Responding of zooplankton to environmental factor changes in the Changjiang River estuarine regions in spring-summer from 2016 to 2020

The estuarine areas are under frequent influence from freshwater intrusion and ocean currents,in which zooplankton species are diversified and variable as they are sensitive to physio-chemical variations in water.Therefore,understanding the relationships between zooplankton and environmental factors help us know the water quality.To achieve co-existence with species in similar ecological group or habit,they could inevitably alter themselves to fit the ecology and adjust the function according to the competitive exclusion in ecological theory.However,information of the co-existence of dominant species in the Changjiang(Yangtze)River estuary(CRE)and adjacent waters remains scarce.We explored the relationships between dominant zooplankton and environmental factors in the study region in spring-summer from 2016 to 2020,involving particularly the composition of dominant species,ecological groups,their relationships with environmental factors,and co-existence of important species,using the non-multidimensional scale analysis(nMDS)method and redundancy analysis.Results show that Labidocera euchaeta and Tortanus vermiculus were dominant species in the study scope.The turnover rate of dominant zooplankton was greater(>50%)in spring while the species number was higher in summer.The dominant species were estuarine,offshore,and eurytopic based on the adaptation to salinity.In spring,the ecological groups were dominated by estuarine species,while in summer by estuarine and offshore species.In addition,the nMDS showed that the dominant species in the same ecological group were more dispersed and not prominently clustered;the dominant species were staggered among different ecological groups.The temperature,salinity,pH,dissolved oxygen,and chlorophyll a were the main environmental factors on the distribution of the dominant species in spring,while in summer were dissolved oxygen,temperature,salinity,and pH.The domination of medusae of Nemopsis bachei and Pleurobrachia globosa in zooplankton community in spring,and the continuous decrease in abundance of L.euchaeta reflected the effects of local climate change.The temperature and salinity changes in different years and the subsequent response of zooplankton reflected the influence of freshwater intrusion and/or ocean currents.Zooplankton in similar ecological habits exhibited the competitive exclusion in terms of co-existence.

Dominant woody plant species recognition with a hierarchical model based on multimodal geospatial data for subtropical forests

Since the launch of the Google Earth Engine(GEE)cloud platform in 2010,it has been widely used,leading to a wealth of valuable information.However,the potential of GEE for forest resource management has not been fully exploited.To extract dominant woody plant species,GEE combined Sen-tinel-1(S1)and Sentinel-2(S2)data with the addition of the National Forest Resources Inventory(NFRI)and topographic data,resulting in a 10 m resolution multimodal geospatial dataset for subtropical forests in southeast China.Spectral and texture features,red-edge bands,and vegetation indices of S1 and S2 data were computed.A hierarchical model obtained information on forest distribution and area and the dominant woody plant species.The results suggest that combining data sources from the S1 winter and S2 yearly ranges enhances accuracy in forest distribution and area extraction compared to using either data source independently.Similarly,for dominant woody species recognition,using S1 winter and S2 data across all four seasons was accurate.Including terrain factors and removing spatial correlation from NFRI sample points further improved the recognition accuracy.The optimal forest extraction achieved an overall accuracy(OA)of 97.4%and a maplevel image classification efficacy(MICE)of 96.7%.OA and MICE were 83.6%and 80.7%for dominant species extraction,respectively.The high accuracy and efficacy values indicate that the hierarchical recognition model based on multimodal remote sensing data performed extremely well for extracting information about dominant woody plant species.Visualizing the results using the GEE application allows for an intuitive display of forest and species distribution,offering significant convenience for forest resource monitoring.

The effects of data aggregation on long-term projections of forest stands development

Forest management planning often relies on Airborne Laser Scanning(ALS)-based Forest Management Inventories(FMIs)for sustainable and efficient decision-making.Employing the area-based(ABA)approach,these inventories estimate forest characteristics for grid cell areas(pixels),which are then usually summarized at the stand level.Using the ALS-based high-resolution Norwegian Forest Resource Maps(16 m×16 m pixel resolution)alongside with stand-level growth and yield models,this study explores the impact of three levels of pixel aggregation(standlevel,stand-level with species strata,and pixel-level)on projected stand development.The results indicate significant differences in the projected outputs based on the aggregation level.Notably,the most substantial difference in estimated volume occurred between stand-level and pixel-level aggregation,ranging from-301 to+253 m^(3)·ha^(-1)for single stands.The differences were,on average,higher for broadleaves than for spruce and pine dominated stands,and for mixed stands and stands with higher variability than for pure and homogenous stands.In conclusion,this research underscores the critical role of input data resolution in forest planning and management,emphasizing the need for improved data collection practices to ensure sustainable forest management.

