Data Record Research Articles

An Overview about FPT Industrial Telematic Service for Monitoring and Diagnostic purposes. First approaches to Signal Logger Data from Heavy-Duty Commercial Vehicles

Abstract One of several services of FPT Industrial Customer Service team is Monitoring&Diagnostic of engines through telematic. FPT Industrial S.p.A. is an Italian brand of Iveco Group dedicated to the design, production, and sale of powertrains and solutions for on- and off-road applications. The focus of this study is on heavy-duty on-road vehicles. They are part of an Iveco vehicle fleet powered by FPT engines equipped with telematic devices. The telematic data have been used for energy efficiency and driving style relations and analysis; after every key-on event the acquisition and transmission of data start. An on-board device, called Telematics Mobile Diagnostic (TMD), is responsible for sending this data flow from Dongle, connected to the OBD port, to control room with a frequency of 1 Hz. The large amount of data will be useful for interesting analysis of drivers’ real use: an investigation about their behaviors and missions has been carried out. Therefore, the main purpose of the work is to keep track of vehicle efficiency, energy spent to distance travelled ratio (kWh/km). Hence, a correlation between the dynamicity of the drive, through Driving Scores and Pearson’s coefficient, and consumption has been proposed. The outcome is a characterization of the missions with few indexes, inferred by telematic data, without consulting any plot.

ГІБРИДНИЙ МЕТОД АНАЛІЗУ ТА ІДЕНТИФІКАЦІЇ ШКІДЛИВОГО DOH-ТРАФІКУ

This study addresses the challenges associated with detecting DNS over HTTPS (DoH) traffic, a relatively new protocol that has not been extensively researched. The detection methods discussed include TLS inspection, application logging, and open-source tools such as Zeek and RITA. TLS inspection, which involves decrypting and analyzing traffic, is the most intrusive and requires full control over the network and client configurations. Application logging, such as that available in Mozilla Firefox, necessitates administrative control over client systems, which may be impractical. Zeek analyzes network logs to identify domains accessed without regular DNS queries, while JA3 fingerprints and RITA focus on detecting malicious DoH traffic by analyzing TLS handshake parameters and beacon-like activities, respectively. Additionally, maintaining up-to-date blacklists of IP addresses and SNI values can help identify DoH traffic but faces scalability and evasion challenges. The study highlights that no current solution is entirely feasible, with many requiring excessive administrative overhead or failing to scale effectively. A hybrid approach using machine learning models and traffic analysis, as illustrated by the CIRA-CIC-DoHBrw-2020 dataset, is proposed for more effective detection of malicious DoH traffic. This approach involves the architecture of a two-stage DoH traffic identification system is presented, consisting of three subsystems: traffic, training and evaluation, and identification. They operate sequentially, with the system's function being traffic identification, training, testing, and information processing within the DoH protocol. The next step is process of cross-validation, which involves training a machine learning model K times, with each iteration using a different fold as the validation set, while the remaining folds serve as the training set. The aim of this work: Development and implementation a DoH traffic identification system, which, unlike existing solutions, is based on a hybrid approach to identifying malicious traffic using open tools for detecting encrypted DNS traffic and specialized machine learning models.

Determination of Average Water Demand and Diurnal Consumption Pattern for a Multifamily Apartment Complex in Peshawar

Abstract: Accurately estimating and understanding domestic water demand and consumption patterns is essential for the efficient planning and management of drinking water supply systems. Traditional methods for estimating water demand are labor-intensive and often rely on assumptions. To overcome these limitations, this study employed a novel approach using highprecision data loggers to monitor water levels continuously in rooftop tanks at 5-minute intervals within a residential apartment complex in Peshawar, Pakistan. The findings indicate that per capita water consumption varies between 97 and 209 liters per capita per day (lpcd), with an average consumption of 173 lpcd. This methodology offers enhanced accuracy in quantifying water usage, providing a robust alternative to conventional estimation techniques.

