Value Of Factor Research Articles

Love waves propagation in layered viscoelastic waveguides characterized by a Zener model

This paper describes a theory of surface Love waves propagating in lossy waveguides consisting of a viscoelastic layer deposited on a semi-infinite elastic substrate. The Zener model to describe the viscoelastic behavior of a medium is used. This simple model captures both the relaxation and retardation. A new form of the unsteady momentum equation for viscoelastic waveguides has been established. By using appropriate boundary conditions, an analytical expression for the complex dispersion equation of Love waves has been deduced. The influence of the loss factor and the ratio of shear moduli of the surface layer on the dispersion curves of Love waves velocity and attenuation is analyzed numerically. The numerical solutions show the dependence of the velocity change and the wave attenuation in terms of the loss factor and the ratio of shear moduli. The obtained results show that the change in the ratio of shear moduli can represent a hardening or softening effect of the surface layer. These effects depend on the loss factor value of the surface layer. In addition, these results are novel, fundamental and can be applied in the characterization of the viscoelastic properties of soft biomaterials and tissues, in nondestructive testing of materials, in geophysics and seismology. Thus, the obtained complex dispersion equation can be very useful to interpret the experimental measurements of Love waves properties in viscoelastic waveguides.

Ligand based-design of potential schistosomiasis inhibitors through QSAR, homology modeling, molecular dynamics, pharmacokinetics, and DFT studies

ObjectivesSchistosomiasis, a neglected tropical disease, is a leading cause of mortality in affected geographic areas. Currently, because no vaccine for schistosomiasis is available, control measures rely on widespread administration of the drug praziquantel (PZQ). The mass administration of PZQ has prompted concerns regarding the emergence of drug resistance. Therefore, new therapeutic targets and potential compounds are necessary to combat schistosomiasis. MethodsTwenty-four potent derivatives of PZQ were optimized via density functional theory (DFT) at the B3LYP/6-31G∗ level. Quantitative structureactivity relationship (QSAR) models were generated and statistically validated, and a lead candidate was selected to develop therapeutic options with improved efficacy against schistosomiasis. The biological and binding energies of the designed compounds were evaluated. In addition, molecular dynamics; drug-likeness; absorption, distribution, metabolism, excretion, and toxicity (ADMET); and DFT studies were performed on the newly designed compounds. ResultsFive QSAR models were generated, among which model 1 had favorable validation parameters (R2train: 0.957, R2adj: 0.941, LOF: 0.101, Q2cv: 0.906, and R2test: 0.783) and was chosen to identify a lead candidate. Other statistical parameters for the chosen model included variance inflation factor values ranging from 1.242 to 1.678, and a Y-scrambling coefficient (cRp2) of 0.747. Five new compounds were designed with improved predicted activity (ranging from 5.081 to 7.022) surpassing those of both the lead compound and PZQ (predicted pEC50 of 5.545). Molecular dynamics simulation revealed high binding affinity of the proposed compounds toward the target receptor. ADMET and drug-likeness assessments indicated adherence to Lipinski's rule of five criteria, thereby suggesting pharmacological and oral safety. In addition, DFT analysis indicated resistance to electronic alteration during chemical reactions. ConclusionThe proposed compounds exhibited potential drug characteristics, thus indicating their suitability for further investigation to enhance schistosomiasis treatment options.

Predictive Postoperative Inflammatory Response Indicators of Infectious Complications Following Gastrectomy for Gastric Cancer.

