Quantitative determination of the critical size of inclined coal pillar in old goaf water affected area is of great significance for water damage prevention and safe mining. The critical size of inclined waterproof coal pillar is derived by using theoretical analysis, numerical calculation and field engineering practice for the stability of the waterproof coal pillar in old goaf water affected area of 1303 working face of Dananhu I mine in Xinjiang region. Firstly, a force model of inclined waterproof coal pillar was established to reveal the law that the critical size of the coal pillar increases with the increase of coal seam inclination under the action of asymmetric load. Then, numerical simulation was applied to reveal the dynamic evolution process of plastic deformation-destabilization-destruction of section coal pillar under the influence of mining and single-side water pressure, and the critical size of waterproof coal pillar in study area was determined to be 19.09m. Finally, measures such as pumping and pressure relief and slurry reinforcement were adopted to reduce the deformation rate of the roadway on side of waterproof coal pillar, which ensured the stability of the coal pillar and roadway and the safe recovery of the working face.

To assess the impact of a deep learning (DL) denoising reconstruction algorithm applied to identical patient scans acquired with two different voxel dimensions, representing distinct spatial resolutions. This IRB approved prospective study was conducted at a tertiary pediatric center in compliance with the Health Insurance Portability and Accountability Act. We used a General Electric Signa Premier unit (GE Medical Systems, Milwaukee, WI) to acquire two DTI sequences of the left knee on each child at 3T: an in-plane 2.0 x 2.0 mm2 with section thickness of 3.0 mm and a 2 mm3 isovolumetric voxel, neither had an inter-section gap. We used a multi-band DTI acquisi-tion with fat-suppressed single-shot spin-echo echo-planar sequence (20 non-collinear directions; b-values of 0 and 600 sec/mm2). The MR vendor-provided a commercially available DL model applied with 75% noise reduction settings to same subject DTI sequences at different spatial res-olutions. We compared DTI tract metrics from both DL-reconstructed scans and non-denoised scans for femur and tibia, at each spatial resolution. Differences were evaluated using Wilcox-on-signed ranked test and Bland-Altman plots. When comparing DL versus non-denoised diffu-sion metrics in femur and tibia using the 2 mm x 2mm x 3 mm voxel dimension there were no significant differences between tract count (p = 0.1, p =0.14) tract volume (p = 0.14, p = 0.29), or tibial tract length (p=0.16); femur tract length exhibited a significant difference (p

Background: Nowadays, the prevalence of digital device usage has shifted the demands for multifocal intraocular lenses. To accurately capture outcomes, clinical practice must evaluate digital reading performance. We aimed to assess the digital reading performance using a digital device in patients with diffractive multifocal intraocular lenses. Methods: Patients with bilateral diffractive multifocal intraocular lens implantation were included in the study. Monocular and binocular uncorrected and corrected visual acuity was measured using the LogMAR chart and the MNREAD application. Binocular uncorrected defocus curves were obtained using the LogMAR chart at 4m. The reading acuity was measured using the MNREAD application with positive and negative display polarities. The mean digital critical print size (CPS) was recorded using the MNREAD application at 40cm. Results: Our study reported uncorrected distance, intermediate, and near visual acuity were -0.084 ± 0.079, -0.014 ± 0.078, and 0.040 ± 0.081, respectively. The mean reading acuity at three months postoperatively with positive display polarity at 60cm and 40cm was -0.115 ± 0.102 and -0.008 ± 0.083, respectively. The mean digital CPS at three months postoperatively was 0.238 ± 0.100 logMAR. Conclusions: Incorporating digital reading performance measurements provides additional advantages in assessing the effectiveness of bilateral diffractive multifocal intraocular lens implantation.

ABSTRACT: Waterlogging is a common abiotic stress in global maize production. Maize flowering stage (from tasseling to silking) is more fragile to environmental stresses among different growth stages. The effects of waterlogging at flowering stage on the grain yield and starch quality of waxy maize were studied using Suyunuo5 (SYN5) and Yunuo7 (YN7). The grain yield and starch concentration of both hybrids were reduced by waterlogging. The size of starch granules and proportion of small-molecule amylopectin increased in SYN5 and decreased in YN7 when plants suffered waterlogging at flowering, in contrast to the change trend of relative crystallinity. The pasting viscosities and gelatinization temperatures were reduced, whereas the gelatinization enthalpy was unaffected by waterlogging in both hybrids. Our study indicated that waterlogging at flowering reduced the grain yield, restricted starch deposition, and deteriorated the pasting property of waxy maize. Between the two hybrids, YN7 and high pasting viscosities and low retrogradation percentage than SYN5, indicated its advantages on produce starch for viscous and less retrograde food. Results provide information for utilization of waxy maize grain in food production.

Network neuroscience delves into comprehending the intricate arrangement and interactions within the neural networks of the brain. By merging insights from both neuroscience and network theory, it investigates the brain's structure and function through the lens of interconnected nodes (symbolizing brain regions) and edges (symbolizing the connections among these regions) forming a dynamic network. Graph metrics play a pivotal role in neuroscience by providing quantifiable insights into the intricate connectivity patterns within the brain's neural networks. Frequently, nodes are extracted from functional or structural atlases, which can lead to diverse shapes and sizes. Nevertheless, our understanding of how these differing node characteristics and definitions impact the computed graph metrics in neuroimaging data remains limited. This study adopts a data-driven methodology to delineate functional nodes, subsequently examining the influence of their sizes on resultant graph metrics. By employing the Neuromark framework, an entirely automated independent component analysis (ICA) is applied to resting state fMRI data. Through this, functional network connectivity (FNC) matrices are computed—capturing Pearson correlations between component-time courses—while employing a proportional threshold to streamline node connections based on these correlations. Subsequently, various global and local graph metrics are computed, offering insights into network characteristics. Global metrics provide an overarching summary of the network structure, while local measures delve into structural intricacies at the individual component level. Node sizes are computed based on voxel counts surpassing a designated threshold. Next, we calculated the Pearson correlation between the obtained node sizes and the graph metrics, which we term 'node-metric coupling' (NMC). Our findings revealed consistent and noteworthy correlations between the values of graph metrics and the dimensions of brain nodes. To delve deeper into the implications of this correlation, we examined the node-metric coupling within a dataset comprising Alzheimer's disease, mild cognitive impairment, and control subjects. The disparities observed in node-metric coupling among these groups underscore the necessity of accounting for this factor during analysis. The two principal outcomes of this study are as follows: Firstly, the substantial interplay between varying node sizes within a given atlas and the resultant graph metrics; and secondly, the potential utility of node-metric coupling as a viable biomarker for brain disorders. These discoveries hold significant ramifications. While comparing studies employing diverse atlases is already a challenge, our work highlights an additional, critical source of variability: accounting for node sizes. Consequently, the association between intra-atlas node size and graph metric should be thoughtfully acknowledged in future neuroimaging investigations.

Raindrop size distribution (RSD) is an index for reflecting precipitation characteristics. Analyzing the differences of RSD plays an important role in understanding the precipitation microphysical processes and improving quantitative precipitation prediction of radar. In this paper, the RSD data of Dafang (57708) station, Majang (57828) station, and Luodian (57916) station (with an altitude of 1722.7m, 985.0m, and 441.5m, respectively) in Guizhou are analyzed according to the precipitation microphysical characteristics. First,Particles with particle size less than 1mm contributes the highest value to the density of particle number , and decrease with the descending altitude. Second, the GAMMA distribution fit shows a better fit compare to M-P distribution fit, and GAMMA distribution fit increases with the ascending altitude. Third, the mass-weighted average diameter is not sensitive enough to the change of precipitation intensity with correlation coefficients of 54.84%, but there is a obvious relationship between the average volume diameter and the precipitation intensity with correlation coefficients of 69.15%. Then, the precipitation prediction model is established using LSTM neural network after fusing the representative microphysical characteristics of RSD with radar and rain gauge data. The precipitation prediction model is applied to the Dafang (57708) site to predict precipitation for time range of 0-180 minutes, and it is found that for the prediction of convective cloud and stratiform cloud precipitation, the 60-minute prediction results are the most consistent with the actual precipitation, where the correlation coefficients are 92.87% and 92.57%, respectively. Conclusively, the results demonstrate that combining with the RSD base data could improve the reliability of precipitation forecasting.

Nanoparticles are of great importance for various scientific and technological applications, drug discovery, ecology, molecular biology, etc. Size is a basic characteristic of any particle, and dynamic light scattering is beyond competition when measuring particle size in dispersions ranging from nanometers to micrometers. Unfortunately, this method has a serious problem in processing and interpreting experimental data. Instrument noise and polydispersity of the sample lead to the situation when one initial autocorrelation function corresponds to several different particle size distributions. Sometimes these different solutions of the inverse task can be found by changing parameters in the software. Sometimes the scientist cannot be suspicious of possible other solutions, having one result from the program. In this article I demonstrate the problem on model and experimental data using three known programs: CONTIN, the Malvern Zetasizer and DynaLS. I also present my own free program Autocor, which allows to test our own hypotheses about the modality and shape of the particle size distribution by optimizing the parameters of our own models with a small number of degrees of freedom.

Repetitive elements are a major component of DNA sequences due to their ability to propagate through the genome. Characterization of Metazoan repetitive profiles is picking up, however, current pipelines are failing to identify a significant proportion of divergent repeats in non-model organisms. The order Decapoda, for which repeat content analyses are largely lacking, is characterized by extremely variable genome sizes that suggest an important presence of repetitive elements. Here we developed a new standardized pipeline to annotate repetitive elements in non-model organisms, which we applied on 20 Decapoda and 6 other crustacean genomes. With our new tool we identify 10% more repetitive elements than standard pipelines. Repetitive elements were more abundant in Decapoda species than in other crustaceans, with an incredibly large number of highly repeated satDNA families. Moreover, we demonstrated a high correlation between assembly size and transposable elements and a different repeat dynamics between Dendrobranchiata and Reptantia. The patterns of repetitive elements largely reflect the phylogenetic relationships of Decapoda and the distinct evolutionary trajectories within Crustacea. In summary, our results highlight the impact of repetitive elements on genome evolution in Decapoda and the value of our novel annotation pipeline, which will provide a baseline for future comparative analyses.

The binding affinity of trastuzumab and pertuzumab to HER2 has been studied using both experimental and in-silico methods. The experiments were conducted using the antibodies in their complete IgG form, as used in clinical therapy, and the extracellular domain of the HER2 protein in solution. This approach provides a precise, reproducible, and reliable view of the interaction between them in physiological conditions. Dynamic light scattering and size exclusion chromatography coupled with tetra detection were utilized to characterize the protein complexes, measure their concentrations, and calculate the equilibrium free binding energy, ΔGbind. In addition, PRODIGY, a QSAR-like model with excellent predictive ability, was employed to obtain in-silico ΔGbind estimations. The results obtained indicate that pertuzumab exhibits a slightly higher binding affinity to HER2 than trastuzumab. The difference in binding affinity was explained based on the contribution of the different interfacial contact (IC) descriptors to the ΔGbind value estimated by the PRODIGY model. Furthermore, experiments revealed that the pertuzumab IgG antibody binds preferentially to two HER2 proteins, one per Fab fragment, while trastuzumab mainly forms a monovalent complex. This finding was interpreted based on a geometrical model that identified steric crowding in the trastuzumab-HER2 complex as compared to the pertuzumab-HER2 complex.

Blast charge initiation procedures have a significant impact on both mining safety and production rates. In this study, the inventory benefit of an electric initiation system was investigated to assess its influence on both fragmentation and blast-induced damages. The Wipfrag software's was used to examine the size distribution and productivity of 12 small-scale blasts initiated by both non-electric and electric detonators. All blast rounds was initiated with plain type of electric and NONEL detonators. The average burden, spacing, stemming length, and charge weight were, respectively, 0.85 m, 1.10 m, 0.66m, and 1.1kg. The results showed that the mesh through which 80% of the blast fragments will pass for the electric blast is smaller than the mesh through which the material products from the NONEL blast will pass. The results also demonstrate that the generated blast-induced ground vibration (PPV) from all blast rounds for electric blast varies from 0.4–1.2 mm/s and 80–105dB, while that for non-electric blast ranges from 0.05–0.2mm/s and 72–95dB. As a result, the electric blast initiation technique was found to produce good fragmentation, with a higher percentage of optimum fragment sizes on spec than non-electrically initiated blasts.

