QTL Mapping and Q×E Interactions of Grain Cooking and Nutrient Qualities in Rice Under Upland and Lowland Environments

Grain cooking and nutrient qualities are the most important components of rice （Oryza sativa L.） quality. A doubled haploid （DH） population from a cross between two japonica cultivars was used to examine the phenotypic values and potential QTLs for the quality traits. The cooking and nutrient quality traits, including the amylose content （AC）, the gel consistency （CJC）, the gelatinization temperature （GT）, and the protein content （PC）, in rice grown under upland and lowland environments were evaluated. Significant differences for AC, GC, GT, and PC between upland and lowland environments were detected. The phenotypic values of all four traits were higher under upland environment than lowland environment. The value of PC under upland environment was significantly higher （by 37.9%） than that under lowland environment. This suggests that upland cultivation had large effect on both cooking and nutrient qualifies. A total of seven QTLs and twelve pairs of QTLs were detected to have significant additive and epistatic effects for the four traits. Significant Q x E interaction effects of two QTLs and two pairs of QTLs were also discovered. The general contribution of additive QTLs ranged from 1.91% to 19.77%. The Q × E interactions of QTLs QGt3 and QAc6 accounted for 8.99% and 47.86% of the phenotypic variation, respectively, whereas those of the 2 pairs of epistatic QTLs, QAc6-QAcllb and QAc8-QAc9, accounted for 32.54% and 11.82%, respectively. Five QTLs QGt6b, QGt8, QGt11, QGcl, and QPc2, which had relatively high general contribution and no Q x E interactions, were selected to facilitate the upland rice grain quality breeding.

QTL Analysis of Lodging-related Morphological Traits of Soybean under Two Eco-environments

[Objective] This study is to map QTLs for lodging-related morphological traits of soybean, aiming at providing basis for breeding lodging-resistant varieties. [Method] To map the QTLs for lodging-related morphological traits, an F216-F218 RIL population containing 147 lines derived from a cross between Charleston as female and Dongnong 594 as male parent were used as experimental materials in this study. Totally 164 SSR primers screened out from amplification on two parents, were employed to amplify the F216-F218 RIL population for constructing a genetic linkage map. The QTLs for nodes on main stem, stem thickness and stem weight of the F216-F218 RIL soybean population were investigated in two eco-environments for three years. [Result] Sixteen QTLs for nodes on main stem were detected in A1, B1, C2, Dla, D2, F, G, H and N linkage groups, respectively; Ten QTLs for stem thickness in A1, B1, C2, Dla, E and G linkage groups, respectively; Fifteen QTLs for stem weight in A1, A2, C2, Dla, Dlb and G linkage groups, respectively. Of these QTLs, five for nodes on main stem, one for stem thickness and six for stem weight could be detected by both CIM and MIM, accounting for 8.6%-27.0%, 9.0%- 11.0%, and 6.0%-39.0% of the general phenotypic variation, respectively. From ex- perimental data of two years, Three QTLs for nodes on main stem and two for stem weight could be detected, accounting for 8.0%-60.2% and 10.0%-23.0% of the general phenotypic variation, respectively; while no QTL for stem thickness was re- peatedly detected during more than two years. [Conclusion] Comparison of the QTLs mapped for nodes on main stem, stem thickness and stem weight indicates that these three morphological traits are closely related with lodging-resistance of soybean.

Stability of QTL Across Environments and QTL-by-Environment Interactions for Plant and Ear Height in Maize

