bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Oil Recovery Screening of Oil Fields in Central California for ASP Alkali Surfactant Polymer
Authors: Hampton Thomas J
Published: April 2022

Objectives/Scope

This paper demonstrates the potential of alkali surfactant polymer (ASP) within the Central California Oil Fields, which covers Kern, Tulare, and Fresno Counties. Typically, enhanced oil recovery (EOR) screening is performed across a wide range of processes and is applied to individual reservoirs on a case-by-case basis. This study focuses on a single EOR ASP process across multiple fields and pools specific to Central California.

Methods, Procedures, Process

Reservoir characteristics and Canadian analogs were used to screen for the ASP potential in Central California. Reservoir characteristics data were digitized and taken from what is locally known as the "Gold Book" of Central California (Volume 1, 1998, published by the California Division of Oil & Gas, subsequently renamed CalGEM (California Geologic Energy Management Division). The book contains data for 137 oil and gas fields with 605 pools. Various ASP screening methods and analogs were applied to this dataset. Candidates were then ranked for detailed future analyses.

Results, Observations, and Conclusions

Screening resulted in the identification of 166 of the 605 pools that passed the Taber and Delamaide screening methods and compared well to analogous Canadian successful commercial ASP projects. Fields were then ranked according to various reservoir properties, size of potential recovery, and location (access to chemicals). The top five, with supporting data, are shown. Graphs and maps were used to illustrate the top-ranked pools along with their locations.

Novel/Additive Information

The results of initial screening and ranking of Central Californian pools illustrate its potential for ASP applications. Although there have been some ASP studies and pilots conducted in the San Joaquin Basin oil fields, the results are not in the public sphere. Some data have been published by CalGEM on two successful ASP pilots in the Shallow Oil Zone of the Elk Hills Oil Field, California. This study was performed to show possible application of ASP in 166 pools within the 605 pools in the San Joaquin Basin by using publicly available information to identify oil fields that warrant further detailed investigations of oil chemistry, core analysis, reservoir simulation, risk assessments, and in-depth economic studies.
Towards a Machine Learning Based Dynamic Surrogate Modeling and Optimization of Steam Injection Policy in SAGD
Authors: JL Guevara , Japan Trivedi
Published: April 2022

This paper presents a methodology for the identification of a dynamic-surrogate model and the optimization of steam injection rates of a multi-well heterogeneous SAGD process. The optimization refers to finding the steam injection rates at every time step (steam injection policy) that will maximize cumulative net present value at the end of the production horizon.

The solution methodology consists of identifying one-step prediction non-linear models and then using these models in a recursive scheme to predict the established production horizon. These models are identified offline and then used as a substitute for the reservoir simulation model, considered computationally expensive, in the optimization process. This approach makes use of the reinforcement learning agent-environment interaction: based on the current state St, the agent takes an action At, and the environment transitions into a new state St+1 and offers a scalar reward Rt. Additionally, the well-known genetic algorithm is used for optimization purposes.

The approach is applied to a multi-well reservoir simulation model, built using publicly available data that includes data from northern Alberta SAGD operations considering two (2) time step lengths: daily (Case 1) and weekly (Case 2). Furthermore, the performance of the approach is evaluated in terms of: i) Mean Absolute Error (MAE) between the predicted time-series and the true values (effectivity), ii) the effect of randomness of the design of experiments over the MAE (robustness regarding the design of experiments) and iii) changes in the variance of the errors over the prediction time frame (performance as number of time step prediction increases).

Results show that for a daily time step (Case 1) the proposed approach was able to predict significantly well the selected output as opposed to Case 2 which exhibit much higher MAE values. Also, there is a small but important effect of the randomness of the design of experiments over the MAE values in both cases. Furthermore, Case 1 showed a significant higher level of robustness over the prediction than Case 2. In particular, the changes in variance of the error in Case 1 was much less that for Case 2.
Biogas Produced from Local Waste Reduces the Carbon Intensity of Steam Flooded Oil Production
Authors: Wirtel, P.E. Steve , Zuback Joseph
Published: April 2022

Kore has developed technology that can convert California forestry waste that is an extreme fire hazard and other organic wastes into renewable energy co-products: an energy dense "biogas" and a stable, elemental "biocarbon" solid. This biogas has a heat value that compares favorably to and can replace or augment natural gas used to produce power, heat, and/or steam. Alternatively the gas can serve as feedstock to produce renewable hydrogen or renewable natural gas. The biocarbon is stable – it will not revert to CO2 or CH4. Burying or blending the carbon into soil can serve as a means of carbon sequestration such that the overall the process is carbon negative and the gas fuels produced have an ultra-low carbon intensity.

Steam generation traditionally relies on natural gas combustion as the source of heat. When steam is required for enhanced oil recovery, natural gas combustion increases the carbon intensity of the crude oil product, increasing the carbon intensity of fuels refined from California crude oil compared to crude oil imported into the state. By replacing some or all of the natural gas used to generate steam with Kore's carbon negative biogas, the life cycle carbon intensity of refined fuels produced from California heavy crude can be reduced, potentially to a comparable or lower carbon intensity than fuels refined from imported oil.

