Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
Climate change is significantly impacting cotton production in the Tarim River Basin.The study investigated the climate change characteristics from 2021 to 2100 using climate change datasets simulated per the coupled ...Climate change is significantly impacting cotton production in the Tarim River Basin.The study investigated the climate change characteristics from 2021 to 2100 using climate change datasets simulated per the coupled model inter-comparison project phase six(CMIP6)climatic patterns under the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5.The DSSAT-CROPGROCotton model,along with stepwise multiple regression analyses,was used to simulate changes in the potential yield of seed cotton due to climate change.The results show that while future temperatures in the Tarim River Basin will rise significantly,changes in precipitation and radiation during the cotton-growing season are minimal.Seed cotton yields are more sensitive to low temperatures than to precipitation and radiation.The potential yield of seed cotton under the SSP2-4.5 scenario would increase by 14.8%,23.7%,29.0%,and 29.4%in the 2030S,2050S,2070S,and 2090S,respectively.In contrast,under the SSP5-8.5 scenario,the potential yield of seed cotton would see increases of 17.5%,27.1%,30.1%,and 22.6%,respectively.Except for the 2090s under the SSP5-8.5 scenario,future seed cotton production can withstand a 10%to 20%deficit in irrigation.These findings will help develop climate change adaptation strategies for cotton cultivation.展开更多
Objective Traditional Chinese medicine(TCM)incorporates traditional diagnostic methods and several major treatment modalities including Chinese herbal medicine,Chinese patent medicine,and non-pharmacological methods s...Objective Traditional Chinese medicine(TCM)incorporates traditional diagnostic methods and several major treatment modalities including Chinese herbal medicine,Chinese patent medicine,and non-pharmacological methods such as acupuncture and tuina.Even though TCM is used daily by more than 70,000 healthcare facilities and over 700,000 clinical practitioners in China,there is a poor understanding of the extent to which TCM diagnostic methods are used,how different treatment modalities are deployed in general,and what major factors may affect the integration of TCM and Western medicine.This study aimed to fill this void in the literature.Methods In the 2021 National Healthcare Improvement Evaluation Survey,we included three questions gauging the perception and practices of TCM amongst physicians working in TCM-related facilities,investigating the frequency of their deployment of TCM diagnostic methods,and predominant TCM treatment methods.Our empirical analysis included descriptive statistics,intergroup chi-square analysis,and binary logistic regression to examine the association between different types of facilities and individual characteristics and TCM utilization patterns.Results A total of 7618 clinical physicians comprised our study sample.Among them,84.27%have integrated TCM and Western medicine in their clinical practice,and 80.77%of TCM practitioners used the 4 diagnostic methods as a tool in their clinical practice.Chinese herbal medicine was the most widely utilized modality by Chinese TCM physicians(used by 88.49%of respondents),compared with the Chinese patent medicine and non-pharmacological TCM methods,which were used by 73.14%,and 69.39%,respectively.Herbal tea as an out-of-pocket health-maintenance intervention is also a notable practice,recommended by 29.43%of physicians.Significant variations exist across certain institutions,departments,and individual practitioners.Conclusion Given that most of the surveyed physicians integrated TCM with Western medicine in their clinical practices,the practice of“pure TCM”appears to be obsolete in China’s tertiary healthcare institutions.Notably,remarkable variation exists in the use of different TCM modalities across institutions and among individuals,which might be related to and thus limited by the practitioners’experience.Future research focusing on the efficacy and safety of TCM interventions for specific diseases,the development of standardized clinical guidelines,and the enhancement of TCM education and training are called for to optimize TCM-Western medicine integration.展开更多
Background Cotton crop is infested by numerous arthropod pests from sowing to harvesting,causing substantial direct and indirect yield losses.Knowledge of seasonal population trends and the relative occurrence of pest...Background Cotton crop is infested by numerous arthropod pests from sowing to harvesting,causing substantial direct and indirect yield losses.Knowledge of seasonal population trends and the relative occurrence of pests and their natural enemies is required to minimize the pest population and yield losses.In the current study,analysis of the seasonal population trend of pests and natural enemies and their relative occurrence on cultivars of three cotton species in Central India has been carried out.Results A higher number and diversity of sucking pests were observed during the vegetative cotton growth stage(60 days after sowing),declining as the crop matured.With the exception of cotton jassid(Amrasca biguttula biguttula Ishida),which caused significant crop damage mainly from August to September;populations of other sucking insects seldom reached economic threshold levels(ETL)throughout the studied period.The bollworm complex populations were minimal,except for the pink bollworm(Pectinophora gossypiella Saunders),which re-emerged as a menace to cotton crops during the cotton cropping season 2017–2018 due to resistance development against Bt-cotton.A reasonably good number of predatory arthropods,including coccinellids,lacewings,and spiders,were found actively preying on the arthropod pest complex of the cotton crop during the early vegetative growth stage.Linear regression indicates a significant relationship between green boll infestations and pink bollworm moths in pheromone traps.Multiple linear regression analyse showed mean weekly weather at one-or two-week lag periods had a significant impact on sucking pest population(cotton aphid,cotton jassid,cotton whitefly,and onion thrips)fluctuation.Gossypium hirsutum cultivars RCH 2 and DCH 32,and G.barbadense cultivar Suvin were found susceptible to cotton jassid and onion thrips.Phule Dhanvantary,an G.arboreum cotton cultivar,demonstrated the highest tolerance among all evaluated cultivars against all sucking pests.Conclusion These findings have important implications for pest management in cotton crops.Susceptible cultivars warrant more attention for plant protection measures,making them more input-intensive.The choice of appropriate cultivars can help minimize input costs,thereby increasing net returns for cotton farmers.展开更多
