Variation In Quality Research Articles

Transcriptional profiling of mucus production in rhesus macaque endocervical cells under hormonal regulation.

Endocervical mucus production is a key regulator of fertility throughout the menstrual cycle. With cycle-dependent variability in mucus quality and quantity, cervical mucus can either facilitate or block sperm ascension into the upper female reproductive tract. This study seeks to identify genes involved in the hormonal regulation of mucus production, modification, and regulation through profiling the transcriptome of endocervical cells from the non-human primate, the rhesus macaque (Macaca mulatta). We treated differentiated primary endocervical cultures with estradiol (E2) and progesterone (P4) to mimic peri-ovulatory and luteal-phase hormonal changes. Using RNA-sequencing, we identified differential expression of gene pathways and mucus producing and modifying genes in cells treated with E2 compared to hormone-free conditions and E2 compared to E2-primed cells treated with P4. We pursued differential gene expression analysis on RNA-sequenced cells. Sequence validation was done using qPCR. Our study identified 158 genes that show significant differential expression in E2-only conditions compared to hormone-free control, and 250 genes that show significant differential expression in P4-treated conditions compared to E2-only conditions. From this list, we found hormone-induced changes in transcriptional profiles for genes across several classes of mucus production, including ion channels and enzymes involved in post-translational mucin modification that have not previously been described as hormonally regulated. Our study is the first to use an in vitro culture system to create an epithelial-cell specific transcriptome of the endocervix. As a result, our study identifies new genes and pathways altered by sex-steroids in cervical mucus production.

Dual temporal attention mechanism-based convolutional LSTM model for industrial dynamic soft sensor

Abstract Deep learning is an appropriate methodology for modeling complex industrial data in the field of soft sensors, owing to its powerful feature representation capability. Given the nonlinear and dynamic nature of the process industry, the key challenge for soft sensor technology is to effectively mine dynamic information from long sequences and accurately extract features of relevance to quality. A dual temporal attention mechanism-based convolutional long short-term memory network (DTA-ConvLSTM) under an encoder-decoder framework is proposed as a soft sensor model to acquire quality-relevant dynamic features from serial data. Considering different influences of process variables for prediction at multiple time steps and various locations, ConvLSTM and temporal self-attention mechanism are utilized as the encoder to adaptively fuse spatiotemporal features and capture long-term dynamic properties of process in order to capture the trends of industrial variables. Furthermore, a quality-driven temporal attention mechanism is employed throughout the decoding process to dynamically select relevant features to more accurately track quality changes. The encoder-decoder model meticulously analyses the interactions between process and quality variables by incorporating dual-sequence dynamic information to improve the prediction performance. The validity and superiority of the DTA-ConvLSTM model was validated on two industrial case studies of the debutanizer column and sulfur recovery unit. Compared to the traditional LSTM model, the proposed model demonstrated a substantial improvement with the accuracy R2 up to 97.3% and 94.9% and the root mean square error reducing to 0.122 and 0.022.

Spatial and seasonal assessment of surface water quality for domestic use in a semi-arid area of the Upper Kebir Sub-basin, NE Algeria

ABSTRACT The present study was conducted out in the Upper Kebir Sub-basin [North East (NE) Algeria] aiming to evaluate the status and spatial–seasonal variability of water quality for domestic purposes using hydrogeochemical parameters and water quality indices. Surface water samples were collected from selected 27 sites, in the period 2020–2021 during both the wet and dry seasons and were analysed for 22 parameters. The findings were compared with standards and the water quality indices were calculated. The analysis revealed that the basin was mainly polluted and showed significant seasonal and spatial variations in water quality, considerably influenced by climatic conditions (surface runoff) and human activities (urban sewage and agricultural activities). The results reveal significant spatio-temporal fluctuations and highlight areas likely to be affected by anthropogenic activities.

