Internal Relationships Research Articles

Integrative Taxonomy Reveals New Insights into the Species Validity of the Neocaridina davidi-N. denticulata-N. heteropoda Complex and Mitogenomic Phylogeny of Caridean Shrimps

The genus Neocaridina, originating from East Asia and representing a small-size landlocked shrimp group of the family Atyidae, is an important group of ornamental shrimps and plays significant ecological roles in their natural habitats. Owing to the considerable variability of the taxonomic characters it employed, Neocaridina is constantly under revision, and the validation of several species is currently questionable. In the present study, several Neocaridina shrimps were collected from the Baiyangdian drainage area. Through morphological examination, they exhibited delicately diagnostical differences in the dactyli of the third pereiopod and the endopod of the first and second pleopod and were classified into morph A, morph B and morph C. According to the literature description, morph A and morph C were identified as N. denticulata denticulata and N. denticulata sinensis, respectively. Among them, morph B presents an intermediate state between morph A and morph C. Subsequently, we determined the mitogenomes of morph A, morph B and morph C. Based on the morphological characteristics, genetic variation and phylogenetic tree, we contend that N. davidi, N. d. denticulata, N. d. sinensis and N. heteropoda should belong to the same species, and we propose retaining the name N. denticulata. The reconstructed mitogenomic phylogeny indicated that the monophyly of several genera within Atyidae has been challenged, suggesting that the established classification of Atyidae requires substantial taxonomic revision at all taxonomic levels. Furthermore, the tree’s topologies supported Atyidae at a deeper base within Caridea. More comprehensive taxon sampling is still needed to resolve the explicit internal relationships among Caridea.

The role of light rail systems in urban regionalisation processes and in defining the bioregional vision of the Pontine plain in Italy

ABSTRACT Urban regionalisation or new regionalism is a land transformation process that involves the emergence of new sprawl settlements in the European Union and North America. These settlements are often composed of residential or micro-productive units that cause ecological fragmentation, biodiversity loss, and spatial reorganisation. This process challenges conventional spatial analytical and planning frameworks and calls for a new approach. This paper argues that bioregional units which account for complex human-environment interactions and the sustainability of natural resources and ecosystems can provide a new analytical and planning framework. Bioregions represent the main living environments for people, and mobility is a key driver shaping their lifestyle choices. This paper explores the role of light rail systems (LRSs) in enhancing the sustainability and well-being of bioregions, using the Pontine bioregion in Italy as a case study. It reviews the bioregional theory and applies the bioregional framework to the Pontine plain presenting the main features of the Pontine bioregion, including its internal and external urban relationships. Building on these analyses, the paper then discusses the proposal of a new railway network system that integrates LRSs as strategic elements for efficient mobility, urban regeneration, social cohesion, and environmental sustainability of the bioregional territory.

Assessment and Multiscenario Simulation of Land Use and Ecosystem Services Interactions in Inner Mongolia

ABSTRACTBalancing land development and ecological protection poses significant challenges for sustainable development in arid and semi‐arid regions like Inner Mongolia. This study uses the integrated valuation of ecosystem services (ESs) trade‐offs model and patch‐generated land‐use simulation model to analyze the impacts of land‐use/cover (LULC) changes on ESs from 2005 to 2020 and simulate scenarios for 2035. The results show that (1) ecological governance efforts improved the comprehensive ecological index (CEI), habitat quality, and soil conservation capacity but led to a decrease in the annual water yield (AWY) in the eastern region. Additionally, the conversion of grassland and forest land to construction land and farmland caused slight declines in carbon sequestration and increased nitrogen export. (2) The external driving factors of different ESs vary, and the internal relationships within ESs have also changed. Notably, changes in LULC transformed the synergy between AWY and habitat quality into a trade‐off relationship after 2010 due to increased forest and grassland. (3) Among the five land‐use scenarios, the comprehensive development scenario combined with zonal management strategies can achieve the sustainable development goals of economic growth, ecological protection, and food security. This study clarifies the internal and external factors affecting ESs in Inner Mongolia and provides a scientific basis for future LULC management and ecological governance policies. It fills a gap in the spatiotemporal simulation of ESs under multiple scenarios in this region. These findings offer valuable references for promoting sustainable development in similar arid and semi‐arid regions, highlighting the importance of integrating multi‐objective strategies and adaptive management practices to balance ecological and economic objectives.

