Showing papers by "Chung Yuan Christian University published in 2020"

FLAG Review 2019

Abstract: We review lattice results related to pion, kaon, D-meson, B-meson, and nucleon physics with the aim of making them easily accessible to the nuclear and particle physics communities. More specifically, we report on the determination of the light-quark masses, the form factor $f_+(0)$ arising in the semileptonic $K \rightarrow \pi $ transition at zero momentum transfer, as well as the decay constant ratio $f_K/f_\pi $ and its consequences for the CKM matrix elements $V_{us}$ and $V_{ud}$. Furthermore, we describe the results obtained on the lattice for some of the low-energy constants of $SU(2)_L\times SU(2)_R$ and $SU(3)_L\times SU(3)_R$ Chiral Perturbation Theory. We review the determination of the $B_K$ parameter of neutral kaon mixing as well as the additional four B parameters that arise in theories of physics beyond the Standard Model. For the heavy-quark sector, we provide results for $m_c$ and $m_b$ as well as those for D- and B-meson decay constants, form factors, and mixing parameters. These are the heavy-quark quantities most relevant for the determination of CKM matrix elements and the global CKM unitarity-triangle fit. We review the status of lattice determinations of the strong coupling constant $\alpha _s$. Finally, in this review we have added a new section reviewing results for nucleon matrix elements of the axial, scalar and tensor bilinears, both isovector and flavor diagonal.

Unsupervised K-Means Clustering Algorithm

Abstract: The k-means algorithm is generally the most known and used clustering method. There are various extensions of k-means to be proposed in the literature. Although it is an unsupervised learning to clustering in pattern recognition and machine learning, the k-means algorithm and its extensions are always influenced by initializations with a necessary number of clusters a priori. That is, the k-means algorithm is not exactly an unsupervised clustering method. In this paper, we construct an unsupervised learning schema for the k-means algorithm so that it is free of initializations without parameter selection and can also simultaneously find an optimal number of clusters. That is, we propose a novel unsupervised k-means (U-k-means) clustering algorithm with automatically finding an optimal number of clusters without giving any initialization and parameter selection. The computational complexity of the proposed U-k-means clustering algorithm is also analyzed. Comparisons between the proposed U-k-means and other existing methods are made. Experimental results and comparisons actually demonstrate these good aspects of the proposed U-k-means clustering algorithm.

Polyamide nanofiltration membrane with highly uniform sub-nanometre pores for sub-1 Å precision separation.

Abstract: Separating molecules or ions with sub-Angstrom scale precision is important but technically challenging. Achieving such a precise separation using membranes requires Angstrom scale pores with a high level of pore size uniformity. Herein, we demonstrate that precise solute-solute separation can be achieved using polyamide membranes formed via surfactant-assembly regulated interfacial polymerization (SARIP). The dynamic, self-assembled network of surfactants facilitates faster and more homogeneous diffusion of amine monomers across the water/hexane interface during interfacial polymerization, thereby forming a polyamide active layer with more uniform sub-nanometre pores compared to those formed via conventional interfacial polymerization. The polyamide membrane formed by SARIP exhibits highly size-dependent sieving of solutes, yielding a step-wise transition from low rejection to near-perfect rejection over a solute size range smaller than half Angstrom. SARIP represents an approach for the scalable fabrication of ultra-selective membranes with uniform nanopores for precise separation of ions and small solutes. Separating molecules or ions with sub-Angstrom scale precision is important but technically challenging. Here, the authors demonstrate that precise solute-solute separation can be achieved using polyamide membranes formed via surfactant-assembly regulated interfacial polymerization.

