Changes In Dynamic Parameters Research Articles

Evolution of Posturographic and Dynamic Baropodometry 4 Weeks after Total Knee Arthroplasty

This is a prospective study, which included patients followed for advanced knee osteoarthritis (N = 10, mean age 72 ± 7.9 years) candidates for total knee arthroplasty (TKA). Functional status was carried out by WOMAC score. Posturological and dynamic baropodometric analysis were carried out before (M0) and 4 weeks after TKA (M1) using a PRESSCAM® stabilometry platform (SIDAS®, 38,000 VOIRON, MEDICAPTEURS®). Data provided information on the distribution of foot pressures on the operated and non-operated side. Comparison of baropodometric parameters was performed before (M0) and 4 weeks after TKA (M1). The total WOMAC score decreased significantly after TKA (P <0.05). The changes in posturographic and dynamic parameters of surfaces, pressure and force measured at M1 were not significant. At M0, the stabilogram position was deviated in all patients towards the contralateral operated side. At M1, we noted normalization of the stabilogram position in 2 patients. Surface of COP ellipse was superior to 1 cm2 (%) in one patient before TKA and in 2 patients after TKA. Comparison of medio lateral indexes indicated significant changes in surface area and average pressure (p<0.05). In conclusion posturographic and dynamic baropodometry analysis could help clinicians to correct the postural instability after total knee arthroplasty. Long-term follow-up studies will be able to confirm the use of baropodometry in evaluating TKA.

Effect of the Lactation Phases on the Amplitude of Variation in Blood Serum Steroid Hormones and Some Hematochemical Analytes in Three Dairy Cow Breeds.

Lactation in dairy cows implies comprehensive endocrine and metabolic changes including a systemic electrolytic reaction. Previous studies have rarely considered these specific demands due to the influence of lactation periods. Therefore, this study aimed to assess the effects of early, middle, and late lactation phases on the dynamic changes in serum concentrations of progesterone (P4), 17β-oestradiol (E2), cortisol, and some electrolytes (Ca++, Mg++, Na+, K+, Cl-, Pi) and biochemical parameters (alanine aminotransferase (ALT), aspartate aminotransferase (AST), lactate dehydrogenase (LDH), creatine kinase (CK), total bilirubin, urea, and iron (Fe++) in 10 Holstein, 10 Brown Swiss, and 10 Modicana multiparous healthy dairy cows (4.2 ± 1.7 years of age) sampled at 60-day intervals throughout lactation. Lactation induced significant changes in the concentrations of P4, which peaked at >120-180 days, decreased at >240-300 days, and increased again after 300 days. Cortisol showed an opposite trend to P4, with concentrations progressively decreasing, except for the phase between >240 and 300 days, and a steep drop at >300 days compared to previous phases. Na+ concentrations showed the lowest values at 0-60 d and the highest ones at >180-240 days, whereas Mg++ showed the highest values at >60-120 d and the lowest at >300 d. Significant correlations were found between P4 with cortisol, Cl- and K+, and cortisol with Ca++ and LDH. Significant differences in average concentrations of AST, ALT, LDH, Ca++, Mg++, and Fe++ were observed among different dairy cow breeds. Understanding the dynamic changes in hormone levels, electrolytes, and biochemical parameters during different lactation phases, while considering breed differences in dairy cows, is crucial for improving herd health management and milk production in commercial dairy farms.

An empirical analysis of learning and forgetting mechanisms in repeated evacuations: A panel recursive logit approach

Global efforts to address climate change increasingly focus on risk communication to encourage people's mitigation behaviour. This study investigates how risk communication influences evacuation behaviour, through repeated risk communications and stated preference surveys. In modelling the learning process of infrequent events like disasters, it is necessary to consider decision-making under uncertainty about future situations and the tendency to forget acquired information. We propose a recursive model that captures two decision dynamics relevant to infrequent events: proactive decision-making amid dynamically changing conditions and the learning and forgetting processes between events. The former is modelled using the recursive logit model on a time-expanded network, while the latter is represented by dynamic changes in utility and memory decay parameters. The estimation results indicate that risk communication generally promotes earlier evacuation to safer places. However, effective communication strategies and the duration of their effects differ based on individuals' perceived and actual risks.