GASSF-Net: Geometric Algebra Based Spectral-Spatial Hierarchical Fusion Network for Hyperspectral and LiDAR Image Classification

The field of multi-source remote sensing observation is becoming increasingly dynamic through the integration of various remote sensing data sources. However, existing deep learning methods face challenges in differentiating between internal and external relationships and capturing fine spatial features. These models often struggle to effectively capture comprehensive information across remote sensing data bands, and they have inherent differences in the size, structure, and physical properties of different remote sensing datasets. To address these challenges, this paper proposes a novel geometric-algebra-based spectral–spatial hierarchical fusion network (GASSF-Net), which uses geometric algebra for the first time to process multi-source remote sensing images, enabling a more holistic approach to handling these images by simultaneously leveraging the real and imaginary components of geometric algebra to express structural information. This method captures the internal and external relationships between remote sensing image features and spatial information, effectively fusing the features of different remote sensing data to improve classification accuracy. GASSF-Net uses geometric algebra (GA) to represent pixels from different bands as multivectors, thus capturing the intrinsic relationships between spectral bands while preserving spatial information. The network begins by deeply mining the spectral–spatial features of a hyperspectral image (HSI) using pairwise covariance operators. These features are then extracted through two branches: a geometric-algebra-based branch and a real-valued network branch. Additionally, the geometric-algebra-based network extracts spatial information from light detection and ranging (LiDAR) to complement the elevation data lacking in the HSI. Finally, a genetic-algorithm-based cross-fusion module is introduced to fuse the HSI and LiDAR data for improved classification. Experiments conducted on three well-known datasets, Trento, MUUFL, and Houston, demonstrate that GASSF-Net significantly outperforms traditional methods in terms of classification accuracy and model efficiency.

Degradation law of bond strength of reinforced concrete with corrosion-induced cracks and machine learning prediction model

During long term operation service, reinforced concrete (RC) structures are subjected to corrosive media such as chloride salts, which results in the degradation of interface bond performance, subsequently reducing the load bearing capacity and service life of the structures. To accurately assess the durability of RC structures in environments such as oceans and salt lakes, this study combines experimental methods with machine learning (ML) techniques to explore the degradation patterns and predictive models of bond performance under chloride salt corrosion. Accordingly, a series of central pull-out tests were conducted based on an electrochemical accelerated-dry-wet cycle corrosion regime to investigate the degradation patterns of bond performance between corroded steel bars and concrete under different corrosion degree and corrosion-induced crack widths. By comparatively analyzing the evolution patterns of cracks and the morphology of the steel bars in reinforced concrete specimens and their failure modes, and integrating the mechanical degradation mechanism with chemical and microscopic corrosion mechanisms, an in-depth analysis of the corrosion-induced degradation patterns at the bond interface was performed. The internal relationships between corrosion degree, corrosion-induced crack width and bond strength were discussed, and the variation patterns of bond strength with corrosion-induced crack width and corrosion degree were explored. Moreover, the bond strength patterns were analyzed from an energy perspective. The results indicate that bond strength and bond energy decrease with an increase in the corrosion-induced crack width of the concrete. Additionally, based on the experimental data from this study, ML predictive models for bond strength were established using corrosion-induced crack width as the control variable. The results show that the ML-based bond strength predictive models fit well with the experimental data, offering higher accuracy and reliability compared to traditional bond strength models. The research findings provide significant theoretical basis and practical guidance for safety assessment, maintenance, reinforcement, and full-life design of corroded RC structures.

Tailored Engineering on the Interface Between Lithium Metal Anode and Solid‐State Electrolytes

The replacement of non‐aqueous organic electrolytes with solid‐state electrolytes (SSEs) in solid‐state lithium metal batteries (SLMBs) is considered a promising strategy to address the constraints of lithium‐ion batteries, especially in terms of energy density and reliability. Nevertheless, few SLMBs can deliver the required cycling performance and long‐term stability for practical use, primarily due to suboptimal interface properties. Given the diverse solidification pathways leading to different interface characteristics, it is crucial to pinpoint the source of interface deterioration and develop appropriate remedies. This review focuses on Li|SSE interface issues between lithium metal anode and SSE, discussing recent advancements in the understanding of (electro)chemistry, the impact of defects, and interface evolutions that vary among different SSE species. The state‐of‐the‐art strategies concerning modified SEI, artificial interlayer, surface architecture, and composite structure are summarized and delved into the internal relationships between interface characteristics and performance enhancements. The current challenges and opportunities in characterizing and modifying the Li|SSE interface are suggested as potential directions for achieving practical SLMBs.

