Search

Transformers are widely used in natural language processing due to their ability to model longer-term dependencies in text. Although these models achieve state-of-the-art performance for many language related tasks, their applicability outside of the natural language processing field has been minimal. In this work, we propose the use of transformer models for the prediction of dynamical systems representative of physical phenomena. The use of Koopman based embeddings provide a unique and powerful method for projecting any dynamical system into a vector representation which can then be predicted by a transformer. The proposed model is able to accurately predict various dynamical systems and outperform classical methods that are commonly used in the scientific machine learning literature., 22 pages, 14 figures, 3 appendices

Mechanical sorting plays a pivotal role in current municipal solid waste management systems for resource recovery. However, material recovery facilities, generally face several challenges in meeting quality standards for multiple waste fractions. Improving these facilities requires a better understanding of municipal solid waste physical characteristics, since they are directly targeted by mechanical sorting unit operations. Three waste physical properties (bulk density, particle size and shape factor) were characterized for several recyclable materials. Narrow ranges of densities were observed for similar waste materials, while the particle size distributions were found to vary widely. Statistical parameters were determined for these two properties. A novel approach, based on the void fraction of a waste item, is proposed to quantify the shape factor. Potential applications of the characterization results for improving mechanical sorting are demonstrated through the analysis of the recovery of corrugated cardboards and multilayer cardboards in a material recovery facility.

PURPOSE Detectors for positron emission tomography (PET) typically use two types of scintillation crystals, pixelated or monolithic. A variant of these types of scintillators are the so-called semi-monolithic crystals. They consist of a monolithic crystal segmented in one direction in pieces called slabs. These scintillators have the potential to successfully combine the benefits of pixelated and monolithic configurations, providing good timing and spatial resolutions as well as the capacity to decode the depth of interaction (DOI) information. In this work, the timing performance of a detector based on semi-monolithic crystals was studied in depth. The energy response was also evaluated. METHODS The semi-monolithic detector consists of 1 × 24 LYSO slabs of 25.4 × 12 × 0.95 mm3 each. The bottom surface of the slabs is coupled to an array of 8 × 8 silicon photomultipliers (SiPMs) of 3 × 3 mm2 active area, 50 μm cell size and 3.2 mm pitch. The 64 output signals were independently readout by the TOFPET2 ASIC. In order to achieve the best coincidence time resolution (CTR), four different time walk corrections were tested. Additional work investigated the best method of combining the timestamps belonging to the same event. RESULTS The resolvability of the slabs in the measured flood maps improves with the thickness of a light guide placed in between the scintillators and photosensors. The energy resolution does not change significantly with values as good as 13.7%. Regarding the CTR, values of 335.8, 363, 369.8, and 402.5 ps have been obtained for the whole detector for no light guide, 0.5, 1.0, and 1.5 mm thickness light guide cases, respectively. These values further improve to 276.1, 302.6, 305.6 and 336.2 ps, respectively, when energy-weighted averaging of timestamps is applied. CONCLUSIONS We have shown both an excellent timing resolution and good energy resolution for a PET detector based on semi-monolithic crystals. The use of light guides of different thicknesses does not significantly affect the energy resolution of the whole detector, but the timing capabilities slightly worsen with the increasing thickness of the light guide.

The pathologies of parathyroid glands are widespread among endocrine system diseases, excluding diabetes and thyroid pathology. There are only two methods that are used to treat hyperparathyroidisms, such as surgery and conservative therapy. However, transracial thermal destruction methods (ablation) have recently appeared in clinical practice. The methods have good precision and connect with physical phenomena, such as interaction laser, radiofrequency, microwave, and HIFU irradiation with bio substance. The review is dedicated to critically analyze the modern methods for local thermal destruction of the hyper-functioning parathyroid glands. The review includes data from randomized clinical trials from 2012 to 2021. The studies were from Google Scholar and Pubmed with a total number of 1,938 patients (laser ablation ― 216 patients, radiofrequency ablation ― 225, microwave ablation ― 1467, high-density ultrasound ablation ― 30 patients). Recommendations methods of thermal destruction application were obtained during the review. Furthermore, we have designed some algorithms for hyperparathyroidism treatment. Moreover, thermal destruction methods were observed. There are four modern methods of thermal destruction which have been analyzed like alternatives to surgery. Each of them has advantages and disadvantages, its profile of safety and effectiveness. After processing information from a proven database, the most popular among specialists is methods of microwave ablation. However, laser ablation is more effective than other ways.

Relative binding free energy calculations in drug design are becoming a useful tool in facilitating lead binding affinity optimization in a cost- and time-efficient manner. However, they have been limited by technical challenges such as the manual creation of large numbers of input files to set up, run, and analyze free energy simulations. In this Application Note, we describe FEPrepare, a novel web-based tool, which automates the setup procedure for relative binding FEP calculations for the dual-topology scheme of NAMD, one of the major MD engines, using OPLS-AA force field topology and parameter files. FEPrepare provides the user with all necessary files needed to run a FEP/MD simulation with NAMD. FEPrepare can be accessed and used at https://feprepare.vi-seem.eu/.

Purpose To assess if single shot acquisitions with solid-state dosimeters as well as Robson’s method could replace ionization chambers for tube output and HVL measurements, saving medical physicists time. Material and methods The energy responses of 4 solid-state dosimeters with automatic calculation of HVL were compared to ionization chamber measurements. Five anode/filter combinations were tested: Mo/Mo, Mo/Rh, Rh/Rh, W/Rh and W/Ag, from 24kVp to 35kVp. Tube output was measured free in air. HVL was measured using the solid-state dosimeters (single-shot acquisition), then manually with aluminum sheets and finally using the parametrization method of Robson. Results Deviations in tube output and HVL related to energy response in SSD were small in the 25–32 kVp range, and for tube output typically within 3%. Extrapolation using the Robson parametrization was within 5%, except for one device and for all W/Rh. Deviations of the HVL using the single shot approach were within 10% of the gold standard data. Larger deviations were found at the extreme tube voltages of 24kVp and 35kVp (maximum of 24%). Conclusion With the assumption that deviations in tube output of 5% and for HVL of 10% are acceptable, all tested solid state dosimeters met this criterion in the tube voltage range of 26kVp to 32kVp. Robson’s method worked well for the spectra for which the method was developed, making both alternative approaches trustworthy for routine quality assurance purposes.