Three circumstances unique to California enable this approach to be timely and economically viable: 1) legislation requiring diversion of organic wastes from landfills, 2) the need to beneficially manage forest debris responsible for major fires in California, and 3) legislation enabling credits for decarbonizing transportation fuels (Low Carbon Fuel Standard) that offset the costs of thermal conversion of organic wastes to renewable energy fuels.
A Plug Removal Technique with Rotary Water Jet: Equipment Design, Simulation Study and Experiments
Authors: Zhou Qiucheng , Luo Ning , Li Jianmin , Lei Yuchao , Gao Yanfang , Liu Jiefan , Dou Huiping , Wang Jigang , Wang Xiaoxuan , Yu Chao
Published: April 2022

The reinjection of cooled thermal waters back into sandstone geothermal reservoirs is restricted by two factors, one is the plug near the well, and the other is the plug of the sand-control screens. Plug removal technique with rotary water jet is proposed to relieve the plug in the vicinity of the well. This paper presents a series of studies about plug removal technique with rotary jet flow, including equipment design, simulation study and experiments. Firstly, the composition and function of the plug removal equipment with rotary water jet were presented. The equipment is mainly composed of spray gun, filter, rotary jet nozzle and guide head, etc. Secondly, the flow field characteristics of the rotary jet in the wellbore were simulated and the flushing effects of distribution of nozzles of the jet plug removal tool under construction conditions were studied. Finally, several experiments were performed with actually plugged sand-control screens removed from a well to verify the feasibility of this technique. And the plug removal result of vertical water jet was compared with rotary water jet. This study indicates that the equipment designed is proved to have high success ratio and remarkable effectiveness. The main principle of the technique is to use a rotary nozzle to generate a high-pressure water jet to directly flush the wellbore, and to remove the plug through high-frequency oscillating hydraulic waves and cavitation noise. Thereby, the plug of the screen and the formation can be removed, and the formation permeability can be improved. The study results show that the plug removal technique with rotary water jet is effective to remove the plugs in screen and the vicinity of the well. And jet pressure is an important factor that affects the plug removal and cleaning efficiency. In conclusion, the presented technique can solve the problem that plug often occurs during the reinjection of cooled thermal waters back into sandstone geothermal reservoirs and have a great effectiveness in field application. It has a great prospect in the increase of geothermal water production and reinjection.
History and Future of Oil Production in California
Authors: Frederick Jesse Donald
Published: April 2022

This paper presents a historic overview of the resource and technology for exploration and the production of hydrocarbons that has literally propelled California to be the "Golden State", as well as created modern civilization as we know it today; it is difficult to imagine its elimination by fiat. Also, the paper specifically looks forward into the next challenges for the professionals charged with implementing new applied science to the current policy shift of a steady transition from carbon to the hydrogen economy while "making energy happen" for the consumer.

Looking at history one sees California specifically, needs to make technically-based prudent regulatory provisions to make sure the industry is in place and ready with the flexible capacity for an "open-up" of energy in order to deliver resources absent adaptive measures such as idled standby wells or massive reserves in above ground storage. Crisis response to conditions resulting from the lack of robust adaptive infrastructure demands either a high level of capacity/inventory of essentials or a just-in-time response which draws on a large-shared pool of resource or one risks the high impact shocks to the lower quartile Californians.
State of Art Fracturing Optimization Reduces Water Blockage in Unconventional Gas/Condensate Wells
Authors: Ibrahim Mazher Hassan , Sinkey Matt , Johnston Thomas
Published: April 2022

Hydraulic fracturing (fracing) is the most effective technique for improving the productivity of gas condensate reservoirs. The water used during fracing creates the conductivity needed for production, however, it will also create water blockage in the path of gas flow. The pressure and flow rate behavior of a gas condensate reservoir is distinctly different from the behavior of a solution gas drive reservoir. The producing rate is not only affected by the pressure gradient but is also a more complex function of the actual value of the flowing bottomhole pressure. Initially, the additional pressure required during flowback is needed to produce the water used during fracturing. The reservoir energy to lift this water to the surface requires more pressure drop around the wellbore. Additionally, unnecessary water used during fracing operations incrementally increases the pressure drop near the wellbore. Increased pressure drop leads the formation to reach the dew point sooner and condensate banking start to build in the fracture system. Increased condensate banking leaves valuable liquid hydrocarbon in the reservoir. Water blockages reduce well productivity and speed up the condensate damage due to the high-pressure drop required.

An innovative pattern recognition and machine learning technology was applied in real-time during fracture treatment to increase fracture complexity, improve fracture conductivity, increase diffusion surface area, and improve stage productivity index. This technology focuses on creating the most stimulated fracture surface area per volume of water injected, resulting in the same fracture surface area but with a large reduction in water injected. The reduction of the water leads to an improved well productivity index by minimizing water blockage around the wellbore.

Increasing fracture surface area per volume of frac water injected has a positive impact on the post-frac productivity of treated wells by increasing condensate production rates with less drawdown compared with traditional frac designs. In addition, using the optimum water volume has reduced the cost of fracturing operations and the cost of water flow back disposal leading to significant increases in well Net Present Value (NPV). A field case will be presented with condensate performance.