Long‐term monitoring of water table and saltwater intrusion dynamics through time‐lapse transient electromagnetic

AbstractUnderstanding hydrogeological processes often requires continuous measurements, which in many cases are not cost‐efficient. Time‐lapse geophysical studies are invaluable for investigating dynamic subsurface processes. They offer several advantages over traditional borehole‐based monitoring methods, such as being cost‐efficient and non‐intrusive. However, to be effective as an early warning tool, these studies must provide real‐time information on the processes. This is often not feasible with traditional geophysical methods, which typically do not offer real‐time monitoring. In this study, we present a windowed inversion approach for time‐lapse transient electromagnetic (TEM) monitoring. The advantages of this approach include: (i) immediate and continuous results as each time‐step dataset is acquired; (ii) no limitations on the size of the monitoring period or dataset; and (iii) the use of model information from previous inversion results for robust and continuous outcomes. The results from a synthetic study are followed by two field case studies, demonstrating the advantages of the windowed inversion compared to the inversion of the full dataset. We monitored the water table dynamics of a shallow unconfined aquifer over 8 months and the saltwater intrusion in a confined aquifer over 10 months using a monitoring TEM (mTEM) system while collecting nearly continuous daily measurements. With the windowed approach, the water table dynamics was recovered with an accuracy of 10 cm, and the changes in salinity were tracked with results comparable to those of an EC data logger.

Assessment of Bleaching Stress Vulnerability of Lakshadweep Islands using Google Earth Engine (GEE)

Coral reefs, among the Earth’s most diverse and valuable ecosystems, face unprecedented challenges due to climate change. Coral bleaching is a phenomenon wherein corals lose their symbiotic zooxanthellae owing to various stressors, leading to a whitening effect of the coral tissues. In recent decades, climate change has intensified coral bleaching events. Multiple stressors, including elevated Sea Surface Temperature (SST), extreme irradiance levels, and various biotic and abiotic factors trigger bleaching events. Coral bleaching is primarily driven by thermal stress caused by elevated SSTs. Climate change has worsened bleaching’s frequency and intensity. Global bleaching events are often linked to planetary ocean-atmospheric circulation processes such as El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). This study focused on assessing the vulnerability of coral reefs in the Lakshadweep region of India from 2016 to 2023 using National Oceanic and Atmospheric Administration’s Climate Data Record Optimum Interpolation Sea Surface Temperature (NOAA CDR OISST) daily data. GOOGLE EARTH ENGINE (GEE) is a cloud computing platform which is used to collect and generate the base data for this study. The vulnerability assessment utilized two bleaching indices: SST anomaly and Degree Heating Week (DHW). Analysis of DHW data reveals that 2020 experienced the highest SST anomaly residence time due to IOD event of 2019, as compared to 2016 and 2023 which are known El Niño years. All Lakshadweep islands exhibited vulnerability, although in varying degrees across different areas. Based on the magnitude, intensity, and frequency of bleaching stress, the islands are categorized into different categories of vulnerability. This study identifies Baliyapaniyam, Cheriyam-Kalpeni and Suhelipar reefs as very highly vulnerable reefs in Lakshadweep. This study highlights the urgent need for monitoring and management measures to mitigate the impacts of climate change on coral reef ecosystems using spatial vulnerability patterns.

Near-real-time atmospheric and oceanic science products of Himawari-8 and Himawari-9 geostationary satellites over the South China Sea

