bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Approach for the Prediction of Real-Time Rate of Penetration in Drilling for Petroleum by Combining the Attention-Based Bidirectional-Long Short-Term Memory and Long Short-Term Memory
Authors: Lyu Z. , Wei F. , Pan Y. , Li L. , Song C. , Song G. , Zhu Z. , Song X.
Published: February 2025

Rate of penetration has been considered as an important factor in the entire drilling industry, which can largely determine the overall costs of drilling a well. This paper proposed a novel real-time prediction of rate of penetration by combining the Attention-based Bidirectional-Long Short-Term Memory and Long Short-Term Memory (Att-Bi-LSTM-LSTM). Eight parameters, which are total vertical depth, weight on bit, revolutions per minute, mud flow rate, density, viscosity, drill-bit outer-diameter, lithology, and rate of penetration, are adopted as datasets. The drilling speed of the well is trained and validated through the drilling data while a sliding window is introduced for the real-time update. In addition, the presented prediction model is compared with other traditional prediction methods. Finally, the prospect of field application and further study is discussed and suggested. The results indicate that the proposed model shows good accuracy and robustness. Moreover, compared with the traditional methods, the model exhibits good superiority with smaller absolute and relative errors. For field applications, the model proposed in this paper attempts to provide a solution to the prediction of real-time rate of penetration. The results are expected to provide guidance for the further study on the increase of drilling speed and reduction of well costs.
Unlocking Hidden Potential: Conventional Log Analysis of Low Resistivity Pay in Gulf of Thailand
Authors: Chokthanyawat S. , Wanwises J. , Chaiwan P. , Junput N. , Thamvittayapoom W. , Thurachen S. , Jiwalai T.
Published: February 2025

Characterizing and evaluating low resistivity pays using conventional log acquisition and the Thomas-Stieber shale distribution method leads to improved hydrocarbon discovery, production, and economic feasibility. This study focuses primarily in the Gulf of Thailand, where results are limited despite the presence of over a hundred wells.

The Thomas-Stieber shale distribution method is a sophisticated approach used in the evaluation of low resistivity pay zones, particularly in fluvial depositional environments like the Gulf of Thailand. This method provides additional information to support the interpretation of conventional logs by accounting for the effects of shale distribution within reservoirs. By applying this technique, geologists, petrophysicists, and petroleum engineers can distinguish between hydrocarbon-bearing formations and those with conductive minerals or shales that may lead to low resistivity readings

From the single sand perforation on low resistivity pay, the effectiveness of this method in the Gulf of Thailand is proven, highlighting its potential to improve the volume of hydrocarbon discovery. This helps operators revisit their idle wells to redevelop existing wells, gain additional production, and potentially reduce the number of new drilled wells, thereby reducing CAPEX/OPEX.

This paper is supported by actual production results from more than three low resistivity pays and confirms the existence of low resistivity pay in the Gulf of Thailand. Operators can better distinguish between hydrocarbon-bearing sands and non-productive zones, leading to more effective production strategies. Accurate characterization of these zones is essential for maximizing hydrocarbon production from both idle wells (non-producing) and newly drilled wells, thereby improving overall field development plans.
Hybrid Velocity Model Building Approach (Wells and Seismic) in Unconventional
Authors: Ghosal Sambit , Nayak Soumya , Cheng Liwei , Pavlov Dmitriy , Wu Xianyun , Johnston Graham , Cruz-konen Heather
Published: February 2025

In this paper we demonstrate the methodology to build the velocity model for domain conversion of seismic image data with an aim to maximize value of seismic in unconventional assets. A velocity model is necessary to map depth and thickness of subsurface layers, interpreted from seismic reflection images. Where a seismic reflection image is produced by time or depth imaging, ensures the proper focusing and lateral positioning of the subsurface reflectors. Although a good seismic image is not enough for an exploration or field development. Good well ties and reliable depth conversion are also required (Etris et al, 2002). Time to depth conversion using vertical propagation velocities addresses vertical positioning of the reflectors to true depth. Also, depth conversion is a way to remove the structural ambiguity inherent in time and verify subsurface structure. A depth conversion consists of imaging first, to obtain the best seismic image, then depthing, to tie wells and predict depth away from the wells.
PTTEP Online Ergonomics Checkup
Authors: Amornrat T. , Waraphan N. , Athitaya J. , Jina K.
Published: February 2025

Work-related musculoskeletal disorders (WMSDs) are a common problem among office workers. WMSDs are caused by excessive work over a period of time. They initially localize and progress over time with aggravating factors including awkward posture, and static or prolonged posture.

The prevalence and incidence of WMSDs was found to be associated with an increase of computer use as most occupations involve compute use. The body structure disorders related to this WMSD include back, neck, and those extremities.

