Additional Parameters Research Articles

Designing a Novel Porous Fixation Plate with a Gyroid Lattice Structure for Humerus Fractures Using a Probabilistic Approach

Conventional fixation plates permanently attached to the body can lead to complications, such as stress shielding and aseptic loosening, due to their contact with the bone, resulting in bone loss. The contact between these solid fixation plates and the bone surface inhibits blood flow, potentially leading to necrosis at the interface. To overcome this challenge, a porous implant featuring a gyroid lattice structure for humerus bone fixation is proposed. However, designing such an implant typically involves deterministic approaches, which do not account for uncertainties in design parameters, loadings on the plate, and additive manufacturing process parameters. Consequently, the actual conditions experienced by the plate may not be accurately modeled. Herein, both deterministic and probabilistic analyses of a porous implant with a gyroid lattice structure positioned on the humeral bone is conducted. The findings are compared to the failure probabilities of both the conventional fixation plate and the optimal plate derived from a previous study. The study reveals that uncertainties in design parameters significantly influence the plate's failure probability compared to deterministic analysis, emphasizing the importance of probability‐based analyses for a reliable plate design.

Using Level-Based Multiple Reasoning in a Web-Based Intelligent System for the Diagnosis of Farmed Fish Diseases

Farmed fish disease diagnosis is an important problem in the fish farming industry, affecting quality of production and financial losses. In this paper, we present a web-based intelligent system that tackles the problem of fish disease diagnosis. To this end, it uses multiple knowledge representation and reasoning methods: rule-based, case-based, weight-based, and voting. Knowledge, which concerns the diagnosis of sea bass diseases, was acquired from experts in the field and represented in the form of decision trees. The diagnostic process is performed in two stages: a general one and a specialized one. In the general stage, a level-based diagnosis is performed, where environmental parameters, external signs, and internal signs are successively examined, and the three most probable diseases are identified. In the specialized stage, which is optional, a specialized expert system is used for each of the resulting diseases, where additional parameters concerning laboratory tests (microbiological, microscopic, molecular, and chemical) are considered. The general stage is the most useful, given that it can be performed on-site in real-time, whereas the specialized one requires time-consuming lab tests. The system also provides explanations for its decisions. Evaluation of the general-stage diagnostic process showed a top-3 accuracy of 78.79% on expert test cases and 94% on an artificial dataset.

PREVALENCE OF LATENT TUBERCULOSIS IN DIABETIC AND NON-DIABETIC INDIVIDUALS IN A TERTIARY CARE CENTER: A COMPARATIVE STUDY

Aims and Objectives: The aims of this study were as follows: (1) To study the prevalence of latent tuberculosis (TB) in diabetic and non-diabetic population attending the tertiary care hospital. (2) To investigate the association between diabetes mellitus (DM) and latent TB, evaluating the prevalence of positive tuberculin tests and assessing glycemic parameters in diabetic patients with latent TB. Methods: This was a single-center, hospital-based, observational, and comparative study conducted in the department of general medicine of a tertiary care medical college. One hundred and thirty-six diabetic patients of either gender or 137 healthy individuals acting as control group were included in this study on the basis of a predefined inclusion and exclusion criteria. Patients were evaluated by detailed history and clinical examination. The diagnosis of latent TB was based on a positive tuberculin test without any clinical features of active TB. The prevalence of latent TB infection was compared in both the groups. p<0.05 was taken as statistically significant. Results: Patients in both the groups were found to be comparable in terms of gender distribution and mean age. Predominant patients were found to have type 2 DM. The mean duration of DM was noted to be 91.58±60.68 months. The most common diagnoses of patients in non-diabetes group were COVID-19 (9.49%), neurological diseases (8.76%), infections (7.3%), acute myocardial infarction (6.57%), and iron deficiency anemia (5.84%). About 21.32% of cases in DM group were noted to have latent TB, while the proportion of latent TB was noted to be 7.30% in the non-diabetes group. The mean fasting blood sugar, mean post-prandial blood sugar, as well as mean HbA1c were significantly higher (p<0.05) in the subgroup with latent TB versus the subgroup without latent TB. Conclusion: Individuals with diabetes mellitus were found to have increased risk of latent TB infection. In addition, male gender and elevated glycemic parameters were found to be key factors associated with latent tuberculous infection in diabetes.

Biomechanical Analysis of the Impact of Transverse Connectors of Pedicle-Screw-Based Fixation on Thoracolumbar Compression Fracture

Contemporary clinical practice is progressively shifting towards percutaneous minimally invasive surgery. Conversely, the incorporation of transverse connectors in the design of spinal fixation systems is associated with more invasive open surgical procedures. The primary objective of this investigation was to evaluate the influence of transverse connectors in posterior spinal fixation system designs in cases involving vertebral compression fractures, specifically on selected mechanical parameters of the thoracolumbar spine in situations of instability. This research objective was achieved through a combination of experimental tests and numerical simulations. From the experimental tests conducted, critical mechanical parameters were ascertained, including the bending stiffness coefficient and energy dissipation. Numerical simulations were employed to determine additional parameters, such as the angular range of motion for individual spinal segments, intradiscal pressure within individual intervertebral discs, and stress distribution on the articular facets. Analyzing the impact of transverse connectors on the obtained results revealed that their inclusion in a fixation system results in a minor increase in stiffness and a decrease in mobility in comparison to fixation systems devoid of connectors. These findings create the potential for utilizing minimally invasive surgery as a viable alternative to open surgical procedures.

Analytical solution of an Ill-posed system of nonlinear ODE’s

In this paper, we discuss a solution strategy for an overdetermined ODE system that uses elliptic functions. In particular, we show how an apparently ill-posed ODE system can be made amenable to treatment by Jacobian elliptic functions by introducing additional free parameters and still obtain a solution that corresponds well to the physically expected behaviour.

Optimal stock allocation for an automated portfolio recommender system in the perspective of maximum fund utilization

“Buying or selling” a favorable combination of stocks is always challenging for non-professional investors due to its inherent complex and dynamic nature. Creating an automated Portfolio Recommender System (RS) for investors, has been an active area of research. The reliable performance of a portfolio depends on several complex factors, namely market fluctuations, market, and investors’ behavioral patterns, customers’ demographic classification, etc. In addition, the inter-relationship between the stocks needs more investigation along with the return and associated risk for the proper selection of a portfolio. In this work, the daily closing prices and volume of 297 Indian stocks from Large, Mid, and Small Cap categories from different sectors in the National Stock Exchange (NSE) of India for the FY 2021–22 have been considered. The set of dissimilar stocks has been extracted through K-means clustering using several additional parameters, namely, beta factor and proportionate volume, along with the traditional concepts of expected return and associated risk to create sample portfolios. Subsequently, the standard portfolios from the samples have been constructed utilizing Markowitz’s Modern Portfolio Theory (MPT) with a trade-off between expected return and associated risk. Next, for the purpose of comparing the maximum utilization of the investment amount, the greedy algorithm, as well as the integer programming problem, have been applied to different investment options. The associated numbers of discrete stock allocations have been obtained accordingly. The comparison shows that the greedy algorithm performs better than integer programming problem from the perspective of maximum fund utilization. The performance validation confirms that the MPT model is better than the Hierarchical Risk Parity (HRP) model, even in a period of market crisis. Finally, on the basis of different portfolio indices, the standard portfolios and other similar portfolios using the cosine similarity approach are recommended in accordance with investors’ choice.

A model reference adaptive control framework for floating offshore wind turbines with collective and individual blade pitch strategy

The utilization of floating offshore wind turbines is regarded as a promising solution for offshore renewables, wherein blade pitch control plays a crucial role in both operation and maintenance. Among the various blade pitch control methods, strategies that involve more states pertaining to the control objectives demonstrate superior tracking performance. However, these approaches necessitate additional linearization and parameter tuning efforts, particularly when addressing varying operating conditions in real-world unsteady environments. In this study, a decoupled model reference adaptive control framework with inner control laws for ideal responses for both collective and individual blade pitch is employed, in the context of floating offshore wind turbine control problems during operation beyond rated conditions. According to the simulations conducted on a benchmark wind turbine simulator under a series of turbulent wind speeds, the proposed integrated controller achieved reductions in power fluctuation and damage equivalent load in blades compared to corresponding baseline controllers, at the expense of acceptable deterioration in tower base loads and blade actuator activities. The proposed scheme demonstrates its adaptability in serving the entire operating range, mitigating the need for parameter tuning due to variations in wind speed, and exhibits potential to involve more control purposes.

