bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing Field Performance with Flow Control Technologies: A Case Study of Reducing Carbon Intensity in Oil Production in the Sultanate of Oman
Authors: Harthi M. , Moradi M. , Lawati A. , AlJumah A.
Published: April 2024

Reduction of carbon emissions has become a global objective driving both government and private sectors to develop and mature technologies that fit this purpose. This paper will evaluate how deploying rate-controlled production (RCP) Autonomous Inflow Control Devices (AICDs) in a field, with hundreds of wells completed with AICD completion, reduced carbon emissions during prolonged periods of production. The study introduces a workflow that uses a publicly available Greenhouse Gas (GHG) estimator for different field development plans.

The production data of 28 wells from a reservoir in the Sultanate of Oman were analyzed. The RCP AICD is a self-regulated based on the properties of the fluid passing through, which optimises oil production while reducing the production of unwanted fluids. To ensure an accurate comparison, the data underwent extensive pre-processing, and some modelling was conducted. The collected data, including fluid properties, formation characteristics, and operational processes were all used to feed the estimator, which then run for various scenarios with and without AICD cases to predict the energy consumption and greenhouse gas emissions associated with each operation and treatment involved in the field development.

By calculating these emissions, operators can identify the major sources of emissions and energy consumption and optimize their processes to reach net-zero. The results show that the use of AICDs completion in the wells has resulted in reduced capex and opex including drilling a reduced number of wells (both producers and injectors), less requirement of energy extensive production, surface processes and re-injection of unwanted fluids to achieve the target production rate for the field.

The study's findings revealed that AICDs have significant effects on improving oil production by 217% while reducing total water production by 52%, as well as on the environment. For instance, the use of AICD completions in the field was estimated to reduce carbon intensity, greenhouse gas emissions, and energy consumption by up to 51%, 47%, and 110%, respectively; compared to stand-alone screen (SAS) is installed in the other wells. Also, the finding shows that production operation was a major contributor to GHG emission and energy consumption for non AICD completion scenarios compared to any other operation or process involved in oil production.

This study provides a comprehensive workflow to quantify the impacts of the use of new technologies, especially flow control devices on the reduction of carbon emissions. It also illustrates the significant role of flow control technologies toward net zero targets by achieving less carbon intense oil production.
A Dynamic Reservoir Modelling of Carbon Dioxide Storage in Depleted Dry Gas Reservoir in Northern Oman: A Case Study
Authors: Al Ajmi A. , Ivanov D. , Kazemi A. , Al-Maamari R. , Bogachev K.
Published: April 2024

The objective of this study is to evaluate CO2 storage potential of a small gas field located in Northern Oman using advanced reservoir simulation techniques. The field is to be used for CO2 storage in the future when this reservoir is depleted. The study includes the estimation of structural, residual, solubility and mineral trapping mechanisms, as well as determination of safe operating pressure limits for CO2 injection.

The study utilizes various reservoir simulation methods to investigate each trapping mechanism, taking into account the hydrodynamic, physical, and chemical conditions within the reservoir. Specifically, solubility trapping is analyzed using Henry's law, while residual trapping is modeled using the critical gas saturation via Corey correlations. To analyze risks of faults reactivation and leakage into overlying formations, the geomechanical analysis was applied in the study. At the end of the study, a sensitivity analysis is performed to assess the influence of uncertain parameters for each technical approach.

The results of the case study provided both quantitative and qualitative evaluations of each trapping mechanism for the gas field. Potential deformation and fracturing of the caprock trap were predicted to ensure it remains intact to prevent CO2 leakage. Additionally, the study demonstrated the practical application of various reservoir simulation techniques for modelling CO2 storage, adding further value to the study. In spite of the fact, that the gas field has been well studied during exploration and production periods, including previous reservoir simulations, a sufficient level of uncertainty still exists in reservoir description, fluid and rock properties and even was increased with adding CO2 storage approaches. This study took into account these uncertain parameters, and probabilities were calculated for the estimations of trapping mechanisms.

This case study presents a complete modelling cycle for CO2 storage within a depleted gas reservoir, employing a range of diverse reservoir simulation techniques. It serves as a valuable guide for those interested in modelling CO2 storage through the application of various reservoir simulation methods.
Strengthening Well Abandonment Process Through Well Retirement AI Digital Advisor
Authors: Reddicharla N. , Alshehhi S. , Cristea Z. , Ali Sultan Ali M. , Gonczi D. , Toumi O.
Published: April 2024

The Operator manages a diversified and dynamic portfolio with thousands of wells. As the production methods evolve from naturally flowing to improved and enhanced oil recovery methods, artificial lift, unconventional and sour hydrocarbon reservoirs, the wells stock is continuously exposed to a changing spectrum of operational conditions that will eventually have an impact on the expected wells’ life span. The safe retirement of wells at the end of lifecycle through proper Plugging & Abandonment (P&A) operations, along with drilling and commissioning of replacement wells, has a significant cost impact in the long term. From this perspective, the Operator implemented its one-of-a-kind, innovative well retirement digital advisory solution to forecast candidate wells for P&A based on advanced data analytics and automation.

