Single Run Research Articles

MSIpixel: a fully automated pipeline for compound annotation and quantitation in mass spectrometry imaging experiments.

Mass spectrometry imaging (MSI) is commonly used to map the spatial distribution of small molecules within complex biological matrices. One of the major challenges in imaging MS-based spatial metabolomics is molecular identification and metabolite annotation, to address this limitation, annotation is often complemented with parallel bulk LC-MS2-based metabolomics to confirm and validate identifications. Here we applied MSI method, utilizing data-dependent acquisition, to visualize and identify unknown molecules in a single instrument run. To reach this aim we developed MSIpixel, a fully automated pipeline for compound annotation and quantitation in MSI experiments. It overcomes challenges in molecular identification, and improving reliability and comprehensiveness in MSI-based spatial metabolomics.

Intrusive and non-intrusive uncertainty quantification methodologies for pyrolysis modeling

In this work we discuss and compare multiple uncertainty analysis methodologies for pyrolysis modeling. Using Arrhenius equation as the pyrolysis model and kinetic parameters for PMMA material as uncertain variables, different approaches for stochastic uncertainty quantification and their computational effort are analyzed. First non-intrusive (NI) methods are compared through convergence analysis where the deterministic model can be used as is to ascertain the statistical moments, followed by an intrusive polynomial chaos (IPC) approach which requires reformulation of the deterministic model, but solution of the model only once. The applied NI methods include Monte Carlo based simulations, regression and projection based non-intrusive polynomial chaos (NIPC) methods. The uncertainty analysis and convergence comparison is performed for three materials including the effects of overlapping reactions and dependent parameters. In general for different uncertain parameters and materials, IPC gave accurate statistical information in a single model run compared to NIPC projection requiring runs ranging from tens to hundreds and NIPC regression requiring runs in range of thousands to generate converged statistics. However, in case of only a few uncertain parameters, presence of non-polynomial functions in the model and small-scale simulations, projection based NIPC outshines IPC in terms of simplicity and applicability.

Nonlinear regression of remaining surgery duration from videos via Bayesian LSTM-based deep negative correlation learning

In this paper, we address the problem of estimating remaining surgery duration (RSD) from surgical video frames. We propose a Bayesian long short-term memory (LSTM) network-based Deep Negative Correlation Learning approach called BD-Net for accurate regression of RSD prediction as well as estimation of prediction uncertainty. Our method aims to extract discriminative visual features from surgical video frames and model the temporal dependencies among frames to improve the RSD prediction accuracy. To this end, we propose to train an ensemble of Bayesian LSTMs on top of a backbone network by the way of deep negative correlation learning (DNCL). More specifically, we deeply learn a pool of decorrelated Bayesian regressors with sound generalization capabilities through managing their intrinsic diversities. BD-Net is simple and efficient. After training, it can produce both RSD prediction and uncertainty estimation in a single inference run. We demonstrate the efficacy of BD-Net on publicly available datasets of two different types of surgeries: one containing 101 cataract microscopic surgeries with short durations and the other containing 80 cholecystectomy laparoscopic surgeries with relatively longer durations. Experimental results on both datasets demonstrate that the proposed BD-Net achieves better results than the state-of-the-art (SOTA) methods. A reference implementation of our method can be found at: https://github.com/jywu511/BD-Net.

Engineering chirality at wafer scale with ordered carbon nanotube architectures

Creating artificial matter with controllable chirality in a simple and scalable manner brings new opportunities to diverse areas. Here we show two such methods based on controlled vacuum filtration - twist stacking and mechanical rotation - for fabricating wafer-scale chiral architectures of ordered carbon nanotubes (CNTs) with tunable and large circular dichroism (CD). By controlling the stacking angle and handedness in the twist-stacking approach, we maximize the CD response and achieve a high deep-ultraviolet ellipticity of 40 ± 1 mdeg nm−1. Our theoretical simulations using the transfer matrix method reproduce the experimentally observed CD spectra and further predict that an optimized film of twist-stacked CNTs can exhibit an ellipticity as high as 150 mdeg nm−1, corresponding to a g factor of 0.22. Furthermore, the mechanical rotation method not only accelerates the fabrication of twisted structures but also produces both chiralities simultaneously in a single sample, in a single run, and in a controllable manner. The created wafer-scale objects represent an alternative type of synthetic chiral matter consisting of ordered quantum wires whose macroscopic properties are governed by nanoscopic electronic signatures and can be used to explore chiral phenomena and develop chiral photonic and optoelectronic devices.

