Good Agreement Research Articles

Microstereolithography-fabricated microneedles for fluid sampling of histamine-contaminated tuna

A custom-designed microneedle sampling system was prepared using dynamic mask microstereolithography; this sampling system was used for determination of histamine content in fresh, histamine-spiked, and spoiled tuna flesh. Lateral flow (test strip) assays were successfully utilized in the microneedle sampling system to assess histamine content. Good agreement was noted between data obtained from the microneedle sampling system and a commercially available histamine detection kit. A discrepancy was noted in the results from the microneedle sampling system and the commercially available histamine detection kit at low (negative) levels of histamine. There was an improvement in the agreement between the microneedle sampling system and the commercially available histamine detection kit at higher histamine levels. The results, which showed an improvement in the test duration and the amount of reagent needed for histamine detection, indicate the promise of printed microneedle sampling systems for histamine detection in seafood samples and other types of food testing.

Treatment of Reactive Orange 16 Dye-Bearing Wastewater by Electro-Fenton Process with Stainless-Steel Electrodes: Statistical Optimization and Operational Analysis

Abstract: In the current work, the Electro-Fenton (EF) based Reactive Orange 16 (RO16) dye treatment was studied and compared with central composite (CC) and Taguchi design (TD) statistical optimization tools. Color removal (RC) and COD decay (RCOD) were chosen responses for the effect of pH (A), electrolysis time (B), initial dye concentration (C), and current density (D). The facecentred CC design and L16 orthogonal array were used in the experimental procedures. At optimal conditions, the coefficient of determination (R2) values of 0.99 for CC and 0.97 for TD suggest statistical significance and good model agreement. The results of the ANOVA and Prob. > F values supported the model’s successful experimental data fitting. Taguchi method was found as an appropriate methodology for parameter percentage contributions with fewer experimental runs. Moreover, the S/N ratio charts proved to be a successful CC design replacement. The current density and pH were found to be the most important factors for the EF process. A higher biodegradability (BOD5/COD) and minimum iron concentration (0.45 mg/L) in the effluent sludge demonstrated good environmental disposal suitability. In the last, the effect of various inhibitors/scavengers (SO4 −2, PO4 −3, EDTA, etc.) on the EF process performance was also carried out.

An evaluation of AI generated literature reviews in musculoskeletal radiology

PurposeThe use of artificial intelligence (AI) tools to aid in summarizing information in medicine and research has recently garnered a huge amount of interest. While tools such as ChatGPT produce convincing and naturally sounding output, the answers are sometimes incorrect. Some of these drawbacks, it is hoped, can be avoided by using programmes trained for a more specific scope. In this study we compared the performance of a new AI tool (the-literature.com) to the latest version OpenAI's ChatGPT (GPT-4) in summarizing topics that the authors have significantly contributed to. MethodsThe AI tools were asked to produce a literature review on 7 topics. These were selected based on the research topics that the authors were intimately familiar with and have contributed to through their own publications. The output produced by the AI tools were graded on a 1–5 Likert scale for accuracy, comprehensiveness, and relevance by two fellowship trained consultant radiologists. ResultsThe-literature.com produced 3 excellent summaries, 3 very poor summaries not relevant to the prompt, and one summary, which was relevant but did not include all relevant papers. All of the summaries produced by GPT-4 were relevant, but fewer relevant papers were identified. The average Likert rating was for the-literature was 2.88 and 3.86 for GPT-4. There was good agreement between the ratings of both radiologists (ICC = 0.883). ConclusionSummaries produced by AI in its current state require careful human validation. GPT-4 on average provides higher quality summaries. Neither tool can reliably identify all relevant publications.

