An analysis of neurovascular disease markers in the hippocampus of Tupaia chinensis at different growth stages

IntroductionIt is considered that Tupaia chinensis can replace laboratory primates in the study of nervous system diseases. To date, however, protein expression in the brain of Tupaia chinensis has not been fully understood.MethodThree age groups of T. chinensis-15 days, 3 months and 1.5 years—were selected to study their hippocampal protein expression profiles.ResultsA significant difference was observed between the 15-day group and the other two age groups, where as there were no significant differences between the 3-month and 1.5-year age groups. The Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis found that differentially expressed proteins could be enriched in several pathways related to neurovascular diseases, such as metabolic pathways for Alzheimer's disease (AD), Huntington's disease, Parkinson's disease, and other diseases. The KEGG enrichment also showed that relevant protein involved in oxidative phosphorylation in the hippocampus of T. chinensis for 15days were downregulated, and ribosomal proteins (RPs) were upregulated, compared to those in the hippocampus of the other two age groups.DiscussionIt was suggested that when the hippocampus of T. chinensis developed from day 15 to 3 months, the expression of oxidatively phosphorylated proteins and RPs would vary over time. Meanwhile, the hippocamppal protein expression profile of T. chinensis after 3 months had become stable. Moreover, the study underlines that, during the early development of the hippocampus of T. chinensis, energy demand increases while protein synthesis decreases. The mitochondria of T. chinensis changes with age, and the oxidative phosphorylation metabolic pathway of mitochondria is closely related to neurovascular diseases, such as stroke and cerebral ischemia

Comparison of Droplet Distribution and Control Effect of Wheat Aphids under Different Operation Parameters of the Crop Protection UAV in the Wheat Flowering Stage

Aphid is one of the main insect pests of wheat in the flowering stage, so timely and effective control of wheat aphids plays an important role in ensuring wheat yield. The crop protection Unmanned Aerial Vehicle (UAV) is widely used in the control of wheat pests and diseases nowadays. In order to screen out the suitable operation parameters of the crop protection UAV to control the wheat aphids, this study conducted wheat aphid distribution investigation tests and droplet distribution tests. With the P20 electric four-rotor crop protection UAV (Guangzhou Jifei Technology Co., Ltd., Guangzhou, China) as the test equipment, four levels of flight speed (FS: 3, 4, 5, 6 m/s) and three levels of flight height (FH: 1.5, 2, 2.5 m) were combined as operation parameters, tests were carried out to compare the density and uniformity of droplet coverage, and the wheat aphid control tests were carried out by using the optimized operation parameters. The results of the wheat aphid distribution investigation test showed that aphids mainly distributed in the lower layer of the wheat plant canopy, accounting for more than 90.61%. The results of the droplet distribution test showed that with the increase in FS and FH, the coverage density and the droplet distribution uniformity in the upper and lower layers of wheat showed a downward trend under the condition of considering the boundary overlap of spraying width (SW) in multi-routes. Through the comparison of operation efficiency and droplet distribution quality, two combinations of parameters A1 (FS: 3 m/s, FH: 1.5 m) and B1 (FS: 4 m/s, FH: 1.5 m) were selected for the aphid control effect test. The results of the control test showed that the average control effect of A1 (92.05%) on aphids was 10.3% higher than that of B1 (81.75%) 7 days after pesticide application, which indicated that improving the droplet distribution uniformity in the lower layer of wheat could significantly improve the control effect of aphids. This study result could provide reference for the same type of crop protection UAV to control the same type of wheat diseases and insect pests in the same growing stage

Energy-Efficient Power Allocation for Full-Duplex Device-to-Device Underlaying Cellular Networks with NOMA

Full-duplex (FD), Device-to-Device (D2D) and non-orthogonal multiple access (NOMA) are promising wireless communication techniques to improve the utilization of spectrum resources. Meanwhile, introducing FD, D2D and NOMA in cellular networks is very challenging due to the complex interference problem. To deal with the complex interference of FD D2D underlaying NOMA cellular networks, power allocation (PA) is extensively studied as an efficient interference management technique. However, most of the previous research works on PA to optimize energy efficiency only consider the system framework of partially joint combining techniques of FD, D2D and NOMA, and the constraints of optimization problem are very different. In this paper, in order to further improve the energy efficiency of a system, a dual-layer iteration power allocation algorithm is proposed to eliminate the complex interference. The outer-layer iteration is to solve the non-linear fractional objective function based on Dinkelbach, and the inner-layer iteration is to solve the non-convex optimization problem based on D.C. programming. Then, the non-convex and non-linear fractional objective function is transformed into a convex function to solve the optimal power allocation. In this approach, FD D2D users reuse the spectrum with downlink NOMA cellular users. Imperfect self-interference (SI) cancellation at the FD D2D users and the successive interference cancellation (SIC) at the strong NOMA user are considered in the system framework. The optimization problem is constructed to maximize the system’s energy efficiency with the constraints of successful SIC, QoS requirements, the maximum transmit power of BS and FD D2D users. Numerical results demonstrate that the proposed algorithm outperforms the traditional orthogonal multiple access (OMA) in terms of energy efficiency with a higher system sum rate