Investigation of dynamic response characteristics of light fixed-wing aircraft

In order to ensure the stability of light fixed-wing aircraft during flight missions, considering the effects of relative airflow velocity and angle of attack, the distribution characteristics of velocity and pressure fields under different conditions, as well as the law of change of dynamic parameters, were derived by using aerodynamic methods. In the free modal condition, the modal truncation method was used to simulate and analyze the low-order modal shapes. Based on the modal analysis results, the sweep frequency range was set to 3-50 Hz, with a step size of 1.6 Hz, for a total of 30 substeps. A harmonic load of 1500 N was applied to the fuselage, and the displacement-frequency response curves and stress-frequency response curves of the fuselage structure and wing structure were extracted after the calculation. The results shows that the maximum lift-drag ratio occurs when the angle of attack is 6°, and the peak displacement deformation of the aircraft occurred around 24 Hz.

Nonlinear harmonic resonant behaviors and bifurcation in a Two Degree-of-Freedom Duffing oscillator coupled system of Tension Leg Platform type Floating Offshore Wind Turbine

The surge-heave coupled motion model of a Tension Leg Platform type Floating Offshore Wind Turbine (TLP FOWT) is first established. By taking the tendons stretching and platform set-down motion into consideration, the nonlinear model is a Duffing oscillator coupled system. We analyze the nonlinear feature in the surge-heave coupled motions by the semi-analytical algorithms in nonlinear dynamics. The harmonic balance method is applied to obtain the analytical solutions of the nonlinear system under wind and wave excitations. The analytical solution verifies the excellent accuracy. To further achieve the heave motion response, we organize the bifurcation analysis and discuss the effects of the dynamic parameters on the heave responses. The results reveal the multi components of heave motion, which consist of constant, primary harmonic resonate and higher order harmonic resonate. In addition, the change of dynamic parameters has various effects on the response. The increment of wave load leads to the expansion of heave response, and an instantaneous expansion appear. Both linear surge and heave damping only affect the amplitudes of heave motion. The nonlinear surge stiffness and heave stiffness can barely affect the primary harmonic resonance amplitudes, but they present different effects on the higher order harmonic resonance component.

Changes of Left Ventricular Global Longitudinal Strain and Diastolic Function Parameters in Patients Undergoing Primary Percutaneous Coronary Intervention with TIMI Flow Grade III after Anterior ST Segment Elevation Myocardial Infarction

Abstract Background STEMI is the most serious presentation of atherosclerotic CAD carrying the most hazardous consequences. STEMI is caused by occlusion of a major coronary artery and primary PCI is the recommended reperfusion therapy over fibrinolysis if performed by an experienced team as soon as possible. Myocardial infarction makes significant changes in composition, shape, and contractile function of myocardium. Especially left ventricle which is the major contributor to the contractile function of the heart, so it affects the systolic and diastolic functions of the heart. Objective To study the dynamic changes of left ventricular global longitudinal strain and diastolic function parameters in patients undergoing primary percutaneous coronary intervention with TIMI flow grade III after anterior STEMI Methods This study is a prospective observational study that was conducted at Ain Shams university hospitals, in the time interval from October 2022 till June 2023. A total of 100 Patients with anterior STEMI Results Our study showed significant improvement in LV systolic function, GLS and diastolic function parameters after PCI during the follow-up. Age > 53, DM, Chest pain to door > 7 hours and CK-total > 4356 were associated with no GLS recovery in Univariate analysis. In multivariate analysis, Chest pain to door > 7 hours was independently associated with no GLS recovery at follow-up with a sensitivity 90 % and specificity 95%. Conclusion In the present study we found Our study showed significant improvement in LV systolic function, GLS and diastolic function parameters after PCI during the follow-up. Age > 53, DM, Chest pain to door > 7 hours and CK-total > 4356 were associated with no GLS recovery in Univariate analysis. In multivariate analysis, Chest pain to door > 7 hours was independently associated with no GLS recovery at follow-up with a sensitivity 90 % and specificity 95%.

