Values Of Parameters Research Articles

Magnetized effects of double diffusion model on mixed convective Casson nanofluid subject to generalized perspective of Fourier and Fick’s laws

Understanding the flow behavior of non-Newtonian fluids from an industrial standpoint is crucial. Many industrial and technical activities, such as the extrusion of polymer sheets, the manufacturing of paper, and the development of photographic films, require non-Newtonian fluids. Heat and mass transport have various manufacturing uses. However, classical heat and mass transfer theories (Fourier and Fick laws) cannot anticipate thermal and solute relaxation time occurrences. The purpose of this investigation is to apply the modified Ohm law to the heat and mass transportation systems, which are established by generalized Fourier and Fick’s equations, respectively. A three-dimensional Darcy–Forchheimer flow through a porous medium integrating Hall and ion slip effects is studied for a non-Newtonian fluid known as a “Casson nanofluid” with mixed convection across a stretched surface. To investigate heat transfer augmentation, the modified Buongiorno model for nanofluids is used. It covers practical nanofluid properties as well as the mechanics of random motion and thermo-migration in nanoparticles. These groups of Partial Differential Equations (PDEs) that represent the mathematical model are combined with the proper similarity transformations to create an ordinary differential equations system, which is then resolved using the power of the Lobatto IIIA method. Examples of numerical and graphical data are given to show how various physical constraints affect the variation for velocities, temperatures, mass transfer, dimensionless shear stress, as well as Nusselt and Sherwood numbers. It turns out that lowering the Casson fluid parameters’ values reduces the velocity in the spatial coordinates (x, y). A rise in the Hall parameter's values ultimately leads to an improvement in the fluid. This paper sheds light on useful applications including power generation, conservation of energy, friction elimination, and nanofluidics. Nonetheless, the work highlights an important point: by carefully adjusting the Casson parameter, thermophoresis parameter, and Brownian motion parameter, the flow of a Casson fluid, including nanoparticles, may be controlled.

Non-Markovian processes on heteroclinic networks.

Sets of saddle equilibria connected by trajectories are known as heteroclinic networks. Trajectories near a heteroclinic network typically spend a long period of time near one of the saddles before rapidly transitioning to the neighborhood of a different saddle. The sequence of saddles visited by a trajectory can be considered a stochastic sequence of states. In the presence of small-amplitude noise, this sequence may be either Markovian or non-Markovian, depending on the appearance of a phenomenon called lift-off at one or more saddles of the network. In this paper, we investigate how lift-off occurring at one saddle affects the dynamics near the next saddle visited, how we might determine the order of the associated Markov chain of states, and how we might calculate the transition probabilities of that Markov chain. We first review methods developed by Bakhtin to determine the map describing the dynamics near a linear saddle in the presence of noise and extend the results to include three different initial probability distributions. Using Bakhtin's map, we determine conditions under which the effect of lift-off persists as the trajectory moves past a subsequent saddle. We then propose a method for finding a lower bound for the order of this Markov chain. Many of the theoretical results in this paper are only valid in the limit of small noise, and we numerically investigate how close simulated results get to the theoretical predictions over a range of noise amplitudes and parameter values.

A radiotherapy community data-driven approach to determine which complexity metrics best predict the impact of atypical TPS beam modeling on clinical dose calculation accuracy.

