S-shaped Research Articles

Review of the Simulators Used in Pharmacology Education and Statistical Models When Creating the Simulators

Animal experiments have long been used as an educational tool in pharmacological education; however, from the perspective of animal welfare, it is necessary to decrease the number of animals used. ingAlthough using of simulators is effective, the development of these simulators is necessary when there is no existing simulator for animal experiments. In this review, we describe free, downloadable, and commercial simulators that are currently used in pharmacological education. Furthermore, we introduce two strategies to create simulators of animal experiments: (1) bioassay, and (2) experiments that measure the reaction time. We also describe five sigmoid curves (logistic curve, cumulative distribution function [CDF] of normal distribution, Gompertz curve, von Bertalanffy curve, and CDF of Weibull curve) to fit the results and their inverse functions. Using this strategy, it is possible to create a simulator that calculates the reaction time following drug administration. Moreover, we introduce a statistical model for local anesthetic agents using hierarchical Bayesian modeling. Considering the correlation among estimated parameters, we suggest it is possible to create simulators that give results more similar to those of animal experiments. The pharmacological education will be possible by these simulators at educational institutions where animal experiments are difficult due to various restrictions. It is expected that the number of simulator-based education programs will increase in the future.

Determination of Equilibrium Loading by Empirical Models for the Modeling of Breakthrough Curves in a Fixed-Bed Column: From Experience to Practice

Empirical models have been found to be inadequate in both accounting for breakthrough behaviors and reflecting the performance of fixed-bed systems, primarily due to their lack of a robust theoretical foundation. This limitation severely restricts their practical application. To address this difficulty, the adjustable parameters of six empirical models were first determined using the Levenberg–Marquardt iteration algorithm. The fitting quality of these models was subsequently evaluated by several error statistics, including the reduced chi-square (χ2), adjusted coefficient of determination (Adj. R2), residual sum of squares (RSS) and root of mean squared error (RMSE). In addition, the Akaike information criterion (AIC) and Bayesian information criterion (BIC) were employed to further compare these empirical models with the different parameters. The equilibrium loading, breakthrough capacity and saturation capacity were then solved by the int command of MATLAB 2023b software. Meanwhile, the breakthrough time and saturation time were determined by its fzero command. Regardless of whether empirical or mechanistic models were used, the model with the asymmetric S-shaped curve could well describe the measured breakthrough curves. Based on the parallel sigmoidal model, the predicted equilibrium loadings were 101.11, 116.69 and 129.50 mg g−1, respectively, at adsorbent masses of 0.1, 0.3 and 0.5 g. This study aimed to conveniently obtain the critical process parameters through MATLAB software using empirical breakthrough models, thereby providing reliable information for the design and optimization of fixed-bed adsorbers.

Differentiating the contributions of Na+/K+ pump current and persistent Na+ current in simulated voltage-clamp experiments.

The persistent Na+ current (INaP) is thought to play important roles in many brain regions including the generation of inspiration in the ventral respiratory column (VRC) of mammals. The characterization of the slow inactivation of INaP requires long-lasting voltage steps (>1 s), which will increase intracellular Na+ and activate the Na+/K+-ATPase pump current (IPump). Thus, IPump may contribute to the previously measured slow inactivation of INaP and the generation of the inspiratory bursting rhythm. To test this hypothesis, we computationally modeled a respiratory pacemaker neuron that included a non-inactivating INaP and IPump in addition to other basic spike-generating currents. This model produces an inspiration-like bursting rhythm, in which the dynamics of [Na+]i account for burst initiation and termination. We simulated a voltage-clamp experiment measuring the INaP inactivation kinetics using our model of non-inactivating INaP and IPump. Consistent with prior measurements in the VRC, we found a sigmoidal inactivation curve and a current that only partially inactivated reaching a minimum inactivation of 0.39. The biexponential time course of inactivation had decay rate constants of 0.59 s and 3.71 s with contributions of 57% and 43% respectively. The time constant of inactivation was 2.67 s. This decay was caused by the slow growth of IPump and the slow hyperpolarization of the Na+ reversal potential in response to the growing [Na+]i. We conclude that important biophysical properties previously attributed to the INaP may be caused by IPump. This has important implications for understanding respiratory rhythmogenesis and other neuronal functions.