Background and Aims: Metabolic Syndrome (MetS), a global problem, predisposes to an increased risk for Type 2 diabetes and premature cardiovascular disease. While MetS is associated with central obesity, there is scanty data on adipocyte hypertrophy, increased fat cell size (FCS), in MetS. The aim of this study was to investigate FCS status in gluteal adipose tissue biopsy of patients with nascent MetS without the confounding of diabetes, cardiovascular disease, smoking or lipid therapy . Methods and Results: Fasting blood and subcutaneous gluteal adipose tissue (SAT) biopsy were obtained in MetS (n=20) and controls (n=19). Cardio metabolic features, FFA levels, hsCRP and HOMA-IR were significantly increased in patients with MetS. Waist-circumference adjusted-FCS was significantly increased in patients with MetS and increased with increasing severity of MetS. Furthermore, there were significant correlations between FCS with glucose, HDL-C and the ratio of TG: HDL-C. There were significant correlations between FCS and FFA, endotoxin and monocyte TLR4 abundance. Also, FCS correlated with readouts of NLRP3 Inflammasome activity. Most importantly, FCS correlated with markers of fibrosis and angiogenesis. Conclusions: In conclusion, in patients with nascent MetS, we demonstrate WC-adjusted increase in FCS from gluteal AT that correlated with cellular inflammation, fibrosis and angiogenesis. While these preliminary observations were in gluteal fat, future studies are warranted to confirm these findings in visceral and other fat depots.

The results of the study of the influence of the size of cylindrical samples of A5N aluminum on the time and rate of their cooling are presented. According to experimental data, the temperature dependence of the heat transfer coefficient for pure metals is calculated. It revealed that the process of cooling of the aluminium and its alloys has a relaxation behavior. It has found that the main mechanisms of natural air cooling are convection heat transfer and radiation. The characteristic cooling time due to radiation is less than due to convection. The contribution of thermal radiation is noticeable at high temperatures. It was found that the characteristic times of cooling due to radiation and convection increase with increase in volume to area ratio of the sample.

Apple (Malus x domestica) fruit size is dependent on cell division and cell expansion, processes which are subsequently regulated by plant hormones such as auxins, gibberellins, and cytokinins. In this study, we investigated the role of cell division and cell expansion in apple growth and identified which of the two was more deterministic to final fruit size. Three cultivars of different sizes were selected, namely, ‘Twenty Ounce’ (large-sized), ‘Royal Gala’ (medium-sized), and ‘Crabapple’ (small-sized). Gene expression and cell size analyses were conducted over the course of two consecutive seasons. The expression patterns of three classes of genes were markedly similar across all cultivars. Two cell division markers, namely, MdCDKB2;2 and MdANT2, were discovered to be correlatively expressed as both displayed initially high expression levels, which gradually declined from the early to late stages of growth time course. For cell expansion markers, MdEXP3 was upregulated as the cells expanded, while MdARF106 was expressed in both the cell division and expansion stages. Meanwhile, the ripening related gene MdACO1 was expectedly expressed only during the ending stages associated with ripening. Interestingly, the cell measurements taken regularly from each cultivar throughout the same eperimental timespan showed that cell sizes were unaltered and remained constant from initial pollination at the zeroth Days After Pollination (DAP), to ripening at 120 Days After Full Bloom (DAFB).

Microgrids are becoming popular nowadays because they provide clean, efficient, and low-cost energy. To use the stored energy in times of emergency or peak loads, microgrids require bulk storage capacity. Since microgrids are the future of renewable energy, the energy storage technology employed should be optimized to generate electricity. Batteries play a variety of essential roles in daily life and are used at peak hours and during a time of emergency. There are different types of batteries i.e., lion batteries, lead-acid batteries, etc. Optimal battery sizing of microgrids is a challenging problem, that limits modern technologies such as electric vehicles, etc. It is important to know different battery features such as battery life, battery throughput, and battery autonomy to get optimal battery sizing for microgrids. Mixed-integer linear programming (MILP) is an established technique for the integration and optimization of different energy sources and parameters for optimal battery sizing. A new MILP based dataset is introduced in this work. Support vector machine (SVM) is the machine learning application used to estimate the optimum battery size. The impact of feature selection algorithms on the proposed machine learning-based model is evaluated. The performance of the six best-performing feature selection algorithms is analyzed. The experimental results show that the feature selection algorithms improve the performance of the proposed methodology. Ranker search shows the best performance with a Spearman’s rank-ordered correlation constant of 0.9756, linear correlation constant of 0.9452, Kendall correlation constant of 0.8488 and root mean squared error of 0.0525.

A paradigm shift away from null hypothesis significance testing seems in progress. Based on simulations, we illustrate some of the underlying motivations. First, P-values vary strongly from study to study, hence dichotomous inference using significance thresholds is usually unjustified. Second, statistically significant results have overestimated effect sizes, a bias declining with increasing statistical power. Third, statistically non-significant results have underestimated effect sizes, and this bias gets stronger with higher statistical power. Fourth, the tested statistical hypotheses usually lack biological justification and are often uninformative. Despite these problems, a screen of 48 papers from the 2020 volume of the Journal of Evolutionary Biology exemplifies that significance testing is still used almost universally in evolutionary biology. All screened studies tested default null hypotheses of zero effect with the default significance threshold of p = 0.05, none presented a pre-specified alternative hypothesis, pre-study power calculation, and the probability of ‘false negatives’(beta error). The results sections of the papers presented 49 significance tests on average (median 23, range 0–390). Of 41 studies that contained verbal descriptions of a ‘statistically non-significant’ result, 26 (63%) falsely claimed the absence of an effect. We conclude that studies in ecology and evolutionary biology are mostly exploratory and descriptive. We should thus shift from claiming to ‘test’ specific hypotheses statistically to describing and discussing many hypotheses (possible true effect sizes) that are most compatible with our data, given our statistical model. We already have the means for doing so, because we routinely present compatibility (‘confidence’) intervals covering these hypotheses.

The purpose of this article is to simulate data transmission and calculate traffic parameters in SAGIN air segment for which Ad Hoc network of flying drones is considered as a model. Traffic modeling is based on the manet-routing-compare example from the ns3 simulator library, which has been supplemented with the code for calculation packet losses, throughput/goodput, and message transmission delays. The program allowed considering drones movement at both low and high speeds from 3.6 km/h to 72 km/h. The dependences of traffic losses on data transmission power, transaction sizes and data transmission rate are obtained and analyzed. The distribution of the average effective arrival rate λ and the throughput/goodput for drones has been studied. Comparing traffic characteristics in models with different numbers of drones allows judging how the required quality of service can be achieved by choosing the right transmission parameters.

Surround modulation is a phenomenon whereby costimulation of the extra-classical receptive field and classical receptive field would modulate the visual responses induced individually by classical receptive field. However, there lacks systematic study about surround modulation properties existing in avian optic tectum. In this study, neuronal activities are recorded from pigeon optic tectum, and the responses to moving and flashed squares and bars of different sizes are compared. The statistical results showed that most tectal neurons presented surround suppression as stimuli size grew larger both in moving and flashed paradigms, and the suppression degree induced by larger flashed square was comparable with that by moving one when it crossed near the cell’s RF center, which corresponds to fully surrounding condition. The suppression degree grew weaker when the stimuli move across the RF border, which corresponds to partially surrounding condition. Meanwhile, the fully surround suppression induced by flashed square was also more intense than partially surrounded by flashed bars. The results provide new insight for understanding the spatial arrangement of lateral inhibitions from feedback or feedforward streams, which would help to make clear the generation mechanism of surround modulation found in avian optic tectum.

Landslides are serious geological hazards that become a disaster worldwide, causing a large number of casualties and economic losses every year. There are many factors affecting landslide susceptibility, such as rainfall, soil and slope. Each of them has an important role in the process of slope losing stability. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient and soil type on landslide susceptibility are studied. In the process of rainfall-induced landslide, the relevant physical quantities of soil changes continuously. Their values and processes are closely related to the time of landslide occurrence. Hence, the variation of soil volumetric water content, matrix suction, pore water pressure and total stress throughout the rainfall are measured. As the results, soil type, slope gradient and rainfall intensity have a large influence on landslide susceptibility. The occurrence of landslides has a prerequisite that the slope is greater than or equal to 15°. The rainfall intensity needs to be not less than 80 mm/h. The difference of rainfall pattern also affects the landslide susceptibility. The rainfall pattern with rainfall intensity peak at the later stage is more likely to induce landslide. Coarser soils with gravels are prone to landslides when other conditions are the same. Steeper slopes, stronger rainfall, and coarser soils can all increase the amount of sediment yield.

The present paper investigates the influence of the specimen size of EN-AW6082 wrought aluminium alloy subjected to very high cycle fatigue (VHCF) tests. The hourglass specimens were tested under fully reversed loading condition, up to 10^9 cycles, by means of the ultrasonic fatigue testing machine developed by Italsigma® (Italy). Three specimens groups were considered, with a diameter in the middle cross-section ranging from 3 mm up to 12 mm. The stress field in the specimens was determined numerically and by strain gauge measurements in correspondence of the cross-section surface. The dispersion of experimental results has been accounted for, and data are reported in P-S-N diagrams. The decrease in fatigue resistance with increasing specimen size is evident. Theoretical explanation for the observed specimen-size effect is provided, based on Fractal Geometry concepts, allowing to obtain scale independent P-S*-N curves. The fatigue life expectation in the VHCF regime of the EN-AW6082 aluminium alloy full-scale components is rather overestimated if it is assessed only from standard small specimens of 3 mm in diameter. Experimental tests carried out on larger specimen, and a proper extrapolation, are required to assure safe structural design.

Nanographene oxide (GOn) constitutes a nanomaterial of high value in the biomedical field. However, large scale production of highly stable aqueous dispersions of GOn is yet to be achieved. In this work, we explored high-power ultrasonication as a method to reduce particle size of GO and characterized the impact of the process in the physico-chemical properties of the material. GOn was obtained with lateral dimensions of 99 ±43 nm and surface charge of −39.9 ± 2.2 mV. High-power ultrasonication enabled an improvement of stability features, particularly by resulting in a decrease of the average particle size, as well as zeta potential, in comparison to GO obtained by low-power exfoliation and centrifugation (287 ± 139 nm; −29.7 ± 1.2 mV). Re-markably, GOn aqueous dispersions were stable for up to 6 months of shelf-time, with a global process yield of 74%. This novel method enabled the production of large volumes of highly con-centrated (7.5 mg mL-1) GOn aqueous dispersions. Chemical characterization of GOn allowed the identification of characteristic oxygen functional groups, supporting high-power ultrasonication as a fast, efficient and productive process for reducing GO lateral size, while maintaining the material’s chemical features.

The information entropy for Smoluchowski coagulation equation is proposed based on statistical mechanics. And the normalized particle size distribution is a lognormal function at equilibrium from the principle of maximum entropy and moment constraint. The geometric mean volume and standard deviation in the distribution function are determined as simple constant. The results reveal that the assumption that algebraic mean volume be unit in self-preserving hypothesis is reasonable in some sense. Based on the present definition of information entropy, the Cercignani’s conjecture holds naturally for Smoluchowski coagulation equation. Together with the proof that the conjecture is also true for Boltzmann equation, Cercignani’s conjecture will holds for any two-body collision systems, which will benefit the understanding of Brownian motion and molecule kinematic theory, such as the stability of the dissipative system, and the mathematical theory of convergence to thermodynamic equilibrium.

Thermal shape memory polymers (SMPs) find increasing applications in biology and medicine due to their promising potential for improved biocompatibility. In such applications, the inevitable penetration of small molecules from the ambient fluid into the polymer influences the shape recovery process and often leads to a reduction of the temperature, at which shape recovery takes place. We show here via molecular dynamics simulations that the size of additive molecules plays a key role for this process. While the effect of concentration on the recovery rate is monotonic in the investigated range, a non-monotonic dependence on the size of additive molecules emerges at temperatures close to the glass transition. This work thus identifies the additives’ size to be a qualitatively novel parameter for switching the recovery process in polymer-based shape memory materials.

Metal oxide based electrodes play a crucial role in various as a transparent conductive oxide (TCO). One of the metal oxides, nickel oxide is a promising electrical conductive material. Here, we display that incorporation of vanadium in NiO lattice significantly improve both electrical conductivity and hole extraction. Also, vanadium doped nickel oxide exhibits a lower crystalline size compared to pristine nickel oxide, which maintains the reduction of surface roughness. These results indicating that the vanadium is an excellent dopant for NiO.

