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Continuous, real-time monitoring of surface seismic activity around the globe is of great interest for acquiring new insight into global tomography analyses and for recognition of seismic patterns leading to potentially hazardous situations. The already-existing telecommunication fiber optic network arises as an ideal solution for this application, owing to its ubiquity and the capacity of optical fibers to perform distributed, highly sensitive monitoring of vibrations at relatively low cost (ultra-high density of point sensors available with minimal deployment of new equipment). This perspective article discusses early approaches on the application of fiber-optic distributed acoustic sensors (DASs) for seismic activity monitoring. The benefits and potential impact of DAS technology in these kinds of applications are here illustrated with new experimental results on teleseism monitoring based on a specific approach: the so-called chirped-pulse DAS. This technology offers promising prospects for the field of seismic tomography due to its appealing properties in terms of simplicity, consistent sensitivity across sensing channels, and robustness. Furthermore, we also report on several signal processing techniques readily applicable to chirped-pulse DAS recordings for extracting relevant seismic information from ambient acoustic noise. The outcome presented here may serve as a foundation for a novel conception for ubiquitous seismic monitoring with minimal investment.

With the increasing implementation of renewable energies, the impact that this type of installation can have on the electricity supply grid is of great importance. In this context, the aim of this work is to analyse how the production and injection of electricity generated by a series of small photovoltaic (PV) installations influence some parameters of the electricity grid in the low-voltage (LV) distribution networks to which they are connected, by analysing the basic data provided by the inverters of these installations. The presence of a slight rise in the grid voltage values in the Point of Common Coupling (PCC) as the production of the PV plants increases has been verified, with maximum slopes between 0.95 and 0.00027 V/kW, but which do not result in voltage values close to the limits set by the regulations. In addition to assessing this impact, the results obtained made it possible to determine the hosting capacity that the networks into which these installations inject their energy would have for this type of installation so as not to have a detrimental effect on the voltage values of the grid. The possible influence of the production of PV installations on the voltage imbalance between phases or on the frequency of the grid has also been analysed in this work. Although the values recorded by the inverters have limitations in their measurements that do not make them valid for assessing events such as the presence of harmonics or flickers, they do allow a first analysis to be made of the influence of PV plant production on some grid parameters, without the need to incorporate additional measurement systems in these renewable installations. However, it is important to be aware of the limitations of the measurements of this equipment and, as far as possible, to choose inverter models that carry out this type of measurement as completely as possible.

La Alianza del Pacífico surge como una iniciativa de integración económica. Se espera que se obtenga un PIB combinado de más de 2 billones de dólares, que estaría entre los diez más grandes de la economía mundial. Esta integración ofrece una oportunidad importante para nuevos posicionamientos de sus integrantes. Con el acuerdo, Colombia aspira a un posicionamiento como líder regional en materia de seguridad, a través de propuestas de acciones integrales ante las nuevas amenazas, particular-mente, el narcotráfico. El objetivo de este artículo es examinar las posibilidades que tendría Colombia para cumplir con dicho posicionamiento. Con este fin, se estudiarán las premisas del realismo estructural que sostienen que la Alianza del Pacífico es una oportunidad para que Colombia supere el rezago en materia de integración y para que conforme alianzas estratégicas con otros actores internacionales en aras a coadyuvar no solo a la seguridad de los miembros de la Alianza, sino de la región.

Inflammatory bowel diseases (IBD) are characterized by chronic dysregulation of immune homeostasis, epithelial demise, immune cell activation, and microbial translocation. Each of these processes leads to proinflammatory changes via the release of cytokines, damage-associated molecular patterns (DAMPs), and pathogen-associated molecular patterns (PAMPs), respectively. The impact of these noxious agents on the survival and function of the enteric nervous system (ENS) is poorly understood. Here, we show that in contrast to an expected decrease, experimental as well as clinical colitis causes an increase in the transcript levels of enteric neuronal and glial genes. Immunostaining revealed an elevated neuronal innervation of the inflamed regions of the gut mucosa. The increase was seen in models with overt damage to epithelial cells and models of T cell-induced colitis. Transcriptomic data from treatment naïve pediatric IBD patients also confirmed the increase in the neuroglial genes and were replicated on an independent adult IBD dataset. This induction in the neuroglial genes was transient as levels returned to normal upon the induction of remission in both mouse models as well as colitis patients. Our data highlight the dynamic and robust nature of the enteric nervous system in colitis and open novel questions on its regulation.