Better understanding of genotype-by-environment interaction （GEI） is expected to provide a solid foundation for genetic improvement of crop productivity especially under drought-prone environments. To elucidate the genetic basis of the plant and ear height, 2 F2：3 populations were derived from the crosses of Qi 319 × Huangzaosi （Q/H） and Ye 478 × Huangzaosi （Y/H） with 230 and 235 families, respectively, and their parents were evaluated under 3 diverse environments in Henan, Beijing, and Xinjiang, China during the year of 2007 and 2008, and all the lines were also evaluated under water stress environment. The mapping results showed that a total of 21 and 12 QTLs were identified for plant height in the Q/H and Y/H population, respectively, and 24 and 13 QTLs for ear height, respectively. About 56 and 73% of the QTLs for 2 traits did not present significant QTL-by-environment interaction （QE1） in the normal joint analyses for Q/H and Y/H population, respectively, and about 73% of the QTLs detected did not show significant QEI according to joint analyses for stress condition in Q/H. Most of the detected major QTLs exhibited high stability across different environments. Besides, several major QTLs were detected with large and consistent effect under normal condition （Chr. 6 and 7 in Q/H; Chr. 1, 3 and 9 in Y/H）, or across 2 water regimes （Chr. 1, 8 and 10 for in Q/H）. There were several constitutive QTLs （3 for Q/H and 1 for Y/H） with no or minor QTL-by-environment for the 2 populations. Finally, we found several genomic regions （Chr. 1, 10, etc.） to be co-located across the populations, which could provide useful reference for genetic improvement of these traits in maize breeding programs. Comparative genomic analysis revealed that 3 genes/genetic segments associated with plant height in rice were orthologous to these 3 identified genomic regions carrying the major QTLs for plant and ear height on Chr. 1, 6, and 8, respectively.

QTL mapping for leaf area in maize (Zea mays L.) under multienvironments

Leaves are the main organs of photosynthesis in green plants. Leaf area plays a vital role in dry matter accumulation and grain yield in maize （Zea mays L.）. Thus, investigating the genetic basis of leaf area will aid efforts to breed maize with high yield. In this study, a total of 150 F7 recombinant inbred lines （RILs） derived from a cross between the maize lines Xu 178 and K12 were used to evaluate three ear-leaves area （TELA） under multi-environments. Inclusive composite interval map- ping （ICIM） was used to identify quantitative trait loci （QTLs） for TELA under a single environment and estimated breeding value （EBV）. A total of eight QTLs were detected under a single environmental condition, and four QTLs were identified for EBV which also can be detected in single environment. This indicated that the EBV-detected QTLs have high genetic stability. A major QTL （qTELA_2-9） located in chromosome bin 2.04/2.05 could be detected in four environments and has a high phenotypic contribution rate （ranging from 10.79 to 16.51%） that making it a good target for molecular breeding. In addition, joint analysis was used to reveal the genetic basis of leaf area in six environments. In total, six QTLxenvironment interactions and nine epistatic interactions were identified. Our results reveal that the genetic basis of the leaf area is not only mainly determined by additive effects, but also affected by epistatic effects environmental interaction effects.

Influence of static cartoons combined with dynamic virtual environments on preoperative anxiety of preschool-aged children undergoing surgery

BACKGROUND Preschoolers become anxious when they are about to undergo anesthesia and surgery,warranting the development of more appropriate and effective interventions.AIM To explore the effect of static cartoons combined with dynamic virtual environments on preoperative anxiety and anesthesia induction compliance in preschool-aged children undergoing surgery.METHODS One hundred and sixteen preschool-aged children were selected and assigned to the drug(n=37),intervention(n=40),and control(n=39)groups.All the children received routine preoperative checkups and nursing before being transferred to the preoperative preparation room on the day of the operation.The drug group received 0.5 mg/kg midazolam and the intervention group treatment consisting of static cartoons combined with dynamic virtual environments.The control group received no intervention.The modified Yale Preoperative Anxiety Scale was used to evaluate the children’s anxiety level on the day before surgery(T0),before leaving the preoperative preparation room(T1),when entering the operating room(T2),and at anesthesia induction(T3).Compliance during anesthesia induction(T3)was evaluated using the Induction Compliance Checklist(ICC).Changes in mean arterial pressure(MAP),heart rate(HR),and respiratory rate(RR)were also recorded at each time point.RESULTS The anxiety scores of the three groups increased variously at T1 and T2.At T3,both the drug and intervention groups had similar anxiety scores,both of which were lower than those in the control group.At T1 and T2,MAP,HR,and RR of the three groups increased.The drug and control groups had significantly higher MAP and RR than the intervention group at T2.At T3,the MAP,HR,and RR of the drug group decreased and were significantly lower than those in the control group but were comparable to those in the intervention group.Both the drug and intervention groups had similar ICC scores and duration of anesthesia induction(T3),both of which were higher than those of the control group.CONCLUSION Combining static cartoons with dynamic virtual environments as effective as medication,specifically midazolam,in reducing preoperative anxiety and fear in preschool-aged children.This approach also improve their compliance during anesthesia induction and helped maintain their stable vital signs.