It is crucial to build a well-established workflow to simplify the well abandonment process to assure that no more value can be generated, or integrity cannot be restored. The well abandonment definition is related to remnant life, integrity, cost, and priority. The important components are reservoir health and well integrity. Digital advisor integrates reservoir simulation forecasts with the lifespan of wells based on production/injection, long-term profile and economic value. The system automates the ranking of well integrity candidates which are not fully in compliance with integrity management standards. Risk assessment is embedded in the advisor by defining the business impact of the wells. Data is automatically captured by predefined schedules from instrumentation and flat files, and operational data storage under relational database management systems.

This well retirement advisor provides a deterministic retirement candidates list, assuming each well's lifetime of 25 years from well spud date. It enables fast identification of P&A candidate wells based on reservoir health considerations. The time optimized list is updated with well integrity data statistics and forecasts. The approach has been tested in a mature oil field that has more than 800 wells and successfully identified the prioritized list of well retirement candidates. It provided a solid and consistent basis for the long-term projections of P&A candidate wells.

This advisory system helps to meet production targets through on-time replacement wells. This application has the potential to reduce OPEX cost through reduction of suspended well in the asset. It helps to proactively prepare for the well abandonment phase. Data availability and quality is critical for the successful implementation of applications such as the Well Retirement Advisor.
A Case-Study on Dynamic Quantum PLT Method Applied for Separate Accounting of Produced Fluids in Case of Commingled Production
Authors: Titovsky Nikita , Vasechkin Dmitry , Saprykina Kseniya , Upadhye Vishwajit
Published: April 2024

An oilfield operator has a requirement and therefore faces a challenge of separate production monitoring and accounting of production fluids for each reservoir, in the field case of dual completion and commingled production from different reservoirs. The existing assessment and tool-assisted methods offer only a partial solution to this problem. This article discusses the use of quantum PLT technology in directional wells by installing downhole a bottom-hole dual completion assembly equipped with quantum marker inserts for separate monitoring of production from different reservoirs.

To enable separate production accounting with the use of the dynamic quantum PLT method, a straddle packer system with quantum marker inserts carrying unique inflow indicators for each production interval is installed in the cased wellbore. When contacting hydrocarbons and water, markers are released from the composite material into the fluid. In the course of the steady-state well production, wellhead fluid samples are taken sequentially. The completion assembly provides for separate accounting for each production formation without the need for well shutdown and withdrawal of pumping equipment. The samples are analysed in the laboratory using the flow cytometry method to quantify the production distribution across the well zones.
Machine Learning Techniques for Inorganic Scale Precipitation Prediction: A Real Field Data from a Carbonate Reservoir
Authors: Harrasi Mohammed Talib Said Al , Kazemi Alireza , Al-Hmouz Rami , Abdulsalaam Abdulrahman Aal , Hajri Rashid Al
Published: April 2024

The precipitation of inorganic scales in the oil and gas industry has been identified as a major issue for flow assurance and the optimization of oil and gas fields due to the damage that these precipitations can cause in reservoirs, well completions, and surface facilities. On the other hand, predicting these precipitations has always been challenging for engineers of petroleum, production, and production facilities. Although many commercial computer programs in the industry can predict inorganic scale precipitations with some accuracy, the majority have many limitations that can negatively impact prediction performance.

Machine learning (ML) has received substantial attention in the oil and gas industry in recent years. The purpose of this study is to investigate the use of machine learning algorithms as a new approach to predicting inorganic scale precipitations in oil and gas carbonate formations.

The methodology of the current study consists of gathering input and output data, such as pressure, temperature, artificial lifting type, target formation, water ionic composition, pH, TDS, and whether or not each well tends to precipitate the inorganic scale. The algorithms chosen for prediction are Naive Bayes (NA), Neural Network classifier (NN), Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), and K- Nearest Neighbors (KNN), and they will be evaluated based on accuracy and other classification performance metrics.

The results of the models show that SVM, DT, and KNN are the best classifiers in terms of prediction accuracy scores with around 83%. Furthermore, a decision tree chart was created based on the Decision Tree (DT) model and can be used to examine the scale precipitation tendency for any future water sample. The chart is validated using real well cases from the same field, demonstrating a match between the predicted class (the well possesses or does not possess a high potential to precipitate inorganic scale) and the data collected in the well's interventions history reports. Based on the DT model, the artificial lifting method, target formation, pressure at the pump depth, and SO42-, HCO3- ionic compositions are found to be the strongest features that play a significant role in the scale precipitations in the studied field.

Implementing the proposed model will lead to many benefits, including properly employed well intervention resources, reduced oil deferment due to pump failures caused by scale precipitation, and reduced budget overspending entailed by unexpected failures in pumps, valves, or even surface facilities.
Tapping Moveable Oil Rim in Challenging Matured Oil Field Through the Synergy Geosteering Approach
Authors: Sultanov N. , Hendrawati M. S. , Hardiani R. , Buniamin N. , Abdullah N. A. , Alang K. A. , Wang H.
Published: April 2024

ABC field is located in offshore Peninsula Malaysia where recently a redevelopment project was undertaken to target the unswept oil via drilling horizontal wells. Offset well’s performance suggested highly dynamic fluid contact movement with reservoir sweep being non-uniform. Fluid types were expected to have low resistivity low contrast and vertical depth uncertainty of structure adding the complexity in landing and horizontal section drilling. A multi-disciplinary approach with synergy geosteering was vital to optimize horizontal well placement. A workflow was developed which synergized subsurface and drilling scope to mitigate risks associated with the uncertainties.

