Relevant Parameters Research Articles

Computational Modeling of Bone Fracture Healing Under Different Initial Conditions and Mechanical Load.

Computational model of bone healing can replace animal experiments to study the parameters affecting the bone healing process, thus reducing the damage to experimental animals and saving a lot of time. We propose a computational model for continuous simulation of four phases of bone healing to study the effects of mechanical environmental and biological factors, including initial conditions at the fracture site, mechanical stimulus loading, and vascular growth rate. A finite element model of mechanobiological fracture healing containing several pre-determined variables was developed for bone healing after fracture in sheep, which included many relevant parameters and biological effects during fracture healing, such as the effects of mechanical environment, blood supply level in the local fracture area, cell migration and diffusion, and resorption effects of fracture healing. The effects of several parameters on indices such as Young's modulus of the callus during bone healing were obtained by simulation. The initial geometry of the healing tissue and mechanical loading had the greatest effect on fracture healing, and different preset values were likely to cause delayed or non-healing fractures. Changed initial tissue properties of the healing tissue showed a nonlinear effect on fracture healing rather than a linear delay or advancement. Parameters related to angiogenesis had a greater effect on fracture healing compared to those related to cell migration. This paper quantified the effect of fracture healing pre-determined variables on fracture healing to better understand the application of mechanobiology in fracture healing simulation models and optimization of treatment strategies. The importance of initial conditions and loads on fracture healing has been shown to help physicians treat bone nonunion or delayed bone healing after a fracture.

Radiographic assessment of the peri-implant site.

While peri-implant mucositis relies solely on clinical parameters, radiological assessment becomes indispensable for diagnosing peri-implantitis. Intraoral radiography, with its simplicity of application, low radiation exposure, and adequate representation of peri-implant structures, stands out as the standard of care for both immediate and follow-up assessments. Standardization by custom-made radiologic splints allows for excellent comparability with previous images and allows for the determination of even small changes in contour and density of the peri-implant bone. Furthermore, other radiographic modalities like panoramic radiography and cone beam computed tomography (CBCT) may provide useful features for specific patients and clinical cases while also showing innate limitations. Beyond the assessment of the marginal peri-implant bone level as the crucial parameter of clinical relevance, radiologic assessment may reveal various other findings related to the prosthetic restoration itself, the precision of its fit to the implant, and the peri-implant soft and hard tissues. Since such findings can be crucial for the assessment of peri-implant health and the implants' prognosis, a systematic diagnostic evaluation pathway for a thorough assessment is recommended to extract all relevant information from radiologic imaging. This article also provides an overview of the clinical and chronological indications for different imaging modalities in peri-implant issues.

Research-based Analytical Procedures to Evaluate Diabetic Biomarkers and Related Parameters: In Vitro and In Vivo Methods.

The degenerative tendency of diabetes leads to micro- and macrovascular complications due to abnormal levels of biochemicals, particularly in patients with poor diabetic control. Diabetes is supposed to be treated by reducing blood glucose levels, scavenging free radicals, and maintaining other relevant parameters close to normal ranges. In preclinical studies, numerous in vivo trials on animals as well as in vitro tests are used to assess the antidiabetic and antioxidant effects of the test substances. Since a substance that performs poorly in vitro won't perform better in vivo, the outcomes of in vitro studies can be utilized as a direct indicator of in vivo activities. The objective of the present study is to provide research scholars with a comprehensive overview of laboratory methods and procedures for a few selected diabetic biomarkers and related parameters. The search was conducted on scientific database portals such as ScienceDirect, PubMed, Google Scholar, BASE, DOAJ, etc. Conclusion: The development of new biomarkers is greatly facilitated by modern technology such as cell culture research, lipidomics study, microRNA biomarkers, machine learning techniques, and improved electron microscopies. These biomarkers do, however, have some usage restrictions. There is a critical need to find more accurate and sensitive biomarkers. With a few modifications, these biomarkers can be used with or even replace conventional markers of diabetes.

