bluuebunny/crossref_metadata_2025 huggingface dataset:
Offshore Implementation of Temperature Microchip Under Critical Well Conditions
Authors: Li Bodong , Dokhani Vahid , Gooneratne Chinthaka , Zhan Guodong , Shi Zhaorui
Published: September 2021

Drilling microchips are millimeter-size sensing devices, capable of measuring in-situ downhole temperature, and at the same time, withstanding harsh downhole conditions. In this work, 140 microchips were dropped from the drill pipe during the connections. The devices travel through the bottomhole assembly (BHA), drill bit, annulus, and eventually get recovered at the shale shaker. A total of 80 microchips were recovered at the shaker, which resulted in a physical recovery rate of 57%. The microchip recorded the dynamic temperature profile of the entire wellbore including a long openhole section only a few hours before the well turned into total loss. The data downloaded from the microchip shows an excellent consistency throughout the three tests. The measured dynamic bottomhole temperature provides a correction of 10 deg F to the best practice of the industry in terms of downhole thermal simulation, offering valuable measured input for the optimization of thermal activated LCMs or cementing job. To our best knowledge, it is the industry's first successful attempt in logging an openhole section in a highly loss zone. The microchip recorded the dynamic temperature profile of a long open hole only a few hours before the well turned into a total loss. Due to the lack of industrial solutions for downhole temperature measurement under such conditions, the microchip technology showed unique advantage for critical applications, especially in operations with highly valued assets.
Sustaining Remote Operations Adoption Post Pandemic: A Major Key to a Net Zero Future
Authors: Richard Yates Martin , Brahim Imed Ben , AlNofaily Shady Mohamed , Ernesti Klaus-Dieter
Published: September 2021

The North Sea has always been a pioneer for the adoption of remote operations services (ROS) in offshore drilling applications. Drilling services such as Measurement While Drilling (MWD), Logging While Drilling (LWD) and/or mud logging (ML) have been performed with an element of ROS for over the last two decades. Early adoption of these remote services delivered initial benefits to operators such as reducing HSE risks related to the travel and accommodation of field service employees at offshore rig sites. Meanwhile service companies were able to explore the added efficiencies gained by having multi-skilled employees providing a higher level of support to customers while also gaining additional agility to manage their personnel through tighter market cycles. The mutual benefit of this early adoption created a solid foundation for ROS to expand the scope of influence in drilling operations to include Directional Drilling (DD).

Despite the maturity of ROS within a select community of operators in the North Sea, the industry standard for service delivery in offshore operations has continued to require field service employees to perform DD, MWD, and LWD services at rig sites until this past year. With the COVID-19 pandemic in 2020, operators and service companies were quickly and abruptly confronted with the challenges of new HSE regulations, travel restrictions, and increased financial scrutiny. ROS presented a tailored solution to not only sustain business continuity but also create added efficiency, consistency, and risk management.

Over the course of 2020, adoption of ROS rapidly accelerated across offshore operations in the North Sea and reached up to 100% penetration in key sectors. This tremendous achievement has made a significant impact on project performance and HSE efficiencies by ensuring on time service delivery while reducing personnel on board (POB). In addition, as more operators and services companies explore ways of reducing their carbon footprints and achieving a net zero future, ROS has proven to be a way to significantly reduce carbon emissions associated with transportation and utilities of offshore personnel.

This paper discusses the methods that enabled a record high adoption rate for ROS and explores the critical components of its success. It illustrates the management of change in service delivery processes, the introduction of new technology to unlock greater productivity and synergies, and the new approach to design the core competencies needed to support ROS. It also describes the need for flexible ROS service models to meet the specific project needs of various operators. The paper concludes with the numerous benefits realized through ROS such as improved performance and consistently reliable service delivery. The paper also examines the resulting carbon emission reduction, how to quantify it, and the role ROS plays in achieving a net zero emissions future.
Natural Language Processing and Text Mining Approaches in Production Shortfalls Analytics: Methodology, Case-Study and Value in the North Sea
Authors: Bernier Edgar , Perrier Sebastien
Published: September 2021

Maximizing operational efficiency is a critical challenge in oil and gas production, particularly important for mature assets in the North Sea. The causes of production shortfalls are numerous, distributed across a wide range of disciplines, technical and non-technical causes.

The primary reason to apply Natural Language Processing (NLP) and text mining on several years of shortfall history was the need to support efficiently the evaluation of digital transformation use-case screenings and value mapping exercises, through a proper mapping of the issues faced. Obviously, this mapping contributed as well to reflect on operational surveillance and maintenance strategies to reduce the production shortfalls.

This paper presents a methodology where the historical records of descriptions, comments and results of investigation regarding production shortfalls are revisited, adding to existing shortfall classifications and statistics, in particular in two domains: richer first root-cause mapping, and a series of advanced visualizations and analytics.

