Quadratic Fitting Research Articles

Osmotic dehydration optimization of butternut squash (Cucurbita moschata Duch) using response surface methodology

Butternut squash (Cucurbita moschata Duch) has a reasonably high carotene content. The flour-making process of it is related to the carotene content and antioxidant activity. It is essential to determine the optimum conditions of osmotic dehydration process by treating the concentration of the salt solution (5-15%), immersion time (60-180 mins), and stirring speed (10-40 rpm) on colour, beta-carotene content, and antioxidant activity using Response Surface Methodology (RSM) with Box-Behnken Design (BBD). All responses had a quadratic model fit (p<0.05). The R2 values are 86.7 for water loss, 84.9 for a solid gain, 96.3 for colour (ΔE), 94.3 for colour (chroma), 65.5 for beta-carotene, and 70 for antioxidant activity, respectively. The decrease in water content was strongly influenced by the salt solution concentration, stirring speed, and soaking time. However, among three factors, the salt solution concentration was the most influential. The stirring speed significantly influences the addition of solids to the material (solid gain) during the osmotic dehydration process. In contrast, ΔE and chroma were influenced by the stirring speed and immersion time for colour changes. Stirring speed influences beta-carotene levels. The amount of antioxidant activity was influenced by the stirring speed and immersion time. The optimization results obtained a salt solution concentration of 15%, a stirring speed of 25 rpm, and an immersion value of 155.8 mins. The magnitude of the three factors above provides a predictive value for water content to decrease to a maximum of 8.57%, solid gain to increase by 8.34%, beta-carotene content to decrease by 11.07% on a wet basis, antioxidant activity to decrease by 2.74, ΔE 20.22, and chroma of 71.07. The composite desirability value was 77.30%. Treating the salt concentration, soaking time, and stirring frequency affect the colour change, water loss, addition of solids, beta-carotene levels and antioxidant activity. The research finds that reducing the water content in the DO process has a significant effect, so the drying process can be carried out more quickly. In addition, the significance of the optimal conditions for the honey gourd DO process can be applied to further processing, for example, for the manufacture of industrial-scale flour

Improving Tunnel Boring Machine Tunneling Performance by Investigating the Particle Size Distribution of Rock Chips and Cutter Consumption

The construction environment of deep rock tunnels is complex, and effectively enhancing tunnel boring machine (TBM) tunneling efficiency is paramount. Increasing rock-breaking efficiency and minimizing cutter consumption are essential strategies for improving TBM tunneling efficiency. Selecting suitable tunneling parameters is crucial for enhancing rock-breaking efficiency and reducing cutter consumption. Existing research on the optimization of the ratio of maximum cutter spacing to penetration (Smax/P) based on field-measured data is limited, and few studies compare and analyze the relationship between SE, CI, and the Smax/P ratio separately. Consequently, this study determined optimal tunneling parameters for various types of surrounding rock and construction environments, aiming to more accurately optimize TBM tunneling performance during construction processes based on on-site construction data. This study conducted a comparative analysis of specific energy (SE) and the coarseness index (CI). Under both working conditions, the quadratic fitting coefficients of the CI are 4.2% and 10.6% higher than those of the SE, respectively, with the CI selected to represent the particle size distribution of rock chips. Finally, taking into account both the correlations between the CI and the ratio of maximum cutter spacing to penetration (Smax/P), as well as cutter consumption and the Smax/P ratio, an optimization method for the TBM tunneling parameter was established under both dry and saturated conditions. The research findings indicate that cutter consumption exhibits an exponential increase with a higher rock Cerchar Abrasivity Index (CAI); it initially decreases as the Smax/P ratio increases and subsequently increases in both dry and saturated conditions. Instead, the CI demonstrates an initial increase and subsequent decrease as the Smax/P ratio increases. Maximizing rock-breaking efficiency and minimizing cutter consumption are crucial for improving tunneling performance. In saturated conditions, the corresponding optimal Smax/P ratio ranges are 7.055–8.319 for soft rock, 8.606–8.931 for medium–hard rock, and 13.50–14.00 for hard rock, and these optimal ranges under dry conditions are 8.495–9.457, 10.972–12.169, and 16.5–17.5 for the same rock types. This study provides optimal Smax/P ratio ranges for TBM tunneling, thereby significantly enhancing tunneling efficiency.