Species’ geographical range, environmental range and traits lead to specimen collection preference of dominant plant species of grasslands in Northern China

Many different factors,such as species traits,socio-economic factors,geographical and environmental factors,can lead to specimen collection preference.This study aims to determine whether grassland specimen collection in China is preferred by species traits(i.e.,plant height,flowering and fruiting period),environmental range(i.e.,the temperature and precipitation range)and geographical range(i.e.,distribution range and altitudinal range).Ordinary least squares models and phylogenetic generalized linear mixed models were used to analyze the relationships between specimen number and the explanatory variables.Random Forest models were then used to find the most parsimonious multivariate model.The results showed that interannual variation in specimen number between 1900 and 2020 was considerable.Specimen number of these species in southeast China was notably lower than that in northwest China.Environmental range and geographical range of species had significant positive correlations with specimen number.In addition,there were relatively weak but significant associations between specimen number and species trait(i.e.,plant height and flowering and fruiting period).Random Forest models indicated that distribution range was the most important variable,followed by flowering and fruiting period,and altitudinal range.These findings suggest that future floristic surveys should pay more attention to species with small geographical range,narrow environmental range,short plant height,and short flowering and fruiting period.The correction of specimen collection preference will also make the results of species distribution model,species evolution and other works based on specimen data more accurate.

Quantum algorithm for minimum dominating set problem with circuit design

Using quantum algorithms to solve various problems has attracted widespread attention with the development of quantum computing.Researchers are particularly interested in using the acceleration properties of quantum algorithms to solve NP-complete problems.This paper focuses on the well-known NP-complete problem of finding the minimum dominating set in undirected graphs.To expedite the search process,a quantum algorithm employing Grover’s search is proposed.However,a challenge arises from the unknown number of solutions for the minimum dominating set,rendering direct usage of original Grover’s search impossible.Thus,a swap test method is introduced to ascertain the number of iterations required.The oracle,diffusion operators,and swap test are designed with achievable quantum gates.The query complexity is O(1.414^(n))and the space complexity is O(n).To validate the proposed approach,qiskit software package is employed to simulate the quantum circuit,yielding the anticipated results.

Complex adaptive system theory,agent-based modeling,and simulation in dominant technology formation

Dominant technology formation is the key for the hightech industry to“cross the chasm”and gain an established foothold in the market(and hence disrupt the regime).Therefore,a stimulus-response model is proposed to investigate the dominant technology by exploring its formation process and mechanism.Specifically,based on complex adaptive system theory and the basic stimulus-response model,we use a combination of agent-based modeling and system dynamics modeling to capture the interactions between dominant technology and the socio-technical landscape.The results indicate the following:(i)The dynamic interaction is“stimulus-reaction-selection”,which promotes the dominant technology’s formation.(ii)The dominant technology’s formation can be described as a dynamic process in which the adaptation intensity of technology standards increases continuously until it becomes the leading technology under the dual action of internal and external mechanisms.(iii)The dominant technology’s formation in the high-tech industry is influenced by learning ability,the number of adopting users and adaptability.Therein,a“critical scale”of learning ability exists to promote the formation of leading technology:a large number of adopting users can promote the dominant technology’s formation by influencing the adaptive response of technology standards to the socio-technical landscape and the choice of technology standards by the socio-technical landscape.There is a minimum threshold and a maximum threshold for the role of adaptability in the dominant technology’s formation.(iv)The socio-technical landscape can promote the leading technology’s shaping in the high-tech industry,and different elements have different effects.This study promotes research on the formation mechanism of dominant technology in the high-tech industry,presents new perspectives and methods for researchers,and provides essential enlightenment for managers to formulate technology strategies.

Safety and efficacy of transcatheter arterial embolization in autosomal dominant polycystic kidney patients with gross hematuria: Six case reports

BACKGROUND To retrospectively report the safety and efficacy of renal transcatheter arterial embolization for treating autosomal dominant polycystic kidney disease(ADPKD)patients with gross hematuria.CASE SUMMARY The purpose of this study is to retrospectively report the safety and efficacy of renal transcatheter arterial embolization for treating ADPKD patients with gross hematuria.Materials and methods:During the period from January 2018 to December 2019,renal transcatheter arterial embolization was carried out on 6 patients with polycystic kidneys and gross hematuria.Renal arteriography was performed first,and then we determined the location of the hemorrhage and performed embolization under digital subtraction angiography monitoring.Improvements in routine blood test results,routine urine test results,urine color and postoperative reactions were observed and analyzed.Results:Renal transcatheter arterial embolization was successfully conducted in 6 patients.The indices of 5 patients and the color of gross hematuria improved after surgery compared with before surgery.No severe complication reactions occurred.CONCLUSION For autosomal dominant polycystic kidney syndrome patients with gross hematuria,transcatheter arterial embolization was safe and effective.

