Variable Quantities Research Articles

Investment Management as a Mechanism for Economic Diversification in the Kingdom of Saudi Arabia: between Opportunities and Challenges – Analytical and Foresight Study 2030 Vision

Investment plays an increasing role in promoting economic diversification, and this only succeeds if it is managed effectively. Economic diversification is a crucial feature of supportable progress, as divergence improves economic steadiness and support to surge GDP and encourages organisational and long standing change not only in the budget but also in extra columns of expansion such as communal establishments and proportions. Nevertheless, there is no accord on the consequences in the literature review for the reason that of several influences, for example the employment of dissimilar variable quantity, methods, KSA countries, and time periods. Thus, this work provides detailed insight into the current and future trends and shifts of the Saudi economy. The paper conducts a measurement and analysis of the Saudi economic diversification in light of Vision 2030, the findings of which are used to develop and propose a study framework for developing a dynamic economy.

К РАСЧЕТУ ЖИДКОСТНЫХ ТАРЕЛЬЧАТЫХ СЕПАРАТОРОВ С ПАРАБОЛИЧЕСКИМИ ВСТАВКАМИ

The object of the study is liquid disk separators with curvilinear inserts, which are described by equations of the type . The study was conducted to study the effect of the insert shape on the intensity of the centrifugal force on the liquid flow, as well as on the length of the sedimentation path (or float) of dispersed medium particles. The efficiency of clarification of dispersed media is predetermined by two design characteristics of the device - the length of the particle sedimentation path and the direction of the centrifugal force relative to the walls of the curved channel. For parabolic inserts, the distance between them and the angle of inclination of the walls are variable quantities. To calculate these quantities, nonlinear equations are constructed and an algorithm for numerical calculations is proposed. The calculation results are presented as graphical dependencies of the above parameters along the channel length. The calculations were performed for paraboloids of revolution with degrees m=2, 3 and 4 at coefficient a=2, 3 and 4. As the coefficient a increases, the distance between the inserts decreases. The influence of the exponent m on the gap between the paraboloids of revolution is more complex. The gap size along the channel length decreased from 3 cm to several millimeters. The angle of inclination of the walls relative to the rotation axis decreased in the range from 70 to 10 degrees. As the parameters a and m increase, this angle decreases, therefore, the component of the centrifugal force directed perpendicular to the channel wall increases. The equations of motion of the liquid system were solved by the method of equal flow surfaces, according to which the flow is represented as several layers with their own velocities. At the inlet section, the velocity diagram develops from a flat profile to a parabolic form. As a result of the action of the centrifugal force, an asymmetry of the velocity profile is observed. The obtained results can be used to justify the geometric characteristics of a plate separator with parabolic inserts and to coordinate them with the flow regime parameters.

Rapid manufacture of low-seed CAR-T cells in a GMP-grade hollow-fiber bioreactor platform

Both quality of product and rapidity of manufacture are critical parameters if ex vivo manufacturing of autologous chimeric antigen receptor T cell (CAR-T) therapies is to reach its full potential. The Quantum Flex™ Cell Expansion System from Terumo Blood and Cell Technologies (Terumo BCT), a hollow-fiber bioreactor platform, is one of several cell expansion systems available to cell and gene therapy manufacturers to generate such cells in a GMP-compliant manner. In this study, the dynamic range of the Quantum Flex platform to expand CD19 CAR-T cells from variable quantities of starting material was investigated. Reflecting the industry's utilization of contract development manufacturing organizations (CDMOs) for accelerating clinical timelines, Terumo Blood and Cell Technologies performed a technology transfer of application protocols for study execution. Four different amounts starting material (1, 3, 6, and 15 million cells) were expanded on Quantum Flex, using a unique donor's cells for each run. In this study, CAR-T cells were created using commercially obtained T cells and an anti-CD19 CAR-T lentiviral construct. The resultant heterogenous cell populations were expanded for 7 days in the functionally closed bioreactor platform. Expansion kinetics for all 4 starting material amounts were remarkedly similar, resulting in a 150- to 200-fold increase in cell numbers. This allowed for a study maximum of 2.6 billion cells from loading 15 million cells. Viability remained high throughout the expansion process with > 93% for all 4 donors at harvest. To complete the manufacturing cycle, the automated and functionally closed Finia™ Fill and Finish System (Terumo Blood and Cell Technologies, Lakewood, CO) was used to formulate the cells for cryopreservation. Post-procedure analysis for potency and cytotoxicity demonstrated the production of efficacious cells. With this range of starting numbers, the platform is relevant to adult, pediatric, and compassionate CAR-T expansion dosing. Today, several platforms are available to achieve sufficient cell yields for therapeutic applications of CAR-T, and awareness of the capabilities, pros, and cons of each platform is critical to drive progress.