Protein structure refinement is the last step in protein structure prediction pipelines. Physics-based refinement via molecular dynamics (MD) simulations has made significant progress during recent years. During CASP14, we tested a new refinement protocol based on an improved sampling strategy via MD simulations. MD simulations were carried out at an elevated temperature (360 K). An optimized use of biasing restraints and the use of multiple starting models led to enhanced sampling. The new protocol generally improved the model quality. In comparison with our previous protocols, the CASP14 protocol showed clear improvements. Our approach was successful with most initial models, many based on deep learning methods. However, we found that our approach was not able to refine machine-learning models from the AlphaFold2 group, often decreasing already high initial qualities. To better understand the role of refinement given new types of models based on machine-learning, a detailed analysis via MD simulations and Markov state modeling is presented here. We continue to find that MD-based refinement has the potential to improve AI predictions. We also identified several practical issues that make it difficult to realize that potential. Increasingly important is the consideration of inter-domain and oligomeric contacts in simulations; the presence of large kinetic barriers in refinement pathways also continues to present challenges. Finally, we provide a perspective on how physics-based refinement could continue to play a role in the future for improving initial predictions based on machine learning-based methods.

The COVID-19 pandemic is well into its second year, but countries are only beginning to grapple with the lasting health crisis. In March, a UK consortium reported that 1 in 5 people who were hospitalized with the disease had a new disability after discharge1. A large US study found similar effects for both hospitalized and non-hospitalized people2. Among adults who were not hospitalized, 1 in 10 have ongoing symptoms 12 weeks after a positive test3. Treatment services for the long-term consequences of COVID-19 are already having to be absorbed into health and care systems urgently. Tackling this requires a much clearer picture of the burden of the disease than currently exists.

This study examined whether an inertial measurement unit (IMU), in combination with machine learning, could accurately predict two indirect measures of bowling intensity through ball release speed (BRS) and perceived intensity zone (PIZ). One IMU was attached to the thoracic back of 44 fast bowlers. Each participant bowled 36 deliveries at two different PIZ zones (Zone 1 = 24 deliveries at 70% to 85% of maximum perceived bowling effort; Zone 2 = 12 deliveries at 100% of maximum perceived bowling effort) in a random order. IMU data (sampling rate = 250 Hz) were downsampled to 125 Hz, 50 Hz, and 25 Hz to determine if model accuracy was affected by the sampling frequency. Data were analysed using four machine learning models. A two-way repeated-measures ANOVA was used to compare the mean absolute error (MAE) and accuracy scores (separately) across the four models and four sampling frequencies. Gradient boosting models were shown to be the most consistent at measuring BRS (MAE = 3.61 km/h) and PIZ (F-score = 88%) across all sampling frequencies. This method could be used to measure BRS and PIZ which may contribute to a better understanding of overall bowling load which may help to reduce injuries.

In this work, a new high-volume, continuous particle separation device that separates based upon size and charge is described. Two continuous flow-electrical-split-flow lateral transport thin (Fl-El-SPLITT) device architectures (a platinum electrode on a porous membrane and a porous graphite electrode under a membrane) were developed and shown to improve particle separations over a purely electrical-SPLITT device. The graphite FL-El-SPLITT device architecture achieved the best separation of approximately 60% of small (28 nm) vs large (1000 nm) polystyrene particles. Fl-El-SPLITT (platinum) achieved a 75% separation on a single pass using these same particles. Fl-El-SPLITT (platinum) achieved a moderate 26% continuous separation of U87 glioma cell-derived small extracellular vesicles (EVs) from medium EVs. Control parameter testing showed that El-SPLITT continuously directed particle motility within a channel to exit a selected port based upon the applied voltage using either direct current or alternating current. The transition from one port to the other was dependent upon the voltage applied. Both large and small polystyrene particles transitioned together rather than separating at each of the applied voltages. These data present the first ever validation of El-SPLITT in continuous versus batch format. The Fl-El-SPLITT device architecture, monitoring, and electrical and fluid interfacing systems are described in detail for the first time. Capabilities afforded to the system by the flow addition include enhanced particle separation as well as the ability to filter out small particles or desalinate fluids. High-throughput continuous separations based upon electrophoretic mobility will be streamlined by this new technique that combines electrical and flow fields into a single device.

Because of the wealth of fascinating physical phenomena observed in topological insulators (TIs), their exciting properties have been intensively investigated for electronic and optoelectronic appl...

Flexible and transparent artificial synapses with extremely low energy consumption have potential for use in brain-like neuromorphic electronics. However, most of the transparent materials for flexible memristive artificial synapses were reported to show picojoule-scale high energy consumption with kiloohm-scale low resistance, which limits the scalability for parallel operation. Here, we report on a flexible memristive artificial synapse based on Cs3Cu2I5 with energy consumption as low as 10.48 aJ (= 10.48 × 10−18 J) μm−2 and resistance as high as 243 MΩ for writing pulses. Interface-type resistive switching at the Schottky junction between p-type Cu3Cs2I5 and Au is verified, where migration of iodide vacancies and asymmetric carrier transport owing to the effective hole mass is three times heavier than effective electron mass are found to play critical roles in controlling the conductance, leading to high resistance. There was little difference in synaptic weight updates with high linearity and 250 states before and after bending the flexible device. Moreover, the MNIST-based recognition rate of over 90% is maintained upon bending, indicative of a promising candidate for highly efficient flexible artificial synapses.

This work presents an analysis of the temperature influence on the performance of a lateral thin-film SOI PIN photodiodes when illuminated by low wavelengths, in the range of blue and ultra-violet (UV). Experimental measurements performed from 100K to 400K showed that the optical responsitivity of SOI PIN photodetectors is affected by temperature change, being reduced at low and moderately high temperatures. Two-dimensional numerical simulations showed the same trends as in the experimental results, and were used both to investigate the physical phenomena responsible for the observed behavior as a function of the temperature as well as to predict the influence of silicon film thickness downscaling on the photodetector performance.

