bluuebunny/crossref_metadata_2025 huggingface dataset:
Rejuvenation of Watered-Out Fractured Carbonate Horizontal Well by Microgel/Gel Injection
Authors: Gaillard Nicolas , Omonte German , Bouillot Jerome , Zaitoun Alain , Duboin Francois André , Bertrand Charles
Published: June 2023

In a world where oil production declines and where investments in fossil resources are lower and lower, operators are looking for solutions to optimize the production of existing wells. This is the case for horizontal wells in carbonate formations suffering from channeling with strong bottom aquifer. Such problem occurred for well MRS-1H located in France. Its production started in 2001 with high water-cut (80-85%) that increased rapidly with time to reach 99.7% in 2022 for a gross production of 5000 bpd. Even with a barrel at 80 USD, the extraction of oil in such conditions is not economical due to the high OPEX required for pumping and water disposal. A Water Shutoff (WSO) treatment was designed having as target to decrease water production by, at least, a factor of 2, while keeping the volume of oil production at same level.

The bottom aquifer is located in the very permeable Upper Bathonian formation, just below Lower Callovian formation. Oil in place is 36° API with a viscosity of 3.3 cp. Reservoir temperature and pressure are 70 °C and 186 bar respectively. Reservoir water salinity is between 5 to 10 g/L TDS.

The main problem is the presence of a channeling connection between the well and the aquifer by a fracture network localized close to the heel of the horizontal drain. WSO treatment consisted in injecting by bullheading a first slug of microgel followed by a slug of elastic gel followed by a third slug of microgel. The total volume of the chemical treatment was 300m3.

During the injection, wellhead pressure increased and remained stable below 60 bar for an injection rate of 3bpm. The fact that pressure did not build up (especially during the injection of the gel slug) indicates that the treatment penetrated in low resistance flow areas (fractures). After 15 days of shut in, the well was put back on production, showing a dramatic drop of gross production rate, reaching 630 bpd while it was 5000 bpd before the treatment. The oil production reached 17 bpd corresponding to an oil cut of 2.5% (compared to 0.3% initially). The well has kept this behavior with time, making its production economical.

The bullhead treatment combining microgel and gel proves to be a good WSO strategy for wells suffering from strong bottom aquifer channeling and should have many applications in fractured carbonate reservoirs.
Stabilization of Drilling Foams Using Nanoparticles
Authors: Salih Mohamed , Ahmed Ramadan , Amani Mahmood
Published: June 2023

Foam is the preferred fluid for underbalanced drilling due to its superior hole-cleaning capacity and reduced liquid requirements. However, it must have reasonable stability to function as a drilling fluid under borehole conditions. Unstable foam loses its viscosity and generates drained liquid that causes slugging flow, resulting in temporary overbalance that can damage the formation. This study aims to improve foam stability of aqueous foam using nanoparticles with unique surface properties.

Due to their small sizing and large specific surface area, nanoparticles exhibit unique properties. In addition, their surfaces can be modified to display the desired properties for a given application. In this study, bare (NS1) and coated silicon oxide nanoparticles (NS2, and NS3) have been utilized to enhance the stability of foams. A foam circulating flow loop with horizontal pipe viscometers and a vertical drainage testing cell was used to create foams and analyze their characteristics. At 1000 psi, foams with different nanoparticle concentrations and foam qualities were generated. Their rheology and stability were then investigated. A sonicator and laboratory blender were used to mix nanoparticles with water and anionic surfactant to prepare the liquid phase of foams. The hydrostatic pressure distribution at different column depths as a function of time was measured after trapping a fully generated foam in a vertical test cell. Initially, baseline foams without nanoparticles were tested. Later, two types of nanoparticles (bare and coated) were tested at different nanoparticle concentrations (1 to 3 wt%).

Increasing the baseline foam quality (in-situ gas volumetric concentration) from 40 to 60% resulted in a significant increase in apparent viscosity and a reduction in liquid drainage. Nanoparticles containing foam also showed similar trends of property changes with foam quality. Besides this, experiments demonstrated the impact of nanoparticles on the characteristics of foams. The viscosity and stability of foams increased with the addition of nanoparticles. Also, the drainage of foams noticeably decreased while their half-life improved with the concentration of nanoparticles. The effectiveness of nanoparticles is also influenced by their type. Silica nanoparticles that are coated (functionalized) with an amino group (NS2) provide better foam stability than regular nanoparticles (NS1) and nanoparticles treated (coated) with silane (NS3). This study contributes to the formulation of a new generation of drilling foams that can be used in harsh borehole environments where foam instability becomes a major concern.
Controlling Asphaltene Deposition in Ageing Wells
Authors: Grutters Mark , Alshamsi Mohammed , Punnapala Sameer , Abdallah Dalia , Al-Ali Aamna
Published: June 2023

ADNOC Onshore produces asphaltene-unstable crudes subject to severe wellbore deposition, which is exacerbated by miscible WAG injection. In one of the oilfields, commissioned in 1973 and producing approximately 400,000 BPD from 4 key reservoirs a cluster of approximately 20 wells experienced severe asphaltene deposition. Over time field conditions changed, reservoir pressure declined and water cut increased from 0% to 30%. With these changes the number of shut-ins due to asphaltene deposition started to change. Regular well intervention by gauge cutters or PLT tools confirmed that little to no asphaltene build up occurred in wells with high water cut.