In recent years, the use of highly flexible wings in aerial vehicles (e.g., aircraft or drones) has been attracting increasing interest, as they are lightweight, which can improve fuel-efficiency and distinct flight performances. Continuous wing monitoring can provide valuable information to prevent fatal failures and optimize aircraft control. In this paper, we demonstrate the capabilities of a distributed optical fiber sensor based on time-expanded phase-sensitive optical time-domain reflectometry (TE-ΦOTDR) technology for structural health monitoring of highly flexible wings, including static (i.e., bend and torsion), and dynamic (e.g., vibration) structural deformation. This distributed sensing technology provides a remarkable spatial resolution of 2 cm, with detection and processing bandwidths well under the MHz, arising as a novel, highly efficient monitoring methodology for this kind of structure. Conventional optical fibers were embedded in two highly flexible specimens that represented an aircraft wing, and different bending and twisting movements were detected and quantified with high sensitivity and minimal intrusiveness.

Rationale: Lipoprotein glomerulopathy (LPG) is a rare renal disorder that features glomerular capillary lipoprotein thrombi, proteinuria, and progressive renal failure. Although most reported cases describe involvement in Asian patients, occurrence in Caucasian and other ethnicities has also been reported. Presenting concern: A 28-year-old Hispanic female with a past medical history of hypertension, high cholesterol, gastritis, and a strong family history of renal disease presented with abdominal pain. On admission, her blood pressure was elevated. A computed tomography scan was unremarkable. Her laboratory studies showed proteinuria, high creatinine level, and an abnormal lipid profile. Diagnosis: The kidney biopsy showed glomerular capillary lipoprotein thrombi that stained positively for Oil-Red-O, confirming the lipid nature of the material consistent with LPG. Intervention: After stabilizing her blood pressure, the patient was started on fenofibrate to treat her high cholesterol and improve her renal function. Outcome: Her lipid profile and renal function were initially improved. However, after one year of treatment, her renal function started to decline and the patient was referred to a transplant center for further management. Novel finding: To the best of our knowledge, this the first reported incidence of LPG in a Hispanic female.

As Germany struggles to meet its near-term emissions reduction targets in lagging sectors like heating or transport, the need to identify energy transition pathways beyond power generation is urgent. This paper presents an investigation of tangible and climate-friendly transformation paths to replace the existing coal-fired units used for heat and power generation in Berlin with a largely CO2-free innovative technology mix. Although the literature has extensively covered the decarbonization of the power generation sector on different geographic scales, few studies have focused on the decarbonization of the heat sector in cities with large district heating networks, like Berlin. This paper aims to fill this gap. The proposed methodology combines three key elements: (1) scenario analysis including high-fidelity models of the European power market and the heat demand in Berlin, (2) evaluation of energy potential from low-carbon alternative sources, and (3) a techno-economic portfolio optimization. The results suggest that a coal phase-out by 2030 is feasible without any discontinuities in the provision of heat. Although low-carbon sources could partially substitute coal-based heat, they would not be sufficient to replace it completely. Thus, a gas-based hydrogen-ready combined heat and power plant linked with a power-to-heat plant would be required to fill the gap.

ABA is involved in plant responses to a broad range of pathogens and exhibits complex antagonistic and synergistic relationships with salicylic acid (SA) and ethylene (ET) signaling pathways, respectively. However, the specific receptor of ABA that triggers the positive and negative responses of ABA during immune responses remains unknown. Through a reverse genetic analysis, we identified that PYR1, a member of the family of PYR/PYL/RCAR ABA receptors, is transcriptionally upregulated and specifically perceives ABA during biotic stress, initiating downstream signaling mediated by ABA-activated SnRK2 protein kinases. This exerts a damping effect on SA-mediated signaling, required for resistance to biotrophic pathogens, and simultaneously a positive control over the resistance to necrotrophic pathogens controlled by ET. We demonstrated that PYR1-mediated signaling exerted control on a priori established hormonal cross-talk between SA and ET, thereby redirecting defense outputs. Defects in ABA/PYR1 signaling activated SA biosynthesis and sensitized plants for immune priming by poising SA-responsive genes for enhanced expression. As a trade-off effect, pyr1-mediated activation of the SA pathway blunted ET perception, which is pivotal for the activation of resistance towards fungal necrotrophs. The specific perception of ABA by PYR1 represented a regulatory node, modulating different outcomes in disease resistance.

