Hierarchical Cluster Analysis Method Research Articles

Musculoskeletal Diseases as the Most Prevalent Component of Multimorbidity: A Population-Based Study.

Background/Objectives: Due to their high frequency, common risk factors, and similar pathogenic mechanisms, musculoskeletal disorders (MSDs) are more likely to occur with other chronic illnesses, making them a "component disorder" of multimorbidity. Our objective was to assess the prevalence of multimorbidity and to identify the most common clusters of diagnosis within multimorbidity states, with the primary hypothesis that the most common clusters of multimorbidity are MSDs. Methods: The current study employed data from a population-based 2019 European Health Interview Survey (EHIS). Multimorbidity was defined as a ≥2 diagnosis from the list of 17 chronic non-communicable diseases, and to define clusters, the statistical method of hierarchical cluster analysis (HCA) was performed. Results: Out of 13,178 respondents, multimorbidity was present among 4398 (33.4%). The HCA method yielded six multimorbidity clusters representing the most common diagnoses. The primary multimorbidity cluster, which was prevalent among both genders, age groups, incomes per capita, and statistical regions, consisted of three diagnoses: (1) lower spine deformity or other chronic back problem (back pain), (2) cervical deformity or other chronic problem with the cervical spine, and (3) osteoarthritis. Conclusions: Given the influence of musculoskeletal disorders on multimorbidity, it is imperative to implement appropriate measures to assist patients in relieving the physical discomfort and pain they endure. Public health information, programs, and campaigns should be utilized to promote a healthy lifestyle. Policymakers should prioritize the prevention of MSDs by encouraging increased physical activity and a healthy diet, as well as focusing on improving functional abilities.

Ecosystem services provided by urban woody plants in the context of spatial relations: Çankırı case area

Ecosystem services (ES), which are defined as the benefits provided by humans from ecosystems, provide recreation opportunities for urban people with green areas in the cities, while supporting biodiversity on the other hand. This research seeks to answer the following 3 questions: (1) Can the contribution of plants used in urban parks to urban ES be measured? (2) Are the location and characteristics of the areas where plants are placed in urban parks a factor in providing ES? (3) Which ES stands out in the network of relationships established by the ES provided by plants in urban green spaces? Within the scope of these questions, ES provided by woody plants in Çankırı urban park, which is an essential green area for Çankırı/Türkiye, were examined. In the light of the examinations on-site, the presence of 49 woody plant taxa was determined. The contribution of plant taxa to the ecosystem has been assessed within the framework of 13 sub-parameters related to provisioning, supporting, regulating and cultural services. Hot spot analysis and hierarchical cluster analysis methods were used to determine the ES and spatial distribution of taxa within the park. Subsequently, a centrality analysis was carried out in the Graph Commons program using the network mapping method to determine the importance of ES provided by plants. As a result of the study, it was revealed that the woody plants used in Çankırı urban park contribute highly to the urban ecosystem in terms of pollination, erosion control, recreation and education, soil and air quality improvement and habitat provision. However, the spatial distribution of taxa was not balanced. Therefore, a balanced spatial distribution of woody plant taxa, which make a valuable contribution to ES, in urban green spaces is an issue that should be considered in urban ES planning.

초등교사의 수업실행 저해요인에 관한 연구

Objectives This study focused on the factors which inhibit the teaching practices as they were perceived by elementary school teachers. Methods Thirty-five elementary school teachers were interviewed, and research materials were analyzed using a concept map approach. From the interview, 44 key sentences were extracted as a final statement, and the concept mapping was completed using the Multidimensional Scaling and Hierarchical Cluster Analysis method. 970 elementary school teachers were asked to answered the 5-point Likert scale questionnaires to check which statement could affect the teaching practices. Results First, the elementary school teachers recognized the factors inhabiting the teaching practices in the “job performance-relationship formation” and “inside-outside the school” dimensions. Second, elementary school teachers recognized the inhabiting factors in 8 clusters; “formalism of educational administration,” “inefficiency of school work,” “lack of trust between teachers and parents,” “lack of efficiency in business processing,” “lack of administrators’ leadership,” “lack of teaching support,” “negative teaching culture,” and “lack of professionalism and teacher’s philosophy” appeared in that order. Conclusions This study will help to identify ways to improve the teaching expertise by identifying the inhibiting factors as perceived by elementary school teachers.