To quantify the impact of treatment planning system beam model parameters, based on the actual spread in radiotherapy community data, on clinical treatment plans and determine which complexity metrics best describe the impact beam modeling errors have on dose accuracy. Ten beam modeling parameters for a Varian accelerator were modified in RayStation to match radiotherapy community data at the 2.5, 25, 50, 75, and 97.5 percentile levels. These modifications were evaluated on 25 patient cases, including prostate, non-small cell lung, H&N, brain, and mesothelioma, generating 1,000 plan perturbations. Differences in the mean planned dose to clinical target volumes (CTV) and organs at risk (OAR) were evaluated with respect to the planned dose using the reference (50th-percentile) parameter values. Correlation between CTV dose differences, and 18 different complexity metrics were evaluated using linear regression; R-squared values were used to determine the best metric. Perturbations to MLC offset and transmission parameters demonstrated the greatest changes in dose: up to 5.7% in CTVs and 16.7% for OARs. More complex clinical plans showed greater dose perturbation with atypical beam model parameters. The mean MLC Gap and Tongue & Groove index (TGi) complexity metrics best described the impact of TPS beam modeling variations on clinical dose delivery across all anatomical sites; similar, though not identical, trends between complexity and dose perturbation were observed among all sites. Extreme values for MLC offset and MLC transmission beam modeling parameters were found to most substantially impact the dose distribution of clinical plans and careful attention should be given to these beam modeling parameters. The mean MLC Gap and TGi complexity metrics were best suited to identifying clinical plans most sensitive to beam modeling errors; this could help provide focus for clinical QA in identifying unacceptable plans.

Optimization of suspended particulate transport parameters from measured concentration profiles with a new analytical model

The water body’s suspended concentration reflects many coastal environmental indicators, which is important for predicting ecological hazards. The modeling of any concentration in water requires solving the settling-diffusion equation (SDE), and the values of several key input parameters therein (settling velocity ws, eddy diffusivity Ds, and erosion rates p(t)) directly determine the prediction performance. The time-consuming large-scale simulations would benefit if the parameter values could be estimated through available observations in the target sea area. The present work proposes a new optimization method for synchronously estimating the three parameters from limited concentration observations. First, an analytical solution to the one-dimensional vertical (1DV) SDE for suspended concentrations in an unsteady scenario is derived. Second, the near bottom suspended sediment concentration (SSC) profiles are measured with high-resolution observation. Third, the key parameters are optimized through the best fit of the measured SSC profiles and those modeled with the unsteady solution. Nonlinear least square fitting (NLSF) is introduced to judge the best fits automatically. The high-resolution concentration measurements in a specially-designed cylindrical tank experiment using the Yellow River Delta sediments test the proposed method. The method performs well in the initial period of turbulence generation when sediment resuspension is significant. It optimizes p(t), ws, and Ds with reasonable values and uniqueness of their combination. The proposed theory is a practical tool for quickly estimating key substance transport parameters from limited observations; it also has the potential to construct local parametric models to benefit the 3D modeling of coastal substance transport. Although the present work takes SSC as an example, it can be extended to any suspended particulate concentration in the water.

Aczel–Alsina T-norm based group decision-making technique for the evaluation of electric cars using generalized orthopair fuzzy aggregation information with unknown weights

Data management and finding precise outcomes from large amounts of information are among the biggest challenges for scientists. The technique of multi-attribute group decision-making (MAGDM) is a valuable tool for investigating fuzzy data precisely. The key objective of the paper is to redefine the q-rung orthopair (q-RO) fuzzy set (FS) (q-ROFS) in the term of interval-valued and proposed new aggregation operators (AOs) based on the Aczel-Alsina (AA) t-norm (TN) and t-conorm (TCN) operations. The AA operational laws are a generalized form of existing TNs and TCNs and give more reliable results because they can fluctuate in their parametric values. The concept of interval-valued enlarges the space of membership degree (MD) and non-membership degree (NMD) for decision-makers. By taking qth power, the interval-valued q-ROFS (IV-q-ROFS) structure. The IV-q-ROFS can handle the uncertainty and vagueness in data, then interval-valued intuitionistic FS (IV-IFS) and interval-valued Pythagorean FS (PyFS) (IV-PyFS) and provide accurate results. The thought of power AOs (PAOs) makes the relationship between weight vectors and reduces the chances of uncertainty in aggregated results. By taking advantage of PAOs, this article is devoted to introducing the interval-valued q-ROF Aczel-Alsina power-weighted averaging (IV-q-ROFAAPWA) and interval-valued q-ROF Aczel-Alsina power-weighted geometric (IV-q-ROFAAPWG) operators. The fundamental axioms of AOs, idempotency, boundedness, and monotonicity, are also discussed. To illustrate the importance of suggested AOs, the real-life problem of electric car selection was solved by applying the MAGDM method using the proposed IV-q-ROFAAPWA and IV-q-ROFAAPWG operators. The comparison of proposed AOs with currently present AOs is also part of the article. We finally constructed solid conclusions.

