bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning Assisted Flash Calculation for Sour Gas and Crude Oil
Authors: Koyanbayev Madiyar , Wang Lei , Zhumatai Aset
Published: January 2023

Compositional modeling is an effective and necessary technique for designing and optimizing complex oil and gas production processes, such as gas injection enhanced oil recovery (EOR). Generally, about 70% of computational time in compositional modeling is consumed by flash calculation. Replacing iterative flash calculations partially or completely in obtaining the satisfactorily accurate number of phases and compositionswith machine learning (ML) models is proven to be an efficient strategy to accelerate flash calculation. In this study, support vector machine (SVM), artificial neural network (ANN), and decision trees (DT) models were trained, validated, and tested based on 10,000 PVT data sets, which were artificially generated for a sour crude oil sample containing 13.32 mol% H2S and 2.9 mol% CO2. Comparative analysis showed that all three ML models could be used to make an accurate prediction. The obtained ANN model was compared with the vapor–liquid equilibrium (VLE) calculation and was used as a surrogate model for accelerating the flash calculation. The comparison revealed that the ANN model reduced the computational time of the VLE calculation by as high as 250 times. Moreover, the phase diagram of sour crude oil obtained by the ANN model was close to the phase diagram generated by VLE, which proves the accuracy and robustness of the ANN model. Overall, this work shows that ANN model is effective in accelerating flash calculation and reducing the computational time of compositional reservoir simulation.
A Detail Study Evaluating the Impact of Downhole and Wellhead Compression to Optimize Production From Gas Wells with Liquid Loading Issue: An ADNOC Onshore Gas Field Case Study
Authors: Bernadi Bondan , M. Douglas Mahmoud , Al Shamsi Alia Belal Zuwaid Belal , Omar Alawadhi Fatima , Nabil Mohamed Ihab , Ahmed Hosani Mariam , Mohamed Al Bairaq Ahmed , Abdullayev Azer , Roopal Allen
Published: January 2023

An onshore retrograde gas field in Abu Dhabi has several wells with severe liquid loading issue as reflected by low intermittent production rates. To overcome this, a study was performed by looking at the effectiveness of downhole and wellhead compression and their impact on the production rates. Utilizing IAM, the benefit will not only be seen at the well level but also at the field scale with the ultimate goal to increase the Recovery Factor.

The study was started by identifying the wells suffering from liquid loading issue. The wells were then ranked according to the severity of the problem based on the GLR values. Hence, the top 2 wells were prioritized as the candidates. Both the downhole and wellhead compressors were then modelled in IAM and several sensitivity runs were performed to evaluate the optimum compressor settings to see the impact on flow stabilization and wells productivity. The selected best scenarios were also compared with the base case as reference where no intervention was performed at all (natural flow).

The study reveals that both downhole and wellhead compression can give wells flowrate stability with substantial improvement on the production rates for longer duration of time compared to the base case scenario. More than that, the downhole compression shows better gain for production rates compared to the wellhead compression. This is mainly attributed to the fact that gas density is higher at the bottom of the well than at the surface and since the mass flow rate depends on the density of the gas and the volumetric flow rate, this will lead to higher mass flow rate for the same volumetric flow. Consequently, a downhole compressor will produce more fluid quantity rather than a wellhead compressor.

The study clearly demonstrates and evaluates the effectiveness of downhole and wellhead compressors to mitigate liquid loading inclusively to improve gas wells production. By utilizing IAM that is capable to capture the interactions between subsurface to surface network elements, the improvements on wells deliverability after implementing downhole and/or wellhead compression can be accounted more accurately taking into account more complex production operations with the ultimate goal to maximize the field Recovery Factor.
Unveiling Reservoir Architecture and Characterization Using Ultra-HD Bed Boundary Mapper
Authors: Saleh Abdullah S. , Sultan Shehri A. , Santoso Gagok Imam , Alshammari Huliayan Furreh
Published: January 2023

Drilling a well in one specific layer is challenging. In the subject well, multiple zones have been determined in the target reservoir. Each zone has its own property and distribution. The objective of this paper is to unveil the reservoir architecture and formation characterization using the latest logging-while-drilling (LWD) technology in ultra-high definition boundary orientation.

The methods presented in this paper are to integrate field geological knowledge, wellbore centric LWD data (Images and Triple Combo) and Ultra High Definition Bed Boundary Mapper that extend EM measurements, which allows a better fine-tuning structure and formation resistivity interpretation around the wellbore, independent of mud type. Along with those measurements, a new resistivity inversion has been developed that computes geometrically corrected resistivity for both vertical Rv, and horizontal Rh from bed boundary locations, and formation relative dip. In addition, formation relative dips and boundary positions from the inversion are in good agreement with relative dips from other sources such an image analysis.

The tool deployed successfully and enabled optimum reservoir exposure in a good porosity zone. Along the boundary orientation for geosteering purposes, the technology was able to map another two porous zones within a 20 ft depth of the investigation. The qualitative formation resistivity, both Rh and Rv, were also used for formation evaluation in this reservoir at the well location, which brought the robust information value, especially in high angle and horizontal (HA/HZ) wells because of the complicated tool responses when crossing boundaries. Deep directional EM tools are beneficial for inversions to derive formation properties since they provide more measurements and information about the formation resistivity without the need to cross layer boundaries. Data validation done through several validations by comparing the RhRv value with the vertical well resistivity. Other than that, we also did a general approach for solving formation parameters to search through all possible model scenario and find the one that best matches the actual 2 Mhz 28 and 16-in. coaxial propagation responses using a 2-layer model.