Impact of the COVID-19 event on air quality in central China

Abstract: In early 2020, the COVID-19 epidemic spread globally. This study investigated the air quality of three cities in Hubei Province, Wuhan, Jingmen, and Enshi, central China, from January to March 2017–2020 to analyze the impact of the epidemic prevention and control actions on air quality. The results indicated that in the three cities, during February 2020, when the epidemic prevention and control actions were taken, the average concentrations of atmospheric PM2.5, PM10, SO2, CO, and NO2 in the three cities were 46.1 µg m–3, 50.8 µg m–3, 2.56 ppb, 0.60 ppm, and 6.70 ppb, and were 30.1%, 40.5%, 33.4%, 27.9%, and 61.4% lower than the levels in February 2017–2019, respectively. However, the average O3 concentration (23.1, 32.4, and 40.2 ppb) in 2020 did not show a significant decrease, and even increased by 12.7%, 14.3%, and 11.6% in January, February, and March, respectively. This is because a lower concentration of NO2 resulted in constraints on the NO + O3 reaction, and the O3 could not be effectively further depleted. In addition, the average air quality index (AQI) for the three cities in January, February, and March 2020 were 32.2%, 27.7%, and 14.9% lower than the levels in 2017–2019, respectively. Based on the AQIs for the three cities, the combined proportions of Class I and Class Ⅱ in January, February, and March 2020 increased by 27.9%, 24.8%, and 4.3%, respectively, while the combined proportion of AQI Classes III, IV, V, and VI was reduced from 34.8% to 15.8%. In addition, in the first three months of 2020, the indicatory air pollutants in the three cities for the AQIs were predominant in the following order: PM2.5 (72.0%), O3 (16.4%), PM10 (8.3%), NO2 (2.9%), and CO (0.4%). This study provides useful information for establishing a scientific air pollution control strategy and is a valuable reference for future research on improving urban air quality.

Potential Toxicity of Iron Oxide Magnetic Nanoparticles: A Review.

Abstract: The noteworthy intensification in the development of nanotechnology has led to the development of various types of nanoparticles. The diverse applications of these nanoparticles make them desirable candidate for areas such as drug delivery, coasmetics, medicine, electronics, and contrast agents for magnetic resonance imaging (MRI) and so on. Iron oxide magnetic nanoparticles are a branch of nanoparticles which is specifically being considered as a contrast agent for MRI as well as targeted drug delivery vehicles, angiogenic therapy and chemotherapy as small size gives them advantage to travel intravascular or intracavity actively for drug delivery. Besides the mentioned advantages, the toxicity of the iron oxide magnetic nanoparticles is still less explored. For in vivo applications magnetic nanoparticles should be nontoxic and compatible with the body fluids. These particles tend to degrade in the body hence there is a need to understand the toxicity of the particles as whole and degraded products interacting within the body. Some nanoparticles have demonstrated toxic effects such inflammation, ulceration, and decreases in growth rate, decline in viability and triggering of neurobehavioral alterations in plants and cell lines as well as in animal models. The cause of nanoparticles' toxicity is attributed to their specific characteristics of great surface to volume ratio, chemical composition, size, and dosage, retention in body, immunogenicity, organ specific toxicity, breakdown and elimination from the body. In the current review paper, we aim to sum up the current knowledge on the toxic effects of different magnetic nanoparticles on cell lines, marine organisms and rodents. We believe that the comprehensive data can provide significant study parameters and recent developments in the field. Thereafter, collecting profound knowledge on the background of the subject matter, will contribute to drive research in this field in a new sustainable direction.

Nanoplastics Cause Neurobehavioral Impairments, Reproductive and Oxidative Damages, and Biomarker Responses in Zebrafish: Throwing up Alarms of Wide Spread Health Risk of Exposure.