Radiative impact of the Hunga stratospheric volcanic plume: role of aerosols and water vapor over Réunion Island (21° S, 55° E)

Abstract. This study attempts to quantify the radiative impact over Réunion Island (21° S, 55° E) in the southern tropical Indian Ocean of the aerosols and water vapor (WV) injected into the stratosphere by the eruption of the Hunga underwater volcano in the South Pacific on 15 January 2022 . Ground-based lidar and satellite passive instruments are used to parameterize a state-of-the-art radiative transfer (RT) model for the first 13 months after the volcano eruption. The descending rate of the aerosol volcanic plume is −8 m d−1. At this rate, aerosols are expected to be present in the stratosphere until the first half of 2025. The overall aerosol and water vapor impact on the Earth's radiation budget for the whole period is negative (cooling, −0.82 ± 0.35 W m−2) and dominated by the aerosol impact (∼ 95 %; the remaining ∼ 5 % is due to the water vapor). At the Earth's surface, aerosols are the main drivers and produce a negative (cooling, −1.04 ± 0.36 W m−2) radiative impact. Water vapor has hardly any radiative effect at the surface. Between the short-term (months 2 to 4 after the eruption, February–April 2022) and mid-term (months 5 to 14 after the eruption, May 2022–February 2023) periods, the aerosol and water vapor radiative effect at the surface and top of atmosphere (TOA) reduces by 22 % and 25 %, respectively. During the mid-term period, heating / cooling (H / C) rate profiles show a clear vertical difference locally in the stratosphere between the aerosol warming impact (18 to 26 km) and the water vapor cooling (22 to 30 km). The resulting aerosol and water vapor heating / cooling rate profile follows an S-shaped curve with peaks slightly larger for the moist layer (−0.09 K d−1) than for the sulfate layer (+0.06 K d−1).

The molar dose of FAPI administered impacts on the FAP-targeted PET imaging and therapy in mouse syngeneic tumor models.

Since fibroblast activation protein (FAP), one predominant biomarker of cancer associated fibroblasts (CAFs), is highly expressed in the tumor stroma of various epidermal-derived cancers, targeting FAP for tumor diagnosis and treatment has shown substantial potentials in both preclinical and clinical studies. However, in preclinical settings, tumor-bearing mice exhibit relatively low absolute FAP expression levels, leading to challenges in acquiring high-quality PET images using radiolabeled FAP ligands (FAPIs) with low molar activity, because of which a saturation effect in imaging is prone to happen. Moreover, how exactly the molar dose of FAPI administered to a mouse influences the targeted PET imaging and radiotherapy remains unclear now. Therefore, this study aims to investigate the impacts of the molar dose of the administered FAPI on FAP-targeted PET imaging and radiotherapy in mouse syngeneic tumor models. [68Ga]Ga-FAPI-04 with various molar doses of FAPI-04 was administered to wild-type 4T1 tumor-bearing mice, followed by static PET imaging. Sigmoidal curves were generated to analyze the correlation between the standard uptake value (SUV) and the administered molar doses of FAPI-04. Similarly, [177Lu]Lu-DOTAGA.(SA.FAPi)2 with a consistent dose of radioactivity but containing different moles of DOTAGA.(SA.FAPi)2 were injected into 4T1 tumor-bearing mice to assess the therapeutic effect. [68Ga]Ga-FAPI-04 was also applied to different tumor models for PET/CT imaging. A gradient blocking effect was observed with increasing FAPI molar dose in [68Ga]Ga-FAPI-04 PET imaging and [177Lu]Lu-DOTAGA.(SA.FAPi)2 treatment, with various imaging and therapeutic outcomes. [68Ga]Ga-FAPI-04 PET exhibit potentials to characterize murine derived FAP expression with low molar dose of administered FAPI-04 using various tumor models. The molar dose of FAPI in [68Ga]Ga/[177Lu]Lu-FAPI had a substantial impact on FAP-targeted imaging and therapy in mouse syngeneic tumor models. To acquire enhanced reliability and reproducibility in preclinical situation, it is critical to carefully consider the molar dose of the radiotracer when applying radiolabeled FAP ligands to FAP-targeted imaging and radiotherapy.

