bluuebunny/crossref_metadata_2025 huggingface dataset:
Forward and Inverse Stratigraphic Modeling in Exploration and Appraisal Workflows: Insights from Miocene Carbonate Platforms, Central Luconia, South China Sea
Authors: Granjeon Didier , Gervais Véronique
Published: April 2023

Estimating the geometry and sedimentary heterogeneities of carbonate platforms is a very challenging task. In recent decades, numerical stratigraphic forward models have been developed to provide a quantitative view of sedimentary processes with the resulting stratigraphic architecture. Although used in many academic and industrial studies, this numerical approach is rarely used in everyday exploration and appraisal workflows. The calibration of these models on available seismic and well data is indeed a challenging and time-consuming process.

Here we use the DionisosFlow model to simulate a carbonate platform typical of the Miocene formations observed in Central Luconia, South China Sea. We build a reference simulation or virtual ground truth from literature data, using for instance the Haq et al. (1988), Laskar et al. (2011), and Bosscher and Schlager (1992) curves, which prove indications on sea-level variations, orbital parameters, and carbonate production as a function of water depth, respectively. We analyze the sensitivity of the simulation results to the parameters controlling the physical processes: accommodation space creation, carbonate production, and sediment transport.

Results show that stratigraphic modeling makes it possible to test the concepts of sequence stratigraphy in a virtual digital world, thus opening the possibility of testing the sensitivity of the different characteristics of a sedimentary system to physical parameters. We also propose an innovative approach to using this stratigraphic modeling in operational cases. The first step is to identify a diachronous geological body such as the carbonate platform sensu stricto, which is easily identifiable using seismic data. A comparison of the geometry of this geological body with the thickness maps derived from the seismic interpretation provides a first regional metric controlling the shape of the studied sedimentary systems. The second step is to validate the simulation results with well data, and, in particular, facies from the log interpretation. The computation of vertical proportion curves (VPC) in the vicinity of wells facilitates understanding the local variability of facies in the digital world as well as in the real world. This second metric, based on a comparison of VPCs, makes it possible to assess sequences and sedimentary heterogeneities and to define much smoother cost functions, thus facilitating the use of automatic optimization algorithms.

In conclusion, this work shows that numerical stratigraphic forward modeling is a tool that reproduces stratigraphic concepts using simple physical laws. Through the use of well and seismic metrics adapted to the resolution of the model, use of this numerical approach in daily exploration work to complement the interpretation of seismic and well data provides a quantitative stratigraphic view of the studied area to better access uncertainties and risk in exploration.
Spatial Distribution of Sedimentary Facies on Modern Carbonate Platforms Interpreted via Remote Sensing, Northwest Celebes Sea, Malaysia
Authors: Chalabi Aicha , Soto Grisel Jimenez , Pierson Bernard J.
Published: April 2023

Remote-sensing analysis of high-resolution satellite imagery of modern carbonate platforms in the Celebes Sea, east of Sabah, Borneo, Malaysia, was used to map geomorphology and sediment. Unsupervised classification of satellite images was interpreted in the context of environmental facies of seven isolated carbonate platforms and calibrated using analyses of surface sediments. In total, 140 sediment samples were collected and analyzed for grain-size and sorting. The grain-size analysis showed that sediment varied among the geomorphic elements, which included island, island/volcano, reef complex, carbonate sand shoal, grass-covered sand shoal, shallow lagoon, and deep lagoon. To generate carbonate sediment texture maps, the proportion of mud and the grain-size attributes (mean grain size and sorting) of each sediment sample provided a basis to classify samples into rock-equivalent textures. Integration of remote-sensing, field, and sedimentological data provided a means to characterize texture distribution maps and depositional facies maps. These maps suggest that mudstone to wackestone occurs mainly in the deep lagoon; wackestone to packstone is dominant in the shallow lagoon; the carbonate sand shoal is characterized by packstone to grainstone; and the reef complex is made up of boundstone to rudstone. These results facilitate estimates of the proportions of potential reservoirs on these platforms and the heterogeneity in facies distribution, based on the size of various recent carbonate platforms. Diagenesis notwithstanding, ancient analogs indicate the Selakan and Maiga platforms could be potential reservoirs, whereas the Selakan and Gaya platforms display more facies classes and represent poor potential reservoirs.
Management of Gas Slugging Along With Sand Handling to Improve ESP Performance and Efficiency
Authors: Vazhappilly Neil Johnson , Guanacas Luis , Gonzalez Gustavo
Published: April 2023

