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The straightforward synthesis of copper(I) salicylate from salicylic acid and copper(I) oxide is described for the first time and its identity confirmed by XPS and XRDP techniques. The copper(I) salicylate produced in this way was used as catalyst for the efficient and selective preparation of both 1-acyloxy-1,2,3-triazoles and 1-sulfonyl-1,2,3-triazoles through the CuAAC approach.

Heteroaromatic biaryls are core scaffolds found in a plethora of pharmaceuticals, however, their direct synthesis by the Suzuki cross-coupling is limited to heteroaromatic halide starting materials. Here, we report a direct synthesis of diverse nitrogen-containing heteroaromatic biaryls by Pd-catalyzed decarbonylative Suzuki cross-coupling of widely available heterocyclic carboxylic acids with arylboronic acids. The practical and modular nature of this cross-coupling enabled the straightforward preparation of >45 heterobiaryl products using pyridines, pyrimidines, pyrazines and quinolines in excellent yields. We anticipate that the modular nature of this protocol will find broad application in medicinal chemistry and drug discovery research.

Cancer is one of the main causes of death in dogs and cats. What was once considered a death sentence is now a disease that can be treated and in most cases, it is possible to extend survival times with good quality of life. Antineoplastic treatment is usually a combination of multiple therapeutic modalities, in which surgery plays an important role for diagnosis and local control of the disease. Chemotherapy, and most recently immunotherapy, help in the systemic control of the remaining disease. Other modalities such as electrochemotherapy, radiotherapy and cryosurgery can also help in the management of cancer patients. In Mexico, oncology is still a novel medical specialty, but one in constant development.

Stabilized by a bulky N‐heterocyclic carbene [BPDPr, 1,3‐bis(2,6‐diisopropylphenyl)‐1,3‐diazonine‐2‐ylidene] ligand, new silver carboxylate complexes of the form BPDPrAgO2C‐R (R=Me, Ph) have been synthesized and fully characterized in solution and in the solid state and implemented as sole catalysts (base‐, additive‐, and, in some cases, solvent‐free) in the challenging fixation of carbon dioxide to unsubstituted propargylic derivatives for the synthesis of oxazolidinones and α‐methylene cyclic carbonates. Derived from X‐ray diffraction studies, the molecular geometry and the concept of buried volume were employed to describe the structural and steric features of these silver complexes. Their stability and efficiency as catalysts have been demonstrated by the synthesis of 29 carboxylation products (72–98 % yield) at low catalyst loadings (0.01–1.5 mol%). Characteristics are high turnover numbers (up to 9400), catalyst recyclability (up to 96 % yield after the 7th cycle with no decomposition of the silver complex), and the possibility to scale‐up the reaction., CO2 fixation: The first expanded ring N‐heterocyclic carbene silver carboxylate complexes are efficient and reusable catalysts in the chemical fixation of carbon dioxide to unsubstituted propargylic derivatives under homogeneous or heterogeneous reaction conditions.

This critical and conceptual analysis problematizes the machismo binary and situates it in a third space framework. It explores Latinx males’ higher education experiences and how machismo influences academic decision-making. Situating Latinx males’ college-going in the third space provides a more nuanced portrayal of their academic decision-making across diverse postsecondary settings. In doing so, the Latinx Gender Identity Development Model for Latinx Males in the Third Space is proposed and connects machismo with other domains such as marianismo, caballerismo and familismo. The proposed framework is illustrated by applying it to Latinx males across critical dimensions that impact their decision-making in the higher education landscape.

This article explores the ethical and clinical issues that may arise when utilizing group psychotherapy to work with transgender and gender diverse (TGD) individuals. Considering the unique barrier...

The synthesis and full characterization of new air-stable AgI and CuI complexes bearing structurally bulky expanded-ring N-heterocyclic carbene (erNHC) ligands is presented. The condensation of protonated NHC salts with Ag2 O afforded a collection of AgI complexes, and their first use as ligand transfer reagents led to novel isostructural CuI or AuI complexes. In situ deprotonation of the NHC salts in the presence of a copper(I) source, provides a library of new CuI complexes. The solid-state structures feature large N-CNHC -N angles (118-128°) and almost identical angles between the aryl groups on the nitrogen atoms and the plane of the N-C-N unit of the carbene (i.e. torsion angles close to 0°). Among the steric parameters, the percent buried volume (%Vbur ) values span easily in the 50-57 % range, and that one of (9-Dipp)CuBr complex (%Vbur =57.5) overcomes to other known erNHC-metal complexes reported to date. Preliminary catalytic experiments in the copper-catalyzed coupling between N-tosylhydrazone and phenylacetylene, afforded 76-93 % product at the 0.5-2.5 mol % catalyst loading, proving the stability of CuI erNHC complexes at elevated temperatures (100 °C).

