and through Blackness. Moreover, this article looks at the centrality of literary studies (and its attending methodologies) in building and envisaging the nascent field of Black ecology.

Speech Enhancement for Robust Speech Recognition Using Weighted Low Rank and Sparse Decomposition Models under Low SNR Conditions

Noise estimation is a crucial stage in speech enhancement (SE), and it commonly necessitates the use of prior models for speech, noise, or both. Prior models, on the other hand, can be ineffective in dealing with unseen nonstationary noise, especially at low signal to noise (SNR) levels. This paper proposes to assess the efficacy of an unsupervised SE approach based on weighted low rank and sparse matrix factorization to estimate noise and speech when neither is available beforehand by decomposing the input noisy spectrum into a low-rank noise component and a sparse speech component. Due to the approximation of the actual rank of noise, these techniques are constrained, and they do not directly exploit the low-rank property in optimization. Nuclear norm minimization (NNM) is the most well-known approach, as it can precisely recover the matrix's rank under certain restricted and theoretical guarantee conditions. NNM, on the other hand, is unable to reliably estimate the matrix rank in many situations. Significant advancements in computer vision and machine learning applications have demonstrated that a weighted nuclear norm minimization (WNNM), overcomes NNM shortcomings, and achieves a superior matrix rank approximation than NNM. Consequently, in this study, we present alternate SE algorithms that make use of weighted low rank and sparsity constraints to separate speech and noise spectrograms. Following that, they were trained and evaluated on a standard Automatic Speech Recognition (ASR) engine to lower the Word Error Rate (WER). Extensive investigations on the impact of real-world noise on speech signals show that the proposed model outperforms the existing state of art models in terms of objective measures like SDR, PESQ, SIG, BAK, OVL, and STOI values in varied noise circumstances under low SNR environments.

Moving Average-Based Multitasking In Silico Classification Modeling: Where Do We Stand and What Is Next?

Conventional in silico modeling is often viewed as ‘one-target’ or ‘single-task’ computer-aided modeling since it mainly relies on forecasting an endpoint of interest from similar input data. Multitasking or multitarget in silico modeling, in contrast, embraces a set of computational techniques that efficiently integrate multiple types of input data for setting up unique in silico models able to predict the outcome(s) relating to various experimental and/or theoretical conditions. The latter, specifically, based upon the Box–Jenkins moving average approach, has been applied in the last decade to several research fields including drug and materials design, environmental sciences, and nanotechnology. The present review discusses the current status of multitasking computer-aided modeling efforts, meanwhile describing both the existing challenges and future opportunities of its underlying techniques. Some important applications are also discussed to exemplify the ability of multitasking modeling in deriving holistic and reliable in silico classification-based models as well as in designing new chemical entities, either through fragment-based design or virtual screening. Focus will also be given to some software recently developed to automate and accelerate such types of modeling. Overall, this review may serve as a guideline for researchers to grasp the scope of multitasking computer-aided modeling as a promising in silico tool.

Microwave and Acoustic Absorption Metamaterials

Wave absorption metamaterials have been an enduring topic over the past two decades, propelled not only by novel scientific advances, but also by their extensive application potential. In this review, we aim to provide some general insights into the absorption mechanism common to both microwave and acoustic systems. By establishing a universal model for resonance-based metamaterials, we present the theoretical conditions for broadband impedance matching and introduce the fundamental causal limit as an evaluation tool for absorption performance. Under this integrated framework, we survey the recent advances on metamaterials absorption in both microwave and acoustic systems, with the focus on those that pushed the overall performance close to the causal limit. We take note of some new, emerging metastructures that can circumvent the constraint imposed by causal limit, thereby opening a new avenue to low-frequency absorption. This review concludes by discussing the existing challenges with possible solutions and the broad horizon for future developments.