Variance-based reliability sensitivity with dependent inputs using failure samples

Reliability sensitivity analysis is concerned with measuring the influence of a system’s uncertain input parameters on its probability of failure. Statistically dependent inputs present a challenge in both computing and interpreting these sensitivity indices; such dependencies require discerning between variable interactions produced by the probabilistic model describing the system inputs and the computational model describing the system itself. To accomplish such a separation of effects in the context of reliability sensitivity analysis we extend on an idea originally proposed by Mara and Tarantola (2012) for model outputs unrelated to rare events. We compute the independent (influence via computational model) and full (influence via both computational and probabilistic model) contributions of all inputs to the variance of the indicator function of the rare event. We compute this full set of variance-based sensitivity indices of the rare event indicator using a single set of failure samples. This is possible by considering d different hierarchically structured isoprobabilistic transformations of this set of failure samples from the original d-dimensional space of dependent inputs to standard-normal space. The approach facilitates computing the full set of variance-based reliability sensitivity indices with a single set of failure samples obtained as the byproduct of a single run of a sample-based rare event estimation method. That is, no additional evaluations of the computational model are required. We demonstrate the approach on a test function and two engineering problems.

Development and Validation of RP-HPLC Method for the Determination of Enoxaparin Sodium in Dry Injection Formulation.

Enoxaparin sodium is an anticoagulant medication that is used as a blood thinning agent. It is mostly used for the treatment and prevention of deep vein thrombosis (DVT) and pulmonary embolism (PE). It is also used in certain surgeries and during pregnancy. For the treatment of acute coronary syndrome (ACS) and heart attacks, it may be used. Enoxaparin sodium was validated by the RP-HPLC method. A simple RP-HPLC method was developed in a single HPLC run in a dry powder injection formulation. All injections of HPLC sample were 20 μL volume. The chromatographic separation was completed in the isocratic mode. The used column was USP-L8 (250 mm × 4.6 mm) of BDS type of 10 μm meters in the same mobile phase throughout the analysis by using methanol and ultrapure water with a ratio of 7:93, respectively. The flow rate was 1.0 mL/min. The mobile phase was filtered through 0.45 μm filter paper, and isocratic elution was performed. The refractive index (RI) detector was used to analyze this sample. The specific peak of enoxaparin sodium was observed at 5:56 min. The calculated detection limit (LOD) was 0.351 ppm, and the calculated quantitation limit was 1.063 ppm. In repeatability of precision, the average calculated assay (%) was 100.85%, and the calculated RSD (%) was 0.01. In the accuracy test, the RSD (%) was 0.50, and the mean recovery (%) was 100.35. The system's suitability was within the limit. This newly developed method is proposed according to ICH guidelines, and rules and can be applied effectively for the exact estimation of enoxaparin sodium in injection formulation. This newly developed methodology is affordable in cost as long as less time is taken and the consumption of samples is in smaller quantities for every investigation. In medicinal chemistry, the USP (United States Pharmacopeia) and BP (British Pharmacopeia) are directly involved in production as well as in quality testing.

Stability indicating high‐performance liquid chromatography method for determining doxycycline hyclate and related substances in their various dosage forms: Utilizing Six Sigma tools, uniformity testing, and in‐vitro dissolution approaches

