Combination Of Methods Research Articles

Enhancing artificial permafrost table predictions using integrated climate and ground temperature data: A case study from the Qinghai-Xizang highway

The complexities of permafrost changes, driven by climate warming and engineering activities, coupled with challenges in data acquisition, make it crucial and challenging to accurately predict the artificial permafrost table, particularly for subgrades in high-temperature unstable permafrost regions. To address this, this study developed a hybrid machine learning model (RF-LSTM-XGBoost) for permafrost table prediction. By analyzing climate change and ground temperature data from various positions and depths along the subgrade in the Tuotuo River section of the Qinghai-Xizang Highway, the Spearman correlation coefficient method was initially used to determine the important influencing factors. Random Forest (RF), Long Short-Term Memory Neural Network (LSTM), and Extreme Gradient Boosting (XGBoost) models were used to predict the artificial permafrost table, and grid search and cross-validation methods were employed to optimize the hyperparameters of each model. A linear weighted combination method based on the minimum cumulative absolute error was utilized to merge the models, and its performance was compared with the individual RF, LSTM, and XGBoost models. Subsequently, the feature importance of the variables in the machine learning model was analyzed. The results indicated a strong correlation between artificial permafrost table changes and factors such as daily average atmospheric temperature, subgrade surface ground temperature, and subgrade surface ground heat flux during the freezing-thawing cycle. The combined model highlighted daily atmospheric temperature as the most influential predictor, followed by ground heat flux, with the surface ground temperature being less impactful. The combined model demonstrated improved predictive accuracy, with MSE, MAPE, RMSE, MAE, and R2 values of 0.003, 0.052, 0.0085, 0.029, and 0.989, respectively, surpassing those of individual models. This model offers a rapid, accurate, and reliable approach for permafrost table prediction, advancing subgrade stability research in challenging permafrost environments.

Research and Analysis of a Smart System for Intelligent Control of PCM Water Storage Tank for Stock Farm Needs

Energy efficiency is a very important component in modern systems. Modern research examines innovative methods and techniques for increasing the efficiency of heat generation systems. A popular approach is to apply combined methods of using energy from different heat sources. This article describes а basic algorithm for developing an intelligent control for a system of hot-water storage tanks with PCM adapted for a stock farm's needs. The main components of the system are described along with the PCM advantages. The prerequisites for the system’s operation are analyzed and adapted for its management. The developed algorithm and a control system are tested in a simulated environment and are presented conclusions of the system’s energy efficiency improvement.

Comparative study of pathogen detection methods for central nervous system infections: laboratory testing of tuberculous meningitis

BackgroundTuberculous meningitis (TBM) is a severe central nervous system (CNS) infection with a challenging diagnosis due to inadequate detection methods. This study evaluated current clinical detection methods and their applicability.MethodsA cohort of 514 CNS infection patients from 2018 to 2020 was studied. Data on general demographics, Cerebrospinal Fluid (CSF) analysis, epidemiology, and clinical outcomes were collected. TBM patients were identified, and the sensitivities of mmetagenomic next-generation sequencing (NGS), GeneXpert, and microbial culture were compared. Kappa statistic assessed the consistency between methods.ResultsAmong the patients involved, TBM (29%) and neurosyphilis (25%) were the two most prevalent CNS infections. CSF analysis indicated that 76% of patients had leukocytosis, suggesting a potential CNS inflammation. In TBM cases, 92.5% had elevated CSF protein and leukocyte counts. Moreover, the percentage of positive mNGS results was 55.6%. GeneXpert and MTB cultures alone had lower sensitivity, but combined use resulted in a 53.4% positive rate.ConclusionsThis study highlights the high sensitivity of mNGS, comparable to GeneXpert and MTB culture. The combined methods are cost-effective and straightforward, and can partially substitute for mNGS, offering valuable alternatives for TBM diagnosis and providing insights into multiple diagnostic strategies in clinical practice.