The Effect of Brand Image, Price and Product Quality on Purchasing Decisions for Iphone Products

This study is designed to examine the impact of Brand Image, Price, and Product Quality on Purchasing Decisions for iPhone products, especially in competition with other brands. The increasingly competitive condition of the cellphone market, especially with the emergence of iPhone products as a basic necessity in an ever-growing era, also affects the company's strategy for maintaining its position in the market. In addition, this study also aims to identify the most dominant factor influencing the purchase decision of iPhone products between Brand Image, Price, or Product Quality. The survey method was chosen to collect information from 96 respondents of potential iPhone product users at Universitas Pelita Bangsa, specifically from the class of 2020 students at the Faculty of Economics, Business Management Study Program. In this research, the approach applied is quantitative, using questionnaires and literature studies as data collection techniques. Data analysis was carried out through several methods, including validity test, reliability test, classical assumption test, multiple linear regression analysis, and hypothesis testing. Based on the t-test results, a calculated t-value of 2.861 with a significance level of 0.005 was obtained, indicating acceptance of the initial hypothesis. This confirms the significant and positive effect of brand image on purchasing decisions. The t-test results on the price variable produced a t-value of 8.009 with a significance level of 0.00, which indicates that the second hypothesis is accepted. This shows that price partially has a positive and significant influence on purchasing decisions. Meanwhile, the product quality variable obtained from the t-test results shows a calculated t-value of 2.022 with a significance of 0.046, stating the acceptance of the third hypothesis and indicating a positive and significant effect of product quality on purchasing decisions. Based on these findings, it can be concluded that 81.5% of purchasing decisions are influenced by a combination of brand image, price, and product quality variables, while the other 18.5% are influenced by other variables not examined in this study.

Integrated cultivation of tambaqui (Colossoma macropomum) with coriander (Coriandrum sativum L.) grown at different plant density

The present study aimed to evaluate an aquaponic bioeconomic model integrating the cultivation of tambaqui (Colossoma macropomum) with coriander (Coriandrum sativum) at different densities of 32, 72, 128, and 512 cells m−2 for 19 days. The hydroponic bed was configured on a bench with a capacity of 100 L (1.62 m-long, 0.72 m-width, and 0.1 m-depth) and was coupled to a plastic tank with the fish. The coriander seeds were irrigated for four days until germination, when they were transferred to the hydroponic beds. Two hundred forty tambaqui juveniles (113.5 ± 0.15 g and 19.6 ± 0.20 cm) were distributed in 12 tanks (1000-L capacity) in aquaponic units, totaling 20 fish per unit. The fish were fed commercial feed (36% protein and 7% lipids), and water quality variables were monitored daily. At 5, 10, and 15 days after transplanting to the hydroponic bed, the leaf number (LN) and plant height (PH, in cm) of the coriander were determined. Additionally, total fresh mass (TFM, in g), leaf fresh mass (LFM, in g), root fresh mass (RFM, in g), total dry mass (TDM, in g), leaf dry mass (LDM, in g), root dry mass (RDM, in g), leaf length (LL, in cm), root length (RL, in cm), yield of total fresh mass (YTFM, in kg m−2), and the nutritional composition of macro and micronutrients were determined, as well as fish growth performance. A density of 512 cells m−2 reduced the electrical conductivity (0.097 ± 0.001 dS m−1) of the water. The pH, dissolved oxygen, and temperature did not differ significantly between the densities. The total ammonia nitrogen (28.81 ± 2.26 mg L−1) and nitrate (51.07 ± 0.81 mg L−1) concentrations were greater at a density of 32 cells m−2. At the end of the 19-day period, the fish growth indices did not significantly differ (p > 0.05) as a function of coriander cultivation density. Density significantly influenced coriander growth. All variables (PH with root, LL, RL, LFM, TFM, LDM, TDM, RFM, RDM, and YTFM) were significantly influenced (p < 0.05) as a function of cultivation density. YTFM (1.82 ± 0.45 kg m−2), PH (30.39 ± 0.61 cm), and LL (16.62 ± 0.53 cm) were significantly higher (p < 0.05) at a density of 512 cells m−2. RL was significantly higher (p < 0.05) at densities of 72 and 32 cells m−2, of the order of 15.98 ± 0.43 and 18.79 ± 1.01 cm, respectively. Boron was significantly greater at a density of 512 cells m−2 (39.70 ± 1.04 mg kg−1) than at 32 cells m−2 (29.93 ± 4.66 mg kg−1). Similarly, sodium was significantly more abundant at a density of 512 cells m−2 (5975.54 ± 783.82 mg kg−1) when compared to the densities of 128 and 72 cells m−2, which were 4179.97 ± 287.31 and 3760.60 ± 224.31 mg kg−1, respectively. Aquaponic production in the equatorial Amazon region accelerated, and the optimal density for coriander integrated with tambaqui without compromising plant growth performance was 128 cells m−2.

