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Summary While total vessel length is widely recognized as being of fundamental functional significance, opinion is more divided regarding the potential functional importance of vessel element length, a variable that Sherwin Carlquist regarded as functionally significant. We show that vessel element length can, as Carlquist predicted, affect vessel resistance to deformation. Perforation plates are locally thickened annuli, so tubes with annuli resist deformation better than those without, and tubes with closely-spaced annuli resist deformation better than those with distantly spaced ones. However, there is a tradeoff between deformation resistance and conductance. With a comparative analysis across more than 1000 species of angiosperms, we show that both vessel element length and the areas of individual inter-conduit pits scale positively with vessel diameter. Such covariation is expected if plants are to maintain conductance as they grow taller. Congruent with Carlquist’s thinking, we found that species with vessel elements that are exceptionally short tend to grow in drylands, whereas those with vessel elements that are exceptionally long tend to grow in moist climates. Finally, we show evidence suggesting that selection on vessel element length is an important determinant of imperforate tracheary element length. Conversely, the evidence for selection on imperforate tracheary element length affecting vessel element length appears to be weaker. These results seem sufficient to establish that, whatever the functional importance of total vessel length, vessel element length is a variable of functional significance in its own right, congruent with Sherwin Carlquist’s long-held views.

El Archivo Histórico de la Pontificia Universidad Gregoriana conserva entre sus importantes fondos un conjunto documental relacionado con la labor del arquitecto-matemático Juan Bautista Villalpando SJ durante su larga estancia en el Colegio Romano de la Compañía de Jesús (1590-1608), y sobre la preparación del comentario a Ezequiel y la restitución del Templo de Jerusalén contenidas en su obra In Ezechielem explanationes. Este artículo estudia correspondencia enviada por eruditos europeos a Villalpando, junto a un manuscrito ilustrado obra del jesuita, en relación fundamentalmente con la gestación de los aspectos arquitectónicos y gráficos de su proyecto editorial.

Chromatin immunoprecipitation (ChIP-Seq) has emerged as a superior alternative to microarray technology as it provides higher resolution, less noise, greater coverage and wider dynamic range. While ChIP-Seq enables probing of DNA-protein interaction over the entire genome, it requires the use of sophisticated tools to recognize hidden patterns and extract meaningful data. Over the years, various attempts have resulted in several algorithms making use of different heuristics to accurately determine individual peaks corresponding to unique DNA-protein. However, finding all the significant peaks with high accuracy in a reasonable time is still a challenge. In this work, we propose the use of Multi-level thresholding algorithm, which we call LinMLTBS, used to identify the enriched regions on ChIP-Seq data. Although various suboptimal heuristics have been proposed for multi-level thresholding, we emphasize on the use of an algorithm capable of obtaining an optimal solution, while maintaining linear-time complexity. Testing various algorithm on various ENCODE project datasets shows that our approach attains higher accuracy relative to previously proposed peak finders while retaining a reasonable processing speed.

Resumen Objetivo La ecografia intestinal se considera una alternativa para la evaluacion de la recurrencia posquirurgica (RPQ) de la enfermedad de Crohn. El objetivo de este estudio es evaluar la correlacion entre los hallazgos ecograficos y endoscopicos. Metodos Se recogieron de forma retrospectiva los datos de pacientes con enfermedad de Crohn y reseccion ileocecal en los que se habia realizado una colonoscopia y una ecografia intestinal para la deteccion de RPQ. La RPQ se evaluo empleando el indice de Rutgeerts (IR). Los hallazgos ecograficos analizados fueron el grosor de la pared intestinal, la hiperemia parietal por Doppler, la desestructuracion del patron de capas y la proliferacion fibrograsa. Resultados Se incluyo a un total de 31 pacientes, 15 (48,4%) sin recurrencia (IR? Conclusiones En nuestra experiencia, la ecografia tiene una alta rentabilidad diagnostica para la deteccion de RPQ y puede considerarse en muchas ocasiones como una alternativa valida y no invasiva a la ileocolonoscopia.