Initial run results are very encouraging, demonstrating the value to improve efficiency in reservoir characterization and interpretation. The technology enables better understanding the reservoir architecture and formation evaluation through several application from single LWD measurement.
Fluid Monitoring to Optimize GOGD Recovery in Highly Fractured Reservoir Field in North of Sultanate of Oman
Authors: Al Hussaini Azza , Al Nofli Kholood , Agarwal Kavita , Abri Mustafa
Published: January 2023

Gas oil Gravity Drainage (GOGD) process is one of the highly efficient recovery mechanism in heavily fractured carbonate reservoirs. The driving force is the gravity, the oil is moving down from the matrix block through fractures until it reaches the producers. To ensure optimum offtake from the reservoir through the horizontal wells the oil rim need to be stabilized and very well managed through the gas injection, offtake/intake balance, aquifer pump off.

A key challenge of optimizing the gas injection as well as the offtake from the horizontal wells to achieve effective GOGD recovery is to ensure that a minimum oil rim thickness is maintained, and that oil rim is kept at the same depth as the oil production well. If not;

When the oil rim moves down, the well will produce gas instead of oil, therefore resulting in deferment and inefficient GOGD recovery. When the oil rim moves up, the well will produce water from the fracture system, therefore resulting in deferment and significant time to recover the oil rim to the correct depth.

A typical monitoring method for the fracture fluid fill is to run "gradio" surveys in dedicated observation wells to measure the fGOC and fOWC (where "f" represent the fracture system contacts i.e. fractured gas oil contact and fractured oil water contact rather than the matrix contacts). Also the fluid movement in matrix can be monitored by Pulsed-Neutron logging, in combination with Open-hole logs that have been acquired at different times through the development.

In addition to the logging methods, GOGD Flow Unit characterization was introduced to depict the effect of the intake/offtake changes and oil rim movement within the GOGD system along with a surveillance strategy focusing on reservoir optimization. Fluid contact visualization plots were generated for each flow unit which give a clearer picture in how effective is the current GOGD system and the future reservoir development and optimization.

More than 5 flow units with almost 150 active wells,3 gradio wells and 5 pulsed neutron log data were reviewed, to generate fluid contact visualization plots and justify flow unit production behavior. This analysis initiative helped to depict the effect of the intake/offtake changes and oil rim movement within the GOGD system. This work also led to adding additional development opportunities like placement of future new wells or adding perfs /carrying out zone change in existing closed in wells either to produce oil or to pump off water. This eventually fed into the reservoir optimization and surveillance strategy.
Deep Learning-Based and Kernel-Based Proxy Models for Nonlinearly Constrained Life-Cycle Production Optimization
Authors: Atadeger Aykut , Onur Mustafa , Sheth Soham , Banerjee Raj
Published: January 2023

In this study, we investigate the use of deep learning-based and kernel-based proxy models in nonlinearly constrained production optimization and compare their performances with directly using the high-fidelity simulators (HFS) for such optimization in terms of computational cost and optimal results obtained. One of the proxy models is embed to control and observe (E2CO), a deep learning-based model, and the other model is a kernel-based proxy, least-squares support-vector regression (LS-SVR). Both proxies have the capability of predicting well outputs. The sequential quadratic programming (SQP) method is used to perform nonlinearly constrained production optimization. The objective function considered here is the net present value (NPV), and the nonlinear state constraints are field liquid production rate (FLPR) and field water production rate (FWPR). NPV, FLPR, and FWPR are constructed by using two different types of proxy models. The gradient of the objective function as well as the Jacobian matrix of constraints are computed analytically for the LS-SVR, whereas the method of stochastic simplex approximated gradient (StoSAG) is used for optimization with E2CO and HFS. The reservoir model considered in this study is a two-phase, three-dimensional reservoir with heterogeneous permeability which is taken from the SPE10 benchmark case. Well controls are optimized to maximize the NPV in an oil-water waterflooding scenario. It is observed that all proxy models can find optimal NPV results like optimal NPV obtained by HFS with much less computational effort. Among proxy models, LS-SVR is found to be less computationally demanding in the training process. Overall, both proxy models are orders of magnitude faster than numerical models in the prediction. We provide new insights into the accuracy and prediction performances of these machine learning-based proxy models for 3D oil-water systems as well as their efficiency in nonlinearly constrained production optimization for waterflooding applications.
Does it Have to be Complex? Pragmatic Approach to Developing Newly Discovered Naturally Fractured Reservoir
Authors: Suut Nur Suria Amalia , Shukri Khalsa , Borbajo Renato
Published: January 2023

Located in remote interior South of Oman, Field X historically comprised of multi-stacked clastic reservoirs. Since its production in 1980s, production had declined significantly that the field was identified as a potential abandonment candidate. In 2020, Field X integrated team successfully discovered commercial oil accumulation in overburden, naturally fractured carbonates reservoir Y; first carbonates discovery in the area. This case study focused on how the team embarked on the challenge to accelerate production from this new reservoir. Following this success, short-term opportunities were identified whereby existing vertical well stocks were re-perforated to evacuate production from reservoir Y.