Pengaruh Harga, Kualitas Pelayanan Dan Store Atmosphere Terhadap Kepuasan Pelanggan

The advent of contemporary lifestyles has precipitated a surge in the number of coffee shops, which have become pivotal sites for social interaction and work. In light of the pivotal role coffee shops play in contemporary society, it is crucial to gain insight into the factors that shape consumer satisfaction. The degree of consumer loyalty to a product, in this case coffee, is significantly influenced by the level of satisfaction experienced by the customer. The objective of this study is to gain insight into the influence of price, service quality and shop atmosphere on customer satisfaction at Sarang Kopi Susu Café in Karanggede, Boyolali. This research employs a mixed-methods approach, integrating both qualitative and quantitative techniques. The research population comprised all customers of the Sarang Kopi Susu Café. A sample of 100 respondents was selected using purposive sampling. The data were analysed using multiple linear regression analysis, a t-test, an F-test and a coefficient of determination (R²). The results of this study indicate that variable X1, namely price, has a positive but insignificant effect on customer satisfaction. Conversely, the variables of service quality and store atmosphere have a significant effect on customer satisfaction at Cafe Sarang Kopi Susu Karanggede, Boyolali.

Analysis of the Relationships between Quality of Life, Resilience, and Life Satisfaction Variables in Retired Individuals

Quality of life, resilience, and life satisfaction are influential variables during periods of change and adaptation, such as retirement. To assess the relationships between these variables and to analyze differences based on sex and length of time in retirement. This descriptive-correlational study was conducted with a sample of 63 participants, aged 50 to 84 years, who were effectively retired and residing in Spain. Participants completed a form measuring levels of resilience, quality of life, life satisfaction, and sociodemographic data. The data showed a positive and significant correlation between resilience and life satisfaction, and between quality of life and life satisfaction. Significant differences were found in quality of life based on the length of time in retirement. This study has elucidated the relationships between quality of life, resilience, and life satisfaction, as well as the influence of sociodemographic variables on these factors. These insights will aid in developing effective intervention programs for the retirement stage that promote quality of life, resilience, and life satisfaction among retired individuals.

Neural network-based hybrid modeling approach incorporating Bayesian optimization with industrial soft sensor application

Hybrid modeling combines physical and data-driven models to improve the performance of industrial soft sensors. However, simplified physical assumptions and extensive parameter optimization increase the complexity of the model and decrease its robustness and accuracy. In this study, a novel neural network-based approach for hybrid modeling was developed, based on Runge-Kutta (RK) and Bayesian hyperparameter optimization. First, the recursive solution equation for the quality variable was derived using the master equation, which included the black-box term and RK method. Second, the numerical solution of the black-box term was inverted using the derived equation as a label for the training samples, and hyperparameters were optimized using Bayesian optimization. Finally, during the prediction phase, quality variables at subsequent times were derived by solving a recursive equation containing neural network approximations. The superiority of the proposed soft sensing method was assessed through studies on a continuous stirred tank reactor (CSTR) case and a simulated penicillin case. The experimental findings demonstrate that the proposed method is better than existing methods in terms of robustness and accuracy.

Assessment of ∆9-THC and ∆9-THCCOOH Bias, Precision, and Ionization Suppression/Enhancement between Solid Tissue Homogenate and Supernatant by LC-MS/MS.