Abstract: Plastic pollution is a growing global emergency and it could serve as a geological indicator of the Anthropocene era. Microplastics are potentially more hazardous than macroplastics, as the former can permeate biological membranes. The toxicity of microplastic exposure on humans and aquatic organisms has been documented, but the toxicity and behavioral changes of nanoplastics (NPs) in mammals are scarce. In spite of their small size, nanoplastics have an enormous surface area, which bears the potential to bind even bigger amounts of toxic compounds in comparison to microplastics. Here, we used polystyrene nanoplastics (PS-NPs) (diameter size at ~70 nm) to investigate the neurobehavioral alterations, tissue distribution, accumulation, and specific health risk of nanoplastics in adult zebrafish. The results demonstrated that PS-NPs accumulated in gonads, intestine, liver, and brain with a tissue distribution pattern that was greatly dependent on the size and shape of the NPs particle. Importantly, an analysis of multiple behavior endpoints and different biochemical biomarkers evidenced that PS-NPs exposure induced disturbance of lipid and energy metabolism as well as oxidative stress and tissue accumulation. Pronounced behavior alterations in their locomotion activity, aggressiveness, shoal formation, and predator avoidance behavior were exhibited by the high concentration of the PS-NPs group, along with the dysregulated circadian rhythm locomotion activity after its chronic exposure. Moreover, several important neurotransmitter biomarkers for neurotoxicity investigation were significantly altered after one week of PS-NPs exposure and these significant changes may indicate the potential toxicity from PS-NPs exposure. In addition, after ~1-month incubation, the fluorescence spectroscopy results revealed the accumulation and distribution of PS-NPs across zebrafish tissues, especially in gonads, which would possibly further affect fish reproductive function. Overall, our results provided new evidence for the adverse consequences of PS-NPs-induced behavioral dysregulation and changes at the molecular level that eventually reduce the survival fitness of zebrafish in the ecosystem.

Recent progress and advances in the environmental applications of MXene related materials

Abstract: MXenes are a new type of two-dimensional (2D) transition metal carbide or carbonitride material with a 2D structure similar to graphene. The general formula of MXenes is Mn+1XnTx, in which M is an early transition metal element, X represents carbon, nitrogen and boron, and T is a surface oxygen-containing or fluorine-containing group. These novel 2D materials possess a unique 2D layered structure, large specific surface area, good conductivity, stability, and mechanical properties. Benefitting from these properties, MXenes have received increasing attention and emerged as new substrate materials for exploration of various applications including, energy storage and conversion, photothermal treatment, drug delivery, environmental adsorption and catalytic degradation. The progress on various applications of MXene-based materials has been reviewed; while only a few of them covered environmental remediation, surface modification of MXenes has never been highlighted. In this review, we highlight recent advances and achievements in surface modification and environmental applications (such as environmental adsorption and catalytic degradation) of MXene-based materials. The current studies on the biocompatibility and toxicity of MXenes and related materials are summarized in the following sections. The challenges and future directions of the environmental applications of MXene-based materials are also discussed and highlighted.

Recent development and prospects of surface modification and biomedical applications of MXenes

Abstract: MXenes, as a novel kind of two-dimensional (2D) materials, were first discovered by Gogotsi et al. in 2011. Owing to their multifarious chemical compositions and outstanding physicochemical properties, the novel types of 2D materials have attracted intensive research interest for potential applications in various fields such as energy storage and conversion, environmental remediation, catalysis, and biomedicine. Although many achievements have been made in recent years, there still remains a lack of reviews to summarize these recent advances of MXenes, especially in biomedical fields. Understanding the current status of surface modification, biomedical applications and toxicity of MXenes and related materials will give some inspiration to the development of novel methods for the preparation of multifunctional MXene-based materials and promote the practical biomedical applications of MXenes and related materials. In this review, we present the recent developments in the surface modification of MXenes and the biomedical applications of MXene-based materials. In the first section, some typical surface modification strategies were introduced and the related issues were also discussed. Then, the potential biomedical applications (such as biosensor, biological imaging, photothermal therapy, drug delivery, theranostic nanoplatforms, and antibacterial agents) of MXenes and related materials were summarized and highlighted in the following sections. In the last section, the toxicity and biocompatibility of MXenes in vitro were mentioned. Finally, the development, future directions and challenges about the surface modification of MXene-based materials for biomedical applications were discussed. We believe that this review article will attract great interest from the scientists in materials, chemistry, biomedicine and related fields and promote the development of MXenes and related materials for biomedical applications.

