Dominant Feature Research Articles

Modulating Coarse-Grained Dynamics by Perturbing Free Energy Landscapes.

We introduce an approach to describe the long-time dynamics of multiatomic molecules by modulating the free energy landscape (FEL) to capture dominant features of the energy-barrier crossing dynamics of the all-atom (AA) system. Notably, we establish that the self-diffusion coefficient of coarse-grained (CG) systems can be accurately delineated by enhancing conservative force fields with high-frequency perturbations. Using theoretical arguments, we show that these perturbations do not alter the lower-order distribution functions, thereby preserving the structure of the AA system after coarse-graining. We demonstrate the utility of this approach using molecular dynamics simulations of simple molecules in bulk with distinct dynamical characteristics with and without time scale separations as well as for inhomogeneous systems where a fluid is confined in a slit-like nanochannel. Additionally, we also apply our approach to more powerful many-body potentials optimized by using machine learning (ML).

Semi-supervised spectral classification of DESI white dwarfs by dimensionality reduction

Abstract As a new generation of large-sky spectroscopic surveys comes online, the enormous data volume poses unprecedented challenges in classifying spectra. Modern unsupervised techniques have the power to group spectra based on their dominant features, circumventing the complete reliance on training data suffered by supervised methods. We outline the use of dimensionality reduction to generate a 2D map of the structure of an intermediate-resolution spectroscopic dataset. This technique efficiently separates white dwarfs of different spectral classes in the Dark Energy Spectroscopic Instrument’s Early Data Release (DESI EDR), identifying spectral features that had been missed even by visual classification. By focusing the method on particular spectral regions, we identify white dwarfs with helium features at 90percnt recall, and cataclysmic variables at 100percnt recall, illustrating rapid selection of low-contamination samples from spectroscopic surveys. We also demonstrate the use of dimensionality reduction in a supervised manner, outlining a procedure to classify any white dwarf spectrum in comparison with those in the DESI EDR. With upcoming surveys promising tens of millions of spectra, our work highlights the potential for semi-supervised techniques as an efficient means of classification and dataset visualisation.

Feasibility of Acoustic Features of Vowel Sounds in Estimating the Upper Airway Cross Sectional Area during Wakefulness: A Pilot Study

Assessment of upper airway dimensions has shown great promise in understanding the pathogenesis of obstructive sleep apnea (OSA). However, the current screening system for OSA does not have an objective assessment of the upper airway. The assessment of the upper airway can accurately be performed by MRI or CT scans, which are costly and not easily accessible. Acoustic pharyngometry or Ultrasonography could be less expensive technologies, but these require trained personnel which makes these technologies not easily accessible, especially when assessing the upper airway in a clinic environment or before surgery. In this study, we aimed to investigate the utility of vowel articulation in assessing the upper airway dimension during normal breathing. To accomplish that, we measured the upper airway cross-sectional area (UA-XSA) by acoustic pharyngometry and then asked the participants to produce 5 vowels for 3 seconds and recorded them with a microphone. We extracted 710 acoustic features from all vowels and compared these features with UA-XSA and developed regression models to estimate the UA-XSA. Our results showed that Mel frequency cepstral coefficients (MFCC) were the most dominant features of vowels, as 7 out of 9 features were from MFCC in the main feature set. The multiple regression analysis showed that the combination of the acoustic features with the anthropometric features achieved an R2 of 0.80 in estimating UA-XSA. The important advantage of acoustic analysis of vowel sounds is that it is simple and can be easily implemented in wearable devices or mobile applications. Such acoustic-based technologies can be accessible in different clinical settings such as the intensive care unit and can be used in remote areas. Thus, these results could be used to develop user-friendly applications to use the acoustic features and demographical information to estimate the UA-XSA.

Functioning of Conceptual Metaphor in Shaping Image of Iraq in Regional and Federal Media in Germany

This comparative study examines the role of conceptual metaphorization as a means of shaping the image of Iraq in regional and federal media in Germany from 2019 to 2024. The analysis focuses on the frequency of metaphors, the magnitude and dominant features of the nominative field of metaphors, semantic and part-of-speech properties of metaphor representatives, and the salient characteristics of the country as components of its image, along with paradigmatic and syntagmatic relationships. It identifies both stable and variable patterns of metaphorization across the two groups of media. The study highlights recurring metaphors such as “Iraq as a Living Being,” “Iraq as an Incomplete Whole,” “Iraq as a Place of Uncontrolled Power,” “Iraq as a Warrior,” “Iraq as a Theater,” “Iraq as a Toy,” and “Iraq as a Refuge.” The findings conclude the effectiveness of conceptual metaphor as a tool for stereotyping; similarities in the composition of metaphors despite differences in their frequency and density across various German media; a predominance of complex, structural, and ontological metaphors; and the presence of compatible and coherent metaphors. Notably, there is an interdependence between the frequency and density of the nominative field of metaphors, with higher density observed in federal media; stability in terms of the part-of-speech affiliation of representatives and dominance of noun representatives; predominant overlap in the dominant features of nominative fields across different media groups; and the existence of metaphors with varying degrees of conventionality.