Prediction Intervals for Overdispersed Poisson Data and Their Application in Medical and Pre-Clinical Quality Control.

In pre-clinical and medical quality control, it is of interest to assess the stability of the process under monitoring or to validate a current observation using historical control data. Classically, this is done by the application of historical control limits (HCL) graphically displayed in control charts. In many applications, HCL are applied to count data, for example, the number of revertant colonies (Ames assay) or the number of relapses per multiple sclerosis patient. Count data may be overdispersed, can be heavily right-skewed and clusters may differ in cluster size or other baseline quantities (e.g., number of petri dishes per control group or different length of monitoring times per patient). Based on the quasi-Poisson assumption or the negative-binomial distribution, we propose prediction intervals for overdispersed count data to be used as HCL. Variable baseline quantities are accounted for by offsets. Furthermore, we provide a bootstrap calibration algorithm that accounts for the skewed distribution and achieves equal tail probabilities. Comprehensive Monte-Carlo simulations assessing the coverage probabilities of eight different methods for HCL calculation reveal, that the bootstrap calibrated prediction intervals control the type-1-error best. Heuristics traditionally used in control charts (e.g., the limits in Shewhart c- or u-charts or the mean ± 2 SD) fail to control a pre-specified coverage probability. The application of HCL is demonstrated based on data from the Ames assay and for numbers of relapses of multiple sclerosis patients. The proposed prediction intervals and the algorithm for bootstrap calibration are publicly available via the R package predint.

Single nucleus DNA sequencing of flow sorted archived frozen and formalin fixed paraffin embedded solid tumors.

Archived samples, including frozen and formalin fixed paraffin embedded (FFPE) tissues, are a vast resource of clinically annotated materials for the application of high-definition genomics to improve patient management and provide a molecular basis for the delivery of personalized cancer therapeutics. Notably, FFPE tissues are stable, provide repeat sampling of tissues of interest, and can be stored indefinitely at ambient temperature. The development of single cell DNA sequencing (scDNA-seq) technologies provides an unparalleled opportunity for the study of tumor heterogeneity and the identification of often rare subclonal cell populations that drive tumor evolution and progression to advanced therapy resistant disease. However, major limitations to the use of archived tissues for scDNA-seq include the low yields of intact cells in the presence of high levels of subcellular debris in biopsies, and the highly variable quantity and quality of the DNA extracted from samples of interest. The latter is of high significance for the use of FFPE tissues due to the presence of DNA-protein crosslinks. In addition, many samples, notably tumors arising in solid tissues, contain admixtures of reactive stroma, inflammatory cells, and necrosis in immediate contact with tumor cells. To expand their use for translational studies, we optimized flow sorting and sequencing of single nuclei from archived fresh frozen (FF) and FFPE tumor tissues. Our methods, which include isolation of intact nuclei suitable for library preparations, quality control (QC) metrics for each step, and a single cell sequencing bioinformatic processing and analysis pipeline, were validated with flow sorted nuclei from matching FF and FFPE ovarian cancer surgical samples and a sequencing panel of 553 amplicons targeting single nucleotide and copy number variants in genes of interest. Our flow sorting based protocol provides intact nuclei suitable for snDNA-seq from archival FF and FFPE tissues. Furthermore, we have developed QC steps that optimize the preparation and selection of samples for deep single cell clonal profiling. Our data processing pipeline captures rare subclones in tumors with highly variable genomes based on variants in genes of interest.

The Effect of Working Capital Turnover and Current Ratio (CR) on Return On Investment (ROI) at PT Harum Energy, Tbk (A Company Listed on the Indonesia Stock Exchange Period 2015-2022)