Pore size engineering of cost-effective all-nanoporous multilayer membranes for propane/propylene separation

In this study, a new multi-layer hybrid nanocomposite membrane named MFI/GO/ZIF-8 has been synthesized. This membrane combines three nanoporous materials with different morphologies in one membrane without using polymer materials. This allows access to a previously accessible region of very high permeability and selectivity properties. In addition to introducing a new and efficient MFI/GO/ZIF-8 membrane in this work, controlling the pore size of the zeolite layer has been investigated to increase the selectivity and permeability of propylene. The membrane was made using a solvent-free hydrothermal method and a layer-by-layer deposition method. To control the pore size of the MFI layer, a two-step synthesis strategy has been implemented. In the first step, three key parameters, including crystallization time, NaOH concentration and aging time of initial suspension, are controlled. In the second step, the effect of three additional parameters including hydrothermal time, hydrothermal temperature and NH4F concentration has been investigated. The results show that the optimal pore size has decreased from 177.8 nm to 120.53 nm (i.e., 32.2%). The MFI/GO/ZIF-8 membrane with fine-tuned crystal size in the zeolite layer was subjected to detailed tests for propylene selectivity and permeability. The structural characteristics of the membrane were also performed using FT-IR, XRD, FESEM and EDS techniques. The results show that the synergistic interaction between the three layers in the nanocomposite membrane significantly improves the selectivity and permeability of propylene. The permeability and selectivity of propylene increased from 50 to 60 GPU and from 136 to 177, respectively, before and after precise crystal size control. MFI/GO/ZIF-8 membrane by controlling the pore size of the zeolite layer shows a significant increase of 23.1% in selectivity and 16.7% in propylene permeability compared to the initial state. Also, due to the precise synthesis method, the absence of solvent and the use of cheap support, the prepared membrane is considered an environmentally friendly and low-cost membrane. This study emphasizes the potential of increasing the selectivity and permeability of propylene in the MFI/GO/ZIF-8 hybrid membrane by controlling the crystal size of the zeolite layer.

Physical-layer key distribution based on commonly-driven laser synchronization with random modulation of drive light.

We propose and experimentally demonstrate a physical-layer key distribution scheme using commonly-driven laser synchronization with random modulation of drive light. Two parameter-matched semiconductor lasers injected by a common complex drive light are used as entropy sources for legitimate users. Legitimate users generate their own random signal by randomly time-division multiplexing of two random sequences with a certain duration according to individual control codes, and then independently modulate the drive light. Laser synchronization is achieved during time slots when the modulation sequences of two users are identical, and thus provide highly correlated randomness for extracting random numbers as shared keys. Experimental results show that the random modulation of the drive light reduces the correlation between the drive light and laser outputs. In addition, laser synchronization is sensitive to the modulation delay and then the latter can be used as an additional hardware parameter. These mean that security is enhanced. In addition, the proposed method has a short laser synchronization recovery time of lower than 1.1 ns, meaning a high rate of key distribution. The upper limit of final key rate of 2.55 Gb/s with a criterion of bit error rate of 1.68 × 10-3 is achieved in experiments. Our results provide a promising candidate for protecting the security of optical fiber communication.

Computational and physical aspects for the occurrence of crease in an elastomer under general loading conditions

We study the occurrence of crease in an elastomer under three loading conditions from both computational and physical points of view. A two-dimensional finite element analysis, including a perturbation force-based approach, is performed to detect the stable creased state, where the crease formation is completed. A mesh convergence study for the energy release and crease depth in the creased state provides a guideline for the finite element mesh requisite for predicting the occurrence of crease. We also visualize the mesh convergence for the critical creasing onset by plotting the set of compressive strain and mesh resolution at the point where the energy release is zero. In addition, the present evaluation method of the surface tension using the energy release and surface area change for an elastomer with a traction-free surface yields a good prediction for the creasing onset delayed by surface tension without additional numerical implementations or adjustment parameters. This facilitates the comprehensive study of the creasing onset delayed by the surface tension under general loading conditions. The results reveal that tensile deformation in the out-of-plane direction encourages the retardation of the creasing onset via the extension of the width and the energy emission. We further demonstrate that energetically preferential crease interval can be used to evaluate the spacing between creases delayed by moderate surface tension.

