In contemporary agronomic research, the focus has increasingly shifted towards non-destructive imaging and precise phenotypic characterization. A photon-counting micro-CT system has been developed, ...which is capable of imaging lychee fruit at the micrometer level and capturing a full energy spectrum, thanks to its advanced photon-counting detectors.
For automatic measurement of phenotypic traits, seven CNN-based deep learning models including AttentionUNet, DeeplabV3+, SegNet, TransUNet, UNet, UNet++, and UNet3+ were developed. Machine learning techniques tailored for small-sample training were employed to identify key characteristics of various lychee species.
These models demonstrate outstanding performance with Dice, Recall, and Precision indices predominantly ranging between 0.90 and 0.99. The Mean Intersection over Union (MIoU) consistently falls between 0.88 and 0.98. This approach served both as a feature selection process and a means of classification, significantly enhancing the study's ability to discern and categorize distinct lychee varieties.
This research not only contributes to the advancement of non-destructive plant analysis but also opens new avenues for exploring the intricate phenotypic variations within plant species.
To assess potential variations in the absorbed dose between Chinese and Caucasian children exposed to 18F-FDG PET scan and to investigate the factors contributing to dose differences, this work ...employed patient-specific phantoms and our compartment model for calculating the patient-specific absorbed dose in Chinese children. Methods: Data of 29 Chinese pediatric patients undergoing whole-body 18F-FDG PET/CT studies were retrospectively collected, including PET images for activity distributions and corresponding CT images for organ segmentation and phantom construction. A biokinetic compartment model was implemented to obtain cumulated activities. Absorbed radiation dose for both CT and PET component were calculated using Monte Carlo simulations. Regression models were fitted to time integrated activity coefficient (TIAC) and organ absorbed dose for each patient. Results: TIACs of all the organs in compartment model and the organ dose for 12 organs were correlated with patients' weight. Young children have significantly large uptake in brain compared to adults. The distinctions of anatomical and biological characteristics between Chinese and Caucasian children contribute to variations in the absorbed dose of 18F-FDG PET scans. PET contributed more in organ dose than CT did in most organs, especially in brain and bladder. The average effective dose (± SD) was 4.48 mSv (± 1.12 mSv), 7.04 mSv (± 2.49 mSv) and 11.52 mSv (± 3.20 mSv) from CT, PET and their sum respectively. PET contributed 1.57 times higher than CT. Conclusions: To the best of our knowledge, this work represents the first attempt to estimate patient-specific radiation doses from PET/CT for Chinese pediatric patients. TIACs derived from our methodology in both age groups exhibited significant differences from the that reported in ICRP 128. Our methodology offers valuable approach not only for estimating pharmacokinetic characteristics and patient-specific doses in pediatric patients undergoing 18F-FDG studies but also for other cohorts with similar characteristics.
Aiming at the lack of evaluation indicators of the influence of collaborative design team members, this paper proposes a collaborative design team member influence algorithm DesignRank that combines ...collaborative design behavior characteristics with PageRank. The DesignRank algorithm takes into account the two factors of self-design level and interactor's design level, and calculates the influence of group members in the collaborative design platform. The experimental results show that the DesignRank algorithm is a more comprehensive and complex method.
Unsupervised Re-ID methods aim at learning robust and discriminative features from unlabeled data. However, existing methods often ignore the relationship between module parameters of Re-ID framework ...and feature distributions, which may lead to feature misalignment and hinder the model performance. To address this problem, we propose a dynamic clustering and cluster contrastive learning (DCCC) method. Specifically, we first design a dynamic clustering parameters scheduler (DCPS) which adjust the hyper-parameter of clustering to fit the variation of intra- and inter-class distances. Then, a dynamic cluster contrastive learning (DyCL) method is designed to match the cluster representation vectors' weights with the local feature association. Finally, a label smoothing soft contrastive loss (\(L_{ss}\)) is built to keep the balance between cluster contrastive learning and self-supervised learning with low computational consumption and high computational efficiency. Experiments on several widely used public datasets validate the effectiveness of our proposed DCCC which outperforms previous state-of-the-art methods by achieving the best performance.
Confining photons in a finite volume is highly desirable in modern photonic devices, such as waveguides, lasers and cavities. Decades ago, this motivated the study and application of photonic ...crystals, which have a photonic bandgap that forbids light propagation in all directions
. Recently, inspired by the discoveries of topological insulators
, the confinement of photons with topological protection has been demonstrated in two-dimensional (2D) photonic structures known as photonic topological insulators
, with promising applications in topological lasers
and robust optical delay lines
. However, a fully three-dimensional (3D) topological photonic bandgap has not been achieved. Here we experimentally demonstrate a 3D photonic topological insulator with an extremely wide (more than 25 per cent bandwidth) 3D topological bandgap. The composite material (metallic patterns on printed circuit boards) consists of split-ring resonators (classical electromagnetic artificial atoms) with strong magneto-electric coupling and behaves like a 'weak' topological insulator (that is, with an even number of surface Dirac cones), or a stack of 2D quantum spin Hall insulators. Using direct field measurements, we map out both the gapped bulk band structure and the Dirac-like dispersion of the photonic surface states, and demonstrate robust photonic propagation along a non-planar surface. Our work extends the family of 3D topological insulators from fermions to bosons and paves the way for applications in topological photonic cavities, circuits and lasers in 3D geometries.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•A novel nitrite sensor was fabricated using TiO2–Ti3C2TX/CTAB/chitosan composite modified electrode.•TiO2–Ti3C2TX nanohybrid was synthesized by a two-step calcination process.•The electrochemical ...sensor showed a detection limit of 0.85 μM with a linear range of 0.003 to 1.25 mM.•The sensor was applied for nitrite detection in real samples with satisfactory recovery.
