Holographic Duals of Black Holes in Five-dimensional Minimal Supergravity

We examine the dual conformal field theory for extremal charged black holes in five-dimensional minimal supergravity with 2 independent angular momenta. The conformal field theory Virasoro algebra, central charge, and temperature are calculated. Additionally the conformal field theory entropy is calculated using the Cardy formula and agrees with the Bekenstein-Hawking black hole entropy. The central charges are directly proportional to the angular momentum components of the black hole. In five and higher dimensions, rotations of the spacetime correspond to rotations of the central charges leading to an apparent symmetry relating the conformal field theories dual to each black hole. A rotationally invariant central charge, which is proportional to the total angular momentum, is used to discuss the supersymmetric BMPV black hole limits.Comment: inaccurate descriptions are clarifie

Conflation of short identity-by-descent segments bias their inferred length distribution

Identity-by-descent (IBD) is a fundamental concept in genetics with many applications. In a common definition, two haplotypes are said to contain an IBD segment if they share a segment that is inherited from a recent shared common ancestor without intervening recombination. Long IBD segments (> 1cM) can be efficiently detected by a number of algorithms using high-density SNP array data from a population sample. However, these approaches detect IBD based on contiguous segments of identity-by-state, and such segments may exist due to the conflation of smaller, nearby IBD segments. We quantified this effect using coalescent simulations, finding that nearly 40% of inferred segments 1-2cM long are results of conflations of two or more shorter segments, under demographic scenarios typical for modern humans. This biases the inferred IBD segment length distribution, and so can affect downstream inferences. We observed this conflation effect universally across different IBD detection programs and human demographic histories, and found inference of segments longer than 2cM to be much more reliable (less than 5% conflation rate). As an example of how this can negatively affect downstream analyses, we present and analyze a novel estimator of the de novo mutation rate using IBD segments, and demonstrate that the biased length distribution of the IBD segments due to conflation can lead to inflated estimates if the conflation is not modeled. Understanding the conflation effect in detail will make its correction in future methods more tractable

City of Bell - Audit Report: Administrative and Internal Accounting Controls

This is a report of the State Controller’s Office audit of the City of Bell’s administrative and internal accounting controls system. The audit was conducted at the request Interim City Administrator Pedro Carrillo for an assessment of the adequacy of the city’s controls to safeguard public assets and to ensure proper use of public funds

Quadratic Gradient: Uniting Gradient Algorithm and Newton Method as One

It might be inadequate for the line search technique for Newton's method to use only one floating point number. A column vector of the same size as the gradient might be better than a mere float number to accelerate each of the gradient elements with different rates. Moreover, a square matrix of the same order as the Hessian matrix might be helpful to correct the Hessian matrix. Chiang applied something between a column vector and a square matrix, namely a diagonal matrix, to accelerate the gradient and further proposed a faster gradient variant called quadratic gradient. In this paper, we present a new way to build a new version of the quadratic gradient. This new quadratic gradient doesn't satisfy the convergence conditions of the fixed Hessian Newton's method. However, experimental results show that it sometimes has a better performance than the original one in convergence rate. Also, Chiang speculates that there might be a relation between the Hessian matrix and the learning rate for the first-order gradient descent method. We prove that the floating number $\frac{1}{\epsilon + \max \{| \lambda_i | \}}$ can be a good learning rate of the gradient methods, where $\epsilon$ is a number to avoid division by zero and $\lambda_i$ the eigenvalues of the Hessian matrix.Comment: In this work, we proposed an enhanced Adam method via quadratic gradient and applied the quadratic gradient to the general numerical optimization problems. The quadratic gradient can indeed be used to build enhanced gradient methods for general optimization problems. There is a good chance that quadratic gradient can also be applied to quasi-Newton methods, such as the famous BFGS metho

Subsidiary Performance In MNCs: The Influences Of Absorptive Capacity And Social Capital On Knowledge Transfer

Multinational corporation (MNC) subsidiaries have become more closely linked to globalized business networks. The rapid technological changes are accelerating globalization, these changes have forced producers to constantly upgrade their process technologies, introduce new products and reduce costs to increase profits. Subsidiary performance is at the core of increased profits for MNCs. Accordingly, this research focuses upon subsidiary performance regarding three key contingencies that current international business literature deems likely to impact the bottom line: absorptive capacity, knowledge transfer and social capital. Unique data from more than 300 MNCs with locations in China, Japan, Malaysia, Singapore, South Korea and Taiwan were collected and analyzed. Findings suggest that concentrating on these three factors in subsidiaries’ knowledge environment could improve MNCs’ overall performance