Review of Copper and Copper Nanoparticle Toxicity in Fish.

Abstract: This review summarizes the present knowledge on the toxicity of copper and copper nanoparticles (CuNPs) to various fish species. In previous decades, the excessive usage of metal and metallic nanoparticles has increased significantly, increasing the probability of the accumulation and discharge of metals in various trophic levels of the environment. Due to these concerns, it is important to understand the toxicity mechanisms of metals and metallic nanoparticles before they lead to unhealthy effects on human health. In this review paper, we specifically focus on the effect of metal copper and CuNPs on different fish organs under different physiochemical parameters of various water bodies. Nowadays, different forms of copper have distinctive and specific usages, e.g., copper sulfate is a well-established pesticide which is used to control the growth of algae in lakes and ponds. Deactivating the fungi enzymes prevents fungal spores from germinating. This process of deactivation is achieved via the free cupric ions, which are established as the most toxic forms of copper. Complexes of copper with other ligands may or may not be bioavailable for use in aquatic organisms. On the other hand, CuNPs have shown cost-effectiveness and numerous promising uses, but the toxicity and availability of copper in a nanoparticle form is largely unknown, Additionally, physiochemical factors such as the hardness of the water, alkalinity, presence of inorganic and organic ligands, levels of pH, and temperature in various different water bodies affect the toxicity caused by copper and CuNPs. However, comprehensive knowledge and data regarding the pattern of toxicity for copper metal ions and CuNPs in marine organisms is still limited. In this review, we carry out a critical analysis of the availability of the toxicological profiles of copper metal ions and CuNPs for different fishes in order to understand the toxicity mechanisms of copper and CuNPs. We believe that this review will provide valuable information on the toxicological profile of copper, which will further help in devising safe guidelines for the usage of copper and CuNPs in a sustainable manner.

From design to applications of stimuli-responsive hydrogel strain sensors

Abstract: Stimuli-responsive hydrogel strain sensors that synergize the advantages of both soft-wet hydrogels and smart functional materials have attracted rapidly increasing interest for exploring the opportunities from material design principles to emerging applications in electronic skins, health monitors, and human–machine interfaces. Stimuli-responsive hydrogel strain sensors possess smart and on-demand ability to specifically recognize various external stimuli and convert them into strain-induced mechanical, thermal, optical, and electrical signals. This review presents an up-to-date summary over the past five years on hydrogel strain sensors from different aspects, including material designs, gelation/fabrication methods, stimuli-responsive principles, and sensing performance. Hydrogel strain sensors are classified into five major categories based on the nature of the stimuli, and representative examples from each category are carefully selected and discussed in terms of structures, response mechanisms, and potential medical applications. Finally, current challenges and future perspectives of hydrogel strain sensors are tentatively proposed to stimulate more and better research in this emerging field.

Air quality index, indicatory air pollutants and impact of covid-19 event on the air quality near central china