Understanding CO adsorption in MOFs combining atomic simulations and machine learning

This study introduces a computational method integrating molecular simulations and machine learning (ML) to assess the CO adsorption capacities of synthesized and hypothetical metal–organic frameworks (MOFs) at various pressures. After extracting structural, chemical, and energy-based features of the synthesized and hypothetical MOFs (hMOFs), we conducted molecular simulations to compute CO adsorption in synthesized MOFs and used these simulation results to train ML models for predicting CO adsorption in hMOFs. Results showed that CO uptakes of synthesized MOFs and hMOFs are between 0.02–2.28 mol/kg and 0.45–3.06 mol/kg, respectively, at 1 bar, 298 K. At low pressures (0.1 and 1 bar), Henry’s constant of CO is the most dominant feature, whereas structural properties such as surface area and porosity are more influential for determining the CO uptakes of MOFs at high pressure (10 bar). Structural and chemical analyses revealed that MOFs with narrow pores (4.4–7.3 Å), aromatic ring-containing linkers and carboxylic acid groups, along with metal nodes such as Co, Zn, Ni achieve high CO uptakes at 1 bar. Our approach evaluated the CO uptakes of ~ 100,000 MOFs, the most extensive and diverse set studied for CO capture thus far, as a robust alternative to computationally demanding molecular simulations and iterative experiments.

“i write unbalanced poetry”

In examining changes to Bernadette Mayer’s writing style following her cerebral hemorrhage in 1994, the article investigates the ways in which Mayer’s poetics have been informed by disability. Positioning the effects of her stroke not as limitations but as capacities for generating new knowledge, Mayer’s embodiment of disability in her late work also provokes a reassessment of her early work. Asserting that disability complicates normative time frames, an analysis of Mayer’s relationship to and representation of time reveals that disability informed her poetics not only after her stroke, but in anticipation of it, too. Drawing on archival evidence from Mayer’s papers and correspondence at the University of California San Diego, improvisation is established as a dominant feature in her late work, while the anticipation of disability in her early work contributes to the development of performance-inflected poetics.

Comparative Analysis of Deep Learning Models for Building Extraction from High-resolution Satellite Imagery

In this research, an approach to extract buildings from Google's satellite imagery was proposed. The performances of various deep learning models (U-Net, RIU-Net, U-Net++, Res-U-Net, and DeepLabV3+) on pre-processed datasets were compared. The models were trained using the similarity metrics of Intersection over Union (IoU) and Dice Similarity Coefficient (DSC). The best-performing models among the segmentation techniques were Res-U-Net and DeepLabV3+. Res-U-Net, an enhanced version of the traditional U-Net model that incorporates residual connections for improved feature propagation, achieved an F1 score of 85.43% when using the RGB dataset. Similarly, DeepLabV3+ also achieved high performance on the Enhanced RGB dataset, obtaining an F1 score of 85.18% after applying pre-processing techniques. This research highlights the significance of color as a dominant feature for accurate building extraction from satellite images. The findings contribute to improved methodologies for building identification, benefiting urban planning, and disaster management applications.

INVESTIGATING THE INHERITANCE PATTERNS AND POTENTIAL ASSOCIATIONS OF SELECTED HUMAN MORPHOGENETIC TRAITS

This research analyses the distribution, inheritance patterns, and potential associations between various physical characteristics(Handedness, Hand-clasping, Tongue-rolling, tongue folding and Hitchhiker’s thumb, Mid-phalangeal hair, bent little finger, Cleft chin, Widow’s peak, earlobe attachment & Dimpled cheeks) in students from the Faculty of Agriculture Sciences. The Chi-square was used of independence to assess inheritance patterns and potential links. The findings reveal interesting patterns: some recessive traits viz; Mid-phalangeal hair, bent little finger, Cleft chin, Widow’s peak, earlobe attachment & Dimpled cheeks were more common than their dominant counterparts. In contrast, dominant features such as handedness, hand-clasping, tongue-rolling, tongue folding, and hitchhiker's thumb were found more frequently. There is also a significant relationship between morphogenetic features (tongue rolling, mid-phalangeal hair, and widow's peak) and gender. This investigation has implications for several disciplines, including human genetics, forensics, and anthropology. Establishing a baseline for this specific population size group allows for future investigation into human variety and the intriguing realm of inheritance.

