Sample Length Research Articles

Impact of molecular convection in time-resolved thermal lensing: a computational exploration

In this study, we comprehensively investigate thermal lens (TL) spectroscopy, known for its ultra-sensitivity in probing molecular properties through nonlinear heating responses to femtosecond lasers. Using time-resolved TL spectroscopy and numerical simulations, we focus on the influence of convection on heat generation and the resulting phase shift in the probe beam. We examined single-beam, dual-beam same wavelength, and dual-beam different wavelength scenarios, systematically investigating power dependence, pump beam spot size, and sample length limitations. Our findings reveal a direct relationship between the TL effect and pump power, resulting in decreased probe beam transmittance with increasing convection. Additionally, the TL strength grows within the Rayleigh regime as the sample length increases. Utilizing the same wavelength for the probe beam enhances the TL effect in dual-beam setups. Notably, tight focusing of the pump beam substantially reduces the lag between convection and conduction. Our empirical results closely match the experimental data, providing a thorough explanation of the TL process and its underlying principles. These insights can be applied to design and optimize TL-based optical devices and systems for higher sensitivity, highlighting the potential of TL spectroscopy in advanced molecular property probing.

Van der Waals Stacking-Determined Polymorphs of Quasi-One-Dimensional BiSCl Grown by Chemical Vapor Deposition.

We report chemical vapor deposition (CVD) synthesis of two quasi-one-dimensional (quasi-1D) polymorphs of BiSCl, denoted by y-BiSCl and r-BiSCl. The length of the CVD samples can reach about 0.4 mm. Such quasi-1D samples of the two polymorphs can be readily separated into individual pieces for either characterization or application. The two polymorphs can be clearly differentiated by Raman spectroscopy. First-principles calculations and group analysis are used to assign each Raman peak to the corresponding vibrational mode. Ultraviolet-visible measurements on solution grown thin-film samples reveal that the two polymorphs exhibit significantly different band gaps of 2.08 eV (y-BiSCl) and 1.81 eV (r-BiSCl). First-principles calculation further shows that the interatomic chain binding energy is 18.1 meV/Å2, confirming that the van der Waals stacking determines the difference in their band gaps. Our findings highlight the possibility of realizing the desired functionalities in quasi-1D materials by controlling stacking orientation.

Analyzing Monofractal Short and Very Short Time Series: A Comparison of Detrended Fluctuation Analysis and Convolutional Neural Networks as Classifiers

Time series data are a crucial information source for various natural and societal processes. Short time series can exhibit long-range correlations that reveal significant features not easily discernible in longer ones. Such short time series find utility in AI applications for training models to recognize patterns, make predictions, and perform classification tasks. However, traditional methods like DFA fail as classifiers for monofractal short time series, especially when the series are very short. In this study, we evaluate the performance of the traditional DFA method against the CNN-SVM approach of neural networks as classifiers for different monofractal models. We examine their performance as a function of the decreasing length of synthetic samples. The results demonstrate that CNN-SVM achieves superior classification rates compared to DFA. The overall accuracy rate of CNN-SVM ranges between 64% and 98%, whereas DFA’s accuracy rate ranges between 16% and 64%.

Computational modeling and statistical analysis of buckling characteristics of polysilicon reinforced fiber

The purpose of this study is to evaluate the effect of volume fraction of continuous carbon fiber and sample length on buckling characteristics of polysilicon. A statistical design of 12 samples were formulated with constant cross-section area of 2500 mm2 using Design of Experiment software (DOE). The samples were sketched using ABAQUS 2019 software, and the total buckling force each sample was estimated. The estimated buckling forces were statically evaluated as a response using DOE. The estimated forces of 3.48776e07, 4.00652e07 and 5.78142e07 newton for the simulated samples of 100 mm in length and 0,15, and 25% volume fraction respectively, is an indication of positive effect of fiber volume fraction on the necessary force for buckling. In addition, similar tendency was found in other samples (the higher fiber volume fractions the higher buckling force). However, the estimated buckling force for each sample was negatively affected with length of the sample. The result indicated a value of 4.00652E+07, 5.00447E+06 and 1.80390E+06 newton at a constant fiber volume fraction and different length of 100, 300 and 500 mm respectively. The statistical analysis of the simulated buckling force showed a signification design, and the date of one factor effect is highly supported by the simulated buckling forces. The equation of a significant design can be used to estimate the buckling force at any fiber volume fraction and sample length.