Therefore, PTTEP in conjunction with Medical and Occupational Health Team and The Faculty of Physical Therapy, Mahidol University have established the "Office Ergonomics Checkup and Consultation Project" to identify, assess and give advice for ergonomics in computer users in PTTEP Domestic Assets since 2013. From 2013 to 2019, the project conducted quarterly onsite checkups and consultations at PTTEP Headquarters. Additionally, annual sessions were held at one of the remote operation sites on a rotational basis. Most participants in the project experienced relief from their WMSDs after regularly performing exercises recommended by physical therapists.
Technologies and Achievements for Drilling and Completion of Onshore Deep and Ultra-Deep Wells in China
Authors: Zhang Jiawei , Wang Haige , Ji Guodong , Cui Meng , Chen Lili , Li Wenzhe , Liu Li
Published: February 2025

In the last decade, newly discovered oil and gas reservoirs have gradually shifted from shallow-medium to deep and ultra-deep layers globally. China also has great potential in deep and ultra-deep oil and gas resources, which is identified as the main frontiers due to the increasing difficulty in maintaining economic and sustainable hydrocarbon production from shallow-medium fields after long-term continuous exploitation. The cost-effective E&P of deep and ultra-deep oil and gas resources are crucial for achieving China's energy transition and succession strategy.

This paper reviews numerous challenges encountered during the drilling and completion of deep and ultra-deep wells, including down-hole tool failure due to ultra-high temperature, well control risks from ultra-high pressure, well control or leakage risks due to the narrow pressure window, low ROP due to high strength and abrasive formations, and pipe stuck or wellbore stability problems in salt or mudstone layers. The paper also presents the breakthroughs and applications of high-end equipment, cutting-edge tools and core downhole fluids developed to overcome these challenges, ensuring safe and efficient drilling and completion operations of deep and ultra-deep wells.

With successful breakthroughs and applications of technologies including the 12000m drill rig, wellbore structure optimization, managed-pressure drilling, efficient drill bits, drilling speed-up, ultra-high temperature resistant and high-density drilling fluids, leakage prevention, cementing, ultra-high temperature and pressure resistant oil testing and completion, and ultra-deep coiled tubing equipment, the number of onshore deep and ultra-deep wells in China has been increasing in recent years. Continuous improvements have been achieved in technical performance indicators such as the drilling cycle, ROP and other metrics. Over 200 wells successfully drilled with MD exceeding 8000m have enabled China to normalize 8000m ultra-deep onshore drilling, with drilling capacity reaching 9000m. Moreover, the well depth of TK-1 has successfully exceeded 10000m, making China the second country in the world to successfully drill onshore vertical well with the depth over 10000m. These achievements have well supported the E&P of deep and ultra-deep oil and gas resources in key areas such as the Tarim, Sichuan, Junggar and Qaidam Basins of China.

Additionally, helpful case histories are also provided to illustrate the current status and future directions for research and development of engineering technologies, aiming to achieve a secure and sustainable energy transition while reducing carbon emission through cost-effective E&P of deep and ultra-deep oil and gas resources.
An Accurate Connectivity Identification Method for Complex Shallow Fluvial Offshore Reservoir in Low-Amplitude Structure and its Application in C Oilfield, Bohai Bay Basin
Authors: Li Wenbin , Wang Yichuan , Sun Xijia , Liu Gongli
Published: February 2025

Connectivity is crucial for reserve scale, reservoir understanding and well deployment, which determines reserves and production significantly. However, traditional identification methods always fail in complex shallow fluvial offshore reservoir in low-amplitude structure due to complex wavefield, poor data and fast lateral phase transitions cause by a huge amount of channels cutting and overlapping with each other. Aiming at this problem, we present an accurate identification technology to indicate complex connectivity in these areas more exactly. Firstly, suppress marine noise in several domains. Secondly, establish typical contact modes of channels, whose connectivity are determined based on real data and production performance. Thirdly, seismic response characteristics of typical modes are analyzed based on different series of channel models with changing cutting depth, channel width and sand thickness through forward modeling. Finally, different techniques are used to identify internal single channels and dissect whole areas based on response characteristics respectively, achieving connectivity and remaining-oil areas ultimately better. Results of real data show that our result brings a very good application in promoting efficient development of Oilfield C, which achieves connectivity as well as remaining-oil enrichment areas, ensures successful optimization and implementation of 51 horizontal wells with a 93% oil-layer drilling rate, and provides a powerful tool for characterization of heterogeneity of complex shallow fluvial offshore reservoir in low-amplitude structure.
Geosteering in Laminated Porcellanitic Barmer Hill Formation: a Case Study from Tight Oil Development Reservoir, India
Authors: Walia Neha , Vardhan Harsh , Mokhtar Roslan , Bhuyan Abhinav , Singh Ranjeet , Upadhyay Akriti
Published: February 2025

Deep Azimuthal Resistivity (DAR) geosteering technology enables wells to be steered based on the resistivity observed around the wellbore and in adjacent layers. These types of logging-while-drilling (LWD) measurements provide both petrophysical data and early warning of approaching bed boundaries using geosignals. The geosignal measurement can only be calculated from an azimuthal resistivity tool and it uses raw phase shift and attenuation data, it will horn in the direction of conductivity. A common objective of these applications is typically to enhance production through more precise wellbore positioning, based on accurate characterization of bed boundaries positions and formation resistivity. A 6-1/8″ lateral section was geosteered within BH-6 unit of Barmer-Hill formation. The Barmer Hill reservoir is characterized by tilted fault block structures, with numerous gravity collapse faults. Negotiating this structural complexity, compounded by the presence of multiple hydraulic fracturing operations, posed significant geosteering challenges. BH-6 unit consists of thick high-porosity diatomite lobes intercalated with 1m-thick lacustrine claystone. The geosteering primary objective was to precisely position the well in "sweet zone" of BH6 and maintain the trajectory within this optimal zone and keeping it away from BH-6 intra shale beds. This case study showcases the capabilities of DAR geosteering tools effective well placement and trajectory management within thinly laminated formations.
Full Borehole Image Data Computation Using GAN Based Model
Authors: Liu Y. , Zhou J. , Zhang J. , Li P. , Zhou Y.
Published: February 2025