A modification to the Friedman and Ortega isoconversional methods for evaluation of the activation energy as a function of conversion and temperature

The Friedman and Ortega isoconversional methods typically apply linear regression to the isoconversional kinetic data for calculation of activation energy solely as a function of extent of conversion. However, in complex reactions, activation energy depends on both conversion and temperature. Our modification involves quadratic curve fitting instead of linear regression, resulting in the determination of activation energy as a function of conversion and temperature. The new technique enables the calculation of the temperature dependence of activation energy for different heating rates, making it a valuable addition to isoconversional analysis. The conventional and modified approaches were utilized on the isoconversional kinetic data concerning polyethylene thermal degradation. The results provided a more detailed representation of the variations in activation energy when nonlinear regression was used.

High dynamic range 3D shape reconstruction: Combination of adaptive fringe intensity, iterative exposure time adjustment and least quadratic curve fitting

For three-dimensional (3D) reconstruction of specular surfaces based on fringe projection profilometry (FPP), a hybrid approach combining adaptive fringe projection, iterative exposure time adjustment and least quadratic curve fitting is proposed. First, we propose an adaptive projection fringe intensity generation method in the camera image. Second, we build a new pixel matching between the camera and projector, and correct the pixel matching on the specular surfaces based on linear interpolation. Third, we propose an iterative exposure time adjustment method based on saturated pixel statistics. Fourth, we fuse the multiple results to obtain the final 3D reconstructed surface. Finally, we adopt a least quadratic curve fitting algorithm to fit the residual phase errors. Experiments confirmed the validity of the proposed method.

Performances of different yield-detrending methods in assessing the impacts of agricultural drought and flooding: A case study in the middle-and-lower reach of the Yangtze River, China

In evaluating the impacts of drought and flooding disasters on crop yields, accurately calculating meteorological yield (i.e., detrended yield) is an important procedure. The present work aimed to compare various yield-detrending methods in terms of characterizing the regression relationships between meteorological yield and the intensities of drought and flooding. Taking the middle-and-lower reach of the Yangtze River (MLRYR) as the study region, the intensities of drought and flooding during the growing seasons of four study crops (cotton, oilseed rape, wheat, and maize) were quantified using the standardized precipitation evapotranspiration index. Nine popular yield-detrending methods and the first-difference method were employed to determine meteorological yields. The results indicated that the examined methods consistently identified the cases with very significant yield-reducing impacts of drought and flooding. The first-difference method identified 58 significant regression relationships, outperforming the yield-detrending methods (identifying 39–44 significant regression relationships). The 20-yr moving average and the linear fitting methods performed best at the provincial level, while the cubic smoothing spline and the quadratic polynomial fitting methods performed best at the district level. Based on these best-performing methods, the average method was proposed and exhibited wider applicability and better performance than the individual methods. In terms of meteorological yield losses, cotton was the most affected crop (35% of all districts experienced severe cotton yield loss) and Anhui was the most affected region (with an average crop yield loss of 14.06%). The yield-reducing impact of flooding was significant in 41 districts; in comparison, the impact of drought was significant only in 7 districts. Additionally, oilseed rape was the crop most affected by drought and flooding. These results can provide guidance for assessing agricultural drought and flooding disasters under climate change.

Experimental and theoretical insights into vanadium-based alloys for room temperature hydrogen storage on the example of Ti16Cr22Zr5V55-xFe2Mnx (x=0–3) alloys

In this work, the microstructures and hydrogen storage properties of the Ti16Zr5Cr22V55-xFe2Mnx (x =0, 1, 2, 3) hydrogen storage alloys were comprehensively investigated toward application under ambient conditions. The X-ray diffraction (XRD) patterns and scanning electron microscopy (SEM) images of the alloys indicated that all of the alloys consist of a BCC main phase and a small amount of C14 Laves secondary phase. All of the studied alloys have a good activation performance and fast absorption/desorption kinetics at 298 K. The flatness of desorption plateau of alloy is improved by the tiny Mn introduction. With the increase of Mn content, the lattice parameter of BCC main phase, electron density and hydrogen absorption/desorption capacity decrease, and the desorption plateau pressure at 298 K increases in the range of 0.1–1 MPa. In addition, the essence of the dependence of high hydrogen capacity on electron density was revealed based on Fermi level. The Tilt, hysteresis, and width of plateau of PCT curve of vanadium-based alloys were clarified on the basis of Sievert's law. And a good quadratic fitting between desorption plateau pressure and Mn content was manifested.

