Quantifying source-sink relationships in leaf-color modified rice genotypes during grain filling

Leaf-color modification can affect canopy photosynthesis,with potential effects on rice yield and yield components.Modulating source-sink relationships through crop management is often used to improve crop productivity.This study investigated whether and how modifying leaf color alters source-sink relationships and whether current crop cultivation practices remain applicable for leaf-color modified genotypes.Periodically collected data of total biomass and nitrogen(N)accumulation in rice genotypes of four genetic backgrounds and their leaf-color modified variants(greener or yellower)were analyzed,using a recently established modelling method to quantify the source-sink(im)balance during grain filling.Among all leaf-color variants,only one yellower-leaf variant showed a higher source capacity than its normal genotype.This was associated with greater post-flowering N-uptake that prolonged the functional leaf-N duration,and this greater post-flowering N-uptake was possible because of reduced pre-flowering N-uptake.A density experiment showed that current management practices(insufficient planting density accompanied by abundant N application)are unsuitable for the yellower-leaf genotype,ultimately limiting its yield potential.Leaf-color modification affects source-sink relationships by regulating the N trade-off between pre-and post-flowering uptake,as well as N translocation between source and sink organs.To best exploit leaf-color modification for improving crop productivity,adjustments of crop management practices are required.

What diameter?What height?Influence of measures of average tree size on area-based allometric volume relationships

Volume is an important attribute used in many forest management decisions.Data from 83 fixed-area plots located in central New Brunswick,Canada,are used to examine how different measures of stand-level diameter and height influence volume prediction using a stand-level variant of Honer's(1967)volume equation.When density was included in the models(Volume=f(Diameter,Height,Density))choice of diameter measure was more important than choice of height measure.When density was not included(Volume=f(Diameter,Height)),the opposite was true.For models with density included,moment-based estimators of stand diameter and height performed better than all other measures.For models without density,largest tree estimators of stand diameter and height performed better than other measures.The overall best equation used quadratic mean diameter,Lorey's height,and density(root mean square error=5.26 m^3·ha^(-1);1.9%relative error).The best equation without density used mean diameter of the largest trees needed to calculate a stand density index of 400 and the mean height of the tallest 400 trees per ha(root mean square error=32.08 m^(3)·ha^(-1);11.8%relative error).The results of this study have some important implications for height subsampling and LiDAR-derived forest inventory analyses.

Three anti-inflammatory polysaccharides from Lonicera japonica Thunb.:insights into the structure-function relationships

This study demonstrates the feasibility of producing three polysaccharides(neutral LJP-1,acidic LJP-2 and acidic LJP-3)with significant in vitro and in vivo anti-inflammatory activities from the flowers of Lonicera japonica.The three polysaccharides differed in chemical composition,molecular weight(Mw)distribution,glycosidic linkage pattern,functional groups and morphology.They exhibited excellent protective effects(in a dose-dependent manner)in lipopolysaccharide-injured RAW264.7 macrophages and Cu SO4-damaged zebrafish via reducing NO production and inhibiting the overexpressions of inflammation-related transcription factors,inflammatory proteins and cytokines in the NF-κB/MAPK signaling pathways.Their antiinflammatory effects varied owing to their different molecular characteristics and chemical compositions.Overall,LJP-2 at 400μg/m L was the most effective.LJP-2 consisted mainly of→5)-α-L-Araf(1→,→4)-α-LGalp A(1→and→2)-α-L-Rhap(1→residues with terminal T-β-D-Glcp.Thus,honeysuckle flowers are good sources of anti-inflammatory polysaccharides,and precise fractionation enables the production of potent antiinflammatory agents for the development of functional foods and healthcare products.