Geosteering pre-job model was built with multiple offset wells’ properties and range of expected fluid contacts. Post pilot hole drilling the model was updated by incorporating the actual fluid contacts and structure for an optimum drilling strategy. The structure uncertainty was further reduced with the advantage of deterministic inversion of high-definition reservoir mapping technology while drilling. Due to observed non-uniform fluid contacts away from the landing point, real-time inversion in combination with open hole logs was used in horizontal section to maintain desired stand off from both oil and gas. The high-definition reservoir scale mapping with deterministic inversion method was utilized to identify low resistivity low contrast boundaries of oil from transition zone which was challenging to be achieved by a conventional geosteering tool. The top of reservoirs mapped by geosteering were incorporated with the seismic amplitude analysis to assist in real time decision making. It was essential to ensure smooth landing point for good borehole tortuosity since the landing and horizontal section were drilled in one section. The tool clearly revealed the transition zone and Oil Water Contact (OWC) at 10-20m TVD below the bit with higher confidence compared to standard tool in horizontal section. In the lateral section, OWC and dip angle were mapped concurrently which allowed the team to achieve the required production length while maintaining standoff from the swept zone.

The success of integrated subsurface workflow with synergy of geosteering proven as the ultimate solution to overcome the challenges of horizontal well placement in this field. All wells with geosteering accomplished landing at an optimum depth and planned horizontal length despite tight True Vertical Depth (TVD) window. Ultimately, wells completed and unloaded, delivering higher than the expected rates with close to zero water cut (WC).
Novel Application of Citric Acid Based Natural Deep Eutectic Solvent in Drilling Fluids for Shale Swelling Prevention
Authors: Rasool M. H. , Ahmad M. , Zamir A. , Amjad B.
Published: April 2024

Shale swelling in clastic reservoirs presents a significant challenge, leading to instability issues in wellbores. Using water-based drilling mud with specific shale inhibitors is better for the environment compared to using oil-based mud. Although there's been interest in using ionic liquids (ILs) as shale inhibitors due to their customizable nature and strong electrostatic properties, however, research reveals that widely used imidazolium based ILs in drilling muds are toxic, non-biodegradable, and are expensive. Deep Eutectic Solvents (DES), often seen as a more economical and less toxic IL alternative, still lack true environmental sustainability. The latest development in this area is Natural Deep Eutectic Solvents (NADES), known for their genuine eco-friendliness. This study uses NADES formulated with citric acid (Hydrogen Bond Acceptor) and glycerine (Hydrogen Bond Donor) as a drilling fluid additive, prepared according to API 13B-1 standards and compares its efficacy with KCl, imidazolium based ionic liquid and Choline Chloride:Urea based DES. The research assesses various mud properties, revealing that NADES improve the yield point to plastic viscosity ratio (YP/PV), reduce mudcake thickness by 26%, and decrease filtrate volume by 30.1% at a 3% concentration. Remarkably, NADES achieve an impressive 49.14% inhibition of swelling, attributed to their ability to modify surface activity, zeta potential, and clay layer spacing. NADES emerge as non-toxic, cost-effective, and highly efficient shale inhibitors, offering a promising alternative to ILs and DES for environmentally conscious drilling operations.
Assessment of the Feasibility of CO2 Storage in Carbonate Saline Aquifers and Structural Traps in North Oman
Authors: Borner N. D. , Aljiroudi F. , Bosch J. , Madaschi A. , Gavnholt J. , Dhahli A. , Al Baloshi S. , Sarfare M. , Bos R. , Al Bulushi N.
Published: April 2024

Petroleum Development Oman (PDO) has set a target to reduce CO2 emissions to net zero by 2050, which is aligned with Oman’s country vision. A mid- and long-term strategy has been developed to identify cost-competitive abatement staircases, including elimination of routine flaring, driving energy efficiency across operating assets and increasing the share of power generation from renewable power sources (solar and wind). Although these activities will lead to a step-change reduction in CO2 emission levels, Carbon Capture, Utilisation and Storage (CCUS) will be a key enabler of PDO’s net zero targets.

