bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing a Novel Machine Learning-Based Petrophysical Rock Typing (PRT) Classification: Applied on Heterogenous Carbonate Reservoirs
Authors: Abbas Mohammed A. , Al-Mudhafar Watheq J. , Alsubaih Ahmed , Al-Maliki Ali , Al-Sukaini Ali
Published: September 2024

Petrophysical Rock Typing (PRT) from core and well log data is a valuable tool for reservoir discrimination and recoverable reserve estimation in heterogeneous multimodal pore carbonate systems. However, the traditional PRT methods are often ineffective in these systems because of the complex pore geometry and distribution. This work introduces an innovative PRT technique that utilizes cutting-edge machine learning algorithms to categorize petrophysical rock types in a supergiant oil and gas field located in southern Iraq. The study initially employs Ward's hierarchical clustering method to define PRT from mercury injection capillary pressure (MICP) data. Ward's algorithm methodology discovers five separate groups, each of which corresponds to a different petrophysical rock type with a distinct pore geometry and system. The probabilistic neural network (PNN) approach is then used to classify PRTs from well-logging data in a cored well. The PNN algorithm is able to learn the non-linear complex relationships between well logging data and characterized PRTs, and it is able to predict PRTs with high accuracy. The confusion matrix and the total correct percent (TCP) were used as additional criteria to analyze the effectiveness of the PNN classification algorithm's performance. The study's results showed that the predicted and observed PRT had an exceptional match by attaining 94% of TCP based on the testing subset and 95 % of TCP for the entire dataset. The predicted PRT distribution is utilized as an extra independent variable to improve the modelling and prediction of core permeability and saturation height function that are essential to achieve a realistic geological distribution. The study's findings demonstrate that the suggested PRT approach can accurately categorize PRT in heterogeneous multimodal pore carbonate systems. The strategy can be easily applied to different reservoirs and has the potential to enhance the overall reservoir characterization.
Video-Powered AI Solutions for Active Monitoring and Safety Improvement in Offshore Environments: The BRAM Offshore and Altave Case
Authors: Neto Wilson Augusto Borges Leal , Gonçalves José Henrique Mouallem , Duplan Marco
Published: September 2024

This paper explores the utilization of video-based artificial intelligence (AI) tools for enhancing safety measures in offshore environments, specifically within the Bram Offshore fleet in Brazil. The study focuses on the application of AI-powered systems in monitoring and analyzing critical activities, identifying potential risks, and preventing hazardous incidents. It highlights the development and implementation of advanced AI algorithms integrated with video monitoring technology, showcasing their effectiveness in real-time risk detection and mitigation. By monitoring Personal Protective Equipment (PPE) compliance and managing Red Zone areas, these AI solutions significantly improve safety protocols and incident prevention. High-resolution cameras capture detailed images of operations, and the resulting dataset is used to train deep learning algorithms through techniques such as segmentation, classification, object detection, pose estimation, and tracking. Real-time insights are presented on a web platform as alerts, reports, and dashboards, with audible alarms for critical scenarios to ensure immediate interventions. The system's effectiveness is demonstrated through data from the Reedbuck vessel during the last year of operation. Key findings include enhanced hazard detection and improved safety, establishing video-based AI tools as a transformative approach to safety management in the offshore industry.
Early Wells Delivery Leads to Substantial Oil and Gas Field Development Projects Net Profit Value Gain
Authors: Vigor H. , Estvold S. , Kern S. , Vasvary A.
Published: September 2024

An unconventional resources operator is more likely to achieve a higher value from an unconventional field development campaign by establishing a collaborative work relationship with the lead drilling rig contractor at the outset of the early planning stages. This paper discusses the multiple benefits of early collaboration, with the end result of earlier delivery of wells and production revenues, leading to substantial project net present value (NPV) gains.

Traditionally, the field development plan is solely managed by the operator. A plan typically describes the subsurface properties of the field and outlines the development plan for it which includes drilling, completion, testing, stimulation, and production strategies. The planning stage is critical to optimize the selection of the right rigs for the job. Super spec fast-moving rigs, combined with drilling technology deployment, can help to safely and efficiently drill a well and thereby reduce the amount of time needed to complete the well program. Technologies assist to enable proper wellbore placement, directional drilling automation, rate of penetration (ROP) enhancement, and help reduce the occurrence of downhole tool failure events leading to well construction nonproductive time (NPT). In a multi-well pad environment, early and predictable well delivery helps avoid fracking delays and leads to an earlier production onset. Efficiency can be jointly optimized by defining together the following: optimal well pad layout, number of wells, distance between wells, well suspension strategy after drilling and prior to frac operations, simultaneous operations matrix between top hole drilling, batch drilling and reservoir fracking, to optimize well construction, reservoir drainage, and the frac campaign.

The analysis presented in this paper compares a one well pad Base Case scenario to multiple super spec multi-well pad scenarios, showing that optimum use of rigs on multi-well pad deployments can lead to a greater number of wells drilled within the same timeframe with lower individual cycle times.

