Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Concept of optimum basin thickness in heat exchanger–assisted solar stills

Environmental Science and Pollution Research - It is suggested by many works on solar stills that water thickness should be kept as low as possible to reduce its thermal inertia and obtain best...     

Inventory of emissions from major air pollutant categories in Turkey

In this study, an inventory of air pollutant emission estimates from major air polluting sources in Turkey for period between 1985 and 2005 with 5-year intervals were estimated. Inventory covers anthropogenic sources of five major air pollutants of particulate matter, sulfur dioxide, carbon monoxide, nitrogen oxides and non-methane volatile organic compounds. Their break-down with respect to main activity sectors were shown and their distribution by the largest industrial source categories were worked out as annual estimates. This inventory and its analysis point to serious environmental implications of air pollutants and a need to develop a policy plan for reducing these emissions.     

Prevalence of Norovirus Infection in Children and Adults with Acute Gastroenteritis,Tehran, Iran, 2008–2009

Noroviruses are one of important agents that cause acute viral gastroenteritis worldwide. These viruses are belonging to Caliciviridae family and are genetically diverse. To date, there is no valuable data about prevalence of norovirus infection and the dominant genogroup/genotype among Iranian population. The objective of this study was to determine the frequency of norovirus infection in Iranian patients with gastroenteritis referred to three hospitals of Tehran and to specify the dominant genogroup/genotype of this virus among our study population. A total of 293 patients with acute gastroenteritis were included in the study. Detection of norovirus was performed using RT-PCR method and confirmed by direct sequencing with specific designed primers for capsid region of norovirus genome. Phylogenetic analysis was performed using the neighbor-joining method. Norovirus strains identified in our study were subsequently categorized according to previously defined genogroup/genotypes. Of these, norovirus GII was dominant genogroup. Sixty-five percent (17 of 26) of positive samples were determined as GII and 35% (9 of 26) were determined as GI, respectively, in 2008–2009. And among 8 sequenced strains of genogroup II the most frequent genotype was GII.3. The results of this study indicated that norovirus must be considered as one of the infectious causes of acute gastroenteritis among Iranian population. We also found that GII.3 is more prevalent in our study population. To the best of our knowledge there is limited data about the role of noroviruses in children and adults’ acute gastroenteritis among Iranian patients and this prevalence and genotyping report of norovirus infection could be remarkable for further studies.     

Baselines for land-use change in the tropics: application to avoided deforestation projects

Although forest conservation activities, particularly in the tropics, offer significant potential for mitigating carbon (C) emissions, these types of activities have faced obstacles in the policy arena caused by the difficulty in determining key elements of the project cycle, particularly the baseline. A baseline for forest conservation has two main components: the projected land-use change and the corresponding carbon stocks in applicable pools in vegetation and soil, with land-use change being the most difficult to address analytically. In this paper we focus on developing and comparing three models, ranging from relatively simple extrapolations of past trends in land use based on simple drivers such as population growth to more complex extrapolations of past trends using spatially explicit models of land-use change driven by biophysical and socioeconomic factors. The three models used for making baseline projections of tropical deforestation at the regional scale are: the Forest Area Change (FAC) model, the Land Use and Carbon Sequestration (LUCS) model, and the Geographical Modeling (GEOMOD) model. The models were used to project deforestation in six tropical regions that featured different ecological and socioeconomic conditions, population dynamics, and uses of the land: (1) northern Belize; (2) Santa Cruz State, Bolivia; (3) Paraná State, Brazil; (4) Campeche, Mexico; (5) Chiapas, Mexico; and (6) Michoacán, Mexico. A comparison of all model outputs across all six regions shows that each model produced quite different deforestation baselines. In general, the simplest FAC model, applied at the national administrative-unit scale, projected the highest amount of forest loss (four out of six regions) and the LUCS model the least amount of loss (four out of five regions). Based on simulations of GEOMOD, we found that readily observable physical and biological factors as well as distance to areas of past disturbance were each about twice as important as either sociological/demographic or economic/infrastructure factors (less observable) in explaining empirical land-use patterns. We propose from the lessons learned, a methodology comprised of three main steps and six tasks can be used to begin developing credible baselines. We also propose that the baselines be projected over a 10-year period because, although projections beyond 10 years are feasible, they are likely to be unrealistic for policy purposes. In the first step, an historic land-use change and deforestation estimate is made by determining the analytic domain (size of the region relative to the size of proposed project), obtaining historic data, analyzing candidate baseline drivers, and identifying three to four major drivers. In the second step, a baseline of where deforestation is likely to occur–a potential land-use change (PLUC) map—is produced using a spatial model such as GEOMOD that uses the key drivers from step one. Then rates of deforestation are projected over a 10-year baseline period based on one of the three models. Using the PLUC maps, projected rates of deforestation, and carbon stock estimates, baseline projections are developed that can be used for project GHG accounting and crediting purposes: The final step proposes that, at agreed interval (e.g., about 10 years), the baseline assumptions about baseline drivers be re-assessed. This step reviews the viability of the 10-year baseline in light of changes in one or more key baseline drivers (e.g., new roads, new communities, new protected area, etc.). The potential land-use change map and estimates of rates of deforestation could be re-done at the agreed interval, allowing the deforestation rates and changes in spatial drivers to be incorporated into a defense of the existing baseline, or the derivation of a new baseline projection.     