In vitro PK/PD modeling of tyrosine kinase inhibitors in non-small cell lung cancer cell lines.

Tyrosine kinase inhibitors (TKIs) are routinely prescribed for the treatment of non-small cell lung cancer (NSCLC). As with all medications, patients can experience adverse events due to TKIs. Unfortunately, the relationship between many TKIs and the occurrence of certain adverse events remains unclear. There are limited invivo studies which focus on TKIs and their effects on different regulation pathways. Many invitro studies, however, that investigate the effects of TKIs observe additional changes, such as changes in gene activations or protein expressions. These studies could potentially help to gain greater understanding of the mechanisms for TKI induced adverse events. However, in order to utilize these pathways in a pharmacokinetic/pharmacodynamic (PK/PD) framework, an invitro PK/PD model needs to be developed, in order to characterize the effects of TKIs in NSCLC cell lines. Through the use of ordinary differential equations, cell viability data and nonlinear mixed effects modeling, an invitro TKI PK/PD model was developed with estimated PK and PD parameter values for the TKIs alectinib, crizotinib, erlotinib, and gefitinib. The relative standard errors for the population parameters are all less than 25%. The inclusion of random effects enabled the model to predict individual parameter values which provided a closer fit to the observed response. It is hoped that this model can be extended to include invitro data of certain pathways that may potentially be linked with adverse events and provide a better understanding of TKI-induced adverse events.

Sagittal Abdominal Diameter as the Best Predictor of Metabolic Syndrome in HIV-Infected Men on Antiretroviral Therapy.

The interaction of human immunodeficiency virus (HIV), host and antiretroviral therapy (ART) causes a range of metabolic disorders that can be characterized as a metabolic syndrome (MetS) that increases the cardiovascular risk. MetS involves central obesity, which can be detected using different anthropometric parameters. To assess the abilities of different anthropometric parameters in the prediction of MetS in HIV-infected men on ART. The study involved 92 male participants (mean age 44.46±10.38 years), divided into two groups: with and without MetS. All subjects underwent biochemical evaluation (triglycerides, HDL-cholesterol, fasting glucose), blood pressure measurement and anthropometric assessment: body mass, body height, body mass index (BMI), body fat mass, body circumferences (chest, upper arm, forearm, waist, hip, proximal and middle thigh and calf), sagittal abdominal diameter (SAD), skinfold thicknesses (subscapular, anterior and posterior upper arm, anterior and lateral forearm, abdominal, supraspinal, thigh and calf), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), waist-to-thigh ratio (WTR), sagittal abdominal diameter-to-body height ratio (SADH), body adiposity index (BAI) and conicity index. MetS was specified according to IDF criteria. Subjects with MetS had statistically significant higher values of all anthropometric parameters except middle thigh circumference, calf skinfold and body height. According to ROC analysis and Binary Logistic Regression, SAD has been shown as the best predictor of MetS with a predictive value of 21.40 cm (AUC:0.91), followed by WHR with a predictive value of 0.93. Sagittal abdominal diameter is the strongest anthropometric indicator of MetS in HIV-infected patients on ART.