Combination of pretarsal and preseptal botulinum toxin injections in the treatment of blepharospasm: A prospective nonrandomized clinical trial

PurposeTo compare the efficacy of two botulinum toxin (BoNT) injection methods, pretarsal (PT) combined with preseptal (PS) injection (PT-PS) and conventional PT injection, in the treatment of benign essential blepharospasm (BEB). DesignProspective nonrandomized clinical trial. MethodsFrom January 2023 to April 2024, 95 BoNT injections into orbicularis oculi were performed in 45 BEB patients, including 52 PT-PS injections s and 43 PT injections. Jankovic Rating Scale (JRS) and Blepharospasm Disability Index (BSDI) were used to assess motor symptoms. The efficacy of two injection methods for BEB was compared in terms of latency to response (LTR), latency to the peak response (LPR), duration of peak response (DPR), duration of response (DOR), satisfaction degree, and possible complications. ResultsBoth injection methods significantly improved JRS and BSDI scores in patients with BEB. However, PT-PS injections showed a shorter LTR [(4.00(3.00,6.00) vs 5.00(4.00,7.00) days, p=0.024] and LPR [23.50(16.00,26.00) vs 26.00(20.00,30.00) days, p=0.040], a longer DPR [88.00(80.50,104.75) vs 75.00(65.00,92.00) days, p=0.003] and DOR [135.00(118.50,153.75) vs 121.00(107.00,135.00) days, p=0.003] than PT injections. Patients with PT-PS injections were more satisfied than those with PT injections [9.50(8.50,10.00) vs 8.00(7.50,9.00), p<0.001], and around 2/3 of patients were more willing to receive the combined injection method later. Among patients receiving PT-PS injections, only one case experienced ptosis, and there were no significant differences in other complications such as lacrimation, dry eyes, and blurred vision between the two injection methods. ConclusionsPT-PS injections of BoNT showed more advantages in the treatment of BEB than PT injections in terms of both their efficacy and patients’ satisfactions.

Water retention characteristics and mechanical properties of vegetated biopolymer and biochar-reinforced sandy loam

Vegetation is a sustainable strategy for erosion control and slope stabilization, though its initial cultivation can be lengthy and potentially weaken soil structures. This study compared two bio-mediated ground improvement techniques, biopolymer and biochar, known for their supportive effects on vegetation growth. Additionally, a novel treatment combining biopolymer and biochar was examined for its potential in vegetated-engineering practices. Engineering performance was assessed through soil water characteristic curve, vegetation growth, direct shear testing, and rainfall simulation. The results revealed that biopolymer and biochar treatments enhanced soil water capacity but negatively impacted vegetation germination rates and shear strength of the reinforced soil, attributed to hydrogel formation and increased soil water content from irrigation. In comparison, soil reinforced with the combined method showed a promotion in the vegetation while maintaining the soil’s mechanical performance throughout the cultivation period and exhibited only minor reductions in the shear strength compared to other reinforced soils. Moreover, the new treatment showed improved soil erodibility under a majority of rainfall occasions, regardless of the vegetation coverage. This enhanced engineering performance by the new treatment is believed to be the polymerisation between the biopolymer hydrogel, biochar and soil particles.

Forecasting the equity premium: can machine learning beat the historical average?

We empirically predict the equity premium with the selected machine learning methods in Gu et al. (Empirical asset pricing via machine learning. Rev. Financ. Stud., 2020, 33(5), 2223–2273). We also consider four additional popular machine learning methods (ridge regression, support vector regression, k-nearest neighbors, and extreme gradient boosted trees) and their combination method. Using a dataset of both macroeconomic and technical predictors, we find that despite showcasing strong in-sample forecasting abilities, particularly with tree-based models, the out-of-sample results support Welch and Goyal (A comprehensive look at the empirical performance of equity premium prediction. Rev. Financ. Stud., 2008, 21(4), 1455–1508) that the competing forecasting models generally fail to outperform the historical average benchmark. We attribute this failure to the small dataset size and the low signal-to-noise ratio inherent in equity premium prediction. Our variable importance analysis further identifies three bond interest rate-related variables as the most dominant predictors for the equity premium. The economic value from a market timing perspective highlights that the historical average benchmark strategy generates the highest average return of 25.63% and the best Sharpe ratio of 0.8. Finally, our findings are robust across a variety of settings.