Performance evaluation of different reflected signal extraction methods on GNSS-R derived sea level heights

In order to obtain reliable GNSS-R derived sea level heights (SLHs), it is crucial to extract accurate reflected signals from signal-to-noise ratio (SNR) data. In this study, Quadratic Fitting, Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), and Singular Spectrum Analysis (SSA) are adopted for extracting the reflected signals from SNR data, which are then analyzed with Lomb Scargle Periodogram (LSP) assisted with tidal harmonic analysis for GNSS-R SLHs. Three continuous GNSS stations including Onsala in Sweden, Friday Harbor in the United States, and Brest in France with tidal ranges of approximately 1 m, 3 m, and 7 m, respectively, were used in the study. The derived SLHs were evaluated against the nearby or co-located tide gauge records. The results reveal that the three proposed algorithms effectively cope with the multi-peaks spectrum problems when using the conventional Quadratic Fitting without a priori reflected height constraint, and SSA can provide the solutions with fewer outliers among the proposed methods with the RMSEs of 6.7 cm, 13.4 cm and 39.6 cm at Onsala, Friday Harbor, and Brest stations, respectively. Without implementing tidal harmonic analysis, SSA is the method capable of acquiring reliable SLHs among the stations, as evidenced by comparing with co-located gauge records, particularly at the Brest station. In summary, SSA not only distinguishes signals across different frequencies, but also orders the signal components according to their eigenvalues, demonstrating the potential to extract the reflected signals from SNR and enhance the stability and accuracy of GNSS-R applications.

Graph-Based Method for Calibration of High-Resolution Mass Spectra of Natural Organic Matter.

Inaccuracies in ion detection and signal processing can undermine confidence in the molecular formula assignment of high-resolution mass spectrometry, which relies on precise matching of the mass-to-charge ratio (m/z). This study proposes a novel graph-based spectra calibration method, MSCMcalib, which implements coordinate transformation and pattern detection. MSCMcalib maps uncalibrated m/z data onto a modified 2D mass defect plot, facilitating the automatic calibration of detected lines, i.e., the calibration of uncalibrated peaks aligned with these lines. The "propagation" method is subsequently employed to accurately and automatically calibrate 605 m/z values across multiple lines, encompassing 98% of the m/z range. The calibrated m/z values divide the m/z range of the spectrum into multiple subintervals, with each subinterval undergoing a process of "scaling" calibration. The utilization of narrower partitions effectively mitigates divergence issues at both ends that arise from the polynomial fitting of errors against m/z. The effectiveness of MSCMcalib is validated through the calibration of SRFA data with m/z error ranges spanning from -10 to -6 ppm, resulting in an additional assignment of 11%-30% more molecular formulas compared to the quadratic fitting calibration.

Pressure-dependent thermal conductivity transient measurement of graphene

The thermal properties of graphene determine the thermal damage evaluation of graphene diaphragm and the lifetime of graphene-based devices. The conventional transient measurement method tends to result in the low-precision thermal conductivity (κ) for suspended monolayer graphene and complex interferometry setup. Hence, in order to improve κ measurement of graphene, a simple, miniaturized and portable Fabry-Perot (F–P) resonator with 10-layer graphene is proposed to perform the actuation and vibration detection of the suspended graphene. Then, the κ value can be calculated by means of laser-heated graphene's thermomechanical response, along with the established model for thermal time constant (τ) of a uniformly heated circular film. A quadratic fit is applied to the measured κ at different air pressures and an average fitting curve is obtained, thus determining that the measured κ relatively decreases by 13.32% with the increasing air pressure outside the F–P cavity from ∼22 kPa to ∼101 kPa. Subsequently, the COMSOL heat transfer simulation confirms that convective heat transfer is the primary reason for the external air pressure affecting transient measurements of κ of graphene. Hence, after taking the intercept of the average fitting curve, the predicted κ at 0 Pa of 10-layer suspended graphene is calculated to be 194.48 W/(m·K), which is close to the fitting curve calculated from previously reported κ of graphene with different layers. This study contributes to accurate transient measurement of κ in graphene, and is also instructive for investigating transient thermal process in other two-dimensional materials.