A dual purpose design is presented in this paper to face high gas presence and sand production conditions in petroleum wells with an Electric Submersible Pump (ESP) system installed. The results of this design's application in severely problematic wells, due to high gas and sand production, will confirm the importance of conditioning the fluid before it gets to the pump intake. This engineered design consists of different stages from the isolation of the pump intake until the tubing bodies in charge of gas and sand handling. Engineering concepts were applied in the construction of this solution such as gas re-solubilization, changes of pressure and velocity, agitation, and vortex effect to finally present a design that is capable of breaking gas slugs into smaller gas bubbles that can be produced by the ESP system without impacting its performance, and at the same time separating fine solid particles (<250 microns) using centrifugal forces. Case studies from wells located in the Permian basin will better explain the positive impact of selecting a proper downhole conditioning system to improve the ESP systems efficiency. A drastic improvement on the sensor parameters will also illustrate the effect of handling the gas and sand before the pump intake, which also leads to one of the most important consequences: A decrease in the number of shutdowns, which in turn decreases non-productive time, resulting in positive impact of fluid production. Additionally, the flexibility of this design is significant, since it allows it to be installed in a wide range of fluid production, gas-liquid ratio, tubing and casing sizes. The novelty of this new design is the addition of the surge valve below the packer, which accomplishes multiple purposes: to avoid surging in the well, to allow testing the packer to assure it is properly set, and finally, allow chemical injection below the packer.
Development of a Multi-Completion Gas and Downhole Water Sink-Assisted Gravity Drainage (MC-DWS-AGD) to Improve Oil Recovery and Reduce Water Cut in Reservoirs with Strong Water Aquifers
Authors: Al-Obaidi Dahlia A. , Wood David A. , Al-Mudhafar Watheq J. , Wojtanowicz Andrew A. , Merzoug Ahmed
Published: April 2023

Gas and downhole water sink assisted gravity drainage (GDWS-AGD) is a promising gas-based enhanced oil recovery (EOR) process applicable for reservoirs associated with infinite aquifers. However, it can be costly to implement because it typically involves the drilling of multiple vertical gas-injection wells. The drilling and well-completion costs can be substantially reduced by using additional completions for gas injection in the oil production wells through the annulus positioned at the top of the reservoir. Multi-completion-GDWS-AGD (MC-GDWS-AGD) can be configured to include separate completions for gas injection, oil, and water production in individual wells. This study simulates the MC-GDWS-AGD process applied to the synthetic reservoir (PUNQ-S3, based on a real North Sea Field) by placing multiple completions in two wells, which include a gas injection loop, and 2-horizontal wells with a diameter of 2⅜ inch, first one for producing oil located above the oil/water contact and the second one for water sink placed below the oil/water contact. Hydraulic packers are positioned to isolate the multiple completions and an electric submersible pump are positioned to produce the water zone. These results compare to a base case involving no MC-GDWS-AGD wells, which achieved 55.5% oil recovery and 70% water cut.
Scalable Geothermal Energy Potential from Sedimentary Basins in Oklahoma
Authors: Vivas Cesar , Salehi Saeed , Nygaard Runar , Rehg Danny
Published: April 2023

Geothermal energy has vast potential as a reliable energy source of the future. However, its development has mostly been tied to specific geological locations or igneous rocks. Even though most western US regions have high thermal gradients compared to other places, higher temperatures are easily achievable by increasing the total depth in sedimentary rocks. The oil and gas industry has successfully mastered drilling sedimentary basins cost-effectively. Comparing cost/ft from typical sedimentary basins to granite or igneous rocks shows a tremendous difference. In addition, recent hydraulic fracturing technology transfer from the oil and gas industry can be deployed for geothermal applications.

A potential new path toward expanded geothermal energy production is to use known porous and permeable reservoir rocks in appropriate sedimentary basins, where those formations have a sufficient temperature, thickness, porosity, and permeability, existing at depths that drilling time makes well construction costs economical for geothermal applications.

In this paper, we will examine the unique potentials that sedimentary basins in Oklahoma offer to the geothermal industry for different end-user purposes, such as electricity generation or direct heat applications. The state has high geothermal gradients in some regions in the Arkoma Anadarko Basins that could be used for medium-temperature resources. Case studies from Oklahoma show how the many oil and gas wells in the state can enable geothermal direct-use projects. A state-wide levelized cost of energy analysis using geothermal gradient data indicates that there are areas with the potential to produce geothermal power at 14 cents/kWh or less. Geothermal energy has the potential to play a crucial role in Oklahoma's energy supply by offering a clean and renewable source of power that can fulfill energy demands.
Application of Machine Learning Optimization Workflow to Improve Oil Recovery
Authors: Koray Abdul-Muaizz , Bui Dung , Ampomah William , Appiah Kubi Emmanuel , Klumpenhower Joshua
Published: April 2023

Machine learning application in the oil and gas industry is rapidly becoming popular and in recent years has been applied in the optimization of production for various reservoirs. The objective of this paper is to evaluate the efficacy of advanced machine learning algorithms in reservoir production optimization.