Perioperative factors are useful for predicting postoperative infectious complications (PIC) in gastric cancer. Specifically, postoperative inflammatory response indicators (PIRI), [C-reactive protein (CRP) level, body temperature (BT), and white blood cell (WBC) count], are widely used in clinical practice. We investigated predictive factors for PIC, including PIRI, to establish a simple and practical indicator of postoperative complications after gastrectomy. We retrospectively collected clinical data from 200 patients with fStage I-III gastric cancer. Univariate/multivariate analysis was performed to evaluate the relationship of predictive factors [host factors, clinicopathological factors, and PIRI (BT, WBC count, and CRP level on postoperative day (POD) 1 and 3) ]. Cut-off values of the predictive factors were analyzed using receiver operating characteristic (ROC) curve modulated by the presence/absence of PIC Grade II, III (Clavien-Dindo classification). Age [Odds ratio (OR): 5.67], smoking history (OR: 3.51), and CRP level (OR: 5.65), WBC count (OR: 8.96), and BT (OR: 3.37) on POD3 were selected as independent factors from multivariate analysis. Cut-off values were 77 years, 14.8 mg/dL, 116.0×102/μL, and 37.4°C, respectively. Predictive factors relative to PIC in gastric cancer were CRP level ≥ 14.8 mg/dL, WBC count ≥ 116.0×102/μL, and BT ≥ 37.4°C all on POD3. Age ≥ 77 years, and history of smoking were relative to PIC, suggesting a simple and practical indicator applicable in clinical practice.

Value of serum brain-derived neurotrophic factor and glial fibrillary acidic protein for detecting depression in patients with Helicobacter pylori infection

ObjectiveInfection with helicobacter pylori (H. pylori) is associated with depression, and depression can affect the outcome of H. pylori treatment. This study aimed to evaluate the value of serum brain-derived neurotrophic factor (BDNF) and glial fibrillary acidic protein (GFAP) for predicting depression in H. pylori-positive patients. MethodA total of 82H. pylori-positive and 82H. pylori-negative patients were recruited for this study. All patients underwent neuropsychological and gastrointestinal assessments and blood sampling. BDNF and GFAP levels were measured in serum. The least absolute shrinkage and selection operator (LASSO) model was used to determine a composite marker. ResultsH. pylori-positive patients showed significantly increased serum GFAP levels and significantly decreased serum BDNF levels compared to H. pylori-negative patients. Among H. pylori-positive patients, serum levels of gastrin 17 (G-17), pepsinogen (PG) I/PGII, BDNF, and GFAP, as well as Gastrointestinal Symptom Rating Scale (GSRS) scores, were significantly correlated with Hamilton Depression Scale (HAMD-24) overall scores and factor scores. Interactions between serum BDNF/GFAP and gastrointestinal serum indices or GSRS scores were significantly associated with HAMD-24 scores in H. pylori-positive patients. The LASSO model indicated that the combination of serum BDNF, GFAP, and G-17 and GSRS scores could identify H. pylori-positive patients with depression with an area under the curve of 0.879. ConclusionCirculating changes in BDNF and GFAP were associated with the occurrence of depression in H. pylori-positive patients. A composite marker including neural and gastrointestinal function-related indices may be of value for identifying depression among H. pylori-positive patients.

Role of substrate temperature on the performance of BaTiO3/Si photodetector prepared by pulsed laser deposition

In this study, the pulsed laser deposition (PLD) method was employed to fabricate nanostructured BaTiO3 films on glass and silicon substrates at varying temperatures. The structural analysis confirmed the formation of crystalline nanostructured BaTiO3 with mixed tetragonal and hexagonal phases, and the film deposited at 150 °C has the best crystallinity and largest particle size. The optical energy gap of the BaTiO3 nanostructure decreases from 3.94 to 3.84 eV, with increasing substrate temperature from 60 to 150 °C. Photoluminescence spectra of BaTiO3 films deposited at 25, 60, 100, and 150 °C exhibit emission peaks centered at 450, 512, 474, and 531 nm, respectively. Raman spectra of BaTiO3 films show E (LO), A (TO), E (LO) + TO, and B1 vibration modes. Hall measurements reveal that the mobility of the BaTiO3 film increases with temperature up to 100 °C and then decreases at 150 °C. The current–voltage characteristics of the BaTiO3/p-Si heterojunction, deposited over a temperature range of 25 to 150 °C, were investigated in the dark and under illumination. The heterojunctions exhibit rectifying properties, with the best rectification factor observed for the heterojunction prepared at 100 °C. The values of the ideality factor for the heterojunctions fabricated at 25, 60, 100, and 150 °C were 4.3, 3.8, 2.8, and 5, respectively. The study reveals an improvement in both the figures of merit and the photodetector performance with increased substrate temperature. The responsivity increases from 2.2 to 9.25 A/W as the deposition temperature rises from 25 to 100 °C. The detectivity (D*) and external quantum efficiency (EQE) of the photodetector prepared at the optimum substrate temperature of 100 °C, were found to be 4.62 × 1012 Jones and 114%, respectively, at 500 nm.

