Spatio-temporal Variation Characteristics of Extreme Climate Events and Their Teleconnections to Large-scale Ocean-atmospheric Circulation Patterns in Huaihe River Basin,China During 1959–2019

Huaihe River Basin(HRB) is located in China’s north-south climatic transition zone,which is very sensitive to global climate change.Based on the daily maximum temperature,minimum temperature,and precipitation data of 40 meteorological stations and nine monthly large-scale ocean-atmospheric circulation indices data during 1959–2019,we present an assessment of the spatial and temporal variations of extreme temperature and precipitation events in the HRB using nine extreme climate indices,and analyze the teleconnection relationship between extreme climate indices and large-scale ocean-atmospheric circulation indices.The results show that warm extreme indices show a significant(P < 0.05) increasing trend,while cold extreme indices(except for cold spell duration) and diurnal temperature range(DTR) show a significant decreasing trend.Furthermore,all extreme temperature indices show significant mutations during 1959-2019.Spatially,a stronger warming trend occurs in eastern HRB than western HRB,while maximum 5-d precipitation(Rx5day) and rainstorm days(R25) show an increasing trend in the southern,central,and northwestern regions of HRB.Arctic oscillation(AO),Atlantic multidecadal oscillation(AMO),and East Atlantic/Western Russia(EA/WR) have a stronger correlation with extreme climate indices compared to other circulation indices.AO and AMO(EA/WR) exhibit a significant(P < 0.05) negative(positive)correlation with frost days and diurnal temperature range.Extreme warm events are strongly correlated with the variability of AMO and EA/WR in most parts of HRB,while extreme cold events are closely related to the variability of AO and AMO in eastern HRB.In contrast,AMO,AO,and EA/WR show limited impacts on extreme precipitation events in most parts of HRB.

Spatio-temporal variation of trace elements distributed over surface water of Upper Ganga River Basin in Western Himalayan Region

The rivers draining from the Himalayan range distribute enormous amount of fresh water to the people living in downstream regions.Trace metals flowed with river water can lead to serious impact on ecological system and human health.Nevertheless,the documentation on trace elements of Himalayan rivers is inadequately documented.The current study deals with the spatial and temporal variability of the major and trace elements of Ganga river water in epirhithron,metarhithron and hyporhithron zone belonging to Himalayan segment.Water samples from nineteen monitoring locations were collected in pre-monsoon(May-June),monsoon(AugustSeptember)and post-monsoon(December)seasons and subjected to be assessed for 20 elements(Ag,Al,Ba,Cd,Ca,Cr,Cu,Fe,Ga,K,Mn,Mg,Na,Ni,Pb,Sr,Th,U,Zn,and Zr)using ICP-OES(Inductively Coupled Plasma-Optical Emission Spectrometer).Different water pollution indexes such as HPI(Heavy Metal Pollution Index),MI(Metal Index)and PI(Pollution Index)were used to describe current water quality status at each monitoring station under particular classified ecological zone.The studied stations in hyporhithron zone had the value of Metal Index(MI>1),indicating threshold of warning.Further,the highest values of HPI in hyporhithron zone correspond to poor water quality status.Sites with poor water quality were also found to be contaminated as per the Pollution Index(PI),exhibiting high concentrations for element(Fe).However,the epirhithron and metarhithron zone in Himalayan segment showed excellent water quality mainly contributed from natural sources.Cluster Analysis(CA)and Principal Component Analysis(PCA)were applied to identify the main influential sources for Ganga river water pollution.The Kriging interpolation method was also applied to prepare spatial distribution map of computed indexes(HPI,MI,and PI).With the help of index of local Moran’s I(LMI),identified spatial clusters and spatial outliers revealed the elevated concentration of most elements in hyporhithron zone.The dataset presented in this study would be convenient for government officials in developing more effective management policies and necessary steps to check and monitor the Ganga river water quality.It was also suggested that further investigations in terms of trace elemental sources and their role in self-purification properties of Ganga water can be addressed in future.

Improved spatio-temporal alignment measurement method for hull deformation

In this paper,an improved spatio-temporal alignment measurement method is presented to address the inertial matching measurement of hull deformation under the coexistence of time delay and large misalignment angle.Large misalignment angle and time delay often occur simultaneously and bring great challenges to the accurate measurement of hull deformation in space and time.The proposed method utilizes coarse alignment with large misalignment angle and time delay estimation of inertial measurement unit modeling to establish a brand-new spatiotemporal aligned hull deformation measurement model.In addition,two-step loop control is designed to ensure the accurate description of dynamic deformation angle and static deformation angle by the time-space alignment method of hull deformation.The experiments illustrate that the proposed method can effectively measure the hull deformation angle when time delay and large misalignment angle coexist.