The cleanliness of seed cotton plays a critical role in the pre-treatment of cotton textiles,and the removal of impurity during the harvesting process directly determines the quality and market value of cotton textile...The cleanliness of seed cotton plays a critical role in the pre-treatment of cotton textiles,and the removal of impurity during the harvesting process directly determines the quality and market value of cotton textiles.By fusing band combination optimization with deep learning,this study aims to achieve more efficient and accurate detection of film impurities in seed cotton on the production line.By applying hyperspectral imaging and a one-dimensional deep learning algorithm,we detect and classify impurities in seed cotton after harvest.The main categories detected include pure cotton,conveyor belt,film covering seed cotton,and film adhered to the conveyor belt.The proposed method achieves an impurity detection rate of 99.698%.To further ensure the feasibility and practical application potential of this strategy,we compare our results against existing mainstream methods.In addition,the model shows excellent recognition performance on pseudo-color images of real samples.With a processing time of 11.764μs per pixel from experimental data,it shows a much improved speed requirement while maintaining the accuracy of real production lines.This strategy provides an accurate and efficient method for removing impurities during cotton processing.展开更多
Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,su...Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.展开更多
Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planti...Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planting system(HDPS)offers a viable method to enhance productivity by increasing plant populations per unit area,optimizing resource utilization,and facilitating machine picking.Cotton is an indeterminate plant that produce excessive vegeta-tive growth in favorable soil fertility and moisture conditions,which posing challenges for efficient machine picking.To address this issue,the application of plant growth retardants(PGRs)is essential for controlling canopy architecture.PGRs reduce internode elongation,promote regulated branching,and increase plant compactness,making cotton plants better suited for machine picking.PGRs application also optimizes photosynthates distribution between veg-etative and reproductive growth,resulting in higher yields and improved fibre quality.The integration of HDPS and PGRs applications results in an optimal plant architecture for improving machine picking efficiency.However,the success of this integration is determined by some factors,including cotton variety,environmental conditions,and geographical variations.These approaches not only address yield stagnation and labour shortages but also help to establish more effective and sustainable cotton farming practices,resulting in higher cotton productivity.展开更多
In modal logic,topological semantics is an intuitive and natural special case of neighbourhood semantics.This paper stems from the observation that the satisfaction relation of topological semantics applies to subset ...In modal logic,topological semantics is an intuitive and natural special case of neighbourhood semantics.This paper stems from the observation that the satisfaction relation of topological semantics applies to subset spaces which are more general than topological spaces.The minimal modal logic which is strongly sound and complete with respect to the class of subset spaces is found.Soundness and completeness results of some famous modal logics(e.g.S4,S5 and Tr)with respect to various important classes of subset spaces(eg intersection structures and complete fields of sets)are also proved.In the meantime,some known results,e.g.the soundness and completeness of Tr with respect to the class of discrete topological spaces,are proved directly using some modifications of the method of canonical mode1,without a detour via neighbourhood semantics or relational semantics.展开更多
The early-maturing cotton planting area in northern Xinjiang is a significant high-quality cotton production region in China.The screening and identification of early-maturing cotton germplasm resources are essential ...The early-maturing cotton planting area in northern Xinjiang is a significant high-quality cotton production region in China.The screening and identification of early-maturing cotton germplasm resources are essential for the selection and breeding of early-maturing machine-picked cotton varieties,thereby facilitating the development of high-quality early-maturing machine-picked cotton materials.In this study,19 self-fertilized early-maturing materials were screened and identified.Among these,the varieties G15 and G9 were selected based on their superior overall traits.Notably,the G9 variety exhibited exceptional early-maturing characteristics,with a reproductive period of 116 d.展开更多
Seed priming is an effective seed pretreatment technology that enhances germination and overall crop performance by optimizing seed hydration and metabolic processes before planting.Seed quality is a critical determin...Seed priming is an effective seed pretreatment technology that enhances germination and overall crop performance by optimizing seed hydration and metabolic processes before planting.Seed quality is a critical determinant of cotton(Gossypium hirsutum)crop performance,influencing germination,plant vigor,and yield.This study evaluates the effects of seed priming with potassium salts(1%and 2%KCl and K2SO4)on germination,morphological traits,and Cry1Ac gene expression in three Bt cotton cultivars(IUB-2013,NIAB-878B,FH-142)as Cry1Ac enhance the pest resistance in Bt cotton and reduce the plant’s dependence on chemical insecticides.Seeds were primed for six hours,air-dried,and sown in the field.Germination rates,plant height,number of bolls per plant,boll weight,seed cotton yield,and ginning outturn(GOT)were assessed at crop maturity.Cry1Ac gene expression was quantified to explore the influence of priming treatments on transgene activity.Results demonstrated that 1%K2SO4 priming significantly enhanced germination and yield-related traits,with Cry1Ac expression peaking in the IUB-2013 cultivar under 1%K2SO4 treatment.These findings suggest that potassium-based halopriming improves cotton seedling establishment and Bt gene expression.This study addresses the critical gaps in understanding the effects of seed halopriming on morphological traits,germination,and expression of the Cry1Ac gene in Bt cotton while providing a novel eco-friendly and cost-effective halopriming approach,offering the potential to improve cotton production.展开更多
