A Novel Method for Precise Onboard Real-Time Orbit Determination with a Standalone GPS Receiver.

Satellite remote sensing systems require accurate, autonomous and real-time orbit determinations (RTOD) for geo-referencing. Onboard Global Positioning System (GPS) has widely been used to undertake such tasks. In this paper, a novel RTOD method achieving decimeter precision using GPS carrier phases, required by China's HY2A and ZY3 missions, is presented. A key to the algorithm success is the introduction of a new parameter, termed pseudo-ambiguity. This parameter combines the phase ambiguity, the orbit, and clock offset errors of the GPS broadcast ephemeris together to absorb a large part of the combined error. Based on the analysis of the characteristics of the orbit and clock offset errors, the pseudo-ambiguity can be modeled as a random walk, and estimated in an extended Kalman filter. Experiments of processing real data from HY2A and ZY3, simulating onboard operational scenarios of these two missions, are performed using the developed software SATODS. Results have demonstrated that the position and velocity accuracy (3D RMS) of 0.2-0.4 m and 0.2-0.4 mm/s, respectively, are achieved using dual-frequency carrier phases for HY2A, and slightly worse results for ZY3. These results show it is feasible to obtain orbit accuracy at decimeter level of 3-5 dm for position and 0.3-0.5 mm/s for velocity with this RTOD method.

Parameterization of Four Models to Estimate Crop Evapotranspiration in a Solar Greenhouse.

Working to simplify mechanistic models on the basis of reliability for estimating crop evapotranspiration (ET) in a greenhouse is still worthwhile for horticulturists. In this study, four ET models (Penman-Monteith, Priestley-Taylor, and Shuttleworth-Wallace models, and the Crop coefficient method) were parameterized after taking the restriction effect of resistance parameters in these models on ET into account, named as PA-PM, PA-PT, PA-CC, and PA-SW, respectively. The performance of these four parameterized models was compared at different growth stages, as well as the entire growing season. Tomatoes that were ET-grown in a solar greenhouse without a heating device were measured using weighting lysimeters during 2016-2017 and 2019-2021, in which data from 2016 were used to adjust the model parameters, and data from the other four study years were used to examine the model performance. The results indicated that the PA-PT and PA-CC models have a better performance in estimating tomato ET at four growth stages, while the PA-PM and PA-SW performed well only at the development and middle stages. Compared to the ET that was measured with the weighting lysimeters, the ET that was predicted using the PA-PM model was 27.0% lower at the initial stage, and 8.7% higher at the late stage; the ET that was computed using the PA-SW model was 19.5% and 13.6% higher at the initial and late stages, respectively. The PA-PT model yielded the lowest root mean square error and the highest index of agreement against the other models over the entire growing season, indicating that the PA-PT model is the best recommended model for estimating tomato ET in a solar greenhouse.

Analysis of the Spatial-Temporal Distribution Characteristics of Climate and Its Impact on Winter Wheat Production in Shanxi Province, China, 1964-2018.

The possible influence of global climate changes on agricultural production is becoming increasingly significant, necessitating greater attention to improving agricultural production in response to temperature rises and precipitation variability. As one of the main winter wheat-producing areas in China, the temporal and spatial distribution characteristics of precipitation, accumulated temperature, and actual yield and climatic yield of winter wheat during the growing period in Shanxi Province were analysed in detail. With the utilisation of daily meteorological data collected from 12 meteorological stations in Shanxi Province in 1964-2018, our study analysed the change in winter wheat yield with climate change using GIS combined with wavelet analysis. The results show the following: (1) Accumulated temperature and precipitation are the two most important limiting factors among the main physical factors that impact yield. Based on the analysis of the ArcGIS geographical detector, the correlation between the actual yield of winter wheat and the precipitation during the growth period was the highest, reaching 0.469, and the meteorological yield and accumulated temperature during this period also reached its peak value of 0.376. (2) The regions with more suitable precipitation and accumulated temperature during the growth period of winter wheat in the study area had relatively high actual winter wheat yields. Overall, the average actual yield of the entire region showed a significant increasing trend over time, with an upward trend of 47.827 kg ha-1 yr-1. (3) The variation coefficient of winter wheat climatic yield was relatively stable in 2008-2018. In particular, there were many years of continuous reduction in winter wheat yields prior to 2006. Thereafter, the impact of climate change on winter wheat yields became smaller. This study expands our understanding of the complex interactions between climate variables and crop yield but also provides practical recommendations for enhancing agricultural practices in this region.