Towards Optimal Variable Selection Methods for Soil Property Prediction Using a Regional Soil Vis-NIR Spectral Library

Soil visible and near-infrared (Vis-NIR, 350–2500 nm) spectroscopy has been proven as an alternative to conventional laboratory analysis due to its advantages being rapid, cost-effective, non-destructive and environmentally friendly. Different variable selection methods have been used to deal with the high redundancy, heavy computation, and model complexity of using full spectra in spectral modelling. However, most previous studies used a linear algorithm in the variable selection, and the application of a non-linear algorithm remains poorly explored. To address the current knowledge gap, based on a regional soil Vis-NIR spectral library (1430 soil samples), we evaluated seven variable selection algorithms together with three predictive algorithms in predicting seven soil properties. Our results showed that Cubist overperformed partial least squares regression (PLSR) and random forests (RF) in most soil properties (R2 > 0.75 for soil organic matter, total nitrogen and pH) when using the full spectra. Most of variable selection can greatly reduce the number of spectral bands and therefore simplified predictive models without losing accuracy. The results also showed that there was no silver bullet for the optimal variable selection algorithm among different predictive algorithms: (1) competitive adaptive reweighted sampling (CARS) always performed best for the PLSR algorithm, followed by forward recursive feature selection (FRFS); (2) recursive feature elimination (RFE) and genetic algorithm (GA) generally had better accuracy than others for the Cubist algorithm; and (3) FRFS had the best model performance for the RF algorithm. In addition, the performance was generally better when the algorithm used in the variable selection matched the predictive algorithm. The outcome of this study provides a valuable reference for predicting soil information using spectroscopic techniques together with variable selection algorithms

An improved estimate of soil carbon pool and carbon fluxes in the Qinghai-Tibetan grasslands using data assimilation with an ecosystem biogeochemical model

The accurate estimation of soil carbon (C) pool and fluxes is a prerequisite to better understand the terrestrial C feedback to climate change. However, recent studies showed considerable uncertainties in soil C estimates. To provide a reliable C estimate in the grasslands of the Qinghai-Tibet Plateau (QTP), we calibrated key parameters in a process-based ecosystem model (the CENTURY model) through data assimilation based on 570 soil samples and 21 sites of eddy covariance measurements. Two assimilating strategies (Opt1 – assimilating C pool observations; Opt2 –assimilating both C pool and C flux) were examined. Compared to default parameterization, our results showed both Opt1 and Opt2 improved the soil organic carbon density (SOCD) estimation, with R2 increasing from 0.59 to 0.75 and 0.73, respectively. Opt2 was superior to Opt1 in constraint of parameters dominating aboveground processes and yield a better estimation of net ecosystem production (NEP). Based on different parameterization, the spatial variability of SOCD and NEP across the QTP grassland were generated. Both Opt1 and Opt2 ameliorated the overestimation of SOCD by the default model, estimating a total soil C of 6.63 Pg and 6.48 Pg C for the topsoil (0–30 cm) of the QTP grasslands, respectively. Opt2 showed lower uncertainties in the NEP estimation and predicted a net sink of 14.33 Tg C annually. Compared with existing datasets, our study provided a more reliable estimation of carbon storage and fluxes in the QTP grassland with the calibrated ecosystem model. The results highlight that data assimilation with multiple observational data sets is promising to constrain process-based ecosystem models and increase the robustness of model predictions for terrestrial C cycle feedback to future climate change

Effects of Leaf Surface Roughness and Contact Angle on In Vivo Measurement of Droplet Retention

