Highlights • The multi-channel fully convolutional networks is designed. • We segment liver tumors from multiphase contrast-enhanced CT images. • We train one network for each phase of CT images and ...fuse their high-layer features together. • This method can make full use of the characteristics of different enhancement phases of CT images. • The results showed our model provided greater accuracy and robustness than previous methods.
Accurate segmentation of specific organ from computed tomography (CT) scans is a basic and crucial task for accurate diagnosis and treatment. To avoid time-consuming manual optimization and to help ...physicians distinguish diseases, an automatic organ segmentation framework is presented. The framework utilized convolution neural networks (CNN) to classify pixels. To reduce the redundant inputs, the simple linear iterative clustering (SLIC) of super-pixels and the support vector machine (SVM) classifier are introduced. To establish the perfect boundary of organs in one-pixel-level, the pixels need to be classified step-by-step. First, the SLIC is used to cut an image into grids and extract respective digital signatures. Next, the signature is classified by the SVM, and the rough edges are acquired. Finally, a precise boundary is obtained by the CNN, which is based on patches around each pixel-point. The framework is applied to abdominal CT scans of livers and high-resolution computed tomography (HRCT) scans of lungs. The experimental CT scans are derived from two public datasets (Sliver 07 and a Chinese local dataset). Experimental results show that the proposed method can precisely and efficiently detect the organs. This method consumes 38 s/slice for liver segmentation. The Dice coefficient of the liver segmentation results reaches to 97.43%. For lung segmentation, the Dice coefficient is 97.93%. This finding demonstrates that the proposed framework is a favorable method for lung segmentation of HRCT scans.
Effects of supplementation of chickpea flour (CF) (10% and 20%) to wheat flour (WF) followed by Transglutaminase (TGase) treatment (0-1.2%) were investigated to synergistically boost nutritional and ...texture properties of Asian noodles. The results showed that CF supplementation diluted both gluten-forming proteins and starch content of the blend, resulting in the weak dough, high cooking loss, and poor sensory quality. However, TGase treatment at 0.4-0.8% dosage could effectively recover the dough structure by crosslinking, including CF proteins as evidenced by Mixolab, SDS-PAGE, and dynamic viscoelasticity. The latter also distinguished the distinct dough structure treated by TGase from the wheat gluten-network. SEM revealed the improved network matrix and well-embedded starch granules in raw and cooked noodles. The cooked noodles substituted with 10% CF with 0.4% TGase treatment had the lowest cooking loss and comparable sensory qualities to WF control (p < .05).
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Development of high‐performance organic thermoelectric (TE) materials is of vital importance for flexible power generation and solid‐cooling applications. Demonstrated here is the significant ...enhancement in TE performance of selenium‐substituted diketopyrrolopyrrole (DPP) derivatives. Along with strong intermolecular interactions and high Hall mobilities of 1.0–2.3 cm2 V−1 s−1 in doping‐states for polymers, PDPPSe‐12 exhibits a maximum power factor and ZT of up to 364 μW m−1 K−2 and 0.25, respectively. The performance is more than twice that of the sulfur‐based DPP derivative and represents the highest value for p‐type organic thermoelectric materials based on high‐mobility polymers. These results reveal that selenium substitution can serve as a powerful strategy towards rationally designed thermoelectric polymers with state‐of‐the‐art performances.
Packed in: A high‐performance p‐type organic thermoelectric material based on a selenium‐substituted diketopyrrolopyrrole (DPP) polymer was developed. With strong intermolecular interactions and ordered molecular packing, PDPPSe‐12 exhibits high Hall mobilities of 1.0–2.3 cm2 V−1 s−1 in doped states, yielding a maximum PF and ZT value of 364 μW m−1 K−2 and 0.25, respectively.
Breaking the thermoelectric (TE) trade‐off relationship is an important task for maximizing the TE performance of polymeric semiconductors. Existing efforts have focused on designing high‐mobility ...semiconductors and achieving ordered molecular doping, ignoring the critical role of the molecular orientation during TE conversion. Herein, the achievement of ZT to 0.40 is reported by fine‐tuning the molecular orientation of one diketopyrrolopyrrole (DPP)‐based polymer (DPP‐BTz). Films with bimodal molecular orientation yield superior doping efficiency by increasing the lamellar spacing and achieve increased splitting between the Fermi energy and the transport energy to enhance the thermopower. These factors contribute to the simultaneous improvement in the Seebeck coefficient and electrical conductivity in an unexpected manner. Importantly, the bimodal film exhibits a maximum power factor of up to 346 µW m−1 K−2, >400% higher than that of unimodal films. These results demonstrate the great potential of molecular orientation engineering in polymeric semiconductors for developing state‐of‐the‐art organic TE (OTE) materials.
Bimodal orientation of diketopyrrolopyrrole‐based polymer films exhibits a figure of merit of 0.40, which is more than 400% superior to the corresponding values of face‐on/edge‐on unimodal films.
Mimicking sensory adaptation with transistors is essential for developing next‐generation smart circuits. A key challenge is how to obtain controllable and reversible short‐term signal decay while ...simultaneously maintaining long‐term electrical stability. By introducing a buried dynamic‐trapping interface within the dielectric layer, an organic adaptive transistor (OAT) with sensory adaptation functionality is developed. The device induces self‐adaptive interfacial trapping to enable volatile shielding of the gating field, thereby leading to rapid and temporary carrier concentration decay in the conductive channel without diminishing the mobility upon a fixed voltage bias. More importantly, the device exhibits a fine‐tuned decay constant ranging from 50 ms to 5 s, accurately matching the adaptation timescales in bio‐systems. This not only suggests promising applications of OATs in flexible artificial intelligent elements, but also provides a strategy for engineering organic devices toward novel biomimetic functions.