: Annona squamosa L. is an important medicinal plant used in traditional medicine for the treatment of various diseases. Different parts of A. squamosa L. have various therapeutic effects; however, the anticancer activity of the leaves has not yet been identified. In vitro, MTT, nuclear staining, and LDH assays were used to evaluate cell survival and proliferation in cells exposed to the extracts. The effect of the extracts on cell migration was investigated using a monolayer wound repair assay, and the apoptotic effects were evaluated using flow cytometry. A breast cancer model was used to study the effect of the extract on the tumor size, and the expression of different proliferative and apoptotic markers was evaluated by immunohistochemical analysis. At a concentration of 100 µg/mL, A. squamosa leaf extracts exerted strong antiproliferative and cytotoxic effects against various cell lines. The extracts reduced wound closure and strongly induced apoptosis. In vivo study, rats were sacrificed 24 h after the last injection, and tumor size, as well as the expression of proliferative and apoptotic markers, were observed to be greatly affected by treatment with the extracts. Therefore, A. squamosa leaf extract may be developed as a potential novel drug to treat breast cancer in the future

This study was aimed at investigating the effects of roasting and cryogenic milling on particle size, water solubility, and amount of bioactive components in ginseng root. Samples were pulverized by cryogenic milling, and one treatment condition was selected for each size range (10-50 μm, and >50 μm). The selected samples were roasted at different temperatures (160-200 °C) followed by cryogenic milling. Powdered samples were analyzed for their physicochemical characteristics. Results revealed that roasted samples exhibited significantly smaller particle size than controls (not roasted, p<0.05), and the particle size of roasted samples decreased with increase in roasting temperature until flocculation occurred around 180-190 °C. With decrease in particle size of ginseng; water solubility index, antioxidant activity, total polyphenol content, and total polysaccharide content were observed to increase. Ginseng samples showed an increasing trend in antioxidant activity with decreasing particle size (p>0.05) with significantly higher values for all roasted samples compared to the controls (p<0.05). Non-polar ginsenosides such as Rg2(S), Rg2(R), Rg3(S), Rg3(R), and Rh1(S) showed an increase in temperature-dependent manner. This study revealed that roasting at certain temperature range with cryogenic milling has positive effects on ginseng by reducing its particle size, and increasing water solubility and bioactive components.

This study aimed to decrease the particle size of ginseng by roasting and cryogenic milling to increase its water solubility and physiological activity. The samples were roasted for different times (9–21 min) and generated in different sizes (10–50, and > 50 μm). All roasted samples revealed significantly smaller particle sizes than did non-roasted samples based on Sauter mean diameter (D [3,2], p < 0.05). Further, the particle sizes of roasted samples decreased till roasting up to 15 min. In terms of the water solubility index (WSI), antioxidant activity, total polyphenol content (TPC), and total polysaccharides according to particle size, 10-20 μm-sized samples showed the highest values when compared with >50 μm-sized samples. Based on roasting time, WSI values of all samples roasted for up to 15 min were higher than those of the control (not roasted) (p < 0.05). Antioxidant activity and TPC also increased with increasing roasting time. Total polysaccharide content was the highest upon roasting for 15 min except for the 10-20 μm sample. Ginsenoside content of roasted samples >20 μm size was higher than that of the control (not roasted) except after 15 min of roasting. Therefore, roasting and cryogenic milling are effective in producing ginseng root powder.

Precipitation processes are technologies commonly used in hydrometallurgical plants to recover metals or to treat wastewaters. Moreover, solid-liquid separation technologies, such as thickening or filtering, are relevant unit operations, included in the precipitation technologies. These methods are strongly dependent on the characteristics of the solid precipitates formed during the specific precipitation reaction. One of these characteristics is the particle size distribution (PSD) of the solid precipitates which are fed into a solid-liquid separation process. Therefore, PSD determination is a typical practice for the characterization of the slurries generated in a precipitation plant. Furthermore, the precipitates generated in these processes have a colloidal or aggregation behavior, depending on the operational conditions. Nevertheless, the conventional methods used to estimate PSD (e.g., laser diffraction and/or ciclosizer) have not been designed to measure particles that tend to aggregate or disaggregate, since they include external forces (e.g., centrifugal, agitation, pumping and sonication). These forces affect the true size of the aggregates formed in a unit operation, thereby losing representativity in terms of aggregates particle size. This study presents an alternative method of measuring the size distribution of particles with aggregation behavior, particularly, by using non-invasive microscopy and image processing and analysis. The samples used have been obtained from an experimental precipitation process by applying sulfidization to treat the cyanide-copper complexes contained in a cyanidation solution. This method has been validated with statistical tools and compared with a conventional analysis based on laser diffraction. Our results show significant differences between the methods analyzed, demonstrating that image processing and analysis by microscopy is an excellent and non-invasive alternative to obtaining size distribution of aggregates in precipitation processes.

We examined the causality between growth opportunities and earnings quality of the emerging economies. We develop an argument that growth opportunities should lead to high-quality earnings of the developing economies against the prior studies from developed economies which posit that growth opportunities result in a lower quality of earnings. The findings revealed that Growth Opportunities had a positive significant effect on Earnings Quality (EQ). Thus, the study concluded that growth opportunities are useful in determining the earnings quality of firms. The study recommends that managers should take advantage of their firms' growth opportunities to provide quality accounting information which will directly provide expanded opportunities for business growth. Though literature confirms that generally, earnings management might not be necessarily bad in business operational practice, managers are advised to avoid extreme aggressiveness in managing earnings as this may culminate in the negative manipulation of accounting information.

The reinforcement of concrete by using polyolefin fibres may be considered in structural design to meet the requirements of the applicable code rules. In order to achieve a reliable use of such a composite material, use of full-scale real structures is needed. The conversion of lab testing data into real practice properties is challenging and significantly influenced by various aspects, among which the size effect is a key one. Given that the available literature does not report coinciding conclusions about such an effect on quasi-brittle materials reinforced with fibres, further research is justified. Therefore, this work studies the behaviour of notched beams with three proportional sizes by using self-compacting polyolefin reinforced concrete with a fibre volume fraction of 1.1%. Flexural testing was carried out according to the standard EN-14651, with the results revealing the existence of the size effect. In addition, a reduction of the residual strength identified in the larger specimens was observed in fracture surfaces with equal fibre content.

Much of the debate on Plan S seems to concentrate on how to make toll access journals open access, taking for granted that existing open access journals are Plan S compliant. We suspected this was not so, and set out to explore this using DOAJ's journal metadata. We conclude that an overwhelmingly large majority of open access journals are not Plan S compliant, and that it is small HSS publishers not charging APCs that are least compliant and will face major challenges with becoming compliant. Plan S need to give special considerations to smaller publishers and/or non-APC-based journals.

The aim of this paper is to at first evaluate the influence of three key parameters including weld current, weld time and electrode force on nugget diameter and tensile strength in resistance projection welding. Then, a 2-D axis-symmetric finite element model is developed to simulate the projection welding and predict the nugget diameter. Finally, the FEM results are compared to experimental data to verify the simulation model and simulated results. In the finite element model, the temperature-dependent material properties were taken into account.

Live fuel moisture content (LFMC) influences fire activity at landscape scale and fire behavior in laboratory experiments. However, field evidences linking LFMC to fire behavior are very limited despite numerous field experiments. In the present study, we reanalyze a shrubland fire dataset with a special focus on LFMC to explain this counterintuitive outcome. We found that this controversy might result from three reasons. First, the range of experimental LFMC data was too moist to reveal significant effect with the widespread exponential or power functions. Indeed, LFMC exhibited a strong effect below 100%, but marginal above this threshold, contrary to these functions. Second, we found that the LFMC significance was unlikely when the size of the dataset was smaller than 40. Finally, a complementary analysis suggested that 10 to 15% of random measurement error in variables could lead to an underestimation by 30 % of the LFMC effect. The effect of LFMC in field experiments is thus stronger than previously reported in the range prevailing during the actual French fire season and in accordance with observations at different scales. This highlights the need to improve our understanding of the relationship between LFMC and fire behavior to refine fire danger predictions.

In our previous works we have proposed design equations that can predict with reasonable accuracy the transition point from homogeneous to heterogeneous regime as well as the gas holdup and the mean Sauter diameter at the homogeneous regime. The validity of the proposed correlations was checked with data obtained using different geometrical configurations and several Newtonian and non-Newtonian liquids as well as the addition of surfactants. However, in all the experiments the gas phase was atmospheric air. This work investigates the effect of gas phase properties by conducting experiments employing various gases (i.e., air, CO₂, He) that cover a wide range of physical property values. Experiments revealed that only the use of low-density gas (He) has a measurable effect on bubble column performance. More precisely, when the low-density gas (He) is employed, the transition point shifts to higher gas flow rates and the gas holdup decreases, a fact attributed to the lower momentum force exerted by the gas. In view of the new data, the proposed correlations have been slightly modified to include the effect of gas phase properties and it is found that they can predict the aforementioned quantities with an accuracy of ±15%. It has been also proved that CFD simulations are an accurate means for assessing the flow characteristics inside a bubble column.

Significant changes have occurred at Arabian Gulf Coast of Saudi Arabia over the last three decades. The area of mangrove was reduced by about 55%. Thus the economic, social, and environmental value of mangroves must be assessed over short -to long-term scales and employ these assessments for the awareness rising at local communities. This study provides a preliminary assessment of the risks on mangrove vegetation; it will provide database to mitigate the tremendous pressures due to coastal development and urban activities. The effects of human development on the mangrove plant cover in Eastern Region of KSA were recognised, during 2013 to 2016. The mean variations of physio-chemical characteristics in water and sediment were recorded. With regard to water analyses including; nitrogen, phosphorus, TSS, TDS, BOD, and turbidity were evaluated. On the other hand, for sediment: TDS, nitrogen, phosphorus, sulphate and total organic carbon were assessed. Moreover, the growth parameters: plant height, and size index, of Avicennia marina were recorded and estimated. It is concluded that human impact and urban developments have exerted drastic effects on the coastal ecosystems and its environments.

Terrestrial LiDAR becomes more and more popular to estimate leaf and plant area density. Voxel-based approaches account for this vegetation heterogeneity and significant work has been done in this recent research field, but no general theoretical analysis is available. Although estimators have been proposed and several causes of biases have been identified, their consistency and efficiency have not been evaluated. Also, confidence intervals are almost never provided. In the present paper, we solve the transmittance equation and use the Maximum Likelihood Estimation (MLE), to derive unbiased estimators and confidence intervals for the attenuation coefficient, which is proportional to leaf area density. The new estimators and confidence intervals are defined at voxel scale, and account for the number of beams crossing the voxel, the inequality of path lengths in voxel, the size of vegetation elements, as well as for the variability of element positions between vegetation samples. They are completed by numerous numerical simulations for the evaluation of estimator consistency and efficiency, as well as the assessment of the coverage probabilities of confidence intervals. • Although commonly used when the beam number is low, the usual estimators are strongly biased and the 95% confidence intervals can be ≈±100% of the estimate. • Our unbiased estimators are consistent in a wider range of validity than the usual ones, especially for the unbiased MLE, which is consistent when the beam number is as low as 5. The unbiased MLE is efficient, meaning it reaches the lowest residual errors that can be expected (for an unbiased estimator). Also the unbiased MLE does not require any bias correction when path lengths are unequal. • When elements are small (or voxel is large), 103 beams entering the voxel leads to some confidence intervals ≈±10%, but when elements are larger (or voxel smaller), it can remain wider than ±50%, even for a large beam number. This is explained by the variability of element positions between vegetation samples. Such a result shows that a significant part of residual error can be explained by random effects. • Confidence intervals are much smaller (±5 to 10%) when LAD estimates are averaged over several small voxels, typically within a horizontal layer or in the crown of individual plants. In this context, our unbiased estimators show a reduction of 50% of the radius of confidence intervals, in comparison to usual estimators. Our study provides some new ready-to-use estimators and confidence intervals for attenuation coefficients, which are consistent and efficient within a fairly large range of parameter values. The consistency is achieved for a low beam number, which is promising for application to airborne LiDAR data. They entail to raise the level of understanding and confidence on LAD estimation. Among other applications, their usage should help determine the most suitable voxel size, for given vegetation types and scanning density, whereas existing guidelines are highly variable among studies, probably because of differences in vegetation, scanning design and estimators.

To reduce weight and simplify maintenance, ship structures frequently include openings and cut-outs. While these features offer practical advantages, they can weaken the structural integrity of key components. This study explores the effects of these geometric discontinuities on the double-bottom floor plates of a Panamax-class container ship under axial and transverse loads. Through numerical simulations and experimental testing, we analyzed different cut-out configurations and stiffening strategies to assess their impact on stress distribution, plate thickness and fatigue behavior. The results reveal that side cut-outs significantly increase stress, particularly under transverse loads, while central openings have less impact. Additionally, increasing plate thickness consistently reduces stress levels across all models, improving structural durability. Fatigue analysis shows that certain stiffening configurations, particularly those with longitudinal stiffeners in the bottom plates, enhance fatigue life. These findings offer critical design insights for optimizing hull structures, balancing weight reduction with strength improvement. The study provides valuable recommendations for reducing stress concentrations and extending the fatigue life of ship components, contributing to more efficient and safer ship designs.

