Objective and subjective measurements of slipperiness in fast-food restaurants in the USA and their comparison with the previous results obtained in Taiwan

Floor slipperiness is a critical issue in slip and fall incidents which are a major source of occupational injuries. The objectives of the current study were to investigate if the protocols used in a field study conducted in Taiwan could be used in similar environments in the USA and whether consistent results could be obtained. Protocols used in the field study to investigate floor slipperiness in western-style fast-food restaurants in Taiwan included both objective and subjective measurements. Using the same methods as in Taiwan, friction was measured on tiles in six major working areas of 10 fast-food kitchens in the USA as an objective measurement of slipperiness, while the subjective measurement was employees’ ratings of floor slipperiness over the same areas. The Pearson’s and Spearman’s correlation coefficients in the USA between the averaged friction coefficients and subjective ratings for all 60 evaluated areas across 10 restaurants were 0.33 (p = 0.01) and 0.36 (p = 0.005), respectively, which were lower than the correlations of 0.49 and 0.45, respectively, obtained in Taiwan. Cultural differences, the amount of water on the floors in the sink areas and the existence of a slip resistant shoe program in one country might be contributors to the lower correlation coefficients in the USA. However, the current study confirmed the results obtained in Taiwan that average friction coefficient and perception values are in fair agreement, suggesting that both might be reasonably good indicators of slipperiness.     

Incentives to diffuse advanced abatement technology under environmental liability law

Polluting firms with advanced abatement technology at their disposal have incentives or disincentives to share this technology with other polluting firms. The ‘direction’ and extent of those incentives depends on the liability rule applicable and the way technical change impacts marginal abatement costs. We establish that incentives for diffusion are socially optimal under strict liability and socially suboptimal under negligence if technical change lowers marginal abatement costs for all levels of abatement. Negligence may, however, induce better diffusion incentives than strict liability if technical change decreases (increases) marginal abatement costs for low (high) levels of abatement.     

Stochastic landslide vulnerability modeling in space and time in a part of the northern Himalayas, India

Little is known about the quantitative vulnerability analysis to landslides as not many attempts have been made to assess it comprehensively. This study assesses the spatio-temporal vulnerability of elements at risk to landslides in a stochastic framework. The study includes buildings, persons inside buildings, and traffic as elements at risk to landslides. Building vulnerability is the expected damage and depends on the position of a building with respect to the landslide hazard at a given time. Population and vehicle vulnerability are the expected death toll in a building and vehicle damage in space and time respectively. The study was carried out in a road corridor in the Indian Himalayas that is highly susceptible to landslides. Results showed that 26% of the buildings fall in the high and very high vulnerability categories. Population vulnerability inside buildings showed a value >0.75 during 0800 to 1000 hours and 1600 to 1800 hours in more buildings that other times of the day. It was also observed in the study region that the vulnerability of vehicle is above 0.6 in half of the road stretches during 0800 hours to 1000 hours and 1600 to 1800 hours due to high traffic density on the road section. From this study, we conclude that the vulnerability of an element at risk to landslide is a space and time event, and can be quantified using stochastic modeling. Therefore, the stochastic vulnerability modeling forms the basis for a quantitative landslide risk analysis and assessment.     

Impacts of bioethanol on gasoline prices in the Philippines: an econometric analysis

The rising prices of crude oil in the world market and the continuing global trend to mainstream renewable energy use have prompted the Philippines to consider alternative fuels. Since 2006 when a new law was implemented requiring a 10 % blend to unleaded gasoline, the use of ethanol has increased significantly. Sugarcane (Saccharum spp.), cassava (Manihot esculenta ) and sweet potato (Ipomoea batatas) have been the major feedstock in ethanol production. This analysis focused on the impacts of E10 (10 % ethanol content) on the retail price of gasoline and how this might affect gasoline prices. Recognizing the direct dependence of the price of E10 on gasoline prices, the analysis focused on analyzing the price of ethanol. The hypothesis is that since ethanol is what makes E10 cheaper than gas given the lower cost of its production i.e., domestically grown raw materials, then cheaper ethanol should depress the price of E10 and therefore gas, ceteris paribus. The price of E10 is endogenous since it is a function of the price of gasoline, being a major input to its production, 90 % in fact. Using fixed-effects, 2007–2009 provincial panel data, from second stage least squares econometric estimation, the impact of ethanol use on retail regular gasoline prices is quantified. The partial effect analysis indicates that a 1-peso (rate: 1USD - PhP 41.96) increase in the price of feedstock prices as inputs to the production of E10 increases the price of gasoline by 37 centavos per liter. The analysis shows the positive relationship between the prices of E10 and gasoline.     