Abstract. The initial release of near-real-time (NRT) atmospheric and oceanic science products from Japanese Himawari-8 and Himawari-9 (H8/9) geostationary (GEO) satellites over the South China Sea (SCS) was unveiled in 2024. The primary objective behind crafting these NRT H8/9 satellite products is to facilitate weather and marine environment monitoring, enhance maritime security, and aid ocean navigation, among other purposes. As part of this investigation, a novel NRT data processing system was devised to generate a variety of regional H8/9 GEO satellite science products within a resolution of 10 min and a gridded resolution of 0.05° × 0.05° from 3 November 2022 to the present. This algorithm system was built upon the preceding Fengyun (FY) geostationary satellite algorithm test bed (FYGAT), which was the prototype of the FY-4 GEO meteorological satellite science product operational processing system. These regional H8/9 GEO satellite science products encompass a range of crucial data such as cloud mask, fraction, height, phase, optical, and microphysical properties; layered precipitable water; and sea surface temperature. We subjected these products to rigorous evaluations against high-quality analogous satellite products and reanalysis data spanning 1 year in 2023. The validations underscore a strong consistency between the H8/9 GEO satellite atmospheric and oceanic science products over the SCS and the referenced products. Nevertheless, slight discrepancies in these satellite science products were identified, primarily stemming from variations in sensor/dataset characteristics, retrieval algorithms, and geometric conditions. These outcomes demonstrate the suitability of the first edition of NRT atmospheric and oceanic science products of H8/9 satellites over the SCS in supporting the intended quantitative applications. This NRT GEO satellite data record is publicly accessible through the File Transfer Protocol (FTP) provided by the Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) in China. Free access to the dataset is possible via https://doi.org/10.6084/m9.figshare.25015853 (Liu et al., 2024).

Intelligence data acquisition based on embedded system in Chinese cuisine cooker (CCICR V1.0)

The Chinese cooking process, intricate and diverse, encompasses a wide range of dishes, generating substantial data that often poses significant challenges for automation. To address these challenges, this paper introduces a versatile, highly reliable, user-friendly, and intelligent data recorder specifically designed for Chinese cuisine-the Chinese Cuisine Intelligent Cooker Recorder-V1.0 (CCICR-V1.0). This device is intended to record data generated during the cooking process and provide essential support for intelligent cooking robot systems. The core of CCICR-V1.0 is a STM32 microcontroller, equipped with sensors that monitor temperature, pressure, and attitude. These sensors facilitate the intelligent collection of data related to dishes, ingredients, and the movements of cookware throughout the cooking process. To ensure efficient data acquisition and storage, CCICR-V1.0 employs a multi-task data buffering storage method that effectively allocates CPU resources. NAND Flash is used as the storage medium, guaranteeing secure storage, management, and preservation of high-frequency, multi-channel data. Experimental results demonstrate the effectiveness of CCICR-V1.0 in achieving multi-channel, high-frequency data acquisition and storage in complex environments. This leads to an increase in automation efficiency of 89.9%. The weighing module demonstrates a maximum relative error of only 0.288%, while the attitude sensor experiment shows an attitude information error of just 0.22°C. Furthermore, the non-contact infrared temperature measurement module exhibits impressive performance with a maximum absolute error of 0.258∘C\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ C$$\\end{document} and a maximum relative error of 0.88%. Notably, this measurement module has achieved a cost reduction of approximately 91.7% and an accuracy improvement of around 40%. Additionally, the response time of CCICR-V1.0 is less than 3 ms. With its ability to effectively capture data related to Chinese cooking, CCICR-V1.0 holds commercial value for widespread adoption and application in the field of intelligent cooking.

Physical Heat Cycle Measurement of Resistance Spot Welding

Resistance spot welding (RSW) is still the ideal joining method in the automotive industry. Mostly steel sheets are used in the car body, so overlap and layering are required for welding or riveting, as spot welding provides simultaneous clamping force with interfacial welding to ensure the required strength and quality. A fundamental understanding of heating and cooling rates in thermal distributions is essential for predicting microstructure formation in the weld and the heat-affected zones (HAZ) of RSW joints. The ability to measure the heat cycle in the RSW process can be valuable in weld control and welding parameter optimization. RSW parameters can be optimized through tensile shear tests and microscopic investigations. Heat cycle measurement (HCM) demonstrates the welding consequences in terms of the change in mechanical properties and microstructural formations. The accuracy of cooling rate measurements including t8/5 cooling time is very important to predict the microstructural evolution in the HAZ, however, the thermocouple measurement raises numerous challenges due to the high temperature gradient and small weld and HAZ size. During our investigations heat cycle measurement has been conducted experimentally by a K-type thermocouple. The data logger is connected to the output of the thermocouple for recording the voltage to measure the temperature distributions as a function of both time and position during the welding process. Measurement results of 1 mm thick martensitic MS1400 steel overlapped RSW joints are discussed, and the HCM curve of heating and cooling rates of the spot-welding process is presented. The heat cycle during RSW was measured with two different welding parameter combinations. In addition to welding current, welding time, and electrode force, pulsation has shown disparate curves. Numerous experiments have been attempted to measure the heat cycle in HAZ sub-zones due to the difficulty of positioning the thermocouple accurately, uppercritical HAZ, intercritical HAZ, and subcritical HAZ were investigated and measured in both welding parameter combinations. Difficulties were encountered in the experimental work as a result of the instantaneous welding time and the vibration resulting from the passage of alternating electrical current between the two electrodes. A magnetic field is generated that affects the thermocouple measurement and appears as a noisy curve that is filtered out and smoothed. Joule heat, interfacial heat generation, and cooling effects of electrodes are also considered in the experiment.