The finite volume method (FVM) is a kind of numerical analysis method that is simple and can take into account the topography as the finite element method (FEM). The adjoint state method (ASM) can easily and efficiently calculate the gradient vector of the objective function for the inversion. We developed a program to apply these methods to 3-D Magnetotelluric (MT) inversion and verified it using test models. In the forward modelling, it was confirmed that the program could perform analysis properly and efficiently considering topography and subsurface resistivity heterogeneity. Furthermore, we conducted the inversion using a synthetic open dataset and could reconstruct the true model of the dataset. The comparison with the previous work revealed that the computation time was comparable in spite of the fact that we calculated without MPI implementation, which the previous work used.

This paper is devoted to the finite time internal and the external synchronization (hybrid synchronization) for complex networks by means of intermittent control. Different from most previous research achievements, the finite time synchronization include internal and the external synchronization, this article employs the intermittent control to drive the complex networks to achieve synchronization in finite time. To be specific, the internal and the external synchronization all achieve consistent synchronization in finite time by devise Lyapunov function. Finally, numerical examples are presented to illustrate the validness of theoretical results.

Objective: Despite long simulation times, recently developed finite element analysis (FEA) models of knee joints have demonstrated their suitability for predicting individual risk of onset and progression of knee osteoarthritis. Therefore, the objective of this study was to assess the feasibility of machine learning (ML) to replicate outcomes obtained from FEA when simulating mechanical responses and predicting cartilage degeneration within knee joint. Design: Two ML models based on the Gaussian Process Regression (GPR) algorithms were developed. The first model (GPR1) utilized age, weight, and anatomical joint dimensions as predictor variables to predict tissue mechanical responses and cartilage degeneration based on FEA data. The second model (GPR2) utilized age, weight, height, and gender to predict anatomical joint dimensions, which were then used as inputs in the GPR1 model. Finally, the GPR1 and combined GPR1+GPR2 models were used to investigate the importance of clinical imaging when making personalized predictions for knees from healthy subjects with no history of knee injuries. Results: In the GPR1 model, R2 of 0.9 was exceeded for most of the predicted mechanical parameters. The GPR2 model was able to predict knee shape with R2 of 0.67 - 0.9. Both GPR1 and combined GPR1+GPR2 models offered equally good performance (AUC = 0.73 - 0.74) at classifying patients at high risk for the onset and development of knee osteoarthritis. Conclusions: In the future, real-time and easy-to-use GPR models may provide a rapid technology to evaluate mechanical responses within knee for researchers or clinicians who have no former knowledge from FEA.

(1) Background: This study aimed to compare the effect of polyetheretherketone (PEEK) and titanium abutments on implant prosthetic systems and supporting bone using three-dimensional finite element analysis (FEA); (2) Methods: A three-dimensional finite element analysis was conducted using CATIA and Abaqus software to model mandibular first molar implant systems with titanium and PEEK abutments. Under external loading conditions, finite element analysis was conducted for the stresses in implant components and surrounding bones of each group; (3) Results: The implant fixture of the PEEK model exhibited the highest von Mises stress (VMS). The lowest VMS was observed in the abutment screw of the titanium model. Both implant systems demonstrated similar stress distribution and magnitudes in cortical and cancellous bones; (4) Conclusion: PEEK abutments show similar stress distribution in surrounding bone compared to titanium. However, PEEK absorbs the stresses within the implant system and exhibits the highest VMS values due to its low mechanical and physical properties. Therefore, PEEK abutments need improved mechanical properties for better clinical application.

This paper introduces a low-tech capacitive micromachined ultrasonic transducer (CMUT) designed with low environmental footprint materials. The fabrication process involves a copper plate as the fixed bottom electrode, a polymer-based adhesive as a dielectric material, and an aluminum foil as the top electrode.Finite element simulations include studies of displacement, mechanical stresses, and eigenfrequency. Experimental measurements validate the device's electromechanical behavior, showing an eigenfrequency of 88.6 kHz and a displacement of 22 pm. The low-tech CMUT demonstrates potential for applications such as ultrasonic actuation and energy harvesting, offering simplicity, biocompatibility, and low environmental impact. While not directly ready for applications, these transducers provide hands-on experience with technology similar to high-performance silicon-based implementations. These low-tech MUTs are perfect practical case studies for teaching purposes, combining simulation and experimental validation.

The ANSYS 2024R1 student edition was used to create a finite element model of a basketball rim and backboard. This finite element model included the use of steel for the rim and its mount, a tempered glass backboard, and an aluminum frame behind the backboard. After a mesh was created, fixed support boundary conditions were applied to the four corners of the aluminum frame. The subsequently calculated mode shapes and frequencies were compared to empirical modal analysis previously done at the United States Military Academy at West Point, New York. Four mode shapes and frequencies agreed rather well between the theoretical finite element analysis and previously published empirical modal analysis, specifically where the rim was vibrating in the vertical direction, which was the direction that the accelerometer was aligned for modal analysis. However, three mode shapes missed by the empirical modal analysis were found where the vibration of the rim was confined to the horizontal plane, which was orthogonal to the orientation of our accelerometer.

The design of water Vessel fender system can minimize impact energy, which could result in severe vessel or offshore structure damage during collision. In order to protect Offshore structures and vessels from damage after impact, a Fender design approach is proposed which uses Soft materials like rubber, sand, inflated rubber tube, etc. to reduce damage on impacted vessels as well as offshore structures like wind turbines, bridges, oil drilling platforms in water etc. The fender is designed in such a way that it can handle vessels made of different material, sizes, and weights.The proposed solution is a fender consisting of a number of layers of soft sandwich materials, each layer getting softer as it moves away from the structure i.e. Hard-Soft fender design which can absorb impact energy upon collision. To handle lighter vessels made of soft or brittle materials, the outer layer is made of inflatable or Very soft foam rubber; however, the inner layer covering the offshore structure is made of hard material to handle heavy vessels made of hard material such as steel. Furthermore, the use of sand as a natural fender along waterways such as narrow channels is also proposed to reduce the cost of fender installation and catastrophic vessel impact damage on rocky ground since it produces less deformation just like rubber fender as demonstrated in the simulation. Finite Element Analysis using ANSYS software, Explicit Dynamic Autodyn, was performed. The results showed a considerable decrease in the total deformation and internal energy of the vessel and fended structure when collision occurs. Furthermore, the result showed that Hard-Soft fender layer performs much better than Soft-Hard-Soft followed by Soft-Hard Fender layer design.

In this paper, we aim to address the challenge of airflow interference during fault detection in high-speed train bogies by introducing a flow field and investigating the characteristics of the sound field distribution of critical components under its influence. This approach overcomes the limitation observed in previous studies that ignored the impact of the flow field. Furthermore, we evaluate and compare various layouts for inter-track acoustic sensor arrays. The proposed sensing methods hold significant practical engineering value, and the collected data serves as a valuable reference for acquiring acoustic signals from key bogie components in future research.

An estimation of the electric sources in the heart were conducted using a novel method, based on Huygens’ Principle, aiming at a direct estimation of equivalent bioelectric sources over the heart surface in real time. The main scope of this work was to establish a new, fast approach for the solution of the inverse electrocardiography problem. The study was based on recorded electrocardiograms (ECGs). Based on the Huygens’ principle, measurements obtained from a patient’s thorax surface were interpolated over the surface of the employed volume conductor model and considered as a secondary Huygens’ sources. These sources, being non-zero only over the surface under study, were employed to determine the weighting factors of the eigen-functions expansion describing the generated voltage distribution over the whole volume conductor volume. With the availability of the potential distribution stemming from measurements, the electromagnetics reciprocity theorem is applied once again to yield the equivalent sources over the pericardium. The methodology is self validated, since the surface potentials calculated from these equivalent sources are in very good agreement with ECG measurements. The ultimate aim of this effort is to create a tool providing the equivalent epicardial voltage or current sources in real time, i.e. during the ECG measurements with multiple electrodes.

Model-based approaches form the basis of the majority of damage detection and localization studies; however, built-in online detection technique can offer an alternative for future structural health monitoring technologies. Thus, in this paper, we present a dynamic localization algorithm for damage localization in functionally graded plates. The method depends on the creation of a grid matrix that contains the dynamic response of the structure over time. Subsequently, an optimization process is carried out via a linear equation representing the information contained within the grid to achieve accurate localization of damage. Due to the inherent sparsity of the localization nature, the FISTA algorithm has been employed as a problem solver. The approach is tested in the case of the functionally graded plate under clamped free boundary conditions. Several, damage scenarios were investigated for the case of damage signals on and off the grid. The results show that the proposed approach is capable of accurately predicting damage position and can be suitable for use in low size data systems.

A novel phase-field method based numerical approach to modeling the compaction process of sedi- ments is presented. Water-logged rock or soil sediments are deposited on the water basins over time and the increasing volume of the sediment compacts under its own weight and external pressure. Coupled evolution of mass conservation, Darcy flow, and the viscoelastic constitutive response, in conjunction with the evolution of porosity and permeability, make this problem highly non-linear and involve moving boundaries. We adopt a phase-field approach to represent the moving sediment interface, and the underlying multiphasic model permits for studying compaction in dynamically evolving sediments. This approach does not necessitate a change of domain sizes as is the case of existing traditional models of sedimentation but rather treats sedimentation growth as a problem of interface motion. We first model a classical compaction problem in 1D to compare with existing results in the literature, and then extend the framework to 2D to model the compaction process taking place under the influence of gravity. The model is then extensively applied to understand the effect of the sediment initial state and the sediment material properties on the compaction process and its spatiotemporal evolution. Lastly, a strong validation of our phase-field treatment results against predictions from traditional methods of solving open boundary sediment compaction problems, and a good agreement between the conventional understanding and the numerical predictions of porosity dependence on the fluid pore pressure for various cases of geological interest, are used to demonstrate the applicability and scalability of this novel numerical framework to model more advanced sediment compaction problems and geometries.

Brain tumors are abnormal cells growth in the brain tissues that can be cancerous, or not. In any case, they could be a very aggressive disease that should be detected as early as possible. Usually, magnetic resonance imaging (MRI) is the main tool commonly adopted by neurologists and radiologists to identify and classify any possible anomalies present in the brain anatomy. In the present work, an automatic unsupervised method called Z2-$\gamma$, based on the use of adaptive finite-elements and suitable pre-processing and post-processing techniques, is introduced. In particular, the proposed methodology is able to automatically classify whether a given MR image represents a healthy or a diseased brain and in this latter case, is able to locate the tumor area.

Here we consider sums of finite products of Chebyshev polynomials of the third and fourth kinds. Then we represent each of those sums of finite products as linear combinations of the four kinds of Chebyshev polynomials which involve the hypergeometric function ₃F₂.

Polymer nanocomposites are composed of polymer materials reinforced with nano fillers. In the present study the effective thermal conductivity of the composites filled with nanofillers has been investigated using commercially available finite element software ABAQUS 6.11. The nanofillers used were alumina particles and multi-walled carbon nanotubes (MWNTs) and the matrix was considered to be made of epoxy. For the analysis 2D and 3D Representative Volume Elements (RVEs) were generated using Random Sequential Adsorption (RSA) algorithm using MATLAB and Python scripts. Thermal conductivity was found out for 2D and 3D RVEs for different area and weight fractions respectively. Two different shapes of the alumina nanoparticles were considered: spherical (circular) and ellipsoidal (elliptical) for 3D (2D) analysis. It was found that the thermal conductivity was increased with the addition of nanofillers. The increase in thermal conductivity was approximately same for both types of inclusions at corresponding area or weight fractions in 2D or 3D analysis. The results showed that addition of MWNTs to the composites lead to a significant increase in thermal conductivity than spherical or ellipsoidal inclusions.

This paper presents a comprehensive simulation framework for the investigation of electromigration (EM) in nano-interconnects, with a primary focus on unravelling the influential role of microstructure. To this end, a novel approach to generate conductor metal’s microstructures is presented, whereby a predefined statistical distribution of grain sizes obtained from experimental texture analyses can be incorporated into the developed EM modelling framework. The framework considers the impact of diffusion heterogeneity through the metal texture and interfaces. As such, the intricate interplay between microstructural/interfacial properties, and the resulting atomic flux and stress distribution within nanointerconnects could be investigated. Additionally, the study advances beyond the state of the art by comprehensively simulating all stages of electromigration, including stress evolution, void nucleation, and void dynamics while considering the impact of microstructure. Specifically, the model was employed to study the impact of trench dimensions on dual damascene copper texture and its subsequent impact on electromigration aging, where the model findings were corroborated by comparing to available experimental findings. A nearly linear augmentation in normalized lifetime was detected for aspect ratios equal to or greater than 1. However, a saturation is detected for wider lines with no effective enhancement in lifetime. An aspect ratio of 1 seems to maximize EM lifetime for each cross-sectional area by fostering a bamboo-like structure, where about 2-fold of increase is estimated when going from aspect ratio 2 to 1.

