Distributional Characteristics Research Articles

The proposal and calculation method of the annular domain weight function for the electromagnetic flowmeter under annular conductivity distribution

Researching on the characteristic of weight function distribution under non-uniform conductivity distribution is of significant importance for expanding the engineering applications of electromagnetic flowmeter. In this paper, the characteristic of weight function distribution is firstly explored for annular conductivity distribution where the center and outer ring are both conductive. The research results indicate an important finding that the average value of the weight function within any small annular domain of the center or outer ring remains constant as the radial position changes. Therefore, the concept of ‘annular domain weight function’ is then innovatively proposed. Furthermore, the relationship is studied between the ratio of the annular domain weight function of the center and outer ring and the annular feature parameters. Ultimately, the correlations are obtained for calculating the annular domain weight functions of the center and outer ring.

Trends in physical fitness among Lithuanian adolescents aged 11–17 years between 1992 and 2022

BackgroundPhysical fitness is an excellent marker of general health and performance. We aimed to calculate trends in physical fitness among Lithuanian adolescents between 1992 and 2022.MethodsUsing a repeated cross-sectional design,...

Research focus and emerging trends of cancer-related fatigue in nursing arena: A bibliometric analysis from 2012 to 2021.

To explore distributed characteristics and identify research focus and emerging trends related to cancer-related fatigue (CRF) in the nursing field. Data were collected from the Web of Science Core Collection database between January 2012 and December 2021 using an advanced search strategy. Data were extracted and analyzed using CiteSpace and Microsoft Excel. A total of 967 articles were included in this study. The number of published nursing studies on CRF has increased with slight fluctuations. Keyword co-occurrence analysis and timeline view indicated that CRF is closely related to quality of life, and there is a correlation between CRF and other symptoms. Moreover, increasing attention has been paid to CRF nursing interventions. The assessment tools and their different language versions, risk factors and reviews of CRF were the research frontiers in recent years with citation bursts. In the field of nursing, the focus of CRF research is still on risk factors, adverse outcomes and nursing management. Assessment tools will continue to be developed and additional risk factors will be studied in the future.

Poverty induced inequality in nutrition among children born during 2010-2021 in India.

Almost two-fifth of the children in India is stunted and among various factors, poverty differential in child undernutrition is the largest. Using the latest population-based survey of National Family Health Survey, 2015-16 and 2019-21 this paper examined the poverty induced inequality in child stunting across the sub-populations of India. A sample of 213,136 children aged between 0-5 years from NFHS fourth round and 98,222 children in the same age group from the NFHS fifth round constitute the study sample. The wealth index is used as the proxy of household's economic wellbeing and height-for-age (HAZ) z-score of a child is used to identify the stunting status of the child. Box plots are drawn to understand the distributional characteristics of the HAZ score for both the study sample. We calculate the Erreygers corrected concentration index and decomposed the concentration indices using Gonzalo-Almorox and Urbanos-Garrido method. During 2015-16, more than half of the children from the poorest wealth quintile were stunted (52%), compared to 22% among the children from richest wealth quintile. In 2015-16, stunting was as high as 65% among the children of mothers with low stature (height less than 145 cm) and from the poorest wealth quintile whereas, the prevalence was observed 56% from the same sub-population during 2019-21. Among various factors, the concentration index of stunting was observed highest among the children of 36-47 months (-0.28) followed by children of age 48-59 months (-0.27) and among the fully immunized children (-0.25). Similar to NFHS-4, NFHS-5 also shows a predominantly higher socio-economic inequality among 24+ months children and among the fully immunised children. Factors like child age, birth order and sanitation showed positive elasticity. Decomposition analysis of NFHS-4 data shows that due to uneven distribution of wealth, mother's education as a determinant of child stunting solely explained 33% of the overall inequality followed by improved access to sanitation (24%), mother's height (8%) and place of residence (5%). Similar to NFHS-4, NFHS-5 data also shows that mother's education, sanitation, mother's height and place of residence predominantly contributes to the overall wealth inequality in child stunting. In India, poverty differential in child undernutrition is acute among the different sub-population of children. And the concentration of stunted children is higher among the different sub-population with higher wealth poverty. Mother's education, improved sanitation and mother's height explained larger variation in the overall inequalities in child nutrition across India.

