bluuebunny/crossref_metadata_2025 huggingface dataset:
Low sensitivity of chromogranin A in the diagnosis of insulinoma: a single-center study
Authors: Yukina Marina Y. , Troshina Ekaterina A. , Nuralieva Nurana F. , Rebrova Olga Y. , Nikankina Larisa V. , Mokrysheva Natalia G.
Published: October 2024

Background: Insulinoma is a neuroendocrine tumor (NET), with its main clinical manifestation being the hypoglycemic syndrome. The symptoms of hypoglycemia are nonspecific, and therefore, in most cases, the diagnosis is made untimely. The Russian clinical guidelines for the diagnosis and treatment of NET suggest as a diagnostic test that the universal circulating marker of all NET, chromogranin A (CgA) be determined. However, the literature data on the sensitivity of CgA in the diagnosis of insulinoma are contradictory.
Aim: To evaluate the diagnostic effectiveness of the CgA test in the diagnosis of insulinoma.
Materials and methods: This was a hospital-based single-center, cross-sectional comparative (first step) and prospective non-comparative (second step) study conducted from 2016 to 2022. During the first part of the study, we determined serum CgA in 120 patients with suspected non-diabetic hypoglycemia and compared its levels in the patients with and without confirmed insulinoma (n = 87 and n = 33, respectively). During the second study step, CgA was measured in the insulinoma patients at 6 [4.0; 7.0] months after surgery. The CgA levels at baseline and post-surgery were analyzed in 74 patients (those with recurring non-diabetic hypoglycemia were excluded from the analysis).
Results: In the study subjects without insulinoma, the median CgA level was 0.7 [0.5; 1.1] (range, 0.1 to 2.0) nmol/l and the difference (with Bonferroni adjustment) from its levels in the patients with insulinoma before surgery was non-significant (1.0 [0.7; 1.4], range, 0.1 to 8.5 nmol/l, р = 0.045). The CgA concentration in the insulinoma patients after surgery was 0.9 [0.7; 1.2], range, 0 to 1.9 nmol/l and significantly differed from that at baseline (1.0 [0.7; 1.4], range, 0.1 to 8.5 nmol/l, p = 0.012, Wilcoxon test). In the patients with insulinoma before surgery the CgA levels exceeding the generally accepted reference range ( 2 nmol/l) was found in 11.5% (n = 10), with its median level of 2.5 [2.3; 4.1], range 2.3 to 8.5 nmol/l. There were no significant associations between the CgA levels and localization, tumor numbers, their size and malignization grade, insulin and proinsulin values, and duration of fasting. The sensitivity and specificity of the CgA test were 12% [95% confidence interval [CI]: 6%–20%] and 100% [95% CI: 97%–100%], respectively. The prognostic value of a positive result (PVPR) was 100% [95% CI: 69%–100%] and the prognostic value of a negative result (PVNR) 30% [95% CI: 28%–32%].
Conclusion: As a diagnostic test, CgA has high specificity and prognostic value of a positive result. However, the uncertainty of the prognostic value of a negative result is unacceptably high. A special study is required to clarify the operational characteristics of CgA in insulinoma.
Is the Romer Hypothesis valid for Newly Industrialized Countries? Evidence from panel ARDL
Authors: Çelik Hüseyin , Alev Nigar , Erdemli Muhyettin
Published: October 2024

Purpose ― This study investigates the effect of trade openness on inflation, referred to as the Romer hypothesis, for Newly Industrialized Countries (NICs) from 1990 to 2022.Methods ― It uses a panel ARDL method and the Dumitrescu-Hurlin (2012) causality test. Economic growth, credit, and money supply are included in the model as independent variables. Findings ― The findings reveal no statistically significant long-term and short-term relationships between trade openness and inflation. However, money supply has statistically significant positive effects on inflation in the long run, while economic growth and credit exhibit no statistically significant impact. In the short run, money supply and economic growth reduced inflation. According to the Dumitrescu-Hurlin (2012) panel causality test, a bidirectional relationship exists between inflation and economic growth, money supply, and credit, while a unidirectional relationship is observed between inflation and trade openness. Implications ― Reducing the external dependency of sectors that rely on imported inputs is necessary to mitigate the adverse effects of trade openness on inflation in NICs. It is crucial to ensure that monetary policy helps align money supply and credit expansions with real sector trends.Originality ― This research is pioneering in its focus on testing the Romer hypothesis for Newly Industrialized Countries (NICs).
Skill bias in the labour market: Evidence from Iran
Authors: Mohebi Mehdi , Komijani Akbar
Published: October 2024