The benefits of this close collaboration are three-fold: planning for success and performance in reducing well construction time and cost due to modern rigs and technologies deployment, optimizing rig and frac fleet deployments through proper well pads activities including simultaneous operations, and early well delivery leading to unlocking additional revenue through early production. More than 40% project NPV gain can be recorded over drilling campaigns, making it an attractive strategy for the operator.
Advancing Oilfield Safety: A Computer Vision Approach to Line of Fire Risk Detection
Authors: Lam Tammy , Santhalingam Vignesh , Abinader Antonio , Vesselinov Velizar , Krishna Dhananjaya
Published: September 2024

In industrial environments, the movement of heavy equipment poses significant risks to personnel. This paper presents a Line of Fire (LoF) Detection system that leverages real-time video feeds, object detection, and motion tracking to identify and alert when individuals are in the path of moving equipment, specifically pipes. The system utilizes advanced machine learning models for person detection and pipe segmentation, combined with a robust alert mechanism, to enhance safety measures.
Development of BOP API Flange Capacity Using Simulation Approach
Authors: Lu Wangming , Loganathan Sriram , Singh Yanez , Corkhill John
Published: September 2024

Flanges commonly selected for use in offshore equipment are based on the designs found in American Petroleum Institute (API) standards and depend on the predicted load during planned operations and capacity of the flange. The flange capacity is derived from standard analysis techniques provided by API Technical Reports 6AF, 6AF1, and 6AF2. It is however possible to conduct analysis to determine the flange capacities using more sophisticated methods to improve the accuracy of the analysis which can potentially lead to deriving higher capacity results that are less conservative. This paper presents a detailed analysis of an API 18-3/4" 15 ksi BX-164 flange capacity at ambient and an elevated temperature of 375°F. It also clarifies stress and leakage criteria and details the discrepancies in analysis methodology and capacity results between API 6AF2 and ourapproach.

To calculate the capacity of an API 18-3/4" 15 ksi BX-164 flange, a 180-degree 3D model is created to calculate the detailed load and stress distribution under different combinations of loadsincluding a flange, hub, and gasket. Both flange and hub are modeled with linear elastic material properties while the gasket is modeled with elastic-plastic material properties. For the flange capacity at elevated temperatures, a steady state decoupled thermal analysis is performed first to obtain the temperature gradient and subsequent thermal stress. The material properties are derated due to elevated temperature per API 6MET. An elastic-plastic approach is then employed to calculate the capacity under a series of load combinations of pressure, tension and bending, using the design factors defined in ASME BPVC, Section VIII, Division 2. The analysis result is based on both stress and leakagecriteria to determine the limiting capacity under various load cases.

This work presents a capacity chart that shows the relationship between pressure and bending under various tensions at both ambient and elevated temperatures and further clarifies the stress and leakage criteria. Results show that the overall capacity at ambient temperature based on this analysis is significantly higher than published API reports. Additionally, the capacity of the flanged connection at 375°F is reduced when compared to the capacity at ambient temperature. The capacity reduction from elevated temperature is more pronounced at lower pressures. The flange capacity at both ambient and elevated temperatures is governed by bolt stress criteria.

As publicly available capacity charts for API 18-3/4" 15 ksi BX-164 flanges calculated using modern finite element approaches are rare, the analysis method presented in this paper defines a process to calculate the flange capacity at elevated temperatures. This approach can potentially lead to deriving higher capacity results that are less conservative which aids in operational and well design decisions.
A New Methodology for Data Assimilation Using Capacitance-Resistance Model Combined with Fractional Flow and Aquifer Modeling
Authors: Maschio Célio , Avansi Guilherme Daniel , Schiozer Denis José
Published: September 2024

Data assimilation for uncertainty reduction (DAUR) using reservoir simulators demands high computational time and resources. Depending on the reservoir model, the process can take days or weeks. Therefore, it is desirable to speed up the process to increase its efficiency, keeping the quality of the result. Our aim in this paper is to present a new methodology for data assimilation (DA) using the capacitance-resistance model (CRM), integrated with fractional flow (FF) models, to reduce the computational time and resources in the process. The methodology brings novel contributions, such as (a) applying the CRM in a probabilistic manner for DA, (b) developing a new FF approach, and (c) proposing a new approach for aquifer modeling under uncertainty. The methodology was successfully applied in a real field case. To validate the CRM results, we compared the DA process using the CRM with the DA results using the reservoir simulator. This comparison showed a very good agreement between the results. Notably, the CRM approach was up to 279 times faster than the process using the reservoir simulator. We also validated the CRM results using several kinds of multidisciplinary geoengineering data from the same studied case, including (1) historical injection, (2) hydraulic communication analysis based on static well pressure, (3) water salinity measurements analysis, and (4) 4D seismic analysis. These analyses showed the consistency of the CRM results in terms of physical representativeness. After an extensive validation process, we can state that the CRM approach, combined with the novel FF proposed in this work, has great potential to be applied in DA, reservoir management, and production strategy optimization, thus contributing to the acceleration of the decision-making process.
Identification of Nearly Pure Leakoff Phase from Pressure Falloff Curve and Its Interpretation on Stimulated Fracture Areas
Authors: Wei Zhaoyang , Sheng Mao , Hu Zhongyu , Cheng Shizhong , Liao Qinzhuo , Tian Shouceng
Published: September 2024