Crack Propagation Tests for Load Sequences Developed Using Different Flight Parameters of a Trainer Aircraft

Abstract Military aircraft are subjected to highly variable and unpredictable loads due to diverse mission profiles, armament configurations, and individual piloting styles. This variability complicates the definition of precise load spectra, particularly in cases where data loss occurs due to Flight Data Recorder (FDR) malfunctions or data mishandling. This paper investigates the use of different flight parameters, such as load factor (nz ), barometric height (Hb ), and horizontal velocity (Vp ), to define load sequences for the PZL-130 “Orlik” TC-II military trainer aircraft. These sequences were then used to evaluate crack propagation using Compact Tension (CT) specimens. The results show that the incorporation of additional flight parameters improves the accuracy of crack propagation predictions when compared to direct strain measurements. This study highlights the potential of using available flight data to develop reliable load spectra for fatigue life estimation in military aircraft, even when direct load measurements are not financially feasible.

Implementasi Teknologi Blockchain Dalam Pengembangan Aplikasi Manajemen Penyaluran Bantuan Sosial Berbasis Web

The distribution of social assistance is a crucial component of the government's efforts to reducepoverty and social inequality. However, the implementation of aid programs often faces issuesrelated to transparency, data security, and the risk of misuse. Blockchain technology, with its abilityto provide a transparent and immutable record of data, offers a potential solution to address theseissues. Blockchain can increase transparency by providing a digital ledger that can be accessed byall relevant parties, without the possibility of data manipulation. The technology also allows forimmutable data logging, thus addressing data security concerns and the risk of misuse. In addition,the use of smart contracts allows for the automation of the aid distribution process in accordancewith predetermined provisions, thereby reducing errors and potential abuse. As such, blockchainoffers a potential solution to increase effectiveness and accountability in the implementation ofsocial assistance programs.

Comparison of a two-step Tempus600 hub solution single-tube vs. container-based, one-step pneumatic transport system.

Efficient and timely transportation of clinical samples is pivotal to ensure accurate diagnoses and effective patient care. During the transportation process, preservation of sample integrity is crucial to avoid pre-analytical aberrations on laboratory results. Here, we present a comparative analysis between a two-step Tempus600 hub solution single-tube and a one-step, container-based pneumatic transport system (PTS) from Airco, for the in-house transportation of blood samples. Ten blood samples from healthy volunteers were split in 10 mL collection tubes filled at full or half capacity for transportation with the two PTS (about 250 m). To compare the impact of transportation, markers of hemolysis such as lactate dehydrogenase (LDH), potassium (K+), and the hemolysis index (HI), were determined. Additionally, differences in HI in routine samples and repeated transportation was investigated. To assess and compare the mechanistic impact profiles, we recorded the acceleration profiles of the two PTS using a shock data logger. Transportation using the Tempus600 hub solution resulted in 49 and 46 % higher HI with samples filled to total or half capacity, respectively. Routine samples transported with the Tempus600 hub solution showed a higher median HI by 23 and 33 %. Additionally, shock logger analysis showed an elevated amount of shocks (6.5 fold) and shock intensities (1.8 fold). The Tempus600 hub solution caused an increased number of unreportable LDH or K+ results based on the hemolysis index. However, it was only statistically significant for LDH (p<0.01 and p<0.08)- while the comparisons for K+ were not statistically significant (p<0.28 and p<0.56).

