THE ROLE OF AGRICULTURAL ECONOMICS IN A CHANGING ENVIRONMENT

Environmental Economics and Policy,

Recognition and Management of Psychiatric Emergencies

Emergencies are simply unforeseen occurrences which present themselves to physicians in a variety of ways. Indeed, a physician is not the first person on hand for most emergencies but may merely be called upon for appropriate intervention. Any of us can be presented with an emergency, psychiatric or otherwise, at any moment. However, each of us has his own particular probability of sampling psychiatric emergencies, depending upon who he is and what he does. In actual fact, psychiatric emergencies more often confront people other than psychiatrists, for example, the policeman, the social worker, and the general practitioner (Ewing, 1965). As in most medical matters, prevention is preferable to cure. Thus, anticipation of complications and the early detection of pending emergencies are skills to be cultivated--something I will talk about later

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,

Mathematicians’ Central Role in Educating the STEM Workforce

In the recent report Engage to Excel,1 President Obama’s Council of Advisors on Science and Technology (PCAST) identifies mathematics as a bottleneck in undergraduate Science, Technology, Engineering, and Mathematics (STEM) education. Among PCAST’s recommendations are ones calling for the development and teaching of college-level mathematics courses “by faculty from mathematics-intensive disciplines other than mathematics” and for “a new pathway for producing K–12 mathematics teachers…in programs in mathematics-intensive fields other than mathematics.”2 While we are in sharp disagreement with these specific recommendations, we do share PCAST’s concern for the state of STEM education. We encourage the mathematics community to focus constructively on the broad view the report sketches. We appeal to the community to amplify its communications with other STEM disciplines, to publicize its teaching innovations, and to redouble its efforts to meet the challenges discussed by PCAST

Granulocyte Macrophage Colony-Stimulating Factor: A New Putative Therapeutic Target in Multiple Sclerosis

Experimental autoimmune encephalomyelitis (EAE), a model for multiple sclerosis, can be induced by immunization with a number of myelin antigens. In particular, myelin oligodendrocyte glycoprotein, a central nervous system (CNS)-specific antigen expressed on the myelin surface, is able to induce a paralytic MS-like disease with extensive CNS inflammation and demyelination in several strains of animals. Although not well understood, the egress of immune cells into the CNS in EAE is governed by a complex interplay between pro and antiinflammatory cytokines and chemokines. The hematopoietic growth factor, granulocyte macrophage colony-stimulating factor (GM-CSF), is considered to play a central role in maintaining chronic inflammation. The present study was designed to investigate the previously unexplored role of GM-CSF in autoimmune-mediated demyelination. GM-CSF−/− mice are resistant to EAE, display decreased antigen-specific proliferation of splenocytes, and fail to sustain immune cell infiltrates in the CNS, thus revealing key activities for GM-CSF in the development of inflammatory demyelinating lesions and control of migration and/or proliferation of leukocytes within the CNS. These results hold implications for the pathogenesis of inflammatory and demyelinating diseases and may provide the basis for more effective therapies for inflammatory diseases, and more specifically for multiple sclerosis

Evaluation and application of static headspace-multicapillary column-gas chromatography-ion mobility spectrometry for complex sample analysis.

An evaluation of static headspace-multicapillary column-gas chromatography-ion mobility spectrometry (SHS-MCC-GC-IMS) has been undertaken to assess its applicability for the determination of 32 volatile compounds (VCs). The key experimental variables of sample incubation time and temperature have been evaluated alongside the MCC-GC variables of column polarity, syringe temperature, injection temperature, injection volume, column temperature and carrier gas flow rate coupled with the IMS variables of temperature and drift gas flow rate. This evaluation resulted in six sets of experimental variables being required to separate the 32 VCs. The optimum experimental variables for SHS-MCC-GC-IMS, the retention time and drift time operating parameters were determined; to normalise the operating parameters, the relative drift time and normalised reduced ion mobility for each VC were determined. In addition, a full theoretical explanation is provided on the formation of the monomer, dimer and trimer of a VC. The optimum operating condition for each VC calibration data was obtained alongside limit of detection (LOD) and limit of quantitation (LOQ) values. Typical detection limits ranged from 0.1ng bis(methylthio)methane, ethylbutanoate and (E)-2-nonenal to 472ng isovaleric acid with correlation coefficient (R(2)) data ranging from 0.9793 (for the dimer of octanal) through to 0.9990 (for isobutyric acid). Finally, the developed protocols were applied to the analysis of malodour in sock samples. Initial work involved spiking an inert matrix and sock samples with appropriate concentrations of eight VCs. The average recovery from the inert matrix was 101±18% (n=8), while recoveries from the sock samples were lower, that is, 54±30% (n=8) for sock type 1 and 78±24% (n=6) for sock type 2. Finally, SHS-MCC-GC-IMS was applied to sock malodour in a field trial based on 11 volunteers (mixed gender) over a 3-week period. By applying the SHS-MCC-GC-IMS database, four VCs were identified and quantified: ammonia, dimethyl disulphide, dimethyl trisulphide and butyric acid. A link was identified between the presence of high ammonia and dimethyl disulphide concentrations and a high malodour odour grading, that is, ≥ 6. Statistical analysis did not find any correlation between the occurrence of dimethyl disulphide and participant gender

Population Monte Carlo algorithms

We give a cross-disciplinary survey on ``population'' Monte Carlo algorithms. In these algorithms, a set of ``walkers'' or ``particles'' is used as a representation of a high-dimensional vector. The computation is carried out by a random walk and split/deletion of these objects. The algorithms are developed in various fields in physics and statistical sciences and called by lots of different terms -- ``quantum Monte Carlo'', ``transfer-matrix Monte Carlo'', ``Monte Carlo filter (particle filter)'',``sequential Monte Carlo'' and ``PERM'' etc. Here we discuss them in a coherent framework. We also touch on related algorithms -- genetic algorithms and annealed importance sampling.Comment: Title is changed (Population-based Monte Carlo -> Population Monte Carlo). A number of small but important corrections and additions. References are also added. Original Version is read at 2000 Workshop on Information-Based Induction Sciences (July 17-18, 2000, Syuzenji, Shizuoka, Japan). No figure