bluuebunny/crossref_metadata_2025_split huggingface dataset:
Produced Water, X-Ray Fluorescence Spectrometry and Machine Learning: How Can They be Connected?
Authors: Atheaux Isabelle , Makarychev-Mikhailov Sergey M , Campos Faria Débora , Farrell Jesse W , MacKay Bruce A 
Published: May 2022

Abstract
Fast and reliable field-portable chemical analysis of produced waters remains one of the main challenges of scale-risk mitigation, as it enables timely control over scale inhibitor type and dosage. While many analytical methods are potentially applicable to produced waters, most of them lack reliability under field conditions or do not meet increasingly tight cost requirements. X-ray fluorescence (XRF) spectrometry is routinely used in the oil field for analysis of cores, drilling cuttings, and muds, as it provides quick noninvasive detection of many elements simultaneously. Inexpensive portable handheld analyzers typically feature limited element range, sensitivity, and resolution, and are therefore expected to be inferior to benchtop analyzers. The question is whether handheld devices can offer suitable detection limits and accuracy for produced water analysis, despite these limitations. At the same time, one of the major challenges of XRF, the so-called matrix effect, is strong in produced waters and also negatively affects the analysis accuracy.
This study demonstrates how multivariate machine-learning (ML) techniques can be applied to the full XRF spectra recorded with a handheld analyzer. ML spectra processing is shown to successfully mitigate matrix effects and enable simultaneous quantification of all ions of interest. Interestingly, key physical (density) and chemical (total dissolved solids and hardness) properties of produced water can also be quantified using ML techniques. In the paper, the experimental protocols are described first, followed by a detailed discussion of the data workflows, which covers the XRF spectra preprocessing, algorithm selection and tuning, and independent validation procedures. Over 50 different ML algorithms are trained on different spectra ranges of a multicomponent calibration dataset, and the three best models are applied to several real-life produced water sample sets for validation. A rigorous error analysis is performed for all ML models. In field samples, the resulting analysis errors (RMSE) are less than 100 mg/L for barium and strontium, less than 150 mg/L for sulfate, and remarkably small/accurate for other ions and properties considering measurement with a handheld device.
Sulfide Scale Controls and Predictions Using Water-Soluble Polymer
Authors: Ko Saebom , Wang Xin , Li Wei , Dai Zhaoy , Paudyal Samridhdi , Yao Xuanzhu , Leschied Cianna , Shen Yu-Yi , Pimentel Daniel , Kan Amy T. , Tomson Mason B. 
Published: May 2022

Abstract
Recently, sulfide scale related issues have been significantly increased, probably due to implementation of more aggressive technologies and exploration of unconventional fields, such as high temperature, high pressure, and high salinity. Firstly, sulfide scales (i.e., FeS, PbS, and ZnS) are one of the most or significantly unsolved deposition problem in oil and gas production. Secondly, sulfide scales have oleophilic nature so that they can be difficult to separate sulfide scales from oil phase during production processes. Polymeric dispersants have exhibited their feasibility to prevent the deposition of sulfide scales, but dispersants have not been widely validated to control sulfide scale problems and limited numbers of trials and reports have been available. The objectives of this study are: (1) to evaluate dispersion efficiency of sulfide scale dispersants in a wide range of conditions of brine ionic strength, calcium concentrations, solution pH, and temperature; (2) to examine the effect of dispersants on sulfide scale wettability; (3) to understand the mechanism of a dispersion process; and (4) to apply the newly developed dispersion model for a prediction of a minimum dispersant concentration (MDC). Among tested natural and synthetic water-soluble polymers, carboxymethyl cellulose (CMC) showed the best dispersion efficiency for sulfide scales with an individual particle size of around 4 nm. The second-best dispersants identified in our study were polyvinyl pyrrolidone (PVP) and polyacrylamide (PAM). Despite some degrees of aggregation of dispersed sulfide particles, their size was still in the nanometer ranges of 100 to 500 nm. Dispersed sulfide particles remained in the water phase, while settled ones were transferred to the oil phase. Transmission electron microscope (TEM) and Fourier-transform infrared (FT-IR) results showed that CMC was adsorbed on the surface of FeS particles through H-bond and complexation between Fe(II) and carboxylate groups, controlling particles growth and preventing them from settling. CMC was effective to disperse sulfide scales in conditions of brine ionic strength (58.5 – 234 g/L NaCl), Ca2+ concentrations (1,000 – 8,000 mg/L), pH (4.3 – 6.7), and temperature (70 – 120 °C). In these reaction conditions, MDC of CMC ranged from 5 to 200 mg/L. The combination of CMC and diethylenetriamine penta(methylene phosphonic) acid (DTPMP) enhanced CMC dispersion efficiency in some conditions. MDC of CMC for PbS and ZnS scales were 2 and 5 mg/L, respectively. MDC prediction model predicted MDC quite reasonably in wide range of NaCl concentrations (58.5 – 234 g/L) and SI of FeSm (0.13 – 2.03).
Kinetics of Transformation and Inhibition of Calcium Carbonate Scale Formation in Mixed Oil Fractions
Authors: Sanni Olujide , Charpentier Thibaut , Harbottle David , Barker Richard , Pessu Frederick , Neville Anne 
Published: May 2022