AbstractDoxycycline hyclate (DOXH) is very important to treat acne and prevent infections caused by bacteria, so quantifying doxycycline hyclate and its related substances is crucial. In this work, All analytes of doxycycline and its related substances, including methacycline, 4‐epi doxycycline, 6‐epi doxycycline, and 2‐acetyl‐2‐carbamoyl doxycycline, were successfully separated at low concentrations in a single run utilizing the suggested isocratic high‐performance liquid chromatography method with a mobile phase comprising water:acetonitrile:perchloric acid (75:25:0.2, v/v), Phenomenex Luna C18 column (50 × 4.6 mm, 3 μm i.d.) maintained at 30°C with a flow rate of 0.7 mL/min, injection volume of 25 μL, and photodiode array detector at 269 nm. DOXH and its related substances were linear in the range of 0.25–50, 0.1–30, 0.2–35, 0.5–50, and 0.6–20 μg/mL, respectively, with correlation coefficients greater than 0.999 and good accuracy results between 98% and 102%. The method has been successfully used to determine the drug's comparative study in both generic and reference products, demonstrating the similarity between the two products. According to the International Council for Harmonization requirements, the proposed approach was validated. Additionally, the technique has effectively studied in vitro dissolution, Six Sigma, and content uniformity.

An accelerated computational platform for optimal field developments with reduced footprint

Reducing the environmental footprint and increasing efficiency of hydrocarbon production as well as geological sequestration of carbon dioxide (CO2) through optimally selected and operated fewer wells is crucial for cleaner and more sustainable energy transition. We describe a parallel subsurface field-development optimization (SFDO) platform with novel components. SFDO enables the optimization of well-locations/-trajectories (WLO), controls (WCO), and both jointly (WLO–WCO). All objective function computations are performed in parallel at a given iteration in SFDO.The novel distributed quasi-Newton (DQN) optimizer is an important new element in accelerating SFDO. DQN is developed using a multi-threaded optimization paradigm that utilizes high-performance computing (HPC) to distribute an ensemble of optimization threads. By operating its threads in parallel within a single optimization run, DQN efficiently identifies multiple distinct local optima of the objective function. DQN tracks and updates a common input-output (training) data set by recording the responses from successful simulation runs. The support-vector regression (SVR) method is used to approximate the Hessian matrix while objective function gradients are estimated analytically using SVR-computed sensitivities.The DQN implementation inside SFDO is extensively tested and validated in this work. We first validate DQN using a synthetic test case with a pre-computed solution. DQN incurs fewest number of simulations, and thus, the shortest run time while successfully finding the global optimum. For the first time in the literature, we show that DQN is more effective than alternative methods in problems involving WCO and WLO–WCO. Then, we report on DQN's performance against alternative techniques in four realistic applications, namely on a WLO problem for environmental footprint reduction and a novel WLO–WCO application for the geological sequestration of CO2 involving a novel take on WLO with deforming well trajectories. Finally, we describe two realistic WLO problems in which the well count is also optimized in addition to the well locations. One of these applications is for heater-well pattern optimization for an innovative unconventional thermal recovery method. DQN finds local optima by incurring a significantly lower computational cost in comparison to alternative methods. Results of the field tests support the advantageous qualities of DQN previously observed in synthetic tests. We conclude that SFDO accelerated with DQN helps increase the efficiency and reduce the footprint of realistic field-scale developments.

Single-tube multiplex real-time PCR with EvaGreen and high-resolution melting analysis for diagnosis of α0-thalassemia--SEA,--THAI, and--CR type deletions.

Regions with a high prevalence of α-thalassemia (α-thal) require simple, rapid, and accurate tests for carrier screening and prenatal diagnosis. Diagnosis of multiple deletions in a single tube is necessary to clearly identify individuals with α0-thalassemia in the routine setting, especially in at-risk couples. Therefore, we aimed to develop a single-tube multiplex real-time PCR with EvaGreen and high-resolution melting (HRM) analysis for the identification of α0-thalassemia Southeast Asian (SEA), Thai and Chiang Rai (CR) type deletions. The results of the HRM analysis indicated that the amplified fragments from α0-thal--CR,--THAI,--SEA, and the wild-type α-globin gene had specific peak heights at mean melting temperature (Tm) values of 85.40°C, 86.50°C, 87.65°C, and 91.04°C, respectively. The frequencies of α0-thal--SEA,--THAI,--CR obtained from routine testing in 2,135 samples were 17.89%, 0.19% and 0.19%, respectively. This method would be useful for preventing Hb Bart's hydrops fetalis. Detection of multiple deletions in a single run is cost-effective, highly accurate and timesaving. This technique could enable wider α-thalassemia diagnosis in high prevalence areas and served as an example for thalassemia routine setting.

