Three-dimensional stress variation characteristics in deep hard rock of CJPL-Ⅱ project based on in-situ monitoring

In deep hard rock excavation, stress plays a pivotal role in inducing stress-controlled failure. While the impact of excavation-induced stress disturbance on rock failure and tunnel stability has undergone comprehensive examination through laboratory tests and numerical simulations, its validation through insitu stress tests remains unexplored. This study analyzes the three-dimensional stress changes in the surrounding rock at various depths, monitored during the excavation of B2 Lab in China Jinping Underground Laboratory Phase Ⅱ(CJPL-Ⅱ). The investigation delves into the three-dimensional stress variation characteristics in deep hard rock, encompassing stress components and principal stress. The results indicate changes in both the magnitude and direction of the principal stress during tunnel excavation. To quantitatively describe the degree of stress disturbance, a series of stress evaluation indexes are established based on the distances between stress tensors, including the stress disturbance index(SDI), the principal stress magnitude disturbance index(SDIm), and the principal stress direction disturbance index(SDId). The SDI indicates the greatest stress disturbance in the surrounding rock is 4.5 m from the tunnel wall in B2 Lab. SDIm shows that the principal stress magnitude disturbance peaks at2.5 m from the tunnel wall. SDId reveals that the largest change in principal stress direction does not necessarily occur near the tunnel wall but at a specific depth from it. The established relationship between SDI and the depth of the excavation damaged zone(EDZ) can serve as a criterion for determining the depth of the EDZ in deep hard rock engineering. Additionally, it provides a reference for future construction and support considerations.

The driving force of water resource stress change based on the STIRPAT model:take Zhangye City as a case study

A prominent contradiction between supply and demand of water resources has restricted local development in social and economic aspects of Zhangye City,located in a typical arid region of China.Our study quantified the Water Resource Stress Index(WRSI)from 2003 to 2017 and examined the factors of population,urbanization level,GDP per capita,Engel coefficient,and water consumption per unit of GDP by using the extended stochastic impact by regression on population,affluence and technology(STIRPAT)model to find the key factors that impact WRSI of Zhangye City to relieve the pressure on water resources.The ridge regression method is applied to improve this model to eliminate multicollinearity problems.The WRSI system was developed from the following three aspects:water resources utilization(WR),regional economic development water use(WU),and water environment stress(WE).Results show that the WRSI index has fallen from 0.81(2003)to 0.17(2017),with an average annual decreased rate of 9.8%.Moreover,the absolute values of normalized coefficients demonstrate that the Engel coefficient has the largest positive contribution to increase WRSI with an elastic coefficient of 0.2709,followed by water consumption per unit of GDP and population with elastic coefficients of 0.0971 and 0.0387,respectively.In contrast,the urbanization level and GDP per capita can decrease WRSI by−0.2449 and−0.089,respectively.The decline of WRSI was attributed to water-saving society construction which included the improvement of water saving technology and the adjustment of agricultural planting structures.Furthermore,this study demonstrated the feasibility of evaluating the driving forces affecting WRSI by using the STIRPAT model and ridge regression analysis.

Triple test cross analysis for seed yield and its components in sesame under water stress conditions

Water deficit is a limiting factor in sesame cultivars yield,thus identification of genetic mechanisms of sesame traits under water stress conditions is essential to development of water stress tolerant genotypes.Hence,the triple test cross(TTC)analysis in F_(2) population of the sesame cross(NA_(76)NA_(54))was used.Since,30 TTC families with their 13 respective parents were evaluated during the summer season 2020 under two irrigation treatments.i.e.,normal irrigation with 5952.38 m^(3) hm^(-2) of applied water,and water stress with 2976.19 m^(3) hm^(-2) of applied water.This was implemented at the experimental field of Kafr El Hamam/Sharkia,Agricultural Research Station,Agricultural Research Center(ARC),Egypt.Additive(D)and dominance(H)gene actions as well as epistatic and its two components of additiveadditive,additivedominance plus dominancedominance were involved in the inheritance of all studied traits under both irrigation treatments and their combined analysis.The degree of dominance(H/D)^(0.5) verified the presence of partial dominance in most cases.The correlation coefficient between sums(additive)and differences(dominance)was non-significant,showing that dominant genes between lines were ambidirectional.The moderately water stress tolerant TTC families as the best selected families were found in families 22,25,10,12,and 15.Therefore,postponing selection in these selected families to later segregating generations for all studied traits would be effective to exploit the positive effects of additiveadditive epistasis.