Key decisions that needed to be answered for full field development concept were optimum number of wells, well type and recovery mechanism. Analogues study was done and horizontal appraisal wells were identified and drilled. Acquisition and interpretation of static (including image logs) and dynamic (including pressure transient analysis) data in reservoir Y provided somewhat fractures characterization. A model framing event was conducted to identify complexity level of dynamic modeling required to answer above key decisions. History matching and sensitivity analysis using experimental design was performed to identify the most impacting key parameters to the development. Reperforation of existing vertical well stocks and 2021 horizontal well appraisal drilling not only generated early oil, but also valuable data gathering which helped in determining uncertainties ranges. Sensitivity analysis concluded that key uncertainties to the project were fracture characterization and its distribution across the field and oil water contact. Decision-based modeling approach was carried out. This means rather than building complex 3D-discrete fracture network model, a relatively simple full-field 3D-Dual Permeability simulation was deemed sufficient to answer decisions to be made whilst honoring uncertainty ranges. This was not only efficient but also at the same time brought early insights to key uncertainties in the development and therefore the team was able to identify what additional data acquisitions are relevant for the project moving forward. Three deterministic realisations were selected from probabilistic runs, and forecast results were also benchmarked to analogous fields for realism checks.

The development will be phased, with high confidence wells drilling scheduled to start in early 2023, to balance between early oil recovery (first key value driver of the project), lower UTC and maximising ultimate recovery. The total development of reservoir Y, up to 5 wells drilling campaign, was estimated to bring total resources volume double of that of NFA's (no further activities) remaining reserves. This leads to growth for Field X with attractive UTC and NPV and ultimately maximizing its value.
Physics Informed Surrogate Model Development in Predicting Dynamic Temporal and Spatial Variations During CO2 Injection into Deep Saline Aquifers
Authors: Tariq Zeeshan , Yan Bicheng , Sun Shuyu
Published: January 2023

Geological Carbon Sequestration (GCS) in deep geological formations, like saline aquifers and depleted oil and gas reservoirs, brings enormous potential for large-scale storage of carbon dioxide (CO2). The successful implementation of GCS requires a comprehensive risk assessment of the confinement of plumes at each potential storage site. The accurate prediction of the flow, geochemical, and geomechanical responses of the formation is essential for the management of GCS in long-term operations because excessive pressure buildup due to injection can potentially induce fracturing of the cap-rock, or activate pre-existing faults, through which fluid can leak. In this study, we build a Deep Learning (DL) workflow to effectively infer the storage potential of CO2 in deep saline aquifers. Specifically, a reservoir model is built to simulate the process of CO2 injection into deep saline aquifers, which considers the coupled phenomenon of flow and hydromechanics. Further, the reservoir model was sampled to account for a wide range of petro-physical, geological, and operational parameters. These samples generated a massive physics-informed simulation database (about 1500 simulated data points) that provides training data for the DL workflow. The ranges of varied parameters were obtained from an extensive literature survey. The DL workflow consists of Fourier Neural Operator (FNO) to take the input of the parameterized variables used in the simulation database and jointly predict the temporal-spatial responses of pressure and CO2 saturation plumes at different periods. Average Absolute Percentage Error (AAPE) and coefficient of determination (R2), Structural similarity index (SSIM), and Peak Signal to Noise Ratio (PSNR) are used as error metrics to evaluate the performance of the DL workflow. Through our blind testing experiments, the DL workflow offers predictions as accurate as our physics-based reservoir simulations, yet 300 times more efficient than the latter. The developed workflow shows superior performance with an AAPE of less than 5% and R2 score of more than 0.99 between actual and predicted values. The workflow can predict other required outputs that numerical simulators can typically calculate, such as solubility trapping, mineral trapping, and injected fluid densities in supercritical and aqueous phases. The proposed DL workflow is not only physics informed but also driven by inputs and outputs (data-driven) and thus offers a robust prediction of the carbon storage potential in deep saline aquifers with considering the coupled physics and potential fluid leakage risk.
A study on the characteristics of suicide risk group and establishment plan of its management system: Focused on the civil-police cooperation system
Authors:   Korean Association of Public Safety and Criminal Justice, Kim Jin-Hyeok
Published: January 2023

Suicide can be defined as any act by a person of terminating his or her life through his or her own act with a clear intent of ending the life. Suicide is recognized as a serious social problem, but it has not been successfully prevented for a long time. Suicide prevention has not been successful not only because the causes of suicide are complex and complicated, but also because the prevention system has not been well administered.
Suicides can be classified into suicides from social, economic and environmental causes; social disconnection and maladjustment; mental and psychological causes; irreversible health deterioration; and from various interacting causes.
In order to effectively control these problems of suicides, it is necessary to establish a control system of suicide prevention at the national level, improve relevant laws, install a police-centered public-private partnership suicide prevention system, and organize and use treatment and response manuals for each type of suicide.
The most important measures would be to change public awareness and form a consensus on the environment which prompts suicide. Along with the nationwide expansion of suicide prevention education, it is also essential to remedy a social environment which creates a demand for suicides. Such remedy is needed because it is difficult to achieve an intended effect just by controlling suppliers when there are many people with demand. Therefore, the basic policy of suicide prevention should be to create a social environment which can control the demand for suicides, too.
CYP2B6 genetic variation in cyclophosphamide metabolism and hemorrhagic cystitis in Fanconi anemia patients undergoing allogeneic hematopoietic cell transplantation
Authors: Ferdjallah Asmaa , Long Susie , DeFor Todd , Hoffmann Cody , Wagner John , Jacobson Pamala , MacMillan Margaret
Published: January 2023