Assessment of immune status markers during occupational lead exposure

The immune system is sensitive to the effects of environmental factors, and according to numerous studies, lead has an immunotoxic effect. At the same time, there is evidence of the multidirectional nature of the impact of lead on the immune system, determined by the degree of exposure to this heavy metal, which makes it current to study changes in immunological markers in workers of a modern lead recycling plant, taking into account levels and complexity of exposure. In the era of personalized medicine, monitoring the potential influence of occupational factors exposure on the immune system can facilitate a personalized approach to the prevention of work-related health conditions. The aim of the study: to evaluate changes in immune status markers among employees of lead recycling plant. The main group – 62 men working at a lead recycling plant, the control group – 47 men not exposed to occupational factors. Laboratory examination included a determination of the lead blood level, a clinical blood test, the serum levels of IL- 1â, IL- 10, IL- 8, MCP-1, C3 and C4 complement components, IgA, IgM, IgG. In the main group, compared to the control group, a higher number of neutrophils, lymphocytes, monocytes, higher levels of IL-8, C3 and C4 components of the complement system, and lower levels of IgM were detected. In the main group, the following changes in markers were significantly more often detected in comparison with reference values: an increase in the C3 component of complement (51.6% in the main group compared to 12.5% in the control group), decreased IgG (24.2% compared to 6.2%) and increased IgA (22.6% compared to 6.2%). Associations were identified between the lead blood level and the number of lymphocytes, the level of IgG, between work experience in contact with lead and the level of MCP-1 and C3 complement components. The results of the studies revealed the presence of changes in the immune status markers of workers at a lead recycling plant, which demonstrate a proinflammatory effect of lead and an influence on the humoral immune status. The identified changes in immunological parameters may underlie the mechanisms of formation of pathological conditions associated with lead exposure, which determines the relevance of continuing research to assess dynamic changes in immunological parameters and develop a system for monitoring the immune status of workers exposed to lead and its compounds to optimize preventive measures.

The impact of everolimus on hematologic parameters in patients with renal angiomyolipoma associated with tuberous sclerosis complex

BackgroundEverolimus is an effective treatment for renal angiomyolipoma associated with TSC (TSC-RAML). However, its impact on hematologic parameters in TSC-RAML patients remains unclear.MethodsHematologic data were collected from TSC-RAML patients undergoing everolimus treatment in two registered clinical trials. Dynamic changes in hematologic parameters during treatment were analyzed. Additionally, we also explored variations in hematologic impact based on gender and age within the patient population.ResultA total of 55 patients from the two clinical trials are included in this analysis. Hemoglobin, white blood cells (WBC), lymphocytes, neutrophils, and platelet showed significant decreases during everolimus treatment (P < 0.05). However, the decline in hemoglobin, WBC, and neutrophils attenuated by the 12th month (P ≥ 0.05). Aspartate transaminase (AST), Alanine transferase (ALT), total cholesterol (TC), and triglyceride (TG) increased significantly during everolimus treatment (P < 0.05), and these increases persisted throughout the year-long treatment. Hemoglobin decreased significantly more in male patients (− 15 vs − 6, P = 0.010), and AST showed a more significant increase in males (7.0 vs 3.0, P = 0.041). Platelet counts decreased significantly more in younger patients (≤ 30 years old) compared to older patients (− 50 vs − 14, P = 0.020).ConclusionEverolimus administration in TSC-RAML patients may increase hematologic risks, with male and younger patients potentially exhibiting greater susceptibility to these effects.

Do dynamic changes in haematological and biochemical parameters predict mortality in critically ill COVID-19 patients?