The methodology put in place uses natural-language pre-processing techniques, combined with keyword-based text-mining and classification techniques. The limitations associated to the size and quality of these language datasets will be described, and the results discussed, highlighting the value of reaching high level of data granularity while defeating the ‘more information, less attention’ bias.

At the same time, visual designs are introduced to display efficiently the different dimensions of this data (impact, frequency evolution through time, location in term of field and affected systems, root causes and other cause-related categories). The ambition in the domain of visualization is to create User Experience-friendly shortfall analytics, that can be displayed in smart rooms and collaborative rooms, where display's efficiency is higher when user-interactions are kept minimal, number of charts is limited and multiple dimensions do not collide.

The paper is based on several applications across the North Sea. This case study and the associated lessons learned regarding natural language processing and text mining applied to similar technical concise data are answering several frequently asked questions on the value of the textual data records gathered over years.
Complete EOS Thermal Formulation for Simulation of CO2 Storage
Authors: Moncorgé Arthur , Petitfrère Martin , Thibeau Sylvain
Published: September 2021

Storage of CO2 in depleted gas reservoirs or large aquifers is one of the available solutions to reduce anthropogenic greenhouse gas emissions. Numerical modeling of these processes requires the use of large geological models with several orders of magnitude of variations in the porous media properties. Moreover, modeling the injection of highly concentrated and cold CO2 in large reservoirs with the correct physics is introducing numerical challenges that conventional reservoir simulators cannot handle. We propose a thermal formulation based on a full equation of state formalism to model pure CO2 and CO2 mixtures with the residual gas of depleted reservoirs. Most of the reservoir simulators model the phase-equilibriums with a pressure-temperature based formulation. With this usual framework, it is not possible to exhibit two phases with pure CO2 contents. Moreover, in this classical framework, the crossing of the phase envelope is associated with a large discontinuity in the enthalpy computation which can prevent the convergence of the energy conservation equation. In this work, accurate and continuous phase properties are obtained basing our formulation on enthalpy as a primary variable. We first implement a new phase-split algorithm with input variables as pressure and enthalpy instead of the usual pressure and temperature and we validate it on several test cases. This algorithm can model situations where the mixture can change rapidly from one phase to the other at constant pressure and temperature. Then treating enthalpy instead of temperature as a primary variable in both the reservoir and the well modeling algorithms, our reservoir simulator can model situations with pure or near pure components as well as crossing of the phase envelope that usual formulations implemented in reservoir simulators cannot handle. We first validate our new formulation against the usual formulation on a problem where both formulations can correctly represent the physics. Then we show situations where the usual formulations fail to represent the correct physics and that are simulated well with our new formulation. Finally, we apply our new model for the simulation of pure and cold CO2 injection in a real depleted gas reservoir from the Netherlands.
Mooring Integrity in Electrification Projects - Learning from the Floating Production Sector in Early Years of Harsh Environment Operations
Authors: Robinson Nigel J. , Rosie Scott M.
Published: September 2021

There is a growing interest in electrification of offshore production assets using renewable energy devices. Typical configurations have arrays of power generating devices, located a short distance away from the platform and linked by subsea cables. To date, floating offshore wind turbines and wave energy converters have been trialed as sources of electrical power. With hulls, moorings and cables set out in close proximity, there is a unique station keeping risk profile that needs to be managed, to ensure fitness for service through the life of the field.

When developing electrification schemes, there is a body of relevant research that can be accessed to help identify and control mooring risks. In the early days of North Sea floating production, the industry encountered multiple instances of accelerated mooring line degradation. The causes and mitigations were researched through joint industry projects, leading to the publication of operating guidance through OGUK, the HSE, ISO and others. This guidance, along with a series of milestone papers, offers a valuable body of learning that is available to electrification projects.

In this paper, the authors survey the integrity threats and challenges affecting moorings in electrification schemes that are based around small arrays of wind turbines or wave energy converters. Through qualitative risk assessment, comparison is made to mooring integrity issues in the floating production sector. The relevance of guidance from oil and gas is reviewed. Consideration is given to the consequences of a line failure, and how in some cases these may represent intolerable risks. It is argued that a through-life integrity risk assessment is essential for successful deployments; also, that existing OGUK guidance on mooring integrity be extended, to reflect the specifics of electrification projects.
Application of Monte Carlo Analysis and Self-Organizing Maps to De-Risk Compressor Re-Wheeling
Authors: Nelson Greg Michael , Barrie Robert
Published: September 2021

Objectives / Scope

Re-wheeling compressors to match late-life field conditions gives significant benefits in operational efficiency and carbon reduction. But changing the compressor wheels and increasing shaft speeds also introduces a risk in terms of the rotor-dynamic stability of the system. API assessments use deterministic methods to assess the design change, but give less information in terms of the key risks and how to control them. This paper outlines new methods for assessing rotor dynamic risks to compressors during re-wheeling and their value over traditional methods.