Data-Driven Batch Process Monitoring for Continuous Annealing of Cold-Rolled Strip Steel

The continuous annealing process (CAP) is a crucial process of steel production, which has a significant impact on the uniformity and stability of mechanical properties. A novel batch monitoring process based on kernel dissimilarity (KDISSIM) and Kmeans++ is proposed in this paper, focusing on problems such as unequal sample lengths between batches and nonlinearity between variables. First, KDISSIM is used to describe the dissimilarity between batches. Secondly, Kmeans++ is employed to improve the accuracy of clustering tasks based on historical batches. The largest cluster is considered to be at a relatively stable control level, and these batches are further used as training data. Then, the center batch and boundary batch of the training set are used as the reference batch and monitoring threshold for the monitoring model, respectively. Finally, the effectiveness of the proposed method is verified via the actual CAP data, providing a feasible solution for CAP batch monitoring.

Application of aminotrimethylphosphonic acid modified starch‐based flame retardant in cellulosic paper

AbstractThe development of green and efficient bio‐based flame retardants is very important for the development of flame‐retardant cellulosic paper. In this study, a novel type of starch‐based synergistic flame retardant (SAPU) was prepared using corn starch as carbon sources, amino trimethylphosphonic acid, and urea as phosphorus and nitrogen sources through the one‐pot method. Subsequently, the flame‐retardant cellulosic paper was prepared by impregnation, and the flame retardancy of the cellulosic paper was evaluated by vertical combustion, limiting oxygen index (LOI), and thermogravimetric analysis. The results demonstrated that the SAPU exhibited a favorable flame‐retardant effect on cellulosic paper. At a concentration of 25.0%, the vertical burning residue of flame‐retardant paper accounted for 49.16% of the total length of the paper sample, while the LOI was 39.4%. The tensile strength and burst index of cellulosic paper were found to be decreased by 6.36% and 19.1%, respectively, in comparison to the base paper. Conversely, the ring crush strength was observed to be increased by 156.2%. The carbon residue rate at 700°C under a nitrogen atmosphere rose from 11.56% of the base paper to 28.77% of the flame‐retardant paper. The flame‐retardant SAPU effectively improved the thermal stability of cellulosic paper.

CT guided versus non-image guided bone marrow aspiration and biopsy: Comparison of indications, specimen quality and cost

PurposeTo compare the indications, specimen quality, and cost of CT versus non-image guided bone marrow aspirate and biopsy (BMAB). MethodsAll CT and non-image guided BMAB performed from January 2013–July 2022 were studied. Body-mass-index (BMI), skin-to-bone distance, aspirate, and core specimen quality, and core sample length were documented. Indications for CT guided BMAB were recorded. Categorical variables were compared using chi-squared test and continuous variables using Mann-Whitney test. Analysis of per-biopsy factors used linear mixed-effect models to adjust for clustering. Cost of CT and non-image guided BMAB was taken from patient billing data. ResultsThere were 301 CT and 6535 non-image guided BMABs studied. All CT guided BMAB were studied. A subset of 317 non-image guided BMAB was selected randomly from the top ten CT BMAB referrers. BMI (kg/m2) and skin-to-bone distance (cm) was higher in the CT versus the non-image guided group; 34.4 v 26.8, p < 0.0001; 4.8 v 2.5, p < 0.0001, respectively. Aspirate and core sample quality were not different between groups, p = 0.21 and p = 0.12, respectively. CT guided core marrow samples were longer, p < 0.0001. The most common CT BMAB referral indications were large body habitus (47.7 %), failed attempt (18.8 %) and not stated (17.4 %). Cost of a CT guided BMAB with conscious sedation was $3945 USD versus $310 USD for non-image guided. ConclusionCT guided BMAB are commonly performed in patients with large body habitus and failed attempt. However, the cost is 12.7 fold higher with no increase in specimen quality. These findings can help referrers be cost conscious.