ENSO effects on the relationship between aerosols and evapotranspiration in the south of the Amazon biome

The effects of the El Nino-Southern Oscillation (ENSO) events have local, regional, and global consequences for water regimes, causing floods or extreme drought events. Tropical forests are strongly affected by ENSO, and in the case of the Amazon, its territorial extension allows for a wide variation of these effects. The prolongation of drought events in the Amazon basin contributes to an increase in gas and aerosol particle emissions mainly caused by biomass burning, which in turn alter radiative fluxes and evapotranspiration rates, cyclically interfering with the hydrological regime. The ENSO effects on the interactions between aerosol particles and evapotranspiration is a critical aspect to be systematically investigated. Therefore, this study aimed to evaluate the ENSO effect on a site located on the southern portion of the Amazonian region. In addition to quantifying and testing possible differences between aerosols and evapotranspiration under different ENSO classes (El Niño, La Niña and Neutrality), this study also evaluated possible variations in evapotranspiration as a function of the aerosol load. A highly significant difference was found for air temperature, relative humidity and aerosol load between the El Niño and La Niña classes. For evapotranspiration, significant differences were found for the El Niño and La Niña classes and for El Niño and Neutrality classes. Under the Neutrality class, the aerosol load correlated significantly with evapotranspiration, explaining 20% of the phenomenon. Under the El Niño and La Niña classes, no significant linear correlation was found between aerosol load and evapotranspiration. However, the results showed that for the total data set, there is a positive and significant correlation between aerosol and evapotranspiration. It increases with a quadratic fit, i.e., the aerosol favors evapotranspiration rates up to a certain concentration threshold. The results obtained in this study can help to understand the effects of ENSO events on atmospheric conditions in the southern Amazon basin, in addition to elucidating the role of aerosols in feedback to the water cycle in the region.

High-Precision Joint TDOA and FDOA Location System

Passive location based on TDOA (time difference of arrival) and FDOA (frequency difference of arrival) is the mainstream method for target localization. This paper proposes a fast time–frequency difference positioning method to address issues such as low accuracy, large computational resource utilization, and limited suitability for real-time signal processing in the conventional CAF (cross-ambiguity function)-based approach, aiming to complete the processing of the target radiation source to obtain the target parameters within a short timeframe. In the mixing product operation step of the CAF, a frequency-domain approach replaces the time-domain convolution operation in PW-ZFFT (pre-weighted Zoom-FFT) to reduce the computational load of the CAF. Additionally, a quadratic surface fitting method is used to enhance the accuracy of TDOA and FDOA. The localization solution is obtained using Newton’s method, which can provide more accurate results compared to analytical methods. Next, a signal processing platform is designed with FPGA (field-programmable gate array) and multi-core DSP (digital signal processor), and works by dividing and mapping the algorithm functional modules according to the hardware’s characteristics. We analyze the architectural advantages of multi-core DSP and design methods to improve program performance, such as EDMA transfer optimization, inline function optimization, and cache optimization. Finally, this paper constructs simulation tests in typical positioning scenarios and compares them to hardware measurement results, thus confirming the correctness and real-time capability of the program.