In this paper it was evaluated whether changes to asphaltene deposition severity can be linked to water production, or that other production factors might contribute. Field data were reviewed for the period 2003 to 2022, for a total of 12 wells with a history of moderate to severe asphaltene deposition. The field data included PVT data and stock tank oil properties, well testing data, production allocation data, wireline inspection data, field lab analysis of wellbore deposits and chemical soaks. The review indicated that changes in asphaltene deposition were not influenced by a gradual decline in reservoir pressure or gas break through causing changes to the AOP location. A scoring matrix was developed to determine the ‘deposition severity’ for each well for every year and plotted against the average water cut of that year. From this scoring matrix it was concluded that there is a weak correlation between the severity of asphaltene deposition and water cut. Even at water cuts around 40% asphaltene deposition has not stopped completely, but the number of required interventions has dropped.

Or long-term goal is to develop correlations that can be used to predict future behavior of asphaltenes, for optimization of field development plans in reservoirs subject to WAG and surfactant/polymer flooding. A correlation can help to understand whether asphaltene deposition will be permanent or reduce over time for different development scenarios and whether mitigation by inhibitor injection or periodic cleaning with solvents is most effective and economical.
A Novel Experiment Setup to Model the Effects of Temperature on Halite Scaling and Inhibition
Authors: Navarathna Chanaka , Leschied Cianna , Wang Xin , Reiss Amit , Ye Yuqing , Pimentel Daniel , Shen Yu-Yi , Yao Xuanzhu , Kan Amy , Tomson Mason
Published: June 2023

Halite is a common scale in oil/gas production. Freshwater is widely used to combat halite scaling, but this is costly. Therefore, halite inhibitors have also been examined in laboratory and field tests. However, there are certain flaws in the laboratory studies of halite inhibitors, the temperature decreases were so abrupt, or the experiments are limited to lower temperatures. As a result, inaccurate results and unrepresentative field conditions are produced. Our new precisely temperature-controlled method simulates halite precipitation at high temperatures up to 120+ °C with real-time monitoring using a laser and a video camera. This method uses batch reactor convection cooling to gradually increase the saturation index (SI) to trigger the halite nucleation observed by turbidity laser measurements. The cooling rate is commonly set at 0.5 °C/min to simulate a real-world downhole to surface hot brine movement, typically 25-35 °C of cooling. Low to high Ca2+ values were used to validate the experimental data with thermodynamic predictions. The experimental data and ScaleSoftPitzer™ (SSP) predictions are very close and with high precision. The high temperature inhibition properties of halite inhibitors are not well-known, and lack of information can lead to overtreating the scale with higher inhibitor concentrations than needed. By simulating the temperature drop that occurs when brine is transported from the downhole to the surface, this approach can establish the effective SI range for a specific inhibitor. Our data shows that even at low 0.1-100 mg/L concentrations, some inhibitors with carboxylate, sulfonate, and acetamide moieties can effectively treated halite scale and dramatically extend the stability range. Despite the weak thermal stability and incompatibility with high Ca2+ concentrations, potassium ferrocyanide demonstrated outstanding inhibitory effectiveness. The longer the inhibition period or brine transit distance, the lower the scaling temperature. By treating the scale with the least amount of inhibitors and combining it with less water dilution, production can continue uninterrupted at significantly enhanced cost savings. Overall, this approach is reliable while remaining straightforward. In addition, it can model field conditions in an oil/gas production system to evaluate the risk of halite scaling at higher temperatures than any previous method.
Development of a New Chemical Formulation for Heavy Oil Viscosity Reduction and Displacement
Authors: Chen Shaohua , Han Ming , AlSofi Abdulkareem , Huang Tianping
Published: June 2023

