Practical Size Research Articles

Sieve estimation of the accelerated mean model based on panel count data

Panel count data are gathered when subjects are examined at discrete times during a study, and only the number of recurrent events occurring before each examination time is recorded. We consider a semiparametric accelerated mean model for panel count data in which the effect of the covariates is to transform the time scale of the baseline mean function. Semiparametric inference for the model is inherently challenging because the finite-dimensional regression parameters appear in the argument of the (infinite-dimensional) functional parameter, i.e., the baseline mean function, leading to the phenomenon of bundled parameters. We propose sieve pseudolikelihood and likelihood methods to construct the random criterion function for estimating the model parameters. An inexact block coordinate ascent algorithm is used to obtain these estimators. We establish the consistency and rate of convergence of the proposed estimators, as well as the asymptotic normality of the estimators of the regression parameters. Novel consistent estimators of the asymptotic covariances of the estimated regression parameters are derived by leveraging the counting process associated with the examination times. Comprehensive simulation studies demonstrate that the optimization algorithm is much less sensitive to the initial values than the Newton–Raphson method. The proposed estimators perform well for practical sample sizes, and are more efficient than existing methods. An example based on real data shows that due to this efficiency gain, the proposed method is better able to detect the significance of practically meaningful covariates than an existing method.

Exploring AES Encryption Implementation Through Quantum Computing Techniques

A coming great revolution in technology is quantum computing, which opens new attacks on most of the developed cryptographic algorithms, including AES. These emerging quantum capabilities risk weakening cryptographic techniques, which safeguard a vast amount of data across the globe. This research uses Grover's algorithm to explore the vulnerabilities of the Advanced Encryption Standard to quantum attacks. By implementing quantum cryptographic algorithms and Quantum Error Correction on simulators and quantum hardware, the study evaluates the effectiveness of these techniques in mitigating noise and improving the reliability of quantum computations. The study shows that while AES is theoretically at risk due to Grover’s algorithm, which demonstrates a theoretical reduction in AES key search complexity, current hardware limitations and noise levels encountered in today’s quantum computers reduce the immediate threat and limit practical exploitation. The research also examines NTRU encryption, a quantum-resistant alternative, highlighting its robustness in quantum environments. The findings emphasize the need for further development in QEC and quantum-resistant cryptography to secure digital communications against future quantum threats. Future work will focus on advancing QEC techniques and refining quantum algorithms, addressing both hardware and theoretical advancements, including the potential use of high-capacity processors like Jiuzhang 3.0. These improvements will ensure the scalability of quantum-resistant systems to practical key sizes and usage scenarios.

Dynamic responses of thin-walled FRP-concrete-steel tubular wind turbine tower under horizontal impact loading: Experimental study and FE modelling

Thin-walled FRP-concrete-steel tubular towers (TW-FCSTs), composed of an outer FRP tube, an inner hollow steel tube, and an interlayer of concrete, represent a novel type of wind turbine tower with promising application prospects. Given their potential risks to potential vehicle or vessel collisions, this study investigates the dynamic responses of five cantilevered TW-FCSTs using a horizontal impact device. These TW-FCSTs possess significantly large void ratios (i.e., φ=0.73or0.82) and practical large column sizes (i.e., Dc = 300 mm, Hc = 1500 mm). The experimental programme of this paper investigates several key parameters, including FRP thickness, steel thickness, and void ratio of TW-FCSTs, as well as the velocity and numbers of impact loading. Experimental findings demonstrate the following insights: (1) cantilevered TW-FCSTs exhibit an overall flexural failure mode after the horizontal impact loading; (2) the increase in steel thickness or FRP thickness contributes to greater energy dissipation and reduced localized dent deformation; (3) the higher void ratio results in more pronounced localized dent deformation and less overall deformation in specimens; (4) the proportion of energy dissipation caused by localized dent deformation increased with impact velocity, signifying more severe localized dent deformation at higher impact velocities. The utilization of FE models in LS-DYNA effectively simulates the dynamic performance of cantilevered TW-FCSTs, offering reliable predictions. Parametric studies were conducted to analyze influences of impact mass, impact height, concrete strength, and steel yield strength.