The extensive Mesozoic carbonate rock sequences of North Oman provide an exciting opportunity for CO2 storage in both dipping saline aquifers and structural traps. While hydrocarbons are produced from these carbonates in numerous fields in the country, they also have enormous potential for carbon storage with multiple reservoir-seal pairs, particularly in the Shuaiba, Kharaib, Lekhwair and Habshan Formations of the Kahmah Group. Unlike the majority of CCS projects globally which utilise clastic saline aquifers and depleted fields, carbonates present an additional challenge due to the pervasive nature of faults and fractures which can exert a large influence on both injectivity potential and containment of the CO2 plume.
Gas Blockage Near Wellbore: A Diagnostic Tool for identifying Critical Flow in Oil and Gas Reservoirs
Authors: Herrera C. G. , Marhoon H. S. , Bo Khamseen S. H. , Sadah M. D.
Published: April 2024

Predicting critical gas rate when a well stops producing due unstable flow demands good understanding of fluid flow behavior in both reservoir and wellbore. Turner equation is well-recognized in the oil and gas industry to estimate critical gas velocity in the wellbore. This paper proposes the use of a basic diagnostic plot derived from Darcy flow equation to predict unstable flow as a phenomenon happening not only in the wellbore, but also in the reservoir due to gas blockage caused by an increase in liquid saturation near wellbore. It will be demonstrated that critical rate in the reservoir is linked to the relative permeabilities. This diagnostic can be used without knowing the relative permeabilities, as it clearly shows maximum limits of Water Gas Ratio (WGR) where the well experience unstable flow.

This proposed approach is a powerful diagnostic tool supported by well-known fluid mechanic equations with excellent track record in gas condensate and volatile oil fields developed under blowdown or gas injection with normal/over-pressure regimes. The objective of this approach is to aid production and reservoir engineers on decision-making process for gas injection strategies, tubing completion changes, artificial lift methods, compression projects, mechanical/chemical stimulations, healthy choke management strategy and well re-activation screening. By combining decline curve analysis or reservoir simulation with the proposed diagnostic plot, it is possible to predict when the well will reach critical flow conditions and proactively assess potential impact on reserves/production. Reservoir simulators have wellbore flow constraint options that can be related to the critical rate in the wellbore, but a constraint at reservoir level is still required to be included. This constraint can easily be implemented by setting a maximum WGR based on the correlation to avoid over estimation of hydrocarbons production forecast.

The simplicity of the proposed diagnostic plot aids engineers to identify and rank wells that need immediate or future interventions. Furthermore, this paper demonstrates that the diagnostic model can be easily calibrated with a single separator test close to its critical flow conditions. Future research could include additional reservoir parameters sensitivities such as skin, permeability, relative permeability, hysteresis, fluid types and finally incorporate this constraint as a standard into analytical and reservoir simulation models.
Influence of Water Saturation and Water Memory on CO2 Hydrate Formation/Dissociation in Porous Media Under Flowing Condition
Authors: Aghajanloo M. , Taghinejad S. M. , Voskov D. , Farajzadeh R.
Published: April 2024

Injection of high-pressure CO2 into depleted gas reservoirs can lead to low temperatures promoting formation of hydrate in the near wellbore area resulting in reduced injection rates. The design of effective mitigation methods requires an understanding of the impact of crucial parameters on the formation and dissociation of CO2 hydrate within the porous medium under flowing conditions. This study investigates the influence of water saturation (ranging from 20% to 40%) on the saturation and kinetics of CO2 hydrate during continuous CO2 injection. The experiments were conducted under a medical X-ray computed tomography (CT) to monitor the dynamics of hydrate growth inside the core and to calculate the hydrate saturation profile. The experimental data reveal increase in CO2 hydrate saturation with increasing water saturation levels. The extent of permeability reduction is strongly dependent on the initial water saturation: beyond a certain water saturation the core is fully blocked. For water saturations representative of the depleted gas fields, although the amount of generated hydrate is not sufficient to fully block the CO2 flow path, a significant reduction in permeability (approximately 80%) is measured. It is also observed that the volume of water+hydrate phases increases during hydrate formation, indicating a lower-than-water density for CO2 hydrate. Having a history of hydrate at the same water saturation leads to an increase in CO2 consumption compared to the primary formation of hydrate, confirming the existence of the water memory effect in porous media.
WITHDRAWN: Lingual Foramina of the Mandible: Anatomic Variations in a Turkish Population
Authors: KURT Bilgesu , KARACA Inci Rana , GULEN Orhan
Published: April 2024

The full text of this preprint has been withdrawn by the authors due to author disagreement with the posting of the preprint. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
The Transition from Galaxy-wide Gas Inflow to Outflow in Quasar Host Galaxies
Authors: Chen Zhifu , He Zhicheng , Liu Guilin , Wang Tinggui , Ho Luis , Wang Junxian , Bian Weihao , Cai Zheng , Mou Guobin , Gu Qiusheng , Wang Zhiwen
Published: April 2024

Galactic-wide outflows driven by active galactic nuclei (AGNs) is a routinely invoked mechanism in galaxy evolution models. Hitherto, the interplay among the interstellar gas on galactic scales, the propagation of AGN outflows and the fundamental AGN parameters during evolution remains elusive. Powerful nuclear outflows are found to favorably exist at early AGN stages usually associated with high accretion rates and weak narrow emission lines. In a sample of quasars emitting Mg II narrow absorption lines (NALs) from the Sloan Digital Sky Survey, we discover an unprecedented and spectacular phenomenon where galaxy-scale inflows transforming into outflows accompanied by an increasing strength of the narrow O III line, at a confidence level of 6.7 σ. The fact that nuclear outflows diminish while galaxy-wide outflows intensifies as AGNs evolve implies that early-stage outflows interact with interstellar medium on galactic scales and trigger the gradual transformation into galaxy-wide outflows, providing observational links to the hypothetical multi-stage propagation of AGN outflows that globally regulates galaxy evolution.
Balancing the Encoder and Decoder Complexity in Image Compression for Classification
Authors: Duan Zhihao , Hossain Md Adnan Faisal , He Jiangpeng , Zhu Fengqing Maggie
Published: April 2024