Sputtering Heterogeneous Tungsten Carbide Targets by Light Ions Bombardment

Background:: This paper presents a model for sputtering heterogeneous two-component materials with light ions. Method:: The model, based on two sputtering mechanisms, makes it possible to calculate the total sputtering coefficients of the target components, and it is easily transformed for the case of sputtering different types of targets. Model testing was conducted for the case of sputtering homogeneous tungsten carbide targets with ions of different energies. Results:: The results of the calculations are given in comparison with experimental data and the results of computer simulation. The comparison shows good agreement of the calculated values with the data of other authors. The proposed model was used to describe stationary (stoichiometric) sputtering of tungsten carbide targets. Using this model, the concentrations of components in the modified target layer were calculated, and the thickness of the modified layer was also estimated. Conclusion:: The method of calculating the concentration of target components in the modified layer and the thickness of this layer can be the basis of the technology of creating materials with given properties of the surface layer.

Analysis of the Optical Properties and Electronic Structure of Semiconductors of the Cu2NiXS4 (X = Si, Ge, Sn) Family as New Promising Materials for Optoelectronic Devices

In this work, the optoelectronic characteristics of kesterites of the Cu2NiXS4 system (X = Si, Ge, Sn) were studied. The electronic properties of the Cu2NiXS4 (X = Si, Ge, Sn) system were studied using first-principles calculations within the framework of density functional theory. For calculations, ab initio codes VASP and Wien2k were used. The high-precision modified Beke-Jones (mBJ) functional and the hybrid HSE06 functional were used to estimate the bandgap, electronic, and optical properties. Calculations have shown that when replacing Si with Ge and Sn, the band gap decreases from 2.58 eV to 1.33 eV. Replacing Si with Ge and Sn reduces the overall density of electronic states. In addition, new deep (shallow) states are formed in the band gap of these crystals, which is confirmed by the behavior of their optical properties. The obtained band gap values are compared with existing experimental measurements, demonstrating good agreement between HSE06 calculations and experimental data. The nature of changes in the dielectric constant, absorption capacity, and optical conductivity of these systems depending on the photon energy has also been studied. The statistical dielectric constant and refractive index of these materials were found. The results will help increase the amount of information about the properties of the materials under study and will allow the use of these compounds in a wider range of optoelectronic devices, in particular, in solar cells and other devices that use solar radiation to generate electric current.

Developing screening tools to estimate the risk of diabetic kidney disease in patients with type 2 diabetes mellitus.

Diabetic kidney disease (DKD) is an important microvascular complication of diabetes mellitus (DM). This study aimed to develop predictive nomograms to estimate the risk of DKD in patients with type 2 diabetes mellitus (T2DM). The medical records of patients with T2DM in our hospital from March 2022 to March 2023 were retrospectively reviewed. The enrolled patients were randomly selected for training and validation sets in a 7:3 ratio. The models for predicting risk of DKD were virtualized by the nomograms using logistic regression analysis. Among the enrolled 597 patients, 418 were assigned to the training set, while 179 were assigned to the validation set. Using the predictors included glycated hemoglobin A1c (HbA1c), high density lipoprotein cholesterol (HDL-C), presence of diabetic retinopathy (DR) and duration of diabetes (DD), we constructed a full model (model 1) for predicting DKD. And using the laboratory indexes of HbA1c, HDL-C, and cystatin C (Cys-C), we developed a laboratory-based model (model 2). The C-indexes were 0.897 for model 1 and 0.867 for model 2, respectively. The calibration curves demonstrated a good agreement between prediction and observation in the two models. The decision curve analysis (DCA) curves showed that the two models achieved a net benefit across all threshold probabilities. We successfully constructed two prediction models to evaluate the risk of DKD in patients with T2DM. The two models exhibited good predictive performance and could be recommended for DKD screening and early detection.

Design and Analysis of Surface-Mounted Permanent-Magnet Field-Modulation Machine for Achieving High Power Factor

Along with the establishment of general air-gap field modulation theory, a new type of field-modulation machine has attracted increasing attention. However, the low power factor always plagued its popularization. This paper is to focus on the simplest structure surface-mounted permanent-magnet field-modulation (SMPMFM) machine, aiming at exploring the implementation of high power-factor design. The key is that the power factor calculation formula is derived parametrically, hence the originally vague causal relationship between the structural parameters and power factor become clear, guided by which the initial structure design for high power factor achievement is determined, meanwhile the power factor adjustment evaluation and the electromagnetic performance comparison with the help of finite element analysis (FEA) are conducted to verify the validity of the proposed power factor calculation formula. Finally, a feasible high-power-factor SMPMFM prototype is fabricated and the experimental testing is performed, which has a good agreement with the formular calculation and FEA results. Hence, the validity of the proposed analysis for achieving high power-factor design of field-modulation machines is verified.

