bluuebunny/crossref_metadata_2025 huggingface dataset:
Ecogeography of Dioscorea remotiflora Kunth Reveals Its Potential in Regions Already Affected by Climate Change
Authors: Velázquez-Hernández Jocelyn Maira , Ruíz-Corral José Ariel , Durán-Puga Noé , Macías Miguel Ángel , González-Eguiarte Diego Raymundo , Santacruz-Ruvalcaba Fernando , García-Romero Giovanni Emmanuel , Gallegos-Rodríguez Agustín
Published: September 2023

Dioscorea remotiflora, a perennial climbing herbaceous plant wild and native to México, bears tubers of important ethnobotanical and nutritional value. However, the information for its production and use is precarious. The objective of this research was to characterize the adaptation habitats of D. remotiflora in order to determine its ecological descriptors and current distribution, as well as to model its potential distribution. A comprehensive database encompassing 481 geo-referenced accessions was assembled. Using the Agroclimatic Information System for México and Central America (SIAMEXCA), 42 environmental variables were formulated. The MaxEnt model within the Kuenm R-package was employed to predict the species distribution. The findings reveal a greater presence of D. remotiflora in harsh environments, characterized by arid to semi-arid conditions, poor soils, and hot climates with long dry periods. The plant's nutritional and medicinal attributes, combined with its ecological adaptability, suggest its viability within evolving regional cropping systems under the influence of climate change. Niche modeling revealed that seven key variables determine the geographical distribution of D. remotiflora: precipitation of the warmest quarter, precipitation of the driest month, minimum temperature of the coldest month, November-April solar radiation, annual mean relative humidity, annual moisture availability index, and May-October mean temperature. Favorable regions for D. remotiflora coincide with its current presence sites, while other suitable areas, such as the Yucatan Peninsula, Northeast region, and Gulf of México, offer potential expansion opportunities for the species distribution. The characterization obtained for D. remotiflora, together with the description of its edaphic and climatic adaptation habitats, will enable an efficient design of strategies for its use and conservation in the near future.
Targeting Cytochrome P450 Enzymes in Ovarian Cancers: new approaches for Tumour-Selective Interventions
Authors: Al-saraireh Yousef M. , Alshammari Fatemah O. F. O. , Abu-azzam Omar H. , Al-dalain Sa’ed M. , Al-sarayra Yahya M. , Haddad Mansour , Makeen Hafiz , Al-Qtaitat Aiman , Almermesh Mohammad , Al-sarayreh Sameeh A.
Published: September 2023

Over the past decade, significant developments have occurred in treatment strategies for ovarian cancer, yet targeted therapy with few side effects is still a major issue. The cytochrome P450 (CYP) enzyme family plays a vital role in the tumorigenesis process and metabolism of drugs, with a negative impact on therapy outcomes. Gaining more insight into CYP expression is crucial for understanding the pathophysiology of ovarian cancer since many isoforms are essential for the metabolism of xenobiotics and steroid hormones, which drive the disease's development. The purpose of this review is to provide a clear understanding of differential CYP expression in ovarian cancer and its implications for the prognosis of ovarian cancer patients, together with their polymorphisms' effect on chemotherapy metabolism. Finally, we provide our thoughts on opportunities to exploit metabolic CYP expression for novel therapeutic development to treat ovarian cancer.
Improving Precipitation Forecasting in Jilin Province Using Deep Learning and Gaussian Noise
Authors: Yibo Zhang , Chengcheng Wang , Pengcheng Wang , Lu Zhang , Qingbo Yu , Hui Xu , Maofa Wang
Published: September 2023

This paper explores the use of different deep learning models for predicting precipitation in 56 meteorological stations in Jilin Province, China. The models used include Stacked-LSTM, Transformer, and SVR, and Gaussian noise is added to the data to improve their robustness. Results show that the Stacked-LSTM model performs the best, achieving high prediction accuracy and stability. The study also conducts variable attribution analysis using LightGBM and finds that temperature, dew point, precipitation in previous days, and air pressure are the most important factors affecting precipitation prediction, which is consistent with traditional meteorological theory. The paper provides detailed information on the data processing, model training, and parameter settings, which can serve as a reference for future precipitation prediction tasks. The findings suggest that adding Gaussian noise to the dataset can improve the model's generalization ability, especially for predicting days with zero precipitation. Overall, this study provides useful insights into the application of deep learning models in precipitation prediction and can contribute to the development of meteorological forecasting and applications.
A New Low-Cost IoT Based Monitoring System Design for Stand-Alone Solar Photovoltaic Plant and Power Estimation
Authors: Demir Batıkan Erdem
Published: September 2023

