Faculty Forum : Blue Sky Strategic Plan Pathway 2

The Blue Sky Strategic Plan’s Pathway 2 is entitled “Securing Our Future: Ensuring Financial Sustainability”. As the Pathway 2 Chair, Jeffery Mills, President of the University of Maine Foundation, presented to the University community a review of initiatives and accomplishments related to Pathway 2. He led a discussion and gathered feedback. UMaine community members were encouraged to attend. For those unable to attend, a video of the Forum and an opportunity to provide feedback were available through the webpage after the Forum

Predictive Model for Thermal and Stress Field in Selective Laser Melting Process -- Part I

During the part forming in laser powder bed fusion process, thermal distortion is one big problem due to the thermal stress which is caused by the high cooling rate and temperature gradient. Therefore, it is important to know the effect of process parameters on thermal and stress evolution in the melt zone. In this paper, a 3D finite element model for Selective Laser Melting (SLM) process based on sequentially coupled thermo-mechanical field analysis was developed for accurately predicting thermal history and surface features, like distortion and residual stress. Temperature dependent material properties for performed material 304L stainless steel are incorporated into the model capturing the change from powder to fully dense solid stainless steel. Surface temperature gradients and thermal stress were fully presented in the development of different parameter sets, which designed for the probability of reducing defect formation. Simulation results showed that the sequent thermal cyclic melting in successive scanned tracks resulted in alternating compressive and tensile thermal stresses. A predictive model for thermal and stress field in large part by selective laser melting process is come up in Part II. After the parts cooled down to room temperature, higher residual stresses were found in longitudinal stress. This paper will provide guidance on how to achieve minimum residual stresses and deformations by the study of the process parameters

Basic Issues in Economic Comparisons of Commercial and Sport Fisheries: A Study of Allocation Alternatives for Alaska Kenai River Sockeye Salmon Fisheries

Allocation between commercial and sport fisheries is becoming an increasingly difficult and divisive issue in fisheries management. As conflicts over allocation have increased, so has interest in the relative economic contributions of commercial and sport fisheries. This paper describes eight basic issues in economic comparisons of commercial and sport fisheries. These basic issues should be considered in evaluating or planning any economic comparison of commercial and sport fisheries--from a back-of-the-envelope comparison to a formal study. We illustrate these issues by describing how they arose in an economic comparison o f commercial and sport fisheries for Alaska's Kenai River sockeye salmon. Prepared for presentation at a session on "The Role of Economics in Fisheries Management" at the 1998 Annual Meeting of the American Fisheries Society Hartford, Connecticut August 24, 199

Studies to assess the effect of pet training aids specifically remote static pulse systems on the welfare of domestic dogs