Evaluation of Irrigation Modes for Greenhouse Drip Irrigation Tomatoes Based on AquaCrop and DSSAT Models.

The improvement of the simulation accuracy of crop models in different greenhouse environments would be better applied to the automation management of greenhouse cultivation. Tomatoes under drip irrigation in a greenhouse were taken as the research object, and the cumulative evaporation capacity (Ep) of the 20 cm standard evaporation dish was taken as the basis for irrigation. Three treatments were set up in the experiment: high water treatment without mulch (NM-0.9 Ep), high water treatment with mulch (M-0.9 Ep), and low water treatment with mulch (M-0.5 Ep). AquaCrop and DSSAT models were used to simulate the canopy coverage, soil water content, biomass, and yield of the tomatoes. Data from 2020 were used to correct the model, and simulation results from 2021 were analyzed in this paper. The results showed that: (1) Of the two crop models, the simulation accuracy of the greenhouse tomato canopy coverage kCC was higher, and the root mean square errors were less than 6.8% (AquaCrop model) and 8.5% (DSSAT model); (2) The AquaCrop model could accurately simulate soil water change under high water treatments, while the DSSAT model was more suitable for the conditions without mulch; (3) The relative error RE of simulated and observed values for biomass B, yield Y, and water use efficiency WUE in the AquaCrop model were less than 2.0%, 2.3%, and 9.0%, respectively, while those of the DSSAT model were less than 4.7%, 7.6%, and 10.4%, respectively; (4) Considering the simulation results of each index comprehensively, the AquaCrop model was superior to the DSSAT model; subsequently, the former was used to predict 16 different water and film coating treatments (S1-S16). It was found that the greenhouse tomato yield and WUE were the highest under S7 (0.8 Ep), at 8.201 t/ha and 2.79 kg/m3, respectively.

Root Distribution of Tomato Cultivated in Greenhouse under Different Ventilation and Water Conditions.

Mastering root distribution is essential for optimizing the root zone environment and for improving water use efficiency, especially for crops cultivated in greenhouses. Here, we set up two irrigation amount levels based on measurements of the cumulative 20 cm pan evaporation (Ep) (i.e., K0.9: 0.9 Ep; K0.5: 0.5 Ep), and three ventilation modes through opening the greenhouse vents at different locations (TR: open the roof vents only; TRS: open both the roof and south vents; TS: open the south vents only) to reveal the effects of the ventilation mode and irrigation amount on the root distribution of greenhouse tomato. Six treatments were designed in blocks with the ventilation mode as the main treatment and the irrigation amount as the vice treatment. On this basis, the normalized root length density (NRLD) model of six treatments was developed by considering air environment, soil water and temperature conditions, root length density (RLD) and yield. The results showed that air speed of the TRS was significantly higher than TR and TS (p < 0.01), and the air temperature and relative humidity under different ventilation showed the rule: TR > TS > TRS. There was a significant third-order polynomial function relationship between NRLD and soil depth, and the coefficient of the cubic term (R0) had a bivariate quadratic polynomial function relationship with irrigation amount and air speed (determination coefficient, R2 = 0.86). Root mean square errors of the simulated and measured value of NRLD under TR, TRS and TS were 0.20, 0.23 and 0.27 in 2020, and 0.31, 0.23 and 0.28 in 2021, respectively, normalized root mean squared errors were 15%, 17%, 20% in 2020, and 23%, 18% and 21% in 2021. The RLD distribution ratio from the ground surface to a one-quarter relative root depth was 74.1%, and 88.0% from the surface to a one-half relative root depth. The results of the yield showed that a better combination of ventilation and irrigation was recommended as TRS combined with K0.9.