Risk factors determining adherence to tyrosine kinase inhibitors in chronic myeloid leukaemia.

Tyrosine kinase inhibitors (TKIs) have successfully changed the natural course of chronic myeloid leukaemia (CML). Although they are highly effective drugs, their clinical benefit is conditioned by adherence. This study aims to analyse the adherence of CML patients treated with TKIs and to identify the main factors influencing their adherence to TKIs treatment. An 8-month prospective, observational, multicentre study which included patients diagnosed with CML on treatment with TKIs attending the outpatient departments (OPD) of the Pharmacy Services of the participating hospitals. Adherence was assessed using two methods: the Simplified Medication Adherence Questionnaire (SMAQ) and the register of treatment dispensations from the OPDs. To analyse the predictors of adherence, a questionnaire was developed to report demographic and socio-economic information on the patients. A total of 130 patients enrolled in this study. Adherence rate was 56.9% (n = 74) among individuals, not conditioned by the type of drug used: imatinib (54.8%), nilotinib (63.6%) or dasatinib (54.3%) (p = 0.67). The patient educational level (p = 0.047) and employment status (p = 0.028) were predictors of non-adherence to treatment. Adherence is one of the most relevant parameters affecting the effectiveness of highly effective chronic treatments. Approximately half of our patients showed inadequate adherence to treatment with TKIs, with employment status and the individual's level of education emerging as the determining factors.

Development of ergo-refined operator's workplace and biophysically actual cost-benefit analysis of riding type self-propelled machines with special reference for female operators.

Female agricultural workers contribute to 37% of the total agricultural workforce in India, however, most self-propelled machinery is designed for male agricultural workers. The primary objective was to determine the impact of the ergo-refined operator's workplace on various aspects of operator performance and comfort, including actuating force, posture, and physiological parameters. Experiments were carried out in real field conditions using a full factorial randomized design. Twelve female operators participated in the study, and measurements were taken for control lever actuating force, operator posture, heart rate, and other relevant parameters. The ergo-refined operator's workplace intervention resulted in significant reductions in actuating force for various control levers, angles of joints, working heart rate (WHR), oxygen consumption rate (OCR), muscle load, and whole-body vibration (WBV) acceleration. These reductions were observed under different operating conditions. The findings suggest that the ergo-refined operator's workplace is effective in enhancing operator comfort and reducing physical strain during the operation of riding type self-propelled machines. It contributes to improved safety, comfort, and operational efficiency for operators working in field conditions. ANOVA and MANOVA analyses confirmed the positive impact of operating conditions and engine speed on the measured parameters when using the ergo-refined operator's workplace.

Near-infrared Spectrum Characteristics of Micro-Nano Material Based Diffraction Optical Devices

Diffractive optics devices are optical devices in which the amplitude or phase of the incident light is spatially modulated periodically by a micro-nanomaterial based structure. The study of diffractive optics devices in the field of micro and nano can change the spectroscopic behavior of micro and nano diffractive optics devices by varying the microstructure of the structure and the optical wave properties, which can effectively and reasonably modulate the optical wave signal. To study the effect of different parameter structures on the performance of micro-nano diffraction optical devices, in this paper, two three-dimensional array structures of diffractive optical devices are proposed, which are a vertex-intersecting regular tetrahedron structure and a base-intersecting regular frustum structure. Using the Finite-Difference Time-Domain method, the spectroscopic images of the diffractive optics of the constructed micro-nano diffractive devices are studied in the near-infrared band by varying the height of the constructed structures, the type of structures, the wavelength of the incident light waves, and the polarization direction of the light waves in different 3D height coordinates. The effects of different parameter changes on the performance of the micro-nano diffractive optics devices were analyzed by image comparison. The results show that the best diffraction effect is achieved at a structure height of 0.9 μm for both models with different structure types. The study of both structures at this structure height reveals that the location of diffraction occurrence and the intensity of diffraction can be tuned by varying the structure and the relevant parameters such as the polarization of the light wave. This paper has some theoretical applications for the study of high-performance diffractive optics.