A novel polycyclic aromatic hydrocarbon (PAH) based water-soluble viscosity reducer (VR) formulation was designed to reduce heavy oil viscosity for enhancing heavy oil production by chemical flooding. The polyaromatic structures such as benzene, naphthalene, and pyrene units in the VR formulation target asphaltene and resin components in heavy crude oil via π-π interaction to hinder formation and self-assembly of asphaltene aggregates and to reduce the viscosity of heavy oil accordingly. Two main chemical components in the VR package were synthesized from the reaction between poly(ethylene glycol) and naphthalenemethanol or pyrenemethanol to yield amphiphilic molecules. The chemical structured were confirmed by 1H NMR spectra. Heavy oil displacement evaluations were conducted through two experimental setups – a coreflooding equipment and a visualized micromodel. In the coreflooding experiments, a commercially available benchmark VR (BVR) and the synthesized VR (SVR) solutions at the optimized concentrations were injected to displace the heavy oil saturated in carbonate cores. The residual oil distribution pattern after injection of chemical slug and the profile change of saturated oil during chemical flooding with the BVR and SVR were observed using a micromodel equipment. At 0.2 wt%, the SVR package formed oil-in-water (O/W) emulsions with heavy oil at an oil-to-water ratio of 7:3 and dramatically reduced the viscosity of heavy oil by 84% at 50 °C. Visualized micromodel displacement tests showed that the injected SVR solution gradually emulsified the heavy oil at the oil/water interface to form emulsion droplets, which were subsequently deformed and stretched into long and narrow emulsion strips to pass through the smaller pores and throats along with injected fluid, thus facilitating the mobility of heavy oil and enhancing the oil production eventually. Coreflooding testing indicated that the injected SVR fluid significantly decreased the injection pressure due to viscosity reduction of the heavy oil. The oil production was enhanced by around 11% on the basis of water flooding. As a comparison, the heavy oil production by injection of the BVR solution was improved by 8%. The performance of the SVR on heavy oil viscosity reduction and oil displacement was found more pronounced than the BVR. Therefore, the formulated SVR package exhibits a great potential in heavy oil production.
The Impact of Variations in Water and Gas Flow Rates on Scaling Potential of Carbonate Reservoirs Under CO2-WAG Injection
Authors: Braga Gusmao Patricia , Mackay Eric James
Published: June 2023

This paper uses reactive transport modelling to analyse the impact of variations in the water and gas injection flow rates from a geochemical perspective on the scaling potential of carbonate reservoirs under CO2-WAG injection. A sensitivity analysis of the calcite saturation index is performed for different water and gas injection flow rates. Geochemical properties of the injection fronts are analysed through the reservoir.

The study is carried out using a 1D model of water-alternating-gas injection, assuming a light oil with 1.2% CO2 concentration, desulphated seawater injection and calcite as the rock substrate. The reactive transport modelling is performed using a commercial compositional reservoir simulator with the WOLERY database. Pressure, temperature, formation water (FW) and injected water (IW) compositions are based on published data. The scale potential is measured by calculating the saturation index and water production rates.

Results show that calcite dissolution occurs continuously in the block closest to the injection well, and equilibrium is not reached in this region during water injection, but it is reached during CO2 injection. The extent of the reaction decreases from the injector to the producer well because the fluid becomes more saturated with CO2 as it flows through the reservoir. The reaction also decreases as the water and gas injection flow rates decrease, mainly due to the reduced volume throughput. The reactions during the water injection part of the cycle occur further away from the waterflood front as the water injection rate declines, and the reactions during the CO2 injection part of the cycle occur further away from the gas flood front as the CO2 injection rate declines. The system takes longer to reach equilibrium at lower flow rates, and so the water composition varies for longer. In the highest water flow rate model, it takes a very short time to reach equilibrium after the water breakthrough in the producer well. In the lowest water flow rate model, it takes more than five times as long.

This work indicates the previously unreported finding that the water and gas injection flow rates may affect the geochemical equilibrium in the reservoir, specifically demonstrating that the reactions during the non-equilibrium stage may occur further away from the water and gas flood fronts, depending on the water and gas flow rates.
The Study and Application of Seepage Reconstruction for Water Plugging in High Permeability Sandstone Reservoirs
Authors: Zhang Yanna , Li Liangchuan , Yan Fei , Wang Yucai
Published: June 2023

In the medium/high permeability sandstone reservoirs, long-term water flooding led to large pore channels formed in the reservoir, and the injected water quickly breaks into oil wells along the large pore channels, resulting in water cut increase rapidly and a significant reduction in water flooding efficiency. The traditional water shut-off by chemical or cement squeeze cannot reduce water cut for a long time and cannot increase oil production because they don't change the existing seepage characteristics of the reservoir.

The seepage reconstruction is a combination of chemical water shut-off and fracturing technology. It involves innovation on intelligent water control materials and fracturing injection process. There are three plugging slugs, a strong plugging slug, a seepage reconstruction slug, and a tail plugging slug, should be filled into reservoir one by one. The strong plugging slug adopts inorganic polymer to shut-off the large pore by low speed injection. The seepage reconstruction slug is composed of 70-140 mesh quartz sand, 50-80um ceramist and intelligent water control materials with a ratio of 6:3:1, which is carried by low-concentration guar. The tail plugging slug is made of self-consolidated material to prevent sand returning from formation.

The technology is used in G111-6 located in J oil field, which is successful in increasing oil production from 3.08bopd to 56.28bopd and reducing the water cut from 96.64% to 78%. The validity period was 492d, and the total oil production was 22624bbls. The technology of seepage reconstruction for water shut-off could effectively reduce the water cut and greatly increase the daily oil production. It effectively improves waterflood development efficiency of medium/high permeability sandstone reservoirs in high water cut stage.