Headway regularity as an attribute for classifying bus drivers

Different indices have been proposed in the literature to characterize headway regularity. These metrics aggregate the headway variability for a service, but none can be directly associated with a specific driver. This paper seeks to understand drivers' influence on a service's regularity. To do so, we propose four regularity indices related to a driver's performance and use the Hierarchical Clustering Analysis method to generate a classification of drivers according to their contribution to the headway regularity during the operation of a service. We characterize each class based on the driver's attributes such as age, years of experience as a driver, and years in the bus company, and those attributes associated with the operation, such as number of services per day and period of the day. The results show consistency in the classification obtained, with nearly 90% of drivers remaining in the same regularity classes regardless of the index.

문학 글쓰기의 과제 수행에 대한 분석 연구

Objectives The purpose of this study is to examine what students at G and K universities recognize and make meaning of after appreciating literary works, and to show the performance results.
 Methods For this purpose, this study used students' writing assignments conducted at two universities as analysis data. As a method of statistically analyzing text data, KH-coder 3 (Folder), a corpus research method, was used to conduct K University assignments such as ‘extracted word correspondence analysis, extracted word multidimensional scaling method, hierarchical cluster analysis, network analysis, and self-organizing instruction method.’ was used to present statistical results intuitively, focusing on typical cases by type. As for the analysis method of G University's project, we presented the results of the task analysis through three methods: ‘correspondence analysis, network analysis, and hierarchical cluster analysis’, and presented some conclusions focusing on typical cases by type.
 Results First, through texts, students at K University remember their somewhat turbulent times and learn about where their foundation came from, how they lived in relationships with their family and friends. It showed that they had come. It had the effect of soothing the wounded heart of the present through the experience of writing down past memories and memories. Second, as a result of student responses at G University, there was a tendency to interpret the story as a story about an immature boy, Namu, experiencing loss, accepting the loss and growing, and also interpreting loss as the basis for growth. Additionally, students responded that they understood the two characters as complementary and aimed for a relationship of growth. Third, while watching the character's growth process, students projected their inner self and showed a journey to self-understanding. And, he said that he applied the characters' motifs of innocence, love, and memories to his own life and felt comfort. In addition, positive writing responses were shown regarding the importance of nature and life.
 Conclusions In this study, we applied literary writing teaching and learning activities that can promote self-growth and found the results to be meaningful in literary education.

Analyzing Spatial Groundwater Salinity Using Multivariate Analysis and Multiple Linear Regression Models

The increase in the amount of groundwater withdrawal will inevitably pose a threat of seawater intrusion. The purpose of this research was to identify the distribution of shallow groundwater salinity in North Jakarta, West Jakarta and Central Jakarta and to develop a regional model of shallow groundwater salinity distribution. The data used in this study was that of the groundwater quality monitoring, obtained from the Regional Environment Status Book (SLHD), published by The Environment office of Greater Jakarta released in 2022, involving a total of 121 sample points in North Jakarta, West Jakarta, and Central Jakarta. The primary data was taken at 6 (six) sampling locations for model validation purposes. The study began with data grouping, using the Hierarchical Cluster Analysis (HCA) method. The results of identifying the highest distribution of salinity are in cluster 3 (three). A model was subsequently developed, after removing the outliers, with multiple linear analysis methods using the variable the distance from the coastline (X1), well depth (X2) and hardness (X3), to determine the influence of EC, TDS and salinity distribution in shallow groundwater. The results obtained are as follows; EC Models: YEC3 = -1.879+ (1.19.X1) + (5.08.X3). TDS models: YTDS3 = -2.211.30 + (0.81.X1) + (101.41.X2) + (4.07.X3). Salinity models: Ysalinity3 = -0.07+ (6.75×10-5.X1) + (2.4×10-4.X3). Model verification results for R2EC3 = 0.70; R2TDS3 = 0.92; R2salinity3 = 0.88. Validation results produce 21.14% for EC, 8.21% for TDS, and 22.87% for Salinity. This needs further research by increasing the number of primary samples.