The purpose of this study was to determine the effect of working capital turnover and current ratio (cr) on return on investment (roi) at PT Harum Energy, Tbk for the period 2015-2022. The research method used is a descriptive associative method. The population consists of secondary data from the financial statements of PT Harum Energy, Tbk. The sample taken used non-probability sampling with purpose sampling method with specific criteria, see the quarterly financial reports of PT Harum Energy, Tbk for the period 2015-2022. To test the influence analysis, Pearson product moment correlation analysis, coefficient of determination analysis, multiple linear regression analysis and t-test and F-test hypothesis testing were applied. The results of the investigation demonstrate that the value of the correlation between working capital turnover and (roi) is -0,193 the correlation value of this falls into the extremely low group, current ratio to return on investment is 0,251 It falls under the low group. The outcomes of the determination analysis show that the quantity of the independent variables influence and contribution (working capital turnover and current ratio) to the dependent variable (return on investment) is 25% and the remainder 75% is affected by additional factors that the author did not look into

Groundwater Pollution Source and Aquifer Parameter Estimation Based on a Stacked Autoencoder Substitute

A concurrent heuristic search iterative process (CHSIP) is used for estimating groundwater pollution sources and aquifer parameters in this work. Frequent calls to carry out a numerical simulation of groundwater pollution have generated a huge calculated load during the CHSIP. Therefore, a valid means to mitigate this is building a substitute to emulate the numerical simulation at a low calculated load. However, there is a complicated nonlinear correlativity between the import and export of the numerical simulation on account of the large quantity of variables. This leads to a poor approach accuracy of the substitute compared to the simulation when using shallow learning methods. Therefore, we first built a stacked autoencoder substitute, using the deep learning method, to boost the approach accuracy of the substitute compared to the numerical simulation. In total, 400 training samples and 100 testing samples for the substitute were collected by employing the Latin hypercube sampling method and running the numerical simulator. The CHSIP was then employed for estimating the groundwater pollution sources and aquifer parameters, and the estimated outcome was obtained when the CHSIP was terminated. The data analysis, including interval estimation and point estimation, was implemented on the MATLAB platform. A relevant hypothetical case is set to verify our approaches, which shows that the CHSIP is helpful for estimating the groundwater pollution source and aquifer parameters and that the stacked autoencoder method can effectively boost the approach precision of the substitute for the simulator.

Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm

In this paper, a new method is designed to effectively determine the parameters of proton exchange membrane fuel cells (PEMFCs), i.e., ξ1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\xi }_{1}$$\\end{document}, ξ2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\xi }_{2}$$\\end{document}, ξ3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\xi }_{3}$$\\end{document}, ξ4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\\xi }_{4}$$\\end{document}, RC\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}_{\ ext{C}}$$\\end{document}, λ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\lambda$$\\end{document}, and b\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$b$$\\end{document}. The fuel cells (FCs) involve multiple variable quantities with complex non-linear behaviours, demanding accurate modelling to ensure optimal operation. An accurate model of these FCs is essential to evaluate their performance accurately. Furthermore, the design of the FCs significantly impacts simulation studies, which are crucial for various technological applications. This study proposed an improved parameter estimation procedure for PEMFCs by using the GOOSE algorithm, which was inspired by the adaptive behaviours found in geese during their relaxing and foraging times. The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. In order to validate the proposed algorithm, a number of experiments using various datasets were conducted and compared the outcomes with different state-of-the-art algorithms. The outcomes indicate that the proposed GOOSE algorithm not only produced promising results but also exhibited superior performance in comparison to other similar algorithms. This approach demonstrates the ability of the GOOSE algorithm to simulate complex systems and enhances the robustness and adaptability of the simulation tool by integrating essential behaviours into the computational framework. The proposed strategy facilitates the development of more accurate and effective advancements in the utilization of FCs.

A two-layer planning method for location and capacity determination of public electric vehicle charging stations

The planning of public charging stations is crucial for the growth of electric vehicles (EVs). To improve the accuracy of predicting EV charging demand in urban areas, we propose a charging decision-making model based on fuzzy logic. Meanwhile, the influence of private charging piles is considered to further enhance the accuracy of predicting public charging demand. To address the issue of optimization algorithms easily getting stuck in local optima due to the vast quantity of variables involved in the location and capacity planning process, this paper introduces a two-layer planning method. In specific, the upper-level location model optimizes the locations of charging stations, while the lower-layer capacity model determines the number of charging piles within each station, leading to a reduction in the number of variables for each layer. Moreover, through iterative exchange results between the upper-layer location model and lower-layer capacity model, the optimal solution can be attained. The simulation results demonstrate that the proposed method can simultaneously consider the perspectives of both EV drivers and charging station investors, while also enhancing the utilization rates of public charging piles.

