bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a Green Field Reservoir in the Niger Delta: The Journey and Success Story
Authors: Okpani O. O. , Akinwande M. , Atuanya C. , Adegoke O. , Aina T. , Igiri T. , Nnachetta E. 
Published: August 2024

Abstract
The paper shows the journey and key lessons learned in the successful development of a green field reservoir that initially had significant subsurface uncertainties. Acquisition, interpretation, and integration of key subsurface data was critical to the reduction of subsurface uncertainties, and successful development of the reservoir.
Reservoir J8-02 was discovered in 1991 as saturated reservoir by Well-I which proved an oil column of 42 ft with an LKO. A pilot well (Well-P), drilled in 2019 to determine the reservoir extent and hydrocarbon column, logged a GOC and an OWC; and proved up an additional 147 ft column of oil. The fluid contacts established from well log data were validated by repeat formation pressure tests acquired using Well-P.
Based on the results from Well-P, a horizontal well (Well-PH) was planned to be completed in the reservoir with the lateral depth at 30 ft below the GOC. Due to issues experienced with MWD, the well was completed in the reservoir with the toe being about 15 ft offset from the GOC. When Well-PH was brought online in 2019, it produced at low oil rate, very high GOR and with light oil API of 42. Evaluation of Well-PH production performance and the open hole log suggested that Well-PH was producing from a fluid transition zone (high GOR/high oil API) between the gas cap and the oil leg. A new well (Well-YH) was then planned to target the oil leg below the fluid transition zone in the eastern part of the reservoir.
A depth uncertainty assessment was done and incorporated into the planned well landing depth. However, due to possible gas sag effect on the seismic, the structure was encountered shallower than the pre-drill uncertainty range; this resulted in the new drill (Well-YH) being sub-optimally landed in the transition zone and within the low-quality section of the reservoir lobe. The transition zone was confirmed in Well-YH by real-time gas chromatograph analysis from mud logging. The decision was made to geologically sidetrack Well-YH.
The sidetrack (Well-YHST) was successfully drilled into the good quality interval with the toe of the lateral at 34 ft below the transition zone. Geo-steering (Resistivity contrast-based depth to boundary tool) and mudlogging proved to be key enablers towards the successful landing of the well. Well-YHST was brought online and is currently producing at very good rate (2100 bopd compared to 1250 bopd pre-drill estimate), low GOR and oil API of 36 degrees. Based on this positive outcome, an additional well is being planned to be drilled to further improve oil recovery in the reservoir.
Well Test Design & Acquisition Strategies: Proactively Assuring Data Usability by Optimizing Design and Data Acquisition
Authors: Nwabulue Nnamdi , Lazson Nchekwube , Akpara Kingsley , Ikhuehi Martins , Kalu Chuks 
Published: August 2024

Abstract
Well testing is a key part of reservoir and well surveillance exercises as it helps us understand the changes in production & injection wells since the previous survey such as damage skin, flow efficiency, drainage area, productivity index and fluid distribution in the wellbore. Well testing has proved to be invaluable not just with reservoir information but also a tool for validating the completion efficiency as well as additional development. The results from the analysis of the acquired well test data will be used to determine stimulation candidates, needs for gaslift design/optimization and checking of downhole jewelry integrity.
In recent times, we have struggled to acquire good data making the interpretation process difficult with some of the extracted results not in conformance with geology while others are just outright unphysical. Most of the cases of bad test results could be traced to deviation from BHP design, operational challenges, leaking valves and partly closure of downhole sleeves.
This paper presents the challenges from our BHP (Bottom Hole Pressure) acquisition campaigns, impact on interpretation and remedial actions taken to improve the quality of the acquired data. The learnings from this will assist other engineers to streamline their interpretations and proactively managing well test operation through well test design, understanding the multiphase production complexity, importance of proper vendor selection/equipment calibration, operation supervision and proper operation documentation.
Maximizing Value in Mature Assets Through Integrated Gas Management
Authors: Adetula O. B. , Okonkwo G. C. , Idih R. , Ataga J. F. 
Published: August 2024