Multi-scenario flexibility assessment of power systems considering renewable energy output uncertainty

The widespread adoption of renewable energy sources presents a significant challenge to the flexibility of power system. To assess the flexibility of the power system in scenarios with uncertain renewable energy output, it is crucial to quantify it quantitatively. This evaluation plays a vital role in planning flexible regulatory resources and dispatching resources for both the energy source and load. This study introduces a novel flexibility assessment model tailored for power grids with high renewable energy penetration, specifically addressing uncertainty associated with wind and PV. By analyzing the impact of wind and PV uncertainty on system flexibility, the paper proposes an improved cohesive hierarchical cluster analysis method, incorporating reliability considerations based on the Davies-Bouldin classification reliability index. Additionally, the study develops models for flexibility resources and demands within high renewable energy power systems, along with quantitative assessment indicators across three key aspects. Through a structured flexibility assessment process accounting for wind and PV uncertainty, the effectiveness of the proposed approach is validated using real-world data from a renewable energy power grid in Shandong province. A set of typical renewable energy output scenarios with uncertainty is constructed using the improved hierarchical cluster analysis method. The study then analyses the impact of different wind and PV penetration rates and the proportion of energy storage units on system flexibility by the flexibility assessment model to validate the proposed method's effectiveness.

Gold nanoclusters-based fluorescence sensor array for herbicides qualitative and quantitative analysis

Herbicides have been extensively used around the world, which poses a potential hazard to humans and wildlife. Accurate detection of herbicides is crucial for the environment and human health. Herein, a simple and sensitive fluorescence sensor array was constructed for discrimination and identification of herbicides. Fluorescent gold nanoclusters modified with 11-mercaptoundecanoic acid or reduced glutathione were prepared, respectively. Metal ions quenched the fluorescence of nanoclusters through coordination and leading to the aggregation of gold nanoclusters. The addition of auxin herbicides (2,4-dichlorophenoxyacetic acid, 2-methyl-4-chlorophenoxyacetic acid, decamba, picloram, quinclorac) restored the fluorescence of nanoclusters with different degrees. The mechanism study showed auxin herbicides can bind with metal ions and re-disperse the gold nanoclusters from the aggregation state. The "on-off-on" fluorescent sensor array was constructed basic on above detection mechanism. Combined with principal component analysis (PCA) and hierarchical cluster analysis (HCA) methods, auxin herbicides are well separated on 2D/3D PCA score plots and HCA dendrogram in the range of 40–500 μm. In addition, the fluorescence sensor array performed successful in detecting real samples and blind samples. The developed sensor system shows a promising in practical detection of herbicides.

MORPHOSTRUCTURAL TRAITS IN INDONESIAN FEMALE GOAT BREEDS OF BOER, BOERKA, KACANG AND ETTAWA CROSS

Morphostructural characterization can be used to identify unique characteristics in different animal breeds and an essential tool for the identification and classification of these breeds. The objective of this study was to characterize four Indonesian goat breeds based on their morphostructural traits. A total of 315 female goats (does) at 2.5 - 3.5 years of age were used currently and consisted of 28 Boer, 118 Boerka, 141 Kacang and 28 Ettawa cross. Total eleven body measurements and ten body conformations were measured to describe the morphostructure of goats. Two statistical methods of canonical discriminant analysis (CDA) and hierarchical cluster analysis (HCA) were used to differentiate goat breeds. Body measurement and body index were able to discriminate goat breeds with canonical correlation (Function 1) of 0.81 and 0.77, respectively. According to HCA of morphostructural traits, Boerka and Kacang does are classified into similar cluster. Body measurement is better for discriminating goat breeds rather than body conformation.

