Expression and functional characterization of odorant-binding protein 2 in the predatory mite Neoseiulus barkeri.

Olfaction plays a crucial role for arthropods in foraging, mating, and oviposition. The odorant-binding protein (OBP) gene is considered one of the most important olfactory genes. However, little is known about its functions in predatory mites. Here, we used Neoseiulus barkeri, an important commercialized natural pest control, to explore the chemosensory characteristics of OBP. In this study, N. barkeri was attracted by methyl salicylate (MeSA) and showed higher crawling speeds under MeSA treatment. Then, we identified and cloned an OBP gene named Nbarobp2 and analyzed its expression profiles in the predatory mite. Nbarobp2 was 663 bp, was highly expressed in larval and nymphal stages, and was significantly upregulated in N. barkeri under MeSA treatment. Nbarobp2 encoded 202 amino acid residues with a molecular weight of 23 kDa (after removing the signal peptide). Sequence comparisons revealed that the OBPs in Arachnida shared 6 conserved cysteine sites, but were distinguishable from the OBPs of Insecta on the phylogenetic tree. RNA interference, Western blotting, and binding affinity assays further proved that Nbarobp2 was involved in volatile perception in predatory mites. This study shed light on the functional characteristics of OBPs in predatory mites, providing a new insight for better biological control.

Measurement of Personal Experienced Temperature Variations in Rural Households Using Wearable Monitors: A Pilot Study.

The time-varying data of air temperatures experienced by people in their daily lives is an important basis for studying human thermal sensation, adaptation, comfort, and health. It is also very important for designing targeted strategies to help people reduce uncomfortable experience. In this study, a small (98 mm × 49 mm × 25 mm), lightweight (~100 g), and portable temperature logger with a wide measurement range (-40 to 100 °C) and appropriate accuracy (±0.3 °C precision) was combined with a phone holder that was adapted as an armband sleeve to constitute a wearable monitor. Fourteen monitors were worn by 14 residents in 6 different households in rural Beijing, China, to monitor their personal thermal environment. In the context of having very similar living habits in winter and coping strategies for thermal discomfort, the temperatures that 14 residents experienced exhibited wide ranges and large variations during the two-day test period. The highest and lowest temperatures experienced by residents reached 30.6 and -16.6 °C, respectively. This paper provided new data and evidences about various temperatures experienced by residents, even though they were from the same family and lived together for decades. In terms of methodology, as an exploration, the present study indicated that using personal wearable monitors is a viable method to capture the real experienced thermal environment, which extended the method for collecting data regarding complex experiences in different environments to aid the study of human responses to the real-world thermal environment.

Air pollutant emission factors of solid fuel stoves and estimated emission amounts in rural Beijing.

Solid fuels used for heating and cooking in rural households cause a large amount of pollutant emissions. Actions are being taken to replace these solid fuels with cleaner energy carriers. However, the pollutant emission amounts from solid fuels over large areas have rarely been evaluated. In this study, we tested eight common heating stoves consuming bituminous coal chunk, anthracite coal chunk, and anthracite coal briquette; three honeycomb briquette stoves; and three traditional cookstoves consuming corn straw and wood in rural Beijing. Emission factors of particulate matter with aerodynamic diameters ≤2.5 µm (PM2.5), carbon monoxide (CO), nitrogen oxide (NOx), and sulfur dioxide (SO2), were measured as 0.08-13.74 g/kg, 10.80-148.5 g/kg, 0.52-8.44 g/kg, and 0-0.85 g/kg, respectively, for coal heating stoves; 0.35-1.11 g/kg, 16.10-109.43 g/kg, 0.51-0.75 g/kg, and 0-1.98 g/kg, respectively, for honeycomb briquette cookstoves; and 5.90-11.79 g/kg, 28.96-50.23 g/kg, 1.52-2.46 g/kg, and 0-0.05 g/kg, respectively, for traditional biomass cookstoves. Combining emission performance and solid fuel consumption, the estimated annual PM2.5, CO, NOx, and SO2 emission amounts were 26.18 Gg, 394.07 Gg, 14.56 Gg, and 1.53 Gg, respectively. The results present useful information regarding the emission inventory of common solid fuels in rural Beijing on a city-scale. This study provides an example for future intervention projects and environment evaluation in the rural areas of other cities.

Advanced household heat pumps for air pollution control: A pilot field study in Ulaanbaatar, the coldest capital city in the world.

Ulaanbaatar - the coldest capital in the world - is home to half of Mongolia's population, much of which uses coal for household heating, contributing to high wintertime air pollution. We piloted two-stage air-to-air heat pumps in 2017, when temperatures dropped to -39 °C. These heat pumps were reliable and efficient, with an average coefficient of performance of 1.86 on the coldest days. Heat pumps' recurrent costs were similar to those of coal stoves and lower than those of resistive heaters.

Application of particle swarm optimization algorithm in the heating system planning problem.

Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem.