Timoth Mkilima

Electroactive microbiomes are mixed microbial communities in which one or more members exchange electrons with extracellular minerals, redox‐active compounds, electrodes, or partner organisms and in which community interactions materially influence net electron flow. This review develops a mechanism–interface–function–readiness framework that connects extracellular electron transfer (EET) with biofilm ecology, microbiome–electrode organisation, environmental process performance, and translational maturity. Direct transfer through multiheme cytochromes and conductive structures, mediated transfer through soluble redox shuttles, and interspecies electron transfer are evaluated as system‐dependent pathways rather than universally ranked mechanisms. Particular emphasis is placed on wastewater treatment and resource recovery, anaerobic digestion, pollutant and metal transformation, soil and sediment bioelectrochemistry, carbon conversion, microbial fuel cells, microbial electrolysis cells, electro‐fermentation, and microbial electrosynthesis. Multi‐omics, metabolic modelling, synthetic biology, advanced materials, and artificial intelligence are examined according to the strength of their direct evidence in electroactive systems. Across applications, performance depends strongly on reactor configuration, electrode properties, inoculum, biofilm architecture, mass and charge transport, substrate loading, and normalisation basis, making unqualified cross‐study numerical comparison inappropriate. Major barriers are long‐term stability, mechanistic attribution in mixed communities, standardisation, scale‐up, energy and mass balances, biosafety, techno‐economic feasibility, and regulatory compatibility.

Per‐ and polyfluoroalkyl substances (PFAS) are exceptionally persistent environmental contaminants for which conventional adsorption and containment processes provide aqueous‐phase removal without eliminating the underlying organofluorine hazard. This critical integrative review evaluates destructive PFAS treatment through evidence on reaction mechanism, parent‐compound disappearance, partial degradation, defluorination, full mineralization, energy demand, byproduct formation, matrix effects, and deployment maturity. The technologies examined comprise electrochemical oxidation, advanced oxidation‐reduction processes that generate hydrated electrons, non‐thermal plasma, supercritical water oxidation, sonolysis, and thermal or hydrothermal routes. Adsorption is treated objectively as an essential concentration step in integrated concentrate‐and‐destroy treatment trains rather than as a terminal remediation process. To improve cross‐technology comparison, the review introduces Organofluorine Conversion Efficiency, which quantifies conversion of organically bound fluorine to recovered inorganic fluoride without implying destruction of elemental fluorine, together with fluorine mass‐balance closure, specific energy consumption, electric energy per order, and byproduct verification. A nine‐level PFAS Destruction Readiness Level framework is also formalized using explicit criteria for analytical confirmation, matrix realism, continuous operation, energy and cost evidence, residual management, independent validation, and regulatory acceptance. The synthesis shows that advanced reduction and cooperative redox pathways can overcome limitations of hydroxyl‐radical‐dominated oxidation for selected PFAS, but performance remains strongly matrix‐ and scale‐dependent. The proposed framework provides regulators, utilities, researchers, and technology developers with a consistent basis for distinguishing molecular disappearance from verified, deployable mineralization.

Microbial electrochemical systems couple extracellular electron transfer with substrate oxidation or CO ₂ reduction, but their performance is constrained by biofilm heterogeneity, transport gradients, electrode polarization, and community drift. This review examines intelligent plasmonic bio‐holoelectrochemical systems (iPBHS) as an evidence‐derived reference architecture integrating transparent bioelectrochemical reactors, optically addressable electrodes, structured‐light delivery, spatial sensing, and model‐predictive control. The synthesis focuses on four themes: plasmonic modulation of biomass‐normalized electron transfer, spatial transfer of projected photon fields into electrochemical responses, feedback control under safety and conservation constraints, and electron‐product carbon routing. Particular attention is given to mechanistic discrimination using resonant and off‐resonant illumination, temperature‐equivalent and structurally matched controls, spatially resolved measurements, and factorial interaction analysis. Evidence from microbial electrosynthesis, plasmonic photoelectrochemistry, optogenetic biofilms, digital twins, and reactor‐scale engineering is critically compared, while incompatible component‐level gains are not pooled. Carbon, electron, energy, and life‐cycle accounting provide the basis for evaluating system performance and scalability. No complete iPBHS prototype has yet been demonstrated, making cumulative validation of its constituent mechanisms the central research priority.