In logging interpretation, electrical image data is used to identify important geological features such as fissures and cavities, providing crucial information for evaluating productivity. Therefore, obtaining high-quality, fully restored electrical image data is essential for both manual and AI-based image interpretation methods. However, traditional image processing algorithms often produce restored data with poor correlation between geological features across plates, as well as noise and jagged edges. To address this issue, we propose a reliable method for filling in missing sections of electrical image data that can predict high-quality images using deep learning algorithms. While traditional image inpainting algorithms fail to extract meaningful features from pad data, deep learning networks using the encoder-decoder architecture can automatically learn representations of borehole images. In this work, we propose a Generative Adversarial Network (GAN) based inpainting model that generates high-quality missing pad data with semantically meaningful features as a reference for image logging interpretation. We achieved a U-Net based model as an encoder to aggregate contextual information from various feature maps through borehole image data. Based on the encoder, a simple up-sampling decoder with convolution layers is applied to predict the data in the missing area of borehole image data. The pixel-wise discriminator is used to distinguish between real image data and the corresponding synthesized patch. Our proposed model outperforms traditional inpainting methods, achieving an average accuracy of over 89% when inpainting missing areas of real borehole image data, and further validating the superiority of our method through analyzing the image log data with different azimuths. As a result, the encoder in this work also demonstrates its ability to be an efficient backbone model for extracting significant information from borehole image data.
Extending Saturation Water Calculation in 3D Reservoir Space Using Stochastic Approach
Authors: Manuaba Ida Bagus Gede Hermawan , Santoso Gagok Imam , Wibisono Dermawan , Marhaendrajana Taufan
Published: February 2025

Updating the reservoir model post-production involves integrating new data and describing for changes in resistivity and water saturation over time. This paper explains into extending the calculation beyond the wellbore, using a stochastic approach to navigate these challenges and enhance accuracy in reservoir characterization.

The Archie Equation is frequently used to assess resistivity and saturation. However, due to measurement uncertainties, a single deterministic value isn't sufficient. By adding stochastic methods in Archie Equation, we integrate diverse data inputs from various sources to enhance calculation and tackle uncertainty more effectively. The example was applied in a carbonate reservoir with some water corridors, and the computational approach extended in a radius of 200 feet within a 3D volume using LWD 3D reservoir mapping technology. By extending the analysis beyond traditional boundaries, we aim to provide a more holistic understanding of reservoir dynamics and improve decision-making in oil and gas production operations.

The well was drilled to a depth of approximately 4,000 feet measured depth (MD) within the reservoir section, utilizing comprehensive petrophysical analysis to assess textural properties and reservoir characteristics vital for optimizing completion strategies. Using the 3D Resistivity Volume from UDAR tool, water saturation levels within a 200-foot radius were calculated and correlated with interpretations near the borehole. However, due to the extensive nature of these calculations, the analysis was limited to a 100-foot radius. This example focused solely on the stochastic approach to demonstrate its robustness in accurately delineating fluid distribution within the 3D spatial domain.
Maximizing Drilling Efficiency in Deviated Wells Using AI Based ROP Optimization
Authors: Karnot Mahdi , Talib Montadher , Alkamil Ethar H. K. , Alattar Atheer , Taher Salam , Saleh Abdullah M.
Published: February 2025

This research presents a machine learning-based approach aimed at optimizing the rate of penetration (ROP) in S-shaped wells. The method uses historical drilling data from wells in Southern Iraq to find out the best drilling operating variables. Dynamic Time Warping (DTW) is applied to prioritize data from wells with similar characteristics to enhance relevance. The framework is adaptable, incorporating new field data and expert insights as necessary. The performance of the method was evaluated by comparing the results to existing well data, with clear improvements identified.

Initially, two machine learning models—Extra Trees Regressor and XGBoost—were utilized to predict ROP using 17 different input factors, such as torque and SPP. The accuracy of these models was assessed using correlation coefficients, and Extra Trees Regressor, the more accurate model, was selected to proceed into the second phase.

Next, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Firework Algorithm (FWA) were used to fine-tune key parameters like WOB, RPM, surface pump pressure (SPP), and flow rate to further improve ROP. The dataset comprised data from 6 wells, the data was partitioned to 75% to train the ML models and 25% to test them. In the prediction phase, the correlation coefficients for the models were: Extra Trees Regressor (0.99) and XGBoost (0.97) for the training set, and Extra Trees Regressor (0.96) and XGBoost (0.94) for the testing set. The average optimization improvements were 30.66% for GA, 22.33% for PSO, and 14.5% for FWA.
АНАЛИЗ ЛОКАЛЬНЫХ СИСТЕМ В ТУРИСТСКО-РЕКРЕАЦИОННОЙ СФЕРЕ ЭКОНОМИКИ ПРИВОЛЖСКОГО ФЕДЕРАЛЬНОГО ОКРУГА
Authors: Лежнин В.В.
Published: February 2025

Рассмотрены локальные системы в туристско-рекреационной сфере экономики на примере регионов Приволжского федерального округа. Выявлены лидирующие и отстающие регионы по анализируемым показателям развития локальных систем. Представлен анализ статистических данных развития локальных систем в туристско-рекреационной сфере экономики на примере Приволжского федерального округа. Определены уровни взаимодействия локальных систем между собой.

Introduction. Tourist-recreational sector is one of actively developing sector of economy. Development of tourist-recreational sector is of multiplicative nature, which means the joint development of catering, hotel services and hospitality industry, advertisement, agriculture, insurance, etc. The goal of the study is to analyze the local systems of tourist-recreational sector based on the example of Volga Federal District and reveal their major perspectives for development. The following indicators were chosen for the analysis 1) number of foreign citizens, housed in the territory of Volga Federal District in the collective and individual accommodation facilities; 2) number of Russian citizens, housed in the territory of Volga Federal District; 3) number of tourists, housed in sanatorium-and-spa institutions of Volga Federal District; 4) number of tourist organizations, performing activities with service consumers; 5) number of Russian tourists, sent to tours. Results. According to the analysis, Republic of Tatarstan takes the first place among the regions of Volga Federal District by number of foreign citizens housed in the hotels, Nizhny Novgorod oblast takes the second place, and Samara oblast - the third one. Republic of Tatarstan also takes the first place by number of Russian tourists sent to tours, Perm Territory takes the second place. Conclusion. The group of leading regions by tourist-recreational indicators (Republic of Tatarstan, Nizhny Novgorod oblast, Republic of Bashkortostan, Perm Territory) was revealed. Mari El Republic and Republic of Mordovia show low results in the tourist-recreational sector development. Thus, it is important to pay a particular attention to the tourist sector development in these regions.
МЕСТНЫЕ БЮДЖЕТЫ: ДОХОДЫ, МЕЖБЮДЖЕТНЫЕ ТРАНСФЕРТЫ, ДОЛГОВЫЕ ОБЯЗАТЕЛЬСТВА
Authors: Зотиков Н.З. , Урусова И.Н.
Published: February 2025

Местные бюджеты являются главным звеном всей бюджетной системы России. Основными источниками доходов бюджетов различных уровней являются закреплённые за ними налоговые доходы, неналоговые доходы, а также межбюджетные трансферты. В статье анализируются роль и значение доходов местных бюджетов. Авторский подход заключается в том, что в статье рассматриваются доходы не отдельных видов местных бюджетов, а всех местных бюджетов в целом. Цель статьи – исследование проблемных вопросов формирования доходов местных бюджетов на основании официальных данных Минфина России. Исследованием установлено, что финансовые проблемы местных бюджетов, особенно муниципальных районов и поселений, заложены в самом налогово-бюджетном механизме, без внесения в него существенных изменений благополучие местных бюджетов недостижимо.

Introduction. The existing fiscal mechanism, in which certain tax revenues are assigned to each level of the budget system, has led to deficits of regional and local budgets, their subsidization; they need constant gratuitous injections from the federal center. Regional and local budgets were practically without funds for successful economic development. The aim and objectives of the study are to use the official data provided by the Ministry of Finance of the Russian Federation for a period of several years in order to analyze financial problems and their causes not only in relation to local budgets in general, but also to the budgets of municipal districts, municipal areas, rural and urban settlements. Methods. The study is based on such research methods as analysis and synthesis, grouping, generalization, table method, etc. The results obtained indicate an unsatisfactory financial condition of the budgets of municipal districts, urban and rural settlements that prevail in the structure of local budgets. Tax revenues assigned to local budgets (personal property tax, land tax) make up no more than 20-25 per cent of the local budget tax revenues; over two thirds of the local budget tax revenues accounts for the federal tax - personal income tax. A significant share of the total revenue of local budgets comes from gratuitous revenues, grants and subsidies which do not foster interest in the development of local territories, but only cover local budget deficits. Conclusion. The study confirmed that effective taxes should be assigned to local budgets, which would encourage interest of the local budgets in the development of their territories. This relates to the taxes received by local budgets before the introduction of the Tax Code of the Russian Federation: VAT, income tax. The practical relevance of the study is that its findings and suggestions can be used in the activities of the relevant branches of government in the development and enhancement of the fiscal policy.
КОНЦЕПТУАЛЬНЫЙ ПОДХОД К ESG-ОЦЕНКЕ КАК ФАКТОРУ УСТОЙЧИВОГО РАЗВИТИЯ КОМПАНИИ
Authors: Губайдуллина Т.Н. , Глазкова И.Н.
Published: February 2025