The innovation of this technology is the effective combination of fracturing technology and traditional chemical water shut off technology. The goals of water shut-off and oil increase are realized by innovative design of three plugging slugs. It provides a new approach for water shut-off in medium/high permeability sandstone reservoirs with high water cut.
Geochemical Artificial Intelligence Tool for Enhanced Water Management
Authors: Birkle Peter , Ismailova Leyla , Tirikov Egor , Saeed Waleed , AlSaif Maram , Al Ibrahim Mustafa
Published: June 2023

Produced water from crude oil and gas producing zones is geochemically heterogeneous due to the input from diverse underground sources and/or operation-related fluids. The present work targets developing and implementing an innovative numerical tool to automatically predict the type and provenance of recovered produced water from exploration and production. Machine learning-based tools was assessed for the automated classification of produced water types in oilfields with a differentiation of formation water from operation-related fluids. Multiple algorithms in machine learning were tested on hundreds of training and testing datasets of produced water samples to identify methods with the highest performance rates. A combination of the supervised XGBoost algorithm with semi-supervised self-training methods resulted in the two best-performing algorithms for all metrics (accuracy, precision, recall) with an accuracy above 90%.

The developed software allows the automated recognition of representative formation water samples, and its differentiation from drilling or operation-related fluids, such as mud filtrate, completion brine, supply water, condensate water, and mixed water types. The algorithm was successfully tested for the classification of hundreds of produced water samples from different fields and reservoirs to define accurate formation water properties for several wells and lithological units. In general, the majority of produced water samples resulted in being post-testimonies from drilling, workover, and production-related activities.

Enhanced water management by processed geochemical data can directly contribute to a potential reduction in drilling lost-time, well cleanup time, and reducing the risk of drilling dry holes. Additionally, well control can be optimized by identifying water inflow zones, and the amount of required bottomhole samples can be reduced by identifying nonrepresentative sampling intervals. Furthermore, geochemical fingerprinting of formation water as dominant reservoir fluid can provide analogous clues on the source rock, migration, trapping, and alteration of hydrocarbons.
Water Digital Avatar—Where Chemistry is Mixed with Machine Learning
Authors: Farrell Jesse , Makarychev-Mikhailov Sergey
Published: June 2023

Water affects almost every operation in the exploration and production (E&P) industry, with its properties important to flow assurance, to three-phase flow pressure/volume/temperature (PVT) modeling, and for fluid compatibility purposes across well construction, stimulation, and production operations. Until now, time-intensive laboratory tests or cumbersome third-party simulators were required to extract physicochemical properties. Here, a family of machine-learning-based reduced-order models (ROM), trained on rigorous first-principle thermodynamic simulation results, is presented.

Approximately 90,000 representative produced-water samples were generated using the United States Geological Survey (USGS) Produced Waters Geochemical Database (Blondes et al. 2019), with systematic variation of the concentrations of 14 common ions. A training data set of 1 million rows was constructed, further varying temperatures and pressures using broad ranges (50-400°F and 14.7-20,000 psi). Thermodynamic simulations were used to generate a data set with more than 500 parameters, including speciation; physicochemical properties such as density, thermal conductivity, heat capacity, and salinity; and notably, the scaling potential for 11 common oilfield scale-forming minerals. More than 20 machine-learning algorithms were screened using cross-validation, and boosted decision trees were found to provide the best accuracy. The CatBoost algorithm (Prokhorenkova et al. 2018) was selected and further optimized. Model validation using unseen data showed relative errors of less than 1% for the majority of predicted properties, which is remarkable for such a complex multicomponent and multiphase system. Simulation details, modeling, and validation results are discussed.

Trained and optimized ROMs can be incorporated in any workflow that depends on water property predictions. As a demonstration, a web application, Water Digital Avatar, was built from these ROMs to quickly and accurately process predictions of water properties and scaling potential on the basis of the entered water composition and desired conditions. The streamlined workflow provides users with model predictions in tabulated and graphical forms for analysis within the web application or offline by means of a downloaded spreadsheet.

The developed ROMs that predict water properties enable automated decision making and improve water management workflows. The presented approach can be further extended to other oilfield, chemical, and chemical engineering applications.
From Chicory Roots to Salmon Fish Waste: All the Challenges of a Trip to Sustainability for Scale Inhibitors and Low Dosage Hydrate Inhibitors
Authors: Parravicini Davide , Di Toto Raul Antonio , Davies Hannah
Published: June 2023

The use of environmentally acceptable inhibitors – particularly in the North Sea - has been of interest for many years. Traditional scale and hydrate inhibitors show poor to moderate biodegradability. P-based inhibitors could lead to eutrophication and polymers are mainly petroleum derivatives. More sustainable technologies have historically suffered from higher costs to maintain the same performance. This paper highlights all the successful efforts made to develop new environmentally friendly and cost-effective technologies having best-in-class performance.