Computation of Improved Searls Estimation of Population Variance Using Robust Auxiliary Parameters

:Variation is an inherent phenomenon, whether in natural things or man-made. Thus, it seems essential to estimate this variation. Various authors have worked in the direction of improved estimation of population variance utilizing the known auxiliary parameters for better policymaking.Methods:In this article, a new Searls ratio type class of estimator is suggested for elevated estimation of population variance of the main variable. As the suggested estimator is biased, its bias and mean squared error (MSE) has been derived up to the order-one approximation. The optimum values for the Searls characterizing scalars are obtained. The minimum MSE of the introduced estimator is obtained for the optimum Searls characterizing scalars. A theoretical comparison between the suggested estimator and the competing estimators has been made through their mean squared errors. The efficiency conditions of the suggested estimator over competing estimators are also obtained. These theoretical conditions are verified using some natural data sets. The computation of R codes for the biases and MSEs of the suggested and competing estimators is developed and used for three natural populations in the study by Naz et al. The estimator with the least MSE is recommended for practical utility. The empirical study has been done using R programming.Results:The MSEs of different competing and the suggested estimators are obtained for three natural populations. The estimator under comparison with the least MSE is recommended for practical applications.Discussion:The aim to search for the most efficient estimator for improved estimation is fulfilled through the proper use of the auxiliary parameters obtained from the known auxiliary variable. The suggested estimator may be used for elevated estimation of the population variance.Conclusion:The introduced estimator has the least MSE as compared to competing estimators of population variance for all three natural populations. Thus, it may be recommended for application in various fields.

Reducing Uncertainty In Log Analysis Due To Presence Of Heavy-Conductive Minerals In Sendimentary Rocks

Presence of heavy-conductive mineral(s) in formation rocks tends to provide negative influence to some log readings especially the resistivity log. With regard to its function in log analysis, any distortion in resistivity log readings will certainly lead to potential misinterpretation on petrophysical properties such as water saturation (S.) Therefore a method dedicated to minimizing the effect is indeed necessary.This paper presents results of a study on presence of heavy-conductive minerals, distributed in structural form, on resistivity reading. Based on analogy and expansion of a structural clay distribution model, a correction method plus its application procedure have been proposed. Since the method is develop using an approach that is considered valid in general term it is, therefore, conceptually applicable to any field cases as long as its theoretical conditions are met. In order to make application of the method easier it has also been presented in form of nomographs.Application of the method on log analysis of two wells in West Java has proved itself well in which corrections on calculated water saturation have yielded values that are more consistent when compared to production test data. The method is also prepared in a manner that it can be easily integrated into standard log analysis practices.

Methodology for Complete Decorrelation of Power Supply EM Side-Channel Signal and Sensitive Data

Electro-magnetic (EM) side channel attacks have become a serious threat to security of Internet-of-Things (IoT) devices. Power supply generated by voltage regulators is one of the most common attack targets due to its strong EM emanations. In this brief we derive analytical conditions for complete theoretical decorrelation of the power supply EM side-channel signal and the sensitive data. The output of the power supply converter is modelled as amplitude modulation (AM) of the load signal by the converter capacitance that acts as a carrier. By applying Price theorem (Papoulis and Pillai, 2002), we obtain the exact theoretical conditions that converter capacitance needs to fulfil in order to prevent EM side-channel attacks. The conditions are further adapted for practical implementation. When the proposed methodology is applied to AES measured traces, the correlation coefficient between the leaked signal and the sensitive data is 0.05. Such low correlation indicates the proposed methodology is a promising candidate against the attacks that exploit AM signals to extract sensitive data, such as, TEMPEST and active EM attacks. Test Vector Leakage Assessment (TVLA) <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\rho $ </tex-math></inline-formula> -test detects no leaky points, thereby confirming circuit protection against differential and correlation EM attacks as well.

Plieth-Kalinowska, Izabela &amp; Adam Musielewicz. 2019. Acceptance and social adaptation of children with developmental dysfunctions, Bydgoszcz: University of Kazimierz Wielki

This is a review of a book entitled Acceptance and social adaptation of children with developmental dysfunctions, written by Izabela Plieth-Kalinowska and Adam Musielewicz. The monograph shows the specificity and ways of organising the developmental conditions of a child with a disability functioning in different social environments. The publication contains characteristics of theoretical conditions of disability and practical ways of its diagnosis and examples of supporting activities.