Melting and heat generating influences on radiative flow of two-phase magneto-Williamson nanofluid via stretchable surface with slippage velocity and activation energy

Melting heat and solutal transference in a magnetohydrodynamic flowing of Williamson nanofluid have been described, with the mathematical model guided by Arrhenius activation energy, chemically reactive species, and convective boundary restrictions. By implementing suitable similarity conversions, the regulating equations of partial differential equations (PDEs) (formed by continuity, impetus, energy, and concentricity components) are condensed to an arrangement of ordinary differential equations (ODEs). These commonalities are in nonlinear form, which includes the fluid’s velocity, heat, and concentration changes. Finally, the standard Keller box approach is used to solve this ODEs system computationally (KBM). Under the influence of regulating parameters, the computational results are tallied and displayed in suitable diagrams. The friction force factor, local Nusselt, and Sherwood values are tabulated. Furthermore, the velocity, energy, and concentration contours are plotted versus fluid thickness. The attributes of Williamson nanofluid flowing, melting heat transfer, and mass transference are debated in depth toward the end of this study. Among the most important outcomes that have been reached is that the rate of heat and solutal transport heightened between 52.5 and 55.2% by detraction of the magnetic field, Weissenberg number, and Brownian motion. We also found that there is an inverse relationship between the mass transmission and heat generating factor.

Traceability and reuse mechanisms, the most important properties of model transformation languages

ContextDedicated model transformation languages are claimed to provide many benefits over the use of general purpose languages for developing model transformations. However, the actual advantages and disadvantages associated with the use of model transformation languages are poorly understood empirically. There is little knowledge and even less empirical assessment about what advantages and disadvantages hold in which cases and where they originate from. In a prior interview study, we elicited expert opinions on what advantages result from what factors surrounding model transformation languages as well as a number of moderating factors that moderate the influence.ObjectiveWe aim to quantitatively asses the interview results to confirm or reject the influences and moderation effects posed by different factors. We further intend to gain insights into how valuable different factors are to the discussion so that future studies can draw on these data for designing targeted and relevant studies.MethodWe gather data on the factors and quality attributes using an online survey. To analyse the data and examine the hypothesised influences and moderations, we use universal structure modelling based on a structural equation model. Universal structure modelling produces significance values and path coefficients for each hypothesised and modelled interdependence between factors and quality attributes that can be used to confirm or reject correlation and to weigh the strength of influence present.ResultsWe analyzed 113 responses. The results show that the MTL capabilities Tracing and Reuse Mechanisms are most important overall. Though the observed effects were generally 10 times lower than anticipated. Furthermore, we found that moderation effects need to be individually assessed for each influence on a quality attribute. The moderation effects of a single moderating variable vary significantly for each influence, with the strongest effects being 1000 times higher than the weakest.ConclusionThe empirical assessment of MTLs is a complex topic that cannot be solved by looking at a single stand-alone factor. Our results provide clear indication that evaluation should consider transformations of different sizes and use-cases that go beyond mapping one elements attributes to another. Language development on the other hand should focus on providing practical, transformation specific reuse mechanisms that allow MTLs to excel in areas such as maintainability and productivity compared to GPLs.