Abstract
The thermodynamic and kinetic uncertainities created by the mixing together of various fluids during oil processing and transportation will affect scaling tendency of facilities and the efficiency of inhibitors to combat scaling. The most severe operational challenges with pipeline transportation are flow assurance issues due to scale formation, which often lead to blockage of pipelines, and related to the flow of multiphase fluids. There is therefore the need for an understanding and assessment of the mechanisms and kinetics of scale formation in multiphase systems containing mxture of oil phases.
This work studies the mechanisms and behavior of precipitation of calcium carbonate scale in mixed oil fractions. Experiments were conducted in both single and multiphase systems for SR 211 at 30°C and SR 198 at 60°C. The mixed oil fractions include 50ml cyclohexane, 30ml kerosene, 20ml toluene and 0.01% asphaltene, fully dissolved in toluene. Homogeneous dispersion in the two-phase mixture was achieved using the Rotating Cylinder Electrode (RCE) with an overhead impeller blade stirring at 520 rpm to create The fouling process was investigated in the presence of a chemical scale inhibitor, polyphosphinocarboxylic acid (PPCA) at below the Minimum Inhibitor Concentratio (MIC). Samples are collected and analysed using the Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD) and Atomic Absorption Spectroscopy (AAS) techniques to evaluate the morphology, polymorphic transformation and calcium ion concentration respectively at different time intervals.
The study shows that the presence of an organic phase has a major effect on CaCO3 polymorphic abundance, slowing down the initial rapid transformation of vaterite to calcite. Injection of inhibitor below MIC combined with the presence of asphaltene do not prevent the bulk scaling but has an effect on the relative distribution as well as stability of the metastable vaterite. This could provide further insights for the development of inhibition and control strategies to deal with CaCO3 scale formation in multiphase systems.
Effects of Thermal Stress in Hot Dry Rock Fracturing
Authors: Luo Tianyu , Liu Yuanshuang 
Published: May 2022