Semantic and distributional patterns of Spanish negation with nouns and adjectives: A Lexical-Realizational Functional Grammar approach

This study examines the semantic and distributional characteristics of the Spanish negation no when it occurs before nouns and adjectives, specifically, whether these instances diverge from sentential negation, but also from negation via prefixes such as des- ‘dis-’ or in- ‘in-, un-’. Using data from the Spanish Web 2011 corpus, it is shown that the use of no before adjectives aligns with other forms of constituent negation, often resulting in a contradictory interpretation, that is similar to that of sentential negation. However, the interpretation of no preceding nouns exhibits a broader range of interpretations, depending on whether the noun refers to an eventuality, quality, or entity. In such instances, no shows parallels to negative prefixes, frequently indicating privation rather than contradiction. Consequently, no can be analyzed as a building block of phrases, expressing syntactic negation, behaving similarly to other adverbs, as well as a building block of words, expressing lexical negation, resembling Spanish prefix-like elements like cuasi ‘almost’ or ex ‘ex-’. The analysis is couched within the framework of Lexical-Realizational Functional Grammar (LRFG), integrating aspects of Lexical Functional Grammar and Distributed Morphology. This approach does not treat morphology and syntax as separate modules, thus allowing us to account for the variable distribution and interpretation of no by means of a single representation in vocabulary structure, drawing on constituent structure representations which are needed on independent grounds for adverbs and for prefix-like elements.

An Indicator Based on Spatial Coordinate Information for Assessing the Capability for Dynamic Machining Performance of Five-Axis Flank Milling.

As a spatial coordinate sensor, the touch-trigger on-machine probe is a key equipment in manufacturing that ensures machining quality, and it has played an important role in five-axis flank milling. However, in flank milling, the utilization of the deviation as a conventional indicator for quality assessment of the machining performance is incomprehensive without considering the characteristics of the machining method. In this paper, the error mutual moment is introduced as an indicator to assess the capability for dynamic machining performance of the machine tool in flank milling based on the spatial coordinate information of the touch-trigger on-machine probe considering the characteristic of the error distribution of the flank milling. Experiments are carried out to validate the advantages of the error mutual moment to assess the capability for dynamic machining performance compared with the deviation. Results show that the error mutual moment shows more significant discrepancies than the deviation in assessing the capability for dynamic machining performance of flank milling. The error mutual moment has the potential to be applied as a quality assessment sensor.

From nature to urbanity: exploring phyllosphere microbiome and functional gene responses to the Anthropocene.

The Anthropocene exerts various pressures and influences on the stability and function of the Earth's ecosystems. However, our understanding of how the microbiome responds in form and function to these disturbances is still limited, particularly when considering the phyllosphere, which represents one of the largest microbial reservoirs in the terrestrial ecosystem. In this study, we comprehensively characterized tree phyllosphere bacteria and associated nutrient-cycling genes in natural, rural, suburban, and urban habitats in China. Results revealed that phyllosphere bacterial community diversity, richness, stability, and composition heterogeneity were greatest at the most disturbed sites. Stochastic processes primarily governed the assembly of phyllosphere bacterial communities, although the role of deterministic processes (environmental selection) in shaping these communities gradually increased as we moved from rural to urban sites. Our findings also suggest that human disturbance is associated with the reduced influence of drift as increasingly layered environmental filters deterministically constrain phyllosphere bacterial communities. The intensification of human activity was mirrored in changes in functional gene expression within the phyllosphere microbiome, resulting in enhanced gene abundance, diversity, and compositional variation in highly human-driven disturbed environments. Furthermore, we found that while the relative proportion of core microbial taxa decreased in disturbed habitats, a core set of microbial taxa shaped the distributional characteristics of both microbiomes and functional genes at all levels of disturbance. In sum, this study offers valuable insights into how anthropogenic disturbance may influence phyllosphere microbial dynamics and improves our understanding of the intricate relationship between environmental stressors, microbial communities, and plant function within the Anthropocene.