Background
Fanconi anemia (FA) is an inherited disorder characterized by congenital malformations, bone marrow failure and malignancies. Hematopoietic cell transplant (HCT) is the only proven cure for the hematological complications. FA patients have increased chromosomal instability and aberrant DNA repair and thus can only tolerate low doses of chemotherapy or radiation as part of conditioning prior to HCT. Yet, they are still prone to severe regimen related toxicities (RRT) including hemorrhagic cystitis (HC) from cyclophosphamide (CY).
Objective
As CYP2B6 is a primary enzyme responsible for the catalyzation of the prodrug form of CY, understanding the association between CYP2B6 genetic variants and HC in FA patients may predict which patients will be more susceptible to developing HC.
Study Design:
A descriptive genetic association study was performed to identify genetic variants associated with HC in patients with FA who underwent HCT between 1999 and 2017. All patients received a CY-based preparative regimen and had pretransplant recipient DNA available for genomic analysis.
Results
Forty FA pediatric patients were eligible for this analysis. They had received HCT from matched sibling donors (n = 6) or alternative donors (n = 34) for marrow failure (n = 38) or myelodysplastic syndrome (n = 2). The incidence of HC was 32.5% which occurred at a median of 32 days (range 20–180) after HCT. Nine patients had a concomitant viral infection (BK virus, n = 8 both adenovirus and BK virus, n = 1). No genetic variants were significantly associated with HC. The top variants were rs2279343 (g.23060A > G), and rs2279344 (g.23280G > A) in the CYP2B6 gene. The incidence of HC among FA patients with the rs2279343 variant was 42% (CI 22–62%) compared to 20% (CI 0–40%) among those without the variant (p = 0.19). The incidence of HC among patients with the variant in rs2279344 was 40% (CI 22–58%) compared to 10% (CI 0–28%) among those without (p = 0.11).
Conclusion
No variants in our analysis were statistically associated with HC. The data suggest that CYP2B6 variants may increase the risk for HC in FA patients who received a CY based preparative therapy but these risk variants must be further evaluated in a larger population.
Challenges of Consumer Culture and Solid-waste to the Environment Protection in Pokhara Metropolitan City, Nepal
Authors: Subedi Shukra Raj , Poudel Jiban M , Subedi Madhusudan , Sharma Bigyan , Subedi Sunil , Neupane Bhim P , Lamichhane Basanta L , Neupane Badri N , Bohara Krishna K , Shrestha Gopi L
Published: January 2023

Changing consumer culture and increasing solid-waste have become global environmental issues leading to myriad challenges for management, especially in urban spaces. Against this backdrop, this study explores the challenges of solid-waste attached to changing consumer culture in the context of Pokhara, an urbanized tourist city in Nepal. The study has followed the qualitative research design generated through primary and secondary data. For this purpose, five informants have selected by purposive sampling and gathered their experiences, knowledge, and understanding of the relationship between changing consumer culture and increased solid-waste through in-depth interviews. The findings reveal that the leading cause of the environmental problem in this area is due to changing consumer culture along with rapidly growing urbanized cities and an increased attachment towards readymade items, which are in forceful demand with the stretching of the global market. It leads to an increase in solid-waste, and now it is a burning issue for protecting the environment in this area. Hence, consumer culture and solid-waste have interconnected aspects and contributing factors to an environmental problem in Pokhara.
New method for the isotopic study of ancient conchiolin from archaeological shells of freshwater mussels (Unionoida)
Authors: García-Vázquez Ana , Radu Valentin , Lazăr Cǎtǎlin
Published: January 2023

Freshwater mussels shells are common remains in archaeological sites of the Gumelnița culture (5th millennium BC, Romania), and were part of the diet of its ancient inhabitants. The proteins of these shells are often preserved and can be used for paleodietary and paleoecosystem reconstructions by stable isotopes.
To obtain the empirical relationship between the isotopic composition of sell organic matrix and soft tissues, we analysed the body (foot and mantle), the muscle, the conchiolin of the shell and stomach contents of modern individuals of Unio tumidus from the Danube. In addition, modern shells were digested in 5M HCl and archaeological in 1M HCl to obtain the shell organic matrix or conchiolin.
We established a quality criterion for freshwater mussel shell conchiolin of 3.6 (± 0.3) for the C:N and obtained an offset of Δ15Nconchiolin-defatted body= +0.95‰, Δ13Cconchiolin-defatted body = +0.93‰ for the soft tissues, and an offset of Δ15Nconchiolin-muscle= +1.7‰, Δ13Cconchiolin-muscle= +0.3‰ for the muscle.
Freshwater mussels from Gumelnița showed that they came from different sources (rivers, lakes, ponds…) but which not necessarily have to come from long distances since all these different habitats were present in the vicinity of the site.
Prognostic and immune infiltrative biomarkers of CENPO in pan- cancer and its relationship with lung adenocarcinoma cell proliferation and metastasis
Authors: Wang Yuanbiao , Ye Daowen , Li Ying , Lv Fenghong , Shen Wanbo , Li Hui , Tian Linghan , Fan Zongling , Li Yanling , wang Yan , Li Feng , Huang Qiubo , Chen Yan
Published: January 2023

