The Capital Structure Puzzle: What Are We Missing?

An important piece of the capital structure puzzle has been missing, and it is not a contracting friction. It is recognition that managers do not have sufficient knowledge to optimize capital structure with any real precision. The literature critique in this paper i) identifies the conceptual sources of the main empirical failures of the leading models of capital structure and ii) shows how those failures can be repaired by taking into account imperfect managerial knowledge and several other factors. The analysis yields a compact set of principles for thinking about capital structure in an empirically supported way.

Robust Adaptive Neural Cooperative Control for the USV-UAV Based on the LVS-LVA Guidance Principle

Around the cooperative path-following control for the underactuated surface vessel (USV) and the unmanned aerial vehicle (UAV), a logic virtual ship-logic virtual aircraft (LVS-LVA) guidance principle is developed to generate the reference heading signals for the USV-UAV system by using the “virtual ship” and the “virtual aircraft”, which is critical to establish an effective correlation between the USV and the UAV. Taking the steerable variables (the main engine speed and the rudder angle of the USV, and the rotor angular velocities of the UAV) as the control input, a robust adaptive neural cooperative control algorithm was designed by employing the dynamic surface control (DSC), radial basic function neural networks (RBF-NNs) and the event-triggered technique. In the proposed algorithm, the reference roll angle and pitch angle for the UAV can be calculated from the position control loop by virtue of the nonlinear decouple technique. In addition, the system uncertainties were approximated through the RBF-NNs and the transmission burden from the controller to the actuators was reduced for merits of the event-triggered technique. Thus, the derived control law is superior in terms of the concise form, low transmission burden and robustness. Furthermore, the tracking errors of the USV-UAV cooperative control system can converge to a small compact set through adjusting the designed control parameters appropriately, and it can be also guaranteed that all the signals are the semi-global uniformly ultimately bounded (SGUUB). Finally, the effectiveness of the proposed algorithm has been verified via numerical simulations in the presence of the time-varying disturbances.

Profiling of a shaped worm cutter for shaping gears with non-involute tooth profile

Of the mechanical transmissions used in mechanical engineering, the most common are gears with an involute profile of the teeth flanks. Gears made up of such wheels have a number of advantages, but they also have a number of significant disadvantages. Therefore jne of the current trends is the study of gears with a complex non-involute profile of the teeth flank which have advantages over involute gears in a number of applications, as well as the development of tools for their processing. There are two ways of gear teeth cutting: the copying method and the rolling-in method. The rolling-in method has advantages. The profile of the tool working by the rolling-in method does not depend on the number of teeth of the gear being cut, therefore, the same tool can be used to cut gears with any number of teeth. The accuracy of a gear made by the rolling-in method is significantly higher than the accuracy of a gear made by the copying method. This is primarily due to the continuity of the rolling-in process. When cutting teeth by the rolling method, the tooth surface is formed as a result of processing with a tool, the cutting edges of which are the tooth profile of the mating rack or the tooth profile of the mating gear, and during processing the tool and the workpiece form a mating gear pair. The most common gear cutting tool is the hob cutter. For the machining of gear wheels with a non-involute tooth profile widely used in industry equipment is used. One of the options for a rolling gear cutting tool for shaping gear wheels with a non-involute tooth profile can be a shaped worm cutter. The article describes the method of profiling of the cutting part of shaped hob cutter for machining of gear wheels with normal accuracy. To solve the problem the unified mathematical base – the apparatus of multiparameter mappings of space – the unified structure of mappings for gears and a compact set of unified operators, parameters and functional connections is used.

Two modifications of extension of piyavskii’s global optimization algorithm to a function continuous on a compact interval and its convergence

В работах R.J. Vanderbei доказано, что непрерывная на выпуклом компактном множестве функция обладает свойством $\varepsilon $-липшицевости, обобщающим классическое понятие липшицевости. На основе этого свойства R.J. Vanderbei предложено одно обобщение метода Пиявского поиска глобального минимума непрерывной на отрезке функции. В данной работе предлагаются одна модификация этого метода для положительной $\varepsilon $-константы и одна модификация для положительной $\varepsilon $-константы и условия останова, не зависящего от выбора $\varepsilon $. Доказана сходимость предлагаемых алгоритмов, приведены результаты численных экспериментов на основе применения разработанной программы. Данные методы могут быть применены для оптимизации любых непрерывных на отрезке функций, например, при решении некоторых обратных задачах баллистики и в экономике в прямых задачах потребительского выбора маршаллианского типа с переменными ценами благ и с непрерывной функцией полезности. R.J. Vanderbei in his works proves that any continuous on a compact set function has the $\varepsilon $-Lipschitz property which extends conventional Lipschitz continuity. Based on this feature Vanderbei proposed one extension of Piyavskii’s global optimization algorithm to the continuous function case. In this paper we propose one modification of the Vanderbei’s algorithm for a positive $\varepsilon $-constant and another modification for a positive $\varepsilon $-constant and $\varepsilon $ value independent termination condition. We prove proposed methods convergence and perform several computational experiments with designed software for known test functions.