The use of real-time fracture optimization technology with the integration of rock and reservoir fluid properties leads to better well performance. Production benefits of increased condensate production result in no reserves being lost-in-place to condensate blockage. Added ESG benefits are reduced superfluous water use, pump time, and water disposal costs.
Performance Analysis and Improvement of Multi-Fractured Horizontal Wells in Naturally Fractured Reservoirs
Authors: Manrique Jorge , Manrique Joseph Francisco
Published: April 2022

This paper investigates the performance, of multi-fractured horizontal wells completed in naturally fractured reservoirs (NFR). The performance of these wells was modeled using a reservoir simulator that incorporates microseismics data to infer the area of production influence of the hydraulically induced fractures. A unique and novel set of microseismics diagnostics are introduced and used to identify fracture initiation, infer hydraulic fractures lengths, and determine propagation of the induced fractures.

These results are input into an analytical Rate Transient solutions derived to account for variable fracture lengths, different orientations of the multiple hydraulic fractures along the wellbore, and to implement a well performance model that links the well architecture with the reservoir dynamics. Inflow performance and productivity relationships constructed using these solutions, provide a way to forecast deliverability performance of the reservoir-well-completion system and was used in conjunction of Artificial intelligence and Machine learning algorithms to create an optimization road map for completion optimization of multifractured horizontals

The approach was used to benchmark and assess the performance of horizontals in fractured reservoirs, and when coupled with surveillance workflows, it was used as a production management tool. Field production results show the practical application of the performance solutions when applied to design and optimization of horizontal wells. Results for horizontal well types (new drills and refracturing) of several multi-staged propped fractured horizontals intersecting fracture "swarms" in the unconventional Haynesville and Bossier are presented. The approach is equally applicable to unconventional reservoirs, LTO and waxy crude in NFR.

The methodology suggests a practical alternative to analyze and forecast the performance of horizontal well completions, estimate the efficiency of a horizontal completed with "N" frac stages in the form of a decline curve, determine the number of stages effectively contributing to production, estimate the degree of stimulation (SD) of the combined well system, and to provide an indication of the unrealized potential as an indicator for opportunity improvement.
A Simulation Augmented Machine Learning Approach for Cyclic Steam Stimulation Development Targeting Lower Carbon/Higher Return
Authors: Izgec Omer , Li Yunan , Javaheri Mohammad , Tawfik Miral , Osako Ichiro
Published: April 2022

Finding more energy-efficient and lower carbon emitting ways to develop heavy oil reservoirs is key for economically unlocking more than 50% of the remaining oil reserves worldwide. Continuous steam injection (CSI) is one of the most widely used yet energy-intensive heavy oil enhanced oil recovery techniques. One of the proposed methods to reduce the carbon footprint of heavy oil developments is using cyclic steam development (CSD) rather than continuous steam injection where applicable.

The study has two objectives. First, we developed a CSD conceptual model which describes the physical principles, represents the full life cycle of a CSD and focuses on key elements. Second, a thermal simulation model (based on the conceptual model) for CSD was calibrated to field data. Using thismodel, we conducted a parametric study to select the most impactful input parameters for machine learning model (MLM) training. We introduced a point-based regression method to train the MLM at every single time step for time series prediction of selected properties such as oil production, reservoir pressure, and so on. To manage large amounts of trained MLMs, we also conducted dimension reduction on prediction matrix using Principal Component Analysis (PCA). Once the MLM was trained with the field and simulated data, a web-based fast predictive tool was developed to provide consistent and robust predictions within seconds. This makes it possible to quickly evaluate various scenarios, assess uncertainties and optimize injection job parameters. Furthermore, the tool generates type-curves to identify the inflection point where increasing injected steam volume (per cycle) will not lead to improved recovery due to longer injection period or down-time for CSD wells. The presented workflow can also be widely applied to different recovery techniques, and asset classes.
Solvent Versus Surfactant Co-Injection with Steam to Improve Efficiency of Steam Assisted Bitumen and Heavy Oil Recovery Processes
Authors: Ozum Baki
Published: April 2022