Hybrid quantum-classical computation for automatic guided vehicles scheduling

Motivated by recent efforts to develop quantum computing for practical, industrial-scale challenges, we demonstrate the effectiveness of state-of-the-art hybrid (not necessarily quantum) solvers in addressing the business-centric optimization problem of scheduling Automatic Guided Vehicles (AGVs). Some solvers can already leverage noisy intermediate-scale quantum (NISQ) devices. In our study, we utilize D-Wave hybrid solvers that implement classical heuristics with potential assistance from a quantum processing unit. This hybrid methodology performs comparably to existing classical solvers. However, due to the proprietary nature of the software, the precise contribution of quantum computation remains unclear. Our analysis focuses on a practical, business-oriented scenario: scheduling AGVs within a factory constrained by limited space, simulating a realistic production setting. Our approach maps a realistic AGVs problem onto one reminiscent of railway scheduling and demonstrates that the AGVs problem is better suited to quantum computing than its railway counterpart, the latter being denser in terms of the average number of constraints per variable. The main idea here is to highlight the potential usefulness of a hybrid approach for handling AGVs scheduling problems of practical sizes. We show that a scenario involving up to 21 AGVs, significant due to possible deadlocks, can be efficiently addressed by a hybrid solver in seconds.

Planning Split-Apheresis Designs for Demonstrating Comparability of Cellular and Gene Therapy Products.

A recent FDA draft guidance discusses statistical considerations for demonstrating comparability of cell and gene therapy products and processes. One experimental study described in the guidance is the split-apheresis design. The FDA draft guidance recommends a paired data analysis for such a design. This paper demonstrates that the paired analysis is under powered for some quality attributes for practical sample sizes of three to five donors unless a significant portion of variability is attributed to donor. Addition of historic lots from the pre-change process can increase the power for these attributes. This paper provides appropriate statistical methods for including this information.

Head-to-head comparison of 18F-sodium fluoride coronary PET imaging between a silicon photomultiplier with digital photon counting and conventional scanners

BackgroundWe compared silicone photomultipliers with digital photon counting (SiPM) and photomultiplier tubes (PMT) PET in imaging coronary plaque activity with 18F-sodium fluoride (18F-NaF) and evaluated comprehensively SiPM PET reconstruction settings. MethodsIn 25 cardiovascular disease patients (mean age 67±12 years), we conducted 18F-NaF PET on a SiPM (Biograph Vision) and conventional PET (Discovery 710) on the same day as part of a prospective clinical trial (NCT03689946). Following administration of 250 MBq of 18F-NaF, patients underwent a contrast-enhanced CT angiography and a 30-min PET acquisition in list mode on each PET consecutively. Image noise was defined as mean standard deviation of blood pool activity within the left atria. Target-to-background ratio (TBR) and signal-to-noise ratio (SNR) were measured within the whole-vessel tubular 3-dimensional volumes of interest on the cardiac motion and attenuation corrected 18F-NaF PET images using dedicated software. ResultsThere were significant differences in image noise and background activity between the two PETs (Image noise (%), PMT: 7.6±3.7 vs. SiPM: 4.0±2.3, p<0.001; background activity, PMT: 1.4±0.4 vs. SiPM: 1.0±0.3, p<0.001). Similarly, the SNR and TBR were significantly higher in vessels scanned with the SiPM PET (SNR, PMT: 16.3±11.5 vs. SiPM: 32.7±29.8, p<0.001; TBR, PMT: 0.8±0.4 vs. SiPM: 1.1±0.6, p<0.001). SiPM PET image reconstruction with a 256 matrix, 1.4 mm pixel, and 2 mm Gaussian filter provided best tradeoff in terms of maximal SNR, TBR and clinically practical file size. ConclusionsIn 18F-NaF coronary PET imaging, the SiPM PET showed superior image contrast and less image noise compared to PMT PET.