Potential functions of construction worker–machine interaction safety assessment

The interaction of several workers with intelligent construction machinery can lead to serious collisions. Typically, the safety distance is used as an indicator of the safety of worker–machine interactions (WMI). However, the degree of risk does not increase linearly with decreasing worker–machine distances. To further reveal the essence of WMI safety, this study proposes a new method for assessing the safety state of WMIs, namely, the construction safety potential field. It is used to describe the factors and patterns associated with the spatial overlap and decay of hazardous energy in WMI operations. The proposed method was tested in an earthworks construction WMI operation and the results were valid. A preliminary discussion of the relevant parameters constituting the construction safety potential field model is presented. The contributions of the research is proposing a generic energy-based model, which provides a novel idea for the interpretation of safety issues in construction WMI operations and opens up a new foundation for the development of active safety control.

Near-real-time Mueller polarimetric image processing for neurosurgical intervention.

Wide-field imaging Mueller polarimetry is a revolutionary, label-free, and non-invasive modality for computer-aided intervention; in neurosurgery, it aims to provide visual feedback of white matter fibre bundle orientation from derived parameters. Conventionally, robust polarimetric parameters are estimated after averaging multiple measurements of intensity for each pair of probing and detected polarised light. Long multi-shot averaging, however, is not compatible with real-time in vivo imaging, and the current performance of polarimetric data processing hinders the translation to clinical practice. A learning-based denoising framework is tailored for fast, single-shot, noisy acquisitions of polarimetric intensities. Also, performance-optimised image processing tools are devised for the derivation of clinically relevant parameters. The combination recovers accurate polarimetric parameters from fast acquisitions with near-real-time performance, under the assumption of pseudo-Gaussian polarimetric acquisition noise. The denoising framework is trained, validated, and tested on experimental data comprising tumour-free and diseased human brain samples in different conditions. Accuracy and image quality indices showed significant ( ) improvements on testing data for a fast single-pass denoising versus the state-of-the-art and high polarimetric image quality standards. The computational time is reported for the end-to-end processing. The end-to-end image processing achieved real-time performance for a localised field of view ( ). The denoised polarimetric intensities produced visibly clear directional patterns of neuronal fibre tracts in line with reference polarimetric image quality standards; directional disruption was kept in case of neoplastic lesions. The presented advances pave the way towards feasible oncological neurosurgical translations of novel, label-free, interventional feedback.

Interdependencies in Electrode Manufacturing: A Comprehensive Study Based on Design Augmentation and Explainable Machine Learning

AbstractElectrode manufacturing, as the core of battery cell production, is a complex process chain with a large number of interrelated parameters. An in‐depth understanding of the processes, their relevant parameters, and the resulting effects on intermediate and final product properties can accelerate the transition toward quality‐oriented, efficient battery cell production. Given the complexity of the process chain, data‐driven models have emerged as promising solutions for analyzing the existing interdependencies. The accuracy and effectiveness of these models significantly depend on the quality and comprehensiveness of the underlying data. With a low‐quality dataset, there is an increased risk of drawing inaccurate conclusions or generating misleading results. This article aimed to demonstrate a use case for the evaluation and enhancement of historical datasets to provide a statistically robust foundation for the development of machine learning models. The study was based on pilot‐scale anode manufacturing and covered variations in the coating, drying, and calendering processes. The key intermediate product and process parameters were used to predict two primary target variables: adhesion strength and discharge capacity at different C‐rates. To gain a better understanding of the analyzed interdependencies, explainable machine learning methods were adopted.

Protocol parameter extraction and centralization framework for comprehensive and in-depth CT protocol review and management.