In Alberta, Canada bitumen is produced by SAGD and CSS methods at about 1.5×106 barrels per day capacity. Efficiency of these operations is measured by steam-to-bitumen mass ration, which is reported in the range of 2.6 to 5. Oil industry has invested on solvent such as light hydrocarbons co-injection with steam to reduce SBR, speculating that solvent would reduce bitumen viscosity and increase Darcy mobility of bitumen in the reservoir, which has resulted limited commercial success. In majority of these studies, effect of solvent co-injected with steam on bitumen-water interfacial tension, therefore on Darcy permeability was ignored. Our laboratory has been studying to increase Darcy permeability of bitumen by reducing bitumen-water interfacial tension. For this purpose two methods were investigated: (i) surfactant species were produced by in-situ sulfonation-sulfoxidation of bitumen asphaltenes by co-injecting a trace amount of gaseous sulfur dioxide (SO2) with steam; and (ii) co-injection of biodiesel (BD) as a surfactant additive, with steam at under 2 g-BD/kg-bitumen dosages, which corresponds to under 0.32 kg-BD/bbl-bitumen, or under 0.67 kg-BD/ton-steam if SBR is 3:1. Bitumen recovery tests were also made to compare performances of solvent versus surfactant co-injection with steam methods by operating the test apparatus in bath mode, which most likely stimulate the steam zone of the steam zone of the SAGD and CSS reservoirs. These tests showed that solvent co-injection potentially reduces bitumen recovery efficiency compared to steam-only methods. We wonder that the solvent co-injected with steam increases bitumen-water interfacial tension, increases slip velocity at bitumen-water interface and reduces Darcy permeability of bitumen. Experimental observations supported with fluid dynamics analysis of two immiscible fluids with slip boundary condition at the interface of two fluids were encouraging to expand our research in BD-water emulsions flooding for cold heavy oil recovery, CHOPS and Post CHOPS, and BD-solvent-water emulsions flooding for extra viscous heavy oil, and bitumen production from high permeability reservoirs, which would eliminate demand for steam. Experimental data on bitumen viscosity, bitumen-water interfacial tension and potential effects of solvent and surfactant co-injection with steam on commercial steam assisted bitumen and heavy oil recovery operations will be discussed.
Well Production Optimization through Annulus Gas Management using Gas Handling System in Auca Field, Ecuador.
Authors: Briones Luna César Alejandro , Villa Alzate Carlos , Pastrana Vargas Wilmar Andrés , Azancot Annalyn , González Martínez Darío De Jesús , Segovia Galárraga Rubén Darío , Campana Álvarez Danny Rafael , Salcedo Vallejo Jaime Patricio , Cadena Espín Raúl Fernando , Canaveral Caizaluisa Edwin Gonzalo , Gambaretto Agustín , Paredes Martínez Walter Vinicio , Molina Edison , Vera César Andrés , Arévalo Diego
Published: April 2022

Improving production is a main goal in the industry, mainly in countries where now it is possible to apply accessible technology. Digital Oil Field projects have been successfully implemented worldwide, showing their value in terms of losses reduction and oil production optimization. Annular Gas handling system (AGHS) is part of those projects, aiming to improve well production systems.

Gas accumulation in the annulus is a well-known operational condition which may lead, depending on the volume and associated gas, to ESP production system issues (gas lock). With this in mind, a technical team was formed to create an autonomous annular gas handling system with the main objective to optimize production by avoiding gas related issues, but also to reduce human intervention in the process. This is translated into less kilometers driven and therefore less people exposure.

The main task of the gas handling system consists in regulate the gas outlet through an automatic valve according to a remote order. This order can be given as a percentage of opening denominated "manual control", or as a value of casing head pressure (CHP), denominated "automatic mode" where the valve keeps adjusting automatically in order to maintain the set point pressure (SP). In this way, the manual operation of the annulus valve from an operator on-field is no more needed.

This case solution presents the pilot test results and a feasibility analysis for the expansion of the AGHS Skids. The pilot included two wells in the Auca brownfield: ACAK-182 and ACAK-124, in which an incremental production of 30% and 12% respectively was achieved after pilot implementation. Additionally, manual annular valve interventions were reduced 98% after the automated gas-handling system was tested.

This project demonstrated that intelligent, customized and specific solutions enabled incremental production at a very low cost, reducing people exposure by avoiding trips from pad to pad for annular valve manipulation. Additionally, AGHS Skid improved the efficiency of the ESP in 11% and reduced energy consumption in 11% KVA resulting in higher production with lower power consumption. Also, people were able to spend time working on production optimization rather than operational tasks.
Evaluation of Geological Carbon Storage Opportunities in California and a Deep Look in the Vicinity of Kern County
Authors: Kim Tae Wook , Yaw Sean , Kovscek Anthony R.
Published: April 2022

Geological carbon storage has a critical role to play for the US to accomplish carbon neutrality by 2050. In this work, previous studies of geological carbon storage are reviewed, redefined, and evaluated to focus on providing proper candidate storage sites in the Southern San Joaquin Basin. This study clarifies not only the CO2 capture and storage opportunity but also the potential economic benefit. A three-stage selection method is applied to a catalog of saline formations and hydrocarbon fields to qualify sites for additional in-depth study. The three stages consist of screening using geological criteria, defining exclusion zones, and qualifying sites (Callas and Benson, 2020; Kim et al., 2022). Exclusion zones define potentially unacceptable storage sites based on seismic risk, surface environment such as sensitive habitats, social, and economic aspects. Nine saline formations and 133 hydrocarbon fields were examined. The exclusion zones including faulted, seismically active, large population density, restricted lands, and sensitive habitats, were subtracted from hydrocarbon fields and saline formations. This process resulted in qualified sites. Finally, qualified sites were prioritized using a scoring system. The estimated CO2 storage resource in the qualified saline formations ranged from 16.6 to 52 GtCO2 whereas the estimated CO2 storage resource in hydrocarbon fields ranged from 0.45 - 1.15 GtCO2. Among hydrocarbon fields, 15 CO2-EOR candidate fields with storage resources of 0.36 – 0.88 GtCO2 are located in Kern County. Considering the scoring system, a total of 41 storage sites including 7 hydrocarbon fields were defined as target CO2 storage sites. The opportunities for 41 CO2 storage sites in and around Kern County were linked to selected large CO2 emitters in Southern California including Imperial, Kern, Los Angeles, Orange, San Bernardino, Santa Barbara, San Luis Obispo, and Ventura Counties. Finally, the prospective storage sites and emitters were analyzed technoeconomically using SimCCS to find optimal conditions to deploy CCS projects. Regional GHG emissions from oil and gas facilities such as EOR steam generators and CHPs can be captured and stored economically in geological formations as a result of LCFS and 45Q credits. The sensitivity of 45Q credit value and covered period are critical factors to incentivize CCS deployment. The deployment scenarios evaluated using SimCCS teach that the Southern San Joaquin basin is an excellent potential regional carbon storage hub.
The Workers Behind the Citrus Fruits: A focused Human Rights Impact Assessment of Coop Sweden’s Moroccan citrus fruit supply chains
Authors: Alestig Mira , Banerji Sabita
Published: April 2022