Winter wheat irrigation parameters in the Brazilian Cerrado

Wheat is the second most produced cereal in the world. The gap between production and consumption in Brazil shows that wheat production must be increased to meet the domestic demand. In this context, the objective of this study was to determine the crop coefficient of wheat and the ideal moment for irrigation, based on the soil water depletion rate (f). The study was carried out in the tropics, on an Oxisoil (Typic Haplustox), in an experimental field of Embrapa Cerrados in Planaltina, Federal District of Brazil. The experimental design consisted of randomized blocks with three replications. The treatments were differentiated by the soil water depletion index (f) of 0.2, 0.4, 0.6, and 0.8. In other words, irrigation was initiated when 20, 40, 60 and 80% of the available soil water capacity (AWC) at a soil depth of 0.4 m was consumed by the crop. Wheat yield and yield components were evaluated. The phenological development was monitored based on Zadok’s scale, in days after emergence, and the management parameters crop coefficient (Kc) and irrigation timing were determined. The results indicated a soil water depletion index of 0.4 as the best indicator for beginning wheat irrigation. Under this condition, Kc can be estimated daily as a function of days after emergence (DAE) by the quadratic polynomial regression or curve fitting method, adjusted as follows: Kc = −0.000298 × DAE² + 0.036695 × DAE + 0.332486. Alternatively, the means of Kc of each phenological crop phase can be used: Kc = 0.45 (establishment); 0.81 (tillering); 1.21 (booting); 1.43 (flowering); 1.27 (grain formation); and 0.89 (maturation). Thus, there is a limit of consumption of soil available water, at which wheat still achieves the full yield potential, with a rational use of water which varies according to the development phase.

Study on optimal allocation of energy storage in multi-regional integrated energy system considering stepped carbon trading

Abstract In this study, an energy storage configuration optimization model of multi regional integrated energy system based on integrated scheduling and stepped Carbon emission trading is proposed. By analyzing the steady-state, dynamic, and variable operating characteristics of multi regional integrated energy systems, a distributed energy planning modeling method was adopted to construct energy storage configuration constraint objects and optimization models. The target scheme of energy storage configuration is optimized by using the results of integrated scheduling scheme and dynamic distribution analysis of ladder Carbon emission trading, and the parameters are optimally estimated by using Monte Carlo method and quadratic fitting algorithm. The simulation results show that this method has a strong scheduling capability in the context of stepped Carbon emission trading, can accurately assess the load demand and supply demand relationship, reduce carbon emissions, and improve energy efficiency, with an average of 0.9121.

Efluente da piscicultura e tempos de recirculação nas trocas gasosas e nutrição do agrião hidropônico

ABSTRACT The present study evaluated the potential use of fish farming effluent incorporated into the standard nutrient solution and recirculation time on gas exchange and macro and micronutrient contents of watercress in a hydroponic system. The study was conducted in randomized blocks, in a split-plot scheme with 4 replicates, in two experiments carried out in spring and summer seasons. Plots were composed of different proportions of nutrient solution (NS) and fish farming effluent (FFE): S1 (0% NS and 100% FFE), S2 (25% NS and 75% FFE), S3 (50% NS and 50% FFE), S4 (75% NS and 25% FFE), and S5 (100% NS and 0% FFE). Subplots consisted of two solution recirculation times (Time 1 – T1: 15 for 15 min and Time 2 – T2: 15 for 30 min), totaling 40 experimental plots. Net photosynthesis, stomatal conductance, transpiration, substomatal CO2 concentration, SPAD index, and macro and micronutrient contents were evaluated. Net photosynthesis showed a quadratic fit in both cultivation cycles, with maximum values observed with use of 86.0% NS (spring) and 64.9% NS (summer). Leaf N and P contents indicate that the use of approximately 70% NS can be considered satisfactory, as it promoted the highest values of these macronutrients. Using fish farming effluent can enable the production of watercress in hydroponic systems, influencing the nutritional status of the crop.

Exploring the dependence of gas cooling and heating functions on the incident radiation field with machine learning

ABSTRACT Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped up by using interpolation tables of pre-computed values, at the expense of making significant and sometimes even unjustified approximations. Here, we explore the capacity of machine learning to approximate cooling and heating functions with a generalized radiation field. Specifically, we use the machine learning algorithm XGBoost to predict cooling and heating functions calculated with the photoionization code cloudy at fixed metallicity, using different combinations of photoionization rates as features. We perform a constrained quadratic fit in metallicity to enable a fair comparison with traditional interpolation methods at arbitrary metallicity. We consider the relative importance of various photoionization rates through both a principal component analysis (PCA) and calculation of SHapley Additive exPlanation (shap) values for our XGBoost models. We use feature importance information to select different subsets of rates to use in model training. Our XGBoost models outperform a traditional interpolation approach at each fixed metallicity, regardless of feature selection. At arbitrary metallicity, we are able to reduce the frequency of the largest cooling and heating function errors compared to an interpolation table. We find that the primary bottleneck to increasing accuracy lies in accurately capturing the metallicity dependence. This study demonstrates the potential of machine learning methods such as XGBoost to capture the non-linear behaviour of cooling and heating functions.

