Bio-economic evaluation of pasture-cropping, a novel system of integrating perennial pastures and crops on crop-livestock farms

Pasture-cropping is a novel approach to increase the area of perennial crops in mixed sheep and cropping systems. It involves planting annual cereals directly into a living perennial pasture. There is interest in subtropical grasses as they are winter dormant and their growth profile is potentially well suited to pasture-cropping. However, a wide range of factors can affect the uptake of such systems. This paper assesses the relative importance of factors that can influence decisions to introduce pasture-cropping. In this paper the research question is: what factors predispose a farm to take up a new technology such as (1) subtropical grass and (2) subtropical grass that is pasture-cropped. The analysis uses the MIDAS model of a central wheatbelt farm in Western Australia. The results suggest the adoption of subtropical grasses is likely to be strongly influenced by soil mix; feed quality; and whether the farm is predominantly grazing or cropping and by the presence of meat versus wool producing animals. The same factors are relevant for subtropical grass that is pasture-cropped but in addition yield penalties due to competition between the host perennial and the companion cereal become important. The results suggest the level of forage production by subtropical grass is less important but this factor is likely to become more important if feed quality can be improved.Environmental Economics and Policy,

ADOPT: a tool for predicting adoption of agricultural innovations

A wealth of evidence exists about the adoption of new practices and technologies in agriculture but there does not appear to have been any attempt to simplify this vast body of research knowledge into a model to make quantitative predictions across a broad range of contexts. This is despite increasing demand from research, development and extension agencies for estimates of likely extent of adoption and the likely timeframes for project impacts. This paper reports on the reasoning underpinning the development of ADOPT (Adoption and Diffusion Outcome Prediction Tool). The tool has been designed to: 1) predict an innovation‘s likely peak extent of adoption and likely time for reaching that peak; 2) encourage users to consider the influence of a structured set of factors affecting adoption; and 3) engage R, D & E managers and practitioners by making adoptability knowledge and considerations more transparent and understandable. The tool is structured around four aspects of adoption: 1) characteristics of the innovation, 2) characteristics of the population, 3) actual advantage of using the innovation, and 4) learning of the actual advantage of the innovation. The conceptual framework used for developing ADOPT is described.Adoption, Diffusion, Prediction, Research and Development/Tech Change/Emerging Technologies,

Success rates of re-excision after positive margins for invasive lobular carcinoma of the breast.

Rates of positive margins after surgical resection of invasive lobular carcinoma (ILC) are high (ranging from 18 to 60%), yet the efficacy of re-excision lumpReceptor subtypeectomy for clearing positive margins is unknown. Concerns about the diffuse nature of ILC may drive increased rates of completion mastectomy to treat positive margins, thus lowering breast conservation rates. We therefore determined the success rate of re-excision lumpectomy in women with ILC and positive margins after surgical resection. We identified 314 cases of stage I-III ILC treated with breast conserving surgery (BCS) at the University of California, San Francisco. Surgical procedures, pathology reports, and outcomes were analyzed using univariate and multivariate statistics and Cox-proportional hazards models. We evaluated outcomes before and after the year 2014, when new margin management consensus guidelines were published. Positive initial margins occurred in 118 (37.6%) cases. Of these, 62 (52.5%) underwent re-excision lumpectomy, which cleared the margin in 74.2%. On multivariate analysis, node negativity was significantly associated with successful re-excision (odds ratio [OR] 3.99, 95% CI 1.15-13.81, p = 0.029). After 2014, we saw fewer initial positive margins (42.7% versus 25.5%, p = 0.009), second surgeries (54.6% versus 20.2%, p < 0.001), and completion mastectomies (27.7% versus 4.5%, p < 0.001). In this large cohort of women with ILC, re-excision lumpectomy was highly successful at clearing positive margins. Additionally, positive margins and completion mastectomy rates significantly decreased over time. These findings highlight improvements in management of ILC, and suggest that completion mastectomy may not be required for those with positive margins after initial BCS

An Evolving Understanding of Enigmatic Large Ripples on Mars

Two scales of ripples form in fine sand on Mars. The larger ripples were proposed to have an equilibrium size set by an aerodynamic process, making them larger under thinner atmospheres and distinct from smaller impact ripples. Sullivan et al. (2020) show that large ripples can develop in a numerical model due to Mars’ low atmospheric pressure. Although their proposed growth‐limiting mechanism is consistent with an aerodynamic process, they argue that the ripples in their model are simply large versions of impact ripples, not a separate class of ripples. Here, we explore this debate by synthesizing recent advances in large‐ripple formation. Although significant knowledge gaps remain, it is clear that large martian ripples are larger under thinner atmospheres, and thus remain a powerful paleoclimate indicator

Commercialisation and Impacts of Pasture Legumes in Southern Australia–Lessons Learnt