Characterizing permeability-porosity relationships of porous rocks using a stress sensitivity model in consideration of elastic-structural deformation and tortuosity sensitivity

Clarifying the relationship between stress sensitivities of permeability and porosity is of great significance in guiding underground resource mining.More and more studies focus on how to construct stress sensitivity models to describe the relationship and obtain a comprehensive stress sensitivity of porous rock.However,the limitations of elastic deformation calculation and incompleteness of considered tortuosity sensitivity lead to the fact that the existing stress sensitivity models are still unsatisfactory in terms of accuracy and generalization.Therefore,a more accurate and generic stress sensitivity model considering elastic-structural deformation of capillary cross-section and tortuosity sensitivity is proposed in this paper.The elastic deformation is derived from the fractal scaling model and Hooke's law.Considering the effects of elastic-structural deformation on tortuosity sensitivity,an empirical formula is proposed,and the conditions for its applicability are clarified.The predictive performance of the proposed model for the permeability-porosity relationships is validated in several sets of publicly available experimental data.These experimental data are from different rocks under different pressure cycles.The mean and standard deviation of relative errors of predicted stress sensitivity with respect to experimental data are 2.63%and 1.91%.Compared with other models,the proposed model has higher accuracy and better predictive generalization performance.It is also found that the porosity sensitivity exponent a,which can describe permeability-porosity relationships,is 2 when only elastic deformation is considered.a decreases from 2 when structural deformation is also considered.In addition,a may be greater than 3 due to the increase in tortuosity sensitivity when tortuosity sensitivity is considered even if the rock is not fractured.

Monitor and Acceptance among Couples in Romantic Relationships:Actor-Partner Interdependence Models Based on the Monitor and Acceptance Theory

Communication could be an essential part of couples in their daily life.Based on Monitor and Acceptance Theory(MAT),the present study explored the mediating role of communication in the relationship between mindfulness and relationship quality among college-student couples.The research examined the dynamic relationship of monitoring and acceptance to relationship satisfaction in the Actor-Partner Interdependence Model(APIM),and the mediating effect of positive or negative communications in these relationships.A total of 96 pairs of couples in the universities in Nanjing,China participated in the research.Momentary measurements were used to measure the momentary levels of their monitor,acceptance,positive/negative communication,and relationship satisfaction.A Hierarchical Linear Model(HLM)was used to deal with the APIM.Results showed that the women’s monitor facet of state mindfulness negatively predicted men’s relationship satisfaction through women’s negative communication,and the women’s acceptance facet of state mindfulness positively predicted women’s relationship satisfaction through women’s positive and negative communication at the within-person level.The study highlights the importance of cooperation in monitoring and acceptance for couples to own and hold high levels of relationship satisfaction.

Floristic composition and edaphic relationships in ferruginous campo rupestre reference ecosystems

Land use change and occupation have led to modifications in the environment causing loss of biodiversity and ecosystem services throughout the planet.Some environments with high economic relevance,such as the ferruginous campo rupestre(rupestrian grassland known as Canga in Brazil),are even more susceptible to severe impacts due to their extreme habitat conditions and low resilience.The determination of reference ecosystems based on the intrinsic characteristics of the ecosystem is essential for conservation as well as to the implementation of ecological restoration.We proposed the reference ecosystem of the three main types of habitats of the ferruginous campo rupestre based on their floristic composition.We described the floristic composition of each habitat and evaluated the physicochemical properties of the soils and the relationship between plants and soils.All three habitats showed high diversity of plant species and many endemic species,such as Chamaecrista choriophylla,Cuphea pseudovaccinium,Lychnophora pinaster,and Vellozia subalata.The distribution of vegetation was strongly related with the edaphic characteristics,with a set of species more adapted to high concentration of base saturation,fine sand,organic carbon,and iron,while another set of species succeeded in more acidic soils with higher S and silt concentration.We provide support for the contention that the ferruginous campo rupestre is a mosaic of different habitats shaped by intrinsic local conditions.Failure to recognize the floristic composition of each particular habitat can lead to inappropriate restoration,increased habitat homogenization and increased loss of biodiversity and ecosystem services.This study also advances the knowledge base for building the reference ecosystem for the different types of ferruginous campo rupestre habitats,as well as a key database for highlighting those species contribute most to community assembly in this diverse and threatened tropical mountain ecosystem.

Different mechanisms underlie similar species-area relationships in two tropical archipelagoes

Despite much research in the field of island biogeography,mechanisms regulating insular diversity remain elusive.Here,we aim to explore mechanisms underlying plant species-area relationships in two tropical archipelagoes in the South China Sea.We found positive plant species-area relationships for both coral and continental archipelagoes.However,our results showed that different mechanisms contributed to similar plant species-area relationships between the two archipelagoes.For coral islands,soil nutrients and spatial distance among communities played major roles in shaping plant community structure and species diversity.By contrast,the direct effect of island area,and to a lesser extent,soil nutrients determined plant species richness on continental islands.Intriguingly,increasing soil nutrients availability(N,P,K)had opposite effects on plant diversity between the two archipelagoes.In summary,the habitat quality effect and dispersal limitation are important for regulating plant diversity on coral islands,whereas the passive sampling effect,and to a lesser extent,the habitat quality effect are important for regulating plant diversity on continental islands.More generally,our findings indicate that island plant species-area relationships are outcomes of the interplay of both niche and neutral processes,but the driving mechanisms behind these relationships depends on the type of islands.

