Development of a Hydrous Ethanol Fuel Feeding Device for Spark-Ignition Engine

While the Philippine Biofuels Act of 2006 mandates the use of anhydrous bioethanol as blend for gasoline, the potential of hydrous ethanol as an alternative fuel for spark-ignition engines has not been fully realized. This study explored the possibility of using hydrous ethanol as fuel for spark-ignition engines with minimal modifications and without the need for gasoline blend. A fuel feeding device was developed to feed hydrous ethanol fuel into the intake manifold of the engine, bypassing the carburetor. By replacing the components that are not compatible with hydrous ethanol and installing a fuel feeding device developed at PhilRice, two spark-ignition engines were able to run solely on 80-95% hydrous ethanol fuel. The fuel economy was found to be a significant issue in the utilization of hydrous ethanol fuel as there is a 75% increase in fuel consumption when using hydrous ethanol. There is potential for hydrous ethanol to be used as fuel if it can be produced locally and sold at half the pump price of gasoline

Rice Straw Geotextile As Ground Cover ForSoil Erosion Mitigation

Generally, the study aimed to mitigate soil erosion using rice straw geotextile as ground cover. Specifically, it attempted to: evaluate the effect of RSM and RSN as ground cover in mitigating soil erosion at varying slope gradients and different rainfall intensities, and; determine the relationship of slope gradient versus sediment concentration, sediment yield and quantity of soil loss at different levels of rainfall intensity. Results revealed that RSGT as ground cover greatly affected soil erosion. Under rainfall intensities of 75, 100 and 125 mm/hr, RSM had significantly lower soil loss as compared to RSN, CCN And NGC. However, RSN and CCN were comparable with each other but differ significantly with NGC.  Sediment concentration, sediment yield and soil erosion exhibited a nonlinear relationship with slope gradient. At any given level of rainfall intensity, the three indicators increased correspondingly as the slope was increased from 10 to 35o and then  declined when  the slope was further  increased from 35 to 60o. Sediment concentration best fitted (R2 = 0.977) in a quadratic model in the form of a second-degree polynomial equation: SC = 0.551 + 0.626S - 0.008S2 Likewise, observed sediment yield best fitted (R2 = 0.954) a second degree polynomial equation as expressed by a quadratic model: SY = 356.0 + 61.70S – 0.972S2 Moreover, the observed soil erosion was best modeled with R2 = 97.1% confidence by a second degree polynomial equation. The regression model is quadratic in form and is given by the equation: SE = 68.92 + 11.11S - 0.174S2. Keywords: rice straw, geotextile, ground cover, soil erosion, mitigation, rainfall simulatio

The economy on a cusp: The proposed VAT amendments and their larger significande

Debates on the revision of the value-added tax (VAT) are about to reach the penultimate stage. Once house and senate have passed their respective versions of the bill, congress - through a bicameral conference committee sometimes referred to as the 'third chamber' - must then agree on the final form of the law. After all the media-posturing, the politicking, and horse-trading have subsided, politicians of both chambers are still left to confront the nation's true interests - and their own consciences. It is vital that they finally pass a law that is right in form and adequate to the economy's needs

Population, poverty, politics and the reproductive health bill

Following an earlier paper titled 'Population and Poverty: The Real Score' (UPSE Discussion Paper 0415, December 2004), the present paper was first issued in August 2008 as a contribution to the public debate on the population issue that never seemed to die in this country. The debate heated up about that time in reaction to a revival of moves to push for legislation on reproductive health and family planning (RH/FP). Those attempts at legislation, however, failed in the 13th Congress, and again in the 14th Congress. Since late last year, the debate has been heating up further on the heels of President Noy Aquino's pronouncements seeming to favor RH/FP, though he prefers the nomenclature 'responsible parenthood'. With some updating of the data, this paper remains as relevant as ever to the ongoing public debate. It is being re-issued as a Discussion Paper for wider circulation

Cross-Sectional Dating of Novel Haplotypes of HERV-K 113 and HERV-K 115 Indicate These Proviruses Originated in Africa before Homo sapiens

The human genome, human endogenous retroviruses (HERV), of which HERV-K113 and HERV-K115 are the only known full-length proviruses that are insertionally polymorphic. Although a handful of previously published papers have documented their prevalence in the global population; to date, there has been no report on their prevalence in the United States population. Here, we studied the geographic distribution of K113 and K115 among 156 HIV-1+ subjects from the United States, including African Americans, Hispanics, and Caucasians. In the individuals studied, we found higher insertion frequencies of K113 (21%) and K115 (35%) in African Americans compared with Caucasians (K113 9% and K115 6%) within the United States. We also report the presence of three single nucleotide polymorphism sites in the K113 5′ long terminal repeats (LTRs) and four in the K115 5′ LTR that together constituted four haplotypes for K113 and five haplotypes for K115. HERV insertion times can be estimated from the sequence differences between the 5′ and 3′ LTR of each insertion, but this dating method cannot be used with HERV-K115. We developed a method to estimate insertion times by applying coalescent inference to 5′ LTR sequences within our study population and validated this approach using an independent estimate derived from the genetic distance between K113 5′ and 3′ LTR sequences. Using our method, we estimated the insertion dates of K113 and K115 to be a minimum of 800,000 and 1.1 million years ago, respectively. Both these insertion dates predate the emergence of anatomically modern Homo sapiens

Blue Noise Plots

We propose Blue Noise Plots, two-dimensional dot plots that depict data points of univariate data sets. While often one-dimensional strip plots are used to depict such data, one of their main problems is visual clutter which results from overlap. To reduce this overlap, jitter plots were introduced, whereby an additional, non-encoding plot dimension is introduced, along which the data point representing dots are randomly perturbed. Unfortunately, this randomness can suggest non-existent clusters, and often leads to visually unappealing plots, in which overlap might still occur. To overcome these shortcomings, we introduce BlueNoise Plots where random jitter along the non-encoding plot dimension is replaced by optimizing all dots to keep a minimum distance in 2D i. e., Blue Noise. We evaluate the effectiveness as well as the aesthetics of Blue Noise Plots through both, a quantitative and a qualitative user study. The Python implementation of Blue Noise Plots is available here.Comment: 9 pages, 16 figure

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)