Circadian rhythm in atrial fibrillation detected by implantable loop recorder: a post-hoc analysis of a randomized clinical trial

Abstract Introduction Previous studies suggest the existence of circadian, weekly, and seasonal rhythms in the occurrence of atrial fibrillation (AF), which may be utilized to improve the yield of screening. The heterogeneity of AF natural history also necessitates better phenotyping to overcome the challenges of identifying candidates for screening and treatment. Purpose To explore the potential circadian rhythm in AF occurrence in persons without known arrhythmia but at high risk of AF and stroke. Methods Post-hoc analysis of the LOOP study (Atrial Fibrillation Detected by Continuous Electrocardiogram Monitoring Using Implantable Loop Recorder to Prevent Stroke in High-Risk Individuals), which randomized 6004 AF naïve participants (≥70 years old with additional stroke risk factors) 1:3 to receive implantable loop recorder screening or usual care. All loop recorder data was extracted to obtain the date and time of AF episode onset, AF duration, mean and max heart rate (HR) during AF, and symptom annotations. New-onset AF episodes lasting ≥6 minutes were adjudicated, and all subsequent episodes were included in the analysis. Results A total of 41,713 AF episodes (median duration 18 (8-64) minutes) were identified among 430 participants (Table 1). The median number of episodes for each participant with AF was 21 (4-82) and the median AF burden was 0.17% (0.04%-0.83%) of time from debut to end of monitoring. The most and least frequent days of AF onset were Sunday (15.3%) and Friday (13.6%), respectively, while AF occurred slightly more often during spring (26%) than in other seasons. The median time of onset was 09:57:15 AM (05:15:30 AM – 03:33:00 PM). The most frequent time of onset was at 09:00 AM (rounded to the nearest hour), which was two times more likely than at 09:00 PM, and 22% of all episodes occurred between 08:00 and 11:00 AM (Figure 1). A total of 25,329 (61%) episodes occurred between midnight and noon (AM). Nocturnal episodes, defined as episodes with onset between 10:00 PM and 07:00 AM, occurred in 368 (86%) AF participants and constituted a median of 40% of all episodes and 37% (14%-63%) of each participant’s episodes. The median duration of nocturnal episodes was 28 (10-104) minutes compared to 14 (8-44) minutes for daytime episodes. The averaged heart rate during AF was 81 (71-96) beats per minute (BPM), while 330 (77%) participants had AF episodes with heart rates equal to or above 100 BPM, and the duration of these episodes was 50 (15-201) minutes compared to 30 (21-85) minutes for slower episodes (below 100 BPM). Conclusion A circadian pattern was observed for screening-detected AF. AF onset occurred predominantly between 08:00 and 11:00 AM, representing more than one in five episodes. Nocturnal AF occurred in most participants with AF and accounted for almost half of all episodes, while these episodes also lasted longer than daytime episodes. This may warrant future studies investigating the timing of AF screening.

Traditional and contemporary building thermal sensations prediction models in a warm-humid climate