A method of determining the bremsstrahlung flux-weighted average photonuclear cross section

Based on a developed analytical model, a method is proposed for measuring the photonuclear cross section averaged over bremsstrahlung flux without application of additional target-monitor of photon flux. The method involves the use of a thin isotopic target, that completely overlaps the photon beam (a photonuclear converter), as well as an algorithm for processing the data on the yield of a reaction under study in such a target. The novel technique was validated on the reactions 100Mo(γ,n)99Mo and 58Ni(γ,n)57Ni in the range of photon end-point energy of 40.7–93.9 MeV. The photon flux-weighted average cross sections of the reactions measured experimentally are in good agreement with Monte Carlo simulations and TALYS predictions on their excitation functions.

Multioutput Wireless Charger for Drone Swarms With Reduced Switch Requirements and Independent Regulation Capability

This paper develops a cost-effective and efficient wireless charger with multiple outputs based on newly proposed H3 bridge inverter, which has the benefits of reduced switch requirements and independent regulation capability. The output power of each channel is regulated by asymmetric duty cycle control. With the help of auxiliary LC branch, soft switching is ensured in spite of load variations. The sequential logic of driver signals is analyzed in detail to explore the independent regulation characteristic. For arbitrary 2 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> (or 2 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> +1) outputs, the total number of required switches is only 3 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> (or 3 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> +2) and the voltage stress of switches is the input voltage, which can reduce switch requirements. Simulation and experimental results are in good agreement with each other, proving the proposed wireless charger as a feasible solution for drone swarms.

Forecasting High Wind Events in the HRRR Model over Wyoming and Colorado. Part I: Evaluation of Wind Speeds and Gusts

Abstract Strong wind events cause significant societal damage ranging from loss of property and disruption of commerce to loss of life. Over portions of the United States, the strongest winds occur in the cold season and may be driven by interactions with the terrain (downslope winds, gap flow, and mountain wave activity). In the first part of this two-part series, we evaluate the High-Resolution Rapid Refresh (HRRR) model wind speed and gust forecasts for the 2016–22 winter months over Wyoming and Colorado, an area prone to downslope windstorms and gap flows due to its complex topography. The HRRR model exhibits a positive bias for low wind speeds/gusts and a large negative bias for strong wind speeds/gusts. In general, the model misses many strong wind events, but when it does predict strong winds, there is a high false alarm probability. An analysis of proxies for surface winds is conducted. Specifically, 700- and 850-mb (1 mb = 1 hPa) geopotential height gradients are found to be good proxies for strong wind speeds and gusts at two wind-prone locations in Wyoming. Given the good agreement between low-level height gradients and surface wind speeds yet a strong negative bias for strong wind speeds and gusts, there is a potential shortcoming in the boundary layer physics in the HRRR model with regard to predicting strong winds over complex terrain, which is the focus of the second part of this two-part study. Last, the sites with the largest strong wind speed bias are found to mostly sit on the leeward side of high mountains, suggesting that the HRRR model performs poorly in the prediction of downslope windstorms. Significance Statement We investigate the performance of the High-Resolution Rapid Refresh (HRRR) model with respect to strong wintertime wind speeds and gusts over the complex terrain of Wyoming and Colorado. We show that the overall performance of the HRRR model is low with regard to strong wind speed and wind gust forecasts across the investigated winter seasons, with a large negative bias in predicted strong wind speeds and gusts and a small positive bias for weak wind speeds and gusts. The largest biases are found to be on the leeward side of high mountains, indicating poor prediction of downslope winds. This study also utilizes National Weather Service forecasting metrics to understand their performance with respect to strong wind forecasts, and we find that they provide skill in forecasting these events.

Establishment and Validation of a Blood Test-based Nomogram to Diagnose Patients with AFP-negative HCC.