A 3-D geological model was constructed based on permeability calculated using a machine learning technique which involved different architectures of algorithms tested using a 5-fold cross-validation to decide the best machine learning algorithm. Sensitivity analysis and a subsequent history matching were conducted using a machine learning workflow. The aquifer properties, permeability heterogeneity in different directions and relative permeability were the control variables assessed. Field development scenarios were exploited with the objective to optimize cumulative oil recovery. The impact of using a normal depletion plan to a secondary recovery plan using waterflooding was investigated. Different injection well placement locations, well patterns as well as the possibility of converting existing oil producing wells to water injection wells were exploited. Considering the outcome of an economic analysis, the optimum development strategy was realized as an outcome for the optimization process. Prior to forecasting cumulative oil production using artificial neural network (ANN) for the optimization process on the generated surrogate model, a sensitivity analysis was performed where the well location, injection rates and bottomhole pressure of both the producer and injector wells were specified as control variables. The water cut as part of the optimization process was utilized as a secondary constraint. Forecasting was performed for a 15-year period. The history-matching results from the constructed geological model showed that the oil rate, water rate, bottom hole pressure, and average reservoir pressure were matched within a 10% deviation from the observed data. In this study, the ANN optimizer was found to provide the best results for the field cumulative oil production. Using a secondary recovery development plan was observed to significantly increase the cumulative oil production. A machine learning based proxy model was built for the prediction of cumulative oil production to reduce computational time. In this study, we propose an approach applied to reservoir production optimization utilizing a machine learning workflow. This was accomplished by utilizing a surrogate model which was calibrated with a number of training simulations and then optimized using advanced machine learning algorithms. A detailed economic analysis was also conducted showing the impact of a variety of field development strategies.
Leak Detection in Natural Gas Pipelines Based on Unsupervised Reconstruction of Healthy Flow Data
Authors: Liang Jing , Liang Shan , Zhang Hao , Zuo Zhonglin , Ma Li , Dai Juan
Published: April 2023

Timely detection of leak accidents plays an essential role in the safe operation and risk assessment of natural gas pipelines. However, the scarce leak data and complex operating conditions lead to small samples, data imbalance, and problems with confusing operating conditions. The reliance on leak data limits the recognition performance of the artificial intelligence classification method for leakage operating conditions. A leak detection method based on the unsupervised reconstruction of healthy flow data is established to address these problems. First, an unsupervised neural network is established to reconstruct healthy flow data from real natural gas pipelines. And a model update strategy based on active learning is designed to improve the model’s adaptability for time-varying pipelines. Next, a dynamic alarm threshold strategy that accounts for the knowledge of the experience and statistical characteristics of the data segments is suggested to prevent false alarms caused by ambiguous operating conditions. Finally, unlike most recent work that only considers simulated data or laboratory data, this paper conducts a leak case study on an actual natural gas pipeline in service to improve the robustness of the proposed method in the actual operating environment. The findings of this paper can be used as a reference to analyze pipeline behavior analysis based on pipeline flow trend characteristics and early alarm management.
Terrorist Crimes in the Era of Digitalization: Forms of Activity and Measures for Counteraction
Authors: Antonova E. Yu.
Published: April 2023

Objective: to elaborate recommendations on counteraction against terrorist crimes committed in the digital (cyber-) space and/or using digital technologies.

Methods: the methodological basis of the research are the universal dialectic method of cognition, the integrity of general and specific scientific methods such as analysis, synthesis, logical method, ascent from the abstract to the specific, induction, deduction, etc.

Results: it was determined that the development of the digital (cyber-) space and digital technologies promotes the intensity of terrorism and has led to the change of the mechanism of terrorist crimes commitment. A conclusion was made that, to provide the efficiency of measures for counteracting terrorist crimes committed in the digital (cyber-) space and/or using digital technologies, a distinct strategy is necessary, as well as the appropriate regulatory basis.

Scientiﬁc novelty: the article analyzes such forms of criminal activities of terrorist groups, committed in the digital (cyber-) space and/or using digital technologies, as dissemination of the ideology of violence and propaganda of terrorist activity, recruiting new members and their training, implementing digital technologies for preparation and immediate terrorist activity, and funding. The advantages were revealed of the use of digital space and/or digital technologies when committing terrorist crimes. In the author’s opinion, the change of the mechanism of terrorist crimes commitment associated with the use of digital technologies should be taken into account during criminalization (change of the intensity of penalization) of publicly dangerous deeds. The important areas of state policy in the sphere of counteraction against these crimes are education and enlightenment activity, training of the personnel of law-enforcement agencies, broadening their authorities to ensure a clear and effective control over digital content.

Practical signiﬁcance: is due to the possibility to use the formulated conclusions and proposals for further scientific elaboration of the state criminal policy in the sphere of counteraction against terrorist crimes committed in the digital (cyber-) space and/or using digital technologies.
Concept of Electronic Evidence in Criminal Legal Procedure
Authors: Dmitrieva A. A. , Pastukhov P. S.
Published: April 2023

Objective: elucidating the potential of digital transformation for elaborating the optimal means and methods of collecting evidences and introducing scientific organization of labor of the officials implementing criminal procedure. The scientific approach within the concept consists in minimizing the costs of collecting evidentiary information in criminal cases in electronic form and by electronic means, as well as storing the criminal case materials in electronic form.

Methods: dialectic method occupies the leading position among the research methods, the issues of electronic documentation being considered in the interaction and interdependence with information-technological development of the society. The set of scientific cognition methods within the research creates prerequisites for objective and comprehensive approach to the problems under study.

