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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher">BJCR</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">British Journal of Contemporary Research</journal-title>
        <abbrev-journal-title xml:lang="en">BJCR</abbrev-journal-title>
      </journal-title-group>
      <issn>2979-8582</issn>
      <publisher>
        <publisher-name>Bexford Publishing Ltd</publisher-name>
        <publisher-loc><uri>https://bexfordpublishing.co.uk</uri></publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">BEX_OCT_26_089</article-id>
      <article-id pub-id-type="doi">10.67693/BJCR-6UTHFG7U</article-id>
      <article-categories>
        <subj-group xml:lang="en" subj-group-type="heading">
          <subject>Original Research Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title xml:lang="en">Groundwater Hydrogeochemistry, Uranium Mobility and Human Health Risk in the Mikir Hills, Assam, India: An Integrated Multivariate, Machine-Learning and Risk-Assessment Framework</article-title>
      </title-group>
      <contrib-group content-type="author">
      <contrib corresp="yes">
        <name-alternatives>
          <name name-style="western" specific-use="primary">
            <given-names>Ashokaditya P. Dhurandhar</given-names>
          </name>
        </name-alternatives>
        <email>apdhurandhar@gmail.com</email>
        <bio xml:lang="en"><p>Orion Geohytech India, G-10 Brahmaputra Apartment, Aakar Nagar, Katol Road, Nagpur, India</p></bio>
      </contrib>
      </contrib-group>
      <pub-date date-type="pub" publication-format="epub">
        <day>10</day>
        <month>11</month>
        <year>2026</year>
      </pub-date>
      <volume>1</volume>
      <issue>6</issue>
      
      
      <pub-history>
        <event event-type="received">
          <event-desc>Received: <date date-type="received">
            <day>10</day>
            <month>10</month>
            <year>2026</year>
          </date></event-desc>
        </event>
        
        <event event-type="accepted">
          <event-desc>Accepted: <date date-type="accepted">
            <day>16</day>
            <month>10</month>
            <year>2026</year>
          </date></event-desc>
        </event>
      </pub-history>
      <permissions>
        <copyright-statement>Copyright (c) 2026 Ashokaditya P. Dhurandhar</copyright-statement>
        <copyright-year>2026</copyright-year>
        <license xlink:href="https://creativecommons.org/licenses/by/4.0">
          <license-p>This work is licensed under a Creative Commons Attribution 4.0 International License.</license-p>
        </license>
      </permissions>
      <abstract><p>Groundwater in the Mikir Hills of Assam, India, occurs within a complexly layered lithostratigraphic framework spanning Archaean basement gneisses to Quaternary alluvium. To characterise the hydrogeochemical controls on major ions, trace metals, and uranium (U) behaviour, a dataset of 143 groundwater samples across 16 core parameters (U, Na, K, Ca, Mg, Cl, SO4, HCO3, pH, electrical conductivity, TDS, Cu, Pb, Zn, Ni, and Fe) was evaluated using an integrated multivariate, geochemical, and machine-learning framework. Hydrochemical facies analysis demonstrates that groundwaters are predominantly of Ca–Mg–HCO3 (52%) and mixed Ca–Na–HCO3 (30%) types, with Gibbs formulations confirming rock-weathering dominance alongside negative chloro-alkaline indices denoting reverse ion exchange. Speciation modeling indicates widespread supersaturation with respect to calcite (SI=+0.42) and dolomite (SI=+0.77), confirming that carbonate buffering establishes circumneutral-to-alkaline conditions. Nonparametric correlation and principal component analysis (PCA; four components explaining 67.2% of total variance) show that U is decoupled from bulk mineralisation (loading −0.04 on PC1) and instead loads on PC3 (0.64) and PC4 (0.35) alongside Cu, Fe, and Zn. Random Forest (RF) regression reveals negative cross-validated performance (R2=−0.077), whereas RF classification effectively discriminates upper-quartile U concentrations (&gt;0.50 μg/L) with a ROC-AUC of 0.794. The Entropy-Weighted Water Quality Index (EWQI) identifies 38% of samples within poor-to-very-poor categories, driven predominantly by Fe and localized trace elements. Chemical health-risk assessment establishes non-carcinogenic hazard quotients (HQ) exceeding 1.0 in 19% of adult and 31% of child cohorts, with cumulative hazard indices (HI&gt;1.0) reaching 47% and 58%, respectively. These findings demonstrate that U migration is governed by redox-mediated Fe–Mn cycling, carbonate ligand complexation, and structural fracture conduits rather than bulk salinity. Identification of overlapping anomalies in high-strain corridors and fault zones—specifically at the Akashiganga–Udganga Convergence—host a significant alignment of peak gaseous Radon (&gt;1100 counts/50 s) alongside Aqueous Radium (Ra) and Aqueous Uranium (U) anomalies, designating this convergence zone as the prime vector target for concealed mineralization.</p></abstract>
    </article-meta>
  </front>
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