Intrusion Detection System for Smart Industrial Environments with Ensemble Feature Selection and Deep Convolutional Neural Networks

Smart Industrial environments use the Industrial Internet of Things(IIoT)for their routine operations and transform their industrial operations with intelligent and driven approaches.However,IIoT devices are vulnerable to cyber threats and exploits due to their connectivity with the internet.Traditional signature-based IDS are effective in detecting known attacks,but they are unable to detect unknown emerging attacks.Therefore,there is the need for an IDS which can learn from data and detect new threats.Ensemble Machine Learning(ML)and individual Deep Learning(DL)based IDS have been developed,and these individual models achieved low accuracy;however,their performance can be improved with the ensemble stacking technique.In this paper,we have proposed a Deep Stacked Neural Network(DSNN)based IDS,which consists of two stacked Convolutional Neural Network(CNN)models as base learners and Extreme Gradient Boosting(XGB)as the meta learner.The proposed DSNN model was trained and evaluated with the next-generation dataset,TON_IoT.Several pre-processing techniques were applied to prepare a dataset for the model,including ensemble feature selection and the SMOTE technique.Accuracy,precision,recall,F1-score,and false positive rates were used to evaluate the performance of the proposed ensemble model.Our experimental results showed that the accuracy for binary classification is 99.61%,which is better than in the baseline individual DL and ML models.In addition,the model proposed for IDS has been compared with similar models.The proposed DSNN achieved better performance metrics than the other models.The proposed DSNN model will be used to develop enhanced IDS for threat mitigation in smart industrial environments.

Multi-environment BSA-seq using large F3 populations is able to achieve reliable QTL mapping with high power and resolution: An experimental demonstration in rice

Bulked-segregant analysis by deep sequencing(BSA-seq) is a widely used method for mapping QTL(quantitative trait loci) due to its simplicity, speed, cost-effectiveness, and efficiency. However, the ability of BSA-seq to detect QTL is often limited by inappropriate experimental designs, as evidenced by numerous practical studies. Most BSA-seq studies have utilized small to medium-sized populations, with F2populations being the most common choice. Nevertheless, theoretical studies have shown that using a large population with an appropriate pool size can significantly enhance the power and resolution of QTL detection in BSA-seq, with F_(3)populations offering notable advantages over F2populations. To provide an experimental demonstration, we tested the power of BSA-seq to identify QTL controlling days from sowing to heading(DTH) in a 7200-plant rice F_(3)population in two environments, with a pool size of approximately 500. Each experiment identified 34 QTL, an order of magnitude greater than reported in most BSA-seq experiments, of which 23 were detected in both experiments, with 17 of these located near41 previously reported QTL and eight cloned genes known to control DTH in rice. These results indicate that QTL mapping by BSA-seq in large F_(3)populations and multi-environment experiments can achieve high power, resolution, and reliability.

Naturalized Decorations for HSCT Ward Environments at Peking University First Hospital

The haematopoietic stem cell transplantation(HSCT)ward serves as a temporary residence for patients following their surgical procedures,necessitating adherence to rigorous aseptic standards.However,the current atmosphere within these wards frequently contributes to feelings of depression among patients.Research indicates that a restorative environment has the potential to alleviate negative emotional states in individuals.This study utilized the HSCT ward of Peking University First Hospital as a case study to examine the decorative preferences.This investigation was conducted through a questionnaire that was informed by the patients’inherent preferences and insights derived from research on restorative environments.The results indicated that the incorporation of floral decorations,particularly those resembling sunflowers,in ward corridors,communal activity areas,and walls can significantly enhance patients’sense of hope.Additionally,it is essential to improve the environmental visual experience in the nurses’lounge and demonstration rooms for medical staff.