Methods

New methods were developed to extend beyond the API requirements in order to assess and manage the rotor-dynamic risk as part of a peer review process of re-wheeling a compressor train. A combination of sensitivity studies on key parameters and Self Organizing Maps (SOMs - a machine learning technique) was used to identify the factors which present the greatest risk to the re-wheeling, and a Monte Carlo analysis was used to identify the change in risk of rotor-dynamic problems when compared with the existing machine.

Results

The Monte Carlo analysis used random distributions of factors on key input parameters, and the same factors were applied to the existing and re-wheeled designs. It identified that although the re-wheeled design was nominally more stable than the existing design according to the API analysis, it actually presented a greater risk of instability. This is because the distribution of resulting stability values had a higher mean but a greater spread than the existing machine when subject to uncertainty in input parameters. Since the existing machine is free from dynamics problems, the parameter combinations which resulted in an unstable existing machine could be discounted, but the resulting subset of factors when applied to the re-wheeled design still gave some unstable cases. Therefore, the fact that the existing machine is free from dynamics problems does not in itself discount the possibility of problems following the re-wheel.

SOMs were used to identify the components which posed the greatest risk to the re-wheeled design. This highlighted that low stiffness in two particular bearings along the high speed shaft would pose the greatest risk to shaft stability, meaning that close attention can be paid by the operators and OEMs to this to manage the risks as the re-wheel progresses.

Novel Information

This work shows that probabilistic and machine learning techniques have significant value in managing risks during compressor re-wheeling, highlighting risks which would not be identified using standard deterministic methods and focusing attention on the aspects which are most important to manage them.
Are There Potentially Significant Long-Term Health Consequences of Exposure to Fine Airborne Particulate Matter PM10 to Personnel on the United Kingdom's Offshore Drilling Rigs?
Authors: Grainger Samuel Thomas
Published: September 2021

Drilling mud is a slurry comprising oil, water, and chemical additives. Mud is critical to drilling a modern well as it is circulated down a wellbore to remove rock cuttings and to power the drill bit. A significant volume of this drilling mud is used and later recirculated. The drilling mud warms at depth, creating steam, which holds suspended PM and dissolved chemicals. Many of the pieces of equipment are open or only partially enclosed, allowing for steam generation, while other processes generate aerosolised sprays. There is a significant potential for petroleum workers to become exposed and potentially suffer health effects because of drilling mud exposure. This study aims to find the major sources of PM10 on petroleum wells and quantify the levels of exposure and health hazard associated with drilling mud on petroleum rigs. A literature search was performed, which included all available materials which contained static or mobile concentrations of PM10 or oil mist within the UK or international petroleum drilling sites with a preference for North Sea operations. The study predicts the total PM10 by estimating the combined impact of both solid PM and oil mist. Using this conversion, it is also possible to estimate PM10 concentrations when using water-based muds. The work designates and discusses the expected health ramifications of excess exposure. A quantitative assessment of the risk of silicosis 15 years post-exposure is also calculated, predicting dire consequences to petroleum personnel in the long term. The exposure assessment methods, hygienic standards, and preventive measures are also addressed briefly.
Ensuring That Fatigue is Managed in Oil and Gas Operations
Authors: Holmes Alexandra , Ruscitto Cristina , Booth Sarah
Published: September 2021

As in any shiftworking industry, fatigue poses a hazard to workers within the oil and gas industry, irrespective of job role and site location. In order to demonstrate adherence to health and safety regulations, operators can be expected to manage shift patterns and hours of work, such that they are appropriate and do not result in unnecessary levels of fatigue that may reduce the safety of the operation. Reliance on hours of work limitations (for example the European Working Time Directive) or industry normalised working patterns may no longer be considered sufficient to ensure that the risk posed by fatigue is appropriately managed.

This paper presents how a scientific approach can be applied and adapted to suit the context and the populations being studied in order to answer specific operational questions and provide tailored fatigue risk mitigations. It describes a method by which site and job role fatigue levels can be assessed, in order for appropriate controls to be implemented. It will use case studies to illustrate how data collection methods are tailored to reflect specific operational environments. Data collection is particularly important in parts of the industry where common shift arrangements differ from those which have historically been studied.

The method outlines an approach to rigorously assess contributors to fatigue and fatigue levels in an organisation following appropriate scientific methods. Both subjective and objective data are collected, using methods such as fatigue and sleepiness scales, sleep diaries and collection of objective sleep data using validated sleep tracking devices. The approach is specifically tailored to the population of interest – reflecting their shift pattern, and collecting further data on workload, task demand, and operational or location-specific factors (for example travel to site, onsite sleeping facilities, or sea sickness on floating platforms). The method also allows for inferences to be made about the impact of circadian misalignment and shift timing on sleep, performance and mood.

