Least-squares Research Articles

Enhanced Lissajous-based algorithm for phase-measuring in two-step phase-shifting fringe projection profilometry

Two-step phase-shifting profilometry is widely used in many applications due to its good trade-off between measurement resolution and efficiency. In this technique, however, it is not easy to accurately calculate fringe phases from only two available fringe patterns, especially when these patterns have nonuniform or even discontinuous background intensities, modulations, or fringe phases. To solve this problem, we propose in this paper an enhanced Lissajous-based algorithm. With it, intensity pairs within the neighborhood of a point form a Lissajous trajectory if their backgrounds and modulations are assumed to be constant. Fitting this Lissajous curve enables us to roughly estimate fringe phase at this point, and a linearized algorithm is suggested here for alleviating the computational complexity. After that, we provide a least-squares method to correct the errors caused by the uneven background intensities by modeling them as linearly varying values within the neighborhood. Further, from the residuals of the above step, the edges and discontinuities in the fringe patterns, where a piecewise algorithm generally have large errors, can be detected. The fringe phases at these edges are recalculated by using forward or backward extrapolations. Simulation and experimental results demonstrate this proposed algorithm to have a relatively high measurement accuracy in two-step phase-shifting fringe projection profilometry.

Switching treatment to cipaglucosidase alfa plus miglustat positively affects patient-reported outcome measures in patients with late-onset Pompe disease.

Late-onset Pompe disease (LOPD), a rare autosomal recessive multisystemic disorder, substantially impacts patients' day-to-day activities, outcomes, and health-related quality of life (HRQoL). The PROPEL trial compared cipaglucosidase alfa plus miglustat (cipa+mig) with alglucosidase alfa plus placebo (alg+pbo) in adult patients with LOPD over 52weeks and showed improved motor and respiratory function in patients switching treatment from standard-of-care enzyme replacement therapy (ERT) to cipa+mig at baseline. This study evaluated the impact of cipa+mig on patient-reported outcomes (PROs), including HRQoL in ERT-experienced patients, using data from PROPEL. PROs evaluated included the Subject's Global Impression of Change (SGIC), Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function Short Form 20a, PROMIS Fatigue Short Form 8a, Rasch-built Pompe-specific Activity (R-PAct), and European Quality of Life-5 Dimensions 5 Response Levels (EQ-5D-5L). The proportions of responders in the cipa+mig arm and the alg+pbo arm were compared via chi-squared or Fisher's exact test (patient-level responder analysis), and least squares (LS) mean differences were calculated for change from baseline at Week 52 of the PRO measures (group-level analysis). At Week 52, patient-level SGIC responder and group-level SGIC analyses favored cipa+mig compared with alg+pbo across all SGIC domains (e.g. 90 vs. 59% responders in the cipa+mig vs. the alg+pbo group for SGIC ability to move around; P = 0.0005; and LS mean difference 0.385; P = 0.02). Similarly, PROMIS Physical Function and Fatigue domains numerically favored cipa+mig in both analyses (e.g. 50 vs. 40% responders in the cipa+mig vs. alg+pbo arm for PROMIS Physical Function; P = 0.37; and LS mean difference 3.1; P = 0.11). R-PAct for both treatment groups was similar in the patient-level responder analysis, but numerically favored alg+pbo in the group-level analysis (35% responders in both arms; P = 0.95; and LS mean difference -0.8; P = 0.48). Self-care, usual activities, and depression/anxiety domains of EQ-5D-5L numerically favored cipa+mig in both analyses (e.g. 20 vs. 12% responders in the cipa+mig vs. alg+pbo arm for EQ-5D-5L self-care; P = 0.54; and LS mean difference -0.108; P = 0.52). Overall, switching treatment from alglucosidase alfa to cipa+mig positively impacted PRO measurements during the double-blind period of PROPEL. NCT03729362; Registration date: November 1, 2018; https://clinicaltrials.gov/study/NCT03729362.