This paper reports on a focused human rights impact assessment (HRIA) of Coop Sweden’s Moroccan citrus supply chains. The HRIA aimed to assess the actual and potential human rights impacts at the production stage of the value chain in Morocco, to identify their root causes, and to provide recommendations to relevant stakeholders concerning their mitigation and/or remediation. The assessment took just over a year and consisted of five phases of analysis using a methodology aligned with the UN Guiding Principles on Business and Human Rights (UNGPs). The field phase took place between January and April 2021. The HRIA was commissioned by Coop Sweden, who wanted a better picture of working conditions in the citrus sector and of the experiences of workers in seasonal production.
Analyzing Voter Turnout in Lebanon: Political Change in Times of Crisis
Authors: Abed Dana , Sawaya Rihab , Tabbal Nadim
Published: April 2022

In May 2022, Lebanon is hosting its first parliamentary elections since the popular uprising of October 2019, when massive protests took place to denounce the current ruling elites. This research looks at voter turnout and behavior on the eve of the elections and examines the will for political change. It argues that in the current Lebanese context, there needs to be further political awareness-raising, and campaigns should be more inclusive of women and the queer community. Independent campaigns should focus on developing strong governing capacities that voters can trust, and create further space for civic and political engagement on the local and national levels.
Hardware Realization of Polar Decoder Using Reinforcement Learning Algorithm
Authors: A Albert Raj , A Calin , T Latha , D Subbulakshmi , J Vijila
Published: April 2022

Error control coding is nearly ubiquitous in our information-based society. In recent days, one amongst the error correcting techniques referred to as the polar codes which attracts the researchers as it represents one of the foremost breakthroughs in 5G standard. It is built by polarization effect of polarization matrix and it is one of the capacity achieving algorithms. It is proved that Successive List decoding (SCL) algorithm improves the efficiency of Polar codes. However, when the codelength increases the latency also increases. It is expected that Reinforcement learning algorithm (RLA) will be able to reduce the latency of the decoder. Therefore, in this article, Markov decision-process algorithm is proposed. RLA uses this Markov decision process when the decoding probabilities are unknown. The same is implemented in the hardware architecture. The implementation result shows that, this method reduces decoding latency to 33% without sacrificing a frame error rate. Experiment result shows that the hardware complexity is also reduced when compared to SCL decoding algorithm. This project is developed using System Generator (Xilinx), with a target device of FPGA-Virtex6.
Identification of Attention Deficit Hyperactivity Disorder with Deep Learning Model
Authors: KASIM Ömer
Published: April 2022

This article explores the detection of Attention Deficit Hyperactivity Disorder (ADHD), a neurobehavioral disorder, from electroencephalography (EEG) signals. Due to the unstable behavior of EEG signals caused by complex neuronal activity in the brain, frequency analysis methods are required to extract the hidden patterns. In this study, the feature extraction was performed with the Multitaper and Multivariate Variational Mode Decomposition methods. Then, these features were analyzed with the neighborhood component analysis and the features that contribute effectively to the classification were selected. The deep learning model including the convolution, pooling, and bidirectional long short term cell and fully connected layer was trained with the selected features. The trained model could effectively classify the subjects with ADHD with a deep learning model, support vector machines and linear discriminant analysis. The proposed approach was validated with an ADHD open access dataset (doi:10.21227/rzfh-zn36). Experimental results showed that the proposed approach can innovatively classify ADHD subjects from Control group effectively. The proposed method was able to classify 1210 test samples in 0.1 seconds with an accuracy of 95.54%. The proposed method is promising for distinguishing subjects with attention deficit hyperactivity disorder effectively.
Efficiency of the H2O2 consumption by the Mineralization of Hydrochlorothiazide via Photo-Fenton UVA: A Time Dependent Analysis
Authors: Mota-Lima Andressa , Cunha-Filho Fernando José Vieria , Chiavone-Filho Osvaldo , Nascimento Claudio Augusto Oller do
Published: April 2022