Heat stress decreased transpiration but increased evapotranspiration in gerbera.

Heat stress is a major constraint for plant production, and evapotranspiration is highly linked to plant production. However, the response mechanism of evapotranspiration to heat stress remains unclear. Here, we investigated the effects of heat stress during two main growth stages on transpiration and evapotranspiration of gerbera. Two levels of day/night temperature were adopted during the vegetative growth stage (VG) and the flowering bud differentiation stage (FBD), namely control (CK; 28/18 °C) and heat stress (HS; 38/28°C) levels. The duration of HS was set as 5, 10, 15, and 20 days, respectively. At the beginning of HS, hourly transpiration was mainly inhibited near noon. With continuation of HS, the duration and extent of inhibition of hourly transpiration increased. Daily transpiration rate was also markedly reduced by HS during the VG (18.9%-31.8%) and FBD (12.1%-20.3%) stages compared to CK. The decrease in the daily transpiration rate was greater for longer duration of heat stress. This reduction of transpiration was the main contributor to stomatal limitation at the beginning of HS, while additional inhibition of root activity, leaf area, and root biomass occurred under long-term HS. The daily transpiration rate could not recover after the end of HS (so-called recovery phase), except when HS lasted 5 days during the VG stage. Interestingly, daily evapotranspiration during HS was substantially increased during the VG (12.6%-24.5%) and FBD (8.4%-17.6%) stages as a result of more increased evaporation (100%-115%) than reduced transpiration. However, during the recovery phase, the daily evapotranspiration was markedly decreased at the VG (11.2%-22.7%) and FBD (11.1%-19.2%) stages. Hence, we suggest that disproportionate variation of transpiration and evaporation during HS, especially at the recovery phase, should be considered in various evapotranspiration models and climate scenarios projections.

An aerosol deposition based MEMS piezoelectric accelerometer for low noise measurement.

Potentially applied in low-noise applications such as structural health monitoring (SHM), a 1-axis piezoelectric MEMS accelerometer based on aerosol deposition is designed, fabricated, simulated, and measured in this study. It is a cantilever beam structure with a tip proof mass and PZT sensing layer. To figure out whether the design is suitable for SHM, working bandwidth and noise level are obtained via simulation. For the first time, we use aerosol deposition method to deposit thick PZT film during the fabrication process to achieve high sensitivity. In performance measurement, we obtain the charge sensitivity, natural frequency, working bandwidth and noise equivalent acceleration of 22.74 pC/g, 867.4 Hz, 10-200 Hz (within ±5% deviation) and 5.6 µ g / Hz (at 20 Hz). To demonstrate its feasibility for real applications, vibrations of a fan are measured by our designed sensor and a commercial piezoelectric accelerometer, and the results match well with each other. Moreover, shaker vibration measurement with ADXL1001 indicates that the fabricated sensor has a much lower noise level. In the end, we show that our designed accelerometer has good performance compared to piezoelectric MEMS accelerometers in relevant studies and great potential for low-noise applications compared to low-noise capacitive MEMS accelerometers.

Use of focused computerized cognitive training (Neuroflex) to improve symptoms in women with persistent chemotherapy-related cognitive impairment.