Assessing total mortality following seabird wrecks given variable data quantity and quality: the Cassin’s auklet die-off

Assessing total mortality following seabird wrecks given variable data quantity and quality: the Cassin’s auklet die-off

A two-stage accelerated search strategy for large-scale multi-objective evolutionary algorithm

Since large-scale multi-objective problems (LSMOPs) have huge decision variables, the traditional evolutionary algorithms are facing difficulties of low exploitation efficiency and high exploration costs in solving LSMOPs. Therefore, this paper proposes an evolutionary strategy based on two-stage accelerated search optimizers (ATAES). Specifically, a convergence optimizer is devised in the first stage, while a three-layer lightweight convolutional neural network model is built, and the population is homogenized into two subsets, the diversity subset, and the convergence subset, which serve as input nodes and the expected output nodes of the neural network, respectively. Then, by constantly backpropagating the gradient, a satisfactory individual will be produced. Once exploitation stagnation is discovered in the first phase, the second phase will be run, where a diversity optimizer using a differential optimization algorithm with opposite learning is suggested to increase the exploration range of candidate solutions and thereby increase the population's diversity. Finally, to validate the algorithm's performance, on multi-objective LSMOP and DTLZ benchmark suits with decision variable quantities of 100, 300, 500, and 1000, the ATAES demonstrated its superiority with other advanced multi-objective evolutionary algorithms.

Metal accretion scars may be common on magnetic, polluted white dwarfs

More than 30% of white dwarfs exhibit atmospheric metals, which are understood to be from recent or ongoing accretion of circumstellar debris. In cool white dwarfs, surface motions should rapidly homogenise photospheric abundances, and the accreted heavy elements should diffuse inward on a timescale much longer than that for surface mixing. The recent discovery of a metal scar on WD 0816–310 implies its B ≈ 140 kG magnetic field has impeded surface mixing of metals near the visible magnetic pole. Here, we report the discovery of a second magnetic, metal-polluted white dwarf, WD 2138–332, which exhibits periodic variability in longitudinal field, metal line strength, and broadband photometry. All three variable quantities have the same period, and show remarkable correlations: the published light curves have a brightness minimum exactly when the longitudinal field and line strength have a maximum, and a maximum when the longitudinal field and line strength have a minimum. The simplest interpretation of the line strength variability is that there is an enhanced metal concentration around one pole of the magnetic field; however, the variable line-blanketing cannot account for the observed multi-band light curves. More theoretical work is required to understand the efficiency of horizontal mixing of the accreted metal atoms, and the origin of photometric variability. Because both magnetic, metal-polluted white dwarfs that have been monitored to date show that metal line strengths vary in phase with the longitudinal field, we suggest that metal scars around magnetic poles may be a common feature of metal-polluted white dwarfs.

ASSESSMENT OF DEMOGRAPHIC CAPACITY IN THE CONTEXT OF SPATIAL PLANNING

The article discusses the issue of demographic capacity assessment in the spatial planning process. Demographic capacity (DC) is the maximum amount of population that can be accommodated in a given area, provided that the daily living requirements of the population are met with local resources, ensuring the ecological balance of the area. The need to calculate the DC stems from the goals and requirements of the proportionately and sustainable development of the area. Due to the complexity of the considered issue, an inventory of the factors determining the DC of the area and justification of their assessment methodology was carried out. DC is a variable quantity that can be changed in the conditions of scientific-technical, socio-economic progress, replenishment of national wealth. In spatial planning, we attach great importance to the integral magnitude of DC assessment. The minimum of the indicators calculated by various factors was accepted as the integrating indicator of the DC. In the article, demographic carrying capacity is calculated according to the following factors: ecological security, territorial opportunities, water resources and recreational resources. As a result of the analysis of private DC, the integrated DC of the studied area is accepted.

Viscosity of Clayey Soils: Experimental Studies

Due to the high rate of the development of housing, transportation and hydraulic engineering construction in the last hundred years, the study of the phenomenon of creep of clay soils has become a subject of scientific research. In the study, experimental investigations of clay soil were conducted using a simple shear device in kinematic loading mode, aimed at examining the influence of shear rate on the viscosity coefficient of the clay soil and its strength characteristics. The tests were performed at four different shear rates and three different vertical load values. Based on the results of experimental and theoretical studies, the viscosity coefficients of clay soil were obtained, and a new rheological equation was proposed, which simultaneously takes into account the influence of Coulomb friction, structural cohesion, cohesion of water–colloidal bonds and viscous resistance of the soil. It has been shown that the shear rate has a significant impact on the viscosity coefficient of clay soil, and the viscosity coefficient itself is a variable quantity, depending both on the magnitude of the applied load and the duration of its application. The obtained results can be used for further improvement of methods for calculating the settlement of structures over time, as well as for predicting the time until the bearing capacity of foundation soils is exhausted.