LC-MS-MS assays are frequently utilized for screening and confirmatory purposes in the forensic toxicology laboratory. While these techniques are excellent for the targeted identification and quantitation of a wide variety of drug classes, validation and determining fit-for-purpose is a requirement for each method. In the United States, ANSI/ASB Standard 036 currently serves as a primary resource in forensic toxicology method validation, and mandates that laboratories evaluate critical performance characteristics to help ensure the production of forensically defensible results. Due to the variability of specimen quality frequently encountered in the discipline of postmortem toxicology, the [Author Information Removed] Office of the Chief Medical Examiner Forensic Toxicology Laboratory routinely analyzes solid tissue specimens as part of the medicolegal death investigation process and evaluates liver as a representative solid tissue matrix during method validation. Authentic postmortem specimens (e.g., liver, kidney, skeletal muscle, and spleen) were used to investigate the effects of analyzing solid tissue homogenate versus solid tissue supernatant on bias, precision, and ionization suppression/enhancement of ∆9-THC and ∆9-THCCOOH. Bias was <20% for Δ9-THC and ∆9-THCCOOH in liver homogenate and supernatant with a single exception of the low QC concentration for Δ9-THC in liver homogenate (-29%). Within-run and between-run CV was <20% for Δ9-THC and ∆9-THCCOOH in liver homogenate and supernatant. Δ9-THC and Δ9-THC-d3 exhibited significant ion suppression in both liver homogenate and supernatant, while ∆9-THCCOOH and ∆9-THCCOOH-d3 showed both ion suppression and enhancement in these matrices. Noticeable quantitative differences were observed in authentic postmortem solid tissue homogenate and supernatant specimens despite evaluating from identical tissue samplings. A brief discussion of the results is presented using a validated LC-MS-MS method for the confirmation and quantitation of ∆9-THC and ∆9-THCCOOH in postmortem casework.

Characterizing normal perinatal development of the human brain structural connectivity.

Early brain development is characterized by the formation of a highly organized structural connectome, which underlies brain's cognitive abilities and influences its response to diseases and environmental factors. Hence, quantitative assessment of structural connectivity in the perinatal stage is useful for studying normal and abnormal neurodevelopment. However, estimation of the connectome from diffusion MRI data involves complex computations. For the perinatal period, these computations are further challenged by the rapid brain development, inherently low signal quality, imaging difficulties, and high inter-subject variability. These factors make it difficult to chart the normal development of the structural connectome. As a result, there is a lack of reliable normative baselines of structural connectivity metrics at this critical stage in brain development. In this study, we developed a computational method based on spatio-temporal averaging in the image space for determining such baselines. We used this method to analyze the structural connectivity between 33 and 44 postmenstrual weeks using data from 166 subjects. Our results unveiled clear and strong trends in the development of structural connectivity in the perinatal stage. We observed increases in measures of network integration and segregation, and widespread strengthening of the connections within and across brain lobes and hemispheres. We also observed asymmetry patterns that were consistent between different connection weighting approaches. Connection weighting based on fractional anisotropy and neurite density produced the most consistent results. Our proposed method also showed considerable agreement with an alternative technique based on connectome averaging. The new computational method and results of this study can be useful for assessing normal and abnormal development of the structural connectome early in life.

Using Scorecards to Tune Ethos Directive Templates: An Adaptive Radiation Therapy Individualized Approach-Cervix Dosimetric Planning Study

The Adaptive Radiation Therapy Individualized Approach-Cervix clinical trial uses predefined clinical directive templates (CDTs) combined with RapidPlan dose-volume histogram estimations (DVHe) to guide plan optimization in the Ethos treatment planning system. The dosimetric scorecard is a scoring tool that quantifies improvements in plan quality after physicians have precisely expressed their complete clinical intent. To our knowledge, this is the first study to use the dosimetric scorecard tool to tune an Ethos CDT to improve resulting plan quality. Iterative replanning was used to modify the draft CDT (CDT-1) in Ethos 1.1 to generate a new CDT (CDT-2) that maximized the clinical consensus scorecard's total score compared with CDT-1. CDT-2 was established, and resulting plans were compared with and without a DVHe. Additional fixed field intensity modulated radiation therapy beam geometries were compared between CDT-1 and CDT-2, both with DVHe. After obtaining favorable results when comparing CDT-1 versus CDT-2 for 2 test cases, 10 additional cases were retrospectively identified and tested. CDT-2 reduced organ at risk doses without compromising planning target volume coverage in the initial test cases. When combined with DVHe, CDT-2 marginally outperformed CDT-1. Plan quality further improved with a 19-field geometry. In the expanded analysis, CDT-2 achieved higher scores than CDT-1 in most cases, with the 19-field approach showing superiority. Optimization and calculation time increased by 1.9 minutes, monitor unit (MU)/field decreased by 44.4, whereas beam-on time increased by 2.8 minutes when increasing fields to 19 from 9. Reoptimization with Ethos 1.1 Maintenance Release 1 resulted in decreased MU and minimal score changes. The scorecard is an effective tool to adjust an Ethos CDT to improve the average calculated plan quality. It also allowed for easy evaluation of the dosimetric impact of other planning parameters (beam arrangements and use of DVHe) to identify the best approach. Using a finely tuned CDT is expected to improve planning efficiency and decrease intrainstitutional plan quality variability, benefiting cone beam computed tomography-guided adaptive radiation therapy.

