100-Gb/s point-to-point solutions for long-reach passive optical networks in sparse rural and urban areas

Long reach-passive optical networks (LR-PON) are being proposed as a means of enabling ubiquitous fiber-to-the-home (FTTH) by massive sharing of network resources and therefore reducing per customer costs to affordable levels. In this paper, we analyze the chain solutions for LR-PON deployment in urban and rural areas at 100-Gb/s point-to-point transmission using dual polarization-quaternary phase shift-keying (DP-QPSK) modulation. The numerical analysis shows that with appropriate finite impulse response (FIR) filter designs, 100-Gb/s transmission can be achieved with at least 512 way split and up to 160 km total distance, which is sufficient for many of the optical paths in a practical situation, for point-to-point link from one LR-PON to another LR-PON through the optical switch at the metro nodes and across a core light path through the core network without regeneration.

Characterization of polymer fiber Bragg grating with ultrafast laser micromachining

We report that the main photosensitive mechanism of poly(methyl methacrylate)-based optical fiber Bragg grating (POFBG) under ultraviolet laser micromachining is a complex process of both photodegradation and negative thermo-optic effect. We found experimentally the unique characteristics of Bragg resonance splitting and reunion during the laser micromachining process providing the evidence of photodegradation, while the mean refractive index change of POFBG was measured to be negative confirming further photodegradation of polymer fiber. The thermal-induced refractive index change of POFBG was also observed by recording the Bragg wavelength shift. Furthermore, the dynamic thermal response of the micromachined-POFBG was demonstrated under constant humidity, showing a linear and negative response of around -47.1 pm/°C.

Mecanismos de transmissão de preços e parcelas de mercado: uma análise sobre as exportações brasileiras de manga

Climate and environmental conditions allowed Brazil to become one of the largest producers of tropical fruits in the world. The São Francisco Valley, over the years, has emerged as the main fruit-producing region of the country, especially mangos and grapes. The mango, which is produced in this region, has reached a good international position, especially in European and American markets. However, the domestic price has absorbed more and more the impact of fluctuations in the international market expectations affecting the production and marketing of producers. The objective of the study is to analyze the transmission ratio of export prices of the mango, with the American market prices and the European Union in the period from 2003 to 2013. It is intended also to analyze the factors affecting the fluctuations of exports Brazilian mango for the main import markets. To achieve the proposed objectives, we used, in the methodology, the autoregressive vector model, in order to find the price transmission mechanism and the mechanisms of impacts through the impulse response function. We also used, the Constant Market Share model, in order to observe the importance of the effects competitiveness, destination, and growth in world trade on the changes of Brazilian mango exports in the period. The data used were obtained from the database of the Ministry of Development and Foreign Trade - MIDIC and FAOSTAT (Food and Agriculture Organization of the United Nations). Among the results, it was found that the Brazilian domestic prices are influenced by the US market price, and that price shocks promoted this market can impact on the growth of the internal prices for several months. It was noted also that the competitiveness effect accounted for the largest portion of the effective growth of Brazilian exports, in other word, the country has improved its competitiveness among the other exporting countries.

Predicting Transcript Production Rates in Yeast With Sparse Linear Models

To provide biological insights into transcriptional regulation, a couple of groups have recently presented models relating the promoter DNA-bound transcription factors (TFs) to downstream gene’s mean transcript level or transcript production rates over time. However, transcript production is dynamic in response to changes of TF concentrations over time. Also, TFs are not the only factors binding to promoters; other DNA binding factors (DBFs) bind as well, especially nucleosomes, resulting in competition between DBFs for binding at same genomic location. Additionally, not only TFs, but also some other elements regulate transcription. Within core promoter, various regulatory elements influence RNAPII recruitment, PIC formation, RNAPII searching for TSS, and RNAPII initiating transcription. Moreover, it is proposed that downstream from TSS, nucleosomes resist RNAPII elongation.

Here, we provide a machine learning framework to predict transcript production rates from DNA sequences. We applied this framework in the S. cerevisiae yeast for two scenarios: a) to predict the dynamic transcript production rate during the cell cycle for native promoters; b) to predict the mean transcript production rate over time for synthetic promoters. As far as we know, our framework is the first successful attempt to have a model that can predict dynamic transcript production rates from DNA sequences only: with cell cycle data set, we got Pearson correlation coefficient Cp = 0.751 and coefficient of determination r2 = 0.564 on test set for predicting dynamic transcript production rate over time. Also, for DREAM6 Gene Promoter Expression Prediction challenge, our fitted model outperformed all participant teams, best of all teams, and a model combining best team’s k-mer based sequence features and another paper’s biologically mechanistic features, in terms of all scoring metrics.