Data regarding bowel preparation in patients with Inflammatory Bowel Disease (IBD) are scarce.To compare efficacy, safety, and tolerability of low-volume preparations in patients with IBD.Single-center, randomized, prescriber, and colonoscopist-blinded clinical trial. IBD outpatients undergoing colonoscopy were randomized 1:1:1 to receive 1 Liter-polyethylene glycol-ascorbate (1L-PEG), 2 Liters-PEG, or sodium picosulfate (SP). The primary endpoint was percentage of quality cleansing assessedNinety-two patients were included (33 1L-PEG, 28 2L-PEG, and 31 SP). No significant differences between preparations were observed in quality or high-quality total BBPS or high-quality segmental BBPS. Complete intake of the solution was higher for SP (We observed no differences in efficacy between low-volume preparations in patients with IBD. Complete intake was higher for SP and lower for 1L-PEG. SP and 2L-PEG instructions were better understood and graded, and SP was more likely to be retaken. Willingness to retake was lower for 1L-PEG. No serious adverse events were reported.No differences in terms of efficacy were regarded in this clinical trial comparing low-volume preparations for colonoscopy in patients with IBD: however, Sodium Pisoculfate is better tolerated and accepted from patient's point of view. No serious adverse events were reported.

This paper presents the design and simulation of a Parallel Kinematic (PK) testbed for head impacts. The proposed design is presented as a novel head impact testbed using a parallel platform as main motion simulation mechanism. The testbed is used to give a motion to a head mannequin to impact against a steel plate. In addition, the platform in the testbed allows to modify the orientation of the head mannequin model to evaluate different types of impacts. The testbed has been modeled with software MS ADAMS® to evaluate its performance with a dynamic simulation and to characterize the testbed design during top and lateral impact events. Results show that PK testbed gives a significant force and acceleration to the head mannequin at the moment of the impact.

The operation schedule of the power generation units in electrical power systems is determined by the optimisation problem known as unit commitment (UC), aiming at minimising the total cost considering the generation constraints. To obtain a feasible solution from the network perspective, the security-constrained UC (SCUC) problem has been defined to embed the network constraints in the optimisation problem as well. Also, the higher penetration of renewable energy sources (RES) has increased the difficulty of UC problem, mainly due to the uncertainty and the high variability of RES. This paper proposed a SCUC with economic dispatch (SCUCED) optimisation developed in two stages. The first one is the solution of a merit-order based zonal day-ahead market (ZDAM) optimisation to define a preliminary generation schedule. In the second stage, the SCUCED is solved based on AC load flow routines and sensitivity factors to embed the full network representation. The approach is applied to a modified version of the IEEE 39-bus test system.

The paper presents an approach for online centralized control in active distribution networks. It combines a proportional integral (PI) control unit with a corrective control unit (CCU), based on the principle of Model Predictive Control (MPC). The proposed controller is designed to accommodate the increasing penetration of distributed generation in active distribution networks. It helps in continuously satisfying the reactive power requirements of the transmission system operators (TSOs), while maintaining an acceptable voltage profile in the active distribution network, and simultaneously minimizing the total active power losses. The controller also ensures compliance to operation requirements of distribution network operators (DNOs). By replacing the full load flow (LF) calculation with sensitivities, derived from a linearized model of the network, the controller can work in real-time applications. Moreover, the computational burden of the proposed controller is reduced since the CCU is activated only when a voltage violation or considerable change of operation condition occurs. The performance of the proposed controller is demonstrated on a 11-kV test network with 75 buses and 22 distributed generators.

BACKGROUND: Bowel preparation is crucial for colonoscopies in patients with Inflammatory Bowel Disease (IBD). However, data regarding cleansing solutions in this setting are scarce. AIMS: Our aim was to compare efficacy, safety, and tolerability of three different low-volume preparations in patients with IBD.METHODS: Single-center, randomized, prescriber- and colonoscopist-blinded clinical trial. IBD outpatients undergoing colonoscopy were randomized 1:1:1 to receive 1 Liter-polyethylene glycol-ascorbate (1L-PEG), 2 Liters-PEG or sodium picosulfate (SP). Primary endpoint was efficacy in terms of percentage of quality cleansing assessed via the Boston Bowel Preparation Scale (BBPS >=6 with segments >=2). Secondary endpoints were efficacy in terms of total high quality cleansing (BBPS 8 or 9), high quality segmental BBPS (>=2) and patients’ tolerability, symptoms, and satisfaction, assessed by questionnaires before and after colonoscopy. Safety was monitored by adverse event reporting, laboratory evaluation at colonoscopy and telephonic follow-up.RESULTS: 92 patients were included (33 1L-PEG, 28 2L-PEG and 31 SP). No significant differences between preparations were observed in quality or high-quality total BBPS or high-quality segmental BBPS. Complete intake of the solution was higher for SP (p=0,006) and lower for 1L-PEG (p=0,02). Clinically irrelevant hyponatremia was higher in the SP group (pCONCLUSIONS: We observed no differences between PEG-based bowel preparations and SP regarding efficacy in patients with IBD. Complete intake was higher for SP and lower for 1L-PEG. SP and 2L-PEG instructions were better understood and graded, and SP was more likely to be retaken. Willingness to retake was lower for 1L-PEG. No serious adverse events were reported.