Abstract: Both the air quality index (AQI) and indicatory air pollutants of Anqing, Hefei, and Suzhou near central China from 2017 to 2019, and the impact of COVID-19 epidemic prevention and control actions on air quality were investigated. The combined data for the three cities from 2017 to 2019 indicated that the lowest AQI (averaged 78.1) occurred in the summer season, for which the AQI proportions for classes I, II, III, IV, V, and VI were 25.6%, 49.9%, 21.9%, 2.7%, 0%, and 0%, respectively. The highest (AQI average of 112.6) was in winter, for which the proportions were 7.4%, 39.5%, 33.3%, 12.5%, 7.2%, and 0.1%, respectively. PM2.5, PM10, and NO2 in order were the most important indicatory air pollutants for AQI classes IV, V, and VI, which all prevailed in winter and spring, while O3 was the indicatory air pollutant that occurred most in summer. The COVID-19 event, which triggered global attention, broke out at the end of 2019. This study also investigated and compared the air quality levels in the three cities from January to March 2017–2019 with those in 2020. The results showed that during February 2020, in the three cities, the average ambient air concentrations of PM2.5, PM10, SO2, CO, and NO2 were 41.9 µg m–3, 50.1 µg m–3, 2.18 ppb, 0.48 ppm, and 8.97 ppb, and were 46.5%, 48.9%, 52.5%, 36.2%, and 52.8%, respectively, lower than those in the same month in 2017–2019, respectively. However, the O3 average concentration (80.6 ppb) did not show significant fluctuations and even slightly increased by 3.6%. This is because a lower concentration of NO2 resulted in constraints on the reaction of NO + O3, so the O3 level could not be effectively further reduced. In addition, this study also analyzed and compared the five highest daily AQIs from February 2017–2019 with those of 2020 for the three cities. The mean AQI for the 5 days with the highest daily AQI (averaged 122.6) in February 2020 was 45.1% lower than that for February 2017–2019 (averaging 223.2), and the indicatory air pollutant was always PM2.5, which decreased by 46.7% (from 173.6 to 92.6 µg m–3). It is clear that during the COVID-19 epidemic prevention and control action periods, the air quality near central China improved significantly.

Novel Architecture Titanium Carbide (Ti3C2Tx) MXene Cocatalysts toward Photocatalytic Hydrogen Production: A Mini-Review.

Abstract: Low dimensional transition metal carbide and nitride (MXenes) have been emerging as frontier materials for energy storage and conversion. Ti3C2Tx was the first MXenes that discovered and soon become the most widely investigated among the MXenes family. Interestingly, Ti3C2Tx exhibits ultrahigh catalytic activity towards the hydrogen evolution reaction. In addition, Ti3C2Tx is electronically conductive, and its optical bandgap is tunable in the visible region, making it become one of the most promising candidates for the photocatalytic hydrogen evolution reaction (HER). In this review, we provide comprehensive strategies for the utilization of Ti3C2Tx as a catalyst for improving solar-driven HER, including surface functional groups engineering, structural modification, and cocatalyst coupling. In addition, the reaming obstacle for using these materials in a practical system is evaluated. Finally, the direction for the future development of these materials featuring high photocatalytic activity toward HER is discussed.

Seamless multimaterial 3D liquid-crystalline elastomer actuators for next-generation entirely soft robots

Abstract: Liquid-crystalline elastomers (LCEs) are excellent soft actuator materials for a wide range of applications, especially the blooming area of soft robotics. For entirely soft LCE robots to exhibit high dexterity and complicated performance, several components are typically required to be integrated together in one single robot body. Here, we show that seamless multicomponent/multimaterial three-dimensional (3D) LCE robots can be created via simultaneously welding and aligning LCE materials with different chemical compositions and physical properties without other additives such as tapes and glues (just like metal welding). Both welding and aligning of the LCE materials rely on thermal polymerization of preformed LCE films with reactive acrylate groups. This method provides an easy way to robustly fabricate arbitrary 3D desirable geometries with strongly stable reversible actuations and multifunctionalities, which greatly enlarges and benefits the future applications and manufacturing of LCE soft robots.

Liquid-Crystalline Soft Actuators with Switchable Thermal Reprogrammability

Abstract: Thermal reprogrammability is essential for new-generation large dry soft actuators, but the realization sacrifices the favored actuation performance. The contradiction between thermal reprogrammability and stability hampers efforts to design high-performance soft actuators to be robust and thermally adaptable. Now, a strategy has been developed that relies on repeatedly switching on/off thermal reprogrammability in liquid-crystalline elastomer (LCE) actuators to resolve this problem. By post-synthesis swelling, a latent siloxane exchange reaction can be induced in the common siloxane LCEs (switching on), enabling reprogramming into on-demand 3D-shaped actuators; by switching off the dynamic network by heating, actuation stability is guaranteed even at high temperature (180 °C). Using partially black-ink-patterned LCEs, selectively switching off reprogrammability allows integration of completely different actuation modes in one monolithic actuator for more delicate and elaborate tasks.