The method presented in this paper has been used in field data collection in two very different environments. These studies are used as case studies to examine how the methodology can be tailored to ensure that the collected data are appropriate to the operation being studied, and lessons learned to improve the methods in the future.
Industry First AI-Powered Fully Automated Safety Observation System Deployed to Global Offshore Fleet
Authors: Brown Nassima , Brown Adrian , Degupta Abhijeet , Quinn Barry , Stringer Dustin , Yankov Bozhidar
Published: September 2021

As the oil and gas industry is facing tumultuous challenges, adoption of cutting-edge digital technologies has been accelerated to deliver safer, more efficient operations with less impact on the environment.

While advanced AI and other digital technologies have been rapidly evolving in many fields in the industry, the HSE sector is playing catch-up. With the increasing complexity of risks and safety management processes, the effective application of data-driven technologies has become significantly harder, particularly for international organizations with varying levels of digital readiness across diverse global operations. Leaders are more cautious to implement solutions that are not fit-for purpose, due to concerns over inconsistencies in rolling out the program across international markets and the impact this may have on ongoing operations.

This paper describes how the effective application of Artificial intelligence (AI) and Machine Learning (ML) technologies have been used to engineer a solution that fully digitizes and automates the end-to-end offshore behavior-based safety program across a global offshore fleet; optimizing a critical safety process used by many leading oil & gas organization to drive positive workplace safety culture. The complex safety program has been transformed into clear, efficient and automated workflow, with real-time analytics and live transparent dashboards which detail critical safety indicators in real time, aiding decision-making and improving operational performance.

The novel behavior-based safety digital solution, referred to as 3C observation tool within Noble drilling, has been built to be fully aligned with the organization's safety management system requirements and procedures, using modern and agile tools and applications for fully scalability and easy deployment. It has been critical in sharpening the offshore safety observation program across global operations, resulting in a boost of the workforce engagement by 30%, and subsequently increasing safety awareness skill set attainment; improving overall offshore safety culture, all while reducing operating costs by up to 70% and cutting carbon footprint through the elimination of 15,000 manhours and half a million paper cards each year, when compared to previously used methods and workflows
First Use of Machine Learning for Penetration Rate Optimisation on Elgin Franklin
Authors: O'Leary Daniel , Polak Deirdree , Popat Roman , Eatough Oliver , Brian Tom
Published: September 2021

Optimising the Rate of Penetration (ROP) on Development wells contributes heavily to delivery of projects ahead of schedule and has long been a goal for drilling engineers. Selecting the best parameters to achieve this has often proved difficult due to the extensive quantities of data concerning formation types, bottom-hole assembly (BHA) design and bit specifications. Legacy drilling data can also be vast and not well characterised, making it very difficult to robustly analyse manually. Additionally, multiple stakeholders can each have their own hypotheses on how to improve drilling performance, including bit vendors, directional drilling companies, drilling engineers and offshore supervisors, creating further confusion in this field.

Together with its team of data scientists, TotalEnergies E&P UK (TEPUK) has utilised machine learning to analyse field and equipment data and produce guidelines for optimised drilling rate. The machine learning algorithm identifies parameters which have a statistical likelihood of improving ROP performance whilst drilling. The model was developed using offset well data from TotalEnergies' Realtime Support Centre (RTSC) and bit design information. This represented the first use of Machine Learning in the 20+ years of drilling on Elgin Franklin. Adapting to this new data-based method forms part of a wider digital revolution within TEPUK and the Offshore Drilling Industry. In this case, an integrated approach from the data scientists, drilling engineers and supervisors was required to transition to a new way of working.

The first trial of using optimised parameters was on a recent Franklin well (F13) in the Cretaceous Chalk formations. The model generated statistically optimised parameter sheets which were strictly executed on site. Within the guideline sheets were suggested ranges of Revolutions per Minute (RPM), Flowrate, Weight on Bit (WOB) and Torque, as well as recommendations for bit blades and cutters. Heatmaps were generated to show what combination of WOB and RPM would likely achieve best ROP in each sub formation. The parameter range defined was specifically narrow to reduce any time spent varying parameters. In practice the new digital approach was successfully adopted offshore and contributed to the delivery of the 12 ½" and 8 ½" sections in record time for the field, resulting in significant savings versus AFE.