An Analysis of the Immediate Liability Law for Building Permits via the Principal-Agent Problem

The inefficiency in the process of obtaining a building permit in Brazil can be mitigated with the approval of new laws that allow a relationship of consideration for services between the public administration and self-employed professionals, especially the architect. A Principal-Agent model is proposed to formalize possible Immediate Liability laws for building permits. The URB-Architect relationship can be formulated through the game theory, and the results following optimal policies ensure a theoretical condition of actions previously carried out by the public sector to be carried out by self-employed professionals.

Experimental evidence for local thermal non-equilibrium during heat transport in sand representative of natural conditions

When modelling heat transport in hydrogeological systems, a standard assumption is local thermal equilibrium (LTE), which implies that the porous medium temperature at the interface between the solid and fluid instantaneously reaches equilibrium. Few studies have investigated the validity of the LTE assumption and its violation, also known as local thermal non-equilibrium (LTNE), as well as its impact on the accuracy of heat transport models. While the theoretical conditions under which LTNE occurs in natural groundwater flow have recently been revealed, these have not yet been experimentally verified. We examined the applicability of the LTE assumption by conducting systematic laboratory experiments using eight distinct flow velocities (Reynolds number, Re < 0.37) through sand (0.76 mm grain size), injecting both heat and solute as tracers and observing the response at multiple points downstream. Theoretical heat transport parameters were calculated from solute tracer experiments by applying a retardation factor, and the results were subsequently compared to the actual parameters estimated from heat tracing. Our experimental results confirm that the LTE assumption can be violated under natural groundwater flow conditions, and that LTNE impacts thermal dispersion coefficients more significantly than thermal front velocities. The largest differences between the predicted and estimated thermal transport parameters were 112% and 13% for the dispersion coefficients and velocities, respectively. Our results demonstrate that LTNE effects need to be considered in heat transport modelling especially when analyzing thermal dispersion coefficients.

Modeling Warp in Corrugated Cardboard Based on Homogenization Techniques for In-Process Measurement Applications

A model for describing warp—characterized as a systematic, large-scale deviation from the intended flat shape—in corrugated board based on Kirchhoff plate theory is proposed. It is based on established homogenization techniques and only a minimum of model assumptions. This yields general results applicable to any kind of corrugated cardboard. Since the model is intended to be used with industrial data, basic material properties which are usually not measured in practice are summarized to a few parameters. Those parameters can easily be fitted to the measurement data, allowing the user to systematically identify ways to reduce warp in a given situation in practice. In particular, the model can be used both as a filter to separate the warp from other surface effects such as washboarding, and to interpolate between discrete sample points scattered across the surface of a corrugated board sheet. Applying the model only requires height measurements of the corrugated board at several known (not necessarily exactly predetermined) locations across the corrugated board and acts as an interpolation or regression method between those points. These data can be acquired during production in a cost-efficient way and do not require any destructive testing of the board. The principle of an algorithm for fitting measured data to the model is presented and illustrated with examples taken from ongoing measurements. Additionally, the case of warp-free board is analyzed in more detail to deduce additional theoretical conditions necessary to reach this state.

Evaluation on carbon isotope fractionation and gas-in-place content based on pressure-holding coring technique