BACKGROUND AND OBJECTIVES The purpose of this ex vivo study is to investigate whether it is possible to pre-determine and set the optimal separation times for the SWEEPS Er:YAG laser pulses pair during laser-assisted irrigation of endodontic root canals based on known lateral dimensions of the endodontic access cavities of different types of teeth. STUDY DESIGN/MATERIALS AND METHODS As the optimal SWEEPS laser pulse pair separation for enhanced shockwave generation depends on the life-cycle of a single-pulse bubble, measurements of the oscillation time T B of the Er:YAG laser-generated bubble were made in 23 different endodontic access cavities of different types of teeth progressively widened in three different steps, into larger cavities, for a total of 69 cavities of different shapes and sizes. Different fiber-tip geometries (flat and radial), laser pulse energies (10 mJ and 20 mJ) and depth of fiber-tip insertion (2 mm and 4 mm) were also investigated. The obtained data were then analyzed using the reported relationship between the bubble oscillation time and the diameter of a cylindrically shaped cavity. RESULTS A good fit to the relation analogue for ideal cylindrical cavities was found by taking the characteristic diameter of the access cavity to be represented by the cavity diameter either in the mesiodistal (D min ) or buccolingual (D max ) direction, or alternatively by the average of the two diameters (D ave ). The best fit was obtained for D min (R 2 = 0.73) followed in order by D ave (R 2 = 0.71) and D max (R 2 = 0.63). CONCLUSION In spite of the endodontic cavities being non-cylindrical and of varied shape and size, the bubble oscillation time T B and the corresponding optimal SWEEPS separation time can be well predicted using a single characteristic dimension of the access cavity. This finding enables a simple and practical method for determining optimal conditions for shock wave generation and enhanced photodynamic streaming in differently shaped and sized root canals, leading to improved treatment efficacy and safety of root canal irrigation. Lasers Surg. Med. 2020. © 2020 The Authors. Lasers in Surgery and Medicine published by Wiley Periodicals LLC.

Information recovery from incomplete measurements, typically performed by a numerical means, is beneficial in a variety of classical and quantum signal processing. Random and sparse sampling with nanophotonic and light scattering approaches has received attention to overcome the hardware limitations of conventional spectrometers and hyperspectral imagers but requires high-precision nanofabrications and bulky media. We report a simple spectral information processing scheme in which light transport through an Anderson-localized medium serves as an entropy source for compressive sampling directly in the frequency domain. As implied by the "lustrous" reflection originating from the exquisite multilayered nanostructures, a pearl (or mother-of-pearl) allows us to exploit the spatial and spectral intensity fluctuations originating from strong light localization for extracting salient spectral information with a compact and thin form factor. Pearl-inspired light localization in low-dimensional structures can offer an alternative of spectral information processing by hybridizing digital and physical properties at a material level.

Impedance spectroscopy is a measurement method applied in many fields of science and technology, such as electrochemistry, material science, biology and medicine [1]. For impedance spectroscopy (IS), knowledge from several fields of science and technology about measurement procedures, electrochemical and physical phenomena, modeling, signal processing and electronic systems is indispensable. For this purpose, the IEEE Instrumentation and Measurement Society launched a technical committee on this field, acting as a platform for promoting experience exchange and networking between scientists and experts from industry. It serves to share the knowledge and experience between scientists and to support new comers aiming to specialize in the field of impedance spectroscopy.

Currently, Computational Fluid Dynamics (CFD) was utilized to predict the performance, geometry optimization or physical phenomena of a breastshot waterwheel. The CFD method requires the turbulent model to predict the turbulent flow. However, until now there is special attention on the effective turbulent model used in the analysis of breastshot waterwheel. This study is to identify the suitable turbulence model for a breatshot waterwheel. The two turbulence models investigated are: standard k-epsilon model and shear stress transport (SST) k-omega. Pressure based and one degrees of freedom (one-DoF) feature was used in this case with 75 Nm, 150 Nm, 225 Nm and 300 Nm as preloads. Based on the results, the standard k-epsilon model gave similar result with the SST k-omega model. Therefore, the simulation for breastshot waterwheel will be efficient if using the standard k-epsilon model because it requires lower computational power than the SST k-omega model. However, to study about physical phenomenon, the SST k-omega model is recommend.

To Perform reliably and consistently over sustained periods of time, large-scale automation critically relies on computer simulation. Simulation allows us and supervisory AI to effectively design, validate, and continuously improve complex processes, and helps practitioners to gain insight into the operation and justify future investments. While numerous successful applications of simulation in industry exist, such as circuit simulation, finite element methods, and computeraided design (CAD), state-of-the-art simulators fall short of accurately modeling physical phenomena, such as friction, impact, and deformation.

Introduction: Hydration status is considered a parameter likely to influence the risk of decompression sickness (DCS), but scientific evidence is scarce and conflicting. This experiment aimed to analyse the influence of pre-hydration on DCS occurrence in a rat model. Methods: Intra-peritoneal injections of saline solution were administered to rats (NaCl 0.9% 0 ml (Control), 0.1 ml (Group 1), or 1 ml·100g-1 body mass (Group 2) at each of 24 h, 12 h, and 30 min prior to simulated air dives (45 min at 1,010 kPa; compression and decompression rates 101 kPa·min-1; stops 5 min at 202 kPa, 5 min at 160 kPa, 10 min at 130 kPa). Evaluation of DCS occurrence and severity was made after decompression. Results: Pre-dive hydration reduced severe DCS from 47% (Control) to 29% (Group 1) and 0% (Group 2), and increased the proportion of animals without any signs of DCS from 40 (Control) to 57% (Group 1) and 93% (Group 2); Chi2 P = 0.041. Conclusions: This experiment demonstrated that pre-hydration can drastically reduce the DCS occurrence in an animal model. In the context of scuba diving, this result highlights the importance of elucidating the mechanisms linking hydration status and DCS risk.

Many important physical phenomena involve subtle signals that are difficult to observe with the unaided eye, yet visualizing them can be very informative. Current motion magnification techniques can reveal these small temporal variations in video, but require precise prior knowledge about the target signal, and cannot deal with interference motions at a similar frequency. We present DeepMag, an end-to-end deep neural video-processing framework based on gradient ascent that enables automated magnification of subtle color and motion signals from a specific source, even in the presence of large motions of various velocities. The advantages of DeepMag are highlighted via the task of video-based physiological visualization. Through systematic quantitative and qualitative evaluation of the approach on videos with different levels of head motion, we compare the magnification of pulse and respiration to existing state-of-the-art methods. Our method produces magnified videos with substantially fewer artifacts and blurring whilst magnifying the physiological changes by a similar degree.

