Quantitative characterizations of anisotropic dynamic properties in organic-rich shale with different kerogen content

Understanding the quantitative responses of anisotropic dynamic properties in organic-rich shale with different kerogen content(KC)is of great significance in hydrocarbon exploration and development.Conducting controlled experiments with a single variable is challenging for natural shales due to their high variations in components,diagenesis conditions,or pore fluid.We employed the hot-pressing technique to construct 11 well-controlled artificial shale with varying KC.These artificial shale samples were successive machined into prismatic shape for ultrasonic measurements along different directions.Observations revealed bedding perpendicular P-wave velocities are more sensitive to the increasing KC than bedding paralleling velocities due to the preferential alignments of kerogen.All elastic stiffnesses except C_(13)are generally decreasing with the increasing KC,the variation of C_(1) and C_(33)on kerogen content are more sensitive than those of C_(44)and C_(66).Apparent dynamic mechanical parameters(v and E)were found to have linear correlation with the true ones from complete anisotropic equations independent of KC,which hold value towards the interpretation of well logs consistently across formations,Anisotropic mechanical parameters(ΔE and brittlenessΔB)tend to decrease with the reducing KC,withΔB showing great sensitivity to KC variations.In the range of low KC(<10%),the V_(P)/V_(S) ratio demonstrated a linearly negative correlation with KC,and the V_(P)/V_(S) ratio magnitude of less than 1.75may serve as a significant characterization for highly organic-rich(>10%)shale,compilation of data from natural organic rich-shales globally verified the similar systematic relationships that can be empirically used to predict the fraction of KC in shales.

Longitudinal dependence of the forecast accuracy of the ionospheric total electron content in the equatorial zone

The longitudinal dependence of the behavior of ionospheric parameters has been the subject of a number of works where significant variations are discovered.This also applies to the prediction of the ionospheric total electron content(TEC),which neural network methods have recently been widely used.However,the results are mainly presented for a limited set of meridians.This paper examines the longitudinal dependence of the TEC forecast accuracy in the equatorial zone.In this case,the methods are used that provided the best accuracy on three meridians:European(30°E),Southeastern(110°E)and American(75°W).Results for the stations considered are analyzed as a function of longitude using the Jet Propulsion Laboratory Global Ionosphere Map(JPL GIM)for 2015.These results are for 2 h ahead and 24 h ahead forecast.It was found that in this case,based on the metric values,three groups of architectures can be distinguished.The first group included long short-term memory(LSTM),gated recurrent unit(GRU),and temporal convolutional networks(TCN)models as a part of unidirectional deep learning models;the second group is based on the recurrent models from the first group,which were supplemented with a bidirectional algorithm,increasing the TEC forecasting accuracy by 2-3 times.The third group,which includes the bidirectional TCN architecture(BiTCN),provided the highest accuracy.For this architecture,according to data obtained for 9 equatorial stations,practical independence of the TEC prediction accuracy from longitude was observed under the following metrics(Mean Absolute Error MAE,Root Mean Square Error RMSE,Mean Absolute Percentage Error MAPE):MAE(2 h)is 0.2 TECU approximately;MAE(24 h)is 0.4 TECU approximately;RMSE(2 h)is less than 0.5 TECU except Niue station(RMSE(2 h)is 1 TECU approximately);RMSE(24 h)is in the range of 1.0-1.7 TECU;MAPE(2 h)<1%except Darwin station,MAPE(24 h)<2%.This result was confirmed by data from additional 5 stations that formed latitudinal chains in the equatorial part of the three meridians.The complete correspondence of the observational and predicted TEC values is illustrated using several stations for disturbed conditions on December 19-22,2015,which included the strongest magnetic storm in the second half of the year(min Dst=-155 nT).