Progressive structural changes of microbial transglutaminase modified fish gelatin during gastric digestion.

This study investigated the progressive structural changes of fish gelatin in thermally reversible (TR) and irreversible (TI) states, formed through microbial transglutaminase (MTGase) cross-linking during in vitro gastric digestion. The focus was on dynamic structural changes and gastric digestion characteristics. Free amino content and SDS-PAGE analyses showed that both TR and TI groups were hydrolyzed into smaller fragments by pepsin during digestion. Surface hydrophobicity and endogenous fluorescence analyses revealed that hydrophobic groups in TR samples became embedded, whereas those in TI samples were exposed as digestion progressed. The microstructure of fish gelatin varied states and changed over digestion time. Two digestion patterns were observed: the fitted curves of TR groups exhibited initially increasing that later stabilized, whereas the TI samples followed an S-shaped curve with three distinct stages-an initial stable phase, followed by a rise, and concluding with a final stabilization. A schematic model illustrated the dynamic structural changes of fish gelatin in different states during simulated gastric digestion. This study provides a basis for the development of high-quality collagen supplement products.

Incidence rate of total knee arthroplasties in eleven European countries: Do they reach a plateau?

From several decades, the evolutions of the Incidence Rate (IR) of Primary Knee Arthroplasties are continuously increasing worldwide and have been widely studied in several countries. Some recent works have highlighted the fact that the IR is following a sigmoid curve composed of an exponential growth followed by a linear phase and finished by a plateau. Our objective is to assess the IR evolution of eleven European countries, representing thus a large proportion of this continent, regarding this sigmoid. IRs of primary knee arthroplasties for Austria, Denmark, Finland, France, Germany, Hungary, Italy, Poland, Spain, Sweden, and the United Kingdom between 2005 and 2019 were retrieved from the EUROSTAT database. Several regression models were fitted to each country's IRs: Poisson, linear, asymptotic, logistic, and Gompertz regression. For each country and each model, the RMSE (Root Mean Square Error) and R2 were calculated and used to estimate their position with respect to this sigmoid curve. The best regression models for knee arthroplasties varied following countries. Logistic and Gompertz regressions had the lowest RMSE and R2 values for Austria, Denmark, Germany, Sweden, and the UK. Hungary, Italy, and Poland favored the Poisson regression model. Finland and Spain presented difficulties in determining the optimal model (linear or Poisson), while France faced challenges in choosing between logistic, Gompertz, and linear regression. In conclusion, the growth dynamics of IR differ across European countries. Some countries seem to have already reached a plateau and will therefore experience slight growth in the future.

Study on the dust production characteristics of coal cutting at different drilling speeds of cutting head

In order to address the unclear mechanism of dust generation during coal cutting by picks at the current driving face, experiments on dust generation at different drilling speeds were conducted using a self-built experimental apparatus for coal cutting dust. Numerical simulations were also employed to further analyze the dust generation mechanism during coal cutting by cutter picks. The research findings indicate that as the drilling speed increases, the dust generation initially increases and then stabilizes. The peak values of total dust and potentially respirable dust generation rates were observed at a drilling speed of 200mm/min, reaching 204.21g/t and 29.73g/t, respectively. The particle size distribution of dust generated from the cutting of the same coal followed a similar trend. The coal fragmentation by cutter picks is a result of the combined action of tensile and shear forces. The growth of crack quantity follows an S-shaped curve, characterized by slow growth, rapid growth, and stabilization. With an increase in cutting depth, both the force and torque on the cutting head exhibited a continuous increase followed by stable fluctuations. The energy consumption during the cutting process mainly involves overcoming the coal's strain energy, and the trend of energy dissipation initially increases and then decreases. These research findings provide a theoretical basis for further understanding the mechanism of coal cutting dust generation by cutter picks and achieving efficient control of dust emissions at the source.