CT protocol management is an arduous task that requires expertise from a variety of radiology professionals, including technologists, radiologists, radiology IT professionals, and medical physicists. Each CT vendor has unique, proprietary protocol file structures, some of which may vary by scanner model, making it difficult to develop a universal framework for distilling technical parameters to a human-readable file format. An ideal solution for CT protocol management is to minimize the work required for parameter extraction by introducing a data format into the workflow that is universal to all CT scanners. In this paper, we report a framework for CT protocol management that converts raw protocol files to an intermediary format before outputting them in a human-readable format for a variety of practical clinical applications, including routine protocol review, protocol version tracking, and cross-protocol comparisons. The framework was developed in Python 3. Technical parameters of interest were determined via collaborative effort between medical physicists and lead technologists. Protocol files were extracted and analyzed from a variety of scanners across our hospital-wide CT fleet, including various systems from Siemens and GE. Protocols were subcategorized based on relevant technical parameters into regular, dual-energy, and cardiac CT protocols. Backend code for technical parameter extraction from raw protocol files to a JavaScript Object Notation (JSON) format was performed on a per-system basis. Conversion from JSON to a readable output format (MS Excel) was performed identically for all scanners using the universal framework developed and presented in this work. Example results for Siemens and GE scanners are shown, including side-by-side comparisons for protocols with similar clinical indications. In conclusion, our CT protocol management framework may be deployed on any CT system to improve clinical efficiency in protocol review and upkeep.

Simulation of Small-Scale Solar Power Generation System in The Central Java Region: A Case Study of the Cilacap Area

The limitations of conventional non-renewable energy resources raise concerns about sustainability and energy supply security in the future. One of the worrying factors is the carbon dioxide emissions that can affect living organisms' health. Renewable energy sources, such as solar, wind, and hydropower, emerge as solutions capable of minimizing environmental impacts and reducing dependence on limited resources. Therefore, this research will simulate and design a small-scale renewable energy power generation system, particularly solar energy, in the Cilacap region, Central Java. The main components involved in this research include PV arrays, IGBT diodes, and universal bridges, supported by supporting elements such as displays, scopes, resistors, capacitors, inductors, and bus selectors. The technical data used as input are specific to the area. The simulation results show that the direct power generated by one modelled PV array is 221.7 W per hour. This research contributes to optimising small-scale solar power generation systems in the designated area, considering relevant components and parameters to enhance efficiency and sustainability.

Replica analysis of overfitting in regression models for time to event data: the impact of censoring

We use statistical mechanics techniques, viz. the replica method, to model the effect of censoring on overfitting in Cox’s proportional hazards model, the dominant regression method for time-to-event data. In the overfitting regime, Maximum Likelihood (ML) parameter estimators are known to be biased already for small values of the ratio of the number of covariates over the number of samples. The inclusion of censoring was avoided in previous overfitting analyses for mathematical convenience, but is vital to make any theory applicable to real-world medical data, where censoring is ubiquitous. Upon constructing efficient algorithms for solving the new (and more complex) Replica Symmetric (RS) equations and comparing the solutions with numerical simulation data, we find excellent agreement, even for large censoring rates. We then address the practical problem of using the theory to correct the biased ML estimators without knowledge of the data-generating distribution. This is achieved via a novel numerical algorithm that self-consistently approximates all relevant parameters of the data generating distribution while simultaneously solving the RS equations. We investigate numerically the statistics of the corrected estimators, and show that the proposed new algorithm indeed succeeds in removing the bias of the ML estimators, for both the association parameters and for the cumulative hazard.

Mechanical impairment characteristics and a novel constitutive model for rocks subjected to uniaxial loading process

The study of constitutive relationship and damage degradation is crucial in solving the stability challenges faced in the rock engineering. In this work, the stress-strain relationships of different type of rocks subjected to uniaxial loading processes are investigated in details. Experimental results demonstrate measurements, such as uniaxial compressive strength (UCS), tangent deformation modulus, peak strain, and Poisson’s ratio ([Formula: see text]). A novel piecewise constitutive model is proposed that utilizes both a constitutive model during compaction and a conventional damage model using the strain equivalence assumption and logistic growth theory to represent the characteristics of stress-deformation curves during both compaction and post-compaction stages. The performance of the proposed constitutive models in capturing deformation characteristics of damaged rocks is demonstrated to be more outstanding in comparison to existing models. In all experimental cases discussed in this study, the proposed model outperforms existing reference models in terms of the coefficients of determination ([Formula: see text]), with the former having coefficients of determination greater than 0.95. Furthermore, physical meanings of relevant model parameters are found to be closely associated with properties of experimental stress-strain curves.