Titanium Complex with New Schiff Base 4-(N, N-dimethylaminobenzylidene)-1- phenylsemicarbazide: Synthesis, Thermal, XRD, and Antibacterial properties

4-(N, N-dimethylaminobenzylidene) 1-phenylsemicarbazide Schiff base (SB) was synthesized from 1-phenylsemicarbazide and 4-(N,N-dimethylaminobenzaldehyde). Numerous analytical approaches, such as ele-mental analysis, 1HNMR, 13CNMR, electronic spectra, and FT-IR spectroscopy were utilized to analyze the newly synthesized Schiff base. The Ti (IV) Schiff base complex was produced, and its electrolytic nature, stability, and octahedral structural properties were determined by elemental, IR, UV-Vis spectral, conductivity, and thermal studies (TGA-DTA). From XRD results, the practical size of Schiff base and its complex were in the nano range with crystallinity structure. To evaluate the antibacterial activity, the free ligand and its complex were assessed in vitro against Pseudomonas aeruginosa, Escherichia coli, and Staphylococcus aureus. These results show that the metal complex has stronger antibacterial action than the Schiff base ligand.

Numerical investigation of the impact of various parameters on blowing accuracy in the XRT intelligent ore sorting machine blowing process

XRT separation equipment is attracting much attention as the mining industry increasingly uses pre-sorting technology. Its sorting accuracy is affected by differences in ore shape and particle size during operation. This paper, in which numerical simulations are conducted to investigate the resistance of ores under various situations, including varying blowing distances, cross-sections, and practical sizes, Additionally, this paper conducts validation tests. The test results indicate that within the 0.1-0.25 m section from the nozzle exit, there is a rapid decrease in velocity, accompanied by a significant change in ore resistance. Beyond the 0.25 m mark, the velocity reduction slows down, while the ore resistance becomes smaller. There exists a notable disparity in the resistance of ores with varying cross-sectional geometries. The size of the jet velocity surface caused by blowing distance significantly influences the resistance of ore with varying particle sizes. Furthermore, the resistance of the ore remains constant subsequent to the impact surface of the ore surpassing the surface of the jet velocity. Consequently, appropriately modifying the blowing distance, inlet pressure, and jet speed in accordance with the cross-sectional area and particle size of the majority of the ores stream can enhance the precision of the sorting process.

Synthesis of Carbon Dots via Microwave-Assisted Process: Specific Sensing of Fe(III) and Antibacterial Activity.

Carbon dots synthesized from a renewable and sustainable source of biomass have greater attention in the nanomaterial research field. In the present study, we adopted a facile and green synthesis of carbon dots from bio waste of pumpkin seeds using a one-pot microwave-assisted carbonization method. The synthesized carbon dots exhibit excellent photoluminescence properties with a bright blue emission peak at 399nm and fluorescence quantum yield was about 9.5%. The optical properties and structure of carbon dots were examined using various spectroscopy techniques and the synthesized carbon practical size was about 4.37nm and possessed good solubility in water. Carbon dots were used for the detection of Ferric ions in the water bodies and the interaction between Fe3+ ions and carbon dots was evaluated by fluorescence spectroscopy techniques. This method is a simple and selective detection of Fe3+ in the aqueous medium. Interestingly carbon dots also show good antibacterial activity at a very low concentration (1mg/L) for effective control of E. coli 93% and Pseudomonas aeruginosa (81%), within 12h.

Absolute risk from double nested case-control designs: cause-specific proportional hazards models with and without augmented estimating equations.

We estimate relative hazards and absolute risks (or cumulative incidence or crude risk) under cause-specific proportional hazards models for competing risks from double nested case-control (DNCC) data. In the DNCC design, controls are time-matched not only to cases from the cause of primary interest, but also to cases from competing risks (the phase-two sample). Complete covariate data are available in the phase-two sample, but other cohort members only have information on survival outcomes and some covariates. Design-weighted estimators use inverse sampling probabilities computed from Samuelsen-type calculations for DNCC. To take advantage of additional information available on all cohort members, we augment the estimating equationswith a term that is unbiased for zero but improves the efficiency of estimates from the cause-specific proportional hazards model. We establish the asymptotic properties of the proposed estimators, including the estimator of absolute risk, and derive consistent variance estimators. We show that augmented design-weighted estimators are more efficient than design-weighted estimators. Through simulations, we show that the proposed asymptotic methods yield nominal operating characteristics in practical sample sizes. We illustrate the methods using prostate cancer mortality data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Study of the National Cancer Institute.