Normal mode extraction has attracted extensive attention over the past few decades due to its practical value in enhancing the performance of underwater acoustic signal processing.Singular value decomposition(SVD)is a...Normal mode extraction has attracted extensive attention over the past few decades due to its practical value in enhancing the performance of underwater acoustic signal processing.Singular value decomposition(SVD)is an effective method to extract modal depth functions using vertical line arrays(VLA),particularly in scenarios when no prior environment information is available.However,the SVD method requires rigorous orthogonality conditions,and its performance severely degenerates in the presence of mode degeneracy.Consequently,the SVD approach is often not feasible in practical scenarios.This paper proposes a full rank decomposition(FRD)method to address these issues.Compared to the SVD method,the FRD method has three distinct advantages:1)the conditions that the FRD method requires are much easier to be fulfilled in practical scenarios;2)both modal depth functions and wavenumbers can be simultaneously extracted via the FRD method;3)the FRD method is not affected by the phenomenon of mode degeneracy.Numerical simulations are conducted in two types of waveguides to verify the FRD method.The impacts of environment configurations and noise levels on the precision of the extracted modal depth functions and wavenumbers are also investigated through simulation.展开更多
This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided t...This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided the theoretical basis for this study. A survey research design involving a stratified sampling technique was adopted. The descriptives on transport modes, amount and time spent revealed that 10 (76.9%) males and 3 (23.1%) females preferred bicycle as means of transportation, 7 (58.3%) males and 5 (41.7%) females preferred motorcycle, while a significant proportion 90 (53.9%) males and 77 (46.1%) females preferred tricycle, 80 (63.0%) males and 47 (37.0%) females preferred cars/taxis, and 12 (46.2%) males and 14 (53.8%) females preferred mass transit bus. However, 14 (46.7%) males and 16 (53.3%) females in marshy terrain and coastal locations preferred canoes and boats. The result of the logistic regression model revealed that gender modal preference is more likely to be influenced by mode of transportation with a beta weight of 1.140, safety considerations 1.139, ownership of transport 1.135 and distance to place of work 1.073. Hence, this study recommends that a combination of these factors should be incorporated into transport planning to achieve effective transport planning and sustainable development in the Yenagoa metropolis.展开更多
Background The bromodomain(BRD) proteins play a pivotal role in regulating gene expression by recognizing acetylated lysine residues and acting as chromatin-associated post-translational modification-inducing proteins...Background The bromodomain(BRD) proteins play a pivotal role in regulating gene expression by recognizing acetylated lysine residues and acting as chromatin-associated post-translational modification-inducing proteins. Although BRD proteins have been extensively studied in mammals, they have also been characterized in plants like Arabidopsis thaliana and Oryza sativa, where they regulate stress-responsive genes related to drought, salinity, and cold. However, their roles in cotton species remain unexplored.Results In this genome-wide comparative analysis, 145 BRD genes were identified in the tetraploid species(Gossypium hirsutum and G. barbadense), compared with 82 BRD genes in their diploid progenitors(G. arboreum and G. raimondii), indicating that polyploidization significantly influenced BRD gene evolution. Gene duplication analysis revealed 78.85% of duplications were segmental and 21.15% were tandem among 104 in-paralogous gene pairs, contributing to BRD gene expansion. Gene structure, motif, and domain analyses demonstrated that most genes were intron-less and conserved throughout evolution. Syntenic analysis revealed a greater number of orthologous gene pairs in the Dt sub-genome than in the At sub-genome. The abundance of regulatory, hormonal, and defense-related cis-regulatory elements in the promoter region suggests that BRD genes play a role in both biotic and abiotic stress responses. Protein-protein interaction analysis indicated that global transcription factor group E(GTE) transcription factors regulate BRD genes. Expression analysis revealed that BRD genes are predominantly involved in ovule development, with some genes displaying specific expression patterns under heat, cold, and salt stress. Furthermore, qRT-PCR analysis demonstrated significant differential expression of BRD genes between the tolerant and sensitive genotype, underscoring their potential role in mediating drought and salinity stress responses.Conclusions This study provides valuable insights into the evolution of BRD genes across species and their roles in abiotic stress tolerance, highlighting their potential in breeding programs to develop drought and salinity tolerant cotton varieties.展开更多
In the present paper,we give a systematic study of the discrete correspondence the-ory and topological correspondence theory of modal meet-implication logic and moda1 meet-semilattice logic,in the semantics provided i...In the present paper,we give a systematic study of the discrete correspondence the-ory and topological correspondence theory of modal meet-implication logic and moda1 meet-semilattice logic,in the semantics provided in[21].The special features of the present paper include the following three points:the first one is that the semantic structure used is based on a semilattice rather than an ordinary partial order,the second one is that the propositional vari-ables are interpreted as filters rather than upsets,and the nominals,which are the“first-order counterparts of propositional variables,are interpreted as principal filters rather than principal upsets;the third one is that in topological correspondence theory,the collection of admissi-ble valuations is not closed under taking disjunction,which makes the proof of the topological Ackermann 1emma different from existing settings.展开更多