Abstract
Gas management in mature producing oil and gas fields within an integrated facility network poses numerous challenges due to complex facility interdependencies and constraints. A review of the short-term gas demand and supply projections within a key gas gathering hub highlights a significant gas supply shortage for injection, hindering realization of the full oil value potential through gas injection.
This paper presents the development of an integrated strategy to optimize the utilization of associated gas supply within existing facility constraints, aimed at maximizing overall value. A multidisciplinary approach, including holding workshops to review field performance, analyze gas injection requirements, and identify opportunities to manage supply gaps, was adopted. A framework was established to prioritize gas injection based on Additional Oil Recovery (AOR), departing from the conventional allocation method that prioritizes gas distribution solely based on the contributions of each field to the gas gathering hub. The approach ensures gas distribution is optimized to maximize incremental oil production derived from gas injection.
Proposed strategies to mitigate near-term supply short falls include prioritization, external gas sourcing, gas cap blowdown and utilization of high GOR wells. Collaborative efforts have resulted in improved near-term injection benefits despite limited gas supply, with recent reservoir pressure trends indicating reservoirs are positioned to deliver expected mid- and long-term value. The Reservoir Engineer played a pivotal role as a central interface and coordinator in achieving effective gas management.
Development and Validation of a Deep-Learning Model for Differential Treatment Benefit Prediction for Adults with Major Depressive Disorder Deployed in the Artificial Intelligence in Depression – Medication Enhancement (AID-ME) Study
Authors: Benrimoh David , Armstrong Caitrin , Mehltretter Joseph , Fratila Robert , Perlman Kelly , Israel Sonia , Kapelner Adam , Parikh Sagar , Karp Jordan , Heller Katherine , Turecki Gustavo 
Published: August 2024

Abstract

We introduce an artificial intelligence (AI) model aiming to personalize treatment in adult major depression, which was deployed in the Artificial Intelligence in Depression: Medication Enhancement (AID-ME) Study. Our objectives were to predict probabilities of remission across multiple pharmacological treatments, validate model predictions, and examine them for biases. Data from 9,042 adults with moderate to severe major depression from antidepressant clinical trials were standardized into a common framework and feature selection retained 25 clinical and demographic variables. Using Bayesian optimization, a deep learning model was trained on the training set and refined using the validation set. On the held-out test set, the model demonstrated an AUC of 0.65 and outperformed a null model (p = 0.01). The model demonstrated clinical utility, achieving an absolute improvement in population remission rate in hypothetical and actual improvement testing. While the model identified escitalopram as generally outperforming other drugs (consistent with the input data), there was otherwise significant variation in drug rankings. The model did not amplify potentially harmful biases. We demonstrate the first model capable of predicting outcomes for 10 treatments, intended to be used at or near the start of treatment to personalize treatment; AID-ME cluster randomized trial results are reported separately.
Single-Cell Transcriptomic Analysis of Specific Responses of Different Cell Populations of Hemocytes to the Re-infection of Bacteria, a Case Study in Abalone
Authors: Zhang Ziping , Zhang Xin , Sun Yulong , Feng Jianjun , Wang Yilei 
Published: August 2024