The quest for a safe and effective anesthetic medication in the mid-20th century led to the discovery of CI-581, which was later named ketamine. Ketamine was labeled a "dissociative anesthetic" due to the state of sensory deprivation that it induces in the subjects receiving it. Although it enjoyed widespread use at the beginning of the Vietnam war, its use rapidly waned due to its psychedelic effect and it became more popular as a recreational drug, and in the field of veterinary medicine. However, as we gained more knowledge about its multiple sites of action, it has reemerged as a useful anesthetic/analgesic agent. In the last decade, the field of neurology has witnessed the growing use of ketamine for the treatment of several neurological conditions including migraine, status epilepticus, stroke, and traumatic brain injury (TBI). Ketamine acts primarily as a non-competitive N-methyl-D-aspartate (NMDA) receptor antagonist. The binding of ketamine to NMDA receptors leads to decreased frequency and duration of Ca

The computational burden and the time required to train a deep reinforcement learning (DRL) can be appreciable, especially for the particular case of a DRL control used for frequency control of multi-electrical energy storage (MEESS). This paper presents an assessment of four training configurations of the actor and critic network to determine the configuration training that produces the lower computational time, considering the specific case of frequency control of MEESS. The training configuration cases are defined considering two processing units: CPU and GPU and are evaluated considering serial and parallel computing using MATLAB® 2020b Parallel Computing Toolbox. The agent used for this assessment is the Deep Deterministic Policy Gradient (DDPG) agent. The environment represents the dynamic model to provide enhanced frequency response to the power system by controlling the state of charge of energy storage systems. Simulation results demonstrated that the best configuration to reduce the computational time is training both actor and critic network on CPU using parallel computing.

Painful anal fissures could be distressing conditions that severely impair the patients' quality of life. The analgesic effectiveness of topical drugs, such as calcium-antagonists and nitrates is quite variable. The inhalational anesthetic sevoflurane is being repurposed as a topical analgesic for painful chronic wounds. We report a pioneer experience treating a painful chronic anal fissure with topical sevoflurane. A young adult male was suffering from an extremely painful chronic anal fissure, which severely affected his quality of life. The topical treatment with nitroglycerine and diltiazem gels failed. The patient agreed to the treatement with topical sevoflurane as an off-label medication, and it produced an immediate, intense, and long-lasting analgesic effect. An intense but rapidly transient burning sensation, as well as persistent but well-tolerated flatulence were the only adverse effects. The quality of life was greatly improved, and the cost of the treatment was affordable. Therefore, the off-label use of topical sevoflurane appears to be an effective alternative for the symptomatic treatment of painful anal fissures.

Introduction The dose of thiopurine drugs in combined treatments with anti-TNF in inflammatory bowel disease (IBD) has not been clearly established. The purpose of this study is to assess whether the dose of azathioprine influences clinical and biochemical response/remission rates, and anti-TNF drug levels/antibody formation. Material and methods Patients with IBD on combined maintenance treatment with azathioprine and infliximab or adalimumab were selected. Based on the dose of azathioprine, two groups were defined (standard: 2–2.5 mg/kg/day; and decreased: less than 2 mg/kg/day). Results In the IFX group, there were no statistically significant differences (p = 0.204) in the rates of remission (39% vs 41.3%), response (10% vs 21.7%) or failure (51.5% vs 37%) depending on the dose of thiopurine drugs. No differences were found between AZA-dose dependent IFX levels (2.46 vs 3.21 μg/mL; p = 0.211). In the adalimumab group, there were no statistically significant differences (p = 0.83) in the rates of remission (66% vs 56%), response without remission (15.38% vs 25%) or failure (18% vs 18%) depending on the dose of thiopurines. With respect to ADA-levels, no differences were found in both groups (7.69 vs 8.23 μg/mL; p = 0.37). Conclusion In our experience, no statistically significant differences were found in either anti-TNF levels or clinical-biological response/remission rates based on doses of azathioprine.