SEED VIABILITY AND GROWTH OF CACAO PLANT (Theobroma cacao L.) SEEDLINGS SULAWESI 01 AND ICCRI 08 CLONES

Cocoa is one of the important agricultural commodities for various industrial activities such as cosmetics and food. Cocoa is widely consumed by the community, both in the form of instant chocolate and cocoa powder. Cocoa productivity is under its potential productivity, and have to enhance the cocoa production. The selection of clones for cocoa planting materials could determines the results of the plant. Plants convey genetic traits that can determine production capacity. Seedling viability and growth are indicators to determine whether plants can grow adeptly. Cocoa clones Sulawesi 01 and ICCRI 08 are superior clones that have the advantage of high productivity and are resistant to pests and diseases. The purpose of the study was to determine the viability of seeds and the growth of two cocoa clones Sulawesi 01 and ICCRI 08. The study design was a Completely Randomized Design with 2 levels and each had replications. The results of this study showed that the ICCRI 08 clone had the highest germinability of 92.1% and further the seedling growth parameters with a height of 6.6 cm at 21 days after planting. The highest vigor index measurement of 426.4 was in the ICCRI 08 clone and was significantly different compared to the Sulawesi 01 clone. The sigmoid curve showed the presence of growth initiation and exponential phases as indicated by increased growth as the plant age increased.

Effect of Drug-to-Protein Reaction Kinetics on the Results of Thermal Proteome Profiling.

In this Letter, a two-term formalism for constructing protein solubility curves in thermal proteome profiling (TPP) is considered, which takes into account the efficiency of the drug-protein binding reaction. When the reaction is incomplete, this results in distortion of the otherwise sigmoidal shape of the curve after drug treatment, which is often observed in experiments. This distortion may be significant enough to disqualify the corresponding protein from the list of drug target candidates, thus negatively affecting the results of TPP data analysis. To further assist this analysis, we also developed the solubility curve simulation software to visualize the discussed effect. Several experimental data sets from recent TPP studies have been reprocessed, and we demonstrate in a few examples that the proposed two-term equation fits correctly the observed protein solubility curves with distorted shapes, also highlighting the previously unrecognized targets.

Micellar Choline-Acetyltransferase Complexes Exhibit Ultra-Boosted Catalytic Rate for Acetylcholine Synthesis-Mechanistic Insights for Development of Acetylcholine-Enhancing Micellar Nanotherapeutics.

Choline-acetyltransferase (ChAT) is the key cholinergic enzyme responsible for the biosynthesis of acetylcholine (ACh), a crucial signaling molecule with both canonical neurotransmitter function and auto- and paracrine signaling activity in non-neuronal cells, such as lymphocytes and astroglia. Cholinergic dysfunction is linked to both neurodegenerative and inflammatory diseases. In this study, we investigated a serendipitous observation, namely that the catalytic rate of human recombinant ChAT (rhChAT) protein greatly differed in buffered solution in the presence and absence of Triton X-100 (TX100). At a single concentration of 0.05% (v/v), TX100 boosted the specific activity of rhChAT by 4-fold. Dose-response analysis within a TX100 concentration range of 0.8% to 0.008% (accounting for 13.7 mM to 0.013 mM) resulted in an S-shaped response curve, indicative of an over 10-fold boost in the catalytic rate of rhChAT. This dramatic boost was unlikely due to a mere structural stabilization since it remained even after the addition of 1.0 mg/mL gelatin to the ChAT solution as a protein stabilizer. Furthermore, we found that the catalytic function of the ACh-degrading enzyme, AChE, was unaffected by TX100, underscoring the specificity of the effect for ChAT. Examination of the dose-response curve in relation to the critical micelle concentration (CMC) of TX100 revealed that a boost in ChAT activity occurred when the TX100 concentration passed its CMC, indicating that formation of micelle-ChAT complexes was crucial. We challenged this hypothesis by repeating the experiment on Tween 20 (TW20), another non-ionic surfactant with ~3-fold lower CMC compared to TX100 (0.06 vs. 0.2 mM). The analysis confirmed that micelle formation is crucial for ultra-boosting the activity of ChAT. In silico molecular dynamic simulation supported the notion of ChAT-micelle complex formation. We hypothesize that TX100 or TW20 micelles, by mimicking cell-membrane microenvironments, facilitate ChAT in accessing its full catalytic potential by fine-tuning its structural stabilization and/or enhancing its substrate accessibility. These insights are expected to facilitate research toward the development of new cholinergic-enhancing therapeutics through the formulation of micelle-embedded ChAT nanoparticles.