Design and Modelling of Urban Stormwater Management and Treatment Infrastructure for Communities in Wuse, Abuja

Effective stormwater management can be used to regulate water quantity and quality for environmental sustainability, flood control, pollution reduction and other advantages of civil engineering infrastructures. Pollution of the environment and contamination of water sources can emanate from improper stormwater management. This study used a small-scale model of rainwater harvesting to analyze the design and model of urban stormwater management and treatment infrastructure for the neighborhoods in Abuja. The water quality of the treated stormwater retrieved has improved as a result of the usage of memory foam, alum, and chlorine to filter out contaminants and pathogens. With the fictitious stormwater treatment model created for this study, average values of the physicochemical parameters were collected from the stormwater discharge after it had been filtered and treated. The use of potash alum has had a variety of effects on the water’s quality. From 697 mg.L-1 to 635 mg.L-1, the total dissolved solids dropped. The DO dropped from 5.87 mg.L-1 to 3.92 mg.L-1 as well. Additionally, the turbidity rose from 4.42 FNU to 4.58 FNU, and the salinity rose from 0.7 PSU to 1.44 PSU, respectively. pH decreases from 19.78 to 15.17 mg.L-1, BOD decreases from 8.35 to 6.51, and COD decreases from 2.55 to 1.9. Calcium hardness has decreased from 287 mg.L-1 to 265.83 mg.L-1. The conductivity increases marginally from 3.24 ms.cm-1 to 3.82 ms.cm-1. The Fe2+ and Zn2+ ions exhibit a little decrease from 0.143 mg.L-1 to 0.055 mg.L-1 and from 0.092 mg.L-1 to 0.045 mg.L-1, respectively. Due to inadequate or nonexistent drainage systems in the many states and villages throughout the country, stormwater run-off management and treatment in Nigeria have been a colossal failure. Effective stormwater management can be sustained by using legal and environmental laws.

Proving chaos for a system of coupled logistic maps: A topological approach.

In the work, we prove the presence of chaotic dynamics, for suitable values of the model parameters, for the discrete-time system, composed of two coupled logistic maps, as formulated in Yousefi et al. [Discrete Dyn. Nat. Soc. 5, 161-177 (2000)], which describes two interdependent economies, characterized by two competitive markets each, with a demand link between them. In particular, we rely on the SAP (Stretching Along the Paths) method, based on a stretching relation for maps defined on sets homeomorphic to the unit square and expanding the paths along one direction. Such technique is topological in nature and allows to establish the existence of a semiconjugacy between the considered dynamical system and the Bernoulli shift, so that the main features related to the chaos of the latter (e.g., the positivity of the topological entropy) are transmitted to the former. In more detail, we apply the SAP method both to the first and to the second iterate of the map associated with our system, and we show how dealing with the second iterate, although being more demanding in terms of computations, allows for a larger freedom in the sign and in the variation range of the linking parameters for which chaos emerges. Moreover, the latter choice guarantees a good agreement with the numerical simulations, which highlight the presence of a chaotic attractor under the conditions derived for the applicability of the SAP technique to the second iterate of the map.

Prognosis of mechanically ventilated patients with COVID-19 after failure of high-flow nasal cannula: a retrospective cohort study

BackgroundThere is an argument whether the delayed intubation aggravate the respiratory failure in Acute respiratory distress syndrome (ARDS) patients with coronavirus disease 2019 (COVID-19). We aimed to investigate the effect of high-flow nasal cannula (HFNC) failure before mechanical ventilation on clinical outcomes in mechanically ventilated patients with COVID-19.MethodsThis retrospective cohort study included mechanically ventilated patients who were diagnosed with COVID-19 and admitted to the intensive care unit (ICU) between February 2020 and December 2021 at Asan Medical Center. The patients were divided into HFNC failure (HFNC-F) and mechanical ventilation (MV) groups according to the use of HFNC before MV. The primary outcome of this study was to compare the worst values of ventilator parameters from day 1 to day 3 after mechanical ventilation between the two groups.ResultsOverall, 158 mechanically ventilated patients with COVID-19 were included in this study: 107 patients (67.7%) in the HFNC-F group and 51 (32.3%) in the MV group. The two groups had similar profiles of ventilator parameter from day 1 to day 3 after mechanical ventilation, except of dynamic compliance on day 3 (28.38 mL/cmH2O in MV vs. 30.67 mL/H2O in HFNC-F, p = 0.032). In addition, the HFNC-F group (5.6%) had a lower rate of ECMO at 28 days than the MV group (17.6%), even after adjustment (adjusted hazard ratio, 0.30; 95% confidence interval, 0.11–0.83; p = 0.045).ConclusionsAmong mechanically ventilated COVID-19 patients, HFNC failure before mechanical ventilation was not associated with deterioration of respiratory failure.