Modern pollen-vegetation relationships along altitudinal vegetation belts in the Leigong Mountain of southwestern China

Understanding the distribution,dispersal,and correlation of modern pollen with vegetation in mountainous regions is essential for establishing accurate modern analogs for fossil pollen records.This study,conducted in Leigong Mountain on the YunnanGuizhou Plateau of southwestern China,involved the collection of 35 surface soil samples from diverse vegetation communities along an elevational gradient ranging from 1210 to 1875 meters.The results reveal a close correspondence between modern pollen assemblages and vegetation zones.Principal Component Analysis(PCA)results indicate that pollen assemblages can effectively distinguish between subtropical montane evergreen broad-leaved forest(SEBF)and subtropical montane deciduous broadleaved forest(SDBF).However,both SEBF and SDBF show significant overlap with subtropical montane evergreen-deciduous broad-leaved mixed forest(SEMF).Detrended Correspondence Analysis(DCA)results clearly distinguish the three vegetation zones,and the first axis of DCA shows a significant positive correlation with elevation(p<0.01,R=0.48).Discriminant Analysis(DA)successfully assigns 94.4%of the modern pollen samples to their respective vegetation zones.Pollen taxa such as Impatiens,Astertype,and Rosaceae exhibit significant indicative capabilities for the SEBF zone,effectively distinguishing this vegetation zone from others.Pinus and Alnus display overrepresentation in the Leigong Mountain region,while Quercus(D,deciduous-type)and Poaceae exhibit high representation in the SEBF zone.In the SEBF zone,both pollen diversity and richness are the lowest.Our study reveals the complex relationship between the richness and diversity of pollen and vegetation.The diversity and richness of tree and shrub pollen are found to be lower than those of the corresponding plants.The pollen-vegetation relationship elucidated in this study serves as a critical reference for reconstructing ancient environments from fossil pollen retrieved in this region.

Predicting Users’ Latent Suicidal Risk in Social Media: An Ensemble Model Based on Social Network Relationships

Suicide has become a critical concern,necessitating the development of effective preventative strategies.Social media platforms offer a valuable resource for identifying signs of suicidal ideation.Despite progress in detecting suicidal ideation on social media,accurately identifying individuals who express suicidal thoughts less openly or infrequently poses a significant challenge.To tackle this,we have developed a dataset focused on Chinese suicide narratives from Weibo’s Tree Hole feature and introduced an ensemble model named Text Convolutional Neural Network based on Social Network relationships(TCNN-SN).This model enhances predictive performance by leveraging social network relationship features and applying correction factors within a weighted linear fusion framework.It is specifically designed to identify key individuals who can help uncover hidden suicidal users and clusters.Our model,assessed using the bespoke dataset and benchmarked against alternative classification approaches,demonstrates superior accuracy,F1-score and AUC metrics,achieving 88.57%,88.75%and 94.25%,respectively,outperforming traditional TextCNN models by 12.18%,10.84%and 10.85%.We assert that our methodology offers a significant advancement in the predictive identification of individuals at risk,thereby contributing to the prevention and reduction of suicide incidences.

The Risk Role of Defeat on the Mental Health of College Students:A Moderated Mediation Effect of Academic Stress and Interpersonal Relationships