Purpose ― Most global economies are dealing with the issue of skill bias. In developing and underdeveloped countries, skill bias poses a problem by preventing the educated from participating in the economy's production function, especially in the long run. This paper expands on the skill-wage relationship and investigates this issue in the case of Iran from 1981 to 2021.Methods- Applying Impulse Responses from VECM and the Structural VAR model separates the relationship between skill and wage into short- and long-term effects. The structural wage model was estimated using the structural vector auto-regression model.Findings ― The results show that skill played a significant role in wage determination only for three periods in the short run, and the effect was neutral in the long run. This means that skill accumulation through advancement in graduate and postgraduate study is unlikely to increase wages in the long run.Implication ― According to the findings, skill bias implies that education attainment in the Iranian labour market can only improve wages to a minimum extent. This also proves that factors other than education determine wage growth in the economy. Originality ― The skill-wage relationship has not been a focus of studies in education outcome fields. Moreover, in the case of Iran, this investigation is novel, and there is a lack of studies on the relationship between compensation and skill.
Modeling of low-frequency acoustic NDE to detect delaminations in multilayer polymer-composite structures
Authors: Hsyung Chang Shun , Shevtsov Sergey , Chebanenko Valeriy , Snezhina Natalie
Published: October 2024

The article experimentally and numerically investigates the effectiveness of low-frequency acoustic nondestructive evaluation (NDE) and the localization of possible delaminations in a multilayered carbon fiber reinforced plastic (CFRP) panel with transverse isotropy of the material. The experiments were carried out on a flat square panel, where wave motions were excited by a disk-shaped omnidirectional piezoelectric (PZT) actuator placed at the center of the 2 mm-thick panel and artificially created circular delaminations, with diameters of 1.5 and 3 cm, were located along the diagonals of the square at a distance of 22 cm from the center. The dispersion analysis of antisymmetric (A0) and symmetric (S0) Lamb waves and horizontally polarized shear waves (SH0) for such a panel, with given engineering constants, and subsequent finite element (FE) study showed that only A0 waves generated at sound frequencies can be used for delamination diagnostics by registering of out-of-plane velocities at surface points of the tested structure using a simple laser vibrometer. It is shown that due to sufficient sensitivity, noise immunity, and reliability, the proposed method of acoustic testing of thin-walled composite parts can be effectively used in production conditions.
Population assessment of the Endangered Forty-spotted Pardalote Pardalotus quadragintus on Maria Island, Tasmania
Authors:   Ross Analytics Pty Ltd, 1 Lynden Road, Bonnet Hill TAS 7053, Australia, Reid Keith ,   Institute of Marine and Antarctic Studies, University of Tasmania, 20 Castray Esplanade, Battery Point, Hobart TAS 7004, Australia, Bryant Sally ,   School of Natural Sciences, University of Tasmania, Hobart TAS 7001, Australia, Baker G. Barry ,   Institute of Marine and Antarctic Studies, University of Tasmania, 20 Castray Esplanade, Battery Point, Hobart TAS 7004, Australia,   Latitude 42 Environmental Consultants Pty Ltd, 114 Watsons Road, Kettering TAS 7115, Australia,   Research Institute for the Environment and Livelihoods, Charles Darwin University, Darwin NT 0909, Australia, Bok Erin ,   School of Natural Sciences, University of Tasmania, Hobart TAS 7001, Australia, Hingston Andrew ,   School of Natural Sciences, University of Tasmania, Hobart TAS 7001, Australia
Published: October 2024

The Forty-spotted Pardalote Pardalotus quadragintus is one of the smallest birds in Australia and is endemic to Tasmania, where it occurs only in forest or woodland containing White Gum Eucalyptus viminalis. It is listed as Endangered under the Tasmanian Threatened Species Protection Act 1995 and Commonwealth Environment Protection and Biodiversity Conservation Act 1999. A habitat-stratified survey of Forty-spotted Pardalotes on Maria Island, off the eastern coast of Tasmania, was undertaken in August 2023 to provide a robust estimate of the population. Initial stratification using available vegetation mapping overestimated the availability of suitable habitat based on survey-site habitat evaluations. Forty-spotted Pardalotes were detected at 14 of 74 survey sites, with all detections being at sites where White Gum was the main tree species present. Their mean density was 1.66 birds per hectare, with an estimated total population of 847 birds (CV 0.38, confidence intervals 404–1776 birds). This estimate is consistent with previous uncorrected count-based estimates, although comparisons with historical counts are highly subjective given the substantial methodological differences. Only ~5% of Maria Island supports the preferred habitat for this species and further research on the requirements for, and abundance of, suitable microhabitat is recommended to further refine population estimates and guide conservation management actions.
Monkeypox Virus and Vaccinia Vaccines: Genomic and Antigenic Differences Relevant to Outbreaks and Vaccinology
Authors: Shen-Gunther Jane , Cai Hong , Wang Yufeng
Published: October 2024

Amid the current multi-country mpox outbreak, analyzing monkeypox virus (MPXV) and vaccinia virus (VACV) genomes is vital for understanding evolutionary processes that may impact vaccine efficacy and design. This study aimed to elucidate the phylogenetic relationships and structural features of viral antigens, which are crucial for developing effective vaccines. By aligning 1,903 MPXV genomes from the NCBI Virus repository (released between 2022 and 2024), an increase in phylogenetic diversity was observed compared to previous studies. These genomes grouped into Clade I (25 genomes) and Clade IIB (1,898 genomes), with a new Clade I sub-lineage emerging from samples collected in Sud-Kivu province, Democratic Republic of the Congo. Homology-based modeling of six key neutralization determinants encoded by the highly conserved Clade I MPXV genes revealed several amino acid variants near potential antibody binding sites compared to those of vaccinia and variola virus templates. Despite these structural differences, the long-standing vaccinia vaccines, initially created for smallpox, still play a crucial role in safeguarding humanity against mpox today. The findings have deepened our understanding of disparate evolutionary mechanisms for MPXV and VACV, influencing vaccine efficacy. The workflows for viral genomic analysis and structural modeling in CLC Genomics Workbench will facilitate MPXV research and vaccinology. Finally, this study highlights the critical role of MPXV metagenomic surveillance in identifying viral evolution and potential vaccine resistance.
New Advances on the Dispersive and Polar Surface Properties of Poly(styrene-co-butadiene) using Inverse Gas Chromatography
Authors: Hamieh Tayssir
Published: October 2024