An interpretable surrogate model for H2S solubility forecasting in ionic liquids based on machine learning

Here we investigated four different ML-based models, i.e., gaussian process regression (GPR), extreme gradient boosting (i.e., XGBoost), random forest (RF), and support vector machine (SVM), for predicting the solubility of H2S in various ionic liquids (ILs). The dataset was divided into training and testing sets in an 80:20 ratio while the model performance for all models were evaluated using the coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE). Overall, all models effectively predicted H2S solubility, albeit with varying degrees of performance. The GPR provides the best performance, with R2 of 0.9918, MAE of 0.0090, and RMSE of 0.0147. Following this is the XGBoost model with an R2 value of 0.9827, MAE of 0.0155, and RMSE of 0.0213. The RF model displayed slightly lower performance, with an R2 value of 0.9395, MAE of 0.0261, and RMSE of 0.0398 while the lowest performance was demonstrated by the SVM model, which gave an R2 value of 0.9036, MAE of 0.0402, and RMSE of 0.0508. We used SHAP analysis and identified the pressure, temperature, Estate_VSA3, Estate_VSA5, and MinEStateIndex as the top five dominant input features in our model interpretation. In a nutshell, this work presents new insights into the molecular characteristics that affect the solubility of H2S in ILs, paving future research path in this field.

Spectral proper orthogonal decomposition analysis of a spatially developing underexpanded round jet at Re = 45 000

This study conducts a comprehensive analysis of the coherent structures within a spatially developing underexpanded axisymmetric jet at a Reynolds number of 45 000, utilizing high-fidelity implicit large eddy simulations (iLES) in conjunction with spectral proper orthogonal decomposition (SPOD). In the frequency–wavenumber space, the global SPOD analysis identifies three distinct coherent structures, corresponding to three different mechanisms, namely, Kelvin–Helmholtz (KH), Orr, and lift-up. Their salient characteristics are discussed in detail. Local SPOD analysis further explores the streamwise evolution of these coherent structures, revealing that the influence of KH mechanism is confined to the near field, while the lift-up mechanism persists and dominates the energy content beyond the potential core, with the streaks of azimuthal wavenumbers one and two being the most energetic. The reconstruction of turbulent kinetic energy (TKE) and Reynolds shear stress from SPOD modes is assessed, and the first few azimuthal modes with low wavenumbers and frequencies are found crucial for capturing the dominant features of the flow. It is found that only the m = 0 and m = 1 modes contribute to the TKE at the centerline. The Reynolds shear stress reconstruction quality is comparable to TKE, but with a negligible contribution from the m = 0 mode. The azimuthal mode m = 1 captures the slope of the actual Reynolds shear stress profile in the vicinity of centerline, while m = 2 and higher modes capture the peak location of the actual profile.

TimeNorm: a novel normalization method for time course microbiome data.

Metagenomic time-course studies provide valuable insights into the dynamics of microbial systems and have become increasingly popular alongside the reduction in costs of next-generation sequencing technologies. Normalization is a common but critical preprocessing step before proceeding with downstream analysis. To the best of our knowledge, currently there is no reported method to appropriately normalize microbial time-series data. We propose TimeNorm, a novel normalization method that considers the compositional property and time dependency in time-course microbiome data. It is the first method designed for normalizing time-series data within the same time point (intra-time normalization) and across time points (bridge normalization), separately. Intra-time normalization normalizes microbial samples under the same condition based on common dominant features. Bridge normalization detects and utilizes a group of most stable features across two adjacent time points for normalization. Through comprehensive simulation studies and application to a real study, we demonstrate that TimeNorm outperforms existing normalization methods and boosts the power of downstream differential abundance analysis.