Hybrid Mode: Routinization of the Transition Mode as the Third Common Mode for Compound VTOL Drones

Fixed-wing Vertical Takeoff and Landing (VTOL) drones have been widely researched and applied because they combine the advantages of both rotorcraft and fixed-wing drones. However, the research on the transition mode of this type of drone has mainly focused on completing the process quickly and stably, and the application potential of this mode has not been given much attention. The objective of this paper is to routinize the transition mode of compound VTOL drones, i.e., this mode works continuously for a longer period of time as a third commonly used mode besides multi-rotor and fixed-wing modes, which is referred to as the hybrid mode. For this purpose, we perform detailed dynamics modeling of the drone in this mode and use saturated PID controllers to control the altitude, velocity, and attitude of the drone. In addition, for more stable altitude control in hybrid mode, we identify the relevant parameters for the lift of the fixed-wings and the thrust of the actuators. Simulation and experimental results show that the designed control method can effectively control the compound VTOL drone in hybrid mode. Moreover, it is proven that flight in hybrid mode can reduce the flight energy consumption to some extent.

Chromatin Immunoprecipitation (ChIP) Using Drosophila Antennal and Brain Samples.

Chromatin immunoprecipitation (ChIP) is a common approach for studying the binding pattern of proteins on DNA sequences or the landscape of histones with different marks throughout the genome. ChIP is used on various organisms, including Drosophila This protocol provides a detailed overview of the immunoprecipitation portion of a ChIP procedure from samples of Drosophila nervous systems, specifically antennae and brains, that have already been fixed and sheared. These methods can be applied to other tissues of interest after optimizing for sample size and other relevant parameters.

Impact of Depth on Underground Hydrogen Storage Operations in Deep Aquifers

Underground hydrogen storage in geological structures is considered appropriate for storing large amounts of hydrogen. Using the geological Konary structure in the deep saline aquifers, an analysis of the influence of depth on hydrogen storage was carried out. Hydrogen injection and withdrawal modeling was performed using TOUGH2 software, assuming different structure depths. Changes in the relevant parameters for the operation of an underground hydrogen storage facility, including the amount of H2 injected in the initial filling period, cushion gas, working gas, and average amount of extracted water, are presented. The results showed that increasing the depth to approximately 1500 m positively affects hydrogen storage (flow rate of injected hydrogen, total capacity, and working gas). Below this depth, the trend was reversed. The cushion gas-to-working gas ratio did not significantly change with increasing depth. Its magnitude depends on the length of the initial hydrogen filling period. An increase in the depth of hydrogen storage is associated with a greater amount of extracted water. Increasing the duration of the initial hydrogen filling period will reduce the water production but increase the cushion gas volume.

Assessment of patients with head and neck cancer using the MD Anderson Dysphagia Inventory: Results of a study into its comprehensiveness, comprehensibility and relevance to clinical practice.