A new two-step variational model for multiplicative noise removal with applications to texture images

Multiplicative noise removal problems have attracted much attention in recent years.Unlike additive noise,multiplicative noise destroys almost all information of the original image,especially for texture images.Motivated by the TV-Stokes model,we propose a new two-step variational model to denoise the texture images corrupted by multiplicative noise with a good geometry explanation in this paper.In the first step,we convert the multiplicative denoising problem into an additive one by the logarithm transform and propagate the isophote directions in the tangential field smoothing.Once the isophote directions are constructed,an image is restored to fit the constructed directions in the second step.The existence and uniqueness of the solution to the variational problems are proved.In these two steps,we use the gradient descent method and construct finite difference schemes to solve the problems.Especially,the augmented Lagrangian method and the fast Fourier transform are adopted to accelerate the calculation.Experimental results show that the proposed model can remove the multiplicative noise efficiently and protect the texture well.

Epidemic Characteristics and Spatio-Temporal Patterns of HFRS in Qingdao City,China,2010-2022

Objective This study investigated the epidemic characteristics and spatio-temporal dynamics of hemorrhagic fever with renal syndrome(HFRS)in Qingdao City,China.Methods Information was collected on HFRS cases in Qingdao City from 2010 to 2022.Descriptive epidemiologic,seasonal decomposition,spatial autocorrelation,and spatio-temporal cluster analyses were performed.Results A total of 2,220 patients with HFRS were reported over the study period,with an average annual incidence of 1.89/100,000 and a case fatality rate of 2.52%.The male:female ratio was 2.8:1.75.3%of patients were aged between 16 and 60 years old,75.3%of patients were farmers,and 11.6%had both“three red”and“three pain”symptoms.The HFRS epidemic showed two-peak seasonality:the primary fall-winter peak and the minor spring peak.The HFRS epidemic presented highly spatially heterogeneous,street/township-level hot spots that were mostly distributed in Huangdao,Pingdu,and Jiaozhou.The spatio-temporal cluster analysis revealed three cluster areas in Qingdao City that were located in the south of Huangdao District during the fall-winter peak.Conclusion The distribution of HFRS in Qingdao exhibited periodic,seasonal,and regional characteristics,with high spatial clustering heterogeneity.The typical symptoms of“three red”and“three pain”in patients with HFRS were not obvious.

Dynamic adaptive spatio-temporal graph network for COVID-19 forecasting

Appropriately characterising the mixed space-time relations of the contagion process caused by hybrid space and time factors remains the primary challenge in COVID-19 forecasting.However,in previous deep learning models for epidemic forecasting,spatial and temporal variations are captured separately.A unified model is developed to cover all spatio-temporal relations.However,this measure is insufficient for modelling the complex spatio-temporal relations of infectious disease transmission.A dynamic adaptive spatio-temporal graph network(DASTGN)is proposed based on attention mechanisms to improve prediction accuracy.In DASTGN,complex spatio-temporal relations are depicted by adaptively fusing the mixed space-time effects and dynamic space-time dependency structure.This dual-scale model considers the time-specific,space-specific,and direct effects of the propagation process at the fine-grained level.Furthermore,the model characterises impacts from various space-time neighbour blocks under time-varying interventions at the coarse-grained level.The performance comparisons on the three COVID-19 datasets reveal that DASTGN achieves state-of-the-art results with a maximum improvement of 17.092%in the root mean-square error and 11.563%in the mean absolute error.Experimental results indicate that the mechanisms of designing DASTGN can effectively detect some spreading characteristics of COVID-19.The spatio-temporal weight matrices learned in each proposed module reveal diffusion patterns in various scenarios.In conclusion,DASTGN has successfully captured the dynamic spatio-temporal variations of COVID-19,and considering multiple dynamic space-time relationships is essential in epidemic forecasting.

An Intelligent Framework for Resilience Recovery of FANETs with Spatio-Temporal Aggregation and Multi-Head Attention Mechanism

Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.

Warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography

High speed photography technique is potentially the most effective way to measure the motion parameter of warhead fragment benefiting from its advantages of high accuracy,high resolution and high efficiency.However,it faces challenge in dense objects tracking and 3D trajectories reconstruction due to the characteristics of small size and dense distribution of fragment swarm.To address these challenges,this work presents a warhead fragments motion trajectories tracking and spatio-temporal distribution reconstruction method based on high-speed stereo photography.Firstly,background difference algorithm is utilized to extract the center and area of each fragment in the image sequence.Subsequently,a multi-object tracking(MOT)algorithm using Kalman filtering and Hungarian optimal assignment is developed to realize real-time and robust trajectories tracking of fragment swarm.To reconstruct 3D motion trajectories,a global stereo trajectories matching strategy is presented,which takes advantages of epipolar constraint and continuity constraint to correctly retrieve stereo correspondence followed by 3D trajectories refinement using polynomial fitting.Finally,the simulation and experimental results demonstrate that the proposed method can accurately track the motion trajectories and reconstruct the spatio-temporal distribution of 1.0×10^(3)fragments in a field of view(FOV)of 3.2 m×2.5 m,and the accuracy of the velocity estimation can achieve 98.6%.

Variational data encoding and correlations in quantum-enhanced machine learning

Leveraging the extraordinary phenomena of quantum superposition and quantum correlation,quantum computing offers unprecedented potential for addressing challenges beyond the reach of classical computers.This paper tackles two pivotal challenges in the realm of quantum computing:firstly,the development of an effective encoding protocol for translating classical data into quantum states,a critical step for any quantum computation.Different encoding strategies can significantly influence quantum computer performance.Secondly,we address the need to counteract the inevitable noise that can hinder quantum acceleration.Our primary contribution is the introduction of a novel variational data encoding method,grounded in quantum regression algorithm models.By adapting the learning concept from machine learning,we render data encoding a learnable process.This allowed us to study the role of quantum correlation in data encoding.Through numerical simulations of various regression tasks,we demonstrate the efficacy of our variational data encoding,particularly post-learning from instructional data.Moreover,we delve into the role of quantum correlation in enhancing task performance,especially in noisy environments.Our findings underscore the critical role of quantum correlation in not only bolstering performance but also in mitigating noise interference,thus advancing the frontier of quantum computing.

A Study to Observe Pulse Pressure Variation after Induction with Propofol for General Anesthesia

Background and Aims: Pulse pressure variation (PPV) is a reliable and predictive dynamic parameter presently being utilized for fluid responsiveness. In the operating room, fluid administration based on PPV monitoring helps the physician in deciding whether to volume resuscitate or use interventions in patients undergoing surgery. Propofol is an intravenous induction agent which lowers blood pressure. There are multiple causes such as depression in cardiac output, and peripheral vasodilatation for hypotension. We undertook this study to observe the utility of PPV as a guide to fluid therapy after propofol induction. Primary outcome of our study was to monitor PPV as a marker of fluid responsiveness for the hypotension caused by propofol induction. Secondary outcome included the correlation of PPV with other hemodynamic parameters like heart rate (HR), systolic blood pressure (SBP), and diastolic blood pressure (DBP);after induction with propofol at regular interval of time. Methods: A total number of 90 patients were recruited. Either of the radial artery was then cannulated under local anaesthesia with 20G VygonLeadercath arterial cannula and invasive monitoring transduced. A baseline recording of heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP) and PPV was then recorded. Patients were then induced with predetermined doses of propofol (2 mg/kg) and recordings of HR, SBP, DBP, and PPV were taken at 5, 10 and 15 minutes. Results: Intraoperatively, PPV was significantly higher at 5 minutes and significantly lower at 15 minutes after induction. It was observed that there were no statistically significant correlations between PPV and SBP or DBP. PPV was strongly and directly associated with HR. Conclusion: We were able to establish that PPV predicts fluid responsiveness in hypotension caused by propofol induction;and can be used to administer fluid therapy in managing such hypotension. However, PPV was not directly correlated with hypotension subsequent to propofol administration.

