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The Non-Thermal Effect of UV-B Irradiation on Onion Growth

Nashnoush et al. | Jun 09, 2020

The Non-Thermal Effect of UV-B Irradiation on Onion Growth

UV-B radiation due to the depletion of ozone threatens plant life, potentially damaging ecosystems and dismantling food webs. Here, the impact of UV-B radiation on the physiology and morphology of Allum cepa, the common onion, was assessed. Mitosis vitality decreased, suggesting UV-B damage can influence the plant’s physiology.

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Strain-selective in vitro and in silico structure activity relationship (SAR) of N-acyl β-lactam broad spectrum antibiotics

Poosarla et al. | Oct 19, 2021

Strain-selective <i>in vitro</i> and <i>in silico</i> structure activity relationship (SAR) of N-acyl β-lactam broad spectrum antibiotics

In this study, the authors investigate the antibacterial efficacy of penicillin G and its analogs amoxicillin, carbenicillin, piperacillin, cloxacillin, and ampicillin, against four species of bacteria. Results showed that all six penicillin-type antibiotics inhibit Staphylococcus epidermidis, Escherichia coli, and Neisseria sicca with varying degrees of efficacy but exhibited no inhibition against Bacillus cereus. Penicillin G had the greatest broad-spectrum antibacterial activity with a high radius of inhibition against S. epidermidis, E. coli, and N. sicca.

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The effects of stress on the bacterial community associated with the sea anemone Diadumene lineata

Cahill et al. | Feb 15, 2021

The effects of stress on the bacterial community associated with the sea anemone Diadumene lineata

In healthy ecosystems, organisms interact in a relationship that helps maintain one another's existence. Stress can disrupt this interaction, compromising the survival of some of the members of such relationships. Here, the authors investigate the effect of stress on the interaction between anemones and their microbiome. Their study suggests that stress changes the composition of the surface microbiome of the anemone D. lineata, which is accompanied by an increase in mucus secretion. Future research into the composition of this stress-induced mucus might reveal useful antimicrobial properties.

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The Effect of Delivery Method, Speaker Demographics, and Physical Environment on the Engagement Level of Older Adults

Seides et al. | May 24, 2015

The Effect of Delivery Method, Speaker Demographics, and Physical Environment on the Engagement Level of Older Adults

With an increasing older adult population and rapid advancements in technology, it is important that senior citizens learn to use new technologies to remain active in society. A variety of factors on learning were investigated through surveys of senior citizens. Older adults preferred an interactive lesson style, which also seemed to help them retain more course material.

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The Effects of Altered Microbiome on Caenorhabditis elegans Egg Laying Behavior

Gohari et al. | Aug 12, 2019

The Effects of Altered Microbiome on <em>Caenorhabditis elegans</em> Egg Laying Behavior

Since the discovery that thousands of different bacteria colonize our gut, many of which are important for human wellbeing, understanding the significance of balancing the different species on the human body has been intensely researched. Untangling the complexity of the gut microbiome and establishing the effect of the various strains on human health is a challenge in many circumstances, and the need for simpler systems to improve our basic understanding of microbe-host interactions seems necessary. C. elegans are a well-established laboratory animal that feed on bacteria and can thus serve as a less complex system for studying microbe-host interactions. Here the authors investigate how the choice of bacterial diet affects worm fertility. The same approach could be applied to many different outcomes, and facilitate our understanding of how the microbes colonizing our guts affect various bodily functions.

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Differential privacy in machine learning for traffic forecasting

Vinay et al. | Dec 21, 2022

Differential privacy in machine learning for traffic forecasting

In this paper, we measured the privacy budgets and utilities of different differentially private mechanisms combined with different machine learning models that forecast traffic congestion at future timestamps. We expected the ANNs combined with the Staircase mechanism to perform the best with every value in the privacy budget range, especially with the medium high values of the privacy budget. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and neural network models to forecast and then added differentially private Laplacian, Gaussian, and Staircase noise to our datasets. We tested two real traffic congestion datasets, experimented with the different models, and examined their utility for different privacy budgets. We found that a favorable combination for this application was neural networks with the Staircase mechanism. Our findings identify the optimal models when dealing with tricky time series forecasting and can be used in non-traffic applications like disease tracking and population growth.

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