The MD Anderson Dysphagia Inventory (MDADI) is a widely used patient-reported outcome measure (PROM) which assesses dysphagia-related quality of life (QoL) in head and neck cancer (HNC). Despite its common use in HNC research and clinical practice, few of its psychometric properties have been reappraised since its inception. The aim of this study was to perform a survey-based qualitative analysis of UK HNC clinicians' perceptions of the content validity of the MDADI, evaluating it across the parameters of relevance, comprehensiveness and comprehensibility as per the COSMIN guideline for PROM assessment. Four themes relating to the content validity of the MDADI were identified: (1) MDADI items lack clarity of definition of the terms 'swallowing', 'eating' and 'dysphagia'; (2) the MDADI is perceived to be overly negative in tone including items that service users may find distressing or disempowering; (3) items in the tool are exclusory to specific subgroups of patients, such as those who are nil by mouth or socially isolated; and (4) modifications to the MDADI were suggested and encouraged to make it more clinically useful and patient-centred. This study indicates that MDADI's content validity is 'insufficient' when rated by COSMIN parameters. This has significant implications for its continued use in HNC research and clinical practice. Further re-evaluation of the content validity of the MDADI is warranted, with potential future amendment of items being indicated if the results of this study are corroborated in subsequent research. What is already known on the subject The MD Anderson Dysphagia Inventory (MDADI) patient-reported outcome measure of dysphagia-related quality of life is widely used in clinical practice and international clinical trials. Content validity is considered to be the most important property of a tool when assessing its psychometric strengths and weaknesses; however, the MDADI's content validity has not been reappraised since its initial development. What this paper adds to existing knowledge This study presents UK speech and language therapists' opinions and experience of the content validity of the MDADI and this first reappraisal of its content validity since its initial development highlights several issues with this psychometric parameter of the tool. This study highlights that further re-evaluation of the content validity of the MDADI is warranted, with potential future amendment of items being indicated if the results of this study are corroborated in subsequent research. What are the potential or actual clinical implications of this work? Clinicians cannot assume that commonly used outcomes tools have strong psychometric profiles. Consideration of the content validity of outcomes tools during selection for use in clinical and research practice should be key, as this will encourage use of tools that produce relevant, valid data that can contribute meaningfully to patient-centred care.

Design and fabrication of an opto-mechanical antenna in the NIR range

In this study we present a novel device for the direct transduction of optical radiation in the near-infrared region into mechanical actuation, which is based on a plasmonic optical nanoantenna integrated in a microcantilever. We propose and demonstrate the feasibility of a simple fabrication process consisting in the nano-tailoring of a commercially available Atomic Force Microscope (AFM) cantilever by means of the Focused Ion Beam (FIB) milling technique. Furthermore, the comprehensive analysis of the device performance characteristics included in this work reveals the different sensitivity values of these characteristics to the fabrication process tolerances of the most relevant geometric design parameters.

Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model

Ripple-Spreading Network of China’s Systemic Financial Risk Contagion: New Evidence from the Regime-Switching Model

Polarization Insensitive and Thin Metamaterial Absorber Performed in High-Frequency 5G Bands

A variety of fascinating applications, including 5G communication devices, high-speed data transfer, and large-scale Internet of Things (IoT), make life easier with 5G technology. Despite the 5G’s superior features, the percentage of electromagnetic (EM) waves in the environment execute a significant increase, unpleasantly. Broadband metamaterial absorbers are an appealing alternative to gather these unwanted signals. This study aims to numerically investigate a broadband metamaterial absorber (MMA) in the 5G high-frequency spectral range with the metasurface formed with coupled resistors. In addition, the 24.25-27.5GHz frequency range, one of the high-frequency 5G bands used by selected countries such as the European Union and China, was preferred. The minor aim of this study is that the usage of coupled elements as resistors may have the ability to increase the absorption bandwidth and magnitude. Comprehensive simulations were performed using the finite integration technique (FIT) utilized by the CST Microwave Studio program to investigate the absorber performance and other relevant parameters. The unit cell design is created metal-substrate-metal structures as asymmetric, single-layer, and easy to implement. The absorption responses are investigated according to the oblique incidence angle, polarization angle for TE &TM modes. The suggested MMA provided an absorbency response above 87.6% in the frequency range 24.20-27.30GHz under normal incidence. Moreover, to comprehend the physical mechanism on absorption, the top and bottom surfaces of the absorber's electric field and surface current distributions are assessed. The designed MMA resulting in relatively high performance and polarization insensitive is helpful for electromagnetic interference (EMI) shielding of 5G signals in the FR2/mmWave frequency regime.