This project assessed the welfare of dogs trained with pet training aids, specifically remote static pulse collar systems (e-collars). Previous work has focused on a very limited number of devices in a very limited range of contexts and the evidence of the impact of such devices on dog's overall quality of life is inconclusive. Project AW1402 aimed to assess the physical characteristics of the e-collars and the physiological, behavioural and psychological consequences of their use in dog training in four objectives. 1. Investigate the resistance in the neck skin of a range of dogs 2. Measure the physical output properties of the devices under investigation 3. Evaluate methods for recording behavioural/psychological measures of emotional state in the context of dog training. 4. Investigate the long term behavioural, physiological and psychological effects of using training devices in the domestic dog A representative selection of e-collars was purchased to allow the assessment of electrical properties in laboratory tests and the evaluation of manuals (Objective 2). As the electrical output of the e-collars depended on the impedance presented by the dogs' necks, this was measured first on a sample of dogs of a number of breed and cross-breeds under dry and wet conditions (Objective 1). This was done under supervision of an animal welfare specialist and did not cause pain or distress as indicative from the dogs' behaviours. The impedance of dogs can be modelled as a passive resistance with a value of about 10kΩ (10th -90th percentile range 4 – 150kΩ) for wet dogs and 600kΩ (22 – 950kΩ) for dry dogs. The momentary stimulus generated by the e-collars comprised a sequence of identical short voltage pulses. The continuous stimulus comprised a much longer sequence of the same voltage pulses. There were considerable differences between tested e-collar models in the voltages, the number of pulses in, and length of each stimulus, but little variation within individual models of e-collars. The peak voltage delivered by e-collars varied significantly with the resistance of the dog, from as much as 6000V at 500kΩ to 100V at 5kΩ. The highest voltages were generated for only a few millionths of a second. To allow meaningful comparisons between e-collars (taking into account the differences in electrical characteristics), a stimulus strength ranking indicator (SSRI) was developed. This showed differences between the selected e-collars, as well as differences in the relationship between momentary and continuous stimuli. Manuals were clear on operation, but gave varying levels of information on using the e-collar in training. Generally they did not adequately explain their full potential, for instance with respect to using the tone or vibrate functions. Advice in manuals was not always taken up by end-users as evident from responses in owner questionnaire collected as part of objectives 3 and 4. A pilot study involving 10 dogs with prior experience of e-collars and 10 control dogs (matched by age, sex, breed and where possible behavioural problem) was conducted to develop and evaluate protocols for assessing dog welfare in home and training environments (Objective 3). This was followed by a larger field study (Objective 4) involving 65 dogs with prior experience of e-collar training and 65 matched controls. Cases and matched controls for Objective 4 were initially recruited from a separate training methods survey distributed to dog owners to reduce sampling bias, but this was later supplemented by other recruitment methods. Data collection in Objective 4 included:- 1. An owner questionnaire to collect demographic data on dogs and owners; and owner-reports of behaviour during training and efficacy of training methods. 2. First passage urine to measure cortisol, creatinine, and metabolites of the neuro-transmitters serotonin (5-HIAA) and dopamine (HVA). 3. Saliva for assay of cortisol prior to and during training. 4. Observations of dog behaviour during fitting of inactivated e-collar 5. Observation of dog behaviours during a series of standard training tasks (“stay”, “leave” and “recall” and the situation for which the focal device was used) given by both owner and a researcher and conducted in the context where the focal device had been originally used for training. Each set of tests were repeated both without (Test 1) and with (Test 2) the wearing of a dummy or inactivated e-collar to enable comparisons to be made between measures for the same dogs when wearing an e-collar (which may predict the application of stimulus for the dog) and not. 6. A spatial discrimination task designed to use judgement bias to assess underlying affective state. Questionnaire data included type of device used, time since use, owner perceptions of the success of training, and owner reports of behavioural responses to use. Training methods used by owners in the control group could be sub-divided into those mainly using positive reinforcement (reward based) training, and those using methods based largely on punishment or negative reinforcement. Most owners (68%) purchased e-collars new, mainly from the internet, though some owners borrowed or purchased second hand collars. Problems with recall (40%) and livestock worrying (33%) accounted for the majority of reasons for e-collars use, although some manuals included information on use for basic obedience. Owner reports on operation of devices suggested they were often unclear as to how best use e-collars in training and some appeared not to have followed manual advice (if available). 36% of owners reported vocalisations on first use, and 26% on subsequent use of e-collars. This suggested that operating levels may not have been set in accordance with manufacturer’s instruction (where available), though due to owners often being unable to recall how they used the device this could not always be verified. Owners reported the addressed behaviours to be more severe in e-collar trained dogs than the controls. Owners showed a high degree of satisfaction with the effectiveness of all the training approaches used, though owners from the e-collar group were more likely to state they would prefer to try other forms of training in the future. No significant differences between groups were identified for behaviours shown during collar fitting, although a wide range of behavioural responses among dogs were noted. These differences were considered likely to reflect response to novelty in the control group, and the specific events that usually followed collar fitting in the e-collar group such no consequence, going for a walk or stimulus application. Because of high variability between dogs, it was considered that differences in measures between the first series of training tasks (Test 1; conducted with no collar) and the second series of training tasks (Test 2; conducted with dogs wearing a dummy collar) would be more reliable than absolute differences between groups. There was a significant increase in salivary cortisol between tests in the e-collar group compared to the sub-group of dogs trained using positive reinforcement. A behavioural scale incorporating proportion of training period tense, an inverse of proportion of training time relaxed, and proportion of time with attention directed at owner (whoever was training) significantly increased in the e-collar group, as compared to both the whole control group and the sub-set of dogs predominantly trained using positive reinforcement. These differences may reflect increased emotional arousal in e-collar dogs as a result of previous learned associations with the collar. Data was collected for a further 11 control dogs who experienced both sets of standard training tasks but wearing no collar to test for potential order effects. Their behavioural and physiological responses were consistent with control dogs who wore the e-collar for the second set of tasks. There was some evidence of higher baseline cortisol in control dogs compared with e-collar dogs in both the urinary cortisol: creatinine (reflecting cortisol production overnight before researcher arrival) and baseline salivary cortisol (taken after the arrival of the researcher and likely to be influenced by the events associated with visitor arrival and greeting) particularly when considering just the positive reinforcement sub-group. However these differences were small and found not to be significant when a multiple comparison Bonferroni correction was applied. There were no significant differences in neurotransmitter metabolites between the two groups. Neither were there significant differences between control and e-collar dogs with respect to speed to ambiguous probes in the judgement bias task. However, in the latter case, group effects were confounded by strong effects of arena size where different test spaces had been used. Overall, this project has highlighted the very variable outcomes between individual dogs when trained using e-collars. The combination of differences in individual dog’s perception of stimuli, different stimulus strength and characteristics from collars of different brands, differences between momentary and continuous stimuli, differences between training advice in manuals, differences in owner understanding of training approaches and how owners use the devices in a range of different circumstances are likely to lead to a wide range of training experiences for pet dogs. This variability in experience is evidenced in the data from trained dogs such as owner reports of their dogs’ response to e-collar use. Significant differences were, however, found in data collected from e-collar and control dogs undergoing standard training tests with and without dummy e-collars. These included a difference in the change in salivary cortisol between tests with e-collar dogs showing an increase and positive reinforcement dogs showing a lowering of salivary cortisol between the tests. There were also behavioural changes that were consistent with changes in emotional state, with e-collar dogs showing an increase in a behavioural scale incorporating time spent tense and the inverse of time relaxed between the two situations. These training tasks were designed as far as possible to replicate the context where e-collar training had occurred in the past, and indicate a shift towards higher levels of physiological and behavioural arousal in the e-collar dogs as well as a tendency to focus more on the owner than when they had not been wearing a collar. Thus it seems reasonable to conclude that the previous use of e-collars in training is associated with behavioural and physiological responses that are consistent with negative emotional states. It is therefore suggested that the use of e-collars in training pet dogs leads to a negative impact on welfare, at least in a proportion of animals trained using this technique