FEM, DEM and FDEM applications on impact fracture of glass and laminated glass – A revie

Structural glass components are prevalently used in engineering. Due to the brittle nature, glass or laminated glass may fracture during an impact action, and the flying fragments may spread over a wide range, resulting in human injuries and asset losses. In this article, the authors aimed at providing a comprehensive review concerning the numerical applications on the impact fracture of glass and laminated glass. Relevant numerical applications employing the finite element method (FEM), discrete element method (DEM) and combined finite-discrete element method (FDEM) were reviewed, and features of the simulations were summarised. Insights into the accuracy, efficiency, ease of implementation and range of applicability were also provided. This review is meant for the rapid and beneficial understanding towards the impact fracture mechanism of glass and laminated glass.

The construction of international wetland urban ecological security pattern coupled with MSPA and ESF.

Creating an ecological security pattern is crucial for balancing the sustainable development of areas where human activities and the natural environment intersect. Using Hefei, an internationally recognized Wetland City, as a case study, we extracted ecological sources through ecological service function (ESF) analysis and morphological spatial pattern analysis (MSPA) core area connectivity analysis. Based on these ecological sources, we developed an ecological resistance surface system and identified ecological corridors and nodes using circuit theory. The findings are as follows: (1) Ecological source areas: The primary ecological sources in Hefei are located in the water bodies, forested areas, and scattered grasslands in the central and eastern parts of the city. This ecological source area covers 978.96 km2, which constitutes 8.55% of the city's total area. (2) Ecological corridors: Hefei contains 43 ecological corridors with a total length of 940.3km, averaging 21.87km each. These corridors are crucial for maintaining ecological connectivity and facilitating species movement. (3) Ecological nodes: There are 13 significant ecological nodes in Hefei, including 6 ecological obstacle points and 7 ecological pinpoints. These nodes play a vital role in supporting ecological processes and ensuring habitat connectivity. (4) Evaluation metrics: The α and β values for the source identification method that integrates MSPA with ecological service functions were 2.15 and 0.8, respectively, which are higher than those of the control group. Conversely, the γ-value was 0.18, lower than that of the control group. These results indicate that the combined ecological source extraction method provides significant advantages in terms of ecological corridor integrity, connectivity, and ecological flow management.

Enhancing protein extraction from Pleurotus ostreatus using synergistic pH-shifting and ultrasonic technology: Optimization via RSM and 1H NMR-based metabolomic profiling

This study explores the impact of ultrasound and pH-shifting on protein extraction from P. ostreatus, employing 1H NMR techniques to monitor metabolites and elucidate the extraction mechanism. The NMR-based metabolic analysis demonstrated that extended sonication time significantly boosted amino acid release. To optimize conditions for maximizing protein yield, response surface methodology was performed. This research aims to enhance protein extraction from P. ostreatus by analyzing the interplay between ultrasound treatment and pH-shifting. The results indicate that the synergistic use of pH-shifting and ultrasound-assisted extraction (UAE) significantly improves protein yield. The amino acid profile of the protein concentrates revealed a high content of essential amino acids, with tryptophan identified as the limiting amino acid. Additionally, the combined extraction method enhanced the emulsifying properties and foaming stability of the protein concentrates. Thus, combining pH-shifting and UAE is a promising technique for extracting high-quality protein from P. ostreatus, enhancing functional properties and efficiency.

Value of automated breast ultrasound in screening: Standalone and as a supplemental to digital breast tomosynthesis.