Responsive integration performed by laser-induced Er3+ structural doping and graphene nanoplatelets

Laser-induced preparation method has the advantages of high efficiency, high yield, no ionic diffusion restriction and competitive side reaction, which can prepare diversified composite materials based on small-scale and distributed characteristics. Besides, integrating multiple performance and conducting inductive feedback are helpful for the reliability and calibration of laser-induced materials in the precision field. Herein, responsive integration is designed based on graphene nanoplatelets/ZnSe:Er3+ composite with optical, electrical, thermal and visual properties for real-time feedback. Er3+ ions doped ZnSe is obtained by fast laser-induced method, combined with two-dimensional graphene nanoplatelets and assembled into temperature-sensitive polyimide and cellulose paper, realizing the characteristics of photoelectric conversion and photothermal conversion. Besides, red fluorescence guiding perceptual behavior can also be produced under the radiation of NIR laser. Based on the proposed composite, bionic flower is constructed, and exhibits good motion features in blooming. Meanwhile, large curvature bending, high thermal sensitivity and strong fluorescence emission are also revealed. Such performance combination design provides a convenient approach for multi signals cross feedback in soft actuator, which strengthens the monitoring and guidance of motion perceptions, and can be potentially applied in diversified fields.

Validity, test-retest reliability, and responsiveness of the Indonesian version of FACIT-COST measure for subjective financial toxicity.

Financial toxicity describes the impairment of financial wellbeing in patients due to the burden of cancer diagnosis and care. The COST: A Functional Assessment of Chronic Illness Therapy Measure of Financial Toxicity (FACIT-COST) is the most widely used cancer-specific measure of subjective financial toxicity, having been validated in multiple languages, but not in Indonesian. This study aimed to validate the Indonesian version of FACIT-COST in a breast cancer sample. A single-center prospective cohort study was performed in Indonesia. Female breast cancer patients aged ≥ 18 undergoing treatment at baseline were invited to participate and followed for up to six months. The survey included the official Indonesian version of FACIT-COST (v2) which was administered to the patients by interviewers. Clinical information (e.g., metastasis status, disease duration) was provided based on medical records. The following measurement properties of FACIT-COST were tested: distributional characteristics, structural validity (principal component [PCA] and confirmatory factor analyses [CFA]), internal consistency reliability (Cronbach's alpha and McDonald's omega), known-groups validity (Mann-Whitney U or Kruskal-Wallis H test), test-retest reliability, and responsiveness to change. Overall, 300 female patients participated at baseline. No patients reported the best or worst possible FACIT-COST total scores. The PCA proposed a two-factor model structure for the instrument, which was confirmed by the CFA (RMSEA = 0.042, SRMR = 0.049, CFI = 0.99, TLI = 0.99). The internal consistency reliability of the two factors was considered adequate (Cronbach's alpha = 0.774-0.882, McDonald's omega = 0.786-0.888). The FACIT-COST total score significantly discriminated across the following known-groups: age, education, residential setting, income, employment, metastasis status, number of symptoms, and financial coping strategies. The FACIT-COST demonstrated excellent test-retest reliability (intraclass correlation coefficient = 0.96) and satisfactory responsiveness to change (standardized response mean and effect size ranges=|0.39| to |0.92|). This is the first study to validate the FACIT-COST in patients with breast cancer and to present the measurement properties of the Indonesian version of FACIT-COST. The Indonesian FACIT-COST demonstrates acceptable psychometric performance and shows potential as a valid measure of subjective financial toxicity. The instrument may serve as a valuable tool for informing health policies that focus on providing resource support to improve cancer care in Indonesia.

The distributional characteristics of Interreg Transnational Programmes and their role in promoting regional cohesion

Interreg is an instrument of Cohesion Policy promoting cooperation among different organizations of Europe to tackle common challenges. Project funding within Interreg could become competitive, given the strong interest from numerous institutions in participating. This, in turn, may lead to disparities in the number of projects implemented across European regions. If participation is driven by factors such as the economic development level of regions, then the fundamental aim of Cohesion Policy—to reduce the gaps between developed and lagging regions—may not be well served by Interreg, as existing gaps may be exacerbated. Given this issue, the paper focuses on the 12 Interreg transnational programmes, which bring together regions from many different countries. The paper examines the distributional characteristics of these programmes using conventional statistical and network measures with data from the 2014–2020 programming period. It then develops a novel indicator of regional participation levels and constructs and empirically tests a framework for measuring the effect of various socioeconomic, geographical, and demographic factors on the participation levels of EU regions. The analysis reveals differences in the allocation patterns of projects among the programmes and shows that different types of networks are formed. Additionally, the instrument appears to benefit smaller and wealthier regions, which results in counteracting demographic inequalities but simultaneously augmenting economic ones. To address this challenge, the paper provides recommendations for management authorities to make the formation of partnerships more equitable.