Universal and nonuniversal statistics of transmission in thin random layered media

The statistics of transmission through random 1D media are generally presumed to be universal and to depend only upon a single dimensionless parameter-the ratio of the sample length and the mean free path, s = L / ℓ . Here we show in numerical simulations and optical measurements of random binary systems, and most prominently in systems for which s<1, that the statistics of the logarithm of transmission, ln ⁡ T , are universal for transmission near the upper cutoff of unity and depend distinctively upon the reflectivity of the layer interfaces and their number near a lower cutoff. The universal segment of the probability distribution function of the logarithm of transmission, P ( ln ⁡ T ) is manifested with as few as three binary layers. For a given value of s, P ( ln ⁡ T ) evolves towards a universal distribution as the number of layers increases. Optical measurements in stacks of 5 and 20 glass coverslips exhibit statistics at low and moderate values of transmission that are close to those found in simulations for 1D layered media, while differences appear at higher transmission where the transmission time in the medium is longer and the wave explores the transverse nonuniformity of the sample.

Development of explainable recognition models for ADMFB flow regimes based on ensemble learning

The spatiotemporal characteristics of fluidization within an Air Dense Medium Fluidized Bed (ADMFB) are critical for its heat and mass transfer, as well as for mixing and separation processes. Yet, detailed analyses of the dynamic behavior of flow regimes during progressive transformations are scarce. This study captured synchronous pressure drop signals at multiple points along the sidewall of the bed using a non-intrusive measurement technique. Statistical analyses were utilized to extract the pressure drop's characteristic parameters and examine the statistical features' spatiotemporal fluctuations during fluidization state transitions. We proposed a method to quantitatively characterize the bed's real-time fluidization state through the combined use of multiple-point pressure characteristics. Following this approach, a multidimensional spatio-temporal matrix was constructed to depict the flow regime transitions quantitatively. Concurrently, ensemble learning techniques were applied to classify flow regimes based on various feature parameters and sample lengths. In the final phase, comprehensive interpretations and detailed visual analyses were deployed on the inputs to the optimized ensemble learning model, XGBoost, utilizing the Shapley Additive Explanations (SHAP) framework. This study provides additional insights and methodologies for managing the transition and intelligent control of flow regimes within an ADMFB.

Detection of congestive heart failure based on Gramian angular field and two-dimensional symbolic phase permutation entropy

Congestive heart failure (CHF) is a serious threat to human health. Electrocardiogram (ECG) signals have been proven to be useful in the detection of CHF. However, the low amplitude and short duration of the ECG signals, as well as the superimposed noise during the real-time acquisition of the signal, seriously affect the CHF detection. To improve the detection rate of CHF, this paper proposes a congestive heart failure detection method based on Gramian angular field (GAF) and two-dimensional symbolic phase permutation entropy (SPPE2D). The significant advantage of this method is that it reduces the sensitivity to noise, and good performance can be obtained without denoising using raw ECG signals. We segment the original ECG signals into 2 s non-overlapping segments and convert them into images using the GAF method. Then, the SPPE2D algorithm is proposed to measure the complexity between normal sinus rhythm (NSR) and CHF, and analyze the anti-noise performance of the algorithm. Finally, the SPPE2D features of GAF images are computed and input into a support vector machine (SVM) for CHF detection. Classification accuracy on the Massachusetts Institute of Technology − Beth Israel Hospital Normal Sinus Rhythm Database and Beth Israel Deaconess Medical Center Congestive Heart Failure Database is 99.59%, sensitivity is 99.42%, specificity is 99.80%, and F1-score is 99.62%. The accuracy of detecting CHF reach more than 97.75% in the other five CHF databases. The experimental results show that the method based on GAF and SPPE2D can effectively detect CHF by images of ECG signals and has good robustness. CHF can be detected using the 2 s sample lengths of ECG signals recording with high sensitivity, giving clinicians ample time to treat patients with CHF.

Assessing the Effect of Twisting and Twisting Fatigue on ZnO:Al Thin Film Performance on PEN and PET Substrates.