CMI is nowadays a well-known chemistry, derived from chicory roots and patented. It also represents one of the first biopolymer-based scale inhibitors for O&G applications. Despite its good scale inhibition and dispersion performance, the chemical structure is affected by poor thermal stability, which makes this technology less attractive for high temperature oilfield conditions. After extensive R&D work, carried out with the aim of developing new biodegradable, low toxic and ESG compliant technologies not suffering from the same limitations of CMI, two biodegradable phosphonated amino acid chemistries have been developed: PHAAC1 and PHAAC2. While the first product is inherently biodegradable and provides good performance against barium sulfate, the second and most recent readily biodegradable technology is characterized by an exceptional thermal stability and a MIC against calcite 7 to 10x lower than standard chemistries at high temperature (up to 190°C).

Lessons learned were then extended to hydrates inhibitors, with the development of a new cost-effective Kinetic Hydrate Inhibitor based on fish waste, representing a nice example of circular economy. Encouraging performance has been observed and industrialization is currently ongoing. Constant cooling and Isothermal tests provided encouraging results, in line with currently used KHI. More work has to be done to further explore the potential features of this technology.

The systematic applicative R&D approach replicating field conditions, the processes and results described in this work represent a significant step forward, confirming the possibility to develop ESG complaint technologies combining good ecotoxicological profiles and outstanding performance. An approach to circular technologies is also outlined as a base for future development.
Assessment of Friction Reducer Performance Within a Continuous Brine Spectrum
Authors: Aften Carl , Sullivan Keith , Thorpe Russell
Published: June 2023

The performance of friction reducers in standard flow loops is a function of the specific friction reducer, environmental factors such as brine composition and fluid temperature, and the unique loop design and run procedure. This study examines the performance of various commercial and experimental friction reducers using Design of Experiments with variables of friction reducer loading expressed in gallons per thousand gallons, brine Total Dissolved Solids expressed in parts per million, and R+ Hardness expressed as the mole ratio of cationic hardness ions to the Total Dissolved Solids in decimal percentage. The ultimate percent friction reduction is generally dependent upon these variables, and each friction reducer generates unique profiles used to predict performance within the above variable space.

This study evaluated 12 inverse emulsion friction reducers of various charge types in a 100 foot once through pipe. For this design of study, the Total Dissolved Solids was varied from 5,000 to 150,000 parts per million, the R+ Hardness varied from 0.0 to 0.3, and the friction reducer loading varied from 0.25 to 1.00 gallons per thousand gallons. Each reducer was injected into a reservoir containing a brine with the previously referenced, pre-established levels of Total Dissolved Solids and R+ Hardness, and the resulting maximum percentage friction reduction calculated by standard differential pressure protocol.

The response surfaces generated had Ajusted-R2 values from 0.86 to 0.99 demonstrating an exceptionally good fit for the chosen regression model. The contour profiles expressed a general similarity between related charge types with type of charge significantly influencing the response surface profile. Typically, as friction reducer loading increased, percent friction reduction increased or a maximum plateau was achieved, or performance declined. Certain friction reducers’ performances increased as Total Dissolved Solids and/or R+ Hardness increased whereas many reducers’ performances decreased. The gradient of the response surfaces varied from linear progressing to cubic functions with arithmetic transformations.

How friction loop results transmute to full scale hydraulic fracturing operations is not yet fully understood and no delineated process currently exists. However, mapping response surfaces of specific friction reducers then comparing responses to other friction reducers’ response data provides insight and can articulate how reducers’ performances are affected by friction reducer loading, TDS, and R+ Hardness, particularly in operations involving highly variable water quality. As brine character can vary during a hydraulic fractioning treatment, the best practice may be to either use a friction reducer known to perform well within the expected brine level or anticipate using multiple friction reducers for a specific treatment.
Enhancing Anatomy Education Through Cooperative Learning: Harnessing Virtual Reality for Effective Gross Anatomy Learning
Authors: Wang Chao-Ying , Yin Ti , Ma Kuo-Hsing , Shyu Jia-Fwu , Cheng Chia-Pi , Wang Yu-Chao , Huang Yun-Ling , Chiang Ming-Hsien
Published: June 2023

Background: The advent of virtual reality (VR) in education offers unique possibilities for facilitating cooperative learning strategies, particularly in fields demanding intricate spatial understanding such as gross anatomy.
Objectives: This study investigates the impact of integrating cooperative learning strategies within a VR-based gross anatomy curriculum, focusing on enhancing students’ anatomy knowledge and skills.
Methods and Participants: We analyzed the performance of two cohorts of first-year nursing students across five semesters (2016-2020), where traditional learning methods were used in the first three semesters (2016-2018), and a VR-based cooperative learning approach was adopted in the last two semesters (2019-2020).
Results: Our findings suggest that the VR-based cooperative learning group achieved significantly higher scores in their gross anatomy laboratory courses compared to their counterparts learning through traditional methods. Furthermore, instances of VR-induced motion sickness were reported to be less prevalent in the cooperative learning environment.
Conclusions: This research provides valuable insights into how the integration of VR technology and cooperative learning strategies can not only enhance learning outcomes, but also improve the VR-learning experience by reducing motion sickness. It accentuates the potential of VR-based cooperative learning as an impactful educational tool in anatomy education. Future research should further explore the optimal integration of VR and cooperative learning strategies in diverse course types and their potential in enhancing educational outcomes and learning experience.
A SAT Solver + Computer Algebra Attack on the Minimum Kochen-Specker Problem
Authors: Li Zhengyu , Bright Curtis , Ganesh Vijay
Published: June 2023