Multiagent DDOS attack detection model: Optimal trained hybrid classifier and entropy-based mitigation process

ABSTRACT This study proposes a novel multi-agent system designed to detect Distributed Denial of Service (DDoS) attacks, addressing the increasing need for robust cybersecurity measures. The hypothesis posits that a structured multi-agent approach can enhance detection accuracy and response efficiency in DDoS attack scenarios. The methodology involves a five-stage detection model: (1) Preprocessing using a modified double sigmoid normalization technique to eliminate duplicate data; (2) Feature Extraction where raw data and improved correlation-based features, mutual information, and statistical features are identified; (3) Dimensionality Reduction conducted by a reducer agent to streamline the feature set; (4) Classification utilizing Deep Belief Networks (DBN), Bi-LSTM, and Deep Maxout models, with their weights optimally tuned using the hybrid optimization algorithm, WUJSO; and (5) Decision Making by the decision agent to ascertain the presence of attacks, followed by mitigation through modified entropy-based techniques. The results demonstrate that the proposed method achieves a detection accuracy of 0.953 at a learning rate of 90%, significantly outperforming other methods, including Bi-GRU (0.857), DEEP-MAXOUT (0.910), Bi-LSTM (0.865), RNN (0.814), NN (0.894), and DBN (0.761). This research underscores the effectiveness of the multi-agent approach in enhancing DDoS attack detection and mitigation.

Conceptual Framework for Gigajoule-Scale Deuterium-Tritium Fusion Yield from an End-Sourced, High-Current, Snowplow-Driven, Shear Flow–Stabilized Nanosecond Timescale Z-pinch

A conceptual framework, supported and illustrated by computational modeling, is reported for a high-current snowplow discharge mode in coaxial electrodes consisting of a conical inductive storage section and a center conductor extension tapered in radius with a sigmoid curve from a 4-cm-radius to a 3-mm-radius stem. The inductive storage section can be loaded with Bθ flux by a relatively low-power snowplow discharge. In the sigmoid-tapered extension, the flux is shown to flow along the taper, increasing both field strength and flow velocity as it accelerates to a smaller radius, resulting in a petawatt flow of Bθ flux along the 3-mm-radius center conductor stem at 40 MA and 200 cm/µs. Next, we present calculations of pinching a 0.8-cm-long pure deuterium-tritium (DT) target located as if in the stem. The pinch, formed when the petawatt flow passes over the target, was calculated to produce over half a gigajoule of DT fusion yield. Additionally, a half-scale 20-MA calculation was performed, and an approximate yield scaling formula was found with a dependence on the drive current to the fourth power.

Overwintering at multiple life stages in Schizotetranychus shii (Acari: Tetranychidae), a specialist of evergreen chinquapin.

Spider mites (Acari: Tetranychidae) overwinter as eggs or adult females, but some do so as multiple life stages on evergreen hosts. However, proximate factors influencing such overwintering stages remain poorly understood. This study investigated photoperiodic responses and life-stage compositions during winter in a population of Schizotetranychus shii, a specialist of Japanese chinquapin (Fagaceae). The proportion of non-ovipositing females at 20°C followed a sigmoid curve with increasing photoperiod. The critical day length was estimated as a photoperiod of 11.8h light and 12.2h dark (11.8L), which was similar to the natural photoperiod from late September to early October. Although females grown under 10L and 11L conditions never oviposited within 7days, 90-96% of them started oviposition within 30days without chilling, indicating shallow reproductive diapause. In the field, all life stages occurred throughout winter, but their proportions varied considerably. The proportion of eggs declined from early October (62%) to early December (12%), as predicted by the critical day length, but steeply increased toward late February (96%), in which only adult females and eggs remained. These findings suggest that short-day conditions in the field do not maintain adult diapause as predicted by the above experiment. In summary, a short photoperiod in October or November arrests oviposition in emerging females, but they commence oviposition during the short-day season when immature stages are still growing. As a result, individuals at all life stages coexist until all immature stages mature in February.