The number of physical devices connected to the Internet such as vehicles, household appliances and other "things" has been steadily increasing in recent years, thus forming the basis for the Internet of Things (IoT). IoT ecosystem extends beyond country borders and application domains, combining thousands of versatile devices that differ in terms of their structures, capabilities, and available resources. It is therefore not surprising that the landscape of wireless communication technologies and the degree of IoT devices available today is excessively broad and diverse. Interference between networks leads to frame collisions and consequent packet loss. Frame collisions occur when two or more packets overlap in time and frequency and use the same Long Range (LoRa) parameters, i.e. the same Spreading Factor (SF), Bandwidth (BW) and Carrier Frequency (CF). When most devices use the same configuration, collision probability is higher. The probability of frame collisions is also affected by traffic characteristics, particularly the periodicity of the transmission and the payload size. Larger payload sizes and more frequent transmissions accumulate with higher Time on Air (ToA) and channel occupancy [1]. Transmission powers and the location of the gateways also influences this situation. The aim of this experimental work is to verify the effects of collisions and interference in Long Range Wide Area Network (LoRaWAN), regarding the periodicity of transmissions and the payload sizes in a context of an inter-SF interference scenario. And to validate measuring tools like Received Signal Strength Indicator (RSSI), ToA and Packet Delivery Ratio (PDR) in the reliability of a network. We validate our conclusions by analyzing ToA according with RSSI and different data sizes, the RSSI for different SFs and different data sizes and finally the packet loss through the PDR for a better understanding of the reliability of packet transmission in our link. In the end we conclude that in an environment with inter-SF interference, the choice of SFs and packet lengths impacts ToA. When dealing with multiple devices near gateways, different SFs and varying packet lengths can lead to increased latency and longer ToA. Consequently, the risk of packet loss becomes more significant, especially if the signal-to-interference ratio (SIR) is low. This limitation will therefore affect scalability, particularly in Non-Line-Of-Sight (NLOS) scenarios.

The seed habit is the most complex and successful method of sexual reproduction in vascular plants. It represents a remarkable moment in the evolution of plants that afterwards spread on land. In particular, seed size had a pivotal role as for evolutionary success and agronomic trait, especially in the field of crop domestication. Given that crop seeds constitute one of the primary products for consumption, it follows that seed size represents a fundamental determinant of crop yield. This adaptative feature is strictly controlled by genetic traits from both maternal and zygotic tissues, although seed development and growth are also affected by environmental cues. Despite being a highly exploited topic for both basic and applied research, there are still many issues to be elucidated as for developmental biology as well as for agronomic science. This review addresses a number of open questions related to cues that influence seed growth and size, and how developmental processes are influenced by them. Besides, new insights on the genetic-molecular control of this adaptive trait are presented.

A study was carried out in a Waste Sorting Plant (WSP) located in France and treating dry recyclable household waste (DRHW) as well as dry recyclable commercial and industrial waste (DRCIW). The aim was to investigate the exposure to bioaerosol and dust. The aim of the study was to assess the extent to which the measurement of concentration, species composition and particle size distribution can contribute to a better assessment of the biological risks associated with exposure. Both stationary and personal bioaerosol and dust samples were collect in the (WSP). The results confirm that waste and waste sorting activities are sources of airborne fungi. Indeed, ambient concentrations ranged from 7.3×103 to 8.5×105 CFU/m3 for culturable moulds and up to up to 4 mg/m3 for dust. Personal exposure to inhalable dust was found up to 3 mg/m3 for dust and ranged from 8.6×103 to 1.5×106 CFU/m3 for fungi. Airborne fungal communities were found to be dominated by the Penicillium genera in both bioaerosols and settled dust samples, followed by the Aspergillus, Cladosporium, Wallemia, Mucor, and Rhizopus genera. Fungi were carried by particles of aerodynamic diameters mainly between around 2.0 and 10.0 µm. The findings dealing with size distribution and biodiversity of bioaerosols suggest that employees are exposed to complex bioaerosols during their work and helps to make a finer diagnosis of the risks involved, which is often difficult in the absence of any OEL for bioaerosols in general.

In this paper, the effects on the rheological properties, particle size distribution, and fluorescence properties of red wine were investigated under microwave irradiation, and the mechanism of the effects of microwave irradiation on the sensory properties of red wine was discussed. The results showed that the effect of microwave on the rheological properties in red wine could be fitted by the Power-law model and Carson model, through the analysis of the rheological constants, yield stress, and viscosity coefficient of wine, it was found that microwave treatment could improve leg phenomenon and thickening effect by the change of rheological properties; the particle size distribution in wine indicated that microwave irradiation did change the particle size distribution through friction effect and oxidative polymerization, resulting in the wine’s visual effect and mouthfeel; the wine quality could be improved by enhancing the fluorescence intensity under different microwave conditions, which meant that microwave technology could speed up the formation of fluorescent substances, such as the polymerization of flavan-3-ols. In conclusion, microwave treatment could modify the sensory characteristics of wine, and further provide the theoretical basis for the application of microwave in winemaking.

Morphological study of lakes defines the sensitivity of their watershed. Moreover, it plays important role in safeguarding the lake’s ecosystem services through proper planning and utilization of the lakes’ resources. In the last few decades, the morphology of lakes in Ethiopian and Kenyan Rift (EKR) valley are experiencing contradicting morphological changes. Being in the same system, some are shrinking and others are expanding beyond their natural boundaries. The objective of this review is to shed light on the trends in spatio-temporal water level fluctuation and their contributing factors for lakes to the academia and decision makers. Peer reviewed article journals, conference proceedings, thesis, and book chapters collected from online sources and supplied by authors on request formed a database of 346 documents where 226 are critically assessed. The review indicated that lakes in Ethiopian rift are shrinking and expanding, while Kenyan lakes are expanding. The en-dorheic lakes suffered the most fluctuations due to anthropogenic factors at the expense of loss of forest and woodlands in their watershed. While the lakes’ water quality related to the morphological changes are given less attention, the predicted 12 m drop of Lake Turkana due to projects in the Omo catchment did not materialize.

This study aims to explore the differences between loess and landslide deposits, focusing on as-pects such as particle distribution, consolidation characteristics, and dynamic shear modulus. Through a series of experiments, the research reveals the similarities and differences between these two entities, yielding several key findings. Firstly, the process of landsliding disrupts the original structure of the loess, resulting in a reduction in porosity and a densification of the soil. This alteration in structural properties leads to significant disparities in physical attributes be-tween landslide deposits and undisturbed loess. Additionally, the movement and sorting of par-ticles during landslides cause variations in particle size distribution across different sections of the landslide deposits. Secondly, the landslide process not only alters the soil's structure but also changes the particle sizes within the loess. Particle wear and sieving result in the transformation of larger particles into smaller ones, leading to a more uniform particle size distribution. This shift in structure and particle size directly impacts the consolidation characteristics of landslide deposits, resulting in a substantial reduction in compression coefficient. Despite undergoing consolidation for decades, the middle and lower sections of landslide deposits still exhibit un-der-consolidation. Although the differences in the maximum dynamic shear modulus between loess and landslide deposits at varying depths are relatively minor, differences in porosity and consolidation characteristics lead to faster decay rates of the dynamic shear modulus for the lat-ter. The study also highlights a reduction in the water sensitivity of the maximum dynamic shear modulus within landslide deposits. Based on experimental results, a predictive model is pro-posed, utilizing A and m values to estimate the maximum dynamic shear modulus of both loess and landslide deposits. In conclusion, this research uncovers the impact of landslide processes on the structure and properties of loess, providing insightful understanding into the disparities between these two entities.

Background: Accurate estimation of dietary intake is challenging. But whilst some progress has been made in high-income countries, low- and middle-income countries (LMICs) remain behind, contributing to critical nutritional data gaps. This study aimed to validate an objective, passive image-based dietary intake assessment method against weighed food records in London, UK for onward deployment to LMICs. Methods: Wearable camera devices were used to capture food intake of eating occasions in 18 adults and 17 children of Ghanaian and Kenyan origin living in London. Participants were provided pre-weighed meals of Ghanaian and Kenyan cuisine and camera devices to automatically capture images of the eating occasions. Food images were assessed for portion size, energy, and nutrient intake, and relative validity of the method compared to the weighed food records. Results: Pearson and Intra-class correlation coefficient of estimates of intakes of food, energy and 19 nutrients ranged from 0.60 to 0.95 and 0.67 to 0.90, respectively. Bland-Altman analysis showed good agreement between the image-based method and weighed food record. Under-estimation of dietary intake by the image-based method ranged from 4 to 23%. Conclusions: Passive food image capture and analysis provides an objective assessment of dietary intake comparable to weighed food records.

Loess is a special soil with high water sensitivity, which covers a large area in northwest China. Cracks are prone to generate in loess under the arid and semi-arid climate, which will provide the preferential channel for water and reduce the mechanical properties of soils. It is of great significance to understand the evolution characteristics and mechanisms of the cracks in loess areas. At present, the researches on cracks in soils are mainly concentrated in the characteristics of different cracking patterns. However, the spacing cracks are mostly discussed in materials like rock and concrete, rather than soils. The cracking characteristics and mechanisms of spacing cracks in loess is still inadequate. In this research, the drying tests of loess are carried out with different sizes of specimens. The parameters of spacing cracks and local strain distributions of the loess samples are obtained via PCAS and DIC methods during desiccation, respectively. The cracking modes, space cracking laws like insertion and saturation of spacing cracks are revealed. Finally, the size effect on the characteristics of spacing cracks is verified with a discrete element software MatDEM.

The size of seeds is particularly important for agricultural development, as it is a key trait that determines yield. It is controlled by the coordinated development of the integument, endosperm, and embryo. Large seeds are one of the important ways to improve the ultimate “sink strength” of crops, providing more nutrients for early plant growth and showing certain tolerance to abiotic stresses. There are several pathways for regulating plant seed size, including the HAIKU (IKU) pathway, ubiquitin-proteasome pathway, G (Guanosine triphosphate) protein regulatory pathway, mitogen-activated protein kinase (MAPK) pathway, transcriptional regulators pathway, phytohormone regulatory pathways including auxin, brassinosteroid (BR), gibberellin (GA), jasmonic acid (JA), cytokinin (CK), Abscisic acid (ABA), and MicroRNAs (miRNAs) regulatory pathway. This article summarized the seed size regulatory network and prospected ways to improve yield. We expect to provide valuable reference to researcher in the related field.

This study examines the effects of particle size and heat pipe angle on the thermal effectiveness of a cylindrical screen mesh heat pipe using silver nanoparticles as the test substance. The experiment investigates three different particle sizes (30nm, 50nm, and 80nm) and four different heat pipe angles (0°, 45°, 60°, and 90°) on the heat transmission characteristics of the heat pipe. The results show that the thermal conductivity of the heat pipe increased with an increase in heat pipe angle for all particle sizes, with the highest thermal conductivity attained at a 90° heat pipe angle. Furthermore, the thermal resistance of the heat pipe decreased as the particle size decreased for all heat pipe angles. The thermal conductivity measurements of the particle sizes - 30, 50, and 80 nm - were 250 W/mK, 200 W/mK, and 150 W/mK, respectively. The heat transfer coefficient values for particle sizes 30nm, 50nm, and 80nm were 5500 W/m2K, 4500 W/m2K, and 3500 W/m2K, respectively. The study also found that the heat transfer coefficient increased with increased heat pipe angle for all particle sizes, with the highest heat transfer coefficient obtained at a 90° heat pipe angle.

The COVID-19 pandemic had a wide-ranging impact, resulting in a global recession due to weakened purchasing power. This circumstance necessitates business organizations adapting to developments and being more conscious of the risk of financial statement fraud. The intention of this research is to investigate the way corporate governance affected financial statement fraud during the COVID-19 pandemic. To acquire empirical data for examining corporate governance variables on financial statement fraud, the research was examined using quantitative methods. The study takes advantage of secondary data acquired from annual reports of companies under special monitoring listed on the Indonesia Stock Exchange of 2020-2021. The logistic regression method was used to evaluate 134 data sets, and financial statement fraud was measured using the Z-Score and F-Score models. The results indicate that using the Z-score, only the board size has a negative effect on financial statement fraud during the COVID- 19 pandemic. Meanwhile, using the F-Score, the corporate governance variables studied are not proven to have an influence on financial statement fraud during the COVID 19 pandemic.