The dispersive and polar properties of materials, and especially of polymers and copolymers play an important role in several engineering applications implying their surfaces and interfaces. The surface energetic properties of poly(styrene-co-butadiene) have never been studied. We proposed in this study an accurate determination of such properties by using the inverse gas chromatography (IGC) at infinite dilution. Background: The IGC surface technique led to the dispersive and polar properties of poly(styrene-co-butadiene) rubber (SBR) by adsorption of organic solvents at various temperatures. Methods: Our new methodology based on the thermal Hamieh model and the London dispersion interaction energy was used to determine the London dispersion surface energy, the polar acid-base surface energy, and the Lewis acid-base properties of the copolymer. Results: The different surface energy parameters of the SBR were obtained as a function of temperature from the chromatographic measurements. Conclusions: The dispersive and polar free energies of adsorption of the various n-alkanes and polar molecules on poly(styrene-co-butadiene) were determined at different temperatures. A decrease of the London dispersive surface energy and the polar Lewis acid-base surface energies of SBR was highlighted when the temperature increased. It was showed a Lewis amphoteric character of poly(styrene-co-butadiene) with a highest basic constant 10 times larger than its acidic constant.
Geometry of Triadic Harmony
Authors: Venkatesh Unnathi
Published: October 2024

This paper explores the intersection of geometry and music, investigat- ing how mathematical structures shape musical theory, composition, and perception. It begins by examining the geometric foundations of pitch organization, including the circular representation of pitch classes and the tonal space. We then explore rhythmic structures through symmetry, analysing how patterns in time are geometrically conceived. Finally, the study examines more recent developments in computational music theory, such as the use of topological data analysis to model musical transformations and voice leading.
Data Augmentation of Breast Ultrasound Images Using Wasserstein Generative Adversarial Networks
Authors: Diyasa I Gede Susrama Mas , Humairah Sayyidah , Puspaningrum Eva Yulia , Durry Fara Disa , Lestari Wahyu Dwi , Caesarendra Wahyu
Published: October 2024

Breast cancer is among the most prevalent cancers in Indonesia. One of the methods for early detection of breast cancer is utilizing ultrasound images to classify breast conditions into normal, benign tumors, or cancer. The advent of deep learning technology facilitates the image analysis process, such as the use of Transfer Learning Convolutional Neural Networks (CNNs). Generally, CNN models require large and balanced datasets to perform well in classification tasks. However, medical datasets like breast ultrasound images tend to be limited and imbalanced. The Wasserstein GAN (WGAN) is a generative data augmentation method capable of producing synthetic images by learning the pattern of the distribution of real image data. The implementation of the Wasserstein distance results in the training process of WGAN demonstrating stability from epochs 3000, 2500, and 3000 out of a total of 5000 epochs. The quality of the synthetic images improves with an increasing number of training iterations. By using WGAN, all of the evaluation metrics of each classifier are increasing, with the best accuracy score is achieved by VGG16 model with 83.33% accuracy
HUBUNGAN PENGETAHUAN K3 DAN PENGAWASAN TERHADAP UNSAFE ACTION PEKERJA KONSTRUKSI PT X
Authors: Fauzi Rachmawati Prihantina , Pinogoro Gumilar Bagus , Chahyadhi Bachtiar
Published: October 2024

Pekerjaan konstruksi merupakan pekerjaan beresiko tinggi karena memiliki berbagai macam risiko bahaya yang dapat menyebabkan kecelakaan kerja. Kecelakaan kerja dapat disebabkan karena berbagai faktor, namum 80% kecelakaan kerja disebabkan karena unsafe action. Berdasarkan hasil survei awal pernah terjadi kecelakaan kerja karena unsafe action yang disebabkan karena kurangnya pengetahuan serta pengawasan pada pekerja konstruksi. Penelitian ini bertujuan untuk mengetahui hubungan pengetahuan K3 dan pengawasan dengan unsafe action. Metode yang digunakan merupakan observasional analitik dengan pendekatan cross sectional. Teknik sampling yang digunakan adalah total sampling. Jumlah sampel yang digunakan adalah 85 orang. Penelitian ini menggunakan kuesioner yang dianalisis secara bivariat menggunakan Somers’d dan multivariat menggunakan uji regresi logistik ordinal. Analisis data dilakukkan dengan menggunakan software SPSS versi 25.Hasil penelitian menunjukan mayoritas reponden memiliki pengetahuan K3 kurang (55,3%) dan pengawasan cukup (50.6%) dengan Tingkat unsafe action tinggi (43,5%). Hasil uji korelasi somers’d menunjukan adanya hubungan antara pengetahuan K3 dengan unsafe action (p = 0,001, r = -0,491 ) danjuga adanya hubungan signifikan antara pengawasan dengan unsafe action (p =0,001, r = -0,528). Hasil uji regresi logistik ordinal menujukan bahwa pengawasan memiliki kekuatan korelasi lebih besar (wald=17.624) dalam unsafe action dibandingkan pengetahuan K3 (wald=11.119).
HUBUNGAN ANTARA KECERDASAN EMOSIONAL DENGAN STRES KERJA PERAWAT ICU DAN IGD DI RUMAH SAKIT X BANYUWANGI
Authors: Imama Ullya Nur , Dwiyanti Endang
Published: October 2024