Multi-omics analysis reveals the pivotal role of phytohormone homeostasis in regulating maize grain water content

Grain water content(GWC)is a key determinant for mechanical harvesting of maize(Zea mays).In our previous research,we identified a quantitative trait locus,qGWC1,associated with GWC in maize.Here,we examined near-isogenic lines(NILs)NILL and NILH that differed at the qGWC1 locus.Lower GWC in NILL was primarily attributed to reduced grain water weight(GWW)and smaller fresh grain size,rather than the accumulation of dry matter.The difference in GWC between the NILs became more pronounced approximately 35 d after pollination(DAP),arising from a faster dehydration rate in NILL.Through an integrated analysis of the transcriptome,proteome,and metabolome,coupled with an examination of hormones and their derivatives,we detected a marked decrease in JA,along with an increase in cytokinin,storage forms of IAA(IAA-Glu,IAA-ASP),and IAA precursor IPA in immature NILL kernels.During kernel development,genes associated with sucrose synthases,starch biosynthesis,and zein production in NILL,exhibited an initial up-regulation followed by a gradual down-regulation,compared to those in NILH.This discovery highlights the crucial role of phytohormone homeostasis and genes related to kernel development in balancing GWC and dry matter accumulation in maize kernels.

TLC Identification of Yao Medicine Pileostegia tomentellal and Extraction Technology and Content Determination of Umbelliferone

[Objectives]To establish a TLC and content determination method of Pileostegia tomentellal,with umbelliferone as the indicator component.[Methods]TLC identification was performed by silica gel G thin layer plate with n-hexane-ethyl acetate(4:3)as the developing agent,and the plate was examined by UV lamp(365 nm).The umbelliferone content was determined by HPLC:Inertsil ODS-3 C 18 column(4.60 mm×250 mm,5μm);mobile phase acetonitrile-0.2%phosphoric acid gradient elution;detection wavelength 320 nm,flow rate 1.0 mL/min,column temperature 30℃,injection volume 10μL.[Results]The chromatogram of P.tomentellal showed the same color spot in the same position as that of reference medicinal material,and the spot was clear with good specificity.Umbelliferone showed a good linear relationship when the injection volume was 2.63-131.27μg/mL(R^(2)=0.9997).The average recovery of umbelliferone in the low,middle and high adding groups of P.tomentellal was 99.57%and the RSD was 2.15%.[Conclusions]The method can effectively identify Yao medicine P.tomentellal and accurately determine the content of umbelliferone in medicinal materials,which will provide a scientific basis for the development and utilization of medicinal resources of Yao medicine P.tomentellal.

Estimation of unfrozen water content of saturated sandstones using nuclear magnetic resonance, mercury intrusion porosimetry, and ultrasonic tests

The unfrozenwater content(UWC)is a crucial parameter that affects the strength and thermal properties of rocks in relation to engineering construction and geological disasters in cold regions.In this study,three different methods were employed to test and estimate the UWC of saturated sandstones,including nuclear magnetic resonance(NMR),mercury intrusion porosimetry(MIP),and ultrasonic methods.The NMR method enabled the direct measurement of the UWC of sandstones using the free induction decay(FID).The MIP method was used to analyze the pore structures of sandstones,with the UWC subsequently calculated based on pore ice crystallization.Therefore,the MIP test constituted an indirect measurement method.Furthermore,a correlation was established between the P-wave velocity and the UWC of these sandstones based on the mixture theory,which could be employed to estimate the UWC as an empirical method.All methods demonstrated that the UWC initially exhibited a rapid decrease from 0C to5C and then generally became constant beyond20C.However,these test methods had different characteristics.The NMR method was used to directly and accurately calculate the UWC in the laboratory.However,the cost and complexity of NMR equipment have precluded its use in the field.The UWC can be effectively estimated by the MIP test,but the estimation accuracy is influenced by the ice crystallization process and the pore size distribution.The P-wave velocity has been demonstrated to be a straightforward and practical empirical parameter and was utilized to estimate the UWC based on the mixture theory.This method may be more suitable in the field.All methods confirmed the existence of a hysteresis phenomenon in the freezing-thawing process.The average hysteresis coefficient was approximately 0.538,thus validating the GibbseThomson equation.This study not only presents alternative methodologies for estimating the UWC of saturated sandstones but also contribute to our understanding of the freezing-thawing process of pore water.