We aimed to determine the value of standalone and supplemental automated breast ultrasound (ABUS) in detecting cancers in an opportunistic screening setting with digital breast tomosynthesis (DBT) and compare this combined screening method to DBT and ABUS alone in women older than 39 years with BI-RADS B-D density categories. In this prospective opportunistic screening study, 3466 women aged 39 or older with BI-RADS B-D density categories and with a mean age of 50 were included. The screening protocol consisted of DBT mediolateral-oblique views, 2D craniocaudal views, and ABUS with three projections for both breasts. ABUS was evaluated blinded to mammography findings. Statistical analysis evaluated diagnostic performance for DBT, ABUS, and combined workflows. Twenty-nine cancers were screen-detected. ABUS and DBT exhibited the same cancer detection rates (CDR) at 7.5/1000 whereas DBT + ABUS showed 8.4/1000, with ABUS contributing an additional CDR of 0.9/1000. Standalone ABUS outperformed DBT in detecting 12.5% more invasive cancers. DBT displayed better accuracy (95%) compared to ABUS (88%) and combined approach (86%). Sensitivities for DBT and ABUS were the same (84%), with DBT + ABUS showing a higher rate (94%). DBT outperformed ABUS in specificity (95% vs. 88%). DBT + ABUS exhibited a higher recall rate (14.89%) compared to ABUS (12.38%) and DBT (6.03%) (p < .001). Standalone ABUS detected more invasive cancers compared to DBT, with a higher recall rate. The combined approach showed a higher CDR by detecting one additional cancer per thousand.

Evaluation of adsorption, photocatalysis, and combinational methods for the treatment of a cationic dye-bearing wastewater

Evaluation of adsorption, photocatalysis, and combinational methods for the treatment of a cationic dye-bearing wastewater

The Ability of Physical Education Teachers in Implementing Learning at Elementary Schools in Southwest Aceh Regency

Physical education teachers are responsible for preparing quality Learning Implementation Plans and implementing effective learning processes so that learning objectives are achieved. A good Learning Implementation Plan will make it easier for teachers to implement structured and directed learning. Physical education teachers face challenges in implementing effective learning processes. The physical education learning process must actively involve students and train their motor skills. However, in practice, physical education teachers often face difficulties in managing classes and making students actively engaged in learning. The approach used by the author in this study was a mixed-method approach (combined method) with an explanatory sequential design type. The research sample comprised nine physical education teachers working in elementary schools throughout Aceh Barat Daya Regency. The data collection techniques used by the researcher were observation and interview techniques. 1) Physical education teachers' ability to implement learning in elementary schools in Aceh Barat Daya Regency obtained the "Good" category with an average score of 6.5. Teachers can display personality aspects that include indicators of being charming, authoritative, firm, full of calling, and alert. In learning activities, teachers can carry out activities to open lessons, master materials, determine learning steps (activities), evaluate the process and learning outcomes, and close learning well. 2) The obstacles felt by physical education teachers in implementing the learning process at Elementary Schools in Southwest Aceh Regency are related to the limited availability of physical education learning facilities and infrastructure at schools. This has an impact on the less-than-optimal implementation of learning and evaluation activities. In addition, the limited time in learning activities, especially to evaluate the learning process of each student as a whole, so that teachers choose a fast and simple evaluation method. 1) The ability of physical education teachers to implement learning in Elementary Schools in Aceh Barat Daya Regency obtained the "Good" category. Teachers can display personality aspects and implement learning well. 2) The obstacles felt by physical education teachers in implementing the learning process at SD Negeri Aceh Barat Daya Regency are related to the limited availability of physical education learning facilities and infrastructure at the school and limited time in learning activities, especially to evaluate the learning process of each student as a whole.

Predicting Lactobacillus delbrueckii subsp. bulgaricus-Streptococcus thermophilus interactions based on a highly accurate semi-supervised learning method.