BACKGROUND: Critically ill COVID-19 patients are usually subjected to clinical, laboratory, and radiological diagnostic procedures resulting in numerous findings. Utilizing these findings as indicators for disease progression or outcome prediction is particularly intriguing. OBJECTIVES: Exploring the significance of dynamic changes in haematological and biochemical parameters in predicting the mortality of critically ill COVID-19 patients. METHODS: The present study was a prospective and observational study involving mechanically ventilated 75 critically ill adult COVID-19 patients with hypoxemic respiratory failure. The collected data included baseline patient characteristics, treatment options, outcome, and laboratory findings at admission and 7 days after. The dynamics of the obtained findings were compared between survivors and non-survivors. RESULTS: The 28-day survival rate was 61.3%. In the group of non-survivors significant dynamic changes were found for C-reactive protein (p= 0.001), interleukin-6 (p&lt; 0.001), lymphocyte (p= 0.003), neutrophil-lymphocyte ratio (p= 0.003), platelets (p&lt; 0.001), haemoglobin (p&lt; 0.001), iron (p= 0.012), and total iron-binding capacity (p&lt; 0.001). Statistically significant changes over time were found for ferritin (p= 0.010), D-dimer (p&lt; 0.001), hs-troponin T (p&lt; 0.002), lactate dehydrogenase (p= 0.001), glucose (p= 0.023), unsaturated iron-binding capacity (p= 0.008), and vitamin D (p&lt; 0.001). CONCLUSION: The dynamic changes in inflammatory, haematological and biochemical parameters can predict disease severity, and outcome.

An evaluation of the effectiveness of four chemical additives on the fermentation characteristics, in vitro digestibility and aerobic stability of total mixed ration silage based on soy sauce residue.

The study aimed to compare the impact of four chemical additives on fermentation characteristics, aerobic stability and in vitro digestibility of total mixed ration (TMR) silage based on soy sauce residue. The TMR (35% soy sauce residue + 45% Napier grass + 20% concentrate) was placed into silos (10 L). The experiment followed the completely random design, treated with different chemical additives: (1) distilled water (control); (2) 0.1% potassium sorbate (SP); (3) 0.1% sodium benzoate (SS); (4) 0.5% calcium propionate (SC); (5) 0.5% sodium diacetate (SD). Total of 100 silos (5 treatments × 4 aerobic exposure days × 5 replicates) were ensiled for 60 days. After exposure to the air, the samples were analyzed for the dynamic change of fermentation parameters at 4, 9 and 15 days, and the data was analyzed as repeated measures. The content of butyric acid and ammonia nitrogen was maintained at a low level. The highest (p < 0.05) lactic acid (LA) content and the lowest (p < 0.05) pH value were measured in SP. At the first 4 days of aerobic exposure, TMR silages treated with four chemical additives were more stable relative to the control, as indicated by the low pH value and yeast counts. Furthermore, the highest (p < 0.05) LA content and the lowest (p < 0.05) pH value indicated that SP performed superior aerobic stability compared with other chemical additives. The SP shows higher (p < 0.05) 72 h cumulative gas production (GP72) and in vitro neutral detergent fiber digestibility (IVNDFD) relative to the control. In conclusion, the SP performed superior in improving fermentation characteristics, aerobic stability and in vitro digestibility of TMR silages based on soy sauce residue.

Probabilistic Analysis of Critical Speed Values of a Rotating Machine as a Function of the Change of Dynamic Parameters.

Real-world rotordynamic systems exhibit inherent uncertainties in manufacturing tolerances, material properties, and operating conditions. This study presents a Monte Carlo simulation approach using MSC Adams View and Adams Insight to investigate the impact of these uncertainties on the performance of a Laval/Jeffcott rotor model. Key uncertainties in bearing damping, bearing clearance, and mass imbalance were modeled with probabilistic distributions. The Monte Carlo analysis revealed the probabilistic nature of critical speeds, vibration amplitudes, and overall system stability. The findings highlight the importance of probabilistic methods in robust rotordynamic design and provide insights for establishing manufacturing tolerances and operational limits.

Dynamic Assessment of Hematological Parameters as Predictive Biomarkers for Disease Severity and Prognosis in COVID-19 Patients: A Longitudinal Study.