Background The centromere protein O (CENPO) is an important member of the centromere protein family. However, the role of CENPO in pan–cancer and immune infiltration has not been reported. Here, we investigated the role of CENPO in pan–cancer and further validated its role in lung adenocarcinoma (LUAD) by in vitro experiments.
Method The UCSC Xena database and The Cancer Genome Atlas (TCGA)–LUAD data were used to assess the mRNA expression levels of CENPO. The potential value of CENPO as a diagnostic and prognostic biomarker for pan–cancer was evaluated using TCGA data and the GEPIA database. The mRNA expression profiles of LUAD patients and the corresponding clinical data were downloaded for correlation analysis. The role of CENPO in immune infiltration was investigated using the UCSC Xena database. Subsequently, RT–QPCR was performed to detect the expression of CENPO. Cell proliferation, migration, and invasion were determined using CCK–8, wound–healing assay, and transwell assay, respectively.
Results CENPO is highly expressed in most cancers, and the upregulation of CENPO is associated with poor prognosis in many cancers. CENPO expression correlates with age, TNM stage, N stage, T stage, and receipt of radiotherapy in LUAD patients, and LUAD patients with high CENPO expression have poorer overall survival (OS) and disease–free survival (DFS). In addition, CENPO expression is associated with immune cell infiltration and immune checkpoint inhibitors. Moreover, the expression of CENPO was closely related to the expression of tumor mutational load and microsatellite instability. In vitro experiments showed that CENPO expression was increased in LUAD cell lines and that knockdown of CENPO significantly inhibited the proliferation, cell invasion, and migration ability of LUAD cells.
Conclusion CENPO may be a potential pan–cancer biomarker and oncogene, especially in LUAD. In addition, CENPO is associated with immune cell infiltration and may serve as a new molecular therapeutic target and effective prognostic marker for LUAD.
The role of theory-based HIV and sexual health interventions in enhancing positive sexual behaviour outcomes and reducing risk factors among young people in Sub-Saharan Africa. A scoping review protocol.
Authors: Mukanga Bright , Taylor Myra , Dlamini Siyabonga Blessing
Published: January 2023

Background
In Sub-Sahara Africa, young people aged between 15 and 24 years are disproportionately affected by the HIV pandemic and represent a growing population in need of sexual and reproductive health (SRH) services. Several theory-based HIV prevention interventions have been developed and implemented to reduce the risk of HIV infection transmission among young people and enhance positive sexual behaviours. However, there are few evidence syntheses that highlight the role of theory-based HIV and sexual health interventions in enhancing positive sexual behaviours among young people in Sub-Saharan Africa. This review aims to map evidence on the role of theory-based HIV prevention intervention in enhancing positive sexual behaviour outcomes and reducing risk factors among young people aged 10–24 years of age in Sub-Saharan Africa.
Methods and Analysis
This scoping review will adopt the methodological framework of Arksey and O’Malley. We will identify several databases which will include PubMed, Scopus, MEDLINE, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), ProQuest One Academic, Web of Science, and Google scholar. We will search for relevant studies from 2012 onwards, written in English, and conducted in the SSA region. We will adopt a two-stage process where two independent reviewers will screen the titles and abstracts for eligibility after which they will carry out data extraction and analysis through an iterative process. This will be followed by a full-text screening of the articles from the selected titles and abstracts.
Discussion
Results from this scoping review can inform policy changes and guide future HIV programme developers to develop and implement effective theory-based HIV interventions among young people in SSA. It can provide insights on how theories can be combined to address complex behavioural characteristics. Importantly, the review will act as a backdrop to many theory-based HIV interventions that seek to integrate the positive youth development approach in existing HIV prevention programmes.
Epidemiology of autoimmune liver disease in Korea: Evidence from a nationwide real-world database
Authors: Lim Jihye , Kim Hwa Jung
Published: January 2023

Background
Autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC) are all immune-mediated chronic inflammatory liver diseases. Autoimmune liver diseases are rare, making identification and treatment difficult. To improve clinical outcomes and enhance patient quality of life, we performed an epidemiological study of autoimmune liver diseases based on real-world comprehensive data.
Results
We used National Health Insurance Service claims data in Korea from 2005 to 2019. Patients were identified using the International Classification of Disease 10th Revision code, and rare intractable disease codes assigned according to the strict diagnostic criteria. In the AIH cohort, 8,572 (83.9%) were females and the mean age at diagnosis was 56.3 ± 14.3 years. PBC also showed female dominance (83.3%) and the mean age was 57.8 ± 12.6 years. Patients with PSC showed no sex predominance and had a mean age of 57.8 ± 21.5 years. During the study period, there were 10,212, 6,784, and 888 AIH, PBC, and PSC patients, respectively. The prevalence of AIH, PBC, and PSC in 2019 were 18.4, 11.8, and 1.5 per 100,000 population, while the corresponding incidences were 2.3, 1.4, and 0.3 per 100,000 population, respectively. Analysis of sex-age-standardized data showed that the annual prevalence of these diseases is increasing. The 10-year survival rates were 89.8%, 74.9%, and 73.4% for AIH, PBC, and PSC, respectively.
Conclusions
The number of patients with autoimmune liver disease in South Korea is increasing over time. Further research on autoimmune liver disease is needed to fulfill unmet clinical needs.
Geoelectric studies in earthquake hazard assessment – the case of the Kozlodui nuclear power plant, Bulgaria
Authors: Kovacikova Svetlana , Boyadzhiev Georgi , Logvinov Igor
Published: January 2023