Sinwar’s Rise in Hamas: An In-depth Analysis of Internal Dynamics and Regional Interactions

This commentary examines the implications of Yahya Sinwar’s election as the new head of Hamas following the assassination of Ismail Haniyeh. It highlights Hamas’ internal adaptability and the significance of its electoral processes in a context marked by external pressures and regional dynamics. The assassination is analyzed not only as a tactical operation by Israeli forces but also as a strategic move aimed at destabilizing Hamas internally and undermining its regional alliances, including efforts toward Palestinian reconciliation. Sinwar’s leadership is framed within the broader historical and organizational context of Hamas, emphasizing his rise due to his involvement in key military operations and his status as a founding member. The commentary further explores the potential ramifications of Sinwar’s leadership for Hamas’ organizational cohesion and regional relations, particularly in light of Operation al-Aqsa Flood and the anticipated role of external actors like Iran and Hezbollah. Ultimately, this analysis sheds light on how Hamas navigates its internal challenges and external relationships amid ongoing conflict, underscoring the complexities that define its political trajectory in a rapidly changing regional landscape.

Characterization Model Research on Deformation of Arch Dam Based on Correlation Analysis Using Monitoring Data

Deformation is the most direct indicator of structural state changes in arch dams. Therefore, numerous deformation monitoring points are typically arranged on arch dams to obtain deformation data from each point. Considering the complex relationships between the deformation at each monitoring point, this study focuses on the internal structural relationships and information fusion within the dam. The Pearson correlation coefficient is used as a similarity index to determine significant linear correlations between the measuring points. Ward’s cluster analysis method is then applied to group these points based on their similarities. To identify measuring points with strong nonlinear correlations, the Maximum Information Coefficient (MIC) method is employed. By integrating these linear and nonlinear correlations, a model is constructed to characterize the deformation at specific measurement points using data from strongly correlated points. The effectiveness of this model is verified through a concrete engineering case study, offering a novel approach for analyzing arch dam deformations.

Measuring the Pupillary Light Reflex Using Portable Instruments in Applied Settings.

The early components of the pupillary light reflex (PLR) are governed by the parasympathetic nervous system. The use of cheap, portable pupillometry devices may allow for the testing of parasympathetic-system health in field settings. We examined the reliability of two portable instruments for measuring the PLR and their sensitivity to individual differences known to modulate the PLR. Parameters of the PLR were measured in a community sample (N = 108) in a variety of field settings. Measurements were taken using a commercial pupillometer (NeuroLight, IDMED) and an iPhone using the Reflex Pro PLR analyser (Brightlamp). The parameters of baseline pupil diameter, constriction latency, amplitude and relative amplitude of constriction, and constriction velocity were measured. Individual differences related to age, levels of anxiety, and post-traumatic stress disorder (PTSD) symptomology were assessed. Some measures could not be attained using the iPhone under these field conditions. The reliability of the measures was high, save for the measurement of contraction latency which was particularly unreliable for the iPhone system. The parameters of the PLR showed the same internal relationships as those established in laboratory-based measurements. Age was negatively correlated with all the reliable PLR parameters for both systems. Effects of anxiety and PTSD symptomology were also apparent. The study demonstrated that a hand-held portable infrared pupillometer can be used successfully to measure the PLR parameters under field settings and can be used to examine individual differences. This may allow these devices to be used in workplaces, sports fields, roadsides, etc., to examine parasympathetic activity where needed.

Robust scheduling of a pulp and paper mill considering flexibility provision from steam power generation

The production scheduling and flexibility provision analysis are of great importance for industrial facilities to provide support for the main power grid. This study proposes a comprehensive scheduling model for an industrial pulp and paper (P&P) mill that considers the flexibility provision from steam power generation. In this model, the internal relationships between the production and consumption of electricity, steam, and pulp in the operational processes of the P&P mill are investigated. Meanwhile, the available flexibility of steam power generation is quantified and further enhanced for participation in the manual frequency restoration reserve (MFRR) market. Furthermore, a robust scheduling model that uses support vector clustering (SVC) technology is proposed to assess the impact of uncertainties in steam temperature and pressure on the available flexibility of steam power generation, thereby reducing the probability of failing to provide the contracted flexibility for MFRR. Simulation results demonstrate that the comprehensive scheduling model significantly increases the available flexibility of steam power generation for MFRR, resulting in a daily revenue increase of $1839.8. Moreover, a balance between the revenue obtained from the MFRR market and the probability of economic penalties incurred for failing to meet the contracted flexibility is achieved by comparing different levels of conservatism in the robust scheduling model.