Study on the relationship between Vitamin D deficiency and Leukocyte Ratio in Multidrug Resistant Tuberculosis patients

Tuberculosis (TB) remains an important health problem in Indonesia,the problems more complex with phenomenon of multi-drug resistance Tuberculosis (MDR) which cause worse prognosis, long treatment,high risk of transmission to other and side effect of treatment. Vitamin D plays a role in non specific and specific immune responses in Mycobacterium tuberculosis (M.tb) infection. Vitamin D have a role in hematopoiesis and affects the early development of monocytes and granulocytes. M.tb infection causes changer in the ratio of neutrophil cells, lymphocytes and monocytes. Changes in the ratio reflect an increase or decrease of effective immune response. Using a case control design, this study will evaluate the correlation between vitamin D, leukocyte ratio and MDR-TB patients among MDR-TB patient cases and TB patient controls. Independent variable in this study were vitamin D levels, leukocyte ratios consisting of NLR, MLR, NMLR, and clinical status of respondents were the dependent variable. The result of this study found that vitamin D levels of TB patients all showed values ​​that were within range of in the insufficiency and deficiency categories. From this result TB patients must coverIn addition, the NLR and NMLR parameters were able to show that immune status problems were mainly found in the MDR-TB patients

Material intensity and embodied CO2 benchmark for reinforced concrete structures in Brazil

Cement and steel production significantly contribute to global CO2 emissions, with reinforced concrete structures accounting for a substantial portion. Therefore, optimizing the structural design helps reduce material and carbon intensity. However, industry-based benchmarks for material and carbon intensity of structures are scarce and lack transparency. This study fills this gap by analyzing detailed industry data derived from construction designs of 53 reinforced concrete structures for multifamily residential buildings in Brazil and assessing their cradle-to-gate material intensity and embodied CO2 emissions. The findings revealed significant variations in the usage of steel (70–159 kg/m³) and concrete (0.17–0.29 m³/m2). The quantity of structural materials ranged from 418 to 731 kg/m2, and the embodied CO2 ranged from 35 to 140 kg CO2/m2, including the variability in CO2 emissions during material production. Building height is the primary geometric parameter that determined material intensity and embodied CO2, particularly for columns. However, structural materials quantity varies considerably among buildings with the same number of stories, suggesting the presence of additional design parameters influencing material intensity. The results emphasize the role of designers in promoting decarbonization through dematerialization. Also, selecting the right material supplier is important as, on average, differences between manufacturers corresponds to a difference of 38 kg CO2/m2 in structural embodied CO2. Selecting low-carbon material suppliers and employing structural design benchmarking practices can efficiently reduce the embodied carbon of reinforced concrete structures.

Making TSM better: Preserving foundational philosophy for efficient action recognition

In this study, we present the Discriminative Temporal Shift Module (D-TSM), an enhancement of the Temporal Shift Module (TSM) for action recognition. TSM has limitations in capturing intricate temporal dynamics due to its simplistic feature shifting. D-TSM addresses this by introducing a subtraction operation before the shifting. This enables the extraction of discriminative features between adjacent frames, thereby allowing for effective action recognition where subtle motions serve as crucial cues. It preserves TSM’s foundational philosophy, prioritizing minimal computational overhead and no additional parameters. Our experiments demonstrate that D-TSM significantly improves performance of TSM and outperforms other leading 2D CNN-based methods.

Non-thermal WIMP production from higher order moduli decay

In a non-standard cosmological scenario heavy, long-lived particles, which we call moduli, dominate the energy density prior to Big Bang Nucleosynthesis. Weakly Interacting Massive Particles (WIMPs) may be produced non-thermally from moduli decays. The final relic abundance then depends on additional parameters such as the branching ratio of moduli to WIMPs and the modulus mass. This is of interest for WIMP candidates, such as a bino-like neutralino, where thermal production in standard cosmology leads to an overdensity. Previous works have shown that the correct dark matter (DM) relic density can then still be obtained if the moduli, with mass less than 107 GeV, decay to WIMPs with a branching ratio of less than 10-4. This upper bound could easily be violated once higher order corrections, involving final states with more than two particles, are included. We compute the branching ratios of three- and four-body decays of a modulus into final states involving two DM particles for general couplings. We then apply these expressions to sparticle production within the Minimal Supersymmetric Standard Model (MSSM) with neutralino DM. We find that this upper bound on the branching ratio can be satisfied in simplified models through an appropriate choice of as yet undetermined couplings. However, in the MSSM, it requires sparticle masses to be very close to half the modulus mass, in contrast to the idea of weak-scale supersymmetry.