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to substantial morbidity and mortality worldwide. Hematological abnormalities are common in COVID-19 patients and play a significant role in disease pathogenesis and prognosis. This study aimed to longitudinally monitor hematological parameters in COVID-19 patients and investigate their predictive value for disease severity and prognosis. A prospective longitudinal design was employed to enroll 121 adult patients diagnosed with COVID-19 based on positive SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test results. Baseline demographic and clinical data were collected, and hematological parameters, including complete blood count (CBC) indices, inflammatory markers, and coagulation profiles, were measured at predefined time points during hospitalization or outpatient visits. Follow-up assessments were conducted longitudinally to monitor the disease progression and clinical outcomes. This study revealed dynamic changes in hematological parameters over the course of COVID-19. Hemoglobin levels showed a decrease from baseline (mean ± SD: 12.5 ± 1.8 g/dL) to the peak of illness (10.2 ± 2.0 g/dL), indicating the development of anemia during the acute phase of infection. White blood cell counts demonstrated an initial increase (8.9 ± 3.2 × 10^9/L) followed by a decline (5.4 ± 1.9 × 10^9/L) as the disease progressed, suggesting an early inflammatory response followed by immune suppression. The platelet counts fluctuated, with a decrease observed during the acute phase (190 ± 50 × 10^9/L) and subsequent recovery during convalescence (240 ± 60 × 10^9/L). Inflammatory markers, such as C-reactive protein and interleukin-6, were elevated, peaking at 120 and 150 pg/mL, respectively, indicating systemic inflammation. Coagulation profiles showed abnormalities suggestive of COVID-19-associated coagulopathy, including elevated D-dimer levels (mean ± SD: 3.5 ± 1.2 µg/mL) and prolonged prothrombin time (15.8 ± 2.5 seconds). Longitudinal analysis of hematological parameters revealed associations between disease severity and clinical outcomes, with certain abnormalities correlating with an increased risk of complications and a poor prognosis. This study highlights the importance of monitoring hematological parameters in COVID-19 patients for risk stratification, prognostication, and guiding therapeutic interventions.

Metoda pomiaru temperatury ciała człowieka za pomocą kamery termowizyjnej

Measurement and monitoring of human physiological parameters play an important role in many applications such as health care, sports training and prevention of disease spread. Dynamic changes in physiological parameters can reveal not only changes in a patient’s physiological state and function, but also be used to assess a person’s activity status, fitness and fatigue. Body temperature is among the most important human physiological parameters for assessing basic vital functions, apart from heart rate, blood pressure and respiratory rate. In medical practice, various types of measuring instruments are used to measure temperature, such as liquid thermometers, electronic thermometers, non-contact ear thermometers, non-contact forehead thermometers. Liquid and electronic thermometers require the appropriate sensors to be connected to a person, which may be undesirable or impossible as, for example, in newborns or during sports training. Non-contact thermometers operate over short distances and often force a specific position of the person during the measurement. In addition, the above body temperature measurement techniques require direct supervision by medical personnel, which often reduces the effectiveness and efficiency of screening temperature measurement. In screening temperature measurements of a large number of people, especially those on the move, a measuring thermal imaging camera works well. The article presents a method for measuring human body temperature using a thermal imaging camera. The presented method is characterized by high accuracy of temperature measurement, which allows medical use of the obtained measurements. The measurement method has been tested on a test stand and for a selected test sample of people. The measurements and tests carried out confirmed the possibility of obtaining temperature measurement accuracy with an expanded uncertainty of less than 0.05 K with a resolution of less than 0.1 K.

Dynamic changes of complete blood cell count parameters among airport workers during the COVID-19 pandemic in Chongqing, China: A retrospective longitudinal study

Background and aimsThis study aimed to examine the dynamic changes in the complete blood counts of airport staff from 2019 to 2021 and assess the impact of the coronavirus disease 2019 (COVID-19) on their overall health status during the first pandemic wave. Materials and methodsA total of 2144 airport staff members from Chongqing Jiangbei International Airport who underwent health examinations for three consecutive years from 2019 to 2021 were recruited for this study. Venous blood samples were collected for a complete blood cell count. ResultsChanges were observed in blood routine parameters from airport staff over three consecutive years. After adjusting for age, body mass index, and systolic blood pressure, the red blood cell count decreased consecutively during the COVID-19 pandemic. Hemoglobin and basophil counts decreased significantly during COVID-19 year 1. Lymphocyte and platelet counts decreased, whereas the monocyte-to-lymphocyte ratio increased in COVID-19 year 2. However, the white blood cell count, neutrophil count, neutrophil-to-lymphocyte ratio, and eosinophil count did not change from 2019 to 2021. ConclusionThis study showed changes in complete blood counts in frontline airport workers, especially men, during the COVID-19 pandemic. Therefore, paying more attention to the overall health conditions and immune function of airport staff engaged in intensive work is necessary.