Iron Toxicity Tolerance of Rice Genotypes in Relation to Growth,Yield and Physiochemical Characters

Iron(Fe)toxicity,generated from excess reduced ferrous Fe(Fe^(2+))ion formation within the soil under submerged condition,is a potent environmental stress that limits lowland rice production.Total 11 diverse Thai rice genotypes,including a recognized tolerant genotype Azucena and a susceptible genotype IR64,were evaluated against 5 Fe^(2+)levels[0(control),150,300,600 and 900 mg/L]to screen the tested genotypes for their Fe-toxicity tolerance and to classify them as a sensitive/tolerant category.The evaluation was conducted by a germination study,followed by a polyhouse study on growth,yield and physiochemical performances.Results showed significant variations in Fe^(2+)-tolerance across genotypes.Increasing Fe^(2+)level beyond 300 mg/L was detrimental for germination and growth of all the tested genotypes,although germination responses were negatively affected at Fe^(2+)≥300 mg/L.Physiochemical responses in the form of leaf greenness,net photosynthetic rate,membrane stability index and Fe contents in leaf and root were the most representative of Fe^(2+)-toxicity-mediated impairments on overall growth and yield.Difference in physiochemical responses was effectively correlated with the contrasting ability of the genotypes on lowering excess Fe^(2+)in tissues.Analysis of average tolerance and stress tolerance index unveiled that the genotypes RD85 and RD31 were the closest to the tolerant check Azucena and the sensitive check IR64,respectively.The unweighted pair group method with arithmetic means clustering revealed three major clusters,with cluster Ⅱ(four genotypes)being Fe^(2+)tolerant and cluster Ⅰ(four genotypes)being Fe^(2+)sensitive.Principal component(PC)analysis and genotype by trait-biplot analysis showed that the first two components explained 90.5%of the total variation,with PC1 accounting for 56.6%and PC2 for 33.9%of the total variation.The identified tolerant rice genotypes show potentials for cultivation in Fe^(2+)-toxic lowlands for increased productivity.The findings contribute to the present understanding on Fe^(2+)-toxicity response and provide a basis for future genotype selection or rice crop improvement programs against Fe^(2+)-toxicity.

Isolating higher yielding and more stable rice genotypes in stress environments: fine-tuning a selection method using production and resilience score indices

In Asia, the rice crop sustains millions of people. However, growing demand for this crop needs to be met while simultaneously reducing its water consumption to cope with the effects of climate change. Lowland cropping systems are the most common and productive but have particularly high water requirements. High-yielding rice genotypes adapted to drier environments(such as rainfed or aerobic rice ecosystems) are needed to increase the water use efficiency of cropping. Identifying these genotypes requires fast and more accurate selection methods. It is hypothesized that applying a new quantitative selection method(the score index selection method), can usefully compare rice yield responses over different years and stress intensities to select genotypes more rapidly and efficiently. Applying the score index to previously published rice yield data for 39 genotypes grown in no-stress and two stress environments, identified three genotypes(ARB 8, IR55419-04 and ARB 7) with higher and stable yield under moderate to severe stress conditions. These genotypes are postulated to be better adapted to stress environment such as upland and aerobic environments. Importantly, the score index selection method offers improved precision than the conventional breeding selection method in identifying genotypes that are well-suited to a range of stress levels within the target environment.