Two cotton research institute(CRI)near-isogenic lines,CRI-12 glanded and CRI-12 glandless,were used to pinpoint potential genes and metabolic pathways linked to gossypol biosynthesis through transcriptome sequencing.W...Two cotton research institute(CRI)near-isogenic lines,CRI-12 glanded and CRI-12 glandless,were used to pinpoint potential genes and metabolic pathways linked to gossypol biosynthesis through transcriptome sequencing.We discovered more than 235 million clean reads and 1,184 differentially expressed genes(DEGs).Consecutively,we conducted a weighted gene co-expression network analysis and found a strong correlation between white and yellow modules containing GhTPS(GH_D09G0090)and GhCYP(GH_D05G2016)hub genes with the gossypol content.Importance of the GhTPS and GhCYP genes was demonstrated using RT-qPCR,virusinduced gene silencing(VIGS),and target metabolite analysis.Silencing these genes resulted in fewer glands on both leaves and stems two weeks after the infection compared to the wild type.In addition,152 metabolites were identified through targeted metabolite profiling.Differential metabolite screening revealed 12 and 18 significantly different metabolites in TRV:GhTPS and TRV:GhCYP plants vs.the control group,respectively,showing a reduction in the accumulation of metabolites compared to the control.Content of hemigossypol,the final product of gossypol biosynthesis,was also reduced,as revealed by target metabolite analysis,suggesting the role of these genes in the gossypol biosynthetic pathway.Furthermore,a highly significant difference in gossypol content between the glanded and glandless lines was recorded.Findings of this study reveal a strong link between the gossypol content and GhTPS and GhCYP hub genes,suggesting their role in the gossypol biosynthetic pathway to reduce the accumulation of hemigossypol,which may offer new comprehension into the regulatory checkpoints of the gossypol biosynthesis pathway in cotton.展开更多
Background Thidiazuron(TDZ)is a widely used chemical defoliant in commercial cotton production and is often combined with the herbicide Diuron to form the commercial defoliant mixture known as TDZ·Diuron(T·D...Background Thidiazuron(TDZ)is a widely used chemical defoliant in commercial cotton production and is often combined with the herbicide Diuron to form the commercial defoliant mixture known as TDZ·Diuron(T·D,540 g·L^(-1)suspension).However,due to increasing concerns about the environmental and biological risks posed by Diuron,there is an urgent need to develop safer and more effective alternatives.Jasmonic acid(JA)and its derivatives are key phytohormones in organ senescence and abscission.Results Greenhouse experiments at the seedling stage revealed that Me-JA(0.8 mmol·L^(-1))alone did not induce defoliation.However,its co-application with TDZ(0.45 mmol·L^(-1))at concentrations of 0.6,0.8,and 1.0 mmol·L^(-1)significantly enhanced defoliation efficacy.The most effective combination—TDZ with 0.8 mmol·L^(-1)Me-JA—achieved a 100%defoliation rate at 5 days after treatment(DAT),23.7 percentage points higher than TDZ alone,and comparable to the commercial TDZ·Diuron formulation with equivalent TDZ content.Field trials conducted in Beijing(Shangzhuang),Hebei(Hejian),and Xinjiang(Shihezi)confirmed that the combination of 0.6 mmol·L^(-1)Me-JA with 1.70 mmol·L^(-1)TDZ provided optimal defoliation performance.At 21 DAT,the defoliation rate increased by 13.5–16.3 percentage points compared with TDZ alone.Furthermore,boll opening rates improved by 5.7–12.7 percentage points relative to TDZ-only treatments.Phytohormonal analyses from the Shangzhuang site showed that the combined treatment significantly altered hormone levels in both leaves and petioles.Compared with TDZ alone,the mixture reduced concentrations of auxin(IAA),cytokinins(Z+ZR,iP+iPA,DHZ+DHZR),and gibberellic acid(GA3),while increasing levels of JA,abscisic acid(ABA),and brassinosteroids(BR).These hormonal shifts may underlie the enhanced defoliation observed with the combined treatment.Importantly,the TDZ-Me-JA combination did not adversely affect cotton yield,yield components,or fiber quality.Conclusion The combination of Me-JA and TDZ has a good defoliation effect without affecting crop yield or fiber quality.And it provides a promising foundation for the development of novel,environmentally friendly cotton defoliants.展开更多
Background Unravelling the relationship between trichome density and resistance to jassids in upland cotton,nine parental lines,viz.MCU 5,CO 14,CO 17,TCH 1828,KC 2,KC 3,GISV 323,GTHV 15–34,and RHC 1409 were obtained ...Background Unravelling the relationship between trichome density and resistance to jassids in upland cotton,nine parental lines,viz.MCU 5,CO 14,CO 17,TCH 1828,KC 2,KC 3,GISV 323,GTHV 15–34,and RHC 1409 were obtained from the Tamilnadu Agricultural University.These genotypes were subjected to molecular analysis using 27 primers,merely the JESPR 154 primer amplifying a 150-bp fragment in genotypes exhibiting the pubescence.Result This finding validated the association between pubescence and jassid resistance.Further analysis revealed that resistant genotypes(KC 3,GTHV 15–34,GISV 323,and RHC 1409)exhibited significantly higher trichome densities and length compared with susceptible genotypes.These results stalwartly support the hypothesis that trichomes play a pivotal role in conferring resistance to jassids in upland cotton.Conclusion By breeding cotton varieties with increased trichome density and length,it is possible to reduce jassid infestations,thereby decreasing the reliance on chemical pesticides and promoting a more sustainable agricultural environment.展开更多
基金supported by the Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金supported by the Science and Technology Program of Xinjiang Construction Corps(No.2024AB064)the National Natural Science Foundation of China(Nos.41975044,42001314)。
文摘Climate change is significantly impacting cotton production in the Tarim River Basin.The study investigated the climate change characteristics from 2021 to 2100 using climate change datasets simulated per the coupled model inter-comparison project phase six(CMIP6)climatic patterns under the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5.The DSSAT-CROPGROCotton model,along with stepwise multiple regression analyses,was used to simulate changes in the potential yield of seed cotton due to climate change.The results show that while future temperatures in the Tarim River Basin will rise significantly,changes in precipitation and radiation during the cotton-growing season are minimal.Seed cotton yields are more sensitive to low temperatures than to precipitation and radiation.The potential yield of seed cotton under the SSP2-4.5 scenario would increase by 14.8%,23.7%,29.0%,and 29.4%in the 2030S,2050S,2070S,and 2090S,respectively.In contrast,under the SSP5-8.5 scenario,the potential yield of seed cotton would see increases of 17.5%,27.1%,30.1%,and 22.6%,respectively.Except for the 2090s under the SSP5-8.5 scenario,future seed cotton production can withstand a 10%to 20%deficit in irrigation.These findings will help develop climate change adaptation strategies for cotton cultivation.