Human preferences and lifestyles significantly impact buildings’ energy consumption. Consequently, a better understanding of occupants’ behavior is crucial to decrease energy consumption and maintain occupants’ comfort. Occupant-centric control (OCC) strategies are effective approaches to fulfil such a purpose. As such, occupancy detection and prediction are of prime importance, particularly to manage Electric Space Heating (ESH) systems, due to the relatively slow dynamics of the temperature in dwellings. This paper proposes an Explicit Duration Hidden Markov Model (EDHMM) for unsupervised online presence detection and a hazard-based approach for occupancy prediction. Moreover, a control strategy using a cost function, weighted by occupancy predictions, and a load-shifting strategy based on time-varying electricity price are put forward. This work initially validates the consistency of the proposed approach by using synthetic data generated by a Monte Carlo simulation. Subsequently, the performance of our framework is compared with previous methods presented in the literature through experimental validation. Results demonstrate that the proposed EDHMM approach is efficient in detecting occupancy states. Besides, the results of the field implementation show the potential of the proposed control strategy to preserve occupants’ thermal comfort while decreasing the heating energy consumption.

La fundacion de la catedral de Baeza sobre los restos de su antigua aljama a partir de 1226 inauguro la politica de conversiones de grandes mezquitas andalusies del Valle del Guadalquivir implementada durante los reinados de Fernando III y Alfonso X de Castilla. Una serie a traves de la cual se configuro un modelo transcultural de iglesia que, si bien hoy apenas resulta reconocible mas alla de un reducido grupo de edificios, como las catedrales de Cordoba o Sevilla, fue, sin embargo, el mas habitual en la arquitectura religiosa de la mitad sur de la Peninsula Iberica hasta bien entrada la Edad Moderna. Dentro de este conjunto, el proceso de transformacion de la Catedral de Baeza representa un caso especialmente interesante de estudiar, por tratarse de la primera vez en que se cristianizaba una gran mezquita en Castilla desde la de Toledo en tiempos de Alfonso VI de Leon. En este articulo analizamos el contexto sociopolitico y cultural de dicha conversion, asi como algunas de las soluciones arquitectonicas ensayadas en ella y que devendrian norma en el resto de las mezquitas-catedrales de los nuevos territorios cristianos durante el siglo XIII.

Due to the impact of human lifestyle on building energy consumption, the development of occupants’ behavior models is crucial for energy-saving purposes. In this regard, occupancy modeling is an effective approach to intend such a purpose. However, the literature reveals that existing occupancy models have limitations related to the representation of occupancy state duration and the integration of occupancy variability among individuals. Accordingly, this paper proposes an explicit differentiated duration probabilistic model to generate realistic daily occupancy profiles in residential buildings. The discrete-time Markov chain theory and the semi-parametric Cox proportional hazards model (Cox regression) are used to predict household occupancy profiles. The proposed model is able to capture occupancy states duration and integrate human behavior variability according to individuals’ characteristics. Moreover, a parametric analysis is employed to investigate these characteristics’ impact on the model performance and consequently, select the most significant input variables. A validation process is conducted by comparing the model performance with that of previous methods, presented in the literature. For this purpose, the $k$ cross-validation technique is utilized. Validation results demonstrate that the proposed approach is highly efficient in generating realistic household occupancy profiles.

In this study, a novel methodology is proposed for sensitivity-based tuning and analysis of derivative-based fast active power injection (FAPI) controllers in type-4 wind turbine units integrated into a low-inertia power system. The FAPI controller is attached to a power electronic interfaced generation (PEIG) represented by a generic model of wind turbines type 4. It consists of a combination of droop and derivative controllers, which is dependent on the measurement of the frequency. The tuning methodology performs parametric sensitivity to search for the most suitable set of parameters of the attached FAPI that minimises the maximum frequency deviation in the containment period. The FAPI is adjusted to safeguard system stability when increasing the share of PEIG. Since the input signal of the FAPI is the measured frequency, the impact of different values and parameter settings of the phase-locked loop used for the FAPI controller is also investigated. Detailed validation with a full-scaled wind power converter is also provided with a real-time digital simulator testbed. Obtained simulation results using a three-area test system, identify the maximum achievable degree of increase in the share of wind power when a proper combination of wind park locations considering their suggested settings for inertia emulation.