Novel sensorized additive manufacturing-based enlighted tooling concepts for aeronautical parts

This paper presents lightweight tooling concepts based on additive manufacturing, with the aim of developing advanced tooling systems as well as installing sensors for real-time monitoring and control during the anchoring and manufacturing of aeronautical parts. Leveraging additive manufacturing techniques in the production of tooling yields benefits in manufacturing flexibility and material usage. These concepts transform traditional tooling systems into active, intelligent tools, improving the manufacturing process and part quality. Integrated sensors measure variables such as displacement, humidity and temperature allowing data analysis and correlation with process quality variables such as accuracy errors, tolerances achieved and surface finish. In addition to sensor integration, additive manufacturing by directed energy arc and wire deposition (DED-arc) has been selected for part manufacturing. The research includes the mechanical characterisation of the material and the microstructure of the material once manufactured by DED-arc. Design for additive manufacturing" principles guide the design process to effectively exploit the capabilities of DED-arc. These turrets, equipped with sensors, allow real-time monitoring and control of turret deformation during clamping and manufacturing of aeronautical parts. As a first step, deformation monitoring is carried out within the defined tolerance of ± 0.15, which allows a control point to be established in the turret. Future analysis of the sensor data will allow correlations with process quality variables to be established. Remarkably, the optimised version of the turret after applying DED technology weighed only 2.2 kg, significantly lighter than the original 6 kg version. Additive manufacturing and the use of lightweight structures for fixture fabrication, followed by the addition of sensors, provide valuable information and control, improving process efficiency and part quality. This research contributes to the development of intelligent and efficient tool systems for aeronautical applications.

PENGARUH FOOD QUALITY DAN INOVASI PRODUK TERHADAP CUSTOMER SATISFACTION DI PENTOL NONA BENGKULU

The quality of a food product is very important for every founder of a food selling company. Apart from that, to increase consumer satisfaction, a business must innovate. The aim of this research is to determine the influence of food quality and product innovation on customer satisfaction at Pentol Nona Bengkulu. This type of research is a descriptive quantitative approach. The population in this research is all consumers at Pentol Nona Bengkulu within 1 month. Sampling in this study was determined using the unknown population formula so that the number of samples in this study was 96 respondents. The data collection techniques in this research are observation and questionnaires. The data analysis techniques used are multiple linear regression, coefficient of determination, and hypothesis testing. It was found that food quality has a positive effect on customer satisfaction of Pentol Nona Bengkulu City consumers, so the higher the food quality, the higher the customer satisfaction at Pentol Nona Bengkulu City. Product innovation has a positive effect on customer satisfaction of Pentol Nona Bengkulu City consumers, so the higher the product innovation, the higher the customer satisfaction at Pentol Nona Bengkulu City. Together, the food quality and product innovation variables influence the customer satisfaction variable at Pentol Nona, Bengkulu City. Keywords : Food Quality, Innovation Of Product, Customer Satisfaction

Bioactive compounds and physico-chemical characteristics of guavas bagged with different materials

There are several alternatives to bags used for field fruit bagging but little is known about their management in the orchards and the influence of the materials on the phytochemicals and on the physicochemical properties of the fruits after harvest. This study aimed at evaluating fruit bagging with different materials regarding its management and interference in bioactive compounds and physico-chemical features of guava cultivars ‘Paluma’, ‘Século XXI’ and ‘Pedro Sato’, which were cultivated in an organic farming system. The experiment was carried in Brazilian Agricultural Research Corporation in 2014/2015 and 2015/2016 harvests. Guavas underwent the following treatments: no bagging (witness); non-woven fabric (TNT); kraft paper; white paper and transparent perforated polyethylene. The following fruit quality variables were analyzed: total phenols; antioxidant activity; carotenoids; peel color; soluble solids; pH; and titratable acidity. This study found that bagging materials interfered both in the phenol content and in the antioxidant activity of the three guava cultivars even though they did not affect pulp carotenoids. Fruit bagging with TNT and transparent perforated polyethylene provided more resistance against weather adversities. Bagging of guava cultivars ‘Paluma’, ‘Século XXI’ and ‘Pedro Sato’ changed the phytochemical and physicochemical features of the fruits.