Spatiotemporal functional permutation tests for comparing observed climate behavior to climate model projections

Abstract. Comparisons of observed and modeled climate behavior often focus on central tendencies, which overlook other important distributional characteristics related to quantiles and variability. We propose two permutation procedures, standard and stratified, for assessing the accuracy of climate models. Both procedures eliminate the need to model cross-correlations in the data, encouraging their application in a variety of contexts. By making only slightly stronger assumptions, the stratified procedure dramatically strengthens the ability to detect a difference in the distribution of observed and climate model data. The proposed procedures allow researchers to identify potential model deficiencies over space and time for a variety of distributional characteristics, providing a more comprehensive assessment of climate model accuracy, which will hopefully lead to further model refinements. The proposed statistical methodology is applied to temperature data generated by the state-of-the-art North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX).

Development and optimization of an Artificial Neural Network (ANN) model for predicting the cadmium fixation efficiency of biochar in soil

This study addresses the issue of soil cadmium pollution and the common problem of data missing during the training of artificial neural network models. A substantial amount of characteristic data regarding the immobilization of cadmium in soil through biochar was collected from the literature. Subsequently, data was organized and analyzed using correlation matrix analysis and feature importance analysis. The results revealed that the feature importance of biochar (52%) was relatively significant. A novel approach is introduced, involving a non-deterministic optimization technique based on linear interpolation to supplement the missing data within the dataset. The completed dataset effectively preserves the distributional characteristics of the original data, thereby enhancing the training performance of the neural network model. Through three phases, namely data incompleteness, data supplementation, and genetic algorithm optimization, the neural network model was progressively refined. The outcome of this iterative process is a high-performance artificial neural network model capable of predicting the efficiency of biochar in immobilizing cadmium in soil. The significance of these findings lies in their potential to advance the application of machine learning in environmental science, particularly in addressing complex pollution scenarios.

ICT and energy rebound effect: Empirical analysis based on data from Chinese cities

Information and communication technology (ICT) is predicted to emerge as a new driver of economic growth in the future and has been identified as a significant strategic emerging industry. It is of great theoretical and practical significance to include ICT in the energy rebound measurement framework. Based on Chinese city-level data from 2006 to 2019, this paper incorporates ICT into an improved stochastic frontier (SFA) model of energy consumption to measure the energy rebound effect (ERE) in 252 prefecture-level cities, and further investigates the formation mechanism of ICT affecting the ERE. The results show that when ICT is included in the energy rebound measurement framework, the average value of ERE in each region of China ranges from 0.4627 to 0.6458, with an overall average value of 0.5532, indicating that China's actual reduction in energy consumption is only about 40% of that expected. In terms of distributional characteristics, the mean value of ERE increases from coastal to inland, with the center of gravity always deviating from mainland China's geometric center (103°50′E, 36°N), the degree of spatial imbalance in the east-west direction is much greater than in the north-south direction. It is worth noting that ICT has a significant dampening effect on ERE, and the conclusion still holds after a series of robustness tests. In addition, the mechanisms by which ICT affects energy rebound include breaking through geographical and administrative barriers and reducing the impact of market segmentation on factor mobility.

Tense and aspect in the interlanguage of Slavic speakers learning Romance languages

ABSTRACT The study addresses the research gap of how being a speaker of a Slavic language influences the ability to convey tempo-aspectual meanings in Romance languages by examining personal and impersonal narratives delivered in written and spoken mode by learners of L3 Spanish and L3 Italian with L1 Slovak and L2 English. Narratives are analysed following the methods of interlanguage analysis proposed by Ellis and Barkhuizen [(2005). Analysing learner language. Oxford University Press] and Salaberry and Comajoan [(2013). Research design and methodology in studies on L2 tense and aspect. De Gruyter Mouton], such as coding for grounding, frequency analysis of tense forms and lexical aspectual classes, etc. Following the ideas presented by Bayley (2013, Data analysis: Quantitative approaches. In M. R. Salaberry & L. Comajoan (Eds.), Research design andmethodology in studies on L2 tense and aspect (pp. 357–390). De Gruyter Mouton), binomial logistic regression models were built which showed that (a) the combination of discourse grounding and lexical aspect is of predictive power regarding the appropriateness of participants’ choices of morphological marking; (b) the distributional characteristics of morphological marking on telic predicates differs from activities and statives. One of the main differences compared to the results of previous studies, conducted on speakers of Germanic languages, is that the data did not provide enough evidence for morphological marking being used to convey primarily temporal distinctions (see Salaberry, 1999, The development of past tense verbal morphology in classroom L2 Spanish. Applied Linguistics, 20(2), 151–178. https://doi.org/10.1093/applin/20.2.151; Wiberg, E. (1996). Reference to past events in bilingual Italian-Swedish children of school age. Linguistics, 34(5), 1087–1114. https://doi.org/10.1515/ling.1996.34.5.1087]) and presented the marking of telic predicates in foreground with perfective morphology as consistent, disregarding the level of participants’ performance.