Antimicrobials in Eisenia fetida earthworms: A comprehensive study from method development to the assessment of uptake and degradation

In this work, an accurate analytical method was developed for the simultaneous analysis of twenty-seven antimicrobials (AMs) in earthworms using liquid chromatography coupled to a triple quadrupole mass spectrometry detector (UHPLC-MS/MS). Adequate apparent recoveries (80–120 %) and limits of quantification (LOQ) (1 μg·kg−1 - 10 μg·kg−1) were obtained, with the exception of norfloxacin (34 μg·kg−1). The method was applied to evaluate the accumulation of sulfamethazine (SMZ) and tetracycline (TC) in earthworms after performing OECD-207 toxicity test, in which Eisenia fetida (E. fetida) organisms were exposed to soils spiked with 10 mg·kg−1, 100 mg·kg−1 or 1000 mg·kg−1 of SMZ and TC, individually. The results confirmed the bioaccumulation of both AMs in the organisms, showing a greater tendency to accumulate SMZ since higher bioconcentration factor values were obtained for this compound at the exposure concentrations tested. In addition, the degradation of both AMs in both matrices, soils and earthworms was studied using liquid chromatography coupled to a q-Orbitrap high resolution mass spectrometry detector. Thirteen transformation products (TPs) were successfully identified, eight of them being identified for the first time in soil/earthworm (such as 4-Amino-3-chloro-n-(4,6-dimethylpyrimidin-2-yl)benzenesulfonamide or 4-(dimethylamino)-1,11,12a-trihydroxy-6,6-dimethyl-3,7,10,12-tetraoxo-3,4,4a,5,5a,6,7,10,12,12a-decahydrotetracene-2-carboxamide, among others) and their formation/degradation trend over time was also studied. Regarding the biological effects, only SMZ caused changes in earthworm growth, evidenced by weight loss in earthworms exposed to concentrations of 100 mg·kg−1 and 1000 mg·kg−1. Riboflavin decreased at all concentrations of SMZ, as well as at the highest concentration of TC. This indicates that these antibiotics can potentially alter the immune system of E. fetida. This research represents a significant advance in improving our knowledge about the contamination of soil by AM over time. It investigates the various ways in which earthworms are exposed to AMs, either by skin contact or ingestion. Furthermore, it explores how these substances accumulate in earthworms, the processes by which earthworms break them down or metabolise them, as well as the resulting TPs. Finally, it examines the potential effects of these substances on the environment.

Screening of representative rainfall event series for long-term hydrological performance evaluation of grassed swales.

Evaluation of the hydrological performance of grassed swales usually needs long-term monitoring data. At present, suitable techniques for simulating the hydrological performance using limited monitoring data are not available. Therefore, current study aims to investigate the relationship between saturated hydraulic conductivity (Ks) fitting results and rainfall characteristics of various events series length. Data from a full-scale grassed swale (Enschede, the Netherlands) were utilized as long-term rainfall event series length (95 rainfall events) on the fitting outcomes. Short-term rainfall event series were extracted from these long-term series and used as input in fitting into a multivariate nonlinear model between Ks and its influencing rainfall indicators (antecedent dry days, temperature, rainfall, rainfall duration, total rainfall, and seasonal factor (spring, summer, autumn, and winter, herein refer as 1, 2, 3, and 4). Comparison of short-term and long-term rainfall event series fitting results allowed to obtain a representative short-term series that leads to similar results with those using long-term series. A cluster analysis was conducted based on the fitting results of the representative rainfall event series with their rainfall event characteristics using average values of influencing rainfall indicators. The seasonal index (average value of seasonal factors) was found to be the most representative short rainfall event series indicator. Furthermore, a Bayesian network was proposed in the current study to predict if a given short-term rainfall event series is representative. It was validated by a data series (58 rainfall events) from another full-scale grassed swale located in Utrecht, the Netherlands. Results revealed that it is quite promising and useful to evaluate the representativeness of short-term rainfall event series used for long-term hydrological performance evaluation of grassed swales.