ABSTRACT Passive ways of providing thermal comfort have been intensively researched in many nations. Despite researchers’ strenuous efforts, most studies on thermal comfort concerns are centred on continents such as Asia, America, Europe, and Africa, with a handful of studies comparing building types in the sub-Saharan area. However, none has focused on statistical models to predict the thermal sensations of occupants in traditional and modern structures during the dry season. Hence, this study investigated interior relative humidity, air temperature, and occupants’ thermal feelings in traditional and modern structures in the dry season in Okigwe, Nigeria. The data for this investigation was collected by physically measuring relative humidity and air temperature using data loggers. A longitudinal survey technique was also used to elicit answers from the residents of the selected traditional and modern structures on the thermal feeling of comfort temperature. To predict the inhabitants’ thermal sensations in the building types investigated, two statistical models were developed: ‘TSVt = 0.65 (MITt) – 13.5’ for traditional structures and ‘TSVc = 0.74 (MITc) – 16’ for modern. The comfort range and neutral temperature of ‘3.15 ≤ TSV ≤ 4.85’ 1–7 yielded 26.8°C as the neutral temperature for the occupants of traditional buildings, with the comfort ranging between 25.6°C and 28.2°C. Contemporary building occupants’ neutral temperature and comfort ranges from 25.9°C to 28.2°C. The study therefore recommended the use of the developed models by Architects, Planners, and Designers for predicting the occupants’ sensations of the building types before preliminary investigations and design sketches, as with such information, the designer possesses the necessary tools for providing buildings that are thermally comfortable for maximum comfort and minimal consumption of energy.

Effects of High Tunnel Soil Solarization on Sclerotinia sclerotiorum in the Temperate Climate of Central Kentucky.

Diseases caused by Sclerotinia spp. can affect a wide range of plants, including vegetables, with yield losses ranging from 10 to 50%. Sclerotinia diseases can be especially problematic in high tunnels where high-value vegetable crops are planted in early spring to extend the growing season, achieve earlier harvest, and bring higher profits. Fungicide applications and crop rotations are limited due to product application restrictions and constraints on time, crop resistance, and profitability. Soil solarization is a cultural management method that uses transparent polyethylene to raise soil temperatures via solar irradiation to kill pathogens, pests, and weeds. A two-year study was conducted in a Kentucky high tunnel to determine the maximum temperature potential of solarization at various soil depths at different durations during different seasons and to identify temperatures at which S. sclerotiorum sclerotia lose viability. The experiment included solarization treatments of 2, 4, and 6 weeks and a non-solarized control implemented in spring, summer, and fall. Sclerotia and temperature data loggers were buried at 5.1, 10.2, and 15.2 cm soil depths. The number of hours at which soil temperatures reached ≥ 40 °C was greatest in summer in both years, followed by fall, and then spring. The highest average daily maximum soil temperature reached was 48.9°C, which occurred during the summer 6-week solarization in Year 1. The viability of buried sclerotia was overall lower in solarized treatments compared to non-solarized treatments in both years. In general, the 2-week solarization treatment had significantly higher percent sclerotial germination than the 4-week and 6-week treatments, which were not significantly different from one another. The viability of sclerotia was progressively higher with burial depth. In both years, sclerotia germination was significantly lower in summer compared to spring and fall.

How realistic are multi-decadal reconstructions of GRACE-like total water storage anomalies?

Reconstructions allow us to extend the Gravity Recovery And Climate Experiment (GRACE) data record into the past and bridge the one-year gap between GRACE and its successor, GRACE-FO (Follow on). Reconstructed total water storage anomalies (TWSA) are obtained by identifying relations between GRACE-derived TWSA and climate variables via statistical and machine learning techniques. However, a comparative analysis of the characteristics and realism of reconstructions is missing.In this contribution, we close this gap by comparing three global reconstructions by Humphrey and Gudmundsson (2019), Li et al. (2021) and Chandanpurkar et al. (2022) mutually and against output from the Water Global Analysis and Prognosis (WaterGAP) hydrological model from 1979 onwards, against large-scale mass-change derived from geodetic satellite laser ranging (SLR) from 1992 onwards, and finally against differing GRACE and GRACE-FO solutions from 2002 onwards. The reconstructions vary regarding design and trained GRACE solution.Reconstructions recover the TWSA signal for humid climate regions but disagree for arid climate regions, which is evident on the inter-annual timescales. At seasonal and sub-seasonal timescales, the reconstructions agree surprisingly well in many regions. Our comparison against independent SLR data reveals that reconstructions (only) partially succeed in representing anomalous TWSA for areas that are influenced by significant climate modes such as El Niño-Southern Oscillation (ENSO).