生物炭负载氮还田对水稻生长、根系形态及氮素利用的影响

建立连接富营养化水体养分与农田养分的枢纽是减少农田养分投入、缓解水体富营养化的难点.为探明生物炭材料负载氮还田的可行性,开展了基于溶液氮及生物炭负载氮两种氮源添加方式的水稻根箱试验.结果表明,生物炭负载氮添加方式分别较溶液氮添加方式降低了水稻地上部分生物量及氮累积16%及14%,提高了生物量根冠比25%～27%,降低了氮利用效率.不定根的根长及体积是两种氮源添加方式在水稻地下部分差异的体现,地下部分生物量及氮累积与土壤铵态氮含量呈正相关关系,而地上部分氮累积与根尖数呈负相关关系.生物炭负载氮完全替代化学肥料施用农田会影响水稻生物量及氮素利用.但生物炭负载氮与普通化学肥料共同施用,水稻并不会显现利用偏好.生物炭负载氮对水稻氮素利用无不良影响,且能有效提高土壤矿质态氮固持量.因此,生物炭可以作为载体实现水体到农田土壤的氮素迁移,鉴于化肥氮替代比例对作物生长的影响,适宜替代比例还需进一步研究确定.     

Circulation and Stream Plume Modeling in Conesus Lake

A three-dimensional hydrodynamic model that includes the effect of drag from macrophytes was applied to Conesus Lake to study the seasonal circulation and thermal structure during spring and early summer. Local weather conditions and stream flow data were used to drive the model. The drag coefficient for macrophytes was calculated as a function of leaf density. In general, the model results show good agreements with the observations, including vertical temperature profiles measured at two locations and average surface temperature derived from calibrated thermal imagery for large-scale simulations of the entire lake. Additional high-resolution simulations were carried out to understand water circulation and transport of sediment and model-generated tracer during hydrometeorological events at stream mouths for two experimental sites. The model results show that the plume development at stream mouths during storm events in Conesus Lake are site-dependent and may either be current- or wind-driven. The results also show a significant effect from the presence of macrophytes on sediment deposition near stream mouths.     

Estimation of transport and degradation parameters for naphthalene and anthracene: influence of mass transfer on kinetics

The distributions of culturable bacteria and functional bacteria associated with nitrogen (N) or phosphorus (P) in the backwater areas of the Three Gorges Reservoir (TGR) were investigated. Results from seven locations in the TGR indicated that the abundance of total bacteria was high, with 8.12 × 10⁶, 2.70 × 10⁷, and 6.73 × 10¹⁰ colony-forming units per milliliter or per gram dry weight in surface water, bottom water, and sediments, respectively. Aquatic environments with higher nutrient loadings possessed higher bacteria densities and lower bacteria community diversities. Eight kinds of functional bacteria ratios, including surface water to bottom water and ratios of water to sediments, were calculated, in which four kinds of functional bacteria, namely, nitrogen-fixing bacteria, ammonia-oxidizing bacteria, nitrite-oxidizing bacteria, and organophosphate-solubilizing bacteria, displayed obvious differences in different locations. Based on the functional bacteria ratios of water to sediments, it was found that the obtained result of location grouping from cluster analysis was similar to that based on the community-level physiological profiles studies. The above results showed that the ratios of functional bacteria could distinguish the aquatic environments with different trophic conditions in the TGR. This demonstrated that the distribution ratios of functional bacteria in aquatic environments could work as potential bioindicators to reflect the trophic condition of the water.     

Artificial intelligence in obstetric ultrasound: A scoping review

The objective is to summarize the current use of artificial intelligence (AI) in obstetric ultrasound. PubMed, Cochrane Library, and ClinicalTrials.gov databases were searched using the following keywords “neural networks”, OR “artificial intelligence”, OR “machine learning”, OR “deep learning”, AND “obstetrics”, OR “obstetrical”, OR “fetus”, OR “foetus”, OR “fetal”, OR “foetal”, OR “pregnancy”, or “pregnant”, AND “ultrasound” from inception through May 2022. The search was limited to the English language. Studies were eligible for inclusion if they described the use of AI in obstetric ultrasound. Obstetric ultrasound was defined as the process of obtaining ultrasound images of a fetus, amniotic fluid, or placenta. AI was defined as the use of neural networks, machine learning, or deep learning methods. The authors’ search identified a total of 127 papers that fulfilled our inclusion criteria. The current uses of AI in obstetric ultrasound include first trimester pregnancy ultrasound, assessment of placenta, fetal biometry, fetal echocardiography, fetal neurosonography, assessment of fetal anatomy, and other uses including assessment of fetal lung maturity and screening for risk of adverse pregnancy outcomes. AI holds the potential to improve the ultrasound efficiency, pregnancy outcomes in low resource settings, detection of congenital malformations and prediction of adverse pregnancy outcomes.