An organic adaptive transistor (OAT) with an inbuilt dynamic charge trapping interface within the dielectric layer is demonstrated to be a versatile platform for biomimetic sensory adaptation applications. Its precisely regulated decay constant accurately matches the adaptation timescales in bio‐systems, suggesting OATs are promising candidates for the next generation of smart applications.
Additive manufacturing (AM) has attracted many attentions because of its design freedom and rapid manufacturing; however, it is still limited in actual application due to the existing defects. In ...particular, various defect features have been proved to affect the fatigue performance of components and lead to fatigue scatter. In order to properly assess the influences of these defect features, a defect driven physics-informed neural network (PiNN) is developed. By embedding the critical defects information into loss functions, the defect driven PiNN is enhanced to capture physical information during training progress. The results of fatigue life prediction for different AM materials show that the proposed PiNN effectively improves the generalization ability under small samples condition. Compared with the fracture mechanics-based PiNN, the proposed PiNN provides physically consistent and higher accuracy without depending on the choice of fracture mechanics-based model. Moreover, this work provides a scalable framework being able to integrate more prior knowledge into the proposed PiNN.
This article is part of the theme issue 'Physics-informed machine learning and its structural integrity applications (Part 1)'.
Marine microplastic pollution (MMP) is becoming one of the most pressing environmental problems facing humanity today. The novel coronavirus epidemic has raised the issue of environmental ...contamination caused by large-scale improper disposal of medical waste such as disposable masks (DMs). To assess the impact of MMP caused by DMs and to seek solutions for the prevention and control of MMP, this study uses the Driving force-Pressure-State-Impact-Response (DPSIR) framework to establish a causal chain of MMP caused by DMs. The conclusion shows that the novel coronavirus epidemic has led to a surge in the use of DMs, which has brought pressure on resource constraints and environmental pollution at the same time. Improperly DMs enter the environment and eventually transform into MMP, which not only endangers the marine ecological system but also poses potential human health risks as well as economic and social hazards. In addition, further research on environmentally friendly masks (cloth masks and biodegradable masks) is essential to mitigate the environmental damage caused by the large-scale global use of DMs. This study provides a scientific and theoretical basis for the assessment of MMP from discarded DMs, and the findings of this study will provide a reference for the formulation of relevant policies.
Melittin (M) has attracted increasing attention for its significant antitumor effects and various immunomodulatory effects. However, various obstacles such as the short plasma half-life and adverse ...reactions restrict its application. This study aimed to systematically investigate the self-assembly mechanism, components of the protein corona, targeting behavior, and anti-4 T1 tumor effect of vitamin E-succinic acid-(glutamate)
/melittin nanoparticles with varying amounts of glutamic acid. Here, we present a new vitamin E-succinic acid-(glutamate)
(E
), vitamin E-succinic acid-(glutamate)
(E
) or vitamin E-succinic acid-(glutamate)
(E
), and their co-assembly system with positively charged melittin in water. The molecular dynamics simulations demonstrated that the electrostatic energy and van der Waals force in the system decreased significantly with the increase in the amount of glutamic acid. The melittin and E
system exhibited the optimal stability for nanoparticle self-assembly. When nanoparticles derived from different self-assembly systems were co-incubated with plasma from patients with breast cancer, the protein corona showed heterogeneity. In vivo imaging demonstrated that an increase in the number of glutamic acid residues enhanced circulation duration and tumor-targeting effects. Both in vitro and in vivo antitumor evaluation indicated a significant increase in the antitumor effect with the addition of glutamic acid. According to our research findings, the number of glutamic acid residues plays a crucial role in the targeted delivery of melittin for immunomodulation and inhibition of 4 T1 breast cancer. Due to the self-assembly capabilities of vitamin E-succinic acid-(glutamate)
in water, these nanoparticles carry significant potential for delivering cationic peptides such as melittin.
Modulating photophysical processes is a fundamental way for tuning performance of many organic devices. However, it has not been explored as an effective strategy to manipulate the thermoelectric ...(TE) conversion of organic semiconductors (OSCs) owing to their critical requirement to carrier concentration (>1018 cm−3) and the fact of low exciton separation efficiency in single element OSCs. Here, an electric field modulated photo‐thermoelectric (P‐TE) effect in an n‐type OSC is demonstrated to realize a significant improvement of TE performance. The electrical and spectroscopy characterizations reveal that the electric field gating generates combined modulation of exciton separation, charge screening, and carrier recombination, which produces a more than ten times improvement of photoinduced carrier concentration. These coupled processes contribute to the unconventional Seebeck coefficient (S)‐electrical conductivity (σ) trade‐off relationship of the photoexcited films, therefore leading to a more than 500% enhancement in the power factor for n‐type OTE semiconductors. This work opens a unique way toward state‐of‐the‐art organic P‐TE materials for energy harvesting applications.
An electric field is demonstrated to enhance the photo‐thermoelectric effect by promoting the exciton separation efficiency with a coupled modulation process. The increased photoinduced carrier concentration and abnormal trade‐off relationship of the thermoelectric parameters together lead to an enhancement in the power factor of more than 500% to 11.2 μW m−1 K−2.
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