The connection between digital literacy and the three core dimensions of psychological well-being is not yet well understood, and the evidence is controversial. We analyzed a sample of 2,314 individuals, aged 50 years and older, that participated in the English Longitudinal Study of Aging. Participants were clustered according to drivers of psychological well-being using Self-Organizing Maps. The resulting groups were subsequently studied separately using generalized estimating equations fitted on 2-year lagged repeated measures using three scales to capture the dimensions of well-being and Markov models. The clustering analysis suggested the existence of four different groups of participants. Statistical models found differences in the connection between internet use and psychological well-being depending on the group. The Markov models showed a clear association between internet use and the potential for transition among groups of the population characterized, among other things, by higher levels of psychological well-being.

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The authors of this article present content, outcomes, and analysis of testimonios created and used by Latino male adolescents during group counseling. Testimonios, a verbal rendition of the journe...

A doctoral student in counseling psychology, sociology of education scholar, and a counselor and school psychologist extend the work of the canonical theoretical framework and testimonios in Tellin...

Background: Solitary bone plasmacytoma is a plasmatic cell dyscrasia; its presentation in the posterior fossa is very rare. Case Description: We present two cases, a 59-year-old male and a 50-year-old female, both with heterogeneous clinical presentation. One had symptoms compatible with endocranial hypertension, and the other presented with a hemispheric cerebellar syndrome and ipsilateral trigeminal neuralgia. They were both related to an intraosseous tumor of the occipital region near the torcula with large extension to the posterior fossa. The diagnosis of a plasma cell neoplasm arising from the diploe of the squamous portion of the occipital bone was confirmed with immunohistochemistry. Conclusion: The treatment for a cranial tumor that is suspected to be a solitary bone plasmacytoma requires a multidisciplinary team to diagnose, plan a total resection, and after surgery continue with the follow-up of the patient. Solitary bone plasmacytoma should be considered as a differential diagnosis for a tumor that produces cancellous bone widening without sclerotic borders.

Convective weather is a large source of disruption for air traffic management operations. Being able to predict thunderstorms the day before operations can help traffic managers plan around weather and improve air traffic flow management operations. In this paper, machine learning is applied on data from satellite storm observations and ensemble numerical weather prediction products to detect convective weather 36 h in advance. The learning task is formulated as a binary classification problem and a neural network is trained to predict the occurrence of storms. The neural network results are used to develop a probabilistic based convection indicator capable of outperforming existing convection indicators found in the literature. Lastly, applications of the neural network based indicator in an air traffic management setting are presented. financial support of the Spanish Ministry of Science, Innovation and Universities under grant RTI2018-098471-B-C32. The project has received funding from the SESAR Joint Undertaking within the framework of the European Union’s Horizon 2020 research and innovation programme under grant agreement No 891965.

The Home Health Care Scheduling Problem involves allocating professional caregivers to patients' places of residence to meet service demands. These services are regular in nature and must be provided at specific times during the week. In this paper, we present a heuristic with two tie-breaking mechanisms suitable for large-scale versions of the problem. The greedy algorithm merges service lots to minimize the accumulated unproductive time. As a result, the solution is restructured in such a way as to increase its efficiency. The approach is tested on a real-world large instance of the problem for a company whose current resource allocation is inefficient. The solutions are benchmarked against the current service assignment and those obtained by a Ward clustering algorithm, and the results show an improvement in efficiency and cost. The authors acknowledge financial support granted by the Spanish Ministry of Science and Innovation under grant TIN2011-28336 (MOVES).

The synthesis and full characterization of new air‐stable AgI and CuI complexes bearing structurally bulky expanded‐ring N‐heterocyclic carbene (erNHC) ligands is presented. The condensation of protonated NHC salts with Ag2O afforded a collection of AgI complexes, and their first use as ligand transfer reagents led to novel isostructural CuI or AuI complexes. In situ deprotonation of the NHC salts in the presence of a copper(I) source, provides a library of new CuI complexes. The solid‐state structures feature large N‐CNHC‐N angles (118–128°) and almost identical angles between the aryl groups on the nitrogen atoms and the plane of the N‐C‐N unit of the carbene (i.e. torsion angles close to 0°). Among the steric parameters, the percent buried volume (%V bur) values span easily in the 50–57 % range, and that one of (9‐Dipp)CuBr complex (%V bur=57.5) overcomes to other known erNHC–metal complexes reported to date. Preliminary catalytic experiments in the copper‐catalyzed coupling between N‐tosylhydrazone and phenylacetylene, afforded 76–93 % product at the 0.5–2.5 mol % catalyst loading, proving the stability of CuI erNHC complexes at elevated temperatures (100 °C)., A unique family of AgI and CuI complexes possessing sterically demanding N‐heterocyclic carbene ligands is described. Their structural and steric profiling reveals the highest buried volumes (%V bur up to 57.5) for any expanded‐ring backbone NHC complex. For the first time, the AgI complexes have been employed as ligand‐transfer reagents while the CuI complexes proved to be efficient candidates for catalysis (see figure).

