Earth Sciences Pakistan (ESP)

Extensive growth in development, urbanization, and population has exacted more pressure on the availability and quality of groundwater resources. Human effort has been directed at solving groundwater scarcity in a crystalline basement rock environment, through the identification of joints, cracks, fractures, faults, and weathered materials that may exhibit favourable disposition to groundwater accumulation for water sustainability. This research applied Multi-Criteria Decision Analysis (MCDA) in the context of Analytical Hierarchical Process (AHP) to geoelectric parameters to model Groundwater Potential Zones (GWPZ) in the Federal Polytechnic, Ado Ekiti, Ekiti State, Nigeria. The Electrical Resistivity method was adopted using 2D Resistivity Tomography and Vertical Electrical Sounding (VES) utilizing Schlumberger configuration. 2D Resistivity Tomography was delineated to determine vertical and lateral ranges in apparent resistivity of the subsurface geological properties favourable to groundwater accumulation and development. Eight (18) VES were acquired across the study area. The iterated VES results were used to generate geoelectric sections, maps, and second-order parameters. The MCDA in the context of the AHP technique was used to assign scores to various contributing parameters based on their relative contribution to groundwater potential. The GWPZ was generated by incorporating the selected and weighting seven important defined variables (Coefficient of anisotropy, overburden thickness, aquifer resistivity, aquifer thickness, storativity, transmissivity, and hydraulic conductivity) in the Surfer 12 environment in reflection to their groundwater availability. The groundwater potential was categorized into high, moderate, low, and very low. Very low to low groundwater potential characterized the entire study area, occupying 75% with moderate to high occupying 25%. The finding revealed that the study area was characterized by very low to low groundwater potential. This research will assist in the development and monitoring of groundwater occurrences by decision policymakers to improve recharge techniques, especially in very low and low groundwater recharge zones

Earthquake early warning systems have become vital for minimizing damage from seismic events. However, their automated detection capabilities need strengthening to provide real-time alerts. Current algorithms have limitations in identification of P-waves and magnitude estimation, impacting warning lead times. Additionally, existing single-algorithm dependent systems are prone to errors. There is a need for
standardized practices to optimally select and combine algorithms. Machine learning and artificial intelligence show promise to make detection more robust. Models trained on diverse seismological data can learn complex patterns to detect emergent P-waves earlier and refine magnitude assessment. However, research exploring such data driven approaches within early warning systems is limited. This study aims to address this research gap and strengthen automated detection capabilities. It proposes a machine learning model integrating multiple existing algorithms using a novel prioritization framework. Performance is evaluated on real earthquake datasets through simulations vis-à-vis single algorithms. By developing an optimized multi-algorithm framework, this study seeks to improve warning lead times and reliability. The model is designed considering operational requirements of early warning systems. Comparison of results with past methods helps evaluate contributions to the field. Overall, the research strives to enhance seismic hazard mitigation through more efficient automated detection in early warning networks.

This paper presents a detailed study on refraction survey carried out in the Central Swamp Depobelt of the Niger Delta in order to compute the characteristics of the surface waves. Twenty-seven (27) boreholes were each drilled in the Central Swamp Depobelt of the Niger Delta to 66m. The borehole data were acquired using Seismograph McSeis-160MX Recorder, hydrophone detector and electric detonator as the source. Analysis of the results shows two-layer refractors. The consolidated-layer velocities range between 1580 and 1906ms-1with an average of 1737.78ms-1. Weathered-layer (surface) velocities range between 213 and 781ms-1 with an average of 504.81ms-1. Air-blast low velocities range between 213 and 377ms-1 with an average of 307.33ms-1. Depths from refracting surfaces range between 2.25 and 6.12m with an average of 4.58m. Dominant surface wave frequencies range between 5 and 10Hz. The layer thickness and velocity parameters can be applied in static correction in the processing of seismic reflection survey data. The dominant frequency information can also be integrated with the other parameters in detector and source arrays design necessary for attenuating the ground roll noise in the study area.

In recent years, machine learning (ML) has burgeoned as a transformative tool, particularly within predictive maintenance applications. The mining sector, characterized by its heavy machinery and capital-intensive equipment, stands to benefit immensely from advancements in predictive maintenance techniques. This comprehensive review delves into the recent innovations in ML-driven predictive maintenance and their significant applications within the mining industry. Drawing from an array of case studies and empirical analyses, this paper underscores the tangible operational efficiencies and cost-saving benefits brought about by these ML methodologies. Furthermore, it offers critical insights into the challenges, best practices, and the potential future trajectory of this intersection of machine learning and mining operations.

This study investigates the geology and the engineering geological properties of lateritic soil of Ita – Oniyan area of Ondo state, Southwestern, Nigeria. Twenty soil samples were collected from twenty test pits at depth of about 1.0m and were air–dried for two weeks and, thereafter were subjected to laboratory analyses which include natural moisture content, particle size analysis, consistency limits, linear shrinkage, specific gravity, standard compaction, shear strength, and unsoaked California Bearing Ratio (CBR) tests. Results showed that the natural moisture content of the soils ranged from 7% to 28%, the liquid limit ranged from 30.2% to 69.1%, the plastic limit ranged from 17.5% to 43.4%, while the plasticity index ranged from 8.6% to 36.9%. The soils were grouped into CL (low plasticity), CI (medium plasticity), and CH (high plasticity). Linear shrinkage ranged from 3.7% to 11.9%. Grain size analysis gave coarse contents varying from 30.4% to 98.1% and fine contents from 27.4% to 86.9%. The unsoaked CBR ranged from 18% to 72%, for compaction, MDD ranged from 1482kg/m3 to 1981kg/m3, and OMC from 13.7% to 32.5%. Geologic mapping showed that the major rock types in the study area were biotite gneiss, charnockite, quartzite and granite parent rocks from which the soil was formed. The soil samples are made up of lateritic soil with high clay content mainly illite, since the soil samples in the study area have poor engineering properties therefore the soil needed to be stabilized to improve their engineering properties.