Following the success of the guideline implementation, steps have been taken to integrate the machine learning model with live incoming data on TotalEnergies' digital drilling online platform. Since the initial trial on Franklin, online ROP optimisation features have been deployed on the Elgin field and currently provide live parameter guidance, a forecast to section TD and data driven bit change scenario analyses whist drilling.
Impact of CO2 Specifications on Design and Operation Challenges of CO2 Transport and Storage Systems in CCUS
Authors: Nazeri Mahmoud , Haghighi Hooman , Mckay Craig , Erickson Dale , Zhai Suling
Published: September 2021

The presence of impurities in captured CO2 plays a vital role in the safe and effective CO2 transport and storage in the CCUS chain. Impurities can significantly increase the cost of processing, transport, and storage and moreover add additional challenges to the design, operation, health and safety and integrity aspects. The effects of various impurities on the aforementioned challenges have been addressed in this work.

Despite the importance of this area, there are still some knowledge gaps in terms of assessing the impact of CO2 specification on CCUS design and operations. International standards address different elements of the CCS chain, but none cover the full chain or consider the full chain economics. There are also differences between industry and leading CO2 authorities regarding the potential issues and challenges of implementing those standards. This paper reviews available standards and references which provide specifications/limitations for impurities for the purpose of transport and storage.

In this work, the modified cubic EoSs and GERG EoS have been used to predict the thermodynamic properties and tuned viscosity models have been used for the prediction of transport properties. The required specifications for the quality of CO2 streams have been investigated using the above methodology for fluid properties, followed by the use of commercial software packages for thermohydraulic analysis of CO2 pipelines. Additionally, the storage capacity and geochemistry of fluids under high-pressure and high-temperature (HPHT) storage conditions were investigated.

The impact of impurities has been assessed based on various CO2 sources using commercial capturing technologies. The assessment considered the impact of impurities on thermodynamic, thermohydraulic, integrity and operation of CO2 transport, injection, and storage system. This would include the effects of various types of components and their typical concentrations, e.g., water content, non-condensable gases (N2, O2, CH4, Ar, H2and CO), toxic gases (H2S and SO2), and hydrocarbons, on the thermophysical properties including density, viscosity, phase envelope and hydraulic parameters. A comparison of modelling results against the available experimental data measured at elevated pressure and temperature conditions have also been presented.

This paper has mainly focused on the lessons learned from past CO2 transport design and operational experiences in order to identify the areas where it could lead to an optimised system in terms of design, costs, and operation. Additionally, past experience in the design of CO2 pipelines and operation of CO2 injection has been used to identify opportunities where CO2 specifications and guidelines could potentially be modified in order to achieve an optimised and cost-effective CO2 transport and injection system.

Keywords: CO2 Specification; CO2 Transport Pipelines; Design and Operation Challenges; CO2 impurities; CCUS;
Microbiome-Gut-Brain-Axis Communication Influences Metabolic Switch in the Mosquito Anopheles Culicifacies
Authors: DIXIT RAJNIKANT
Published: September 2021

Periodic ingestion of a protein-rich blood meal by adult female mosquitoes causes a drastic metabolic change in their innate physiological status, which is referred to as ‘metabolic switch. Although the down-regulation of olfactory factors is key to restrain host-attraction, how the gut ‘metabolic switch’ modulates brain functions, and resilience physiological homeostasis remains unexplored. Here we demonstrate that the protein-rich diet induces the expression of brain transcripts related to mitochondrial function and energy metabolism, possibly to cause a shift of the brain’s engagement to manage organismal homeostasis. A dynamic expression pattern of neuro-signalling and neuro-modulatory genes in both gut and brain, establishes an active brain-distant organ communication. Disruption of this comunication through decapitation, does not affect the modulation of the neuro-modulator receptor genes in the gut. In parallel, an unusual and paramount shift in the level of the Neurotransmitters (NTs), from the brain to the gut after blood feeding, further supports the idea of the gut’s ability to serve as a ‘second brain’. Finally, a comparative metagenomics evaluation of gut microbiome population dynamics, highlighted that blood-feeding not only suppresses Enterobacteriaceae family member by 50%, but favors rapid proliferation of Pseudomonadales to 46% of the total community. Notable obesrvation of a rapid proliferation of Pseudomonas bacterial sp. in the gut correlates a possible cause for the suppression of appetite after blood-feeding. Additionally, an altered NTs dynamics of naïve and aseptic mosquitoes provide the initial evidence that gut-endosymbionts are key modulators for the synthesis of major neuroactive molecules. Conclusion: Our data establish a new conceptual understanding of microbiome-gut-brain-axis communication in mosquitoes.Data deposition: Mosquito Brain RNAseq data are accessible under Accession IDs: SRR9853884 (Ac-Br-SF); SRR9853885 (Ac-Br-BF-30Min), SRR9853883 (Ac-Br-BF-30hrs) at NCBI repository. Mosquito Gut metagenomics data are accessible under accession IDs: SRR12579422 (Ac-MG-SF); SRR12622557 (Ac-MG-BF) at NCBI repository.
Scattered Trees as Crucial Elements in Maintaining Urban Diversity: A Case Study with Canopy ants in a Biodiversity Hotspot
Authors: Mendonça-Santos Renata Grasiele , Antoniazzi Reuber , Camarota Flávio , Reis Yana , Viana-Junior Arleu
Published: September 2021

