When soil material is subjected to external loading (pressure), its particles tend to undergo rearrangement because of the gradual expulsion of air/water from the soil mass which gives rise to reduction in volume. The loading pattern has a significant effect on the behavior of soil as it responds to the loading. In this research, two categories of consolidation tests; namely Rapid Loading Tests and Standard loading tests were carried out on different soil samples extracted from four different locations within Port Harcourt, Nigeria to investigate the effect of rate of loading on the consolidation properties of cohesive soils. In the Rapid loading Tests, the incremental loading was done at every one-hour (1hr.) interval to simulate the rapid loading whereas in the Standard Loading Tests, the load increment was done at every 24 hours or until there was no significant change in the dial gauge reading. The results of the investigation showed that the values for the coefficient of volume compressibility (mv), and compression index (Cc) were higher by an average of 34.8% and 77.2% respectively whereas the values of Coefficient of consolidation (cv), Swelling Index (Cs), the time factor for 90% consolidation (t90) and Preconsolidation pressure (Pc) were found to be reduced by an average of 37.8%, 33.8% ,32.6% and 15.4%respectively. More so, the settlements were found to be higher by an average of 23.5% in the rapidly loaded soil samples as compared to those of the standard loading tests. Lastly, the results of the investigation, when compared to the recommended values, were found to be within the acceptable range of values. Hence, it could be concluded that soils respond differently depending on the loading pattern, and that the compressibility properties of soil materials can be affected by the rate of loading.

Public infrastructure projects frequently experience schedule delays, cost escalation, rework, coordination failures, and performance uncertainty caused by fragmented construction planning, changing environmental conditions, and incomplete geotechnical information. This study proposes a risk-informed construction delivery model that integrates construction risk prediction, lifecycle performance governance, environmental exposure assessment, and subsurface uncertainty evaluation to improve the resilience of public infrastructure projects. The framework organizes project risk into four connected dimensions: construction execution risk, lifecycle infrastructure performance risk, environmental and drainage-related exposure risk, and geotechnical reliability risk. A weighted decision matrix evaluates project vulnerability using measurable indicators, including delay probability, coordination complexity, design revision frequency, soil variability, and environmental exposure. The study also introduces a Project Resilience Index to evaluate infrastructure delivery performance under changing environmental and geotechnical conditions during planning, design, and construction. The framework is suitable for conceptual, analytical, and simulation-based evaluation without requiring proprietary project datasets. Scenario-based evaluation indicates that increasing environmental exposure and subsurface uncertainty increase project vulnerability while reducing resilience throughout construction delivery. The proposed framework provides a unified project delivery approach connecting BIM-oriented coordination, engineering management, urban environmental systems, and foundation reliability for resilient public infrastructure management.

Solid electrolytes are commonly designed using static descriptors such as crystallographic bottlenecks, vacancy concentrations, and migration barriers, yet emerging evidence shows that anion translation, rotation, vibration, and disorder can actively reorganize ionic energy landscapes. This review establishes a unified materials framework linking dynamic anion sublattices, cooperative ion migration, and metastable pathway engineering across lithium-, sodium-, proton-, and multivalent-ion conductors. A literature synthesis will compare sulfides, halides, oxyhalides, complex hydrides, solid acids, antiperovskites, and amorphous or partially crystalline electrolytes. Particular emphasis is placed on distinguishing independent hopping from correlated, concerted, paddle-wheel, and phonon-assisted transport; identifying when anion motion is causal rather than merely coincident; and determining how mixed-anion chemistry, defects, strain, mechanochemistry, quenching, and controlled amorphization stabilize transport-active configurations. Mode-resolved spectroscopy, neutron methods, solid-state nuclear magnetic resonance, total scattering, ab initio molecular dynamics, enhanced sampling, and machine-learned interatomic potentials are critically evaluated for resolving coupled sublattice dynamics across time and length scales. Quantitative structure–dynamics–transport relationships are proposed using conductivity, activation energy, correlation factors, rotational timescales, phonon characteristics, disorder metrics, and electrochemical stability. The review concludes with experimentally testable design rules and standardized reporting priorities for discovering room-temperature solid electrolytes that combine rapid ion conduction, metastable retention, interfacial compatibility, and device-level durability.

The convergence of the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) has strengthened smart greenhouse management by enabling continuous environmental monitoring, automated control, and more informed use of agricultural resources. This review examines and synthesises research on IoT- and WSN-enabled greenhouse systems published between 2015 and 2026. Peer-reviewed studies retrieved mainly from IEEE Xplore and Google Scholar were analysed across sensing technologies, system architecture, communication methods, network topology, control approaches, cloud–edge computing, energy management, and performance assessment. The reviewed studies show that achieving strong performance in one area often requires compromises elsewhere, particularly among communication range, energy demand, reliability, scalability, latency, computational capacity, and cost. ZigBee is particularly suitable for low-power, short-range mesh networks, whereas LoRa better supports wider-area deployments. Clustered and hybrid network structures offer favourable scalability and reliability, while cloud–edge architectures combine scalable analytics with rapid local processing. Intelligent control improves prediction, adaptability, and resource use, whereas renewable energy and intelligent energy management can reduce reliance on conventional power sources. Practical deployment, however, remains constrained by sensor reliability, energy limitations, communication instability, interoperability, cybersecurity risks, and limited long-term validation. Future studies should place greater emphasis on energy-autonomous systems, edge intelligence, secure and interoperable architectures, digital twins, adaptive autonomous control, and realistic evaluation of emerging communication technologies for greenhouse applications. Overall, future smart greenhouses are likely to depend increasingly on integrated architectures that combine energy efficiency, adaptive control, reliable connectivity, and security to support sustainable operation.