Barriers and facilitators for universal gestational diabetes Mellitus screening in a low resource setting: a cross-sectional study in Sri Lanka

Gestational Diabetes Mellitus (GDM) is associated with adverse maternal and perinatal outcomes and increased risk of developing diabetes in later life. Sri Lanka adopted universal GDM screening at two time points in pregnancy (before 12 weeks and between 24 and 28 weeks) in 2014 and its utilization has not been assessed. This study assessed the utilization of GDM screening services and associated factors among antenatal mothers in Southern Sri Lanka. A cross-sectional study was carried out in a consecutive sample of 420 postpartum mothers who delivered at three major hospitals in Sri Lanka. Data were collected on socio-demographics, pregnancy, availability and utilization of screening services and logistics using an interviewer-administered questionnaire and a data record sheet. Data was analysed using SPSS software. Chi-square test and binary logistic regression was used to assess the association between variables. The coverage of first and second screening tests were 91.4% and 94.5% and timeliness were 72.4% and 59.5%, respectively. The median period of amenorrhoea at the first and second screening were 10.0 (inter-quartile range: 2.5) weeks and 28.0 (inter-quartile range: 1.5) weeks. A higher utilization was associated with higher income (OR = 3.4, 95% CI: 1.1–10.5) and planned pregnancy (OR = 4.9, 95% CI: 2.2–10.7) for the first screening test. Primiparity (OR = 0.3, 95% CI: 0.1–0.9) and proximity of the nearest laboratory (OR = 3.5, 95% CI: 1.0–12.0) were positively associated with the second screening test. The timeliness of both screening tests was associated with planned pregnancy (OR = 2.1, 95% CI: 1.1-4.0 and OR = 2.3, 95% CI: 1.1–4.5) and being non-employed during the pregnancy (OR = 2.5, 95% CI: 1.4–4.3 and OR = 2.3, 95% CI: 1.3–4.1). A high utilization of GDM screening was observed. Timeliness should be ensured through improved availability and accessibility of screening facilities.

Improved modelling of low-pressure rotor speed in commercial turbofan engines: A comprehensive analysis of machine learning approaches

Accurate engine thrust modelling offers notable opportunities for reducing fuel consumption, mitigating emission effects, managing air traffic, and optimizing the preliminary design of aircraft. This study focuses on the development of machine learning models to predict the low-pressure rotor speed (N1) parameter, which is closely related to the thrust of turbofan engines, for commercial aircraft during the cruise phase. The analysis utilizes a Flight Data Recorder (FDR) dataset from 1086 actual flights involving twin-engine, narrow-body, short-to-medium haul commercial aircraft equipped with CFM56-7B turbofan engines. To achieve accurate N1 parameter predictions, the study employs machine learning models, including Deep Learning (DL), Random Forest (RF), Gradient Boosted Machines (GBM), and Artificial Neural Networks (ANN). These models are evaluated using statistically significant indicators, demonstrating that machine learning models yield highly accurate results. Among the models tested, the DL model provides the most precise estimates of the N1 parameter. This study not only advances the understanding of engine thrust modelling through machine learning but also provides practical insights for the aerospace industry. The findings underline the potential of machine learning techniques in delivering superior prediction accuracy, which can be integrated into real-time flight management systems, ultimately contributing to more sustainable and efficient aviation operations.

Pollutant Dispersion of Aircraft Exhaust Gas during the Landing and Takeoff Cycle with Improved Gaussian Diffusion Model