Evaluation of fractures post-hydraulic fracturing is crucial for optimizing fracturing designs. Pressure falloff analysis methods, due to their cost-effectiveness and ease of data acquisition, have been widely used in oil fields. However, traditional pressure falloff analysis methods are based on the assumption of simple double-wing fractures and often overlook the impact of early-time abnormal leakoff behaviors. While some scholars have proposed pressure falloff equations for individual abnormal leakoff behavior, establishing pressure falloff models that consider the coupling of multiple abnormal leakoff behaviors is challenging, making the assessment of complex fracture networks difficult. This paper proposes a method that identifies the phase of nearly pure leakoff pressure falloff through continuous wavelet transform (CWT) and utilizes this phase for fracture inversion. Additionally, the fracture inversion model considers the differences in closure pressure and fracture compliance between main and secondary fractures. This method is applied to a shale horizontal well, and the results show that the inversion fracture areas are 20.3% smaller on average than the traditional method after removing the disturbance of abnormal leakoff behaviors. The new method is verified by the production data of each stage. The correlation between the main fracture area of new method and the production of each stage is better than that of the traditional method, and the correlation coefficient is 0.767. It is also found that the development degree of natural fractures affects the proportion of main and secondary fractures. In addition, it is found from the time-frequency diagram after CWT that the stages with higher secondary fracture proportions have more high-frequency components in the time-frequency diagram.
Estimating Carbon Dioxide Solubility in Brine Using Mixed Effects Random Forest Based on Genetic Algorithm: Implications for Carbon Dioxide Sequestration in Saline Aquifers
Authors: Mwakipunda Grant Charles , Ibrahim AL-Wesabi , Kouassi Allou Koffi Franck , Komba Norga Alloyce , Ayimadu Edwin Twum , Mgimba Melckzedeck Michael , Ngata Mbega Ramadhani , Yu Long
Published: September 2024

Accurate prediction of carbon dioxide (CO2) solubility in brine is crucial for the success of carbon capture and storage (CCS) by means of geological formations like aquifers. This study investigates the effectiveness of a novel genetic algorithm-mixed effects random forest (GA-MERF) model for estimating CO2 solubility in brine. The model’s performance is compared with established methods like the group method of data handling (GMDH), backpropagation neural networks (BPNN), and traditional thermodynamic models. The GA-MERF model utilizes experimental data collected from literature, encompassing key factors influencing CO2 solubility: temperature (T), pressure (P), and salinity. These data are used to train and validate the model’s ability to predict CO2 solubility values. The results demonstrate the superiority of GA-MERF compared to the other models. Notably, GA-MERF achieves a high coefficient of determination (R) of 0.9994 in unseen data, indicating a strong correlation between estimated and actual CO2 solubility values. Furthermore, the model exhibits exceptionally low error metrics, with a root mean squared error (RMSE) of 2×10-8 and a mean absolute error (MAE) of 1.8×10-11, signifying outstanding accuracy in estimating CO2 solubility in brine. Beyond its high accuracy, GA-MERF offers an additional benefit—reduced computational time compared to the other models investigated, with 65 seconds. This efficiency makes GA-MERF a particularly attractive tool for real-world applications where rapid and reliable CO2 solubility predictions are critical. In conclusion, this study presents GA-MERF as a powerful and efficient model for predicting CO2 solubility in brine. Its superior performance compared to existing methods and previous literature highlights its potential as a valuable tool for researchers and engineers working on CCS projects utilizing aquifer storage. The high accuracy, low error rates, and reduced computational time make GA-MERF a promising candidate for advancing the development of effective and efficient CCS technologies.
Quantifying the Transformational Requirements of the Electricity Sector Under Uncertain Expectations of Carbon Removal
Authors: Yang Pingjian , AFRANE SANDYLOVE , Ampah Jeffrey , ADUN HUMPHREY , Chen Jianlin , Zou Hongyang , Mao Guozhu
Published: September 2024

Decarbonization and carbon dioxide removal (CDR) are crucial for achieving global climate targets. The power sector is pivotal in this process, yet the role of CDR in deep decarbonization and its implications on the sector have been underexplored. Using a global multi-sector model, we quantify the effects of CDR on the transformation of the power sector under different CDR reliance levels by 2050 — high (4–10 Gt/yr), moderate (2.5-5 Gt/yr), and low (≤ 1Gt/yr)—aligned with 1.5°C and 2°C climate targets. We show that BECCS is essential for future electricity demands, particularly in Asia and Central America. High CDR pathways could require 10–20% of electricity consumption in South America and Australia/New Zealand for carbon removal. Major economies like China, the US, and India face significant investment needs, risking stranded assets worth up to US$165–225 billion by mid-century under low CDR compared to high CDR. Regions heavily dependent on coal, such as China and India, face greater stranding costs, while gas-dependent regions like the Middle East and Russia have relatively lower costs. Global mitigation efforts with limited CDR require a 15% reduction in committed emissions compared to high-CDR scenarios, with the most pronounced reduction of 65% anticipated for India.
Herbal Teat Dip preparation is helpful in reducing the mastitis-causing pathogens in Rathi Cattle
Authors: Sharma Akansha , Arora Rajni , Nehra Rajesh , Manzoor Tahir
Published: September 2024