Symmetry is omnipresent in nature and we encounter symmetry routinely in our everyday life. It is also common on the microscopic level, where symmetry is often key to the proper function of core biological processes. The human brain is exquisitely well suited to recognize such symmetrical features with ease. In contrast, computational recognition of such patterns in images is still surprisingly challenging. In this paper we describe a mathematical approach to identifying smaller local symmetrical structures within larger images. Our algorithm attributes a local symmetry score to each image pixel, which subsequently allows the identification of the symmetrical centers of an object. Though there are already many methods available to detect symmetry in images, to the best of our knowledge, our algorithm is the first that is easily applicable in ImageJ/FIJI. We have created an interactive plugin in FIJI that allows the detection and thresholding of local symmetry values. The plugin combines the different reflection symmetry axis of a square to get a good coverage of reflection symmetry in all directions. To demonstrate the plugins potential, we analyzed images of bacterial chemoreceptor arrays and intracellular vesicle trafficking events, which are two prominent examples of biological systems with symmetrical patterns.

Ultrasound is extensively used in medical imaging, being safe and inexpensive and operating in real time. Its scope of applications has been widely broadened by the use of ultrasound contrast agents (UCAs) in the form of microscopic bubbles coated by a biocompatible shell. Their increased use has motivated a large amount of research to understand and characterize their physical properties as well as their interaction with the ultrasound field and their surrounding environment. Here we review the theoretical models that have been proposed to study and predict the behavior of UCAs. We begin with a brief introduction on the development of UCAs. We then present the basics of free-gas-bubble dynamics upon which UCA modeling is based. We review extensively the linear and non-linear models for shell elasticity and viscosity and present models for non-spherical and asymmetric bubble oscillations, especially in the presence of surrounding walls or tissue. Then, higher-order effects such as microstreaming, shedding and acoustic radiation forces are considered. We conclude this review with promising directions for the modeling and development of novel agents.

In this study, supply chain patterns of steel products are investigated from the viewpoints of quality assurance responsibility and understanding of physical phenomena in steel. This study focuses on the differences in supply chain patterns between steel nails for common use and valve springs for the automotive industry. In the supply chain of steel nails for common use, which takes a conventional pattern from raw materials to final products, the quality of each supplier’s product is guaranteed just by the Japanese Industrial Standards (JIS), and no supplier takes quality assurance responsibilities beyond its business range. By contrast, in the supply chain of valve springs for automotive use, each supplier takes quality assurance responsibilities for the final product beyond its business range, and the suppliers cooperate with one another to fulfill stringent quality requirements by automotive manufacturers. Therefore, the supply chain pattern of valve springs is different from the conventional pattern of common use steel products like steel nails. It was also found that the supply chain pattern of valve springs can be caused by the insufficient understanding of physical phenomena in steel, martensitic transformation and hardening in this case. This study suggests that the conditions that determine the supply chain pattern of a steel product could be business practices for quality assurance, namely based on standard specifications or users’ requirements, and the natural scientific understanding level about physical phenomena in steel. Although this study focuses on steel nails and valve springs, this finding is applicable to other steel products.

Conventional ultrafiltration (UF) technology suffers from membrane fouling and limited separation performance. This work demonstrates a novel electrical tuning strategy to improve the separation efficiency of the UF process. An electrically enhanced UF (EUF) system with two sets of oppositely placed membrane-electrode modules was set up. A series of multicycle treatment experiments were conducted to reveal the performance and tuning mechanism of the EUF system. The applied electrical tuning operation brought about an up to 68% reduction of average transmembrane pressure increasing rate (

We have developed a novel button click rendering mechanism based on active lateral force feedback. The effect can be localized because electroadhesion between a finger and a surface can be localized. Psychophysical experiments were conducted to evaluate the quality of a rendered button click, which subjects judged to be acceptable. Both the experiment results and the subjects' comments confirm that this button click rendering mechanism has the ability to generate a range of realistic button click sensations that could match subjects' different preferences. We can thus generate a button click on a flat surface without macroscopic motion of the surface in the lateral or normal direction, and we can localize this haptic effect to an individual finger., Comment: Accepted, IEEE Transactions on Haptics

Doppler effect is the physical phenomena in which the emitted frequency is a source of change at a time when accepted by the detector due to relative movement of the detector towards the source of the wave or vice versa. This research aims to identify the Doppler effect symptoms by utilizing sensors found in smartphones. This research uses experimental method that combine the mechanical instruments and microphone smartphone sensor as measurement tool. The mechanical instruments used are a smartphone with the help of frequency sound generator software, Physics Toolbox, the camera as an instrument of data collectors, and Tracker as a motion analyzer software. Based on the results of the experiments, the author retrieved the value of the error and the standard deviation of each of the observed symptoms. The symptoms of Doppler effect upon source moving closer and moving away when the silent observer shows the error value of 0.04 % and 0.1185 % respectively with a standard deviation of 0.018 and 1.005. In addition, the experiment on Doppler effect as the source is staying still and as the observer approaching the source provides error value of 8.60 % and standard deviation of 13.501. As for the experiment on Doppler effect as the source and the observers are approaching each other displays the error value of 4.31 % and the standard deviation of 0.087. Overall, this experiment generates error value of 3.267 % and standard deviation of 3.665, inferring that the experiments conducted are accurate and precise in representing the Doppler effect phenomenon. Based on the results of this experiments, the researcher recommends to carry out practicum on Doppler effects with the help of smartphone sensors .

Concentric tube robots, composed of nested pre-curved tubes, have the potential to perform minimally invasive surgery at difficult-to-reach sites in the human body. In order to plan motions that safely perform surgeries in constrained spaces that require avoiding sensitive structures, the ability to accurately estimate the entire shape of the robot is needed. Many state-of-the-art physics-based shape models are unable to account for complex physical phenomena and subsequently are less accurate than is required for safe surgery. In this work, we present a learned model that can estimate the entire shape of a concentric tube robot. The learned model is based on a deep neural network that is trained using a mixture of simulated and physical data. We evaluate multiple network architectures and demonstrate the model’s ability to compute the full shape of a concentric tube robot with high accuracy.