Case study: Nutrients distribution and assessment of the current trophic status of Plastiras lake in Thessaly (central Greece) after tropical storm Daniel

Based on the interactions of three water quality variables, chlorophyll-a (Chl-a), secchi depth (SD – water transparency) and total phosphorus (TP), this study was aimed to assess the trophic state of Plastiras Lake through the modified method of Carlson's trophic state index (CTSI). Eutrophication is one of the most serious problems for water quality and CTSI is an important index for monitoring water quality status and eutrophication assessment. The classification scale for Trophic State Index (TSI) fluctuates from 0 to 100 and the results of this study showed that the mean TSI for Chl-a was 42.95, for SD was 45.50 and for TP was 75.15. The overall CTSI finally was 54.53. These show that Plastiras Lake is presently classified as mesotrophic to eutrophic which reflects the current levels of nutrients in the lake.

Reproducible MS/MS library cleaning pipeline in matchms

Mass spectral libraries have proven to be essential for mass spectrum annotation, both for library matching and training new machine learning algorithms. A key step in training machine learning models is the availability of high-quality training data. Public libraries of mass spectrometry data that are open to user submission often suffer from limited metadata curation and harmonization. The resulting variability in data quality makes training of machine learning models challenging. Here we present a library cleaning pipeline designed for cleaning tandem mass spectrometry library data. The pipeline is designed with ease of use, flexibility, and reproducibility as leading principles.Scientific contributionThis pipeline will result in cleaner public mass spectral libraries that will improve library searching and the quality of machine-learning training datasets in mass spectrometry. This pipeline builds on previous work by adding new functionality for curating and correcting annotated libraries, by validating structure annotations. Due to the high quality of our software, the reproducibility, and improved logging, we think our new pipeline has the potential to become the standard in the field for cleaning tandem mass spectrometry libraries.Graphical

Predicting air quality using random forest: A case study in Amman-Zarqa

The Spatiotemporal variability of air quality is influenced by various factors over time. The objectives of this research are to create prediction models for Carbon monoxide (CO) and Nitrogen dioxide (NO2) and determine the factors which that most impact CO and NO2 monthly using Random Forest Prediction. The methodology relies on Random Forest Prediction to predict air quality monthly in 2021, incorporating eight variables land surface temperature (LST), normalizeddifferencebuilt-upindex (NDBI), built-up index (BU index), normalized differencevegetation index (NDVI), digital elevation model (DEM), relative humidity (RH), wind speed (WS), and wind direction (WD). The results indicate that RH, elevation, WD, and LST are the most significant factors influencing CO concentrations, representing 33%, 24%, 12%, and 10% respectively at annual level in 2021. Similarly, WD, WS, RH, elevation and LST are the most importance factors impacting NO2 concentrations, representing 24%, 21%, 18%, 12%, and 10% respectively at an annual level in 2021. Furthermore, NDBI and BU index had the lowest impact in on both CO and NO2, with BU index showing a slightly higher percentage in NO2 models compared to CO models. Regarding cross-validation, the MAE values in CO models range from 0.11 to 0.18, and the RMSE values range from 0.14 to 0.23. Additionally, the MAE values in NO2 models ranges from 3.78 to 7.30, and RMSE values range from 4.93 to 9.23.

Geological Modeling of Shale Oil in Member 7 of the Yanchang Formation, Heshui South Area, Ordos Basin