Mapping the Parameter Space of Simulated Lotteries

Abstract This study presents an econophysics based approach to the study of lotteries. By treating lotteries as complex systems we analyse the guiding dynamics of real-world lotteries. We found that the growth of the jackpot, that can be won, between two successive draws is proportional to its preceding value. This growth is best described as a linear function with two parameters a and b reflecting foundational player pool sales and the excitement generated by the current jackpot respectively. A computer simulation considering additional parameters (such as the price of a ticket: s, and the format of the lottery: p) is used to study the statistical features of simulated lotteries covering a vast parameter space. This approach enables us to construct a detailed map of how various parameters influence lottery behaviour by examining the statistical characteristics of the simulated lotteries. The findings emphasize the need for thoughtful pricing strategies in real-world lotteries and suggest that simulations can assist organizers in making informed decisions.

Quantitative Phase Field Model for Electrochemical Systems

Modeling microstructure evolution in electrochemical systems is vital for understanding the mechanism of various electrochemical processes. In this work, we propose a general phase field framework that is fully variational and thus guarantees that the energy decreases upon evolution in an isothermal system. The bulk and interface free energies are decoupled using a grand potential formulation to enhance numerical efficiency. The variational definition of the overpotential is used, and the reaction kinetics is incorporated into the evolution equation for the phase field to correctly capture capillary effects and eliminate additional model parameter calibrations. A higher-order kinetic correction is derived to accurately reproduce general reaction models such as the Butler-Volmer, Marcus, and Marcus-Hush-Chidsey models. Electrostatic potentials in the electrode and the electrolyte are considered separately as independent variables, providing additional freedom to capture the interfacial potential jump. To handle realistic materials and processing parameters for practical applications, a driving force extension method is used to enhance the grid size by three orders of magnitude. Finally, we comprehensively verify our phase field model using classical electrochemical theory.

Comprehensive integrated analysis of MR and DCE-MR radiomics models for prognostic prediction in nasopharyngeal carcinoma

Although prognostic prediction of nasopharyngeal carcinoma (NPC) remains a pivotal research area, the role of dynamic contrast-enhanced magnetic resonance (DCE-MR) has been less explored. This study aimed to investigate the role of DCR-MR in predicting progression-free survival (PFS) in patients with NPC using magnetic resonance (MR)- and DCE-MR-based radiomic models. A total of 434 patients with two MR scanning sequences were included. The MR- and DCE-MR-based radiomics models were developed based on 289 patients with only MR scanning sequences and 145 patients with four additional pharmacokinetic parameters (volume fraction of extravascular extracellular space (ve), volume fraction of plasma space (vp), volume transfer constant (Ktrans), and reverse reflux rate constant (kep) of DCE-MR. A combined model integrating MR and DCE-MR was constructed. Utilizing methods such as correlation analysis, least absolute shrinkage and selection operator regression, and multivariate Cox proportional hazards regression, we built the radiomics models. Finally, we calculated the net reclassification index and C-index to evaluate and compare the prognostic performance of the radiomics models. Kaplan-Meier survival curve analysis was performed to investigate the model’s ability to stratify risk in patients with NPC. The integration of MR and DCE-MR radiomic features significantly enhanced prognostic prediction performance compared to MR- and DCE-MR-based models, evidenced by a test set C-index of 0.808 vs 0.729 and 0.731, respectively. The combined radiomics model improved net reclassification by 22.9%–52.6% and could significantly stratify the risk levels of patients with NPC (p = 0.036). Furthermore, the MR-based radiomic feature maps achieved similar results to the DCE-MR pharmacokinetic parameters in terms of reflecting the underlying angiogenesis information in NPC. Compared to conventional MR-based radiomics models, the combined radiomics model integrating MR and DCE-MR showed promising results in delivering more accurate prognostic predictions and provided more clinical benefits in quantifying and monitoring phenotypic changes associated with NPC prognosis.

