Estudo da distribuição ótima das unidades coletoras de materiais reciclados em São Bernardo do Campo – um mapa para o investidor social

A reciclagem tem-se mostrado excelente oportunidade de novos empreendimentos, traduzindo-se em emprego e renda para diversos níveis sociais. Diante disso, o presente estudo tem o objetivo de mapear os potenciais pontos de oferta de resíduos sólidos e descobrir qual seria a melhor localização geográfica de São Bernardo do Campo para a implantação de unidades coletoras desses materiais reciclados. Os pontos de oferta em potencial obtidos neste estudo passaram a compor um modelo de distribuição em rede, representadas por um grafo, onde os “nós” do grafo representam a localização geográfica de cada um dos pontos e as “arestas” dos grafos as distâncias entre cada uma delas e um ponto estratégico, cujas coordenadas cartesianas constituíram as variáveis do modelo. Para a resolução do modelo, utilizou-se o algoritmo conhecido por Generalized Reduced Gradiente (GRG). Os resultados e metodologia utilizada nesta pesquisa são apresentados e podem subsidiar a tomada de decisão de investidores sociais

Reliable Activation of Immature Neurons in the Adult Hippocampus

Neurons born in the adult dentate gyrus develop, mature, and connect over a long interval that can last from six to eight weeks. It has been proposed that, during this period, developing neurons play a relevant role in hippocampal signal processing owing to their distinctive electrical properties. However, it has remained unknown whether immature neurons can be recruited into a network before synaptic and functional maturity have been achieved. To address this question, we used retroviral expression of green fluorescent protein to identify developing granule cells of the adult mouse hippocampus and investigate the balance of afferent excitation, intrinsic excitability, and firing behavior by patch clamp recordings in acute slices. We found that glutamatergic inputs onto young neurons are significantly weaker than those of mature cells, yet stimulation of cortical excitatory axons elicits a similar spiking probability in neurons at either developmental stage. Young neurons are highly efficient in transducing ionic currents into membrane depolarization due to their high input resistance, which decreases substantially in mature neurons as the inward rectifier potassium (Kir) conductance increases. Pharmacological blockade of Kir channels in mature neurons mimics the high excitability characteristic of young neurons. Conversely, Kir overexpression induces mature-like firing properties in young neurons. Therefore, the differences in excitatory drive of young and mature neurons are compensated by changes in membrane excitability that render an equalized firing activity. These observations demonstrate that the adult hippocampus continuously generates a population of highly excitable young neurons capable of information processing

Computational Model of the Insect Pheromone Transduction Cascade

A biophysical model of receptor potential generation in the male moth olfactory receptor neuron is presented. It takes into account all pre-effector processes—the translocation of pheromone molecules from air to sensillum lymph, their deactivation and interaction with the receptors, and the G-protein and effector enzyme activation—and focuses on the main post-effector processes. These processes involve the production and degradation of second messengers (IP3 and DAG), the opening and closing of a series of ionic channels (IP3-gated Ca2+ channel, DAG-gated cationic channel, Ca2+-gated Cl− channel, and Ca2+- and voltage-gated K+ channel), and Ca2+ extrusion mechanisms. The whole network is regulated by modulators (protein kinase C and Ca2+-calmodulin) that exert feedback inhibition on the effector and channels. The evolution in time of these linked chemical species and currents and the resulting membrane potentials in response to single pulse stimulation of various intensities were simulated. The unknown parameter values were fitted by comparison to the amplitude and temporal characteristics (rising and falling times) of the experimentally measured receptor potential at various pheromone doses. The model obtained captures the main features of the dose–response curves: the wide dynamic range of six decades with the same amplitudes as the experimental data, the short rising time, and the long falling time. It also reproduces the second messenger kinetics. It suggests that the two main types of depolarizing ionic channels play different roles at low and high pheromone concentrations; the DAG-gated cationic channel plays the major role for depolarization at low concentrations, and the Ca2+-gated Cl− channel plays the major role for depolarization at middle and high concentrations. Several testable predictions are proposed, and future developments are discussed

DSP Design With Hardware Accelerator For Convolutional Neural Networks

Convolutional Neural Networks impressed the world in 2012 by reaching state-of-the-art accuracy levels in the ImageNet Large Scale Visual Recognition Challenge. The era of machine learning has arrived and with it countless applications varying from autonomous driving to unstructured robotic manipulation. Computational complexity in the past years has grown exponentially, requiring highly efficient low power new hardware architectures, capable of executing those. In this work, we have performed optimization in three levels of hardware design: from algorithmic, to system, and accelerator level. The design of a DSP with Tensilica and the integration of Xenergic dual port SRAMs, for direct memory access of a convolution hardware accelerator, lead to four orders speed-up on the initial identified bottleneck, causing an estimated three times final speed-up of a single handwritten classification image compared to the pure software implementation. Higher speed-up is expected for deeper convolutional architectures and larger image dimensions, due to the linear time complexity scaling of the convolution hardware accelerator in comparison to conventional non-linear software-based approaches.Artificial Intelligence is becoming more and more used in newer technologies, from mobile phones featuring voice detection to autonomous driving cars and also in the new industries. For such applications the "intelligence" requirements are increasing. Today much computations are solved by using the cloud. For example, in mobile phones, voice assistance only works with an internet connection. The same approaches are not possible for autonomic controlled vehicles. The essential control features have to be inside the vehicle. Therefore we are in need to bring Artificial Intelligence into mobile devices. This thesis aims to implement a benchmark classification problem (MNIST) by using a programmable processor, designed with a commercial tool, and a flexible hardware accelerator to speed up a convolutional neural network that recognizes handwritten digits between 0 and 9. Therefore we have designed and trained a reference architecture in the programming language Python, from which the weights were obtained to implement the same architecture on the designed processor (by using C/C++). By investigation of the most resources consuming functions, we have figured out that the convolution has the highest computation cost. Hence the accelerator was implemented and instructions added, directly connecting it to the processor. Results obtained achieved four orders of magnitude total speed-up of the identified bottleneck. Yielding in an estimated three times final speed-up for a single handwritten classification image, compared to a pure software implementation at the same processor. Additionally, an open-source processor alternative is proposed

Amorpha-4,11-diene synthase: cloning and functional expression of a key enzyme in the biosynthetic pathway of the novel antimalarial drug artemisinin

The sesquiterpenoid artemisinin, isolated from the plant Artemisia annua L., and its semi-synthetic derivatives are a new and very effective group of antimalarial drugs. A branch point in the biosynthesis of this compound is the cyclisation of the ubiquitous precursor farnesyl diphosphate into the first specific precursor of artemisinin, namely amorpha-4,11-diene. Here we describe the isolation of a cDNA clone encoding amorpha-4,11-diene synthase. The deduced amino acid sequence exhibits the highest identity (50%) with a putative sesquiterpene cyclase of A. annua. When expressed in Escherichia coli, the recombinant enzyme catalyses the formation of amorpha-4,11-diene from farnesyl diphosphate. Introduction of the gene into tobacco (Nicotiana tabacum L.) resulted in the expression of an active enzyme and the accumulation of amorpha-4,11-diene ranging from 0.2 to 1.7 ng per g fresh weight.