This paper presents a study on the computational complexity of coding for machines, with a focus on image coding for classification.We first conduct a comprehensive set of experiments to analyze the size of the encoder (which encodes images to bitstreams), the size of the decoder (which decodes bitstreams and predicts class labels), and their impact on the rate-accuracy trade-off in compression for classification.Through empirical investigation, we demonstrate a complementary relationship between the encoder size and the decoder size, \ie, it is better to employ a large encoder with a small decoder and vice versa.Motivated by this relationship, we introduce a feature compression-based method for efficient image compression for classification.By compressing features at various layers of a neural network-based image classification model, our method achieves adjustable rate, accuracy, and encoder (or decoder) size using a single model.Experimental results on ImageNet classification show that our method achieves competitive results with existing methods while being much more flexible.The code will be made publicly available.
Modified Lemaire extra-articular tenodesis with soft anchors in patients with high-grade anterior knee instability undergoing revision anterior cruciate ligament reconstruction (ACLR)
Authors: Conteduca Jacopo , Giaracuni Marco , Pichierri Paolo , Longo Damiano , Meccariello Luigi , Rollo Giuseppe
Published: April 2024

Purpose:
Additional lateral extra-articular procedures can reduce the risk of failure of primary anterior cruciate ligament reconstruction (ACLR). The purpose of this study was to evaluate the clinical outcome of patients treated with modified Lemaire extra-articular tenodesis with soft anchors in combination with revision ACLR for combined ACL graft failure and high-grade anterior knee instability.
Methods:
Between 2020 and 2022, 15 patients with graft failure after primary ACLR and high-grade anterior knee instability who underwent revision ACLR and modified Lemaire extra-articular tenodesis with soft anchors were included in the retrospective study. High-grade anterior knee instability was defined as a high-grade pivot shift and side-to-side difference of more than seven millimetres in the Rolimeter® test.
All patients underwent a standardized bilateral knee subjective and objective evaluation, which included a Rolimeter arthrometric evaluation and bilateral weightbearing anteroposterior radiographs in full extension and lateral views.
Results:
Subjective evaluation yielded a median score of 6 (range, 3-9) on the Tegner activity scale. The mean Lysholm score was 95 (SD=9.5), and the mean subjective IKDC 2000 score was 95.4 (SD=7.8). On clinical examination, twelve patients had a negative Lachman test result one patient had a positive Lachman test result with a firm endpoint, and another patient had a positive Lachman test result. One patient had a grade 1+ pivot shift. No signs of femoral tunnel convergence were observed.
Conclusions:
The results of our study show that the use of modified Lemaire extra-articular tenodesis with soft anchors during revision ACLR represents a valid option in patients with primary ACLR failure and high-grade anterior knee instability.
Screening of quorum sensing inhibitors for Pseudomonas aeruginosa in the traditional Chinese medicine Phellodendron amurense
Authors: Yi yu , Zhou Ye , Lin Susu , shi Kefan , Mei Jianfeng , Ying guoqing , Wu shujiang
Published: April 2024

Drug-resistant bacterial infections pose a significant challenge in the field of bacterial disease treatment. Finding new antibacterial pathways and targets to combat drug-resistant bacteria is crucial. The bacterial quorum sensing (QS) system regulates the expression of bacterial virulence factors. Inhibiting bacterial QS and reducing bacterial virulence can achieve antibacterial therapeutic effects, making QS inhibition an effective strategy to control bacterial pathogenicity. This article mainly focused on the PqsA protein in the QS system of Pseudomonas aeruginosa. An affinity chromatography medium was developed using the SpyTag/SpyCatcher heteropeptide bond system. Berberine, which can interact with the PqsA target, was screened from Phellodendron amurense by affinity chromatography. We characterized its structure, verified its inhibitory activity on Pseudomonas aeruginosa, and preliminarily analyzed its mechanism using molecular docking technology. This method can also be widely applied to the immobilization of various protein targets and effective screening of active substances.
Pasteurella multocida from deep nasal swabs and tracheobronchial lavage in calves
Authors: Myrenås Mattias , Pringle Märit , Harbom Boel , Bengtsson Björn
Published: April 2024