Цель исследования заключается в том, чтобы определить, существует ли положительная или отрицательная взаимосвязь между отчётностью об устойчивом развитии, управлением экономическими, социальными и управленческими факторами (ESG) и корпоративной эффективностью и устойчивым ростом предприятий. Устойчивый рост на уровне компании представлен как измерение, которое зависит от отчётности по устойчивому развитию и управления факторами ESG. Большая часть существующей литературы посвящена причинно-следственной связи между показателями устойчивости и финансовыми показателями. В работе рассматривается влияние и реализация критериев ESG не только на производительность, но и на устойчивый рост компаний.

sustainable development; ESG criteria; financial performance; market indicators; sustainable growth
Measurements of Local pH Gradients for Electrocatalysts in Oxygen Evolution Reaction by Electrochemiluminescence
Authors: Wang Yu , Zhou Sijia , Zhen Yongjun , Wang Yongji , Hou Yuhua , Wu Kaiqing , Huang Chaofeng , Liu Songqin , Shen Yanfei , Chen Ran , Zhang Yuanjian
Published: February 2025

An accurate understanding of the mechanism of the oxygen evolution reaction (OER) is crucial for catalyst designing in the hydrogen energy industry. Despite significant advancements in microscopic pH detection, selective, sensitive, speedy and reliable detection of local pH gradients near the catalysts during OER remains elusive. Here, we pioneer an electrochemiluminescence method for local pH detection during OER. For this purpose, a new class of ECL emitters based on ECL resonance energy transfer (ECL-RET) was theoretically predicted and facilely synthesized by grafting functional fluorescent dyes onto noble 2D carbon nitride. By positioning one of as-prepared ECL emitters with pH-responsibility neighboring to OER catalysts, local pH gradients generation near the catalysts could be qualitatively measured in real-time with subsecond resolution. It provided details of the reaction mechanism of OER and unveiled the catalyst degrading pathway caused by proton accumulation. Besides, the average proton generation rate on the catalyst was also extractable from the local pH measurement, as a quantitative descriptor of the OER reaction rate. Owing to the high designability of the grafting method, this study opens up new strategies for studying reaction mechanisms and detecting intermediates.
From Data to Chemistry: Revealing Causality and Reaction Coordinates through Interpretable Machine Learning in Supramolecular Transition Metal Catalysis
Authors: Talmazan Radu A. , Gamper Jakob , Castillo Ivan , Hofer Thomas S. , Podewitz Maren
Published: February 2025

Supramolecular transition-metal catalysts with tailored reaction environments allow for the usage of abundant 3d metals as catalytic centres, leading to more sustainable chemical processes. However, such catalysts are large and flexible systems with intricate interactions, resulting in complex reaction coordinates. To capture their dynamic nature, we developed a broadly applicable, high-throughput workflow, leveraging quantum mechanics/molecular mechanics molecular dynamics (QM/MM MD) in explicit solvent, to investigate a Cu(I)-calix[8]arene catalysed C-N coupling reaction. The system complexity and high amount of data generated from sampling the reaction require automated analyses. To identify and quantify the reaction coordinate from noisy simulation trajectories, we applied interpretable machine learning techniques (Lasso, Random Forest, Logistic Regression) in a consensus model, alongside dimensionality reduction methods (PCA, LDA, tICA). Leveraging a Granger Causality model, we go beyond the traditional view of a reaction coordinate, by defining it as a sequence of molecular motions that led up to the reaction.
The Unique Factor Governing Atomistic Rh-Catalyzed Dehydrogenation of CH₄
Authors: Sun Changqing
Published: February 2025

We uncovered that the valence density-of-states (DOS) gain, denoted as polarity (), of the catalyst Rh- uniquely governs the efficiency of CH4 dehydrogenation based on quantum computations of CH4-Rh(111;100) surfaces with and without Rh1 adatoms and Rh0 vacancies. Atomic undercoordination shortens the ligand-catalyst distance, transforming the undercoordinated Rh into a dipole Rh- species that forms the Rh-:H+-C- coupling bonds, where “:” denotes the electron-rich pole. The Rh-:H+ attraction and Rh-:C- repulsion shorten the RhP:H distance and elongate the H-C bond. The extents of Rh-:H-C segmental relaxation, catalyst valence band upward shift, and adsorption energy all vary exponentially with . The adsorption energy follows the order: Rh30(111) > Rh1/Rh(111) > Rh10(100) > Rh1/Rh(100) > Rh10(111) > Rh(100) > Rh(111) order, highlighting the significance of the dipolar coordination configuration. These findings should apply to undercoordinated catalytic reactions where the electric field of the dipolar catalyst plays a key role.
A Systematic Investigation of TMB Substrate Composition for Signal Enhancement in ELISA
Authors: Khramtsov Pavel , Novokshonova Anastasia , Galaeva Zarina , Morozova Maria , Bezukladnikova Tatiana , Rayev Mikhail
Published: February 2025