Results: the authors’ concept of electronic evidence is a system of information-technological and legal views on the criminal-procedural form, which is intended for optimizing the process of collecting, registering and preserving them in the criminal case materials. The concept development is aimed at elaborating new approaches to organizing the work of investigation agencies and courts, taking into account the achievements in the sphere of information technologies, providing new techniques of collecting criminal-relevant, criminal-procedural, criminological significant information when investigating and hearing of a criminal case. The proposed concept is also aimed at improving interaction and in-service communication of the officials of the preliminary investigation bodies with the officials of information-technological systems for the purposes of collecting evidentiary information in electronic form.

Scientiﬁc novelty: the changes were systemically analyzed, which are taking place in the contemporary information society, through the prism of the emerging problems between the sectoral criminal-procedural evidentiary law and more modern technological means of collecting evidentiary information. The article demonstrates a new approach to creating technological interaction using digital technologies, on the scientific base of organization of proving activity, intended to optimize and rationalize the process of proving in criminal procedure.

Practical signiﬁcance: the research materials can be used to prepare proposals on making changes and additions in the current legislation with a view of implementing the practice of already functioning models of criminal-procedural activity of foreign countries, an inexhaustible potential of information-technologies, software, and artificial intelligence to rationalize proving in criminal cases.
Illaria Lavrentyevna Bachilo – the Founder of Informational Law in Russia
Authors: Talapina E. V. , Zharova A. K.
Published: April 2023

Objective: to assess the scientific contribution of Illaria Lavrentyevna Bachilo into forming the science of informational law in Russia; the role and significance of I. L. Bachilo’s scientific works for the Russian informational law.

Methods: the methods used in the work are: retrospective scientific and bibliographical analysis, analysis and synthesis, comparison and cross checking, bibliographical study of documents.

Results: a brief analysis of scientific activity of an outstanding researcher Illaria Lavrentyevna Bachilo was carried out; the most significant works were described, which, in the authors’ opinion, appeared to be fundamental in the formation and development of the science of informational law.

Scientiﬁc novelty: the article presents the main stages and achievements of I. L. Bachilo’s academic life and reflects the personal estimations and impressions of the authors, formed during mutual work with Illaria Lavrentyevna Bachilo.

Practical signiﬁcance: the information presented in the article will allow scientists, especially young researchers, to get acquainted with the personality and activity of a prominent scientist, a deep and intelligent person, whose memory will always dwell with the hearts of the people working in the Section of Informational Law of the Institute of State and Law of the Russian Academy of Sciences.
Discovery of Initial SARS-CoV-2 as DNA Viruses and Reliable Interactive COVID-19 DNA Methylation Markers and Druggable Targets and Potential Malignant Diseases with Long Incubation Period
Authors: Zhang Zhengjun
Published: April 2023

COVID-19 research needs interactive reliable biomarkers at genomic and genetic levels. Earlier research has established the existence of reliable interactive genomic biomarkers. However, reliable DNA methylation markers haven't been identified at the epigenetic level, not to mention interactiveness. This study, from 865,859 methylation sites, discovers two miniature sets of Infinium MethylationEPIC sites, each having seven (CpG sites, genes) to interact with each other and with disease subtypes. They lead to nearly perfect (96.87-100% accuracy) prediction of COVID-19 patients from patients with other diseases or healthy controls. These CpG sites can jointly explain some post-COVID-19-related conditions. These CpG sites and the optimum performed genomic biomarkers reported in our earlier work rise to be potential druggable targets. Among these CpG sites, diseases associated with cg16785077 (gene MX1) can have an incubation period of up to six to eight years, which raises a serious (or urgent) issue to investigate now or sooner. The gene PARP9 (cg25932713) is one of the only three human genes that contain both PARP domains and macrodomains. MX1 and PARP9 together were linked to SARS-CoV-1, MERS-CoV, and SARS-CoV-2. The new findings of CpG sites cg16785077 (gene MX1) and cg25932713 (PARP9) in COVID-19 at DNA methylation levels indicate that the initial SARS-CoV-2 may be better treated as transcribed viral DNA into RNA virus due to the long incubation feature of MX1 associated diseases, i.e., not as an RNA virus that has been concerned by scientists. Such a discovery will significantly change the scientific thinking and knowledge of viruses.
Effects of heat consumption and diffusion-thermo on MHD flow of fractionalized Brinkman type fluid
Authors: Ramzan Muhammad , Nazar Mudassar
Published: April 2023

