2004-2005 Lynn University Chorus Concert

https://spiral.lynn.edu/conservatory_otherseasonalconcerts/1041/thumbnail.jp

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures

Electrochemical Biosensing of Algal Toxins in Water: The Current State-of-the-Art

Due to increasing stringency of water legislation and extreme consequences that failure to detect some contaminants in water can involve, there has been a strong interest in developing electrochemical biosensors for algal toxin detection during the past decade, evidenced by literature increasing from 2 journal papers pre-2009 to 24 between 2009 and 2018. In this context, this review has summarized recent progress of successful algal toxin detection in water using electrochemical biosensing techniques. Satisfactory detection recoveries using real environmental water samples and good sensor repeatability and reproducibility have been achieved, along with some excellent limit-of-detection (LOD) reported. Recent electrochemical biosensor literature in algal toxin detection is compared and discussed to cover three major design components: (1) biorecognition elements, (2) electrochemical read-out techniques, and (3) sensor electrodes and signal amplification strategy. The recent development of electrochemical biosensors has provided one more step further toward quick in situ detection of algal toxins in the contamination point of the water source. In the end, we have also critically reviewed the current challenges and research opportunities regarding electrochemical biosensors for algal toxin detection that need to be addressed before they attain commercial viability

Combined and single effects of pesticide carbaryl and toxic Microcystis aeruginosa on the life history of Daphnia pulicaria

The combined influence of a pesticide (carbaryl) and a cyanotoxin (microcystin LR) on the life history of Daphnia pulicaria was investigated. At the beginning of the experiments animals were pulse exposed to carbaryl for 24 h and microcystins were delivered bound in Microcystis’ cells at different, sub-lethal concentrations (chronic exposure). In order to determine the actual carbaryl concentrations in the water LC–MS/MS was used. For analyses of the cyanotoxin concentration in Daphnia’s body enzyme-linked immunosorbent assay (ELISA) was used. Individual daphnids were cultured in a flow-through system under constant light (16 h of light: 8 h of dark), temperature (20°C), and food conditions (Scenedesmus obliquus, 1 mg of C l−1). The results showed that in the treatments with carbaryl egg numbers per female did not differ significantly from controls, but the mortality of newborns increased significantly. Increasing microcystin concentrations significantly delayed maturation, reduced size at first reproduction, number of eggs, and newborns. The interaction between carbaryl and Microcystis was highly significant. Animals matured later and at a smaller size than in controls. The number of eggs per female was reduced as well. Moreover, combined stressors caused frequent premature delivery of offspring with body deformations such as dented carapax or an undeveloped heart. This effect is concluded to be synergistic and could not be predicted from the effects of the single stressors.

20th Annual Elementary Choral Festivals

Program listing performers and works performe

"If only I had taken the other road...": Regret, risk and reinforced learning in informed route-choice

This paper presents a study of the effect of regret on route choice behavior when both descriptional information and experiential feedback on choice outcomes are provided. The relevance of Regret Theory in travel behavior has been well demonstrated in non-repeated choice environments involving decisions on the basis of descriptional information. The relation between regret and reinforced learning through experiential feedbacks is less understood. Using data obtained from a simple route-choice experiment involving different levels of travel time variability, discrete-choice models accounting for regret aversion effects are estimated. The results suggest that regret aversion is more evident when descriptional information is provided ex-ante compared to a pure learning from experience condition. Yet, the source of regret is related more strongly to experiential feedbacks rather than to the descriptional information itself. Payoff variability is negatively associated with regret. Regret aversion is more observable in choice situations that reveal risk-seeking, and less in the case of risk-aversion. These results are important for predicting the possible behavioral impacts of emerging information and communication technologies and intelligent transportation systems on travelers' behavior. © 2012 Springer Science+Business Media, LLC

Electron/pion separation with an Emulsion Cloud Chamber by using a Neural Network

We have studied the performance of a new algorithm for electron/pion separation in an Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The software for separation consists of two parts: a shower reconstruction algorithm and a Neural Network that assigns to each reconstructed shower the probability to be an electron or a pion. The performance has been studied for the ECC of the OPERA experiment [1]. The $e/\pi$ separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data taken at CERN (pion beams) and at DESY (electron beams). The algorithm allows to achieve a 90% electron identification efficiency with a pion misidentification smaller than 1% for energies higher than 2 GeV

2004-2005 A Concert of Vocal Music

https://spiral.lynn.edu/conservatory_otherseasonalconcerts/1047/thumbnail.jp

The detection of neutrino interactions in the emulsion/lead target of the OPERA experiment

The OPERA neutrino detector in the underground Gran Sasso Laboratory (LNGS) was designed to perform the first detection of neutrino oscillations in appearance mode through the study of $\nu_\mu\to\nu_\tau$ oscillations. The apparatus consists of an emulsion/lead target complemented by electronic detectors and it is placed in the high energy long-baseline CERN to LNGS beam (CNGS) 730 km away from the neutrino source. Runs with CNGS neutrinos were successfully carried out in 2007 and 2008 with the detector fully operational with its related facilities for the emulsion handling and analysis. After a brief description of the beam and of the experimental setup we report on the collection, reconstruction and analysis procedures of first samples of neutrino interaction events