What happens after the funding ends?: A qualitative sustainability investigation of emergency department-based peer support programs implemented as part of Indiana's opioid state targeted response initiative

Introduction: In 2017, funding disseminated through the US Substance Abuse and Mental Health Services Administration's Opioid State Targeted Response (STR) program accelerated the expansion of peer recovery support services across several states to engage emergency department patients presenting with opioid use disorder. While there is some literature on the initial implementation of these programs, little is known about their sustainability after the STR funding's end. Identifying what happened to these programs is a key component of understanding their ultimate impact and can inform future activities to develop, fund, or sustain similar efforts. Methods: We collected qualitative data from six organizations that participated in Indiana's STR-funded Recovery Coaching and Peer Support Initiative (RCPSI). The semi-structured interview guide was designed to gather data related to eight domains of sustainability (i.e., environmental support, funding stability, partnerships, organizational capacity, program evaluation, program adaptation, program evaluation, communications, and strategic planning). The analysts followed a deductive-inductive analysis approach, using the eight domains as an a priori coding structure and developing higher-level inductive themes. Results: A total of ten individuals (roles included 4 Program Supervisors, 2 Nurse Administrators, a Psychiatric Social Worker, a Mobile Treatment Manager, a Grant Coordinator, and a Vice President of Planning) participated in six interviews. Two programs did not sustain services, primarily because they lacked a sufficient volume of eligible patients to justify services. Factors identified as supporting sustainability in the other four programs included (1) identification of alternate funding sources, (2) evolving internal support for ED-based opioid use disorder treatment, and (3) investment in internal and external relationships. Furthermore, these themes operated across multiple sustainability domains. Conclusions: The findings illustrate a dynamic interplay between program context and multiple theorized sustainability domains that impacted the viability of RCPSI programs after the end of STR funding. Results indicate a need for a better understanding of the factors influencing the sustainability of programs supported by federal funding to mitigate the opioid crisis, and such findings will likely apply to a broader range of grant-supported programs.

Dual-stream transformer-attention fusion network for short-term carbon price prediction

Accurate prediction of carbon price provides important references for relevant companies, investors, and policymakers. However, the nonlinear, non-stationary, and random of carbon price time series pose the current prediction models a challenging task for carbon price prediction. Considering deep learning, especially for Transformer, has got a promising space in time series prediction. Therefore, this study develops a dual-stream Transformer-attention fusion network (DTF-Net), which contains three modules: multi-scale extraction, dual-stream Transformer, and attention fusion module. Firstly, the external variables of atmospheric pollution and the target variable of carbon price are taken as inputs, and the multi-scale extraction module is constructed via multiple one-dimensional convolutions with kernels to mine features on different time scales, enhancing feature engineering. Then, inspired by the idea of “divide and conquer”, the dual-stream Transformer module is applied to independently capture multivariate internal relationships and univariate temporal dependencies, improving feature learning. Finally, the attention fusion module designs the attention mechanism to generate real-time weights and dynamically integrate the above features, highlighting core features. In summary, the proposed DTF-Net network has not only relatively high prediction accuracy but also refined designs and clear multi-layer functions. Five experiments under two carbon price datasets from Hubei and Beijing carbon markets in China show the average improvements of mean absolute percentage error (MAPE) are 63.70 % and 64.55 %, 54.51 % and 53.03 %, and 57.04 % and 52.24 % for recursive, parallel and hybrid methods, respectively. The proposed DTF-Net outperforms eighteen benchmark models and is an addition to predicting carbon prices.

New specimens of Bunaia woodwardi Clarke, 1919 (Euchelicerata): a new member of Offacolidae providing insight supporting the Arachnomorpha.

The rapid early diversification of arthropods has made understanding internal relationships within the group fiendish. Particularly unresolved is the origin of Euchelicerata, a clade consisting of the Prosomapoda (comprising the extant Xiphosura and Arachnida and the extinct Chasmataspidida, Eurypterida and synziphosurines) and the extinct Offacolidae. Here we describe new material of the Silurian 'synziphosurine' Bunaia woodwardi Clarke, 1919 that reveals previously unknown features of its ventral anatomy: a pair of elongated chelicerae in the prosoma, followed posteriorly by five pairs of biramous appendages, a first pre-abdomen somite bearing a pair of paddle-like uniramous appendages (exopods) and a ventral pretelsonic process. Phylogenetic analyses retrieve B. woodwardi as a member of Offacolidae closely related to Setapedites abundantis from the Early Ordovician Fezouata Biota. An anatomical comparison of the pretelsonic process of B. woodwardi, also present in Setapedites, with the posterior trunk morphologies of other Offacolidae, Habeliida and Vicissicaudata, suggests a possible homologous appendicular origin. This proposed apomorphic character supports a monophyletic Arachnomorpha, formed of Vicissicaudata, Habeliida and Euchelicerata. The establishment of this new homology could help to clarify the highly enigmatic phylogeny at the base of the euchelicerates as well as the sequence of character acquisition during their early evolution.