Free convection flow of fractionalized Brinkmantype fluid over a vertical plate is obtained. Moreover, in the modelof problem, additional effects like, diffusion thermo and magneticfield are also used. The constant Proportional Caputo (CPC)derivative is used to solve this model. The Fick's and Fourier'slaws are used for generalization of flow problem. Firstly, partialdifferential equations for energy, mass and momentum are madeOrdinary differential equations using Laplace transform method. Theimpact of parameters such as Dufour effect, magnetic parameterchemical reaction R, heat generation/absorption, Brinkman parameterare plotted and discussed through numerous graphs.
The Relationship Between Insomnia and Anxiety Among COVID-19 Patients in China: the Chain Mediating Effect of Psychological Capital and Self-esteem
Authors: Du Juan , Wu Chao , Zheng Wenkai , Gao Li , Li Ling , Liu Zhuo , Ni Chunping , Heng Chunni , Lang Hongjuan
Published: April 2023

Background：The outbreak of Corona Virus Disease (COVID-19) in 2019 has continued until now, posing a huge threat to the public’s physical and mental health, resulting in different degrees of mental health problems. As a vulnerable segment of the public, anxiety is one of the most common mental health problems among COVID-19 patients. Excessive anxiety aggravates the physical and psychological symptoms of COVID-19 patients, which is detrimental to their treatment and recovery, increases financial expenditure, affects family relations, and adds to the medical burden.
Objective: This study aimed to explore the role of psychological capital and self-esteem in the relationship between insomnia and anxiety, thereby shedding light on the mechanism of the effect of insomnia on anxiety in COVID-19 patients.
Methods: A cross-sectional study was conducted from April to May 2022 in Fangcang hospital in Shanghai, China. The self-administered questionnaires were distributed to 718 COVID-19 patients via cell phone using the Internet platform "Questionnaire Star", which included Athens Insomnia Scale, Psychological Capital Questionnaire, Self-esteem Scale, Self-Rating Anxiety Scale, gender, age, marital status, education. Data analysis was performed using descriptive analysis, independent-samples t-test, one-way analysis of variance, Pearson correlation analysis, ordinary least-squares regression, and bootstrap method.
Results: Education background had significant impact on anxiety in COVID-19 patients (F =7.701, P < 0.001). Insomnia, psychological capital, self-esteem and anxiety were significantly correlated, respectively (P < 0.001). And Regression analysis showed that insomnia had a direct negative predictive effect on psychological capital (β = -0.699, P < 0.001) and self-esteem (β = -0.129, P < 0.001). Psychological capital had a direct positive predictive effect on self-esteem (β = 0.116, P < 0.001). Insomnia had a direct positive predictive effect on anxiety (β = 0.611, P < 0.001). Both psychological capital and self-esteem had significant negative predictive effects on anxiety (β = -0.060, P < 0.001; β = -0.722, P < 0.001).
Conclusions: Insomnia had a significant positive predictive effect on anxiety. Insomnia was first associated with a decrease in psychological capital, followed by a sequential decrease in self-esteem, which in turn was associated with increased anxiety symptoms in COVID-19 patients.
Nanomechanical thermometry for probing sub-nW thermal transport
Authors: Oh Sangmin , Davaji Benyamin , Jameel Osama , Lal Amit , Lee Chung Hoon
Published: April 2023

Measuring local temperature at the micro/nanoscale requires high resolution thermometery due to the ultra low thermal transport. Among practical temperature measurement methods, the optical method has demonstrated the highest temperature resolution (∼10−5 K). We present a sub micro-Kelvin resolution thermometry (∼10−8 K with a controlled environment, ∼10−6 K with a noisy open lab environment) that uses a 20 nm thick silicon nitride (SiN) membrane. The temperature resolution of the SiN membrane device is inversely proportional to the stiffness of the membrane. Analysis and measurements of the stiffness and noise equivalent temperature (NET) of the pre-stressed SiN membrane are presented. The achievable heat output resolution of the membrane device is sub nano-Watt (< 0.5 nW) and suitable for studying thermal transport at the micro/nanoscale.
Genomic virulence features of Beauveria bassiana as a biocontrol agent for the mountain pine beetle population
Authors: Li Janet X. , Fernandez Kleinberg X. , Ritland Carol , Jancsik Sharon , Engelhardt Daniel B. , Coombe Lauren , Warren Rene L. , Belkum Marco J. , Carroll Allan L. , Vederas John C. , Bohlmann Joerg , Birol Inanc
Published: April 2023

Background: The mountain pine beetle, Dendroctonus ponderosae, is an irruptive bark beetle that causes extensive mortality to many pine species within the forests of western North America. Driven by climate change and wildfire suppression, a recent MPB outbreak has spread across more than 18 million hectares, including areas to the east of the Rocky Mountains that comprise populations and species of pines not previously affected. Despite its impacts, there are few tactics available to control MPB populations. Beauveria bassiana is an entomopathogenic fungus used as a biological agent in agriculture and forestry and has potential as a management tactic for the mountain pine beetle population. This work investigates the phenotypic and genomic variation between B. bassianastrains to identify optimal strains against a specific insect.
Results: Using comparative genome and transcriptome analyses of eight B. bassiana isolates, we have identified the genetic basis of virulence, which includes oosporein production. Genes unique to the more virulent strains included functions in biosynthesis of mycotoxins, membrane transporters, and transcription factors. Significant differential expression of genes related to virulence, transmembrane transport, and stress response was identified between the different strains, as well as up to nine-fold upregulation of genes involved in the biosynthesis of oosporein. Differential correlation analysis revealed transcription factors that may be involved in regulating oosporein production.
Conclusion: This study provides a foundation for the selection and/or engineering of the most effect strain of B. bassiana for the biological control of mountain pine beetle and other insect pests populations.
Analysis of a Petroleum Industry System Using Supplementary Variable and Neural Network Approach
Authors: EKATA EKATA , SINGH S B
Published: April 2023