Abstract

It is commonly believed that invertebrates lack immune memory due to the absence of immunoglobulins, related molecules, cells, and organs. However, our previous research demonstrated that Haliotis discus hannai, a prominent abalone species cultivated in China, often faces substantial economic losses due to diseases, particularly those caused by Vibrio sp. exhibited higher survival rates upon re-infection with Vibrio parahaemolyticus compared to the initial infection, implying the existence of immune memory. We hypothesized that hemocytes, which play a critical role in pathogen resistance in abalone, might be involved in the immune memory process. Therefore, we aimed to investigate the hemocyte response mechanism to V. parahaemolyticus re-infection to provide valuable insights for preventing and controlling abalone vibriosis and advancing sustainable abalone aquaculture. Additionally, our research aimed to contribute to understanding the origin and evolution of immune memory mechanisms. This study constructed a transcriptome map of abalone hemocytes using 10× Genomics single-cell RNA sequencing (scRNA-seq). Traditionally, abalone hemocytes were categorized into three cell types: hyalinocytes, semi-granulocytes, and granulocytes. The initial cell division resulted in the formation of 15 clusters further through subsequent analysis using scRNA-seq. Among these clusters, cluster_11 exhibited unique characteristics, indicating a more mature cluster of GRCs. This specific subpopulation displayed significant functionality as a core immune regulator, manifesting robust phagocytic and endocytic activities and substantial involvement in signal transduction and immune regulatory processes. Furthermore, we analyzed and detailed functional variances among different hemocyte types. Through the implementation of RNA interference technology, we validated the interplay between key signaling pathways. Interestingly, our findings suggested the potential existence of a classical TLR/NF-κB signaling pathway in abalone hemocytes, which may contribute to the immune regulation process in response to V. parahaemolyticus re-infection, as preliminarily confirmed in our study.
Combination antiretroviral therapy prevents SIV-induced aging in the hippocampus and neurodegeneration throughout the brain
Authors: MacLean Andrew , Horn Miranda , Midkiff Cecily , Zandt Alison Van , Saied Ahmad 
Published: August 2024

Abstract

Virus-induced accelerated aging has been proposed as a potential mechanism underlying the persistence of HIV-associated neurocognitive disorders (HAND) despite advances in access and adherence to combination antiretroviral therapies (cART). While some studies have demonstrated evidence of accelerated aging in PLWH, studies examining acute infection, and cART intervention are limited, with most studies being in vitro or utilizing small animal models. Here, we utilized FFPE tissues from Simian immunodeficiency virus (SIV) infected rhesus macaques to assess the levels of two proteins commonly associated with aging - the cellular senescence marker p16INK4a (p16) and the NAD-dependent deacetylase sirtuin 1 (SIRT1). Our central hypothesis was that SIV infection induces accelerated aging phenotypes in the brain characterized by increased expression of p16 and altered expression of SIRT1 that correlate with increased neurodegeneration, and that cART inhibits this process. We found that SIV infection induced increased GFAP, p16, SIRT1, and neurodegeneration in multiple brain regions, and treatment with cART reduced GFAP expression in SIV-infected animals and thus likely decreases inflammation in the brain. Importantly, cART reversed SIV-induced accelerated aging (p16 and SIRT1) and neurodegeneration in the frontal lobe and hippocampus. Combined, these data suggest that cART is both safe and effective in reducing neuroinflammation and age-associated alterations in astrocytes that contribute to neurodegeneration, providing possible therapeutic targets in the treatment of HAND.
Cross-cultural adaptation and psychometric evaluation of the Chinese version of the Sickness Presenteeism Scale- Nurses:A cross-sectional study
Authors: Li Chuang , Meng Zhixing , Lin Youbei , Zhang Lan 
Published: August 2024

Abstract

Background There is a lack of an evaluation instrument to gauge how presenteeism practices affect nurses' productivity at work and the quality of the medical treatment they provide. The purpose of this study was to translate the Sickness Presenteeism Scale-Nurse (SPS-N) into the Chinese version of the SPS-N and to verify its reliability and validity in Chinese nurses.Methods The SPS-N was translated according to the Brislin translation model after authorization by the original author. A convenience sampling method was used and the reliability and validity of the scale were tested among 503 Chinese nurses.Results The Cronbach's ɑ of the Chinese SPS-N was 0.924, and the content validity of the items ranged from 0.830 to 1.000. The four-factor exploratory factor model was used to explain 78.354% of the total variance. CMIN/DF = 2.527, RMSEA = 0.067, AGFI = 0.857, TLI = 0.941, IFI = 0.950 ,CFI = 0.949, GFI = 0.900, and PGFI = 0.692 were the model fit outcomes in the validation factor analysis. All of the model fit markers fell within reasonable bounds.Conclusion The reliability and validity of the Chinese version of the SPS-N can be used to evaluate the influence of nurses' presenteeism behavior on job performance. To inform nursing managers in developing programs and interventions to improve the performance of clinical nurses.
Drying Kinetics of Microalgae Chlorella vulgaris: A Thermogravimetric and Differential Scanning Calorimetry Study
Authors: Karmakar Debabrata , Tasnim Nishat , Hasan Md. Rakibul , Arefin Paroma , Bhowmik Dip , Nibir Yead Morshed , Kabir Kazi Bayezid , Karim Rezaul 
Published: August 2024