This study presents a cost-effective IoT-based remote monitoring system for solar PV energy systems, along with a machine learning-based PV power estimator. Remote access is crucial for tracking PV systems installed in remote areas. In this system, an open-source and IoT-compatible data logger is employed. The data logger collects important performance data of the PV system and transfers it to a server. Real-time visualization of this data is displayed in the designed web and mobile monitoring interfaces. The measured data includes the current, voltage, and temperature information of the PV generator and battery, as well as environmental parameters such as temperature, radiation, humidity, and pressure. Subsequently, this data is used for PV power estimation using machine learning methods. This enables the identification of maintenance requirements and the prediction of potential issues in the PV system. When a problem occurs in the PV system, the user is alerted through the mobile application. Early detection and intervention prevent power loss and damage to system components. When comparing the results of linear regression, SVM, decision trees, random forests, and KNN machine learning methods for power estimation based on performance evaluation criteria, it was observed that the random forests algorithm provided the best results. In conclusion, the developed monitoring and estimation system, along with web and mobile interfaces, is suitable for large-scale PV energy systems.
Improving Learning Achievement through Balanced Nutrition among Junior High School Students in Jayapura City, Indonesia
Authors: Irab Semuel Piter , Efendi Ferry , Zainuri Agus , Sinaga Evi , Hidayat Rodhi Rusdianto , Putra Miftah Fariz Prima
Published: September 2023

Background and Objectives: Optimal learning achievement is often obtained through the consumption of nutritious and balanced food, which prevents poor nutritional statuses, such as severely underweight, underweight, overweight, and obese. This is particularly relevant to Junior High School students aged 11-16 years, who are more prone to malnutrition. Therefore, this study aimed to improve learning achievement through balanced nutrition among Junior High School students. Materials and Methods: The study procedures were carried out using a quantitative approach with a cross-sectional design. The sample population consisted of 350 Junior High School students in Jayapura Municipality, Papua Province, Indonesia. Primary and secondary data were obtained from relevant sources and analyzed using frequency distribution analysis and statistical path analysis tests. Results: The results showed the indirect effect of exogenous variables on the endogenous, where nutritional knowledge and a balanced diet influenced nutritional status (p-value = 0.001), but physical activity had no impact (p-value = 0.167). Meanwhile, the direct effect of exogenous variables on the endogenous showed that nutritional knowledge, interest in learning, and nutritional status influenced students’ achievement (p-value = 0.001). Based on these results, nutritional status played a crucial role in improving the learning achievement of junior high school students.
Decrease of α-Globin and Increase of the Autophagy-Activating Kinase ULK1 mRNA in Erythroid Precursors from β-Thalassemia Patients Treated with Sirolimus
Authors: Zurlo Matteo , Zuccato Cristina , Cosenza Lucia Carmela , Gasparello Jessica , Gamberini Maria Rita , Stievano Alice , Fortini Monica , Prosdocimi Marco , Finotti Alessia , Gambari Roberto
Published: September 2023

The β-thalassemias are hereditary monogenic diseases characterized by low or absent production of adult hemoglobin and excess in the content of α-globin. This excess is cytotoxic for the erythroid cells and responsible of the β-thalassemia associated ineffective erythropoiesis. Therefore, the decrease of α-globin excess is a relevant clinical effect for these patients and can be obtained by induction of fetal hemoglobin, by autophagy, or both. The in vivo effects of sirolimus (rapamycin) and analogues on induction of fetal hemoglobin (HbF) is of key importance for therapeutic protocols in a variety of hemoglobinopathies, including β-thalassemia. In this research communication, we report data showing that decrease of autophagy-associated p62 protein, increased expression of ULK-1 and reduction of the excess of α-globin is operating in erythroid precursors (ErPCs) stimulated in vitro with low dosages of sirolimus. In addition, increased ULK-1 mRNA content and decrease of α-globin content were found in ErPCs isolated from β-thalassemia patients recruited for the NCT03877809 clinical trial and treated with 0.5-2 mg/day sirolimus. Our data support the concept that autophagy, ULK1 expression and α-globin chain reduction should be considered important endpoints in sirolimus-based clinical trials for β-thalassemia.
A Mini Review on the Recent High-Impact Nanozymatic Sensors Constructed over 2016–2023
Authors: Hormozi Jangi Saeed Reza
Published: September 2023

As formally is known, nanozymes are the nanomaterials or nanoscale materials which reveal enzyme-like properties. These nanomaterilas can be utilzied instead of the natural enzymes for simulation of enzymatic reactions in harsh environmental conditions. Among different nanoscale enzyme-like materials, the majority of them reveal peroxidase-like activity, due to the high catalytic efficiency and stability of peroxidase-like nanozymes, they had been widely utilized for sensing and detection via constructing the colorimetric and fluorescence-based analytical and bioanalytical sensors. There are several high impact nanozymatic sensors which reported in the literature. Although the review articles published in this field, however, the current reviews focus on the introducing nanozyme field not description on the best articles published in this filed. Hence, this article aimed to present a brief introduction on the nanozyme-based chemistry with emphasizing on the historical overview of recent nanozymatic sensors. In this regard the best nanozymatic sensors which published over 2016-2023 were briefly described and overviewed.
A Variety of Optical Wave Solutions to Space-Time Fractional Perturbed Kundu-Eckhaus Model with Full Non-Linearity
Authors: Zafar Asim , Raheel Muhammad , Tariq Kalim U , Mahnashi Ali M. , Zahran Emad H.M. , Cevikel Adem , Bekir Ahmet
Published: September 2023