This study explores the suitability of neural networks with a convolutional component as an alternative to traditional multilayer perceptrons in the domain of trend classification of cryptocurrency exchange rates using technical analysis in high frequencies. The experimental work compares the performance of four different network architectures -convolutional neural network, hybrid CNN-LSTM network, multilayer perceptron and radial basis function neural network- to predict whether six popular cryptocurrencies -Bitcoin, Dash, Ether, Litecoin, Monero and Ripple- will increase their value vs. USD in the next minute. The results, based on 18 technical indicators derived from the exchange rates at a one-minute resolution over one year, suggest that all series were predictable to a certain extent using the technical indicators. Convolutional LSTM neural networks outperformed all the rest significantly, while CNN neural networks were also able to provide good results specially in the Bitcoin, Ether and Litecoin cryptocurrencies. We would also like to acknowledge the financial support of the Spanish Ministry of Science, Innovation and Universities under grant PGC2018-096849-B-I00 (MCFin)

Lean manufacturing practices focus on minimizing all forms of waste from the production system. The applicability of lean manufacturing concepts and principles has often been questioned in sectors including aerospace manufacturing primarily due to their high variety - low volume environments. The key challenges include the difficulty in changing the factory layout, lack of plant-specific manufacturing strategies, lack of benchmarking between manufacturing plants and non-existence of learning through experimentation culture. Consequently, the aerospace manufacturing industries have struggled to implement lean principles over the years successfully. Industry 4.0 is a new paradigm that is significantly influencing several manufacturing industries across the globe. Applying the concepts of Industry 4.0 along with the conventional lean transformation technology could potentially address these challenges. The focus of this research is to study the possibilities of integrating Industry 4.0 tools with existing lean manufacturing philosophies within the aerospace manufacturing sector in order to improve various aspects of manufacturing processes in a cyber-physical environment. A case study is performed considering a quality inspection department in a typical aerospace industry. The case study is simulated using discrete event simulation tool — Arena. The study found that a hybrid approach involving the holistic merger of the lean principles along with the Industry 4.0 tools known as Lean Industry 4.0 is the best way forward for the aerospace manufacturing sector. The outcomes of this research provide an understanding of the role of industry 4.0 paradigm and their implementation in several other high-technology and high-risk manufacturing sectors including life sciences, space, and defense industries.

Nine‐ and ten‐membered N‐heterocyclic carbene (NHC) ligands have been developed and for the first time their gold(I) complexes were synthesized. The protonated NHC pro‐ligands 2 a–h were prepared by the reaction of readily available N,N′‐diarylformamidines with bis‐electrophilic building blocks, followed by anion exchange. In situ deprotonation of the tetrafluoroborates 2 a–h with tBuOK in the presence of AuCl(SMe2) provided fast access to NHC‐gold(I) complexes 3–10. These new NHC‐gold(I) complexes show very good catalytic activity in a cycloisomerization reaction (0.1 mol % catalyst loading, up to 100 % conversion) and their solid‐state structures reveal high steric hindrance around the metal atom (%V bur up to 53.0) which is caused by their expanded‐ring architecture., Meet the new members of the golden family: A new series of N‐heterocyclic carbene ligands bearing a rigid expanded‐ring backbone, supply unique stability to the gold(I) complex, and provide a high steric hindrance towards the metal center, which results in an excellent catalytic activity.