Abstract

Microalgae are a diverse group of eukaryotic organisms that thrive in various habitats and have significant potential as alternatives to fossil fuels and sources of valuable chemicals like PUFAs, carotenoids, and antioxidants. Despite their efficiency in biomass production, utilizing microalgae effectively poses challenges. Microalgae grow in aqueous media and must be dried before being used for biofuel production, chemical extraction, or nutraceutical products. While extensive research exists on microalgae's benefits and uses, few studies focus on drying methods. This study examines the drying kinetics of Chlorella vulgaris. Drying behavior data was obtained using Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC). Results showed that biomass moisture content decreased rapidly with increasing temperature, peaking at 65–80°C. Four non-isothermal drying models were developed using popular drying kinetics models for agricultural products and evaluated based on the coefficient of determination (R²) and reduced chi-square (χ²). Page’s model emerged as the best fit for describing the drying kinetics of Chlorella vulgaris.
Enhancing Spiking Rate Control in Brain-Computer Interfaces through Functional Connectivity-Based Grouping
Authors: Li Runda 
Published: August 2024

Abstract

Background: Brain-Computer Interfaces (BCIs) have transformed neuroscience and bioengineering by enabling direct communication between the brain and external devices. Effective neural signal decoding is crucial for BCI performance, yet it is often hindered by noise and instability in neuronal firing rates and patterns.
New Method: This essay introduces an innovative approach to enhancing spiking rate control in BCIs through functional connectivity-based grouping. Functional connectivity refers to the statistical relationships between neural activities. The proposed methodology involves pre-recording analysis using techniques such as pairwise cross-correlation, Granger causality, and coherence to analyze functional connectivity. Neurons are then grouped into ''functional groups'' or ''microcircuits'' based on their connectivity profiles. This grouping is leveraged through adaptive filtering and dimensionality reduction to improve BCI performance.
Results: The experimental results demonstrate that the functional connectivity-based grouping approach significantly enhances BCI performance. Benefits include noise reduction, increased stability, and improved neural signal decoding.
Comparison with Existing Methods: Compared to existing methods, the proposed approach offers superior noise reduction and stability, leading to more accurate and reliable BCI performance.
Conclusions: Our research highlights the potential of functional connectivity-based grouping in enhancing BCI performance. The findings underscore the importance of pilot testing, optimized decoding, and real-time adjustment, offering a promising avenue for future BCI development.
Inter-species SNPs from buffalo liver transcriptome indicate diversity in immune pathways between buffalo and cattle
Authors: Venkata Chaitanya Kumar Thota , Singh Sudhakar , Vedamurthy Gowdar Veerapa , Singh Dheer , Onteru Suneel Kumar 
Published: August 2024