An Optimization Study on a Novel Mechanical Rubber Tree Tapping Mechanism and Technology

All-natural rubber is harvested from rubber trees (Hevea brasiliensis Muell. Arg.) by traditional tapping knives, so rubber tapping still heavily relies on labor. Therefore, this study explored a novel, hand-held mechanical rubber tapping machine for rubber tree harvesting. In this study, a mechanical tapping cutter with a vertical blade and adjustable guide was first described. The response surface method was applied to evaluate factors affecting the tapping effect. The experimental values were in close agreement with the predicted value. Machine-tapped latex was comparable in quality to hand-tapped latex. Based on the single-factor results, the response surface method (RSM) and the center combined rotation design (CCRD) optimization method were adopted to explore the influence of three factors influencing vertical blade height (A), cutting force (B), and spiral angle (C) on the tapping effect. Regarding the cutting rate of the old rubber line (Y1), cutting time (Y2), latex flow rate (Y3), and average cutting current (Y4) as evaluation indexes of the tapping effect, an optimization scheme was determined. The quadratic model fits for all the responses. The test results showed that the main factors affecting Y1, Y2, Y3, and Y4 were A and B, B, A and C, and B, respectively. Under optimal conditions, the influencing factors of A, B, and C were 10.24 mm, 51.67 N, and 24.77°, respectively, when the evaluation index values of Y1, Y2, Y3, and Y4 were 98%, 8.65 mL/5 min, 9.00 s, and 1.16 A. The range of the relative error between the experimental and predicted results was from −11.11% to 11.11%. According to the optimized treatment scheme, a comparison test was designed between mechanical and manual rubber tapping tools. To verify the availability and effect of the mechanical tapping method preliminarily, the important rubber tapping evaluation indexes included bark thickness, bark excision, latex flow time, cutting time, ash content, and cutting depth, which were selected to serve as a comparison test. There was no significant difference between hand and mechanical methods, except ash content (p < 0.05) and cutting time (p < 0.01). The mechanical tapping machine proposed in this study is meaningful to improve cutting efficiency, practicality, and operability. Furthermore, it provides crucial theoretical references for the development of intelligent tapping machines.

Evaluating surface roughness of curved surface with circular profile based on arithmetic circular arc fitting

A procedure based on Kåsa fit for evaluating the surface roughness of a curved surface with a circular arc profile was suggested in this paper. To investigate the effectiveness of the method, some curved surface profiles with preset surface roughness were numerically generated, and their surface roughness was evaluated by the procedure based on Kåsa fit. And the surface roughness of two experimental surface profiles evaluated by the method based on Kåsa fit was compared with those evaluated by linear fitting and quadratic polynomial fitting to demonstrate both the effectiveness and the preservation of Kåsa fit-based procedure. Results show that the evaluated value of surface roughness by Kåsa fit-based procedure only deviated from the actual value by less than 10%, even in the case of considerable fitting parameters’ error (>30%). Also, the Kåsa fit can report a reasonable value of surface roughness with better preservation of shift and rotation motion of the surface profile compared to both linear fit and quadratic polynomial fitting, especially for the curved surface with a short radius. This procedure based on Kåsa fit can be used in evaluating surface roughness of curved surface with circular arc profile no matter what pose of the object under observed.