Mastitis remains a significant challenge in the dairy industry, leading to substantial economic losses due to antibiotic-resistant pathogens and antimicrobial residues in milk. This study focuses on sub-clinical mastitis, a hidden threat to dairy cattle productivity. It evaluated the effectiveness of a post-milking herbal teat dip combined with oral trisodium citrate supplementation in improving milk quality and reducing bacterial counts. Twenty-four lactating Rathi cows were divided into four groups, with treatments including a herbal teat dip containing aloe vera, turmeric, castor oil, and lemon. Results showed significant reductions in Staphylococcus and Streptococcus colonies, especially in the combined treatment group. These findings suggest that herbal teat dips and trisodium citrate can effectively combat sub-clinical mastitis, enhancing milk quality and reducing antibiotic use.
Hexokinase-I directly binds to a charged membrane-buried glutamate of mitochondrial VDAC1 and VDAC2
Authors: Holthuis Joost , Bieker Sebastian , Timme Michael , Woge Nils , Hassan Dina , Brown Chelsea , Marrink Siewert , Melo Manuel
Published: September 2024

Binding of hexokinase HKI to mitochondrial voltage-dependent anion channels (VDACs) has far-reaching physiological implications. However, the structural basis of this interaction is unclear. Combining computer simulations with experiments in cells, we here show that complex assembly relies on intimate contacts between the N-terminal alpha-helix of HKI and a charged membrane-buried glutamate on the outer wall of VDAC1 and VDAC2. Protonation of this residue blocks complex formation in silico while acidification of the cytosol causes a reversable release of HKI from mitochondria. Membrane insertion of HKI occurs adjacent to the bilayer-facing glutamate where a pair of polar channel residues mediates a marked thinning of the cytoplasmic leaflet. Disrupting the membrane thinning capacity of VDAC1 dramatically impairs its ability to bind HKI in silico and in cells. Our data reveal key topological and mechanistic insights into HKI-VDAC complex assembly that may benefit the development of therapeutics to counter pathogenic imbalances in this process.
Optimizing Student Outcomes: The Role of Blockchain in Academic Performance Management
Authors: Batra Iti
Published: September 2024

The integration of blockchain technology in academic performance management has the potential to significantly improve data security, transparency, and efficiency in educational institutions. This paper examines the impact of blockchain on managing academic records, emphasizing its role in reducing data security incidents, cutting administrative costs, and enhancing time efficiency. For instance, institutions that implemented blockchain saw an 83% reduction in data security incidents and a 40% decrease in administrative costs. Additionally, the time required for transcript verification dropped from an average of 5 days to instant verification, resulting in a 100% improvement in efficiency. Student satisfaction also rose by 25%, with accuracy in academic records improving from 95% to 99.9%. These findings suggest that blockchain technology can create a more secure, efficient, and student-centered academic environment, optimizing student outcomes and institutional operations.
Fiber optic characterization on the development law of water conducting fracture zones: An Experiment Study
Authors: Hu Tao , Song Chunhua , Che Jiancheng , Han Kaiqiang , Huo Taihu , Hu Tongxu , Li Bo
Published: September 2024

To prevent coal mine disasters, it is not only necessary to predict the height of Water Conducting Fracture Zones (WCFZ), but also to grasp the development law of the WCFZ in time and space. Therefore, taking a working face as background, a similar simulation experiment was carried out using fiber optic sensing. Both five vertical optical fibers were evenly laid between the open-off cut and the stopping line, and four horizontal optical fibers with different heights were laid in the experiment model to characterize the spatiotemporal development of the WCFZ by the strain distribution variation. The results showed the optical fibers strain varies in a boss curve, the upper boundary of the boss in each vertical optical fiber keeps moving upwards while the right boundary of each horizontal fiber continuously shifts to the right, WCFZ presents an unequal trapezoidal shape development process. In this experiment, the height of the caving zone and WCFZ are 25.77m and 90.27m, the initial and final caving angle are 63°and 47.75°respectively. These results are consistence with those of Close-Range Photogrammetry and empirical formula. So, it is feasible to characterize WCFZ development by the horizontal and vertical optical fibers strain.
The epidemiological transition of years of life lost due to early death from common events in the northeast of Iran
Authors: Esmaeilzadeh Nayereh , Bajestani Majid Jafari Nejad , Ghorbanzadeh HamidReza , Abdollahzadeh Hasan , Mohajeri Aazam
Published: September 2024