There has been a growing recognition of the role that various aspects of culture play in the theory and practice of psychotherapy. One aspect of culture that has received little attention, however, is language. Specifically, we lack comprehensive understanding of the value bilingual clients find in expressing thoughts, feelings, and experiences in two languages. Research that enhances understanding of the role that bilingualism plays in psychotherapy may thus help improve the quality of services that bilingual clients receive. To this end, we interviewed eight bilingual Latinx people (seven of Mexican descent and one Puerto Rican) between the ages of 20 and 37 about their experience using Spanish and English in psychotherapy. Using descriptive phenomenological analysis, we identified and interpreted 250 meaning units that were grouped into five overarching themes: (a) Enhancing Expression and Understanding, (b) An Affirming Experience, (c) Facilitating Therapeutic Processes, (d) Utility of a Therapist Bilingual Orientation, and (e) Strengthening the Therapeutic Relationship. Findings speak to the value for bilingual Latinx clients of being able to use both of their languages in psychotherapy. Implications for multicultural psychotherapy research and practice are discussed. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Rubbing is an important problem in machinery industry which occurs when a rotating element hits a stationary part. This rotor-to-stator rub may result in the catastrophic breakdown of the machine. In this work, the phenomenon of rotor rubbing is analyzed from the perspective that the signal analysis tools that are in use today to detect this defect emphasize or highlight particular aspects of the studied phenomenon. So, sometimes it is necessary to use more than one tool to deepen the understanding of the problem. For this purpose, laboratory tests were performed on a rotor system with a rubbing mechanism, while mechanical vibrations were measured with an accelerometer and a data acquisition system. Experiments were carried out for fixed rotor speed, and for run-up and run-down rotor speed conditions. The analysis approach included various processing tools to study their capabilities in rubbing detection: Root Mean Square (RMS), Fourier transform, Wavelet transform and Hurst exponent. Fixed rubbing conditions show similar results for RMS and Hurst exponent on the information obtained. For variable run-up and run-down rotor speed conditions, the Hurst exponent shows predictability, a fact that can be used for rub detection. However, the Wavelet and Fourier Transforms operated in a very distinct way. Although both transforms give frequency information, Fourier transform results in a more detailed frequency analysis, while the Wavelet transform can give time localization of the rubbing phenomenon.

Review: Understanding Love: Philosophy, Film, and Fiction, eds. Susan Wolf, Christopher Grau, Oxford, Oxford University Press 2014, 397 pages

En un ciclo de producción de tilapia, se realizó el cultivo de hongos setas, forrajes verdes y cucurbitáceas en un sistema acuapónico, con el objetivo de evaluar la eciencia en la remoción y aprovechamiento de desechos nitrogenados. Para el estudio se usó un sistema de recirculación de tres tinas circulares de 7 m3 , en las que se sembraron 64 tilapias por m3 . En la primera fase, se mantuvieron tres ciclos de cultivo de setas de 20 d, en dos sistemas: acuaponía y riego tradicional. Posteriormente, se realizaron seis ciclos de 12 d de crecimiento de cuatro forrajes verdes: maíz amarillo y blanco, trigo y sorgo, para luego realizar un ciclo de 45 d de pepino y sandía en bicultivo. La producción acumulada total de setas en el tratamiento de acuaponía durante los tres ciclos fue 16 % superior al obtenido con riego tradicional. La mayor producción de forraje en biomasa total fresca se obtuvo el trigo (47.55 kg); la mayor longitud de tallos (27 ± 2.20 cm) y eciencia de remoción de metabolitos nitrogenados en el maíz blanco. Las plantas de pepino y sandía produjeron frutos al segundo mes de cultivo, con rendimiento de 27.15 y 4.84 kg, respectivamente, las cuales fueron más ecientes en aprovechar los metabolitos que las setas y los forrajes. En el ciclo de producción producción de tilapia se puede cultivar diferentes vegetales y aprovechar los metabolitos nitrogenados con acuaponía.

In recent years, the problem of concept drift has gained importance in the financial domain. The succession of manias, panics and crashes have stressed the non-stationary nature and the likelihood of drastic structural or concept changes in the markets. Traditional systems are unable or slow to adapt to these changes. Ensemble-based systems are widely known for their good results predicting both cyclic and non-stationary data such as stock prices. In this work, we propose RCARF (Recurring Concepts Adaptive Random Forests), an ensemble tree-based online classifier that handles recurring concepts explicitly. The algorithm extends the capabilities of a version of Random Forest for evolving data streams, adding on top a mechanism to store and handle a shared collection of inactive trees, called concept history, which holds memories of the way market operators reacted in similar circumstances. This works in conjunction with a decision strategy that reacts to drift by replacing active trees with the best available alternative: either a previously stored tree from the concept history or a newly trained background tree. Both mechanisms are designed to provide fast reaction times and are thus applicable to high-frequency data. The experimental validation of the algorithm is based on the prediction of price movement directions one second ahead in the SPDR (Standard &amp, Poor&rsquo, s Depositary Receipts) S&amp, P 500 Exchange-Traded Fund. RCARF is benchmarked against other popular methods from the incremental online machine learning literature and is able to achieve competitive results.