High temperature vacuum brazing of tungsten to tungsten alloy with structural material

The present paper offers an overview of experimental research on the vacuum brazing procedure used to join tungsten-based refractory materials and tungsten alloy with SS316L (a structural material) at high temperatures. The objective of joining tungsten (W) to tungsten alloy material (WL10) and SS316L materials is to develop a joining technique for fabricating the helium-cooled divertor target relevant to a DEMO-like fusion reactor. These divertor fingers are expected to withstand an incident heat flux of 10 MW/m2 and to be cooled by helium jets in an environment of high pressure (10 MPa) and high-temperature (600 °C) helium gas. High-temperature vacuum brazing has been performed at temperatures exceeding 1000 °C using selective brazing fillers in the Gleeble Machine-3800 thermo-mechanical simulator to join W (tungsten) to WL10 alloy (tungsten + 1 % Lanthanum oxide). Furthermore, vacuum brazing of multilayer materials, such as W-WL10-SS316L, has been conducted at 1050 °C for a 3 min hold time using AMS 4777 filler material in a single run on the Gleeble machine. The brazed specimens have undergone testing for 500 thermal cycles from 950 °C to 815 °C on the Gleeble-3800 machine to pre-qualify the brazed joints. Non-destructive testing (NDT), including ultrasonic testing (UT), microstructural analysis, and mechanical characterization, is employed to assess the quality of the brazed joints. The study presents the experimental techniques and the results of the characterization.

A New Delayed Hemolysis Transfusion Diagnosis Score Based on Intra Vascular Hemolysis Parameters

Introduction Delayed hemolysis transfusion reaction (DHTR) is a serious complication of sickle cell disease (SCD), accounting for 6% of all-cause mortality (Habibi Am J Hematol 2016). Although transfusion risk management has improved, the diagnosis of DHTR remains difficult and has long been underestimated. In fact, the main manifestation of DHTR in SCD patients is vaso-occlusive crisis (VOC), often associated with acute chest syndrome (ACS) and multiorgan failure, which makes transfusion attribution somewhat difficult. DHTR treatment, although not yet well codified, is based on immunoglobulins, corticoids or eculizumab in severe forms, depending on the team (Pirenne Blood 2018). Our team has proposed the use of a nomogram to guide diagnosis based on HbA decline (calculated by multiplying HbA and MCH) (Mekontso Dessap Am J Hematol 2016). However, this requires rapid quantification of hemoglobin fractions (often by HPLC) and a post-transfusion reference value, which is often lacking. Given the precise measurement of intravascular markers of hemolysis by spectroscopy that we have developed, we wondered if this could provide a simpler and faster diagnostic tool for DHTR. We performed a cross-sectional cohort study to test this hypothesis. Methods We performed intravascular hemolysis assays, including measurement of plasma hemoglobin, heme, methemoglobin, carboxyhemoglobin, hemopexin, and bilirubin, in a single run on thawed samples from patients in different cohorts. In short, the method combines a biochemical and mathematical multistep analysis (BET 18P3417). Cohorts of patients experiencing a DHTR were compared with patients in steady state and patients at the time of acute chest syndrome (ACS) in the ICU. Patients gave informed consent in accordance with French law (SCD transfu, Erythropedie, FCDREP and TASC cohorts). Two experts independently reviewed all DHTR cases to retrospectively confirm the diagnosis. Logistic regression with k-fold cross-validation (3-fold) was applied to a dataset containing hemolytic biomarkers to predict the occurrence of DHTR using python3 and the sklearn library. The performance of the model was evaluated using various metrics such as accuracy and area under the ROC curve (AUC). Specificity, sensitivity, positive predictive value (PPV) and negative predictive value (NPV) were also calculated. The confusion matrix table shows the predictive performance of the model for the classification of DHTR occurrence. Results Samples and clinical data of 53 SCD patients with DHTR, Y patients at steady state, and Z patients during acute chest syndrome were analyzed and included in this study. During DHTR plasma Hemoglobin (47.8 vs 12.8 µM, p<0.0001), Heme (27.9 vs 3.2 µM, p<0.0001), Heme/Hemoglobin ratio (1.02 vs 0.4 ; p<0.0001), MetHb (11.7 vs 2.6 µM, p=0.0003) were significantly higher in DHTR whereas Hemopexin level was lower (1.53 µM vs 2.7 µM, p=0.03) A diagnostic score was obtained by combining plasma levels of hemoglobin, heme, HbCO, MetHb, bilirubin, hemopexin. The AUC was 0.86 with a mean identical cross-validation. The accuracy and precision of the score were 0.85 and 0.76, respectively. The specificity was 0.93, the sensitivity was 0.66, the positive predictive value (PPV) was 0.76 and the negative predictive value (NPV) was 0.88. Conclusions This score may help clinicians diagnose DHTR early and then provide appropriate treatment. However, a prospective study is needed to validate the score.