Fault root cause analysis using degree of change and mean variable threshold limit in non-linear dynamic distillation column

The chemical industrial processes are both dynamic and complex. The presence of instability and danger in the production process poses significant challenges to safety management. Early and accurate fault diagnosis is essential to ensure a sustainable and stable chemical process performance. Most studies in literature do not provide detailed information about diagnosing the root cause of faults in distillation columns using contribution plots. Using principal component analysis (PCA) in conventional contribution plots leads to a large number of contributing variables, making it difficult to identify the root cause of a specific fault. In this study, the authors suggest employing the Degree of Change of Contribution Values (DCC) and Mean Variable Threshold Limit (LMVT) techniques alongside the Wavelet Transform-Principal Component Analysis (WT-PCA) method to decrease the quantity of fault identification variables in a non-linear system (distillation column). The Aspen Plus software is utilized to perform a dynamic simulation of a distillation column, generating data for both normal and faulty operations. Two distinct types of faults are considered, which include loss of feed flow and feed temperature changes. This study aims to analyze the results obtained from the Hotelling T2 and SPE contribution plots by calculating the average difference between the normal and faulty conditions using the Degree of Change in Contribution Values. This procedure is performed to determine the extent of deviation from the standard state. Subsequently, the variables that have surpassed the threshold limit for means variables (LMVT) are designated as the variables that serve as the primary underlying cause of the fault. The technique was employed in a case study involving a nonlinear distillation column, and the results indicate that only one "dominant" variable intersects the LMVT by Hotelling T2, which represents the true underlying cause of the corresponding fault.

Implementation of Small Term Reduction in Taylor Series in Analytical Physics Problem

This research is motivated by the low ability of students to apply mathematical solving methods to analytic physics. The purpose of this research is to show the implementation of small term reduction in Taylor series on analytic physics problems. The analytical physics material described in this study is the pendulum oscillation material, heat conduction and the perturbation quantum state function. This research method involves a mathematical derivation of the Taylor series formation. The epicenter of the idea of reducing the Taylor series in this study is the use of very small terms in the Taylor series to reduce terms with values reaching towards zero, namely the third term and the fourth term. This small term reduction method is spread into problems of mechanics, oscillations, heat, electricity, magnetism and quantum mechanics. The results of this study show that after using the small term reduction principle, the equations to be solved are like first-order and second-order differential equations. By solving these equations we get a variable physical quantity.

Phytochemical, proximate analysis and antioxidant activity of the rhizome of Alpinia nigra (Gaertn.) B.L. Burtt (Zingiberaceae) in Tamulpur district, Assam

The present research examines the chemical composition, proximate characteristics and antioxidant analysis of Alpinia nigra’s rhizome extract. Results of GC-MS analysis revealed a total of 22 volatile compounds of which Tris (tert-butyldimethylsilyloxy) arsane (2.89 %), 2-ethylthiolane, S, S-dioxide (3.47 %), Ambrial (6.68 %) and Silicic acid, diethyl bis (trimethylsilyl) ester (4.59 %) were the major compounds. The rhizome was found to have variable quantities of proximate compositions such as moisture content (55.5 %), ash content (4.72 %), crude fat (52 %), crude fibre (41.25 %), crude protein (28.95 µg/g), carbohydrate (46.27 %) and dry matter (33.4 %). The crude extraction of the rhizome was done by Soxhlet apparatus. The phytochemical screening showed the presence of alkaloid, tannin, terpenoid, glycoside, steroid, carbohydrate and a considerable amount of phenol and flavonoid. Phenolic and flavonoid content in the extracts was determined by the Folin-Ciocalteu and aluminium chloride assays as gallic acid equivalent and quercetin equivalent respectively. To evaluate the antioxidant activity of rhizome extract, phosphomolybdenum assay, ferric-reducing antioxidant power (FRAP) and 1,1-diphenyl-2-picryl-hydrazil (DPPH) were used. The findings indicate that the rhizome extract is rich in phenol and flavonoid content and would serve as a promising source of natural antioxidants in the food, cosmetics and pharmaceutical industries.