Statistical Identification of Independent Shocks with Kernel-based Maximum Likelihood Estimation and an Application to the Global Crude Oil Market

Independent component analysis has emerged as a promising approach for revealing structural relationships in multivariate dynamic systems, particularly in scenarios with limited knowledge of causal patterns. This article introduces a robust kernel-based maximum likelihood (KML) estimation method that accommodates the distributional characteristics of the structural sources of data variation. Our Monte Carlo study demonstrates the superior performance of the KML estimator compared to existing approaches for independence-based identification. Moreover, the proposed method enables partial identification and dimension reduction even in the presence of dependent shocks. We illustrate the benefits of our approach by applying it to the global oil market model of Kilian, highlighting its ability to capture unmodeled higher-order dependence between oil supply and speculative oil demand shocks.

Prevalence Characteristics of Osteoporosis Fractures in the Elderly in Two Regions of China and Analysis of the Lag Effect of Air Pollutants on them.

Air pollution is increasing and threatening human health. The objective of this study is to investigate the population distribution characteristics of elderly osteoporosis fractures in Hebei Province and Xinjiang Uygur Autonomous Region and to analyze the effects of air pollutants on the number of elderly osteoporosis fracture inpatients in the two regions. A retrospective collection of elderly osteoporosis fracture cases was conducted in selected hospitals in Hebei Province and Xinjiang Uygur Autonomous Region from January 1, 2018 to December 31, 2022. The chi-square test was used to compare the distributional characteristics of the population in the two regions. Additionally, we used a distributed lag nonlinear model (DLNM) in order to assess the effect of air pollutants on the number of daily hospital admissions of elderly osteoporosis fracture patients in different regions. A total of 19,203 elderly osteoporosis fracture patients were included in the study. The average age of these patients was 76.66 ± 7.55 years, and the majority of them were female (13,514 instances, 70.37%). The disparities in age distribution (χ2 = 133.9 p < 0.001), fracture site (χ2 = 62.0 p < 0.001), and hospitalization cost (Z = -15.635 p < 0.001) between the two regions were statistically significant. The lag effect curves of PM2.5, PM10, and NO2 on the number of elderly osteoporosis fracture hospitalizations in Xinjiang Uygur Autonomous Region exhibited a similar pattern resembling a "W"-shaped curve. All three pollutants reached their highest values after a lag time of 14 days (PM2.5: RR = 1.053, 95% CI: 1.031, 1.074; PM10: RR = 1.031, 95% CI: 1.018, 1.043; NO2: RR = 1.125, 95% CI: 1.070, 1.182). In Hebei Province, the largest impacts of PM2.5 and PM10 were observed after a lag of 14 days (PM2.5: RR = 1.022, 95% CI: 1.013, 1.028; PM10: RR = 1.013, 95% CI: 1.008, 1.018). Similarly, the maximum effect of NO2 was observed after a lag of 11 days (RR = 1.020, 95% CI: 1.010, 1.028). There were differences in the epidemiological characteristics of hospitalized patients with osteoporosis fractures between the two regions, PM2.5, PM10, and NO2 increased the number of hospitalizations for osteoporosis fractures. Exposure to air pollutants such as PM2.5 increases the risk of osteoporosis fractures in the elderly population.