Is order-2 proportionality good enough for approximating the most likely path flow in user equilibrium traffic assignment?

The proportionality condition is a standard approach to dealing with the non-uniqueness issue in the user equilibrium (UE) traffic assignment problems (TAP). Although the proportionality condition can reduce the degree of arbitrariness, it remains unclear how much arbitrariness remains and whether it can meaningfully affect model outcomes and relevant decisions that depend on them. The answers to these questions are impeded by the lack of an efficient algorithm that can find the exact maximum entropy UE path flow solution for networks of practical size. In this paper, we fill this gap by developing a high-performance augmented Lagrangian algorithm that effectively exploits the special problem structure. Our numerical results reveal that there are a considerable number of links with non-negligible arbitrariness in the solution generated by the proportionality condition, and that this problem becomes worse if the level of congestion increases in the network. Since about a decade ago, many practitioners have relied on state-of-the-art traffic assignment tools based on the proportionality condition to perform select link analysis, among other applications. The results reported herein are a reminder that their toolbox may need reevaluation and perhaps an upgrade.

Evaluation of output factors of different radiotherapy planning systems using Exradin W2 plastic scintillator detector.

This study aims to evaluate the output factors (OPF) of different radiation therapy planning systems (TPSs) using a plastic scintillator detector (PSD). The validation results for determining a practical field size for clinical use were verified. The implemented validation system was an Exradin W2 PSD. The focus was to validate the OPFs of the small irradiation fields of two modeled radiation TPSs using RayStation version 10.0.1 and Monaco version 5.51.10. The linear accelerator used for irradiation was a TrueBeam with three energies: 4, 6, and 10MV. RayStation calculations showed that when the irradiation field size was reduced from 10 × 10 to 0.5 × 0.5cm2, the results were within 2.0% of the measured values for all energies. Similarly, the values calculated using Monaco were within approximately 2.0% of the measured values for irradiation field sizes between 10 × 10 and 1.5 × 1.5cm2 for all beam energies of interest. Thus, PSDs are effective validation tools for OPF calculations in TPS. A TPS modeled with the same source data has different minimum irradiation field sizes that can be calculated. These findings could aid in verification of equipment accuracy for treatment planning requiring highly accurate dose calculations and for third-party evaluation of OPF calculations for TPS.

Optimal autonomous truck platooning with detours, nonlinear costs, and a platoon size constraint

Autonomous trucks offer a promising avenue for enhancing the efficiency and reducing the environmental impact of road freight transportation. This paper examines a transitional phase towards a fully unmanned truck fleet, focusing on a platooning approach with a lead driver. We develop a novel optimization model for autonomous truck platooning that simultaneously considers platoon formation, scheduling, and routing to minimize costs related to labor and fuel. The model incorporates the possibility of detours, nonlinear fuel savings due to air-drag reduction, and the practical platoon size limit. We present an enhanced column generation method, termed the platoon-generation-and-updating approach, which demonstrates high effectiveness in reducing computational time and complexity. Our numerical analysis, based on the Hong Kong highway network, demonstrates the substantial cost advantages of autonomous truck platooning. It also investigates how platooning efficiency is influenced by various operating factors, including truck fleet size, platoon size restrictions, labor-to-fuel cost ratio, and the strictness of delivery time windows, with practical implications interwoven into the discussion.

Early Metabolic Endpoints Identify Persistent Treatment Efficacy in Recent-Onset Type 1 Diabetes Immunotherapy Trials.