Chemical differences among collapsing low-mass protostellar cores

Context. Organic features lead to two distinct types of Class 0/I low-mass protostars: hot corino sources exhibiting abundant saturated complex organic molecules (COMs) and warm carbon-chain chemistry (WCCC) sources exhibiting abundant unsaturated carbon-chain molecules. Some observations suggest that the chemical variations between WCCC sources and hot corino sources are associated with local environments and the luminosity of protostars. Aims. We aim to investigate the physical conditions that significantly affect WCCC and hot corino chemistry, as well as to reproduce the chemical characteristics of prototypical WCCC sources and hybrid sources, where both carbon-chain molecules and COMs are abundant. Methods. We conducted a gas-grain chemical simulation in collapsing protostellar cores, adopting a selection of typical physical parameters for the fiducial model. By adjusting the values of certain physical parameters, such as the visual extinction of ambient clouds (AVamb), cosmic-ray ionization rate (ζ), maximum temperature during the warm-up phase (Tmax), and contraction timescale of protostars (tcont), we studied the dependence of WCCC and hot corino chemistry on these physical parameters. Subsequently, we ran a model with different physical parameters to reproduce scarce COMs in prototypical WCCC sources. Results. The fiducial model predicts abundant carbon-chain molecules and COMs. It also reproduces WCCC and hot corino chemistry in the hybrid source L483. This suggests that WCCC and hot corino chemistry can coexist in some hybrid sources. Ultraviolet (UV) photons and cosmic rays can boost WCCC features by accelerating the dissociation of CO and CH4 molecules. On the other hand, UV photons can weaken the hot corino chemistry by photodissociation reactions, while the dependence of hot corino chemistry on cosmic rays is relatively complex. The value of Tmax does not affect any WCCC features, while it can influence hot corino chemistry by changing the effective duration of two-body surface reactions for most COMs. The long tcont can boost WCCC and hot corino chemistry by prolonging the effective duration of WCCC reactions in the gas phase and surface formation reactions for COMs, respectively. The scarcity of COMs in prototypical WCCC sources can be explained by insufficient dust temperatures in the inner envelopes that are typically required to activate hot corino chemistry. Meanwhile, the high ζ and the long tcont favors the explanation for scarce COMs in these sources. Conclusions. The chemical differences between WCCC sources and hot corino sources can be attributed to the variations in local environments, such as AVamb and ζ, as well as the protostellar property, tcont.

Hydrophobic effects on a solid sphere translating in a Brinkman couple stress fluid covered by a concentric spherical cavity

In this study, a fluid flow with an incompressible axisymmetric steady couple stress translated through a porous media is analyzed between a hollow sphere and a concentric rigid sphere. In the permeable region, the flow field is regulated by Brinkman's equation. The slip and spin slip conditions are applied on both the rigid sphere and spherical cavity surfaces. Modified Bessel functions provide a systematic approach to the problem by utilizing the principle of a stream function. On the inner sphere, the wall correction factor that an incompressible couple stress fluid encounters is calculated. The effects of the slip, spin slip, coupling stress parameter, separation distance, and permeability parameter on the field functions and the normalized drag force are also graphically shown. The corresponding results are contrasted with the outcomes reported for particular cases of couple stress fluid and viscous fluid flow in two permeability-free concentric circles. Furthermore, graphs of the streamlines for various values of the relevant parameters have been included.