Purpose: Chemotherapy-related cognitive impairment (CRCI) is a distressing and increasingly recognized long-term sequela reported by breast cancer patients following cancer treatment. There is an urgent but unmet clinical need for treatments that improve CRCI. In this context, we proposed the use of a novel cognitive enhancement strategy called Neuroflex to target CRCI experienced by breast cancer survivors. Methods: The primary aim of this pilot study was to evaluate the feasibility and acceptability of Neuroflex, a novel digital cognitive enhancement strategy, in breast and gynecologic cancer survivors with CRCI. Secondary analyses focused on whether improvements in performance on Neuroflex were associated with improvement in subjective cognitive complaints and objective cognitive performance measures. Results: Participants (N = 21) completed an average of 7.42 hours of Neuroflex training per week, an average of 44.5 (±1.01) hours total, and had a 100% completion rate. Participants exhibited significant improvement in self-reported cognitive function as well as significant improvement on tasks of verbal learning and memory and auditory working memory. Participants also exhibited improvement in mood, as well as improvement on a disability assessment. Conclusions: Results demonstrate feasibility and that breast cancer survivors are capable of completing a lengthy and challenging cognitive training program. Secondly, Neuroflex may confer specific cognitive benefits to both self-reported and objective performance. Results strongly support further investigation of Neuroflex in a larger controlled trial to establish efficacy for CRCI symptoms. Further studies may also result in optimization of this digital intervention for women with CRCI.

Rationally Designed Enzyme-Resistant Peptidic Assemblies for Plasma Membrane Targeting in Cancer Treatment.

Peptides are being increasingly important for subcellular targeted cancer treatment to improve specificity and reverse multidrug resistance. However, there has been yet any report on targeting plasma membrane (PM) through self-assembling peptides. A simple synthetic peptidic molecule (tF4) is developed. It is revealed that tF4 is carboxyl esterase-resistant and self-assembles into vesical nanostructures. Importantly, tF4 assemblies interact with PM through orthogonal hydrogen bonding and hydrophobic interaction to regulate cancer cellular functions. Mechanistically, tF4 assemblies induce stress fiber formation, cytoskeleton reconstruction, and death receptor 4/5 (DR4/5) expression in cancer cells. DR4/5 triggers extrinsic caspase-8 signaling cascade, resulting in cell death. The results provide a new strategy for developing enzyme-resistant and PM-targeting peptidic molecules against cancer.

Prediction of Greenhouse Tomato Crop Evapotranspiration Using XGBoost Machine Learning Model.

Crop evapotranspiration estimation is a key parameter for achieving functional irrigation systems. However, ET is difficult to directly measure, so an ideal solution was to develop a simulation model to obtain ET. There are many ways to calculate ET, most of which use models based on the Penman−Monteith equation, but they are often inaccurate when applied to greenhouse crop evapotranspiration. The use of machine learning models to predict ET has gradually increased, but research into their application for greenhouse crops is relatively rare. We used experimental data for three years (2019−2021) to model the effects on ET of eight meteorological factors (net solar radiation (Rn), mean temperature (Ta), minimum temperature (Tamin), maximum temperature (Tamax), relative humidity (RH), minimum relative humidity (RHmin), maximum relative humidity (RHmax), and wind speed (V)) using a greenhouse drip irrigated tomato crop ET prediction model (XGBR-ET) that was based on XGBoost regression (XGBR). The model was compared with seven other common regression models (linear regression (LR), support vector regression (SVR), K neighbors regression (KNR), random forest regression (RFR), AdaBoost regression (ABR), bagging regression (BR), and gradient boosting regression (GBR)). The results showed that Rn, Ta, and Tamax were positively correlated with ET, and that Tamin, RH, RHmin, RHmax, and V were negatively correlated with ET. Rn had the greatest correlation with ET (r = 0.89), and V had the least correlation with ET (r = 0.43). The eight models were ordered, in terms of prediction accuracy, XGBR-ET > GBR-ET > SVR-ET > ABR-ET > BR-ET > LR-ET > KNR-ET > RFR-ET. The statistical indicators mean square error (0.032), root mean square error (0.163), mean absolute error (0.132), mean absolute percentage error (4.47%), and coefficient of determination (0.981) of XGBR-ET showed that XGBR-ET modeled daily ET for greenhouse tomatoes well. The parameters of the XGBR-ET model were ablated to show that the order of importance of meteorological factors on XGBR-ET was Rn > RH > RHmin> Tamax> RHmax> Tamin> Ta> V. Selecting Rn, RH, RHmin, Tamax, and Tamin as model input variables using XGBR ensured the prediction accuracy of the model (mean square error 0.047). This study has value as a reference for the simplification of the calculation of evapotranspiration for drip irrigated greenhouse tomato crops using a novel application of machine learning as a basis for an effective irrigation program.