Abstract 4136334: Treatment Satisfaction With an “Inclisiran First” Implementation Strategy Versus Usual Care in Patients With Atherosclerotic Cardiovascular Disease

Background: Despite the availability of effective lipid-lowering therapies (LLTs), most patients (pts) with ASCVD do not meet guideline-recommended LDL-C goals. In VICTORION-INITIATE (NCT04929249), an “inclisiran first” (IF) strategy of adding inclisiran immediately on failure to achieve LDL-C <70 mg/dL, despite maximally tolerated statin therapy, in pts with ASCVD led to significantly higher LDL-C goal attainment vs usual care (UC) at Day 330. Objective: To evaluate change from baseline to Day 330 in pt-reported treatment satisfaction with an IF implementation strategy vs UC in pts with ASCVD enrolled in VICTORION-INITIATE. Methods: VICTORION-INITIATE, a Phase 3b, open-label, prospective trial, was conducted at 45 representative clinical sites across 20 US states. Pts randomized 1:1 (stratified by insurance status) received inclisiran 284 mg (300 mg inclisiran sodium) at Days 0, 90, and 270 plus UC or UC alone (lipid management directed by treating physicians). We evaluated change from baseline to Day 330 in pt-reported satisfaction with IF vs UC using the validated 11-question Treatment Satisfaction Questionnaire for Medication (TSQM)-II comprising 4 domains (effectiveness, side effects, convenience, and global satisfaction) scored from 0–100. As a post-hoc analysis of a pre-specified exploratory endpoint, we analyzed the difference in least-squares (LS) mean change in TSQM-II domain scores for IF vs UC using ANCOVA with baseline scores as a covariate. Results: We randomized 450 patients: median age 67 years, 30.9% female, 25.8% with a history of statin intolerance. From baseline to Day 330, difference in LS mean change (95% confidence interval) in TSQM-II scores for IF (n=139) vs UC (n=105) was significant (p<0.001) for effectiveness (10.4 [5.4, 15.5]), convenience (10.5 [5.8, 15.2]), and global satisfaction (12.1 [7.2, 16.9]). Statistical comparison was not applicable for the side effects domain at Day 330 due to the small sample size (IF: n=6, UC: n=7). On Day 330, mean scores for IF exceeded UC for each TSQM-II question (Figure). Conclusions: An IF implementation strategy resulted in significantly greater change from baseline to Day 330 across multiple domains of pt-reported treatment satisfaction vs UC.

A Comparison of Battery Equivalent Circuit Model Parameter Extraction Approaches Based on Electrochemical Impedance Spectroscopy

This paper presents three approaches to estimating the battery parameters of the electrical equivalent circuit model (ECM) based on electrochemical impedance spectroscopy (EIS); these approaches are referred to as (a) least squares (LS), (b) exhaustive search (ES), and (c) nonlinear least squares (NLS). The ES approach is assisted by the LS method for the rough determination of the lower and upper bound of the ECM parameters, and the NLS approach is incorporated with the Monte Carlo run such that different initial guesses can be assigned to improve the goodness of EIS fitting. The proposed approaches are validated using both simulated and real EIS data. Compared to the LS approach, the ES and NLS approaches show better fitting accuracy at various noise levels, whereas in both the validation using simulated EIS data and actual EIS data collected from LG 18650 and Molicel 21700 batteries, the NLS approach shows better fitting accuracy than that of LS and ES approaches. In all cases, compared with the ES approach, the computational time of the NLS approach is significantly faster, and compared with the LS approach, the NLS approach shows a minimal difference in computational time and considerably better fitting performance.

Synergistic Effect of Influence Factors on Ammonia Volatilization in Fertilizer Solution: A Laboratory Experiment

Ammonia volatilization, which is one of the main ways that nitrogen gas is released from farmland, restricts promotion of the utilization of nitrogen fertilizer and contains some potential environmental risks. To investigate the general pattern of ammonia volatilization under actual paddy field conditions, we designed an indoor simulated system to measure the amount of ammonia volatilized within a single time period by controlling the pH and concentration of NH4+ (c(NH4+)) in the solution, the gas–liquid interfacial gas velocity, and the ambient temperature. In this paper, the influence of these factors, the synergistic effect on ammonia volatilization, and their quantitative relationship are discussed. We used solutions of ammonium bicarbonate (SAB) and diammonium phosphate (SDP) for the simulation experiments, and the results showed that there is a significant linear relationship between the amount of ammonia volatilization and c(NH4+). The correlation coefficients were between 0.9214 to 0.9897 and 0.8932 to 0.9904 for SAB and SDP, respectively. The quantitative relationship between temperature and pH and the influence factor (CIF) and the initial ammonia volatilization fluxes (IAVFs) was analyzed by the least-squares method, and the degrees of polynomial were one and two, respectively. The regression equations of the SAB and SDP among the amount of ammonia volatilization with the concentration of ammonium nitrogen, the temperature, and the pH were calculated by using MATLAB. Considering the effects of temperature and pH on the CIF and IAVFs under individual conditions, we used a binary cubic model to fit the relationship between temperature and pH to the CIF and IAVFs. The simulation results showed that the correlation coefficients between the CIF and IAVFs for SAB were 0.9980 and 0.9680, respectively, and the correlation coefficients were 0.9946 and 0.9708 for SDP, respectively. The quantitative equation took into account the coefficient of determination and degrees of polynomial, and the ammonia volatilization fluxes can be calculated by using these equations.