Urban environments are under a high degree of human disturbance, which profoundly changes their abiotic characteristics, affecting the biotic communities. A conspicuous element in cities are scattered trees, often included in urban planning around the world. These trees are key elements for urban ecological processes and services and act as islands of resources (i.e., food and shelter) for a considerable arthropod’s diversity, such as ants. Studies involving ants in urban environments often focus on ground-dwelling ants, and few studies seek to glimpse the ants that occupy scattered trees and, even less, how these ants and trees interact within cities. This study aimed to investigate the ant communities foraging day and night on trees in an urban area inside a biodiversity hotspot, the Brazilian Atlantic Forest. Specifically, we investigated how tree characteristics (tree size, tree isolation, presence of extrafloral nectaries, and the tree origin, i.e., native and exotic) modulate ant diversity and ant-plant interactions. We found that the species composition is different between day and night, as well as the central core of generalist ant species of day and night interaction networks. The tree size increases beta-diversity among trees only of the nocturnal ant community, while none of the tree characteristics shaped the ant community. This study is the first to address the role of scattered trees in maintaining the diversity of arboreal ants in urban landscapes, focusing on species diversity and their interaction networks. Overall, we provide insights supporting the conservation value of scattered trees in maintaining urban biodiversity.
Cavities Herald Persistent Sputum Positivity
Authors: Jawad Nadia , Saifullah Nausheen , Ahmed Naseem , Jafri Saira
Published: September 2021

Aim: To determine the factors associated with persistent sputum positivity at the end of two months of treatment in patients presenting with (drug-susceptible) pulmonary tuberculosis at a tertiary care hospital in Karachi.Setting: A cross-sectional study was conducted at the Department of Chest Medicine (Ward 12), Jinnah Postgraduate Medical Center (JPMC), Karachi over six months.Methods:A sample of 73 consenting, newly diagnosed, smear positive drug-susceptible pulmonary tuberculosis patients was studied. Demographic (age, gender, height, weight and duration of tuberculosis, body mass index (BMI), socioeconomic, occupational, marital, educational and residential statuses) and clinical factors (chest X-ray extent and cavities, initial smear results, diabetic and smoking statuses) which may be associated with sputum non-conversion were entered in a proforma. Patients were followed up at two months of treatment with a sputum smear. Data analysis was done on SPSS-20.0.Results:Rate of sputum positivity after two months of treatment was 17.8%. None of the factors was associated with persistence of sputum positivity except for the presence of chest radiograph (CXR) cavities; which made it 5.5 times more likely that the patient would remain smear-positive at two months (p=0.035).Conclusion:The finding of CXR cavities makes it highly likely that a pulmonary tuberculosis patient may remain infectious or have an unfavourable outcome despite taking treatment for 2 months. Clinicians and national policy-makers should thus bear in mind the implications this can have with regard to disease control and pay particular attention in terms of stringent monitoring and Directly Observed Treatment Short-course (DOTS) provision.
Neoadjuvant Chemotherapy Followed by Surgery/Chemoradiotherapy Versus Radical Chemoradiotherapy in Stage IB2, IIA2, IIB Locally Advanced Cervical Carcinoma: A Retrospective Multicenter Study of 388 Patients
Authors: He Mingyuan , Su Xing , Song Honglin , Li Ying , Gu Fei , Sun Xiaoge , Li Xiaofan , Cheng Guanghui
Published: September 2021

Purpose: The present study aimed to compare the oncologic outcomes and side effects between neoadjuvant chemotherapy followed by surgery/chemoradiotherapy and radical chemoradiotherapy for locally advanced cervical carcinoma (LACC).Methods: We conducted a retrospective review of patients with LACC (IB2, IIA2 and IIB stages) from six hospitals between June 2007 and January 2017. Results: A total of 388 patients were included, in which 278 patients received radical chemoradiotherapy (Standard group), and 110 patients received neoadjuvant chemotherapy. 65 patients of the 110 received radical hysterectomy (Surgery group), and 45 received chemoradiotherapy (Neo-Ra group). The 5-year overall survival (OS) in Surgery group (92.5%) was similar to that of the Standard group (84.9%), but both groups had higher OS rates than Neo-Ra group (75.6%). The 5-year disease-free survival (DFS) and progression-free survival (PFS) showed no differences among the three groups, respectively. There were no significant differences for grades 1-3 gastrointestinal and genitourinary toxicities among the three groups. No patient had grade 4 adverse effects. In multivariate analysis, tumor regression (CR vs. PR+SD+PD), pathological type (squamous cancer vs. non-squamous cancer) and lymph node metastasis (positive vs. negative) were considered as independent predictors of OS. Furthermore, besides above factors, the maximum diameter of tumors and adjuvant chemotherapy were also considered as significant prognostic factors for DFS and PFS.Conclusion: These findings showed that neoadjuvant chemotherapy followed by radical hysterectomy as a feasible and reliable therapy, resulting in encouraging oncologic outcomes and low side effects when compared to those obtained by standard chemoradiotherapy for IB2, IIA2, IIB stage cervical carcinoma patients.
Short Note: Extracellular Export and Consumption of Glucose in Antarctic Sea Ice
Authors: Kennedy Fraser , McMinn Andrew , Martin Andrew
Published: September 2021