A STUDY OF THE IMPACT OF SERVICE QUALITY ON CUSTOMER REVISIT INTENTION OF PSYCHOLOGICAL SERVICE COMPANIES: USING CUSTOMER EXPERIENCE AND DISEASE AWARENESS AS MEDIATING VARIABLES

In today's society, mental health issues are receiving increasing attention, and numerous psychological service companies have emerged as providers of professional mental health services. However, the market competition is also becoming more intense, making service quality a crucial factor for psychological enterprises to achieve long-term development and customer loyalty. This study aims to explore the specific mechanisms by which various elements of service quality, such as accessibility, convenience, reliability, and efficiency, affect clients' willingness to revisit psychological consulting firms. Through empirical analysis, the study seeks to clarify the degree of association between different service quality dimensions and the intention to revisit and analyze their internal relationships. Therefore, the study will survey clients who have received psychological counseling and therapy services, using client experience and disease perception as mediating variables to examine the impact of service quality on the revisit intention of customers in psychological service enterprises. Additionally, through an in-depth study of the YM Psychological Counselor Training Company, the research will analyze issues related to the company's low revisit intention and propose recommendations for adjustment, offering a reference for similar enterprises.

Psychoanalysis and homosexuality: The relevance of homophobia and shame for all sexualities

This article will describe some contemporary developments in psychoanalytic thinking about sexuality, from a post‐heteronormative standpoint. Psychoanalytic theorising of homosexuality had been generally homophobic for decades, reflecting society stereotypes. Previously, many analysts prescribed treatment to convert “the homosexual patient” to “healthy heterosexuality”, which Freud had regarded as likely to be unsuccessful. The author argues that psychoanalysis, having been part of the “disease” of homophobia, and the lengthy shadow cast by shame, can also contribute to its “cure” by promoting a broader understanding of the conscious and unconscious nature of desire and identity. The author considers the central role played by the superego in maintaining shame’s dominance and explores the impact of shame on time and temporality, including shame’s unique après coup nature. The struggle for acceptance of non‐heteronormative sexuality is discussed and contemporary developments in theorising desire, internalised homophobia, and Oedipus are explored. Drawing on fictional composite clinical vignettes, the author describes current challenges that clinicians face in relation to homophobia and shame, illustrating the central importance for clinicians to address where shame and homophobia lie within their own internal worlds and object relationships.

THE MYTH OF "PROXIES" (REPLACERS) AND THE SO-CALLED PHENOMENA OF CONSTELLATIONS

In Hellinger's family constellations, as well as in the (systemic) constellation work of practitioners who do not directly refer (or no longer refer) to Hellinger, the concept of substitution plays a central role. Its roots go back to occult ideas. It is assumed that in constellations, the participants, called "substitutes", act as true representatives of the real members of the system and are supposedly able to reliably reflect their internal states and relationships with each other. In this article, we will critically examine this assertion, which is fundamental to the constellation process and has been called the "constellation phenomenon". Contrary to the assertion that we are dealing with a phenomenon that is incomprehensible from a naturalistic point of view, it is shown that the process of constellations can be easily explained with the help of psychological mechanisms, some of which have been known for a very long time, as well as in the light of recent discoveries about so-called mirror neurons. According to this, there is no mysterious "transfer of information" between the participants in the constellation and the members of the family system, but rather a creative and highly error-prone simulation in order to reconstruct the depicted system.