Mixed-meal tolerance test-stimulated area under the curve (AUC) C-peptide at 12-24 months represents the primary end point for nearly all intervention trials seeking to preserve β-cell function in recent-onset type 1 diabetes. We hypothesized that participant benefit might be detected earlier and predict outcomes at 12 months posttherapy. Such findings would support shorter trials to establish initial efficacy. We examined data from six Type 1 Diabetes TrialNet immunotherapy randomized controlled trials in a post hoc analysis and included additional stimulated metabolic indices beyond C-peptide AUC. We partitioned the analysis into successful and unsuccessful trials and analyzed the data both in the aggregate as well as individually for each trial. Among trials meeting their primary end point, we identified a treatment effect at 3 and 6 months when using C-peptide AUC (P = 0.030 and P < 0.001, respectively) as a dynamic measure (i.e., change from baseline). Importantly, no such difference was seen in the unsuccessful trials. The use of C-peptide AUC as a 6-month dynamic measure not only detected treatment efficacy but also suggested long-term C-peptide preservation (R2 for 12-month C-peptide AUC adjusted for age and baseline value was 0.80, P < 0.001), and this finding supported the concept of smaller trial sizes down to 54 participants. Early dynamic measures can identify a treatment effect among successful immune therapies in type 1 diabetes trials with good long-term prediction and practical sample size over a 6-month period. While external validation of these findings is required, strong rationale and data exist in support of shortening early-phase clinical trials.

Imaging in double-casing wells with convolutional neural network based on inception module

The evaluation of well integrity in double-casing wells is critical for ensuring well stability, preventing oil and gas leaks, avoiding pollution, and ensuring safety throughout well development and production. However, the current predominant method of assessing cementing quality primarily focuses on single-casing wells, with limited work conducted on double-casing wells. This study introduces a novel approach for evaluating the cementing quality using the Inception module of convolutional neural networks. First, the finite-difference method is employed to generate borehole sonic data corresponding to a variety of model configurations, which are used to train a neural network that learns spatial features from the borehole sonic data to reconstruct the slowness model. By adjusting the network architecture and parameters, it is discovered that a neural network with two blocks and 4096 nodes in the fully connected layer demonstrated the best imaging results and exhibited strong anti-noise capabilities. The proposed method is validated using practical wellbore size models, demonstrating excellent results and offering a more effective means of evaluating wellbore integrity in double-casing wells. In addition, dipole acoustic logging data are used to conduct slowness model imaging of the compressional (P-) wave and shear (S-) wave in double-casing wells to verify the feasibility of cementing quality evaluation. The developed method contributes to more accurate evaluations of wellbore integrity for the oil and gas industry, leading to improved safety and environmental outcomes.

Single-shot readout of a superconducting qubit using a thermal detector

Measuring the state of a qubit is a key fundamental operation of a quantum computer. High-fidelity single-shot readout of superconducting qubits can be achieved using parametric amplifiers at millikelvin temperatures. However, scaling parametric amplifiers beyond hundreds of qubits is challenging due to practical size and power limitations. Nanobolometers can, in contrast, offer scalability, sensitivity and speed suitable for qubit readout. Here we show that a bolometer can provide single-shot qubit readout with a readout duration of 13.9 μs and a single-shot fidelity of 0.618. The fidelity is mainly limited by the energy relaxation time of the qubit (28 μs), and a fidelity of 0.927 is found after removing errors arising from this relaxation. In the future, higher-fidelity single-shot readout may be achieved through improvements in chip design and experimental setup, as well as a change in the bolometer absorber material to reduce the readout time to the level of hundreds of nanoseconds and below.

Spectroscopic and biological studies of mixed ligand complexes of transition metal (II) ions with chloroquine and ketoprofen

To create fresh transition metal complexes of chloroquine and ketoprofen, we combined Ni(II), Co(II), Cu(II), and Zn(II). Metal analysis, IR, UV-vis, and X-ray diffraction (XRD) spectrum analyzes of the complexes were utilized to characterize them. The octahedral geometry was proposed for all compounds on the basis of the UV-vis and magnetic susceptibility data. The practical size of the ligands and complexes with crystallinity structure was in the nano range according to the XRD data. The antibacterial and antifungal activities of the ligands and their metal complexes have been examined.