Glucose microsensors were used to measure extracellular glucose exudation and consumption in a sea ice algal community. Glucose export increased with increasing irradiance between 15 and 512 µmol photons m− 2 s− 1. This export correlated with declining FvFm values and increasing NPQ values, implying that glucose export resulted from exposure to above optimal irradiances. Glucose concentrations in samples treated with DCMU to block photosynthesis, declined at all irradiances. Bacterial consumption of glucose was between 6% and 34% of extracellular export per hour.
Consumption-Based CO2 Emissions Accounting And Scenario Simulation In Asia And Pacific Region
Authors: Rahman Mohammad Mazibar , Anan Nishat , Mas Abu Hashan Md , Hasan Mahmudul , Tseng Ming-Lang
Published: September 2021

This study uses a consumer-based accounting approach to evaluate CO2 emission factors of 17 major Asia and Pacific countries that distribute all emissions in the supply chain to the commodity up to the final consumption location due to the influence of a country's consumption patterns. In addition, the number of emissions connected with each country's consumption of products and services, mainly in Asia and the Pacific countries, has received little attention. This study contributes to understand the effects of the country's consumption of products and services on carbon emission peaks and formulate efficient carbon-mitigation plans for governments and decision-makers. The accelerating economic growth and industrialization have posed significant challenges to global carbon-mitigation efforts and climate change response; as a result, each country has been provided a higher emphasis on CO2 emission. The Monte Carlo simulation technique has been used to create a dynamic scenario simulation model to investigate possible future peaks of Asia and Pacific countries' carbon emissions, considering the uncertainties of factors. The result shows that total consumption-based CO2 emissions are remarkable in the three Asian countries, including China (387451.95 metric tons (Mt) CO2), Japan (185259.60 Mt CO2), and India (100720.46 Mt CO2). In South Korea, Brunei, and Taiwan, annual consumption emissions are 1.77, 1.62, and 1.49 tons of CO2 per person. In terms of final consumption, the household sector is the supreme noteworthy donor to consumption-based emissions, accounting for 27–56%. The household sector probably peak at 19.7 Gt CO2 as per the dynamic scenario simulation. As for three other types of final demand, the government expenditure will possibly reach at highest 44.0 Gt CO2 by the next 30 years while the capital formation will probably hit its highest emissions at 149.5 Gt CO2.
KLF4 Inhibits Activation of Human Hepatic Stellate Cells LX-2 in vitro
Authors: Xue YinKai , TAN Jun , Yao TianCi , Chen QingYong , Jiang Ke , Wang ZhiRui , Zheng Hai
Published: September 2021

BackgroundHepatic Stellate Cell (HSC) represents a key factor in liver fibrosis. Early-stage liver fibrosis is still reversible and is intimately associated with the state of HSC. KLF4 has been shown to play a pivotal role in a wide array of physiological and pathological processes. MethodsIn this study, we examined the effect of Kruppel-like factor 4 (KLF4) on the proliferation, apoptosis and phenotype of HSC in resting state in human HSC LX-2 cells, and the role KLF4 plays in the maintenance of the resting state of HSC, with an attempt to provide an experimental basis for the diagnosis, treatment and prognosis evaluation of liver fibrosis. We designed a KLF4 lentiviral vector and a KLF4 shRNA lentiviral vector, to up-regulate and silence KLF4 expression in LX-2 cells by transfection. We examined LX-2 cell proliferation by plate cloning and CCK8 assay, flow cytometrically detected cell cycle distribution and cellular apoptosis rate and determined some quiescence and activation markers of HSC by Western blotting. ResultsOur result showed that E-cadherin and ZO-1, dubbed quiescent HSC markers, were significantly increased. N-cadherin while a-AMA, known as activated HSC marker, was significantly decreased. In contrast, cell proliferation and apoptosis rate were elevated in LX-2 cells whose KLF4 expression had been silenced. Conclusions﻿Our results indicated that KLF4 inhibited the proliferation and activation of human HSC LX-2 and might be a key regulatory protein in the maintenance of quiescence of HSC and might serve as a target for the inhibition of hepatic fibrosis.
A Multi-objective MILP Model Proposed to Optimize a Supply Chain Network for Microalgae-based Biofuels and Co-products: A Case Study in Iran
Authors: Zerafati Mohammad Ehsan , Bozorgi-Amiri Ali , Golmohammadi Amir-Mohammad , Jolai Fariborz
Published: September 2021

