bluuebunny/crossref_metadata_2025_split huggingface dataset:
Stochastic Economic Ranking Addresses Risk and Uncertainty for Decision-Makers
Authors: Carpenter Chris 
Published: December 2023

_
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 213385, “Stochastic Economic Ranking: A Prudent Way To Address Risk and Uncertainty for Decision-Makers,” by Mahesh Narayanan, SPE, Mehaboob Abdulazeez, SPE, and Khadija Bukhamsin, SPE, Saudi Aramco, et al. The paper has not been peer reviewed.

_
Project screening and ranking is inevitable even when an organization faces no resource bottlenecks. In project economic predictions, the stochastic approach is prevalent and proves to be the most natural approach to address technical and commercial uncertainties. In contrast with a deterministic approach, a stochastic Monte Carlo simulation helps in understanding the range of possible outcomes to enable effective decision-making. The objective of the complete paper is to present an integrated stochastic work flow that addresses the subsurface, surface, and cost uncertainties to screen, rank, and grade opportunities early in the derisking process.

Introduction
The proposed work flow simultaneously can address all technical and commercial uncertainties with a Monte Carlo model and predict a range of possible economic outcomes with customized economic analysis tools. In other words, it can achieve complete unbiased sample randomness in expected project outcomes. The work flow also creates a stage-gate decision-tree approach and reviews economics as a series of staged investments. This helps to expose incremental capital in the life cycle of a project responsibly and help with course correction where necessary.

Value Addition: Stochastic Approach
A common practice in the oil and gas industry is to simply examine low, middle, and high cases. This is a limited view of possible scenarios and provides a false sense of precision regarding expected project outcomes.
The term “stochastic” refers to the property of being well-described by a random probability distribution. A stochastic approach features the following advantages:
- A stochastic model addresses uncertainties in inputs with complete unbiased randomness in the outcomes.
- By running thousands of calculations and using many different estimates of future economic conditions, stochastic models predict a range of possible future investment results, showing the potential upside and downside of each.
- Once the work flow is followed and the model is set up, multiple realizations can be created with a single click.

Proposed Integrated Stochastic Methodology
In the world of project economics, classical stochastic economics is a tool to address uncertainty and risk. In simple terms, a mean or deterministic view of a production profile, along with one view of a schedule, is taken and blended with probabilistic distribution of cost inputs. This data is then taken through a Monte Carlo model to create multiple scenarios to predict a range of possible economic outcomes. This narrow range of economic outcomes only covers the uncertainty in cost but does not cover variability in well performance and time.
Nanomembrane Approach Reuses Waste, Cleans Produced Water
Authors: Carpenter Chris 
Published: December 2023

_
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 213946, “Nanomembranes From Polymeric Waste for Produced-Water Treatment,” by Anton Manakhov, Iaroslav Rybkin, and Fahd I. AlGhunaimi, Saudi Aramco, et al. The paper has not been peer reviewed.

_
In the oil and gas sector, produced water is the most significant waste stream. Among the different materials used for water filtration, including ceramics, polymers, and carbon nanomaterials, polymeric nanofibers can be considered a unique solution that can be used as a membrane or an adsorbent. In the complete paper, the authors write that polymeric nanofibers can be prepared from polystyrene waste.

Introduction
The management of polystyrene trash and recycling creates a significant environmental problem. While most of this substance ends up in landfills, only a small portion of polystyrene is recycled or burned. By turning this trash into products with added value, recycling will become more appealing economically and will result in lower CO2 emissions and less chemical waste dumped on the ground.
At the same time, the use of modified nanofiltration membranes for generated-water purification has been a subject of study for many researchers. The complete paper includes a review of the literature dedicated to advances in this approach.
Dissolved polystyrene waste can be used as a feedstock in the electrospinning process to create nanofibrous membranes. Electrospinning is one of the more basic methods for producing nanofibers with dimensions ranging from micrometers to nanometers. Strong electrostatic forces are used to overcome the surface tension of a polymer solution or melt. These pressures produce the ejection of charged polymer jets, which dry as they approach a grounded electrode, where they are gathered as nanofibers.
In this work, the nanofibrous polystyrene membranes were prepared from discarded expanded polystyrene waste. Initially, polystyrene waste was collected and dissolved in an organic solvent; then, the nanofibrous membranes were prepared by the electrospinning of nanofibers from this solution. The morphology, pore sizes, and other parameters were controlled and optimized by tuning the concentration of polystyrene, the nature of the solvent, and the spinning voltage to form uniformly sized nanofibrous membranes.
Hehuan Anshen Decoction Inhibits Hypothalamic Ferroptosis to Ameliorate p-Chlorophenylalanine-induced Insomnia
Authors: Deng Qing , Li Yanan , He Linting , Wang Yuxia , Li Nana , Zhao Zhenghao , Kui Wenyun , Xu Jian , Wang Kaiqiang , Sha Zhongwei , Xue Chunchun 
Published: December 2023