Rapid desolvation-triggered domino lattice rearrangement in a metal–organic framework

Abstract: Topological transitions between considerably different phases typically require harsh conditions to collectively break chemical bonds and overcome the stress caused to the original structure by altering its correlated bond environment. In this work we present a case system that can achieve rapid rearrangement of the whole lattice of a metal–organic framework through a domino alteration of the bond connectivity under mild conditions. The system transforms from a disordered metal–organic framework with low porosity to a highly porous and crystalline isomer within 40 s following activation (solvent exchange and desolvation), resulting in a substantial increase in surface area from 725 to 2,749 m2 g–1. Spectroscopic measurements show that this counter-intuitive lattice rearrangement involves a metastable intermediate that results from solvent removal on coordinatively unsaturated metal sites. This disordered–crystalline switch between two topological distinct metal–organic frameworks is shown to be reversible over four cycles through activation and reimmersion in polar solvents. A disordered metal–organic framework converts into a more porous, crystalline phase within 40 s following solvent exchange and desolvation. The rapid domino rearrangement of the whole lattice, which involves carboxylate migration on coordinatively unsaturated metal sites, is accompanied by a substantial increase in surface area.

Adsorption process and mechanism of acetaminophen onto commercial activated carbon

Abstract: The presence of acetaminophen (also known as paracetamol; PRC) micropollutant in water can cause some potential health risks for human. In this study, commercial activated carbon (CAC), which has been oxidized with HNO3 by supplier to increase the oxygen-functional groups, was applied to remove PRC from water. Results demonstrated that CAC is a dominantly mesoporous material (accounting for 76.3%) with large surface area (SBET = 1284 m2/g) and high total pore volume (VTotal = 0.680 cm3/g). CAC possessed abundantly oxygen-containing functionalities and low pHPZC (4.95). Raman spectrum of CAC indicated that CAC possessed a more disordered structure with a high intensity ratio of D band and G band (ID/IG = 2.011). Adsorption study showed that the adsorption capacity of CAC towards PRC was less affected by solution pH value (2.0–10), and ionic strength (0–1.0 M NaCl), and different water matrixes (distilled water, tap water, coastal water, wastewater from water treatment plant, groundwater, and wastewater from beauty salon). The adsorption process occurred rapidly, with around 52% of PRC in solution (∼517 mg/L) being removed within 5 min of contact. The Langmuir maximum adsorption capacity of CAC was 221 mg/g under 1.0 g/L of CAC, pH 7.0, 25 °C, and initial concentration of paracetamol (∼100–1200 mg/L). The pore-filling was the most important mechanism. The SBET and VTotal of CAC after adsorption decreased (by approximately 96% for both) to 45.6 m2/g and 0.039 cm3/g, respectively. The second important mechanism involved in n-π interaction was established by a remarkably decrease in the band intensity (the FTIR spectrum after adsorption) at 1630 cm−1 (the C O group). Weak π-π interaction was confirmed a significant decrease in the ID/IG ratio from 2.011 to 1.947 after adsorption. Hydrogen bonding formations were recommended by decreasing band intensity in FTIR spectrum at 3448 cm−1 (O H) and 1045 cm−1 (C O). Weak van der Waals force was identified through the study of effect of solution temperature and desorption. Consequently, oxidized CAC can serve as a promising and potential material for efficiently eliminating PRC from water environments.