Stres kerja adalah suatu bentuk adaptasi terhadap ketidaksesuaian individu dengan lingkungan kerjanya. Stres kerja yang terjadi pada perawat dapat mempengaruhi keselamatan dan kesehatan kerja. Penelitian ini bertujuan untuk mengetahui hubungan karakteristik dan kecerdasan emosional dengan stres kerja pada perawat ruang IGD dan ICU di Rumah Sakit X di Banyuwangi. Penelitian ini merupan penelitian kuantitatif dengan desain cross sectional. Sampel dalam penelitian ini merupakan total populasi. Hasil penelitian ini adalah variabel jenis kelamin (p value 0,043), umur (p value 0,017), masa kerja (p value 0,002), dan kecerdasan emosional (p value 0,027) mempunyai nilai p value < 0,05. Kesimpulan dari penelitian ini bahwa variabel jenis kelamin, umur, masa kerja, dan kecerdasan emosional berhubungan terhadap stres kerja perawat IGD dan ICU di Rumah Sakit X di Banyuwangi.
Sindrome de burnout y ansiedad en contexto de pandemia por COVID-19 en personal del sistema de transporte asistido de Emergencias EsSalud 2023
Authors:   , Galdos Hurtado Juan Elias
Published: October 2024

Objetivo: Determinar la relación entre el síndrome de burnout y ansiedad en contexto de pandemia por COVID-19 en personal del sistema de transporte asistido de emergencias EsSalud 2023. Métodos: Estudio observacional, correlacional y transversal, con una muestra de 99 trabajadores en abril de 2023. Se aplicaron dos cuestionarios, para la variable síndrome de burnout “Cuestionario Maslach Burnout Inventory (MBI)” y en la variable ansiedad “Escala para el trastorno de ansiedad generalizada (GAD-7)”. Para el análisis de datos se utilizó la prueba Rho de Spearman y regresión lineal múltiple. Se obtuvo aprobación de Comité de ética. Resultados: El 87.9% de los trabajadores tuvieron un nivel bajo de síndrome de burnout, el 44.4% de trabajadores presentaron ansiedad y de ellos el leve fue más frecuente. En el análisis bivariado se demostró que existe relación directa entre el síndrome de burnout y ansiedad (Rho=0.565; p=0.000). Al analizar las dimensiones de síndrome de burnout se observó que el agotamiento emocional (Rho=0.658; p=0.000), la despersonalización (Rho=0.455; p=0.000) y la realización personal (Rho=-0.239; p=0.017) se relacionaron con la ansiedad. En el análisis multivariado se observó que el síndrome de burnout influye en la ansiedad, incluso ajustado por edad, sexo, grado de instrucción, antecedente familiar de COVID-19 y categoría profesional. Conclusiones: Existe relación directa entre el síndrome de burnout y la ansiedad en el personal del sistema de transporte asistido de emergencias EsSalud 2023. Se requiere impulsar estrategias de promoción de la salud mental laboral hacia el manejo de ansiedad y síndrome de burnout.
Artificial Lift Failures and Operational Challenges in a Chemical EOR Field - A Comparative Analysis of Sucker Rod Pumps and Electric Submersible Pumps
Authors: Hoy M. , Derler M. , Lobianco L. , Knauhs P. , Marschall C.
Published: October 2024

OMV Austria E&P looks back on more than a decade of polymer flooding in one of its mature oil fields within the Vienna basin. Rapidly increasing material prices and longer delivery times put especially the chemical Enhanced Oil Recovery (EOR) operators under pressure. Production improvement and run life optimization of Artificial Lift (AL) systems are two key aspects to enhance the cost effectiveness of their brown fields. In OMV Austria, the operation of Sucker Rod Pumps (SRPs) in polymer back producing fields is a standard technology, while Electrical Submersible Pumps (ESPs) still represent a novelty in this special application.

Both the success of design adaptations and operational challenges over a decade of polymer flooding got reviewed. Special attention was drawn to the potential negative effects of the non-Newtonian back produced polymer. In addition, internal tear-downs of all pulled pump installations rendered valuable data for the subsequent root cause analysis on the most common failure mode.

The comparison of failures in polymer back producing versus conventional AL systems in OMV Austria showed a significant increase in corrosion and wear failures in polymer wells. For both SRPs and ESPs remedial actions were defined in order to elongate the run life of the installations. Furthermore, the necessity for design adaptations could be validated and further optimized.

