Statistical modelling for precision agriculture: A case study in optimal environmental schedules for Agaricus Bisporus production via variable domain functional regression

Quantifying the effects of environmental factors over the duration of the growing process on Agaricus Bisporus (button mushroom) yields has been difficult, as common functional data analysis approaches require fixed length functional data. The data available from commercial growers, however, is of variable duration, due to commercial considerations. We employ a recently proposed regression technique termed Variable-Domain Functional Regression in order to be able to accommodate these irregular-length datasets. In this way, we are able to quantify the contribution of covariates such as temperature, humidity and water spraying volumes across the growing process, and for different lengths of growing processes. Our results indicate that optimal oxygen and temperature levels vary across the growing cycle and we propose environmental schedules for these covariates to optimise overall yields

Yield anisotropy effects on buckling of circular tubes under bending

AbstractRelatively thin-walled tubes bent into the plastic range buckle by axial wrinkling. The wrinkles initially grow stably but eventually localize and cause catastrophic failure in the form of sharp local kinking. The onset of axial wrinkling was previously established by bifurcation analyses that use instantaneous deformation theory moduli. The curvatures at bifurcation were predicted accurately, but the wrinkle wavelengths were consistently longer than measured values. The subject is revisited with the aim of resolving this discrepancy. A set of new bending experiments is conducted on aluminum alloy tubes. The results are shown to be in line with previous ones. However, the tubes used were found to exhibit plastic anisotropy, which was measured and characterized through Hill’s quadratic anisotropic yield function. The anisotropy was incorporated in the flow theory used for prebuckling and postbuckling calculations as well as in the deformation theory used for bifurcation checks. With the anisotropy accounted for, calculated tube responses are found to be in excellent agreement with the measured ones while the predicted bifurcation curvatures and wrinkle wavelengths fall in line with the measurements also. The postbuckling response is established using a finite element model of a tube assigned an initial axisymmetric imperfection with the calculated wavelength. The response develops a limit moment that is followed by a sharp kink that grows while the overall moment drops. The curvature at the limit moment agrees well with the experimental onset of failure. From parametric studies of the various instabilities it is concluded that, for optimum predictions, anisotropy must be incorporated in both bifurcation buckling as well as in postbuckling calculations

PMU Placement for Power System Observability Using Binary Particle Swarm Optimization

A binary particle swarm optimization (BPSO) based methodology for the optimal placement of phasor measurement units (PMUs) for complete observability of a power system is presented in this paper. The objectives of the optimization problem are to minimize the total number of PMUs required, and to maximize the measurement redundancy at the power system buses. Simulation results on the IEEE 14-bus and 30-bus test systems are presented in this paper

A correlative study of Quantitative EMG and biopsy findings in 31 patients with myopathies

A direct correlation of QEMG with muscle biopsy findings might help delineate the sensitivity of QEMG in identifying muscle pathology as well as provide information on electrophysiological- histological correlations. In a study of 31 patients with a variety of myopathies we found that the sensitivity of QEMG was between 24 to 69% depending of the specific method of signal analysis. The positive predictive value of abnormal QEMG was more than 90% while its negative predictive value was only about 20%. Amplitude outlier analysis was superior especially in minimally weak muscles (MRC > 4) and was particularly sensitive at detecting increased variability in fiber size and more subtle myopathic changes

Seismic retrofitting and health monitoring of school buildings of Cyprus

The vulnerability of existing buildings to seismic forces and their retrofitting is an international problem. The majority of structures in seismic-prone areas worldwide are structures that have been designed either without the consideration of seismic forces, or with previous codes of practice specifying lower levels of seismic forces. In Cyprus, after the three earthquakes that occurred in 1995, 1996, and 1999, the Cyprus State, acting in a pioneering way internationally, has decided the seismic retrofitting of all school buildings, taking into account the sensitivity of the society towards these structures, which house the future generation of the society. In this paper the overall assessment methodology is presented, along with details of the over 10 year ongoing retrofitting program of the school buildings of Cyprus, with emphasis on the description of the program and the development of a wireless monitoring system. In addition, mathematical models of selected school buildings are presented and comparison is made with in-situ measurement

Genetic background modifies amyloidosis in a mouse model of ATTR neuropathy

AbstractPenetrance and age of onset of ATTRV30M amyloidotic neuropathy varies significantly among different populations. This variability has been attributed to both genetic and environmental modifiers. We studied the effect of genetic background on phenotype in two lines of transgenic mice bearing the same ATTRV30M transgene. Amyloid deposition, transthyretin (TTR), megalin, clusterin and disease markers of endoplasmic reticulum stress, the ubiquitin-proteasome system, apoptosis, and complement activation were assessed with WB and immunohistochemistry in donor and recipient tissue. Our results indicate that genetic background modulates amyloid deposition by influencing TTR handling in recipient tissue and may partly account for the marked variability in penetrance observed in various world populations

Systems Level Metabolic Phenotype of Methotrexate Administration in the Context of Non-alcoholic Steatohepatitis in the Rat.