In this paper, the new optical wave solutions of truncated M-fractional perturbed Kundu-Eckhaus model with full non-linearity are obtained by utilizing the expa function technique and modified extended tanh expansion function technique. The solutions are in the form of dark soliton, bright soliton, singular solitons and other form of solutions. The gained solutions are helpful for the further development of concerned model. The obtained results have also been presented graphically in both two-dimensional and three-dimensional formats to discuss the dynamical features as well as the parametric dependence of the constructed solutions. The study offers a highly spectacular and acceptable techniques to combine various intriguing wave demonstrations for more sophisticated models of the modern day.
Essential Role of BMP4 Signaling in the Avian Ceca in Colorectal Enteric Nervous System Development
Authors: Kovács Tamás , Halasy Viktória , Pethő Csongor , Szőcs Emőke , Soós Ádám , Dóra Dávid , Pascal De Santa Barbara , Faure Sandrine , Stavely Rhian G , Goldstein Allan M , Nagy Nándor
Published: September 2023

The enteric nervous system (ENS) is principally derived from vagal neural crest cells that migrate caudally along the entire length of the gastrointestinal tract, giving rise to neurons and glial cells in two ganglionated plexuses. Incomplete migration of enteric neural crest-derived cells (ENCDC) leads to Hirschsprung disease, a congenital disorder characterized by the absence of enteric ganglia along variable lengths of the colorectum. Our recent data [1] support an essential role for the avian ceca, present at the junction of midgut and hindgut, in hindgut ENS development, since ablation of the cecal buds leads to incomplete ENCDC colonization of the hindgut. In situ hybridization shows bone morphogenetic protein-4 (BMP4) highly expressed in the cecal mesenchyme, leading us to hypothesize that cecal BMP4 is required for hindgut ENS development. To test this, we modulated BMP4 activity using embryonic intestinal organ culture techniques and retroviral infection in ovo. We show that overexpression or inhibition of BMP4 in the ceca disrupts hindgut ENS development, with GDNF playing an important regulatory role. Our results suggest that these two important signaling pathways are required for normal ENCDC migration and enteric ganglion formation in the developing hindgut ENS.
The Emotional Experience of Mexican Women with SARS-CoV-2 during Pregnancy—A Qualitative Study
Authors: Gómez-López María Eugenia , Aldrete-Cortez Vania , González-Carpinteiro Aline , Mendizabal-Espinosa Rosa Maria , Bobadilla-Ortiz Liliana
Published: September 2023

Pregnant women have been considered a high-risk group for SARS-CoV-2 infection; the impact of the disease on the health of a mother and her child is still being studied. The emotional impact of the pandemic on pregnant women has been extensively studied. Emotional distress is proposed as a perspective to explain the emotional manifestations of women during this stage as something common rather than pathological. The objective of this study was to know the emotional experience of women who tested positive for SARS-CoV-2 towards the end of their pregnancy, during the first and second waves of COVID in Mexico. A qualitative study was carried out: 18 pregnant women with COVID were interviewed. A thematic analysis of the data was performed, resulting in three main themes and 14 subthemes. The COVID-infected mothers-to-be experienced mild to moderate emotional distress. It was more intense for those with comorbidities. This distress was aggravated during obstetrical complications and comorbidities, as well as during COVID and postpartum. The emotional distress was appeased by both the perception of medical care and social support. The emotional distress of pregnant women with COVID requires emotional accompaniment to reduce its impact.
Smart eHealth System for Asthma Attack Prevention and Environmental Factors Monitoring
Authors: Alharbi Eman , Cherif Asma , Nadeem Farrukh
Published: September 2023

Recently, there has been growing interest in using smart eHealth systems to manage asthma. However, limitations still exist in providing smart services and accurate predictions tailored to individual patients’ needs. This study aims to develop an adaptive ubiquitous computing framework that leverages different bio-signals and spatial data to provide personalized asthma attack prediction and safe route recommendations. We proposed a smart eHealth framework consisting of multiple layers that employ telemonitoring application, environmental sensors, and advanced machine-learning algorithms to deliver smart services to the user. The proposed smart eHealth system predicts asthma attacks and uses spatial data to provide a safe route that drives the patient away from any asthma trigger. Additionally, the framework incorporates an adaptation layer that continuously updates the system based on real-time environmental data and daily bio-signals reported by the user. The developed telemonitoring application collected a dataset containing 665 records used to train the prediction models. The testing result demonstrates a remarkable 98% accuracy in predicting asthma attacks with a recall of 96%. The eHealth system was tested online by ten asthma patients, and its accuracy achieved 94% of accuracy and a recall of 95.2% in generating safe routes for asthma patients, ensuring a safer and asthma-trigger-free experience. The test shows that 89% of patients were satisfied with the safer recommended route than their usual one. This research contributes to enhancing the capabilities of smart healthcare systems in managing asthma and improving patient outcomes. The adaptive feature of the proposed eHealth system ensures that the predictions and recommendations remain relevant and personalized to the current conditions and needs of the individual.
One Health: Safeguarding Biosecurity and Cyberbiosecurity in Toxin and Venom Research Laboratories
Authors: Bhore Subhash Janardhan
Published: September 2023