In the South-Tyrol region (Italy), 46 gasifiers are currently operating and €200,000 are annually paid to dispose of as a waste 1300 tons of char. Therefore, there is a considerable interest in finding alternatives for the valorization of this solid by-product. The aim of this work is to assess the potential of char as energy source and to compare two scenarios. The first scenario considers the possibility of exploiting char in a dedicated burner integrated in the gasification plant. The second scenario assumes that all the char is collected from South-Tyrol and co-fired with biomass in an existing combustion-ORC plant. An economic analysis was performed evaluating the discounted payback time and both scenarios were modeled using Aspen Plus®. The results reveal that substantial savings in the operating costs of the plants can be achieved. In the first scenario the owners of the gasification plants could save from 50% to 94% of the char disposal costs with a payback time ranging between 3 and 7 years. In the second scenario, the owner of the plant could save approximately €235 k per year with a payback time of approximately 7 years. The present study provides a basis for further techno-economic studies on char combustion. The results can be helpful for the owners of the gasification plants in determining the most cost-effective way to dispose char and to avoid disposing it of as a waste. Furthermore, it is demonstrated how char could be used as a renewable fuel, with better performance than raw biomass.

Picosecond-range avalanche sharpening diodes commutating fast-rising high-voltage pulses of submicrosecond duration are simulated numerically. It is demonstrated that the maximum duration of the commutated pulse are limited by physical phenomena related to the transition of the diode to the double-avalanche-injection mode instead of the drift extraction of nonequilibrium electron–hole plasma. Double avalanche injection is in principle capable of supporting the diode structure in the conducting state after switching. However, the negative differential conductivity, which is attributed to the double injection mode, causes the transverse instability of uniform current distribution and isothermal current filamentation.

Near-field nanoscopy at terahertz (THz) frequencies is uniquely placed to probe a multitude of physical phenomena at the nanoscale. However, at THz frequencies, the scattering efficiency of standar...

The use of machine learning in chemistry is on the rise for the prediction of chemical properties. The input feature representation or descriptor in these applications is an important factor that affects the accuracy as well as the extent of the explored chemical space. Here, we present the periodic table tensor descriptor that combines features from Behler-Parrinello's symmetry functions and a periodic table representation. Using our descriptor and a convolutional neural network model, we achieved 2.2 kcal/mol and 94 meV/atom mean absolute error for the prediction of the atomization energy of organic molecules in the QM9 data set and the formation energy of materials from Materials Project data set, respectively. We also show that structures optimized with a force field derived from this modelcan be used as input to predict the atomization energies of molecules at density functional theory level. Our approach extends the application of Behler-Parrinello's symmetry functions without a limitation on the number of elements, which is highly promising for universal property calculators in large chemical spaces.

Omnia in mensura et numero et pondere disposuisti is a famous Latin phrase from Solomon’s Book of Wisdom, dated to the mid first century BC, meaning that all things were ordered in measure, number, and weight. Naturally, the wisdom is appearing in its relation to man. The Wisdom of Solomon is understood as the perfection of knowledge of the righteous as a gift from God showing itself in action. Consequently, a natural and obvious conjecture is that measurement science is the science of sciences. In fact, it is a basis of all experimental and theoretical research activities. Each measuring process assumes an object of measurement. Some science disciplines, such as quantum physics, are still incomprehensible despite complex mathematical interpretations. No phenomenon is a real phenomenon unless it is observable in space and time, that is, unless it is a subject to measurement. The science of measurement is an indispensable ingredient in all scientific fields. Mathematical foundations and interpretation of the measurement science were accepted and further developed in most of the scientific fields, including physics, cosmology, geology, environment, quantum mechanics, statistics, and metrology. In this year, 2020, Measurement Science Review celebrates its 20th anniversary and we are using this special opportunity to highlight the importance of measurement science and to express our faith that the journal will continue to be an excellent place for exchanging bright ideas in the field of measurement science. As an illustration and motivation for usage and further development of mathematical methods in measurement science, we briefly present the simple least squares method, frequently used for measurement evaluation, and its possible modification. The modified least squares estimation method was applied and experimentally tested for magnetic field homogeneity adjustment.

Van der Waals (vdW) heterostructures, artificial stacks of two-dimensional materials, present an exciting platform to explore new physical phenomena and unique applications. An important and increasingly recognized factor limiting the electrical and optical performance of heterostructure samples is the presence of interfacial contamination. In published work reporting various heterostructure fabrication methods, evidence for the cleanliness of samples is often presented as optical and atomic force microscopy images, typically exhibiting a completely flat topography. In this work, we demonstrate that such samples may nonetheless contain a uniformly thin layer of contaminants at the heterostructure interface. As alternatives, we propose two robust visualization methods that are highly sensitive to such residues, based on photoluminescence mapping and on selective solvent diffusion. The detection capability and straightforward implementation of these two imaging techniques make them powerful tools to assess and improve the cleanliness of a wide variety of fabrication techniques for heterostructures comprising any combination of vdW materials.

Purpose We aim to analyze the efficacy of different focus sizes and the influence of pulse pressure (intensity) during shock wave lithotripsy (SWL) in terms of stone fragmentation. Methods Combination of three focal sizes (F1 = 2 mm, F2 = 4 mm, F3 = 8 mm) and 11 output pressure settings (intensity 10–20) of a piezoelectric lithotripter (Wolf PiezoLith 3000) were tested on artificial stones (n = 99). The stones were placed within a 2 mm mesh cage. The needed number of shockwaves (SW) to first visible crack, 50% and 100% stone disintegration were recorded. Results Similar number of SW’s were observed until the first crack 10, 11 and 11 SW’s for F1, F2, and F3, respectively (p > 0,05). The median number of SW needed for 50% stone disintegration was 245 for F1 group, 242 for F2 group and 656 for F3 group. F1 vs F2 p = 0.7, F1 vs F3 and F2 vs F3 p F1, F2 and F3, respectively. Only for F1 vs F3 and F2 vs F3 (all p Conclusions A smaller focus size, as well as a higher peak pressure results in a more effective stone fragmentation. However, these results need to be confirmed in an in vivo setting with multiple parameters interfering the efficacy, like BMI, respiration or stone migration.