Aims: To measure the impact of the COVID-19 outbreak on deaths and health systems by calculating Years of life lost (YLL)
Methods: The YLL from 2018-2022 for five common causes of mortality in subgroups of sex and age in northeast Iran was calculated based on WHO methods.
Results: YLL for men increased from 188006 years of life in 2018 to 268106 in 2022, and from 147750 to 214296 in women. Women's YLL was higher in the first year of the outbreak (2020), but in the second year, men's mortality was approximately 28 years sooner than expected and women's mortality was 10 years sooner in the first and 26 years sooner in the second year. In general, aging people (≥75 years old) were more vulnerable two years ago, especially women. Two years ago, the YLL for men aged 30-60 increased, while the YLL for women aged 40-60 increased. Cancer or neoplasm has a regular YLL (YLL=9), but infectious or parasitic diseases have increasingly become life-giving (YLL = 1.4 in 2018 to 25.7 in 2022). The first year of the outback saw a drastic reduction in respiratory disease deaths (YLL in 2021 = 3.8 compared to more than 5 in other years) due to a neglect of respiratory diseases.
Conclusions: A rise in YLL could be caused by conditions that require high levels of care but for which effective treatments remain elusive, potentially increasing healthcare costs.
Biomimetic intelligent nanoplatform with cascade amplification effect for tumor synergy therapy
Authors: Wang Ying , Ji Qing , Yan Chao , Ji Pang
Published: September 2024

Tumor heterogeneity, immune-suppressive microenvironment and the precise killing of tumor cells by drugs are important factors affecting tumor treatment. In this study, an environment-responsive therapeutic nanoplatform based on metal-organic frameworks (FM@IQ/PST&ZIF-8/DOX) is developed. Under near-infrared (NIR) irradiation, it realizes the combined treatment of photothermal/immunotherapy/chemotherapy, compensating for the deficiencies of each single treatment and effectively achieving the cascade effect of tumor treatment. When it enters the blood circulation, the surface-modified erythrocyte cell membrane can disguise itself, effectively avoiding its elimination by body immune system. Moreover, the surface-modified folic acid molecules can specific binding with the folic acid receptors on the surface of tumor cells, increasing the uptake of tumor cells to them and thereby promoting its accumulation in tumor tissues. Under NIR irradiation, it induces apoptosis of tumor cells and releases tumor-associated antigen, effectively solving the problem of poor therapeutic effect caused by tumor heterogeneity. Subsequently, the slightly acidic tumor microenvironment can cause the framework of FM@IQ/PST&ZIF-8/DOX to collapse, achieving the precise release of imiquimod and doxorubicin. In this therapeutic platform, imiquimod, as a small molecule immune modulator, can effectively improve the immunosuppressive microenvironment, stimulate the body's anti-tumor immune response and inhibit the recurrence and metastasis of tumors. Therefore, the novel FM@IQ/PST&ZIF-8/DOX drug delivery system designed in this research can not only achieve controllable and precise drug release, but also improve the immunosuppressive tumor microenvironment. It is expected to become a promising new strategy for tumor treatment and provide corresponding inspiration for the later research and development of environment-responsive drugs.
Fear of Violence and Brain Drain Analysis among Healthcare Workers in Turkey
Authors: Mutlu Hatice , Bozkurt Gözde , Öngel Gökten
Published: September 2024

Background: This study investigates the relationship between brain drain intention and exposure to violence among healthcare professionals in Turkey. It aims to explore how healthcare professionals' attitudes towards brain drain are influenced by their fear of violence, education level, professional experience, and income.
Methods: A cross-sectional study design was employed, utilizing a quantile regression model to analyze the variation in brain drain attitudes across different percentiles. The model specifically examines how fear of violence affects these attitudes at various levels.
Results: The analysis reveals that the intention to engage in brain drain increases with higher levels of education and professional experience. Conversely, a high fear of violence is associated with a reduced tendency to emigrate. Additionally, the findings indicate that as income increases, attitude scores towards brain drain decrease.
Conclusions: The study underscores the importance of factors such as fear of violence, income level, and professional experience in shaping healthcare professionals' decisions regarding brain drain. These findings contribute to a deeper understanding of the dynamics influencing brain drain. Future research could further investigate these variables, providing valuable insights for policymakers to develop strategies to prevent or manage brain drain, particularly by examining the impact of employment and security policies on individuals' decisions to stay or leave.
Design and dispensing volume estimation of a single piezo-driven dispenser with rigid-flexible combined transmission mechanism
Authors: Wu Min , Zheng Jun-Jie , Zhao Run-Mao , Chen Jian-Neng , Wang Qi-Cheng , Wei Yi-Kun , Pan Shao-Fei
Published: September 2024