Background
Bovine respiratory disease (BRD) is common in intensively raised cattle and is often treated with antibiotics. To guide practitioners, knowledge of the bacteria involved in an outbreak and their antibiotic susceptibility is warranted. To this end, samples from the upper or lower respiratory tract of calves can be submitted for bacteriological culture and susceptibility testing of relevant isolates. However, it is debated whether isolates from the upper respiratory tract are representative of bacteria causing infections in the lower tract. In this study, we used MALDI-TOF MS, multilocus sequence typing (MLST) and core-genome multilocus sequence typing (cgMLST) to compare isolates from deep nasal swabs (DNS) and from tracheobronchial lavage (TBL) in 219 calves from 25 farms.
Results:
The predominant bacterial pathogen in this study was Pasteurella multocida, which was isolated from 37.4% of DNS and 22.4% of TBL. There was no statistically significant difference in isolation frequency between healthy and diseased calves for DNS (p = 0.778) or TBL (p = 0.410). At least one P. multocida isolate was obtained from 83.3% of the calf groups. At the 49 samplings where P. multocida was isolated from TBL, the same species was isolated from DNS at 29 samplings (59.2%). From 28 of these samplings, isolates were evaluated by MLST and at 24 samplings (86.0%) P. multocida from DNS and TBL were of the same sequence type (ST). Moreover, at 21 of the samplings (75.0%), cgMLST showed that the genetic distance within isolate pairs was less than two alleles, and DNS and TBL isolates were considered identical. At seven samplings (25%), the genetic distance within isolate pairs was greater, and DNS and TBL isolates were considered nonidentical. Within farms and groups of calves, P. multocida of several different STs were isolated.
Conclusions:
Pasteurella multocida was readily isolated from DNS and in calves where this species was isolated also from TBL, isolates from DNS and TBL were identical at 75% of the samplings. This suggests that during an outbreak of BRD, submission of DNS samples from 4–6 calves could be a convenient approach for practitioners seeking guidance on bacterial pathogens present and their antibiotic susceptibility.
Convergent evidence for temperature-dependent emergence of silicification in terrestrial plants
Authors: Liang Yongchao , Pang Zhihao , Tombeur Félix , Hartley Susan , Zohner Constantin , Nikolic Miroslav , Violle Cyrille , Mo Lidong , Crowther Thomas , Guan Dong-Xing , Luo Zhongkui , Zhu Yong-Guan , Wang Yuxiao , Zhang Ping , Peng Hongyun , Nikolic Nina
Published: April 2024

While research on terrestrial silicon (Si) biogeochemistry and its beneficial effects for plants has received significant attention in last decades, the reasons for the emergence of high-Si taxa remain unclear. Although the “arms race” hypothesis (i.e. increased silicification through co-evolution with mammalian grazers) has received some support, other studies have pointed to the role of environmental factors, such as high temperatures and low atmospheric CO2 levels, which could have favored the emergence of silicification. Here, we combine experimentation and analysis of existing databases to test the role of temperature on the expression and emergence of silicification in terrestrial plants. We first show through experimental manipulations of rice that Si is beneficial for growth under high temperature stress, but harmful under low temperature. We then found that, globally, the average temperature of the distribution of high-Si plants was 1.2°C higher than that of low-Si plants. Moreover, within China, a notable positive correlation emerged between the concentrations of phytoliths in wheat and rice and air temperature. From an evolutionary perspective, 65–77% of high-Si families (> 10 mg Si g− 1 DW) originated during warm geological periods, while 57–75% of low-Si families (< 1 mg Si g− 1 DW) originated during cold geological periods. On average, Earth's temperatures during the emergence of high-Si families were 3°C higher than those during the emergence of low-Si families. A correlation was also observed between the divergence of proteins related to Si transport (Lsi1, Lsi2, Lsi3, and Lsi6) and historical climatic variability. Together, cumulative evidence suggests that plant Si variation is closely related to global and long-term climate change, with potential repercussions for global Si and C biogeochemical cycles.
Cell competition drives bronchiolization and pulmonary fibrosis.
Authors: De Langhe Stijn (P) , Warren Rachel , Klinkhammer Kylie , Lyu Handeng , Yao Changfu , Stripp Barry
Published: April 2024

Idiopathic pulmonary fibrosis (IPF) is a progressive scarring disease arising from the maladaptive differentiation of lung stem cells into bronchial epithelial cells rather than into alveolar type 1 (AT1) cells, which are responsible for gas exchange. Here, we report that healthy lungs maintain their stem cells through tonic Hippo and β-catenin signaling, which promote Yap/Taz degradation and allow for low level expression of the Wnt target gene Myc. Inactivation of upstream activators of the Hippo pathway in lung stem cells inhibits this tonic β-catenin signaling and Myc expression and promotes their Taz mediated differentiation into AT1 cells. Vice versa, increased Myc in collaboration with Yap promotes the differentiation of lung stem cells along the basal and myoepithelial like lineages allowing them to invade and bronchiolize the lung parenchyma in a process reminiscent of submucosal gland development. Our findings indicate that stem cells exhibiting the highest Myc levels become supercompetitors that drive remodeling, whereas loser cells with lower Myc levels terminally differentiate into AT1 cells.
Study on a hybrid solar power prediction model based on a numerical weather prediction and random forests
Authors: GUAN Liang , Zou Lanjun
Published: April 2024