基金The Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences——A Strategic Study on Healthy China Development and Health System Reform(2021-I2M-1-046).
文摘Objective Traditional Chinese medicine(TCM)incorporates traditional diagnostic methods and several major treatment modalities including Chinese herbal medicine,Chinese patent medicine,and non-pharmacological methods such as acupuncture and tuina.Even though TCM is used daily by more than 70,000 healthcare facilities and over 700,000 clinical practitioners in China,there is a poor understanding of the extent to which TCM diagnostic methods are used,how different treatment modalities are deployed in general,and what major factors may affect the integration of TCM and Western medicine.This study aimed to fill this void in the literature.Methods In the 2021 National Healthcare Improvement Evaluation Survey,we included three questions gauging the perception and practices of TCM amongst physicians working in TCM-related facilities,investigating the frequency of their deployment of TCM diagnostic methods,and predominant TCM treatment methods.Our empirical analysis included descriptive statistics,intergroup chi-square analysis,and binary logistic regression to examine the association between different types of facilities and individual characteristics and TCM utilization patterns.Results A total of 7618 clinical physicians comprised our study sample.Among them,84.27%have integrated TCM and Western medicine in their clinical practice,and 80.77%of TCM practitioners used the 4 diagnostic methods as a tool in their clinical practice.Chinese herbal medicine was the most widely utilized modality by Chinese TCM physicians(used by 88.49%of respondents),compared with the Chinese patent medicine and non-pharmacological TCM methods,which were used by 73.14%,and 69.39%,respectively.Herbal tea as an out-of-pocket health-maintenance intervention is also a notable practice,recommended by 29.43%of physicians.Significant variations exist across certain institutions,departments,and individual practitioners.Conclusion Given that most of the surveyed physicians integrated TCM with Western medicine in their clinical practices,the practice of“pure TCM”appears to be obsolete in China’s tertiary healthcare institutions.Notably,remarkable variation exists in the use of different TCM modalities across institutions and among individuals,which might be related to and thus limited by the practitioners’experience.Future research focusing on the efficacy and safety of TCM interventions for specific diseases,the development of standardized clinical guidelines,and the enhancement of TCM education and training are called for to optimize TCM-Western medicine integration.
基金Funding support for the Crop Pest Surveillance and Advisory Project(CROPSAP)。
文摘Background Cotton crop is infested by numerous arthropod pests from sowing to harvesting,causing substantial direct and indirect yield losses.Knowledge of seasonal population trends and the relative occurrence of pests and their natural enemies is required to minimize the pest population and yield losses.In the current study,analysis of the seasonal population trend of pests and natural enemies and their relative occurrence on cultivars of three cotton species in Central India has been carried out.Results A higher number and diversity of sucking pests were observed during the vegetative cotton growth stage(60 days after sowing),declining as the crop matured.With the exception of cotton jassid(Amrasca biguttula biguttula Ishida),which caused significant crop damage mainly from August to September;populations of other sucking insects seldom reached economic threshold levels(ETL)throughout the studied period.The bollworm complex populations were minimal,except for the pink bollworm(Pectinophora gossypiella Saunders),which re-emerged as a menace to cotton crops during the cotton cropping season 2017–2018 due to resistance development against Bt-cotton.A reasonably good number of predatory arthropods,including coccinellids,lacewings,and spiders,were found actively preying on the arthropod pest complex of the cotton crop during the early vegetative growth stage.Linear regression indicates a significant relationship between green boll infestations and pink bollworm moths in pheromone traps.Multiple linear regression analyse showed mean weekly weather at one-or two-week lag periods had a significant impact on sucking pest population(cotton aphid,cotton jassid,cotton whitefly,and onion thrips)fluctuation.Gossypium hirsutum cultivars RCH 2 and DCH 32,and G.barbadense cultivar Suvin were found susceptible to cotton jassid and onion thrips.Phule Dhanvantary,an G.arboreum cotton cultivar,demonstrated the highest tolerance among all evaluated cultivars against all sucking pests.Conclusion These findings have important implications for pest management in cotton crops.Susceptible cultivars warrant more attention for plant protection measures,making them more input-intensive.The choice of appropriate cultivars can help minimize input costs,thereby increasing net returns for cotton farmers.