Privacy-Preserving CNN Training with Transfer Learning

Privacy-preserving nerual network inference has been well studied while homomorphic CNN training still remains an open challenging task. In this paper, we present a practical solution to implement privacy-preserving CNN training based on mere Homomorphic Encryption (HE) technique. To our best knowledge, this is the first attempt successfully to crack this nut and no work ever before has achieved this goal. Several techniques combine to make it done: (1) with transfer learning, privacy-preserving CNN training can be reduced to homomorphic neural network training, or even multiclass logistic regression (MLR) training; (2) via a faster gradient variant called $\texttt{Quadratic Gradient}$, an enhanced gradient method for MLR with a state-of-the-art performance in converge speed is applied in this work to achieve high performance; (3) we employ the thought of transformation in mathematics to transform approximating Softmax function in encryption domain to the well-studied approximation of Sigmoid function. A new type of loss function is alongside been developed to complement this change; and (4) we use a simple but flexible matrix-encoding method named $\texttt{Volley Revolver}$ to manage the data flow in the ciphertexts, which is the key factor to complete the whole homomorphic CNN training. The complete, runnable C++ code to implement our work can be found at: https://github.com/petitioner/HE.CNNtraining. We select $\texttt{REGNET\_X\_400MF}$ as our pre-train model for using transfer learning. We use the first 128 MNIST training images as training data and the whole MNIST testing dataset as the testing data. The client only needs to upload 6 ciphertexts to the cloud and it takes $\sim 21$ mins to perform 2 iterations on a cloud with 64 vCPUs, resulting in a precision of $21.49\%$.Comment: In this work, we initiated to implement privacy-persevering CNN training based on mere HE techniques by presenting a faster HE-friendly algorith

The Mechanical Impact of the Tibetan Plateau on the Seasonal Evolution of the South Asian Monsoon

The impact of the Tibetan Plateau on the South Asian monsoon is examined using a hierarchy of atmospheric general circulation models. During the premonsoon season and monsoon onset (April–June), when westerly winds over the Southern Tibetan Plateau are still strong, the Tibetan Plateau triggers early monsoon rainfall downstream, particularly over the Bay of Bengal and South China. The downstream moist convection is accompanied by strong monsoonal low-level winds. In experiments where the Tibetan Plateau is removed, monsoon onset occurs about a month later, but the monsoon circulation becomes progressively stronger and reaches comparable strength during the mature phase. During the mature and decaying phase of monsoon (July–September), when westerly winds over the Southern Tibetan Plateau almost disappear, monsoon circulation strength is not much affected by the presence of the Tibetan Plateau. A dry dynamical core with east–west-oriented narrow mountains in the subtropics consistently simulates downstream convergence with background zonal westerlies over the mountain. In a moist atmosphere, the mechanically driven downstream convergence is expected to be associated with significant moisture convergence. The authors speculate that the mechanically driven downstream convergence in the presence of the Tibetan Plateau is responsible for zonally asymmetric monsoon onset, particularly over the Bay of Bengal and South China

Cross-layer Congestion Control, Routing and Scheduling Design in Ad Hoc Wireless Networks

This paper considers jointly optimal design of crosslayer congestion control, routing and scheduling for ad hoc wireless networks. We first formulate the rate constraint and scheduling constraint using multicommodity flow variables, and formulate resource allocation in networks with fixed wireless channels (or single-rate wireless devices that can mask channel variations) as a utility maximization problem with these constraints. By dual decomposition, the resource allocation problem naturally decomposes into three subproblems: congestion control, routing and scheduling that interact through congestion price. The global convergence property of this algorithm is proved. We next extend the dual algorithm to handle networks with timevarying channels and adaptive multi-rate devices. The stability of the resulting system is established, and its performance is characterized with respect to an ideal reference system which has the best feasible rate region at link layer. We then generalize the aforementioned results to a general model of queueing network served by a set of interdependent parallel servers with time-varying service capabilities, which models many design problems in communication networks. We show that for a general convex optimization problem where a subset of variables lie in a polytope and the rest in a convex set, the dual-based algorithm remains stable and optimal when the constraint set is modulated by an irreducible finite-state Markov chain. This paper thus presents a step toward a systematic way to carry out cross-layer design in the framework of “layering as optimization decomposition” for time-varying channel models

Comments on "The Role of the Central Asian Mountains on the Midwinter Suppression of North Pacific Storminess" - Reply

We thank Chang and Lin for their thoughtful and constructive comments on our study (Park et al. 2010). In Park et al. (2010), we did not explicitly state that the topography-forced stationary waves are the direct cause for the reduced downstream transient eddy kinetic energy (EKE). The response of stationary waves to topography may saturate even with a relatively small mountain (Cook and Held 1992); furthermore, their magnitudes are much smaller than thermally forced stationary waves (Chang 2009; Held et al. 2002). Instead, we suggest that quasistationary waves generated by the central Asian mountains may strongly affect North Pacific storminess by changing the year-to-year variability of westerly winds over the eastern Eurasian continent. Observational analyses indicate that the midwinter suppression of North Pacific storminess does not occur every year. Some years experience stronger and more meridionally confined zonal winds over the western North Pacific, leading to stronger midwinter suppression (Harnik and Chang 2004; Nakamura and Sampe 2002)