Training researchers and stakeholders is crucial to mitigate the risks associated with toxins and venom. By sharing knowledge on the responsible use of toxins, venoms, chemicals, and data from biosecurity and cyberbiosecurity perspectives, we empower laboratorians to make informed choices. We need to remember that cultivating a culture of sustainable biosafety and biosecurity is vital for one health. This technical note highlights the essence of safeguarding biosecurity and cyberbiosecurity in toxin and venom research laboratories workshop designed and implemented to boost biosecurity.
The New Era of Therapeutic Strategies for the Treatment of Retinitis Pigmentosa: From Pathomolecular Mechanisms to the Development of Cell-Based Therapies
Authors: Becherucci Valentina , Bacci Giacomo Maria , Marziali Elisa , Sodi Andrea , Bambi Franco , Caputo Roberto
Published: September 2023

Retinitis Pigmentosa, defined more properly as rod-cone dystrophy, is the paradigm of diffuse inherited retinal dystrophies, one of the rare diseases with the highest prevalence in the worldwide population and one of the main causes of low vision in pediatric and elderly age groups. Advancement and understanding in molecular biology and gene editing technologies raised the interest in putting the basis for new therapeutic strategies in rare diseases. As a consequence, new possibilities for clinicians and patients are arising due to the feasibility of treating such a devastating disorder reducing its complications. The scope of this review is to focus on the pathomolecular mechanisms underlying RP better to understand the prospective for its treatment with innovative approaches.
Determination of the Characteristics of Non-stationary Random Processes by Non-parametric Methods of Solution Theory
Authors: Yesmagambetov Bulat-Batyr
Published: September 2023

This article is devoted to methods of processing random processes. Of particular relevance is the task of processing broadband non-stationary random processes. The processing of random processes is usually related to the assessment of their probabilistic characteristics. Very often, a non-stationary broadband random process is represented by a single implementation in a priori uncertainty about the type of distribution function. Such random processes occur in information and measuring communication systems in which information is transmitted at a real time pace (for example, radio telemetry systems of spacecraft). The use of methods of traditional mathematical statistics, for example, maximum likelihood methods to determine probability characteristics, in this case is not possible. The article discusses a method of processing non-stationary broadband random processes based on the use of non-parametric methods of decision theory. An algorithm for dividing the observation interval into stationary intervals using non-parametric Kendall statistics is considered, as well as methods for estimating probabilistic characteristics on the stationary interval using ordinal statistics. The article presents the results of statistical modeling using the Mathcad program.
Interaction of Thiol Antioxidants with a,β-Unsaturated Ketone Moiety of Curcumin; Its Implication for Stability and Bioactivity of Curcuminoids
Authors: Lee Bo Hyun , Song Eiseul , Hong Jungil
Published: September 2023

Many biological functions of curcumin have been reported. As certain bioactivities of curcumin are eliminated by antioxidants, reactive oxygen species generated by curcumin have been suggested as a relevant mechanism. In the present study, effects of different types of antioxidants on stability and bioactivities of curcumin were analyzed. High concentrations (>4mM) of the thiol antioxidants including N-acetylcysteine (NAC), glutathione (GSH) and β-mercaptoethanol accelerated decomposition of curcumin and other curcuminoids; Submillimolar levels (<0.5 mM) of GSH and NAC rather improved their stability. Ascorbic acid or superoxide dismutase also stabilized curcumin regardless of their concentration. Cellular levels and bioactivities of curcumin including cytotoxicity and induction of heme oxygenase-1 were significantly reduced in the presence of 8 mM of GSH and NAC. The effects were enhanced in the presence of submillilmolar GSH and NAC, or non-thiol antioxidants. The present results indicate that antioxidants with reduced thiol group could directly interact with α, β-unsaturated carbonyl moiety of curcuminoids and modulate their stability and bioactivity.
Optimization of Spray Tower Gas Scrubbers for Water-Tube Boilers
Authors: Mendoza Haro Edgar Italo , Camacho Jaime , Mendoza Carla , Mendoza Xavier
Published: September 2023

The sugar company Valdez S.A. Entity located within the geographical limits of the city of Milagro, needs to reduce its emissions to the environment and does not always comply with the air emissions standards for stationary combustion sources, which indicates that for equipment installed before 2003 they have a maximum limit of 300 mg / m³. A mist eliminator was designed to work inside the original wet gas scrubber of the water-tube cauldron #10, which uses Bagasse as fuel, for the generation of steam for industrial use. The research is documentary and field. The methodology used was mixed. focusing on the comparison of three types of technologies to meet the objectives, the fog eliminators types: Demister, Cyclone and Chevron. To find the appropriate complement, a comparison sheet was made, which is a table of contents evaluated quantitatively, analyzing indicators formulated in each of the contents. The results, supported by the Multiple Criteria Decision Analysis methodology, select the Chevron type fog eliminator, with the best efficiency for capture. Using AutoCAD, allows to visualize in 3D, the structural design in the gas scrubber.
Noise and Legal Dispute: Applications and Limits of the Italian Stardard UNI/TS 11844
Authors: Serpilli Fabio , Di Loreto Samantha , Lori Valter , Montelpare Sergio
Published: September 2023