基金supported in part by the Six Talent Peaks Project in Jiangsu Province under Grant 013040315in part by the China Textile Industry Federation Science and Technology Guidance Project under Grant 2017107+1 种基金in part by the National Natural Science Foundation of China under Grant 31570714in part by the China Scholarship Council under Grant 202108320290。
文摘The cleanliness of seed cotton plays a critical role in the pre-treatment of cotton textiles,and the removal of impurity during the harvesting process directly determines the quality and market value of cotton textiles.By fusing band combination optimization with deep learning,this study aims to achieve more efficient and accurate detection of film impurities in seed cotton on the production line.By applying hyperspectral imaging and a one-dimensional deep learning algorithm,we detect and classify impurities in seed cotton after harvest.The main categories detected include pure cotton,conveyor belt,film covering seed cotton,and film adhered to the conveyor belt.The proposed method achieves an impurity detection rate of 99.698%.To further ensure the feasibility and practical application potential of this strategy,we compare our results against existing mainstream methods.In addition,the model shows excellent recognition performance on pseudo-color images of real samples.With a processing time of 11.764μs per pixel from experimental data,it shows a much improved speed requirement while maintaining the accuracy of real production lines.This strategy provides an accurate and efficient method for removing impurities during cotton processing.
基金funded through India Meteorological Department,New Delhi,India under the Forecasting Agricultural output using Space,Agrometeorol ogy and Land based observations(FASAL)project and fund number:No.ASC/FASAL/KT-11/01/HQ-2010.
文摘Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.
文摘Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planting system(HDPS)offers a viable method to enhance productivity by increasing plant populations per unit area,optimizing resource utilization,and facilitating machine picking.Cotton is an indeterminate plant that produce excessive vegeta-tive growth in favorable soil fertility and moisture conditions,which posing challenges for efficient machine picking.To address this issue,the application of plant growth retardants(PGRs)is essential for controlling canopy architecture.PGRs reduce internode elongation,promote regulated branching,and increase plant compactness,making cotton plants better suited for machine picking.PGRs application also optimizes photosynthates distribution between veg-etative and reproductive growth,resulting in higher yields and improved fibre quality.The integration of HDPS and PGRs applications results in an optimal plant architecture for improving machine picking efficiency.However,the success of this integration is determined by some factors,including cotton variety,environmental conditions,and geographical variations.These approaches not only address yield stagnation and labour shortages but also help to establish more effective and sustainable cotton farming practices,resulting in higher cotton productivity.
基金supported by the National Social Science Fund of China(No.20CZX048)。
文摘In modal logic,topological semantics is an intuitive and natural special case of neighbourhood semantics.This paper stems from the observation that the satisfaction relation of topological semantics applies to subset spaces which are more general than topological spaces.The minimal modal logic which is strongly sound and complete with respect to the class of subset spaces is found.Soundness and completeness results of some famous modal logics(e.g.S4,S5 and Tr)with respect to various important classes of subset spaces(eg intersection structures and complete fields of sets)are also proved.In the meantime,some known results,e.g.the soundness and completeness of Tr with respect to the class of discrete topological spaces,are proved directly using some modifications of the method of canonical mode1,without a detour via neighbourhood semantics or relational semantics.
基金Supported by Major Project of Agricultural Biological Breeding(2024AB001)Germplasm Resource Innovation of Early-maturing Machine-picked Cotton in the Northern Xinjiang(2023RC04)New Germplasm Creation and Variety Selection and Application of Early-maturing and Anti-stress Machine-picked Cotton(2021NY01).
文摘The early-maturing cotton planting area in northern Xinjiang is a significant high-quality cotton production region in China.The screening and identification of early-maturing cotton germplasm resources are essential for the selection and breeding of early-maturing machine-picked cotton varieties,thereby facilitating the development of high-quality early-maturing machine-picked cotton materials.In this study,19 self-fertilized early-maturing materials were screened and identified.Among these,the varieties G15 and G9 were selected based on their superior overall traits.Notably,the G9 variety exhibited exceptional early-maturing characteristics,with a reproductive period of 116 d.
基金National Natural Science Foundation of China(3216045632360474+2 种基金32360486)grants from the Provincial Basic Research Program(Natural Science)([2020]1Z018)Provincial Key Technology R&D Program([2021]YiBan272).
文摘Seed priming is an effective seed pretreatment technology that enhances germination and overall crop performance by optimizing seed hydration and metabolic processes before planting.Seed quality is a critical determinant of cotton(Gossypium hirsutum)crop performance,influencing germination,plant vigor,and yield.This study evaluates the effects of seed priming with potassium salts(1%and 2%KCl and K2SO4)on germination,morphological traits,and Cry1Ac gene expression in three Bt cotton cultivars(IUB-2013,NIAB-878B,FH-142)as Cry1Ac enhance the pest resistance in Bt cotton and reduce the plant’s dependence on chemical insecticides.Seeds were primed for six hours,air-dried,and sown in the field.Germination rates,plant height,number of bolls per plant,boll weight,seed cotton yield,and ginning outturn(GOT)were assessed at crop maturity.Cry1Ac gene expression was quantified to explore the influence of priming treatments on transgene activity.Results demonstrated that 1%K2SO4 priming significantly enhanced germination and yield-related traits,with Cry1Ac expression peaking in the IUB-2013 cultivar under 1%K2SO4 treatment.These findings suggest that potassium-based halopriming improves cotton seedling establishment and Bt gene expression.This study addresses the critical gaps in understanding the effects of seed halopriming on morphological traits,germination,and expression of the Cry1Ac gene in Bt cotton while providing a novel eco-friendly and cost-effective halopriming approach,offering the potential to improve cotton production.