Moreover, our framework shows its capability of identifying generalizable fea- tures by interpreting the highly predictive models, and thereby provide support for associated hypothesized mechanisms about transcriptional regulation. With the learned sparse linear models, we got results supporting the following biological insights: a) TFs govern the probability of RNAPII recruitment and initiation possibly through interactions with PIC components and transcription cofactors; b) the core promoter amplifies the transcript production probably by influencing PIC formation, RNAPII recruitment, DNA melting, RNAPII searching for and selecting TSS, releasing RNAPII from general transcription factors, and thereby initiation; c) there is strong transcriptional synergy between TFs and core promoter elements; d) the regulatory elements within core promoter region are more than TATA box and nucleosome free region, suggesting the existence of still unidentified TAF-dependent and cofactor-dependent core promoter elements in yeast S. cerevisiae; e) nucleosome occupancy is helpful for representing +1 and -1 nucleosomes’ regulatory roles on transcription.

The Use of Almost Linear Phase IIR filters In DFT Modulated Filter Banks for Communication Systems

This paper is on the use and performance of M-path polyphase Infinite Impulse Response (IIR) filters for channelisation, conventionally where Finite Impulse Response (FIR) filters are preferred. This paper specifically focuses on the Discrete Fourier Transform (DFT) modulated filter banks, which are known to be an efficient choice for channelisation in communication systems. In this paper, the low-pass prototype filter for the DFT filter bank has been implemented using an M-path polyphase IIR filter and we show that the spikes present at the stopband can be avoided by making use of the guardbands between narrowband channels. It will be shown that the channelisation performance will not be affected when polyphase IIR filters are employed instead of their counterparts derived from FIR prototype filters. Detailed complexity and performance analysis of the proposed use will be given in this article.

Pass-through of International food prices to domestic ination during and after the great recession: evidence from a set of Latin American economies

We examined how international food price shocks have impacted local ination processes in Brazil, Chile, Colombia, Mexico, and Peru in the past decade -- Using impulse-response analysis coming from cointegrated VARs, we wind that international food ination shocks take from one to six quarters to pass through to domestic head-line ination, depending on the country -- In addition, by calculating the elasticity of local prices to an international food price shock, we found that this pass-through is not complete -- We also take a closer look at how this type of shock affects local food and core prices separately, and asses the possibility second round effects over core ination stemming from the shock -- We wind that a transmission to headline prices does occur, and that part of the transmission is associated with rising core prices both directly and through possible second round effects, which implies a role for monetary policy when such a shock takes place -- This is especially relevant given that international food prices have recently been on an upward trend after falling considerably during the Great Recession

Asynchronus design for improved EMC behavior of ICs

International audience

An Analysis of Colombian Power Market Price Behavior from an Industrial Organization Perspective

We analyze the behavior of spot prices in the Colombian wholesale power market, using a series of models derived from industrial organization theory -- We first create a Cournot-based model that simulates the strategic behavior of the market-leader power generators, which we use to estimate two industrial organization variables, the Index of Residual Demand and the Herfindahl-Hirschman Index (HHI) -- We use these variables to create VAR models that estimate spot prices and power market impulse-response relationships -- The results from these models show that hydroelectric generators can use their water storage capability strategically to affect off-peak prices primarily, while the thermal generators can manage their capacity strategically to affect on-peak prices -- In addition, shocks to the Index of Residual Capacity and to the HHI cause spot price fluctuations, which can be interpreted as the generators´ strategic response to these shocks

Bioorthogonal Noncanonical Amino Acid Tagging for Selective Analysis of the Pseudomonas aeruginosa Proteome

In natural environments, bacterial physiology is frequently characterized by slow metabolic rates and complex cellular heterogeneities. The opportunistic pathogen Pseudomonas aeruginosa provides one such example; P. aeruginosa forms untreatable chronic biofilm infections of the cystic fibrosis lung, where oxygen limitation can lead to states of metabolic dormancy. To better understand the biology of these states, in vitro experiments must be adapted to better recapitulate natural settings. However, low rates of protein turnover and cellular or phenotypic complexity make these systems difficult to study using established methods. Here we adapt the bioorthogonal noncanonical amino acid tagging (BONCAT) method for time- and cell-selective proteomic analysis to the study of P. aeruginosa. Analysis of proteins synthesized in an anoxic dormancy state led to the discovery of a new type of transcriptional regulator which we designated SutA. We performed detailed analyses of SutA’s role in transcription under slow growth states and we elucidated the structural basis for its regulatory behavior. Additionally, we used cell-selective targeting of BONCAT labeling to measure the dynamic proteomic response of an antibiotic-tolerant biofilm subpopulation. Overall this work shows the utility of selective proteomics as applied to bacterial physiology and describes the broad biological insight obtained from that application.