Shifting alpine plant distributions with global change: Testing the environmental matching hypothesis

ABSTRACT Species facing novel temperature, precipitation, and nitrogen (N) deposition regimes must move or adapt to persist. For long-lived plants, a primary form of climate acclimation is through shifting geographic range limits or establishing in favorable microclimates. One commonly assumed but rarely tested hypothesis is that these shifts can be predicted by environmental matching: that the environmental characteristics that define a current distribution should predict how a population will shift with environmental changes. To test this hypothesis, we transplanted four alpine and two subalpine plant species into environments with experimentally increased temperature, snow, and N. We predicted that species would perform best when environmental change matched their geographic distributional characteristics: increased temperature, snow, and N (two subalpine species), increased temperature (two dry meadow specialists), and increased snow (two snowbed specialists). Our results provided limited support for the environmental matching hypothesis. Snowbed specialists did not benefit from increased snow, dry meadow specialists' performance did not consistently differ among the treatments, and subalpine plants' survival was not affected by treatments while their growth response was variable among species. Our results suggest that global change effects will vary among species and distributional shifts are not easily predicted by species environmental preference.

The ambiguity-resolved detector: a detector for the mixed-integer GNSS model

In this contribution, we introduce the ambiguity-resolved (AR) detector and study its distributional characteristics. The AR-detector is a new detector that lies in between the commonly used ambiguity-float (AF) and ambiguity-known (AK) detectors. As the ambiguity vector can seldomly be known completely, usage of the AK-detector is questionable as reliance on its distributional properties will then generally be incorrect. The AR-detector resolves the shortcomings of the AK-detector by treating the ambiguities as unknown integers. We show how the detector improves upon the AF-detector, and we demonstrate that the, for ambiguity-resolved parameter estimation, commonly required extreme success rates can be relaxed for detection, thus showing that improved model validation is also possible with smaller success rates. As such, the AR-detector is designed to work for mixed-integer GNSS models.

Spatial distributed characteristics of carbon dioxide emissions based on fossil energy consumption and their driving factors at provincial scale in China

The spatial distribution characteristics of carbon dioxide (CO2) emissions of coal, crude oil and natural gas in China during 2019 were revealed through Exploratory Spatial Data Analysis (ESDA) method. Then spatial differences of the impacts of socio-economic factors on CO2 emissions were discussed by using geographical weighted regression (GWR) model. Furthermore, the relationship between urbanization and CO2 emissions was explored by combing the center of gravity model with coupling coordination development degree model. The findings demonstrate that the high spatial agglomeration effect and risk areas of coal-based CO2 emissions are concentrated in the northern region (the maximum emissions up to 1005.09 Mt), and the same type of natural gas-based CO2 emissions are distributed in the central region, while the low spatial agglomeration effect and risk areas of crude oil-based CO2 emissions are mainly in the western region. Under the positive impact from energy intensity (average influence coefficient is 1.59), CO2 emissions show a good coupling trend with economic urbanization, but present a spatial differentiation of unbalanced western and coordinated eastern regions with population urbanization. This study enriches the content of energy-based carbon emissions from geographic and management disciplines, also gives scientific foundation for differential formulation of carbon emission reduction policies.

Distribution of Carbon-Sequestering Microbes in Different Habitats and the Interaction with Habitat Factors in a Natural Karst Cave

The distributional characteristics of microorganisms in karst cave ecosystems have been widely studied. However, in such a dark, humid, and oligotrophic habitat, studies on the differences in carbon-sequestering bacteria in multiple habitats are limited. Therefore, to learn the distribution characteristics of carbon-sequestering colonies in cave habitats and their correlation with habitat factors (e.g., pH, Ca2+, Mg2+, etc.), samples from five cave habitats (weathered rock walls, underground river water, drips, sediments, and air) were collected from the twilight and dark zones of Shiziyan Cave (CO2 concentration 5385 ppm). The results of high-throughput sequencing and statistical analyses showed that there were significant differences in the distribution of communities in different habitats, with higher abundance in sediments habitat and underground river water habitat, and the dominant phyla of Pseudomonadota (30.53%) and Cyanobacteria (75.11%) in these two habitats. The microbial diversity of the carbon-sequestering microbial community was higher in sediments than in underground river water. The pH, and Ca2+, SO42−, and NO3− concentrations can alter the diversity of carbon-sequestering microbes, thereby affecting carbon cycling in caves. Carbon metabolism analyses suggest that microbes in the habitat can cooperate and coexist by participating in different carbon metabolic pathways. These results expanded our understanding of carbon-sequestering microbial communities in cave systems and their responses to the environment.