The presented analysis supports the pilot scope of the ESP wells with more information and clearly demonstrates that ESPs can be used in future polymer development projects within the OMV Group. Addressing the operational and run life challenges effectively leads to improved oil recovery rates and extended reservoir life, making polymer waterflooding a viable EOR option for mature oil fields.
Case Study on Digital Surface Controlled Gas Lift for Unconventional and Mature Fields
Authors: Shaw Joel
Published: October 2024

Objectives / Scope

A new surface controlled gas lift technology focused on cost sensitive applications has been recently developed and deployed the Permian Basin of West Texas. This paper will describe the new technology, summarize the installation process, and discuss its relevance to other unconventional, onshore, and mature field applications.

Methods, Procedures, and Processes

This discussion initially summarizes the advantages this new iteration of digital surface controlled gas lift offers over more traditional gas lift methodologies. That is followed by a description of a recent unconventional installation highlighting additional advantages. It further offers considerations that drive a successful installation. That leads directly to other applications appropriate for this technology.

Results, Observations, and Conclusions

The successful installation showcases the intersection of engineering and field experience. Exposure to a broad spectrum of environments has built an understanding of the elements and features critical to specific applications. Lessons learned from extensive installations and designs have helped hone this tool into one that caters to unconventional and mature assets. Vast field experience has guided the processes and preparation required to implement a successful implementation. This has now been proven by the successful implementation of the technology in an unconventional application and holds true for challenging applications worldwide.

Novel/Additive Information

Surface controlled gas lift systems have been installed in premium wells all over the world. However, this case study and the new surface controlled gas lift system provide an example and opportunity to expand this technology to a broader set of wells in unconventional and mature fields.
Techno-Commercial Study for Selecting Efficient Artificial Lift Method
Authors: Ghamdi Ahmed Khalid. , Sumananda Chrysostom. , Partadiwirya Rusam. , Rivera Villarreal Leigber Eduardo.
Published: October 2024

Gas Lift and Electric Submersible Pump (ESP) are two well-established techniques used to increase or restore oil wells production. Both methods are commonly utilized in the industry and each approach has its own set of benefits and drawbacks. The decision regarding which one to use is based on various technical and commercial factors.

This study offers a comprehensive comparison of gas lift and ESP based on critical technical attributes such as well depth, reservoir pressure, and fluid properties, as well as commercial factors like installation cost, operating cost, and maintenance cost. The aim of this analysis is to provide a detailed evaluation of the two methods and establish a clear understanding of their suitability for specific applications. The study also investigates the economic feasibility of each method by analyzing their production rates, energy efficiency, and overall return on investment.

Gas lift is a widely used method for wells with low-to-medium depth and low-to-medium reservoir pressure. Gas lift has low installation costs, requires minimal maintenance, and is relatively energy-efficient. However, it may not be suitable for wells with high water cut or high viscosity fluids.

ESP, on the other hand, is a commonly used method for wells with high depth and suited to handle any water cut. The installation costs associated with ESP are considerable, and the system requires regular maintenance to function optimally. Additionally, ESP consumes a significant amount of energy. However, it can provide high production rates but cannot handle high gas-to-oil ratios and viscous fluids.

Ultimately, the choice between gas lift and ESP depends on a thorough evaluation of the technical and commercial factors specific to each well. Factors such as well depth, reservoir pressure, fluid properties, installation cost, operating cost, and maintenance cost must be considered to determine the most suitable method for the well.
Using Rolling Survivability and MTTF for Tracking the ESP Performance and Reliability and Identify Promptly the Continuous Improvement Plans
Authors: Wang F. , Suarez L. , Chacon E. , Savarimuthu J. , Guiter K. J. , Shang S.
Published: October 2024

"What gets measured gets improved."

There are many different methods in the industry in measuring the ESP performance. Average run life for active ESPs and/or for inactive ESPs and/or for all ESPs is a simple method to calculate average run life for a certain population but the result maybe misleading especially it maybe change up and down greatly due to high or low frequency of new installations. MTBF or MTTF method is preferred by some companies but the result maybe misleading too. MTBF or MTTF is not service life and the calculation assumed constant ESP failure rate which is not a reality. It is therefore difficult to understand real ESP performance subsequently hard to identify areas of improvement.

The Kaplan Meier method is another widely used one in reliability analysis. The MTTF is calculated as the total area under the Kaplan Meier curve. This paper uses the same method but for a basis of rolling datapoint, plotting R(90), R(180), R(270) and R(365) monthly progression. The trend could indicate the reliability improvement over time or at specific period due to specific in ESP applications. It could also visualize the deterioration of the reliability due to improper way of operating the ESP. 1 year data rolling is used for reflecting better the changes of R(90) and R(180). 2 years rolling data is recommended for R(270) and R(365). This new reliability metrics for ESP performance analysis has been successfully used in US Land.

Raw data would need to be extracted from business system or local tracking database. This should include as many details as possible, such activity date, pull date, customer, county, depth, casing information, Pump/Motor/completion types, BHT, well conditions etc. Upon calculation after process the raw activity data, the monthly evolution of the R(t) over time since January 2020 are plotted out. Such graph visualizes the changes of reliability until May 2024, at the time of the paper is being drafted.