To elucidate the basic thermophysical properties at low temperatures of lipiodol, which is used as a marker by transarterial injection before CT-guided cryoablation for solid tumors, by fundamental experiments with pure lipiodol phantom. The freezing point of lipiodol was measured using differential scanning calorimeter (DSC) by detecting differences in the heating rate during heating from − 30 °C. Freezing experiments were conducted using pure lipiodol and a tissue phantom, which were prepared in an acrylic container at 37 °C. The growth of the frozen region was observed for 10 min. Temperatures were monitored at the cryoprobe surface and designated positions around the cryoprobe. The DSC experiment showed that freezing was observed between − 5 and − 30 °C, which indicated that the freezing point was approximately − 5 °C. Freezing experiments revealed that the diameter of frozen region in the lipiodol was smaller than that in the tissue phantom (5 mm vs 24 mm) after 10-min freezing. The temperature at the probe surface was − 130 °C in lipiodol, which was 25 °C lower than that in the tissue phantom. There was a larger temperature gradient near the cryoprobe in lipiodol due to lower thermal conductivity. The present results suggest that an extremely high concentration of lipiodol (close to pure lipiodol) potentially reduces frozen region because of its lower freezing point and smaller thermal conductivity. However, since lipiodol concentrations in clinical cases differ from the current model, further studies using models that are close to clinical conditions are required. No level of evidence, laboratory investigation.

The term skin fragility disorders describes a group of conditions in which the structural integrity of the skin is compromised and its resistance to external shear forces diminished. Skin fragility can have different causes, ranging from genetic variations to inflammatory or physical phenomena. The genetic skin fragility disorders, collectively called epidermolysis bullosa, serve as a paradigm for the study of causes and mechanisms of skin fragility. Recent biomedical research has revealed substantial genetic heterogeneity of the epidermolysis bullosa group, delivered ample new knowledge on its pathophysiology, and facilitated the design of evidence-based therapeutic strategies. The therapy development process extends from in vitro testing to preclinical validation in animal models, and clinical trials. This article reviews different approaches to curative and symptom-relief therapies, and appraises their status and perspectives for clinical implementation.

Background dehydration is associated with significant adverse outcomes in older people despite being largely preventable and treatable. Little research has focused on the views of community-dwelling older people on hydration, healthy drinking and the perceived importance of drinking well in later life. Objectives to understand community-dwelling older people and informal carers’ views on hydration in later life and how older people can be supported to drink well. Methods qualitative study using interviews and a focus group exploring hydration and nutrition in later life (24 older people at risk of malnutrition and dehydration, 9 informal carers) and thematic analysis. Results this article presents the findings on hydration alone. Four themes are presented: perceptions of healthy drinking, barriers to and facilitators of drinking in later life and supporting older people to drink well. The perceived importance of adequate hydration in later life was polarised. Concerns about urinary incontinence and knowledge gaps were significant barriers. Consideration of individual taste preference and functional capacity acted as facilitators. Distinct habitual drinking patterns with medications and meals exist within individuals. Many relied on thirst at other times or when fluid demands are greater (such as hot weather), a known unreliable prompt in later life. Conclusions older people could be supported to drink well by building upon existing habitual drinking patterns. Primary care and public health should consider individual barriers, facilitators and tailored education. A multidisciplinary approach to promote hydration should be incorporated into care for older people with more complex needs.

To compare the effectiveness and safety of escalating and fixed energy output modalities of shockwave lithotripsy (SWL) in the treatment of urinary stones. A systematic literature search using PubMed, Embase, Cochrane Library and Web of Science was performed to obtain relevant studies up to December 2018. Summarized mean differences (MDs) and risk differences (RDs) with 95% confidence intervals (CIs) were used for comparing continuous and dichotomous variables, respectively. Six RCTs including 775 patients were identified. In the overall pooled outcomes, no significant difference was detected between escalating and fixed voltage group regarding initial and final success rate (SR) and stone-free status (SFS), auxiliary procedure and complication (hematoma, febrile episode, and pain) rate. However, when shockwave frequency ≥ 90 shocks/min, total shocks per session ≤ 3000, or 1–3 SWL sessions were performed, escalating group was associated with significantly higher SR1 (defined as SFS + fragments ≤ 4 mm); in addition, escalating group brought significantly less hematoma when total shocks per session ≤ 3000. Escalating voltage SWL offered comparable safety and effectiveness to that of fixed voltage SWL. However, escalating voltage SWL could be recommended in following conditions: (1) shockwave frequency ≥ 90 shocks/min, total shocks per session ≤ 3000, or 1–3 SWL sessions, for better stone removal; (2) total shocks per session ≤ 3000, for less hematoma formation.

Given energy and water scarcity, it is necessary to develop an in-depth understanding of the energy-water nexus in China for its sustainable development. Previous studies have focused on nexus accounting, synergy conservation, and system optimization, but its induction mechanism along the supply chains has not been uncovered. This paper proposes a top-down structural path analysis (SPA) and combines it with an environmental input-output model (EIOM) to identify the critical final demand, consumption sectors, and supply chain paths inducing the energy-water nexus. The results show that the largest final demand of water for energy production (WFE) is capital formation, while the largest final demand of energy for water supply (EFW) is urban consumption. The distribution of WFE at different production layers shows an inverted U shape. Most WFE is indirectly consumed by other sectors, such as construction, through three-step supply chain paths. In contrast, the distribution of EFW shows a L shape, and most EFW is directly consumed by the final demand. In addition, some critical supply chain paths inducing more WFE and EFW are identified. Finally, some policies targeting the energy-water nexus management are proposed, which are conducive to resource conservation and the sustainable supply of energy and water.

This paper presents a detailed characterization of turbulence in the incoming flow to the clarification component of a water treatment plant, ?Los Molinos? (Córdoba, Argentina). The main problems were related to the presence of turbulent flow patterns throughout the treatment, affecting the proper development of the physical processes required for water clarification. Namely: (a) a poor hydraulic design that could produce a non-homogeneous spatial distribution of the flow, recirculation zones and flow stagnation, and a non-uniform discharge distribution among the sedimentation units as a result of different cross-sectional dimensions of the transverse-channel, and (b) high turbulence intensity that affect the flocs´ size as well as the efficiency of the settling tanks and filters. Firstly, a detailed in-situ experimental characterization of the turbulent flow was undertaken. An acoustic Doppler velocimeter (ADV) was used to characterize the flow turbulence, whereas for discharge measurements and mean flow velocity field an acoustic Doppler current profiler (ADCP) was employed. Secondly, a numerical model, based on the Reynolds-averaged Navier?Stokes (RANS) equations and the k-e turbulence closure model, was validated with the experimental data. Finally, based on the results, a diagnosis and recommendations were made for the optimization of the hydraulic design of the water treatment plant. Fil: Ragessi, Ivan Matias. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: García, Carlos Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Estudios Avanzados en Ingeniería y Tecnología. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto de Estudios Avanzados en Ingeniería y Tecnología; Argentina Fil: Marquez Damian, Santiago. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina Fil: Pozzi Piacenza, Cecilia Elena. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina Fil: Cantero, Mariano Ignacio. Comisión Nacional de Energía Atómica. Gerencia del Área de Energía Nuclear. Instituto Balseiro; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