Incidental renal cell carcinoma post bilateral nephrectomy in autosomal dominant polycystic kidney disease

BACKGROUND Renal cell carcinoma(RCC)is more common in patients with autosomal dominant polycystic kidney disease(ADPKD)than in the general population.Diagnosing RCC in ADPKD is challenging due to the presence of multiple renal cysts,often leading to delays and difficulties in distinguishing RCC from cyst infection or hemorrhage.A total of 38 kidneys were excised from 19 patients,with a mean age of 56.8 years and an average hemodialysis duration of 84.2 months.Eight patients underwent open nephrectomies,and 11 underwent hand-assisted laparoscopic nephrec-tomies.RCC was detected in 15.8%of kidneys,affecting 21.1%of patients.Two patients had multifocal RCC in both kidneys.All RCC cases were pT1 stage,with the largest lesion averaging 16.5 mm in diameter.The average operative duration was 120 minutes,with intraoperative blood loss averaging 184.2 mL.Five patients required blood transfusions.Postoperative complications occurred in five patients,with a mean hospital stay of 17.1 days.The mean follow-up period was 28.1 months.CONCLUSION The prevalence of RCC is higher in patients with ADPKD with ESRD than in those with ESRD alone.Thus,clinicians should be cautious and implement surveillance programs to monitor the development of RCC in patients with ADPKD,particularly those on dialysis.

Vector Dominance with Threshold Searchable Encryption (VDTSE) for the Internet of Things

The Internet of Medical Things(IoMT)is an application of the Internet of Things(IoT)in the medical field.It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems,which is essential in smart healthcare.However,Personal Health Records(PHRs)are normally kept in public cloud servers controlled by IoMT service providers,so privacy and security incidents may be frequent.Fortunately,Searchable Encryption(SE),which can be used to execute queries on encrypted data,can address the issue above.Nevertheless,most existing SE schemes cannot solve the vector dominance threshold problem.In response to this,we present a SE scheme called Vector Dominance with Threshold Searchable Encryption(VDTSE)in this study.We use a Lagrangian polynomial technique and convert the vector dominance threshold problem into a constraint that the number of two equal-length vectors’corresponding bits excluding wildcards is not less than a threshold t.Then,we solve the problem using the proposed technique modified in Hidden Vector Encryption(HVE).This technique makes the trapdoor size linear to the number of attributes and thus much smaller than that of other similar SE schemes.A rigorous experimental analysis of a specific application for privacy-preserving diabetes demonstrates the feasibility of the proposed VDTSE scheme.

A Reference Vector-Assisted Many-Objective Optimization Algorithm with Adaptive Niche Dominance Relation

It is still a huge challenge for traditional Pareto-dominatedmany-objective optimization algorithms to solve manyobjective optimization problems because these algorithms hardly maintain the balance between convergence and diversity and can only find a group of solutions focused on a small area on the Pareto front,resulting in poor performance of those algorithms.For this reason,we propose a reference vector-assisted algorithmwith an adaptive niche dominance relation,for short MaOEA-AR.The new dominance relation forms a niche based on the angle between candidate solutions.By comparing these solutions,the solutionwith the best convergence is found to be the non-dominated solution to improve the selection pressure.In reproduction,a mutation strategy of k-bit crossover and hybrid mutation is used to generate high-quality offspring.On 23 test problems with up to 15-objective,we compared the proposed algorithm with five state-of-the-art algorithms.The experimental results verified that the proposed algorithm is competitive.

Unmasking Oppression:A Beauvoirian Analysis of Gender Dynamics in Bapsi Sidhwa’s Pakistani Bride

Delving into the intricacies of Pakistani society,this study offers a poignant exploration of the profound identity crises experienced by women,as depicted in Bapsi Sidhwa’s seminal work,Pakistani Bride(1990).Sidhwa’s narrative serves as a compelling lens through which to examine the multifaceted challenges faced by women within the patriarchal confines of Pakistani culture.Through the character of Zaitoon,Sidhwa adeptly navigates the intersections of tradition,patriarchy,and societal expectations,shedding light on the marginalized status of women in Pakistan.Employing qualitative research methods and drawing upon the theoretical framework of Simone de Beauvoir’s Second Sex(1949),this study delves into the nuanced complexities of female identity formation within a male-dominated society.Key themes such as identity subjugation,patriarchy,and the clash between social and traditional boundaries are meticulously analyzed.This research not only offers a critical examination of Sidhwa’s narrative techniques but also serves as a potent call to action,urging societal introspection and advocating for the empowerment of women in Pakistani society.