By analyzing the rolling R(t), directions of improvements are clear, and area of improvements then can be promptly identified with the common tools and methodologies such high tier DIFA.

Some operators changed the fracking process after they acquired the asset from previous operator. The reliability dropped and stayed at much lower level for all R(180), R(270) and R(365), due to the heavy wear from much more sand production. The comparison of reliability before and after the acquisition, and among peers in the same region are presented clearly that the need of review the fracking service and technology of sand avoidance, and upgrade the ESP metallurgy so as to improve the longevity of the ESP.

Some operators where there is large volume of installations monthly improved the ESP reliability over the time continuously, through successfully implementation of new technologies, DIFA and engineering upgrades/improvements.
An Artificial Intelligent Cutting-Edge Technology for Automated Field Production Optimization & ESP Failures Prediction
Authors: El Sherbeny W. I. , Denver L. , Rameraize S. , Azzaz R. , Sobhi S. , Al Aseef S.
Published: October 2024

Unpredicted an Electrical Submersible Pump (ESP) failure can have a serious impact on well production and overall field economics; therefore, it is important to reliably predict the starting time of damaging operating conditions and take proactive action to prevent early failure of an ESP. Most operators rely mainly on production engineers to monitor and optimize equipment performance with remote monitoring and surveillance technologies that provide threshold-based diagnostics to detect electrical or mechanical problems. Due to fundamental constraints in exception-based monitoring, it is extremely difficult to reliably predict the root cause of equipment failure and remaining useful life (RUL) of an ESP.

Methods, Procedures, Process

Predictive Failure Analysis (PFA) leverages artificial intelligence (AI), statistical and physics-based models to constantly predict Remaining Useful Life (RUL) and possible failure cause. The models are qualified and validated using historical sensor time-series from both running and failed ESPs. The validated models are deployed to predict short-term events that may lead to sudden failure, such as a broken shaft, short-circuit, grounded downhole failure; as well as long-term events which build up over time, such as pump low efficiency, sand, scale deposition and gassy conditions.

Results, Observations, Conclusions

The paper presents a case history for a major operator that was experiencing similar operational challenges in three of its producing assets. unpredicted failures happen frequently since they are hard to predict ahead of time with the data available to production engineers. This case study demonstrates how Advanced ESP Predictive Failure Analytics (PFA) technology has helped this operator to detect such events and extend ESP run life. For one ESP, PFA detected scale deposition and predicted a sharp decline in RUL. After confirming the decrease in production fluid, and other surface and downhole sensor trends indicating scale deposition in the ESP, the production engineer applied chemical injection and avoided the failure. For a second ESP in this case study, PFA detected a grounding condition and predicted sudden decline in RUL. The production engineer noticed motor amps increased beyond the recommended threshold and performed electrical optimization to reduce motor amps. The ESP ran for another year and eventually failed due to grounded downhole sensor failure, which PFA had detected two weeks prior to the failure.

Novel/Additive Information

PFA is a unique approach that combines AI, physics-based, and expert knowledge-based approaches to provide interpretable predictions of ESP failure. Unlike traditional CBM approaches, PFA generates fewer alarms with longer lead times, enabling the operator to take preventive measures to avoid sudden failure. In addition, PFA ranks ESPs based on criticality, which enables effective surveillance of large number of wells.
Enhanced Measures and Procedures for Safe Installation and Operation of Electrical Submersible Pumps with Permanent Magnet Motors
Authors: Albori M. M. , Alsayedali A. A. , Balkhair O. M. , Funes M. S.
Published: October 2024

Permanent magnet motor (PMM) applications in electrical submersible pump (ESP) artificial lifting method had been in an increasing trend. This is due to the advantages PMM provides compared with the existing utilized system of induction current motors (ICM). The paper will discuss handling and operational measurements when dealing with permanent magnet motor due to the difference of conventional system of ICM and non-conventional PMM operating principles.

The paper will discuss: different operating principles of ESP motors types used and procedures, measures and precautions used to deal with ESP motors in general and permanent magnet motors in particular during different processes such as installation or uninstallation events. Detailed view will be discussed in the paper covering ESP related motor and electrical system handling procedures. The procedures and processes used are in accordance with industrial approved establishments and organizations standards.

ESP downhole systems consists of different components that can be classified into two main systems: mechanical and electrical systems. The ESP electrical system requires additional auxiliaries’ systems, that includes surface system such as electrical transformers, and variable frequency drive (VFD). The electrical systems are considered one of the most critical system that enables ESP to work properly. Thus, understanding how systems work and differences between motor types and their working principle can help in choosing correct measurement to deal with such systems to complete jobs optimally. Detailed steps and processes during operational events will be discussed to handle ESP electrical systems and permanent magnet motors effectively.