Sustainable Development and Operational Mechanism Innovation of Educational Management Paths in Colleges and Universities in the Digital Era

Abstract With the continuous integration of digital technology in daily life, the management path of colleges and universities also carries out development and optimization. The triple helix theory of education management model innovation in colleges and universities is the basis of this paper, which builds a model for education management innovation led by schools. An evaluation index system for college education management quality was constructed, taking into account the quality effect demand of education management. On this basis, combining the hierarchical method and cluster analysis method to calculate and classify the weights of the indicators of educational management in colleges and universities, and evaluating the quality of educational management in colleges and universities through the fuzzy comprehensive evaluation method to complete the construction of the indicator system of quality of educational management in colleges and universities. After examining the performance of the evaluation model and the rationality of the indexes, it is applied to the educational management examples to explore the sustainable development path of the educational management path in colleges and universities. The results show that the overall index coefficient is 0.875 and greater than 0.6, and the comprehensive evaluation score of the actual management quality of the triple helix educational management is 4.6826 points out of 5, which verifies the validity and reasonableness of this paper based on the triple helix educational management innovation model. The sustainable development of educational management is positively impacted by its scientific guidance on the innovative direction of university educational management models.

Lanthanide MOF-based luminescent sensor arrays for the detection of castration-resistant prostate cancer curing drugs and biomarkers.

In recent years, castration-resistant prostate cancer (CRPC) has profoundly impacted the lives of many men, and early diagnosis of medication and illness is crucial. Therefore, a highly efficient detection method for CRPC biomarkers and curing drugs is required. However, the complex and diverse structures of CRPC drugs pose significant challenges for their detection and differentiation. Lanthanide metal-organic frameworks (Ln-MOFs) show great potential for sensing applications due to their intense and characteristic luminescence. In this work, a series of new bimetallic Ln-MOFs (EuxTb1-x-MOF) based luminescent sensor arrays have been developed to identify CRPC drugs, including in mixtures, via principal component analysis (PCA) and hierarchical cluster analysis (HCA) methods. These Ln-MOFs are built with a highly conjugated H2L linker (H2L = 5-(4-(triazole-1-yl)phenyl)isophthalic acid) and exhibit robust strong luminescence emissions (mainly located at 543 and 614 nm) and high energy transfer efficiencies. More specifically, Eu0.096Tb0.904-MOF (MOF 3) has demonstrated good sensing performances for CRPC curing drugs in real human serum samples. Furthermore, the curing drug hydroxyflutamide has been combined with MOF 3, to construct a robust composite sensing platform MOF 3@hydroxyflutamide for highly efficient detection of CRPC biomarkers such as the androgen receptor (AR) and prostate-specific antigen (PSA). Finally, luminescence lifetime measurements, zeta potential measurements, and density functional theory (DFT) calculations were performed to gain insights into the sensing mechanism.

Combination of chemometrics and mass spectrometric methods for the data mining of molecular structure information of coal and biomass

The combination of mass spectrometry (MS) data and chemometrics methods is conducive to obtaining more comprehensive molecular information and evaluating the transfer behavior of O and N atoms during the conversion of biomass and coal. In this work, 12 thermal dissolution (TD) extracts of coal/biomass samples and the catalytic hydrogenation products of TD extracts were analyzed by Orbitrap MS using spectral stitching and in-source collision-activated dissociation (ISCAD) methods. Spectral stitching improves the detection ability towards minor and trace species, enhancing the number of identified compounds by two times. Meanwhile, ISCAD provides more comprehensive molecular structure information, which can illustrate the transfer patterns of heteroatoms and deepen the understanding of the structural characteristics of aromatic rings during the conversion of biomass and coal. Two chemometrics methods, principal component analysis (PCA) and hierarchical cluster analysis (HCA), were introduced to dig out the detailed similarities and differences between O-containing and N-containing compounds in coal and biomass. HCA method not only recognized the category of O-containing and N-containing compounds in each sample, but also showed the removal behavior of O and N atoms in biomass and coal. Thus, the combination of MS methods and chemometrics method is expected to provide methodological support to elucidate the molecular structure and conversion pathways for complex coal and biomass.