We have compared the performance of different machine learning techniques for human activity recognition. Experiments were made using a benchmark dataset where each subject wore a device in the pocket and another on the wrist. The dataset comprises thirteen activities, including physical activities, common postures, working activities and leisure activities. We apply a methodology known as the activity recognition chain, a sequence of steps involving preprocessing, segmentation, feature extraction and classification for traditional machine learning methods, we also tested convolutional deep learning networks that operate on raw data instead of using computed features. Results show that combination of two sensors does not necessarily result in an improved accuracy. We have determined that best results are obtained by the extremely randomized trees approach, operating on precomputed features and on data obtained from the wrist sensor. Deep learning architectures did not produce competitive results with the tested architecture.

The home care and scheduling problem (HCSP) consists on the design of a set of routes to be used by caregivers that provide daily assistance at specific times to patients located in a definite geographic area. In this study we propose a modified version of Ant Colony Optimization (ACO), called IACS-HCSP, to approach this task. In order to be used in this problem, ACO requires modifications in the problem representation and additional mechanisms to deal with constraints. We propose a dynamic neighborhood graph and an improved method that constructs the solution that improves its exploration capability over deterministic or greedy heuristic methods. This technique has been applied to a very large real world instance of HCSP for which results are available for comparison. IACS-HCSP is able to improve the previous results on this specific instance in terms of cost. At the same time it can be used to help decision making when there is a choice between competing objectives, because it finds a full range of feasible solutions with different equilibria between time and size of the required labor force.

This paper tries to tackle the modern challenge of practical steganalysis over large data by presenting a novel approach whose aim is to perform with perfect accuracy and in a completely automatic manner. The objective is to detect changes introduced by the steganographic process in those data objects, including signatures related to the tools being used. Our approach achieves this by first extracting reliable regularities by analyzing pairs of modified and unmodified data objects; then, combines these findings by creating general patterns present on data used for training. Finally, we construct a Naive Bayes model that is used to perform classification, and operates on attributes extracted using the aforementioned patterns. This technique has been be applied for different steganographic tools that operate in media files of several types. We are able to replicate or improve on a number or previously published results, but more importantly, we in addition present new steganalytic findings over a number of popular tools that had no previous known attacks. This work was supported by Engineering and Physical Sciences Research Council (EPSRC) Grant EP/N024192/1 (J.C.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This work was supported by European Union’s Horizon 2020 Research and Innovation Programme, Grant agreement No.700326.

This work explores the connection between psychological well-being and Internet use in older adults. The study is based on a sample of 2314 participants in the English Longitudinal Study of Aging. The subjects, aged 50 years and older, were interviewed every two years over the 2006-2007 to 2014-2015 period. The connection between the use of Internet/Email and the main dimensions of psychological well-being (evaluative, hedonic and eudaimonic) was analyzed by means of three generalized estimating equation models that were fitted on 2-year lagged repeated measurements. The outcome variables, the scores on three well-being scales, were explained in terms of Internet/Email use, controlling for covariates that included health and socioeconomic indicators. The results support the existence of a direct relationship between Internet/Email use and psychological well-being. The connection between the main predictor and the score of the participants on the scale used to measure the eudaimonic aspect was positive and statistically significant at conventional levels (p-value: 0.015). However, the relevance of digital literacy on the evaluative and the hedonic components could not be confirmed (p-values for evaluative and hedonic dimensions were 0.078 and 0.192, respectively). This project was funded by the European Union’s CIP (Competitiveness and Innovation Framework Programme) (ICT-PSP-2012) under Grant Agreement No. 325146 (Social Ecosystem for Antiaging, Capacitation andWellbeing—SEACW project).

A polynomial algorithm for the sensor placement for observability problem in Continuous timed Petri nets (ContPN) is presented. Afterwards, an observer design with a single observer structure is proposed to avoid the classical approach requiring one observer for each LS, which becomes prohibited in classes of ContPN. In addition, this observer has the feature that it presents global and finite time convergence to the marking of the ContPN. The effectiveness of our approach is shown through illustrative examples.

The home care crew scheduling (HCCS) problem is a planning task whose goal is to allocate a set of professional caregivers in the most efficient way to perform a number of assistencial and health care visits to the customers private homes. This is part of an important trend in advanced health care systems, to promote "independent living" specially in situations of dependency on long-term care. This not only ensures a higher quality of life but also a lower cost for society. Real instances of the HCCS problem are large and highly constrained due to both caregivers' contract limitations and customers' needs. This paper presents an advanced parallel model that solves HCCS problems using a grid-based asynchronous evolutionary algorithm (EA). Our approach has been tested using a grid computing facility of up to 300 nodes. The algorithm is a modified (1 + lambda) EA, parallelized using a master/worker model that minimizes communication requirements and processor bottlenecks by distributing both the execution of the EA operators and the evaluation of solutions. We have used three large real-world instances provided by a private company to perform experimentation with different configurations of the EA and number of workers. Results show that our algorithm achieves solutions that clearly outperform the solution provided by the company and the grid-based algorithm is able to handle real world HCCS problems The work of Francisco Luna and Juan F. Valenzuela is funded by the Spanish Ministry of Economy, Industry and Competitiveness under contract TIN2016-75097-P. The work of Alejandro Cervantes and Pedro Isasi is funded by the Spanish Ministry of Science and Innovation under contract TIN2011-28336.