Prenatal cannibalism in an insect

Host selection and infection strategies of parasitoids often correlate with high parental investment and low numbers of progeny. In this study, we investigate how additional internal mechanisms might shape brood size and fitness of the offspring. Emblemasoma auditrix is a parasitoid fly in which about 38 larvae hatch simultaneously in utero. After host location, a single larva is deposited into the host, where it rapidly develops and pupates after about 5 days. The search for hosts can take several weeks, and during that time, the larvae arrest their development and remain in the first larval instar. Nevertheless, the larvae increase in weight within the uterus, and this growth correlates to a decrease in the number of larvae, although no larvae are deposited. Thus, our data indicate a first case of prenatal cannibalism in an invertebrate with larvae feeding on each other within the uterus of the adult.     

Male satin bowerbirds (<Emphasis Type="Italic">Ptilonorhynchus violaceus</Emphasis>) compensate for sexual signal loss by enhancing multiple display features

Numerous studies have focussed on the relationship between female choice and the multiple exaggerated sexual traits of males. However, little is known about the ability of males to actively enhance specific components of their display in response to the loss of one component. We investigated the capacity of male satin bowerbirds (Ptilonorhynchus violaceus) to respond to the loss of one of their sexual signals by performing an experiment in which we removed decorations at their bowers. We found that males compensated for decoration loss by increasing bower construction behaviour and decreasing their latency to bower painting. These results are novel because they suggest that males can assess the quality of their own display and make decisions about how to augment their displays. We discuss these results in the context of previous studies of mate choice in satin bowerbirds, as both of the supplementary behaviours we observed are known correlates of male mating success.     

Studies on the use of power ultrasound in solid–liquid myrobalan extraction process

Focus on eco-friendly processing techniques makes vegetable tanning a viable option in leather processing and establishes the subsequent need for the more efficient methods of extraction in tannin manufacture. Application of ultrasound has been tried in the extraction of tannins from myrobalan nuts in order to improve the extraction efficiency, to perform the extraction under milder process conditions and to reduce the process time. The influence of process parameters such as ultrasonic output power, time and temperature has been studied. Scale-up trials and the use of ultrasound in pulse mode have also been attempted. The results show that a three- to fivefold improvement is possible with ultrasonic output from 20 to 100 W. Extraction efficiency has been calculated from the maximum extractable materials from myrobalan nuts. Extraction efficiency is found to be 90% for ultrasound, 100 W without external heating as compared to 77% for control process at 70 °C for 4 h. Therefore, ultrasound could be employed even dispensing with provision for temperature controls. The use of ultrasound in pulse mode offered 70% extraction efficiency of continuous mode. Scale-up trials indicate that there exists an optimum ultrasonic output power depending on the amount of nuts used, to achieve better extraction efficiency. The effectiveness of ultrasonically extracted tannin solution has also been tested in the tanning process for its applicability. The degree of tanning efficacy has been assessed by shrinkage temperature measurement. The results indicate that ultrasonically extracted tannin solution is suitable for tanning process. Therefore, application of ultrasound in tannin extract manufacture is a viable option with added advantages.