Empirical forecasting practices of a British university

This article is based on a single case study aimed at examining behavioral issues of forecasting, in particular the role and practice of forecasting in a British university settings. Key variables were identified in establishing associations between the variables that provide suitable criteria for the purpose of this study. Data collection was based on questionnaires distributed to people involved and interviews which were held with prominent staff of the University. Fisher-exact tests were performed to identify significant associations between variables. Results indicated the various levels of perceptions and practices of forecasting produced by the people involved at the University. The study implies that useful insights can be gathered through forecasting from a different perspective of the non-profit making service industry

Profile-Based Optimal Matchings in the Student-Project Allocation Problem

In the Student/Project Allocation problem (spa) we seek to assign students to individual or group projects offered by lecturers. Students provide a list of projects they find acceptable in order of preference. Each student can be assigned to at most one project and there are constraints on the maximum number of students that can be assigned to each project and lecturer. We seek matchings of students to projects that are optimal with respect to profile, which is a vector whose rth component indicates how many students have their rth-choice project. We present an efficient algorithm for finding agreedy maximum matching in the spa context – this is a maximum matching whose profile is lexicographically maximum. We then show how to adapt this algorithm to find a generous maximum matching – this is a matching whose reverse profile is lexicographically minimum. Our algorithms involve finding optimal flows in networks. We demonstrate how this approach can allow for additional constraints, such as lecturer lower quotas, to be handled flexibly

An introduction to the Cambridge advanced modeller

Complex products and their development processes may be viewed as systems, whose different aspects can be modelled as networks of interactions between elements in different domains. Many approaches have been proposed to explore, support or improve engineering processes by building such models. Developing these approaches, and applying them to problems of realistic complexity, often requires specialised computer software suitable for manipulating large data sets. However, creating suitable tools can be difficult–because software development is time-consuming and requires skills that many researchers and practitioners do not possess. We developed an approach which aims to address this problem by recognising the iterative nature of modelling research and its often tight coupling with prototype software development, and by reducing the effort of software prototyping and revision within this process. The approach is enabled by, and embodied in, the Cambridge Advanced Modeller (CAM)–a configurable software platform we have developed, refined and applied over several years and through a number of research projects

Parametric Oscillation with Squeezed Vacuum Reservoirs

Employing the quantum Hamiltonian describing the interaction of two-mode light (signal-idler modes) generated by a nondegenerate parametric oscillator (NDPO) with two uncorrelated squeezed vacuum reservoirs (USVR), we derive the master equation. The corresponding Fokker-Planck equation for the Q-function is then solved employing a propagator method developed in Ref. \cite{1}. Making use of this Q-function, we calculate the quadrature fluctuations of the optical system. From these results we infer that the signal-idler modes are in squeezed states and the squeezing occurs in the first quadrature. When the NDPO operates below threshold we show that, for a large squeezing parameter, a squeezing amounting to a noise suppression approaching 100% below the vacuum level in the first quadrature can be achieved.Comment: 16 page

Structural and torsional properties of the Trachycarpus fortunei palm petiole

The Trachycarpus fortunei palm is a good example of a palm with a large leaf blade supported by a correspondingly large petiole. The way in which the material and functional properties of the petiole interact is analysed using engineering and botanical methods with a view to understanding how the petiole functions from a structural standpoint. Initially, the histological aspects of the petiole are analysed at a microscopic level from sections of the petiole taken at regular intervals along its axis, in order to determine the density and location of the vascular bundles. A modified torsion rig was used to measure the torsion and shear stress variation along petiole sample lengths. Knowledge of vascular bundle placement within the petiole sections and their torsional loading characteristics contribute to understanding the petiole function

A platelet alpha-granule membrane protein (GMP-140) is expressed on the plasma membrane after activation.

We have previously characterized a monoclonal antibody, S12, that binds only to activated platelets (McEver, R.P., and M.N. Martin, 1984, J. Biol. Chem., 259:9799-9804). It identifies a platelet membrane protein of Mr 140,000, which we have designated as GMP-140. Using immunocytochemical techniques we have now localized this protein in unstimulated and thrombin-stimulated platelets. Polyclonal antibodies to purified GMP-140 were used to enhance the sensitivity of detection. Nonpermeabilized, unstimulated platelets, incubated with anti-GMP-140 antibodies, and then with IgG-gold probes, showed very little label for GMP-140 along their plasma membranes. In contrast, thrombin-stimulated platelets exhibited at least a 50-fold increase in the amount of label along the plasma membrane. On frozen thin sections of unstimulated platelets we observed immunogold label along the alpha-granule membranes. We also employed the more sensitive technique of permeabilizing with saponin unstimulated platelets in suspension, and then incubating the cells with polyclonal anti-GMP-140 antibodies and Fab-peroxidase conjugate. Alpha-granule membranes showed heavy reaction product, but no other intracellular organelles were specifically labeled. These results demonstrate that GMP-140 is an alpha-granule membrane protein that is expressed on the platelet plasma membrane during degranulation

Geographic variation and evolutionary history of Dipodomys nitratoides (Rodentia: Heteromyidae), a species in severe decline