보육교사의 그릿 군집유형에 따른 교사효능감과 심리적 소진의 차이

Objectives The purposes of this study is to identify the types of grit for child care teacher based on the two com-ponents of grit, perseverance of effort and consistency of interest, and to examine the differences in teacher effi-cacy and psychological burnout by identified grit type.
 Methods A survey was conducted on 638 child care teaches in Nationwide. Based on the collected data, cluster types were derived through hierarchical cluster analysis and K-means cluster analysis methods, and the analysis was performed by one-way ANOVA.
 Results The analysis of the data revealed that child care teacher's grit could be classified in to four types ‘low grit’, ‘perseverance of effort’, ‘consistency of interest’, and ‘high grit’ according to the degree of two components of grit. With this, there were significant differences of child care teacher's teacher efficacy and psychological burnout according to cluster types based on the grit.
 Conclusions Therefore, this research multi-dimensionally approached grit focused on these days, and, based on this, the child care teacher's grit is important for the development of teacher efficacy and psychological burnout, and that an social and policy approach that can enhance child care teacher's grit is needed for better teacher effi-cacy and psychological burnout.

Multivariate analysis of morphometric traits of Malaimadu cattle-autochthonous draft cattle of south India.

Malaimadu cattle is a less explored indigenous cattle germplasm reared in the Western Ghats area of Tamil Nadu, south India. This study aimed to analyze the morphological structure of the Malaimadu cattle using a multivariate approach that explains and best represents body conformation. Sixteen body measurements were obtained from 156 adult female cattle from their native breeding tract. The Nearest Neighbor Method of Hierarchical Cluster analysis was used to group the morphometric traits into clusters. Pearson's coefficients of correlation (r) were estimated to determine the phenotypic correlations between different body measurements. Traits were analyzed using varimax rotated principal component analysis (PCA) with Kaiser normalization. Cluster analysis categorizes morphometric traits into two distinct clusters with the first cluster formed by traits related to horns and face, while the second cluster denotes general body conformation. Out of 120 phenotypic correlations, 55 were significant of which 51 were positive correlations. The estimated correlation coefficient ranges between - 0.50 (body length and face width) to 0.85 (chest girth and body weight). PCA extracted six components representing 70.19% of the total variance, while the first principal component comprises chest girth (CG), body weight (BW), height at wither (HW), and Paunch girth (PG) alone accounts for 23.70% thereby describing the general size and shape of the animal. The multivariate approach has proven to be effective in differentiating Malaimadu cattle from other indigenous breeds of south India with clear morphometric differences that help in identifying the pure phenotype for future propagation and also for devising breeding strategies.

Substantiating the normative values of company's liquidity ratios: Evidence from the engineering, transport and logistics industries

Subject. The article addresses the normative values of financial indicators of the liquidity group that are formed as a result of financial and economic relations of the enterprise. Objectives. The aim is to calculate the normative values of financial indicators of the liquidity group for engineering, transport and logistics companies, using the hierarchical cluster analysis tool. Methods. The study draws on general scientific research methods. Results. We offered an algorithm to calculate the normative values of financial indicators, using the hierarchical cluster analysis; calculated the normative values of the quick liquidity ratio, current liquidity ratio, and absolute liquidity ratio for the branches of mechanical engineering, transport and logistics. Conclusions. The calculated financial indicators are applicable for the analysis of financial and economic activities of mechanical engineering, transport and logistics enterprises. The proposed algorithm based on the method of hierarchical cluster analysis can be used to calculate other financial indicators of enterprises operating in various industries.

