Development of new sealed bipolar lead-acid battery

New light weight composite bipolar plates which can withstand the corrosive environment of the lead acid battery have made possible the construction of a sealed bipolar lead acid battery that promises to achieve very high specific power levels and substantially higher energy densities than conventional lead acid batteries. Performance projections based on preliminary experimental results show that the peak specific power of the battery can be as high as 90 kW/kg, and that a specific power of 5 kW/kg can be sustained over several thousand pulses

Enhancement of Chest X-ray Images for Diagnosis Purposes

This study presents image quality comparison between original images and three image enhancement techniques namely imadjust, histogram equalization (HE) and contrast limited adaptive histogram equalization (CLAHE). These techniques are applied to a collection of eight chest x-ray images which are considered as dark, noisy and low in contrast and radiation dosage. The lacks of quality can be solved with these enhancement image techniques. These techniques raised the quality of images and improve the diagnostic ability of the pathological features observed in the images. Then the quality image factors including peak signal-to-noise ratio (PSNR), Mean squared error (MSE), (MAXERR) and (L2rat) were used to evaluate the characteristic of the images. The findings showed that the enhancement techniques managed to enhance the images make them more qualified than original images. Keywords: Histogram Equalization, Contrast Limited Adaptive Histogram Equalization and Image Quality

Enhancement of Chest X-ray Images for Diagnosis Purposes

This study presents image quality comparison between original images and three image enhancement techniques namely imadjust, histogram equalization (HE) and contrast limited adaptive histogram equalization (CLAHE). These techniques are applied to a collection of eight chest x-ray images which are considered as dark, noisy and low in contrast and radiation dosage. The lacks of quality can be solved with these enhancement image techniques. These techniques raised the quality of images and improve the diagnostic ability of the pathological features observed in the images. Then the quality image factors including peak signal-to-noise ratio (PSNR), Mean squared error (MSE), (MAXERR) and (L2rat) were used to evaluate the characteristic of the images. The findings showed that the enhancement techniques managed to enhance the images make them more qualified than original images. Keywords: Histogram Equalization, Contrast Limited Adaptive Histogram Equalization and Image Quality

A mapping approach to synchronization in the "Zajfman trap". II: the observed bunch

We extend a recently introduced mapping model, which explains the bunching phenomenon in an ion beam resonator for two ions [Geyer, Tannor, J. Phys. B 37 (2004) 73], to describe the dynamics of the whole ion bunch. We calculate the time delay of the ions from a model of the bunch geometry and find that the bunch takes on a spherical form at the turning points in the electrostatic mirrors. From this condition we derive how the observed bunch length depends on the experimental parameters. We give an interpretation of the criteria for the existence of the bunch, which were derived from the experimental observations by Pedersen et al [Pedersen etal, Phys. Rev. A 65 042704].Comment: 25 pages, 6 figures; added new section 5 and clarified text; submitted to J. Phys.

Cytological Detection of Thyroid Cancer by Optical Image Analysis

This research explores the use of features of cells in digital optical images of human thyroid tissue as an important base to diagnose the cancer. It presents some efficient features of cells nuclei for detection of thyroid malignancy such as (radius, smoothness, compactness, expected value and variance). The cytological characteristics are very important and usual method to separate abnormal and normal cases in all diseases. The algorithm of neural network used to detect thyroid cancer successfully with accuracy of 99%. Keywords: thyroid cancer, neural network, optical images, malignanc

The miRNAome of the postpartum dairy cow liver in negative energy balance

peer-reviewedBackground: Negative energy balance (NEB) is an altered metabolic state in high yielding cows that occurs during the first few weeks postpartum when energy demands for lactation and maintenance exceed the energy supply from dietary intake. NEB can, in turn, lead to metabolic disorders and to reduced fertility. Alterations in the expression of more than 700 hepatic genes have previously been reported in a study of NEB in postpartum dairy cows. miRNAs (microRNA) are known to mediate many alterations in gene expression post transcriptionally. To study the hepatic miRNA content of postpartum dairy cows, including their overall abundance and differential expression, in mild NEB (MNEB) and severe NEB (SNEB), short read RNA sequencing was carried out. To identify putative targets of differentially expressed miRNAs among differentially expressed hepatic genes reported previously in dairy cows in SNEB computational target identification was employed. Results: Our results indicate that the dairy cow liver expresses 53 miRNAs at a lower threshold of 10 reads per million. Of these, 10 miRNAs accounted for greater than 95% of the miRNAome (miRNA content). Of the highly expressed miRNAs, miR-122 constitutes 75% followed by miR-192 and miR-3596. Five out of thirteen let-7 miRNA family members are also among the highly expressed miRNAs. miR-143, down-regulated in SNEB, was found to have 4 putative up-regulated gene targets associated with SNEB including LRP2 (low density lipoprotein receptor-related protein 2), involved in lipid metabolism and up-regulated in SNEB. Conclusions: This is the first liver miRNA-seq profiling study of moderate yielding dairy cows in the early postpartum period. Tissue specific miR-122 and liver enriched miR-192 are two of the most abundant miRNAs in the postpartum dairy cow liver. miR-143 is significantly down-regulated in SNEB and putative targets of miRNA-143 which are up-regulated in SNEB, include a gene involved in lipid metabolism.Teagasc Walsh Fellowship Programm