Abstract
Insomnia is a highly prevalent health condition with a global impact. The hypothalamus, a crucial brain region governing sleep-wake cycles, plays a pivotal role in the manifestation of insomnia. Perturbation in the hypothalamus correlates with the development of insomnia by inducing neuronal demise. Furthermore, emerging evidence acknowledges the involvement of ferroptosis, a new form of programmed cell death, in various neurological disorders. Hehuan Anshen Decoction (HHASD), an innovative formula derived from Traditional Chinese medicine, has demonstrated therapeutic efficacy in treating insomnia, however, the potential pharmacological mechanism underlying its anti-insomnia effects remains incompletely elucidated. This study aimed to explore the underlying mechanism of HHASD treatment in mice with insomnia induced by p-Chlorophenylalanine (PCPA). PCPA-treated insomnia mice were administered HHASD orally for 7 days. The main constituents of HHASD were identified by high-performance liquid chromatography (HPLC). The anti-insomnia effects of HHASD were assessed through behavioral tests, encompassing the open field test and pentobarbital sodium-induced sleep test, alongside the measurement of hypothalamic 5-HT levels. Then, we conducted an in-depth analysis of specific ferroptosis markers, considering morphology, biochemistry, and genetics. The results demonstrated that HHASD could effectively improve the insomnia phenotype induced by PCPA, resulting in decreased sleep latency and prolonged sleep duration. Specifically, HHASD exerted a neuroprotective effect by enhancing the integrity of Nissl bodies in the hypothalamus of the insomnia mouse modeling. Mechanistic analysis revealed that HHASD could reverse the hypothalamic ferroptosis phenotype of insomnia mice by restoring the lowered levels of glutathione (GSH) and superoxide dismutase (SOD), inhibiting iron accumulation and elevated malondialdehyde (MDA), and mitigating mitochondrial cristae damage. Furthermore, HHASD enhanced the expression of SLC7A11 and GPX4 and reduced the ASCL4 in the hypothalamus, while the anti-insomnia effect of HHASD in the PCPA mice was eliminated by the GPX4 inhibitor RLS3. In summary, HHASD ameliorates insomnia-related behaviors and protects against neuronal damage by suppressing hypothalamic ferroptosis.
Performance and emissions of an engine operating with the direct injection of diesel, biodiesel, and wet ethanol blends
Authors: de Souza Ivair Carvalho , HANRIOT Sergio , Moreira Vinícius Guerra , Amorim Rogério Jorge 
Published: December 2023

Abstract
This research evaluates the performance and pollutant emissions of a motor generator set equipped with a compression ignition engine, adapted to operate with the direct injection of ethanol and diesel oil. Fuel injection was conducted with separate systems. The experiments were carried out with power loads varying from 15 kW to 37.5 kW, an ethanol injection angle of 40o crank angle degree (CAD) before the top dead center (BTDC), and a 23o CAD BTDC diesel injection angle. The diesel fuel was replaced with ethanol mass percentages ranging from 52% to 59%, with the ethanol being over-hydrated from 7% to 30% by the mass of water. The emissions and performance exhibited different behaviors, varying according to the power loads and hydration contents. The results showed significant reductions in the emissions of nitrogen oxides (NOx) and smoke opacity for all the fuel mixtures used. An increase of approximately 5% in engine fuel conversion efficiency was observed when operating with ethanol blends at higher power loads. The occurrence of an ignition delay with the use of wet ethanol did not vary significantly with the amount of water mass, but it did vary with the operating load. It was also found that a higher volume of water in the fuel promoted an increase in the in-cylinder pressure at higher loads. These results suggest that the use of a fuel mixture containing diesel oil and wet ethanol blends, directly injected by separate systems, can favor the reduction of emissions and reliance on petroleum-based fuels. This could potentially lead to a cost reduction in the production of this renewable fuel, without compromising the performance of the engine.
Ubiquitin-independent degradation of Bim blocks macrophage pyroptosis in sepsis-related tissue injury
Authors: Li Lei , Shi Peilin , Du Yingying , Yang Bo , Guan Qiujing , Jing Yiming , Tang Hao , Shen Shihui , Wu Chunrong , Zhang Yunyan 
Published: December 2023