Semi-supervised learning based hybrid beamforming under time-varying propagation environments

Hybrid precoding is considered as a promising low-cost technique for millimeter wave(mm-wave)massive Multi-Input Multi-Output(MIMO)systems.In this work,referring to the time-varying propagation circumstances,with semi-supervised Incremental Learning(IL),we propose an online hybrid beamforming scheme.Firstly,given the constraint of constant modulus on analog beamformer and combiner,we propose a new broadnetwork-based structure for the design model of hybrid beamforming.Compared with the existing network structure,the proposed network structure can achieve better transmission performance and lower complexity.Moreover,to enhance the efficiency of IL further,by combining the semi-supervised graph with IL,we propose a hybrid beamforming scheme based on chunk-by-chunk semi-supervised learning,where only few transmissions are required to calculate the label and all other unlabelled transmissions would also be put into a training data chunk.Unlike the existing single-by-single approach where transmissions during the model update are not taken into the consideration of model update,all transmissions,even the ones during the model update,would make contributions to model update in the proposed method.During the model update,the amount of unlabelled transmissions is very large and they also carry some information,the prediction performance can be enhanced to some extent by these unlabelled channel data.Simulation results demonstrate the spectral efficiency of the proposed method outperforms that of the existing single-by-single approach.Besides,we prove the general complexity of the proposed method is lower than that of the existing approach and give the condition under which its absolute complexity outperforms that of the existing approach.

Impact of typical environments in China’s western mountainous areas on the durability of railway concrete:a review

Purpose–This study aims to analyze the impact mechanism of typical environments in China’s western mountainous areas on the durability of railway concrete and propose measures to improve durability.Design/methodology/approach–With the continuous promotion of infrastructure construction,the focus of China’s railway construction has gradually shifted to the western region.The four typical environments of large temperature differences,strong winds and dryness,high cold and low air pressure unique to the western mountainous areas of China have adverse effects on the durability of typical railway structure concrete(bridges,ballastless tracks and tunnels).This study identified the characteristics of four typical environments in the western mountainous areas of China through on-site research.The impact mechanism of the four typical environments on the durability of concrete in different structural parts of railways has been explored through theoretical analysis and experimental research;Finally,a strategy for improving the durability of railway concrete suitable for the western mountainous areas of China was proposed.Findings–The daily temperature difference in the western mountainous areas of China is more than twice that of the plain region,which will lead to significant temperature deformation and stress in the multi-layered structure of railway ballastless tracks.It will result in cracking.The wind speed in the western plateau region is about 2.5 to 3 times that of the plain region,and the average annual rainfall is only 1/5 of that in the plain region.The drying effect on the surface of casting concrete will significantly accelerate its cracking process,leading to serious durability problems.The environmental temperature in the western mountainous areas of China is generally low,and there are more freeze-thaw cycles,which will increase the risk of freeze-thaw damage to railway concrete.The environmental air pressure in the western plateau region is only 60%of that in the plain region.The moisture inside the concrete is more likely to diffuse into the surrounding environment under the pressure difference,resulting in greater water loss and shrinkage deformation of the concrete in the plateau region.The above four issues will collectively lead to the rapid deterioration of concrete durability in the western plateau region.The corresponding durability improvement suggestions from theoretical research,new technology development and standard system was proposed in this paper.Originality/value–The research can provide the mechanism of durability degradation of railway concrete in the western mountainous areas of China and corresponding improvement strategies.

Distribution and geochemical significance of alkylbenzenes for crude oil with different depositional environments and thermal maturities

A total of 45 alkylbenzenes were detected and identified in crude oils with different depositional environments and thermal maturities from the Tarim Basin,Beibuwan Basin,and Songliao Basin using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry(GC×GCTOFMS).By analyzing the distribution characteristics of C0-C5alkylbenzenes,it is found that the content of some alkylbenzenes varies greatly in crude oils.Based on the distribution characteristics of 1,2,4,5-tetramethylbenzene(Te MB)and 1,2,3,4-Te MB,the ratio of 1,2,4,5-Te MB to 1,2,3,4-Te MB is proposed to indicate the organic matter origin and depositional environment of ancient sediments.Oil samples originated mainly from lower hydrobiont,algae,bacteria and source rocks deposited under reducing/anoxic conditions have low 1,2,4,5-/1,2,3,4-Te MB values(less than 0.6),while oil samples originated mainly from terrestrial higher plants and source rocks deposited under oxic/sub-oxic conditions have higher 1,2,4,5-/1,2,3,4-Te MB values(greater than 1.0).The significant difference of 1,2,4,5-/1,2,3,4-Te MB values is controlled by 1,2,4,5-Te MB content.1,2,4,5-Te MB content in oils derived from source rocks deposited in oxidized sedimentary environment(greater than 1.0 mg/g whole oil)is higher than that in oils from source rocks deposited in reduced sedimentary environment(less than 1.0 mg/g whole oil).1,2,4,5-/1,2,3,4-Te MB ratio might not or slightly be affected by evaporative fractionation,biodegradation and thermal maturity.1,2,4,5-/1,2,3,4-Te MB ratio and 1,2,4,5-Te MB content can be used as supplementary parameter for the identification of sedimentary environment and organic matter input.It should be noted that compared to the identification of organic matter sources,the 1,2,4,5-/1,2,3,4-Te MB parameter is more effective in identifying sedimentary environments.