This study examines the electromechanical characteristics of aluminium-doped zinc oxide (AZO) films. The films were produced using the RF magnetron sputtering process with a consistent thickness of 150 nm on various polymer substrates. The study focuses on assessing the electro-mechanical failure processes of coated segments using flexible substrates, namely polyethylene naphthalate (PEN) and polyethylene terephthalate (PET), with a specific emphasis on typical cracking and delamination occurrences. This examination involves conducting twisting deformation together with using standardised electrical resistance measurements and optical microscope monitoring instruments. It was found that the crack initiation angle is mostly dependent on the mechanical mismatch between the coating and substrate. Higher critical twisting angle values are observed for the AZO/PEN film during twisting testing. Relative to the perpendicular plane of the untwisted sample, it was found that cracks initiated at a twist angle equal to 42° ± 2.1° and 38° ± 1.7° for AZO/PEN and AZO/PET, respectively, and propagated along the sample length. SEM images indicate that the twisting motion results in deformation in the thin film material, leading to the presence of both types of stress in the film structure. These discoveries emphasise the significance of studying the mechanical properties of thin films under different stress conditions, as it can impact their performance and reliability in real-world applications. The electromechanical stability of AZO was found to be similar on both substrates during fatigue testing. Studying the electromechanical properties of various material combinations is important for selecting polymer substrates and predicting the durability of flexible electronic devices made from polyester.

Null Phase Assumption-Based Technique for Constructing the Target Model of Seismic Irregularity on High-Speed Railways

High-speed railways are “lifeline projects” that shoulder the heavy responsibility of transporting relief supplies and medical forces for the first time after earthquakes. To ensure the train’s safety after earthquakes, it is of great urgency to ascertain a post-earthquake speed threshold. To that end, a target model for seismic irregularity emerges as a key parameter. In this paper, a null phase assumption-based technique for the mutual conversion between evolutionary power spectral density and non-stationary signal was proposed. Taking a high-speed railway track-bridge system as the research object, the target model of seismic irregularities was constructed based on the proposed technique. The rationality of the target model of seismic irregularities was verified, and the construction parameter settings were discussed. Moreover, a simplified frequency-domain fitting method for the target model of seismic irregularities was proposed based on the spectral decomposition theory. According to the research findings, the null phase assumption-based technique is capable of performing interconversion between seismic irregularity and its evolutionary power spectral density with satisfactory accuracy. It is recommended to set the minimum number of seismic irregularities, spatial sampling interval, hop size, and length of window function as 50, 0.25[Formula: see text]m, 1, and 40 to 100, respectively.

NerveTracker: a Python-based software toolkit for visualizing and tracking groups of nerve fibers in serial block-face microscopy with ultraviolet surface excitation images.

Information about the spatial organization of fibers within a nerve is crucial to our understanding of nerve anatomy and its response to neuromodulation therapies. A serial block-face microscopy method [three-dimensional microscopy with ultraviolet surface excitation (3D-MUSE)] has been developed to image nerves over extended depths ex vivo. To routinely visualize and track nerve fibers in these datasets, a dedicated and customizable software tool is required. Our objective was to develop custom software that includes image processing and visualization methods to perform microscopic tractography along the length of a peripheral nerve sample. We modified common computer vision algorithms (optic flow and structure tensor) to track groups of peripheral nerve fibers along the length of the nerve. Interactive streamline visualization and manual editing tools are provided. Optionally, deep learning segmentation of fascicles (fiber bundles) can be applied to constrain the tracts from inadvertently crossing into the epineurium. As an example, we performed tractography on vagus and tibial nerve datasets and assessed accuracy by comparing the resulting nerve tracts with segmentations of fascicles as they split and merge with each other in the nerve sample stack. We found that a normalized Dice overlap ( ) metric had a mean value above 0.75 across several millimeters along the nerve. We also found that the tractograms were robust to changes in certain image properties (e.g., downsampling in-plane and out-of-plane), which resulted in only a 2% to 9% change to the mean values. In a vagus nerve sample, tractography allowed us to readily identify that subsets of fibers from four distinct fascicles merge into a single fascicle as we move along the nerve's length. Overall, we demonstrated the feasibility of performing automated microscopic tractography on 3D-MUSE datasets of peripheral nerves. The software should be applicable to other imaging approaches. The code is available at https://github.com/ckolluru/NerveTracker.