Performance of the Improved Priestley-Taylor Model for Simulating Evapotranspiration of Greenhouse Tomato at Different Growth Stages.

Mastering crop evapotranspiration (ET) and improving the accuracy of ET simulation is critical for optimizing the irrigation schedule and saving water resources, particularly for crops cultivated in a greenhouse. Taking greenhouse-grown tomato under drip irrigation as an example, two weighing lysimeters were used to monitor ET at two seasons (2019 and 2020), whilst meteorological factors inside the greenhouse were measured using an automatic weather station. Then the path analysis approach was employed to determine the main environmental control factors of ET. On this basis, an improved Priestley-Taylor (IPT) model was developed to simulate tomato ET at different growth stages by considering the influence of environmental changes on model parameters (e.g., leaf senescence coefficient, temperature constraint coefficient and soil evaporative water stress coefficient). Results showed that the average daily ET varied from 0.06 to 6.57 mm d−1, which were ~0.98, ~2.58, ~3.70 and ~3.32 mm/d at the initial, development, middle and late stages, respectively, with the total ET over the whole growth stage of ~333.0 mm. Net solar radiation (Rn) and vapor pressure deficit (VPD) were the direct influencing factors of ET, whereas air temperature (Ta) was the limiting factor and wind speed (u2) had a little influence on ET. The order of correlation coefficients between meteorological factors and ET at two seasons was Rn > VPD > Ta > u2. The IPT model can accurately simulate ET in hourly and daily scales. The root mean square error of hourly ET at four stages changed from 0.002 to 0.08 mm h−1 and daily ET varied from 0.54 to 0.57 mm d−1. The IPT coefficient was close to the recommended PT coefficient (1.26) when the average Ta approaches 26 °C and LAI approaches 2.5 cm2 cm−2 in greenhouse conditions. Our results can provide a theoretical basis for further optimization of greenhouse crop irrigation schedules and improvement of water use efficiency.

Palmitate impairs the autophagic flux to induce p62-dependent apoptosis through the upregulation of CYLD in NRCMs.

The most abundant saturated free fatty acid such as palmitate (PA), can accumulate in cardiomyocytes and induce lipotoxicity. CYLD is a known regulator in the development of cardiovascular disease and an important mediator of apoptosis. The role of CYLD in PA-induced cardiomyocyte apoptosis is not completely known. Here, we showed that PA treatment resulted in a concentration- and time-dependent effect on neonatal rat cardiomyocytes (NRCMs) apoptosis. PA impaired autophagy by significantly increasing the expression levels of LC3-II, Beclin 1, and also p62 in NRCMs. The autophagy flux was measured by detecting the fluorescence in the cells with Ad-mCherry-GFP-LC3B, a decrease in red puncta and a significant increase in yellow puncta in response to PA stimulation indicated that PA impairs the autophagic flux at the late stage of autophagosome-lysosome fusion. We further found knocked down of p62 by siRNA significantly decreased the expression level of cleaved caspase-3, decreased the apoptosis rate, also alleviated the loss of mitochondrial membrane potential, and decreased AIF and Cyt C releasing from mitochondria into the cytoplasm in the PA-treated NRCMs. From this, we considered that p62 accumulation was responsible for mitochondria-mediated apoptosis in PA-treated NRCMs. In addition, PA-induced a strong elevation of CYLD, siRNA-mediated knockdown of CYLD significantly antagonized PA-induced apoptosis and restored the autophagic flux in NRCMs. Knockdown of CYLD activation of the Wnt/ß-catenin pathway to restore the autophagic flux and reduce the accumulation of p62 in PA- stimulated NRCMs, while an inhibitor of the Wnt/ß-catenin pathway reversed this effect. Thus, our findings provide new insight into the molecular mechanism of PA toxicity in myocardial cells and suggest that CYLD may be a new therapeutic target for lipotoxic cardiomyopathy.