Forage legumes are a key feature of temperate grasslands in southern Australia, valued for their ability to increase animal production, improve soil fertility and fix atmospheric nitrogen. Of the 36 temperate annual legume and 11 temperate perennial legume species with registered cultivars introduced or domesticated in Australia over the last 100 years, a third have made a major contribution to agriculture, a third have modest use and a third have failed to make any commercial impact. Highly successful species include subterranean clover, barrel medic, white clover, lucerne, French serradella and balansa clover. Species were assessed on the scale of their application, ease of seed production and specific requirements for agronomic management to determine critical factors for maximising commercial success. Of fundamental importance is the need to understand the farming systems context for legume technologies, particularly as it relates to potential scale of application and impact on farm profitability. Other factors included a requirement for parallel investment in rhizobiology, implementing an adequate ‘duty of care’ problem-solving framework for each new plant product and the need to construct a commercialisation model that optimises the trade-off between rapid adoption by farmers and profitability of the seed industry. Our experience to date indicates that seed industry engagement is highest when they have exclusive rights to a cultivar, can exercise some control over seed production and can market seed for a premium price without having to carry over significant seed quantities from one season to the next. A capability for non-specialist seed production on-farm (with lower associated seed costs) is a disincentive for the seed industry, but may be an appropriate commercialisation model for some public cultivars

Systems pharmacology approach for prediction of pulmonary and systemic pharmacokinetics and receptor occupancy of inhaled drugs

Pulmonary drug disposition after inhalation is complex involving mechanisms, such as regional drug deposition, dissolution, and mucociliary clearance. This study aimed to develop a systems pharmacology approach to mechanistically describe lung disposition in rats and thereby provide an integrated understanding of the system. When drug- and formulation-specific properties for the poorly soluble drug fluticasone propionate were fed into the model, it proved predictive of the pharmacokinetics and receptor occupancy after intravenous administration and nose-only inhalation. As the model clearly distinguishes among drug-specific, formulation-specific, and system-specific properties, it was possible to identify key determinants of pulmonary selectivity of receptor occupancy of inhaled drugs: slow particle dissolution and slow drug-receptor dissociation. Hence, it enables assessment of factors for lung targeting, including molecular properties, formulation, as well as the physiology of the animal species, thereby providing a general framework for rational drug design and facilitated translation of lung targeting from animal to man

Maximal variance reduction for stochastic propagators with applications to the static quark spectrum

We study a new method -- maximal variance reduction -- for reducing the variance of stochastic estimators for quark propagators. We find that while this method is comparable to usual iterative inversion for light-light mesons, a considerable improvement is achieved for systems containing at least one infinitely heavy quark. Such systems are needed for heavy quark effective theory. As an illustration of the effectiveness of the method we present results for the masses of the ground state and excited states of $\bar{Q}q$ mesons and $\bar{Q}qq$ baryons. We compare these results with the experimental spectra involving $b$ quarks.Comment: 31 pages with 7 postscript file

An analog of glibenclamide selectively enhances autophagic degradation of misfolded α1-antitrypsin Z

The classical form of α1-antitrypsin deficiency (ATD) is characterized by intracellular accumulation of the misfolded variant α1-antitrypsin Z (ATZ) and severe liver disease in some of the affected individuals. In this study, we investigated the possibility of discovering novel therapeutic agents that would reduce ATZ accumulation by interrogating a C. elegans model of ATD with high-content genome-wide RNAi screening and computational systems pharmacology strategies. The RNAi screening was utilized to identify genes that modify the intracellular accumulation of ATZ and a novel computational pipeline was developed to make high confidence predictions on repurposable drugs. This approach identified glibenclamide (GLB), a sulfonylurea drug that has been used broadly in clinical medicine as an oral hypoglycemic agent. Here we show that GLB promotes autophagic degradation of misfolded ATZ in mammalian cell line models of ATD. Furthermore, an analog of GLB reduces hepatic ATZ accumulation and hepatic fibrosis in a mouse model in vivo without affecting blood glucose or insulin levels. These results provide support for a drug discovery strategy using simple organisms as human disease models combined with genetic and computational screening methods. They also show that GLB and/or at least one of its analogs can be immediately tested to arrest the progression of human ATD liver disease.</div

Prediction of suicidal ideation and attempt in 9 and 10 year-old children using transdiagnostic risk features

The objective of the current study was to build predictive models for suicidal ideation in a sample of children aged 9–10 using features previously implicated in risk among older adolescent and adult populations. This case-control analysis utilized baseline data from the Adolescent Brain and Cognitive Development (ABCD) Study, collected from 21 research sites across the United States (N = 11,369). Several regression and ensemble learning models were compared on their ability to classify individuals with suicidal ideation and/or attempt from healthy controls, as assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia–Present and Lifetime Version. When comparing control participants (mean age: 9.92±0.62 years; 4944 girls [49%]) to participants with suicidal ideation (mean age: 9.89±0.63 years; 451 girls [40%]), both logistic regression with feature selection and elastic net without feature selection predicted suicidal ideation with an AUC of 0.70 (CI 95%: 0.70–0.71). The random forest with feature selection trained to predict suicidal ideation predicted a holdout set of children with a history of suicidal ideation and attempt (mean age: 9.96±0.62 years; 79 girls [41%]) from controls with an AUC of 0.77 (CI 95%: 0.76–0.77). Important features from these models included feelings of loneliness and worthlessness, impulsivity, prodromal psychosis symptoms, and behavioral problems. This investigation provided an unprecedented opportunity to identify suicide risk in youth. The use of machine learning to examine a large number of predictors spanning a variety of domains provides novel insight into transdiagnostic factors important for risk classification