Adverse drug reactions (ADRs) represent a significant clinical challenge with respect to patient morbidity and mortality. We investigated the hepatotoxicity and systems level metabolic phenotype of methotrexate (MTX) in the context of a prevalent liver disease; non-alcoholic steatohepatitis (NASH). A nuclear magnetic resonance spectroscopic-based metabonomic approach was employed to analyze the metabolic consequences of MTX (0, 10, 40, and 100 mg/kg) in the urine and liver of healthy rats (control diet) and in a model of NASH (methionine-choline deficient diet). Histopathological analysis confirmed baseline (0 mg/kg) liver necrosis, liver inflammation, and lipid accumulation in the NASH model. Administration of MTX (40 and 100 mg/kg) led to liver necrosis in the control cohort, whereas the NASH cohort also displayed biliary hyperplasia and liver fibrosis (100 mg/kg), providing evidence of the synergistic effect of MTX and NASH. The complementary hepatic and urinary metabolic phenotypes of the NASH model, at baseline, revealed perturbation of multiple metabolites associated with oxidative and energetic stress, and folate homeostasis. Administration of MTX in both diet cohorts showed dose-dependent metabolic consequences affecting gut microbial, energy, nucleobase, nucleoside, and folate metabolism. Furthermore, a unique panel of metabolic changes reflective of the synergistic effect of MTX and NASH was identified, including the elevation of hepatic phenylalanine, urocanate, acetate, and both urinary and hepatic formiminoglutamic acid. This systems level metabonomic analysis of the hepatotoxicity of MTX in the context of NASH provided novel mechanistic insight of potential wider clinical relevance for further understanding the role of liver pathology as a risk factor for ADRs

Emission-aware Energy Storage Scheduling for a Greener Grid

Reducing our reliance on carbon-intensive energy sources is vital for reducing the carbon footprint of the electric grid. Although the grid is seeing increasing deployments of clean, renewable sources of energy, a significant portion of the grid demand is still met using traditional carbon-intensive energy sources. In this paper, we study the problem of using energy storage deployed in the grid to reduce the grid's carbon emissions. While energy storage has previously been used for grid optimizations such as peak shaving and smoothing intermittent sources, our insight is to use distributed storage to enable utilities to reduce their reliance on their less efficient and most carbon-intensive power plants and thereby reduce their overall emission footprint. We formulate the problem of emission-aware scheduling of distributed energy storage as an optimization problem, and use a robust optimization approach that is well-suited for handling the uncertainty in load predictions, especially in the presence of intermittent renewables such as solar and wind. We evaluate our approach using a state of the art neural network load forecasting technique and real load traces from a distribution grid with 1,341 homes. Our results show a reduction of >0.5 million kg in annual carbon emissions -- equivalent to a drop of 23.3% in our electric grid emissions.Comment: 11 pages, 7 figure, This paper will appear in the Proceedings of the ACM International Conference on Future Energy Systems (e-Energy 20) June 2020, Australi

Tailoring CD19xCD3-DART exposure enhances T-cells to eradication of B-cell neoplasms.

Many patients with B-cell malignancies can be successfully treated, although tumor eradication is rarely achieved. T-cell-directed killing of tumor cells using engineered T-cells or bispecific antibodies is a promising approach for the treatment of hematologic malignancies. We investigated the efficacy of CD19xCD3 DART bispecific antibody in a broad panel of human primary B-cell malignancies. The CD19xCD3 DART identified 2 distinct subsets of patients, in which the neoplastic lymphocytes were eliminated with rapid or slow kinetics. Delayed responses were always overcome by a prolonged or repeated DART exposure. Both CD4 and CD8 effector cytotoxic cells were generated, and DART-mediated killing of CD4+ cells into cytotoxic effectors required the presence of CD8+ cells. Serial exposures to DART led to the exponential expansion of CD4 + and CD8 + cells and to the sequential ablation of neoplastic cells in absence of a PD-L1-mediated exhaustion. Lastly, patient-derived neoplastic B-cells (B-Acute Lymphoblast Leukemia and Diffuse Large B Cell Lymphoma) could be proficiently eradicated in a xenograft mouse model by DART-armed cytokine induced killer (CIK) cells. Collectively, patient tailored DART exposures can result in the effective elimination of CD19 positive leukemia and B-cell lymphoma and the association of bispecific antibodies with unmatched CIK cells represents an effective modality for the treatment of CD19 positive leukemia/lymphoma