Signal processing for miniature mass spectrometer based on LSTM-EEMD feature digging

Miniature mass spectrometers exhibit immense application potential in on-site detection due to their small size and low cost. However, their detection accuracy is severely affected by factors such as sample pre-processing and environmental conditions. In this study, we propose a data processing method based on long short-term memory-ensemble empirical mode decomposition (LSTM-EEMD) to improve the quality of on-site detection data from miniature mass spectrometers. The EEMD method can clearly decompose the different physical feature components in the small-scale spectrometer signals, while the LSTM method can adaptively learn the internal feature relationships of the signals. Thus, by combining the two, the parameters for the EEMD signal reconstruction can be optimized in an adaptive manner, obtaining the optimized coefficients. Compared to the previous EEMD feature enhancement approach, the LSTM-EEMD method not only significantly improves the coefficient of determination (R2) and relative standard deviation (RSD) of the data, enhancing the linear range, but also achieves fully adaptive processing throughout the workflow, greatly boosting the efficiency. By leveraging a miniature mass spectrometer, data for N-acetyl-l-aspartic acid (NAA), 2-Hydroxyglutarate (2-HG), and γ-Aminobutyric acid (GABA) in actual blood samples have been obtained. The experimental results demonstrate that the LSTM-EEMD method can markedly enhance the accuracy and usability of the biological sample data in practical testing, providing new perspectives and possibilities for research and applications in the relevant domain.

A Guideline Enabling Knowledge Managers to Communicate Better with Business Managers

Aligning Knowledge Management (KM) with overarching business strategies is considered as important for organizational success and sustainability. But this crucial element is often missing in the implementation and operation of KM. This paper explores the concept of "business alignment" within the context of KM, elaborating its critical role in enhancing collaboration, minimizing errors, and supporting optimal outcomes across the enterprise. We suggest a comprehensive definition of KM alignment, where KM activities are strategically integrated with business objectives, ensuring visible and measurable benefits to employees and executives. The research addresses key questions such as what constitutes an organization and how KM can facilitate its survival and growth. An organization is not merely a standalone entity but a collective endeavor that thrives on managing internal and external relationships. We argue that the effective alignment of KM with business strategies ensures that these relationships are optimized, thereby enhancing organizational resilience and adaptability. This holistic perspective visualizes the interconnected nature of businesses and highlights the essential role of KM. Our approach involves a systematic examination of business relationships and their alignment with KM practices. We analyze one case study from the construction industry, illustrating how strategic KM initiatives contribute to their sustained success. Additionally, we propose a set of Key Performance Indicators (KPIs) derived from real-world scenarios, linking them to specific business needs and challenges. These KPIs serve as a roadmap for C-level managers, guiding them in integrating KM into their strategic frameworks. The findings underscore the value of KM in mitigating risks associated with poor relationship management. We provide a process and actionable insights for business leaders on leveraging KM to foster innovation, streamline processes, and enhance overall performance. The paper concludes with practical recommendations for implementing KM solutions tailored to different organizational maturity levels and industry contexts.

The Evolutionary Biology of Chelicerata.

Chelicerata constitutes an ancient, biodiverse, and ecologically significant group of Arthropoda. The study of chelicerate evolution has undergone a renaissance in the past decade, resulting in major changes to our understanding of the higher-level phylogeny and internal relationships of living orders. Included among these conceptual advances are the discoveries of multiple whole-genome duplication events in a subset of chelicerate orders, such as horseshoe crabs, spiders, and scorpions. As a result, longstanding hypotheses and textbook scenarios of chelicerate evolution, such as the monophyly of Arachnida and a single colonization of land by the common ancestor of arachnids, have come into contention. The retention of ancient, duplicated genes across this lineage also offers fertile ground for investigating the role of gene duplication in chelicerate macroevolution. This new frontier of investigation is paralleled by the timely establishment of the first gene editing protocols for arachnid models, facilitating a new generation of experimental approaches.

Neolithic to Bronze Age human maternal genetic history in Yunnan, China

Yunnan in southwest China is a geographically and ethnically complex region at the intersection of southern China and Southeast Asia, and a focal point for human migrations. To clarify its maternal genetic history, we generated 152 complete mitogenomes from 17 Yunnan archaeological sites. Our results reveal distinct genetic histories segregated by geographical regions. Maternal lineages of ancient populations from northwestern and northern Yunnan exhibit closer affinities with past and present-day populations from northern East Asia and Tibet, providing important genetic evidence for the migration and interaction of populations along the Tibetan-Yi corridor since the Neolithic. Between 5500 and 1800 years ago, central Yunnan populations maintained their internal genetic relationships, including a 7000-year-old basal lineage of the rare and widely dispersed haplogroup M61. At the Xingyi site, changes in mitochondrial DNA haplogroup occurred between the Late Neolithic and Bronze Age, with haplogroup shifting from those predominant in the Yellow River region to those predominant in coastal southern China. These results highlight the high diversity of Yunnan populations during the Neolithic to Bronze Age.