One of the most fundamental results in the foundations of quantum mechanics is the Kochen--Specker (KS) theorem, a `no-go' theorem which states that contextuality is an essential feature of any hidden-variable theory. The theorem hinges on the existence of a mathematical object called a KS vector system. Although the existence of a KS vector system was first established by Kochen and Specker, the problem of the minimum size of such a system has stubbornly remained open for over 50 years. In this paper, we present a new method based on a combination of a SAT solver and a computer algebra system (CAS) to address this problem. We improve the lower bound on the minimum number of vectors in a KS system from 22 to 23 and improve the efficiency of the search by a factor of over 1000 when compared to the most recent computational methods. Finding a minimum KS system would simplify experimental tests of the KS theorem and have direct applications in quantum information processing, specifically in the security of quantum cryptographic protocols based on complementarity, zero-error classical communication, and dimension witnessing.
Criminal Face Detection System
Authors: Venkatesh Machala , Dhanalakshmi Chintha , Adapa Aditya , Manzoor  , K Anvesh
Published: June 2023

The rise in crime rates and the increasing demand for effective criminal identification and prevention measures have prompted the implementation of security technologies, such as CCTV cameras. To address this need, we present a research study that introduces an automated facial recognition system based on the Local Binary Patterns Histogram (LBPH) classifier and Fisherface algorithm. This system utilizes a Haar feature-based cascade classifier to detect faces in real-time, and subsequently matches the identified faces against a criminal database. Despite the inherent challenges in achieving accurate face identification, the Viola-Jones framework is employed to precisely locate facial positions and other distinguishing features within an image. Face detection classifiers, which are publicly accessible through organizations like OpenCV, contribute to the implementation of our proposed system. The potential benefits of our system include bolstering criminal identification and prevention efforts within both public and private spaces.
How Common is Remission in Rheumatoid Factor-Positive Juvenile Idiopathic Arthritis Patients? The Multicenter Pediatric Rheumatology Academy (PeRA) Research Group Experience
Authors: Ozdel Semanur , Sonmez Hafize Emine , Caglayan Sengul , Akgun Ozlem , Aydın Tuncay , Baba Ozge , Bagrul Ilknur , Yener Gulcin Otar , Ozturk Kubra , Demir Ferhat , Yıldırım Deniz Gezgin , Karadag Serife Gul , Baglan Esra , Cakan Mustafa , Kalyoncu Mukaddes , Makay Balahan Bora , Unsal Sevket Erbil , Bakkaloglu Sevcan , Bulbul Mehmet , Sozeri Betul , Ayaz Nuray Aktay
Published: June 2023

Objective
Rheumatoid factor (RF)-positive polyarthritis is the least common type of juvenile idiopathic arthritis (JIA). Functional disability in RF-positive polyarthritis patients is much more severe than in patients with other subtypes; but data on this subtype alone is limited. This study aimed to analyze clinical features, long-term follow-up, treatment response, and remission status in a large multicenter cohort of RF-positive polyarthritis patients.
Methods
This retrospective study included RF-positive polyarthritis patients that were followed up for ≥ 6 months between 2017 and 2022 by the Pediatric Rheumatology Academy (PeRA)-Research Group (RG). Data on patient demographics, clinical and laboratory characteristics were obtained from medical charts. JIA treatments and duration of treatment were also recorded. The patients were divided into 2 groups based on methotrexate (MTX) response, as follows: group 1: MTX responsive, group 2: MTX unresponsive. Clinical and laboratory findings were compared between the 2 groups.
Results
The study included 56 (45 female and 11 male) patients. The median age at onset of RF-positive polyarthritis was 13.2 years [(interquartile range) (IQR) : 9.0–15.0 years] and the median duration of follow-up was 41.5 months (IQR: 19.5–75.7 months). Symmetrical arthritis affecting the metacarpophalangeal and proximal interphalangeal joints of the hands was commonly observed. Subcutaneous MTX was the preferred initial treatment; however, it was ineffective in 39 (69.6%) of the patients. Of 25 patients followed for 24 months, 56% still had active disease at 24 months.
Conclusion
During 2 years of treatment, 56% of the RF-positive polyarthritis patients did not achieve remission, and they should be considered as a distinct and important clinical entity requiring aggressive and early treatment.
Quantifying the Vulnerabilities of the Online Public Square to Manipulation Tactics
Authors: Truong Bao Tran , Lou Xiaodan , Flammini Alessandro , Menczer Filippo
Published: June 2023