On the physical significance of non-local material parameters in optical metamaterials

When light interacts with a material made from subwavelength periodically arranged constituents, non-local effects can emerge. They occur because of either a complicated response of the constituents or possible lattice interactions. In lowest-order approximations of a general non-local response function, phenomena like an artificial magnetism and a bi-anisotropic response emerge. However, investigations beyond these lowest-order descriptions of non-local effects are needed for optical metamaterials (MMs) where a significant long-range interaction becomes evident. This highlights the need for additional material parameters to account for spatial non-locality in an effective medium description. These material parameters emerge from a Taylor expansion of the general and exact non-local response function. Even though these non-local parameters improve the effective description, their physical significance is yet to be understood. To improve the situation, we consider a conceptional MM consisting of scatterers characterized by a prescribed multipolar response arranged on a square lattice. Lorentzian polarizabilities describe the scatterers in the electric dipolar, electric quadrupolar, and magnetic dipolar terms. A slab of such a MM is homogenized while considering an increasing number of non-local terms in the constitutive relations at the effective level. We show that the effective permittivity and permeability are linked to the electric and magnetic dipole moments of the scatterers. The non-local material parameters are related to the higher-order multipolar moments and their interaction with the dipolar terms. Studying the effective material parameters with the knowledge of the induced multipolar moments in the lattice facilitates our understanding of the significance of each material parameter. Our insights aid in deciding on the order to truncate the Taylor expansion of the considered constitutive relations for a given MM.

Robust Bilinear Probabilistic PCA Using a Matrix Variate t Distribution.

The bilinear probabilistic principal component analysis (BPPCA) was introduced recently as a model-based dimension reduction technique on matrix data. However, BPPCA is based on the Gaussian assumption and hence is vulnerable to potential outlying matrix-valued observations. In this article, we present a new robust extension of BPPCA, called BPPCA using a matrix variate t distribution ( t BPPCA), that is built upon a matrix variate t distribution. Like the multivariate t , this distribution offers an additional robustness tuning parameter, which can downweight outliers. By introducing a Gamma distributed latent weight variable, this distribution can be represented hierarchically. With this representation, two efficient accelerated expectation-maximization (EM)-like algorithms for parameter estimation are developed. Experiments on a number of synthetic and real datasets are conducted to understand t BPPCA and compare with several closely related competitors, including its vector-based counterpart. The results reveal that t BPPCA is generally more robust and accurate in the presence of outliers. Moreover, the expected latent weights under t BPPCA can be effectively used for outliers' detection, which is much more reliable than its vector-based counterpart due to its better robustness.

Performance of handheld ultrasound devices in diagnosis of pulmonary hypertension and right heart dysfunction in ICU patients.

The use of handheld ultrasonography devices (HHUD) has increased recently but there are limited data about their performance in the evaluation of right heart dysfunction (RHD) and pulmonary hypertension (PHT). The aim of the study is to compare the performance of a HHUD with a conventional ultrasound device (CUD) in assessing PHT and RHD. This single-center prospective study was performed in a seven-bed teaching hospital intensive care unit (ICU). PHT and RHD criteria were compared by HHUD and CUD. Additional PHT criteria and right ventricle (RV) systolic and diastolic dysfunction criteria were also measured. Forty-six patients were included in the study. There was no significant difference between the imaging rates and mean values of the parameters measured by both devices. When the positivity rates for additional PHT parameters and RHD criteria were compared, there were no significant differences between the devices. In Bland-Altman's analysis, there was good agreement and there was no bias between the measurements of the two devices but left ventricular end-systolic eccentricity index (LVSEI), right atrium area (RAA), and pulmonary artery diameter (PAD). Ninety percent of the patients had PHT probability, of whom 43% had a low, 37% had intermediate and 10% had a high probability of PHT. Ninety-two percent of the patients had RHD and there was no significant difference between the devices in the diagnosis of RHD (p=.212). When RV systolic and diastolic dysfunction evaluations of the devices were compared according to the British Society of Echocardiography (BSE) criteria there was no significant difference between the devices' measurements in the evaluation of systolic and diastolic function. The imaging and measurement capabilities of the HHUDs for PHT and RHD parameters were similar to CUDs, and considering the inconsistent parameters, the HHUD can be useful in diagnosing these problems.