Exploration of the efficacy and mechanism of treating head wind disease with the combination change of ginger volatile oil and gingerol by using content-weighted network pharmacology technology

Background:Exploring the efficacy,potential components,and mechanism of the combination of ginger essential oil and gingerols in the treatment of head wind disease based on network pharmacology technology with content weight.Methods:The experimental groups were divided into:0:10,1:4,1:2,1:1,2:1,4:1,10:0.The relative content(Ri)of the chemical constituents of ginger's volatile oil was determined using gas chromatography-mass spectrometry(GC-MS).Additionally,the physicochemical and biological property parameters(LogP,MDCK,PPB,MW)of the components were considered.To assess the quantitative effect of the components,a grading score was performed,and the quantitative effect index(Ki)was calculated.Subsequently,the target effect index(Ti)was calculated by combining the component-target matching score(Fit score).Using these calculations,the target effect score A was determined under the influence of multiple components targeting different targets.Key targets with A≥1000 were identified.To predict the targets related to head wind disease,the Comparative Toxicogenomics Database(https://ctdbase.org/),Gene Cards(https://www.genecards.org/),and Disgenet database(https://www.disgenet.org/)were utilized.The key targets,obtained from different proportions of ginger's volatile oil and gingerol,were intersected with the predicted targets.This facilitated network pharmacological analysis and verification of the efficacy.Results:The content of volatile oil in ginger demonstrated an impact on key targets associated with the volatile oil group.Each specific combination of volatile oil consistently activated distinct pathways,with variations stemming from changes in content.Experimental testing revealed that different combinations of ginger's volatile oil and gingerol effectively alleviated migraine symptoms in rats.Conclusion:Through the application of content-weighted network pharmacology technology and pharmacodynamic verification,it was determined that altering the ratio between ginger's volatile oil and gingerol leads to variations in potential targets and pathways,consequently impacting its efficacy.

Mechanical properties and acoustic emission characteristics of soft rock with different water contents under dynamic disturbance

Uniaxial compression tests and cyclic loading acoustic emission tests were conducted on 20%,40%,60%,80%,dry and saturated muddy sandstone by using a creep impact loading system to investigate the mechanical properties and acoustic emission characteristics of soft rocks with different water contents under dynamic disturbance.The mechanical properties and acoustic emission characteristics of muddy sandstones at different water contents were analysed.Results of experimental studies show that water is a key factor in the mechanical properties of rocks,softening them,increasing their porosity,reducing their brittleness and increasing their plasticity.Under uniaxial compression,the macroscopic damage characteristics of the muddy sandstone change from mono-bevel shear damage and‘X’type conjugate bevel shear damage to a roadway bottom-drum type damage as the water content increases.Dynamic perturbation has a strengthening effect on the mechanical properties of samples with 60%and less water content,and a weakening effect on samples with 80%and more water content,but the weakening effect is not obvious.Macroscopic damage characteristics of dry samples remain unchanged,water samples from shear damage and tensile–shear composite damage gradually transformed into cleavage damage,until saturation transformation monoclinic shear damage.The evolution of acoustic emission energy and event number is mainly divided into four stages:loading stage(Ⅰ),dynamic loading stage(Ⅱ),yield failure stage(Ⅲ),and post-peak stage(Ⅳ),the acoustic emission characteristics of the stages were different for different water contents.The characteristic value of acoustic emission key point frequency gradually decreases,and the damage degree of the specimen increases,corresponding to low water content—high main frequency—low damage and high water content—low main frequency—high damage.

Prevalence of Malnutrition and Anaemia in Children ≤ 5 Years of Age in Some Conflict Hit Areas of Meme Division of the South West Region of Cameroon

Malnutrition refers to the deficiency, imbalances, or excesses in a person’s intake of energy or nutrients [1]. Khan defines anaemia as below level of Haemoglobin in red blood shown by a lower number of functioning red blood cells [2]. The crisis in the North West and South West Regions of Cameroon has led to several negative effects on children’s living conditions. There has been an increase in malnutrition and anaemia in the South West Region and Kumba in particular. The main objective of this study was “to examine the prevalence of malnutrition and anaemia in children ≤ 5 years of age in some conflict-hit areas of Meme Division”. A descriptive cross-sectional study was conducted in 2023 from March to June. We recruited 200 children ≤ 5 years into the study from three hospitals. The regional hospital annex in Kumba, Presbyterian General Hospital Kumba and the Ntam Hospital in Kumba. Socio-demographic factors were assessed using questionnaire, nutritional status was assessed by the use anthropometric measurements and an auto haematology analyser was used to determine anaemia. The overall prevalence of malnutrition in the study area was 40.5%. The prevalence of malnutrition varied significantly (P < 0.001) with the study sites. The overall prevalence of anaemia in the study area was 70.5%. The prevalence of anaemia was not significantly associated with the study sites. The prevalence of Malnutrition and Anaemia in children ≤ 5 years of age is very high in the Kumba municipalities. This could be attributed to the ongoing crisis which has caused a lot of social migrations from rural areas to Urban areas which are safer.