Architecture of interconnected components/system networks on very large dimension increase the designing intricacy of the systems which can decrease the efficiency of system’s performance. Petroleum is the main material of a multitude of chemicals and plays an immense role in power generation. In view of this, present article deals with the study of reliability and profitability of a model pertaining to a petroleum industry system. The proposed system fails due to hardware failure and common cause failure. All types of failures and waiting time are supposed to be exponentially distributed while repairs are generally distributed. On the other hand, feed forward back propagation (FFBP) algorithms, one of the neural network (NN) techniques, is beneficial in foretelling various parameters of reliability and improve its accuracy and uniformity. All the failures, repairs and waiting time are considered as neural weights. The gradient descent learning mechanism of FFBPNN is utilized to update the neural weights and improves the reliability and profit functions up to the desired accuracy. System’s state probabilities, including reliability and expected profit are assessed using both supplementary variable technique (SVT) and NN methods. The Matlab code is generated to execute the FFBP algorithm for minimizing the error up to 10–4 precision and optimize the results. Numerical examples are incorporated to illustrate the study which may be helpful for system designer(s).
MSC Classification: 35A01 , 65L10 , 65L12 , 65L20 , 65L70
Mean time to failure of dams
Authors: Opyrchał Leszek , Bąk Aleksandra
Published: April 2023

Dams are among the largest structures constructed by human. Their disasters result in numerous casualties and large material losses. The statistical analysis of the reasons for dam disasters was carried out by the International Commission on Large Dams. The hazard function h(t) and next, the reliability function R(t) were calculated based on that data, using the fitting of the power function in the infant mortality period and a constant function in the operation period. The knowledge of the reliability function allowed for calculating the mean time to failure which was 112957 ± 12443 years. It was also demonstrated that in the operation period the annual dam failure ratio is 8.719×10− 6 ± 0.297×10− 6. It is a value that is proximate to the recommendations of the U.S. Army Corps of Engineers which suggests the tolerance for the annual dam disaster risk not to exceed 10− 6 for newly-constructed dams and 10− 4 for already existing ones.
Radiomics analysis of baseline computed tomography to predict oncological outcomes in patients treated for resectable colorectal cancer liver metastasis
Authors: Montagnon Emmanuel , Cerny Milena , Hamilton Vincent , Derennes Thomas , Ilinca André , Elforaici Mohamed , Jabbour Gilbert , Edmond Rafi , Wu Anni , Romero Francisco , Cadrin-Chênevert Alexandre , Kadoury Samuel , Turcotte Simon , Tang An
Published: April 2023

Predicting recurrence and survival of patients with upfront resectable colorectal cancer liver metastases (CRLM) is crucial to personalize treatment. The purpose of this work was to determine whether radiomics analysis of baseline computed tomography (CT) images could help predict outcomes of resectable CRLM compared to the clinical risk score (CRS). From a registry of 251 patients treated with systemic chemotherapy and surgery for CRLM, radiomics features extracted from baseline CT images were developed to predict time to recurrence (TTR) and disease-specific survival (DSS) and compared to low- and high-risk groups based on the CRS using Kaplan-Meier estimates and Log-rank test. CRS scores provided significant separation of low- vs. high-risk CRLM patients for TTR (p = 0.002) and DSS (p = 0.002), whereas radiomics signatures improved separation by 4–6 and 6–8 orders of magnitude for TTR and DSS (p < 0.0001), respectively. CRS alone provided median survival times for TTR of 1.67 and 1.05 years for low- and high-risk groups respectively, while radiomics yielded 2.87 and 0.92 years. Radiomics signatures outperformed the CRS for stratifying CRLM patients in low- and high-risk groups. Early prediction of patient outcome may reduce CRLM patient exposure to ineffective yet toxic chemotherapy or high-risk major hepatectomies.
A novel genetic-based residual stress and deformation prediction method for the coupled machining process of connecting rod
Authors: Zhou HongGen , Peng Zhicheng , Li GuoChao , Zhou Tao , Wu Hengheng , Sun Li
Published: April 2023