Lithium-ion point-of-care ultrasound battery joint state of charge estimation

With recent advances in ultrasound technology, including accessibility and portability, point-of-care ultrasound systems (POCUS) are becoming ubiquitous in urban and rural health services. The efficient use of POCUS battery power is necessary due to the limited access to electricity in rural locations. Accurate estimation of the state-of-charge (SOC) of the onboard lithium-ion battery is crucial in ensuring the safe, efficient, and reliable operation of the battery management system (BMS). This research suggests a novel approach for striking a reasonable balance between the POCUS battery management systems computation time and SOC estimate accuracy. Given that the lithium-ion battery is a non-linear and time-varying system, it is modelled by a second-order RC equivalent circuit model (2-RC ECM). Real-time parametric identification is carried out using the method of recursive least squares with respect to an adaptive forgetting factor (AFFRLS). The joint SOC evaluation technique, ordering the results of real-time identification and the Extended Kalman Filter (EKF) recommended for estimating battery SOC at temperatures between 0 and 45 °C. Simulations were carried out using experimental data from the DST (Dynamic Stress Test), incremental current and, the Federal Urban Driving Program (FUDS) of the CALCE research group to evaluate the proposed approach. Based on the monitoring of dynamic changes in model parameters and the computational complexity of existing algorithms, the results reveal that the joint AFFRLS-EKF estimation proposed for the SOC strategy achieves good accuracy, high adaptability and rapid convergence of SOC estimation.

Dynamic changes of hematological and hemostatic parameters in COVID-19 hospitalized patients: Potential role as severity biomarkers for the Chilean population.

COVID-19 is still a global health issue, there is limited evidence in South America regarding laboratory biomarkers associated with severe disease. The objective of our study was to identify hematological and hemostatic changes associated with severe COVID-19. A total of 170 hospitalized patients with COVID19 were included in the study, defining their severity according to established criteria. Demographic, clinical, and laboratory (days 1, 3, 7, 15) data were obtained. We performed a statistical analysis, assuming significance with a value of p < 0.05. We analyzed the correlation between severity and biomarkers and established cut-off values for severe patients through ROC curves, estimating Odds Ratio associated with severe disease. Day 1 was observed significant differences between moderate vs severe patients for leukocytes (WBC), Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and D-dimer, establishing cut-off points for each of them. The markers we found associated to risk of severe disease were WBC (OR=3.2396; p = 0.0003), NLR (OR=5.7084; p < 0.0001), PLR (OR=4.4094; p < 0.0001), Neutrophil (OR=4.1193; p < 0.0001), D-dimer (OR=2.7827; p = 0.0124). The results allow to establish basic laboratory biomarkers associated to severe disease, which could be used as prognostic markers.

Dynamic changes of physicochemical parameters, antioxidant activity, organic acids, polyphenols, and volatile components in prune vinegar during fermentation

To investigate the quality variations of prune vinegar during fermentation, multivariate statistical analysis (MSA) was used in conjunction with high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS). The results showed that the pH decreased slightly, there was a rapid decline in sugar content, and a gradual increase in total acid content, which achieved stabilization at 3.68 g/100 mL. The content of organic acid increased, while the total phenol content decreased. The total flavonoid content did not change significantly. Furthermore, the antioxidant capacity initially decreased and then increased. Prune vinegar contains important phenolics such as rutin, resveratrol, salicylic acid, trans-ferulic acid, and (+)-catechin. In addition, the flavor of prune fruit vinegar underwent changes during the fermentation process. During the fermentation of fruit vinegar, large quantities of 2,3-butanediol, glacial acetic acid, nonanoic acid, ethyl acetate, ethyl heptanoate, ethyl caproate, and linalool were produced. These compounds give prune vinegar its distinctive fruity and floral aroma. This study provided a comprehensive framework for the efficient processing of prunes and a strategy for enhancing the quality characteristics of prune vinegar or other fermented products.

