Modelling the carbonization process to develop a cost-effective, smokeless, continuous, down-draft rice husk carbonizer suitable for rice growing regions

This work discusses modeling of the operational processes occurring in a small-scale, down-draft, continuous rice husk (40 kg h-1) carbonizer suitable for application in poor rice growing regions. The model was used as a tool to optimize the performance of a constructed carbonizer using material and heat balances. The carbonizer technology operating principles are discussed in terms of four operational “zones” and the possible reactions occurring in each zone. The material balance model was used to determine the amounts of each participating material at each zone, and the energy balance was generated using the material balance solutions. The final output of the model for O2, CO, and CO2 was reconciled with testing performance of the constructed carbonizer. The results suggested that 99.2% (weight basis) of the total CO produced during carbonization was burnt at the ignition chamber zone, resulting in only 0.8% CO emission from the chimney. The energy balance determined there was a high potential for the carbonizer to produce useful heat, for rice farm activities, with flue gasses calculated at 724oC. The material and heat balance models were successfully verified by prototype testing

Identification of a common HLA-DP4-restricted T-cell epitope in the conserved region of the respiratory syncytial virus G protein

The cellular immune response to respiratory syncytial virus (RSV) is important in both protection and immunopathogenesis. In contrast to HLA class I, HLA class II-restricted RSV-specific T-cell epitopes have not been identified. Here, we describe the generation and characterization of two human RSV-specific CD4(+)-T-cell clones (TCCs) associated with type 0-like cytokine profiles. TCC 1 was specific for the matrix protein and restricted over HLA-DPB1*1601, while TCC 2 was specific for the attachment protein G and restricted over either HLA-DPB1*0401 or -0402. Interestingly, the latter epitope is conserved in both RSV type A and B viruses. Given the high allele frequencies of HLA-DPB1*0401 and -0402 worldwide, this epitope could be widely recognized and boosted by recurrent RSV infections. Indeed, peptide stimulation of peripheral blood mononuclear cells from healthy adults resulted in the detection of specific responses in 8 of 13 donors. Additional G-specific TCCs were generated from three of these cultures, which recognized the identical (n = 2) or almost identical (n = 1) HLA-DP4-restricted epitope as TCC 2. No significant differences were found between the capacities of cell lines obtained from infants with severe (n = 41) or mild (n = 46) RSV lower respiratory tract infections to function as antigen-presenting cells to the G-specific TCCs, suggesting that the severity of RSV disease is not linked to the allelic frequency of HLA-DP4. In conclusion, we have identified an RSV G-specific human T helper cell epitope restricted by the widely expressed HLA class II alleles DPB1*0401 and -0402. Its putative role in protection and/or immunopathogenesis remains to be determined

Scale invariant scalar metric fluctuations during inflation: non-perturbative formalism from a 5D vacuum

We extend to 5D an approach of a 4D non-perturbative formalism to study scalar metric fluctuations of a 5D Riemann-flat de Sitter background metric. In contrast with the results obtained in 4D, the spectrum of cosmological scalar metric fluctuations during inflation can be scale invariant and the background inflaton field can take sub-Planckian values.Comment: final version to be published in Eur. Phys. J.

Ferrets as a novel animal model for studying human respiratory syncytial virus infections in immunocompetent and immunocompromised hosts

Human respiratory syncytial virus (HRSV) is an important cause of severe respiratory tract disease in immunocompromised patients. Animal models are indispensable for evaluating novel intervention strategies in this complex patient population. To complement existing models in rodents and non-human primates, we have evaluated the potential benefits of an HRSV infection model in ferrets (Mustela putorius furo). Nine- to 12-month-old HRSV-seronegative immunocompetent or immunocompromised ferrets were infected with a low-passage wild-type strain of HRSV subgroup A (105 TCID50) administered by intra-tracheal or intra-nasal inoculation. Immune suppression was achieved by bi-daily oral administration of tacrolimus, mycophenolate mofetil, and prednisolone. Throat and nose swabs were collected daily and animals were euthanized four, seven, or 21 days post-infection (DPI). Virus loads were determined by quantitative virus culture and qPCR. We observed efficient HRSV replication in both the upper and lower respiratory tract. In immunocompromised ferrets, virus loads reached higher levels and showed delayed clearance as compared to those in immunocompetent animals. Histopathological evaluation of animals euthanized 4 DPI demonstrated that the virus replicated in the respiratory epithelial cells of the trachea, bronchi, and bronchioles. These animal models can contribute to an assessment of the efficacy and safety of novel HRSV intervention strategies

Geodesic motion in the neighbourhood of submanifolds embedded in warped product spaces

We study the classical geodesic motions of nonzero rest mass test particles and photons in (3+1+n)- dimensional warped product spaces. An important feature of these spaces is that they allow a natural decoupling between the motions in the (3+1)-dimensional spacetime and those in the extra n dimensions. Using this decoupling and employing phase space analysis we investigate the conditions for confinement of particles and photons to the (3+1)- spacetime submanifold. In addition to providing information regarding the motion of photons, we also show that these motions are not constrained by the value of the extrinsic curvature. We obtain the general conditions for the confinement of geodesics in the case of pseudo-Riemannian manifolds as well as establishing the conditions for the stability of such confinement. These results also generalise a recent result of the authors concerning the embeddings of hypersurfaces with codimension one.Comment: 8 pages, 1 figure. To appear in General Relativity and Gravitation as a contributed paper to Mashhoon Festschrif

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations