Exploring Agricultural Production Systems and Their Fundamental Components with System Dynamics Modelling

Agricultural production in the United States is undergoing marked changes due to rapid shifts in consumer demands, input costs, and concerns for food safety and environmental impact. Agricultural production systems are comprised of multidimensional components and drivers that interact in complex ways to influence production sustainability. In a mixed-methods approach, we combine qualitative and quantitative data to develop and simulate a system dynamics model that explores the systemic interaction of these drivers on the economic, environmental and social sustainability of agricultural production. We then use this model to evaluate the role of each driver in determining the differences in sustainability between three distinct production systems: crops only, livestock only, and an integrated crops and livestock system. The result from these modelling efforts found that the greatest potential for sustainability existed with the crops only production system. While this study presents a stand-alone contribution to sector knowledge and practice, it encourages future research in this sector that employs similar systems-based methods to enable more sustainable practices and policies within agricultural production

Proteome analysis of the hyaluronic acid-producing bacterium, Streptococcus zooepidemicus

Background: Streptococcus equi subsp. zooepidemicus (S. zooepidemicus) is a commensal of horses and an opportunistic pathogen in many animals and humans. Some strains produce copious amounts of hyaluronic acid, making S. zooepidemicus an important industrial microorganism for the production of this valuable biopolymer used in the pharmaceutical and cosmetic industry. Encapsulation by hyaluronic acid is considered an important virulence factor in other streptococci, though the importance in S. zooepidemicus remains poorly understood. Proteomics may provide a better understanding of virulence factors in S. zooepidemicus, facilitate the design of better diagnostics and treatments, and guide engineering of superior production strains

Mode-coupling theory and the fluctuation-dissipation theorem for nonlinear Langevin equations with multiplicative noise

In this letter, we develop a mode-coupling theory for a class of nonlinear Langevin equations with multiplicative noise using a field theoretic formalism. These equations are simplified models of realistic colloidal suspensions. We prove that the derived equations are consistent with the fluctuation-dissipation theorem. We also discuss the generalization of the result given here to real fluids, and the possible description of supercooled fluids in the aging regime. We demonstrate that the standard idealized mode-coupling theory is not consistent with the FDT in a strict field theoretic sense.Comment: 14 pages, to appear in J. Phys.

The Impact of Plant Essential Oils and Fine Mesh Row Covers on Flea Beetle (Chrysomelidae) Management in Brassicaceous Greens Production

Brassicaceous leafy greens are an important crop for small growers but are difficult to produce due to damage by flea beetles. Flea beetles are problematic for growers as they chew many small holes through leaves rendering produce unmarketable. We tested the efficacy of several essential oils, the woven-mesh row cover ProtekNet, and the spunbonded row cover Agribon, compared to organic and conventional insecticides and no spray controls in the spring and fall of 2019. We found that the two row cover treatments (Agribon and ProtekNet) provided the best control of flea beetles and associated damage. Thyme oil was highly phytotoxic and killed the crop entirely and rosemary and neem essential oils caused mild phytotoxic burns. Organic insecticides rarely performed better than the no spray control. While conventional insecticides controlled most flea beetles, the crop was often still too highly damaged to sell. The results of our study suggest row covers offer producers an effective method of flea beetle control that reduces their dependence on insecticides for conventional and organic production

Characteristics of effective collaborative care for treatment of depression: a systematic review and meta-regression of 74 randomised controlled trials

This is a freely-available open access publication. Please cite the published version which is available via the DOI link in this record.BACKGROUND: Collaborative care is a complex intervention based on chronic disease management models and is effective in the management of depression. However, there is still uncertainty about which components of collaborative care are effective. We used meta-regression to identify factors in collaborative care associated with improvement in patient outcomes (depressive symptoms) and the process of care (use of anti-depressant medication). METHODS AND FINDINGS: Systematic review with meta-regression. The Cochrane Collaboration Depression, Anxiety and Neurosis Group trials registers were searched from inception to 9th February 2012. An update was run in the CENTRAL trials database on 29th December 2013. Inclusion criteria were: randomised controlled trials of collaborative care for adults ≥18 years with a primary diagnosis of depression or mixed anxiety and depressive disorder. Random effects meta-regression was used to estimate regression coefficients with 95% confidence intervals (CIs) between study level covariates and depressive symptoms and relative risk (95% CI) and anti-depressant use. The association between anti-depressant use and improvement in depression was also explored. Seventy four trials were identified (85 comparisons, across 21,345 participants). Collaborative care that included psychological interventions predicted improvement in depression (β coefficient -0.11, 95% CI -0.20 to -0.01, p = 0.03). Systematic identification of patients (relative risk 1.43, 95% CI 1.12 to 1.81, p = 0.004) and the presence of a chronic physical condition (relative risk 1.32, 95% CI 1.05 to 1.65, p = 0.02) predicted use of anti-depressant medication. CONCLUSION: Trials of collaborative care that included psychological treatment, with or without anti-depressant medication, appeared to improve depression more than those without psychological treatment. Trials that used systematic methods to identify patients with depression and also trials that included patients with a chronic physical condition reported improved use of anti-depressant medication. However, these findings are limited by the observational nature of meta-regression, incomplete data reporting, and the use of study aggregates.NIH