Screening of angiotensin converting enzyme inhibitors from natural products via origami microfluidic paper-based analytical devices with colorimetric detection

We report the screening of angiotensin converting enzyme (ACE) inhibitors on an origami microfluidic paper-based analytical device (μPAD) using colorimetric detection. The hydrolysis product reacts with ninhydrin, resulting in a purple color at the detection zones. Images of the μPADs are captured using a common cell phone and analyzed with Photoshop software. This platform allows six independent colorimetric reactions to take place simultaneously, and the IC50 values can be obtained in a single run within 22 min. The relative standard deviations of inhibition efficiencies are generally lower than 4.0 % (n = 5). The IC50 values of captopril and five products from natural plants were obtained and corresponded well with UV methods. The relative deviations between the two methods are within the range of −5 % to +5 %. This work is a proof-of-concept successfully demonstrating the use of μPADs technology to screen enzyme inhibitors from natural products.

Multigram Synthesis of Dimethyl Stellane-1,5-Dicarboxylateas a Key Precursor for the ortho-Benzene Mimics.

Herein we present previously unavailable C(sp3)-rich polycyclic hydrocarbon scaffolds which have a potential to become valuable tools in medicinal chemistry and crop science as saturated bioisosteres of benzenoids. We have developed a scalable protocol (up to 50 g from a single synthetic run) for the synthesis of tricyclo[3.3.0.03,7]octane (bisnoradamantane or stellane) 1,5-dicarboxylic acid derivatives. X-ray crystallographic analysis of the stellane 1,5-dicarboxylic acid dimethyl ester has revealed that this scaffold is an optimal saturated isostere for ortho-disubstituted benzene where substituents exhibit the in-plane topology. The synthetic protocol is based on the oxidative cyclization of dimethyl octahydropentalene-2,5-dicarboxylate (DMOD) through lithiation followed by I2 oxidation. The reaction outcome is determined by the stereochemistry of the substrate. While the endo,endo cis-DMOD, exclusively gives the "unwanted" Claisen cyclization product the exo,endo cis- and exo,exo cis- stereoisomers afford the desired stellane 1,5-dicarboxylic acid dimethyl ester quantitatively. DFT computations have revealed that the reaction proceeds via the dianion of dimethyl octahydropentalene-2,5-dicarboxylate, which undergoes SET oxidation by I2 to form a radical anion. The subsequent cyclization followed by a second SET oxidation gives desired stellane derivative.

Simultaneous qualitative and quantitative determination of 104 fat-soluble synthetic dyes in foods using disperse solid-phase extraction and UHPLC-Q-Orbitrap HRMS analysis.

Public exposure to synthetic dyes through foods has attracted ongoing and serious attention. Here we developed and validated a simultaneous screening and quantitation method for the analysis of fat-soluble synthetic dyes that most frequently found in foods, using C18 d-SPE clean-up and UHPLC-Q-Orbitrap HRMS on Full-MS/dd-MS2 mode. During a single run, 104 dyes including 6 pairs of isomers were distinguished based on chromatographic separation and unique product ions. The method showed satisfactory linearity (R>0.99), recoveries (61.3%-118.8%), precision (<20%) and limit of quantification (0.05-0.5mg/kg). For 98% of test dyes, screening detection limits ranged from 2.5 to 25μg/kg. The validated method was successfully applied to real commercial foodstuffs revealing the presence of two selected illegal dyes in three samples.