Scaling relations between mass components and rotational velocity in disk galaxies

Abstract In this study, we re-evaluate the baryonic Tully–Fisher relation (BTFR) by analyzing the correlations between maximum rotational velocity and various mass components, including stellar mass, atomic hydrogen (H i) mass, baryonic mass, and dark matter mass in a sample of 141 disk galaxies from the SPARC (Spitzer Photometry and Accurate Rotation Curves) database, augmented by recent data on stellar and dark matter masses. We apply multiple statistical methods, including Monte Carlo orthogonal distance regression (MCODR), Monte Carlo least-squares (MCLS), and traditional least-squares (LS), to assess the impact of different fitting techniques on the derived scaling relations between the mass components (stellar, H i, and dark matter) and maximum rotational velocities of these galaxies. We find that the selection of statistical methods significantly influences the derived slopes and intercepts the relation between maximum rotational velocity and mass components. The MCODR method that accounts for errors in both variables consistently produces steeper slopes, suggesting a stronger correlation between stellar mass and rotational dynamics compared to other methods. In contrast, the MCLS method tends to yield flatter slopes, highlighting the sensitivity of this approach to outliers. Despite the variations in slope and intercept across different methods, the fundamental relation between baryonic mass and rotational velocity remains robust. We have also compared dark matter mass derived from different halo models [NFW (Navarro–Frenk–White) versus combined NFW + Dekel–Zhao profiles] and noted that the slope from the NFW profile is slightly steeper than that from the combined profile, highlighting the sensitivity of scaling relations to the selection of halo model. Overall, this study reinforces the robustness of the BTFR across different mass components in disk galaxies while emphasizing the critical role of statistical methods and dark matter profiles in analyzing galactic dynamics.

Unbiased and reproducible liver MRI-PDFF estimation using a scan protocol-informed deep learning method.

To estimate proton density fat fraction (PDFF) from chemical shift encoded (CSE) MR images using a deep learning (DL)-based method that is precise and robust to different MR scanners and acquisition echo times (TEs). Variable echo times neural network (VET-Net) is a two-stage framework that first estimates nonlinear variables of the CSE-MR signal model, to posteriorly estimate water/fat signal components using the least-squares method. VET-Net incorporates a vector with TEs as an auxiliary input, therefore enabling PDFF calculation with any TE setting. A single-site liver CSE-MRI dataset (188 subjects, 4146 axial slices) was considered, which was split into training (150 subjects), validation (18), and testing (20) subsets. Testing subjects were scanned using several protocols with different TEs, which we then used to measure the PDFF reproducibility coefficient (RDC) at two regions of interest (ROIs): the right posterior and left hepatic lobes. An open-source multi-site and multi-vendor fat-water phantom dataset was also used for PDFF bias assessment. VET-Net showed RDCs of 1.71% and 1.04% on the right posterior and left hepatic lobes, respectively, across different TEs, which was comparable to a reference graph cuts-based method (RDCs = 1.71% and 0.86%). VET-Net also showed a smaller PDFF bias (-0.55%) than graph cuts (0.93%) when tested on a multi-site phantom dataset. Reproducibility (1.94% and 1.59%) and bias (-2.04%) were negatively affected when the auxiliary TE input was not considered. VET-Net provided unbiased and precise PDFF estimations using CSE-MR images from different hardware vendors and different TEs, outperforming conventional DL approaches. Question Reproducibility of liver PDFF DL-based approaches on different scan protocols or manufacturers is not validated. Findings VET-Net showed a PDFF bias of -0.55% on a multi-site phantom dataset, and RDCs of 1.71% and 1.04% at two liver ROIs. Clinical relevance VET-Net provides efficient, in terms of scan and processing times, and unbiased PDFF estimations across different MR scanners and scan protocols, and therefore it can be leveraged to expand the use of MRI-based liver fat quantification to assess hepatic steatosis.

