Asymptotic Solutions of Diffusion Models for Risk Reserves

We study a family of diffusion models for risk reserves which account for the investment income earned and for the inflation experienced on claim amounts. After we defined the process of the conditional probability of ruin over finite time and imposed the appropriate boundary conditions, classical results from the theory of diffusion processes turn the stochastic differential equation to a special class of initial and boundary value problems defined by a linear diffusion equation. Armedwith asymptotic analysis and perturbation theory, we obtain the asymptotic solutions of the diffusion models (possibly degenerate) governing the conditional probability of ruin over a finite time in terms of interest rate

Discrete-Time Recurrent Neural Network and Its Application to Compression of Infra-Red Spectrum

We study the discrete-time recurrent neural network that derived from the Leaky-integrator model and its application to compression of infra-red spec- trum. Our results show that the discrete-time Leaky-integrator recurrent neural network (RNN) model can be used to approximate the continuous-time model and inherit its dynamical characters if a proper step size is chosen. Moreover, the discrete-time Leaky-integrator RNN model is absolutely stable. By developing the double discrete integral method and employing the state space search algorithm for the discrete-time recurrent neural network model, we demonstrate with quality spectra regenerated from the compressed data how to compress the infra-red spectrum effectively. The information we stored is the parameters of the system and its initial states. The method offers an ideal setting to carry out the recurrent neural network approach to chaotic cases of data compression

Discrete-Time Recurrent Neural Network and Its Application to Compression of Infra-Red Spectrum

We study the discrete-time recurrent neural network that derived from the Leaky-integrator model and its application to compression of infra-red spec- trum. Our results show that the discrete-time Leaky-integrator recurrent neural network (RNN) model can be used to approximate the continuous-time model and inherit its dynamical characters if a proper step size is chosen. Moreover, the discrete-time Leaky-integrator RNN model is absolutely stable. By developing the double discrete integral method and employing the state space search algorithm for the discrete-time recurrent neural network model, we demonstrate with quality spectra regenerated from the compressed data how to compress the infra-red spectrum effectively. The information we stored is the parameters of the system and its initial states. The method offers an ideal setting to carry out the recurrent neural network approach to chaotic cases of data compression

A New Optimization Algorithm for Single Hidden Layer Feedforward Neural Networks

Feedforward neural networks are the most commonly used function approximation techniques in neural networks. By the universal approximation theorem, it is clear that a single-hidden layer feedforward neural network (FNN) is sufficient to approximate the corresponding desired outputs arbitrarily close. Some researchers use genetic algorithms (GAs) to explore the global optimal solution of the FNN structure. However, it is rather time consuming to use GA for the training of FNN. In this paper, we propose a new optimization algorithm for a single-hidden layer FNN. The method is based on the convex combination algorithm for massaging information in the hidden layer. In fact, this technique explores a continuum idea which combines the classic mutation and crossover strategies in GA together. The proposed method has the advantage over GA which requires a lot of preprocessing works in breaking down the data into a sequence of binary codes before learning or mutation can apply. Also, we set up a new error function to measure the performance of the FNN and obtain the optimal choice of the connection weights and thus the nonlinear optimization problem can be solved directly. Several computational experiments are used to illustrate the proposed algorithm, which has good exploration and exploitation capabilities in search of the optimal weight for single hidden layer FNNs

Robust converter-fed motor control based on active rejection of multiple disturbances

In this work, an advanced motion controller is proposed for buck converter-fed DC motor systems. The design is based on an idea of active disturbance rejection control (ADRC) with its key component being a custom observer capable of reconstructing various types of disturbances (including complex, harmonic signals). A special formulation of the proposed design allows the control action to be expressed in a concise and practically appealing form reducing its implementation requirements. The obtained experimental results show increased performance of the introduced approach over conventionally used methods in tracking precision and disturbance rejection, while keeping similar level of energy consumption. A stability analysis using theory of singular perturbation further supports the validity of proposed control approach.Comment: 30 pages, 7 figures, 1 tabl

Stress-responsive pathways and small RNA changes distinguish variable developmental phenotypes caused by MSH1 loss.