The summer standardized precipitation evapotranspiration index (SPEI) dataset for six European regions over the past millennium reconstructed by tree-ring chronologies

ABSTRACT Accurate reconstructed series are crucial for studying the differences in regional hydroclimatic variations in Europe over the past millennium. Using hierarchical clustering analysis and stepwise regression methods, we reconstructed yearly time series of the summer standardized precipitation evapotranspiration index (SPEI) for six European regions over the past millennium. Our analysis also revealed prominent regional hydroclimatic differences in multidecadal signals over the past 500 years. For instance, in the 1500s–1570s (from the beginning of the 1500s to the end of the 1570s), drying trends were observed in northern and southeastern Europe, whereas southwestern Europe experienced a wetting trend. Moreover, drying trends were observed in northern and central Europe in the 1640s–1670s. Additionally, wetting trends were observed in western and central Europe during the 1830s–1850s, with drying trends in northern and southeastern Europe. Notably, the hydroclimatic variations in most European regions showed drying trends in the 1920s–1950s, especially in southern Europe. By utilizing large amounts of tree-ring samples and directly comparing regional hydroclimatic variations, our reconstructions provide a consistent and comprehensive dataset for further analysis. The reconstructed dataset is available at https://doi.org/10.57760/sciencedb.07215.

Network formation and differentiation of chitosan–acrylic acid hydrogels using X-ray absorption spectroscopy and multivariate analysis of Fourier transform infrared spectra

Chitosan–acrylic acid (Cs–AA) hydrogels were prepared by blending different Cs concentrations and AA:Cs ratios. The Cs–AA hydrogel samples were analyzed using synchrotron radiation-induced near edge X-ray absorption fine structure (NEXAFS) and Fourier transform infrared (FTIR) spectroscopies. The characteristics of Cs were observed through the C, O, and N K edges in NEXAFS. Significant shifts in the Cs characteristic features were induced by the addition of AA. The NEXAFS findings confirmed the new covalent and ionic bridges to form the network of the Cs–AA hydrogel. Raw FTIR spectra were used to investigate the different functional groups of each of the macromolecules. The study attempted to discriminate the Cs–AA hydrogels prepared with different Cs wt% concentration and AA:Cs ratio using multivariate approaches. The preprocessed dataset was evaluated using principal component analysis (PCA) and hierarchical cluster analysis (HCA). The PCA and HCA methods showed the possibility of discriminating the Cs–AA hydrogel samples from the control samples and with each other. The approaches further confirmed that the CO groups found in the range of 1700–1800 cm−1 can be used as an identifier for Cs–AA hydrogel samples prepared using different solution parameters. The use of FTIR coupled with multivariate approaches provided a simple and reliable way to inspect the possible discrimination of Cs–AA hydrogels.

Second-order calibration-assisted LC-MS method for simultaneous determination of multiple active components and origin difference analysis of vinegar-processed cyperi rhizoma

In this work, a liquid chromatography-mass spectrometry (LC-MS) technique combined with alternating normalization weighted error algorithm (ANWE) method was proposed to realize the simultaneously fast quantification of 9 main active ingredients including isomers and origin difference analysis of vinegar-processed cyperi rhizoma (VCR). Overlapping peaks, similar mass spectra and fragment ions of isomers, and unknown matrix interference were all addressed by the proposed approach, which also yielded quantitatively and qualitatively acceptable results. Their average spiked recoveries range from 83.6% to 103.5%. It is worth mentioning that the proposed method can achieve accurate quantification of isomers α-cyperone and nocatone under simple chromatographic elution conditions. And the quantitative results of PARAFAC and ANWE algorithm were compared. Compared with the LC-MS/MS method, the quantitative results of ANWE-LC-MS method are not significantly different, and the required time is shorter. Meanwhile, the ANWE algorithm was used to resolve the 42 VCR's LC-MS fingerprints and determine the relative concentrations of components. Heatmap analysis reveals the difference in the content of the extracted variables in VCR samples, and the unsupervised hierarchical clustering analysis (HCA) method was used for their origins cluster. In addition, the partial least squares discriminant analysis (PLS-DA) method was adapted for the classification of Guang VCR and Non-Guang VCR accurately and five representative difference marker compounds were screened out with the variable importance in projection (VIP). In a word, this work is anticipated to serve as a reference for the development of quality standards for medications made from VCR or other Chinese herbs, as well as for the study of the origin discrimination.