Mathematical Modeling of Biogas Production in Sanitary Landfills

Objective: The objective of this study is to evaluate the biogas production potential in sanitary landfills using the Verhulst mathematical model, which is employed to represent natural phenomena constrained by a saturation point. Theoretical Framework: It was based on references on energy use from waste, possible conversion routes, in addition to mathematical models that estimate the energy potential for biogas generation. Method: The methodology adopted for this research involves the use of data collected in an experimental cell, subsequently applying the De Verhulst model through a regression with minimization of errors using the Least Squares Method (LSM). Results and Discussion: The results indicated that the developed model correlates well with the observed data, demonstrating its suitability as a predictive model for biogas production. Research Implications: The research contributes to the construction of a theoretical framework for the adaptation, elaboration and use of mathematical models to predict the energy potential in the generation of biogas in landfills. Originality/Value: This study contributes to the literature by using a population growth model (Verhulst) to predict landfill biogas production.

Combining long short-term memory and shape superposition for estimating moving load-induced global responses of bridges

Recently, a method of estimating the global responses of bridges was introduced, by combining a deep neural network (DNN) and shape superposition method (SSM). This DNN-SSM model demonstrated superior performance to the traditional estimation method based on the least-squares method. However, the application and validation of this approach have been restricted to static problems. For bridges, the dynamic effect induced by the moving load requires consideration. Therefore, this study proposes a long short-term memory (LSTM)-SSM model to improve the estimation performance for dynamic global responses. The LSTM-SSM model consists of LSTM layers, followed by fully connected DNN layers and a post-process part based on SSM. Limited displacement, slope, and strain data were used as the inputs, and the global displacement, slope, and strain were estimated. To validate the effectiveness and improvement of the LSTM-SSM model, a numerical model of a cable-stayed bridge was used to compare the proposed model with the previously developed DNN-SSM model. The validation results indicated that the LSTM-SSM model can provide more accurate estimates of the dynamic global response than DNN-SSM models. Finally, a technique for structural safety monitoring based on the proposed method was introduced.

Least Squares Learning? Evidence from the Laboratory

We report on an experiment testing the empirical relevance of least squares (LS) learning, a common way of modelling how individuals learn a rational expectations equilibrium (REE). Subjects are endowed with the correct perceived law of motion (PLM) for a price level variable they are seeking to forecast, but do not know the true parameterization of that PLM. Instead, they must choose and can adjust the parameters of this PLM over 50 periods. Consistent with the E-stability of the REE in the model studied, 97.8% of subjects achieve weak convergence to the REE in terms of their price level predictions. However, the number of participants that can be characterized as least squares learners via the adjustments they make to the parameterization of the PLM over time depends on properties of the data generating process of the dependent and independent variables. Participants learn the REE faster, and behave more like least squares learners when there is greater variance in the independent variable of the model. We consider several alternatives to least squares learning and find evidence that many subjects employ a simple satisficing approach.

The Effects of money supply on Economic Growth of Laos

This research aims to analyze the effect of money supply volume on the economic growth of Lao PDR. Using secondary data annually from 2012–2022. which uses the multiple regression equation (multiple regression) with the method of least squares (OLS) to estimate the coefficients of dependent variables and independent variables, starting from checking the properties of the unit root data using the Augmented Dick Fuller test statistic method to test the data. Through checking the properties of the model of external factors that affect the amount of money supply (M2), it was found that the coefficient of decision Adjusted R Square = 0.9931, which means that the independent variables Gross National Income (GNI), Exchange Rate (Exr), and Consumer Price Index (CPI) can explain the variable according to the amount of money (M2) determined up to 99.31%; the rest depends on other factors that are not included in the study. Therefore, the model of external factors that affect the amount of money M2 can be used and depends on at least one factor identified. Also, by bringing the data to test the effect of the independent variable on the dependent variable in the long term and in the short term, ECM(-1) found that the model that simulates the effect of the amount of money M2 on the economic growth of the Lao PDR in the long-term equilibrium state (co-integration) and in the short-term equilibrium state (Error Correction Model: ECM) is not applicable and does not depend on the identified factors. But it will have a long-term effect, which, through checking the properties of the model from a long-term perspective, found that the coefficient of decision Adjusted R Square = 0.6877, which means that the independent variable M2 money can explain the variable according to the economic growth rate determined in the long term up to 68.77%. The change in the money M2 in the short term does not affect the economic growth rate of the Lao PDR, but the change in the money M2 in the long term will definitely affect the economic growth rate.