The Late Eocene planktic foraminiferal species Turborotalia semicunialensis Anan with its raised keel in the first two chambers of the last whorl, was recorded recently from the planktic foraminiferal zonation Globigerinatheca index Zone (E16) of Jabal Hafit, United Arab Emirates (UAE). Another forms of this species, but under another names from the Turborotalia cerroazulensis group, were recorded from Cambay Basin, northwest of India (to the east of UAE), and from Wadi Hitan, Fayum area, Western Desert of Egypt (to the west of UAE). This documentation expanded the stratigraphic range of T. semicunialensis from E15 to P16 zonation throughout the Late Eocene. In general, the planktic foraminifera is predominantly considered to be related to open marine environment, photic zone, middle-upper neritic environment (100-200 m water depth).

Pavement blocks are increasingly popular in construction due to their durability, versatility, and aesthetics. However, their conventional production process heavily relies on natural resources like sand, cement, and aggregates, raising sustainability concerns. The construction industry faces growing pressure to adopt eco-friendly practices that minimize environmental harm and conserve resources. This study explored using waste materials in making interlocking pavement blocks. It found that replacing some cement with bagasse ash, fly ash, and brick kiln dust improved compressive strength compared to traditional blocks after 28 days. Substituting some aggregate with crushed waste plastic slightly reduced tensile strength, particularly at 7 and 28 days, with lower replacement ratios performing better. Overall, using waste materials in pavement block production has the potential to promote sustainable construction by reducing environmental impact and costs, aligning with sustainable development principles and resource efficiency.

Earth’s geological history spans billions of years, yielding insights into its evolution, climate shifts, and life’s development. This article provides a comprehensive overview, encompassing eons, eras, and pivotal events. Geological processes like tectonics, volcanism, and continental formation are explored. We analyze stratigraphy, paleontology, and dating techniques to offer a clear understanding of Earth’s journey. Beginning with the geological time scale, the narrative delves into Precambrian eons, from the fiery Hadean to the emergence of complex life in the Proterozoic. The Paleozoic era’s emergence of terrestrial life and Cambrian explosion are detailed, along with the Mesozoic’s reptilian dominance and Pangaea’s breakup. The Cenozoic era, spanning from dinosaurs to the present, covers mammalian evolution, ice ages, and hominid impact. Geological processes that shaped Earth’s surface and lithosphere are outlined, including tectonics’ role in continental movement. Extinctions, climate shifts, and land bridge formations demonstrate how geology influenced life. Human interaction’s geological consequences, such as climate change and resource utilization, are considered. Understanding Earth’s geological history underscores our planet’s dynamic nature, informing conservation and resource management decisions. Through this exploration, we uncover the intricate relationship between geological processes, biological evolution, and environmental systems that define our world.

The modern taxonomical consideration is used for most diagnostic sixteen Maastrichtian-Neogene Rotaliid benthic foraminiferal species of the genus Pararotalia Le Calvez which has wide geographic distribution in many Tethyan sites: USA, Northern Tethys (England, France, Belgium, Holland, Germany, Italy, Poland, Slovenia, Romania) and Southern Tethys (Libya, Egypt, Tanzania, UAE, Pakistan, India). The Maastrichtian-Paleocene species is P. tuberculifera (Reuss). The Paleocene species is P. macneili Loeblich and Tappan. The Paleocene-Eocene species is P. ishamae Loeblich and Tappan. The Eocene species are: P. audouini (d’Orbigny), P. clavezae Loeblich & Tappan, P. inermis (Terquem), P. khirthari Haque, and P. pakistanica Anan. The Eocene-Oligocene species is P. spinigera (Le Calcez). The Oligocene species are: P. byramensis (Cushman), P. curryi Loeblich & Tappan, P. parva (Cushman) and P. subinermis Bhatia. The Neogene species are: Pararotalia aculeata (d’Orbigny), P. armata (d’Orbigny) and P. loeblichi Anan. One species is believed to be new: Pararotalia loeblichi Anan, n. sp. Eight species of them were recorded from USA (about 50%), 6 from Romania (about 37.5%), 5 from each of France, Egypt, UAE and Pakistan (about 31.5%), 3 from Poland (about 19%), 2 from Belgium, Italy and Slovenia (about 12.5%), 1 species from each of England, Libya and India (about 6%). The petaloid test and keeled peripheral margin are mostly represented warm water environment.

The latest Maastrichtian planktic foraminiferal Egyptian species Plummerita haggagae Anan from the planktic foraminiferal zonation P. hantkeninoides Zone of Duwi section (Qusseir area, Red Sea coast, Eastern Desert of Egypt) has last spine-like prolongation of the three penultimate of four-chambered volution test, and also recorded here from the same stratigraphic horizon of Per Fat section (Duhok area, Kurdistan region of Iraq). This species represents the third group of Plummerita (Plummerita haggagae group of Anan). The other two groups of Plummerita, which produced by Brönnimann (1952) from Trinidad, are: Plummerita hantkeninoides group (last five-chambered volution: P. hantkeninoides, P. costata, P. inflata), and Plummerita reicheli group (last six-chambered volition: P. reicheli, P. pustulata, P. hexacamerata). P. haggagae is distinguished by its four-chambered volition in dextral coiling, with axially pointed spine-like prolongation for the three penultimate chambers, but without spine-like prolongation of the last fourth inflated chamber. The fauna of Gabal Duwi in central Egypt is predominantly considered here to be related to MTF (middle-upper neritic environment (100-200 m water depth).