Effects of Hugoniot properties on jet onset conditions

Jets are the earliest ejected material from a hypervelocity impact event. Jets comprises of projectile and target's surface material and are ejected at velocities higher than escape velocity for Earth. Effects of Hugoniot properties of the projectile and target material on jet initiation are not well understood. We, therefore, developed a mathematical model that incorporated the limitations imposed by Hugoniot properties on jet initiation for hypervelocity impact. This model analysed the effects of changes in Hugoniot properties of the projectile and target on the jet onset time, jet onset velocity and jetting side (projectile or target). The results reveal that (i) jet initiates earlier and at higher velocity if the jetting side has higher value of shock parameter or higher velocity of sound in the material; (ii) jet initiates later and at lower velocity if jetting side has high density; (iii) effect of s-parameter and speed of sound in material is more profound than the effect of density.

Proximate analysis, levels of trace heavy metals and associated human health risk assessments of Ethiopian white sugars

In this study, white sugar samples collected from five Ethiopian sugar manufacturing plants were analyzed for their proximate composition, and trace heavy metals level (Fe, Co, Ni, Mn, Zn, Cr, Cd, and Pb). Human health risk assessments associated with heavy metals exposure from white sugar ingestion were also assessed. Proximate analysis was conducted according to AOAC methods. For heavy metals determination, the sugar samples were digested using a mixture of HNO3, HClO4 and H2O2 (4:3:1) at 250 °C for 3 h prior to FAAS analysis. The measured mean values (%) of proximate parameters including moisture, ash, fiber, protein, fat and carbohydrate were found in the range of 0.07–0.61, 2.56–4.33, 0.06–0.24, 0.78–1.49, 1.16–1.89 and 92.13–95.03, respectively. The average concentration of heavy metals found in the sugar samples were ranged as 1.366–12.502, 0.107–0.268, 0.099–0.842, 0.458–1.000, 10.140–25.480, 0.053–0.322, 0.427–0.827 and 0.074–0.528 in mg/kg for Fe, Mn, Ni, Co, Zn, Cr, Cd and Pb, respectively. All the studied metals are below FAO/WHO permissible limit except Cd and Pb in Kessem, Fincha'a and Metahara samples. The target hazard quotient (THQ) and hazard index (HI) values are <1, indicating no non-carcinogenic risks of the heavy metals to an adult population via consumption of white sugar. However, the single element incremental lifetime cancer risk (ILCR) occurrence is probable from Ni for samples obtained from Kessem sugar factory (ILCR>1.0 × 10−4). The cumulative ILCR of heavy metals (Ni, Cr, Cd and Pb) resulting from consumption of white sugar by an adult person reveal a potential adverse cancer risk (ILCR>1.0 × 10−4) for all the studied samples except for sugar samples obtained from Wonji sugar factory. Therefore, continuous monitoring of these toxic metals should be made mainly by sugar industries and responsible government regulatory bodies to avert heavy metal toxicity associated with white sugar consumption in Ethiopia.

The prevalence of fibromyalgia in adults at Al-Karak Jordan: a cross-sectional study.

Fibromyalgia is a chronic and intricate musculoskeletal disorder characterized by widespread pain, fatigue, and tenderness in specific anatomical regions. Although its prevalence varies among populations, understanding the prevalence in different geographical areas is crucial for healthcare planning. This cross-sectional study aims to determine the prevalence of fibromyalgia in adults residing in Al-Karak, Jordan. The city's unique demographic and environmental characteristics may influence the occurrence of fibromyalgia among its adult population. The study aims to address gaps in knowledge, provide localized insights, and shed light on fibromyalgia's burden on the community's health. Accurate prevalence data aids healthcare planning and resource allocation. This research collected data from 965 social media participants using Google Forms. The American College of Rheumatology survey criteria for diagnosing fibromyalgia were used. To investigate the predictive value of various parameters, univariate and multivariate logistic regression analyses were performed. The study found a 26.5% prevalence of fibromyalgia in the studied population. Female gender, mental health illnesses, and comorbidities like irritable bowel syndrome, psychiatric disorders, and rheumatological and neurological diseases were significantly associated with fibromyalgia. Age, BMI, marital status, employment status, and certain comorbidities did not show statistically significant predictive value. This study sheds light on fibromyalgia's prevalence and associated factors in the Al-Karak population. The identified predictors highlight the necessity for comprehensive healthcare strategies and interventions to mitigate the disease burden. These findings aid policymakers and healthcare professionals in planning and implementing effective measures for fibromyalgia management and prevention. Further research is warranted to deepen our understanding of fibromyalgia's complexity and its implications in this region.