Contains fulltext : 215291.pdf (Publisher’s version ) (Closed access) INTRODUCTION: There is a high degree of uncertainty regarding the appropriate force level that should be applied during orthodontic tooth movement (OTM). As a result, orthodontic treatments may take longer than necessary, leading to unwanted side effects. This review aimed to identify an optimal force range with the rate of OTM as the primary outcome. External apical root resorption and pain were evaluated as secondary outcomes, and the influence of growth was examined. METHODS: Five electronic databases were searched (MEDLINE [via PubMed], Embase [via OVID], Cochrane Library, CINAHL, and Web of Science) with no publication date or language restrictions. Inclusion eligibility screening, quality assessment, and data extraction were performed by 3 investigators. Each retrieved record was assessed by 2 observers independently. Only randomized controlled trials and randomized split-mouth studies were included. RESULTS: A total of 12 articles satisfied the inclusion criteria-two randomized controlled trials and 10 randomized split-mouth studies. Only 1 study showed a low risk of bias, whereas the remaining 11 were unclear. The qualitative analysis showed that forces between 50 cN and 250 cN produced a similar OTM rate; forces >250 cN yielded a slightly higher rate but were accompanied by adverse effects. Because of considerable heterogeneity in methodology, clinical diversity with varying forces between 18 cN and 360 cN, and poor statistical reporting, a meta-analysis was deemed inappropriate. CONCLUSIONS: Forces between 50 cN and 100 cN seem optimal for OTM, patient comfort and potentially exhibit fewer side effects. Nevertheless, careful data interpretation is necessary because of the lack of strong evidence. Protocol registration: PROSPERO CRD42016039985.

Background Polymethylmethacrylate cement is used in total knee arthroplasty and plays a significant role in the success of the procedure. Temperature variation is known to influence cement setting time in vitro. Our aim is to evaluate the relationship between ambient theatre temperature and cement setting time in vivo. Methods Theatre temperature and cement setting time were prospectively recorded during 683 total knee arthroplasties over 8 years using a single cement and vacuum mixing system (Simplex with tobramycin). Setting time was defined as the time until a scalpel blade could not indent the cement surface. Results Mean temperature was 18.92°C (SD 1.16) and setting time 13.08 min (SD 1.92). A moderate inverse relationship exists between ambient temperature and setting time (Pearson's R = -0.423); however, potential setting times within a given temperature range varied considerably ( 20°C: 7.5-16 min), suggesting that temperature alone cannot reliably predict setting time. Conclusion Our data support the current understanding of bone cement properties in vivo and suggest that surgeons should be mindful in regards to unpredictable cement setting time and optimal theatre environment.

In the past two decades, ionic liquids (ILs) have blossomed as versatile task-specific materials with a unique combination of properties, which can be beneficial for a plethora of different applications. The additional need of incorporating ILs into solid devices led to the development of a new class of ionic soft-solid materials, named here iongels. Nowadays, iongels cover a wide range of materials mostly composed of an IL component immobilized within different matrices such as polymers, inorganic networks, biopolymers or inorganic nanoparticles. This review aims at presenting an integrated perspective on the recent progress and advances in this emerging type of material. We provide an analysis of the main families of iongels and highlight the emerging types of these ionic soft materials offering additional properties, such as thermoresponsiveness, self-healing, mixed ionic/electronic properties, and (photo)luminescence, among others. Next, recent trends in additive manufacturing (3D printing) of iongels are presented. Finally, their new applications in the areas of energy, gas separation and (bio)electronics are detailed and discussed in terms of performance, underpinning it to the structural features and processing of iongel materials.

Coal preparation is effective in controlling primary mercury emissions in coal combustion systems; however, the combustion of coal preparation byproducts may cause secondary emissions. The inconsistent coal preparation statistics, unclear mercury distribution characteristics during coal preparation, and limited information regarding the byproduct utilization pathways lead to great uncertainty in the evaluation of the effect of coal preparation in China. This study elucidated the mercury distribution in coal preparation based on the activity levels of 2886 coal preparation plants, coal mercury content database, tested mercury distribution factors of typical plants, and then traced the mercury flows and emissions in the downstream sectors using a cross-industry mercury flow model. We found that coal preparation altered the mercury flows by reducing 68 tonnes of mercury to sectors such as coking and increasing the flows to byproduct utilization sectors. Combusting cleaned coal rather than raw coal reduced the mercury emissions by 47 tonnes; however, this was offset by secondary mercury emissions. Coal gangue spontaneous combustion and the cement kiln coprocessing process were dominant secondary emitters. Our results highlight the necessity of whole-process emission control of atmospheric mercury based on flow maps. Future comprehensive utilization of wastes in China should fully evaluate the potential secondary mercury emissions.

In this paper, we examine routing protocols with the shortest path in sensor networks. In doing this, we propose a genetic algorithm (GA)-based Ad Hoc On-Demand Multipath Distance Vector routing protocol (GA-AOMDV). We utilize a fitness function that optimizes routes based on the energy consumption in their nodes. We compare this algorithm with other existing ad hoc routing protocols including LEACH-GA, GA-AODV, AODV, DSR, EPAR, EBAR_BFS. Results prove that our protocol enhances the network performance in terms of packet delivery ratio, throughput, round trip time and energy consumption. GA-AOMDV protocol achieves average gain that is 7 to 22% over other protocols. Therefore, our protocol extends the network lifetime for data communications.