Passivity-Based Output Feedback Control for Systems with Nonlinear Outputs via High-Gain Observers

In this paper, a high-gain observer with nonlinear output is designed. The scaled estimation error system is constructed with a passive function based on the nonlinear output function and a strictly positive real transfer function of boundary-layer system. The ultimate boundedness and exponential stability of the estimation error for the global and regional two cases are demonstrated, as long as high-gain observer's decay rate is fast enough. For the regional case, due to the restriction on the passive function, the estimation error has a region of attraction which is a subset of the intersection of a positively invariant compact set and the strip coming from the restriction. The extended results under passivity of the output function and strictly positive realness of the transfer function are presented. The performance recovery property of the output feedback using high-gain observer with nonlinear output is validated. Some examples are applied in the simulation to illustrate the proposed results in this paper.

Accessible Modeling of the German Energy Transition: An Open, Compact, and Validated Model

We present an easily accessible model for dispatch and expansion planning of the German multi-modal energy system from today until 2050. The model can be used with low efforts while comparing favorably with historic data and other studies of future developments. More specifically, the model is based on a linear programming partial equilibrium framework and uses a compact set of technologies to ease the comprehension for new modelers. It contains all equations and parameters needed, with the data sources and model assumptions documented in detail. All code and data are openly accessible and usable. The model can reproduce today’s energy mix and its CO2 emissions with deviations below 10%. The generated energy transition path, for an 80% CO2 reduction scenario until 2050, is consistent with leading studies on this topic. Our work thus summarizes the key insights of previous works and can serve as a validated and ready-to-use platform for other modelers to examine additional hypotheses.

Liouville type theorems for solutions of semilinear equations on non-compact Riemannian manifolds

It is proved that the Liouville function associated with the semilinear equation $\Delta u -g(x,u)=0$ is identical to zero if and only if there is only a trivial bounded solution of the semilinear equation on non-compact Riemannian manifolds. This result generalizes the corresponding result of S.A. Korolkov for the case of the stationary Schrödinger equation $ \Delta u-q (x) u = 0$. The concept of the capacity of a compact set associated with the stationary Schrödinger equation is also introduced and it is proved that if the capacity of any compact set is equal to zero, then the Liouville function is identically zero.

Probabilistic seismic hazard analysis for spatially distributed infrastructure considering the correlation of spectral acceleration across spectral periods

Regional seismic hazard analyses are necessary to assess the infrastructure performance within a region and ensure that mitigation funds are utilized effectively by probabilistically considering the suite of potential earthquake events. This research aims to efficiently represent the regional seismic hazard through a compact set of seismic inputs in the form of spectral acceleration (SA) maps by considering the spatial cross-correlation of SA at a wide period range. The SA maps can then be used to probabilistically estimate the performance of a portfolio of spatially distributed structures with different fundamental periods. Efficient representation reduces the number of required SA maps to decrease the computational demands of the infrastructure performance analysis in the subsequent steps. The added dimension of the between-period spatial SA correlation exacerbates the challenge of effectively simulating and selecting a set of SA maps to reproduce the hazard curves particularly at long return periods. Two approaches are proposed to generate an optimal set of SA maps: (a) a simulation-based methodology that uses state-of-the-art variance reduction methods and (b) a simplified methodology that aims to increase the ease of use and reduce the computational demands of the simulation. The two approaches are implemented and compared using the city of San Francisco as a case study to illustrate their feasibility. The simplified approach increases the scalability of the methodology to larger study areas at the expense of reduced accuracy in terms of seismic hazard curve and SA correlation errors.

Precision Autism: Genomic Stratification of Disorders Making Up the Broad Spectrum May Demystify Its “Epidemic Rates”

In the last decade, Autism has broadened and often shifted its diagnostics criteria, allowing several neuropsychiatric and neurological disorders of known etiology. This has resulted in a highly heterogeneous spectrum with apparent exponential rates in prevalence. I ask if it is possible to leverage existing genetic information about those disorders making up Autism today and use it to stratify this spectrum. To that end, I combine genes linked to Autism in the SFARI database and genomic information from the DisGeNET portal on 25 diseases, inclusive of non-neurological ones. I use the GTEx data on genes’ expression on 54 human tissues and ask if there are overlapping genes across those associated to these diseases and those from SFARI-Autism. I find a compact set of genes across all brain-disorders which express highly in tissues fundamental for somatic-sensory-motor function, self-regulation, memory, and cognition. Then, I offer a new stratification that provides a distance-based orderly clustering into possible Autism subtypes, amenable to design personalized targeted therapies within the framework of Precision Medicine. I conclude that viewing Autism through this physiological (Precision) lens, rather than viewing it exclusively from a psychological behavioral construct, may make it a more manageable condition and dispel the Autism epidemic myth.

Robust Synchronization Control of Uncertain Fractional-Order Chaotic Systems via Disturbance Observer

This paper studies the synchronization of two different fractional-order chaotic systems through the fractional-order control method, which can ensure that the synchronization error converges to a sufficiently small compact set. Afterwards, the disturbance observer of the synchronization control scheme based on adaptive parameters is designed to predict unknown disturbances. The Lyapunov function method is used to verify the appropriateness of the disturbance observer design and the convergence of the synchronization error, and then the feasibility of the control scheme is obtained. Finally, our simulation studies verify and clarify the proposed method.