A cloud model target damage effectiveness assessment algorithm based on spatio-temporal sequence finite multilayer fragments dispersion

To solve the problem of target damage assessment when fragments attack target under uncertain projectile and target intersection in an air defense intercept,this paper proposes a method for calculating target damage probability leveraging spatio-temporal finite multilayer fragments distribution and the target damage assessment algorithm based on cloud model theory.Drawing on the spatial dispersion characteristics of fragments of projectile proximity explosion,we divide into a finite number of fragments distribution planes based on the time series in space,set up a fragment layer dispersion model grounded in the time series and intersection criterion for determining the effective penetration of each layer of fragments into the target.Building on the precondition that the multilayer fragments of the time series effectively assail the target,we also establish the damage criterion of the perforation and penetration damage and deduce the damage probability calculation model.Taking the damage probability of the fragment layer in the spatio-temporal sequence to the target as the input state variable,we introduce cloud model theory to research the target damage assessment method.Combining the equivalent simulation experiment,the scientific and rational nature of the proposed method were validated through quantitative calculations and comparative analysis.

Small temporal variation in abundance of virioplankton compared to bacterioplankton and phytoplankton in two bays in the northern South China Sea

Variations of picoplankton groups were investigated over a one-month period in Daya Bay and Sanya Bay,in the northern South China Sea.The two coastal regions exhibited different variation patterns in physicochemical parameters.Moreover,the diel variations of picoplankton groups were different between the two bays.The abundance of the picoplankton in Sanya Bay displayed a pronounced diel variation,while it was not significant in Daya Bay.In addition,some similar patterns of picoplankton abundance were discovered.In the two bays,virioplankton exhibited the smallest fluctuation range,whereas picocyanobacteria fluctuated most markedly.The fluctuation range of picoplankton groups was larger in spring tide than in neap tide,especially in Sanya Bay.Random forest model analysis demonstrated that the variation of picoplankton groups was attributed to physical and chemical factors in Sanya Bay and Daya Bay,respectively.Therefore,our findings suggest that virioplankton abundance can persist more stably in response to changing environmental conditions compared to bacterioplankton and picophytoplankton.

Associations of genome-wide structural variations with phenotypic differences in cross-bred Eurasian pigs

Background During approximately 10,000 years of domestication and selection,a large number of structural variations(SVs)have emerged in the genome of pig breeds,profoundly influencing their phenotypes and the ability to adapt to the local environment.SVs(≥50 bp)are widely distributed in the genome,mainly in the form of insertion(INS),mobile element insertion(MEI),deletion(DEL),duplication(DUP),inversion(INV),and translocation(TRA).While studies have investigated the SVs in pig genomes,genome-wide association studies(GWAS)-based on SVs have been rarely conducted.Results Here,we obtained a high-quality SV map containing 123,151 SVs from 15 Large White and 15 Min pigs through integrating the power of several SV tools,with 53.95%of the SVs being reported for the first time.These high-quality SVs were used to recover the population genetic structure,confirming the accuracy of genotyping.Potential functional SV loci were then identified based on positional effects and breed stratification.Finally,GWAS were performed for 36 traits by genotyping the screened potential causal loci in the F2 population according to their corresponding genomic positions.We identified a large number of loci involved in 8 carcass traits and 6 skeletal traits on chromosome 7,with FKBP5 containing the most significant SV locus for almost all traits.In addition,we found several significant loci in intramuscular fat,abdominal circumference,heart weight,and liver weight,etc.Conclusions We constructed a high-quality SV map using high-coverage sequencing data and then analyzed them by performing GWAS for 25 carcass traits,7 skeletal traits,and 4 meat quality traits to determine that SVs may affect body size between European and Chinese pig breeds.

Temperature is a cryptic factor shaping the geographical pattern of genetic variation in Ceratophyllum demersum across a subtropical freshwater lake

Macrophyte habitats exhibit remarkable heterogeneity,encompassing the spatial variation of abiotic and biotic components such as changes in water conditions and weather as well as anthropogenic stressors.Environmental factors are thought to be important drivers shaping the genetic and epigenetic variation of aquatic plants.However,the links among genetic diversity,epigenetic variation,and environmental variables remain largely unclear,especially for clonal aquatic plants.Here,we performed population genetic and epigenetic analyses in conjunction with habitat discrimination to elucidate the environmental factors driving intraspecies genetic and epigenetic variation in hornwort(Ceratophyllum demersum)in a subtropical lake.Environmental factors were highly correlated with the genetic and epigenetic variation of C.demersum,with temperature being a key driver of the genetic variation.Lower temperature was detected to be correlated with greater genetic and epigenetic variation.Genetic and epigenetic variation were positively driven by water temperature,but were negatively affected by ambient air temperature.These findings indicate that the genetic and epigenetic variation of this clonal aquatic herb is not related to the geographic feature but is instead driven by environmental conditions,and demonstrate the effects of temperature on local genetic and epigenetic variation in aquatic systems.