Recently, due to the efficiency of cultivating microalgae, researchers and investors have paid considerable attention to the production of different biofuel products that are environmentally friendly. In this study, a two-stage deterministic model is proposed to design a microalgae-based biofuels and co-products supply chain network (MBCSCN). In the first stage, the appropriate locations for the cultivation of microalgae are identified through the analytical hierarchy process (AHP). In the second stage, a deterministic mathematical mixed integer linear programing (MILP) model is developed for a period of five years based on the criteria of economic and environmental impacts. The economic objective function maximizes the overall profit, while the environmental impacts objective function seeks to minimize the consumed fossil fuel throughout the supply chain. Then, a multi-objective MILP optimization problem is solved using the ε-constraint method. The proposed model is evaluated through a case study in Iran. It has helped to identify appropriate locations for the cultivation of microalgae and to specify the required quantity of feedstock, the species of microalgae, the required technology, and the transportation modes in each step of the supply chain.
A Novel Technique for Endoscope Progression in Gastroscopy Resection: “6”- Turn of Gastroscopy Along The Greater Curvature Wall for Dissection of Stromal Tumor in The Muscularis Propria of The Gastric Fundus
Authors: Guo Hai-Mei , Sun Ying , Cai Shuang , Miao Feng , Zheng Yan , Yu Yang , Zhao Zhi-Feng , Liu Lu
Published: September 2021

Objective
The fundus of the stomach is a challenging region for endoscopic resection of gastrointestinal stromal tumors (GISTs), especially in the anterior wall of the fornix at the side of the greater curvature. The aim of this study was to introduce using the “6”-turn of gastroscopy along the greater curvature wall (6TGS) technique in operation on the gastric fundus and provide evidence of its advantages.
Methods
The clinical data of patients with stromal tumor in muscularis propria at the gastric fundus (STMF) at the Fourth Hospital of China Medical University between July 2016 and Dec 2020 were reviewed. The novel 6TGS technique was used in the procedure. The beneficial effects, suitability, applicable lesion site, influencing factors, and success rates of 6TGS were analyzed.
Results
Ten cases in total were reviewed, and the 6TGS technique was successfully performed in 7 cases (70%). In all 7 patients, the gastroscope’s tip could access the location just below the gastric cardia, and all angles/sites of the fundus of the stomach could be operated on. The lesion was easily accessed, and the gastroscope was stable with good left-right movement ability and moderate forward and backward movement ability.
Conclusion
6TGS can improve the safety of gastroscopy resection of STMF and facilitate the excision of tumors in challenging sites in the gastric fundus. Patients need to be under general anesthesia with endotracheal intubation in the supine position to perform the 6TGS technique after distending the stomach with less air.
Virtual Instruction On Demand for Educational Orientation of Graduate Medical Education Trainees During The COVID-19 Pandemic
Authors: Holliday Scott , Hussain Nasir , Lang Matthew , Burt Coranita , Clevenger Amber , Barbee Jeffery , Start Amanda , Fiorda-Diaz Juan , Clinchot Daniel , Essandoh Michael
Published: September 2021

Background: Graduate medical education (GME) orientation is traditionally an in-person endeavor. The COVID-19 pandemic has prompted virtual approaches to trainee onboarding to reduce viral transmission; however, virtual orientation has not been well-described in GME. This study assesses the effectiveness of virtual orientation of GME trainees using data from an electronic survey.Objectives: We aimed to determine the usefulness of virtual instruction on demand for GME trainee onboarding at a large sponsoring institution.Methods: We conducted a retrospective analysis of de-identified electronic survey responses by residents and fellows who underwent GME orientation at our institution from June to August 2020. The primary outcome was to determine the effectiveness of virtual GME orientation for onboarding, and secondary outcomes included identifying barriers to implementation and weaknesses associated with virtual GME orientation. We conducted orientation sessions for the incoming residents and fellows using CarmenCanvas, our institutional learning management system (LMS).Results: 272 of 337 incoming trainees completed the virtual GME orientation survey. 97% of respondents reported that the contents of the orientation modules would help them perform their duties. 79% of trainees rated the overall quality as very good or good, 91% responded that virtual orientation provided effective learning, 94% reported accessing the course content easily, 92% reported easy navigation of the modules, 91% described it as well-organized, and 87% said that the modules supported their learning.Conclusions: Virtual instruction on demand is a safe, effective, and practical approach to resident and fellow onboarding into a GME sponsoring institution in the COVID-19 pandemic era.