‘De novo’ drug discovery is costly, slow, and with high risk. Repurposing known drugs for treatment of other diseases offers a fast, low-cost/risk and highly-efficient method toward development of efficacious treatments. The emergence of large-scale heterogeneous biomolecular networks, molecular, chemical and bioactivity data, and genomic and phenotypic data of pharmacological compounds is enabling the development of new area of drug repurposing called ‘in silico’ drug repurposing, i.e., computational drug repurposing (CDR). The aim of CDR is to discover new indications for an existing drug (drug-centric) or to identify effective drugs for a disease (disease-centric). Both drug-centric and disease-centric approaches have the common challenge of either assessing the similarity or connections between drugs and diseases. However, traditional CDR is fraught with many challenges due to the underlying complex pharmacology and biology of diseases, genes, and drugs, as well as the complexity of their associations. As such, capturing highly non-linear associations among drugs, genes, diseases by most existing CDR methods has been challenging. We propose a network-based integration approach that can best capture knowledge (and complex relationships) contained within and between drugs, genes and disease data. A network-based machine learning approach is applied thereafter by using the extracted knowledge and relationships in order to identify single and pair of approved or experimental drugs with potential therapeutic effects on different breast cancer subtypes. Indeed, further clinical analysis is needed to confirm the therapeutic effects of identified drugs on each breast cancer subtype.

Gas injection has become one of the most investigated methods for enhanced oil recovery in unconventional reservoirs. Nonetheless, the presence of natural and induced fractures negatively impacts the gas injection efficiency due to its channeling towards nearby wells or poor coverage in the treated area due to lack of conformance. To overcome these difficulties and boost the oil recovery process by gas injection, this work presents a novel gas dispersible foam technology to improve the sweep efficiency of gas injection in unconventional IOR/EOR projects. The development and evaluation of this technology has passed through a series of laboratory assurance stages that include fluids characterization, compatibility, and extensive coreflooding tests. A modelling approach is also presented, which was validated using lab and field data taken from the implementation of the technique in an extremely low porosity, tight and naturally fractured quartz-arenite gas condensate reservoir in Colombia. The workflow herein presented encompasses interdisciplinary components such as laboratory evaluation, reservoir modeling, treatment design, and wellsite setup and execution. Laboratory testing and inter-well field applications results, along with the development and testing of a phenomenological modelling approach, demonstrate that the gas dispersible foam injection can be a high potential technique for oil and/or condensate recovery in unconventional reservoirs given its proven ability to improve the deep reservoir gas conformance and avoid the lack of gas containment during gas injection IOR/EOR in unconventional plays. Lab results in a tight naturally fractured sample, suggest that the estimated incremental oil recovery was ~36% and the effective gas mobility reduction was ~45%. This technique also exhibited less chemical adsorption losses, which contributes to better chemical emplacement and longer durability. The main results of the field application, including a progressive decrease in gas injectivity at the gas injector, a consistent reduction in GOR with an associated oil increase at the influenced producer well, and a reported treatment durability of ~ 6 months, were all properly represented by the model. Each step of the workflow herein proposed not only assures the gas-based projects success, but also allows for smaller logistics footprint at the well location, along with less water consumption, which translates into cheaper and more efficient gas injection conformance operations.

Inverter-based generation (IBG) is critical in achieving a dependable and resilient electrical system while meeting the net-zero emission goal. The enormous integration of IBG tends to produce various issues, including reduced rotational inertia and reduced short circuit levels. Several scientific publications agree that the voltage source converters (VSCs) empowered by the so-called grid forming (GFM) control may provide a lasting answer for reaching the future net-zero IBG-dominated power systems. This paper presents a comparative analysis of the dynamic performance between IBR using synchronverter and a traditional synchronous generator (SG), where the specific concern is the transient stability conditions. DIgSILENT PowerFactory has been used for time-domain simulations using a test system, and numerical simulations considering an N-l event prove the significant benefit of GFN converter controls in providing active power during a voltage sag induced by a short circuit condition, allowing the system to endure longer short circuit durations.