Economic growth and public and private investment returns

We study the macroeconomic effects of public and private investment in 17 OECD economies through a VAR analysis with annual data from 1960 to 2014. From impulse response functions we find that public investment had a positive growth effect in most countries, and a contractionary effect in Finland, UK, Sweden, Japan, and Canada. Public investment led to private investment crowding out in Belgium, Ireland, Finland, Canada, Sweden, the UK and crowding-in effects in the rest of the countries. Private investment has a positive growth effect in all countries; crowds-out (crowds-in) public investment in Belgium and Sweden (in the rest of the countries). The partial rates of return of public and private investment are mostly positive.

Macroeconomic rates of return of public and private investment : crowding-in and crowding-out effects

Using annual data from 14 European Union countries, plus Canada, Japan and the United States, we evaluate the macroeconomic effects of public and private investment through VAR analysis. From impulse response functions, we are able to assess the extent of crowding-in or crowding-out of both components of investment. We also compute the associated macroeconomic rates of return of public and private investment for each country. The results point mostly to the existence of positive effects of public investment and private investment on output. On the other hand, the crowding-in effects of public investment on private investment vary across countries, while the crowding-in effect of private investment on public investment is more generalised.

The fiscal consequences of deflation : evidence from the golden age of globalization

We study the fiscal consequences of deflation on a panel of 17 economies in the first wave of globalization, between 1870 and 1914. By means of impulse response analyses and panel regressions, we find that a 1 percent fall in the price level leads to an increase in the public debt ratio of about 0.23- 0.32 pp. and accounting for trade openness, monetary policy and the exchange rate raises the absolute value of the coefficient on deflation. Moreover, the public debt ratio increases when deflation is also associated with a period of economic recession. For government revenue, lagged deflation comes out with a statistically significant negative coefficient, while government primary expenditure seems relatively invariant to changes in prices.

The conjugate gradient partitioned block frequency-domain for multichannel adaptive filtering

The conjugate gradient is the most popular optimization method for solving large systems of linear equations. In a system identification problem, for example, where very large impulse response is involved, it is necessary to apply a particular strategy which diminishes the delay, while improving the convergence time. In this paper we propose a new scheme which combines frequency-domain adaptive filtering with a conjugate gradient technique in order to solve a high order multichannel adaptive filter, while being delayless and guaranteeing a very short convergence time.

In-car sound linear simulation

In recent years, vehicle acoustics have gained significant importance in new car development: increasingly advanced infotainment systems for spatial audio and sound enhancement algorithms have become the norm in modern vehicles. In the past, car manufacturers had to build numerous prototypes to study the sound behaviour inside the car cabin or the effect of new algorithms under development. Nowadays, advanced simulation techniques can reduce development costs and time. In this work, after selecting the reference test vehicle, a modern luxury sedan equipped with a high-end sound system, two independent tools were developed: a simulation tool created in the Comsol Multiphysics environment and an auralization tool developed in the Cycling ‘74 MAX environment. The simulation tool can calculate the impulse response and acoustic spectrum at a specific position inside the cockpit. Its input data are the vehicle’s geometry, acoustic absorption parameters of materials, the acoustic characteristics and position of loudspeakers, and the type and position of virtual microphones (or microphone arrays). The simulation tool can also provide binaural impulse responses thanks to Head Related Transfer Functions (HRTFs) and an innovative algorithm able to compute the HRTF at any distance and angle from the head. Impulse responses from simulations or acoustic measurements inside the car cabin are processed and fed into the auralization tool, enabling real-time interaction by applying filters, changing the channels gain or displaying the acoustic spectrum. Since the acoustic simulation of a vehicle involves multiple topics, the focus of this work has not only been the development of two tools but also the study and application of new techniques for acoustic characterization of the materials that compose the cockpit and the loudspeaker simulation. Specifically, three different methods have been applied for material characterization through the use of a pressure-velocity probe, a Laser Doppler Vibrometer (LDV), and a microphone array.

Multidisciplinary optimization of a catamaran's hydrofoil design with dynamic response surface and distributive processing

This paper presents a rational approach to the design of a catamaran's hydrofoil applied within a modern context of multidisciplinary optimization. The approach used includes the use of response surfaces represented by neural networks and a distributed programming environment that increases the optimization speed. A rational approach to the problem simplifies the complex optimization model; when combined with the distributed dynamic training used for the response surfaces, this model increases the efficiency of the process. The results achieved using this approach have justified this publication.