Lactobacillus delbrueckii subsp. bulgaricus (L. bulgaricus) and Streptococcus thermophilus (S. thermophilus) are commonly used starters in milk fermentation. Fermentation experiments revealed that L. bulgaricus-S. thermophilus interactions (LbStI) substantially impact dairy product quality and production. Traditional biological humidity experiments are time-consuming and labor-intensive in screening interaction combinations, an artificial intelligence-based method for screening interactive starter combinations is necessary. However, in the current research on artificial intelligence based interaction prediction in the field of bioinformatics, most successful models adopt supervised learning methods, and there is a lack of research on interaction prediction with only a small number of labeled samples. Hence, this study aimed to develop a semi-supervised learning framework for predicting LbStI using genomic data from 362 isolates (181 per species). The framework consisted of a two-part model: a co-clustering prediction model (based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) dataset) and a Laplacian regularized least squares prediction model (based on K-mer analysis and gene composition of all isolates datasets). To enhance accuracy, we integrated the separate outcomes produced by each component of the two-part model to generate the ultimate LbStI prediction results, which were verified through milk fermentation experiments. Validation through milk fermentation experiments confirmed a high precision rate of 85% (17/20; validated with 20 randomly selected combinations of expected interacting isolates). Our data suggest that the biosynthetic pathways of cysteine, riboflavin, teichoic acid, and exopolysaccharides, as well as the ATP-binding cassette transport systems, contribute to the mutualistic relationship between these starter bacteria during milk fermentation. However, this finding requires further experimental verification. The presented model and data are valuable resources for academics and industry professionals interested in screening dairy starter cultures and understanding their interactions.

PREDICTION SYSTEM FOR THE AMOUNT OF SUGAR PRODUCTION USING ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM

Sugar is one of the staple foods most Indonesians use, so sugar production needs to be done optimally to meet people's needs. This research will design a prediction system for the amount of sugar production in PTPN XI PG Prajekan using the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. ANFIS is a combined method of two systems, namely a fuzzy logic system and an artificial neural network system. This research consists of data collection, ANFIS system design, ANFIS training, ANFIS testing, accuracy calculation, and result analysis. The prediction system for the amount of sugar production is designed to predict the variable which is the amount of sugar production in the year using the input variables (sugarcane harvested area in year ), (amount of sugarcane in year ), (average of yield in year ), and (number of milling days in year ). The experiments in this research used variations of the type of membership function and the number of membership functions. The best model obtained in this research is a model with a difference between two sigmoidal membership functions and a product of two sigmoidal membership functions with a total of 2 membership functions for each input variable. Both models have the same Mean Absolute Percentage Error (MAPE) value, which is 1.79% in the training process and 4.82% in the testing process.

Progress in modeling avian hyperuricemia and gout (Review).

Human organ tissue is vulnerable to hyperuricemia (HUA), which negatively impacts quality of life, particularly when it progresses to gout. Chicken uric acid formation and metabolism are similar to human uric acid metabolism; therefore, theoretically, the genesis and progression of human HUA and gout may be similar to those of poultry models. The present review explored HUA and gout and the progress of poultry-induced HUA and gout models. The present study reviewed procedures of modelling chicken gout and HUA and the detection indices and current concerns regarding these models. Notably, In the production of poultry hyperuricemia model, the combined method of water and food induction has a higher success rate and stability. Compared with mice induced HUA and gout models, poultry induced HUA and gout models had less kidney damage, and the models were stable and long-lasting.

ТЕХНОЛОГИЧЕСКИЕ ПАРАМЕТРЫ КОМБИНИРОВАННОГО МЕТОДА ЭЛЕКТРОФИЗИКОХИМИЧЕСКОЙ ОБРАБОТКИ МАТЕРИАЛОВ

This paper describes a combined material processing method using the principles of an electrochemical electroerosion treatment method. Mathematical calculations of processing modes are given, as well as graphs of the efficiency and accuracy of processing, depending on the materials used as a working medium.

An integrated approach to the treatment of a patient with chronic tonsillitis. Clinical case

Chronic tonsillitis (CT) is a common infectious-allergic disease leading to severe general somatic complications, including rheumatic damage of joints and heart, kidney disease. Currently in Russia there is an increase in the number of patients with CT. Therapy for CT in outpatient practice is often limited to only washing the lacunae of the palatine tonsils, without the use of local drugs. We observed a 35-year-old patient with a diagnosis of chronic tonsillitis and a history of the disease of more than 1.5 years. A combined method of therapy was chosen, including treatment with the Tonsillor apparatus using low-frequency ultrasound therapy and local use of Viroxinol for irrigation of the tonsils and mucous membrane. As a result of the complex treatment, pronounced positive dynamics and a decrease in the clinical symptoms of CT were achieved.