Artificial intelligence is increasingly embedded in educational processes, yet much of the literature continues to examine individual tools rather than the relationships amongst pedagogy, curriculum, assessment, knowledge validation, institutional authority, and governance. This systematic narrative review examines these relationships whilst explicitly separating evidence-based patterns from conceptual interpretation. The review followed a PRISMA-informed protocol covering database selection, Boolean search strategy, eligibility criteria, staged screening, type-appropriate quality appraisal, structured extraction, citation auditing, and thematic synthesis. Scopus, Web of Science Core Collection, ERIC, and ScienceDirect formed the reproducible database core, whilst Google Scholar and backward and forward citation tracking were used as supplementary discovery mechanisms. After duplicate removal, title and abstract screening, full-text assessment, and quality appraisal, 124 studies were retained for synthesis. The review addressed four questions concerning how artificial intelligence is conceptualised in contemporary educational research; how it is associated with changes in pedagogy, curriculum, learning analytics, assessment, and governance; what recurring relationships connect adaptive feedback, curriculum sequencing, human-AI roles, epistemic validation, and institutional accountability; and what ethical, epistemological, and governance challenges accompany increasing human-AI participation. The synthesis indicates an uneven movement from isolated tool adoption towards more adaptive and data-informed arrangements, accompanied by substantial debate over technological determinism, platform power, teacher agency, language bias, data colonialism, and epistemic justice. Adaptive epistemic ecosystems and post-linear pedagogy are therefore advanced as synthesis-derived, integrative conceptual constructs rather than predetermined coding categories or universal empirical claims. Their contribution lies in specifying testable relationships amongst human-AI cognition, learning-data infrastructures, pedagogical adaptation, epistemic validation, governance, and contextual boundary conditions whilst preserving the distinction between observed patterns, interpretive synthesis, and future-oriented propositions.

Flow diagram showing AMR-related constituents moving from municipal, hospital-influenced, and industrial or pha rmaceutical wastewater through primary treatment, biological treatment, solids separation, and disinfection or advanced polishi ng. Outputs include treated effluent, reclaimed water, sludge or biosolids, and residual streams. These connect to receiving wat ers, irrigation or reuse, land application or further handling, and return-to-treatment or separate management pathways. Resista nce-risk endpoints include reduced viable antibiotic-resistant bacteria, reduced ARG burden, reduced MGE dissemination pote ntial, reduced antibiotic and co-selective pressure, and safer discharge or reuse. The diagram emphasizes target-specific treat ment, pathway-based monitoring, and management of effluent, sludge, and residual streams. Wastewater treatment plants (WWTPs) receive antibiotic-resistant ba cteria, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), antibiotic residues, disinfectants, metals, and oth er co-selective pressures from municipal wastewater and high-risk hospital, industrial, and pharmaceutical streams. Conventio nal performance indicators do not capture viability, gene persistence, mobility, selection pressure, or exposure relevance. Perce ntage removal or single-gene log reduction may therefore misrepresent resistance-risk reduction because resistance-related tar gets and residual streams respond differently across treatment processes. This structured critical review evaluates conventiona l and advanced WWTP processes and develops a pathway-specific framework for effluent, sludge, biosolids, reclaimed water, concentrate, and backwash. In a representative full-scale study of three Dutch WWTPs, conventional treatment produced avera ge reductions of 1.86 log10 for selected ARGs and 2.31 log10 for Escherichia coli; in a separate representative study, ozone-bas ed advanced treatment exceeded 3 log10 inactivation of resistant bacteria under favorable conditions. Biological treatment can reduce biomass-associated AMR while transferring part of the burden to sludge, whereas disinfection can reduce viable organis ms without fully removing DNA-based ARG signals. WWTP assessment therefore combines target identity, absolute and relati ve abundance, load reduction, gene mobility, residual selection pressure, regrowth potential, and exposure context..

The digital transformation of criminal justice systems is reshaping investigations, prosecutions and court proceedings by changing how evidence is generated, preserved, verified and evaluated. This structured review examines the admissibility of digital evidence and the prospects for integrating blockchain technologies into law enforcement practice through a methodologically transparent synthesis of legal, forensic, governance, and computer-science literature. The analysis covers electronic case management, digital evidence lifecycle controls, blockchain-enabled chain-of-custody systems, smart-contract-assisted workflows, privacy-preserving architectures and cross-border evidentiary recognition. The review develops a blockchain-enabled evidentiary governance framework that links digital evidence generation, chain-of-custody management, blockchain verification, legal admissibility, and judicial trust outcomes. It also distinguishes established findings, such as the operational value of electronic case management and cryptographic verification, from emerging pilot evidence and future hypotheses concerning automated enforcement, cross-jurisdictional ledgers and autonomous justice systems. The synthesis shows that blockchain can strengthen evidentiary integrity when deployed as a governed verification layer combining permissioned architecture, off-chain evidence storage, on-chain metadata, validated consensus rules and auditable institutional oversight. However, its implementation remains constrained by governance failures, smart contract vulnerabilities, oracle and data-quality risks, scalability limits, privacy conflicts, legal uncertainty, institutional resistance and cost-benefit trade-offs. The review concludes that criminal justice digitalisation requires socio-technical governance rather than technological substitution, with legal reform, professional capacity, interoperability standards and rights-preserving design forming the foundation for trustworthy digital proceedings.