Photovoltaic grid-connected applications pose challenges to the stable and safe operation of power systems. Solar power predicted by a hybrid model based on numerical weather prediction (NWP) and random forests (RF) in order to enable grid-connected planning to balance fluctuations. Using downward solar short-wave radiation flux, temperature, wind speed, and other meteorological parameters obtained from the numerical weather forecast model, PV power forecast models with different initial time and durations under various weather conditions by RF are established. The correlations between observed and predicted power in daily, monthly and seasonal change are analyzed and both two powers are compared under three different detailed weather types. The results show that compared with NWP-principle method, this hybrid NWP-RF method can simulate the change of solar power under different weather conditions in the middle-lower plain of the Yangtze River more accurately. This model has an acceptable amount of data computation and high prediction accuracy, so that it can apply to engineering.
Rational Electrolytes Design for Li-Metal Batteries Operated Under Extreme Conditions: A Combined DFT, COSMO-RS, and Machine Learning Study
Authors: Jiang Jyh-Chiang , Wu Liang-Ting , Zhan Yu-Ting , Li Zhong-Lun , Chen Po-Ting , Hwang Bing Joe
Published: April 2024

Developing electrolytes for Li metal batteries capable of operating under extreme conditions is a significant challenge and is often hindered by the absence of systematic solvent screening studies. In this study, 190 binary mixtures comprising 20 solvents were assessed by calculating the density functional theory (DFT) and conductor-like screening model for realistic solvents (COSMO-RS) to identify electrolytes with a wide liquid temperature rangeand high LiTFSI solubility. Tetramethylene sulfone (TMS) has emerged as a promising candidate because of its high boiling point and low enthalpy of fusion, which increase the bubble point and reduce the eutectic temperature in mixtures. Utilizing a machine learning model with seven σ-descriptors, Li- and TFSI-ion binding energies were accurately predicted. These binding energies were primarily influenced by strong electrostatic and van der Waals interactions. This integrated approach highlights the effectiveness of the combined DFT, COSMO-RS, and machine learning techniques for guiding electrolyte design.
Climate change risks and adaptive capacity analysis in the Botswana livestock industry
Authors: Kgosikoma Olaotswe Ernest , Kgosikoma Keneilwe Ruth
Published: April 2024

Livestock production systems on dryland ecosystems in the region are highly vulnerable to climate change and this study identifies the climate risks that threaten the livestock industry in Botswana and assesses climate resilient adaptation practices used by smallholder livestock farmers using Multiple Criteria Analysis. In addition, barriers to adoption of adaptation practices in the livestock sector are also assessed by regional experts in livestock and climate change. Precipitation is projected to decline between September and February, and this will be exacerbated by increased temperatures, which could lead to reduced forage plant productivity and reduced rangeland carrying capacity. To deal with these climate risks, farmers prefer the use of different livestock types which scored significantly towards livelihood improvement. Livestock supplementation and breeding locally adapted breeds also ranked high due to their high potential to contribute towards greenhouse gas mitigation and technical simplicity, respectively. The experts attributed poor adoption of ecosystem-based adaptation and change in agricultural practices to lack of knowledge. Financial constraints were also linked to failure to supplement livestock and water development. Adaptation to climate change could be limited by multiple barriers and there is an urgent need to address such barriers to facilitate adoption of climate resilient practices by smallholder farmers and thus improve resilience to climate change in the livestock sector.
Establishing the Automatic Identification of Clinical Trial Cohorts from Electronic Health Records by Matching Normalized Eligibility Criteria and Patient Clinical Characteristics
Authors: Lee K. , Mai Y. , Liu Z. , Raja K. , Higashi M. K. , Jun T. , Ma M. , Wang T. , Ai L. , Calay E. , Oh W. , Schadt E. , Wang X.
Published: April 2024

The use of electronic health records (EHRs) holds the potential to enhance clinical trial activities. However, the identification of eligible patients within EHRs presents considerable challenges. We aimed to develop a pipeline for phenotyping eligibility criteria, enabling the identification of patients from EHRs with clinical characteristics that match those criteria. We utilized clinical trial eligibility criteria and patient EHRs from the Mount Sinai Database. The criteria and EHR data were normalized using national standard terminologies and in-house databases, facilitating computability and queryability. The pipeline employed rule-based pattern recognition and manual annotation. Our pipeline normalized 367 out of 640 unique eligibility criteria attributes, covering various medical conditions including non-small cell lung cancer, small cell lung cancer, prostate cancer, breast cancer, multiple myeloma, ulcerative colitis, Crohn’s disease, non-alcoholic steatohepatitis, and sickle cell anemia. 174 were encoded with standard terminologies and 193 were normalized using the in-house reference tables. The agreement between automated and manual normalization was high (Cohen's Kappa = 0.82), and patient matching demonstrated a 0.94 F1 score. Our system has proven effective on EHRs from multiple institutions, showing broad applicability and promising improved clinical trial processes, leading to better patient selection, and enhanced clinical research outcomes.
Exploring Digital Games-Based Learning Design for Enhancing Resilience in Higher Education Students: Unveiling the Potential of RESSIL
Authors: White Wendee , Gault Paul , Shimi Jill , Herd Kristi , Manwaring Gaye
Published: April 2024