Deep Learning-Based Carbon Emission Forecasting and Peak Carbon Pathways in China’s Logistics Industry

As a major energy-consuming industry, energy conservation and emission reduction in the logistics industry are critical to China’s timely achievement of its dual-carbon goals of “carbon peaking” by 2030 and “carbon neutrality” by 2060. Based on deep learning, Random Forest (RF) was used to screen out the key factors affecting carbon emissions in the logistics industry, and the Whale Algorithm-optimized Radial Basis Function Neural Network (WOA-RBF) was proposed. The Monte Carlo simulation predicted the future evolution trends of each key factor under the three scenarios of baseline scenario (BAU), policy regulation scenario (PR), and technological breakthrough scenario (TB) and accurately predicted the carbon emission trends of the logistics industry from 2023 to 2035 by using the most probable future values of each influencing factor as inputs to the WOA-RBF prediction model. The results of the study demonstrate that fixed asset investment (LFI), population (P), total energy consumption (E), energy consumption per unit of value added of the logistics industry (EIL), share of oil consumption (OR), and share of railway freight turnover (RTR) are the key factors influencing the logistics industry’s carbon emissions. Monte Carlo simulations can effectively reflect the uncertainty of future changes in these key factors. In comparison to the BAU and PR scenarios, the TB scenario, with the combined incentives of national policy regulation and technology innovation, is the most likely for the logistics industry to meet the “Peak Carbon” goal baseline scenario.

Identification and treatment of persistent small airway dysfunction in paediatric patients with asthma: a retrospective cohort study

BackgroundAsthma is a common respiratory disease. In asthma, the small airways have more intensive inflammation and prominent airway remodelling, compared to the central airways. We aimed to investigate the predictive value of risk factors and the fractional concentration of exhaled nitric oxide (FeNO) for persistent small airway dysfunction (p-SAD), and compare the effects of different treatment modalities.MethodsThis retrospective cohort study included 248 children with asthma (aged 4–11 years). Binary logistic regression was used to analyse the risk factors for p-SAD. Correlations among FEV1/FVC, small airway function parameters, and FeNO levels in patients with asthma were analysed using Spearman’s rank correlation. The receiver operating characteristic curve and the Delong test were used to analyse the predictive value of FeNO for p-SAD. Differences in the treatment effects of inhaled corticosteroids (ICS) and ICS with a long-acting beta-agonist (ICS/LABA) on p-SAD were analysed using Fisher’s exact test.ResultsAsthmatic children with older age of receiving the regular treatment (OR 1.782, 95% CI 1.082–2.935), with younger age at the time of onset of suspected asthma symptoms (OR 0.602, 95% CI 0.365–0.993), with longer duration of using ICS or ICS/LABA (OR 1.642, 95% CI 1.170–2.305) and with worse asthma control (OR 3.893, 95% CI 1.699–8.922) had increased risk for p-SAD. Significant negative correlations of small airway function parameters with FeNO at a 200 mL/s flow rate (FeNO200), and the concentration of nitric oxide in the alveolar or acinar region (CaNO) were observed. The areas under the curve of FeNO200 (cut-off:10.5ppb), CaNO (cut-off:5.1ppb), and FeNO200 combined with CaNO were 0.743, 0.697, and 0.750, respectively, for asthma with p-SAD. After using ICS or ICS/LABA, switching to ICS/LABA was easier than continuing with ICS to improve small airway dysfunction (SAD) in the 8th month.ConclusionsPaediatric asthma with p-SAD is associated with older age at receiving regular treatment, younger age at the time of onset of suspected asthma symptoms, longer duration of using ICS or ICS/LABA, worse asthma control, and higher FeNO200 and CaNO levels, all of which can be combined with small airway function indicators to distinguish p-SAD from asthma. ICS/LABA improves SAD better than ICS alone.