Tomato detection method using domain adaptive learning for dense planting environments

This study aimed to address the challenge of accurately and reliably detecting tomatoes in dense planting environments,a critical prerequisite for the automation implementation of robotic harvesting.However,the heavy reliance on extensive manually annotated datasets for training deep learning models still poses significant limitations to their application in real-world agricultural production environments.To overcome these limitations,we employed domain adaptive learning approach combined with the YOLOv5 model to develop a novel tomato detection model called as TDA-YOLO(tomato detection domain adaptation).We designated the normal illumination scenes in dense planting environments as the source domain and utilized various other illumination scenes as the target domain.To construct bridge mechanism between source and target domains,neural preset for color style transfer is introduced to generate a pseudo-dataset,which served to deal with domain discrepancy.Furthermore,this study combines the semi-supervised learning method to enable the model to extract domain-invariant features more fully,and uses knowledge distillation to improve the model's ability to adapt to the target domain.Additionally,for purpose of promoting inference speed and low computational demand,the lightweight FasterNet network was integrated into the YOLOv5's C3 module,creating a modified C3_Faster module.The experimental results demonstrated that the proposed TDA-YOLO model significantly outperformed original YOLOv5s model,achieving a mAP(mean average precision)of 96.80%for tomato detection across diverse scenarios in dense planting environments,increasing by 7.19 percentage points;Compared with the latest YOLOv8 and YOLOv9,it is also 2.17 and 1.19 percentage points higher,respectively.The model's average detection time per image was an impressive 15 milliseconds,with a FLOPs(floating point operations per second)count of 13.8 G.After acceleration processing,the detection accuracy of the TDA-YOLO model on the Jetson Xavier NX development board is 90.95%,the mAP value is 91.35%,and the detection time of each image is 21 ms,which can still meet the requirements of real-time detection of tomatoes in dense planting environment.The experimental results show that the proposed TDA-YOLO model can accurately and quickly detect tomatoes in dense planting environment,and at the same time avoid the use of a large number of annotated data,which provides technical support for the development of automatic harvesting systems for tomatoes and other fruits.

Changes in human settlement environments and their drivers in valley cities located in arid and semi-arid regions:A case study of Lanzhou in Western China

Development of urban human settlement environments(HSEs)is an integral part of promoting high-quality and sustainable regional development and constructing a beautiful China.The city of Lanzhou,located at the geometric center of China,is the only provincial capital traversed by the Yellow River.Given the constraints posed by the valley topography and the need for economic development,the development of this HSE,which is located within an arid region,poses considerable challenges.Evidently,an understanding of the evolution of HSEs and drivers of changes in them contributes to high-quality,sustainable urban development in arid and semi-arid regions.An analytical model was developed using the parameters of relief degree of land surface,human comfort days,the land cover index,nighttime light index,and precipitation.This model was used in combination with population density and the gross domestic product to analyze the spatial distribution of Lanzhou's HSE and its drivers.The results showed that landscapes in Lanzhou underwent significant changes between 2000 and 2022,with an increase in building-up land(+0.946%),cultivated land(+0.134%),and forest land(+0.018%)and a decrease in grassland(-1.10%).There was significant outward expansion of the main urban zone of Lanzhou and of various county towns,with the increase in building-up land being most prominent.During this period,there were significant changes in the periphery of the core urban area and county towns in Lanzhou,with decreases moving from the urban center(the highest value)to the surrounding areas(Yongdeng County had the lowest value).The correlation between the HSE and population density grew stronger in Anning and Chengguan Districts but became weaker in Xigu and Qilihe Districts.Spatiotemporal variations in the HSE were primarily caused by climate change,followed by human activities,and were also influenced by the valley topography.Overall,the spatial distribution of population density and the HSE in Lanzhou demonstrated good consistency under the in-fluence of economic development and urbanization.