Enhanced dynamic fine‐grained popularity‐based caching algorithm for ICN‐based edge computing networks

AbstractIn this letter, we propose an Enhanced Dynamic Fine‐Grained Popularity‐based Caching (ED‐FGPC) algorithm to efficiently cache static contents in ICN‐based edge computing networks. The content popularity changes with time. Thus, the ED‐FGPC algorithm considers the number of incoming interests, the practical file size, and the available cache size to adjust the content popularity threshold. This allows dynamic adjustment of the content popularity threshold. Additionally, ED‐FGPC incorporates a single bit called cached bit (CB) in the header field of the content. This eliminates caching redundancy in the on‐path routers. The cache eviction policy jointly considers the content popularity and the average content access timestamp for content replacement. Based on the content access pattern, this allows finer adjustment of the content eviction policy. We use analytical and mathematical modeling to derive the effectiveness and efficiency of our contribution. Results present a better hit ratio due to dynamic adjustment of the content popularity threshold and the elimination of caching redundancy from the on‐path routers.

Designing high-speed GEO-to-Moon optical wireless communication links

Moon exploration and colonization will strongly rely upon high-speed optical wireless communications over a huge distance (around 400,000 km). Here, we introduce a holistic model, including the propagation issues as well as the realistic communication limitations and the expected practical limitations. We focus on the communication issues in a link connecting a GEO satellite to a fixed Moon optical station: here, we consider the challenging 10 Gbit/s transmission rate, and we assume an optical pre-amplified receiver, which is today the only option for high speed; we then select three different modulation formats, with corresponding implementations and increasing complexity and performance. Under these assumptions, we estimate the common operating conditions at the forward error correction threshold and point out the role of the transmitter and receiver telescopes: for practical size (e.g., 1 m), relevant limitations arise, which we combine with the typical photons-per-bit sensitivity values in an optical link. We find that all considered modulation formats can be used at 10 Gbit/s, although with different margins and hardware requirements, particularly considering the size of the optical antennas. We then extend the analysis to higher rates, up to 40 Gbit/s. This work can open the way to the realization of optical wireless communication systems to/from the future Moon Village.

Pretest and posttest reliability to measure the impact of online team-based learning workshops during the Covid-19 pandemic as a continuing faculty development activity among health professional educators

Medical education has been facing unprecedented challenges due to the COVID-19 pandemic leaving aftermath, which needs continuing reparative work. Imperative to exploring solutions faced by Covid pandemic challenges, various immediate steps were taken by medical schools globally including the faculty development activities transformed into online strategies. Workshops are the most common methods of the FDA to enhance knowledge and skills in specific areas of teaching and learning and assessment. A retrospective analysis of three of the TBL online FDA workshops is presented to determine its immediate impact on teaching and learning as well as an assessment model using pretest and posttest designs of a 3-point Likert scale of participants attending a half-day online workshop during the Covid19 pandemic for faculty development in a teaching hospital in Malaysia. Data was collected and analysed using online links created in Microsoft Google form at the beginning and towards the end of each workshop on a 3-point Likert scale of agreed, disagreed and not sure. A 15 items questionnaire was administered with additional information of participants’ trends in studying the reading materials sent out a week prior to the actual workshop. An interventional strategy between the two tests were four plenaries and a break-out session with hands-on group work followed by presentations. A collated quantitative data was gathered from 82 participants attending the online TBL workshops. Data were analysed using the statistical test of paired t-test, one-way ANOVA and ANCOVA with effect size in SPSS version 24. The percentage correct pretest and posttest score difference was significant at p = .013. The mean difference between pretest and posttest scores was significant at t = 31.345, p &lt; 0.01. A significant difference in mean scores between groups was found, F (2,79) = 4.923, P = .010 using one-way ANOVA. Post-hoc analysis revealed significantly high posttest mean scores compared to partially read and not read groups at p = .033 and .014, respectively. However, the difference between partially read and not read was insignificant. A difference in mean posttest scores among the three groups using one-way ANCOVA on removing the effect of pretest was found significant at F (2, 80) = 6.211, p = 0.003. The effect size using Cohen’s d and Partial Eta Squared have a large practical effect of 2.072 and a moderate effect of 11.1% and 13.70% shown in paired t-test, ANOVA and ANCOVA respectively. A significant difference in the mean pretest and posttest scores was found between the groups. A post-test score, controlling on pretest score, was also significant, with a large Cohen’s d and moderate practical effect size suggesting an effectively delivered TBL online workshop. Keywords: Faculty development, online workshops, pretest, posttest design, quantitative evaluation, team-based learning