Mental Health Consequences among Sudanese Due to the Armed Conflicts and Civil Unrest of 2023: One Year Later

Aim: To investigate depression, anxiety, PTSD, and insomnia levels among Sudanese citizens after a year has passed since the start of Armed Forces conflict in Sudan. Methods: An online survey was distributed. It is composed of five parts, covering the following areas: 1) sociodemographic data;2) depression assessment;3) generalized anxiety disorder assessment;4) post-traumatic stress disorder assessment;and 5) insomnia assessment. Statistical Package for Social Sciences version 27 was used for data analysis;frequency and percentage were used to describe the qualitative variables. Spearman’s correlation analysis and Chi-square test were used for correlation and association analysis;a P-value equal to or less than 0.05 was considered statistically significant. Results: The study included 283 participants, primarily female (76.0%), with a mean age of 35.26 ± 6.96 years. The majority of participants were married (50.5%) and had a university level of education (50.2%). At the start of the war, 70.3% of participants were inside the war zones, and at the time of data collection, 73.5% were outside Sudan. The length of stay in the war zone ranged from 1 to 300 days, with a mean of 48.59 ± 70.284 days. Additionally, 63.3% of participants stated that they did not receive any form of mental health intervention, and the remaining did not provide an answer. There was a high prevalence of moderate-severe depression (50.5%), moderate anxiety (35.3%), PTSD (56.5%), and sub-threshold insomnia (53.4%) among the participants. Correlation analyses revealed associations between demographic factors such as sex, age, marital status, and education and mental health issues. Notably, female participants showed a higher prevalence of PTSD (53.0%) compared to male participants (67.6%). Conclusions: There is a substantial impact of war-related trauma on mental health, revealing a high prevalence of moderate-severe depression, moderate anxiety, PTSD, and sub-threshold insomnia among the participants. This emphasizes the importance of tailored interventions and support systems to address the unique needs of individuals affected by war trauma.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.However,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content delivery.This challenge can be eased by sinking some critical content from cloud to edge.In this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new challenges.This work focuses on establishing a highly efficient content delivery framework in the IoE environment.In particular,the IoE environment is re-constructed as an end-edge-cloud collaborative system,in which the concept of digital twin is applied to promote the collaboration.Based on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)model.Then,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)technology.Finally,a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead.The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.

Surface and Content Validity of the Mentoring Function Scale for Novice Nurses

This study aimed to examine the surface and content validity of the Mentoring Function Scale for Novice Nurses, used to assess the mentoring of entry-level nurses, and to refine the scale items. In Study 1, six nurse education researchers, selected using convenience sampling, with five or more years of nursing experience and experience teaching novice nurses, were invited to an expert meeting in July 2015. A group interview was conducted that lasted approximately 120 minutes. Study 2 examined the content validity index. Between September and November 2015, we distributed a self-administered questionnaire survey to 11 participants selected by convenience sampling. The participants included five nurse education researchers with a minimum of five years of nursing experience and experience teaching novice nurses, as well as six clinical nurses with a master’s degree or higher. Finally, 81 questionnaire items were retained from the initial 125 items. The 81-item Mentoring Function Scale for Novice Nurses had higher content validity than the original scale. To further increase the scale’s applicability, future studies should assess its reliability, construct validity, and criterion-related validity.