Background:College students face significant academic and physiological changes,making them more susceptible to psychological issues such as depression,self-injury,and suicidal ideation.Feelings of defeat can exacerbate these risks by increasing academic stress.However,interpersonal relationships can moderate the impact of academic stress on students’mental health.Utilizing the presage–process–product model,this study aims to empirically investigate how feelings of defeat influence depression,self-injury,and suicidal ideation among college students.Additionally,it explores the mediating role of academic stress and the moderating role of various types of interpersonal relationships.Methods:A total of 1612 college students(750 females,862 males,mean age=19.64±0.62 years)were recruited through cluster sampling.Data were collected via offline questionnaires administered by a trained psychology teacher and a postgraduate student,ensuring high reliability with two examiners per class.Latent profile analysis(LPA)was used to examine the impact of defeat on mental health outcomes,while mediation analysis was conducted to assess the roles of academic stress and interpersonal relationships.Results:1.Defeat is identified as a significant risk factor for mental health issues among college students;2.Four distinct patterns of interpersonal relationships were identified:the interpersonal-relationship risk group,the father–child-relationship high-risk group,the general interpersonal-relationship group,and the superior interpersonal-relationship group;3.Academic stress partially mediates the relationship between defeat and mental health issues such as depression,self-injury,and suicidal ideation;4.Different interpersonal relationship models moderate the impact of academic stress on depression and suicidal ideation.Conclusion:Defeat is a significant risk factor for mental health problems in college students.Academic stress partially mediates the negative impact of defeat on mental health,while patterns of interpersonal relationships moderate this impact.Effective early prevention and intervention should focus on monitoring students’stress levels and fostering warm,positive parent–child relationships.

Adherence in Patients with Type 2 Diabetes and Depression and the Role of Physician-Patient Relationship: A Cross-Sectional Study

Background: Diabetes mellitus (DM) challenges health and quality of life of patients, families, and communities. Patients with comorbid depression are more likely to develop macrovascular and microvascular complications. The aim was to assess glycemic control and adherence in diabetic patients with comorbid depression. Further, the study evaluated the relationship between adherence and the physician-patient relationship. Methods: The study was conducted at Al-Agouza Family Medicine Center (AFMC) between February 2018 and March 2020. The included patients were between 35 - 80 years of age;had type 2 diabetes with hemoglobin A1c (HbA1c) ≥ 6.5%, fasting plasma glucose ≥ 126 mg/dl, and scored between 11 - 30 on the Beck Depression Inventory (BDI). Logistic regression, chi-square, and analysis of variance (ANOVA) were used to assess the relationship between depression, adherence, physician-patient relationship, and other variables. Results: The study included 100 eligible patients with a median BDI score of 20 (10 - 30). The median diabetic panel for patients was FBS 188 (126 - 348) mg/dl, PPS 282.50 (162 - 448) mg/dl, and HbA1c 9.5 (6.6 - 14.0)%. Depression and regular follow-up visits were statistically associated with improvement of diabetes symptoms (p = 0.019). There was a significant relationship (p 0.001) between adherence, regular follow-up visits, and knowledge of DM. Further, there was a significant relationship between the physician-patient relationship and DM improvement (p = 0.047). Conclusion: Physician-patient relationship was paramount to improving adherence and positive diabetes care. Our findings suggest a shift to a physician-patient relationship model with mutual agreement on medical decisions is highly recommended.

Research on the Evaluation System of Community Daycare Center Planning and Implementation from the Perspective of Subject-Object Relationships

Through literature review,we found that evaluations of urban planning implementation often focus narrowly on either the subject(stakeholders)or the object(projects),while micro-level aspects such as site selection and construction are primarily considered within the context of planning implementation.There is insufficient research on the evaluation of implementation.Community daycare centers play a crucial role in the community home care model,yet there is relatively little research on their usage efficiency,satisfaction levels,and spatial evaluation of planning implementation.Based on the theoretical understanding of the human environment,including the subject,object,and their interactions,an evaluation system for the planning and implementation of community day care centers was constructed,incorporating subjective evaluation,objective evaluation,and comparative analysis.

Optimizing Spatial Relationships in GCN to Improve the Classification Accuracy of Remote Sensing Images

Semantic segmentation of remote sensing images is one of the core tasks of remote sensing image interpretation.With the continuous develop-ment of artificial intelligence technology,the use of deep learning methods for interpreting remote-sensing images has matured.Existing neural networks disregard the spatial relationship between two targets in remote sensing images.Semantic segmentation models that combine convolutional neural networks(CNNs)and graph convolutional neural networks(GCNs)cause a lack of feature boundaries,which leads to the unsatisfactory segmentation of various target feature boundaries.In this paper,we propose a new semantic segmentation model for remote sensing images(called DGCN hereinafter),which combines deep semantic segmentation networks(DSSN)and GCNs.In the GCN module,a loss function for boundary information is employed to optimize the learning of spatial relationship features between the target features and their relationships.A hierarchical fusion method is utilized for feature fusion and classification to optimize the spatial relationship informa-tion in the original feature information.Extensive experiments on ISPRS 2D and DeepGlobe semantic segmentation datasets show that compared with the existing semantic segmentation models of remote sensing images,the DGCN significantly optimizes the segmentation effect of feature boundaries,effectively reduces the noise in the segmentation results and improves the segmentation accuracy,which demonstrates the advancements of our model.