Social media, the modern public square, is vulnerable to manipulation. By controlling inauthentic accounts impersonating humans, malicious actors can amplify disinformation within target communities. The consequences of such operations are difficult to evaluate due to the ethical challenges posed by experiments that would influence online communities. Here we use a social media model that simulates information diffusion in an empirical network to quantify the impacts of adversarial manipulation tactics on the quality of content.
We find that social media features such as high information load, limited attention, and the presence of influentials exacerbate the vulnerabilities of online communities. Infiltrating a community is the most harmful tactic that bad actors can exploit and the most likely to make low-quality content go viral. The harm is further compounded by inauthentic agents flooding the network with engaging low-quality content, but is mitigated when influential or vulnerable individuals are targeted. These insights suggest countermeasures that platforms could employ to increase the resilience of social media users to manipulation.
Pattern formation in reaction-diffusion information propagation model on multiplex simplicial complexes
Authors: Ye Yong , Zhou Jiaying , Zhao Yi
Published: June 2023

Turing pattern for explaining the spatial distribution in nature mostly focused on continuous media and existing networks but there are few attempts at studying them on the systems with high-order interactions. Considering that high-order interactions have a particularly significant impact on rumor propagation, this article establishes a generalized reaction-diffusion rumor propagation model based on a multiplex network, where simplicial complexes are employed to describe the high-order structures. It aims to provide the spatial distribution patterns of the population participating in rumor propagation and identify structural factors that affect such patterns. We theoretically give the necessary conditions for Turing instability in the single-layer and multiplex networks with consideration of high-order interactions. In the numerical simulation, we demonstrate that Turing pattern is controlled by adjusting the diffusion coefficient, high-order structure intensity, and average degree of the network. The results conclude that: (i) in a single-layer network, Turing pattern only exists when high-order interactions appear, and the difference in diffusion rate plays a decisive role, (ii) in a multiplex network, Turing pattern can still be observed under the same diffusion rates, which are affected by the difference of higher-order intensity between two layers, and (iii) in the existing networks, the average degree of the network takes an important impact on Turing pattern. All these findings contribute to comprehending the impact of network structure on pattern formation, especially the high-order interactions on Turing pattern.
Influence of the addition of glycerol-derived polymers on the properties of post-consumer recycled PET
Authors: Seixas Ana Amélia Aragão , Figueiredo L. R. F. , Santos A. S. F. , Medeiros E. S.
Published: June 2023

In the present work, the influence of glycerol prepolymers, as potential chain extenders in the reactive mixture with post-consumer recycled PET (PET-PCR), was studied, namely: poly(glycerol citrate) (PGC), poly(glycerol succinate) (PGSu) and poly(glycerol citrate-co-succinate) (PGCSu). Mixture of recycled PET with 2wt% of glycerol prepolymers or Joncryl ADR®4638, commercial chain extender, were processed in an internal mixer at 265°C for 6min and 60rpm. The compositions were characterized by viscosimetry, carboxylic end groups (CEG) through the Pohl method, crosslinking degree as the percentage of insoluble gel, Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The addition of glycerol prepolymers increased the fluidity in the post-consumer PET resin, consequently, decreasing its viscosity by 33% for PETPCR/PGC, 24% for PET-PCR/PGSu, 44% for PET-PCR/PGCSu and 17% PET-PCR/Joncryl; the molecular weight in the order of 42% for PET-PCR/PGC, 31% for PET-PCR/PGSu, 55% for PETPCR/PGCSu and 23% for PET-PCR/Joncryl and increasing the number of carboxylic end groups. Although they did not show extensive chain crosslinking, the samples were fragile and brittle, thus making the tensile test unfeasible. Thermogravimetry showed that the polyesters were thermally stable up to approximately 350°C and the sample that presented the lowest thermal stability was the PETPCR/PGCSu corroborating to the highest reduction in the molecular weight recorded. The DSC results showed na almost constant melting and glass transition temperature among the samples, a decrease of 8°C in the crystallization temperature and an increase in the degree of crystallinity relative to neat PET-PCR, which corroborates to the intrinsic viscosity results. These results indicated that at the concentration and processing conditions used, the potential additives to chain extenders had an opposite effect to the desired one, that is, they reduced the molecular weight of recycled PET and the same effect occurred for the commercial chain extender. However, the additive that showed the greatest potential for use as chain extender was PGSu, which presented results similar to the commercial extender Joncryl ADR®4638, composed of multifunctional epoxy groups.
Majorana zero modes in Y-shape interacting Kitaev wires.
Authors: Kaushal Nitin , Alvarez Gonzalo , Dagotto Elbio , pandey Bradraj
Published: June 2023

Motivated by the recent experimental realization of minimal Kitaev chains using quantum dots, we investigate the Majorana zero modes (MZM) in Y -shape Kitaev wires. We solve the associated Kitaev models analytically at the sweet spot (th = ∆) and derive the exact form of MZM wave-functions in this geometry. The novelty of our result is the observation of non-local MZMs near the junction center, made of a linear combination of edge sites MZMs for each arm. Furthermore, we simulate the stability of local (on site) and non-local MZMs modes in the presence of Coulomb repulsion, using density matrix renormalization group theory. Our local density-of-states calculation shows that these non-local MZMs are as equally topologically protected as the local MZMs when in the presence of Coulomb repulsion.
Proposing new design and retrofitting objectives for seismic design of hospital structures - A case study of Imam Khomeini Hospital in Eslamabad-e Gharb
Authors: Mehrjoo Majid , Aval Seyed Bahram Beheshti
Published: June 2023