Study on the Fine Configuration of Reservoir in River Facies Oilfield in Bohai Sea Area

The geological conditions of offshore shallow water delta oil reservoirs were complex, with limited well data and large well spacing. Taking A Oilfield in the Bohai Sea Area, China as an example, the target sand body was formed in a shallow water delta sedimentary environment, with well-developed underwater distributary channels and frequent branching and diversion. The reservoir was strong non-uniformity and uneven plane water cut pressure. To this end, based on the existing work of predecessors, combined with seismic, logging, and production dynamics data, and based on the genesis mechanism of shallow water delta reservoirs, the boundary of composite river channels was identified through seismic facies, and logging facies were used to subdivide them into single river levels within the composite river channels. Then, seismic waveform characteristics were applied to track and characterize the plane distribution of single river channels, guiding the efficient development of offshore shallow water delta oil fields and achieving increased storage and production in Bohai Oilfield, China.

Effects of Different Arbuscular Mycorrhizal Fungi on Physiology of Viola prionantha under Salt Stress

Arbuscular mycorrhizal(AM)fungi distribute widely in natural habits and play a variety of ecological functions.In order to test the physiological response to salt stress mediated by different AM fungi,Viola prionantha was selected as the host,the dominant AM fungus in the rhizosphere of V.philippica growing in Songnen saline-alkali grassland,Rhizophagus irregularis,and their mixtures were used as inoculants,and NaCl stress was applied after the roots were colonized.The results showed that V.philippica could be colonized by AM fungi in the field and the colonization rate ranged from 73.33%to 96.67%,and Claroideoglomus etunicatum was identified as the dominant AM fungi species in the rhizosphere of V.philippica by morphology combined with sequencing for AM fungal AML1/AML2 target.Inoculation with both the species resulted in the formation of mycorrhizal symbiosis(the colonization rate was more than 70%)and AM fungi significantly enhanced plants’tolerance to salt stress of varying magnitude.Higher activity of antioxidant enzymes and augmented levels of proline and other osmoregulators were observed in AM plants.The content of MDA in CK was higher than that in the inoculations with the stress of 100,200,and 250 mM.All indices except soluble protein content and MDA content were significantly correlated with AM fungal colonization indices.The analysis for different AM fungal effects showed that the mixtures and R.irregularis worked even better than C.etunicatum.These results will provide theoretical support for the exploration and screening of salt-tolerant AM fungi species and also for the application of AM-ornamental plants in saline-alkali urban greening.

Hybrid data-driven framework for shale gas production performance analysis via game theory, machine learning, and optimization approaches

A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.

The notion of dominant terminology in bibliometric research

In this opinion paper, we introduce the expressions of dominant terminology and dominant term in the quantitative studies of science in analogy to the notion of dominant design in product development and innovation.

A Graph Theory Based Self-Learning Honeypot to Detect Persistent Threats

Attacks on the cyber space is getting exponential in recent times.Illegal penetrations and breaches are real threats to the individuals and organizations.Conventional security systems are good enough to detect the known threats but when it comes to Advanced Persistent Threats(APTs)they fails.These APTs are targeted,more sophisticated and very persistent and incorporates lot of evasive techniques to bypass the existing defenses.Hence,there is a need for an effective defense system that can achieve a complete reliance of security.To address the above-mentioned issues,this paper proposes a novel honeypot system that tracks the anonymous behavior of the APT threats.The key idea of honeypot leverages the concepts of graph theory to detect such targeted attacks.The proposed honey-pot is self-realizing,strategic assisted which withholds the APTs actionable tech-niques and observes the behavior for analysis and modelling.The proposed graph theory based self learning honeypot using the resultsγ(C(n,1)),γc(C(n,1)),γsc(C(n,1))outperforms traditional techniques by detecting APTs behavioral with detection rate of 96%.