Differentiating between motors types and required systems’ measurements will be discussed to understand the needed processes to complete required jobs in optimum and effective manners.
Direct Differentiation of Human Adult Adipose Tissue into Multilineage Functional Organoids
Authors: Li Qingfeng
Published: October 2024

Current strategies for generating organoids typically relay on intricate in vitro manipulation of dissociated stem cells including the isolation, expansion, and genetic processing of cells, which pose safety and scalability challenges for therapeutic translation. The direct generation of organoids from readily accessible tissues may offer a solution to these issues. Herein, we demonstrate the direct generation of functional organoids representing all three germ layers from human adult adipose tissue without any single-cell manipulation steps. Specifically, we generated reaggregated microfat (RMF) tissues from human adipose tissue using a specialized suspension culture system. These RMF tissues can be converted into mesodermal bone marrow organoids capable of reconstituting human normal hematopoiesis in immunodeficient mice; endodermal insulin-producing organoids able to reverse hyperglycemia in STZ-induced diabetic mice; and ectodermal nervous-like tissues resembling neurons and neuroglial cells. These findings highlight the potential of human adult adipose tissue as a safe and scalable platform for generating diverse clinically-relevant organoids for regenerative therapy.
Economic Impacts and Opportunities in the Health App Industry
Authors: Mukhi Sushree Sangeeta , Tiwari Bhupendra Bahadur , Kuriakose Annu
Published: October 2024

The research paper revolves around the business of health apps across the world and possible impact of the number of users and downloads on the revenue generation of health apps. With the help of trend analysis and linear regression methods, significant impact was studied on the variables like users, downloads and revenue of health apps for past 8 years (N = 8) (2016 to 2023). The downloads (independent variable) didn’t show any significant impact on revenue (dependent variable) where p > 0.05 whereas the users (independent variable) showed a significant impact on revenue (dependent variable) where the p < 0.05. The users of these health apps play a significant role on the business of these health apps by directing impacting the revenue generation, whereas the downloads of these health apps don’t show any impact on the revenue generation of these health apps. The rise in the number of users boosted drastically during the pandemic year 2019 and 2020 and same impact can be seen on the revenue also.
Effective image and data analytics approaches for sub-surface defect detection and identification in composite materials from pulse thermography scans
Authors: Reta Carolina , Rico-Espino Jose-Guadalupe , Rodriguez-Hernandez Gerardo
Published: October 2024

The early detection of internal defects in wind turbine blades made of composite materials is crucial to prevent potential damage that could compromise their structural integrity and performance. Even minor defects, like porosity or fiber misalignment, can significantly affect the blade’s durability and strength, leading to costly maintenance or replacement.
This study examines four common types of sub-surface defects in composite material specimens, such as defective fiber misalignment, inclusion, fiber breakage, and porosity. We utilize a series of thermal images obtained through long-pulse active thermography of samples with induced sub-surface defects. Our approach analyzes the thermal image sequence to capture temperature changes during heat pulse exposure. In this work we present a segmentation method that effectively identifies regions corresponding to sub-surface defects, based on k-means clustering and watershed transform. Furthermore, our approach utilizes principal components projections for the visual identification of sub-surface defects. This valuable data is then fed into a set of machine learning classifiers, enabling their automatic classification. Remarkably, the na¨ıve Bayes classifier excelled in accurately identifying the four distinct types of sub-surface defects in the specimens.
By integrating the proposed segmentation and classification methods, our study enables the comprehensive analysis of sub-surface defects in composite materials, providing significant advancements for quality control in the manufacturing of wind turbine blades. Additionally, our study demonstrates the reliability of the long-pulse active thermography data for identifying and classifying subsurface defects in wind turbine blades.
Removal of amoxicillin employing Fenton-type process using delaminated clay and layered double hydroxides impregnated with Fe or Cu as catalysts
Authors: Lugo Lorena , Diaz John , Contreras Julián , Diaz Sergio , Centeno Miguel , García Juan Carlos Cortés , Moreno Sonia , Celis Crispín , Pérez-Flórez Alejandro
Published: October 2024

The presence of antibiotics in the environment has raised concerns due to their potential negative effects on ecosystems. Conventional water treatment methods are ineffective at removing antibiotics. This study aims to investigate the efficiency of Fenton-like processes catalyzed by delaminated clay and layered double hydroxides impregnated with Fe or Cu for the degradation of amoxicillin. The catalysts were obtained by synthesizing delaminated clay and layered double hydroxides and subsequently impregnating them with Fe or Cu. The characterization of catalysts involved X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray fluorescence (XRF), N2 adsorption-desorption, and X-ray photoelectron spectroscopy (XPS). Catalytic activity was assessed by varying the concentration of hydrogen peroxide, the initial concentration of amoxicillin, and the amount of catalyst. The determination of byproducts was done by high-performance liquid chromatography (HPLC) with a quadrupole time-of-flight mass spectrometer (QqTof). The study found that layered double hydroxides impregnated with Fe or Cu were able to remove 100% of amoxicillin in just 20 min. The study identified 16 byproducts, indicating a degradation process. Under all of the studied conditions, the copper catalysts showed the highest percentage of amoxicillin removal.
Current Status, Hotspots, and Future Directions of Research on the Treatment of Medullary Thyroid Carcinoma: A Bibliometric Analysis and Systematic Evaluation
Authors: Xian Tongcheng , Wang Jie , Li Ruoyin , Yang Minye , Zhang Xuelin , Bie Jun , Luo Yi
Published: October 2024