基金supported by the National Natural Science Foundation of China(Nos.12304504,12304506 and U22 A2012)the Youth Innovation Promotion Association,Chinese Academy of Sciences(No.2021023)+1 种基金the Strategy Priority Research Program(Category B)of Chinese Academy of Sciences(Nos.XDB0700100 and XDB0700000)the Natural Science Foundation of Tianjin(No.22JCYBJC00070).
文摘Normal mode extraction has attracted extensive attention over the past few decades due to its practical value in enhancing the performance of underwater acoustic signal processing.Singular value decomposition(SVD)is an effective method to extract modal depth functions using vertical line arrays(VLA),particularly in scenarios when no prior environment information is available.However,the SVD method requires rigorous orthogonality conditions,and its performance severely degenerates in the presence of mode degeneracy.Consequently,the SVD approach is often not feasible in practical scenarios.This paper proposes a full rank decomposition(FRD)method to address these issues.Compared to the SVD method,the FRD method has three distinct advantages:1)the conditions that the FRD method requires are much easier to be fulfilled in practical scenarios;2)both modal depth functions and wavenumbers can be simultaneously extracted via the FRD method;3)the FRD method is not affected by the phenomenon of mode degeneracy.Numerical simulations are conducted in two types of waveguides to verify the FRD method.The impacts of environment configurations and noise levels on the precision of the extracted modal depth functions and wavenumbers are also investigated through simulation.
文摘This study examined gender differences in modal choice among residents of coastal communities of Yenagoa metropolis in Bayelsa State, Nigeria. The Four-Step model of transportation planning and modal choice provided the theoretical basis for this study. A survey research design involving a stratified sampling technique was adopted. The descriptives on transport modes, amount and time spent revealed that 10 (76.9%) males and 3 (23.1%) females preferred bicycle as means of transportation, 7 (58.3%) males and 5 (41.7%) females preferred motorcycle, while a significant proportion 90 (53.9%) males and 77 (46.1%) females preferred tricycle, 80 (63.0%) males and 47 (37.0%) females preferred cars/taxis, and 12 (46.2%) males and 14 (53.8%) females preferred mass transit bus. However, 14 (46.7%) males and 16 (53.3%) females in marshy terrain and coastal locations preferred canoes and boats. The result of the logistic regression model revealed that gender modal preference is more likely to be influenced by mode of transportation with a beta weight of 1.140, safety considerations 1.139, ownership of transport 1.135 and distance to place of work 1.073. Hence, this study recommends that a combination of these factors should be incorporated into transport planning to achieve effective transport planning and sustainable development in the Yenagoa metropolis.
文摘Background The bromodomain(BRD) proteins play a pivotal role in regulating gene expression by recognizing acetylated lysine residues and acting as chromatin-associated post-translational modification-inducing proteins. Although BRD proteins have been extensively studied in mammals, they have also been characterized in plants like Arabidopsis thaliana and Oryza sativa, where they regulate stress-responsive genes related to drought, salinity, and cold. However, their roles in cotton species remain unexplored.Results In this genome-wide comparative analysis, 145 BRD genes were identified in the tetraploid species(Gossypium hirsutum and G. barbadense), compared with 82 BRD genes in their diploid progenitors(G. arboreum and G. raimondii), indicating that polyploidization significantly influenced BRD gene evolution. Gene duplication analysis revealed 78.85% of duplications were segmental and 21.15% were tandem among 104 in-paralogous gene pairs, contributing to BRD gene expansion. Gene structure, motif, and domain analyses demonstrated that most genes were intron-less and conserved throughout evolution. Syntenic analysis revealed a greater number of orthologous gene pairs in the Dt sub-genome than in the At sub-genome. The abundance of regulatory, hormonal, and defense-related cis-regulatory elements in the promoter region suggests that BRD genes play a role in both biotic and abiotic stress responses. Protein-protein interaction analysis indicated that global transcription factor group E(GTE) transcription factors regulate BRD genes. Expression analysis revealed that BRD genes are predominantly involved in ovule development, with some genes displaying specific expression patterns under heat, cold, and salt stress. Furthermore, qRT-PCR analysis demonstrated significant differential expression of BRD genes between the tolerant and sensitive genotype, underscoring their potential role in mediating drought and salinity stress responses.Conclusions This study provides valuable insights into the evolution of BRD genes across species and their roles in abiotic stress tolerance, highlighting their potential in breeding programs to develop drought and salinity tolerant cotton varieties.
基金supported by the Chinese Ministry of Education of Humanities and Social Science Project(23YJC72040003)the Key Project of Chinese Ministry of Education(22JJD720021)supported by the Natural Science Foundation of Shandong Province,China(project number:ZR2023QF021)。
文摘In the present paper,we give a systematic study of the discrete correspondence the-ory and topological correspondence theory of modal meet-implication logic and moda1 meet-semilattice logic,in the semantics provided in[21].The special features of the present paper include the following three points:the first one is that the semantic structure used is based on a semilattice rather than an ordinary partial order,the second one is that the propositional vari-ables are interpreted as filters rather than upsets,and the nominals,which are the“first-order counterparts of propositional variables,are interpreted as principal filters rather than principal upsets;the third one is that in topological correspondence theory,the collection of admissi-ble valuations is not closed under taking disjunction,which makes the proof of the topological Ackermann 1emma different from existing settings.