Mediating role of physical activity in the relationship between psychological distress and intimate relationships among stroke patients

BACKGROUND Stroke patients often experience psychological distress,which can impact their intimate relationships with spouses,subsequently influencing their treatment and recovery.Physical activity is considered a key rehabilitation method for stroke patients.This paper aims to analyze whether psychological distress affects intimate relationship between spouses through physical activity.AIM To explore the mediating effect of physical activity between psychological distress and intimate relationship in stroke patients.METHODS A total of 256 stroke patients who underwent treatment at the First People’s Hospital of Shangqiu between July 2021 and July 2022 were enrolled in this study.The participants completed questionnaires,including the Kessler Psychological Distress Scale(K10),the Quality of Relationship Index(QRI),International Physical Activity Questionnaire,and a general information questionnaire.Data analysis were performed using SPSS 23.0.The Harman test was employed to detect common method deviations,and Spearman correlation was used for correlation analysis.The mediating effect was assessed using Process 3.4.1,with significance testing of the regression coefficients conducted using the bias-corrected percentile Bootstrap method(5000 iterations,95%confidence interval).Statistical significance was set at P<0.05.RESULTS The results showed that patients scored an average of 21.61±6.44 points on the K10,32.40±6.19 points on the QRI;the median physical activity level according to the International Physical Activity Questionnaire was 1861(566,2846)MET·min/w.The level of physical activity(the physical activity intensity of the patients reflected by the Interna-tional Physical Activity Questionnaire-Long Form scale)negatively correlated with psychological distress and intimacy(P<0.05),and positively correlated with each other(P<0.05),with the correlation stronger at lower physical activity levels compared to higher ones.The mediating effect of physical activity between psychological distress and intimate relationship was calculated to be 40.23%.Bootstrap analysis further validated the results.The mediating effect of psychological distress on intimate relationships through physical activity level was-0.284,with a confidence interval of-0.409 to-0.163,excluding 0,confirming a significant mediating effect of psychological distress on intimate relationships.CONCLUSION Physical activity significantly affects relationship between psychological distress and intimate relationships among stroke patients.Addressing the role of physical activity may have implications for improving patient outcomes and rehabilitation strategies.

Relationship between Kawasaki disease and abdominal pain

This editorial presents an analysis of an article recently published in the World Journal of Clinical Cases.Kawasaki disease(KD)is a well-known pediatric vasculitis characterized by fever,rash,conjunctivitis,oral mucosal changes,and swelling of the extremities.This editorial aims to delve into the intricate relationship between KD and abdominal pain,drawing insights from recent research findings to provide a comprehensive understanding and potential avenues for future investigation.

Four new orientation relationships of Mg_(17)Al_(12) phase with magnesium matrix in Mg-8Al-0.5Zn alloys

Although the non-basal precipitates, those not parallel to the basal plane, are more effective to block basal slip in Mg-Al alloys, the crystallographic orientation relationship(OR) between these precipitates and the α-Mg matrix has not been well established. In this work, the crystallography of the non-basal Mg_(17)Al_(12) precipitates in AZ80 alloy was systematically investigated by transmission electron microscopy(TEM). By tilting to a suitable electron beam direction, different kinds of non-basal precipitates were recognized in TEM, and the following four new ORs between the non-basal Mg_(17)Al_(12) precipitates and the matrix were revealed: ■, and ■.Furthermore, these ORs and their habit planes were explained using the edge-to-edge matching model. The findings in this work can provide some guidelines for designing the microstructure of Mg-Al alloys to enhance their precipitation hardening potential.