The study presents the results of geoelectric research for seismic risk assessment on the example of the Kozlodui nuclear power plant in Bulgaria. The image of the geoelectric structure in the study area was obtained using one-dimensional inverse electrical resistivity modeling of the full five-component magnetotelluric data and quasi-three-dimensional inverse conductivity modeling of the geomagnetic responses recorded during the summer 2021 field campaign. According to the presented results, the geoelectrically anomalous structure is divided into two levels. The near-surface anomalous structure in the immediate reach of human geotechnical activity corresponds to the electrically conductive sedimentary fill. The mid-crustal layer is coincident with the low seismic velocity zone at the brittle and ductile crust interface, revealed in previous studies. The presented results imply that the geological environment is not affected by large faults capable of transmitting seismic energy from tectonically active areas, however, in further studies, attention should be paid to the strike-slip fault systems adjacent to the study area.
Management of giant ovarian tumors in elderly adults: Preoperative evaluation using comprehensive geriatric assessment and estimation of physiologic ability and surgical stress and perioperative management effectiveness using Aron Alpha method and enhanced recovery after surgery
Authors: Kakinuma Kaoru , Kakinuma Toshiyuki , Shinohara Takumi , Shimizu Ayano , Okamoto Rora , Kaneko Ayaka , Saito Koyomi , Takeshima Nobuhiro , Yanagida Kaoru , Ohwada Michitaka
Published: January 2023

Purpose: We assessed the effectiveness of preoperative evaluation using comprehensive geriatric assessment (CGA) and estimation of physiologic ability and surgical stress (E-PASS), the Aron Alpha method, and perioperative management based on Enhanced Recovery After Surgery (ERAS) for giant ovarian tumors in elderly adults.
Methods: We focused on five giant ovarian tumor cases among elderly patients. Preoperative evaluation using the E-PASS scoring system and CGA was performed. Furthermore, the minimally invasive surgical method, the Aron Alpha method, was conducted, and we performed perioperative management using ERAS.
Results: The mean age was 75.8±8.8 years, and the comorbidities were hypertension in three cases, hyperlipidemia in two cases, angina pectoris in one case, cholecystitis in one case, and lower extremity varicose veins in one case. The mean tumor size was 21.0±5.4 cm. The examination using the E-PASS scoring system showed a preoperative risk score of 0.7±0.4, surgical stress score of 0, and comprehensive risk score of 0.3±0.3. In CGA, two cases had problems with instrumental activities of daily living and cognitive function. The mean duration of surgery was 89.0±16.6 minutes, and the mean blood loss was 56.0±65.4 mL. No surgery-associated complications were observed, and early postoperative ambulation, rehabilitation intervention, and postoperative analgesic management were conducted. No patients had prolonged hospitalization and activities of daily living decline.
Conclusion: We were able to confirm the usefulness and safety of the minimally invasive Aron Alpha method and ERAS-based perioperative management of giant ovarian tumors in elderly patients by performing a detailed preoperative evaluation using CGA and E-PASS.
Presentation, Clinical Spectrum and Chromosomal Abnormalities of Children with Turner Syndrome: A Single-Centre Experience from Sri Lanka and review of literature
Authors: Gunasekara Buddhi , Hoole Thabitha Jebaseeli , Atapattu Navoda
Published: January 2023

Background
Diagnosing Turner Syndrome at an early age (before 5 years) is important in achieving an optimal final adult. Significant delay in diagnosis has been reported worldwide. This study describes the presentation and clinical spectrum to create awareness for early referral.
Methods
Retrospective data on the initial presentation, clinical spectrum, and chromosomal abnormalities of 45 patients diagnosed with Turner syndrome was extracted from the departmental database.
Results
The mean age of diagnosis is 8.0 years. The majority (46.5%) were diagnosed between 5 to 12 years of age and 29% in adolescence. 24.5 % were diagnosed before the age of 5 years : 4.5% were diagnosed antenatally and 11% in the neonatal period. 80% of girls first presented to the Endocrine service after 5 years.
Majority presented with short stature (67%), the rest with dysmorphic features (13%), neonatal lymphedema (4.5 %), typical cardiac lesions (4.5 %), and autoimmune hypothyroidism (4.5%). The majority were referred by pediatricians (51%) and cardiologists (17%).
The commonest karyotype (55.5%) was 45, XO. 48% had cardiac lesions including bicuspid aortic valves (18%) and Coarctation of the aorta (9%). Renal anomalies were detected in 18% and ovarian abnormalities in 73%. Other manifestations included recurrent Otitis media in 18%, hearing impairment in 23%, Ophthalmological defects in 27%, autoimmune hypothyroidism in 11%, and below-average school performances in 7%.
Conclusions
The majority were diagnosed and referred to Endocrinology after 5 years of age. Delays in the evaluation of short stature and lack of awareness of TS clinical spectrum may have contributed.
Radar Vital Signs Detection by Using Optimized CNN+GRU Model
Authors: Özkaya UMUT
Published: January 2023