Abstract

Pyroptosis, a typical inflammatory cell death mode, has been increasingly demonstrated to have therapeutic value in inflammatory diseases such as sepsis. However, the mechanisms and therapeutic targets of sepsis remain elusive. Here, we reported that REGγ inhibition promoted pyroptosis by regulating members of the gasdermin family in macrophages. Mechanistically, REGγ directly degraded Bim, a factor of the BCL-2 family that can inhibit the accumulation of GSDMD/E, ultimately preventing the occurrence of pyroptosis. Furthermore, cecal ligation and puncture (CLP)-induced sepsis model mice showed downregulation of REGγ at both the RNA and protein levels. Gasdermin-mediated pyroptosis was augmented in REGγ-knockout mice, and these mice exhibited more severe sepsis-related tissue injury. More importantly, we found that REGγ expression was downregulated in clinical sepsis samples, such as those from patients with Pseudomonas aeruginosa (PA) infection. Finally, PA-infected mice showed decreased REGγ levels in the lung. In summary, our study reveals that the REGγ-Bim-GSDMD/E pathway is a novel regulatory mechanism of pyroptosis in sepsis-related tissue injury.
Genetic mechanisms underlying gray matter atrophy in Parkinson’s disease: a combined transcriptome and neuroimaging study
Authors: Fang Xiangming , Ji Yi , Xu Min , Zhao Han , Cai Huanhuan , Chen Kaidong , Zhang Li , Mao Haixia , Wang Feng , Zhu Jiajia 
Published: December 2023

Abstract

Extensive research has shown prominent gray matter atrophy in patients with Parkinson's disease (PD), yet its genetic mechanisms are largely unknown. To achieve a more thorough characterization of gray matter alterations in PD, we performed a comprehensive neuroimaging meta-analysis of previous literature including 1,831 PD patients and 1,378 controls as well as examined group gray matter differences in an independent dataset. Utilizing the Allen Human Brain Atlas, we performed spatial association analyses linking transcriptome data to neuroimaging findings to identify genes correlated with gray matter atrophy in PD. Subsequently, we conducted enrichment analyses for the identified genes associated with gray matter atrophy in PD patients and performed a series of gene functional feature analyses (i.e., specific expression, protein-protein interaction (PPI) and behavioral relevance analyses) for deep understanding. Our meta-analysis and independent dataset neuroimaging analysis consistently revealed significant gray matter atrophy in the superior temporal gyrus of PD patients. Transcriptome-neuroimaging correlation analysis identified 1,952 genes whose expression correlated with gray matter atrophy in PD. These genes were enriched in biologically significant processes and exhibited selective expression in brain tissue, dopamine receptor cells, and neurons. Regarding behavioral relevance, these genes were linked to perception and motion domains. Our findings suggest that prominent gray matter atrophy in PD may be a consequence of intricate interactions among a diverse set of genes with various functional features.
Geophysical and geochemical soil characteristics of industrially influenced topsoils of the Arctic Circle Fjord
Authors: Zawadzki Jarosław , Fabijańczyk Piotr 
Published: December 2023