The role of baseline 2-[18 F]-FDG-PET/CT metrics and radiomics features in predicting primary gastric lymphoma diagnosis.

Diffuse Large B-Cell Lymphomas (DLCBL) and mucosa-associated lymphoid tissue (MALT) are the two most common primary gastric lymphomas (PGLs), but have strongly different features. DLBCL is more aggressive, is frequently diagnosed at an advanced stage and has a poorer prognosis. The aim of this retrospective study was to explore the role of fluorine-18-fluorodeoxyglucose positron emission tomography/computed tomography (2-[18 F]-FDG-PET/CT) and radiomics features (RFs) in predicting the final diagnosis of patients with PGLs. Ninety-one patients with newly diagnosed PGLs who underwent pre-treatment 2-[18 F]-FDG-PET/CT were included. PET images were qualitatively and semi-quantitatively analyzed by deriving maximum standardized uptake value body weight (SUVbw), maximum standardized uptake value lean body mass (SUVlbm), maximum standardized uptake value body surface area (SUVbsa), lesion to liver SUVmax ratio (L-L SUV R), lesion to blood-pool SUVmax ratio (L-BP SUV R), metabolic tumor volume (gMTV) and total lesion glycolysis of gastric lesion (gTLG), total MTV (tMTV), TLG, and first-order RFs (histogram-related and shape related). Receiver-operating characteristic (ROC) curve analyses were performed to determine the differential diagnostic values of PET parameters. The final diagnosis was DLBCL in 54 (59%) cases and MALT in 37 cases (41%). PGLs showed FDG avidity in 83 cases (90%), 54/54 of DLBCL and 29/37 of MALT. All PET/CT metabolic features, such as stage of disease and tumor size, were significantly higher in DLBCL than MALT; while the presence of H. Pylori infection was more common in MALT. At univariate analysis, all PET/CT metrics were significantly higher in DLBCL than MALT lymphomas, while among RFs only Shape volume_vx and Shape sphericity showed a significant difference between the two groups. In conclusion we demonstrated that 2-[18 F]-FDG-PET/CT parameters can potentially discriminate between DLBCL and MALT lymphomas with high accuracy. Among first-order RFs, only Shape volume_vx and Shape sphericity helped in the differential diagnosis.

Analytic structure of the associated Legendre functions of the second kind

We consider the complex ν plane structure of the associated Legendre functions of the second kind Qν−1/2−K(cosh⁡ρ). We find that for any noninteger value of K the Qν−1/2−K(cosh⁡ρ) have an infinite number of poles in the complex ν plane, but for any negative integer K there are no poles at all. For K = 0 or any positive integer K there is only a finite number of poles, with there only being one single pole (at ν = 0) when K = 0. This pattern is analogous to the pattern of exceptional points that appear in a wide variety of physical contexts. However, while theories with exceptional points usually lose a finite number of degrees of freedom at the exceptional points, the Qν−1/2−K(cosh⁡ρ) lose an infinite number of poles whenever K is integer. Moreover, while theories with exceptional points usually have a finite number of such exceptional points, the Qν−1/2−K(cosh⁡ρ) possess an infinite number of points (all integer K) at which they lose degrees of freedom. Other than in the PT-symmetry Jordan-block case, exceptional points usually occur at complex values of parameters. While not being Jordan-block exceptional points themselves, the poles associated with the Qν−1/2−K(cosh⁡ρ) nonetheless occur at real values of K.