We examined geographic patterns of diversification in the highly impacted San Joaquin kangaroo rat, Dipodomys nitratoides, throughout its range in the San Joaquin Valley and adjacent basins in central California. The currently recognized subspecies were distinct by the original set of mensural and color variables used in their formal diagnoses, although the Fresno kangaroo rat (D. n. exilis) is the most strongly differentiated with sharp steps in character clines relative to the adjacent Tipton (D. n. nitratoides) and short-nosed (D. n. brevinasus) races. The latter two grade more smoothly into one another but still exhibit independent, and different, character clines within themselves. At the molecular level, as delineated by mtDNA cytochrome b sequences, most population samples retain high levels of diversity despite significant retraction in the species range and severe fragmentation of local populations in recent decades due primarily to landscape conversion for agriculture and secondarily to increased urbanization. Haplotype apportionment bears no relationship to morphologically defined subspecies boundaries. Rather, a haplotype network is shallow, most haplotypes are single-step variants, and the time to coalescence is substantially more recent than the time of species split between D. nitratoides and its sister taxon, D. merriami. The biogeographic history of the species within the San Joaquin Valley appears tied to mid-late Pleistocene expansion following significant drying of the valley resulting from the rain shadow produced by uplift of the Central Coastal Ranges

Identifying Significant Features in Cancer Methylation Data Using Gene Pathway Segmentation

In order to provide the most effective therapy for cancer, it is important to be able to diagnose whether a patient's cancer will respond to a proposed treatment. Methylation profiling could contain information from which such predictions could be made. Currently, hypothesis testing is used to determine whether possible biomarkers for cancer progression produce statistically significant results. However, this approach requires the identification of individual genes, or sets of genes, as candidate hypotheses, and with the increasing size of modern microarrays, this task is becoming progressively harder. Exhaustive testing of small sets of genes is computationally infeasible, and so hypothesis generation depends either on the use of established biological knowledge or on heuristic methods. As an alternative machine learning, methods can be used to identify groups of genes that are acting together within sets of cancer data and associate their behaviors with cancer progression. These methods have the advantage of being multivariate and unbiased but unfortunately also rapidly become computationally infeasible as the number of gene probes and datasets increases. To address this problem, we have investigated a way of utilizing prior knowledge to segment microarray datasets in such a way that machine learning can be used to identify candidate sets of genes for hypothesis testing. A methylation dataset is divided into subsets, where each subset contains only the probes that relate to a known gene pathway. Each of these pathway subsets is used independently for classification. The classification method is AdaBoost with decision trees as weak classifiers. Since each pathway subset contains a relatively small number of gene probes, it is possible to train and test its classification accuracy quickly and determine whether it has valuable diagnostic information. Finally, genes from successful pathway subsets can be combined to create a classifier of high accuracy

Effect of exercise-induced arterial hypoxemia on quadriceps muscle fatigue in healthy humans

The effect of exercise-induced arterial hypoxemia (EIAH) on quadriceps muscle fatigue was assessed in 11 male endurance-trained subjects [peak O2 uptake (V̇o2 peak) = 56.4 ± 2.8 ml·kg−1·min−1; mean ± SE]. Subjects exercised on a cycle ergometer at ≥90% V̇o2 peak to exhaustion (13.2 ± 0.8 min), during which time arterial O2 saturation (SaO2) fell from 97.7 ± 0.1% at rest to 91.9 ± 0.9% (range 84–94%) at end exercise, primarily because of changes in blood pH (7.183 ± 0.017) and body temperature (38.9 ± 0.2°C). On a separate occasion, subjects repeated the exercise, for the same duration and at the same power output as before, but breathed gas mixtures [inspired O2 fraction (FiO2) = 0.25–0.31] that prevented EIAH (SaO2 = 97–99%). Quadriceps muscle fatigue was assessed via supramaximal paired magnetic stimuli of the femoral nerve (1–100 Hz). Immediately after exercise at FiO2 0.21, the mean force response across 1–100 Hz decreased 33 ± 5% compared with only 15 ± 5% when EIAH was prevented (P < 0.05). In a subgroup of four less fit subjects, who showed minimal EIAH at FiO2 0.21 (SaO2 = 95.3 ± 0.7%), the decrease in evoked force was exacerbated by 35% (P < 0.05) in response to further desaturation induced via FiO2 0.17 (SaO2 = 87.8 ± 0.5%) for the same duration and intensity of exercise. We conclude that the arterial O2 desaturation that occurs in fit subjects during high-intensity exercise in normoxia (−6 ± 1% ΔSaO2 from rest) contributes significantly toward quadriceps muscle fatigue via a peripheral mechanism

Degradation of connective tissue matrices by macrophages. III. Morphological and biochemical studies on extracellular, pericellular, and intracellular events in matrix proteolysis by macrophages in culture.

We have shown that macrophages in culture degrade the glycoproteins and amorphous elastin of insoluble extracellular matrices. Ultrastructural observation of the macrophage-matrix interaction revealed that connective tissue macromolecules were solubilized from the matrix extracellularly. At least part of the matrix breakdown was localized to the immediate vicinity of the cells, as shown by morphological and biochemical studies, although the rate of degradation correlated closely with the secretion of proteinases by various inflammatory stimuli in vivo, by glucocorticoids, prostaglandin E2 or colchicine, or by phagocytosis of latex, zymosan, or cholesterol-albumin complexes in culture was reflected in altered rates of glycoprotein and elastin degradation by the macrophages. Alteration of endocytosis and lysosomal digestion by cytochalasin B, NH4Cl, and proteinase inhibitors did not decrease the overall rate of matrix solubilization, but reduced the processing of the matrix fragments to peptides. Therefore, extracellular, pericellular, and lysosomal events each contribute to degradation of extracellular matrix macromolecules by inflammatory macrophages