Repeated Plyometric Exercise Attenuates Blood Glucose in Healthy Adults

International Journal of Exercise Science 10(7): 1076-1084, 2017. Plyometric exercise is popular in commercial exercise programs aiming to maximize energy expenditure for weight loss. However, the effect of plyometric exercise on blood glucose is unknown. The purpose of this study was to investigate the effect of relatively high intensity plyometric exercise on blood glucose. Thirteen subjects (6 females age= 21.8 ± 1.0 yrs.; height= 163.7 ± 7.8 cm; mass= 60.8 ± 6.7 kg and 7 males age= 22.0 ± 2.6 yrs.; height= 182.3 ± 3.6 cm; mass= 87.4 ± 12.5 kg) volunteered to participate. Subjects completed two random conditions on two separate days, consisting of either five sets of 10 maximal effort countermovement squat jumps (SJ) with 50 seconds’ rest between sets or quiet sitting (SIT) for the time equated to the SJ duration (~4min). Immediately after each condition, subjects drank 75g of anhydrous glucose (CHO) in 100ml of water. Blood glucose measurements were taken via finger prick pre and immediately post SJ or SIT, and 5, 15, 30, and 60 min post. A 2x6 (condition x time) ANOVA revealed a significant interaction where SJ blood glucose was lower at 15 (114.0 ± 14.6 mg/dl) and 30 (142.1 ± 22.5 mg/dl) min compared to SIT (15min 130.8 ± 14.0 mg/dl and 30min 159.3 ± 21.0 mg/dl). The current plyometric protocol attenuated CHO-induced blood glucose at 15 and 30 min. This may be due to increased physiological stress applied to the muscles, thus increasing muscular glucose uptake

Succession of physiological stages hallmarks the transcriptomic response of the fungus Aspergillus niger to lignocellulose.

BackgroundUnderstanding how fungi degrade lignocellulose is a cornerstone of improving renewables-based biotechnology, in particular for the production of hydrolytic enzymes. Considerable progress has been made in investigating fungal degradation during time-points where CAZyme expression peaks. However, a robust understanding of the fungal survival strategies over its life time on lignocellulose is thereby missed. Here we aimed to uncover the physiological responses of the biotechnological workhorse and enzyme producer Aspergillus niger over its life time to six substrates important for biofuel production.ResultsWe analysed the response of A. niger to the feedstock Miscanthus and compared it with our previous study on wheat straw, alone or in combination with hydrothermal or ionic liquid feedstock pretreatments. Conserved (substrate-independent) metabolic responses as well as those affected by pretreatment and feedstock were identified via multivariate analysis of genome-wide transcriptomics combined with targeted transcript and protein analyses and mapping to a metabolic model. Initial exposure to all substrates increased fatty acid beta-oxidation and lipid metabolism transcripts. In a strain carrying a deletion of the ortholog of the Aspergillus nidulans fatty acid beta-oxidation transcriptional regulator farA, there was a reduction in expression of selected lignocellulose degradative CAZyme-encoding genes suggesting that beta-oxidation contributes to adaptation to lignocellulose. Mannan degradation expression was wheat straw feedstock-dependent and pectin degradation was higher on the untreated substrates. In the later life stages, known and novel secondary metabolite gene clusters were activated, which are of high interest due to their potential to synthesize bioactive compounds.ConclusionIn this study, which includes the first transcriptional response of Aspergilli to Miscanthus, we highlighted that life time as well as substrate composition and structure (via variations in pretreatment and feedstock) influence the fungal responses to lignocellulose. We also demonstrated that the fungal response contains physiological stages that are conserved across substrates and are typically found outside of the conditions with high CAZyme expression, as exemplified by the stages that are dominated by lipid and secondary metabolism

Palaeogeographical evolution of the Rattray Volcanic Province, Central North Sea

Funded by Carnegie Trust for the Universities of Scotland PHD060365Peer reviewedPostprin

RAMPARTS: A Programmer-Friendly System for Building Homomorphic Encryption Applications

Homomorphic Encryption (HE) is an emerging technology that enables computing on data while the data is encrypted. A major challenge with homomorphic encryption is that it takes extensive expert knowledge to design meaningful and useful programs that are constructed from atomic HE operations. We present RAMPARTS to address this challenge. RAMPARTS provides an environment for developing HE applications in Julia, a high-level language, the same way as ``cleartext\u27\u27 applications are typically written in Julia. RAMPARTS makes the following three contributions. First, we use symbolic execution to automate the construction of an optimized computation circuit where both the circuit size and multiplicative depth are chosen by the compiler. Second, RAMPARTS automatically selects the HE parameters for the generated circuit, which is typically done manually by an HE expert. Third, RAMPARTS automatically selects the plaintext encoding for input values, and performs input and output data transformations. These three operations are not easily performed by programmers who are not HE experts. Thus, RAMPARTS makes HE more widely available and usable by the the population of programmers. We compare our approach with Cingulata, the only previously known system that automatically generates circuits for HE computations. The HE circuits generated by RAMPARTS are significantly more efficient than the circuits compiled by Cingulata. For instance, our runtimes for key generation/circuit compilation and all online operations are more than one order of magnitude lower for a sample image processing application used for performance evaluation in our study

Household Effects of School Closure during Pandemic (H1N1) 2009, Pennsylvania, USA

To determine the effects of school closure, we surveyed 214 households after a 1-week elementary school closure because of pandemic (H1N1) 2009. Students spent 77% of the closure days at home, 69% of students visited at least 1 other location, and 79% of households reported that adults missed no days of work to watch children