In forensic acoustics, a possible area of analysis is represented by unwanted sound that 1
is perceived as a source of intrusion or disturbance within a certain auditory context. This context 2
is defined as the "auditory scene" and refers to the set of sounds present in a specific environment. 3
The presence of unwanted sounds in the auditory scene can cause a wide range of negative effects, 4
including disturbance, discomfort, moral or immoral harm, and other types of negative impact on the 5
health and well-being of individuals exposed to noise. In 2022, the technical specification UNI/TS 6
11844:2022 dedicated to the measurement and analysis of intrusive noise was published. The standard 7
introduces the concept of intrusive noise and defines its calculation methods based on environmental 8
measurements. The purposes of this technical specification is to provide an objective support to 9
methods already in used in acoustic disputes, where the assessment of the annoyance of a noise is 10
often a subjective evaluation of the technician. This work delves into the application to some real 11
cases, identifying the potentiality and the limits of the standardized method.
Brain Endothelial Cells Activate Neuroinflammatory Pathways in Response to Early Cerebral Small Vessel Disease (CSVD) Patients’ Plasma
Authors: Cifù Adriana , Janes Francesco , Mio Catia , Domenis Rossana , Pessa Maria Elena , Garbo Riccardo , Curcio Francesco , Valente Mariarosaria , Fabris Martina
Published: September 2023

The pathogenesis of Cerebral Small Vessel Disease (CSVD) is largely unknown. Endothelial disfunction has been suggested as the turning point in CSVD development. In this study we tested the effect of plasma from CSVD patients on human cerebral microvascular endothelial cells with the aim of describing the pattern of endothelial activation. Plasma samples from 3 groups of young subjects have been tested: PTs (subjects affected by early stage CSVD); CTRLs (control subjects without abnormalities at MRI scanning); BDs (blood donors). Human Brain Endothelial Cells 5i (HBEC5i) were treated with plasma and total RNA was extracted. RNAs were pooled to reduce gene expression-based variability and NGS analysis was performed. Differentially expressed genes were highlighted comparing PTs, CTRLs and BDs with HBEC5i untreated cells. No significantly altered pathway was evaluated in BD related treatment. Regulation of p38 MAPK cascade (GO:1900744) was the solely pathway altered in CTRLs related treatment. Indeed, 36 different biological processes turned out to be deregulated after PTs treatment of HBEC5i, i.e., the cytokine-mediated signaling pathway (GO:0019221). Endothelial cells activate inflammatory pathways in response to stimuli from CSVD patients’ plasma, suggesting the pathogenetic role of neuroinflammation from the early asymptomatic phases of cerebrovascular disease.
A New Model for IT Management in the Digital Era
Authors: Wynn Martin , Felser Kerstin
Published: September 2023

This article examines how digitalisation is impacting the management of IT. Phase 1 of the re-search focuses on the German automotive industry, and adopts a qualitative inductive approach, based on feedback from 19 semi-structured interviews with IT managers and professionals. Five key aspects of digitalisation are identified, and a new model for the management of IT is devel-oped. Phase 2 then reviews the deployment of digital technologies in eight organisations from other industry sectors and assesses the overall impact on the management of IT. The results suggest that the transition to new IT management structures in the German automotive industry may be the forerunner of a change process that will impact more widely in other industries, in particular where digital technologies are now embedded in an organisation’s products or services. The results also provide some new perspectives on the conceptualisation of digitalisation and digital transformation, and represent a contribution to the developing theory around new tech-nology deployment and IT management in the digital era.
Synthesis of a New Dinuclear Cu(I) Complex with Triazine Ligand and diphenylphosphine methane: X-ray Structure, Optical properties, DFT calculations and application in DSSC
Authors: Peñuelas Carlos A. , Campos-Gaxiola José J. , Soto-Rojo Rody , Cruz-Enríquez Adriana , Reynoso-Soto Edgar A. , Miranda-Soto Valentín , García Juventino J. , Flores Alamo Marcos , Baldenebro-López Jesús , Glossman Mitnik Daniel
Published: September 2023