BACKGROUND: Proper regulation of nuclear-encoded, organelle-targeted genes is crucial for plastid and mitochondrial function. Among these genes, MutS Homolog 1 (MSH1) is notable for generating an assortment of mutant phenotypes with varying degrees of penetrance and pleiotropy. Stronger phenotypes have been connected to stress tolerance and epigenetic changes, and in Arabidopsis T-DNA mutants, two generations of homozygosity with the msh1 insertion are required before severe phenotypes begin to emerge. These observations prompted us to examine how msh1 mutants contrast according to generation and phenotype by profiling their respective transcriptomes and small RNA populations. RESULTS: Using RNA-seq, we analyze pathways that are associated with MSH1 loss, including abiotic stresses such as cold response, pathogen defense and immune response, salicylic acid, MAPK signaling, and circadian rhythm. Subtle redox and environment-responsive changes also begin in the first generation, in the absence of strong phenotypes. Using small RNA-seq we further identify miRNA changes, and uncover siRNA trends that indicate modifications at the chromatin organization level. In all cases, the magnitude of changes among protein-coding genes, transposable elements, and small RNAs increases according to generation and phenotypic severity. CONCLUSION: Loss of MSH1 is sufficient to cause large-scale regulatory changes in pathways that have been individually linked to one another, but rarely described all together within a single mutant background. This study enforces the recognition of organelles as critical integrators of both internal and external cues, and highlights the relationship between organelle and nuclear regulation in fundamental aspects of plant development and stress signaling. Our findings also encourage further investigation into potential connections between organelle state and genome regulation vis-á-vis small RNA feedback

On Vibration Suppression and Trajectory Tracking in Largely Uncertain Torsional System: An Error-based ADRC Approach

In this work, a practically relevant control problem of compensating harmonic uncertainties is tackled. The problem is formulated and solved here using an active disturbance rejection control (ADRC) methodology. A novel, custom ADRC structure is proposed that utilizes an innovative resonant extended state observer (RESO), dedicated to systems subjected to harmonic interferences. In order to make the introduced solution more industry-friendly, the entire observer-centered control topology is additionally restructured into one degree-of-freedom, compact, feedback error-based form (similar to ubiquitous in practice PID controller). Such reorganization enables a straightforward implementation and commission of the proposed technique in wide range of industrial control platforms, thus potentially increasing its outreach. In order to verify the efficiency of the introduced method, a multi-criteria experimental case study using a torsional plant is conducted in a trajectory tracking task, showing satisfactory performance in vibration suppression, without the often problem of noise amplification due to high observer/controller gains. Finally, a frequency analysis and a rigorous stability proof of the proposed control structure are given

Analisis Sistem Pengendalian Intern Penyaluran Kredit Pada PD BPR Rokan Hulu

Bank yang mempunyai kegiatan utamanya menyalurkan dana kepada masyarakat dalam bentuk kredit mempunyai resiko yang cukup besar, oleh karena itu diperlukan sistem pengendalian intern penyaluran kredit yang efektif untuk mengurangi dan mencegah resiko tersebut. PD. BPR Rokan Hulu merupakan salah satu lembaga keuangan yang kegiatan utamanya adalah menyalurkan dana kepada masyarakat. Penelitian ini bertujuan untuk mengetahui efektifitas penerapan sistem pengendalian intern dalam penyaluran kredit yang dilaksanakan oleh PD. BPR Rokan Hulu. Data penelitian ini diperoleh dari kuesioner dan dokumentasi, teknik analisis data yang digunakan dalam penelitian ini adalah metode analisis deskriptif. Penelitian ini mengunakan metode studi kasus yang berfokus pada sistem pengendalian intern penyaluran kredit pada PD. BPR. Rokan Hulu. Penelitian ini dilakukan dengan menganalisis data tentang komponen-komponen sistem pengendalian intern dari hasil dokumen, dan menghitung hasil keusioner mengunakan rumusan champion.Hasil analisis yang dilakukan menunjukkan bahwa sistem penyaluran kredit yang dilaksanakan oleh PD. BPR Rokan Hulu telah didukung oleh penerapan sistem pengendalian intern yang sangat efektif, berdasarkan hasil jawaban kuesioner yang diperoleh adalah sebesar 92,90% yaitu berada dalam rentang 76% - 100% atau penerapan pengendalian intern sangat efektif dalam menunjang prosedur penyaluran kredit, dan telah memenuhi kelima komponen sistem pengendalian intern yaitu lingkungan pengendalian, penafsiran risiko, aktivitas pengendalian, informasi dan komunikasi, dan pemantauan