Chronic immune-mediated diseases, including inflammatory bowel disease (IBD), present an increased risk of developing early atherosclerosis and cardiovascular events (CVE) at early age.To describe the baseline and 1-year cardiovascular profile of patients with IBD according to the biologic treatment received, taking into account the inflammatory activity.It is a retrospective, observational study that included 374 patients. Cardiovascular risk factors (CVRF) and CVE were collected at the baseline visit and at one-year follow-up to describe the cardiovascular risk according to the biological treatment received, also assessing clinical and biological remission.A total of 374 patients were included: 146 (38.73%) were treated with Infliximab, 128 (33.95%) with adalimumab, 61 (16.18%) with ustekinumab and 42 (11.14%) with vedolizumab. The changes in blood glucose levels are [86.31mg/dL (84.57-88.06) vs. 89.25mg/dL (87.54-90.96), P=.001] for those treated with antiTNFα and [86.52mg/dL (83.48-89.55) vs. 89.44mg/dL (85.77-93.11), P=.11] in the other group. In the group treated with antiTNFα total cholesterol values at baseline visit are [169.40mg/dL (164.97-173.83) vs. 177.40mg/dL (172.75-182.05) at one year of treatment, P=.001], those of HDL [50.22mg/dL (48.39-52.04) vs. 54.26mg/dL (52.46-56.07), P=.001] and those of triglycerides [114.77mg/dL (106.36-123.18) vs. 121.83mg/dL (112.11-131.54), P=.054]. Regarding weight, an increase was observed, both in those patients treated with antiTNFα [71.39kg (69.53-73.25) vs. 72.87kg (71.05-74.70), P.001], and in the group treated with ustekinumab and vedolizumab [67.59kg (64.10-71.08) vs. 69.43kg (65.65-73.04), P=.003]. Concerning CVE, no significant differences were observed neither according to the drug used (p=0.36), nor according to personal history of CVE (P=.23) nor according to inflammatory activity (P=.46).Our results on a real cohort of patients with IBD treated with biologic drugs show a better control of certain cardiovascular parameters such as CRP or HDL, but a worsening of others such as total cholesterol or triglycerides, regardless of the treatment. Therefore, it is possibly the disease control and not the therapeutic target used, the one that affect the cardiovascular risk of these patients.

Motivation One of the main challenges in applying graph convolutional neural networks (CNNs) on gene-interaction data is the lack of understanding of the vector space to which they belong, and also the inherent difficulties involved in representing those interactions on a significantly lower dimension, viz Euclidean spaces. The challenge becomes more prevalent when dealing with various types of heterogeneous data. We introduce a systematic, generalized method, called iSOM-GSN, used to transform ‘multi-omic’ data with higher dimensions onto a 2D grid. Afterwards, we apply a CNN to predict disease states of various types. Based on the idea of Kohonen’s self-organizing map, we generate a 2D grid for each sample for a given set of genes that represent a gene similarity network. Results We have tested the model to predict breast and prostate cancer using gene expression, DNA methylation and copy number alteration. Prediction accuracies in the 94–98% range were obtained for tumor stages of breast cancer and calculated Gleason scores of prostate cancer with just 14 input genes for both cases. The scheme not only outputs nearly perfect classification accuracy, but also provides an enhanced scheme for representation learning, visualization, dimensionality reduction and interpretation of multi-omic data. Availability and implementation The source code and sample data are available via a Github project at https://github.com/NaziaFatima/iSOM_GSN. Supplementary information Supplementary data are available at Bioinformatics online.

El objetivo del trabajo fue realizar sondeos de perforación a diamantina en relación a sondaje HCD-004. El área de estudio se localiza en la provincia Tomás Frías del departamento de Potosí. La campaña de prospección geoquímica, dio como resultado anomalías en Zn, Pb y Ag que corresponden a una estructura oxidada tipo stockwork emplazada en una ignimbrita (0,141 % de Zn, 0,149 % de Pb y 4,2 ppm de Ag). Se analizó la presencia de Sn por el método AAS Espectrofotometría de Absorción atómica - Fire Assays. Los sondajes HCD-005 y HCD-006 siguieron anomalías geoquímicas y la traza de la estructura que controla la brecha hidrotermal cortada en el pozo de la primera fase, en ambos pozos la recuperación fue superior al 95 % que se considera buena. Se procedió a realizar una estimación del recurso mineralógico el peso específico determinado fue de 2,58 gr/cc obteniéndose un tonelaje total de 1.947.841,82 Tn con valores de 0,34 % de Zn y 0,075 % de Pb.