A Single-Run HPLC-MS Multiplex Assay for Therapeutic Drug Monitoring of Relevant First- and Second-Line Antibiotics in the Treatment of Drug-Resistant Tuberculosis.

The treatment of drug-resistant Mycobacterium tuberculosis relies on complex antibiotic therapy. Inadequate antibiotic exposure can lead to treatment failure, acquired drug resistance, and an increased risk of adverse events. Therapeutic drug monitoring (TDM) can be used to optimize the antibiotic exposure. Therefore, we aimed to develop a single-run multiplex assay using high-performance liquid chromatography-mass spectrometry (HPLC-MS) for TDM of patients with multidrug-resistant, pre-extensively drug-resistant and extensively drug-resistant tuberculosis. A target profile for sufficient performance, based on the intended clinical application, was established and the assay was developed accordingly. Antibiotics were analyzed on a zwitterionic hydrophilic interaction liquid chromatography column and a triple quadrupole mass spectrometer using stable isotope-labeled internal standards. The assay was sufficiently sensitive to monitor drug concentrations over five half-lives for rifampicin, rifabutin, levofloxacin, moxifloxacin, bedaquiline, linezolid, clofazimine, terizidone/cycloserine, ethambutol, delamanid, pyrazinamide, meropenem, prothionamide, and para-amino salicylic acid (PAS). Accuracy and precision were sufficient to support clinical decision making (≤±15% in clinical samples and ±20-25% in spiked samples, with 80% of future measured concentrations predicted to fall within ±40% of nominal concentrations). The method was applied in the TDM of two patients with complex drug-resistant tuberculosis. All relevant antibiotics from their regimens could be quantified and high-dose therapy was initiated, followed by microbiological conversion. In conclusion, we developed a multiplex assay that enables TDM of the relevant first- and second-line anti-tuberculosis medicines in a single run and was able to show its applicability in TDM of two drug-resistant tuberculosis patients.

Low bandgap GaAsNBi solar cells

The development of low bandgap GaAsNBi solar cells grown using MBE is reported. The devices include a pin heterostructure with GaAsNBi as the i-layer. The substrate rotation is stopped during epitaxy of the GaAsNBi layer (stationary growth), resulting in a continuous variation in the source fluxes over the wafer, enabling the investigation of a wide range of growth conditions in a single growth run. In particular, we investigate the photovoltaic properties as a function of the As/Ga flux ratio around the critical stoichiometric value. For slightly below stoichiometric As/Ga, the lattice mismatch and bandgap energy are minimized to 8 × 10-4 and 0.86 eV, respectively, while the crystal quality remains good. Increasing As/Ga over the stoichiometric ratio leads to a rapid increase in the tensile mismatch and bandgap energy, likely due to reduction in Bi incorporation. Despite a slightly higher open-circuit voltage offset at high As/Ga, this also leads to an clear increase in the external quantum efficiency and short-circuit current, suggesting significant differences in the carrier collection efficiencies. The results demonstrate the importance of the As/Ga flux ratio in controlling the solar cell performance, and the viability of GaAsNBi as a candidate for a low bandgap subjunction in multijunction solar cells.