OBJECTIVE: Radon is an important risk factor for lung cancer. Here we use maps of the geographic variation in radon to estimate the lung cancer risk associated with living in high radon areas of Canada. METHODS: Geographic variation in radon was estimated using two mapping methods. The first used a Health Canada survey of 14,000 residential radon measurements aggregated to health regions, and the second, radon risk areas previously estimated from geology, sediment geochemistry and aerial gamma-ray spectrometry. Lung cancer risk associated with living in these radon areas was examined using a population-based case-control study of 2,390 lung cancer cases and 3,507 controls collected from 1994-1997 in eight Canadian provinces. Residential histories over a 20-year period were used in combination with the two mapping methods to estimate ecological radon exposures. Hierarchical logistic regression analyses were used to estimate odds ratios for lung cancer incidence, after adjusting for a comprehensive set of individual and geographic covariates. RESULTS: Across health regions in Canada, significant variation in average residential radon concentrations (range: 16-386 Bq/m 3 ) and in high geological-based radon areas (range: 0-100%) is present. In multivariate models, a 50 Bq/m 3 increase in average health region radon was associated with a 7% (95% CI: -6-21%) increase in the odds of lung cancer. For every 10 years that individuals lived in high radon geological areas, the odds of lung cancer increased by 11% (95% CI: 1-23%). CONCLUSIONS: These findings provide further evidence that radon is an important risk factor for lung cancer and that risks are unevenly distributed across Canada.

In the context of forecasting for renewable energy, it is common to produce point forecasts but it is also important to have information about the uncertainty of the forecast. To this extent, instead of providing a single measure for the prediction, lower and upper bound for the expected value for the solar radiation are used (prediction interval). This estimation of optimal prediction intervals requires the simultaneous optimization of two objective measures: on one hand, it is important that the coverage probability of the interval is as close as possible to a given target value. On the other, in order to bound uncertainty, intervals must be narrow; this means that there is a trade-off between both objectives, as narrow intervals reduce the coverage probability for those solutions, as the actual value of solar radiation is more likely to fall outside the predicted margins. In this work we propose a multi-objective evolutionary approach that is able to optimize both goals simultaneously. The proposal uses neural networks to create complex non-linear models whose outputs are the upper and lower limits of the prediction intervals. Results have been compared with a single-objective optimization of similar neural network architectures and a baseline algorithm (quantile estimation with gradient boosting). Results show that the neural network is able to provide accurate results. Also, the multi-objective approach is able to obtain the best results and has also the advantage that a single run is able to obtain prediction intervals for any target coverage probability. This work has been funded by the Spanish Ministry of Science under contract ENE2014-56126-C2-2-R (AOPRIN-SOL project).

Stream Processing has recently become one of the current commercial trends to face huge amounts of data. However, normally these techniques need specific infrastructures and high resources in terms of memory and computing nodes. This paper shows how mini-batch techniques and topology extraction methods can help making gigabytes of data to be manageable for just one server using computationally costly Machine Learning techniques as Support Vector Machines. The algorithm iGNGSVM is proposed to improve the performance of Support Vector Machines in datasets where the data is continuously arriving. It is benchmarked against a mini-batch version of LibSVM, achieving good accuracy rates and performing faster than this.

This paper presents a full approach to outcomes due to the measurement of distance between two points in space, taking as reference XBee signal's (radio waves) attenuation as they travel from point A to B. XBee modules are able to communicate with each other, creating networks which consist of a coordinator, routers and end devices; allowing information flow across the network members. As bits voyage, attenuation is readable, which opens a door to the possibility of creating a positioning system.