[Diagnosis method of cotton water status based on infrared thermal imaging].

Canopy temperature is one of promising signals for evaluating crop water status. The infrared thermal imager can provide real-time temperature distributions over larger areas with high spatial resolution. The main factors (the observation orientation, angle and distance) controlling the accuracy of measuring canopy temperature with the infrared thermal imaging were investigated in a cotton field. Moreover, the correlation relationships between the crop water stress index (CWSI), which was observed using different methods, and soil water content (SWC), leaf water potential (LWP), and stomatal conductance (g(s)) of cotton in different water treatments were analyzed. Results indicated that the CWSI, which was measured in the opposite direction of the sun with the observation angle of 45°, was in good correlation with LWP, g(s) and SWC, indicating it was a suitable observing method of canopy temperature. The canopy temperature gradually decreased with the increasing observation distance, so the calibration was necessary for long-distance measurement. By analyzing the relationship between the temperature at the dry/wet reference surface and the canopy temperature, we developed a suitable and simplified model of CWSI for cotton in the North China Plain.

State-dependent alterations in sleep/wake architecture elicited by the M4 PAM VU0467154 - Relation to antipsychotic-like drug effects.

Accumulating evidence indicates direct relationships between sleep abnormalities and the severity and prevalence of other symptom clusters in schizophrenia. Assessment of potential state-dependent alterations in sleep architecture and arousal relative to antipsychotic-like activity is critical for the development of novel antipsychotic drugs (APDs). Recently, we reported that VU0467154, a selective positive allosteric modulator (PAM) of the M4 muscarinic acetylcholine receptor (mAChR), exhibits robust APD-like and cognitive enhancing activity in rodents. However, the state-dependent effects of VU0467154 on sleep architecture and arousal have not been examined. Using polysomnography and quantitative electroencephalographic recordings from subcranial electrodes in rats, we evaluated the effects of VU0467154, in comparison with the atypical APD clozapine and the M1/M4-preferring mAChR agonist xanomeline. VU0467154 induced state-dependent alterations in sleep architecture and arousal including delayed Rapid Eye Movement (REM) sleep onset, increased cumulative duration of total and Non-Rapid Eye Movement (NREM) sleep, and increased arousal during waking periods. Clozapine decreased arousal during wake, increased cumulative NREM, and decreased REM sleep. In contrast, xanomeline increased time awake and arousal during wake, but reduced slow wave activity during NREM sleep. Additionally, in combination with the N-methyl-d-aspartate subtype of glutamate receptor (NMDAR) antagonist MK-801, modeling NMDAR hypofunction thought to underlie many symptoms in schizophrenia, both VU0467154 and clozapine attenuated MK-801-induced elevations in high frequency gamma power consistent with an APD-like mechanism of action. These findings suggest that selective M4 PAMs may represent a novel mechanism for treating multiple symptoms of schizophrenia, including disruptions in sleep architecture without a sedative profile.

[Irrigation scheduling with a 20 cm standard pan for drip-irrigated cucumber grown in solar greenhouse in the North China Plain].

An experiment was conducted in 2013 and 2014 at the Xinxiang Comprehensive Experimental Station, Chinese Academy of Agriculture Sciences. Water amount was estimated with the Ep-20 and pan coefficient. Responses of cucumber evapotranspiration (ET), yield, quality and water use efficiency (WUE) to different drip irrigation amounts (Kcp1: 0.25; Kcp2: 0.5; Kcp3: 0.75; Kcp4: 1.0; Kcp5: 1.25) were investigated. The possibility of developing drip irrigation scheduling using the 20 cm pan was also discussed. Results showed that the seasonal evapotranspiration of cucumber ranged between 129 and 314 mm, and the water consumption generally increased with the increase in drip irrigation water amount. There was no significance difference in cucumber yield between the treatments with Kcp > 0.75, and the responses of mean fruit mass, number and length to water amount had a threshold value (0.75Ep-20). Regarding the fruit quality, the contents of total soluble solids, vitamin C and soluble sugar slightly decreased with increasing the irrigation water amount, while the soluble protein content varied in order as: Kcp2 > Kcp3 > Kcp4 > Kcp1 > Kcp5. There was a significant positive correlation (P < 0.01) between the pan evaporation and the reference crop evapotranspiration estimated based on a modified Penman-Monteith equation. In a conclusion, the drip water amount calculated with Kcp of 0.75 and the 20 cm pan were easy and feasible for cucumber cultivation in solar greenhouse in the North China Plain.