The Blame Game: The Role of Media Environments and Political Discussion in Americans’ Attribution of Blame for Interparty Hostility

Abstract Polarization and hostility between political parties is a dominant feature of politics in the United States and is growing in many other democracies worldwide. Yet, there remain questions of who the public blames for this hostility and how those attributions of blame emerge. This study examines the role of partisan strength, political media exposure, and political discussion on blame for partisan hostility. Analyses of survey data (YouGov) collected during the 2020 U.S. presidential election suggest that political discussions play a particularly strong role in shaping attributions of blame, while partisan strength and political media exposure are relatively less influential. The data also indicate that who one talks to about politics matters for placing blame, as conversations with like-minded partisans lead to more blame placed on the out-party and less blame on the in-party, whereas political discussions with people who hold different views can temper out-party blame. Overall, findings suggest that political discussion may matter more than political media exposure for attributions of blame for partisan hostility.

69 The Holos model for estimating greenhouse gases and soil carbon: Characterizing regionalized beef farm model systems

Abstract The objective of this work is to characterize regionally representative beef farm systems that represent dominant or typical surveyed management practices for 11 beef-producing regions across Canada. This work fulfills two further purposes 1) to improve and expand the Holos model interface; and 2) to facilitate the estimation of greenhouse gas (GHG) emissions and soil carbon (C) changes on beef farms in different regions of Canada. Holos version 4 is the whole-farm model of Agriculture and Agri-Food Canada’s to estimate GHG emissions and changes in soil C on Canadian farms in response to shifts in management practices. Holos can be implemented in all 10 Canadian provinces and accounts for GHG emissions from crop and livestock production [enteric and manure methane (CH4), manure and soil N2O emissions], farm machines and infrastructure [on-farm energy carbon dioxide (CO2) emissions], as well as from the upstream production of some farm inputs (synthetic fertilizer and pesticides). The model is designed to utilize data readily available on the farm to answer, ‘What if?’ scenarios, whereby the user can test the effect of changing management practices on their whole-farm GHG budget. To reduce the data input burden on the user, Holos V4 has built-in model livestock systems for beef, dairy, swine and poultry production that characterize the dominant features of these operations in Canada at the national scale based on relevant literature/data and expert opinion. Regarding beef production, we have characterized regionally specific model beef farms for incorporation into Holos, one for each of 11 Canadian beef-producing regions. General characteristics and management practices for each farm were based on the 2011 Beef Farm Survey (Sheppard et al., 2015), which summarizes management information from 1,009 Canadian beef farms, combined with data from the Canadian Cow-Calf Cost of Production Network (Canfax 2023). Each regional farm includes cow-calf, backgrounding in confinement, backgrounding on pasture and finishing components, and considers all the specific feed (e.g., forage, grains, by-products) required for each stage of the beef cycle. These 11 model farms are simulated within the current Holos V4 model to explore the impacts of variation in beef management practices on farm GHG emissions across Canada and on soil C stocks on lands used to produce feed and graze cattle. An overview of the national-level dairy, swine and poultry components in Holos will be presented along with a more detailed perspective of whole-farm GHG budget and multi-decadal soil C dynamics in regionalized beef farms. The impact of management and environmental factors that lead to differences in GHG emissions and soil C stocks in beef farms will also be explored.

Deep Learning-Based Artificial Intelligence Can Differentiate Treatment-Resistant and Responsive Depression Cases with High Accuracy.

Background: Although there are many treatment options available for depression, a large portion of patients with depression are diagnosed with treatment-resistant depression (TRD), which is characterized by an inadequate response to antidepressant treatment. Identifying the TRD population is crucial in terms of saving time and resources in depression treatment. Recently several studies employed various methods on EEG datasets for automatic depression detection or treatment outcome prediction. However, no previous study has used the deep learning (DL) approach and EEG signals for detecting treatment resistance. Method: 77 patients with TRD, 43 patients with non-TRD, and 40 healthy controls were compared using GoogleNet convolutional neural network and DL on EEG data. Additionally, Class Activation Maps (CAMs) acquired from the TRD and non-TRD groups were used to obtain distinctive regions for classification. Results: GoogleNet classified the healthy controls and non-TRD group with 88.43%, the healthy controls and TRD subjects with 89.73%, and the TRD and non-TRD group with 90.05% accuracy. The external validation accuracy for the TRD-non-TRD classification was 73.33%. Finally, the CAM analysis revealed that the TRD group contained dominant features in class detection of deep learning architecture in almost all electrodes. Limitations: Our study is limited by the moderate sample size of clinical groups and the retrospective nature of the study. Conclusion: These findings suggest that EEG-based deep learning can be used to classify treatment resistance in depression and may in the future prove to be a useful tool in psychiatry practice to identify patients who need more vigorous intervention.