A reconfigurable wireless power transfer system with constant exciting current for charging multiple batteries

At present, wireless power transfer (WPT) systems with constant current (CC) or constant voltage (CV) characteristics are typically achieved using a single transmitter and single pickup (STSP) configuration, which cannot transfer power to multiple battery loads simultaneously. In this paper, the LCC-LCC/S reconfigurable topology is proposed to realize the CC-to-CV transition for multiple battery loads. An LCC topology is designed on the primary side to achieve a constant current (0.362A) flowing through the transmitting coil to enable independent operation of power pickups. A reconfigurable LCC/S topology is designed on the secondary side to achieve the CC-to-CV transition of the battery loads. The received power from the pickups remains unaffected when pickups are moved in or out or are in different operating modes (CC or CV). The circuit can maintain zero phase angle (ZPA) operation, which greatly enhances the overall power density of the system. Additionally, detailed design process for the compensation parameters on both the primary and secondary sides are provided. Theoretical analysis proves that good system stability and robustness can be obtained in the case of variable quantity of pickups and quality factors of coils. The experimental prototype was built, with the CC value for the battery load designed at 0.7A and the CV value designed at 8 V. Experimental results demonstrate the smooth CC-to-CV transition of the proposed WPT system (with 3 pickups) at a power output of 15.4 W, and the system’s maximum efficiency can reach 75.5 %.

Compact fusion blanket using plasma facing liquid Li-LiH walls and Pb pebbles

Liquid plasma facing walls allow for increased neutron-wall loading expanding the design space of fusion power-plants and experimental devices towards compact high-field reactors. This study presents the design of a compact radial build blanket for fusion devices composed of variable quantities of Lead (Pb) and Lithium-Lithium Hydride (Li-LiH). A tank-like cylindrical neutronic model of the early design of the stellarator reactor proposed by Renaissance Fusion is implemented in OpenMC (neutron transport and dose rate analyses). The reactor's radial build composition and blanket layer thicknesses are varied to fulfill the requirements on tritium breeding ratio (TBR), nuclear heat extraction, radiation shielding (for the coils, internal structures and external environment) for a stellarator-based power-plant. The analyses suggest that a radial build lower than a meter thick between the plasma and coils would be sufficient to allow for a TBR ∼ 1.60, an energy multiplication factor of ∼ 1.07, to capture ≥ 90% of the nuclear heat, limit the neutron fluence at the coils below 1019 n/cm2, and limit the structural damage on the liquid metal vessel and magnet structure. In particular, a blanket composed of 32 cm of Pb and Li-LiH, 54 cm of a heavy metal hydride such as vanadium hydride (VH2), along with a 1.3 m of concrete bioshield, would minimize the radial build of the stellarator reactor while fulfilling tritium breeding, shielding and heat extraction requirements.

Visualization of Keratopathy Associated With the Antibody-Drug Conjugate Belantamab Mafodotin Using Infrared Imaging in Patients With Multiple Myeloma.

The treatment of patients with relapsed/refractory multiple myeloma (RRMM) with the antibody-drug conjugate belantamab mafodotin is affected by ocular adverse effects, most frequently keratopathy with corneal microcyst-like epithelial changes (MECs). To assess ocular side effects, the "Keratopathy and Visual Acuity (KVA) scale," based on the extent of keratopathy subjectively graded on slit-lamp examination and the change in best corrected visual acuity from baseline, was created. Advanced corneal imaging techniques have been explored to further characterize MECs and identify objective imaging biomarkers. We examined whether infrared reflectance imaging of the anterior segment (AS-IR) could contribute to the assessment, monitoring, and documentation of corneal toxicity in patients treated with belantamab mafodotin. In addition to the KVA examination, AS-IR imaging was performed. AS-IR images were evaluated for presence of visible hyporeflective lesions and their spatial and temporal distribution between visits and compared with keratopathy identified on slit-lamp examination. To standardize the assessment, a scoring system for lesions on AS-IR was implemented for additional analysis. Nine patients undergoing treatment with belantamab mafodotin for up to 9 months were examined. All patients exhibited hyporeflective lesions on AS-IR imaging, indicative of corneal toxicity corresponding to MECs observed on slit-lamp examination. AS-IR lesions showed early occurrence, variable quantity and size, and distinct distribution patterns, correlating with clinical findings during treatment. As shown for belantamab mafodotin, AS-IR imaging represents a fast, noninvasive, supplemental method for documentation, monitoring, and assessment of corneal adverse effects during treatment with antibody-drug conjugates, which may enable more standardized analyses.