Background
Medullary thyroid carcinoma (MTC) is a rare neuroendocrine tumor for which some of the current treatments are controversial or still in the preliminary stages of research.
Methods
In this study, we searched the relevant literature in the Web of Science core database from its inception to June 2024. After screening, we performed bibliometric analyses using CiteSpace and Microsoft Excel.
Results
In total, 1694 articles were included in this study. In this field of research, American and Italian institutes lead in the number of papers. Wells SA is the most influential author in this field and J CLIN ENDOCR METAB is the most cited journal. Management, calcitonin, RET gene, surgery, antiangiogenic therapy, tyrosine kinase inhibitors, and peptide receptor radionuclide therapy are the hot research areas in the field of MTC treatment. Prophylactic thyroidectomy, targeted therapy, peptide receptor radionuclide therapy, and positron emission tomography are future research frontiers and global trends.
Conclusions
Research in this field has focused on surgical treatment, targeted therapy, radiotherapy, imaging and treatment management. Based on the results of the bibliometric analysis, a systematic assessment of the current status and future research directions of various treatment options for MTC was conducted, providing new ideas for further research in the field of MTC treatment.
Adult Influenza Vaccination Coverage Before, During and After the COVID-19 Pandemic in Canada
Authors: Chen Ruoke , Gilbert Nicolas L. , Dubé Ève
Published: October 2024

Background
Vaccination prevents seasonal influenza and its complications, particularly among high-risk populations. The COVID-19 pandemic has been reported to impact healthcare behaviors and vaccination patterns. This study aims to assess influenza vaccination coverage and changes in vaccination settings among Canadian adults from the 2018–2019 to the 2023–2024 seasons.
Method
We conducted a retrospective analysis of data from multiple cycles of the Seasonal Influenza Vaccination Coverage Survey (SIVCS). Vaccination coverage was examined across different seasons, stratified by population groups. Odds ratios (ORs) were calculated to compare vaccination likelihoods across seasons, with 2018–2019 serving as the reference. Chi-square tests were applied to determine whether there were significant differences in the place of vaccination since the pre-pandemic season.
Results
When comparing vaccine uptake before, during and after the COVID-19 pandemic, we observed a temporary coverage decline in 2021–2022 season (OR = 0.882, 95% CI = 0.787–0.988) compared to the pre-pandemic season in 2018–2019. By the 2022–2023 and 2023–2024 seasons, vaccination coverage returned to pre-pandemic levels. Coverage among adults aged 18–64 without chronic medical condition consistently remained lower than in other groups. The places of vaccination shifted markedly, with pharmacies becoming the predominant site, increasing from 35.4% in 2018–2019 to 57.4% in 2023–2024, while doctor's offices saw a decline from 32.7–15.2% over the same period.
Conclusion
Our findings highlight the transient effect of the pandemic on flu vaccine uptake in Canada. The increasing use of pharmacies for vaccinations underscores the importance of accessible and convenient vaccination sites. Future efforts should focus on maintaining and improving vaccination coverage through diverse and adaptable vaccination settings.
Examining local truth regimes on flooding and river management in the Lower Missouri River Basin, USA
Authors: Catalano Angela J. , Hall Damon M. , Gentil Gerardo M.
Published: October 2024

Riverine flooding is increasing in frequency and intensity, requiring river management agencies to consider new approaches to working with communities on flood mitigation planning. Communication and information sharing between agencies and communities is complex, and mistrust and misinformation arise quickly when communities perceive that they are excluded from planning. Subsequently, riverfront community members create narratives that can be examined as truth regimes — truths created and repeated that indicate how flooding and its causes are understood, represented, and discussed within their communities — to explain why flooding occurs in their area. To better understand community perceptions of river management related to repeated flooding, we employed a qualitative methodology of semi-structured interviews with 112 community members in 3 communities on the Missouri River, USA. Discourse analysis of the interviews revealed three dominant truth regimes that shape perceptions of river management in these communities: 1) upstream reservoir releases are driven by recreational aims, such as fishing and boating, instead of flood control; 2) endangered species management surpasses other uses; and 3) river navigation for commerce is no longer prioritized. For environmental managers, understanding the truths circulating within communities can help moderate mistrust of and frustration with governing bodies, guide project messaging to disarm false truth regimes, and improve the communication of science and policy.
IOT edge computing layer modification based cyber-attack detection using Federated-Active Learning
Authors: Vinothini J , E Srie Vidhya Janani
Published: October 2024

The Internet of Things and its practical uses are becoming more widespread as the number of connected devices increases, but it always carries a risk to network security. Therefore, it is vital for an IoT network design to rapidly and accurately identify potential attackers. While many proposed solutions focus on secure IoT algorithms, little attention has been given to reducing complexity. To address this gap, this paper proposes an IOT edge computing layer modification based cyber-attack detection edge-cloud architecture that enables quick response by detecting attacks at the Intelligent Buffalo based Secure Edge-enabled Computing layer near their source, offering versatility while decreasing the Cloud’s workload. Additionally, F-AL, a low-complexity multi-attack detection model for deployment at the edge zone, leveraging high accuracy federated active learning approaches, is introduced. The performance evaluation is conducted using the latest BoT-IoT dataset against other Machine Learning and Deep Learning methods which demonstrate that FAL outperforms SVM, FLAD, DL, DNN in terms of accuracy.