Dominant features of phasic evolutions in the winter Arctic-midlatitude linkage since 1979

Abstract Over the past decades, the Arctic-midlatitude linkage has been extensively explored. Recent studies have suggested that the characteristics of phasic evolutions in the relationship between the Arctic warming and midlatitudes remain elusive. Therefore, this study systematically investigates this issue by using running empirical orthogonal function (EOF) and moving correlation, and the results show a phasic alternation process in the relationship between the tropospheric thickness over the Barents-Kara Seas (BKS) and East Asian temperature, characterized by a phasic weak (P1: 1979-2000)–strong (P2: 2001-2011)–weak (P3: 2012-2021) connection. Our results highlight that since the winter of 2010, despite the Arctic sea ice being in an exceptionally reduced phase and continuous Arctic warming, the Arctic-midlatitude connection has not exhibited sustained strengthening relative to P2 phase. Moreover, it is found that changes of the connection between the BKS warming and the East Asian winter Monsoon may contribute to this phasic evolution, and the Arctic Oscillation (AO) plays an important role in modulating their phasic evolutions. The conclusions of this study help to deepen our understanding of the evolution of the strength and weakness of the relationship between Arctic warming and climate variations in midlatitudes.

Haemorrhagic cholecystitis: a case report—focus on the optimal diagnosis and management algorithm

Haemorrhagic cholecystitis refers to an inflammatory process of the gallbladder, complicated by bleeding into the gallbladder or biliary system (haemobilia). Approximately 10–15% of adults have cholelithiasis, but most patients do not develop symptoms. Acute cholecystitis occurs in about 10% of symptomatic patients. Among the recognized complications of acute cholecystitis, the haemorrhagic form occurs uncommonly. Underlying risk factors include a bleeding diathesis or treatment with anticoagulants, aneurysm rupture of colecystic artery and trauma. It is often associated with cholelithiasis. The presenting feature is right upper quadrant pain, which is a dominant feature and may mimic non-haemorrhagic acute cholecystitis. Haemorrhagic cholecystitis is diagnosed by radiographic imaging. The first-choice exam is ultrasonography. However, ultrasound does not appear to be ideal for differentiating between acute and haemorrhagic cholecystitis. Computed tomography (CT) scan is the gold standard in the diagnosis of haemorrhagic cholecystitis. MRI may show breakdown products of blood and can be used to estimate the age of the haemorrhage. Surgical resection or embolization of a cystic artery pseudoaneurysm should be considered the treatment of choice, due to the high risk of fatality associated with this condition. We describe a case of haemorrhagic cholecystitis in an 80-year-old male with secondary haemophilia and cholelithiasis who presented to our department of radiology with right upper quadrant pain.

Cell blebbing novel therapeutic possibilities to counter metastasis.

Cells constantly reshape there plasma membrane and cytoskeleton during physiological and pathological processes (Hagmann et al. in J Cell Biochem 73:488-499, 1999). Cell blebbing, the formation of bulges or protrusions on the cell membrane, is related to mechanical stress, changes in intracellular pressure, chemical signals, or genetic anomalies. These membrane bulges interfere with the force balance of actin filaments, microtubules, and intermediate filaments, the basic components of the cytoskeleton (Charras in J Microsc 231:466-478,2008). In the past, these blebs with circular structures were considered apoptotic markers (Blaser et al. in Dev Cell 11:613-627,2006). Cell blebbing activates phagocytes and promotes the rapid removal of intrinsic compartments. However, recent studies have revealed that blebbing is associated with dynamic cell reorganization and alters the movement of cells in-vivo and in-vitro (Charras and Paluch in Nat Rev Mol Cell Biol 9:730-736,2008). During tumor progression, blebbing promotes invasion of cancer cells into blood, and lymphatic vessels, facilitating tumor progression and metastasis (Weems et al. in Nature 615:517-525,2023). Blebbing is a dominant feature of tumor cells generally absent in normal cells. Restricting tumor blebbing reduces anoikis resistance (survival in suspension) (Weems et al. in Nature 615:517-525,2023). Hence, therapeutic intervention with targeting blebbing could be highly selective for proliferating pro-metastatic tumor cells, providing a novel therapeutic pathway for tumor metastasis with minimal side effects. Here, we review the association between cell blebbing and tumor cells, to uncover new research directions and strategies for metastatic cancer therapy. Finaly, we aim to identify the druggable targets of metastatic cancer in relation to cell blebbing.