Ferland Engineering Education and Design Center (EEDC) Virtual Beam Topping Ceremony

Construction of the $78 million Engineering Education and Design Center (EEDC) on the University of Maine campus began in May 2020, with workers following state-mandated health and safety guidelines. Work on the 105,000-square-foot facility is expected to be completed in spring 2022. Design and construction of EEDC involved 78 graduates of the University of Maine, many from the College of Engineering. Over 500 alumni, friends, corporations, and foundations contributed to the fund-raising effort. Retired power industry executive and Skowhegan, Maine native, Jim Ferland and his wife Eileen provided a$10-million naming gift for the new Center. Jim Ferland earned a degree in Mechanical Engineering from the University of Maine in 1964. Click on the download link for a machine-generated English-language transcript

Wolf Management In The Northwestern United States

Gray wolves (Canis lupus) were deliberately eliminated from the northern Rocky Mountains (NRM) by 1930. Restoration began in 1986. There are currently nearly 120 breeding pair and 1800 wolves. Wolf restoration initially proceeded with more benefits and fewer problems than predicted. However, conflicts have steadily increased since 2002 when the population first met its minimum recovery goal. About 40 million has been spent since 1974 and the management program currently costs >4 million/yr. Wolves were delisted in 2008 and 2009 but relisted by federal court order in 2009 and 2010. While the NRM wolf population is biologically recovered, public opinion remains divisive and the legal, political, and policy decisions will continue to be litigated by a diversity of interests. Science is a poor tool to resolve the differing human values that continue to be debated with great passion through wolf symbolism

An improved, high-quality draft genome sequence of the Germination-Arrest Factor-producing Pseudomonas fluorescens WH6

