Effects of 4-Week training intervention with unknown loads on power output performance and throwing velocity in junior team handball players

PURPOSE:To compare the effect of 4-week unknown vs known loads strength training intervention on power output performance and throwing velocity in junior team handball players. METHODS:Twenty-eight junior team-handball players (17.2 ± 0.6 years, 1.79 ± 0.07 m, 75.6 ± 9.4 kg)were divided into two groups (unknown loads: UL; known loads: KL). Both groups performed two sessions weekly consisting of four sets of six repetitions of the bench press throw exercise, using the 30%, 50% and 70% of subjects' individual 1 repetition maximum (1RM). In each set, two repetitions with each load were performed, but the order of the loads was randomised. In the KL group, researchers told the subjects the load to mobilise prior each repetition, while in the UL group, researchers did not provide any information. Maximal dynamic strength (1RM bench press), power output (with 30, 50 and 70% of 1RM) and throwing velocity (7 m standing throw and 9 m jumping throw) were assessed pre- and post-training intervention. RESULTS:Both UL and KL group improved similarly their 1RM bench press as well as mean and peak power with all loads. There were significant improvements in power developed in all the early time intervals measured (150 ms) with the three loads (30, 50, 70% 1RM) in the UL group, while KL only improved with 30% 1RM (all the time intervals) and with 70% 1RM (at certain time intervals). Only the UL group improved throwing velocity in both standing (4.7%) and jumping (5.3%) throw (p > 0.05). CONCLUSIONS:The use of unknown loads has led to greater gains in power output in the early time intervals as well as to increases in throwing velocity compared with known loads. Therefore unknown loads are of significant practical use to increase both strength and in-field performance in a short period of training

Color image segmentation using perceptual spaces through applets for determining and preventing diseases in chili peppers

Plant pathogens cause disease in plants. Chili peppers are one of the most important crops in the world. There are currently disease detection techniques classified as: biochemical, microscopy, immunology, nucleic acid hybridization, identification by visual inspection in vitro or in situ but these have the following disadvantages: they require several days, their implementation is costly and highly trained. This paper proposes a method for knowing and preventing the disease in chili peppers plant through a color image processing, using online system developed in Java applets. This system gets results in real time and remotely (Internet). The images are converted to perceptual spaces [hue, saturation and lightness (HSL), hue, saturation, and intensity (HSI) and hue saturation and value (HSV)]. Sequence was applied to the proposed method. HSI color space was the best detected disease. The percentage of disease in the leaf is of 12.42%. HSL and HSV do not expose the exact area of the disease compared to the HSI color space. Finally, images were analyzed and the disease is known by the expert in plant pathology to take preventive or corrective actions.Keywords: Applets, knowing disease, color image segmentation, perceptual spacesAfrican Journal of Biotechnology Vol. 12(7), pp. 679-68

The flashfm approach for fine-mapping multiple quantitative traits

Funder: “Expanding excellence in England” award from Research EnglandJoint fine-mapping that leverages information between quantitative traits could improve accuracy and resolution over single-trait fine-mapping. Using summary statistics, flashfm (flexible and shared information fine-mapping) fine-maps signals for multiple traits, allowing for missing trait measurements and use of related individuals. In a Bayesian framework, prior model probabilities are formulated to favour model combinations that share causal variants to capitalise on information between traits. Simulation studies demonstrate that both approaches produce broadly equivalent results when traits have no shared causal variants. When traits share at least one causal variant, flashfm reduces the number of potential causal variants by 30% compared with single-trait fine-mapping. In a Ugandan cohort with 33 cardiometabolic traits, flashfm gave a 20% reduction in the total number of potential causal variants from single-trait fine-mapping. Here we show flashfm is computationally efficient and can easily be deployed across publicly available summary statistics for signals in up to six traits.Wellcome Trust [WT107881

Quantification of virus syndrome in chili peppers

One of the most important problems to produce chili crops is the presence of diseases caused by pathogen agents, such as viruses, therefore, there is a substantial necessity to better predict the behavior of the diseases of these crops, determining a more precise quantification of the disease’s syndrome that allows the investigators to evaluate better practices, from handling to the experimental level and will permit producers to take opportunistic corrective action thereby, reducing production loses and increasing the quality of the crop. This review discussed methods that have been used for the quantification of disease in plants, specifically for chili peppers crops, thereby, suggesting a better alternative for the quantification of the disease’ syndromes in regards to this crop. The result of these reflections indicates that most methods used for quantification are based on visual assessments, discarding differences of data between distinctive evaluators. These methods generate subjective results.Key words: Quantification, plant diseases, severity, syndrome, viruses

Gastrointestinal-Sparing Effects of Novel NSAIDs in Rats with Compromised Mucosal Defence