© 2020, © 2020 Taylor & Francis Group, LLC. In this paper, a new control approach using an optimal linear control with prescribed degree of stability for modular multi-level converters (MMC) is presented and analyzed. The proposed controller relies on a linear quadratic regulator with integral action which brings the ability of state variable reference tracking for modular multi-level converters. Since MMC is a complex system with several state variables, a unified control system design for this system is vital. The proposed controller of this study is designed to obtain wider stability margin thanks to the implementation of prescribed degree of stability concept to minimize the quadratic performance index of the control structure. By means of this method, the poles of the closed-loop system will be shifted to the desired places in the left half side of the S-plane. The main advantages of this control strategy compared to previous methods are that it will be possible to control the state of energy for each phase separately, while there will be superior tolerance to nonlinearities and the enhanced stability margin with less sensitivity to plant-parameter variations. The performance of the designed controller is verified through MATLABTM simulations (The MathWorks, Natick, MA, USA) with the nonlinear model of MMC.

The presence of different water masses in depth may influence the species distribution and community structure in deep-sea benthic ecosystems. In the North Atlantic, the Mediterranean Outflow Water (MOW) represents an important forcing water mass, whose influence on the distribution of cold-water corals in the northern European margins has been particularly investigated. However, the MOW also spreads westwards into the central North Atlantic bathing several seamounts and seafloor elevations, whose deep-sea benthic communities are still poorly known. In this study, we provide a local to large-scale comprehensive description of deep-sea megabenthic assemblages along the western branch of the MOW, from its origin in the western Mediterranean Sea to the Central North Atlantic close to the Azores archipelago. For some of the studied seafloor elevations, such as Ormonde (Gorringe bank, offshore SW Portugal margin) and Formigas seamounts (SE Azores archipelago), this is the first time these assemblages have been characterized and quantified. The results indicate a strong effect of substrate type in the structure and diversity of the assemblages at local scales; but the effect of water masses becomes more relevant when a large bathymetrical gradient is considered. The results also suggest a potential role of the MOW for biodiversity and biogeographic patterns at the North Atlantic basin, suggesting a potential enhancement of the biodiversity of some deep-sea megabenthic assemblages. Understanding water masses as an integrative tool to delineate biodiversity and biogeographic patterns from local to large scale will contribute to identify different megabenthic assemblages, including vulnerable marine ecosystems, as well as potential regions of refugia under future climate change conditions., SI

570 Background: Over 8900 Canadians are diagnosed with bladder cancer every year, ranking it the fifth most frequent cancer. It can manifest as either non-muscle invasive bladder cancer (NMIBC) or muscle invasive bladder cancer (MIBC). The majority of patients initially receive a diagnosis of NMIBC, although high-grade NMIBC has a 50–70% recurrence rate and 10–30% chance at progressing to MIBC. The transition from high-grade NMIBC to MIBC is poorly understood, and there are currently no accurate biomarkers that predict disease progression. We propose a comprehensive molecular characterization to pinpoint specific copy number alterations (CNAs) related to either MIBC or NMIBC, and hence define the molecular development. Methods: This study analyzed a public dataset from MSKCC and 30 bladder cancer patient samples from Windsor Regional Hospital, both containing NMIBC and MIBC samples. Comprehensive gene sequencing was performed, and CNAs were obtained in over 500 common tumour gene panels. Results: Preliminary data from this study found MIBC may be predicted with 91% accuracy and 95% precision using CNA values of TP53, DDR2 and MLL2. In particular, MIBC correlates with gain of DDR2 or MLL2. Importantly, it has been demonstrated that high expression of DDR2 is associated with a worse prognosis. A panel of bladder carcinoma cell lines were used to validate the DDR2 findings. DDR2 values were quantified across the panels and corresponded with proliferation and invasiveness of cell lines. DDR2 was examined as a possible therapeutic target. Conclusions: Taken together, these findings provide insight to the pathogenesis of muscle invasion in bladder cancer. The potential to identify "genomic triggers" for the transition was facilitated by creating a genetic profile at these two stages.