In current study, the production of microparticles from fifteen commercial sugarcane pulp (SCP) lunch-boxes into different types of food under different conditions was investigated, where we used DI water, 4% HAc, and 95% EtOH to simulate aqueous, acidic, and fatty foods. Results showed that compared with DI water and 95% EtOH, 4% HAc caused the degradation of sugarcane fibers, resulting in the highest number of microparticles released, which was significantly greater than the specified limit value. It was estimated that consumers might intake a total number of 36,400 ~ 231,700 items per meal per lunch-box, of which the proportion of microparticles with particle size between 100 ~ 500 μm was the largest, with a number of 12,376 ~ 130,795 items. Moreover, of all SCP lunch-box except S-11, Al and Fe are the main metals, ranging between 35.16 ~ 1244.04 and 44.71 ~ 398.52 mg/kg, respectively, followed by Pb, Ti, and Sr. Interestingly, unlike other lunch-boxes, the content of Pb in S-11 was the highest, with a number of 136 mg/kg. This study provides important information that the safeness including both the production of microparticles and the metallic elements should be considered for SCP lunch-boxes when in contact with food.

The ongoing exponential growth of human population poses a risk to sustainable development goals (SDGs). Unless we understand the drivers of this growth and inform policy development accordingly, SDGs would remain a dream. One of the old theories of population growth known as the Malthusian theory predicts that resource availability drives population growth to a certain time when population growth outrun resource availability, leading to all sort of crises known as Malthusian crisis. Although the link between economic growth and population has been widely investigated while testing the theory, little is known about environmental and social factors po-tentially driving population growth. Here, because of various crises of our time recalling the Malthusian crisis, we revisited the theory by fitting structural equation models to environmental, social and economic data collected over 30-year period in South Africa. None of the social varia-bles tested predicts population growth. Instead, we found that biodiversity (species protection index) correlates positively with population growth. Biodiversity provides various resources through ecosystem goods and services to human, thus supporting population growth as pre-dicted in the Malthusian theory. However, we also found that this population growth may lead to conservation conflict as we found that biodiversity habitat (wetland area) correlates negatively with population growth, thus raising the compromising effect of population growth on life on earth. What’s more, we found a significant link between economic growth measured as GDP and population growth, further supporting the Malthusian prediction. Overall, our study re-affirms the value of biodiversity to human and suggests that the Malthusian theory should continuously be tested with predictors other than economic.

The research presents the inter-comparison of atmospheric variables measured by 9 automatic meteorological stations. This set of data was compared with the measurements of other meteorological stations in order to standardize the values that must be adjusted when taken to different areas. The data of a set of a total of 9 GMX500, which measures conventional meteorological variables, and 10 WS100 sensors, which measures precipitation parameters. The automatic stations were set up at the Huancayo Observatory (Geophysical Institute of Peru) for a period of 5 months. The data set of GMX500 were evaluated comparing with the average of the 9 sensors and the WS100 was compared with a optical disdrometer Parsivel2. The temperature, pressure, relative humidity, wind speed, rainfall rate, and drop size distribution was evaluated. A pair of GMX500 sensors presented high data dispersion, it was found found that the errors came from a bad configuration; once this problem was solved, good agreement was archived, with low RMSE and high correlation. I was found that the WS100 sensors overestimate the precipitation with a percent bias close to 100% and the differences increase with the greater intensity of rain. The DSD retrieved by WS100 have unrealistic behavior with higher concentrations in diameters of 1 mm and 5 mm, in addition to a flattened curve.

Otolith morphology analysis is one of the main tools used for fish or fish stock identification. Moreover, otolith shape can also be used in fish dietary studies (stomach content) for the identi-fication of prey fishes and their size according to the relationship between fish and otolith sizes. In the present study, the relationship between fish length and otolith morphological dimensions was investigated for the sabre squirrelfish, Sargocentron spiniferum (Forsskål, 1775) (family: Hol-ocentridae). Samples of 185 fish were collected from the coast of the Red Sea, Egypt. To analyze the relationship between fish and otolith, otolith morphometric measurements (length, width, area, perimeter, weight, sulcus, and ostium) and shape factors (aspect ratio, compactness, form factor, rectangularity, roundness, ellipticity, squareness) describing outline shape were extracted using image analysis. Generalized linear models were applied for the relationship between body length and each otolith morphology feature. From the relationships between the total length of fish and fourteen morphology features, only otolith length, caudal length, and squareness were significantly correlated with fish size. Our results provide more information for the relationship between fish length and otolith morphometric features.

The present study was conducted the status of sea bass from Kokko and Kyuntone of The Gulf of Motttama Wetland (GoMW) area in Thanatpin Township in Bago Region Myanmar from September 2019 to August 2020. Fifty specimens were monthly collected, measured and weighed. Invoices of sea bass were collected for the depot and fish sellers by monthly. In Kokko, mean value of standard length and body weight were highest in March (32.70±1.58, 660.7±112.23). The mean value of standard length was peak in January (31.39±7.16) but peak of body weight was in March (963.24±280.86) in Kyuntone villages. The lowest mean value of standard length and body weight were found in June at both study areas. According to the invoice data revealed that monthly catch weight of sea bass is most abundance in October (829.92) kg in Kokko, (339.12) kg in Kyuntone. Based on price of relations to size group, small size C &lt; 300g (41%) was mostly abundance in Kokko and in Kyuntone small size C &lt; 300g (35%) was second abundance. Specimens were not landed in April and May. In June, young specimens were very rarely seen in both study sites. The important roles of wetland fishes, the economic valuation of GOMW in Myanmar and samples of fishing gear and value chain of sea bass in Myanmar was expressed in this study.

Various crystallite size estimation methods were used to analyze X-ray diffractograms of spherical cerium dioxide and donut-like titanium dioxide anatase nanoparticles aiming to evaluate their reliability and limitations. The microstructural parameters were estimated from Scherrer, Monshi, Williamson-Hall, and their variants: i) uniform deformation model, ii) uniform strain deformation model, and iii) uniform deformation energy density model, and also size-strain plot, and Halder-Wagner method. For that, and improved systematic Matlab code was developed to estimate the crystallite sizes and strain, and the linear regression analysis was used to compare all the models based on the coefficient of determination, where the Halder Wagner method gave the highest value (close to 1). Therefore, being the best candidate to fit the X-ray Diffraction data of metal-oxide nanoparticles. Advanced Rietveld was introduced for comparison purposes. Refined microstructural parameters were obtained from a nanostructured 40.5 nm Lanthanum hexaboride nanoparticles and correlated with the above estimation methods and transmission electron microscopy images. In addition, electron density modelling was also studied for final refined nanostructures, and μ-Raman spectra were recorded for each material estimating the mean crystallite size and comparing by means of a phonon confinement model.

Size effect on plain concrete specimens is well known and can be correctly captured when performing numerical simulations by using a well characterised softening function, but in the case of fibre reinforced concrete this is not directly applicable, since an only diagram cannot capture the material behaviour on elements with different size due to dependence of the orientation factor of the fibres with the size of the specimen. In previous works, the use of a trilinear softening diagram proved to be very convenient for reproducing fracture of polyolefin fibre reinforced concrete elements, but only if it is previously adapted for each specimen size. In this work, a predictive methodology is used to reproduce fracture of polyolefin fibre reinforced concrete specimens of different sizes under three-point bending. Fracture is reproduced by means of a well known embedded cohesive model, with a trilinear softening function that is defined specifically for each specimen size. The fundamental points of these softening functions are defined a priori by using empirical expressions proposed in past works, based on an extensive experimental background. Therefore, the numerical results are obtained in a predictive manner, and then compared with a previous experimental campaign, showing that this approach properly captures the size effect, although some values of the fundamental points in the trilinear diagram could be defined more accurately.

Otolith morphology analysis is one of the main tools used for fish or fish stock identification. Moreover, otolith shape can also be used in fish dietary studies (stomach content) for the identification of prey fishes and their size according to the relationship between fish and otolith sizes. In the present study, the relationship between fish length and otolith morphological dimensions was investigated for the sabre squirrelfish, Sargocentron spiniferum (Forsskål, 1775) (family: Holocentridae). Samples of 185 fish were collected from the coast of the Red Sea, Egypt. To analyze the relationship between fish and otolith, otolith morphometric measurements (length, width, area, perimeter, weight, sulcus, and ostium) and shape factors (aspect ratio, compactness, form factor, rectangularity, roundness, ellipticity, squareness) describing outline shape were extracted using image analysis. Generalized linear models were applied for the relationship between body length and each otolith morphology feature. From the relationships between the total length of fish and fourteen morphology features, only otolith length, caudal length, and squareness were significantly correlated with fish size. Our results provide more information for the relationship between fish length and otolith morphometric features.

In this paper, the definition of information entropy of Smoluchowski coagulation equation for Brownian motion is introduced based on coagulation probability. The expression of entropy is the function of geometric average particle volume and standard deviation with lognormal distribution assumption. The asymptotic solution with moment method shows that the entropy is a monotone increasing function of time, which is equivalence to the entropy based on particle size distribution. the result reveals that the present definition of entropy of Smoluchowski coagulation equation are inadequate because the particle average volume at equilibrium cannot be determined from the principle of maximum entropy. This provides a basis for further exploring the global properties of Smoluchowski coagulation equation.

This study aims to model grinding of a Polish slag and evaluate the particle size distributions of the products obtained after different grinding times. Then, selected products were alkali activated in order to investigate the effect of particle size on the compressive strength of the produced alkali activated materials (AAMs). Other parameters affecting alkali activation, i.e. temperature, curing and ageing time were also examined. Among the different mathematical models used to simulate the particle size distribution, Rosin-Rammler (RR) was found to be the most suitable. When piecewise regression analysis was applied to experimental data it was found that the particle size distribution of the slag products exhibits multi fractal character. In addition, grinding of slag exhibits non-first-order behavior and the reduction rate of each size is time dependent. The grinding rate and consequently the grinding efficiency increases when the particle size increases, but drops sharply near zero after prolonged grinding periods. Regarding alkali activation, it is deduced that among the parameters studied, particle size (and the respective specific surface area) of the raw slag product and curing temperature have the most noticeable impact on the compressive strength of the produced AAMs.

In this paper, we examine the mathematical and physical consistencies of the three primary couple stress theories: original Mindlin-Tiersten-Koiter couple stress theory (MTK-CST), modified couple stress theory (M-CST) and consistent couple stress theory (C-CST). As has been known for many years, MTK-CST suffers from some fundamental inconsistencies, such as the indeterminacy of the couple-stress tensor. Therefore, despite the fact that MTK-CST has a fundamental position in the evolution of size-dependent continuum mechanics, it is not a reliable theory within continuum mechanics, for example, in developing new size-dependent multi-physics formulations. We also observe that M-CST not only inherits all inconsistences from the original MTK-CST, but also suffers from new additional inconsistencies, such as the introduction of a new non-physical governing equation. These inconsistencies refute the claim of those who state that the couple-stress tensor may be chosen symmetric. Therefore, the apparent success of MTK-CST and M-CST in describing a size-effect for some problems, such as two-dimensional plate and beam bending, is not enough to justify these theories as suitable for general cases. In fact, the symmetric couple-stresses in M-CST create torsional or anticlastic deformation, not bending. On the other hand, C-CST, with a skew-symmetric couple-stress tensor, is the consistent continuum mechanics suitable for solving different size-dependent solid, fluid and multi-physics problems.

This research aims to determine the influence of the independent commissioners, audit committee, institutional ownership, firm size and leverage against the integrity of the financial reporting information. This research is quantitative research with the causal approach. This study uses secondary data and panel data regression analysis method. The research results prove that audit committee, institutional ownership and leverage effect on the integrity of the financial reporting information. But it does not prove that the independent commissioner and firm size effect on the integrity of the financial reporting information.

The relationship between city size, coastal land use and air temperature rise with distance from coast during summer day is analyzed using the meso-scale Weather Research & Forecasting (WRF) model in five coastal cities in Japan with different sizes and coastal land use (Tokyo, Osaka, Nagoya, Hiroshima and Sendai) and inland cities in Germany (Berlin, Essen and Karlsruhe). Air temperature increased as distance from the coast increased, reached its maximum, and then decreased slightly. In Nagoya and Sendai, the number of urban land use in coastal areas is less than the other three cities, where air temperature is a little lower. As a result, air temperature difference between coastal and inland urban area is small and the curve of air temperature rise is smaller than those in Tokyo and Osaka. In Sendai, air temperature in the inland urban area is the same as in the other cities, but air temperature in the coastal urban area is a little lower than the other cities, due to about one degree lower sea surface temperature influenced by the latitude. In three German cities, the urban boundary layer may not develop sufficiently because the fetch distance is not enough.