Consideration of spectral interference in total reflection X-ray fluorescence analysis using a limited number of calibration samples: Case study of ocean polymetallic nodules

A novel approach for quantitative analysis in total-reflection X-ray fluorescence (TXRF) which can be employed for the samples with complex matrices inducing overlapping spectral signals in the scenario of limited availability of standard samples is proposed. The approach is based on the least squares (LS) decomposition of real spectra into the weighted sum of simulated individual element subspectra and requires only a single sample of matrix-matched reference material. Oceanic polymetallic nodules and crusts, having complex mineral matrix and containing high concentrations of overlapping elements, were chosen to demonstrate the feasibility of the approach in quantification of 11 elements. The comparison of the results obtained with LS decomposition, internal standard and linear calibration with three standard samples was performed. It was demonstrated that the performance of the proposed approach and of the linear calibration was better than that of internal standard for most of the elements; however, the proposed method requires only a single standard sample.

Coordinate-Independent 3-D Ultrasound Principal Stretch and Direction Imaging.

In clinical ultrasound, current 2-D strain imaging faces challenges in quantifying three orthogonal normal strain components. This requires separate image acquisitions based on the pixel-dependent cardiac coordinate system, leading to additional computations and estimation discrepancies due to probe orientation. Most systems lack shear strain information, as displaying all components is challenging to interpret. This paper presents a 3-D high-spatial-resolution, coordinate-independent strain imaging approach based on principal stretch and axis estimation. All strain components are transformed into three principal stretches along three normal principal axes, enabling direct visualization of the primary deformation. We devised an efficient 3-D speckle tracking method with tilt filtering, incorporating randomized searching in a two-pass tracking framework and rotating the phase of the 3-D correlation function for robust filtering. The proposed speckle tracking approach significantly improves estimates of displacement gradients related to the axial displacement component. Non-axial displacement gradient estimates are enhanced using a correlation-weighted least-squares method constrained by tissue incompressibility. Simulated and in vivo canine cardiac datasets were evaluated to estimate Lagrangian strains from end-diastole to end-systole. The proposed speckle tracking method improves displacement estimation by a factor of 4.3 to 10.5 over conventional 1-pass processing. Maximum principal axis/direction imaging enables better detection of local disease regions than conventional strain imaging. Coordinate-independent tracking can identify myocardial abnormalities with high accuracy. This study offers enhanced accuracy and robustness in strain imaging compared to current methods.

IMPROVEMENT OF THE ALLOY STRUCTURE OF THE Ni-Cr-Со-W-Mo-Al-Ti-C SYSTEM

Purpose. Establishing the specifics of the influence of alloying elements on the formation of carbides in the structure, their shape and the possibility of separating TLC phases for the system of the Ni-Cr-Co-W-Mo-Al-Ti-C type using the CALPHAD calculation method of prediction in comparison with data obtained by the method of raster electron microscopy. Research methods. The results of experimental and calculated data, formed on the basis of experimental and results taken from open sources, are presented. The chemical composition was determined on a REM-106I scanning electron microscope equipped with an energy dispersive analysis. Experimental values were processed by the method of least squares with obtaining correlation dependencies of the “parameter-property” type and establishing mathematical equations of regression models that optimally describe these dependencies. Results. It was established that when the concentration of titanium is more than 4 % and molybdenum is more than 6 % and 15 % chromium, the formation of TSC phases (Р, s and m- phases) is possible, which reduce the operational properties of the alloy. It was found that when the alloy contains more than 25 % chromium, a solid chromium-based solution is formed, which reduces the properties of the alloy (mechanical and corrosion). It is shown that the obtained dependences correspond to reality and coincide with experimental data at the level of 10 %. Scientific novelty. Obtained dependences of the influence of alloying elements on the chemical composition of carbides will allow predicting properties without conducting experiments. It was established that changes in the course of dependencies are closely correlated with the processes occurring in the structure of alloys. Practical value. The obtained dependencies can be used both for the development of new heat-resistant alloys and for the improvement of the compositions of industrial alloys.