A new copper(I) complex, [Cu2(L)2dppm](PF6)2 (1) [L = 3-(2-Pyridyl)-5,6-diphenyl-1,2,4-triazine and dppm: Bis(diphenylphosphino)methane] was prepared and characterized by IR, 1H-NMR, 31P-NMR spectroscopy, elemental and thermogravimetric analysis, and single-crystal X-ray diffraction technique. Complex 1 is a dinuclear compound, showing that L and dppm act as tridentate and bidentate chelating ligands, respectively. The two Cu(I) atoms exhibit a distorted tetrahedral coordination sphere embedded in N3P environments. The supramolecular interactions in the solid-state structure are characterized by C−H···N, C−H···F, C-H···π and π···π intermolecular interactions that were analyzed by inspection of the Hirshfeld surface and fingerprint plots. Additionally, the complex was studied experimentally in solution by UV–Vis spectroscopy and cyclic voltammetry; also, theoretical studies with Time-Dependent Density Functional Theory (TD-DFT) were performed. Moreover, the optical and electrochemical properties have been studied, focusing on the band gap. Compound 1 has been used as a co-sensitizer in a dye-sensitized solar cell, showing good activity.
Evaluation of Coproporphyrins I and III as an Endogenous Marker for Hepatic Organic Anion Transporting Polypeptides and Multidrug Resistance-Associated Proteins (MRP 2/3) Activity in Animal Models of Nonalcoholic Steatohepatitis Using a Mechanistic Model
Authors: Kumar Rajeev , Chatterjee Sagnik , Gilibili Ravindranath Reddy , Mariappam T Thanga , Shen Hong
Published: September 2023

Coproporphyrins I and III (CP-I and CP-III) are established as substrates of hepatic sinusoidal organic anion transporting polypeptides (Oatps), multidrug resistance-associated protein 3 (Mrp3), and canalicular transporter Mrp2. We aimed to evaluate the potential of plasma CP-I and CP-III concentrations to indicate functional changes in hepatic transporters in nonalcoholic stea-tohepatitis (NASH) rodent models using modeling and simulation approach. Mechanistic copro-porphyrins (CP-I and CP-III) models in rats and mice were constructed based on metabolism, transport, and elimination pathways in rodents. To parameterize the rat mechanistic model, we measured CP concentrations in plasma, liver, bile, and urine in healthy control Sprague Dawley rats. The mouse mechanistic model was parameterized using published data. The rat and mouse CP models described the steady-state levels of CP-I and CP-III in plasma, liver, and bile. The model recapitulated the observed high plasma CP-III / CP-1 ratio (9- and 3-fold in rats and mice, respec-tively) and elimination pathways of CP-I (>90% via biliary secretion) and CP-III (equal via bile and urine). Rat CP model was further validated with the published rat fistula model. The simulated increased plasma CP-I concentrations (4-fold), resulted from decreased Oatp activity (0.6-fold) and increased Mrp3 activity (3-fold) were comparable to those observed in bile-duct ligated NASH model. Sensitivity analysis revealed that 90% inhibition of Oatp and Mrp2 leads to a 4-fold and 2.5-fold increase in plasma CP-I levels, respectively. Additionally, we demonstrated the utility of the mechanistic CP models in testing hypothesis and understanding the mechanisms of the ob-served plasma CPs disposition in the Oatp knockout (KO) mice, bile-duct ligation NASH mice, and Mrp2 deficient TR- rats. Collectively, using a mechanistic model, we conclude that CP-I is a robust and predictable marker for assessing change in the activity of Oatps and Mrps in animal models. Our analysis suggests that efflux transporters (Mrp2 and Mrp3) can play an important role in the disposition of CP-I along with Oatp transporters in rodents.
Clubfoot and the Ponseti Method: A Bibliometric Analysis
Authors: Kiani Sara N. , Yang Daniel , Zheng Jenny L. , Spiegel David A.
Published: September 2023

Background:

The aim of the present study was to perform a bibliometric analysis of research articles published on clubfoot to provide a quantitative description of the literature and to gather information on the institutions, journals, researchers, and countries publishing on this topic.

Methods:

This bibliometric analysis consisted of 2 Web of Science searches. The first identified all articles published prior to April 25, 2022, with “clubfoot” in the title, abstract, or keywords, and the second identified all articles with “Ponseti.” Studies were exported in BibTeX format and uploaded into Biblioshiny software in RStudio. Descriptive statistics are reported for variables related to the article, author, and country in which the research was conducted.

Results:

A total of 2,177 articles identified using the term “clubfoot” were included. The first article was published in 1902, and there was a 3% annual growth rate. A total of 762 articles identified using the term “Ponseti” were included, with the first published in 1992 and a 13.9% annual growth rate. The Journal of Pediatric Orthopaedics accounted for almost one-quarter of all published reports.

Conclusions:

The literature on clubfoot has expanded in the past decades, and the percentage of studies concerning the Ponseti method has increased dramatically in the years following adoption in the U.S. and, more recently, globally. While a number of studies involved collaboration between authors in high-income and low- and middle-income countries, further collaboration will be essential to evaluate outcomes and help improve service delivery as adoption of this method increases globally.