The Variation of Plankton Community Structure in Artificial Reef Area and Adjacent Waters in Haizhou Bay

Plankton are an important component of marine protected areas(MPAs),and its communities would require much smaller interpatch distances to ensure connection among MPAs.According to the survey from MPAs dominated by artificial reefs and adjacent waters(estuary area(EA),aquaculture area(AA),artificial reef area(ARA),natural area(NA)and comprehensive effect area(CEA))in Haizhou Bay in spring and autumn,we analyzed phyto-zooplankton composition,abundance and biomass,and correlation with hydrologic variables to gain information about the forces that structure the plankton.The results showed that the dominant zooplankton were copepods(spring,98.9%;autumn,94.2%),while the phytoplankton were mainly composed of Bacillariophyta(spring,61.8%;autumn,95.6%).The RDA results showed that temperature,salinity and depth highly associated with the distribution and composition of plankton species among the habitats than other factors in spring;temperature,Chla and DO had the strongest influence in autumn.The zooplankton in the ARA and AA ecosystems basically contained the same species as those in other habitats,and each habitat also exhibited a relatively unique combination of plankton species.The structures of the EA zooplankton in spring and the EA phytoplankton in both seasons were much different than other habitats,which may have been caused by factors such as currents and tides.We concluded that there exists similarity of the plankton community between artificial reef area and adjacent waters,whereas the EAs may be relatively independent systems.Therefore,these interaction between plankton community should be considered when designing MPA networks,and ocean circulations should be considered more than the environmental factors.

Seasonal Variation of Hearing Sensitivity in the Red-eared Slider(Trachemys scripta elegans)

Seasonal variation of hearing sensitivity has been observed in many vertebrate groups with obvious vocal behaviors.Circulating hormones,conspecific calling signals,and temperature are potential factors that drive these plasticity patterns.Turtles have a hearing range that appears to be limited to under 1.5 kHz and are often thought to be non-vocal;thus,they are commonly neglected in vocal communication research.In this study,we aimed to determine whether the auditory phenotype exhibits seasonal variation in sensitivity and to analyze the potential factors driving such variation patterns in turtles.We measured hearing sensitivity and sex hormone levels in female(estradiol)and male(testosterone and dihydrotestosterone)Red-eared sliders(Trachemys scripta elegans)during spring and winter.The results showed that auditory brainstem response(ABR)thresholds were significantly lower in spring than in winter at a frequency range of 0.5-0.9 kHz.The hearing-sensitivity bandwidth was wider,and the ABR latency was significantly shorter in spring than in winter.No significant differences were found in estradiol,testosterone,and dihydrotestosterone levels in T.scripta elegans between spring and winter.This study is the first to reveal the seasonal variation of peripheral hearing sensitivity in turtles,a special animal group with limited hearing range and less vocalization.Temperature variations may be used to explain these seasonal effects,but further research is required to confirm our findings.

Insights into genetic diversity and phenotypic variations in domestic geese through comprehensive population and pan-genome analysis

Background Domestic goose breeds are descended from either the Swan goose(Anser cygnoides)or the Greylag goose(Anser anser),exhibiting variations in body size,reproductive performance,egg production,feather color,and other phenotypic traits.Constructing a pan-genome facilitates a thorough identification of genetic variations,thereby deepening our comprehension of the molecular mechanisms underlying genetic diversity and phenotypic variability.Results To comprehensively facilitate population genomic and pan-genomic analyses in geese,we embarked on the task of 659 geese whole genome resequencing data and compiling a database of 155 RNA-seq samples.By constructing the pan-genome for geese,we generated non-reference contigs totaling 612 Mb,unveiling a collection of 2,813 novel genes and pinpointing 15,567 core genes,1,324 softcore genes,2,734 shell genes,and 878 cloud genes in goose genomes.Furthermore,we detected an 81.97 Mb genomic region showing signs of genome selection,encompassing the TGFBR2 gene correlated with variations in body weight among geese.Genome-wide association studies utilizing single nucleotide polymorphisms(SNPs)and presence-absence variation revealed significant genomic associations with various goose meat quality,reproductive,and body composition traits.For instance,a gene encoding the SVEP1 protein was linked to carcass oblique length,and a distinct gene-CDS haplotype of the SVEP1 gene exhibited an association with carcass oblique length.Notably,the pan-genome analysis revealed enrichment of variable genes in the“hair follicle maturation”Gene Ontology term,potentially linked to the selection of feather-related traits in geese.A gene presence-absence variation analysis suggested a reduced frequency of genes associated with“regulation of heart contraction”in domesticated geese compared to their wild counterparts.Our study provided novel insights into gene expression features and functions by integrating gene expression patterns across multiple organs and tissues in geese and analyzing population variation.Conclusion This accomplishment originates from the discernment of a multitude of selection signals and candidate genes associated with a wide array of traits,thereby markedly enhancing our understanding of the processes underlying domestication and breeding in geese.Moreover,assembling the pan-genome for geese has yielded a comprehensive apprehension of the goose genome,establishing it as an indispensable asset poised to offer innovative viewpoints and make substantial contributions to future geese breeding initiatives.