3,3',5,5'-Tetramethylbenzidine (TMB) remains one of the most widely utilized chromogenic substrates for horseradish peroxidase (HRP) in colorimetric immunoassays, including enzyme-linked immunosorbent assays (ELISA). Despite its introduction into ELISA workflows over four decades ago, limited research has been conducted to systematically optimize TMB substrate formulations. Recent advancements in the field have proposed innovative approaches to enhance HRP catalysis, such as the use of deep eutectic solvents and ionic liquids, alongside investigations into the chemical properties of TMB and its analogs to identify more efficient alternatives. However, the development of stable and high-performance TMB solutions for clinical diagnostics requires a comprehensive understanding of how formulation parameters influence signal intensity and stability. In this study, we address these gaps by conducting a systematic evaluation of key factors affecting TMB substrate performance, including buffer pH, composition and molarity, specific ion effects, incorporation of organic solvents, and the use of polymer stabilizers. Additionally, novel strategies for signal amplification, identified through an extensive review of literature and patents, were experimentally tested. Based on these findings, we developed an optimized TMB formulation that was benchmarked against existing formulations reported in the literature.
Endothelial dysfunction in patients with systemic AL amyloidosis
Authors: Khyshova Viktoria A. , Rekhtina Irina G. , Zozulya Nadezhda I. , Dvirnyk Valentina N. , Mendeleeva Larisa P.
Published: February 2025

Background. Research related to the state of blood vessels in systemic AL amyloidosis (AL-A) is mostly done on experimental models. The pathogenetic and clinical significance of vascular dysfunction in patients with AL-A is poorly understood.
Aim. To study the levels of endothelial dysfunction markers in patients with AL-A at the onset of the disease and after anti-tumor therapy.
Materials and methods. The study group included 30 patients with AL-A. The comparison group consisted of 10 patients with multiple myeloma (MM), and the control group included 10 healthy individuals. Patients with AL-A were divided into 2 groups: the first group included 20 patients who underwent the full planned induction therapy, and the second group included 10 patients whose treatment was stopped due to a significant increase in N-terminal pro-brain natriuretic peptide (NTproBNP) levels. The levels of asymmetric dimethylarginine (ADMA), big endothelin (bET), and E-selectin were measured by enzyme-linked immunosorbent assay in serum before and after completion (or premature cessation) of anti-tumor therapy.
Results. Patients with AL-A had significantly higher levels of E-selectin and ADMA in serum compared to patients with MM and healthy individuals. An increase in at least one marker of endothelial dysfunction (E-selectin and ADMA) was observed in 27 (90%) patients with AL-A at disease onset. There were no differences in bET levels. In all patients in the first group, reaching hematologic remission was associated with a decrease in E-selectin and ADMA levels compared to baseline values (p0.001). In 5 (55%) out of 9 patients with hematologic and organ response, ADMA levels decreased to normal values. In all patients of the second group, the increase in NTproBNP was accompanied by a significant increase in ADMA (p=0.005) and E-selectin (p=0.007) levels compared to baseline values. Adverse cardiovascular events were observed in 80% of patients with elevated NTproBNP levels. The increase in cardiac markers during anti-tumor therapy was more common in advanced stages of heart involvement. Stage IIIA AL-A was present in 23% of patients in the first group and 70% in the second group (p=0.003). After discontinuation of therapy, the levels of cardiac markers decreased to baseline values, which ruled out disease progression.
Conclusion. A pronounced endothelial dysfunction was observed in 90% of patients with AL-A. Reduction in endothelial dysfunction markers was observed upon achieving hematologic and organ response. Anti-tumor therapy in patients with amyloid cardiomyopathy can cause additional endothelial damage, resulting in increased NTproBNP levels and cardiovascular complications.
Rebamipide: thirty years of experience. A review
Authors: Bakulina Natalia V. , Ponomarenko Viktoriia A. , Bakulin Igor G.
Published: February 2025

The review article describes the 30-year practice of using the cytoprotector rebamipide. The use of the drug in South Korea and Russia in various gastrointestinal disorders, including gastroesophageal reflux disease, functional and organic dyspepsia, chronic gastritis, gastric ulcer, including those associated with H. pylori, inflammatory bowel diseases, irritable bowel syndrome, and as a carcinopreventive agent has been demonstrated. Particular attention is paid to drug-induced conditions, given the uncontrolled use of non-steroidal anti-inflammatory drugs and the high prevalence of cardiovascular diseases, which requires the use of antithrombotic drugs with ulcerogenic action.
Non-alcoholic fatty liver disease and cognitive impairment
Authors: Onuchina Elena V. , Dambaeva Bairma B. , Glazunova Anna G. , Mikhailova Ayuna Kh. , Vorobyova Elena M. , Soshina Elena I. , Efremenko Natalya V.
Published: February 2025