Hepatocellular carcinoma (HCC) is the fourth leading cause of cancer death worldwide. Alpha-protein (AFP) is the most widely used blood biomarker for HCC. However, elevated serum AFP is only observed in part of HCC. This study aimed to develop an efficient nomogram model to distinguish patients with alpha- protein-negative HCC and liver cirrhosis. A total of 1130 patients (508 HCC patients + 622 cirrhosis patients) were enrolled in the training cohort. A total of 244 HCC patients and 246 cirrhosis patients were enrolled in the validation cohort. A total of 41 parameters about blood tests were analyzed with logistic regression. The nomogram was based on independent factors and validated both internally and externally. Independent factors were eosinophils %, hemoglobin concentration distribution width, fibrinogen, platelet counts, total bile acid, and mitochondria aspartate aminotransferase. The calibration curve for the probability of HCC showed good agreement between prediction by nomogram and actual observation. The concordance index was 0.851. In the validation cohort, the nomogram distinguished HCC from liver cirrhosis with an area under the curve of receiver operating characteristic of 0.754. This proposed nomogram was an accurate and useful method to distinguish patients with AFP-negative HCC from liver cirrhosis.

Comparable cigarette consumption data collected using timeline follow-back and digital diary among treatment-seeking smokers.

The timeline follow-back interview is a common method of collecting daily cigarette consumption (cigarettes per day [CPD]) in smoking research. However, it may be subject to recall bias due to its reliance on retrospective reports. The increasing ownership of smartphones allows researchers to administer app-based digital diaries (DD) to collect CPD, which is expected to have less recall bias. Several studies have compared these two methods and found a noticeable discrepancy between them. However, these studies have mainly focused on the time window when smokers were smoking ad libitum. In this study, we wanted to determine the comparability of these two methods when treatment-seeking smokers are attempting to quit smoking. In a cessation trial, treatment-seeking smokers (n = 251) reported their CPD using the timeline follow-back and DD methods over a 12-week treatment period. To evaluate the comparability, we used the Bland-Altman comparison approach for agreement, correlational analysis between CPD and biochemical measures, digit bias, and logistic regression for predicting abstinence. We found that the two methods exhibited good agreement, and the agreement did not vary as a function of consumption levels. Consistent with this agreement, CPD data from both methods showed similar correlations with biochemical measures of smoking and predicted 6-month abstinence in a comparable fashion. Despite the agreement, the DD method appeared to be more precise by having a lower digit bias than the timeline follow-back method. Capturing smoking behavior using either TLFB or DD approaches yields similar data while smokers are attempting to quit smoking. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Revisiting the rovibrational (de-)excitation of molecular hydrogen by helium

Context. The collisional (de-)excitation of H2 by He plays an important role in the thermal balance and chemistry of various astro-physical environments, making accurate rate coefficients essential for interpreting observations of the interstellar medium. Aims. Our goal is to utilize a state-of-the-art potential energy surface (PES) to provide comprehensive state-to-state rate coefficients for He-induced transitions among rovibrational levels of H2. Methods. We performed quantum scattering calculations for the H2-He system. Thus, we were able to provide state-to-state rate coefficients for 1059 transitions between rovibrational levels of H2, with internal energies up to ≃15 000 cm−1, for temperatures ranging from 20 to 8000 K. Results. Our results demonstrate a good agreement with previous calculations for pure rotational transitions between low-lying rotational levels. However, we do find significant discrepancies for rovibrational processes involving highly-excited rotational and vibrational states. We attribute these differences to two key factors: (1) the broader range of intramolecular distances covered by ab initio points and (2) the superior accuracy of the PES, resulting from the utilization of the state-of-the-art quantum chemistry methods, compared to previous lower-level calculations. Conclusions. Radiative transfer calculations performed with the new collisional data indicate that the population of rotational levels in excited vibrational states experiences significant modifications, highlighting the critical need for this updated dataset in models of high-temperature astrophysical environments.