Residual stress is the main factor that causes the deformation of connecting rod during its coupled machining process. Thus, it is essential to predict the residual stress and deformation of the connecting rod before its machining. As the traditional independent analysis method is no longer suit to the coupled machining process, a novel genetic-based method is processed. Firstly, the genetic mechanism of residual stress field and deformation field was established to realize the effective correlation of multiple machining process simulation models. Secondly, a milling process was established based on the birth and death element method, which converts complex milling processes into dynamic loading of milling forces and the death of elements of the FEM model. It realizes the coupling of initial residual stress (IRS) and machining induced residual stress (MIRS). Then, a multi-process simulation model of heat treatment, cutting off, and milling of connecting rod is established, which can reveal the evolution law of residual stress field under multi-process coupling of connecting rod, the coupling mechanism between IRS and MIRS, and the deformation response law of big hole cylinder of connecting rod. The proposed method will have great significance to the deformation control of connecting rod.
Social-economic impacts of rewilding: the case of the pinniped population boom on California coast
Authors: Levrel Harold
Published: April 2023

This paper explores the dynamics of change and reorganization of coastal California socioecosystems over the past 30 years in response to regional population increases of two pinniped species: the California sea lion Zalophus californianus and the harbour seal Phoca vitulina. The work presented focuses on four very different types of socio-ecosystems - urban beaches, harbours, a river, the coastal marine ecosystem (continental shelf). The dynamics of rewilding led to the questioning of the management of these spaces by certain local stakeholders who saw their uses threatened, generating a strong judicialisation of the relationship between humans and non-humans. This paper presents the solutions, mainly technical, that have been tested to deal with this dynamic, with no obvious effectiveness due to the adaptability of pinnipeds and the impossibility of harassing federally protected species.
Association of coronary plaque morphology with inflammatory biomarkers and target lesion revascularization in patients with chronic coronary syndrome: An optical coherence tomography study
Authors: Saiin Kohei , Konishi Takao , Kazui Sho , Yasui Yutaro , Takahashi Yuki , Naito Seiichiro , Takenaka Sakae , Mizuguchi Yoshifumi , Tada Atsushi , Kobayashi Yuta , Kato Yoshiya , Omote Kazunori , Sato Takuma , Kamiya Kiwamu , Nagai Toshiyuki , Tanaka Shinya , Anzai Toshihisa
Published: April 2023

Background: The characteristics of high-risk coronary atherosclerosis evaluated using optical coherence tomography can have a prognostic role. Inflammatory biomarkers may be related to the severity of coronary artery disease. This study investigated the association of high-risk morphological features of coronary plaques on optical coherence tomography with circulating levels of inflammatory biomarkers and adverse cardiovascular events.
Methods: We prospectively analyzed the data of 30 consecutive patients with chronic coronary syndrome who underwent percutaneous coronary intervention using optical coherence tomography between April 2020 and November 2020 at our university hospital. Estimation of inflammatory biomarker levels and optical coherence tomography analysis focused on high-risk coronary plaque features were performed. Based on the coronary plaque risk score, patients were defined as having a low coronary plaque risk score (coronary plaque risk score≤3) or high coronary plaque risk score (coronary plaque risk score≥4). The primary outcome was target lesion revascularization.
Results: Targetlesion revascularization was achieved in 6 (20%) patients within 15 months of percutaneous coronary intervention. High coronary plaque risk score on optical coherence tomography was directly correlated with target lesion revascularization (P=0.029). In logistic regression analysis, coronary plaque risk score was associated with target lesion revascularization (odds ratio, 10.0; 95% confidence interval, 1.34–74.5). Serum monocyte chemoattractant protein-1 level was significantly correlated with the coronary plaque risk score (P=0.020).
Conclusions: In patients with chronic coronary syndrome, coronary plaque risk score may be a surrogate predictor of target lesion revascularization. Serum monocyte chemoattractant protein-1 may aid detection of high-risk coronary atherosclerosis.
Identification of Model Based on Oxidative Stress-related Genes for Predicting Prognosis and Therapeutic Features in Bladder Cancer
Authors: Huang Jianxu , Luo Weihan , Li Yuqing , Li Yingrui , Wang Yongqiang , Wu Song
Published: April 2023

Background: Bladder cancer is one of the most common malignant tumors, presenting as a heterogenous entity that requires a severe stratified strategy to enhance clinical decision-making and patient counseling. Multiple studies have investigated the relationship between oxidative stress and tumor progression, highlighting its potential role in cancer pathogenesis. Herein, our study aimed to establish a prognostic model based on the oxidative stress-related gene for risk stratification in bladder cancer.
Methods: Differentially expressed oxidative stress genes (oxidative stress DEGs) were identified using microarray and clinical data from the GEO database. Functional enrichment and survival analyses were performed in screened oxidative stress DEGs. A risk score model was constructed, and its diagnostic value and relationship with the prognosis as well as its sensitivity to chemotherapy and immunotherapy were verified through Cox regression, receiver operating characteristic curve and drug sensitivity analysis. The TCGA-BLCA cohort was set as the training cohort, GSE13507 and GSE32894 were used for external validation. A nomogram was constructed to facilitate the clinical application.
Results: The risk score model demonstrated a significant difference in overall survival between the high- and low-risk groups. The area under the curve and hazard ratio revealed the independent prognostic value of the model. There are differences in the sensitivity of chemotherapy and immunotherapy between the high- and low-risk groups.
Conclusions: Our findings provide a new prognostic model that can serve as a reliable reference for the prognosis and personalized therapy of patients with bladder cancer.
Left Knee Septic Monoarthritis in a Pediatric Patient due to Shewanella Putrefaciens: Case Report in Colombia
Authors: Madrid Nathalie Yepes , Mejia Luis Fernando , Urrego José Fernando Gomez
Published: April 2023