Canopy Temperature Depression as a Potential Selection Criterion for Drought Resistance in Wheat

Field studies were conducted at Bushland, Texas, USA, in 2004 to examine usefulness of canopy temperature depression （CTD）, the difference of air-canopy temperature, in screening wheat （Triticum aestivum L.） genotypes for yield under dryland and irrigated. Forty winter wheat genotypes were grown under irrigation and dryland. CTDs were recorded after heading between 1 330 and 1 530 h on 6 clear days for dryland and 9 days for irrigation. Drought susceptible index （DSI） for each genotype was calculated using mean yield under dryland and irrigated conditions. Genotypes exhibited great differences in CTD under each environment. The dryland CTDs averaged 1.33℃ ranging from -0.67 to 2.57℃, and the average irrigation CTD were 4.59℃ ranging from 3.21 to 5.62℃. A low yield reduction was observed under dryland conditions relative to irrigated conditions for high-CTD genotypes. CTD values were highly negatively correlated with DSI under dryland, and genotypes of CTDs = 1.3℃ in dryland condition were identified as drought resistant. For 21 genotypes classified as drought resistant by DSI, their CTDs were 1.68℃ for dryland and 4.35℃ for irrigation on average; for 19 genotypes classified as drought susceptible by DSI, average CTD was 0.94℃ in dryland and 4.85℃ in irrigation. The high-yield genotypes consistently had high CTD values, and the low-yield ones had low CTD values for all measurements in dryland. After heading, genotypes maintained consistent ranking for CTD. Regression results for CTD and yield suggested that the best time for taking CTD measurement was 3-4 weeks after heading in irrigation but any time before senescence in dryland. Crop water stress index （CWSI） calculated from CTD data was highly correlated with CWSI calculated from yield, which suggesting traditional costly CWSI measurement may be improved by using portable infrared thermometers. Most importantly, grain yield was highly correlated with CTD under dryland （R^2 = 0.79-0.86） and irrigation （R^2 = 0.46-0.58） conditions. These results clearly indicated grain yield and water stress can be predicted by taking CTD values in field, which can be used by breeding programs as a potential selection criterion for grain yield and drought resistance in wheat, but a second study year is needed to confirm further.

Crop water stress index for off-season greenhouse green peppers in Liaoning, China

The crop water stress index(CWSI)is a complex instrument to effectively monitor the degree of water stress of crops and provides guidance for timely irrigation.In an experiment utilizing the CWSI with off-season green peppers planted in barrels in a greenhouse in Liaoning Province,Northeast China,this study monitors the sub-indexes--such as canopy temperature,environmental factors and yield--determines the changing law of each constituent,achieves an empirical model as well as a baseline formula for the canopy temperature of the peppers with a sufficient water supply,and verifies the rationality of the formula with corresponding experimental data.The results obtained by using the CWSI show that the optimal time to determine the water deficit for off-season green peppers is at noon,by measuring the diurnal variation in the peppers with different water supplies.There is a nonlinear relationship between the yield and the average CWSI at the prime fruit-bearing period;moreover,the optimal time to supply water for off-season green peppers comes when the average water stress index ranges between 0.2 and 0.4 during the prime fruiting stage,thereby ensuring a high yield.