Ki-67 Expression of 50% Is the Optimal Cut-Off to Predict Survival Outcomes in Mantle Cell Lymphoma (MCL): A Pooled Analysis from CALGB 50403 (Alliance) and MCL Real-World Study Cohort

Introduction The Ki-67 index has been previously shown to be prognostic, wherein the cut-off of 30% was associated with inferior survival outcomes (Determann O et al, Blood 2008) in newly diagnosed MCL patients (pts). However, this cut-off determination was made in pts treated with CHOP/R-CHOP as the first-line treatment, controlled only for MIPI, and predates the advent of novel agents. Short diagnosis to treatment interval (DTI ≤ 14 days) was recently shown to be prognostic in newly diagnosed MCL but its association with Ki-67 is unknown. We sought to determine the optimal Ki-67 cut-off in MCL and its prognostic relevance in the modern era. Methods This is a pooled analysis of 2 large datasets, one prospective (CALGB 50403) and one retrospective (MCL real world study [MCL-RWS]). CALGB is now part of the Alliance for Clinical Trials in Oncology. CALGB 50403 is a phase II randomized study wherein newly diagnosed MCL pts received intensive induction chemoimmunotherapy (IIC) followed by autologous transplant, and posttransplant rituximab. The MCL-RWS included adult pts (≥18 years [yrs]) with MCL treated from 2000 to 2017 at 12 participating US sites. Pts from sites in the MCL-RWS that enrolled on CALGB 50403 were excluded. Ki-67 was scored by central review in 10% increments in the CALGB 50403 and per institutional standard in the MCL-RWS. We assessed Ki-67 as a continuous variable and used a restricted quadratic spline fit to find an optimal cut-off. We looked at the associations between Ki-67 and other known/ established MCL prognostic markers including MIPI and DTI. The outcome parameters were PFS and OS. Time-to-event endpoints were evaluated by Kaplan-Meier and Cox proportional hazard methods. Results Among the 793 pts (n=666, MCL-RWS and n=127, CALGB 50403) in the pooled analysis, Ki-67 was available in 385 pts (311 from MCL-RWS and 74 from CALGB 50403). The median OS (mOS) and PFS (mPFS) in the entire cohort (n=793) was 11.8 years and 4.7 years, respectively. The two groups (gps), those with and without Ki-67 data, were well balanced including MIPI and DTI. The median age was 62 yrs (range, 32-88), 81% males, 94% with ECOG performance status (PS) 0-1 and 84% with stage 4. We found a Ki-67 cut-off of 50% to be optimal as the relative hazard of death rises after 50%. Pts in the Ki-67 >50% gp had significantly higher proportion with short DTI (36% vs 17%, p<0.001), ECOG PS ≥2 (12% vs 5%, p=0.02), elevated LDH (58% vs 39%, p=0.005), and MIPI ≥6.2 (38% vs 20%, p=0.007) compared to Ki-67 of ≤50%. Ki-67 >50% was associated with significantly inferior PFS with a hazard ratio (HR) of 2.10 (95%CI 1.50-2.92) compared to Ki-67 ≤50% with a mPFS of 2.1 vs 5.3 yrs, respectively, regardless of the age (young [≤65 yrs], 2.6 vs 5.3 yrs or old [>65 yrs], 1.1 vs 5.4 yrs) or receipt of IIC (2.2 vs 5.9 yrs). Figure 1 shows the statistically significant difference in PFS between the Ki-67 gps of ≤10%, >10% to <30%, ≥30 to ≤50%, and >50%. Ki-67 >50% remained prognostic for PFS in multivariable analysis (MVA) after adjusting for significant variables in univariable analysis (UVA) including short DTI, ECOG PS ≥2, stage 4, elevated LDH, and MIPI ≥6.2 with adjusted HR (aHR) 2.19, 95%CI 1.38-3.48, p <0.001. Ki-67 >50% was associated with significantly inferior OS with a HR of 2.10 (95%CI 1.33-3.32) compared to Ki-67 ≤50% with a mOS of 9.4 yrs vs not reached (NR), respectively, regardless of the age or receipt of IIC. Figure 2 shows the statistically significant difference in OS between the Ki-67 gps of ≤10%, >10% to <30%, ≥30 to ≤50%, and >50%. Ki-67 >50% was not prognostic for OS in MVA after adjusting for significant variables in the UVA (MIPI and sex), aHR 1.79, 95% CI 0.92-3.49, p=0.08. Similar findings were seen in multivariable analysis with Ki-67 >30%, which showed no prognostic significance (aHR 1.46, 95%CI 0.82-2.58, p=0.19). Because of disparate datasets, we performed sensitivity analysis looking at the prognostic relevance of in individual datasets (CALGB 50403 and MCL-RWS) and found Ki67 >50% was prognostic for PFS and OS in both of the datasets consistent with the primary analysis. Conclusions This study evaluating the optimal Ki-67 cut off for pts with newly diagnosed MCL in the modern era found that Ki-67 > 50% was prognostic for PFS but not OS in MVA. A potential reason for the lack of prognostic relevance for OS in this more recent dataset is the availability of effective options at relapse. We also found that short DTI was associated with high Ki-67 gp which is a novel finding.