Summary
China has rich geothermal hot dry rock (HDR) resources, but the development and usage of its thermal energy are still at an early stage. At present, few studies have investigated the variation law for fracturing pressure on the borehole wall and fracture wall under the influence of thermal stress. This study investigates the fracturing pressure around the borehole wall based on rock mechanics and thermal stress analysis. Two models were developed: one for borehole wall fracturing pressure with consideration for thermal stress and the other for temperature difference conditions related to the automatic opening of fractures. By analyzing the temperature variation in the fracture wall, the mechanism for the opening of branch fractures at the fracture wall was investigated based on rock mechanics, the theory of fracture extension in hydraulic fracturing, and the theory of thermal stresses. We developed a computational model for tensile or shear damage related to branch fractures in the fracture wall with consideration for thermal stress, as well as a model for temperature difference conditions for the automatic opening of branch fractures. The simulation results show that the fracturing pressure decreased significantly when thermal stress was considered. Under normal geostress and temperature conditions, large temperature difference conditions are needed for the HDR borehole wall to break naturally because of thermal stress alone. During fracture extension, branch fractures on the fracture wall are more likely to form because of thermal stress. Irrespective of the type of damage (tensile or shear), branch fractures on the fracture wall closer to the borehole required lower net fracturing pressure. The decline in the net fracturing pressure was greater in response to shear damage than to tensile damage. In a high-temperature thermal reservoir, when branch fractures in the fracture wall were subjected to the temperature difference conditions for automatic opening, shear damage was more likely to occur than tensile damage. From the results, the following conclusions were obtained: The developed mechanical model of fracture opening reflects the mechanism of fracturing at the borehole wall and the fracture wall during HDR fracturing, thereby revealing the mechanism of the formation of fracture networks under thermal stress. For HDR fracturing, thermal stress promotes the formation of branch fractures in the fracture wall and increases the occurrence of complex fractures in the near-well region. Under thermal stress, the main fractures are less likely to extend in the optimal direction but instead tend to develop into complex fractures, which is not conducive to fracture connectivity between wells.
Exploring lived experience of recovery processes in those with schizophrenia: A systematic review with thematic synthesis of qualitative evidence
Authors: Murray Malcolm , Menadue Christopher B. 
Published: May 2022

Abstract
The purpose of the study was to conduct a systematic review of literature which explores lived experiences of the manifestation, appearance of meaning, and interpretation of the recovery process in schizophrenia. Recovery as a lived experience in schizophrenia is an idiosyncratic and debated process that emerges from the perspectives of people who experience schizophrenia. Recovery literature is gained from qualitative accounts and synthesising these accounts provides an overview of the evidence base for recovery. A search of Medline, Emcare, Cinahl and Scopus databases discovered 11 studies that were published between 2016–2020 that met the scope of the review. Studies were included if they used qualitative methodology to explore how individuals with schizophrenia experience the process of recovery. Studies were subjected to quality assessment using the Critical Appraisal Skills Program (CASP) Qualitative Research Checklist. Several themes were identified during the qualitative analysis. These themes were linked by a common thread. This “meta-theme” is “connection.” Connection with individual sense of self and connecting with the social world. Connecting with self enhance the capacity of those with schizophrenia to be able to connect interpersonally and intersubjectively with the social world, which is seen to lead to recovery. The reviewed literature supported the theoretical approach that the person with schizophrenia needed to regain their lost self before taking further steps in the recovery process. Further research of schizophrenia as a self – disorder being phenomenologically designed would further highlight the necessity of this for the recovery process. Such research would illuminate recovery being about who you are and not about how sane or normal you are.
Effectiveness Comparison between Blended Learning of Histology Practical in Flipped Physical Classrooms and Flipped Virtual Classrooms for MBBS Students
Authors: Zhong Jinjie , Li Zhongjie , Hu Xinyang , Wang Linlin , Chen Yingying 
Published: May 2022

Abstract
Background
The flipped classroom blended learning model has been proven effective in the teaching of undergraduate medical courses as shown by student acceptance and results. Since COVID-19 necessitated the application of online learning, the effect of the blended learning model on teaching quality has required additional attention.
Methods
The objectives of this study were to reproduce a blended learning model flipped in a virtual classroom (FVCR-BL) in 2020 (N = 146) and a physical classroom (FPCR-BL) in 2021 (N = 93), and to evaluate their effects and student perceptions compared to a traditional learning model in a physical classroom (PCR-TL) in 2019 (N = 89).
Results
The results clarified that FPCR-BL students obtained higher final exam scores and were more likely to engage in face-to-face interactions with instructors than FVCR-BL students. FPCR-BL and FVCR-BL students had higher classroom quiz scores than the PCR-TL students owing to the contribution of blended learning. The results of the questionnaire showed that participants of FPCR-BL positively rated the online learning and preview test, with a cumulative percentage of 68.31%, were more satisfying than other learning activities of blended learning. There were significant correlations (r = 0.581, P < 0.05) between one factor (online learning) and the other three blended learning strategies.
Conclusions
In the flipped classroom with a blended learning process of histology, enhancing the quality of online learning boosts student satisfaction and improves knowledge learning; peer-to-peer interactions and instructor-to-peer interactions in the physical classroom improved knowledge construction.
Effect of Bacillus amyloliquefaciens LSG2-8 on the intestinal barrier function of Rhynchocypris lagowskii
Authors: Yu Meng nan , Zhang Yu rou , Zhang Dong ming , Wang Qiu ju , Wang Gui qin , Mahmound Elsadek , Yao Qi , Chen Yu ke , Guo Zhi xin 
Published: May 2022