Multi-objective optimization problems are often subject to the presence of objectives that require expensive resampling for their computation. This is the case for many robustness metrics, which are frequently used as an additional objective that accounts for the reliability of specific sections of the solution space. Typical robustness measurements use resampling, but the number of samples that constitute a precise dispersion measure has a potentially large impact on the computational cost of an algorithm. This article proposes the integration of dominance based statistical testing methods as part of the selection mechanism of evolutionary multi-objective genetic algorithms with the aim of reducing the number of fitness evaluations. The performance of the approach is tested on five classical benchmark functions integrating it into two well-known algorithms, NSGA-II and SPEA2. The experimental results show a significant reduction in the number of fitness evaluations while, at the same time, maintaining the quality of the solutions. The authors acknowledge financial support granted by the Spanish Ministry of Economy and Competitivity under grant ENE2014-56126-C2-2-R.

Background: Population exposure assessment methods that capture local-scale pollutant variability are needed for large-scale epidemiological studies and surveillance, policy, and regulatory purposes. Currently, such exposure methods are limited. Methods: We created 2006 national pollutant models for fine particulate matter [PM with aerodynamic diameter ≤ 2.5 μm (PM₂.₅)], nitrogen dioxide (NO₂), benzene, ethylbenzene, and 1,3‑butadiene from routinely collected fixed-site monitoring data in Canada. In multiple regression models, we incorporated satellite estimates and geographic predictor variables to capture background and regional pollutant variation and used deterministic gradients to capture local-scale variation. The national NO₂ and benzene models are evaluated with independent measurements from previous land use regression models that were conducted in seven Canadian cities. National models are applied to census block-face points, each of which represents the location of approximately 89 individuals, to produce estimates of population exposure. Results: The national NO₂ model explained 73% of the variability in fixed-site monitor concentrations, PM₂.₅ 46%, benzene 62%, ethylbenzene 67%, and 1,3-butadiene 68%. The NO₂ model predicted, on average, 43% of the within-city variability in the independent NO₂ data compared with 18% when using inverse distance weighting of fixed-site monitoring data. Benzene models performed poorly in predicting within-city benzene variability. Based on our national models, we estimated Canadian ambient annual average population-weighted exposures (in micrograms per cubic meter) of 8.39 for PM₂.₅, 23.37 for NO₂, 1.04 for benzene, 0.63 for ethylbenzene, and 0.09 for 1,3-butadiene. Conclusions: The national pollutant models created here improve exposure assessment compared with traditional monitor-based approaches by capturing both regional and local-scale pollution variation. Applying national models to routinely collected population location data can extend land use modeling techniques to population exposure assessment and to informing surveillance, policy, and regulation.

Canine mammary carcinoma is the most common cancer among female dogs and is often fatal due to the development of distant metastases. In humans, solid tumors are made up of heterogeneous cell populations, which perform different roles in the tumor economy. A small subset of tumor cells can hold or acquire stem cell characteristics, enabling them to drive tumor growth, recurrence and metastasis. In veterinary medicine, the molecular drivers of canine mammary carcinoma are as yet undefined. Here we report that putative cancer stem cells (CSCs) can be isolated form a canine mammary carcinoma cell line, REM134. We show that these cells have an increased ability to form tumorspheres, a characteristic of stem cells, and that they express embryonic stem cell markers associated with pluripotency. Moreover, canine CSCs are relatively resistant to the cytotoxic effects of common chemotherapeutic drugs and ionizing radiation, indicating that failure of clinical therapy to eradicate canine mammary cancer may be due to the survival of CSCs. The epithelial to mesenchymal transition (EMT) has been associated with cancer invasion, metastasis, and the acquisition of stem cell characteristics. Our results show that canine CSCs predominantly express mesenchymal markers and are more invasive than parental cells, indicating that these cells have a mesenchymal phenotype. Furthermore, we show that canine mammary cancer cells can be induced to undergo EMT by TGFβ and that these cells have an increased ability to form tumorspheres. Our findings indicate that EMT induction can enrich for cells with CSC properties, and provide further insight into canine CSC biology.

La prueba de daño en materia de acceso a la información es una herramienta interpretativa para reducir la discrecionalidad en las clasificaciones de reserva de la información. En México, el marco regulatorio toma como referencia el principio de proporcionalidad para la aplicación de la prueba; sin embargo, es necesario aclarar los motivos y estándares de dicha aplicación para comprender la metodología a través de la cual deben llevarse a cabo las argumentaciones que den fundamento a una reserva de información, ya que sin ella el ejercicio seguirá siendo discrecional por parte de los sujetos obligados.

Many commentators warn that oil scarcity increases the likelihood of war; we question this simplistic concept of scarcity-driven wars. Questioning the relationship between violence, scarcity, and o...