Numerical study of transitions in lid-driven flows in shallow cavities

In this article, three dimensional (3D) lid-driven flow in shallow cavities with a unit square base are studied. The numerical solution of the Navier–Stokes equations modeling incompressible viscous fluid flow in a cavity is obtained via a methodology combining a first order accurate operator-splitting scheme, a L 2 -projection Stokes solver, a wave-like equation treatment of the advection and finite element space approximations. Numerical results of a lid-driven flow in a cubic cavity show a good agreement with those reported in literature. The critical Reynolds numbers (Re cr ) for having flow with increasing of oscillating amplitude (a Hopf bifurcation) in different shallow cavities are obtained and associated oscillating modes are studied.

The Nanoplasmonic Purcell Effect in Ultrafast and High-Light-Yield Perovskite Scintillators.

The development of X-ray scintillators with ultrahigh light yields and ultrafast response times is a long sought-after goal. In this work, a fundamental mechanism that pushes the frontiers of ultrafast X-ray scintillator performance is theoretically predicted and experimentally demonstrated: the use of nanoscale-confined surface plasmon polariton modes to tailor the scintillator response time via the Purcell effect. By incorporating nanoplasmonic materials in scintillator devices, this work predicts over tenfold enhancement in decay rate and 38% reduction in time resolution even with only a simple planar design. The nanoplasmonic Purcell effect is experimentally demonstrated using perovskite scintillators, enhancing the light yield by over 120% to 88 ± 11 ph/keV, and the decay rate by over 60% to 2.0 ± 0.2 ns for the average decay time, and 0.7 ± 0.1 ns for the ultrafast decay component, in good agreement with the predictions of ourtheoretical framework. Proof-of-concept X-ray imaging experiments are performed using nanoplasmonic scintillators, demonstrating 182% enhancement in the modulation transfer function at four line pairs per millimeter spatial frequency. This work highlights the enormous potential of nanoplasmonics in optimizing ultrafast scintillator devices for applications including time-of-flight X-ray imaging and photon-counting computed tomography.

Investigating the Mixture Quality in Multi-Injector Burner Systems, Part II: Model Application

Abstract Multi-injector burner systems offer a high spatial-temporal mixture homogeneity due to their small size and thus have a high NOx emission reduction potential at increasing flame temperatures. This potential is reduced due to the sensitivity of the mixing quality to inflow distortions caused by the flow path in the burner head. A deep understanding of the link between the inflow conditions and the mixture quality helps to optimize the flow field upstream of the injectors within the spatial and pressure loss constraints of gas turbine combustors to obtain minimal NOx emissions. This paper presents a new model approach for determining the mixture quality in multi-injector burners with output-based proper orthogonal decomposition (O-POD). The sensitivity to the inflow distortion is considered with the so-called observable vector, which describes the injector inflow conditions and is given as model input. The target quantity is the probability mass function (PMF) of the equivalence ratio at the injector outlet. This model allows a fast estimation of the mixing PMF for arbitrary inflow conditions, which is otherwise only accessible with complex time-resolved experimental or numerical approaches. The performance of the model was demonstrated with 21 reference datasets, for which a good agreement between the experimental results and the model output was obtained.

Numerical Investigation of a Hydrogen–Air Flame for NOx Prediction

Abstract Sustainable aviation fuels are a major candidate to reduce pollutant emissions in future aeronautical engines. Recently, the use of hydrogen as a fuel has gained a high interest partly because its combustion is free from carbon dioxide, a greenhouse gas, and produces few pollutants, mainly nitrogen oxides (NOx). Over the last decades, efforts on numerical methods for combustion simulation in aero-engines have largely been focused on kerosene-air combustion. However, the current transition may have a significant impact on the computational methodologies for combustor design. Hydrogen defines novel modeling issues and challenges the current state of art on numerical methodologies. The current study presents a numerical investigation of a hydrogen–air burner using large-eddy simulations (LES) with a focus on NOx prediction. The considered configuration is a two-staged combustor, similar to the well-known RQL (Rich-Quench-Lean) technology, supplied by a single coaxial injector characterized experimentally. Two combustion models are investigated: (i) tabulated chemistry based on premixed flamelets (ii) transported chemistry description by using a 21-species chemical scheme. Numerical results are compared with experimental data (NOx concentrations, temperature distributions, pressure losses). A focus on model predictions is carried out. Results show a good agreement to predict the main flow characteristics and the premixed flame position over different operating points and geometries for both frameworks. In contrast, NOx emissions are more sensitive: while the overall trend is well captured, the quantification is more scattered. Finally, an in-depth analysis is proposed to link NOx production with the nonpremixed flame size.