Shewanella putrefaciens is a Gram-negative bacillus and marine pathogen that rarely causes disease in humans. We present the case of a previously healthy pediatric patient with a sharp wound and septic monoarthritis of the left knee due to Shewanella putrefaciens, we describe the bacteriological, and clinical characteristics and antibiogram of this bacteria spp since resistance patterns must be taken into account when managing patients, so as not to induce intrinsic antimicrobial resistance.
Genome-wide identification of GH9 gene family and the assessment of its role during fruit abscission zone formation in Vaccinium ashei
Authors: Zheng Weiwei , Wang Yingying , Xu Yue , Liao Fangfang , Li Ting , Li Xiaolong , Wu Boping , Hong Seung-Beom , Xu Kai , Zang Yunxiang
Published: April 2023

Glycosyl hydrolase family 9 (GH9) cellulases play a crucial role in both cellulose synthesis and hydrolysis during plant growth and development. Despite this importance, there is currently no study on the involvement of GH9-encoding genes, specifically VaGH9s, in abscission zone formation of rabbiteye blueberries (Vaccinium ashei). In this study, we identified a total of 61 VaGH9s in the genome, which can be classified into three subclasses based on conserved motifs and domains, gene structures, and phylogenetic analyses. Our synteny analysis revealed that VaGH9s are more closely related to the GH9s of Populus L. than to those of Arabidopsis, Vitis vinifera, and Citrus sinensis. In-silico structural analysis predicted that most of VaGH9s are hydrophilic, and localized in cell membrane and/or cell wall, and the variable sets of cis-acting regulatory elements and functional diversity with four categories of stress response, hormone regulation, growth and development, and transcription factor-related elements are present in the promoter sequence of VaGH9s genes. Transcriptomic analysis showed that there were 22 differentially expressed VaGH9s in fruit abscission zone tissue at the veraison stage, and the expression of VaGH9B2 and VaGH9C10 was continuously increased during fruit maturation, which were in parallel with the increasing levels of cellulase activity and oxidative stress indicators, suggesting that they are involved in the separation stage of fruit abscission in Vaccinium ashei. Our work identified 22 VaGH9s potentially involved in different stages of fruit abscission and would aid further investigation into the molecular regulation of abscission in rabbiteye blueberries fruit.
BABS (Becoming Active in Beating osteoarthritiS): Study protocol of a randomized controlled trial on the effectiveness of an information campaign in improving the management of osteoarthritis and quality of care
Authors: Oomen J. M.H. , Schers H. J. , Das E. , Koëter S. , Ende C. H. , Assendelft W. J.J.
Published: April 2023

Background
Despite recommendations, non-surgical treatment modalities in knee and/or hip osteoarthritis (KHOA) are underused. This article describes the development and content of an information campaign and the design of a randomized controlled trial (RCT) on the effectiveness of such a information campaign, targeting both KHOA patients and healthcare professionals (HCPs), on healthcare utilization.
Methods
The Behaviour Change Wheel (BCW) was used as a theoretical framework for the campaign design. After an inventory of the literature, a selection was made of factors influencing healthcare use. The campaign aims to increase 1) awareness and knowledge of patients and their HCPs about OA and treatment options, and 2) quality of communication and interdisciplinary collaboration. Main elements of the campaign include written materials and an educational program. Persuasive communication techniques (i.e., message framing, narratives) are embedded within the campaign to positively impact beliefs about conservative treatments. The effectiveness of the campaign will be evaluated with a cluster RCT. The study aims to recruit 300 patients in 24 general practices (GPs), randomly allocated to intervention or usual care (ratio 1:1). GPs and affiliated HCPs are invited to participate in the trial and recruit patients. Patients are eligible to participate if they are Dutch speaking, aged 50 to 75, registered with KHOA at the GP practice, without joint replacement nor having considerable walking impairment. The main endpoint is the difference in rate of referral to hospital care as reported by patients over a period of 18 months. Secondary parameters include quality of care, beliefs about KHOA treatment modalities, physical activity, self-management behavior, and referral rates to secondary care. Patients receive online questionnaires at baseline, 6, 12, and 18 months. Online questionnaires are sent to HCPs at baseline and after 12 months to assess (changes in) beliefs about KHOA treatment modalities, and qualitative interviews are performed with HCPs of the intervention group at 12 months to assess network collaboration.
Conclusion
This article reports on a systematic, theory-based approach, building a toolbox of evidence-based intervention strategies. Furthermore, the RCT will provide insight into the effectiveness of an information campaign on impacting patterns of healthcare consumption.
Trial registration
International Clinical Trial Registry Platform (ICTRP), trial number NL9140, registration date 23-12-2020