In the photo-chemical conversion of hydrogen peroxide (H2O2) into radical ⦁OH, the impact of radiation dose (the quantum yield) on the oxidation kinetics has been properly reported, whereas the H2O2 dose is mostly treated as an attempt-and-error variable. This present work formally analyses the oxidant dose in terms of the efficiency of ⦁OH consumption by the micropollutant mineralization, which ultimately enables a generalist strategy for more cost-effective dosimetry of the oxidant. The experimental time-dependent measure of two reagents (pollutant and oxidant) and one product (CO2) enables assessment to the micro-kinetics from the perspective of the chemical dynamic. The analysis was demonstrated for photo-Fenton (FP) oxidation of hydrochlorothiazide (HCT) using a tubular photo-reactor and UVA radiation. The average value of ~ 38% was on top of the best efficiencies in association with some of the fastest rates of mineralization. Such efficiencies are demonstrated to depend on the stochiometric concentration of the oxidant. Here, the variable stoichiometric H2O2 excess for mineralization is proposed as a universal metric to quantify the (under-) over-dose of H2O2. Overall, H2O2 excess between 2 and 5 leads to H2O2 consumption efficiencies above 30% together with a fast rate of CO2 formation (mineralization), whereas any value below 1 invariably leads to a sluggish oxidation rate, leading even to the full depletion of the oxidant. Aside from proposing a selection criterion for the most cost-effective H2O2-dose and providing some examples, this work carefully analyzes the commitment of the H2O2 excess with respect to the energy costs (EEO).
Low FTO expression serves as a potential biomarker for diagnosis and prognosis of patients with liver cancer
Authors: Shi Hongyun , Fu Chang , Quan Panpan , Zhang Liyue , Liu Yunpeng , Jiao Yan
Published: April 2022

Background: As an important part of m6A modification, FTO plays a carcinogenic effect in cancer. In this study, we aim to explore whether FTO could be a new target for diagnosis and prognostic of patients with liver cancer.Material and Methods: We obtained and analysis data from TCGA database by using R software (version 3.5.1). The box plot was used to analyze the pattern of FTO expression. Receiver operating characteristic (ROC) curve was performed to evaluate diagnostic value of FTO expression in liver cancer. Fisher’s exact and chi-square tests were used to analyze relationship between FTO expression and clinical pathological characteristics. Kaplan-Meier curve and Cox regression analysis were used to explore the prognostic value of FTO in liver cancer.Results: We observed that FTO was down-regulated in liver cancer and was associated with patients’ age. ROC curve showed that FTO expression had good clinical diagnostic value. Our results also revealed that FTO expression was associated with age, histologic grade, M classification, vital status, and overall survival (OS) of patients. Low FTO expression decreased OS, and was an independent predictor of poor prognosis in patients with liver cancer.Conclusion: FTO could serves as a potential biomarker for the diagnosis and prognosis of liver cancer
Deep Learning for MYC binding site recognition
Authors: Fioresi R. , Demurtas P. , Perini G.
Published: April 2022

Motivation: The definition of the genome distribution of the Myc transcription factor is extremely important since it may help predict its transcriptional activity particularly in the context of cancer. Myc is among the most powerful oncogenes involved in the occurrence and development of more than 80% of different types of pediatric and adult cancers. Myc regulates thousands of genes which can be in part different, depending on the type of tissues and tumours. Myc distribution along the genome has been determined experimentally through chromatin immunoprecipitation This approach, although powerful, is very time consuming and cannot be routinely applied to tumours of individual patients. Thus, it becomes of paramount importance to develop in-silico tools that can effectively and rapidly predict its distribution on a given cell genome. New advanced computational tools (DeeperBind) can then be successfully employed to determine the function of Myc in a specific tumour, and may help to devise new directions and approaches to experiments first and personalized and more effective therapeutic treatments for a single patient later on. Results: The use of DeeperBind with DeepRAM on Colab platform can effectively predict the binding sites for the MYC factor with an accuracy above 0.96 AUC, when trained with multiple cell lines. The analysis of the filters in DeeperBind trained models shows, besides the consensus sequence CACGTG classically associated to the MYC factor, also the other consensus sequences G/C box or TGGGA, respectively bound by the SP1 and MIZ-1 transcription factors, which are known to mediate the MYC repressive response. Overall, our findings suggest a stronger sinergy between the machine learning tools as DeeperBind and biological experiments, which may reduce the time consuming experiments by providing a direction to guide them.
External validation of VO2max prediction models based on recreational and elite endurance athletes
Authors: Wiecha Szczepan , Kasiak Przemysław Seweryn , Cieśliński Igor , Takken Tim , Pałka Tomasz , Knechtle Beat , Nikolaidis Pantelis T , Małek Łukasz A , Postuła Marek , Mamcarz Artur , Śliż Daniel
Published: April 2022