Automatic diagnosis of strawberry water stress status based on machine vision

Water stress status of plants is very important for irrigation scheduling.However,plant water stress status monitoring has become the bottleneck of irrigation scheduling.In this study,an automatic water stress status monitoring method for strawberry plant was proposed and realized using combined RGB and infrared image information.RGB image and infrared images were obtained using RGB digital camera and infrared thermal camera,which were placed in a fixed shell in parallel.In the first experimental stage,three kinds of water stress treatments were carried out on three groups of strawberry plants,and each group includes three repetitions.Single point plant temperature,dry surface temperature,wet surface temperature were measured.In the second experimental stage,the infrared and visible light images of the canopy leaves were obtained.Meanwhile,plant temperature,dry surface temperature,wet surface temperature,and stomatal conductance were measured not only for single point but also for plant area temperature measurement.Fusion information of infrared image and visible light image was analyzed using image processing technology,to calculate the average temperature of plant areas.Based on single point temperature,area temperature,dry surface temperature and wet surface temperature of the plant,single point crop water stress index(CWSI)and area CWSI were calculated.Through analysis of variance(ANOVA),the experimental results showed that CWSI measured for plants under different treatments,were significantly different.Through correlation analysis,the experimental results showed that,determination coefficient between area CWSI and the corresponding stomatal conductance of three strawberry groups were 0.8834,0.8730 and 0.8851,respectively,which were larger than that of single-point CWSI and stomatal conductance.The results showed that area CWSI is more suitable to be used as the criteria for automatic diagnosis of plants.

Clinical effect of acupuncture at ghost points combined with fluoxetine hydrochloride on mild-to-moderate depression

BACKGROUND Depression is a common,chronic,and recurrent mood disorder that has become a worldwide health hazard.Fluoxetine hydrochloride,a common treatment method,can inhibit 5-hydroxytryptamine(5-HT)recycling in the presynaptic membrane;however,the efficacy of a single drug is inadequate.At present,mildto-moderate depression can be treated with acupuncture of ghost caves,but the clinical curative effect of combined therapy with fluoxetine hydrochloride has not been sufficiently reported.AIM To evaluate the clinical effect of acupuncture at ghost points combined with fluoxetine hydrochloride in the treatment of mild-to-moderate depression.METHODS This retrospective study included 160 patients with mild-to-moderate depression who were admitted to Shanghai Hospital of Integrated Traditional Chinese and Western Medicine,Affiliated to Shanghai University of Traditional Chinese Medicine,between January 2022 and June 2023.Patients were separated into a single-agent group(fluoxetine hydrochloride treatment,n=80)and a coalition group(fluoxetine hydrochloride treatment combined with acupuncture at ghost points,n=80).Pre-treatment symptoms were recorded,and the clinical curative effect and adverse reactions[Asberg Antidepressant Side Effects Scale(SERS)]were assessed.Depression before and after treatment[Hamilton Depression Scale(HAMD)-24],neurotransmitter levels[5-HT,norepinephrine(NE),dopamine(DA)],oxidative stress indicators[superoxide dismutase(SOD),malondialdehyde(MDA)],and sleep quality[Pittsburgh Sleep Quality Index(PSQI)]were compared.RESULTS The total efficacy rate was 97.50%in the coalition group and 86.25%in the single-agent group(P<0.05).After 2,4,6,and 8 wk of treatment,the HAMD,self-rating depression scale,and SERS scores of the coalition and single-agent groups decreased compared with pre-treatment,and the decrease was more significant in the coalition group(P<0.05).After 8 wk of treatment,the levels of NE,DA,5-HT,and SOD in the coalition and single-agent groups increased,while the levels of MDA decreased;the increases and decrease in the coalition group were more significant(P<0.05).The PSQI scores of the coalition and single-agent groups decreased,and the decrease was more significant in the coalition group(P<0.05).CONCLUSION Acupuncture at ghost points combined with paroxetine tablets can safely improve depressive symptoms and sleep disorders,regulate neurotransmitter levels,and reduce stress responses in patients with mild-to-moderate depression.