Effects of virtual agents on interaction efficiency and environmental immersion in MR environments

Background Physical entity interactions in mixed reality(MR)environments aim to harness human capabilities in manipulating physical objects,thereby enhancing virtual environment(VEs)functionality.In MR,a common strategy is to use virtual agents as substitutes for physical entities,balancing interaction efficiency with environmental immersion.However,the impact of virtual agent size and form on interaction performance remains unclear.Methods Two experiments were conducted to explore how virtual agent size and form affect interaction performance,immersion,and preference in MR environments.The first experiment assessed five virtual agent sizes(25%,50%,75%,100%,and 125%of physical size).The second experiment tested four types of frames(no frame,consistent frame,half frame,and surrounding frame)across all agent sizes.Participants,utilizing a head mounted display,performed tasks involving moving cups,typing words,and using a mouse.They completed questionnaires assessing aspects such as the virtual environment effects,interaction effects,collision concerns,and preferences.Results Results from the first experiment revealed that agents matching physical object size produced the best overall performance.The second experiment demonstrated that consistent framing notably enhances interaction accuracy and speed but reduces immersion.To balance efficiency and immersion,frameless agents matching physical object sizes were deemed optimal.Conclusions Virtual agents matching physical entity sizes enhance user experience and interaction performance.Conversely,familiar frames from 2D interfaces detrimentally affect interaction and immersion in virtual spaces.This study provides valuable insights for the future development of MR systems.

Protected simultaneous quantum remote state preparation scheme by weak and reversal measurements in noisy environments

We discuss a quantum remote state preparation protocol by which two parties, Alice and Candy, prepare a single-qubit and a two-qubit state, respectively, at the site of the receiver Bob. The single-qubit state is known to Alice while the two-qubit state which is a non-maximally entangled Bell state is known to Candy. The three parties are connected through a single entangled state which acts as a quantum channel. We first describe the protocol in the ideal case when the entangled channel under use is in a pure state. After that, we consider the effect of amplitude damping(AD) noise on the quantum channel and describe the protocol executed through the noisy channel. The decrement of the fidelity is shown to occur with the increment in the noise parameter. This is shown by numerical computation in specific examples of the states to be created. Finally, we show that it is possible to maintain the label of fidelity to some extent and hence to decrease the effect of noise by the application of weak and reversal measurements. We also present a scheme for the generation of the five-qubit entangled resource which we require as a quantum channel. The generation scheme is run on the IBMQ platform.

Passive IoT Localization Technology Based on SD-PDOA in NLOS and Multi-Path Environments

Addressing the challenges of passive Radio Frequency Identification(RFID)indoor localization technology in Non-Line-of-Sight(NLoS)and multipath environments,this paper presents an innovative approach by introducing a combined technology integrating an improved Kalman Filter with Space Domain Phase Difference of Arrival(SD-PDOA)and Received Signal Strength Indicator(RSSI).This methodology utilizes the distinct channel characteristics in multipath and NLoS contexts to effectively filter out interference and accurately extract localization information,thereby facilitating high precision and stability in passive RFID localization.The efficacy of this approach is demonstrated through detailed simulations and empirical tests conducted on a custom-built experimental platform consisting of passive RFID tags and an R420 reader.The findings are significant:in NLoS conditions,the four-antenna localization system achieved a notable localization accuracy of 0.25 m at a distance of 5 m.In complex multipath environments,this system achieved a localization accuracy of approximately 0.5 m at a distance of 5 m.When compared to conventional passive localization methods,our proposed solution exhibits a substantial improvement in indoor localization accuracy under NLoS and multipath conditions.This research provides a robust and effective technical solution for high-precision passive indoor localization in the Internet of Things(IoT)system,marking a significant advancement in the field.