Nonlinear Analytical Solution in Axial Flux Permanent Magnet Machines Using Scalar Potential

Analytical model (AM) has significant value on early design stage for electric machines, in terms of both time and accuracy. AM can be developed based on vector or scalar potential, but all AMs for armature reaction are using the vector potential, and it is a difficult matter to model armature reaction by scalar potential. This is the gap that the work here proposed aims to fill. We, for the first time, report the load magnetic field prediction by using magnetic scalar potential. Also, the proposed nonlinear AM is developed for the surface mounted permanent magnet machine. The proposed model is development based on the two-dimensional harmonic subdomain approach by solving the Maxwell's equations. The magnetic sources, viz., the armature reaction is regarded as line current and solved at the connection boundaries. The comprehensive derivations and calculation algorithm are explained in detail. Moreover, the analytical model is developed for an axial flux PM machine, both finite element model and experiment are verified the correctness of proposed model, and good agreement is achieved. Moreover, a slightly modification can also be applied to the radial flux PM machines.

Indication of a fast ejecta fragment in the atomic cloud interacting with the southwestern limb of SN 1006

Context. Supernova remnants interacting with molecular and atomic clouds are interesting X-ray sources for studies of broadband nonthermal emission. X-ray line emission in these systems can be produced by different processes, such as low-energy cosmic rays (LECRs) interacting with the cloud and fast ejecta fragments moving in the cloud. Aims. This paper is aimed at studying the origin of the non-thermal X-ray emission of the southwestern limb of SN 1006 beyond the main shock to determine whether the emission is due to LECRs diffusing in the cloud or to ejecta knots moving into the cloud. Methods. We analyzed the X-ray emission of the southwestern limb of SN 1006, where the remnant interacts with an atomic cloud, using three different X-ray telescopes: NuSTAR, Chandra, and XMM-Newton. We also performed a combined spectro-imaging analysis of this region. Results. Our analysis of the nonthermal X-ray emission of the southwestern limb of SN 1006 interacting with an atomic cloud has led to the detection of an extended X-ray source in the atomic cloud, approximately 2 pc upstream of the shock front. The source is characterized by a hard continuum (described by a power law with photon index Γ ∼ 1.4) and by Ne, Si, and Fe emission lines. The observed flux suggests that the origin of the X-ray emission is not associated with LECRs interacting with the cloud. On the other hand, the spectral properties of the source, together with the detection of an IR counterpart visible with Spitzer-MIPS at 24 μm, are in good agreement with the general expectations for a fast ejecta fragment moving within the atomic cloud. Conclusions. We detected X-ray and IR emission from a possible ejecta fragment, with an approximate radius of 1 × 1017 cm and approximate mass of 10−3 M⊙ at about 2 pc out of the shell of SN 1006, in the interaction region between the southwestern limb of the remnant and the atomic cloud.

Effects of hammer configurations on pearl millet grinding system with a hammer mill: theory and experiment

In grinding processes using hammer mills, the configuration, number and speed of hammers are some of the main factors that can affect system performance. This paper aims to investigate the effects of hammer configurations in terms of specific energy consumption (SEC), grinding mass efficiency, and productivity. These effects were studied theoretically on the basis of classical grinding laws and experimentally with four different hammer configurations. From theoretical studies, a decreasing power model of SEC versus hammer configurations was developed, which was then validated with a determination coefficient of 0.99 in experiments using a 2 HP-DC hammer mill. The good agreement between theoretical and experimental results confirms that the specific energy consumption and the productivity are directly dependent on hammer configurations, but the effects are not significant for grinding mass efficiency.