Recent studies on using single-cell RNA sequencing (scRNA-seq) technology have been widely applied in biological studies such as drug discovery. Prior to in-depth investigations of the functionality of single cells for pathological goals, identification of cell types is an essential step that can be sped up using computational methods. Recently, supervised learning methods have been developed to automatically identify cell types. Due to the lack of sufficient annotated datasets, these methods have not been commonly used in scRNA-seq studies. Classification methods can simply take advantage of feature selection techniques to improve cell type prediction while identifying the most informative genes among a high number of genes in high-dimensional scRNA-seq datasets. In this regard, we introduce a combination of two powerful techniques for representation learning and unsupervised feature selection to automatically achieve cell type identification in two steps. Average prediction accuracy of 98% obtained on six different cell types in a Human Pancreas scRNA-seq dataset. In addition, we found that 11 out of 13 selected genes are biologically related to two cell types in the Human Pancreas, which confirms the effectiveness of the proposed approach.

The growing installation of distributed energy resources (DER) in the network allows an active interaction between the transmission and distribution system operators. This interaction is possible mainly by the power electronic converters (PECs) incorporated in the DER, used as an interface with the network. The PECs, also known as smart inverters, offers excellent controllability features and allow DER to provide procurement services to the distribution and transmission network. This paper focuses on evaluating the reactive power control features of the smart inverter considering eight control local modes following the IEEE 1547-2018 standard. Moreover, it is proposed an optimal reactive power controller able to minimise the active power losses in the network by optimally adapting the reactive power injection/absorption of the smart inverter. This optimal controller ensures all the busbar voltages are inside the permissible limits, and the reactive power limits of the smart inverter are enforced. The Vestfold and Telemark distribution network model was implemented using DIgSILENT PowerFactory to evaluate the optimal and the eight local reactive power control modes. Simulation results show the proposed optimal reactive power control is the best option to offer the service of active power loss minimisation using smart inverters for the daily steady-state performance of the DSO network.

La lectura contextual de la historia de Tamar (2 Sm 13, 1-22) con un grupo de mujeres que vive con VIH reveló sus propias historias en las que la estigmatización causada por los otros las ha llevado a vivir discriminación, silencio, prejuicio y vulneración de sus derechos. Esta realidad se constituye en un lugar teológico, sin duda, porque sólo podemos hablar de Dios si hablamos de la humanidad de los marginados y excluidos de nuestro tiempo. Los datos recabados bajo la investigación-acción participativa y la lectura contextual de la Biblia permitieron hacer una aproximación teológica al drama vivido por estas mujeres, en el cual se ejerce el poder sobre lo femenino, su cuerpo y su sexualidad como signo del anti-reino y de la no-vida. Además, el recorrido realizado por las mujeres también les permitió su propia sanación y darse cuenta de que, sólo si rompen el silencio, podrán luchar por sus derechos bajo la conciencia de que son víctimas, no culpables. Se trata de una apuesta por la justicia querida por Dios, de ese Dios que se autocomunica en la historia humana.

Identifying relevant disease modules such as target cell types is a significant step for studying diseases. High-throughput single-cell RNA-Seq (scRNA-seq) technologies have advanced in recent years, enabling researchers to investigate cells individually and understand their biological mechanisms. Computational techniques such as clustering, are the most suitable approach in scRNA-seq data analysis when the cell types have not been well-characterized. These techniques can be used to identify a group of genes that belong to a specific cell type based on their similar gene expression patterns. However, due to the sparsity and high-dimensionality of scRNA-seq data, classical clustering methods are not efficient. Therefore, the use of non-linear dimensionality reduction techniques to improve clustering results is crucial. We introduce a method that is used to identify representative clusters of different cell types by combining non-linear dimensionality reduction techniques and clustering algorithms. We assess the impact of different dimensionality reduction techniques combined with the clustering of thirteen publicly available scRNA-seq datasets of different tissues, sizes, and technologies. We further performed gene set enrichment analysis to evaluate the proposed method’s performance. As such, our results show that modified locally linear embedding combined with independent component analysis yields overall the best performance relative to the existing unsupervised methods across different datasets.