Wearable devices may have significant disadvantages compared to non-contact sensors. In addition, heart and respiratory rate information may be insufficient for expert evaluation. Radar sensors allow vital signals to be detected without interfering with subject activities. In this study, a high performance Convolutional Neural Network (CNN) model is proposed to classify four different types of radar vital signs. Firstly, raw radar data is converted into 2-dimensional matrix form by spectrogram method in order to analyze raw radar data in time and frequency environment. Spectrogram processing on raw radar data is required for training and testing of pre-trained CNN networks. Afterwards, high-level features obtained from pre-trained CNN networks were fused by using Canonical Correlation Analysis (CCA). These features were used to train and test for Gated Recurrent Unit (GRU) block structure optimized by Whale Optimization algorithm (WOA). The proposed Spectrogram Content Based Optimized CNN + GRU Model performance is 95.52% Accuracy (ACC), 94.74% Sensitivity (SEN), 98.29% Specificity (SPE=, 96.35% Precision (PRE), 95.40% F1-Score and 93.96% Matthews Correlation Coefficient (MCC). Our proposed method showed that preferability potential of non-destructive radar technology is more valuable than wearable technologies.
Extracellular vesicles carrying miR-6836 derived from resistant tumor cells transfer cisplatin resistance of epithelial ovarian cancer via DLG2-YAP1 signaling pathway
Authors: Song Yongmei , Zou Yazhu , Zhao Zitong , Wang Jingjing , Ma Liying , Liu Yi , Sun Li
Published: January 2023

Chemotherapy resistance is a significant cause for poor prognosis of epithelial ovarian cancer (EOC). However, the molecular mechanism of chemo-resistance remains unclear, and developing available therapies and effective biomarkers for resistant EOC is in urgent demand. Stemness of cancer cells directly results in chemo-resistance. Exosomal miRNAs rebuild tumor microenvironment (TME) and act as widely used clinical liquid biopsy markers. In our study, high throughput screenings and comprehensive analysis were performed to screen for miRNAs, which were both up-regulated in resistant EOC tissues and related to stemness, and miR-6836 was identified accordingly. Clinically, high miR-6836 expression was closely correlated with poor chemotherapy response and survival for EOC patients. Functionally, miR-6836 promoted EOC cell cisplatin resistance by increasing stemness and suppressing apoptosis. Mechanistically, miR-6836 directly targeted DLG2 to enhance Yap1 nuclear translocation, and was regulated by TEAD1 forming the positive feedback loop: miR-6836-DLG2-Yap1-TEAD1. Furthermore, miR-6836 could be packaged into secreted exosomes in cisplatin-resistant EOC cells and exosomal miR-6836 was able to be delivered into cisplatin-sensitive EOC cells and reverse their cisplatin response. Our study revealed the molecular mechanisms of chemotherapy resistance, and identified miR-6836 as the possible therapeutic target and effective biopsy marker for resistant EOC.
Lateral Sinus Flour Augmentation by Deproteinized Bovine Bone Material in Severe Alveolar Bone Atrophy: Micro Ct Study
Authors: Shpachynskyi Oleksandr , Kiss Tamás , Helyes Zsuzsanna , Kopchak Andrii
Published: January 2023

Purpose
To investigate differences in trabecular architecture revealed after lateral sinus floor augmentation (LSFA) by a two-stage approach using deproteinized bovine bone mineral (DBB) alone, based on micro-computed tomography (micro-CT).
Methods
Twenty patients (10 men and 10 women) were included in the study and divided into two groups: 1) the main group – 10 patients who needed LSFA to create the appropriate bone volume for installation of the implant with residual bone height (RBH) less than 3 mm; 2) the control group – 10 patients with RBH more than 10 mm and no necessity for bone augmentation procedures. During implant placement, bone biopsies were harvested from implant osteotomy sites for micro-CT.
Results
No significant differences in the 3-D morphometric parameters of all bone structures in the region of interest (ROI) were observed in the biopsies of the augmented bone.
Conclusion
The slight differences in trabecular architecture revealed in the present study demonstrated higher porosity, bone volume to surface ratio, anisotropy rate and decreased trabecular pattern factor in the control group as a result of a continuous functional remodeling process. Therefore, maxillary sinus floor elevation with DBB alone is a strategy thas provides an appropriate 3-D architecture of the newly formed bone tissue and adequate primary stability of the dental implants.
Hospitalizations for Coronavirus Disease 2019: An Analysis of the Occurrence Waves
Authors: Garbin Juliana Rodrigues Tovar , Leite Franciéle Marabotti Costa , Dell’Antonio Cristiano Soares Silva , Dell’Antonio Larissa Soares , Santos Ana Paula Brioschi dos , Lopes-Júnior Luís Carlos
Published: January 2023