Nonsteroidal anti-inflammatory drugs are among the most commonly used prescription and over-the-counter medications, but they often produce significant gastrointestinal ulceration and bleeding, particularly in elderly patients and patients with certain co-morbidities. Novel anti-inflammatory drugs are seldom tested in animal models that mimic the high risk human users, leading to an underestimate of the true toxicity of the drugs. In the present study we examined the effects of two novel NSAIDs and two commonly used NSAIDs in models in which mucosal defence was expected to be impaired. Naproxen, celecoxib, ATB-346 (a hydrogen sulfide- and naproxen-releasing compound) and NCX 429 (a nitric oxide- and naproxen-releasing compound) were evaluated in healthy, arthritic, obese, and hypertensive rats and in rats of advanced age (19 months) and rats co-administered low-dose aspirin and/or omeprazole. In all models except hypertension, greater gastric and/or intestinal damage was observed when naproxen was administered in these models than in healthy rats. Celecoxib-induced damage was significantly increased when co-administered with low-dose aspirin and/or omeprazole. In contrast, ATB-346 and NCX 429, when tested at doses that were as effective as naproxen and celecoxib in reducing inflammation and inhibiting cyclooxygenase activity, did not produce significant gastric or intestinal damage in any of the models. These results demonstrate that animal models of human co-morbidities display the same increased susceptibility to NSAID-induced gastrointestinal damage as observed in humans. Moreover, two novel NSAIDs that release mediators of mucosal defence (hydrogen sulfide and nitric oxide) do not induce significant gastrointestinal damage in these models of impaired mucosal defence

Attosecond physics at the nanoscale

Recently two emerging areas of research, attosecond and nanoscale physics, have started to come together. Attosecond physics deals with phenomena occurring when ultrashort laser pulses, with duration on the femto- and sub-femtosecond time scales, interact with atoms, molecules or solids. The laser-induced electron dynamics occurs natively on a timescale down to a few hundred or even tens of attoseconds, which is comparable with the optical field. On the other hand, the second branch involves the manipulation and engineering of mesoscopic systems, such as solids, metals and dielectrics, with nanometric precision. Although nano-engineering is a vast and well-established research field on its own, the merger with intense laser physics is relatively recent. In this article we present a comprehensive experimental and theoretical overview of physics that takes place when short and intense laser pulses interact with nanosystems, such as metallic and dielectric nanostructures. In particular we elucidate how the spatially inhomogeneous laser induced fields at a nanometer scale modify the laser-driven electron dynamics. Consequently, this has important impact on pivotal processes such as ATI and HHG. The deep understanding of the coupled dynamics between these spatially inhomogeneous fields and matter configures a promising way to new avenues of research and applications. Thanks to the maturity that attosecond physics has reached, together with the tremendous advance in material engineering and manipulation techniques, the age of atto-nano physics has begun, but it is in the initial stage. We present thus some of the open questions, challenges and prospects for experimental confirmation of theoretical predictions, as well as experiments aimed at characterizing the induced fields and the unique electron dynamics initiated by them with high temporal and spatial resolution

El ácido valproico tiene efecto neuroprotector en un modelo de estrés oxidativo agudo en ratas

The excess of the free radical production at has been implied has a common factor in pathogenesis of a big number of neurodegenerative processes, including Alzheimer’s and Parkinson’s disease and in ischemia/reperfusion induced brain damage. Valproic Acid (VPA), which traditionally has been used as an antiepileptic drug, now is proposed as a neuroprotective agent, but is not clear it’s mechanisms of action. In this paper, its effect was investigated in an acute oxidative stress model with Sprague Dawley rats, in which iron sulfate was used as injury and lipid peroxidation and carbonylated proteins were quantified at cerebral cortex, showing that it blocked formation of free radicals. Levels of MDA atcerebral cortex that received oxidative injury in the group of animals treated with VPA were 57% lower in comparison to control group, also the amount of carbonylated proteins was 65% lower in the cerebral cortex of experimental animals in contrast to control group. Furthermore, it was found that the antioxidant effect showed by the VPA, was equally significant than showed by vitamin E.El exceso de producción de radicales libres en el cerebro ha sido implicada como un factor común en la patogénesis de un gran número de procesos neurodegenerativos, incluyendo la enfermedad de Alzheimer, la enfermedad de Parkinson, y en la isquemia/reperfusión cerebral. El ácido valproico (VPA) que tradicionalmente ha sido utilizado como fármaco antiepiléptico, actualmente se propone como agente neuroprotector, pero aún no está claro cual es su mecanismo de acción. En esta investigación se probó su efecto en un modelo de estrés oxidativo agudo en ratas Sprague Dawley para lo cual se usó el sulfato de hierro como agente inductor de daño y se cuantificó la peroxidación lipídica y proteínas carboniladas en corteza cerebral, demostrándose que bloqueó la formación de radicales libres. Los niveles de malondialdehído en la corteza cerebral que recibió la agresión oxidativa en el grupo de animales tratados con VPA fueron 57% inferiores en relación al grupo control que no recibió VPA, mientras que la cantidad de proteínas carboniladas fue un 65% inferior en la corteza cerebral de los animales experimentales en comparación al grupo control. Adicionalmente se encontró que el efecto antioxidante exhibido por el VPA, fue igual de significativo al presentado por la vitamina E

Reproducibility of experiments in recommender systems evaluation

© IFIP International Federation for Information Processing 2018 Published by Springer International Publishing AG 2018. All Rights Reserved. Recommender systems evaluation is usually based on predictive accuracy metrics with better scores meaning recommendations of higher quality. However, the comparison of results is becoming increasingly difficult, since there are different recommendation frameworks and different settings in the design and implementation of the experiments. Furthermore, there might be minor differences on algorithm implementation among the different frameworks. In this paper, we compare well known recommendation algorithms, using the same dataset, metrics and overall settings, the results of which point to result differences across frameworks with the exact same settings. Hence, we propose the use of standards that should be followed as guidelines to ensure the replication of experiments and the reproducibility of the results