Abstract
Probiotics have been widely used in aquaculture. This article aims to study the effect of Bacillus amyloliquefaciens LSG2-8 on the intestinal barrier function of Rhynchocypris lagowskii. B. amyloliquefaciens LSG2-8 were added to R. lagowskii basal diets (CK) as additives at four concentrations: 1.0 × 106 (D−6), 1.0 × 107 (D−7), 1.0 × 108 (D−8) and 1.0 × 109 (D−9) CFU/g by dry weight of basal diet. After a 56 days feeding experiment, the intestinal digestive enzymes and immune enzymes activity of R. lagowski on group D-6, D-7, D-8 and D-9 diet were significantly higher than the control (p < 0.05). In molecular experiments, we found that the levels of TGF-β mRNA, IL-10 mRNA, ZO-1 mRNA and Claudin-3 mRNA in group D-8 R.. lagowskii were significantly higher (p < 0.05) than the control and other groups. Furthermore, the levels of IL-1β and IL-8 mRNA of R. lagowski on group D-6, D-7, D-8 and D-9 diet were significantly lower than the control (p < 0.05). In addition, we found that B. amyloliquefaciens LSG2-8 can regulate the intestinal flora balance and improve the intestinal structure of R. lagowskii. In conclusion, B. amyloliquefaciens LSG2-8 can improve the intestinal barrier function of R. lagowskii,and can be used as a feed additive in aquaculture.
Identifying groundwater contaminant sources based on the hybrid gradient grey wolf algorithm and deep belief neural network
Authors: Li Jiuhui , Wu Zhengfeng , He Hongshi , Lu Wenxi 
Published: May 2022

Abstract
Optimization models used to identify groundwater contamination sources (GCSs) often have many variables to determine and a high degree of nonlinearity. When the grey wolf optimization algorithm (GWO) is used to solve this kind of optimization model, due to the relatively weak local search ability, it has the disadvantage of premature convergence. To improve the GWO, the gradient descent algorithm (GDA) and the GWO were integrated to construct a hybrid gradient GWO (HGWO) with little dependence on the initial value and a strong local search ability. The HGWO was then applied to solve the optimization model without falling into premature convergence, which improved the accuracy of the GCS identification results. In addition, the calculation load generated was reduced by calling the simulation model, and computing time was saved in the process of solving the optimization model. A surrogate model of the numerical simulation model was established by applying a deep belief neural network (DBNN) to participate in the iterative calculation. The results show that compared with the simulated annealing algorithm (SA) and GWO, the HGWO had higher calculation accuracy and could improve the identification accuracy of GCSs. Although the calculation efficiency of the HGWO was insufficient, the improvement in solution accuracy was sufficient to overcome this shortcoming. The DBNN surrogate model had high accuracy and could save 99% of the computing time by participating in the iterative calculation instead of the simulation model.
The emerging burden of chronic diseases, disease-stratified exploration and gender-differentiated healthcare utilisation among adult patients in Bangladesh
Authors: Mahumud Rashidul Alam , Mosharaf Md Parvez , Kundu Satyajit , Rahman Md. Ashfikur , Dukhi Natisha , Shahajalal Md , Mistry Sabuj Kanti , Alam Khorshed , Gow Jeff 
Published: May 2022