In recent years, numerous prognostic models have been developed to predict VO2max. Nevertheless, their accuracy in endurance athletes (EA) stays mostly unvalidated. This study aimed to compare predicted VO2max (pVO2max) with directly measured VO2max.5,260 healthy adult EA underwent a maximal exertion cardiopulmonary exercise test (CPET) (84.76% male; age 34.6±9.5 yrs.; VO2max 52.97±7.39 mL·min-1·kg-1, BMI 23.59±2.73 kg·m-2). 13 models have been selected to establish pVO2max. Participants were classified into four endurance subgroups (high-, recreational-, low- trained, and “transition”) and four age subgroups (18-30, 31-45, 46-60, and ≥61 yrs.). Validation was performed according to TRIPOD guidelines. pVO2max was low-to-moderately associated with direct CPET measurements (p>0.05). Models with the highest accuracy were for males on a cycle ergometer (CE) (Kokkinos R2=0.64), females on CE (Kokkinos R2=0.65), males on a treadmill (TE) (Wasserman R2 =0.26), females on TE (Wasserman R2=0.30). However, selected models underestimated pVO2max for younger and higher trained EA and overestimated for older and lower trained EA. All equations demonstrated merely moderate accuracy and should only be used as a supplemental method for physicians to estimate CRF in EA. It is necessary to derive new models on EA populations to include routinely in clinical practice and sports diagnostic.
Polarized th2 cells attenuates high-fat-diet induced obesity through the suppression of lipogenesis
Authors: Dong Lijun , Gao Jingtao , Yu Lu , Liu Shibo , Zhao Yuxin , Zhang Wen , Liang Yinming , Wang Hui
Published: April 2022

Immune cells such as macrophages, B cells, neutrophils and T cell subsets are involved in obesity. However, the tissue-specific function of Th2 cells in adipose tissue remains unknown. We show here that adoptive transfer of polarized Th2 cells to CD3ε knockout (CD3ε−/−) mice attenuates obesity after high-fat-diet (HFD), accompanied by relieved hepatic steatosis, glucose intolerance, and insulin resistance. Mechanistically, Th2 cell treatment promoted oxidative phosphorylation of adipocytes, contributing to the decrease of lipid droplet accumulation. Our data indicate that Th2 cell treatment is a novel approach to the treatment of diet-induced obesity and other diseases involving lipid droplet accumulation disorders.
WITHDRAWN: Inflation Nexus Economic Growth in Ethiopia
Authors: Mognhod Haymanot Bassie
Published: April 2022

Price stability and achieving sustainable economic growth are the major goals of macroeconomic policy and the key indicators of macroeconomic stability. Pursuing of price stability is primary to long-run growth and development; it should be the concern of every economy. This study investigated the nexus of inflation and economic growth in Ethiopia, using the vector autoregressive (VAR) model by employing the data series for the period ranging from 1980 to 2021. The ADF Unit root test confirmed that the variables in the model are integrated of order I (0). The descriptive statistics concludes that the relationship between inflation and economic growth are inconclusive. From VAR regression result, the lagged value of inflation has positive and significant effect on inflation at 1% level of significance. But the lagged value of economic growth has insignificant effect on inflation in Ethiopia. On the other hand, the lagged value of economic growth has positive and significant effect on economic growth and the lagged value of inflation has positive and significant effect on economic growth at 1% level of significance. The estimated model passes diagnostic tests and the Eigen value stability condition displays all the Eigen values lie inside the unit circle. Hence, VAR satisfies stability condition. Long run sustainable development emphasis should be given to accelerate economic growth and compute the threshold inflation-growth level, so that growth rate takes care of the stability in inflation.
Determinants of metabolic syndrome among type two diabetic patients following diabetic clinic of Arba Minch General hospital, southern Ethiopia- a case-control study
Authors: Abebe Getachew , Fikadu Teshale , Hailu Tadiwos , Temesgen Rodas
Published: April 2022

cardiovascular disease and early death. Globally, 70–80% of diabetic patient develop metabolic syndrome Comprehensive knowledge about risk factors for metabolic syndrome are essential to decrease the risk of cardiovascular diseases and improve the quality of life for diabetic patient. Thus, this study aims to determine predictors of metabolic syndrome among type two diabetic patients. This study aims to identify determinants of metabolic syndrome among type two diabetic patients.Methods: Institutional based unmatched case-control study was conducted. 204 systematically selected study participants were involved. Data was collected using a pre-tested, interviewer-administered questionnaire. Bivariate and multivariable logistic regression analyses were employed to identify determinants of metabolic syndrome using STAT version 16. Result: The probability of being female was 3.4 times higher among cases than controls as compared to being male [AOR=3.35, 95% CI (1.28, 8.73)]. The odds of being a rural dweller were 2 times higher among cases than controls as compared to rural dwellers [AOR = 3.10, 95% CI (1.27, 7.624)]. The likelihood being government employment was 4.4 times higher among cases than controls as compared to self-employed [AOR= 4.39, 95% CI ((1.28, 14.97)]. The odds of being obese were 2.7 times higher among cases than controls as compared to normal body mass index [AOR= 2.72, 95% CI ((1.03, 7.17)].Conclusion: -our study indicated that sex, residence, occupation, and body mass index were found to be determinants of metabolic syndrome. Organizations who work in diabetic mellitus and health professionals should focus on these factors in their efforts to reduce the risk of cardiovascular disease among diabetics.
Targeting MDC1 promotes apoptosis and sensitizes Imatinib resistance in CML cells by mainly disrupting non-homologous end-joining repair
Authors: Liang Yang , Qin Yuefeng , Jiang Guoyun , Feng Wenli , Yuan Ying
Published: April 2022