Droplet retention during pesticide application is a serious problem because run-off droplets flow out of the target area and pose a hazard to human health and the environment. The present study was conducted with the aim to measure the droplet retention of sprayed droplets on crop leaves in vivo using a constructed test system. In the measurement, three crop species with different surface properties (tomato, chili pepper, and winter wheat) were selected for droplet retention determination, and the variations in the time intervals of maximum retention and stable retention were determined. Contact angle and surface roughness (Ra), which are the most important surface properties of crop leaves, were used as independent variables. The Ra values of tomato, pepper, and winter wheat were 24.73 μm, 5.28 μm, and 17.59 μm, respectively, while the contact angles of tomato, pepper, and winter wheat were 97.67°, 70.07° and 131.98°, respectively. The results showed that the curves of droplet retention on sprayed tomato and wheat leaves had similar patterns over time and could be divided into four periods (rapidly increasing period, slowly increasing period, collapsing period, and stable period). The maximum droplet retention on tomato leaf surface was Rmax = 0.169 g⋅cm−2, and the stable retention was Rst = 0.134 g⋅cm−2. The maximum droplet retention on the surface of winter wheat leaf was Rmax = 0.244 g⋅cm−2, and the stable retention was Rst = 0.093 g⋅cm−2. However, droplet retention on pepper leaves was different from that on tomato and wheat leaves. The curve pattern of droplet retention on pepper leaves over time showed two peaks and two valleys. Moreover, the maximum retention, Rmax, was in the range of 0.149~0.151 g⋅cm−2, and the stable retention was Rst = 0.077 g⋅cm−2. It is expected that the obtained results can be used to characterize the properties of crop leaves and that this study can contribute to the improvement of droplet retention for effective chemical application and the reduction in the environmental pollution caused by agricultural pesticides

Optogenetic Activation of the Excitatory Neurons Expressing CaMKIIα in the Ventral Tegmental Area Upregulates the Locomotor Activity of Free Behaving Rats

The ventral tegmental area (VTA) plays an important role in motivation and motor activity of mammals. Previous studies have reported that electrical stimulations of the VTA’s neuronal projections were able to upregulate the locomotor activity of behaving rats. However, which types of neurons in the VTA that take part in the activation remain elusive. In this paper we employed optogenetic technique to selectively activate the excitatory neurons expressing CaMKIIα in the VTA region and induced a higher locomotor activity for free behaving rats. Further behavioral studies indicated that reward learning mediated in the enhancement of the rat locomotor activity. Finally the immunohistochemistry studies explored that the excitatory neurons under the optogenetic activation in VTA were partly dopaminergic that may participate as a vital role in the optogenetic activation of the locomotor activity. In total, our study provided an optogenetic approach to selectively upregulate the locomotor activity of free behaving rats, thus facilitating both neuroscience researches and neural engineering such as animal robotics in the future

Fixed Spraying Systems Application in Citrus Orchards: Nozzle Type and Nozzle Position Effects on Droplet Deposition and Pest Control

Pesticide application is an essential means of controlling plant diseases and pests in citrus orchards. In recent years, fixed spraying systems have gradually been used as alternatives to traditional sprayers and manual sprayers in some hilly citrus orchards. In this paper, influences of fixed system spraying parameters, such as droplet size and spraying height, on spraying quality were elucidated and analyzed. The performances of two nozzle types, pressure-swirl nozzles and fixed spray plate sprinklers, were assessed and compared by effective droplet coverage ratio (DCR), droplet distribution uniformity coefficient of variation (CV), and droplet penetration ratio (DPR). The results showed that appropriately increasing droplet size and spraying height could improve the DCR and distribution uniformity of pressure-swirl nozzles. The DCR and distribution uniformity of fixed spray plate sprinklers had a positive correlation with droplet size, while spraying height had no significant effect on these variables. Additionally, with the increase in droplet size, DPR initially increased and then gradually decreased. The optimized results showed that the optimal parameters for pressure-swirl nozzles were a droplet size of 240 μm and spraying height of 100 cm, while for fixed spray plate sprinklers, the results were a droplet size of 240 μm and spraying height of 50 cm. Comparison results showed that the spraying quality of fixed spray plate sprinklers was better overall, with values of DCR, CV, and DPR being 37.15%, 24.20%, and 71.67%, respectively, while the corresponding values for pressure-swirl nozzles were 39.65%, 35.41%, and 56.02%. Based on the above results and the occurrence rule of citrus pests and disease, the optimal spraying parameters of fixed spraying systems were selected to control the Asian citrus psyllid Diaphorina citri. Furthermore, the effect of fixed spraying systems on controlling Diaphorina citri reached the maximum at 3 days after spraying, which was 97.83%, and the effect declined at 14 days after spraying, which was 85.47%. This study provides valuable scientific references for guiding the application of fixed spraying systems in hilly citrus orchards