Real-Time Imaging of Calcium Dynamics in Human Sperm After Precise Single-Cell Stimulation.

Calcium signaling is a critical regulator of sperm activation and function during the processes of capacitation and fertilization. Here, we describe a combined method for calcium imaging of single, live human sperm in response to stimuli administered with a precisely targeted delivery technique. This protocol is an adaptation of techniques developed for studies of murine sperm [1, 2], and enables real-time monitoring of human sperm calcium dynamics with high spatiotemporal resolution and concurrent detection of acrosome exocytosis (AE), a functional endpoint of sperm capacitation and requirement for physiological fertilization.The described imaging technique provides a valuable tool for exploration of calcium regulation in human sperm, which is essential to answer important questions and knowledge gaps regarding the link between calcium dynamics, AE, and fertilization. The versatility of this technique can be amplified through use of various indicator dyes or integration with pharmacological strategies such as pre-treating sperm with inhibitors or activators targeting specific receptors, channels, or intracellular signaling pathways of interest. Beyond fundamental inquiries into sperm physiology, this method can also be applied to assess the impact of potential contraceptive compounds on calcium signaling, AE, and membrane integrity.

Study on the Consolidation Characteristics of Slurry-like Mud Treated by Flocculation-Solidification-High-Pressure Filtration Combined Method.

The disposal and reutilization of the enormous amounts of slurry-like mud (MS) dredged from navigation channel construction, ecological dredging, and other construction activities have been receiving increasing attention. In this paper, a flocculation-solidification-high-pressure filtration combined method (FSHCM) is used to treat MS, and the consolidation characteristics of The SHCM-treated MS are studied by conducting a series of one-dimensional consolidation compression tests. Various parameters, including the dosage of the curing agent, initial water content, and dry weight of the MS, are systematically analyzed to evaluate their influence on the consolidation behavior. The experimental results demonstrate that higher curing agent and initial water contents enhance the structural yield stress and compressive resistance, while increased dry weight decreases the structural yield stress but increases the compressive strain and void ratio. As the curing age increases, the ability of the FSHCM-treated MS to resist compressive deformation is further enhanced. In addition, the compressibility of the mud cake samples changes significantly at the yield point. This study has practical guiding significance for the optimal design and long-term application of FSHCM-treated MS.

Preparation of artificial humic acid from corn straw and its high-efficiency adsorption on norfloxacin

In this study, the biomass artificial humic acid (AHA) with efficient adsorption performance for norfloxacin (NOR) was prepared by ultrasonic-assisted acid-alkaline combined hydrothermal method with corn straw as raw material. Characterization analysis showed that AHA was a typical amorphous structure, and the oxygen content of AHA prepared by ultrasonic-assisted hydrothermal method was obviously improved compared with that without ultrasonic-assisted method. The saturated adsorption capacity of AHA was 551.53 mg/g, which was higher than that of other reported materials, such high-efficiency adsorption is due to the abundant oxygen-containing groups (–OH, –C=O, etc.) in AHA, which were functional groups that can be π-π stacked, hydrogen bonded and electrostatically bonded with NOR. It had good selective adsorption for NOR, with less interference from acidity of environmental water, coexisting inorganic ions and common antibiotics. When it was applied to adsorb NOR with concentration of 10.0 mg/L in simulated water prepared by environmental water, the highest removal rate was 91%, which indicated that AHA could not only remove all the NOR in the polluted water with complex components at the highest concentration of 630 μg/L, but also its adsorption capacity far exceeded the pollution amount. The research had important practical significance in realizing the recycling of agricultural wastes and the removal of environmental pollution.