Clinical Relevance:

This paper explores how the orthopaedic and scientific communities have increasingly contributed to literature on Ponseti casting and clubfoot, and discusses how contributions to the literature are becoming increasingly widespread.
Resilience modeling for civil military operations with the framework incorporating complex uncertainty systems
Authors: Ehlschlaeger Charles , Burkhalter Jeffrey , Chiu Imes , Linkov Igor , Cegan Jeffrey , David Olaf , Ouyang Yanfeng , Parker Joshua , Serafin Francesco , Morrison Dawn , Westervelt James , Lin Liqun , Palacio Jenny , Patterson Dave , Perkins Timothy , Petit Antoine , Liu Yining
Published: September 2023

Framework Incorporating Complex Uncertain Systems (FICUS) provides geographic risk analysis capabilities that will dramatically improve military intelligence in locations with the Engineer Research and Development’s (ERDC) demographic and infrastructure models built and calibrated. When completed, FICUS would improve intelligence products by incorporating existing tools from the National Geospatial Intelligence Agency, ERDC, and FICUS prototype models, even in places without demographic or infrastructure capabilities. FICUS would support higher-fidelity intelligence analysis of population, environmental, and infrastructure interaction in areas with Human Infrastructure System Assessment (HISA) and urban security models built and calibrated. This technical report will demonstrate FICUS prototype tools that allow Civil Affairs Soldiers to provide situational awareness information via a browser interface.
Analisis Validitas Konstruk, Konvergen, dan Diskriminan dari Instrument Well-Being
Authors: Purnamasari Mega Isvandiana
Published: September 2023

Tujuan dari studi ini yaitu untuk melakukan memvalidasi instrumen pengukuran Well-Being (WB) menggunakan analisis factor konfimatori. Validasi instrumen bertujuan untuk memastikan bahwa butir-butir yang ada mampu secara akurat mencerminkan WB yang hendak diukur. Instrumen yang digunakan dalam penelitian ini adalah instrument yang dikembangkan oleh Riff, dengan total 42 pertanyaan yang mencakup 6 aspek WB. Pendekatan deskriptif kuantitatif digunakan dalam penelitian ini, melibatkan 284 mahasiswa PGSD STKIP PGRI Pacitan sebagai responden. Validitas instrumen dievaluasi menggunakan analisis faktor konfirmatori. Tiga jenis validitas dihitung, yaitu validitas konstruk, konvergen, dan diskriminan. Hasil analisis menunjukkan bahwa validitas konstruk terpenuhi dengan nilai RMSEA sebesar 0.78 dan GFI sebesar 0.908, dengan mengeluarkan 18 pertanyaan karena memiliki faktor loading yang rendah. Selanjutnya, validitas konvergen menunjukkan bahwa dua aspek, yaitu Hubungan Positif dan Penguasaan Lingkungan, memiliki nilai AVE kurang dari 0.5. Terakhir, validitas diskriminan terpenuhi dengan tidak adanya indikasi multikolinieritas pada pertanyaan-pertanyaan yang digunakan. Dari hasil ini dapat disimpulkan bahwa instrumen WB yang dapat digunakan terdiri dari 24 pertanyaan, dengan masing-masing aspek terdiri dari 4 butir.
Impact of Salinity on Waterflood Displacement Efficiency
Authors: Al Jadidi A. Y. , Mackay E. J.
Published: September 2023

Fluid properties are among the main parameters that influence waterflood performance. This paper aims to investigate the impact of salinity on displacement efficiency by understanding the effects on physical properties. Besides salinity, dissolved CO2 and temperature effects are also evaluated. Based on these, the paper assesses when the different effects are significant, in which brine tracking and temperature modelling are required. In addition, it provides insights about reservoir applications involving CO2.

The majority of the studies in the literature about the effects of salinity, mainly the injection of low salinity water, on oil recovery involve geochemical reactions, and there is a lack of studies about the effects of physical properties in that regard.

In this work, a sensitivity analysis by compositional reservoir simulation is conducted, where variable salinity cases are simulated in isothermal and non-isothermal systems, with oil composition considering both with and without dissolved CO2. Both 2D and 3D grids are used.

The analysis shows that salinity did not strongly impact the oil recovery; its effect on density and viscosity is insufficient to impact displacement efficiency. Moreover, CO2 increased the oil recovery significantly for both 2D and 3D systems, which is attributed to improving oil viscosity and oil swelling phenomena. The reduction in temperature improved the oil recovery slightly for 2D systems and significantly for 3D systems. This suggests that injecting cool brines into hot reservoirs leads to better oil recovery for 3D systems when there is no CO2 due to gravitational effects, while 2D systems, where gravity is less pronounced, have more recovery in the presence of CO2. Additionally, gravity effects are minimized due to the very low mobility ratio. Based on that, brine tracking is generally not required, while temperature modelling in compositional simulations is advised.
AI Enabled Digital Rock Technology for Larger Scale Modelling of Complex Fractured Subsurface Rocks
Authors: Panaitescu C. T. , Wu K. , Tanino Y. , Starkey A.
Published: September 2023

Quantifying and modelling fractured subsurface rocks, characterised by their complex geometric heterogeneity, is crucial to the geo-energy transition because it helps predict flow properties in fractured systems. Multiscale Digital Rock Technology (MDRT) offers a solution to analyse comprehensive fluid flow mechanisms from the pore scale to much larger scales. In addition, artificial intelligence (AI) techniques can add significant value to geoscience workflows, automating time-consuming tasks, some even prohibitively long if done manually (such as 3D image volume labelling), and obtaining new insight from combining highly diverse data sources.