Aim. To evaluate the efficacy of oral administration of the original ademetionine (Geptral) at a dose of 1500 mg/s in patients with NAFLD at the steatosis stage and cognitive impairment within the framework of a prospective observational open non-comparative study in real clinical practice against the background of achieved lifestyle modification.
Materials and methods. Thirty patients with NAFLD and cognitive impairment were examined using routine methods examination. NAFLD was diagnosed in accordance with the clinical guidelines of the Ministry of Health of the Russian Federation. All patients met the criteria for MAFLD. Cognitive functions were assessed using the Montreal Cognitive Assessment Scale. After selection, patients were recommended dietary and physical activity modification in combination with oral administration of the original ademetionine at a dose of 1500 mg/day. The duration of the study was 6 months.
Results. Oral administration of the original ademetionine for 6 months against the background of lifestyle modification improved cognitive functions with an increase in the Montreal Cognitive Assessment Scale score from 19.1 (16.3–20.1) to 27.6 (25.1–29.0; p=0.001). In addition, the study found a decrease in the severity of steatosis according to the FLI index and quantitative ultrasound. Additionally, a decrease in the Fatigue Assessment Scale (FAS) scores from 34 [25–39] to 19 [16–27]; p=0.000002, and 10-year fatal and non-fatal cardiovascular risk according to the SCORE2 scale from 34 [15–44] to 9 [7–13]; p=0.000002, was revealed.
Conclusion. The original ademetionine as a multitarget drug for NAFLD may be useful in terms of improving cognitive functions, increasing adherence to lifestyle modification, and improving its quality and duration.
Combination of Crohn's disease and intestinal tuberculosis. Clinical observation
Authors: Ruchkina Irina N. , Knyazev Oleg V. , Kieva Alina A. , Lishchinskaya Albina A. , Khomeriki Sergey G. , Pelipas Irina G. , Lesko Konstantin A. , Demchenko Alexandra N. , Рafrfenov Asfold I.
Published: February 2025

According to WHO, extrapulmonary forms of tuberculosis (TB) account for 10–15% of the total number of tuberculosis cases worldwide. Crohn's disease (CD) and intestinal tuberculosis have similar clinical, endoscopic and morphological manifestations in many ways. In all cases, when detecting intestinal CD, it is necessary to exclude tuberculosis infection in biopsies using PCR diagnostics. The risk of developing various forms of TB increases with pathogenetic immunosuppressive therapy for inflammatory bowel diseases. A clinical case of a rare combination of the intestinal form of TB and CD is presented, reflecting the difficulty of diagnosing the two pathologies and the difficulty of choosing therapy when they are combined.
Drain the Swamp to Save the Swamp: mitigating capture in environmental regulatory systems
Authors: Doole Marie , Stephens Theo
Published: February 2025

Regulatory capture undermines the integrity and effectiveness of environmental regulatory systems by allowing the power of vestedinterests to undermine the public interest in nature (i.e., humanity’s collective interest in a healthy and sustainable biosphere). Mitigating the capture of environmental regulatory systems necessitates a deliberate rebalancing of the power of different actors within a democratic context to reduce the typical dominance of vested interests. This rebalancing must address both the narrative framing and direct capture actions of vested interests (Ulucanlar et al., 2023). Cumulatively, the mitigation strategies we propose (promoting evidence-based policy, rigorous analysis, transparency and supporting public interest advocacy) will support that rebalancing.
Federal Workforce Reforms in Trump’s Second Term: two scenarios
Authors: Baehler Karen
Published: February 2025

Five early proposals from the second Trump administration add up to a potentially dramatic shift of power within the executive branch of the federal government and between the executive and legislative branches. With help from conservative think tanks and the Republican-led Congress, the 2024 election has opened the door to an increasingly powerful US presidency and an ever-weaker constitutional order.
‘Fortress New Zealand’: examining refugee status determination for 11,000 asylum claimants through integrated data
Authors: Fadgen Tim , Malihi Arezoo Zarintaj , Manning Deborah , Mills Harry , Marlowe Jay
Published: February 2025

This article presents a profile of Aotearoa New Zealand’s asylum claimants – people who have sought recognition as a refugee or protected person and then applied for a temporary visa. Sourcing data from New Zealand’s Integrated Data Infrastructure (IDI), we considered 11,091 refugee claimants between 1997 and 2022. The data suggests that the path to recognition can be long and circuitous, requiring multiple applications before status recognition. The data also reveals a wide health and mental health services uptake gap despite recent policy changes. When read together, we contend that this data supports the notion that everyday, discerning bordering exists in New Zealand through different forms of permeability and permanence based on gender and ethnicity. The article concludes with some insights for future policy directions.
Effectiveness of a machine learning classifier model
Authors: Sakalle Sonal , Rai Sakshi
Published: February 2025

As a statistical tool, predictive modelling may foretell how something will act in the future. In order to foretell how people will act in the future, machine learning has become a popular tool. Determining which of the many accessible algorithms is best suited to the data at hand is an intriguing challenge. The field of study that finds the greatest value in predictive modelling is educational data mining. Accurately predicting undergraduate students' grades has several benefits for both students and teachers. Students might be more motivated to choose their future endeavours with the support of early prediction. Using data gathered from undergraduate studies, this study displays the outcomes of many machine learning methods. It uses data obtained from undergraduate studies to assess the efficacy of several machine learning methods. Choosing the proper characteristics and the right prediction algorithm are two big problems that are addressed.
Barriers and Strategies for Overcoming Caste Patriarchy in Women's Political Empowerment
Authors: Pandey Bhoopesh Kumar , Kumar Alok
Published: February 2025

The subject of women's political engagement has recently come to the forefront in democracies. The term "political participation" encompasses not only casting a ballot but also taking part in any and all political processes. Without women's equitable involvement, democracy would fail, despite the fact that they make up half of the global population. There have been many initiatives on a global and national scale to encourage more women to run for office. Women in India have the same legal protections as males, according to the country's constitution. In addition, local governments are required to set aside a certain number of seats for women from certain demographics. Political participation by women in India is fully encouraged and supported. Particularly in rural regions, Dalit women are among the most marginalised members of society, and their political engagement is fraught with difficulty.
Machine Learning Algorithms to Enhance The Performance of PD Prediction
Authors: Bopche Lakshmikant , Bhangari D. S.
Published: February 2025