To solve the problems of entire replacement due to fatigue of the flexible part, the preload structure is easy to loosen or the preloading force cannot be adjusted, and the volume of adhesive droplets is difficult to estimate. A rigid-flexible combined mechanism with a unilateral preloading feature was introduced, and a droplet volume estimation method was proposed. Firstly, the principle of the single piezo-driven dispenser was analyzed, a static model of the displacement transmission mechanism was established, and the transmission ratio was designed. Secondly, based on the limiting method and the curtain area assumption, a linearized dispensing volume estimation model was proposed, then the fluid simulation model was established and the localized high-pressure of the chamber was simulated to verify the theoretical model. Lastly, a dispenser prototype was manufactured and tested. The results show that the designed dispenser worked stably, with a droplet consistency of diameter within 4.22%. The relative error average (REA) of localized high pressure between the simulation and theory was within 6.5%, and the trend of the measured droplet volume is consistent with the theory under different control parameters, which has a REA of within 5.3%, verifying the feasibility of the proposed droplet volume estimation model. When the dispensing frequency reached 400 Hz, the minimum diameter and volume were 0.43 mm and 0.092 ul, respectively. Experiments show that the designed structure and theoretical model are reliable.
The influence of surface-groundwater interactions on nutrient dynamics in urban in-channel treatment systems
Authors: Silveira Fabio C. , Cochrane Thomas A. , Bello-Mendoza Ricardo , Charters Frances
Published: September 2024

In-channel water treatment systems remove excess nutrients through biological, chemical, and physical processes associated with the hyporheic zone. However, the impact of surface and groundwater interactions on these treatment processes is poorly understood. This research aims to assess the influence of varying groundwater conditions (neutral, drainage, and seepage) and different bed sediment hydraulic conductivities on nitrogen and phosphorus dynamics in in-channel treatment systems. A flume containing bed sediment was used to study changes in surface water quality under different groundwater and bed sediment conditions. Results show that groundwater interactions influence nutrient concentrations in the surface water. An elevation in dissolved reactive phosphorus and ammoniacal nitrogen and a decrease in nitrate concentrations in the surface water under seepage groundwater conditions was evident. In addition, low hydraulic conductivity sediment led to greater changes in nutrients concentration while high hydraulic conductivity sediment led to greater variations in pH and Eh values. Water-saturated bed sediment promoted a reduction of nitrate concentrations in the surface water. The findings could assist the design and monitoring of in-channel treatment systems where groundwater and surface water interact.
A Prototype Modeling of a Smart Agriculture Monitoring System using IOT Based Drones for Spraying Pesticides
Authors: Karmakar Rahul , Paul Tanaya , Mandal Aditi
Published: September 2024

Due to the health complications arising from the use of pesticides and insecticides, a considerable number of farmers in the agricultural sector are facing significant health challenges. The conventional practice of manually applying pesticides to crop fields through traditional irrigation systems has adverse effects on health. An optimistic alternative to this manual approach involves the integration of drones for pesticide application. This substitution not only lessens the physical burden on farmers but also accelerates task completion, as drones can efficiently carry and spray insecticides across the entire farm. The two indispensable agricultural processes crucial for achieving optimal crop production include fertilizer application and pesticide use. Farmers can easily navigate the user-friendly design of this application, enhancing their ability to carry out agricultural tasks with efficiency. A quadcopter, commonly known as a drone, is employed for agricultural purposes to uniformly distribute pesticides across a field, thereby significantly reducing the labor required by farmers. Through an Android app, the farmer gains control over the drone, establishing a seamless connection with the device via the drone's Wi-Fi module. The drone is capable of precisely navigating the farmer's land, efficiently spraying pesticides across the entire area, regardless of crop variety or field shape. Addressing the need for a comprehensive model to enhance yields, especially in large irrigation areas with diverse crops, seasons, and influencing factors, a formal model of a drone-based smart irrigation system prototype is presented in this study. The developed model utilizes the Event-B methodology, and its validity is verified through the support of the RODIN tool. This approach ensures a robust and reliable foundation for the implementation of an advanced agricultural irrigation system, taking into account various parameters that contribute to successful and efficient crop management.
Effects of circuit resistance training on serum myokine METRNL, cytokines, insulin resistance, body composition, and lipid profile in overweight participants: A 6-week intervention study
Authors: Alizadeh Hamid , Safarzade Alireza
Published: September 2024

Objectives: This study investigated the effects of circuit resistance training (CRT) on Meteorin-like protein (METRNL), interleukin-4 (IL-4), interleukin-13 (IL-13), and metabolic health markers in overweight individuals.
Methods: Thirty overweight male university students (BMI 25-30 kg/m²) were randomly assigned to a 6-week CRT intervention group (n=15) and a control group (n=15). The CRT program comprised three weekly 45-minute sessions at 60-70% of one-repetition maximum. Serum METRNL, IL-4, IL-13, insulin resistance index, body composition, and lipid profile were measured pre-and post-intervention.
Results: The CRT group showed significant improvements compared to controls. Body mass index and body fat percentage decreased, while serum METRNL, IL-4, and IL-13 levels increased significantly (p<0.05). Metabolic health markers improved, with reductions in fasting blood glucose, fasting insulin, HOMA-IR, total cholesterol, triglycerides, and LDL-C, and increased HDL-C (p<0.05). Lean body mass remained unchanged between groups.
Conclusions: CRT effectively enhances METRNL secretion, potentially contributing to improved immune and metabolic functions in overweight individuals. This suggests its potential as a therapeutic strategy for managing obesity-related immunometabolic disorders, warranting further investigation.
Multi-channel Correlated Diffusion for Text-Driven Artistic Style Transfer
Authors: Jiang Guoquan , Wang Canyu , Huo Zhanqiang , Xu Huan
Published: September 2024