We propose a novel machine-learning algorithm for semantic segmentation of rock matrix, fractures, vugs, and secondary mineralogy. After implementing and examining deep and shallow-learning approaches, we concluded to use shallow machine-learning methods for increased computational efficiency and explainability while achieving comparable accuracy. By integrating our novel machine-learning algorithm into the multiscale Pore Network Model (PNM) code, we improve the modelling method of subsurface flow, particularly in complex fractured subsurface systems and carbonates.

The resulting algorithm accurately discriminates between pores, fractures, and vugs. Therefore, it enhances the accuracy of pore-fracture-vug network extraction and simulation and provides an improved analysis of complex rock structures. Moreover, the segmentation results are integrated into a Fracture-Pore Network Model, validated against high-fidelity OpenFOAM simulation.

This integration of fractures into the PNM code allows for larger scale fluid flow simulation in complex fractured subsurface systems. The current research produced a fast algorithm that accurately and automatically segments X-ray micro-computed tomography (micro-CT) samples having pores, fractures, and vugs. Our validation also showcases the potential of this algorithm to improve existing industrial core analysis practices.
A New Innovative Cement Evaluation Method for Highly Deviated or Horizontal Wells
Authors: Kumar A. , Singh K. , Oliver D. S , Dutta S.
Published: September 2023

Evaluation of cement integrity to prevent fluid migration in the annular space behind casing may become challenging under certain well conditions. Conventional cement evaluation tools are useful in most scenarios, but in highly challenging operations (deviated or horizontal wells), there is a pressing need for more advanced cement evaluation and processing techniques to increase the confidence of the measurements for the evaluation of wellbore integrity.

Pulse-Echo and/or Flexural wave measurement, along with sonic measurements, are generally run in tandem for improved cement evaluation. The method relies on knowing the wellbore fluid properties (acoustic velocity and acoustic impedance), which may change in deviated or horizontal sections of a well due to mud settling or mud segregation with lighter components on the high side and heavier components on the lower side of the well. This segregation phenomenon, if not accounted for, results in erroneous cement interpretation answers with uncertainty, such as low-acoustic impedance stripe in the direction of heavier mud components. A new advanced ultrasonic technology and its embedded unique inversion processing known as R+, based on 3-parameter inversion approach is developed, which first computes the wellbore mud impedance 360 deg and then uses it as an input to compute the annular material acoustic impedance accurately. This method can also reveal wellbore conditions such as mud settling and segregation.

This paper demonstrates the application of new advanced ultrasonic tool and the R+ inversion processing through multiple case studies. In all the cases explained in the paper, we see that due to mud segregation in the borehole, it was difficult to identify true annular conditions. The R+ inversion method was used to confirm the wellbore fluid heterogeneity. All the case studies compare cement evaluation performed using the classic T3 method with R+ inversion method. The uncertainties faced due to mud segregation inside the wellbore were properly addressed with the new R+ inversion method, and the final cement interpretation helps the operators in taking operational decisions in time.

The advanced ultrasonic technology and R+ inversion method will ensure accurate cement evaluation in challenging wellbore environments where mud segregation is expected irrespective of casing sizes and cement types. With accurate cement evaluation, the operators can avoid unnecessary costly cement remedial operations at any point (new well, intervention, plug and abandonment), thus impacting the rig activities.
Active Magnetic Ranging While Drilling: Prototype Tool Test
Authors: Husby K. , Hjelstuen M. , Eriksen T. J. , Liberale A. , Koraei M. , Ytrehus J. D. , Saasen A.
Published: September 2023

A well intercept operation has the scope to drill into an existing well. Similarly, some infill drilling operations are conducted with the scope of avoiding interception with other wells. A prototype of a tool for Active Magnetic Ranging While Drilling (AMR) without the use of a wireline operation has been developed. The main scope of the current article is presenting the results of a prototype test of this new tool in attest well.

The ranging tool emits a low frequency alternating current into the formation to reach the target well, and then run through that's casing back to the well being drilled. This electric current set up a variable magnetic field that is measured by the AMR tool determining the direction towards the target well as well as the distance. If drilling a relief well, 10 - 25 wireline runs are needed before the target well is intercepted. The present AMR tool is fully integrated in the drill pipe and, thus, all the tripping operations are avoided.

A prototype of an active magnetic ranging tool on the drill pipe has been developed. This tool is outlined in detail in the paper. Most focus will be given to a performance test conducted in a research well in Norway. A drill pipe is placed in a vertical well, being the target well. The AMR tool was run in the research well and the direction and distance to nearby target wells was measured. The set-up and the results of this logging operation conducted on a drill pipe is described in detail. It is shown how the direction and distance between the two wells are measured using the tool.

Most intercept operations are not relief well drilling, but cases where a well needs to be intercepted because a well section shall be connected to another well, or during plug and abandonment operation. The tool can also be used for avoiding collision with other wells, which is a relevant scope for drilling infill wells in older fields or radiator wells in geothermal drilling. The tool and its potential are outlined in the paper.