Reference Scenarios for Policies to Minimize the Generation and Recycling of Municipal Solid Waste

This article aims to design and propose time-evolution scenarios to support the implementation of policy instruments that promote recycling and minimize MSW generation. Two reference scenarios, Audacious and Realistic, are presented, drawing on international and Brazilian references and represented by S-shaped curves and your inflection points. For each scenario, instruments and guidelines are proposed and classified by experts for their applicability to Brazilian municipalities of various population groups. Findings highlight educational and economic instruments as primary drivers of recycling and waste reduction, yielding significant decreases in per capita generation (47%) and recycling rates (24% recyclables and 20% organics). The survey with experts confirms that these strategies are broadly applicable across different population groups. The proposed scenarios contribute to the policy instruments implementation to reduce MSW generation and promote recycling, enabling decision-makers to select effective strategies for MSW management plans and supporting future studies in evaluating policy impacts through mathematical modeling.

A cultural evolution theory for contemporary polarization trends in moral opinions

While existing theories of political polarization tend to suggest that the opinions of liberals and conservatives move in opposite directions, available data indicate that opinions on a wide range of moral issues move in the liberal direction among both liberals and conservatives. Moreover, some political scientists have hypothesized that this movement follows an S-shaped curve among liberals and a similar, but later, S-shaped curve among conservatives, so that polarization on a given issue first increases (as opinions at an initial stage move faster among liberals) and then decreases (as opinions at a later stage move faster among conservatives). Here we show that these dynamics are explained by Moral Argument Theory, a cultural evolution theory positing that opinion shifts on moral issues arise from a certain content bias in social opinion transmission. This theory also yields several other specific predictions about trends and polarization in moral opinions, which we test against longitudinal data on 55 moral issues from the General Social Survey (sample sizes between 1798 and 57,809 per issue). The predictions are generally confirmed. We conclude that a cultural evolution perspective can provide valuable insights for social science in understanding contemporary societal changes.

Preictal period optimization for deep learning-based epileptic seizure prediction

Objective. Accurate seizure prediction could prove critical for improving patient safety and quality of life in drug-resistant epilepsy. While deep learning-based approaches have shown promising performance using scalp electroencephalogram (EEG) signals, the incomplete understanding and variability of the preictal state imposes challenges in identifying the optimal preictal period (OPP) for labeling the EEG segments. This study introduces novel measures to capture model behavior under different preictal definitions and proposes a data-centric deep learning methodology to identify the OPP.Approach. We trained a competent subject-specific CNN-Transformer model to detect preictal EEG segments using the open-access CHB-MIT dataset. To capture the temporal dynamics of the model's predictions, we fitted a sigmoidal curve to the model outputs obtained from uninterrupted multi-hour EEG recordings prior to seizure onset. From this fitted curve, we derived key performance measures reflecting the timing of predictions, including classifier convergence, average error, output stability, and the transition between interictal and preictal states. These measures were then combined to compute the Continuous Input-Output Performance Ratio, a novel metric designed to comprehensively compare model behavior across different preictal definitions (60, 45, 30, and 15 min) and suggest the OPP for each patient.Main results.The CNN-Transformer model achieved state-of-the-art performance (area under the curve of 99.35% andF1-score of 97.46%) using minimally pre-processed EEG signals. The 60-minute preictal definition was associated with earlier seizure prediction, lower error in the preictal state, and reduced output fluctuations, leading to significantly higher CIOPR scores (p< 0.001). Conventional accuracy-related metrics (sensitivity, specificity, F1-score) were less sensitive to varying preictal definitions and often discordant with CIOPR findings. Cross- and intra-patient heterogeneities in the prediction times were also observed, complicating the establishment of a global preictal interval.Significance. The newly developed metrics demonstrate that varying the preictal period significantly impacts the timing of predictions in ways not captured by conventional accuracy-related metrics. Understanding this impact and the inter-seizure heterogeneities is essential for developing intelligent systems tailored to individual patient needs and for underlining practical limitations in detecting the preictal period in real-world clinical applications.