Statistical distribution of geomechanical properties and‘Sweet Spots’identification in part of the upper Bakken

Completions and Reservoir Quality are two key attributes that are used to characterize nonconventional hydrocarbon assets.This is because,for optimum exploitation of these unconventional assets,horizontal wells need to be drilled in“Sweet Spots”(i.e.,regions where Completions and Reservoir Quality are both superior).One way to quantify these qualities is to use reservoir and geomechanical properties.These properties can be estimated on a location basis from well logs,and then mapped over terrain using geostatistical modeling.This study presents a‘Sweet Spots’identification workflow based on three performance indexes(Storage Potential Index,Brittleness Index,and Horizontal Stress Index)that can be used to quantify CQ and RQ.The performance indexes are computed from petrophysical property volumes(of Young's Modulus,Bulk Modulus,Shear Modulus,Poisson's Ratio,Minimum Horizontal Stress,Volume of Shale,Total Organic Carbon,Thickness,and Porosity)which are in turn computed from well logs and geostatistical simulation.In the end,the study offers a method to compare the predicted“Sweet Spots”against available production data via their correlation coefficient.The resulting reasonable formation property maps,the successful identification of‘Sweet Spots’,and a correlation coefficient of 0.88(between the predicted“Sweet Spots”and well production data)point to the potential of the proposed effort.

Non-invasive water status detection in grapevine(Vitis vinifera L.)by thermography

Grapevines are preferentially grown under mild to moderate water stress conditions to achieve the best compromise between wine quality and quantity.Water status detection for advanced irrigation scheduling is frequently done by predawn leaf water potential(ΨPD)or leaf stomata conductance(gL)measurements.However,these measurements are time and labor consuming.Therefore,the use of infrared thermography(IRT)opens up the possibility to study large population of leaves and to give an overview on the stomatal variation and their dynamics.In the present study IRT was used to identify water stress of potted grapevines.In order to define the sensitivity of IRT measurements to water stress,the IRT-based water status information were compared with simultaneously measuredΨPD and gL data.Correlations between IRT-based CWSI data on the one hand and gL andΨPD on the other showed the potential of IRT for water stress detection.However,the CWSI calculation procedure is laborious and the sensitivity of CWSI for water stress detection still needs to be improved.Therefore,further improvements are necessary in order to apply remote IRT-based systems for irrigation scheduling in the field.

Evaluation of sample scale effect on geomechanical tests

The size of the rock specimen affects the stress concentrates in the vicinity of the top/bottom of the rock specimen during the evaluation of the geomechanical parameters in the laboratory,which causes un-reliable results.However,the appropriate size for geomechanical evaluation is not well understood yet because of limitations in the sampling and analysis.In this study,a series of numerical simulations using a finite element package was conducted to investigate the effect of sample aspect ratio,fluid saturation,and porosity,on the mechanical behavior of the rock under elastic and poroelastic conditions.In addition,two concepts,stress/strain homogeneity index(SHI)and representative elementary volume(REV),were developed to find out the appropriate sample size.The results show that the presence of stiff platens,which are dissimilar to the specimen material,causes significant stress concentration in the two ends of the specimen.The concentration of stress in the specimen reduces when the aspect ratio increases.An optimum aspect ratio(length-to-diameter equal to 3)was observed by SHI analysis which after that the changes in stress concentration are insignificant.The REV size analysis confirms the obtained optimum aspect ratio by SHI analysis.The saturated specimens show a lower magnitude of stress than applied stress because of the presence of pore pressure,which can carry a portion of the stress.The higher void ratio results in lower strength of the specimen.This study could be beneficial for the better design of geomechanical tests to have reliable results.

Renminbi Nominal Effective Exchange Rate for Third Market Competition:An Approach Based on Disaggregated Trade Data

When measuring the nominal effective exchange rate （NEER）, three factors should be considered： direct import competition, direct export competition and third market competuion. The traditional NEER methodology using aggregated export trade data underestimates the competition between countries producing homogeneous goods, so that the weight of the effective exchange rates is too reliant on trade scale. Based on 2002 6-digit items of the Harmonized Commodity Description and Coding System, this paper employs the competitive stress index to adjust the weighting system of the renminbi NEER for third market competition. In the new weighting system, European countries and some emerging economies have higher weights compared with some of the developed countries, including the USA, Japan and resources-dominated eeonomies~ This research will facilitate the understanding of changes in China＇s export competitiveness.