Chiral separation of terbutaline by supercritical fluid chromatography with peak purity determination by UPLC–MS and modeling for chiral recognition mechanism

AbstractBACKGROUNDTerbutaline is the drug of choice for asthma patients but it exists in racemic mixture. (R)‐(−)‐terbutaline is 200 times more active than (S)‐(+)‐terbutaline yet it is not advisable to prescribe racemic mixture due to certain adverse effects of (S)‐(+)‐terbutaline. Therefore, a fast, effective and reproducible separation method is necessary.RESULTSChiral separation was achieved on Chiralpak‐IE and Chiralpak‐IG columns (250 × 4.6 mm, 5 μm) using carbon dioxide‐methanol (CO2‐MeOH, 60:40) with a 0.2% triethylamine mobile phase. The flow was 1.0 mL min−1 with detection at 223 nm using a photodiode array (PDA) detector. The values of retention, separation and resolution factors were in the ranges 1.88–2.38, 1.14–1.26 and 0.91–1.17, respectively; with best separation with Chiralpak‐IE. The tailing factors and number of theoretical plates were in the range of 1.0–1.23 and 487–3699. The purity of the separated peaks was determined by ultra‐performance liquid chromatography–mass spectrometry (UPLC–MS); indicating 100% purity of the peaks. The chiral recognition was determined by modeling with binding affinities −5.0 and −6.0 for S‐ and R‐enantiomers, respectively; indicating S‐enantiomer elution first followed by R‐enantiomers. The major forces responsible for the chiral resolution were hydrogen bonding and π‐π interactions.CONCLUSIONOwing to the great demand for optically active pure drugs and high economic pressure on analytical techniques, the chiral separation of terbutaline was achieved via inexpensive supercritical fluid chromatography. The reported method may be used to prepare optically active pure terbutaline drugs (R‐enantiomers) at a pilot scale. © 2024 Society of Chemical Industry (SCI).

Enhanced heat transfer and fluid motion in 3D nanofluid with anisotropic slip and magnetic field

Abstract A mathematical model is envisaged that discusses the motion of 3D nanofluids (NFs) with anisotropic slip influence magnetic field past a stretching sheet. The heat transportation phenomenon is analysed by melting effect, heat generation, and chemical reaction. The main motivation of this study is to analyse the behaviour of liquid motion and heat transfer (HT) of NFs because this study has huge applications in boiling, solar energy, and micropower generation, which are used in the engineering process. The physical governing partial differential equation is transformed into a coupled non-linear system of ordinary differential equations using suitable appropriate transformations. The translated equations are calculated using Runge–Kutta–Fehlberg method via shooting procedure. The physical characteristics of various parameters on velocities, concentration, and thermal fields are explored in detail. The HT is high in NFs when compared to pure or regular liquids for ascending values of heat source parameter and slip factor. Also, the skin friction coefficients via coordinate axes and rate of Nusselt number were analysed.

Comparison of the neutronic properties of the (Th-233U)O2, (Th-233U)C, and (Th-233U)N fuels in small long-life PWR cores with 300, 400, and 500 MWth of power