Parking block regions host dangerous behaviors that can be detected from a surveillance camera perspective. However, these regions are often occluded, subject to ground bumpiness or steep slopes, and thus they are hard to segment. Firstly, the paper proposes a pyramidal solution that takes advantage of satellite views of the same scene, based on a deep Convolutional Neural Network (CNN). Training a CNN from the surveillance camera perspective is rather impossible due to the combinatory explosion generated by multiple point-of-views. However, CNNs showed great promise on previous works over satellite images. Secondly, even though there are many datasets for occupancy detection in parking lots, none of them were designed to tackle the parking block segmentation problem directly. Given the lack of a suitable dataset, we also propose APKLOT, a dataset of roughly 7000 polygons for segmenting parking blocks from the satellite perspective and from the camera perspective. Moreover, our method achieves more than 50% intersection over union (IoU) in all the testing sets, that is, at both the satellite view and the camera view.

Until recently, the amount of solar irradiance reaching the Earth surface was considered to be a steady value over the years. However, there is increasing observational evidence showing that this quantity undergoes substantial variations over time, which need to be addressed in different scenarios ranging from climate change to solar energy applications. With the growing interest in developing solar energy technology with enhanced efficiency and optimized management, the monitoring of solar irradiance at the ground level is now considered to be a fundamental input in the pursuit of that goal. Here, we propose the first fiber-based distributed sensor able of monitoring ground solar irradiance in real time, with meter scale spatial resolutions over distances of several tens of kilometers (up to 100 km). The technique is based on an optical fiber reflectometry technique (CP-ϕOTDR), which enables real time and long-range high-sensitivity bolometric measurements of solar radiance with a single optical fiber cable and a single interrogator unit. The method is explained and analyzed theoretically. A validation of the method is proposed using a solar simulator irradiating standard optical fibers, where we demonstrate the ability to detect and quantify solar irradiance with less than a 0.1 W/m2 resolution.

Whether patients waitlisted for a second transplant after failure of a previous kidney graft have higher mortality than transplant-näive waitlisted patients is uncertain.We assessed the relationship between a failed transplant and mortality in 3851 adult KT candidates, listed between 1984-2012, using a competing risk analysis in the total population and in a propensity score-matched cohort. Mortality was also modeled by inverse probability weighting (IPTW) competing risk regression.At waitlist entry 225 (5.8%) patients had experienced transplant failure. All-cause mortality was higher in the post-graft failure group (16% vs. 11%; P = 0.033). Most deaths occurred within three years after listing. Cardiovascular disease was the leading cause of death (25.3%), followed by infections (19.3%). Multivariate competing risk regression showed that prior transplant failure was associated with a 1.5-fold increased risk of mortality (95% confidence interval [CI], 1.01-2.2). After propensity score matching (1:5), the competing risk regression model revealed a subhazard ratio (SHR) of 1.6 (95% CI, 1.01-2.5). A similar mortality risk was observed after the IPTW analysis (SHR, 1.7; 95% CI, 1.1-2.6).Previous transplant failure is associated with increased mortality among KT candidates after relisting. This information is important in daily clinical practice when assessing relisted patients for a retransplant.

Delays in transportation due to congestion generated by public and private transportation are common in many urban areas of the world. To make transportation systems more efficient, intelligent transportation systems (ITS) are currently being developed. One of the objectives of ITS is to detect congested areas and redirect vehicles away from them. However, most existing approaches only react once the traffic jam has occurred and, therefore, the delay has already spread to more areas of the traffic network. We propose a vehicle redirection system to avoid congestion that uses a model based on deep learning to predict the future state of the traffic network. The model uses the information obtained from the previous step to determine the zones with possible congestion, and redirects the vehicles that are about to cross them. Alternative routes are generated using the entropy-balanced k Shortest Path algorithm (EBkSP). The proposal uses information obtained in real time by a set of probe cars to detect non-recurrent congestion. The results obtained from simulations in various scenarios have shown that the proposal is capable of reducing the average travel time (ATT) by up to 19%, benefiting a maximum of 38% of the vehicles.