Gas-in-place (GIP) and gas-adsorbed ratio are crucial parameters for resource potential assessment and production strategy optimization. Although various methods have been proposed to evaluate these two parameters, none have been widely recognized due to a lack of convincing comparison and validation. In this study, we established a GIP content calculation method by summing five gas components in the pressure-holding coring (PHC) technique: lost gas during retrieving, extracted gas during depressurization, lost gas during surface exposure, degassed gas, and residual gas. The GIP content of the four pressure-holding shale cores retrieved from the Longmaxi Formation of Lu-2 well, Sichuan Basin, China, ranges from 6.46 cm3/g to 10.58 cm3/g, which is used for comparing and verifying theoretical methods. The comparison results show that traditional methods, including the USBM, polynomial fit, ACF, and MCF methods, failed to accurately evaluate GIP content due to their defects in the theoretical foundation and boundary conditions settings. The carbon isotope fractionation (CIF) model derived on a rigorous theoretical basis and equipped with variable boundary conditions achieves the highest accuracy when evaluating the GIP content. Furthermore, the CIF model can determine the gas-adsorbed ratio, another critical parameter that traditional methods cannot obtain; the calculated gas-adsorbed ratio of five shale samples from the Lu-2 well is between 11.15% and 24.56%, with an average of 17.10%. With the help of the CIF model, we confirmed the general pattern of isotope fractionation during shale gas degassing and discussed the limitation and potential of two empirical parameters, δ13C1 of the first sample and △δ13C1 (the difference in δ13C1 value between the last and first sample), in indicating the adsorbed gas content.

Separation of active components tyrosol and salidroside from Rhodiola rosea crude extract by two-step multistage fractionation extraction

Rhodiola rosea contains many active ingredients, such as salidroside and tyrosol. However, separating the active components from Rhodiola rosea crude extract is difficult due to their similar physical properties. Multi-stage centrifugal fractionation extraction method was used due to its strong extraction and separation ability. Three solvents (n-butanol, n-amyl alcohol, and isobutyl acetate) with better distribution coefficient (k) and separation factor (α) were selected from nine organic solvents by single-stage extraction experiment. NaCl was used to break the two-phase emulsification during extraction. A two-step multi-stage extraction process was designed to separate multiple components. The multi-stage fractionation extraction experiments were carried out under the theoretical optimum conditions. In the first step, monomer 6 (tyrosol) was isolated and enriched in organic phase with a purity of over 94% using the above three solvents. In the second step using n-butanol as solvent, monomer 3 (picein) was enriched in organic phase with a purity of 93.6%, and monomer 5 (salidroside) was enriched in aqueous phase with a purity of 85.2%. Finally, the effect of the number of stages was simulated for the separation of picein. The yield of picein reached 80%, and the purity was close to 100% by more than 20 stages.

Contactless but loyal customers: The roles of anxiety and sociability in the hotel service context

To move their businesses in a positive direction, service providers are increasingly adopting contactless technologies. However, the influence of contactless service (CS) on important customer outcomes has been ignored. This study formulated a research framework to investigate the roles of customer anxiety and sociability in the relationship between CS and customer loyalty in the hotel setting. The findings revealed that CS is positively related to customer loyalty. Pandemic-related customer anxiety helps transit the positive impact of CS on customer loyalty. However, customer sociability dampens the effects of CS on customer loyalty. More specifically, as customer sociability increases, the positive impact of CS on customer loyalty decreases directly and indirectly via customer anxiety. Our findings provide novel contributions to the emerging CS literature by disclosing the psychological mechanisms under the “contactless effect” and the potential theoretical boundary condition. In addition, the findings deliver practicable benefits to service managers in fighting the COVID-19 crisis.

Role of Peer Coaching in Transmitting the Benefits of Leader Coaching.

Drawing on social information processing theory, the present study examines how and when leader coaching can be beneficial for team performance. Based on a sample of 58 teams from a sanitary product company in China, we found that peer coaching served as a mediator linking leader coaching and team performance. Moreover, the team individualistic/collectivism value moderated the first-stage relationship that the relationship between leader coaching and peer coaching was more positive when the team individualism value was low, but not significant when the team individualism value was high; while team task interdependence moderated the second-stage relationship that the relationship between peer coaching and team performance was more positive when the team task interdependence was high, but not significant when it was low. The findings enrich our understandings of the effectiveness of leader coaching behavior by uncovering the theoretical mechanism and boundary conditions. The study also provides important implications for coaching practice in organizations.