Estimation of Fe Grade at an Ore Deposit Using Extreme Gradient Boosting Trees (XGBoost)

Estimating the spatial distribution of ore grade is one of the most critical and important steps to continue investment decision on the deposit. Kriging is the most widely used method to estimate the ore grade while alternative techniques are being developed. Machine learning algorithms can be used as alternative methods to classical kriging. In this paper, Fe grade of a deposit is estimated with XGBoost algorithm, and results are compared with kriging estimation results. For estimation processes, samples collected from the drillholes are used. To mitigate the effect of varying sampling length, both estimations use composites of these samples. Due to the different nature of the estimation methods, different steps have been taken to perform estimations. Results show that XGBoost estimates produced higher ranged estimates which is a desired result in ore grade estimation while minimum and maximum of the estimates were lower and higher than the kriging estimates, respectively. However, like kriging estimates, estimation results were smoother than composites while variance of the XGBoost estimates were lower than variance of composites. This means that even though estimation with XGBoost mitigates the smoothing effect, estimation results suffer from smoothing effect like kriging.

Virtual screening of cucurbituril host-guest complexes: Large-scale benchmark of end-point protocols under MM and QM Hamiltonians

The similarity of protein–ligand and host–guest complexes leads to the direct extension of end-point free energy techniques to virtual screening of the latter. Despite the massive application of end-point calculations in modelling and predictions of host–guest binding, it still lacks a large-scale benchmark test with sufficient sizes, sampling length and diverse coverages of chemical spaces to get rid of many disturbing factors and provide an unbiased statistical perspective of practical performance and value of end-point screening. Cucurbiturils as one of the main-stream macrocycles are quite popular in pharmaceutical research and industrial applications as drug reservoirs and carriers. In this work, we gather a large dataset of ∼150 host–guest complexes involving cucurbiturils with varying numbers of repeating units, extensively sample the conformational space in physical end states with both the single- and three-trajectory protocols, and extract the affinity estimates with a variety of MM and QM/GBSA Hamiltonians with implicit solvents. The diversity of chemical compositions, the quality of configurational sampling, and the comprehensiveness of parameter combinations are unprecedently high, enabling us to deduce conclusive pictures of the end-point performance in host–guest binding. Unlike previous reports on improved performance due to the incorporation of the QM treatment, shifting to QM/GBSA treatments deteriorates both the reproduction of absolute affinities and the prediction of affinity ranks in our large-scale end-point benchmark, regardless of the employed sampling protocol (i.e., single- and three-trajectory realization). Overall, in the end-point screening of cucurbituril host–guest complexes, we recommend sticking to the original MM/GBSA Hamiltonians in both sampling and free energy estimation. The best/recommended selection with high accuracy and robustness among all end-point protocols benchmarked in this work is the three-trajectory GAFF + GBOBC-I regime, which achieves top performances for both the reproduction of absolute affinities and ranking different host–guest pairs. Docking estimates with seven main-stream protocols have been observed as a promising tool for host–guest binding, but their ranking powers in the current large host–guest dataset does not surpass end-point tools, validating the value of post-docking end-point screening.

Length-Weight, Length-Length Relationships and Condition Factor of Picarel, Spicara smaris (Linnaeus, 1758) Sampled from Aegean Sea and Black Sea

In this study, length-weight relationship (LWR), length-length relationship (LLR) and condition factor (K) of Spicara smaris (Linnaeus, 1758) collected from Aegean Sea and Black Sea during 2023-2024 fishing season were determined. A total of 116 samples (Aegean Sea N=56, Black Sea N=50) were obtained from commercial fishermen. The mean (±SD) total length and weight of samples varies between 15.47±0.98 cm, 34.82±6.45 g, and 12.35±1.40 cm, 20.01±8.93 g for Aegean and Black Sea, respectively. The slopes (b values) of the total length–weight regressions indicated (-) negative allometric growth to (+) positive allometric growth in localities. In addition, LLRs were calculated by using the linear regression model. LLRs were also highly significant (P

Stress – deformation relations of Scotch Pine (Pinus sylvestris L.) under different conditions