An electrochemical sensing platform based on TiO2–Ti3C2TX nanohybrid, hexadecyl trimethyl ammonium bromide (CTAB) and chitosan (CS) modified glassy carbon electrode (GCE) has been developed for the detection of nitrite. The TiO2–Ti3C2TX nanohybrid was synthesized by a two-step calcination process. The nanohybrid and its preparation process were characterized by scanning electron microscopy, X-ray diffraction and X-ray photoelectron spectroscopy. Electrochemical methods were used to characterize and investigate the electrochemical behavior and nitrite response of TiO2–Ti3C2TX/CTAB/CS/GCE. Under optimized conditions, the prepared TiO2–Ti3C2TX/CTAB/CS/GCE electrode displayed two linear ranges from 0.003 to 0.25 mM and 0.25 to 1.25 mM with a detection limit of 0.85 μM. Furthermore, the practical applicability of the electrochemical sensor was validated by the detection of nitrite in water and milk samples with good recovery.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Due to the scarcity of metallic lithium and the limited specific energy density of traditional inorganic cathodes, the application of lithium‐ion batteries (LIBs) in the large‐scale energy storage ...market is severely limited. To meet the growing power demands of electric vehicles and electronics, low‐cost and sustainable battery technologies need to be developed. Organic batteries and organic electrode materials emerge at a historic moment and show great potential. Polymer organic materials (POEs) with longer cycle life than small organic molecules that are easily soluble in liquid electrolytes provide more opportunities for advanced electrode materials. However, many issues remain to be addressed before POEs are widely used, such as sluggish electrode reaction kinetics and poor electronic conductivity. Herein, the classification, energy storage mechanism and features of POEs are briefly summarized. Further, the existing problems and design strategies of POEs are discussed and summarized in depth. This review aims to highlight the potential role of structural and morphological design in improving the practical performance of POEs in LIBs and provides insights into the in‐depth understanding and development of organic batteries and organic electrode materials.
High demand for sustainable and low‐cost battery technologies inevitably advances the research for the investigation of polymer organic electrodes (POEs). In this review, the classification of POEs and their energy storage mechanisms are presented, and existing problems and design strategies of POEs are also discussed.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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•Self-assembly method for fabricating D-Ti3C2TX/GR 2D/2D nanohybrid was developed.•The D-Ti3C2TX/GR nanohybrid provided an enhanced electro-catalytic activity for the reduction of ...p-NP.•The proposed sensor based on D-Ti3C2TX/GR exhibited high sensitivity and low detection limit for p-NP detection.
p-Nitrophenol (p-NP) is an important phenolic environmental pollutant. The development of novel rapid determination methods for p-NP is of significance for environmental monitoring. In this work, a sensitive electrochemical sensor based on Ti3C2TX MXene/graphene composite was developed to detect p-NP in aqueous samples. Firstly, delaminated titanium carbide (D-Ti3C2TX) was successfully prepared via an optimized minimally intensive layer delamination (MILD) method, which was further followed by the self-assembly method to form D-Ti3C2TX/graphene (D-Ti3C2TX/GR) composite. The prepared materials were characterized by scanning electron microscopic (SEM), X-ray diffraction (XRD), atomic force microscopy (AFM) and Raman spectroscopy. Then the glassy carbon electrode (GCE) was modified by D-Ti3C2TX/GR composite to prepare the D-Ti3C2TX/GR/GCE sensor. The electrochemical behavior of D-Ti3C2TX/GR/GCE was investigated by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and chronocoulometry. Furthermore, the proposed sensor showed a strong electrochemical response based on the p-NP reduction reaction, benefiting from abundant active sites, fast electron transfer, and excellent electro-catalytic performance of the D-Ti3C2TX/GR composite. Under the optimal conditions, the D-Ti3C2TX/GR based electrochemical sensor displayed a linear response in the p-NP concentration range from 1 to 175 μmol·L−1 with a detection limit of 0.16 μmol·L−1. The anti-interference performance, reproducibility, stability, and recovery in real sample analysis were also further evaluated. This study provided a novel and sensitive method for the rapid determination of p-NP in environmental samples.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
A sensitive electrochemical sensor was fabricated for the rapid determination of bisphenol A (BPA) based on cerium-centered metal-organic framework electrochemically reduced graphene oxide composite ...(Ce-MOF-ERGO) coupled with cetyltrimethylammonium bromide (CTAB) signal amplification. The Ce-MOF-ERGO was synthesized by electrochemical reduction of Ce-MOF-graphene oxide (GO) composite. Under the optimized conditions, the proposed electrochemical sensor exhibited a linear response for BPA in concentration range 3 nM to 10 μM with a detection limit of 1.9 nM. The excellent performance of the proposed sensor was attributed to the high conductivity, large surface area, and catalytic activity of Ce-MOF-ERGO composite. Moreover, the oxidation signals of BPA on Ce-MOF-ERGO-modified electrode were further enhanced significantly after addition of CTAB in electrolyte solution. Based on the dual signal amplification strategy, the sensor exhibited high sensitivity for BPA detection and was successfully applied to detect BPA in real samples with good recoveries.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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