Visualizing Street Pavement Anomalies through Fog Computing V2I Networks and Machine Learning.

Analyzing data related to the conditions of city streets and avenues could help to make better decisions about public spending on mobility. Generally, streets and avenues are fixed as soon as they have a citizen report or when a major incident occurs. However, it is uncommon for cities to have real-time reactive systems that detect the different problems they have to fix on the pavement. This work proposes a solution to detect anomalies in streets through state analysis using sensors within the vehicles that travel daily and connecting them to a fog-computing architecture on a V2I network. The system detects and classifies the main road problems or abnormal conditions in streets and avenues using Machine Learning Algorithms (MLA), comparing roughness against a flat reference. An instrumented vehicle obtained the reference through accelerometry sensors and then sent the data through a mid-range communication system. With these data, the system compared an Artificial Neural Network (supervised MLA) and a K-Nearest Neighbor (Supervised MLA) to select the best option to handle the acquired data. This system makes it desirable to visualize the streets' quality and map the areas with the most significant anomalies.

Stress alters the expression of cancer-related genes in the prostate.

BACKGROUND: Prostate cancer is a major contributor to mortality worldwide, and significant efforts are being undertaken to decipher specific cellular and molecular pathways underlying the disease. Chronic stress is known to suppress reproductive function and promote tumor progression in several cancer models, but our understanding of the mechanisms through which stress contributes to cancer development and progression is incomplete. We therefore examined the relationship between stress, modulation of the gonadotropin-releasing hormone (GnRH) system, and changes in the expression of cancer-related genes in the rat prostate. METHODS: Adult male rats were acutely or repeatedly exposed to restraint stress, and compared to unstressed controls and groups that were allowed 14 days of recovery from the stress. Prostate tissue was collected and frozen for gene expression analyses by PCR array before the rats were transcardially perfused; and brain tissues harvested and immunohistochemically stained for Fos to determine neuronal activation. RESULTS: Acute stress elevated Fos expression in the paraventricular nucleus of the hypothalamus (PVH), an effect that habituated with repeated stress exposure. Data from the PCR arrays showed that repeated stress significantly increases the transcript levels of several genes associated with cellular proliferation, including proto-oncogenes. Data from another array platform showed that both acute and repeated stress can induce significant changes in metastatic gene expression. The functional diversity of genes with altered expression, which includes transcription factors, growth factor receptors, apoptotic genes, and extracellular matrix components, suggests that stress is able to induce aberrant changes in pathways that are deregulated in prostate cancer. CONCLUSIONS: Our findings further support the notion that stress can affect cancer outcomes, perhaps by interfering with neuroendocrine mechanisms involved in the control of reproduction.

Effects of furadan in the brown mussel Perna perna and in the mangrove oyster Crassostrea rhizophorae.

Furadan is a carbamate pesticide used widely to combat agricultural pests. However little information is available about the toxicity of furadan in aquatic macroinvertebrates. The in vivo effects of furadan were evaluated in mussels, Perna perna, and oysters, Crassostrea rhizophorae. Glutathione S-transferase (GST), catalase (CAT) and cholinesterase (ChE) activities were measured in the gills of both species exposed to furadan (100 microg/l) for 96 h. No changes were observed in GST activity in the exposed groups. CAT activity was higher (9%) in the oysters exposed to furadan. ChE activity was inhibited by 64 and 35%, respectively, in C. rhizophorae and P. perna exposed to furadan, suggesting that the former is more susceptible to the toxic effects of furadan.