Deep learning's strong performance and capacity to learn features automatically have propelled it into the AI mainstream in recent years, where it is being used in a wide variety of applications. In certain fields, like medicine, deep learning may outperform human physicians in terms of accuracy. neurodegenerative diseases, especially Alzheimer's disease, affecting neurons. Tremors, stiffness, and decreased balance are classic motor symptoms of Parkinson's disease, which is caused by a depletion of dopamine neurons in the brain. This disruption in smooth coordination and communication with other nerve cells makes the condition more difficult to control. One of the hallmark clinical aspects of Parkinson's disease is a decline in motor coordination, which shows the central role of dopamine in controlling movement. Motor and non-motor symptoms are also affected by a lack of dopamine neurons. Manual symptom checking is still used to identify Parkinson's disease by doctors and other medical professionals. Researchers have proposed a plethora of ways for Parkinson's disease diagnosis. Voice signals, handwriting traces, MRIs, PET/SPECT scans, and a battery of other modalities are all part of the toolbox for these techniques. Patients with the condition now have improved alternatives for managing symptoms, even though there is no proven medicine to change the illness.
Impact of Various Telecom Policies on Tele-Density Growth
Authors: Kumar Pramit , Sharma Ravindar Prasad
Published: February 2025

Seventy percent of India's rural population works in agriculture, although the sector only accounts for 23 percent of the country's gross domestic product (GDP). Factors like as unpredictable weather, inefficient markets, and investment-related obstacles pose significant risks to the industry. The expansion of cellular networks into rural India has the potential to significantly boost agricultural output. There have been substantial positive welfare impacts from mobile telephony, as shown by the empirical research. Technological advancements, such as the ever-increasing efficiency and decreasing prices of telecom equipment, and regulatory reform, which has enabled enterprises to compete more freely in the telecom market, are the primary forces behind the proliferation of mobile telecommunications (Gruber). Given that 70% of India's population resides 60 percent of the population is under the age of 18 in rural regions of 35, it is crucial to comprehend the immense potential associated with the younger generation's propensity to utilize the internet and the correlation between the expansion of education and its proliferation, as highlighted in the 2011 ICT report.
Nanocomposite photocatalyst facile fabrication with efficient photocatalytic activity under visible light
Authors: Suman Sandeep Kumar , Singh Naval
Published: February 2025

A precipitation-deposition mixture of manganese dioxide and lead sulphide was produced with lead sulphide concentrations ranging from half a milligramme (0.5 PbS) to one and a half milligrammes (1.5 PbS). Testing the metal with different instruments was the next stage. Some of the methods that were used include photoluminescence spectroscopy, SEM, ED-X-ray spectrometry, BET-surface area, and UV-visible diffuse reflectance spectra. Testing the photocatalytic activity using methylene blue dye revealed that 1% PbS/MoS2 outperformed both 0.5% and 1.5% PbS/MoS2. We looked at the photocatalytic activity as a function of pH and catalyst dose, among other factors. Light activates the PbS-MoS2 combination, which effectively breaks down methylene blue (MB) dye.
Impact on Competitiveness in Indian Automobile Sector During Post Liberalization Phase
Authors: Kamble Kalpesh Sunil , Jha Vinay Chandra
Published: February 2025

The Indian automobile sector has undergone significant transformations, particularly during the post-liberalization phase that commenced in 1991. This phase marked the opening of the Indian economy to global markets, ushering in technological advancements, foreign direct investment (FDI), and increased competition. This study critically examines the impact of liberalization on the competitiveness of the Indian automobile sector. By analyzing key factors such as market entry of global automobile giants, adoption of modern manufacturing practices, and the role of government policies, the study reveals that liberalization enhanced both domestic and international competitiveness. However, it also exposed the sector to global market volatility and operational challenges. The study further discusses the industry's transition, highlighting shifts in production standards, consumer preferences, and supply chain efficiencies, all of which contributed to the sector's resilience and growth.
A Study of HRM in Team Building and Organizational Development
Authors: Divyanshi Litoriya Divyanshi Litoriya , Dr. Indal Kumar Dr. Indal Kumar
Published: February 2025

The goal of teambuilding activities is to increase productivity by strengthening relationshipsamongst employees. The potential for dissatisfaction among team members should be taken into accountthroughout the hiring process. Team building activities should be supplemented by actual work experience.Good HR policies and procedures may aid in the formation of effective teams, which may increase outputand morale. Individual members, supervisors, and upper-level executives, as well as the organization'soverall structure, culture, work methods, and social interactions, are all affected. The new rules areexpensive and complicated, so it will take time to form an effective implementation team and put them intoeffect. The gains have been so considerable, however, that those responsible for their implementationhave no intention of going back to the previous systems. Despite these obstacles, a concerted effort todevelop teams may lead to a number of beneficial outcomes. That's why we're looking at how tomaximize team productivity.