Influence of yeast size on the kinetics of cell disruption in an ultrasonic homogenizer

The results of studies on the disintegration kinetics of the yeast Saccharomyces cerevisiae are presented. The process was carried out in a 500 W ultrasonic homogenizer equipped with a spherical working chamber with a volume of 100 cm 3. The concentration of the suspension of microorganisms was 0.05 g d.m./cm 3. The continuous phase was water solution containing 0.15 M NaCl and 4 mM K 2HPO 4. The kinetics of cell disruption were studied by the direct method. The theory of random transformation of dispersed matter was used to analyze the process. There was significant variation in the size of yeast cells. The range of changes in the values of parameters describing the size of microorganisms was divided into size classes. The kinetics of cell disruption in individual classes was described by a first-order linear differential equation. During the implosion of cavitation bubbles, the transformation volume of individual microorganisms is generated. It has been shown that as the volume of cells in subsequent size classes increases, their transformation volumes do not increase significantly. The safe volume for cells remains unchanged. As the size of the microorganisms increased, there was no increase in the constant rate of cell disruption.

Dynamic evolution control for the DC/DC boost converter design and implementation

This paper introduces the design and hardware implementation of the dynamic evolution control for a DC/DC boost converter. The development of the controller aims to effectively regulate the output voltage of the DC/DC boost converter with a high degree of precision. A comprehensive examination of the duty cycle formula for the boost converter is conducted using a non-linear analysis approach. This study introduces a methodology for the synthesis of a converter controller utilizing the principles of dynamic evolution control theory. The converter's output consistently aligns with the target voltage by following the dynamic evolution path determined by the designed controller. The performance evaluation of the proposed boost converter controller utilizing dynamic evolution control is being validated through the utilization of MATLAB/Simulink simulation software. The effectiveness of the proposed controller is further validated through the presentation of hardware results. The performance of the controller was evaluated by varying the values of parameters k and m.

In Silico Analysis of Natural Plant-Derived Cyclotides with Antifungal Activity against Pathogenic Fungi.

Fungal infections in plants, animals, and humans are widespread across the world. Limited classes of antifungal drugs to treat fungal infections and loss of drug efficacy due to rapidly evolving fungal strains pose a challenge in the agriculture and health sectors. Hence, the search for a new class of antifungal agents is imperative. Cyclotides are cyclic plant peptides with multiple bioactivities, including antifungal activity. They have six conserved cysteine residues forming three disulfide linkages (CI-CIV, CII-CV, CIII-CVI) that establish a Cyclic Cystine Knot (CCK) structure, making them extremely resistant to chemical, enzymatic, and thermal attacks. This in silico analysis of natural, plant-derived cyclotides aimed to assess the parameters that can assist and hasten the process of selecting the cyclotides with potent antifungal activity and prioritize them for in vivo/ in vitro experiments. The objective of this study was to conduct in silico studies to compare the physicochemical parameters, sequence diversity, surface structures, and membrane-cyclotide interactions of experimentally screened (from literature survey) potent (MIC ≤ 20 μM) and non-potent (MIC > 20 μM) cyclotides for antifungal activity. Cyclotide sequences assessed for antifungal activity were retrieved from the database (Cybase). Various online and offline tools were used for sequence-based studies, such as physicochemical parameters, sequence diversity, and neighbor-joining trees. Structure-based studies involving surface structure analysis and membrane-cyclotide interaction were also carried out. All investigations were conducted in silico. Physicochemical parameter values, viz. isoelectric point, net charge, and the number of basic amino acids, were significantly higher in potent cyclotides compared to non-potent cyclotides. The surface structure of potent cyclotides showed a larger hydrophobic patch with a higher number of hydrophobic amino acids. Furthermore, the membrane-cyclotide interaction studies of potent cyclotides revealed lower transfer free energy (ΔG transfer) and higher penetration depth into fungal membranes, indicating higher binding stability and membrane-disruption ability. These in silico studies can be applied for rapidly identifying putatively potent antifungal cyclotides for in vivo and in vitro experiments, which will ultimately be relevant in the agriculture and pharmaceutical sectors.