A novel diurnal and seasonal variation analysis of BTEX in Bengaluru urban area

In the urban atmosphere of Bengaluru, various volatile organic compounds(VOCs), particularly Benzene,Toluene, Ethylbenzene, and Xylene(BTEX), have shown an increasing trend in concentration. The present research was conducted during summer and monsoon seasons, focusing on Kadubeesanahalli, a high-traffic area within the Bengaluru Metropolitan City. Hourly sample data was collected using a BTEX analyzer(Model GC955-600) and subsequently transformed into daily, monthly, and seasonal values. The study revealed distinct patterns in benzene concentrations. Benzene levels were lowest during the early morning hours, specifically from 1:00 a.m.to 7:00 a.m.. Concentrations then increased from 7:00 a.m. to 9:00 a.m. and again from 4:00 p.m. to 11:00 p.m.,corresponding to the morning and evening peak traffic hours. However, between 10:00 a.m. and 4:00 p.m., the concentration decreased due to reduced traffic levels. These diurnal variations in benzene concentration are influenced by meteorological parameters. Comparing the two seasons, higher concentrations of Benzene, EthylBenzene, and MP-xylene were observed during the summer season. This increase is attributed to the elevated temperatures during summer, which promote the vaporization of BTEX compounds. Conversely, lower BTEX concentrations were recorded during the monsoon season due to the wet deposition process. The observed positive correlation(r > 0.5) among BTEX parameters strongly suggests a common source, most likely originating from vehicular emissions.

STRONGLY CONVERGENT INERTIAL FORWARD-BACKWARD-FORWARD ALGORITHM WITHOUT ON-LINE RULE FOR VARIATIONAL INEQUALITIES

This paper studies a strongly convergent inertial forward-backward-forward algorithm for the variational inequality problem in Hilbert spaces.In our convergence analysis,we do not assume the on-line rule of the inertial parameters and the iterates,which have been assumed by several authors whenever a strongly convergent algorithm with an inertial extrapolation step is proposed for a variational inequality problem.Consequently,our proof arguments are different from what is obtainable in the relevant literature.Finally,we give numerical tests to confirm the theoretical analysis and show that our proposed algorithm is superior to related ones in the literature.

Natural variation in the cytochrome c oxidase subunit 5B OsCOX5B regulates seed vigor by altering energy production in rice

Seed vigor is a crucial trait for the direct seeding of rice.Here we examined the genetic regulation of seed vigor traits in rice,including germination index(GI)and germination potential(GP),using a genome-wide association study approach.One major quantitative trait locus,qGI6/qGP6,was identified simultaneously for both GI and GP.The candidate gene encoding the cytochrome c oxidase subunit 5B(OsCOX5B)was validated for qGI6/qGP6.The disruption of OsCOX5B caused the vigor traits to be significantly lower in Oscox5b mutants than in the japonica Nipponbare wild type(WT).Gene co-expression analysis revealed that OsCOX5B influences seed vigor mainly by modulating the tricarboxylic acid cycle process.The glucose levels were significantly higher while the pyruvic acid and adenosine triphosphate levels were significantly lower in Oscox5b mutants than in WT during seed germination.The elite haplotype of OsCOX5B facilitates seed vigor by increasing its expression during seed germination.Thus,we propose that OsCOX5B is a potential target for the breeding of rice varieties with enhanced seed vigor for direct seeding.