어머니 행복감 군집유형에 따른 유아의 공감능력과 배려행동의 차이

Objectives This study aimed to examine the differences in empathy ability and caring behavior of children across the cluster type of mother's happiness. Methods A survey was conducted on 370 mothers with children aged 4 to 5 living in Seoul and Gyeonggi Province, from October to November 2021. Based on the collected data, cluster types were derived through hierarchical cluster analysis and K-means cluster analysis methods, and the analysis was performed by one-way ANOVA. The main research findings are as follows. Results First, four types of happiness were identified: ‘a group for higher happiness’, ‘a group for higher autonomy’, ‘a group for higher personal growth’, and ‘a group for lower happiness’. Second, the children of mothers from the ‘higher happiness group’ and ‘higher autonomy group’ showed higher empathy and caring behavior than those of mothers from the other groups. Lastly, children of mothers of the ‘higher personal growth’ group were not higher in empathy and caring behavior than those of other mother groups. Conclusions The study results imply that the mother's happiness as a caregiver is important for the development of children's empathy and caring behavior, and that an social and policy approach that can enhance mother's happiness is needed for better children’s empathy and caring behavior. This study is to understand the relationship between parent-child finteraction, child's self-regulation, and child's caring behavior in the early childhood.

Spatial-Temporal Characteristics and Influencing Factors of Lake Water and Groundwater Chemistry in Hulun Lake, Northeast China

Lakes in cold and arid regions are extremely vulnerable to global climate change, and the study of seasonal spatial and temporal fluctuations of lake-groundwater chemistry is of major significance for water resource management and environmental preservation. In this study, we combined hydrogeochemical, multivariate statistical, and spatial interpolation methods to assess spatial and temporal variations of lake and groundwater chemistry in Hulun Lake during the frozen and non-frozen periods. The results show that sodium (Na+) is the most abundant cation in the Hulun Lake area. Bicarbonate (HCO3−) and sulfate (SO42−) are the most predominant anions in the lake, river, and ground water during both seasons. The higher Na+ + K+ concentrations in the frozen season were related to longer circulation time and lower renewable rate. The water chemistry of the lake was of the HCO3-SO4-Cl-Na type and that of groundwater in the east and west regions was of the SO4-Cl-Na and HCO3-Na types, respectively. The chemical compositions of groundwater in the non-frozen season were mainly affected by evaporation and concentration, while rock weathering, evaporation, and human activities jointly controlled groundwater chemical component in the frozen period. Based on hierarchical cluster analysis (HCA) and principal component analysis (PCA) methods, Ca2+, NO3−, and SO42− were identified as the main controlling indicators of the chemical characteristics of groundwater and lake water. The increase of Ca2+ concentration in the center of the lake was related to groundwater discharge along the marginal tectonic fracture zone along the lake shores, which was the potential groundwater discharge area. The unconsolidated aquifer provides recharge channels for groundwater on the eastern side, which has a certain influence on the increase of nutrient concentration (NO3−) in the lake on the eastern shore. This research adds to our rough understanding of the lake-groundwater interaction in Hulun Lake, and provides a scientific foundation for the sustainable use of water resources, as well as the eco-logical integrity preservation in cold and arid regions.