The first-line drug Imatinib (IM) has achieved a curative effect in most chronic myeloid leukemia (CML) patients, but drug resistance remains a problem. More alternative therapeutic strategies need to explore. In recent years, targeting dysregulated DNA repair mechanisms provided promising options for CML treatment. We discovered the versatile MDC1 interacted with γ-H2AX and 53BP1 in the early stage of the DNA damage response of cells. MDC1 was over-expressed in CML cell lines and patients’ BMMCs. By knocking down MDC1, non-homologous end-joining (NHEJ) pathways were mainly inhibited, leading to an intense accumulation of unrepaired intracellular DNA damage and an apparent cell apoptosis promotion. Notably, targeting MDC1 further enhanced drug sensitivity in IM-resistant CML cells. Our work demonstrated that MDC1 is a prospective target for CML treatment through regulating DNA damage repair mechanism, and also an alternative option to cope with the current IM resistance dilemma. This study extends the understanding of regulating dysfunctional DNA repair mechanisms for cancer treatment.
The human right to safely give birth: Data from 193 countries show that gender equality does affect maternal mortality.
Authors: Bagade Tanmay , Chojenta Catherine , Harris Melissa L , Oldmeadow Christopher , Loxton Deborah
Published: April 2022

Background While a reduction in the global maternal mortality ratio (MMR) has slowed, newer strategies are needed to achieve an ongoing and sustainable reduction of the MMR. Previous studies have investigated the association between health system-related factors such as wealth inequalities, healthcare access and use on maternal mortality. However, a women’s rights-based approach to address MMR has not been studied, excluding the health system-related factors. This study aimed to analyse the association between gender equality and MMR globally.Methods Using structural equation modelling (SEM), secondary and open access data from the United Nations and other international agencies from 193 countries were analysed using structural equation modelling (SEM). Gender-sensitive variables that represented the theoretical, conceptual framework of the study were selected. The association between latent variable gender equality and the outcome, MMR, was examined in the SEM. A second SEM model (n=158) was designed to include two variables related to gender-based violence.Findings Out of 521 gender-sensitive variables, we used 11 variables to estimate two models in SEM (Goodness of Fit Index=0‧929 for Model 1 and 0‧939 for Model 2). The latent variable, gender equality, was negatively associated with MMR (p<0‧001, Z=–6‧96, 95% CI: –6508.98 to –3141.89 for Model 1 and p<0‧001, Z=–7‧23, 95% CI: –6045.356 to –3467.515 for Model 2).Interpretation Gender equality was significantly associated with maternal mortality. Investing in higher education for women, improving their paid employment opportunities, increasing participation in leadership roles and politics, reducing intimate partner violence (IPV) and ending child marriage can significantly reduce maternal mortality.
Cardiovascular disease risk prediction models in Chinese population- A systematic review and meta-analysis
Authors: Zhiting Guo , Jiaying Tang , Haiying Han , Yuping Zhang , Qunfei Yu , Jingfen Jin
Published: April 2022

Background: There is an increasing prevalence of CVDs in China which represented the top leading cause of mortality. It is critical to know that precise CVDs risk identification is the fundamental prevention component. This study sought to systematically review the Cardiovascular disease (CVDs) risk prediction models derived and(or) validated in Chinese population to promote CVD primary prevention. Methods: Reports were included if they derived or validated one or more CVDs risk prediction models in the Chinese. Pubmed, Embase, CINAHL, Web of Science, Scopus, China National Knowledge Infrastructure (CNKI), VIP database et al. were searched. Risk of bias was conducted with PROBAST (Prediction model Risk of Bias Assessment Tool). Meta-analysis was performed in R using the package metamisc. Results: From 55183 records, 22 studies were included. Twelve studies derived 18 CVDs risk prediction models, of which seven models were derived based on multicenter cohort including more than two provinces of mainland China, one was model developed based on New Zealand cohort including Chinese. The number of predictors was from 6 to 22. The definitions of predicted outcomes showed considerable heterogeneity. Fourteen articles described 29 validations of 8 models. The Framingham model, the Pooled Cohorts Equations (PCEs) were the most frequently validated foreign tools. Discrimination was acceptable and similar for males and females among models (0.60-0.83). Calibration estimates changed substantially from one population to another. China-PAR showed good calibration [Observed/Expected events ratio=0.99, 95%PI (0.57,1.70)] and female [1.10, 95%PI (0.23,5.16)]. Conclusions: Several models developed or validated in Chinese population. The usefulness of most of the models remains unclear due to incomplete external validation and head-to-head comparison. Future research should focus on externally validating or tailoring these models to local settings.Trail registration: This systematic review was registered at PROSPERO (International Prospective Register of Systematic Reviews, CRD42021277453).