This paper compares two methods for retrofitting an existing hospital concrete structure to improve its seismic performance: internal and external retrofitting. Internal retrofitting involves adding chevron braces, reinforcing shear walls with Fibre-reinforced plastic (FRP) coating, and wrapping the walls, columns, and beams using steel jackets. External retrofitting uses two braced exterior steel frames connected to the concrete building using dampers. The paper also proposes a new design objective for hospital structures that ensures immediate occupancy performance level under earthquake hazard level-1 and prevents collapse under higher ground motion intensity. The paper evaluates the base structure, the two retrofitting schemes, and the proposed design method using pushover and nonlinear dynamic analyses under 20 selected earthquake records. The paper then compares the probabilistic seismic risk models using fragility curves. The results show that external retrofitting is more effective and economical than internal retrofitting and that the proposed design objective can significantly reduce the seismic risk of hospital structures.
Prediction and Validation of Mild Cognitive Impairment in Occupational Dust Exposure Population Based on Machine Learning
Authors: Cai Fulin , Zhang Mei , Liu Yafeng , Chen Xiufeng , He Jiale , Xue Sheng
Published: June 2023

Objective: Workers who are exposed to dust for extended periods of time may experience varying degrees of cognitive impairment. However, there is limited research on the associated risk factors. This study aims to identify key variables using machine learning algorithms (ML) and develop a model to predict the occurrence of mild cognitive impairment in miners.
Methods: A total of 1938 miners were included in the study. Univariate analysis and multivariable logistic regression were employed to identify independent risk factors for cognitive impairment among miners. The dataset was randomly divided into a training set and a validation set in an 8:2 ratio, consisting of 1550 and 388 individuals, respectively. An additional group of 351 miners was collected as a test set for cognitive impairment assessment. Seven machine learning algorithms, including XGBoost, Logistic Regression, Random Forest, Complement Naive Bayes, Multi-Layer Perceptron, Support Vector Machine, and K-Nearest Neighbors, were used to establish a predictive model for mild cognitive impairment in the dust-exposed population, based on baseline characteristics of the workers. The predictive performance of the models was evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC), and the XGBoost model was further explained using the SHapley Additive exPlanations (SHAP) package. Cognitive function assessments using rank sum tests were conducted to compare differences in cognitive domains between the mild cognitive impairment group and the normal group.
Results: Univariate and multivariable logistic regression analyses revealed that education level, age, years of employment, SSRS (Self-Rating Scale for Stress), and HAMA (Hamilton Anxiety Rating Scale) were independent risk factors for cognitive impairment among dust-exposed workers. Comparative analysis of the performance of the seven machine learning algorithms demonstrated that XGBoost (training set: AUC=0.959, validation set: AUC=0.795) and Logistic Regression (training set: AUC=0.818, validation set: AUC=0.816) models exhibited superior predictive performance. Results from the test set showed that the AUC of the XGBoost model (AUC=0.913) outperformed the Logistic Regression model (AUC=0.778). Miners with mild cognitive impairment exhibited significant impairments (p<0.05) in visual spatial abilities, attention, abstract thinking, and memory areas.
Conclusion: Education level, age, years of employment, SSRS, and HAMA were identified as independent risk factors for cognitive impairment among miners. Machine learning algorithms can be used to predict the risk of cognitive impairment in this population, with XGBoost algorithm showing the best performance. The developed model can guide the implementation of appropriate preventive measures for dust-exposed workers.
Ongoing shuffling of protein fragments diversifies core viral functions to tackle bacterial resistance mechanisms
Authors: Smug Bogna , Szczepaniak Krzysztof , Rocha Eduardo , Dunin-Horkawicz Stanislaw , Mostowy Rafal
Published: June 2023

Phages are known for their genetic modularity. Their genomes are built of independent functional modules that evolve separately and combine in various ways, making them astoundingly diverse. Multiple studies have demonstrated how genome mosaicism emerges in phage populations and facilitates adaptation to their hosts, bacteria. However, less is known about the extent of (within-)protein modularity and its impact on viral evolution. To fill this knowledge gap, here we quantified such modularity by detecting instances of protein mosaicism, defined as a homologous fragment between two otherwise unrelated proteins. We used highly sensitive homology detection to quantify protein mosaicism between pairs of 133,574 representative phage proteins and to understand its relationship with functional diversity in phage genomes. We found that diverse functional classes often shared homologous domains. This phenomenon was often linked to protein modularity, particularly in receptor-binding proteins, endolysins and DNA polymerases. We also identified multiple instances of recent diversification via exchange and gain/loss of domains in receptor-binding proteins, neck passage structures, endolysins and some members of the core replication machinery. We argue that the ongoing diversification via shuffling of protein domains associated with those functions is reflective of co-evolutionary arms race and the resulting diversifying selection to overcome multiple bacterial resistance mechanisms.