Comparison of growth and nutrient uptake capacities of three dominant species of Qinhuangdao green tides

Since 2015, green tides have been blooming in offshore waters of Qinhuangdao, with serious impacts on the local ecological environment and tourism. Ulva australis, Bryopsis plumosa, and U. prolifera are the dominant species of Qinhuangdao green tides, following a sequential succession pattern. Ulva prolifera is the dominant species,with the highest biomass and the greatest influence on the local ecological environment. To study the reason of green tide dominant species succession and U. profilera became the dominant species with the largest biomass,we compared and analyzed the growth and nutrient uptake capacity of the three algae. The results showed that temperature significantly affects the growth of the three species. Within the temperature range of the experimental setup, the optimum temperature for the growth of U. australis, B. plumosa and U. profilera is10℃, 15℃, and 20–25℃, respectively. Combined with the temperature variation trend during green tide bloom development, we believe that temperature is the key environmental factor for the succession of the dominant species. Ulva prolifera has a higher growth rate than U. australis and B. plumosa under the same nitrate,ammonium, and phosphate levels. Significant differences in the maximum absorption rate(R_(max)) and R_(max)/Ks(the relationship between uptake rate and substrate concentration) values indicated that U. prolifera had an apparent competitive advantage over U. australis and B. plumosa regarding nutrient uptake. Therefore, the strong growth and nutrient uptake capacities of U. prolifera might be the main reason for becoming the dominant species with the largest biomass in Qinhuangdao green tides.

Effect of slope position on leaf and fine root C,N and P stoichiometry and rhizosphere soil properties in Tectona grandis plantations

Little is known about C-N-P stoichiometries and content in teak(Tectona grandis)plantations in South China,which are mostly sited on hilly areas with lateritic soil,and the effect of slope position on the accumulation of these elements in trees and rhizosphere soils.Here we analyzed the C,N,P content and stoichiometry in leaves,fine roots and rhizosphere soils of trees on the upper and lower slopes of a 12-year-old teak plantation.The Kraft classification system of tree status was used to sample dominant,subdominant and mean trees at each slope position.The results showed that the C,N and P contents in leaves were higher than in fine roots and rhizosphere soils.The lowest C/N,C/P and N/P ratios were found in rhizosphere soils,and the C/N and C/P ratios in fine roots were higher than in leaves.Nutrient accumulation in leaves,fine roots and rhizosphere soils were significantly influenced by slope position and tree class with their interaction mainly showing a greater effect on rhizosphere soils.Leaf C content and C/N ratio,fine root C and P contents,and C/N and C/P ratios all increased distinctly with declining slope position.The contents of organic matter(SOM),ammonium(NH4+-N),nitrate-nitrogen(NO3--N)and available potassium(AK)in rhizosphere soils were mainly enriched on upper slopes,but exchange calcium(ECa),available phosphorus(AP),and pH were relatively lower.Variations in the C,N and P stoichiometries in trees were mainly attributed to the differences in rhizosphere soil properties.N and P contents showed significant positive linear relationships between leaf and rhizosphere soil,and C content negative linear correlation among leaves,fine roots and rhizosphere soils.Chemical properties of rhizosphere soils,particularly C/N and NH4+-N,had significant effects on the leaf nutrients in trees on the upper slope.Correspondingly,rhizosphere soil properties mainly influenced fine root nutrients on the lower slope,and soil AK was the major influencing factor.Overall,these results offer new insights for the sustainability and management of teak plantations in hilly areas.

Clinical Characteristics of Macular Hole and Macular Epiretinal Membrane in Dominant and Nondominant Eyes

Ocular dominance(OD) is referred to the superiority of one eye over the other when the visual sense is produced[1]. This condition can be considered as a preference for the particular laterality of the eye during a mono-visual task or the relative contributions of visual signal transduction between eyes[2]. Empirically, OD tendencies are exhibited in habitual and subconscious behavior.

Distribution pattern of macrobenthic assemblages along a salinity gradient in the Hangzhou Bay and its adjacent waters

It is widely acknowledged that the distribution of macrobenthos is affected by salinity, but the degree of influence varies in different areas. To explore the distribution pattern of macrobenthic assemblages in the Hangzhou Bay,12 stations were sampled to collect macrobenthos and the corresponding bottom water. Changes in the general characteristics of macrobenthos along the salinity gradient in the Hangzhou Bay and its adjacent waters were considered. Three dominant species were identified, including the polychaetes Sternaspis chinensis, the crustacea Oratosquilla oratoria and the echinoderm Ophiuroglypha kinbergi. And the macrobenthic assemblages showed a zonal distribution along with the salinity change. The correlation analyses showed that salinity, depth,temperature, suspended solids and dissolved oxygen had concurrent significant correlations with carnivorous group, Margalef species richness(d), Brillouin index(H) and Shannon-Wiener diversity index(H'). In light of the strong correlation between salinity and Changjiang River diluted water, which produces considerable disturbances by freshwater inflows, the deposition of suspended solids and the resuspension of seabed sediments,the combined environmental disturbances, instead of salinity alone, should be adopted to explain the zonation distribution pattern of macrobenthic assemblages.