Abstract

This study aimed to investigate the value of magnetic susceptibility within a fjord located on the border of the Arctic Circle. A suitable research area was established near the town of Mo, where magnetometric and chemical measurements were made in four measurement areas. These areas were located at varying distances from Ranfjorden. In addition, a large industrial area, Mo Industrial Park, was located at the research site, and the measurement areas were located so that the distance to this potential source of pollution was also different. As a consequence, the measurement areas were characterized by both varied anthropogenic pressure and natural conditions. During the study, the values of the soil magnetic susceptibility and concentrations of 18 elements in the soil were measured, which were later used to calculate selected measures of spatial continuity as well as classical statistics and factor analysis. The values of soil magnetic susceptibility measured in individual areas decreased with distance from the potential pollution source, Mo Industrial Park, which may suggest that the soils located away from the potential emission source were characterized by a lower concentration of technogenic magnetic particles (TMP). A similar situation was observed in the case of selected concentrations of elements in the soil and in the case of selected parameters of spatial correlations of soil magnetic susceptibility, which were characterized by a similar tendency of changes as in the case of magnetic susceptibility.
An Unsupervised Rotating Machinery Fault Diagnosis Method Based on Multi-Scale Feature Residual Neural Network
Authors: Li Xueyi , Yuan Peng , Yu Tianyu , Li Daiyou , Xie Zhijie , Kong Xiangwei 
Published: December 2023

Abstract
In complex settings, noise affects rotating parts like bearings and gears, weakening fault signals and complicating feature selection, resulting in redundancy. To address this, a multi-scale residual neural network is proposed for machinery fault diagnosis with domain adaptation. Using residual connections, it fuses vibration signal features from a multi-scale network for a global view. The method employs maximum mean discrepancy and entropy boundaries for adaptation, enhancing signal classification. Successful unsupervised cross-domain fault diagnosis is shown in experiments. Future work aims to refine the network architecture and enhance generalization through advanced data augmentation.
Euler–Darboux the spatial analogue equation with strong degeneracy
Authors: Dolgopolov Mikhail , Elisov Maksim , Rodionova Irina 
Published: December 2023

Abstract
On the set Ω, which is a prism bounded by the planes y=x, y=0, x=h, z=0, z=h (h>0), a spatial analogue of the Euler–Darboux–Poisson equation is considered with two parameters taking values 1) α=1, 0 < β < 1; 2) α=1, 1 < β < 2; 3) α=1, −1 < β < 0. The singularity plane of the coefficients of the equation z = x − y divides the set Ω into two subregions, in which for each of the three cases: a) a general solution to this equation is constructed; b) problems with boundary conditions on the plane z = x − y were formulated and solved (modified Cauchy problems); c) on the set Ω, a boundary value problem was solved with data on adjacent faces of the prism and matching conditions on the internal plane z = x − y.
Mesoporous La0.8Sr0.2MnO3/P-COK-12 catalyst synthesized by template method:Highly active for the complete oxidation of CO
Authors: Huang Xuehui , Hu Xiangao , Deng Penghui , Chen Wenzhen 
Published: December 2023

Abstract
In this study, an environmentally friendly mesoporous material called COK-12 was created using inexpensive sodium silicate as a silica source and surfactant P123 as a soft template. COK-12 was then modified with p-xylene to produce a template called P-COK-12, which had a compact and well-ordered pore structure. For the first time, this modified mesoporous material was used as a template to prepare a mesoporous La0.8Sr0.2MnO3 (LSM) catalyst through a combination of the nano-casting and sol-gel methods. The results showed that the LSM-550 catalyst, synthesized at 550 °C for 2 hours, had a large specific surface area of 72.11 m2/g and the highest molar ratio of surface Mn4+/Mn3+ and Oads/Olat. Additionally, the CO conversion results for different LSM-T samples (T=550, 600, 650, 700 °C) indicated that the LSM-550 sample exhibited the best catalytic activity, with T50 of 180 °C and T90 of 218 °C, as well as excellent stability.
Scholarly recommendation system for NIH funded grants based on biomedical word embedding models
Authors: Zhang Zitong , Yaseen Ashraf , Wu Hulin 
Published: December 2023