Abstract

Graphical abstract
Abstract:
The duration of negative energy balance (NEB), a physiological adaptation in females during early postpartum, and its coping mechanisms vary among animals, breeds and species because of genetic differences. However, genetic variations that may influence the NEB differences between cattle and buffaloes were not reported. Therefore, the present study aims to identify such genetic differences between cattle and buffaloes by identifying inter-species single nucleotide polymorphisms (SNPs) by mapping the available liver RNA-seq data earlier obtained from three early postpartum buffaloes and three heifers to the cattle genome (UMD 3.1) using the SNP eff tool. The liver transcriptome data were chosen, as it is the major metabolic organ in balancing metabolic milieu to meet different physiological demands during early postpartum. Using the identified interspecies SNPs, intragenus SNPs (Buffalo) were derived from six different Murrah buffaloes and mapped them to the Bubalus bubalis (ASM312139v1) genome. Further, functional annotation and biological pathway analyses were performed for those genes harbouring the putative SNPs. We identified a total of 1,40,056 interspecies and 188 intragenus SNPs. Functional annotation and pathway analyses revealed that most of the putative interspecies SNPs between the cattle (Bos taurus UMD 3.1) and buffalo (Bubalis bubalus) were in the protein metabolism genes (>1900) predominantly involved in the immune system (>1800 genes). Similarly, most of the putative intragenus SNPs among buffaloes were in the genes of lipid metabolic pathways. In conclusion, our study suggests that cattle and buffaloes might differ in protein metabolism genes involved in immunity at the deoxyribonucleic acid (DNA) level.
Development of bioactive quinoa protein hydrolysate-based emulsion gels: Evaluation of their antioxidant and rheological properties
Authors: Lingiardi Nadia , Galante Micaela , Spelzini Darío 
Published: August 2024

Abstract

This work aimed to develop oil-in-water emulsion gels based on quinoa protein or quinoa protein hydrolysates, alginate, and high-oleic sunflower oil and to characterize their potential as functional food ingredients with antioxidant capacity. Quinoa protein concentrate (QPC) was hydrolyzed with alcalase. The resulting quinoa protein hydrolysates (QPH) (DH: 30 ± 4%) were evaluated for their iron-chelating activity and reducing power. The antioxidant capacity of the QPC or QPH-based emulsion gels was determined using the ABTS and DPPH methods, and they were also subjected to rheological analysis. The QPH exhibited higher ability to chelate ferrous ions and higher reducing power compared to QPC (p = 0.004; p < 0.000, respectively). The ABTS and DPPH free radical scavenging activity of QPH-based emulsion gels was higher than that obtained from QPC-based emulsion gels (p = 0.001; p = 0.001). Furthermore, QPH proved to be more effective in depressing lipid oxidation than QPC. After 30 days of storage, QPH-based emulsion gels showed lower levels of malondialdehyde compared to those obtained from QPC-based emulsion gels (p < 0.000). The rheological behavior of the emulsion gels revealed that the storage modulus (Gʹ) was greater than the loss modulus (Gʺ) throughout the entire frequency range, thus deformation in the linear region was mainly elastic. The strain recovery occurred because of the good viscoelastic properties of the samples. Although the strengthening of QPH-based emulsion gels was lesser than that of those with QPC, the gel structure remained stable through the entire temperature range.
Enhancing Weakly Supervised Semantic Segmentation through Multi-Class Token Attention Learning
Authors: Luo Huilan , Zeng Zhen 
Published: August 2024

Abstract

Weakly supervised semantic segmentation (WSSS) using image-level class labels is challenging due to the limitations of Class Activation Maps (CAMs) in convolutional neural networks (CNNs), which often highlight only the most discriminative image regions. We propose the Hierarchical Multi-Class Token Attention Network (HMCTANet), a novel approach leveraging a Conformer backbone that integrates CNN and Transformer branches. HMCTANet enhances CAMs through multi-class token attention and a Class-Aware Training (CAT) strategy that aligns class tokens with ground-truth labels. Additionally, we introduce a Class Token Regularization Module (CTRM) to improve the discriminative power of class tokens. Our Refinement Module (RM) further refines segmentation by combining class-specific attention and patch-level affinity from the Transformer branch with the CAMs from the CNN branch. HMCTANet achieves state-of-the-art performance, with mIoU scores of 69.0% and 68.4% on the PASCAL VOC 2012 validation and test sets, respectively, demonstrating the effectiveness of our approach for WSSS tasks.