At room temperature, the indentation morphologies of crystalline copper with different grain size including nanocrystalline (NC), ultrafine-grained (UFG) and coarse-grained (CG) copper were studied by nanoindentation at the strain rate of 0.04/s without holding time at indentation depth of 2000 nm. As the grain size increasing, the height of the pile-up around the residual indentation increases and then has a slightly decrease in the CG Cu, While the area of the pile-up increases constantly. Our analysis has revealed that the dislocation motion and GB activities in the NC Cu, some cross- and multiple-slips dislocation insides the larger grain in the UFG Cu, and forest dislocations from the intragranular Frank-Read sources in the CG Cu, would directly induce these distinct pile-up effect.

The energy, momentum and the action associated with the time domain transition radiation fields are investigated. The results show that for a charged particle moving with speed $v$, the longitudinal momentum associated with the transition radiation is approximately equal to $E/c$ for values of $1-v/c$ smaller than about 10^-3 where $E$ is the total radiated energy and c is the speed of light in free space. The action of the transition radiation, defined as the product of the energy dissipated and the duration of the emission, increases as $1-v/c$ decreases and, for an electron, it becomes equal to $h/4\pi$ when $v=c-v_m$ where $v_m$ is the speed associated with the lowest energy state of a particle confined inside the universe and h is the Plank constant. Combining these results with Heisenberg’s uncertainty principle, an expression for the electronic charge based on other fundamental physical constants is derived. The best agreement between the experimentally observed electronic charge and the theoretical prediction is obtained when one assumes that the actual size of the universe is about 250 times larger than the visible universe.

The article presents the results of experimental studies on wound models made in ballistic gel casts and dressed with a vacuum dressing. Compared to previously published articles, the thesis presents quantitative parameters describing the behavior of wounds under the influence of vacuum. A significant reduction in wound volume was noted. This effect is independent of the size of the wound. The experimental studies results were supported by numerical calculations using the finite element method.

In this paper, we integrate the Finite Element Method (FEM) with orthogonal polynomial approximation in high-dimensional spaces to innovatively model the Moon’s surface gravity anomaly. Our aim is to approximate solutions to Laplace’s classical differential equations of gravity, employing classical Chebyshev polynomials as basis functions. Using classical Chebyshev polynomials as basis functions, the least-squares approximation was used to approximate discrete samples of the approximation function. These test functions provide an understanding of errors in approximation and corresponding errors due to differentiation and integration. These test functions provide an understanding of errors in approximation and corresponding errors due to differentiation and integration. The first application of this project is to substitute the globally-valid classical spherical harmonic series of approximations with locally-valid series of orthogonal polynomial approximations (i.e. using the FEM approach). With an error tolerance set at 10−9ms−2, we use this method to adapt the gravity model radially upwards from the lunar surface. The results showcase a need for a higher degree of approximation on and near the lunar surface, with the necessity decreasing as the radius increases. Notably, this method achieves a computational speedup of five orders of magnitude when applying the method to radial adaptation. More intrinsically, our second application involves using the methodology as an effective tool in solving boundary value problems. Specifically, we implement this approach to solve classical differential equations involved with high precision, long-term orbit propagation. This application provides a four-order of magnitude speedup in computational time while maintaining an error within the 10−10ms−2 error range for various orbit propagation tests. Alongside the advancements in orthogonal approximation theory, the FEM enables revolutionary speedups in orbit propagation without compromising accuracy.

This work focuses on the well-known issue of mass conservation in the context of the finite element technique for computational fluid dynamic simulations. Specifically, non-conventional finite element families for solving Navier-Stokes equations are investigated to address the mathematical constraint of incompressible flows. Raviart-Thomas finite elements are employed for the achievement of a discrete free-divergence velocity. In particular, the proposed algorithm projects the velocity field into the discrete free-divergence space by using the lowest-order Raviart-Thomas element. This decomposition is applied in the context of the projection method, a numerical algorithm employed for solving Navier-Stokes equations. Numerical examples validate the approach’s effectiveness, considering different types of computational grids. Additionally, the presented paper considers an interface advection problem using marker approximation, in the context of multiphase flow simulations. Numerical tests, equipped with an analytical velocity field for the surface advection, are presented to compare exact and non-exact divergence-free velocity interpolation.

Boeing and Airbus developed a special testing procedure to investigate the compressive response of laminates that have been impacted (following standards ASTM D 7137 and DIN 65561). This study focuses on both experimental and numerical analysis of Kevlar plates subjected to compression after impact. To ensure high quality and appropriate mechanical properties, the composite plates were manufactured using autoclaving. The DIN 65561 protocol was followed for all three test systems. Initially, ultrasonic C-scanning was performed on all plates before testing to confirm they were free of any significant defects arising from the manufacturing process. Subsequently, low-energy impact testing was conducted at levels ranging from 0 to 8 Joules. Three specimens were tested at each energy level. After the impact, all specimens underwent ultrasonic C-scanning again to assess the internal delamination damage caused by the impactor. Finally, both pristine and impacted specimens were subjected to compressive testing using the special jig specified in DIN 65561. The compressive impact strength results obtained from these tests were plotted against the delamination area measured by C-scanning. This data was then compared to results obtained from specimens with artificial damage. Semi-empirical equations were used to fit both sets of curves. The same procedure (impact testing, C-scanning, and data analysis) was repeated to investigate the relationship between impact energy and total delamination area. Lastly, finite element modeling was employed to predict the buckling stresses that develop under compression in the impacted systems studied. These modelling approaches have demonstrated good accuracy in reproducing experimental results for CAI tests.

Graphene foam prepared by chemical vapor deposition method is a promising thermal interfacial material. However, the thermal properties of graphene foam highly depend on the experimental fabrication conditions during the chemical vapor deposition process. Aiming to reveal how to prepare the appropriate graphene foam for the various thermal management scenarios, the influence of experimental conditions on thermal properties of graphene foam is investigated. Furthermore, the contribution of thermal conductivity and thermal radiation to the effective thermal coefficient of graphene foam is carried out for comparison. Research results show that, the porosity and the cross-section shape of struts of growth template are two critical factors to affect the thermal transport of graphene foam, especially with the increase of temperature. In addition, the deposition time of graphene determines the wall thickness and affects the thermal conductivity directly. The thermal radiation contributes more than thermal conductivity when the temperature climbs continuously. Comparatively, the effective thermal coefficient of graphene foam composite with high porosity and circular shape struts is much superior to others at high temperature. The research findings can provide important guidance for the graphene foam fabrication and its applications in the field of thermal management.

The use of tuning forks to measure fluid density and viscosity is widely employed in fields such as food, medicine, textiles, automobiles, petrochemicals, and deep drilling. The explicit analytical model based on Euler-Bernoulli cantilever beam theory for the relationship between tuning fork resonance characteristics and the density and viscosity of fluid is only applicable to the situation where the fluid viscous effect is very small. In this paper, the finite element method is used to simulate the influence of large variations in fluid density and viscosity on the resonance characteristic parameters (resonant frequency and quality factor) of the tuning fork. The numerical simulation results are compared with the analytical analysis results and experimental measurement results. Then, the sensitivity of tuning fork resonance characteristic parameters to fluid density and viscosity is studied. The results show that compared with the analytical results, the numerical simulation results have a higher degree of agreement with the experimental measurement results. The relative difference in resonant frequency is less than 2%, and the relative difference in quality factor is less than 4%. This indicates that the finite element method includes the influence of fluid viscosity on tuning fork resonance parameters, which is more in line with the actual conditions than the analytical model. Simulating and analyzing the sensitivity of the tuning fork to fluid density and viscosity by the finite element method, it is possible to consider the situation where fluid density and viscosity vary over a large range. Compared with experimental measurements, this method has higher efficiency and can significantly save time and economic costs. This study can overcome the limitation of existing explicit analytical models, which are only applicable when the viscous effects of the fluid are very small. It enables a more accurate simulation of the coupling vibration between tuning forks and fluids, thereby providing theoretical references for further optimizing tuning fork structural parameters to enhance the accuracy of measuring fluid characteristic parameters.

Lightweight component design is effectively achievable through the sandwich structures, many past research studies in the aerospace and racing sectors (since 1920s) has proven it. To extend their application into automotive and other transport industries, the manufacturing cycle times must be reduced. This can be achieved by thermoplastic sandwich materials of continuous fibre-reinforced thermoplastic (CFRTP) cover layers and thermoplastic honeycomb cores. To widespread the application of flat thermoplastic-based sandwich panels into complex parts, a novel forming technology was developed by the Fraunhofer Institute of Microstructure of Materials and Systems (IMWS). For an increase in reproducibility of the sandwich component production and a decrease in manufacturing defects, numerical modelling methods and experimental validation are needed. The finite element (FE) modelling of this thermoforming process is a thermo-mechanical assignment with all three: material, geometry, and boundary non-linearities. In the scope of this work, the material behavior of different sandwich components (cover layers, honeycomb core, interface) under thermo-mechanical loads is characterized in detail, and a complex numerical model is developed to describe the thermoforming process of thermoplastic-based sandwich laminate. The critical forming condition like wrinkling that occurs due to friction in a sandwich or poor intra-ply shear in cross-ply studied, validated, and optimized. A thermoplastic sandwich made of polypropylene (PP) honeycomb core and polypropylene glass fibre (PP/GF) cross-ply as cover layers was used for this study, and numerical modelling was executed in LS-DYNA software.

The insufficient toughness of concrete can lead to the occurrence of crack expansion, ultimately resulting in a decline in the physical and mechanical properties such as bearing capacity and deformation characteristics of structural components. In severe cases, this may lead to brittle failure, where the entire structure and system fail suddenly without significant deformation after being stressed. Additionally, during the process of shear and bending failure of reinforced concrete beams, the cracks generated on the side of the beam are mostly I-II composite cracks. Considering the material nonlinearity and geometric irregularity of reinforced concrete, it is of great significance to study the dynamic evolution law of crack expansion in reinforced concrete members. Based on experimental data, this paper aims to utilize the nonlinear finite element simulation software Abaqus to conduct finite element simulations of crack expansion in simple supported reinforced concrete beams. By accurately controlling the constitutive curves of concrete and reinforcement materials, the design of seismic performance of structural members can be enhanced, thereby making essential contributions to the preliminary analysis of actual crack control engineering. The nonlinear finite element results indicate that the joint cracks of the frame with the floor slab primarily manifest as flexural cracks, with the concrete damage degree of the floor slab being higher than that of the beam. This finding underscores the importance of considering the behavior of concrete and reinforcement materials in designing for seismic performance and crack control in actual engineering applications.

In this study, the autofrettage method, which is used to increase the durability of cylindrical parts, was applied to a barrel made of steel material according to the AISI 4340 standard. Assuming that the barrel works continuously under the pressure of 400 MPa, optimum autofrettage was performed. The stresses occurring on the barrel before and after autofretage were calculated. Additionally, analytical equivalent stress values (Von-Mises) formed on the part's wall were compared with numerical analysis results obtained with a commercial finite element program ANSYS®, and their compatibility was examined. As a result of the calculations and analysis performed, it was observed that autofretage has positive effect on increasing the pressure carrying capacity of the barrel. After autofrettage the cylindrical part, it was determined that the Von-Mises stress values formed in the part wall changed and these stresses took the lowest value at a point (elastic-plastic interface). It has been evaluated that this point gives the optimal autofretage pressure value for a certain operating pressure. After the autofrettage application, it was determined that the Von-Mises Stress value in the barrel wall decreased by 25.27 % and the pressure carrying capacity of the barrel increased without any design or dimensional change. It has been seen that the analytical and numerical analysis results are consistent with each other, and it is expected that this study will guide and contribute to the studies to be conducted on increasing the strength or lightening the weight of the parts.

In order to examine the impact of geometric configuration of the human vocal tract on the redistribution of acoustic energy in the frequency spectrum, it is necessary to assemble computation models, which facilitate simple modification of the model’s geometric characteristics. This article describes how the human vocal tract model was constructed using so-called super-elements using the improved reduced system method. The mentioned procedure allows using such a model for demanding optimization calculations, for which the model is modified on the super-element level. Furthermore, the article presents an alternative approach, in which an isoparametric element of a higher degree polynomial was derived. Both approaches were compared and used to find the geometric configuration of the human vocal tract amplifying acoustic energy values on the frequency spectrum to around 3kHz.