Abstract
Objective
Research grants, which are available from several sources, are essential for scholars to sustain a good standing in academia. Although securing grant funds for research is very competitive, being able to locate and find previously funded grants and projects that are relevant to researchers’ interests would be very helpful. In this work, we developed a funded-grants/projects recommendation system for the National Institute of Health (NIH) grants.
Methods
Our system aims to recommend funded grants to researchers based on their publications or input keywords. By extracting summary information from funded grants and their associated applications, we employed two embedding models for biomedical words and sentences (Biowordvec and Biosentvec), and compare multiple recommendation methods to recommend the most relevant funded grants for researchers’ input.
Results
Compared to a baseline method, the recommendation system based on biomedical word embedding models provided higher performance. The system also received an average rate of 3.53 out of 5, based on the relevancy evaluation results from biomedical researchers.
Conclusion
Both internal and external evaluation results prove the effectiveness of our recommendation system. The system would be helpful for biomedical researchers to locate and find previously funded grants related to their interests.
Research on the applicability of regularization methods in ship magnetic field modeling based on magnetic dipole arrays
Authors: LU Binjie , Zhang Xiaobing 
Published: December 2023

Abstract
In order to solve the problem of ship magnetic field modeling, a magnetic dipole array model was established, a modeling inversion equation system was constructed, and the degree of sickness of the solved equation system under different numbers of magnetic dipoles was quantitatively analyzed based on the coefficient matrix conditional number. In order to solve the problem of the pathological system of magnetic field modeling equations, a regularization method based on the conjugate gradient least squares method was designed to invert the magnetic moment parameters of the magnetic dipole. In order to analyze the applicability of the regularization method in magnetic field modeling inversion, the modeling accuracy, modeling robustness, calculation time and other metrics are defined. A detailed test of the ship model was designed, and the magnetic field passing characteristics of the two types of ship models at different positive and horizontal conditions at two depths were measured. Under the condition of no interference and interference, the conjugate gradient least squares method is used to invert the magnetic field model, and the numerical test analysis shows that the conjugate gradient least squares method has higher applicability than the generalized inverse solution method and the stepwise regression method. Under the condition of interference, the relative error of magnetic field fitting of the array model with 15 magnetic dipoles is 0.1537, and the relative error of magnetic field extrapolation is 0.0868.
Novelty and Innovation: Enhancing Shrimp Harvesting Efficiency and Quality Through Centrifugal Extraction and Pipe Transportation
Authors: thoetrattanakiat songphon , Samseemoung Grianggai , Sangpradit Kiattisak 
Published: December 2023

Abstract
The innovative integration of a Centrifugal Shrimp Harvester into closed pond aquaculture systems represents a significant advancement in aquaculture technology. This study introduces and assesses the efficiency of the harvester in comparison to manual harvesting methods, examining parameters such as shrimp quality, loss rates, and harvesting speed. Particularly noteworthy is the incorporation of shrimp transportation through a pipeline, introducing a novel dimension that amplifies the transformative potential of the technology. Results underscore that the Centrifugal Shrimp Harvester outperforms manual methods, achieving an impressive yield rate of 3338 kg/hour with a minimal loss rate of 0.01%. While the technology shows promise in increasing productivity and minimizing shrimp damage, a more in-depth investigation is necessary to assess its economic viability, including operational costs and labor expenses. The study not only illuminates the transformative potential of the Centrifugal Shrimp Harvester but also emphasizes the necessity for ongoing research to ensure its practical application in real-world aquaculture settings. The Centrifugal Shrimp Harvester emerges as a transformative force in aquaculture, featuring innovative features and superior performance. It has the potential to revolutionize shrimp harvesting practices, contributing to more sustainable and efficient aquaculture production.
Modeling Non-Homogenous Poisson Process and Estimating the Intensity Function for Earthquake Occurrences in Iraq using Simulation
Authors: Fatah Khwazbeen Saida 
Published: December 2023

Abstract
The Non-homogeneous Poisson Process, with time dependent intensity functions, is commonly used to model the scenarios of counting the number of events that appear to take place in a given time interval. The identification of the process relies on the functional form for the intensity function, which can be difficult to determine. In this paper, a Non-Homogenous Poisson Process model is proposed to predict the intensity function for the number of earthquake occurrences in Iraq; the constructed model allows anticipating the number of earthquakes occur at any time interval with a specific time length. Then, to estimate the model parameters, the data obtained from the annual reports of the Iraqi Meteorological Organization and Seismology (IMOS) from January, 1st 2018 to May, 1st 2023 is used. Moreover, a simulation study is conducted and a new algorithm is introduced to show the performance and the applicability of the proposed model.