Parameter Identification Method of a Double-Layer Supercapacitor by Using a Real Voltage Source

This article presents a new method for obtaining the electrical parameters of a supercapacitor (SC) modeled as a constant resistor in series with a capacitance that linearly varies with its internal voltage. This model provides sufficiently accurate results when the SC is subjected to rapid, short-term charging and discharging. In other methods described in the literature, the parameters are obtained by charging or discharging the SC with a constant current source of high value. In this study, the electrical parameters are calculated by charging or discharging the cell with a real constant voltage source (RVS) or by discharging the SC through a known and constant resistance. The calculation procedure requires the measurement of the cell voltage as a function of time. Two alternative estimation methods have been employed: the three-point method (3PM) and the least squares method (LSM). A series of experimental tests were conducted on cells from various manufacturers, with capacitances ranging from 150 F to 600 F. The laboratory measurements were then compared with the results obtained from theoretical models incorporating the parameters obtained for the variable capacity model. The results demonstrated that this straightforward procedure is capable of accurately characterizing the main branch of any SC.

The impact of LEP gene polymorphisms located at exon 2 (LEP-HinfI) and intron 2 (LEP-Sau3AI) on growth and reproductive traits in Saanen goats

Abstract. Leptin (LEP), alternatively recognized as the obesity gene, influences food consumption, energy balance, and lipid metabolism. Additionally, it plays a crucial role in energy metabolism, and variations in the LEP gene have been studied extensively among various livestock species. These investigations have unveiled correlations with traits such as meat quality, milk yield and composition, and growth characteristics. Nevertheless, the existing knowledge regarding its correlation with growth and reproductive traits in goats is comparatively limited, particularly when juxtaposed with studies of cattle. Hence, the objective of the current study was to investigate the relationship between polymorphisms in the intron 2 (Sau3AI) and exon 2 (HinfI) regions of the LEP gene and growth and reproductive traits in Saanen goats. The study comprised 185 Saanen goats in total. The PCR-RFLP (polymerase chain reaction restriction fragment length polymorphism) technique was employed to genotype these polymorphisms. Population genetic analysis included the number of effective alleles, heterozygosity, polymorphism information content, and compatibility with the Hardy–Weinberg equilibrium. The general linear model procedure's least-squares methods were used for the statistical analysis. The SNP (single-nucleotide polymorphism) located in exon 2 (LEP-HinfI) was monomorphic. Remarkably, the SNP located in intron 2 (LEP-Sau3AI) was associated with birth weight (p<0.05) and average daily weight gain (p<0.05). In this context, the AA genotype demonstrated higher birth weight and daily live weight gain means compared to other genotypes. No significant differences were observed in litter size, total weight gain, or morphometric measurements. The caprine LEP-Sau3AI polymorphism situated within intron 2 proved influential in traits critical for the profitability and sustainability of goat breeding. The findings of this study provide novel and valuable information for future research on the LEP gene in goats.

Parameter estimation in vapor-liquid equilibrium modeling of compounds related to biodiesel production using opposite point-based differential evolution algorithm.

Biodiesel stands out as the most favorable alternatives to fossil-derived diesel, offering a multitude of environmental benefits. At various stages of biodiesel production, the separation processes necessitate thermodynamic models with the capability to correlate and predict phase equilibria of mixtures. In this study, application of the classical differential evolution (DE) and its new enhanced version, the OPDE algorithm, for modeling vapor-liquid equilibrium (VLE) associated with components related to biodiesel production is presented. The algorithms were analysed and contrasted in terms of their performance, in estimating parameters for Wilson, NRTL and UNIFAC models. Additionally, classical least-squares (LS) and error-in-variable (EIV) approaches were examined and compared. Also, VLE datasets for a specific system have been merged, and parameters have been estimated. The findings suggest that parameters obtained through LS approach align with those reported in literature, indicating faster convergence in all problems. In contrast, the EIV approach achieved a higher objective function value compared to the LS approach, exhibiting low deviation. OPDE outperformed DE in terms of performance. The enhancement in RMSTD value has been found within range 91%-99% for EIV approach. Further, novel findings derived from some of the studied VLE datasets are presented.