Evaluating aviation emissions and examining the dispersion properties of contaminants are crucial for understanding atmospheric pollution. To assess the pollutant emissions and dispersion of aircraft during the landing and takeoff (LTO) cycle, and address air pollution surrounding the airport resulting from flight operations, this study evaluated emissions throughout the LTO phase based on Quick Access Recorder (QAR) data in conjunction with the first-order approximation method. An improved Gaussian diffusion model for mobile point sources was employed to examine the diffusion characteristics of contaminants. Additionally, CFD calculation outcomes for various exhaust velocities and wind speeds were utilized to validate the trustworthiness of the improved Gaussian model. The discussion also encompasses the influence of diffusion time, wind direction, wind speed, temperature gradient, and particle deposition on the concentration distribution of contaminants. The findings indicated that the Gaussian diffusion model aligned with the results of the CFD calculations. The diffusion distribution of contaminants around airports varies over time and is significantly influenced by atmospheric environmental factors, including wind direction, wind speed, and atmospheric stability. Specifically, a change in wind direction from 0° to 45° caused a shift of approximately 1000 m in the contaminant’s center. An increase in wind speed from 3 m/s to 5 m/s led to a decrease in concentration by about 15%. Furthermore, a transition in atmospheric stability from category ‘a’ (very unstable) to ‘f’ (very stable) resulted in a two-order-of-magnitude increase in contaminant concentrations.

Synthesis of Silver Nanoparticles and Forced Convective Heat Transfer Coefficient Measurement of Silver-Water Nanofluids at Laminar Flow

Heat management in industries and other areas is a major issue currently worldwide. Conventional heat transfer fluids like water and ethylene glycol are not very effective. Nanofluids (NFs), composed of nanoparticles (NPs) dispersed throughout a base fluid (BF), have recently been identified as promising heat management agents for various industrial and other applications. Heat transmission is one of the many uses for AgNPs–water NFs (silver NPs (AgNPs) dispersed in water). The goal of this work was to determine the AgNPs–water NFs' forced convective heat transfer coefficient (HTC) in laminar flow. Due to this, we present the results of the HTC study of AgNPs–water NFs in laminar flow in this paper. First, using AgNO3 as a precursor, a chemical reduction approach was used for facile synthesis of AgNPs in one pot at ambient temperature. Synthesized NPs were examined using ultraviolet-visible spectroscopy (UV-vis), X-ray diffraction (XRD), and transform electron microscopy (TEM) techniques. The average particle size obtained from TEM is 25 nm. The required quantity of AgNPs was added to the water to produce 0.5 and 1.0 vol% of AgNPs–water NFs. Next, zeta potential and dynamic light scattering (DLS), in addition to time-lapse observation and captured picture comparison, were used to assess the stability of the formulated NFs. To calculate the forced convective HTC of prepared NFs in laminar flow, a vertical shell and tube heat transfer apparatus and computer-based data recorder were used. According to the results, in comparison to BF, the HTC of 0.5 and 1.0 vol% NFs was 3.3 and 5 times greater, respectively which encourages the use of AgNPs–water NFs in industry and other heat management. Jagannath University Journal of Science, Volume 11, Number 1, June 2024, pp. 13−22

Pre-extension Popularization of Improved Dual Purpose Koekoek Chickens in Tahtay Maichew District Central Zone of Tigray, Ethiopia

Central zone of Tigray has potential and poultry stock. However, the productivity in terms of egg and meat is low since the majority of household depends on local chickens and rearing of their chickens through a traditional production practices. Then, the objectives of the pre-extension popularization of Koekoek breed was i) to popularize and evaluate the production performance the Koekoek breed chickens in the small holder Farmers and ii) To analyze farmers feedback towards this improved Koekoek chickens breed at smallholder farmers' management. T/maichew District, My-sie kebelle was selected based on the project financial support of Irish Aid Operational Research (OR) purposely. A total of 17 household heads willingly participated to adopt the Koekoek breeds. Data record sheet and semi-structured questionnaires were prepared to collect the required data. Then, using simple descriptive and Likert measurement level used to achieve result. The finding of the research shows that an annual average yield was found to be 204 eggs per year/ chicken. Similarly, the respondents agreed on that the chickens have well adapted, good growing ability, relatively resistance to diseases, have good scavenging ability, and productivity as well have medium eggs size and good egg and meat tasty of Koekoek chickens. The improved chickens’ breed (Koekoek) is better to be transferred to other mandate areas of Axum Agricultural Research Center. In addition, collaboration of stakeholders needs to be strengthening so that large scale demonstration community production system is going to be functional. Strengthen the human resource and institutional innovations are important point for dissemination of the improved poultry breeds to all beneficiaries of small holder farmers.