The development of wearable devices and remote sensor networks progressively relies on their increased power autonomy, which can be further expanded by replacing conventional power sources, characterized by limited lifetimes, with energy harvesting systems. Due to its pervasiveness, kinetic energy is considered as one of the most promising energy forms, especially when combined with the simple and scalable piezoelectric approach. The integration of piezoelectric energy harvesters, generally in the form of bimorph cantilevers, with wearable and remote sensors, highlighted a drawback of such a configuration, i.e., their narrow operating bandwidth. In order to overcome this disadvantage while maximizing power outputs, optimized cantilever geometries, developed using the design of experiments approach, are analysed and combined in this work with frequency up-conversion excitation that allows converting random kinetic ambient motion into a periodical excitation of the harvester. The developed optimised designs, all with the same harvesters’ footprint area of 23 × 15 mm, are thoroughly analysed via coupled harmonic and transient numerical analyses, along with the mostly neglected strength analyses. The models are validated experimentally via innovative experimental setups. The thus-proposed ϕ = 50 mm watch-like prototype allows, by using a rotating flywheel, the collection of low-frequency (ca. 1 to 3 Hz) human kinetic energy, and the periodic excitation of the optimized harvesters that, oscillating at their eigenfrequencies (~325 to ~930 Hz), display specific power outputs improved by up to 5.5 times, when compared to a conventional rectangular form, with maximal power outputs of up to &gt, 130 mW and average power outputs of up to &gt, 3 mW. These power levels should amply satisfy the requirements of factual wearable medical systems, while providing also an adaptability to accommodate several diverse sensors. All of this creates the preconditions for the development of novel autonomous wearable devices aimed not only at sensor networks for remote patient monitoring and telemedicine, but, potentially, also for IoT and structural health monitoring.

Objective: Given the ever-changing flow of obstetric patients in the hospital, how the government and hospital management plan and allocate medical resources has become an important problem that needs to be urgently solved. In this study a prediction method for calculating the monthly and daily flow of patients based on time series is proposed to provide decision support for government and hospital management.Methods: The historical patient flow data from the Department of Obstetrics and Gynecology of the First Hospital of Jilin University, China, from January 1, 2018, to February 29, 2020, were used as the training set. Seven models such as XGBoost, SVM, RF, and NNAR were used to predict the daily patient flow in the next 14 days. The HoltWinters model is then used to predict the monthly flow of patients over the next year.Results: The results of this analysis and prediction model showed that the obstetric inpatient flow was not a purely random process, and that patient flow was not only accompanied by the random patient flow but also showed a trend change and seasonal change rule. ACF,PACF,Ljung_box, and residual histogram were then used to verify the accuracy of the prediction model, and the results show that the Holtwiners model was optimal. R2, MAPE, and other indicators were used to measure the accuracy of the 14 day prediction model, and the results showed that HoltWinters and STL prediction models achieved high accuracy.Conclusion: In this paper, the time series model was used to analyze the trend and seasonal changes of obstetric patient flow and predict the patient flow in the next 14 days and 12 months. On this basis, combined with the trend and seasonal changes of obstetric patient flow, a more reasonable and fair horizontal allocation scheme of medical resources is proposed, combined with the prediction of patient flow.

To minimize the curtailment of renewable generation and incentivize grid-scale energy storage deployment, a concept of combining stationary and mobile applications of battery energy storage systems built within renewable energy farms is proposed. A simulation-based optimization model is developed to obtain the optimal design parameters such as battery capacity and power ratings by solving a multi-objective optimization problem that aims to maximize the economic profitability, the energy provided for transportation electrification, the demand peak shaving, and the renewable energy utilized. Two applications considered for the stationary energy storage systems are the end-consumer arbitrage and frequency regulation, while the mobile application envisions a scenario of a grid-independent battery-powered electric vehicle charging station network. The charging stations receive supplies from the energy storage system that absorbs renewable energy, contributing to a sustained DC demand that helps with revenues. Representative results are presented for two operation modes and different sets of weights assigned to the objectives. Substantial improvement in the profitability of combined applications over single stationary applications is shown. Pareto frontier of a reduced dimensional problem is obtained to show the trade-off between design objectives. This work could pave the road for future implementations of the new form of energy storage systems.

International audience; Purpose: An antibubble is an encapsulated gas bubble with an incompressible inclusion inside the gas phase. Current-generation ultrasound contrast agents are bubble-based: they contain encapsulted gas bubbles with no inclusions. The objective of this work is to determine the linear and nonlinear responses of an antibubble contrast agent in comparison to two bubble-based ultrasound contrast agents, i.e., reference bubbles and SonoVueᵀᴹ.Methods: Side scatter and attenuation of the three contrast agents were measured, using single-element ultrasound transducers, operating at 1 MHz, 2.25 MHz and 3.5 MHz. The scatter measurements were performed at acoustic pressures of 200 kPa and 300 kPa for 1 MHz, 300 kPa and 450 kPa for 2.25 MHz, and 370 kPa and 560 kPa for 3.5 MHz. Attenuation measurements were conducted at pressures of 13 kPa, 55 kPa and 50 kPa for 1 MHz, 2.25 MHz, and 3.5 MHz, respectively. In addition, a dynamic contrast-enhanced ultrasound measurement was performed, imaging the contrast agent flow through a vascular phantom with a commertial diagnostic linear array probe.Results: Antibubbles generated equivalent or stronger harmonic signal, compared to bubble-based ultrasound contrast agents. The 2nd harmonic side-scatter amplitude of the antibubble agent was up to 3 dB greater than that of reference bubble agent and up to 4 dB greater than that of SonoVueᵀᴹ at the estimated concentration of 8 x 10⁴ bubbles/mL. For ultrasound with a center transmit frequency of 1 MHz, the attenuation coefficient of the antibubble agent was 8.7 dB/cm, whereas the attenuation coefficient of the reference agent was 7.7 dB/cm and 0.3 dB/cm for SonoVueᵀᴹ. At 2.25 MHz the attenuation coefficients were 9.7 dB/cm, 3.0 dB/cm and 0.6 dB/cm, respectively. For 3.5 MHz, they were 4.4 dB/cm, 1.8 dB/cm and 1.0 dB/cm, respectively. We hypothesize that the antibubble agent attenuation is greater than that of the reference agent due to the solid cores in the antibubble agent. A dynamic contrast-enhanced ultrasound recording showed the nonlinear signal of the antibubble agent to be 31% greater than for reference bubbles and 23% lower than SonoVueᵀᴹ at a high concentration of 2 x 10⁶ bubbles/mL.Conclusion: Endoskeletal antibubbles generate comparable or greater higher harmonics than reference bubbles and SonoVueᵀᴹ. As a result, antibubbles with liquid therapeutic agents inside the gas phase have high potential to become a traceable therapeutic agent.