Abstract The neutronic characteristics of (Th-233U)O2, (Th-233U)C, and (Th-233U)N have been compared in small long-life pressurized water reactors (PWRs). Neutronic calculations were carried out at 300 MWth, 400 MWth, and 500 MWth with two cladding types: zircaloy-4 and ZIRLO (Zr low oxygen). They were performed using the Standard Reactor Analysis Code (SRAC) and JENDL-4.0 nuclide data, dividing the reactor core into three fuel zones with varying 233U enrichment levels, ranging from 3% to 9% and fluctuating by 1%, employing the PIJ module at the fuel cell level and the CITATION module at the reactor core level. In addition, 231Pa was added as burnable poison (BP). The (Th-233U)N fuel demonstrated superior criticality compared to the other fuel types, as it consistently achieves critical conditions throughout the reactor’s operating cycle with excess reactivity <1.00% dk/k for several fuel configurations at the 300 MWth and 400 MWth power levels. Moreover, the (Th-233U)N and (Th-233U)C fuels exhibited similar and flatter power density distribution patterns compared to the (Th-233U)O2 fuel. The power peaking factor (PPF) value was relatively higher for (Th-233U)O2 fuel than the other two fuels. The (Th-233U)N fuel exhibited the most negative Doppler coefficient, followed by (Th-233U)C and (Th-233U)O2 fuels. Analysis of burnup levels revealed that the (Th-233U)O2 fuel achieved significantly higher burnup than the other two fuels.

Pion-photon and kaon-photon transition distribution amplitudes in the Nambu–Jona-Lasinio model* *Supported by the Scientific Research Foundation of Nanjing Institute of Technology (YKJ202352), the Natural Science Foundation of Jiangsu Province, China (BK20191472), and the China Postdoctoral Science Foundation (2022M721564)

The Nambu–Jona-Lasinio model is utilized to investigate the pion- and kaon-photon leading-twist transition distribution amplitudes using proper time regularization. Separately, the properties of the vector and axial vector pion-photon transition distribution amplitudes are examined, and the results meet the desired properties. Our study involves sum rule and polynomiality condition. The vector and axial vector pion-photon transition form factors that are present in the process are the first Mellin moments of the pion-photon transition distribution amplitudes. The vector transition form factor originates from the internal structure of hadrons, the axial current can be coupled to a pion, this pion is virtual, and its contribution will be present independently of the external hadrons. The kaon transition form factors are similar. The vector form factor's value at zero momentum transfer is determined by the axial anomaly, while this is not the case for the axial one. The vector and axial form factors, as well as the neutral pion vector form factor , are depicted. According to our findings, the pion axial transition form factor is harder than the vector transition form factor and harder than the electromagnetic form factor. We also discuss the link between and transitions distribution amplitudes.

Pengaruh Faktor Motivasi Dan Persepsi Pengunjung Terhadap Keputusan Pembelian Tiket Pada Konser Act: Sweet Mirage In Jakarta

This research aims to explore the motivational factors and perceptions of visitors influencing ticket purchasing decisions for the music concert titled Act: Sweet Mirage In Jakarta, featuring the South Korean group TOMORROW X TOGETHER. The study involved a sample of 87 respondents and utilized a quantitative analysis research method with data collected through questionnaires. The multiple linear regression analysis results indicated a regression coefficient value of 0.222 for motivational factors, showing a positive and significant impact on purchasing decisions. Additionally, the regression coefficient value for visitor perception factors was 0.630, indicating a positive impact on purchasing decisions. Both variables collectively influence the ticket purchasing decision for the Act: Sweet Mirage In Jakarta concert, as evidenced by the computed F-value of 8.847, which exceeds the critical F-value of 3.11.

Multi-collinearity in Research and Wayforward

In multi-linear regression, there will be two or more independent variables also known as predictor variables. The main task in multi-linear regression is to find how the predictor variable impacts the dependent variable when there is a change in predictor variables by one unit. However, without testing multi-co linearity between these predictor variables, such a model will create difficulties in terms of defining the real impact of the predictor variable (independent) on the predicted variable (dependent). This situation makes us aware in terms of variable selection while conducting multi-linear regression to find the exact impact. To explain this issue, 14 students were selected and asked to fill up the form with their marks obtained in the recent examination, the number of study hours at home, the number of hours hanging out with friends, and the number of copies added during an exam. The research aimed to observe if there is a multi-co linearity issue between predictor variables (number of study hours, number of hours hanging out with friends, and number of copies added during an exam). SPSS-version 25 is used to find a correlation matrix between predictor variables, matrix scatter plot, the value of Tolerance, Variance Inflation Factor (VIF) value, condition index, and variation proportion. Multi-co linearity issue observed in two predictor variables thus further solution explained.