Text-driven image style transfer methods offer users intuitive control over artistic style, bypassing the need for reference style images. However, traditional approaches face challenges in maintaining content structure and achieving realistic stylization. In this paper, we present a novel multi-channel correlated diffusion model for text-driven artistic style transfer. By leveraging the CLIP model to guide the generation of learnable noise and introducing multi-channel correlation diffusion, along with refining the channels to filter out redundant information produced by the multi-channel calculation, we overcome the disruptive effect of noise on image texture during diffusion. Furthermore, we design a threshold-constrained contrastive balance text-image matching loss to ensure a strong correlation between textual descriptions and stylized images. Experimental results demonstrate that our method outperforms state-of-the-art models, achieving outstanding image stylization while maintaining content structure and adhering closely to text style descriptions. Quantitative and qualitative evaluations confirm the effectiveness of our approach. The relevant code is available at https://github.com/shehuiyao-a11y/mccstyler.
Larval habitat diversity, physicochemical characterization and their effect on the density of larval malaria vectors in the city of Accra, Ghana
Authors: Sabtiu Abdul Rahim Mohammed , Hinne Isaac Amankona , Sr Isaac Kwame , Doe Richard Tettey , Attah Simon Kwaku , Aboagye-Antwi Fred , Afrane Yaw Asare
Published: September 2024

Background
Malaria is more prevalent in rural areas due to fewer mosquito breeding habitats in urban settings. However, urban factors such as irrigated farming, open sewers, and discarded containers create mosquito breeding sites. This study investigates the diversity and distribution of larval habitats and the impact of physicochemical characteristics on the presence and density of Anopheles gambiae s.l. larvae in Accra, Ghana.
Methods
Larval surveys and collections were conducted at fifteen locations in Accra, divided into five categories: Irrigated Urban Farming (IUF), Lower Socioeconomic Status (LS), Middle Socioeconomic Status (MS), High Socioeconomic Status (HS), and Peri-urban (PU) areas. Physicochemical parameters were measured, and species identification was performed using morphological and molecular methods.
Results
A total of 727 breeding habitats were identified, with 65.34% (475/727) positive for Anopheles larvae. Drainage ditches were the most common habitat type (48.21%, 229/475). The highest abundance of An. gambiae s.l. was found in IUF sites (6,244/22,919), especially during the rainy season (77.01%, 17,650/22,919; R² = 3.46, P = 0.000). Polluted habitats, including household effluents, had higher ammonium levels (3.4 mg/L NH₄-N) compared to unpolluted ones (1.3 mg/L NH₄-N). Other distinguishing parameters included dissolved oxygen (34% vs 52.9%), conductivity (5106 µS/cm vs 2049 µS/cm), and total dissolved solids (3181 mg/L vs 1255 mg/L). The predominant malaria vector was An. coluzzii (54.4%, 368/677). Additionally, the invasive An. stephensi, previously unreported in Ghana, was detected.
Conclusion
Malaria vectors breed in diverse and often polluted urban habitats, with high larval densities in urban agricultural areas. The detection of the invasive An. stephensi highlights the need for continuous monitoring and vector control strategies in urban settings.
Humid heatwaves are controlled by daily rainfall variability
Authors: Jackson Lawrence , Birch Cathryn , Chagnaud Guillaume , Marsham John , Taylor Christopher
Published: September 2024

Humid heatwaves are a growing risk to human and animal health, especially in tropical regions. While there is established research on dry-bulb temperature heatwaves, greater understanding of the meteorological drivers is urgently needed. In this study, we find that recent rainfall is a key control on the occurrence of humid heatwaves and its effect is regulated by the energy- or moisture-limited state of the land surface. In moisture-limited environments, heatwaves are likely during, or immediately after, enhanced rainfall. In energy-limited environments, heatwaves are likely after suppression of rainfall for two days or longer. The nature of the threat to health from heat stress varies by environment. It depends on local adaptation to temperature or humidity extremes, as well as vulnerability to absolute or anomalous extremes. Adaptation and early warning will benefit from this new understanding of humid heatwave drivers, which shows the possibility of predicting events using satellite-derived rainfall and surface moisture data.
Prevalence and socio-demographic aspect of gender-based violence at the Zinder holistic care centre (Niger) : A cross-sectional study
Authors: Salifou Zalika Lankoande , Diaouga Hamidou Soumana , Garba Souleymane Oumarou , Salissou Z , Yacouba Hassane , Nassirou Souley Aboua , Garba Rahamatou Madeleine , Nayama Madi
Published: September 2024