Influences of different alkaline and acidic diagenetic environments on diagenetic evolution and reservoir quality of alkaline lake shales

Thin section and argon-ion polishing scanning electron microscope observations were used to analyze the sedimentary and diagenetic environments and main diagenesis of the Permian Fengcheng Formation shales in different depositional zones of Mahu Sag in the Junggar Basin,and to reconstruct their differential diagenetic evolutional processes.The diagenetic environment of shales in the lake-central zone kept alkaline,which mainly underwent the early stage(Ro<0.5%)dominated by the authigenesis of Na-carbonates and K-feldspar and the late stage(Ro>0.5%)dominated by the replacement of Na-carbonates by reedmergnerite.The shales from the marginal zone underwent a transition from weak alkaline to acidic diagenetic environments,with the early stage dominated by the authigenesis of Mg-bearing clay and silica and the late stage dominated by the dissolution of feldspar and carbonate minerals.The shales from the transitional zone also underwent a transition from an early alkaline diagenetic environment,evidenced by the formation of dolomite and zeolite,to a late acidic diagenetic environment,represented by the reedmergnerite replacement and silicification of feldspar and carbonate minerals.The differences in formation of authigenic minerals during early diagenetic stage determine the fracability of shales.The differences in dissolution of minerals during late diagenetic stage control the content of free shale oil.Dolomitic shale in the transitional zone and siltstone in the marginal zone have relatively high content of free shale oil and strong fracability,and are favorable“sweet spots”for shale oil exploitation and development.

Impact of Outdoor Activities in Different Landscape Environments on the Physical and Mental Health of College Students

To investigate whether outdoor activities have an improvement effect on the emotions of young people and the differences in the impact of outdoor activities on the emotions of young people under different landscape environmental conditions,the participating students are asked to engage in outdoor activities in different landscape environments and divided into four groups.Each group is assigned to engage in outdoor activities in four types of landscape areas:open lawn area,low shrub area,dense forest area,and waterfront area.The activities include outdoor yoga and making leaf mandalas.The results show that outdoor yoga has the best effect on reducing pulse and blood pressure and regulating emotions in open lawn area and waterfront area,followed by leaf mantras in waterfront area and outdoor yoga in dense forest area.However,both activities have no significant effect in low shrub area.

Cold environments and human metabolism: A traditional chinese medicine perspective

The concept of Traditional Chinese Medicine(TCM)emphasizes the intrinsic connection between human beings and nature,positing that the human body undergoes distinct physiological changes in response to various natural environments.Cold,as a primary external factor in cold areas,necessitates the body's autonomous adaptation to uphold optimal living conditions.The repercussions of cold on the body are both far-reaching and profound,with metabolic equilibrium adjustments playing a pivotal role.This article,rooted in the TCM principle of Yin-Yang balance,delves into the metabolic intricacies and adaptive responses to the human body in cold environments.The effects manifest in heat-producing tissues,systemic substance consumption,the blood substance concentrations,liver function,and metabolic rhythms.The article subsequently presents TCM recommendations for maintaining health in cold climates.It concludes by advocating the exploration of metabolic homeostasis changes as a key avenue for investigating the metabolic traits s of populations in cold regions.We posit that such insights will enhance comprehension of the metabolic shifts in cold region populations and advance the evolution of regional medicine.

QTL Analysis of Some Agronomic Traits in Rice Under Different Growing Environments

The culm length, panicle length, spikelets per panicle and panicle exsertion were evaluated by using F2：3 population including 200 lines derived from the cross of indica and japonica Milyang 23/Jileng 1 under five different environments of Beijing （natural normal growing environment）, Kunming （natural cold environment）, Gongzhuling of China （cold water irrigation） and Chuncheon of Korea （natural normal growing environment and cold water irrigation）, and QTLs of these traits were analyzed by using SSR markers. The results showed that 44 QTLs related to these agronomic traits were detected under five different growing environments, and these QTLs have been located on 11 chromosomes except chromosome 9. The QTLs for qCLla, qCL1b, qCL5a, qCL6b, qPLla, qPL3a, qPL6b, qPL6c, qPL7b, qSP8b, qSPlc, qSP11a, qSP12, and qPE1 have been detected under more than two growing environments, and those that were little affected by environments, were stable QTLs. Among them, qCLla, qCLlb, qPLla, qSPlc, and qPE1 explained 24.2-55.2%, 22.7-39.9%, 12.5-27.7%, 14.4-33.5%, and 26.6-28.7% of observed phynotypic variation, respectively, which were major genes mainly appearing as overdominance. These QTLs cause the increase in action to culm length, panicle length, spikelets per panicle, and panicle exsertion under cold environment, showing that these QTLs were correlated with cold tolerance.