基金financial help from the National Key R&D Program of China(2021YFE0101200)the Key Research and Development Project of Jiangsu Province,China(Modern Agriculture,BE2022364)+1 种基金the State Key Laboratory of Cotton Bio-breeding and Integrated Utilization Open Fund,China(CB2024A06)support of the Ministry of Science,Technological Development and Innovation of the Republic of Serbia(451-03-66/2024-03/200007)。
文摘Two cotton research institute(CRI)near-isogenic lines,CRI-12 glanded and CRI-12 glandless,were used to pinpoint potential genes and metabolic pathways linked to gossypol biosynthesis through transcriptome sequencing.We discovered more than 235 million clean reads and 1,184 differentially expressed genes(DEGs).Consecutively,we conducted a weighted gene co-expression network analysis and found a strong correlation between white and yellow modules containing GhTPS(GH_D09G0090)and GhCYP(GH_D05G2016)hub genes with the gossypol content.Importance of the GhTPS and GhCYP genes was demonstrated using RT-qPCR,virusinduced gene silencing(VIGS),and target metabolite analysis.Silencing these genes resulted in fewer glands on both leaves and stems two weeks after the infection compared to the wild type.In addition,152 metabolites were identified through targeted metabolite profiling.Differential metabolite screening revealed 12 and 18 significantly different metabolites in TRV:GhTPS and TRV:GhCYP plants vs.the control group,respectively,showing a reduction in the accumulation of metabolites compared to the control.Content of hemigossypol,the final product of gossypol biosynthesis,was also reduced,as revealed by target metabolite analysis,suggesting the role of these genes in the gossypol biosynthetic pathway.Furthermore,a highly significant difference in gossypol content between the glanded and glandless lines was recorded.Findings of this study reveal a strong link between the gossypol content and GhTPS and GhCYP hub genes,suggesting their role in the gossypol biosynthetic pathway to reduce the accumulation of hemigossypol,which may offer new comprehension into the regulatory checkpoints of the gossypol biosynthesis pathway in cotton.
基金funded by the China Agriculture Research System(CARS–15–16)。
文摘Background Thidiazuron(TDZ)is a widely used chemical defoliant in commercial cotton production and is often combined with the herbicide Diuron to form the commercial defoliant mixture known as TDZ·Diuron(T·D,540 g·L^(-1)suspension).However,due to increasing concerns about the environmental and biological risks posed by Diuron,there is an urgent need to develop safer and more effective alternatives.Jasmonic acid(JA)and its derivatives are key phytohormones in organ senescence and abscission.Results Greenhouse experiments at the seedling stage revealed that Me-JA(0.8 mmol·L^(-1))alone did not induce defoliation.However,its co-application with TDZ(0.45 mmol·L^(-1))at concentrations of 0.6,0.8,and 1.0 mmol·L^(-1)significantly enhanced defoliation efficacy.The most effective combination—TDZ with 0.8 mmol·L^(-1)Me-JA—achieved a 100%defoliation rate at 5 days after treatment(DAT),23.7 percentage points higher than TDZ alone,and comparable to the commercial TDZ·Diuron formulation with equivalent TDZ content.Field trials conducted in Beijing(Shangzhuang),Hebei(Hejian),and Xinjiang(Shihezi)confirmed that the combination of 0.6 mmol·L^(-1)Me-JA with 1.70 mmol·L^(-1)TDZ provided optimal defoliation performance.At 21 DAT,the defoliation rate increased by 13.5–16.3 percentage points compared with TDZ alone.Furthermore,boll opening rates improved by 5.7–12.7 percentage points relative to TDZ-only treatments.Phytohormonal analyses from the Shangzhuang site showed that the combined treatment significantly altered hormone levels in both leaves and petioles.Compared with TDZ alone,the mixture reduced concentrations of auxin(IAA),cytokinins(Z+ZR,iP+iPA,DHZ+DHZR),and gibberellic acid(GA3),while increasing levels of JA,abscisic acid(ABA),and brassinosteroids(BR).These hormonal shifts may underlie the enhanced defoliation observed with the combined treatment.Importantly,the TDZ-Me-JA combination did not adversely affect cotton yield,yield components,or fiber quality.Conclusion The combination of Me-JA and TDZ has a good defoliation effect without affecting crop yield or fiber quality.And it provides a promising foundation for the development of novel,environmentally friendly cotton defoliants.
文摘Background Unravelling the relationship between trichome density and resistance to jassids in upland cotton,nine parental lines,viz.MCU 5,CO 14,CO 17,TCH 1828,KC 2,KC 3,GISV 323,GTHV 15–34,and RHC 1409 were obtained from the Tamilnadu Agricultural University.These genotypes were subjected to molecular analysis using 27 primers,merely the JESPR 154 primer amplifying a 150-bp fragment in genotypes exhibiting the pubescence.Result This finding validated the association between pubescence and jassid resistance.Further analysis revealed that resistant genotypes(KC 3,GTHV 15–34,GISV 323,and RHC 1409)exhibited significantly higher trichome densities and length compared with susceptible genotypes.These results stalwartly support the hypothesis that trichomes play a pivotal role in conferring resistance to jassids in upland cotton.Conclusion By breeding cotton varieties with increased trichome density and length,it is possible to reduce jassid infestations,thereby decreasing the reliance on chemical pesticides and promoting a more sustainable agricultural environment.