Remote sensing (RS) and geographic information systems (GIS) increasingly support ecosystem and biodiversity monitoring, yet evidence remains fragmented across sensors, indicators, analytical methods, and policy applications. This review synthesises 163 peer-reviewed studies published from 2015 to 2025 to determine how RS and GIS indicators can be selected, validated, and translated into decision-relevant evidence. The synthesis compares satellite and unmanned aerial vehicle platforms, vegetation indices, change-detection techniques, landscape metrics, machine-learning models, cloud-computing workflows, and multi-scale validation strategies. No sensor, index, or classifier is universally optimal. Landsat and Sentinel-2 provide the strongest basis for long-term and large-area monitoring, whereas commercial imagery and unmanned aerial vehicles better resolve fine habitat features and localised disturbance. Vegetation indices remain useful ecosystem proxies but cannot independently represent species composition, ecological integrity, or causal degradation processes. Reliable applications therefore require context-specific indicator selection, transparent preprocessing, representative ground reference data, uncertainty reporting, and integration of spectral, structural, ecological, and socio-economic evidence. Data fusion and machine learning improve monitoring performance when validation is rigorous, but computational sophistication cannot compensate for weak reference data. The review concludes that policy value depends on converting remotely sensed change into explicit, validated decision rules for zoning, restoration, protected-area management, and biodiversity reporting.

To accurately assess foundation behaviour under urban conditions, it is essential to integrate geotechnical analysis with continuously evolving hydrogeological parameters. In rapidly developing cities such as Astana, long-term fluctuations in seasonal groundwater levels, salinity dynamics, and changes in soil permeability significantly influence stress–strain behaviour and structural settlement. This study employs multiple software tools, supported by detailed hydrogeological monitoring, laboratory testing, and integrated numerical simulations, to analyse the development of settlement and stress–strain characteristics for both the synagogue and the Independence Palace. The results show that between 2002 and 2020, groundwater salinity at the synagogue site increased from 1.10 g/L to 3.39 g/L, accompanied by a 23% rise in soil permeability. At the Independence Palace site, salinity reached 2.01 g/L, with an 18% increase in permeability. Numerical simulations conducted using GEO5, PLAXIS 2D, and LIRA SAPR revealed consistent trends but varying magnitudes of subsidence. PLAXIS 2D predicted settlement values approximately 15–25% higher than GEO5, while LIRA SAPR produced estimates 10–20% lower. Among the models, GEO5 demonstrated the closest agreement with field observations. The Independence Palace underwent relatively rapid stabilisation due to an effective drainage system, with consolidation occurring over approximately 100–150 days. In contrast, the synagogue experienced prolonged settlement over a period of 10–15 years, driven by high groundwater saturation and river recharge. These findings confirm that hydrochemical evolution plays a critical role in governing soil permeability. Consequently, cross-validation using multiple modelling platforms is essential, and long-term settlement assessments in complex hydrogeological environments must account for time-dependent changes in permeability.

The construction sector is experiencing increasing demand for deep underground structures in urban environments, where excavations frequently intersect fractured aquifers. Such conditions pose significant risks to structural stability and long-term durability due to groundwater inflow and elevated hydrostatic pressures. This study investigates the influence of deep underground construction on fractured aquifer systems using the Abu Dhabi Plaza development in Kazakhstan as a case study. An integrated methodological approach combining hydrogeological monitoring, hydrochemical analysis, and engineering–geological testing was applied. Groundwater levels were monitored using observation wells, while triaxial and uniaxial compression tests were conducted to evaluate the mechanical properties of rock and soil materials. Hydraulic gradients, flow velocities, and hydrostatic pressures were estimated using Darcy’s law and the Boussinesq equation, supported by GIS-based spatial analysis. Groundwater mineralisation is consistently represented in this study by total dissolved solids (TDS), expressed in g/L. The results indicate that groundwater in the Quaternary aquifer is fresh to slightly mineralised, with TDS ranging from 0.47 to 1.50 g/L, whereas groundwater in the fractured Ordovician aquifer exhibits a more stable hydrochemical regime with TDS values of 0.72–0.73 g/L. Statistical analysis identifies two primary controls on groundwater chemistry: (i) natural geochemical processes associated with water–rock interaction and (ii) technogenic influences related to urban activities. Hydrodynamic calculations indicate a hydraulic gradient of approximately 0.136, a filtration velocity of about 0.35 m/day, well discharge reaching 0.11 L/s, and hydrostatic pressure ranging from 1.45 to 2.81 atm. Groundwater drawdown caused by excavation dewatering reached 29–30 m. The findings demonstrate that groundwater inflow is primarily controlled by fracture-controlled permeability and structural heterogeneity within the aquifer system. These results highlight the importance of integrated hydrogeological and hydrochemical assessment, in which TDS serves as the principal quantitative indicator of groundwater mineralisation, for the effective management of groundwater-related risks during deep underground construction.