DREAM II. The spin-orbit angle distribution of close-in exoplanets under the lens of tides

The spin-orbit angle, or obliquity, is a powerful observational marker that allows us to access the dynamical history of exoplanetary systems. Here, we have examined the distribution of spin-orbit angles for close-in exoplanets and put it in a statistical context of tidal interactions between planets and their stars. We confirm the observed trends between the obliquity and physical quantities directly connected to tides, namely the stellar effective temperature, the planet-to-star mass ratio, and the scaled orbital distance. We further devised a tidal efficiency factor combining critical parameters that control the strength of tidal effects and used it to corroborate the strong link between the spin-orbit angle distribution and tidal interactions. In particular, we developed a readily usable formula to estimate the probability that a system is misaligned, which will prove useful in global population studies. By building a robust statistical framework, we reconstructed the distribution of the three-dimensional spin-orbit angles, allowing for a sample of nearly 200 true obliquities to be analyzed for the first time. This realistic distribution maintains the sky-projected trends, and additionally hints toward a striking pileup of truly aligned systems. The comparison between the full population and a pristine subsample unaffected by tidal interactions suggests that perpendicular architectures are resilient toward tidal realignment, providing evidence that orbital misalignments are sculpted by disruptive dynamical processes that preferentially lead to polar orbits. On the other hand, star-planet interactions seem to efficiently realign or quench the formation of any tilted configuration other than for polar orbits, and in particular for antialigned orbits.Comment: Accepted in A&

Effects of study design and allocation on self-reported alcohol consumption: randomized trial.

BACKGROUND: What participants think about the nature of a study might affect their behaviour and bias findings. We tested two hypotheses: (1) participants told they were in an intervention trial would report lower alcohol consumption at follow-up than those told they were in a cohort study; (2) participants told they were in the intervention group in a trial would have lower alcohol consumption at follow-up than those told they were in the control group. METHODS: Students from four universities (N = 72,903) were invited to participate in a 'research project on student drinking'. Of 10,415 respondents, 6,788 were moderate to heavy drinkers and were randomized. Group A ('cohort') were informed their drinking would be assessed at baseline and again in one month. Group B ('control') were told the study was an intervention trial and they were in the control group. Group C ('intervention') were told the study was an intervention trial and they were to receive the intervention. All were assessed and directed to read identical online alcohol education material. Whether and how long they accessed the material were recorded. One month later, alcohol intake was reassessed. RESULTS: In relation to hypothesis 1, there were no differences between the groups on the prespecified outcome measures. In relation to hypothesis 2, there were no differences though all point estimates were in the hypothesized direction (that is, 'intervention' < 'control'). The 'cohort' and 'control' groups accessed the material to a similar extent (59% versus 57%) while the 'intervention' group were more likely to access it (78%) and to read it for longer (median 35 s (25th and 75th percentiles: 6, 97) versus medians of 7 s (0, 28) and 8 s (4, 42) for the 'cohort' and 'control' groups, respectively). CONCLUSIONS: Although the context given to the research participants significantly influenced access to the online information and reading time, this did not translate into any effect on drinking behaviour, for either hypothesis. This might be because of failure in the experimental paradigm or the possibility of weaker effects using the online approach. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry ACTRN12610000846022

Exploring the Design of mHealth Systems for Health Behavior Change using Mobile Biosensors

A person’s health behavior plays a vital role in mitigating their risk of disease and promoting positive health outcomes. In recent years, mHealth systems have emerged to offer novel approaches for encouraging and supporting users in changing their health behavior. Mobile biosensors represent a promising technology in this regard; that is, sensors that collect physiological data (e.g., heart rate, respiration, skin conductance) that individuals wear, carry, or access during their normal daily activities. mHealth system designers have started to use the health information from physiological data to deliver behavior-change interventions. However, little research provides guidance about how one can design mHealth systems to use mobile biosensors for health behavior change. In order to address this research gap, we conducted an exploratory study. Following a hybrid approach that combines deductive and inductive reasoning, we integrated a body of fragmented literature and conducted 30 semi-structured interviews with mHealth stakeholders. From this study, we developed a theoretical framework and six general design guidelines that shed light on the theoretical pathways for how the mHealth interface can facilitate behavior change and provide practical design considerations

An improved artificial jellyfish search optimizer for parameter identification of photovoltaic models

The optimization of photovoltaic (PV) systems relies on the development of an accurate model of the parameter values for the solar/PV generating units. This work proposes a modified artificial jellyfish search optimizer (MJSO) with a novel premature convergence strategy (PCS) to define effectively the unknown parameters of PV systems. The PCS works on preserving the diversity among the members of the population while accelerating the convergence toward the best solution based on two motions: (i) moving the current solution between two particles selected randomly from the population, and (ii) searching for better solutions between the best-so-far one and a random one from the population. To confirm its efficacy, the proposed method is validated on three different PV technologies and is being compared with some of the latest competitive computational frameworks. The numerical simulations and results confirm the dominance of the proposed algorithm in terms of the accuracy of the final results and convergence rate. In addition, to assess the performance of the proposed approach under different operation conditions for the solar cells, two additional PV modules (multi-crystalline and thin-film) are investigated, and the demonstrated scenarios highlight the utility of the proposed MJSO-based methodology.</p