<p>Abstract</p> <p>Background</p> <p><it>Pseudomonas fluorescens </it>is a genetically and physiologically diverse species of bacteria present in many habitats and in association with plants. This species of bacteria produces a large array of secondary metabolites with potential as natural products. <it>P. fluorescens </it>isolate WH6 produces Germination-Arrest Factor (GAF), a predicted small peptide or amino acid analog with herbicidal activity that specifically inhibits germination of seeds of graminaceous species.</p> <p>Results</p> <p>We used a hybrid next-generation sequencing approach to develop a high-quality draft genome sequence for <it>P. fluorescens </it>WH6. We employed automated, manual, and experimental methods to further improve the draft genome sequence. From this assembly of 6.27 megabases, we predicted 5876 genes, of which 3115 were core to <it>P. fluorescens </it>and 1567 were unique to WH6. Comparative genomic studies of WH6 revealed high similarity in synteny and orthology of genes with <it>P. fluorescens </it>SBW25. A phylogenomic study also placed WH6 in the same lineage as SBW25. In a previous non-saturating mutagenesis screen we identified two genes necessary for GAF activity in WH6. Mapping of their flanking sequences revealed genes that encode a candidate anti-sigma factor and an aminotransferase. Finally, we discovered several candidate virulence and host-association mechanisms, one of which appears to be a complete type III secretion system.</p> <p>Conclusions</p> <p>The improved high-quality draft genome sequence of WH6 contributes towards resolving the <it>P. fluorescens </it>species, providing additional impetus for establishing two separate lineages in <it>P. fluorescens</it>. Despite the high levels of orthology and synteny to SBW25, WH6 still had a substantial number of unique genes and represents another source for the discovery of genes with implications in affecting plant growth and health. Two genes are demonstrably necessary for GAF and further characterization of their proteins is important for developing natural products as control measure against grassy weeds. Finally, WH6 is the first isolate of <it>P. fluorescens </it>reported to encode a complete T3SS. This gives us the opportunity to explore the role of what has traditionally been thought of as a virulence mechanism for non-pathogenic interactions with plants.</p

JWST reveals widespread CO ice and gas absorption in the Galactic Center cloud G0.253+0.016

We report JWST NIRCam observations of G0.253+0.016, the molecular cloud in the Central Molecular Zone known as The Brick, with the F182M, F187N, F212N, F410M, F405N, and F466N filters. We catalog 56,146 stars detected in all 6 filters using the crowdsource package. Stars within and behind The Brick exhibit prodigious absorption in the F466N filter that is produced by a combination of CO ice and gas. In support of this conclusion, and as a general resource, we present models of CO gas and ice and CO$_2$ ice in the F466N, F470N, and F410M filters. Both CO gas and ice may contribute to the observed stellar colors. We show, however, that CO gas does not absorb the Pf$\beta$ and Hu$\epsilon$ lines in F466N, but that these lines show excess absorption, indicating that CO ice is also present and contributes to observed F466N absorption. The most strongly absorbed stars in F466N are extincted by $\sim$ 2 magnitudes, corresponding to $>$ 80\% flux loss. This high observed absorption requires very high column densities of CO, requiring total CO column that is in tension with standard CO abundance and/or gas-to-dust ratios. There is therefore likely to be a greater CO/H$_2$ ratio (X$_{CO} > 10^{-4}$) and more dust per H$_2$ molecule ($>0.01$) in the Galactic Center than the Galactic disk. Ice and/or gas absorption is observed even in the cloud outskirts, implying that additional caution is needed when interpreting stellar photometry in filters that overlap with ice bands throughout our Galactic Center. The widespread CO absorption in our Galactic Center hints that significant ice absorption is likely present in other galactic centers.Comment: Submitted to ApJ. Revised after second referee report. 16 pages, 11 figure

Developing and Selecting Auditory Warnings for a Real-Time Behavioral Intervention

Real-time sensing and computing technologies are increasingly used in the delivery of real-time health behavior interventions. Auditory signals play a critical role in many of these interventions, impacting not only behavioral response but also treatment adherence and participant retention. Yet, few behavioral interventions that employ auditory feedback report the characteristics of sounds used and even fewer design signals specifically for their intervention. This paper describes a four-step process used in developing and selecting auditory warnings for a behavioral trial designed to reduce indoor secondhand smoke exposure. In step one, relevant information was gathered from ergonomic and behavioral science literature to assist a panel of research assistants in developing criteria for intervention-specific auditory feedback. In step two, multiple sounds were identified through internet searches and modified in accordance with the developed criteria, and two sounds were selected that best met those criteria. In step three, a survey was conducted among 64 persons from the primary sampling frame of the larger behavioral trial to compare the relative aversiveness of sounds, determine respondents\u27 reported behavioral reactions to those signals, and assess participant’s preference between sounds. In the final step, survey results were used to select the appropriate sound for auditory warnings. Ultimately, a single-tone pulse, 500 milliseconds (ms) in length that repeats every 270 ms for three cycles was chosen for the behavioral trial. The methods described herein represent one example of steps that can be followed to develop and select auditory feedback tailored for a given behavioral intervention