"This paper presents the design of a distributed control law for the output regulation and output consen- sus of a set of N agents. In this approach, each agent dynamics is represented by a switched linear system. The representation of the agents is neither constrained to be the same nor to have the same state dimension, and communication among agents is considered to be switching. It is also considered that some agents get the reference to be followed from the output of a virtual agent, and every agent gets the output information of its neighbors. Using this information, every agent computes the exosystem state to solve its individual regulation problem. The approach herein proposed employs a local switched stabilizing feedback for each agent based on a common Lyapunov function. A numerical example is provided in order to illustrate the proposed control law."

Se realizó un estudio prospectivo longitudinal en el Hospital “Dr. Ernesto Guevara de la Serna”, en el período comprendido de enero a diciembre del 2013, con un universo y muestra de 286 pacientes, que acudieron a la consulta de Medicina Natural y Tradicional de forma voluntaria, o que fueron remitidos por otras especialidades médicas con diagnóstico de obesidad y podían o no estar acompañados de otra patología (asma, diabetes mellitus, gota, hipertensión arterial, etc.). A estos pacientes se les realizó diagnóstico oriental, para posterior tratamiento con catgupuntura, la que se aplicó en los puntos escogidos al efecto. Del total de los pacientes (193 femeninas, 93 masculinos) evolucionaron de forma satisfactoria 178 y no así el resto. El grupo de edades que más acudió fue el de 26 a 35 años y este mismo grupo etario fue el que mejor respuesta al tratamiento tuvo, poniéndose de manifiesto la efectividad de la terapia aplicada, a la que se le conjugaron dietoterapia y ejercicios.

El propósito central de este artículo es adelantar un proyecto político y normativo parael establecimiento internacional de los derechos sexuales como derechos humanos.Debido a la organización social del sexo y del género en nuestras sociedades con-temporáneas, consideramos que son urgentes las demandas por diseñar y establecernormas para proteger la diferencia sexual y auspiciar la afirmación de la diversidadsexual. Por un lado, identificamos la necesidad de establecer algunos derechos sexualesnegativos capaces de proteger la integridad sexual de ciertos individuos que histórica-mente han sido marginados y de algunos grupos que suelen ser blanco de la violenciaheterosexista. Por el otro, consideramos necesario promover derechos sexuales positivosque afirmen la diversidad sexual y auspicien vidas sexuales llenas de placer. Sostenemos que para la justificación y aceptación de los derechos sexuales negati-vos sólo se requiere una política y una ética de la tolerancia. En cambio los derechossexuales positivos exigen la adopción de un paradigma político y ético diferente, basa-do en el reconocimiento. El proyecto político de los derechos sexuales positivos busca, enúltima instancia, destruir la hegemonía masculina sobre la práctica y el discurso de lasexualidad, y pretende asimismo descentrar la heterosexualidad. Pese a los límites delos movimientos sociales basados en la identidad sexual, su impacto social y culturalha sido profundo. Por ello opinamos que los derechos sexuales negativos son hoy unproyecto más que factible. Más aún, hemos desarrollado la idea de que la posibilidadde concretar el proyecto de los derechos sexuales positivos resulta de la combinacióncreativa de dos fuerzas. Primero, los potenciales emancipatorios de los movimientossociales basados en la identidad sexual que han permitido mantener un cuestionamientoconstante de la actual organización social de la sexualidad. Segundo, las transforma-ciones profundas en teoría social y filosofía que nos lleva a pensar y experimentar lasexualidad (y sus identidades) de manera no esencialista, descentrada, relacional,interactiva y fluida. Finalmente, esto abre la posibilidad de desestabilizar los efectosque las relaciones de poder tienen sobre el sexo, la sexualidad y la identidad sexual.

Polyethylene films were separated and recovered from polyethylene–aluminum composites derived from recycling multilayer postconsumer aseptic packaging. A brief study about the separation process by dissolving PE–aluminum (PE–Al) composites into a series of organic solvents with a combination of time and temperature is presented. Through this procedure, 56% polyethylene is recovered from this kind of composites in optimized conditions. DSC and TGA studies were performed to determine the thermal stability of recovered polyethylene films and to establish a comparison with a PE reference commercial product, demonstrating that recovered polyethylene films kept their thermal properties.

Derechos reproductivos ha pasado de ser un enunciado descriptivo para convertirse en un área temática con legitimidad de estudio. Sin embargo, su transformación en campo cognoscitivo dependerá de la dinámica que se genere por su relevancia social y política, por su aceptación en comunidades académicas y de las intervenciones conceptuales de los estudiosos. Con base en una reconstrucción histórico-crítica del enunciado, de las dimensiones y las relaciones constitutivas implicadas en su uso contemporáneo, este trabajo elabora una diagramación conceptual y una propuesta analítica, como una contribución a la fundación del campo cognoscitivo.