An epigenetic breeding system in soybean for increased yield and stability

Epigenetic variation has been associated with a wide range of adaptive phenotypes in plants, but there exist few direct means for exploiting this variation. RNAi suppression of the plant-specific gene, MutS HOMOLOG1 (MSH1), in multiple plant species produces a range of developmental changes accompanied by modulation of defence, phytohormone and abiotic stress response pathways along with methylome repatterning. This msh1-conditioned developmental reprogramming is retained independent of transgene segregation, giving rise to transgene-null ‘memory’ effects. An isogenic memory line crossed to wild type produces progeny families displaying increased variation in adaptive traits that respond to selection. This study investigates amenability of the MSH1 system for inducing agronomically valuable epigenetic variation in soybean. We developed MSH1 epi-populations by crossing with msh1-acquired soybean memory lines. Derived soybean epi-lines showed increase in variance for multiple yield-related traits including pods per plant, seed weight and maturity time in both glasshouse and field trials. Selected epi-F2:4 and epi-F2:5 lines showed an increase in seed yield over wild type. By epi-F2:6, we observed a return of MSH1-derived enhanced growth back to wild-type levels. Epi-populations also showed evidence of reduced epitype-by-environment (e 9 E) interaction, indicating higher yield stability. Transcript profiling of epi-lines identified putative signatures of enhanced growth behaviour across generations. Genes related to cell cycle, abscisic acid biosynthesis and auxin response, particularly SMALL AUXIN UP RNAs (SAURs), were differentially expressed in epi-F2:4 lines that showed increased yield when compared to epi-F2:6. These data support the potential of MSH1-derived epigenetic variation in plant breeding for enhanced yield and yield stability

Global gene expression analyses of bystander and alpha particle irradiated normal human lung fibroblasts: Synchronous and differential responses

<p>Abstract</p> <p>Background</p> <p>The existence of a radiation bystander effect, in which non-irradiated cells respond to signals from irradiated cells, is now well established. It raises concerns for the interpretation of risks arising from exposure to low doses of ionizing radiation. However, the regulatory mechanisms involved in the bystander response have not been well elucidated. To provide insight into the signaling pathways responding in bystanders, we have measured global gene expression four hours after bystander and direct alpha particle exposure of primary human lung fibroblasts.</p> <p>Results</p> <p>Although common p53-regulated radiation response genes like <it>CDKN1A </it>were expressed at elevated levels in the directly exposed cultures, they showed little or no change in the bystanders. In contrast, genes regulated by NFκB, such as <it>PTGS2 </it>(cyclooxygenase-2), <it>IL8 </it>and <it>BCL2A1</it>, responded nearly identically in bystander and irradiated cells. This trend was substantiated by gene ontology and pathway analyses of the microarray data, which suggest that bystander cells mount a full NFκB response, but a muted or partial p53 response. In time-course analyses, quantitative real-time PCR measurements of <it>CDKN1A </it>showed the expected 4-hour peak of expression in irradiated but not bystander cells. In contrast, <it>PTGS2, IL8 </it>and <it>BCL2A1 </it>responded with two waves of expression in both bystander and directly irradiated cells, one peaking at half an hour and the other between four and six hours after irradiation.</p> <p>Conclusion</p> <p>Two major transcriptional hubs that regulate the direct response to ionizing radiation are also implicated in regulation of the bystander response, but to dramatically different degrees. While activation of the p53 response pathway is minimal in bystander cells, the NFκB response is virtually identical in irradiated and bystander cells. This alteration in the balance of signaling is likely to lead to different outcomes in irradiated cells and their bystanders, perhaps leading to greater survival of bystanders and increased risk from any long-term damage they have sustained.</p