In recent years, with the increase in maritime trade, the necessity of increasing the capacities of the ports has emerged. However, while it is planned to increase the capacities of the ports, it is important that the port continues to operate at the same time. In this respect, the old port structures should not be damaged during the capacity increase. In this study, the strengthening of a port in Guinea is discussed as a case study. In the study, the existing quay wall was evaluated, and geotechnical and structural alternatives of the new structure to be built for capacity increase were evaluated. A combined system was designed as a pile foundation and a reinforced foundation with plastic piles so as not to damage the existing quay wall. The pile capacities obtained as a result of the analyses were verified by loading tests.

This work introduces a novel numerical method designed to address three-dimensional unsteady free surface flows incorporating integral viscoelastic constitutive equations, specifically, the K-BKZ-PSM (Kaye–Bernstein, Kearsley, Zapas - Papanastasiou, Scriven, Macosko) model. The new proposed methodology employs a second-order finite difference approach along with the deformation fields method to solve the integral constitutive equation, and the marker-particle method (known as \emph{Marker-and-Cell}) to accurately capture the evolution of the fluid's free surface. The newly developed numerical method has proven its effectiveness in handling complex fluid flow scenarios, including confined flows and extrudate swell simulations of Boger fluids. Furthermore, a new semi-analytical solution for velocity and stress fields is derived, considering fully developed flows of a K-BKZ-PSM fluid in a pipe.

This paper presents a finite element analysis of the bi-directional orthogonal model, which incorporates individual crack strain separation and tracking. The objective of the research is to expand the current shear friction model to manage bi-directional cracking at any angle, allowing for a more universal model that can be applied to intricate structures and non-proportional loading cases. The proposed model was initially developed as a total strain-based model, with the assumption that crack strains are equivalent to total strains, but was subsequently recalculated to improve accuracy by separating crack strains from total strains. Furthermore, a separate crack strain formulation was created to account for strains in the concrete's uncracked portions and locked-in crack strains. The article then discusses the testing of various convergence methods and loading programs to achieve high convergence. Comparative analyses of the generalized shear friction model with other models for crack orientation and loading cases similar to those of a reinforced concrete membrane are also presented. The MATLAB program successfully applied the bi-directional cracking model for one finite element under a uniform cyclical strain state, using a secant stiffness formulation.

Crystallization often occurs in the laser welding of amorphous alloys, reducing the amorphous alloys’ properties. So, it is necessary to simulate the temperature field curve of the welding area by computer and then determine the power and laser moving speed of laser welding. In this paper, the temperature field curve of Zr41.2Ti13.8Cu12.5Ni10Be22.5(Vit1) amorphous alloy in laser welding is obtained by finite element analysis. The continuous heating curve (CHT) of Vit1 is fitted by the Vogel-Fulcher-Tammann (VFT) equation and the Kissinger equation. If the temperature field curve intersects with the CHT curve, crystallization occurs. The experiment results show that the VFT equation can be used to predict the crystallization of Vit1 better in laser welding. The tem-perature and welding time are increased by using low welding speed. Therefore, the temperature of the weld zone cannot fall in time, resulting intersection of the temperature field curve and the CHT curve. So, crystallization can be avoided if the welding speed is controlled within a rea-sonable range, and the highest temperature is kept under the CHT curve.

The successful handling of large semiconductor wafers is crucial for scaling up their production. Early-stage warpage control allows to prevent undesirable asymmetric warpage, known as wafer bifurcation or buckling. Indeed, even in a gravity-free environment, thinning an 8" or 12" semiconductor wafer can result in warpage and bifurcation. To mitigate this issue, the taiko method, which involves creating a thicker ring region around the rim of the wafer, has been widely used. Previous research has focused on the theoretical factors affecting the warpage of a backside metalized taiko wafer. This work extends the case to a front-side metalized taiko wafer and introduces the concept of the equivalent thickness of a taiko wafer. The equivalent thickness of a taiko wafer, influenced by the ring region, lies in between the thickness of the central region and that of the annular region. Because of the limited number of taiko wafers that can be produced on a production line, modelling can be beneficial. In this work we compared the results of a developed analytical model with those obtained from a finite element analysis (FEA) approach with ANSYSY® software to model the equivalent thickness of a taiko wafer. We investigated the curvature as a function of the stress of the metal layer, considering key design factors such as the substrate region thickness, the thickness of the thin metal film, the step height, and the width of the ring region. By systematically varying the thickness of the central region of the taiko wafer, we explored the curvature as a function of stress induced by thermal load in the linear regime and determined the slopes in the linear region of the curvature vs. stress curves. The aim of this study is to identify regularities and similarities with the Stoney equation and investigate the validity of the analytical approach for the case of a taiko substrate. It results that there is a good agreement between the analytical model of a taiko wafer and the numerical analysis gained by the FEA methods.

Wearable thermoelectric generators (w-TEGs) convert thermal energy into electrical energy to realize self-powering of intelligent electronic devices, thus reducing the burden of battery replacement and charging, and improving the usage time and efficiency of electronic devices. Through finite element simulation, this study successfully designed high-performance thermoelectric generator and made it into wearable thermoelectric module by adopting “rigid device - flexible connection” method. It was found that higher convective heat transfer coefficient on cold-end leads to larger effective temperature difference and better power generation performance of device in typical wearable scenario. Meanwhile, at same convective heat transfer coefficient on the cold-end, longer TE leg length leads to larger temperature difference established at both ends of device, larger device output power and open-circuit voltage. However, when the convective heat transfer coefficient increases to a certain level, optimization effect of increasing TE leg length on device power generation performance will gradually diminish. For devices with fixed temperature difference between two ends, longer TE leg length leads to higher resistance of TEG, resulting in lower device output power but slight increase in open-circuit voltage. Finally, sixteen 16×4×2 mm2 TEGs (L=1.38 mm, W=0.6 mm) and two modules were fabricated and tested. At hot end temperature Th=33 ℃ and cold end temperature Tc=30 ℃, the actual maximum output power Pout of TEG is about 0.2 mW, and the actual maximum output power Pout of TEG module is about 1.602 mW, which is highly consistent with the simulated value. This work brings great convenience to research and development of wearable thermoelectric modules and provides new, environmentally friendly and efficient power solution for wearable devices.

The link of fracture analysis of large ships is an essential part of the structural safety of ships. However, the finite element analysis of large structure according to the traditional method not only has high requirements on the computer, but also the influence of the mesh encryption at special locations makes further requirements on the accuracy of the ship. In this paper, based on the extended finite element method (XFEM) and the multi-point constraint method (MPC), the dynamic crack expansion process of the rectangular plate containing cracks under the multi-scale model is comparatively studied by using ABAQUS simulation software Finally, the applicability of the method is verified by applying the multi-scale model of ship nodes. The results show that the computational effort of the multi-scale model is significantly reduced with the same accuracy and allowable error, which proves the accuracy and efficiency of the method.

This paper presents the experimental and numerical studies of the vertical stress distribution beneath the centerline of circular footings resting on the sand. Vertical stress values due to circular load in medium-dense sand were measured using soil stress transducers. Reduced-scale laboratory model tests were carried out in a square-shaped test box and vertical stresses were measured at the centerline of the circular footing at different depths of the sand. In order to determine the effect of footing width on vertical stress distribution, laboratory experiments were performed on circular footings of different diameters. In addition, a series of finite element analyses was carried out on the test model to validate the findings of the experimental study. In the numerical analysis, the sand was modeled as a non-linear elastoplastic material. The analyses were performed using the finite element method with two-dimensional axisymmetric and three-dimensional conditions. The results obtained from laboratory model tests and numerical analysis were compared with the vertical stress values obtained from the theoretical solution in the literature. Vertical stress distribution in horizontal planes at any depth from the footing base shows the same characteristic form in all methods. However, some differences were observed between experimental, numerical, and theoretical results and discussed.

This article presents a case study on the structural assessment of a reinforced concrete (RC) foundation exposed to low temperatures. The foundation supports a 19,500 m³-capacity tank with low-temperature (-89°C) ethane. Icing and bubbling were observed on the tank’s surface soon after it started operations. Condensation was also observed at the bottom of the 0.8 m-depth RC slab, which raised concerns about the structural condition of the concrete. This study provides details of the field and analytical investigations conducted to assess the structural condition of the foundation. Heat transfer finite element (FE) analyses were performed to examine the concrete sections subjected to low temperatures. It was found that the ethane leakage produced a low temperature on the top side of the concrete foundation of +9.7°C. Overall, the temperatures calculated by the FE analyses were in good agreement with actual field measurements, within a ±5% accuracy. The simplified heat transfer equation for porous media used in this study was sufficiently accurate to model the effects of the ethane leakage in the concrete foundation, provided the ambient temperature at the site is taken into account in the analysis. The results also confirm that reinforcing bars can be neglected in the thermal analysis of massive concrete slabs. The results from the field measurements and FE analyses confirmed that the structural integrity of the RC foundation was never compromised. The approaches, methods and techniques discussed in this article are deemed suitable to solve the practical and scientific challenges involved in the structural assessment and repairs of large special structures. Accordingly, they can serve as useful reference and guidance for engineers and practitioners working in the field of forensic engineering.

The Gol'denveizer problem of a torus was studied analytically by Audoly and Pomeau (2002), and the accuracy of the Audoly and Pomeau linear law was confirmed numerically by Sun (2021). However, the law does not include the major radius R of the torus. To find the influence of the major radius, we used finite element numerical simulation to simulate different cases, and we propose a modified Audoly and Pomeau linear law for vertical deformation, which includes R. A linear law of horizontal deformation is presented as well. Our studies show that the Audoly and Pomeau linear law has high accuracy. With modified vertical and horizontal deformation, a displacement-compatible relation between them is formulated.

Orofacial injuries are common occurrences during contact sports activities; however, there is an absence of data regarding the performance of hybrid occlusal splint mouthguards, especially during compressive loading. To evaluate the total deformation and stress concentration, a skull model was selected and duplicated to receive two different designs of mouthguard devices: one model received a conventional custom-made mouthguard (MG) with 4-mm thickness and the other received a novel hybrid occlusal splint-mouthguard (HMG) with the same thickness. Both models were subdivided into finite elements. The frictionless contacts were used, and a nonlinear analysis was performed simulating the compressive loading in occlusion. The results were presented in von-Mises stress maps (MPa) and Total Deformation (mm). A higher stress concentration in teeth was observed for the model with the conventional MG, while the HMG design displayed a promising mechanical response with lower stress magnitude. The HMG de-sign displayed a higher magnitude of stress on its occlusal portion than the MG design. The hybrid mouthguard (HMG) reduced (1) jaw displacement during chewing and (2) the generated stresses in maxil-lary and mandibular teeth.

Energy efficiency and leakage magnetic field (LMF) are two important issues in electric vehicle inductive chargers. In this work, the maximum achievable coil efficiency and the corresponding LMF strength are formulated as functions of hardware parameters, and figure of merits (FOM) are proposed for assessing the efficiency and LMF performance of the coil assembly pair. The impacts of the coil assemblies’ geometric parameters on both FOMs are examined with the aid of finite element analysis (FEA), and measures to improve the FOMs are extracted from FEA results. A coil assembly pair is manually optimized within given dimensional limits. Compared with the initial design, the optimized one achieves higher efficiency and lower LMF strength while consuming less copper. The performance improvement is verified by FEA results and experimental data measured on an 85 kHz electric vehicle inductive charger prototype. The key measures for coil assembly optimization are summarized.

Steel is one of the essential materials in the world's civilization. It is essential to produce many products such as pipelines, mechanical elements in machines, vehicles, profiles, and beam sections for buildings in many industries. Until the '50s of the 20th century, steel products required a complex process known as ingot casting; for years, steelmakers focused on developing and simplifying this process. The result was the con-tinuous casting process (CCP); it is the most productive method to produce steel. The CCP allows producing significant volumes of steel sections without interruption and is more productive than the formal ingot casting process. The CCP begins by transferring the liquid steel from the steel-ladle to a tundish. This tundish or vessel distributes the liquid steel, by flowing through its volume, to one or more strands having wa-ter-cooled copper molds. The mold is the primary cooling system, PCS, solidifying a steel shell to withstand a liquid core and its friction forces with the mold wall. Further down the mold, the rolls drive the steel section in the SCS. Here the steel section is cooled, solidifying the remaining liquid core, by sprays placed in every cooling segment all around the billet and along the curved section of the machine. Finally, the steel strand goes towards a horizontal-straight free-spray zone, losing heat by radiation mechanism, where the billet cools down further to total solidification. A moving torch cutting-scissor splits the billet to the desired length at the end of this heat-radiant zone.