The Caching and Pricing Strategy for Information-Centric Networking with Advertisers’Participation

As users’access to the network has evolved into the acquisition of mass contents instead of IP addresses,the IP network architecture based on end-to-end communication cannot meet users’needs.Therefore,the Information-Centric Networking(ICN)came into being.From a technical point of view,ICN is a promising future network architecture.Researching and customizing a reasonable pricing mechanism plays a positive role in promoting the deployment of ICN.The current research on ICN pricing mechanism is focused on paid content.Therefore,we study an ICN pricing model for free content,which uses game theory based on Nash equilibrium to analysis.In this work,advertisers are considered,and an advertiser model is established to describe the economic interaction between advertisers and ICN entities.This solution can formulate the best pricing strategy for all ICN entities and maximize the benefits of each entity.Our extensive analysis and numerical results show that the proposed pricing framework is significantly better than existing solutions when it comes to free content.

Selection and application of four QTLs for grain protein content in modern wheat cultivars

The grain protein content(GPC)is the key parameter for wheat grain nutritional quality.This study conducted a resampling GWAS analysis using 406 wheat accessions across eight environments,and identified four previously reported GPC QTLs.An analysis of 87 landraces and 259 modern cultivars revealed the loss of superior GPC haplotypes,especially in Chinese cultivars.These haplotypes were preferentially adopted in different agroecological zones and had broad effects on wheat yield and agronomic traits.Most GPC QTLs did not significantly reduce yield,suggesting that high GPC can be achieved without a yield penalty.The results of this study provide a reference for future GPC breeding in wheat using the four identified QTLs.

A Study on the Correlation between Salivary Cortisol Content and Anxiety and Depression in Pregnant and Postpartum Women

Objective: To analyze the correlation between salivary cortisol content and anxiety and depression in pregnant and postpartum women. Method: 300 pregnant and postpartum women who were admitted from January 2021 to December 2021 were selected as the research subjects. They were all tested with the Hamilton Anxiety Scale (HAMA) and the Edinburgh Postnatal Depression Scale (EPDS). 40 pregnant women with anxiety and depression were selected as the observation group, and 50 normal pregnant women were selected as the control group, adopting logistic regression analysis to investigate the correlation between salivary cortisol and postpartum anxiety and depression during pregnancy. Result: The salivary cortisol levels in the observation group were significantly higher than those in the control group before bedtime, after waking up the next day, 15 minutes after waking up, 30 minutes after waking up, 60 minutes after waking up, and 1 hour before lunch (p < 0.05). Maternal depression and anxiety were not related to age, weight, gestational age, negative events, or history of adverse pregnancy and childbirth (p > 0.05). Maternal depression and anxiety are closely related to salivary cortisol levels and educational background (p Conclusion: There is a close correlation between anxiety and depression and an increase in cortisol levels, suggesting that the salivary cortisol awakening response during pregnancy has a predictive effect on the occurrence of postpartum depression.

Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system

Upper ocean heat content(OHC)has been widely recognized as a crucial precursor to high-impact climate variability,especially for that being indispensable to the long-term memory of the ocean.Assessing the predictability of OHC using state-of-the-art climate models is invaluable for improving and advancing climate forecasts.Recently developed retrospective forecast experiments,based on a Community Earth System Model ensemble prediction system,offer a great opportunity to comprehensively explore OHC predictability.Our results indicate that the skill of actual OHC predictions varies across different oceans and diminishes as the lead time of prediction extends.The spatial distribution of the actual prediction skill closely resembles the corresponding persistence skill,indicating that the persistence of OHC serves as the primary predictive signal for its predictability.The decline in actual prediction skill is more pronounced in the Indian and Atlantic oceans than in the Pacific Ocean,particularly within tropical regions.Additionally,notable seasonal variations in the actual prediction skills across different oceans align well with the phase-locking features of OHC variability.The potential predictability of OHC generally surpasses the actual prediction skill at all lead times,highlighting significant room for improvement in current OHC predictions,especially for the North Indian Ocean and the Atlantic Ocean.Achieving such improvements necessitates a collaborative effort to enhance the quality of ocean observations,develop effective data assimilation methods,and reduce model bias.