Entrepreneurial Intention in Romanian Engineering Students: Expanding the Theory of Planned Behavior

This study analyzes the entrepreneurial intention of Romanian engineering students. We had a sample of 700 students (mean age = 23.14; SD = 2.92; 378 males and 322 females) who belonged to three technical universities and completed an online survey between October and December 2023. This research extends the theory of planned behavior (TPB) to explore the factors influencing students’ entrepreneurial intentions. In addition to base TPB components, such as attitude, normative and perceived behavioral control factors, we considered curiosity and well-being. Three structural equation models were used, one after the other, through the method of partial least squares (PLS-EM). The results show that attitude, perceived control behavior and curiosity have a positive impact on entrepreneurial intention, whereas subjectivenorms, surprisingly, have a negative impact on it. Psychological well-being expressed through autonomy is not associated with entrepreneurial intention in our sample of students. This article contributes to a better understanding of entrepreneurial intention in engineering students.

A least-squares Fourier frame method for nonlocal diffusion models on arbitrary domains

We introduce a least-squares Fourier frame method for solving nonlocal diffusion models with Dirichlet volume constraint on arbitrary domains. The mathematical structure of a frame rather than a basis allows using a discrete least-squares approximation on irregular domains and imposing non-periodic boundary conditions. The method has inherited the one-dimensional integral expression of Fourier symbols of the nonlocal diffusion operator from Fourier spectral methods for any d spatial dimensions. High precision of its solution can be achieved via a direct solver such as pivoted QR decomposition even though the corresponding system is extremely ill-conditioned, due to the redundancy in the frame. The extension of AZ algorithm improves the complexity of solving the rectangular linear system to O(Nlog2⁡N) for 1d problems and O(N2log2⁡N) for 2d problems, compared with O(N3) of the direct solvers, where N is the number of degrees of freedom. We present ample numerical experiments to show the flexibility, fast convergence and asymptotical compatibility of the proposed method.

Efficacy and safety of cofrogliptin once every 2 weeks in Chinese patients with type 2 diabetes: A randomized, double-blind, placebo-controlled, phase 3 trial.

We conducted a multicentre, randomized phase 3 trial in China to evaluate the efficacy and safety of cofrogliptin (HSK7653), a novel long-acting dipeptidyl peptidase-4 inhibitor, in patients with drug-naïve type 2 diabetes (T2D). Patients with inadequately controlled T2D were randomly assigned (1:1:1) to cofrogliptin 10 mg, cofrogliptin 25 mg or placebo, taken orally once every 2 weeks for a 24-week double-blind period. Eligible patients then received cofrogliptin 25 mg in a 28-week open-label extension. The primary endpoint was the change in glycated haemoglobin (HbA1c) from baseline to week 24. In total, 475 patients (median age: 54.0 years) were randomized and received at least one dose of cofrogliptin 10 mg (n = 158), cofrogliptin 25 mg (n = 158) or placebo (n = 159); 401 patients entered the open-label extension. At week 24, the least-squares (LS) mean difference (95% confidence interval [CI]) in HbA1c versus placebo was -0.63% (-0.81, -0.46) with cofrogliptin 10 mg and -0.59% (-0.77, -0.42) with cofrogliptin 25 mg (both p < 0.0001). The LS mean (standard error) change in HbA1c from baseline was maintained at the end of the study in patients given open-label cofrogliptin 25 mg for an additional 28 weeks: cofrogliptin 10 mg: -0.86% (0.07); cofrogliptin 25 mg: -0.74% (0.07); placebo: -0.89% (0.07). Over the entire study, common adverse events were hyperuricaemia, hyperlipidaemia, hypertriglyceridaemia, increased lipase, upper respiratory tract infection and urinary tract infection. Hypoglycaemic events did not significantly differ between groups. Cofrogliptin provided glycaemic control over 52 weeks and was generally well tolerated in patients with T2D. Registered on Clinicaltrials.gov with the registration number NCT04556851 (https://clinicaltrials.gov/study/NCT04556851).