Comparing the market history of mobile phones and electric cars by using sigmoid curves

The time curves of market history for mobile phones and for electric cars is compared by sigmoid curves. Creating the approximate sigmoid curves of the curves showing the real data of products sold in function of the time, it is possible to find similarities and differences of the time history of the market of mobile phones and electric cars. One of the most important decisions during this investigation is to decide, which curve describes better the product investigated: Logistic curve (Pearl-Reed curve) or Growth curve (Bertalanffy)? On the basis of many characteristics of these curves, in the second step of the study it is possible to characterise the market of the products, and the comparison can give important points of view for the understanding the present situation of the markets and to try to forecast their possible future.

Magnetic Structure of Ba2CaCo2Si6O17 with Zigzag Spin Chains of Co2+ in High Spin‐3/2 State

The magnetic properties and crystal chemistry of the novel Ba2CaCo2Si6O17 compound exhibiting one‐dimensional zigzag chains of Co2+ ions (S = 3/2) are investigated using powder X‐ray diffraction (PXRD), scanning lectron microscopy, energy dispersive‐Xray spectroscopy, and temperature and field‐dependent magnetic measurements. The refinement of PXRD data suggests a Cmcm space group in orthorhombic symmetry for Ba2CaCo2Si6O17 compound, consisting of a CoO4 tetrahedral network including 1‐D zigzag Co2+ chains. Microstructural and elemental analysis substantiate the proper stoichiometry of the synthesized material. Magnetic measurements show paramagnetic characteristics at room temperature, followed by a transition from paramagnetic to antiferromagnetic (AFM) ordering near 17 K, superimposed with weak ferromagnetic ordering (WFM) characteristics. Magnetic hysteresis (M–H) at 5 K depicts a sigmoid curve with unsaturated magnetization even at high fields. The negative Weiss temperature value ≈−98 K substantiates the strong antiferromagnetic exchange interaction with a frustration index of ≈5.76. The effective paramagnetic moment is 3.34μB, close to the spin‐only value 3.87μB of Co2+ (S = 3/2). The competing and short‐range FM‐AFM interaction is observed because of the zigzag Co2+ chain in the compound. The onset of WFM is attributed to the zigzag magnetic chain‐induced lattice and spin distortion in Ba2CaCo2Si6O17 compound.

Low-dose lung CT: Optimizing diagnostic radiation dose – A phantom study

Background/purposeTo investigate a quantitative method for assessing image quality of low dose lung computed tomography (CT) and find the lowest exposure dose providing diagnostic images. MethodsAxial volumetric lung CT acquisitions (256 slice scanner) were performed on three different sized anthropomorphic phantoms at different dose levels. The maximum steepness of sigmoid curves fitted to line density profiles was measured at lung-to-pleura interfaces. For each phantom, image sharpness was calculated as the median of 468 measurements from 39 different locations. Diagnostic image quality for the adult and paediatric phantom was rated by three radiologists using 4-point Likert scales. The image sharpness cut-off for obtaining adequate image quality was determined from qualitative ratings. ResultsAdequate diagnostic image quality was reached at a median steepness of 713 HU/mm in the adult phantom with a corresponding CTDIvol of 0.14 mGy and an effective dose of 0.13 mSv at a dose level of 100 kVp and 10 mA. In the paediatric phantom diagnostic image quality was reached at a median steepness of 1139 HU/mm with a corresponding CTDIvol of 0.13 mGy and an effective dose of 0.08 mSv at a dose level of 100 kVp and 10 mA. ConclusionsDetermination of image sharpness on line density profiles can be used as quantitative measure for image quality of lung CT. Sufficient-quality lung CT can be achieved at effective radiation doses of 0.13 mSv (adult phantom) and 0.08 mSv (paediatric phantom). These findings suggest that substantial dose reduction is feasible without compromising diagnostic accuracy.