Background: Gender-based violence is an important public health problem worldwide. The aim of this study was to describe the prevalence, the socio-demographic profile of patients (survivors and perpetrators) and the different types of gender-based violence treated at the Zinder holistic care centre in the Republic of Niger.
Methods: This was a descriptive cross-sectional study of cases of gender-based violence recorded and managed at the holistic gender-based violence management centre in Zinder (Niger) over the period from 1 January 2022 to 31 December 2023. The data collected were analysed using EPI infos version 7.1 software.
Results: During the study period, 515 cases of gender-based violence were recorded. Most of the victims were women and girls (95.15%). Minors accounted for 42.28% of cases. The victims were aged 18 and over in 57.67% (297 cases). Single people accounted for 39.22% of cases. Students accounted for 41.36% of cases. As regards the perpetrators of gender-based violence, men accounted for almost all the cases (95.53%). In 45.44% of cases it was the sexual partner, and in 36.12% of cases the assault took place in the victim's home. Five types of gender-based violence were observed: physical violence (121 cases, 23.5%), denial of resources, opportunities or services (148 cases, 28%), rape (117 cases, 22.7%), sexual abuse (64 cases, 12.4%), forced marriage (42 cases, 8%) and psychological/emotional abuse (28 cases, 5.4%).
Conclusion: Gender-based violence is common in Niger. The victims were young women, pupils or students, single and unemployed. Efforts still need to be made to increase the reporting of cases of GBV, involve community leaders and provide optimal medical, legal and socio-professional care.
Effects of nursing care delivery models on nurses’ fatigue: a cross-sectional study
Authors: Kisanuki Naomi , Oriyama Sanae
Published: September 2024

A new nursing care delivery model has been developed in Japan in which all nurses, including experienced nurses, work in pairs to provide daily nursing care for multiple patients. This study aimed to confirm the effectiveness of the paired system by comparing physical changes and mental fatigue before and after work with the conventional system in which one nurse is responsible for several patients. Physical and mental fatigue levels were measured before and after for 675 nurses working at two hospitals with >400 beds. Repeated measures of two-way analysis of variance for changes over time before and after work revealed no interaction. In the paired system, self-negativity was significantly decreased after than before work. This is because, in the paired system, two workers always communicate and consult with each other while performing their work; thus, emotional stress may less accumulate. The system remains not fully established because it has only been implemented for a short time. Strengthening pair relationships was considered an innovative model.
Identification and in silico analysis of phytochemicals from Phyla nodiflora (l.): Potential bioactive compounds for targeted therapy
Authors: Balasubramanian Rajagopal , Seenivasan Prasanna , AU Thangavelu
Published: September 2024

The increasing demand for safer, more sustainable alternatives to chemical-based medicines has prompted significant interest in plant-derived bioactive compounds, which are known to possess a wide range of therapeutic properties. Among these, Phyla nodiflora (L.), a medicinal plant used in traditional medicine, has garnered attention due to its potential for treating various ailments. However, a comprehensive understanding of the bioactive compounds in P. nodiflora and their mechanisms of action is lacking. In this backdrop, the present study aims to explore the therapeutic potential of phytochemicals derived from hexane and methanolic leaf extract of P. nodiflora. Through GC-MS analysis, we identified 50 distinct chemicals, among these the predominant 10 bioactive compounds were selected for further investigation based on their known pharmacological activities and subjected to molecular docking against protein targets: Protein Tyrosine Phosphatase 1B, Androgen Receptor, Cyclin A, and NKCC1. The results highlight n-Hexadecanoic acid, stigmasterol, and beta-sitosterol as potent candidates for drug development with promising therapeutic potential for diabetes, alopecia, cancer, and anti-diuresis. These findings provide valuable insights into the medicinal value of P. nodiflora and open avenues for further research, including in vitro and in vivo studies, to validate the efficacy of these compounds. The results also underscore the importance of plant-based drug discovery efforts in developing novel treatments for non-communicable diseases, thus contributing to the growing body of research in ethnopharmacology and natural product chemistry.
Assessing biosocial vectors in water contamination, the incidence of water-borne illnesses, and insecurity in Kathmandu, Nepal
Authors: Elder Laura , Funfrock Julie , Castro Emily , Lamichhane-Khadka Reena
Published: September 2024

In this study, we use water quality tests, epidemiological data, and ethnographic interviews gathered in Kathmandu in 2017 to provide an interdisciplinary analysis of water insecurity, illness, and targeted responses. Our findings fit the pattern of the past 20 years: the concentration of coliform bacteria across water sources remains unsafe. Our epidemiological data documents high rates of water-borne infectious diseases consistent with fecal contamination of water sources. Our ethnographic interviews suggest that social marginalization, poverty, and dislocation are major drivers in the incidence of illness. Evaluating some of the collective responses to water insecurity and contamination, we argue that effectively addressing water pollution, scarcity, and health outcomes in Kathmandu requires redirecting the focus of programs and the primary methods of implementation. Instead of large-scale top-down infrastructural interventions such as the Melamchi Water Supply Project, programs should target women's leadership in and subsidize funding for small-scale, community-managed interventions.