In various applications, damping from the surrounding fluid severely degrades the performance of micro-electro-mechanical systems (MEMS). In this paper, mechanical amplification through parametric resonance was investigated in a piezoelectrically actuated MEMS to overcome the effects of damping. The device was fabricated using the PiezoMUMPS process, which is based on a Silicon-on-Insulator (SOI) process with an additional aluminum nitride (AlN) layer. Here, a double-clamped cantilever beam with a concentrated mass at the center was excited at its first resonance mode (out-of-plane motion) in air and at atmospheric conditions. A parametric signal modulating the stiffness of the beam was added at twice the frequency of the excitation signal, which was swept through the resonance frequency of the mode. The displacement at the center of the device was detected optically. A four-fold increase in the quality-factor, Q, of the resonator was obtained at the highest values in amplitude used for the parametric excitation. The spring modulation constant was obtained from the effective quality-factor, Q e f f , versus parametric excitation voltage curve. This study demonstrates that through these methods, significant improvements in performance of MEMS in fluids can be obtained, even for devices fabricated using standard commercial processes.

People interact with systems and applications through several devices and are willing to share information about preferences, interests and characteristics. Social networking profiles, data from advanced sensors attached to personal gadgets, and semantic web technologies such as FOAF and microformats are valuable sources of personal information that could provide a fair understanding of the user, but profile information is scattered over different user models. Some researchers in the ubiquitous user modeling community envision the need to share user model’s information from heterogeneous sources. In this paper, we address the syntactic and semantic heterogeneity of user models in order to enable user modeling interoperability. We present a dynamic user profile structure based in Simple Knowledge Organization for the Web (SKOS) to provide knowledge representation for ubiquitous user model. We propose a two-tier matching strategy for concept schemas alignment to enable user modeling interoperability. Our proposal is proved in the application scenario of sharing and reusing data in order to deal with overweight and obesity.

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs’ context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs’ categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs’ categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs’ categories are provided. The experimental results show that the recommendations suggested by HyRA are promising.

Review of Rebecca Riger Tsurumi. The Closed Hand: Images of the Japanese in Modern Peruvian Literature . West Lafayette, Indiana: Purdue UP, 2012. xv + 314 pp.

Tissues and biomaterials used for corneal surface repair require fulfilling specific optical standards prior to implantation in the patient. However, there is not a feasible evaluation method to be applied in clinical or Good Manufacturing Practice settings. In this study, we describe and assess an innovative easy-applied photographic-based method (PBM) for measuring functional optical blurring and transparency in corneal surface grafts.Plastic compressed collagen scaffolds (PCCS) and multilayered amniotic membranes (AM) samples were optically and histologically evaluated. Transparency and image blurring measures were obtained by PBM, analyzing photographic images of a standardized band pattern taken through the samples. These measures were compared and correlated to those obtained applying the Inverse Adding-Doubling (IAD) technique, which is the gold standard method.All the samples used for optical evaluation by PBM or IAD were histological suitable. PCCS samples presented transmittance values higher than 60%, values that increased with increasing wavelength as determined by IAD. The PBM indicated that PCCS had a transparency ratio (TR) value of 80.3 ± 2.8%, with a blurring index (BI) of 50.6 ± 4.2%. TR and BI obtained from the PBM showed a high correlation (ρ>|0.6|) with the diffuse transmittance and the diffuse reflectance, both determined using the IAD (p

Review of Abraham Acosta. Thresholds of Illiteracy: Theory, Latin America, and the Crisis of Resistance . New York: Fordham UP, 2014. xiv + 276 pp.

[This corrects the article DOI: 10.1371/journal.pone.0142099.].

The combustion of coal wastes resulting from mining is of particular environmental concern, and the importance of proper management involving real-time assessment of their status and identification of probable evolution scenarios is recognized. Continuous monitoring of the combustion temperature and emission levels of certain gases allows for the possibility of planning corrective actions to minimize their negative impact on the surroundings. Optical fiber technology is well suited to this purpose and here we describe the main attributes and results obtained from a fiber optic sensing system projected to gather data on distributed temperature and gas emissions in these harsh environments.