Depth Quality Improvement with a 607 MHz Time-Compressive Computational Pseudo-dToF CMOS Image Sensor

In this paper, we present a prototype pseudo-direct time-of-flight (ToF) CMOS image sensor, achieving high distance accuracy, precision, and robustness to multipath interference. An indirect ToF (iToF)-based image sensor, which enables high spatial resolution, is used to acquire temporal compressed signals in the charge domain. Whole received light waveforms, like those acquired with conventional direct ToF (dToF) image sensors, can be obtained after image reconstruction based on compressive sensing. Therefore, this method has the advantages of both dToF and iToF depth image sensors, such as high resolution, high accuracy, immunity to multipath interference, and the absence of motion artifacts. Additionally, two approaches to refine the depth resolution are explained: (1) the introduction of a sub-time window; and (2) oversampling in image reconstruction and quadratic fitting in the depth calculation. Experimental results show the separation of two reflections 40 cm apart under multipath interference conditions and a significant improvement in distance precision down to around 1 cm. Point cloud map videos demonstrate the improvements in depth resolution and accuracy. These results suggest that the proposed method could be a promising approach for virtually implementing dToF imaging suitable for challenging environments with multipath interference.

Characterize the Long-term Ionospheric Response to the Changes in Solar Activity at Low-Latitude Stations of the East African Sector

In this research, we examine the long-term ionospheric response to solar conditions from 2009-2019 using GPS-TEC observations from 8 stations in East Africa at low/equatorial latitudes. To determine the effects of solar activity on ionospheric vertical-Total-Electron-Content (vTEC), solar proxies (EUV, F10.7, and SSN) were used. We have applied statistical analysis and used quadratic fits with solar indices to find the types of trends, forecast vTEC, and describe the daily, monthly, and seasonal variations of vTEC. We stated the fluctuations and dependency of GPS-vTEC on solar activity. From seasonal analysis, the greater values of GPS-vTEC were observed in the equinox’s season from 2009-2016, followed by the December and June solstices, respectively. The highest values of GPS-vTEC were recorded in the years 2014 (70 and 67 TECU), 2013 (57 and 65 TECU), 2012 (56 and 60 TECU) at the March and September equinoxes, and the 2015 March equinox (68 TECU), and the lowest value of GPS-vTEC was recorded (2-3 TECU) for all seasons from 03 to 07 EAT. The changes in vTEC have confirmed worthy agreement with the changes in solar parameters, and EUV flux has a stronger association with vTEC than the F10.7 and SSN by 2% and 7%, respectively. Daily and monthly variations of vTEC showed positive associations with the solar parameters (EUV, F10.7, and SSN) from 2009-2019. We got both linear and nonlinear trends; however, when we approximated (EUV)2,(F10.7)2, and (SSN)2 coefficients, linear trends in vTEC were dominant. This analysis confirms that a quadratic polynomial can well capture the long-term solar activity dependency of vTEC in a statistical sense; based on the anticipated and observed vTEC values, the modeled outcome is suitable using EUV, F10.7, and SSN indices. But the modeled result is better using EUV and F10.7 than SSN in the region. In the predictions of vTEC, the maximum deviations and number of errors were observed during solar maxima years for EUV, F10.7, and SSN compared with the deviations and number of errors in solar minima years. Therefore, F10.7 is a better proxy of EUV flux in solar cycle 24 using monthly values, and the EUV flux is a better controller of GPS-vTEC changes compared to F10.7 and SSN, even if F10.7 is a proxy of EUV based on daily values.