Validation and identification of anoikis-related lncRNA signatures for improving prognosis in clear cell renal cell carcinoma.

Clear cell carcinoma (ccRCC) usually has a high metastasis rate and high mortality rate. To enable precise risk stratification, there is a need for novel biomarkers. As one form of apoptosis, anoikis results from the disruption of cell-cell connection or cell-ECM attachment. However, the impact of anoikis-related lncRNAs on ccRCC has not yet received adequate attention. The study utilized univariate Cox regression analysis in order to identify the overall survival (OS) associated anoikis-related lncRNAs (ARLs), followed by the LASSO algorithm for selection. On this basis, a risk model was subsequently established using five anoikis-related lncRNAs. To dig the inner molecular mechanism, KEGG, GO, and GSVA analyses were conducted. Additionally, the immune infiltration landscape was estimated using the ESTIMATE, CIBERSORT, and ssGSEA algorithms. The study constructed a novel risk model based on five ARLs (AC092611.2, AC027601.2, AC103809.1, AL133215.2, and AL162586.1). Patients categorized as low-risk exhibited significantly better OS. Notably, the study observed marked different immune infiltration landscapes and drug sensitivity by risk stratification. Additionally, the study preliminarily explored potential signal pathways associated with risk stratification. The study exhibited the crucial role of ARLs in the carcinogenesis of ccRCC, potentially through differential immune infiltration. Furthermore, the established risk model could serve as a valuable stratification factor for predicting OS prognosis.

Application of text mining and coupling theory to depth cognition of aviation safety risk

Aviation accidents have attracted a lot of attention due to the fatalities and considerable property loss. The complexity underlying these accidents is often the result of multiple risk factors coupling together, thereby increasing the difficulty of risks identification and comprehensive controlling. It is necessary to enhance proactive safety management capabilities and aircraft operational reliability through deeply cognitive risk information. This paper explores the application of Latent Dirichlet Allocation (LDA) model of text mining and coupling theory in two aviation safety datasets. The results of applying LDA topic modeling categorize risks across different datasets. Subsequently, the N-K model is employed to measure various coupling modes of risk factors, and the coupling effects between different risk factors were further analyzed. The results indicate that the two datasets identify different risk categories, and the coupling values of the risk factors usually increase with the number of factors. The results also reveal a higher degree of coupling among three risk factors: pilot manipulation, aircraft systems, and aircraft engines in the NTSB dataset. The proposed methodology shows significance in enhancing the accuracy of aviation risk analysis and the efficiency of accident prevention.

Extraction of Rare Earth Elements from Chloride Solutions Using Mixtures of P507 and Cyanex 272

In this study, the extraction of rare earth elements (REEs) from chloride solutions after leaching REE carbonate concentrate with solutions of the mixtures of P507 (2-ethylhexylphosphonic acid mono-2-ethylhexyl ester) and Cyanex 272 (bis(2,4,4-trimethylpentyl)phosphinic acid) (1:1) at various concentrations was experimentally studied. It was shown that the distribution ratios of all REEs decrease with the increasing concentration of these metals in the initial solution, which is associated with the loading of the organic phase. The most significant improvement in the extraction is observed for the heavy group of rare earth elements. The extractability of REEs increases with the increasing atomic number of the element, as is typical for the extraction of these metals with acidic organophosphorus extractants. The data obtained show that the separation factors of adjacent rare earth elements decrease slightly with the increasing concentration of metals in the initial aqueous solution. Increasing the concentration of the extractant mixture does not have a significant effect on the values of the adjacent REE separation factors. The data obtained on the distribution ratios and separation factors made it possible to propose a flow sheet for the separation of rare earth elements with the production of Y, Ho, Tb and Dy.