Structure-guided Capacitance Relationships in Oxidized Graphene Porous Materials Based Supercapacitors

Supercapacitors formed from porous carbon and graphene-oxide(GO)materials are usually dominated by either electric double-layer capacitance,pseudo-capacitance,or both.Due to these combined features,reduced GO materials have been shown to offer superior capacitance over typical nanoporous carbon materials;however,there is a significant variation in reported values,ranging between 25 and 350 F g^(−1).This undermines the structure(e.g.,oxygen functionality and/or surface area)-performance relationships for optimization of cost and scalable factors.This work demonstrates important structure-controlled charge storage relationships.For this,a series of exfoliated graphene(EG)derivatives are produced via thermal-shock exfoliation of GO precursors and following controlled graphitization of EG(GEG)generates materials with varied amounts of porosity,redox-active oxygen groups and graphitic components.Experimental results show significantly varied capacitance values between 30 and 250 F g^(−1)at 1.0 A g^(−1)in GEG structures;this suggests that for a given specific surface area the redox-active and hydrophilic oxygen content can boost the capacitance to 250–300%higher compared to typical mesoporous carbon materials.GEGs with identical oxygen functionality show a surface area governed capacitance.This allows to establish direct structure-performance relationships between 1)redox-active oxygen functional concentration and capacitance and 2)surface area and capacitance.

Solubility study of hydrogen in direct coal liquefaction solvent based on quantitative structure–property relationships model

Direct coal liquefaction(DCL)is an important and effective method of converting coal into high-valueadded chemicals and fuel oil.In DCL,heating the direct coal liquefaction solvent(DCLS)from low to high temperature and pre-hydrogenation of the DCLS are critical steps.Therefore,studying the dissolution of hydrogen in DCLS under liquefaction conditions gains importance.However,it is difficult to precisely determine hydrogen solubility only by experiments,especially under the actual DCL conditions.To address this issue,we developed a prediction model of hydrogen solubility in a single solvent based on the machine-learning quantitative structure–property relationship(ML-QSPR)methods.The results showed that the squared correlation coefficient R^(2)=0.92 and root mean square error RMSE=0.095,indicating the model’s good statistical performance.The external validation of the model also reveals excellent accuracy and predictive ability.Molecular polarization(a)is the main factor affecting the dissolution of hydrogen in DCLS.The hydrogen solubility in acyclic alkanes increases with increasing carbon number.Whereas in polycyclic aromatics,it decreases with increasing ring number,and in hydrogenated aromatics,it increases with hydrogenation degree.This work provides a new reference for the selection and proportioning of DCLS,i.e.,a solvent with higher hydrogen solubility can be added to provide active hydrogen for the reaction and thus reduce the hydrogen pressure.Besides,it brings important insight into the theoretical significance and practical value of the DCL.

Bidirectional relationship between diabetes mellitus and depression:Mechanisms and epidemiology

Diabetes mellitus and depression exhibit a complex bidirectional relationship that profoundly impacts patient health and quality of life.This review explores the physiological mechanisms,including inflammation,oxidative stress,and neu-roendocrine dysregulation,that link these conditions.Psychosocial factors such as social support and lifestyle choices also contribute significantly.Epidemiological insights reveal a higher prevalence of depression among diabetics and an in-creased risk of diabetes in depressed individuals,influenced by demographic variables.Integrated management strategies combining mental health asse-ssments and personalized treatments are essential.Future research should focus on longitudinal and multi-omics studies to deepen understanding and improve therapeutic outcomes.

Elucidating the structure-activity relationship of Cu-Ag bimetallic catalysts for electrochemical CO_(2) reduction

Developing bimetallic catalysts is an effective strategy for enhancing the activity and selectivity of electrochemical CO_(2) reduction reactions,where understanding the structure-activity relationship is essential for catalyst design.Herein,we prepared two Cu-Ag bimetallic catalysts with Ag nanoparticles attached to the top or the bottom of Cu nanowires.When tested in a flow cell,the Cu-Ag catalyst with Ag nanoparticles on the bottom achieved a faradaic efficiency of 54%for ethylene production,much higher than the catalyst with Ag nanoparticles on the top.The catalysts were further studied in the H-cell and zero-gap MEA cell.It was found that placing the two metals in the intensified reaction zone is crucial to triggering the tandem reaction of bimetallic catalysts.Our work elucidates the structure-activity relationship of bimetallic catalysts for CO_(2) reduction and demonstrates the importance of considering both catalyst structures and cell characteristics to achieve high activity and selectivity.