Geographical Information Systems (GIS) are often used to assess and monitor the environmental impacts caused by mining activities. The aim of this work was to develop a new application to produce dynamic maps for monitoring the temperature variations in a self-burning coal waste pile, under a GIS open source environment—GIS-ECOAL (freely available). The performance of the application was evaluated with distributed temperature measurements gathered in the S. Pedro da Cova (Portugal) coal waste pile. In order to obtain the temperature data, an optical fiber cable was disposed over the affected area of the pile, with 42 location stakes acting as precisely-located control points for the temperature measurement. A monthly data set from July (15 min of interval) was fed into the application and a video composed by several layouts with temperature measurements was created allowing for recognizing two main areas with higher temperatures. The field observations also allow the identification of these zones; however, the identification of an area with higher temperatures in the top of the studied area was only possible through the visualization of the images created by this application. The generated videos make possible the dynamic and continuous visualization of the combustion process in the monitored area.

This paper presents a novel surveillance system aimed at the detection and classification of threats in the vicinity of a long gas pipeline. The sensing system is based on phase-sensitive optical time domain reflectometry (ϕ-OTDR) technology for signal acquisition and pattern recognition strategies for threat identification. The proposal incorporates contextual information at the feature level and applies a system combination strategy for pattern classification. The contextual information at the feature level is based on the tandem approach (using feature representations produced by discriminatively-trained multi-layer perceptrons) by employing feature vectors that spread different temporal contexts. The system combination strategy is based on a posterior combination of likelihoods computed from different pattern classification processes. The system operates in two different modes: (1) machine + activity identification, which recognizes the activity being carried out by a certain machine, and (2) threat detection, aimed at detecting threats no matter what the real activity being conducted is. In comparison with a previous system based on the same rigorous experimental setup, the results show that the system combination from the contextual feature information improves the results for each individual class in both operational modes, as well as the overall classification accuracy, with statistically-significant improvements.

Obesity, is a chronic, biological, preventable, and treatable disease. The accumulation of fat mass causes physical changes (adiposity), metabolic and hormonal changes due to adipose tissue dysfunction (adiposopathy), and psychological changes. Bariatric endocrinology was conceived from the need to address the neuro-endocrinological derangements that are associated with adiposopathy, and from the need to broaden the scope of the management of its complications. In addition to the well-established metabolic complications of overweight and obesity, adiposopathy leads to hyperinsulinemia, hyperleptinemia, hypoadiponectinemia, dysregulation of gut peptides including GLP-1 and ghrelin, the development of an inflammatory milieu, and the strong risk of vascular disease. Therapy for adiposopathy hinges on effectively lowering the ratio of orexigenic to anorexigenic signals reaching the the hypothalamus and other relevant brain regions, favoring a lower caloric intake. Adiposopathy, overweight and obesity should be treated indefinitely with the specific aims to reduce fat mass for the adiposity complications, and to normalize adipose tissue function for the adiposopathic complications. This paper defines the principles of medical practice in bariatric endocrinology—the treatment of overweight and obesity as means to treat adiposopathy and its accompanying metabolic and hormonal derangements.

O que justificaria um Dossiê sobre Trabalho e Educação no Campo? A necessidade de desocultar o trabalho no campo e politizar o trato dado à educação do campo nas pesquisas, no pensamento e nas políticas educacionais. A primeira constatação é que a relação trabalho, terra, educação vai merecendo atenção nas pesquisas, na produção teórica e nas políticas. Entretanto, essa relação ainda carece de maior centralidade. Uma relação que exige ser desocultada, afirmada e legitimada no pensamento educacional. A diversidade de textos se propõe essa tarefa.

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms.

The purpose of this paper is to review the recent results of the authors in the area of infectious disease modelling by means of branching stochastic processes. This is a new approach involving age-dependent branching models, which turned out to be more appropriate and flexible for describing the spread of an infection in a given population, than discrete time ones. Concretely, Bellman-Harris and Sevast’yanov’s branching processes are investigated. It is justified that the proposed models are proper candidates as models of infectious diseases with incubation period like measles, mumps, avian flu, etc. It is worth to notice that in general the developed methodology is applicable to the diseases that follow the so-called SIR (susceptible- infected-removed) scheme in terms of epidemiological models. Two policies of extra-vaccination level are proposed and compared on the ground of simulation examples.