Tuning the bandgap of 2D metallic Zn nanostructures

The semiconducting behavior of two-dimensional (2D) metal nanostructures has recently attracted much interest for their possible applications in optoelectronics and others. In particular, tuning the bandgap of such nanostructures can open up a new avenue for fabricating functional nano-devices. In the present article, we report the synthesis of 2D metallic Zn nanosheets at room temperature using a ball mill, which is capable of producing large-scale materials in a single run. Initially, nanoplates were formed for ball milling the octahedral-shaped Zn nanoparticles for the time of milling of 6 h. Subsequent ball milling for another 6 h leads these nanoplates to nearly uniform nanosheets. The thickness of these 2D nanostructures was found to decrease with an increase in the time of milling. Visible photoluminescence (PL) emissions centered at ∼3, ∼2.9, and ∼2.75 eV were observed from all the Zn particles showing semiconductor behavior. The origin of such semiconductor behavior was explained based on the radiative transition of electrons from the sp band to the upper states of the 3d band. This argument was confirmed through the studies of photoelectron spectroscopy and the first principle calculations employing density functional theory (DFT). Furthermore, excitation-dependent PL studies indicated that the bandgap of the 2D Zn nanostructures decreased with the increase in the ball milling time. Therefore, a redshift in the bandgap was observed with the increase in the ball milling time. Such changes in the bandgap with the thickness of 2D Zn nanostructures were also verified from the studies of DFT. Thus, the present study demonstrated that the bandgap of 2D metallic Zn nanostructures could be effectively tuned by reducing the thickness.

Parametric simulation of electron backscatter diffraction patterns through generative models

Recently, discriminative machine learning models have been widely used to predict various attributes from Electron Backscatter Diffraction (EBSD) patterns. However, there has never been any generative model developed for EBSD pattern simulation. On one hand, the training of generative models is much harder than that of discriminative ones; On the other hand, numerous variables affecting EBSD pattern formation make the input space high-dimensional and its relationship with the distribution of backscattered electrons complicated. In this study, we propose a framework (EBSD-CVAE/GAN) with great flexibility and scalability to realize parametric simulation of EBSD patterns. Compared with the frequently used forward model, EBSD-CVAE/GAN can take variables more than just orientation and generate corresponding EBSD patterns in a single run. The accuracy and quality of generated patterns are systematically evaluated. The model does not only summarize a distribution of backscattered electrons at a higher level, but also mitigates data scarcity in this field.

In Situ Rapid Analysis of Squalene, Tocopherols, and Sterols in Walnut Oils Based on Supercritical Fluid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry.

Quantification of liposoluble micronutrients in large-scale vegetable oil samples is urgently needed, because their health benefits are increasingly emphasized. However, current analytical methods are limited to either labor-intensive preparation processes or time-consuming chromatography separation. In this work, an online oil matrix separation strategy for direct, rapid, and simultaneous determination of squalene, tocopherols, and phytosterols in walnut oil (WO) was developed on the basis of the lipid class separation mode of supercritical fluid chromatography. A single run was completed in 13 min containing 6 min of column cleaning and balancing. Satisfactory limit of detections (0.05-0.20 ng/mL), limit of quantifications (0.15-0.45 ng/mL), recoveries (70.61-101.44%), and matrix effects (78.43-91.62%) were achieved, indicating the reliability of this method. In addition, eight sterol esters were identified in WO, which have not previously been reported. The proposed method was applied to characterize the liposoluble micronutrient profile of WO samples obtained from different walnut cultivars, geographical origins, and processes.

Design and Development of Mini Tractor Operated Multipurpose Equipment for Groundnut Crop

A study was developed to design and fabricate a multipurpose equipment during the year of 2021 in the Departmental Workshop of Farm Machinery and Power Engineering and evaluated at field of Dr. NTR College of Agricultural Engineering, Bapatla, Andhra Pradesh, India. The proposed design of machine is economical to fabricate, and have greater design simplicity than its counterpart, with proper seed placement at desired depth, distance between rowsis adjusted because of tynes are fitted with the nut and bolts. Developed multipurpose equipment also done spraying and weeding attachment can be used simultaneously on single run in groundnut crop so that, the time and labour can be saved and it can be used for any narrow row crops for intercultural operations. The overall dimensions of developed multipurpose equipment are 1800×600×1550 mm and the weight of machine was 150 kg. The designed and develop machine was operated at various speeds i.e 1.8, 2.5 and 3.2 km h-1. The field efficiency while doing sowing, spraying and weeding of equipment varies from 78,83 and 78% at 1.8, 2.5 and 3.2 km h-1. The different operations were operated effectively at 2.5 km h-1. The use of multipurpose equipment helps to overcome the problems of drudgery, labour shortage timeless of operation and as a result, the farm power availability in farms can be increased. Hence, there is a need for a multipurpose implement for carrying different operations in groundnut crop.