Abstract
Background: Chronic diseases are considered one of the major causes of illness, disability and death worldwide. Chronic illness leads to a huge health and economic burden, especially in low- and middle-income countries. This study examined disease-stratified healthcare utilisation (HCU) in adult Bangladesh patients with chronic diseases from a gender perspective.Methods: Data from the nationally representative Household Income and Expenditure Survey 2016-2017 consisting of 12,005 patients with diagnosed chronic diseases was used. Gender differentiated chronic disease stratified-analytical exploration was performed using logistic regression to identify the potential factors for higher or lower utilisation of healthcare services after step-by-step adjusting for independent confounding factors.Results: The five most prevalent chronic diseases among patients were gastric/ulcer (Male/Female (M/F):16.77% / 16.40%), arthritis/rheumatism (M/F:13.70% / 13.86%), respiratory diseases/asthma/bronchitis (M/F: 12.09% / 12.55%), chronic heart disease (M/F: 8.30% / 7.41%), and blood pressure (M/F: 8.20% / 8.87%). Eighty-six percent of patients with chronic diseases utilised health care services during the previous 30 days. Although most patients received outpatient healthcare services, a substantial difference in HCU among employed male (53%) and female (8%) patients were observed. Chronic heart disease patients were more likely to utilise health care than other disease types for both genders while the magnitude of HCU was significantly higher in males (OR = 2.22; 95% CI:1.51-3.26) than their female counterparts (OR = 1.44; 1.02-2.04). A similar association was observed among patients with diabetes and respiratory diseases.Conclusion: Emerging burden of chronic diseases were observed in Bangladesh. Patients with chronic heart disease utilised more healthcare services than patients experiencing other chronic diseases. The distribution of HCU varied by patient’s gender for the empolyment status. Risk-pooling mechanisms and access to free or low-cost healthcare services among the most disadvantaged people might enhance their universal health coverage.
Milk proteins as a feed restriction signature indicating the metabolic adaptation of dairy cows
Authors: Leduc A. , Guillou S. Le , Bianchi L. , Correia L. Oliveira , Gelé M. , Pires J. , Martin P. , Leroux C. , Provost F. Le , Boutinaud M. 
Published: May 2022

Abstract
Milk production in dairy cows is affected by numerous factors, including diet. Feed restriction is known to have little impact on milk total protein content but its effect on the fine protein composition is still poorly documented. The objective of this study was to describe the effects of two feed restriction trials of different intensities on the milk protein composition of Holstein cows. One restriction trial was short and of high intensity (SH), the second was long and of moderate intensity (LM). Feed restriction decreased the milk protein yield for caseins under the LM trial and of all six major milk proteins under the SH trial. These decreased yields lead to lower concentrations of αs1-, αs2- and β-caseins during the SH trial. The milk proteome was affected as a function of restriction intensity. Among the 345 proteins identified eight varied under the LM trial and 160 under the SH trial. Ontology analyses revealed their implication in carbohydrate, lipid and protein metabolisms as well as in the immune system. These proteins reflected adaptations of the animal and mammary gland physiology to feed restriction and constituted a signature of this change.
Primary, Dural-Based, Ewing Sarcoma in a Pediatric Patient: Presentation of a Rare Tumor Entity with Literature Review
Authors: GULER Ali , SENOL Yigit Can 
Published: May 2022

Abstract
Primary Ewing's sarcoma originating from the calvaria bone and/or underlying Dural involvement has been reported relatively rarely in the literature. Those originating from the dura and invading the bone above it in both directions, both towards the brain parenchyma and via the dura, are even rarer.CASE DESCRIPTION: We present a case of a 14-year-old girl with no known focal neurological deficit who presented with the complaint of vertigo for only 2 months. In neuroradiological examination, The left frontoparietal region of the brain showed the presence of a tumor originating from the dura, invading both bone and brain parenchyma. No other tumor location was discovered after radiological examination. Since the patient had a shift in the brain and progressive loss of strength on the right side, the patient was taken to surgery for tumor excision. The frozen result sent per-operatively was consistent with a round blue cell tumor. Adjuvant chemotherapy treatment was given to the patient after the definitive pathology report was compatible with Ewing's sarcoma. CONCLUSION: The patient had an uneventful neurological recovery without permanent neurological deficit. When the patient was kept under close clinical and radiological surveillance one year after the operation, no recurrence of the disease was observed. Bone marrow biopsy results and pet computerized tomography results confirmed the case of primary intracerebral Ewing sarcoma. This case illustrates an extremely rare location of primary Ewing's sarcoma with a set of clinical signs and symptoms extremely rare for this location of this rare disease entity.