In this study, precise samples of Scots pine wood were subjected to bending strength tests in air dry, moisture above LDN and steamed conditions. In the tests, in addition to resistance values, stress and deformation at the elastic limit, II. zone length and total deformation were investigated. As a result of the experiments, it was observed that the materials lost some resistance after the maximum load was reached in LDN and steamed samples, but they continued to carry the load. This situation has led to the need to create two different resistance classes: maximum bending tensile strength and bending fracture resistance. The maximum stress in bending and fracture resistance in bending was found to be highest in air-dried samples, while the lowest was found in steamed samples. In examining the elastic limit resistance and deformations, the highest values were found in air-dried samples, while the lowest values were found in steamed samples. In determining the II. zone length, it was determined that the II. zone length of steamed samples gave the highest value, while air-dried samples gave the lowest value. In determining the total deformations, it was concluded that while the most deformation occurred in the steamed samples, the least deformation occurred in the air-dried samples.

Electrofracturing of Shale at Elevated Pressure

Electrofracturing deeply buried shale formations could be used to increase reservoir permeability and improve reservoir production without requiring large volumes of freshwater. This paper describes a novel experimental system and initial test results to electrofracture shale under high confining pressures. Core-scale laboratory testing was performed on twelve rock samples recovered from a shale gas reservoir. Each sample was subjected to confining pressures of 20.7 MPa (3000 psi) or 58.6 MPa (8000 psi), representative of overburden pressures at depth. Samples were then subjected to application of high voltage until specimen fracture. The experiments produced deformed samples with multiple fracture types, both parallel and oblique to bedding planes. Electrofracturing increased permeabilities by up to nine orders of magnitude for extended time periods. Rock fracture and throughgoing fractures were demonstrated. Computed tomography images revealed the creation of fractures and tube/tunnel flow channels, which resisted closure under hydrostatic pressures up to 58.6 MPa. The breakdown energy and permeability changes in the sample were independent of applied confining pressure. The cumulative energy input required for fracture depended on applied confining pressure and sample length. The energy required to fracture samples up to 9 cm in length is generally more than 0.5 kJ/cm, but no greater than 1 kJ/cm. Our results show that electrofracture of shales under confining pressure is possible and could be a possible water-free mechanism for reservoir stimulation.

Determination of Optimal Sample Length for Passive Intermodulation Measurements in Microstrip Lines with Non-Contact Connections

Determination of Optimal Sample Length for Passive Intermodulation Measurements in Microstrip Lines with Non-Contact Connections

High-resolution 2D-DoA sequential algorithm of azimuth and elevation estimation in automotive distributed system of coherent MIMO radars

Objectives. One of the main tasks of radiolocation involves the problem of increasing spatial resolution of the targets in the case of limited aperture of the radar antenna array and short length of time samples (snapshots). Algorithms must be developed to provide high angular resolution and low computational complexity. In order to conform with the existing Advanced Driver Assistance Systems requirements, modern cars are equipped with more than one radar having a common signal processing scheme to improve performance during target detection, positioning, and recognition as compared to a single radar. The present study aims to develop a two-dimensional Direction-of-Arrival algorithm with low computation complexity as part of distributed coherent automotive radar system for cases involving short time samples (snapshots).Methods. A virtual antenna array formation algorithm is formulated according to the two-dimensional Capon method. A proposed modification of two-dimensional Capon algorithm is based on sequentially estimating the directions of arrival for the distributed radar system. The Monte Carlo method is used to compare the effectiveness of the considered algorithms.Results. The 2D-DoA sequential algorithm of azimuth and elevation estimation is proposed. The comparative analysis results for the developed algorithm and classical 2D Capon method based on numerical simulation using Monte Carlo method are presented. The proposed scheme of DoA estimation for coherent signal processing of distributed radars is shown to lead to an improvement of the main considered metrics representing the probability of correctly estimating the number of targets, mean square error, and square error compared to a single radar system. The proposed low-computational algorithm shows the gain in complexity compared to full 2D Capon algorithm.Conclusions. The proposed two-stage algorithm for estimating the directions of arrival of signals in azimuth and elevation planes can be applied to the distributed system of coherent radars with several receiving and transmitting antennas representing multiple input multiple output (MIMO) radars. The algorithm is based on sequentially estimating the directions of arrival, implying estimation in the azimuthal plane at the first stage and estimation in the vertical plane at the second stage. The performance of a coherent radar system with limited antenna array configuration of separate radar is close in characteristics to a high-performance 4D-radar with a large antenna array system.