A Secure and Reliable Device Access Control Scheme for IoT Based Sensor Cloud Systems

Abstract: Among other security concerns, the reliable device to device direct communication is an important research aspect in sensor cloud system application of Internet of things (IoT). The access control mechanism can ensure the reliability through secure communication among two IoT devices without mediation of intermediate agent. Mainly, it requires twofold strategy involving the authentication of each other and session key establishment. Quite recently, in 2019, Das et al. proposed a certificate based lightweight access control and key agreement scheme for IoT devices (LACKA-IoT) to ensure smooth and secure access control and claimed LACKA-IoT to withstand the several attacks. Specifically, it is claimed that LACKA-IoT can resist device impersonation and man in middle attacks. However, the proof in this article refutes their claim and it is shown here, that LACKA-IoT is insecure against both device impersonation and man in middle attacks. An adversary just by using public parameters and by listening the communication channel can impersonate any device. Moreover, the same can also launch successful man in middle attack using public parameters and listened messages from public channel. An improved protocol iLACKA-IoT is then proposed in the paper. The iLACKA-IoT provides resistance against various types of threats and provides the required level of security, for evidence both formal validation through random or real (ROR) model as well as the informal validation through discussion on attack resilience is provided. The iLACKA-IoT is not only better in security but also provides performance efficiency as compared with LACKA-IoT and related schemes.

An Updated Review of Toxicity Effect of the Rare Earth Elements (REEs) on Aquatic Organisms

Abstract: Rare earth elements (REEs) or "technology metals" were coined by the U.S. Department of Energy, a group of seventeen elements found in the Earth's crust. These chemical elements are vital and irreplaceable to the world of technology owing to their unique physical, chemical, and light-emitting properties, all of which are beneficial in modern healthcare, telecommunication, and defense. Rare earth elements are relatively abundant in Earth's crust, with critical qualities to the device performance. The reuse and recycling of rare earth elements through different technologies can minimize impacts on the environment; however, there is insufficient data about their biological, bioaccumulation, and health effects. The increasing usage of rare earth elements has raised concern about environmental toxicity, which may further cause harmful effects on human health. The study aims to review the toxicity analysis of these rare earth elements concerning aquatic biota, considering it to be the sensitive indicator of the environment. Based on the limited reports of REE effects, the review highlights the need for more detailed studies on the hormetic effects of REEs. Aquatic biota is a cheap, robust, and efficient platform to study REEs' toxicity, mobility of REEs, and biomagnification in water bodies. REEs' diverse effects on aquatic life forms have been observed due to the lack of safety limits and extensive use in the various sectors. In accordance with the available data, we have put in efforts to compile all the relevant research results in this paper related to the topic "toxicity effect of REEs on aquatic life".

Deep learning-based attenuation map generation for myocardial perfusion SPECT.

Abstract: Attenuation correction using CT transmission scanning increases the accuracy of single-photon emission computed tomography (SPECT) and enables quantitative analysis. Current existing SPECT-only systems normally do not support transmission scanning and therefore scans on these systems are susceptible to attenuation artifacts. Moreover, the use of CT scans also increases radiation dose to patients and significant artifacts can occur due to the misregistration between the SPECT and CT scans as a result of patient motion. The purpose of this study is to develop an approach to estimate attenuation maps directly from SPECT emission data using deep learning methods. Both photopeak window and scatter window SPECT images were used as inputs to better utilize the underlying attenuation information embedded in the emission data. The CT-based attenuation maps were used as labels with which cardiac SPECT/CT images of 65 patients were included for training and testing. We implemented and evaluated deep fully convolutional neural networks using both standard training and training using an adversarial strategy. The synthetic attenuation maps were qualitatively and quantitatively consistent with the CT-based attenuation map. The globally normalized mean absolute error (NMAE) between the synthetic and CT-based attenuation maps were 3.60% ± 0.85% among the 25 testing subjects. The SPECT reconstructed images corrected using the CT-based attenuation map and synthetic attenuation map are highly consistent. The NMAE between the reconstructed SPECT images that were corrected using the synthetic and CT-based attenuation maps was 0.26% ± 0.15%, whereas the localized absolute percentage error was 1.33% ± 3.80% in the left ventricle (LV) myocardium and 1.07% ± 2.58% in the LV blood pool. We developed a deep convolutional neural network to estimate attenuation maps for SPECT directly from the emission data. The proposed method is capable of generating highly reliable attenuation maps to facilitate attenuation correction for SPECT-only scanners for myocardial perfusion imaging.