Eocene planktonic foraminifera from the north Eastern Desert, Egypt: Biostratigraphic, paleoenvironmental and sequence stratigraphy implications

This study deals with the reconstruction of the paleoenvironment and the paleoclimate situation of the middle–upper Eocene sediments in the northwest Fayum area. The reconstruction is based on comprehensive stratigraphical and geochemical analyses of major oxides and trace elements for selected sediment samples from the Gehannam Formation (Bartonian–Priabonian), the Birket Qarun and the Qasr El Sagha formations (Priabonian). The sedimentological features coupled with paleo-redox trace elemental ratios (Ni/Co, V/Cr, U/Th, V/(V + Ni), and Cu/Zn), paleosalinity (Sr/Ba, Mg/Al ×100, Ca/Al), and paleowater depth (Fe/Mn) proxies, indicate that deposition took place in a shallow marine agitated environment with high oxygen levels. Paleoclimate indicators (Sr/Cu, Rb/Sr, K₂O₃/Al₂O₃, Ga/Rb, C-value, CIA, and CIW) suggest warm and prevailing arid climatic conditions, with minor humid periods at some intervals. The observed low values of the total organic carbon (TOC) are attributed to significant high sediment influx, predominant oxygenated conditions, and poor primary productivity, which is further confirmed by low values of paleoprimary productivity proxies (P, Ni/Al, Cu/Al, P/Al and P/Ti, and Ba_bio ratios). These findings enhance our understanding of the Eocene environments and provide insights into sedimentation processes during this period.

The Eocene deposits of Egypt provide a wide variety of shallow marine facies and fossil assemblages, allowing paleoenvironmental reconstructions in this warmhouse climate interval. Forty-three rock samples have been collected from two middle Eocene sections, exposed at southeast Beni-Suef area in northern Egypt. The studied outcrops are lithologicsally subdivided into two rock units named from base to top as follows: (1) the Qarara Formation (Lutetian) and (2) the El Fashn Formation (Bartonian). Most investigated rock samples showed richness in benthic foraminiferal assemblages and only rare occurrences of index planktonic foraminifera. They yielded 160 foraminifera species which belong to 4 suborders, 19 superfamilies, 34 families, and 59 genera. The stratigraphic distribution of the identified species allowed us to define four local benthic bio-ecozones: (1) Bolivina carinata Lowest Occurrence Zone (Lutetian), (2) Cibicides mabahethi/Cancris auriculus primitivus Concurrent-Range Zone, (3) Nonion scaphum Lowest Occurrence Zone, and (4) Brizalina cookei/Nonionella insecta Concurrent-Range Zone (Bartonian). These biozones are described and discussed in detail and correlated to stratigraphic equivalents in Egypt. The rareness of index planktonic foraminifera through the studied sections does not allow a precise biostratigraphic and chronostratigraphic correlation. The shale samples show low TOC values, which may be related to low productivity, high sediment influx, and/or prevailing oxic conditions. Bulk rock geochemistry, consistent with the benthic foraminifera ecological preferences, indicated that the studied sections were deposited in moderate to high oxygen levels and warm climatic conditions in a typical shelf marine setting. The identified species showed strong similarities with nearby southern Tethys areas, reflecting migration via the trans-Sahara seaway, and minor similarities with those identified from the northwestern Tethys and the North Atlantic province attributed to the change in the environmental and climatic conditions, such as cooler, latitudinal zoned climatic conditions along the northwestern Tethys, which was unsuitable for their biological demands. The warming trend identified from Lutetian to Bartonian intervals corresponds to the onset of the Middle Eocene Climatic Optimum (MECO).

Categorization of Arabic text is a significant challenge nowadays owing to the richness of text that occurs through various modules. Also, the Arabic language is considered the fifth spoken one. During the last decade, scholars incubated few concerns about this regard comparing with English language. The objective behind this investigation is to perform and evaluate new mechanism relating to different techniques of machine learning specifically for classifying Arabic text in fresh different data set. Preprocessing steps along with the representation pattern of text are essential for handling text without artifacts. We use a binary term occurrence matrix as mutual information for feature vector representation method. This paper evaluates the outcomes of classification via using Deep learning, K-Nearest Neighbor, Support Vector Machine and Naïve Bayes classifiers in similarity text level and N-gram level. It has been extracted out the outcomes that the Deep learning achieves better performance compared to itself in case of increasing similarity level and N-gram level.

Twenty-nine sediment samples were collected from Hurghada Bay, a highly impacted coastal area along the Northern Red Sea of Egypt, to evaluate environmental quality and human-induced effects on benthic ostracods. As potential bioindicators, benthic ostracods are highly responsive to environmental disturbances, with pollution leading to reduced abundance, lower diversity, and increased opportunistic taxa. To investigate the link between ostracod assemblages and sediment contamination, we measured the concentrations of eight heavy metals (Cu, Cd, Zn, Pb, As, Cr, Ni, and Mn) using inductively coupled plasma–atomic emission spectrometry (ICP-AES). Multivariate statistical analyses identified three distinct ostracod assemblages distributed across three station groups with varying pollution levels. Group I, associated with offshore stations, exhibited low to moderate heavy metal (HM) concentrations and high ostracod abundance and was dominated by Moosella striata, Hiltermannicythere rubrimaris, Ruggieria danielopoli, Neonesidea schulzi, and Paranesidea fracticorallcola, where the water depth and sand content are the main controlling factors. In contrast, Group II, corresponding to stations with the highest HMs and total organic matter (TOM), was dominated by pollution-tolerant species Jugosocythereis borchersi, Cyprideis torosa, Alocopocythere reticulata, and, to a lesser extent, Ghardaglaia triebeli, with reduced ostracod density and diversity. Group III, characterized by stations influenced by the mud-controlling factor, had the lowest HMs and was dominated by pollution-sensitive species Xestoleberis rhomboidei, Paranesidea fortificata, and Loxocorniculum ghardaquensis. These findings highlight the ecological risks posed by HM pollution and emphasize the urgent need for pollution mitigation strategies and continued monitoring to preserve the Red Sea’s benthic biodiversity.