A rodent model of traumatic stress induces lasting sleep and quantitative electroencephalographic disturbances.

Hyperarousal and sleep disturbances are common, debilitating symptoms of post-traumatic stress disorder (PTSD). PTSD patients also exhibit abnormalities in quantitative electroencephalography (qEEG) power spectra during wake as well as rapid eye movement (REM) and non-REM (NREM) sleep. Selective serotonin reuptake inhibitors (SSRIs), the first-line pharmacological treatment for PTSD, provide modest remediation of the hyperarousal symptoms in PTSD patients, but have little to no effect on the sleep-wake architecture deficits. Development of novel therapeutics for these sleep-wake architecture deficits is limited by a lack of relevant animal models. Thus, the present study investigated whether single prolonged stress (SPS), a rodent model of traumatic stress, induces PTSD-like sleep-wake and qEEG spectral power abnormalities that correlate with changes in central serotonin (5-HT) and neuropeptide Y (NPY) signaling in rats. Rats were implanted with telemetric recording devices to continuously measure EEG before and after SPS treatment. A second cohort of rats was used to measure SPS-induced changes in plasma corticosterone, 5-HT utilization, and NPY expression in brain regions that comprise the neural fear circuitry. SPS caused sustained dysregulation of NREM and REM sleep, accompanied by state-dependent alterations in qEEG power spectra indicative of cortical hyperarousal. These changes corresponded with acute induction of the corticosterone receptor co-chaperone FK506-binding protein 51 and delayed reductions in 5-HT utilization and NPY expression in the amygdala. SPS represents a preclinical model of PTSD-related sleep-wake and qEEG disturbances with underlying alterations in neurotransmitter systems known to modulate both sleep-wake architecture and the neural fear circuitry.

[Effects of irrigation threshold on soil temperature in blossom and fruit-set periods of muskmelon under mulching-drip irrigation in greenhouse].

It is very significant for muskmelon growth and production to maintain optimal conditions of soil moisture and temperature, especially during blossom and fruit-bearing periods. The object of this study was to analyze the effects of different soil water thresholds (T1: 55% of the field capacity, T2: 65% of the field capacity, T3: 75% of the field capacity, CK: 85% of the field capacity) on soil temperature under mulching-drip irrigation in greenhouse. Moreover, effects of the ratio of soil moisture to heat in the plough layer (0-20 cm) on muskmelon growth and fruit setting were investigated. Results indicated that during the flowering and fruit bearing periods, the order of mean soil temperature in the plough layer for the different treatments was T1 > T2 > T3 > CK. There was an inverse correlation between soil temperature in the plough layer and moisture. The maximum one-day variations for soil temperature on sunny day, rainy day and after irrigation were observed in the soil surface under the plastic film mulch, while the minimum happened in the soil layer of 20 cm outside the mulch. The soil temperature extreme was closely related with soil depth, and the difference in the extreme soil temperature between the soil surface and the soil layers of 10 and 20 cm was significant. The treatment T3, with the fastest plant growth rate, the minimum duration of fruit bearing and the maximum fruit setting rate, could be selected as the optimal treatment, and the ratio of soil moisture to heat in T3 was 1.62 mm · °C(-1). Therefore, taking into consideration the relationship between soil moisture and temperature during flowering and fruit bearing periods of muskmelon under mulching-drip irrigation, the ratio of soil water to heat in the plough layer should be kept at 1.62 mm · C(-1). The result would be very meaningful for drip-irrigated muskmelon production and management in greenhouse in North China.