Experimental and numerical analyses of the effect of fibre content on the close-in blast performance of a UHPFRC beam

Limited research has been conducted on the influences of fiber content on close-in blasting characteristics for ultrahigh-performance fiber-reinforced concrete(UHPFRC)beams.This paper aims to address this knowledge gap through experimental and mesoscale numerical methods.Experiments were conducted on ten UHPFRC beams built with varying steel fiber volumetric fractions subjected to close-in explosive conditions.Additionally,this study considered other parameters,such as the longitudinal reinforcement type and ratio.In the case of UHPFRC beams featuring normal-strength longitudinal reinforcement of diametersΦ12,Φ16,andΦ20,a reduction in maximum displacement by magnitudes of19.6%,19.5%,and 17.4%was observed,respectively,as the volumetric fractions of fiber increased from1.0%to 2.5%.In addition,increasing the longitudinal reinforcement ratio and using high-strength steel longitudinal reinforcement both significantly reduced the deformation characteristics and increase the blasting resistances of UHPFRC beams.However,the effects on the local crushing and spalling damage were not significant.A mesoscale finite element model,which considers the impacts of fiber parameters on UHPFRC beam behaviors,was also established and well correlated with the test findings.Nevertheless,parametric analyses were further conducted to examine the impacts of the steel fiber content and length and the hybrid effects of various types of microfibers and steel fibers on the blasting performance of UHPFRC beams.

Layered Coded Cache Placement and Cooperative Delivery with Sharing Links in Satellite-Terrestrial Integrated Networks

Cooperative utilization of multidimensional resources including cache, power and spectrum in satellite-terrestrial integrated networks(STINs) can provide a feasible approach for massive streaming media content delivery over the seamless global coverage area. However, the on-board supportable resources of a single satellite are extremely limited and lack of interaction with others. In this paper, we design a network model with two-layered cache deployment, i.e., satellite layer and ground base station layer, and two types of sharing links, i.e., terrestrial-satellite sharing(TSS) links and inter-satellite sharing(ISS) links, to enhance the capability of cooperative delivery over STINs. Thus, we use rateless codes for the content divided-packet transmission, and derive the total energy efficiency(EE) in the whole transmission procedure, which is defined as the ratio of traffic offloading and energy consumption. We formulate two optimization problems about maximizing EE in different sharing scenarios(only TSS and TSS-ISS),and propose two optimized algorithms to obtain the optimal content placement matrixes, respectively.Simulation results demonstrate that, enabling sharing links with optimized cache placement have more than 2 times improvement of EE performance than other traditional placement schemes. Particularly, TSS-ISS schemes have the higher EE performance than only TSS schemes under the conditions of enough number of satellites and smaller inter-satellite distances.

QTL analysis for ascorbic acid content in strawberry fruit reveals a complex genetic architecture and association with GDP-L-galactose phosphorylase

Strawberry(Fragaria×ananassa)fruits are an excellent source of L-ascorbic acid(AsA),a powerful antioxidant for plants and humans.Identifying the genetic components underlying AsA accumulation is crucial for enhancing strawberry nutritional quality.Here,we unravel the genetic architecture of AsA accumulation using an F1 population derived from parental lines‘Candonga’and‘Senga Sengana’,adapted to distinct Southern and Northern European areas.To account for environmental effects,the F1 and parental lines were grown and phenotyped in five locations across Europe(France,Germany,Italy,Poland and Spain).Fruit AsA content displayed normal distribution typical of quantitative traits and ranged five-fold,with significant differences among genotypes and environments.AsA content in each country and the average in all of them was used in combination with 6,974 markers for quantitative trait locus(QTL)analysis.Environmentally stable QTLs for AsA content were detected in linkage group(LG)3A,LG 5A,LG 5B,LG 6B and LG 7C.Candidate genes were identified within stable QTL intervals and expression analysis in lines with contrasting AsA content suggested that GDP-L-Galactose Phosphorylase FaGGP(3A),and the chloroplast-located AsA transporter gene FaPHT4;4(7C)might be the underlying genetic factors for QTLs on LG 3A and 7C,respectively.We show that recessive alleles of FaGGP(3A)inherited from both parental lines increase fruit AsA content.Furthermore,expression of FaGGP(3A)was two-fold higher in lines with high AsA.Markers here identified represent a useful resource for efficient selection of new strawberry cultivars with increased AsA content.

An Improved Bounded Conflict-Based Search for Multi-AGV Pathfinding in Automated Container Terminals

As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.