Fractal study on the nonlinear seepage mechanism during low-permeability coal water injection

In the initial stage of coal seam water injection, due to the high density and low permeability of coal bodies, an obvious startup pressure gradient is observed in relation to water seepage; this phenomenon leads to low-velocity nonlinear seepage. In this paper, we study the nonlinear seepage law and the main influencing parameters of the water injection process. First, based on the startup pressure gradient, the nonlinear seepage equation, and the fractal theory, we formulated a nonlinear seepage model of coal seam water injection that considered the fractal characteristics of a complex coal structure. Subsequently, we carried out coal seam water injection and gas radial seepage experiments under a high overburden pressure, obtaining the startup pressure gradient according to the seepage characteristics and the changes of dynamic parameters. Then, the dynamic parameters of water injection, the structural parameters of the coal samples, the physical parameters, and the fractal dimension were substituted into the theoretical model to obtain the theoretically calculated value. Finally, through comparative analysis of theoretical and experimental startup pressure gradient calculation results, it is found that with the increase in the overburden pressure, the permeability of coal and the connectivity effect are reduced, while the fracture tortuosity and the startup pressure gradient increase. Moreover, coal seam permeability does not seem to be the single decisive factor for the nonlinear startup pressure gradient.

Assessment of Sequential Yeast Inoculation for Blackcurrant Wine Fermentation

Blackcurrant is well known for its health benefits, but its wine products are understudied. In this research, studies were conducted after non-Saccharomyces and Saccharomyces yeast strain inoculation in less than 20% (w/v) fruit must for blackcurrant fermentation. Three inoculations were carried out on blackcurrant musts, as follows: (1) sequential inoculation with Torulaspora delbrueckii (strain Biodiva) followed by Saccharomyces EC1118 strain; (2) sequential inoculation with Metschnikowia pulcherimma (strain Flavia) followed by EC1118; (3) single-strain inoculation with EC1118 as the control treatment. None of these treatments did alter sugar consumption dynamics. Biodiva inoculation had impacts on both color dynamic parameter changes and final wine color profiles compared to EC1118. The final wine compositions indicate that Biodiva treatment had a significant impact on wine pH and acidity, whereas EC1118 single-strain largely influenced wine ethanol and glycerol contents. Although the total antioxidant capabilities were close among the three produced wines, the monophenol profiles indicate that Biodiva enhanced the total anthocyanin and hydroxycinnamates content but reduced the total flavanol contents in the final wine. EC1118 and Flavia wines contained more total flavanols compared to Biodiva treatment. The nonflavonoid profiles indicate that there were no significant differences among the three treatments. Our findings provide useful information for the application of yeast strains in blackcurrant wine fermentation.

A study on ice resistance prediction based on deep learning data generation method

Accurate prediction of ice resistance plays an important role in ensuring the safety of ship navigation when sailing in ice regions. This paper focuses on the design of a data generation deep learning model and an interpretable ice resistance prediction deep learning model. By selecting the appropriate ship, ice parameters and model experimental data to build the dataset, the influence of different data preprocessing methods on the model results are discussed. The processed data is expanded by Deep Convolutional Generative Adversarial Network (DCGAN). On this basis, a Graph Neural Network (GNN) is built to explain the distribution of network weights and the generalization effect of the model. The established model (GNN-DCGAN) and several ice resistance prediction methods are compared and analyzed. In addition, the design of polar ships needs to comprehensively consider the dynamic changes of ship design parameters and the mechanical properties of ice. In this paper, taking MT UIKKU as an example, the parameter sensitivity analysis is carried out to study the scope of application of the model and the contribution of different parameters. The results show that the DCGAN method can improve the prediction accuracy and application scope of GNN model. The predictions exhibit a high level of agreement with the experimental data, which can provide valuable references for the design of ship in ice regions.