In recent years, the Chang 7 member of the Mesozoic Triassic Yanchang Formation in the Ordos Basin has emerged as a significant repository of abundant and distinctive unconventional oil resources. The Heshui area boasts substantial shale oil reserves, with reported third-level reserves surpassing 600 million tons. However, the region in the southern part of Heshui is marked by pronounced variability in reservoir quality, intricate oil–water dynamics, low formation energy, and suboptimal fluid properties, leading to divergent development outcomes for horizontal wells. There is an imperative need to devise and refine new geological models to underpin the efficient exploitation of shale oil in the southern Heshui area. This study focuses on the shale oil reservoir of the Chang 7 member in the southern Heshui area of the Ordos Basin, conducting detailed stratigraphic correlation and establishing a refined isochronous stratigraphic framework. Utilizing PetrelTM modeling software (version 2018), we integrate deterministic and stochastic modeling approaches, adhering to the principles of isochronous and phased modeling. By assessing the thickness of sand and mudstone layers and the overall stratigraphic sequence, we derive a geological probability surface. Subsequently, this surface is harnessed to constrain the lithofacies, yielding a constrained lithofacies model. Employing sequential indicator simulation and sequential Gaussian stochastic simulation, we develop a reservoir attribute model that is anchored in the lithofacies model and its controls, culminating in a robust and dependable static model. Employing the geological probability surface constraint method, we meticulously construct the reservoir matrix model, amalgamating individual well data with the inherent certainty and randomness of reservoir plane thickness. This approach further enhances the model’s accuracy and mitigates the uncertainty and randomness associated with inter-well interpolation to a significant degree.

Influence of shift work on sleep quality and circadian patterns of heart rate variability among nurses

ABSTRACT Background: Shift work implementation is essential for providing continuous patient care in hospitals. However, working in shifts on a routine basis may disrupt the circadian pattern and alter the sleep-wakefulness cycle in nurses. Stress due to shift work can influence the adaptability of the cardiovascular system, produce psychophysiological strain and deteriorate work performance in female nurses. Objective: This study investigated the effect of morning and night shift work on sleep quality and circadian patterns governing heart rate variability (HRV) in female nurses working in a tertiary care hospital. Methods: Thirty-eight healthy female nurses were recruited. Frequency and time domain parameters of HRV were recorded as markers of cardiac autonomic function. A student t-test was used to investigate differences in HRV between morning and night shift workers. Mann-Whitney non-parametric test was applied for the difference between Pittsburgh Sleep Quality Index (PSQI) scores in the two groups Results: Standard deviation of the normal-to-normal interval (SDNN) (msec), total power (ms2) and high-frequency (HF) band power (ms2) were significantly reduced in night shift nurses than in morning shift nurses. The low-frequency (LF)/HF ratio was significantly increased in night shift nurses. The differences in standard deviation of the averages of NN intervals (SDaNN) (msec), root mean square of successive differences between adjacent NN intervals (RMSSD), mean NN, very low-frequency (VLF) band power (ms2) and LF band power (ms2) were not statistically significant. The global PSQI score was significantly higher among night shift workers than in morning shifts. Conclusion: Inadequate sleep can disrupt the body’s ability to regulate heart rhythm and increase the risk of cardiovascular diseases and mortality. The research suggests a propensity for autonomic imbalance in night shift workers when compared to their counterparts on morning shifts.

Prediction of stress level in military submariners, based on physical conditioning and sleep quality variables

The objective of the study was to predict the level of stress in military submariners based on physical fitness and sleep quality variables. Cross-sectional and correlational research, with a sample of 40 male submariners (28.70±3.98 years old). Body mass and composition data were analyzed (MCT), height, BMI, waist, body fat (%G), dominant handgrip (PMDom), cardiorespiratory fitness (VO2max), squats, sit-ups, relative power of lower limbs (PotRel MMII), stress (PSS-10), Epworth Sleepiness Assessment (ESE) and Pittsburgh Sleep Quality Index (PSQI). Overall, negative associations (p&lt;0.05) were observed between VO2max and MCT, BMI, %BF, and waist; PotRel MMII and age and %BF; squat and %G; sit-up and MCT, BMI, %BF and waist; and finally, stress and VO2max and sit-up. Furthermore, positive associations (p&lt;0.05) between BMI and MCT; %BF and MCT and BMI; waist and age, BMI, MCT, and %BF; squats and PMdom., VO2max and PotRel MMII; sit-ups and VO2max, PotRel LL and squats; ending with PSQI and stress. Furthermore, among the stress level prediction equation models developed, the equation Stress=15.92+1.538(PSQI)-0.497(VO2max)+0.188(Squat) met the proposed requirements, which is based on sleep quality, cardiorespiratory fitness, and number of squats. Keywords: Submariner; stress, physical fitness, sleep quality, military personal.