The pandemic has been characterized by several waves defined by viral strains responsible for the predominance of infections. We aimed to analyze the mean length of hospital stay for patients with COVID-19 during the first three waves of the pandemic and its distribution according to sociodemographic and clinical variables. This retrospective study used the notifications of patients hospitalized for COVID-19 in a Brazilian state during the period of the three waves of the disease as the data source. There were 13,910 hospitalizations for confirmed COVID-19 cases. The first wave was the longest, with 4,101 (29.5%) hospitalizations, while the third, although shorter, had a higher number of hospitalized patients (N=6,960). The average length of stay in the hospital was associated with age groups up to 59 years old and from 60 to 79 y.o., high school and higher education, pregnant women (P=0,036) white and non-white race, female and male sex, and residents of the urban area (P < 0.05). Regarding the presence of comorbidities, there was a statistically significant difference in the mean number of days of hospitalization among patients with chronic cardiovascular disease, diabetes mellitus, and obesity (P< 0.05). In conclusion, the COVID-19 pandemic has been distinctly revealed among the waves.
Federated Learning based Spatio-Temporal framework for real-time traffic prediction
Authors: Kaur Gaganbir , Grewal Surender K , Jain Aarti
Published: January 2023

Wireless Sensor Network (WSN)is widely explored for traffic flow prediction. Traffic forecasting is a spatio-temporal problem because of the dynamic nature of road traffic. The data collected from users for traffic prediction is often private in nature. These characteristics make it necessary to develop a framework for accurately predicting traffic flow while maintaining user data privacy. This paper proposes a Federated Learning-based spatio-temporal approach termed Fed-STGRU for traffic prediction without transmitting raw user data over the network. Federated Learning is a distributed machine learning approach incorporating techniques like Stochastic Gradient Descent for data privacy preservation. The proposed scheme preserves privacy while attaining comparable accuracy and loss as baseline algorithms, FedAvg and TGCN.
VLSI Architecture for Implementing OTFS
Authors: Shadangi Ashish Ranjan , Das Suvra Sekhar , Chakrabarti Indrajit
Published: January 2023

Orthogonal Time Frequency Space (OTFS) modulation is proposed to support high-speed and reliable vehicular communication scenarios, which is a novel two-dimensional (2D) delay-Doppler domain modulation technique. Compared with traditional modulation schemes such as orthogonal frequency division multiplexing (OFDM), OTFS has displayed better performance in very high-mobility wireless channels. In this work, we have proposed the novel VLSI architecture for OTFS in the Additive White Gaussian Noise (AWGN) channel condition and shown the resource utilization report of our proposed architecture to implement on Field Programmable Gate Array (FPGA) board, along with the relationship between inputs and outputs of the OTFS signal in the delay-Doppler domain.
Biodiversity in cities. The effect of spatial scale and biodiversity data in heterogeneous landscapes.
Authors: Lopez Carol X. Garzon , Savickyte Gabija
Published: January 2023

The assessment and monitoring of biodiversity in urban areas has been performed until now through dedicated on site studies and a small number of studies using online digital biodiversity databases. The question remains as to what extent an efficient and effective monitoring scheme could be implemented, one that not only facilitates comparisons across time and space, but also serves as an early change detection tool that complement local studies. Global Biodiversity Information Facility (GBIF) has been promoted for its central role, gathering and harmonizing biodiversity data worldwide, thereby facilitating the assessment and monitoring of biodiversity in multiple ecosystems. While GBIF data has been investigated for its potential at large scales (national, global) and in natural ecosystems, the question remains as to what extent, and in which context, is GBIF data applicable to urban biodiversity assessment and monitoring. In this study we have shown that the type of organisms surveyed -as well as its ecology and the spatial scale(s) of the assessments are critical to identify the effect of urban and green infrastructure in cities.
Synthesis and investigation on synergetic effect of activated carbon loaded silver nanoparticles with enhanced photocatalytic and antibacterial activity
Authors: Ragupathy S. , Ramasundaram Subramaniyan , Krishnakumar M. , Babu A. C. Ramesh , Govindarasu Mydhili , Ramu A. G. , Oh Tae Hwan , Choi Dongjin
Published: January 2023

In this study, we used a cashew nut shell to successfully manufacture silver nanoparticle-loaded cashew nut shell activated carbon (Ag/CNSAC). XRD, XPS, SEM with EDS, FT-IR, and BET analysis are used to characterize the products' structural and chemical contents. The XRD, XPS, and EDS data provided convincing proof that Ag loaded on CNSAC formed. The energy dispersive spectrum analysis and X-ray diffraction pattern both supported the face-centered cubic and amorphous structures of Ag/CNSAC. The SEM micrographs showed inner surface development of Ag NPs and many tiny pores in CNSAC. The photodegradation of methylene blue (MB) dye by the Ag/CNSAC photocatalyst was investigated. This effective degradation of MB dye by Ag/CNSAC is attributed to the cooperative action of Ag as a photocatalyst and CNSAC as a catalytic support and adsorbent. In tests with gram-positive and negative bacteria including Escherichia coli (E. coli) and Staphylococcus (S. aureus), the as-product Ag/CNSAC showed outstanding antibacterial efficacy. Additionally, this study demonstrates a workable procedure for creating an affordable and efficient Ag/CNSAC for the photocatalytic eradication of organic contaminants.