­Soviet ‘Easterns/Osterns’ of the 1920s: Adventure Films on the Caucasian Frontier of Russia

The article elucidates the issue of representation in Soviet cinema of historical events that transpired during the formation of the Caucasian frontier and the interactions that emerged between the indigenous population and the tsarist troops. The term “Eastern” is analogous to the term “Western” which refers to films about the exploration of the Wild West. This is a useful way of conceptualizing Soviet silent films created on Caucasian material from the 19th–early 20th centuries. This article aims to examine feature films from the 1920s that depict Russia’s advance into the Caucasus. It seeks to identify similarities and differences between these films and the first Soviet “Easterns/Osterns” and “Westerns,” as well as to analyze the influence of ideological attitudes in historical science on the interpretation and depiction of events that took place on the Caucasian frontier. The visual sources utilized in this study include the silent films ‘Abrek Zaur’ (1926), ‘The Law of the Mountains’ (1927), and ‘Zelimkhan’ (1929). Additionally, published materials from the 1920s, including periodicals such as newspapers and magazines, were consulted. The study yielded insights into the stylistic similarities between classic Westerns and the first Soviet Easterns, including the portrayal of protagonists, the use of action and stunts, and the incorporation of jumps. The content of the films is correlated with real historical events, but they reflect the Bolshevik paradigm of history in the study of ethnosocial conflicts in the Caucasus. In films about highlanders, masculine culture is a dominant feature due to gender attitudes and the national cultural identity of the peoples of the Caucasus. Films about mountaineers were instrumental in shaping perceptions of the Caucasus during the early decades of the twentieth century. They illustrate the attributes of traditional culture, daily life, customs of mountain village inhabitants, the characteristics of the landscape, and architectural features. In general, films of an adventurous nature created on Caucasian material are of interest to those with an affinity for classic cinema, particularly the earliest Soviet Eastern films, as well as to researchers seeking to gain insight into significant historical and cultural information. This article is intended for those engaged in the study of the history of Soviet cinema.

Bruno Latour, Writer

This article focuses on Bruno Latour’s writing. Through a series of examples, it shows how he has always sought to match the form of his works to their content, in a quest for coherence uncommon in the social sciences. Beyond the diversity of his works, we can nevertheless identify one dominant feature: a very explicit concern for the reader, and the use of a variety of techniques to engage him or her in an experience that is as sensible as it is intellectual.

Integrated seismic, petrophysical, and geochemical studies for evaluating the petroleum system of the Upper Bahariya-Abu Roash G sequence in the Karama Field, Abu Gharadig Basin, North Western Desert, Egypt

The main aim of this study is to delineate the hydrocarbon potential and evaluate the petroleum system elements of the Cenomanian Abu Roash G (AR/G) and the Upper Bahariya Members in the Karama Field. It lies at the southeast borders of the Abu Gharadig Basin, a well-known basin in the W.D. to the NE of Africa. We accomplish this study by analyzing a total of thirty 2D seismic profiles, a complete data set of well logs for five wells, and their geochemical data. The workflow starts with illustrating the dominant subsurface structural features, defining the main potential reservoirs and their parameters, and checking the maturity of the probable source rocks. The seismic interpretation indicated that the research area had been influenced by a NE-SW anticlinal structure accompanied by a set of WNW-ESE and NW-SE normal faults that are controlled by the positive compression inversion process that dominated during the Late Cretaceous. Analyzing and processing the well log data sets suggest that the reservoirs of the Abu Roash G (AR/G) and the Upper Bahariya Members are characterized by poor to good reservoir settings with net-pay thickness reaching up to 13–50 feet in the different wells (av. Effective porosity (∅eff) = 17.7 % and 15.6% for the AR/G and the Upper Bahariya Members, av. Shale volume (Vsh) = 17.4 % and 13.6 %, av. Water saturation (Sw) = 38.9 % and 39.8 %, while av. Hydrocarbon saturation values (So) = 60.2 % and 61.1%, respectively). The geochemical and maturity analyses assisted in determining the potential mature source rocks of the Jurassic Khatatba Shale (TOC = 0.70–5.67%; S1+S2 = 0.43–5.97 mg/g, Ro = 0.54–1.06 %) with some contribution from the Cretaceous sources (Alam El-Bueib and Bahariya Formations). Studying elements of the petroleum regime of the Karama Field indicates that the trapped hydrocarbons are structurally controlled by three-way dip closures, horst blocks, sealing faults, and vertical sealing by impervious shale and limestone beds. This case study could be applied to similar analogs in other oil fields in the Egyptian Western Desert to delineate their hydrocarbon potential and structural setting.