This study addresses the increasing recognition of resilience as a pivotal component of student success against the backdrop of mounting concerns regarding student mental health and wellbeing in higher education. Drawing from interdisciplinary literature, the study integrates insights from resilience theory and digital game-based learning to inform the design of an adventure-based digital game, ‘Resilience Education Supports Students in Life’ (RESSIL), aimed at developing the resilience capacities of undergraduate students. A purposeful pilot study approach supports an exploration of the User Experience (Ux) to gain insights into the effectiveness and value of RESSIL’s design and its potential for achieving its intended aim. Focus group discussions engage undergraduate students from diverse academic backgrounds and thematic analysis sheds light on the effectiveness of RESSIL's game design in fostering engagement, facilitating knowledge transfer, and nurturing resilience-related skills among players. The findings underscore the significance of integrating narrative-driven gameplay and multisensory engagement to cultivate meaningful Ux and improve learning outcomes. Furthermore, the study highlights the critical role of aligning learning content with game elements to ensure coherence and optimise the game's utility. Insights gained from this pilot study offer valuable guidance for enhancing the game and lay the foundation for a larger study investigating RESSIL’s efficacy as a resilience intervention. This research contributes to the ongoing discourse on DGBL in higher education, emphasising the importance of user-centered design principles and co-creation methodologies in developing effective educational games.
Exploring the Role of ENO1 in Regulating Cell Proliferation and Cell Cycle in Hepatocellular Carcinoma: Insights from Proteomic Analysis
Authors: Ma Li-Na , Yang Xiao-qing , Luo Xia , Hai Long , Ma Zi-min , Ding Xiang-Chun
Published: April 2024

Background and Aims: Hepatocellular carcinoma (HCC), a prevalent solid organ malignancy, is intricately linked to the glycolytic enzyme Alpha-enolase (ENO1). ENO1's overexpression is associated with malignant tumor progression and poor clinical outcomes, yet its role in HCC cell proliferation and differentiation warrants further investigation. This study focuses on identifying ENO1-interacting proteins in HCC, exploring their involvement in cell proliferation and the cell cycle. Materials and Methods: We employed RNA interference to downregulate ENO1 in HepG2 cells, evaluating effects on cell proliferation, cycle progression, and key signaling pathways using MTT assays, flow cytometry, and Western blotting. Identifying ENO1-interacting proteins involved combining RNAi and co-immunoprecipitation with isobaric tags (iTRAQ). We confirmed five proteins central to proliferation and cell cycle regulation through immunofluorescence microscopy and additional co-immunoprecipitation. Pathway analysis and follow-up experiments were conducted for further elucidation. Results: ENO1 silencing significantly inhibited HepG2 cell proliferation and extended G2/M and S phases. We identified 40 ENO1-interacting proteins with notable expression changes, including PCNA, HSP90, PCBP1, PSME1, and PEBP1. Significant downregulation was observed in PCNA, various cyclins, and phosphorylated ERK1/2, MAPK, and AKT, alongside an upregulation of P21. However, levels of CDK1, CDK2, ERK1/2, MAPK, and AKT remained unchanged. Conclusions: This study highlights the glycolytic pathway's crucial role in HCC development. The identified ENO1-interacting proteins like PCNA, HSP90, PCBP1, PSME1, and PEBP1 are key in tumor development, differentiation, invasion, and metastasis. The interaction between ENO1 and PCNA, influencing cell cycle regulators and phosphorylation processes, offers new insights into HCC molecular dynamics and potential therapeutic avenues.
Fine Mapping and Identification of a Fusarium Wilt Resistance Gene FwS1 in Pea
Authors: Deng Dong , Sun Suli , Wu Wenqi , Duan Canxing , Wu Xuehong , Zhu Zhendong
Published: April 2024

Pea Fusarium wilt, incited by Fusarium oxysporum f. sp. pisi (Fop), has always been a devastating disease that causes severe yield losses and economic damage in pea-growing regions worldwide. The utilization of pea cultivars carrying resistance gene is the most efficient approach for managing this disease. In order to finely map resistance gene, a F2 population was established through the cross between Shijiadacaiwan 1 (resistant) and Y4 (susceptible). The resistance genetic analysis indicated that the Fop resistance in Shijiadacaiwan 1 was governed by a single dominant gene, named as FwS1. Based on the bulked segregant analysis sequencing (BSA-seq) analyses, the gene FwS1 was initially detected on chromosome 6 (i.e., linking group Ⅱ, chr6LG2), and subsequent linkage mapping with 589 F2 individuals fine-mapped the gene FwS1 into a 91.4 kb region. The further functional annotation and haplotype analysis confirmed that the gene Psat6g003960, characterized by a NB-ARC (nucleotide-binding adaptor shared by APAF-1, R proteins, and CED-4) domain, was considered as the most promising candidate gene. The encoding amino acids were altered by a “T/C” single-nucleotide polymorphism (SNP) in the first exon of the Psat6g003960, resulting in the observed differences of Fop resistance in peas. Based on this SNP locus, the molecular marker A016180 was determined to be a diagnostic marker for FwS1 by validating its specificity in both pea accessions and genetic populations with different genetic backgrounds. The FwS1 with diagnostic KASP marker A016180 could facilitate marker-assisted selection in resistance pea breeding in pea. In addition, upon comparing the candidate gene Psat6g003960 of 74SN3B and SJ1, it was noted that their sequences are identical, suggesting that the FwS1 and Fwf may be the same resistance gene against Fusarium wilt.